Prediction of surface exposed proteins in Streptococcus pyogenes, with a potential application to other Gram‐positive bacteria

Abstract

The in silico prediction of bacterial surface exposed proteins is of growing interest for the rational development of vaccines and in the study of bacteria-host relationships, whether pathogenic or host beneficial. This interest is driven by the increase in the use of DNA sequencing as a major tool in the early characterization of pathogenic bacteria and, more recently, even of complex ecosystems at the host-environment interface in metagenomics approaches. Current protein localization protocols are not suited to this prediction task as they ignore the potential surface exposition of many membrane-associated proteins. Therefore, we developed a new flow scheme, SurfG+, for the processing of protein sequence data with the particular aim of identification of potentially surface exposed (PSE) proteins from Gram-positive bacteria, which was validated for Streptococcus pyogenes. The results of an exploratory case study on closely related lactobacilli of the acidophilus group suggest that the yogurt bacterium Lactobacillus delbrueckii ssp. bulgaricus (L. bulgaricus) dedicates a relatively important fraction of its coding capacity to secreted proteins, while the probiotic gastrointestinal (GI) tract bacteria L. johnsonii and L. gasseri appear to encode a larger variety of PSE proteins, that may play a role in the interaction with the host.

The Complete Genome of Propionibacterium freudenreichii CIRM-BIA1T, a Hardy Actinobacterium with Food and Probiotic Applications

“…Analysis of the genome using SurfG+ [75] suggests the existence of 161 surface exposed proteins, including seven distinct S-layer proteins (PFREUD_03310, PFREUD_16070, PFREUD_18270, PFREUD_18290, PFREUD_23030, PFREUD_23570, PFREUD_00110), one of which, SlpA (PFREUD_18290) was identified here by surface proteomics. Slp proteins are involved in lactobacilli adhesion [76] and immunomodulation [77].…”

Identification of Peptidoglycan-Associated Proteins as Vaccine Candidates for Enterococcal Infections

“…New bioinformatic approaches have been developed and these strategies have significantly improved the prediction of bacterial protein localization. These include the pipelines SLEP (Surface Localization Extracellular Proteins), developed by Giombini et al [28], LocateP developed by Zhou et al [29], and SurfG+ developed by Barinov et al [30]. However, these in silico approaches are still not fully reliable and do not provide detailed surface protein localization in the bacterial cell wall [26].…”

Properties of probiotic bacteria explored by proteomic approaches

“…Analysis for the presence of conserved domains [33] or motifs [34] reveals proteins that are covalently linked to the Gram positive cell wall through the action of a sortase [35] or likely to be bound in a non-covalent way. The recently developed analysis tool SurfG+ takes into consideration that specific parts of integral membrane proteins can also be surface exposed, as has been demonstrated experimentally [31]. Depending on the bacterial species, this type of surface exposed proteins may outnumber the lipoproteins and LPxTG proteins so far considered as the paradigms of surface proteins in Gram-positive bacteria.…”

“…a, covalently bound to the cell wall; b, non-covalently bound to the cell wall; c, membrane-bound lipoprotein; d, membrane anchored through N or C-terminal transmembrane helix; e, membrane anchored through several TMH; e1, surface exposed N or C-terminal end; e2, surface exposed loop; f, secreted; g, 'moonlighting'; M, cell membrane; W, cell wall; E, surface exposed or secreted. Adapted from [31].…”

“…Dedicated software allows the prediction of protein localization (usually in the categories 'cytoplasmic', 'membrane', 'cell wall', and 'secreted' (e.g. PsortB [30], and surface exposition (SurfG+) [31] (Figure 1). The underlying algorithms recognize signal peptides characteristic of secreted proteins or membrane bound lipoproteins, and predict hydrophobic trans-membrane domains [32].…”