Characterization of antibiotic resistomes by reprogrammed bacteriophage-enabled functional metagenomics in clinical strains
Functional metagenomics is a powerful experimental tool to identify antibiotic resistance genes (ARGs) in the environment, but the range of suitable host bacterial species is limited. This limitation affects both the scope of the identified ARGs and the interpretation of their clinical relevance. He...
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Dokumentumtípus: | Cikk |
Megjelent: |
2023
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Sorozat: | NATURE MICROBIOLOGY
8 No. 3 |
Tárgyszavak: | |
doi: | 10.1038/s41564-023-01320-2 |
mtmt: | 33634821 |
Online Access: | http://publicatio.bibl.u-szeged.hu/27235 |
Tartalmi kivonat: | Functional metagenomics is a powerful experimental tool to identify antibiotic resistance genes (ARGs) in the environment, but the range of suitable host bacterial species is limited. This limitation affects both the scope of the identified ARGs and the interpretation of their clinical relevance. Here we present a functional metagenomics pipeline called Reprogrammed Bacteriophage Particle Assisted Multi-species Functional Metagenomics (DEEPMINE). This approach combines and improves the use of T7 bacteriophage with exchanged tail fibres and targeted mutagenesis to expand phage host-specificity and efficiency for functional metagenomics. These modified phage particles were used to introduce large metagenomic plasmid libraries into clinically relevant bacterial pathogens. By screening for ARGs in soil and gut microbiomes and clinical genomes against 13 antibiotics, we demonstrate that this approach substantially expands the list of identified ARGs. Many ARGs have species-specific effects on resistance; they provide a high level of resistance in one bacterial species but yield very limited resistance in a related species. Finally, we identified mobile ARGs against antibiotics that are currently under clinical development or have recently been approved. Overall, DEEPMINE expands the functional metagenomics toolbox for studying microbial communities. |
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Terjedelem/Fizikai jellemzők: | 410-423 |
ISSN: | 2058-5276 |