Literature DB >> 31355980

Stochastic exits from dormancy give rise to heavy-tailed distributions of descendants in bacterial populations.

Erik S Wright1, Kalin H Vetsigian2.   

Abstract

Variance in reproductive success is a major determinant of the degree of genetic drift in a population. While many plants and animals exhibit high variance in their number of progeny, far less is known about these distributions for microorganisms. Here, we used a strain barcoding approach to quantify variability in offspring number among replicate bacterial populations and developed a Bayesian method to infer the distribution of descendants from this variability. We applied our approach to measure the offspring distributions for five strains of bacteria from the genus Streptomyces after germination and growth in a homogenous laboratory environment. The distributions of descendants were heavy-tailed, with a few cells effectively 'winning the jackpot' to become a disproportionately large fraction of the population. This extreme variability in reproductive success largely traced back to initial populations of spores stochastically exiting dormancy, which provided early-germinating spores with an exponential advantage. In simulations with multiple dormancy cycles, heavy-tailed distributions of descendants decreased the effective population size by many orders of magnitude and led to allele dynamics differing substantially from classical population genetics models with matching effective population size. Collectively, these results demonstrate that extreme variability in reproductive success can occur even in growth conditions that are far more homogeneous than the natural environment. Thus, extreme variability in reproductive success might be an important factor shaping microbial population dynamics with implications for predicting the fate of beneficial mutations, interpreting sequence variability within populations and explaining variability in infection outcomes across patients.
© 2019 John Wiley & Sons Ltd.

Entities:  

Keywords:  effective population size; genetic drift; high-resolution lineage tracking; microbial population ecology; variance reproductive success

Mesh:

Year:  2019        PMID: 31355980     DOI: 10.1111/mec.15200

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  5 in total

1.  Wide lag time distributions break a trade-off between reproduction and survival in bacteria.

Authors:  Stefany Moreno-Gámez; Daniel J Kiviet; Clément Vulin; Susan Schlegel; Kim Schlegel; G Sander van Doorn; Martin Ackermann
Journal:  Proc Natl Acad Sci U S A       Date:  2020-07-15       Impact factor: 11.205

2.  Phenotypic-dependent variability and the emergence of tolerance in bacterial populations.

Authors:  José Camacho Mateu; Matteo Sireci; Miguel A Muñoz
Journal:  PLoS Comput Biol       Date:  2021-09-23       Impact factor: 4.475

3.  Mutability of demographic noise in microbial range expansions.

Authors:  QinQin Yu; Matti Gralka; Marie-Cécilia Duvernoy; Megan Sousa; Arbel Harpak; Oskar Hallatschek
Journal:  ISME J       Date:  2021-03-21       Impact factor: 11.217

4.  Seed banks alter the molecular evolutionary dynamics of Bacillus subtilis.

Authors:  William R Shoemaker; Evgeniya Polezhaeva; Kenzie B Givens; Jay T Lennon
Journal:  Genetics       Date:  2022-05-31       Impact factor: 4.402

5.  Powerful and robust non-parametric association testing for microbiome data via a zero-inflated quantile approach (ZINQ).

Authors:  Wodan Ling; Ni Zhao; Anna M Plantinga; Lenore J Launer; Anthony A Fodor; Katie A Meyer; Michael C Wu
Journal:  Microbiome       Date:  2021-09-02       Impact factor: 14.650

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.