1
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Torrillo PA, Lieberman TD. Reversions mask the contribution of adaptive evolution in microbiomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.14.557751. [PMID: 37745437 PMCID: PMC10515931 DOI: 10.1101/2023.09.14.557751] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
When examining bacterial genomes for evidence of past selection, the results obtained depend heavily on the mutational distance between chosen genomes. Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed byd N / d S , the normalized ratio of nonsynonymous to synonymous mutations. Here, we show that the classical interpretation of this scale-dependence, weak purifying selection, leads to problematic mutation accumulation when applied to available gut microbiome data. We propose an alternative, adaptive reversion model with exactly opposite implications for dynamical intuition and applications ofd N / d S . Reversions that occur and sweep within-host populations are nearly guaranteed in microbiomes due to large population sizes, short generation times, and variable environments. Using analytical and simulation approaches, we show that adaptive reversion can explain thed N / d S decay given only dozens of locally-fluctuating selective pressures, which is realistic in the context of Bacteroides genomes. The success of the adaptive reversion model argues for interpreting low values ofd N / d S obtained from long-time scales with caution, as they may emerge even when adaptive sweeps are frequent. Our work thus inverts the interpretation of an old observation in bacterial evolution, illustrates the potential of mutational reversions to shape genomic landscapes over time, and highlights the importance of studying bacterial genomic evolution on short time scales.
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Affiliation(s)
- Paul A. Torrillo
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Tami D. Lieberman
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
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2
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McEnany J, Good BH. Predicting the First Steps of Evolution in Randomly Assembled Communities. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.15.571925. [PMID: 38168431 PMCID: PMC10760118 DOI: 10.1101/2023.12.15.571925] [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: 01/05/2024]
Abstract
Microbial communities can self-assemble into highly diverse states with predictable statistical properties. However, these initial states can be disrupted by rapid evolution of the resident strains. When a new mutation arises, it competes for resources with its parent strain and with the other species in the community. This interplay between ecology and evolution is difficult to capture with existing community assembly theory. Here, we introduce a mathematical framework for predicting the first steps of evolution in large randomly assembled communities that compete for substitutable resources. We show how the fitness effects of new mutations and the probability that they coexist with their parent depends on the size of the community, the saturation of its niches, and the metabolic overlap between its members. We find that successful mutations are often able to coexist with their parent strains, even in saturated communities with low niche availability. At the same time, these invading mutants often cause extinctions of metabolically distant species. Our results suggest that even small amounts of evolution can produce distinct genetic signatures in natural microbial communities.
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Affiliation(s)
- John McEnany
- Biophysics Program, Stanford University, Stanford, CA 94305, USA
| | - 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
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3
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Freire TFA, Hu Z, Wood KB, Gjini E. Modeling spatial evolution of multi-drug resistance under drug environmental gradients. PLoS Comput Biol 2024; 20:e1012098. [PMID: 38820350 PMCID: PMC11142541 DOI: 10.1371/journal.pcbi.1012098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 04/23/2024] [Indexed: 06/02/2024] Open
Abstract
Multi-drug combinations to treat bacterial populations are at the forefront of approaches for infection control and prevention of antibiotic resistance. Although the evolution of antibiotic resistance has been theoretically studied with mathematical population dynamics models, extensions to spatial dynamics remain rare in the literature, including in particular spatial evolution of multi-drug resistance. In this study, we propose a reaction-diffusion system that describes the multi-drug evolution of bacteria based on a drug-concentration rescaling approach. We show how the resistance to drugs in space, and the consequent adaptation of growth rate, is governed by a Price equation with diffusion, integrating features of drug interactions and collateral resistances or sensitivities to the drugs. We study spatial versions of the model where the distribution of drugs is homogeneous across space, and where the drugs vary environmentally in a piecewise-constant, linear and nonlinear manner. Although in many evolution models, per capita growth rate is a natural surrogate for fitness, in spatially-extended, potentially heterogeneous habitats, fitness is an emergent property that potentially reflects additional complexities, from boundary conditions to the specific spatial variation of growth rates. Applying concepts from perturbation theory and reaction-diffusion equations, we propose an analytical metric for characterization of average mutant fitness in the spatial system based on the principal eigenvalue of our linear problem, λ1. This enables an accurate translation from drug spatial gradients and mutant antibiotic susceptibility traits to the relative advantage of each mutant across the environment. Our approach allows one to predict the precise outcomes of selection among mutants over space, ultimately from comparing their λ1 values, which encode a critical interplay between growth functions, movement traits, habitat size and boundary conditions. Such mathematical understanding opens new avenues for multi-drug therapeutic optimization.
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Affiliation(s)
- Tomas Ferreira Amaro Freire
- Center for Computational and Stochastic Mathematics, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal
| | - Zhijian Hu
- Departments of Biophysics and Physics, University of Michigan, United States of America
| | - Kevin B. Wood
- Departments of Biophysics and Physics, University of Michigan, United States of America
| | - Erida Gjini
- Center for Computational and Stochastic Mathematics, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal
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4
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Wong DPGH, Good BH. Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking. Nat Commun 2024; 15:1605. [PMID: 38383538 PMCID: PMC10881964 DOI: 10.1038/s41467-024-45792-0] [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: 09/21/2022] [Accepted: 02/05/2024] [Indexed: 02/23/2024] Open
Abstract
Gut microbiota can adapt to their host environment by rapidly acquiring new mutations. However, the dynamics of this process are difficult to characterize in dominant gut species in their complex in vivo environment. Here we show that the fine-scale dynamics of genome-wide transposon libraries can enable quantitative inferences of these in vivo evolutionary forces. By analyzing >400,000 lineages across four human Bacteroides strains in gnotobiotic mice, we observed positive selection on thousands of cryptic variants - most of which were unrelated to their original gene knockouts. The spectrum of fitness benefits varied between species, and displayed diverse tradeoffs over time and in different dietary conditions, enabling inferences of their underlying function. These results suggest that within-host adaptations arise from an intense competition between numerous contending variants, which can strongly influence their emergent evolutionary tradeoffs.
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Affiliation(s)
- Daniel P G H Wong
- Department of Applied Physics, Stanford University, Stanford, CA, 94305, USA
| | - 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.
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5
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Liu Z, Good BH. Dynamics of bacterial recombination in the human gut microbiome. PLoS Biol 2024; 22:e3002472. [PMID: 38329938 PMCID: PMC10852326 DOI: 10.1371/journal.pbio.3002472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 12/14/2023] [Indexed: 02/10/2024] Open
Abstract
Horizontal gene transfer (HGT) is a ubiquitous force in microbial evolution. Previous work has shown that the human gut is a hotspot for gene transfer between species, but the more subtle exchange of variation within species-also known as recombination-remains poorly characterized in this ecosystem. Here, we show that the genetic structure of the human gut microbiome provides an opportunity to measure recent recombination events from sequenced fecal samples, enabling quantitative comparisons across diverse commensal species that inhabit a common environment. By analyzing recent recombination events in the core genomes of 29 human gut bacteria, we observed widespread heterogeneities in the rates and lengths of transferred fragments, which are difficult to explain by existing models of ecological isolation or homology-dependent recombination rates. We also show that natural selection helps facilitate the spread of genetic variants across strain backgrounds, both within individual hosts and across the broader population. These results shed light on the dynamics of in situ recombination, which can strongly constrain the adaptability of gut microbial communities.
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Affiliation(s)
- Zhiru Liu
- Department of Applied Physics, Stanford University, Stanford, California, United States of America
| | - Benjamin H. Good
- Department of Applied Physics, Stanford University, Stanford, California, United States of America
- Department of Biology, Stanford University, Stanford, California, United States of America
- Chan Zuckerberg Biohub–San Francisco, San Francisco, California, United States of America
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6
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Scheidweiler D, Bordoloi AD, Jiao W, Sentchilo V, Bollani M, Chhun A, Engel P, de Anna P. Spatial structure, chemotaxis and quorum sensing shape bacterial biomass accumulation in complex porous media. Nat Commun 2024; 15:191. [PMID: 38167276 PMCID: PMC10761857 DOI: 10.1038/s41467-023-44267-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: 03/28/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024] Open
Abstract
Biological tissues, sediments, or engineered systems are spatially structured media with a tortuous and porous structure that host the flow of fluids. Such complex environments can influence the spatial and temporal colonization patterns of bacteria by controlling the transport of individual bacterial cells, the availability of resources, and the distribution of chemical signals for communication. Yet, due to the multi-scale structure of these complex systems, it is hard to assess how different biotic and abiotic properties work together to control the accumulation of bacterial biomass. Here, we explore how flow-mediated interactions allow the gut commensal Escherichia coli to colonize a porous structure that is composed of heterogenous dead-end pores (DEPs) and connecting percolating channels, i.e. transmitting pores (TPs), mimicking the structured surface of mammalian guts. We find that in presence of flow, gradients of the quorum sensing (QS) signaling molecule autoinducer-2 (AI-2) promote E. coli chemotactic accumulation in the DEPs. In this crowded environment, the combination of growth and cell-to-cell collision favors the development of suspended bacterial aggregates. This results in hot-spots of resource consumption, which, upon resource limitation, triggers the mechanical evasion of biomass from nutrients and oxygen depleted DEPs. Our findings demonstrate that microscale medium structure and complex flow coupled with bacterial quorum sensing and chemotaxis control the heterogenous accumulation of bacterial biomass in a spatially structured environment, such as villi and crypts in the gut or in tortuous pores within soil and filters.
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Affiliation(s)
- David Scheidweiler
- Institute of Earth Sciences, University of Lausanne, CH-1015, Lausanne, Switzerland.
| | - Ankur Deep Bordoloi
- Institute of Earth Sciences, University of Lausanne, CH-1015, Lausanne, Switzerland
| | - Wenqiao Jiao
- Institute of Earth Sciences, University of Lausanne, CH-1015, Lausanne, Switzerland
| | - Vladimir Sentchilo
- Department of Fundamental Microbiology, University of Lausanne, CH-1015, Lausanne, Switzerland
| | | | - Audam Chhun
- Department of Fundamental Microbiology, University of Lausanne, CH-1015, Lausanne, Switzerland
| | - Philipp Engel
- Department of Fundamental Microbiology, University of Lausanne, CH-1015, Lausanne, Switzerland
| | - Pietro de Anna
- Institute of Earth Sciences, University of Lausanne, CH-1015, Lausanne, Switzerland.
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7
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Etheridge AM, Letter I, Kurtz TG, Ralph PL, Ho Lung TT. Looking forwards and backwards: dynamics and genealogies of locally regulated populations. ARXIV 2023:arXiv:2305.14488v2. [PMID: 37292478 PMCID: PMC10246084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
We introduce a broad class of mechanistic spatial models to describe how spatially heterogeneous populations live, die, and reproduce. Individuals are represented by points of a point measure, whose birth and death rates can depend both on spatial position and local population density, defined at a location to be the convolution of the point measure with a suitable non-negative integrable kernel centred on that location. We pass to three different scaling limits: an interacting superprocess, a nonlocal partial differential equation (PDE), and a classical PDE. The classical PDE is obtained both by a two-step convergence argument, in which we first scale time and population size and pass to the nonlocal PDE, and then scale the kernel that determines local population density; and in the important special case in which the limit is a reaction-diffusion equation, directly by simultaneously scaling the kernel width, timescale and population size in our individual based model. A novelty of our model is that we explicitly model a juvenile phase. The number of juveniles produced by an individual depends on local population density at the location of the parent; these juvenile offspring are thrown off in a (possibly heterogeneous, anisotropic) Gaussian distribution around the location of the parent; they then reach (instant) maturity with a probability that can depend on the local population density at the location at which they land. Although we only record mature individuals, a trace of this two-step description remains in our population models, resulting in novel limits in which the spatial dynamics are governed by a nonlinear diffusion. Using a lookdown representation, we are able to retain information about genealogies relating individuals in our population and, in the case of deterministic limiting models, we use this to deduce the backwards in time motion of the ancestral lineage of an individual sampled from the population. We observe that knowing the history of the population density is not enough to determine the motion of ancestral lineages in our model. We also investigate (and contrast) the behaviour of lineages for three different deterministic models of a population expanding its range as a travelling wave: the Fisher-KPP equation, the Allen-Cahn equation, and a porous medium equation with logistic growth.
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Affiliation(s)
- Alison M Etheridge
- Department of Statistics, Oxford University, 24-29 St Giles, Oxford OX1 3LB, UK
| | - Ian Letter
- Department of Statistics, Oxford University, 24-29 St Giles, Oxford OX1 3LB, UK
| | - Thomas G Kurtz
- Departments of Mathematics and Statistics, University of Wisconsin - Madison, 480 Lincoln Drive, Madison, WI 53706-1388, USA
| | - Peter L Ralph
- Departments of Mathematics and Biology, University of Oregon, Fenton Hall, Eugene, OR 97403-1222, USA
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8
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Freire T, Hu Z, Wood KB, Gjini E. Modeling spatial evolution of multi-drug resistance under drug environmental gradients. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.16.567447. [PMID: 38014279 PMCID: PMC10680811 DOI: 10.1101/2023.11.16.567447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Multi-drug combinations to treat bacterial populations are at the forefront of approaches for infection control and prevention of antibiotic resistance. Although the evolution of antibiotic resistance has been theoretically studied with mathematical population dynamics models, extensions to spatial dynamics remain rare in the literature, including in particular spatial evolution of multi-drug resistance. In this study, we propose a reaction-diffusion system that describes the multi-drug evolution of bacteria, based on a rescaling approach (Gjini and Wood, 2021). We show how the resistance to drugs in space, and the consequent adaptation of growth rate is governed by a Price equation with diffusion. The covariance terms in this equation integrate features of drug interactions and collateral resistances or sensitivities to the drugs. We study spatial versions of the model where the distribution of drugs is homogeneous across space, and where the drugs vary environmentally in a piecewise-constant, linear and nonlinear manner. Applying concepts from perturbation theory and reaction-diffusion equations, we propose an analytical characterization of average mutant fitness in the spatial system based on the principal eigenvalue of our linear problem. This enables an accurate translation from drug spatial gradients and mutant antibiotic susceptibility traits, to the relative advantage of each mutant across the environment. Such a mathematical understanding allows to predict the precise outcomes of selection over space, ultimately from the fundamental balance between growth and movement traits, and their diversity in a population.
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Affiliation(s)
- Tomas Freire
- Center for Computational and Stochastic Mathematics, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal
| | - Zhijian Hu
- Departments of Biophysics and Physics, University of Michigan, USA
| | - Kevin B. Wood
- Departments of Biophysics and Physics, University of Michigan, USA
| | - Erida Gjini
- Center for Computational and Stochastic Mathematics, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal
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9
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Mah JC, Lohmueller KE, Garud N. Inference of the demographic histories and selective effects of human gut commensal microbiota over the course of human history. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.09.566454. [PMID: 38014007 PMCID: PMC10680615 DOI: 10.1101/2023.11.09.566454] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Despite the importance of gut commensal microbiota to human health, there is little knowledge about their evolutionary histories, including their population demographic histories and their distributions of fitness effects (DFE) of new mutations. Here, we infer the demographic histories and DFEs of 27 of the most highly prevalent and abundant commensal gut microbial species in North Americans over timescales exceeding human generations using a collection of lineages inferred from a panel of healthy hosts. We find overall reductions in genetic variation among commensal gut microbes sampled from a Western population relative to an African rural population. Additionally, some species in North American microbiomes display contractions in population size and others expansions, potentially occurring at several key historical moments in human history. DFEs across species vary from highly to mildly deleterious, with accessory genes experiencing more drift compared to core genes. Within genera, DFEs tend to be more congruent, reflective of underlying phylogenetic relationships. Taken together, these findings suggest that human commensal gut microbes have distinct evolutionary histories, possibly reflecting the unique roles of individual members of the microbiome.
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10
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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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11
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Xue KS, Walton SJ, Goldman DA, Morrison ML, Verster AJ, Parrott AB, Yu FB, Neff NF, Rosenberg NA, Ross BD, Petrov DA, Huang KC, Good BH, Relman DA. Prolonged delays in human microbiota transmission after a controlled antibiotic perturbation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.26.559480. [PMID: 37808827 PMCID: PMC10557656 DOI: 10.1101/2023.09.26.559480] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Humans constantly encounter new microbes, but few become long-term residents of the adult gut microbiome. Classical theories predict that colonization is determined by the availability of open niches, but it remains unclear whether other ecological barriers limit commensal colonization in natural settings. To disentangle these effects, we used a controlled perturbation with the antibiotic ciprofloxacin to investigate the dynamics of gut microbiome transmission in 22 households of healthy, cohabiting adults. Colonization was rare in three-quarters of antibiotic-taking subjects, whose resident strains rapidly recovered in the week after antibiotics ended. In contrast, the remaining antibiotic-taking subjects exhibited lasting responses, with extensive species losses and transient expansions of potential opportunistic pathogens. These subjects experienced elevated rates of commensal colonization, but only after long delays: many new colonizers underwent sudden, correlated expansions months after the antibiotic perturbation. Furthermore, strains that had previously transmitted between cohabiting partners rarely recolonized after antibiotic disruptions, showing that colonization displays substantial historical contingency. This work demonstrates that there remain substantial ecological barriers to colonization even after major microbiome disruptions, suggesting that dispersal interactions and priority effects limit the pace of community change.
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Affiliation(s)
- Katherine S Xue
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Sophie Jean Walton
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Biophysics Training Program, Stanford, CA 94305, USA
| | - Doran A Goldman
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Maike L Morrison
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Adrian J Verster
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth College, Hanover, NH 03755, USA
| | | | | | - Norma F Neff
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Noah A Rosenberg
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Benjamin D Ross
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth College, Hanover, NH 03755, USA
| | - Dmitri A Petrov
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Kerwyn Casey Huang
- Department of Bioengineering, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Benjamin H Good
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
- Department of Applied Physics, Stanford, CA 94305, USA
| | - David A Relman
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Infectious Diseases Section, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA
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12
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Dapa T, Wong DP, Vasquez KS, Xavier KB, Huang KC, Good BH. Within-host evolution of the gut microbiome. Curr Opin Microbiol 2023; 71:102258. [PMID: 36608574 PMCID: PMC9993085 DOI: 10.1016/j.mib.2022.102258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 12/05/2022] [Accepted: 12/05/2022] [Indexed: 01/06/2023]
Abstract
Gut bacteria inhabit a complex environment that is shaped by interactions with their host and the other members of the community. While these ecological interactions have evolved over millions of years, mounting evidence suggests that gut commensals can evolve on much shorter timescales as well, by acquiring new mutations within individual hosts. In this review, we highlight recent progress in understanding the causes and consequences of short-term evolution in the mammalian gut, from experimental evolution in murine hosts to longitudinal tracking of human cohorts. We also discuss new opportunities for future progress by expanding the repertoire of focal species, hosts, and surrounding communities, and by combining deep-sequencing technologies with quantitative frameworks from population genetics.
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Affiliation(s)
- Tanja Dapa
- Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal
| | - Daniel Pgh Wong
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Kimberly S Vasquez
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | | | - Kerwyn Casey Huang
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA.
| | - Benjamin H Good
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA.
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13
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Zhang M, Zhang J, Wang C, Yan JK, Yi J, Ning J, Huo XK, Yu ZL, Zhang BJ, Sun CP, Ma XC. Biotransformation of 18β-Glycyrrhetinic Acid by Human Intestinal Fungus Aspergillus niger RG13B1 and the Potential Anti-Inflammatory Mechanism of Its Metabolites. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:15104-15115. [PMID: 36414003 DOI: 10.1021/acs.jafc.2c05455] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
18β-Glycyrrhetinic acid (GA) is a triterpenoid possessing an anti-inflammatory activity in vivo, while the low bioavailability limits its application due to its intestinal accumulation. In order to investigate the metabolism of GA in intestinal microbes, it was incubated with human intestinal fungus Aspergillus niger RG13B1, finally leading to the isolation and identification of three new metabolites (1-3) and three known metabolites (4-6) based on 1D and 2D NMR and high-resolution electrospray ionization mass spectroscopy spectra. Metabolite 6 could target myeloid differentiation protein 2 (MD2) to suppress the activation of nuclear factor-kappa B (NF-κB) signaling pathway via inhibiting the nuclear translocation of p65 to downregulate its target proteins and genes in lipopolysaccharide (LPS)-mediated RAW264.7 cells. Molecular dynamics suggested that metabolite 6 interacted with MD2 through the hydrogen bond of amino acid residue Arg90. These findings demonstrated that metabolite 6 could serve as a potential candidate to develop the new inhibitors of MD2.
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Affiliation(s)
- Min Zhang
- College of Pharmacy, Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Juan Zhang
- College of Pharmacy, Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
- School of Pharmaceutical Sciences, Health Science Center, Shenzhen University, Shenzhen 518060, China
| | - Chao Wang
- College of Pharmacy, Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Jian-Kun Yan
- School of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050091, China
| | - Jing Yi
- College of Pharmacy, Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Jing Ning
- College of Pharmacy, Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Xiao-Kui Huo
- College of Pharmacy, Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Zhen-Long Yu
- College of Pharmacy, Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Bao-Jing Zhang
- College of Pharmacy, Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Cheng-Peng Sun
- College of Pharmacy, Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Xiao-Chi Ma
- College of Pharmacy, Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
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