Metagenomics approach to predict antibiotic resistance genes in sputum samples of adult people with cystic fibrosis: a pilot study

Damage induced by lung infections in people with cystic fibrosis (CF) is the leading factor to the mortality and morbidity of CF. To treat bacterial infections, people with CF are prescribed antibiotics. Routine antibiotic susceptibility (ABS) testing relies on culture-dependent, phenotypic techniques. These take several days up to more than a week, while timely intervention is key. To bridge this time gap, physicians in CF care use patient history of ABS data to start antibiotics, with risk of resistance to it. This pilot study explores a time saving alternative: the possibility to predict antibiotic resistance genes using shotgun metagenomics and artificial intelligence. By quicker prediction of ABS, people with CF can receive more adequate care, which results in the possible prevention of chronic infections and contributes to antibiotic stewardship.

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Publication Details

Journal
Microbiology Spectrum
Published
2025-11-05
DOI
https://doi.org/10.1128/spectrum.02299-24
Primary Topic
Cystic Fibrosis Research Advances
Type
article
Field-Weighted Citation Impact
0.00

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article

Metagenomics approach to predict antibiotic resistance genes in sputum samples of adult people with cystic fibrosis: a pilot study

Jacqueline E. van Muijlwijk‐Koezen, Mahmoud I. Abdel‐Aziz, Anke H. Maitland‐van der Zee, Anne H. Neerincx et al.
Microbiology Spectrum
Cystic Fibrosis Research Advances
article

Metagenomics approach to predict antibiotic resistance genes in sputum samples of adult people with cystic fibrosis: a pilot study

Jacqueline E. van Muijlwijk‐Koezen, Mahmoud I. Abdel‐Aziz, Anke H. Maitland‐van der Zee, Anne H. Neerincx, Josje Altenburg, Christof J. Majoor, Els J.M. Weersink, Sonja van Scheijen
article en

Abstract

Damage induced by lung infections in people with cystic fibrosis (CF) is the leading factor to the mortality and morbidity of CF. To treat bacterial infections, people with CF are prescribed antibiotics. Routine antibiotic susceptibility (ABS) testing relies on culture-dependent, phenotypic techniques. These take several days up to more than a week, while timely intervention is key. To bridge this time gap, physicians in CF care use patient history of ABS data to start antibiotics, with risk of resistance to it. This pilot study explores a time saving alternative: the possibility to predict antibiotic resistance genes using shotgun metagenomics and artificial intelligence. By quicker prediction of ABS, people with CF can receive more adequate care, which results in the possible prevention of chronic infections and contributes to antibiotic stewardship.

Microbiology SpectrumVol. 13(12)
Netherlands Center for Occupational Diseases (NL), Emma Kinderziekenhuis (NL), Center for Personalized Cancer Treatment (NL), Amsterdam Neuroscience (NL), Office of Infectious Diseases (US), Infectious Diseases Institute (UG), GGD Amsterdam (NL), Amsterdam University Medical Centers (NL), Amsterdam University of Applied Sciences (NL), Vrije Universiteit Amsterdam (NL), University of Amsterdam (NL)
Health~Holland, ZonMw, Stichting Astma Bestrijding, Eurostars
Openalex Percentile: Top 53%
Cystic Fibrosis Research Advances
DOIOpen Access PDFOpenAlex
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