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CyanoPATH: a knowledgebase of genome-scale functional repertoire for toxic cyanobacterial blooms.

Wei DuGaoyang LiNicholas HoLandon JenkinsDrew HockadayJiankang TanHuansheng Cao
Published in: Briefings in bioinformatics (2021)
CyanoPATH is a database that curates and analyzes the common genomic functional repertoire for cyanobacteria harmful algal blooms (CyanoHABs) in eutrophic waters. Based on the literature of empirical studies and genome/protein databases, it summarizes four types of information: common biological functions (pathways) driving CyanoHABs, customized pathway maps, classification of blooming type based on databases and the genomes of cyanobacteria. A total of 19 pathways are reconstructed, which are involved in the utilization of macronutrients (e.g. carbon, nitrogen, phosphorus and sulfur), micronutrients (e.g. zinc, magnesium, iron, etc.) and other resources (e.g. light and vitamins) and in stress resistance (e.g. lead and copper). These pathways, comprised of both transport and biochemical reactions, are reconstructed with proteins from NCBI and reactions from KEGG and visualized with self-created transport/reaction maps. The pathways are hierarchical and consist of subpathways, protein/enzyme complexes and constituent proteins. New cyanobacterial genomes can be annotated and visualized for these pathways and compared with existing species. This set of genomic functional repertoire is useful in analyzing aquatic metagenomes and metatranscriptomes in CyanoHAB research. Most importantly, it establishes a link between genome and ecology. All these reference proteins, pathways and maps and genomes are free to download at http://www.csbg-jlu.info/CyanoPATH.
Keyphrases
  • machine learning
  • systematic review
  • deep learning
  • risk assessment
  • dna methylation
  • protein protein
  • amino acid
  • stress induced
  • copy number