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Quantifying bacterial evolution in the wild: A birthday problem for Campylobacter lineages

Abstract:
Measuring molecular evolution in bacteria typically requires estimation of the rate at which nucleotide changes accumulate in strains sampled at different times that share a common ancestor. This approach has been useful for dating ecological and evolutionary events that coincide with the emergence of important lineages, such as outbreak strains and obligate human pathogens. However, in multi-host (niche) transmission scenarios, where the pathogen is essentially an opportunistic environmental organism, sampling is often sporadic and rarely reflects the overall population, particularly when concentrated on clinical isolates. This means that approaches that assume recent common ancestry are not applicable. Here we present a new approach to estimate the molecular clock rate in Campylobacter that draws on the popular probability conundrum known as the 'birthday problem'. Using large genomic datasets and comparative genomic approaches, we use isolate pairs that share recent common ancestry to estimate the rate of nucleotide change for the population. Identifying synonymous and non-synonymous nucleotide changes, both within and outside of recombined regions of the genome, we quantify clock-like diversification to estimate synonymous rates of nucleotide change for the common pathogenic bacteria Campylobacter colt (2.4 x 10(-6) s/s/y) and Campylobacter jejuni (3.4 x 10(-6) s/s/y). Finally, using estimated total rates of nucleotide change, we infer the number of effective lineages within the sample time frame-analogous to a shared birthday-and assess the rate of turnover of lineages in our sample set over short evolutionary timescales. This provides a generalizable approach to calibrating rates in populations of environmental bacteria and shows that multiple lineages are maintained, implying that large-scale clonal sweeps may take hundreds of years or more in these species.Peer reviewe
Publication status:
Published
Peer review status:
Peer reviewed

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Role:
Author
ORCID:
0000-0001-8888-0812
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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0001-6376-5121
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Role:
Author
ORCID:
0000-0002-5997-2002
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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-7411-4743
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Role:
Author
ORCID:
0000-0003-4232-9448


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Funder identifier:
10.13039/501100000265
Grant:
MR/L015080/1
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Funder identifier:
10.13039/100000002
Grant:
1R01AI158576-01
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Funder identifier:
10.13039/501100000268
Grant:
BB/P504750/1
More from this funder
Funder identifier:
10.13039/501100003399
Grant:
2019SHZDZX02


Publisher:
Public Library of Science
Journal:
PLoS Genetics More from this journal
Volume:
17
Issue:
9
Pages:
e1009829-e1009829
Publication date:
2021-09-28
DOI:
EISSN:
1553-7404
ISSN:
1553-7390


Language:
English
Keywords:
Pubs id:
1279027
Local pid:
pubs:1279027
Source identifiers:
W3201697337
Deposit date:
2026-04-28
ARK identifier:
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