QSDB—a graphical Quorum Sensing Database

Abstract

The human microbiome is largely shaped by the chemical interactions of its microbial members, which includes cross-talk via shared signals or quenching of the signalling of other species. Quorum sensing is a process that allows microbes to coordinate their behaviour in dependence of their population density and to adjust gene expression accordingly. We present the Quorum Sensing Database (QSDB), a comprehensive database of all published sensing and quenching relations between organisms and signalling molecules of the human microbiome, as well as an interactive web interface that allows browsing the database, provides graphical depictions of sensing mechanisms as Systems Biology Graphical Notation diagrams and links to other databases. Database URL : QSDB (Quorum Sensing DataBase) is freely available via an interactive web interface and as a downloadable csv file at http://qsdb.org .

Wekemo Bioincloud: A user‐friendly platform for meta‐omics data analyses

“… ARDB [34]: Antibiotic Resistance Genes Database is used to track antibiotic resistance genes. BacMet [35]: Antibacterial Biocide and Metal Resistance Genes Database is used to confer the resistance to metals or antibacterial biocides. CAZy [36]: Carbohydrate‐Active EnZyme is used to describe enzyme families responsible for cleaving or building complex carbohydrates. CARD [37]: Comprehensive Antibiotic Resistance Database is employed to identify antibiotic resistance and virulence factors. COGs [38]: Clusters of Orthologous Groups of proteins are attempted on a phylogenetic classification of the proteins. EC [39]: Enzyme Commission, the numbers represent enzymes and enzyme genes. Evolutionary gene genealogy. GO [40]: Gene Ontology, annotations report connections between gene products and the biological types. KEGG [41]: Kyoto Encyclopedia of Genes and Genomes is utilized to identify functions within the biological system. MGE [42]: Mobile Genetic Elements is used to carry various kinds of genes endowing their hosts with resistance to antibiotics and/or metals, pathogenicity, symbiosis, and metabolism of new substrates. MetaCyc [43]: It contains pathways involved in both primary and secondary metabolism. QSDB [44]: Quorum Sensing Database, a phenomenon in which the accumulation of signaling molecules allows a single cell to perceive the number of bacteria, enabling coordinated responses and behaviors among bacterial cells. VFDB [45]: Virulence Factors Database is accessed to get bacterial virulence factors.…”

“… MetaCyc [ 43 ]: It contains pathways involved in both primary and secondary metabolism. QSDB [ 44 ]: Quorum Sensing Database, a phenomenon in which the accumulation of signaling molecules allows a single cell to perceive the number of bacteria, enabling coordinated responses and behaviors among bacterial cells. VFDB [ 45 ]: Virulence Factors Database is accessed to get bacterial virulence factors.…”

Design considerations for representing systems biology information with the Systems Biology Graphical Notation

“…In addition to the features listed above, SBGN-ED was extended to provide the SBGN Bricks dictionary [ 90 ] allowing the design of SBGN maps using the SBGN Bricks (see Section 2.3 ). Furthermore, using functionality provided by Vanted, SBGN-ED also supports interaction for SBGN maps (including general interaction with networks [ 96 ], the use of different glyphs in navigation [ 97 ], or mental-map preserving interaction [ 98 ]) SBGN-ED has been used to design SBGN PD maps in general [ 99 ] or in dedicated projects such as RIMAS [ 100 ] (Regulatory Interaction Maps of Arabidopsis Seed Development), MetaCrop [ 25 , 26 ] (a curated repository containing information about the metabolism in crop plants), QSDB [ 101 ] (Quorum-sensing database) and the COVID-19 Disease Map [ 102 , 103 ] (a computational knowledge repository of virus–host interaction mechanisms).…”

Constructions of quorum sensing signaling network for activated sludge microbial community

“…These databases have been collected separately and lack the network character focusing on signals shared between different species of natural microbiota. Concerning QS-based interactions for different organisms, the QSDB [ 27 ] database collected all published sensing and quenching relations between organisms and signaling molecules of the human microbiome, and the QSHGM [ 28 ] database visualized and deciphered intricate QS-based interactions for human gut microbiota. Research on the QS-based interactions for different organisms in human microbiome is well-established.…”