Sequence-Based Prediction of Type III Secreted Proteins

Abstract

The type III secretion system (TTSS) is a key mechanism for host cell interaction used by a variety of bacterial pathogens and symbionts of plants and animals including humans. The TTSS represents a molecular syringe with which the bacteria deliver effector proteins directly into the host cell cytosol. Despite the importance of the TTSS for bacterial pathogenesis, recognition and targeting of type III secreted proteins has up until now been poorly understood. Several hypotheses are discussed, including an mRNA-based signal, a chaperon-mediated process, or an N-terminal signal peptide. In this study, we systematically analyzed the amino acid composition and secondary structure of N-termini of 100 experimentally verified effector proteins. Based on this, we developed a machine-learning approach for the prediction of TTSS effector proteins, taking into account N-terminal sequence features such as frequencies of amino acids, short peptides, or residues with certain physico-chemical properties. The resulting computational model revealed a strong type III secretion signal in the N-terminus that can be used to detect effectors with sensitivity of ∼71% and selectivity of ∼85%. This signal seems to be taxonomically universal and conserved among animal pathogens and plant symbionts, since we could successfully detect effector proteins if the respective group was excluded from training. The application of our prediction approach to 739 complete bacterial and archaeal genome sequences resulted in the identification of between 0% and 12% putative TTSS effector proteins. Comparison of effector proteins with orthologs that are not secreted by the TTSS showed no clear pattern of signal acquisition by fusion, suggesting convergent evolutionary processes shaping the type III secretion signal. The newly developed program EffectiveT3 (http://www.chlamydiaedb.org) is the first universal in silico prediction program for the identification of novel TTSS effectors. Our findings will facilitate further studies on and improve our understanding of type III secretion and its role in pathogen–host interactions.

Endofungal bacterium controls its host by an hrp type III secretion system

“…Two ORFs (ORF 3 and 4), which are absent in all related gene clusters appear to be inserted into the T3SS cluster during evolution. (Arnold et al, 2009). As expected, the putative secretin SctC was found to harbor a secretion signature.…”

“…Prediction of potentially type III secreted effector proteins was carried out by using T3SS PREDICTION server (Lö wer and Schneider, 2009) and the EFFECTIVE T3 prediction tool (Arnold et al, 2009). …”

Protein Flexibility and Coiled-Coil Propensity: New Insights Into Type III and Other Bacterial Secretion Systems

“…The prevailing view, supported by extensive biocomputing analyses, is that the amino acid composition of the N-terminal region of the effectors serves as secretion signal (Lloyd et al, 2001;Buttner and He, 2009;Arnold et al, 2009;Samudrala et al, 2009). The required Nterminal peptide length for secretion is usually 10-15 residues, whereas the minimum length needed for translocation is 50-60 residues.…”

“…In less well characterized bacterial species there is certainly a wide spectrum of unknown effectors. This situation may be now changing through new approaches that use advanced machine learning algorithms to identify within individual types of secretion systems common themes for effectors and other system components that go beyond simple amino acid motifs (Arnold et al, 2009;Samudrala et al, 2009), or through the identification of important structural and physicochemical properties as universal signatures of virulence factors (Gazi et al, 2008;. This review will focus on the well-characterized T3SS proteins where the prevalence of coiled-coil domains along with pronounced structural flexibility/disorder have been proposed to be characteristic properties associated with a protein-protein interaction mode within T3SS and as essential requirements for secretion (Delahay and Frankel, 2002;Pallen et al, 1997;Gazi et al, 2008;.…”

YscU/FlhB of Yersinia pseudotuberculosis Harbors a C-terminal Type III Secretion Signal

“…These characteristics provide the secretion signal with a high tolerance for introduction of point mutations that barely affect the secretion efficiency (22). These features of the T3S signal were used to develop prediction software to identify T3S-substrates (20,23). In Yersinia, the T3S-ATPase YscN, recognizes the secretion signal of the effector proteins when they are in complex with their cognate chaperone (24).…”