Minimizing treatment-induced emergence of antibiotic resistance in bacterial infections

American Association for the Advancement of Science (AAAS) - Tập 375 Số 6583 - Trang 889-894 - 2022
Mathew Stracy1,2, Olga Snitser2, Idan Yelin2, Yara Amer2, Miriam Parizade3, Rachel Katz3, Galit Rimler3, Tamar Wolf3, Esma Herzel4, Gideon Koren4, Jacob Kuint4,5, Betsy Foxman6, Gabriel Chodick4,5, Varda Shalev4,5, Roy Kishony7,2,8
1Department of Biochemistry, University of Oxford, Oxford, UK
2Faculty of Biology, Technion, Israel Institute of Technology, Haifa, Israel
3Maccabi Mega Lab, Maccabi Healthcare Services, Tel Aviv, Israel.
4Maccabitech, Maccabi Healthcare Services, Tel Aviv, Israel
5Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
6Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
7Department of Computer Science, Technion Israel Institute of Technology, Haifa, Israel
8Lorry I. Lokey Interdisciplinary, Center for Life Sciences and Engineering, Technion – Israel Institute of Technology, Haifa, Israel

Tóm tắt

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.

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American Association for the Advancement of Science (AAAS)

Tập 375 Số 6583

889-894

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