About

The mibPOPdb database is a manually curated integrative resource dedicated to microbial bioremediation of persistent organic pollutants (POP) research. Data are systematically and manually collected from the scientific literature. It is a freely accessible platform providing information on a collection of resources such as key gene, strain and their systematic taxonomy, and scientific literature citations derived from published and experimentally validated persistent organic pollutants biodegradation datasets. It is an integrated resource that provides tools for predicting the biodegradability of compounds, generating automated structures of compounds, predicting the toxicity of chemicals, and bioinformatics utilities for POP degrading microbial sequence analysis. By providing and consolidating high-level curated information on microbial bioremediation of POPs into a single resource, mibPOPdb will be an important web resource that can foster studies into POP degrading microbial communities and help enhance our understanding of microbial bioremediation of persistent organic pollutants.

The database contains data on algal, archaeal, bacterial, and fungal microbial isolates experimentally validated in the published literature to degrade persistent organic pollutants.

Content

• Compound listing information (Stockholm Convention Listing, Listing year, etc.)
• Compound description (Compound name, Structure, SMILES, Physiochemical properties, External links to numerical identifiers, etc.)
• Structural analogs (similar compounds)
• Publications (scientific literature)
• Compound metabolized (POP metabolized, Degradation pathway map)
• Degradation gene information (Strain ID, Taxonomy of organisms, encoding gene, Nucleotide, and Protein external links, FASTA links, etc.)
• General information of strain (Strain ID, taxonomy, GenBank ID, FASTA sequence)
• Bioremediation information (POP metabolized, Biodegradation rate, Primary intermediates, Final product, degradation technique, Enzyme activity detected)
• Sample collection information (Continent, Country, Isolation source, Habitat)
• Publication Information (Title, PMID, Reference, External links to research, Abstract)
• External links (BRENDA, Uniprot, AlgaeBase, KEGG, EAWAG-BBD, WoRMS, etc.)

This is the first release of mibPOPdb, and it is in its infancy and thus is incomplete. The database will be updated periodically, and article curation is ongoing, as new articles related to microbial bioremediation of persistent organic pollutants are continuously published. Biyearly updates will be carried out on the database.

The mibPOPdb database was developed to assist environmental scientists and engineers working to understand microbial degradation of persistent organic pollutants by providing genes, strains that are important for POP remediation research and also includes toolkits for users to input their datasets in the context of the database. As such, one is reminded that this database is not the ultimate source of microbial bioremediation of persistent organic pollutants. Please note that datasets displayed in this manually curated resource it is not error-free. When making use of this data, users are urged to verify the authenticity and validity of the datasets provided before using them.

Users can search for specific genes, strains, keywords, or a combination of concurrent conditions related to microbial bioremediation of POP. See the mibPOPdb Tutorial section for more details about all the query options.
Any queries or data misrepresentation-related issues concerning the mibPOPdb can be reported via the contact feature incorporated into the mibPOPdb. The administrator will respond to their queries.

In order to appreciate the functionality and visualization of the mibPOPdb database, we recommend users use the latest versions of Google Chrome, Mozilla Firefox, and Microsoft Edge browsers.

Where appropriate sources from which the data included in mibPOPdb was extracted were cited. For example, citing the relevant sources such as NCBI, WoRMS, AlgaeBase, FungiDB, and relevant literature sources from which valid data was extracted were also cited for each data entry.