Genotyping of Mycobacterium tuberculosis and

Genotyping of Mycobacterium tuberculosis and

Mycobacterium leprae ancient DNA

A thesis submitted to The University of Manchester for the degree of

Doctor of Philosophy

in the Faculty of Science and Engineering

2020

Ammielle A. Kerudin

School of Earth and Environmental Sciences

2

Table of Contents

List of Tables ................................................................................................................... 5

List of Figures .................................................................................................................. 7

List of Abbreviations ..................................................................................................... 10

Abstract .......................................................................................................................... 13

Declaration ..................................................................................................................... 14

Copyright ....................................................................................................................... 14

Dedication and Acknowledgement ................................................................................ 15

Chapter 1: Introduction .................................................................................................. 16

1.1 Aims and objectives ............................................................................................. 16

1.2 The biology of tuberculosis and leprosy .............................................................. 18

1.3 Skeletal changes in tuberculosis and leprosy ....................................................... 25

1.4 History of tuberculosis and leprosy based on historical documents and skeletal

changes evidence ........................................................................................................ 31

1.4.1 History of tuberculosis..................................................................................... 31

1.4.2 History of leprosy ............................................................................................ 34

1.4.3 The concern in using historical documents as evidence of ancient disease .... 36

1.5 Ancient DNA........................................................................................................ 38

1.5.1 Ancient DNA background ............................................................................... 38

1.5.2 Characteristic of ancient DNA ........................................................................ 38

1.5.2.1 Fragmentation ........................................................................................... 39

1.5.2.2 Miscoding lesions ..................................................................................... 40

1.5.2.3 Blocking lesions ........................................................................................ 41

1.6 Ancient DNA studies of tuberculosis and leprosy ............................................... 42

1.6.1 Ancient DNA studies of tuberculosis .............................................................. 42

1.6.1.1 Case confirmation ..................................................................................... 42

1.6.1.2 Origin and evolution of tuberculosis ......................................................... 44

1.6.2 Ancient DNA studies of leprosy ...................................................................... 50

1.6.2.1 Case confirmation ..................................................................................... 50

1.6.2.2 Origin and evolution of leprosy ................................................................ 52

Chapter 2: Materials and methods ................................................................................. 56

2.1 Archaeological samples........................................................................................ 56

2.2 Authentication regimes ........................................................................................ 66

2.3 Bone scraping and crushing ................................................................................. 67

2.4 Ancient DNA extraction....................................................................................... 68

2.5 PCR assays screening for ancient DNA preservation .......................................... 69

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2.6 Next generation sequencing ................................................................................. 73

2.6.1 DNA library preparation .................................................................................. 73

2.6.2 Target enrichment: in-solution target hybridization capture ........................... 76

2.6.3 Quality control and quantification of sequencing libraries .............................. 78

2.7 Bioinformatics analysis ........................................................................................ 80

2.7.1 Merging of paired reads and removal of adapter sequences ............................ 82

2.7.2 Mapping to reference genome ......................................................................... 83

2.7.3 Cleaning and sorting reads (PicardTools) ........................................................ 83

2.7.4 Metagenomic content analysis ......................................................................... 84

2.7.5 Sequence variant analysis ................................................................................ 84

Chapter 3: Study of M. tuberculosis aDNA in archaeological remains from Yorkshire,

England. ......................................................................................................................... 85

Part I: MTBC aDNA screening by polymerase chain reaction. ..................................... 85

3.1 Introduction .......................................................................................................... 85

3.2 Results .................................................................................................................. 87

3.2.1 St Andrew Fishergate 6.................................................................................... 95

3.2.2 St Andrew Fishergate 277 ................................................................................ 99

3.2.3 St Andrew Fishergate 339................................................................................ 99

3.2.4 St Helen on the walls 6003 ............................................................................ 100

3.2.5 East Heslington 229 ....................................................................................... 102

3.2.6 Wetwang Slack 2 ........................................................................................... 102

3.2.7 Wetwang Slack 7 ........................................................................................... 104

3.2.8 Wharram Percy 26 and Wharram Percy 1600 ............................................... 104

3.2.9 Addingham 134 and Addingham 223 ............................................................ 106

3.2.10 Addingham 103 ............................................................................................ 106

3.2.11 Melton 5319 ................................................................................................. 109

3.2.12 Hickleton 46 ................................................................................................. 109

3.2.13 St Giles by Brompton Bridge 1542 .............................................................. 111

3.2.14 Sewerby 34 .................................................................................................. 111

3.3 Discussion........................................................................................................... 112

3.3.1 MTBC positive samples ................................................................................. 112

3.3.2 Contamination ................................................................................................ 113

3.3.3 Failure of MTBC aDNA detection ................................................................ 116

3.3.4 Samples for Next Generation Sequencing ..................................................... 118

Chapter 4: Study of M. tuberculosis aDNA in archaeological remains from Yorkshire,

England. Part 2: Next Generation Sequencing. ............................................................ 120

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4.1 Introduction ........................................................................................................ 120

4.2 Results ................................................................................................................ 121

4.2.1 Shotgun sequencing...................................................................................... 121

4.2.2 Target hybridization capture .......................................................................... 143

4.3 Discussion .......................................................................................................... 144

4.3.1 Efficiency of shotgun sequencing in isolating endogenous DNA ................. 144

4.3.2 Taxonomical content of the archaeological samples ..................................... 146

4.3.3 Target enrichment sequencing strategy ......................................................... 150

4.3.4 Possible mixed infection in sample St Andrew Fishergate House 6 ............. 151

4.3.5 MTBC aDNA detection in bone remains from Yorkshire ............................ 151

Chapter 5: Genotyping of Mycobacterium leprae ancient DNA from mediaeval England

...................................................................................................................................... 153

5.1 Background of study .......................................................................................... 153

5.2 Publication draft ................................................................................................. 155

5.2.1 Introduction ................................................................................................... 156

5.2.2 Material and methods .................................................................................... 159

5.2.2.1 Skeletons ................................................................................................. 159

5.2.2.2 Ancient DNA regime .............................................................................. 162

5.2.2.3 DNA extraction, PCR and sequencing.................................................... 162

5.2.2.4 Data analysis ........................................................................................... 164

5.2.3 Results ........................................................................................................... 164

5.2.4 Discussion ...................................................................................................... 167

5.3 Supplementary information ................................................................................ 175

Chapter 6: Conclusion.................................................................................................. 190

6.1 The extent to which the objectives have been addressed: objective one

(tuberculosis) ............................................................................................................ 190

6.2 The extent to which the objectives have been addressed: objective two

(leprosy)…………………………………………………………………………….192

6.3 Limitations of the thesis and future work........................................................... 192

6.4 Ethical issues raised by this work ...................................................................... 193

References .................................................................................................................... 195

Appendices ................................................................................................................... 218

Word counts: 47, 645 words

5

List of Tables

Table 2.1: A complete list of all bone remains studied for the preservation of MTBC

aDNA……………………………………………………………………..59-65

Table 2.2: List of primers used in the PCR screening for MTBC aDNA presence..........72

Table 3.1: Result summary for all PCR assays tested on all samples, using original DNA

extract and 10-fold diluted DNA…….…………………....……...............88-92

Table 3.2: Sanger sequence result summary for 15 samples with a positive band in at

least one of the PCR assays…………………………………………...…93-94

Table 4.1: The result summary of the shotgun read mapping against the M. tuberculosis

reference genome……………….……………………………….…………123

Table 4.2: The number of reads assigned to each super kingdom, genus and species of

interest by MEGAN for sample St Andrew Fishergate 253……………..…124


interest by MEGAN for sample St Andrew Fishergate 6……………...…...127


interest by MEGAN for sample St Helen-on-the-Walls 5494…….….…….130


interest by MEGAN for sample Helen-on-the-Walls 6003………………...133


interest by MEGAN for sample Hickleton 46……………………….....…..135


interest by MEGAN for sample Wetwang Slack 185…………….…..…….137


interest by MEGAN for sample Wetwang Slack 7………………..…..……139


interest by MEGAN for sample Wetwang Slack 8………………..………..141

Table 4.10: Comparison of shotgun and target enrichment NGS results for St Andrew

Fishergate 6.……………………………………………………….……….143

Table 4.11: The DNA library concentrations for the 8 samples subjected to shotgun

NGS………………………………………………………………..……….144

Table 4.12: Comparison of the 20 most abundant species in each sample as determined

by BLAST and MEGAN analysis of the reads obtained by shotgun

sequencing………………………………………………...………..…148- 149

Table 5.1. Details of skeletons and samples that were taken………………….………161

Table 5.2. Results of RLEP PCRs……………………………………………..………165

Table 5.3. Genotype assignments……………………………………………..………166

Table S5.1. Detailed osteological report………………………………………;;….…184

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Table S5.2. Summary statistics for Illumina sequencing following enrichment of

samples by in-solution hybridization……………………………………….185

Table S5.3. Identities in the C21, C48 and R5046 genomes of the 215 SNPs known in

modern M. leprae strains………………………………………………..…186

Table S5.4. Unique variations (highlighted in green) present in the C21, C48 and/or

R5046 genomes………………………………..………………….....187-189

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List of Figures

Figure 1.1: The mechanism of tuberculosis infection in cells and granulomas formation

in active and latent tuberculosis infection…………………………………20

Figure 1.2: The bone changes indicative of tuberculosis infection in skeletal

remains………………………………...…………………………………..27

Figure 1.3: The bone changes of leprosy on foot……………………………………...29

Figure 1.4: The genotyping scheme of MTBC members using the katG463 and gyrA95

markers. …………………………………………………………...………45

Figure 1.5: MTBC phylogenetic lineage 1 to 7……………………………………..…46

Figure 1.6: The distribution of different leprosy subtypes around the world………….54

Figure 2.1: The origin locations of the Yorkshire archaeological remains……………58

Figure 2.2: A simplified scheme of make up of dual-indexed DNA library

fragments………………………………………………………………….74

Figure 2.3: The relationship between the SPRI beads-to-template ratios to fragment size

selection……………………………………………………………………79

Figure 2.4: The bioinformatics analysis flows performed on different samples………81

Figure 2.5: Three outcome from paired-end data from Illumina sequencing by

AdapterRemoval v2……………………………………….……………….82

Figure 3.1: Gel electrophoresis results for the sample St Andrew Fishergate 6 showing

positive bands for three markers………………………………..….………96

Figure 3.2: The alignment of St Andrew Fishergate 6 Sanger clone sequences of IS6110

123 bp and nested 92 bp PCR product against M. tuberculosis H37Rv

reference sequence……………………………….….……………………..97

Figure 3.3: The alignment of St Andrew Fishergate House 6 Sanger clone sequences of

gyrA and Pks 15/1 PCR product against M. tuberculosis H37Rv reference

sequence……………………………………………………………………98

Figure 3.4: The alignment of St Andrew Fishergate House 339 clone sequence of gyrA

PCR product against the reference M. tuberculosis H37Rv sequence…….99

Figure 3.5: gyrA PCR amplification for sample St Helen-on-the-Walls 6003……..…100

Figure 3.6: The alignment of St Helen on the Walls 6003 clone sequences from the gyrA

PCR assay to the M. tuberculosis H37Rv reference sequence…..……….101

Figure 3.7: The alignment of Heslington East 229 clone sequences from the IS6110 123

bp PCR assay to the M. tuberculosis H37Rv reference sequence…….…101

Figure 3.8: The alignment of Wetwang Slack 2 clone sequences from the gyrA PCR

assay against the M. tuberculosis H37Rv reference sequence……….….103

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Figure 3.9: The alignment of Wetwang Slack 7 clone sequences from the IS6110 123 bp

PCR assay against the M. tuberculosis H37Rv reference sequence...........103

Figure 3.10: The alignment of Wharram Percy 26 clone sequences from the gyrA PCR

assay against the M. tuberculosis H37Rv reference

sequence……………………………………………………………….....105

Figure 3.11: The alignment of Wharram Percy 1600 clone sequences from the gyrA PCR

assay against the M. tuberculosis H37Rv reference sequence.…..............105

Figure 3.12: The alignment of Addingham 134 and Addingham 223 clone sequences

from the IS6110 first step, 123 bp PCR assay against the M. tuberculosis

H37Rv reference sequence…………………………….…….….………...107

Figure 3.13: The alignment of Addingham 103 clone sequences from the gyrA PCR

assay against the M. tuberculosis H37Rv reference sequence…….……...108

Figure 3.14: The alignment of Melton 5319 clone sequences from the gyrA PCR assay

against the M. tuberculosis H37Rv reference sequence……...…………..108

Figure 3.15: The alignment of Hickleton 46 clone sequences from the gyrA PCR assay

against the M. tuberculosis H37Rv reference sequence…………………..110

Figure 3.16: IS6110 123 bp and nested 92 bp PCR amplification of sample Sewerby

34………………………………………………………………………...111

Figure 4.1: The 20 species with highest read number assigned by MEGAN for sample

St Andrew Fishergate 253………………………………………………..126

Figure 4.2: The 20 species with highest read number assigned by MEGAN for sample St

Andrew Fishergate 6……………………………………………………..129


Helen-on-the-Walls 5494………………………………………………..131


Helen-on-the-Walls 6003………………………………………………..134


Hickleton 46…………………………………………………….……….136


Wetwang Slack 185……………………………………………………...138

Figure 4.7 The 20 species with highest read number assigned by MEGAN for sample

Wetwang Slack 7………………………………………………………...140

Figure 4.8 The 20 species with highest read number assigned by MEGAN for sample

Wetwang Slack 8………………………………………….…………..…142

Figure 4.9: The electropherogram showing the DNA library size distribution of the

sample Wetwang Slack 185……………………………….….………….145

Figure 5.1: Locations of the sites from which skeletal samples were obtained….…..159

9

Figure S5.1: Skeleton C21…………………………………………………………178



Figure S5.4: Skeleton C227………………………………………………………..179

Figure S5.5: Skeleton R5046………………………………………………………180

Figure S5.6: Skeleton R5256………………………………………………………181

Figure S5.7: Skeleton H3726………………………………………………………182

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List of Abbreviations

A. mirum – Actinosynnema mirum

A. sulfonivorans - Arthrobacter sulfonivorans

AD – Anno Domini

aDNA – Ancient DNA

AMS – Accelerator mass spectrometry

ATP – Adenosine 5’-triphosphate

BB – Borderline borderline

BC – Before Christ

BCE – Before common era

BL leprosy – Borderline lepromatous leprosy

BLAST – Basic local alignment search tools

BQSR – Base quality score recalibration

BSA – Bovine serum albumin

BT leprosy – Borderline tuberculoid leprosy

BWA – Burrows-Wheeler aligner

C. woesei –- Conexibacter woesei

CD4+ – Cluster of differentiation 4

CD8+ – Cluster of differentiation 8

CDC – Centres for disease control and prevention

DNA – Deoxyribonucleic acid

dNTPs – Deoxyribonucleotide triphosphate

dsDNA – Double stranded deoxyribonucleic acid

E. coli – Escherichia coli

EB buffer – Elution buffer

EDTA – Ethylenediaminetetraacetic acid

F. Johnsoniae – Flavobacteria Johnsoniae

GATK – Genome analysis toolkit

GTCF – Genomic Technologies Core Facility

gyrA –DNA gyrase subunit A

H. sapiens – Homo sapiens

HIV – Human immunodeficiency virus

IFN-γ – Interferon gamma

IL-10 – Interleukin 10





IS1081 – Insertion sequence 1081

IS6110 – Insertion element 6110

K. flavida – Kribella flavida

K. setae – Kitasatospora setae

katG – Catalase peroxidase

K. albida – Kutzneria albida

LCA – Lowest common ancestor

LSPs – Large sequence polymorphisms

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M. africanum – Mycobacterium africanum

M. bovis – Mycobacterium bovis

M. caprae – Mycobacterium caprae

M. fascicularis – Niastella koreensis

M. microti – Mycobacterium microti

M. pinnipedii – Mycobacterium pinnipedii

M. tuberculosis – Mycobacterium tuberculosis

MDR-TB – Multi-drug resistance tuberculosis

MEGAN – MEtaGenome Analyzer

MIRU – microsatellites or microbial interspersed repetitive units

MOTT – Mycobacterium other than tuberculosis

MPC – Magnetic particle collector

MRCA – Most recent common ancestor

MTBC – Mycobacterium tuberculosis complex

N. dassonvillei – Nocardiopsis dassonvillei

N. dassonvillei – Nocardiopsis dassonvillei

N. dokdonensis – Nocardioides dokdonensis

N. moscoviensis – Nitrospora moscoviensis

NERC – National Environment Research Council

NGS – Next generation sequencing

PCR – Polymerase chain reaction

PGG – Principal genetic group

Pks 15/1 – Polyketide synthase 15/1

qPCR – Quantitative polymerase chain reaction

R. tataouinensis – Ramlibacter tataouinensis

RD2 – Region of difference 2

RD7 – Region of difference 7

RLEP – Mycobacterium leprae repetitive element

S. amylolyticus – Sandaracinus amylolyticus

S. avermitilis – Streptomyces avermitilis

S. bingchenggenesis – Streptomyces bingchenggenesis

S. cellulosum – Sorangium cellulosum

S. denitrificans – Steroidobacter denitrificans

S. espanaensis – Saccharothrix espanaensis

S. fulvissmus – Streptomyces fulvissmus

S. hindustanus – Streptoalloteichus hindustanus

S. laurentii – Streptomyces laurentii

S. roseum – Streptosporangium roseum

S. venezuelae – Streptomyces venezuelae

S. violaceusniger – Streptomyces violaceusniger

SAM – Sequence alignment mapping

SNPs – Single nucleotide polymorphisms

SPRI – Solid phase reverse immobilization

T. actinomycetes – Thermophilic actinomycetes

T. bispora – Thermobispora bispora

T. curvata – Thermomonospora curvata

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TbD1 – M. tuberculosis specific deletion

Th1 – Helper T cell type 1

Th2 – Helper T cell type 2

TLR – Toll-like receptors

UV – Ultraviolet

V. paradoxus – Variovorax paradoxus

VNTRs – Variable number tandem repeats

WGS – Whole genome sequencing

WHO – World Health Organization

XDR-TB – Extensively drug-resistant tuberculosis

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Abstract

The overall aim of this study was to employ a biomolecular technique – ancient DNA

(aDNA) – to study two ancient diseases that were endemic in Europe (and therefore

Britain) during the medieval period: tuberculosis and leprosy. In humans, the diseases

are caused by M. tuberculosis and M. leprae, respectively – both of which are members

of the M. tuberculosis complex (MTBC). Skeletal manifestations of both diseases may

develop in bone remains, which can be recognized using osteological analysis. In some

cases, however, the skeletal changes are ambiguous. Ancient DNA methods are used for

case confirmation and to answer historical questions such as the spread, origin and

evolution of disease. The first objective of this thesis was to determine whether the

MTBC aDNA detection frequency is high enough to plan a larger study to test

hypotheses such as possible strain differences in urban and rural areas, as it has been

suggested that urbanization assists the spread of tuberculosis, enhancing its virulence. To

meet this objective, 60 skeletal remains from 16 different locations in Yorkshire,

England were studied. All samples were screened for MTBC aDNA presence and 8

samples were selected for next-generation sequencing (NGS). In the PCR assay

screening, only 1 sample produced a positive MTBC amplification. However, when

subjected to NGS, this sample together with the other 7 samples did not produce enough

sequence reads to allow genome comparisons. An attempt to compare metagenomic

content between urban and rural sites was also performed. There was no specific

difference in metagenomic content between urban and rural samples. Based on the PCR

analysis, the sample St Andrew Fishergate 6, dated to the early 14th century AD, showed

evidence of possible tuberculosis infection. NGS analysis further revealed a possible M.

tuberculosis and M. leprae mixed infection, albeit with insufficient read coverage to

determine genome sequence polymorphism. The second objective was to use NGS to

determine the genotype of the M. leprae strains present in skeletons from two mediaeval

sites, at Chichester and Raund Furnells, both in England. This study served as a

continuation for the previous confirmation by PCR of leprosy in these skeletons. The

samples were further subjected to whole M. leprae genome target enrichment before

subsequent high-throughput sequencing. For all 3 historical M. leprae isolates, at least

70% genome sequence coverage was obtained, with a mean read depth of 4-10x. The

near-complete genome sequences that were obtained allowed subtype identification for

each of the ancient M. leprae isolates. Two mediaeval samples from Chichester

belonged to the 3I subtype, which is typical of ancient Northern European and

contemporary North American isolates. Meanwhile, an M. leprae isolate from Raunds

was identified as belonging to the 3K subtype – the first example of this subtype

identified in Britain. Transmission of the M. leprae 3K subtype to Britain is suggested to

have been associated with the travels of crusaders and pilgrims to the Holy Land during

the mediaeval period. The overall conclusion of the work is that although M. leprae

aDNA is well preserved in skeletal remains showing osteological signs of leprosy, the

same is not true for MTBC preservation in skeletons showing indications of

tuberculosis. To test hypotheses such as the effect of urbanisation on tuberculosis, a high

frequency of MTBC detection must be achieved, but this is complicated by the very

nature of ancient DNA itself – highly fragmented, low endogenous DNA copy, presence

of environmental contaminants – and by the possibility of low bacterial load in skeletons

at the time of death. In projects where the testing of a high number of samples is

required, more stringent selection criteria must be imposed to minimize the impact of

destructive analysis.

14

Declaration

No portion of the work referred to in the thesis has been submitted in support of an

application for another degree or qualification of this or any other university or other

institute of learning

Copyright

i. The author of this thesis (including any appendices and/or schedules to this

thesis) owns certain copyright or related rights in it (the “Copyright”) and

s/he has given The University of Manchester certain rights to use such

Copyright, including for administrative purposes.

ii. Copies of this thesis, either in full or in extracts and whether in hard or

electronic copy, may be made only in accordance with the Copyright,

Designs and Patents Act 1988 (as amended) and regulations issued under it

or, where appropriate, in accordance with licensing agreements which the

University has from time to time. This page must form part of any such

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iii. The ownership of certain Copyright, patents, designs, trademarks and other

intellectual property (the “Intellectual Property”) and any reproductions of

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(“Reproductions”), which may be described in this thesis, may not be owned

by the author and may be owned by third parties. Such Intellectual Property

and Reproductions cannot and must not be made available for use without the

prior written permission of the owner(s) of the relevant Intellectual Property

and/or Reproductions.

iv. Further information on the conditions under which disclosure, publication

and commercialisation of this thesis, the Copyright and any Intellectual

Property and/or Reproductions described in it may take place is available in

the University IP Policy (see

http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=24420), in any

relevant Thesis restriction declarations deposited in the University Library,

The University Library’s regulations (see

http://www.library.manchester.ac.uk/about/regulations/) and in the

University’s policy on Presentation of Theses.

15

Dedication and Acknowledgement

This work is dedicated to my parents, Kerudin Masintai and Rusinang Sibul who

inspired and taught me that nothing is more precious than education in life. You both

inspired me, prayed for me and supported me in a way that nobody could ever have done

and most importantly, it is your love that kept me going.

There are so many people whom I would like to thank – those who made my PhD

journey possible, bearable and enjoyable even – at times.

First, I submit my heartiest gratitude to my respected supervisor, Emeritus Prof Terry

Brown for his guidance, constant support and most of all his positivity and trust in me. I

could not have asked for a better supervisor. I would also like to thank my advisors, Dr

Richard Preziosi and Dr Russell Garwood for their guidance and support.

Secondly, I would like to show my appreciation to MARA who funded my PhD study –

which made it possible for me to pursue my PhD studies.

And to my family: brothers – Halley and Frankie, sister in laws, nephews and nieces; my

extended family and my family in law, thank you for your unwavering love, support and

encouragement which made it possible for me to go through some rough days along the

way.

To everyone in Brown’s group – thank you for your encouragement and support; for

treating me warmly for the last four years. Especially to Konstantina, Jannine, and Romy

who trained me in the lab; introduced and taught me about the “ancient DNA world”.

And to Kamalliawati for her lending ears, her house door that is always open for me and

for her constant encouragement. Most of all, thank you for making my thesis submission

possible – I wouldn’t have made it without you.

And to wrap this up, my biggest thanks to my husband, Benedict who have been

supportive from day one and for putting up with my rants and my emotional days. Most

of all, thank you for your patience throughout the years.

To my dear Estelle, you are my source of strength.

16

Chapter 1: Introduction

The history of mankind has been intertwined with infectious diseases. Tuberculosis and

leprosy, which are both contagious illnesses of ancient origins, have greatly affected the

course of world history. These diseases are still massive threats to human health to this

date, albeit their centuries of existence and the availability of treatments (World Health

Organization 2018a; World Health Organization 2018b). Their persistence in human

populations attracted studies from a wide range of fields. In sync to the notion: “the past

informs the present” (Brown & Barnes 2015, p.144), in the ever-growing discipline of

palaeopathology, ancient DNA is appropriately employed to answer historical questions

about palaeodiseases (Monot et al. 2005; Bos et al. 2014; Kay et al. 2015; Schuenemann

et al. 2018). The first isolation and detection of ancient DNA, from a dried muscle of

extinct Equus quagga in 1984, immediately ignited interest in the vast potential of this

tool in archaeology (Higuchi et al. 1984). Less than a decade later, Spigelman and

Lemma successfully isolated and detected the first microbial pathogen ancient DNA: M.

tuberculosis through the polymerase chain reaction (PCR) (Spigelman & Lemma 1993).

Since then, the study of ancient DNA in palaeopathology has not just been limited to

disease confirmation but also applied in answering broader and deeper questions, for

example, spread of disease through phylogeography and evolution of disease (Bos et al.

2014; Donoghue et al. 2015; Kay et al. 2015; Schuenemann et al. 2018).

1.1 Aims and Objectives

The overall aim of this study is to employ a biomolecular technique – ancient DNA – to

study two ancient diseases that were endemic in Europe (and therefore Britain) during

the medieval period: tuberculosis and leprosy. This chapter will focus on the background

of both ancient diseases studied: tuberculosis and leprosy. The biology of infection will

be described, followed by the manifestation of each disease in skeletons, which allows

the identification of the diseases in archaeological skeletons. The ability of tuberculosis

and leprosy to leave “fingerprint” changes in bones allows the identification of each

disease in skeletal remains using osteological methods. The limitation of this method

will be explained, which will then bring the ancient DNA method in to the picture. This

will be followed by the description of ancient DNA. The next section will describe the

ancient DNA study that has been done for both tuberculosis and leprosy to this date,

17

which includes case confirmation and evolutionary and disease origin studies. Chapter 2

describes the materials and methods performed as well as their relevance for this study.

The research described in the thesis had two objectives. The first objective was to

determine if the success rate of M. tuberculosis complex aDNA detection is high enough

to make it worthwhile to plan larger projects to test hypotheses such as possible strain

differences in urban and rural areas, as it has been suggested that urbanization assists the

spread of tuberculosis, enhancing its virulence (Comas & Gagneux 2011). Therefore, in

order to explore the association of urbanization and M. tuberculosis genotypes,

archaeological bones from urban and rural locations in Yorkshire, the majority with

tuberculosis indicative lesions which have been diagnosed by previous various

osteological studies, were examined. Yorkshire was selected because York was the

second largest city after London, during the 14th-15th centuries AD, and underwent rapid

urbanization during this time. The study of bones with tuberculosis lesions from

Yorkshire is split into 2 chapters: Chapter 3 and Chapter 4. The work described in

Chapter 3 aimed to screen all bone remains for the preservation of MTBC aDNA

through use of PCR assays of four targets selected based on their specificity for the

MTBC genome. The presence of MTBC aDNA is verified by cloning of PCR bands and

subsequent Sanger sequencing and matching the obtained sequences to the reference M.

tuberculosis H37Rv sequence. Based on the results obtained from Chapter 3, bone

remains were selected for next generation sequencing (NGS) using two sequencing

strategies, shotgun and target enrichment, which is described in Chapter 4. In Chapter 4,

the sequences obtained were then evaluated by various bioinformatic methods.

The work described in Chapters 3 and 4 showed that there is not extensive preservation

of MTBC aDNA in the bones from Yorkshire that were studied. The project was

therefore extended to include one additional objective. This additional objective aimed

to use NGS to determine the genotype of the M. leprae strains present in bones from

Chichester and Raund Furnells, both in England. This study serves as a continuation for

the previous confirmation by PCR of leprosy from Chichester and Raund Furnells, both

in England (Müller 2008). This work is described in Chapter 5. Leprosy was endemic in

Europe before it declined during the 16th century for unknown reasons, remaining only

in certain parts of Europe, human leprosy completely vanishing from Britain. Therefore,

archaeological remains are the only source of information on leprosy in Britain.

Identifying the genotypes of the M. leprae strains detected in the bones from Chichester

and Raund Furnells, as well as identifying new polymorphisms from each sequence in

18

comparison with the modern M. leprae TN strain (the reference genome that is used in

comparisons of M. leprae strain variability), will give an indication of the diversity of M.

leprae strains present in Britain during the medieval period, as well as giving clues about

the spread of leprosy to this part of the world. Finally, Chapter 6 describes the

conclusion of the works presented in this thesis.

1.2 The biology of tuberculosis and leprosy

Tuberculosis is one of the ten most common causes of global death (World Health

Organization 2018a). The World Health Organization (WHO) reported 1.7 million

fatalities caused by this disease alone, while there were 10.4 million people who

contracted the disease in 2016. Tuberculosis is also the leading cause of death among

HIV patients, accounting for 40% death in the same year (World Health Organization

2018a). This chronic granulomatous disease is caused by an obligate bacterium in

humans and animals (Brites & Gagneux 2015). There are seven closely related species

of Mycobacterium known with the ability of cause this disease: M. tuberculosis, M.

bovis, M. africanum, M. canettii, M. caprae, M. pinnipedii and M. microti (Wirth et al.

2008; Homolka et al. 2012). These pathogens are together known as the group members

of Mycobacterium tuberculosis complex (MTBC). The majority of infections in humans

and animals are caused by M. tuberculosis and M. bovis respectively (Bouwman et al.

2012). M. tuberculosis is transmitted through airborne droplets containing the pathogen

bacilli from an individual with active pulmonary tuberculosis infection, in which the

lung will be the primary site of infection (CDC 2013). On the other hand, the

transmission of M. bovis usually occurs through ingestion of contaminated milk and

meat, typically from cattle, where the gut will in turn become the main site of infection

(Atkins 2000; Waddington 2006). This is no longer a significant route of transmission

today, but bovine tuberculosis was a major problem in Britain from 1850 to 1950 where

it was responsible for approximately 800,000 deaths in the population (Atkins 2000;

Atkins 2008).

Tuberculosis bacilli are transmitted through droplet nuclei which will traverse the

mucociliary system and reach the alveoli of the lungs (CDC 2013). In this process, the

first line of defence would be the mucus-secreting goblet cells in the upper part of the

airways where the bacilli will be trapped on the mucus and subsequently “removed”

upward in accordance to the coordination by the cilia present on the cell surfaces

19

(Knechel 2009). The “unfiltered” bacteria will have the opportunity to invade the

alveolar spaces before they are subsequently phagocytized by the alveolar macrophages

(Pieters 2008). Following ingestion by macrophages, the mycobacteria will start to

multiply at a very slow rate (Knechel 2009). The macrophages will attempt to destroy

the bacteria by releasing cytokines and proteolytic enzymes (Flesch & Kaufmann 1993).

This cytokine production will trigger immune response from T cells through the

recognition of the mycobacteria antigen presented on the surface of macrophages. The

accumulation of immune cells including T cells, B cells and macrophages will aid the

formation of granulomas surrounding the M. tuberculosis, in an individual with good

cell-mediated immunity (Figure 1.1-a) (Pai et al. 2016). This will slow the replication of

the mycobacteria and prevents their spread. The micro-environment will contain the

bacteria but in the majority of cases, a complete eradication of the pathogen will not

occur but instead, they will adapt and survive (Forrellad et al. 2013). The low pH and

oxygen level conditions in the micro-environment will promote latency where the bacilli

survive within the granulomas but do not establish active infection to the host until the

immune system is compromised (Wayne & Hayes 1996; Cardona & Ruiz-Manzano

2004). The bacilli can stay in dormant stage, encapsulated in the calcified lesion, for

years, and even for a lifetime (Lin & Flynn 2010). In contrast, in hosts with a weaker

immune system, the infection will not be contained, therefore primary progressive

tuberculosis infection will be established (Figure 1.1-b) (Pai et al. 2016). The risks of

acquiring active tuberculosis infection is higher in HIV and diabetes patients,

malnourished people, as well as those who consume tobacco, with 8% of the cases

worldwide associated with smoking (World Health Organization 2018a). More than 95%

of tuberculosis cases and fatalities occur in the developing world; 45% and 25% of the

new cases are in Asia and Africa, respectively (World Health Organization 2018a).

Tuberculosis infection that occurs in the lungs is termed pulmonary tuberculosis

(Campbell & Bah-Sow 2006). The symptoms of pulmonary tuberculosis include cough

and sputum production, difficulties in breathing, haemoptysis, gradual wright loss, fever,

wasting, malaise, and anorexia in some cases (Campbell & Bah-Sow 2006). The typical

diagnostic methods for pulmonary tuberculosis include radiologic study, sputum direct

microscopy and culture and molecular detection (Ryu 2015). Although the lungs are the

primary site of tuberculosis infection, the bacilli can escape the lungs and spread to the

other parts of the body through the bloodstream and the lymphatic system (Ramirez-

Lapausa et al. 2015). Extrapulmonary tuberculosis can affect any part of the body but the

typical sites of infection are the lymph node, pleura, bones and joints or other skeletal

20

Figure 1.1: The mechanism of tuberculosis infection in cells and granulomas formation in active and latent tuberculosis infection. (a)

Inhaled tubercle bacilli enter the alveolar space of the lungs and bacteria elimination will be attempted by alveolar macrophages. In case of

unsuccessful bacteria elimination, the pathogens will invade the interstitial tissue of the lung. T cell priming will be initiated through the action of

either dendritic cells or monocytes – transporting the bacilli to pulmonary lymph nodes. This event will “attract” immune cells such as T cells and

B cells to the lung parenchyma leading to a subsequent granuloma formation. (b) M. tuberculosis replication occurs within the granuloma,

leading to high bacterial load. Failure of infection containment leads to bacteria dissemination to body organs. At this stage, the bacilli have the

ability to spread through the bloodstream or re-enter the respiratory tract to initiate similar immune reactions. In this infection phase, the host now

has active tuberculosis – will show symptoms and with the ability to infect other individuals (figure taken from Pai et al. 2016: 5).

21

parts, central nervous system, genitourinary system and abdomen (Golden & Vikram

2005). Extrapulmonary tuberculosis most frequently occurs in the lymph node and the

most frequent presentation is cervical lymphadenopathy but the involvement of the

inguinal, axillary, mesenteric, mediastinal and intramammary regions are also possible

(Golden & Vikram 2005). Approximately 35% of extrapulmonary tuberculosis cases

affect the skeletons; frequently spondylitis, followed by tuberculosis arthritis

concentrated on the joints (weight-bearing) and extraspinal manifestation (Golden &

Vikram 2005; Vanhoenacker et al. 2009). This type of tuberculosis involvement will be

discussed further in the next section. The regime treatment of a supposedly drug-

susceptible tuberculosis patient is a multi-drug combination consisting of rifampin,

isoniazid, pyrazinamide and ethambutol (Horsburgh et al. 2015). The inclusion of

ethambutol is not desired especially in young children due to its toxicity; it is usually

omitted in the treatment once drug-susceptibility is confirmed. The standard duration of

treatment for drug-susceptible patients is six months (Horsburgh et al. 2015). The multi-

drug combination regimen has been quite successful in treating tuberculosis patients; 53

million deaths were prevented between years 2000 and 2016 (World Health

Organization 2018a). However, the emergence of multi-drug resistance tuberculosis

(MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) halted the progression

towards zero tuberculosis cases (World Health Organization 2018a; World Health

Organization no date). According to the World Health Organization, there were

approximately 490,000 people with MDR-TB, with 600,000 newly reported cases of

rifampin drug resistance (World Health Organization 2018a). The treatment for

multidrug-resistant (MDR) tuberculosis is often complex and must be adjusted

specifically to the individuals by expert physicians according to drug-susceptibility

results performed using culture or DNA testing methods (Lange et al. 2014). Due to the

emergence of MDR-TB and XDR-TB, it is apparent that discoveries of new drugs and

vaccines are crucial. In addition, an effective public health system is also needed in order

to keep tuberculosis spread in check (Russell et al. 2010)

22

The second ancient disease of interest in this study is leprosy. This chronic infectious

disease causes manifestation on the skin, upper respiratory tract, peripheral nerves and

sometimes the eyes (Yassin et al. 1975; Lastória & de Abreu 2014). According to the

data gathered from 145 countries, there were 173,358 leprosy sufferers and 216,108 new

cases reported in 2016 alone (World Health Organization 2018b). Prior to 2008, M.

leprae was the sole leprosy pathogen known, before the identification of the second

leprosy causative pathogen: Mycobacterium lepromatosis (Han et al. 2008). Apart from

the majority infection observed in humans, leprosy infection has also been observed in

nine-banded armadillos in southern United States, chimpanzees, sootey mangabey

monkeys, and British Isles red squirrels (Meyers et al. 1991; Truman et al. 2011; Avanzi

et al. 2016). M. leprae is an extremely slow growing pathogen with a doubling time of

12.5 days (Jacobson & Krahenbuhl 1999). Similar to M. tuberculosis, this pathogen is

also an obligate intracellular bacterium (Groathouse et al. 2006). The study of M. leprae

is made difficult due to inability of its cultivation in normal cell culture media (Davis et

al. 2013). In vivo, leprosy has been studied using mouse foot-pad inoculation technique

and on immunocompromised mice, but neither systems are as successful as the

armadillo as an animal model for leprosy (Shepard 1960; Rees 1966; Kirchheimer &

Storrs 1971; Kirchheimer et al. 1972).

Although the precise path of M. leprae transmission is yet to be proven, an

overwhelming number of studies suggest that leprosy infection may spread through

nasal discharge containing M. leprae bacilli from untreated leprosy patients (Rees &

McDougall 1977; de Wit et al. 1993; Martinez et al. 2011). The bacilli will then make

their way into the healthy individual’s body through the respiratory route. Another

possible way for the bacilli to gain entry is through skin contact with a leprosy patient

(Satapathy et al. 2005). The bacilli enter the healthy individual’s body, possibly through

the skin and nose, and the host innate immune system will recognize the “foreign body”

and be triggered. This occurs through recognition of the mycobacterial lipoproteins by

the Toll-like receptors (TLRs) on macrophage and monocyte surfaces (Walker &

Lockwood 2006). In the case of M. leprae infection, recognition by the TLR2/1

heterodimer will allow the differentiation of monocytes into both dendritic cells and

macrophages (Modlin 2010). This will be followed by naïve T cell activation through

antigen presentation by dendritic cells to trigger more Th1 response (Walker &

Lockwood 2006).

23

Rather than M. leprae virulence, the clinical manifestation of this disease is determined

by the immune status of the individuals affected (Jin et al. 2018). One of the

classifications of leprosy discriminates between tuberculoid and lepromatous leprosy, as

well as the borderline intermediate infection, based on the resistance of the patient

towards the infection (Ridley & Jopling 1966).

An individual with stronger immune status will be able to “fight” the infection and will

only manifest the “mild” tuberculoid leprosy infection (Jacobson & Krahenbuhl 1999).

In this case, intense phagocytic activity will be triggered in lesions through the

secretions from Th1 T-cells (IL-2, lymphotoxin-α and interferon (IFN)-γ) (Walker &

Lockwood 2006; Bobosha et al. 2014). The cytokine-triggered macrophages will form

granulomas together with lymphocytes (Wang, Maeda, et al. 2013). Inside the

granulomas, T cells will produce granulysin, an antimicrobial protein (Walker &

Lockwood 2006). For these individuals, the CD4+ cells will outnumber the CD8+ cells

(Modlin 1994). Therefore, the infection will be halted by “trapping” the M. leprae inside

well-formed granulomas.

In contrast to tuberculoid leprosy, the granuloma is not so well-formed in lepromatous

leprosy, thus, making it difficult to “trap” the M. leprae bacilli (Wang, Maeda, et al.

2013). This is due to the different types of cytokines produced: IL-4, IL-5 and IL-10

(Yamamura et al. 1991). The cytokines IL-4 and IL-10 are capable of downregulating

TLR2 on monocytes while the latter will inhibit IL-12 production (secretion of which

will allow the activation of naïve T cells) (Zumla & James 1996; Walker & Lockwood

2006). The Th2 immune response will be activated while suppressing that of Th1, which

is responsible for initiation of the macrophage response (Modlin 1994). This type of

leprosy infection is characterized by the absence of granulomas and lack of successful

cell-mediated immunity.

The third type or degree of leprosy infection is intermediate or borderline infection

(Ridley & Jopling 1966). For this spectrum, the immunology response can change from

tuberculoid to lepromatous (White & Franco-Paredes 2015). Three types of borderline

leprosy infections are: borderline borderline (BB), borderline lepromatous (BL) and

borderline tuberculoid (BT) (Ridley & Jopling 1966). The borderline tuberculoid

spectrum of infections is the most common type of leprosy, although the exact

immunology is still not well-understood (Ankad 2018).

24

The clinical representation of leprosy depends on the strength of the host’s immune

system to fight M. leprae infection (Jin et al. 2018). In tuberculoid leprosy, there are

very few lesions found (Zumla & James 1996). The lesions are usually plaques and

macules with sharply demarcated edges (Lynnerup & Boldsen 2012). The appearance of

the lesions is usually hairless and hypoesthetic, which is due to the damage on the

dermal nerve fibres (Gunatilake & Settinayake 2004). The spread of infection to the

peripheral nerves such as the tibia, fibula and ulna is possible, however the damage is

limited. The effects on the nerves of a tuberculoid leprosy patient may include noticeable

enlargement of the area where the peripheral nerves are affected (Gunatilake &

Settinayake 2004). This is due to the granulomatous inflammation on the nerves which

in turn cause sensory and motor loss, resulting in the inability to detect pain (Walker &

Lockwood 2006). The swelling nerves could also experience further impairment as a

result of the entrapment inside the fibro-osseous tunnels.

In lepromatous leprosy, the early signs of disease include skin changes in the form of

macules distributed uniformly and widely on the face predominantly, and some are also

distributed on the upper limbs of the body (Lynnerup & Boldsen 2012). The edges of

these macules are almost undistinguishable and usually coupled with hypopigmentation

and redness on the skin (Gunatilake & Settinayake 2004; Reibel et al. 2015). In addition,

the face skin may thicken when the disease is neglected and untreated, and this results in

an appearance known as “leonine face” (Walker & Lockwood 2006). Dermal

involvement is pronounced in leprosy patients in this pole, which may give rise to

“glove and stocking” neuropathy (Sabin & Ebner 1969). The peripheral nerves may be

affected at a later stage (Lynnerup & Boldsen 2012). Skin lesions characteristic of

patients with borderline leprosy have characteristics in between those of tuberculoid and

lepromatous leprosy.

M. leprae shows a strong tropism in macrophages and Schwann’s cells of the peripheral

nervous systems (Reibel et al. 2015). Inside the cells, the pathogen bacilli will actively

proliferate, causing cell deterioration and failure to regenerate (Spierings et al. 2000).

Untreated leprosy nerve involvement will eventually result in deformity and disability,

sometimes irreversible (Lastória & de Abreu 2014). This occurs through sensory loss as

a result of nerve damage which in turn causes unnoticed injury, which leads to

secondary infections, causing damages in tissues (White & Franco-Paredes 2015). The

patient will eventually become disabled from the loss of motor function.

25

Multidrug combination regimen was introduced in 1982 which includes rifampicin,

clofazimine and dapsone (Jacobson & Krahenbuhl 1999; Reibel et al. 2015). The

duration of the course of treatment is still in debate; WHO has fixed the duration for 12

months, however many still argue that the duration is not sufficient for the infection to

resolve (Kumar et al. 2013; Malathi & Thappa 2013).

1.3 Skeletal changes in tuberculosis and leprosy

The field of palaeopathology has traditionally relied heavily on macroscopic inspection

to recognize ancient diseases in bone remains. Macroscopic or visual examination

provide direct evidence of such diagnosis in skeletal remains. It is crucial to understand

the effects of diseases in the human body, especially the skeleton, in a modern clinical

sense in order for the diagnosis to be made with skeletal remains (Roberts and

Manchester 2010). In bone remains, the osteological changes caused by infectious

diseases could be in the form of bone destructions, bone formation, or a mixture of both

(Roberts and Manchester 2010). Skeletal involvements are also common in modern

clinical samples, in the post-antibiotic era (Steyn et al. 2013; Steyn & Buskes 2016). The

lesion distribution on the skeleton is an important clue to identify the type of infection

the individual had suffered. Typically, palaeopathology researchers are performing the

osteological analysis using macroscopic and radiological methods but the histological

approach has become increasingly popular.

The skeletal changes in tuberculosis and leprosy are a manifestation of a chronic, long-

established infection in a relatively healthy individual (Zink et al. 2001; Tayles &

Buckley 2004; Adachi et al. 2006; Rubini, Zaio & Roberts 2014; Suzuki et al. 2014;

Steyn & Buskes 2016; Inskip et al. 2017). The tuberculosis bone changes occur in an

individual with a secondary tuberculosis infection, where the infection of a person with

latent tuberculosis is reactivated (Ortner 2003; Roberts & Manchester 2010). In

secondary tuberculosis infection, the tubercle bacilli spread haematogenously within the

bones to other parts of the body (Roberts & Manchester 2010). The bacilli will

predominantly reside in the skeletal areas where the circulatory and metabolic rates are

high inside the skeleton, e.g. in the haemopoietic or red marrow (Ortner 2003).

Regardless of the age of individuals, the red bone marrow can be found in all bones

including the vertebrae, sternum and ribs (Prabhakar et al. 2009).

26

Tuberculosis infection in skeletal remains can be recognized from bone destruction in

the spine, especially the lower thoracic and lumbar vertebrae (Roberts and Manchester

2010). In most cases, the bone changes are severe which involves abscess development

inside the vertebrae which in turn perforate into the abdomen or chest, and the affected

spine will finally collapse (Figure 1.2 – a) (Roberts & Manchester 2010; Holloway et al.

2013). In archaeological remains, result of the spinal collapse will cause an angular

deformity of the spine. This is the most common type of skeletal tuberculosis, which

accounts for 25-60% of infections (Roberts & Manchester 2010). Skeletal lesions on the

vertebrae are usually shown as osteolytic lesions on the frontal area of the lower thoracic

and the upper lumbar, in which the number of affected vertebrae is usually between one

to four (Holloway et al. 2011; Rasouli et al. 2012). Following the spine, the knee and hip

are the second part of the body that are frequently infected which make up to 10-20 to

15-30% of skeletal tuberculosis cases other than spine involvement, respectively (Ortner

2003; Roberts & Manchester 2010). The tuberculosis infections on these joints are

characterised by fibrous fixation also known as ankylosis (Roberts & Manchester 2010;

Saraf & Tuli 2015). However, great care has to be taken on confirming tuberculosis

diagnosis based on this evidence as it may also be caused by pyogenic osteomyelitis,

brucellosis and fungal infections (Holloway et al. 2011).

Other than that, there are other non-specific bone changes of tuberculosis. These include

new bone formation giving rise to rib lesions, which are increasingly common in post-

antibiotic era (Steyn & Buskes 2016). The tuberculosis lesions on the ribs could be the

result of chronic pulmonary tuberculosis (Figure 1.2 – b) (Kelley & Micozzi 1984;

Matos & Santos 2006). These lesions are typically subtle with the characteristics of

periosteal new bone formation as well as bone resorption (Roberts & Buikstra 2003).

The lesions usually result from bloodstream spread of bacilli, but can also be caused by

direct extension from neighbouring tuberculosis foci and extension from abscesses

within the paravertebral region (Ortner 2003; Roberts & Manchester 2010). New bone

formation is the result of the response of bone tissue to traumatic insults or pathological

infection. The bone infection will cause an inflammatory response that will trigger the

production of new bone on top of the periosteal bone surface, which sometimes can

result in a different colour to the bone ‘layer’ (Figure 1.2 -b). In 2003, Ortner

mentioned that rib tuberculous changes normally occur in 9% of tuberculosis sufferers

(Ortner 2003). In minor cases, dactylitis, which is toe or fingers inflammation, and skull

involvements are also characteristics used for tuberculosis diagnosis (Holloway et al.

2011; Steyn & Buskes 2016). Although these non-specific bone changes have been

27

Figure 1.2: The bone changes indicative of tuberculosis infection in skeletal remains.

(a) The destructive spinal lesions and collapse of vertebrae which is considered pathognomonic

for tuberculosis. The red arrow indicates where the vertebral bodies collapse occurred, which

results in spinal angular deformity in people suffering from spinal tuberculosis. (b) Rib bones

showing new bone formation, as shown by the yellow arrows. New bone formation is one of the

characteristics of probable tuberculosis infection in skeletal remains. (Images from Charlotte

Roberts’ personal collection, personal communication 2019).

(a)

(b)

28

considered more and more in future studies, especially the rib lesions, caution should be

taken as to never treat these as a definitive evidence of tuberculosis infection (Roberts

and Manchester 2010). The non-specific bone changes can also be caused by other

conditions. Endocranial new bone formation could also be caused by induced

meningitis. Similarly, rib lesions can also be attributed to other diseases such as

metastases, unspecific osteomyelitis, pneumonia, bronchiectasis and mycosis (Nicklish

et al. 2012).

Characterisation of bone changes in skeletal remains suspected to be infected by leprosy

was first undertaken by a Danish physician Vilhelm Møller-Christensen in 1953 (Møller-

Christensen 1953; Lynnerup & Boldsen 2012). Leprosy is a slow progressing, chronic

infection which explains its strong manifestation on the skeleton as written by Lynnerup

and Boldsen (2012), “leprosy is a disease one dies with rather than of”. Bone lesions of

leprosy infection in archaeological remains are recognizable on the skull, the extremities

of the hands and feet as well as the lower legs (Thappa et al. 1992; Roberts &

Manchester 2010; Mohammad et al. 2016). As previously mentioned, M. leprae bacilli

attack the peripheral nerves, causing functional loss (Gunatilake & Settinayake 2004).

This will subsequently cause deformities, with most affected regions being the upper and

lower limbs due to muscle paralysis on these regions. Consequently, anaesthesia will

occur on the hands and feet, thus allowing secondary infection to manifest, causing

tissue necrosis due to the unnoticed injuries. In turn, this will give rise to an appearance

of what is known as “clawed hands” (Ortner 2003; Gunawan et al. 2017). On the foot,

the loss of bones on the distal phalanges also may occur, giving rise to a noticeable

“pencil ends” configuration on the metatarsals (Figure 1.3) (Roberts & Manchester

2010). This appearance is associated with the bone atrophy that always takes place

starting from the distal margins of the hands or feet (Barnetson 1951). This bone atrophy

could then proceed to the proximal bones. For example, on the foot, bone absorption

may begin on the distal phalanx, and proceed to the proximal bones, resulting in the loss

of all or some of the phalanges. Further progress of the bone absorption could lead to the

pencilling of the metatarsals, as depicted in Figure 1.3. Although not as frequently as on

the foot, the same pattern of bone absorption can occur on the hand (Ankad et al. 2011).

The bone absorption that typically starts from the distal fingertip, will cause a defect that

looks like a V-shape or “sharpened” fingertip (Lu et al. 2015). Similarly, the worsening

and further progression of the bone absorption will eventually lead to the disappearance

29

of the distal phalanx or will leave behind irregular looking bone remains. The bone

absorption will progress to proximal bones.

Figure 1.3: The bone changes of leprosy on the foot.

The image below shows the ‘pencilling’ appearance of the foot metatarsals and loss of some of

the foot phalanges. As a comparison, the image on top is showing the normal foot appearance in

a modern skeleton. The blue brackets are showing the metatarsal bones, while the red brackets

are showing the phalanges in both normal and affected bones. The yellow arrows depict the

affected bones where the loss of phalanges and pencilling of metatarsal bones has occurred.

(Image from Charlotte Roberts’ personal collection, personal communication, 2019).

30

On the skull, the most recognizable leprosy change is what is termed as rhinomaxillary

syndrome (Ortner 2003). This term was introduced by Andersen and Manchester (1992)

in place of ‘facies leprosa’ proposed by Møller-Christensen in 1978. The former is a

preferred term in palaeopathology as the latter is also used to describe the soft tissue

changes and therefore will not best fit the palaeopathology contexts (Andersen &

Manchester 1992). Rhinomaxillary syndrome is exclusively the result of lepromatous

and near-lepromatous leprosy, therefore the presence of all elements of the bone changes

is pathognomonic of these conditions (Andersen & Manchester 1992; Nerlich & Zink

2008). The tendency of M. leprae to invade the cooler regions of the face explains the

lesion distribution on the mucosal membranes and the cooler exposed skin area

(Andersen & Manchester 1992). The bony lesions in rhinomaxillary syndrome can be

observed in the nasal cavity, the maxilla, on the oral surface of the palatine and alveolar

processes, without any effect shown on the mandible. The absence of lesions in the

mandibular region is explained by the difference in temperature in the regions affected.

Perforation is also possible on the palate, accompanying the inflammatory pitting on

both sides of it (Roberts & Manchester 2010). Apart from that, incisor teeth loss also

may occur as a result of the alveolar bone loss on the upper jaw in that region of the

teeth. The effects on the nasal spine and nasal aperture will include absorption and

remodelling, respectively.

There are always limitations in any discipline, and this is particularly the case with

palaeopathology. This has been highlighted by Wood and colleagues (1992), who

described the “osteological paradox”, which summarises the uncertainties that arise

when it is attempted to use skeletal evidence to study the health and disease status of a

past population. The author highlighted three major problems in palaeopathology. These

are the non-fixed state of the population (so a single or small group of skeletons from

one point in time is not representative of a large population that might be undergoing

change due to migration and mixing with other populations), selective mortality (not all

people with a disease died because of that disease), and the individual variations in the

risks of contracting disease and death (so skeletons with palaeopathological lesions

might represent only a biased proportion of population as a whole). These are the

limitations that are considered impossible to overcome. Other limitations that should be

taken into consideration is that the ‘dead populations’ being studied cannot be

considered to be representative of the living populations (Roberts and Manchester 2010).

Besides, the diagnosis confirmation is heavily dependent on the state of preservation of

31

the skeletal remains. Furthermore, bone changes in acute diseases might be difficult to

detect as the individuals might have died quickly from the disease without having

enough time to develop bone changes.

The most challenging aspect of ancient disease diagnosis based on osteological

observation is the lack of bone lesions specific for certain diseases. The abnormal bone

lesions observed could be the result of different diseases, therefore affecting the

accuracy of the differential diagnosis (Klaus 2017). This is particularly apparent in the

diagnosis of tuberculosis as the non-specific bone lesions could also be a result of other

diseases as previously described in this section. Furthermore, even if there are

pathognomonic bone changes that can diagnose a disease correctly, it would still be

dangerous to use this information to infer the disease status of the population from which

the studied skeleton originated. This information would still suffer from the osteological

paradox. Therefore, to overcome this, it is useful to incorporate other methods such as

molecular study of a skeleton to identify the disease or diseases suffered by that

individual in the past. The biomolecular study of skeletal remains, specifically the use of

ancient DNA, will be further described in the following section 1.6. This section

explains how such studies may complement and add precision to palaeopathological

studies of both tuberculosis and leprosy.

1.4 History of tuberculosis and leprosy based on historical

documents and skeletal changes evidence

1.4.1 History of tuberculosis

Historical documents – written or pictorial – are the key sources which can indicate the

antiquity of certain diseases, albeit the interpretations should be made with caution. The

first convincing historical evidence of tuberculosis appeared in the Chinese literature,

documented by Emperor Shennong of China, dating to approximately 2700 BCE

(Tripathy 2015). This medical text mentioned “xulao bing” which can be interpreted as

“weak consumption”, thought to describe tuberculosis. Medical papyrus from Egypt

such as the Ebers Papyrus (1500 BCE) is the other well-known ancient document which

outline diseases and treatments affecting populations in that area during that period

(Khalil & Richa 2014). A few authors are convinced that this document might be

32

describing tuberculosis. However, Chalke (1962), in much earlier writing is convinced

otherwise. The same differing opinions are held regarding the Bible references about

tuberculosis. Daniel and Daniel (1999) suggested that two verses from the Old

Testament are describing tuberculosis, but Chalke has stated that the descriptions from

the Bible are ambiguous and there is not sufficient information to support the description

of tuberculosis such as is present today (Chalke 1962; Daniel & Daniel 1999).

Throughout different periods, tuberculosis has been called by many names. Tuberculosis

was known during the Classical Greece period as ‘phthisis’, according to the records in

Greek ancient literature, during the period of Hippocrates (460-370 BC) (Moonan 2018).

He was one of the most well-known Greek physicians, who stated in his records that

‘phthisis’ was the most typical disease where death is almost inevitable during that time.

In addition, Hippocrates also described the symptoms of ‘phthisis’ in his Book 1 ‘of the

Epidemics’ including fever, coughing accompanied by concentrated sputa, colourless

urine, and loss in desire to consume food and drinks (Firth 2014). His book also noted

that people who severely suffering from ‘phthisis’ were in the age range between 18 and

35. Hippocrates was in agreement with others who believed at this time that the nature of

‘phthisis’ transmission was hereditary (Lakhtakia 2013). However, the famous Greek

philosopher Aristotle believed that this disease is contagious rather than hereditary, in

contrary to other contemporaries during that period. After Hippocrates, another

renowned physician, Galen, described phthisis, emphasising the presence of “lung

ulcers”, throat or thorax, and body consumption by pus in addition to the other

symptoms already described by Hippocrates (Rosenthal 2013). Some treatment methods

were also outlined such as the use of opium to induce sleep and to numb pains,

bloodletting and recommended diets (Tripathy 2015).

In Europe, tuberculosis was endemic in the 17th century AD and continued to be so for

two centuries, which is why it was known as the “Great White Plague” (Barberis et al.

2017). During this period, tuberculosis was the leading cause of death and whoever

contracted the disease was considered to have received a death sentence, as fatality

occured in almost all instances of infection. The spread of the disease agent was

aggravated by the living conditions in Europe during that time, which were overcrowded

and unsanitary (Roberts & Manchester 2010; Tripathy 2015). In the 17th century AD, the

Bills of Mortality were available in London as a record of mortalities together with their

diagnosis – with tuberculosis being the most common cause of death (Matossian 1985).

Later, from the 19th century onwards, the Registrar General’s statistics provide a quite

33

accurate representation of the disease progress in both Wales and England, which show a

stable drop in the prevalence of tuberculosis in these regions except during the World

Wars (Davies et al. 1999). The 19th century AD was the period of tuberculosis

romanticism (Daniel 2006). During this time, tuberculosis claimed many lives among

the glamorous, talented, smart and good-looking young individuals in society. The

characteristics of tuberculosis sufferers, pale and thin, added to the “romantic” aspect of

the disease, which was considered stylish during that time. In fact, tuberculosis is

depicted in many arts. Portrait of individuals with hunched-back and thin, pale looking

young women were often depicted during this era (Roberts & Buikstra, 2003).

There are many historical documents available throughout the centuries about

tuberculosis. However, precaution should be taken in using or verifying this information.

The accuracy of the tuberculosis diagnosis is questionable; there are instances where the

disease was wrongly assigned (Davies 1998). Diseases with similar symptoms should be

taken into consideration when confirming these diagnoses. For example, non-

tuberculous pneumonia and bronchitis may exhibit similar symptoms to tuberculosis

(Ukil 1940). In addition, the credibility of the individuals who assessed the disease must

also be taken into consideration (Roberts & Buikstra, 2003).

Other than historical documents, the antiquity of tuberculosis can also be inferred

through osteological analysis as described in section 1.3. The earliest skeletal evidence

in different locations based on the study of skeletal changes is described here. The

earliest skeletal evidence of tuberculosis is a female skeleton showing spondylitis found

in the Neolithic level of Arma dell’Aquila Cave in Liguria, Italy (Canci et al. 1996). The

age of the skeleton (5800±90 years BP) was determined based on the 14C radiocarbon

dating of a neighbouring grave located on the same horizon. There is also evidence of

skeletal tuberculosis in the Old World at the Late Neolithic tell settlement site in the

South of Hungary dated 4932-4602 cal BC (Masson et al. 2015). The earliest skeletal

evidence in Britain was found at Tarrant Hinton, Dorset, at an Iron Age site (400-230

BC) (Mays & Taylor 2003). Evidence of tuberculosis in Asia comes from relatively

recent sites, from China, dated to the second century BC, Japan (454 BC – 124 AD) and

Thailand (300 BC – 300 AD) (Suzuki & Inoue 2007; Stone et al. 2009). Plenty of

tuberculosis evidence is available from this period onwards including skeletal evidence

found in France, Lithuania and Austria dated to the 4th century (Stone et al. 2009). In the

Americas, skeletal evidence for tuberculosis mounted throughout the 20th century AD

(Stone et al. 2009). In South America, one of the earliest convincing pieces of evidence

34

of tuberculosis from human remains is from the Andean populations of Peru and

Northern Chile (Allison et al. 1981). Meanwhile in North America, all the skeletons with

evidence of tuberculosis are dated after 1000 AD (Roberts & Buikstra 2003).

Confirmation of ancient tuberculosis cases based on additional biomolecular evidence

will be discussed further in section 1.6.1.1.

1.4.2 History of leprosy

Similar to tuberculosis, leprosy also has existed since antiquity. The earliest mentions of

this disease can be traced back from ancient Egypt (1550 BC), India (600 BC); and

China (4th century BC – 217 BC) (Leung 2009; Robbins et al. 2009). Many authors

believe that the Ebers Papyrus from 16th century Egypt includes a description of leprosy

infection (Robbins et al. 2009). However, a few scholars are sceptical, based on the

accuracy of the translation of this manuscript (Mark 2002). In fact, the notion was

previously rejected and faced strong criticism due to a lack of consistency between the

disease characteristics as described and the symptoms of modern leprosy as we know

today. It was later agreed that the disease description is more fitting to gas gangrene

compared to leprosy (Mark 2002). Sushruta Samitha (600 BC), an ancient Indian

medical document, provided descriptions of disease characteristics that almost all agree

with advanced lepromatous leprosy symptoms (Dharmendra 1947; Jacob & Franco-

Paredes 2008). These include sensation loss, ulceration and disfigurement of limbs,

collapsing of the nose, and falling off of fingers (Roberts & Manchester 2010). Sushruta

Samitha is the only ancient medical writing that gives the most precise description of

leprosy. These texts were estimated to be compiled around 600 BC but the writings are

believed to contain information which was acquired from a much earlier period

(Dharmendra 1947). There are other Indian ancient literatures that might have mentioned

this disease; these are the Laws of Manu and the Atharava Veda (Jacob & Franco-

Paredes 2008). However clinical descriptions of the disease are absent, therefore there is

no significance confidence to confirm that the disease described was leprosy

(Dharmendra 1947). A description of leprosy from China has been acquired from a 3rd

century bamboo book which outlined similar disease characteristics as described in the

Sushruta Samitha (Roberts & Manchester 2010). The presence of these ancient medical

documents with such articulate descriptions of the disease raises the possibility that

leprosy might have existed in the Far East and India from a very early period, as the

35

authors seem to have a deep clinical understanding and judgement of the disease

(Roberts & Manchester 2010). Based on the presence of such detailed and accurate

medical writing and the presence of clinically skilled individuals, it is quite possible that

leprosy was prevalent in these regions during that period of time (Roberts & Manchester

2010). It has also been suggested that leprosy is referred to in the Book of Leviticus, in

the mention of the word tzaraat, but this proposal was later dismissed as a

mistranslation, and it is now accepted that the tzaarat mentioned in the bible was a range

of skin diseases and not the leprosy that we know of today (Trautman 1984; Mark 2002;

Grzybowski & Nita 2016).

In Europe, the prevalence of leprosy infection peaked in the 11th to 14th centuries AD

(Mendum et al. 2014). Leprosy was feared and stigmatized due to the disability and

disfigurement that it caused as well as the lack of understanding of this disease during

that time (Bennett et al. 2008; Sermrittirong & Van Brakel 2014). Leprosy was seen as a

punishment from God and the patients were isolated in a specific area or “facility” called

a leposarium, to avoid contagion from the infected individuals (Donoghue et al. 2015).

During the Middle Ages in Europe, people who were suffering from leprosy infection

were required to wear distinguishing attire, and had to ring bells to let people know that

they were close by (Bennett et al. 2008). In addition, they were also expected be on the

side of the road where the wind does not blow from, as people were so afraid of this

disease and they shunned whoever was suffering from it (Hussain 2007). Leprosy, due to

its unpleasant outcome, was viewed as a blasphemy and even thought to be inherited.

Due to its dramatic representation and high prevalence throughout history, leprosy has

inspired many art works (Gron 1973). Leprosy has been one of the most misunderstood

diseases and still is in certain regions of the world (Sermrittirong & Van Brakel 2014).

Luckily, the discovery of the causative pathogen M. leprae in 1874 by Dr. Gerhard

Armauer Hansen of Norway was the most important moment in the history of leprosy as

it opened a pathway to the understanding of this disease (Irgens 1984; Trautman 1984;

Ghosh & Chaudhuri 2015).

The earliest convincing evidence of leprosy in human remains is from Balathal India,

dated to 2,000 BC (Robbins et al. 2009). This might support the speculation that the

Mediterranean leprosy brought to Europe by the armies of Alexander the Great

originated in the Indo-Gangetic basin, which was not supported by any skeletal evidence

before in the review by Stone and colleagues (2009). One of the earliest evidence of

leprosy in skeletal remains has also been observed at the Dakleh Oasis in Egypt (250

36

BC) (Dzierzykray-Rogalski 1980) and in Israel and Nubia (Stone et al. 2009). More

leprosy bone studies will be elaborated further in section 1.6.2.

1.4.3 The concern in using historical documents as evidence of ancient

disease

Historical texts are crucial in the process of deciphering diseases in historic populations

(Metcalfe, 2007). The writers who lived in the past can provide a clue about the culture

of societies during that time, which then can assist the palaeopathological analysis of

human remains. In some historical texts, the signs and symptoms of diseases are

recorded clearly, and therefore can provide a direct source of information. In

palaeopathological studies, the exclusion of historical written documents will pose extra

challenges to the research itself and might cause inaccuracy in the interpretation

(Mitchell 2017). However, it is also worth noting that cautions must be taken in

interpreting historical documents as evidence of diseases in the past.

The differences in belief and perspective during the historic period might put the study at

risk of misinterpretation (Mitchell 2011). As the ancient medical texts are derived from

various civilizations, it is expected that they were written according to the perspective of

the belief in that geographical area during that time (Roberts 1971). Consequently, this

might give rise to a different description that can be easily misinterpreted from the

context of what we know in this modern medical period. Therefore, it is important to

consider the time when the historical documents were written and the interpretation must

be made by someone with an expertise in the beliefs and perspective of the ancient

civilization (Mitchell 2017).

Furthermore, the evidence of disease must be obtained by reading the original version of

the historical documents (Mitchell 2011; Mitchell 2017). Modern translations or any

quotes from secondary sources are best to be avoided where possible. The concern with

using documents from modern translation is that the translator might not have a medical

background, therefore affecting the accuracy of the disease’s descriptions. Therefore, it

is highly desirable that palaeopathologists work hand in hand with medical historians

who are sufficiently versed in the linguistics to make sure that the original texts are

properly translated and interpreted (Mitchell 2017). In addition, we also cannot be sure

that the medical writers have witnessed the disease during their lifetime or simply just

37

copied it from the previous records of their predecessors. If this is the case, it will give a

wrong indication of the timeline of the disease – or if it really has existed in the

population during the time the document was written. The skills and competency of the

medical personnel who produced the documents cannot be verified. It could be someone

who never had any medical training. By considering all these concerns, there is a lot of

room for disease misinterpretation.

The nature of the written sources and artwork also must be taken into account when

making an interpretation about past diseases. In the investigation of ancient diseases, it is

sensible to start by looking at historical medical texts. When using such document, the

historian must consider when they were written, the person who wrote them and the

purpose for producing or writing such a document (Mitchell et al. 2017). Typically, such

texts are written and being presented to someone high up. Therefore, the writer might

have the intention of impressing this person in power in order to gain something in

return, for example lucrative posts or career advancement (McVaugh, 2006). It is

possible that the text being presented might have been subject to alteration in order to

impress whoever the text was being presented to. Meanwhile, non-medical texts are

often written by non-medical practitioners with only basic medical knowledge

(Robinson 2003). Therefore, although they may not have as much bias as the medical

texts, the disease descriptions that were written could be quite vague and following

personal observations on only the obvious and clearest symptoms and signs. In the case

of histories, the text usually covers a long time range, therefore some of the chronicles

might have been copied from oral tales or much older written sources (Mitchell 2017).

Other documents that can be the source of disease information are biographies, personal

letters and diaries. These types of document can be highly illuminating as sometimes the

diseases are described in detail – how they, their friends or families feel or experience

when they suffered from the disease. Births and deaths registers could also provide good

information about the severity of a disease in the past – the statistic of disease in the past

in a particular region (Wrigley et al. 1997). However, these could also be the subject of

disease misinterpretation and alteration, depending on the reason for why such document

is being produced.

In short, there are many historical documents available which recorded diseases in the

past and they are no doubt great sources of information. But caution must be taken when

making interpretations by thinking carefully about what the document means to the

writer and to whom the document is being presented, and when was the document

38

written; artworks included. When using historical documents, it is also important that the

person is frank about how confident he or she is about the accuracy of the interpretation

(Mitchell 2017). Some documents might only mention a few symptoms and some

symptoms described could be ambiguous and could be present in more than one disease.

Therefore, the choice of words is important and remarks about other possible diseases

should be made.

1.5 Ancient DNA

1.5.1 Ancient DNA background

Genetic information from archaeological biological remains can be preserved and stored

in the form of ancient DNA (aDNA), which then can be assessed and studied (Higuchi et

al. 1984; Spigelman & Lemma 1993). The ancient DNA research field began in 1984

with the isolation of DNA from a preserved Equus quagga skin; this is a zebra-like

animal which became extinct 100 years previously (Higuchi et al. 1984). This

publication provoked interest to study aDNA in much wider types of archaeological

specimens but this was initially hindered by the difficulties in analysing the extremely

low amounts of fragmented and degraded nucleic acid materials from ancient specimens

(Brown & Brown 1992). The development of the polymerase chain reaction (PCR) by

Kary Mullis in 1985 opened a new pathway to study ancient DNA more efficiently as it

allows rapid amplification of a single fragment of DNA, which is perfect for aDNA

which typically exists at a very low copy number (Mullis et al. 1986). This led to the

first application of PCR to amplify aDNA from a 7000-year-old brain (Pääbo et al.

1988). Fast forward to this date, aDNA has been extracted from various archaeological

samples and studied using the current state-of-the-art sequencing technologies (Green &

Speller 2017).

1.5.2 Characteristic of ancient DNA

The DNA molecules of an organism are in constant threat of chemical “attack” at all

times. Fortunately, this is countered by enzymatic repair mechanisms when the organism

is still living to protect its genome integrity (Dabney, Meyer & Pääbo 2013). However,

upon the death of the organism, the genome becomes exposed to various “destroying

39

agents” that may affect its stability such as intracellular nucleases. This is termed

autolysis (Brown & Brown 2011). This, together with two other degradation factors,

environmental effects and microbial attack, influence the state of aDNA preservation

(Burger et al. 1999; Turner-Walker 2008; Kistler et al. 2017). Those biomolecules that

manage to escape the degrading autolysis activity will stand a possibility of being

archaeologically preserved (Brown & Brown 2011). However, they will be subjected to

other less rapid but persistent decaying processes due to the environment, both physical

and chemical factors (Turner-Walker 2008). The chemical agents include oxygen and

water, which are highly reactive and possess the ability to promote oxidative and

hydrolytic reactions, respectively. In addition, the by-products released from the

degradation of one type of biomolecule might themselves trigger decay of another

biomolecular type (Brown & Brown 2011). The physical factors involved in

biomolecular decay include geological, ultraviolet (UV) and cosmic radiations, which

possess the ability to significantly affect the integrity of biomolecules in both living cells

and post-mortem (Cadet & Wagner 2013). However, it is possible to disrupt the

complete destruction of the DNA molecules under favourable circumstances, for

example by freezing or desiccation of specimens (Nicholls 2005). The third degradation

factor, microbial, is also important as several types of microbe are attracted towards

organic material contained in biological remains as this may provide nutrients and an

energy source. In order to “feed” on the organic materials, microbes will secrete certain

enzyme(s) whose function is to break down the organic materials, including DNA,

leading to their degradation (Turner-Walker 2008). The extent of microbial-facilitated

biomolecular destruction depends on the microflora population existing in the burial

environment. Due to the presence of these destructive factors and the absence of repair

mechanisms after death, typical features of ancient DNA are (i) short fragment size due

to degradation; (ii) the presence of DNA replication blocking lesions; and (iii) the

presence of miscoding lesions (Dabney, Meyer & Pääbo 2013), as described below.

1.5.2.1 Fragmentation

Desiccation or anoxic conditions are thought to be the most suitable for DNA

preservation as these exclude the presence of DNA-damaging water and oxygen

(Nicholls 2005; Brown & Barnes 2015). Water targets the β-N-glycosidic bond resulting

in the release of purine or pyrimidine bases from the nucleotide sugar component,

40

consequently creating apurinic or apyrimidinic sites (Kim & Wilson 2012). These sites

are vulnerable to chemical attack, which will then lead to DNA fragmentation, creating

short fragments (Dabney, Meyer & Pääbo 2013). According to the results of in vitro

studies with contemporary DNA specimens, it has been proposed that DNA

fragmentation is caused by hydrolytic depurination. Subsequently, single-strand breaks

will occur due to hydrolysis of the phosphate backbone. These studies provide

supporting evidence to correlate temperature to fragmentation rate (Lindahl &

Andersson 1972; Lindahl & Nyberg 1972). Accordingly, thermal history was proved to

be a useful determinant in predicting the state of biomolecular survival in fossil bones;

the assumption is that DNA depurination is the main determinant of DNA degradation

(Smith et al. 2003). During the preservation period, DNA molecules that are contained

in archaeological remains undergo fragmentation. In result, the aDNA molecules

acquired from archaeological specimens are relatively short (Pääbo 1989). The average

fragment length of aDNA isolated from dried animal muscle tissue is between 100 to

200 base pairs; the maximum fragment length is 500 base pairs (Pääbo 1989). Studies

have shown that the size of aDNA fragments or the degree of fragmentation is

independent of the age of the archaeological specimen (Pääbo 1989; Hagelberg & Clegg

1991; Kistler et al. 2017). Instead of a time factor, it seems that the rapidity of tissue

desiccation after the time of death is more likely to be the determinant of the degree of

DNA fragmentation (Pääbo 1989). The aDNA decay model established for mammal

bones proposed by Kistler and colleagues (2017) suggests that DNA fragmentation

reaches a threshold rapidly after death and then slows down. In contrast, for DNA loss

throughout the preservation period, the process of bulk diffusion out of the sample might

be the major factor. By saying this, this group emphasized the importance of creating

optimum conditions in a closed system in order to improve the DNA preservation.

1.5.2.2 Miscoding lesions

Miscoding lesions are typical of aDNA as a result of hydrolytic deamination of

nucleotide bases (Dabney, Meyer & Pääbo 2013). These will cause errors of “reading”

by DNA polymerase during amplification resulting in incorporation of incorrect

nucleotides during PCR. Cytosine (C) has the highest susceptibility towards

deamination, which will produce uracil (U). During DNA duplication with a strand

containing a miscoding lesion used as template, uracil will direct adenine (A)

41

incorporation that subsequently causes C to T or G to A transition in the amplified PCR

product. Hofreiter and colleagues demonstrated the presence of modified deoxycytidine

in aDNA extracts from animal teeth and bones with ages ranging between 25,000 to

50,000 years (Hofreiter et al. 2001). The treatment of the aDNA template with uracil N-

glycosylase significantly lowered the numbers of substitutions. In their ancient DNA

damage model, using Neandertal mammoth DNA, Briggs and colleagues concluded that

nucleotide misincorporations in aDNA arise mainly because of cytosine deamination,

and are aggravated in single stranded molecules, which are typical for aDNA (Briggs et

al. 2007).

1.5.2.3 Blocking lesions

One of the effects of polynucleotide modification is inhibition of DNA polymerase

progress along the aDNA template strand (Brown & Brown 2011). This is due to

“blocking lesions” which inhibit DNA replication in living cells and may cause eventual

death to cells. However, in living cells, the repair mechanisms usually act accordingly

before such consequences occur (Karanam et al. 2013). However, these mechanisms will

cease to function post mortem, which results in the accumulation of blocking lesions

(Gilbert et al. 2003). If an aDNA sample with blocking lesions were to be used in PCR,

then shorter products are expected, as the Taq DNA polymerase will not be able to copy

the template to full length due to the inhibition from the blocking lesions (Feuillie et al.

2014). The majority of blocking lesions are caused by purine and pyrimidine oxidation

(Dabney, Meyer & Pääbo 2013). Some of the powerful oxidation agents known are

cosmic rays, and derivatives of geological radiation such as super-oxide, hydrogen

peroxide and hydroxyl radicals (Brown & Brown 2011). Oxygen is known as the less

reactive oxidant. Oxidation may disrupt the purine or pyrimidine ring structure and

break it open (Kim & Wilson 2012). This process also may cause purines on the

opposite strands to be dimerized. Maillard reactions may occur which may consequently

cause DNA-protein cross-links. These cross-links are effective blocking lesions which

can in turn prevent DNA amplification by Taq DNA polymerase (Brown & Brown

2011). Other than oxidation, modifications of guanines has also been suggested to be

one of the factors causing blocking lesions (Heyn et al. 2010). Other than cross-links,

the attachment of a peptide to a polynucleotide could also be sufficient to act as a

“blocker”.

42

1.6 Ancient DNA studies of tuberculosis and leprosy

Ancient DNA can be potentially recovered from any form of living remains: humans,

plants, animals. The sources of archaeological aDNA are reviewed by Green and Speller

(2017). Due to the variety of its sources, albeit hindered by preservation state and

molecule damage, aDNA has evolved as an important tool in archaeology. Ancient DNA

has been used to study myriad topics and answer historical questions including the

identification of sex and the relationship between archaeological skeletons; the study of

diets of the people in antiquity; the study of agricultural origin and spread; the

technology used in prehistoric periods; the history of early human origins and

migrations; and the study of ancient disease or palaeopathology (Brown & Brown 2011).

The aDNA application that will be discussed in detail here is the study of past diseases:

tuberculosis and leprosy. To this date, the study of both leprosy and tuberculosis has

been focused on case confirmation and the origin and evolution of both diseases. As

described in section 1.3, skeletal manifestations of both tuberculosis and leprosy are

providing a perfect opportunity to study both diseases using osteological methods.

However, this method does have limitations. For both diseases, not all infected

individuals show skeletal manifestations (Zink et al. 2001), and even for those skeletons

that do show bone changes, the lesions could be ambiguous and could be caused by

other types of disease that give rise to similar bone changes (Roberts & Manchester

2010). Therefore, aDNA studies may offer more precise disease identification by trying

to detect the presence of the pathogen that caused the infection. Evidently, the success of

aDNA disease detection methods depends on the preservation state of the skeletons

themselves.

1.6.1 Ancient DNA studies of tuberculosis

1.6.1.1 Case confirmation

The majority of aDNA studies of past diseases have been done on tuberculosis. This is

owing to the fact that tuberculosis is viewed as one of the most important palaeodiseases

in terms of its long co-existence with human populations as shown by the lesions in

archaeological remains, as well as the fatality burden that still exists today, despite the

previous success of the multi-drug treatments. Ancient tuberculosis has been the focus of

43

aDNA studies as it can cause identifiable bone changes and its DNA can persist in

archaeological remains despite long preservation periods (Spigelman & Lemma 1993).

The aDNA study of MTBC can provide an insight to the origin and evolution of this

ancient disease, which in turn might lead to a better understanding of this disease. As

described earlier, tuberculosis may cause skeletal changes in affected individuals. Out of

all individuals with active tuberculosis infections, only about 3-5% will develop skeletal

manifestation (Roberts & Buikstra 2003). From this 3-5%, approximately 50% will

develop spine tuberculosis. Therefore, the study of tuberculosis aDNA is typically

performed by extracting DNA from the vertebrae and sometimes the ribs – the ribs may

also show lesions in the case of tuberculosis infection (Mays & Taylor 2003; Taylor et

al. 2005).

The typical method of M. tuberculosis complex ancient DNA detection in archaeological

remains is by PCR assays utilising target regions that are thought to be specific to

MTBC members. The two earliest targets that have been used to screen for the presence

of MTBC are the multi-copy targets, insertion sequences IS6110 and IS1081 (Taylor et

al. 1996; Zink et al. 2001). These markers were thought to enhance the likelihood of

ancient TB detection as they are highly conserved within MTBC members as well as

their multi-copy nature. In each bacterium, IS6110 and IS1081 exist in zero to 26 copies

and five to six copies respectively (van Soolingen et al. 1992; Alonso et al. 2013).

However, there are some limitations in using IS6110 as the genetic marker. It is absent

in certain M. tuberculosis strains particularly in some Asian regions, where more than

10% of strains lack IS6110 (Brown & Brown 2011). Furthermore, there is a constant

suspicion about the lack of specificity of IS6110 as a marker (Müller et al. 2015). In

2015, Müller and colleagues published a study which confirmed the presence of IS6110

in ‘mycobacteria other than tuberculosis’ (MOTT) in archaeological remains from

Roman England and medieval Scotland. This study raised a doubt of using IS6110 as the

sole target in confirming archaeological detection of tuberculosis; usage of other more

specific tests is recommended when screening for the presence of ancient TB DNA.

Also, IS6110 and IS1081 do not allow discrimination between MTBC members, which

has prompted the study of single copy markers that might be to be used to identify

individual species in the MTBC group (Coros et al. 2008). One of these markers is the

oxyR pseudogene which harbours a single nucleotide polymorphism (SNP) that has the

discriminative power to distinguish M. bovis from the remaining members of the MTBC

(Sreevatsan et al. 1996). The presence of an A nucleotide at the 285th nucleotide position

of this gene confirms the M. bovis identity while the presence of G points out the

44

identity of the bacterium as being one of the other members of the complex (Sreevatsan

et al. 1996). More recently, two more genes harbouring distinguishing SNPs were

discovered and applied to ancient tuberculosis detection and discrimination: katG and

gyrA (Sreevatsan et al. 1997). The study of variable regions in 100 strains of M.

tuberculosis, M. bovis, M. africanum, M. microti and M. canettii led to the detection of

an M. tuberculosis specific deletion (TbD1) which allows discrimination between

“ancient” and “modern” strains of M. tuberculosis (Brosch et al. 2002). Another single

copy marker that is routinely used in M. tuberculosis aDNA detection is RD2 – currently

known as RD7 – although this is not as frequently used as IS6110 (Gordon et al. 1999).

This particular region can distinguish M. tuberculosis from M. bovis due to its intact

nature in M. tuberculosis but absence in the M. bovis genome.

PCR screening using IS6110, IS1081 and TbD1 confirmed the earliest case of

tuberculosis, dating from 9250 to 8160 years ago (Hershkovitz et al. 2008). The skeletal

remains belonged to a woman and an infant buried together, and were recovered from

Atlit-Yam in the East Mediterranean. Adult and infant aDNA were extracted from rib

and long bone, respectively. The study of aDNA in archaeological remains has brought

about exciting discoveries about this disease in the past. In 1994, Salo and colleagues

successfully amplified IS6110 from naturally mummified lung tissues from a body

which belonged to a 1000-year-old female recovered in Southern Peru (Salo et al. 1994).

This evidence pointed to the presence of human tuberculosis in the New World during

the pre-Columbian period.

1.6.1.2 Origin and evolution of tuberculosis

The study of MTBC variations has resulted in the attempts to reconstruct the origin and

evolution of tuberculosis. The genotyping studies performed in archaeological

specimens are benefiting from the genomic variation studies in contemporary MTBC

isolates.

One of such studies was performed by Sreevatsan and colleagues (1997) which

successfully identified two important SNP markers: katG and gyrA, which allow the

genotyping of MTBC strains into three main principal groups (PGG) : PGG1 to PGG3.

They looked at 26 structural genes in 842 modern MTBC global isolates and

successfully identified the two SNP markers. The discrimination lies in nucleotide

45

mutations in the codon positions 463 and 95 of the katG and gyrA genes, respectively.

The T to G nucleotide substitution on the 463rd position of katG will result in a leucine

to arginine amino acid change. Similarly, the C to G nucleotide substitution at the 95th

codon position of gyrA gene will result to a threonine to serine amino acid substitution.

The distribution of MTBC isolates is depicted in Figure 1.4 below. Interestingly, all M.

microti, M. africanum and M. bovis isolates were categorized specifically PGG1, while

M. tuberculosis isolates are spread across group PGG1 to group PGG3. It was then

highlighted that the species in PGG1 are ancestral to PGG2 and PGG3 as there is more

genetic variations observed – it was assumed that these pathogens were allowed to

accumulate more genetic variations by a longer time of evolution. However, the lack of

neutral mutations was highlighted in this study, as up to 95% of nonsynonymous

mutations are harboured in the antibiotic resistance genes which are under a strong

positive selection pressure (Sreevatsan et al. 1997).

Figure 1.4: The genotyping scheme of MTBC members using the katG463 and

gyrA95 markers. (taken from Sreevatsan et al. 1997: p. 9,871).

Later, a study performed by Bos and research members (2002) have discovered a

specific deletion in RD region and TbD1 gene that can be used to separate between

modern and ancient M. tuberculosis isolates. The classification is based on the absence

or presence of the deletion in the MTBC genome. Another important study of

contemporary MTBC isolates was published by Filliol and colleagues in 2006, where

they successfully classified MTBC into phylogenetically distinct groups made up of six

lineages described as SNP cluster groups (SCGs) as well as five subgroups (Filliol et al.

2006). The M. bovis isolates are contained in the seventh group.

46

Figure 1.5: MTBC phylogenetic lineages 1 to 7.

The ‘modern’ and ‘ancient’ MTBC can be distinguished based on the presence or absence of 7bp

deletions within the TbD1 region. Each branch is showing different MTBC lineages (L1-L7)

which is also associated to the geographical origins of the individuals where the MTBC isolates

were extracted from. (Taken from Brites et al. 2015).

Next, an additional phylogenetic lineage was recognized giving rise to 7 M. tuberculosis

lineages: L1-L7 (Figure 1.5), where M. bovis is now typically being called lineage 8

(Comas et al. 2013). It was revealed that there is a strong link between the place of birth

of the individual and the geographical origin of the M. tuberculosis sample. Lineage 1

typically occurs in the Indian Ocean and the Philippines, lineage 2 is linked to East Asia

tuberculosis, lineage 3 is assigned to both East Africa and India, lineage 4 is for

tuberculosis in Europe and North and South America, whereas lineage 5 occurs

predominantly in West Africa (Witas et al. 2015). Interestingly, lineage 4 is the most

typical group of M. tuberculosis and lineage 7 has only been found in the Ethiopian

region or among recent emigrants from Ethiopia. M. tuberculosis lineage genotyping has

been performed with several archaeological specimens. In 2012, Bouwman and

colleagues performed target enrichment for 247 SNPs of which 214 sites were

47

successfully covered in the subsequent sequencing. From this study, an individual from

the 19th century whose body was recovered from St George’s Crypt in Leeds, West

Yorkshire, England was identified to harbour a genotype belonging to lineage 2, SNP

type (ST) 14/40 and SCG 6 (Bouwman et al. 2012). Another British MTBC aDNA study

was also performed by Müller and colleagues (2014b) revealing that multiple genotypes

of M. tuberculosis were present in this region between the 18th – 19th centuries.

Many studies have been performed to decipher the origin and evolution of MTBC – both

using contemporary and ancient isolates. The most common misconceptions of the

evolution of tuberculosis is that human tubercle bacilli were derived from M. bovis

(Kapur et al. 1994; Stead et al. 1995). This assumption was initiated by the zoonotic

acquisition of tuberculosis infection by humans where the disease can be transmitted

through the ingestion of meat or milk products that have been contaminated by M. bovis.

This idea is propagated even further by the fact that M. tuberculosis has a highly

specialized niche in humans, while M. bovis have a wide host spectrum including cattle,

goats and sheep. The initial theory was that a strain of M. bovis successfully infected a

human, followed by successful spread within human populations. This led to co-

evolution of the tubercle bacillus with human hosts for millennia that resulted in a highly

specialized niche inside the human body, finally giving M. tuberculosis. Furthermore,

the earliest DNA evidence of human tuberculosis is only 9,250-8,160 years ago – which

is a skeleton from the now submerged Atlit-Yam site in the Eastern Mediterranean

(Hershkovitz et al. 2008). Meanwhile, the animal tuberculosis biomolecular evidence

points to a much older case – 17,000 before present (BP) isolated from the an extinct

long-horned bison recovered from the Natural Trap Cave in Wyoming, North America

(Rothschild et al. 2001). This theory however was proposed prior to the availability of

the whole genome sequence (WGS) of M. tuberculosis. The WGS of M. tuberculosis

allowed a comparative genomics study, which successfully uncovered variable genomic

regions among the MTBC members. Among the variable genomic regions uncovered is

the M. tuberculosis specific deletion 1 (TbD1) that is deleted in M. tuberculosis H37Rv

but is intact in the other members of the MTBC. In a set of experiments involving 100

strains of MTBC including M. tuberculosis, M. bovis, M. africanum, M. canettii and M.

microti, 20 variable regions were studied by Brosch and colleagues (2002), including the

TbD1. The MTBC member strains were collected from hosts from diverse global

locations. In this study, it was further found that some of the M. tuberculosis strains have

the deletion in the TbD1 region. In addition, this study also showed that M. bovis

harbours more deletions in its genome in comparison to M. tuberculosis; and based on

48

the M. bovis AF2122/97 (cattle strain) near-complete genome, it was shown that M.

bovis has a smaller genome compared to M. tuberculosis. It was speculated that the

tubercle bacilli that are most similar to the precursor of M. tuberculosis are human

pathogens, not an animal pathogen (M. bovis) – contrary to previous beliefs.

Meanwhile, MTBC origin is also being extensively studied using contemporary and

ancient isolates – with results for the date of origin varying in range from 70 kya to less

than 6,000 years ago. In an earlier publication, Kapur and colleagues (1994) studied

eight short target sequences in 31 modern M. tuberculosis isolates from all parts of the

world. The result revealed a very low nucleotide diversity among the M. tuberculosis

isolates. The calculation of evolutionary time scale based on the number of variations in

four genes suggested that the divergence among the modern isolates might have begun

15,300 to 20,400 years ago. This timeline coincides approximately to the

palaeomigration of humans into the New World. In addition, this time estimate also

coincides with the beginning of cattle domestication which convinced the authors that

rather than M. tuberculosis, M. bovis was the more ancestral species. However, this

study is not without its limitations. It did not take into account the diversity levels in the

other members of the MTBC, hence weakening the argument.

Later, a study by Sreevatsan and colleagues (1997) proposed a recent evolutionary

bottleneck event – with the speciation time predicted to have occurred around 15,000-

20,000 years ago. This assumption was based on the small allelic diversity observed in

the tubercle bacilli. An African origin of MTBC was proposed and several other studies

are also in line with this theory (Gutierrez et al. 2005; Hershberg et al. 2008; Wirth et al.

2008). The age of the M. tuberculosis last common ancestor was estimated by looking at

the accumulation rate of synonymous substitutions. By counting the synonymous

substitution rate, Gutierrez and colleagues (2005) estimated that M. tuberculosis has

existed since 3 million years ago. This coincides with the presence of hominids in East

Africa 3 million years ago – supporting the theory of the emergence of tubercle bacilli

from Africa. From there, it was speculated that the bacilli underwent early

diversification followed by the spread of successful clones to the other parts of the world

following human migrations out of Africa. However, the evidence from archaeological

specimens is not in line with this theory. Bos and colleagues (2014) proposed that the

age of the M. tuberculosis complex most recent common ancestor (MRCA) is less than

6,000 years ago. This conclusion was derived from an aDNA study of a Pre-Columbian

skeleton aged approximately 1,000-years-old. The Peruvian ancient genomes are more

49

closely related to animal lineages; closest to M. pinnipedii strains – restricted to seals

and sea lions. This provides a plausible theory of seal and sea lions as the possible route

of tuberculosis pathogen entry to the New World. The study confirmed pre-Columbian

MTBC infection in South America.

Another recent comprehensive study of ancient M. tuberculosis was published in 2015

by Kay and colleagues. This group has successfully obtained genome sequences of 14

ancient M. tuberculosis isolates through a shotgun metagenomics method, without prior

target enrichment (Kay et al. 2015). The 18th century Hungarian M. tuberculosis isolates

were extracted from human remains, most of which had undergone natural

mummification, recovered from a Dominican church in Vac. The genome sequences

depicted that all 14 ancient M. tuberculosis isolates belonged to phylogeny lineage 4.

This lineage characterization, which is also known as the Euro-American lineage, was

also confirmed by the 7 bp nucleotide deletion within the pks15/1 gene region. A

phylogenetic analysis performed with 1,582 unassembled genomes of other identified

lineage 4 members revealed that at least 12 M. tuberculosis strains were present in this

region during that time. Kay et al. (2015) also dated the divergence time for lineage 4 by

utilizing four high-coverage M. tuberculosis ancient genomes. The mutation rate of this

lineage is estimated to be 5.00 x 10-8 substitutions per nucleotide in one year. This is in

line with the hypothesis from the previous historical M. tuberculosis study (Bos et al.

2014), which suggested the age of the last common ancestor to be not more than 6,000

years ago. Mixed-infection from multiple M. tuberculosis genotypes was also shown in

this study.

In contrary to the hypothesis derived from contemporary MTBC isolates, in historical M.

tuberculosis isolates, Bos et al. (2014) and Kay et al. (2015) predicted the age of the last

common ancestor to be less than 6,000 years ago. However, this is not in line with

several historical tuberculosis cases that are older than 6,000 years old supported by

osteological and biomolecular evidence (Rothschild et al. 2001; Hershkovitz et al. 2008;

Nicklisch et al. 2012). This discrepancy could be influenced by the errors made in the

assumptions in the phylogenetic dating. Kay and colleagues (2015) also proposed that

contamination could also be the cause of this discrepancy. Looking at the current

theories of tuberculosis origin, it seems that more studies are needed to obtain a

conclusion that is consistent for both the contemporary and historical study of

tuberculosis.

50

1.6.2 Ancient DNA studies of leprosy

1.6.2.1 Case confirmation

Similar to tuberculosis, the earliest studies of leprosy ancient DNA were mainly

focussed on case confirmation as an extension of the osteological diagnosis approach.

Rafi and colleagues detected the first ancient M. leprae DNA in 1994 from a 600 AD

archaeological bone recovered from a grave at the Monastery of St John the Baptist,

located at the river Jordan which is where Jesus is believed to have been baptised by

John (Rafi et al. 1994). The detection was performed by PCR amplification of a part of

the 36 kDa antigen and 65 kDa protein encoding genes, the first of which is specific to

M. leprae and the second of which is found in all mycobacteria (Hartskeerl et al. 1989;

Telenti et al. 1993). PCR amplification of the 36 kDa gene gives a 530 bp product,

which is relatively large for ancient DNA amplification, considering the fragmented and

damaged nature of ancient DNA. In 2001, this problem was addressed by Donoghue and

colleagues by designing M. leprae specific primers for a nested PCR which targets the

repetitive element RLEP, and which gives an outer product of 129 bp and a 99 bp

product for the nested PCR (Donoghue et al. 2001). M. leprae detection by PCR of this

repetitive element was demonstrated by Woods and Cole (1990) with modern isolates,

and then subsequently used by Yoon and colleagues (Yoon et al. 1993) with clinical M.

leprae isolates. The repetitive element was first used for detection of M. leprae from

archaeological remains by Donoghue et al. (2001). Today, RLEP is the most frequently

used target to detect M. leprae in archaeological remains. The repetitive element RLEP

is dispersed in at least 28 copies throughout the genomes of modern M. leprae isolates

(Woods & Cole 1990), and is attractive for ancient M. leprae detection as its multi-copy

nature increases the chance of DNA fragment preservation.

The oldest case of leprosy confirmed with ancient DNA is from The Tomb of the Shroud

in Hinnom Valley, Mount Zion (Matheson et al. 2009). The location is associated with

the traditional Akeldama, mentioned in the Bible as the “Field of Blood”. The age of the

skeletal remains is estimated to be from 2025±28 years BP as estimated by the AMS

radiocarbon method. Interestingly, one of the skeletons is not only positive for M. leprae

DNA but also tested positive for M. tuberculosis DNA which indicates co-infection

(Matheson et al. 2009). The presence of these two pathogenic mycobacteria indicates

immune-suppression, which is one of the characteristics of a person with lepromatous or

51

multi-bacillary spectrum leprosy. This skeleton gave positive PCR results for both the

nested RLEP assay and the 18 kDA gene, although the product for the 18 kDa PCR was

in low amounts due to the single copy nature of the marker. The same marker was used

to detect M. leprae DNA in skeletal remains from a South German ossuary and a

Hungarian cemetery dated approximately to 1400-1800 AD and the 10th century AD,

respectively (Haas et al. 2000). The Germany samples were taken from skulls while the

Hungarian sample was from the hard palate and both gave positive RLEP1 and RLEP3

amplifications. In the same study, DNA from the hands and feet were also examined but

did not produce sufficient amplification products for M. leprae detection. The results

suggest that peripheral parts of a skeleton displaying signs of leprosy may contain

significantly fewer bacteria, or it could be that the peripheral bone changes are the result

of secondary infection. This also suggests that the rhinomaxillary alteration is a result of

direct M. leprae bacterial involvement. The first ancient leprosy case from Britain was

from Orkney, Scotland (Taylor et al. 2000). The archaeological remains recovered from

the 13-14th Norse Christian cemetery located at Newark Bay showed lepromatous

leprosy skeletal changes. Screening with the RLEP PCR produced positive amplification

for the extract from the skull bones but not the clavicle, left scapula, vertebra, or femur.

This again, seems to align to the result obtained by Haas and colleagues (Haas et al.

2000). On the other hand, a study of 12th century AD skeletal remains recovered from

the fortress site of Capilla y Castillo de San Jorge in Spain reported successful M. leprae

detection from metacarpal bones following RLEP PCR (Montiel et al. 2003). The

positive identification was also supported by restriction analysis with ClaI which detects

a site present in the RLEP region as well as Sanger sequencing.

Later studies have detected more leprosy cases from global locations. The earliest case

of leprosy confirmed by osteological evidence of high confidence is from the Roman

period (Rubini, Erdal, et al. 2014). A skeleton recovered from Martellona, Italy, was of a

child aged between 4 to 5 years with pronounced rhinomaxillary syndrome strongly

suggestive of a well-developed leprosy infection. This is the youngest individual with a

confirmed case of leprosy. It is quite surprising to observe convincing skeletal

manifestations in such young individuals, considering leprosy is a chronic and slow

progressive infection. However, one of the proposed explanations for this was that the

M. leprae strain that existed at this time was more aggressive compared to contemporary

M. leprae (Rubini, Erdal, et al. 2014). Another childhood leprosy case that was reported

in the same study, describing a 4-5 month old infant from Kovuklukaya, Turkey, with

some indication of chronic inflammation in the bone, is even more surprising as the

52

leprosy case was confirmed by molecular evidence (Rubini, Erdal, et al. 2014). These

skeletal remains are estimated to age from the 8th to 10th centuries AD, during the

Byzantine period. Both cases most probably result from in utero haematogenous

transmission of the infection from a pregnant mother who was suffering from leprosy

infection. In addition, past leprosy cases have also been confirmed through molecular

evidence in Japan, from archaeological remains recovered from the Hatanai site located

in the Honshu Island of Japan (Suzuki et al. 2010). The analysis of the excavation sites

estimated the age of the bone remains to be most likely from the mid-18th to the early

19th century AD. The bones show characteristics of the lepromatous type of leprosy,

with rhinomaxillary syndrome (Suzuki et al. 2010). Another study by Watson and

Lockwood (2009) confirmed leprosy cases in Croatia (8th-9th century AD), Denmark

(1275-1560 AD) and the United Kingdom (900-1000 AD). The positive detections were

from the rhino-maxillary area (Croatia), palatine bone (Denmark) and rhino-maxillary,

tibia, and metatarsal (United Kingdom). Positive M. leprae detection has also been

obtained from a Byzantine skeleton dated 300-600 AD from Bet Guvrin, Israel

(Spigelman & Donoghue 2001).

1.6.2.2 Origin and evolution of leprosy

Most of the past leprosy case confirmation studies described previously were performed

by amplification of the RLEP region. Whole genome sequencing of the modern M.

leprae TN strain from Tamil Nadu, India, provided an opportunity to explore additional

sites of the genome that could be studied and applied to ancient M. leprae isolates (Cole

et al. 2001). The 3,268,210 bp genome of M. leprae has a G+C content of only 57.8%,

which is much lower than that of M. tuberculosis, whose genome is 4,411,531 bp with

65.6% G+C content. In fact, the G+C content of M. leprae is the lowest of all known

mycobacteria (Singh & Cole 2011). From the genome sequence analysis done by Cole

and colleagues, only 49.5% of the M. leprae genome codes for proteins, while 27% and

23.5% of the genome are pseudogenes and non-coding DNA, respectively (Cole et al.

2001). From a comparison of the M. leprae and M. tuberculosis genomes, under the

assumption that these were at one point of time in a state of similar topology, it was

concluded that the M. leprae genome has undergone significant downsizing, and may

have lost around 2,000 genes since the last common ancestor of the two species

(Eiglmeier et al. 2001). The high number of pseudogenes together with the increasing

53

number of insertion sequences (IS) and reduced G+C content are attributes of reductive

evolution, which can be linked to the extreme obligate nature of M. leprae (Singh &

Cole 2011). The reason for the massive gene inactivation could be the highly specific

niches occupied by the bacteria, such as Schwann’s cells, where M. leprae will not be

subject to competitive pressure from other microbes. Gomez-Valero and colleagues

(2007) suggested that the shaping of M. leprae into a highly specialized pathogen was

due to massive gene reduction which most likely happened at the same time as the

pseudogenization events.

The sequencing of the whole M. leprae TN genome allowed further exploration of

regions and targets that can be used in genotyping. Selected genes, pseudogenes and

non-coding regions were compared between the genomes M. leprae TN and Brazilian

strains (Monot et al. 2005). This comparative genomic study resulted in the discovery of

three unique SNPs that can classify M. leprae isolates into four groups: SNPs type 1 to

4. These SNPs, at positions 14,676, 1,642,875 and 2,935,685, interestingly show strong

association with the geographic origins of patients. SNP type 1 is mostly shown by

patients from Asia, East Africa and the Pacific region, SNP type 4 is typically found in

the Caribbean and West Africa, while SNP type 3 is the typical of the M. leprae type

infecting the people in Europe, North Africa and the Americas, as demonstrated in

Figure 1.6 (Monot et al. 2005). Fascinatingly, SNP type 2 is the least typical type,

infection of M. leprae with this type being found only in Malawi, Ethiopia, Nepal or

North India, and New Caledonia (Monot et al. 2005). Based on this scheme, it is

suggested that leprosy originated in the Near East or in Eastern Africa. Subsequently,

successive human migrations have been responsible for the dissemination of this disease

worldwide. This scheme was soon used to classify ancient M. leprae isolates from

Europe, including the United Kingdom, Denmark and Croatia (Watson & Lockwood

2009). This study showed that all ancient M. leprae isolates genotyped from these three

European countries (476 AD to 1350 AD) belong to SNP type 3 (Watson & Lockwood

2009). A comprehensive study performed by Monot and colleagues (2009) involved the

comparative analysis of four complete genomes of modern M. leprae strains: M. leprae

TN from India, M. leprae Br4923 from Brazil, M. leprae Thai 53 from Thailand, and M.

leprae NHDP63 from the United States. The analysis revealed extremely low sequence

diversity among strains: they are

54

Figure 1.6: The distribution of four different leprosy SNP types around the world

and the prediction of human migrations.

Each SNP type is depicted in a different colour. SNP-type 1: yellow, SNP-type 2: orange, SNP-

type 3: purple, SNP-type 4: green. The arrows are showing the proposed routes of migrations,

inferred from SNP analysis – the colour is similar to the circles for each SNP-type. The

estimated time of migration (in years) is shown in grey arrows. The estimation was made based

on genetic, archaeological and anthropological studies (Figure taken from Monot et al. 2005).

99.995% identical. There were only 215 polymorphic sites and 5 pseudogenes identified.

The evaluation of polymorphic sites classified M. leprae isolates into 16 subtypes (1A-

1D, 2E-2H, 3I-3LM, 4N-4O) that are closely related to the geographical location of their

hosts. This subtyping scheme is able to shed light on the trade routes and migration

patterns of humans in the past, as depicted in Figure 1.6 (Monot et al. 2005). Based on

the construction of a phylogenetic tree of the present M. leprae isolate sequences, the

genotype of the ancestral M. leprae strain was estimated as between type 2 and 3. This

result supports the previous assumption that M. leprae in East Africa could belong to

type 2. This type 2 East African strain then produced the type 1 strain that moved east to

Asia following human migrations. From there, M. leprae spread to the west, towards the

Middle East then Europe, in type 3 form before finally giving rise to the type 4 that can

be found in West Africa, the latter movement believed to be through the slave trade. The

introduction of leprosy to the Americas was most probably through European

immigrants instead of crossings of humans via the Bering straits (Monot et al. 2009). A

genome-wide comparison of five medieval M. leprae strains, each with more than 80%

genome coverage, discriminated M. leprae isolates into five distinct branches, 0-4, each

55

associated with a particular subtype (Schuenemann et al. 2018). The most ancestral

branch 0 is associated with subtype 3K which can be found in contemporary M. leprae

strains isolated in China and New Caledonia.

56

Chapter 2: Materials and methods

2.1 Archaeological samples

The archaeological bones described here are the samples studied in Chapter 3 and 4. The

samples investigated in Chapter 5 is described separately in each respective chapter.

Sixty skeletal samples from sixty individuals dated from Roman to the post-Medieval

periods were studied (Table 2.1, Table S2.1). Rib fragments were mainly analysed from

the 60 skeletons from 16 different locations in Yorkshire. The samples originated from

urban and rural locations of Yorkshire. The exact location in each site is shown in

Figure 2.1. Seven of the sites are in York city, therefore the samples from the area are

classified as “urban”. The sample from East Heslington is still considered urban

although it is not located inside the city of York. This classification is based on its

proximity to York in comparison to the other rural sites. It could have been a separate

community in the past but the closeness to York made it possible for people to be

exposed to the same strain of MTBC that was circulating in the city during that period.

The archaeological bones were collected by Dr Darlene Weston as part of the National

Environment Research Council (NERC) project on “The Palaeopathology of

Tuberculosis in Britain and Europe” (NE/E015697/1, 2007–2010), subsequently

continued as “Palaeopopulation genomics of Mycobacterium tuberculosis

(NE/K012185/1, 2013–2016). Two from the 60 bone remains: 3 Driffield Terrace 13 and

East Heslington 229 have previously been studied and reported by Dr Romy Muller and

colleagues (2014a). The remaining 58 samples were studied for the first time in this

project. DNA extraction was performed from the bone powder in the aDNA lab facility

at the Manchester Institute of Biotechnology. In my work, PCR assays were used to test

for MTBC aDNA preservation, using markers which are supposedly specific to the

MTBC genome: the insertion sequence IS6110, and the gyrA, Rv0083 and Pks 15/1 loci

(Bouwman et al. 2012; Alonso et al. 2013; Müller et al. 2014a). Although the specificity

of the multi-copy region IS6110 is questionable, it is still the most robust target for

MTBC aDNA detection so far (Müller et al. 2015). Therefore, as per the

recommendation by Muller et al. (2015), the screening was accompanied by the other

three single copy regions, which are deemed specific to the MTBC genome. Nested PCR

was incorporated in the IS6110 assay to enhance the detection power and increase

57

detection specificity. The three single-copy targets have previously been used for SNP

(gyrA, Rv0083) and indel (Pks15/1) genotyping (Müller et al. 2014b).

58

(b)

(a)

Figure 2.1: The origin locations of the Yorkshire archaeological remains. (a) The rural sites

which are marked by red placemarks and one of the urban sites marked by the yellow

placemarks. The red circle marks the city of York location where the rest of the urban samples

were taken from, (b) The urban sites in the city of York marked by yellow placemarks. Some of

the placemarks overlap with each other. Images are extracted from Google Earth.

York

59

Burial location Period Context Skeleton

number

Parts of skeletons

showing

tuberculosis

lesions or non-

specific lesions

Part of

skeleton

studied

Reference

York Minster Early

mediaeval

Urban

cemetery

1 Control Right rib Lee n.d.

15 Lytic lesions on

sacrum and lower

thoracic

vertebrae.

Periosteal bone

formation and

lytic lesions on

the ribs

Right shaft

femur

Fishergate House Late

mediaeval

Urban

cemetery

86 Periosteal new

bone formation

on the right ribs

Right rib Holst 2005

98 Rib lesions Left rib

108 Lytic lesions on

lateral portions of

lower thoracic

and lumbar

vertebral bodies

and lesions on the

ribs

Left rib

60

135 Rib lesions Left rib

147 Control Rib

149 Control Rib

St Andrew Fishergate Late

mediaeval

(Early 14th

century AD)

Urban

cemetery

6 Lytic lesions on

sacrum and lower

thoracic

vertebrae.

Periosteal bone

formation and

lytic lesions on

the ribs

Rib Stroud & Kemp 1993

277 Rib lesions Rib

286 Rib lesions Rib

296 Periosteal new

bone formation

on bodies of L1-

L3 vertebrae.

Lytic lesions

observed on body

of L1 vertebrae

Rib

323 Destruction of L5

vertebrae.

Periosteal new

bone formation

and lytic lesions

on the ribs

Fragment

from

proximal

right tibia

61

339 Lytic lesions on

the thoracic and

lumbar vertebrae

Rib

384 Rib lesions

accompanied by

endocranial

lesions

Rib

34 Control Rib

131 Control Rib

253 Control Rib

St Helen-on-the-Walls Late

mediaeval

Urban

cemetery

5000 Left os coxa

which is a

separated element

from mixed

context

Rib Dawes & Magilton 1980

5844 Lesions on the

left ribs and the

L4 and L5

vertebrae

Left rib

6003 Lower thoracic

and lumber

vertebrae

Rib

5494 Control Rib

62

East Heslington Late Roman

(3-8th

century AD)

Burial

associated

with high-

status

Roman villa

in rural

location

229 Lower thoracic

vertebrae

Lumbar

vertebrae

body

Holst 2008; Neal & Roskams 2012

3 Driffield Terrace Roman

(Early 3rd

century AD)

Urban

cemetery

37 Rib lesions Rib Caffell & Holst 2012; Muldner et al. 2011

54 Rib lesions Rib

13 None Rib

15 Rib lesions Rib

6 Driffield Terrace Roman

(Early 3rd

century AD)

Urban

cemetery

19 Rib lesions Rib Caffell & Holst 2012

22 None Rib

St Peter’s Huddersfield Post

mediaeval

Urban

churchyard

5 Rib lesions Right rib Cafell & Holst 2008b

7 Rib lesions Right

femur

17 Control Proximal

end of left

humerus

Wetwang Slack Iron Age Rural

cemetery

1 Rib lesions Right rib Dent 1984

2 Destruction of left

hip

Rib

63

5 Lytic lesions on

thoracic vertebrae

T12 and lumbar

vertebrae L2

Rib

6 Lytic lesions on

upper thoracic

vertebrae

Rib

8 Lytic lesion on

right ilium

Rib

9 Psoas abscess on

the left femur

Rib

3 Control Rib

4 Control Rib

7 Control Rib

Settlement 185 N/A Vertebrae Dent 1984

360 N/A Vertebrae

415 N/A Vertebrae

Sewerby Anglo-

Saxon (mid-

6th – 7th

century AD)

Rural

cemetery

34 Calcified pleura Skull

fragment

Hirst 1985

44 Control Mid-shaft

left radius

64

St Giles by Brompton

Bridge

Late

mediaeval

(12th-15th

century AD)

Rural church

cemetery

1288 Rib lesions Rib

fragment

Cardwell et al. 1995

1531 Rib lesions Rib

fragment

1542 Control Left

humerus

fragment

Alicy Hill Early

mediaeval

(7th century

AD)

Rural

cemetery

1044 Pott’s spine with

lytic lesions on

T11 and T12

vertebrae

Rib Hall & Whyman 1996

1043 Control Rib

Wharram Percy Late

mediaeval

Rural

cemetery

26 Left elbow Distal left

ulna

Mays et al. 2007

1600 Control Femur

fragment

Addingham Early

mediaeval

(670-

990AD)

Rural

cemetery

134 Pott’s spine Rib

fragment

Adams 1996

223 Rib lesions Rib

fragment

103 Control Rib

fragment

Melton Roman Rural 4297 Rib lesions Left rib Caffell & Holst 2008a

65

cemetery 2554 Rib lesions Right rib

5319 Control Left tibia

Hickleton Late

mediaeval –

early post

mediaeval

Rural 46 Spine Vertebrae Manchester & Roberts 1986

Table 2.1: A complete list of all bone remains studied for the preservation of MTBC aDNA. This table showing the skeleton dates, site origins, skeleton

parts showing lesion or non-specific lesions (and control) and skeleton parts sampled in the study. N/A: information not available

66

2.2 Authentication regimes

As discussed previously, the damaged, fragmented and low copy nature of ancient

DNA demands protocols to be performed in a very careful manner (Dabney, Meyer, et

al. 2013). DNA templates of these characteristics are very prone to exogenous DNA

contamination (Knapp et al. 2015). The typical sources of contamination are from the

environment and DNA of the personnel handling the archaeological remains which

effortlessly outcompete the very little and damaged endogenous aDNA recovered

(Noonan et al. 2005; Poinar et al. 2006). There is a risk to introduce contaminants at

any stage of the experiments (Gruber 2015). The study was carefully tailored to make

sure there is a balance between minimizing the risk of contamination in samples and

maximizing the yield of endogenous DNA.

All experimental protocols prior to PCR amplification in the PCR thermocycler were

performed in physically isolated clean rooms dedicated to ancient DNA at the

Manchester Institute of Biotechnology. The clean rooms are located on a different

floor (lower ground) to the laboratory where all the “modern” or “post PCR

amplification” experimental works is carried out on the second floor (previously first

floor) in the building. There are two clean rooms dedicated for experimental works

using archaeological bone remains as starting materials: a human bone aDNA

extraction room and a human bone aDNA PCR mixture preparation room. Both rooms

are physically isolated from each other. Access to these rooms is restricted to trained

lab personnel and the inevitable occasional equipment maintenance, and is locked at all

times except when in use. Each room is designed to have an antechamber at the anterior

of the clean room which acts as contamination buffer zone and gowning area before

entering the clean room. The room is supplied with ultra-filtered air which circulates in

the room in a positive displacement manner. This manner of air circulation will avoid

the uptake of possibly-contaminated unfiltered air from the outside of the clean room.

In addition, the clean rooms are also equipped with ultraviolet (UV) lights (254 nm);

the rooms are UV irradiated for at least four hours after each use.

67

Appropriate protective clothing is worn before entering the clean room; the gowning is

performed in the antechamber. The protective clothing includes disposable

polypropylene coverall, surgical mask, hair cover/net, goggle, disposable shoe covers

and two layers of gloves with the outside layer being changed regularly. Benches and

surfaces inside the aDNA room are cleaned with 5% sodium hypochlorite, followed by

70% ethanol. The more delicate equipment surfaces such as centrifuges and weighing

balances are cleaned with DNA Away (Molecular Bioproducts). Smaller equipment

such as pipettes, consumables and selected reagents were UV irradiated (254 nm,

120,000 µJ cm-2 for 2 × 5 min, with 180° rotation between the two exposures) before

use. All DNA extraction protocols were performed in a Class II biological safety

cabinet. Meanwhile, in a physically separate aDNA dedicated room, PCR mixtures

were prepared in a laminar flow cabinet. This room is restricted for PCR mixture

preparation before the amplification is performed in a distant modern laboratory

dedicated to modern samples and post-PCR experiments. In addition, the PCR clean

room is also used for DNA library mixture preparation, again prior to the amplification

step.

2.3 Bone scraping and crushing

The archaeological bone samples studied in Chapter 3 and Chapter 4 have previously

being scraped and crushed by personnel in Brown lab: Dr Abigail Bouwman and Dr

Romy Muller. Meanwhile, the samples described in Chapter 5 have been scraped,

crushed, extracted and screened for M. leprae presence by Dr Romy Muller as part of

her Master’s project. The starting materials used in my project were DNA extracts with

confirmed positive detection of M. leprae aDNA. The protocol described in this section

explains how the bone powder was prepared.

The part of bone of interest, usually the part showing lesions, was cut using a small

hacksaw while the remaining bone fragments, if any were kept. The exposed surface

area of the bones was scraped with a scalpel, to remove the outer 1 mm, before placing

in a small sampling bag and UV irradiating on both sides for approximately 5 minutes

on each side. This is followed by bone crushing. Finally, the bone powder was weighed

and transferred to sterile 1.5 mL Eppendorf tubes for subsequent DNA extraction.

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2.4 Ancient DNA extraction

This procedure was performed on the bone powder samples described in Chapter 3 and

4. The ancient DNA extraction procedure performed in this study follows the protocols

described by Dabney and colleagues with a few modifications (Dabney, Knapp, et al.

2013). The two days DNA extraction used 200 mg of bone powder in each extraction

batch. Each extraction batch included four different samples and two extraction blanks.

In cases where DNA extraction was performed on only one or two samples, only one

extraction blank was included. For the extraction blanks, similar reagents were added,

and the same protocols were performed but no sample was added to the tube, not even

water.

On the first day of extraction, the 200 mg bone powder was mixed with extraction

buffer in a Falcon™ 50 mL conical centrifuge tube. The extraction buffer comprises

0.45 M Ethylenediaminetetraacetic acid (EDTA), 0.25 mg/ mL molecular biology

grade Proteinase K (New England BioLabs) and Invitrogen™ UltraPure™

DNase/RNase-free distilled water to 2 mL final volume. Next, the samples were

incubated overnight (18 to 24 hours) in the dark in a water bath set to 37°C, with

constant agitation at 200 rpm. The incubation step is aiding the DNA release from the

bones by enhancing the powder digestion (Rohland & Hofreiter 2007).

On the second day of DNA extraction, the incubated solution was centrifuged at 6,000

rpm in an Eppendorf centrifuge for 5 minutes. This step was repeated twice by slightly

turning the Falcon™ 50 mL conical centrifuge tube containing the extraction solution

each time. After the third time of centrifuging, the supernatant was transferred to a new

Falcon™ 50 mL conical centrifuge tube and mixed with 12 mL binding/PB buffer

(Qiagen). The addition of binding buffer will aid the efficiency of DNA binding to the

spin-column membrane. This step and the subsequent steps were performed following

the instructions for the Qiagen MinElute kit with a few amendments. Now, the total

volume of the supernatant-binding buffer mix solution is 14 mL which exceeded the

maximum volume of the spin-columns provided by the manufacturer (Qiagen).

Therefore, in order to accommodate this, the Qiagen-provided spin-column was

connected to a reservoir and attached to a Falcon™ 50 mL conical centrifuge tube.

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Next, the binding apparatus was centrifuged at 6,000 rpm for 5 minutes. Subsequently,

the spin column was detached from the binding apparatus and placed into a collection

tube provided by the manufacturer (Qiagen). To dry, the spin-column was centrifuged

for 1 minute at 6,000 rpm speed. This is followed by two washing steps with 750 mL

washing/PE buffer (Qiagen). In between the washing steps, the spin-column was

centrifuged at 3,300 g for 1 minute. Lastly, two rounds of elution were performed by

adding 30 µL elution/EB buffer at each step, yielding 60 µL total volume of DNA

extract.

2.5 PCR assays screening for ancient DNA preservation

This step was performed for all samples mentioned in this study except for the samples

in Chapter 5, as the presence of M. leprae aDNA has already been confirmed in a

previous study (Müller 2008). To maintain the “ancient” nature of the DNA extract

used as the template, the PCR mix was prepared in the PCR clean room before

amplification in the modern laboratory. To maintain the one-way workflow, the

subsequent experiments post-PCR amplification were all performed in the modern

laboratory.

All DNA extract samples obtained from archaeological skeletons mentioned in Chapter

3 and 4 were screened for MTBC aDNA presence. In order to avoid contamination, a

positive control of M. tuberculosis DNA was not included in this study, which means

there will be no source of modern M. tuberculosis contamination, though there is still

the possibility of cross-contamination from M. tuberculosis DNA positive samples. In

each round of PCR amplification using the ancient DNA extract, two negative controls

(the PCR mix with no added DNA extract) were included.

The PCR assays for MTBC aDNA presence screening targeted four regions of the

MTBC genome, both multi-copy and single-copy regions. The first region targeted was

the multi-copy insertion sequence IS6110, which is typically used in MTBC aDNA

detection (Salo et al. 1994; Rothschild et al. 2001). The insertion sequence IS6110 can

exist in up to 26 copies per genome (Alonso et al. 2013). However, in rare cases, some

M. tuberculosis isolates have no copies (Huyen et al. 2013). The multi-copy nature

increases the chance of preservation of this target region in archaeological bone

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remains and hence increases the sensitivity of the PCR assay. To further increase the

detection signal, a nested PCR which amplifies a 92 bp fragment within the 123 bp

product from the first round of PCR was incorporated in the study (Konomi et al.

2002). Moreover, the presence of the band from the nested PCR in the gel

electrophoresis increases the confidence that the PCR band signal obtained from the

first PCR step was indeed from MTBC aDNA.

Apart from the insertion sequence IS6110, three single-copy targets were also included

in the MTBC aDNA preservation study. These targets are gyrA, Rv0083 and

polyketide synthase pks15/1, which have been used in MTBC strain discrimination in

previous studies (Müller et al. 2014b). Both gyrA and Rv0083 contain discriminative

SNPs while insertion or deletion of the polyketide synthase 15/1 enables MTBC strains

to be classified (Bouwman et al. 2012).

The PCR mixture with a total volume of 30 µL contained 1 x Amplitaq Gold 360

Master Mix (Applied Biosystems), 10% v/v 360 GC enhancer (Applied Biosystems),

0.5 ng/µL of bovine serum albumin (BSA) (New England Bio Labs), 400 nM of

forward and reverse primers and water. The purpose of adding BSA is to minimize the

PCR inhibitions (Forbes & Hicks 1996; Abu Al-Soud & Rådström 2000). The primer

sequences used in each PCR assay are depicted in Table 2.2. Since the amount of

endogenous DNA in the extract is not known, 3 to 6 µL DNA extract was used as the

template. For the IS6110 nested PCR, 1 µL of PCR product from the first step

amplification was used as the template. PCR inhibitors are often a problem in ancient

DNA studies, as these may have been co-extracted therefore hindering the PCR

amplification process. Hence, apart from the original undiluted DNA, a 10-fold diluted

DNA template was prepared for each sample and tested by adding 6 µL of this template

in the PCR mix.

For the first step of the nested IS6110 PCR, and for the gyrA, Rv0083 and Pks 15/1

PCRs, the cycle conditions were set as: 95ºC for 5 minutes followed by 45 cycles of

95ºC for 45 seconds, annealing temperature (Table 2.2) for 45 seconds and extension at

72ºC for 45 seconds. Lastly, the final extension was performed at 72ºC for 7 minutes.

Identical cycle conditions were set up for the IS6110 nested PCR, but instead of 45

cycles, 25 cycles were performed. The IS6110 nested PCR amplification was

performed in a separate thermal cycler machine to the other four assays, as the template

used is the already-amplified PCR product from IS6110, therefore considered as no

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longer “ancient”. This is to minimize the risk of contamination. The PCR products were

loaded into a 1.5% agarose gel electrophoresis which was stained with GelRed Nucleic

Acid Gel stain (Biotium, Inc). A UV transilluminator was used to visualize any PCR

bands in the agarose gel. Bands that are believed to be the correct or near to the correct

size were purified using the MinElute PCR purification kit following the standard

supplier procedure (Qiagen). In the case of multiple bands produced from the same

sample, and where one of the bands is of correct of near correct size, the band was

excised and the DNA purified with the MinElute Gel Extraction kit following the

standard supplier procedure (Qiagen).

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Table 2.2: List of primers used in the PCR screening for MTBC aDNA presence. Four MTBC specific targets were used in the MTBC aDNA presence

screening. The primer sequences, annealing temperatures and amplicon sizes are shown.

Target Primer pair sequence 5'-3' Annealing

temperature

(°C)

Amplicon

size (bp)

Reference

IS6110 first step F- CCTGCGAGCGTAGGCGTCGG 68 123 (Thierry et al. 1990)

R- CTCGTCCAGCGCCGCTTCGG

IS6110 nested PCR F- TCGGTGACAAAGGCCACGTA 58 92 (Taylor et al. 1996)

R- TTCGGACCACCAGCACC T

gyrA F- CCGGTCGGTTGCCGAGACCA 68 104 (Bouwman et al. 2012)

R- GCGGGTAGCGCAGCGACCAG

Rv0083 F- GCCACCGCCCCGACCAC 69 110 (Bouwman et al. 2012)

R- GTCACCCACACCGCCGAGTC

Pks 15/1 F- ATCTCGCCGAAATCACCCACG 67 92-99 (Bouwman et al. 2012)

R - CGTACCAGCCCCCGCAGAG

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Once purified, the PCR products were then cloned in XL-1 Blue competent Escherichia

coli cells (Agilent Technologies) using the blunt-end system CloneJET PCR Cloning kit

(ThermoFisher Scientific) protocols. Positive clones were screened using pJET vector

specific primers: pJET forward primer

(5’-CGACTCACTATAGGGGAGAGCGGC-3’) and pJET reverse primer (5’-

AAGAACATCGATTTTCCATGGCAG-3’). The 20 µL PCR mix comprises 200 nM of

each primer mentioned, 1x Taq PCR buffer and 0.5 units of Taq DNA polymerase, both

from New England Biolabs, and 200 µM of dNTP mix. Cycle conditions were: 95ºC

initial denaturation for 3 minutes followed by 30 cycles of denaturation at 94ºC for 30

seconds, annealing at 60ºC for 30 seconds, and extension at 72ºC for 30 seconds. Lastly,

the final extension was set to 72ºC for 7 minutes. Next, the positive clones were purified

and sent for Sanger sequencing at GATC Biotech (now Eurofins Genomics). The

resulting Sanger sequences were visualised and analysed in Geneious 8.1

(https://www.geneious.com, Kearse et al., 2012). In Geneious, the sequences were

trimmed and aligned to the M. tuberculosis H37Rv reference sequence for each region.

The possible identities for the sequences which failed to match the reference sequence

were determined using the NCBI Basic Alignment Search Tool (BLAST).

2.6 Next generation sequencing

2.6.1 DNA library preparation

For the samples in Chapter 3 and 4, depending on the PCR evaluation of MTBC aDNA

presence, appropriate samples were selected to be further studied using next generation

sequencing (NGS). For the samples in Chapter 5, all samples deemed positive for M.

leprae aDNA from the previous study (Müller 2008), were subjected to NGS. For all the

samples subjected to NGS, the DNA libraries were prepared following the double

indexing strategy for Illumina Genome Analyzer sequencing. Following the

development of high throughput DNA sequencing, it is a routine to include multiplexed

samples (pooling multiple libraries together) per run to increase cost efficiency (Rohland

& Reich 2012). In Illumina sequencing, the multiplexing strategy usually allows simple

identification by including an embedding index (short fragment of unique sequence)

within one of the adapters (Kircher et al. 2012). However, one of the drawbacks of this

approach is the risk of falsely assigning the resulting sequences to their original samples,

which is highly undesirable in a genotyping study. Therefore, a double-indexing method,

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in which indexes are placed in both universal adapters at both ends of the sequence, was

utilized in DNA library preparation in this study in order to improve multiplex

sequencing accuracy (Kircher et al. 2012).

Figure 2.2: A simplified scheme of make up of dual-indexed DNA library fragments.

Adapters (green) are ligated to both ends of the DNA insert. In the indexing PCR amplification,

P7 and P5 adapters (light and dark blue); each contain different indices (yellow), will be attached

to the insert.

The DNA library was prepared to obtain fragments which contain compenents as

depicted in Figure 2.2 above. The DNA library preparation was preformed in house,

rather than outsourcing, to make sure the conditions comply to ancient DNA

requirements. The DNA library preparation involves a series of stages including blunt-

end repair, adapter ligation, adapter fill-in, and the final indexing PCR. The protocols

followed the steps described by Meyer and Kircher (Meyer & Kircher 2010). All first

part of the procedure was performed in the clean room before the subsequent

amplification steps were performed in the modern laboratory. All tubes used were DNA

LoBind tubes which minimize the sticking of DNA to the walls. The DNA templates

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were not subjected to any DNA shearing, as per the typical modern DNA library

preparation protocols, as ancient DNA is already fragmented.

Firstly, blunt-end repair was performed to remove or fill the overhanging 5’- and 3’-

ends. These actions are completed by T4 DNA polymerase while the T4 polynucleotide

kinase is attaching the 5’-phosphates. In this step, 1 x Buffer Tango (ThermoFisher

Scientific), dNTPs (100 µM each), 1 mM adenosine 5’-triphosphate (ATP)

(ThermoFisher Scientific), 0.5 U/µL T4 polynucleotide kinase (ThermoFisher Scientific)

and 0.1U/µL T4 DNA polymersae (ThermoFisher Scientific) and 25 µL DNA template

were combined together to make up 50 µL reaction. Next, the mix solution was

incubated at 25ºC for 15 minutes followed by 12ºC at 5 minutes in a thermal cycler.

Subsequently, the solution was purified following the standard MinElute PCR

purification kit (Qiagen) protocols and eluted in 20 µL volume.

Secondly, the two adapters, P5 and P7 were attached to the ends of the blunt-end

repaired DNA templates through the actions of T4 DNA ligase. The reaction mix with a

total volume of 50 µL comprises 1 x DNA ligase buffer (ThermoFisher Scientific), 5%

polyethylene glycol 4000 (PEG-4000) (ThermoFisher Scientific) and 0.125 U/µL T4

DNA ligase (ThermoFisher Scientific) was prepared and combined together with 20 µL

purified and blunt-end repaired DNA template from the previous step. This solution was

incubated at 22ºC for 30 minutes. Similarly to the previous step, after this incubation the

solution was purified using the MinElute PCR purification kit (Qiagen) and eluted to

obtain 20 µL final volume.

Next, nicks produced from the previous step were filled-in with Bst polymerase in an

adapter fill-in reaction. This reaction was prepared by mixing 1 X ThermoPol reaction

buffer (New England Biolabs), dNTPs (250 µM each) and 0.3 U/µL Bst polymerase,

large fragment (New England Biolabs) which was then combined together with the 20

µL eluate from the previous step to make up a 40 µL reaction. There was no purification

step necessary in this stage as the Bst polymerase is inactivated by heating to 80°C. Prior

to the next step, the indexing PCR, the number of molecules in the DNA library has to

be quantified in order to calculate the PCR cycle number needed to obtain a sufficient

amount of the DNA library. The samples were quantified by quantitative PCR (qPCR)

against standards with known concentration. The qPCR mix which was prepared in a 96

well plates consists 1 x LightCycler® 480 SYBR Green I Master (Roche Life Science),

200 nM of each primer which are complementary to the universal adapter sequence: IS7

primer 5’–ACACTCTTTCCCTACACGAC-3’ and IS8 primer 5’-

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GTGACTGGAGTTCAGACGTGT-3’ (Meyer & Kircher 2010). DNA sample of

volume 1 µL was then added to the mix to give a 20 µL reaction volume. The reactions

were run in a LightCycler® 480 Instrument II (Roche Life Science) with cycles at: 95°C

for 10 minutes, followed by 45 cycles of 95°C for 15 seconds, 59°C for 25 seconds and

72°C for 35 seconds. In addition, the amount of DNA was also measured in the original

DNA sample with a Qubit® fluorometer (ThermoFisher Scientific) following the

dsDNA High Sensitivity Assay (ThermoFisher Scientific) protocol. Determination of the

optimal PCR cycle number was then carried out as described by Meyer and Kircher

(2010).

Finally, the P7 and P5 adapters with indexes embedded were attached at both ends of the

library by PCR amplification. The whole library volume was used as the template in 7 x

25 µL reactions consisting of 1 x KAPA HiFi HotStart Uracil + ReadyMix (Roche Life

Science), 200 nM of each P5 and P7 indexing primers. The amplification was performed

in a thermal cycler with initial denaturation for 4 minutes at 95°C, followed by the

optimum cycle number (determined in the previous step) of denaturation at 98°C for 20

seconds, annealing at 63°C for 30 seconds, and elongation or extension at 72°C for 30

seconds; lastly, final extension was performed at 72°C for 1 minute. The amplified

library was purified following the MinElute PCR purification kit (Qiagen) standard

protocols to give a final elution volume of 25 µL. The next step will depend on the NGS

starategy that is to be performed to the DNA library: shotgun sequencing or target

capture. For shotgun sequencing, there are no further steps needed before pooling except

for quality control and quantification before sending for sequencing.

2.6.2 Target enrichment: in-solution target hybridization capture

This study used the in-solution DNA capture strategy for whole genome target

enrichment. The baits targeting the whole genome of M. tuberculosis and M. leprae were

designed in house in Brown’s lab group. These baits were supplied as part of the

myBaits® custom target kit from Arbor Biosciences (formerly MYcroarray®). They

were designed based on the whole genome sequence of the M. tuberculosis ancestor

genome and the M. leprae TN genome (Cole et al. 2001; Comas et al. 2013) . The baits

are 80 bp in length and have 2X tiling density, which means each base of the genome is

covered twice by different baits.

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The target capture protocols were performed in the modern laboratory as the indexed

libraries used as template have already been PCR amplified. The steps were performed

following the standard myBaits® in-solution sequence capture protocols. The indexed

DNA libraries were used as templates with the total of 25 µL volume reduced to 7 µL

using the Eppendorf® centrifugal vacuum concentrator. In the first step, which is the

hybridization step, the DNA library templates are denatured into single strands, followed

by addition of adapter blockers, which allows the baits to hybridize to their

complementary targets. This was performed by preparing the hybridization mix and the

blockers mix into two separate Eppendorf LoBind 0.5 mL tubes. The hybridization

contained HYB#1, HYB#2, HYB#3, HYB#4, RNase block and the baits in 18.5 µL final

volume. Meanwhile, the blockers mix comprising BLOCK#1, BLOCK#2, BLOCK#3

and the 7 µL sequencing library were combined together in a separate 0.5 ml tube. The

tube containing the blockers mix was incubated in the thermal cycler at 95°C for 5

minutes to allow DNA library denaturation and the adapter blocking actions. Next, both

tubes containing the blockers mix and hybridization mix were incubated at the

hybridization temperature (60-65°C) for 5 minutes. After the 5 minutes, the

hybridization mix was then transferred to the blockers mix and the incubation resumed

for 36 hours to allow the baits to hybridize to the sequencing templates. The samples

described in Chapter 5 were hybridized at 65°C while the samples described in Chapter

4 were hybridized at 60°C.

After the 36 hours incubation, it is expected that the baits bound to the complementary

sequencing libraries will form bait-target hybrids. In the hybrid bind step, the solution

mix from the previous step will be combined with streptavidin-coated magnetic beads,

Dynabeads® MyOne™ Streptavidin C1 (ThermoFisher Scientific), which will bind to

the bait-target hybrids. The hybrids that are bound to the magnetic beads are pelleted in a

magnetic particle collector (MPC) while the non-hybrids (exogenous DNA) will remain

in the solution and will be removed in the washing steps. In this step, beads were first

washed three times with Binding Buffer which had been allowed to equilibrate to room

temperature prior to use. The washed beads were suspended in 70 µL Binding Buffer

before the capture reaction was transferred to it in the water bath. The capture reaction-

beads mix was incubated at the hybridization temperature for 30 minutes with occasional

tube agitation. Next the beads (which are now bound to the bait-target hybrids) were

pelleted in the MPC, the supernatant (which contains non-target DNA) was removed and

the beads were washed with Wash Buffer 2.2 that had already been incubated at the

hybridization temperature for at least 45 minutes before use. This step was repeated

78

three times before the beads were eventually eluted in 30 µL EB buffer. The post-

capture DNA libraries were amplified using the beads suspension solution as template.

A 35 µL PCR mix comprising 1 X KAPA HotStart ReadyMix (Roche) and 500 nM of

each IS5 and IS6 primer was added to the 15 uL post-capture template forming a 50 µL

post-capture PCR reaction. Two tubes for each sample were included in the

amplification. In the thermal cycler, the templates were pre-denatured at 98°C for 2

minutes followed by 8-14 cycles of denaturation at 98°C for 20 seconds, annealing at

60°C for 30 seconds and elongation at 72°C for 30 seconds. Lastly, the final elongation

was carried out at 72°C for 5 minutes. The amplified post-capture PCR products of the

same sample from the two tubes were combined together. The beads were pelleted in the

MPC and the supernatant was collected for purification with MinElute PCR purification

kit (Qiagen) following the standard protocols. The final elution volume in EB buffer

(Qiagen) was 20 µL. The protocols are repeated when performing double capture to

increase the yield even further, although caution should be taken as there may be some

loss of sequence targets during the procedures. The samples described in Chapter 4 were

subjected to double capture while the samples in Chapter 5 had only a single

hybridization capture performed.

2.6.3 Quality control and quantification of sequencing libraries

Quality control was performed after the indexing PCR (Section 2.6.1) for shotgun

sequencing or after the hybridization capture (2.6.2) for a target enriched library. The

NGS was performed using both the Illumina HiSeq 2500 and Illumina HiSeq 4000

sequencing techonology depending on the instrument availability at the Genomic

Technologies Core Facility (GTCF), at the University of Manchester. Adapter dimers

may affect the cluster efficiency and the subsequent reads obtained (Kircher et al. 2011).

Therefore, it is important to monitor the presence of adapter dimers in the sequencing

libraries. The presence of these adapter dimers was assayed using the Bioanalyzer 2100

(Agilent Technologies) instrument. The DNA High Sensitivity kit (Agilent

Technologies) allows the inspection of the fragment size distribution in the sequencing

DNA library. In case of a DNA library with high content of adapter dimers, the adapter

dimers were removed following the SPRIselect (Beckman Coulter) standard protocols.

The SPRI-based chemistry allows the selection of longer fragments while getting rid of

shorter ones (Figure 2.3). The sequencing library volume was adjusted to 50 µL. A 1.2x

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ratio to template (60 µL) of SPRIselect (Beckman Coulter) was then added to the

sequencing library. The SPRI beads were pelleted in the MPC where the clear

supernatant (containing smaller fragments) was discarded. The pellets were washed with

180 µL of 85% ethanol, and the 85% ethanol then removed and the pellet allowed to dry.

The pellet was eluted in 20-25 µL EB buffer, placed in the MPC and the supernatant

kept as it contain the desired sequencing libraries.

Figure 2.3: The relationship between the SPRI beads-to-template ratios to fragment size

selection. The 1.2X SPRI beads-to-template ratio was used to filter out the adapter dimers from

the sequencing library in this study (figure taken from Beckman Coulter 2012).

The libraries from multiple samples were pooled together in an equimolar ratio before

being sent for sequencing. For this purpose, the sequencing libraries were quantified

with the qPCR based KAPA library quantification kit Illumina® platforms (Roche). Pre-

diluted DNA standards with 452 bp length, flanked by P5 and P7 primers (similar to the

primers in the Illumina flow cell) with concentrations from 20 pM to 2x10-4 pM were

used to generate a standard curve. The concentration of the DNA library was calculated

by plotting against the standard curve using absolute quantification methods. A dilution

series was prepared for the sequencing library and used as the template in a qPCR. The

reactions were prepared in a 96 well plate with each well containing a 20 µL reaction

comprising 1X LightCycler® 480 SYBR Green I Master (Roche Life Science), 200 nM

of each primer – IS5 and IS6, and 4 µL of diluted library template. At least duplicates

were prepared for both sample and standard reactions. The qPCR was performed in the

LightCycler® 480 Instrument II (Roche Life Science). The cycle conditions were: initial

80

denaturation for 5 minutes at 95°C; 35 x amplification cycles with denaturation at 95°C

for 15 seconds, annealing at 60°C for 25 seconds, and extension at 72°C for 35 seconds;

followed by melt curve analysis at 95°C for 5 seconds, 55°C for 1 minute, increasing to

97°C with 7 acquisition per °C. In the analysis, the absolute quantification method was

used to generate a standard curve from the DNA standards. The standard curve was

verified to have a ∆Cq value between 3.1 to 3.6, a reaction efficiency range of 90% to

110% ,and a R2 value ≥0.99. A standard curve with one criterion lying outside of the

range will require repeating as the library conecntration calculation will be doubted. In

the concentration calculation, the standard curve is used to convert the concentration of

diluted library to pM. Next, the average size-adjusted concentration was calculated for

each library dilution, and the concentration converted to nM. The average library

fragment length used in this calculation is obtained from the results of the Bioanalyzer

analsysis. Based on the concentration value (in nM) obtained for each library, pooled

sequencing reactions were prepared in final volume of 20 µL to be sent for NGS at he

Genomic Technologies Core Facility (GTCF) of the University of Manchester. The

samples described in Chapter 4, for shotgun sequencing, were run in an Illumina HiSeq

2500 with paired end sequencing at 100 bp length. The samples described in Chapter 4

for target capture sequencing and the samples described in Chapter 5 were run using the

Illumina HiSeq 4000 platform with paired end sequencing with 75 bp length on each

pair. The sequencing facility performed all the sequencing protocols and the raw data

were received in the form of demultiplexed fasta sequence files.

2.7 Bioinformatics analysis

The bioinformatics analysis was performed in a Linux-based operating system based on

Debian, Ubuntu 16.04. The starting raw data from the sequencer were obtained as

demultiplexed FASTQ files. The analysis flows that were performed are depicted in

Figure 2.4. Each sample was processed in a different pathway based on the outcome of

downstream analysis. The paired-end sequencing produced read 1 and read 2, one from

each end. These two reads can be aligned together, and depending on the length, they

can be merged or collapsed together forming a single collapsed read (Lindgreen 2012).

This allows better alignment to the reference sequence, improving the entire data set.

FASTQ file format has four lines with the first line containing the sequencer information

and sequence identifier, the second line showing the nucleotide sequence which could be

81

either A, C, T, G or N, the third line usually a plus (+) sign which acts as a separator,

and the fourth or the last line is the quality scores of each base (Cock et al. 2010). The

quality score is encoded in Phred +33 format. The quality score is an estimation of the

probability that the base called in that position is incorrect.

Figure 2.4: The bioinformatics analysis flows performed on different samples. Purple:

analysis performed on all samples. Green: analysis performed on samples described in Chapter

4. Pink: analysis performed on samples described in Chapter 5.

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2.7.1 Merging of paired reads and removal of adapter sequences

The FASTQ data still contain the adapter sequences which will interfere with

downstream analysis such as mapping. Therefore, removing these is a crucial first step

in the data analysis. This was performed using the AdapterRemoval v2 program

(Schubert et al. 2016). This program not only trims the adapter sequences but it also

allows the merging or collapsing of two overlapping paired reads.

Figure 2.5: Three outcome from paired-end data from Illumina sequencing by

AdapterRemoval v2. (A) Pair 1 and pair 2 read mates are longer than 75 or 100 bp (depending

on the sequencer used) therefore do not overlap with each other, (B) Read sequence mates

overlap at minimum 5 bp will be collapsed forming a single sequence, (C) Read mates are both

overlap with each other and to the adapter sequence. Adapted from (Lindgreen 2012).

Paired-end sequencing reads a DNA fragment from both ends. The lengths of the reads

produced are 100 or 75 bp depending on the sequencer used. In the case of longer target

fragments, the read mates do not overlap with each other, and therefore are kept in

separate pair1 and pair2 FASTQ files (Figure 2.5-A). Read sequence mates that overlap

at 5 or more bases will be merged together forming a single collapsed sequence (Figure

2.5-B). The mismatch rate that is allowed within the overlapping region is 1/3; if this

83

rate is exceeded, the read mates will not be merged into a single collapsed read. In

Figure 2.5-A and B, there is no adapter contamination. In Figure 2.5:C, as the sequence

is very short, the read mates not only overlap with each other, they also overlap with the

adapter sequence causing adapter contamination. The two reads will be merged into one

collapsed read, and the adapter sequence contamination will be removed. However, if

the resulting collapsed sequence is less than 25 bp length it was removed. The stretches

of Ns and low quality bases from the 5’ and 3’ termini were trimmed (Schubert et al.

2016).

2.7.2 Mapping to reference genome

In the M. tuberculosis study, the M. tuberculosis ancestor genome (Comas et al. 2013)

was used as the reference, while in the M. leprae study the reads were mapped against

the M. leprae TN genome (Cole et al. 2001) sequence. The mapping was performed

using the Burrows-Wheeler Aligner 0.7.12 (bwa) programme (Li & Durbin 2009).

Firstly, the reference genome was indexed. Pairs 1 and 2 from the uncollapsed reads

were mapped separately to the reference genome, unlike the collapsed reads. The

resulting file is in Sequence Alignment/Mapping (SAM) format (Li et al. 2009). This

format stores read mapping information in respect to the reference genome. BWA-ALN

algorithm was used in the alignment with disabled seeding and maximum edit distance

of 0.1. Subsequently, BWA sampe and BWA samse was performed to generate the SAM

file from paired reads and collapsed/merged reads, respectively.

2.7.3 Cleaning and sorting reads (PicardTools)

PicardTools (http://broadinstitute.github.io/picard) CleanSam option was performed for

soft clipping. After that, the coordinates of the reads in respect to the reference genome

were added using SortSam of PicardTools. The mapped reads were extracted into a new

separate file using Samtools with the SAMtools view option. Read duplicates were

removed using the PicardTools MarkDuplicates option. After this step, the subsequent

analysis that was performed depended on the result obtained. If the number of reads

obtained is sufficient for genotyping analysis (Chapter 5), the programs used are

depicted in pink as shown in Figure 2.4 (will be described in section 2.7.5). Otherwise,

the analysis will be similar to what is depicted in green, as the metagenomics contents

identification will be performed instead (will be described in section 2.7.4).

http://broadinstitute.github.io/picard

84

2.7.4 Metagenomic content analysis

In the metagenome content analysis, only the collapsed reads were used in the analysis.

BEDTools (Quinlan & Hall 2010) was used for file conversion from BAM to Fastq files.

FASTQ files were converted to FASTA files using the Seqtk programme

(https://github.com/lh3/seqtk). Once the file has been converted to FASTA file, it was

then run in Basic Local Alignment Search Tools (BLAST) to identify the possible

identity of each read against the NCBI database. The BLAST output was then visualized

in MEtaGenome Analyzer 5 (MEGAN 5) (Huson et al. 2007) to identify the taxonomic

profile of each sample. In MEGAN 5, the identification of a sample’s taxonomical

content is estimated based on the lowest common ancestor (LCA) concept. In this

concept, if multiple taxa are found in the BLAST search for one read, the lowest shared

ancestor will be assigned as the taxon identity for this read. The LCA parameters were

set to min score: 0; max expected: 1.0e-7; top percent: 0; min support percent: 0; min

support: 1; LCA percent: 100. This is the last step in the analysis for the samples studied

in Chapter 4. For the analysis performed in Chapter 5, the subsequent steps will be

described in section 2.7.5.

2.7.5 Sequence variant analysis

To study the sequence variants in each sample, the BAM file containing reads mapped to

the reference genome is converted to a FASTA file and the sequence identity determined

by BLAST. Once the possible identity of each read is identified in BLAST, the resulting

file was visualized in MEGAN to view the taxonomic content. Using an in house perl

script, a FASTA file which only contains the reads assigned to M. leprae in MEGAN

was extracted from the original mapped read BAM file. The in house script was also

used to prepare the FASTQ file for subsequent analysis with the Genome Analysis

Toolkit (GATK) 3.6 (McKenna et al. 2010). Base Quality Score Recalibration (BQSR)

was performed in GATK 3.6 before the recalibrated BAM file was visualized in

Geneious® 8.1 (Kearse et al. 2012) for polymorphism analysis. Unique polymorphisms

in the microbial isolates were confirmed if the read has at least 5-fold depth in that

position and variant frequency of at least 80%.

85

Chapter 3: Study of M. tuberculosis aDNA in

archaeological remains from Yorkshire, England.

Part I: MTBC aDNA screening by polymerase chain reaction.

3.1 Introduction

Chapter 3 and Chapter 4 focus on the biomolecular study done on 60 archaeological

skeletal remains originating from 16 different locations in Yorkshire, England. The aim

is to determine whether the success rate in MTBC aDNA detection is high enough to

make it worthwhile to plan a larger project to test hypotheses such as possible strain

differences in urban and rural areas. Chapter 3 describes the preliminary study

undertaken to screen for the presence of MTBC aDNA in each of the bone samples

using PCR assay and Sanger sequencing. Based on the PCR assay results, the samples

deemed positive for MTBC aDNA preservation were subjected to NGS – which is the

focus in Chapter 4.

York – the location of origin for 32 of the samples – was a thriving city during the

Roman era. It was founded by the Roman Ninth Legion (Legio IX Hispana) in ca. 71 AD

and they remained there until the 4th century AD (Ottaway 2004). After the Romans had

left, the regional context of York was left blank until 627 AD (Palliser 2014). Not much

is known about this city for three centuries, from around 400 to 700 AD. Although the

city was not completely abandoned, its urbanization had definitely shrunken by the fifth

century AD. In the late sixth century AD, immigrants who were coming across the North

Sea, known as the Angles or English, occupied York districts and this period is also

known as the Anglo-Saxon period. Fast forwards to 866 AD, the town was captured by

the Vikings who decided to remain and settle there; the name of the town was later

changed to Jórvík (Addyman 1980). Jórvík became the capital of a new Viking kingdom

in 870s to 980s AD, resulting in the growth of York into a bigger town than it was

previously (Palliser 2014). During the ‘Viking period’, Jórvík was more heavily

populated following the development of a large commercial zone located between the

two important rivers in the town and the fortress (Palliser 2014). The Normans

conquered York in the 11th century AD and it was made the northern operations base by

William the Conqueror (Bartlett 2000). York was a thriving port and successful

manufacturer during the mediaeval period and was well-connected to Europe. This

86

attracted many other craftsmen to live in York. In addition, hospitals were run by the

church during the mediaeval period in York.

However, the arrival of the Black Death in 1349 AD caused a drastic decline in the

population of York (Nuttgens 2007). Despite the plagues which struck this town several

more times, York remained as one of the most important towns in the northern region of

England until the 16th century AD. York ceased to be the most important town in the 17th

century AD due to competition from neighbouring places (Sheahan & Whellan 1855;

Sellers 1987). Nevertheless, York retained its importance especially in the middle 18th

century AD (Sheahan and Whellan 1855). The industrial revolution resulted in the

booming of other towns in Yorkshire. During the beginning of the 19th century, York

remained as a market town and main distributing hub for its rural hinterlands

(Armstrong 1974). It was not until towards the middle 19th century that the population in

York grew rapidly again when it became the centre of railway transportation. The

housing condition was overcrowded, especially after the arrival of Irish immigrants who

escaped the potato famine (MacRaild 1999). The living conditions are imagined to be

overcrowded, unsanitary and dirty. The population continued to grow rapidly but the

living conditions were better in the 20th century AD due to clearing efforts done by the

York council (Rawnsley & Singleton 1995).

Based on the above history, York did undergo rapid urbanization in the past.

Urbanization has been suspected to assist the spread of tuberculosis or even to promote

the evolution to more aggressive MTBC strains (Comas & Gagneux 2011). The

inclusion of both urban and rural skeletal remains provides an opportunity to attempt

sequence comparisons between the two origins of MTBC isolates.

87

3.2 Results

The summary of the PCR results is depicted in Table 3.1. The positive and negative

detections given in the table refer to the agarose gel observations. The presence of a

band of similar or near-exact to the expected length is marked positive. For the samples

without any bands or unspecific amplification, they are marked as negative. All the

bands with sizes similar or near-exact to the expected length were cloned and Sanger

sequenced. The resulting sequences were compared to the M. tuberculosis H37Rv

reference sequence. The sequence that matches the reference sequence is deemed

positive and vice versa for the sequence that did not match the reference sequence. This

result is indicated in the bracket next to the positive/negative mark for the agarose gel

band result (Table 3.1).

Fifteen samples from 9 different locations produced a band with size similar or near to

the expected band size. All samples from York Minster, Fishergate House, 3 Driffield

Terrace, 6 Driffield Terrace, St Peter Huddersfield and Ailcy Hill produced negative

PCR amplification for all four PCR targets. The results for the suspected PCR positive

samples are further described below and the Sanger sequencing result is summarised in

Table 3.2.

88

Sample

origin

Sample

number

IS6110 gyrA Rv0083 Pks 15/1

123bp 92 bp

Undiluted

DNA

1:10

diluted

DNA

Undiluted

DNA

1:10

diluted

DNA

Undiluted

DNA

1:10

diluted

DNA

Undiluted

DNA

1:10

diluted

DNA

Undiluted

DNA

1:10

diluted

DNA

York Minster 15 - - - - - - - - - -

1 - - - - - - - - - -

Fishergate

House

147 - - - - - - - - - -

98 - - - - - - - - - -

86 - - - - - - - - - -

149 - - - - - - - - - -

108 - - - - - - - - - -

135 - - - - - - - - - -

St Andrew

Fishergate

6 -a/+(+)b +(+)a/+(+)b +(+)a/+(+)b +(+)a/+(+)b -a/-b -a/+(-)b -a/-b -a/-b -a/-b -a/+(+)b

253 - - - - - - - - -

131 - - - - - - - - - -

277 - - - - - - - +(-) - -

89

34 - - - - - - - - - -

323 - - - - - - - - - -

296 - - - - - - - - - -

384 - - - - - - - - - -

339 - - - - - +(-) - - - -

286 - - - - - - - - - -

St Helen on

the Walls

5494 - - - - - - - - - -

6003 - - - - +(-) n.d. - - - -

5000 - - - - - - - - - -

5844 - - - - - - - - - -

East

Heslington

229 - +(-) - - - - - - - -

3 Driffield

Terrace

15 - - - - - - - - - -

37 - - - - - - - - - -

13 - - - - - - - - - -

54 - - - - - - - - - -

6 Driffield 19 - - - - - - - - - -

90

Terrace 22 - - - - - - - - - -

St Peter

Huddersfield

5 - - - - - - - - - -

17 - - - - - - - - - -

7 - - - - - - - - - -

Wetwang

Slack

1 - - - - - - - - - -

2 - - - - - +(-) - - - -

3 - - - - - - - - - -

6 - - - - - - - - - -

4 - - - - - - - - - -

5 - - - - - - - - - -

7 +(-) - - - - - - - - -

8 - - - - - - - - - -

9 - - - - - - - - - -

185 - - - - - - - - - -

360 - - - - - - - - - -

415 - - - - - - - - - -

91

Sewerby 44 - - - - - - - - - -

34 +(n.d.) +(n.d) - - - - - - - -

St Giles by

Brompton

Bridge

1288 - - - - - - - - - -

1531 - - - - - - - - - -

1542 - +(-) - - - - - - - -

Ailcy Hill 1043 - - - - - - - - - -

1044 - - - - - - - - - -

Wharram

Percy

26 - - - - +(-) - - - - -

1600 - - - - +(-) - - - - -

Addingham 103 - - - - - +(-) - - - -

134 - +(-) - - - - - - - -

223 - +(-) - - - - - - - -

Melton 4297 - - - - - - - - - -

5319 - - - - +(-) - - - - -

2554 - - - - - - - - - -

Hickleton 46 - - - - +(-) - - - - -

92

Table 3.1: Result summary for all PCR assays tested on all samples, using original DNA extract and 10-fold diluted DNA.

+ PCR band similar or close to the size of the expected PCR product length observed in gel electrophoresis (single band or multiple bands)

- No band produced, or the size of the produced band/bands is not similar to the length of the expected PCR product

n.d. Not done, (+) Sanger sequence identity matched the M. tuberculosis H37Rv reference sequence

(-) Sanger sequence identity did not match the M. tuberculosis H37Rv reference sequence

(a) First extraction; (b) second extraction - only for those samples with two extractions performed

93

Sample PCR assay Fragment length (bp) Number of mismatches to the reference genome

(bp)

Possible sequence identity by BLAST Pairwise identity E-value

St Andrew Fishergate 6

IS6110 123 bp 123 0-1 n.d. n.d. n.d.

IS6110 92 bp 92 0 n.d. n.d. n.d.

gyrA 104 6 Mycobacterium peregrium partial gyrA sequence

98.40% 1.33 e-21

Pks 15/1 91 3-4 M. tuberculosis and M. bovis 92.20% 5.76 e-11


Rv0083 109 n.a. Nocardioides sp. JS614 80.00% 1.31 e-4


gyrA 104 6 Partial gyrA gene from an uncultured bacterium: ancient DNA from St Peter's

Collegiate Church 28-a,b isolate

96.90% 1.62 e-20

St Helen on the walls 6003

gyA 104 8-10 Mycobacterium vaccae 95.30% 8.61 e-19

East Heslington 229

IS6110 123 bp 123 16 Unidentified partial IS6110-like insertion sequence; isolate IS6110-like sequence type

B

100.00% 3.9 e-23

Wetwang Slack 2 gyrA 104 11 Uncultured bacterium partial gyrA gene of St Shchekavitsa 8-a-e ancient isolates

90.60% 4.3 e-15

Wetwang Slack 7 IS6110 123 bp 118 14 (and 5 bp gaps) Unidentified partial IS6110-like insertion sequence; isolate IS6110-like sequence type

B

91.50% 4.60 e-23

94

Wharram Percy 26

gyrA 104 7 Mycobacterium chelonae 98.40% 1.33 e-21

Wharram Percy 1600

gyrA 104 9 Mycobacterium chelonae 95.30% 6.90 e-19

Addingham 134 IS6110 123 bp 123 16 Unidentified partial IS6110-like insertion sequence; isolate IS6110-like sequence type

B

98.80% 6.85 e-31

Addingham 223 IS6110 123 bp 123 16 Unidentified partial IS6110-like insertion sequence; isolate IS6110-like sequence type

B

98.80% 3.68 e-31

Addingham 103 gyrA 104 6 Mycobacterium peregrinum 98.40% 1.35 e-21

Melton 5319 gyrA 104 8 and 12 Variant 1 and 2: Mycobacterium chelonae Variant 1: 96.9%, Variant 2: 90.9%

Variant 1: 1.62 e-20 , Variant 2: 4.36 e-15

Hickleton 46 gyrA 104 8 Mycobacterium chelonae 96.90% 1.62 e-20

St Giles by Brompton Bridge

1542

IS6110 123 bp 134 49 Streptomyces lunaelactis 97.80% 2.72 e-35

Table 3.2: Sanger sequence result summary for 15 samples with a positive band in at least one of the PCR assays.

n.d. Not done. BLAST search was not performed as the product sequence completely matches the reference genome.

n.a. Not aligned. The sequence cannot be aligned to the reference genome in Geneious due a large number of mismatches.

95

3.2.1 St Andrew Fishergate 6

This sample produced a positive PCR amplification in the second nested step of the

IS6110 assay when the original undiluted DNA template was used (Figure 3.1-a).

Positive amplification was achieved in both the first and nested step of IS6110 where

the 10-fold diluted DNA was used as template (Figure 3.1-a). In this extraction, the

other three single-copy target PCR assays produced negative amplification (not shown).

A second DNA extraction was performed; positive amplification was observed in the

first and nested step of the IS6110 assay in both instances where undiluted and 10-fold

diluted DNA were used as templates (Figure 3.1-b). Positive amplification was

obtained from 10-fold diluted DNA in the gyrA PCR assay but not from the undiluted

DNA (Figure 3.1-b). A very faint band was shown in the agarose gel from the 10-fold

diluted DNA amplification for the Pks 15/1 PCR assay, and similar to the gyrA assay,

no band was produced when the undiluted DNA was used as template (Figure 3.1-b).

The Sanger sequences of the cloned IS6110 PCR product when aligned to the M.

tuberculosis H37Rv reference genome revealed a complete match in 5 clone sequences,

and one mismatch each at inconsistent positions in 4 clones for the first extraction. On

the other hand, all IS6110 nested PCR sequences show a complete match to the

reference genome (Figure 3.2-a). For the second St Andrew Fishergate 6 extraction, all

clone sequences for both the IS6110 123 bp and nested PCRs show a complete match

to the reference genome with no mismatch observed (Figure 3.2-b). The sequence

identities are also supported by BLAST analysis. The 3 clone sequences from the gyrA

PCR assay of the second DNA extraction revealed 6 mismatches from the 64 bp

sequence (after trimming of primers) in consistent positions for all the clones (Figure

3.3-a). BLAST search revealed the highest sequence similarity to Mycobacterium

peregrium partial gyrA sequence (Table 3.2). Meanwhile, the clone sequences from

Pks 15/1 PCR amplification of St Andrew Fishergate 6 second extraction contained

three consistent mismatches in all clones, and another one shared mismatch in 2 clones

(Figure 3.3-b). Based on the BLAST search result, the highest sequence match was

shown against M. tuberculosis and M. bovis (Table 3.2).

96

M A B C D

100 bp

200 bp

IS6110 - 123 bp IS6110 - 92 bp

M A B C D E F G H

200 bp

100 bp

IS6110 - 123 bp IS6110 - 92 bp gyrA Pks 15/1

Figure 3.1: Gel electrophoresis results for the sample St Andrew Fishergate 6 showing

positive bands for three markers. (a) DNA extraction 1. A and C: undiluted DNA as

template; B and D: 10-fold diluted DNA as template. (b) DNA extraction 2. A, C, E and G:

undiluted DNA as template, B, D, F and H: 10-fold diluted DNA as template. In both 1 and 2,

M: DNA ladder.

(a)

(b)

97

Figure 3.2: The alignment of St Andrew Fishergate 6 Sanger clone sequences of IS6110 123 bp and nested 92 bp PCR product against M. tuberculosis

H37Rv reference sequence. (a) St Andrew Fishergate 6 DNA extraction 1, (b) St Andrew Fishergate 6 DNA extraction 2. Primer sequences are omitted from

the alignment. Mismatches are highlighted in blue.

(a)

(b)

98

Figure 3.3: The alignment of St Andrew Fishergate House 6 Sanger clone sequences of gyrA and Pks 15/1 PCR product against M. tuberculosis H37Rv

reference sequence. (a) gyrA and (b) Pks 15/1 DNA extraction 2. Primer sequences are omitted from the alignment. Mismatches are highlighted in blue

(a)

(b)

99


Skeleton St Andrew Fishergate House 277 produced multiple bands in the Rv0083

assay, one with a length close to the expected 110 bp PCR product from this assay

(Figure S3.1). The faint lower band was cut from the agarose gel, purified and cloned

into competent E. coli cells. The clone Sanger sequences show a PCR product of 109

bp, shorter than the expected fragment length (not shown). The alignment to the

reference M. tuberculosis H37Rv sequence shows only 74.2% pairwise identity.

BLAST search revealed that Nocardioides sp. JS614 as the closest match to the clone

sequences. However, the e-value for this match is only 1.31e-4 (Table 3.2).


St Andrew Fishergate produced a positive band in the gyrA PCR assay, while showing

negative amplifications in the other PCR assays. The positive band was produced from

the amplification of the 10-fold diluted DNA template. It was faint (Figure S3.2) but

had an apparent length close to 104 bp. However, the sequence length spanned by both

forward and reverse primers had 6 mismatches with the reference sequence (Figure

3.4). The possible identity of the amplified sequence based on BLAST analysis is the

partial gyrA gene from an uncultured bacterium: ancient DNA from St Peter’s

Collegiate Church 28-a,b isolate (Müller et al. 2016).

Figure 3.4: The alignment of St Andrew Fishergate House 339 clone sequence of gyrA

PCR product against the reference M. tuberculosis H37Rv sequence. Primer sequences are

omitted from the alignment. Mismatches are highlighted in blue.

100

M A

200 bp

100 bp

3.2.4 St Helen on the walls 6003

Figure 3.5: gyrA PCR amplification for sample St Helen on the Walls 6003. A: undiluted

DNA template. M is the DNA ladder with the 100 bp and 200 bp marked in the figure. Faint

lower band is shown inside the red box.

St Helen on the Walls produced double bands in the gyrA assay when undiluted DNA

was tested, one of which with had a size close to the expected gyrA PCR product

(Figure 3.5). The 10-1 DNA dilution was not tested for this particular assay for this

sample. This sample tested negative for the other PCR assays. Clone sequences

revealed a 104 bp PCR product, which matched the expected product length of the

gyrA target. However, the sequence did not correspond to the reference M. tuberculosis

sequence. There are 8 consistent mismatches throughout all 9 clones, and one mismatch

that is present in 6 clones (Figure 3.6). Two clones show one mismatch each, in

different positions. BLAST search shows a closest match to Mycobacterium vaccae

(Table 3.2).

101

Figure 3.6: The alignment of St Helen on the Walls 6003 clone sequences from the gyrA PCR assay to the M. tuberculosis H37Rv reference sequence.

The reference sequence is shown at the top, while the mismatches are highlighted in blue. Primer sequences are omitted from the alignment and BLAST search.

Figure 3.7: The alignment of East Heslington 229 clone sequences from the IS6110 123 bp PCR assay to the M. tuberculosis H37Rv reference sequence.

The reference sequence is shown at the top, while the mismatches are highlighted in blue. Primer sequences are omitted from the alignment and BLAST search.

102

3.2.5 East Heslington 229

Skeleton East Heslington 229 produced multiple bands in the first step of the IS6110

PCR assay. The lowest band as marked in Figure S3.3 shows a faint possible positive

amplification. However, the subsequent IS6110 nested 92 bp PCR assay did not

produce positive amplification. The lowest band from the first step PCR assay was

excised from the gel, cloned and Sanger sequenced. Clone sequences revealed a

product with 123 bp length, however the sequence did not match the reference M.

tuberculosis H37Rv. There are 16 mismatches within the region spanned between the

forward and reverse primers, consistently found across all clones (Figure 3.7). The

closest match of this sequence is to the unidentified partial IS6110-like insertion

sequence; isolate IS6110-like sequence type B, which is reported in Müller et al.

(2015).

3.2.6 Wetwang Slack 2

The Wetwang Slack 2 skeleton produced multiple bands for the gyrA PCR

amplification, in which the length of the lower band can be approximated to 104 bp

(Figure S3.4). The other PCR assays tested for this sample produced negative

amplification – absence of band or bands with differing length to the expected product

size. The amplicon produced by the Wetwang Slack 2 sample is 104 bp as confirmed

by the clone Sanger sequences. However, the sequence does not correspond to the

reference. There are 11 mismatches to the reference within the 64 bp sequence – after

the primers are removed (Figure 3.8). Based on the BLAST search result, the closest

sequence match is to the uncultured bacterium partial gyrA gene of St Shchekavitsa 8-

a-e ancient isolates which was reported by Müller and colleagues (2015).

103

Figure 3.8: The alignment of Wetwang Slack 2 clone sequences from the gyrA PCR assay against the M. tuberculosis H37Rv reference sequence.

Disagreements to the reference sequence are highlighted in blue. Forward and reverse primer sequences are omitted from this figure as well as in the BLAST

search.

Figure 3.9: The alignment of Wetwang Slack 7 clone sequences from the IS6110 123 bp PCR assay against the M. tuberculosis H37Rv reference

sequence. Disagreements to the reference sequence are highlighted in blue while the gaps are shown in red. Forward and reverse primers are omitted from the

alignment and for the BLAST search.

104

3.2.7 Wetwang Slack 7

The undiluted DNA of the sample Wetwang Slack 7 produced a band with a size that

matches the expected 123 bp product with undiluted DNA as the template (Figure

S3.5). The subsequent nested PCR did not produce positive amplification. The clone

Sanger sequence however confirmed that the amplicon size is 118 bp, 5 bp shorter than

the expected product (Figure 3.9). The closest identity match of this sequence is to the

unidentified partial IS6110-like insertion sequence, isolate IS6110-like sequence type B

(Müller et al. 2015). Wetwang Slack 7 produced negative amplification for the IS6110

nested 92 bp PCR assay and the other 3 targets.

3.2.8 Wharram Percy 26 and Wharram Percy 1600

Both sample Wharram Percy 26 and Wharram Percy 1600 showed positive

amplification for the gyrA target (Figure S3.6) while showing negative amplification

for the other three targets. The positive amplification was obtained from the undiluted

DNA as template. The clone Sanger sequences revealed a 104 bp amplicon from both

samples, similar to the expected product length. However, the nucleotide sequences do

not correspond to the reference sequence. Wharram Percy 26 clone sequences show 7

mismatches to the reference sequence (Figure 3.10). The possible sequence identity

determined by BLAST is matched to Mycobacterium chelonae. The Wharram Percy

1600 clone sequence contain 9 mismatches against the reference sequence (Figure

3.11). Similar to Wharram Percy 26, the best BLAST match was assigned to M.

chelonae.

105

Figure 3.10: The alignment of Wharram Percy 26 clone sequences from the gyrA PCR assay against the M. tuberculosis H37Rv reference sequence. The

disagreements to the reference sequence are highlighted in blue. The forward and reverse primer sequences were trimmed from the alignment and were not

included in the BLAST search query.

Figure 3.11: The alignment of Wharram Percy 1600 clone sequences from the gyrA PCR assay against the M. tuberculosis H37Rv reference sequence.

The disagreements to the reference sequence are highlighted in blue. The forward and reverse primer sequences were trimmed from the alignment and were not

included in the BLAST search query.

106

3.2.9 Addingham 134 and Addingham 223

Both of samples Addingham 134 and Addingham 223 gave positive amplification in

the IS6110 first step, 123 bp PCR assay using the 10-fold diluted DNA as template

(Figure S3.7). The samples amplified multiple bands, with one of the bands showing a

length close to the expected amplicon size. These samples, however, produced negative

amplification in the subsequent nested IS6110 PCR assay and in PCR of the other 3

targets. Sanger sequences of product clones verified the amplicon size of 123 bp from

both samples, matching the expected fragment size. However, the nucleotide sequences

did not match the M. tuberculosis H37Rv reference. Both Addingham 134 and

Addingham 223 show 16 mismatches within the 83 bp amplicon (primer sequences

omitted) (Figure 3.12). BLAST search suggested the unidentified partial IS6110-like

insertion sequence, isolate IS6110-like sequence type B as the possible identity of the

amplicons from both samples.

3.2.10 Addingham 103

The sample Addingham 103 showed positive amplification in the gyrA PCR assay

using the 10-1 diluted DNA as template (Figure S3.8). This sample produced negative

amplification for the other targets. Sanger sequences from clones confirmed the

presence of a 104 bp amplicon which matches the expected product length. The

nucleotide sequences, however, do not correspond to the M. tuberculosis H37Rv

reference as there are 6 mismatches within the region spanned between the forward and

reverse primers (Figure 3.13). BLAST search revealed Mycobacterium peregrinum as

the possible sequence identity with 98.4% pairwise identity and e-value of 1.35e-21.

107

(a)

(b)

Figure 3.12: The alignment of Addingham 134 and Addingham 223 clone sequences from the IS6110 first step, 123 bp PCR assay against the M.

tuberculosis H37Rv reference sequence. (a) Addingham 134, (b) Addingham 223. The disagreements to the reference sequence are highlighted in blue.

Forward and reverse primer sequences are omitted from this figure as well as in the BLAST search.

108

Figure 3.13: The alignment of Addingham 103 clone sequences from the gyrA PCR assay against the M. tuberculosis H37Rv reference sequence. The

disagreements to the reference sequence are highlighted in blue. Forward and reverse sequence are omitted from this figure as well as in the BLAST search.

Figure 3.14: The alignment of Melton 5319 clone sequences from the gyrA PCR assay against the M. tuberculosis H37Rv reference sequence. The


109

3.2.11 Melton 5319

The amplification of the Melton 5319 undiluted DNA sample produced a faint band in

the agarose gel with length that matches the expected amplicon length (Figure S3.9).

The presence of a 104 bp product is confirmed by the clone Sanger sequences. Two

sequence variants are produced: one with 8 mismatches and one with 12 mismatches

against the reference sequence (Figure 3.14). Both do not correspond to M.

tuberculosis. The most possible identity for both sequence variants is Mycobacterium

chelonae as determined by BLAST search. The first sequence variant (with 8

mismatches) has 96.9% pairwise identity with 1.62e-20 e-value, while the second

sequence variant (with 12 mismatches) has 90.9% pairwise identity with 4.36e-15 e-

value.

3.2.12 Hickleton 46

Positive amplification of the gyrA target was produced from undiluted DNA of the

Hickleton 46 sample (Figure S3.10). A faint band at the expected position can be

observed after the amplification of the 10-1 diluted DNA of this sample. No positive

amplification was obtained from the other PCR assays. Sanger sequencing from clones

revealed the presence of a 104 bp amplicon, matching the expected PCR product

length. The nucleotide sequences, however, do not correspond to the M. tuberculosis

H37Rv reference as there are 8 mismatches within the region spanned between the

forward and reverse primers (Figure 3.15). The BLAST search suggests M. chelonae as

the most possible identity of the sequence rather than M. tuberculosis. This claim is

supported by 96.9% pairwise identity and 1.62e-20 e-value: the probability that the

matches occurred by chance.

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Figure 3.15: The alignment of Hickleton 46 clone sequences from the gyrA PCR assay against the M. tuberculosis H37Rv reference sequence. The


111

IS6110

123 bp

IS6110

Nested 92 bp

M A B C D

200 bp

100 bp

3.2.13 St Giles by Brompton Bridge 1542

The sample St Giles by Brompton Bridge produced multiple bands in the IS6110 123 bp

PCR assay; one of the bands produced from the 10-1 DNA dilution template had a band

length close to the expected size (Figure S3.11). Sanger sequences revealed the amplicon

size to be 134 bp, which is 11 bp larger than the expected PCR product. In the alignment

against the M. tuberculosis H37Rv sequence, 49 disagreements were found, including

gaps (not shown). The closest sequence match in a BLAST search was Streptomyces

lunaelactis (Table 3.2). This bacterium has previously been isolated from moonmilk

speleothem from a cave (Maciejewska et al. 2015).

3.2.14 Sewerby 34

Figure 3.16: IS6110 123 bp and nested 92 bp PCR amplification of sample Sewerby 34. A

and C: undiluted DNA template, B and D: 10-1 diluted DNA template. M is showing the DNA

ladder with 100 bp and 200 bp bands indicated in the figure.

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Positive amplification seemed to be produced from both the undiluted and 10-1 diluted

DNA template of Sewerby 34 for the IS6110 123 bp assay (Figure 3.16). However, the

sequence identity cannot be verified as the product could not be cloned. The cloning was

not pursued further as the nested PCR did not produce any positive amplification;

therefore, it is unlikely that the identity is MTBC.

3.3 Discussion

3.3.1 MTBC positive samples

In this study, a sample is considered MTBC-positive if positive amplification supported

by a Sanger sequence that matches the M. tuberculosis reference is obtained in at least

one of the assays. Exception is made for the small number of mismatches that can be

accounted for as miscoding lesions in the aDNA targets (Müller et al. 2014a). From the

60 archaeological remains studied, only seven of them produced positive amplification

in the first step of the IS6110 PCR assay: St Andrew Fishergate 6, East Heslington 229,

Wetwang Slack 7, Addingham 134, Addingham 223, St Giles by Brompton Bridge 1542

and Sewerby 34. In the subsequent nested PCR of this target, only St Andrew Fishergate

6 produced positive amplification, with a match to M. tuberculosis identity supported by

Sanger sequencing. The other six samples gave products that did not match the reference

sequence, albeit the product length was similar to the expected amplicon length with the

exception of Wetwang Slack 7 and St Giles by Brompton Bridge 1542. These other six

samples also produced negative amplification in the nested PCR, which can be attributed

to the dissimilarity of the sequence produced from the first IS6110 PCR step.

The results of the MTBC preservation screening therefore suggested that only one of the

60 samples contain MTBC aDNA: St Andrew Fishergate 6. The positive band from both

steps of the IS6110 PCR assay was confirmed as MTBC through Sanger sequencing.

There was one nucleotide discrepancy in each of the three clones for the 123 bp product

which is likely to be a result of miscoding lesions which are common in ancient DNA

templates (Brown & Brown 2011; Dabney, Meyer & Pääbo 2013). These mismatches

were only present in three of the clones and occurred at inconsistent positions. In

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addition, these mismatches did not appear in the clone sequences derived from the

nested PCR amplicon. Therefore, the nucleotide discrepancies are very unlikely to be

true polymorphisms. This is further supported by the additional presence of clone Sanger

sequences for the amplicons from both steps of the IS6110 PCR from the second DNA

extraction which completely matched the reference sequence without any presence of

polymorphisms. The 7 bp deletion in the Pks15/1 region was also detected in this

sample. The absence of these 7 nucleotides is associated with the Euro-American lineage

of M. tuberculosis and has also been found in other ancient isolates (Bouwman et al.

2012). Three mismatches appeared in each of the clone sequences, which again can be

attributed to miscoding lesions (Müller et al. 2014a). Interestingly all the mismatches are

C → T substitutions which is a hallmark attribute of an ancient miscoding lesion.

Hydrolytic deamination will result in nucleotide modification, resulting in errors when

read by DNA polymerase during DNA replication (Dabney, Meyer, Pääbo 2013).

Cytosine is the primary target of such modification: deamination, which will form uracil

that will further incorporate adenine during the DNA duplication. This will cause either

a C → T or G → A substitution depending on which strand of the DNA is being

amplified (Dabney, Meyer, Pääbo 2013). In the gyrA PCR of St Andrew Fishergate 6,

however, despite the length of PCR product matching that of the expected amplicon, the

sequence did not agree with the M. tuberculosis reference. Instead, the most likely

identity as determined by BLAST analysis is to M. peregrinum. This sequence could

therefore have originated from a contaminant. M. peregrinum is a member of the

Mycobacterium fortuitum complex; one of the members of the rapidly growing non-

tuberculous mycobacteria. The M. fortuitum complex have previously been isolated from

the environment such as soil and water-related sources (Nagao et al. 2009).

3.3.2 Contamination

Three samples produced ambiguous results in the first round of amplification directed at

the insertion sequence IS6110. These samples produced near-exact length amplicons,

which is an indication of MTBC presence: the samples are East Heslington 229,

Addingham 134 and Addingham 223. However, all the samples failed to produce

positive amplification in the subsequent nested PCR round. Sanger sequences from all

three samples are similar to the MTBC reference sequence, but with 16 mismatches; the

positions of these mismatches consistent within the clones from each individual sample.

https://www.sciencedirect.com/topics/immunology-and-microbiology/mycobacterium-fortuitum

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It is tempting to associate the similarity to cross-contamination between these samples.

However, firstly, except for Addingham 134 and Addingham 223, East Heslington 229

was processed in a different DNA extraction and PCR screening batch. Therefore, it is

unlikely that cross-contamination occurred in samples that were handled at different

times. In addition, all three samples produced multiple bands in the gel electrophoresis,

but the numbers and sizes of the unspecific bands were inconsistent across all 3 samples.

The closest match for these three sequences, according to the BLAST results, is the

unidentified partial IS6110-like insertion sequence, sequence type B, which was reported

by Müller et al. (2015). It can be argued that the sequence might have arisen from

contamination as the samples described by the study mentioned were processed in the

same facility. However, the sequence match is not 100% identical to the previously

reported sequence type B. All three samples show one mismatch relative to the sequence

type B, with the mismatch for Addingham 134 and Addingham 223 located in the same

position, but not in the similar position for sample East Heslington 229. It is possible

that the sequence is a product of a contaminant present in the burial environments, which

would explain the sequence similarity for the samples collected from Addingham but not

from East Heslington (Yang & Watt 2005).

The IS6110 PCR for samples Wetwang Slack 7 and St Giles by Brompton Bridge 1542

produced amplicons of 118 bp and 134 bp, respectively. The closest match for the

sequence from the Wetwang Slack 7 sample is the unidentified IS6110-like sequence

type B. Other than the 5 bp deletion in Wetwang Slack 7, there is only one mismatch

found compared to the unidentified IS6110-like sequence type B. Meanwhile, the

sequence from the sample St Giles by Brompton Bridge 1542 matched to Streptomyces

lunaelactis. This actinobacterium species was previously isolated from moonmilk

deposit of a cave (Maciejewska et al. 2015). Bacteria from the genus Streptomyces have

been isolated from various environmental sources worldwide, where they dominate soil

populations; 106 to 109 Streptomyces cells can be isolated from a gram of soil (Barka et

al. 2016).

Furthermore, eight samples produced ambiguous results for the gyrA PCR. Similar to

the samples discussed previously, the correct-length amplicons have different sequences

compared to the M. tuberculosis reference. Two of the samples best matched to the

unspecific gyrA sequence obtained from ancient isolates previously reported by Müller

and colleagues (2015). The samples St Andrew Fishergate 339 and Wetwang Slack 2

gave sequences that are similar but not identical to the gyrA amplicon sequence obtained

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from ancient DNA from St Peter’s Collegiate Church 28-a-b and ancient DNA from St

Shchekavitsa 8-a-e, respectively. Although the ancient isolates which both samples were

best matched to were processed in the same facility, the sequences are not identical, with

at least 2 mismatches in each sample. The other six samples (St Helen-on-the-Walls

6003, Wharram Percy 26, Wharram Percy 1600, Addingham 103, Melton 5319 and

Hickleton 46) all produced amplicons with sequence best match to mycobacterium

species. The three species the samples matched to are M. vaccae, M. peregrinum and M.

chelonae. All three mycobacterium species are classified as mycobacterium other than

tuberculosis (MOTT) (Ho et al. 2012; Thomson et al. 2013). M. vaccae is a natural soil

non-pathogenic bacterium (Ho et al. 2012). The contamination of environmental bacteria

is entirely plausible as the skeletons were left in contact with soil during the preservation

years (Wilbur et al. 2009). Meanwhile, M. chelonae and M. peregrinum are both part of

the rapidly growing mycobacteria (RGM) group (Fernández-Roblas et al. 2000). M.

chelonae, although typically found in the environment, in water and soil, is also shown

to be able to cause clinical infection in humans. In fact, in the contemporary era, this

bacterium has been shown as a contaminant on hospital equipment (Shimoide et al.

1995). The clinical manifestation of this bacterium infection include skin and soft tissue

infections and, sometimes, pulmonary diseases and infections in joints, bones and

muscles in immunosuppressed patients (Brown‐Elliott et al. 2001).

The successful amplification in the first step of the IS6110 and gyrA PCR with the

correct amplicon length but in fact non-MTBC DNA sequence demonstrates the

difficulties in screening of M. tuberculosis DNA from archaeological remains. There are

so far 188 identified species with valid names within the Mycobacterium genus; the

majority of these are environment bacteria, typically found in soil and water and only a

small number being pathogenic species (Gupta et al. 2018). The species within this

genus are divided into two groups: slow growing mycobacterium, which take more than

7 days to form colonies, and rapid growing mycobacterium, taking less than 7 days for

colony formation. The environmental mycobacteria are also known as ‘mycobacteria

other than tuberculosis’ (MOTT). One of the contamination sources from M.

tuberculosis study is the MOTT bacteria that are present in the soil environment of the

burials and, for some, might have invaded the skeletal remains (Müller et al. 2016). The

DNA from these MOTT bacteria can be amplified as shown in this study. This is raising

a question on the specificity of the PCR assays used to screen MTBC DNA from

archaeological remains (Wilbur et al. 2009). The PCR assays used to detect the presence

MTBC DNA are considered specific for these species from clinical samples (Eisenach et

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al. 1990). However, considering the complex bacterial content of archaeological

specimens, this might not hold true as demonstrated by a previous study (Müller et al.

2015) and now, in this study. The first round of the IS6110 PCR assay, as well as the

gyrA and Rv0083 PCRs have demonstrated the ability to produce amplicons of the

expected length, however with non-MTBC sequences. In the case of gyrA target, most

of the amplicons obtained in this study are from MOTT. This highlights the importance

of performing sequencing verification of the amplicon as it is clear that these targets are

not solely amplifying MTBC aDNA.

PCR assays were designed to incorporate AmpliTaq Gold and BSA in the reaction mix

as it was shown that AmpliTaq Gold has greater efficiency in PCR while the BSA may

reduce the effect of inhibitors on the amplification (Forbes & Hicks 1996; Abu Al-Soud

& Rådström 2000; Pandey et al. 2012). In addition to the original undiluted DNA, 10-1

diluted DNA also used as a template in the PCR screening. The purpose of testing 10-1

diluted DNA is to further minimize the effect of inhibitors in the amplification efficiency

(Wilson 1997). Two of the main challenges of ancient DNA studies are the low copy of

available endogenous DNA and the presence of PCR inhibitors (Dabney, Meyer &

Pääbo 2013). From the 16 samples with positive bands, only 2 of them show positive or

positive-like amplification from both undiluted and 10-1 diluted DNA templates. In the

undiluted DNA, the amount of endogenous DNA is maximized, but unfortunately so is

the amount of the PCR inhibitors. While in the 10-1 diluted DNA, the effect of the PCR

inhibitors will be reduced but the number of the endogenous DNA molecules will be

reduced as well. This could be the reason why some samples only produced positive or

positive-like amplification with one of the DNA templates.

3.3.3 Failure of MTBC aDNA detection

Based on the osteological studies performed previously, most of the archaeological

skeletons studied here are suggested to be positive for tuberculosis infection (Table 2.1).

However, based on the PCR screening results, using four targets supposedly specific for

MTBC, only one sample, St Andrew Fishergate 6, shows evidence for the presence for

MTBC aDNA. This raises a question on whether these individuals were not infected

with tuberculosis or whether the detection failures were caused by any other factors.

Even the samples which show Pott’s lesion, which is considered to be a pathognomonic

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sign of tuberculosis infection, did not show any evidence for MTBC aDNA. There are

several factors that might contribute to the failure of MTBC aDNA amplification. The

most important determinant is the preservation of the archaeological bone remains. The

skeletons could be in poor preservation state – resulting in low endogenous DNA

amounts (Taylor et al. 1996; Donoghue 2011). The low endogenous DNA amount

combined with the presence of environmental contaminants will contribute further to the

complication of endogenous DNA amplification (Wilbur et al. 2009; Müller et al. 2016).

Environmental organisms may contaminate the skeletal remains throughout the

preservation years (Tsangaras & Greenwood 2012). The presence of abundant

environmental organisms including MOTT may result in positive amplification as

depicted in this study (Wilbur et al. 2009). In addition, the bacterial load of infectious

pathogen at the time of death could also have contributed to the failure of the MTBC

aDNA amplification (Barnes & Thomas 2006). It could be that a high bacterial load is

necessary in order for the pathogen DNA to be retained in the bones throughout the

preservation history. The inability to obtain positive amplification from the samples

cannot therefore dispute the presence of tuberculosis infection in the individuals studied.

Furthermore, the archaeological remains selected in this study comprised of skeletal

bone showing tuberculosis lesions and normal bones without any lesions. Majority of the

non-control specimen studied showing lesions on ribs; others are showing either

vertebrae, hips or endocranial lesions. The generally accepted pathognomonic bone

change of tuberculosis is the destructive lesions observed on the vertebrae, typically on

the lumbar spine or lower thoracic (Roberts 2015). There is an absence or very little

involvement of new bone formations. Other than the spine, the effect can also be seen in

the knee and hips, although other parts of the body can also be affected. The bone

change in ribs is classified as non-specific tuberculosis lesions. Although previous

studies have observed the potential of rib lesions as an indicative for tuberculosis in

archaeological remains, the bone change on this part of the body can also be the result of

any other types of diseases. Therefore, it is also possible that the non-specific lesions

observed on the majority of the bones studied here were caused by other diseases.

Caution must be taken to conclude a diagnosis based on non-specific bone changes

alone. The biomolecular analysis method is incorporated in ancient tuberculosis

diagnosis confirmation for this reason. However, one also should not rely completely on

an ancient DNA study result as the occurrence of false negatives are possible due to the

factors highlighted above. By performing both osteological and biomolecular analysis

together on archaeological remains it might be possible to increase the confidence of the

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palaeodisease diagnosis. It is dangerous to draw a definite conclusion on whether

tuberculosis infection is absence or present based on either type of analysis alone

(Roberts 2015).

3.3.4 Samples for Next Generation Sequencing

Eight samples were selected for NGS. Ideally, the samples to be chosen should be those

with positive MTBC aDNA detection, confirmed by PCR assay and Sanger sequencing.

However, as previously shown, only St Andrew Fishergate 6 gave positive results for the

presence of MTBC aDNA. Therefore, another seven samples were selected from the

‘negative’ samples. The use of ‘negative’ samples is justified because PCR failure can

arise if a sample contains aDNA that is too short to amplify, or where contaminants are

present, and under these circumstances NGS following DNA capture can still be

successful (Templeton et al. 2013).

The main selection criterion for the eight samples used for NGS remained the

comparison between rural and urban sites. In choosing these eight samples, other

considerations were the presence or absence of lesions and, when lesions were present,

the part of the skeleton affected, the choice made to include a range of examples in case

aDNA preservation was affected by any of these factors. Practical considerations such as

the amount of sample material available were also taken into account. However, the

main interest is still to compare MTBC aDNA between samples retrieved from urban

and rural locations.

From the eight samples selected for NGS, four samples are from urban and rural sites

respectively. From the four urban samples, two are from St Andrew Fishergate and the

other two are from St Helen-on-the-Walls. From the first location, a sample with

tuberculosis lesion (St Andrew Fishergate 6, which gave positive PCR results) and a

control bone (St Andrew Fishergate 253) were chosen. Meanwhile, from the second

urban location, St Helen-on-the-Walls 6003 and St Helen-on-the-Walls 5494 were a

bone with tuberculosis lesion and a control bone respectively. St Helen-on-the-Walls

6003 was chosen as the skeletal remains show lesions on the lower thoracic and lumbar

vertebrae which is highly likely to be caused by tuberculosis, albeit these samples tested

negative for MTBC aDNA in the PCR screening.

From the rural samples, one is from Hickleton and the remaining three are from

Wetwang Slack, the latter being a site with relatively large amounts of available sample

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material, so it would be possible to repeat NGS experiments if necessary. The three

samples from Wetwang Slack include rib bones with lesions (Wetwang Slack 8) and

without lesions (Wetwang Slack 7). The third sample that was included from this site is

Wetwang Slack 185, which is a sample from a vertebrae bone. Sample 46 from

Hickleton was chosen as this individual was showing spine lesions and the vertebra was

used for the study. Spinal lesions are generally accepted as the pathognomonic sign of

tuberculosis infection, therefore there is a probability that this individual had indeed

contracted tuberculosis, although the PCR tests showed otherwise. The selection for the

next samples for NGS (if any) would be based on the NGS results of these samples.

More samples would have been chosen if the NGS results (Chapter 4) had been more

promising.

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Chapter 4: Study of M. tuberculosis aDNA in archaeological

remains from Yorkshire, England. Part 2: Next Generation

Sequencing.

4.1 Introduction

In the early ‘age’ of ancient DNA study, the focus was mainly directed towards the

detection of the presence of the organism of interest, which was routinely performed

through PCR (Spigelman & Lemma 1993; Salo et al. 1994; Haas et al. 2000). Before the

advent of the high throughput sequencing technologies, the acquisition of aDNA

sequence was highly challenging owing to its very low endogenous DNA concentration,

degraded and short fragment length (Rizzi et al. 2012). The largest amount of genomic

aDNA sequence generated by the Sanger method was the 26,861 bp sequence from an

extinct Pleistocene cave bear (Noonan et al. 2005). The pioneering of NGS has

accelerated the aDNA field with the first NGS performed on an ancient specimen

producing 13 million bp of DNA sequence from the extinct woolly mammoth;

representing a 480-fold of increase compared with the cave bear genome data reported

by Noonan and colleagues (2005) previously (Poinar et al. 2006). NGS has

revolutionized the study of MTBC ancient DNA as well. Hybridization capture directed

at polymorphic regions of the M. tuberculosis genome in a 19th century English skeleton

managed to identify the genotype as closely associated to MTBC strains that were

thought to be common in North America in the early 20th century, albeit very rare today

(Bouwman et al. 2012). Metagenomics NGS performed from an archaeological tissue

sample from a mummy recovered from Vac, Hungary produced 32x M. tuberculosis

genome coverage which enabled the identification of mixed infection originating from

two different M. tuberculosis genotypes (Chan et al. 2013). Metagenomics study of other

18th century Hungarian archaeological remains also showed infection from different M.

tuberculosis genotypes during this period of time (Kay et al. 2015). From these

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examples, it is shown that metagenomics and hybridization capture can be applied as

NGS strategies in studying ancient MTBC DNA.

Both metagenomics and target enrichment through in-solution capture were used as high

throughput sequencing strategies in this study. Metagenomics or shotgun sequencing

was performed with eight samples as indicated in Chapter 3. The shotgun strategy is

used to allow the identification of all known organisms in the archaeological remains.

The sample St Andrew Fishergate 6 was also subjected to whole M. tuberculosis genome

target enrichment to further increase the reads from M. tuberculosis.

The eight samples subjected to NGS were St Andrew Fishergate 253, St Andrew

Fishergate 6, St Helen-on-the-Walls 5494, St-Helen-on-the-Walls 6003, Hickleton 46,

Wetwang Slack 185, Wetwang Slack 7 and Wetwang Slack 8. The first four samples

mentioned originated from urban locations while the remaining four were excavated

from rural parts of Yorkshire. These are all subjected to shotgun sequencing methods. In

addition to this, the sample St Andrew Fishergate 6, which tested positive for MTBC

aDNA in the PCR screening described in Chapter 3, was also subjected to target

enrichment through in-solution hybridization capture method before sequencing using

NGS. All of these samples were sequenced using the Illumina HiSeq platform.

4.2 Results

4.2.1 Shotgun sequencing

The computational tools and parameters used to analyse the sequence of all samples

were the same to ensure consistency. The sequences were pre-processed using the

programs explained in Section 2.7. In both the shotgun and hybridization studies, only

the collapsed reads were used in the subsequent analyses to ensure consistency across all

samples. The collapsed reads were aligned to the M. tuberculosis ancestor reference

genome (Comas et al. 2014).

The shotgun sequencing yielded 1.2 x 107 to 6.0 x 107 collapsed reads for all samples

except for St Andrew Fishergate 6 and Wetwang Slack 185 (Table 4.1). However, less

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than 1% of the total reads mapped to M. tuberculosis for all samples. Even the sample St

Andrew Fishergate 6, which produced positive PCR screening of MTBC aDNA

(Chapter 3), has only 0.0476% of reads mapped to M. tuberculosis, this being 1,210

reads before duplicate removal and only 60 reads after duplicate removal. The highest

mapped read percentage is Wetwang Slack 185, which had the lowest number of total

collapsed reads. As well as investigating the number of reads mapped to M. tuberculosis,

the metagenome content of the samples was also explored. This was done using the

NCBI Blastn tool to assign each read to its respective taxonomy. In the BLAST search,

the minimum e-value was assigned at 1x10-7 to avoid a match occurring only by chance.

The word size, which is defined by the sensitivity of the search, was set to 20, which

mean that 20 “words” have to match between the query and the database to initiate the

extension to match. The results were then visualized and analysed in MEGAN 5. Due to

computational power limitations, running the 10s of millions of reads in MEGAN, a read

subset was extracted randomly from each file to be used in downstream analysis, except

for St Andrew Fishergate 6 and Wetwang Slack 185 where it was computationally

possible to run all reads. The exact bioinformatics steps to perform these analyses were

explained in detail in section 2.7.

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Archaeological sample Number

of reads

Reads mapped to M. tuberculosis % of reads

mapped to M.

tuberculosis

Before duplicate reads

removals

After duplicate

reads removal

St Andrew Fishergate 253 22,143,918 5,747 2,815 0.0260

St Andrew Fishergate 6 2,541,970 1,210 60 0.0476

St Helen-on-the-Walls 5494 15,385,188 802 149 0.0052

St Helen-on-the-Walls 6003 57,912,949 7,344 4,493 0.0127

Hickleton 46 35,541,718 3,751 1,947 0.0106

Wetwang Slack 185 4,662 9 9 0.1931

Wetwang Slack 7 30,548,281 13,669 4,543 0.0447

Wetwang Slack 8 12,549,272 5,200 2,355 0.0414

Table 4.1: The result summary of the shotgun read mapping against the M. tuberculosis reference genome. The read numbers that passed the

pre-processing quality control, the number of reads mapped to the M. tuberculosis reference genome and their respective percentages are shown in the

table. The number of reads mapped to the M. tuberculosis reference genome before duplicate removal was used to calculate the percentage.

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The taxonomic content of each sample was visualized in MEGAN 5. In MEGAN 5, firstly,

the number of reads corresponding to each superkingdom (i.e. Bacteria, Eukaryota,

Archaea, Viruses) was determined. This was calculated based on the total number of reads

with identifiable taxonomy. Next, the percentage of reads of the organism of interest in the

respective superkingdom was calculated. In Bacteria superkingdom, the percentage of

Mycobacterium genus, the intermediate level MTBC and M. tuberculosis species were

calculated in respect to the amount of the bacterial reads rather than the total read number.

The same analysis was performed for Homo sapiens: the percentage of H. sapiens reads

was calculated based on the overall Eukaryota reads – not the total read number.


Super Kingdom

Number of

reads Percentage

Bacteria 39031 50.47%

Mycobacterium 2852 7.31%

MTBC 94 0.24%

M. tuberculosis 3 0.001%

Archaea 743 0.90%

Viruses 0 0.00%

Eukaryota 37559 48.57%

H. sapiens 2565 6.83%

Table 4.2: The number of reads assigned to each superkingdom, genus and species of interest

by MEGAN for sample St Andrew Fishergate 253. The superkingdom is highlighted in yellow,

genus in blue, species in green while the intermediate level MTBC is highlighted in red.

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A subset of collapsed reads was investigated in BLAST for the identification of the

possible organisms that the reads belonged to. For the extract from skeleton 253 from St

Andrew Fishergate, 48.57% and 50.47% of the assigned reads belonged to the Eukaryota

and Bacteria superkingdoms, respectively (Table 4.2). Mycobacterium genus accounted for

7.31% of the total bacteria content of the extract, with only 0.24% (94 reads) assigned to

MTBC. There were no reads assigned to virus DNA. From the overall eukaryote reads,

6.83% belong to H. sapiens. In the identification of the 20 species dominating the reads

(Figure 4.1), H. sapiens shows the highest number of reads followed by Thermomonospora

curvata. Most of the organisms with the most abundant reads are soil-dwelling bacteria:

Sandaracinus amylolyticus, Sorangium cellulosum, Streptomyces bingchenggenesis,

Kitasatospora setae, Streptomyces cattleya, Streptomyces violaceusniger, Nocardiopsis

dassanovillei and Rhosopseudomonas palustris (Lampky 1971; Ichikawa et al. 2010; Sun

et al. 2010; Mohr et al. 2012; Wang et al. 2013; McMurry & Chang 2017). Interestingly,

the 20th most abundant species is Ramilibacter tataouinensis, a novel desert bacterium

which was isolated from fragments of meteorite submerged in sands of Tunisian desert

showing properties of persistence in desert environments (Strobel et al. 2012).

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Figure 4.1: The 20 species with the highest read number assigned by MEGAN for sample St Andrew Fishergate 253. The number of reads

assigned to each species is shown on the top of the bars in the figure.

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by MEGAN for sample St Andrew Fishergate 6. The superkingdom is highlighted in yellow,


The majority of the reads from skeleton 6 from St Andrew Fishergate originated from

bacteria (91.06%); followed by 8.76% from eukaryotes, 0.17% archaea and no reads from

viruses (Table 4.3). From the overall reads of bacteria, only 0.30% were identified as

belonged to the Mycobacterium genus, and only one read was matched to MTBC. Homo

sapiens accounted for 32.3% of the Eukaryota reads. The most abundant reads in sample

St Andrew Fishergate 6 originated from Streptosporangium roseum , a soil-dwelling

non-pathogenic, non-motile spore-producing bacterium (Nolan et al. 2010). The second

most abundant reads originated from H. sapiens (Figure 4.2). In addition, other than H.

sapiens, sequences from mammals are also present in high proportions in this sample.

These include Macaca fascicularis and Ovis canadensis which are Southeast Asian

monkey and North American bighorn sheep, respectively (Higashino et al. 2012). Most of

the organism with abundant reads in this sample are naturally occurring soil bacteria:

Super

Kingdom

Number of

reads Percentage

Bacteria 390318 91.06%


MTBC 1 0.00%


M. leprae 229 0.06%

Archaea 743 0.17%

Viruses 0 0.00%


H. sapiens 12106 32.23%

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Streptomyces lydicus, Saccharopolyspora erythraea, Streptomyces iranensis, Lysobacter

enzymogen, Conexibacter woesei and Streptomyces vietnamensis (Zhu et al. 2007; Pukall

et al. 2010; de Lima Procópio et al. 2012; Qian et al. 2013). It is worth noting that most of

the species are from the Streptomyces genus, representing the largest genus within the

Actinobacteria class. Streptomyces are typically found in soil and decaying vegetation (de

Lima Procópio et al. 2012). Three of the most abundant species are also found in the

sample from the same site, St Andrew Fishergate 253: T. curvata, N. dassonvillei and

Kutzneria albida.

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Figure 4.2: The 20 species with the highest read number assigned by MEGAN for sample St Andrew Fishergate 6. The number of reads

assigned to each species is shown on top of the bars in the figure.

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St Helen-on-the-Walls 5494

Super

Kingdom

Number of

reads Percentage

Bacteria 42585 76.95%


MTBC 2 0.00%


Archaea 397 0.72%

Viruses 27 0.05%


H. sapiens 3834 31.10%


by MEGAN for sample St Helen-on-the-Walls 5494. The superkingdom is highlighted in yellow,


The reads from the sample St Helen-on-the-Walls 5494 are dominated by bacteria and

eukaryotes with 76.95% and 22.28%, respectively (Table 4.4). From the overall bacterial

population in the sample, only 0.31% of the reads were classified to Mycobacterium. Only

two of the overall reads were identified as belonging to MTBC. Archaea and viruses were

identified in the sample with abundance percentages of 0.72 (397 reads) and 0.05 (27

reads), respectively. No reads were specifically matched to M. tuberculosis. The

taxonomy composition of sample St Helen-on-the-Walls 5494 revealed H. sapiens as the

most abundant reads in the sample (Figure 4.3). A. sulfonivorans and K. flavida are both

bacteria from the Actinobacteria class that naturally occur in soil (Park et al. 1999;

Mongodin et al. 2006). Interestingly, in addition to H. sapiens, two other primates were

also identified to be among the most abundant reads in this sample: M. fascicularis and

Pan troglodytes. M. fascicularis is the species name for monkey, typically found in

Southeast Asia while P. troglodytes is referring to chimpanzee which is

131

Figure 4.3: The 20 species with the highest read number assigned by MEGAN for sample St Helen-on-the-Walls 5494. The number of reads


132

also known as the African apes (Luke & Verma 1995). It is suggested as the closest

existing relatives to humans. Flavobacterium johnsoniae together with Pedobacter

heparinus and Niastella koreensis are common inhabitants of soil environments (Agarwal

et al. 1997; Weon et al. 2006; Han et al. 2009). A few of the species with the most reads

have been identified to be able to cause infection in humans: Pseudomonas stutzeri,

Arcobacter butzleri, Flavobacterium psychrophilum and Sphingobacterium sp. ML3W

(Lalucat et al. 2006; Arguello et al. 2015; Smith et al. 2015; Rochat et al. 2017). P. stutzeri

was shown to be associated to septicemia, bacteremia, bone infection, endocarditis, eye

infection, meningitis, skin infection, ventriculitis, urinary tract infection and pneumonia

(Lalucat et al. 2006). However, this bacterium was identified to be low in virulence and the

small number of deaths reported to be associated with this pathogen is still doubtful. The

20th most abundant read in sample St Helen-on-the-Walls 5494 came from the species

Sphingobacterium sp. ML3W which previously has been isolated from patients who

suffers from chronic respiratory infection (Smith et al. 2015).

133

St Helen-on-the-Walls 6003

Super

Kingdom

Number of

reads Percentage

Bacteria 481912 98.15%


MTBC 0 0.00%


Archaea 4584 0.93%

Viruses 64 0.01%


H. sapiens 720 16.30%


by MEGAN for sample Helen-on-the-Walls 6003. The superkingdom is highlighted in yellow,


The BLAST search result visualized in MEGAN revealed that 98.15% of the successfully

assigned reads belong to the Bacteria superkingdom (Table 4.5). From the overall bacterial

content, 0.93% are assigned to the Mycobacterium genus but none of the reads is

specifically assigned to the MTBC. Archaea and viruses comprise 0.93% and 0.01% of the

reads, respectively. Only 0.90% from the reads are from Eukaryota: 16.3% of these are

from H. sapiens. The most abundant read in the sample belongs to F. johnsoniae, a

bacterium most commonly found in soil and freshwater which also gave abundant reads for

sample St Helen-on-the-Walls 5494 (Figure 4.4). Similar to the three samples described

previously, most of the species with the most abundant reads are naturally found in the

environment, especially soil: K. flavida, Nocardoides sp. JS614, A. sulfonivorans,

Sterptomyces pristinaespiralis, Nocardiodes dokdonensis, N. koreensis, S. amylolyticus, V.

paradoxus, Rhodoplanes sp. Z2-YC6860 and Arthrobacter sp. Strain FB24. Interestingly,

Ramilbacter tataouinensis, which has 1,759 reads assigned, has been previously shown to

have a strong adaptation to a desert lifestyle (de Luca et al. 2011).

134

Figure 4.4: The 20 species with the highest read number assigned by MEGAN for sample St Helen-on-the-Walls 6003. The number of reads


135

Hickleton 46

Super

Kingdom

Number of

reads Percentage

Bacteria 564847 97.04%


MTBC 0 0.00%


Archaea 3621 0.62%

Viruses 2004 0.34%


H. sapiens 3424 29.47%


by MEGAN for sample Hickleton 46. The superkingdom is highlighted in yellow, genus in blue,

species in green while the intermediate level MTBC is highlighted in red.

The identifiable reads from the sample Hickleton 46 comprise of 97.04% bacteria, 2.0%

eukaryotes, 0.62% archaea and 0.34% virus sequences. From the bacteria, 1,254 reads

(0.22%) are assigned to Mycobacterium but none of them were identified as MTBC (Table

4.6). In the taxonomical classification performed by MEGAN, the most abundant reads in

the sample originated from the species Streptomyces albus (Figure 4.5). This organism has

been isolated from a wide range of environmental niches. In addition, this microorganism

was shown to be able to cause mycetoma infection in humans (Martín et al. 2004).

Mycetoma is a progressively destructive chronic inflammatory disease. The foot is the

most commonly affected part, but other regions of the body can be infected as well. More

than half of the 20 most abundant species in the sample belong to the Streptomyces genus.

As previously described, Streptomyces sp. are predominantly found in soil and decaying

vegetation (de Lima Procópio et al. 2012). Another soil-inhabiting bacterium, K. setae is

also abundant; this particular microorganism has similar morphology and lifestyle to the

species within the Streptomyces genus (Ichikawa et al. 2010).

136

Figure 4.5: The 20 species with the highest read number assigned by MEGAN for sample Hickleton 46. The number of reads assigned to each

species is shown on top of the bars in the figure.

137

Wetwang Slack 185


by MEGAN for sample Wetwang Slack 185. The superkingdom is highlighted in yellow, genus

in blue, species in green while the intermediate level MTBC is highlighted in red.

There were very few reads produced from sequencing of the sample Wetwang Slack 185.

The majority (96.77%) of the identified reads were assigned to bacteria (Table 4.7). There

were 10 reads assigned to the Mycobacterium genus accounting for 1.34% of the overall

bacteria read number. However, none of these reads were identified as belonging to MTBC

aDNA. There were no virus sequences identified in the sample. Meanwhile, archaea and

eukaryote reads were identified with 0.52 and 2.52% abundance, respectively. From the

reads identified as belonging to eukaryota, only one read was assigned to H. sapiens.

Similar to sample St Andrew Fishergate 6, the most abundant reads in this sample were

assigned to S. roseum (Figure 4.6). T. bispora is also present abundantly as in sample St

Andrew Fishergate 6. Interestingly, M. leprae was identified as the third most abundant

species in the sample. A number of species are identified as soil-dwelling bacteria:

Kocuria rhizopila and Amycolatopsis orientalis. K. rhizopila was shown to be able to cause

human infections in a few instances, particularly of the bloodstream (Becker et al. 2008;

Moissenet et al. 2012). Another soil-inhabiting bacterium is the Amycolatopsis orientalis.

Six of the most abundant species in the sample belong to the Streptomyces genus – typical

soil-dwelling bacteria. Species belong to the genus Nocardiodes are widespread in aquatic

and terrestrial environments such as soil as wastewater.

Super

Kingdom

Number of

reads Percentage

Bacteria 748 96.77%


MTBC 0 0.00%


Archaea 4 0.52%

Viruses 0 0.00%

Eukaryota 21 2.72%

H. sapiens 1 4.76%

138

Figure 4.6: The 20 species with the highest read number assigned by MEGAN for sample Wetwang Slack 185. The number of reads assigned to

each species is shown on top of the bars in the figure.

139

Wetwang Slack 7

Super

Kingdom

Number of

reads Percentage

Bacteria 763098 99.45%


MTBC 78 0.01%


Archaea 1970 0.26%

Viruses 12 0.00%


H. sapiens 576 26.06%


by MEGAN for sample Wetwang Slack 7. The superkingdom is highlighted in yellow, genus in

blue, species in green while the intermediate level MTBC is highlighted in red.

The majority of the reads obtained from the Wetwang Slack 7 sample originated from

bacteria with 0.29% from the overall population from Mycobacterium (Table 4.8). There

were 78 reads assigned to the MTBC group but only one of them was specifically assigned

to M. tuberculosis. The remaining reads were assigned to archaea (0.26%) and eukaryotes

(0.29%) of which 26.06% of the overall read population was assigned to H. sapiens.

There are also a small number of reads assigned to viruses (12 reads). In the determination

of the abundant species in the sample, S. roseum was shown to exhibit the most reads

(Figure 4.7). Two of the most abundant species are from the Lysobacter genus. Species in

this genus are ubiquitous in water and soil. The other two species, which have not been

described previously, Streptomyces sp. 769 and Catenulispora acidiphila, are soil-dwelling

bacteria.

140

Figure 4.7: The 20 species with the highest read number assigned by MEGAN for sample Wetwang Slack 7. The number of reads assigned to


141

Wetwang Slack 8

Super Kingdom

Number of

reads Percentage

Bacteria 724453 99.36%


MTBC 30 0.00%


Archaea 2375 0.33%

Viruses 38 0.01%


H. sapiens 274 12.24%


by MEGAN for sample Wetwang Slack 8. The superkingdom is highlighted in yellow, genus in

blue, species in green while the intermediate level MTBC is highlighted in red.

The reads from the sample Wetwang Slack 8 mostly originated from bacteria (99.36%), of

which 0.23% was from the Mycobacterium genus, with 30 reads are assigned to MTBC

(Table 4.9). Only one read was assigned to M. tuberculosis. Some of the reads are assigned

to eukaryotes (0.31%), archaea (0.33%) and viruses (0.01%). From the eukaryote reads,

12.24% were assigned to H. sapiens. The most abundant read in sample Wetwang Slack 8

is from S. roseum (Figure 4.8); similar to Wetwang Slack 7, Wetwang Slack 185 and St

Andrew Fishergate 6. Nineteen of the 20 most abundant species in sample Wetwang Slack

8 are also found in the other previous samples. The only unique abundant species in this

sample is the bacterium Micromonospora narathiwatensis, which has been reported to be

found widely in the environment including water, sandstone, soils, mangrove sediments

and root nodules (Thawai et al. 2018).

142

Figure 4.8 The 20 species with the highest read number assigned by MEGAN for sample Wetwang Slack 8. The number of reads assigned to


143

4.2.2 Target hybridization capture

Target enrichment was performed on sample St Andrew Fishergate 6 for both the M.

tuberculosis and M. leprae genomes separately. Target enrichment directed at M. leprae

was performed because 229 reads were assigned to M. leprae in the shotgun sequencing of

this sample. The results of shotgun sequencing and M. tuberculosis and M. leprae target

enrichment are summarized in Table 4.10.

Sequencing

strategy

Total read

number

Reads mapped to reference genome Percentage

Before duplicate

removal

After duplicate

removal

Shotgun sequencing 2,541,970 1,210 60 0.05%

M. tuberculosis

target capture

43,199,554 4,528 1,108 0.01%

M. leprae target

capture

23,600,572 898,728 4,104 3.81%

Table 4.10: Comparison of shotgun and target enrichment NGS results for St Andrew

Fishergate 6.

The percentage of reads mapped to the M. tuberculosis reference genome after shotgun

sequencing was higher than those from the library subjected to M. tuberculosis enrichment.

However, a higher percentage of reads mapped to the M. leprae reference genome than to

M. tuberculosis. None of the three NGS strategies gave sufficient reads to enable data to be

obtained on the genotypes of the M. tuberculosis and M. leprae bacteria in the sample.

144

4.3 Discussion

4.3.1 Efficiency of shotgun sequencing in isolating endogenous DNA

The maximum percentage of endogenous (M. tuberculosis) DNA recovered from any

sample was 0.19%, from Wetwang Slack 185. However, this figure could be affected by

bias as this sample produced very few reads, reflecting the low concentration of Wetwang

Slack 185 DNA that was added to the pool that acted as the template for library

preparation (Table 4.11). Both St Andrew Fishergate 6 and Wetwang 185 exhibit the

lowest initial DNA library concentration. During the pooling of the 8 samples into a single

sequencing library, the other 6 samples were diluted so that they can be pooled in an

equimolar ratio. However, based on the electropherogram result (Figure 4.9), a high

proportion of adapter dimers is present in Wetwang Slack 185 DNA library – as indicated

by the fluorescence peak at the 109 bp position. Although all samples were pooled in an

equimolar ratio, most of the reads produced from this sample could be from the adapter

dimers contamination, which explains the very small number of reads that were obtained.

Sample DNA library concentration (nM)

St Andrew Fishergate 6 25.29

St Andrew Fishergate 253 665.15

St Helen-on-the-Walls 5494 166.29

St Helen-on-the-Walls 6003 556.31

Hickleton 46 468.75

Wetwang Slack 185 89.36



Table 4.11: The DNA library concentrations for the 8 samples subjected to shotgun NGS.

These concentration values were used to pool the samples into a single NGS library in an

equimolar ratio. St Andrew Fishergate 6 and Wetwang Slack 185 have the lowest concentration

among all samples.

145

Figure 4.9: The electropherogram showing the DNA library size distribution of the sample

Wetwang Slack 185. The fluorescence signal (FU) shown on the y-axis, is plotted against the

DNA library size indicated on the x-axis. The detection of the fluorescence signal is dependent on

the number of sequences with the respective sizes present in the sample.

The second-highest percentage of endogenous content is from St Andrew Fishergate 6,

Wetwang Slack 7 and Wetwang Slack 8, each with approximately 0.04% of endogenous

DNA. The very low endogenous DNA recovery could be due to several factors. The first

problem could be the presence of environmental DNA contaminants, which may

outcompete the endogenous DNA (Noonan et al. 2005; Der Sarkissian et al. 2014; Llamas

et al. 2016). In shotgun sequencing, the entire DNA that is present in the sample will be

sequenced. Some of the microorganisms in the burial soil might not have been successfully

removed during the pre-extraction protocols and their DNA will be included in the

sequencing library. The soil microorganism DNA might be in a better condition compared

to the endogenous aDNA and will probably be more abundant in the sample (Green et al.

2008; Knapp & Hofreiter 2010). As shown by the taxonomy determination using MEGAN,

the bacteria DNA content is at least 91% in all six samples: St Andrew Fishergate 6, St

Helen-on-the-Walls 6003, Hickleton 46, Wetwang Slack 185, Wetwang Slack 7 and

Wetwang Slack 8. Sample St Andrew Fishergate 253 has an almost equal content of

146

bacteria and eukaryote reads and this is reflected in the species determinations with H.

sapiens being the most abundant species in the sample. Similarly, with St Helen-on-the-

Walls 5494 where again there is a relatively low proportion of bacterial reads in the

sample, H. sapiens is identified as the most abundant species. However, in each sample,

the majority of the reads are from environmental bacteria. All the samples studied here

were recovered from grave burials and therefore have had long years of contact with soil.

Therefore, shotgun sequencing might not be the best strategy to obtain endogenous aDNA

from archaeological specimens which have been buried in this way (Der Sarkissian et al.

2014). Shotgun sequencing is probably much more suited for much better preserved

archaeological remains (Gilbert et al. 2007).

4.3.2 Taxonomical content of the archaeological samples

The collapsed read datasets from shotgun sequencing were examined by BLAST and

MEGAN in order to assign reads to species. The resulting taxonomies for six of the

samples contained at least 1400 species, the exceptions being St Andrew Fishergate 6 (293

species) and Wetwang Slack 185 (77 species). The number of species identified in the

other samples was 2,365 for St Andrew Fishergate 253; 1,467 species for St Helen-on-the-

Walls 5494; 2,631 species for St Helen-on-the-Walls 6003; 2,181 species for Hickleton 46;

1,916 species for Wetwang Slack 7 and 1,820 species for Wetwang Slack 8.

The taxonomies contained several species that are not expected to have come into contact

with the skeletons, such as mammals including monkeys and bighorn sheep, as well as

some bacteria from specialised environments such as desert soil. Some of these anomalies

are due to the absence from the NCBI database, which is searched by BLAST, of many

species, especially bacteria species that have not been studied yet (Santamaria et al. 2012;

Breitwieser et al. 2019). In these cases, the read is assigned to its closest match in the

database, which will be a species related to the one from which the read was obtained,

though possibly a species that lives in a different environment (Porter & Beiko 2013). This

means that some of the species that are identified are incorrect, but these incorrect

identifications should be consistent, so identification of the same set of species in two

147

skeletons suggests that the taxonomic contents of those two skeletons are similar.

Comparisons between skeletons could therefore show differences in the preservation

conditions, for example, whether this is different in urban and rural areas.

Due to the high number of species in each taxonomy, only the 20 most abundant species in

each sample were studied and compared between each sample. All the species that are

shared by at least two samples are depicted in Table 4.12. There is no specific pattern

observed between urban and non-urban regions. However, there are 6 species that were

present abundantly in urban but not non-urban samples which are Sorangium cellulosum,

Sandaracinus amylolyticus, Rhodoplanes sp. Z2-YC6860, Ramlibacter tataouinensis,

Conexibacter woesei and Macaca fascisularis. S. cellulosum, S. amylolyticus,

Rhodoplanes sp. Z2-YC6860 and C. woesei are all found in soils (Lampky 1971; Pukall et

al. 2010; Mohr et al. 2012; Rosa et al. 2018). R. tataouinensis was isolated from meteorite

buried in Tunisia desert sand and adapted to this lifestyle, and so this identification is

presumably, in fact, an unidentified related bacterium present in soil. The reads identified

as Macaca are probably degraded human DNA reads, which contain miscoding lesions

resulting in misidentification. There were also five species that were found in both of the

St Helen-on-the-Walls samples, these are Flavobacteria johnsoniae, Kribela flavida,

Arthrobacter sulfonivorans, Variovorax paradoxus and Arthrobacter sp. strain FB24. All

of these are common soil bacteria.

Meanwhile for the samples from non-urban regions, Streptomyces sp. S10, Streptomyces

avermitilis, Streptomyces venezuelae, Streptomyces laurentii, and Streptomyces sp. Mg1

are the unique abundant organisms which are present only in Hickleton and Wetwang

Slack sample. The Streptomyces genus contains many soil-dwelling bacteria and these

identifications are not unusual. These taxonomies show that there are some similarities

between samples from the same site and some similarities among urban and rural samples

(Table 4.12). However, because the total number of reads is low for all samples, it is not

possible to compare the different taxonomies with endogenous DNA preservation and it is

unknown if the environmental bacteria affect the preservation of ancient DNA in a sample.

148

Sample/shared species St Andrew Fishergate253


St Helen-on-the-

Walls 5494

St Helen-on-the-Walls

6003

Hickleton 46

Wetwang Slack 185

Wetwang Slack 7

Wetwang Slack 8

Thermonospora curvata yes yes yes yes yes

Kutzneria albida yes yes yes

Nocardiopsis dassonvillei yes yes yes yes

Flavobacteria Johnsoniae yes yes

Kribela flavida yes yes

Nitrospora moscoviensis yes yes yes yes yes

Arthrobacter sulfonivorans yes yes

Steroidobacter denitrificans yes yes yes yes yes yes

Variovorax paradoxus yes yes

Arthrobacter sp. Strain FB24 yes yes

Sorangium cellulosum yes yes

Streptomyces cattleya yes yes

Candidatus Nitrospira defluvii yes yes yes yes

Homo sapiens yes yes yes yes yes

Streptomyces sp. S10 yes yes

Kitasatospora setae yes yes yes yes

Streptomyces fulvissmus yes yes

Streptomyces avermitilis yes yes

Streptomyces venezuelae yes yes

Streptomyces laurentii yes yes

Streptomyces sp. Mg1 yes yes

Streptosporangium roseum yes yes yes yes

Thermobispora bispora yes yes yes yes

Kribella flavida yes yes

149

Nocardioides dokdonensis yes yes

Streptoalloteichus hindustanus yes yes yes yes

Streptomyces violaceusniger yes yes

Streptomyces bingchenggenesis

yes yes yes yes

Actinosynnema mirum yes yes yes

Kibdelosporangium sp MJ126-NF4

yes yes

Saccharothrix espanaensis yes yes yes

Niastella Koreensis yes yes yes

Frankia sp. Eul1c yes yes

Saccharopolyspora erythraea yes yes

Frankia sp. EAN1pec yes yes

Sandaracinus amylolyticus yes yes

Rhodoplanes sp. Z2-YC6860 yes yes

Nocardiopsis dassonvillei yes yes yes

Ramlibacter tataouinensis yes yes

Frankia sp. Eul1c yes yes

Conexibacter woesei yes yes

Macaca Fascicularis yes yes

Niastella koreensis yes yes

Number of species unique to sample

2 5 8 3 8 10 5 1

Table 4.12: Comparison of the 20 most abundant species in each sample as determined by BLAST and MEGAN analysis of the reads

obtained by shotgun sequencing. Yes: species is present abundantly in the sample, yellow: species is present abundantly in at least one skeleton in

all locations (urban and rural), blue: the abundant species is only present in the urban locations, pink: the abundant species is only present in the rural

locations, green: the presence of the abundant species is specific to a single location.

150

Pathogenic bacteria are present abundantly in two samples: St Helen-on-the-Walls 5494

and Wetwang Slack 185. The A. butzleri, a pathogenic bacterium species is abundantly

found in skeleton 5494 from St Helen-on-the-Walls. This microorganism has been

recognized as an emerging pathogen where it was associated with a persistent watery

diarrhoea case in a patient with chronic lymphocytic leukaemia (Arguello et al. 2015).

Two infectious bacteria species were identified in Wetwang Slack 185 sample. M. leprae

is the causative agent of leprosy, while K. rhizophila has been previously inflicted to a

persistent bloodstream infection and it was recognized as an emerging “micrococcus”

(Becker et al. 2008; Moissenet et al. 2012). The death of individuals St Helen on the

Walls 5494 and Wetwang Slack 185 could possibly be associated to these pathogens.

However, care should be taken in deriving such a conclusion. First, the manifestation

and nature of preservation of these pathogens in bone remains are not known. The

identities of these pathogens are not confirmed – the results may be a detection of

similar (but not yet identified) environmental bacteria. Secondly, the M. leprae and K.

rhizophila species account for only 6 and 4 reads in sample Wetwang Slack 185,

respectively. This is due to the low read number obtained from this sample as described

in section 4.4.1. This is not sufficient to draw a conclusion about the cause of death of

individual 185 from Wetwang Slack.

The most abundant read in sample Hickleton 46 is from the species S. album which was

shown to able to cause mycetoma infection in humans (Martin et al. 2004). Interestingly,

mycetoma or also previously known as Madura foot is an alternative diagnosis for

leprosy in skeletons (Hershkovitz et al. 1993). It is possible that the individuals St

Helen-on-the-Walls 5494, Wetwang Slack 185 and Hickleton 46 could have contracted

infections from the pathogens found in the samples but survived. However, the data

presented here are not sufficient to draw such a conclusion.

4.3.3 Target enrichment sequencing strategy

In sample St Andrew Fishergate House 6, the percentage of endogenous DNA recovered

after target enrichment did not differ that much in comparison to the shotgun sequencing

result. It was suggested that the success of target enrichment, especially in-solution

hybridization capture, is vastly dependent on the amount of endogenous DNA in the

original sample; an endogenous DNA amount of at least 1% in the overall DNA content

will be more likely to yield successful results after target enrichment (Cruz-Dávalos et

151

al. 2018). In addition, low clonality and low complexity of starting samples are

important factors in determining the success of target enrichment – especially for

archaeological specimens.

4.3.4 Possible mixed infection in sample St Andrew Fishergate House 6

The skeleton 6 from St Andrew Fishergate showed positive amplifications, verified by

Sanger sequencing as being M. tuberculosis, for at least two of the MTBC PCRs in each

of two DNA extraction batches. From the PCR result, it can be inferred that this sample

does contain MTBC aDNA. However, the result from the shotgun sequencing did not

show many reads mapped to the M. tuberculosis reference genome. The taxonomical

content determination of this sample showed that more reads were assigned to M. leprae

compared to M. tuberculosis. PCR was performed to screen for the presence on M.

leprae aDNA in the sample, but no amplification was shown. Separate target capture

was attempted for both M. tuberculosis and M. leprae, giving enriched libraries that

produced 1,108 and 4,104 reads that mapped to M. tuberculosis and M. leprae,

respectively, with a higher endogenous percentage for M. leprae. This suggests a

possible mixed infection in St Andrew Fishergate 6. Co-infection of M. tuberculosis and

M. leprosy has been demonstrated by Donoghue and colleagues (2005). The mixed-

infection was shown in bone remains from 1st century AD Israel, 4th century AD

(Roman) Egypt, 10th century AD Hungary and mediaeval (10-13th century AD) Sweden

(Donoghue et al. 2005). These cases are older than skeleton 6 from St Andrew

Fishergate (early 14th century AD). The latter is around the time where the prevalence of

leprosy peaked in Britain before it disappeared from this region. However, the number

of reads obtained was not enough to provide sufficient coverage to give any genotype

information for either Mycobacterium.

4.3.5 MTBC aDNA detection in bone remains from Yorkshire

The objective of the study performed in Chapter 3 and Chapter 4 was to determine if the

frequency of MTBC aDNA detection is high enough to plan for a much larger project to

test the hypothesis that there were strain differences between urban and rural areas.

Testing this hypothesis would require a much larger sample size and higher frequency of

positive results than was achieved in this thesis.

152

In the PCR screening, only one of the 60 samples produced a positive result of MTBC.

Other samples produced non-specific amplification, even though some of these skeletons

showed destructive lesions on the vertebrae – a specific bone change indicative of

tuberculosis. Eight samples were sequenced in order to compare the metagenomic

content and to see if there is any MTBC aDNA that can be detected by the NGS.

However, the NGS results showed an extremely low number of MTBC reads, even in

the PCR positive sample: St Andrew Fishergate 6. The frequency of the MTBC aDNA

detection is not high enough to enable endogenous sequence comparison between

different samples. The target capture is expected to increase the number of endogenous

read output from the samples. However, this is not the case in this study. Perhaps this is

due to extremely low copies of endogenous DNA in the sample to begin with. To study

broader hypotheses a much larger sample size would be required in order to obtain a

high enough aDNA detection frequency to allow different strains of MTBC to be

detected and compared. In addition, much better-preserved specimens might be

considered for such studies.

The study described in Chapters 3 and 4 highlight the difficulties in detecting and

isolating MTBC aDNA due to environmental contaminants. In addition, the study also

demonstrates the non-specific results of PCR assays that are supposedly specific to

MTBC alone. Caution should be taken in confirming the presence of tuberculosis

infection based on the skeletal lesions alone, especially the non-specific lesions.

Similarly, caution has to be taken when making disease identification based on positive

PCR results without sequencing authentication.

153

Chapter 5: Genotyping of Mycobacterium leprae ancient DNA

from mediaeval England

5.1 Background of study

This chapter focuses on a genotyping study of M. leprae isolates, which were

responsible for the leprosy endemic in mediaeval England. Leprosy was endemic in

Britain during the mediaeval period and the peak infection occurred in the 13th century

AD (Mendum et al. 2014). In the 15th century AD, human leprosy started to decline

before disappearing in the 16th century AD, although leprosy has recently been detected

in British red squirrels (Avanzi et al. 2016). The same timeline is reflected in Europe,

except for some regions where there is still some leprosy cases reported (Ramos et al.

2016). The absence of contemporary cases in Britain makes it difficult to know which

strains and genotypes were present in this region. Moreover, M. leprae is an extremely

host-dependent pathogen that cannot be cultured in normal culture medium, which

makes leprosy study even more difficult (Groathouse et al. 2006). Therefore, the ability

to study aDNA from archaeological remains provides an opportunity to access genomic

information of past M. leprae strains, especially where there is a zero modern human

leprosy cases as such in Britain.

Here, whole genome target enrichment was used as the NGS strategy, as it was shown to

substantially increase the proportion of M. leprae endogenous DNA in a sequencing

library in previous studies (Bos et al. 2014; Schuenemann et al. 2018). The three English

samples from Chichester and Raunds were tested positive for M. leprae aDNA in a

previous study, confirming the osteological observations (Müller 2008). This provided

the opportunity to retrieve genome sequences of the M. leprae strains present in this

region during that period of time. By comparing the Chichester and Raunds samples

with these other ancient samples, it will be possible to explore the diversity of M. leprae

infections in the past and the spread of different strains.

154

Here, this study is presented in form of a complete manuscript that has been submitted

and accepted, subject to revision for publication in Journal of Archaeological Science.

The roles of each author are outlined as follow.

Authors’ contributions: The osteological examination, DNA extraction and PCR

screening were performed by Dr Romy Muller as part of her Master’s project which was

supervised by Dr Christopher Knusel in 2008 at University of Bradford. She also

prepared the initial DNA library at Manchester Institute of Biotechnology during her

employment as Postdoctoral Research Associate in Brown’s lab. The following DNA

library target enrichment, final DNA library preparation and bioinformatics data analysis

and interpretation were performed by myself. The first draft of the article was written by

myself before being reviewed by my supervisor, Prof Terry Brown. The bone remains to

be studied were provided by Dr Jo Buckberry.

155

5.2 Publication draft

Ancient Mycobacterium leprae genomes from the mediaeval sites of Chichester and

Raunds in England

Ammielle Kerudina, Romy Müllera, Jo Buckberryb, Christopher J. Knüselc, Terence A.

Browna,*

a School of Earth and Environmental Sciences, Manchester Institute of Biotechnology,

University of Manchester, Manchester M1 7DN, UK

b Biological Anthropology Research Centre, School of Archaeological and Forensic

Sciences, University of Bradford, Bradford BD7 1DP, UK

c UMR5199 PACEA, Bâtiment B8, Allée Geoffroy Saint Hilaire, CS 50023, Pessac

Cedex, France 33615

Corresponding author

Email address: [email protected]

156

Abstract

We examined seven skeletons from mediaeval contexts from three sites in England for

the presence of Mycobacterium leprae DNA, each of the skeletons displaying

osteological indicators of leprosy. Polymerase chain reactions directed at the species-

specific RLEP multicopy sequence produced positive results with three skeletons, these

being among those with the clearest osteological signs of leprosy. Following in-solution

hybridization capture, sufficient sequence reads were obtained to cover >70% of the M.

leprae genomes from these three skeletons, with a mean read depth of 4–10. Two

skeletons from a mediaeval hospital in Chichester, UK, dating to the 14th–17th centuries

AD, contained M. leprae strains of subtype 3I, which has previously been reported in

mediaeval England. The third skeleton, from a churchyard cemetery at Raunds Furnells,

UK, dating to the 10th to mid-12th centuries AD, carried subtype 3K, which has been

recorded at 7th–13th century AD sites in Turkey, Hungary and Denmark, but not

previously in Britain. We suggest that crusaders or pilgrims to the Holy Land might have

been responsible for the transmission of subtype 3K from southeast Europe to Britain.

Keywords: Ancient DNA, Leprosy, Mediaeval England, Mycobacterium leprae,

Palaeopathology

5.2.1 Introduction

Leprosy is a slowly progressive, chronic granulomatous disease caused by

Mycobacterium leprae (Hansen, 1874) and potentially, in a minority of cases, by the

more recently characterised agent described as Mycobacterium lepromatosis (Han et al.,

2008). The primary symptoms are granulomas of the skin, peripheral nerves and

respiratory tract, but sometimes the eyes, bones and nasal cartilage are also affected

(Britton and Lockwood, 2004). The bacilli accumulate in the extremities of the body,

invading the Schwann cells causing nerve damage followed by a gradual sensory loss

and eventually leading to deformities and disabilities (Masaki et al., 2013). A multi-drug

regime comprising dapsone, rifampicin and clofazimine has been used successfully to

treat 16 million leprosy patients over the last twenty years, but new infections are

frequent with 210,671 leprosy cases reported in 2017 (World Health Organisation,

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2018). With the highest incidence of new cases occurring in northeast South America,

central Africa and the Indian subcontinent, leprosy is classified as a ‘neglected tropical

disease’ (Lenk et al., 2018). Although the disease itself is curable, leprosy-related

deformities and disabilities are irreversible, especially when treatment has been delayed

(Britton and Lockwood, 2004). Some 2–3 million people worldwide display post-leprosy

disfigurements, and many are subject to the social discrimination referred to as leprosy

stigma, which in the past was driven by misunderstandings regarding transmission of the

disease, and which still persists today in some parts of the world (Grzybowski et al.,

2016).

Leprosy is one of the oldest diseases known to humankind. Although ambiguous,

textual references to skin diseases in the Indian Atharva Veda and Laws of Manu (2000–

1500 BC) (Bloomfield, 2004) and the Egyptian Ebers papyrus (1550 BC) (Hulse, 1972)

have been identified as leprosy, and there are more recent accounts of the disease dating

from the 6th century BC to 1st century AD from India (Bhishagratna, 1996), China

(McLeod and Yates, 1981; Leung, 2008), Greece (Pinhasi et al., 2005) and Rome

(Roberts and Manchester, 2010). Additional evidence is provided by palaeopathological

examination of archaeological skeletons for the osteological manifestations of the

disease that can be observed in the hands, feet, facial bones, tibiae and fibulae of

affected skeletons (Roberts and Manchester, 2010). The oldest skeleton displaying such

lesions dates to 2000 BC, from Rajasthan in northwest India (Robbins et al., 2009), in

accordance with the Indian textual references from the same period. It has been

suggested that the disease was brought to Europe and Northern Africa by the armies of

Alexander the Great, with their return from the Indian campaign in 327–326 C (Roberts

and Manchester, 2010). There is skeletal evidence of leprosy in Egypt at 200 BC

(Dzierzykray-Rogalski, 1980) and in western Europe from the 4th century AD (Reader,

1974). However, the disease appears to have been uncommon in Europe until the

mediaeval period, when skeletons displaying lesions become more abundant (Roberts

and Manchester, 2010). In Britain, the prevalence of leprosy peaks in the 13th century

AD and then declines during the 15th century AD before becoming uncommon again

from the 16th century AD onwards (for a review of the osteological evidence for Britain,

see Roberts, 2002), possibly because of improved social conditions combined with the

development of enhanced resistance to the disease among the human population

(Schuenemann et al., 2013). The decline is mirrored in continental Europe (Bennike,

2002), although the disease persisted in some parts of Norway and elsewhere until the

19th century AD (Boldsen, 2001).

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About 5% of leprosy cases develop skeletal changes, and the lesions used in

osteological assessment of the disease can be ambiguous. An important adjunct to

palaeopathology has therefore been provided by the detection and sequencing of M.

leprae DNA, which is sometimes preserved in archaeological skeletons displaying

osteological lesions and has also occasionally been detected in skeletons free from such

lesions (Donoghue et al., 2017). Initially ancient DNA typing was used mainly to

support osteological identifications of leprosy (Rafi et al., 1994; Taylor et al., 2000,

2006; Donoghue et al., 2001, 2005, 2015; Inskip et al., 2015), but with increasing

knowledge of genomic diversity among extant M. leprae strains it has become possible

to contextualise ancient DNA data within an evolutionary scheme for the bacterium

(Schuenemann et al., 2018). The M. leprae genome is 3.27 Mb, substantially smaller

than the 4.42 Mb genome of Mycobacterium tuberculosis, and contains relatively high

number of pseudogenes, indicative of reductive evolution (Singh and Cole, 2011).

Different strains show high sequence similarity, with only a small number of variations

in the form of indels and single nucleotide polymorphisms (SNPs) (Monot et al., 2009).

The SNP variations were initially used to divide modern isolates into four main types

and 16 subtypes called 1A–1D, 2E–2H, 3I–3M and 4N–4P. With the addition of more

sequences, this classification has become elaborated into a phylogenetic scheme

comprising six main branches, with branches 1 and 2 corresponding to types 1 and 2,

respectively, branch 3 to subtype 3I, branch 4 to the type 4 strains and also subtypes 3L

and 3M, and branches 5 and 0 to different variants of subtype 3K (Schuenemann et al.,

2013, 2018). Among modern isolates, variants display geographical partitioning with

branch 1 associated with south and east Asia, branch 2 with south and southwest Asia,

branch 3 with Central and North America, branch 4 with west Africa and South

America, and branches 5 and 0 with east Asia (Monot et al., 2009; Schuenemann et al.,

2013). However, these present-day distributions do not reflect the full complexity of M.

leprae distribution in the past, especially in mediaeval Europe where subtypes within

branches 2, 3, 4 and 0 have been identified in skeletons dating from the 5th–14th centuries

AD (Singh and Cole, 2011).

Although M. leprae aDNA has been reported from a number of British sites

(reviewed by Donoghue et al., 2017), sufficient data for subtype identification has only

been obtained from six skeletons from the St Mary Magdalen leprosarium in Winchester

(Scheunemann et al., 2013; Taylor et al., 2013; Mendum et al., 2014; Roffey et al.,

2017) and one skeleton from a cemetery in Great Chesterford, Essex (Scheunemann et

al., 2018). Three of the Winchester skeletons yielded subtype 3I and the other three, as

159

well as the Great Chesterford sample, were subtype 2F. To extend the geographical

range of our knowledge of ancient M. leprae subtypes in Britain, we carried out a

biomolecular examination of seven skeletons from three sites from mediaeval England

(Fig. 5.1), each displaying pathological lesions indicative of leprosy though with varying

degrees of ambiguity. We report M. leprae genome sequences for three of these

skeletons. Two of the genomes correspond to subtype 3I, previously known in Britain,

but the third is novel to Britain and highlights the role that individual mobility might

have played in adding complexity to the phylogeography of M. leprae in mediaeval

Europe.

Figure 5.1: Locations of the sites from which skeletal samples were obtained.

5.2.2 Material and methods

5.2.2.1 Skeletons

Samples were selected, with permission, from the collection of the Biological

Anthropological Research Centre, University of Bradford, UK, based on various criteria.

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First, skeletons that clearly show pathological rhinomaxillary changes indicative of

leprosy were identified. Given that these changes are pathogonomic for lepromatous

leprosy, bilateral and symmetrical non-specific changes in the lower limb and feet of

those skeletons are hypothesized to be associated with the disease as well. Additionally,

skeletons were sought that showed non-specific lesions in the lower limbs and feet as

commonly seen in leprosy but where no rhinomaxillary alterations could be recorded,

either because they were not present or they could not be observed due to the state of

preservation of the skeleton. The distribution of these lesions, as well as the fact that no

other alterations were found which would suggest a different aetiology, made the

differential diagnosis of leprosy for these skeletons likely. The decision about which

skeletal element and, in case of bilateral skeletal involvement, which side of the body

would be sampled, was based on whether or not destruction was justifiable given the

importance of the specimens for future studies.

Based on these criteria, samples were taken from seven skeletons from three sites

(Table S5.1, Supplementary Note). Skeletons C21, C35, C48 and C227 were excavated

in 1989 from a cemetery that had belonged to the Hospital of St James and St Mary

Magdalene, Chichester, UK. The original hospital was founded c.1118 AD and housed

leprosy sufferers until being dissolved in 1442 AD and converted to an almshouse when

the prevalence of leprosy declined in the UK (Magilton et al., 2008). Based on

osteological data, C21 was a young adult male, C35 an adult of indeterminate sex, C48 a

mature adult male, and C227 an adult, likely male. All four skeletons were dated to the

14th–17th century AD, based on historical documents and associated pottery (Magilton et

al., 2008). Skeletons R5046 and R5256 were males of 17–25 and 25–35 years,

respectively, from the late Anglo-Saxon churchyard cemetery at Raunds Furnells,

Northamptonshire, UK, excavated during 1977–1985. Stratigraphical analyses and

radiocarbon dating suggested that the churchyard cemetery was in use from the mid-10th

until mid-12th centuries (Boddington, 1996). Individual H3726 was a less well-preserved

and incomplete male skeleton of 25–35 years from a cemetery in the southwest area of

the cathedral at Hereford, UK, excavated in 1993 (Stone and Appleton-Fox, 1996). The

cemetery was in use from the 12th–16th centuries AD.

161

Table 5.1: Details of skeletons and samples that were taken.

Site Skeleton Sex, age at death Leprosy indicatorsa Elements sampleda

Rhinomaxillary

changes

Sub-periosteal new

bone formation

Other

changes

Chichester C21 Young adult male Yes Yes Yes Tibia, metatarsus

C35 Adult, indeterminate

sex

No Yes Yes Tibia

C48 Mature adult Yes Yes No Tibia, fibula

C227 Male(?) adult Yes Yes Yes Calcaneus, phalanx

Raunds R5046 Male, 17–25 years Yes Yes Yes Fibula

R5256 Male 25–35 years No Yes No Tibia, fibula, new bone

formation

Hereford H3726 Male 25–35 years Viscerocranium

absent

Yes Yes Tibia, fibula

a For details of pathology and elements sampled, see Supplementary Note (summary of archaeological sites, pathological lesions of skeletons, and elements that

were sampled) and Supplementary Table S5.1 (detailed osteological report).

162

Skeletons C21, C48 and C227 from Chichester and the Raunds skeleton R5046

displayed rhinomaxillary changes and other lesions indicative of leprosy (Table S5.1,

Supplementary Note, Supplementary Table S5.1). The fourth Chichester skeleton, C35,

and individual R5256 from Raunds did not show the typical rhinomaxillary changes but

both did have sub-periosteal new bone formation on other skeletal elements. Only parts

of the left lower limb were recovered from the Hereford skeleton H3726 and so

rhinomaxillary changes could not be assessed. However, the pattern of sub-periosteal

new bone formation on the lower limbs and feet suggested a possible leprous infection.

5.2.2.2 Ancient DNA regime

DNA extractions, PCRs and Illumina library preparations were performed in two

physically separated laboratories within the specialized ancient DNA research facility

at the University of Manchester. Each laboratory was supplied with ultra-filtered air

under positive displacement. After each use, benches and equipment were

decontaminated by UV irradiation and by cleaning with 5% hypochlorite acid, 70%

ethanol and DNA Away (Molecular Bioproducts). Small equipment, plasticware and

UV-stable reagents were decontaminated by UV irradiation (254 nm, 120,000 mJ cm–2

for 2 5 min, with 180° rotation between the two exposures) before use. Aqueous

solutions were similarly irradiated for 15 min. Personnel wore a disposable forensic

suit, face mask, hair net, goggles, two layers of gloves and disposable shoe covers at all

times. DNA extractions were accompanied by two blanks (normal extraction but

without skeletal material) per five samples and every set of 5–7 PCRs was

accompanied by at least two blanks (set up with water rather than DNA extract).

5.2.2.3 DNA extraction, PCR and sequencing

Bone samples were taken using a hacksaw or electronic drill by personnel wearing

protective clothing, including forensic suits, hair nets, face masks and two pairs of

sterile gloves. Samples were placed in sterile plastic bags and stored under dry and cool

conditions and transferred to the ancient DNA facility. The bone surfaces were

163

decontaminated by mechanical removal of the outer 1–2 mm of each sample, followed

by UV irradiation (254 nm, 120,000 mJ cm–2) for 2 5 min, with 180° rotation

between the two exposures (Bouwman et al., 2006). Bone samples were then placed in

a DNA-free plastic bag wrapped in a sterile piece of aluminium foil and crushed into

fine powder. DNA was extracted from 0.2 g of bone powder by standard methods

(method D of Bouwman and Brown, 2002; Dabney et al., 2013).

An initial screening for presence of M. leprae DNA was carried out by hemi-nested

PCR directed at the RLEP repetitive element, in 50 µl reactions comprising 2.5 µl of

DNA extract or 1.0 µl of first round PCR product, 1 AmpliTaq Gold PCR Master Mix

(ThermoFisher Scientific), 2 mM MgCl2, 200 µM dNTPs, 200 ng each primer, 1%

bovine serum albumin and 1.25 units AmpliTaq Gold DNA polymerase (ThermoFisher

Scientific). The primers for the first PCR (forward: 5´–

CACCTGATGTTATCCCTTGC–3´; reverse: 5´–ATCATCGATGCACTGTTCAC–3)

amplified a 133 bp fragment, and the second PCR (forward: 5´–

CATTTCTGCCGCTGGTATC –3´; reverse as for first PCR) amplified a 111 bp

fragment. Cycling conditions were 7 min at 95°C, followed by 35 cycles each

consisting of 1 min at 56°C, 1 min at 72°C, 1 min at 94°C, and a final cycle at 56°C for

1 min and 72°C for 10 min. PCR products were analysed by agarose gel electrophoresis

and directly purified using the QIAquick PCR product purification kit (Qiagen) prior to

Sanger sequencing (GATC Biotech, Cologne).

Dual-indexed libraries for Illumina sequencing were prepared from positive

samples. No DNA fragmentation step was performed as ancient DNA is already highly

degraded. Library preparation included a blunt-end repair step but no A-tailing,

followed by purification using the MinElute PCR purification kit (Qiagen), with elution

in 20 µl. Subsequent adapter ligation was performed using p5 and p7 adapters at a

concentration of 0.2 µM (Meyer and Kircher, 2010). Nicks from the previous step were

filled in with Bst polymerase before quantification by qPCR (Roche LightCycler 480)

and fluorimetry (Qubit 2.0) to determine the number of cycles required for the

subsequent indexing PCR. Sample-specific barcodes were added by double-indexing

(Kircher et al., 2012), using KAPA HiFi Uracil+ (Kapa Biosystems). Samples were

then pooled in equimolar ratios and sequenced from both ends in a single flow cell

(Illumina HiSeq 4000). As well as shotgun sequencing, samples were also sequenced

after enrichment by in-solution hybridization capture (MYcroarray) according to the

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manufacturer's instructions for degraded samples. RNA baits were transcribed from 80-

mer oligonucleotides complementary to the M. leprae TN genome to give an array with

2 tiling density. Sequence data are curated at the European Nucleotide Archive under

study accession number PRJEB31393.

5.2.2.4 Data analysis

Raw sequencing data were pre-processed with AdapterRemoval 2.1 (Schubert et al.,

2016) to remove adapter sequence remnants, trim low quality bases and merge paired-

end reads. Reads of at least 25 bp which formed pairs with at least 11 bp overlap, and

non-overlapping pair mates of >25 bp, were retained in separate files. The paired-end

reads were then mapped to the M. leprae TN genome with BWA 0.7.12 (Li and Durbin,

2009). The alignments were cleaned by soft clipping, sorted based on coordinate with

Picard Tools (http://broadinstitute.github.io/picard), and mapped reads with a

quality score of at least 20 extracted using SAMtools 0.1.19 (Li et al., 2009). Read

duplicates were removed using the MarkDuplicates option in Picard Tools. The

mapped reads with duplicates removed were converted to Fasta files and tested by

BLAST (Altschul et al., 1990) with the outputs visualised using MEGAN 6 (Huson et

al., 2016). Base quality score recalibration was performed with GATK 3.6 (McKenna

et al., 2010) using the non-human genome method. The recalibrated alignments

containing the reads that mapped to M. leprae and were verified by BLAST were

visualized using Geneious 8.1.9 (Kearse et al., 2012). Polymorphisms were considered

genuine if supported by at least 5 coverage and a variant frequency of at least 80%.

5.2.3 Results

Samples (Table 5.1) were screened for the presence of M. leprae DNA by hemi-

nested polymerase chain reactions (PCRs) directed at the multicopy RLEP element,

which is believed to be specific to this species (Braet et al., 2018) and has previously

been used for detection of M. leprae ancient DNA (Donoghue et al., 2017). The first-

round PCRs provided products of the correct size, as judged by agarose gel

electrophoresis, for the two samples (tibia and metatarsus) taken from skeleton C21, the

165

two samples (tibia and fibula) from C48, and the single sample (fibula) from R5046

(Table 5.2). The second-round PCRs provided bands of the expected sizes from the

same samples, and no others. The results were replicated with a second set of PCRs on

the same extracts. None of negative controls (extraction blanks and PCR blanks)

revealed amplification products. Direct sequencing of the PCR products verified their

identity as genuine RLEP amplicons.

Table 5.2: Results of RLEP PCRs.

Skeleton Sampled element PCR resultsa

C 21 Tibia +,+

Metatarsus +,+

C 35 Tibia –,–

C 48 Tibia +,+

Fibula +,+

C227 Calcaneus –,–

Phalanx –,–

R5046 Fibula +,+

R5256 Tibia –,–

Fibula –,–

New bone formation –,–

H3726 Tibia –,–

Fibula –,–

a Result of first hemi-nested PCR, result of second hemi-nested PCR.

166

Samples from the three positive skeletons – C21, C48 and R5046 – were further

studied by Illumina sequencing. Shotgun sequencing was attempted for all three

samples but less than 0.001% of the reads mapped to the M. leprae TN genome, which

was insufficient for genome analysis. In-solution hybridization capture was therefore

used to enrich the samples for M. leprae sequences. Enrichment dramatically increased

the numbers of reads mapping to the reference genome (Supplementary Table S5.2),

with >70% of the genome covered for each of the samples and a mean read depth of 4–

10. The data enabled the ancient strains to be assigned to M. leprae genotypes (Table

5.3) (Monot et al., 2009), revealing that C21 and C48 belong to subtype 3I and R5046

to subtype 3K.

Table 5.3 Genotype assignments.

Skeleton SNP positiona Type SNP positiona Subtype

14,676 1,642,875 2,935,685 413,902 1,133,492 2,312,059 3,267,975

C21 C T C 3 G T C G I

C48 C T C 3 G T C G I

R5046 C T C 3 G G G G K

a SNP positions according to the M. leprae TN genome sequence.

Comparisons between different modern strains of M. leprae have revealed a total of

215 polymorphic sites (Monot et al., 2009). These sites were examined in the ancient

M. leprae genomes to determine whether the SNP version that was present was the

same as in the M. leprae TN reference sequence, or was the alternative SNP version

present in some other modern genomes (Supplementary Table S5.3). Of the three

ancient genomes, R5046 was the most greatly diverged from M. leprae TN, with 119 of

the 183 SNPs (65.0%) that were covered by the ancient sequence displaying the version

not present in the reference genome. In comparison, 53.1% and 56.1% of the SNPs

167

covered in the C21 and C48 genomes, respectively, had the non-reference version. The

greater dissimilarity between R5046 and M. leprae TN reflects the greater phylogenetic

distance between subtype 3K and subtype 1A, to which TN belongs (Schuenemann et

al., 2018). An additional 41 sites, comprising 30 SNPs and 11 indels, were specific to

the three ancient genomes reported here (Supplementary Table 5.4). Of the 30 SNPs,

18 were present only in the R5046 genome, and 7 and 5 were unique to C21 and C48,

respectively. None of the 30 SNPs were present in all three ancient genomes. Of the

eleven indels, five were specific to R5046 and six were present in all three samples,

four of the latter in pseudogenes.

5.2.4 Discussion

We examined seven skeletons from mediaeval contexts of three sites in England,

each of the skeletons displaying osteological indicators of leprosy, though with

different degrees of ambiguity. We identified M. leprae DNA in three skeletons and

following enrichment by in-solution hybridization obtained sufficient sequence data to

assign skeletons C21 and C48 to subtype 3I and skeleton R5046 to subtype 3K.

Although C21 and C48 came from the same cemetery, and were curated together for 25

years prior to DNA analysis, we can be confident that both contain endogenous M.

leprae DNA (as opposed to cross-contamination between the skeletons or

contamination from a single external source) as their M. leprae genome sequences are

non-identical.

Each of the three skeletons that produced positive results had extensive osteological

indications of leprosy, including rhinomaxillary changes, sub-periosteal new bone

formation, and other lesions on various skeletal elements. Of the samples that produced

negative results, C227 had a pathological condition most likely indicative of leprosy, in

particular pencilling of the fifth metatarsal with complete resorption of the head and

distal part of the diaphysis in the right foot as well as a slight pitting of the palate.

However, this skeleton displayed relatively poor physical preservation, indicating that

the failure to detect M. leprae DNA was possibly due to biomolecular degradation

before the skeleton was excavated. Skeletons C35 and R5256 did not display

rhinomaxillary changes, weakening the diagnosis of leprosy in both cases. The

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pathology of the other parts of skeleton C35 could be ascribed to a treponemal disease

or other infection, and R5256 displayed new bone formation on the ossa coxae and left

scapula, skeletal elements that are not usually involved in leprosy infection, possibly

suggesting a systemic condition other than leprosy. Skeleton H3726 comprised only

fragments of the left lower limb, so the pathological evidence for leprosy was rather

weak, and unsupported by the DNA evidence. Overall, the results confirm those of

other groups (Rafi et al., 1994; Taylor et al, 2000, 2006, 2013; Donoghue et al., 2001,

2005, 2015; Inskip et al., 2015) by emphasising the value of ancient DNA analysis as a

means of providing independent support to palaeopathological identifications of

leprosy.

M. leprae strains previously reported from mediaeval Britain and Ireland have been

assigned to subtypes 2F and 3I (Taylor et al., 2013, 2018; Schuenemann et al., 2013,

2018; Mendum et al., 2014), the latter corresponding to branch 3 in the more recent

phylogenetic classification (Schuenemann et al., 2018). The discovery of subtype 3I in

two skeletons from Chichester, dating to the 14th–18th centuries AD, is therefore

consistent with these previous studies. Subtype 3K, however, has not previously been

reported in Britain. In modern M. leprae, this subtype is associated with east Asia, in

particular Japan, China, the Philippines and New Caledonia (Schuenemann et al.,

2018). Among ancient specimens it has been detected in a Turkish skeleton from the

8th–9th centuries AD (Erdal, 2004), three skeletons from Hungary, from the 7th–10th

centuries AD (Pálfi et al., 2002; Molnár et al., 2006; Schuenemann et al., 2018), and

another from 11th–13th century AD Denmark (Schuenemann et al., 2018). The R5046

skeleton is from a similar period (10th to mid-12th centuries AD) as these other

European detections, but is the most westerly in location, and hence the most distant

from the modern distribution of the subtype. The distribution pattern raises the

intriguing possibility that the individual represented by skeleton R5046 did not contract

leprosy in Britain but instead had travelled to continental Europe and/or Asia and

contracted the disease there. It has previously been suggested that human mobility

along the Silk Route was responsible for bringing subtype 3K to eastern Europe from

its supposed centre of origin in east Asia (Monot et al., 2009). During the Anglo-Saxon

period, up until the 10th century AD, there was also extensive mobility between Britain

and continental Europe, especially of educated clerics who taught and held religious

positions in various European countries (Palmer, 2009). Additionally, the 11th century

AD marks the beginning of the crusades by which European adventurers attempted to

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gain control of the Christian Holy Land of Jerusalem. One of the routes taken by the

crusaders, and by pilgrims, to reach the Holy Land from western and central Europe

began in Vienna and passed along the Danube and the Via Diagonalis to

Constantinople, traversing Hungary, Serbia and Bulgaria (The Way to Jerusalem,

2018). It is therefore possible that leprosy of subtype 3K was transmitted to Britain and

other parts of western Europe by crusaders and pilgrims who had travelled to the Holy

Land and back via this route.

Acknowledgements

We thank Anthea Boylston (University of Bradford) for assistance with the

osteological examination, and Keri Brown (University of Manchester, UK) for

assistance with sampling. This work was funded by a studentship awarded by Majlis

Amanah Rakyat (MARA) to A.K. and by the University of Bradford and the University

of Manchester.

References

Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J., 1990. Basic local

alignment search tool. J. Mol. Biol. 215, 403–410. https://doi.org/10.1016/S0022-

2836(05)80360-2.

Bennike, P., 2002. Vilhelm Moller-Christensen: his work and legacy, in: Roberts, C.A.,

Lewis, M.E., Manchester, K. (Eds.), The Past and Present of Leprosy: Archaeological,

Historical, Palaeopathological and Clinical Approaches. BAR International Series

1054, Archaeopress, Oxford, pp. 135–144.

Bhishagratna, K.K, 1996. English Translation of Sushruta Samhita (ca 600 BC). Bose,

Calcutta.

Bloomfield, M., 2004. Hymns of the Atharva Veda. Kessinger Publishing, Whitefish.

Boddington, A., 1996. Raunds Furnells: the Anglo-Saxon Church and Churchyard.

Archaeological Report 7, English Heritage.

Boldsen, J.L., 2001. Epidemiological approach to the paleopathological diagnosis of

leprosy. Am. J. Phys. Anthropol. 115, 380–387. https://doi.org/10.1002/ajpa.1094.

170

Bouwman, A.S., Brown T.A., 2002. Comparison between silica-based methods for the

extraction of DNA from human bones from 18th–mid-19th century London. Ancient

Biomol. 4, 173–178. https://doi.org/10.1080/1358612021000028470.

Bouwman, A.S., Chilvers, E.R., Brown, K.A. & Brown T.A., 2006. Identification of

the authentic ancient DNA sequence in a human bone contaminated with modern DNA.

Am. J. Phys. Anthropol. 131, 428–431. https://doi.org/10.1002/ajpa.20411.

Braet, S., Vandelannoote, K., Meehan, C.J., Brum Fontes, A.N., Hasker, E., Rosa, P.S.,

Lucena-Silva, N., Rigouts, L., Suffys, P.N., De Jong, B.C., 2018. The repetitive

element RLEP is a highly specific target for detection of Mycobacterium leprae. J.

Clin. Microbiol. 56, e01924-17. https://doi.org/10.1128/JCM.01924-17.

Britton, W.J., Lockwood, D.N.J., 2004. Leprosy. Lancet 363, 1209–1219.

https://doi.org/10.1016/S0140-6736(04)15952-7 (2004).

Dabney, J., Knapp, M., Glocke, I., Gansauge, M.T., Weihmann, A., Nickel, B.,

Valdiosera, C., García, N., Pääbo, S., Arsuaga, J.L., Meyer, M., 2013. Complete

mitochondrial genome sequence of a Middle Pleistocene cave bear reconstructed from

ultrashort DNA fragments. Proc. Natl. Acad. Sci USA 110, 15758–15763.

https://doi.org/10.1073/pnas.1314445110.

Donoghue, H.D., Holton, J., Spigelman, M., 2001. PCR primers that can detect low

levels of Mycobacterium leprae DNA. J. Med. Microbiol. 50, 177–182.

https://doi.org/10.1099/0022-1317-50-2-177.

Donoghue, H.D., Marcsik, A., Matheson, C., Vernon, K., Nuorala, E., Molto, J.E.,

Greenblatt, C.L., Spigelman, M., 2005. Co-infection of Mycobacterium tuberculosis

and Mycobacterium leprae in human archaeological samples: A possible explanation

for the historical decline of leprosy. Proc. R. Soc. B 272, 389–394.

https://doi.org/10.1098/rspb.2004.2966.

Donoghue, H.D., Taylor, G.M., Marcsik, A., Molnar, A., Palfi, G., Pap, I., Teschler-

Nicola, M., Pinhasi, R., Erdal, Y.S., Velemínsky, P., Likovsky, J., Belcastro, M.G.,

Mariotti, V., Riga, A., Rubini, M., Zaio, P., Besra, G.S., Lee, O.Y., Wu. H.H.,

Minnikin, D.E., Bull, I.D., O'Grady, J., Spigelman, M., 2015. A migration-driven

model for the historical spread of leprosy in mediaeval Eastern and Central Europe.

Infect. Genet. Evol. 31, 250–256. https://doi.org/10.1016/j.meegid.2015.02.001.

Donoghue, H.D., Taylor, G.M., Stewart, G.R., Lee, O.Y.-C., Wu, H.H.T., Besra, G.S.,

Minnikin, D.E., 2017. Positive diagnosis of ancient leprosy and tuberculosis using

ancient DNA and lipid biomarkers. Diversity 9(4), 46.

https://doi.org/10.3390/d9040046.

Dzierzykray-Rogalski, T., 1980. Paleopathology of the Ptolemaic inhabitants of

Dakhleh Oasis (Egypt). J. Hum. Evol. 9, 71–72. https://doi.org/10.1016/0047-

2484(80)90044-5.

171

Erdal, Y.S., 2004. Health status of the Kovuklukaya (Boyabat/Sinop) people and its

relations with their lifestyle. Anadolu Araştirmalari 22, 169–196.

Grzybowski, A., Sak, J., Pawlikowski, J., Nita, M., 2016. Leprosy: social implications

from antiquity to the present. Clin. Dermatol. 34, 8–10,

https://doi.org/10.1016/j.clindermatol.2015.10.009.

Han, X.Y., Seo, Y.H., Sizer, K.C., Schoberle, T., May, G.S., Spencer, J.S., Li, W.,

Nair, R.G., 2008. A new mycobacterium species causing diffuse lepromatous leprosy.

Am. J. Clin. Pathol. 130, 856–864. https://doi.org/10.1309/AJCPP72FJZZRRVMM.

Hansen, G.H.A., 1874. Undersøgelser Angående Spedalskhedens Årsager. Norsk Mag.

Laegervidenskaben. 4, 1–88.

Hulse, E.V., 1972. Leprosy and Ancient Egypt. Lancet 2, 1024.

https://doi.org/10.1016/S0140-6736(72)92636-0.

Huson, D.H., Beier, S., Flade, I., Górska, A., El-Hadidi, M., Mitra, S., Ruscheweyhm

H.J., Tappu, R., 2016. MEGAN community edition – interactive exploration and

analysis of large-scale microbiome sequencing data. PLoS Comput. Biol. 12(6),

e1004957. https://doi.org/10.1371/journal.pcbi.1004957.

Inskip, S.A., Taylor, G.M., Zakrzewski, S.R., Mays, S.A., Pike, A.W.G., Llewellyn, G.,

Williams, C.M., Lee, O.Y., Wu, H.H., Minnikin, D.E., Besra, G.S., Stewart, G.R.,

2015. Osteological, biomolecular and geochemical examination of an early Anglo-

Saxon case of lepromatous leprosy. PLoS ONE 10, e0124282.

https://doi.org/10.1371/journal.pone.0124282.

Kearse, M., Moir, R., Wilson, A., Stones-Havas, S., Cheung, M., Sturrock, S., Buxton,

S., Cooper, A., Markowitz, S., Duran, C., Thierer, T., Ashton, B., Meintjes, P.,

Drummond, A., 2012. Geneious basic: an integrated and extendable desktop software

platform for the organization and analysis of sequence data. Bioinformatics 28, 1647–

1649. https://doi.org/10.1093/bioinformatics/bts199.

Kircher, M., Sawyer, S., Meyer, M., 2012. Double indexing overcomes inaccuracies in

multiplex sequencing on the Illumina platform. Nucl. Acids Res. 40(1), e3.

https://doi.org/10.1093/nar/gkr771.

Lenk, E.J., Redekop, W.K., Luyendijk, M., Fitzpatrick, C., Niessen, L., Stolk, W.A.,

Tediosi, F., Rijnsburger, A.J., Bakker, R., Hontelez, J.A.C., Richardus, J.H., Jacobson,

J., Le Rutte, E.A., de Vlas, S.J., Severeens, J.L., 2018. Socioeconomic benefit to

individuals of achieving 2020 targets for four neglected tropical diseases

controlled/eliminated by innovative and intensified disease management: Human

African trypanosomiasis, leprosy, visceral leishmaniasis, Chagas disease. PLoS Negl.

Trop. Dis. 12(3), e0006250. https://doi.org/10.1371/journal.pntd.0006250.

Leung, A.K.C., 2008. Leprosy in China: a history. Columbia University Press, New

York.

172

Li, H., Durbin, R., 2009. Fast and accurate short read alignment with Burrows-Wheeler

transform. Bioinformatics 15, 1754–1760.

https://doi.org/10.1093/bioinformatics/btp698.

Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G.,

Abecasis, G., Durbin, R., 2009. The sequence alignment/map format and SAMtools.

Bioinformatics 25, 2078–2079. https://doi.org/10.1093/bioinformatics/btp352.

Magilton. J., Lee, F., Boylston, A., 2008. ‘Lepers Outside the Gate’: Excavation at the

Cemetery of the Hospital of St James and St Mary Magdelene, Chichester, 1986-87 and

1993. CBA Research report 158, Council for British Archaeology, York.

Masaki, T., Qu, J., Cholewa-Waclaw, J., Burr, K., Raaum, R., Rambukkana, A., 2013.

Reprogramming adult Schwann cells to stem cell-like cells by leprosy bacilli promotes

dissemination of infection. Cell 152, 51–67. https://doi.org/10.1016/j.cell.2012.12.014.

McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A.,

Garimella, K., Altshuler, D., Gabriel, S., Daly, M., DePristo, M.A., 2010. The Genome

Analysis Toolkit: a MapReduce framework for analysing next-generation DNA

sequencing data. Genome Res. 20, 1297–1303. https:/.doi.org/10.1101/gr.107524.110.

McLeod, K., Yates, R., 1981. Forms of Ch'in law: an annotated translation of the Feng-

chen shih. Harv. J. Asiat. Stud. 41, 111–163. https://doi.org/10.2307/2719003.

Mendum, T.A., Schuenemann, V.J., Roffey, S., Taylor, G.M., Wu, H., Singh, P.,

Tucker, K., Hinds, J., Cole, S.T., Kierzek, A.M., Nieselt, K., Krause, J., Stewart, G.R.,

2014. Mycobacterium leprae genomes from a British mediaeval leprosy hospital:

towards understanding an ancient epidemic. BMC Genomics 15, 270.

https://doi.org/10.1186/1471-2164-15-270.

Meyer, M., Kircher, M., 2010. Illumina sequencing library preparation for highly

multiplexed target capture and sequencing. Cold Spring Harb. Protoc. 2010(6),

pdb.prot5448. https://doi.org/10.1101/pdb.prot5448.

Molnár, E., Marcsik, A., Bereczki, Z., Donoghue, H.D., 2006. Pathological cases from

the 7th century in Hungary, in Paleopathology Association, 16th European Meeting,

Scientific Program and Abstracts. Supplement to Paleopathology Newsletter, pp. 36–

37.

Monot, M., Honoré, N., Garnier, T., Zidane, N., Sherafi, D., Paniz-Mondolfi, A.,

Matsuoka, M., Taylor, G.M., Donoghue, H.D., Bouwman, A., Mays, S., Watson, C.,

Lockwood, D., Khamesipour, A., Dowlati, Y., Jianping, S., Rea, T.H., Vera-Cabrera,

L., Stefani, M.M., Banu, S., Macdonald, M., Sapkota, B.R., Spencer, J.S., Thomas, J.,

Harshman, K., Singh, P., Busso, P., Gattiker, A., Rougemont, J., Brennan, P.J., Cole,

S.T., 2009. Comparative genomic and phyleogeographic analysis of Mycobacterium

leprae. Nat. Gen. 42, 1282–1289. https://doi.org/0.1038/ng.477.

173

Pálfi, G., Zink, A., Haas, C.J., Marcsik, A., Dutour, O., Nerlich, A.G., 2002. Historical

and palaeopathological evidence of leprosy in Hungary, in: Roberts, C.A., Lewis, M.E.,

Manchester, K. (Eds.), The Past and Present of Leprosy: Archaeological, Historical,

Palaeopathological and Clinical Approaches. BAR International Series 1054,

Archaeopress, Oxford, pp. 205–209.

Palmer, J.T., 2009. Anglo-Saxons in a Frankish World, 690–900. Brepols, Turnhout.

Pinhasi, R., Foley, R., Donoghue, H.D., 2005. Reconsidering the antiquity of leprosy.

Science 312, 846. https://doi.org/10.1126/science.312.5775.846a.

Rafi, A., Spigelman, A., Stanford, J., Lemma, E., Donoghue, H., Zias, J., 1994. DNA of

Mycobacterium leprae detected by PCR in ancient bone. Int. J. Osteoarchaeol. 4, 287–

290. https://doi.org/10.1016/S0140-6736(94)92494-5.

Reader, R., 1974. New evidence for the antiquity of leprosy in early Britain. J.

Archaeol. Sci. 1, 205–207. https://doi.org/10.1016/0305-4403(74)90043-0.

Robbins, G., Tripathy, M., Misra, V.N., Mohanty, R.K., Shinde, V.S., Gray, K.M.,

Schug, M.D., 2009. Ancient skeletal evidence for leprosy in India (2000 B.C.). PLoS

ONE 4(5), 1-8. https://doi.org/10.1371/journal.pone.0005669.

Roberts, C., Manchester, K., 2010. The Archaeology of Disease, third ed. The History

Press, Stroud.

Roberts, C.A., 2002. The antiquity of leprosy in Britain: the skeletal evidence, in:

Roberts, C.A., Lewis, M.E., Manchester, K. (Eds.), The Past and Present of Leprosy:

Archaeological, Historical, Palaeopathological and Clinical Approaches. BAR

International Series 1054, Archaeopress, Oxford, pp. 213–222.

Roffey, S., Tucker, K., Filipek-Ogden, K., Montgomery, J., Cameron, J., O’Connell, T.,

Evans, J., Marter, P., Taylor, G.M., 2017. Investigation of a medieval pilgrim burial

excavated from the leprosarium of St Mary Magdalen Winchester, UK. PLoS Negl.

Trop. Dis. 11(1), e0005186. https://doi.org/10.1371/journal.pntd.0005186.

Schubert, M., Lindgreen, S., Orlando, L., 2016. AdapterRemoval v2: rapid adapter

trimming, identification, and read merging. BMC Res. Notes 9, 88.

https://doi.org/10.1186/s13104-016-1900-2.

Schuenemann, V.J., Singh, P., Mendum, T.A., Krause-Kyora, B., Jager, G., Bos, K.I.,

Herbig, A., Economou, C., Benjak, A., Busso, P., Nebel, A., Boldsen, J.L., Kjellström,

A., Wu, H., Stewart, G.R., Taylor, G.M., Bauer, P., Lee, O.Y.-C., Wu, H.H.T.,

Minnikin, D.E., Besra, G.S., Tucker, K., Roffey, S., Sow, S.O., Cole, S.T., Nieselt, K.,

Krause, J., 2013. Genome-wide comparison of mediaeval and modern Mycobacterium

leprae. Science 341, 179–183. https://doi.org/10.1126/science.1238286.

Schuenemann, V.J., Avanzi, C., Krause-Kyora, B., Seitz, A., Herbig, A., Inskip, S.,

Bonazzi, M., Reiter, E., Urban, C., Dangvard Pedersen, D., Taylor, G.M., Singh, P.4,

174

Stewart, G.R., Velemínský, P., Likovsky, J., Marcsik, A., Molnár, E., Pálfi, G.,

Mariotti, V., Riga, A., Belcastro, M.G., Boldsen, J.L., Nebel, A., Mays, S., Donoghue,

H.D., Zakrzewski, S., Benjak, A., Nieselt, K., Cole, S.T., Krause, J., 2018. Ancient

genomes reveal a high diversity of Mycobacterium leprae in mediaeval Europe. PLoS

Pathog. 14(5), e1006997. https://doi.org/10.1371/ journal.ppat.1006997.

Singh, P., Cole, S.T., 2011. Mycobacterium leprae: genes, pseudogenes and genetic

diversity. Future Microbiol. 6, 57–71, https://doi.org/10.2217/fmb.10.153.

Stone, R., Appleton-Fox, N., 1996. A View from Hereford's Past: a Report on the

Archaeological Excavation in Hereford Cathedral Close in 1993. Logaston Press,

Eardisley.

Taylor, G.M., Widdison, S., Brown, I.N., Young, D., 2000. A mediaeval case of

lepromatous leprosy from 13th–14th century Orkney, Scotland. J. Archaeol. Sci. 27,

1133–1138. https://doi.org/10.1006/jasc.1999.0532.

Taylor, G.M., Watson, C.L., Bouwman, A.S., Lockwood, D.N.J., Mays, S.A., 2006.

Variable number tandem repeat (VNTR) typing of two palaeopathological cases of

lepromatous leprosy from mediaeval England. J. Archaeol. Sci. 33, 1569–1579.

https://doi.org/10.1016/j.jas.2006.02.008.

Taylor, G.M., Tucker, K., Butler, R., Pike, A.W.G., Lewis, J., Roffey, S., Marter, P.,

Lee, O.Y., Wu, H.H., Minnikin, D.E., Besra, G.S., Singh, P., Cole, S.T., Stewart, G.R.,

2013. Detection and strain typing of ancient Mycobacterium leprae from a mediaeval

leprosy hospital. PLoS ONE 8, e62406. https://doi.org/10.1371/journal.pone.0062406.

Taylor, G.M., Murphy, E.M., Mendum, T.A., Pike, A.W.G., Linscott, B., Wu, H.,

O'Grady, J., Richardson, H., O'Donovan, E., Troy, C., Stewart, G.R., 2018. Leprosy at

the edge of Europe – biomolecular, isotopic and osteoarchaeological findings from

medieval Ireland. PLoS ONE 13, e0209495. https://doi.

org/10.1371/journal.pone.0209495.

The Way to Jerusalem, 2018. Historical routes: routes to the Holy Land.

http://www.waytojerusalem.com/en/historical-routes/routes-to-the-holy-land.

World Health Organization, 2018. Global leprosy update, 2017: reducing the disease

burden due to leprosy. Wkly Epidemiol. Rec. 93, 445–456.

https://apps.who.int/iris/handle/10665/27

175

5.3 Supplementary information

Ancient Mycobacterium leprae genomes from the mediaeval sites of Chichester and

Raunds in England

Ammielle Kerudina, Romy Müllera, Jo Buckberryb, Christopher J. Knüselc, Terence A.

Browna,*

a School of Earth and Environmental Sciences, Manchester Institute of Biotechnology,

University of Manchester, Manchester M1 7DN, UK

b Biological Anthropology Research Centre, School of Archaeological and Forensic

Sciences, University of Bradford, Bradford BD7 1DP, UK

c UMR5199 PACEA, Bâtiment B8, Allée Geoffroy Saint Hilaire, CS 50023, Pessac

Cedex, France 33615

Supplementary Information

Supplementary Note 1. Summary of archaeological sites, pathological lesions of

skeletons, and elements that were sampled.

Supplementary Table S5.1. Detailed osteological report. – see Kerudin et al Table

S1.xlsx.

Supplementary Table S5.2. Summary statistics for Illumina sequencing following

enrichment of samples by in-solution hybridization.

176

Supplementary Table S5.3. Identities in the C21, C48 and R5046 genomes of the 215

SNPs known in modern M. leprae strains.

Supplementary Table S5.4. Unique variations (highlighted in green) present in the

C21, C48 and/or R5046 genomes.

177

Supplementary Note 1

Details of archaeological sites, pathological lesions of skeletons, and elements that

were sampled

Chichester. The Chichester site is situated outside the old city walls in the city of

Chichester, West Sussex, UK. The cemetery from which the skeletons were recovered

once served the mediaeval hospital of St. James and St. Mary Magdalene which was

used from approximately the early 12th until the 17th century AD (Magilton et al.,

2008). As indicated from contemporary documents, since its foundation at

approximately 1118 AD until 1442 AD, the hospital was used as a leprosarium, and

later became an almshouse. The original excavation was conducted in 1986–87 and

recovered 330 individuals, while ongoing work in 1993 revealed a further 44 skeletons.

The skeletons recovered from the cemetery date from around 1300–1700 AD, based on

associated pottery as well as on historical documents. For analytical reasons, the

cemetery was divided into two main areas, A and B, further subdivided into A1, and

A2, and B1 and B2. Skeleton C227 was excavated from Area B1, and the other three

from Area A2. It is suspected that Area A predates Area B.

Skeleton C21. Palaeopathological examination of skeleton C21 revealed rhinomaxillary

changes as well as new bone formation in several parts of the skeleton, in particular in

the lower limbs. Additional changes in the hands and feet were also suggestive of a

leprous infection. For DNA analysis, the middle third of the diaphysis of the left tibia

and the first metatarsal of the left foot (apart from its proximal articular surface) were

selected. The tibia shows new sub-periosteal striated compact bone formation,

diffusely, along the entire diaphysis (Fig. S5.1A), and the metatarsal shows porous and

compact sub-periosteal new bone formation (Fig. S5.1B).

178

Skeleton C35. Apart from a slight alveolar recession, no signs of rhinomaxillary

syndrome were found in this individual. However, both tibiae and fibulae show sub-

periosteal new bone formation. Especially, the fibulae and the right tibia are osteitic in

appearance and the right tibia and fibula were ankylosed. The distribution of these

pathological alterations, together with signs of infection in the left foot (the right foot is

missing) and bony exostoses on the left talus, may be due to leprosy. Therefore, the

proximal part of the broken distal diaphysis of the right fibula was chosen for analysis

(Fig. S5.2). This element shows sub-periosteal new porous compact bone formation,

partially striated and partially with overlying woven bone formation and is heavily

osteitic. Even though broken post-mortem, it is obvious that the most distal part of the

distal right fibula was ankylosed with the tibia through the interosseus ligament.

Skeleton C48. Rhinomaxillary changes as seen in leprosy were present and further

pathological alterations throughout the infracranial skeleton are hypothesised to be

associated with the disease. Sub-periosteal new bone formation can be seen in both

tibiae and fibulae, in the calcanei and in other bones of the left foot. In particular, the

left metatarsals are heavily osteitic and show areas of lytic destruction. Furthermore,

the tarsals of the left foot show dorsal tarsal bars. For DNA analysis, a part of the distal

end of the diaphysis was selected from both left tibia and fibula. The tibia shows

subperiosteal new striated porous compact bone formation diffusely spread along the

entire diaphysis. The lateral and postero-lateral aspects of the middle to distal third of

Fig. S5.1. Skeleton C21. (A) Sub-periosteal new compact bone formation on the diaphysis of the left tibia

(medial view). (B) Sub-periosteal new compact bone formation on the left first metatarsal (plantar view).

Fig. S5.2. Skeleton C35. Sub-periosteal new compact

bone formation with overlying woven bone on the right

fibula (medial view). Note the osteitic appearance and

that the distal head of the fibula was ankylosed with the

tibia before post-mortem breakage.

179

Fig. S5.4. Skeleton C227. (A) Plantar

view of the proximal phalanx of the right

tarsal digit I showing slight new porous

compact bone formation. (B) Lateral

view of the right calcaneus showing sub-

periosteal new compact bone formation.

Fig. S5.3. Skeleton C48. (A) Lateral view of the left

tibia showing diffuse, compact and striated sub-periosteal

new bone formation. Note the slightly osteitic

appearance in the distal to middle third of the diaphysis.

(B) Anterior aspect of the left fibula showing diffuse sub-

periosteal new bone formation. The new bone formation

is porous and compact. Note the osteitic appearance.

the diaphysis are affected most severely, with a slightly osteitic appearance in the distal

part laterally (Fig. S5.3A). Also the fibula exhibits diffuse subperiosteal new bone

formation, porous, compact and striated in appearance. The new bone formation is most

severe in the distal up to the middle part of the diaphysis, demonstrating osteitic

swelling (Fig. S5.3B).

Skeleton C227. This individual is badly preserved with only parts of the maxillae, parts

of the right lower limbs and part of the distal condyle of the femur present. Except

pitting of the palate, no rhinomaxillary changes suggestive of leprosy were recorded.

However, infectious alterations of the right foot that resulted in ankylosis of several

bones could be observed. New porous compact bone formation was also noted on the

right first metatarsal as well as on the calcaneus. The proximal phalanx of the right first

metatarsal, showing slight new porous compact bone formation (Fig. S5.4A), and the

distal part of the right calcaneus which, overall, showed new compact bone formation

(Fig. S5.4B), were chosen for DNA analysis.

Raunds. The late Anglo-Saxon church and churchyard of Raunds Furnells is situated in

East Northamptonshire, south of the River Nene. Excavation of the church and the

associated cemetery was conducted between 1977 and 1985 (Boddington, 1996). Based

on stratigraphic analyses and radiocarbon dating, the cemetery was in use from the

mid-10th until the late 11th or mid-12th centuries AD. Excavation of the graveyard

180

Fig. S5.5. Skeleton R5046.

Left fibula showing new

striated compact bone

formation.

recovered the remains of 363 individuals, most of these in a fairly good state of

preservation. Skeleton R5046 was buried on the southeastern edge of the graveyard

(zone 5), and R5256 in central zone 1. Both burials were orientated east-west with the

head directed westwards.

Skeleton R5046. This individual shows slight rhinomaxillary changes suggestive of

lepromatous leprosy. Bilateral pathological alterations in the lower limbs could further

be attributed to the disease. In particular, the left tibia shows sub-periosteal new

compact bone formation, partially striated and partially with overlying woven bone.

This sub-periosteal reaction is most severe on the lateral but also medial aspect of the

shaft. For the right tibia only a small plaque of new bone formation at the mid-shaft

medially could be recorded. New striated compact bone was also found on the left

fibula, spreading diffusely along the entire shaft. The distal shaft is affected most

severely and possesses a swollen osteitic appearance. For DNA analysis, the distal part

of the diaphysis of the fibula was selected (Fig. S5.5). As the proximal edge of this part

was treated with glue this area was removed before crushing of the bone.

Skeleton R5256. This skeleton presents a questionable case of leprosy. No pathological

alterations suggestive of rhinomaxillary syndrome could be observed. However, sub-

periosteal new bone formation as often seen in leprosy was found throughout the lower

extremities, including tibia and fibulae as well as the femora and bones of the right

foot. Sub-periosteal new bone formation was also found on the ossa coxae and on the

left scapula, skeletal elements that are usually not involved in leprous infection. For

DNA analysis, the distal third of the diaphysis of the left fibula showing sub-periosteal

new bone formation was selected (Fig. S5.6A). In addition, a window was excised and

collected from the antero-medial part of the distal diaphysis of the left tibia as this also

possessed sub-periosteal new bone formation (Fig. S5.6B). During the excision, a small

piece of new woven bone flaked off and was also tested for DNA.

181

Hereford. Hereford is located in the west of England, north of the River Wye. An

archaeological excavation was conducted on the southwest corner of the cathedral in

the summer of 1993 in preparation for construction of a new library to re-house the

historical treasures of Hereford cathedral (Stone and Appleton-Fox, 1996). The

excavation revealed parts of a cemetery associated with the cathedral that was in use

for much of the mediaeval period. As well a grave pit filled with the bones of an

estimated 5000 individuals, dated to the beginning 12th century, the excavation revealed

approximately 1100 additional individuals. These individuals were most likely buried

between the end of the 12th century and the closing down of the cemetery in the 16th

century when, according to historical documents, it became a garden. Many of the

skeletons are incomplete due to disturbances by later burials, including around 200

individuals excavated from three mass graves dating to the late 14th or early 15th

centuries who may have been victims of the plague. Individual H3726 was recovered

from the southeastern edge of cemetery, orientated in the east-west direction with the

head at the western end.

Skeleton H3726. This skeleton is badly preserved. Only fragments of the left lower

limb are present, comprising the femur, tibia and fibula. Both tibia and fibula show sub-

periosteal new bone formation diffusely spread along the entire diaphysis. For DNA

analysis, a piece of bone was cut from the distal part of the distal fragment of the

diaphysis of the tibia, which exhibits a patch of new bone formation on its lateral aspect

(Fig. S5.7A). A second sample was taken from the distal fragment of the diaphysis of

the fibula (Fig. S5.7B).

Fig. S5.6. Skeleton R5256. (A) Lateral view of the

diaphysis of the left fibula showing sub-periosteal new

bone formation. (B) Anterior view of the left tibia

exhibiting sub-periosteal new bone formation.

182

Fig. S5.7. Skeleton H3726. (A) Fragmented left tibia showing sub-periosteal new bone formation diffusely

spread along the entire diaphyses. Note the patch of new bone formation on the lateral aspect of the distal

diaphysis. (B) Fragmented left fibula exhibiting sub-periosteal new bone formation diffusely spread along the

diaphysis.

183

References

Boddington, A., 1996. Raunds Furnells: the Anglo-Saxon Church and Churchyard.

Archaeological Report 7, English Heritage.

Magilton. J., Lee, F., Boylston, A., 2008. ‘Lepers Outside the Gate’: Excavation at the

Cemetery of the Hospital of St James and St Mary Magdelene, Chichester, 1986-87

and 1993. CBA Research report 158, Council for British Archaeology, York.

Stone, R., Appleton-Fox, N., 1996. A View from Hereford's Past: a Report on the

Archaeological Excavation in Hereford Cathedral Close in 1993. Logaston Press,

Eardisley.

184

Supplementary Table S5.1

Detailed osteological report.

see Kerudin et al Table S1.xlsx.

185


Summary statistics for Illumina sequencing following enrichment of samples by in-solution

hybridization.

Statistic C21 C48 R5046

Non-duplicate reads mapped to M. leprae 174,013 150,929 437,081

Pairwise identity (%) 99.3 99.0 98.4

Mean depth of coverage 4.4 3.6 10

% of reference genome covered 71.8 73.4 86.6

186


Identities in the C21, C48 and R5046 genomes of the 215 SNPs known in modern M. leprae

strains.

SNP version C21 C48 R5046

Version in the M. leprae TN genome 76 72 64

Version not in the M. leprae TN genome 86 92 119

SNPs not covered in the ancient sequence 53 51 32

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Unique variations (highlighted in green) present in the C21, C48 and/or R5046 genomes.

Type Position in M. leprae

TN sequence

Variation

Locus

M. leprae TN C21 C48 R5046

Indel 202,441 (G)3 (G)3 (G)3 (G)2 ML0141

SNP 285,608 C C C A ML0214

SNP 389,111 C not covered T C Intergenic

SNP 523,366 G G not covered A RLEP

Indel 639,281 T(6) T(6) T(6) (T)7 Intergenic

SNP 698,809 G G G A ML0575

SNP 727,160 G T G G Intergenic

SNP 792,321 A A A T moxR3 (pseudogene)

SNP 865,934 C C C T ML0723 (pseudogene)

SNP 924,308 C C A C ML0779

SNP 938,796 G G A G ML0794 (pseudogene)

Indel 944,192 – A A A PPE (pseudogene)

SNP 954,575 G A G G ML0805 (pseudogene)

188

Indel 958,229 (C)2 (C)3 (C)3 (C)3 ML0809 (pseudogene)

SNP 1,288,067 G G G T ML1113

SNP 1,353,076 G G G A fadA4

SNP 1,445,832 C T C C Intergenic

SNP 1,451,503 T T not covered C RLEP

Indel 1,477,964 T T T – Intergenic

SNP 1,561,467 C C C G PPE (pseudogene)

SNP 1,605,242 A C A A ML1345 (pseudogene)

SNP 1,828,126 A A A G ML1514 (pseudogene)

Indel 1,849,027 (C)2 (C)3 (C)3 (C)3 PPE (pseudogene)

Indel 1,912,457 – C C C mpt53 (pseudogene)

Indel 2,127,771 – not covered not covered C Intergenic

SNP 2,330,059 T T T C Repeat region

SNP 2,470,760 C T C C ML2079 (pseudogene)

Indel 2,486,597 (T)8 (T)8 (T)8 (T)7 ML2090 (pseudogene)

SNP 2,568,277 G G G A Intergenic

SNP 2,615,157 A A A C Intergenic

SNP 2,710,194 A A A G ML2286 (pseudogene)

SNP 2,719,838 C C C T acS (pseudogene)

189

SNP 2,778,223 G C G G ML2340 (pseudogene)

SNP 2,796,573 C not covered C T ML2353

Indel 2,893,092 – T T T Intergenic

SNP 2,953,004 C C T C ML2478

Indel 3,100,774 (C)3 (C)4 (C)4 (C)4 Intergenic

SNP 3,164,216 C C C A Intergenic

SNP 3,221,222 T T T C ML2676 (pseudogene)

SNP 3,253,040 G A G G ML2699

SNP 3,263,734 C C T C ML2707

190

Chapter 6: Conclusion

Ancient DNA is recognised to be a very valuable tool in palaeopathology as it can not

only confirm the presence of diseases in the past but also shed light on the origin, spread

and evolution of palaeodiseases. Ancient DNA, albeit a fairly new field of research,

holds tremendous potential in understanding diseases in the past. The completed work

presented here contributes important insights in the study of tuberculosis and leprosy. It

highlights the danger of assuming the authenticity of a MTBC PCR fragment without

characterization by sequencing. Consequently, this raises questions about the specificity

of the PCR markers routinely used to confirm the presence of MTBC ancient DNA,

confirming the suspicion raised by a past study (Müller et al. 2016). This thesis serves as

a good reminder of the need to for stringent methods when using aDNA to perform

disease identification in palaeopathology. It also demonstrates the extent of exogenous

DNA presence in an archaeological sample acquired by microbial contamination

throughout the preservation years or even during sample handling. Furthermore, this

thesis presents an important addition to our knowledge of leprosy through the discovery

of a new M. leprae subtype that has never been reported in mediaeval England before.

This discovery sheds new light on the spread of leprosy to England in the past.

6.1 The extent to which the objectives have been addressed:

objective one (tuberculosis)

The first objective of this thesis was to determine whether the MTBC aDNA detection

frequency is high enough to plan a larger study to test hypotheses such as possible strain

differences in urban and rural areas. This objective was addressed by screening 60

archaeological bone samples collected from rural and urban locations in Yorkshire,

England, for the presence of MTBC aDNA. This work was done in two stages, the first

stage being the screening of MTBC aDNA presence using PCR assays and further

verification with Sanger sequencing. One sample from the 14th century AD, St Andrew

Fishergate 6, showed evidence of MTBC aDNA presence, supporting the osteological

observation of tuberculosis indicative lesions on the vertebrae and the ribs of this

skeleton. Fourteen other samples gave exact or near-length PCR fragments but none of

these matched the MTBC sequence, demonstrating the importance of sequence

authentication to verify MTBC aDNA presence in archaeological bones, and questioning

191

the specificity of the markers routinely used in MTBC aDNA detection, especially

IS6110 (Muller et al. 2016). However, inclusion of the nested IS6110 PCR increased the

specificity of detection for this marker in this study, as St Andrew Fishergate 6, was the

only sample that showed positive amplification in both the first step and nested PCR,

and was also the only sample whose amplified fragment matched the MTBC reference

sequence.

The second stage in the work addressing the first objective involved NGS of eight

selected samples from stage one, all of which were subjected to shotgun sequencing and,

in the case of St Andrew Fishergate 6 to additional enrichment using the hybridization

target method. The number of reads mapped to the M. tuberculosis reference sequence

after shotgun sequencing was between 0.0052-0.1931% of the total. These low

percentages indicate that a large portion of the sequencing capacity is dominated by the

environmental DNA, as revealed by taxonomical classification of the reads. This study

suggests that the shotgun approach might be better suited for much better-preserved

archaeological specimens, for example, naturally mummified remains (Sabin et al.

2020). However, the hybridization capture target enrichment procedure did not

significantly increase the percentage MTBC reads for St Andrew Fishergate 6, although

the parallel M. leprae capture carried out with this sample provided M. leprae reads,

suggesting a possible mixed infection between the two pathogens. Mixed infection has

been reported in much earlier cases (Donoghue et al. 2005) than St Andrew Fishergate 6

(early 14th century AD).

In summary, the MTBC aDNA detection frequency obtained in this study was not high

enough to enable a larger scale study to be planned to test hypotheses such as possible

strain differences in urban and rural areas in historic Yorkshire. The negative results

could be due the preservation conditions resulting in a high amount of aDNA

breakdown, or possibly the bacterial load (the number of MTBC bacteria present in the

bone) at time of death was low, in which case even under good preservation conditions

there might not be enough aDNA to detect. Another possibility is that M. tuberculosis

was not be present in some of the samples. Thirty eight samples with lesions associated

with tuberculosis gave no evidence of MTBC aDNA. Although these results cannot be

used to completely refute the probability of these individuals ever being infected with

tuberculosis, they suggest that a differential diagnosis should also be considered for

these skeletal remains.

192

6.2 The extent to which the objectives have been addressed:

objective two (leprosy)

The second objective of the thesis was to use NGS to determine the genotype of the M.

leprae strains present in skeletons from two mediaeval sites, at Chichester and Raund

Furnells, both in England. This objective was addressed by typing the polymorphic sites

within the M. leprae genome to determine the strain and diversity of the ancient samples

previously suggested to contain M. leprae aDNA through PCR screening. Near complete

whole genome sequences were generated by target enrichment NGS allowing the

genotypes of three historical M. leprae isolates to be determined. The two isolates from

Chichester belonged to the typical European subtype – 3I. Meanwhile, the first 3K

subtype, dating to the 10th to mid-12th century AD, from historical M. leprae samples in

Britain is reported here. Based on the phylogeographic scheme of M. leprae isolates, the

transmission of the 3K subtype was suggested to be associated with the travels of

crusaders and pilgrims to the Holy Land during the mediaeval period.

6.3 Limitations of the thesis and future work

This study was not without its challenges and limitations. The main limitation arose

from the very nature of ancient DNA itself. As previously explained, physical and

chemical damages exerted on the bone remains during their preservation history will

cause DNA fragmentation, resulting in short fragments which could be missed during

the DNA extraction. This will subsequently lead to insufficient amounts of template for

PCR amplification and NGS. Skeleton remains recovered from grave burials are also at

high risk of environmental contamination that may interfere with PCR and NGS

analysis. This burial method allows close contact of skeletons to soil, and hence the

accumulation of soil microorganisms within the bones over time during the preservation

period. As demonstrated from the tuberculosis NGS results, this type of environmental

contamination leads to the sequences being dominated by exogenous bacteria, so there

are very few authentic aDNA reads.

DNA fragmentation and contamination of samples with environmental bacteria were not

limitations in addressing the second objective of the thesis. Each of the three samples

that had previously tested positive with M. leprae PCRs gave enough NGS sequences to

allow polymorphic sites in the M. leprae genome to be typed and the strains identified.

193

These results suggest that it is worth while carrying out future work using NGS to type

M. leprae aDNA with samples showing indications of leprosy, and the results of this

work could add more information on the strains of leprosy present in mediaeval Britain,

and tell more about how leprosy spread to Britain. The success in obtaining M. leprae

genome sequences reported in this thesis appears to agree with previous work (e.g.

Schuenemann et al. 2013, 2018) where a high proportion of bones showing indications

of leprosy could be sequenced, but it is difficult to make a comparison because negative

results are not often published.

The complications caused by DNA fragmentation and contamination did limit the

conclusions that could be drawn with regard to the first objective. Only one of 60

samples gave authentic MTBC sequences after PCR, and none of the eight samples that

were tested by NGS gave enough sequences for genome comparisons. Because negative

results are not often published, it is difficult to compare the high degree of negative

results reported in this thesis with other work, although Müller et al. (2014a) had

negative results with 43 of 77 British and European samples (1st-19th centuries AD)

tested by PCR. The limitation is that it was not possible to determine if the high

proportion of negative results is due to problems with the preservation and

contamination of the samples, or the absence of MTBC aDNA due to low bacterial load

at time of death. It would be interesting in future projects to compare hybridization

capture of both MTBC and human aDNA with the same samples, to see if the degree of

preservation of the two types of aDNA are comparable. If samples with good human

aDNA preservation still give negative results when tested for MTBC aDNA, then it

would suggest that the MTBC bacterial load in the samples was too low for aDNA

detection.

6.4 Ethical issues raised by this work

Naturally, in order to achieve the higher number of M. tuberculosis aDNA detections

needed to test hypotheses such as differences between strains in urban and rural

communities, more archaeological specimens could be used. However, the main ethical

concern in ancient DNA study, which is destructive sampling, should not be ignored

(Kaestle & Horsburgh 2002; Wilbur et al. 2009). Archaeological bone materials are seen

as historically precious due to their irreplaceable nature, and therefore should be

194

protected properly. Inevitably, the study of aDNA is destructive, because it requires part

of the skeleton to be taken and crushed. One of the recommendations to address this

issue is to only study the samples with the highest likeliness to yield positive results

(Kaestle & Horsburgh 2002). However, in an MTBC study, satisfying this requirement

is complicated by the fact that only 3-5% of active tuberculosis infections result in

skeletal manifestation (Roberts & Buikstra 2003).

Ancient DNA is still a fairly new interdisciplinary field, with the first ancient DNA

extraction performed only 36 years ago (Higuchi et al. 1984). Understandably, more

work is needed in order to “perfect” the way of studying ancient DNA without

compromising the ethical issues. Destructive analysis is obviously a valid concern, but

the tremendous potential of ancient DNA should not be ignored. However, the results

presented in this thesis suggest that in future studies, sample selection should be made

more stringent, so that valuable material is not needlessly destroyed. In previous studies,

M. tuberculosis aDNA has been successfully isolated from bones without lesions (Baron

et al. 1996; Müller et al. 2014a). One of the ways to address the concerns about

destruction would therefore be to sample bones that are available in a large number in

the skeleton, such as ribs, even if these do not themselves show lesions. If this approach

is combined with use only of skeletons with tuberculosis pathognomonic lesions, or

from sites with clear historical reports or evidences of tuberculosis, then it might be

possible to obtain sufficient MTBC NGS results for large scale studies, without

destroying large amounts of important material. To do this, it is important for historians,

osteologists, and molecular biologists to communicate with one another and to work

together to fill in the gaps in this field of research (Brown and Brown 1992; Squires et

al. 2019).

195

References

Abu Al-Soud, W. & Rådström, P., 2000, ‘Effects of amplification facilitators on

diagnostic PCR in the presence of blood, feces, and meat.’, Journal of Clinical

Microbiology, 38(12), 4463–70.

Adachi, N., Suzuki, T., Sakaue, K., Takigawa, W., Ohshima, N. & Dodo, Y., 2006,

‘Kinship analysis of the Jomon skeletons unearthed from a double burial at the

Usu-Moshiri site, Hokkaido, Japan’, Anthropological Science, 114(1), 29–34.

Adams, M., 1996, 'Excavation of pre-conquest cemetery at Addingham, West

Yorkshire', Medieval Archaeology, 40(1), 151-191.

Addyman, P.V., 1980, ‘Eburacum, Jorvik, York’, Scientific American, 242(3), 76-87.

Agarwal, S., Hunnicutt, D.W. & McBride, M.J., 1997, ‘Cloning and characterization of

the Flavobacterium johnsoniae (Cytophaga johnsonae) gliding motility gene,

gldA.’, Proceedings of the National Academy of Sciences of the United States of

America, 94(22), 12139–44.

Allison, M.J., Gerszten, E., Munizaga, J., Santoro, C. & Mendoza, D., 1981,

Tuberculosis in Pre-Columbian Andean populations, in Buikstra J.E. (ed.),

Prehistoric tuberculosis in the Americas, 49–61, Northwestern University

Archaeological Program, Evanston Illinois.

Alonso, H., Samper, S., Martín, C. & Otal, I., 2013, ‘Mapping IS6110 in high-copy

number Mycobacterium tuberculosis strains shows specific insertion points in the

Beijing genotype’, BMC Genomics, 14(1), 422.

Andersen, J.G. & Manchester, K., 1992, ‘The rhinomaxillary syndrome in leprosy: A

clinical, radiological and palaeopathological study’, International Journal of

Osteoarchaeology, 2(2), 121–129.

Ankad, B.S., 2018, ‘Dermoscopy of borderline tuberculoid leprosy’, International

Journal of Dermatology, 57, 74–76.

Arguello, E., Otto, C.C., Mead, P. & Babady, N.E., 2015, ‘Bacteremia caused by

Arcobacter butzleri in an immunocompromised host’, Journal of Clinical

microbiology, 53(4), 1448–51.

Armstrong, A., 1974, Stability and change in an English county town: a social study of

York 1801-51, Cambridge University Press, New York USA.

Atkins, P., 2008, ‘Fear of animal foods: a century of zoonotics.’, Appetite, 51(1), 18–21.

Atkins, P.J., 2000, Milk consumptions and tuberculosis in Britain, 1850-1950, in Fenton

A. (ed.), Order and disorder: the health implications of eating and drinking in the

nineteenth and tweentieth centuries, 83–95, Tuckwell Press, East Linton.

Avanzi, C., Del-Pozo, J., Benjak, A., Stevenson, K., Simpson, V.R., Busso, P.,

McLuckie, J., Loiseau, C., Lawton, C., Schoening, J., Shaw, D.J., Piton, J., Vera-

Cabrera, L., Velarde-Felix, J.S., McDermott, F., Gordon, S. V., Cole, S.T. &

Meredith, A.L., 2016, ‘Red squirrels in the British Isles are infected with leprosy

bacilli’, Science, 354(6313), 744–747.

Ankad, B.S., Hombal, A., Rao, S. & Naidu, V.M., 2011, 'Radiological changes in the

hands and feet of leprosty patients with deformities', Journal of Clinical and

Diagnostic Research, 5(4), 703-707.

Barberis, I., Bragazzi, N.L., Galluzzo, L. & Martini, M., 2017, ‘The history of

tuberculosis: from the first historical records to the isolation of Koch’s bacillus’,

Journal of Preventive Medicine and Hygiene, 58, E9–E12.

196

Barka, E.A., Vatsa, P., Sanchez, L., Gaveau-Vaillant, N., Jacquard, C., Meier-Kolthoff,

J.P., Klenk, H.-P., Clément, C., Ouhdouch, Y. & van Wezel, G.P., 2016,

‘Taxonomy, physiology, and natural products of Actinobacteria’, Microbiology and

Molecular Biology Reviews, 80(1), 1–43.

Barnes, I. & Thomas, M.G., 2006, ‘Evaluating bacterial pathogen DNA preservation in

museum osteological collections’, Proceedings of the Royal Society of London B:

Biological Sciences, 273(1587), 645–53.

Barnetson, J., 1951, 'Pathogenesis of bone changes in neural leprosy', International

Journal of Leprosy, 19(3), 297-307.

Baron, H., Hummel, S. & Herrmann, B., 1996, ‘Mycobacterium tuberculosis complex

DNA in ancient human bones’, Journal of Archaeological Science, 23, 667-671.

Bartlett, R., 2000, England under the Norman and Angevin Kings 1075 – 1225, Oxford

University Press, Oxford United Kingdom.

Becker, K., Rutsch, F., Uekotter, A., Kipp, F., Konig, J., Marquardt, T., Peters, G. & von

Eiff, C., 2008, ‘Kocuria rhizophila adds to the emerging spectrum of Micrococcal

species involved in human infections’, Journal of Clinical Microbiology, 46(10),

3537–3539.

Beckman Coulter, 2012, SPRIselect User Guide.

Bennett, B.H., Parker, D.L. & Robson, M., 2008, ‘Leprosy: steps along the journey of

eradication’, Public Health Reports , 123(2), 198–205.

Bobosha, K., Wilson, L., van Meijgaarden, K.E., Bekele, Y., Zewdie, M., van der Ploeg-

van Schip, J.J., Abebe, M., Hussein, J., Khadge, S., Neupane, K.D., Hagge, D.A.,

Jordanova, E.S., Aseffa, A., Ottenhoff, T.H.M. & Geluk, A., 2014, ‘T-Cell

regulation in lepromatous leprosy’, PLoS Neglected Tropical Diseases, 8(4), e2773.

Bos, K.I., Harkins, K.M., Herbig, A., Coscolla, M., Weber, N., Comas, I., Forrest, S.A.,

Bryant, J.M., Harris, S.R., Schuenemann, V.J., Campbell, T.J., Majander, K.K.,

Wilbur, A.K., Guichon, R.A., Wolfe Steadman, D.L., Cook, D.C., Niemann, S.,

Behr, M.A., Zumarraga, M., Bastida, R., Huson, D., Nieselt, K., Young, D.,

Parkhill, J., Buikstra, J.E., Gagneux, S., Stone, A.C. & Krause, J., 2014, ‘Pre-

Columbian Mycobacterial genomes reveal seals as a source of New World human

tuberculosis’, Nature, 514(7523), 494–497.

Bouwman, A.S., Kennedy, S.L., Müller, R., Stephens, R.H., Holst, M., Caffell, A.C.,

Roberts, C.A. & Brown, T.A., 2012, ‘Genotype of a historic strain of

Mycobacterium tuberculosis’, Proceedings of the National Academy of Sciences of

the United States of America, 109(45), 18511–18516.

Breitwieser, F.P., Lu, J. & Salzberg, S.L., 2019, ‘A review of methods and databases for

metagenomic classification and assembly’, Briefings in Bioinformatics, 20(4),

1125-1136.

Briggs, A.W., Stenzel, U., Johnson, P.L.F., Green, R.E., Kelso, J., Prüfer, K., Meyer, M.,

Krause, J., Ronan, M.T., Lachmann, M. & Pääbo, S., 2007, ‘Patterns of damage in

genomic DNA sequences from a Neandertal’, Proceedings of the National

Academy of Sciences, 104(37), 14616–14621.

Brites, D. & Gagneux, S., 2015, ‘Co-evolution of Mycobacterium tuberculosis and

Homo sapiens’, Immunological Reviews, 264(1), 6–24.

197

Brosch, R., Gordon, S. V., Marmiesse, M., Brodin, P., Buchrieser, C., Eiglmeier, K.,

Garnier, T., Gutierrez, C., Hewinson, G., Kremer, K., Parsons, L.M., Pym, A.S.,

Samper, S., van Soolingen, D. & Cole, S.T., 2002, ‘A new evolutionary scenario

for the Mycobacterium tuberculosis complex’, Proceedings of the National

Academy of Sciences of the United States of America, 99(6), 3684–3689.

Brown‐Elliott, B.A., Wallace Jr., R.J., Blinkhorn, R., Crist, C.J. & Mann, L.B., 2001,

‘Successful treatment of disseminated Mycobacterium chelonae infection with

Linezolid’, Clinical Infectious Diseases, 33(8), 1433–1434.

Brown, T.A. & Barnes, I.M., 2015, ‘The current and future applications of ancient DNA

in quaternary science’, Journal of Quaternary Science, 30(2), 144–153.

Brown, T.A. & Brown, K.A., 1992, ‘Ancient DNA and the archaeologist’, Antiquity,

66(250), 10–23.

Brown, T.A. & Brown, K.A, 2011, Biomolecular acrhaeology: an introduction, John

Wiley & Sons Ltd, West Sussex United Kingdom.

Burger, J., Hummel, S., Hermann, B. & Henke, W., 1999, ‘DNA preservation: a

microsatellite-DNA study on ancient skeletal remains’, Electrophoresis, 20(8),

1722–1728.

Cadet, J. & Wagner, J.R., 2013, ‘DNA base damage by reactive oxygen species,

oxidizing agents, and UV radiation’, Cold Spring Harbor Perspectives in Biology,

5(2), a012559–a012559.

Caffell, A. & Holst, M., 2008a, ‘Osteological analysis: Melton A63 East Yorkshire’,

York Osteoarchaeology No. 0507, Unpublished.

Caffell, A. & Holst, M., 2008b, ‘Osteological analysis: St Peter's Church, Huddersfield,

West Yorkshire’, York Osteoarchaeology No. 0508, Unpublished.

Caffell, A. & Holst, M., 2012, ‘Osteological analysis: 3 and 6 Driffield Terrace, York,

North Yorkshire', York Osteoarchaeology No. 0212. Unpublished.

Campbell, I.A. & Bah-Sow, O., 2006, ‘Pulmonary tuberculosis: diagnosis and

treatment’, British Medical Journal, 332, 1194–1197.

Canci, A., Minozzi, S. & Borgognini Tarli, S.M., 1996, ‘New evidence of tuberculous

spondylitis from Neolithic Liguria (Italy)’, International Journal of

Osteoarchaeology 6, 497–501.

Cardona, P.-J. & Ruiz-Manzano, J., 2004, ‘On the nature of Mycobacterium

tuberculosis-latent bacilli’, The European Respiratory Journal, 24(6), 1044–51.

Cardwell, P., Chundun, Z., Costley, S., Hall, J., Hanson, J., Huntley, J., Jamfrey, C.,

Maxwell, R., Speed, G., Simpson, R. & Stallibrass, S., 1995, 'Excavation of the

hospital of St Giles by Brompton Bridge, North Yorkshire', Archaeological Journal

152, 109-245.

CDC, 2013, Chapter 2: Transmission and pathogensis of tuberculosis, in Core

curriculum on tuberculosis: what the clinician should know (6th edn.), 19–44,

Centers for Disease Control and Prevention, Atlanta Georgia, USA.

Chalke, H.D., 1962, ‘The impact of tuberculosis on history, literature and art’, Medical

History, 6(4), 301–18.

Chan, J.Z.-M., Sergeant, M.J., Lee, O.Y.-C., Minnikin, D.E., Besra, G.S., Pap, I.,

Spigelman, M., Donoghue, H.D. & Pallen, M.J., 2013, ‘Metagenomic analysis of

tuberculosis in a mummy’, New England Journal of Medicine, 369(3), 289–290.

198

Cock, P.J.A., Fields, C.J., Goto, N., Heuer, M.L. & Rice, P.M., 2010, ‘The Sanger

FASTQ file format for sequences with quality scores, and the Solexa/Illumina

FASTQ variants’, Nucleic Acids Research, 38(6), 1767–71.

Cole, S.T., Eiglmeier, K., Parkhill, J., James, K.D., Thomson, N.R., Wheeler, P.R.,

Honoré, N., Garnier, T., Churcher, C., Harris, D., Mungall, K., Basham, D., Brown,

D., Chillingworth, T., Connor, R., Davies, R.M., Devlin, K., Duthoy, S., Feltwell,

T., Fraser, A., Hamlin, N., Holroyd, S., Hornsby, T., Jagels, K., Lacroix, C.,

Maclean, J., Moule, S., Murphy, L., Oliver, K., Quail, M.A., Rajandream, M.A.,

Rutherford, K.M., Rutter, S., Seeger, K., Simon, S., Simmonds, M., Skelton, J.,

Squares, R., Squares, S., Stevens, K., Taylor, K., Whitehead, S., Woodward, J.R. &

Barrell, B.G., 2001, ‘Massive gene decay in the leprosy bacillus’, Nature, 409,

1007–1011.

Comas, I., Coscolla, M., Luo, T., Borrell, S., Holt, K.E., Parkhill, J., Malla, B., Berg, S.,

Thwaites, G., Yeboah-Manu, D., Bothamley, G., Mei, J., Wei, L., Bentley, S.,

Harris, S.R., Niemann, S., Diel, R., Aseffa, A., Gao, Q., Young, D. & Gagneux, S.,

2013, ‘Out-of-Africa migration and Neolithic co-expansion of Mycobacterium

tuberculosis with modern humans’, Nature Genetics, 45(10), 1176–1182.

Comas, I. & Gagneux, S., 2011, ‘A role for systems epidemiology in tuberculosis

research’, Trends in Microbiology, 19(10), 492–500.

Coros, A., DeConno, E. & Derbyshire, K.M., 2008, ‘IS6110, a Mycobacterium

tuberculosis complex-specific insertion sequence, is also present in the genome of

Mycobacterium smegmatis, suggestive of lateral gene transfer among mycobacterial

species’, Journal of Bacteriology, 190(9), 3408–10.

Cruz-Dávalos, D.I., Nieves-Colón, M.A., Sockell, A., Poznik, G.D., Schroeder, H.,

Stone, A.C., Bustamante, C.D., Malaspinas, A.-S. & Ávila-Arcos, M.C., 2018, ‘In-

solution Y-chromosome capture-enrichment on ancient DNA libraries’, BMC

Genomics, 19(1), 608.

Dabney, J., Knapp, M., Glocke, I., Gansauge, M.-T., Weihmann, A., Nickel, B.,

Valdiosera, C., García, N., Pääbo, S., Arsuaga, J.-L. & Meyer, M., 2013, ‘Complete

mitochondrial genome sequence of a middle Pleistocene cave bear reconstructed

from ultrashort DNA fragments’, Proceedings of the National Academy of Sciences

of the United States of America, 110(39), 15758–15763.

Dabney, J., Meyer, M. & Pääbo, S., 2013, ‘Ancient DNA damage’, Cold Spring Harbor

Perspectives in Biology, 5(7), a012567.

Daniel, T.M., 2006, ‘The history of tuberculosis’, Respiratory Medicine, 100(11), 1862–

1870.

Daniel, V.S. & Daniel, T.M., 1999, ‘Old Testament biblical references to tuberculosis’,

Clinical Infectious Diseases, 29(6), 1557–1558.

Davies, P.D.O., 1998, ‘A little history of tuberculosis’, 3–10. Available at:

http://www.evolve360.co.uk/Data/10/Docs/19/19Davies.pdf.

Davies, R.P.O., Tocque, K., Bellis, M.A., Remmington, T. & Davies, P.D.O., 1999,

‘Historical declines in tuberculosis in England and Wales: improving social

conditions or natural selection?’, The International Journal of Tuberculosis and

Lung Disease, 3(12), 1051-1054.

Davis, G.L., Ray, N.A., Lahiri, R., Gillis, T.P., Krahenbuhl, J.L., Williams, D.L. &

Adams, L.B., 2013, ‘Molecular assays for determining Mycobacterium leprae

viability in tissues of experimentally infected mice’, PLoS Neglected Tropical

Diseases, 7(8), e2404.

http://www.evolve360.co.uk/Data/10/Docs/19/19Davies.pdf

199

Dawes, J.D. & Magilton, J., 1980, ‘The Cemetery of St. Helen-on-the-Walls, Aldwark.

12/1’, York: Council for British Archaeology.

de Lima Procópio, R.E. de, Silva, I.R. da, Martins, M.K., Azevedo, J.L. de & Araújo,

J.M. de, 2012, ‘Antibiotics produced by Streptomyces’, The Brazilian Journal of

Infectious Diseases, 16(5), 466–471.

de Luca, G., Barakat, M., Ortet, P. Fochesato, S., Jourlin-Castelli, C., Ansaldi, M., Py,

B., Fichant, G., Coutinho, P.M., Voulhoux, R., Bastien, O., Maréchal, E., Henrissat,

B., Quentin, Y., Noirot, P., Filloux, A., Méjean,V., DuBow, M.S., Barras, F.,

Barbe, V., Weissenbach, J., Michalcescu, I., Verméglio, A., Anchouak, W. &

Heulin, T., 2011, ‘The cyst-dividing bacterium Ramlibacter tataouinensis TTB310

genome reveals a well-stocked toolbox for adaptation to a desert environment’,

PLoS ONE, 6(9), e23784.

Dent, J.S., 1984, Wetwang Slack: an Iron Age cemetery on the Yorkshire Wolds, M. Phil

dissertation, University of Sheffield.

Der Sarkissian, C., Ermini, L., Jonsson, H., Alekseev, A.N., Crubezy, E., Saphiro, B. &

Orlando, L., 2014, 'Shotgun microbial profiling of fossil remains', Molecular

Ecology, 23, 1780-1798.

de Wit, M.Y., Douglas, J.T., McFadden, J. & Klatser, P.R., 1993, ‘Polymerase chain

reaction for detection of Mycobacterium leprae in nasal swab specimens’, Journal

of Clinical Microbiology, 31(3), 502–6.

Dharmendra, 1947, ‘Leprosy in ancient Indian medicine’, International Journal of

Leprosy, 15(4), 424–430.

Donoghue, H.D., 2011, ‘Insights gained from palaeomicrobiology into ancient and

modern tuberculosis’, Clinical Microbiology and Infection, 17(6), 821–829.

Donoghue, H.D., Holton, J. & Spigelman, M., 2001, ‘PCR primers that can detect low

levels of Mycobacterium leprae DNA’, Journal of Medical Microbiology, 50, 177–

182.

Donoghue, H.D., Marcsik, A., Matheson, C., Vernon, K., Nuorala, E., Molto, J.E.,

Greenblatt, C.L. & Spigelman, M., 2005, ‘Co-infection of Mycobacterium

tuberculosis and Mycobacterium leprae in human archaeological samples: a

possible explanation for the historical decline of leprosy’, Proceedings of the Royal

Society of London B: Biological Sciences, 272(1561), 389–394.

Donoghue, H.D., Spigelman, M., O’Grady, J., Szikossy, I., Pap, I., Lee, O.Y.-C., Wu,

H.H.T., Besra, G.S. & Minnikin, D.E., 2015, ‘Ancient DNA analysis – An

established technique in charting the evolution of tuberculosis and leprosy’,

Tuberculosis, 95, S140–S144.

Dzierzykray-Rogalski, T., 1980, ‘Paleopathology of the Ptolemaic inhabitants of

Dakhleh Oasis (Egypt)’, Journal of Human Evolution, 9(1), 71–74.

Eiglmeier, K., Parkhill, J., Honoré, N., Garnier, T., Tekaia, F., Telenti, A., Klatser, P.,

James, K.D., Thomson, N.R., Wheeler, P.R., Churcher, C., Harris, D., Mungall, K.,

Barrell, B.G. & Cole, S.T., 2001, ‘The decaying genome of Mycobacterium

leprae.’, Leprosy Review, 72(4), 387–98.

Eisenach, K.D., Cave, M.D., Bates, J.H. & Crawford, J.T., 1990, ‘Polymerase chain

reaction amplification of a repetitive DNA sequence specific for Mycobacterium

tuberculosis.’, The Journal of Infectious Diseases, 161(5), 977–81.

200

Fernández-Roblas, R., Esteban, J., Cabria, F., López, J.C., Jiménez, M.S. & Soriano, F.,

2000, ‘In vitro susceptibilities of rapidly growing mycobacteria to telithromycin

(HMR 3647) and seven other antimicrobials’, Antimicrobial Agents and

Chemotherapy, 44(1), 181–2.

Feuillie, C., Merheb, M.M., Gillet, B., Montagnac, G., Daniel, I. & Hänni, C., 2014,

‘Detection of DNA sequences refractory to PCR amplification using a biophysical

SERRS assay (Surface Enhanced Resonant Raman Spectroscopy)’, PloS ONE,

9(12), e114148.

Filliol, I., Motiwala, A.S., Cavatore, M., Qi, W., Hazbón, M.H., del Valle, M.B, Fyfe, J.,

García-garcía, L., Rastogi, N., Sola, C., Zozio, T., Guerrero, M.I., León, C.I.,

Crabtree, J., Angiuoli, S., Eisenach, K.D., Durmaz, R., Joloba, M.L., Rendón, A.,

Sifuentes-Osornio, J., de León, A.P., Cave, M.D., Fleischmann, R., Whittam, T.S.

& Alland, D., 2006, ‘Global phylogeny of Mycobacterium tuberculosis based on

Single Nucleotide Polymorphism ( SNP ) analysis : insights into tuberculosis

evolution, phylogenetic accuracy of other DNA fingerprinting systems, and

recommendations for a minimal standard SNP Set’, Journal of Bacteriology,

188(2), 759-772.

Firth, J., 2014, ‘History of tuberculosis part 1 - phthisis, consumption and the white

plague’, History, 22(2), 29–35.

Flesch, I.E.A. & Kaufmann, H.E., 1993, ‘Role of cytokines in tuberculosis’,

Immunobiology, 189, 316–339.

Forbes, B.A. & Hicks, K.E., 1996, ‘Substances interfering with direct detection of

Mycobacterium tuberculosis in clinical specimens by PCR: effects of bovine serum

albumin’, Journal of Clinical Microbiology, 34(9), 2125–8.

Forrellad, M.A., Klepp, L.I., Gioffré, A., y García, J.S., Morbidoni, H.R., de la Paz

Santangelo, M., Cataldi, A.A. & Bigi, F., 2013, ‘Virulence factors of the

Mycobacterium tuberculosis complex’, Virulence, 4(1), 3–66.

Ghosh, S. & Chaudhuri, S., 2015, ‘Chronicles of Gerhard-Henrik Armauer Hansen’s life

and work’, Indian Journal of Dermatology, 60(3), 219–21.

Gilbert, M.T.P., Hansen, A.J., Willerslev, E., Rudbeck, L., Barnes, I., Lynnerup, N. &

Cooper, A., 2003, ‘Characterization of genetic miscoding lesions caused by

postmortem damage’, American Journal of Human Genetics, 72(1), 48–61.

Gilbert, M.T.P., Tomsho, L.P., Rendulic, S., Packard, M., Drautz, D.I., Sher, A.,

Tikhonov, A., Dalen, L., Kuznetsova, T., Kosintsev, P., Campos, P.F., Higham, T.,

Collins, M.J., Wilson, A.S., Shidlovskiy, F., Buigues, B., Ericson, P.G.P.,

Germonpre, M., Gotherstrom, A., Iacumin, P., Nikolaev, V., Nowak-Kemp, M.,

Willerslev, E., Knight, J.R., Irzyk, G.P., Perbost, C.S., Fredrikson, K.M., Harkins,

T.T., Sheridan, S., Miller, W. & Schuster, S.C., 2007, ‘Whole-genome shotgun

sequencing of mitochondria from ancient hair shafts’, Science, 317(5846), 1927–

1930.

Golden, M.P. & Vikram, H.R., 2005, ‘Extrapulmonary tuberculosis: an overview',

American Family Physician, 72(9), 1761–1768.

Gomez-Valero, L., Rocha, E.P.C., Latorre, A. & Silva, F.J., 2007, ‘Reconstructing the

ancestor of Mycobacterium leprae: the dynamics of gene loss and genome

reduction’, Genome Research, 17, 1178–1185.

Gordon, S.V, Brosch, R., Billault, A., Garnier, T., Eiglmeier, K. & Cole, S.T., 1999,

‘Identification of variable regions in the genomes of tubercle bacilli using bacterial

artificial chromosome arrays’, Molecular Microbiology, 32(3), 643–55.

https://pubmed.ncbi.nlm.nih.gov/?term=Ponce+de+Le%C3%B3n+A&cauthor_id=16385065

201

Green, E.J. & Speller, C.F., 2017, ‘Novel substrates as sources of ancient DNA:

prospects and hurdles’, Genes, 8(7), 180.

Green, R.E., Malaspinas, A.-S., Krause, J., Briggs, A.W., Johnson, P.L.F., Uhler, C.,

Meyer, M., Good, J.M., Maricic, T., Stenzel, U., Prüfer, K., Siebauer, M., Burbano,

H.A., Ronan, M., Rothberg, J.M., Egholm, M., Rudan, P., Brajković, D., Kućan, Ž.,

Gušić, I., Wikström, M., Laakkonen, L., Kelso, J., Slatkin, M. & Pääbo, S., 2008,

‘A complete Neandertal mitochondrial genome sequence determined by high-

throughput sequencing’, Cell, 134(3), 416–426.

Groathouse, N.A., Brown, S.E., Knudson, D.L., Brennan, P.J. & Slayden, R.A., 2006,

‘Isothermal amplification and molecular typing of the obligate intracellular

pathogen Mycobacterium leprae isolated from tissues of unknown origins’, Journal

of Clinical Microbiology, 44(4), 1502–1508.

Gron, K., 1973, ‘Leprosy in literature and art’, International Journal of Leprosy, 41(2),

249–283.

Gruber, K., 2015, ‘Here, there, and everywhere: from PCRs to next-generation

sequencing technologies and sequence databases, DNA contaminants creep in from

the most unlikely places’, EMBO Reports, 16(8), 898–901.

Grzybowski, A. & Nita, M., 2016, ‘Leprosy in the bible’, Clinics in Dermatology, 34, 3–

7.

Gunatilake, S.B. & Settinayake, S., 2004, ‘Lepsory’, Practical Neurology, 4, 194–203.

Gunawan, H., Haryati, N.S. & Suwarsa, O., 2017, 'Swan neck deformity mimicking

claw hand caused by arthritis in leprosy', Case Reports in Dermatology, 9(3), 231-

235.

Gupta, R.S., Lo, B. & Son, J., 2018, ‘Phylogenomics and comparative genomic studies

robustly support division of the genus Mycobacterium into an emended genus

Mycobacterium and four novel genera’, Frontiers in Microbiology, 9, 67.

Gutierrez, M.C., Brisse, S., Brosch, R., Fabre, M., Omaïs, B., Marmiesse, M., Supply, P.

& Vincent, V., 2005, ‘Ancient origin and gene mosaicism of the progenitor of

Mycobacterium tuberculosis’, PLoS Pathogens, 1(1), e5.

Haas, C.J., Zink, A., Palfi, G., Szeimies, U. & Nerlich, A.G., 2000, ‘Detection of leprosy

in ancient human skeletal remains by molecular identification of Mycobacterium

leprae’, American Journal of Clinical Pathology, 114, 428–436.

Hall, R.A. & Whyman, M., 1996, 'Settlement and Monasticism at Ripon, North

Yorkshire, from the 7th to 11th Centuries A.D.', Medieval Archaeology, 40(1), 62-

150.

Hagelberg, E. & Clegg, J.B., 1991, ‘Isolation and characterization of DNA from

archaeological bone.’, Proceedings of the Royal Society of London B: Biological

Sciences, 244(1309), 45–50.

Han, C., Spring, S., Lapidus, A., Rio, T.G. Del, Tice, H., Copeland, A., Cheng, J.-F.,

Lucas, S., Chen, F., Nolan, M., Bruce, D., Goodwin, L., Pitluck, S., Ivanova, N.,

Mavromatis, K., Mikhailova, N., Pati, A., Chen, A., Palaniappan, K., Land, M.,

Hauser, L., Chang, Y.-J., Jeffries, C.C., Saunders, E., Chertkov, O., Brettin, T.,

Göker, M., Rohde, M., Bristow, J., Eisen, J.A., Markowitz, V., Hugenholtz, P.,

Kyrpides, N.C., Klenk, H.-P. & Detter, J.C., 2009, ‘Complete genome sequence of

Pedobacter heparinus type strain (HIM 762-3T)’, Standards in Genomic Sciences,

1(1), 54–62.

202

Han, X.Y., Seo, Y.H., Sizer, K.C., Schoberle, T., May, G.S., Spencer, J.S., Li, W. &

Nair, R.G., 2008, ‘A new Mycobacterium species causing diffuse lepromatous

leprosy’, American Journal of Clinical Pathology, 130(6), 856–864.

Hartskeerl, R.A., de Wit, M.Y.L. & Klatser, P.R., 1989, ‘Polymerase chain reaction for

the detection of Mycobacterium leprae', Microbiology, 135(2357–2364).

Hershberg, R., Lipatov, M., Small, P.M., Sheffer, H., Niemann, S., Homolka, S., Roach,

J.C., Kremer, K., Petrov, D.A, Feldman, M.W. & Gagneux, S., 2008, ‘High

functional diversity in Mycobacterium tuberculosis driven by genetic drift and

human demography’, PLoS Biology, 6(12), e311.

Hershkovitz, I., Arensburg, B. & Speirs, M., 1993, 'Leprosy or madura foot? The

ambigious nature of infectious disease in palaeopathology: reply to Dr.

Manchester', American Journal of Physical Anthropology', 91, 251-253.

Hershkovitz, I., Donoghue, H.D., Minnikin, D.E., Besra, G.S., Lee, O.Y.-C., Gernaey,

A.M., Galili, E., Eshed, V., Greenblatt, C.L., Lemma, E., Bar-Gal, G.K.,

Spigelman, M., Kahila Bar-Gal, G. & Spigelman, M., 2008, ‘Detection and

molecular characterization of 9,000-year-old Mycobacterium tuberculosis from a

Neolithic settlement in the Eastern Mediterranean.’, PloS one, 3(10), e3426.

Heyn, P., Stenzel, U., Briggs, A.W., Kircher, M., Hofreiter, M. & Meyer, M., 2010,

‘Road blocks on paleogenomes-polymerase extension profiling reveals the

frequency of blocking lesions in ancient DNA’, Nucleic Acids Research, 38(16),

e161.

Higashino, A., Sakate, R., Kameoka, Y., Takahashi, I., Hirata, M., Tanuma, R., Masui,

T., Yasutomi, Y. & Osada, N., 2012, ‘Whole-genome sequencing and analysis of

the Malaysian Cynomolgus macaque (Macaca fascicularis) genome’, Genome

Biology, 13(7), R58.

Higuchi, R., Bowman, B., Freiberger, M., Ryder, O.A. & Wilson, A.C., 1984, ‘DNA

sequences from the quagga, an extinct member of the horse family’, Nature,

312(5991), 282–284.

Hirst, S.M., 1985, ‘An Anglo-Saxon inhumation cemetery at Sewerby, East Yorkshire’,

York University Archaeological Publications 4.

Ho, Y.S., Adroub, S.A., Abadi, M., Alwan, B. Al, Alkhateeb, R., Gao, G., Ragab, A.,

Ali, S., van Soolingen, D., Bitter, W., Pain, A. & Abdallah, A.M., 2012, ‘Complete

genome sequence of Mycobacterium vaccae type strain ATCC 25954’, Journal of

Bacteriology, 194(22), 6339–40.

Hofreiter, M., Jaenicke, V., Serre, D., Haeseler, A. Von & Paabo, S., 2001, ‘DNA

sequences from multiple amplifications reveal artifacts induced by cytosine

deamination in ancient DNA’, Nucleic Acids Research, 29(23), 4793–4799.

Holloway, K.L., Henneberg, R.J., de Barros Lopes, M. & Henneberg, M., 2011,

‘Evolution of human tuberculosis: a systematic review and meta-analysis of

paleopathological evidence’, HOMO, 62(6), 402–458.

Holloway, K.L., Link, K., Ruhli, F. & Hennenberg, M., 2013, 'Skeletal lesions in human

tuberculosis may sometimes heal: and aid to palaeopathological diagnoses', PLoS

ONE, 8(4). e62798.

Holst, M., 2005, Artefacts environmental evidence: the human bone, in Spall, C.A. &

Toop, N.J. (eds) Report on Excavations: July 2000–July 2002, Blue Bridge Lane

and Fishergate House: York, APC Monograph Series.

203

Holst, M., 2008, ‘Osteological analysis: Heslington East, York’, York Osteoarchaeology

No. 1108, Unpublished.

Homolka, S., Projahn, M., Feuerriegel, S., Ubben, T., Diel, R., Nübel, U. & Niemann,

S., 2012, ‘High resolution discrimination of clinical Mycobacterium tuberculosis

complex strains based on single nucleotide polymorphisms’, PLoS ONE, 7(7),

e39855.

Horsburgh, C.R., Barry, C.E. & Lange, C., 2015, ‘Treatment of tuberculosis’, The New

England Journal of Medicine, 373(22), 2149–2160.

Huson, D.H., Auch, A.F., Qi, J. & Schuster, S.C., 2007, ‘MEGAN analysis of

metagenomic data’, Genome Research, 17(3), 377–386.

Hussain, T., 2007, ‘Leprosy and tuberculosis: an insight-review’, Critical Reviews in


Huyen, M.N.T., Tiemersma, E.W., Kremer, K., de Haas, P., Lan, N.T.N., Buu, T.N.,

Sola, C., Cobelens, F.G.J. & van Soolingen, D., 2013, ‘Characterisation of

Mycobacterium tuberculosis isolates lacking IS6110 in Viet Nam’, The

International Journal of Tuberculosis and Lung Disease, 17(11), 1479–1485.

Ichikawa, N., Oguchi, A., Ikeda, H., Ishikawa, J., Kitani, S., Watanabe, Y., Nakamura,

S., Katano, Y., Kishi, E., Sasagawa, M., Ankai, A., Fukui, S., Hashimoto, Y.,

Kamata, S., Otoguro, M., Tanikawa, S., Nihira, T., Horinouchi, S., Ohnishi, Y.,

Hayakawa, M., Kuzuyama, T., Arisawa, A., Nomoto, F., Miura, H., Takahashi, Y.

& Fujita, N., 2010, ‘Genome sequence of Kitasatospora setae NBRC 14216T: an

evolutionary snapshot of the family Streptomycetaceae’, DNA Research, 17(6),

393–406.

Inskip, S., Taylor, G.M., Anderson, S. & Stewart, G., 2017, ‘Leprosy in pre-Norman

Suffolk, UK: biomolecular and geochemical analysis of the woman from Hoxne’,

Journal of Medical Microbiology, 66(11), 1640–1649.

Irgens, L.M., 1984, ‘The discovery of Mycobacterium leprae. A medical achievement in

the light of evolving scientific methods’, The American Journal of

Dermatopathology, 6(4), 337–43.

Jacob, J.T. & Franco-Paredes, C., 2008, ‘The stigmatization of leprosy in India and its

impact on future approaches to elimination and control.’, PLoS Neglected Tropical

Diseases, 2(1), e113.

Jacobson, R.R. & Krahenbuhl, J.L., 1999, ‘Leprosy’, Lancet, 353(9153), 655–660.

Jin, S.-H., Ahn, K.J. & An, S., 2018, ‘Importance of the immune response to

Mycobacterium leprae in the skin’, Biomedical Dermatology, 2(1), 1.

Kaestle, F. A. & Horsburgh, K. A., 2002, ‘Ancient DNA in anthropology: methods,

applications, and ethics’, Yearbook of Physical Anthropology, 45, 92-130.

Kapur, V., Whittam, T.S. & Musser, J.M., 1994, ‘Is Mycobacterium tuberculosis 15,000

Years Old?’, The Journal of Infectious Diseases, 170(5), 1348–1349.

Karanam, K., Loewer, A. & Lahav, G., 2013, ‘Dynamics of the DNA damage response:

insights from live-cell imaging’, Briefings in Functional Genomics, 12(2), 109–17.

Kay, G.L., Sergeant, M.J., Zhou, Z., Chan, J.Z.-M.Z.-M., Millard, A., Quick, J.,

Szikossy, I., Pap, I.I., Spigelman, M., Loman, N.J., Achtman, M., Donoghue, H.D.

& Pallen, M.J., 2015, ‘Eighteenth-century genomes show that mixed infectoins

were common at time of peak tuberculosis in Europe’, Nature Communications,

6(6717), 1–9.

204

Kearse, M., Moir, R., Wilson, A., Stones-Havas, S., Cheung, M., Sturrock, S., Buxton,

S., Cooper, A., Markowitz, S., Duran, C., Thierer, T., Ashton, B., Meintjes, P. &

Drummond, A., 2012, ‘Geneious Basic: an integrated and extendable desktop

software platform for the organization and analysis of sequence data’,

Bioinformatics, 28, 1647–1649.

Kelley, M.A. & Micozzi, M.S., 1984, ‘Rib lesions in chronic pulmonary tuberculosis’,

American Journal of Physical Anthropology, 65(4), 381–386.

Khalil, R.B. & Richa, S., 2014, ‘When affective disorders were considered to emanate

from the heart: the Ebers Papyrus’, American Journal of Psychiatry, 171(3), 275.

Kim, Y.-J. & Wilson, D.M., 2012, ‘Overview of base excision repair biochemistry.’,

Current Molecular Pharmacology, 5(1), 3–13.

Kircher, M., Heyn, P. & Kelso, J., 2011, ‘Addressing challenges in the production and

analysis of illumina sequencing data’, BMC Genomics, 12, 382.

Kircher, M., Sawyer, S. & Meyer, M., 2012, ‘Double indexing overcomes inaccuracies

in multiplex sequencing on the Illumina platform’, Nucleic Acids Research, 40(1),

e3.

Kirchheimer, W.F. & Storrs, E.E., 1971, ‘Attempts to establish the armadillo (Dasypus

novemcinctus Linn.) as a model for the study of leprosy. I. Report of lepromatoid

leprosy in an experimentally infected armadillo’, International Journal of Leprosy

and Other Mycobacterial Diseases, 39(3), 693–702.

Kirchheimer, W.F., Storrs, E.E. & Binford, C.H., 1972, ‘Attempts to establish the

Armadillo (Dasypus novemcinctus Linn.) as a model for the study of leprosy. II.

Histopathologic and bacteriologic post-mortem findings in lepromatoid leprosy in

the Armadillo’, International Journal of Leprosy and Other Mycobacterial

Diseases, 40(3), 229–42.

Kistler, L., Ware, R., Smith, O., Collins, M. & Allaby, R.G., 2017, ‘A new model for

ancient DNA decay based on paleogenomic meta-analysis’, Nucleic Acids

Research, 45(11), 6310–6320.

Klaus, H.D., 2017, 'Paleopathological rigor and differential diagnosis: case studies

involving terminology, description, and diagnostic frameworks for scurvy in

skeletal remains', International Journal of Palaeopathology, 19, 96-110.

Knapp, M. & Hofreiter, M., 2010, ‘Next generation sequencing of ancient DNA:

requirements, strategies and perspectives’, Genes, 1(2), 227–243.

Knapp, M., Lalueza-Fox, C. & Hofreiter, M., 2015, ‘Re-inventing ancient human DNA’,

Investigative Genetics, 6(1), 4.

Knechel, N.A., 2009, ‘Tuberculosis: pathophysiology, clinical features, and diagnosis’,

Critical Care Nurse, 29(2), 34–43.

Konomi, N., Lebwohl, E., Mowbray, K., Tattersall, I. & Zhang, D., 2002, ‘Detection of

Mycobacterial DNA in Andean mummies’, Journal of Clinical Microbiology,

40(12), 4738–40.

Kumar, A., Girdhar, A. & Girdhar, B.K., 2013, ‘Twelve months fixed duration WHO

multidrug therapy for multibacillary leprosy: incidence of relapses in Agra field

based cohort study’, The Indian Journal of Medical Research, 138(4), 536–40.

Lakhtakia, R., 2013, ‘Of animalcula, phthisis and scrofula: historical insights into

tuberculosis in the pre-Koch era’, Sultan Qaboos University Medical Journal,

13(4), 486–490.

205

Lalucat, J., Bennasar, A., Bosch, R., García-Valdés, E. & Palleroni, N.J., 2006, ‘Biology

of Pseudomonas stutzeri’, Microbiology and Molecular Biology Reviews, 70(2),

510–47.

Lampky, J.R., 1971, ‘Distribution of Sorangium cellulosum’, Applied Microbiology,

22(5), 937–938.

Lange, C., Abubakar, I., Alffenaar, J.-W.C., Bothamley, G., Caminero, J.A., Carvalho,

A.C.C., Chang, K.-C., Codecasa, L., Correia, A., Crudu, V., Davies, P., Dedicoat,

M., Drobniewski, F., Duarte, R., Ehlers, C., Erkens, C., Goletti, D., Günther, G.,

Ibraim, E., Kampmann, B., Kuksa, L., de Lange, W., van Leth, F., van Lunzen, J.,

Matteelli, A., Menzies, D., Monedero, I., Richter, E., Rüsch-Gerdes, S., Sandgren,

A., Scardigli, A., Skrahina, A., Tortoli, E., Volchenkov, G., Wagner, D., van der

Werf, M.J., Williams, B., Yew, W.-W., Zellweger, J.-P., Cirillo, D.M. & TBNET,

2014, ‘Management of patients with multidrug-resistant/extensively drug-resistant

tuberculosis in Europe: a TBNET consensus statement’, The European Respiratory

Journal, 44(1), 23–63.

Lastória, J.C. & Morgado De Abreu, M.A.M., 2014, ‘Leprosy: review of the

epidemiological, clinical, and etiopathogenic aspects-Part 1’, Anais Brasileiros de

Dermatologia, 89(2), 205–218.

Lee, F., No date, ‘The pathological report on selected skeletons from the Anglo-Saxon

levels at York Minster’, Calvin Wells Laboratory University of Bradford,

Unpublished.

Leung, A.K.C., 2009, ‘Introduction’, in Leung A.K.C. (ed.), Leprosy in China: a

history, 1–16, Columbia University Press, New York.

Li, H. & Durbin, R., 2009, ‘Fast and accurate short read alignment with Burrows-

Wheeler transform’, Bioinformatics, 15, 1754–1760.

Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G.,

Abecasis, G. & Durbin, R., 2009, ‘The Sequence Alignment/Map format and

SAMtools’, Bioinformatics, 25(16), 2078–2079.

Lin, P.L. & Flynn, J.L., 2010, ‘Understanding latent tuberculosis: a moving target’, The

Journal of Immunology, 185(1), 15–22.

Lindahl, T. & Andersson, A., 1972, ‘Rate of chain breakage at apurinic sites in double-

stranded deoxyribonucleic acid’, Biochemistry, 11(19), 3618–3623.

Lindahl, T. & Nyberg, B., 1972, ‘Rate of depurination of native deoxyribonucleic acid’,

Biochemistry, 11(19), 3610–3618.

Lindgreen, S., 2012, ‘AdapterRemoval: easy cleaning of next-generation sequencing

reads’, BMC Research Notes, 5, 337–341.

Llamas, B., Valverde, G., Fehren-Schmitz, L., Weyrich, L.S., Cooper, A. & Haak, W.,

2016, ‘From the field to the laboratory: controlling DNA contamination in human

ancient DNA research in the high-throughput sequencing era’, Science and

Technology of Archaeological Research, 3(1), 1–14.

Luke, S. & Verma, R.S., 1995, ‘Human (Homo sapiens) and chimpanzee (Pan

troglodytes) share similar ancestral centromeric alpha satellite DNA sequences but

other fractions of heterochromatin differ considerably’, American Journal of

Physical Anthropology, 96(1), 63–71.

Lu, Z., Wu, J. & Cheng, G., 2015, 'Leprosy', in Li, H. (ed), Radiology of Infectious

Diseases: Volume 2, 131-142, Springer, Dordrecht.

Lynnerup, N. & Boldsen, J., 2012, ‘Leprosy (Hansen’s disease)’, in Grauer A.L. (ed.), A

Companion to Paleopathology, 458–471, Wiley-Blackwell, Oxford UK.

206

Maciejewska, M., Pessi, I.S., Arguelles-Arias, A., Noirfalise, P., Luis, G., Ongena, M.,

Barton, H., Carnol, M. & Rigali, S., 2015, ‘Streptomyces lunaelactis sp. nov., a

novel ferroverdin A-producing Streptomyces species isolated from a moonmilk

speleothem’, Antonie van Leeuwenhoek, 107(2), 519–531.

MacRaild, D. M., 1999, Irish migrants in modern Britain, 1750-1922, St. Martin’s Press

Inc, New York USA.

Malathi, M. & Thappa, D.M., 2013, ‘Fixed-duration therapy in leprosy: limitations and

opportunities’, Indian Journal of Dermatology, 58(2), 93–100.

Manchester, K. & Roberts, C.A., 1986, ‘Palaeopathological evidence of tuberculosis and

leprosy in Britain’, SERC Report (Grant 337.367).

Mark, S., 2002, ‘Alexander the Great, geafaring, and the spread of leprosy’, Journal of

the History of Medicine and Allied Sciences, 57(3), 285–311.

Martín, M.C., Manteca, A., Castillo, M.L., Vázquez, F. & Méndez, F.J., 2004,

‘Streptomyces albus isolated from a human actinomycetoma and characterized by

molecular techniques’, Journal of Clinical Microbiology, 42(12), 5957–60.

Martinez, T.S., Figueira, M.M.N.., Costa, A.V., Gonçalves, M.A., Goulart, L.R. &

Goulart, I.M.B., 2011, ‘Oral mucosa as a source of Mycobacterium leprae infection

and transmission, and implications of bacterial DNA detection and the

immunological status’, Clinical Microbiology and Infection, 17(11), 1653–1658.

Masson, M., Bereczki, Z., Molnár, E., Donoghue, H.D., Minnikin, D.E., Lee, O.Y.-C.,

Wu, H.H.T., Besra, G.S. & Bull, I.D., 2015, ‘7000 year-old tuberculosis cases from

Hungary – osteological and biomolecular evidence’, Tuberculosis, 95, S13–S17.

Matheson, C.D., Vernon, K.K., Lahti, A., Fratpietro, R., Spigelman, M., Gibson, S.,

Greenblatt, C.L., Donoghue, H.D. & Zissu, B., 2009, ‘Molecular exploration of the

first-century tomb of the Shroud in Akeldama, Jerusalem’, PLoS ONE, 4(12),

e8319.

Matos, V. & Santos, A.L., 2006, ‘On the trail of pulmonary tuberculosis based on rib

lesions: results from the human identified skeletal collection from the Museu

Bocage (Lisbon, Portugal)’, American Journal of Physical Anthropology, 130(2),

190–200.

Matossian, M.K., 1985, ‘Death in London’, The Journal of Interdisciplinary History,

16(2), 183–197.

Mays, S., Harding, C. & Heighway, C., 2007, ‘Wharram XI: The churchyard York’,

York University Press.

Mays, S. & Taylor, G.M., 2003, ‘A first prehistoric case of tuberculosis from Britain’,

International Journal of Osteoarchaeology, 13(4), 189–196.

McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A.,

Garimella, K., Altshuler, D., Gabriel, S., Daly, M. & DePristo, M.A., 2010, ‘The

Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation

DNA sequencing data’, Genome Research, 20(9), 1297–1303.

McMurry, J.L. & Chang, M.C.Y., 2017, ‘Fluorothreonyl-tRNA deacylase prevents

mistranslation in the organofluorine producer Streptomyces cattleya’, Proceedings

of the National Academy of Sciences of the United States of America, 114(45),

11920–11925.

McVaugh, M. R., 2006, The rational surgery of Middle Ages, SISMEL. Edizioni del

Galluzzo, Florence.

207

Mendum, T.A., Schuenemann, V.J., Roffey, S., Taylor, G., Wu, H., Singh, P., Tucker,

K., Hinds, J., Cole, S.T., Kierzek, A.M., Nieselt, K., Krause, J. & Stewart, G.R.,

2014, ‘Mycobacterium leprae genomes from a British medieval leprosy hospital:

towards understanding an ancient epidemic’, BMC Genomics, 15(1), 270.

Metcalfe, N.H., 2007, ‘A description of the methods used to obtain information on

ancient disease and medicine and how the evidence has survived’, Postgraduate

Medical Journal, 83(984):655-658.

Meyer, M. & Kircher, M., 2010, ‘Illumina sequencing library preparation for highly

multiplexed target capture and sequencing’, Cold Spring Harbor Protocols,

2919(6), pdb.prot5448.

Meyers, W.M., Gormus, B.J., Walsh, G.P., B, B.G. & B, H.G., 1991, ‘Naturally

acquired and experimental leprosy in nonhuman primates’, The American Journal

of Tropical Medicine and Hygiene, 44(4 Pt 2), 24–27.

Mitchell, P.D., 2011, ‘Retrospective diagnosis and the use of historical texts for

investigating disease in the past’, International Journal of Palaeopathology, 1(2),

81-88.

Mitchell, P.D., 2017, ‘Improving the use of historical written sources in

palaeopathology’, International Journal of Palaeopathology, 19, 88-95.

Modlin, R.L., 1994, ‘Th1-Th2 paradigm: insights from leprosy', The Journal of

Investigative Dermatology, 102(6), 828–32.

Modlin, R.L., 2010, ‘The innate immune response in leprosy’, Current Opinion in

Immunology, 22(1), 48–54.

Mohammad, W., Malhotra, S.K. & Garg, P.K., 'Clinico-radiological correlation of bone

changes in leprosy patients presenting with disabilities/deformities', Indian Journal

of Leprosy, 88(2), 83-95.

Mohr, K.I., Garcia, R.O., Gerth, K., Irschik, H. & Muller, R., 2012, ‘Sandaracinus

amylolyticus gen. nov., sp. nov., a starch-degrading soil myxobacterium, and

description of Sandaracinaceae fam. nov’, International Journal of Systematic and

Evolutionary Microbiology, 62(Pt 5), 1191–1198.

Moissenet, D., Becker, K., Mérens, A., Ferroni, A., Dubern, B. & Vu-Thien, H., 2012,

‘Persistent bloodstream infection with Kocuria rhizophila related to a damaged

central catheter’, Journal of Clinical Microbiology, 50(4), 1495–8.

Møller-Christensen, V., 1953, ‘Location and excavation of the first Danish leper

graveyard from the Middle Ages - St. Jørgen’s Farm, Naestved’, Bulletin of the

History of Medicine, 27(2), 112–123.

Mongodin, E.F., Shapir, N., Daughtery, S.C., DeBoy, R.T., Emerson, J.B., Shvartzbeyn,

A., Radune, D., Vamathevan, J., Riggs, F., Grinberg, V., Khouri, H., Wackett, L.P.,

Nelson, K.E. & Sadowsky, M.J., 2006, ‘Secrets of soil survival revealed by the

qenome sequence of Arthrobacter aurescens TC1’, PLoS Genetics, 2(12), e214.

Monot, M., Honoré, N., Garnier, T., Araoz, R., Coppée, J.-Y.Y., Lacroix, C., Sow, S.,

Spencer, J.S., Truman, R.W., Williams, D.L., Gelber, R., Virmond, M., Flageul, B.,

Cho, S.-N.N., Ji, B., Paniz-Mondolfi, A., Convit, J., Young, S., Fine, P.E.,

Rasolofo, V., Brennan, P.J. & Cole, S.T., 2005, ‘On the origin of leprosy’, Science,

308(5724), 1040–1042.

208

Monot, M., Honoré, N., Garnier, T., Zidane, N., Sherafi, D., Paniz-Mondolfi, A.,

Matsuoka, M., Taylor, G.M., Donoghue, H.D., Bouwman, A., Mays, S., Watson,

C., Lockwood, D., Khamispour, A., Dowlati, Y., Jianping, S., Rea, T.H., Vera-

Cabrera, L., Stefani, M.M., Banu, S., Macdonald, M., Sapkota, B.R., Spencer, J.S.,

Thomas, J., Harshman, K., Singh, P., Busso, P., Gattiker, A., Rougemont, J.,

Brennan, P.J. & Cole, S.T., 2009, ‘Comparative genomic and phylogeographic

analysis of Mycobacterium leprae’, Nature Genetics, 41(12), 1282–1289.

Montiel, R., García, C., Cañadas, M.P., Isidro, A., Guijo, J.M. & Malgosa, A., 2003,

‘DNA sequences of Mycobacterium leprae recovered from ancient bones’, FEMS

Microbiology Letters, 226(2), 413–4.

Moonan, P.K., 2018, ‘Tuberculosis—the face of struggles, the struggles we face, and the

dreams that lie within’, Emerging Infectious Diseases, 24(3), 592–593.

Müldner, G., Chenery, C. & Eckardt, H., 2011, ‘The ‘headless Romans’: multi-isotope

investigations of an unusual burial ground from Roman Britain’, Journal of

Archaeological Science, 38,280–290.

Müller, R., 2008, The biomolecular archaeology of leprosy, PhD thesis, University of

Bradford.

Müller, R., Roberts, C.A. & Brown, T.A., 2014a, ‘Biomolecular identification of ancient

Mycobacterium tuberculosis complex DNA in human remains from Britain and

continental Europe’, American Journal of Physical Anthropology, 153, 178–189.

Müller, R., Roberts, C.A. & Brown, T.A., 2014b, ‘Genotyping of ancient

Mycobacterium tuberculosis strains reveals historic genetic diversity’, Proceedings

of the Royal Society of London B: Biological Sciences, 281 (17181), 20133236.

Müller, R., Roberts, C.A. & Brown, T.A., 2015, ‘Complications in the study of ancient

tuberculosis: non-specificity of IS6110 PCRs’, Science and Technology of

Archaeological Research, 1(1), 1–8.

Müller, R., Roberts, C.A. & Brown, T.A., 2016, ‘Complications in the study of ancient

tuberculosis: presence of environmental bacteria in human archaeological remains’,

Journal of Archaeological Science, 68, 5–11.

Mullis, K., Faloona, F., Scharf, S., Saiki, R., Horn, G. & Erlich, H., 1986, ‘Specific

enzymatic amplification of DNA in Vvtro: the polymerase chain reaction’, Cold

Spring Harbor Symposia on Quantitative Biology, 51, 263–273.

Nagao, M., Sonobe, M., Bando, T., Saito, T., Shirano, M., Matsushima, A., Fujihara, N.,

Takakura, S., Iinuma, Y. & Ichiyama, S., 2009, ‘Surgical site infection due to

Mycobacterium peregrinum: a case report and literature review’, International

Journal of Infectious Diseases, 13(2), 209–211.

Neal, C. & Roskams, S., 2012, ‘Assessment report Heslington East, Volumes 1 and 2’,

Archaeology Data Service archive, http://archaeologydataservice.ac.uk.

Nerlich, A.G. & Zink, A.R., 2008, Past leprae, in Raoult, D. & Drancourt, M. (eds.),

Paleomicrobiology: Past human infections, 99–123, Springer-Verlag, Berlin

Heidelberg.

Nicholls, H., 2005, ‘Ancient DNA comes of age’, PLoS Biology, 3(2), e56.

Nicklisch, N., Maixner, F., Ganslmeier, R., Friederich, S., Dresely, V., Meller, H., Zink,

A. & Alt, K.W., 2012, ‘Rib lesions in skeletons from early Neolithic sites in central

Germany: on the trail of tuberculosis at the onset of agriculture’, American Journal

of Physical Anthropology, 149(3), 391–404.

209

Nolan, M., Sikorski, J., Jando, M., Lucas, S., Lapidus, A., Glavina Del Rio, T., Chen, F.,

Tice, H., Pitluck, S., Cheng, J.-F., Chertkov, O., Sims, D., Meincke, L., Brettin, T.,

Han, C., Detter, J.C., Bruce, D., Goodwin, L., Land, M., Hauser, L., Chang, Y.-J.,

Jeffries, C.D., Ivanova, N., Mavromatis, K., Mikhailova, N., Chen, A., Palaniappan,

K., Chain, P., Rohde, M., Göker, M., Bristow, J., Eisen, J.A., Markowitz, V.,

Hugenholtz, P., Kyrpides, N.C. & Klenk, H.-P., 2010, ‘Complete genome sequence

of Streptosporangium roseum type strain (NI 9100T)’, Standards in Genomic

Sciences, 2(1), 29–37.

Noonan, J.P., Hofreiter, M., Smith, D., Priest, J.R., Rohland, N., Rabeder, G., Krause, J.,

Detter, C., Pääbo, S. & Rubin, E.M., 2005, ‘Genomic sequencing of Pleistocene

cave bears’, Science, 309(5721), 597–600.

Nuttgens, P., 2007, The History of York: From the earliest times to the year 2000,

Blackthorn Press, York United Kingdom.

Ortner, D.J., 2003, Identification of pathological conditions in human skeletal remains,

2nd edn, Academic Press, San Diego USA.

Ottaway, P., 2004, Roman York, Tempus, Stroud.

Pääbo, S., 1989, ‘Ancient DNA: extraction, characterization, molecular cloning, and

enzymatic amplification’, Proceedings of the National Academy of Sciences of the

United States of America, 86, 1939–1943.

Pääbo, S., Gifford, J.A. & Wilson, A.C., 1988, ‘Mitochondrial DNA sequences from a

7000-year old brain’, Nucleic Acids Research, 16(20), 9775–87.

Pai, M., Behr, M.A., Dowdy, D., Dheda, K., Divangahi, M., Boehme, C.C., Ginsberg,

A., Swaminathan, S., Spigelman, M., Getahun, H., Menzies, D. & Raviglione, M.,

2016, ‘Tuberculosis’, Nature Reviews Disease Primers, 2, 16076.

Palliser, D.M., 2014, Medieval York: 600-1540, 1st edn, Oxford University Press, New

York USA.

Pandey, R.K., Singh, D.P., Sudhakar, G., Thangaraj, K. & Rao, V.R., 2012,

‘Standardization of PCR conditions for an ancient DNA amplification’,

International Journal of Human Sciences, 9, 1.

Park, Y-H., Yoon, J-H., Shin, Y.K., Suzuki, K-I., Kudo, T., Seino, A., Kim, H-J., Lee, J-

S. & Lee, S.T., 1999, 'Classification of 'Nocardioides fulvus' IFO 14399 and

Nocardioides sp. ATCC 39419 in Kribbella gen. nov., as Kribbella flavida sp. nov.

and Kribbella sandramycini sp. nov., International Journal of Systematic

Bacteriology, 49, 743-752.

Pieters, J., 2008, ‘Mycobacterium tuberculosis and the macrophage: maintaining a

balance’, Cell Host & Microbe, 3(6), 399–407.

Poinar, H.N., Schwarz, C., Qi, J., Shapiro, B., Macphee, R.D.E., Buigues, B., Tikhonov,

A., Huson, D.H., Tomsho, L.P., Auch, A., Rampp, M., Miller, W. & Schuster, S.C.,

2006, ‘Metagenomics to paleogenomics: large-scale sequencing of mammoth

DNA’, Science, 311(5759), 392–394.

Porter, M.S. & Beiko, R.G., 2013, ‘SPANNER: taxonomic assignment of sequences

using pyramid matching of similarity profiles’, Bioinformatics, 29(15), 1858–64.

Prabhakar, M., Ershler, W.B. & Longo, D.L., 2009, ‘Bone marrow, thymus and blood:

changes across the lifespan’, Aging Health, 5(3), 385–393.

210

Pukall, R., Lapidus, A., Glavina Del Rio, T., Copeland, A., Tice, H., Cheng, J.-F., Lucas,

S., Chen, F., Nolan, M., Bruce, D., Goodwin, L., Pitluck, S., Mavromatis, K.,

Ivanova, N., Ovchinnikova, G., Pati, A., Chen, A., Palaniappan, K., Land, M.,

Hauser, L., Chang, Y.-J., Jeffries, C.D., Chain, P., Meincke, L., Sims, D., Brettin,

T., Detter, J.C., Rohde, M., Göker, M., Bristow, J., Eisen, J.A., Markowitz, V.,

Kyrpides, N.C., Klenk, H.-P. & Hugenholtz, P., 2010, ‘Complete genome sequence

of Conexibacter woesei type strain (ID131577)’, Standards in Genomic Sciences,

2(2), 212–9.

Qian, G., Wang, Y., Liu, Y., Xu, F., He, Y.-W., Du, L., Venturi, V., Fan, J., Hu, B. &

Liu, F., 2013, ‘Lysobacter enzymogenes uses two distinct cell-cell signaling

systems for differential regulation of secondary-metabolite biosynthesis and colony

morphology’, Applied and Environmental Microbiology, 79(21), 6604–16.

Quinlan, A.R. & Hall, I.M., 2010, ‘BEDTools: a flexible suite of utilities for comparing

genomic features’, Bioinformatics, 26(6), 841–842.

Rafi, A., Spigelman, M., Stanford, J., Lemma, E., Donoghue, H. & Zlas, J., 1994, ‘DNA

of Mycobacterium leprae detected by PCR in ancient bone’, The Lancet,

343(8909), 287–290.

Ramirez-Lapausa, M., Menendez-Saldana, A. & Noguerado-Asensio, A., 2015,

‘Extrapulmonary tuberculosis: an overview’, Journal of Spanish Prison Health, 17,

3–11.

Ramos, J.M., Romero, D. & Belinchón, I., 2016, ‘Epidemiology of leprosy in Spain: the

role of the international migration’, PLoS Neglected Tropical Diseases, 10(3),

e0004321.

Rasouli, M.R., Mirkoohi, M., Vaccaro, A.R., Yarandi, K.K. & Rahimi-Movaghar, V.,

2012, 'Spinal tuberculosis: diagnosis and management', Asian Spine Journal, 6(4),

294-308.

Rawnsley, S. L. & Singleton, F. B., 1995, A History of Yorkshire, 3rd edn, Phillimore,

Chichester.

Rees, R.J.W., 1966, ‘Enhanced susceptibility of thymectomized and irradiated mice to

infection with Mycobacterium leprae’, Nature, 211(5049), 657–658.

Rees, R.J.W. & McDougall, A.C., 1977, ‘Airborne infection with Mycobacterium leprae

in mice’, International Journal of Leprosy, 44(1&2), 99–103.

Reibel, F., Cambau, E. & Aubry, A., 2015, ‘Update on the epidemiology, diagnosis, and

treatment of leprosy’, Médecine et Maladies Infectieuses, 45(9), 383–393.

Ridley, D.S. & Jopling, W.H., 1966, ‘Classification of leprosy according to immunity. A

five group system’, International Journal of Leprosy, 34(3), 255–273.

Rizzi, E., Lari, M., Gigli, E., Bellis, G. De & Caramelli, D., 2012, ‘Ancient DNA

studies: new perspectives on old samples’, Genetics Selection Evolution, 44(1), 21.

Robbins, G., Tripathy, V.M., Misra, V.N., Mohanty, R.K., Shinde, V.S., Gray, K.M. &

Schug, M.D., 2009, ‘Ancient skeletal evidence for leprosy in India (2000 B.C.)’,

PLoS ONE, 4(5), e5669.

Roberts, C.A. & Buikstra, J.E., 2003, The bioarchaeology of tuberculosis : a global

perspective on a re-emerging disease, University Press of Florida, Gainesville

Florida.

Roberts, C. & Manchester, K., 2010, The archaeology of disease, 3rd edn, The History

Press, Stroud Gloucestershire.

211

Roberts, C.A., 2015, 'Old World tuberculosis: evidence from human remains with a

review of current research and future prospects', Tuberculosis, 95, S117-S121.

Roberts, R.S., 1971, The use of literary and documentary evidence in history of

medicine, in Clarke, E. (ed), Modern methods in the history of medicine, 36-56,

Athlone Press, London.

Robinson, C.F., 2003, Islamic Historiography, Cambridge University Press,Cambridge.

Rochat, T., Fujiwara-Nagata, E., Calvez, S., Dalsgaard, I., Madsen, L., Calteau, A.,

Lunazzi, A., Nicolas, P., Wiklund, T., Bernardet, J.-F. & Duchaud, E., 2017,

‘Genomic Characterization of Flavobacterium psychrophilum serotypes and

development of a multiplex PCR-based serotyping scheme', Frontiers in

Microbiology, 8, 1752.

Rohland, N. & Hofreiter, M., 2007, ‘Ancient DNA extraction from bones and teeth’,

Nature Protocols, 2(7), 1756–1762.

Rohland, N. & Reich, D., 2012, ‘Cost-effective, high-throughput DNA sequencing

libraries for multiplexed target capture’, Genome Research, 22(5), 939–946.

Rosa, L.T., Springthorpe, V., Bianconi, M.E., Thomas, G.H. & Kelly, D.J., ‘Massive

over-representation of solute-binding proteins (SBPs) from the tripartite

tricarboxylate transporter (TTT) family in the genome of the α-proteobacterium

Rhodoplanes sp. Z2-YC6860’, Microbial Genomics, 4(5), e000176.

Rosenthal, M., 2013, ‘Tuberculosis: ancient history, modern scourge’, Journal of

Ancient Diseases & Preventive Remedies, 1(2), 1–4.

Rothschild, B.M., Martin, L.D., Lev, G., Bercovier, H., Bar‐Gal, G.K., Greenblatt, C.,

Donoghue, H., Spigelman, M. & Brittain, D., 2001, ‘Mycobacterium tuberculosis

Complex DNA from and extinct bison dated 17,000 years before the present’,

Clinical Infectious Diseases, 33(3), 305–311.

Rubini, M., Erdal, Y.S., Spigelman, M., Zaio, P. & Donoghue, H.D., 2014,

‘Paleopathological and molecular study on two cases of ancient childhood leprosy

from the Roman and Byzantine empires’, International Journal of

Osteoarchaeology, 24, 570–582.

Rubini, M., Zaio, P. & Roberts, C., 2014, ‘Tuberculosis and leprosy in Italy. New

skeletal evidence’, HOMO, 65(1), 13–32.

Russell, D.G., Barry, C.E. & Flynn, J.L., 2010, ‘Tuberculosis: what we don’t know can,

and does, hurt us’, Science, 328(5980), 852–856.

Ryu, Y.J., 2015, ‘Diagnosis of pulmonary tuberculosis: recent advances and diagnostic

algorithms’, Tuberculosis and Respiratory Diseases, 78(2), 64–71.

Sabin, S., Herbig, A., Vågene, A.J., Ahlström, T., Bozovic, G., Arcini, C., Kühnert, D.

& Bos, K.I., 2020, ‘A seventeenth-century Mycobacterium tuberculosis genome

supports a Neolithic emergence of the Mycobacterium tuberculosis complex’,

Genome Biology, 21(201).

Sabin, T.D. & Ebner, J.D., 1969, ‘Patterns of sensory loss in lepromatous leprosy’,

International Journal of Leprosy, 37(3), 239–248.

Salo, W.L., Aufderheide, A.C., Buikstrat, J. & Holcomb, T.A., 1994, 'Identification of

Mycobacterium tuberculosis DNA in a pre-Columbian Peruvian mummy',

Proceedings of the National Academy of Sciences of the United States of America,

91(6),2091-2094.

212

Santamaria, M., Fosso, B., Consiglio, A., Caro, G. De, Grillo, G., Licciulli, F., Liuni, S.,

Marzano, M., Alonso-Alemany, D., Valiente, G. & Pesole, G., 2012, ‘Reference

databases for taxonomic assignment in metagenomics’, Briefings in Bioinformatics,

13(6), 682–695.

Saraf, S.K. & Tuli, S.M., 2015, 'Tuberculosis of hip: a current concept review', Indian

Journal of Orthopaedics, 49(1), 1-9.

Satapathy, J., Kar, B.R. & Job, C.K., 2005, ‘Presence of Mycobacterium leprae in

epidermal cells of lepromatous skin and its significance’, Indian Journal of

Dermatology, Venereology and Leprology, 71(4), 267–269.

Schubert, M., Lindgreen, S. & Orlando, L., 2016, ‘AdapterRemoval v2: rapid adapter

trimming, identification, and read merging’, BMC Research Notes, 9(1), 88.

Schuenemann, V.J., Avanzi, C., Krause-Kyora, B., Seitz, A., Herbig, A., Inskip, S.,

Bonazzi, M., Reiter, E., Urban, C., Dangvard Pedersen, D., Taylor, G.M., Singh, P.,

Stewart, G.R., Velemínský, P., Likovsky, J., Marcsik, A., Molnár, E., Pálfi, G.,

Mariotti, V., Riga, A., Belcastro, M.G., Boldsen, J.L., Nebel, A., Mays, S.,

Donoghue, H.D., Zakrzewski, S., Benjak, A., Nieselt, K., Cole, S.T. & Krause, J.,

2018, ‘Ancient genomes reveal a high diversity of Mycobacterium leprae in

medieval Europe’, PLoS Pathogens, 14(5), e1006997.

Schuenemann, V.J., Singh, P., Mendum, T.A., Krause-Kyora, B., Jäger, G., Bos, K.I.,

Herbig, A., Economou, C., Benjak, A., Busso, P., Nebel, A., Bolsden, J.L.,

Kjellström, A., Wu, H., Stewart, G.R., Taylor, G.M., Bauer, P., Lee, O.Y.C., Wu,

H.H.T, Minnikin, D.E., Besra, G.S., Tucker, K., Roffey, S., Sow, S.O., Cole, S.T.,

Nieselt, K. & Krause, J., 2013, 'Genome-wide comparison of Medieval and modern

Mycobacterium leprae', Science, 341, 179-183.

Sellers, M., 1987, ‘York in the Sixteenth and Seventeenth centuries’, The English

Historical Review, 12 (47) 437-447.

Sermrittirong, S. & Van Brakel, W.H., 2014, ‘Stigma in leprosy: concepts, causes and

determinants’, Leprosy Review, 85, 36–47.

Sheahan, J. J. & Whellan, T., 1855, History and topography of the city of York; The

Ainsty Wapentake; and the East Reading of Yorkshire; Embracing a general review

of the early history of Great Britain, and a general history and description of the

county of York (Volume 1), John Green Beverley, Great Britain.

Shepard, C.C., 1960, ‘The experimental disease that follows the injections of human

leprosy bacilli into foot-pads of mice’, The Journal of Experimental Medicine,

112(3), 445–54.

Shimoide, H., Anzai, E., Murata, Y., Kusajima, K., Ichihara, H., Takano, T., Hirayama,

N., Sato, N. & Kobayashi, Y., 1995, ‘Contamination of flexible fiberoptic

bronchoscopes with Mycobacterium chelonae linked to an automated endoscope

disinfection machine-on the relationship between the presence of the organism in

the intestinal tract and contamination of disinfection machine, and a case of

gallbladder and bile duct infection with M. chelonae’, Kekkaku (Tuberculosis),

70(10), 571–7.

Singh, P. & Cole, S.T., 2011, ‘Mycobacterium leprae: genes, pseudogenes and genetic

diversity’, Future Microbiology, 6(1), 57–71.

Smith, C.I., Chamberlain, A.T., Riley, M.S., Stringer, C. & Collins, M.J., 2003, ‘The

thermal history of human fossils and the likelihood of successful DNA

amplification’, Journal of Human Evolution, 45(3), 203–217.

213

Smith, S.A., Krasucki, S.P., McDowell, J. V & Balke, V.L., 2015, ‘Complete genome

sequence of Sphingobacterium sp. strain ML3W, isolated from wings of Myotis

lucifugus infected with white nose syndrome’, Genome Announcements, 3(1),

e01477-14.

Spierings, E., De Boer, T., Zulianello, L. & Ottenhoff, T.H., 2000, ‘The role of Schwann

cells, T cells and Mycobacterium leprae in the immunopathogenesis of nerve

damage in leprosy’, Leprosy Review, 71 Suppl, S121–S129.

Spigelman, M. & Donoghue, H.D., 2001, ‘Brief communication: unusual pathological

condition in the lower extremities of a skeleton from ancient Israel’, American

Journal of Physical Anthropology, 114, 92–93.

Spigelman, M. & Lemma, E., 1993, ‘The use of the polymerase chain reaction (PCR) to

detect Mycobacterium tuberculosis in ancient skeletons’, International Journal of

Osteoarchaeology, 3(2), 137–143.

Squires, K., Booth, T. & Roberts, C.A., 2019, The ethics of sampling human skeletal

remains for destructive analyses, in Squires, K., Errickson, D. & Márquez-Grant,

N. (eds), Ethical approaches to human remains. Springer, Cham.

Sreevatsan, S., Escalante, P., Pan, X., Gillies, D.A., Siddiqui, S., Khalaf, C.N.,

Kreiswirth, B.N., Bifani, P., Adams, L.G., Ficht, T., Perumaalla, V.S., Cave, M.D.,

Embden, J.D. van & Musser, J.M., 1996, ‘Identification of a polymorphic

nucleotide in oxyR specific for Mycobacterium bovis.’, Journal of Clinical


Sreevatsan, S., Pan, X.I., Stockbauer, K.E., Connell, N.D., Kreiswirth, B.N., Whittam,

T.S. & Musser, J.M., 1997, 'Restricted structural gene polymorphism in the

Mycobacterium tuberculosis complex indicates evolutionarily recent global

dissemination', Proceedings of the National Academy of Sciences of the United

States of America, 94, 9869-9874.

Stead, W.W., Eisenach, K.D., Cave, M.D., Beggs, M.L., Templeton, G.L., Thoen, C. &

Bates, J.H., 1995, ‘When did Mycobacterium tuberculosis infection first occur in

the New World? An important question with public health implications’, Clinical

Commentary, 151, 1267–1268.

Steyn, M & Buskes, J., 2016, 'Skeletal manifestations of tuberculosis in modern human

remains', Clinical Anatomy, 29, 854-861.

Steyn, M., Scholtz, Y., Botha, D. & Pretorius, S., 2013, 'The changing face of

tuberculosis: trends in tuberculosis-associated skeletal changes', Tuberculosis, 93,

467–474.

Stone, A.C., Wilbur, A.K., Buikstra, J.E. & Roberts, C.A, 2009, ‘Tuberculosis and

leprosy in perspective’, American Journal of Physical Anthropology, 140 Suppl,

66–94.

Strobel, T., Al-Dilaimi, A., Blom, J., Gessner, A., Kalinowski, J., Luzhetska, M., Pühler,

A., Szczepanowski, R., Bechthold, A. & Rückert, C., 2012, ‘Complete genome

sequence of Saccharothrix espanaensis DSM 44229T and comparison to the other

completely sequenced Pseudonocardiaceae’, BMC Genomics, 13(1), 465.

Stroud, G., & Kemp, R.L., 1993, ‘Cemeteries of the church and priory of St. Andrew,

Fishergate, part 2’, York Archaeological Trust.

214

Sun, H., Lapidus, A., Nolan, M., Lucas, S., Rio, T.G. Del, Tice, H., Cheng, J.-F., Tapia,

R., Han, C., Goodwin, L., Pitluck, S., Pagani, I., Ivanova, N., Mavromatis, K.,

Mikhailova, N., Pati, A., Chen, A., Palaniappan, K., Land, M., Hauser, L., Chang,

Y.-J., Jeffries, C.D., Djao, O.D.N., Rohde, M., Sikorski, J., Göker, M., Woyke, T.,

Bristow, J., Eisen, J.A., Markowitz, V., Hugenholtz, P., Kyrpides, N.C. & Klenk,

H.-P., 2010, ‘Complete genome sequence of Nocardiopsis dassonvillei type strain

(IMRU 509)’, Standards in Genomic Sciences, 3(3), 325–36.

Suzuki, K., Saso, A., Hoshino, K., Sakurai, J., Tanigawa, K., Luo, Y., Ishido, Y., Mori,

S., Hirata, K. & Ishii, N., 2014, ‘Paleopathological evidence and detection of

Mycobacterium leprae DNA from archaeological skeletal remains of Nabe-kaburi

(head-covered with iron pots) burials in Japan’, PloS ONE, 9(2), e88356.

Suzuki, K., Takigawa, W., Tanigawa, K., Nakamura, K., Ishido, Y., Kawashima, A.,

Wu, H., Akama, T., Sue, M., Yoshihara, A., Mori, S. & Ishii, N., 2010, ‘Detection

of Mycobacterium leprae DNA from achaeological skeletal remains in Japan using

whole genome amplification and polymerase chain reaction’, PLoS ONE, 5(8),

e12422.

Suzuki, T. & Inoue, T., 2007, ‘Earliest evidence of spinal tuberculosis from the

Aneolithic Yayoi period in Japan’, International Journal of Osteoarchaeology, 17,

392–402.

Tayles, N. & Buckley, H.R., 2004, ‘Leprosy and tuberculosis in Iron Age Southeast

Asia?’, American Journal of Physical Anthropology, 125, 239–256.

Taylor, G.M., Widdison, S., Brown, I.N., Young, D. & Molleson, T., 2000, ‘A

Mediaeval case of lepromatous leprosy from 13–14th century Orkney, Scotland’,

Journal of Archaeological Science, 27(12), 1133–1138.

Taylor, G.M., Young, D.B. & Mays, S.A., 2005, ‘Genotypic analysis of the earliest

known prehistoric sase of tuberculosis in Britain’, Journal of Clinical

Microbiology, 43(5), 2236–2240.

Taylor, M.G., Crossey, M., Saldanha, J. & Waldron, T., 1996, ‘DNA from

Mycobacterium tuberculosis identified in Mediaeval human skeletal remains using

polymerase chain reaction’, Journal of Archaeological Science, 23(5), 789–798.

Telenti, A., Marchesi, F., Balz, M., Bally, F., Bottger, E. & Bodmer, T., 1993, ‘Rapid

identification of Mycobacteria to the species level by polymerase chain reaction

enzyme analysis’, Journal of Clinical Microbiology, 31, 175–178.

Templeton, J.E.L., Brotherton, P.M., Llamas, B., Soubrier, J., Haak, W., Cooper, A. &

Austin, J.J., 2013, 'DNA capture and next-generation sequencing can recover whole

mitocholdrial genomes from highly degraded samples for human identification',

Investigative Genetics, 4(1), 26.

Thappa, D.M., Sharma, V.K., Kaur, S. & Suri, S., 1992, 'Radiological changes in hands

and feet in disabled leprosy patients: a clinico-radiological correlation', Indian

Journal of Leprosy, 64(1), 58-66.

Thawai, C., Kanchanasin, P., Ohkuma, M., Kudo, T. & Tanasupawat, S., 2018,

‘Identification and antimicrobial activity of Micromonospora strains from Thai peat

swamp forest soil’, Journal of Applied Pharmaceutical Science, 8(4), 119–125.

Thierry, D., Brisson-noël, A., Vincent-lévy-frébault, V., Nguyen, S., Guesdon, J.L &

Gicquel, B., 1990, ‘Characterization of a Mycobacterium tuberculosis Insertion

Sequence, IS6110, and its application in diagnosis’, Journal of Clinical

Microbiology 28(12), 2668–2673.

215

Thomson, R., Tolson, C., Carter, R., Coulter, C., Huygens, F. & Hargreaves, M., 2013,

‘Isolation of nontuberculous Mycobacteria (NTM) from household water and

shower aerosols in patients with pulmonary disease caused by NTM’, Journal of

Clinical Microbiology, 51(9), 3006–11.

Trautman, J.R., 1984, ‘A brief history of Hansen’s Disease’, Bulletin of the New York

Academy of Medicine, 60(7), 689–695.

Tripathy, S.N., 2015, Tuberculosis manual for obstetricians and gynecologists, 1st edn,

Jaypee Brothers Medical Publisher, New Delhi India.

Truman, R.W., Singh, P., Sharma, R., Busso, P., Rougemont, J., Paniz-Mondolfi, A.,

Kapopoulou, A., Brisse, S., Scollard, D.M., Gillis, T.P. & Cole, S.T., 2011,

‘Probable zoonotic leprosy in the Southern United States’, New England Journal of

Medicine, 364(17), 1626–1633.

Tsangaras, K. & Greenwood, A.D., 2012, ‘Museums and disease: using tissue archive

and museum samples to study pathogens’, Annals of Anatomy - Anatomischer

Anzeiger, 194(1), 58–73.

Turner-Walker, G., 2008, The chemical and microbial degradation of bones and teeth,

in Pinhasi, R. & Mays, S., (eds.), Advances in Human Palaeopathology, 3–29,

Wiley, Chichester.

Ukil, A.C., 1940, ‘Chronic non-tuberculous infections of the lung’, The Indian Medical

Gazette, 75(10), 581–588.

Vanhoenacker, F.M., Sanghvi, D.A. & Backer, A.I. De, 2009, ‘Imaging features of

extraaxial musculoskeletal tuberculosis’, The Indian Journal of Radiology &

Imaging, 19(3), 176–86.

van Soolingen,, Hermans, P.W., de Haas, P.E. & van Embden, J.D., 1992, ‘Insertion

element IS1081-associated restriction fragment length polymorphisms in

Mycobacterium tuberculosis complex species: a reliable tool for recognizing

Mycobacterium bovis BCG’, Journal of Clinical Microbiology, 30(7), 1772–7.

Waddington, K., 2006, The bovine scourge: meat, tuberculosis and the public’s health,

1860s-1914, The Boydell Press, Woodbridge.

Walker, S.L. & Lockwood, D.N.J., 2006, ‘The clinical and immunological features of

leprosy’, British Medical Bulletin, 77–78(1), 103–121.

Wang, H., Maeda, Y., Fukutomi, Y. & Makino, M., 2013, ‘An in vitro model of

Mycobacterium leprae induced granuloma formation.’, BMC Infectious Diseases,

13, 279.

Wang, X.-J., Zhang, B., Yan, Y.-J., An, J., Zhang, J., Liu, C.-X. & Xiang, W.-S., 2013,

‘Characterization and analysis of an industrial strain of Streptomyces

bingchenggensis by genome sequencing and gene microarray’, Genome, 56(11),

677–689.

Watson, C.L. & Lockwood, D.N.J., 2009, ‘Single nucleotide polymorphism analysis of

European archaeological M. leprae DNA’, PLoS ONE, 4(10), e7547.

Wayne, L.G. & Hayes, L.G., 1996, ‘An in vitro model for sequential study of shiftdown

of Mycobacterium tuberculosis through two stages of nonreplicating persistence’,

Infection and Immunity, 64(6), 2062–2069.

216

Weon, H.-Y., Kim, B.-Y., Yoo, S.-H., Lee, S.-Y., Kwon, S.-W., Go, S.-J. &

Stackebrandt, E., 2006, ‘Niastella koreensis gen. nov., sp. nov. and Niastella

yeongjuensis sp. nov., novel members of the phylum Bacteroidetes, isolated from

soil cultivated with Korean ginseng’, International Journal of Sytematic and

Evolutionary Microbiology, 56(8), 1777–1782.

White, C. & Franco-Paredes, C., 2015, ‘Leprosy in the 21st century’, Clinical

Microbiology Reviews, 28(1), 80–94.

Wilbur, A.K., Bouwman, A.S., Stone, A.C., Roberts, C. A., Pfister, L.-A., Buikstra, J.E.

& Brown, T.A., 2009, ‘Deficiencies and challenges in the study of ancient

tuberculosis DNA’, Journal of Archaeological Science, 36(9), 1990–1997.

Wilson, I.G., 1997, ‘Inhibition and facilitation of nucleic acid amplification’, Applied

and Environmental Microbiology, 63(10), 3741–51.

Wirth, T., Hildebrand, F., Allix-Béguec, C., Wölbeling, F., Kubica, T., Kremer, K., van

Soolingen, D., Rüsch-Gerdes, S., Locht, C., Brisse, S., Meyer, A., Supply, P. &

Niemann, S., 2008, ‘Origin, spread and demography of the Mycobacterium

tuberculosis complex’, PLoS Pathogens, 4(9), e1000160.

Witas, H.W., Donoghue, H.D., Kubiak, D., Lewandowska, M. & Gładykowska-

Rzeczycka, J.J., 2015, ‘Molecular studies on ancient M. tuberculosis and M. leprae:

methods of pathogen and host DNA analysis’, European Journal of Clinical

Microbiology & Infectious Diseases, 34(9), 1733–49.

Wood, J.W., Milner, G.R., Harpending, H.C. & Weiss, K.M., 1992, 'The osteological

paradox: problems of inferring prehistoric health from skeletal samples', Current

Anthropology, 33(4), 343-370.

Woods, S.A. & Cole, S.T., 1990, ‘A family of dispersed repeats in Mycobacterium

leprae’, Molecular Microbiology, 4(10), 1745–51.

World Health Organization, 2018a, Tuberculosis [Fact Sheets].

World Health Organization, 2018b, Leprosy [Fact Sheets].

World Health Organization, no date, Drug-resistant TB: XDR-TB FAQ.

Wrigley, E.A., Davies, R.S., Oeppen, J.E. & Schofield, R.S., 1997, English population

history from family reconstruction, 1580-1837, Cambridge University Press,

Cambridge.

Yamamura, M., Uyemura, K., Deans, R., Weinberg, K., Rea, T., Bloom, B. & Modlin,

R.L., 1991, ‘Defining protective responses to pathogens: cytokine profiles in

leprosy lesions’, Science, 254(5029), 277–279.

Yang, D.Y. & Watt, K., 2005, ‘Contamination controls when preparing archaeological

remains for ancient DNA analysis’, Journal of Archaeological Science, 32(3), 331–

336.

Yassin, A., Shennawy, M. el, Enany, G. el, Wassef, N.F. & Shoeb, S., 1975, ‘Leprosy of

the upper respiratory tract. A clinical bacteriological, histopathological and

histochemical study of twenty cases’, The Journal of Laryngology and Otology,

89(5), 505–11.

Yoon, K.H., Cho, S.N., Lee, M.K., Abalos, R.M., Cellona, R. V, Fajardo, T.T., Guido,

L.S., Cruz, E.C. Dela, Walsh, G.P., Kim, J.D. & Kim, J.D., 1993, ‘Evaluation of

polymerase chain reaction amplification of Mycobacterium leprae-specific

repetitive sequence in biopsy specimens from leprosy patients’, Journal of Clinical


217

Zhu, H.-H., Guo, J., Yao, Q., Yang, S.-Z., Deng, M.-R., Phuong, L.T.B., Hanh, V.T. &

Ryan, M.J., 2007, ‘Streptomyces vietnamensis sp. nov., a streptomycete with violet

blue diffusible pigment isolated from soil in Vietnam’, International Journal of

Sytematic and Evolutionary Microbiology, 57(8), 1770–1774.

Zink, A., Haas, C.J., Reischl, U., Szeimies, U. & Nerlich, A.G., 2001, ‘Molecular

analysis of skeletal tuberculosis in an ancient Egyptian population’, Journal of

Medical Microbiology, 50, 355–366.

Zumla, A. & James, G., 1996, ‘Granulomatous infections: etiology and classification’,

Clinical Infetious Diseases, 23, 146–158.

218

Appendices

Site Name Skeleton Number Sampled

Age Sex

Melton 4297 36-45 M

2554 11-13 yrs

J

5319 36-45 M

St Peter's Huddersfield

5 46+ M

7 46+ M

17 18-25 F

St Andrew Fishergate

6 20-30 M

277 5 yrs J

286 5-6 yrs J

296 18-25 M

323 16-18 M

339 30-40 M

384 4-6 yrs J

34 adult F?

131 46+ M

253 30-40 F

3 Driffield Terrace 37 36-45 M

54 26-35 M

13 16-18 M?

15 26-35 M

6 Driffield Terrace 19 26-35 M

22 36-45 M?

St Helen-on-the-Walls

5000 adult I

5844 26-35 F

6003 36-45 F

5494 46+ F

Heslington East 229 26-35 M

Wharram Percy 26 46+ F

1600 adult I

Sewerby G34 46+ M

G44 N/A M

Addingham 134 26-35 M

223 14-16 yrs

J

103 26-35 M

St Giles by Brompton Bridge

1288 26-35 M?

1531 18-25 F?

1542 26-35 M?

Wetwang Slack 1 14 yrs J

2 36-45 M

5 26-35 M

6 26-35 M

8 18-25 F

9 25-30 M

219

3 18-25 M

4 18-25 F

7 26-35 F

Hickleton 46 N/A N/A

York Minster 1 18-25 M

15 36-45 M

Ailcy Hill 1044 N/A J

1043 46+ M

Fishergate House C1163 (86) 46+ M

C1188 (98) 36-45 M

C1205 (108) 12-14 yrs

N/A

C1259 (135) 26-35 F

C1282 (147) 26-35 M

C1286 (149) 36-45 F

Table S2.1: Additional skeleton information for the 57 skeleton studied. This table is

showing the age and sex information for the Yorkshire archaeological bones studied (except for

the three samples from Wetwang Slack settlement as this information is not available). M: male,

F: female, N/A: information not available, J: juvenile, I: ambiguous.

220

M A B

200 bp

100 bp

Figure S3.1: Rv0083 PCR assay amplification for sample St Andrew Fishergate 277. A:

undiluted DNA template, B: 10-fold diluted DNA template. M is the DNA ladder with the 100

bp and 200 bp marked in the figure. Faint lower band is shown inside the red box.

Figure S3.2: gyrA PCR assay amplification for sample St Andrew Fishergate 339. A:

undiluted DNA template, B: 10-fold diluted DNA template. M is the DNA ladder with the 100

bp and 200 bp marked in the figure. Faint lower band is shown inside the red box.

M A B

200 bp

100 bp

221

M A B

200 bp

100 bp

200 bp

100 bp

A B M

Figure S3.3: IS6110 123 bp PCR amplification of the sample Heslington East 229. A:

undiluted DNA template, B: 10-1 diluted DNA template. M is showing the DNA ladder with the

100 bp and 200 bp marked in the figure. Faint lower band is shown inside the red box.

Figure S3.4: gyrA PCR amplification of the sample Wetwang Slack 2. A: undiluted DNA

template, B: 10-1 diluted DNA template. M is showing the DNA ladder with the 100 bp and 200

bp marked in the figure. Faint lower band is shown inside the red box.

222

200 bp

100 bp

A B M

M A B C D

100 bp

200 bp

Figure S3.5: IS6110-123 bp PCR amplification of the sample Wetwang Slack 7. A:

undiluted DNA template, B: 10-1 diluted DNA template. M is showing the DNA ladder with the

100 bp and 200 bp marked in the figure.

Figure S3.6: gyrA PCR amplification of the samples Wharram Percy 26 and Wharram

Percy 1600. A and C: undiluted and 10-1 diluted DNA templates of Wharram Percy 26,

respectively; B and D: undiluted and 10-1 diluted DNA template of Wharram Percy1600,

respectively. M is showing the DNA ladder with the 100 bp and 200 bp marked in the figure.

223

M A B C D

200 bp

100 bp

M A B

200 bp

100 bp

Figure S3.7: IS6110 first step PCR amplification of the samples Addingham 134 and

Addingham 223. A and C: undiluted DNA and 10-1 diluted DNA templates of Addingham 134,

respectively; B and D: undiluted DNA and 10-1 diluted DNA templates of Addingham 223,

respectively. M is showing the DNA ladder with the 100 bp and 200 bp marked in the figure.

The bands of interest are shown in the red boxes.

Figure S3.8: gyrA PCR amplification of the sample Addingham 103. A: undiluted DNA


bp are marked in the figure.

224

M A B

200 bp

100 bp

M A B

200 bp

100 bp

Figure S3.9: gyrA PCR amplification of the sample Melton 5319 sample. A: undiluted DNA


bp bands indicated in the figure.

Figure S3.10: gyrA PCR amplification of the sample Hickleton 46. A: undiluted DNA

template, B: 10-1 diluted DNA template. M is showing the DNA ladder with 100 bp and 200 bp

bands indicated in the figure.

225

M A B

200 bp

100 bp

Figure S3.11: IS6110 123 bp PCR amplification of the sample St Giles by Brompton Bridge

1542. A: undiluted DNA template, B: 10-1 diluted DNA template. M is showing the DNA ladder

with 100 bp and 200 bp bands indicated in the figure. The desired band is marked inside the red

box.

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