| Autor: |
Shuyi Wang, Shijun Sun, Qi Wang, Hongbin Chen, Yifan Guo, Meng Cai, Yuyao Yin, Shuai Ma, Hui Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Communications Biology, Vol 7, Iss 1, Pp 1-11 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2399-3642 |
| DOI: |
10.1038/s42003-024-06720-6 |
| Popis: |
Abstract Clinical metagenomics (CMg) Nanopore sequencing can facilitate infectious disease diagnosis. In China, sub-lineages ST11-KL64 and ST11-KL47 Carbapenem-resistant Klebsiella pneumoniae (CRKP) are widely prevalent. We propose PathoTracker, a specially compiled database and arranged method for strain feature identification in CMg samples and CRKP traceability. A database targeting high-prevalence horizontal gene transfer in CRKP strains and a ST11-only database for distinguishing two sub-lineages in China were created. To make the database user-friendly, facilitate immediate downstream strain feature identification from raw Nanopore metagenomic data, and avoid the need for phylogenetic analysis from scratch, we developed data analysis methods. The methods included pre-performed phylogenetic analysis, gene-isolate-cluster index and multilevel pan-genome database and reduced storage space by 10-fold and random-access memory by 52-fold compared with normal methods. PathoTracker can provide accurate and fast strain-level analysis for CMg data after 1 h Nanopore sequencing, allowing early warning of outbreaks. A user-friendly page ( http://PathoTracker.pku.edu.cn/ ) was developed to facilitate online analysis, including strain-level feature, species identifications and phylogenetic analyses. PathoTracker proposed in this study will aid in the downstream analysis of CMg. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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