Metabolic and Ecological Study of Environmental Pentose ... · Metabolic and Ecological Study of Environmental Pentose Utilizing Bacteria (E-PUB) By Farhana Sharmin BSc (Hons) In

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Metabolic and Ecological Study of Environmental Pentose Utilizing

Bacteria (E-PUB)

By

Farhana Sharmin

BSc (Hons) In Microbiology

Gono University, Bangladesh

Master of Science (Food and Bio Process Technology,

Asian Institute of Technology (AIT), Bangkok, Thailand

A thesis submitted in partial fulfilment of the requirements for the degree of

Doctor of Philosophy

School of Biomedical Sciences

Faculty of Health

Queensland University of Technology

2012

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TABLE OF CONTENTS

LIST OF TABLES IV

LIST OF FIGURES VI

LIST OF ABBREVIATIONS VIII

ACKNOWLEDGEMENTS XII

ABSTRACT 3

CHAPTER 1 5

INTRODUCTION, HYPOTHESIS, AIMS AND OBJECTIVES 5

1.1 BACKGROUND 5

1.2 RESEARCH PROBLEM AND HYPOTHESIS 7

1.3 AIMS AND OBJECTIVES OF RESEARCH 7

1.4 RESEARCH PLAN 9

CHAPTER 2 11

LITERATURE REVIEW 11

2.0 INTRODUCTION 11

2.1 BRIEF HISTORICAL BACKGROUND 11

2.2 THE CHEMISTRY OF PLANT BIOMASS 13

2.3 MICROBIAL ASPECTS OF FERMENTATION TECHNOLOGY 19

2.4 METHODOLOGY 29

CHAPTER 3

ISOLATION AND IDENTIFICATION OF ENVIRONMENTAL PENTOSE-UTILIZING BACTERIA 37

3.0 SUMMARY 37

3.1 INTRODUCTION 37

3.2 MATERIALS AND METHODS 38

3.3 RESULTS 43

3.4 DISCUSSION 47

3.5 CONCLUSIONS 49

CHAPTER 4

CATABOLIC CHARACTERISTICS OF ENVIRONMENTAL PENTOSE-UTILIZING BACTERIA (E-PUB) 50

4.0 SUMMARY 50

4.1 INTRODUCTION 50


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4.3 RESULTS 53

4.4 DISCUSSION 62

4.5 CONCLUSIONS 68

CHAPTER 5

ANABOLIC CHARACTERISTICS OF ENVIRONMENTAL PENTOSE-UTILIZING BACTERIA 69

5.0 SUMMARY 69

5.1 INTRODUCTION 69


5.3 RESULTS 74

5.4 DISCUSSION 81

5.5 CONCLUSIONS 87

CHAPTER 6

ECOLOGICAL STUDY OF ENVIRONMENTAL PENTOSE-UTILIZING BACTERIA BY DENATURING

GRADIENT GEL ELECTROPHORESIS (DGGE) 88

6.0 SUMMARY 88

6.1 INTRODUCTION 88


6.3 RESULTS 94

6.4 DISCUSSION 103

6.5 CONCLUSIONS 109

CHAPTER 7

TAXONOMIC ANALYSIS OF PENTOSE-RICH NATURAL ENVIRONMENTS USING A HIGH DENSITY

OLIGONUCLEOTIDE MICROARRAY (PHYLOCHIP) TECHNOLOGY 111

7.0 SUMMARY 111

7.1 INTRODUCTION 111


7.3 RESULTS 115

7.4 DISCUSSION 123

7.5 CONCLUSIONS 126

CHAPTER 8 128

SUMMARY, CONCLUSION AND FUTURE WORK 128

8.1 REVISITING THE HYPOTHESIS AND AIMS 128

8.2 SUMMARY OF FINDINGS 129

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8.3 SIGNIFICANCE OF FINDINGS 132

8.4 FUTURE DIRECTIONS 133

REFERENCES 137

APPENDIX A ERROR! BOOKMARK NOT DEFINED.

APPENDIX B ERROR! BOOKMARK NOT DEFINED.

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LIST OF TABLES

Table 2.1: Comparison of various lignocellulosic raw materials...................................................17

Table 2.2: List of pentose utilizing microorganisms (adapted from Singh and Mishra, 1995).......23

Table 2.3: List of microbial products from pentose fermentation (Singh and Mishra, 1995).......27

Table 3.1: Location of Collected Samples.....................................................................................39

Table 3.2: PCR reaction mixture details........................................................................................42

Table 3.3: Characteristics of selected isolates from Maryborough (A)..........................................43

Table 3.4: Characteristics of selected isolates from Maryborough (B)......................................... 44

Table 3.5: Characteristics of selected isolates from Proserpine....................................................44

Table 3.6: 16S rDNA sequencing results of unknown isolates......................................................46

Table 4.1: Specific growth rates of E-PUB cultures.......................................................................56

Table 4.2: Statistical analysis of p values of specific growth rates................................................57

Table 4.3: Analysis of diauxie growth............................................................................................59

Table 4.4: P value of significance specific growth rate of combination of glucose and pentose

sugars............................................................................................................................................60

Table 4.5: Amount of glucose at the second lag phase of the growth medium............................61

Table 4.6: Ratio of specific growth rate (µ) for xylose utilization as a single sugar compared to

that of the same sugar as part of a dual carbon source system.....................................................61

Table 5.1: HPLC injector programme for amino acid detection.....................................................73

Table 5.2: Names of amino acids detected and their elution times..............................................74

Table 5.3: Amino acids produced by E-PUB isolates …………………………….…….…………………………….75

Table 5.4: Performance characteristics of HPLC UV detection of amino acid...............................77

Table 5.5: Amino acid production using single and dual carbon sources as substrates………..……80

Table 5.6: Total biomass measured from single pentose and dual sugar carbon substrate.........80

Table 5.7: Yield of amino acid expressed in mg per g of biomass .................................................81

Table 6.1: List of the samples collected from different sugar mills...............................................90

Table 6.2: 16S rDNA sequencing results including samples and DGGE band details...................102

Table 6.3: 16S rDNA sequencing result with closest matched Genus/species based on the

percentage (%) of similarity.........................................................................................................103

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Table 7.1: Richness of the bacterial taxa present in environmental samples from sugar-cane

processing sites............................................................................................................................116

Table 7.2: Evenness (Shannon’s diversity index; H’) of bacterial communities present from

sugar-cane processing sites.........................................................................................................116

Table 7.3: Summary of CAP data showing the significance of sample types and location effects

on bacterial community composition..........................................................................................121

Table 7.4: Summary SIMPER data...............................................................................................123

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LIST OF FIGURES

Figure 2.1: Chemical structure of starch..................................................................................15

Figure 2.2: Chemical structure of pectin.......................................................................................15

Figure 2.3: Structure of lignocellulose...........................................................................................16

Figure 2.4: Chemical structure of xylan and xylose formation ....................................................19

Figure 2.5: o-phthalaldehyde (OPA) and mercaptoethanol reaction...........................................32

Figure 3.1: Map of the Queensland sugar mill regions.................................................................38

Figure 3.2: 16S rDNA PCR amplification image after gel electrophoresis……….......................….45

Figure 4.1 (a-g): Comparison of growth curves for various carbon sources..................................55

Figure 4.2: Results of the growth measurements for the various cultures...................................58

Figure 4.3: Metabolic pathway of breakdown pentose and glucose sugars….....................…….63

Figure 4.4: Metabolic pathways for the breakdown of sugars (xylose included.......................64

Figure 5.1: Chromatogram of a mixture of 0.5 µL amino acids standards…………………..............…74

Figure 5.2: Chromatograms of the amino acid mixture present in microbial

cultures..................776

Figure 5.3: HPLC for LB medium-blank analysis.............................................................................78

Figure 5.4: End-products of dual-sugar metabolism (glucose and pentose)…….......................... 79

Figure 5.5: Formation of intracellular and extracellular amino acids...........................................82

Figure 5.6: Glycine biosynthesis…………………………………….……………………………………………………….. 86

Figure 6.1: Diagram showing a typical sugar processing mill. .........…………………………………………..91

Figure 6.2: Community fingerprint analysis using the Bray-Curtis method................................96

Figure 6.3: DGGE profiles of bacterial community structures in liquid samples..........................97

Figure 6.4: Phylogenetic tree analysis of liquid samples by.........................................................97

Figure 6.5: Non-metric multi-dimensional scaling (MDS) plot analysis of DGGE bands .............99

Figure 6.6: DGGE profiles of bacterial community structures in soil samples.............................100

Figure 6.7: Phylogenetic tree analysis of solid samples...............................................................100

Figure 6.8: DGGE gel image indicating the lane numbers............................................................101

Figure 7.1: Dominant bacterial phyla present. ...........................................................................117

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Figure 7.2: Distribution of bacterial Classes present within the four dominant Phyla ...............118

Figure 7.3: Heat map / 2-way clustering of samples according to PhyloChip OTU’s. Clustering

based on Euclidean distance using complete linkage method.....................................................120

Figure 7.4: nMDS ordination plot showing similarity in bacterial community structure.............122

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LIST of ABBREVIATIONS

A. Actinomyces

Ala Alanine

AT Annealing Temperature

Arg Arginine

Asp Aspartic acid

bp Base Pairs

BLAST Basic Local Alignment Search Tool

C. Corynebacterium

CAP Canonical Analysis of Principal

cDNA Copy DNA

Cys Cysteine

CV Coefficient of Variation

DGGE Denaturing Gradient Gel Electrophoresis

DNA Deoxyribonucleic Acid

dNTPs Nucleoside Triphosphates

dsDNA Double Stranded DNA

E Shannon Evenness Index

EDTA Ethylenediaminetetracetic acid

FISH Fluorescence In Situ Hydridization

FMOC Fluorenylmethoxycarbonyl

GC Gas Chromatography

gDNA Genomic DNA

Glu Glutamic acid

Gly Glycine

g Gram (weight)

H Shannon-Wiener diversity index

h Hour

HPLC High Performance Liquid Chromatography

His Histidine

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Ile Isoleucine

LB Luria-Bertani

lys Lysine

µL Microlitre

µM/ µmol Micromolar

M Molar

mL Millilitre

min Minute

mMol milli-Mole

MDS Multidimensional scaling

N. Nocardia

ng Nano gram

OPA o-Phthaldialdehyde

OTU Operational Taxonomic Unit

OD Optical Density

phe Phenylalanine

% Percentage

PCR Polymerase Chain Reaction

P. Propionibacterium

pmol Picomole

qPCR Quantitative real-time PCR

RE Restriction Endonuclease

R. Rhodococcus

RNA Ribonucleic Acid

rRNA Ribosomal RNA

rpm Rotation per Minute

RT-PCR Reverse Transcription PCR

ser Serine

SD Standard Deviation

SNP Single Nucleotide Polymorphisom

x

SSU Small Subunit

TAE Tris Acetate EDTA

TE Tris EDTA

thr Threonine

tyr Tyrosine

U Units

UV Ultraviolet

UPGMA Unweighted Pair Group Arithmetic Mean

W/V Weight/ Volume

List of Supplementary Materials

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Appendix A: Thesis-associated Poster/paper presentations

Posters presented at National/International Conferences

1. Farhana Sharmin, John Bartley, Flavia Huygens, Megan Hargreaves (2009). Pentose

Utilizing Corynebacterium sp. Producing Industrial Valuable Amino Acids: 3rd Congress

of European Microbiologists, FEMS, Gothenburg, Sweden and also presented in the

same year at Australian Society for Microbiology conference held in Perth.

2. Farhana Sharmin, Megan Hargreaves (2009), Microbial Metabolism of Pentoses

Released from Lignocellulosic Biomass: 3rd Congress of European Microbiologists,

FEMS; Gothenburg, Sweden.

3. Farhana Sharmin, John Bartley, Flavia Huygens, Megan Hargreaves (2010). PCR-DGGE

fingerprinting for detection of microbial diversity from Queensland sugar industrial

waste. Joint meeting of the NZ Microbiological Society and NZ Society for Biochemistry

& Molecular Biology, University of Auckland, New Zealand.

Papers submitted for Publication

1. Farhana Sharmin, Flavia Huygens, Steve Wakelin and Megan Hargreaves “Firmicutes

dominated the bacterial taxa with in sugar-cane processing plants". Scientific Reports

(under review).

2. Farhana Sharmin, Flavia Huygens and Megan Hargreaves “A review of pentose utilizing

bacteria from bagasse hemicelluolse”. Biotechnology Letter (Manuscript submitted).

3. Farhana Sharmin, Flavia Huygens and Megan Hargraves. “Isolation and Identification and

Ecological Analysis of Environmental Pentose-Utilizing Microbial Community”, Journal of

Applied Microbiology (Manuscript submitted)

4. Farhana Sharmin, Flavia Huygens and Megan Hargreaves. “Study of Catabolic and

Anabolic Characteristics of Environmental Pentose-Utilizing Bacteria”. In Progress

Appendix B: Results and Calculations

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ACKNOWLEDGEMENTS

I wish to express a great dept of gratitude to my patient and persistent PhD supervisor, Associate

Professor Megan Hargreaves for sharing her knowledge and for her direction, guidance,

feedback, advice and enormous inspiration during my PhD journey and pregnancy. My thanks

also go to Dr. Flavia Huygens for being such a wonderful and friendly associate supervisor and

for being such a dedicated and thorough research scientist. You have been very generous with

your time during my PhD. Many thanks also to Dr. John Bartley for helping me in the area of

chemistry, especially in the field of HPLC set up. This thesis definitely owes a lot to your insight

and supervision and I hope that it meets your high standards.

I would like to thank Dr Mark Dawson, as an external supervisor and review committee member.

Thank you for being so supportive and thorough with your feedback.

I’d like to acknowledge the members of the EMRG lab and others, who have been an absolute

pleasure to work with, and who have been extremely helpful with their sharing of ideas, skills

and lab time. They include: Irani Rathnayake, Maxim Sheludchenko, Chaminda Ranasinghe,

Phillipa Perrott, Sue Gill, Vincent Chand and Chris Carvalho.

To Charles Wan - thanks for your support in the initial settling in period in the lab, and also for

helping me with molecular tasks, for example primer design, PCR and gel electrophoresis etc. I

would like also to thank Prof Margaret Britz for giving me an opportunity of embarking on this

PhD by approving the scholarship; sharing her immense knowledge and giving me initial

direction and advice during my early stages of this PhD.

My thanks also to the corresponding people of Maryborough, Proserpine and Mackay sugar

Industries for providing samples. I also would like to thank to Dr. James Smith for collecting the

initial samples. I would like to thank Dr. Steven Walkelin for helping me with my Metagenomic

PhyloChip analysis.

I would finally like to acknowledge my family and friends Mum, Dad, sister Rehnuma, brother

Mehedi and husband Jafar who have provided me with much support and encouragement

during my candidature.

xiii

STATEMENT of AUTHORSHIP

The work contained in this thesis has not been previously submitted to meet requirements for an

award at this or any other higher education institution. To the best of my knowledge and belief, the

thesis contains no material previously published or written by another person except where due

reference is made.

S1gnature

�D. 0 7- . 'J.p/2__ Date

Dedication

I dedicate my dissertation to my wonderful family for supporting me and encouraging me through

this whole process. Special thanks are due to Mohammad Amanullah, Mrs. Delowara Ahmed, and

Abu Jafar Siddiquee. My dad and husband kept me grounded through this process, my daughter

Junainah Siddiquee kept me laughing and on my feet, and my parents sacrificed many luxuries

during my upbringing so that I could always have an excellent education.

QUT Verified Signature

Chapter 1 Introduction

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ABSTRACT Lignocellulosic materials, such as sugar cane bagasse, a waste product of the sugarcane

processing industry, agricultural residues and herbaceous crops, may serve as an abundant and

comparatively cheap feedstock for largescale industrial fermentation, resulting in the production

of marketable end-products. However, the complex structure of lignocellulosic materials, the

presence of various hexose and pentose sugars in the hemicellulose component, and the

presence of various compounds that inhibit the organisms selected for the fermentation

process, all constitute barriers that add to the production costs and make full scale industrial

production economically less feasible. The work presented in this thesis was conducted in order

to screen microorganisms for ability to utilize pentose sugars derived from the sugar mill

industrial waste. A large number of individual bacterial strains were investigated from hemi-

cellulose rich material collected at the Proserpine and Maryborough sugar mills, notably soil

samples from the mill sites. The research conducted to isolation of six pentose-capable Gram-

positive organisms from the actinomycetes group by using pentose as a sole carbon source in

the cultivation process.

The isolates were identified as Corynebacterium glutamicum, Actinomyces odontolyticus,

Nocardia elegans, and Propionibacterium freudenreichii all of which were isolated from the

hemicellulose-enriched soil. Pentose degrading microbes are very rare in the environment, so

this was a significant discovery. Previous research indicated that microbes could degrade

pentose after genetic modification but the microbes discovered in this research were able to

naturally utilize pentose.

Six isolates, identified as four different genera, were investigated for their ability to utilize single

sugars as substrates (glucose, xylose, arabinose or ribose), and also dual sugars as substrates (a

hexose plus a pentose). The results demonstrated that C. glutamicum, A. odontolyticus, N.

elegans, and P. freudenreichii were pentose-capable (able to grow using xylose or other pentose

sugar), and also showed diauxie growth characteristics during the dual-sugar (glucose, in

combination with xylose, arabinose or ribose) carbon source tests. In addition, it was shown

that the isolates displayed very small differences in growth rates when grown on dual sugars as

compared to single sugars, whether pentose or hexose in nature.

The anabolic characteristics of C. glutamicum, A. odontolyticus, N. elegans and P. freudenreichii

were subsequently investigated by qualitative analysis of their end-products, using high

performance liquid chromatography (HPLC). All of the organisms produced arginine and cysteine

after utilization of the pentose substrates alone. In addition, P. freudenreichii produced alanine


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and glycine. The end-product profile arising from culture with dual carbon sources was also

tested. Interestingly, this time the product was different. All of them produced the amino acid

glycine, when grown on a combination substrate-mix of glucose with xylose, and also glucose

with arabinose. Only N. elegans was able to break down ribose, either singly or in combination

with glucose, and the end-product of metabolism of the glucose plus ribose substrate

combination was glutamic acid.

The ecological analysis of microbial abundance in sugar mill waste was performed using

denaturing gradient gel electrophoresis (DGGE) and also the metagenomic microarray PhyloChip

method. Eleven solid samples and seven liquid samples were investigated. A very complex

bacterial ecosystem was demonstrated in the seven liquid samples after testing with the

PhyloChip method. It was also shown that bagasse leachate was the most different, compared to

all of the other samples, by virtue of its richness in variety of taxa and the complexity of its

bacterial community. The bacterial community in solid samples from Proserpine, Mackay and

Maryborough sugar mills showed huge diversity. The information found from 16S rDNA

sequencing results was that the bacterial genera Brevibacillus, Rhodospirillaceae, Bacillus, Vibrio

and Pseudomonas were present in greatest abundance. In addition, Corynebacterium was also

found in the soil samples.

The metagenomic studies of the sugar mill samples demonstrate two important outcomes:

firstly that the bagasse leachate, as potentially the most pentose-rich sample tested, had the

most complex and diverse bacterial community; and secondly that the pentose-capable isolates

that were initially discovered at the beginning of this study, were not amongst the most

abundant taxonomic groups discovered in the sugar mill samples, and in fact were, as suspected,

very rare. As a bioprospecting exercise, therefore, the study has discovered organisms that are

naturally present, but in very small numbers, in the appropriate natural environment. This has

implications for the industrial application of E-PUB, in that a seeding process using a starter

culture will be necessary for industrial purposes, rather than simply assuming that natural

fermentation might occur.


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CHAPTER 1

Introduction, Hypothesis, Aims and Objectives

1.1 Background

Microbial utilization of lignocellulosic biomass for the production of commercially valuable

products such as chemicals, liquid fuels, protein enriched food/feed, and preparation of

cellulose polymers, is an attractive approach to help meet energy and food demands of

developed and developing countries. There has been considerable interest in the conversion of

renewable resources into fuels and other products over past years, as petroleum prices rise and

the potential impact of global warming demands technologies that close the carbon cycle

(Govindaswamy and Vane, 2007). The technologies for producing ethanol from plant biomass

constituents such as starch have been available for a number of years. However, the competing

use of starch for food production has focused research on alternative sources, such as the use of

lignocellulosic fractions of plants for production of fuel and chemicals. Government policy in the

USA has mandated that biofuels must increasingly come from sustainable resources, so that

crop wastes in the future will become the primary source of biofuels and other similar products,

rather than carbohydrates such as starch which can be better employed as food products (U.S.

Department of Energy, 2005).

Lignocellulosic biomass contains several polymeric components such as lignin, cellulose and

hemicellulose. Fractionation and enzymatic treatment can therefore yield various product

streams that are rich in phenolics from lignin, glucose from cellulose, and pentoses (mainly

xylose and arabinose) from hemicellulose. Unfortunately, fermentation involving mixtures of

sugars (glucose, xylose, arabinose and others) such as are present in the lignocellulosic biomass,

usually results in the preferential use of glucose due to catabolite repression and consequent

failure to fully utilize all of the available sugars. Commercial fermentation systems aim to

maximize productivity, so that high product yields per unit of microbial biomass are produced,

and the fullest possible use of the carbohydrate source provided, is always the preferred

outcome.

Utilization of the fraction containing hemicellulose in lignocellulosic biomass, is an important

factor in optimizing the economics of biomass-related commercial processes given that


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hemicellulose makes up a significant proportion (44% carbon content) of the potentially

available carbon for use in fermentation or chemical extraction processes (Hoch, 2007).

Although there are several potential uses for fractions enriched with hemicellulose, such as non-

biological processes for the production of chemicals, the use of hemicellulose carbon as a

fermentable substrate remains an attractive route for producing chemicals that have intrinsic

commercial value. Examples include the production of acids that can be used in the food

industry (such as variety of amino acids, acetic, propionic and lactic acid) or polymer production

(butyrate and lactic acid).

The bioconversion of pentoses derived from hemicellulose remains a bottleneck in development

of industrial fermentation processes, as microbes such as Saccharomyces cerevisiae, that are

known to be able to produce high yields of product, are not able to utilize pentose substrates

naturally. Conversely, those that are able to utilize pentose sugars, such as Pichia stipitis,

produce end-products at unacceptably low yields and productivity levels (Agbogbo et al., 2006).

Strategies for enhancing the utilization of xylose and, to a lesser extent, arabinose have to date

involved such processes as genetically engineering S. cerevisiae to allow xylose utilization

(Pitkänen et al., 2005; Hahn-Hägerdal et al., 2007). Some limitations of these methods include

difficulties in using engineered microbes in large scale industrial processes, such as poor public

perception, the possibility of back-mutation and the unsuitable physiological properties of the

resulting strains. Some success has been achieved with natural selection, developing strains of

S. cerevisiae that are able to utilize xylose (Attfield and Philip, 2006; Govindaswamy and Vane,

2007). While the growth rates achieved were quite slow, the principle provides an interesting

alternative to genetic engineering.

Kawaguchi et al., (2006) have attempted amino acid synthesis using Corynebacterium

glutamicum, an industrially proven bacterium, using a xylose substrate and forcing carbon flow

to ethanol production using high cell density fermentation under bacteriostatic conditions. This

approach is unproven except in defined medium conditions and also relies on genetically

engineered strains.

Other bacterial strains capable of metabolising pentoses for the production of alternative fuels

or industrial chemicals include solventogenic Clostridium sp. for production of butanol from

pentoses (Patel et al., 2006) alkane production by Vibrio furnissii (Patel et al., 2006) and lactic

acid production by acid-tolerant, thermophilic Bacillus strains or Lactobacillus pentosus (Cruz et

al., 2007).


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The challenge is that the fractionation process for cellullosic biomass generates only cellulose

and hemicellulose, rather than completely separating the glucose polymers from the pentose

polymers. Thus, any successful process must deal with the situation where at least two sugars

may be present, and sometimes more.

This research will investigate the use of naturally occurring bacteria, isolated specifically for the

purpose of breaking down the pentose sugars naturally present in the fraction of hemicellulose

from lignocellulosic waste. The taxonomy, ecology and metabolism of these potentially valuable

organisms will also be investigated.

1.2 Research Problem and Hypothesis

The fractions of hemicellulose from lignocellulosic waste have always contained some residual

cellulose, so the sugars available for industrial fermentation will normally contain a mixture of

pentoses plus glucose. Efficient use of this fraction as a fermentation feedstock would thus

require the use of microbes that can metabolise such pentoses in the presence of glucose,

resulting in efficient use of the sugars available.

The research hypothesis, therefore, was that pentose utilizing organisms isolated from

naturally pentose enriched environments may subsequently be used to degrade pentose

sugars such as those found in hemicellulose from agricultural waste, and produce

commercially valuable by-products.

1.3 Aims and Objectives of Research

In order to prove this hypothesis, I have defined three major aims. These aims, and the

objectives required to achieve the aims, are described in the following paragraphs.

The first aim of this research was to isolate, identify and taxonomically characterize pentose-

capable organisms from waste products of agricultural processes, specifically hemicellulose-

enriched soil from sugar cane milling.

The second aim of this research was to detect and identify major end-products from pentose

and diauxie growth of the suitable isolates obtained.

The final aim was to investigate microbial populations in pentose rich habitats, using a

metagenomic approach, specifically Denaturing Gradient Gel Electrophoresis (DGGE) and

PhyloChip. This is important, in order to relate the pentose-capable isolates back to their natural


8

environment, and to establish whether the in-situ breakdown of pentose sugars is likely to occur

naturally, or whether the process would require seeding in order to initiate the intended

metabolic outcomes.

These aims will be achieved by the completion of the following objectives:

Aim 1 - Objective 1: Collect environmental samples from pentose-rich sites, particularly those

found in sugarcane growing and processing sites, and screen these samples for their

ability to utilize pentose sugars. Identify pentose-capable isolates.

Objective 2: Test pentose (xylose, arabinose and ribose) carbon sources, to determine

the growth characteristics of pentose-capable isolates in single carbon media.

Objective 3: Test pentose-capable isolates for their growth characteristics in a dual

carbon medium, using glucose plus each of the three pentose sugars separately.

Aim 2 – Objective 1: Identify the end-products of metabolism of glucose and each of the three

pentose sugars by the test organisms.

Objective 2: Identify end-products of diauxic metabolism of glucose plus each of the

three pentose sugars by the testing of organisms.

Aim 3 – Objective 1: Analyse microbial communities in sugar mill samples of water, soil, and

bagasse leachate collected from five cane-growing areas in Queensland, Australia, using

Denaturing Gradient Gel Electrophoresis (DGGE) and subsequent DNA sequencing.

Objective 2: Analyse microbial communities present in sugar mill samples (as above)

using PhyloChip analysis methods.

Objective 3: Use the two metagenomic analyses to demonstrate the complexity and

richness of a microbial community in the most pentose-rich sample (bagasse leachate),

as compared with those present in other sugar mill samples.


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1.4 Research Plan

Aim 1: To isolate, identify and characterize pentose-capable organisms from waste products of

agricultural processes (bagasse from sugarcane)

DIAUXIE CURVES FOR GLUCOSE plus PENTOSE

GROWTH CURVES (g, µ data) for SINGLE CARBON

SOURCES

ISOLATES IDENTIFIED

SCREEN FOR PENTOSE UTILIZATION CAPACITY

COLLECT ISOLATES

Chapter 3

Chapter 4


10

Aim 2: To detect and identify major end-products from single sugar (pentose) and

diauxie(glucose plus pentose) growth of the 6 isolates obtained.

Aim 3: To investigate microbial populations in pentose rich habitats, using a metagenomic

approach, specifically DGGE and PhyloChip analysis.

END PRODUCT ANALYSIS FROM

PENTOSE METABOLISM

END PRODUCT ANALYSIS FROM MIXED SUGAR METABOLISM

IDENTIFICATION OF END PRODUCTS

COLLECT WATER, BAGASSE AND SOIL FROM SUGAR CANE

REFINERIES

ECOLOGY STUDY OF ENVIRONMENTAL PENTOSE

UTILIZING BACTERIA

(DGGE)

TAXONOMY of ENVIRONMENTAL PENTOSE UTILIZING BACTERIA

(PHYLOCHIP)

Chapter 5

Chapter 6

Chapter 7

Chapter 2 Literature Review

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CHAPTER 2

Literature Review

2.0 Introduction

This critical review of current literature is structured as follows: firstly, a brief summary will be

presented of the history and background of industrial fermentation, leading to its particular

application for the purposes of recycling agricultural waste and production of commercially

important end-products (Section 2.1). This will be followed by a detailed analysis of the chemical

aspects of lignocellulose, in particular considering the nature of the potential substrate materials

(Section 2.2). The third section (Section 2.3) will detail the research to date, regarding the

microbial aspects of the process, including an overview of the current state of knowledge

regarding genetically altered and natural microorganisms, their end-products and ecological

aspects of research of this kind. Finally, in Section 2.4 a review of the methodology employed in

this important area of research will be reported, with particular focus on cutting-edge methods

being used in this research.

2.1 Brief Historical Background

Fermentation has always been an important part of our lives: foods can be spoiled by microbial

fermentations; and foods can be made by microbial fermentations. It was not understood how

fermentation actually worked until the research of Louis Pasteur in the latter part of the

nineteenth century and the work that followed (Laser et al., 2002). Fermentation is a microbial

process in which enzymatically controlled transformations of organic compounds occur. In this

process microbes utilize a variety of organic compounds including carbohydrates and may

produce products for use by human beings. Fermentation results in the production of foods such

as bread, wine, and beer. Bread predates the earliest agriculture and was discovered when wild

cereal grains were found to be edible (Demain, 2005). Fermented dough was thought to be

discovered by accident, when dough was not baked immediately and underwent fermentation

(Hornsey, 2003). Egypt and Mesopotamia exported bread making to Greece and Rome, and the

Romans subsequently improved the technique, leading eventually to the discovery of the role of

yeasts in baking, by Pasteur, followed by the production of baker’s yeast cultures (Hornsey,

2003).


12

The Chinese were using fermentation around 4000 BC to produce foods such as yogurt, cheese,

fermented rice, and soy sauces. Milk has been a dietary staple since at least 9000 BC, resulting in

fermented products such as cheese, yoghurt, and sour cream (Tamang and Kailasapathy, 2010).

Modern cheese manufacturing follows almost the same steps as were used in ancient times,

including a fermentation step involving lactic acid bacteria. Many cheeses are also ripened by

means of fungi which either occur naturally or are inoculated into or onto the cheese, to add to

their distinctive flavour (Steinkraus, 1995).

Biochemically, fermentation involves the breaking down of complex organic substances into

simpler ones by means of microbial metabolic pathways. Fermentative metabolism may be

defined as the use of carbon sources to produce end-products that contain chemical energy,

usually in the absence of oxygen. These endproducts are not fully oxidized are not able to be

metabolized further in the absence of oxygen. Sugars are common substrates for fermentation

process, and examples of fermentation products are ethanol, lactic acid and lactose (Todar,

2008). In some cases the microbial cell obtains energy through glycolysis, splitting a sugar

molecule and removing electrons from the molecule. The electrons are then passed to an

organic molecule such as pyruvic acid.

Cellulosic biomass represents the only foreseeable, sustainable source of organic fuels,

chemicals, and materials (Olsson and Hahn-Hägerdal, 1996; Lynd et al., 2001). A primary

technological challenge in biologically processing cellulosic biomass into fuels and chemicals is

that of overcoming the recalcitrance of cellulose to hydrolysis. Cellulose hydrolysis processes are

typically categorized into those that use strong mineral acids and those that use cellulase

enzymes. Although processes using acids are more technologically developed, enzymatic

processes have comparable projected costs and are expected to enjoy an increasing cost

advantage as the technology improves (NREL, 1999; Lynd et al., 2001). Due to its resistance to

enzymatic attack, however, naturally occurring cellulosic biomass must be pretreated before it

can be enzymatically hydrolyzed. Pretreatment is one of the most expensive and least

technologically mature unit operations in lignocellulosic conversion processes using enzymatic

hydrolysis (Lynd et al., 2001).

To be effective, a pretreatment process must produce reactive fibre, preserve the utility of the

pentosan (hemicellulose) fraction, and limit the extent to which the pretreated material inhibits

growth of the fermenting microorganisms. To be economical, the process should minimize

energy demands and limit costs associated with feedstock size reduction, materials of

construction, and treatment of process residues Lynd et al., (2001). These process conditions


13

such as temperature, reaction time, pH, and biomass concentration affect these substrate

factors, and thus influence pretreatment performance.

Pretreatment processes can be loosely grouped into three categories: physical, chemical, and

hydrothermal. Physical pretreatments, which are typical, demand large amounts of energy and

are expensive, employing purely mechanical means to reduce feedstock particle size so as to

increase available surface area. A variety of chemicals, such as acids, alkalis, organic solvents,

oxidizing agents, supercritical fluids, and ligninase enzymes have been considered for use as

chemical pretreatment agents (Nathan-Mosier et al., 2005). These agents are used to initiate

chemical reactions in order disrupt the biomass structure.

Hydrothermal pretreatment refers to the use of water as liquid or vapour or both, to provide the

heat to pretreat biomass. Relative to dilute acid pretreatment, hydrothermal pretreatment

processes have several potential advantages in particular the fact that there is no requirement

for purchased acid, for special noncorrosive reactor materials or for preliminary feedstock size

reduction (Nathan-Mosier et al., 2005). Furthermore, hydrothermal processes produce much

lower quantities of hydrolyzate neutralization residues, which result from the process and may

be an adverse influence on the formation of large amounts of biomass. Review of further studies

and discussion regarding microbial fermentation will be found in Section 2.3 - Microbial Aspects

of Fermentation Technology.

2.2 The Chemistry of Plant Biomass

Plant biomass is biodegradable and serves as a good alternative source of energy and

chemical products because of its safety, reliability and resulting reduction of pollution.

Rising costs, the finite nature of fossil fuels and the ecological problems associated with CO2

emissions, are combining to create renewed interest in plant biomass as a sustainable basis

for the production of alternative resources for energy, transport fuels and chemicals (U.S.

Department of Energy, 2005).

Sugar cane bagasse is the fibrous matter that remains after sugarcane is crushed to extract the

juice. A typical chemical analysis of bagasse is (on a washed and dried basis): cellulose 45–55%,

hemicellulose 20–25%, lignin 18–24%, ash 1–4%, waxes <1%. Currently bagasse is being used as

a primary fuel for sugar milling and processing operations, with occasional supplementation by

sawdust, coal and fuel oil (Womersley, 2006). The component of bagasse that is of most interest

in an industrial sense is the fraction of hemicellulose-.

The major polysaccharides in the primary wall of plants are cellulose, hemicellulose and pectin.

The secondary cell wall consists of woody tissue, which is composed predominantly of cellulose,


14

lignin, and hemicellulose. Together, these layers are called “lignocellulose” (Almersheim, 1976 ).

Plant biomass consists mainly of three components: starch; pectin; and lignocellulose. Each of

these will now be discussed in turn, with particular respect to their potential ability to act as a

source of energy and essential chemicals.

2.2.1 Starch

Starch is the major carbohydrate reserve in plant tubers and seed endosperm where it is found

as granules, each typically containing several million amylopectin molecules accompanied by a

much larger number of smaller amylose molecules (Shigechi et al., 2004). The structure of starch

is shown in Figure 2.1. By far the largest commercial source of starch is corn (maize) with other

commonly used sources being wheat, potato, tapioca and rice. Recent years have seen the

introduction of large scale processing for the bioconversion of biomass resources, especially

starchy materials, to ethanol, which is expected to find a wide range of applications, including

use as a biofuel and as the starting material for various chemicals. However, the process is

expensive. There are two main reasons for the present high cost: firstly that the yeast

Saccharomyces cerevisiae cannot utilize raw starchy materials, so large amounts of amylolytic

enzymes, (glucoamylase and α-amylase) need to be added; and secondly that the starchy

materials need to be cooked at a high temperature (140°C to 180°C) to obtain a high ethanol

yield. Non-cooking and low-temperature cooking fermentation systems, used to reduce the

energy cost for the cooking of starchy materials, have succeeded in reducing energy

consumption of the process by approximately 50%. However, it is still necessary to add

amylolytic enzymes to hydrolyse the starchy materials to glucose (Shigechi et al., 2004) which is

a costly exercise. On the other hand, some scientists disagree with the use of starch to produce

ethanol or any other industrial chemicals from starchy crops because this practice can be seen to

be contributing to a global food shortage (Fong, 2008).

The main drawback of using starch is that its high sensitivity to moisture renders it unsuitable for

many applications. In an effort to overcome this problem, synthetic plastics have been

experimentally combined with starch (Janssen and Moscicki, 2009), leading to new materials

with properties similar to the modern plastics that fulfil the market demand. Such "mixed"

plastics may contain as much as 50% w/w starch.


15

Figure 2.1: Chemical structure of starch.

(Source: Unina, 2009, http://www.whatischemistry.unina.it/en/starch.html)

2.2.2 Pectin

Pectin is a heteropolysaccharide compound which consists of primary cell wall of plants. Pectin

consists of a chain-like configuration of D-galacturonic acid which makes pectin-backbone

named homogalacturonan (Figure 2.2).

Figure 2.2: Chemical structure of pectin

(Source: Cybercolloids, http://www.cybercolloids.net/library/pectin/introduction-pectin-

structure)

Many plants including legumes, vegetables, and citrus fruits have high levels of pectin. Pectin is

an insoluble protoprotein which is contained in a section of non woody parts of the plants.

Pectin is considered an important dietary fibre, and is reputed to have many health benefits.

Pectin does not, however, have an important role as a nutritional or fermentable substrate. The

quantity, structure and chemical constitution of pectin in plants vary throughout the plants’


16

structure. For example, the skins of citrus fruits, apples and other fruits contain much more

pectin than the pulp. Fruits become ripe and soften due the enzymatic action of pectinase and

pectinesterase breaking down pectin (Cybercolloids; Belitz et al., 2004).

2.2.3 Lignocelluloses

Plant cell walls are composed of cellulose and hemicellulose, pectin and in many cases lignin.

Lignocellulosic biomass refers to plant biomass that is composed of cellulose (44%),

hemicellulose (30%), and lignin (26%) (U.S. Department of Energy, 2005). The dry mass

composition of various lignocellulosic materials including carbohydrate and non-carbohydrate

are shown in Table 2.1.

Figure 2.3: Structure of lignocellulose (ref. Rubin, 2008, page 843 figure 2)

For use as a fermentation substrate, lignocellulosic biomass is firstly pre-treated by physical and

chemical means to free the polymeric components lignin, cellulose and hemicellulose.

Fractionation and enzymatic treatment can subsequently yield various output streams that are

rich in phenolics from lignin, glucose from cellulose and pentoses (mainly xylose and arabinose)

from hemicellulose. Fractionation is necessary to enable the extraction of chemicals from these

streams for further processing and the use of unfractionated lignocellulosic can lead to the


17

inhibition of microbes during biofuel fermentations, mainly caused by phenolics and their

derivatives (Singh and Mishra, 1995).

The principal components of lignocellulose (lignin, cellulose and hemicellulose) are examined in

more detail in the following paragraphs, particularly with respect to their potential as a

substrate for microbial industrial processing.

Table 2.1: Comparison of various lignocellulosic raw materials (Lee, 1997)

Carbohydrate (% of sugar equivalent)

Corn

stover

Wheat

straw

Rice

straw

Rice

hulls

Bagasse

fibre

Cotton

gin

trash

Newsprint Populous

tristis

Douglas

fibre

Glucose 39.0 36.6 41.0 36.1 38.1 20.0 64.4 40.0 50.0

Mannose 0.3 0.8 1.8 3.0 n/a 2.1 16.6 8.0 12.0

Galactose 0.8 2.4 0.4 0.1 1.1 0.1 n/a n/a 1.3

Xylose 14.8 19.2 14.8 14.0 23.3 4.6 4.6 13.0 3.4

Arabinose 3.2 2.4 4.5 2.6 2.5 2.3 0.5 2.0 1.1

Non carbohydrate (%)

Lignin 15.1 14.5 9.9 19.4 18.4 17.6 21.0 20.0 28.3

Ash 4.3 9.6 12.4 20.1 2.8 14.8 0.4 1.0 0.2

Protein 4.0 3.0 n/a n/a 3.0 3.0 n/a n/a n/a

2.2.3.1 Lignin

Lignin is a complex polymer of phenylpropane units and is a component of wood. It is cross-

linked to cellulose fibers, hardening and strengthening the cell walls of plants with a variety of

different chemical bonds. The function of lignin is to give plants structural rigidity and to protect

their cellulose and hemicellulose from microbial attack. It has been shown that the fungi and

actinomycetes are able to degrade very low amount of lignin (Richard, 2006). This is relevant for

microbial fermentation processes. However, since lignin is very difficult to degrade, it is unlikely

to be a good choice for use in industrial fermentation processes.

2.2.3.2 Cellulose

Cellulose is a polysaccharide which contain a straight chain of few hundred to over ten thousand

β (1→4) linked D-glucose molecules. There are only few enzymes are needed to break down this


18

molecule due to its conservative structure and repeated similar linkages. Humans do not have

suitable enzymes to break down cellulose but some microorganisms are capable of degrading

cellulose.

Traditionally, baker’s yeast (Saccharomyces cerevisiae), has been used in the brewery industry to

produce ethanol from hexoses (6-carbon sugars). Due to the complex nature of the

carbohydrates present in lignocellulosic biomass, a significant amount of xylose and arabinose

(5-carbon sugars derived from the hemicellulose portion of the lignocellulose) is also present in

the hydrolysate. For example, in the hydrolysate of corn stover, approximately 30% of the total

fermentable sugars is xylose (Karhumaa et al., 2005). As a result, the ability of the fermenting

microorganisms to use the whole range of sugars available from the hydrolysate is vital to

increase the economic competitiveness of cellulosic ethanol and potentially bio-based

chemicals.

Recently, genetically engineered yeasts has been developed to efficiently ferment xylose and

arabinose (Öhgren et al., 2006), and even both together. Yeasts are especially attractive for use

in cellulosic ethanol processes as they have been used in such processes for hundreds, even

thousands, of years. Their advantages are that they are tolerant to high ethanol and inhibitor

concentrations and as they can grow at low pH values. This prevents bacterial contamination

(Karhumaa et al., 2005), bacteria being less tolerant of acidity than yeasts.

2.2.3.3 Hemicellulose

Hemicellulose are a heterogeneous class of polymers representing in general, 15–35% of plant

biomass and which may contain many different sugar monomers: pentoses (d-xylose, l-

arabinose); hexoses (d-mannose, d-glucose, d-galactose); and/or uronic acids (d-glucuronic, d-4-

O-methylgalacturonic and d-galacturonic acids). Hemicellulose contain mostly d-pentose sugars

and occasionally small amounts of L-sugars as well. Xylose is always present in the largest

amounts, but mannuronic acid and galacturonic acid also tend to be present. Other sugars such

as l-rhamnose and l-fucose may also be present in small amounts and the hydroxyl groups of

sugars may be partially substituted with acetyl groups (Desantis et al., 2007). Xylans are the

main hemicellulose components of secondary cell walls constituting about 20-30% of the

biomass of hardwoods and herbaceous plants. Mannan-type hemicellulose like glucomannans

and galactoglucomannans are the other two major hemicellulosic components of the secondary

wall of softwoods whereas in hardwoods they occur in minor amounts. In some tissues of

grasses and cereals, xylans can account for up to 50% (Heinze et al., 2005). Xylans are usually


19

available in huge amounts as by-products of forest, agriculture, agro-industries, wood pulp and

paper industries.

In contrast to cellulose, which contains only anhydrous glucose, sugar monomers in

hemicellulose can include not only glucose, but also xylose, mannose, galactose, rhamnose, and

arabinose. Unlike cellulose, hemicellulose (also a polysaccharide) consists of shorter chains -

500-3000 sugar units as opposed to 700- 15,000 glucose molecules per polymer present in

cellulose. In addition, hemicellulose is a branched polymer, while cellulose is unbranched. Xylan

is an example of a pentosan consisting of D-xylose (Figure 2.4) units with 1β→4 linkages.

Figure 2.4: Chemical structure of xylan and xylose formation (Held, 2012, page

3, Figure 3)

Utilization of the fraction of hemicellulose in lignocellulosic biomass is an important factor in

optimizing the economics of biomass fuel processes, given that hemicellulose makes up a

significant proportion of the potentially available carbon for fermentation or chemical

extraction. Although there are several potential uses of hemicellulose-enriched fractions as

specialty or industrial chemicals produced by non-biological processes, the use of hemicellulose

carbon as a fermentable substrate remains an attractive route for producing chemicals that have

an intrinsic commercial value.

2.3 Microbial Aspects of Fermentation Technology

2.3.1 Fermentation of lignocellulosic sugars

Research and development studies of fermentation technology have been conducted over the

last few decades to make fermentation processes more efficient. In principle, most of the


20

biochemical and microbiological problems, such as discovering suitable strains of

microorganisms, and establishing optimal conditions, have been addressed.

Fermentation of lignocellulosic biomass is a good option to deal with several industrial and

agricultural by-products. Lignocellulosic biomass is a sustainable product. There are several

energy crops that might be cultivated at different seasons of the year, and these could deliver

high energy industrial products throughout the year, rather than seasonally (Lin and Tanaka,

2006).

However, the problem still to be solved is that of identifying suitable pentose utilizing

microorganisms. Unlike the age-old processes based on Saccharomyces fermentation of glucose,

processes and organisms for use with lignocellulosic feed-stock are yet to be put into practice in

an industrial sense, and are still in the research and development phase. Some of the difficulties

encountered in this area of research will be now discussed.

The first issue to be resolved in studying the effect of pentose fermentation pathways is an

observed inhibition effect. Castro et al., (2003) reported that in order to minimize negative

effects on the pentose fermentation process, it was necessary to: prevent accumulation of

inhibitory components (such as hydroxymethylfurfual) by detoxifying them; improve media

composition; and allow the microorganism to acclimatize to the toxic inhibitors. In addition,

hemicellulosic hydrolysates are used to dilute the raw material to a standard sugar

concentration. Similar processes may be applied for the industrial production of ethanol. This

has the potential to ensure high levels of product whilst avoiding treatment designed to remove

inhibitory compounds that are normally found in the hemicellulosic acid hydrolysate. Such a

dilution step also decreases the necessity for addition of extra microbial nutrients and requires

minimal changes to industrial fermentation plants and processes for its implementation. The

performance of an innovative two-stage continuous bioreactor with a cell recycle-potential,

capable of giving very high productivity was investigated by Chaabane et al., (2006).

Fermentative activity of the yeast, Saccharomyces was not influenced by the total biomass

concentration in the range tested (up to 157 g L−1). A key parameter for improving ethanol

production would then be a better management of the cell viability (Chaabane et al., 2006).

A second issue related to the effective utilization of lignocellulosic biomass by fermentation is

the presence of a mixture of carbon sources, the major components being cellulose, which is

almost all glucose, and hemicellulose, which consists partly of pentose and partly of hexose

sugars. Consequently, pentose sugars (e.g., xylose, arabinose, and ribose) constitute a smaller

proportion of lignocellulosic biomass than do hexoses. Moreover, microorganisms generally use


21

hexoses preferentially over pentoses. Therefore, reliance on the fermentation of pentoses alone

could never become a viable strategy for commercial fermentation processes. Inevitably, there

are some exceptions, such as the conversion of xylose to the sweetener xylitol, but such cases

are rare (Hahn-Hägerdal et al., 2007).

Unfractionated hydrolysates, including pentoses, would obviously be the preferred fermentation

substrate so long as the microorganism can convert the various available sugars, whether they

are pentoses or hexoses or a mixture of these (Bruinenberg et al., 1983). Culture-based solutions

to the mixed carbon-sources problem include sequential fermentation with different microbial

species, and the co-culture of several microorganisms with different substrate capabilities.

Alternatively, the use of a single microorganism capable of using all of the substrates present is

an attractive option. Due to the resulting simplification of the industrial process a single-vessel

fermentation step may be employed, with a single starter culture as the inoculum.

One very common outcome of mixed carbon source fermentation is the diauxie phenomenon,

whereby one sugar (generally the energy-efficient glucose) is used prior to the other(s). This

characteristic can be easily observed by measuring the growth curves of an organism growing in

a mixed carbon source medium, noting particularly that two distinct growth phases are present,

separated by a lag period. The diauxie growth pattern is generally attributed to catabolic

repression (Nishizawa et al., 2004).

Inhibition of β-galactosidase expression in a glucose-lactose diauxie system is a typical example

of a catabolic repression effect in Escherichia coli, and this has therefore been used as a model

system to investigate the mechanism of the diauxie phenomenon. It is assumed that the

inhibitory effect of glucose on the expression of the lac operon is mediated by a reduction of the

cyclic Adenosine Mono Phosphate (cAMP) levels in the glucose-lactose system (Grimmler et al.,

2010). However, there is no direct evidence to support this explanation.

In order to examine the roles of cAMP and the cAMP receptor protein (CRP) in the diauxie effect,

the intracellular levels of these factors were determined during diauxie growth in a glucose-

lactose medium (Verho et al., 2003; Wang et al., 2005). The levels of cAMP and CRP in the

lactose grown phase were not higher than those in a glucose-grown phase. Addition of

exogenous cAMP eliminated diauxie growth but did not eliminate glucose repression. Glucose

repression and diauxie were observed in cells that lacked cAMP but produced a cAMP-

independent CRP (Wong et al., 1997; Jeppsson et al., 2006). In addition, inactivation of the lac

repressor by the disruption of the lacI gene or the addition of IPTG, effectively eliminated


22

glucose repression. For this purpose, a novel lag model was proposed for diauxie, which has two

functional forms, each embodying the dependence of total cell mass on the lag period with

higher cell mass resulting in a shorter period of growth suppression between primary and

secondary substrates (Wong et al., 1997).

The efficiency of sugar breakdown in microorganisms is dependent not only on the metabolic

pathways available to the organism, but also on the effective transport of the sugar molecules

into the microbial cell. Carrier-mediated transport is the predominant mechanism of sugar

uptake in microorganisms. Specific mechanisms and relative uptake rates for various sugars are

species dependent (Singh and Mishra, 1995). At least in baker’s yeast (S. cerevisiae), the uptake

rates of xylose and glucose are comparable, but the efficiency of xylose transport appears to be

lower than that of glucose, and the yeast’s affinity (Michaelis constant) for xylose is much less

than for glucose (Singh and Mishra, 1995; Toivari et al., 2001).

Efficient use of the lignocellulosic fraction as a fermentation feedstock may be effected by one

of at least three possible scenarios. The first option requires microbes that can metabolise the

pentoses in the presence of glucose, preferably without being subject to catabolite repression

and so being capable of the simultaneous use of the sugars. A second possibility is that the

selected microorganism should carry out an efficient diauxie process using two or more sugars

sequentially. A third option is to use a sequential process involving a number of microbial

processes to enhance the selective fermentation of hemicellulose pentoses in a mixture of

substrates. In such a scenario, any glucose present could be used later, or earlier, in ethanol

production by S. cerevisiae (Attfield and Philip, 2006). This is an attractive option, because large

scale ethanol production by S. cerevisiae is an established technology that will be hard to replace

by alternative biological processes (Becker and Boles, 2003). From the perspective of maximizing

the yield of ethanol as a biofuel, a process that can rescue glucose from the hemicellulose

fraction for use in high yielding yeast fermentation would be desirable (Hahn-Hägerdal et al.,

2006), and would consequently prevent the possibility of catabolite repression.

2.3.2 Microorganisms with a natural ability to ferment lignocellulosic biomass

Several microorganisms, including certain bacteria, yeasts and filamentous fungi, have been

reported as being able to ferment lignocellulosic hydrolysates, so generating ethanol. As ethanol

production is the oldest and most familiar industrial fermentation process known, this is the best

researched of the microbial fermentation processes.

It might reasonably be expected that a pentose-utilizing microorganism can be found in a

hemicellulose-enriched habitat. Such environments include any areas where decaying plant


23

matter may be present, such as soil and natural water-sources (ponds, streams). Soil bacteria

such as Mycobacterium spp, Corynebacterium sp, and Clostridium acetobutylicum, are able to

utilize pentoses naturally (Singh and Mishra, 1995). Others mentioned in the literature have

included bacteria such as Klebsiella species and Bacillus sp, and yeasts such as Pichia stipitis, and

Kluveromyces species. A number of other naturally occurring organisms that convert pentoses to

ethanol are listed in Table 2.2 (Singh and Mishra 1995). Kastner et al., (1999) listed the yeast P.

stipitis, Pachysolen tanophilus and Candida shehatae as potential pentose fermenters.

Rhodococcus spp are particularly important due to their ability to catabolize a wide range of

compounds and produce bioactive steroids, acrylamide and acrylic acid and their involvement in

fossil fuel biodesulfurization (McLeod et al., 2006).

Table 2.2: List of pentose utilizing microorganisms (adapted from Singh and Mishra, 1995)

The common and well-known bacterium, Escherichia coli, also has some advantageous

characteristics as a candidate for ethanol production, such as its ability to ferment a wide range

of sugars, including D-xylose and L-arabinose, its capacity for simple genetic manipulation and its

history of prior industrial use (e.g. for the production of recombinant proteins). However, a

number of drawbacks can also be identified: the neutral preferred pH range (6–8) makes

bacterial fermentation susceptible to contamination; the low tolerance to lignocellulose derived

inhibitors; low ethanol tolerance; and mixed product formation (ethanol, acetic acid, lactic acid

and others), reducing the yield of any single product such as ethanol (Dien et al., 2003).

The high ethanol yield and specific productivity observed for the yeast, Zymomonas mobilis are

consequences of anaerobic D-glucose utilization using the Entner–Doudoroff (ED) pathway.

However, Z. mobilis has disadvantages similar to those of E. coli, such as the neutral pH range

and low tolerance to lignocellulose-derived inhibitors. Moreover, Z. mobilis has a narrow

substrate range, lacking the ability to utilize all of the main sugars from lignocellulose except D-

glucose.

Bacteria Yeasts and moulds Actinomycetes

Zymomonas mobilis Zymobacter palmae Escherichia coli Salmonella typhimurium Clostridium acetobutylicum Bacilus subtilis

Saccharomyces cerevisiae Rhodotorula glutinis Pichia stipitis Candida shehatae Aspergillus niger Rhizopus solani Fusarium oxysporum

Rhodococcus


24

The yeast S. cerevisiae is the most commonly used microorganism in traditional industrial

fermentations, including current sucrose, starch and cellulose based fermentation processes,

and can efficiently ferment simple hexose sugars, such as D-glucose, D-mannose and D-

galactose, and disaccharides like sucrose and maltose (Richard et al., 2003). S. cerevisiae also has

a relatively good tolerance to lignocellulose-derived inhibitors and high osmotic pressure

(Moorbach and Krämer, 2003). Furthermore, the fermentation rate is not significantly reduced

at ethanol concentrations below 10% (v/v) (Ozcan et al., 1991). The major inconvenience in

using S. cerevisiae for lignocellulosic fermentation is its lack of any natural ability to utilize the

pentose sugars D-xylose and L-arabinose, which dominate the pentose sugar fraction of

hemicellulose.

In contrast to S. cerevisiae, the yeast Pichia stipitis is able to metabolise the main hemicellulose

sugar monomers and to ferment xylose. P. stipitis, its anamorph Candida shehatae, and also

Pachysolen tanophilus efficiently ferment xylose but only under oxygen limited conditions

(Ligthelm et al., 1988). Moreover, these yeasts are less tolerant to pH, ethanol and hydrolysate

inhibitors when compared to S. cerevisiae (Hahn-Hägerdal et al., 2007). P. stipitis is also

described as being capable of producing hemicellulolytic enzymes (Jeffries et al., 2007).

2.3.3 Genetic modification of microorganisms to allow pentose fermentation

A lack of microorganisms that are able to naturally and efficiently ferment hexoses and pentoses

is a major constraint to the economic utilisation of biomass. Therefore, recombinant strains of

bacteria and yeast have been developed to meet the requirements of industrial lignocellulose

fermentation.

Escherichia coli, Klebsiella oxytoca, and Zymomonus mobilis have all been genetically engineered

to produce ethanol efficiently from all hexose and pentose sugars present in the polymers of

hemicellulose (Ingram et al., 1987; Dien et al., 2002; Kim et al., 2007; Yanase et al., 2007). Three

recombinant fermentation strains were designed as candidates for the improvement of biofuel

processes. These were S. cerevisiae, E. coli and Zymomonas mobilis ( Singh and Mishra, 1995;

Hahn-Hagerdal et al., 2001; Attfield and Philip, 2006). Others mentioned in the literature

included Klebsiella species, Pichia stipitis, Bacillus species and Kluveromyces species (Bothast et

al., 1999).

Kawaguchi et al., (2006, page 3418) reported that wild type “C. glutamicum was unable to utilize

xylose under both standard aerobic and oxygen deprivation conditions, owing to the lack of

xylose isomerase activity. However, metabolically engineered C. glutamicum has been widely


25

used for the industrial production of various amino acids and nucleic acids from sucrose and

glucose based media”.

In my opinion, both biocatalyst and genetically modified derivatives of microbes are potentially

useful for the conversion of pentose-rich feed stocks such as corn stover, corn fiber, bagasse,

rice hulls, and rice straw into commodity chemicals such as lactic acid, fatty acids, acetic acid and

several other industrial chemicals. However the genetic modification processes are time

consuming and expensive.

2.3.4 End-products of microbial fermentation of lignocellulose

According to Rosenberg (1980), methods are available for biologically converting pentose sugars,

which are the major constituents of hemicellulose, to ethanol and other neutral products. These

products could be used as clean-burning liquid fuels, solvents or chemical feed-stocks. Pentose

fermentations which did not yield ethanol as a significant product (>5% yields, g/g substrate

fermented) were not considered as potential biofuel processes (Rosenberg, 1980). Lactic acid,

fatty acids and acetic acid are used in the food industry as additives, flavouring agents and

preservatives. A list of microbial end-product from pentose fermentation is supplied in Table 2.3.

The production of lactic acid and its derivatives is economically dependent on many factors of

which the cost of raw material is highly significant. It is very expensive to use purified sugars like

glucose and sucrose as the feedstock for lactic acid production. Different food or agro-industrial

products or residues are cheaper alternatives to refined sugars for lactic acid production.

Sucrose-containing materials such as molasses, starchy materials and lignocellulose/

hemicellulose hydrolyzates are most economical for use in lactic acid production (Patel et al.,

2004). Sugarcane bagasse has been reported to be useful in lactic acid production by the fungus

Rhizopus oryzae and the bacterium Lactobacillus. However, it was used only as a supplement to

the sugars or starch hydrolyzate that comprised the major carbon source (Barker and Worgan,

1981). Generally, Lactobacillus species are deficient in cellulolytic and amylolytic capacity (that

is, they lack the capability for breaking down starch into sugars), so necessitating the prior

hydrolysis of cellulosic and starchy wastes to improve their utilization (John et al., 2007).

Corynebacterium spp are Gram-positive bacteria, constituting part of the Actinomycetes

subdivision of Eubacteria. Some unknown pathogens of human and others are industrially

important due to their ability to degrade a wide range of chemicals. When grown in a mineral

medium and under conditions of oxygen deprivation, this aerobic bacterium is essentially under

bacteriostatic conditions, but continues to maintain its major metabolic capabilities. It is

therefore able to excrete significant amounts of several metabolites, such as lactic, succinic, or


26

acetic acids, even though cellular growth is essentially arrested (Kawaguchi et al., 2006). By

stopping the production of cell biomass a process will occur, which stimulates the productiony of

end products. . C. glutamicum uses many ordinary substrates such as sucrose and glucose for

industrial product yield. But until recently C. glutamicum were unable to utilize xylose due to

lack of appropriate enzyme systems. Xylose degradation is necessary for microorganisms that

are required to produce valuable industrial products from lignocellulosic biomass. Kawaguchi et

al., (2006) solved this problem by modifying a recombinant C. glutamicum strain with ability to

utilizing both glucose and xylose.Using the conventional, well developed methods of thermal or

acidic pre-treatment (Lee, 1997), lignocellulosic raw materials are de-lignified. Then, either

simultaneously (simultaneous saccharification and fermentation process) or separately, ethanol

fermentation is carried out utilizing the released hexose and pentose sugars in the cellulose and

hemicellulose hydrolyzates.

Scientists at the Solar Energy Research Institute, USA (U.S. Department of Energy, 2005)

conducted an economic analysis of xylose fermentation and a simultaneous saccharification and

fermentation process for wood to ethanol conversion. It was demonstrated by this team, that

the production cost of ethanol could be reduced from $US1.65 to $US1.23 per gallon (converted

to Australian currency (exchange rates correct as on 11th July 2012).This is a reduction of 1.61

cents/litre to 1.20 cents/litre) if all the xylose was utilized for the ethanol production. Enhancing

the yield of xylose utilization from 85% to 95% resulted in a cost reduction by 2.4 cents (US) per

gallon, and in a decrease in fermentation time from 2 days to 1 day, bringing about a cost

reduction of 1.3 cents (US) per gallon. Based on the cost of wood at $US34 per dry ton and on a

fermentation capacity of 10,000 tons per day, an estimated ethanol production cost of 74 cents

(US) per gallon (21 cents (AU$) per L) was obtained. From this information, it is evident that

bioconversion of xylose to ethanol has the potential to markedly affect the cost of overall

ethanol production from lignocellulosic biomass (Von Sivers and Zacchi, 1996).


27

Table 2.3: List of microbial products from pentose fermentation (Singh and Mishra, 1995)

Product name Bacteria Yeast

Acetic acid, Acetone,

butanol, Propionic acid

Clostridium, Bacillus

Lactic acid, Citric acid Bacillus Aspergillus, Saccharomyces,

Candida

Xylitol, Pentitol Corynebacteria,

Mycobacterium

Saccharomyces, Pichia, Candida

In terms of non-ethanol end-products, amino acids are amongst the most important, particularly

in nutrition, owing to their central role in biochemistry. Convenient sources of amino acids are

being researched for industrial production purposes. For example, Beaman et al., (1971 ) were

able to recover more than trace amounts of arginine, aspartic acid, glycine, lysine, serine,

threonine, valine, phenylalanine, leucine, and isoleucine from the cell walls of Nocardia rubra.

They also confirmed the presence of minor amounts of several amino acids in thoroughly

washed and unextracted cell walls of Nocardia spp. It was observed that alkaline ethanol

removed these "background amino acids" too.

Some investigators have suggested that the amino acids found in small quantities in cell wall

hydrolysates are the result of contamination with cytoplasmic components. It would appear

from a quantitative investigation, using both alkaline ethanol extracted and unextracted cell

walls prepared from actively growing bacteria (N. Rubra) (Beaman, 1975), that a significant

amount of peptide is associated with the lipoidal components of the outer cell envelope. The

loss of this material is associated with a loss of a characteristic pattern of convolutions present

on the surface of actively growing N. rubra. Earlier investigators, employing growth conditions

differing variously from those employed by Beaman et al., (1971) and using mild methods of

extracting carefully prepared cell walls, noted the effects of such extraction on the

ultrastructures of the cell envelope.

According to Hermann (2003), the total annual worldwide consumption of amino acids in 2003

was estimated to be over 2 million tons (1,814,370 tonnes), a figure which has no doubt been

exceeded in 2012. The annual demand for amino acids like MSG-based flavour enhancers or feed

additives comprised mainly of L-lysine, D, L-methionine and L-threonine, is estimated to be

significantly higher than 1 million tons (907,185 tonnes) each. In addition, the annual demand


28

for amino acids used in pharmaceutical products, mainly for intravenous nutrition, was 15,000

tons (13,608 tonnes).

l-Valine,l-isoleucine, l-threonine, l-aspartic acid and L-alanine are some of the amino acids

produced by Corynebacterium. Around 1.5 million tons (1.36 million tonnes) L-glutamic acid are

produced per year using coryneform bacteria. It is clear that amino acids are essential

requirements for the food and pharmaceutical industries and that the Corynebacterium group of

bacteria are capable of producing amino acids. Since amino acids are essential requirements for

the food and pharmaceutical industries, it follows that the coryneform group of bacteria should

prove to be an ideal group for the purpose of synthesising those products from previously

discarded agricultural waste, which is the main focus of my research.

2.3.5 Ecology of microbial communities

Microbes are capable of changing their habitat, metabolic characteristics, and ecological roles

over time. It is possible to detect microbial roles and densities in the environment by ecological

analysis. Fast and reliable cultivation-independent identification techniques for filamentous

bacteria in activated sludge have been employed for the evaluation of their importance in the

sewage treatment process as well as for investigation into the problems that may arise during

the process. The earlier study by Schuppler et al., (1998) demonstrated that the classical

approaches failed to differentiate foam-causing species such as Gordona amarae, Rhodococcus

rhodochrous and Tsukamurella paurometabolum due to their variable morphology, staining

behaviour and fastidious nature. As previous research has shown, there are several methods

available for comparative sequence analysis of 16S rRNA sequences directly retrieved from

natural microbial communities. This represents the most powerful method for describing species

composition of ecological niches, as both cultured and as yet uncultured microorganisms can be

identified.

Microbial ecology research is generally based on either autecological or synecological

approaches. Autecological studies are those involved with the behaviour of the individual

species with in a population, while synecological studies deal with interaction of populations of

different kinds of microorganisms within an ecosystem (Craig et al., 2010). Survival and activity

of viruses and bacteria in sewage systems, surface water, groundwater, and aerosols are

examples of suitable issues for synecological study. Indicator organisms, such as E. coli, in

sewage water and receiving water fall in the autoecological domain (NH&MRC, 2004).

Autecological study of indicator bacteria involves the issues of the habitats, life cycles and


29

nature of the relationship of the indicator to the presence of pathogenic bacteria (Craig et al.,

2010).

Habitatoriented issues are generally best studied by synecological methods, Example include

studies of biogeochemical cycling (the carbon cycle, nitrogen cycle, sulphur cycle etc.), microbial

ecology of the rumen, microbial interactions in sewage, biodegradation of pollutants in soils and

aquatic ecosystems, and the production of goods such as cheese, pickles and fermented

beverages (Christon, 1991).

Metagenomic libraries with molecular bases (phylogenetics, DNA microarrays, and functional

genomics) are powerful tools for exploring microbial diversity in various ecosystems, and also for

investigating the large amount of data regarding the genetic information derived from

uncultured microorganisms. This information will form the basis of new initiatives aiming to

conduct genomic studies that link phylogenetic and functional information about environmental

microbial flora, including both culture-capable and uncultured.

Craig et al., (2010) reviewed progress toward understanding the biology of uncultured Bacteria,

Archaea, and viruses through metagenomic analyses. For sequence-based approaches, the

speed and cost of nucleotide sequencing will cease to be a barrier as sequencing technology

continues to improve and becomes less expensive. Advances that will facilitate the management

and analysis of large libraries include bioinformatics tools to analyze vast sequence databases

and reassemble multiple genomes rapidly, together with affordable gene chips for library

profiling and the ready distinction of clones that are expressing genes, from those clones that are

silent. Functional analysis will require more innovation in method development. Most important

among these are the strategies to improve heterologous gene expression and approaches for the

efficient screening of large libraries (Sebat et al., 2003). Amann et al., (1995) estimated that

>99% of microorganisms that were observable in nature typically were not able to be cultivated

using standard culture techniques. The majority of the bacterial taxonomic divisions are poorly

represented by cultured organisms. The overall performance of 16S rDNA sequence analysis was

considered to be excellent, since it was able to resolve almost 90% of identifications, when

applied to a large collection of phenotypically unidentifiable bacterial isolates. In order to

improve this performance, efforts should be made to complete 16S rDNA databases with high-

quality sequences and to develop electronic tools for sequence comparison and interpretation.

2.4 Methodology

2.4.1 End product analysis by high performance liquid chromatography (HPLC)


30

The identification and analysis of amino acids has permitted vast research efforts into protein

and food testing since Moore and Stein (1951) invented an ion exchange chromatography

process to isolate un-derivatized amino acids (AAs) subsequent to post-column derivatization

with ninhydrin and further identification. Many developments followed this initial work,

resulting in the sophisticated procedures such as HPLC, which are used for the same purposes,

but with much greater efficiency and accuracy today. OPA is used to detect primary amino acids.

However, the secondary AAs were not detected, because another derivatizing agent, 9-

fluorenylmethyl chloroformate (FMOC), necessary for their detection, was not used in this

research.

High performance liquid chromatography (HPLC) is basically a highly improved form of column

chromatography. Instead of a solvent being allowed to drip through a column under gravity, it is

forced through under high pressures of up to 400 atmospheres (Lefebvre et al., 2002). There are

some differences between HPLC and gas chromatography (GC), which make HPLC cheaper and

faster than GC. Firstly, the process of separating the compounds in a mixture is carried out

between a liquid stationary phase and a gaseous mobile phase in a GC, whereas in HPLC the

stationary phase is a solid and the moving phase is a liquid. Secondly, the column through which

the gas phase in GC passes is located in an oven where the temperature of the gas can be

controlled, whereas HPLC typically has no issues with temperature control. Thirdly, for a GC the

concentration of a compound in the gas phase is solely a function of the vapour pressure of the

gas; whereas HPLC is not affected by such a concentration problem.

Liquid chromatography with electrochemical or fluorescence detection has been used to analyse

amino acids. However, the fluorescence detection has greater sensitivity and so is usually

selected. As amino acids do not fluoresce, a derivatizationis required. The reagent o-

phthalaldehyde with 2-mercaptoethanol (OPA/2-ME) as catalyst is as derivatizant (Moore and

Stein, 1951; Peris-Vicente et al., 2005). The drawback of derivatization using in amino acid

analysis can be impaired by the presence of some pigments because the metallic cations of the

pigments can form complexes with some amino acids, changing the relative amount of free

amino acid. The use of a cation sequestering reagent such as ethylendiamine tetraacetic acid

(EDTA) can avoid the interference of the pigments (De La Cruz-Canizares et al., 2004).

In experiments performed by Peris-Vicente et al., (2005) asparagine and glutamine were not

analyzed, because hydrolysis converts them to aspartic and glutamic acid. The glutamic acid is

also partially converted into pyroglutamic acid during hydrolysis. The hydrolysis destroys

tryptophane, and the o-phthalaldehyde derivatives were weak, so proline and the cysteine did

not appear.


31

The direct UV or fluorescence detection of amino acids by chromatographic analysis is difficult

due to the absence of a strong chromophore or fluorophore. Specific detection approaches

have been applied such as amperometric/electrochemical, evaporative light scattering,

chemiluminescent nitrogen and mass spectrometry detectors (Zoppa et al., 2006). The

combination of chromatographic separation and pre- or post column derivatization followed by

UV or fluorescence detection remains the most convenient and widely used analytical approach

to improve sensitivity. In particular, pre-column derivatization offers the advantage of increasing

hydrophobicity of the amino acids so that they can be retained on the columns. Commercially

available derivatization UV and fluorogenic reagents commonly used for the pre-column

derivatization of amino acids are phenyl isothiocyanate (PITC), 4- nitrobenzoyl chloride, p-

nitrobenzyl bromide, o-phthalaldehyde (OPA), 9-fluorenylmethyl chloroformate (FMOC-Cl),

dansyl chloride (Dns-Cl), 4-fluoro-7-nitro-2,1,3-benzoxadiazole (NBD-F), and naphthalene-2,3-

dicarboxaldehyde (Peace and Gilani, 2005). However, the use of these reagents can involve

different drawbacks such as limited selectivity and sensitivity, low stability of the derivatives,

time-consuming derivatization procedure or the need for extraction procedures before the

analysis. OPA has the advantage of reacting rapidly under mild conditions with the primary

amino group, but generally it is used as a post-column derivatization reagent owing to the

instability of its derivatives.

Recently, 2,7-dimethyl-3,8-dinitrodipyrazolo 1,5-a:1′,5′-d]pyrazine-4,9-dione (DDPP) and 4,7-

phenan throline-5,6-dione (phanquinone) were proposed as new pre-column derivatization

reagents for HPLC analysis of amino acids using UV or fluorescence detection (Gatti and Gioia,

2008). Both compounds have been proven to be selective towards the amino function giving

stable derivatives, useful for quality control of commercial formulations. The high sensitivity of

the phanquinone method also allowed its application to biological samples. Gatti et al., (2010)

focused on the use of 2,5-dimethyl-1H-pyrrole-3,4 dicarbaldehyde (DPD). Owing to its structural

analogy with OPA, it has the intrinsic potential to react quickly under mild conditions with the

functional site of amino acids (Figure 2.5), but has not previously been studied as an analytical

reagent (Gatti et al., 2010).


32

Figure 2.5: o-phthalaldehyde (OPA) and mercaptoethanol reaction (Ref: Woodward and

Henderson, 2010, page 2, figure 1)

The Agilent 1100 HPLC is used for immediate identification of amino acids by ZORBAX Eclipse

AAA high efficiency HPLC column. It has a short analysis time from injection to injection can be

as low as 14 min (10 min analysis times) for a 7.5 cm column and 24 min (16 min. analysis times)

on the 15 cm long column. Sensitivity (5 - 50 pmol with DAD, FLD) and accuracy are gained by

using both OPA and FMOC derivitization in Agilent 1100 HPLC instrument. The Eclipse AAA is

using OPA and FMOC derivatization process for quick powerful resolution of 24 amino acids

separation (Henderson, 2009; Woodward and Henderson, 2010).

2.4.2 Denaturing gradient gel electrophoresis (DGGE)

Microbial ecological analysis has been dramatically improved in the last ten years. Conventional

procedures like culture and microscopic methods are enough to superficially explore the

microbial communities in our environment. Microscopic identification is useful for many natural

bacteria due to their irregular and small morphological cell size. However, media used for the

cultivation of environmental microorganisms do not necessarily support growth of an

increasingly recognized portion of the indigenous population and so may give a biased view of

the community composition. Isolation (culture) of the vast majority of naturally occurring

bacteria in pure culture is impossible (Muhling et al., 2008), due to our lack of knowledge of the

specific culture conditions they require and due to the potential for synergy between different

organisms. Comparisons of culturable and total microscopic cell counts from diverse habitats

have demonstrated the inadequacy of the culture-dependent approach to analyse microbial

community composition effectively (Muhling et al., 2008). Therefore, other tools are required to

supplement the conventional microbiological techniques used in microbial ecology, including

those that use the gene sequences of DNA as a molecular marker for identification of


33

microorganisms. This has dramatically changed our perception of the diversity of microbial

communities.

One of these techniques is denaturing gradient gel electrophoresis (DGGE) in which DNA

fragments are separated in a gradient of DNA denaturants according to differences in their

sequences. Temperature gradient gel electrophoresis (TGGE) is a similar process but with a

changing temperature gradient (TGGE) to distinguish the DNA fragments. Both are relatively

easy to perform and are especially well suited to the analysis of multiple samples (Ercolini,

2004). Since the introduction of DGGE into microbial ecology by Muyzer and Smalla (1998), and

later work by Brons and van Elsas (2008), this method has been adapted in many laboratories as

a convenient tool for the assessment of microbial diversity in natural samples.

DGGE methods are applied to identify the similar length of double-stranded DNA fragments

through PCR amplification. The difference between the strength of GC (3 hydrogen bonds per

pairing) and AT base pairing (2 hydrogen bonds) are detected by this method. Generally high

concentration of GC containing double-stranded DNA will be stay long till they migrate to higher

concentration of denaturation. It is preferable to travel large size of double-stranded DNA in the

acrylamide gel by electrophoresis. In this situation, differing sequence of DNA fragments could

be identified in that gel (Muyzer and Smalla, 1998).

DNA extractions from microbial communities are amplified with specific set of primers for 16S

rDNA called PCR products. This is difficult to separate from each other of same size PCR products

by agarose gel electrophoresis (Dees and Ghiorse, 2001). Sequence variations between different

bacterial rDNAs bring about different melting properties of these DNA molecules, and separation

can be achieved using polyacrylamide gels containing a gradient of DNA denaturants, such as a

mixture of urea and formamide.

The PCR products are double stranded before the gel run starts. Then the products enter into

the denaturing condition and it slowly becomes stronger as the product traverses the gel. PCR

products with different sequences therefore start melting at different positions (i.e at different

denaturant concentrations) in the gel. Melting proceeds in ‘melting domains’. Once a domain

with the lowest melting temperature reaches its melting temperature at a particular position in

the denaturant gradient, a transition from a double-stranded to a partially melted molecule

occurs. The protruding single strands effectively cause a halt in the progress of the molecule at

that position. To avoid the entire separation of two DNA strands, a 40-nucleotide GC-rich

sequence (‘GC-clamp’) is adhere at the 5’-end of each PCR primers (Horst-Backhaus et al., 1996;

Morimoto et al., 2005).


34

PCR-DGGE is an identifying technique for observing to differentiate of microbial genetic diversity

and measuring the richness of dominant microbial species. Moreover, DGGE permits the

detection of individual microbes by hybridization analysis with specific probes, using DNA

sequencing analysis. The study of microbial activity in different habitats, for example soil,

sediments, water hydrothermal vents, mats sewage treatment plants, air etc are possible by

PCR-DGGE technique (Green et al., 2007; Liang et al., 2008). The microbial habitats in our

research are sourced from various samples of a hemicellulose-enriched sugar mill area.

2.4.3 Identification of unknown microorganisms based on 16S rDNA sequence

analysis

Small ribosomal subunits in prokaryotes contain 16S rDNA and the large subunit contains 5S and

23S rDNAs. Usually, microbial 16S, 23S, and 5S rDNA genes are arranged as a co-transcribed

operon. There are between one and several copies of the operon distributed in the genome. For

instance Ecoli has seven (Yusupov et al., 2001). The length of 16S rDNA is about 1.542

nucleotides, which are highly conserved. The 16S rDNA analysis has become a very valuable

tool, to permit identification the unknown and known microorganisms. One of the important

issues is the recognition of difficult-to-culture organisms in the laboratory from extreme

environments. Only about 1% of the community is revealed by culturing techniques. The ability

to map sequences has rapidly moved research in a different direction, towards analysis of the

hypervariabale regions of 16S rDNA. Generally these are at the edge of highly protected regions.

Primers can be designed to match with these regions and to amplify variable regions by PCR. It is

possible to identify a large number of species through DNA sequencing of 16S rDNA (Schuller et

al., 2010).

rRNA is naturally present in high copy numbers (up to 10,000 molecules per cell), it provides a

target for a highly sensitive PCR assay. rRNA molecules form a part of all ribosomes and can

therefore be used as a PCR target independent of gene expression. Computer alignment studies

of these rRNA sequences have revealed the existence of regions with highly conserved

sequences and regions which display sequence variability at the genus and species levels,

allowing the selection of genus- and species specific primers for the PCR (Daley et al., 2008).

The rDNA is the least variable gene in bacterial cells. Consequently 16S rDNA encoding genes

may be used to study the taxonomy, phylogeny and species diversity in all bacteria. So, the study

of 16S rDNA sequences reveals the genetic relatedness of microorganisms. Woese et al. (1990),

proposed the novel three domain system of categorization on the basis of such sequence data.

2.4.4 Metagenomic methods - PhyloChip


35

DNA microarray technology offers the possibility of analysing microbial communities without

pre-requisite cultivation, thus being ideal for biodiversity studies. A DNA PhyloChip has been

developed to assess microbial diversity, based on the transfer of 16S rRNA probes from dot-blot

or fluorescent in situ hybridization (FISH) analyses to a microarray format. Similarly, it is possible

to use 16S rRNA probes to determine a signal on the microarray by the fragmentation of the 16S

rRNA molecule, or PCR amplicon, which have to be less than 150 bp in length to minimize the

formation of secondary structures in the molecules so that the probe can bind to the target site.

Liles et al., (2010) used microarray to probe for sequences based upon a phylogenetic analysis of

16S rRNA genes recovered from members of the bacterial (Acidobacteria) division. They found

that a phylogenetic microarray was useful in revealing changes in microbial population-level

distributions in a complex microbial community (Liles et al., 2010). Phylogenetic microarrays, or

“PhyloChips”, have been inceasingly used to discriminate rapidly between diverse 16S rRNA

genes present in cultured microorganisms or environmentalsamples. Compared to the labour

and resource intensive efforts to clone and sequence a representative number of clones from a

16S rRNA gene clone library, phylogenetic microarrays can provide a rapid and efficient readout

of the phylogenetic diversity present in an environmental sample. Furthermore, a hierarchical

design permits probing for microbial taxa at different phylogenetic levels (Huyghe et al., 2008),

providing information regarding the presence or absence of the many components of the tree of

life.

In general, the same strategies for in-silico development and technical set-up for fabrication and

hybridization of the RHC-PhyloChip were used as for the development of a 16S rRNA-targeted

oligonucleotide microarray for detection of all lineages of recognized sulfate-reducing

prokaryotes (SRP-PhyloChip). In addition, due to their importance for bioremediation and

agriculture, several approaches for the detection of members of the order “Rhodocyclales” have

been developed. Besides traditional cultivation methods, molecular detection of members of

this order has been based on taxon- or clone-selective 16S rRNA gene-targeted PCR primers or

probes (Loy et al., 2005). While these molecular methods were well suited for the detection of a

few selected subgroups or species within the Order Rhodocyclales, tools for surveying the

diversity of members of this Order in parallel were lacking at the time. DNA microarrays, which

have recently been introduced to microbial ecology, generally fulfilled all requirements for the

high-resolution monitoring of complex microbial communities. Their main drawback is the

extremely high cost of purchase and interpretation of the PhyloChips.

The 16S rDNA gene has been used to identify the effects on microbial community structure using

such methods as terminal restriction fragment length polymorphism (T-RFLP), length


36

heterogeneity polymerase chain reaction (LH-PCR), denaturing gradient gel electrophoresis

(DGGE), and cloning and sequencing (Connon et al., 2005; Freeborn et al., 2005). However,

unlike these molecular analysis techniques, microarrays not only indicate general changes in

microbial community structure, but can also identify organisms present in a given sample. Our

research represents an original approach to establish better an understanding of the richness

and variety of the pentose-utilizing microbial population using a metagenomic PhyloChip

method.

This study investigates the metabolic and anabolic chanracteristics of pentose utilizing

microorganism which has not done previously. The research gaps in the literacure have

discussed in this chapter. The role of actinomycetes in sugar waste water treatment ponds and

non-sugar treatment ponds will be analysed in this research project. In addition, this research

also reports the results of analysis of the microbial diversity of microorganisms in hemicellulose-

enriched habitats.

Chapter 3 Identification

37

CHAPTER 3

Isolation and Identification of Environmental Pentose-

Utilizing Bacteria

3.0 Summary

The isolation and identification of environmental pentose-utilizing bacteria (E-PUB) are reported

in this chapter. The selected sources for this investigation were those associated with sugar-

cane mills, as the milling process results in large quantities of hemicellulose-enriched wastes.

The samples were selectively enriched in media containing single pentose sugars as the sole

carbon source. Following basic identification using phenotypic characteristics, the six remaining

isolates were identified further, using 16S rDNA testing followed by DNA sequencing. All of the

isolates were identified as members of the Order Actinomycetales, known to contain genera and

species capable of breaking down plant material, thereby producing industrially useful end

products.

3.1 Introduction

The bioconversion of pentoses derived from hemicellulose remains a problem in developing

industrial level production, as many microbes either preferentially use glucose in the presence of

mixtures of carbohydrates, or cannot use pentose sugars at all. As an initial approach towards

resolving this issue, microorganisms indigenous to a pentose-rich environment were targeted,

which are capable of metabolizing pentose sugars such as xylose, arabinose and ribose, as found

in lignocellulose.

Microorganisms such as the yeast, Rhodotorula glutinis, and bacteria such as Mycobacterium

species, Corynebacterium spp, and Clostridium acetobutylicum, are able to utilize pentoses

naturally (Singh and Mishra, 1995). A number of other naturally occurring organisms that

convert pentoses to ethanol were also named by Singh and Mishra in 1995. These included the

yeasts, Pichia stipitis, Pachysolen tanophilus and, later, Candida shehatae, which was noted by

Kastner et al., (1999).

The screening of environmental samples taken from diverse ecological niches of Queensland

sugar mills was carried out in order to explore the potential of the diversity of microbial flora of

this hemicellulose-enriched habitat. This study was undertaken with the aim of discovering the

presence of pentose-capable species of genera such as Corynebacterium and Nocardia,


38

members of the class Actinomycetes. These are known to be environmental organisms with a

capacity for production of useful bioactive metabolites. These source areas are poorly studied

and may represent diverse and largely unscreened pentose utilizing capability.

3.2 Materials and Methods

3.2.1 Sample collection

This research was carried out in order to discover pentose-utilizing bacteria from soil samples

obtained from 3 different sugar mills in the State of Queensland, Australia (Figure 3.1). The

Proserpine and Maryborough sugar mills were the targeted sampling sites.

PROSERPINE

MACKAY

MARYBOROUGH

Figure 3.1: Map of the Queensland sugar mill regions

(Johnston, http://www.johnston-independent.com/ sugar.html)

Soils from areas surrounding sugar mill waste ponds were collected from the Maryborough and

Proserpine sugar mills. Each soil sample was aseptically collected into sterile test tubes and kept

at 4⁰C until they were processed in order to prevent overgrowth by fast-growing fungi and

bacteria. Processing occurred up to 2 days after sample collection. Sample details and the

collection location are detailed in Table 3.1.

ATCC cultures (Corynebacterium cystitidis (ATCC #29593) Nocardia vaccinii (ATCC #11092)) were

used as controls when required for genotypic and phenotypic comparison with isolates.


39

Table 3.1: Locations of Collected Samples

Sample code Sampling location

58 Effluent Pond (58EP) Proserpine

31 Tailing Gully (31TG) Proserpine

41 Scodellaro (41S) Proserpine

46 Blair (46B) Proserpine

42 Caswell (42C) Proserpine

55 Tropic Isle (55TC) Proserpine

Batch one

Pond cell-1 (PC1) Maryborough








Batch two

cell-1 (NC1) Maryborough








3.2.2 Isolation and Identification (culture-based)

Bacterial strains were isolated from soil samples by means of a series of enrichment steps, in

which cultures were initially inoculated with 10% wet weight of soil using Luria Bertani (LB)

(Atlas, 2004) broths containing one of 0.5% xylose or arabinose or ribose (100 mL cultures in

500 mL Erlenmeyer flasks).


40

Medium was selected from the Handbook of Microbiological Media (Atlas, 2004). The isolation

medium used was minimal Luria Bertani broth with one of the pentoses provided as a sole

carbon source. This enabled a broad range of bacteria to be isolated, including Actinomycetes.

The widely used medium known as Luria Bertani broth is popular with bacteriologists because it

permits fast growth and good yields for many non-fastidious species. The medium consists of

tryptone, yeast extract and salt, adjusted to pH 7.0. While this is not strictly a “minimal medium”

such as would normally be provided for nutritional studies such as these, the intended target

organisms required a somewhat richer source of nutrient than would be supplied by a basal

medium.

To test the carbon source utilization, carbon sources such as pentoses (xylose, arabinose or

ribose), or a hexose (glucose) sugar were provided. Strains were isolated on the basis of their

carbohydrate utilization patterns, specifically growth on several types of pentoses, in the

presence and absence of glucose using LB broth, with the sugars added from sterile stock

solutions to provide the required carbon source(s). It was clear that the organisms isolated from

the environmental samples were not capable of using yeast extract as a carbon source, as a large

number of them could not grow in the broths containing pentose sugars. Had they been able to

utilize yeast extract as an alternative carbon source, these organisms would have grown in all of

the broths, regardless of the sugar provided, since yeast extract was present in all of the media.

Serial sub-culturing was undertaken following an initial 48 hours of aerated growth at 30°C and

this was repeated twice using a 1% inoculum into fresh LB broth with an antifungal agent

(nystatin powder 0.5mg/100ml) added each time. Cultures were aerated by shaking at 100 rpm,

because the target bacterial group was primarily the actinomycetes, which are all aerobes.

Subsequently, individual strains were isolated by plating onto LB agar media containing the same

set of pentoses. Isolates were stored in 50% glycerol at -20°C, prior to testing for their

carbohydrate utilization patterns (see Chapter 4).

As it was expected that suitable organisms for the purposes of this study would be those in the

class Actinomycetes, such as Nocardiaand Corynebacterium, particularly environmental species

of these genera, the following ATCC cultures were used as positive controls:

Nocardia vaccinii (ATCC #11092)

Corynebacterium cystitidis (ATCC #29593)


41

Gram staining, acid fast staining, motility testing, catalase testing and spore staining were

carried out to further identify the target microorganisms according to the phenotypic

characteristics noted in Bergey’s Manual (Holt, 2000).

3.2.3 DNA analysis methods

3.2.3.1 Primer design

DNA analysis was performed in order to confirm the identity of the isolated species. Allele

specific primers for Corynebacterium cystitidis (Primer A) and Nocardia vaccinii (Primer B) were

designed using the Primer Express 2.0 primer design software programme (Applied BioSystems,

USA) and are shown below. Allele specificity is determined by the type of nucleotide base at the

3’ end of the primer sequence.Primers were synthesised by Sigma–Aldrich, Castle Hill, NSW, and

Australia.

Primer A:

5’-GAA-CGC-TGG-CGG-CGT-GCT-3’

5’-ACC-TTG-TTA-CGA-CTT-CGT-3’

Primer B:

5’-GTA-AAA-CGA-CGG-CCA-GGA-TGC-AAC-GCG-AAG-AAC-CTT-ACC-T-3’

5’-CAG-GAA-ACA-GCT-ATG-ACT-ACG-GCT-ACC-TTG-TTA-CGA-CTT-CG-3’

3.2.3.2 Extraction of DNA

DNA was extracted using the QIAGEN DNeasy kit 2006 according to the instructions for Gram-

positive bacteria. The DNeasy Mini spin column was used. DNA was then eluted with buffer for

DNA purification. Presence of DNA was tested using absorbance ratio (A260:280). The critierion

for acceptability range was 1.8 to 2 and all of the results fell into this range.

3.2.3.3 PCR amplification of 16S rDNA

The reaction mixture contained master mix with water, buffer, dNTPs, primers and Taq DNA

polymerase in a single tube. The mixture was then aliquoted into individual tubes. MgCl2 and

template DNA solutions were added to the micro-tube (reagent details Table 3.2), which was

then placed on a thermocycler (BioRad, DNA engine, Peltier, Thermal cycler) to start the PCR

reaction (Bio-Rad laboratories 2008).


42

Table 3.2: PCR reaction mixture details

Reagent Final Concentration Quantity for 50 µL of

reaction mixture

Sterile deionized water - Variable

10X MgCl2 buffer 1X 3.5 µL

2 mM dNTP mix 0.2 mM of each 2.5 µL

Forward Primer 1 µM 1 µL

Reverse Primer 1 µM 1 µL

Taq DNA Polymerase 1.25 u / 50 µL 0.2 µL

Template DNA 1 µg 1 µL

Reactions were carried out in a thermal cycler under the following conditions: initial

denaturation at 94 °C for 3 min; 40 cycles of 95 °C for 1 min, 55 °C for 40 s and 70°C for 1 min 30

sec; final extension at 70 °C for 5 min.

3.2.3.4 Gel electrophoresis

To prepare the gel, a 2% agarose (2% agarose gel on TAE buffer) solution was heated (65 C -

85 C) in a microwave ovenfor about 2 min and then cooled to about 55°C, the gel poured and

the comb inserted. Once solid the gel was covered with 1X TAE running buffer and 5 µL of DNA

mixture was loaded into each well. Samples were run with 80-100 volts for 30-45 minutes.

Finally the gel was washed with buffer (0.5% ethidium bromide: 200 mL 1X TAE) and visualized

under UV light.

3.2.3.5 16S rRNA gene sequencing

The 16S rRNA was sequenced using a Big Dye Terminator Cycle Sequencing reaction. The 20-μL

sequencing reaction consisted of 1 μL Big dye, 3.5 μL sequence buffer 12.5 μL of water, 3.2 pmol

of sequencing primer, and 200 ng PCR product. Cycle sequencing was performed using a Gene

Amp PCR system (BIO-RAD, DNA engine, Peltier, Thermal cycler), programmed for 30 cycles at

96°C for 20sec, 50°C for 20sec, and 60°C for 4 min using 16S forward and reverse primer

sequences A and B from Section 3.2.2.1. Sequencing products were cleaned with 70% ethanol

wash, using ethanol/EDTA methods according to the Griffith University sequencing preparation

instructions. Sequence products were analysed using an ABI 3500 Sequencer (Applied

Biosystems). 16S rDNA sequences were assembled from forward and reverse analyses and then


43

edited with Sequencer software (Bio- Edit). 16S rDNA sequences results were compared with

sequences in GenBank, using the BLAST sequence similarity search.

3.3 Results

3.3.1 Primary identification of isolates

This research conducted all series of experiments in duplicate, to identify the target isolates. The

aim was to isolate actinomycetes, and similar or related organisms. Six cultures proved to be of

great interest from 191 isolates, from eleven different environmental sources (six samples from

Proserpine, and five from Maryborough). The characteristics of these isolates are summarized in

Tables 3.3, 3.4 and 3.5.

There were two different colony types found from the Maryborough mill (A) samples, similar to

the expected appearance of Corynebacterium, Nocardia and Mycobacterium on the basis of

colony descriptions in Bergey’s Manual (Holt, 2000). Colonies found in samples from both

Maryborough mill samples (A and B) and Proserpine mill, are described in Tables 3.3, 3.4 and 3.5

respectively. It should be noted that many of these colony types were very similar in

appearance. The biochemical tests matched correctly with the properties expected of

Actinomycetes (Tables 3.3, 3.4 and 3.5).

Table 3.3: Characteristics of selected isolates from Maryborough (A)

Sample

source

Colony appearance Biochemical properties

Maryborough

(A)

LB(0.5%

xylose)

LB(0.5%

arabinose)

LB(0.5%

ribose)

Gram

stain

Acid

fast

Catalase

test

Motility

test

Endospore

stain

PC1-2

slow growing

white, big dry

colony

_

_

+ rod

_

+

_

_

PC4-1 cream,

irregular,

filamentous

cream,

irregular,

filamentous

_

+ rod

_

+

_

_


44

Table 3.4: Characteristics of selected isolates from Maryborough (B)

Sample

source


Maryborough

(B)

LB(0.5%

xylose)

LB(0.5%

arabinose)

LB(0.5%

ribose)

Gram

stain

Acid

fast

Catalase

test

Motility

test

Endospore

stain

NC1-3

cream,

irregular, flat,

smooth

rhizoid

surface

cream,

irregular, flat,

smooth

rhizoid

surface

_ + rod _ + _ _

NC1-2 white

creamy,

irregular, flat

surface,

_ _ + rod _ + _ _

NC4-1 cream,

irregular,

filamentous

cream,

irregular,

filamentous

cream,

irregular,

filamentous

+ rod _ + _ _

Table 3.5: Characteristics of selected isolates from soil of Proserpine

3.3.2 16S rDNA analysis

PCR analysis of 16S rDNA was performed to confirm the species level identification of the E-PUB

microbes. In Figure 3.2 a, the lanes 2-7 inclusive contained the isolates NC1-2 NC1-3, PC1-2, PC4-

1, NC4-1, 31TG-3, which were amplified with A primer.

Sample

source


Proserpine LB(0.5%

xylose)

LB(0.5%

arabinose)

LB(0.5%

ribose)

Gram

stain

Acid

fast

Catalase

test

Motility

test

Endospore

stain

31TG-3 _ Light cream,

smooth, very

small in size

_ +

cocco

bacilli

_ + _ _


45

a. PCR amplification with primer A (6 unknown isolates)

Figure 3.2: 16S rDNA PCR amplification image after gel electrophoresis

Primer B effectively amplified the isolates NC1-2 NC1-3, PC1-2, PC4-1, NC4-1, 31TG-3, as shown

on Figure 3.2b. The DNA of all indigenous microbes displayed bands on agarose gel after

amplification with primers A and B, which were designed to detect the Order Actinomycetes.

Primer A was designed to detect bacteria similar or identical to Nocardia species, and Primer B

PC1-2 PC4-1 NC1-3 NC1-2 NC4-1 31TG

Indicating 5000 BP according to the marker

Amplification with primer A

PC1-2 PC4-1 NC1-3 NC1-2 NC4-1 31TG

PC1-2 PC4-1 NC1-3 NC1-2 NC4-1

Amplification with primer A 5000 BP

Amplification with primer B and 3000 BP

b. PCR amplification with primers A and B


46

was designed to identify coryneform types and organisms closely related to the

Corynebacterium.

3.3.3 16S rDNA gene sequencing

The sequences were compared using the BLAST program with the sequences in the NCBI

database. Using a threshold of greater than 77% similarity for positive identification, evidence

was found for the presence of Corynebacterium spp., Actinomycess spp., Rhodococcus spp.,

Propionibacterium spp., and Nocardia sp (Table 3.6). Twenty four (both forward A, B and reverse

A, B) sequences were obtained, only partially overlapped with the sequences from Genbank

because the sets of primers (forward and reverse) A and B were used for sequencing for

database entries. Primer A was designed to detect relatives of Corynebacterium and Primer B

was designed for Nocardia-like species. The sequences were aligned according to the similarity

between these sequences and taxonomically placed with microorganisms in Genbank. The list of

identified bacteria found from the pentose-enriched habitat is given in Table 3.6.

Table 3.6: 16S rDNA sequencing results of unknown isolates

The sequencing results, within the limitations of primers designed on partial sequences, were as

expected. They demonstrated that the isolates were all known soil organisms and members of

the Order Actinomycetales.

Isolate

code

Closest matched

Genus/Species by

Primer A

Sequence

similarity

in % (no.

of bases)

Taxonomic

group

Closest matched

Genus/Species by

Primer B

Sequence

similarity

in % (no.

of bases)

Taxonomic

group

PC1-2 Corynebacterium glutamicum

98% Actinobacteria

Corynebacterium freiburgense

80% Actinobacteria

PC4-1 Actinomyces odontolyticus

77% Actinobacteria

Actinomyces odontolyticus

83% Actinobacteria

NC1-3 Actinomyces odontolyticus

77% Actinobacteria

Actinomyces odontolyticus

83% Actinobacteria

NC1-2 Corynebacterium glutamicum

98% Actinobacteria

Corynebacterium freiburgense

80% Actinobacteria

NC4-1 Rhodococcus equi 98% Actinobacteria

Nocardia elegans 87% Actinobacteria

31TG Propionibacterium freudenreichii

79% Actinobacteria

Propionibacterium freudenreichii

99% Actinobacteria


47

3.4 Discussion

Six indigenous cultures belonging to the Order Actinomycetales were isolated from soil samples

of sugar mill treatment ponds in Proserpine and Maryborough sugar mills. The strains were

tagged as NC1-2, NC1-3, PC1-2, PC4-1, NC4-1, 31TG-3 and showed typical Actinomycete

phenotypic (physical and biochemical) characteristics such as a typical rhizoid colony edge,

Gram-positivity, and catalase-positivity.

The analysis of the complete or partial (500 bp of the 5′ end) 16S rRNA gene is the most

extensively used molecular method for species recognition and has a broad database for

comparison (Daley et al., 2008). Under routine conditions, the method is useful and convenient.

The 16S rDNA analysis identified the six indigenous isolates as belonging to four different species

of microorganism. The 16S rDNA sequencing confirmed that primers A and B matched regarding

the identity of two of the isolates: PC4-1 and NC3-1 were both identified as Actinomycetes

odontolyticus; and 31TG was identified as Propionibacterium freudenreichii. Two isolates were

identified as Corynebacterium genus, with the species being either C. freiburgense or C.

glutamicum (PC1-2 and NC1-2). Obviously these species are taxonomically close. The final

isolate, NC4-1 was identified as either Rhodococcus equi or as Nocardia elegans.

Previous research surveys indicate that Actinomyces, Corynebacterium, Nocardia, and the

Rhodococcus complex form distinct taxa of equivalent rank (Embley and Stackebrandt, 1994; Liu

et al., 1996). Propionibacterium is separated from Nocardia according to the oxygen

requirement for growth. Propionibacterium is a facultative aerobe and Nocardia is strictly

aerobic. Nocardia is related to Corynebacterium and Rhodococcus in terms of fatty acid

sequences in the cell wall. Bergey’s Manual (Holt,2000) suggest that Rhodococcus, Nocardia and

Corynebacterum are members of the same family. According to the scientific classification, all of

the isolated bacteria belong to the same Order, the Actinomycetales (Embley and Stackebrandt,

1994; Liu et al., 1996).

Rhodococcus has had several taxonomic designations in recent years (Tsukamura, 1982;

Goodfellow et al., 1998), and the genus most frequently confused with Rhodococcus is Nocardia.

It is therefore evident that these genera are very similar, and according to the identity criteria, it

is not surprising that they have both been associated with the same isolate (refer to Table 3.6:

Result of 16S sequencing). Furthermore the phylogenetic relationships between Rhodococcus,

Mycobacterium, Nocardia and Streptomyces are very close, and data from Mordarski et al.,

(1980) represented the genera Rhodococcus, Mycobacterium, Nocardia and Streptomyces as


48

four recognizable clusters on the similarity map. Rhodococcus equi was poorly defined compared

to Nocardia elegans on BLAST analysis of 16S sequencing.

It is mentioned in Bergey’s Manual (Holt, 2000) that the genus Propionibacterium is also very

frequently confused with Corynebacterium.

Two isolates were identified as being either C. glutamicum or C. freiburgense. The main

difference between species is that C. glutamicum is a non-pathogenic bacterium. On the other

hand, C. freiburgense is pathogenic and is a very recently identified species (Funke et al., 2009).

The characteristics of C. freiburgense are not yet included in Bergey’s Manual. The distinctive

“wagon-wheel” colony appearance (beige–whitish, dryish, convoluted with irregular edges)

described for C. freiburgense (Funke et al., 2009) was not observed in our isolates, so it is

considered most likely that the isolates were C. glutamicum.

It was also mentioned in Holt (2000) that, the actinomycetes showed variable catalase reactions,

however, the Actinomyces spp. isolated in this research were all catalase positive. Previous

research has shown that Corynebacterium, Nocardia and Rhodococcus (Order Actinomycetales)

are mostly pathogenic (Barry and Beaman, 2006) but our isolates were not clinical, being found

instead in the common source of environmental soil. According to Bergey’s Manual (Holt, 2000)

and to Laurent et al., (1999) most of the species of Corynebacterium, Nocardia and Rhodococcus

are widely distributed but particularly abundant in soil which supports our identification of these

isolates as being in this group

Pentose-degrading microorganisms are relatively rare in natural environments and agricultural

soils (Gírio et al., 2010). In the current study, six indigenous members of the Order

Actinomycetales were isolated from hemicellulose-enriched soil from a total of 191 initial

isolates. The strains were given the opportunity to induce their ability to grow in the presence of

different pentose sugars (xylose, arabinose and ribose) as carbon sources. Therefore, the use of

these wild-type microorganisms from soils is an attractive approach for industrial isolates, since

they have already adapted to the pentose-rich habitat of sugar treatment ponds. Samples from

the sugar treatment pond are expected to be hemicellulose-enriched, as sugar cane has high

levels of lignocelluloses, and pentoses are the most abundant carbon source in hemicellulose

(Patel et al., 2004). The microbes found in those habitats were therefore expected to be adapted

to utilize pentose as a carbon source of nutrient. The microbes isolated from the soil of sugar

treatment ponds proved to be common soil bacteria.

Propionibacterium freudenreichii and Actinomyces odontolyticus are potential human pathogens

whereas Rhodococcus equi and Nocardia elegans are usually animal pathogens (Lemee et al.,

http://en.wikipedia.org/wiki/Actinobacteria


49

1994). There are several characteristics of Corynebacterium glutamicum that make it useful for

industrial biotechnology processes. It is not pathogenic, does not form spores, grows quickly, has

relatively few growth requirements, has no extracellular protease secretion and has a relatively

stable genome (Mateos et al., 2006; Burkovski, 2008). C. glutamicum produces several useful

compounds and enzymes. It was first discovered as a producer of glutamate. Now it is also used

to make amino acids, such as lysine, threonine, and isoleucine, as well as vitamins like

pantothenate (Kalinowski et al., 2003; Kirchner and Tauch, 2003).

Another potential use for C. glutamicum is in bioremediation, such as for the remidiation of

arsenic residues. C. glutamicum contains two operons in its genome, the ars1 and ars2 operons,

with further experimentation. Researchers hope to be able to eventually use this bacterium to

take up the arsenic in the environment (Mateos et al., 2006).

3.5 Conclusions

The bacteria isolated and identified in this research are natural isolates from soil samples rich in

hemicellulose, obtained from sugar mills in Queensland, Australia. They were not genetically

modified to promote the preferential use of pentoses. These E-PUB were able to utilize pentose

sugar as a carbon source during their growth on LB medium, following a period of

acclimatization to the supplied pentose carbon sources. It was found that each of the E-PUB

grew on different types of sugar provided as carbon sources. In the absence of a suitable added

carbon source, no growth was observed, so demonstrating that the growth was not due to the

presence of yeast extract or other media constituents.

The isolates were identified as various genera, all members of the Order Actinomycetales.

Members of this order are well known for their ability to produce bioactive metabolites and are

widely distributed in nature.

Further research will be reported in the following chapters, regarding the nature and extent of

the pentose-degradation process, and the resulting end-products.

Chapter 4 Catabolic Characteristics of E-PUB

50

CHAPTER 4

Catabolic Characteristics of Environmental Pentose-

Utilizing Bacteria (E-PUB)

4.0 Summary

In order to examine the metabolic characteristics of the microorganisms isolated from pentose-

enriched samples obtained from sugar cane mills, it was first necessary to test the capability of

those organisms to break down pentose sugars such as those found in hemicellulose. This

chapter describes catabolic characteristics of E-PUB by growing them in media of single pentose

sugar carbon sources, and subsequently in media containing glucose in addition to each pentose

sugar (dual sugar). A set of pentose sugars was selected as being representative of those found

in the natural environment under examination, i.e. the waste products of sugar cane milling. The

organisms tested, having been isolated according to their ability to use pentose sugars (reported

in Chapter 3), were all capable of growing on at least one of the pentoses provided. All were also

able to grow on mixtures of glucose with at least one pentose sugar, demonstrating a

characteristic diauxie growth pattern.

4.1 Introduction

As was discussed in Chapter 2, there are several difficulties with respect to the use of

hemicellulose as a raw material for the industrial production of commercial products. Principal

among these is the fact that the raw material contains a mixture of sugars, including both

hexose sugars, mainly glucose, and pentose sugars, such as xylose, arabinose, and ribose. Most

of the microorganisms capable of fermenting glucose to give high yields of appropriate end-

products, are incapable of also fermenting the pentose sugars, or do so at such low yields that

the proposition is not cost effective (Agbogbo et al., 2006). There has been some discussion

(Pitkänen et al., 2005; Agbogbo et al., 2006; Hahn-Hägerdal et al., 2007) regarding the best

means by which to utilize most efficiently a large component of the sugars present in the

agricultural waste material. One approach to resolving this problem has been to genetically

engineer such organisms, to introduce the additional capacity for pentose-utilization (Pitkänen

et al., 2005; Hahn-Hägerdal et al., 2007).


51

Another possibility has been the suggested use of a mixed starter culture, such that one

organism will use glucose and a second organism would breakdown the pentose substrates.

Finally, the method employed here is to isolate natural, indigenous microorganisms from a

pentose-rich environment, which may reasonably be expected to be pentose-capable, as well as

having the ability to breakdown the more common substrate, glucose. Such isolates were

discovered, as described in Chapter 3, by screening process using pentose substrates.

These isolates were grown in the test pentose sugars separately, and also with glucose, and their

specific growth rates during the exponential phases were compared. Further, their ability to use

glucose and pentose sugars as dual carbon sources was examined. The results of this research

are presented in this chapter. The aim of this research was to study the growth patterns of

microorganisms that could effectively use pentose sugars, both alone, and as a mixture with

glucose.

There were a number of ways by which the utilization of dual sugar substrates might be

accomplished. It is possible that, as the organisms were initially isolated by growth on a pentose

sugar carbon source, they could therefore be pre-induced to pentose-utilization, and were also

constitutively capable of breaking down glucose, as indeed are most microorganisms. In this

scenario, the microorganisms could be expected to use both glucose and pentose sugars

simultaneously, resulting in a rather long exponential growth phase, and a growth rate similar to

that of glucose growth conditions.

More likely, however, is the expectation that the organisms will use a diauxie growth pattern

(Brückner and Titgemeye, 2002), whereby they use glucose first, and, after a second lag phase,

launch into a second exponential growth phase, based on the pentose sugar. This growth

pattern is due to the catabolite repression initiated by the metabolism of glucose, which

prevents simultaneous utilisation of any other substrate. The presence of a diauxie growth

pattern is easily observed by measuring the growth curve of the microorganisms while they

grow in a mixed sugar environment.

In order to calculate the appropriate ratio of sugars for this research, natural bagasse was used

as a source. The partial composition of natural sugarcane bagasse is xylose 25.2 and glucose

41.0, expressed as % w/w of the dry matter (Pandey et al., 2000).


52


Bacterial culture Corynebacterium cystitidis (ATCC 29593), and isolates Propionibacterium

freudenreichii; (31TG) Corynebacterium glutamicum (PC1-2, NC1-2); Actinomyces odontolyticus

(PC4-1, NC1-3) and Nocardia elegans (NC4-1), were used in this study. Duplicate E-PUB cultures

were performed for the analysis of catabolic characteristics. The ATCC culture was used as a

positive control as it was expected that the bacterial isolates would have similar metabolic

characteristics to that culture. The bacteria were recovered from storage in -20°C glycerol stock

by growing them overnight at 30°C in 100 mL of minimal medium (Luria Bertani broth)

containing 0.016 M pentose sugars (xylose or arabinose or ribose).

The overnight cultures were diluted in fresh medium to an approximate concentration of

107cfu/mL, and subsequently incubated at 30°C for approximately 3 days. The resulting biomass

was collected by filtration onto a membrane filter (pore size = 0.2 µm), and then washed with

warmed (to avoid cold-shock on the organism) minimal medium without any carbon sources

(Wittmann et al., 2004). The isolates were then cultured in Luria Bertani (LB) broth

supplemented with 1.0% (w/v) xylose, arabinose or ribose from 20% sterile stock solutions, at

30⁰C in a shaking incubator (Ratek, Orbital Mixer Incubator) at 100 rpm.

Growth was determined by measuring the optical density at 680 nm, using a spectrophotometer

(Beckman Coulter Spectrophotometer) with measurements being taken at 12 hourly intervals

against a medium blank. Optical density was plotted against time in hours from the inoculation

time. The OD was measured at 680 nm, rather than 540 nm as is generally used for bacteria,

because the actinomycetes cells form a mass of cell-chains (Janssen et al., 2001) making the

longer wavelength more effective for measuring optical density. The optical density (OD680) was

measured after 24 hrs incubation and then at 12 hourly intervals until the stationary phase was

reached. The OD value was converted to logarithmic value. Two OD values at the beginning and

end of the exponential phase were selected for OD1 and OD2 and the corresponding times t2 and

t1 values, and used in following equation to calculate μ the specific growth rate, µ, of each

exponential phase:

Next, the specific growth rates for growth on glucose and pentose substrates were compared

using the student T test and SPSS software. The “Independent samples” t-test was used to

decide whether two means were significantly different from each other when the two samples

were taken from different values. The significant p value was considered to be below 0.05.

12

12 lnln

tt

ODOD


53

Following the single carbon source experiments, the same set of organisms was tested in the

same way, but with two sugars being present, these being glucose plus one of the pentose

sugars. The pentose sugar, xylose, is commonly found in agricultural residues and other

lignocellulosic biomasses, but is not the only sugar present. In order to evaluate whether xylose

(or other pentose sugar) catabolism by the indigenous isolates background was repressed in the

presence of glucose, a culture broth of each of the bacterial cultures (the six isolates plus the

positive ATCC control) was prepared in a mineral medium containing xylose, arabinose or ribose.

A sample from each of the cultures was subcultured into media containing each of the following

dual-sugar carbon sources: glucose-xylose; or glucose-arabinose; or glucose-ribose.

Initially, various concentrations of both glucose and the pentose sugars were tested using the

ATCC culture, to establish the optimum balance, which was found to be 50 µL each of glucose

(0.025g or 2.5%) and xylose/arabinose/ ribose (0.0125g or 1.25%) per 100 mL broth medium.

Stock solutions of carbon sources were made as: glucose 0.5 g/mL and pentoses 0.25 g per mL.

This resulted in an almost identical ratio (2:1) of hexose: pentose as that found in naturally in

hemicellulose material (1.6:1).

The broths were incubated at 30°C in a shaking incubator (Ratek: Orbital mixture Incubator) at

100 rpm and the optical density was measured at 12 hourly intervals as per the previous

experiment (above).

Triplicate glucose measurement was performed using Megazyme-Glucose assay kit. Glucose

Reagent Buffer was (25.0 mL) diluted in to 500mL distilled water. All contents of one vial Glucose

Determination Reagent were dissolved in this buffer. The absorbance of blank, standard and

sample was measured at 510 nm after mixed and incubates at 40 or 50°C for 20 min. Glucose

content was calculated by using following formula:

Calculation:

4.3 Results

4.3.1 Comparison of growth using different single carbon sources

This research consisted of a series of growth experiments to investigate the target

microorganism’s catabolic characteristics. The ability of the test organisms to grow using various

carbon sources was measured by observation of the final optical density, indicating increasing

biomass and the efficiency of this utilisation was noted by calculation and comparison of the

specific growth rates during the exponential phases of growth in each case.


54

A possible confounding factor was that the medium contained yeast extract, which could

potentially have acted as a carbon source in its own right, so negating the results of the “single

carbon source” experiments. However, the results show that, while the E-PUB grew on media

that contained different types of sugar as carbon source, some of the sugars consistently did not

support growth. From this evidence, it has can be taken that yeast extract is not sufficient to

support microbial growth as a carbon source for the tested organisms, since, if this were the

case, all of the test systems would have shown a level of background growth due to this source.

Various degrees of E-PUB growth in different pentose sugars revealed that they used the

different pentose sugars as an essential carbon source for growth.

Figure 4.1 illustrates graphically the results of the carbon source utilisation experiments,

depicting for each organism (ATCC strain and the six test isolates), the extent to which it was

able to grow on each carbon source over a period of 4 days, which was in all cases sufficient time

to reach the stationary phase.

In all cases, when the pentose sugars were able to be used, similar final optical density readings

were obtained, indicating that the pentoses were suitable as carbon sources in terms of growth

levels. In general, pentose sugars required longer lag periods than that of glucose, implying the

involvement of an inducible enzyme system, rather that the constitutive one available for

glucose metabolism. However, this was not the case for Actinomyces odontolyticus and

Corynebacterium glutamicum, so a different system may be in place for these genera.

The results clearly demonstrated that all six target isolates could utilize pentose sugars or

glucose to varying, but quite similar, extents. It was considered useful to determine the

efficiency of the metabolism (capacity to utilize carbon sources), by comparing the specific

growth rates of each species. These were calculated based on the OD measurements, and are

shown in Table 4.1. While it may be argued that specific growth rates based on OD are not

necessarily the most accurate, in the case of these organisms, with their “tangled mat” growth

habit, the OD is considered to be equally as accurate as most other commonly used measures of

bacterial growth. C. glutamicum (PC1-2) and C. glutamicum (NC1-2) had different growth rates

in terms of xylose (0.016 and 0.006) and glucose (0.022 and 0.007) utilization even though they

are the same species albeit from different sources. It may be that they are different strains of

the same species. N. elegans (NC4-1) was the only one among E-PUB was able to utilize ribose

(µ=0.009).


55

a b

c d

e f

g

X= xylose, A= arabinose, R= ribose and G= glucose, LB=

Luria Bertani (Appendix Table B1, B3, B5, B7, B9, B11,

B13).

Figure 4.1 (a-g): Comparison of growth curves for various carbon sources. Cultures included an

ATCC culture and isolates from sugar treatment ponds; optical density at 680nm was measured

against time.

0

0.5

1

1.5

2

2.5

24 36 48 60 72 84 96

OD

680

TIME

Corynebacteria cystitidis

LBX

LBG

0

0.5

1

1.5

2

2.5

24 36 48 60 72 84 96

OD

680

TIME

31TG (P. freudenreichii)

LBA

LBG

0

0.5

1

1.5

2

2.5

72 96 120 144 168

OD

680

TIME

PC4-1 (A. odontolyticus)

LBXLBALBG

0

0.5

1

1.5

2

2.5

3

0 12 24 36 48 60 72 84 96

OD

680

TIME

PC1-2 (C.glutamicum)

LBX

LBG

0

0.5

1

1.5

2

2.5

36 48 60 72 84 96

OD

680

TIME

NC1-3 (A.odontolyticus)

LBX

LBA

LBG

0

0.5

1

1.5

2

2.5

72 96 120 144 168

OD

680

TIME

NC1-2 (C.glutamicum)

LBX

LBG

0

0.5

1

1.5

2

2.5

72 96 120 144 168

OD

680

TIME

NC4-1 (N. elegans)

LBX

LBA

LBR

LBG


56

Table 4.1: Specific growth rates of E-PUB cultures. Cultures included control ATCC culture and

known isolates, using single carbon source - pentose sugars or glucose - as carbon sources.

These results showed that the six indigenous isolates, PC4-1 and NC1-3 (A. odontolyticus), PC1-2

and NC1-2 (C. glutamicum), NC4-1 (N. elegans) and 31TG (P. freudenreichii), could utilize

pentose and glucose with approximately the same efficiency as indicated by the very small

difference in specific growth rates. Such differences may, in fact, be a result of the slight

inaccuracy of using OD to calculate the growth rates.

The specific growth rates of all organisms using pentose sugars (mainly xylose) and glucose were

compared by using paired t- test in Statistical Package for the Social Sciences (SPSS) software.

Statistically significant difference would be indicated by a p value of <0.05. A statistically

significant difference was found (Table 4.2) between xylose and glucose utilization by all of the

environmental isolates and the ATCC control, even though the actual growth rates appeared to

vary, as the p value of the comparisons between specific growth rates was less than 0.05.

Specific growth rate (h−1)

Pentoses Hexoses

Bacteria Xylose Arabinose Ribose Glucose

Corynebacteria cystitidis 0.018 - - 0.016

A. odontolyticus (PC4-1) 0.012 0.007 - 0.009

C. glutamicum (PC1-2) 0.016 - - 0.022

C. glutamicum (NC1-2) 0.006 - - 0.007

A. odontolyticus (NC1-3) 0.022 0.013 0.009

N. elegans (NC4-1) 0.022 0.009 0.009 0.021

P. freudenreichii (31TG) - 0.005 - 0.011


57

Table 4.2: Statistical analysis of p values of specific growth rates. Comparison of µ using a

pentose sugar compared to that of glucose

* Arabinose specific growth rate included, as this isolate does not use xylose

4.3.2 Bacterial growth using combination of pentose and hexose (dual carbon sources) sugars

The same set of cultures as those that had been tested in the previous section, was again tested

using similar preparation methods, but this time using a glucose plus pentose dual carbon source

combination.

During the initial cultivation on single pentose sugar substrates, it was seen that the bacterial

isolates were able to utilize the pentose sugars, and were therefore using pentose metabolic

pathways. This may have led us to expect pentose metabolism to begin without a lag phase.

However, cultivation on the dual sugars (Figure 4.2 a, b, c) showed that all isolates preferred to

utilize glucose first and then they entered a stationary/lag phase following glucose depletion,

before the pentose-stimulated growth phase.

Bacteria p value (µ for

xylose vs glucose)

Corynebacteria cystitidis 0.047

A. odontolyticus (PC4-1) 0.040

C. glutamicum (PC1-2) 0.041

C. glutamicum (NC1-2) 0.048

A. odontolyticus (NC1-3) 0.03

N. elegans (NC4-1) 0.047

P. freudenreichii (31TG)* 0.03


58

a

b

c

Figure 4.2: Results of the growth measurements (OD680) for the various cultures.

Graphs depict one sugar combination per graph (a, b and c), and show growth patterns of the six

cultures tested, which were capable of utilizing the dual-sugar carbon source, on each graph

(Appendix Tables B15, B16, B17).

0

0.5

1

1.5

2

2.5

3

0 12 24 36 48 60 72 84 96 108

OD

time

glu+xyl

PC1-2PC4-1NC1-2NC1-3NC4-1

0

0.5

1

1.5

2

2.5

3

24 36 48 60 72 84 96

OD

time

glu+ara

PC4-1

NC4-1

NC1-3

31TG-3

0

0.5

1

1.5

2

2.5

0 12 24 36 48 60 72 84 96 108

OD

time

glu + rib

NC4-1


59

This second lag phase, observed before the pentose sugar exponential phase, was present

despite pre-enrichment of the bacteria with the pentose sugar, indicating that catabolite

repression was indeed taking place, inhibiting the utilization of the pentose until the hexose was

exhausted which was proven by residual glucose measurement (Table 4.5).

C. glutamicum (PC1-2, NC1-2); A. odontolyticus (PC4-1, NC1-3) and N. elegans (NC4-1) isolates

showed diauxie characteristics with glucose/xylose culture media (Figure 4.2 a). However, only

N. elegans (NC4-1) was able to utilize ribose. On the other hand, A. odontolyticus (PC4-1, NC1-

3)and N. elegans (NC4-1) and P. freudenreichii (31TG) indigenous isolates were able to utilize

arabinose after glucose and demonstrated diauxie growth characteristics.

The diauxie experiments demonstrated that all of the organisms could use a hexose and pentose

sugar sequentially. However, only one isolate, N. elegans (NC4-1) metabolised the glucose and

ribose combination, resulting in the same diauxie effect as the other isolates and sugar

combinations. As in the previous single sugar experiments, the specific growth rate for each

exponential phase of growth was calculated, to determine the efficiency of sugar utilization.

Table 4.3: Analysis of diauxie specific growth rates

Specific growth rates (h−1)

Dual sugar carbon source Glucose/Xylose Glucose/Arabinose Glucose/Ribose

Bacteria Glu Xyl Glu Ara Glu Rib

C. glutamicum (PC1-2) 0.050 0.010 - -

C. glutamicum (NC1-2) 0.013 0.008 - -

A. odontolyticus (PC4-1) 0.031 0.006 0.051 0.005

A. odontolyticus (NC1-3) 0.008 0.007 0.051 0.007

N. elegans (NC4-1) 0.032 0.008 0.055 0.004 0.04 0.006

P. freudenreichii (31TG) 0.052 0.004


60

The specific growth rate results from Table 4.3 indicate, as would reasonably be expected, that

the µ value for the glucose component of the growth curves remained reasonably consistant,

demonstrating that the presence of the pentose sugar did not dramatically affect the rate of

glucose utilization. In all cases, a lag period was observed between the glucose and pentose

growth curves, defining the diauxie phenomenon. In the case of xylose and ribose, the lag period

was generally approximately 24 hours; however the arabinose growth periods began only 12

hours after completion of the glucose curves. It is not known whether this lag period is

important, but for practical reasons, it may be useful for industrial purposes to be aware of such

a pause in the metabolic processes.

Table 4.4: P values of significant difference between specific growth rates of dual-sugar

combinations of glucose and pentose sugars

The p values of specific growth rate for glucose and pentoses utilization are presented in Table

4.4. All p values showed no significant difference between specific growth rates for hexose and

pentose-utilization as the p values are below 0.05. The sole exception is N. elegans (NC4-1)

which had p value 0.13 means indicating a significant difference between the rates of growth

using glucose as opposed to arabinose as a carbon source combination.

Residual glucose measurement provided information about the extent of glucose depletion at

the time of second lag phase.

Sugar

combination

C.

glutamicum

( PC1-2)

C.

glutamicum

( NC1-2)

A.

odontolyticus

( PC4-1 )

A.

odontolyticus

( NC1-3)

N.

elegans

( NC4-1)

P.

freudenreichii

(31TG)

glucose and

xylose

combination

0.004

0.011

0.01

0.001

0.001

glucose and

arabinose

combination

0.01 0.03 0.12 0.04

glucose and

ribose

combination

0.035


61

Table 4.5: Amount of glucose at the second lag phase of the growth medium

* The starting concentration of glucose was 2.5% (w/v)

All of the E-PUB organisms utilized glucose during the first log phase in slightly varying amounts

as shown in Table 4.5. Corynebacterium glutamicum used the most glucose, prior to using

xylose, while Nocardia elegans used the least glucose of all tested, when in combination with

ribose, although the shorter incubation time may have influenced this figure.

Table 4.6: Ratio of specific growth rate (µ) for xylose utilization as a single sugar compared to

that of the same sugar as part of a dual carbon source system.

Culture µ for Single sugar (µs) µ for Dual sugar (µd) Ratio µs: µd

C. glutamicum (PC1-2) 0.018 0.010 1.9

C. glutamicum (NC1-2) 0.022 0.008 2.75

A. odontolyticus (PC4-1) 0.010 0.006 1.61

A. odontolyticus (NC1-3) 0.009 0.007 1.14

N. elegans (NC4-1) 0.006 0.008 0.07

P. freudenreichii (31TG) 0.009 (arabinose) 0.015 0.60

Bacteria Residual amount of glucose* (g/100mL) Time

(h)

Glucose/Xylose Glucose/Arabinose Glucose/Ribose

C. glutamicum (PC1-2) 0.0040 or 0.4% 60

C. glutamicum (NC1-2) 0.0037 or 0.3% 60

A. odontolyticus (PC4-1) 0.0013 or 0.1% 0.0009 or 0.09% 60

A. odontolyticus (NC1-3) 0.0018 or 0.1% 0.0005 or 0.05% 60

N. elegans (NC4-1) 0.0002 or 0.2% 0.0041 or 0.4% 0.0001 or

0.01%

48

P. freudenreichii (31TG) 0.0006 or 0.06% 60


62

It is apparent from Table 4.6 that xylose was used more efficiently as a single carbon source than

as part of a dual carbon source system by C. glutamicum and A. odontolyticus, while both N.

elegans and P. freudenreichii were somewhat more efficient in breaking down xylose following

glucose metabolism than as a sole carbon source, although the difference was not statistically

significant. The latter two isolates are therefore better choices for industrial purposes than the

former pair, providing other qualities of the cultures are similar.

4.4 Discussion

The aim of the work presented in this chapter was to prove that microorganisms isolated from a

hemicelluloseenriched environment were able to utilize pentose sugars. In particular, the ability

to use pentose sugar carbon sources in the presence of glucose was considered to be a useful

property, due to the natural combination of these molecules in agricultural waste products,

which may serve as a fermentation feed-stock.

An additional focus of this chapter was to study and explore the metabolic activities of E-PUB.

This not only informs the interpretation of the results of the experiments reported in this

chapter, but also gives some additional information about the end-products of the different

metabolic processes that may be taking place, so informing future research.

Microbial metabolism consists of a network of biochemical processes to maintain life.

Metabolism consists of two major phases: catabolism and anabolism. Usually bacteria

breakdown sugars as a main carbon source or nutrient in the catabolism phase. Microorganisms,

usually heterotrophic bacteria, produce a range of by-products as a result of the anabolic phase.

The most common carbon source for bacteria is glucose, which is broken down via the major

carbohydrate-metabolizing pathways: Embden–Meyerhof–Parnas (EMP) pathway (glycolysis),

pentose phosphate (PP) pathway and the tricarboxylic acid cycle (TCA cycle).

Figure 4.3 shows the glycolytic pathway and its metabolic interconnection with the pentose

phosphate pathway and tricarboxylic acid cycle.


63

Figure 4.3: Metabolic pathways for the breakdown of pentose and glucose sugars (Ref: The new world encyclopedia (http://www.newworldencyclopedia.org/entry/Citric_acid_cycle) and Pelicano et al., 2006, page 4634, figure 1).

Legend: The solid arrows indicate glycolytic reactions and the dashed arrows show the pentose

phosphate pathway. The enzymes abbreviations are HK, hexokinase; PGI, phosphoglucose

isomerase; PFK, phosphofructokinase; TPI, triosephosphate isomerase; GAPDH, glyceraldehyde-

3-phosphate dehydrogenase; PGK, phosphoglycerate kinase; PGM, phosphoglycerate mutase;

PK, pyruvate kinase; PDH: pyruvate dehydrogenase; LDH: lactate dehydrogenase. The colour

schemes in the TCA cycle are as follows: enzymes, coenzymes, substrate names, metal ions,

inorganic molecules, inhibition, and stimulation. The enzymes required to breakdown xylose in

addition to glucose are glucose-6-phosphate dehydogenase, xylose reductase, xylitol

dehydrogenase.


64

Figure 4.4 shows a simplified scheme of the extra- and intracellular pathways involved in xylose

catabolism include enzymes from the glycolytic pathway.

Figure 4.4: Metabolic pathways for the breakdown of sugars (Xylose included)

Ref: Lu et al., 2010, page 3, figure 2.

Legend: An02g07470 (fructose-bis-phosphate aldolase); An14g04920 (triose phosphate

isomerase); An16g01830 (glyceraldehde-3-phosphate dehydrogenase); An08g02260

(phosphoglycerate kinase); An18g06250 (enolase); An07g09530 (pyruvate dehydrogenase

complex: pyruvate dehydrogenase); An07g06840 (dihydrolipoamide dehydrogenase); TCA cycle

enzymes: An08g10530 (aconitase); α-ketoglutarate dehydrogenas complex: An07g06840

(dihydrolipoamide dehydrogenase); An12g07850 (fumarase); An07g02160 (malate

dehydrogenase); enzymes from the pentose phosphate pathway: An02g02930 (ribose-5-

phosphate isomerase); An07g03850 (transaldolase); enzymes involved in anaerobic redox

balancing: An06g00990 (cytoplasmic fumarate reductase); enzymes involved in polyol

metabolism: An01g03480 (sorbitol dehydrogenase); acetate formation: An16g07110 (acetyl-CoA

hydrolase); xylose breakdown: An01g03740 (xylose reductase)

Xylose reductase, which is a pentose reductase and member of the aldoketoreductase family 2

(AKR2), catalyses the first step in five carbon metabolism by reducing xylose and arabinose to

xylitol and arabitol. The gene encoding xylose reductase (Texr) has been isolated from Candida

sp, Pichia stipitis and the thermophilic fungus Talaromyces emersonii.


65

Xylose catabolism involves a series of oxidation and reduction reactions to form D-xylulose,

which then enters the pentose phosphate pathway after phosphorylation to D-xylulose-5-

phosphate. The combined action of xylose reductase and xylitol dehydrogenase is required to

convert D-xylose to D-xylulose and all enzymes of the D-xylose pathway can be used in the L-

arabinose pathway, where arabitol is oxidized by NAD+-dependent arabitol dehydrogenase

producing L-xylulose. This is then converted to xylitol by NADPH-dependent L-xylulose reductase

(Jez and Penning, 2001).

Hahn-Hagerdal et al. (2001) improved the metabolic pathways essential to fermentative

capabilities of recombinant Saccharomyces strains, engineered for xylose metabolism. Several

xylose reductase genes have been identified from different sources (Amore et al., 1991; Billard

et al., 1995; Handumrongkul et al., 1998), and all show a common specificity for NADPH. Site-

directed mutagenesis and structural studies with Candida tenuis xylose reductase (Kratzer et al.

2006), a dual-specific enzyme with a preference for NADPH, revealed the main determinants

involved in pentose-specific substrate-binding recognition, key residues involved in coenzyme

interaction and suggested mechanisms by which certain AKRs can utilize both co-enzymes

(Petschacher et al.,2005; Di Luccio et al., 2006). Xylose reductase from Pichia stipitis, also

targeting amino acids involved in coenzyme interaction resulted in mutant proteins with

reversed coenzyme preference from NADPH to NADH in previous study (Watanabe et al., 2007).

Environmental pentose utilizing bacteria (E-PUB) bacteria were able to breakdown the sugars

tested, including a number of pentose sugars. Pentose sugars are broken down using the

pentose phosphate pathway and glucose is catabolised through the EMP pathway (Figure 4.3

and Figure 4.4). The metabolic pathway diagram illustrates the pathway that the E-PUB were

able to use, in order to utilize pentose naturally, due to presence of xylose reductase and xylitol

dehydrogenase enzymes, whereas previous research has described the need for genetically

engineering to activate of the gene encoding those enzymes. In the previous research, S.

cerevisiae XKS1 was used to initiate the evolution in continuous culture under aerobic conditions

with xylose and arabinose as limiting carbon sources (Karhumaa et al., 2006). Ethanol

productivity benefited from the design of stable S. cerevisiae strains that would co-consume

xylose and arabinose, since both sugars are present in lignocellulosic feedstock. So far there is

only one example of chromosomal integration of xylose and arabinose pathway genes in S.

cerevisiae (Jeppsson et al., 2003). In these engineered industrial strains (TMB3061 and

TMB3063) that carry the Pichia stipitis xylose pathway combined with the B. subtilis - E. coli

arabinose pathway the consumption of arabinose and xylose was low and ethanolic


66

fermentation was limited by extensive arabitol formation from XR enzyme (Karhumaa et al.,

2006). The E-PUBs are aerobic bacteria; however it was necessary to create an anoxic

environment in order to encourage them to produce amino acids.

E-PUB organisms were able to use pentose sugars as a carbon source during cultivation, without

any genetic modification. It has been previously reported that C. glutamicum had been

metabolically engineered to utilize the pentose sugar, xylose (Kawaguchi et al., 2006). The E-PUB

isolates were able to naturally breakdown xylose, arabinose and/or ribose as a sole carbon

sources.

The only isolate capable of utilizing all of the pentose sugars tested was Nocardia elegans (NC4-

1), which was isolated from the sugar treatment pond water of the Proserpine sugar mill, while

the other microorganisms used glucose and at least one pentose sugar. The utilization of both

hexoses and pentose sugars from lignocellulosic materials is promising for future sustainable

recycling, despite there being no previous publications regarding pentose usage from sugar

industry waste. Utilization of hexoses by bacteria and yeast is well known in fermentation

technology but the information of the ability of these organisms to utilized pentose sugars is

scant. The ability to ferment pentoses is not widespread among microorganisms and the most

promising yeast species identified so far are Candida shehatae, Pichia stipitis and Pachysolen

tannophilus (Hahn- Hagerdal et al., 2007; Chandel et al., 2010c). In order to improve the

suitability of these strains at an industrial level, many efforts have been made to construct

appropriate strains by cloning and expression of pentose metabolism genes into common hosts

such as Saccharomyces cerevisiae, Zymomonas mobilis, Escherichia coli etc (Jeffries, 2007; Hahn-

Hagerdal et al., 2007). However it is still remains a challenging issue to get suitable strains that

will fulfil the requirements of industrial production from lignocelluloses (Zhang et al., 2010).

Xylose was the most commonly used pentose sugar of those tested, while ribose supported the

growth of only one isolate. Arabinose, whilst being used by several isolates, did not permit

growth to the same extent, as measured by the final optical density, as other carbon sources in

most cases. The exception to this observation was Actinomyces odontolyticus (NC1-3), whose

growth with arabinose was virtually the same as with the other carbon sources tested.

The analysis of utilization of dual carbon sources was the second objective of this chapter. The

reason that biological treatments of industrial waste are so difficult is that the waste usually

contains many kinds of carbon sources. The efficient utilization of mixtures of various sugars is

critical for attaining complete conversion of lignocellulosic wastes. The physiological capability

for carbon catabolite repression mechanisms, present in many bacteria, is generally regarded to


67

be a mechanism that has evolved to ensure sequential carbohydrate utilization (Nampoothiri

and Pandey, 1995; Brückner and Titgemeye, 2002), with the most energy-efficient carbohydrate

being utilized first. While E. coli is able to ferment xylose, the utilization of this sugar by this

microbe during lignocellulosic hydrolysate fermentation is delayed and is often incomplete

(Naono et al., 1965; Dien et al., 2000). Likewise, genetically engineered Zymomonas mobilis has

been shown to preferentially utilize glucose during co-fermentation of sugar mixtures

(Mohagheghi et al., 2002).

Our research agrees with the findings of Singh and Mishra (1995). Since our E-PUB isolates were

able to utilize a combination carbon source consisting of glucose and a pentose sugar, the sugars

were used sequentially, with glucose used first followed by a lag period, and subsequently a

second exponential phase, thus demonstrating a typical catabolite repression. The bacteria used

in these experiments were not genetically modified to promote the preferential use of pentoses,

but are natural isolates. While that did not measure the levels of the remaining concentrations

of sugar substrates, both first and second growth curves were followed to a subsequent

stationary phase, which would normally suggest that the carbon source was depleted. It has is

predicted that all the sugars may be depleted after the two growth phases; however this study

only measured the glucose levels, which were very low, indicating that this sugar, at least, was

markedly depleted.

There is currently limited information in the literature about bacterial pentose-utilization. The

work presented in this chapter has proven that the isolated indigenous microorganisms were

able to metabolise pentose sugars. It was established that these organisms used pentose sugars

with approximately the same efficiency as glucose utilization when tested as single carbon

source.

However, as a part of a dual carbon source system, the pentose sugars in some cases appeared

to be less efficient as a source of carbon than they were in a single carbon source test. This may

be partially due to a technical anomaly, attributed to the difficulty in accurately measuring the

optical density of slow growing organisms. However, the fact that two of the species were able

to use xylose more effectively as a dual-carbon source than as a single one, confirms our

confidence in these species as novel biofermentation starter cultures.

As previously discussed, pentose-utilization is an important, but rare, trait for the economically

feasible production of chemicals from lignocellulosic biomass by microbial cells. This limitation

was resolved in this study by investigation of indigenous organisms, which proved to be naturally

capable of efficiently and concurrently metabolizing both glucose and xylose.


68

The question may be raised as to the identity of the limiting factor, which causes the diauxie

effect to occur. This factor may be: carbon source; nitrogen source or phosphorous, or indeed

growth conditions such as oxygen supply or pH. This have shown that the glucose levels drop to

a very low figure (Table 4.5) and so predict that carbon source is indeed the limiting factor. Were

the nitrogen or phosphorus to be limiting factors, a second growth phase would not be

observed, since there were no alternative supplies of these elements to fuel such a phase. The

only nutrient supplied in two forms, was the carbon source, and so this is the most likely factor

to be responsible for the diauxie effect.

4.5 Conclusions

Environmental pentose-utilizing bacteria (E-PUB) were able to metabolise pentose sugars when

they were presented as a single carbon sole in minimal growth media, under standard aerobic

conditions. In addition the E-PUB used a diauxie growth pattern, typically observed as a result of

catabolite repression, when presented with a dual sugar carbon source consisting of glucose and

a pentose sugar. In most cases they continued on to utilize the pentose sugar present, after the

glucose supply had been exhausted. As Nocardia elegans also has the ability to use any of the

pentose sugars tested, it is a very promising candidate for industrial fermentations.

Chapter 5 Anabolic Characteristics of E-PUB

69

CHAPTER 5

Anabolic Characteristics of Environmental Pentose-

Utilizing Bacteria

5.0 Summary

In order to determine the ability of environmental pentose-utilizing bacteria (E-PUB) to produce

commercially valuable products such as amino acids from a process of fermentation of pentose

sugars, E-PUB isolates were grown in various pentose substrates, and the presence of amino

acids was analysed using an HPLC system. The products varied, with one or two amino acids

being recovered in all cases.

When the E-PUB isolates were tested in a diauxie system, with dual sugar substrates consisting

of glucose (hexose) plus one of the pentose sugars, the end-product results showed a single

predominant amino acid, identified as glycine by comparison with the standards. This amino acid

is widely used for medical and industrial purposes, and is considered to be a very useful by-

product of the fermentation process, using E-PUB with dual sugars (glucose plus pentose) as

substrates.

5.1 Introduction

Microorganisms closely related to the Corynebacterium genus are frequently used for

fermentation purposes because they are able to utilize various sugars as substrates and in

addition, Corynebacterium strains can produce valuable amino acids as end-products. There

have been several studies performed regarding amino acid production from pentoses, using

genetically modified Corynebacterium strains (Ikeda and Katsumata, 1999; Moritz et al., 2000;

Ohnishi et al., 2005).

Biotechnological production processes have been used for the industrial production of amino

acids for the last 50 years. Market development has been particularly dynamic for the flavour-

enhancer, glutamate and the animal feed amino acids, L-lysine and L-threonine, which are

produced by Corynebacterium spp from hexose sugar sources such as sucrose or glucose. The

market for synthetic amino acids is becoming increasingly important, with annual growth rates

of 5-7% (Leuchtenberger et al., 2005). Amino acids are useful as building blocks for active

ingredients in the production of pharmaceuticals, cosmetics and agricultural products. Nutrition

and health will continue to be the driving forces for exploiting the potential of microorganisms,


70

and possibly also of suitable plants, in order to arrive at even more efficient processes for amino

acid production.

Wise selection of raw materials is essential for economic amino acid production, especially since

the carbon source represents a major component of variable production costs. This explains the

association between amino acid and sugar manufacturing which has developed over time. Some

amino acid production plants are located geographically close to sugar mills in order to decrease

transport costs and on occasion, joint ventures are formed. Depending on the geographical

location of the plants, carbon sources such as cane molasses, beet molasses, or starch

hydrolysates from corn, potato or cassava are used. While molasses is common in Europe, South

America and China, starch hydrolysate is the most important carbon source in North America.

Tapioca hydrolysate, the starch hydrolysate from cassava is widespread in South-East Asia.

However, pure sugars are favourably compared with molasses because of the unwanted side

reactions and variable qualities of the complex media components.

Earlier studies (John et al., 2007) concluded that sugar derivatives from the cellulose and

hemicellulose components of plant biomass are an attractive option as sustainable substrates

for the biological production of many organic acids, fuel and other industrial chemicals. With

respect to the pentose-fraction of hemicellulose biomass, there are several microorganisms

available that have been genetically engineered to break down pentose sugars to produce

ethanol and other organic chemicals. However, this approach is limited by the cost of

production, the physiological characteristics of the microorganisms and the lack of public

support for the use of genetically engineered microbes in large scale chemical production

(Ronald and Admachak, 2008).

This negative public attitude could be addressed by using natural isolates, screened for their

capacity to break down pentose sugars. The alternative process, of selecting mutants that

switch off the glucose metabolism so that alternative, available substrates such as pentose

sugars would be used instead, retains some difficulty in terms of public negativity, as the

mutation aspect is not currently in favour (Ronald and Admachak, 2008).

The main focus of this chapter is to ascertain whether naturally occurring Corynebacterium spp,

now shown to be able to utilize pentose sugars, are also able to produce any industrially

valuable amino acids.

The aim of this current study was to isolate, test and propagate microbes that could effectively

use pentose sugars naturally, and subsequently produce economically valuable end-products. As

the target end-product for this research was to be an amino acid and Corynebacterium spp are


71

known to be able to produce amino acids, this group, and environmental organisms

phenotypically similar to it (see Chapter 3), that are known to utilize pentose sugars (see Chapter

4), were further investigated to identify their end-products, in this chapter.


5.2.1 Equipment

The analysis was performed using two identical Agilent 1100 HPLC (Heracles, Japan) systems.

Each system consisted of a binary pump, a UV detector, a fluorescence detector and an auto

sampler. A reverse phase Agilent Zorbax Eclipse C18 column AAA (4.6150 mm, 3.5 micron) was

used for the chromatographic separation.

5.2.2 Chemicals

Amino acid standard solutions were obtained from Agilent (P/N 5061-3330). O-phthalaldehyde

3-mercaptopropionic acid (OPA-3MPA) and borate buffer were from Agilent. OPA-3MPA was

stored at 2–8°C in small vials crimped with silicon rubber, PTFE-coated cap (Woodward, 2007;

Henderson, 2009). A fresh aliquot of OPA was used for each set of samples. All other solvents

were HPLC grade from Agilent. The HPLC separation of the derivatized amino acids required two

mobile phases. The mobile phases, A (40 mmol/l Na2HPO4 at pH 7.8), and B (45% acetonitrile,

45% methanol, 10% water) were filtered through a 0.22-micron Millipore Durapore PVDF

membrane filter. To prevent microbial growth in the mobile phase, sodium azide (5 mg/L) was

added (Woodward et al., 2010). Potassium tetraborate, perchloric acid and potassium

dihydrogen phosphate were used for protein precipitation and extraction in this experiment.

5.2.3 Cultivation and sample preparation

As all of the E-PUB organisms were able to break down xylose as a carbon source in the growth

medium, xylose was the prefered substrate to analyse the end products. . Duplicate microbial

isolates were cultured on LB media with xylose as a carbon source for 3 days in shaking-

incubator. These young cultures were then held for 24 hours unshaken to produce sufficiently

anoxic conditions to encourage the production of the required end-products. Aliquots (50 μL) of

cultures were centrifuged to separate pellets at 5000 rpm (4620×g) for 30 min. According to the

method developed by Frank and Powers (2007), samples were added to an equal volume (20 μL)

of a standard (62.5 μmol/L) and HPLC-grade water (160 μL) for a final volume of 200 μL. Proteins

were subsequently precipitated by adding 200 μL of 0.5 mol/L perchloric acid. After protein

precipitation, the samples were centrifuged at 15,000 × g for 5 min at room temperature. 150 μL

of the supernatant was filtered in a Spin-X 0.2-μm micro-centrifuge filter by centrifugation at


72

15,000 × g for 1 min. 100 μL of the filtered sample was collected and split between two sample

vials to minimize the time between derivatization and injection on to the HPLC system.

The microbial extraction methods for amino acid analysis require a wide range of solvents. Some

examples include the use of ethanol perchloric acid, glycerol and an aqueous solution of

trichloracetic acid (Nunn and Keil, 2006). The perchloric acid extraction method is a considerably

more effective for qualitative analysis of amino acids than all other extraction techniques. In

addition, the use of perchloric acid is not expensive compared to other extraction chemicals.

The weight of the dry biomass was measured using a 100 mL sample, which was centrifuged in

100 mL centrifuge tubes (4°C, 25 minutes at 5000 rpm(4620×g)), and washed three times with

30 mL distilled water. The resuspended washed pellet was placed in an aluminum jar and freeze

dried at -50°C, vacuum pressure 300 p.a. The weight of the dried pellet was measured to permit

calculation of the yields per unit weight of glucose.

5.2.4 Standard preparation

All amino acid standards were stored at −20 °C. The linearity of the response for each individual

standard across different concentrations ranging from 5 to 1000 μmol/L was measured by

plotting the peak area for each amino acid divided by the area of the internal standard vs.

concentration (Frank and Powers, 2007).

5.2.5 Chromatographic system

The UV detection was performed with an absorbance wavelength of DAD (Dicode Array

Detector) 215 nm. The flow rate of the mobile phase was 1 ml/min throughout the analysis. The

total HPLC run time for the separation of the derivatized amino acids in a single sample or

standard was approx 6-8 min per sample.

Automatic pre-column derivatization with OPA-3MPA was performed at room temperature,

according to the injector programmes listed in Table 5.1, using 1 µL of filtrate (Woodward,

2007). After the derivatization, 0.5 µL of the mixture were injected for each chromatographic

separation. Primary amino acids were derivatized with OPA-3MPA and detected by a UV

detector at 215 nm, with a reference=360 nm, band width=10, slit of 4 nm, peak width of N 0.1

min. The protocol of HPLC injector programme is detailed in Table 5.1.


73

Table 5.1: HPLC injector programme for amino acid detection

5.3.6 Qualitative and quantitative analysis

Performance of a quantitative analysis requires the preparation of a calibration curve (see

Appendix Figure B1 a-e). The quantification was calculated as the average peak area per µmol of

amino acid present in the standard. To undertake quantitative analysis of amino acids, a sample

of a known volume is injected, and the peak area was calculated. The height and area of a peak

are proportional to the concentration of the corresponding component. A calibration curve (see

Appendix Figure B1 a-e) was created using the standard sample.

5.2.7 Recovery and variability

The recovery of the amino acids was calculated as the difference between spiked and unspiked

samples. Each sample was tested in triplicate and calculated for their average recovery.

Recovery was expressed as [(found concentration−basic concentration)/spiked

concentration]×100%. The intra-assay coefficient of variation (CV) was determined by replicate

analysis of a standard solution (n = 10) and a quality control sample (n = 10) in a single run (Frank

and Powers, 2007).

The between-run CV was 10% for all amino acids studied. A critical step for the reproducibility of

the method was the addition of column washes, performed before every injection, with a

Injector Program for mobile phase A and B

Line Function Amount Reagent

1 Draw 2.5 µL Borate Buffer(pH=7.8)

2 Draw 0.5 µL Sample/standard

3 Mix 3 µL in washpot, 400 µL/min speed, 6

times

4 Wait 0.2 min

5 Draw 0.5 µL OPA-3MPA

6 Mix 3.5 µL in washpot, 400 µL/min speed, 6

times

7 Draw 32 µL Water as an injection diluent

8 Mix 3 µL in washpot, 400 µL/min speed, 8

times

9 Inject 0.5 µL


74

mixture of methanol/water (90/10) to regenerate the column. The method demonstrated good

chromatographic separation of amino acids.

5.3 Results

5.3.1 Amino acid standard analysis

There was a linear relationship between the area and the amount of sample in the standard

curve. Figure 5.1 shows the separation of amino acid standards with mobile phase A at pH 7.8.

Separation and detection of a standard mixture (Agilent) of aspartic acid, glutamic acid,

asparagine, histidine, glycine, threonine, arginine, alanine, cysteine, tryptophan, phenylalanine,

and lysine were analysed with this mobile phase. The analysis of amino acids in physiological

fluids has been undertaken with the use of OPA derivatives. The OPA derivatized samples are

detectable in the UV range. The elution times are noted in Table 5.2.

Figure 5.1: Chromatogram of a mixture of 0.5 µL amino acids standards separated using HPLC

with mobile phase A (pH=7.8).

The range (1-13) of detectable standard amino acids is shown in Table 5.2

Table 5.2: Names of amino acids detected and their elution times

Peak no Name of amino acid Elution

time

(min)

Peak no Name of amino acid Elution

time

(min)

1 Aspartic acid 0.2 8 Alanine 3.3

2 Glutamic acid 0.5 9 Tyrosine 3.8

3 Serine 2.1 10 Cysteine 4.0

4 Histidine 2.6 11 Phenylalanine 4.4

5 Glycine 2.7 12 Isoleucine 4.6

6 Threonine 2.8 13 Lysine 4.8

7 Arginine 3.1

5.3.2 Amino acids detected from E-PUB metabolic process using pentose sugar

substrates

1 2 3 4 5 6 7 8 9 10 11 12 13


75

The microbial cells were treated as described above, and subjected to amino acid analysis (also

as described above). All amino acids were separated and identified with both mobile phases and

the within-run and between-run imprecision were comparable in both samples. Amino acids

were separated and identified using chromagraphic separation method with mobile phase A.

The separating condition was a combination of mobile phase of 45% acetonitrile, 45% methanol,

10% water in a flow rate of 1.0 ml/min. These amino acids were separated well under these

conditions. There were few obvious peaks of other components in the sample could be seen in

the chromatogram.

Figure 5.3 shows that all of the tested cultures: N. elegans (NC4-1); A. odontolyticus (PC4-1, NC1-

3); C. glutamicum (NC1-2, PC1-2; and P. freudenreichii (31TG) produced amino acids from xylose

metabolism and also after diaux. A variety of amino acids was produced in quantifiable amounts

after pentose sugar utilization.

Table 5.3: Amino acids produced by E-PUB isolates

Isolate Amino acid from single sugar pentose substrate

Concentration mg/L

N. elegans (NC4-1) Threonine 36

A. odontolyticus (PC4-1, NC1-3) Arginine 45

Cysteine 6

C. glutamicum (NC1-2, PC1-2)) Arginine 46

Cysteine 3

Glycine 5

P. freudenreichii (31TG) Arginine 47

Cysteine 10

Glycine 5

Alanine 6


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a. N. elegans (NC4-1)

b. A. odontolyticus (PC4-1)

c. C. glutamicum (NC1-2)

d. P. freudenreichii (31TG)

e. A. odontolyticus (NC1-3)

Figure 5.2: Continued on next page


77

f. C. glutamicum (pc1-2)

Figure 5.2: Chromatograms of the amino acid mixture present in microbial cultures. Samples derived from the set of E-PUB cultures, and separated using HPLC with mobile phase A (pH=7.8) (A) photodiode array UV detection at 215 nm.

As suggested by Frank and Powers (2007), the within-run CVs for all detectable amino acids

studied was <7% (Table 5.4). The between-run coefficient of variation (CV) was <10% for all

amino acids studied. A critical step for the reproducibility of the method was the addition of

column washes. These were performed by single injections, with a mixture of 45% acetonitrile,

45% methanol and 10% water to regenerate the column.

The method uses minimal sample volume and derivitization of amino acids with o-

phthalaldehyde and UV detection. Recovery and variability data are shown in Table 5.4. For all

concentrations, recovery of amino acids was between 94 and 96%, intra-assay coefficient of

variation (CV) was 1–6%, and inter-assay CV was 3–11% (Table 5.4). The results indicated a good

recovery of all amino acids which was acceptable.

Table 5.4: Performance characteristics of HPLC UV detection of amino acid

Between run and within run coefficient of variation (CV) for amino acids

Amino acids Elution time (min)

Within-run, %CV

Between-run, %CV

Recovery %

Arginine 2.1 5.9 10 96

Glycine 2.6 6.5 10.03 95

Threonine 2.7 6.3 10 94

Alanine 3.4 2.5 4.8 94

Cysteine 4.0 2.2 4.9 94


78

The wide analytical measurement range for all the amino acids studied could only be achieved

using UV detection, with the exception of hydroxyproline and proline. Since these amino acids

were detected by derivatizing with FMOC and using a fluorescence detector, a lower linearity

range was obtained. The within-run coefficient of variation (CV) for all amino acids studied was

5% (Table 5.2).

Figure 5.3 shows the analysis of an LB medium blank. It demonstrated that no free amino acids

were present in the medium. Those peaks that were present were all near 0 or below 1 mAU

value, thus being of no significance in terms of the final analysis.

Figure 5.3: HPLC for LB medium-blank analysis

The LB medium contains yeast extract, which is an inexpensive organic source of proteins and

vitamins for cell growth and synthesis of enzymes such as amylase and protease. This had the

potential to interfere with the results; however the HPLC of the blank medium showed that free

amino acids were not present in the medium. It may be that the yeast extract contains peptides

and small molecular weight protein components, but not significant amounts of free amino

acids.

5.3.3 End product analysis of diauxie metabolism

The end-products after dual-substrate cultivation, using glucose plus a pentose sugar (xylose,

arabinose and ribose) as substrates, were analysed using the HPLC methods as noted above.

Figure 5.4 a shows that four isolates, A. odontolyticus (PC4-1 andNC1-3), N. elegans (NC4-1) and

P. freudenreichii (31TG), cultured on a glucose and arabinose combination, produced the same

peaks over the 7 minutes of HPLC runtime. Glycine was separated from the extracted products

of growth of A. odontolyticus (PC4-1 and NC1-3), N. elegans (NC4-1), and P. freudenreichii (31TG)

isolates. There was a sharp unknown peak at 1.3 min (Figure 5.4 b). However, as shown in

Figure 5.4 c, all six indigenous microorganisms N. elegans (NC4-1), A. odontolyticus (PC4-1 and


79

C1-3), C. glutamicum (PC1-2 and NC1-2), P. freudenreichii (31TG) produced glycine as their

major end product after growth on the glucose with xylose as a dual sugar combination medium.

5.4a

5.4b

5.4c

Figure 5.4: End-products of dual-sugar metabolism (glucose and pentose) 5.4a: End product analysis as produced using glucose plus arabinose substrate combination, by isolates A.odontolyticus (PC4-1), A.odontolyticus (NC1-3), and N.elegans (NC4-1), and P. freudenreichii (31TG). 5.4b: End product analysis as produced using glucose plus ribose substrate combination, by isolate N. elegans (NC4-1). 5.4c: End product analysis as produced using glucose plus xylose substrate combination, by isolates C. glutamicum (PC1-2), C. glutamicum (NC1-2), A. odontolyticus (NC1-3), A. odontolyticus (PC4-1) and N. elegans (NC4-1).

All E-PUB isolates produced approximately 22 mg/L glycine after dual sugar xylose+ glucose

utilization. N. elegans (NC4-1) and A. odontolyticus (PC4-1, NC1-3) produced 22 mg/L glycine

after arabinose + glucose utilization as a combination carbon source. P. freudenreichii (31TG)


80

also produce the same amount of glycine after ribose + glucose utilization. These results are

shown in Table 5.5, together with the results of xylose metabolism for comparison.

Table 5.5: Amino acid production using single and dual carbon sources as substrates

Isolate Amino acid from single sugar substrate

Concentration mg/L

Amino acid from dual sugar substrate

Concentration mg/L

N. elegans (NC4-1) Threonine 36 Glycine 22

A. odontolyticus (PC4-1, NC1-3)

Arginine 45 Glycine 22

Cysteine 6

C. glutamicum (NC1-2, PC1-2))

Arginine 46

Cysteine 3

Glycine 5 Glycine 22

P. freudenreichii (31TG) Arginine

47

Cysteine 10

Glycine 5 Glycine 22

Alanine 6

The measurements of dry biomass after single and dual substrates utilized are given in Table 5.6.

Total biomass was measured following utilization of a single carbon source, and also following

the use of a combination of hexose and pentose (glucose and xylose, glucose and arabinose,

glucose and ribose) substrates during bacterial cultivation.

Table 5.6: Total biomass measured from single pentose and dual sugar carbon substrate

While the amounts of amino acid produced appeared to be similar, it was only by calculating the

yield of amino acid with respect to the biomass production in each case, that it became possible

Biomass Yx/s (g/g) (Single Pentose sugar carbon source)

Biomass Yx/s (g/g) (Dual sugar carbon source)

Bacteria Xylose Arabinose Ribose Glucose/

Xylose

Glucose/

Arabinose

Glucose/

Ribose

C. glutamicum (PC1-2) 0.48 - - 0.44 - -

C. glutamicum (NC1-2) 0.45 - -

0.51 - -

A. odontolyticus (PC4-1) 0.42 0.46 -

0.37 0.41 -

A. odontolyticus (NC1-3) 0.50 0.51 -

0.51 0.48 -

N. elegans (NC4-1) 0.54 0.54 0.51

0.55 0.52 0.49

P. freudenreichii (31TG) - 0.52 -

- 0.55 -


81

to determine which cultures were more efficient in an industrial context. The various yields of

amino acids, expressed in mg amino acid per gram of biomass (calculated on the basis of 500mL

of culture) are summarized in Table 5.7 below.

Table 5.7: Yield of amino acid expressed in mg per g of biomass, based on a 500mL culture size

5.4 Discussion

By means of this investigation, successful anabolism was detected after use of pentose sugars by

isolated indigenous microorganisms.

Among various cheap carbon sources, industrial by-products such as molasses and other

cheaper components like wheat bran and sugar cane bagasse have industrial potential, since

they support both biomass increase, and enzyme production (Kanekar et al., 2002). Sugar cane

bagasse has been the particular focus of this work.

Microorganisms are known to convert nutrients to various vital components necessary to their

survival and reproduction. With the fermentation method, raw materials are added to

microorganism culture media, and the proliferating microorganisms are encouraged to produce

E-PUB Amino acid Amino acid mg/500 mL (Single sugar)

Amino acid Yield (mg/g)

Amino acid mg/500 mL (Dual sugar)

Amino acid Yield (mg/g)

N. elegans (NC4-1) Threonine 18 33.3

Glycine 11 20

A. odontolyticus (PC4-1) Arginine 22.5 48.9

Cysteine 3 6.5

Glycine 11 29.7

A. odontolyticus (NC1-3) Arginine 22.5 44.1

Cysteine 3 5.8

Glycine 11 21.5

C. glutamicum (NC1-2) Arginine 23 47.9

Cysteine 1.5 3.1

Glycine 2.5 5.2 11 25

C. glutamicum (PC1-2) Arginine 23 51.1

Cysteine 1.5 3.3

Glycine 2.5 5.5 11 21.5

P. freudenreichii (31TG) Arginine 23.5 45.1

Cysteine 5 9.6

Glycine 2.5 4.8 11 20

Alanine 3 5.7


82

amino acids by manipulation of the physical conditions. The enzymes play an important role in

catalysing chemical reactions, are indispensable to degrade and synthesize substances and

various amino acids are produced as a result of these reactions.

Figure 5.5: Formation of intracellular and extracellular amino acid (Hundal and Taylor, 2009, page E604, figure 1)

In previous, related research, McCowan and Phibbs (1974) found that the total intracellular pool

increased during exponential growth of Bacillus licheniformis and then decreased rapidly after

the end of growth. Of great interest to the present research, they found that most of the amino

acids were present at low concentrations, while glutamate and alanine comprised 60 to 90% of

the total intracellular free amino acid at most times during the growth cycle. It was concluded

that, in addition to providing monomers for protein synthesis, the intracellular amino acid pool

could be maintained for the storage of energy-providing metabolic intermediates (Hundal and

Taylor, 2009). A 10-fold increase in extracellular amino acid was observed as the cells changed

from vegetative to sporulation metabolism, mostly due to the extrusion of intracellular amino

acid. The bacterial isolates used in the current research were not capable of sporulation,

however it is considered most likely that the maximum production of amino acids was also

undertaken in the stationary phase of their growth cycle, and in the anaerobic conditions.

The main focus of this research was to study amino acid production by E-PUB, with intracellular

amino acids as the primary target, these being indicative of internal metabolic processes related

to the synthesis of the bacterial cell wall. Microorganisms produce a variety of amino acid

products in order to build the cell wall, following which excess amino acids are excreted as


83

extracellular amino acids (Figure 5.5), (Scheffers and Pinho 2005). In this research, it was decided

to focus on intracellular amino acids, as per the method published by Frank and Powers (2007).

So intracellular amino acid extraction was performed from the centrifuged pellet, rather than

from the supernatant. While it is possible that the measured levels could have been higher, if

the supernatant had also been tested, this was not done, as it was expected that a greater

concentration of amino acids would be expected intracellularly, this being their primary

destination.

Ideally, further optimization of various growth parameters such as pH, temperature, incubation

time, levels of nitrogen, phosphorous and other growth factors and the oxygen levels, would

have been performed, preparatory for upscaling the process to an industrial level. Such

optimization would no doubt have the result of improving the yield, which was rather low in the

reported results. It is also acknowledged that further extraction and analysis of extracellular

amino acids, potentially present in the culture supernatant, may prove to be a factor in

improving the yield.

These trials produced good yields of amino acids compared to previous research. For example,

3.6 g/liter threonine was produced from the modified whey permeate by using Escherichia coli

ATCC 21151 for threonine production, and utilizing lactose as a carbon source (Young and

Chipley, 1983). Arginine concentration of the batch fermentation was 36.6 g/liter produced by

Corynebacterium crenatum (Xu et al., 2009). According to Dhillon et al., (1987) Bacillus

sphaericus produced 7g/ litre L-cysteine.

To determine the relationships between the processes of uptake, intracellular pool formation,

and incorporation of amino acids into protein, research regarding the quantitative and

qualitative analysis of bacterial intracellular free amino acids was examined. Significantly, not all

the amino acids present in the proteins of bacteria were present in the pools in detectable

concentrations (that is, greater than 0-1 mM). In particular, the pools of both Gram-positive and

Gram-negative bacteria were found to generally lack tryptophan, tyrosine, phenylalanine,

histidine, arginine, cysteine and methionine. Of the amino acids regularly present in bacterial

pools, leucine, isoleucine, serine, glycine, aspartate, valine, lysine and proline were frequently

present in low concentrations. Whereas according a previous report, 3.4 mM Glycine was

produced by Bacillus subtilis, 1.5 mM B. megaterium and 7.1 mM B. polymyxa; 3.1 mM alanine

produced by Bacillus subtilis, 0.6 mM B. megaterium and 20 mM B. polymyxa; 2.6 mM threonine

from Bacillus subtilis, 0.5 mM B. megaterium and 21 mM B. polymyxa (Tempest and Meers 1970;

Kirchman and Hodson 1986; Iwatani et al., 2007).


84

In the present study, following diauxie breakdown of a pentose sugar and glucose, the only

amino acid produced in measureable quantity was glycine. A. odontolyticus (PC4-1) yielded 29.7

mg/g of biomass, while NC1-3 produced 21.5mg/g biomass. Similarly, C. glutamicum (PC1-2)

produced 21.5mg/g biomass while NC1-2 produced 25mg/g biomass. P. freudenreichii and

N.elegans both produced the lowest concentrations of glycine, which was 20mg/g biomass. The

presence of glycine is not surprising, as it has been shown above to be a major end-product of

bacterial metabolic processes, and it is an end-product of amino acid productive pathways.

The amino acid spectrum produced after single pentose sugar growth was broader, with other

amino acids being detected, such as threonine, cysteine alanine and arginine. Of these, the best

yield was found with arginine, with figures of up to 51.1mg/g biomass produced by C.

glutamicum (PC1-2). However, since the context of this study was that of a mixed substrate, it is

unlikely that the production of arginine would be amenable to industrialization.

Variations in growth conditions were, whilst not explored fully in the present work, admitted to

be very important in studies of this kind. Obviously, the macromolecular composition and

metabolic activity of microorganisms may vary with changes in their growth environment

(Herbert, 1961; Neidhardt, 1963; Brown & Rose, 1969; Tempest, 1970). These phenotypic

changes in cell structure and functioning reflect changes in genetic expression and are

presumably mediated by some environmentally linked mechanism. Thus, changes in the growth

conditions must affect primarily the intracellular concentrations of substances reacting directly

with the genetic control mechanisms. In particular, intracellular amino acids are extremely

variable and markedly dependent on the nutritional complexity of the growth medium (Herbert,

1961; Neidhardt, 1963; Brown & Rose, 1969; Tempest, 1970).

In this work, E-PUB microorganisms have been studied for use in the production of various

industrially important amino acids. One very important variable in this type of work is that of

oxygen availability. Under conditions of oxygen deprivation, microbial cell growth (biomass

increase) is arrested, but the cells retain the capability to produce end-products including

organic acids, such as lactic acid, succinic acid, acetic acid (Inui et al., 2004). This allows, under

anoxic conditions, following aerobic culture, a bioprocess resulting in the production of

commercially valuable amino acids. Actinomyces and Propionibacterum are microorganisms

known to produce succinic and lactic acids (Siqueria, 2003) and so are good candidates for

industrial processes.

Further, oxygen requirements for the growth and production of end-products are known to be

influenced by osmotic pressure. Several researchers (Varela et al., 2002; Morbach and Krämer,


85

2003) have studied the influence of osmotic pressure on the growth and physiology of C.

glutamicum and related species. C. glutamicum was studied as it was considered a very

important microorganism for industrial level amino acid synthesis. Specific growth rates and

carbon-to-biomass yields decreased nearly linearly with increasing osmotic pressure, while the

rate of sugar uptake increased significantly. These scenarios may happen with E-PUB during their

metabolism. Neither of these studies was conducted with pentose sugar substrates, so that it

was predicted that, the response of the E-PUB on metabolic network to osmotic pressure may

be only assumed by comparison with the glucose substrate that was used.

Nitrogen is required for the growth of most bacteria, including Corynebacterium spp, Nocardia

spp and Actinomyces spp. Studies by Varela et al. (2002) demonstrated the nutritional

requirement for nitrogen by C. pyogenes, a bacterium that is quite different to other

Corynebacterium spp of animal origin. Cell wall composition, biochemical properties, metabolic

products and the absence of mycolic acids are the main differences from other species.

However, according to the vitamin requirement, this bacterium is very similar to Actinomyces

spp. Thus it is considered probable that the E-PUB will have a nitrogen dependant metabolism,

un-noted in the present research as nitrogen was provided in excess of demand.

In the 1950s, C. glutamicum was found to be a very efficient producer of L-glutamic acid. Since

that time, biotechnological processes with bacteria of the species Corynebacterium have

become very important in terms of tonnage and economic value. L-glutamic acid and l-lysine are

bulk products and l-valine, l-isoleucine, l-threonine, l-aspartic acid and l-alanine are among other

amino acids produced by Corynebacterium (Hermann, 2003). To date, l-cysteine has been

produced almost completely by extraction from biological materials such as hair. However, an

alternative bioprocess was established in 2000 using E. coli (Daßler et al., 2000). Several

coryneform strains were described that would produce significant amounts of l-cysteine (Wada

et al., 2002). The present research has shown that C. glutamicum produced arginine, glycine and

cysteine from the pentose sugars. The production of arginine and glycine from C. glutamicum

without genetic modification is a new finding. It is considered that the growth of this organism

on pentose sugars is what makes the observed difference in outcome. This will be the milestone

towards industrial production of amino acid in terms of saving costs.

This research did not continue to the extent of examining the enzymes present in E-PUB to

manufacture amino acids; however it is of interest to note the extent of current knowledge in

this field, as this may be quite relevant to industrial scale production. Amino acids can be divided

into groups on the basis of end-product production by anabolic pathway. Alanine is a part of the

pyruvate family whereas glycine and cysteine are members of the serine family; threonine is a


86

part of the aspartate family and arginine falls under the glutamate family. In the anabolic phase,

arginine and threonine are producd as end products through the TCA cycle.

Glycine, the major end-product of the E-PUB metabolism, is formed from 3- phosphoglycerate

(Figure 5.6), and arginine is produced from α-ketoglutarate. All of the environmental pentose-

utilizing bacteria (E-PUB) produced arginine as an end product, with the exception of N. elegans

(NC4-1), which produced threonine. This may be due to the presence of threonine synthase

enzyme. A. odontolyticus (PC4-1 and NC1-3), C. glutamicum (PC1-2 and NC1-2), and P.

freudenreichii (31TG) produced arginine, indicating the probable activity of a combination of the

enzymes arginino-succinate synthetase and arginino-succinate lyase (Figure 5.6). These bacteria

also have produced cysteine because of the possible presence of cystathionine lyase. C.

glutamicum (PC1-2 and NC1-2- ) and P. freudenreichii (31TG) produced glycine due to the

probable presence of glycine hydroxymethyltransferase enzyme. Only P. freudenreichii (31TG)

excreted alanine, this may be due to the presence of alanine transaminase.

In the process of amino acid production, there is an interim step, which is the formation of

glutamate. Although glutamate was not identified by HPLC as an end product, probably due to

the low concentrationm it was found in the review of published literature (chapter 2) that

Corynebacterium sp is mostly known as a glutamic acid producer organism. However in this

study it appeared that glutamate was not present and predictable cause may be that it was

further metabolised to arginine.

Figure 5.6: Glycine biosynthesis (http://themedicalbiochemistrypage.org/amino-acid-

metabolism.php#arginine)

According to Hui et al, (2001) and Thiele et al., (2002) applications of amino acids either in food

and pharmaceuticals or in animal feed nutrition, are expected to increase in the next few years.

It was predicted that, all 6 E-PUB isolates produced arginine and all except N. elegans (NC4-1)


87

produced cysteine. According to previous research (Hui et al., 2001), cysteine was mainly the l-

enantiomer, which is a precursor in the food, pharmaceutical and personal care industries. One

of the largest applications is the production of flavouring products, and arginine is also used as a

food supplement.

In the current research, C. glutamicum (NC1-2 , PC1-2) and P. freudenreichii (31TG) produced

glycine when a single pentose carbon source was metabolised. Glycine is very important in

pharmaceutical applications (Kuan et al., 2003). Furthermore, glycine was the major end product

from diauxie metabolism of all indigenous isolates. Metabolism of glycine may influence the

availability of substrates for the production of other amino acids. Glycine is one of glucogenic

amino acids, which refers to their ability to provide glucose to the blood. Additionally, glycine

also plays a role as a major inhibitory neurotransmitter in the spinal cord and brain stem, and an

anti-inflammatory, cytoprotective, and immune modulating substance (Gundersen et al., 2005).

The production of glycine by E-PUB would be a significant contribution to industrial amino acid

production in terms of health products.

5.5 Conclusions

After catabolic reaction with the pentose sugar, xylose, as a substrate, the isolate N. elegans

(NC4-1) produced threonine whereas A. odontolyticus (PC4-1 and NC1-3), C. glutamicum (PC1-

2and NC1-2), produced arginine and cysteine. Isolate P. freudenreichii (31TG) produced glycine,

arginine, alanine and cysteine after utilization of arabinose as a sole carbon source. All six

isolates produced glycine after dual (xylose and glucose) sugar catabolism. P. freudenreichii

(31TG) also produced glycine after metabolizing a dual sugar combination of glucose and

arabinose. The production of glycine is important because of its pharmaceutical significance.

Chapter 6 Ecology of E-PUB: DGGE

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CHAPTER 6

Ecological Study of Environmental Pentose-Utilizing

Bacteria by Denaturing Gradient Gel Electrophoresis

(DGGE)

6.0 Summary

Previously in this thesis (chapter 3), the process of isolating pentose metabolizing bacteria from

a pentose rich environment was described, in order to assess their industrial potential. While

this autecological approach has many advantages, it must be recognized that the natural eco-

niche of these organisms is not a simple one, and that there is a vast amount of knowledge to be

gained from using a synecological approach, where the bacterial community of a site is

examined as a whole. This approach is best applied using metagenomic methods, such as the

DGGE technique employed here. This research analysed microbial communities in sugar mill

samples such as water, soil, and bagasse leachate collected from five cane-growing areas in

Queensland, Australia, using Denaturing Gradient Gel Electrophoresis (DGGE) and subsequent

DNA sequencing.

It was found that a variety of organisms were present in the bagasse leachate that was not

present in other samples. The most common environmental bacteria Brevibacillus brevis,

Rhodospirillaceae bacterium, Bacillus sp, Vibrio sp and Pseudomonas sp were present in all

samples. Corynebacterium was found in the soil of Proserpine, Mackay and Maryborough sugar

mills.

6.1 Introduction

The dynamics of bacterial communities within a hemicellulose-enriched environment represents

an opportunity for commercial enterprise. There is a wide variety of valuable end-products from

the natural microorganisms after the catabolism of lignocellulosic materials.

Applied molecular microbiology is a rapidly growing research area. One of the branches of this

discipline is involved in the development of molecular methods for the identification and

monitoring of microorganisms in natural ecosystems. The principal reason for the use of culture-

independent techniques is the lack of knowledge of the real conditions under which most

bacteria are growing in their natural habitat and the difficulty in developing growth media that

accurately re-create these conditions (Li et al., 2006). Molecular methods are also characterised

by rapidity and reliability. Genetic fingerprinting techniques are able to provide a profile

representing the genetic diversity of a microbial community from a specific environment


89

(Ercolini, 2004). Denaturing gradient gel electrophoresis (DGGE) is now a commonly used

technique in molecular biology and has become a fundamental method of environmental

microbiology for the characterization of population structure and dynamics (Sanchez et al.,

2007; Green et al., 2007) . The method is powerful, and can rapidly provide a tangible

characterization of community diversity and composition, and shifts in population can be readily

demonstrated.The only major drawback is the inability to load all samples onto the same gel and

the potential for gel-to-gel variation, which influences DGGE analysis (Nunan et al., 2005). In

addition to its use in environmental analyses, DGGE is also used in the medical field for the

detection of mutations, including single nucleotide polymorphisms (SNPs) (Green et al., 2007).

16S rDNA gene sequencing is required to identify the individual microbial species from DGGE

analysis. 16S rDNA gene sequencing is a powerful tool that has been used to trace phylogenetic

relationships between bacteria, and to identify bacteria from various sources, such as

environmental sources (Neufeld et al., 2006) or clinical specimens (Clarridge, 2004 ). This

technology is used today in clinical laboratories for routine identification, especially for slow-

growing, unusual or fastidious bacteria, but also for bacteria that are poorly differentiated by

conventional methods (Clarridge, 2004; Vandamme et al., 1996).

Phenotypic methods present some inherent problems. There can be a substantial amount of

variability among strains belonging to the same species; the corresponding database may not yet

include newly described species; and the test may rely on an individual and subjective

interpretation (Raoult et al., 2004). Identification based on the 16S rDNA sequence is of interest

because the ribosomal small subunit (SSU) exists universally among bacteria and includes

regions with species-specific variability, which makes it possible to identify bacteria to the genus

or species level by comparison with databases in the public domain (Clarridge, 2004 ). The

molecular approach is important for species definition and identification (Clarridge, 2004 ;

Rosselló-Mora and Amann, 2001; Raoult et al., 2004). Other authors (Bosshard et al., 2003; Tang

et al., 2000) have also reported 16S rDNA sequencing use as a tool for bacterial identification.

They have usually compared this molecular identification tool favourably to classical phenotypic

methods. The great potential of the method has been reported for Gram-positive rods and

coryneform bacterial identification (Bosshard et al., 2004; Tang et al., 2000). This is of particular

interest in the present study, as these categories are the focus of this work.


90

6.2 Materials and methods

6.2.1 Extraction of bacterial DNA from samples

Extraction of the DNA from soil and bagasse stockpiled samples was performed using the MOBIO

power soil DNA isolation kit (MOBIO Laboratories inc. USA). The MOBIO ultra clean water DNA

isolation kit was used for DNA extraction from liquid waste and bagasse leachate samples. All

sample details are provided in Table 6.1. Extracted DNA was quantified spectrophotometrically

(Beckman Coulter, Australia) by measuring the absorbance ratio A260:A280, which determines

the purity of the DNA.

Table 6.1: List of the samples collected from different sugar mills

Sample no. Sample nature Sample name Location Sample code

1 Liquid Floor dump sump Proserpine FDS-P

2 Liquid Cooling tower water Proserpine CTW-P

3 Liquid Floor dump sump Mackay FDS-MK

4 Liquid Cooling tower water Mackay CTW-MK

5 Liquid Floor dump sump Maryborough FDS-M

6 Liquid Cooling tower water Maryborough CTW-M

7 Liquid Bagasse leachate Mackay BGL-MK

8 Solid Mud sample Proserpine MS-P

9 Solid Decaying trash from cane farm Proserpine DT-P

10 Solid Bagasse from stockpile Proserpine BG-P

11 Solid Mud sample Maryborough MS-M

12 Solid Decaying trash from cane farm Maryborough DT-M

13 Solid Bagasse from stockpile Maryborough BG-M

14 Solid Mud sample Mackay MS-MK

15 Solid 46 Caswells soils Mackay CS-MK

16 Solid 42 Blair soil Mackay BS-MK

17 Solid 58 Effluent pond soil Mackay EPS-MK

18 Solid 55 Tropic Isle soil Mackay TIS-MK


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6.2.2 Sample description

The Floor dump sump (FDS) holds the liquid waste from washing the raw materials, it is filtered,

passes through the pipe network, and finally is stored in the sump; cooling tower water (CTW).

Figure 6.1: Typical sugar processing mill. Sampling sites marked with arrows. (modified from:

http://www.enterprisewhitsundays.com.au/index.php/download_file/view/109/.)


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Bagasse is sugar cane waste after pulping and extraction; bagasse leachate is liquid in nature,

created by rainwater passing through the bagasse heaps from the bagasse stockpile. All bagasse

piles are covered with tarps and secured with strapping/tyres. All pads are constructed with

road base, self draining to leachate catchment system. A storm water leachate collection system

was collection from each of the storage sites or gravity run-off to mill effluent systems. Water

collected in leachate collection dams/ponds pumped to mill effluent systems.

The sampling site and a diagram of the sugar processing are shown in Figure 6.1. The strategy for

selecting these sites was to ensure samples that might be expected to have hemicellulose-

enrichment. However, cooling tower water (CTW) has no physical connection to the sugar

waste. For this reason, CTW was selected as a control, non-enriched sample. A major objective

of this study was to compare the microbial diversity within hemicellulose-enriched and non-

hemicellulose-enriched habitats. This was because work continues on the bagasse stockpiled

area with respect to mitigating environmental and health issues, associated with large scale

bagasse storage (Womersley, 2006). Leachate and contaminated stormwater from bagasse

stockpiled are generally confined to drains and ponds. Odour from the bagasse stockpile is an

issue, and may include the formation of acetic acid in older piles. Most odour problems are

found at the pile breakdown point (site, and also time). Odour issues persist mainly on site

where bagasse may be confined to conveying systems for extended periods of time.

6.2.3 16S rDNA PCR amplification

PCR amplification was performed in a 25-μL (total volume) reaction mixture. The final

concentration of different components in the mixture was: 50 ng of purified DNA, 0.4 μM of

each primer (Sigma-Aldrich), 200 μM of each deoxynucleoside triphosphate (dNTP, Roche), 1.5

mM MgCl2 (Invitrogen), 1× thermophilic DNA polymerase, PCR 10×reaction buffer (Roche), 1.25

U per 50 μL of Taq DNA polymerase (Roche), and DNAse and RNAse free filter sterilized water

(GIBCO ultrapure water-Invitrogen). PCR amplification of 16S rDNA bacterial genes was carried

out using the universal primers (forward primer 5′ GAGTTTGATCCTGGCTCAG 3′ and reverse

primer 5′ ACGGCTACCTTGTTACGACTT 3′). PCR was performed using the following cycle

conditions: 95°C for 5 min followed by 25 cycles of 94°C for 1 min per cycle, 55°C for 1 min, 72°C

for 1 min and a final extension step of 72°C for 10 min. The PCR samples were amplified using a

PCR thermal cycler (Bio-Rad, DNA engine, Peltier, Thermal cycler, USA) and PCR products were

visualized on a 1% agarose gel stained with ethidium bromide.


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6.2.4 Denaturing gradient gel electrophoresis (DGGE)

Duplicate DGGE was performed with the Bio-Rad DCode System (Bio-Rad, Australia). Equal

volumes of each PCR product were loaded onto polyacrylamide gels with a denaturing gradient

of 30% (7% (w/v) acrylamide–bisacrylamide (37.5:1), 2.55 M urea, 14.68% formamide) to 70%

(7% (w/v) acrylamide–bisacrylamide (37.5:1), 3.57 M urea, 20.56% formamide) with Tris-acetate

EDTA buffer (pH 7.4), at 65° and 60 V, for 16 h. After electrophoresis, the gels were soaked for

30 min in gel-red nucleic acid gel stain (1:10000 dilution) (BIio-Rad, Australia). The stained gels

were immediately photographed on a UV transilluminator (Bio-Rad, Australia).

6.2.5. Analysis of DGGE patterns

The DGGE patterns were analysed using the Bio-Rad software to create a phylogenetic tree

based on the molecular weights of each visible band on the DGGE gel. The gel image was

imported into Total Lab 120 software (Nonlinear Dynamics Ltd, United Kingdom) to determine

the band patterns for each sample. Band location and intensity were imported into PrimerE

software (Plymouth Marine Labs, United Kingdom) and a similarity matrix was created using the

Bray-Curtis method, to observe the similarity of community fingerprints. The Bray-Curtis

similarity coefficient was used to determine site similarities based on organism abundances. It

reflects differences between two samples due both to a differing community composition

and/or a differing total abundance.

6.2.6 Re-extraction of DNA from DGGE gels followed by DNA sequencing

Bands selected for sequence analysis were carefully excised from the DGGE gel with a sterile

scalpel. The middle portion (avoiding edges) of each band was selected to minimize the DNA

contamination and to obtain high concentrations of DNA. The slices were placed in 2-mL

sterilized microfuge tubes. DNA was purified using the MOBIO (MOBIO laboratories, USA) gel

extraction kit. The DNA was quantified by the spectrophotometric method at 260/280 nm. A 5

µL sample of the eluate was used as template DNA for a PCR performed with the universal 16S

rDNA primers and the conditions described above for environmental samples (section 6.2.3).

Five µL of each PCR product was subjected to agarose gel electrophoresis to check product

recovery and to estimate product concentration.

6.2.7 16S rDNA gene sequencing methodology

16S rDNA sequencing was performed using a Dye Terminator Cycle Sequencing reaction method

that included 200 ng PCR product, 3.2 pmol primer, 1 μL big dye, 3.5 μL sequence buffer and

water in a total volume of 20 μL. PCR was performed using a DNA engine, (Peltier, Thermal


94

cycler) programmed for using forward and reverse sequencing primers 16S F 5′

GAGTTTGATCCTGGCTCAG 3′ and R 5′ ACGGCTACCTTGTTACGACTT 3′ respectively. The

sequencing reaction was thermally cycled as follows on the DNA Engine (Peltier, Thermal cycler):

95 °C for 1 min (1 cycle); 98 °C for 45 s, 50 °C for 10 s, 60 °C for 4 min (1 cycle); 98 °C for 15 s, 50

°C for 10 s, 60 °C for 4 min (29 cycles); 4 °C for 5 min (1 cycle); 10 °C hold.

Sequencing products, unincorporating terminators and primers were purified with a 70%

ethanol wash, using an ethanol/EDTA method and big dye x terminator purification kit according

to the Griffith University, Brisbane, Australia DNA sequencing protocol

(http://www.griffith.edu.au/science-aviation/dna-sequencing-facility/services/dna-

sequencing/sequencing-protocolm ). Sequencing products were analysed using an ABI 3500

Sequencer (Applied Biosystems). Consensus sequences were assembled from the forward and

reverse sequences and edited with Sequencer software (Bio- Edit). Consensus results were

compared with sequences in GenBank, using the BLAST sequence similarity search.

6.2.8 Statistical analysis

Statistical analysis of band patterns was performed using the relative band intensity within a

lane as well as the presence vs. absence species. Cluster diagrams were created using the

unweighted pair group method with arithmetic mean (UPGMA). The Bray-Curtis similarity

coefficient was used whereby the relative intensity of each band was also taken into account. In

addition, non-metric multidimensional scaling (MDS) analysis was done in parallel to further

elucidate the differences in DGGE profiles.

Analysis of the bacterial community DGGE profiles was performed with the Bio-Rad software

package according to the provider's instructions. The DGGE gel photographs were screened for

the presence (1) or absence (0) of bands on the DGGE gel. The unweighted pair-group method

with arithmetic averages (UPGMA) algorithm was used (as part of the analysis software), for the

construction of phylogenetic dendrograms.

6.3 Results

6.3.1 PCR–DGGE analysis

The DGGE profiles of bacterial communities in seven liquid and 11 solid samples from

Queensland sugar mills were observed. Lane numbers 1 to 6 contained the extracts from liquid

samples; lane seven contained the bagasse leachate (BGL-MK) and lanes eight to 18 contained

the solid samples.

http://www.griffith.edu.au/science-aviation/dna-sequencing-facility/services/dna-sequencing/sequencing-protocol

http://www.griffith.edu.au/science-aviation/dna-sequencing-facility/services/dna-sequencing/sequencing-protocol


95

6.3.1.1 Analysis of the microbial community structure using the Bray-Curtis method

All microbial communities of solid and liquid samples from the Proserpine, Mackay and

Maryborough sites remained clustered within their respective treatments (Figure 6.2). The Bray-

Curtis dendrogram (Figure 6.2) demonstrated that the association was strongest among

communities in the solid samples in which eight replicate plots shared a 65% similarity.

Additionally, four groups of liquid samples also shared a 65% similarity among plots, except the

cooling tower water from Maryborough and Proserpine. These two samples shared only a 50%

similarity. The bagasse leachate (Mackay only) samples also showed a 65% similarity. However

BG-P shared about 80% similarity with the remainder of the samples (Figure 6.2). The liquid

samples (floor dump sump, cooling tower water and bagasse leachate as available from the

various mills) are also analysed on the MDS plot in Figure 6.5. This further examination was

performed in order to better understand the microbial communities of the liquid samples from

Figure 6.2. Although bagasse form Proserpine and Maryborough were not liquid samples, they

were included in Figure 6.5 to demonstrate the difference between bagasse, and bagasse

leachate, which is considerable.


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Figure 6.2: Community fingerprint analysis using the Bray-Curtis method.

The sample codes are represented in detail in Table 6.1 (Sample type – Mill location).

6.3.1.2 Analysis of microbial community structure in liquid samples

In this part of the study, liquid samples were analysed separately and Figure 6.3 shows the DGGE

profiles of the microbial communities of seven liquid samples including BGL-MK.

FDS-P (1)

CTW-P (2)

FDS-MK (3)

BGL-MK (7)

MS-P (8)

DT-P (9)

CTW-M (6)

CTW-MK (4)

FDS-M (5)

BG-M (13)

DT-M (12)

MS-M (11)

BG-P (10)

MS-MK (14)

CS-MK (15)

BS-MK (16)

EPS-MK (17)

TIS-MK (18)


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Figure 6.3: DGGE profiles of bacterial community structures in liquid samples. Lanes one to seven represent the sample codes FDS-P, CTW-P, FDS-MK, CTW-MK, FDS-M, CTW-M and BGL-MK respectively.

Figure 6.4: Phylogenetic tree analysis of liquid samples by Unweighted Pair Group Method with

Arithmetic Mean (UPGMA)

FDS-P

CTW-P

CTW-MK

CTW-M

FDS-MK

FDS-M

BGL-MK


98

Figure 6.4 represents the DGGE gel profiles that were incorporated into a phylotree by using an

unweighted pair-group average (UPGMA) analysis. UPGMA analysis joins clusters based on the

average distance between all members in the two groups. This analysis revealed that the DGGE

band patterns for each site clustered separately. The greatest difference was found between the

profiles of sample #7 (bagasse leachate from Mackay) and all other liquid samples.

The bagasse leachate sample population (BGL-MK - band 7) shared only 61% similarity with that

of all other liquid samples. On the other hand, a 90 % similarity was noted between floor dump

sump sample populations at Proserpine and Mackay (FDS-P – lane 1 and FDS-MK - lane3).

Interestingly, populations from the cooling tower water at Mackay (CTW-MK – lane 5) and the

floor dump sump from Maryborough (FDS-M - lane 4) have more than an 80% similarity;

whereas the populations of the same category of samples from different locations (CTW-P – lane

2 and CTW-M – lane 6) show only 73% similarity with most liquid samples, with the exception of

bagasse leachate.

Whilst the multidimensional scaling plots of DGGE patterns revealed different patterns of

bacterial communities compared to the source of the sampling (Figure 6.2), in most cases no

clear trend could be observed. This method demonstrated the separation of samples by sample

type but showed minimal effect of location. A variety of types of liquid samples from different

sources were further analysed and the results are displayed in Figure 6.5. From this analysis,

bagasse leachate and bagasse from stockpiled could only be compared with similar samples.

Figure 6.5 is a MDS analysis of phylogenetic relationships (from Figures 6.3 and 6.4) of liquid

samples (FDS-P, CTW-P, FDS-MK, CTW-MK, FDS-M, CTW-M and BGL-MK) including bagasse

samples BG-P and BG-M.

The MDS analysis of these patterns revealed that the structure of the microbial community from

liquid samples; FDS-M, CTW-M, FDS-P, FDS-MK and CTW-MK; were not significantly different,

although CTW from Proserpine mill was slightly different from the other sites (Figure 6.5). In

contrast, bagasse leachate from Mackay (BGL-MK) was significantly different to all other

samples. Also as seen in Figure 6.5, no significant differences were observed between the two

bagasse samples (BG-P, BG-M) from the Proserpine and Maryborough sugar mills.


99

Figure 6.5: Non-metric multi-dimensional scaling (MDS) plot analysis of DGGE bands for liquid

samples plus two bagasse samples

6.3.1.3 Analysis of microbial community structure in solid samples

Each of the distinguishable bands in the separation pattern represents an individual bacterial

species. Clustering of the profiles revealed that there were very large differences between the

profiles of the solid samples. The profiles of solid samples MS-P, DT-PMS-M, DT-M, MS-MK, CS-

MK, EPS-MK, and TIS-MK had showed (Figure 6.7) 83% - 88% similarity with respect to their

clustering. The profile of bagasse from Proserpine (BG-P) was quite different and separate from

other profiles and belonged to a single group, with a similarity of 54% to the profile of sample

BS-MK and others.


100

Figure 6.6: DGGE profiles of bacterial community structures in soil samples

Figure 6.7: Phylogenetic tree analysis of solid samples. All the abbreviations of the sample codes

are listed in Table 6.1.

MS-P

CS-MK

MS-MK

BG-M

DT-M

MS-M

BG-P

DT-P

BS-MK

EPS-MK

TIS-MK


101

There was about 71% similarity between the two groups. Group (a) consisted of samples MS-

MK, CS-MK, EPS-MK, BS-MK, and group (b) of samples MS-M, DT-M, BG-M). This analysis

indicated the bacterial diversity of the hemicellulose-enriched soil waste of Queensland sugar

mills.

6.3.2 16S rDNA sequencing analysis of selected DGGE bands

The 17 sequences were compared with by BLAST software in the NCBI database (Figure 6.8).

Only partial sequences were aligned and the similarity between these sequences of

microorganisms in Genbank is shown in Table 6.2.

Figure 6.8: DGGE gel image indicating the lane numbers

Lanes 1 to 18 represent the sample codes FDS-P, CTW-P,FDS-MK,CTW-MK,FDS-M,CTW-M, BGL-

MK, MS-P, DT-P, BG-P, MS-M, DT-M, BG-M, MS-MK, CS-MK, BS-MK, EPS-MK, TIS-MK

respectively.

Using a threshold of greater than 65%-99% similarity for positive identification, evidence was

found for the presence of Brevibacillus brevis, Rhodospirillaceae bacterium, Rhodospirillaceae

bacterium, Corynebacterium sp., Pseudomonus fluorescens, Bacillus subtilits, endophytic

bacteria, Pseudomonas aeruginosa, Vibrio vulnificus, Azospirillum brasilense, Roseomonas

fauriae, Bulkholderia cepacia, Bacillus cereus, Bacillus thuringiensis, Alcaligenes faecalis, Vibrio

ichtyoenter and Vibrio aestuarianus in all samples tested (Table 6.2 and 6.3).


102

Table 6.2: 16S rDNA sequencing results including samples and DGGE band details

Lane no

Sample nature

Sample name Band No

Species

1 Liquid Floor dump sump from Proserpine (FDS-P)

1,2,5, 10,17

Brevibacillus brevis, Rhodospirillaceae sp., Bacillus subtilits, Roseomonas fauriae, Vibrio aestuarianus

2 Cooling Tower water from Proserpine(CTW-P)

1,2,5, 15,17

Brevibacillus brevis,Rhodospirillaceae sp., Bacillus subtilits, Vibrio ichtyoenter, Vibrio aestuarianus,

3 Floor dump sump from Mackay (FDS-MK)

1,2,5, 9,11,17

Brevibacillus brevis, Rhodospirillaceae sp., Bacillus subtilits, Azospirillum brasilense, Burkholderia cepacia, Vibrio aestuarianus

4 Cooling Tower water from Mackay (CTW-MK)

1,2,6, 17

Brevibacillus brevis, Rhodospirillaceae sp., Endophytic bacterium, Vibrio aestuarianus

5 Floor dump sump from Maryborough(FDS-M)

1,2,4,5, 17

Brevibacillus brevis, Rhodospirillaceae sp., Pseudomonas fluorescens, Bacillus subtilits, Vibrio aestuarianus

6 Cooling Tower water from Maryborough (CTW-M)

1,2,7, 8,12,17

Brevibacillus brevis, Rhodospirillaceae sp., Pseudomonas aeruginosa, Vibrio vulnificus, Bacillus cereus, Vibrio aestuarianus

7 Bagasse leachate from Mackay (BGL-MK)

1,5,8, 13,14,17

Brevibacillus brevis, Bacillus subtilits, Vibrio vulnificus, Bacillus thuringiensis, Alcaligenes faecalis, Vibrio aestuarianus

8 Solid Mud sample from Proserpine (MS-P)

1,4,5,6,8

Brevibacillus brevis, Pseudomonas fluorescens, Bacillus subtilits, Endophytic bacterium, Vibrio vulnificus

9 Decaying trash from cane farm Proserpine( DT-P)

1,2,4,5, 17

Brevibacillus brevis, Rhodospirillaceae sp., Pseudomonas fluorescens, Bacillus subtilits, Vibrio aestuarianus

10 Bagasse from Proserpine(BG-P)

1,3,4,5,8, 17

Brevibacillus brevis, Corynebacterium sp., Pseudomonas fluorescens, Bacillus subtilits, Vibrio vulnificus, Vibrio aestuarianus

11 Mud sample from Maryborough (MS-M)

1,3,4,5, 11,17

Brevibacillus brevis, Corynebacterium sp., Pseudomonas fluorescens, Bacillus subtilits, Burkholderia cepacia, Vibrio aestuarianus

12 Decaying trash from cane farm Maryborough(DT-M)

1,3,4,5, 12,14,15,17

Brevibacillus brevis, Corynebacterium sp., Pseudomonas fluorescens, Bacillus subtilits, Bacillus cereus, Alcaligenes faecalis, Vibrio ichtyoenter, Vibrio aestuarianus

13 Bagasse from Maryborough (BG-M)

1,3,4,5, 13,17

Brevibacillus brevis, Corynebacterium sp., Pseudomonas fluorescens, Bacillus subtilits, Bacillus thuringiensis, Vibrio aestuarianus

14 Mud sample from Mackay (MS-MK)

1,3,5,7, 8,10,17

Brevibacillus brevis, Corynebacterium sp. Bacillus subtilits, Pseudomonas aeruginosa, Vibrio vulnificus, Roseomonas fauriae, Vibrio aestuarianus

15 46 caswells soils from Mackay (CS-MK)

1,3,5,8, 14,15,17

Brevibacillus brevis, Corynebacterium sp., Bacillus subtilits, Vibrio vulnificus, Alcaligenes faecalis, Vibrio ichtyoenter, Vibrio aestuarianus

16 46 Blair soil from Mackay (BS-MK)

1,4,5,12, 13,16

Brevibacillus brevis, Pseudomonas fluorescens, Bacillus subtilits, Bacillus cereus, Bacillus thuringiensis, β- proteobacterium,

17 58 Effluent pond from Mackay (EPS-MK)

1,4,5,8, 16,17

Brevibacillus brevis, Pseudomonas fluorescens, Bacillus subtilits, Vibrio vulnificus, β-proteobacterium sp., Vibrio aestuarianus

18 55 Tropic Isle Mackay (TIS-MK)

1,2,3 Brevibacillus brevis, Rhodospirillaceae sp., Corynebacterium sp.,


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Table 6.3: 16S rDNA sequencing result with closest matched Genus/species based on the

percentage (%) of similarity

Closest matched genus/species using

the Universal Primer 16S rDNA

Sequence similarity in

% (no. of bases)

Taxonomic group

Brevibacillus brevis 93% Proteobacteria

Uncultured Rhodospirillaceae sp., 95% Proteobacteria

Uncultured Corynebacterium sp 96% Actinobacteria

Pseudomonas fluorescens, 97% Proteobacteria

Bacillus subtilits 95% Firmicutes

Endophytic bacterium 70%

Pseudomonas aeruginosa 98% Proteobacteria

Vibrio vulnificus 93% Proteobacteria

Azospirillum brasilense, 95% Proteobacteria

Roseomonas fauriae 95% Proteobacteria

Burkholderia cepacia 97% Proteobacteria

Bacillus cereus 99% Firmicutes

Bacillus thuringiensis 99% Firmicutes

Alcaligenes faecalis 93% Proteobacteria

Vibrio ichtyoenter 92% Proteobacteria

β- proteobacterium 66% Proteobacteria

Vibrio aestuarianus 94% Proteobacteria

6.4 Discussion

Previous research has shown that PCR-DGGE provides detailed information about changes in and

diversity of microbial community structures in the environment, compared to plate count

methods (Li et al., 2006). The results of this study demonstrate that DGGE and 16S rDNA

sequencing used together provide insight into the bacterial community composition of solid and

liquid samples and the different genotypic patterns for each of the bacterial communities that

were observed by these means. To the best of our knowledge, very limited research on the

identification of the ecological diversity in hemicellulose-enriched sites has been conducted.


104

In this study, microbial DNA was analysed from solid (soil, bagasse, decaying trash) and liquid

(bagasse leachate, floor dump sump) sources by the DGGE method. The DGGE of PCR-amplified

16S rRNA gene fragments clearly demonstrated the microbial characteristics of environmental

(solid and liquid) samples from sugar mills in Queensland.

There was a couple of difficulties encountered in this phase of the research. Unfortunately only

one bagasse leachate sample was available, due to a drought at the time of the sampling. The

Mackay sample was sent later in the season, after rainfall events. Another drawback was the

difficulty in loading all samples onto the same gel and the resulting potential for gel-to-gel

variation, which influences DGGE analysis (Nunan et al., 2005). The results were also limited by

the use of Universal primers in the PCR.

Our main aim was to analyze microbial diversity in hemicellulose-enriched habitats such as

bagasse leachate. DGGE profiles of bacterial communities in six liquid waste samples, one

bagasse leachate, two bagasse stockpile samples and nine soil samples from Queensland sugar

mills were observed. Each sample was analyzed in duplicate with the same result. Many equally

intense bands, indicating the presence of a large number of equally abundant ribotypes, were

observed for all sample types.

The DGGE profiles of liquid samples revealed that the band patterns for cooling tower water

from Mackay (CTW-MK) and Proserpine mill (CTW-P) were found to be most similar to each

other, while bagasse stockpiled from the Proserpine mill (BG-P) had the least similarity with the

patterns of the other solid samples. From the MDS analysis, it could be demonstrated that the

sugar cane stored in the floor before crushing, does not contain much freely available

hemicellulose, which may be the reason why there were no significant differences between the

microbial populations found in the cooling tower water (CTW) and floor dump sump (FDS).

Alternatively, the cooing tower water is more ubiquitous than anticipated, and other sampling

sites may be been contaminated by the populations from the cooling tower. This is feasible, as

cooling towers generally produce a fine, but widespread spray of water for a considerable

distance across an industrial site. Thus, the microbial population of the cooling tower may have

been transported to other parts of the site.

Bagasse leachate is expected to have a high hemicellulosic composition compared to that of

stockpiled bagasse, due to the way that it is produced, by slow penetration of rainwater through

a bagasse pile, gradually accumulating soluble products, such that the end result is quite

concentrated. This may be the reason that the DGGE pattern for bagasse leachate (BGL) was

significantly different to those of the stockpiled bagasse, which was also significantly different to


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cooling tower and floor dump samples. Bagasse leachate from Mackay (BGL-MK) and bagasse

stockpiled from Maryborough mill (BG-M) had a 76% similarity in population, probably because

of the similar nutritional composition.

Factors other than hemi-cellulose concentration in the samples, that may potentially contribute

to the variation in microbial communities between samples, include: temperature (ambient cf

factory floor); moisture levels (ranging from dry to very moist) and the related factor of relative

humidity; oxygen availability (either natural or resulting from microbial activity); soil type (clay,

sandy, humous) of the region; and even, possibly, the time of day that sampling occurred (which

may have influenced several of the mentioned factors). An example of the type of habitat likely

to be encountered is freshly baled bagasse, which contains 50 % water and about 3 % sugar, and

heats rapidly after stacking (Lacey, I97I). The temperature remains above 40°C for few weeks

with a maximum of 50°C to 60°C, providing good growing conditions for thermophilic

actinomycetes. Unfortunately, none of these factors were recorded for this project, so it is not

possible to calculate their contribution to the variation between populations in various samples.

According to the phylogenetic tree analysis, the microbial population in bagasse leachate from

Mackay was the most divergent among all of the liquid samples. The floor dump sump from

Proserpine and Mackay sugar mills had the highest similarity (90%) between their microbial

populations probably due to the similarity of the nature of the samples. The floor dump sump

and cooling tower water from Maryborough had more than 80% similarity possibly because both

samples were collected from the same location (Maryborough sugar mill). The remainder of the

samples were highly diverse.

Bagasse leachate, only available from the Mackay mill, was quite different to other liquid

samples, and in fact showed more similarity with the soil samples from the Mackay region. This

indicated that the bacterial communities were similar on the basis of geographical location.

The alkaline-tolerant bacteria Alcaligenes faecalis was found in bagasse leachate and caswells

soils from Mackay mill (CS-MK). The reason may be peculiar to the area (Mackay), such as an

effect of soil chemistry or climate near that sugar mill. Also nitrogen fixing bacteria Azospirillum

brasilense was found in the FDS-Mackay sample. Nitrogen-fixing β-proteobacteria was also

found in Mackay sugar mill. The β-proteobacteria consist of several groups of aerobic or

facultative bacteria, which are often highly versatile in their degradation capacities and play a

role in nitrogen fixation in various types of plants, oxidizing ammonium to produce nitrite, an

important chemical for plant function.


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Since many endospore-forming species can effectively degrade a series of biopolymers such as

proteins, starch, pectin, cellulose, they are assumed to play a significant role in the biological

cycles of carbon and nitrogen. From soil, by direct contact or air-borne dust, endospores can

contaminate almost anything that is not maintained in a sterile environment. They may play a

biodegradative role in whatever they contaminate, and thereby they may be agents of

decomposition and decay. Several Bacillus species are especially important as food spoilage

organisms (Zavarzin, 2006). These abilities and roles are very relevant to the industrial

application that the current research was intended to explore.

All soil samples (MS-M, DT-P; DT-P, TIS-MK; MS-MK, CS-MK; MS-P, EPS-MK) among the solid

samples had more than 80% similarity, but this did not apply to the two bagasse stockpiled

samples. Bagasse stockpiled from Proserpine mill (BG-P) and Maryborough sugar mill (BG-M)

were highly divergent populations compared to the soil samples. The possible reason of this

finding may be the similar composition of nutritional elements present in microbial habitat. Also

microbial growth factors (aeration, pH, RH, temperature, carbon sources) may influence the

source, producing a divergent microbial population.

Corynebacterium spp. were isolated (chapter 3) previously from the soil samples of sugar mills.

Similarly, Corynebacterium spp. were found in this study in solid samples (mud, decaying trash,

and bagasse stockpiled) from Proserpine, Mackay and Maryborough regions, but not from any of

the liquid samples. Corynebacterium spp. that are capable of producing amino acids such as

glutamic acid, valine, isoleucine, threonine, aspartic acid and alanine (Hermann, 2003) were

found in most soil samples. This finding revealed that the presence of commercially valuable

Corynebacterium spp. in sugar industry-related solid samples is widespread.

Most of the microorganisms or groups of microorganisms found in the samples were those

commonly expected in soil and water samples. However, only the soil samples contained the

coryneform group that includes the isolates reported in Chapter 3, and the subject of the

research conducted. It is conjectured that the water samples that were subjected to DGGE

analysis had not undergone any enrichment process, and so would have been colonised mainly

by sucrose-utilizing organisms, that being the carbon source most commonly available in the

selected sites and samples.

The most pentose-rich samples were expected to be the bagasse and bagasse leachate, because

of the close association with sugar cane refuse, and these certainly had a different community

structure to the other samples. However, the bagasse leachate sample also did not contain

detectable levels of Corynebacterium spp. in the DGGE analysis. The samples used in the original,


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culture-based isolation procedure (Chapter 3) were also soil samples. So it must be concluded

that the target coryneform micro-organisms were simply not able to grow in water, at least in

the environments that were under investigation. It is known that Corynebacterium spp. may be

found in both water and soil (Mallory et al., 1977), just as it is also known that members of this

genus, some of which have now been reassigned to other genera (eg. Rhodococcus equii), are

able to cause plant and animal diseases as a result of contact with contaminated soil and water

(Takai et al., 1986).

It is not clear why the Corynebacterium genus was not present in the sampled waters, but clearly

present in the soil. One explanation may be that the drought that was affecting the area when

the samples were first taken, may have selected for soil coryneforms by virtue of the dryness of

the environment. The liquid samples, with the exception of bagasse leachate, would probably

have been originally source from treated water, before being pumped around the site, where

they became contaminated by indigenous microflora. The treatment of the water would have

negatively influenced the ability of the Corynebacterium spp. to grow.

There are some bacteria found in common to both solid and liquid samples. Phylogenetically,

the sequences were distributed into five groups: Bacillus spp, nitrogen fixing Proteobacterium,

Vibrio spp, Pseudomonas sp and Corynebacterium spp. The dominant bands of all of the samples

corresponded to the β-Proteobacterium group, while the sequences recovered from bagasse

leachate samples belonged to Pseudomonas spp. and coryneform groups. Based on the

sequences of the bands excised from each of the samples, there were approximately five to six

different characteristic bands present in each of the liquid and solid samples, the dominant

groups being Proteobacteria and nitrogen-fixing bacteria. It was also found that the presence of

Gram-negative bacteria and Gram-positive bacteria was equally distributed among samples.

The presence of Vibrio spp in these samples would once have been thought to be quite unusual

(Colwell et al., 1992) however current knowledge is that this genus may be found in soil and dust

and is often able to degrade chitin. In addition, this bacterium is known to have the ability to

degrade hemicellulose from the soil along with other genera found in the samples, such as

Bacillus spp., Pseudomonas spp., and Erwinia (My Agriculture Information Bank/Soil

Microbiology). It would be expected that samples from environments surrounding and within

sugar cane mills would include those genera capable of degrading such materials as: cellulose

(Pseudomonas, Cytophaya, Spirillum, Actinomycetes and Cellulomonas); Lignin (Pseudomonas,

Micrococcus, Flavobacterium, Zanthomonas and Streptomyces); and Pectin (Erwinia) (My

Agriculture Information Bank/Soil Microbiology).


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Brevibacillus brevis, Rhodospirillaceae bacterium, Bacillus sp, Vibrio sp and Pseudomonas were

the most wide-spread microorganisms, as they were found in all samples. These microbes are

decomposers, which have the ability to recycle nutrients. Microorganisms have a special role as

degraders in the biogeochemical cycles.

Such microorganisms, because of their ability to degrade a wide range of substrates, are often

used for in-situ microbial biodegradation or bioremediation of domestic, agricultural and

industrial wastes and subsurface pollution in soils, sediments and marine environments. The

ability of each microorganism to degrade toxic waste depends on the nature of the

contaminants. Since most sites typically have multiple pollutant types, the most effective

approach to microbial biodegradation is to use a mixture of bacterial species and strains, each

specific to the biodegradation of one or more types of contaminants. The composition of the

indigenous and added bacteria is carefully controlled, in order to evaluate the activity level and

to permit modifications of the nutrients and other conditions for optimizing the bioremediation

process (Zavarzin, 2006; Koukkou, 2011; Watanabe and Kasai, 2008; Okabe and Kamagata,

2010).

Pseudomonas species, present in many of the samples, are amongst the toughest, most non-

fastidious and denitrifying of organisms. They are used for bioremediation purposes to clean up

oil spills; they grow on plastic surfaces, in disinfectants, and other difficult sites. They are

indigenous in water and can use almost any carbon source available (Madigan and Martinko,

2005). So the presence of Pseudomonas species is quite common in environmental water and

soil samples, and in this context they are known to break down a wide range of plant material,

including cellulose, hemicelluloses, lignin and proteins (My Agriculture Information Bank/Soil

Microbiology).

Brevibacillus brevis, Rhodospirillaceae bacterium, Bacillus sp, Vibrio sp and Pseudomonas play an

important role in the microbial ecosystem in the sugar industry. Large amounts of protein-

producing Brevibacillus brevis (Yamada et al., 1981) were present in all of the samples including

soil and liquid. The photosynthetic bacterium Rhodospirillaceae spp. was present in all liquid

samples except bagasse leachate.

According to Lacey (I97I), a new species Thermoactinomyces sacchari has been isolated from

sugar cane bagasse. Their heat-resistant spores contained dipicolinic acid which causes

bagassosis. Bagassosis is a respiratory disease caused by inhaling dust from mouldy, self-heated,

crushed sugar cane (bagasse). T. sacchari was isolated from the surface of freshly harvested


109

sugar cane, and from muds from filter presses at the sugar mills, but was most abundant in

mouldy self-heated bagasse Other actinomycetes may also cause similar diseases. The

properties and structure of the spores of T. sacchari resemble spore-forming bacteria of the

genera Bacillus and Clostridium (Lacey, I97I). Regular microbial ecological analysis is needed to

monitor the risk of the health issues for people near sugar mill. It is possible that DGGE analysis

of the bagasse stockpiles would provide a rapid means of alerting the mill staff to dangerous

levels of such opportunistic pathogens.

It is apparent that the physical and nutritional characteristics of the microbial habitat have

impacted on the diversity of microbial communities supported. The identification of microbial

species capable of degrading hemicelluloses, has contributed to our research in support of the

aim of discovering species in this environment that have potential for industrial exploitation.

Although the DGGE analysis of the sugar mill samples did not clearly demonstrate the presence

of actinomycetes, DGGE analysis did reveal the presence of Corynebacterium spp. in particular.

Amongst the cultures isolated and characterized previously (Chapter 3), only some were found

to be present in sugar mill samples analysed by DGGE. Thus, some correlation between the

culture-based analysis of the sugar mill samples and DGGE profiles analysis was demonstrated in

this study. However, DGGE analysis provided a more detailed metagenomic picture than culture-

based methods had, and enabled the specific detection of potential pentose-utilizing microbes in

these samples.

6.5 Conclusions

Bacterial DGGE profiles generated using universal bacterial primers revealed the structural

composition of communities in liquid and solid samples. The most complex DGGE pattern

indicated the presence of a number of different bacterial taxa. DNA sequencing identification of

dominant members in DGGE profiles can aid in the selection of suitable isolation media and

conditions, since the phylogenetic positions of bacteria are often consistent with their

physiological properties and culture requirements (Throbäck et al., 2004).

Fingerprinting techniques such as DGGE provide separation of bacterial taxa based on 16S rRNA

banding patterns. In order to recognize the specific taxa that are shown as different bands, 16S

rDNA sequencing is also required. Bacterial 16S rDNA genes were readily detected and a variety

of microbial species from the sugar treatment waste were identified. While the results were

somewhat limited by the universality of the primers used in the PCR (Yu et al., 2008), the results

showed some interesting relationships. Brevibacillus brevis and Vibrio spp were found most

commonly in all of the samples. Rhodospirillaceae sp was found in all liquid samples except


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bagasse leachate. Rhodospirillaceae sp. was also found in DT-P and TIS-MK, different samples

from different locations. Alcaligenes faecalis was present in bagasse leachate and also in soils

from Mackay possible cause of the soil chemistry or climate of sugar mill. However, Burkholderia

cepacia was found as a minor microorganism in floor dump sump in Mackay and a mud sample

from Maryborough sugar mills, two quite different sites. It is important not to over-analyse

these minor taxonomic issues, as the population at this level of single genera may prove to be

ephemeral.

Most importantly, according to the DGGE profiles, Corynebacterium were found in the bagasse

stockpiled and soil samples of Proserpine, Mackay and Maryborough sugar mills. In Chapter 3,

Corynebacteria were reported as being isolated from Maryborough sugar mill’s soils. This

research discovered that Corynebacteria were found as a common bacterium in DGGE

fingerprint but only in soils, and were also found by traditional cultured methods. In addition,

bagasse leachate and bagasse stockpile microbial populations were quite different compared to

other samples. Brevibacillus brevis, Rhodospirillaceae bacterium, Bacillus spp, Vibrio spp and

Pseudomonas were present in all samples tested.

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Chapter 7

Taxonomic analysis of Pentose-rich Natural Environments

Using a High Density Oligonucleotide Microarray

(PhyloChip) Technology

7.0 Summary

The microbial diversity of liquid samples was analysed in samples taken from the three main

sugar mills at Proserpine, Maryborough and Mackay in Queensland, Australia. Of particular

interest was the bagasse leachate sample, as sugar cane hemicellulose is the second most

dominant fraction of bagasse hemicellulose (23-30%), and it is mostly composed of xylose. The

main focus of this study was to explore the microbial diversity in a hemicelluloses-enriched

environment using the PhyloChip microarray identification system. A very complex microbial

community was found in each sample with the most divergent microbial community being found

in the bagasse leachate sample. The phylum Proteobacteria was the most abundant microbial

group present in all samples.

7.1 Introduction

The relatively recent introduction of molecular techniques for the detection and quantification

of microorganisms has started to permit a greater understanding of microbial diversity and its

role in nature. The most powerful new approach for the exploration of microbial diversity from

complex environmental samples is based on the cloning and sequencing of 16S ribosomal RNA

encoding genes. According to previous knowledge of the structure of these genes, coupled with

recent developments in PCR, it is now possible to identify closely related microorganisms by first

amplifying the 16S rRNA gene directly from isolated colonies using universal primers directed at

conserved regions at both ends of the gene, and then sequencing the PCR product (O'Sullivan,

2000).

Recently, a new method has been described, termed Comparative Genome Sequencing (CGS),

which resequences genomes based on custom oligonucleotide and cDNA hybridization arrays

generated by maskless photolithography, eliminating the need for constructing multiple physical

photolithography masks (Albert et al., 2005). More recently, the development of molecular

techniques, such as microarrays/metagenomic /environmental sequencing (Sessitsch et al.,

Chapter 7 PhyloChip

112

2006) or the new phylo sequencing methods, have shown potential advantages for bacterial

community characterization(Huse et al., 2008), and thus can be considered a new promising

direction for bacterial diversity monitoring. Indeed, a recent study showed that a microarray

targeting broad bacterial diversity could reveal greater diversity than had previously been

observed by the cloning-sequencing method (Loy et al., 2005). However, the metagenomic

PhyloChips developed so far focus mainly on functional bacterial groups or on single taxonomic

groups. Few microarrays have been developed in order to explore the microbial diversity (

Sanguin et al., 2009; Palmer et al., 2010). Diversity of communities can be described in terms of

taxa richness and taxa evenness. Richness provides an indication of total taxa present in a

sample/community, whereas evenness provides a measure of how dominant taxa are within a

community.

For the study reported in this chapter were analysed microbial communities in liquid samples

from sugar mills using a PhyloChip microarray analysis method which demonstrated the

presence of a possible pentose-capable community in the most potentially pentose-rich sample

(bagasse leachate).


7.2.1 DNA extraction from environmental samples and 16S rRNA gene amplification

Samples were collected from three different sugar mills at Proserpine (P), Mackay (MK) and

Maryborough (M) which are located in Queensland, Australia. Samples were: Floor dump sump

(FDS); cooling tower wash (CTW); and bagasse leachate (BGL). Seven liquid samples (sample

codes FDS-P, CTW-P, FDS-MK, CTW-MK, FDS-M, CTW-M and BGL-MK) were analysed by the

PhyloChip method. DNA was extracted from all liquid samples including bagasse leachate using

an ultra clean water DNA isolation kit (MOBIO laboratory inc. USA) and following the

manufacturer’s instructions. Extracted DNA was quantified by spectrophotometry to measure

the absorbance ratio at A260:A280, in order to determine the purity of the DNA.

Bacterial 16S rRNA genes were PCR amplified using primers 27F 5'(AGAGTTTGATCCTGGCTCAG)3'

and 1492R 5'(GGTTACCTTGTTACGACTT)3'. PCR mixtures included primers at 0.3 µM each,

dNTP’s at 200 μM each, 1.2 U of Taq polymerase (Takara), 10 x reaction buffers, 10 ng of

template DNA and water to 25 μL. Eight individual PCR reactions were set up over a primer

annealing range of 48-58°C (reducing primer bias). After hot-start enzyme activation, PCR

thermocycling consisted of 35 cycles of denaturation at 95°C for 30 s, annealing for 30 s and with

an extension at 72°C for 90 s. A final elongation step was performed for 10 min at 72°C. PCR

Chapter 7 PhyloChip

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products from the separate 25 µL reactions were pooled, precipitated with isopropanol, washed

with 80% ethanol and resuspended in water to concentrate the PCR products for PhyloChip

analysis.

7.2.2 Microarray analysis of 16S rRNA genes

A high-density oligonucleotide microarray system (PhyloChip) was used to taxonomically identify

the 16S rRNA gene fragments from the liquid samples. The array system, built on the Affymetrix

GeneChip platform (supplied by Affymetrix CA, USA), has probes covering 8,741 prokaryotic 16S

rRNA OTU’s (Operational Taxonomic Unit) PhyloChip; (Brodie et al, 2006; Brodie et al., 2007 ).

For each sample, 500 ng of PCR product was mixed with a control oligonucleotide spike and

digested into 50-200 bp fragments with DNase I (Invitrogen) in One-Phor-All buffer (GE

HealthCare). The 3’ ends of the fragments were labelled with biotin using terminal

deoxynucleotidyl transferase (Promega) according to the GeneChip DNA labelling procedure

(Affymetrix, CA). The biotinylated mixture was denatured (99°C for 5 min) and then hybridised

to a PhyloChip microarray at 48°C and 60 rpm for 16 h. The hybridised array was washed and

stained (streptavidin-phycoerythrin) on an Affymetrix fluidics station according to protocols

described previously (Brodie et al., 2006 ).

7.2.3 Scoring taxa present

The raw PhyloChip array data (CEL data output files from the Affymetrix GeneChip Operating

System) were imported into PhyloTrac for analysis (chatz et al., 2010; PhyloTrac Environmental

Sample Analysis, 2011). Pixel images (fluorescence intensities in well defined grid) were resolved

as probe pairs (perfect match PM and mismatch MM), which are then grouped into probe sets

(OTUs). Each probe set contains an average of 24 probe-pairs per OTU and also contains a

central 17-mer not found in other OTUs. For each PM probe, a missmatched (MM) probe, with a

single nucleotide difference was present. For each probe set, the trimmed mean fluorescence

intensity (highest and lowest probe values removed before averaging) and normalized to

internal spike-in control intensities using a maximum likelihood method, then scaled to the

mean overall array and finally, log transformed. Taxa are considered present in a sample when

at least 90% of the probes in its probe set pass the following criteria: PM/MM ≥ 1.3 and PM ≥

130 x background noise(Desantis et al., 2007).

7.2.4 Classification of taxa

Based on probe sets found to be present on the array, PhyloTrac is immediately able to classify

bacterial taxa present in the samples, and also provide information on their taxonomic ranking

Chapter 7 PhyloChip

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(i.e. phylum; class; order; family; sub-family data) (Schatz et al., 2010). This information was

exported into Excel in which manual reassignment of a few ambiguously-classified taxa was

conducted (e.g. some Bradyrhizobiaceae were classified into the Bradyrhizobiales order and

other Bradyrhizobiaceae into the Rhizobiales). The final tree, linking OTU intensity data in each

sample to taxonomic rankings, was imported into the Primer 6 software package (PRIMER-E Ltd,

UK), whereby data sets could be analysed at Phylum level through to sub-family level.

7.2.5 Diversity of bacteria present and identification of dominant taxa

The total number (i.e. taxa richness) of bacteria OTU’s and families were calculated in PhyloTrac.

The diversity, sensu community evenness/‘classical diversity’, was measured using the Shannon–

Weiner (Shannon; H’) index in Primer 6.

At each taxonomic level, the Weaver index was measured as:

Where pi is the proportion of intensity fluorescence for an individual OTU (at a given taxonomic

level) relative to the sum of all the intensities detected in the sample.

When determining which taxa of bacteria are dominant in a system, the overall intensity data

from PhyloChip cannot be directly used past OTU (sub-family) level. Aggregation of thosedata to

higher taxonomic levels imposes bias as probe coverage for bacteria such as Proteobacteria are

much greater than those for ‘rare’ groups such as Phylum TM7. This can be overcome by using

the ‘top 50’ taxa (probe intensity scores) for each ‘sample type’ (treatment). The most abundant

taxa are thereby selected and effects of differing coverage of probes across taxonomic groups

are minimized. Therefore, for each ‘sample type’ (treatment) the top 50 probe intensity values

were ranked and the combined data merged into a single file containing the top 50 for all

‘sample type’ (treatment) (total of 191 OTU). These data were used to explore which taxa were

dominant in abundance across the treatments. Taxonomic aggregation of OTUs was performed

in Primer6 as described previously.

7.2.6 Determining effects of treatment on bacterial community structure

The effects of treatment type on bacterial community assemblage were first explored at an OTU

level using 2-way clustering in PhyloTrac. Clustering of samples was based on Euclidean

distances and presented as a heat map.

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In Primer6, individual data sheets were generated which contained PhyloChip OTU data of all

samples at each taxonomic level (i.e. data sheets at Phyla level, Order level etc), and the factors

‘sample type’ (treatment) and ‘location’ were assigned to the samples. For each data sheet, the

intensity values were log transformed and a resemblance matrix (similarity matrix) was

generated using the Bray-Curtis method. The influence of ‘sample type’ (treatment) and

‘location’ were then tested at each level of taxonomy using CAP analysis – canonical analysis of

principal components – with probability testing using permutation (999 repeats). Canonical

analysis of principle coordinates (CAP) using the software Primer 6.1 (http://www.primer-

e.com/). Data were log transformed prior to analysis and Euclidean distance was used to create

a similarity matrix comparing sample sites. Canonical analysis of principle were also carried out

as follows: relative taxon abundance was used as ‘species’ data, whereas liquid environmental

data were included in the analysis as ‘treatment’ variables. Correlations were considered

significant at a P<0.05 baseline and to be nearly significant at 0.05<P<0.10. Ordination methods

(nMDS, CAP) were then used to structure high-dimensional community composition data along

simple axes expressing overall compositional similarity and dissimilarity between sites.

Ordination via non-metric multidimensional scaling (nMDS) was used to the identify the effects

of ‘sample type’ (treatment) and ‘location’ detected following CAP analysis. Using PhyloChip

data aggregated to Class taxonomy, similarity between samples were calculated using the Bray-

Curtis method on Log-transformed intensity values. NMDS scaling was used to interpret the

distances in community composition (Bray-Curtis distances).

SIMPER analysis (similarity percentages / species contributions) was used to determine which

taxa were important in partitioning effects of sample treatment on bacterial community

composition (Clarke, 1993). All multivariate data analysis in the Primer6 software package

(PrimerE Ltd., UK) were conducted using routines described in (Clarke and Warwick, 2001).

7.3 Results

7.3.1 Richness and evenness of bacteria present

A DNA microarray (the G2 PhyloChip) was used as a tool to study the bacterial community

structure (Brodie, 2006). PhyloChip analysis revealed a high level of bacterial richness across all

samples as taxonomic groups. Richness of taxa was calculated based on scoring of PhyloChip

probe intensity data using PhyloTrac software package. Overall, 34 different Phyla were found to

be present (Table 7.1), which represents approximately half of those detectable by PhyloChip.

The total OTUs present was 1367 – approximately 16% of those covered on the array. The

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116

highest richness of taxa was in the cooling tower water from Maryborough, which contained

nearly twice the OTUs than other samples, including the comparable sample from Mackay sugar

mill.

Table 7.1: Richness of the bacterial taxa present in environmental samples from sugar-cane

processing sites.

Level BGL-

MK

FDS-MK CTW-M CTW-MK FDS-M CTW-P FDS-P All

Phylum 29 30 32 21 30 21 13 34

Class 54 54 60 38 54 42 25 67

Order 106 90 117 58 90 62 32 127

Family 188 149 211 88 149 89 44 236

Sub-family 215 174 251 98 174 97 49 287

OTU 850 502 1023 209 502 218 135 1367

The microarray analysis also describes evenness of taxa distribution within communities

according to Shannon’s diversity index. Shannon’s index provides information on community

evenness as opposed to species richness. The higher the diversity indicated the higher

Shannon’s Index (Table 7.2). PhyloChip consistently detected more taxa in each of the samples

confirming the highest level of phylum and class found in cooling tower water sample from

Proserpine sugar mill (CTW-P). In addition, the highest number of order and family were found in

bagasse leachate from Mackay. The floor dump sump from Proserpine sugar mill showed the

highest variety of sub-families according to Shannon’s index. The PhyloChip-based OTU richness

according to Table 7.2 was 7.04±0.12. The communities are not being dominated by a few taxa

and this evenness is balanced across the samples.

Table 7.2: Evenness (Shannon’s diversity index; H’) of bacterial communities present from

sugar-cane processing sites.

Level BGL-

MK

FDS-MK CTW-M CTW-MK FDS-M CTW-P FDS-P

Phylum 1.64 1.83 1.71 1.67 1.77 1.85 1.68

Class 2.77 2.83 2.86 2.85 2.86 2.94 2.85

Order 3.94 3.70 3.89 3.98 3.84 3.80 4.01

Family 4.73 4.57 4.66 4.73 4.67 4.66 4.76

Sub-family 4.84 4.68 4.78 4.85 4.78 4.77 4.89

OTU 7.12 6.92 7.08 7.15 7.05 6.95 6.98

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7.3.2 Identification of the dominant taxa

The top 60 PhyloChip probe intensity scores for each treatment were used to characterise the

dominant bacterial phyla in the samples. At a phylum level, the dominant bacteria presenting

Figure 7.1 were Firmicutes, Proteobacteria and Bacteroidetes.

However, the PhyloChip was able to detect a huge range of recessive phyla. Cyanobacteria,

Acidobacteria, TM7, Chlorobi, Natronoanaerobium, Spirochaetes and some unknown phyla were

the minor phyla, which had less than 50 PhyloChip intensity scores in all treatments.

Figure 7.1: Dominant bacterial phyla present. Samples collected from sugar-cane processing

sites, data based on combined top 50 probe intensity scores present in each sample.

BGL-MK

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Figure 7.2: Distribution of bacterial Classes present within the four dominant Phyla.

From Figure 7.2 it is apparent that α-proteobacteria, β-proteobacteria, γproteobacteria, ϵ-

proteobacteria were present, which belong to the phylum Proteobacteria. Clostridium,

Bacillus, Mollicutes and Catabacter were in the Firmicutes groups. The only member of the

phylum Chloroflexi to be detected was the class Anaerolineae. There were three classes in

the Bacteroidetes groups: Bacteroidetes, Sphingobacteria and Flavobacteria.

The microarray detected probe intensity scores of 600,000 as shown in Figure 7.2,

Clostridium and Bacillus, which were the most dominant class in the floor dump sump

samples from the Mackay (FDS-MK) sugar mill. Bacillus, Clostridium, and α- and γ--

Proteobacteria were the most represented classes in the cooling tower waters from

Maryborough (CTW-M), and Mackay (CTW-MK) and also bagasse leachate from Mackay

sugar mills (BGL-MK). The same classes were present as dominant in the floor dump sump in

Maryborough (FDS-M), with the exception of β-Proteobacteria.

BGL-MK

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The PhyloChip analysis revealed that Bacillus, Clostridium, and α-Proteobacteria were the

dominant classes in both the cooling tower water and the floor dump sump of the

Proserpine sugar mill. Exceptionally, there was some γ-proteobacteria found as a dominant

class in the floor dump sump from the Proserpine mill. The results presented in Figure 7.2

demonstrated that the most dominant phyla in all of the samples were Firmicutes and

Proteobacteria.

7.3.3 Determining effects of sample site on bacterial community structure

At the OTU level, the effects of the sampling sites were clearly distinguishable in terms of

community composition (Figure 7.3). For example, at this higher level of resolution the floor

dump sump in Maryborough had a distinctly different bacterial community from the other sites,

while the cooling tower water from Mackay mill exhibited high overall diversity at a taxonomic

level.

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Figure 7.3: Heat map / 2-way clustering of samples according to PhyloChip OTU’s. Clustering

based on Euclidean distance using complete linkage method.

The influence of treatment and location were then formally tested using CAP analysis. CAP

analysis was performed at all taxonomic levels and the summary effects data are presented in

Table 7.3. Since there was a single sample for bagasse leachate, CAP analysis was only

performed to explore differences between the floor dump sump and cooling tower water

treatments and across each of the three locations (Mackay, Maryborough and Prosperine).

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Table 7.3: Summary of CAP data showing the significance of sample types and location effects

on bacterial community composition

Taxa level P ( samples type )(treatment) P (location)

Phylum 0.196 0.795

Class 0.012 0.809

Order 0.087 0.861

Family 0.127 0.640

Sub-family 0.281 0.505

Highlighted cell is a highly significant effect

CAP analysis showed that at very low taxonomic level (sub-family, family) there were no main

treatment effects. The treatment effect means the effect of sample collection site could be

found. There was no significant difference of the diversity of taxa level on the basis of the variety

of the sample types (floor dump sump, cooling tower water and bagasse leachete). This is

surprising as, at this level, most families will be present across the samples. In the middle levels

(Class level) of the taxonomic heirarchy, the effects of sample type (but not location) were highly

significant. At the highest level (Phylum) this relationship is lost, probably as there are not

enough potential differences between Phyla for variations to be observed.

Accordingly, at the Class-level of taxonomy only, ordination of bacterial community structure by

non-metric multidimensional scaling (nMDS) was conducted.

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treatment

Floor dump sediment

Cooling tower

Bagasse

Maryborough

Maryborough

Mackey

Proserpine

ProserpineMaryborough

Mackey

2D Stress: 0.001

Mackay

Mackay

Mackay

Maryborough

Proserpine

Proserpine

Maryborough

treatment

Floor dump sediment

Cooling tower

Bagasse

Maryborough

Maryborough

Mackey

Proserpine

ProserpineMaryborough

Mackey

2D Stress: 0.001

Figure 7.4: nMDS ordination plot showing similarity in bacterial community structure (Class

level) between samples. Samples in close proximity have a more similar community composition.

The nMDS ordination demonstrated the effect (left to right) of treatments on bacterial

community structure (Figure 7.4). A change in taxa composition can be seen in samples moving

from cooling tower water, to floor dump sump, to bagasse leachate. Microbial diversity in

bagasse samples is more divergent due to different habitat composition.

Based on the finding of a highly significant treatment effect on the distribution of bacterial

Classes between cooling tower water and floor dump sump samples, SIMPER analysis was used

to determine which Classes contributed most strongly to the treatment effects. Of the 67

classes detected, variation in only about seven of these contributed to 20% of the total

‘treatment’ effect variation. The summary SIMPER data are given in Table 7.4.

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Table 7.4: Summary of SIMPER data. Table allocates differences of bacterial classes towards

describing the overall ‘treatment’ or ‘sampling site' effect between floor dump and cooling

tower samples on bacterial community composition.

Floor dump sump Cooling tower water

Classes Av. Abund Av .abund Contrib% Cum.%

NC10-1 8.81 10.19 4.94 4.94

Acidobacteria-4 10.28 10.93 3.32 8.26

Betaproteobacteria 14.62 15.38 3.05 11.31

Proteobacteria (UC) 11.55 12.01 2.62 13.93

Deinococcus-Thermus (UC) 11.53 12.20 2.40 16.33

Flavobacteria 13.73 14.34 2.27 18.60

TM7 (UC) 9.99 10.43 2.12 20.71

UC=Un-cultured class

Av.abund = average abundance

Contribut% = percent contribution of that Class to the “sample type” effect

Cum% = cumulative percentage of Classes

The data show that differences in abundance of bacterial Class NC10-1 are most important

(contributing to about 5%) in describing the overall differences in bacterial community

composition between the treatments, however the magnitude of even this effect was small

(only ~5%). Cumulative variation in the abundance of a number of different bacterial classes was

needed to describe the treatment effect more fully. Interestingly, these classes were from a

number of different Phyla.

NC10-1 is merely a candidate Class of the NC10 phyla (there are 2 classes NC10-1 and NC10-2).

None of these exists in pure culture. They are only known by DNA-based detection.

7.4 Discussion

From the earliest cultivation experiments to today's metagenomic analyses, most of the major

discoveries in this field were driven by applications of novel methods. Molecular ecology has had

a major impact by revealing the true scope of microbial diversity and providing genetic markers

that could be used to track important species, even in cases where cultures were unavailable

(Marco, 2010). A phylogenetic microarray that has been developed to used as an example of a

microarray that targets the known diversity within the 16S rDNA gene to determine microbial

community composition (Andersson et al., 2008). Using multiple, confirmatory probes to

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increase the confidence of detection and a mismatch probe for every perfect match probe to

minimize the effect of cross-hybridization by non-target regions.

Bacterial community analysis demonstrated the diversity of bacterial DNA in a hemicelluloses-

enriched environment. PhyloChip microarray data demonstrated a very complex bacterial

ecosystem (details discussed in next paragraph) present in the environment related to the

Queensland sugar industry, in particular the mills. Only seven liquid samples including bagasse

leachate were analysed by using the PhyloChip microarray method. Half of these samples were

identified by the DGGE and 16S rDNA sequencing method; and rest of these samples were

analysed by using PhyloChip microarray. PhyloChip mostly defines bacteria to the phylum, order

and sometimes class level. Bacterial species present in seven liquid samples, including bagasse

leachate, were described in chapter 6 (Table 6.3) as determined by 16S rDNA sequencing.

Acidobacteria, Betaproteobacteria, Deinococcus thermus and Flavobacteria were mostly found

in these selected samples.

According to the PhyloChip analysis, the Phyla Proteobacteria and Firmicutes were the most

dominant groups present in all samples. The Proteobacteria phylum includes a wide range of

pathogens, such as Escherichia coli, Salmonella sp., Vibrio sp., Helicobacter sp. etc. (Madigan

and Martinko, 2005). However, the majority of species in this Phylum are free-living, and include

a number of nitrogen fixing bacteria. According to the information from DGGE and 16S rDNA

sequencing, Vibrio sp. was common species in all liquid samples. Rhodospirillaceae sp. and

Azospirillum brasilense are also a part of the Proteobacteria that were found present in samples

by 16S rDNA sequence analyses.

Proteobacteria comprise one of the largest Phyla of prokaryotes and account for the vast

majority of the known (culturable) Gram-negative bacteria. This group of organisms

encompasses a very complex assemblage of phenotypic and physiological attributes including

many phototrophs, heterotrophs and chemolithotrophs. The Phylum Proteobacteria is of great

biological significance as it includes a large number of known human, animal and plant

pathogens.

The Phylum Firmicutes includes all of the Gram-positive bacteria, but has recently been

redefined to include a core group of related forms called the low-G+C group, in contrast to the

Actinobacteria (Haakensen et al., 2008). Many Firmicutes produce endospores, which are

resistant to desiccation and can survive extreme conditions, making them ideal for

environmental ecosystems such as soil and water. Members of the Firmicutes are known to be

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principally responsible the degradation of major polysaccharides forming acetate, formate, lactic

acid etc (Teusink and Smid, 2006). The presence of Firmicutes as a dominant group is quite rare

for natural samples. In the sugar mill environment, the dominance of Firmicutes may be linked

to the presence of ‘lactic acid’ type bacterial communities. Lactobacilli commonly share the

habitat when the content of sugar level is high in that habitat (Kleerebezem and Vaughan, 2009).

It has been mentioned earlier that bagasse leachate contains very high levels of hemi-cellulose.

According to Kleerebezem and Vaughan (2009), lactic acid bacteria are beneficial Firmicutes in

the intestinal tract, which produce lactic acid as an end-product of carbohydrate fermentation.

This ability has been exploited in food production owing to the growth-inhibiting effect that

acidification has on spoilage agents. Since the lactic acid bacteria are generally regarded as safe

(GRAS) for specifically defined uses and they often produce narrow spectrum antibacterial

peptides active against pathogenic bacteria, they have also been used for health-promoting

purposes such as probiotics (Teusink et al, 1998; Teusink and Smid, 2006). Thus the presence of

high levels of Firmicutes in sugar mill waste samples may have significant implications in the

nutriceuticals industry.

Firmicutes occupy a wide variety of habitats, and can be either useful or problematic in various

food and beverage related industries (Sakamoto and Konings, 2003), in the fuel alcohol industry

(Skinner and Leathers, 2004), and in human and animal health (Carr et al., 2002). It is believed

that numerous industrial applications of Firmicutes such as lactic acid production, remain to be

exploited (Teusink et al., 1998; Teusink and Smid, 2006). One prominent Firmicute, Bacillus spp.,

was found in all samples as a very common bacterium in accord with the results from Chapter 6.

Burkholderia cepacia is a member of the sub-phylum β-proteobacteria and was found in the

floor dump sump of Mackay mill (FDS-MK). Alcaligenes faecalis, also a member of same phylum,

was found in bagasse leachate only. However, species belonging to the phylum, Acidobacteria,

such as Deinococcus thermus and Flavobacteria were not found by 16S rDNA sequencing. This

might be due to experimental error either with DGGE or 16S rDNA sequencing (chapter 6) or

simply that these were present in numbers too low to detect. So this finding reveals that, the

PhyloChip analysis is able to explore wider microbial diversities compared to DGGE methods.

In this study, the Phyla Proteobacteria and Firmicutes were present as the most dominant

groups in bagasse. These include the sub-groups α-proteobacteria, β-proteobacteria, Clostridium

and Bacillius. Interestingly, Firmicutes are numerically low dominant groups in bagasse leachate

sample compared to other samples.This is an interesting finding. The bagasse leachate sample is

the most different in terms of community composition. The subsequent analysis could only look

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for changes between the floor dump sump (FDS) and cooling tower water (CTW) samples which,

on the nMDS are a little bit different but not nearly as much as the bagasse leachate. This may

be because of the composition of nutrients in the habitat. Alcaligenes faecalis was found only in

bagasse leachate. This information revealed that baggasse leachate might be enriched in carbon

and nitrogen sources (hemicellulose).

Lignocellulosic materials, such as sugar cane bagasse represent an abundant, inexpensive source

of organic material that can be a carbon source for microbial growth. Sugarcane bagasse

leachate is residual liquid in nature, created by rainwater passing through the bagasse stockpile

and contains dissolved lignocelluloses. Sugar cane bagasse wastes are an additional source of

microbial nutrients (nitrogen and phosphate source). The micro flora may have the ability to

grow in lignocellulose type substrates. The spent compost/bagasse mix, besides being an

important source of nitrogen and phosphate nutrients, also provides an appropriate support for

the solid matrix as well as native microorganisms that are capable of pentose-utilization.

The class level of taxonomy was highly significant according to the analysis of sample type. The

nature of the floor dump sump (FDS) and cooling tower water (CTW) were different. Basically

microorganism found in the floor dump sump is most likely to be composed of soil bacteria and

that of cooling tower water is most likely composed of airborne bacteria. This may be the

possible reason why there is a high significance of microbial diversity at the class level in these

two types of samples. It was also demonstrated by MDS analysis (Figure 7.4), that the bagasse

leachate from Mackay mill was the most different but it was not possible to compare the nature

of this, because only one sample was available, and from just one location.

Cooling tower water from Maryborough contained the highest richness of taxa according to the

richness analysis. Microorganisms enter cooling towers through the water supply. The constant

fall of water within cooling towers make an air scrubber and which delivers large amounts of

organic, inorganic particulates and microorganisms into the water phase. The combination

increases the water temperatures, humidity and large surface areas in cooling towers to provide

an ideal environment for microbial growth.

7.5 Conclusions

All of the samples studied by the PhyloChip microarray system were highly rich in taxa, which

included not only the numerically dominant groups, but also rarer taxa, indicative of a very

complex bacterial ecosystem. The bagasse leachate sample was the most different in terms of

community composition.

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The richness analysis represents that the cooling tower water from Maryborough contained the

highest richness of taxa compared to other samples, which was unexpected. According to the

evenness analysis (Shannon’s Index), the highest level of phylum and class were found in cooling

tower water from Proserpine (CTW-P) and the highest number of order and family were found in

bagasse leachate from Mackay (BGL-MK). In addition, the highest variety of sub-families was

found in the floor dump sump of Proserpine mill. Firmicutes, Proteobacteria and Bacteroidetes

were present as a dominant phylum in all samples according to the analysis of the identification

of the dominant taxa (Figure 7.1). Moreover, CAP analysis found no significance difference of the

diversity of taxa level on the basis of variety of the sampling location. At the class level of

taxonomy, the effects of sample type (but not location) were highly significant (P=0.12).

The PhyloChip is able to simultaneously identify many thousands of taxa present in an

environmental sample. The PhyloChip is shown to reveal greater diversity within a community

than rRNA gene sequencing due to the placement of the entire gene product on the microarray

compared with the analysis of up to thousands of individual molecules by traditional sequencing

methods (Liu and Jansson, 2010).

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Chapter 8

Summary, conclusion and future work

8.1 Revisiting the hypothesis and aims

The research presented in this thesis was conducted with the aim of investigation of the

hypothesis which was: “That pentose-utilizing organisms may be isolated from pentose-rich

natural environments and consequently be used to ferment pentose sugars such as those

found in hemicellulose from agricultural waste”. It was further hypothesized that the pentose

degradation process would result in commercially valuable end-products such as amino acids.

This hypothesis was investigated by addressing three major aims. The first aim of this research

was to isolate, identify and characterize Gram-positive microbes which were able to degrade

pentose sugars as a carbon source in the culture medium.

The second aim of this research was to detect and identify amino acids as a major end-product

from single pentose cultivation and dual sugar (pentose plus glucose) cultivation of the E-PUB

isolates obtained. The diauxie characteristics and specific growth rates from single and dual

carbon sources in the growth medium were also investigated.

The final aim was to investigate the diversity of microbial populations in pentose-enriched

habitats, using metagenomic methods such as DGGE and PhyloChip microarrays. The dominant

microbial species were identified using 16S rDNA sequencing methods.

8.1.1 Hypothesis

The hypothesis was proved. Six Gram-positive microbes, which belong to the Order

Actinomycetales, were isolated from pentose-rich agricultural waste material. They were able to

utilize pentose sugars at approximately the same rate and efficiency as they utilize glucose. The

extension of the hypothesis was also proved: pentose-utilizing microbes were able to produce

commercially valuable amino acids, in this case glycine.

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8.2 Summary of findings

Pentose-degrading microbes were isolated from the pentose-enriched environment. Six

indigenous Gram-positive microbes were isolated, and were found to belong to the order

Actinomycetales but were of various genera and species. These microbes were isolated from the

soil of sugar treatment ponds from the Proserpine and Maryborough sugar mills. The six

isolated microbes were screened from 191 isolates on the basis of their physiological and

biochemical characteristics. Finally these six indigenous bacteria were identified to the species

level, using 16S rDNA sequencing analysis.

It was confirmed that the isolated microbes were Corynebacterium glutamicum,

Corynebacterium freiburgense, Actinomyces odontolyticus, Rhodococcus equi, Nocardia elegans,

and Propionibacterium freudenreichii. These are of interest as they are uncommon, but

important species in the pentose-enriched environment, as shown by ecological metagenomic

studies.

It was also investigated whether the isolated microbes were able to grow with pentose sugars as

a carbon source in a minimal culture medium, to simulate the growth conditions in their native

habitat. It was proven that these natural isolates were able to use pentose as a carbon source

during growth.

The focus of further study was on the simulated utilization of lignocellulosic biomass through

cultivation. Of the three major components of such biomass, cellulose has almost all carbon in

the form of glucose, whereas hemicellulose also has some pentose. The medium composition

was created in order to simulate the sugar content of “natural” sugarcane bagasse, which

consists of 25.2% xylose and 41.0% glucose, expressed as % w/w of the dry matter (Pandey et

al., 2000).

Consequently, the pentose sugars (e.g., xylose, arabinose, and ribose) nearly always constitute a

much smaller proportion of lignocellulosic biomass than do hexoses. Moreover, microorganisms

generally prefer to metabolise hexoses over pentoses. However, our findings show that the

isolates C. glutamicum, C. freiburgense, A. odontolyticus, R. equi, N.elegans, P. freudenreichii

were able to metabolise pentose approximately same efficiency rate as they did glucoseutilizing

pentose sugars (xylose, arabinose or ribose) as a single sole carbon source during growth

without any genetic modification. All environmental pentose-utilizing bacteria (E-PUB) were able

to metabolise xylose efficiently, as shown by the specific growth rate, which was approximately

same for pentose sugars as for glucose metabolism.

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E-PUB microorganisms were grown on pentoses or hexoses as single carbon and energy sources.

Growth with glucose resulted in a slightly higher specific growth rate than that for xylose or

arabinose.

Dual sugar utilization was also tested. It was proven that all E-PUB microorganisms were able to

show diauxie characteristics during growth on dual sugar combinations (glucose plus

xylose/arabinose/ribose). Diauxie growth with similar growth rate was observed when glucose

was mixed with either xylose or arabinose or ribose and the glucose was consumed first. The

beginning of consumption of the second substrate generally followed a lag phase that was

longer than the lag phase for the first substrate, after which consumption of the two sugars

proceeded simultaneously. Our research suggests that mixtures of hexoses and pentoses, such

as those present in hemicellulose-hydrolysates, can be broken down by the natural E-PUB

microorganisms, thus proving that they are good candidates for the biodegradation of

hemicellulose-hydrolysates. Further research into improving pentose consumption is indicated,

as well as extending the complexity of the carbon source mixture to one approaching that found

in hemicellulose-hydrolysates.

Following the tests that demonstrated the ability of natural isolates to use pentose sugars in the

presence and absence of glucose, it was investigated the end-products of such metabolism. The

amino acid end-products were detected and analysed using High Performance Liquid

Chromatography (HPLC). It was shown that all six isolated microbes were able to produce

arginine and cysteine after growth on xylose, except for N. elegans which did not produce any

cysteine. C. glutamicum and P. freudenreichii produced glycine after single pentose metabolism

under oxygen deprivation conditions. P. freudenreichii also produced alanine after a single sugar

was consumed. An anoxic condition following an aerobic culture period allows the metabolism

of the substrate with the resulting production of industrially valuable amino acids. All six

isolates produced glycine after dual (xylose and glucose) sugar catabolism. P. freudenreichii was

able to degrade arabinose and also produce glycine after dual sugar (arabinose plus glucose)

utilization. Glycine has considerable importance in pharmaceutical applications. Arginine and

cysteine both have importance in food and pharmaceutical industries.

The microbial biosynthesis pathway of glycine, cysteine, arginine and alanine (Stanier et al.,

1977) shows that glycine, and alanine are amino acids of the serine and pyruvate family. The

formation of these amino acids is carried out via the pentose phosphate pathway. Thus, finding

this group of amino acids as end-products in the fermentative process is not unexpected,

particularly using the pentose phosphate pathway for the metabolism of pentose sugars. The

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relationship between the various amino acids and the final product glycine also indicates a

shared biosynthetic pathway.

An ecological study was performed using Denaturing Gradient Gel Electrophoresis (DGGE), and

16S rDNA sequencing methods. This provided further insight into the bacterial community

composition of the solid and liquid samples from the sugar mills, and the similarities and

differences of the genotypic patterns for each of the bacterial communities. The objective of this

study was to evaluate the species diversity contained in a complex habitat. These metagenomic

methods are useful to investigate poorly described, biochemically deficient, or fastidious

organisms. The results of sequencing are more accurate due to the database of phylogenetic

relationships available (Mignard and Flandrois, 2006).

The Phylum Proteobacteria was the most common microbial phylum found in this experiment.

The Actinomycetes group was not dominant in the eco-niches tested using DGGE, despite their

culturability in early experiments. It would appear that the more abundant groups of micro-

organisms in both soil and water samples did not respond to the culture conditions provided,

either because of sub-lethal damage due to drought conditions, or because the culture

conditions did not suit their requirements. Thus, even though the six E-PUB microorganisms

belonged to the family Actinomycetes, this was not a dominant microbial group in the sites from

which these samples were selected. However, Corynebacterium sp., which is related or similar to

the six E-PUB isolates, was also detected in mud and raw bagasse samples. These six E-PUB

microorganisms were the end result of screening 191 microorganisms found in sugar mill

environmental sources (pond soil). Most of the species of Corynebacterium, Nocardia and

Rhodococcus are widely distributed in the environment, but particularly abundant in soil (Holt,

2000).

The significance of the relative rarity of the E-PUB species is that, in order to assess their

capacity in raw material (in particular, bagasse), the raw material will need to be seeded with

the chosen organisms for use in a commercial fermentation process. Due to the relatively small

population of these organisms, a natural seeding process would not be efficient enough to

permit the industrial processing of bagasse. The diversity of microbial communities was also

investigated using High Density Oligonucleotide Microarray (PhyloChip) Technology. The

information about the size of the microbial diversity in liquid samples from the sugar mills was

significant. Acidobacteria, Firmicutes, Beta-Proteobacteria, Deinococcus thermus and

Flavobacteria groups were found in most of the selected samples.

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Microorganisms belonging to the actinomycetes group were not found by PhyloChip assay. This

could be due to the relatively low abundance of the actinomycetes group in the samples tested

as this was also demonstrated to be the case using DGGE analysis. It also revealed that the

microbial diversity depends on the nutritional composition of the natural habitat.

Corynebacterium spp were commonly found in culture based identification, DGGE and PhyloChip

method from sugar mills due to the similarity of habitat. The organisms found in the bagasse

leachate, the most likely pentose-rich sample tested, were significantly different to those of the

floor dump sump and the cooling tower water. However, very common environmental and

highly rich taxa were demonstrated by using this microarray system.

8.3 Significance of findings

This project has made significant contributions to the recycling of agricultural waste material, by

examining its usage as a substrate for industrial fermentation processes, particularly with

respect to the fraction of hemicellulose-, and the pentose sugars, which are abundant in this

source.

Six indigenous bacteria were isolated and identified from the environment, and were able to use

pentose sugars without any genetic modification. They were able to utilize pentose in the

presence of glucose, as would be found in their native environment, and also in its absence. The

efficiencies of the utilization of pentose (xylose, arabinose, and ribose) and glucose were about

equal. Most importantly, the fermentative process resulted in a valuable commercial product,

namely the amino acid glycine. Quantitative analysis also has completed, there was high

concentrationof amino acids produced by E-PUB.

Furthermore, the ecology of the micro-community present in environmental samples from

pentose-rich habitats was investigated using metagenomic methods, and it was established that

they were very complex. The indigenous pentose-utilizing bacteria that were isolated (E-PUB)

were not dominant in the eco-systems tested, with the exception of Corynebacterium sp, which

has implications for the industrial outcomes of this research.

To conclude, the E-PUB isolated in this research were able to utilize pentose naturally. While it

has been found previously that many microorganisms can utilize pentose after genetic

modification, this is the first report of organisms of the Corynebacterium group that are able to

do this without genetic manipulation. While genetically modified organisms can have many

advantages in industrial processes, one major disadvantage is that they may back-mutate to

form a wild type organism during the rather long fermentation period required for this particular

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process (Anderson and Moselio, 2009). Thus, the use of natural, non-mutated organisms is a

great advantage.

8.4 Future directions

Industrial fermentation will be the main outcome of this research. Future work may focus on

determining the relative size of populations of these different bacteria in order to understand

the possibility of a dynamic relationship, illustrated by their presence in leachate and bulk

material and their presence and numbers at specific stages of the degradation process.

To achieve the highest growth rate on pentose-containing feed-stock, and higher product yield,

extensive trials will need to be undertaken. These will determine the impact of changes of

temperature, pH, nutritional composition and incubation period on biomass formation and feed-

stock degradation. In addition, enzymatic analysis should be undertaken to understand the

activity of enzymes responsible for the degradation of pentoses and examine the possibility of

up-regulating them. Finally, quantitative analysis of substrate sugars consumed and end product

analysis also will be a part of the future work.

To maximise the use of biomass, one to ten percent inoculum of microbial cells is generally used

as a starter, to begin the initial aerated step. The optimum growth conditions for C. glutamicum,

N. elegans, P. freudenreichii are: temperature of 30°C; pH 6, in the presence of oxygen (Haynes

and Britz, 1990; Zhao et al., 2011; Lemee et al., 1994). Actinomyes odontolyticus is a newly

identified bacterium. The optimal growth conditions of this bacterium are: temperature range

35-37°C;pH 6-7; and facultative anaerobic condition (Ramos et al., 1997). The growth conditions

need to be optimized for the industrial fermentation using E-PUB. Such conditions as pH;

availability of suitable levels of nutrients such as nitrogen, phosphorus and trace elements;

optimum temperature range, oxygen availability during growth and depletion during

fermentation all must be optimized. In particular, the pH should be at the optimum level during

growth, but during end-product production the pH may be reduced (e.g. citric acid production

from Aspergillus niger; (Haq et al., 2003; Berovic et al., 2007; Sikander et al., 2002). It was not

possible to complete the optimization of the many growth and fermentation variables, due to

time constraints, however it is obvious that this is an important future research objective.

Future experiments should include determination of the efficiency of utilization of different

carbon sources in complex sources such as molasses and other agricultural by-products. For

example Brevibacterium sp. utilises different carbon sources (glucose, fructose, sucrose,

maltose, lactose, xylose and starch) for its growth and for the production of glutamic acid. It is

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possible that our E-PUB organisms may be capable of utilizing a wider range of carbon sources,

which would permit a wider application of the intended industrial process.

Bagasse leachate can be used as a substrate, however before fermentation starts, the bagasse

may need to be treated to destroy the unwanted wild microorganisms present, although ideally

the E-PUB organisms will function effectively in a “natural” substrate. If using heat to treat the

bagasse leachate, the sugars present will be polymerized, and the carbon could be rendered

unsuitable for use by microorganisms. Steam fractionation could be an alternative. Timing is a

main issue for steam fractionation. Steam fractionation of bagasse leachate could be an

expensive process for the scaling up of end-product formation. According to Sasaki et al. (2003),

bagasse samples were extracted as a water-soluble or steam fraction at low temperatures (200–

230°C), and about 30% was extracted at higher temperatures (230–280°C). At 200–230°C,

hydrolysates of hemicellulose (galactose, arabinose and xylose) and aromatic compounds mainly

existed in the extract solution. At this stage, hardly any glucose and cellobiose, which are

normally formed via hydrolysis of cellulose, were yielded and few aromatic compounds were

formed.

Another step would be the measurement of cfu/mL during biomass production. Industrial

fermentation uses fed-batch cultivation of microbes or other single cells, occurring firstly with

and then without, the presence of air. The aeration is performed by stirring the culture mix, or

bubbling air through it, but often using both methods simultaneously. The levels of stirring and

bubbling would need to be optimized for each process. Fed-batch fermentation is an industrial

fermentation technique in between batch and continuous fermentation (Hong, 1986; Stanbury

et al., 1993). A controlled feed rate, with the right component constitution is required during the

process. Fed-batch offers many advantages over batch and continuous cultures. From the

concept of its implementation it can be easily concluded that under controlled conditions and

with the required knowledge of the microorganism involved in the fermentation, the feed of the

required components for growth and/or other substrates required for the production of the

product can never be depleted and the nutritional environment can be maintained

approximately constant during the course of the batch. Sometimes, controlling the substrate is

also important due to catabolite repression. Since this method usually permits the extension of

the operating time, high cell concentrations can be achieved and thereby, improved productivity

(mass of product/volume x time). This aspect is greatly favored in the production of growth-

associated products (Stanbury et al., 1993).

Furthermore, in a fed-batch fermentation, no specialized equipment is required in addition to

that required for batch fermentation, even considering the operating procedures for sterilization

Chapter 8 Summary

135

and the preventing of contamination (Longobardi, 1994). A cyclic fed-batch culture has an

additional advantage: the productive phase of a process may be extended under controlled

conditions. The controlled periodic shifts in growth rate provide an opportunity to optimize

product synthesis, particularly if the product of interest is a secondary metabolite whose

maximum production takes place during the deceleration in growth (Stanbury et al., 1993).

Following the creation of biomass, the process is changed to an anoxic state by stopping the

bubbler to allow microbes to produce fermentation products. The shaking should continue, to

prevent the biomass from settling to the floor of the vessel, which is known as a precipitation.

The process is not unlike that of beer production, in which, following aerobic biomass

production, the yeast is stirred slightly in order to remain fully distributed through the beer

during the anaerobic fermentation step (McPhee, 2003).

Intracellular amino acids were analyzed in this research. As discussed above, different carbon

sources as growth supplements were used so that the possibility of different end-products could

be explored. Examples of bacteria that have proved useful in this context previously include:

Nocardia sp that have industrial importance for the production of antibiotics (Aggarwal et al.,

2011; Chiba et al., 2007); P. freudenreichii, which is important to produce acetic acid and

propionic acid (Lemee et al., 1994); and Corynebacterium glutamicum that is widely used for the

industrial production of amino acids and nucleotides (Haynes and Britz, 1990). Intracellular end-

products were extracted in this study though microorganisms are able to produce both

intracellular and extracellular products. Intracellular end-product analysis could be a significant

contribution in future research as Nocardia, Corynebacterium and Propionibacterium are known

to be able to produce intracellular amino acids (Wittmann et al., 2004; Limpisathian, 2005). C.

glutamicum, Propionibacterium sp are also able to produce extracellular amino acids (Wittmann

et al., 2004; Limpisathian, 2005). In addition, Actinomyces spp. produce cysteine as an

intracellular and valine as an extracellular by products (Eriquez and Pisano, 1979; Schaal et al.,

2006).

In the future, it will be possible to focus on the production of other organic acid and amino acid

end-products after the fermentation of complex carbon sources found in agricultural waste

materials. A diagram of the entire project, including both the completed work and future

directions is shown in Figure 8.1.

Chapter 8 Summary

136

Figure 8.1: Project outlook

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