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Ascensao JA, Lok K, Hallatschek O. Asynchronous abundance fluctuations can drive giant genotype frequency fluctuations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.23.581776. [PMID: 38562700 PMCID: PMC10983864 DOI: 10.1101/2024.02.23.581776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Large stochastic population abundance fluctuations are ubiquitous across the tree of life 1-7 , impacting the predictability of population dynamics and influencing eco-evolutionary outcomes. It has generally been thought that these large abundance fluctuations do not strongly impact evolution, as the relative frequencies of alleles in the population will be unaffected if the abundance of all alleles fluctuate in unison. However, we argue that large abundance fluctuations can lead to significant genotype frequency fluctuations if different genotypes within a population experience these fluctuations asynchronously. By serially diluting mixtures of two closely related E. coli strains, we show that such asynchrony can occur, leading to giant frequency fluctuations that far exceed expectations from models of genetic drift. We develop a flexible, effective model that explains the abundance fluctuations as arising from correlated offspring numbers between individuals, and the large frequency fluctuations result from even slight decoupling in offspring numbers between genotypes. This model accurately describes the observed abundance and frequency fluctuation scaling behaviors. Our findings suggest chaotic dynamics underpin these giant fluctuations, causing initially similar trajectories to diverge exponentially; subtle environmental changes can be magnified, leading to batch correlations in identical growth conditions. Furthermore, we present evidence that such decoupling noise is also present in mixed-genotype S. cerevisiae populations. We demonstrate that such decoupling noise can strongly influence evolutionary outcomes, in a manner distinct from genetic drift. Given the generic nature of asynchronous fluctuations, we anticipate that they are widespread in biological populations, significantly affecting evolutionary and ecological dynamics.
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2
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Abreu CI, Mathur S, Petrov DA. Environmental memory alters the fitness effects of adaptive mutations in fluctuating environments. Nat Ecol Evol 2024:10.1038/s41559-024-02475-9. [PMID: 39020024 DOI: 10.1038/s41559-024-02475-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 06/11/2024] [Indexed: 07/19/2024]
Abstract
Evolution in a static laboratory environment often proceeds via large-effect beneficial mutations that may become maladaptive in other environments. Conversely, natural settings require populations to endure environmental fluctuations. A sensible assumption is that the fitness of a lineage in a fluctuating environment is the time average of its fitness over the sequence of static conditions it encounters. However, transitions between conditions may pose entirely new challenges, which could cause deviations from this time average. To test this, we tracked hundreds of thousands of barcoded yeast lineages evolving in static and fluctuating conditions and subsequently isolated 900 mutants for pooled fitness assays in 15 environments. Here we find that fitness in fluctuating environments indeed often deviates from the time average, leading to fitness non-additivity. Moreover, closer examination reveals that fitness in one component of a fluctuating environment is often strongly influenced by the previous component. We show that this environmental memory is especially common for mutants with high variance in fitness across tested environments. We use a simple mathematical model and whole-genome sequencing to propose mechanisms underlying this effect, including lag time evolution and sensing mutations. Our results show that environmental fluctuations impact fitness and suggest that variance in static environments can explain these impacts.
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Affiliation(s)
- Clare I Abreu
- Department of Biology, Stanford University, Stanford, CA, USA.
| | - Shaili Mathur
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Dmitri A Petrov
- Department of Biology, Stanford University, Stanford, CA, USA.
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3
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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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4
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Huang Y, Mukherjee A, Schink S, Benites NC, Basan M. Evolution and stability of complex microbial communities driven by trade-offs. Mol Syst Biol 2024:10.1038/s44320-024-00051-8. [PMID: 38961275 DOI: 10.1038/s44320-024-00051-8] [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: 04/24/2024] [Revised: 06/18/2024] [Accepted: 06/20/2024] [Indexed: 07/05/2024] Open
Abstract
Microbial communities are ubiquitous in nature and play an important role in ecology and human health. Cross-feeding is thought to be core to microbial communities, though it remains unclear precisely why it emerges. Why have multi-species microbial communities evolved in many contexts and what protects microbial consortia from invasion? Here, we review recent insights into the emergence and stability of coexistence in microbial communities. A particular focus is the long-term evolutionary stability of coexistence, as observed for microbial communities that spontaneously evolved in the E. coli long-term evolution experiment (LTEE). We analyze these findings in the context of recent work on trade-offs between competing microbial objectives, which can constitute a mechanistic basis for the emergence of coexistence. Coexisting communities, rather than monocultures of the 'fittest' single strain, can form stable endpoints of evolutionary trajectories. Hence, the emergence of coexistence might be an obligatory outcome in the evolution of microbial communities. This implies that rather than embodying fragile metastable configurations, some microbial communities can constitute formidable ecosystems that are difficult to disrupt.
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Affiliation(s)
- Yanqing Huang
- Harvard Medical School, Department of Systems Biology, Boston, USA
| | - Avik Mukherjee
- Harvard Medical School, Department of Systems Biology, Boston, USA
| | - Severin Schink
- Harvard Medical School, Department of Systems Biology, Boston, USA
| | | | - Markus Basan
- Harvard Medical School, Department of Systems Biology, Boston, USA.
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5
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Münzbergová Z, Šurinová M, Biscarini F, Níčová E. Genetic response of a perennial grass to warm and wet environments interacts and is associated with trait means as well as plasticity. J Evol Biol 2024; 37:704-716. [PMID: 38761114 DOI: 10.1093/jeb/voae060] [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: 06/29/2023] [Revised: 04/15/2024] [Accepted: 05/17/2024] [Indexed: 05/20/2024]
Abstract
The potential for rapid evolution is an important mechanism allowing species to adapt to changing climatic conditions. Although such potential has been largely studied in various short-lived organisms, to what extent we can observe similar patterns in long-lived plant species, which often dominate natural systems, is largely unexplored. We explored the potential for rapid evolution in Festuca rubra, a long-lived grass with extensive clonal growth dominating in alpine grasslands. We used a field sowing experiment simulating expected climate change in our model region. Specifically, we exposed seeds from five independent seed sources to novel climatic conditions by shifting them along a natural climatic grid and explored the genetic profiles of established seedlings after 3 years. Data on genetic profiles of plants selected under different novel conditions indicate that different climate shifts select significantly different pools of genotypes from common seed pools. Increasing soil moisture was more important than increasing temperature or the interaction of the two climatic factors in selecting pressure. This can indicate negative genetic interaction in response to the combined effects or that the effects of different climates are interactive rather than additive. The selected alleles were found in genomic regions, likely affecting the function of specific genes or their expression. Many of these were also linked to morphological traits (mainly to trait plasticity), suggesting these changes may have a consequence on plant performance. Overall, these data indicate that even long-lived plant species may experience strong selection by climate, and their populations thus have the potential to rapidly adapt to these novel conditions.
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Affiliation(s)
- Zuzana Münzbergová
- Department of Botany, Faculty of Science, Charles University, Benátská 2, Prague, Czech Republic
- Department of Population Ecology, Institute of Botany, Czech Academy of Sciences, Zámek 1, Průhonice, Czech Republic
| | - Maria Šurinová
- Department of Botany, Faculty of Science, Charles University, Benátská 2, Prague, Czech Republic
- Department of Population Ecology, Institute of Botany, Czech Academy of Sciences, Zámek 1, Průhonice, Czech Republic
| | - Filippo Biscarini
- Institute of Agricultural Biology and Biotechnology, National Research Council (IBBA-CNR), Milan, Italy
| | - Eva Níčová
- Department of Population Ecology, Institute of Botany, Czech Academy of Sciences, Zámek 1, Průhonice, Czech Republic
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6
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Helenek C, Krzysztoń R, Petreczky J, Wan Y, Cabral M, Coraci D, Balázsi G. Synthetic gene circuit evolution: Insights and opportunities at the mid-scale. Cell Chem Biol 2024:S2451-9456(24)00219-8. [PMID: 38925113 DOI: 10.1016/j.chembiol.2024.05.018] [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: 02/12/2024] [Revised: 05/07/2024] [Accepted: 05/30/2024] [Indexed: 06/28/2024]
Abstract
Directed evolution focuses on optimizing single genetic components for predefined engineering goals by artificial mutagenesis and selection. In contrast, experimental evolution studies the adaptation of entire genomes in serially propagated cell populations, to provide an experimental basis for evolutionary theory. There is a relatively unexplored gap at the middle ground between these two techniques, to evolve in vivo entire synthetic gene circuits with nontrivial dynamic function instead of single parts or whole genomes. We discuss the requirements for such mid-scale evolution, with hypothetical examples for evolving synthetic gene circuits by appropriate selection and targeted shuffling of a seed set of genetic components in vivo. Implementing similar methods should aid the rapid generation, functionalization, and optimization of synthetic gene circuits in various organisms and environments, accelerating both the development of biomedical and technological applications and the understanding of principles guiding regulatory network evolution.
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Affiliation(s)
- Christopher Helenek
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA
| | - Rafał Krzysztoń
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Julia Petreczky
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Chemistry, Stony Brook University, Stony Brook, NY 11794, USA
| | - Yiming Wan
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Mariana Cabral
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA
| | - Damiano Coraci
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Gábor Balázsi
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA; Stony Brook Cancer Center, Stony Brook University, Stony Brook, NY 11794, USA.
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7
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Schmidlin, Apodaca, Newell, Sastokas, Kinsler, Geiler-Samerotte. Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.17.562616. [PMID: 37905147 PMCID: PMC10614906 DOI: 10.1101/2023.10.17.562616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into 6 classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, while others do. And some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings may yet empower multidrug strategies that leverage tradeoffs to combat resistance. More generally speaking, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.
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Affiliation(s)
- Schmidlin
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ
- School of Life Sciences, Arizona State University, Tempe AZ
| | - Apodaca
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ
- School of Life Sciences, Arizona State University, Tempe AZ
| | - Newell
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ
- School of Life Sciences, Arizona State University, Tempe AZ
| | - Sastokas
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ
- School of Life Sciences, Arizona State University, Tempe AZ
| | - Kinsler
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
| | - Geiler-Samerotte
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ
- School of Life Sciences, Arizona State University, Tempe AZ
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8
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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:S1871-6784(24)00023-2. [PMID: 38871051 DOI: 10.1016/j.nbt.2024.06.002] [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: 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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9
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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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10
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Li XC, Gandara L, Ekelöf M, Richter K, Alexandrov T, Crocker J. Rapid response of fly populations to gene dosage across development and generations. Nat Commun 2024; 15:4551. [PMID: 38811562 PMCID: PMC11137061 DOI: 10.1038/s41467-024-48960-4] [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: 09/06/2023] [Accepted: 05/17/2024] [Indexed: 05/31/2024] Open
Abstract
Although the effects of genetic and environmental perturbations on multicellular organisms are rarely restricted to single phenotypic layers, our current understanding of how developmental programs react to these challenges remains limited. Here, we have examined the phenotypic consequences of disturbing the bicoid regulatory network in early Drosophila embryos. We generated flies with two extra copies of bicoid, which causes a posterior shift of the network's regulatory outputs and a decrease in fitness. We subjected these flies to EMS mutagenesis, followed by experimental evolution. After only 8-15 generations, experimental populations have normalized patterns of gene expression and increased survival. Using a phenomics approach, we find that populations were normalized through rapid increases in embryo size driven by maternal changes in metabolism and ovariole development. We extend our results to additional populations of flies, demonstrating predictability. Together, our results necessitate a broader view of regulatory network evolution at the systems level.
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Affiliation(s)
- Xueying C Li
- European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
- College of Life Sciences, Beijing Normal University, Beijing, China.
| | - Lautaro Gandara
- European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Måns Ekelöf
- European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Kerstin Richter
- European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Theodore Alexandrov
- European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
- Molecular Medicine Partnership Unit between EMBL and Heidelberg University, Heidelberg, Germany
- BioInnovation Institute, Copenhagen, Denmark
| | - Justin Crocker
- European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
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11
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Wang W, Qiu Z, Li H, Wu X, Cui Y, Xie L, Chang B, Li P, Zeng H, Ding T. Patient-derived pathogenic microbe deposition enhances exposure risk in pediatric clinics. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 924:171703. [PMID: 38490424 DOI: 10.1016/j.scitotenv.2024.171703] [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: 10/16/2023] [Revised: 03/11/2024] [Accepted: 03/12/2024] [Indexed: 03/17/2024]
Abstract
Healthcare-associated infections (HAIs) pose significant risks to pediatric patients in outpatient settings. To prevent HAIs, understanding the sources and transmission routes of pathogenic microorganisms is crucial. This study aimed to identify the sources of opportunistic bacterial pathogens (OBPs) in pediatric outpatient settings and determine their transmission routes. Furthermore, assessing the public health risks associated with the core OBPs is important. We collected 310 samples from various sites in pediatric outpatient areas and quantified the bacteria using qPCR and CFU counting. We also performed 16S rRNA gene and single-bacterial whole-genome sequencing to profile the transmission routes and antibiotic resistance characteristics of OBPs. We observed significant variations in microbial diversity and composition among sampling sites in pediatric outpatient settings, with active communication of the microbiota between linked areas. We found that the primary source of OBPs in multi-person contact areas was the hand surface, particularly in pediatric patients. Five core OBPs, Staphylococcus epidermidis, Acinetobacter baumannii, Pseudomonas aeruginosa, Streptococcus mitis, and Streptococcus oralis, were mainly derived from pediatric patients and spread into the environment. These OBPs accumulated at multi-person contact sites, resulting in high microbial diversity in these areas. Transmission tests confirmed the challenging spread of these pathogens, with S. epidermidis transferring from the patient's hand to the environment, leading to an increased abundance and emergence of related strains. More importantly, S. epidermidis isolated from pediatric patients carried more antibiotic-resistance genes. In addition, two strains of multidrug-resistant A. baumannii were isolated from both a child and a parent, confirming the transmission of the five core OBPs centered around pediatric patients and multi-person contact areas. Our results demonstrate that pediatric patients serve as a significant source of OBPs in pediatric outpatient settings. OBPs carried by pediatric patients pose a high public health risk. To effectively control HAIs, increasing hand hygiene measures in pediatric patients and enhancing the frequency of disinfection in multi-person contact areas remains crucial. By targeting these preventive measures, the spread of OBPs can be reduced, thereby mitigating the risk of HAIs in pediatric outpatient settings.
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Affiliation(s)
- Wan Wang
- Department of Immunology and Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control (Sun Yat-sen University), Ministry of Education, Guangzhou 510080, China
| | - Zongyao Qiu
- Center for Disease Control and Prevention of Nanhai District, Foshan 528200, China
| | - Hui Li
- Department of Immunology and Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control (Sun Yat-sen University), Ministry of Education, Guangzhou 510080, China
| | - Xiaorong Wu
- Department of Immunology and Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control (Sun Yat-sen University), Ministry of Education, Guangzhou 510080, China
| | - Ying Cui
- Department of Immunology and Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control (Sun Yat-sen University), Ministry of Education, Guangzhou 510080, China
| | - Lixiang Xie
- Department of Immunology and Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control (Sun Yat-sen University), Ministry of Education, Guangzhou 510080, China
| | - Bozhen Chang
- Department of Immunology and Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control (Sun Yat-sen University), Ministry of Education, Guangzhou 510080, China
| | - Peipei Li
- Department of Immunology and Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control (Sun Yat-sen University), Ministry of Education, Guangzhou 510080, China
| | - Hong Zeng
- Center for Disease Control and Prevention of Nanhai District, Foshan 528200, China.
| | - Tao Ding
- Department of Immunology and Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control (Sun Yat-sen University), Ministry of Education, Guangzhou 510080, China.
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12
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Labourel FJF, Daubin V, Menu F, Rajon E. Proteome allocation and the evolution of metabolic cross-feeding. Evolution 2024; 78:849-859. [PMID: 38376478 DOI: 10.1093/evolut/qpae008] [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: 12/27/2022] [Revised: 01/12/2024] [Accepted: 01/18/2024] [Indexed: 02/21/2024]
Abstract
In a common instance of metabolic cross-feeding (MCF), an organism incompletely metabolizes nutrients and releases metabolites that are used by another to produce energy or building blocks. Why would the former waste edible food, and why does this preferentially occur at specific locations in a metabolic pathway have challenged evolutionary theory for decades. To address these questions, we combine adaptive dynamics with an explicit model of cell metabolism, including enzyme-driven catalysis of metabolic reactions and the cellular constraints acting on the proteome that may incur a cost to expressing all enzymes along a pathway. After pointing out that cells should in principle prioritize upstream reactions when metabolites are restrained inside the cell, we show that the occurrence of permeability-driven MCF is rare and requires that an intermediate metabolite be extremely diffusive. Indeed, only at very high levels of membrane permeability (consistent with those of acetate and glycerol, for instance) and under distinctive sets of parameters should the population diversify and MCF evolve. These results help understand the origins of simple microbial communities, such as those that readily evolve in short-term evolutionary experiments, and may later be extended to investigate how evolution has progressively built up today's extremely diverse ecosystems.
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Affiliation(s)
- Florian J F Labourel
- Univ Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive UMR5558, Villeurbanne, France
- Milner Centre for Evolution, University of Bath, Bath, United Kingdom
- Department of Life Sciences, University of Bath, Bath, United Kingdom
| | - Vincent Daubin
- Univ Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive UMR5558, Villeurbanne, France
| | - Frédéric Menu
- Univ Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive UMR5558, Villeurbanne, France
| | - Etienne Rajon
- Univ Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive UMR5558, Villeurbanne, France
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13
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Kim K, Choe D, Kang M, Cho SH, Cho S, Jeong KJ, Palsson B, Cho BK. Serial adaptive laboratory evolution enhances mixed carbon metabolic capacity of Escherichia coli. Metab Eng 2024; 83:160-171. [PMID: 38636729 DOI: 10.1016/j.ymben.2024.04.004] [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: 01/12/2024] [Revised: 03/31/2024] [Accepted: 04/14/2024] [Indexed: 04/20/2024]
Abstract
Microbes have inherent capacities for utilizing various carbon sources, however they often exhibit sub-par fitness due to low metabolic efficiency. To test whether a bacterial strain can optimally utilize multiple carbon sources, Escherichia coli was serially evolved in L-lactate and glycerol. This yielded two end-point strains that evolved first in L-lactate then in glycerol, and vice versa. The end-point strains displayed a universal growth advantage on single and a mixture of adaptive carbon sources, enabled by a concerted action of carbon source-specialists and generalist mutants. The combination of just four variants of glpK, ppsA, ydcI, and rph-pyrE, accounted for more than 80% of end-point strain fitness. In addition, machine learning analysis revealed a coordinated activity of transcriptional regulators imparting condition-specific regulation of gene expression. The effectiveness of the serial adaptive laboratory evolution (ALE) scheme in bioproduction applications was assessed under single and mixed-carbon culture conditions, in which serial ALE strain exhibited superior productivity of acetoin compared to ancestral strains. Together, systems-level analysis elucidated the molecular basis of serial evolution, which hold potential utility in bioproduction applications.
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Affiliation(s)
- Kangsan Kim
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea; KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Donghui Choe
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Minjeong Kang
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea; KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Sang-Hyeok Cho
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea; KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Suhyung Cho
- KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Ki Jun Jeong
- KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea; Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea; Graduate School of Engineering Biology, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Bernhard Palsson
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA; Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA
| | - Byung-Kwan Cho
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea; KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea; Graduate School of Engineering Biology, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
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14
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uz-Zaman MH, D’Alton S, Barrick JE, Ochman H. Promoter recruitment drives the emergence of proto-genes in a long-term evolution experiment with Escherichia coli. PLoS Biol 2024; 22:e3002418. [PMID: 38713714 PMCID: PMC11101190 DOI: 10.1371/journal.pbio.3002418] [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: 10/18/2023] [Revised: 05/17/2024] [Accepted: 04/18/2024] [Indexed: 05/09/2024] Open
Abstract
The phenomenon of de novo gene birth-the emergence of genes from non-genic sequences-has received considerable attention due to the widespread occurrence of genes that are unique to particular species or genomes. Most instances of de novo gene birth have been recognized through comparative analyses of genome sequences in eukaryotes, despite the abundance of novel, lineage-specific genes in bacteria and the relative ease with which bacteria can be studied in an experimental context. Here, we explore the genetic record of the Escherichia coli long-term evolution experiment (LTEE) for changes indicative of "proto-genic" phases of new gene birth in which non-genic sequences evolve stable transcription and/or translation. Over the time span of the LTEE, non-genic regions are frequently transcribed, translated and differentially expressed, with levels of transcription across low-expressed regions increasing in later generations of the experiment. Proto-genes formed downstream of new mutations result either from insertion element activity or chromosomal translocations that fused preexisting regulatory sequences to regions that were not expressed in the LTEE ancestor. Additionally, we identified instances of proto-gene emergence in which a previously unexpressed sequence was transcribed after formation of an upstream promoter, although such cases were rare compared to those caused by recruitment of preexisting promoters. Tracing the origin of the causative mutations, we discovered that most occurred early in the history of the LTEE, often within the first 20,000 generations, and became fixed soon after emergence. Our findings show that proto-genes emerge frequently within evolving populations, can persist stably, and can serve as potential substrates for new gene formation.
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Affiliation(s)
- Md. Hassan uz-Zaman
- Department of Molecular Biosciences, University of Texas at Austin, Austin, Texas, United States of America
| | - Simon D’Alton
- Department of Molecular Biosciences, University of Texas at Austin, Austin, Texas, United States of America
| | - Jeffrey E. Barrick
- Department of Molecular Biosciences, University of Texas at Austin, Austin, Texas, United States of America
| | - Howard Ochman
- Department of Molecular Biosciences, University of Texas at Austin, Austin, Texas, United States of America
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15
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Liang J, Faucher SP. Interactions between chaperone and energy storage networks during the evolution of Legionella pneumophila under heat shock. PeerJ 2024; 12:e17197. [PMID: 38708341 PMCID: PMC11067923 DOI: 10.7717/peerj.17197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 03/14/2024] [Indexed: 05/07/2024] Open
Abstract
Waterborne transmission of the bacterium Legionella pneumophila has emerged as a major cause of severe nosocomial infections of major public health impact. The major route of transmission involves the uptake of aerosolized bacteria, often from the contaminated hot water systems of large buildings. Public health regulations aimed at controlling the mesophilic pathogen are generally concerned with acute pasteurization and maintaining high temperatures at the heating systems and throughout the plumbing of hot water systems, but L. pneumophila is often able to survive these treatments due to both bacterium-intrinsic and environmental factors. Previous work has established an experimental evolution system to model the observations of increased heat resistance in repeatedly but unsuccessfully pasteurized L. pneumophila populations. Here, we show rapid fixation of novel alleles in lineages selected for resistance to heat shock and shifts in mutational profile related to increases in the temperature of selection. Gene-level and nucleotide-level parallelisms between independently-evolving lineages show the centrality of the DnaJ/DnaK chaperone system in the heat resistance of L. pneumophila. Inference of epistatic interactions through reverse genetics shows an unexpected interaction between DnaJ/DnaK and the polyhydroxybutyrate-accumulation energy storage mechanism used by the species to survive long-term starvation in low-nutrient environments.
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Affiliation(s)
- Jeffrey Liang
- Department of Natural Resource Sciences, McGill University, Sainte-Anne-de-Bellevue, Quebec, Canada
| | - Sebastien P. Faucher
- Department of Natural Resource Sciences, McGill University, Sainte-Anne-de-Bellevue, Quebec, Canada
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16
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Hariri Akbari F, Song Z, Turk M, Gunde-Cimerman N, Gostinčar C. Experimental evolution of extremotolerant and extremophilic fungi under osmotic stress. IUBMB Life 2024. [PMID: 38647201 DOI: 10.1002/iub.2825] [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: 12/29/2023] [Accepted: 03/15/2024] [Indexed: 04/25/2024]
Abstract
Experimental evolution was carried out to investigate the adaptive responses of extremotolerant fungi to a stressful environment. For 12 cultivation cycles, the halotolerant black yeasts Aureobasidium pullulans and Aureobasidium subglaciale were grown at high NaCl or glycerol concentrations, and the halophilic basidiomycete Wallemia ichthyophaga was grown close to its lower NaCl growth limit. All evolved Aureobasidium spp. accelerated their growth at low water activity. Whole genomes of the evolved strains were sequenced. No aneuploidies were detected in any of the genomes, contrary to previous studies on experimental evolution at high salinity with other species. However, several hundred single-nucleotide polymorphisms were identified compared with the genomes of the progenitor strains. Two functional groups of genes were overrepresented among the genes presumably affected by single-nucleotide polymorphisms: voltage-gated potassium channels in A. pullulans at high NaCl concentration, and hydrophobins in W. ichthyophaga at low NaCl concentration. Both groups of genes were previously associated with adaptation to high salinity. Finally, most evolved Aureobasidium spp. strains were found to have increased intracellular and decreased extracellular glycerol concentrations at high salinity, suggesting that the strains have optimised their management of glycerol, their most important compatible solute. Experimental evolution therefore not only confirmed the role of potassium transport, glycerol management, and cell wall in survival at low water activity, but also demonstrated that fungi from extreme environments can further improve their growth rates under constant extreme conditions in a relatively short time and without large scale genomic rearrangements.
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Affiliation(s)
- Farhad Hariri Akbari
- Biotechnical Faculty, Department of Biology, University of Ljubljana, Ljubljana, Slovenia
| | - Zewei Song
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Martina Turk
- Biotechnical Faculty, Department of Biology, University of Ljubljana, Ljubljana, Slovenia
| | - Nina Gunde-Cimerman
- Biotechnical Faculty, Department of Biology, University of Ljubljana, Ljubljana, Slovenia
| | - Cene Gostinčar
- Biotechnical Faculty, Department of Biology, University of Ljubljana, Ljubljana, Slovenia
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17
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Devadhasan A, Kolodny O, Carja O. Competition for resources can reshape the evolutionary properties of spatial structure. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.13.589370. [PMID: 38659847 PMCID: PMC11042312 DOI: 10.1101/2024.04.13.589370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Many evolving ecosystems have spatial structures that can be conceptualized as networks, with nodes representing individuals or homogeneous subpopulations and links the patterns of interaction and replacement between them. Prior models of evolution on networks do not take ecological niche differences and eco-evolutionary interplay into account. Here, we combine a resource competition model with evolutionary graph theory to study how heterogeneous topological structure shapes evolutionary dynamics under global frequency-dependent ecological interactions. We find that the addition of ecological competition for resources can produce a reversal of roles between amplifier and suppressor networks for deleterious mutants entering the population. Moreover, we show that this effect is a non-linear function of ecological niche overlap and discuss intuition for the observed dynamics using simulations and analytical approximations.
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Affiliation(s)
- Anush Devadhasan
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Oren Kolodny
- Department of Ecology, Evolution, and Behavior, E. Silberman Institute of Life Sciences, The Hebrew University of Jerusalem
| | - Oana Carja
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
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18
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Behringer MG, Ho WC, Miller SF, Worthan SB, Cen Z, Stikeleather R, Lynch M. Trade-offs, trade-ups, and high mutational parallelism underlie microbial adaptation during extreme cycles of feast and famine. Curr Biol 2024; 34:1403-1413.e5. [PMID: 38460514 PMCID: PMC11066936 DOI: 10.1016/j.cub.2024.02.040] [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: 10/04/2023] [Revised: 12/12/2023] [Accepted: 02/16/2024] [Indexed: 03/11/2024]
Abstract
Microbes are evolutionarily robust organisms capable of rapid adaptation to complex stress, which enables them to colonize harsh environments. In nature, microbes are regularly challenged by starvation, which is a particularly complex stress because resource limitation often co-occurs with changes in pH, osmolarity, and toxin accumulation created by metabolic waste. Often overlooked are the additional complications introduced by eventual resource replenishment, as successful microbes must withstand rapid environmental shifts before swiftly capitalizing on replenished resources to avoid invasion by competing species. To understand how microbes navigate trade-offs between growth and survival, ultimately adapting to thrive in environments with extreme fluctuations, we experimentally evolved 16 Escherichia coli populations for 900 days in repeated feast/famine conditions with cycles of 100-day starvation before resource replenishment. Using longitudinal population-genomic analysis, we found that evolution in response to extreme feast/famine is characterized by narrow adaptive trajectories with high mutational parallelism and notable mutational order. Genetic reconstructions reveal that early mutations result in trade-offs for biofilm and motility but trade-ups for growth and survival, as these mutations conferred positively correlated advantages during both short-term and long-term culture. Our results demonstrate how microbes can navigate the adaptive landscapes of regularly fluctuating conditions and ultimately follow mutational trajectories that confer benefits across diverse environments.
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Affiliation(s)
- Megan G Behringer
- Department of Biological Sciences, Vanderbilt University, 21st Avenue S, Nashville, TN 37232, USA; Department of Pathology Microbiology and Immunology, Vanderbilt University Medical Center, 21st Avenue S, Nashville, TN 37232, USA.
| | - Wei-Chin Ho
- Biodesign Center for Mechanisms of Evolution, Arizona State University, S McAllister Ave., Tempe, AZ 85281, USA; Department of Biology, University of Texas at Tyler, University Blvd., Tyler, TX 75799, USA.
| | - Samuel F Miller
- Biodesign Center for Mechanisms of Evolution, Arizona State University, S McAllister Ave., Tempe, AZ 85281, USA
| | - Sarah B Worthan
- Department of Biological Sciences, Vanderbilt University, 21st Avenue S, Nashville, TN 37232, USA
| | - Zeer Cen
- Department of Biological Sciences, Vanderbilt University, 21st Avenue S, Nashville, TN 37232, USA
| | - Ryan Stikeleather
- Biodesign Center for Mechanisms of Evolution, Arizona State University, S McAllister Ave., Tempe, AZ 85281, USA
| | - Michael Lynch
- Biodesign Center for Mechanisms of Evolution, Arizona State University, S McAllister Ave., Tempe, AZ 85281, USA
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19
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Garushyants SK, Sane M, Selifanova MV, Agashe D, Bazykin GA, Gelfand MS. Mutational Signatures in Wild Type Escherichia coli Strains Reveal Predominance of DNA Polymerase Errors. Genome Biol Evol 2024; 16:evae035. [PMID: 38401265 PMCID: PMC10995721 DOI: 10.1093/gbe/evae035] [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: 12/06/2023] [Revised: 02/13/2024] [Accepted: 02/17/2024] [Indexed: 02/26/2024] Open
Abstract
While mutational processes operating in the Escherichia coli genome have been revealed by multiple laboratory experiments, the contribution of these processes to accumulation of bacterial polymorphism and evolution in natural environments is unknown. To address this question, we reconstruct signatures of distinct mutational processes from experimental data on E. coli hypermutators, and ask how these processes contribute to differences between naturally occurring E. coli strains. We show that both mutations accumulated in the course of evolution of wild-type strains in nature and in the lab-grown nonmutator laboratory strains are explained predominantly by the low fidelity of DNA polymerases II and III. By contrast, contributions specific to disruption of DNA repair systems cannot be detected, suggesting that temporary accelerations of mutagenesis associated with such disruptions are unimportant for within-species evolution. These observations demonstrate that accumulation of diversity in bacterial strains in nature is predominantly associated with errors of DNA polymerases.
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Affiliation(s)
- Sofya K Garushyants
- A.A. Kharkevich Institute for Information Transmission Problems, RAS, Moscow, Russia
| | - Mrudula Sane
- National Centre for Biological Sciences, Bengaluru, India
| | - Maria V Selifanova
- Faculty of Bioengineering and Bioinformatics, M.V. Lomonosov Moscow State University, Moscow, Russia
| | - Deepa Agashe
- National Centre for Biological Sciences, Bengaluru, India
| | - Georgii A Bazykin
- A.A. Kharkevich Institute for Information Transmission Problems, RAS, Moscow, Russia
| | - Mikhail S Gelfand
- A.A. Kharkevich Institute for Information Transmission Problems, RAS, Moscow, Russia
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
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20
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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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21
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Logares R. Decoding populations in the ocean microbiome. MICROBIOME 2024; 12:67. [PMID: 38561814 PMCID: PMC10983722 DOI: 10.1186/s40168-024-01778-0] [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: 09/27/2023] [Accepted: 02/12/2024] [Indexed: 04/04/2024]
Abstract
Understanding the characteristics and structure of populations is fundamental to comprehending ecosystem processes and evolutionary adaptations. While the study of animal and plant populations has spanned a few centuries, microbial populations have been under scientific scrutiny for a considerably shorter period. In the ocean, analyzing the genetic composition of microbial populations and their adaptations to multiple niches can yield important insights into ecosystem function and the microbiome's response to global change. However, microbial populations have remained elusive to the scientific community due to the challenges associated with isolating microorganisms in the laboratory. Today, advancements in large-scale metagenomics and metatranscriptomics facilitate the investigation of populations from many uncultured microbial species directly from their habitats. The knowledge acquired thus far reveals substantial genetic diversity among various microbial species, showcasing distinct patterns of population differentiation and adaptations, and highlighting the significant role of selection in structuring populations. In the coming years, population genomics is expected to significantly increase our understanding of the architecture and functioning of the ocean microbiome, providing insights into its vulnerability or resilience in the face of ongoing global change. Video Abstract.
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Affiliation(s)
- Ramiro Logares
- Institute of Marine Sciences (ICM), CSIC, Barcelona, Catalonia, 08003, Spain.
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22
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Deng H, Yu H, Deng Y, Qiu Y, Li F, Wang X, He J, Liang W, Lan Y, Qiao L, Zhang Z, Zhang Y, Keasling JD, Luo X. Pathway Evolution Through a Bottlenecking-Debottlenecking Strategy and Machine Learning-Aided Flux Balancing. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2306935. [PMID: 38321783 PMCID: PMC11005738 DOI: 10.1002/advs.202306935] [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: 09/21/2023] [Revised: 12/24/2023] [Indexed: 02/08/2024]
Abstract
The evolution of pathway enzymes enhances the biosynthesis of high-value chemicals, crucial for pharmaceutical, and agrochemical applications. However, unpredictable evolutionary landscapes of pathway genes often hinder successful evolution. Here, the presence of complex epistasis is identifued within the representative naringenin biosynthetic pathway enzymes, hampering straightforward directed evolution. Subsequently, a biofoundry-assisted strategy is developed for pathway bottlenecking and debottlenecking, enabling the parallel evolution of all pathway enzymes along a predictable evolutionary trajectory in six weeks. This study then utilizes a machine learning model, ProEnsemble, to further balance the pathway by optimizing the transcription of individual genes. The broad applicability of this strategy is demonstrated by constructing an Escherichia coli chassis with evolved and balanced pathway genes, resulting in 3.65 g L-1 naringenin. The optimized naringenin chassis also demonstrates enhanced production of other flavonoids. This approach can be readily adapted for any given number of enzymes in the specific metabolic pathway, paving the way for automated chassis construction in contemporary biofoundries.
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Affiliation(s)
- Huaxiang Deng
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of BiotechnologyJiangnan UniversityWuxi214122P. R. China
| | - Han Yu
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- University of Chinese Academy of SciencesBeijing100049P. R. China
| | - Yanwu Deng
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
| | - Yulan Qiu
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
| | - Feifei Li
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
| | - Xinran Wang
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
| | - Jiahui He
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
| | - Weiyue Liang
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of BiotechnologyJiangnan UniversityWuxi214122P. R. China
| | - Yunquan Lan
- Shenzhen Infrastructure for Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
| | - Longjiang Qiao
- Shenzhen Infrastructure for Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
| | - Zhiyu Zhang
- Shenzhen Infrastructure for Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
| | - Yunfeng Zhang
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
| | - Jay D. Keasling
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Joint BioEnergy InstituteEmeryvilleCA94608USA
- Biological Systems and Engineering DivisionLawrence Berkeley National LaboratoryBerkeleyCA94720USA
- Department of Chemical and Biomolecular Engineering & Department of BioengineeringUniversity of CaliforniaBerkeleyCA94720USA
- Novo Nordisk Foundation Center for BiosustainabilityTechnical University of DenmarkKgs. Lyngby2800Denmark
| | - Xiaozhou Luo
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
- University of Chinese Academy of SciencesBeijing100049P. R. China
- Shenzhen Infrastructure for Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055P. R. China
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23
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Maltas J, Tadele DS, Durmaz A, McFarland CD, Hinczewski M, Scott JG. Frequency-dependent ecological interactions increase the prevalence, and shape the distribution, of pre-existing drug resistance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.16.533001. [PMID: 36993678 PMCID: PMC10055114 DOI: 10.1101/2023.03.16.533001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
The evolution of resistance remains one of the primary challenges for modern medicine from infectious diseases to cancers. Many of these resistance-conferring mutations often carry a substantial fitness cost in the absence of treatment. As a result, we would expect these mutants to undergo purifying selection and be rapidly driven to extinction. Nevertheless, pre-existing resistance is frequently observed from drug-resistant malaria to targeted cancer therapies in non-small cell lung cancer (NSCLC) and melanoma. Solutions to this apparent paradox have taken several forms from spatial rescue to simple mutation supply arguments. Recently, in an evolved resistant NSCLC cell line, we found that frequency-dependent ecological interactions between ancestor and resistant mutant ameliorate the cost of resistance in the absence of treatment. Here, we hypothesize that frequency-dependent ecological interactions in general play a major role in the prevalence of pre-existing resistance. We combine numerical simulations with robust analytical approximations to provide a rigorous mathematical framework for studying the effects of frequency-dependent ecological interactions on the evolutionary dynamics of pre-existing resistance. First, we find that ecological interactions significantly expand the parameter regime under which we expect to observe pre-existing resistance. Next, even when positive ecological interactions between mutants and ancestors are rare, these resistant clones provide the primary mode of evolved resistance because even weak positive interaction leads to significantly longer extinction times. We then find that even in the case where mutation supply alone is sufficient to predict pre-existing resistance, frequency-dependent ecological forces still contribute a strong evolutionary pressure that selects for increasingly positive ecological effects (negative frequency-dependent selection). Finally, we genetically engineer several of the most common clinically observed resistance mechanisms to targeted therapies in NSCLC, a treatment notorious for pre-existing resistance. We find that each engineered mutant displays a positive ecological interaction with their ancestor. As a whole, these results suggest that frequency-dependent ecological effects can play a crucial role in shaping the evolutionary dynamics of pre-existing resistance.
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Affiliation(s)
- Jeff Maltas
- Cleveland Clinic, Translational Hematology Oncology Research, Cleveland, OH
- Case Western Reserve University, School of Medicine, Cleveland, OH
| | - Dagim Shiferaw Tadele
- Cleveland Clinic, Translational Hematology Oncology Research, Cleveland, OH
- Oslo University Hospital, Ullevål, Department of Medical Genetics, Oslo, Norway
| | - Arda Durmaz
- Cleveland Clinic, Translational Hematology Oncology Research, Cleveland, OH
| | - Christopher D. McFarland
- Case Western Reserve University, School of Medicine, Cleveland, OH
- Case Comprehensive Cancer Center, Cleveland, OH
| | | | - Jacob G. Scott
- Cleveland Clinic, Translational Hematology Oncology Research, Cleveland, OH
- Case Western Reserve University, School of Medicine, Cleveland, OH
- Case Western Reserve University, Department of Physics, Cleveland, OH
- Case Comprehensive Cancer Center, Cleveland, OH
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24
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Bernatchez L, Ferchaud AL, Berger CS, Venney CJ, Xuereb A. Genomics for monitoring and understanding species responses to global climate change. Nat Rev Genet 2024; 25:165-183. [PMID: 37863940 DOI: 10.1038/s41576-023-00657-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/29/2023] [Indexed: 10/22/2023]
Abstract
All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.
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Affiliation(s)
- Louis Bernatchez
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
| | - Anne-Laure Ferchaud
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada.
- Parks Canada, Office of the Chief Ecosystem Scientist, Protected Areas Establishment, Quebec City, Quebec, Canada.
| | - Chloé Suzanne Berger
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
| | - Clare J Venney
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
| | - Amanda Xuereb
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
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25
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Shi M, Evans CA, McQuillan JL, Noirel J, Pandhal J. LFQRatio: A Normalization Method to Decipher Quantitative Proteome Changes in Microbial Coculture Systems. J Proteome Res 2024; 23:999-1013. [PMID: 38354288 PMCID: PMC10913063 DOI: 10.1021/acs.jproteome.3c00714] [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: 02/16/2024]
Abstract
The value of synthetic microbial communities in biotechnology is gaining traction due to their ability to undertake more complex metabolic tasks than monocultures. However, a thorough understanding of strain interactions, productivity, and stability is often required to optimize growth and scale up cultivation. Quantitative proteomics can provide valuable insights into how microbial strains adapt to changing conditions in biomanufacturing. However, current workflows and methodologies are not suitable for simple artificial coculture systems where strain ratios are dynamic. Here, we established a workflow for coculture proteomics using an exemplar system containing two members, Azotobacter vinelandii and Synechococcus elongatus. Factors affecting the quantitative accuracy of coculture proteomics were investigated, including peptide physicochemical characteristics such as molecular weight, isoelectric point, hydrophobicity, and dynamic range as well as factors relating to protein identification such as varying proteome size and shared peptides between species. Different quantification methods based on spectral counts and intensity were evaluated at the protein and cell level. We propose a new normalization method, named "LFQRatio", to reflect the relative contributions of two distinct cell types emerging from cell ratio changes during cocultivation. LFQRatio can be applied to real coculture proteomics experiments, providing accurate insights into quantitative proteome changes in each strain.
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Affiliation(s)
- Mengxun Shi
- Department of Chemical and Biological Engineering, The University of Sheffield, Mappin Street, Sheffield S1 3JD, U.K
| | - Caroline A Evans
- Department of Chemical and Biological Engineering, The University of Sheffield, Mappin Street, Sheffield S1 3JD, U.K
| | - Josie L McQuillan
- Department of Chemical and Biological Engineering, The University of Sheffield, Mappin Street, Sheffield S1 3JD, U.K
| | - Josselin Noirel
- GBCM Laboratory (EA7528), Conservatoire National des Arts et Métiers, HESAM Université, 2 rue Conté, Paris 75003, France
| | - Jagroop Pandhal
- Department of Chemical and Biological Engineering, The University of Sheffield, Mappin Street, Sheffield S1 3JD, U.K
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26
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Razo-Mejia M, Mani M, Petrov D. Bayesian inference of relative fitness on high-throughput pooled competition assays. PLoS Comput Biol 2024; 20:e1011937. [PMID: 38489348 PMCID: PMC10971673 DOI: 10.1371/journal.pcbi.1011937] [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: 10/18/2023] [Revised: 03/27/2024] [Accepted: 02/21/2024] [Indexed: 03/17/2024] Open
Abstract
The tracking of lineage frequencies via DNA barcode sequencing enables the quantification of microbial fitness. However, experimental noise coming from biotic and abiotic sources complicates the computation of a reliable inference. We present a Bayesian pipeline to infer relative microbial fitness from high-throughput lineage tracking assays. Our model accounts for multiple sources of noise and propagates uncertainties throughout all parameters in a systematic way. Furthermore, using modern variational inference methods based on automatic differentiation, we are able to scale the inference to a large number of unique barcodes. We extend this core model to analyze multi-environment assays, replicate experiments, and barcodes linked to genotypes. On simulations, our method recovers known parameters within posterior credible intervals. This work provides a generalizable Bayesian framework to analyze lineage tracking experiments. The accompanying open-source software library enables the adoption of principled statistical methods in experimental evolution.
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Affiliation(s)
- Manuel Razo-Mejia
- Department of Biology, Stanford University, Stanford, California, United States of America
| | - Madhav Mani
- NSF-Simons Center for Quantitative Biology, Northwestern University, Chicago, Illinois, United States of America
- Department of Engineering Sciences and Applied Mathematics, Northwestern University, Chicago, Illinois, United States of America
| | - Dmitri Petrov
- Department of Biology, Stanford University, Stanford, California, United States of America
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California, United States of America
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
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27
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Shoemaker WR. Eco-evolutionary dynamics: The repeatability of diversification in an experimental microbial community. Curr Biol 2024; 34:R140-R143. [PMID: 38412822 DOI: 10.1016/j.cub.2023.12.053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
Understanding the evolution and subsequent maintenance of ecological diversity is a daunting task. Using a historical microbial evolution experiment, a new paper demonstrates the extent to which diversity can re-emerge in reduced communities and the traits through which rediversification occurs.
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Affiliation(s)
- William R Shoemaker
- Quantitative Life Sciences, The Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste 34151, Italy.
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28
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Ascensao JA, Denk J, Lok K, Yu Q, Wetmore KM, Hallatschek O. Rediversification following ecotype isolation reveals hidden adaptive potential. Curr Biol 2024; 34:855-867.e6. [PMID: 38325377 PMCID: PMC10911448 DOI: 10.1016/j.cub.2024.01.029] [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: 05/10/2023] [Revised: 11/09/2023] [Accepted: 01/10/2024] [Indexed: 02/09/2024]
Abstract
Microbial communities play a critical role in ecological processes, and their diversity is key to their functioning. However, little is known about whether communities can regenerate ecological diversity following ecotype removal or extinction and how the rediversified communities would compare to the original ones. Here, we show that simple two-ecotype communities from the E. coli long-term evolution experiment (LTEE) consistently rediversified into two ecotypes following the isolation of one of the ecotypes, coexisting via negative frequency-dependent selection. Communities separated by more than 30,000 generations of evolutionary time rediversify in similar ways. The rediversified ecotype appears to share a number of growth traits with the ecotype it replaces. However, the rediversified community is also different from the original community in ways relevant to the mechanism of ecotype coexistence-for example, in stationary phase response and survival. We found substantial variation in the transcriptional states between the two original ecotypes, whereas the differences within the rediversified community were comparatively smaller, although the rediversified community showed unique patterns of differential expression. Our results suggest that evolution may leave room for alternative diversification processes even in a maximally reduced community of only two strains. We hypothesize that the presence of alternative evolutionary pathways may be even more pronounced in communities of many species where there are even more potential niches, highlighting an important role for perturbations, such as species removal, in evolving ecological communities.
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Affiliation(s)
- Joao A Ascensao
- Department of Bioengineering, University of California Berkeley, Berkeley, CA, USA
| | - Jonas Denk
- Department of Physics, University of California Berkeley Berkeley, CA, USA
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
| | - Kristen Lok
- Department of Bioengineering, University of California Berkeley, Berkeley, CA, USA
- Present affiliation: Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - QinQin Yu
- Department of Physics, University of California Berkeley Berkeley, CA, USA
- Present affiliation: Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Kelly M Wetmore
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA
| | - Oskar Hallatschek
- Department of Physics, University of California Berkeley Berkeley, CA, USA
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
- Peter Debye Institute for Soft Matter Physics, Leipzig University, 04103 Leipzig, Germany
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29
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Filatov DA, Kirkpatrick M. How does evolution work in superabundant microbes? Trends Microbiol 2024:S0966-842X(24)00024-6. [PMID: 38360431 DOI: 10.1016/j.tim.2024.01.009] [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: 10/13/2023] [Revised: 01/24/2024] [Accepted: 01/26/2024] [Indexed: 02/17/2024]
Abstract
Marine phytoplankton play crucial roles in the Earth's ecological, chemical, and geological processes. They are responsible for about half of global primary production and drive the ocean biological carbon pump. Understanding how plankton species may adapt to the Earth's rapidly changing environments is evidently an urgent priority. This problem requires evolutionary genetic approaches as evolution occurs at the level of allele frequency change within populations driven by genetic drift and natural selection (microevolution). Plankters such as the coccolithophore Gephyrocapsa huxleyi and the cyanobacterium Prochlorococcus 'marinus' are among Earth's most abundant organisms. In this opinion paper we discuss how evolution in astronomically large populations of superabundant microbes (SAMs) may act fundamentally differently than it does in the populations of more modest size found in well-studied organisms. This offers exciting opportunities to study evolution in the conditions that have yet to be explored and also leads to unique challenges. Exploring these opportunities and challenges is the goal of this article.
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Affiliation(s)
- Dmitry A Filatov
- Department of Biology, University of Oxford, Oxford, OX1 3RB, UK.
| | - Mark Kirkpatrick
- Department of Integrative Biology, University of Texas, Austin, TX 78712, USA
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30
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Sharma A, Timilsina S, Abrahamian P, Minsavage GV, Jones JB, Vallad GE, Goss EM. Bacterial Mutation During Seasonal Epidemics. MOLECULAR PLANT-MICROBE INTERACTIONS : MPMI 2024; 37:93-97. [PMID: 38105425 DOI: 10.1094/mpmi-10-23-0164-sc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Rapidly evolving bacterial pathogens pose a unique challenge for long-term plant disease management. In this study, we investigated the types and rate of mutations in bacterial populations during seasonal disease epidemics. Two phylogenetically distinct strains of the bacterial spot pathogen, Xanthomonas perforans, were marked, released in tomato fields, and recaptured at several time points during the growing season. Genomic variations in recaptured isolates were identified by comparative analysis of their whole-genome sequences. In total, 180 unique variations (116 substitutions, 57 insertions/deletions, and 7 structural variations) were identified from 300 genomes, resulting in the overall host-associated mutation rate of ∼0.3 to 0.9/genome/week. This result serves as a benchmark for bacterial mutation during epidemics in similar pathosystems. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
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Affiliation(s)
- Anuj Sharma
- Department of Plant Pathology, University of Florida, Gainesville, FL, U.S.A
- Gulf Coast Research and Education Center, University of Florida, Wimauma, FL, U.S.A
| | - Sujan Timilsina
- Department of Plant Pathology, University of Florida, Gainesville, FL, U.S.A
| | - Peter Abrahamian
- Gulf Coast Research and Education Center, University of Florida, Wimauma, FL, U.S.A
| | - Gerald V Minsavage
- Department of Plant Pathology, University of Florida, Gainesville, FL, U.S.A
| | - Jeffrey B Jones
- Department of Plant Pathology, University of Florida, Gainesville, FL, U.S.A
| | - Gary E Vallad
- Gulf Coast Research and Education Center, University of Florida, Wimauma, FL, U.S.A
| | - Erica M Goss
- Department of Plant Pathology, University of Florida, Gainesville, FL, U.S.A
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, U.S.A
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31
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Nguyen ANT, Gorrell R, Kwok T, Connallon T, McDonald MJ. Horizontal gene transfer facilitates the molecular reverse-evolution of antibiotic sensitivity in experimental populations of H. pylori. Nat Ecol Evol 2024; 8:315-324. [PMID: 38177692 DOI: 10.1038/s41559-023-02269-5] [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: 05/14/2023] [Accepted: 11/09/2023] [Indexed: 01/06/2024]
Abstract
Reversing the evolution of traits harmful to humans, such as antimicrobial resistance, is a key ambition of applied evolutionary biology. A major impediment to reverse evolution is the relatively low spontaneous mutation rates that revert evolved genotypes back to their ancestral state. However, the repeated re-introduction of ancestral alleles by horizontal gene transfer (HGT) could make reverse evolution likely. Here we evolve populations of an antibiotic-resistant strain of Helicobacter pylori in growth conditions without antibiotics while introducing an ancestral antibiotic-sensitive allele by HGT. We evaluate reverse evolution using DNA sequencing and find that HGT facilitates the molecular reverse evolution of the antibiotic resistance allele, and that selection for high rates of HGT drives the evolution of increased HGT rates in low-HGT treatment populations. Finally, we use a theoretical model and carry out simulations to infer how the fitness costs of antibiotic resistance, rates of HGT and effects of genetic drift interact to determine the probability and predictability of reverse evolution.
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Affiliation(s)
- An N T Nguyen
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
- Centre to Impact AMR, Monash University, Clayton, Victoria, Australia
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia
| | - Rebecca Gorrell
- Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, Australia
- Department of Microbiology, Monash University, Clayton, Victoria, Australia
| | - Terry Kwok
- Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, Australia
- Department of Microbiology, Monash University, Clayton, Victoria, Australia
- Biomedical Discovery Institute, Monash University, Clayton, Victoria, Australia
| | - Tim Connallon
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia.
| | - Michael J McDonald
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia.
- Centre to Impact AMR, Monash University, Clayton, Victoria, Australia.
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32
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Moawad A, Abbara A, Bitbol AF. Evolution of cooperation in deme-structured populations on graphs. Phys Rev E 2024; 109:024307. [PMID: 38491653 DOI: 10.1103/physreve.109.024307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 12/19/2023] [Indexed: 03/18/2024]
Abstract
Understanding how cooperation can evolve in populations despite its cost to individual cooperators is an important challenge. Models of spatially structured populations with one individual per node of a graph have shown that cooperation, modeled via the prisoner's dilemma, can be favored by natural selection. These results depend on microscopic update rules, which determine how birth, death, and migration on the graph are coupled. Recently, we developed coarse-grained models of spatially structured populations on graphs, where each node comprises a well-mixed deme, and where migration is independent from division and death, thus bypassing the need for update rules. Here, we study the evolution of cooperation in these models in the rare-migration regime, within the prisoner's dilemma. We find that cooperation is not favored by natural selection in these coarse-grained models on graphs where overall deme fitness does not directly impact migration from a deme. This is due to a separation of scales, whereby cooperation occurs at a local level within demes, while spatial structure matters between demes.
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Affiliation(s)
- Alix Moawad
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland and SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Alia Abbara
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland and SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Anne-Florence Bitbol
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland and SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
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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] [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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Song W, Zhang S, Majzoub ME, Egan S, Kjelleberg S, Thomas T. The impact of interspecific competition on the genomic evolution of Phaeobacter inhibens and Pseudoalteromonas tunicata during biofilm growth. Environ Microbiol 2024; 26:e16553. [PMID: 38062568 DOI: 10.1111/1462-2920.16553] [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: 08/21/2023] [Accepted: 11/24/2023] [Indexed: 01/30/2024]
Abstract
Interspecific interactions in biofilms have been shown to cause the emergence of community-level properties. To understand the impact of interspecific competition on evolution, we deep-sequenced the dispersal population of mono- and co-culture biofilms of two antagonistic marine bacteria (Phaeobacter inhibens 2.10 and Pseudoalteromononas tunicata D2). Enhanced phenotypic and genomic diversification was observed in the P. tunicata D2 populations under both mono- and co-culture biofilms in comparison to P. inhibens 2.10. The genetic variation was exclusively due to single nucleotide variants and small deletions, and showed high variability between replicates, indicating their random emergence. Interspecific competition exerted an apparent strong positive selection on a subset of P. inhibens 2.10 genes (e.g., luxR, cobC, argH, and sinR) that could facilitate competition, while the P. tunicata D2 population was genetically constrained under competition conditions. In the absence of interspecific competition, the P. tunicata D2 replicate populations displayed high levels of mutations affecting the same genes involved in cell motility and biofilm formation. Our results show that interspecific biofilm competition has a complex impact on genomic diversification, which likely depends on the nature of the competing strains and their ability to generate genetic variants due to their genomic constraints.
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Affiliation(s)
- Weizhi Song
- Centre for Marine Science and Innovation, School of Biological, Earth and Environmental Sciences, Faculty of Science, The University of New South Wales, Kensington, New South Wales, Australia
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Kensington, New South Wales, Australia
| | - Shan Zhang
- Centre for Marine Science and Innovation, School of Biological, Earth and Environmental Sciences, Faculty of Science, The University of New South Wales, Kensington, New South Wales, Australia
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Kensington, New South Wales, Australia
| | - Marwan E Majzoub
- Centre for Marine Science and Innovation, School of Biological, Earth and Environmental Sciences, Faculty of Science, The University of New South Wales, Kensington, New South Wales, Australia
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Kensington, New South Wales, Australia
| | - Suhelen Egan
- Centre for Marine Science and Innovation, School of Biological, Earth and Environmental Sciences, Faculty of Science, The University of New South Wales, Kensington, New South Wales, Australia
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Kensington, New South Wales, Australia
| | - Staffan Kjelleberg
- Centre for Marine Science and Innovation, School of Biological, Earth and Environmental Sciences, Faculty of Science, The University of New South Wales, Kensington, New South Wales, Australia
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Kensington, New South Wales, Australia
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Torsten Thomas
- Centre for Marine Science and Innovation, School of Biological, Earth and Environmental Sciences, Faculty of Science, The University of New South Wales, Kensington, New South Wales, Australia
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Kensington, New South Wales, Australia
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37
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Eble H, Joswig M, Lamberti L, Ludington WB. Master regulators of biological systems in higher dimensions. Proc Natl Acad Sci U S A 2023; 120:e2300634120. [PMID: 38096409 PMCID: PMC10743376 DOI: 10.1073/pnas.2300634120] [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: 01/12/2023] [Accepted: 10/23/2023] [Indexed: 12/18/2023] Open
Abstract
A longstanding goal of biology is to identify the key genes and species that critically impact evolution, ecology, and health. Network analysis has revealed keystone species that regulate ecosystems and master regulators that regulate cellular genetic networks. Yet these studies have focused on pairwise biological interactions, which can be affected by the context of genetic background and other species present, generating higher-order interactions. The important regulators of higher-order interactions are unstudied. To address this, we applied a high-dimensional geometry approach that quantifies epistasis in a fitness landscape to ask how individual genes and species influence the interactions in the rest of the biological network. We then generated and also reanalyzed 5-dimensional datasets (two genetic, two microbiome). We identified key genes (e.g., the rbs locus and pykF) and species (e.g., Lactobacilli) that control the interactions of many other genes and species. These higher-order master regulators can induce or suppress evolutionary and ecological diversification by controlling the topography of the fitness landscape. Thus, we provide a method and mathematical justification for exploration of biological networks in higher dimensions.
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Affiliation(s)
- Holger Eble
- Chair of Discrete Mathematics/Geometry, Technical University Berlin, Berlin10623, Germany
| | - Michael Joswig
- Chair of Discrete Mathematics/Geometry, Technical University Berlin, Berlin10623, Germany
- Max Planck Institute for Mathematics in the Sciences, Leipzig04103, Germany
| | - Lisa Lamberti
- Department of Biosystems Science and Engineering, Federal Institute of Technology (ETH Zürich), Basel4058, Switzerland
- Swiss Institute of Bioinformatics, Basel4058, Switzerland
| | - William B. Ludington
- Department of Biosphere Sciences and Engineering, Carnegie Institution for Science, Baltimore, MD21218
- Department of Biology, Johns Hopkins University, Baltimore, MD21218
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38
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Song S, Zhang J. Effective fitness under fluctuating selection with genetic drift. G3 (BETHESDA, MD.) 2023; 13:jkad230. [PMID: 37816122 PMCID: PMC10700052 DOI: 10.1093/g3journal/jkad230] [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: 07/11/2023] [Revised: 07/29/2023] [Accepted: 09/28/2023] [Indexed: 10/12/2023]
Abstract
The natural environment fluctuates for virtually every population of organisms. As a result, the fitness of a mutant may vary temporally. While commonly used for summarizing the effect of fluctuating selection on the mutant, geometric mean fitness can be misleading under some circumstances due to the influence of genetic drift. Here, we show by mathematical proof and computer simulation that, with genetic drift, the geometric mean fitness does not accurately reflect the overall effect of fluctuating selection. We propose an alternative measure based on the average expected allele frequency change caused by selection and demonstrate that this measure-effective fitness-better captures the overall effect of fluctuating selection in the presence of drift.
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Affiliation(s)
- Siliang Song
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA
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39
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Konstantinidis KT. Sequence-discrete species for prokaryotes and other microbes: A historical perspective and pending issues. MLIFE 2023; 2:341-349. [PMID: 38818268 PMCID: PMC10989153 DOI: 10.1002/mlf2.12088] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 09/04/2023] [Accepted: 10/08/2023] [Indexed: 06/01/2024]
Abstract
Whether prokaryotes, and other microorganisms, form distinct clusters that can be recognized as species remains an issue of paramount theoretical as well as practical consequence in identifying, regulating, and communicating about these organisms. In the past decade, comparisons of thousands of genomes of isolates and hundreds of metagenomes have shown that prokaryotic diversity may be predominantly organized in such sequence-discrete clusters, albeit organisms of intermediate relatedness between the identified clusters are also frequently found. Accumulating evidence suggests, however, that the latter "intermediate" organisms show enough ecological and/or functional distinctiveness to be considered different species. Notably, the area of discontinuity between clusters often-but not always-appears to be around 85%-95% genome-average nucleotide identity, consistently among different taxa. More recent studies have revealed remarkably similar diversity patterns for viruses and microbial eukaryotes as well. This high consistency across taxa implies a specific mechanistic process that underlies the maintenance of the clusters. The underlying mechanism may be a substantial reduction in the efficiency of homologous recombination, which mediates (successful) horizontal gene transfer, around 95% nucleotide identity. Deviations from the 95% threshold (e.g., species showing lower intraspecies diversity) may be caused by ecological differentiation that imposes barriers to otherwise frequent gene transfer. While this hypothesis that clusters are driven by ecological differentiation coupled to recombination frequency (i.e., higher recombination within vs. between groups) is appealing, the supporting evidence remains anecdotal. The data needed to rigorously test the hypothesis toward advancing the species concept are also outlined.
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Affiliation(s)
- Konstantinos T. Konstantinidis
- School of Civil and Environmental Engineering, and School of Biological SciencesGeorgia Institute of TechnologyAtlantaGeorgiaUSA
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40
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Ferguson AA, Inclan-Rico JM, Lu D, Bobardt SD, Hung L, Gouil Q, Baker L, Ritchie ME, Jex AR, Schwarz EM, Rossi HL, Nair MG, Dillman AR, Herbert DR. Hookworms dynamically respond to loss of Type 2 immune pressure. PLoS Pathog 2023; 19:e1011797. [PMID: 38079450 PMCID: PMC10735188 DOI: 10.1371/journal.ppat.1011797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 12/21/2023] [Accepted: 11/02/2023] [Indexed: 12/23/2023] Open
Abstract
The impact of the host immune environment on parasite transcription and fitness is currently unknown. It is widely held that hookworm infections have an immunomodulatory impact on the host, but whether the converse is true remains unclear. Immunity against adult-stage hookworms is largely mediated by Type 2 immune responses driven by the transcription factor Signal Transducer and Activator of Transcription 6 (STAT6). This study investigated whether serial passage of the rodent hookworm Nippostrongylus brasiliensis in STAT6-deficient mice (STAT6 KO) caused changes in parasites over time. After adaptation to STAT6 KO hosts, N. brasiliensis increased their reproductive output, feeding capacity, energy content, and body size. Using an improved N. brasiliensis genome, we found that these physiological changes corresponded with a dramatic shift in the transcriptional landscape, including increased expression of gene pathways associated with egg production, but a decrease in genes encoding neuropeptides, proteases, SCP/TAPS proteins, and transthyretin-like proteins; the latter three categories have been repeatedly observed in hookworm excreted/secreted proteins (ESPs) implicated in immunosuppression. Although transcriptional changes started to appear in the first generation of passage in STAT6 KO hosts for both immature and mature adult stages, downregulation of the genes putatively involved in immunosuppression was only observed after multiple generations in this immunodeficient environment. When STAT6 KO-adapted N. brasiliensis were reintroduced to a naive WT host after up to 26 generations, this progressive change in host-adaptation corresponded to increased production of inflammatory cytokines by the WT host. Surprisingly, however, this single exposure of STAT6 KO-adapted N. brasiliensis to WT hosts resulted in worms that were morphologically and transcriptionally indistinguishable from WT-adapted parasites. This work uncovers remarkable plasticity in the ability of hookworms to adapt to their hosts, which may present a general feature of parasitic nematodes.
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Affiliation(s)
- Annabel A. Ferguson
- University of Pennsylvania, School of Veterinary Medicine, Pathobiology Department, Philadelphia, Pennsylvania, United States of America
| | - Juan M. Inclan-Rico
- University of Pennsylvania, School of Veterinary Medicine, Pathobiology Department, Philadelphia, Pennsylvania, United States of America
| | - Dihong Lu
- University of California Riverside, Department of Nematology, Riverside, California, United States of America
| | - Sarah D. Bobardt
- University of California Riverside, School of Medicine, Department of Biomedical Sciences, Riverside, California, United States of America
| | - LiYin Hung
- University of Pennsylvania, School of Veterinary Medicine, Pathobiology Department, Philadelphia, Pennsylvania, United States of America
| | - Quentin Gouil
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- University of Melbourne, Department of Medical Biology, Parkville, Victoria, Australia
| | - Louise Baker
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- University of Melbourne, Department of Veterinary Biosciences, Parkville, Victoria, Australia
| | - Matthew E. Ritchie
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- University of Melbourne, Department of Medical Biology, Parkville, Victoria, Australia
| | - Aaron R. Jex
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- University of Melbourne, Department of Veterinary Biosciences, Parkville, Victoria, Australia
| | - Erich M. Schwarz
- University of Melbourne, Department of Veterinary Biosciences, Parkville, Victoria, Australia
- Cornell University, Department of Molecular Biology and Genetics, Ithaca, New York, United States of America
| | - Heather L. Rossi
- University of Pennsylvania, School of Veterinary Medicine, Pathobiology Department, Philadelphia, Pennsylvania, United States of America
| | - Meera G. Nair
- University of California Riverside, School of Medicine, Department of Biomedical Sciences, Riverside, California, United States of America
| | - Adler R. Dillman
- University of California Riverside, Department of Nematology, Riverside, California, United States of America
| | - De’Broski R. Herbert
- University of Pennsylvania, School of Veterinary Medicine, Pathobiology Department, Philadelphia, Pennsylvania, United States of America
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41
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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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42
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Uz-Zaman MH, D'Alton S, Barrick JE, Ochman H. Promoter capture drives the emergence of proto-genes in Escherichia coli. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.15.567300. [PMID: 38013999 PMCID: PMC10680751 DOI: 10.1101/2023.11.15.567300] [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
The phenomenon of de novo gene birth-the emergence of genes from non-genic sequences-has received considerable attention due to the widespread occurrence of genes that are unique to particular species or genomes. Most instances of de novo gene birth have been recognized through comparative analyses of genome sequences in eukaryotes, despite the abundance of novel, lineage-specific genes in bacteria and the relative ease with which bacteria can be studied in an experimental context. Here, we explore the genetic record of the Escherichia coli Long-Term Evolution Experiment (LTEE) for changes indicative of "proto-genic" phases of new gene birth in which non-genic sequences evolve stable transcription and/or translation. Over the time-span of the LTEE, non-genic regions are frequently transcribed, translated and differentially expressed, thereby serving as raw material for new gene emergence. Most proto-genes result either from insertion element activity or chromosomal translocations that fused pre-existing regulatory sequences to regions that were not expressed in the LTEE ancestor. Additionally, we identified instances of proto-gene emergence in which a previously unexpressed sequence was transcribed after formation of an upstream promoter. Tracing the origin of the causative mutations, we discovered that most occurred early in the history of the LTEE, often within the first 20,000 generations, and became fixed soon after emergence. Our findings show that proto-genes emerge frequently within evolving populations, persist stably, and can serve as potential substrates for new gene formation.
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43
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Good BH, Rosenfeld LB. Eco-evolutionary feedbacks in the human gut microbiome. Nat Commun 2023; 14:7146. [PMID: 37932275 PMCID: PMC10628149 DOI: 10.1038/s41467-023-42769-3] [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: 11/29/2022] [Accepted: 10/20/2023] [Indexed: 11/08/2023] Open
Abstract
Gut microbiota can evolve within their hosts on human-relevant timescales, but little is known about how these changes influence (or are influenced by) the composition of their local community. Here, by combining ecological and evolutionary analyses of a large cohort of human gut metagenomes, we show that the short-term evolution of the microbiota is linked with shifts in its ecological structure. These correlations are not simply explained by expansions of the evolving species, and often involve additional fluctuations in distantly related taxa. We show that similar feedbacks naturally emerge in simple resource competition models, even in the absence of cross-feeding or predation. These results suggest that the structure and function of host microbiota may be shaped by their local evolutionary history, which could have important implications for personalized medicine and microbiome engineering.
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Affiliation(s)
- Benjamin H Good
- Department of Applied Physics, Stanford University, Stanford, CA, 94305, USA.
- Department of Biology, Stanford University, Stanford, CA, 94305, USA.
- Chan Zuckerberg Biohub-San Francisco, San Francisco, CA, 94158, USA.
| | - Layton B Rosenfeld
- Department of Computer Science, Stanford University, Stanford, CA, 94305, USA
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44
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Abbara A, Bitbol AF. Frequent asymmetric migrations suppress natural selection in spatially structured populations. PNAS NEXUS 2023; 2:pgad392. [PMID: 38024415 PMCID: PMC10667037 DOI: 10.1093/pnasnexus/pgad392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 11/06/2023] [Indexed: 12/01/2023]
Abstract
Natural microbial populations often have complex spatial structures. This can impact their evolution, in particular the ability of mutants to take over. While mutant fixation probabilities are known to be unaffected by sufficiently symmetric structures, evolutionary graph theory has shown that some graphs can amplify or suppress natural selection, in a way that depends on microscopic update rules. We propose a model of spatially structured populations on graphs directly inspired by batch culture experiments, alternating within-deme growth on nodes and migration-dilution steps, and yielding successive bottlenecks. This setting bridges models from evolutionary graph theory with Wright-Fisher models. Using a branching process approach, we show that spatial structure with frequent migrations can only yield suppression of natural selection. More precisely, in this regime, circulation graphs, where the total incoming migration flow equals the total outgoing one in each deme, do not impact fixation probability, while all other graphs strictly suppress selection. Suppression becomes stronger as the asymmetry between incoming and outgoing migrations grows. Amplification of natural selection can nevertheless exist in a restricted regime of rare migrations and very small fitness advantages, where we recover the predictions of evolutionary graph theory for the star graph.
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Affiliation(s)
- Alia Abbara
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
- SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Anne-Florence Bitbol
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
- SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
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45
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Pentz JT, MacGillivray K, DuBose JG, Conlin PL, Reinhardt E, Libby E, Ratcliff WC. Evolutionary consequences of nascent multicellular life cycles. eLife 2023; 12:e84336. [PMID: 37889142 PMCID: PMC10611430 DOI: 10.7554/elife.84336] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 10/08/2023] [Indexed: 10/28/2023] Open
Abstract
A key step in the evolutionary transition to multicellularity is the origin of multicellular groups as biological individuals capable of adaptation. Comparative work, supported by theory, suggests clonal development should facilitate this transition, although this hypothesis has never been tested in a single model system. We evolved 20 replicate populations of otherwise isogenic clonally reproducing 'snowflake' yeast (Δace2/∆ace2) and aggregative 'floc' yeast (GAL1p::FLO1 /GAL1p::FLO1) with daily selection for rapid growth in liquid media, which favors faster cell division, followed by selection for rapid sedimentation, which favors larger multicellular groups. While both genotypes adapted to this regime, growing faster and having higher survival during the group-selection phase, there was a stark difference in evolutionary dynamics. Aggregative floc yeast obtained nearly all their increased fitness from faster growth, not improved group survival; indicating that selection acted primarily at the level of cells. In contrast, clonal snowflake yeast mainly benefited from higher group-dependent fitness, indicating a shift in the level of Darwinian individuality from cells to groups. Through genome sequencing and mathematical modeling, we show that the genetic bottlenecks in a clonal life cycle also drive much higher rates of genetic drift-a result with complex implications for this evolutionary transition. Our results highlight the central role that early multicellular life cycles play in the process of multicellular adaptation.
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Affiliation(s)
| | - Kathryn MacGillivray
- School of Biological Sciences, Georgia Institute of TechnologyAtlantaUnited States
- Interdisciplinary Graduate Program in Quantitative Biosciences, Georgia Institute of TechnologyAtlantaUnited States
| | - James G DuBose
- School of Biological Sciences, Georgia Institute of TechnologyAtlantaUnited States
| | - Peter L Conlin
- School of Biological Sciences, Georgia Institute of TechnologyAtlantaUnited States
| | - Emma Reinhardt
- Department of Biology, University of North Carolina at Chapel HillChapel HillUnited States
| | | | - William C Ratcliff
- School of Biological Sciences, Georgia Institute of TechnologyAtlantaUnited States
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46
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Hu G, Wang Y, Liu X, Strube ML, Wang B, Kovács ÁT. Species and condition shape the mutational spectrum in experimentally evolved biofilms. mSystems 2023; 8:e0054823. [PMID: 37768063 PMCID: PMC10654089 DOI: 10.1128/msystems.00548-23] [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: 05/27/2023] [Accepted: 08/11/2023] [Indexed: 09/29/2023] Open
Abstract
IMPORTANCE Biofilm formation is a vital factor for the survival and adaptation of bacteria in diverse environmental niches. Experimental evolution combined with the advancement of whole-population genome sequencing provides us a powerful tool to understand the genomic dynamic of evolutionary adaptation to different environments, such as during biofilm development. Previous studies described the genetic and phenotypic changes of selected clones from experimentally evolved Bacillus thuringiensis and Bacillus subtilis that were adapted under abiotic and biotic biofilm conditions. However, the full understanding of the dynamic evolutionary landscapes was lacking. Furthermore, the differences and similarities of adaptive mechanisms in B. thuringiensis and B. subtilis were not identified. To overcome these limitations, we performed longitudinal whole-population genome sequencing to study the underlying genetic dynamics at high resolution. Our study provides the first comprehensive mutational landscape of two bacterial species' biofilms that is adapted to an abiotic and biotic surface.
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Affiliation(s)
- Guohai Hu
- China National GeneBank, BGI, Shenzhen, China
- BGI Research, Shenzhen, China
- Bacterial Interactions and Evolution Group, DTU Bioengineering, Technical University of Denmark, Lyngby, Denmark
| | - Yue Wang
- China National GeneBank, BGI, Shenzhen, China
- BGI Research, Shenzhen, China
- BGI Research, Beijing, China
| | - Xin Liu
- China National GeneBank, BGI, Shenzhen, China
- BGI Research, Shenzhen, China
- BGI Research, Beijing, China
| | - Mikael Lenz Strube
- Bacterial Ecophysiology and Biotechnology Group, DTU Bioengineering, Technical University of Denmark, Lyngby, Denmark
| | - Bo Wang
- China National GeneBank, BGI, Shenzhen, China
- BGI Research, Shenzhen, China
- Shenzhen Key Laboratory of Environmental Microbial Genomics and Application, BGI Research, Shenzhen, China
| | - Ákos T. Kovács
- Bacterial Interactions and Evolution Group, DTU Bioengineering, Technical University of Denmark, Lyngby, Denmark
- Institute of Biology, Leiden University, Leiden, The Netherlands
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47
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Chen V, Johnson MS, Hérissant L, Humphrey PT, Yuan DC, Li Y, Agarwala A, Hoelscher SB, Petrov DA, Desai MM, Sherlock G. Evolution of haploid and diploid populations reveals common, strong, and variable pleiotropic effects in non-home environments. eLife 2023; 12:e92899. [PMID: 37861305 PMCID: PMC10629826 DOI: 10.7554/elife.92899] [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: 09/21/2023] [Accepted: 09/27/2023] [Indexed: 10/21/2023] Open
Abstract
Adaptation is driven by the selection for beneficial mutations that provide a fitness advantage in the specific environment in which a population is evolving. However, environments are rarely constant or predictable. When an organism well adapted to one environment finds itself in another, pleiotropic effects of mutations that made it well adapted to its former environment will affect its success. To better understand such pleiotropic effects, we evolved both haploid and diploid barcoded budding yeast populations in multiple environments, isolated adaptive clones, and then determined the fitness effects of adaptive mutations in 'non-home' environments in which they were not selected. We find that pleiotropy is common, with most adaptive evolved lineages showing fitness effects in non-home environments. Consistent with other studies, we find that these pleiotropic effects are unpredictable: they are beneficial in some environments and deleterious in others. However, we do find that lineages with adaptive mutations in the same genes tend to show similar pleiotropic effects. We also find that ploidy influences the observed adaptive mutational spectra in a condition-specific fashion. In some conditions, haploids and diploids are selected with adaptive mutations in identical genes, while in others they accumulate mutations in almost completely disjoint sets of genes.
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Affiliation(s)
- Vivian Chen
- Department of Biology, Stanford UniversityStanfordUnited States
| | - Milo S Johnson
- Department of Organismic and Evolutionary Biology, Harvard UniversityCambridgeUnited States
- Quantitative Biology Initiative, Harvard UniversityCambridgeUnited States
- NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard UniversityBostonUnited States
| | - Lucas Hérissant
- Department of Genetics, Stanford UniversityStanfordUnited States
| | - Parris T Humphrey
- Department of Organismic and Evolutionary Biology, Harvard UniversityCambridgeUnited States
| | - David C Yuan
- Department of Biology, Stanford UniversityStanfordUnited States
| | - Yuping Li
- Department of Biology, Stanford UniversityStanfordUnited States
| | - Atish Agarwala
- Department of Physics, Stanford UniversityStanfordUnited States
| | | | - Dmitri A Petrov
- Department of Biology, Stanford UniversityStanfordUnited States
| | - Michael M Desai
- Department of Organismic and Evolutionary Biology, Harvard UniversityCambridgeUnited States
- Quantitative Biology Initiative, Harvard UniversityCambridgeUnited States
- NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard UniversityBostonUnited States
- Department of Physics, Harvard UniversityCambridgeUnited States
| | - Gavin Sherlock
- Department of Genetics, Stanford UniversityStanfordUnited States
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48
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Razo-Mejia M, Mani M, Petrov D. Bayesian inference of relative fitness on high-throughput pooled competition assays. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.14.562365. [PMID: 37904971 PMCID: PMC10614806 DOI: 10.1101/2023.10.14.562365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/01/2023]
Abstract
The tracking of lineage frequencies via DNA barcode sequencing enables the quantification of microbial fitness. However, experimental noise coming from biotic and abiotic sources complicates the computation of a reliable inference. We present a Bayesian pipeline to infer relative microbial fitness from high-throughput lineage tracking assays. Our model accounts for multiple sources of noise and propagates uncertainties throughout all parameters in a systematic way. Furthermore, using modern variational inference methods based on automatic differentiation, we are able to scale the inference to a large number of unique barcodes. We extend this core model to analyze multi-environment assays, replicate experiments, and barcodes linked to genotypes. On simulations, our method recovers known parameters within posterior credible intervals. This work provides a generalizable Bayesian framework to analyze lineage tracking experiments. The accompanying open-source software library enables the adoption of principled statistical methods in experimental evolution.
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Affiliation(s)
| | - Madhav Mani
- NSF-Simons Center for Quantitative Biology, Northwestern University
- Department of Molecular Biosciences, Northwestern University
| | - Dmitri Petrov
- Department of Biology, Stanford University
- Stanford Cancer Institute, Stanford University School of Medicine
- Chan Zuckerberg Biohub
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Jiang S, Zhang C, Han Z, Ma W, Wang S, Huo D, Cui W, Zhai Q, Huang S, Zhang J. Native microbiome dominates over host factors in shaping the probiotic genetic evolution in the gut. NPJ Biofilms Microbiomes 2023; 9:80. [PMID: 37838684 PMCID: PMC10576824 DOI: 10.1038/s41522-023-00447-8] [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: 05/03/2023] [Accepted: 10/02/2023] [Indexed: 10/16/2023] Open
Abstract
Probiotics often acquire potentially adaptive mutations in vivo, gaining new functional traits through gut selection. While both the host and microbiome can contribute to probiotics' genetic evolution, separating the microbiome and the host's contribution to such selective pressures remains challenging. Here, we introduced germ-free (GF) and specific pathogen-free (SPF) mouse models to track how probiotic strains, i.e., Lactiplantibacillus plantarum HNU082 (Lp082) and Bifidobacterium animalis subsp. lactis V9 (BV9), genetically evolved under selection pressures derived from host factors alone and both host and microbial ecological factors. Notably, compared to the genome of a probiotic strain before consumption, the host only elicited <15 probiotic mutations in probiotic genomes that emerged in the luminal environment of GF mice, while a total of 840 mutations in Lp082 mutants and 21,579 mutations in BV9 were found in SPF mice, <0.25% of those derived from both factors that were never captured by other experimental evolution studies, indicating that keen microbial competitions exhibited the predominant evolutionary force in shaping probiotic genetic composition (>99.75%). For a given probiotic, functional genes occurring in potentially adaptive mutations induced by hosts (GF mice) were all shared with those found in mutants of SPF mice. Collectively, the native microbiome consistently drove a more rapid and divergent genetic evolution of probiotic strains in seven days of colonization than host factors did. Our study further laid a theoretical foundation for genetically engineering probiotics for better gut adaptation through in vitro artificial gut ecosystems without the selection pressures derived from host factors.
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Affiliation(s)
- Shuaiming Jiang
- Key Laboratory of Food Nutrition and Functional Food of Hainan Province, School of Food Science and Engineering, Hainan University, Haikou, 570228, China
| | - Chengcheng Zhang
- School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, China
| | - Zhe Han
- Key Laboratory of Food Nutrition and Functional Food of Hainan Province, School of Food Science and Engineering, Hainan University, Haikou, 570228, China
| | - Wenyao Ma
- Key Laboratory of Food Nutrition and Functional Food of Hainan Province, School of Food Science and Engineering, Hainan University, Haikou, 570228, China
| | - Shunhe Wang
- School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, China
| | - Dongxue Huo
- Key Laboratory of Food Nutrition and Functional Food of Hainan Province, School of Food Science and Engineering, Hainan University, Haikou, 570228, China
| | - Weipeng Cui
- Key Laboratory of Food Nutrition and Functional Food of Hainan Province, School of Food Science and Engineering, Hainan University, Haikou, 570228, China
| | - Qixiao Zhai
- School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, China.
| | - Shi Huang
- Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
| | - Jiachao Zhang
- Key Laboratory of Food Nutrition and Functional Food of Hainan Province, School of Food Science and Engineering, Hainan University, Haikou, 570228, China.
- One Health Institute, Hainan University, Haikou, Hainan, 570228, China.
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Lin YP, Lu CY, Lee CR. The Past Contribution and Future Fate of Genetic Variants under Climate Change in an Island Population of Musa itinerans. Am Nat 2023; 202:558-570. [PMID: 37792919 DOI: 10.1086/726015] [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: 10/06/2023]
Abstract
AbstractGenetic variation within species is crucial for sessile species to adapt to novel environments when facing dramatic climate changes. However, the debate continues whether standing ancestral variation adaptive to current environmental variability is sufficient to guarantee future suitability. Using wild banana Musa itinerans, we investigated the relative contribution of standing ancestral variation versus new mutations to environmental adaptation and inferred their future fate. On the continental island of Taiwan, local populations immigrated from the Southeast Asian continent during the ice age and have been isolated since then. This allows the classification of genetic variants into standing ancestral variation (polymorphic in Taiwan and the continent) and new mutations (polymorphic only in Taiwan). For temperature-related variables where Taiwan is mainly within the ancestral climatic range, standing ancestral variation had a slightly stronger association than new mutations. New mutations were more important for precipitation-related variables, where northeastern Taiwan had much more winter rainfall than most of continental Southeast Asia. Upon future climate change, new mutations showed higher genetic offset in regions of abrupt transition between allele frequency and local environments, suggesting their greater spatial heterogeneity of future vulnerability.
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