Ohno A(1), Umezawa K(2), Asai S(3)(4), Kryukov K(1)(5), Nakagawa S(1), Miyachi H(3)(4), Imanishi T(6). Author information:
(1)Department of Molecular Life Science, Tokai University School of Medicine,
Isehara, Kanagawa, 259-1193, Japan.
(2)Department of Emergency and Critical Care Medicine, Tokai University School
of Medicine, Isehara, Kanagawa, 259-1193, Japan.
(3)Department of Laboratory Medicine, Tokai University School of Medicine,
Isehara, Kanagawa, 259-1193, Japan.
(4)Infection Control Division, Tokai University Hospital, Isehara, Kanagawa,
259-1193, Japan.
(5)Department of Genomics and Evolutionary Biology, National Institute of
Genetics, Mishima, Shizuoka, 411-8540, Japan.
(6)Department of Molecular Life Science, Tokai University School of Medicine,
Isehara, Kanagawa, 259-1193, Japan. [Email]
Spread of drug-resistant bacteria is a serious problem worldwide. We thus designed a new sequence-based protocol that can quickly identify bacterial compositions of clinical samples and their drug-resistance profiles simultaneously. Here we utilized propidium monoazide (PMA) that prohibits DNA amplifications from dead bacteria, and subjected the original and antibiotics-treated samples to 16S rRNA metagenome sequencing. We tested our protocol on bacterial mixtures, and observed that sequencing reads derived from drug-resistant bacteria were significantly increased compared with those from drug-sensitive bacteria when samples were treated by antibiotics. Our protocol is scalable and will be useful for quickly profiling drug-resistant bacteria.
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