Minimizing treatment-induced emergence of antibiotic resistance in bacterial infections.

Abstract

Treatment of bacterial infections currently focuses on choosing an antibiotic that matches a pathogen's susceptibility, with less attention paid to the risk that even susceptibility-matched treatments can fail as a result of resistance emerging in response to treatment. Combining whole-genome sequencing of 1113 pre- and posttreatment bacterial isolates with machine-learning analysis of 140,349 urinary tract infections and 7365 wound infections, we found that treatment-induced emergence of resistance could be predicted and minimized at the individual-patient level. Emergence of resistance was common and driven not by de novo resistance evolution but by rapid reinfection with a different strain resistant to the prescribed antibiotic. As most infections are seeded from a patient's own microbiota, these resistance-gaining recurrences can be predicted using the patient's past infection history and minimized by machine learning-personalized antibiotic recommendations, offering a means to reduce the emergence and spread of resistant pathogens.

• Authors: Mathew Stracy, Olga Snitser, Idan Yelin, Yara Amer, Miriam Parizade, Rachel Katz, Galit Rimler, Tamar Wolf, Esma Herzel, Gideon Koren, Jacob Kuint, Betsy Foxman, Gabriel Chodick, Varda Shalev, Roy Kishony
• Journal: Science (New York, N.Y.) (Science) Vol. 375 Issue 6583 Pg. 889-894 (02 25 2022) ISSN: 1095-9203 [Electronic] United States
• PMID: 35201862 (Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't)

Chemical References

• Anti-Bacterial Agents

Topics

• Algorithms
• Anti-Bacterial Agents (therapeutic use)
• Bacteria (drug effects, genetics)
• Bacterial Infections (drug therapy, microbiology)
• Drug Resistance, Bacterial
• Escherichia coli Infections (drug therapy, microbiology)
• Female
• Humans
• Machine Learning
• Male
• Microbial Sensitivity Tests
• Microbiota
• Mutation
• Reinfection (microbiology)
• Urinary Tract Infections (drug therapy, microbiology)
• Whole Genome Sequencing
• Wound Infection (drug therapy, microbiology)