OMPdb: a database of {beta}-barrel outer membrane proteins from Gram-negative bacteria

Protein-lipid charge interactions control the folding of outer membrane proteins into asymmetric membranes

Biological membranes consist of two leaflets of phospholipid molecules that form a bilayer, each leaflet comprising a distinct lipid composition. This asymmetry is created and maintained in vivo by dedicated biochemical pathways, but difficulties in creating stable asymmetric membranes in vitro have restricted our understanding of how bilayer asymmetry modulates the folding, stability and function of membrane proteins. In this study, we used cyclodextrin-mediated lipid exchange to generate liposomes with asymmetric bilayers and characterize the stability and folding kinetics of two bacterial outer membrane proteins (OMPs), OmpA and BamA. We found that excess negative charge in the outer leaflet of a liposome impedes their insertion and folding, while excess negative charge in the inner leaflet accelerates their folding relative to symmetric liposomes with the same membrane composition. Using molecular dynamics, mutational analysis and bioinformatics, we identified a positively charged patch critical for folding and stability. These results rationalize the well-known 'positive-outside' rule of OMPs and suggest insights into the mechanisms that drive OMP folding and assembly in vitro and in vivo.

General features of transmembrane beta barrels from a large database

Large datasets contribute new insights to subjects formerly investigated by exemplars. We used coevolution data to create a large, high-quality database of transmembrane β-barrels (TMBB). By applying simple feature detection on generated evolutionary contact maps, our method (IsItABarrel) achieves 95.88% balanced accuracy when discriminating among protein classes. Moreover, comparison with IsItABarrel revealed a high rate of false positives in previous TMBB algorithms. In addition to being more accurate than previous datasets, our database (available online) contains 1,938,936 bacterial TMBB proteins from 38 phyla, respectively, 17 and 2.2 times larger than the previous sets TMBB-DB and OMPdb. We anticipate that due to its quality and size, the database will serve as a useful resource where high-quality TMBB sequence data are required. We found that TMBBs can be divided into 11 types, three of which have not been previously reported. We find tremendous variance in proteome percentage among TMBB-containing organisms with some using 6.79% of their proteome for TMBBs and others using as little as 0.27% of their proteome. The distribution of the lengths of the TMBBs is suggestive of previously hypothesized duplication events. In addition, we find that the C-terminal β-signal varies among different classes of bacteria though its consensus sequence is LGLGYRF. However, this β-signal is only characteristic of prototypical TMBBs. The ten non-prototypical barrel types have other C-terminal motifs, and it remains to be determined if these alternative motifs facilitate TMBB insertion or perform any other signaling function.

Analysis of bacterial pangenomes reduces CRISPR dark matter and reveals strong association between membranome and CRISPR-Cas systems

CRISPR-Cas systems are prokaryotic acquired immunity mechanisms, which are found in 40% of bacterial genomes. They prevent viral infections through small DNA fragments called spacers. However, the vast majority of these spacers have not yet been associated with the virus they recognize, and it has been named CRISPR dark matter. By analyzing the spacers of tens of thousands of genomes from six bacterial species, we have been able to reduce the CRISPR dark matter from 80% to as low as 15% in some of the species. In addition, we have observed that, when a genome presents CRISPR-Cas systems, this is accompanied by particular sets of membrane proteins. Our results suggest that when bacteria present membrane proteins that make it compete better in its environment and these proteins are, in turn, receptors for specific phages, they would be forced to acquire CRISPR-Cas.

Hidden neural networks for transmembrane protein topology prediction

Hidden Markov Models (HMMs) are amongst the most successful methods for predicting protein features in biological sequence analysis. However, there are biological problems where the Markovian assumption is not sufficient since the sequence context can provide useful information for prediction purposes. Several extensions of HMMs have appeared in the literature in order to overcome their limitations. We apply here a hybrid method that combines HMMs and Neural Networks (NNs), termed Hidden Neural Networks (HNNs), for biological sequence analysis in a straightforward manner. In this framework, the traditional HMM probability parameters are replaced by NN outputs. As a case study, we focus on the topology prediction of for alpha-helical and beta-barrel membrane proteins. The HNNs show performance gains compared to standard HMMs and the respective predictors outperform the top-scoring methods in the field. The implementation of HNNs can be found in the package JUCHMME, downloadable from http://www.compgen.org/tools/juchmme, https://github.com/pbagos/juchmme. The updated PRED-TMBB2 and HMM-TM prediction servers can be accessed at www.compgen.org.

In Silico Analysis of Potential Outer Membrane Beta-Barrel Proteins in Aeromonas hydrophila Pangenome

Outer membrane proteins (OMPs) of Aeromonas hydrophila have a variety of functional roles in virulence and pathogenesis and represent promising targets for vaccine development. The main objective of this study was to develop an in-silico model of beta-barrel OMP present among the valid A. hydrophila pangenomes (n = 22). With a program named the β-barrel Outer Membrane Protein Predictor (BOMP), total beta-barrel OMPs (n = 3127) were predicted across 22 genomes with the estimated median number of 64 per genome. In pangenome analysis, only 32 OMPs were found to be conserved. These beta-barrel OMPs also showed variations among source of isolation, COG and KEGG classes. Among 32 conserved OMPs, a highly antigenic protein was identified by utilizing Vaxijen. With B cell epitope predictions, two fragments of amino acid sequences i.e. GLTLGAQFTGNNDPQNADRSN (21 mer) and FKPSLAYLRTDVKDNARGI DDTATEY (26 mer) bearing B-cell binding sites were selected. Further, an epitope (12 amino acids: GLTLGAQFTGNN) that complexes to maximum MHC alleles with a higher antigenicity was determined. The analysis of evolutionary forces on the identified OMP sequence and epitope indicated that none of basic amino acid sites has shown significantly different substitution ratios. This conserved protein and epitope will be helpful in developing a vaccine that may be effective against all the A. hydrophila strains. Also, this study provides a theoretical basis for vaccine design against other pathogenic bacteria.

The antibiotic darobactin mimics a β-strand to inhibit outer membrane insertase

Antibiotics that target Gram-negative bacteria in new ways are needed to resolve the antimicrobial resistance crisis^1-3. Gram-negative bacteria are protected by an additional outer membrane, rendering proteins on the cell surface attractive drug targets^4,5. The natural compound darobactin targets the bacterial insertase BamA⁶-the central unit of the essential BAM complex, which facilitates the folding and insertion of outer membrane proteins^7-13. BamA lacks a typical catalytic centre, and it is not obvious how a small molecule such as darobactin might inhibit its function. Here we resolve the mode of action of darobactin at the atomic level using a combination of cryo-electron microscopy, X-ray crystallography, native mass spectrometry, in vivo experiments and molecular dynamics simulations. Two cyclizations pre-organize the darobactin peptide in a rigid β-strand conformation. This creates a mimic of the recognition signal of native substrates with a superior ability to bind to the lateral gate of BamA. Upon binding, darobactin replaces a lipid molecule from the lateral gate to use the membrane environment as an extended binding pocket. Because the interaction between darobactin and BamA is largely mediated by backbone contacts, it is particularly robust against potential resistance mutations. Our results identify the lateral gate as a functional hotspot in BamA and will allow the rational design of antibiotics that target this bacterial Achilles heel.

OMPdb: A Global Hub of Beta-Barrel Outer Membrane Proteins

OMPdb (www.ompdb.org) was introduced as a database for β-barrel outer membrane proteins from Gram-negative bacteria in 2011 and then included 69,354 entries classified into 85 families. The database has been updated continuously using a collection of characteristic profile Hidden Markov Models able to discriminate between the different families of prokaryotic transmembrane β-barrels. The number of families has increased ultimately to a total of 129 families in the current, second major version of OMPdb. New additions have been made in parallel with efforts to update existing families and add novel families. Here, we present the upgrade of OMPdb, which from now on aims to become a global repository for all transmembrane β-barrel proteins, both eukaryotic and bacterial.

Computational prediction of secreted proteins in gram-negative bacteria

Gram-negative bacteria harness multiple protein secretion systems and secrete a large proportion of the proteome. Proteins can be exported to periplasmic space, integrated into membrane, transported into extracellular milieu, or translocated into cytoplasm of contacting cells. It is important for accurate, genome-wide annotation of the secreted proteins and their secretion pathways. In this review, we systematically classified the secreted proteins according to the types of secretion systems in Gram-negative bacteria, summarized the known features of these proteins, and reviewed the algorithms and tools for their prediction.

A Novel Design of Multi-epitope Vaccine Against Helicobacter pylori by Immunoinformatics Approach

Helicobacter pylori (H. pylori) is a gram-negative spiral bacterium that caused infections in half of the world’s population and had been identified as type I carcinogen by the World Health Organization. Compared with antibiotic treatment which could result in drug resistance, the vaccine therapy is becoming a promising immunotherapy option against H. pylori. Further, the multi-epitope vaccine could provoke a wider immune protection to control H. pylori infection. In this study, the in-silico immunogenicity calculations on 381 protein sequences of H. pylori were performed, and the immunogenicity of selected proteins with top-ranked score were tested. The B cell epitopes and T cell epitopes from three well performed proteins UreB, PLA1, and Omp6 were assembled into six constructs of multi-epitope vaccines with random orders. In order to select the optimal constructs, the stability of the vaccine structure and the exposure of B cell epitopes on the vaccine surface were evaluated based on structure prediction and solvent accessible surface area analysis. Finally Construct S1 was selected and molecular docking showed that it had the potential of binding TLR2, TLR4, and TLR9 to stimulate strong immune response. In particular, this study provides good suggestions for epitope assembly in the construction of multi-epitope vaccines and it may be helpful to control H. pylori infection in the future.

Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.

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.

Landscape of Eukaryotic Transmembrane Beta Barrel Proteins

Even though in the last few years several families of eukaryotic β-barrel outer membrane proteins have been discovered, their computational characterization and their annotation in public databases are far from complete. The PFAM database includes only very few characteristic profiles for these families, and in most cases, the profile hidden Markov models (pHMMs) have been trained using prokaryotic and eukaryotic proteins together. Here, we present for the first time a comprehensive computational analysis of eukaryotic transmembrane β-barrels. Twelve characteristic pHMMs were built, based on an extensive literature search, which can discriminate eukaryotic β-barrels from other classes of proteins (globular and bacterial β-barrel ones), as well as between mitochondrial and chloroplastic ones. We built eight novel profiles for the chloroplastic β-barrel families that are not present in the PFAM database and also updated the profile for the MDM10 family (PF12519) in the PFAM database and divide the porin family (PF01459) into two separate families, namely, VDAC and TOM40.

The Role of SurA PPIase Domains in Preventing Aggregation of the Outer-Membrane Proteins tOmpA and OmpT

SurA is a conserved ATP-independent periplasmic chaperone involved in the biogenesis of outer-membrane proteins (OMPs). Escherichia coli SurA has a core domain and two peptidylprolyl isomerase (PPIase) domains, the role(s) of which remain unresolved. Here we show that while SurA homologues in early proteobacteria typically contain one or no PPIase domains, the presence of two PPIase domains is common in SurA in later proteobacteria, implying an evolutionary advantage for this domain architecture. Bioinformatics analysis of >350,000 OMP sequences showed that their length, hydrophobicity and aggregation propensity are similar across the proteobacterial classes, ruling out a simple correlation between SurA domain architecture and these properties of OMP sequences. To investigate the role of the PPIase domains in SurA activity, we deleted one or both PPIase domains from E.coli SurA and investigated the ability of the resulting proteins to bind and prevent the aggregation of tOmpA (19 kDa) and OmpT (33 kDa). The results show that wild-type SurA inhibits the aggregation of both OMPs, as do the cytoplasmic OMP chaperones trigger factor and SecB. However, while the ability of SurA to bind and prevent tOmpA aggregation does not depend on its PPIase domains, deletion of even a single PPIase domain ablates the ability of SurA to prevent OmpT aggregation. The results demonstrate that the core domain of SurA endows its generic chaperone ability, while the presence of PPIase domains enhances its chaperone activity for specific OMPs, suggesting one reason for the conservation of multiple PPIase domains in SurA in proteobacteria.

Comparative analysis of membrane protein structure databases

BACKGROUND

Membrane proteins play important roles in cell survival and cell communication, as they function as transporters, receptors, anchors and enzymes. They are also potential targets for drugs that block receptors or inhibit enzymes related to diseases. Although the number of known structures of membrane proteins is still small relative to the size of the proteome as a whole, many new membrane protein structures have been determined recently.

SCOPE OF THE ARTICLE

We compared and analyzed the widely used membrane protein databases, mpstruc, Orientations of Proteins in Membranes (OPM), and PDBTM, as well as the extended dataset of mpstruc based on sequence similarity, the PDB structures whose classification field indicates that they are "membrane proteins" and the proteins with Structural Classification of Proteins (SCOP) class-f domains. We evaluated the relationships between these databases or datasets based on the overlap in their contents and the degree of consistency in the structural, topological, and functional classifications and in the transmembrane domain assignment.

MAJOR CONCLUSIONS

The membrane databases differ from each other in their coverage, and in the criteria that they use for annotation and classification. To ensure the efficient use of these databases, it is important to understand their differences and similarities. The establishment of more detailed and consistent annotations for the sequence, structure, membrane association, and function of membrane proteins is still required.

GENERAL SIGNIFICANCE

Considering the recent growth of experimentally determined structures, a broad survey and cumulative analysis of the sum of knowledge as presented in the membrane protein structure databases can be helpful to elucidate structures and functions of membrane proteins. We also aim to provide a framework for future research and classification of membrane proteins.

Characterization of the first planctomycetal outer membrane protein identifies a channel in the outer membrane of the anammox bacterium Kuenenia stuttgartiensis

Planctomycetes are a bacterial phylum known for their complex intracellular compartmentalization. While most Planctomycetes have two compartments, the anaerobic ammonium oxidizing (anammox) bacteria contain three membrane-enclosed compartments. In contrast to a long-standing consensus, recent insights suggested the outermost Planctomycete membrane to be similar to a Gram-negative outer membrane (OM). One characteristic component that differentiates OMs from cytoplasmic membranes (CMs) is the presence of outer membrane proteins (OMPs) featuring a β-barrel structure that facilitates passage of molecules through the OM. Although proteomic and genomic evidence suggested the presence of OMPs in several Planctomycetes, no experimental verification existed of the pore-forming function and localization of these proteins in the outermost membrane of these exceptional microorganisms. Here, we show via lipid bilayer assays that at least two typical OMP-like channel-forming proteins are present in membrane preparations of the anammox bacterium Kuenenia stuttgartiensis. One of these channel-forming proteins, the highly abundant putative OMP Kustd1878, was purified to homogeneity. Analysis of the channel characteristics via lipid bilayer assays showed that Kustd1878 forms a moderately cation-selective channel with a high current noise and an average single-channel conductance of about 170-190pS in 1M KCl. Antibodies were raised against the purified protein and immunogold localization indicated Kustd1878 to be present in the outermost membrane. Therefore, this work clearly demonstrates the presence of OMPs in anammox Planctomycetes and thus firmly adds to the emerging view that Planctomycetes have a Gram-negative cell envelope.

Braun's Lipoprotein Facilitates OmpA Interaction with the Escherichia coli Cell Wall

Gram-negative bacteria such as Escherichia coli are protected by a complex cell envelope. The development of novel therapeutics against these bacteria necessitates a molecular level understanding of the structure-dynamics-function relationships of the various components of the cell envelope. We use atomistic MD simulations to reveal the details of covalent and noncovalent protein interactions that link the outer membrane to the aqueous periplasmic region. We show that the Braun's lipoprotein tilts and bends, and thereby lifts the cell wall closer to the outer membrane. Both monomers and dimers of the outer membrane porin OmpA can interact with peptidoglycan in the presence of Braun's lipoprotein, but in the absence of the latter, only dimers of OmpA show a propensity to form contacts with peptidoglycan. Our study provides a glimpse of how the molecular components of the bacterial cell envelope interact with each other to mediate cell wall attachment in E. coli.

Predicting Beta Barrel Transmembrane Proteins Using HMMs

Transmembrane beta-barrels (TMBBs) constitute an important structural class of membrane proteins located in the outer membrane of gram-negative bacteria, and in the outer membrane of chloroplasts and mitochondria. They are involved in a wide variety of cellular functions and the prediction of their transmembrane topology, as well as their discrimination in newly sequenced genomes is of great importance as they are promising targets for antimicrobial drugs and vaccines. Several methods have been applied for the prediction of the transmembrane segments and the topology of beta barrel transmembrane proteins utilizing different algorithmic techniques. Hidden Markov Models (HMMs) have been efficiently used in the development of several computational methods used for this task. In this chapter we give a brief review of different available prediction methods for beta barrel transmembrane proteins pointing out sequence and structural features that should be incorporated in a prediction method. We then describe the procedure of the design and development of a Hidden Markov Model capable of predicting the transmembrane beta strands of TMBBs and discriminating them from globular proteins.

Molecular Simulations of Gram-Negative Bacterial Membranes: A Vignette of Some Recent Successes

In the following review we use recent examples from the literature to discuss progress in the area of atomistic and coarse-grained molecular dynamics simulations of selected bacterial membranes and proteins, with a particular focus on Gram-negative bacteria. As structural biology continues to provide increasingly high-resolution data on the proteins that reside within these membranes, simulations have an important role to play in linking these data with the dynamical behavior and function of these proteins. In particular, in the last few years there has been significant progress in addressing the issue of biochemical complexity of bacterial membranes such that the heterogeneity of the lipid and protein components of these membranes are now being incorporated into molecular-level models. Thus, in future we can look forward to complementary data from structural biology and molecular simulations combining to provide key details of structure-dynamics-function relationships in bacterial membranes.

In Silico Structure and Sequence Analysis of Bacterial Porins and Specific Diffusion Channels for Hydrophilic Molecules: Conservation, Multimericity and Multifunctionality

Diffusion channels are involved in the selective uptake of nutrients and form the largest outer membrane protein (OMP) family in Gram-negative bacteria. Differences in pore size and amino acid composition contribute to the specificity. Structure-based multiple sequence alignments shed light on the structure-function relations for all eight subclasses. Entropy-variability analysis results are correlated to known structural and functional aspects, such as structural integrity, multimericity, specificity and biological niche adaptation. The high mutation rate in their surface-exposed loops is likely an important mechanism for host immune system evasion. Multiple sequence alignments for each subclass revealed conserved residue positions that are involved in substrate recognition and specificity. An analysis of monomeric protein channels revealed particular sequence patterns of amino acids that were observed in other classes at multimeric interfaces. This adds to the emerging evidence that all members of the family exist in a multimeric state. Our findings are important for understanding the role of members of this family in a wide range of bacterial processes, including bacterial food uptake, survival and adaptation mechanisms.

Properties and Phylogeny of 76 Families of Bacterial and Eukaryotic Organellar Outer Membrane Pore-Forming Proteins

We here report statistical analyses of 76 families of integral outer membrane pore-forming proteins (OMPPs) found in bacteria and eukaryotic organelles. 47 of these families fall into one superfamily (SFI) which segregate into fifteen phylogenetic clusters. Families with members of the same protein size, topology and substrate specificities often cluster together. Virtually all OMPP families include only proteins that form transmembrane pores. Nine such families, all of which cluster together in the SFI phylogenetic tree, contain both α- and β-structures, are multi domain, multi subunit systems, and transport macromolecules. Most other SFI OMPPs transport small molecules. SFII and SFV homologues derive from Actinobacteria while SFIII and SFIV proteins derive from chloroplasts. Three families of actinobacterial OMPPs and two families of eukaryotic OMPPs apparently consist primarily of α-helices (α-TMSs). Of the 71 families of (putative) β-barrel OMPPs, only twenty could not be assigned to a superfamily, and these derived primarily from Actinobacteria (1), chloroplasts (1), spirochaetes (8), and proteobacteria (10). Proteins were identified in which two or three full length OMPPs are fused together. Family characteristic are described and evidence agrees with a previous proposal suggesting that many arose by adjacent β-hairpin structural unit duplications.

Divergence between the Highly Virulent Zoonotic Pathogen Helicobacter heilmannii and Its Closest Relative, the Low-Virulence "Helicobacter ailurogastricus" sp. nov

Helicobacter heilmannii naturally colonizes the stomachs of dogs and cats and has been associated with gastric disorders in humans. Nine feline Helicobacter strains, classified as H. heilmannii based on ureAB and 16S rRNA gene sequences, were divided into a highly virulent and a low-virulence group. The genomes of these strains were sequenced to investigate their phylogenetic relationships, to define their gene content and diversity, and to determine if the differences in pathogenicity were associated with the presence or absence of potential virulence genes. The capacities of these helicobacters to bind to the gastric mucosa were investigated as well. Our analyses revealed that the low-virulence strains do not belong to the species H. heilmannii but to a novel, closely related species for which we propose the name Helicobacter ailurogastricus. Several homologs of H. pylori virulence factors, such as IceA1, HrgA, and jhp0562-like glycosyltransferase, are present in H. heilmannii but absent in H. ailurogastricus. Both species contain a VacA-like autotransporter, for which the passenger domain is remarkably larger in H. ailurogastricus than in H. heilmannii. In addition, H. ailurogastricus shows clear differences in binding to the gastric mucosa compared to H. heilmannii. These findings highlight the low-virulence character of this novel Helicobacter species.

Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat

During 11–12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication and funding. An important outcome of this meeting was the creation of a Specialist Protein Resource Network that we believe will improve coordination of the activities of its member resources. We invite further protein database resources to join the network and continue the dialogue.

Prediction of structural features and application to outer membrane protein identification

Protein three-dimensional (3D) structures provide insightful information in many fields of biology. One-dimensional properties derived from 3D structures such as secondary structure, residue solvent accessibility, residue depth and backbone torsion angles are helpful to protein function prediction, fold recognition and ab initio folding. Here, we predict various structural features with the assistance of neural network learning. Based on an independent test dataset, protein secondary structure prediction generates an overall Q₃ accuracy of ~80%. Meanwhile, the prediction of relative solvent accessibility obtains the highest mean absolute error of 0.164, and prediction of residue depth achieves the lowest mean absolute error of 0.062. We further improve the outer membrane protein identification by including the predicted structural features in a scoring function using a simple profile-to-profile alignment. The results demonstrate that the accuracy of outer membrane protein identification can be improved by ~3% at a 1% false positive level when structural features are incorporated. Finally, our methods are available as two convenient and easy-to-use programs. One is PSSM-2-Features for predicting secondary structure, relative solvent accessibility, residue depth and backbone torsion angles, the other is PPA-OMP for identifying outer membrane proteins from proteomes.

Key challenges for the creation and maintenance of specialist protein resources

As the volume of data relating to proteins increases, researchers rely more and more on the analysis of published data, thus increasing the importance of good access to these data that vary from the supplemental material of individual articles, all the way to major reference databases with professional staff and long-term funding. Specialist protein resources fill an important middle ground, providing interactive web interfaces to their databases for a focused topic or family of proteins, using specialized approaches that are not feasible in the major reference databases. Many are labors of love, run by a single lab with little or no dedicated funding and there are many challenges to building and maintaining them. This perspective arose from a meeting of several specialist protein resources and major reference databases held at the Wellcome Trust Genome Campus (Cambridge, UK) on August 11 and 12, 2014. During this meeting some common key challenges involved in creating and maintaining such resources were discussed, along with various approaches to address them. In laying out these challenges, we aim to inform users about how these issues impact our resources and illustrate ways in which our working together could enhance their accuracy, currency, and overall value.

Databases for Microbiologists

Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. The purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.

The composition of the global and feature specific cyanobacterial core-genomes

Cyanobacteria are photosynthetic prokaryotes important for many ecosystems with a high potential for biotechnological usage e.g., in the production of bioactive molecules. Either asks for a deep understanding of the functionality of cyanobacteria and their interaction with the environment. This in part can be inferred from the analysis of their genomes or proteomes. Today, many cyanobacterial genomes have been sequenced and annotated. This information can be used to identify biological pathways present in all cyanobacteria as proteins involved in such processes are encoded by a so called core-genome. However, beside identification of fundamental processes, genes specific for certain cyanobacterial features can be identified by a holistic genome analysis as well. We identified 559 genes that define the core-genome of 58 analyzed cyanobacteria, as well as three genes likely to be signature genes for thermophilic and 57 genes likely to be signature genes for heterocyst-forming cyanobacteria. To get insights into cyanobacterial systems for the interaction with the environment we also inspected the diversity of the outer membrane proteome with focus on β-barrel proteins. We observed that most of the transporting outer membrane β-barrel proteins are not globally conserved in the cyanobacterial phylum. In turn, the occurrence of β-barrel proteins shows high strain specificity. The core set of outer membrane proteins globally conserved in cyanobacteria comprises three proteins only, namely the outer membrane β-barrel assembly protein Omp85, the lipid A transfer protein LptD, and an OprB-type porin. Thus, we conclude that cyanobacteria have developed individual strategies for the interaction with the environment, while other intracellular processes like the regulation of the protein homeostasis are globally conserved.

A putative porin gene of Burkholderia sp. NK8 involved in chemotaxis toward β-ketoadipate

Burkholderia sp. NK8 can utilize 3-chlorobenzoate (3CB) as a sole source of carbon because it has a megaplasmid (pNK8) that carries the gene cluster (tfdT-CDEF) encoding chlorocatechol-degrading enzymes. The expression of tfdT-CDEF is induced by 3CB. In this study, we found that NK8 cells were attracted to 3CB and its degradation products, 3- and 4-chlorocatechol, and β-ketoadipate. Capillary assays revealed that a pNK8-eliminated strain (NK82) was defective in chemotaxis toward β-ketoadipate. The introduction of a plasmid carrying a putative outer membrane porin gene, which we name ompNK8, into strain NK82 restored chemotaxis toward β-ketoadipate. RT-PCR analyses demonstrated that the transcription of the ompNK8 gene was enhanced in the presence of 3CB.

Protein structure annotation resources

A key reason three-dimensional (3-D) protein structures are annotated with supporting or derived information is to understand the molecular basis of protein function. To this end, protein structure annotation databases curate key facts and observations, based on community-accepted standards, about the ~100,000 3-D experimental protein structures to date. This review will introduce the primary structure repositories, databases, and value-added structural annotation databases, as well as the range of information they provide. The different levels of annotation data (primary vs. derived vs. inferred) and how they should all be considered accordingly will also be described.

Effects of phosphorus starvation versus limitation on the marine cyanobacterium Prochlorococcus MED4 II: gene expression

Phosphorus (P) availability drives niche differentiation in the most abundant phytoplankter in the oceans, the marine cyanobacterium Prochlorococcus. We compared the molecular response of Prochlorococcus strain MED4 to P starvation in batch culture to P-limited growth in chemostat culture. We also identified an outer membrane porin, PMM0709, which may allow transport of organic phosphorous compounds, rather than phosphate as previously suggested. The expression of three P uptake genes, pstS, the high-affinity phosphate-binding component of the phosphate transporter, phoA, an alkaline phosphatase, and porin PMM0709, were strongly upregulated (between 10- and 700-fold) under both P starvation and limitation. pstS exhibits high basal expression under P-replete conditions and is likely necessary for P uptake regardless of P availability. A P-stress regulatory gene, ptrA, was upregulated in response to both P starvation and limitation although a second regulatory gene, phoB, was not. Elevated expression levels (> 10-fold) of phoR, a P-sensing histidine kinase, were only observed under conditions of P limitation. We suggest Prochlorococcus in P-limited systems are physiologically distinct from cells subjected to abrupt P depletion. Detection of expression of both pstS and phoR in field populations will enable discernment of the present P status of Prochlorococcus in the oligotrophic oceans.

PDBTM: Protein Data Bank of transmembrane proteins after 8 years

The PDBTM database (available at http://pdbtm.enzim.hu), the first comprehensive and up-to-date transmembrane protein selection of the Protein Data Bank, was launched in 2004. The database was created and has been continuously updated by the TMDET algorithm that is able to distinguish between transmembrane and non-transmembrane proteins using their 3D atomic coordinates only. The TMDET algorithm can locate the spatial positions of transmembrane proteins in lipid bilayer as well. During the last 8 years not only the size of the PDBTM database has been steadily growing from ∼400 to 1700 entries but also new structural elements have been identified, in addition to the well-known α-helical bundle and β-barrel structures. Numerous ‘exotic’ transmembrane protein structures have been solved since the first release, which has made it necessary to define these new structural elements, such as membrane loops or interfacial helices in the database. This article reports the new features of the PDBTM database that have been added since its first release, and our current efforts to keep the database up-to-date and easy to use so that it may continue to serve as a fundamental resource for the scientific community.

Genomic analysis indicates the presence of an asymmetric bilayer outer membrane in planctomycetes and verrucomicrobia

Bacteria of the phylum Planctomycetes are of special interest for the study of compartmental cellular organization. Members of this phylum share a very unusual prokaryotic cell plan, featuring several membrane-bound compartments. Recently, it was shown that this cellular organization might extend to certain members of the phylum Verrucomicrobia. The Planctomycete cell plan has been defined as featuring a proteinaceous cell wall, a cytoplasmic membrane surrounding the paryphoplasm, and an intracytoplasmic membrane defining the riboplasm. So far it was presumed that Planctomycetes did not have an asymmetric bilayer outer membrane as observed in Gram-negative bacteria. However, recent work on outer membrane biogenesis has provided several marker genes in the outer membrane protein (OMP) assembly and the lipopolysaccharide (LPS) insertion complexes. Additionally, advances in computational prediction of OMPs provided new tools to perform more accurate genomic screening for such proteins. Here we searched all 22 Planctomycetes and Verrucomicrobia genomes available in GenBank, plus the recently published genome of "Candidatus Scalindua profunda," for markers of outer membrane biogenesis and OMPs. We were able to identify the key components of LPS insertion, OMP assembly and at least eight OMPs in all genomes tested. Additionally, we have analyzed the transcriptome and proteome data of the Planctomycetes "Candidatus Kuenenia stuttgartiensis" and "Ca. S. profunda" and could confirm high expression of several predicted OMPs, including the biomarkers of outer membrane biogenesis. These analyses provide a strong indication that an asymmetrical outer membrane may be present in bacteria of both phyla. However, previous experiments have made obvious that the cell envelope of Planctomycetes is clearly divergent from both the Gram-negative and Gram-positive cell types. Thus, the functional implications of the presence of an outer membrane for the Planctomycete cell plan and compartmentalization are discussed and a revised model including an outer membrane is proposed. Although this model agrees with most experimental data, we do note that the presence, location, and role of an outer membrane within the Planctomycetes and Verrucomicrobia awaits further experimental validation.

TMBB-DB: a transmembrane β-barrel proteome database

MOTIVATION

We previously reported the development of a highly accurate statistical algorithm for identifying β-barrel outer membrane proteins or transmembrane β-barrels (TMBBs), from genomic sequence data of Gram-negative bacteria (Freeman,T.C. and Wimley,W.C. (2010) Bioinformatics, 26, 1965-1974). We have now applied this identification algorithm to all available Gram-negative bacterial genomes (over 600 chromosomes) and have constructed a publicly available, searchable, up-to-date, database of all proteins in these genomes.

RESULTS

For each protein in the database, there is information on (i) β-barrel membrane protein probability for identification of β-barrels, (ii) β-strand and β-hairpin propensity for structure and topology prediction, (iii) signal sequence score because most TMBBs are secreted through the inner membrane translocon and, thus, have a signal sequence, and (iv) transmembrane α-helix predictions, for reducing false positive predictions. This information is sufficient for the accurate identification of most β-barrel membrane proteins in these genomes. In the database there are nearly 50 000 predicted TMBBs (out of 1.9 million total putative proteins). Of those, more than 15 000 are 'hypothetical' or 'putative' proteins, not previously identified as TMBBs. This wealth of genomic information is not available anywhere else.

AVAILABILITY

The TMBB genomic database is available at http://beta-barrel.tulane.edu/.

CONTACT

wwimley@tulane.edu.

XatA, an AT-1 autotransporter important for the virulence of Xylella fastidiosa Temecula1

Xylella fastidiosa Temecula1 is the causative agent of Pierce's disease of grapevine, which is spread by xylem-feeding insects. An important feature of the infection cycle is the ability of X. fastidiosa to colonize and interact with two distinct environments, the xylem of susceptible plants and the insect foregut. Here, we describe our characterization of XatA, the X. fastidiosa autotransporter protein encoded by PD0528. XatA, which is classified as an AT-1 (classical) autotransporter, has a C-terminal β-barrel domain and a passenger domain composed of six tandem repeats of approximately 50 amino acids. Localization studies indicate that XatA is present in both the outer membrane and membrane vesicles and its passenger domain can be found in the supernatant. Moreover, XatA is important for X. fastidiosa autoaggregation and biofilm formation based on mutational analysis and the discovery that Escherichia coli expressing XatA acquire these traits. The xatA mutant also shows a significant decrease in Pierce's disease symptoms when inoculated into grapevines. Finally, X. fastidiosa homologs to XatA, which can be divided into three distinct groups based on synteny, form a single, well-supported clade, suggesting that they arose from a common ancestor.

Methylation and in vivo expression of the surface-exposed Leptospira interrogans outer-membrane protein OmpL32

Recent studies have revealed that bacterial protein methylation is a widespread post-translational modification that is required for virulence in selected pathogenic bacteria. In particular, altered methylation of outer-membrane proteins has been shown to modulate the effectiveness of the host immune response. In this study, 2D gel electrophoresis combined with MALDI-TOF MS identified a Leptospira interrogans serovar Copenhageni strain Fiocruz L1-130 protein, corresponding to ORF LIC11848, which undergoes extensive and differential methylation of glutamic acid residues. Immunofluorescence microscopy implicated LIC11848 as a surface-exposed outer-membrane protein, prompting the designation OmpL32. Indirect immunofluorescence microscopy of golden Syrian hamster liver and kidney sections revealed expression of OmpL32 during colonization of these organs. Identification of methylated surface-exposed outer-membrane proteins, such as OmpL32, provides a foundation for delineating the role of this post-translational modification in leptospiral virulence.

Pattern of amino acid substitutions in transmembrane domains of β-barrel membrane proteins for detecting remote homologs in bacteria and mitochondria

-barrel membrane proteins play an important role in controlling the exchange and transport of ions and organic molecules across bacterial and mitochondrial outer membranes. They are also major regulators of apoptosis and are important determinants of bacterial virulence. In contrast to -helical membrane proteins, their evolutionary pattern of residue substitutions has not been quantified, and there are no scoring matrices appropriate for their detection through sequence alignment. Using a Bayesian Monte Carlo estimator, we have calculated the instantaneous substitution rates of transmembrane domains of bacterial -barrel membrane proteins. The scoring matrices constructed from the estimated rates, called bbTM for -barrel Transmembrane Matrices, improve significantly the sensitivity in detecting homologs of -barrel membrane proteins, while avoiding erroneous selection of both soluble proteins and other membrane proteins of similar composition. The estimated evolutionary patterns are general and can detect -barrel membrane proteins very remote from those used for substitution rate estimation. Furthermore, despite the separation of 2–3 billion years since the proto-mitochondrion entered the proto-eukaryotic cell, mitochondria outer membrane proteins in eukaryotes can also be detected accurately using these scoring matrices derived from bacteria. This is consistent with the suggestion that there is no eukaryote-specific signals for translocation. With these matrices, remote homologs of -barrel membrane proteins with known structures can be reliably detected at genome scale, allowing construction of high quality structural models of their transmembrane domains, at the rate of 131 structures per template protein. The scoring matrices will be useful for identification, classification, and functional inference of membrane proteins from genome and metagenome sequencing projects. The estimated substitution pattern will also help to identify key elements important for the structural and functional integrity of -barrel membrane proteins, and will aid in the design of mutagenesis studies.

Comparative genomics of Helicobacter pylori and the human-derived Helicobacter bizzozeronii CIII-1 strain reveal the molecular basis of the zoonotic nature of non-pylori gastric Helicobacter infections in humans

BACKGROUND

The canine Gram-negative Helicobacter bizzozeronii is one of seven species in Helicobacter heilmannii sensu lato that are detected in 0.17-2.3% of the gastric biopsies of human patients with gastric symptoms. At the present, H. bizzozeronii is the only non-pylori gastric Helicobacter sp. cultivated from human patients and is therefore a good alternative model of human gastric Helicobacter disease. We recently sequenced the genome of the H. bizzozeronii human strain CIII-1, isolated in 2008 from a 47-year old Finnish woman suffering from severe dyspeptic symptoms. In this study, we performed a detailed comparative genome analysis with H. pylori, providing new insights into non-pylori Helicobacter infections and the mechanisms of transmission between the primary animal host and humans.

RESULTS

H. bizzozeronii possesses all the genes necessary for its specialised life in the stomach. However, H. bizzozeronii differs from H. pylori by having a wider metabolic flexibility in terms of its energy sources and electron transport chain. Moreover, H. bizzozeronii harbours a higher number of methyl-accepting chemotaxis proteins, allowing it to respond to a wider spectrum of environmental signals. In this study, H. bizzozeronii has been shown to have high level of genome plasticity. We were able to identify a total of 43 contingency genes, 5 insertion sequences (ISs), 22 mini-IS elements, 1 genomic island and a putative prophage. Although H. bizzozeronii lacks homologues of some of the major H. pylori virulence genes, other candidate virulence factors are present. In particular, we identified a polysaccharide lyase (HBZC1_15820) as a potential new virulence factor of H. bizzozeronii.

CONCLUSIONS

The comparative genome analysis performed in this study increased the knowledge of the biology of gastric Helicobacter species. In particular, we propose the hypothesis that the high metabolic versatility and the ability to react to a range of environmental signals, factors which differentiate H. bizzozeronii as well as H. felis and H. suis from H. pylori, are the molecular basis of the of the zoonotic nature of H. heilmannii sensu lato infection in humans.

Unique residues involved in activation of the multitasking protease/chaperone HtrA from Chlamydia trachomatis

DegP, a member of the HtrA family of proteins, conducts critical bacterial protein quality control by both chaperone and proteolysis activities. The regulatory mechanisms controlling these two distinct activities, however, are unknown. DegP activation is known to involve a unique mechanism of allosteric binding, conformational changes and oligomer formation. We have uncovered a novel role for the residues at the PDZ1:protease interface in oligomer formation specifically for chaperone substrates of Chlamydia trachomatis HtrA (DegP homolog). We have demonstrated that CtHtrA proteolysis could be activated by allosteric binding and oligomer formation. The PDZ1 activator cleft was required for the activation and oligomer formation. However, unique to CtHtrA was the critical role for residues at the PDZ1:protease interface in oligomer formation when the activator was an in vitro chaperone substrate. Furthermore, a potential in vivo chaperone substrate, the major outer membrane protein (MOMP) from Chlamydia, was able to activate CtHtrA and induce oligomer formation. Therefore, we have revealed novel residues involved in the activation of CtHtrA which are likely to have important in vivo implications for outer membrane protein assembly.

Outer membrane proteins can be simply identified using secondary structure element alignment

Background

Outer membrane proteins (OMPs) are frequently found in the outer membranes of gram-negative bacteria, mitochondria and chloroplasts and have been found to play diverse functional roles. Computational discrimination of OMPs from globular proteins and other types of membrane proteins is helpful to accelerate new genome annotation and drug discovery.

Results

Based on the observation that almost all OMPs consist of antiparallel β-strands in a barrel shape and that their secondary structure arrangements differ from those of other types of proteins, we propose a simple method called SSEA-OMP to identify OMPs using secondary structure element alignment. Through intensive benchmark experiments, the proposed SSEA-OMP method is better than some well-established OMP detection methods.

Conclusions

The major advantage of SSEA-OMP is its good prediction performance considering its simplicity. The web server implements the method is freely accessible at http://protein.cau.edu.cn/SSEA-OMP/index.html.