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Pseudomonas aeruginosa DN1, isolated from petroleum-contaminated soil, showed excellent degradation ability toward diverse polycyclic aromatic hydrocarbons (PAHs). Many studies have been done to improve its degradation ability. However, the molecular mechanisms of PAHs degradation in DN1 strain are unclear. In this study, the whole genome of DN1 strain was sequenced and analyzed. Its genome contains 6,641,902 bp and encodes 6,684 putative open reading frames (ORFs), which has the largest genome in almost all the comparative Pseudomonas strains. Results of gene annotation showed that this strain harbored over 100 candidate genes involved in PAHs degradation, including those encoding 25 dioxygenases, four ring-hydroxylating dioxygenases, five ring-cleaving dioxygenases, and various catabolic enzymes, transcriptional regulators, and transporters in the degradation pathways. In addition, gene knockout experiments revealed that the disruption of some key PAHs degradation genes in DN1 strain, such as catA, pcaG, pcaH, and rhdA, did not completely inhibit fluoranthene degradation, even though their degradative rate reduced to some extent. Three intermediate metabolites, including 9-hydroxyfluorene, 1-acenaphthenone, and 1, 8-naphthalic anhydride, were identified as the dominating intermediates in presence of 50 μg/mL fluoranthene as the sole carbon source according to gas chromatography mass spectrometry analysis. Taken together, the genomic and metabolic analysis indicated that the fluoranthene degradation by DN1 strain was initiated by dioxygenation at the C-1, 2-, C-2, 3-, and C-7, 8- positions. These results provide new insights into the genomic plasticity and environmental adaptation of DN1 strain.
Pubmed ID: 30429835 RIS Download
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Curated, relational database containing sequence, classification, structural, functional and evolutionary information about transport systems from variety of living organisms based on IUBMB-approved transporter classification (TC) system. Descriptions, TC numbers, and examples of over 600 families of transport proteins are provided. TC system is analogous to Enzyme Commission (EC) system for classification of enzymes, except that it incorporates both functional and phylogenetic information. TCDB users may submit their own sequenced proteins and descriptions for inclusion into database. The software tools used are all freely available for download. These programs are used for analysis of Protein and DNA sequences. Programs require UNIX server to run.
View all literature mentionsDatabase of peer-reviewed, continually updated annotation for the Pseudomonas aeruginosa PAO1 reference strain genome expanded to include all Pseudomonas species to facilitate cross-strain and cross-species genome comparisons with high quality comparative genomics. The database contains robust assessment of orthologs, a novel ortholog clustering method, and incorporates five views of the data at the sequence and annotation levels (Gbrowse, Mauve and custom views) to facilitate genome comparisons. Other features include more accurate protein subcellular localization predictions and a user-friendly, Boolean searchable log file of updates for the reference strain PAO1. The current annotation is updated using recent research literature and peer-reviewed submissions by a worldwide community of PseudoCAP (Pseudomonas aeruginosa Community Annotation Project) participating researchers. If you are interested in participating, you are invited to get involved. Many annotations, DNA sequences, Orthologs, Intergenic DNA, and Protein sequences are available for download.
View all literature mentionsDatasets and tools for comparative analysis and annotation of all publicly available genomes from three domains of life in a uniquely integrated context. Plasmids that are not part of a specific microbial genome sequencing project and phage genomes are also included in order to increase its genomic context for comparative analysis. The user interface (see User Interface Map) allows navigating the microbial genome data space along its three key dimensions (genes, genomes, and functions), and groups together the main comparative analysis tools. Microbial genome data analysis in IMG usually starts with the definition of an analysis context in terms of selected genomes, functional annotations, and/or genes, followed by the individual or comparative analysis of genomes, functional annotations, or genes.
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