T3SEdb: data warehousing of virulence effectors secreted by the bacterial Type III Secretion System

Abstract

BackgroundEffectors of Type III Secretion System (T3SS) play a pivotal role in establishing and maintaining pathogenicity in the host and therefore the identification of these effectors is important in understanding virulence. However, the effectors display high level of sequence diversity, therefore making the identification a difficult process. There is a need to collate and annotate existing effector sequences in public databases to enable systematic analyses of these sequences for development of models for screening and selection of putative novel effectors from bacterial genomes that can be validated by a smaller number of key experiments.ResultsHerein, we present T3SEdb http://effectors.bic.nus.edu.sg/T3SEdb, a specialized database of annotated T3SS effector (T3SE) sequences containing 1089 records from 46 bacterial species compiled from the literature and public protein databases. Procedures have been defined for i) comprehensive annotation of experimental status of effectors, ii) submission and curation review of records by users of the database, and iii) the regular update of T3SEdb existing and new records. Keyword fielded and sequence searches (BLAST, regular expression) are supported for both experimentally verified and hypothetical T3SEs. More than 171 clusters of T3SEs were detected based on sequence identity comparisons (intra-cluster difference up to ~60%). Owing to this high level of sequence diversity of T3SEs, the T3SEdb provides a large number of experimentally known effector sequences with wide species representation for creation of effector predictors. We created a reliable effector prediction tool, integrated into the database, to demonstrate the application of the database for such endeavours.ConclusionsT3SEdb is the first specialised database reported for T3SS effectors, enriched with manual annotations that facilitated systematic construction of a reliable prediction model for identification of novel effectors. The T3SEdb represents a platform for inclusion of additional annotations of metadata for future developments of sophisticated effector prediction models for screening and selection of putative novel effectors from bacterial genomes/proteomes that can be validated by a small number of key experiments.

Burkholderia pseudomalleitype III secreted protein BipC: role in actin modulation and translocation activities required for the bacterial intracellular lifecycle

“…Type three secretion effector (TTSE) translocation signal peptide online program, such as ModLab (http://gecco.org.chemie.uni-frankfurt.de/T3SS_prediction/T3SS_prediction.html) (Lower & Schneider, 2009), T3SEdb (http://effectors.bic.nus.edu.sg/T3SEdb/predict.php) (Tay et al, 2010) and Effective T3 (http://www.effectors.org/index.jsp) (Amold et al, 2009) were used to predict the presence of TTSE for BipC. The domain family analysis was performed using Pfam protein families database (Finn et al, 2010).…”

dbDiarrhea: The database of pathogen proteins and vaccine antigens from diarrheal pathogens

“…In this context, it was tenable to include proteins for Type III secretion system (T3SS) effectors and T3SS components. These were retrieved from PubMed as well as the T3SEdb database (Tay et al, 2010) . 2.1.1.7.…”

The SdiA-Regulated Gene srgE Encodes a Type III Secreted Effector

“…Through concerted actions, these effectors are known to modulate host cell functions, thereby contributing to the virulence of S. Typhimurium (82,83). Early in silico analyses of SrgE have provided conflicting predictions as to whether SrgE is a T3SS substrate (68)(69)(70)(71)(72). To test the hypothesis that SrgE is a T3SS, we used two different methods, a ␤-lactamase activity reporter assay and a split GFP system, to demonstrate that SrgE is indeed a T3SS effector delivered into host cells via T3SS2.…”

“…SrgE has a length of 488 amino acid residues, a molecular mass of 55 kDa, and a pI of 6.8. Two computer algorithms have suggested that SrgE possesses a type 3 secretion signal (68,69), while three other algorithms do not support this conclusion (70)(71)(72). SrgE also encodes a putative coiledcoil (CC) domain, located between residues 345 and 382.…”