Prediction of lipoprotein signal peptides in Gram-positive bacteria with a Hidden Markov Model

Protein subcellular localization prediction tools

Protein subcellular localization prediction is of great significance in bioinformatics and biological research. Most of the proteins do not have experimentally determined localization information, computational prediction methods and tools have been acting as an active research area for more than two decades now. Knowledge of the subcellular location of a protein provides valuable information about its functionalities, the functioning of the cell, and other possible interactions with proteins. Fast, reliable, and accurate predictors provides platforms to harness the abundance of sequence data to predict subcellular locations accordingly. During the last decade, there has been a considerable amount of research effort aimed at developing subcellular localization predictors. This paper reviews recent subcellular localization prediction tools in the Eukaryotic, Prokaryotic, and Virus-based categories followed by a detailed analysis. Each predictor is discussed based on its main features, strengths, weaknesses, algorithms used, prediction techniques, and analysis. This review is supported by prediction tools taxonomies that highlight their rele- vant area and examples for uncomplicated categorization and ease of understandability. These taxonomies help users find suitable tools according to their needs. Furthermore, recent research gaps and challenges are discussed to cover areas that need the utmost attention. This survey provides an in-depth analysis of the most recent prediction tools to facilitate readers and can be considered a quick guide for researchers to identify and explore the recent literature advancements.

Fatty acids of Helicobacter pylori lipoproteins CagT and Lpp20

Bacterial lipoproteins are post-translationally modified by the addition of acyl chains that anchor the protein to bacterial membranes. This modification includes two ester-linked and one amide-linked acyl chain on lipoproteins from Gram-negative bacteria. Helicobacter pylori lipoproteins have important functions in pathogenesis (including delivering the CagA oncoprotein to mammalian cells) and are recognized by host innate and adaptive immune systems. The number and variety of acyl chains on lipoproteins impact the innate immune response through Toll-like receptor 2. The acyl chains added to lipoproteins are derived from membrane phospholipids. H. pylori membrane phospholipids have previously been shown to consist primarily of C14:0 and C19:0 cyclopropane-containing acyl chains. However, the acyl composition of H. pylori lipoproteins has not been determined. In this study, we characterized the acyl composition of two representative H. pylori lipoproteins, Lpp20 and CagT. Fatty acid methyl esters were prepared from both purified lipoproteins and analyzed by gas chromatography-mass spectrometry. For comparison, we also analyzed H. pylori phospholipids. Consistent with previous studies, we observed that the H. pylori phospholipids contain primarily C14:0 and C19:0 cyclopropane-containing fatty acids. In contrast, both the ester-linked and amide-linked fatty acids found in H. pylori lipoproteins were observed to be almost exclusively C16:0 and C18:0. A discrepancy between the acyl composition of membrane phospholipids and lipoproteins as reported here for H. pylori has been previously reported in other bacteria including Borrelia and Brucella. We discuss possible mechanisms.IMPORTANCEColonization of the stomach by Helicobacter pylori is an important risk factor in the development of gastric cancer, the third leading cause of cancer-related death worldwide. H. pylori persists in the stomach despite an immune response against the bacteria. Recognition of lipoproteins by TLR2 contributes to the innate immune response to H. pylori. However, the role of H. pylori lipoproteins in bacterial persistence is poorly understood. As the host response to lipoproteins depends on the acyl chain content, defining the acyl composition of H. pylori lipoproteins is an important step in characterizing how lipoproteins contribute to persistence.

Secretome analysis and virulence assessment in Abiotrophia defectiva

Background

Abiotrophia defectiva, although infrequently occurring, is a notable cause of culture-negative infective endocarditis with limited research on its virulence. Associated with oral infections such as dental caries, exploring its secretome may provide insights into virulence mechanisms. Our study aimed to analyze and characterize the secretome of A. defectiva strain CCUG 27639.

Methods

Secretome of A. defectiva was prepared from broth cultures and subjected to mass spectrometry and proteomics for protein identification. Inflammatory potential of the secretome was assessed by ELISA.

Results

Eighty-four proteins were identified, with diverse subcellular localizations predicted by PSORTb. Notably, 20 were cytoplasmic, 12 cytoplasmic membrane, 5 extracellular, and 9 cell wall-anchored proteins. Bioinformatics tools revealed 54 proteins secreted via the 'Sec' pathway and 8 via a non-classical pathway. Moonlighting functions were found in 23 proteins, with over 20 exhibiting potential virulence properties, including peroxiredoxin and oligopeptide ABC transporter substrate-binding protein. Gene Ontology and KEGG analyses categorized protein sequences in various pathways. STRING analysis revealed functional protein association networks. Cytokine profiling demonstrated significant proinflammatory cytokine release (IL-8, IL-1β, and CCL5) from human PBMCs.

Conclusions

Our study provides a comprehensive understanding of A. defectiva's secretome, laying the foundation for insights into its pathogenicity.

Review on computer-assisted biosynthetic capacities elucidation to assess metabolic interactions and communication within microbial communities

Microbial communities thrive through interactions and communication, which are challenging to study as most microorganisms are not cultivable. To address this challenge, researchers focus on the extracellular space where communication events occur. Exometabolomics and interactome analysis provide insights into the molecules involved in communication and the dynamics of their interactions. Advances in sequencing technologies and computational methods enable the reconstruction of taxonomic and functional profiles of microbial communities using high-throughput multi-omics data. Network-based approaches, including community flux balance analysis, aim to model molecular interactions within and between communities. Despite these advances, challenges remain in computer-assisted biosynthetic capacities elucidation, requiring continued innovation and collaboration among diverse scientists. This review provides insights into the current state and future directions of computer-assisted biosynthetic capacities elucidation in studying microbial communities.

Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model

Signal peptides (SPs) are essential to target and transfer transmembrane and secreted proteins to the correct positions. Many existing computational tools for predicting SPs disregard the extreme data imbalance problem and rely on additional group information of proteins. Here we introduce Unbiased Organism-agnostic Signal Peptide Network (USPNet), an SP classification and cleavage-site prediction deep learning method. Extensive experimental results show that USPNet substantially outperforms previous methods on classification performance by 10%. An SP-discovering pipeline with USPNet is designed to explore unprecedented SPs from metagenomic data. It reveals 347 SP candidates, with the lowest sequence identity between our candidates and the closest SP in the training dataset at only 13%. In addition, the template modeling scores between candidates and SPs in the training set are mostly above 0.8. The results showcase that USPNet has learnt the SP structure with raw amino acid sequences and the large protein language model, thereby enabling the discovery of unknown SPs.

Protein Sorting Prediction

Many computational methods are available for predicting protein sorting in bacteria. When comparing them, it is important to know that they can be grouped into three fundamentally different approaches: signal-based, global property-based, and homology-based prediction. In this chapter, the strengths and drawbacks of each of these approaches are described through many examples of methods that predict secretion, integration into membranes, or subcellular locations in general. The aim of this chapter is to provide a user-level introduction to the field with a minimum of computational theory.

Phosphorylation of CFP10 modulates Mycobacterium tuberculosis virulence

IMPORTANCE

Secreted virulence factors play a critical role in bacterial pathogenesis. Virulence effectors not only help bacteria to overcome the host immune system but also aid in establishing infection. Mtb, which causes tuberculosis in humans, encodes various virulence effectors. Triggers that modulate the secretion of virulence effectors in Mtb are yet to be fully understood. To gain mechanistic insight into the secretion of virulence effectors, we performed high-throughput proteomic studies. With the help of system-level protein-protein interaction network analysis and empirical validations, we unravelled a link between phosphorylation and secretion. Taking the example of the well-known virulence factor of CFP10, we show that the dynamics of CFP10 phosphorylation strongly influenced bacterial virulence and survival ex vivo and in vivo. This study presents the role of phosphorylation in modulating the secretion of virulence factors.

A conditional gene expression system in Porphyromonas gingivalis for study of the secretion mechanisms of lipoproteins and T9SS cargo proteins

The Gram-negative anaerobe, Porphyromonas gingivalis, is known to be a pathogen associated with chronic periodontitis. P. gingivalis possesses virulence factors such as fimbriae and gingipain proteinases. Fimbrial proteins are secreted to the cell surface as lipoproteins. In contrast, gingipain proteinases are secreted into the bacterial cell surface via the type IX secretion system (T9SS). The transport mechanisms of lipoproteins and T9SS cargo proteins are entirely different and remain unknown. Therefore, using the Tet-on system developed for the genus Bacteroides, we newly created a conditional gene expression system in P. gingivalis. We succeeded in establishing conditional expression of nanoluciferase and its derivatives for lipoprotein export, of FimA for a representative of lipoprotein export, and of T9SS cargo proteins such as Hbp35 and PorA for representatives of type 9 protein export. Using this system, we showed that the lipoprotein export signal, which has recently been found in other species in the phylum Bacteroidota, is also functional in FimA, and that a proton motive force inhibitor can affect type 9 protein export. Collectively, our conditional protein expression method is useful for screening inhibitors of virulence factors, and may be used to investigate the role of proteins essential to bacterial survival in vivo.

Identification and characterization of an abundant lipoprotein from Methylacidiphilum fumariolicum SolV

Bacterial lipoproteins are characterized by the presence of a conserved N-terminal lipid-modified cysteine residue that allows the hydrophilic protein to anchor into bacterial cell membranes. These lipoproteins play essential roles in a wide variety of physiological processes. Based on transcriptome analysis of the verrucomicrobial methanotroph Methylacidiphilum fumariolicum SolV, we identified a highly expressed lipoprotein, WP_009060351 (139 amino acids), in its genome. The first 86 amino acids are specific for the methanotrophic genera Methylacidiphilum and Methylacidmicrobium, while the last 53 amino acids are present only in lipoproteins of members from the phylum Verrucomicrobiota (Hedlund). Heterologous expression of WP_009060351 in Escherichia coli revealed a 25-kDa dimeric protein and a 60-kDa tetrameric protein. Immunoblotting showed that WP_009060351 was present in the total membrane protein and peptidoglycan fractions of M. fumariolicum SolV. The results suggest an involvement of lipoprotein WP_009060351 in the linkage between the outer membrane and the peptidoglycan.

Different culture media and purification methods unveil the core proteome of Propionibacterium freudenreichii-derived extracellular vesicles

Bacterial extracellular vesicles (EVs) are natural lipidic nanoparticles implicated in intercellular communication. Although EV research focused mainly on pathogens, the interest in probiotic-derived EVs is now rising. One example is Propionibacterium freudenreichii, which produces EVs with anti-inflammatory effects on human epithelial cells. Our previous study with P. freudenreichii showed that EVs purified by size exclusion chromatography (SEC) displayed variations in protein content according to bacterial growth conditions. Considering these content variations, we hypothesized that a comparative proteomic analysis of EVs recovered in different conditions would elucidate whether a representative vesicular proteome existed, possibly providing a robust proteome dataset for further analysis. Therefore, P. freudenreichii was grown in two culture media, and EVs were purified by sucrose density gradient ultracentrifugation (UC). Microscopic and size characterization confirmed EV purification, while shotgun proteomics unveiled that they carried a diverse set of proteins. A comparative analysis of the protein content of UC- and SEC-derived EVs, isolated from cultures either in UF (cow milk ultrafiltrate medium) or YEL (laboratory yeast extract lactate medium), showed that EVs from all these conditions shared 308 proteins. This EV core proteome was notably enriched in proteins related to immunomodulation. Moreover, it showed distinctive features, including highly interacting proteins, compositional biases for some specific amino acids, and other biochemical parameters. Overall, this work broadens the toolset for the purification of P. freudenreichii-derived EVs, identifies a representative vesicular proteome, and enumerates conserved features in vesicular proteins. These results hold the potential for providing candidate biomarkers of purification quality, and insights into the mechanisms of EV biogenesis and cargo sorting.

The Two-Track Investigation of Fibronectin Binding Protein A of Staphylococcus aureus from Bovine Mastitis as a Potential Candidate for Immunodiagnosis: A Pilot Study

Bovine mastitis is the most common disease affecting dairy cattle worldwide and it generates substantial losses for cattle breeders. One of the most common pathogens identified in infected milk samples is Staphylococcus aureus. Currently, there is no fast test for recognizing bacteria species on the market. The aim of this study was to bioinformatically and laboratory detect and characterize the fibronectin binding protein A (FnBPA) of S. aureus (SA) in milk samples obtained from cows diagnosed with mastitis. More than 90,000,000 amino acid sequences were subjected to bioinformatic detection in the search for a potential biomarker for bovine SA. The analysis of FnBPA included the detection of signal peptides and nonclassical proteins, antigenicity, and the prediction of epitopes. To confirm the presence of the fnbA gene in four SA isolates, amplification with specific primers was performed. FnBPA was detected by immunoblotting. The immunoreactivity and selectivity were performed with monoclonal anti-FnBPA antibodies and SA-negative serum. The bioinformatic analysis showed that FnBPA is a surface, conservative, immunoreactive, and species-specific protein with antigenic potential. Its presence was confirmed in all of the SA isolates we studied. Immunoblotting proved its immunoreactivity and specificity. Thus, it can be considered a potential biomarker in mastitis immunodiagnostics.

Detection of immunoreactive proteins of Escherichia coli, Streptococcus uberis, and Streptococcus agalactiae isolated from cows with diagnosed mastitis

Introduction

Mastitis is a widespread mammary gland disease of dairy cows that causes severe economic losses to dairy farms. Mastitis can be caused by bacteria, fungi, and algae. The most common species isolated from infected milk are, among others, Streptococcus spp., and Escherichia coli. The aim of our study was protein detection based on both in silico and in vitro methods, which allowed the identification of immunoreactive proteins representative of the following species: Streptococcus uberis, Streptococcus agalactiae, and Escherichia coli.

Methods

The study group included 22 milk samples and 13 serum samples obtained from cows with diagnosed mastitis, whereas the control group constituted 12 milk samples and 12 serum samples isolated from healthy animals. Detection of immunoreactive proteins was done by immunoblotting, while amino acid sequences from investigated proteins were determined by MALDI-TOF. Then, bioinformatic analyses were performed on detected species specific proteins in order to investigate their immunoreactivity.

Results

As a result, we identified 13 proteins: 3 (molybdenum cofactor biosynthesis protein B, aldehyde reductase YahK, outer membrane protein A) for E. coli, 4 (elongation factor Tu, tRNA uridine 5-carboxymethylaminomethyl modification enzyme MnmG, GTPase Obg, glyceraldehyde-3-phosphate dehydrogenase) for S. uberis, and 6 (aspartate carbamoyltransferase, elongation factor Tu, 60 kDa chaperonin, elongation factor G, galactose-6-phosphate isomerase subunit LacA, adenosine deaminase) for S. agalactiae, which demonstrated immunoreactivity to antibodies present in serum from cows with diagnosed mastitis.

Discussion

Due to the confirmed immunoreactivity, specificity and localization in the bacterial cell, these proteins can be considered considered potential targets in innovative rapid immunodiagnostic assays for bovine mastitis, however due to the limited number of examined samples, further examination is needed.

Transcriptome responses of intestinal epithelial cells induced by membrane vesicles of Listeria

Membrane vesicles (MVs) serve as an essential virulence factor in several pathogenic bacteria. The release of MVs by Listeria monocytogenes is only recently recognized; still, the enigmatic role of MVs in pathogenesis is yet to be established. We report the transcriptome response of Caco-2 cells upon exposure to MVs and the L. monocytogenes that leads to observe the up-regulation of autophagy-related genes in the early phase of exposure to MVs. Transcription of inflammatory cytokines is to the peak at the fourth hour of exposure. An array of differentially expressed genes was associated with actin cytoskeleton rearrangement, autophagy, cell cycle arrest, and induction of oxidative stress. At a later time point, transcriptional programs are generated upon interaction with MVs to evade innate immune signals, by modulating the expression of anti-inflammatory genes. KEGG pathway analysis is palpably confirming that MVs appear principally responsible for the induction of immune signaling pathways. Besides, MVs induced the expression of cell cycle regulatory genes, likely responsible for the ability to prolong host cell survival, thus protecting the replicative niche for L. monocytogenes. Notably, we identified several non-coding RNAs (ncRNAs), possibly involved in the regulation of early manipulation of the host gene expression, essential for the persistence of L. monocytogenes.

Impact of Environmental Conditions on the Protein Content of Staphylococcus aureus and Its Derived Extracellular Vesicles

Staphylococcus aureus, a major opportunistic pathogen in humans, produces extracellular vesicles (EVs) that are involved in cellular communication, the delivery of virulence factors, and modulation of the host immune system response. However, to date, the impact of culture conditions on the physicochemical and functional properties of S. aureus EVs is still largely unexplored. Here, we use a proteomic approach to provide a complete protein characterization of S. aureus HG003, a NCTC8325 derivative strain and its derived EVs under four growth conditions: early- and late-stationary growth phases, and in the absence and presence of a sub-inhibitory concentration of vancomycin. The HG003 EV protein composition in terms of subcellular localization, COG and KEGG categories, as well as their relative abundance are modulated by the environment and differs from that of whole-cell (WC). Moreover, the environmental conditions that were tested had a more pronounced impact on the EV protein composition when compared to the WC, supporting the existence of mechanisms for the selective packing of EV cargo. This study provides the first general picture of the impact of different growth conditions in the proteome of S. aureus EVs and its producing-cells and paves the way for future studies to understand better S. aureus EV production, composition, and roles.

Molecular Basis of the Slow Growth of Mycoplasma hominis on Different Energy Sources

Mycoplasma hominis is an opportunistic urogenital pathogen in vertebrates. It is a non-glycolytic species that produces energy via arginine degradation. Among genital mycoplasmas, M. hominis is the most commonly reported to play a role in systemic infections and can persist in the host for a long time. However, it is unclear how M. hominis proceeds under arginine limitation. The recent metabolic reconstruction of M. hominis has demonstrated its ability to catabolize deoxyribose phosphate to produce ATP. In this study, we cultivated M. hominis on two different energy sources (arginine and thymidine) and demonstrated the differences in growth rate, antibiotic sensitivity, and biofilm formation. Using label-free quantitative proteomics, we compared the proteome of M. hominis under these conditions. A total of 466 proteins were identified from M. hominis, representing approximately 85% of the predicted proteome, while the levels of 94 proteins changed significantly. As expected, we observed changes in the levels of metabolic enzymes. The energy source strongly affects the synthesis of enzymes related to RNA modifications and ribosome assembly. The translocation of lipoproteins and other membrane-associated proteins was also impaired. Our study, the first global characterization of the proteomic switching of M. hominis in arginine-deficiency media, illustrates energy source-dependent control of pathogenicity factors and can help to determine the mechanisms underlying the interaction between the growth rate and fitness of genome-reduced bacteria.

Proteomic analysis of the periodontal pathogen Prevotella intermedia secretomes in biofilm and planktonic lifestyles

Prevotella intermedia is an important species associated with periodontitis. Despite the remarkable clinical significance, little is known about the molecular basis for its virulence. The aim of this study was to characterize the secretome of P. intermedia in biofilm and planktonic life mode. The biofilm secretome showed 109 proteins while the planktonic secretome showed 136 proteins. The biofilm and the planktonic secretomes contained 17 and 33 signal-peptide bearing proteins, 13 and 18 lipoproteins, respectively. Superoxide reductase, sensor histidine kinase, C40 family peptidase, elongation factor Tu, threonine synthase etc. were unique to biofilm. Of the ~ 30 proteins with predicted virulence potential from biofilm and planktonic secretomes, only 6 were common between the two groups, implying large differences between biofilm and planktonic modes of P. intermedia. From Gene Ontology biofilm secretome displayed a markedly higher percent proteins compared to planktonic secretome in terms of cellular amino acid metabolic process, nitrogen compound metabolic process etc. Inflammatory cytokine profile analysis revealed that only the biofilm secretome, not the planktonic one, induced important cytokines such as MIP-1α/MIP-1β, IL-1β, and IL-8. In conclusion, the revealed differences in the protein profiles of P. intermedia biofilm and planktonic secretomes may trigger further questions about molecular mechanisms how this species exerts its virulence potential in the oral cavity.

A synthetic 'essentialome' for axenic culturing of 'Candidatus Liberibacter asiaticus'

OBJECTIVE

'Candidatus Liberibacter asiaticus' (CLas) is associated with the devastating citrus 'greening' disease. All attempts to achieve axenic growth and complete Koch's postulates with CLas have failed to date, at best yielding complex cocultures with very low CLas titers detectable only by PCR. Reductive genome evolution has rendered all pathogenic 'Ca. Liberibacter' spp. deficient in multiple key biosynthetic, metabolic and structural pathways that are highly unlikely to be rescued in vitro by media supplementation alone. By contrast, Liberibacter crescens (Lcr) is axenically cultured and its genome is both syntenic and highly similar to CLas. Our objective is to achieve replicative axenic growth of CLas via addition of missing culturability-related Lcr genes.

RESULTS

Bioinformatic analyses identified 405 unique ORFs in Lcr but missing (or truncated) in all 24 sequenced CLas strains. Site-directed mutagenesis confirmed and extended published EZ-Tn5 mutagenesis data, allowing elimination of 310 of these 405 genes as nonessential, leaving 95 experimentally validated Lcr genes as essential for CLas growth in axenic culture. Experimental conditions for conjugation of large GFP-expressing plasmids from Escherichia coli to Lcr were successfully established for the first time, providing a practical method for transfer of large groups of 'essential' Lcr genes to CLas.

The Cytoplasmic Domains of Streptococcus mutans Membrane Protein Insertases YidC1 and YidC2 Confer Unique Structural and Functional Attributes to Each Paralog

Integral and membrane-anchored proteins are pivotal to survival and virulence of the dental pathogen, Streptococcus mutans. The bacterial chaperone/insertase, YidC, contributes to membrane protein translocation. Unlike Escherichia coli, most Gram-positive bacteria contain two YidC paralogs. Herein, we evaluated structural features that functionally delineate S. mutans YidC1 and YidC2. Bacterial YidCs contain five transmembrane domains (TMD), two cytoplasmic loops, and a cytoplasmic tail. Because S. mutans YidC1 (SmYidC1) and YidC2 (SmYidC2) cytoplasmic domains (CD) are less well conserved than are TMD, we engineered ectopic expression of the 14 possible YidC1-YidC2 CD domain swap combinations. Growth and stress tolerance of each was compared to control strains ectopically expressing unmodified yidC1 or yidC2. Acid and osmotic stress sensitivity are associated with yidC2 deletion. Sensitivity to excess zinc was further identified as a ΔyidC1 phenotype. Overall, YidC1 tolerated CD substitutions better than YidC2. Preferences toward particular CD combinations suggested potential intramolecular interactions. In silico analysis predicted salt-bridges between C1 and C2 loops of YidC1, and C1 loop and C-terminal tail of YidC2, respectively. Mutation of contributing residues recapitulated ΔyidC1- and ΔyidC2-associated phenotypes. Taken together, this work revealed the importance of cytoplasmic domains in distinct functional attributes of YidC1 and YidC2, and identified key residues involved in interdomain interactions.

Subtractive proteomic analysis of antigenic extracellular proteins and design a multi-epitope vaccine against Staphylococcus aureus

Staphylococcus aureus is a versatile Gram's positive bacterium that can reside as an asymptomatic colonizer, which can cause a wide range of skin, soft-tissue, and nosocomial infections. A vaccine against multi-drug resistant S. aureus, therefore, is urgently needed. Subtractive proteomics and reverse vaccinology are newly emerging techniques to design multiepitope-based vaccines. The analysis of 7290 proteomes (sensitive and resistant strains), five potent nonhuman homologous vaccine targets [(UNIPORT ID Q2FZL3 (Staphopain B), Q2G2R8 (Staphopain A), Q2FWP0 (uncharacterized leukocidin-like protein 1), Q2G1S6 (uncharacterized protein), and Q2FWV3 (Staphylokinase, putative)] were selected. These proteins were absent in the gut microbiome, which further enhances the significance of these proteins in vaccine design. These five virulence-associated proteins mainly have a role in the invasion mechanism in the host phagocyte cells. MHC I, MHC II, and B cell epitopes were identified in these five proteins. Finalized epitopes were examined by different online servers to screen suitable epitopes for multi-epitope based vaccine design. Shortlisted antigenic and nonallergenic associated epitopes were joined with linkers to design 30 variants (VSA1-VSA30) of multi-epitope vaccine conjugates. The antigenicity and allergenicity of all the 30 vaccine constructs were identified, and VSA30 was found to have the highest antigenicity and lowest allergenicity, and hence was selected for further study. Accordingly, VSA30 was docked with different HLA allelic variants, and the best-docked complex (VSA30-1SYS) was further analyzed by molecular dynamics simulation (MDS). The MDS result confirms the interaction of VSA30 with MHC (HLA-allelic variant). Thus, the final vaccine construct was in silico cloned in the pET28a vector for suitable expression in a heterologous system. Therefore, the designed vaccine construct VSA-30 can be developed as an appropriate vaccine to target S. aureus infection. VSA-30 still needs experimental validation to assure the antigenic and immunogenic properties.

Influence of the Alternative Sigma Factor RpoN on Global Gene Expression and Carbon Catabolism in Enterococcus faecalis V583

The alternative sigma factor σ⁵⁴ has been shown to regulate the expression of a wide array of virulence-associated genes, as well as central metabolism, in bacterial pathogens. In Gram-positive organisms, the σ⁵⁴ is commonly associated with carbon metabolism. In this study, we show that the Enterococcus faecalis alternative sigma factor σ⁵⁴ (RpoN) and its cognate enhancer binding protein MptR are essential for mannose utilization and are primary contributors to glucose uptake through the Mpt phosphotransferase system. To gain further insight into how RpoN contributes to global transcriptional changes, we performed microarray transcriptional analysis of strain V583 and an isogenic rpoN mutant grown in a chemically defined medium with glucose as the sole carbon source. Transcripts of 340 genes were differentially affected in the rpoN mutant; the predicted functions of these genes mainly related to nutrient acquisition. These differentially expressed genes included those with predicted catabolite-responsive element (cre) sites, consistent with loss of repression by the major carbon catabolite repressor CcpA. To determine if the inability to efficiently metabolize glucose/mannose affected infection outcome, we utilized two distinct infection models. We found that the rpoN mutant is significantly attenuated in both rabbit endocarditis and murine catheter-associated urinary tract infection (CAUTI). Here, we examined a ccpA mutant in the CAUTI model and showed that the absence of carbon catabolite control also significantly attenuates bacterial tissue burden in this model. Our data highlight the contribution of central carbon metabolism to growth of E. faecalis at various sites of infection.

Evidence for the Mycobacterial Mce4 Transporter Being a Multiprotein Complex

Mycobacteria possess Mce transporters that import lipids and are thought to function analogously to ATP-binding cassette (ABC) transporters. However, whereas ABC transporters import substrates using a single solute-binding protein (SBP) to deliver a substrate to permease proteins in the membrane, mycobacterial Mce transporters have a potential for six SBPs (MceA to MceF) working with a pair of permeases (YrbEA and YrbEB), a cytoplasmic ATPase (MceG), and multiple Mce-associated membrane (Mam) and orphaned Mam (Omam) proteins to transport lipids. In this study, we used the model mycobacterium Mycobacterium smegmatis to study the requirement for individual Mce, Mam, and Omam proteins in Mce4 transport of cholesterol. All of the Mce4 and Mam4 proteins we investigated were required for cholesterol uptake. However, not all Omam proteins, which are encoded by genes outside mce loci, proved to contribute to cholesterol import. OmamA and OmamB were required for cholesterol import, while OmamC, OmamD, OmamE, and OmamF were not. In the absence of any single Mce4, Mam4, or Omam protein that we tested, the abundance of Mce4A and Mce4E declined. This relationship between the levels of Mce4A and Mce4E and these additional proteins suggests a network of interactions that assemble and/or stabilize a multiprotein Mce4 transporter complex. Further support for Mce transporters being multiprotein complexes was obtained by immunoprecipitation-mass spectrometry, in which we identified every single Mce, YrbE, MceG, Mam, and Omam protein with a role in cholesterol transport as associating with Mce4A. This study represents the first time any of these Mce4 transporter proteins has been shown to associate.IMPORTANCE How lipids travel between membranes of diderm bacteria is a challenging mechanistic question because lipids, which are hydrophobic molecules, must traverse a hydrophilic periplasm. This question is even more complex for mycobacteria, which have a unique cell envelope that is highly impermeable to molecules. A growing body of knowledge identifies Mce transporters as lipid importers for mycobacteria. Here, using protein stability experiments and immunoprecipitation-mass spectrometry, we provide evidence for mycobacterial Mce transporters existing as multiprotein complexes.

Comparison of Current Methods for Signal Peptide Prediction in Phytoplasmas

Although phytoplasma studies are still hampered by the lack of axenic cultivation methods, the availability of genome sequences allowed dramatic advances in the characterization of the virulence mechanisms deployed by phytoplasmas, and highlighted the detection of signal peptides as a crucial step to identify effectors secreted by phytoplasmas. However, various signal peptide prediction methods have been used to mine phytoplasma genomes, and no general evaluation of these methods is available so far for phytoplasma sequences. In this work, we compared the prediction performance of SignalP versions 3.0, 4.0, 4.1, 5.0 and Phobius on several sequence datasets originating from all deposited phytoplasma sequences. SignalP 4.1 with specific parameters showed the most exhaustive and consistent prediction ability. However, the configuration of SignalP 4.1 for increased sensitivity induced a much higher rate of false positives on transmembrane domains located at N-terminus. Moreover, sensitive signal peptide predictions could similarly be achieved by the transmembrane domain prediction ability of TMHMM and Phobius, due to the relatedness between signal peptides and transmembrane regions. Beyond the results presented herein, the datasets assembled in this study form a valuable benchmark to compare and evaluate signal peptide predictors in a field where experimental evidence of secretion is scarce. Additionally, this study illustrates the utility of comparative genomics to strengthen confidence in bioinformatic predictions.

Environmental conditions modulate the protein content and immunomodulatory activity of extracellular vesicles produced by the probiotic Propionibacterium freudenreichii

Propionibacterium freudenreichii is a probiotic Gram-positive bacterium with promising immunomodulatory properties. It modulates regulatory cytokines, mitigates the inflammatory response in vitro and in vivo These properties were initially attributed to specific bacterial surface proteins. Recently, we showed that extracellular vesicles (EVs) produced by P. freudenreichii CIRM-BIA129 mimic the immunomodulatory features of parent cells in vitro (i.e. modulating NF-κB transcription factor activity and IL-8 release) which underlies the role of EVs as mediators of the probiotic effects of the bacterium. The modulation of EV properties, and particularly of those with potential therapeutic applications such as the EVs produced by the probiotic P. freudenreichii, is one of the challenges in the field to achieve efficient yields with the desired optimal functionality. Here we evaluated whether the culture medium in which the bacteria are grown could be used as a lever to modulate the protein content and hence the properties of P. freudenreichii CIRM-BIA129 EVs. The physical, biochemical and functional properties of EVs produced from cells cultivated on laboratory Yeast Extract Lactate (YEL) medium and cow milk ultrafiltrate (UF) medium were compared. UF-derived EVs were more abundant, smaller in diameter and displayed more intense anti-inflammatory activity than YEL-derived EVs. Furthermore, the growth media modulated EV content in terms of both the identities and abundances of their protein cargos, suggesting different patterns of interaction with the host. Proteins involved in amino acid metabolism and central carbon metabolism were modulated, as were the key surface proteins mediating host-propionibacteria interactions.Importance Extracellular vesicles (EVs) are cellular membrane-derived nanosized particles that are produced by most cells in all three kingdoms of life. They play a pivotal role in cell-cell communication through their ability to transport bioactive molecules from donor to recipient cells. Bacterial EVs are important factors in host-microbe interactions. Recently we have shown that EVs produced by the probiotic P. freudenreichii exhibited immunomodulatory properties. We evaluate here the impact of environmental conditions, notably culture media, on P. freudenreichii EV production and function. We show that EVs display considerable differences in protein cargo and immunomodulation depending on the culture medium used. This work offers new perspectives for the development of probiotic EV-based molecular delivery systems, and reinforces the optimization of growth conditions as a tool to modulate the potential therapeutic applications of EVs.

Identification of Lead Compounds against Scm (fms10) in Enterococcus faecium Using Computer Aided Drug Designing

(1) Background: Enterococcus faecium DO is an environmental microbe, which is a mesophilic, facultative, Gram-positive, and multiple habitat microorganism. Enterococcus faecium DO is responsible for many diseases in human. The fight against infectious diseases is confronted by the development of multiple drug resistance in E. faecium. The focus of this research work is to identify a novel compound against this pathogen by using bioinformatics tools and technology. (2) Methods: We screened the proteome (accession No. PRJNA55353) information from the genome database of the National Centre for Biotechnology Information (NCBI) and suggested a potential drug target. I-TASSER was used to predict the three-dimensional structure of the protein, and the structure was optimized and minimized by different tools. PubChem and ChEBI were used to retrieve the inhibitors. Pharmacophore modeling and virtual screening were performed to identify novel compounds. Binding interactions of compounds with target protein were checked using LigPlot. pkCSM, SwissADME, and ProTox-II were used for adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. (3) Results: Novel selected compounds have improved absorption and have better ADMET properties. Based on our results, the chemically identified inhibitor ZINC48942 targeted the receptor that can inhibit the activity of infection in E. faecium. This research work will be beneficial for the scientific community and could aid in the design of a new drug against E. faecium infections. (4) Conclusions: It was observed that novel compounds are potential inhibitors with more efficacy and fewer side effects. This research work will help researchers in testing and identification of these chemicals useful against E. faecium.

Mechanistic Insight into Royal Protein Inhibiting the Gram-Positive Bacteria

Royal jelly (RJ), a natural honeybee product, has a wide range of antibacterial activities. N-glycosylated major royal jelly protein 2 (N-MRJP2), purified from RJ, can inhibit the growth of Paenibacillus larvae (P. larvae, Gram-positive), a contagious etiological agent of the American foulbrood disease of honeybees. However, the inhibitory mechanism is largely unknown. Antibacterial assay and membrane proteome were conducted to investigate the inhibition capacity of RJ from different instar larvae and P. larvae treated by N-MRJP2, respectively. The similar antibacterial efficiency of RJ from different larval instar indicates that RJ is vital for the adaptive immune defense of small larvae. The killing of P. larvae by N-MRJP2 is achieved by disturbing the cell wall biosynthesis, increasing the permeability of cell membrane, hindering aerobic respiration, restraining cell division and inducing cell death. This demonstrates that RJ is critical for the passive immunity of immature larvae and N-MRJP2 can be used as natural antibiotic substance to resist P. larvae, even for other gram-positive bacteria. This constitutes solid evidence that RJ and N-MRJP2 have potentials as novel antibacterial agents.

Living Therapeutics: The Next Frontier of Precision Medicine

Modern medicine has long studied the mechanism and impact of pathogenic microbes on human hosts, but has only recently shifted attention toward the complex and vital roles that commensal and probiotic microbes play in both health and dysbiosis. Fueled by an enhanced appreciation of the human-microbe holobiont, the past decade has yielded countless insights and established many new avenues of investigation in this area. In this review, we discuss advances, limitations, and emerging frontiers for microbes as agents of health maintenance, disease prevention, and cure. We highlight the flexibility of microbial therapeutics across disease states, with special consideration for the rational engineering of microbes toward precision medicine outcomes. As the field advances, we anticipate that tools of synthetic biology will be increasingly employed to engineer functional living therapeutics with the potential to address longstanding limitations of traditional drugs.

Peptidoglycan analysis reveals that synergistic deacetylase activity in vegetative Clostridium difficile impacts the host response

Clostridium difficile is an anaerobic and spore-forming bacterium responsible for 15-25% of postantibiotic diarrhea and 95% of pseudomembranous colitis. Peptidoglycan is a crucial element of the bacterial cell wall that is exposed to the host, making it an important target for the innate immune system. The C. difficile peptidoglycan is largely N-deacetylated on its glucosamine (93% of muropeptides) through the activity of enzymes known as N-deacetylases, and this N-deacetylation modulates host-pathogen interactions, such as resistance to the bacteriolytic activity of lysozyme, virulence, and host innate immune responses. C. difficile genome analysis showed that 12 genes potentially encode N-deacetylases; however, which of these N-deacetylases are involved in peptidoglycan N-deacetylation remains unknown. Here, we report the enzymes responsible for peptidoglycan N-deacetylation and their respective regulation. Through peptidoglycan analysis of several mutants, we found that the N-deacetylases PdaV and PgdA act in synergy. Together they are responsible for the high level of peptidoglycan N-deacetylation in C. difficile and the consequent resistance to lysozyme. We also characterized a third enzyme, PgdB, as a glucosamine N-deacetylase. However, its impact on N-deacetylation and lysozyme resistance is limited, and its physiological role remains to be dissected. Finally, given the influence of peptidoglycan N-deacetylation on host defense against pathogens, we investigated the virulence and colonization ability of the mutants. Unlike what has been shown in other pathogenic bacteria, a lack of N-deacetylation in C. difficile is not linked to a decrease in virulence.

Proteomics of extracellular vesicles produced by Granulicatella adiacens, which causes infective endocarditis

When oral bacteria accidentally enter the bloodstream due to transient tissue damage during dental procedures, they have the potential to attach to the endocardium or an equivalent surface of an indwelling prosthesis and cause infection. Many bacterial species produce extracellular vesicles (EVs) as part of normal physiology, but also use it as a virulence strategy. In this study, it was hypothesized that Granulicatella adiacens produce EVs that possibly help it in virulence. Therefore, the objectives were to isolate and characterize EVs produced by G. adiacens and to investigate its immune-stimulatory effects. The reference strain G. adiacens CCUG 27809 was cultured on chocolate blood agar for 2 days. From subsequent broth culture, the EVs were isolated using differential centrifugation and filtration protocol and then observed using scanning electron microscopy. Proteins in the vesicle preparation were identified by nano LC-ESI-MS/MS. The EVs proteome was analyzed and characterized using different bioinformatics tools. The immune-stimulatory effect of the EVs was studied via ELISA quantification of IL-8, IL-1β and CCL5, major proinflammatory cytokines, produced from stimulated human PBMCs. It was revealed that G. adiacens produced EVs, ranging in diameter from 30 to 250 nm. Overall, G. adiacens EVs contained 112 proteins. The proteome consists of several ribosomal proteins, DNA associated proteins, binding proteins, and metabolic enzymes. It was also shown that these EVs carry putative virulence factors including moonlighting proteins. These EVs were able to induce the production of IL-8, IL-1β and CCL5 from human PBMCs. Further functional characterization of the G. adiacens EVs may provide new insights into virulence mechanisms of this important but less studied oral bacterial species.

The Impacts of Sortase A and the 4'-Phosphopantetheinyl Transferase Homolog Sfp on Streptococcus mutans Extracellular Membrane Vesicle Biogenesis

Extracellular membrane vesicles (EMVs) are produced by many Gram-positive organisms, but information regarding vesiculogenesis is incomplete. We used single gene deletions to evaluate the impacts on Streptococcus mutans EMV biogenesis of Sortase A (SrtA), which affects S. mutans EMV composition, and Sfp, a 4'-phosphopantetheinyl transferase that affects Bacillus subtilis EMV stability. ΔsrtA EMVs were notably larger than Δsfp and wild-type (WT) EMVs. EMV proteins identified from all three strains are known to be involved in cell wall biogenesis and cell architecture, bacterial adhesion, biofilm cell density and matrix development, and microbial competition. Notably, the AtlA autolysin was not processed to its mature active form in the ΔsrtA mutant. Proteomic and lipidomic analyses of all three strains revealed multiple dissimilarities between vesicular and corresponding cytoplasmic membranes (CMs). A higher proportion of EMV proteins are predicted substrates of the general secretion pathway (GSP). Accordingly, the GSP component SecA was identified as a prominent EMV-associated protein. In contrast, CMs contained more multi-pass transmembrane (TM) protein substrates of co-translational transport machineries than EMVs. EMVs from the WT, but not the mutant strains, were enriched in cardiolipin compared to CMs, and all EMVs were over-represented in polyketide flavonoids. EMVs and CMs were rich in long-chain saturated, monounsaturated, and polyunsaturated fatty acids, except for Δsfp EMVs that contained exclusively polyunsaturated fatty acids. Lipoproteins were less prevalent in EMVs of all three strains compared to their CMs. This study provides insight into biophysical characteristics of S. mutans EMVs and indicates discrete partitioning of protein and lipid components between EMVs and corresponding CMs of WT, ΔsrtA, and Δsfp strains.

In Silico Identification of Novel Immunogenic Secreted Proteins of Mycoplasma bovis from Secretome Data and Experimental Verification

Mycoplasma bovis is a major pathogen, responsible for bovine respiratory diseases worldwide. The present lack of effective control measures leaves cattle owners at considerable perpetual risk of M. bovis outbreaks. In this study, we identified M. bovis secreted immunogenic proteins in silico as potential candidates for novel diagnostic agents and vaccines. We used immunoinformatics to analyze 438 M. bovis proteins previously identified with a label-free proteomics analysis of virulent M. bovis HB0801 (P1) and its attenuated P150 strains. The subcellular localization of these proteins was preliminarily screened and 59 proteins were found to be secreted extracellular proteins. Twenty-seven of these proteins contained a large number of predictive T-cell epitopes presented by major histocompatibility complex (MHC) class I and II molecules. Twenty-two of these 27 proteins had a high number of conformational B-cell epitopes, predicted from the corresponding 3D structural templates, including one unique to P1, two unique to P150, and 19 common to both strains. Five proteins were selected for further validation, and two of these, MbovP274 and MbovP570, were successfully expressed and purified. Both were confirmed to be secretory and highly immunogenic proteins that induced a mouse antibody response, reacted with cattle serum positive for M. bovis infection, and significantly increased the production of interleukin 8 (IL-8), IL-12 and interferon γ (IFN-γ) during the secretion of these three cytokines by both M. bovis mutants of these genes. These results should be useful in the development of novel immunological agents against M. bovis infection.

Extracellular Vesicles Produced by the Probiotic Propionibacterium freudenreichii CIRM-BIA 129 Mitigate Inflammation by Modulating the NF-κB Pathway

Extracellular vesicles (EVs) are nanometric spherical structures involved in intercellular communication, whose production is considered to be a widespread phenomenon in living organisms. Bacterial EVs are associated with several processes that include survival, competition, pathogenesis, and immunomodulation. Among probiotic Gram-positive bacteria, some Propionibacterium freudenreichii strains exhibit anti-inflammatory activity, notably via surface proteins such as the surface-layer protein B (SlpB). We have hypothesized that, in addition to surface exposure and secretion of proteins, P. freudenreichii may produce EVs and thus export immunomodulatory proteins to interact with the host. In order to demonstrate their production in this species, EVs were purified from cell-free culture supernatants of the probiotic strain P. freudenreichii CIRM-BIA 129, and their physicochemical characterization, using transmission electron microscopy and nanoparticle tracking analysis (NTA), revealed shapes and sizes typical of EVs. Proteomic characterization showed that EVs contain a broad range of proteins, including immunomodulatory proteins such as SlpB. In silico protein-protein interaction predictions indicated that EV proteins could interact with host proteins, including the immunomodulatory transcription factor NF-κB. This potential interaction has a functional significance because EVs modulate inflammatory responses, as shown by IL-8 release and NF-κB activity, in HT-29 human intestinal epithelial cells. Indeed, EVs displayed an anti-inflammatory effect by modulating the NF-κB pathway; this was dependent on their concentration and on the proinflammatory inducer (LPS-specific). Moreover, while this anti-inflammatory effect partly depended on SlpB, it was not abolished by EV surface proteolysis, suggesting possible intracellular sites of action for EVs. This is the first report on identification of P. freudenreichii-derived EVs, alongside their physicochemical, biochemical and functional characterization. This study has enhanced our understanding of the mechanisms associated with the probiotic activity of P. freudenreichii and identified opportunities to employ bacterial-derived EVs for the development of bioactive products with therapeutic effects.

JUCHMME: a Java Utility for Class Hidden Markov Models and Extensions for biological sequence analysis

SUMMARY

JUCHMME is an open-source software package designed to fit arbitrary custom Hidden Markov Models (HMMs) with a discrete alphabet of symbols. We incorporate a large collection of standard algorithms for HMMs as well as a number of extensions and evaluate the software on various biological problems. Importantly, the JUCHMME toolkit includes several additional features that allow for easy building and evaluation of custom HMMs, which could be a useful resource for the research community.

AVAILABILITY AND IMPLEMENTATION

http://www.compgen.org/tools/juchmme, https://github.com/pbagos/juchmme.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Semi-supervised learning of Hidden Markov Models for biological sequence analysis

MOTIVATION

Hidden Markov Models (HMMs) are probabilistic models widely used in applications in computational sequence analysis. HMMs are basically unsupervised models. However, in the most important applications, they are trained in a supervised manner. Training examples accompanied by labels corresponding to different classes are given as input and the set of parameters that maximize the joint probability of sequences and labels is estimated. A main problem with this approach is that, in the majority of the cases, labels are hard to find and thus the amount of training data is limited. On the other hand, there are plenty of unclassified (unlabeled) sequences deposited in the public databases that could potentially contribute to the training procedure. This approach is called semi-supervised learning and could be very helpful in many applications.

RESULTS

We propose here, a method for semi-supervised learning of HMMs that can incorporate labeled, unlabeled and partially labeled data in a straightforward manner. The algorithm is based on a variant of the Expectation-Maximization (EM) algorithm, where the missing labels of the unlabeled or partially labeled data are considered as the missing data. We apply the algorithm to several biological problems, namely, for the prediction of transmembrane protein topology for alpha-helical and beta-barrel membrane proteins and for the prediction of archaeal signal peptides. The results are very promising, since the algorithms presented here can significantly improve the prediction performance of even the top-scoring classifiers.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Extracellular vesicles produced by human and animal Staphylococcus aureus strains share a highly conserved core proteome

Staphylococcus aureus is an important opportunistic pathogen of humans and animals. It produces extracellular vesicles (EVs) that are involved in cellular communication and enable inter-kingdom crosstalk, the delivery of virulence factors and modulation of the host immune response. The protein content of EVs determines their biological functions. Clarifying which proteins are selected, and how, is of crucial value to understanding the role of EVs in pathogenesis and the development of molecular delivery systems. Here, we postulated that S. aureus EVs share a common proteome containing components involved in cargo sorting. The EV proteomes of five S. aureus strains originating from human, bovine, and ovine hosts were characterised. The clustering of EV proteomes reflected the diversity of the producing strains. A total of 253 proteins were identified, 119 of which composed a core EV proteome with functions in bacterial survival, pathogenesis, and putatively in EV biology. We also identified features in the sequences of EV proteins and the corresponding genes that could account for their packaging into EVs. Our findings corroborate the hypothesis of a selective sorting of proteins into EVs and offer new perspectives concerning the roles of EVs in S. aureus pathogenesis in specific host niches.

Prolonged Heat Stress of Lactobacillus paracasei GCRL163 Improves Binding to Human Colorectal Adenocarcinoma HT-29 Cells and Modulates the Relative Abundance of Secreted and Cell Surface-Located Proteins

Lactobacillus casei group bacteria improve cheese ripening and may interact with host intestinal cells as probiotics, where surface proteins play a key role. Three complementary methods [trypsin shaving (TS), LiCl-sucrose (LS) extraction, and extracellular culture fluid precipitation] were used to analyze cell surface proteins of Lactobacillus paracasei GCRL163 by label-free quantitative proteomics after culture to the mid-exponential phase in bioreactors at pH 6.5 and temperatures of 30-45 °C. A total of 416 proteins, including 300 with transmembrane, cell wall anchoring, and secretory motifs and 116 cytoplasmic proteins, were quantified as surface proteins. Although LS caused significantly greater cell lysis as growth temperature increased, higher numbers of extracytoplasmic proteins were exclusively obtained by LS treatment. Together with the increased positive surface charge of cells cultured at supra-optimal temperatures, proteins including cell wall hydrolases Msp1/p75 and Msp2/p40, α-fucosidase AlfB, SecA, and a PspC-domain putative adhesin were upregulated in surface or secreted protein fractions, suggesting that cell adhesion may be altered. Prolonged heat stress (PHS) increased binding of L. paracasei GCRL163 to human colorectal adenocarcinoma HT-29 cells, relative to acid-stressed cells. This study demonstrates that PHS influences cell adhesion and relative abundance of proteins located on the surface, which may impact probiotic functionality, and the detected novel surface proteins likely linked to the cell cycle and envelope stress.

A Multifunctional Polysaccharide Utilization Gene Cluster in Colwellia echini Encodes Enzymes for the Complete Degradation of κ-Carrageenan, ι-Carrageenan, and Hybrid β/κ-Carrageenan

Here, we report that a recently described bacterium, Colwellia echini, harbors a large number of enzymes enabling the bacterium to grow on κ-carrageenan and agar. The genes are organized in two clusters that encode enzymes for the total degradation of κ-carrageenan and agar, respectively. As the first, we report on the structure/function relationship of a new class of enzymes that hydrolyze furcellaran, a partially sulfated β/κ-carrageenan. Using an in silico model, we hypothesize a molecular structure of furcellaranases and compare structural features and active site architectures of furcellaranases with those of other GH16 polysaccharide hydrolases, such as κ-carrageenases, β-agarases, and β-porphyranases. Furthermore, we describe a new class of enzymes distantly related to GH42 and GH160 β-galactosidases and show that this new class of enzymes is active only on hybrid β/κ-carrageenan oligosaccharides. Finally, we propose a new model for how the carrageenolytic enzyme repertoire enables C. echini to metabolize β/κ-, κ-, and ι-carrageenan.

Algal cell wall polysaccharides constitute a large fraction in the biomass of marine primary producers and are thus important in nutrient transfer between trophic levels in the marine ecosystem. In order for this transfer to take place, polysaccharides must be degraded into smaller mono- and disaccharide units, which are subsequently metabolized, and key components in this degradation are bacterial enzymes. The marine bacterium Colwellia echini A3^T is a potent enzyme producer since it completely hydrolyzes agar and κ-carrageenan. Here, we report that the genome of C. echini A3^T harbors two large gene clusters for the degradation of carrageenan and agar, respectively. Phylogenetical and functional studies combined with transcriptomics and in silico structural modeling revealed that the carrageenolytic cluster encodes furcellaranases, a new class of glycoside hydrolase family 16 (GH16) enzymes that are key enzymes for hydrolysis of furcellaran, a hybrid carrageenan containing both β- and κ-carrageenan motifs. We show that furcellaranases degrade furcellaran into neocarratetraose-43-O-monosulfate [DA-(α1,3)-G4S-(β1,4)-DA-(α1,3)-G], and we propose a molecular model of furcellaranases and compare the active site architectures of furcellaranases, κ-carrageenases, β-agarases, and β-porphyranases. Furthermore, C. echini A3^T was shown to encode κ-carrageenases, ι-carrageenases, and members of a new class of enzymes, active only on hybrid β/κ-carrageenan tetrasaccharides. On the basis of our genomic, transcriptomic, and functional analyses of the carrageenolytic enzyme repertoire, we propose a new model for how C. echini A3^T degrades complex sulfated marine polysaccharides such as furcellaran, κ-carrageenan, and ι-carrageenan.

IMPORTANCE Here, we report that a recently described bacterium, Colwellia echini, harbors a large number of enzymes enabling the bacterium to grow on κ-carrageenan and agar. The genes are organized in two clusters that encode enzymes for the total degradation of κ-carrageenan and agar, respectively. As the first, we report on the structure/function relationship of a new class of enzymes that hydrolyze furcellaran, a partially sulfated β/κ-carrageenan. Using an in silico model, we hypothesize a molecular structure of furcellaranases and compare structural features and active site architectures of furcellaranases with those of other GH16 polysaccharide hydrolases, such as κ-carrageenases, β-agarases, and β-porphyranases. Furthermore, we describe a new class of enzymes distantly related to GH42 and GH160 β-galactosidases and show that this new class of enzymes is active only on hybrid β/κ-carrageenan oligosaccharides. Finally, we propose a new model for how the carrageenolytic enzyme repertoire enables C. echini to metabolize β/κ-, κ-, and ι-carrageenan.

A Brief History of Protein Sorting Prediction

Ever since the signal hypothesis was proposed in 1971, the exact nature of signal peptides has been a focus point of research. The prediction of signal peptides and protein subcellular location from amino acid sequences has been an important problem in bioinformatics since the dawn of this research field, involving many statistical and machine learning technologies. In this review, we provide a historical account of how position-weight matrices, artificial neural networks, hidden Markov models, support vector machines and, lately, deep learning techniques have been used in the attempts to predict where proteins go. Because the secretory pathway was the first one to be studied both experimentally and through bioinformatics, our main focus is on the historical development of prediction methods for signal peptides that target proteins for secretion; prediction methods to identify targeting signals for other cellular compartments are treated in less detail.

Proteomic Analysis and Virulence Assessment of Granulicatella adiacens Secretome

Despite reports on the occurrence of Granulicatella adiacens in infective endocarditis, few mechanistic studies on its virulence characteristics or pathogenicity are available. Proteins secreted by this species may act as determinants of host-microbe interaction and play a role in virulence. Our aim in this study was to investigate and functionally characterize the secretome of G. adiacens. Proteins in the secretome preparation were digested by trypsin and applied to nanoLC-ESI-MS/MS. By using a combined mass spectrometry and bioinformatics approach, we identified 101 proteins. Bioinformatics tools predicting subcellular localization revealed that 18 of the secreted proteins possessed signal sequence. More than 20% of the secretome proteins were putative virulence proteins including serine protease, superoxide dismutase, aminopeptidase, molecular chaperone DnaK, and thioredoxin. Ribosomal proteins, molecular chaperones, and glycolytic enzymes, together known as "moonlighting proteins," comprised fifth of the secretome proteins. By Gene Ontology analysis, more than 60 proteins of the secretome were grouped in biological processes or molecular functions. KEGG pathway analysis disclosed that the secretome consisted of enzymes involved in biosynthesis of antibiotics. Cytokine profiling revealed that secreted proteins stimulated key cytokines, such as IL-1β, MCP-1, TNF-α, and RANTES from human PBMCs. In summary, the results from the current investigation of the G. adiacens secretome provide a basis for understanding possible pathogenic mechanisms of G. adiacens.

Comparative proteomics of two Mycoplasma hyopneumoniae strains and Mycoplasma flocculare identified potential porcine enzootic pneumonia determinants

Mycoplasma hyopneumoniae and Mycoplasma flocculare are genetically similar bacteria, which coinhabit the porcine respiratory tract. These mycoplasmas share most of the known virulence factors, but, while M. hyopneumoniae causes porcine enzootic pneumonia (PEP), M. flocculare is a commensal species. To identify potential PEP determinants and provide novel insights on mycoplasma-host interactions, the whole cell proteomes of two M. hyopneumoniae strains, one pathogenic (7448) and other non-pathogenic (J), and M. flocculare were compared. A cell fractioning approach combined with mass spectrometry (LC-MS/MS) proteomics was used to analyze cytoplasmic and surface-enriched protein fractions. Average detection of ~ 50% of the predicted proteomes of M. hyopneumoniae 7448 and J, and M. flocculare was achieved. Many of the identified proteins were differentially represented in M. hyopneumoniae 7448 in comparison to M. hyopneumoniae J and M. flocculare, including potential PEP determinants, such as adhesins, proteases, and redox-balancing proteins, among others. The LC-MS/MS data also provided experimental validation for several genes previously regarded as hypothetical for all analyzed mycoplasmas, including some coding for proteins bearing virulence-related functional domains. The comprehensive proteome profiling of two M. hyopneumoniae strains and M. flocculare provided tens of novel candidates to PEP determinants or virulence factors, beyond those classically described.

Comprehensive proteomic analysis and pathogenic role of membrane vesicles of Listeria monocytogenes serotype 4b reveals proteins associated with virulence and their possible interaction with host

Membrane vesicles (MVs) are produced by various Gram positive and Gram negative pathogenic bacteria and play an important role in virulence. In this study, the membrane vesicles (MVs) of L. monocytogenes were isolated from the culture supernatant. High-resolution electron microscopy and dynamic light scattering analysis revealed that L. monocytogenes MVs are spherical with a diameter of 200 to 300 nm in size. Further, comprehensive proteomic analyses of MVs and whole cells of L. monocytogenes were performed using LC/MS/MS. A total of 1355 and 312 proteins were identified in the L. monocytogenes cells and MVs, respectively. We identified that 296 proteins are found in both whole cells, and MV proteome and 16 proteins were identified only in the MVs. Also, we have identified the virulence factors such as listeriolysin O (LLO), internalin B (InlB), autolysin, p60, NLP/P60 family protein, UPF0356 protein, and PLC-A in MVs. Computational prediction of host-MV interactions revealed a total of 1841 possible interactions with the host involving 99 MV proteins and 1513 host proteins. We elucidated the possible pathway that mediates internalization of L. monocytogenes MV to host cells and the subsequent pathogenesis mechanisms. The in vitro infection assays showed that the purified MVs could induce cytotoxicity in Caco-2 cells. Using endocytosis inhibitors, we demonstrated that MVs are internalized via actin-mediated endocytosis. These results suggest that L. monocytogenes MVs can interact with host cell and contribute to the pathogenesis of L. monocytogenes during infection.

Prioritization of potential vaccine targets using comparative proteomics and designing of the chimeric multi-epitope vaccine against Pseudomonas aeruginosa

Multidrug-resistant Pseudomonas aeruginosa is one of the worldwide health problems involved in elevated mortality and morbidity. Therefore, it is important to find a therapeutic for this pathogen. In the present study, we have designed a chimeric vaccine against P. aeruginosa with the help of comparative proteomics and reverse vaccinology approaches. Using comparative subtractive proteomic analysis of 1,191 proteomes of P. aeruginosa, a total of twenty unique non-redundant proteomes were selected. In these proteomes, fifteen outer membrane proteins (OMPs) of P. aeruginosa were selected based on the basis of hydrophilicity, non-secretory nature, low transmembrane helix (<1), essentiality, virulence, pathway association, antigenic, and protein-protein network analysis. Reverse vaccinology approach was used to identify antigenic and immunogenic MHC class I, MHC class II and B cell epitopes present in the selected OMPs that can enhance T cell and B cell mediated immunogenicity. The selected epitopes were shortlisted based on their allergenicity, toxicity potentials, solubility, and hydrophilicity analysis. Immunogenic peptides were used to design a multi-epitope vaccine construct. Immune-modulating adjuvants and PADRE (Pan HLA-DR epitopes) sequence were added with epitopes sequence to enhance the immunogenicity. All the epitopes, adjuvants and PADRE sequence were joined by linkers. The designed vaccine constructs (VT1, VT2, VT3, and VT4) were analyzed by their physiochemical properties using different tools. Selected chimeric vaccine constructs (VT1, VT3, and VT4) were further shortlisted by their docking score with different HLA alleles. The final selected VT4 construct was docked with TLR4/MD2 complex and confirmed by molecular dynamics simulation studies. The final vaccine VT-4 construct was in-silico cloned in pET28a. Therefore, the designed construct VT4 may be studied to control the interaction of P. aeruginosa with host and infection caused by P. aeruginosa.

SignalP 5.0 improves signal peptide predictions using deep neural networks

Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish between various types of signal peptides. We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs.

Proteomic Detection of Carbohydrate-Active Enzymes (CAZymes) in Microbial Secretomes

Secretomes from microorganisms growing on biomass contain carbohydrate-active enzymes (CAZymes) of potential biotechnological interest. By analyzing such secretomes, we may discover key enzymes involved in degradation processes and potentially infer the mode-of-action of biomass conversion. Some of these enzymes may have predicted functions in carbohydrate degradation, while others may not, while yet exhibiting a similar expression pattern; these latter enzymes constitute potential novel enzymes involved in the degradation process and provide a basis for further biochemical exploration. Hence, secretomes represent an important source for the study of both predicted and novel CAZymes. Here we describe a plate-based culturing technique that allows for collection of protein fractions that are highly enriched for secreted proteins, bound or unbound to the substrate, and which minimizes contamination by intracellular proteins trough unwanted cell lysis.

Lipoproteins: Structure, Function, Biosynthesis

The Lpp lipoprotein of Escherichia coli is the first identified protein with a covalently linked lipid. It is chemically bound by its C-terminus to murein (peptidoglycan) and inserts by the lipid at the N-terminus into the outer membrane. As the most abundant protein in E. coli (10⁶ molecules per cell) it plays an important role for the integrity of the cell envelope. Lpp represents the type protein of a large variety of lipoproteins found in Gram-negative and Gram-positive bacteria and in archaea that have in common the lipid structure for anchoring the proteins to membranes but otherwise strongly vary in sequence, structure, and function. Predicted lipoproteins in known prokaryotic genomes comprise 2.7% of all proteins. Lipoproteins are modified by a unique phospholipid pathway and transferred from the cytoplasmic membrane into the outer membrane by a special system. They are involved in protein incorporation into the outer membrane, protein secretion across the cytoplasmic membrane, periplasm and outer membrane, signal transduction, conjugation, cell wall metabolism, antibiotic resistance, biofilm formation, and adhesion to host tissues. They are only found in bacteria and function as signal molecules for the innate immune system of vertebrates, where they cause inflammation and elicit innate and adaptive immune response through Toll-like receptors. This review discusses various aspects of Lpp and other lipoproteins of Gram-negative and Gram-positive bacteria and archaea.

Extending hidden Markov models to allow conditioning on previous observations

Hidden Markov Models (HMMs) are probabilistic models widely used in computational molecular biology. However, the Markovian assumption regarding transition probabilities which dictates that the observed symbol depends only on the current state may not be sufficient for some biological problems. In order to overcome the limitations of the first order HMM, a number of extensions have been proposed in the literature to incorporate past information in HMMs conditioning either on the hidden states, or on the observations, or both. Here, we implement a simple extension of the standard HMM in which the current observed symbol (amino acid residue) depends both on the current state and on a series of observed previous symbols. The major advantage of the method is the simplicity in the implementation, which is achieved by properly transforming the observation sequence, using an extended alphabet. Thus, it can utilize all the available algorithms for the training and decoding of HMMs. We investigated the use of several encoding schemes and performed tests in a number of important biological problems previously studied by our team (prediction of transmembrane proteins and prediction of signal peptides). The evaluation shows that, when enough data are available, the performance increased by 1.8%–8.2% and the existing prediction methods may improve using this approach. The methods, for which the improvement was significant (PRED-TMBB2, PRED-TAT and HMM-TM), are available as web-servers freely accessible to academic users at www.compgen.org/tools/ .

In silico characterization of the global Geobacillus and Parageobacillus secretome

Background

Geobacillus and Parageobacillus are two ecologically diverse thermophilic genera within the phylum Firmicutes. These taxa have long been of biotechnological interest due to their ability to secrete thermostable enzymes and other biomolecules that have direct applications in various industrial and clinical fields. Despite the commercial and industrial interest in these microorganisms, the full scope of the secreted protein, i.e. the secretome, of Geobacillus and Parageobacillus species remains largely unexplored, with most studies focusing on single enzymes. A genome-wide exploration of the global secretome can provide a platform for understanding the extracellular functional “protein cloud” and the roles that secreted proteins play in the survival and adaptation of these biotechnologically relevant organisms.

Results

In the present study, the global secretion profile of 64 Geobacillus and Parageobacillus strains, comprising 772 distinct proteins, was predicted using comparative genomic approaches. Thirty-one of these proteins are shared across all strains used in this study and function in cell-wall/membrane biogenesis as well as transport and metabolism of carbohydrates, amino acids and inorganic ions. An analysis of the clustering patterns of the secretomes of the 64 strains according to shared functional orthology revealed a correlation between the secreted profiles of different strains and their phylogeny, with Geobacillus and Parageobacillus species forming two distinct functional clades.

Conclusions

The in silico characterization of the global secretome revealed a metabolically diverse set of secreted proteins, which include proteases, glycoside hydrolases, nutrient binding proteins and toxins.

Electronic supplementary material

The online version of this article (10.1186/s12934-018-1005-9) contains supplementary material, which is available to authorized users.

Genomic analyses reveal two distinct lineages of Corynebacterium ulcerans strains

Corynebacterium ulcerans is an important zoonotic pathogen which is causing diphtheria-like disease in humans globally. In this study, the genomes of three recently isolated C. ulcerans strains, 4940, 2590 and BR-AD 2649, respectively from an asymptomatic carrier, a patient with pharyngitis and a canine host, were sequenced to investigate their virulence potential. A comparative analysis was performed including the published genome sequences of 16 other C. ulcerans isolates. C. ulcerans strains belong to two lineages; 13 strains are grouped together in lineage 1, and six strains comprise lineage 2. Consistent with the zoonotic nature of C. ulcerans infections, isolates from both the human and canine hosts clustered in both the lineages. Most of the strains possessed spaDEF and spaBC gene clusters along with the virulence genes cpp, pld, cwlH, nanH, rpfI, tspA and vsp1. The gene encoding Shiga-like toxin was only present in one strain, and 11 strains carried the tox gene encoding the diphtheria-like toxin. However, none of strains 4940, 2590 and BR-AD 2649 carried any toxin genes. These strains varied in the number of prophages in their genomes, which suggests that they play an important role in introducing diversity in C. ulcerans. The pan-genomic analyses revealed a variation in the number of membrane-associated and secreted proteins that may contribute to the variation in pathogenicity among different strains.

Unraveling Gardnerella vaginalis Surface Proteins Using Cell Shaving Proteomics

Gardnerella vaginalis is one of the main etiologic agents of bacterial vaginosis (BV). This infection is responsible for a wide range of public health costs and is associated with several adverse outcomes during pregnancy. Improving our understanding of G. vaginalis protein cell surface will assist in BV diagnosis. This study represents the first proteomic approach that has analyzed the exposed proteins on G. vaginalis cell surface using a shaving approach. The 261 G. vaginalis proteins identified using this approach were analyzed with bioinformatic tools to detect characteristic motifs from surface-exposed proteins, such as signal peptides (36 proteins), lipobox domains (17 proteins), LPXTG motifs (5 proteins) and transmembrane alpha-helices (66 proteins). One third of the identified proteins were found to have at least one typical motif of surface-exposed proteins. Furthermore, the subcellular location was examined using two predictors (PSORT and Gpos-mPLoc). These bioinformatic tools classified 17% of the identified proteins as surface-associated proteins. Interestingly, we identified 13 members of the ATP-binding cassette (ABC) superfamily, which were mainly involved in the translocation of various substrates across membranes. To validate the location of the G. vaginalis surface-exposed proteins, an immunofluorescence assay with antibodies against Escherichia coli GroEL was performed to reveal the extracellular location of the moonlighting GroEL. In addition, monoclonal antibodies (mAb) against G. vaginalis Cna protein were produced and used to validate the location of Cna on the surface of the G. vaginalis. These high affinity anti-Cna mAb represent a useful tool for the study of this pathogenic microorganism and the BV.