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Métris, Aline, Baranyi, Jozsef, Kingsley, Robert A. 
ORCID: https://orcid.org/0000-0002-0194-6485, Korcsmaros, Tamas, Olbei, Marton, Bohar, Balazs, Fazekas, David, Madgwick, Matthew, Sudhakar, Padhmanand and Hautefort, Isabelle
(2022)
Multilayered networks of SalmoNet2 enable strain comparisons of the Salmonella genus on a molecular level.
mSystems, 7 (4).
ISSN 2379-5077
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Abstract
Serovars of the genus Salmonella primarily evolved as gastrointestinal pathogens in a wide range of hosts. Some serotypes later evolved further, adopting a more invasive lifestyle in a narrower host range associated with systemic infections. A system-level knowledge of these pathogens could identify the complex adaptations associated with the evolution of serovars with distinct pathogenicity, host range, and risk to human health. This promises to aid the design of interventions and serve as a knowledge base in the Salmonella research community. Here, we present SalmoNet2, a major update to SalmoNet1, the first multilayered interaction resource for Salmonella strains, containing protein-protein, transcriptional regulatory, and enzyme-enzyme interactions. The new version extends the number of Salmonella networks from 11 to 20. We now include a strain from the second species in the Salmonella genus, a strain from the Salmonella enterica subspecies arizonae and additional strains of importance from the subspecies enterica, including S. Typhimurium strain D23580, an epidemic multidrug-resistant strain associated with invasive nontyphoidal salmonellosis (iNTS). The database now uses strain specific metabolic models instead of a generalized model to highlight differences between strains. The update has increased the coverage of high-quality protein-protein interactions, and enhanced interoperability with other computational resources by adopting standardized formats. The resource website has been updated with tutorials to help researchers analyze their Salmonella data using molecular interaction networks from SalmoNet2. SalmoNet2 is accessible at http://salmonet.org/. IMPORTANCE Multilayered network databases collate interaction information from multiple sources, and are powerful both as a knowledge base and subject of analysis. Here, we present SalmoNet2, an integrated network resource containing protein-protein, transcriptional regulatory, and metabolic interactions for 20 Salmonella strains. Key improvements to the update include expanding the number of strains, strain-specific metabolic networks, an increase in high-quality protein-protein interactions, community standard computational formats to help interoperability, and online tutorials to help users analyze their data using SalmoNet2.
| Item Type: | Article |
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| Additional Information: | Funding Information: The work of M.O., P.S., I.H., and T.K. were supported by the UKRI BBSRC Gut Microbes and Health Institute Strategic Program BB/R012490/1 and its constituent projects BBS/E/F/000PR10353 and BBS/E/F/000PR10355. M.O., B.B., D.F., P.S., I.H., and T.K. were also supported by a BBSRC Core Strategic Program Grant for Genomes to Food Security (BB/CSP1720/1) and its constituent work packages, BBS/E/T/000PR9819 and BBS/E/T/ 000PR9817. P.S. was supported by the European Research Council Advanced Grant (ERC-2015-AdG, 694679, CrUCCial). M.O. and M.M. were supported by a BBSRC-Norwich Research Park Biosciences Doctoral Training Partnership grant (BB/M011216/1 and BB/ S50743X/1). R.K. was supported by the UKRI Institute Strategic Program Microbes in the Food Chain BB/R012504/1 and its constituent project(s) BBS/E/F/000PR10348 and BBS/ E/F/000PR10349. Publisher Copyright: 2022 Olbei et al. |
| Uncontrolled Keywords: | global regulatory networks,host adaptation,network resource,protein-protein interactions,salmonella,microbiology,physiology,biochemistry,ecology, evolution, behavior and systematics,modelling and simulation,molecular biology,genetics,computer science applications,sdg 3 - good health and well-being ,/dk/atira/pure/subjectarea/asjc/2400/2404 |
| Faculty \ School: | Faculty of Science > School of Biological Sciences |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 04 Nov 2022 14:30 |
| Last Modified: | 04 Mar 2024 18:13 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/89621 |
| DOI: | 10.1128/msystems.01493-21 |
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