View
390
Download
0
Tags:
Embed Size (px)
DESCRIPTION
This presentation will discuss the spread of antibiotic and resistance determinants from human waste streams into natural environments, and the likely consequences for microbial evolution.
Citation preview
Xenobiotics and Xenogenetics: Evolutionary consequences of
antibiotic use
Michael Gillings
Department of Biological Sciences and Genes to Geoscience Research Centre, Macquarie University
Humans are the world’s greatest evolutionary force
Humans are having measurable and dramatic effects on
• Atmosphere
• Hydrosphere
• Biosphere
1. Sequestration of a large proportion of primary production
2. Extinction of a wide range of taxa
3. Pollution with bioactive compounds
4. Accelerating evolutionary change by selection
Palumbi 2001 Science 293: 1786-1790
It is clear that we have precipitated evolutionary changes by both artificial and natural selection, but are we also changing the basal rates at which
evolution can occur?
Antibiotic ResistanceIs arguably the outstanding example of evolution by natural selection
Mutation and lateral transfer of genes between cells and species drives this phenomenon
Selection in the human Microbiome
Antibiotics select for mutations and lateral transfer events that confer resistance. Large quantities of antibiotic are excreted unchanged.
Humans create environmental hotspots for bacterial evolution
Waste streams release resistance determinants and their DNA vectors simultaneously with disinfectants, antibiotics and heavy metals. This creates a hotspot for complex interactions between DNA elements in an environment
containing sub-inhibitory concentrations of diverse selective agents.
Schluter et al. 2007 FEMS Microbiol. Rev. 31: 449-477; Taylor et al. 2011 Trends. Ecol. Evol. 26: 278-284 Gillings 2013 Frontiers in Microbiology 4: 4.
Selection drives fixation of complex DNA elements
Tn402
intI1
gene cassettes
mer operon
transposon backbone
Tn21
IS1326
IS1353
Tn9-like
Plasmid NR1
Tn10
sul
tetA,R
catA1
Gillings and Stokes 2012 Trends in Ecology and Evolution 27: 346-352.
Continued selection has assembled complex mosaic elements
For example, plasmid NR1 contains DNA from as many as twelve different origins.
Such molecules are xenogenetic, in the sense that they arise through human activity.
Unintended effects of antibiotic useThere is good reason to suspect that the use of antibiotics is having effects beyond their intended role as therapeutic agents
• They affect non-target organisms in the human microbiome• They are excreted unchanged, to affect environmental organisms• They promote the fixation of complex, multi-resistance elements• They have effects at sub-inhibitory concentrations
Effects on basal rates of evolutionAll mechanisms that generate diversity are under stabilizing selection; This balances the costs of maintaining genomic integrity against the
potential benefits of genomic innovation
Rate at which diversity is generated (by mutation, lateral transfer or recombination)
Too much diversity; loss of genomic integrity
Too little diversity; high cost of
maintenance
Num
ber
of c
ells
in p
opul
atio
n
Gillings and Stokes 2012 Trends in Ecology and Evolution 27: 346-352.
Antibiotics induce the SOS responseExposure to antibiotics, even at sub-inhibitory concentrations, induces the
SOS response, causing transient increases in the rates of mutation, recombination and lateral gene transfer
Rate at which diversity is generated
Num
ber
of c
ells
in p
opul
atio
n
Transient increase in the overall rate at which diversity is
generated
Mutation rates: Kohanski et al. 2010 Mol Cell 37: 311-320; Thi et al. 2011 Antimicrob Ag Chemo 66: 531-538 Recombination: Lopez & Blazquez 2009 Antimicrob Ag Chemo 53: 3411; Guerin et al. 2009 Science 324: 1034 Lateral transfer: Beaber et al. 2004 Nature 427: 72-74; Prudhomme et al. 2006 Science 313: 89-92
And select for evolvabilityContinual exposure to sub-inhibitory levels antibiotics is likely to select for cell lineages with inherently higher rates of mutation, recombination and
lateral gene transfer
Rate at which diversity is generated
Num
ber
of c
ells
in p
opul
atio
n
Mutation rates: Desai and Fisher 2011 Genetics 188: 977-1014; Gentile et al. 2011 Biol. Lett. 7: 422-424 Recombination: Cambray et al. 2011 Mobile DNA 2: 6; Boucher et al. 2011 mBio 2: e00335-e410 Lateral transfer: Heuer et al. 2010 FEMS Microbiol Ecol 73: 190-196; Palmer & Gilmore 2010 mBio 1: e00227
Directional selection that favors lineages with inherently higher rates
Key Research Questions
Gillings and Stokes 2012 Trends Ecol. Evol. 27: 346-352
in vitro experimentsTest with two genome sequenced isolates:
Ps. aeruginosa PA14 and Ps. fluorescens Pf5
Inoculate triplicate flasks
Control Antibiotic 1 Antibiotic 2 Antibiotic 3
etc
Serial passage
Genome sequence 3 x single colony isolates from each experimental line: 3 isolates x 3 replicates x 6 treatments x 2 species = 108 genomes
Compare with reference genome to score point mutations, transpositions, recombination events and indels.
Soil mesocosm experiments
Inoculate triplicate
mesocosms
Control Antibiotic 1 Antibiotic 2 Antibiotic 3
etc
Genome sequence 3 x single colony isolates from each experimental line: 3 isolates x 3 replicates x 6 treatments x 2 species = 108 genomes
Compare with reference genome to score point mutations, transpositions, recombination events and indels.
To determine if sub-clinical levels of antibiotic pollution increase rates of interspecies lateral gene transfer, reference strains will be
inoculated into soil mesocosms
Field experiments
Genome sequence 3 x single colony isolates of soil pseudomonads from each experimental line: 3 isolates x 3 replicates x 4 treatments x
2 species = 72 genomesCompare genomes to score point mutations, transpositions,
recombination events and indels
We have access to a long term field trial (Ontario, Canada) where antibiotics have been applied each spring since 1999.
Triplicate plots
Control, low, medium, and high treatments
Topp et al 2013 J. Env. Qual. 42:173-178.
Linking genomic data with eco-evo questions
• Sequencing >290 x 6-7Mb genomes – platform?• Storage of sequencing data• Assembly and closure of high quality genomes• High throughput pipeline for analysis of mutations• Confirmation of mutational events• Comparison of rates and statistical testing• Calculation of effects on baseline rates• Potential effects on molecular clock
Transforming data to knowledge:
Global Microbiome
Pangenome Panproteome
Parvome
Resistome
Mobilome
A conceptual map of the microbial world
Clinically important resistance genes are a small sample of the resistome, just as clinically important antibiotics are a fraction of the
small molecules made by bacteria. Effects wrought by antibiotics may influence the entire pangenome
Gillings 2013 Frontiers Microbiol. 4: 4
Clinically important resistance genes
Clinically important antibiotic molecules
Global Microbiome
Pangenome Panproteome
ParvomeResistome
Mobilome
Human antibiotic
production
Antibiotics as pollutants:
Human synthesis of antibiotics overwhelms natural production, and large quantities are released into the environment. Because they are bioactive, pollution with antibiotics should be of serious concern, and
classed in the same category as other xenobiotic compounds.
Pruden et al. 2006 Eviron Sci Technol 40: 7445-7450; Storteboom et al. 2010 Environ Sci Technol 44: 1947-1953
Global Microbiome
Pangenome Panproteome
Parvome
Resistome
Mobilome
Clinically important resistance genes
Clinically important antibiotic molecules
The Future:
As selective pressures continue, more of the resistome will be recruited onto mobile elements, and the diversity of clinically important
resistance genes will increase. General rates of mutation may increase across the entire microbiome.
Gillings and Stokes 2012 Trends Ecol. Evol. 27: 346-352; Gillings 2013 Frontiers Microbiol. 4: 4
100,000 10,000 1,000 100 0years bp
HOLOCENEPLEISTOCENE ANTHROPOCENE
11700 bp 1775 1953
Human microbiomeShift to agricultural diet
Processed foods AntibioticsCesareansBottle feeding
DysbiosisMicrobiomics
Dispersal/Disease
Resistance MercuryArsenic
AntibioticsDisinfectantsHeavy metals
PollutionEvolvability
present
Migration with parasites
Zoonoses Agricultural mutualisms
Age of explorationEpidemics
Black Death
VaccinationEmerging disease
Antibiotic failurePandemics
Paleoanthropocene Industrial Revolution Great Acceleration
Human effects on the global microbiome: commensals and
pathogens