Proteins In Gram-positive Bacteria Research Articles

CW-PRED: Prediction of C-terminal surface anchoring sorting signals in bacteria and Archaea.

Sorting signals are crucial for the anchoring of proteins to the cell surface in archaea and bacteria. These proteins often feature distinct motifs at their C-terminus, cleaved by sortase or sortase-like enzymes. Gram-positive bacteria exhibit the LPXTGX consensus motif, cleaved by sortases, while Gram-negative bacteria employ exosortases recognizing motifs like PEP. Archaea utilize exosortase homologs known as archaeosortases for signal anchoring. Traditionally identification of such C-terminal sorting signals was performed with profile Hidden Markov Models (pHMMs). The Cell-Wall PREDiction (CW-PRED) method introduced for the first time a custom-made class HMM for proteins in Gram-positive bacteria that contain a cell wall sorting signal which begins with an LPXTG motif, followed by a hydrophobic domain and a tail of positively charged residues. Here we present a new and updated version of CW-PRED for predicting C-terminal sorting signals in Archaea, Gram-positive, and Gram-negative bacteria. We used a large training set and several model enhancements that improve motif identification in order to achieve better discrimination between C-terminal signals and other proteins. Cross-validation demonstrates CW-PRED's superiority in sensitivity and specificity compared to other methods. Application of the method in reference proteomes reveals a large number of potential surface proteins not previously identified. The method is available for academic use at http://195.251.108.230/apps.compgen.org/CW-PRED/ and as standalone software.

Small proteins in Gram-positive bacteria.

Small proteins comprising less than 100 amino acids have been often ignored in bacterial genome annotations. About 10 years ago, focused efforts started to investigate whole peptidomes, which resulted in the discovery of a multitude of small proteins, but only a number of them have been characterized in detail. Generally, small proteins can be either membrane or cytosolic proteins. The latter interact with larger proteins, RNA or even metal ions. Here, we summarize our current knowledge on small proteins from Gram-positive bacteria with a special emphasis on the model organism Bacillus subtilis. Our examples include membrane-bound toxins of type I toxin-antitoxin systems, proteins that block the assembly of higher order structures, regulate sporulation or modulate the RNA degradosome. We do not consider antimicrobial peptides. Furthermore, we present methods for the identification and investigation of small proteins.

Tracking Cell Wall-Anchored Proteins in Gram-Positive Bacteria.

Cell wall-anchored surface proteins are integral components of Gram-positive bacterial cell envelope and vital for bacterial survival in different environmental niches. To fulfill their functions, surface protein precursors translocate from cytoplasm to bacterial cell surface in three sequential steps: secretion across the cytoplasmic membrane, covalently anchoring to the cell wall precursor lipid II by sortase A, and incorporation of the lipid II-linked precursors into mature cell wall peptidoglycan. Here, we describe a series of immunofluorescence microscopy methods to track the subcellular localization of cell wall-anchored proteins along the sorting pathway. While the protocols are tailored to Staphylococcus aureus, they can be readily adapted to localize cell wall-anchored proteins as well as membrane proteins in other Gram-positive bacteria.

ArgD of Mycobacterium tuberculosis is a functional N-acetylornithine aminotransferase with moonlighting function as an effective immune modulator

Mycobacterium tuberculosis (M. tuberculosis) encodes an essential enzyme acetyl ornithine aminotransferase ArgD (Rv1655) of arginine biosynthetic pathway which plays crucial role in M. tuberculosis growth and survival. ArgD catalyzes the reversible conversion of N-acetylornithine and 2 oxoglutarate into glutamate-5-semialdehyde and L-glutamate. It also possesses succinyl diaminopimelate aminotransferase activity and can thus carry out the corresponding step in lysine biosynthesis. These essential roles played by ArgD in amino acid biosynthetic pathways highlight it as an important metabolic chokepoint thus an important drug target. We showed that M. tuberculosis ArgD rescues the growth of ΔargD E. coli grown in minimal media validating its functional importance. Phylogenetic analysis of M. tuberculosis ArgD showed homology with proteins in gram positive bacteria, pathogenic and non-pathogenic mycobacteria suggesting the essentiality of this protein. ArgD is a secretory protein that could be utilized by M. tuberculosis to modulate host innate immunity as its moonlighting function. In-silico analysis predicted it to be a highly antigenic protein. The recombinant ArgD protein when exposed to macrophage cells induced enhanced production of pro-inflammatory cytokines TNF, IL6 and IL12 in a dose dependent manner. ArgD also induced the increased production of innate immune effector molecule NOS2 and NO in macrophages. We also demonstrated ArgD mediated activation of the canonical NFkB pathway. Notably, we also show that ArgD is a specific TLR4 agonist involved in the activation of pro-inflammatory signaling for sustained production of effector cytokines. Intriguingly, ArgD protein treatment activated macrophages to acquire the M1 phenotype through the increased surface expression of MHCII and costimulatory molecules CD80 and CD86. ArgD induced robust B-cell response in immunized mice, validating its antigenicity potential as predicted by the in-silico analysis. These properties of M. tuberculosis ArgD signify its functional plasticity that could be exploited as a possible drug target to combat tuberculosis.

PncsHub: a platform for annotating and analyzing non-classically secreted proteins in Gram-positive bacteria.

From industry to food to health, bacteria play an important role in all facets of life. Some of the most important bacteria have been purposely engineered to produce commercial quantities of antibiotics and therapeutics, and non-classical secretion systems are at the forefront of these technologies. Unlike the classical Sec or Tat pathways, non-classically secreted proteins share few common characteristics and use much more diverse secretion pathways for protein transport. Systematically categorizing and investigating the non-classically secreted proteins will enable a deeper understanding of their associated secretion mechanisms and provide a landscape of the Gram-positive secretion pathway distribution. We therefore developed PncsHub (https://pncshub.erc.monash.edu/), the first universal platform for comprehensively annotating and analyzing Gram-positive bacterial non-classically secreted proteins. PncsHub catalogs 4,914 non-classically secreted proteins, which are delicately categorized into 8 subtypes (including the ‘unknown’ subtype) and annotated with data compiled from up to 26 resources and visualisation tools. It incorporates state-of-the-art predictors to identify new and homologous non-classically secreted proteins and includes three analytical modules to visualise the relationships between known and putative non-classically secreted proteins. As such, PncsHub aims to provide integrated services for investigating, predicting and identifying non-classically secreted proteins to promote hypothesis-driven laboratory-based experiments.

The role of RNA-binding proteins in mediating adaptive responses in Gram-positive bacteria.

Bacteria are constantly subjected to stressful conditions, such as antibiotic exposure, nutrient limitation and oxidative stress. For pathogenic bacteria, adapting to the host environment, escaping defence mechanisms and coping with antibiotic stress are crucial for their survival and the establishment of a successful infection. Stress adaptation relies heavily on the rate at which the organism can remodel its gene expression programme to counteract the stress. RNA-binding proteins mediating co- and post-transcriptional regulation have recently emerged as important players in regulating gene expression during adaptive responses. Most of the research on these layers of gene expression regulation has been done in Gram-negative model organisms where, thanks to a wide variety of global studies, large post-transcriptional regulatory networks have been uncovered. Unfortunately, our understanding of post-transcriptional regulation in Gram-positive bacteria is lagging behind. One possible explanation for this is that many proteins employed by Gram-negative bacteria are not well conserved in Gram-positives. And even if they are conserved, they do not always play similar roles as in Gram-negative bacteria. This raises the important question whether Gram-positive bacteria regulate gene expression in a significantly different way. The goal of this review was to discuss this in more detail by reviewing the role of well-known RNA-binding proteins in Gram-positive bacteria and by highlighting their different behaviours with respect to some of their Gram-negative counterparts. Finally, the second part of this review introduces several unusual RNA-binding proteins of Gram-positive species that we believe could also play an important role in adaptive responses.

Polymer Adhesin Domains in Gram-Positive Cell Surface Proteins.

Surface proteins in Gram-positive bacteria are often involved in biofilm formation, host-cell interactions, and surface attachment. Here we review a protein module found in surface proteins that are often encoded on various mobile genetic elements like conjugative plasmids. This module binds to different types of polymers like DNA, lipoteichoic acid and glucans, and is here termed polymer adhesin domain. We analyze all proteins that contain a polymer adhesin domain and classify the proteins into distinct classes based on phylogenetic and protein domain analysis. Protein function and ligand binding show class specificity, information that will be useful in determining the function of the large number of so far uncharacterized proteins containing a polymer adhesin domain.

PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins.

Gram-positive bacteria have developed secretion systems to transport proteins across their cell wall, a process that plays an important role during host infection. These secretion mechanisms have also been harnessed for therapeutic purposes in many biotechnology applications. Accordingly, the identification of features that select a protein for efficient secretion from these microorganisms has become an important task. Among all the secreted proteins, 'non-classical' secreted proteins are difficult to identify as they lack discernable signal peptide sequences and can make use of diverse secretion pathways. Currently, several computational methods have been developed to facilitate the discovery of such non-classical secreted proteins; however, the existing methods are based on either simulated or limited experimental datasets. In addition, they often employ basic features to train the models in a simple and coarse-grained manner. The availability of more experimentally validated datasets, advanced feature engineering techniques and novel machine learning approaches creates new opportunities for the development of improved predictors of 'non-classical' secreted proteins from sequence data. In this work, we first constructed a high-quality dataset of experimentally verified 'non-classical' secreted proteins, which we then used to create benchmark datasets. Using these benchmark datasets, we comprehensively analyzed a wide range of features and assessed their individual performance. Subsequently, we developed a two-layer Light Gradient Boosting Machine (LightGBM) ensemble model that integrates several single feature-based models into an overall prediction framework. At this stage, LightGBM, a gradient boosting machine, was used as a machine learning approach and the necessary parameter optimization was performed by a particle swarm optimization strategy. All single feature-based LightGBM models were then integrated into a unified ensemble model to further improve the predictive performance. Consequently, the final ensemble model achieved a superior performance with an accuracy of 0.900, an F-value of 0.903, Matthew's correlation coefficient of 0.803 and an area under the curve value of 0.963, and outperforming previous state-of-the-art predictors on the independent test. Based on our proposed optimal ensemble model, we further developed an accessible online predictor, PeNGaRoo, to serve users' demands. We believe this online web server, together with our proposed methodology, will expedite the discovery of non-classically secreted effector proteins in Gram-positive bacteria and further inspire the development of next-generation predictors. http://pengaroo.erc.monash.edu/. Supplementary data are available at Bioinformatics online.

Advanced Strategies for Food-Grade Protein Production: A New E. coli/Lactic Acid Bacteria Shuttle Vector for Improved Cloning and Food-Grade Expression.

Food-grade production of recombinant proteins in Gram-positive bacteria, especially in LAB (i.e., Lactococcus, Lactobacillus, and Streptococcus), is of great interest in the areas of recombinant enzyme production, industrial food fermentation, gene and metabolic engineering, as well as antigen delivery for oral vaccination. Food-grade expression relies on hosts generally considered as safe organisms and on clone selection not dependent on antibiotic markers, which limit the overall DNA manipulation workflow, as it can be carried out only in the expression host and not in E. coli. Moreover, many commercial expression vectors lack useful elements for protein purification. We constructed a “shuttle” vector containing a removable selective marker, which allows feasible cloning steps in E. coli and subsequent protein expression in LAB. In fact, the cassette can be easily excised from the selected recombinant plasmid, and the resulting marker-free vector transformed into the final LAB host. Further useful elements, as improved MCS, 6xHis-Tag, and thrombin cleavage site sequences were introduced. The resulting vector allows easy cloning in E. coli, can be quickly converted in a food-grade expression vector and harbors additional elements for improved recombinant protein purification. Overall, such features make the new vector an improved tool for food-grade expression.

Computational and mutational analysis of TatD DNase of Bacillus anthracis.

The role of TatD DNases as DNA repair enzymes or cell death (apoptotic) nucleases is well established in prokaryotes as well as eukaryotes. The current study aims to characterize the TatD nuclease from Bacillus anthracis (Ba TatD) and to explore its key histidine catalytic residues. Ba TatD was found to be a metal-dependent, nonspecific endonuclease which could efficiently cleave double-stranded DNA substrates. Moreover, Ba TatD nuclease was observed to be thermostable up to 55°C and act in a wide pH range indicating its industrial applicability. Diethyl pyrocarbonate-based histidine-selective alkylation of the Ba TatD resulted in a loss of its nuclease activity suggesting a crucial role of the histidine residues in its activity. The key residues of Ba TatD were predicted using sequence analysis and structure-based approaches, and then the predicted residues were further tested by mutational analysis. Upon mutational analysis, H128 and H153 have been found to be crucial for Ba TatD activity, though H153 seems to bear an important but a dispensable role for the Ba TatD nuclease. Ba TatD had a uniform expression in the cytosol of B. anthracis, which indicates a significant role of the protein in the pathogen's life cycle. This is the first study to identify and characterize the TatD DNase from B. anthracis and will be helpful in gaining more insights on the role of TatD proteins in Gram-positive bacteria where it remains unexplored.

Enrichment of Cell Surface-Associated Proteins in Gram-Positive Bacteria by Biotinylation or Trypsin Shaving for Mass Spectrometry Analysis.

In microbial cells surface-exposed proteins represent a physiologically important class of molecules as they enable these cells to interact with their environment both as free-living organisms and during interactions with a host. However, the characteristics of these proteins are quite divergent, which makes attempts to enrich, analyze, and quantify these molecules a challenging task. In this chapter two complementary methods for the enrichment and identification of cell surface-associated proteins, namely the biotinylation and the shaving approaches, are presented. Both protocols have been optimized for Gram-positive bacteria, and we provide a step-by-step guide for sample generation. Possible pitfalls during protein preparation are discussed.

In silico analyses of conservational, functional and phylogenetic distribution of the LuxI and LuxR homologs in Gram-positive bacteria

LuxI and LuxR are key factors that drive quorum sensing (QS) in bacteria through secretion and perception of the signaling molecules e.g. N-Acyl homoserine lactones (AHLs). The role of these proteins is well established in Gram-negative bacteria for intercellular communication but remain under-explored in Gram-positive bacteria where QS peptides are majorly responsible for cell-to-cell communication. Therefore, in the present study, we explored conservation, potential function, topological arrangements and evolutionarily aspects of these proteins in Gram-positive bacteria. Putative LuxI/LuxR containing proteins were retrieved using the domain-based strategy from InterPro v62.0 meta-database. Conservational analyses via multiple sequence alignment and domain showed that these are well conserved in Gram-positive bacteria and possess relatedness with Gram-negative bacteria. Further, Gene ontology and ligand-based functional annotation explain their active involvement in signal transduction mechanism via QS signaling molecules. Moreover, Phylogenetic analyses (LuxI, LuxR, LuxI + LuxR and 16s rRNA) revealed horizontal gene transfer events with significant statistical support among Gram-positive and Gram-negative bacteria. This in-silico study offers a detailed overview of potential LuxI/LuxR distribution in Gram-positive bacteria (mainly Firmicutes and Actinobacteria) and their functional role in QS. It would further help in understanding the extent of interspecies communications between Gram-positive and Gram-negative bacteria through QS signaling molecules.

Structure and specificity of a new class of Ca2+-independent housekeeping sortase from Streptomyces avermitilis provide insights into its non-canonical substrate preference

Surface proteins in Gram-positive bacteria are incorporated into the cell wall through a peptide ligation reaction catalyzed by transpeptidase sortase. Six main classes (A-F) of sortase have been identified of which class A sortase is meant for housekeeping functions. The prototypic housekeeping sortase A (SaSrtA) from Staphylococcus aureus cleaves LPXTG-containing proteins at the scissile T-G peptide bond and ligates protein-LPXT to the terminal Gly residue of the nascent cross-bridge of peptidoglycan lipid II precursor. Sortase-mediated ligation ("sortagging") of LPXTG-containing substrates and Gly-terminated nucleophiles occurs in vitro as well as in cellulo in the presence of Ca2+ and has been applied extensively for protein conjugations. Although the majority of applications emanate from SaSrtA, low catalytic efficiency, LPXTG specificity restriction, and Ca2+ requirement (particularly for in cellulo applications) remain a drawback. Given that Gram-positive bacteria genomes encode a variety of sortases, natural sortase mining can be a viable complementary approach akin to engineering of wild-type SaSrtA. Here, we describe the structure and specificity of a new class E sortase (SavSrtE) annotated to perform housekeeping roles in Streptomyces avermitilis Biochemical experiments define the attributes of an optimum peptide substrate, demonstrate Ca2+-independent activity, and provide insights about contrasting functional characteristics of SavSrtE and SaSrtA. Crystal structure, substrate docking, and mutagenesis experiments have identified a critical residue that dictates the preference for a non-canonical LAXTG recognition motif over LPXTG. These results have implications for rational tailoring of substrate tolerance in sortases. Besides, Ca2+-independent orthogonal specificity of SavSrtE is likely to expand the sortagging toolkit.

Structures of the surface exposed proteins of Gram positive bacteria

The Center for Structural Genomics for Infectious Diseases (CSGID) applies structural genomics approaches to biomedically important proteins from human pathogens. It also provides the infectious disease community with a high throughput pipeline for structure determination that carries out all steps of the process, from target selection through structure deposition. Target proteins include drug targets, essential enzymes, virulence factors and vaccine candidates. The CSGID has deposited over 680 structures in the Protein Data Bank. The proteins that are exposed on the surface of Gram positive bacterial pathogens (including Staphylococcus aureus, Bacillus anthracis, Listeria monocytogenes, Streptococcus species and Clostridium species) have been one focus area for the CSGID. So far, the structures of more than 55 of these proteins have been determined. The surface proteins are important in the interactions between the pathogen and its host, but many of them are as yet functionally uncharacterized. Among the examples that will be presented is the Bacillus anthracis SpoIID protein. SpoIID is part of a coordinated cell wall degradation machine that is essential for sporulation and the morphological changes involved. It represents a new family of lytic transglycosylases that degrade the glycan strands of the peptidoglycan cell wall. The two active site clefts in the dimeric enzyme include residues from both subunits, suggesting that the dimer is required for activity. This project has been funded in whole or in part with Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under Contracts No. HHSN272200700058C and HHSN272201200026C.

Isolation and identification of membrane vesicle-associated proteins in Gram-positive bacteria and mycobacteria

Many intracellular bacterial pathogens naturally release membrane vesicles (MVs) under a variety of growth environments. For pathogenic bacteria there are strong evidences that released MVs are a delivery mechanism for the release of immunologically active molecules that contribute to virulence. Identification of membrane vesicle-associated proteins that can act as immunological modulators is crucial for opening up new horizons for understanding the pathogenesis of certain bacteria and for developing novel vaccines. In this protocol, we provide all the details for isolating MVs secreted by either mycobacteria or Gram-positive bacteria and for the subsequent identification of the protein content of the MVs by mass spectrometry. The protocol is adapted from Gram-negative bacteria and involves four main steps: (1) isolation of MVs from the culture media; (2) purification of MVs by density gradient ultrucentrifugation; (3) acetone precipitation of the MVs protein content and in-solution trypsin digestion and (4) mass spectrometry analysis of the generated peptides and protein identification. Our modifications are:•Growing Mycobacteria in a chemically defined media to reduce the number of unrelated bacterial components in the supernatant.•The use of an ultrafiltration system, which allows concentrating larger volumes.•In solution digestion of proteins followed by peptides purification by ziptip.

Putative cobalt- and nickel-binding proteins and motifs in Streptococcus pneumoniae

Cobalt and nickel play important roles in various biological processes. The present work focuses on the enrichment and identification of Co- and Ni-binding motifs and proteins in Gram-positive bacteria. Immobilized metal affinity column (IMAC) was used to partially enrich putative metal-binding proteins and peptides from Streptococcus pneumoniae, and then LTQ-Orbitrap mass spectrometry (MS) was applied to identify and characterize the metal-binding motifs and proteins. In total, 208 and 223 proteins were isolated by Co- and Ni-IMAC columns respectively, in which 129 proteins were present in both preparations. Based on the gene ontology (GO) analysis, the putative metal-binding proteins were found to be mainly involved in protein metabolism, gene expression regulation and carbohydrate metabolism. These putative metal-binding proteins form a highly connected network, indicating that they may synergistically work together to achieve specific biological functions. Putative Co- and Ni-binding motifs were identified with H(X)nH, M(X)nH and H(X)nM derived from the identified 51 Co-binding peptides and 66 Ni-binding peptides. Statistics of frequency of amino acids in the metal-binding motifs showed that cobalt and nickel prefer to bind histidine and methionine, but not cysteine. These results obtained by a systematic metalloproteomic approach provide important clues for the further investigation of metal homeostasis and metal-related virulence of bacteria.

The immune evasion protein Sbi of Staphylococcus aureus occurs both extracellularly and anchored to the cell envelope by binding lipoteichoic acid

The Sbi protein of Staphylococcus aureus comprises two IgG-binding domains similar to those of protein A and a region that triggers the activation of complement C3. Sbi is expressed on the cell surface but its C-terminal domain lacks motifs associated with wall or membrane anchoring of proteins in Gram-positive bacteria. Cell-associated Sbi fractionates with the cytoplasmic membrane and is not solubilized during protoplast formation. S. aureus expressing Sbi truncates of the C-terminal Y domain allowed identification of residues that are required for association of Sbi with the membrane. Recombinant Sbi bound to purified cytoplasmic membrane material in vitro and to purified lipoteichoic acid. This explains how Sbi partitions with the membrane in fractionation experiments yet is partially exposed on the cell surface. An LTA-defective mutant of S. aureus had reduced levels of Sbi in the cytoplasmic membrane.

The RNPP family of quorum-sensing proteins in Gram-positive bacteria

Quorum sensing is one of several mechanisms that bacterial cells use to interact with each other and coordinate certain physiological processes in response to cell density. This mechanism is mediated by extracellular signaling molecules; once a critical threshold concentration has been reached, a target sensor kinase or response regulator is activated (or repressed), facilitating the expression of quorum sensing-dependent genes. Gram-positive bacteria mostly use oligo-peptides as signaling molecules. These cells have a special kind of quorum-sensing systems in which the receptor protein interacts directly with its cognate signaling peptide. The receptors are either Rap phosphatases or transcriptional regulators and integrate the protein family RNPP, from Rap, Npr, PlcR, and PrgX. These quorum-sensing systems control several microbial processes, like sporulation, virulence, biofilm formation, conjugation, and production of extracellular enzymes. Insights of the mechanism of protein-signaling peptide binding as well as the molecular interaction among receptor protein, signaling peptide, and target DNA have changed some earlier perceptions. In spite of the increased knowledge and the potential biotechnological applications of these quorum-sensing systems, few examples on engineering for biotechnological applications have been published. Real applications will arise only when researchers working in applied microbiology and biotechnology are aware of the importance of quorum-sensing systems for health and bioprocess applications.

Solution structure of the parvulin-type PPIase domain of Staphylococcus aureus PrsA – Implications for the catalytic mechanism of parvulins

BackgroundStaphylococcus aureus is a Gram-positive pathogenic bacterium causing many kinds of infections from mild respiratory tract infections to life-threatening states as sepsis. Recent emergence of S. aureus strains resistant to numerous antibiotics has created a need for new antimicrobial agents and novel drug targets. S. aureus PrsA is a membrane associated extra-cytoplasmic lipoprotein which contains a parvulin-type peptidyl-prolyl cis-trans isomerase domain. PrsA is known to act as an essential folding factor for secreted proteins in Gram-positive bacteria and thus it is a potential target for antimicrobial drugs against S. aureus.ResultsWe have solved a high-resolution solution structure of the parvulin-type peptidyl-prolyl cis-trans isomerase domain of S. aureus PrsA (PrsA-PPIase). The results of substrate peptide titrations pinpoint the active site and demonstrate the substrate preference of the enzyme. With detailed NMR spectroscopic investigation of the orientation and tautomeric state of the active site histidines we are able to give further insight into the structure of the catalytic site. NMR relaxation analysis gives information on the dynamic behaviour of PrsA-PPIase.ConclusionDetailed structural description of the S. aureus PrsA-PPIase lays the foundation for structure-based design of enzyme inhibitors. The structure resembles hPin1-type parvulins both structurally and regarding substrate preference. Even though a wealth of structural data is available on parvulins, the catalytic mechanism has yet to be resolved. The structure of S. aureus PrsA-PPIase and our findings on the role of the conserved active site histidines help in designing further experiments to solve the detailed catalytic mechanism.

PREDICTION OF CELL WALL SORTING SIGNALS IN GRAM-POSITIVE BACTERIA WITH A HIDDEN MARKOV MODEL: APPLICATION TO COMPLETE GENOMES

Surface proteins in Gram-positive bacteria are frequently implicated in virulence. We have focused on a group of extracellular cell wall-attached proteins (CWPs), containing an LPXTG motif for cleavage and covalent coupling to peptidoglycan by sortase enzymes. A hidden Markov model (HMM) approach for predicting the LPXTG-anchored cell wall proteins of Gram-positive bacteria was developed and compared against existing methods. The HMM model is parsimonious in terms of the number of freely estimated parameters, and it has proved to be very sensitive and specific in a training set of 55 experimentally verified LPXTG-anchored cell wall proteins as well as in reliable data sets of globular and transmembrane proteins. In order to identify such proteins in Gram-positive bacteria, a comprehensive analysis of 94 completely sequenced genomes has been performed. We identified, in total, 860 LPXTG-anchored cell wall proteins, a number that is significantly higher compared to those obtained by other available methods. Of these proteins, 237 are hypothetical proteins according to the annotation of SwissProt, and 88 had no homologs in the SwissProt database--this might be evidence that they are members of newly identified families of CWPs. The prediction tool, the database with the proteins identified in the genomes, and supplementary material are available online at http://bioinformatics.biol.uoa.gr/CW-PRED/.