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Mounsey O, Marchetti L, Parada J, Alarcón LV, Aliverti F, Avison MB, Ayala CS, Ballesteros C, Best CM, Bettridge J, Buchamer A, Buldain D, Carranza A, Corti Isgro M, Demeritt D, Escobar MP, Gortari Castillo L, Jaureguiberry M, Lucas MF, Madoz LV, Marconi MJ, Moiso N, Nievas HD, Ramirez Montes De Oca MA, Reding C, Reyher KK, Vass L, Williams S, Giraudo J, De La Sota RL, Mestorino N, Moredo FA, Pellegrino M. Genomic epidemiology of third-generation cephalosporin-resistant Escherichia coli from Argentinian pig and dairy farms reveals animal-specific patterns of co-resistance and resistance mechanisms. Appl Environ Microbiol 2024; 90:e0179123. [PMID: 38334306 PMCID: PMC10952494 DOI: 10.1128/aem.01791-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 12/14/2023] [Indexed: 02/10/2024] Open
Abstract
Control measures are being introduced globally to reduce the prevalence of antibiotic resistance (ABR) in bacteria on farms. However, little is known about the current prevalence and molecular ecology of ABR in bacterial species with the potential to be key opportunistic human pathogens, such as Escherichia coli, on South American farms. Working with 30 dairy cattle farms and 40 pig farms across two provinces in central-eastern Argentina, we report a comprehensive genomic analysis of third-generation cephalosporin-resistant (3GC-R) E. coli, which were recovered from 34.8% (cattle) and 47.8% (pigs) of samples from fecally contaminated sites. Phylogenetic analysis revealed substantial diversity suggestive of long-term horizontal and vertical transmission of 3GC-R mechanisms. CTX-M-15 and CTX-M-2 were more often produced by isolates from dairy farms, while CTX-M-8 and CMY-2 and co-carriage of amoxicillin/clavulanate resistance and florfenicol resistance were more common in isolates from pig farms. This suggests different selective pressures for antibiotic use in these two animal types. We identified the β-lactamase gene blaROB, which has previously only been reported in the family Pasteurellaceae, in 3GC-R E. coli. blaROB was found alongside a novel florfenicol resistance gene, ydhC, also mobilized from a pig pathogen as part of a new composite transposon. As the first comprehensive genomic survey of 3GC-R E. coli in Argentina, these data set a baseline from which to measure the effects of interventions aimed at reducing on-farm ABR and provide an opportunity to investigate the zoonotic transmission of resistant bacteria in this region. IMPORTANCE Little is known about the ecology of critically important antibiotic resistance among bacteria with the potential to be opportunistic human pathogens (e.g., Escherichia coli) on South American farms. By studying 70 pig and dairy cattle farms in central-eastern Argentina, we identified that third-generation cephalosporin resistance (3GC-R) in E. coli was mediated by mechanisms seen more often in certain species and that 3GC-R pig E. coli were more likely to be co-resistant to florfenicol and amoxicillin/clavulanate. This suggests that on-farm antibiotic usage is key to selecting the types of E. coli present on these farms. 3GC-R E. coli and 3GC-R plasmids were diverse, suggestive of long-term circulation in this region. We identified the de novo mobilization of the resistance gene blaROB from pig pathogens into E. coli on a novel mobile genetic element, which shows the importance of surveying poorly studied regions for antibiotic resistance that might impact human health.
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Affiliation(s)
- Oliver Mounsey
- University of Bristol, School of Cellular and Molecular Medicine, Bristol, United Kingdom
| | - Laura Marchetti
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
| | - Julián Parada
- Universidad Nacional de Río Cuarto, Facultad de Agronomía y Veterinaria, Río Cuarto, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Laura V. Alarcón
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
| | - Florencia Aliverti
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
| | - Matthew B. Avison
- University of Bristol, School of Cellular and Molecular Medicine, Bristol, United Kingdom
| | - Carlos S. Ayala
- University of Bristol Veterinary School, Langford, United Kingdom
| | | | - Caroline M. Best
- University of Bristol Veterinary School, Langford, United Kingdom
| | - Judy Bettridge
- University of Bristol Veterinary School, Langford, United Kingdom
- Natural Resources Institute, University of Greenwich, Chatham, United Kingdom
| | - Andrea Buchamer
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
| | - Daniel Buldain
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Alicia Carranza
- Universidad Nacional de Río Cuarto, Facultad de Agronomía y Veterinaria, Río Cuarto, Argentina
| | - Maite Corti Isgro
- Universidad Nacional de Río Cuarto, Facultad de Agronomía y Veterinaria, Río Cuarto, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - David Demeritt
- Department of Geography, King’s College London, London, United Kingdom
| | | | - Lihuel Gortari Castillo
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - María Jaureguiberry
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Mariana F. Lucas
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
- Universidad del Salvador, Facultad de Ciencias Agrarias y Veterinarias, Pilar, Argentina
| | - L. Vanina Madoz
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - María José Marconi
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Nicolás Moiso
- Universidad Nacional de Río Cuarto, Facultad de Agronomía y Veterinaria, Río Cuarto, Argentina
| | - Hernán D. Nievas
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
| | | | - Carlos Reding
- University of Bristol, School of Cellular and Molecular Medicine, Bristol, United Kingdom
| | | | - Lucy Vass
- University of Bristol Veterinary School, Langford, United Kingdom
| | - Sara Williams
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
| | - José Giraudo
- Universidad Nacional de Río Cuarto, Facultad de Agronomía y Veterinaria, Río Cuarto, Argentina
| | - R. Luzbel De La Sota
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Nora Mestorino
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
| | - Fabiana A. Moredo
- Universidad Nacional de La Plata, Facultad de Ciencias Veterinarias, La Plata, Argentina
| | - Matías Pellegrino
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
- Universidad Nacional de Río Cuarto, Facultad de Ciencias Exactas, Físico Químicas y Naturales, Río Cuarto, Argentina
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Reding C, Satapoomin N, Avison MB. Hound: a novel tool for automated mapping of genotype to phenotype in bacterial genomes assembled de novo. Brief Bioinform 2024; 25:bbae057. [PMID: 38385882 PMCID: PMC10883467 DOI: 10.1093/bib/bbae057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 01/11/2024] [Accepted: 01/26/2024] [Indexed: 02/23/2024] Open
Abstract
Increasing evidence suggests that microbial species have a strong within species genetic heterogeneity. This can be problematic for the analysis of prokaryote genomes, which commonly relies on a reference genome to guide the assembly process. Differences between reference and sample genomes will therefore introduce errors in final assembly, jeopardizing the detection from structural variations to point mutations-critical for genomic surveillance of antibiotic resistance. Here we present Hound, a pipeline that integrates publicly available tools to assemble prokaryote genomes de novo, detect user-given genes by similarity to report mutations found in the coding sequence, promoter, as well as relative gene copy number within the assembly. Importantly, Hound can use the query sequence as a guide to merge contigs, and reconstruct genes that were fragmented by the assembler. To showcase Hound, we screened through 5032 bacterial whole-genome sequences isolated from farmed animals and human infections, using the amino acid sequence encoded by blaTEM-1, to detect and predict resistance to amoxicillin/clavulanate which is driven by over-expression of this gene. We believe this tool can facilitate the analysis of prokaryote species that currently lack a reference genome, and can be scaled either up to build automated systems for genomic surveillance or down to integrate into antibiotic susceptibility point-of-care diagnostics.
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Affiliation(s)
- Carlos Reding
- University of Bristol School of Cellular and Molecular Medicine, University Walk, Bristol, BS8 1TD Bristol, UK
| | - Naphat Satapoomin
- University of Bristol School of Cellular and Molecular Medicine, University Walk, Bristol, BS8 1TD Bristol, UK
| | - Matthew B Avison
- University of Bristol School of Cellular and Molecular Medicine, University Walk, Bristol, BS8 1TD Bristol, UK
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Reding C. Predicting the re-distribution of antibiotic molecules caused by inter-species interactions in microbial communities. ISME Commun 2022; 2:110. [PMID: 37938684 PMCID: PMC9723709 DOI: 10.1038/s43705-022-00186-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 10/03/2022] [Accepted: 10/06/2022] [Indexed: 11/09/2023]
Abstract
Microbes associate in nature forming complex communities, but they are often studied in purified form. Here I show that neighbouring species enforce the re-distribution of carbon and antimicrobial molecules, predictably changing drug efficacy with respect to standard laboratory assays. A simple mathematical model, validated experimentally using pairwise competition assays, suggests that differences in drug sensitivity between the competing species causes the re-distribution of drug molecules without affecting carbon uptake. The re-distribution of drug is even when species have similar drug sensitivity, reducing drug efficacy. But when their sensitivities differ the re-distribution is uneven: The most sensitive species accumulates more drug molecules, increasing efficacy against it. Drug efficacy tests relying on samples with multiple species are considered unreliable and unpredictable, but study demonstrates that efficacy in these cases can be qualitatively predicted. It also suggests that living in communities can be beneficial even when all species compete for a single carbon source, as the relationship between cell density and drug required to inhibit their growth may be more complex than previously thought.
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Affiliation(s)
- Carlos Reding
- Department of Biosciences, University of Exeter, EX4 4QD, Exeter, UK.
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94304, USA.
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Reding C, Catalán P, Jansen G, Bergmiller T, Wood E, Rosenstiel P, Schulenburg H, Gudelj I, Beardmore R. The Antibiotic Dosage of Fastest Resistance Evolution: gene amplifications underpinning the inverted-U. Mol Biol Evol 2021; 38:3847-3863. [PMID: 33693929 PMCID: PMC8382913 DOI: 10.1093/molbev/msab025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
To determine the dosage at which antibiotic resistance evolution is most rapid, we treated Escherichia coli in vitro, deploying the antibiotic erythromycin at dosages ranging from zero to high. Adaptation was fastest just below erythromycin’s minimal inhibitory concentration (MIC) and genotype-phenotype correlations determined from whole genome sequencing revealed the molecular basis: simultaneous selection for copy number variation in three resistance mechanisms which exhibited an “inverted-U” pattern of dose-dependence, as did several insertion sequences and an integron. Many genes did not conform to this pattern, however, reflecting changes in selection as dose increased: putative media adaptation polymorphisms at zero antibiotic dosage gave way to drug target (ribosomal RNA operon) amplification at mid dosages whereas prophage-mediated drug efflux amplifications dominated at the highest dosages. All treatments exhibited E. coli increases in the copy number of efflux operons acrAB and emrE at rates that correlated with increases in population density. For strains where the inverted-U was no longer observed following the genetic manipulation of acrAB, it could be recovered by prolonging the antibiotic treatment at subMIC dosages.
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Affiliation(s)
- Carlos Reding
- Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4QD, UK
| | - Pablo Catalán
- Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4QD, UK.,Grupo Interdisciplinar de Sistemas Complejos (GISC), Departamento de Matemáticas, Universidad Carlos III, Madrid, Spain
| | | | | | - Emily Wood
- Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4QD, UK
| | - Phillip Rosenstiel
- Institute of Clinical Molecular Biology (IKMB), CAU Kiel, Kiel 24105, Germany
| | - Hinrich Schulenburg
- Evolutionary Ecology and Genetics, Zoological Institute, CAU Kiel, Kiel 24118, Germany
| | - Ivana Gudelj
- Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4QD, UK
| | - Robert Beardmore
- Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4QD, UK
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Peña-Miller R, Fuentes-Hernandez A, Reding C, Gudelj I, Beardmore R. Testing the optimality properties of a dual antibiotic treatment in a two-locus, two-allele model. J R Soc Interface 2014; 11:20131035. [PMID: 24812050 DOI: 10.1098/rsif.2013.1035] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Mathematically speaking, it is self-evident that the optimal control of complex, dynamical systems with many interacting components cannot be achieved with 'non-responsive' control strategies that are constant through time. Although there are notable exceptions, this is usually how we design treatments with antimicrobial drugs when we give the same dose and the same antibiotic combination each day. Here, we use a frequency- and density-dependent pharmacogenetics mathematical model based on a standard, two-locus, two-allele representation of how bacteria resist antibiotics to probe the question of whether optimal antibiotic treatments might, in fact, be constant through time. The model describes the ecological and evolutionary dynamics of different sub-populations of the bacterium Escherichia coli that compete for a single limiting resource in a two-drug environment. We use in vitro evolutionary experiments to calibrate and test the model and show that antibiotic environments can support dynamically changing and heterogeneous population structures. We then demonstrate, theoretically and empirically, that the best treatment strategies should adapt through time and constant strategies are not optimal.
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Affiliation(s)
- Rafael Peña-Miller
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, , Cuernavaca, Morelos, México
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