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Jiao J, Lv X, Shen C, Morigen M. Genome and transcriptomic analysis of the adaptation of Escherichia coli to environmental stresses. Comput Struct Biotechnol J 2024; 23:2132-2140. [PMID: 38817967 PMCID: PMC11137339 DOI: 10.1016/j.csbj.2024.05.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 05/05/2024] [Accepted: 05/17/2024] [Indexed: 06/01/2024] Open
Abstract
In natural niches, bacteria are forced to spend most of their lives under various environmental stresses, such as nutrient limitation, heavy metal pollution, heat and antibiotic stress. To cope with adverse environments, bacterial genome can during the life cycle, produce potential adaptive mutants. The genomic changes, especially mutations, in the genes that encode RNA polymerase and transcription factors, might lead to variations in the transcriptome. These variations enable bacteria to cope with environmental stresses through physiological adaptation in response to stress. This paper reviews the recent contributions of genomic and transcriptomic analyses in understanding the adaption mechanism of Escherichia coli to environmental stresses. Various genomic changes have been observed in E. coli strains in laboratory or under natural stresses, including starvation, heavy metals, acidic conditions, heat shock and antibiotics. The mutations include slight changes (one to several nucleotides), deletions, insertions, chromosomal rearrangements and variations in copy numbers. The transcriptome of E. coli largely changes due to genomic mutations. However, the transcriptional profiles vary due to variations in stress selections. Cellular adaptation to the selections is associated with transcriptional changes resulting from genomic mutations. Changes in genome and transcriptome are cooperative and jointly affect the adaptation of E. coli to different environments. This comprehensive review reveals that coordination of genome mutations and transcriptional variations needs to be explored further to provide a better understanding of the mechanisms of bacterial adaptation to stresses.
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Affiliation(s)
- Jianlu Jiao
- State Key Laboratory of Reproductive Regulation & Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Xiaoli Lv
- Inner Mongolia Key Laboratory for Molecular Regulation of the Cell, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Chongjie Shen
- State Key Laboratory of Reproductive Regulation & Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Morigen Morigen
- State Key Laboratory of Reproductive Regulation & Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
- Inner Mongolia Key Laboratory for Molecular Regulation of the Cell, School of Life Sciences, Inner Mongolia University, Hohhot, China
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2
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James B, Reesaul H, Kashif S, Behruznia M, Meehan CJ, Domingo-Sananes MR, Hubbard ATM. The effect of antibiotic selection on collateral effects and evolvability of uropathogenic Escherichia coli. NPJ ANTIMICROBIALS AND RESISTANCE 2024; 2:19. [PMID: 39036800 PMCID: PMC11254750 DOI: 10.1038/s44259-024-00037-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 06/28/2024] [Indexed: 07/23/2024]
Abstract
Trimethoprim is recommended as a first-line treatment of urinary tract infections (UTIs) in the UK. In 2018, 31.4% of Escherichia coli isolated from UTIs in England were trimethoprim-resistant, leading to overreliance on other first and second-line antibiotics. Here, we assessed whether, in principle, prior selection with trimethoprim results in collateral effects to other antibiotics recommended for the treatment of UTIs. As collateral effects, we considered changes in susceptibility, mutation-selection window and population establishment probability. We selected 10 trimethoprim-resistant derivatives from three clinical isolates of uropathogenic Escherichia coli. We found that mutations conferring trimethoprim resistance did not have any collateral effects on fosfomycin. In contrast, resistance to trimethoprim resulted in decreased susceptibility (collateral resistance) to nitrofurantoin, below the clinical breakpoint and narrowed the mutation-selection window, thereby reducing the maximum concentration for selection of nitrofurantoin resistance mutations. Our analyses demonstrate that multiple collateral responses should be accounted for when predicting and optimising antibiotic use, limiting future antimicrobial resistance emergence.
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Affiliation(s)
- Beth James
- Department of Biosciences, Nottingham Trent University, Clifton Campus, College Drive, Clifton, Nottingham NG11 8NS UK
| | - Hishikha Reesaul
- Department of Biosciences, Nottingham Trent University, Clifton Campus, College Drive, Clifton, Nottingham NG11 8NS UK
| | - Sidra Kashif
- Department of Biosciences, Nottingham Trent University, Clifton Campus, College Drive, Clifton, Nottingham NG11 8NS UK
| | - Mahboobeh Behruznia
- Department of Biosciences, Nottingham Trent University, Clifton Campus, College Drive, Clifton, Nottingham NG11 8NS UK
| | - Conor J. Meehan
- Department of Biosciences, Nottingham Trent University, Clifton Campus, College Drive, Clifton, Nottingham NG11 8NS UK
| | - Maria Rosa Domingo-Sananes
- Department of Biosciences, Nottingham Trent University, Clifton Campus, College Drive, Clifton, Nottingham NG11 8NS UK
| | - Alasdair T. M. Hubbard
- Department of Biosciences, Nottingham Trent University, Clifton Campus, College Drive, Clifton, Nottingham NG11 8NS UK
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3
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Baquero F, Pérez-Cobas AE, Aracil-Gisbert S, Coque TM, Zamora J. Selection versus transmission: Quantitative and organismic biology in antibiotic resistance. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2024; 121:105606. [PMID: 38768878 DOI: 10.1016/j.meegid.2024.105606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 05/12/2024] [Accepted: 05/17/2024] [Indexed: 05/22/2024]
Abstract
We aimed to determine the importance of selection (mostly dependent on the anthropogenic use of antimicrobials) and transmission (mostly dependent on hygiene and sanitation) as drivers of the spread of antibiotic-resistant bacterial populations. The first obstacle to estimating the relative weight of both independent variables is the lack of detailed quantitative data concerning the number of bacterial cells, potentially either pathogenic or harmless, and bacterial species exposed to antimicrobial action in the microbiotas of specific environments. The second obstacle is the difficulty of considering the relative importance of the transmission and selection exerting their combined effects on antibiotic resistance across eco-biological levels. As a consequence, advances are urgently required in quantitative biology and organismic biology of antimicrobial resistance. The absolute number of humans exposed to antibiotics and the absolute number of potentially pathogenic and commensal bacteria in their microbiomes should influence both the selection and transmission of resistant bacterial populations. The "whole Earth" microbiome, with astonishingly high numbers of bacterial cells and species, which are also exposed to anthropogenic antimicrobials in various biogeographical spaces, shapes the antibiotic resistance landscape. These biogeographical spaces influence various intensities of selection and transmission of potentially pathogenic bacteria. While waiting for more precise data, biostatistics analysis and mathematical or computational modeling can provide proxies to compare the influence of selection and transmission in resistant bacteria. In European countries with lower sanitation levels, antibiotic consumption plays a major role in increasing antibiotic resistance; however, this is not the case in countries with high sanitation levels. Although both independent variables are linked, their relative influence on the level of antibiotic resistance varies according to the particular location. Therefore, interventions directed to decrease antibiotic resistance should be designed "a la carte" for specific locations with particular ecological conditions, including sanitation facilities.
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Affiliation(s)
- F Baquero
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Madrid, Spain; Center for Biomedical Research in Epidemiology and Public Health Network (CIBERESP-Group 33), Madrid, Spain.
| | - A E Pérez-Cobas
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Madrid, Spain; Center for Biomedical Research in Infectious Diseases Network (CIBERINFEC), Madrid, Spain
| | - S Aracil-Gisbert
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Madrid, Spain; Center for Biomedical Research in Infectious Diseases Network (CIBERINFEC), Madrid, Spain
| | - T M Coque
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Madrid, Spain; Center for Biomedical Research in Infectious Diseases Network (CIBERINFEC), Madrid, Spain
| | - J Zamora
- Clinical Biostatistics Unit, Ramón y Cajal University Hospital, and Ramón y Cajal Institute for Health Research (IRYCIS) Madrid, Spain; Center for Biomedical Research in Epidemiology and Public Health Network (CIBERESP-Group 42), Madrid, Spain; Institute of Metabolism and Systems Research, Biostatistics in Maternal and Perinatal Health, University of Birmingham, UK
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4
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Abbas A, Barkhouse A, Hackenberger D, Wright GD. Antibiotic resistance: A key microbial survival mechanism that threatens public health. Cell Host Microbe 2024; 32:837-851. [PMID: 38870900 DOI: 10.1016/j.chom.2024.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 05/13/2024] [Accepted: 05/17/2024] [Indexed: 06/15/2024]
Abstract
Antibiotic resistance (AMR) is a global public health threat, challenging the effectiveness of antibiotics in combating bacterial infections. AMR also represents one of the most crucial survival traits evolved by bacteria. Antibiotics emerged hundreds of millions of years ago as advantageous secondary metabolites produced by microbes. Consequently, AMR is equally ancient and hardwired into the genetic fabric of bacteria. Human use of antibiotics for disease treatment has created selection pressure that spurs the evolution of new resistance mechanisms and the mobilization of existing ones through bacterial populations in the environment, animals, and humans. This integrated web of resistance elements is genetically complex and mechanistically diverse. Addressing this mode of bacterial survival requires innovation and investment to ensure continued use of antibiotics in the future. Strategies ranging from developing new therapies to applying artificial intelligence in monitoring AMR and discovering new drugs are being applied to manage the growing AMR crisis.
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Affiliation(s)
- Amna Abbas
- David Braley Center for Antibiotic Discovery, Michael G. DeGroote Institute for Infectious Disease Research, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Alexandra Barkhouse
- David Braley Center for Antibiotic Discovery, Michael G. DeGroote Institute for Infectious Disease Research, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Dirk Hackenberger
- David Braley Center for Antibiotic Discovery, Michael G. DeGroote Institute for Infectious Disease Research, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Gerard D Wright
- David Braley Center for Antibiotic Discovery, Michael G. DeGroote Institute for Infectious Disease Research, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada.
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Root-Bernstein RS, Bernstein MI. 'Evolutionary poker': an agent-based model of interactome emergence and epistasis tested against Lenski's long-term E. coli experiments. J Physiol 2024; 602:2511-2535. [PMID: 37707489 DOI: 10.1113/jp284421] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 08/23/2023] [Indexed: 09/15/2023] Open
Abstract
A simple agent-based model is presented that produces results matching the experimental data found by Lenski's group for ≤50,000 generations of Escherichia coli bacteria under continuous selective pressure. Although various mathematical models have been devised previously to model the Lenski data, the present model has advantages in terms of overall simplicity and conceptual accessibility. The model also clearly illustrates a number of features of the evolutionary process that are otherwise not obvious, such as the roles of epistasis and historical contingency in adaptation and why evolution is time irreversible ('Dollo's law'). The reason for this irreversibility is that genomes become increasingly integrated or organized, and this organization becomes a novel selective factor itself, against which future generations must compete. Selection for integrated or synergistic networks, systems or sets of mutations or traits, not for individual mutations, confers the main adaptive advantage. The result is a punctuated form of evolution that follows a logarithmic occurrence probability, in which evolution proceeds very quickly when interactomes begin to form but which slows as interactomes become more robust and the difficulty of integrating new mutations increases. Sufficient parameters exist in the game to suggest not only how equilibrium or stasis is reached but also the conditions in which it will be punctuated, the factors governing the rate at which genomic organization occurs and novel traits appear, and how population size, genome size and gene variability affect these.
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Affiliation(s)
| | - Morton I Bernstein
- Department of Physiology, Michigan State University, East Lansing, MI, USA
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6
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Crozier D, Gray JM, Maltas JA, Bonomo RA, Burke ZDC, Card KJ, Scott JG. The evolution of diverse antimicrobial responses in vancomycin-intermediate Staphylococcus aureus and its therapeutic implications. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.30.569373. [PMID: 38077036 PMCID: PMC10705500 DOI: 10.1101/2023.11.30.569373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2023]
Abstract
Staphylococcus aureus causes endocarditis, osteomyelitis, and bacteremia. Clinicians often prescribe vancomycin as an empiric therapy to account for methicillin-resistant S. aureus (MRSA) and narrow treatment based on culture susceptibility results. However, these results reflect a single time point before empiric treatment and represent a limited subset of the total bacterial population within the patient. Thus, while they may indicate that the infection is susceptible to a particular drug, this recommendation may no longer be accurate during therapy. Here, we addressed how antibiotic susceptibility changes over time by accounting for evolution. We evolved 18 methicillin-susceptible S. aureus (MSSA) populations under increasing vancomycin concentrations until they reached intermediate resistance levels. Sequencing revealed parallel mutations that affect cell membrane stress response and cell-wall biosynthesis. The populations exhibited repeated cross-resistance to daptomycin and varied responses to meropenem, gentamicin, and nafcillin. We accounted for this variability by deriving likelihood estimates that express a population's probability of exhibiting a drug response following vancomycin treatment. Our results suggest antistaphylococcal penicillins are preferable first-line treatments for MSSA infections but also highlight the inherent uncertainty that evolution poses to effective therapies. Infections may take varied evolutionary paths; therefore, considering evolution as a probabilistic process should inform our therapeutic choices.
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7
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Mangalam M, Sadri A, Hayano J, Watanabe E, Kiyono K, Kelty-Stephen DG. Multifractal foundations of biomarker discovery for heart disease and stroke. Sci Rep 2023; 13:18316. [PMID: 37880302 PMCID: PMC10600152 DOI: 10.1038/s41598-023-45184-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 10/17/2023] [Indexed: 10/27/2023] Open
Abstract
Any reliable biomarker has to be specific, generalizable, and reproducible across individuals and contexts. The exact values of such a biomarker must represent similar health states in different individuals and at different times within the same individual to result in the minimum possible false-positive and false-negative rates. The application of standard cut-off points and risk scores across populations hinges upon the assumption of such generalizability. Such generalizability, in turn, hinges upon this condition that the phenomenon investigated by current statistical methods is ergodic, i.e., its statistical measures converge over individuals and time within the finite limit of observations. However, emerging evidence indicates that biological processes abound with nonergodicity, threatening this generalizability. Here, we present a solution for how to make generalizable inferences by deriving ergodic descriptions of nonergodic phenomena. For this aim, we proposed capturing the origin of ergodicity-breaking in many biological processes: cascade dynamics. To assess our hypotheses, we embraced the challenge of identifying reliable biomarkers for heart disease and stroke, which, despite being the leading cause of death worldwide and decades of research, lacks reliable biomarkers and risk stratification tools. We showed that raw R-R interval data and its common descriptors based on mean and variance are nonergodic and non-specific. On the other hand, the cascade-dynamical descriptors, the Hurst exponent encoding linear temporal correlations, and multifractal nonlinearity encoding nonlinear interactions across scales described the nonergodic heart rate variability more ergodically and were specific. This study inaugurates applying the critical concept of ergodicity in discovering and applying digital biomarkers of health and disease.
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Affiliation(s)
- Madhur Mangalam
- Division of Biomechanics and Research Development, Department of Biomechanics, and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, NE, 68182, USA.
| | - Arash Sadri
- Lyceum Scientific Charity, Tehran, Iran
- Interdisciplinary Neuroscience Research Program, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, P94V+8MF, Iran
| | - Junichiro Hayano
- Graduate School of Medicine, Nagoya City University, Nagoya, Aichi, 467-8601, Japan
| | - Eiichi Watanabe
- Division of Cardiology, Department of Internal Medicine, Fujita Health University Bantane Hospital, Nagoya, Aichi, 454-0012, Japan
| | - Ken Kiyono
- Graduate School of Engineering Science, Osaka University, Osaka, 560-8531, Japan
| | - Damian G Kelty-Stephen
- Department of Psychology, State University of New York at New Paltz, New Paltz, NY, 12561, USA
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8
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Johnson K, Delaney JC, Guillard T, Reffuveille F, Varin-Simon J, Li K, Wollacott A, Frapy E, Mong S, Tissire H, Viswanathan K, Touti F, Babcock GJ, Shriver Z, Pentelute BL, Plante O, Skurnik D. Development of an antibody fused with an antimicrobial peptide targeting Pseudomonas aeruginosa: A new approach to prevent and treat bacterial infections. PLoS Pathog 2023; 19:e1011612. [PMID: 37676873 PMCID: PMC10508631 DOI: 10.1371/journal.ppat.1011612] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 09/19/2023] [Accepted: 08/12/2023] [Indexed: 09/09/2023] Open
Abstract
The increase in emerging drug resistant Gram-negative bacterial infections is a global concern. In addition, there is growing recognition that compromising the microbiota through the use of broad-spectrum antibiotics can impact long term patient outcomes. Therefore, there is the need to develop new bactericidal strategies to combat Gram-negative infections that would address these specific issues. In this study, we report and characterize one such approach, an antibody-drug conjugate (ADC) that combines (i) targeting the surface of a specific pathogenic organism through a monoclonal antibody with (ii) the high killing activity of an antimicrobial peptide. We focused on a major pathogenic Gram-negative bacterium associated with antibacterial resistance: Pseudomonas aeruginosa. To target this organism, we designed an ADC by fusing an antimicrobial peptide to the C-terminal end of the VH and/or VL-chain of a monoclonal antibody, VSX, that targets the core of P. aeruginosa lipopolysaccharide. This ADC demonstrates appropriately minimal levels of toxicity against mammalian cells, rapidly kills P. aeruginosa strains, and protects mice from P. aeruginosa lung infection when administered therapeutically. Furthermore, we found that the ADC was synergistic with several classes of antibiotics. This approach described in this study might result in a broadly useful strategy for targeting specific pathogenic microorganisms without further augmenting antibiotic resistance.
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Affiliation(s)
- Kenneth Johnson
- Visterra, Inc., Waltham, Massachusetts, United States of America
| | - James C. Delaney
- Visterra, Inc., Waltham, Massachusetts, United States of America
| | - Thomas Guillard
- Inserm UMR-S 1250 P3 Cell, Université de Reims-Champagne-Ardenne, Reims, France
| | - Fany Reffuveille
- Inserm UMR-S 1250 P3 Cell, Université de Reims-Champagne-Ardenne, Reims, France
| | | | - Kai Li
- Visterra, Inc., Waltham, Massachusetts, United States of America
| | - Andrew Wollacott
- Visterra, Inc., Waltham, Massachusetts, United States of America
| | - Eric Frapy
- CNRS, INSERM, Institut Necker Enfants Malades-INEM, F-75015 Paris, France; Faculté de Médecine, University of Paris City, Paris, France
| | - Surin Mong
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Hamid Tissire
- Visterra, Inc., Waltham, Massachusetts, United States of America
| | | | - Faycal Touti
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | | | - Zachary Shriver
- Visterra, Inc., Waltham, Massachusetts, United States of America
| | - Bradley L. Pentelute
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Obadiah Plante
- Visterra, Inc., Waltham, Massachusetts, United States of America
| | - David Skurnik
- CNRS, INSERM, Institut Necker Enfants Malades-INEM, F-75015 Paris, France; Faculté de Médecine, University of Paris City, Paris, France
- Department of Clinical Microbiology, Fédération Hospitalo-Universitaire Prématurité (FHU PREMA), Necker-Enfants Malades University Hospital, Assistance Publique-Hôpitaux de Paris, University of Paris City, Paris, France
- Division of Infectious Diseases, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
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9
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Lenski RE. Revisiting the Design of the Long-Term Evolution Experiment with Escherichia coli. J Mol Evol 2023; 91:241-253. [PMID: 36790511 DOI: 10.1007/s00239-023-10095-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 01/20/2023] [Indexed: 02/16/2023]
Abstract
The long-term evolution experiment (LTEE) with Escherichia coli began in 1988 and it continues to this day, with its 12 populations having recently reached 75,000 generations of evolution in a simple, well-controlled environment. The LTEE was designed to explore open-ended questions about the dynamics and repeatability of phenotypic and genetic evolution. Here I discuss various aspects of the LTEE's experimental design that have enabled its stability and success, including the choices of the culture regime, growth medium, ancestral strain, and statistical replication. I also discuss some of the challenges associated with a long-running project, such as handling procedural errors (e.g., cross-contamination) and managing the expanding collection of frozen samples. The simplicity of the experimental design and procedures have supported the long-term stability of the LTEE. That stability-along with the inherent creativity of the evolutionary process and the emergence of new genomic technologies-provides a platform that has allowed talented students and collaborators to pose questions, collect data, and make discoveries that go far beyond anything I could have imagined at the start of the LTEE.
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Affiliation(s)
- Richard E Lenski
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, 48824, USA.
- Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, MI, 48824, USA.
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10
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Vittadello ST, Stumpf MPH. Open problems in mathematical biology. Math Biosci 2022; 354:108926. [PMID: 36377100 DOI: 10.1016/j.mbs.2022.108926] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 10/21/2022] [Accepted: 10/21/2022] [Indexed: 11/06/2022]
Abstract
Biology is data-rich, and it is equally rich in concepts and hypotheses. Part of trying to understand biological processes and systems is therefore to confront our ideas and hypotheses with data using statistical methods to determine the extent to which our hypotheses agree with reality. But doing so in a systematic way is becoming increasingly challenging as our hypotheses become more detailed, and our data becomes more complex. Mathematical methods are therefore gaining in importance across the life- and biomedical sciences. Mathematical models allow us to test our understanding, make testable predictions about future behaviour, and gain insights into how we can control the behaviour of biological systems. It has been argued that mathematical methods can be of great benefit to biologists to make sense of data. But mathematics and mathematicians are set to benefit equally from considering the often bewildering complexity inherent to living systems. Here we present a small selection of open problems and challenges in mathematical biology. We have chosen these open problems because they are of both biological and mathematical interest.
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Affiliation(s)
- Sean T Vittadello
- Melbourne Integrative Genomics, University of Melbourne, Australia; School of BioSciences, University of Melbourne, Australia
| | - Michael P H Stumpf
- Melbourne Integrative Genomics, University of Melbourne, Australia; School of BioSciences, University of Melbourne, Australia; School of Mathematics and Statistics, University of Melbourne, Australia.
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11
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Smith CE, Smith ANH, Cooper TF, Moore FBG. Fitness of evolving bacterial populations is contingent on deep and shallow history but only shallow history creates predictable patterns. Proc Biol Sci 2022; 289:20221292. [PMID: 36100026 PMCID: PMC9470251 DOI: 10.1098/rspb.2022.1292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Long-term evolution experiments have tested the importance of genetic and environmental factors in influencing evolutionary outcomes. Differences in phylogenetic history, recent adaptation to distinct environments and chance events, all influence the fitness of a population. However, the interplay of these factors on a population's evolutionary potential remains relatively unexplored. We tracked the outcome of 2000 generations of evolution of four natural isolates of Escherichia coli bacteria that were engineered to also create differences in shallow history by adding previously identified mutations selected in a separate long-term experiment. Replicate populations started from each progenitor evolved in four environments. We found that deep and shallow phylogenetic histories both contributed significantly to differences in evolved fitness, though by different amounts in different selection environments. With one exception, chance effects were not significant. Whereas the effect of deep history did not follow any detectable pattern, effects of shallow history followed a pattern of diminishing returns whereby fitter ancestors had smaller fitness increases. These results are consistent with adaptive evolution being contingent on the interaction of several evolutionary forces but demonstrate that the nature of these interactions is not fixed and may not be predictable even when the role of chance is small.
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Affiliation(s)
- Chelsea E Smith
- Department of Biological Sciences, Kent State University, Kent, OH 44242, USA
| | - Adam N H Smith
- School of Mathematical and Computational Sciences, Massey University, Auckland 0634, New Zealand
| | - Tim F Cooper
- School of Natural Sciences, Massey University, Auckland 0634, New Zealand
| | - Francisco B-G Moore
- Department of Biological Sciences, Kent State University, Kent, OH 44242, USA.,Department of Biology, University of Akron, Akron, OH 44325, USA
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12
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Cisneros-Mayoral S, Graña-Miraglia L, Pérez-Morales D, Peña-Miller R, Fuentes-Hernáandez A. Evolutionary history and strength of selection determine the rate of antibiotic resistance adaptation. Mol Biol Evol 2022; 39:6692293. [PMID: 36062982 PMCID: PMC9512152 DOI: 10.1093/molbev/msac185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Bacterial adaptation to stressful environments often produces evolutionary constraints whereby increases in resistance are associated with reduced fitness in a different environment. The exploitation of this resistance-cost trade-off has been proposed as the basis of rational antimicrobial treatment strategies designed to limit the evolution of drug resistance in bacterial pathogens. Recent theoretical, laboratory, and clinical studies have shown that fluctuating selection can maintain drug efficacy and even restore drug susceptibility, but can also increase the rate of adaptation and promote cross-resistance to other antibiotics. In this paper, we combine mathematical modeling, experimental evolution, and whole-genome sequencing to follow evolutionary trajectories towards β-lactam resistance under fluctuating selective conditions. Our experimental model system consists of eight populations of Escherichia coli K12 evolving in parallel to a serial dilution protocol designed to dynamically control the strength of selection for resistance. We implemented adaptive ramps with mild and strong selection, resulting in evolved populations with similar levels of resistance, but with different evolutionary dynamics and diverging genotypic profiles. We found that mutations that emerged under strong selection are unstable in the absence of selection, in contrast to resistance mutations previously selected in the mild selection regime that were stably maintained in drug-free environments and positively selected for when antibiotics were reintroduced. Altogether, our population dynamics model and the phenotypic and genomic analysis of the evolved populations show that the rate of resistance adaptation is contingent upon the strength of selection, but also on evolutionary constraints imposed by prior drug exposures.
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Affiliation(s)
- Sandra Cisneros-Mayoral
- Programa de Biología Sintética, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, 62210, Cuernavaca, Mexico
| | - Lucía Graña-Miraglia
- Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada
| | - Deyanira Pérez-Morales
- Programa de Biología de Sistemas, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de Méexico, 62210, Cuernavaca, Mexico
| | - Rafael Peña-Miller
- Programa de Biología de Sistemas, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, 62210, Cuernavaca, Mexico
| | - Ayari Fuentes-Hernáandez
- Programa de Biología Sintética, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de Méexico, 62210, Cuernavaca, Mexico
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13
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Jangir PK, Yang Q, Shaw LP, Caballero JD, Ogunlana L, Wheatley R, Walsh T, MacLean RC. Pre-existing chromosomal polymorphisms in pathogenic E. coli potentiate the evolution of resistance to a last-resort antibiotic. eLife 2022; 11:78834. [PMID: 35943060 PMCID: PMC9363117 DOI: 10.7554/elife.78834] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 07/22/2022] [Indexed: 12/17/2022] Open
Abstract
Bacterial pathogens show high levels of chromosomal genetic diversity, but the influence of this diversity on the evolution of antibiotic resistance by plasmid acquisition remains unclear. Here, we address this problem in the context of colistin, a 'last line of defence' antibiotic. Using experimental evolution, we show that a plasmid carrying the MCR-1 colistin resistance gene dramatically increases the ability of Escherichia coli to evolve high-level colistin resistance by acquiring mutations in lpxC, an essential chromosomal gene involved in lipopolysaccharide biosynthesis. Crucially, lpxC mutations increase colistin resistance in the presence of the MCR-1 gene, but decrease the resistance of wild-type cells, revealing positive sign epistasis for antibiotic resistance between the chromosomal mutations and a mobile resistance gene. Analysis of public genomic datasets shows that lpxC polymorphisms are common in pathogenic E. coli, including those carrying MCR-1, highlighting the clinical relevance of this interaction. Importantly, lpxC diversity is high in pathogenic E. coli from regions with no history of MCR-1 acquisition, suggesting that pre-existing lpxC polymorphisms potentiated the evolution of high-level colistin resistance by MCR-1 acquisition. More broadly, these findings highlight the importance of standing genetic variation and plasmid/chromosomal interactions in the evolutionary dynamics of antibiotic resistance.
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Affiliation(s)
- Pramod K Jangir
- Department of Zoology, University of OxfordOxfordUnited Kingdom
| | - Qiue Yang
- Fujian Provincial Key Laboratory of Soil Environmental Health and Regulation, College of Resources and Environment, Fujian Agriculture and Forestry UniversityFuzhouChina
| | - Liam P Shaw
- Department of Zoology, University of OxfordOxfordUnited Kingdom
| | | | - Lois Ogunlana
- Department of Zoology, University of OxfordOxfordUnited Kingdom
| | - Rachel Wheatley
- Department of Zoology, University of OxfordOxfordUnited Kingdom
| | - Timothy Walsh
- Department of Zoology, University of OxfordOxfordUnited Kingdom
| | - R Craig MacLean
- Department of Zoology, University of OxfordOxfordUnited Kingdom
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14
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Jagdish T, Nguyen Ba AN. Microbial experimental evolution in a massively multiplexed and high-throughput era. Curr Opin Genet Dev 2022; 75:101943. [PMID: 35752001 DOI: 10.1016/j.gde.2022.101943] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/11/2022] [Accepted: 05/17/2022] [Indexed: 11/25/2022]
Abstract
Experimental evolution with microbial model systems has transformed our understanding of the basic rules underlying ecology and evolution. Experiments leveraging evolution as a central feature put evolutionary theories to the test, and modern sequencing and engineering tools then characterized the molecular basis of adaptation. As theory and experimentations refined our understanding of evolution, a need to increase throughput and experimental complexity has emerged. Here, we summarize recent technologies that have made high-throughput experiments practical and highlight studies that have capitalized on these tools, defining an exciting new era in microbial experimental evolution. Multiple research directions previously limited by experimental scale are now accessible for study and we believe applying evolutionary lessons from in vitro studies onto these applied settings has the potential for major innovations and discoveries across ecology and medicine.
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Affiliation(s)
- Tanush Jagdish
- Department of Molecular and Cellular Biology and The Program for Systems Synthetic and Quantitative Biology, Harvard University, Cambridge, United States.
| | - Alex N Nguyen Ba
- Department of Biology, University of Toronto at Mississauga, Mississauga, Canada; Department of Cell and Systems Biology, University of Toronto, Toronto, Canada.
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15
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Rojas LJ, Yasmin M, Benjamino J, Marshall SM, DeRonde KJ, Krishnan NP, Perez F, Colin AA, Cardenas M, Martinez O, Pérez-Cardona A, Rhoads DD, Jacobs MR, LiPuma JJ, Konstan MW, Vila AJ, Smania A, Mack AR, Scott JG, Adams MD, Abbo LM, Bonomo RA. Genomic heterogeneity underlies multidrug resistance in Pseudomonas aeruginosa: A population-level analysis beyond susceptibility testing. PLoS One 2022; 17:e0265129. [PMID: 35358221 PMCID: PMC8970513 DOI: 10.1371/journal.pone.0265129] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 02/23/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Pseudomonas aeruginosa is a persistent and difficult-to-treat pathogen in many patients, especially those with Cystic Fibrosis (CF). Herein, we describe a longitudinal analysis of a series of multidrug resistant (MDR) P. aeruginosa isolates recovered in a 17-month period, from a young female CF patient who underwent double lung transplantation. Our goal was to understand the genetic basis of the observed resistance phenotypes, establish the genomic population diversity, and define the nature of sequence evolution over time. METHODS Twenty-two sequential P. aeruginosa isolates were obtained within a 17-month period, before and after a double-lung transplant. At the end of the study period, antimicrobial susceptibility testing, whole genome sequencing (WGS), phylogenetic analyses and RNAseq were performed in order to understand the genetic basis of the observed resistance phenotypes, establish the genomic population diversity, and define the nature of sequence changes over time. RESULTS The majority of isolates were resistant to almost all tested antibiotics. A phylogenetic reconstruction revealed 3 major clades representing a genotypically and phenotypically heterogeneous population. The pattern of mutation accumulation and variation of gene expression suggested that a group of closely related strains was present in the patient prior to transplantation and continued to change throughout the course of treatment. A trend toward accumulation of mutations over time was observed. Different mutations in the DNA mismatch repair gene mutL consistent with a hypermutator phenotype were observed in two clades. RNAseq performed on 12 representative isolates revealed substantial differences in the expression of genes associated with antibiotic resistance and virulence traits. CONCLUSIONS The overwhelming current practice in the clinical laboratories setting relies on obtaining a pure culture and reporting the antibiogram from a few isolated colonies to inform therapy decisions. Our analyses revealed significant underlying genomic heterogeneity and unpredictable evolutionary patterns that were independent of prior antibiotic treatment, highlighting the need for comprehensive sampling and population-level analysis when gathering microbiological data in the context of CF P. aeruginosa chronic infection. Our findings challenge the applicability of antimicrobial stewardship programs based on single-isolate resistance profiles for the selection of antibiotic regimens in chronic infections such as CF.
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Affiliation(s)
- Laura J. Rojas
- Department of Molecular Biology and Microbiology, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
- Research Service, Louis Stokes Veterans Affairs Medical Center, Cleveland, Ohio, United States of America
- CWRU-Cleveland VAMC Center for Antimicrobial Resistance and Epidemiology (Case VA CARES), Cleveland, Ohio, United States of America
| | - Mohamad Yasmin
- Research Service, Louis Stokes Veterans Affairs Medical Center, Cleveland, Ohio, United States of America
| | - Jacquelynn Benjamino
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America
| | - Steven M. Marshall
- Research Service, Louis Stokes Veterans Affairs Medical Center, Cleveland, Ohio, United States of America
| | - Kailynn J. DeRonde
- Jackson Memorial Hospital, Jackson Health System, Miami, Florida, United States of America
| | - Nikhil P. Krishnan
- Center for Proteomics and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
- Departments of Translational Hematology and Oncology Research and Radiation Oncology, Cleveland Clinic, Cleveland, Ohio, United States of America
| | - Federico Perez
- Medical Service, Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio, United States of America
- CONICET, Centro de Investigaciones en Química Biológica de Córdoba (CIQUIBIC), Córdoba, Argentina
- Division of Infectious Diseases and HIV Medicine, Cleveland, Ohio, United States of America
- GRECC Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, Ohio, United States of America
| | - Andrew A. Colin
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, Florida, United States of America
| | - Monica Cardenas
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, Florida, United States of America
| | - Octavio Martinez
- Jackson Memorial Hospital, Jackson Health System, Miami, Florida, United States of America
- Division of Pulmonology, Department of Pathology University of Miami Miller School of Medicine, Miami, Florida, United States of America
| | - Armando Pérez-Cardona
- Jackson Memorial Hospital, Jackson Health System, Miami, Florida, United States of America
| | - Daniel D. Rhoads
- Department of Laboratory Medicine and Infection Biology Program, Cleveland Clinic, Cleveland, Ohio, United States of America
- Department of Pathology, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University Cleveland, Ohio, United States of America
| | - Michael R. Jacobs
- Department of Pathology, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University Cleveland, Ohio, United States of America
| | - John J. LiPuma
- Division of Pediatric Infectious Diseases, Department of Pediatrics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Michael W. Konstan
- Department of Pediatrics, Case Western Reserve University School of Medicine and Rainbow Babies and Children’s Hospital, Cleveland, Ohio, United States of America
| | - Alejandro J. Vila
- Instituto de Biología Molecular y Celular de Rosario (IBR, CONICET-UNR), Rosario, Argentina
| | - Andrea Smania
- CONICET, Centro de Investigaciones en Química Biológica de Córdoba (CIQUIBIC), Córdoba, Argentina
- Universidad Nacional de Córdoba, Facultad de Ciencias Químicas, Departamento de Química Biológica, Córdoba, Argentina
| | - Andrew R. Mack
- Department of Molecular Biology and Microbiology, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
- Research Service, Louis Stokes Veterans Affairs Medical Center, Cleveland, Ohio, United States of America
| | - Jacob G. Scott
- Center for Proteomics and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
- Departments of Translational Hematology and Oncology Research and Radiation Oncology, Cleveland Clinic, Cleveland, Ohio, United States of America
| | - Mark D. Adams
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America
| | - Lilian M. Abbo
- Jackson Memorial Hospital, Jackson Health System, Miami, Florida, United States of America
- Division of Infectious Diseases Department of Medicine University of Miami Miller School of Medicine, Miami, Florida, United States of America
| | - Robert A. Bonomo
- Department of Molecular Biology and Microbiology, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
- Research Service, Louis Stokes Veterans Affairs Medical Center, Cleveland, Ohio, United States of America
- CWRU-Cleveland VAMC Center for Antimicrobial Resistance and Epidemiology (Case VA CARES), Cleveland, Ohio, United States of America
- Center for Proteomics and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
- Medical Service, Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio, United States of America
- Division of Infectious Diseases and HIV Medicine, Cleveland, Ohio, United States of America
- GRECC Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, Ohio, United States of America
- Department of Pharmacology, Cleveland, Ohio, United States of America
- Department of Biochemistry Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
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16
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Jordan JA, Lenski RE, Card KJ. Idiosyncratic Fitness Costs of Ampicillin-Resistant Mutants Derived from a Long-Term Experiment with Escherichia coli. Antibiotics (Basel) 2022; 11:antibiotics11030347. [PMID: 35326810 PMCID: PMC8944548 DOI: 10.3390/antibiotics11030347] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 02/28/2022] [Accepted: 03/03/2022] [Indexed: 02/04/2023] Open
Abstract
Antibiotic resistance is a growing concern that has prompted a renewed focus on drug discovery, stewardship, and evolutionary studies of the patterns and processes that underlie this phenomenon. A resistant strain’s competitive fitness relative to its sensitive counterparts in the absence of drug can impact its spread and persistence in both clinical and community settings. In a prior study, we examined the fitness of tetracycline-resistant clones that evolved from five different Escherichia coli genotypes, which had diverged during a long-term evolution experiment. In this study, we build on that work to examine whether ampicillin-resistant mutants are also less fit in the absence of the drug than their sensitive parents, and whether the cost of resistance is constant or variable among independently derived lines. Like the tetracycline-resistant lines, the ampicillin-resistant mutants were often less fit than their sensitive parents, with significant variation in the fitness costs among the mutants. This variation was not associated with the level of resistance conferred by the mutations, nor did it vary across the different parental backgrounds. In our earlier study, some of the variation in fitness costs associated with tetracycline resistance was explained by the effects of different mutations affecting the same cellular pathway and even the same gene. In contrast, the variance among the ampicillin-resistant mutants was associated with different sets of target genes. About half of the resistant clones suffered large fitness deficits, and their mutations impacted major outer-membrane proteins or subunits of RNA polymerases. The other mutants experienced little or no fitness costs and with, one exception, they had mutations affecting other genes and functions. Our findings underscore the importance of comparative studies on the evolution of antibiotic resistance, and they highlight the nuanced processes that shape these phenotypes.
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Affiliation(s)
- Jalin A. Jordan
- Department of Chemistry, Michigan State University, East Lansing, MI 48824, USA;
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Richard E. Lenski
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA;
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824, USA
| | - Kyle J. Card
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824, USA
- Department of Translational Hematology and Oncology Research, Cleveland Clinic Lerner Research Institute, Cleveland, OH 44106, USA
- Correspondence:
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17
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Rayner JG, Sturiale SL, Bailey NW. The persistence and evolutionary consequences of vestigial behaviours. Biol Rev Camb Philos Soc 2022; 97:1389-1407. [PMID: 35218283 PMCID: PMC9540461 DOI: 10.1111/brv.12847] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 02/16/2022] [Accepted: 02/18/2022] [Indexed: 12/23/2022]
Abstract
Behavioural traits are often noted to persist after relaxation or removal of associated selection pressure, whereas it has been observed that morphological traits under similar conditions appear to decay more rapidly. Despite this, persistent non‐adaptive, ‘vestigial’ behavioural variation has received little research scrutiny. Here we review published examples of vestigial behavioural traits, highlighting their surprising prevalence, and argue that their further study can reveal insights about the widely debated role of behaviour in evolution. Some vestigial behaviours incur fitness costs, so may act as a drag on adaptive evolution when that adaptation occurs via trait loss or reversal. In other cases, vestigial behaviours can contribute to future evolutionary trajectories, for example by preserving genetic and phenotypic variation which is later co‐opted by selection during adaptive evolution or diversification, or through re‐emergence after ancestral selection pressures are restored. We explore why vestigial behaviours appear prone to persistence. Behavioural lag may be a general phenomenon arising from relatively high levels of non‐genetic variation in behavioural expression, and pleiotropic constraint. Long‐term persistence of non‐adaptive behavioural traits could also result when their expression is associated with morphological features which might be more rapidly lost or reduced. We propose that vestigial behaviours could provide a substrate for co‐option by novel selective forces, and advocate further study of the fate of behavioural traits following relaxed and reversed selection. Vestigial behaviours have been relatively well studied in the context of antipredator behaviours, but they are far from restricted to this ecological context, and so deserve broader consideration. They also have practical importance, with mixed evidence, for example, as to whether predator/parasite‐avoidance behaviours are rapidly lost in wildlife refuges and captivity. We identify important areas for future research to help determine whether vestigial behaviours essentially represent a form of evolutionary lag, or whether they have more meaningful evolutionary consequences distinct from those of other vestigial and behavioural traits.
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Affiliation(s)
- Jack G Rayner
- Centre for Biological Diversity, Harold Mitchell Building, University of St Andrews, St Andrews, KY16 9TH, U.K
| | - Samantha L Sturiale
- Centre for Biological Diversity, Harold Mitchell Building, University of St Andrews, St Andrews, KY16 9TH, U.K
| | - Nathan W Bailey
- Centre for Biological Diversity, Harold Mitchell Building, University of St Andrews, St Andrews, KY16 9TH, U.K
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18
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Durmaz A, Scott JG. Stability of scRNA-Seq Analysis Workflows is Susceptible to Preprocessing and is Mitigated by Regularized or Supervised Approaches. Evol Bioinform Online 2022; 18:11769343221123050. [PMID: 36199555 PMCID: PMC9527995 DOI: 10.1177/11769343221123050] [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: 03/13/2022] [Accepted: 07/18/2022] [Indexed: 11/04/2022] Open
Abstract
Background: Statistical methods developed to address various questions in single-cell datasets show increased variability to different parameter regimes. In order to delineate further the robustness of commonly utilized methods for single-cell RNA-Seq, we aimed to comprehensively review scRNA-Seq analysis workflows in the setting of dimension reduction, clustering, and trajectory inference. Methods: We utilized datasets with temporal single-cell transcriptomics profiles from public repositories. Combining multiple methods at each level of the workflow, we have performed over 6 k analysis and evaluated the results of clustering and pseudotime estimation using adjusted rand index and rank correlation metrics. We have further integrated neural network methods to assess whether models with increased complexity can show increased bias/variance trade-off. Results: Combinatorial workflows showed that utilizing non-linear dimension reduction techniques such as t-SNE and UMAP are sensitive to initial preprocessing steps hence clustering results on dimension reduced space of single-cell datasets should be utilized carefully. Similarly, pseudotime estimation methods that depend on previous non-linear dimension reduction steps can result in highly variable trajectories. In contrast, methods that avoid non-linearity such as WOT can result in repeatable inferences of temporal gene expression dynamics. Furthermore, imputation methods do not improve clustering or trajectory inference results substantially in terms of repeatability. In contrast, the selection of the normalization method shows an increased effect on downstream analysis where ScTransform reduces variability overall.
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Affiliation(s)
- Arda Durmaz
- Department of Translational Hematology and Oncology Research, Cleveland Clinic, Cleveland, OH, USA
- Systems Biology and Bioinformatics Graduate Program, Case Western Reserve University, Cleveland, OH, USA
| | - Jacob G Scott
- Department of Translational Hematology and Oncology Research, Cleveland Clinic, Cleveland, OH, USA
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19
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Lewis JA, Morran LT. Advantages of laboratory natural selection in the applied sciences. J Evol Biol 2021; 35:5-22. [PMID: 34826161 DOI: 10.1111/jeb.13964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 11/22/2021] [Accepted: 11/23/2021] [Indexed: 11/29/2022]
Abstract
In the past three decades, laboratory natural selection has become a widely used technique in biological research. Most studies which have utilized this technique are in the realm of basic science, often testing hypotheses related to mechanisms of evolutionary change or ecological dynamics. While laboratory natural selection is currently utilized heavily in this setting, there is a significant gap with its usage in applied studies, especially when compared to the other selection experiment methodologies like artificial selection and directed evolution. This is despite avenues of research in the applied sciences which seem well suited to laboratory natural selection. In this review, we place laboratory natural selection in context with other selection experiments, identify the characteristics which make it well suited for particular kinds of applied research and briefly cover key examples of the usefulness of selection experiments within applied science. Finally, we identify three promising areas of inquiry for laboratory natural selection in the applied sciences: bioremediation technology, identifying mechanisms of drug resistance and optimizing biofuel production. Although laboratory natural selection is currently less utilized in applied science when compared to basic research, the method has immense promise in the field moving forward.
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Affiliation(s)
- Jordan A Lewis
- Population Biology, Ecology, and Evolution Graduate Program, Emory University, Atlanta, Georgia, USA
| | - Levi T Morran
- Population Biology, Ecology, and Evolution Graduate Program, Emory University, Atlanta, Georgia, USA.,Department of Biology, Emory University, Atlanta, Georgia, USA
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20
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Abstract
Aging has provided fruitful challenges for evolutionary theory, and evolutionary theory has deepened our understanding of aging. A great deal of genetic and molecular data now exists concerning mortality regulation and there is a growing body of knowledge concerning the life histories of diverse species. Assimilating all relevant data into a framework for the evolution of aging promises to significantly advance the field. We propose extensions of some key concepts to provide greater precision when applying these concepts to age-structured contexts. Secondary or byproduct effects of mutations are proposed as an important factor affecting survival patterns, including effects that may operate in small populations subject to genetic drift, widening the possibilities for mutation accumulation and pleiotropy. Molecular and genetic studies have indicated a diverse array of mechanisms that can modify aging and mortality rates, while transcriptome data indicate a high level of tissue and species specificity for genes affected by aging. The diversity of mechanisms and gene effects that can contribute to the pattern of aging in different organisms may mirror the complex evolutionary processes behind aging.
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Affiliation(s)
- Stewart Frankel
- Biology Department, University of Hartford, West Hartford, CT, United States
| | - Blanka Rogina
- Genetics and Genome Sciences, Institute for Systems Genomics, School of Medicine, University of Connecticut Health Center, Farmington, CT, United States
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21
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Abstract
Rapidly switching between similar antibiotics may help to slow down the evolution of resistance.
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Affiliation(s)
- Anh Huynh
- Department of Biophysics, University of Michigan, Ann Arbor, United States
| | - Kevin B Wood
- Department of Biophysics, University of Michigan, Ann Arbor, United States.,Department of Physics, University of Michigan, Ann Arbor, United States
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22
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Santos-Lopez A, Marshall CW, Haas AL, Turner C, Rasero J, Cooper VS. The roles of history, chance, and natural selection in the evolution of antibiotic resistance. eLife 2021; 10:e70676. [PMID: 34431477 PMCID: PMC8412936 DOI: 10.7554/elife.70676] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 08/24/2021] [Indexed: 12/20/2022] Open
Abstract
History, chance, and selection are the fundamental factors that drive and constrain evolution. We designed evolution experiments to disentangle and quantify effects of these forces on the evolution of antibiotic resistance. Previously, we showed that selection of the pathogen Acinetobacter baumannii in both structured and unstructured environments containing the antibiotic ciprofloxacin produced distinct genotypes and phenotypes, with lower resistance in biofilms as well as collateral sensitivity to β-lactam drugs (Santos-Lopez et al., 2019). Here we study how this prior history influences subsequent evolution in new β-lactam antibiotics. Selection was imposed by increasing concentrations of ceftazidime and imipenem and chance differences arose as random mutations among replicate populations. The effects of history were reduced by increasingly strong selection in new drugs, but not erased, at times revealing important contingencies. A history of selection in structured environments constrained resistance to new drugs and led to frequent loss of resistance to the initial drug by genetic reversions and not compensatory mutations. This research demonstrates that despite strong selective pressures of antibiotics leading to genetic parallelism, history can etch potential vulnerabilities to orthogonal drugs.
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Affiliation(s)
- Alfonso Santos-Lopez
- Department of Microbiology and Molecular Genetics, School of Medicine, University of PittsburghPittsburghUnited States
| | - Christopher W Marshall
- Department of Microbiology and Molecular Genetics, School of Medicine, University of PittsburghPittsburghUnited States
| | - Allison L Haas
- Department of Microbiology and Molecular Genetics, School of Medicine, University of PittsburghPittsburghUnited States
| | - Caroline Turner
- Department of Microbiology and Molecular Genetics, School of Medicine, University of PittsburghPittsburghUnited States
| | - Javier Rasero
- Department of Psychology, Carnegie Mellon UniversityPittsburghUnited States
| | - Vaughn S Cooper
- Department of Microbiology and Molecular Genetics, School of Medicine, University of PittsburghPittsburghUnited States
- Center for Evolutionary Biology and Medicine, University of PittsburghPittsburghUnited States
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23
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Gjini E, Wood KB. Price equation captures the role of drug interactions and collateral effects in the evolution of multidrug resistance. eLife 2021; 10:e64851. [PMID: 34289932 PMCID: PMC8331190 DOI: 10.7554/elife.64851] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 07/08/2021] [Indexed: 01/03/2023] Open
Abstract
Bacterial adaptation to antibiotic combinations depends on the joint inhibitory effects of the two drugs (drug interaction [DI]) and how resistance to one drug impacts resistance to the other (collateral effects [CE]). Here we model these evolutionary dynamics on two-dimensional phenotype spaces that leverage scaling relations between the drug-response surfaces of drug-sensitive (ancestral) and drug-resistant (mutant) populations. We show that evolved resistance to the component drugs - and in turn, the adaptation of growth rate - is governed by a Price equation whose covariance terms encode geometric features of both the two-drug-response surface (DI) in ancestral cells and the correlations between resistance levels to those drugs (CE). Within this framework, mean evolutionary trajectories reduce to a type of weighted gradient dynamics, with the drug interaction dictating the shape of the underlying landscape and the collateral effects constraining the motion on those landscapes. We also demonstrate how constraints on available mutational pathways can be incorporated into the framework, adding a third key driver of evolution. Our results clarify the complex relationship between drug interactions and collateral effects in multidrug environments and illustrate how specific dosage combinations can shift the weighting of these two effects, leading to different and temporally explicit selective outcomes.
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Affiliation(s)
- Erida Gjini
- Center for Computational and Stochastic Mathematics, Instituto Superior Tecnico, University of Lisbon, PortugalLisbonPortugal
| | - Kevin B Wood
- Departments of Biophysics and Physics, University of MichiganAnn ArborUnited States
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24
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Genomic evolution of antibiotic resistance is contingent on genetic background following a long-term experiment with Escherichia coli. Proc Natl Acad Sci U S A 2021; 118:2016886118. [PMID: 33441451 DOI: 10.1073/pnas.2016886118] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Antibiotic resistance is a growing health concern. Efforts to control resistance would benefit from an improved ability to forecast when and how it will evolve. Epistatic interactions between mutations can promote divergent evolutionary trajectories, which complicates our ability to predict evolution. We recently showed that differences between genetic backgrounds can lead to idiosyncratic responses in the evolvability of phenotypic resistance, even among closely related Escherichia coli strains. In this study, we examined whether a strain's genetic background also influences the genotypic evolution of resistance. Do lineages founded by different genotypes take parallel or divergent mutational paths to achieve their evolved resistance states? We addressed this question by sequencing the complete genomes of antibiotic-resistant clones that evolved from several different genetic starting points during our earlier experiments. We first validated our statistical approach by quantifying the specificity of genomic evolution with respect to antibiotic treatment. As expected, mutations in particular genes were strongly associated with each drug. Then, we determined that replicate lines evolved from the same founding genotypes had more parallel mutations at the gene level than lines evolved from different founding genotypes, although these effects were more subtle than those showing antibiotic specificity. Taken together with our previous work, we conclude that historical contingency can alter both genotypic and phenotypic pathways to antibiotic resistance.
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25
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Card KJ, Jordan JA, Lenski RE. Idiosyncratic variation in the fitness costs of tetracycline-resistance mutations in Escherichia coli. Evolution 2021; 75:1230-1238. [PMID: 33634468 DOI: 10.1111/evo.14203] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 02/04/2021] [Accepted: 02/12/2021] [Indexed: 12/15/2022]
Abstract
A bacterium's fitness relative to its competitors, both in the presence and absence of antibiotics, plays a key role in its ecological success and clinical impact. In this study, we examine whether tetracycline-resistant mutants are less fit in the absence of the drug than their sensitive parents, and whether the fitness cost of resistance is constant or variable across independently derived lines. Tetracycline-resistant lines suffered, on average, a reduction in fitness of almost 8%. There was substantial among-line variation in the fitness cost. This variation was not associated with the level of resistance conferred by the mutations, nor did it vary significantly across several genetic backgrounds. The two resistant lines with the most extreme fitness costs involved functionally unrelated mutations on different genetic backgrounds. However, there was also significant variation in the fitness costs for mutations affecting the same pathway and even different alleles of the same gene. Our findings demonstrate that the fitness costs of antibiotic resistance do not always correlate with the phenotypic level of resistance or the underlying genetic changes. Instead, these costs reflect the idiosyncratic effects of particular resistance mutations and the genetic backgrounds in which they occur.
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Affiliation(s)
- Kyle J Card
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, 48824.,Program in Ecology, Evolution, and Behavior, Michigan State University, East Lansing, Michigan, 48824.,BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, 48824
| | - Jalin A Jordan
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, 48824.,Department of Chemistry, Michigan State University, East Lansing, Michigan, 48824
| | - Richard E Lenski
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, 48824.,Program in Ecology, Evolution, and Behavior, Michigan State University, East Lansing, Michigan, 48824.,BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, 48824
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Desjardins E, Kurtz J, Kranke N, Lindeza A, Richter SH. Beyond Standardization: Improving External Validity and Reproducibility in Experimental Evolution. Bioscience 2021. [DOI: 10.1093/biosci/biab008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Discussions of reproducibility are casting doubts on the credibility of experimental outcomes in the life sciences. Although experimental evolution is not typically included in these discussions, this field is also subject to low reproducibility, partly because of the inherent contingencies affecting the evolutionary process. A received view in experimental studies more generally is that standardization (i.e., rigorous homogenization of experimental conditions) is a solution to some issues of significance and internal validity. However, this solution hides several difficulties, including a reduction of external validity and reproducibility. After explaining the meaning of these two notions in the context of experimental evolution, we import from the fields of animal research and ecology and suggests that systematic heterogenization of experimental factors could prove a promising alternative. We also incorporate into our analysis some philosophical reflections on the nature and diversity of research objectives in experimental evolution.
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Affiliation(s)
- Eric Desjardins
- Rotman Institute of Philosophy, Department of Philosophy, University of Western Ontario, London, Ontario, Canada
| | | | | | | | - S Helene Richter
- RG Behavioural Biology and Animal Welfare, Institute of Neuro and Behavioural Biology all at the WWU, Münster, Germany
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27
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Identifying States of Collateral Sensitivity during the Evolution of Therapeutic Resistance in Ewing's Sarcoma. iScience 2020; 23:101293. [PMID: 32623338 PMCID: PMC7334607 DOI: 10.1016/j.isci.2020.101293] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 05/06/2020] [Accepted: 06/15/2020] [Indexed: 12/19/2022] Open
Abstract
Advances in the treatment of Ewing's sarcoma (EWS) are desperately needed, particularly in the case of metastatic disease. A deeper understanding of collateral sensitivity, where the evolution of therapeutic resistance to one drug aligns with sensitivity to another drug, may improve our ability to effectively target this disease. For the first time in a solid tumor, we produced a temporal collateral sensitivity map that demonstrates the evolution of collateral sensitivity and resistance in EWS. We found that the evolution of collateral resistance was predictable with some drugs but had significant variation in response to other drugs. Using this map of temporal collateral sensitivity in EWS, we can see that the path toward collateral sensitivity is not always repeatable, nor is there always a clear trajectory toward resistance or sensitivity. Identifying transcriptomic changes that accompany these states of transient collateral sensitivity could improve treatment planning for patients with EWS. Ewing's sarcoma cell lines were evolved to become resistant to standard chemotherapy A temporal collateral sensitivity map shows response to alternative drugs over time Collateral drug response is repeatable in some instances and stochastic in others Differential gene expression elucidates potential biomarkers of drug response
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28
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Highly parallel lab evolution reveals that epistasis can curb the evolution of antibiotic resistance. Nat Commun 2020; 11:3105. [PMID: 32561723 PMCID: PMC7305214 DOI: 10.1038/s41467-020-16932-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 06/01/2020] [Indexed: 12/12/2022] Open
Abstract
Genetic perturbations that affect bacterial resistance to antibiotics have been characterized genome-wide, but how do such perturbations interact with subsequent evolutionary adaptation to the drug? Here, we show that strong epistasis between resistance mutations and systematically identified genes can be exploited to control spontaneous resistance evolution. We evolved hundreds of Escherichia coli K-12 mutant populations in parallel, using a robotic platform that tightly controls population size and selection pressure. We find a global diminishing-returns epistasis pattern: strains that are initially more sensitive generally undergo larger resistance gains. However, some gene deletion strains deviate from this general trend and curtail the evolvability of resistance, including deletions of genes for membrane transport, LPS biosynthesis, and chaperones. Deletions of efflux pump genes force evolution on inferior mutational paths, not explored in the wild type, and some of these essentially block resistance evolution. This effect is due to strong negative epistasis with resistance mutations. The identified genes and cellular functions provide potential targets for development of adjuvants that may block spontaneous resistance evolution when combined with antibiotics. The antibiotic resistance crisis calls for new ways of restricting the ability of bacteria to evolve resistance. Here, Lukačišinová et al. perform highly controlled evolution experiments in E. coli strains to identify genetic perturbations that strongly limit the evolution of antibiotic resistance through epistasis.
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29
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Maltas J, Krasnick B, Wood KB. Using Selection by Nonantibiotic Stressors to Sensitize Bacteria to Antibiotics. Mol Biol Evol 2020; 37:1394-1406. [PMID: 31851309 PMCID: PMC7182213 DOI: 10.1093/molbev/msz303] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Evolutionary adaptation of bacteria to nonantibiotic selective forces, such as osmotic stress, has been previously associated with increased antibiotic resistance, but much less is known about potentially sensitizing effects of nonantibiotic stressors. In this study, we use laboratory evolution to investigate adaptation of Enterococcus faecalis, an opportunistic bacterial pathogen, to a broad collection of environmental agents, ranging from antibiotics and biocides to extreme pH and osmotic stress. We find that nonantibiotic selection frequently leads to increased sensitivity to other conditions, including multiple antibiotics. Using population sequencing and whole-genome sequencing of single isolates from the evolved populations, we identify multiple mutations in genes previously linked with resistance to the selecting conditions, including genes corresponding to known drug targets or multidrug efflux systems previously tied to collateral sensitivity. Finally, we hypothesized based on the measured sensitivity profiles that sequential rounds of antibiotic and nonantibiotic selection may lead to hypersensitive populations by harnessing the orthogonal collateral effects of particular pairs of selective forces. To test this hypothesis, we show experimentally that populations evolved to a sequence of linezolid (an oxazolidinone antibiotic) and sodium benzoate (a common preservative) exhibit increased sensitivity to more stressors than adaptation to either condition alone. The results demonstrate how sequential adaptation to drug and nondrug environments can be used to sensitize bacteria to antibiotics and highlight new potential strategies for exploiting shared constraints governing adaptation to diverse environmental challenges.
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Affiliation(s)
- Jeff Maltas
- Department of Biophysics, University of Michigan, Ann Arbor, MI
| | - Brian Krasnick
- Department of Biophysics, University of Michigan, Ann Arbor, MI
| | - Kevin B Wood
- Department of Biophysics, University of Michigan, Ann Arbor, MI
- Department of Physics, University of Michigan, Ann Arbor, MI
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30
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Card KJ, LaBar T, Gomez JB, Lenski RE. Historical contingency in the evolution of antibiotic resistance after decades of relaxed selection. PLoS Biol 2019; 17:e3000397. [PMID: 31644535 PMCID: PMC6827916 DOI: 10.1371/journal.pbio.3000397] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 11/04/2019] [Accepted: 10/10/2019] [Indexed: 12/21/2022] Open
Abstract
Populations often encounter changed environments that remove selection for the maintenance of particular phenotypic traits. The resulting genetic decay of those traits under relaxed selection reduces an organism's fitness in its prior environment. However, whether and how such decay alters the subsequent evolvability of a population upon restoration of selection for a previously diminished trait is not well understood. We addressed this question using Escherichia coli strains from the long-term evolution experiment (LTEE) that independently evolved for multiple decades in the absence of antibiotics. We first confirmed that these derived strains are typically more sensitive to various antibiotics than their common ancestor. We then subjected the ancestral and derived strains to various concentrations of these drugs to examine their potential to evolve increased resistance. We found that evolvability was idiosyncratic with respect to initial genotype; that is, the derived strains did not generally compensate for their greater susceptibility by "catching up" to the resistance level of the ancestor. Instead, the capacity to evolve increased resistance was constrained in some backgrounds, implying that evolvability depended upon prior mutations in a historically contingent fashion. We further subjected a time series of clones from one LTEE population to tetracycline and determined that an evolutionary constraint arose early in that population, corroborating the role of contingency. In summary, relaxed selection not only can drive populations to increased antibiotic susceptibility, but it can also affect the subsequent evolvability of antibiotic resistance in an unpredictable manner. This conclusion has potential implications for public health, and it underscores the need to consider the genetic context of pathogens when designing drug-treatment strategies.
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Affiliation(s)
- Kyle J. Card
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, United States of America
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, United States of America
- Program in Ecology, Evolutionary Biology, and Behavior, Michigan State University, East Lansing, Michigan, United States of America
| | - Thomas LaBar
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, United States of America
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Jasper B. Gomez
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, United States of America
- Biomedical Laboratory Diagnostics Program, Michigan State University, East Lansing, Michigan, United States of America
| | - Richard E. Lenski
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, United States of America
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, United States of America
- Program in Ecology, Evolutionary Biology, and Behavior, Michigan State University, East Lansing, Michigan, United States of America
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