1
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Couce A, Limdi A, Magnan M, Owen SV, Herren CM, Lenski RE, Tenaillon O, Baym M. Changing fitness effects of mutations through long-term bacterial evolution. Science 2024; 383:eadd1417. [PMID: 38271521 DOI: 10.1126/science.add1417] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 12/12/2023] [Indexed: 01/27/2024]
Abstract
The distribution of fitness effects of new mutations shapes evolution, but it is challenging to observe how it changes as organisms adapt. Using Escherichia coli lineages spanning 50,000 generations of evolution, we quantify the fitness effects of insertion mutations in every gene. Macroscopically, the fraction of deleterious mutations changed little over time whereas the beneficial tail declined sharply, approaching an exponential distribution. Microscopically, changes in individual gene essentiality and deleterious effects often occurred in parallel; altered essentiality is only partly explained by structural variation. The identity and effect sizes of beneficial mutations changed rapidly over time, but many targets of selection remained predictable because of the importance of loss-of-function mutations. Taken together, these results reveal the dynamic-but statistically predictable-nature of mutational fitness effects.
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Affiliation(s)
- Alejandro Couce
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, F-75018 Paris, France
- Department of Life Sciences, Imperial College London, London SW7 2AZ, UK
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM), 28223 Madrid, Spain
| | - Anurag Limdi
- Department of Biomedical Informatics, and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Melanie Magnan
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, F-75018 Paris, France
| | - Siân V Owen
- Department of Biomedical Informatics, and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Cristina M Herren
- Department of Biomedical Informatics, and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA
- Department of Marine and Environmental Sciences, Northeastern University, Boston, MA 02115, USA
| | - Richard E Lenski
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA
- Program in Ecology, Evolution, and Behavior, Michigan State University, East Lansing, MI 48824, USA
| | - Olivier Tenaillon
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, F-75018 Paris, France
- Université Paris Cité, Inserm, Institut Cochin, F-75014 Paris, France
| | - Michael Baym
- Department of Biomedical Informatics, and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA
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2
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Melissa MJ, Desai MM. A dynamical limit to evolutionary adaptation. Proc Natl Acad Sci U S A 2024; 121:e2312845121. [PMID: 38241432 PMCID: PMC10823227 DOI: 10.1073/pnas.2312845121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 12/06/2023] [Indexed: 01/21/2024] Open
Abstract
Natural selection makes evolutionary adaptation possible even if the overwhelming majority of new mutations are deleterious. However, in rapidly evolving populations where numerous linked mutations occur and segregate simultaneously, clonal interference and genetic hitchhiking can limit the efficiency of selection, allowing deleterious mutations to accumulate over time. This can in principle overwhelm the fitness increases provided by beneficial mutations, leading to an overall fitness decline. Here, we analyze the conditions under which evolution will tend to drive populations to higher versus lower fitness. Our analysis focuses on quantifying the boundary between these two regimes, as a function of parameters such as population size, mutation rates, and selection pressures. This boundary represents a state in which adaptation is precisely balanced by Muller's ratchet, and we show that it can be characterized by rapid molecular evolution without any net fitness change. Finally, we consider the implications of global fitness-mediated epistasis and find that under some circumstances, this can drive populations toward the boundary state, which can thus represent a long-term evolutionary attractor.
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Affiliation(s)
- Matthew J. Melissa
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA02138
- Department of Physics, Harvard University, Cambridge, MA02138
- Quantitative Biology Initiative, Harvard University, Cambridge, MA02138
- National Science Foundation (NSF)-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, MA02138
| | - Michael M. Desai
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA02138
- Department of Physics, Harvard University, Cambridge, MA02138
- Quantitative Biology Initiative, Harvard University, Cambridge, MA02138
- National Science Foundation (NSF)-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, MA02138
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3
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Charmouh AP, Bocedi G, Hartfield M. Inferring the distributions of fitness effects and proportions of strongly deleterious mutations. G3 (BETHESDA, MD.) 2023; 13:jkad140. [PMID: 37337692 PMCID: PMC10468728 DOI: 10.1093/g3journal/jkad140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 06/05/2023] [Accepted: 06/05/2023] [Indexed: 06/21/2023]
Abstract
The distribution of fitness effects is a key property in evolutionary genetics as it has implications for several evolutionary phenomena including the evolution of sex and mating systems, the rate of adaptive evolution, and the prevalence of deleterious mutations. Despite the distribution of fitness effects being extensively studied, the effects of strongly deleterious mutations are difficult to infer since such mutations are unlikely to be present in a sample of haplotypes, so genetic data may contain very little information about them. Recent work has attempted to correct for this issue by expanding the classic gamma-distributed model to explicitly account for strongly deleterious mutations. Here, we use simulations to investigate one such method, adding a parameter (plth) to capture the proportion of strongly deleterious mutations. We show that plth can improve the model fit when applied to individual species but underestimates the true proportion of strongly deleterious mutations. The parameter can also artificially maximize the likelihood when used to jointly infer a distribution of fitness effects from multiple species. As plth and related parameters are used in current inference algorithms, our results are relevant with respect to avoiding model artifacts and improving future tools for inferring the distribution of fitness effects.
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Affiliation(s)
- Anders P Charmouh
- School of Biological Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK
- Bioinformatics Research Centre Aarhus University, University City 81, building 1872, 3rd floor. DK-8000 Aarhus C, Denmark
| | - Greta Bocedi
- School of Biological Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK
| | - Matthew Hartfield
- Institute of Ecology and Evolution, The University of Edinburgh, Edinburgh EH9 3FL, UK
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4
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Melissa MJ, Desai MM. A dynamical limit to evolutionary adaptation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.31.551320. [PMID: 37577473 PMCID: PMC10418092 DOI: 10.1101/2023.07.31.551320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Natural selection makes evolutionary adaptation possible even if the overwhelming majority of new mutations are deleterious. However, in rapidly evolving populations where numerous linked mutations occur and segregate simultaneously, clonal interference and genetic hitchhiking can limit the efficiency of selection, allowing deleterious mutations to accumulate over time. This can in principle overwhelm the fitness increases provided by beneficial mutations, leading to an overall fitness decline. Here, we analyze the conditions under which evolution will tend to drive populations to higher versus lower fitness. Our analysis focuses on quantifying the boundary between these two regimes, as a function of parameters such as population size, mutation rates, and selection pressures. This boundary represents a state in which adaptation is precisely balanced by Muller's ratchet, and we show that it can be characterized by rapid molecular evolution without any net fitness change. Finally, we consider the implications of global fitness-mediated epistasis, and find that under some circumstances this can drive populations towards the boundary state, which can thus represent a long-term evolutionary attractor.
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Affiliation(s)
- Matthew J. Melissa
- Department of Organismic and Evolutionary Biology, Department of Physics, Quantitative Biology Initiative, and NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University
| | - Michael M. Desai
- Department of Organismic and Evolutionary Biology, Department of Physics, Quantitative Biology Initiative, and NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University
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5
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Epley BR. Digest: Few new mutations are recessive lethal. Evolution 2023; 77:1914-1915. [PMID: 37354114 PMCID: PMC10373208 DOI: 10.1093/evolut/qpad117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 06/22/2023] [Indexed: 06/26/2023]
Abstract
When a new mutation arises, what is the probability that it is recessive lethal? Wade et al. find that fewer than 1% of nonsynonymous mutations in humans and Drosophila melanogaster are recessive lethal. The authors show that methods based on site frequency spectrum (SFS) analyses, though generally robust in their estimations of the nonlethal distribution of fitness effects (DFE), are unable to accurately estimate the fraction of recessive lethal mutations.
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Affiliation(s)
- Benjamin R Epley
- Ecology and Evolution, University of Chicago, Chicago, IL, United States
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6
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Ascensao JA, Wetmore KM, Good BH, Arkin AP, Hallatschek O. Quantifying the local adaptive landscape of a nascent bacterial community. Nat Commun 2023; 14:248. [PMID: 36646697 PMCID: PMC9842643 DOI: 10.1038/s41467-022-35677-5] [Citation(s) in RCA: 60] [Impact Index Per Article: 60.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 12/16/2022] [Indexed: 01/17/2023] Open
Abstract
The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes ("L" and "S") shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.
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Affiliation(s)
- Joao A Ascensao
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Kelly M Wetmore
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Benjamin H Good
- Department of Applied Physics, Stanford University, Stanford, CA, 94305, USA
| | - Adam P Arkin
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, 94720, USA.,Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Oskar Hallatschek
- Department of Physics, University of California, Berkeley, Berkeley, CA, 94720, USA. .,Department of Integrative Biology, University of California, Berkeley, Berkeley, CA, 94720, USA. .,Peter Debye Institute for Soft Matter Physics, Leipzig University, 04103, Leipzig, Germany.
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7
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Lynch M, Trickovic B, Kempes CP. Evolutionary scaling of maximum growth rate with organism size. Sci Rep 2022; 12:22586. [PMID: 36585440 PMCID: PMC9803686 DOI: 10.1038/s41598-022-23626-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 11/02/2022] [Indexed: 12/31/2022] Open
Abstract
Data from nearly 1000 species reveal the upper bound to rates of biomass production achievable by natural selection across the Tree of Life. For heterotrophs, maximum growth rates scale positively with organism size in bacteria but negatively in eukaryotes, whereas for phototrophs, the scaling is negligible for cyanobacteria and weakly negative for eukaryotes. These results have significant implications for understanding the bioenergetic consequences of the transition from prokaryotes to eukaryotes, and of the expansion of some groups of the latter into multicellularity. The magnitudes of the scaling coefficients for eukaryotes are significantly lower than expected under any proposed physical-constraint model. Supported by genomic, bioenergetic, and population-genetic data and theory, an alternative hypothesis for the observed negative scaling in eukaryotes postulates that growth-diminishing mutations with small effects passively accumulate with increasing organism size as a consequence of associated increases in the power of random genetic drift. In contrast, conditional on the structural and functional features of ribosomes, natural selection has been able to promote bacteria with the fastest possible growth rates, implying minimal conflicts with both bioenergetic constraints and random genetic drift. If this extension of the drift-barrier hypothesis is correct, the interpretations of comparative studies of biological traits that have traditionally ignored differences in population-genetic environments will require revisiting.
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Affiliation(s)
- Michael Lynch
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ, 85287, USA.
| | - Bogi Trickovic
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ, 85287, USA
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8
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Two modes of evolution shape bacterial strain diversity in the mammalian gut for thousands of generations. Nat Commun 2022; 13:5604. [PMID: 36153389 PMCID: PMC9509342 DOI: 10.1038/s41467-022-33412-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 09/14/2022] [Indexed: 11/17/2022] Open
Abstract
How and at what pace bacteria evolve when colonizing healthy hosts remains unclear. Here, by monitoring evolution for more than six thousand generations in the mouse gut, we show that the successful colonization of an invader Escherichia coli depends on the diversity of the existing microbiota and the presence of a closely related strain. Following colonization, two modes of evolution were observed: one in which diversifying selection leads to long-term coexistence of ecotypes and a second in which directional selection propels selective sweeps. These modes can be quantitatively distinguished by the statistics of mutation trajectories. In our experiments, diversifying selection was marked by the emergence of metabolic mutations, and directional selection by acquisition of prophages, which bring their own benefits and costs. In both modes, we observed parallel evolution, with mutation accumulation rates comparable to those typically observed in vitro on similar time scales. Our results show how rapid ecotype formation and phage domestication can be in the mammalian gut. Here, the authors show that a colonizing bacterial strain evolves in the gut by either generating ecotypes or continuously fixing beneficial mutations. They associate the first mode to metabolic mutations and the second to domestication of bacteriophages that are incorporated into the bacterial genome.
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9
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Pontz M, Bürger R. The effects of epistasis and linkage on the invasion of locally beneficial mutations and the evolution of genomic islands. Theor Popul Biol 2022; 144:49-69. [DOI: 10.1016/j.tpb.2022.01.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 01/04/2022] [Accepted: 01/07/2022] [Indexed: 11/26/2022]
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10
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Vecchyo DOD, Lohmueller KE, Novembre J. Haplotype-based inference of the distribution of fitness effects. Genetics 2022; 220:6501446. [PMID: 35100400 PMCID: PMC8982047 DOI: 10.1093/genetics/iyac002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 12/18/2021] [Indexed: 11/13/2022] Open
Abstract
Abstract
Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some non-equilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.
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Affiliation(s)
- Diego Ortega-Del Vecchyo
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, 76230, México
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
| | - Kirk E Lohmueller
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, Illinois, 60637, United States of America
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, 60637, United States of America
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11
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Moran J, Finlay D, Tikhonov M. Improve it or lose it: Evolvability cost of competition for expression. Phys Rev E 2021; 103:062402. [PMID: 34271680 DOI: 10.1103/physreve.103.062402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 05/24/2021] [Indexed: 11/07/2022]
Abstract
Expression level is known to be a strong determinant of a protein's rate of evolution. But the converse can also be true: evolutionary dynamics can affect expression levels of proteins. Having implications in both directions fosters the possibility of an "improve it or lose it" feedback loop, where higher expressed systems are more likely to improve and be expressed even higher, while those that are expressed less are eventually lost to drift. Using a minimal model to study this in the context of a changing environment, we demonstrate that one unexpected consequence of such a feedback loop is that a slow switch to a new environment can allow genotypes to reach higher fitness sooner than a direct exposure to it.
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Affiliation(s)
- Jacob Moran
- Department of Physics, Washington University in St. Louis, St. Louis, Missouri 63130, USA
| | - Devon Finlay
- Department of Physics, Washington University in St. Louis, St. Louis, Missouri 63130, USA
| | - Mikhail Tikhonov
- Department of Physics, Washington University in St. Louis, St. Louis, Missouri 63130, USA
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12
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Reddy G, Desai MM. Global epistasis emerges from a generic model of a complex trait. eLife 2021; 10:64740. [PMID: 33779543 PMCID: PMC8057814 DOI: 10.7554/elife.64740] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 03/26/2021] [Indexed: 11/20/2022] Open
Abstract
Epistasis between mutations can make adaptation contingent on evolutionary history. Yet despite widespread ‘microscopic’ epistasis between the mutations involved, microbial evolution experiments show consistent patterns of fitness increase between replicate lines. Recent work shows that this consistency is driven in part by global patterns of diminishing-returns and increasing-costs epistasis, which make mutations systematically less beneficial (or more deleterious) on fitter genetic backgrounds. However, the origin of this ‘global’ epistasis remains unknown. Here, we show that diminishing-returns and increasing-costs epistasis emerge generically as a consequence of pervasive microscopic epistasis. Our model predicts a specific quantitative relationship between the magnitude of global epistasis and the stochastic effects of microscopic epistasis, which we confirm by reanalyzing existing data. We further show that the distribution of fitness effects takes on a universal form when epistasis is widespread and introduce a novel fitness landscape model to show how phenotypic evolution can be repeatable despite sequence-level stochasticity.
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Affiliation(s)
- Gautam Reddy
- NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States
| | - Michael M Desai
- NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States.,Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States.,Quantitative Biology Initiative, Harvard University, Cambridge, United States.,Department of Physics, Harvard University, Cambridge, United States
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13
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Barlukova A, Rouzine IM. The evolutionary origin of the universal distribution of mutation fitness effect. PLoS Comput Biol 2021; 17:e1008822. [PMID: 33684109 PMCID: PMC7971868 DOI: 10.1371/journal.pcbi.1008822] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 03/18/2021] [Accepted: 02/19/2021] [Indexed: 01/27/2023] Open
Abstract
An intriguing fact long defying explanation is the observation of a universal exponential distribution of beneficial mutations in fitness effect for different microorganisms. To explain this effect, we use a population model including mutation, directional selection, linkage, and genetic drift. The multiple-mutation regime of adaptation at large population sizes (traveling wave regime) is considered. We demonstrate analytically and by simulation that, regardless of the inherent distribution of mutation fitness effect across genomic sites, an exponential distribution of fitness effects emerges in the long term. This result follows from the exponential statistics of the frequency of the less-fit alleles, f, that we predict to evolve, in the long term, for both polymorphic and monomorphic sites. We map the logarithmic slope of the distribution onto the previously derived fixation probability and demonstrate that it increases linearly in time. Our results demonstrate a striking difference between the distribution of fitness effects observed experimentally for naturally occurring mutations, and the "inherent" distribution obtained in a directed-mutagenesis experiment, which can have any shape depending on the organism. Based on these results, we develop a new method to measure the fitness effect of mutations for each variable residue using DNA sequences sampled from adapting populations. This new method is not sensitive to linkage effects and does not require the one-site model assumptions.
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Affiliation(s)
- Ayuna Barlukova
- Sorbonne Université, Institute de Biologie Paris-Seine, Laboratoire de Biologie Computationnelle et Quantitative, Paris, France
| | - Igor M. Rouzine
- Sorbonne Université, Institute de Biologie Paris-Seine, Laboratoire de Biologie Computationnelle et Quantitative, Paris, France
- * E-mail: ,
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14
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Venkataram S, Monasky R, Sikaroodi SH, Kryazhimskiy S, Kacar B. Evolutionary stalling and a limit on the power of natural selection to improve a cellular module. Proc Natl Acad Sci U S A 2020; 117:18582-18590. [PMID: 32680961 PMCID: PMC7414050 DOI: 10.1073/pnas.1921881117] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Cells consist of molecular modules which perform vital biological functions. Cellular modules are key units of adaptive evolution because organismal fitness depends on their performance. Theory shows that in rapidly evolving populations, such as those of many microbes, adaptation is driven primarily by common beneficial mutations with large effects, while other mutations behave as if they are effectively neutral. As a consequence, if a module can be improved only by rare and/or weak beneficial mutations, its adaptive evolution would stall. However, such evolutionary stalling has not been empirically demonstrated, and it is unclear to what extent stalling may limit the power of natural selection to improve modules. Here we empirically characterize how natural selection improves the translation machinery (TM), an essential cellular module. We experimentally evolved populations of Escherichia coli with genetically perturbed TMs for 1,000 generations. Populations with severe TM defects initially adapted via mutations in the TM, but TM adaptation stalled within about 300 generations. We estimate that the genetic load in our populations incurred by residual TM defects ranges from 0.5 to 19%. Finally, we found evidence that both epistasis and the depletion of the pool of beneficial mutations contributed to evolutionary stalling. Our results suggest that cellular modules may not be fully optimized by natural selection despite the availability of adaptive mutations.
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Affiliation(s)
- Sandeep Venkataram
- Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093
| | - Ross Monasky
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721
| | - Shohreh H Sikaroodi
- Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093
| | - Sergey Kryazhimskiy
- Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093;
| | - Betul Kacar
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721;
- Lunar and Planetary Laboratory, University of Arizona, Tucson, AZ 85721
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15
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The evolutionary scaling of cellular traits imposed by the drift barrier. Proc Natl Acad Sci U S A 2020; 117:10435-10444. [PMID: 32345718 DOI: 10.1073/pnas.2000446117] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Owing to internal homeostatic mechanisms, cellular traits may experience long periods of stable selective pressures, during which the stochastic forces of drift and mutation conspire to generate variation. However, even in the face of invariant selection, the drift barrier defined by the genetic effective population size, which is negatively associated with organism size, can have a substantial influence on the location and dispersion of the long-term steady-state distribution of mean phenotypes. In addition, for multilocus traits, the multiplicity of alternative, functionally equivalent states can draw mean phenotypes away from selective optima, even in the absence of mutation bias. Using a framework for traits with an additive genetic basis, it is shown that 1) optimal phenotypic states may be only rarely achieved; 2) gradients of mean phenotypes with respect to organism size (i.e., allometric relationships) are likely to be molded by differences in the power of random genetic drift across the tree of life; and 3) for any particular set of population-genetic conditions, significant variation in mean phenotypes may exist among lineages exposed to identical selection pressures. These results provide a potentially useful framework for understanding numerous aspects of cellular diversification and illustrate the risks of interpreting such variation in a purely adaptive framework.
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16
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Sidorova A, Levashova N, Garaeva A, Tverdislov V. A percolation model of natural selection. Biosystems 2020; 193-194:104120. [PMID: 32092352 DOI: 10.1016/j.biosystems.2020.104120] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 01/29/2020] [Accepted: 02/15/2020] [Indexed: 12/13/2022]
Abstract
A new approach has been proposed and developed: the selection of optimal variants in the evolutionary mutation flow is considered as an analogue of a percolation filter. Interaction of mutations in a series of generations and random processes of drift determine the collective behavior of nodes (individuals - carriers and converters of mutations) and bonds (mutations) in the space of percolation lattice. It is shown that the choice of the development trajectory at the population level depends on the spectrum of supporting and prohibiting mutations under the influence of conjugate deterministic and random factors. From the point of view of the fluctuation-bifurcation process, new concepts of the lower and upper thresholds of the percolation selection grid are defined in the hierarchical structure of speciation. The upper threshold determines the state of self-organized criticality, which, when overcome, leads to irreversible self-organization processes in the population caused by the accumulation of mutations.
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Affiliation(s)
- Alla Sidorova
- Department of Biophysics, Faculty of Physics, M.V.Lomonosov Moscow State University. Moscow, 119991, Russia.
| | - Natalia Levashova
- Department of Mathematics, Faculty of Physics, M.V.Lomonosov Moscow State University. Moscow, 119991, Russia.
| | - Anastasia Garaeva
- Department of Biophysics, Faculty of Physics, M.V.Lomonosov Moscow State University. Moscow, 119991, Russia.
| | - Vsevolod Tverdislov
- Department of Biophysics, Faculty of Physics, M.V.Lomonosov Moscow State University. Moscow, 119991, Russia.
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17
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Johnson MS, Martsul A, Kryazhimskiy S, Desai MM. Higher-fitness yeast genotypes are less robust to deleterious mutations. Science 2019; 366:490-493. [PMID: 31649199 PMCID: PMC7204892 DOI: 10.1126/science.aay4199] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 09/11/2019] [Indexed: 12/11/2022]
Abstract
Natural selection drives populations toward higher fitness, but second-order selection for adaptability and mutational robustness can also influence evolution. In many microbial systems, diminishing-returns epistasis contributes to a tendency for more-fit genotypes to be less adaptable, but no analogous patterns for robustness are known. To understand how robustness varies across genotypes, we measure the fitness effects of hundreds of individual insertion mutations in a panel of yeast strains. We find that more-fit strains are less robust: They have distributions of fitness effects with lower mean and higher variance. These differences arise because many mutations have more strongly deleterious effects in faster-growing strains. This negative correlation between fitness and robustness implies that second-order selection for robustness will tend to conflict with first-order selection for fitness.
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Affiliation(s)
- Milo S Johnson
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Quantitative Biology Initiative, Harvard University, Cambridge, MA 02138, USA
- NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, MA 02138, USA
| | - Alena Martsul
- Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Sergey Kryazhimskiy
- Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA.
| | - Michael M Desai
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.
- Quantitative Biology Initiative, Harvard University, Cambridge, MA 02138, USA
- NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
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18
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Held T, Klemmer D, Lässig M. Survival of the simplest in microbial evolution. Nat Commun 2019; 10:2472. [PMID: 31171781 PMCID: PMC6554311 DOI: 10.1038/s41467-019-10413-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 05/10/2019] [Indexed: 01/09/2023] Open
Abstract
The evolution of microbial and viral organisms often generates clonal interference, a mode of competition between genetic clades within a population. Here we show how interference impacts systems biology by constraining genetic and phenotypic complexity. Our analysis uses biophysically grounded evolutionary models for molecular phenotypes, such as fold stability and enzymatic activity of genes. We find a generic mode of phenotypic interference that couples the function of individual genes and the population’s global evolutionary dynamics. Biological implications of phenotypic interference include rapid collateral system degradation in adaptation experiments and long-term selection against genome complexity: each additional gene carries a cost proportional to the total number of genes. Recombination above a threshold rate can eliminate this cost, which establishes a universal, biophysically grounded scenario for the evolution of sex. In a broader context, our analysis suggests that the systems biology of microbes is strongly intertwined with their mode of evolution. In asexual populations selection at different genomic loci can interfere with each other. Here, using a biophysical model of molecular evolution the authors show that interference results in long-term degradation of molecular function, an effect that strongly depends on genome size.
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Affiliation(s)
- Torsten Held
- Institut für Biologische Physik, Universität zu Köln, Zülpicherstr. 77, 50937, Köln, Germany
| | - Daniel Klemmer
- Institut für Biologische Physik, Universität zu Köln, Zülpicherstr. 77, 50937, Köln, Germany
| | - Michael Lässig
- Institut für Biologische Physik, Universität zu Köln, Zülpicherstr. 77, 50937, Köln, Germany.
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19
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Jakobson CM, Jarosz DF. Molecular Origins of Complex Heritability in Natural Genotype-to-Phenotype Relationships. Cell Syst 2019; 8:363-379.e3. [PMID: 31054809 PMCID: PMC6560647 DOI: 10.1016/j.cels.2019.04.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 03/25/2019] [Accepted: 04/05/2019] [Indexed: 01/09/2023]
Abstract
The statistical complexity of heredity has long been evident, but its molecular origins remain elusive. To investigate, we charted 90 comprehensive genotype-to-phenotype maps in a large population of wild diploid yeast. In contrast to long-standing assumptions, all types of genetic variation contributed similarly to phenotype. Causal synonymous and regulatory variants exhibited distinct molecular signatures, as did nonlinearities in heterozygote fitness that likely contribute to hybrid vigor. Highly pleiotropic variants altered disordered sequences within signaling hubs, and their effects correlated across environments-even when antagonistic-suggesting that large fitness gains bring concomitant costs. Natural genetic networks defined by the causal loci differed from those determined by precise gene deletions or protein-protein interactions. Finally, we found that traits that would appear omnigenic in less powered studies do in fact have finite genetic determinants. Integrating these molecular principles will be crucial as genome reading and writing become routine in research, industry, and medicine.
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Affiliation(s)
- Christopher M Jakobson
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Daniel F Jarosz
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA.
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20
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Van den Bergh B, Swings T, Fauvart M, Michiels J. Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution. Microbiol Mol Biol Rev 2018; 82:e00008-18. [PMID: 30045954 PMCID: PMC6094045 DOI: 10.1128/mmbr.00008-18] [Citation(s) in RCA: 90] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.
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Affiliation(s)
- Bram Van den Bergh
- Laboratory of Symbiotic and Pathogenic Interactions, Centre of Microbial and Plant Genetics, KU Leuven-University of Leuven, Leuven, Belgium
- Michiels Lab, Center for Microbiology, VIB, Leuven, Belgium
- Douglas Lab, Department of Entomology, Cornell University, Ithaca, New York, USA
| | - Toon Swings
- Laboratory of Symbiotic and Pathogenic Interactions, Centre of Microbial and Plant Genetics, KU Leuven-University of Leuven, Leuven, Belgium
- Michiels Lab, Center for Microbiology, VIB, Leuven, Belgium
| | - Maarten Fauvart
- Laboratory of Symbiotic and Pathogenic Interactions, Centre of Microbial and Plant Genetics, KU Leuven-University of Leuven, Leuven, Belgium
- Michiels Lab, Center for Microbiology, VIB, Leuven, Belgium
- imec, Leuven, Belgium
| | - Jan Michiels
- Laboratory of Symbiotic and Pathogenic Interactions, Centre of Microbial and Plant Genetics, KU Leuven-University of Leuven, Leuven, Belgium
- Michiels Lab, Center for Microbiology, VIB, Leuven, Belgium
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21
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Cvijović I, Nguyen Ba AN, Desai MM. Experimental Studies of Evolutionary Dynamics in Microbes. Trends Genet 2018; 34:693-703. [PMID: 30025666 PMCID: PMC6467257 DOI: 10.1016/j.tig.2018.06.004] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 06/18/2018] [Accepted: 06/22/2018] [Indexed: 11/16/2022]
Abstract
Evolutionary dynamics in laboratory microbial evolution experiments can be surprisingly complex. In the past two decades, observations of these dynamics have challenged simple models of adaptation and have shown that clonal interference, hitchhiking, ecological diversification, and contingency are widespread. In recent years, advances in high-throughput strain maintenance and phenotypic assays, the dramatically reduced cost of genome sequencing, and emerging methods for lineage barcoding have made it possible to observe evolutionary dynamics at unprecedented resolution. These new methods can now begin to provide detailed measurements of key aspects of fitness landscapes and of evolutionary outcomes across a range of systems. These measurements can highlight challenges to existing theoretical models and guide new theoretical work towards the complications that are most widely important.
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Affiliation(s)
- Ivana Cvijović
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; FAS Center for Systems Biology, Harvard University, Cambridge, MA 02138, USA
| | - Alex N Nguyen Ba
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; FAS Center for Systems Biology, Harvard University, Cambridge, MA 02138, USA
| | - Michael M Desai
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; FAS Center for Systems Biology, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Harvard University, Cambridge, MA 02138, USA.
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22
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Huber CD, Kim BY, Marsden CD, Lohmueller KE. Determining the factors driving selective effects of new nonsynonymous mutations. Proc Natl Acad Sci U S A 2017; 114:4465-4470. [PMID: 28400513 PMCID: PMC5410820 DOI: 10.1073/pnas.1619508114] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
The distribution of fitness effects (DFE) of new mutations plays a fundamental role in evolutionary genetics. However, the extent to which the DFE differs across species has yet to be systematically investigated. Furthermore, the biological mechanisms determining the DFE in natural populations remain unclear. Here, we show that theoretical models emphasizing different biological factors at determining the DFE, such as protein stability, back-mutations, species complexity, and mutational robustness make distinct predictions about how the DFE will differ between species. Analyzing amino acid-changing variants from natural populations in a comparative population genomic framework, we find that humans have a higher proportion of strongly deleterious mutations than Drosophila melanogaster. Furthermore, when comparing the DFE across yeast, Drosophila, mice, and humans, the average selection coefficient becomes more deleterious with increasing species complexity. Last, pleiotropic genes have a DFE that is less variable than that of nonpleiotropic genes. Comparing four categories of theoretical models, only Fisher's geometrical model (FGM) is consistent with our findings. FGM assumes that multiple phenotypes are under stabilizing selection, with the number of phenotypes defining the complexity of the organism. Our results suggest that long-term population size and cost of complexity drive the evolution of the DFE, with many implications for evolutionary and medical genomics.
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Affiliation(s)
- Christian D Huber
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095;
| | - Bernard Y Kim
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095
| | - Clare D Marsden
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095;
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, CA 90095
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
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23
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Gjuvsland AB, Zörgö E, Samy JK, Stenberg S, Demirsoy IH, Roque F, Maciaszczyk-Dziubinska E, Migocka M, Alonso-Perez E, Zackrisson M, Wysocki R, Tamás MJ, Jonassen I, Omholt SW, Warringer J. Disentangling genetic and epigenetic determinants of ultrafast adaptation. Mol Syst Biol 2016; 12:892. [PMID: 27979908 PMCID: PMC5199126 DOI: 10.15252/msb.20166951] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
A major rationale for the advocacy of epigenetically mediated adaptive responses is that they facilitate faster adaptation to environmental challenges. This motivated us to develop a theoretical-experimental framework for disclosing the presence of such adaptation-speeding mechanisms in an experimental evolution setting circumventing the need for pursuing costly mutation-accumulation experiments. To this end, we exposed clonal populations of budding yeast to a whole range of stressors. By growth phenotyping, we found that almost complete adaptation to arsenic emerged after a few mitotic cell divisions without involving any phenotypic plasticity. Causative mutations were identified by deep sequencing of the arsenic-adapted populations and reconstructed for validation. Mutation effects on growth phenotypes, and the associated mutational target sizes were quantified and embedded in data-driven individual-based evolutionary population models. We found that the experimentally observed homogeneity of adaptation speed and heterogeneity of molecular solutions could only be accounted for if the mutation rate had been near estimates of the basal mutation rate. The ultrafast adaptation could be fully explained by extensive positive pleiotropy such that all beneficial mutations dramatically enhanced multiple fitness components in concert. As our approach can be exploited across a range of model organisms exposed to a variety of environmental challenges, it may be used for determining the importance of epigenetic adaptation-speeding mechanisms in general.
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Affiliation(s)
- Arne B Gjuvsland
- Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway
| | - Enikö Zörgö
- Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway.,Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Jeevan Ka Samy
- Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway
| | - Simon Stenberg
- Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway
| | - Ibrahim H Demirsoy
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Francisco Roque
- Computational Biology Unit, University of Bergen, Bergen, Norway
| | | | - Magdalena Migocka
- Institute of Experimental Biology, University of Wroclaw, Wroclaw, Poland
| | - Elisa Alonso-Perez
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Martin Zackrisson
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Robert Wysocki
- Institute of Experimental Biology, University of Wroclaw, Wroclaw, Poland
| | - Markus J Tamás
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Inge Jonassen
- Computational Biology Unit, University of Bergen, Bergen, Norway
| | - Stig W Omholt
- Centre for Biodiversity Dynamics, Department of Biology, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
| | - Jonas Warringer
- Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway .,Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
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24
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A Statistical Guide to the Design of Deep Mutational Scanning Experiments. Genetics 2016; 204:77-87. [PMID: 27412710 DOI: 10.1534/genetics.116.190462] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Accepted: 06/29/2016] [Indexed: 12/21/2022] Open
Abstract
The characterization of the distribution of mutational effects is a key goal in evolutionary biology. Recently developed deep-sequencing approaches allow for accurate and simultaneous estimation of the fitness effects of hundreds of engineered mutations by monitoring their relative abundance across time points in a single bulk competition. Naturally, the achievable resolution of the estimated fitness effects depends on the specific experimental setup, the organism and type of mutations studied, and the sequencing technology utilized, among other factors. By means of analytical approximations and simulations, we provide guidelines for optimizing time-sampled deep-sequencing bulk competition experiments, focusing on the number of mutants, the sequencing depth, and the number of sampled time points. Our analytical results show that sampling more time points together with extending the duration of the experiment improves the achievable precision disproportionately compared with increasing the sequencing depth or reducing the number of competing mutants. Even if the duration of the experiment is fixed, sampling more time points and clustering these at the beginning and the end of the experiment increase experimental power and allow for efficient and precise assessment of the entire range of selection coefficients. Finally, we provide a formula for calculating the 95%-confidence interval for the measurement error estimate, which we implement as an interactive web tool. This allows for quantification of the maximum expected a priori precision of the experimental setup, as well as for a statistical threshold for determining deviations from neutrality for specific selection coefficient estimates.
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25
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Dillon MM, Rouillard NP, Van Dam B, Gallet R, Cooper VS. Diverse phenotypic and genetic responses to short-term selection in evolving Escherichia coli populations. Evolution 2016; 70:586-99. [PMID: 26995338 DOI: 10.1111/evo.12868] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Revised: 01/12/2016] [Accepted: 01/14/2016] [Indexed: 12/17/2022]
Abstract
Beneficial mutations fuel adaptation by altering phenotypes that enhance the fit of organisms to their environment. However, the phenotypic effects of mutations often depend on ecological context, making the distribution of effects across multiple environments essential to understanding the true nature of beneficial mutations. Studies that address both the genetic basis and ecological consequences of adaptive mutations remain rare. Here, we characterize the direct and pleiotropic fitness effects of a collection of 21 first-step beneficial mutants derived from naïve and adapted genotypes used in a long-term experimental evolution of Escherichia coli. Whole-genome sequencing was able to identify the majority of beneficial mutations. In contrast to previous studies, we find diverse fitness effects of mutations selected in a simple environment and few cases of genetic parallelism. The pleiotropic effects of these mutations were predominantly positive but some mutants were highly antagonistic in alternative environments. Further, the fitness effects of mutations derived from the adapted genotypes were dramatically reduced in nearly all environments. These findings suggest that many beneficial variants are accessible from a single point on the fitness landscape, and the fixation of alternative beneficial mutations may have dramatic consequences for niche breadth reduction via metabolic erosion.
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Affiliation(s)
- Marcus M Dillon
- Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, New Hampshire, 03824
| | - Nicholas P Rouillard
- Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, New Hampshire, 03824
| | - Brian Van Dam
- Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, New Hampshire, 03824
| | - Romain Gallet
- INRA - UMR BGPI Cirad TA A-54/K, Campus International de Baillarguet, 34398, Montpellier, Cedex 5, France
| | - Vaughn S Cooper
- Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, New Hampshire, 03824. .,Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, 15219.
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