ArticleBMC research notes2013
New players in the same old game: a system level in silico study to predict type III secretion system and effector proteins in bacterial genomes reveals common themes in T3SS mediated pathogenesis.
Article in BMC research notes, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Secretion Systems in Gram-Negative Bacterial Fish Pathogens.Frontiers in microbiology · 2021Review
- Regulation of Type III Secretion of Translocon and Effector Proteins by the EsaB/EsaL/EsaM Complex in Edwardsiella tarda.Infection and immunity · 2017Article
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundType III secretion system (T3SS) plays an important role in virulence or symbiosis of many pathogenic or symbiotic bacteria [CHM 2:291-294, 2007; Physiology (Bethesda) 20:326-339, 2005]. T3SS acts like a tunnel between a bacterium and its host through which the bacterium injects 'effector' proteins into the latter [Nature 444:567-573, 2006; COSB 18:258-266, 2008]. The effectors spatially and temporally modify the host signalling pathways [FEMS Microbiol Rev 35:1100-1125, 2011; Cell Host Microbe5:571-579, 2009]. In spite its crucial role in host-pathogen interaction, the study of T3SS and the associated effectors has been limited to a few bacteria [Cell Microbiol 13:1858-1869, 2011; Nat Rev Microbiol 6:11-16, 2008; Mol Microbiol 80:1420-1438, 2011]. Before one set out to perform systematic experimental studies on an unknown set of bacteria it would be beneficial to identify the potential candidates by developing an in silico screening algorithm. A system level study would also be advantageous over traditional laboratory methods to extract an overriding theme for host-pathogen interaction, if any, from the vast resources of data generated by sequencing multiple bacterial genomes.
resultsWe have developed an in silico protocol in which the most conserved set of T3SS proteins was used as the query against the entire bacterial database with increasingly stringent search parameters. It enabled us to identify several uncharacterized T3SS positive bacteria. We adopted a similar strategy to predict the presence of the already known effectors in the newly identified T3SS positive bacteria. The huge resources of biochemical data [FEMS Microbiol Rev 35:1100-1125, 2011; Cell Host Microbe 5:571-579, 2009; BMC Bioinformatics 7(11):S4, 2010] on the T3SS effectors enabled us to search for the common theme in T3SS mediated pathogenesis. We identified few cellular signalling networks in the host, which are manipulated by most of the T3SS containing pathogens. We went on to look for correlation, if any, between the biological quirks of a particular class of bacteria with the effectors they harbour. We could pin point few effectors, which were enriched in certain classes of bacteria.
conclusionThe current study would open up new avenues to explore many uncharacterized T3SS positive bacteria. The experimental validation of the predictions from this study will unravel a generalized mechanism for T3SS positive bacterial infection into host cell.
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