Dataset Information

CANT-HYD: A Curated Database of Phylogeny-Derived Hidden Markov Models for Annotation of Marker Genes Involved in Hydrocarbon Degradation.

ABSTRACT: Many pathways for hydrocarbon degradation have been discovered, yet there are no dedicated tools to identify and predict the hydrocarbon degradation potential of microbial genomes and metagenomes. Here we present the Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD), a database of 37 HMMs of marker genes involved in anaerobic and aerobic degradation pathways of aliphatic and aromatic hydrocarbons. Using this database, we identify understudied or overlooked hydrocarbon degradation potential in many phyla. We also demonstrate its application in analyzing high-throughput sequence data by predicting hydrocarbon utilization in large metagenomic datasets from diverse environments. CANT-HYD is available at https://github.com/dgittins/CANT-HYD-HydrocarbonBiodegradation.

SUBMITTER: Khot V

PROVIDER: S-EPMC8767102 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

CANT-HYD: A Curated Database of Phylogeny-Derived Hidden Markov Models for Annotation of Marker Genes Involved in Hydrocarbon Degradation.

Khot Varada V Zorz Jackie J Gittins Daniel A DA Chakraborty Anirban A Bell Emma E Bautista María A MA Paquette Alexandre J AJ Hawley Alyse K AK Novotnik Breda B Hubert Casey R J CRJ Strous Marc M Bhatnagar Srijak S

Frontiers in microbiology 20220107

Many pathways for hydrocarbon degradation have been discovered, yet there are no dedicated tools to identify and predict the hydrocarbon degradation potential of microbial genomes and metagenomes. Here we present the Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD), a database of 37 HMMs of marker genes involved in anaerobic and aerobic degradation pathways of aliphatic and aromatic hydrocarbons. Using this database, we identify understudied or overlooked hydrocarbon degra ...[more]

PMID: 35069469

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Project description:BackgroundThe genus Paracoccidioides consists of thermodymorphic fungi responsible for Paracoccidioidomycosis (PCM), a systemic mycosis that has been registered to affect ~10 million people in Latin America. Biogeographical data subdivided the genus Paracoccidioides in five divergent subgroups, which have been recently classified as different species. Genomic sequencing of five Paracoccidioides isolates, representing each of these subgroups/species provided an important framework for the development of post-genomic studies with these fungi. However, functional annotations of these genomes have not been submitted to manual curation and, as a result, ~60-90% of the Paracoccidioides protein-coding genes (depending on isolate/annotation) are currently described as responsible for hypothetical proteins, without any further functional/structural description.Principal findingsThe present work reviews the functional assignment of Paracoccidioides genes, reducing the number of hypothetical proteins to ~25-28%. These results were compiled in a relational database called ParaDB, dedicated to the main representatives of Paracoccidioides spp. ParaDB can be accessed through a friendly graphical interface, which offers search tools based on keywords or protein/DNA sequences. All data contained in ParaDB can be partially or completely downloaded through spreadsheet, multi-fasta and GFF3-formatted files, which can be subsequently used in a variety of downstream functional analyses. Moreover, the entire ParaDB environment has been configured in a Docker service, which has been submitted to the GitHub repository, ensuring long-term data availability to researchers. This service can be downloaded and used to perform fully functional local installations of the database in alternative computing ecosystems, allowing users to conduct their data mining and analyses in a personal and stable working environment.ConclusionsThese new annotations greatly reduce the number of genes identified solely as hypothetical proteins and are integrated into a dedicated database, providing resources to assist researchers in this field to conduct post-genomic studies with this group of human pathogenic fungi.

Dataset Information

CANT-HYD: A Curated Database of Phylogeny-Derived Hidden Markov Models for Annotation of Marker Genes Involved in Hydrocarbon Degradation.

Publications

CANT-HYD: A Curated Database of Phylogeny-Derived Hidden Markov Models for Annotation of Marker Genes Involved in Hydrocarbon Degradation.

Similar Datasets

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