1
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Molinet J, Stelkens R. The evolution of thermal performance curves in response to rising temperatures across the model genus yeast. Proc Natl Acad Sci U S A 2025; 122:e2423262122. [PMID: 40392856 DOI: 10.1073/pnas.2423262122] [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: 11/11/2024] [Accepted: 04/21/2025] [Indexed: 05/22/2025] Open
Abstract
The maintenance of biodiversity crucially depends on the evolutionary potential of populations to adapt to environmental change. Accelerating climate change and extreme temperature events urge us to better understand and forecast evolutionary responses. Here, we harnessed the power of experimental evolution with the microbial model system yeast (Saccharomyces spp.) to measure the evolutionary potential of populations to adapt to future warming, in real-time and across the entire phylogenetic diversity of the genus. We tracked the evolution of thermal performance curves (TPCs) in populations of eight genetically and ecologically diverse species under gradually increasing temperature conditions, from 25 to 40 °C, for up to 600 generations. We found that evolving toward higher critical thermal limits generally came at a cost, causing a decrease in both thermal tolerance and maximum growth performance. The evolution of TPCs varied significantly between species with strong genotype-by-environment interactions, revealing two main trajectories: i) Warm-tolerant species showed an increase in both optimum growth temperature and thermal tolerance, consistent with the "hotter is wider" hypothesis. ii) Cold-tolerant species on the other hand evolved larger thermal breadth and higher thermal limits, but suffered from reduced maximum performance overall, consistent with the generalist or "a jack of all temperatures is a master of none" hypothesis. In addition, cold-tolerant species never reached the warm-tolerant species' upper thermal limits. Our results show that adaptive strategies to increasing temperatures are complex, highlighting the need to consider both within and between species diversity when predicting and managing the impacts of climate change on populations.
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Affiliation(s)
- Jennifer Molinet
- Department of Zoology, Stockholm University, Stockholm 106 91, Sweden
| | - Rike Stelkens
- Department of Zoology, Stockholm University, Stockholm 106 91, Sweden
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2
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Liu Q, Wang Z, Cui J, Li J, Jiang C, Tan G, Qi H. Bacterial Cells Engineered with Synthetic Genetic Materials for Blind Testing of Random Mutagenesis. ACS Synth Biol 2025. [PMID: 40354669 DOI: 10.1021/acssynbio.5c00054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2025]
Abstract
Synthetic genetic materials, particularly those in genetically modified organisms (GMOs) deployed into complex environments, necessitate robust postmarket surveillance for continuous monitoring of both the materials and their applications throughout their lifecycle. Here, we introduce novel-coded genomic material for a blind mutation test that evaluates mutagenesis in synthetic genomic sequences without requiring direct sequence comparison. This test utilizes a Genome-Digest, which is embedded within essential genes, establishing mathematical correlation between the nucleotide sequence and codon order. This novel design allows for independent assessment of mutations by decoding the nucleotide sequence, thereby eliminating the need for reference sequences or extensive bioinformatic analysis. Furthermore, the test has the capability to analyze mixed genomic materials from a single sample and can be extended to the pooled testing of multiple samples as well. Building on this framework, we propose the 'Genome-ShockWatch' methodology. In proof-of-concept trials, it successfully detected mutations that exceeded a predefined threshold in long-read sequencing data from a yogurt sample containing Genome-Digest encoded Nissle 1917 E. coli cells and naturally occurring probiotic bacteria. Consequently, the Genome-Digest system provides a robust foundation for the routine surveillance and management of GMOs and related synthetic products, ensuring their safety and efficacy in diverse environmental contexts.
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Affiliation(s)
- Qian Liu
- School of Chemical Engineering and Technology, Tianjin University, Tianjin 300354, China
- State Key Laboratory of Synthetic Biology, Tianjin University, Tianjin 300354, China
| | - Zhaoguan Wang
- School of Chemical Engineering and Technology, Tianjin University, Tianjin 300354, China
- State Key Laboratory of Synthetic Biology, Tianjin University, Tianjin 300354, China
| | - Jingsong Cui
- School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China
| | - Jiawei Li
- School of Chemical Engineering and Technology, Tianjin University, Tianjin 300354, China
- State Key Laboratory of Synthetic Biology, Tianjin University, Tianjin 300354, China
| | - Changyue Jiang
- School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China
| | - Gaoxu Tan
- School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China
| | - Hao Qi
- School of Chemical Engineering and Technology, Tianjin University, Tianjin 300354, China
- State Key Laboratory of Synthetic Biology, Tianjin University, Tianjin 300354, China
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3
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Schiraldi A. Short- and Long-Term Evolution of Microbial Cultures: A Thermodynamic Perspective. Int J Mol Sci 2025; 26:4187. [PMID: 40362424 PMCID: PMC12071856 DOI: 10.3390/ijms26094187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2025] [Revised: 04/21/2025] [Accepted: 04/25/2025] [Indexed: 05/15/2025] Open
Abstract
A thermodynamic description of cell duplication reflects Odum's view of a feedback energy loop that sustains the transformation of the energy of substrates in the (higher quality) energy of new microbial cells with the dissipation of heat and the (lower quality) energy of catabolites. For a closed batch microbial culture, entropy increases during the whole growth and decay cycle, i.e., the production of entropy during the growth phase displays a rate proportional to the number of cell duplications per unit time, while during the decay phase, it depends on the death rate. Because of its high mobility, water is assumed to exhibit the same thermodynamic activity throughout the system. This assumption leads to the conclusion that an osmotic balance exists between cells and their surrounding medium, which, in a closed batch culture, can affect the rate and the extent of the microbial growth. Finally, the paper suggests a thermodynamic interpretation of the increase in fitness observed in a long-term evolution experiment (LTEE), based on the supposed exergy difference between the generating and generated cells in each duplication, which is also a measure of the "age" of the cells, i.e., aged cells die first. This produces microbial cultures richer in cells with enhanced duplication potential after the many thousand generations considered in an LTEE.
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Affiliation(s)
- Alberto Schiraldi
- Formerly at Department of Food Environment and Nutrition Sciences (DeFENS), University of Milan, 20133 Milan, Italy
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4
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Chihoub D, Pintard C, Lenski RE, Tenaillon O, Couce A. The evolution of robustness and fragility during long-term bacterial adaptation. Proc Natl Acad Sci U S A 2025; 122:e2501901122. [PMID: 40232797 PMCID: PMC12037012 DOI: 10.1073/pnas.2501901122] [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: 01/28/2025] [Accepted: 03/17/2025] [Indexed: 04/16/2025] Open
Abstract
Theory predicts that well-adapted populations may evolve mechanisms to counteract the inevitable influx of deleterious mutations. While mutational robustness can be directly selected in the laboratory, evidence for its spontaneous evolution during general adaptation is mixed. Moreover, whether robustness evolves to include pleiotropic effects remains largely unexplored. Here, we studied the effects of point mutations in the RNA polymerase of Escherichia coli over a 15,000-generation adaptive trajectory. Fitness effects of both beneficial and deleterious mutations were attenuated in fitter backgrounds. In contrast, pleiotropic effects became more severe and widespread with greater adaptation. These results show that trade-offs between robustness and fragility can evolve in regulatory networks, regardless of whether driven by adaptive or nonadaptive processes. More broadly, they illustrate how adaptation can generate hidden variability, with unpredictable evolutionary consequences in new environments.
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Affiliation(s)
- Doha Chihoub
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid, Madrid28223, Spain
| | - Coralie Pintard
- Centre de Recherche sur l’Inflammation, INSERM U1149, Université Paris Diderot, Paris75018, France
| | - Richard E. Lenski
- Department of Microbiology, Genetics, and Immunology, Michigan State University, East Lansing, MI48824
| | - Olivier Tenaillon
- Institut Cochin, INSERM U1016, Université Paris Cité, Paris75014, France
| | - Alejandro Couce
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid, Madrid28223, Spain
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5
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Martyushev LM. The Significance of the Entropic Measure of Time in Natural Sciences. ENTROPY (BASEL, SWITZERLAND) 2025; 27:425. [PMID: 40282659 PMCID: PMC12025688 DOI: 10.3390/e27040425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2025] [Revised: 04/07/2025] [Accepted: 04/11/2025] [Indexed: 04/29/2025]
Abstract
The review presents arguments emphasizing the importance of using the entropic measure of time (EMT) in the study of irreversible evolving systems. The possibilities of this measure for obtaining the laws of system evolution are shown. It is demonstrated that EMT provides a novel and unified perspective on the principle of maximum entropy production (MEPP), which is established in the physics of irreversible processes, as well as on the laws of growth and evolution proposed in biology. Essentially, for irreversible processes, the proposed approach allows, in a certain sense, to identify concepts such as the duration of existence, MEPP, and natural selection. EMT has been used to generalize prior results, indicating that the intrinsic time of a system is logarithmically dependent on extrinsic (Newtonian) time.
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Affiliation(s)
- Leonid M. Martyushev
- Technical Physics Department, Ural Federal University, 19 Mira St., 620002 Ekaterinburg, Russia;
- Institute of Industrial Ecology, Russian Academy of Sciences, 20 S. Kovalevskaya St., 620219 Ekaterinburg, Russia
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6
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Srienc F, Barrett J. Predicting the Rate Structure of an Evolved Metabolic Network. Metabolites 2025; 15:200. [PMID: 40137164 PMCID: PMC11944149 DOI: 10.3390/metabo15030200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2025] [Revised: 02/24/2025] [Accepted: 03/07/2025] [Indexed: 03/27/2025] Open
Abstract
Background: When glucose molecules are metabolized by a biological cell, the molecules are constrained to flow along distinct reaction trajectories, which are defined by the cell's underlying metabolic network. Methods: Using the computational technique of Elementary Mode Analysis, the entire set of all possible trajectories can be enumerated, effectively allowing metabolism to be viewed in a discretized space. Results: With the resulting set of Elementary Flux Modes (EMs), macroscopic fluxes, (of both mass and energy) that cross the cell envelope can be computed by a simple, linear combination of the individual EM trajectories. The challenge in this approach is that the usage probability of each EM is unknown. But, because the analytical framework we have adopted allows metabolism to be viewed in a discrete space, we can use the mathematics of statistical thermodynamics to derive the usage probabilities when the system entropy is maximized. The resulting probabilities, which obey a Boltzmann-type distribution, predict a rate structure for the metabolic network that is in remarkable agreement with experimentally measured rates of adaptively evolved E. coli strains. Conclusions: Thus, in principle, the intracellular dynamic properties of such bacteria can be predicted, using only the knowledge of the DNA sequence, to reconstruct the metabolic reaction network, and the measurement of the specific glucose uptake rate.
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Affiliation(s)
- Friedrich Srienc
- Department of Chemical Engineering and Materials Science and BioTechnology Institute, University of Minnesota, Minneapolis/St. Paul, MN 55455/55108, USA;
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7
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Shibai A, Izutsu M, Kotani H, Furusawa C. Quantitative analysis of relationship between mutation rate and speed of adaptation under antibiotic exposure in Escherichia coli. PLoS Genet 2025; 21:e1011627. [PMID: 40153704 PMCID: PMC11975134 DOI: 10.1371/journal.pgen.1011627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 04/07/2025] [Accepted: 02/17/2025] [Indexed: 03/30/2025] Open
Abstract
Mutations are the ultimate source of biological evolution that creates genetic variation in populations. Mutations can create new advantageous traits but can also potentially interfere with pre-existing organismal functions. Therefore, organisms may have evolved mutation rates to appropriate levels to maintain or improve their fitness. In this study, we aimed to experimentally quantify the relationship between the mutation rate and evolution of antibiotic resistance. We conducted an evolution experiment using 12 Escherichia coli mutator strains with increased mutation rates and five antibiotics. Our results demonstrated that the rate of adaptation generally increased with higher mutation rates, except in a single mutator strain with the highest mutation rate, which exhibited a significant decline in evolutionary speed. To further elucidate these findings, we developed a simple population dynamics model that successfully recapitulated the observed dependence of adaptation speed on mutation rate. These findings provide important insights into the evolution of mutation rate accompanied by the evolution.
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Affiliation(s)
- Atsushi Shibai
- Center for Biosystems Dynamics Research, RIKEN, Osaka, Japan
| | - Minako Izutsu
- Center for Biosystems Dynamics Research, RIKEN, Osaka, Japan
- Department of Microbiology, Genetics, and Immunology, Michigan State University, East Lansing, Michigan, United States of America
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, United States of America
- Ecology, Evolutionary Biology and Behavior Program, Michigan State University, East Lansing, Michigan, United States of America
| | - Hazuki Kotani
- Center for Biosystems Dynamics Research, RIKEN, Osaka, Japan
| | - Chikara Furusawa
- Center for Biosystems Dynamics Research, RIKEN, Osaka, Japan
- Universal Biology Institute, Graduate School of Science, The University of Tokyo, Tokyo, Japan
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8
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Stroud JT, Ratcliff WC. Long-term studies provide unique insights into evolution. Nature 2025; 639:589-601. [PMID: 40108318 DOI: 10.1038/s41586-025-08597-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Accepted: 01/06/2025] [Indexed: 03/22/2025]
Abstract
From experimental evolution in the laboratory to sustained measurements of natural selection in the wild, long-term studies have revolutionized our understanding of evolution. By directly investigating evolutionary dynamics in real time, these approaches have provided unparallelled insights into the complex interplay between evolutionary process and pattern. These approaches can reveal oscillations, stochastic fluctuations and systematic trends that unfold over extended periods, expose critical time lags between environmental shifts and population responses, and illuminate how subtle effects may accumulate into significant evolutionary patterns. Long-term studies can also reveal otherwise cryptic trends that unfold over extended periods, and offer the potential for serendipity: observing rare events that spur new evolutionary hypotheses and research directions. Despite the challenges of conducting long-term research, exacerbated by modern funding landscapes favouring short-term projects, the contributions of long-term studies to evolutionary biology are indispensable. This is particularly true in our rapidly changing, human-dominated world, where such studies offer a crucial window into how environmental changes and altered species interactions shape evolutionary trajectories. In this Review article, we showcase the groundbreaking discoveries of long-term evolutionary studies, underscoring their crucial role in advancing our understanding of the complex nature of evolution across multiple systems and timescales.
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Affiliation(s)
- James T Stroud
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA.
| | - William C Ratcliff
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
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9
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Isaksson H, Lind P, Libby E. Adaptive evolutionary trajectories in complexity: Transitions between unicellularity and facultative differentiated multicellularity. Proc Natl Acad Sci U S A 2025; 122:e2411692122. [PMID: 39841150 PMCID: PMC11789074 DOI: 10.1073/pnas.2411692122] [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: 06/12/2024] [Accepted: 12/12/2024] [Indexed: 01/23/2025] Open
Abstract
Multicellularity spans a wide gamut in terms of complexity, from simple clonal clusters of cells to large-scale organisms composed of differentiated cells and tissues. While recent experiments have demonstrated that simple forms of multicellularity can readily evolve in response to different selective pressures, it is unknown if continued exposure to those same selective pressures will result in the evolution of increased multicellular complexity. We use mathematical models to consider the adaptive trajectories of unicellular organisms exposed to periodic bouts of abiotic stress, such as drought or antibiotics. Populations can improve survival in response to the stress by evolving multicellularity or cell differentiation-or both; however, these responses have associated costs when the stress is absent. We define a parameter space of fitness-relevant traits and identify where multicellularity, differentiation, or their combination is fittest. We then study the effects of adaptation by allowing populations to fix mutations that improve their fitness. We find that while the same mutation can be beneficial to populations of different complexity, e.g., strict unicellularity or life cycles with stages of differentiated multicellularity, the magnitudes of their effects can differ and alter which is fittest. As a result, we observe adaptive trajectories that gain and lose complexity. We also show that the order of mutations, historical contingency, can cause some transitions to be permanent in the absence of neutral evolution. Ultimately, we find that continued exposure to a selective driver for multicellularity can either lead to increasing complexity or a return to unicellularity.
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Affiliation(s)
- Hanna Isaksson
- Department of Mathematics and Mathematical Statistics, Umeå University, Umeå90187, Sweden
- IceLab, Umeå University, Umeå90187, Sweden
| | - Peter Lind
- IceLab, Umeå University, Umeå90187, Sweden
- Department of Molecular Biology, Umeå University, Umeå90187, Sweden
- Umeå Centre for Microbial Research, Umeå University, Umeå90187, Sweden
| | - Eric Libby
- Department of Mathematics and Mathematical Statistics, Umeå University, Umeå90187, Sweden
- IceLab, Umeå University, Umeå90187, Sweden
- Umeå Centre for Microbial Research, Umeå University, Umeå90187, Sweden
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10
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Sumanarathne AS, Gerstein AC. Quantifying Competitive Fitness in Yeast with High-Throughput Fluorescence Microscopy Imaging. Curr Protoc 2025; 5:e70093. [PMID: 39869052 PMCID: PMC11771579 DOI: 10.1002/cpz1.70093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2025]
Abstract
Competitive fitness is a fundamental concept in evolutionary biology that captures the ability of organisms to survive, reproduce, and compete for resources in their environment. Competitive fitness is typically assessed in the lab by growing two or more competitors together and measuring the frequency of each at multiple time points. Traditional microbial competitive fitness assays are labor intensive and involve plating on solid medium and counting colonies. Here, we describe a method to quantitatively measure competitive fitness using fluorescence microscopic imaging and machine-learning-enabled image analysis to directly count the number of cells from each competitor in the mixed population. This high-throughput, primarily automated, and efficient process gives accurate and reproducible results for competitive fitness. Here, we describe the entire process, from sample preparation through microscopy to quantification, and provide instructions and scripts for the image analysis, fitness calculations, and sample data visualizations. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Sample preparation Basic Protocol 2: Photographing fluorescing and non-fluorescing cells using an EVOS microscope Basic Protocol 3: Counting fluorescing and non-fluorescing cells with Orbit Image Analysis Basic Protocol 4: Getting the average cell counts per well and changing the file names Basic Protocol 5: Calculating competitive fitness using R.
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Affiliation(s)
| | - Aleeza C. Gerstein
- Department of MicrobiologyUniversity of ManitobaWinnipegManitobaCanada
- Department of StatisticsUniversity of ManitobaWinnipegManitobaCanada
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11
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Lemée P, Charron R, Bridier A. Genomic Pipeline for Analysis of Mutational Events in Bacteria. Methods Mol Biol 2025; 2852:211-222. [PMID: 39235747 DOI: 10.1007/978-1-0716-4100-2_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/06/2024]
Abstract
Unveiling the strategies of bacterial adaptation to stress constitute a challenging area of research. The understanding of mechanisms governing emergence of resistance to antimicrobials is of particular importance regarding the increasing threat of antibiotic resistance on public health worldwide. In the last decades, the fast democratization of sequencing technologies along with the development of dedicated bioinformatical tools to process data offered new opportunities to characterize genomic variations underlying bacterial adaptation. Thereby, research teams have now the possibility to dive deeper in the deciphering of bacterial adaptive mechanisms through the identification of specific genetic targets mediating survival to stress. In this chapter, we proposed a step-by-step bioinformatical pipeline enabling the identification of mutational events underlying biocidal stress adaptation associated with antimicrobial resistance development using Escherichia marmotae as an illustrative model.
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Affiliation(s)
- Pierre Lemée
- Antibiotics, Biocides, Residues and Resistance (AB2R) Unit, Fougères Laboratory, French Agency for Food, Environmental and Occupational Health & Safety (ANSES), Fougères, France
| | - Raphaël Charron
- Antibiotics, Biocides, Residues and Resistance (AB2R) Unit, Fougères Laboratory, French Agency for Food, Environmental and Occupational Health & Safety (ANSES), Fougères, France
- Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute, Jouy-en-Josas, France
| | - Arnaud Bridier
- Antibiotics, Biocides, Residues and Resistance (AB2R) Unit, Fougères Laboratory, French Agency for Food, Environmental and Occupational Health & Safety (ANSES), Fougères, France.
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12
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Banse P, Luiselli J, Parsons DP, Grohens T, Foley M, Trujillo L, Rouzaud‐Cornabas J, Knibbe C, Beslon G. Forward-in-time simulation of chromosomal rearrangements: The invisible backbone that sustains long-term adaptation. Mol Ecol 2024; 33:e17234. [PMID: 38078552 PMCID: PMC11628651 DOI: 10.1111/mec.17234] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 11/20/2023] [Accepted: 11/24/2023] [Indexed: 12/11/2024]
Abstract
While chromosomal rearrangements are ubiquitous in all domains of life, very little is known about their evolutionary significance, mostly because, apart from a few specifically studied and well-documented mechanisms (interaction with recombination, gene duplication, etc.), very few models take them into account. As a consequence, we lack a general theory to account for their direct and indirect contributions to evolution. Here, we propose Aevol, a forward-in-time simulation platform specifically dedicated to unravelling the evolutionary significance of chromosomal rearrangements (CR) compared to local mutations (LM). Using the platform, we evolve populations of organisms in four conditions characterized by an increasing diversity of mutational operators-from substitutions alone to a mix of substitutions, InDels and CR-but with a constant global mutational rate. Despite being almost invisible in the phylogeny owing to the scarcity of their fixation in the lineages, we show that CR make a decisive contribution to the evolutionary dynamics by comparing the outcome in these four conditions. As expected, chromosomal rearrangements allow fast expansion of the gene repertoire through gene duplication, but they also reduce the effect of diminishing-returns epistasis, hence sustaining adaptation on the long-run. At last, we show that chromosomal rearrangements tightly regulate the size of the genome through indirect selection for reproductive robustness. Overall, these results confirm the need to improve our theoretical understanding of the contribution of chromosomal rearrangements to evolution and show that dedicated platforms like Aevol can efficiently contribute to this agenda.
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Affiliation(s)
- Paul Banse
- Université de Lyon, INSA‐Lyon, Inria, CNRS, Université Claude Bernard Lyon 1, ECL, Université Lumière Lyon 2, LIRIS UMR5205LyonFrance
| | - Juliette Luiselli
- Université de Lyon, INSA‐Lyon, Inria, CNRS, Université Claude Bernard Lyon 1, ECL, Université Lumière Lyon 2, LIRIS UMR5205LyonFrance
| | - David P. Parsons
- Université de Lyon, INSA‐Lyon, Inria, CNRS, Université Claude Bernard Lyon 1, ECL, Université Lumière Lyon 2, LIRIS UMR5205LyonFrance
| | - Théotime Grohens
- Centre for Genomic Regulation (CRG)The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | - Marco Foley
- Université de Lyon, INSA‐Lyon, Inria, CNRS, Université Claude Bernard Lyon 1, ECL, Université Lumière Lyon 2, LIRIS UMR5205LyonFrance
| | - Leonardo Trujillo
- Université de Lyon, INSA‐Lyon, Inria, CNRS, Université Claude Bernard Lyon 1, ECL, Université Lumière Lyon 2, LIRIS UMR5205LyonFrance
| | - Jonathan Rouzaud‐Cornabas
- Université de Lyon, INSA‐Lyon, Inria, CNRS, Université Claude Bernard Lyon 1, ECL, Université Lumière Lyon 2, LIRIS UMR5205LyonFrance
| | - Carole Knibbe
- Université de Lyon, INSA‐Lyon, Inria, Université Claude Bernard Lyon 1, Inserm, INRAE, CarMeN laboratoryPierre‐BéniteFrance
| | - Guillaume Beslon
- Université de Lyon, INSA‐Lyon, Inria, CNRS, Université Claude Bernard Lyon 1, ECL, Université Lumière Lyon 2, LIRIS UMR5205LyonFrance
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13
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Kinsler G, Li Y, Sherlock G, Petrov DA. A high-resolution two-step evolution experiment in yeast reveals a shift from pleiotropic to modular adaptation. PLoS Biol 2024; 22:e3002848. [PMID: 39636818 PMCID: PMC11620474 DOI: 10.1371/journal.pbio.3002848] [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: 04/19/2024] [Accepted: 09/17/2024] [Indexed: 12/07/2024] Open
Abstract
Evolution by natural selection is expected to be a slow and gradual process. In particular, the mutations that drive evolution are predicted to be small and modular, incrementally improving a small number of traits. However, adaptive mutations identified early in microbial evolution experiments, cancer, and other systems often provide substantial fitness gains and pleiotropically improve multiple traits at once. We asked whether such pleiotropically adaptive mutations are common throughout adaptation or are instead a rare feature of early steps in evolution that tend to target key signaling pathways. To do so, we conducted barcoded second-step evolution experiments initiated from 5 first-step mutations identified from a prior yeast evolution experiment. We then isolated hundreds of second-step mutations from these evolution experiments, measured their fitness and performance in several growth phases, and conducted whole genome sequencing of the second-step clones. Here, we found that while the vast majority of mutants isolated from the first-step of evolution in this condition show patterns of pleiotropic adaptation-improving both performance in fermentation and respiration growth phases-second-step mutations show a shift towards modular adaptation, mostly improving respiration performance and only rarely improving fermentation performance. We also identified a shift in the molecular basis of adaptation from genes in cellular signaling pathways towards genes involved in respiration and mitochondrial function. Our results suggest that the genes in cellular signaling pathways may be more likely to provide large, adaptively pleiotropic benefits to the organism due to their ability to coherently affect many phenotypes at once. As such, these genes may serve as the source of pleiotropic adaptation in the early stages of evolution, and once these become exhausted, organisms then adapt more gradually, acquiring smaller, more modular mutations.
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Affiliation(s)
- Grant Kinsler
- Department of Biology, Stanford University, Stanford, California, United States of America
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Yuping Li
- Department of Genetics, Stanford University, Stanford, California, United States of America
- Department of Microbiology & Immunology, University of California, San Francisco, San Francisco, United States of America
| | - Gavin Sherlock
- Department of Genetics, Stanford University, Stanford, California, United States of America
| | - Dmitri A. Petrov
- Department of Biology, Stanford University, Stanford, California, United States of America
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14
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Ingelman H, Heffernan JK, Harris A, Brown SD, Shaikh KM, Saqib AY, Pinheiro MJ, de Lima LA, Martinez KR, Gonzalez-Garcia RA, Hawkins G, Daleiden J, Tran L, Zeleznik H, Jensen RO, Reynoso V, Schindel H, Jänes J, Simpson SD, Köpke M, Marcellin E, Valgepea K. Autotrophic adaptive laboratory evolution of the acetogen Clostridium autoethanogenum delivers the gas-fermenting strain LAbrini with superior growth, products, and robustness. N Biotechnol 2024; 83:1-15. [PMID: 38871051 DOI: 10.1016/j.nbt.2024.06.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 06/05/2024] [Accepted: 06/10/2024] [Indexed: 06/15/2024]
Abstract
Microbes able to convert gaseous one-carbon (C1) waste feedstocks are increasingly important to transition to the sustainable production of renewable chemicals and fuels. Acetogens are interesting biocatalysts since gas fermentation using Clostridium autoethanogenum has been commercialised. However, most acetogen strains need complex nutrients, display slow growth, and are not robust for bioreactor fermentations. In this work, we used three different and independent adaptive laboratory evolution (ALE) strategies to evolve the wild-type C. autoethanogenum to grow faster, without yeast extract and to be robust in operating continuous bioreactor cultures. Multiple evolved strains with improved phenotypes were isolated on minimal media with one strain, named "LAbrini", exhibiting superior performance regarding the maximum specific growth rate, product profile, and robustness in continuous cultures. Whole-genome sequencing of the evolved strains identified 25 mutations. Of particular interest are two genes that acquired seven different mutations across the three ALE strategies, potentially as a result of convergent evolution. Reverse genetic engineering of mutations in potentially sporulation-related genes CLAU_3129 (spo0A) and CLAU_1957 recovered all three superior features of our ALE strains through triggering significant proteomic rearrangements. This work provides a robust C. autoethanogenum strain "LAbrini" to accelerate phenotyping and genetic engineering and to better understand acetogen metabolism.
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Affiliation(s)
- Henri Ingelman
- ERA Chair in Gas Fermentation Technologies, Institute of Bioengineering, University of Tartu, 50411 Tartu, Estonia
| | - James K Heffernan
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, 4072 St. Lucia, Australia
| | | | | | | | - Asfand Yar Saqib
- ERA Chair in Gas Fermentation Technologies, Institute of Bioengineering, University of Tartu, 50411 Tartu, Estonia
| | - Marina J Pinheiro
- ERA Chair in Gas Fermentation Technologies, Institute of Bioengineering, University of Tartu, 50411 Tartu, Estonia
| | - Lorena Azevedo de Lima
- ERA Chair in Gas Fermentation Technologies, Institute of Bioengineering, University of Tartu, 50411 Tartu, Estonia
| | - Karen Rodriguez Martinez
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, 4072 St. Lucia, Australia
| | - Ricardo A Gonzalez-Garcia
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, 4072 St. Lucia, Australia
| | | | | | | | | | | | | | | | - Jürgen Jänes
- Institute of Molecular Systems Biology, ETH Zürich, 8049 Zürich, Switzerland
| | | | | | - Esteban Marcellin
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, 4072 St. Lucia, Australia.
| | - Kaspar Valgepea
- ERA Chair in Gas Fermentation Technologies, Institute of Bioengineering, University of Tartu, 50411 Tartu, Estonia.
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15
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Ferrare JT, Good BH. Evolution of evolvability in rapidly adapting populations. Nat Ecol Evol 2024; 8:2085-2096. [PMID: 39261599 PMCID: PMC12049861 DOI: 10.1038/s41559-024-02527-0] [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: 12/15/2023] [Accepted: 07/29/2024] [Indexed: 09/13/2024]
Abstract
Mutations can alter the short-term fitness of an organism, as well as the rates and benefits of future mutations. While numerous examples of these evolvability modifiers have been observed in rapidly adapting microbial populations, existing theory struggles to predict when they will be favoured by natural selection. Here we develop a mathematical framework for predicting the fates of genetic variants that modify the rates and benefits of future mutations in linked genomic regions. We derive analytical expressions showing how the fixation probabilities of these variants depend on the size of the population and the diversity of competing mutations. We find that competition between linked mutations can dramatically enhance selection for modifiers that increase the benefits of future mutations, even when they impose a strong direct cost on fitness. However, we also find that modest direct benefits can be sufficient to drive evolutionary dead ends to fixation. Our results suggest that subtle differences in evolvability could play an important role in shaping the long-term success of genetic variants in rapidly evolving microbial populations.
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Affiliation(s)
| | - Benjamin H Good
- Department of Applied Physics, Stanford University, Stanford, CA, USA.
- Department of Biology, Stanford University, Stanford, CA, USA.
- Chan Zuckerberg Biohub - San Francisco, San Francisco, CA, USA.
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16
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Natalino M, Fumasoni M. Compensatory Evolution to DNA Replication Stress is Robust to Nutrient Availability. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.29.620637. [PMID: 39553989 PMCID: PMC11565888 DOI: 10.1101/2024.10.29.620637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2024]
Abstract
Evolutionary repair refers to the compensatory evolution that follows perturbations in cellular processes. While evolutionary trajectories are often reproducible, other studies suggest they are shaped by genotype-by-environment (GxE) interactions. Here, we test the predictability of evolutionary repair in response to DNA replication stress-a severe perturbation impairing the conserved mechanisms of DNA synthesis, resulting in genetic instability. We conducted high-throughput experimental evolution on Saccharomyces cerevisiae experiencing constitutive replication stress, grown under different glucose availabilities. We found that glucose levels impact the physiology and adaptation rate of replication stress mutants. However, the genetics of adaptation show remarkable robustness across environments. Recurrent mutations collectively recapitulated the fitness of evolved lines and are advantageous across macronutrient availability. We also identified a novel role of the mediator complex of RNA polymerase II in adaptation to replicative stress. Our results highlight the robustness and predictability of evolutionary repair mechanisms to DNA replication stress and provide new insights into the evolutionary aspects of genome stability, with potential implications for understanding cancer development.
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Affiliation(s)
- Mariana Natalino
- Gulbenkian Institute for Molecular Medicine (GIMM), Lisbon, Portugal
| | - Marco Fumasoni
- Gulbenkian Institute for Molecular Medicine (GIMM), Lisbon, Portugal
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17
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Gusev AO, Martyushev LM. The Relationship Between Astronomical and Developmental Times Emerging in Modeling the Evolution of Agents. ENTROPY (BASEL, SWITZERLAND) 2024; 26:887. [PMID: 39451963 PMCID: PMC11506980 DOI: 10.3390/e26100887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2024] [Revised: 10/17/2024] [Accepted: 10/20/2024] [Indexed: 10/26/2024]
Abstract
The simplest evolutionary model for catching prey by an agent (predator) is considered. The simulation is performed on the basis of a software-emulated Intel i8080 processor. Maximizing the number of catches is chosen as the objective function. This function is associated with energy dissipation and developmental time. It is shown that during Darwinian evolution, agents with an initially a random set of processor commands subsequently acquire a successful catching skill. It is found that in the process of evolution, a logarithmic relationship between astronomical and developmental times arises in agents. This result is important for the ideas available in the literature about the close connection of such concepts as time, Darwinian selection, and the maximization of entropy production.
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Affiliation(s)
- Alexander O. Gusev
- Technical Physics Department, Ural Federal University, Mira St. 19, 620062 Ekaterinburg, Russia
| | - Leonid M. Martyushev
- Technical Physics Department, Ural Federal University, Mira St. 19, 620062 Ekaterinburg, Russia
- Institute of Industrial Ecology, Russian Academy of Sciences, S Kovalevskoi St. 20a, 620219 Ekaterinburg, Russia
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18
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Ardell S, Martsul A, Johnson MS, Kryazhimskiy S. Environment-independent distribution of mutational effects emerges from microscopic epistasis. Science 2024; 386:87-92. [PMID: 39361740 PMCID: PMC11580693 DOI: 10.1126/science.adn0753] [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: 11/21/2023] [Accepted: 08/22/2024] [Indexed: 10/05/2024]
Abstract
Predicting how new mutations alter phenotypes is difficult because mutational effects vary across genotypes and environments. Recently discovered global epistasis, in which the fitness effects of mutations scale with the fitness of the background genotype, can improve predictions, but how the environment modulates this scaling is unknown. We measured the fitness effects of ~100 insertion mutations in 42 strains of Saccharomyces cerevisiae in six laboratory environments and found that the global epistasis scaling is nearly invariant across environments. Instead, the environment tunes one global parameter, the background fitness at which most mutations switch sign. As a consequence, the distribution of mutational effects is predictable across genotypes and environments. Our results suggest that the effective dimensionality of genotype-to-phenotype maps across environments is surprisingly low.
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Affiliation(s)
- Sarah Ardell
- Department of Ecology, Behavior and Evolution, University of California San Diego, La Jolla, CA 92093
| | - Alena Martsul
- Department of Ecology, Behavior and Evolution, University of California San Diego, La Jolla, CA 92093
| | - Milo S. Johnson
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA 94720
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Sergey Kryazhimskiy
- Department of Ecology, Behavior and Evolution, University of California San Diego, La Jolla, CA 92093
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19
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Banse P, Elena SF, Beslon G. Innovation in viruses: fitness valley crossing, neutral landscapes, or just duplications? Virus Evol 2024; 10:veae078. [PMID: 39386076 PMCID: PMC11463231 DOI: 10.1093/ve/veae078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 07/19/2024] [Accepted: 09/18/2024] [Indexed: 10/12/2024] Open
Abstract
Viruses evolve by periods of relative stasis interleaved with sudden, rapid series of mutation fixations, known as evolutionary bursts. These bursts can be triggered by external factors, such as environmental changes, antiviral therapies, or spill-overs from reservoirs into novel host species. However, it has also been suggested that bursts may result from the intrinsic evolutionary dynamics of viruses. Indeed, bursts could be caused by fitness valley crossing, or a neutral exploration of a fitness plateau until an escape mutant is found. In order to investigate the importance of these intrinsic causes of evolutionary bursts, we used a simulation software package to perform massive evolution experiments of viral-like genomes. We tested two conditions: (i) after an external change and (ii) in a constant environment, with the latter condition guaranteeing the absence of an external triggering factor. As expected, an external change was almost systematically followed by an evolutionary burst. However, we also observed bursts in the constant environment as well, albeit much less frequently. We analyzed how many of these bursts are triggered by deleterious, quasi-neutral, or beneficial mutations and show that, while bursts can occasionally be triggered by valley crossing or traveling along neutral ridges, many of them were triggered by chromosomal rearrangements and, in particular, segmental duplications. Our results suggest that combinatorial differences between the different mutation types lead to punctuated evolutionary dynamics, with long periods of stasis occasionally interrupted by short periods of rapid evolution, akin to what is observed in virus evolution.
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Affiliation(s)
- Paul Banse
- INSA Lyon, INRIA, CNRS, Universite Claude Bernard Lyon 1, Ecole Centrale de Lyon, Université Lumière Lyon 2, LIRIS, UMR5205, Villeurbanne 69621, France
| | - Santiago F Elena
- Instituto de Biología Integrativa de Sistemas (I2SysBio), CSIC-Universitat de València, Catedrático Agustín Escardino 9, Paterna, Valencia 46980, Spain
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
| | - Guillaume Beslon
- INSA Lyon, INRIA, CNRS, Universite Claude Bernard Lyon 1, Ecole Centrale de Lyon, Université Lumière Lyon 2, LIRIS, UMR5205, Villeurbanne 69621, France
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20
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Izutsu M, Lake DM, Matson ZWD, Dodson JP, Lenski RE. Effects of periodic bottlenecks on the dynamics of adaptive evolution in microbial populations. MICROBIOLOGY (READING, ENGLAND) 2024; 170:001494. [PMID: 39292609 PMCID: PMC11410044 DOI: 10.1099/mic.0.001494] [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: 08/06/2024] [Accepted: 08/14/2024] [Indexed: 09/20/2024]
Abstract
Population bottlenecks can impact the rate of adaptation in evolving populations. On the one hand, each bottleneck reduces the genetic variation that fuels adaptation. On the other hand, each founder that survives a bottleneck can undergo more generations and leave more descendants in a resource-limited environment, which allows surviving beneficial mutations to spread more quickly. A theoretical model predicted that the rate of fitness gains should be maximized using ~8-fold dilutions. Here we investigate the impact of repeated bottlenecks on the dynamics of adaptation using numerical simulations and experimental populations of Escherichia coli. Our simulations confirm the model's prediction when populations evolve in a regime where beneficial mutations are rare and waiting times between successful mutations are long. However, more extreme dilutions maximize fitness gains in simulations when beneficial mutations are common and clonal interference prevents most of them from fixing. To examine these predictions, we propagated 48 E. coli populations with 2-, 8-, 100-, and 1000-fold dilutions for 150 days. Adaptation began earlier and fitness gains were greater with 100- and 1000-fold dilutions than with 8-fold dilutions, consistent with the simulations when beneficial mutations are common. However, the selection pressures in the 2-fold treatment were qualitatively different from the other treatments, violating a critical assumption of the model and simulations. Thus, varying the dilution factor during periodic bottlenecks can have multiple effects on the dynamics of adaptation caused by differential losses of diversity, different numbers of generations, and altered selection.
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Affiliation(s)
- Minako Izutsu
- Department of Microbiology, Genetics and Immunology, Michigan State University, East Lansing, MI, USA
- Ecology, Evolution and Behavior Program, Michigan State University, East Lansing, MI, USA
| | - Devin M. Lake
- Ecology, Evolution and Behavior Program, Michigan State University, East Lansing, MI, USA
- Department of Integrative Biology, Michigan State University, East Lansing, MI, USA
| | - Zachary W. D. Matson
- Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Jack P. Dodson
- Department of Microbiology, Genetics and Immunology, Michigan State University, East Lansing, MI, USA
| | - Richard E. Lenski
- Department of Microbiology, Genetics and Immunology, Michigan State University, East Lansing, MI, USA
- Ecology, Evolution and Behavior Program, Michigan State University, East Lansing, MI, USA
- Department of Integrative Biology, Michigan State University, East Lansing, MI, USA
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21
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Ardell S, Martsul A, Johnson MS, Kryazhimskiy S. Environment-independent distribution of mutational effects emerges from microscopic epistasis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.18.567655. [PMID: 38014325 PMCID: PMC10680819 DOI: 10.1101/2023.11.18.567655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Predicting how new mutations alter phenotypes is difficult because mutational effects vary across genotypes and environments. Recently discovered global epistasis, where the fitness effects of mutations scale with the fitness of the background genotype, can improve predictions, but how the environment modulates this scaling is unknown. We measured the fitness effects of ~100 insertion mutations in 42 strains of Saccharomyces cerevisiae in six laboratory environments and found that the global-epistasis scaling is nearly invariant across environments. Instead, the environment tunes one global parameter, the background fitness at which most mutations switch sign. As a consequence, the distribution of mutational effects is predictable across genotypes and environments. Our results suggest that the effective dimensionality of genotype-to-phenotype maps across environments is surprisingly low.
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Affiliation(s)
- Sarah Ardell
- Department of Ecology, Behavior and Evolution, University of California San Diego, La Jolla, CA 92093
| | - Alena Martsul
- Department of Ecology, Behavior and Evolution, University of California San Diego, La Jolla, CA 92093
| | - Milo S. Johnson
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA 94720
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Sergey Kryazhimskiy
- Department of Ecology, Behavior and Evolution, University of California San Diego, La Jolla, CA 92093
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22
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Chen P, Zhang J. The loci of environmental adaptation in a model eukaryote. Nat Commun 2024; 15:5672. [PMID: 38971805 PMCID: PMC11227561 DOI: 10.1038/s41467-024-50002-y] [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: 12/19/2023] [Accepted: 06/25/2024] [Indexed: 07/08/2024] Open
Abstract
While the underlying genetic changes have been uncovered in some cases of adaptive evolution, the lack of a systematic study prevents a general understanding of the genomic basis of adaptation. For example, it is unclear whether protein-coding or noncoding mutations are more important to adaptive evolution and whether adaptations to different environments are brought by genetic changes distributed in diverse genes and biological processes or concentrated in a core set. We here perform laboratory evolution of 3360 Saccharomyces cerevisiae populations in 252 environments of varying levels of stress. We find the yeast adaptations to be primarily fueled by large-effect coding mutations overrepresented in a relatively small gene set, despite prevalent antagonistic pleiotropy across environments. Populations generally adapt faster in more stressful environments, partly because of greater benefits of the same mutations in more stressful environments. These and other findings from this model eukaryote help unravel the genomic principles of environmental adaptation.
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Affiliation(s)
- Piaopiao Chen
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, 48109, USA
- College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, 48109, USA.
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23
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Tarkington J, Zufall RA. Correlated responses to selection across diverse environments during experimental evolution of Tetrahymena thermophila. Ecol Evol 2024; 14:e11395. [PMID: 39045496 PMCID: PMC11264346 DOI: 10.1002/ece3.11395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 04/19/2024] [Accepted: 04/26/2024] [Indexed: 07/25/2024] Open
Abstract
Correlated responses to selection have long been observed and studied; however, it remains unclear when they will arise, and in what direction. To contribute to a growing understanding of correlated responses to selection, we used experimental evolution of the ciliate Tetrahymena thermophila to study direct and correlated responses in a variety of different environmental conditions. One experiment focused on adaptation to two different temperatures and the correlated responses across temperatures. Another experiment used inhibitory concentrations of a variety of compounds to test direct and correlated responses to selection. We found that all populations adapted to the environments in which they evolved. We also found many cases of correlated evolution across environments; few conditions resulted in trade-offs and many resulted in a positive correlated response. Surprisingly, in many instances, the correlated response was of a larger magnitude than the direct response. We find that ancestral fitness predicts the extent of adaptation, consistent with diminishing returns epistasis. Unexpectedly, we also find that this pattern of diminishing returns holds across environments regardless of the environment in which evolution occurs. We also found that the correlated response is asymmetric across environments, that is, the fitness of a population evolved in one environment and assayed in a second was inversely related to the fitness of a population evolved in the second environment and assayed in the first. These results support the notion that positive correlated responses to selection across environments are frequent, and worth further study.
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Affiliation(s)
- Jason Tarkington
- Department of Biology and BiochemistryUniversity of HoustonHoustonTexasUSA
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
| | - Rebecca A. Zufall
- Department of Biology and BiochemistryUniversity of HoustonHoustonTexasUSA
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24
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Bramwell G, DeGregori J, Thomas F, Ujvari B. Transmissible cancers, the genomes that do not melt down. Evolution 2024; 78:1205-1211. [PMID: 38656785 DOI: 10.1093/evolut/qpae063] [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: 11/05/2023] [Revised: 04/08/2024] [Accepted: 04/19/2024] [Indexed: 04/26/2024]
Abstract
Evolutionary theory predicts that the accumulation of deleterious mutations in asexually reproducing organisms should lead to genomic decay. Clonally reproducing cell lines, i.e., transmissible cancers, when cells are transmitted as allografts/xenografts, break these rules and survive for centuries and millennia. The currently known 11 transmissible cancer lineages occur in dogs (canine venereal tumour disease), in Tasmanian devils (devil facial tumor diseases, DFT1 and DFT2), and in bivalves (bivalve transmissible neoplasia). Despite the mutation loads of these cell lines being much higher than observed in human cancers, they have not been eliminated in space and time. Here, we provide potential explanations for how these fascinating cell lines may have overcome the fitness decline due to the progressive accumulation of deleterious mutations and propose that the high mutation load may carry an indirect positive fitness outcome. We offer ideas on how these host-pathogen systems could be used to answer outstanding questions in evolutionary biology. The recent studies on the evolution of these clonal pathogens reveal key mechanistic insight into transmissible cancer genomes, information that is essential for future studies investigating how these contagious cancer cell lines can repeatedly evade immune recognition, evolve, and survive in the landscape of highly diverse hosts.
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Affiliation(s)
- Georgina Bramwell
- School of Life and Environmental Sciences, Faculty of Science, Engineering and Built Environment, Deakin University, 75 Pigdons Road, Waurn Ponds, VIC 3216, Australia
| | - James DeGregori
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Frédéric Thomas
- CREEC, UMR IRD 224-CNRS 5290, Université de Montpellier, Montpellier, France
| | - Beata Ujvari
- School of Life and Environmental Sciences, Faculty of Science, Engineering and Built Environment, Deakin University, 75 Pigdons Road, Waurn Ponds, VIC 3216, Australia
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25
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Zion S, Katz S, Hershberg R. Escherichia coli adaptation under prolonged resource exhaustion is characterized by extreme parallelism and frequent historical contingency. PLoS Genet 2024; 20:e1011333. [PMID: 38885285 PMCID: PMC11213340 DOI: 10.1371/journal.pgen.1011333] [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: 01/10/2024] [Revised: 06/28/2024] [Accepted: 06/05/2024] [Indexed: 06/20/2024] Open
Abstract
Like many other non-sporulating bacterial species, Escherichia coli is able to survive prolonged periods of resource exhaustion, by entering a state of growth called long-term stationary phase (LTSP). In July 2015, we initiated a set of evolutionary experiments aimed at characterizing the dynamics of E. coli adaptation under LTSP. In these experiments populations of E. coli were allowed to initially grow on fresh rich media, but were not provided with any new external growth resources since their establishment. Utilizing whole genome sequencing data obtained for hundreds of clones sampled at 12 time points spanning the first six years of these experiments, we reveal several novel aspects of the dynamics of adaptation. First, we show that E. coli continuously adapts genetically, up to six years under resource exhaustion, through the highly convergent accumulation of mutations. We further show that upon entry into LTSP, long-lasting lineages are established. This lineage structure is in itself convergent, with similar lineages arising across independently evolving populations. The high parallelism with which adaptations occur under LTSP, combined with the LTSP populations' lineage structure, enable us to screen for pairs of loci displaying a significant association in the occurrence of mutations, suggestive of a historical contingency. We find that such associations are highly frequent and that a third of convergently mutated loci are involved in at least one such association. Combined our results demonstrate that LTSP adaptation is characterized by remarkably high parallelism and frequent historical contingency.
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Affiliation(s)
- Shira Zion
- Rachel & Menachem Mendelovitch Evolutionary Processes of Mutation & Natural Selection Research Laboratory, Department of Genetics and Developmental Biology, the Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Sophia Katz
- Rachel & Menachem Mendelovitch Evolutionary Processes of Mutation & Natural Selection Research Laboratory, Department of Genetics and Developmental Biology, the Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Ruth Hershberg
- Rachel & Menachem Mendelovitch Evolutionary Processes of Mutation & Natural Selection Research Laboratory, Department of Genetics and Developmental Biology, the Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
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26
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Root-Bernstein RS, Bernstein MI. 'Evolutionary poker': an agent-based model of interactome emergence and epistasis tested against Lenski's long-term E. coli experiments. J Physiol 2024; 602:2511-2535. [PMID: 37707489 DOI: 10.1113/jp284421] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 08/23/2023] [Indexed: 09/15/2023] Open
Abstract
A simple agent-based model is presented that produces results matching the experimental data found by Lenski's group for ≤50,000 generations of Escherichia coli bacteria under continuous selective pressure. Although various mathematical models have been devised previously to model the Lenski data, the present model has advantages in terms of overall simplicity and conceptual accessibility. The model also clearly illustrates a number of features of the evolutionary process that are otherwise not obvious, such as the roles of epistasis and historical contingency in adaptation and why evolution is time irreversible ('Dollo's law'). The reason for this irreversibility is that genomes become increasingly integrated or organized, and this organization becomes a novel selective factor itself, against which future generations must compete. Selection for integrated or synergistic networks, systems or sets of mutations or traits, not for individual mutations, confers the main adaptive advantage. The result is a punctuated form of evolution that follows a logarithmic occurrence probability, in which evolution proceeds very quickly when interactomes begin to form but which slows as interactomes become more robust and the difficulty of integrating new mutations increases. Sufficient parameters exist in the game to suggest not only how equilibrium or stasis is reached but also the conditions in which it will be punctuated, the factors governing the rate at which genomic organization occurs and novel traits appear, and how population size, genome size and gene variability affect these.
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Affiliation(s)
| | - Morton I Bernstein
- Department of Physiology, Michigan State University, East Lansing, MI, USA
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27
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Baverstock K. Responses to commentaries on "The gene: An appraisal". PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2024; 188:31-42. [PMID: 38360273 DOI: 10.1016/j.pbiomolbio.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 02/02/2024] [Indexed: 02/17/2024]
Abstract
The central conclusions of "The Gene: An Appraisal" are that genetic variance does not underpin biological evolution, and, therefore, that genes are not Mendel's units of inheritance. In this response, I will address the criticisms I have received via commentaries on that paper by defending the following statements: 1. Epistasis does not explain the power-law fitness profile of the Long-Term Evolution Experiment (LTEE). The data from the evolution of natural systems displays the power-law form ubiquitously. Epistasis plays no role in evolution. 2. The common characteristics of living things (natural systems) are described by the principle of least action in de Maupertuis's original form, which is synonymous with the 2nd law of thermodynamics and Newton's 2nd law of motion in its complete form, i.e., F = dp/dt. Organisms strive to achieve free energy balance with their environments. 3. Based on an appraisal of the scientific environment between 1880 and 1911, I conclude that Johannsen's genotype conception was perhaps, the only option available to him. 4. The power-law fitness profile of the LTEE falsifies Fisher's Genetical Theory of Natural Selection, Johannsen's genotype conception, and the idea that 'Darwinian evolution' is an exception to the generic thermodynamic process of evolution in natural systems. 5. The use of the technique of genome-wide association to identify the causes and the likelihoods of inherited common diseases and behavioural traits is a 'wild goose chase' because genes are not the units of inheritance.
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Affiliation(s)
- Keith Baverstock
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio Campus, Kuopio, Finland.
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28
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Orsi E, Schada von Borzyskowski L, Noack S, Nikel PI, Lindner SN. Automated in vivo enzyme engineering accelerates biocatalyst optimization. Nat Commun 2024; 15:3447. [PMID: 38658554 PMCID: PMC11043082 DOI: 10.1038/s41467-024-46574-4] [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: 12/21/2023] [Accepted: 03/04/2024] [Indexed: 04/26/2024] Open
Abstract
Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.
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Affiliation(s)
- Enrico Orsi
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kongens Lyngby, Denmark
| | | | - Stephan Noack
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich, 52425, Jülich, Germany
| | - Pablo I Nikel
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kongens Lyngby, Denmark
| | - Steffen N Lindner
- Max Planck Institute of Molecular Plant Physiology, 14476, Potsdam-Golm, Germany.
- Department of Biochemistry, Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität, 10117, Berlin, Germany.
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29
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Venkataraman P, Nagendra P, Ahlawat N, Brajesh RG, Saini S. Convergent genetic adaptation of Escherichia coli in minimal media leads to pleiotropic divergence. Front Mol Biosci 2024; 11:1286824. [PMID: 38660375 PMCID: PMC11039892 DOI: 10.3389/fmolb.2024.1286824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 02/15/2024] [Indexed: 04/26/2024] Open
Abstract
Adaptation in an environment can either be beneficial, neutral or disadvantageous in another. To test the genetic basis of pleiotropic behaviour, we evolved six lines of E. coli independently in environments where glucose and galactose were the sole carbon sources, for 300 generations. All six lines in each environment exhibit convergent adaptation in the environment in which they were evolved. However, pleiotropic behaviour was observed in several environmental contexts, including other carbon environments. Genome sequencing reveals that mutations in global regulators rpoB and rpoC cause this pleiotropy. We report three new alleles of the rpoB gene, and one new allele of the rpoC gene. The novel rpoB alleles confer resistance to Rifampicin, and alter motility. Our results show how single nucleotide changes in the process of adaptation in minimal media can lead to wide-scale pleiotropy, resulting in changes in traits that are not under direct selection.
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Affiliation(s)
| | | | | | | | - Supreet Saini
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, India
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30
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Li Y, Barton JP. Correlated Allele Frequency Changes Reveal Clonal Structure and Selection in Temporal Genetic Data. Mol Biol Evol 2024; 41:msae060. [PMID: 38507665 PMCID: PMC10986812 DOI: 10.1093/molbev/msae060] [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: 10/13/2023] [Revised: 02/02/2024] [Accepted: 03/15/2024] [Indexed: 03/22/2024] Open
Abstract
In evolving populations where the rate of beneficial mutations is large, subpopulations of individuals with competing beneficial mutations can be maintained over long times. Evolution with this kind of clonal structure is commonly observed in a wide range of microbial and viral populations. However, it can be difficult to completely resolve clonal dynamics in data. This is due to limited read lengths in high-throughput sequencing methods, which are often insufficient to directly measure linkage disequilibrium or determine clonal structure. Here, we develop a method to infer clonal structure using correlated allele frequency changes in time-series sequence data. Simulations show that our method recovers true, underlying clonal structures when they are known and accurately estimate linkage disequilibrium. This information can then be combined with other inference methods to improve estimates of the fitness effects of individual mutations. Applications to data suggest novel clonal structures in an E. coli long-term evolution experiment, and yield improved predictions of the effects of mutations on bacterial fitness and antibiotic resistance. Moreover, our method is computationally efficient, requiring orders of magnitude less run time for large data sets than existing methods. Overall, our method provides a powerful tool to infer clonal structures from data sets where only allele frequencies are available, which can also improve downstream analyses.
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Affiliation(s)
- Yunxiao Li
- Department of Physics and Astronomy, University of California, Riverside, CA 92521, USA
| | - John P Barton
- Department of Physics and Astronomy, University of California, Riverside, CA 92521, USA
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA
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31
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Boffi NM, Guo Y, Rycroft CH, Amir A. How microscopic epistasis and clonal interference shape the fitness trajectory in a spin glass model of microbial long-term evolution. eLife 2024; 12:RP87895. [PMID: 38376390 PMCID: PMC10942580 DOI: 10.7554/elife.87895] [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] [Indexed: 02/21/2024] Open
Abstract
The adaptive dynamics of evolving microbial populations takes place on a complex fitness landscape generated by epistatic interactions. The population generically consists of multiple competing strains, a phenomenon known as clonal interference. Microscopic epistasis and clonal interference are central aspects of evolution in microbes, but their combined effects on the functional form of the population's mean fitness are poorly understood. Here, we develop a computational method that resolves the full microscopic complexity of a simulated evolving population subject to a standard serial dilution protocol. Through extensive numerical experimentation, we find that stronger microscopic epistasis gives rise to fitness trajectories with slower growth independent of the number of competing strains, which we quantify with power-law fits and understand mechanistically via a random walk model that neglects dynamical correlations between genes. We show that increasing the level of clonal interference leads to fitness trajectories with faster growth (in functional form) without microscopic epistasis, but leaves the rate of growth invariant when epistasis is sufficiently strong, indicating that the role of clonal interference depends intimately on the underlying fitness landscape. The simulation package for this work may be found at https://github.com/nmboffi/spin_glass_evodyn.
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Affiliation(s)
- Nicholas M Boffi
- Courant Institute of Mathematical Sciences, New York UniversityNew YorkUnited States
| | - Yipei Guo
- Janelia Research CampusAshburnUnited States
| | - Chris H Rycroft
- Department of Mathematics, University of Wisconsin–MadisonMadisonUnited States
- Mathematics Group, Lawrence Berkeley National LaboratoryBerkeleyUnited States
| | - Ariel Amir
- Weizmann Institute of ScienceRehovotIsrael
- John A. Paulson School of Engineering and Applied Sciences, Harvard UniversityCambridgeUnited States
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32
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Poret AJ, Schaefers M, Merakou C, Mansour KE, Lagoudas GK, Cross AR, Goldberg JB, Kishony R, Uluer AZ, McAdam AJ, Blainey PC, Vargas SO, Lieberman TD, Priebe GP. De novo mutations mediate phenotypic switching in an opportunistic human lung pathogen. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.06.579193. [PMID: 38370793 PMCID: PMC10871308 DOI: 10.1101/2024.02.06.579193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Bacteria evolving within human hosts encounter selective tradeoffs that render mutations adaptive in one context and deleterious in another. Here, we report that the cystic fibrosis-associated pathogen Burkholderia dolosa overcomes in-human selective tradeoffs by acquiring successive point mutations that alternate phenotypes. We sequenced the whole genomes of 931 respiratory isolates from two recently infected patients and an epidemiologically-linked, chronically-infected patient. These isolates are contextualized using 112 historical genomes from the same outbreak strain. Within both newly infected patients, diverse parallel mutations that disrupt O-antigen expression quickly arose, comprising 29% and 63% of their B. dolosa communities by 3 years. The selection for loss of O-antigen starkly contrasts with our previous observation of parallel O-antigen-restoring mutations after many years of chronic infection in the historical outbreak. Experimental characterization revealed that O-antigen loss increases uptake in immune cells while decreasing competitiveness in the mouse lung. We propose that the balance of these pressures, and thus whether O-antigen expression is advantageous, depends on tissue localization and infection duration. These results suggest that mutation-driven alternation during infection may be more frequent than appreciated and is underestimated without dense temporal sampling.
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Affiliation(s)
- Alexandra J. Poret
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology
- Department of Biological Engineering, Massachusetts Institute of Technology
| | - Matthew Schaefers
- Department of Anesthesiology, Critical Care and Pain Medicine, Division of Critical Care Medicine, Boston Children's Hospital
- Department of Anaesthesia, Harvard Medical School, Boston, Massachusetts
| | - Christina Merakou
- Department of Anesthesiology, Critical Care and Pain Medicine, Division of Critical Care Medicine, Boston Children's Hospital
- Department of Anaesthesia, Harvard Medical School, Boston, Massachusetts
| | - Kathryn E. Mansour
- Department of Anesthesiology, Critical Care and Pain Medicine, Division of Critical Care Medicine, Boston Children's Hospital
| | - Georgia K. Lagoudas
- Department of Biological Engineering, Massachusetts Institute of Technology
- Broad Institute of MIT and Harvard
| | - Ashley R. Cross
- Department of Pediatrics, Division of Pulmonary, Asthma, Cystic Fibrosis, and Sleep, Emory University School of Medicine
| | - Joanna B. Goldberg
- Department of Pediatrics, Division of Pulmonary, Asthma, Cystic Fibrosis, and Sleep, Emory University School of Medicine
| | - Roy Kishony
- Faculty of Biology and Faculty of Computer Science, Technion Israel
| | - Ahmet Z. Uluer
- Department of Pediatrics, Division of Respiratory Diseases, Boston Children’s Hospital
- Adult CF Program, Brigham and Women’s Hospital
- Department of Pediatrics, Harvard Medical School
| | - Alexander J. McAdam
- Department of Laboratory Medicine, Boston Children’s Hospital
- Department of Pathology, Harvard Medical School
| | - Paul C. Blainey
- Department of Biological Engineering, Massachusetts Institute of Technology
- Broad Institute of MIT and Harvard
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
| | - Sara O. Vargas
- Department of Pathology, Harvard Medical School
- Department of Pathology, Boston Children’s Hospital
| | - Tami D. Lieberman
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology
- Department of Anesthesiology, Critical Care and Pain Medicine, Division of Critical Care Medicine, Boston Children's Hospital
| | - Gregory P. Priebe
- Department of Anesthesiology, Critical Care and Pain Medicine, Division of Critical Care Medicine, Boston Children's Hospital
- Department of Anaesthesia, Harvard Medical School, Boston, Massachusetts
- Broad Institute of MIT and Harvard
- Department of Pediatrics, Division of Infectious Diseases, Boston Children’s Hospital
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33
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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] [Grants] [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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34
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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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35
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Baverstock K. The Gene: An appraisal. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2024; 186:e73-e88. [PMID: 38044248 DOI: 10.1016/j.pbiomolbio.2023.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
The gene can be described as the foundational concept of modern biology. As such, it has spilled over into daily discourse, yet it is acknowledged among biologists to be ill-defined. Here, following a short history of the gene, I analyse critically its role in inheritance, evolution, development, and morphogenesis. Wilhelm Johannsen's genotype-conception, formulated in 1910, has been adopted as the foundation stone of genetics, giving the gene a higher degree of prominence than is justified by the evidence. An analysis of the results of the Long-Term Evolution Experiment (LTEE) with E. coli bacteria, grown over 60,000 generations, does not support spontaneous gene mutation as the source of variance for natural selection. From this it follows that the gene is not Mendel's unit of inheritance: that must be Johannsen's transmission-conception at the gamete phenotype level, a form of inheritance that Johannsen did not consider. Alternatively, I contend that biology viewed on the bases of thermodynamics, complex system dynamics, and self-organisation, provides a new framework for the foundations of biology. In this framework, the gene plays a passive role as a vital information store: it is the phenotype that plays the active role in inheritance, evolution, development, and morphogenesis.
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Affiliation(s)
- Keith Baverstock
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio Campus, Kuopio, Finland.
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36
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Dapa T, Xavier KB. Effect of diet on the evolution of gut commensal bacteria. Gut Microbes 2024; 16:2369337. [PMID: 38904092 PMCID: PMC11195494 DOI: 10.1080/19490976.2024.2369337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 06/12/2024] [Indexed: 06/22/2024] Open
Abstract
The gut microbiota, comprising trillions of diverse microorganisms inhabiting the intestines of animals, forms a complex and indispensable ecosystem with profound implications for the host's well-being. Its functions include contributing to developing the host's immune response, aiding in nutrient digestion, synthesizing essential compounds, acting as a barrier against pathogen invasion, and influencing the development or regression of various pathologies. The dietary habits of the host directly impact this intricate community of gut microbes. Diet influences the composition and function of the gut microbiota through alterations in gene expression, enzymatic activity, and metabolome. While the impact of diet on gut ecology is well-established, the investigation into the relationship between dietary consumption and microbial genotypic diversity has been limited. This review provides an overview of the relationship between diet and gut microbiota, emphasizing the impact of host nutrition on both short- and long-term evolution in the mammalian gut. It is evident that the evolution of the gut microbiota occurs even on short timescales through the acquisition of novel mutations, within the gut bacteria of individual hosts. Consequently, we discuss the importance of considering alterations in bacterial genomic diversity when analyzing microbiota-dependent effects on host physiology. Future investigations into the various microbiota-related traits shall greatly benefit from a deeper understanding of commensal bacterial evolutionary adaptation.
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Affiliation(s)
- Tanja Dapa
- Andalusian Center for Developmental Biology (CABD), Department of Molecular Biology and Biochemical Engineering, Pablo de Olavide University/CSIC/Junta de Andalucía, Seville, Spain
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
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37
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Diaz-Colunga J, Sanchez A, Ogbunugafor CB. Environmental modulation of global epistasis in a drug resistance fitness landscape. Nat Commun 2023; 14:8055. [PMID: 38052815 PMCID: PMC10698197 DOI: 10.1038/s41467-023-43806-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 11/21/2023] [Indexed: 12/07/2023] Open
Abstract
Interactions between mutations (epistasis) can add substantial complexity to genotype-phenotype maps, hampering our ability to predict evolution. Yet, recent studies have shown that the fitness effect of a mutation can often be predicted from the fitness of its genetic background using simple, linear relationships. This phenomenon, termed global epistasis, has been leveraged to reconstruct fitness landscapes and infer adaptive trajectories in a wide variety of contexts. However, little attention has been paid to how patterns of global epistasis may be affected by environmental variation, despite this variation frequently being a major driver of evolution. This is particularly relevant for the evolution of drug resistance, where antimicrobial drugs may change the environment faced by pathogens and shape their adaptive trajectories in ways that can be difficult to predict. By analyzing a fitness landscape of four mutations in a gene encoding an essential enzyme of P. falciparum (a parasite cause of malaria), here we show that patterns of global epistasis can be strongly modulated by the concentration of a drug in the environment. Expanding on previous theoretical results, we demonstrate that this modulation can be quantitatively explained by how specific gene-by-gene interactions are modified by drug dose. Importantly, our results highlight the need to incorporate potential environmental variation into the global epistasis framework in order to predict adaptation in dynamic environments.
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Affiliation(s)
- Juan Diaz-Colunga
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT, 06511, USA.
- Department of Microbial Biotechnology, Spanish National Center for Biotechnology CNB-CSIC, 28049, Madrid, Spain.
- Institute of Functional Biology and Genomics IBFG-CSIC, University of Salamanca, 37007, Salamanca, Spain.
| | - Alvaro Sanchez
- Department of Microbial Biotechnology, Spanish National Center for Biotechnology CNB-CSIC, 28049, Madrid, Spain.
- Institute of Functional Biology and Genomics IBFG-CSIC, University of Salamanca, 37007, Salamanca, Spain.
| | - C Brandon Ogbunugafor
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT, 06511, USA.
- Santa Fe Institute, Santa Fe, NM, 87501, USA.
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38
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Favate JS, Skalenko KS, Chiles E, Su X, Yadavalli SS, Shah P. Linking genotypic and phenotypic changes in the E. coli long-term evolution experiment using metabolomics. eLife 2023; 12:RP87039. [PMID: 37991493 PMCID: PMC10665018 DOI: 10.7554/elife.87039] [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] [Indexed: 11/23/2023] Open
Abstract
Changes in an organism's environment, genome, or gene expression patterns can lead to changes in its metabolism. The metabolic phenotype can be under selection and contributes to adaptation. However, the networked and convoluted nature of an organism's metabolism makes relating mutations, metabolic changes, and effects on fitness challenging. To overcome this challenge, we use the long-term evolution experiment (LTEE) with E. coli as a model to understand how mutations can eventually affect metabolism and perhaps fitness. We used mass spectrometry to broadly survey the metabolomes of the ancestral strains and all 12 evolved lines. We combined this metabolic data with mutation and expression data to suggest how mutations that alter specific reaction pathways, such as the biosynthesis of nicotinamide adenine dinucleotide, might increase fitness in the system. Our work provides a better understanding of how mutations might affect fitness through the metabolic changes in the LTEE and thus provides a major step in developing a complete genotype-phenotype map for this experimental system.
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Affiliation(s)
- John S Favate
- Department of Genetics, Rutgers UniversityPiscatawayUnited States
- Human Genetics Institute of New JerseyPiscatawayUnited States
| | - Kyle S Skalenko
- Department of Genetics, Rutgers UniversityPiscatawayUnited States
- Waksman Institute, Rutgers UniversityPiscatawayUnited States
| | - Eric Chiles
- Cancer Institute of New JerseyNew BrunswickUnited States
| | - Xiaoyang Su
- Cancer Institute of New JerseyNew BrunswickUnited States
| | - Srujana Samhita Yadavalli
- Department of Genetics, Rutgers UniversityPiscatawayUnited States
- Waksman Institute, Rutgers UniversityPiscatawayUnited States
| | - Premal Shah
- Department of Genetics, Rutgers UniversityPiscatawayUnited States
- Human Genetics Institute of New JerseyPiscatawayUnited States
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39
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Westerhoff HV. On paradoxes between optimal growth, metabolic control analysis, and flux balance analysis. Biosystems 2023; 233:104998. [PMID: 37591451 DOI: 10.1016/j.biosystems.2023.104998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 08/04/2023] [Accepted: 08/08/2023] [Indexed: 08/19/2023]
Abstract
In Microbiology it is often assumed that growth rate is maximal. This may be taken to suggest that the dependence of the growth rate on every enzyme activity is at the top of an inverse-parabolic function, i.e. that all flux control coefficients should equal zero. This might seem to imply that the sum of these flux control coefficients equals zero. According to the summation law of Metabolic Control Analysis (MCA) the sum of flux control coefficients should equal 1 however. And in Flux Balance Analysis (FBA) catabolism is often limited by a hard bound, causing catabolism to fully control the fluxes, again in apparent contrast with a flux control coefficient of zero. Here we resolve these paradoxes (apparent contradictions) in an analysis that uses the 'Edinburgh pathway', the 'Amsterdam pathway', as well as a generic metabolic network providing the building blocks or Gibbs energy for microbial growth. We review and show that (i) optimization depends on so-called enzyme control coefficients rather than the 'catalytic control coefficients' of MCA's summation law, (ii) when optimization occurs at fixed total protein, the former differ from the latter to the extent that they may all become equal to zero in the optimum state, (iii) in more realistic scenarios of optimization where catalytically inert biomass is compensating or maintenance metabolism is taken into consideration, the optimum enzyme concentrations should not be expected to equal those that maximize the specific growth rate, (iv) optimization may be in terms of yield rather than specific growth rate, which resolves the paradox because the sum of catalytic control coefficients on yield equals 0, (v) FBA effectively maximizes growth yield, and for yield the summation law states 0 rather than 1, thereby removing the paradox, (vi) furthermore, FBA then comes more often to a 'hard optimum' defined by a maximum catabolic flux and a catabolic-enzyme control coefficient of 1. The trade-off between maintenance metabolism and growth is highlighted as worthy of further analysis.
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Affiliation(s)
- Hans V Westerhoff
- Department of Molecular Cell Biology, Vrije Universiteit Amsterdam, A-Life, De Boelelaan 1085, 1081 HV, Amsterdam, the Netherlands; Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 XH, Amsterdam, the Netherlands; School of Biological Sciences, Medicine and Health, University of Manchester, Manchester, United Kingdom; Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, 7600, South Africa.
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40
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Zhao R, Lukacsovich T, Gaut R, Emerson JJ. FREQ-Seq2: a method for precise high-throughput combinatorial quantification of allele frequencies. G3 (BETHESDA, MD.) 2023; 13:jkad162. [PMID: 37494033 PMCID: PMC10542570 DOI: 10.1093/g3journal/jkad162] [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: 01/26/2023] [Revised: 01/26/2023] [Accepted: 07/14/2023] [Indexed: 07/27/2023]
Abstract
The accurate determination of allele frequencies is crucially important across a wide range of problems in genetics, such as developing population genetic models, making inferences from genome-wide association studies, determining genetic risk for diseases, as well as other scientific and medical applications. Furthermore, understanding how allele frequencies change over time in populations is central to ascertaining their evolutionary dynamics. We present a precise, efficient, and economical method (FREQ-Seq2) for quantifying the relative frequencies of different alleles at loci of interest in mixed population samples. Through the creative use of paired barcode sequences, we exponentially increased the throughput of the original FREQ-Seq method from 48 to 2,304 samples. FREQ-Seq2 can be targeted to specific genomic regions of interest, which are amplified using universal barcoded adapters to generate Illumina sequencing libraries. Our enhanced method, available as a kit along with open-source software for analyzing sequenced libraries, enables the detection and removal of errors that are undetectable in the original FREQ-Seq method as well as other conventional methods for allele frequency quantification. Finally, we validated the performance of our sequencing-based approach with a highly multiplexed set of control samples as well as a competitive evolution experiment in Escherichia coli and compare the latter to estimates derived from manual colony counting. Our analyses demonstrate that FREQ-Seq2 is flexible, inexpensive, and produces large amounts of data with low error, low noise, and desirable statistical properties. In summary, FREQ-Seq2 is a powerful method for quantifying allele frequency that provides a versatile approach for profiling mixed populations.
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Affiliation(s)
- Roy Zhao
- Center for Complex Biological Systems, University of California, Irvine, CA 92697, USA
| | - Tamas Lukacsovich
- Brain Research Institute, University of Zürich, 8057 Zürich, Switzerland
| | - Rebecca Gaut
- Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA
| | - J J Emerson
- Center for Complex Biological Systems, University of California, Irvine, CA 92697, USA
- Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA
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41
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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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42
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Turner CB, Blount ZD, Mitchell DH, Lenski RE. Evolution of a cross-feeding interaction following a key innovation in a long-term evolution experiment with Escherichia coli. MICROBIOLOGY (READING, ENGLAND) 2023; 169:001390. [PMID: 37650867 PMCID: PMC10482366 DOI: 10.1099/mic.0.001390] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 08/15/2023] [Indexed: 09/01/2023]
Abstract
The evolution of a novel trait can profoundly change an organism's effects on its environment, which can in turn affect the further evolution of that organism and any coexisting organisms. We examine these effects and feedbacks following the evolution of a novel function in the Long-Term Evolution Experiment (LTEE) with Escherichia coli. A characteristic feature of E. coli is its inability to grow aerobically on citrate (Cit-). Nonetheless, a Cit+ variant with this capacity evolved in one LTEE population after 31 000 generations. The Cit+ clade then coexisted stably with another clade that retained the ancestral Cit- phenotype. This coexistence was shaped by the evolution of a cross-feeding relationship based on C4-dicarboxylic acids, particularly succinate, fumarate, and malate, that the Cit+ variants release into the medium. Both the Cit- and Cit+ cells evolved to grow on these excreted resources. The evolution of aerobic growth on citrate thus led to a transition from an ecosystem based on a single limiting resource, glucose, to one with at least five resources that were either shared or partitioned between the two coexisting clades. Our findings show that evolutionary novelties can change environmental conditions in ways that facilitate diversity by altering ecosystem structure and the evolutionary trajectories of coexisting lineages.
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Affiliation(s)
- Caroline B. Turner
- Ecology, Evolution and Behavior Program, Michigan State University, East Lansing, MI, USA
- Present address: Department of Biology, Loyola University Chicago, Chicago, IL, USA
| | - Zachary D. Blount
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
| | - Daniel H. Mitchell
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
- Present address: Biological Sciences, University of New Hampshire, Durham, NH, USA
| | - Richard E. Lenski
- Department of Microbiology and Molecular Genetics; and Ecology, Evolution and Behavior Program, Michigan State University, East Lansing, MI, USA
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43
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Wagner A. Evolvability-enhancing mutations in the fitness landscapes of an RNA and a protein. Nat Commun 2023; 14:3624. [PMID: 37336901 PMCID: PMC10279741 DOI: 10.1038/s41467-023-39321-8] [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: 09/26/2022] [Accepted: 06/05/2023] [Indexed: 06/21/2023] Open
Abstract
Can evolvability-the ability to produce adaptive heritable variation-itself evolve through adaptive Darwinian evolution? If so, then Darwinian evolution may help create the conditions that enable Darwinian evolution. Here I propose a framework that is suitable to address this question with available experimental data on adaptive landscapes. I introduce the notion of an evolvability-enhancing mutation, which increases the likelihood that subsequent mutations in an evolving organism, protein, or RNA molecule are adaptive. I search for such mutations in the experimentally characterized and combinatorially complete fitness landscapes of a protein and an RNA molecule. I find that such evolvability-enhancing mutations indeed exist. They constitute a small fraction of all mutations, which shift the distribution of fitness effects of subsequent mutations towards less deleterious mutations, and increase the incidence of beneficial mutations. Evolving populations which experience such mutations can evolve significantly higher fitness. The study of evolvability-enhancing mutations opens many avenues of investigation into the evolution of evolvability.
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Affiliation(s)
- Andreas Wagner
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
- Swiss Institute of Bioinformatics, Quartier Sorge-Batiment Genopode, Lausanne, Switzerland.
- The Santa Fe Institute, Santa Fe, NM, USA.
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44
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Lenski RE. Revisiting the Design of the Long-Term Evolution Experiment with Escherichia coli. J Mol Evol 2023; 91:241-253. [PMID: 36790511 DOI: 10.1007/s00239-023-10095-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 01/20/2023] [Indexed: 02/16/2023]
Abstract
The long-term evolution experiment (LTEE) with Escherichia coli began in 1988 and it continues to this day, with its 12 populations having recently reached 75,000 generations of evolution in a simple, well-controlled environment. The LTEE was designed to explore open-ended questions about the dynamics and repeatability of phenotypic and genetic evolution. Here I discuss various aspects of the LTEE's experimental design that have enabled its stability and success, including the choices of the culture regime, growth medium, ancestral strain, and statistical replication. I also discuss some of the challenges associated with a long-running project, such as handling procedural errors (e.g., cross-contamination) and managing the expanding collection of frozen samples. The simplicity of the experimental design and procedures have supported the long-term stability of the LTEE. That stability-along with the inherent creativity of the evolutionary process and the emergence of new genomic technologies-provides a platform that has allowed talented students and collaborators to pose questions, collect data, and make discoveries that go far beyond anything I could have imagined at the start of the LTEE.
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Affiliation(s)
- Richard E Lenski
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, 48824, USA.
- Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, MI, 48824, USA.
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45
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Martínez AA, Lang GI. Identifying Targets of Selection in Laboratory Evolution Experiments. J Mol Evol 2023; 91:345-355. [PMID: 36810618 PMCID: PMC11197053 DOI: 10.1007/s00239-023-10096-2] [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: 12/07/2022] [Accepted: 02/01/2023] [Indexed: 02/24/2023]
Abstract
Adaptive evolution navigates a balance between chance and determinism. The stochastic processes of mutation and drift generate phenotypic variation; however, once mutations reach an appreciable frequency in the population, their fate is governed by the deterministic action of selection, enriching for favorable genotypes and purging the less-favorable ones. The net result is that replicate populations will traverse similar-but not identical-pathways to higher fitness. This parallelism in evolutionary outcomes can be leveraged to identify the genes and pathways under selection. However, distinguishing between beneficial and neutral mutations is challenging because many beneficial mutations will be lost due to drift and clonal interference, and many neutral (and even deleterious) mutations will fix by hitchhiking. Here, we review the best practices that our laboratory uses to identify genetic targets of selection from next-generation sequencing data of evolved yeast populations. The general principles for identifying the mutations driving adaptation will apply more broadly.
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Affiliation(s)
| | - Gregory I Lang
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA.
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46
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Johnson MS, Reddy G, Desai MM. Epistasis and evolution: recent advances and an outlook for prediction. BMC Biol 2023; 21:120. [PMID: 37226182 PMCID: PMC10206586 DOI: 10.1186/s12915-023-01585-3] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 03/30/2023] [Indexed: 05/26/2023] Open
Abstract
As organisms evolve, the effects of mutations change as a result of epistatic interactions with other mutations accumulated along the line of descent. This can lead to shifts in adaptability or robustness that ultimately shape subsequent evolution. Here, we review recent advances in measuring, modeling, and predicting epistasis along evolutionary trajectories, both in microbial cells and single proteins. We focus on simple patterns of global epistasis that emerge in this data, in which the effects of mutations can be predicted by a small number of variables. The emergence of these patterns offers promise for efforts to model epistasis and predict evolution.
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Affiliation(s)
- Milo S Johnson
- Department of Integrative Biology, University of California, Berkeley, CA, USA
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Gautam Reddy
- Physics & Informatics Laboratories, NTT Research, Inc., Sunnyvale, CA, USA
- Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Michael M Desai
- Department of Organismic and Evolutionary Biology and Department of Physics, Harvard University, Cambridge, MA, USA.
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47
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Venkataram S, Kryazhimskiy S. Evolutionary repeatability of emergent properties of ecological communities. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220047. [PMID: 37004728 PMCID: PMC10067272 DOI: 10.1098/rstb.2022.0047] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 12/07/2022] [Indexed: 04/04/2023] Open
Abstract
Most species belong to ecological communities where their interactions give rise to emergent community-level properties, such as diversity and productivity. Understanding and predicting how these properties change over time has been a major goal in ecology, with important practical implications for sustainability and human health. Less attention has been paid to the fact that community-level properties can also change because member species evolve. Yet, our ability to predict long-term eco-evolutionary dynamics hinges on how repeatably community-level properties change as a result of species evolution. Here, we review studies of evolution of both natural and experimental communities and make the case that community-level properties at least sometimes evolve repeatably. We discuss challenges faced in investigations of evolutionary repeatability. In particular, only a handful of studies enable us to quantify repeatability. We argue that quantifying repeatability at the community level is critical for approaching what we see as three major open questions in the field: (i) Is the observed degree of repeatability surprising? (ii) How is evolutionary repeatability at the community level related to repeatability at the level of traits of member species? (iii) What factors affect repeatability? We outline some theoretical and empirical approaches to addressing these questions. Advances in these directions will not only enrich our basic understanding of evolution and ecology but will also help us predict eco-evolutionary dynamics. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.
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Affiliation(s)
- Sandeep Venkataram
- Department of Ecology, Behavior and Evolution, UC San Diego, La Jolla, CA 92093, USA
| | - Sergey Kryazhimskiy
- Department of Ecology, Behavior and Evolution, UC San Diego, La Jolla, CA 92093, USA
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48
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Favate JS, Skalenko KS, Chiles E, Su X, Yadavalli SS, Shah P. Linking genotypic and phenotypic changes in the E. coli Long-Term Evolution Experiment using metabolomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.15.528756. [PMID: 36874203 PMCID: PMC9985142 DOI: 10.1101/2023.02.15.528756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Changes in an organism's environment, genome, or gene expression patterns can lead to changes in its metabolism. The metabolic phenotype can be under selection and contributes to adaptation. However, the networked and convoluted nature of an organism's metabolism makes relating mutations, metabolic changes, and effects on fitness challenging. To overcome this challenge, we use the Long-Term Evolution Experiment (LTEE) with E. coli as a model to understand how mutations can eventually affect metabolism and perhaps fitness. We used mass-spectrometry to broadly survey the metabolomes of the ancestral strains and all 12 evolved lines. We combined this metabolic data with mutation and expression data to suggest how mutations that alter specific reaction pathways, such as the biosynthesis of nicotinamide adenine dinucleotide, might increase fitness in the system. Our work provides a better understanding of how mutations might affect fitness through the metabolic changes in the LTEE and thus provides a major step in developing a complete genotype-phenotype map for this experimental system.
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Affiliation(s)
- John S. Favate
- Department of Genetics, Rutgers University, Piscataway, New Jersey, USA
- Human Genetics Institute of New Jersey, Piscataway, New Jersey, USA
| | - Kyle S. Skalenko
- Department of Genetics, Rutgers University, Piscataway, New Jersey, USA
- Waksman Institute, Rutgers University, Piscataway, New Jersey, USA
| | - Eric Chiles
- Cancer Institute of New Jersey, New Brunswick, New Jersey, USA
| | - Xiaoyang Su
- Cancer Institute of New Jersey, New Brunswick, New Jersey, USA
| | - Srujana S. Yadavalli
- Department of Genetics, Rutgers University, Piscataway, New Jersey, USA
- Waksman Institute, Rutgers University, Piscataway, New Jersey, USA
| | - Premal Shah
- Department of Genetics, Rutgers University, Piscataway, New Jersey, USA
- Human Genetics Institute of New Jersey, Piscataway, New Jersey, USA
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49
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Wortel MT. Evolutionary coexistence in a fluctuating environment by specialization on resource level. J Evol Biol 2023; 36:622-631. [PMID: 36799532 DOI: 10.1111/jeb.14158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 01/02/2023] [Accepted: 01/18/2023] [Indexed: 02/18/2023]
Abstract
Microbial communities in fluctuating environments, such as oceans or the human gut, contain a wealth of diversity. This diversity contributes to the stability of communities and the functions they have in their hosts and ecosystems. To improve stability and increase production of beneficial compounds, we need to understand the underlying mechanisms causing this diversity. When nutrient levels fluctuate over time, one possibly relevant mechanism is coexistence between specialists on low and specialists on high nutrient levels. The relevance of this process is supported by the observations of coexistence in the laboratory, and by simple models, which show that negative frequency dependence of two such specialists can stabilize coexistence. However, as microbial populations are often large and fast growing, they evolve rapidly. Our aim is to determine what happens when species can evolve; whether evolutionary branching can create diversity or whether evolution will destabilize coexistence. We derive an analytical expression of the invasion fitness in fluctuating environments and use adaptive dynamics techniques to find that evolutionarily stable coexistence requires a special type of trade-off between growth at low and high nutrients. We do not find support for the necessary evolutionary trade-off in data available for the bacterium Escherichia coli and the yeast Saccharomyces cerevisiae on glucose. However, this type of data is scarce and might exist for other species or in different conditions. Moreover, we do find evidence for evolutionarily stable coexistence of the two species together. Since we find this coexistence in the scarce data that are available, we predict that specialization on resource level is a relevant mechanism for species diversity in microbial communities in fluctuating environments in natural settings.
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Affiliation(s)
- Meike T Wortel
- Molecular Biology and Microbial Food Safety, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
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50
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Adaptation to Overflow Metabolism by Mutations That Impair tRNA Modification in Experimentally Evolved Bacteria. mBio 2023; 14:e0028723. [PMID: 36853041 PMCID: PMC10128029 DOI: 10.1128/mbio.00287-23] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023] Open
Abstract
When microbes grow in foreign nutritional environments, selection may enrich mutations in unexpected pathways connecting growth and homeostasis. An evolution experiment designed to identify beneficial mutations in Burkholderia cenocepacia captured six independent nonsynonymous substitutions in the essential gene tilS, which modifies tRNAIle2 by adding a lysine to the anticodon for faithful AUA recognition. Further, five additional mutants acquired mutations in tRNAIle2, which strongly suggests that disrupting the TilS-tRNAIle2 interaction was subject to strong positive selection. Mutated TilS incurred greatly reduced enzymatic function but retained capacity for tRNAIle2 binding. However, both mutant sets outcompeted the wild type by decreasing the lag phase duration by ~3.5 h. We hypothesized that lysine demand could underlie fitness in the experimental conditions. As predicted, supplemental lysine complemented the ancestral fitness deficit, but so did the additions of several other amino acids. Mutant fitness advantages were also specific to rapid growth on galactose using oxidative overflow metabolism that generates redox imbalance, not resources favoring more balanced metabolism. Remarkably, 13 tilS mutations also evolved in the long-term evolution experiment with Escherichia coli, including four fixed mutations. These results suggest that TilS or unknown binding partners contribute to improved growth under conditions of rapid sugar oxidation at the predicted expense of translational accuracy. IMPORTANCE There is growing evidence that the fundamental components of protein translation can play multiple roles in maintaining cellular homeostasis. Enzymes that interact with transfer RNAs not only ensure faithful decoding of the genetic code but also help signal the metabolic state by reacting to imbalances in essential building blocks like free amino acids and cofactors. Here, we present evidence of a secondary function for the essential enzyme TilS, whose only prior known function is to modify tRNAIle(CAU) to ensure accurate translation. Multiple nonsynonymous substitutions in tilS, as well as its cognate tRNA, were selected in evolution experiments favoring rapid, redox-imbalanced growth. These mutations alone decreased lag phase and created a competitive advantage, but at the expense of most primary enzyme function. These results imply that TilS interacts with other factors related to the timing of exponential growth and that tRNA-modifying enzymes may serve multiple roles in monitoring metabolic health.
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