
AbstractThe emergence of antibiotic resistance in human pathogens has become a major threat to modern medicine and in particular hospitalized patients. The outcome of antibiotic treatment can be affected by the composition of the gut resistome either by enabling resistance gene acquisition of infecting pathogens or by modulating the collateral effects of antibiotic treatment on the commensal microbiome. Accordingly, knowledge of the gut resistome composition could enable more effective and individualized treatment of bacterial infections. Yet, rapid workflows for resistome characterization are lacking. To address this challenge we developed the poreFUME workflow that deploys functional metagenomic selections and nanopore sequencing to resistome mapping. We demonstrate the approach by functionally characterizing the gut resistome of an ICU patient. The accuracy of the poreFUME pipeline is >97 % sufficient for the reliable annotation of antibiotic resistance genes. The poreFUME pipeline provides a promising approach for efficient resistome profiling that could inform antibiotic treatment decisions in the future.
Drug Resistance, Microbial, Bacterial Infections, Microbial Sensitivity Tests, Sequence Analysis, DNA, Anti-Bacterial Agents, Gastrointestinal Microbiome, Gastrointestinal Tract, Feces, Intensive Care Units, Nanopores, Methods Online, Humans, Metagenome, /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being; name=SDG 3 - Good Health and Well-being, Gene Library
Drug Resistance, Microbial, Bacterial Infections, Microbial Sensitivity Tests, Sequence Analysis, DNA, Anti-Bacterial Agents, Gastrointestinal Microbiome, Gastrointestinal Tract, Feces, Intensive Care Units, Nanopores, Methods Online, Humans, Metagenome, /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being; name=SDG 3 - Good Health and Well-being, Gene Library
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 62 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
