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Vermeersch L, Cool L, Gorkovskiy A, Voordeckers K, Wenseleers T, Verstrepen KJ. Do microbes have a memory? History-dependent behavior in the adaptation to variable environments. Front Microbiol 2022; 13:1004488. [PMID: 36299722 PMCID: PMC9589428 DOI: 10.3389/fmicb.2022.1004488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 09/26/2022] [Indexed: 11/18/2022] Open
Abstract
Microbes are constantly confronted with changes and challenges in their environment. A proper response to these environmental cues is needed for optimal cellular functioning and fitness. Interestingly, past exposure to environmental cues can accelerate or boost the response when this condition returns, even in daughter cells that have not directly encountered the initial cue. Moreover, this behavior is mostly epigenetic and often goes hand in hand with strong heterogeneity in the strength and speed of the response between isogenic cells of the same population, which might function as a bet-hedging strategy. In this review, we discuss examples of history-dependent behavior (HDB) or “memory,” with a specific focus on HDB in fluctuating environments. In most examples discussed, the lag time before the response to an environmental change is used as an experimentally measurable proxy for HDB. We highlight different mechanisms already implicated in HDB, and by using HDB in fluctuating carbon conditions as a case study, we showcase how the metabolic state of a cell can be a key determining factor for HDB. Finally, we consider possible evolutionary causes and consequences of such HDB.
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Affiliation(s)
- Lieselotte Vermeersch
- VIB – KU Leuven Center for Microbiology, Leuven, Belgium
- CMPG Laboratory of Genetics and Genomics, KU Leuven, Leuven, Belgium
| | - Lloyd Cool
- VIB – KU Leuven Center for Microbiology, Leuven, Belgium
- CMPG Laboratory of Genetics and Genomics, KU Leuven, Leuven, Belgium
- Laboratory of Socioecology and Social Evolution, Department of Biology, KU Leuven, Leuven, Belgium
| | - Anton Gorkovskiy
- VIB – KU Leuven Center for Microbiology, Leuven, Belgium
- CMPG Laboratory of Genetics and Genomics, KU Leuven, Leuven, Belgium
| | - Karin Voordeckers
- VIB – KU Leuven Center for Microbiology, Leuven, Belgium
- CMPG Laboratory of Genetics and Genomics, KU Leuven, Leuven, Belgium
| | - Tom Wenseleers
- Laboratory of Socioecology and Social Evolution, Department of Biology, KU Leuven, Leuven, Belgium
| | - Kevin J. Verstrepen
- VIB – KU Leuven Center for Microbiology, Leuven, Belgium
- CMPG Laboratory of Genetics and Genomics, KU Leuven, Leuven, Belgium
- *Correspondence: Kevin J. Verstrepen,
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Johnson CGM, Fletcher AG, Soyer OS. ChemChaste: Simulating spatially inhomogeneous biochemical reaction-diffusion systems for modeling cell-environment feedbacks. Gigascience 2022; 11:6610007. [PMID: 35715874 PMCID: PMC9205757 DOI: 10.1093/gigascience/giac051] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 03/31/2022] [Accepted: 05/30/2022] [Indexed: 01/21/2023] Open
Abstract
Background Spatial organization plays an important role in the function of many biological systems, from cell fate specification in animal development to multistep metabolic conversions in microbial communities. The study of such systems benefits from the use of spatially explicit computational models that combine a discrete description of cells with a continuum description of one or more chemicals diffusing within a surrounding bulk medium. These models allow the in silico testing and refinement of mechanistic hypotheses. However, most existing models of this type do not account for concurrent bulk and intracellular biochemical reactions and their possible coupling. Conclusions Here, we describe ChemChaste, an extension for the open-source C++ computational biology library Chaste. ChemChaste enables the spatial simulation of both multicellular and bulk biochemistry by expanding on Chaste’s existing capabilities. In particular, ChemChaste enables (i) simulation of an arbitrary number of spatially diffusing chemicals, (ii) spatially heterogeneous chemical diffusion coefficients, and (iii) inclusion of both bulk and intracellular biochemical reactions and their coupling. ChemChaste also introduces a file-based interface that allows users to define the parameters relating to these functional features without the need to interact directly with Chaste’s core C++ code. We describe ChemChaste and demonstrate its functionality using a selection of chemical and biochemical exemplars, with a focus on demonstrating increased ability in modeling bulk chemical reactions and their coupling with intracellular reactions. Availability and implementation ChemChaste version 1.0 is a free, open-source C++ library, available via GitHub at https://github.com/OSS-Lab/ChemChaste under the BSD license, on the Zenodo archive at zendodo doi, as well as on BioTools (biotools:chemchaste) and SciCrunch (RRID:SCR022208) databases.
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Affiliation(s)
- Connah G M Johnson
- Mathematics of Real-World Systems Doctoral Training Centre, University of Warwick, Coventry, CV35 9EF, UK.,School of Life Sciences, University of Warwick, Coventry, CV35 9EF, UK
| | - Alexander G Fletcher
- School of Mathematics & Statistics, University of Sheffield, Sheffield, S3 7RH, UK.,Bateson Centre, University of Sheffield, Sheffield, S10 2TN, UK
| | - Orkun S Soyer
- School of Life Sciences, University of Warwick, Coventry, CV35 9EF, UK
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3
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Baquero F, Martínez JL, F. Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance. Clin Microbiol Rev 2021; 34:e0005019. [PMID: 34190572 PMCID: PMC8404696 DOI: 10.1128/cmr.00050-19] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.
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Affiliation(s)
- F. Baquero
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - J. L. Martínez
- National Center for Biotechnology (CNB-CSIC), Madrid, Spain
| | - V. F. Lanza
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Central Bioinformatics Unit, Ramón y Cajal Institute for Health Research (IRYCIS), Madrid, Spain
| | - J. Rodríguez-Beltrán
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - J. C. Galán
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - A. San Millán
- National Center for Biotechnology (CNB-CSIC), Madrid, Spain
| | - R. Cantón
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - T. M. Coque
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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Camacho Mateu J, Sireci M, Muñoz MA. Phenotypic-dependent variability and the emergence of tolerance in bacterial populations. PLoS Comput Biol 2021; 17:e1009417. [PMID: 34555011 PMCID: PMC8492070 DOI: 10.1371/journal.pcbi.1009417] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 10/05/2021] [Accepted: 09/03/2021] [Indexed: 11/19/2022] Open
Abstract
Ecological and evolutionary dynamics have been historically regarded as unfolding at broadly separated timescales. However, these two types of processes are nowadays well-documented to intersperse much more tightly than traditionally assumed, especially in communities of microorganisms. Advancing the development of mathematical and computational approaches to shed novel light onto eco-evolutionary problems is a challenge of utmost relevance. With this motivation in mind, here we scrutinize recent experimental results showing evidence of rapid evolution of tolerance by lag in bacterial populations that are periodically exposed to antibiotic stress in laboratory conditions. In particular, the distribution of single-cell lag times-i.e., the times that individual bacteria from the community remain in a dormant state to cope with stress-evolves its average value to approximately fit the antibiotic-exposure time. Moreover, the distribution develops right-skewed heavy tails, revealing the presence of individuals with anomalously large lag times. Here, we develop a parsimonious individual-based model mimicking the actual demographic processes of the experimental setup. Individuals are characterized by a single phenotypic trait: their intrinsic lag time, which is transmitted with variation to the progeny. The model-in a version in which the amplitude of phenotypic variations grows with the parent's lag time-is able to reproduce quite well the key empirical observations. Furthermore, we develop a general mathematical framework allowing us to describe with good accuracy the properties of the stochastic model by means of a macroscopic equation, which generalizes the Crow-Kimura equation in population genetics. Even if the model does not account for all the biological mechanisms (e.g., genetic changes) in a detailed way-i.e., it is a phenomenological one-it sheds light onto the eco-evolutionary dynamics of the problem and can be helpful to design strategies to hinder the emergence of tolerance in bacterial communities. From a broader perspective, this work represents a benchmark for the mathematical framework designed to tackle much more general eco-evolutionary problems, thus paving the road to further research avenues.
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Affiliation(s)
- José Camacho Mateu
- Departamento de Matemáticas, Universidad Carlos III de Madrid, Leganés, Spain
| | - Matteo Sireci
- Departamento de Electromagnetismo y Física de la Materia and Instituto Carlos I de Física Teórica y Computacional, Universidad de Granada, Granada, Spain
| | - Miguel A. Muñoz
- Departamento de Electromagnetismo y Física de la Materia and Instituto Carlos I de Física Teórica y Computacional, Universidad de Granada, Granada, Spain
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Rubin IN, Ispolatov I, Doebeli M. Evolution to alternative levels of stable diversity leaves areas of niche space unexplored. PLoS Comput Biol 2021; 17:e1008650. [PMID: 34319970 PMCID: PMC8351994 DOI: 10.1371/journal.pcbi.1008650] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 08/09/2021] [Accepted: 07/07/2021] [Indexed: 11/18/2022] Open
Abstract
One of the oldest and most persistent questions in ecology and evolution is whether natural communities tend to evolve toward saturation and maximal diversity. Robert MacArthur’s classical theory of niche packing and the theory of adaptive radiations both imply that populations will diversify and fully partition any available niche space. However, the saturation of natural populations is still very much an open area of debate and investigation. Additionally, recent evolutionary theory suggests the existence of alternative evolutionary stable states (ESSs), which implies that some stable communities may not be fully saturated. Using models with classical Lotka-Volterra ecological dynamics and three formulations of evolutionary dynamics (a model using adaptive dynamics, an individual-based model, and a partial differential equation model), we show that following an adaptive radiation, communities can often get stuck in low diversity states when limited by mutations of small phenotypic effect. These low diversity metastable states can also be maintained by limited resources and finite population sizes. When small mutations and finite populations are considered together, it is clear that despite the presence of higher-diversity stable states, natural populations are likely not fully saturating their environment and leaving potential niche space unfilled. Additionally, within-species variation can further reduce community diversity from levels predicted by models that assume species-level homogeneity. Understanding if and when communities evolve to saturate their local environments is imperative to our understanding of natural populations. Using computer simulations of classical evolutionary models, we study whether adaptive radiations tend to lead toward saturated communities, in which no new species can invade or remain trapped in alternative, lower diversity stable states. We show that with asymmetric competition and small effect mutations, evolutionary Red Queen dynamics can trap communities in low diversity metastable states. Moreover, limited resources not only reduces community population sizes, but also reduces community diversity, denying the formation of saturated communities and stabilizing low diversity, non-stationary evolutionary dynamics. Our results are directly relevant to the longstanding questions important to both ecological empiricists and theoreticians on the species packing and saturation of natural environments. Also, by showing the ease evolution can trap communities in low diversity metastable states, we demonstrate the potential harm in relying solely on ESSs to answer questions of biodiversity.
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Affiliation(s)
- Ilan N. Rubin
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada
- * E-mail:
| | - Iaroslav Ispolatov
- Universidad de Santiago de Chile (USACH), Departamento de Física, Santiago, Chile
| | - Michael Doebeli
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada
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Tal O, Tran TD. Adaptive Bet-Hedging Revisited: Considerations of Risk and Time Horizon. Bull Math Biol 2020; 82:50. [PMID: 32248315 PMCID: PMC7128013 DOI: 10.1007/s11538-020-00729-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 03/14/2020] [Indexed: 01/06/2023]
Abstract
Models of adaptive bet-hedging commonly adopt insights from Kelly’s famous work on optimal gambling strategies and the financial value of information. In particular, such models seek evolutionary solutions that maximize long-term average growth rate of lineages, even in the face of highly stochastic growth trajectories. Here, we argue for extensive departures from the standard approach to better account for evolutionary contingencies. Crucially, we incorporate considerations of volatility minimization, motivated by interim extinction risk in finite populations, within a finite time horizon approach to growth maximization. We find that a game-theoretic competitive optimality approach best captures these additional constraints and derive the equilibria solutions under straightforward fitness payoff functions and extinction risks. We show that for both maximal growth and minimal time relative payoffs, the log-optimal strategy is a unique pure strategy symmetric equilibrium, invariant with evolutionary time horizon and robust to low extinction risks.
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Affiliation(s)
- Omri Tal
- Max Planck Institute for Mathematics in the Sciences, Inselstrasse 22, 04103, Leipzig, Germany. .,Cohn Institute for the History and Philosophy of Science and Ideas, Tel Aviv University, Tel Aviv-Yafo, Israel.
| | - Tat Dat Tran
- Max Planck Institute for Mathematics in the Sciences, Inselstrasse 22, 04103, Leipzig, Germany.,Institute of Mathematics, Leipzig University, Augustusplatz 10, 04109, Leipzig, Germany
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