Microbial Experimental Evolution – a proving ground for evolutionary theory and a tool for discovery

McDonald, Michael J.

doi:10.15252/embr.201846992

Cited by 123 publications

(108 citation statements)

References 153 publications

(225 reference statements)

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“…Experimental evolution is a powerful tool for identification of genetic elements under selection within different environments 4 . Cooper and colleagues recently showed the value of this approach for Streptococcus pneumoniae in mouse models, using a nasopharyngeal colonisation model similar to that described here, but using a 19F pneumococcal strain (BHN97x) 29 .…”

Section: Discussionmentioning

confidence: 99%

“…The positive correlation between transmission and virulence is well described for a range of pathogens 3 . Experimental evolution approaches 4 have contributed to this understanding, whereby infectious material is passaged from host to host, in an experimental system that promotes gain of infectivity via selection of individuals displaying high levels of in vivo growth. In studies with viral and parasite species, this approach has demonstrated that increased virulence mirrors the increase in transmissibility 5-8 .…”

Section: Introductionmentioning

confidence: 99%

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Identification of colonisation and virulence determinants ofStreptococcus pneumoniaevia experimental evolution in mouse infection models

Green

Howarth

Chaguza

et al. 2020

Preprint

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Streptococcus pneumoniae is a commensal of the human nasopharynx and a major cause of respiratory and invasive disease. Pneumococcus stimulates upper respiratory tract inflammation that promotes shedding from mucosal surfaces and transmission to new hosts. Colonisation and transmission are partially antagonistic processes. Adhesion to surfaces and evasion of host responses favours the former, whilst detachment, promoted by inflammation, is necessary for the latter. We sought to determine how adaptation and evolution of pneumococcus within its nasopharyngeal niche might progress when selective pressures associated with transmission were removed. This was achieved by serial passage of pneumococci in mouse models of nasopharyngeal carriage, manually transferring bacteria between mice. To assess the role of host environmental factors on pneumococcal evolution, we also performed analogous experimental evolution in a mouse pneumonia model, passaging pneumococci through lungs. Nasopharynx-passaged pneumococci became more effective colonisers, whilst those evolved within lungs showed reduced virulence. We observed selection of mutations in genes associated with cell wall biogenesis and metabolism in both nasopharynx and lung lineages, but identified prominent examples of parallel evolution that were niche specific. We focussed on gpsA, a gene in which the same single nucleotide polymorphism arose in two independently evolved nasopharynx-passaged lineages. We identified a single nucleotide change conferring resistance to oxidative stress and enhanced nasopharyngeal colonisation potential. We show that gpsA is also a frequent target of mutation during human colonisation. These findings highlight the role played by the host environment in determining trajectories of bacterial evolution and the potential of experimental evolution in animal infection models for identification of novel pathogen virulence and colonisation factors.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of colonisation and virulence determinants ofStreptococcus pneumoniaevia experimental evolution in mouse infection models

Green

Howarth

Chaguza

et al. 2020

Preprint

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“…Evolution experiments conducted in laboratory environments reproduce key aspects of microbial evolution that are observed in chronic infections and bioreactors (Barrick and Lenski, 2013;Gresham and Dunham, 2014). Certain aspects of genomic and phenotypic evolution in these systems are surprisingly predictable while others are not (Barrick, 2020;Cvijović et al, 2018;Furusawa et al, 2018;McDonald, 2019;Rainey et al, 2017). In theory, profiling many rare mutations in the earliest stages of clonal interference using high-throughput DNA sequencing should allow one to anticipate the future evolution of a population and other populations that evolve in similar environments.…”

Section: Introductionmentioning

confidence: 98%

Profiling the initial burst of beneficial genetic diversity in clonal cell populations to anticipate evolution

Deatherage

Barrick

2020

Preprint

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Clonal populations of cells continuously evolve new genetic diversity, but it takes a significant amount of time for the progeny of a single cell with a new beneficial mutation to outstrip both its ancestor and competitors to fully dominate a population. If genotypes with these driver mutations can be discovered earlier—while they are still extremely rare—it may be possible to anticipate the future evolution of these populations. For example, one could diagnose the likely course of incipient diseases, such as cancer and bacterial infections, and better judge which treatments will be effective, by tracking rare drug-resistant variants. To test this approach, we replayed the first 500 generations of a >70,000-generation Escherichia coli experiment and examined the trajectories of new mutations in eight genes known to be under positive selection in this environment in six populations. By employing a deep sequencing procedure using molecular indexes and target enrichment we were able to track 236 beneficial mutations at frequencies as low as 0.01% and infer selection coefficients for 180 of these. Distinct molecular signatures of selection on protein structure and function were evident for the three genes in which beneficial mutations were most common (nadR, pykF, and topA). We detected mutations hundreds of generations before they became dominant and tracked beneficial alleles in genes that were not mutated in the long-term experiment until thousands of generations had passed. Therefore, this targeted adaptome sequencing approach can function as an early warning system to inform interventions that aim to prevent undesirable evolution.

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“…Due to these obstacles, the majority of microbial studies in microfluidic gradients usually do not encompasses cultivations for more than 2 days [ 27,29–32 ] and may not be able to discover adaptations that often manifest themselves only after prolonged cultivation. [ 7,33 ] To overcome these limitations and to enable long‐term ALE experiments with efficient screening under unfavorable high stress conditions, we here describe a novel, robust, and user‐friendly miniaturized ALE chip design that employs adjustable spatial stress profiles and an in‐flow gradient while at the same time enabling efficient on‐chip screening of the complete cell population.…”

Section: Introductionmentioning

confidence: 99%

Microfluidic Evolution‐On‐A‐Chip Reveals New Mutations that Cause Antibiotic Resistance

Zoheir

Späth

Niemeyer

et al. 2021

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Microfluidic devices can mimic naturally occurring microenvironments and create microbial population heterogeneities ranging from planktonic cells to biofilm states. The exposure of such populations to spatially organized stress gradients can promote their adaptation into complex phenotypes, which are otherwise difficult to achieve with conventional experimental setups. Here a microfluidic chip that employs precise chemical gradients in consecutive microcompartments to perform microbial adaptive laboratory evolution (ALE), a key tool to study evolution in fundamental and applied contexts is described. In the chip developed here, microbial cells can be exposed to a defined profile of stressors such as antibiotics. By modulating this profile, stress adaptation in the chip through resistance or persistence can be specifically controlled. Importantly, chip‐based ALE leads to the discovery of previously unknown mutations in Escherichia coli that confer resistance to nalidixic acid. The microfluidic device presented here can enhance the occurrence of mutations employing defined micro‐environmental conditions to generate data to better understand the parameters that influence the mechanisms of antibiotic resistance.

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Microbial Experimental Evolution – a proving ground for evolutionary theory and a tool for discovery

Cited by 123 publications

References 153 publications

Identification of colonisation and virulence determinants ofStreptococcus pneumoniaevia experimental evolution in mouse infection models

Identification of colonisation and virulence determinants ofStreptococcus pneumoniaevia experimental evolution in mouse infection models

Profiling the initial burst of beneficial genetic diversity in clonal cell populations to anticipate evolution

Microfluidic Evolution‐On‐A‐Chip Reveals New Mutations that Cause Antibiotic Resistance

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