Project Significance:
Catalog of ARGs subtypes and ARGs types will be identified by the broad scanning of met-
agenomic analysis. Influent, effluent, anaerobic digestion sludge and activated sludge will be the survey points. The correlation between microbial community included potential pathogens and ARGs will be investigated using redundancy analysis. This will be one of the pioneer studies
on the fate of ARGs in WWTP using metagenomic analysis with high-throughput sequencing
and hopefully would enhance our knowledge on fate of ARGs in WWTP.
Results Achieved:
We already built up a structured ARGs database with 24 ARGs types and 1209 subtypes, containing 4049 sequences in total. With this comprehensive and hierarchical database, ARGs in environmental samples will be identified and normalized easily by aligning against the database. This database has been released and published on Bioinformatics.(Yang, Y. et al. ARGs-OAP: online analysis pipeline for antibiotic resistance genes detection from metagenomic data using an integrated structured ARG-database. Bioinformatics 2016;32(15):2346-2351.)
