Feature-based reappraisal of the Bacillus subtilis exoproteome

Proteogenomics in Aid of Host-Pathogen Interaction Studies: A Bacterial Perspective

By providing useful tools to study host-pathogen interactions, next-generation omics has recently enabled the study of gene expression changes in both pathogen and infected host simultaneously. However, since great discriminative power is required to study pathogen and host simultaneously throughout the infection process, the depth of quantitative gene expression profiling has proven to be unsatisfactory when focusing on bacterial pathogens, thus preferentially requiring specific strategies or the development of novel methodologies based on complementary omics approaches. In this review, we focus on the difficulties encountered when making use of proteogenomics approaches to study bacterial pathogenesis. In addition, we review different omics strategies (i.e., transcriptomics, proteomics and secretomics) and their applications for studying interactions of pathogens with their host.

Heterologous expression of family 10 xylanases from Acidothermus cellulolyticus enhances the exoproteome of Caldicellulosiruptor bescii and growth on xylan substrates

BACKGROUND

The ability to deconstruct plant biomass without conventional pretreatment has made members of the genus Caldicellulosiruptor the target of investigation for the consolidated processing of lignocellulosic biomass to biofuels and bioproducts. These Gram-positive bacteria are hyperthermophilic anaerobes and the most thermophilic cellulolytic organisms so far described. They use both C5 and C6 sugars simultaneously and have the ability to grow well on xylan, a major component of plant cell walls. This is an important advantage for their use to efficiently convert biomass at yields sufficient for an industrial process. For commodity chemicals, yield from substrate is perhaps the most important economic factor. In an attempt to improve even further the ability of C. bescii to use xylan, we introduced two xylanases from Acidothermus cellulolyticus. Acel_0180 includes tandem carbohydrate-binding modules (CBM2 and CBM3) located at the C-terminus, one of which, CBM2, is not present in C. bescii. Also, the sequences of Xyn10A and Acel_0180 have very little homology with the GH10 domains present in C. bescii. For these reasons, we selected these xylanases as potential candidates for synergistic interaction with those in the C. bescii exoproteome.

RESULTS

Heterologous expression of two xylanases from Acidothermus cellulolyticus in Caldicellulosiruptor bescii resulted in a modest, but significant increase in the activity of the exoproteome of C. bescii on xylan substrates. Even though the increase in extracellular activity was modest, the ability of C. bescii to grow on these substrates was dramatically improved suggesting that the xylan substrate/microbe interaction substantially increased deconstruction over the secreted free enzymes alone.

CONCLUSIONS

We anticipate that the ability to efficiently use xylan, a major component of plant cell walls for conversion of plant biomass to products of interest, will allow the conversion of renewable, sustainable, and inexpensive plant feedstocks to products at high yields.

The Anabaena sp. PCC 7120 Exoproteome: Taking a Peek outside the Box

The interest in examining the subset of proteins present in the extracellular milieu, the exoproteome, has been growing due to novel insights highlighting their role on extracellular matrix organization and biofilm formation, but also on homeostasis and development. The cyanobacterial exoproteome is poorly studied, and the role of cyanobacterial exoproteins on cell wall biogenesis, morphology and even physiology is largely unknown. Here, we present a comprehensive examination of the Anabaena sp. PCC 7120 exoproteome under various growth conditions. Altogether, 139 proteins belonging to 16 different functional categories have been identified. A large fraction (48%) of the identified proteins is classified as "hypothetical", falls into the "other categories" set or presents no similarity to other proteins. The evidence presented here shows that Anabaena sp. PCC 7120 is capable of outer membrane vesicle formation and that these vesicles are likely to contribute to the exoproteome profile. Furthermore, the activity of selected exoproteins associated with oxidative stress has been assessed, suggesting their involvement in redox homeostasis mechanisms in the extracellular space. Finally, we discuss our results in light of other cyanobacterial exoproteome studies and focus on the potential of exploring cyanobacteria as cell factories to produce and secrete selected proteins.

Proteinaceous determinants of surface colonization in bacteria: bacterial adhesion and biofilm formation from a protein secretion perspective

Bacterial colonization of biotic or abiotic surfaces results from two quite distinct physiological processes, namely bacterial adhesion and biofilm formation. Broadly speaking, a biofilm is defined as the sessile development of microbial cells. Biofilm formation arises following bacterial adhesion but not all single bacterial cells adhering reversibly or irreversibly engage inexorably into a sessile mode of growth. Among molecular determinants promoting bacterial colonization, surface proteins are the most functionally diverse active components. To be present on the bacterial cell surface, though, a protein must be secreted in the first place. Considering the close association of secreted proteins with their cognate secretion systems, the secretome (which refers both to the secretion systems and their protein substrates) is a key concept to apprehend the protein secretion and related physiological functions. The protein secretion systems are here considered in light of the differences in the cell-envelope architecture between diderm-LPS (archetypal Gram-negative), monoderm (archetypal Gram-positive) and diderm-mycolate (archetypal acid-fast) bacteria. Besides, their cognate secreted proteins engaged in the bacterial colonization process are regarded from single protein to supramolecular protein structure as well as the non-classical protein secretion. This state-of-the-art on the complement of the secretome (the secretion systems and their cognate effectors) involved in the surface colonization process in diderm-LPS and monoderm bacteria paves the way for future research directions in the field.

Precipitation of iron on the surface of Leptospira interrogans is associated with mutation of the stress response metalloprotease HtpX

High concentrations of free metal ions in the environment can be detrimental to bacterial survival. However, bacteria utilize strategies, including the activation of stress response pathways and immobilizing chemical elements on their surface, to limit this toxicity. In this study, we characterized LA4131, the HtpX-like M48 metalloprotease from Leptospira interrogans, with a putative role in bacterial stress response and membrane homeostasis. Growth of the la4131 transposon mutant strain (L522) in 360 μM FeSO4 (10-fold the normal in vitro concentration) resulted in the production of an amorphous iron precipitate. Atomic force microscopy and transmission electron microscopy analysis of the strain demonstrated that precipitate production was associated with the generation and release of outer membrane vesicles (OMVs) from the leptospiral surface. Transcriptional studies indicated that inactivation of la4131 resulted in altered expression of a subset of metal toxicity and stress response genes. Combining these findings, this report describes OMV production in response to environmental stressors and associates OMV production with the in vitro activity of an HtpX-like metalloprotease.

Comprehensive appraisal of the extracellular proteins from a monoderm bacterium: theoretical and empirical exoproteomes of Listeria monocytogenes EGD-e by secretomics

Defined as proteins actively transported via secretion systems, secreted proteins can have radically different subcellular destinations in monoderm (Gram-positive) bacteria. From degradative enzymes in saprophytes to virulence factors in pathogens, secreted proteins are the main tools used by bacteria to interact with their surroundings. The etiological agent of listeriosis, Listeria monocytogenes, is a Gram-positive facultative intracellular foodborne pathogen, whose ecological niche is the soil and as such should be primarily considered as a ubiquitous saprophyte. Recent advances on protein secretion systems in this species prompted us to investigate the exoproteome. First, an original and rational bioinformatic strategy was developed to mimic the protein exportation steps leading to the extracellular localization of secreted proteins; 79 exoproteins were predicted as secreted via Sec, 1 exoprotein via Tat, 4 bacteriocins via ABC exporters, 3 exoproteins via holins, and 3 exoproteins via the WXG100 system. This bioinformatic analysis allowed for defining a databank of the mature protein set in L. monocytogenes, which was used for generating the theoretical exoproteome and for subsequent protein identification by proteomics. 2-DE proteomic analyses were performed over a wide pI range to experimentally cover the largest protein spectrum possible. A total of 120 spots could be resolved and identified, which corresponded to 50 distinct proteins. These exoproteins were essentially virulence factors, degradative enzymes, and proteins of unknown functions, which exportation would essentially rely on the Sec pathway or nonclassical secretion. This investigation resulted in the first comprehensive appraisal of the exoproteome of L. monocytogenes EGD-e based on theoretical and experimental secretomic analyses, which further provided indications on listerial physiology in relation with its habitat and lifestyle. The novel and rational strategy described here is generic and has been purposely designed for the prediction of proteins localized extracellularly in monoderm bacteria.

Comparative proteomic analysis of extracellular proteins of Clostridium perfringens type A and type C strains

Clostridium perfringens is a medically important clostridial pathogen and an etiological agent causing several diseases in humans and animals. C. perfringens and its toxins have been listed as potential biological and toxin warfare (BTW) agents; thus, efforts to develop strategies for detection and protection are warranted. Forty-eight extracellular proteins of C. perfringens type A and type C strains have been identified here using a 2-dimensional gel electrophoresis-mass spectrometry (2-DE-MS) technique. The SagA protein, the DnaK-type molecular chaperone hsp70, endo-beta-N-acetylglucosaminidase, and hypothetical protein CPF_0656 were among the most abundant proteins secreted by C. perfringens ATCC 13124. The antigenic component of the exoproteome of this strain has also been identified. Most of the extracellular proteins were predicted to be involved in carbohydrate transport and metabolism (16%) or cell envelope biogenesis or to be outer surface protein constituents (13%). More than 50% of the proteins were predictably secreted by either classical or nonclassical pathways. LipoP and TMHMM indicated that nine proteins were extracytoplasmic but cell associated. Immunization with recombinant ornithine carbamoyltransferase (cOTC) clearly resulted in protection against a direct challenge with C. perfringens organisms. A significant rise in IgG titers in response to recombinant cOTC was observed in mice, and IgG2a titers predominated over IgG1 titers (IgG2a/IgG1 ratio, 2). The proliferation of spleen lymphocytes in cOTC-immunized animals suggested a cellular immune response. There were significant increases in the levels of gamma interferon (IFN-gamma) and interleukin 2 (IL-2), suggesting a Th1 type immune response.

Comparative subproteome analyses of planktonic and sessile Staphylococcus xylosus C2a: new insight in cell physiology of a coagulase-negative Staphylococcus in biofilm

Staphylococcus xylosus is a Gram-positive bacterium found on the skin of mammals and frequently isolated from food plants and fermented cheese or meat. To gain further insight in protein determinants involved in biofilm formation by this coagulase-negative Staphylococcus, a comparative proteomic analysis between planktonic and sessile cells was performed. With the use of a protocol previously developed, protein patterns of the cytoplasmic and cell envelope fractions were compared by 2-DE. Following protein identification by MALDI-TOF mass spectrometry and bioinformatic analyses, this study revealed differences in expression levels of 89 distinct proteins with 55 up-expressed and 34 down-expressed proteins in biofilm compared to planktonic cells. Most proteins differentially expressed were related to nitrogen and carbon metabolisms. Besides amino acid biosynthesis and protein translation, protein determinants related to protein secretion were up-expressed in biofilm, suggesting a more active protein trafficking in sessile cells. While up-expression of several enzymes involved in pentose phosphate and glycolytic pathways was observed in biofilm, connections with unexpected metabolic routes were further unravelled. Indeed, this proteomic analysis allowed identifying novel proteins that could be involved in a previously uncovered exopolysaccharide biosynthetic pathway in S. xylosus as well as several enzymes related to polyketide biosynthesis. This findings are particularly relevant considering exopolysaccharide production in S. xylosus is ica-independent contrary to coagulase-negative model strain Staphylococcus epidermidis RP62A.

Overflow of a hyper-produced secretory protein from the Bacillus Sec pathway into the Tat pathway for protein secretion as revealed by proteogenomics

Bacteria secrete numerous proteins into their environment for growth and survival under complex and ever-changing conditions. The highly different characteristics of secreted proteins pose major challenges to the cellular protein export machinery and, accordingly, different pathways have evolved. While the main secretion (Sec) pathway transports proteins in an unfolded state, the twin-arginine translocation (Tat) pathway transports folded proteins. To date, these pathways were believed to act in strictly independent ways. Here, we have employed proteogenomics to investigate the secretion mechanism of the esterase LipA of Bacillus subtilis, using a serendipitously obtained hyper-producing strain. While LipA is secreted Sec-dependently under standard conditions, hyper-produced LipA is secreted predominantly Tat-dependently via an unprecedented overflow mechanism. Two previously identified B. subtilis Tat substrates, PhoD and YwbN, require each a distinct Tat translocase for secretion. In contrast, hyper-produced LipA is transported by both Tat translocases of B. subtilis, showing that they have distinct but overlapping specificities. The identified overflow secretion mechanism for LipA focuses interest on the possibility that secretion pathway choice can be determined by environmental and intracellular conditions. This may provide an explanation for the previous observation that many Sec-dependently transported proteins have potential twin-arginine signal peptides for export via the Tat pathway.

Comparative proteomic analysis of the insulin-induced L6 myotube secretome

Emerging evidence has revealed an endocrine function for skeletal muscle; in fact, certain anti-inflammatory cytokines are secreted only from contractile skeletal muscle. However, the skeletal muscle secretome as a whole is poorly characterized, as is how it changes in response to extracellular stimuli. Herein, we sought to identify and characterize the members of the skeletal muscle secretome, and to determine which protein secretion levels were modulated in response to insulin stimulation. To conduct these studies, we treated differentiated L6 rat skeletal muscle cells with insulin or left them untreated, and we comparatively analyzed the proteins secreted into the media. We fractionated this conditioned media using offline RP HPLC, digested the fractionated proteins, and analyzed the resulting peptides with LC-ESI-MS/MS. We identified a total of 254 proteins, and by using three different filtering methods, we identified 153 of these as secretory proteins. Fourteen proteins were secreted at higher levels under insulin stimulation, including several proteins known to be highly secreted in metabolic diseases; 19 proteins were secreted at lower levels under insulin stimulation. These result not only pinpointed several previously unknown, insulin induced, secretory proteins of skeletal muscle, it also described a novel approach for conditioned secretome analysis.

Candida albicans cell wall proteins

The Candida albicans cell wall maintains the structural integrity of the organism in addition to providing a physical contact interface with the environment. The major components of the cell wall are fibrillar polysaccharides and proteins. The proteins of the cell wall are the focus of this review. Three classes of proteins are present in the candidal cell wall. One group of proteins attach to the cell wall via a glycophosphatidylinositol remnant or by an alkali-labile linkage. A second group of proteins with N-terminal signal sequences but no covalent attachment sequences are secreted by the classical secretory pathway. These proteins may end up in the cell wall or in the extracellular space. The third group of proteins lack a secretory signal, and the pathway(s) by which they become associated with the surface is unknown. Potential constituents of the first two classes have been predicted from analysis of genome sequences. Experimental analyses have identified members of all three classes. Some members of each class selected for consideration of confirmed or proposed function, phenotypic analysis of a mutant, and regulation by growth conditions and transcription factors are discussed in more detail.

Distinctive attributes for predicted secondary structures at terminal sequences of non-classically secreted proteins from proteobacteria

C- and N-terminal sequences (64 amino acid residues each) of 89 non-classically secreted type I, type III and type IV proteins (Swiss-Prot/TrEMBL) from proteobacteria were transformed into predicted secondary structures. Multivariate analysis of variance (MANOVA) confirmed the significance of location (C- or N-termini) and secretion type as essential factors in respect of quantitative representations of structured (a-helices, b-strands) and unstructured (coils) elements. The profiles of secondary structures were transcripted using unequal property values for helices, strands and coils and corresponding numerical vectors (independent variables) were subjected to multiple discriminant analysis with the types of secreted proteins as the dependent variables. The set of strong predictor variables (21 property values located at the region of 2–49 residues from the C-termini) was capable to classify all three types of non-classically secreted proteins with an accuracy of 93.3% for originally and 89.9% for cross-validated (leave-one-out procedure) grouped cases. The average error rate (0.137 ± 0.015) of k-fold (k = 3; 4; 6; 8; 10; 89) cross validation affirmed an acceptable prediction accuracy of defined discriminant functions with regard to the types of non-classically secreted proteins. The proposed prediction tool could be used to specify the secretome proteins from genomic sequences as well as to assess the compatibility between secretion pathways and secretion substrates of proteobacteria.

LocateP: genome-scale subcellular-location predictor for bacterial proteins

Background

In the past decades, various protein subcellular-location (SCL) predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, whereas others such as CELLO and Psortb.v.2.0 aim at a broader classification. Although these tools and pipelines can achieve a high precision in the accurate prediction of signal peptides and transmembrane helices, they have a much lower accuracy when other sequence characteristics are concerned. For instance, it proved notoriously difficult to identify the fate of proteins carrying a putative type I signal peptidase (SPIase) cleavage site, as many of those proteins are retained in the cell membrane as N-terminally anchored membrane proteins. Moreover, most of the SCL classifiers are based on the classification of the Swiss-Prot database and consequently inherited the inconsistency of that SCL classification. As accurate and detailed SCL prediction on a genome scale is highly desired by experimental researchers, we decided to construct a new SCL prediction pipeline: LocateP.

Results

LocateP combines many of the existing high-precision SCL identifiers with our own newly developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins. The pipeline was tested on data sets extracted from literature, including experimental proteomics studies. The tests showed that LocateP performs as well as, or even slightly better than other SCL predictors for some locations and outperforms current tools especially where the N-terminally anchored and the SPIase-cleaved secreted proteins are concerned. Overall, the accuracy of LocateP was always higher than 90%. LocateP was then used to predict the SCLs of all proteins encoded by completed Gram-positive bacterial genomes. The results are stored in the database LocateP-DB [1].

Conclusion

LocateP is by far the most accurate and detailed protein SCL predictor for Gram-positive bacteria currently available.

Metabolite profile analysis: from raw data to regression and classification

Successful metabolic profile analysis will aid in the fundamental understanding of physiology. Here, we present a possible analysis workflow. Initially, the procedure to transform raw data into a data matrix containing relative metabolite levels for each sample is described. Given that, because of experimental issues in the technical equipment, the levels of some metabolites cannot be universally determined or that different experiments need to be compared, missing value estimation and normalization are presented as helpful preprocessing steps. Regression methods are presented in this review as tools to relate metabolite levels with other physiological properties like biomass and gene expression. As the number of measured metabolites often exceeds the number of samples, dimensionality reduction methods are required. Two of these methods are discussed in detail in this review. Throughout this article, practical examples illustrating the application of the aforementioned methods are given. We focus on the uncovering the relationship between metabolism and growth-related properties.

Subcellular shotgun proteomics in plants: looking beyond the usual suspects

In this review we examine the current state of analytical methods used for shotgun proteomics experiments in plants. The rapid advances in this field in recent years are discussed, and contrasted with experiments performed using current widely used procedures. We also examine the use of subcellular fractionation approaches as they apply to plant proteomics, and discuss how appropriate sample preparation can produce a great increase in proteome coverage in subsequent analysis. We conclude that the conjunction of these two techniques represents a significant advance in plant proteomics, and the future of plant biology research will continue to be enriched by the ongoing development of proteomic analytical technology.

Distinctive amino acid residue periodicities in terminal sequences of type III and type I secreted proteins from proteobacteria

The Fourier transform (FT) method was applied to specify the distribution of 14 predefined groups of amino acids (64 residues) at both termini of annotated type III and type I secreted proteins from proteobacteria. Type I proteins displayed a higher occurrence of significant periodicities at both C-and N-termini, indicating potent features to discriminate between secretion types, particularly by the use of variables selected from the full periodicity profiles at 19 orders of FT. The Fishers linear discriminant analysis, together with the stepwise selection of variables throughout equal pairs of combinations for all predefined groups of residues, revealed the C-terminal harmonics of aromatic (HFWY) and aliphatic (VLIA) residues as a set of strong predictor variables to classify both types of secreted proteins with an accuracy of 100% for original grouped cases and 96.4% for cross-validated grouped cases. The prediction accuracy of proposed discriminant function was estimated by repeated k-fold cross-validation procedures where the original data set was randomly divided into k subsets, with one of the k-subsets serving as the test set and the remaining data forming the training set. The average error rate computed across all k-trials and repeats did not exceed that of leave-one-out procedure. The proposed set of predictor variables could be used to assess the compatibility between secretion pathways and secretion substrates of proteobacteria by means of discriminant analysis.