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Hinz A, Amado A, Kassen R, Bank C, Wong A. Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli. Mol Biol Evol 2024; 41:msae086. [PMID: 38709811 PMCID: PMC11110942 DOI: 10.1093/molbev/msae086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 04/11/2024] [Accepted: 04/30/2024] [Indexed: 05/08/2024] Open
Abstract
The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern, and antibiotic restriction is often implemented to reduce the spread of resistance. These measures rely on the existence of deleterious fitness effects (i.e. costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. The fitness effects of AMR mutations are generally studied in laboratory reference strains grown in standard growth environments; however, the genetic and environmental context can influence the magnitude and direction of a mutation's fitness effects. In this study, we measure how three sources of variation impact the fitness effects of Escherichia coli AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji fitness landscape model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate the observed variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, which will ultimately impact their persistence in natural populations.
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Affiliation(s)
- Aaron Hinz
- Department of Biology, Carleton University, Ottawa, ON K1S 5B6, Canada
- Department of Biology, University of Ottawa, Ottawa, ON K1N 6N5, Canada
- Department of Biology, McGill University, Montreal, QC H3A 1B1, Canada
| | - André Amado
- Institute of Ecology and Evolution, University of Bern, Bern, Switzerland
- Division of Theoretical Ecology and Evolution, Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Evolutionary Dynamics Group, Gulbenkian Science Institute, Oeiras, Portugal
| | - Rees Kassen
- Department of Biology, University of Ottawa, Ottawa, ON K1N 6N5, Canada
- Department of Biology, McGill University, Montreal, QC H3A 1B1, Canada
| | - Claudia Bank
- Institute of Ecology and Evolution, University of Bern, Bern, Switzerland
- Division of Theoretical Ecology and Evolution, Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Evolutionary Dynamics Group, Gulbenkian Science Institute, Oeiras, Portugal
| | - Alex Wong
- Department of Biology, Carleton University, Ottawa, ON K1S 5B6, Canada
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2
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Zhang G, Sun X, Fleming J, Ran F, Luo J, Chen H, Ju H, Wang Z, Zhao H, Wang C, Zhang F, Dai X, Yang X, Li C, Liu Y, Wang Y, Zhang X, Jiang Y, Wu Z, Bi L, Zhang H. Genetic factors associated with acquired phenotypic drug resistance and its compensatory evolution during tuberculosis treatment. Clin Microbiol Infect 2024; 30:637-645. [PMID: 38286176 DOI: 10.1016/j.cmi.2024.01.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 01/15/2024] [Accepted: 01/22/2024] [Indexed: 01/31/2024]
Abstract
OBJECTIVES We elucidated the factors, evolution, and compensation of antimicrobial resistance (AMR) in Mycobacterium tuberculosis (MTB) isolates under dual pressure from the intra-host environment and anti-tuberculosis (anti-TB) drugs. METHODS This retrospective case-control study included 337 patients with pulmonary tuberculosis from 15 clinics in Tianjin, China, with phenotypic drug susceptibility testing results available for at least two time points between January 1, 2009 and December 31, 2016. Patients in the case group exhibited acquired AMR to isoniazid (INH) or rifampicin (RIF), while those in the control group lacked acquired AMR. The whole-genome sequencing (WGS) was conducted on 149 serial longitudinal MTB isolates from 46 patients who acquired or reversed phenotypic INH/RIF-resistance during treatment. The genetic basis, associated factors, and intra-host evolution of acquired phenotypic INH/RIF-resistance were elucidated using a combined analysis. RESULTS Anti-TB interruption duration of ≥30 days showed association with acquired phenotypic INH/RIF resistance (aOR = 2·2, 95% CI, 1·0-5·1) and new rpoB mutations (p = 0·024). The MTB evolution was 1·2 (95% CI, 1·02-1·38) single nucleotide polymorphisms per genome per year under dual pressure from the intra-host environment and anti-TB drugs. AMR-associated mutations occurred before phenotypic AMR appearance in cases with acquired phenotypic INH (10 of 16) and RIF (9 of 22) resistances. DISCUSSION Compensatory evolution may promote the fixation of INH/RIF-resistance mutations and affect phenotypic AMR. The TB treatment should be adjusted based on gene sequencing results, especially in persistent culture positivity during treatment, which highlights the clinical importance of WGS in identifying reinfection and AMR acquisition before phenotypic drug susceptibility testing.
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Affiliation(s)
- Guoqin Zhang
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China; Tianjin Center for Tuberculosis Control, Tianjin, China; University of Chinese Academy of Sciences, Beijing, China
| | - Xianhui Sun
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
| | - Joy Fleming
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Fanlei Ran
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
| | - Jianjun Luo
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Hong Chen
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Hanfang Ju
- Tianjin Center for Tuberculosis Control, Tianjin, China
| | - Zhirui Wang
- Tianjin Center for Tuberculosis Control, Tianjin, China
| | - Hui Zhao
- Tianjin Center for Tuberculosis Control, Tianjin, China
| | - Chunhua Wang
- Tianjin Center for Tuberculosis Control, Tianjin, China
| | - Fan Zhang
- Tianjin Center for Tuberculosis Control, Tianjin, China
| | - Xiaowei Dai
- Beijing Center for Disease Prevention and Control, Beijing, China
| | - Xinyu Yang
- Beijing Center for Disease Prevention and Control, Beijing, China
| | - Chuanyou Li
- Biobank of Beijing Chest Hospital, Beijing Tuberculosis and Thoracic Tumour Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Yi Liu
- Biobank of Beijing Chest Hospital, Beijing Tuberculosis and Thoracic Tumour Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing, China
| | | | - Xilin Zhang
- Foshan Fourth People's Hospital, Foshan, China
| | - Yuan Jiang
- Shanghai Municipal Center for Disease Prevention and Control, Beijing, China
| | - Zhilong Wu
- Foshan Fourth People's Hospital, Foshan, China
| | - Lijun Bi
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China; Guangzhou National Laboratory, Guangzhou, China; University of Chinese Academy of Sciences, Beijing, China
| | - Hongtai Zhang
- Beijing Center for Disease Prevention and Control, Beijing, China.
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3
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DelaFuente J, Diaz-Colunga J, Sanchez A, San Millan A. Global epistasis in plasmid-mediated antimicrobial resistance. Mol Syst Biol 2024; 20:311-320. [PMID: 38409539 PMCID: PMC10987494 DOI: 10.1038/s44320-024-00012-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/03/2024] [Accepted: 01/04/2024] [Indexed: 02/28/2024] Open
Abstract
Antimicrobial resistance (AMR) in bacteria is a major public health threat and conjugative plasmids play a key role in the dissemination of AMR genes among bacterial pathogens. Interestingly, the association between AMR plasmids and pathogens is not random and certain associations spread successfully at a global scale. The burst of genome sequencing has increased the resolution of epidemiological programs, broadening our understanding of plasmid distribution in bacterial populations. Despite the immense value of these studies, our ability to predict future plasmid-bacteria associations remains limited. Numerous empirical studies have recently reported systematic patterns in genetic interactions that enable predictability, in a phenomenon known as global epistasis. In this perspective, we argue that global epistasis patterns hold the potential to predict interactions between plasmids and bacterial genomes, thereby facilitating the prediction of future successful associations. To assess the validity of this idea, we use previously published data to identify global epistasis patterns in clinically relevant plasmid-bacteria associations. Furthermore, using simple mechanistic models of antibiotic resistance, we illustrate how global epistasis patterns may allow us to generate new hypotheses on the mechanisms associated with successful plasmid-bacteria associations. Collectively, we aim at illustrating the relevance of exploring global epistasis in the context of plasmid biology.
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Affiliation(s)
| | - Juan Diaz-Colunga
- Centro Nacional de Biotecnología (CNB-CSIC), Madrid, Spain
- Institute of Functional Biology & Genomics, IBFG - CSIC, Universidad de Salamanca, Salamanca, Spain
| | - Alvaro Sanchez
- Centro Nacional de Biotecnología (CNB-CSIC), Madrid, Spain.
- Institute of Functional Biology & Genomics, IBFG - CSIC, Universidad de Salamanca, Salamanca, Spain.
| | - Alvaro San Millan
- Centro Nacional de Biotecnología (CNB-CSIC), Madrid, Spain.
- Centro de Investigación Biológica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.
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4
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Diaz-Colunga J, Sanchez A, Ogbunugafor CB. Environmental modulation of global epistasis in a drug resistance fitness landscape. Nat Commun 2023; 14:8055. [PMID: 38052815 DOI: 10.1038/s41467-023-43806-x] [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: 11/22/2022] [Accepted: 11/21/2023] [Indexed: 12/07/2023] Open
Abstract
Interactions between mutations (epistasis) can add substantial complexity to genotype-phenotype maps, hampering our ability to predict evolution. Yet, recent studies have shown that the fitness effect of a mutation can often be predicted from the fitness of its genetic background using simple, linear relationships. This phenomenon, termed global epistasis, has been leveraged to reconstruct fitness landscapes and infer adaptive trajectories in a wide variety of contexts. However, little attention has been paid to how patterns of global epistasis may be affected by environmental variation, despite this variation frequently being a major driver of evolution. This is particularly relevant for the evolution of drug resistance, where antimicrobial drugs may change the environment faced by pathogens and shape their adaptive trajectories in ways that can be difficult to predict. By analyzing a fitness landscape of four mutations in a gene encoding an essential enzyme of P. falciparum (a parasite cause of malaria), here we show that patterns of global epistasis can be strongly modulated by the concentration of a drug in the environment. Expanding on previous theoretical results, we demonstrate that this modulation can be quantitatively explained by how specific gene-by-gene interactions are modified by drug dose. Importantly, our results highlight the need to incorporate potential environmental variation into the global epistasis framework in order to predict adaptation in dynamic environments.
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Affiliation(s)
- Juan Diaz-Colunga
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT, 06511, USA.
- Department of Microbial Biotechnology, Spanish National Center for Biotechnology CNB-CSIC, 28049, Madrid, Spain.
- Institute of Functional Biology and Genomics IBFG-CSIC, University of Salamanca, 37007, Salamanca, Spain.
| | - Alvaro Sanchez
- Department of Microbial Biotechnology, Spanish National Center for Biotechnology CNB-CSIC, 28049, Madrid, Spain.
- Institute of Functional Biology and Genomics IBFG-CSIC, University of Salamanca, 37007, Salamanca, Spain.
| | - C Brandon Ogbunugafor
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT, 06511, USA.
- Santa Fe Institute, Santa Fe, NM, 87501, USA.
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5
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Kanesaka I, Ohno A, Morita M, Katsuse AK, Morihana T, Ito T, Takahashi H, Kobayashi I. Epigenetic effects of ceftriaxone-resistant Neisseria gonorrhoeae FC428 mosaic-like sequences found in PenA sequences unique to Neisseria subflava and related species. J Antimicrob Chemother 2023; 78:2683-2690. [PMID: 37769185 DOI: 10.1093/jac/dkad281] [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: 03/27/2023] [Accepted: 08/29/2023] [Indexed: 09/30/2023] Open
Abstract
OBJECTIVES The aim of this study was to explore the origin of the PenA mosaic amino acid sequence in the ceftriaxone-resistant Neisseria gonorrhoeae FC428 clone. METHODS The penA sequences of 27 Neisseria subflava pharyngeal isolates were determined by the Sanger method and penA sequences of 52 isolates from nine Neisseria species were obtained from the NCBI database. Comparative analysis of each PenA sequence was performed by multiple sequence alignment using ClustalW. In vitro resistance acquisition experiments were conducted to investigate the possibility of selection pressure by cefixime-induced amino acid substitution mutations in PenA. RESULTS All N. subflava strains, including two with low susceptibility to expanded-spectrum cephalosporins (ESCs), possessed the majority of the PenA FC428 sequence. Furthermore, a number of strains, but not all, of closely related species of N. subflava showed similar results. PenA FC428 sequences were also found in some strains of distantly related species. No new mutations in the penA sequence were observed in colonies with increased MIC in in vitro resistance acquisition experiments. CONCLUSIONS This study provides strong evidence that the FC428 PenA mosaic sequence originated from N. subflava and related species among oral commensal Neisseria species. The results of in vitro resistance acquisition experiments also suggested that one of the PenA FC428-like sequence gene polymorphisms resulted in the expression of ESC resistance. Furthermore, many of the PenA FC428 mosaic sequences were thought to be involved in the so-called epistasis effect that regulates the expression of resistance, without directly contributing to the resistance level itself.
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Affiliation(s)
- Izumo Kanesaka
- Department of Infection Control and Prevention, Faculty of Nursing, Toho University, 4-16-20, Omori-nishi, Ota-ku, Tokyo 143-0015, Japan
| | - Akira Ohno
- Department of Infection Control and Prevention, Faculty of Nursing, Toho University, 4-16-20, Omori-nishi, Ota-ku, Tokyo 143-0015, Japan
| | - Masahiro Morita
- Department of Infection Control and Prevention, Faculty of Nursing, Toho University, 4-16-20, Omori-nishi, Ota-ku, Tokyo 143-0015, Japan
| | - Akiko Kanayama Katsuse
- Department of Infection Control and Prevention, Faculty of Nursing, Toho University, 4-16-20, Omori-nishi, Ota-ku, Tokyo 143-0015, Japan
| | - Takefumi Morihana
- Morihana Dental Clinic, 48, Dojocho-dojo, Kita-ku, Kobe-shi, Hyogo 651-1501, Japan
| | - Takamitsu Ito
- Department of Clinical Laboratory, Higashiosaka City Medical Center, 3-4-5, Nishiiwata, Higashiosaka-shi, Osaka 578-8588, Japan
| | - Hiroshi Takahashi
- Department of Infection Control and Prevention, Faculty of Nursing, Toho University, 4-16-20, Omori-nishi, Ota-ku, Tokyo 143-0015, Japan
| | - Intetsu Kobayashi
- Department of Infection Control and Prevention, Faculty of Nursing, Toho University, 4-16-20, Omori-nishi, Ota-ku, Tokyo 143-0015, Japan
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6
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Coluzzi C, Guillemet M, Mazzamurro F, Touchon M, Godfroid M, Achaz G, Glaser P, Rocha EPC. Chance Favors the Prepared Genomes: Horizontal Transfer Shapes the Emergence of Antibiotic Resistance Mutations in Core Genes. Mol Biol Evol 2023; 40:msad217. [PMID: 37788575 PMCID: PMC10575684 DOI: 10.1093/molbev/msad217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 09/08/2023] [Accepted: 09/19/2023] [Indexed: 10/05/2023] Open
Abstract
Bacterial lineages acquire novel traits at diverse rates in part because the genetic background impacts the successful acquisition of novel genes by horizontal transfer. Yet, how horizontal transfer affects the subsequent evolution of core genes remains poorly understood. Here, we studied the evolution of resistance to quinolones in Escherichia coli accounting for population structure. We found 60 groups of genes whose gain or loss induced an increase in the probability of subsequently becoming resistant to quinolones by point mutations in the gyrase and topoisomerase genes. These groups include functions known to be associated with direct mitigation of the effect of quinolones, with metal uptake, cell growth inhibition, biofilm formation, and sugar metabolism. Many of them are encoded in phages or plasmids. Although some of the chronologies may reflect epidemiological trends, many of these groups encoded functions providing latent phenotypes of antibiotic low-level resistance, tolerance, or persistence under quinolone treatment. The mutations providing resistance were frequent and accumulated very quickly. Their emergence was found to increase the rate of acquisition of other antibiotic resistances setting the path for multidrug resistance. Hence, our findings show that horizontal gene transfer shapes the subsequent emergence of adaptive mutations in core genes. In turn, these mutations further affect the subsequent evolution of resistance by horizontal gene transfer. Given the substantial gene flow within bacterial genomes, interactions between horizontal transfer and point mutations in core genes may be a key to the success of adaptation processes.
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Affiliation(s)
- Charles Coluzzi
- Institut Pasteur, Université Paris Cité, CNRS, UMR3525, Microbial Evolutionary Genomics, Paris, France
| | - Martin Guillemet
- Institut Pasteur, Université Paris Cité, CNRS, UMR3525, Microbial Evolutionary Genomics, Paris, France
| | - Fanny Mazzamurro
- Institut Pasteur, Université Paris Cité, CNRS, UMR3525, Microbial Evolutionary Genomics, Paris, France
- Collège Doctoral, Sorbonne Université, Paris, France
| | - Marie Touchon
- Institut Pasteur, Université Paris Cité, CNRS, UMR3525, Microbial Evolutionary Genomics, Paris, France
| | - Maxime Godfroid
- SMILE Group, Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, Université PSL, Paris, France
| | - Guillaume Achaz
- SMILE Group, Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, Université PSL, Paris, France
| | - Philippe Glaser
- Institut Pasteur, Université de Paris Cité, CNRS, UMR6047, Unité EERA, Paris, France
| | - Eduardo P C Rocha
- Institut Pasteur, Université Paris Cité, CNRS, UMR3525, Microbial Evolutionary Genomics, Paris, France
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7
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Abisado-Duque RG, Townsend KA, Mckee BM, Woods K, Koirala P, Holder AJ, Craddock VD, Cabeen M, Chandler JR. An Amino Acid Substitution in Elongation Factor EF-G1A Alters the Antibiotic Susceptibility of Pseudomonas aeruginosa LasR-Null Mutants. J Bacteriol 2023; 205:e0011423. [PMID: 37191503 PMCID: PMC10294626 DOI: 10.1128/jb.00114-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 04/22/2023] [Indexed: 05/17/2023] Open
Abstract
The opportunistic bacterium Pseudomonas aeruginosa uses the LasR-I quorum-sensing system to increase resistance to the aminoglycoside antibiotic tobramycin. Paradoxically, lasR-null mutants are commonly isolated from chronic human infections treated with tobramycin, suggesting there may be a mechanism that permits the emergence of lasR-null mutants under tobramycin selection. We hypothesized that some other genetic mutations that emerge in these isolates might modulate the effects of lasR-null mutations on antibiotic resistance. To test this hypothesis, we inactivated lasR in several highly tobramycin-resistant isolates from long-term evolution experiments. In some of these isolates, inactivating lasR further increased resistance, compared with decreasing resistance of the wild-type ancestor. These strain-dependent effects were due to a G61A nucleotide polymorphism in the fusA1 gene encoding amino acid substitution A21T in the translation elongation factor EF-G1A. The EF-G1A mutational effects required the MexXY efflux pump and the MexXY regulator ArmZ. The fusA1 mutation also modulated ΔlasR mutant resistance to two other antibiotics, ciprofloxacin and ceftazidime. Our results identify a gene mutation that can reverse the direction of the antibiotic selection of lasR mutants, a phenomenon known as sign epistasis, and provide a possible explanation for the emergence of lasR-null mutants in clinical isolates. IMPORTANCE One of the most common mutations in Pseudomonas aeruginosa clinical isolates is in the quorum sensing lasR gene. In laboratory strains, lasR disruption decreases resistance to the clinical antibiotic tobramycin. To understand how lasR mutations emerge in tobramycin-treated patients, we mutated lasR in highly tobramycin-resistant laboratory strains and determined the effects on resistance. Disrupting lasR enhanced the resistance of some strains. These strains had a single amino acid substitution in the translation factor EF-G1A. The EF-G1A mutation reversed the selective effects of tobramycin on lasR mutants. These results illustrate how adaptive mutations can lead to the emergence of new traits in a population and are relevant to understanding how genetic diversity contributes to the progression of disease during chronic infections.
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Affiliation(s)
| | - Kade A. Townsend
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, USA
| | - Brielle M. Mckee
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, USA
| | - Kathryn Woods
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, USA
| | - Pratik Koirala
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, USA
| | - Alexandra J. Holder
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, USA
| | - Vaughn D. Craddock
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, USA
| | - Matthew Cabeen
- Department of Microbiology and Molecular Genetics, Oklahoma State University, Stillwater, Oklahoma, USA
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Zhuang Z, Sun L, Song X, Zhu H, Li L, Zhou X, Mi K. Trends and challenges of multi-drug resistance in childhood tuberculosis. Front Cell Infect Microbiol 2023; 13:1183590. [PMID: 37333849 PMCID: PMC10275406 DOI: 10.3389/fcimb.2023.1183590] [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: 03/10/2023] [Accepted: 05/23/2023] [Indexed: 06/20/2023] Open
Abstract
Drug-resistant tuberculosis (DR-TB) in children is a growing global health concern, This review provides an overview of the current epidemiology of childhood TB and DR-TB, including prevalence, incidence, and mortality. We discuss the challenges in diagnosing TB and DR-TB in children and the limitations of current diagnostic tools. We summarize the challenges associated with treating multi-drug resistance TB in childhood, including limitations of current treatment options, drug adverse effects, prolonged regimens, and managing and monitoring during treatment. We highlight the urgent need for improved diagnosis and treatment of DR-TB in children. The treatment of children with multidrug-resistant tuberculosis will be expanded to include the evaluation of new drugs or new combinations of drugs. Basic research is needed to support the technological development of biomarkers to assess the phase of therapy, as well as the urgent need for improved diagnostic and treatment options.
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Affiliation(s)
- Zengfang Zhuang
- Chinese Academy of Sciences (CAS) Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China
| | - Lin Sun
- Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Xiaorui Song
- Henan International Joint Laboratory of Children’s Infectious Diseases, Children’s Hospital Affiliated to Zhengzhou University, Henan Children’s Hospital, Zhengzhou Children’s Hospital, Zhengzhou, China
| | - Hanzhao Zhu
- Chinese Academy of Sciences (CAS) Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China
| | - Lianju Li
- Chinese Academy of Sciences (CAS) Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- School of Basic Medicine, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Xintong Zhou
- Chinese Academy of Sciences (CAS) Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| | - Kaixia Mi
- Chinese Academy of Sciences (CAS) Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China
- Henan International Joint Laboratory of Children’s Infectious Diseases, Children’s Hospital Affiliated to Zhengzhou University, Henan Children’s Hospital, Zhengzhou Children’s Hospital, Zhengzhou, China
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9
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Abisado-Duquea RG, McKee BM, Townsend KA, Woods K, Koirala P, Holder AJ, Craddock VD, Cabeen MT, Chandler JR. Tobramycin adaptation alters the antibiotic susceptibility of Pseudomonas aeruginosa quorum sensing-null mutants. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.13.523864. [PMID: 36711731 PMCID: PMC9882136 DOI: 10.1101/2023.01.13.523864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
The opportunistic bacterium Pseudomonas aeruginosa uses the LasR-I quorum sensing system to increase resistance to the aminioglycoside antibiotic tobramycin. Paradoxically, lasR-null mutants are commonly isolated from chronic human infections treated with tobramycin, suggesting there may be a mechanism allowing the lasR-null mutants to persist under tobramycin selection. We hypothesized that the effects of inactivating lasR on tobramycin resistance might be dependent on the presence or absence of other gene mutations in that strain, a phenomenon known as epistasis. To test this hypothesis, we inactivated lasR in several highly tobramycin-resistant isolates from long-term evolution experiments. We show that the effects of ΔlasR on tobramycin resistance are strain dependent. The effects can be attributed to a point mutation in the gene encoding the translation elongation factor fusA1 (G61A nucleotide substitution), which confers a strong selective advantage to lasR-null PA14 under tobramycin selection. This fusA1 G61A mutation results in increased activity of the MexXY efflux pump and expression of the mexXY regulator ArmZ. The fusA1 mutation can also modulate ΔlasR mutant resistance to two other antibiotics, ciprofloxacin and ceftazidime. Our results demonstrate the importance of epistatic gene interactions on antibiotic susceptibility of lasR-null mutants. These results support of the idea that gene interactions might play a significant role in the evolution of quorum sensing in P. aeruginosa.
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10
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Environmental complexity is more important than mutation in driving the evolution of latent novel traits in E. coli. Nat Commun 2022; 13:5904. [PMID: 36202805 PMCID: PMC9537139 DOI: 10.1038/s41467-022-33634-w] [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: 04/07/2022] [Accepted: 09/26/2022] [Indexed: 11/23/2022] Open
Abstract
Recent experiments show that adaptive Darwinian evolution in one environment can lead to the emergence of multiple new traits that provide no immediate benefit in this environment. Such latent non-adaptive traits, however, can become adaptive in future environments. We do not know whether mutation or environment-driven selection is more important for the emergence of such traits. To find out, we evolve multiple wild-type and mutator E. coli populations under two mutation rates in simple (single antibiotic) environments and in complex (multi-antibiotic) environments. We then assay the viability of evolved populations in dozens of new environments and show that all populations become viable in multiple new environments different from those they had evolved in. The number of these new environments increases with environmental complexity but not with the mutation rate. Genome sequencing demonstrates the reason: Different environments affect pleiotropic mutations differently. Our experiments show that the selection pressure provided by an environment can be more important for the evolution of novel traits than the mutational supply experienced by a wild-type and a mutator strain of E. coli. Novel traits without immediate fitness benefit evolve frequently but we don’t know whether mutation or environment-driven selection drives this evolution. Here, using experimental evolution of E. coli populations, the authors demonstrate the importance of selection in the evolution of latent novel traits.
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11
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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.
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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
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12
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Lee MC, Chang H, Sun FJ, Wu AYJ, Lu CH, Lee CM. Association between Antimicrobial Consumption and the Prevalence of Nosocomial Carbapenem-Resistant Escherichia coli and Klebsiella pneumoniae in a Tertiary Hospital in Northern Taiwan. Am J Trop Med Hyg 2022; 107:467-473. [PMID: 35895586 PMCID: PMC9393431 DOI: 10.4269/ajtmh.21-1242] [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: 11/29/2021] [Accepted: 02/21/2022] [Indexed: 08/03/2023] Open
Abstract
Carbapenem-resistant Enterobacteriales has become a threat in Taiwan. This is the first local study focusing on the association between carbapenem-resistant Enterobacteriales and antimicrobial consumption. From January 2012 to December 2020, data were collected in a tertiary care hospital in Taipei, Taiwan. Antimicrobial consumption was estimated by the defined daily dose/1,000 patient-days. During the same period, the prevalence of carbapenem-resistant Escherichia coli (CREC) and carbapenem-resistant Klebsiella pneumoniae (CRKP) were collected through routine surveillance data. The following retrospective analyses were conducted: 1) analysis of antimicrobial consumption over time, (2) analysis and forecast of CREC and CRKP prevalence over time, and 3) analysis of correlation between antimicrobial consumption and the prevalence of CREC and CRKP. The consumption of piperacillin/tazobactam (β = 0.615), fluoroquinolones (β = 0.856), meropenem (β = 0.819), and doripenem (β = 0.891) increased during the observation period (P < 0.001), and the consumption of aminoglycosides (β = -0.852) and imipenem/cilastatin (β = -0.851) decreased (P < 0.001). The prevalence of CRKP rose over time (β = 0.522, P = 0.001) and correlated positively with the consumption of fluoroquinolones, levofloxacin, penicillin/β-lactamase inhibitor, piperacillin/tazobactam, meropenem, and doripenem (P < 0.05). The prevalence of CRKP and CREC both correlated negatively with consumption of aminoglycosides (P < 0.01). The prevalence of CRKP in our hospital increased as the forecast predicted based on an autoregressive integrated moving average model. This study provides alarming messages for members participating in antimicrobial stewardship programs, including the increasing prevalence of CRKP, the increasing consumption of broad-spectrum antibiotics, and the positive correlation between them.
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Affiliation(s)
- Mei-Chun Lee
- Department of Pharmacy, MacKay Memorial Hospital, Taipei, Taiwan
- Nursing and Management, Mackay Junior College of Medicine, Taipei, Taiwan
| | - Hsun Chang
- Division of Infectious Diseases, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan
| | - Fang-Ju Sun
- Nursing and Management, Mackay Junior College of Medicine, Taipei, Taiwan
- Department of Medical Research, MacKay Memorial Hospital, Taipei, Taiwan
| | - Alice Ying-Jung Wu
- Division of Infectious Diseases, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan
| | - Chien-Hung Lu
- Department of Pharmacy, MacKay Memorial Hospital, Taipei, Taiwan
| | - Chun-Ming Lee
- Nursing and Management, Mackay Junior College of Medicine, Taipei, Taiwan
- Division of Infectious Diseases, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan
- MacKay Medical College, New Taipei City, Taiwan
- Department of Internal Medicine, St. Joseph’s Hospital, Yunlin County, Taiwan
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13
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Machine Learning for Antimicrobial Resistance Prediction: Current Practice, Limitations, and Clinical Perspective. Clin Microbiol Rev 2022; 35:e0017921. [PMID: 35612324 DOI: 10.1128/cmr.00179-21] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Antimicrobial resistance (AMR) is a global health crisis that poses a great threat to modern medicine. Effective prevention strategies are urgently required to slow the emergence and further dissemination of AMR. Given the availability of data sets encompassing hundreds or thousands of pathogen genomes, machine learning (ML) is increasingly being used to predict resistance to different antibiotics in pathogens based on gene content and genome composition. A key objective of this work is to advocate for the incorporation of ML into front-line settings but also highlight the further refinements that are necessary to safely and confidently incorporate these methods. The question of what to predict is not trivial given the existence of different quantitative and qualitative laboratory measures of AMR. ML models typically treat genes as independent predictors, with no consideration of structural and functional linkages; they also may not be accurate when new mutational variants of known AMR genes emerge. Finally, to have the technology trusted by end users in public health settings, ML models need to be transparent and explainable to ensure that the basis for prediction is clear. We strongly advocate that the next set of AMR-ML studies should focus on the refinement of these limitations to be able to bridge the gap to diagnostic implementation.
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14
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Hasan CM, Dutta D, Nguyen ANT. Revisiting Antibiotic Resistance: Mechanistic Foundations to Evolutionary Outlook. Antibiotics (Basel) 2021; 11:antibiotics11010040. [PMID: 35052917 PMCID: PMC8773413 DOI: 10.3390/antibiotics11010040] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/22/2021] [Accepted: 11/23/2021] [Indexed: 12/12/2022] Open
Abstract
Antibiotics are the pivotal pillar of contemporary healthcare and have contributed towards its advancement over the decades. Antibiotic resistance emerged as a critical warning to public wellbeing because of unsuccessful management efforts. Resistance is a natural adaptive tool that offers selection pressure to bacteria, and hence cannot be stopped entirely but rather be slowed down. Antibiotic resistance mutations mostly diminish bacterial reproductive fitness in an environment without antibiotics; however, a fraction of resistant populations 'accidentally' emerge as the fittest and thrive in a specific environmental condition, thus favouring the origin of a successful resistant clone. Therefore, despite the time-to-time amendment of treatment regimens, antibiotic resistance has evolved relentlessly. According to the World Health Organization (WHO), we are rapidly approaching a 'post-antibiotic' era. The knowledge gap about antibiotic resistance and room for progress is evident and unified combating strategies to mitigate the inadvertent trends of resistance seem to be lacking. Hence, a comprehensive understanding of the genetic and evolutionary foundations of antibiotic resistance will be efficacious to implement policies to force-stop the emergence of resistant bacteria and treat already emerged ones. Prediction of possible evolutionary lineages of resistant bacteria could offer an unswerving impact in precision medicine. In this review, we will discuss the key molecular mechanisms of resistance development in clinical settings and their spontaneous evolution.
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Affiliation(s)
- Chowdhury M. Hasan
- School of Biological Sciences, University of Queensland, Brisbane 4072, Australia
- Department of Clinical Infection, Microbiology and Immunology, Institute of Infection, Veterinary & Ecological Sciences (IVES), University of Liverpool, Liverpool L7 3EA, UK;
- School of Biological Sciences, Monash University, Melbourne 3800, Australia;
- Correspondence:
| | - Debprasad Dutta
- Department of Clinical Infection, Microbiology and Immunology, Institute of Infection, Veterinary & Ecological Sciences (IVES), University of Liverpool, Liverpool L7 3EA, UK;
- Department of Human Genetics, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore 560029, India
| | - An N. T. Nguyen
- School of Biological Sciences, Monash University, Melbourne 3800, Australia;
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15
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The Neglected Contribution of Streptomycin to the Tuberculosis Drug Resistance Problem. Genes (Basel) 2021; 12:genes12122003. [PMID: 34946952 PMCID: PMC8701281 DOI: 10.3390/genes12122003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 12/14/2021] [Accepted: 12/15/2021] [Indexed: 12/22/2022] Open
Abstract
The airborne pathogen Mycobacterium tuberculosis is responsible for a present major public health problem worsened by the emergence of drug resistance. M. tuberculosis has acquired and developed streptomycin (STR) resistance mechanisms that have been maintained and transmitted in the population over the last decades. Indeed, STR resistant mutations are frequently identified across the main M. tuberculosis lineages that cause tuberculosis outbreaks worldwide. The spread of STR resistance is likely related to the low impact of the most frequent underlying mutations on the fitness of the bacteria. The withdrawal of STR from the first-line treatment of tuberculosis potentially lowered the importance of studying STR resistance. However, the prevalence of STR resistance remains very high, could be underestimated by current genotypic methods, and was found in outbreaks of multi-drug (MDR) and extensively drug (XDR) strains in different geographic regions. Therefore, the contribution of STR resistance to the problem of tuberculosis drug resistance should not be neglected. Here, we review the impact of STR resistance and detail well-known and novel candidate STR resistance mechanisms, genes, and mutations. In addition, we aim to provide insights into the possible role of STR resistance in the development of multi-drug resistant tuberculosis.
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16
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Hernandez B, Herrero-Viñas P, Rawson TM, Moore LSP, Holmes AH, Georgiou P. Resistance Trend Estimation Using Regression Analysis to Enhance Antimicrobial Surveillance: A Multi-Centre Study in London 2009-2016. Antibiotics (Basel) 2021; 10:1267. [PMID: 34680846 PMCID: PMC8533047 DOI: 10.3390/antibiotics10101267] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/04/2021] [Accepted: 10/06/2021] [Indexed: 12/31/2022] Open
Abstract
In the last years, there has been an increase of antimicrobial resistance rates around the world with the misuse and overuse of antimicrobials as one of the main leading drivers. In response to this threat, a variety of initiatives have arisen to promote the efficient use of antimicrobials. These initiatives rely on antimicrobial surveillance systems to promote appropriate prescription practices and are provided by national or global health care institutions with limited consideration of the variations within hospitals. As a consequence, physicians' adherence to these generic guidelines is still limited. To fill this gap, this work presents an automated approach to performing local antimicrobial surveillance from microbiology data. Moreover, in addition to the commonly reported resistance rates, this work estimates secular resistance trends through regression analysis to provide a single value that effectively communicates the resistance trend to a wider audience. The methods considered for trend estimation were ordinary least squares regression, weighted least squares regression with weights inversely proportional to the number of microbiology records available and autoregressive integrated moving average. Among these, weighted least squares regression was found to be the most robust against changes in the granularity of the time series and presented the best performance. To validate the results, three case studies have been thoroughly compared with the existing literature: (i) Escherichia coli in urine cultures; (ii) Escherichia coli in blood cultures; and (iii) Staphylococcus aureus in wound cultures. The benefits of providing local rather than general antimicrobial surveillance data of a higher quality is two fold. Firstly, it has the potential to stimulate engagement among physicians to strengthen their knowledge and awareness on antimicrobial resistance which might encourage prescribers to change their prescription habits more willingly. Moreover, it provides fundamental knowledge to the wide range of stakeholders to revise and potentially tailor existing guidelines to the specific needs of each hospital.
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Affiliation(s)
- Bernard Hernandez
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK; (P.H.-V.); (P.G.)
- Centre for Antimicrobial Optimisation (CAMO), Imperial College London, London W12 0NN, UK; (T.M.R.); (A.H.H.)
| | - Pau Herrero-Viñas
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK; (P.H.-V.); (P.G.)
- Centre for Antimicrobial Optimisation (CAMO), Imperial College London, London W12 0NN, UK; (T.M.R.); (A.H.H.)
| | - Timothy M. Rawson
- Centre for Antimicrobial Optimisation (CAMO), Imperial College London, London W12 0NN, UK; (T.M.R.); (A.H.H.)
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London W12 0NN, UK
| | - Luke S. P. Moore
- Chelsea and Westminster NHS Foundation Trust, London SW10 9NH, UK;
| | - Alison H. Holmes
- Centre for Antimicrobial Optimisation (CAMO), Imperial College London, London W12 0NN, UK; (T.M.R.); (A.H.H.)
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London W12 0NN, UK
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK; (P.H.-V.); (P.G.)
- Centre for Antimicrobial Optimisation (CAMO), Imperial College London, London W12 0NN, UK; (T.M.R.); (A.H.H.)
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17
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Tunstall T, Phelan J, Eccleston C, Clark TG, Furnham N. Structural and Genomic Insights Into Pyrazinamide Resistance in Mycobacterium tuberculosis Underlie Differences Between Ancient and Modern Lineages. Front Mol Biosci 2021; 8:619403. [PMID: 34422898 PMCID: PMC8372558 DOI: 10.3389/fmolb.2021.619403] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 04/14/2021] [Indexed: 11/30/2022] Open
Abstract
Resistance to drugs used to treat tuberculosis disease (TB) continues to remain a public health burden, with missense point mutations in the underlying Mycobacterium tuberculosis bacteria described for nearly all anti-TB drugs. The post-genomics era along with advances in computational and structural biology provide opportunities to understand the interrelationships between the genetic basis and the structural consequences of M. tuberculosis mutations linked to drug resistance. Pyrazinamide (PZA) is a crucial first line antibiotic currently used in TB treatment regimens. The mutational promiscuity exhibited by the pncA gene (target for PZA) necessitates computational approaches to investigate the genetic and structural basis for PZA resistance development. We analysed 424 missense point mutations linked to PZA resistance derived from ∼35K M. tuberculosis clinical isolates sourced globally, which comprised the four main M. tuberculosis lineages (Lineage 1-4). Mutations were annotated to reflect their association with PZA resistance. Genomic measures (minor allele frequency and odds ratio), structural features (surface area, residue depth and hydrophobicity) and biophysical effects (change in stability and ligand affinity) of point mutations on pncA protein stability and ligand affinity were assessed. Missense point mutations within pncA were distributed throughout the gene, with the majority (>80%) of mutations with a destabilising effect on protomer stability and on ligand affinity. Active site residues involved in PZA binding were associated with multiple point mutations highlighting mutational diversity due to selection pressures at these functionally important sites. There were weak associations between genomic measures and biophysical effect of mutations. However, mutations associated with PZA resistance showed statistically significant differences between structural features (surface area and residue depth), but not hydrophobicity score for mutational sites. Most interestingly M. tuberculosis lineage 1 (ancient lineage) exhibited a distinct protein stability profile for mutations associated with PZA resistance, compared to modern lineages.
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Affiliation(s)
- Tanushree Tunstall
- Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Jody Phelan
- Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Charlotte Eccleston
- Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Taane G. Clark
- Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Nicholas Furnham
- Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom
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18
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Jahn LJ, Simon D, Jensen M, Bradshaw C, Ellabaan MMH, Sommer MOA. Compatibility of Evolutionary Responses to Constituent Antibiotics Drive Resistance Evolution to Drug Pairs. Mol Biol Evol 2021; 38:2057-2069. [PMID: 33480997 PMCID: PMC8097295 DOI: 10.1093/molbev/msab006] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Antibiotic combinations are considered a relevant strategy to tackle the global antibiotic resistance crisis since they are believed to increase treatment efficacy and reduce resistance evolution (WHO treatment guidelines for drug-resistant tuberculosis: 2016 update.). However, studies of the evolution of bacterial resistance to combination therapy have focused on a limited number of drugs and have provided contradictory results (Lipsitch, Levin BR. 1997; Hegreness et al. 2008; Munck et al. 2014). To address this gap in our understanding, we performed a large-scale laboratory evolution experiment, adapting eight replicate lineages of Escherichia coli to a diverse set of 22 different antibiotics and 33 antibiotic pairs. We found that combination therapy significantly limits the evolution of de novode novo resistance in E. coli, yet different drug combinations vary substantially in their propensity to select for resistance. In contrast to current theories, the phenotypic features of drug pairs are weak predictors of resistance evolution. Instead, the resistance evolution is driven by the relationship between the evolutionary trajectories that lead to resistance to a drug combination and those that lead to resistance to the component drugs. Drug combinations requiring a novel genetic response from target bacteria compared with the individual component drugs significantly reduce resistance evolution. These data support combination therapy as a treatment option to decelerate resistance evolution and provide a novel framework for selecting optimized drug combinations based on bacterial evolutionary responses.
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Affiliation(s)
- Leonie Johanna Jahn
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Daniel Simon
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Mia Jensen
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Charles Bradshaw
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
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19
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Wang T, Weiss A, Ha Y, You L. Predicting plasmid persistence in microbial communities by coarse-grained modeling. Bioessays 2021; 43:e2100084. [PMID: 34278591 DOI: 10.1002/bies.202100084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 06/15/2021] [Accepted: 06/17/2021] [Indexed: 11/08/2022]
Abstract
Plasmids are a major type of mobile genetic elements (MGEs) that mediate horizontal gene transfer. The stable maintenance of plasmids plays a critical role in the functions and survival for microbial populations. However, predicting and controlling plasmid persistence and abundance in complex microbial communities remain challenging. Computationally, this challenge arises from the combinatorial explosion associated with the conventional modeling framework. Recently, a plasmid-centric framework (PCF) has been developed to overcome this computational bottleneck. This framework enables the derivation of a simple metric, the persistence potential, to predict plasmid persistence and abundance. Here, we discuss how PCF can be extended to account for plasmid interactions. We also discuss how such model-guided predictions of plasmid fates can benefit from the development of new experimental tools and data-driven computational methods.
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Affiliation(s)
- Teng Wang
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
| | - Andrea Weiss
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
| | - Yuanchi Ha
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA.,Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, USA.,Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, North Carolina, USA
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20
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Gutiérrez R, Ram Y, Berman J, Carstens Marques de Sousa K, Nachum-Biala Y, Britzi M, Elad D, Glaser G, Covo S, Harrus S. Adaptive resistance mutations at supra-inhibitory concentrations independent of SOS mutagenesis. Mol Biol Evol 2021; 38:4095-4115. [PMID: 34175952 PMCID: PMC8476149 DOI: 10.1093/molbev/msab196] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Emergence of resistant bacteria during antimicrobial treatment is one of the most critical and universal health threats. It is known that several stress-induced mutagenesis and heteroresistance mechanisms can enhance microbial adaptation to antibiotics. Here, we demonstrate that the pathogen Bartonella can undergo stress-induced mutagenesis despite the fact it lacks error-prone polymerases, the rpoS gene and functional UV-induced mutagenesis. We demonstrate that Bartonella acquire de novo single mutations during rifampicin exposure at suprainhibitory concentrations at a much higher rate than expected from spontaneous fluctuations. This is while exhibiting a minimal heteroresistance capacity. The emerged resistant mutants acquired a single rpoB mutation, whereas no other mutations were found in their whole genome. Interestingly, the emergence of resistance in Bartonella occurred only during gradual exposure to the antibiotic, indicating that Bartonella sense and react to the changing environment. Using a mathematical model, we demonstrated that, to reproduce the experimental results, mutation rates should be transiently increased over 1,000-folds, and a larger population size or greater heteroresistance capacity is required. RNA expression analysis suggests that the increased mutation rate is due to downregulation of key DNA repair genes (mutS, mutY, and recA), associated with DNA breaks caused by massive prophage inductions. These results provide new evidence of the hazard of antibiotic overuse in medicine and agriculture.
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Affiliation(s)
- Ricardo Gutiérrez
- The Koret School of Veterinary Medicine, Faculty of Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel.,The Center for Research in Tropical Diseases, Faculty of Microbiology, University of Costa Rica, San José, Costa Rica
| | - Yoav Ram
- School of Zoology, Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Israel.,School of Computer Science, Interdisciplinary Center Herzliya, Herzliya, Israel
| | - Judith Berman
- Shmunis School of Biomedicine and Cancer, Faculty of Life Sciences, Tel Aviv University, Tel Aviv University, Ramat Aviv, Israel
| | | | - Yaarit Nachum-Biala
- The Koret School of Veterinary Medicine, Faculty of Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
| | - Malka Britzi
- The National Residue Control Laboratory, The Kimron Veterinary Institute, Bet Dagan, Israel
| | - Daniel Elad
- Department of Clinical Bacteriology and Mycology, The Kimron Veterinary Institute, Bet Dagan, Israel
| | - Gad Glaser
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Shay Covo
- Department of Plant Pathology and Microbiology, Faculty of Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
| | - Shimon Harrus
- The Koret School of Veterinary Medicine, Faculty of Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
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21
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Abstract
Antimicrobial resistance (AMR) is an important global health threat that impacts millions of people worldwide each year. Developing methods that can detect and predict AMR phenotypes can help to mitigate the spread of AMR by informing clinical decision making and appropriate mitigation strategies. Many bioinformatic methods have been developed for predicting AMR phenotypes from whole-genome sequences and AMR genes, but recent studies have indicated that predictions can be made from incomplete genome sequence data. In order to more systematically understand this, we built random forest-based machine learning classifiers for predicting susceptible and resistant phenotypes for Klebsiella pneumoniae (1,640 strains), Mycobacterium tuberculosis (2,497 strains), and Salmonella enterica (1,981 strains). We started by building models from alignments that were based on a reference chromosome for each species. We then subsampled each chromosomal alignment and built models for the resulting subalignments, finding that very small regions, representing approximately 0.1 to 0.2% of the chromosome, are predictive. In K. pneumoniae, M. tuberculosis, and S. enterica, the subalignments are able to predict multiple AMR phenotypes with at least 70% accuracy, even though most do not encode an AMR-related function. We used these models to identify regions of the chromosome with high and low predictive signals. Finally, subalignments that retain high accuracy across larger phylogenetic distances were examined in greater detail, revealing genes and intergenic regions with potential links to AMR, virulence, transport, and survival under stress conditions. IMPORTANCE Antimicrobial resistance causes thousands of deaths annually worldwide. Understanding the regions of the genome that are involved in antimicrobial resistance is important for developing mitigation strategies and preventing transmission. Machine learning models are capable of predicting antimicrobial resistance phenotypes from bacterial genome sequence data by identifying resistance genes, mutations, and other correlated features. They are also capable of implicating regions of the genome that have not been previously characterized as being involved in resistance. In this study, we generated global chromosomal alignments for Klebsiella pneumoniae, Mycobacterium tuberculosis, and Salmonella enterica and systematically searched them for small conserved regions of the genome that enable the prediction of antimicrobial resistance phenotypes. In addition to known antimicrobial resistance genes, this analysis identified genes involved in virulence and transport functions, as well as many genes with no previous implication in antimicrobial resistance.
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22
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Collateral Sensitivity to β-Lactam Drugs in Drug-Resistant Tuberculosis Is Driven by the Transcriptional Wiring of BlaI Operon Genes. mSphere 2021; 6:e0024521. [PMID: 34047652 PMCID: PMC8265638 DOI: 10.1128/msphere.00245-21] [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] [Indexed: 12/25/2022] Open
Abstract
The evolution of resistance to one antimicrobial can result in enhanced sensitivity to another, known as "collateral sensitivity." This underexplored phenomenon opens new therapeutic possibilities for patients infected with pathogens unresponsive to classical treatments. Intrinsic resistance to β-lactams in Mycobacterium tuberculosis (the causative agent of tuberculosis) has traditionally curtailed the use of these low-cost and easy-to-administer drugs for tuberculosis treatment. Recently, β-lactam sensitivity has been reported in strains resistant to classical tuberculosis therapy, resurging the interest in β-lactams for tuberculosis. However, a lack of understanding of the molecular underpinnings of this sensitivity has delayed exploration in the clinic. We performed gene expression and network analyses and in silico knockout simulations of genes associated with β-lactam sensitivity and genes associated with resistance to classical tuberculosis drugs to investigate regulatory interactions and identify key gene mediators. We found activation of the key inhibitor of β-lactam resistance, blaI, following classical drug treatment as well as transcriptional links between genes associated with β-lactam sensitivity and those associated with resistance to classical treatment, suggesting that regulatory links might explain collateral sensitivity to β-lactams. Our results support M. tuberculosis β-lactam sensitivity as a collateral consequence of the evolution of resistance to classical tuberculosis drugs, mediated through changes to transcriptional regulation. These findings support continued exploration of β-lactams for the treatment of patients infected with tuberculosis strains resistant to classical therapies. IMPORTANCE Tuberculosis remains a significant cause of global mortality, with strains resistant to classical drug treatment considered a major health concern by the World Health Organization. Challenging treatment regimens and difficulty accessing drugs in low-income communities have led to a high prevalence of strains resistant to multiple drugs, making the development of alternative therapies a priority. Although Mycobacterium tuberculosis is naturally resistant to β-lactam drugs, previous studies have shown sensitivity in strains resistant to classical drug treatment, but we currently lack understanding of the molecular underpinnings behind this phenomenon. We found that genes involved in β-lactam susceptibility are activated after classical drug treatment resulting from tight regulatory links with genes involved in drug resistance. Our study supports the hypothesis that β-lactam susceptibility observed in drug-resistant strains results from the underlying regulatory network of M. tuberculosis, supporting further exploration of the use of β-lactams for tuberculosis treatment.
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23
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Villa TG, Abril AG, Sánchez-Pérez A. Mastering the control of the Rho transcription factor for biotechnological applications. Appl Microbiol Biotechnol 2021; 105:4053-4071. [PMID: 33963893 DOI: 10.1007/s00253-021-11326-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 04/22/2021] [Accepted: 04/27/2021] [Indexed: 12/25/2022]
Abstract
The present review represents an update on the fundamental role played by the Rho factor, which facilitates the process of Rho-dependent transcription termination in the prokaryotic world; it also provides a summary of relevant mutations in the Rho factor and the insights they provide into the functions carried out by this protein. Furthermore, a section is dedicated to the putative future use of Rho (the 'taming' of Rho) to facilitate biotechnological processes and adapt them to different technological contexts. Novel bacterial strains can be designed, containing mutations in the rho gene, that are better suited for different biotechnological applications. This process can obtain novel microbial strains that are adapted to lower temperatures of fermentation, shorter production times, exhibit better nutrient utilization, or display other traits that are beneficial in productive Biotechnology. Additional important issues reviewed here include epistasis, the design of TATA boxes, the role of small RNAs, and the manipulation of clathrin-mediated endocytosis, by some pathogenic bacteria, to invade eukaryotic cells. KEY POINTS: • It is postulated that controlling the action of the prokaryotic Rho factor could generate major biotechnological improvements, such as an increase in bacterial productivity or a reduction of the microbial-specific growth rate. • The review also evaluates the putative impact of epistatic mechanisms on Biotechnology, both as possible responsible for unexpected failures in gene cloning and more important for the genesis of new strains for biotechnological applications • The use of clathrin-coated vesicles by intracellular bacterial microorganisms is included too and proposed as a putative delivery mechanism, for drugs and vaccines.
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Affiliation(s)
- Tomás G Villa
- Department of Microbiology and Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, La Coruña, 15706, Santiago de Compostela, Spain.
| | - Ana G Abril
- Department of Microbiology and Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, La Coruña, 15706, Santiago de Compostela, Spain.
| | - Angeles Sánchez-Pérez
- Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Sydney, NSW, 2006, Australia.
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Halder V, McDonnell B, Uthayakumar D, Usher J, Shapiro RS. Genetic interaction analysis in microbial pathogens: unravelling networks of pathogenesis, antimicrobial susceptibility and host interactions. FEMS Microbiol Rev 2021; 45:fuaa055. [PMID: 33145589 DOI: 10.1093/femsre/fuaa055] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 10/16/2020] [Indexed: 12/13/2022] Open
Abstract
Genetic interaction (GI) analysis is a powerful genetic strategy that analyzes the fitness and phenotypes of single- and double-gene mutant cells in order to dissect the epistatic interactions between genes, categorize genes into biological pathways, and characterize genes of unknown function. GI analysis has been extensively employed in model organisms for foundational, systems-level assessment of the epistatic interactions between genes. More recently, GI analysis has been applied to microbial pathogens and has been instrumental for the study of clinically important infectious organisms. Here, we review recent advances in systems-level GI analysis of diverse microbial pathogens, including bacterial and fungal species. We focus on important applications of GI analysis across pathogens, including GI analysis as a means to decipher complex genetic networks regulating microbial virulence, antimicrobial drug resistance and host-pathogen dynamics, and GI analysis as an approach to uncover novel targets for combination antimicrobial therapeutics. Together, this review bridges our understanding of GI analysis and complex genetic networks, with applications to diverse microbial pathogens, to further our understanding of virulence, the use of antimicrobial therapeutics and host-pathogen interactions. .
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Affiliation(s)
- Viola Halder
- Department of Molecular and Cellular Biology, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Brianna McDonnell
- Department of Molecular and Cellular Biology, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Deeva Uthayakumar
- Department of Molecular and Cellular Biology, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Jane Usher
- Medical Research Council Centre for Medical Mycology, University of Exeter, Geoffrey Pope Building, Stocker Road, Exeter EX4 4QD, UK
| | - Rebecca S Shapiro
- Department of Molecular and Cellular Biology, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
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Emerging macrolide resistance in Bordetella pertussis in mainland China: Findings and warning from the global pertussis initiative. LANCET REGIONAL HEALTH-WESTERN PACIFIC 2021; 8:100098. [PMID: 34327426 PMCID: PMC8315362 DOI: 10.1016/j.lanwpc.2021.100098] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 01/10/2021] [Accepted: 01/14/2021] [Indexed: 11/22/2022]
Abstract
Whooping cough, or pertussis, is a highly communicable infectious disease caused by the bacterium Bordetella pertussis. Vaccination once reduced the incidence of the disease, but a global resurgence of the infection happened during the past two decades, likely due to the waning immunity of vaccination. Macrolides such as erythromycin and azithromycin are the drugs of primary choice for treatment. In this personal view, we call for attention to macrolide-resistant B. pertussis (MRBP), which has emerged and prevailed in mainland China for years and are exclusively mediated by mutations in the 23S rRNA gene. Whether the prevalence of MRBP in China results from overuse of azithromycin in clinical medicine remains unknown. The incidence of MRBP is low in other countries, but this could be a technical illusion since China employs culture as the mainstream diagnostic method whereas nucleic-acid amplification test being widely used in other countries fail to test antimicrobial susceptibility. Given the increasingly frequent global travel that facilitates microbial transmission worldwide, there is a pressing need to perform international surveillance on MRBP to prevent the potential circulation of the organism. Finding alternative agents that possess good activity against B. pertussis is also urgently required.
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Amino Acid k-mer Feature Extraction for Quantitative Antimicrobial Resistance (AMR) Prediction by Machine Learning and Model Interpretation for Biological Insights. BIOLOGY 2020; 9:biology9110365. [PMID: 33126516 PMCID: PMC7694136 DOI: 10.3390/biology9110365] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 10/17/2020] [Accepted: 10/19/2020] [Indexed: 12/31/2022]
Abstract
Machine learning algorithms can learn mechanisms of antimicrobial resistance from the data of DNA sequence without any a priori information. Interpreting a trained machine learning algorithm can be exploited for validating the model and obtaining new information about resistance mechanisms. Different feature extraction methods, such as SNP calling and counting nucleotide k-mers have been proposed for presenting DNA sequences to the model. However, there are trade-offs between interpretability, computational complexity and accuracy for different feature extraction methods. In this study, we have proposed a new feature extraction method, counting amino acid k-mers or oligopeptides, which provides easier model interpretation compared to counting nucleotide k-mers and reaches the same or even better accuracy in comparison with different methods. Additionally, we have trained machine learning algorithms using different feature extraction methods and compared the results in terms of accuracy, model interpretability and computational complexity. We have built a new feature selection pipeline for extraction of important features so that new AMR determinants can be discovered by analyzing these features. This pipeline allows the construction of models that only use a small number of features and can predict resistance accurately.
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Álvarez-Martínez FJ, Barrajón-Catalán E, Micol V. Tackling Antibiotic Resistance with Compounds of Natural Origin: A Comprehensive Review. Biomedicines 2020; 8:E405. [PMID: 33050619 PMCID: PMC7601869 DOI: 10.3390/biomedicines8100405] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 10/08/2020] [Accepted: 10/09/2020] [Indexed: 12/13/2022] Open
Abstract
Drug-resistant bacteria pose a serious threat to human health worldwide. Current antibiotics are losing efficacy and new antimicrobial agents are urgently needed. Living organisms are an invaluable source of antimicrobial compounds. The antimicrobial activity of the most representative natural products of animal, bacterial, fungal and plant origin are reviewed in this paper. Their activity against drug-resistant bacteria, their mechanisms of action, the possible development of resistance against them, their role in current medicine and their future perspectives are discussed. Electronic databases such as PubMed, Scopus and ScienceDirect were used to search scientific contributions until September 2020, using relevant keywords. Natural compounds of heterogeneous origins have been shown to possess antimicrobial capabilities, including against antibiotic-resistant bacteria. The most commonly found mechanisms of antimicrobial action are related to protein biosynthesis and alteration of cell walls and membranes. Various natural compounds, especially phytochemicals, have shown synergistic capacity with antibiotics. There is little literature on the development of specific resistance mechanisms against natural antimicrobial compounds. New technologies such as -omics, network pharmacology and informatics have the potential to identify and characterize new natural antimicrobial compounds in the future. This knowledge may be useful for the development of future therapeutic strategies.
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Affiliation(s)
- Francisco Javier Álvarez-Martínez
- Institute of Research, Development and Innovation in Health Biotechnology of Elche (IDiBE), Universitas Miguel Hernández (UMH), 03202 Elche, Spain; (F.J.Á.-M.); (V.M.)
| | - Enrique Barrajón-Catalán
- Institute of Research, Development and Innovation in Health Biotechnology of Elche (IDiBE), Universitas Miguel Hernández (UMH), 03202 Elche, Spain; (F.J.Á.-M.); (V.M.)
| | - Vicente Micol
- Institute of Research, Development and Innovation in Health Biotechnology of Elche (IDiBE), Universitas Miguel Hernández (UMH), 03202 Elche, Spain; (F.J.Á.-M.); (V.M.)
- CIBER, Fisiopatología de la Obesidad y la Nutrición, CIBERobn, Instituto de Salud Carlos III (CB12/03/30038), 28220 Madrid, Spain
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Lewicka E, Dolowy P, Godziszewska J, Litwin E, Ludwiczak M, Jagura-Burdzy G. Transcriptional Organization of the Stability Module of Broad-Host-Range Plasmid RA3, from the IncU Group. Appl Environ Microbiol 2020; 86:e00847-20. [PMID: 32532870 PMCID: PMC7414963 DOI: 10.1128/aem.00847-20] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 06/06/2020] [Indexed: 02/06/2023] Open
Abstract
The broad-host-range (BHR) conjugative plasmids have developed diverse adaptive mechanisms defining the range of their promiscuity. The BHR conjugative RA3 plasmid, the archetype of the IncU group, can transfer between, replicate in, and be maintained in representatives of Alpha-, Beta-, and Gammaproteobacteria Its stability module encompasses ten open reading frames (ORFs) apparently organized into five operons, all transcribed in the same direction from several strong promoters that are tightly regulated either by autorepressors or by global plasmid-encoded regulators. In this paper, we demonstrate that owing to an efficient RNA polymerase (RNAP) read-through, the transcription from the first promoter, orf02p, may continue through the whole module. Moreover, an analysis of mRNA produced from the wild-type (WT) stability module and its deletion variants deprived of particular internal transcription initiation sites reveals that in fact each operon may be transcribed from any upstream promoter, giving rise to multicistronic transcripts of variable length and creating an additional level of gene expression control by transcript dosage adjustment. The gene expression patterns differ among various hosts, indicating that promoter recognition, regulation, and the RNAP read-through mechanisms are modulated in a species-specific manner.IMPORTANCE The efficiently disseminating conjugative or mobilizable BHR plasmids play key roles in the horizontal spread of genetic information between closely related and phylogenetically distant species, which can be harmful from the medical, veterinary, or industrial point of view. Understanding the mechanisms determining the plasmid's ability to function in diverse hosts is essential to help limit the spread of undesirable plasmid-encoded traits, e.g., antibiotic resistance. The range of a plasmid's promiscuity depends on the adaptations of its transfer, replication, and stability functions to the various hosts. IncU plasmids, with the archetype plasmid RA3, are considered to constitute a reservoir of antibiotic resistance genes in aquatic environments; however, the molecular mechanisms determining their adaptability to a broad range of hosts are rather poorly characterized. Here, we present the transcriptional organization of the stability module and show that the gene transcript dosage effect is an important determinant of the stable maintenance of RA3 in different hosts.
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Affiliation(s)
- Ewa Lewicka
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
| | - Patrycja Dolowy
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
| | - Jolanta Godziszewska
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
| | - Emilia Litwin
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
| | - Marta Ludwiczak
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
| | - Grazyna Jagura-Burdzy
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
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Jacopin E, Lehtinen S, Débarre F, Blanquart F. Factors favouring the evolution of multidrug resistance in bacteria. J R Soc Interface 2020. [PMCID: PMC7423433 DOI: 10.1098/rsif.2020.0105] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The evolution of multidrug antibiotic resistance in commensal bacteria is an important public health concern. Commensal bacteria such as Escherichia coli, Streptococcus pneumoniae or Staphylococcus aureus, are also opportunistic pathogens causing a large fraction of the community-acquired and hospital-acquired bacterial infections. Multidrug resistance (MDR) makes these infections harder to treat with antibiotics and may thus cause substantial additional morbidity and mortality. Here, we develop an evolutionary epidemiology model to identify the factors favouring the evolution of MDR in commensal bacteria. The model describes the evolution of antibiotic resistance in a commensal bacterial species evolving in a host population subjected to multiple antibiotic treatments. We combine statistical analysis of a large number of simulations and mathematical analysis to understand the model behaviour. We find that MDR evolves more readily when it is less costly than expected from the combinations of single resistances (positive epistasis). MDR frequently evolves when bacteria are in contact with multiple drugs prescribed in the host population, even if individual hosts are only treated with a single drug at a time. MDR is favoured when the host population is structured in different classes that vary in their rates of antibiotic treatment. However, under most circumstances, recombination between loci involved in resistance does not meaningfully affect the equilibrium frequency of MDR. Together, these results suggest that MDR is a frequent evolutionary outcome in commensal bacteria that encounter the variety of antibiotics prescribed in the host population. A better characterization of the variability in antibiotic use across the host population (e.g. across age classes or geographical location) would help predict which MDR genotypes will most readily evolve.
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Affiliation(s)
- Eliott Jacopin
- Centre for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France
- AgroParisTech, Université Paris-Saclay, Paris, France
| | - Sonja Lehtinen
- The Oxford Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Institute of Integrative Biology, Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
| | - Florence Débarre
- Sorbonne Université, CNRS, Université Paris Est Créteil, Université de Paris, INRAE, IRD, Institute of Ecology and Environmental sciences of Paris, iEES-Paris (UMR 7618), 75005 Paris, France
| | - François Blanquart
- Centre for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France
- Infection Antimicrobials Modelling Evolution, UMR 1137, INSERM, Université de Paris, Paris, France
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Al-Ajmi D, Rahman S, Banu S. Occurrence, virulence genes, and antimicrobial profiles of Escherichia coli O157 isolated from ruminants slaughtered in Al Ain, United Arab Emirates. BMC Microbiol 2020; 20:210. [PMID: 32677884 PMCID: PMC7364618 DOI: 10.1186/s12866-020-01899-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 07/12/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Shiga toxin-producing Escherichia coli (STEC) is a major source of food-borne illness around the world. E. coli O157 has been widely reported as the most common STEC serogroup and has emerged as an important enteric pathogen. Cattle, in particular have been identified as a major E. coli O157:H7 reservoir of human infections; however, the prevalence of this organism in camels, sheep, and goats is less understood. The aim of this study was to evaluate the occurrence and concentration of E. coli serotype O157 in the feces of healthy camels (n = 140), cattle (n = 137), sheep (n = 141) and goats (n = 150) slaughtered in United Arab Emirates (UAE) for meat consumption between September 2017 and August 2018. We used immunomagnetic separation coupled with a culture-plating method to detect E. coli O157. Non-sorbitol fermenting colonies were assessed via latex-agglutination testing, and positive cultures were analyzed by performing polymerase chain reactions to detect genes encoding attaching and effacing protein (eaeA), hemolysin A (hlyA, also known as ehxA) and Shiga toxin (stx1 and stx2), and E. coli O157:H7 specific genes (rfb O157, uidA, and fliC). All E. coli O157 isolates were analyzed for their susceptibility to 20 selected antimicrobials. RESULTS E. coli O157 was observed in camels, goats, and cattle fecal samples at abundances of 4.3, 2, and 1.46%, respectively, but it was undetectable in sheep feces. The most prevalent E. coli O157 gene in all STEC isolates was stx2;, whereas, stx1 was not detected in any of the samples. The fecal samples from camels, goats, and cattle harbored E. coli O157 isolates that were 100% susceptible to cefotaxime, chloramphenicol, ciprofloxacin, norfloxacin, and polymyxin B. CONCLUSION To our knowledge, this is the first report on the occurrence of E. coli O157 in slaughter animals in the UAE. Our results clearly demonstrate the presence of E. coli O157 in slaughtered animals, which could possibly contaminate meat products intended for human consumption.
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Affiliation(s)
- Dawood Al-Ajmi
- Department of Integrative Agriculture, College of Food and Agriculture, United Arab Emirates University (UAEU), Al Ain, United Arab Emirates.
| | - Shafeeq Rahman
- Department of Integrative Agriculture, College of Food and Agriculture, United Arab Emirates University (UAEU), Al Ain, United Arab Emirates
| | - Sharmila Banu
- Department of Integrative Agriculture, College of Food and Agriculture, United Arab Emirates University (UAEU), Al Ain, United Arab Emirates
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Candida albicans Genetic Background Influences Mean and Heterogeneity of Drug Responses and Genome Stability during Evolution in Fluconazole. mSphere 2020; 5:5/3/e00480-20. [PMID: 32581072 PMCID: PMC7316494 DOI: 10.1128/msphere.00480-20] [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] [Indexed: 01/09/2023] Open
Abstract
Antimicrobial resistance is an evolutionary phenomenon with clinical implications. We tested how replicates from diverse strains of Candida albicans, a prevalent human fungal pathogen, evolve in the commonly prescribed antifungal drug fluconazole. Replicates on average increased in fitness in the level of drug they were evolved to, with the least fit parental strains improving the most. Very few replicates increased resistance above the drug level they were evolved in. Notably, many replicates increased in genome size and changed in drug tolerance (a drug response where a subpopulation of cells grow slowly in high levels of drug), and variability among replicates in fitness, tolerance, and genome size was higher in strains that initially were more sensitive to the drug. Genetic background influenced the average degree of adaptation and the evolved variability of many phenotypes, highlighting that different strains from the same species may respond and adapt very differently during adaptation. The importance of within-species diversity in determining the evolutionary potential of a population to evolve drug resistance or tolerance is not well understood, including in eukaryotic pathogens. To examine the influence of genetic background, we evolved replicates of 20 different clinical isolates of Candida albicans, a human fungal pathogen, in fluconazole, the commonly used antifungal drug. The isolates hailed from the major C. albicans clades and had different initial levels of drug resistance and tolerance to the drug. The majority of replicates rapidly increased in fitness in the evolutionary environment, with the degree of improvement inversely correlated with parental strain fitness in the drug. Improvement was largely restricted to up to the evolutionary level of drug: only 4% of the evolved replicates increased resistance (MIC) above the evolutionary level of drug. Prevalent changes were altered levels of drug tolerance (slow growth of a subpopulation of cells at drug concentrations above the MIC) and increased diversity of genome size. The prevalence and predominant direction of these changes differed in a strain-specific manner, but neither correlated directly with parental fitness or improvement in fitness. Rather, low parental strain fitness was correlated with high levels of heterogeneity in fitness, tolerance, and genome size among evolved replicates. Thus, parental strain background is an important determinant in mean improvement to the evolutionary environment as well as the diversity of evolved phenotypes, and the range of possible responses of a pathogen to an antimicrobial drug cannot be captured by in-depth study of a single strain background. IMPORTANCE Antimicrobial resistance is an evolutionary phenomenon with clinical implications. We tested how replicates from diverse strains of Candida albicans, a prevalent human fungal pathogen, evolve in the commonly prescribed antifungal drug fluconazole. Replicates on average increased in fitness in the level of drug they were evolved to, with the least fit parental strains improving the most. Very few replicates increased resistance above the drug level they were evolved in. Notably, many replicates increased in genome size and changed in drug tolerance (a drug response where a subpopulation of cells grow slowly in high levels of drug), and variability among replicates in fitness, tolerance, and genome size was higher in strains that initially were more sensitive to the drug. Genetic background influenced the average degree of adaptation and the evolved variability of many phenotypes, highlighting that different strains from the same species may respond and adapt very differently during adaptation.
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Hypermutator Pseudomonas aeruginosa Exploits Multiple Genetic Pathways To Develop Multidrug Resistance during Long-Term Infections in the Airways of Cystic Fibrosis Patients. Antimicrob Agents Chemother 2020; 64:AAC.02142-19. [PMID: 32071060 DOI: 10.1128/aac.02142-19] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 12/20/2019] [Indexed: 12/30/2022] Open
Abstract
Pseudomonas aeruginosa exploits intrinsic and acquired resistance mechanisms to resist almost every antibiotic used in chemotherapy. Antimicrobial resistance in P. aeruginosa isolates recovered from cystic fibrosis (CF) patients is further enhanced by the occurrence of hypermutator strains, a hallmark of chronic infections in CF patients. However, the within-patient genetic diversity of P. aeruginosa populations related to antibiotic resistance remains unexplored. Here, we show the evolution of the mutational resistome profile of a P. aeruginosa hypermutator lineage by performing longitudinal and transversal analyses of isolates collected from a CF patient throughout 20 years of chronic infection. Our results show the accumulation of thousands of mutations, with an overall evolutionary history characterized by purifying selection. However, mutations in antibiotic resistance genes appear to have been positively selected, driven by antibiotic treatment. Antibiotic resistance increased as infection progressed toward the establishment of a population constituted by genotypically diversified coexisting sublineages, all of which converged to multidrug resistance. These sublineages emerged by parallel evolution through distinct evolutionary pathways, which affected genes of the same functional categories. Interestingly, ampC and ftsI, encoding the β-lactamase and penicillin-binding protein 3, respectively, were found to be among the most frequently mutated genes. In fact, both genes were targeted by multiple independent mutational events, which led to a wide diversity of coexisting alleles underlying β-lactam resistance. Our findings indicate that hypermutators, apart from boosting antibiotic resistance evolution by simultaneously targeting several genes, favor the emergence of adaptive innovative alleles by clustering beneficial/compensatory mutations in the same gene, hence expanding P. aeruginosa strategies for persistence.
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Antimicrobial Resistance Strategies: Are We Approaching the End? JOURNAL OF PURE AND APPLIED MICROBIOLOGY 2020. [DOI: 10.22207/jpam.14.1.11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Hernando-Amado S, Sanz-García F, Martínez JL. Antibiotic Resistance Evolution Is Contingent on the Quorum-Sensing Response in Pseudomonas aeruginosa. Mol Biol Evol 2020; 36:2238-2251. [PMID: 31228244 DOI: 10.1093/molbev/msz144] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Different works have explored independently the evolution toward antibiotic resistance and the role of eco-adaptive mutations in the adaptation to a new habitat (as the infected host) of bacterial pathogens. However, knowledge about the connection between both processes is still limited. We address this issue by comparing the evolutionary trajectories toward antibiotic resistance of a Pseudomonas aeruginosa lasR defective mutant and its parental wild-type strain, when growing in presence of two ribosome-targeting antibiotics. Quorum-sensing lasR defective mutants are selected in P. aeruginosa populations causing chronic infections. Further, we observed they are also selected in vitro as a first adaptation for growing in culture medium. By using experimental evolution and whole-genome sequencing, we found that the evolutionary trajectories of P. aeruginosa in presence of these antibiotics are different in lasR defective and in wild-type backgrounds, both at the phenotypic and the genotypic levels. Recreation of a set of mutants in both genomic backgrounds (either wild type or lasR defective) allowed us to determine the existence of negative epistatic interactions between lasR and antibiotic resistance determinants. These epistatic interactions could lead to mutual contingency in the evolution of antibiotic resistance when P. aeruginosa colonizes a new habitat in presence of antibiotics. If lasR mutants are selected first, this would constraint antibiotic resistance evolution. Conversely, when resistance mutations (at least those studied in the present work) are selected, lasR mutants may not be selected in presence of antibiotics. These results underlie the importance of contingency and epistatic interactions in modulating antibiotic resistance evolution.
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Barbosa C, Römhild R, Rosenstiel P, Schulenburg H. Evolutionary stability of collateral sensitivity to antibiotics in the model pathogen Pseudomonas aeruginosa. eLife 2019; 8:e51481. [PMID: 31658946 PMCID: PMC6881144 DOI: 10.7554/elife.51481] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 10/21/2019] [Indexed: 12/27/2022] Open
Abstract
Evolution is at the core of the impending antibiotic crisis. Sustainable therapy must thus account for the adaptive potential of pathogens. One option is to exploit evolutionary trade-offs, like collateral sensitivity, where evolved resistance to one antibiotic causes hypersensitivity to another one. To date, the evolutionary stability and thus clinical utility of this trade-off is unclear. We performed a critical experimental test on this key requirement, using evolution experiments with Pseudomonas aeruginosa, and identified three main outcomes: (i) bacteria commonly failed to counter hypersensitivity and went extinct; (ii) hypersensitivity sometimes converted into multidrug resistance; and (iii) resistance gains frequently caused re-sensitization to the previous drug, thereby maintaining the trade-off. Drug order affected the evolutionary outcome, most likely due to variation in the effect size of collateral sensitivity, epistasis among adaptive mutations, and fitness costs. Our finding of robust genetic trade-offs and drug-order effects can guide design of evolution-informed antibiotic therapy.
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Affiliation(s)
- Camilo Barbosa
- Department of Evolutionary Ecology and GeneticsUniversity of KielKielGermany
| | - Roderich Römhild
- Department of Evolutionary Ecology and GeneticsUniversity of KielKielGermany
- Max Planck Institute for Evolutionary BiologyPlönGermany
| | | | - Hinrich Schulenburg
- Department of Evolutionary Ecology and GeneticsUniversity of KielKielGermany
- Max Planck Institute for Evolutionary BiologyPlönGermany
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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. Strains of Escherichia coli from the long-term evolution experiment (LTEE) have independently evolved for multiple decades and tens of thousands of generations in the absence of antibiotics; this study shows that evolution and diversification of a single bacterial species in an antibiotic-free environment can render the subsequent evolution of resistance unpredictable.
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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
- * E-mail:
| | - 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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Adaptive walks on high-dimensional fitness landscapes and seascapes with distance-dependent statistics. Theor Popul Biol 2019; 130:13-49. [PMID: 31605706 DOI: 10.1016/j.tpb.2019.09.011] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 09/07/2019] [Accepted: 09/12/2019] [Indexed: 11/21/2022]
Abstract
The dynamics of evolution is intimately shaped by epistasis - interactions between genetic elements which cause the fitness-effect of combinations of mutations to be non-additive. Analyzing evolutionary dynamics that involves large numbers of epistatic mutations is intrinsically difficult. A crucial feature is that the fitness landscape in the vicinity of the current genome depends on the evolutionary history. A key step is thus developing models that enable study of the effects of past evolution on future evolution. In this work, we introduce a broad class of high-dimensional random fitness landscapes for which the correlations between fitnesses of genomes are a general function of genetic distance. Their Gaussian character allows for tractable computational as well as analytic understanding. We study the properties of these landscapes focusing on the simplest evolutionary process: random adaptive (uphill) walks. Conventional measures of "ruggedness" are shown to not much affect such adaptive walks. Instead, the long-distance statistics of epistasis cause all properties to be highly conditional on past evolution, determining the statistics of the local landscape (the distribution of fitness-effects of available mutations and combinations of these), as well as the global geometry of evolutionary trajectories. In order to further explore the effects of conditioning on past evolution, we model the effects of slowly changing environments. At long times, such fitness "seascapes" cause a statistical steady state with highly intermittent evolutionary dynamics: populations undergo bursts of rapid adaptation, interspersed with periods in which adaptive mutations are rare and the population waits for more new directions to be opened up by changes in the environment. Finally, we discuss prospects for studying more complex evolutionary dynamics and on broader classes of high-dimensional landscapes and seascapes.
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Learning the pattern of epistasis linking genotype and phenotype in a protein. Nat Commun 2019; 10:4213. [PMID: 31527666 PMCID: PMC6746860 DOI: 10.1038/s41467-019-12130-8] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 08/19/2019] [Indexed: 02/02/2023] Open
Abstract
Understanding the pattern of epistasis-the non-independence of mutations-is critical for relating genotype and phenotype. However, the combinatorial complexity of potential epistatic interactions has severely limited the analysis of this problem. Using new mutational approaches, we report a comprehensive experimental study of all 213 mutants that link two phenotypically distinct variants of the Entacmaea quadricolor fluorescent protein-an opportunity to examine epistasis up to the 13th order. The data show the existence of many high-order epistatic interactions between mutations, but also reveal extraordinary sparsity, enabling novel experimental and computational strategies for learning the relevant epistasis. We demonstrate that such information, in turn, can be used to accurately predict phenotypes in practical situations where the number of measurements is limited. Finally, we show how the observed epistasis shapes the solution space of single-mutation trajectories between the parental fluorescent proteins, informative about the protein's evolutionary potential. This work provides conceptual and experimental strategies to profoundly characterize epistasis in a protein, relevant to both natural and laboratory evolution.
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Graves JL, Ewunkem AJ, Ward J, Staley C, Thomas MD, Rhinehardt KL, Han J, Harrison SH. Experimental evolution of gallium resistance in Escherichia coli. EVOLUTION MEDICINE AND PUBLIC HEALTH 2019; 2019:169-180. [PMID: 31890209 PMCID: PMC6928379 DOI: 10.1093/emph/eoz025] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Accepted: 08/29/2019] [Indexed: 12/26/2022]
Abstract
Background and Objectives Metallic antimicrobial materials are of growing interest due to their potential to control pathogenic and multidrug-resistant bacteria. Yet we do not know if utilizing these materials can lead to genetic adaptations that produce even more dangerous bacterial varieties. Methodology Here we utilize experimental evolution to produce strains of Escherichia coli K-12 MG1655 resistant to, the iron analog, gallium nitrate (Ga(NO3)3). Whole genome sequencing was utilized to determine genomic changes associated with gallium resistance. Computational modeling was utilized to propose potential molecular mechanisms of resistance. Results By day 10 of evolution, increased gallium resistance was evident in populations cultured in medium containing a sublethal concentration of gallium. Furthermore, these populations showed increased resistance to ionic silver and iron (III), but not iron (II) and no increase in traditional antibiotic resistance compared with controls and the ancestral strain. In contrast, the control populations showed increased resistance to rifampicin relative to the gallium-resistant and ancestral population. Genomic analysis identified hard selective sweeps of mutations in several genes in the gallium (III)-resistant lines including: fecA (iron citrate outer membrane transporter), insl1 (IS30 tranposase) one intergenic mutations arsC →/→ yhiS; (arsenate reductase/pseudogene) and in one pseudogene yedN ←; (iapH/yopM family). Two additional significant intergenic polymorphisms were found at frequencies > 0.500 in fepD ←/→ entS (iron-enterobactin transporter subunit/enterobactin exporter, iron-regulated) and yfgF ←/→ yfgG (cyclic-di-GMP phosphodiesterase, anaerobic/uncharacterized protein). The control populations displayed mutations in the rpoB gene, a gene associated with rifampicin resistance. Conclusions This study corroborates recent results observed in experiments utilizing pathogenic Pseudomonas strains that also showed that Gram-negative bacteria can rapidly evolve resistance to an atom that mimics an essential micronutrient and shows the pleiotropic consequences associated with this adaptation. Lay summary We utilize experimental evolution to produce strains of Escherichia coli K-12 MG1655 resistant to, the iron analog, gallium nitrate (Ga(NO3)3). Whole genome sequencing was utilized to determine genomic changes associated with gallium resistance. Computational modeling was utilized to propose potential molecular mechanisms of resistance.
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Affiliation(s)
- Joseph L Graves
- Department of Nanoengineering, Joint School of Nanoscience & Nanoengineering, North Carolina A&T State University & UNC Greensboro, Greensboro, NC, USA.,BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, USA
| | - Akamu J Ewunkem
- Department of Nanoengineering, Joint School of Nanoscience & Nanoengineering, North Carolina A&T State University & UNC Greensboro, Greensboro, NC, USA.,BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, USA
| | - Jason Ward
- High School Science Teacher, Davie Public High School, Davie, NC, USA
| | | | - Misty D Thomas
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, USA.,Department of Biology, North Carolina A&T State University, Greensboro, NC, USA
| | - Kristen L Rhinehardt
- Department of Nanoengineering, Joint School of Nanoscience & Nanoengineering, North Carolina A&T State University & UNC Greensboro, Greensboro, NC, USA.,BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, USA
| | - Jian Han
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, USA.,Department of Biology, North Carolina A&T State University, Greensboro, NC, USA
| | - Scott H Harrison
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, USA.,Department of Biology, North Carolina A&T State University, Greensboro, NC, USA
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Hubbard ATM, Jafari NV, Feasey N, Rohn JL, Roberts AP. Effect of Environment on the Evolutionary Trajectories and Growth Characteristics of Antibiotic-Resistant Escherichia coli Mutants. Front Microbiol 2019; 10:2001. [PMID: 31555237 PMCID: PMC6722461 DOI: 10.3389/fmicb.2019.02001] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 08/15/2019] [Indexed: 11/21/2022] Open
Abstract
The fitness cost to bacteria of acquisition of resistance determinants is critically under-investigated, and the identification and exploitation of these fitness costs may lead to novel therapeutic strategies that prevent the emergence of antimicrobial resistance. Here we used Escherichia coli and amoxicillin–clavulanic acid (AMC) resistance as a model to understand how the artificial environments utilized in studies of bacterial fitness could affect the emergence of resistance and associated fitness costs. Further, we explored the predictive value of this data when strains were grown in the more physiologically relevant environments of urine and urothelial organoids. Resistant E. coli isolates were selected for following 24-h exposure to sub-inhibitory concentrations of AMC in either M9, ISO, or LB, followed by growth on LB agar containing AMC. No resistant colonies emerged following growth in M9, whereas resistant isolates were detected from cultures grown in ISO and LB. We observed both within and between media-type variability in the levels of resistance and fitness of the resistant mutants grown in LB. MICs and fitness of these resistant strains in different media (M9, ISO, LB, human urine, and urothelial organoids) showed considerable variation. Media can therefore have a direct effect on the isolation of mutants that confer resistance to AMC and these mutants can exhibit unpredictable MIC and fitness profiles under different growth conditions. This preliminary study highlights the risks in relying on a single culture protocol as a model system to predict the behavior and treatment response of bacteria in vivo and highlights the importance of developing comprehensive experimental designs to ensure effective translation of diagnostic procedures to successful clinical outcomes.
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Affiliation(s)
- Alasdair T M Hubbard
- Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.,Centre for Drugs and Diagnostics, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Nazila V Jafari
- Centre for Urological Biology, Department of Renal Medicine, University College London, London, United Kingdom
| | - Nicholas Feasey
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.,Malawi-Liverpool-Wellcome Trust Clinical Research Programme, University of Malawi, College of Medicine, Blantyre, Malawi
| | - Jennifer L Rohn
- Centre for Urological Biology, Department of Renal Medicine, University College London, London, United Kingdom
| | - Adam P Roberts
- Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.,Centre for Drugs and Diagnostics, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
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Dunai A, Spohn R, Farkas Z, Lázár V, Györkei Á, Apjok G, Boross G, Szappanos B, Grézal G, Faragó A, Bodai L, Papp B, Pál C. Rapid decline of bacterial drug-resistance in an antibiotic-free environment through phenotypic reversion. eLife 2019; 8:e47088. [PMID: 31418687 PMCID: PMC6707769 DOI: 10.7554/elife.47088] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 08/05/2019] [Indexed: 11/18/2022] Open
Abstract
Antibiotic resistance typically induces a fitness cost that shapes the fate of antibiotic-resistant bacterial populations. However, the cost of resistance can be mitigated by compensatory mutations elsewhere in the genome, and therefore the loss of resistance may proceed too slowly to be of practical importance. We present our study on the efficacy and phenotypic impact of compensatory evolution in Escherichia coli strains carrying multiple resistance mutations. We have demonstrated that drug-resistance frequently declines within 480 generations during exposure to an antibiotic-free environment. The extent of resistance loss was found to be generally antibiotic-specific, driven by mutations that reduce both resistance level and fitness costs of antibiotic-resistance mutations. We conclude that phenotypic reversion to the antibiotic-sensitive state can be mediated by the acquisition of additional mutations, while maintaining the original resistance mutations. Our study indicates that restricting antimicrobial usage could be a useful policy, but for certain antibiotics only.
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Affiliation(s)
- Anett Dunai
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
- Doctoral School in Biology, Faculty of Science and InformaticsUniversity of SzegedSzegedHungary
| | - Réka Spohn
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
| | - Zoltán Farkas
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
| | - Viktória Lázár
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
| | - Ádám Györkei
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
| | - Gábor Apjok
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
- Doctoral School in Biology, Faculty of Science and InformaticsUniversity of SzegedSzegedHungary
| | - Gábor Boross
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
| | - Balázs Szappanos
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
| | - Gábor Grézal
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
| | - Anikó Faragó
- Doctoral School in Biology, Faculty of Science and InformaticsUniversity of SzegedSzegedHungary
- Department of Biochemistry and Molecular BiologyUniversity of SzegedSzegedHungary
| | - László Bodai
- Department of Biochemistry and Molecular BiologyUniversity of SzegedSzegedHungary
| | - Balázs Papp
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
| | - Csaba Pál
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research CentreHungarian Academy of SciencesSzegedHungary
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Apjok G, Boross G, Nyerges Á, Fekete G, Lázár V, Papp B, Pál C, Csörgő B. Limited Evolutionary Conservation of the Phenotypic Effects of Antibiotic Resistance Mutations. Mol Biol Evol 2019; 36:1601-1611. [PMID: 31058961 PMCID: PMC6657729 DOI: 10.1093/molbev/msz109] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [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
Multidrug-resistant clinical isolates are common in certain pathogens, but rare in others. This pattern may be due to the fact that mutations shaping resistance have species-specific effects. To investigate this issue, we transferred a range of resistance-conferring mutations and a full resistance gene into Escherichia coli and closely related bacteria. We found that resistance mutations in one bacterial species frequently provide no resistance, in fact even yielding drug hypersensitivity in close relatives. In depth analysis of a key gene involved in aminoglycoside resistance (trkH) indicated that preexisting mutations in other genes-intergenic epistasis-underlie such extreme differences in mutational effects between species. Finally, reconstruction of adaptive landscapes under multiple antibiotic stresses revealed that mutations frequently provide multidrug resistance or elevated drug susceptibility (i.e., collateral sensitivity) only with certain combinations of other resistance mutations. We conclude that resistance and collateral sensitivity are contingent upon the genetic makeup of the bacterial population, and such contingency could shape the long-term fate of resistant bacteria. These results underlie the importance of species-specific treatment strategies.
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Affiliation(s)
- Gábor Apjok
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary
| | - Gábor Boross
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary
- Department of Biology, Stanford University, Stanford, CA
| | - Ákos Nyerges
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary
| | - Gergely Fekete
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary
| | - Viktória Lázár
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary
- Technion – Israel Institute of Technology, Faculty of Biology, Haifa, Israel
| | - Balázs Papp
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary
| | - Csaba Pál
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary
| | - Bálint Csörgő
- Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA
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Naidenov B, Lim A, Willyerd K, Torres NJ, Johnson WL, Hwang HJ, Hoyt P, Gustafson JE, Chen C. Pan-Genomic and Polymorphic Driven Prediction of Antibiotic Resistance in Elizabethkingia. Front Microbiol 2019; 10:1446. [PMID: 31333599 PMCID: PMC6622151 DOI: 10.3389/fmicb.2019.01446] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Accepted: 06/07/2019] [Indexed: 01/21/2023] Open
Abstract
The Elizabethkingia are a genetically diverse genus of emerging pathogens that exhibit multidrug resistance to a range of common antibiotics. Two representative species, Elizabethkingia bruuniana and E. meningoseptica, were phenotypically tested to determine minimum inhibitory concentrations (MICs) for five antibiotics. Ultra-long read sequencing with Oxford Nanopore Technologies (ONT) and subsequent de novo assembly produced complete, gapless circular genomes for each strain. Alignment based annotation with Prokka identified 5,480 features in E. bruuniana and 5,203 features in E. meningoseptica, where none of these identified genes or gene combinations corresponded to observed phenotypic resistance values. Pan-genomic analysis, performed with an additional 19 Elizabethkingia strains, identified a core-genome size of 2,658,537 bp, 32 uniquely identifiable intrinsic chromosomal antibiotic resistance core-genes and 77 antibiotic resistance pan-genes. Using core-SNPs and pan-genes in combination with six machine learning (ML) algorithms, binary classification of clindamycin and vancomycin resistance achieved f1 scores of 0.94 and 0.84, respectively. Performance on the more challenging multiclass problem for fusidic acid, rifampin and ciprofloxacin resulted in f1 scores of 0.70, 0.75, and 0.54, respectively. By producing two sets of quality biological predictors, pan-genome genes and core-genome SNPs, from long-read sequence data and applying an ensemble of ML techniques, our results demonstrated that accurate phenotypic inference, at multiple AMR resolutions, can be achieved.
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Affiliation(s)
- Bryan Naidenov
- Department of Biochemistry and Molecular Biology, 246 Noble Research Center, Oklahoma State University, Stillwater, OK, United States
| | - Alexander Lim
- Department of Biochemistry and Molecular Biology, 246 Noble Research Center, Oklahoma State University, Stillwater, OK, United States
| | - Karyn Willyerd
- Department of Biochemistry and Molecular Biology, 246 Noble Research Center, Oklahoma State University, Stillwater, OK, United States
| | - Nathanial J. Torres
- Department of Cell Biology, Microbiology and Molecular Biology, University of South Florida, Tampa, FL, United States
| | - William L. Johnson
- Department of Biochemistry and Molecular Biology, 246 Noble Research Center, Oklahoma State University, Stillwater, OK, United States
| | - Hong Jin Hwang
- 110F Henry Bellmon Research Center, Bioinformatics Graduate Certificate Program and Genomics Core Facility, Oklahoma State University, Stillwater, OK, United States
| | - Peter Hoyt
- Department of Biochemistry and Molecular Biology, 246 Noble Research Center, Oklahoma State University, Stillwater, OK, United States
- 110F Henry Bellmon Research Center, Bioinformatics Graduate Certificate Program and Genomics Core Facility, Oklahoma State University, Stillwater, OK, United States
| | - John E. Gustafson
- Department of Biochemistry and Molecular Biology, 246 Noble Research Center, Oklahoma State University, Stillwater, OK, United States
| | - Charles Chen
- Department of Biochemistry and Molecular Biology, 246 Noble Research Center, Oklahoma State University, Stillwater, OK, United States
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Lehtinen S, Blanquart F, Lipsitch M, Fraser C. On the evolutionary ecology of multidrug resistance in bacteria. PLoS Pathog 2019; 15:e1007763. [PMID: 31083687 PMCID: PMC6532944 DOI: 10.1371/journal.ppat.1007763] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 05/23/2019] [Accepted: 04/15/2019] [Indexed: 11/23/2022] Open
Abstract
Resistance against different antibiotics appears on the same bacterial strains more often than expected by chance, leading to high frequencies of multidrug resistance. There are multiple explanations for this observation, but these tend to be specific to subsets of antibiotics and/or bacterial species, whereas the trend is pervasive. Here, we consider the question in terms of strain ecology: explaining why resistance to different antibiotics is often seen on the same strain requires an understanding of the competition between strains with different resistance profiles. This work builds on models originally proposed to explain another aspect of strain competition: the stable coexistence of antibiotic sensitivity and resistance observed in a number of bacterial species. We first identify a partial structural similarity in these models: either strain or host population structure stratifies the pathogen population into evolutionarily independent sub-populations and introduces variation in the fitness effect of resistance between these sub-populations, thus creating niches for sensitivity and resistance. We then generalise this unified underlying model to multidrug resistance and show that models with this structure predict high levels of association between resistance to different drugs and high multidrug resistance frequencies. We test predictions from this model in six bacterial datasets and find them to be qualitatively consistent with observed trends. The higher than expected frequencies of multidrug resistance are often interpreted as evidence that these strains are out-competing strains with lower resistance multiplicity. Our work provides an alternative explanation that is compatible with long-term stability in resistance frequencies.
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Affiliation(s)
- Sonja Lehtinen
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - François Blanquart
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France
- IAME, UMR 1137, INSERM, Université Paris Diderot, Paris, France
| | - Marc Lipsitch
- Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Departments of Epidemiology and Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Christophe Fraser
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
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Hoeksema M, Jonker MJ, Brul S, Ter Kuile BH. Effects of a previously selected antibiotic resistance on mutations acquired during development of a second resistance in Escherichia coli. BMC Genomics 2019; 20:284. [PMID: 30975082 PMCID: PMC6458618 DOI: 10.1186/s12864-019-5648-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 03/27/2019] [Indexed: 12/19/2022] Open
Abstract
Background The effect of mutations conferring antibiotic resistance can depend on the genetic background. To determine if a previously de novo acquired antibiotic resistance influences the adaptation to a second antibiotic, antibiotic resistance was selected for by exposure to stepwise increasing sublethal levels of amoxicillin, enrofloxacin, kanamycin, or tetracycline. E. coli populations adapted to either a single or two antibiotics sequentially were characterized using whole genome population sequencing and MIC measurements. Results In a wild-type background, adaptation to any of the antibiotics resulted in the appearance of well-known mutations, as well as a number of mutated genes not known to be associated with antibiotic resistance. Development of a second resistance in a strain with an earlier acquired resistance to a different antibiotic did not always result in the appearance of all mutations associated with resistance in a wild-type background. In general, a more varied set of mutations was acquired during secondary adaptation. The ability of E. coli to maintain the first resistance during this process depended on the combination of antibiotics used. The maintenance of mutations associated with resistance to the first antibiotic did not always predict the residual MIC for that compound. Conclusions In general, the data presented here indicate that adaptation to each antibiotic is unique and independent. The mutational trajectories available in already resistant cells appear more varied than in wild-type cells, indicating that the genetic background of E. coli influences resistance development. The observed mutations cannot always fully explain the resistance pattern observed, indicating a crucial role for adaptation on the gene expression level in de novo acquisition of antibiotic resistance.
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Affiliation(s)
- Marloes Hoeksema
- Laboratory for Molecular Biology and Microbial Food Safety, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Martijs J Jonker
- RNA Biology & Applied Bioinformatics, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Stanley Brul
- Laboratory for Molecular Biology and Microbial Food Safety, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Benno H Ter Kuile
- Laboratory for Molecular Biology and Microbial Food Safety, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands. .,Netherlands Food and Consumer Product Safety Authority, Office for Risk Assessment, Utrecht, The Netherlands.
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46
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Faucher M, Nouvel LX, Dordet-Frisoni E, Sagné E, Baranowski E, Hygonenq MC, Marenda MS, Tardy F, Citti C. Mycoplasmas under experimental antimicrobial selection: The unpredicted contribution of horizontal chromosomal transfer. PLoS Genet 2019; 15:e1007910. [PMID: 30668569 PMCID: PMC6358093 DOI: 10.1371/journal.pgen.1007910] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 02/01/2019] [Accepted: 12/19/2018] [Indexed: 11/18/2022] Open
Abstract
Horizontal Gene Transfer was long thought to be marginal in Mycoplasma a large group of wall-less bacteria often portrayed as minimal cells because of their reduced genomes (ca. 0.5 to 2.0 Mb) and their limited metabolic pathways. This view was recently challenged by the discovery of conjugative exchanges of large chromosomal fragments that equally affected all parts of the chromosome via an unconventional mechanism, so that the whole mycoplasma genome is potentially mobile. By combining next generation sequencing to classical mating and evolutionary experiments, the current study further explored the contribution and impact of this phenomenon on mycoplasma evolution and adaptation using the fluoroquinolone enrofloxacin (Enro), for selective pressure and the ruminant pathogen Mycoplasma agalactiae, as a model organism. For this purpose, we generated isogenic lineages that displayed different combination of spontaneous mutations in Enro target genes (gyrA, gyrB, parC and parE) in association to gradual level of resistance to Enro. We then tested whether these mutations can be acquired by a susceptible population via conjugative chromosomal transfer knowing that, in our model organism, the 4 target genes are scattered in three distinct and distant loci. Our data show that under antibiotic selective pressure, the time scale of the mutational pathway leading to high-level of Enro resistance can be readily compressed into a single conjugative step, in which several EnroR alleles were transferred from resistant to susceptible mycoplasma cells. In addition to acting as an accelerator for antimicrobial dissemination, mycoplasma chromosomal transfer reshuffled genomes beyond expectations and created a mosaic of resistant sub-populations with unpredicted and unrelated features. Our findings provide insights into the process that may drive evolution and adaptability of several pathogenic Mycoplasma spp. via an unconventional conjugative mechanism.
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Affiliation(s)
- Marion Faucher
- IHAP, Université de Toulouse, INRA, ENVT, Toulouse, France
- UMR Mycoplasmoses of ruminants, ANSES, VetAgro Sup, University of Lyon, Lyon, France
| | | | | | - Eveline Sagné
- IHAP, Université de Toulouse, INRA, ENVT, Toulouse, France
| | | | | | - Marc-Serge Marenda
- Asia-Pacific Centre for Animal Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Florence Tardy
- UMR Mycoplasmoses of ruminants, ANSES, VetAgro Sup, University of Lyon, Lyon, France
| | - Christine Citti
- IHAP, Université de Toulouse, INRA, ENVT, Toulouse, France
- * E-mail: (LXN); (CC)
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Nguyen QH, Contamin L, Nguyen TVA, Bañuls A. Insights into the processes that drive the evolution of drug resistance in Mycobacterium tuberculosis. Evol Appl 2018; 11:1498-1511. [PMID: 30344622 PMCID: PMC6183457 DOI: 10.1111/eva.12654] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2017] [Revised: 05/25/2018] [Accepted: 05/27/2018] [Indexed: 01/01/2023] Open
Abstract
At present, the successful transmission of drug-resistant Mycobacterium tuberculosis, including multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains, in human populations, threatens tuberculosis control worldwide. Differently from many other bacteria, M. tuberculosis drug resistance is acquired mainly through mutations in specific drug resistance-associated genes. The panel of mutations is highly diverse, but depends on the affected gene and M. tuberculosis genetic background. The variety of genetic profiles observed in drug-resistant clinical isolates underlines different evolutionary trajectories towards multiple drug resistance, although some mutation patterns are prominent. This review discusses the intrinsic processes that may influence drug resistance evolution in M. tuberculosis, such as mutation rate, drug resistance-associated mutations, fitness cost, compensatory mutations and epistasis. This knowledge should help to better predict the risk of emergence of highly resistant M. tuberculosis strains and to develop new tools and strategies to limit the development and spread of MDR and XDR strains.
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Affiliation(s)
- Quang Huy Nguyen
- Department of Pharmacological, Medical and Agronomical BiotechnologyUniversity of Science and Technology of HanoiVietnam Academy of Science and Technology (VAST)HanoiVietnam
- Institute of Research for DevelopmentUMR MIVEGEC (CNRS‐IRD‐University of Montpellier)MontpellierFrance
- LMI Drug Resistance in South East Asia (LMI DRISA)University of Science and Technology of HanoiVietnam Academy of Science and Technology (VAST)HanoiVietnam
| | - Lucie Contamin
- Institute of Research for DevelopmentUMR MIVEGEC (CNRS‐IRD‐University of Montpellier)MontpellierFrance
- LMI Drug Resistance in South East Asia (LMI DRISA)University of Science and Technology of HanoiVietnam Academy of Science and Technology (VAST)HanoiVietnam
- Department of BacteriologyNational Institute of Hygiene and Epidemiology (NIHE)HanoiVietnam
| | - Thi Van Anh Nguyen
- Department of BacteriologyNational Institute of Hygiene and Epidemiology (NIHE)HanoiVietnam
| | - Anne‐Laure Bañuls
- Institute of Research for DevelopmentUMR MIVEGEC (CNRS‐IRD‐University of Montpellier)MontpellierFrance
- LMI Drug Resistance in South East Asia (LMI DRISA)University of Science and Technology of HanoiVietnam Academy of Science and Technology (VAST)HanoiVietnam
- Department of BacteriologyNational Institute of Hygiene and Epidemiology (NIHE)HanoiVietnam
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48
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Genetics and roadblocks of drug resistant tuberculosis. INFECTION GENETICS AND EVOLUTION 2018; 72:113-130. [PMID: 30261266 DOI: 10.1016/j.meegid.2018.09.023] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 09/20/2018] [Accepted: 09/22/2018] [Indexed: 11/22/2022]
Abstract
Considering the extensive evolutionary history of Mycobacterium tuberculosis, anti-Tuberculosis (TB) drug therapy exerts a recent selective pressure. However, in a microorganism devoid of horizontal gene transfer and with a strictly clonal populational structure such as M. tuberculosis the usual, but not sole, path to overcome drug susceptibility is through de novo mutations on a relatively strict set of genes. The possible allelic diversity that can be associated with drug resistance through several mechanisms such as target alteration or target overexpression, will dictate how these genes can become associated with drug resistance. The success demonstrated by this pathogenic microbe in this latter process and its ability to spread is currently one of the major obstacles to an effective TB elimination. This article reviews the action mechanism of the more important anti-TB drugs, including bedaquiline and delamanid, along with new findings on specific resistance mechanisms. With the development, validation and endorsement of new in vitro molecular tests for drug resistance, knowledge on these resistance mechanisms and microevolutionary dynamics leading to the emergence and fixation of drug resistance mutations within the host is highly important. Additionally, the fitness toll imposed by resistance development is also herein discussed together with known compensatory mechanisms. By elucidating the possible mechanisms that enable one strain to reacquire the original fitness levels, it will be theoretically possible to make more informed decisions and develop novel strategies that can force M. tuberculosis microevolutionary trajectory down through a path of decreasing fitness levels.
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Scortti M, Han L, Alvarez S, Leclercq A, Moura A, Lecuit M, Vazquez-Boland J. Epistatic control of intrinsic resistance by virulence genes in Listeria. PLoS Genet 2018; 14:e1007525. [PMID: 30180166 PMCID: PMC6122793 DOI: 10.1371/journal.pgen.1007525] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Accepted: 06/29/2018] [Indexed: 01/31/2023] Open
Abstract
Elucidating the relationships between antimicrobial resistance and virulence is key to understanding the evolution and population dynamics of resistant pathogens. Here, we show that the susceptibility of the gram-positive bacterium Listeria monocytogenes to the antibiotic fosfomycin is a complex trait involving interactions between resistance and virulence genes and the environment. We found that a FosX enzyme encoded in the listerial core genome confers intrinsic fosfomycin resistance to both pathogenic and non-pathogenic Listeria spp. However, in the genomic context of the pathogenic L. monocytogenes, FosX-mediated resistance is epistatically suppressed by two members of the PrfA virulence regulon, hpt and prfA, which upon activation by host signals induce increased fosfomycin influx into the bacterial cell. Consequently, in infection conditions, most L. monocytogenes isolates become susceptible to fosfomycin despite possessing a gene that confers high-level resistance to the drug. Our study establishes the molecular basis of an epistatic interaction between virulence and resistance genes controlling bacterial susceptibility to an antibiotic. The reported findings provide the rationale for the introduction of fosfomycin in the treatment of Listeria infections even though these bacteria are intrinsically resistant to the antibiotic in vitro.
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Affiliation(s)
- Mariela Scortti
- Microbial Pathogenesis Group, Division of Infection Medicine, Edinburgh Medical School (Biomedical Sciences), University of Edinburgh, Little France campus, Edinburgh, United Kingdom
- Division of Infection & Immunity, The Roslin Institute, University of Edinburgh, Easter Bush campus, Edinburgh, United Kingdom
| | - Lei Han
- Microbial Pathogenesis Group, Division of Infection Medicine, Edinburgh Medical School (Biomedical Sciences), University of Edinburgh, Little France campus, Edinburgh, United Kingdom
| | - Sonsiray Alvarez
- Microbial Pathogenesis Group, Division of Infection Medicine, Edinburgh Medical School (Biomedical Sciences), University of Edinburgh, Little France campus, Edinburgh, United Kingdom
| | - Alexandre Leclercq
- Institut Pasteur, Biology of Infection Unit, INSERM U111 and National Reference Centre / WHO Collaborating Centre for Listeria, Paris, France
| | - Alexandra Moura
- Institut Pasteur, Biology of Infection Unit, INSERM U111 and National Reference Centre / WHO Collaborating Centre for Listeria, Paris, France
| | - Marc Lecuit
- Institut Pasteur, Biology of Infection Unit, INSERM U111 and National Reference Centre / WHO Collaborating Centre for Listeria, Paris, France
- Paris Descartes University, Division of Infectious Diseases and Tropical Medicine, Necker-Enfants Malades University Hospital, Paris, France
| | - Jose Vazquez-Boland
- Microbial Pathogenesis Group, Division of Infection Medicine, Edinburgh Medical School (Biomedical Sciences), University of Edinburgh, Little France campus, Edinburgh, United Kingdom
- Division of Infection & Immunity, The Roslin Institute, University of Edinburgh, Easter Bush campus, Edinburgh, United Kingdom
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50
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Durão P, Balbontín R, Gordo I. Evolutionary Mechanisms Shaping the Maintenance of Antibiotic Resistance. Trends Microbiol 2018; 26:677-691. [DOI: 10.1016/j.tim.2018.01.005] [Citation(s) in RCA: 130] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 01/05/2018] [Accepted: 01/24/2018] [Indexed: 01/10/2023]
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