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- Title
CYPminer: an automated cytochrome P450 identification, classification, and data analysis tool for genome data sets across kingdoms.
- Authors
Kweon, Ohgew; Kim, Seong-Jae; Kim, Jae Hyun; Nho, Seong Won; Bae, Dongryeoul; Chon, Jungwhan; Hart, Mark; Baek, Dong-Heon; Kim, Young-Chang; Wang, Wenjun; Kim, Sung-Kwan; Sutherland, John B.; Cerniglia, Carl E.
- Abstract
Background: Cytochrome P450 monooxygenases (termed CYPs or P450s) are hemoproteins ubiquitously found across all kingdoms, playing a central role in intracellular metabolism, especially in metabolism of drugs and xenobiotics. The explosive growth of genome sequencing brings a new set of challenges and issues for researchers, such as a systematic investigation of CYPs across all kingdoms in terms of identification, classification, and pan-CYPome analyses. Such investigation requires an automated tool that can handle an enormous amount of sequencing data in a timely manner. Results: CYPminer was developed in the Python language to facilitate rapid, comprehensive analysis of CYPs from genomes of all kingdoms. CYPminer consists of two procedures i) to generate the Genome-CYP Matrix (GCM) that lists all occurrences of CYPs across the genomes, and ii) to perform analyses and visualization of the GCM, including pan-CYPomes (pan- and core-CYPome), CYP co-occurrence networks, CYP clouds, and genome clustering data. The performance of CYPminer was evaluated with three datasets from fungal and bacterial genome sequences. Conclusions: CYPminer completes CYP analyses for large-scale genomes from all kingdoms, which allows systematic genome annotation and comparative insights for CYPs. CYPminer also can be extended and adapted easily for broader usage.
- Subjects
CYTOCHROME P-450; DATA analysis; DRUG metabolism; NUCLEOTIDE sequencing; BACTERIAL genomes; GENOMES
- Publication
BMC Bioinformatics, 2020, Vol 21, Issue 1, p1
- ISSN
1471-2105
- Publication type
Article
- DOI
10.1186/s12859-020-3473-2