{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T03:04:59Z","timestamp":1781233499623,"version":"3.54.1"},"reference-count":37,"publisher":"Microbiology Society","issue":"4","license":[{"start":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T00:00:00Z","timestamp":1743638400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000288","name":"Royal Society","doi-asserted-by":"crossref","award":["RGS\\R1\\211163"],"award-info":[{"award-number":["RGS\\R1\\211163"]}],"id":[{"id":"10.13039\/501100000288","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100020894","name":"School of Veterinary Medicine, University of Glasgow","doi-asserted-by":"crossref","award":["Lord Kelvin Adam Smith (LKAS) Ph.D. studentship"],"award-info":[{"award-number":["Lord Kelvin Adam Smith (LKAS) Ph.D. studentship"]}],"id":[{"id":"10.13039\/501100020894","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,4,3]]},"abstract":"<jats:p>\n                    Bloodstream infections (BSIs) represent a significant global health challenge, and traditional diagnostic methods are suboptimal for timely guiding targeted antibiotic therapy. We introduce MultiSeq-AMR, a rapid and modular nanopore amplicon-sequencing workflow to identify bacterial and fungal species and a comprehensive set of antimicrobial resistance (AMR) genes (\n                    <jats:italic>n<\/jats:italic>\n                    =91) from various types of infection sources. We initially benchmarked MultiSeq-AMR using DNA from 16 bacterial and 5 fungal reference strains and accurately identified all species. AMR gene identification exhibited 99.4% categorical agreement (CA: 153\/154 prediction) with whole-genome sequencing. Further validation with 33 BACT\/ALERT positive samples from suspected BSI cases revealed 100% accuracy for genus and 96.7% for species identification, with 97.4% CA (151\/155) for AMR gene prediction. To accelerate microbiological diagnosis, a 6\u2009h culture enrichment step was tested with MultiSeq-AMR using 15 clinically important bacterial species. Of 13 species selected for sequencing, 11 were correctly identified, with 96% CA (59\/61 predictions) for AMR gene identification. With only 2 Mbp yield, sequencing identified 93.7% of species and 89.8% AMR genes initially detected with 20\u201350 Mbp yield\/sample. MultiSeq-AMR holds promise for BSI diagnosis, as species\/AMR genes could be identified under 5\u2009h of BACT\/ALERT positivity and potentially &lt;11\u2009h of sample collection (rapid-enrichment) for a large set of bacterial species. MultiSeq-AMR gene targets can be modified\/increased indefinitely to suit user needs. Further research is required to clinically validate MultiSeq-AMR, especially the rapid enrichment method, to assess its utility in a medical setup and in improving patient outcomes in BSI.\n                  <\/jats:p>","DOI":"10.1099\/mgen.0.001383","type":"journal-article","created":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T11:18:34Z","timestamp":1743679114000},"source":"Crossref","is-referenced-by-count":1,"title":["MultiSeq-AMR: a modular amplicon-sequencing workflow for rapid detection of bloodstream infection and antimicrobial resistance markers"],"prefix":"10.1099","volume":"11","author":[{"given":"Mohammad Saiful Islam","family":"Sajib","sequence":"first","affiliation":[{"name":"School of Biodiversity, One Health & Veterinary Medicine, University of Glasgow, Glasgow, 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