An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species
Abstract
Understanding the microbial genomic contributors to antimicrobial resistance (AMR) is essential for early detection of emerging AMR infections, a pressing global health threat in human and veterinary medicine. Here we used whole genome sequencing and antibiotic susceptibility test data from 980 disease causing Escherichia coli isolated from companion and farm animals to model AMR genotypes and phenotypes for 24 antibiotics. We determined the strength of genotype-to-phenotype relationships for 197 AMR genes with elastic net logistic regression. Model predictors were designed to evaluate different potential modes of AMR genotype translation into resistance phenotypes. Our results show a model that considers the presence of individual AMR genes and total number of AMR genes present from a set of genes known to confer resistance was able to accurately predict isolate resistance on average (mean F 1 score = 98.0%, SD = 2.3%, mean accuracy = 98.2%, SD = 2.7%). However, fitted models sometimes varied for antibiotics in the same class and for the same antibiotic across animal hosts, suggesting heterogeneity in the genetic determinants of AMR resistance. We conclude that an interpretable AMR prediction model can be used to accurately predict resistance phenotypes across multiple host species and reveal testable hypotheses about howmore »
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1996589
- Grant/Contract Number:
- SC0014664
- Resource Type:
- Published Article
- Journal Name:
- PLoS ONE
- Additional Journal Information:
- Journal Name: PLoS ONE Journal Volume: 18 Journal Issue: 8; Journal ID: ISSN 1932-6203
- Publisher:
- Public Library of Science (PLoS)
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Chung, Henri C., Foxx, Christine L., Hicks, Jessica A., Stuber, Tod P., Friedberg, Iddo, Dorman, Karin S., Harris, Beth, and Sattar, ed., Adeel. An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species. United States: N. p., 2023.
Web. doi:10.1371/journal.pone.0290473.
Chung, Henri C., Foxx, Christine L., Hicks, Jessica A., Stuber, Tod P., Friedberg, Iddo, Dorman, Karin S., Harris, Beth, & Sattar, ed., Adeel. An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species. United States. https://doi.org/10.1371/journal.pone.0290473
Chung, Henri C., Foxx, Christine L., Hicks, Jessica A., Stuber, Tod P., Friedberg, Iddo, Dorman, Karin S., Harris, Beth, and Sattar, ed., Adeel. Thu .
"An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species". United States. https://doi.org/10.1371/journal.pone.0290473.
@article{osti_1996589,
title = {An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species},
author = {Chung, Henri C. and Foxx, Christine L. and Hicks, Jessica A. and Stuber, Tod P. and Friedberg, Iddo and Dorman, Karin S. and Harris, Beth and Sattar, ed., Adeel},
abstractNote = {Understanding the microbial genomic contributors to antimicrobial resistance (AMR) is essential for early detection of emerging AMR infections, a pressing global health threat in human and veterinary medicine. Here we used whole genome sequencing and antibiotic susceptibility test data from 980 disease causing Escherichia coli isolated from companion and farm animals to model AMR genotypes and phenotypes for 24 antibiotics. We determined the strength of genotype-to-phenotype relationships for 197 AMR genes with elastic net logistic regression. Model predictors were designed to evaluate different potential modes of AMR genotype translation into resistance phenotypes. Our results show a model that considers the presence of individual AMR genes and total number of AMR genes present from a set of genes known to confer resistance was able to accurately predict isolate resistance on average (mean F 1 score = 98.0%, SD = 2.3%, mean accuracy = 98.2%, SD = 2.7%). However, fitted models sometimes varied for antibiotics in the same class and for the same antibiotic across animal hosts, suggesting heterogeneity in the genetic determinants of AMR resistance. We conclude that an interpretable AMR prediction model can be used to accurately predict resistance phenotypes across multiple host species and reveal testable hypotheses about how the mechanism of resistance may vary across antibiotics within the same class and across animal hosts for the same antibiotic.},
doi = {10.1371/journal.pone.0290473},
journal = {PLoS ONE},
number = 8,
volume = 18,
place = {United States},
year = {Thu Aug 24 00:00:00 EDT 2023},
month = {Thu Aug 24 00:00:00 EDT 2023}
}
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1371/journal.pone.0290473
https://doi.org/10.1371/journal.pone.0290473
Other availability
Search WorldCat to find libraries that may hold this journal
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.
Works referenced in this record:
Genome-Scale Metabolic Models and Machine Learning Reveal Genetic Determinants of Antibiotic Resistance in Escherichia coli and Unravel the Underlying Metabolic Adaptation Mechanisms
journal, August 2021
- Pearcy, Nicole; Hu, Yue; Baker, Michelle
- mSystems, Vol. 6, Issue 4
Identifying novel β-lactamase substrate activity through in silico prediction of antimicrobial resistance
journal, January 2021
- Tsang, Kara K.; Maguire, Finlay; Zubyk, Haley L.
- Microbial Genomics, Vol. 7, Issue 1
Antimicrobial Resistance in
Escherichia coli
journal, July 2018
- Poirel, Laurent; Madec, Jean-Yves; Lupo, Agnese
- Microbiology Spectrum, Vol. 6, Issue 4
Fluoroquinolone Antibiotics
journal, August 1988
- Paton, J. H.; Reeves, D. S.
- Drugs, Vol. 36, Issue 2
Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data
journal, September 2019
- Hicks, Allison L.; Wheeler, Nicole; Sánchez-Busó, Leonor
- PLOS Computational Biology, Vol. 15, Issue 9
Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data
journal, December 2017
- Yang, Yang; Niehaus, Katherine E.; Walker, Timothy M.
- Bioinformatics, Vol. 34, Issue 10
Assembling Single-Cell Genomes and Mini-Metagenomes From Chimeric MDA Products
journal, October 2013
- Nurk, Sergey; Bankevich, Anton; Antipov, Dmitry
- Journal of Computational Biology, Vol. 20, Issue 10
Predicting antimicrobial susceptibility from the bacterial genome: A new paradigm for one health resistance monitoring
journal, October 2020
- McDermott, Patrick F.; Davis, James J.
- Journal of Veterinary Pharmacology and Therapeutics, Vol. 44, Issue 2
Genomic evolution of antimicrobial resistance in Escherichia coli
journal, July 2021
- Leekitcharoenphon, Pimlapas; Johansson, Markus Hans Kristofer; Munk, Patrick
- Scientific Reports, Vol. 11, Issue 1
WGS accurately predicts antimicrobial resistance in Escherichia coli
journal, July 2015
- Tyson, Gregory H.; McDermott, Patrick F.; Li, Cong
- Journal of Antimicrobial Chemotherapy, Vol. 70, Issue 10
Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination
journal, November 2019
- Bhattacharyya, Roby P.; Bandyopadhyay, Nirmalya; Ma, Peijun
- Nature Medicine, Vol. 25, Issue 12
Ridge Regression: Biased Estimation for Nonorthogonal Problems
journal, February 2000
- Hoerl, Arthur E.; Kennard, Robert W.
- Technometrics, Vol. 42, Issue 1
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis
journal, January 2019
- Yang, Yang; Walker, Timothy M.; Walker, A. Sarah
- Bioinformatics, Vol. 35, Issue 18
The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain
journal, May 2018
- Oniciuc, Elena; Likotrafiti, Eleni; Alvarez-Molina, Adrián
- Genes, Vol. 9, Issue 5
Regularization and variable selection via the elastic net
journal, April 2005
- Zou, Hui; Hastie, Trevor
- Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 67, Issue 2
Genomics accurately predicts antimicrobial resistance in Staphylococcus pseudintermedius collected as part of Vet-LIRN resistance monitoring
journal, March 2021
- Tyson, Gregory H.; Ceric, Olgica; Guag, Jake
- Veterinary Microbiology, Vol. 254
Linear Regression Equations To Predict β-Lactam, Macrolide, Lincosamide, and Fluoroquinolone MICs from Molecular Antimicrobial Resistance Determinants in
Streptococcus pneumoniae
journal, January 2022
- Demczuk, Walter; Martin, Irene; Griffith, Averil
- Antimicrobial Agents and Chemotherapy, Vol. 66, Issue 1
Antimicrobial resistance of zoonotic and commensal bacteria in Europe: The missing link between consumption and resistance in veterinary medicine
journal, May 2014
- Garcia-Migura, Lourdes; Hendriksen, Rene S.; Fraile, Lorenzo
- Veterinary Microbiology, Vol. 170, Issue 1-2
Antibiotics Resistance in Escherichia coli Isolated from Livestock in the Emirate of Abu Dhabi, UAE, 2014–2019
journal, April 2022
- Abdelwahab, Ghada Elderdiri; Ishag, Hassan Zackaria Ali; Al Hammadi, Zulaikha Mohamed
- International Journal of Microbiology, Vol. 2022
Metagenome analysis using the Kraken software suite
journal, September 2022
- Lu, Jennifer; Rincon, Natalia; Wood, Derrick E.
- Nature Protocols, Vol. 17, Issue 12
Poultry hatcheries as potential reservoirs for antimicrobial-resistant Escherichia coli: A risk to public health and food safety
journal, April 2018
- Osman, Kamelia M.; Kappell, Anthony D.; Elhadidy, Mohamed
- Scientific Reports, Vol. 8, Issue 1
Genotyping using whole-genome sequencing is a realistic alternative to surveillance based on phenotypic antimicrobial susceptibility testing
journal, December 2012
- Zankari, E.; Hasman, H.; Kaas, R. S.
- Journal of Antimicrobial Chemotherapy, Vol. 68, Issue 4
Whole-Genome Sequencing Analysis Accurately Predicts Antimicrobial Resistance Phenotypes in Campylobacter spp.
journal, October 2015
- Zhao, S.; Tyson, G. H.; Chen, Y.
- Applied and Environmental Microbiology, Vol. 82, Issue 2
Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal Salmonella
journal, October 2018
- Nguyen, Marcus; Long, S. Wesley; McDermott, Patrick F.
- Journal of Clinical Microbiology, Vol. 57, Issue 2
Comparative genomics and the role of lateral gene transfer in the evolution of bovine adapted Streptococcus agalactiae
journal, August 2011
- Richards, Vincent P.; Lang, Ping; Pavinski Bitar, Paulina D.
- Infection, Genetics and Evolution, Vol. 11, Issue 6
Trends in antimicrobial resistance among Escherichia coli from defined infections in humans and animals
journal, February 2020
- Bourély, Clémence; Coeffic, Thomas; Caillon, Jocelyne
- Journal of Antimicrobial Chemotherapy, Vol. 75, Issue 6
Bracken: estimating species abundance in metagenomics data
journal, January 2017
- Lu, Jennifer; Breitwieser, Florian P.; Thielen, Peter
- PeerJ Computer Science, Vol. 3
Identification of acquired antimicrobial resistance genes
journal, July 2012
- Zankari, E.; Hasman, H.; Cosentino, S.
- Journal of Antimicrobial Chemotherapy, Vol. 67, Issue 11
Wild small mammals as sentinels for the environmental transmission of antimicrobial resistance
journal, April 2017
- Furness, Lauren E.; Campbell, Amy; Zhang, Lihong
- Environmental Research, Vol. 154
Regression Shrinkage and Selection Via the Lasso
journal, January 1996
- Tibshirani, Robert
- Journal of the Royal Statistical Society: Series B (Methodological), Vol. 58, Issue 1
Antimicrobial resistance and resistance gene determinants in clinical Escherichia coli from different animal species in Switzerland
journal, January 2003
- Lanz, Roland; Kuhnert, Peter; Boerlin, Patrick
- Veterinary Microbiology, Vol. 91, Issue 1
Critical Importance of a One Health Approach to Antimicrobial Resistance
journal, June 2019
- White, Allison; Hughes, James M.
- EcoHealth, Vol. 16, Issue 3
Predicting antimicrobial susceptibilities for Escherichia coli and Klebsiella pneumoniae isolates using whole genomic sequence data
journal, May 2013
- Stoesser, N.; Batty, E. M.; Eyre, D. W.
- Journal of Antimicrobial Chemotherapy, Vol. 68, Issue 10
Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data
journal, November 2016
- Pesesky, Mitchell W.; Hussain, Tahir; Wallace, Meghan
- Frontiers in Microbiology, Vol. 7
Statistical characterisation of bacterial wild-type MIC value distributions and the determination of epidemiological cut-off values
journal, May 2006
- Turnidge, J.; Kahlmeter, G.; Kronvall, G.
- Clinical Microbiology and Infection, Vol. 12, Issue 5
WGS to predict antibiotic MICs for Neisseria gonorrhoeae
journal, March 2017
- Eyre, David W.; De Silva, Dilrini; Cole, Kevin
- Journal of Antimicrobial Chemotherapy, Vol. 72, Issue 7
Prediction of Staphylococcus aureus Antimicrobial Resistance by Whole-Genome Sequencing
journal, February 2014
- Gordon, N. C.; Price, J. R.; Cole, K.
- Journal of Clinical Microbiology, Vol. 52, Issue 4
Applications of Machine Learning to the Problem of Antimicrobial Resistance: an Emerging Model for Translational Research
journal, June 2021
- Anahtar, Melis N.; Yang, Jason H.; Kanjilal, Sanjat
- Journal of Clinical Microbiology, Vol. 59, Issue 7
European-wide antimicrobial resistance monitoring in commensal Escherichia coli isolated from healthy food animals between 2004 and 2018
journal, October 2022
- De Jong, Anno; El Garch, Farid; Hocquet, Didier
- Journal of Antimicrobial Chemotherapy, Vol. 77, Issue 12
Whole-genome sequencing to control antimicrobial resistance
journal, September 2014
- Köser, Claudio U.; Ellington, Matthew J.; Peacock, Sharon J.
- Trends in Genetics, Vol. 30, Issue 9
Antimicrobial resistance surveillance in the genomic age: AMR surveillance in the genomic age
journal, November 2016
- McArthur, Andrew G.; Tsang, Kara K.
- Annals of the New York Academy of Sciences, Vol. 1388, Issue 1
Identification of Primary Antimicrobial Resistance Drivers in Agricultural Nontyphoidal Salmonella enterica Serovars by Using Machine Learning
journal, August 2019
- Maguire, Finlay; Rehman, Muhammad Attiq; Carrillo, Catherine
- mSystems, Vol. 4, Issue 4
Sample size determination for logistic regression revisited
journal, December 2006
- Demidenko, Eugene
- Statistics in Medicine, Vol. 26, Issue 18
Validating the AMRFinder Tool and Resistance Gene Database by Using Antimicrobial Resistance Genotype-Phenotype Correlations in a Collection of Isolates
journal, August 2019
- Feldgarden, Michael; Brover, Vyacheslav; Haft, Daniel H.
- Antimicrobial Agents and Chemotherapy, Vol. 63, Issue 11
The application of antibiotics in broiler production and the resulting antibiotic resistance in Escherichia coli: A global overview
journal, April 2019
- Roth, Nataliya; Käsbohrer, Annemarie; Mayrhofer, Sigrid
- Poultry Science, Vol. 98, Issue 4
Antimicrobial Resistance Diversity Suggestive of Distinct Salmonella Typhimurium Sources or Selective Pressures in Food-Production Animals
journal, April 2019
- Mellor, Kate C.; Petrovska, Liljana; Thomson, Nicholas R.
- Frontiers in Microbiology, Vol. 10
The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST Subcommittee
journal, January 2017
- Ellington, M. J.; Ekelund, O.; Aarestrup, F. M.
- Clinical Microbiology and Infection, Vol. 23, Issue 1
Contribution of Chromosomal β-Lactamases to β-Lactam Resistance in Enterobacteria
journal, July 1986
- Lindberg, Frederik; Normark, Staffan
- Clinical Infectious Diseases, Vol. 8, Issue Supplement_3
Antimicrobial resistance in zoonotic bacteria: lessons learned from host-specific pathogens
journal, December 2008
- Wassenaar, Trudy M.; Silley, Peter
- Animal Health Research Reviews, Vol. 9, Issue 2
Selection bias in gene extraction on the basis of microarray gene-expression data
journal, April 2002
- Ambroise, C.; McLachlan, G. J.
- Proceedings of the National Academy of Sciences, Vol. 99, Issue 10
NCBI prokaryotic genome annotation pipeline
journal, June 2016
- Tatusova, Tatiana; DiCuccio, Michael; Badretdin, Azat
- Nucleic Acids Research, Vol. 44, Issue 14
European harmonization of MIC breakpoints for antimicrobial susceptibility testing of bacteria
journal, July 2003
- Kahlmeter, G.
- Journal of Antimicrobial Chemotherapy, Vol. 52, Issue 2
MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis
journal, August 2015
- Singhal, Neelja; Kumar, Manish; Kanaujia, Pawan K.
- Frontiers in Microbiology, Vol. 6
National Antimicrobial Resistance Monitoring System: Two Decades of Advancing Public Health Through Integrated Surveillance of Antimicrobial Resistance
journal, October 2017
- Karp, Beth E.; Tate, Heather; Plumblee, Jodie R.
- Foodborne Pathogens and Disease, Vol. 14, Issue 10
Stability selection: Stability Selection
journal, July 2010
- Meinshausen, Nicolai; Bühlmann, Peter
- Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 72, Issue 4
Whole-Genome Sequencing for Detecting Antimicrobial Resistance in Nontyphoidal Salmonella
journal, July 2016
- McDermott, Patrick F.; Tyson, Gregory H.; Kabera, Claudine
- Antimicrobial Agents and Chemotherapy, Vol. 60, Issue 9
Effect of Culture-Independent Diagnostic Tests on Future Emerging Infections Program Surveillance
journal, September 2015
- Langley, Gayle; Besser, John; Iwamoto, Martha
- Emerging Infectious Diseases, Vol. 21, Issue 9
Machine learning for the prediction of antibacterial susceptibility in Mycobacterium tuberculosis
conference, June 2014
- Niehaus, Katherine E.; Walker, Timothy M.; Crook, Derrick W.
- 2014 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)