![]() ![]() The current state-of-the-art in infection diagnostics are mostly based on biochemical analysis of cultured clinical samples ( Vasala et al., 2020). The rising antimicrobial resistance of recent years poses a major threat to humanity and rapid diagnostic tools for bacterial infections are urgently needed ( Avershina et al., 2021a). The SQK-LSK110 Ligation kit resulted in higher genome coverage and more accurate bacterial identification than the SQK-RBK004 Rapid Barcode kit. Flongle data are sufficient for 99.9% genome coverage within at most 20,000 (clinical isolates) or 50,000 (positive blood cultures) sequences generated. Generally, Flongle data allow rapid bacterial ID and resistome detection based on the first 1,000–3,000 generated sequences (10 min to 3 h from the sequencing start), albeit ARG variant identification did not always correspond to ONT MinION and Illumina sequencing-based data. We sequenced both the whole genome and plasmids isolated from these bacteria using two different sequencing kits. pneumoniae that had been cultured overnight. For the analysis, we used pure bacterial cultures of four clinical isolates of Escherichia coli and Klebsiella pneumoniae and two blood samples spiked with either E. This work investigates whether the Oxford Nanopore Technology’s (ONT) Flongle sequencing platform is suitable for real-time sequencing directly from blood cultures to identify bacteria and detect resistance-encoding genes. ![]() ![]() Rapid bacterial identification and antimicrobial resistance gene (ARG) detection are crucial for fast optimization of antibiotic treatment, especially for septic patients where each hour of delayed antibiotic prescription might have lethal consequences. 3Faculty of Health Sciences, Institute of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway.2Division of Laboratory Medicine, Department of Microbiology, Oslo University Hospital, Oslo, Norway.1Department of Biotechnology, Inland Norway University of Applied Sciences, Hamar, Norway. ![]()
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