1
|
Carpenter AC, Feist AM, Harrison FS, Paulsen IT, Williams TC. Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments. Metab Eng Commun 2023; 17:e00227. [PMID: 37538933 PMCID: PMC10393799 DOI: 10.1016/j.mec.2023.e00227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/05/2023] [Accepted: 07/11/2023] [Indexed: 08/05/2023] Open
Abstract
Adaptive Laboratory Evolution (ALE) is a powerful tool for engineering and understanding microbial physiology. ALE relies on the selection and enrichment of mutations that enable survival or faster growth under a selective condition imposed by the experimental setup. Phenotypic fitness landscapes are often underpinned by complex genotypes involving multiple genes, with combinatorial positive and negative effects on fitness. Such genotype relationships result in mutational fitness landscapes with multiple local fitness maxima and valleys. Traversing local maxima to find a global maximum often requires an individual or sub-population of cells to traverse fitness valleys. Traversing involves gaining mutations that are not adaptive for a given local maximum but are necessary to 'peak shift' to another local maximum, or eventually a global maximum. Despite these relatively well understood evolutionary principles, and the combinatorial genotypes that underlie most metabolic phenotypes, the majority of applied ALE experiments are conducted using constant selection pressures. The use of constant pressure can result in populations becoming trapped within local maxima, and often precludes the attainment of optimum phenotypes associated with global maxima. Here, we argue that oscillating selection pressures is an easily accessible mechanism for traversing fitness landscapes in ALE experiments, and provide theoretical and practical frameworks for implementation.
Collapse
Affiliation(s)
- Alexander C. Carpenter
- Department of Molecular Sciences and ARC Centre of Excellence in Synthetic Biology, Centre Headquarters, Macquarie University, Sydney, SW, 2109, Australia
- CSIRO Synthetic Biology Future Science Platform, Canberra, ACT, 2601, Australia
| | - Adam M. Feist
- Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA
- Joint BioEnergy Institute, 5885 Hollis Street, 4th Floor, Emeryville, CA, 94608, USA
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kgs, Lyngby, Denmark
| | - Fergus S.M. Harrison
- Department of Molecular Sciences and ARC Centre of Excellence in Synthetic Biology, Centre Headquarters, Macquarie University, Sydney, SW, 2109, Australia
| | - Ian T. Paulsen
- Department of Molecular Sciences and ARC Centre of Excellence in Synthetic Biology, Centre Headquarters, Macquarie University, Sydney, SW, 2109, Australia
| | - Thomas C. Williams
- Department of Molecular Sciences and ARC Centre of Excellence in Synthetic Biology, Centre Headquarters, Macquarie University, Sydney, SW, 2109, Australia
- CSIRO Synthetic Biology Future Science Platform, Canberra, ACT, 2601, Australia
| |
Collapse
|
2
|
Obolski U, Swarthout TD, Kalizang'oma A, Mwalukomo TS, Chan JM, Weight CM, Brown C, Cave R, Cornick J, Kamng'ona AW, Msefula J, Ercoli G, Brown JS, Lourenço J, Maiden MC, French N, Gupta S, Heyderman RS. The metabolic, virulence and antimicrobial resistance profiles of colonising Streptococcus pneumoniae shift after PCV13 introduction in urban Malawi. Nat Commun 2023; 14:7477. [PMID: 37978177 PMCID: PMC10656543 DOI: 10.1038/s41467-023-43160-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 11/02/2023] [Indexed: 11/19/2023] Open
Abstract
Streptococcus pneumoniae causes substantial mortality among children under 5-years-old worldwide. Polysaccharide conjugate vaccines (PCVs) are highly effective at reducing vaccine serotype disease, but emergence of non-vaccine serotypes and persistent nasopharyngeal carriage threaten this success. We investigated the hypothesis that following vaccine, adapted pneumococcal genotypes emerge with the potential for vaccine escape. We genome sequenced 2804 penumococcal isolates, collected 4-8 years after introduction of PCV13 in Blantyre, Malawi. We developed a pipeline to cluster the pneumococcal population based on metabolic core genes into "Metabolic genotypes" (MTs). We show that S. pneumoniae population genetics are characterised by emergence of MTs with distinct virulence and antimicrobial resistance (AMR) profiles. Preliminary in vitro and murine experiments revealed that representative isolates from emerging MTs differed in growth, haemolytic, epithelial infection, and murine colonisation characteristics. Our results suggest that in the context of PCV13 introduction, pneumococcal population dynamics had shifted, a phenomenon that could further undermine vaccine control and promote spread of AMR.
Collapse
Affiliation(s)
- Uri Obolski
- Department of Epidemiology and Preventive Medicine, School of Public Health, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
- Porter School of the Environment and Earth Sciences, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel.
| | - Todd D Swarthout
- Malawi Liverpool Wellcome Programme, Blantyre, Malawi
- Mucosal Pathogens Research Group, Research Department of Infection, Division of Infection & Immunity, University College London, London, United Kingdom
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Akuzike Kalizang'oma
- Malawi Liverpool Wellcome Programme, Blantyre, Malawi
- Mucosal Pathogens Research Group, Research Department of Infection, Division of Infection & Immunity, University College London, London, United Kingdom
| | | | - Jia Mun Chan
- Mucosal Pathogens Research Group, Research Department of Infection, Division of Infection & Immunity, University College London, London, United Kingdom
| | - Caroline M Weight
- Mucosal Pathogens Research Group, Research Department of Infection, Division of Infection & Immunity, University College London, London, United Kingdom
- Faculty of Health and Medicine, Biomedical and Life Sciences, Lancaster University, Lancaster, United Kingdom
- Biomedical and Life Sciences, Faculty of Health and Medicine, Lancaster University, Lancaster, United Kingdom
| | - Comfort Brown
- Malawi Liverpool Wellcome Programme, Blantyre, Malawi
| | - Rory Cave
- Mucosal Pathogens Research Group, Research Department of Infection, Division of Infection & Immunity, University College London, London, United Kingdom
| | - Jen Cornick
- Malawi Liverpool Wellcome Programme, Blantyre, Malawi
- Clinical Infection, Microbiology and Immunology, Institute of Infection Veterinary & Ecological Science, University of Liverpool, Liverpool, United Kingdom
| | | | | | - Giuseppe Ercoli
- UCL Respiratory, Division of Medicine, University College London, London, United Kingdom
| | - Jeremy S Brown
- UCL Respiratory, Division of Medicine, University College London, London, United Kingdom
| | - José Lourenço
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Universidade Católica Portuguesa, Faculty of Medicine, Biomedical Research Centre, Lisbon, Portugal
| | - Martin C Maiden
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Neil French
- Clinical Infection, Microbiology and Immunology, Institute of Infection Veterinary & Ecological Science, University of Liverpool, Liverpool, United Kingdom
| | - Sunetra Gupta
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Robert S Heyderman
- Malawi Liverpool Wellcome Programme, Blantyre, Malawi.
- Mucosal Pathogens Research Group, Research Department of Infection, Division of Infection & Immunity, University College London, London, United Kingdom.
| |
Collapse
|
3
|
Roitershtein A, Rastegar R, Chapkin RS, Ivanov I. Extinction scenarios in evolutionary processes: a multinomial Wright-Fisher approach. J Math Biol 2023; 87:63. [PMID: 37751048 PMCID: PMC10586398 DOI: 10.1007/s00285-023-01993-7] [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: 12/06/2019] [Revised: 08/16/2023] [Accepted: 08/31/2023] [Indexed: 09/27/2023]
Abstract
We study a discrete-time multi-type Wright-Fisher population process. The mean-field dynamics of the stochastic process is induced by a general replicator difference equation. We prove several results regarding the asymptotic behavior of the model, focusing on the impact of the mean-field dynamics on it. One of the results is a limit theorem that describes sufficient conditions for an almost certain path to extinction, first eliminating the type which is the least fit at the mean-field equilibrium. The effect is explained by the metastability of the stochastic system, which under the conditions of the theorem spends almost all time before the extinction event in a neighborhood of the equilibrium. In addition to the limit theorems, we propose a maximization principle for a general deterministic replicator dynamics and study its implications for the stochastic model.
Collapse
Affiliation(s)
| | - Reza Rastegar
- Occidental Petroleum Corporation, Houston, TX, 77046, USA
| | - Robert S Chapkin
- Department of Nutrition - Program in Integrative Nutrition & Complex Diseases, Texas A &M University, College Station, TX, 77843, USA
| | - Ivan Ivanov
- Department of Veterinary Physiology and Pharmacology, Texas A &M University, College Station, TX, 77843, USA.
| |
Collapse
|
4
|
Lobinska G, Pilpel Y, Ram Y. Phenotype switching of the mutation rate facilitates adaptive evolution. Genetics 2023; 225:iyad111. [PMID: 37293818 PMCID: PMC10471227 DOI: 10.1093/genetics/iyad111] [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: 02/05/2023] [Revised: 02/05/2023] [Accepted: 05/25/2023] [Indexed: 06/10/2023] Open
Abstract
The mutation rate plays an important role in adaptive evolution. It can be modified by mutator and anti-mutator alleles. Recent empirical evidence hints that the mutation rate may vary among genetically identical individuals: evidence from bacteria suggests that the mutation rate can be affected by expression noise of a DNA repair protein and potentially also by translation errors in various proteins. Importantly, this non-genetic variation may be heritable via a transgenerational epigenetic mode of inheritance, giving rise to a mutator phenotype that is independent from mutator alleles. Here, we investigate mathematically how the rate of adaptive evolution is affected by the rate of mutation rate phenotype switching. We model an asexual population with two mutation rate phenotypes, non-mutator and mutator. An offspring may switch from its parental phenotype to the other phenotype. We find that switching rates that correspond to so-far empirically described non-genetic systems of inheritance of the mutation rate lead to higher rates of adaptation on both artificial and natural fitness landscapes. These switching rates can maintain within the same individuals both a mutator phenotype and intermediary mutations, a combination that facilitates adaptation. Moreover, non-genetic inheritance increases the proportion of mutators in the population, which in turn increases the probability of hitchhiking of the mutator phenotype with adaptive mutations. This in turns facilitates the acquisition of additional adaptive mutations. Our results rationalize recently observed noise in the expression of proteins that affect the mutation rate and suggest that non-genetic inheritance of this phenotype may facilitate evolutionary adaptive processes.
Collapse
Affiliation(s)
- Gabriela Lobinska
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Yitzhak Pilpel
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Yoav Ram
- School of Zoology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
| |
Collapse
|
5
|
Lewin-Epstein O, Jaques Y, Feldman MW, Kaufer D, Hadany L. Evolutionary modeling suggests that addictions may be driven by competition-induced microbiome dysbiosis. Commun Biol 2023; 6:782. [PMID: 37495841 PMCID: PMC10372008 DOI: 10.1038/s42003-023-05099-0] [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: 03/16/2022] [Accepted: 07/05/2023] [Indexed: 07/28/2023] Open
Abstract
Recent studies revealed mechanisms by which the microbiome affects its host's brain, behavior and wellbeing, and that dysbiosis - persistent microbiome-imbalance - is associated with the onset and progress of various chronic diseases, including addictive behaviors. Yet, understanding of the ecological and evolutionary processes that shape the host-microbiome ecosystem and affect the host state, is still limited. Here we propose that competition dynamics within the microbiome, associated with host-microbiome mutual regulation, may promote dysbiosis and aggravate addictive behaviors. We construct a mathematical framework, modeling the dynamics of the host-microbiome ecosystem in response to alterations. We find that when this ecosystem is exposed to substantial perturbations, the microbiome may shift towards a composition that reinforces the new host state. Such a positive feedback loop augments post-perturbation imbalances, hindering attempts to return to the initial equilibrium, promoting relapse episodes and prolonging addictions. We show that the initial microbiome composition is a key factor: a diverse microbiome enhances the ecosystem's resilience, whereas lower microbiome diversity is more prone to lead to dysbiosis, exacerbating addictions. This framework provides evolutionary and ecological perspectives on host-microbiome interactions and their implications for host behavior and health, while offering verifiable predictions with potential relevance to clinical treatments.
Collapse
Affiliation(s)
- Ohad Lewin-Epstein
- School of Plant Sciences and Food Security, Tel Aviv University, Tel Aviv, 6997801, Israel.
- Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
| | - Yanabah Jaques
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, 94720, USA
| | - Marcus W Feldman
- Department of Biology, Stanford University, Stanford, CA, 94305, USA
| | - Daniela Kaufer
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, 94720, USA
- Department of Integrative Biology, University of California, Berkeley, CA, 94720, USA
| | - Lilach Hadany
- School of Plant Sciences and Food Security, Tel Aviv University, Tel Aviv, 6997801, Israel.
- Sagol school of neuroscience, Tel Aviv University, Tel Aviv, 6997801, Israel.
| |
Collapse
|
6
|
Ballu A, Despréaux P, Duplaix C, Dérédec A, Carpentier F, Walker AS. Antifungal alternation can be beneficial for durability but at the cost of generalist resistance. Commun Biol 2023; 6:180. [PMID: 36797413 PMCID: PMC9935548 DOI: 10.1038/s42003-023-04550-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 02/03/2023] [Indexed: 02/18/2023] Open
Abstract
The evolution of resistance to pesticides is a major burden in agriculture. Resistance management involves maximizing selection pressure heterogeneity, particularly by combining active ingredients with different modes of action. We tested the hypothesis that alternation may delay the build-up of resistance not only by spreading selection pressure over longer periods, but also by decreasing the rate of evolution of resistance to alternated fungicides, by applying an experimental evolution approach to the economically important crop pathogen Zymoseptoria tritici. Our results show that alternation is either neutral or slows the overall resistance evolution rate, relative to continuous fungicide use, but results in higher levels of generalism in evolved lines. We demonstrate that the nature of the fungicides, and therefore their relative intrinsic risk of resistance may underly this trade-off, more so than the number of fungicides and the rhythm of alternation. This trade-off is also dynamic over the course of resistance evolution. These findings open up new possibilities for tailoring resistance management effectively while optimizing interplay between alternation components.
Collapse
Affiliation(s)
- Agathe Ballu
- grid.507621.7Université Paris-Saclay, INRAE, UR BIOGER, 91120 Palaiseau, France
| | - Philomène Despréaux
- grid.507621.7Université Paris-Saclay, INRAE, UR BIOGER, 91120 Palaiseau, France
| | - Clémentine Duplaix
- grid.507621.7Université Paris-Saclay, INRAE, UR BIOGER, 91120 Palaiseau, France
| | - Anne Dérédec
- grid.507621.7Université Paris-Saclay, INRAE, UR BIOGER, 91120 Palaiseau, France
| | - Florence Carpentier
- grid.507621.7Université Paris-Saclay, INRAE, UR MaIAGE, 78350 Jouy-en-Josas, France ,grid.417885.70000 0001 2185 8223AgroParisTech, 91120 Palaiseau, France
| | | |
Collapse
|
7
|
Azbukina N, Zharikova A, Ramensky V. Intragenic compensation through the lens of deep mutational scanning. Biophys Rev 2022; 14:1161-1182. [PMID: 36345285 PMCID: PMC9636336 DOI: 10.1007/s12551-022-01005-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 09/26/2022] [Indexed: 12/20/2022] Open
Abstract
A significant fraction of mutations in proteins are deleterious and result in adverse consequences for protein function, stability, or interaction with other molecules. Intragenic compensation is a specific case of positive epistasis when a neutral missense mutation cancels effect of a deleterious mutation in the same protein. Permissive compensatory mutations facilitate protein evolution, since without them all sequences would be extremely conserved. Understanding compensatory mechanisms is an important scientific challenge at the intersection of protein biophysics and evolution. In human genetics, intragenic compensatory interactions are important since they may result in variable penetrance of pathogenic mutations or fixation of pathogenic human alleles in orthologous proteins from related species. The latter phenomenon complicates computational and clinical inference of an allele's pathogenicity. Deep mutational scanning is a relatively new technique that enables experimental studies of functional effects of thousands of mutations in proteins. We review the important aspects of the field and discuss existing limitations of current datasets. We reviewed ten published DMS datasets with quantified functional effects of single and double mutations and described rates and patterns of intragenic compensation in eight of them. Supplementary Information The online version contains supplementary material available at 10.1007/s12551-022-01005-w.
Collapse
Affiliation(s)
- Nadezhda Azbukina
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 1-73, Leninskie Gory, 119991 Moscow, Russia
| | - Anastasia Zharikova
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 1-73, Leninskie Gory, 119991 Moscow, Russia
- National Medical Research Center for Therapy and Preventive Medicine, Petroverigsky per., 10, Bld.3, 101000 Moscow, Russia
| | - Vasily Ramensky
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 1-73, Leninskie Gory, 119991 Moscow, Russia
- National Medical Research Center for Therapy and Preventive Medicine, Petroverigsky per., 10, Bld.3, 101000 Moscow, Russia
| |
Collapse
|
8
|
Gabzi T, Pilpel Y, Friedlander T. Fitness landscape analysis of a tRNA gene reveals that the wild type allele is sub-optimal, yet mutationally robust. Mol Biol Evol 2022; 39:6670756. [PMID: 35976926 PMCID: PMC9447856 DOI: 10.1093/molbev/msac178] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Fitness landscape mapping and the prediction of evolutionary trajectories on these landscapes are major tasks in evolutionary biology research. Evolutionary dynamics is tightly linked to the landscape topography, but this relation is not straightforward. Here, we analyze a fitness landscape of a yeast tRNA gene, previously measured under four different conditions. We find that the wild type allele is sub-optimal, and 8–10% of its variants are fitter. We rule out the possibilities that the wild type is fittest on average on these four conditions or located on a local fitness maximum. Notwithstanding, we cannot exclude the possibility that the wild type might be fittest in some of the many conditions in the complex ecology that yeast lives at. Instead, we find that the wild type is mutationally robust (“flat”), while more fit variants are typically mutationally fragile. Similar observations of mutational robustness or flatness have been so far made in very few cases, predominantly in viral genomes.
Collapse
Affiliation(s)
- Tzahi Gabzi
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Yitzhak Pilpel
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Tamar Friedlander
- The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture Faculty of Agriculture, Hebrew University of Jerusalem, 229 Herzl St., Rehovot 7610001, Israel
| |
Collapse
|
9
|
Stark C, Bautista-Leung T, Siegfried J, Herschlag D. Systematic investigation of the link between enzyme catalysis and cold adaptation. eLife 2022; 11:72884. [PMID: 35019838 PMCID: PMC8754429 DOI: 10.7554/elife.72884] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 12/24/2021] [Indexed: 11/13/2022] Open
Abstract
Cold temperature is prevalent across the biosphere and slows the rates of chemical reactions. Increased catalysis has been predicted to be a dominant adaptive trait of enzymes to reduced temperature, and this expectation has informed physical models for enzyme catalysis and influenced bioprospecting strategies. To systematically test rate enhancement as an adaptive trait to cold, we paired kinetic constants of 2223 enzyme reactions with their organism's optimal growth temperature (TGrowth) and analyzed trends of rate constants as a function of TGrowth. These data do not support a general increase in rate enhancement in cold adaptation. In the model enzyme ketosteroid isomerase (KSI), there is prior evidence for temperature adaptation from a change in an active site residue that results in a tradeoff between activity and stability. Nevertheless, we found that little of the rate constant variation for 20 KSI variants was accounted for by TGrowth. In contrast, and consistent with prior expectations, we observed a correlation between stability and TGrowth across 433 proteins. These results suggest that temperature exerts a weaker selection pressure on enzyme rate constants than stability and that evolutionary forces other than temperature are responsible for the majority of enzymatic rate constant variation.
Collapse
Affiliation(s)
- Catherine Stark
- ChEM-H, Stanford University, Stanford, United States.,Department of Biochemistry, Stanford University, Stanford, United States
| | | | - Joanna Siegfried
- Department of Biochemistry, Stanford University, Stanford, United States
| | - Daniel Herschlag
- ChEM-H, Stanford University, Stanford, United States.,Department of Biochemistry, Stanford University, Stanford, United States.,Department of Chemical Engineering, Stanford University, Stanford, United States
| |
Collapse
|
10
|
An Antigenic Thrift-Based Approach to Influenza Vaccine Design. Vaccines (Basel) 2021; 9:vaccines9060657. [PMID: 34208489 PMCID: PMC8235769 DOI: 10.3390/vaccines9060657] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 06/04/2021] [Accepted: 06/05/2021] [Indexed: 11/19/2022] Open
Abstract
The antigenic drift theory states that influenza evolves via the gradual accumulation of mutations, decreasing a host’s immune protection against previous strains. Influenza vaccines are designed accordingly, under the premise of antigenic drift. However, a paradox exists at the centre of influenza research. If influenza evolved primarily through mutation in multiple epitopes, multiple influenza strains should co-circulate. Such a multitude of strains would render influenza vaccines quickly inefficacious. Instead, a single or limited number of strains dominate circulation each influenza season. Unless additional constraints are placed on the evolution of influenza, antigenic drift does not adequately explain these observations. Here, we explore the constraints placed on antigenic drift and a competing theory of influenza evolution – antigenic thrift. In contrast to antigenic drift, antigenic thrift states that immune selection targets epitopes of limited variability, which constrain the variability of the virus. We explain the implications of antigenic drift and antigenic thrift and explore their current and potential uses in the context of influenza vaccine design.
Collapse
|
11
|
Pribis JP, García-Villada L, Zhai Y, Lewin-Epstein O, Wang AZ, Liu J, Xia J, Mei Q, Fitzgerald DM, Bos J, Austin RH, Herman C, Bates D, Hadany L, Hastings PJ, Rosenberg SM. Gamblers: An Antibiotic-Induced Evolvable Cell Subpopulation Differentiated by Reactive-Oxygen-Induced General Stress Response. Mol Cell 2019; 74:785-800.e7. [PMID: 30948267 PMCID: PMC6553487 DOI: 10.1016/j.molcel.2019.02.037] [Citation(s) in RCA: 97] [Impact Index Per Article: 19.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 01/17/2019] [Accepted: 02/26/2019] [Indexed: 11/23/2022]
Abstract
Antibiotics can induce mutations that cause antibiotic resistance. Yet, despite their importance, mechanisms of antibiotic-promoted mutagenesis remain elusive. We report that the fluoroquinolone antibiotic ciprofloxacin (cipro) induces mutations by triggering transient differentiation of a mutant-generating cell subpopulation, using reactive oxygen species (ROS). Cipro-induced DNA breaks activate the Escherichia coli SOS DNA-damage response and error-prone DNA polymerases in all cells. However, mutagenesis is limited to a cell subpopulation in which electron transfer together with SOS induce ROS, which activate the sigma-S (σS) general-stress response, which allows mutagenic DNA-break repair. When sorted, this small σS-response-"on" subpopulation produces most antibiotic cross-resistant mutants. A U.S. Food and Drug Administration (FDA)-approved drug prevents σS induction, specifically inhibiting antibiotic-promoted mutagenesis. Further, SOS-inhibited cell division, which causes multi-chromosome cells, promotes mutagenesis. The data support a model in which within-cell chromosome cooperation together with development of a "gambler" cell subpopulation promote resistance evolution without risking most cells.
Collapse
Affiliation(s)
- John P Pribis
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA; Graduate Program in Integrative Molecular and Biomedical Sciences, Baylor College of Medicine, Houston, TX 77030, USA
| | - Libertad García-Villada
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yin Zhai
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ohad Lewin-Epstein
- Department of Molecular Biology and Ecology of Plants, Tel-Aviv University, Tel-Aviv, Israel
| | - Anthony Z Wang
- Department of Biochemistry and Cell Biology, Rice University, Houston, TX 77030, USA
| | - Jingjing Liu
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jun Xia
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Qian Mei
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA; Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX 77030, USA
| | - Devon M Fitzgerald
- Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Julia Bos
- Department of Physics, Princeton University, Princeton, NJ 08544-0708, USA; Lewis Sigler Institute, Princeton University, Princeton, NJ 08544-0708, USA
| | - Robert H Austin
- Lewis Sigler Institute, Princeton University, Princeton, NJ 08544-0708, USA
| | - Christophe Herman
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA; Graduate Program in Integrative Molecular and Biomedical Sciences, Baylor College of Medicine, Houston, TX 77030, USA
| | - David Bates
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA; Graduate Program in Integrative Molecular and Biomedical Sciences, Baylor College of Medicine, Houston, TX 77030, USA
| | - Lilach Hadany
- Department of Molecular Biology and Ecology of Plants, Tel-Aviv University, Tel-Aviv, Israel
| | - P J Hastings
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Susan M Rosenberg
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; The Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA; Graduate Program in Integrative Molecular and Biomedical Sciences, Baylor College of Medicine, Houston, TX 77030, USA; Department of Biochemistry and Cell Biology, Rice University, Houston, TX 77030, USA; Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX 77030, USA.
| |
Collapse
|
12
|
Zhong Z, Liu CC. Probing pathways of adaptation with continuous evolution. CURRENT OPINION IN SYSTEMS BIOLOGY 2019; 14:18-24. [PMID: 31608311 PMCID: PMC6788780 DOI: 10.1016/j.coisb.2019.02.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Affiliation(s)
- Ziwei Zhong
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA 92697, USA
| | - Chang C. Liu
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA 92697, USA
- Department of Chemistry, University of California, Irvine, Irvine, CA 92697, USA
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA 92697, USA
- Lead Contact
| |
Collapse
|
13
|
Computational Complexity as an Ultimate Constraint on Evolution. Genetics 2019; 212:245-265. [PMID: 30833289 DOI: 10.1534/genetics.119.302000] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Accepted: 02/22/2019] [Indexed: 01/28/2023] Open
Abstract
Experiments show that evolutionary fitness landscapes can have a rich combinatorial structure due to epistasis. For some landscapes, this structure can produce a computational constraint that prevents evolution from finding local fitness optima-thus overturning the traditional assumption that local fitness peaks can always be reached quickly if no other evolutionary forces challenge natural selection. Here, I introduce a distinction between easy landscapes of traditional theory where local fitness peaks can be found in a moderate number of steps, and hard landscapes where finding local optima requires an infeasible amount of time. Hard examples exist even among landscapes with no reciprocal sign epistasis; on these semismooth fitness landscapes, strong selection weak mutation dynamics cannot find the unique peak in polynomial time. More generally, on hard rugged fitness landscapes that include reciprocal sign epistasis, no evolutionary dynamics-even ones that do not follow adaptive paths-can find a local fitness optimum quickly. Moreover, on hard landscapes, the fitness advantage of nearby mutants cannot drop off exponentially fast but has to follow a power-law that long-term evolution experiments have associated with unbounded growth in fitness. Thus, the constraint of computational complexity enables open-ended evolution on finite landscapes. Knowing this constraint allows us to use the tools of theoretical computer science and combinatorial optimization to characterize the fitness landscapes that we expect to see in nature. I present candidates for hard landscapes at scales from single genes, to microbes, to complex organisms with costly learning (Baldwin effect) or maintained cooperation (Hankshaw effect). Just how ubiquitous hard landscapes (and the corresponding ultimate constraint on evolution) are in nature becomes an open empirical question.
Collapse
|
14
|
Blanco C, Janzen E, Pressman A, Saha R, Chen IA. Molecular Fitness Landscapes from High-Coverage Sequence Profiling. Annu Rev Biophys 2019; 48:1-18. [PMID: 30601678 DOI: 10.1146/annurev-biophys-052118-115333] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The function of fitness (or molecular activity) in the space of all possible sequences is known as the fitness landscape. Evolution is a random walk on the fitness landscape, with a bias toward climbing hills. Mapping the topography of real fitness landscapes is fundamental to understanding evolution, but previous efforts were hampered by the difficulty of obtaining large, quantitative data sets. The accessibility of high-throughput sequencing (HTS) has transformed this study, enabling large-scale enumeration of fitness for many mutants and even complete sequence spaces in some cases. We review the progress of high-throughput studies in mapping molecular fitness landscapes, both in vitro and in vivo, as well as opportunities for future research. Such studies are rapidly growing in number. HTS is expected to have a profound effect on the understanding of real molecular fitness landscapes.
Collapse
Affiliation(s)
- Celia Blanco
- Department of Chemistry and Biochemistry, University of California, Santa Barbara, California 93106, USA; , , , ,
| | - Evan Janzen
- Department of Chemistry and Biochemistry, University of California, Santa Barbara, California 93106, USA; , , , , .,Biomolecular Science and Engineering Program, University of California, Santa Barbara, California 93106, USA
| | - Abe Pressman
- Department of Chemistry and Biochemistry, University of California, Santa Barbara, California 93106, USA; , , , , .,Department of Chemical Engineering, University of California, Santa Barbara, California 93106, USA
| | - Ranajay Saha
- Department of Chemistry and Biochemistry, University of California, Santa Barbara, California 93106, USA; , , , ,
| | - Irene A Chen
- Biomolecular Science and Engineering Program, University of California, Santa Barbara, California 93106, USA
| |
Collapse
|
15
|
Obolski U, Lewin-Epstein O, Even-Tov E, Ram Y, Hadany L. With a little help from my friends: cooperation can accelerate the rate of adaptive valley crossing. BMC Evol Biol 2017. [PMID: 28623896 PMCID: PMC5473968 DOI: 10.1186/s12862-017-0983-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Background Natural selection favors changes that lead to genotypes possessing high fitness. A conflict arises when several mutations are required for adaptation, but each mutation is separately deleterious. The process of a population evolving from a genotype encoding for a local fitness maximum to a higher fitness genotype is termed an adaptive peak shift. Results Here we suggest cooperative behavior as a factor that can facilitate adaptive peak shifts. We model cooperation in a public goods scenario, wherein each individual contributes resources that are later equally redistributed among all cooperating individuals. We use mathematical modeling and stochastic simulations to study the effect of cooperation on peak shifts in both panmictic and structured populations. Our results show that cooperation can substantially affect the rate of complex adaptation. Furthermore, we show that cooperation increases the population diversity throughout the peak shift process, thus increasing the robustness of the population to sudden environmental changes. Conclusions We provide a new explanation to adaptive valley crossing in natural populations and suggest that the long term evolution of a species depends on its social behavior. Electronic supplementary material The online version of this article (doi:10.1186/s12862-017-0983-2) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Uri Obolski
- Department of Molecular Biology and Ecology of Plants, Tel-Aviv University, 6997801, Tel Aviv, Israel.,Current address: Department of Zoology, University of Oxford, Oxford, UK
| | - Ohad Lewin-Epstein
- Department of Molecular Biology and Ecology of Plants, Tel-Aviv University, 6997801, Tel Aviv, Israel
| | - Eran Even-Tov
- Department of Molecular Microbiology and Biotechnology, Tel-Aviv University, Tel-Aviv, Israel
| | - Yoav Ram
- Department of Molecular Biology and Ecology of Plants, Tel-Aviv University, 6997801, Tel Aviv, Israel.,Present Address: Department of Biology, Stanford University, Stanford, CA, USA
| | - Lilach Hadany
- Department of Molecular Biology and Ecology of Plants, Tel-Aviv University, 6997801, Tel Aviv, Israel.
| |
Collapse
|