TMBB-DB: a transmembrane β-barrel proteome database

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.

Pfeature: A Tool for Computing Wide Range of Protein Features and Building Prediction Models

In the last three decades, a wide range of protein features have been discovered to annotate a protein. Numerous attempts have been made to integrate these features in a software package/platform so that the user may compute a wide range of features from a single source. To complement the existing methods, we developed a method, Pfeature, for computing a wide range of protein features. Pfeature allows to compute more than 200,000 features required for predicting the overall function of a protein, residue-level annotation of a protein, and function of chemically modified peptides. It has six major modules, namely, composition, binary profiles, evolutionary information, structural features, patterns, and model building. Composition module facilitates to compute most of the existing compositional features, plus novel features. The binary profile of amino acid sequences allows to compute the fraction of each type of residue as well as its position. The evolutionary information module allows to compute evolutionary information of a protein in the form of a position-specific scoring matrix profile generated using Position-Specific Iterative Basic Local Alignment Search Tool (PSI-BLAST); fit for annotation of a protein and its residues. A structural module was developed for computing of structural features/descriptors from a tertiary structure of a protein. These features are suitable to predict the therapeutic potential of a protein containing non-natural or chemically modified residues. The model-building module allows to implement various machine learning techniques for developing classification and regression models as well as feature selection. Pfeature also allows the generation of overlapping patterns and features from a protein. A user-friendly Pfeature is available as a web server python library and stand-alone package.

Colicin E1 opens its hinge to plug TolC

The double membrane architecture of Gram-negative bacteria forms a barrier that is impermeable to most extracellular threats. Bacteriocin proteins evolved to exploit the accessible, surface-exposed proteins embedded in the outer membrane to deliver cytotoxic cargo. Colicin E1 is a bacteriocin produced by, and lethal to, Escherichia coli that hijacks the outer membrane proteins (OMPs) TolC and BtuB to enter the cell. Here, we capture the colicin E1 translocation domain inside its membrane receptor, TolC, by high-resolution cryo-electron microscopy to obtain the first reported structure of a bacteriocin bound to TolC. Colicin E1 binds stably to TolC as an open hinge through the TolC pore—an architectural rearrangement from colicin E1’s unbound conformation. This binding is stable in live E. coli cells as indicated by single-molecule fluorescence microscopy. Finally, colicin E1 fragments binding to TolC plug the channel, inhibiting its native efflux function as an antibiotic efflux pump, and heightening susceptibility to three antibiotic classes. In addition to demonstrating that these protein fragments are useful starting points for developing novel antibiotic potentiators, this method could be expanded to other colicins to inhibit other OMP functions.

Bacteria are constantly warring with each other for space and resources. As a result, they have developed a range of molecular weapons to poison, damage or disable other cells. For instance, bacteriocins are proteins that can latch onto structures at the surface of enemy bacteria and push toxins through their outer membrane.

Bacteria are increasingly resistant to antibiotics, representing a growing concern for modern healthcare. One way that they are able to survive is by using ‘efflux pumps’ studded through their external membranes to expel harmful drugs before these can cause damage. Budiardjo et al. wanted to test whether bacteriocins could interfere with this defence mechanism by blocking efflux pumps.

Bacteriocins are usually formed of binding elements (which recognise specific target proteins) and of a ‘killer tail’ that can stab the cell. Experiments showed that the binding parts of a bacteriocin could effectively ‘plug’ efflux pumps in Escherichia coli bacteria: high-resolution molecular microscopy revealed how the bacteriocin fragment binds to the pump, while fluorescent markers showed that it attached to the surface of E. coli and stopped the efflux pumps from working. As a result, lower amounts of antibiotics were necessary to kill the bacteria when bacteriocins were present.

The work by Budiardjo et al. could lead to new ways to combat bacteria that will reduce the need for current antibiotics. In the future, bacteriocins could also be harnessed to target other proteins than efflux pumps, allowing scientists to manipulate a range of bacterial processes.

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.

The Treponema pallidum Outer Membrane

The outer membrane (OM) of Treponema pallidum, the uncultivatable agent of venereal syphilis, has long been the subject of misconceptions and controversy. Decades ago, researchers postulated that T. pallidum's poor surface antigenicity is the basis for its ability to cause persistent infection, but they mistakenly attributed this enigmatic property to the presence of a protective outer coat of serum proteins and mucopolysaccharides. Subsequent studies revealed that the OM is the barrier to antibody binding, that it contains a paucity of integral membrane proteins, and that the preponderance of the spirochete's immunogenic lipoproteins is periplasmic. Since the advent of recombinant DNA technology, the fragility of the OM, its low protein content, and the lack of sequence relatedness between T. pallidum and Gram-negative outer membrane proteins (OMPs) have complicated efforts to characterize molecules residing at the host-pathogen interface. We have overcome these hurdles using the genomic sequence in concert with computational tools to identify proteins predicted to form β-barrels, the hallmark conformation of OMPs in double-membrane organisms and evolutionarily related eukaryotic organelles. We also have employed diverse methodologies to confirm that some candidate OMPs do, in fact, form amphiphilic β-barrels and are surface-exposed in T. pallidum. These studies have led to a structural homology model for BamA and established the bipartite topology of the T. pallidum repeat (Tpr) family of proteins. Recent bioinformatics has identified several structural orthologs for well-characterized Gram-negative OMPs, suggesting that the T. pallidum OMP repertoire is more Gram-negative-like than previously supposed. Lipoprotein adhesins and proteases on the spirochete surface also may contribute to disease pathogenesis and protective immunity.

ccPDB 2.0: an updated version of datasets created and compiled from Protein Data Bank

ccPDB 2.0 (http://webs.iiitd.edu.in/raghava/ccpdb) is an updated version of the manually curated database ccPDB that maintains datasets required for developing methods to predict the structure and function of proteins. The number of datasets compiled from literature increased from 45 to 141 in ccPDB 2.0. Similarly, the number of protein structures used for creating datasets also increased from ~74 000 to ~137 000 (PDB March 2018 release). ccPDB 2.0 provides the same web services and flexible tools which were present in the previous version of the database. In the updated version, links of the number of methods developed in the past few years have also been incorporated. This updated resource is built on responsive templates which is compatible with smartphones (mobile, iPhone, iPad, tablets etc.) and large screen gadgets. In summary, ccPDB 2.0 is a user-friendly web-based platform that provides comprehensive as well as updated information about datasets.

Evolutionary pathways of repeat protein topology in bacterial outer membrane proteins

Outer membrane proteins (OMPs) are the proteins in the surface of Gram-negative bacteria. These proteins have diverse functions but a single topology: the β-barrel. Sequence analysis has suggested that this common fold is a β-hairpin repeat protein, and that amplification of the β-hairpin has resulted in 8-26-stranded barrels. Using an integrated approach that combines sequence and structural analyses, we find events in which non-amplification diversification also increases barrel strand number. Our network-based analysis reveals strand-number-based evolutionary pathways, including one that progresses from a primordial 8-stranded barrel to 16-strands and further, to 18-strands. Among these pathways are mechanisms of strand number accretion without domain duplication, like a loop-to-hairpin transition. These mechanisms illustrate perpetuation of repeat protein topology without genetic duplication, likely induced by the hydrophobic membrane. Finally, we find that the evolutionary trace is particularly prominent in the C-terminal half of OMPs, implicating this region in the nucleation of OMP folding.

High-resolution structure prediction of β-barrel membrane proteins

[Formula: see text]-Barrel membrane proteins ([Formula: see text]MPs) play important roles, but knowledge of their structures is limited. We have developed a method to predict their 3D structures. We predict strand registers and construct transmembrane (TM) domains of [Formula: see text]MPs accurately, including proteins for which no prediction has been attempted before. Our method also accurately predicts structures from protein families with a limited number of sequences and proteins with novel folds. An average main-chain rmsd of 3.48 Å is achieved between predicted and experimentally resolved structures of TM domains, which is a significant improvement ([Formula: see text]3 Å) over a recent study. For [Formula: see text]MPs with NMR structures, the deviation between predictions and experimentally solved structures is similar to the difference among the NMR structures, indicating excellent prediction accuracy. Moreover, we can now accurately model the extended [Formula: see text]-barrels and loops in non-TM domains, increasing the overall coverage of structure prediction by [Formula: see text]%. Our method is general and can be applied to genome-wide structural prediction of [Formula: see text]MPs.

FmvB: A Francisella tularensis Magnesium-Responsive Outer Membrane Protein that Plays a Role in Virulence

Francisella tularensis is the causative agent of the lethal disease tularemia. Despite decades of research, little is understood about why F. tularensis is so virulent. Bacterial outer membrane proteins (OMPs) are involved in various virulence processes, including protein secretion, host cell attachment, and intracellular survival. Many pathogenic bacteria require metals for intracellular survival and OMPs often play important roles in metal uptake. Previous studies identified three F. tularensis OMPs that play roles in iron acquisition. In this study, we examined two previously uncharacterized proteins, FTT0267 (named fmvA, for Francisellametal and virulence) and FTT0602c (fmvB), which are homologs of the previously studied F. tularensis iron acquisition genes and are predicted OMPs. To study the potential roles of FmvA and FmvB in metal acquisition and virulence, we first examined fmvA and fmvB expression following pulmonary infection of mice, finding that fmvB was upregulated up to 5-fold during F. tularensis infection of mice. Despite sequence homology to previously-characterized iron-acquisition genes, FmvA and FmvB do not appear to be involved iron uptake, as neither fmvA nor fmvB were upregulated in iron-limiting media and neither ΔfmvA nor ΔfmvB exhibited growth defects in iron limitation. However, when other metals were examined in this study, magnesium-limitation significantly induced fmvB expression, ΔfmvB was found to express significantly higher levels of lipopolysaccharide (LPS) in magnesium-limiting medium, and increased numbers of surface protrusions were observed on ΔfmvB in magnesium-limiting medium, compared to wild-type F. tularensis grown in magnesium-limiting medium. RNA sequencing analysis of ΔfmvB revealed the potential mechanism for increased LPS expression, as LPS synthesis genes kdtA and wbtA were significantly upregulated in ΔfmvB, compared with wild-type F. tularensis. To provide further evidence for the potential role of FmvB in magnesium uptake, we demonstrated that FmvB was outer membrane-localized. Finally, ΔfmvB was found to be attenuated in mice and cytokine analyses revealed that ΔfmvB-infected mice produced lower levels of pro-inflammatory cytokines, including GM-CSF, IL-3, and IL-10, compared with mice infected with wild-type F. tularensis. Taken together, although the function of FmvA remains unknown, FmvB appears to play a role in magnesium uptake and F. tularensis virulence. These results may provide new insights into the importance of magnesium for intracellular pathogens.

Consensus computational network analysis for identifying candidate outer membrane proteins from Borrelia spirochetes

Background

Similar to Gram-negative organisms, Borrelia spirochetes are dual-membrane organisms with both an inner and outer membrane. Although the outer membrane contains integral membrane proteins, few of the borrelial outer membrane proteins (OMPs) have been identified and characterized to date. Therefore, we utilized a consensus computational network analysis to identify novel borrelial OMPs.

Results

Using a series of computer-based algorithms, we selected all protein-encoding sequences predicted to be OM-localized and/or to form β-barrels in the borrelial OM. Using this system, we identified 41 potential OMPs from B. burgdorferi and characterized three (BB0838, BB0405, and BB0406) to confirm that our computer-based methodology did, in fact, identify borrelial OMPs. Triton X-114 phase partitioning revealed that BB0838 is found in the detergent phase, which would be expected of a membrane protein. Proteolysis assays indicate that BB0838 is partially sensitive to both proteinase K and trypsin, further indicating that BB0838 is surface-exposed. Consistent with a prior study, we also confirmed that BB0405 is surface-exposed and associates with the borrelial OM. Furthermore, we have shown that BB0406, the product of a co-transcribed downstream gene, also encodes a novel, previously uncharacterized borrelial OMP. Interestingly, while BB0406 has several physicochemical properties consistent with it being an OMP, it was found to be resistant to surface proteolysis. Consistent with BB0405 and BB0406 being OMPs, both were found to be capable of incorporating into liposomes and exhibit pore-forming activity, suggesting that both proteins are porins. Lastly, we expanded our computational analysis to identify OMPs from other borrelial organisms, including both Lyme disease and relapsing fever spirochetes.

Conclusions

Using a consensus computer algorithm, we generated a list of candidate OMPs for both Lyme disease and relapsing fever spirochetes and determined that three of the predicted B. burgdorferi proteins identified were indeed novel borrelial OMPs. The combined studies have identified putative spirochetal OMPs that can now be examined for their roles in virulence, physiology, and disease pathogenesis. Importantly, the studies described in this report provide a framework by which OMPs from any human pathogen with a diderm ultrastructure could be cataloged to identify novel virulence factors and vaccine candidates.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-016-0762-z) contains supplementary material, which is available to authorized users.

The Borrelia afzelii outer membrane protein BAPKO_0422 binds human factor-H and is predicted to form a membrane-spanning β-barrel

The deep evolutionary history of the Spirochetes places their branch point early in the evolution of the diderms, before the divergence of the present day Proteobacteria. As a spirochete, the morphology of the Borrelia cell envelope shares characteristics of both Gram-positive and Gram-negative bacteria. A thin layer of peptidoglycan, tightly associated with the cytoplasmic membrane, is surrounded by a more labile outer membrane (OM). This OM is rich in lipoproteins but with few known integral membrane proteins. The outer membrane protein A (OmpA) domain is an eight-stranded membrane-spanning β-barrel, highly conserved among the Proteobacteria but so far unknown in the Spirochetes. In the present work, we describe the identification of four novel OmpA-like β-barrels from Borrelia afzelii, the most common cause of erythema migrans (EM) rash in Europe. Structural characterization of one these proteins (BAPKO_0422) by SAXS and CD indicate a compact globular structure rich in β-strand consistent with a monomeric β-barrel. Ab initio molecular envelopes calculated from the scattering profile are consistent with homology models and demonstrate that BAPKO_0422 adopts a peanut shape with dimensions 25×45 Å (1 Å=0.1 nm). Deviations from the standard C-terminal signature sequence are apparent; in particular the C-terminal phenylalanine residue commonly found in Proteobacterial OM proteins is replaced by isoleucine/leucine or asparagine. BAPKO_0422 is demonstrated to bind human factor H (fH) and therefore may contribute to immune evasion by inhibition of the complement response. Encoded by chromosomal genes, these proteins are highly conserved between Borrelia subspecies and may be of diagnostic or therapeutic value.

All-atom 3D structure prediction of transmembrane β-barrel proteins from sequences

Transmembrane β-barrels (TMBs) carry out major functions in substrate transport and protein biogenesis but experimental determination of their 3D structure is challenging. Encouraged by successful de novo 3D structure prediction of globular and α-helical membrane proteins from sequence alignments alone, we developed an approach to predict the 3D structure of TMBs. The approach combines the maximum-entropy evolutionary coupling method for predicting residue contacts (EVfold) with a machine-learning approach (boctopus2) for predicting β-strands in the barrel. In a blinded test for 19 TMB proteins of known structure that have a sufficient number of diverse homologous sequences available, this combined method (EVfold_bb) predicts hydrogen-bonded residue pairs between adjacent β-strands at an accuracy of ∼70%. This accuracy is sufficient for the generation of all-atom 3D models. In the transmembrane barrel region, the average 3D structure accuracy [template-modeling (TM) score] of top-ranked models is 0.54 (ranging from 0.36 to 0.85), with a higher (44%) number of residue pairs in correct strand-strand registration than in earlier methods (18%). Although the nonbarrel regions are predicted less accurately overall, the evolutionary couplings identify some highly constrained loop residues and, for FecA protein, the barrel including the structure of a plug domain can be accurately modeled (TM score = 0.68). Lower prediction accuracy tends to be associated with insufficient sequence information and we therefore expect increasing numbers of β-barrel families to become accessible to accurate 3D structure prediction as the number of available sequences increases.

Strategies for the Analysis of Bam Recognition Motifs in Outer Membrane Proteins

Well-structured proteins interact with other proteins through surface-surface interactions. In such cases, the residues that form the interacting surface are not necessarily neighboring residues on the level of protein sequence. In contrast, unfolded or partially unfolded proteins can interact with other proteins through defined linear motifs. In the case of the β-barrel assembly machinery (BAM) in the outer membrane of Gram-negative bacteria, unfolded β-barrel proteins are recognized through a C-terminal linear motif, and are inserted into the membrane. While the exact mechanism of recognition is still under investigation, it has been shown that mutations in the recognition motif can partially or completely abolish membrane insertion. In this chapter, we demonstrate the workflow for motif discovery, motif extraction, and motif visualization on the example of the C-terminal motifs in transmembrane β-barrel proteins.

Identification of Protective Antigens for Vaccination against Systemic Salmonellosis

There is an urgent medical need for improved vaccines with broad serovar coverage and high efficacy against systemic salmonellosis. Subunit vaccines offer excellent safety profiles but require identification of protective antigens, which remains a challenging task. Here, I review crucial properties of Salmonella antigens that might help to narrow down the number of potential candidates from more than 4000 proteins encoded in Salmonella genomes, to a more manageable number of 50–200 most promising antigens. I also discuss complementary approaches for antigen identification and potential limitations of current pre-clinical vaccine testing.

topPTM: a new module of dbPTM for identifying functional post-translational modifications in transmembrane proteins

Transmembrane (TM) proteins have crucial roles in various cellular processes. The location of post-translational modifications (PTMs) on TM proteins is associated with their functional roles in various cellular processes. Given the importance of PTMs in the functioning of TM proteins, this study developed topPTM (available online at http://topPTM.cse.yzu.edu.tw), a new dbPTM module that provides a public resource for identifying the functional PTM sites on TM proteins with structural topology. Experimentally verified TM topology data were integrated from TMPad, TOPDB, PDBTM and OPM. In addition to the PTMs obtained from dbPTM, experimentally verified PTM sites were manually extracted from research articles by text mining. In an attempt to provide a full investigation of PTM sites on TM proteins, all UniProtKB protein entries containing annotations related to membrane localization and TM topology were considered potential TM proteins. Two effective tools were then used to annotate the structural topology of the potential TM proteins. The TM topology of TM proteins is represented by graphical visualization, as well as by the PTM sites. To delineate the structural correlation between the PTM sites and TM topologies, the tertiary structure of PTM sites on TM proteins was visualized by Jmol program. Given the support of research articles by manual curation and the investigation of domain-domain interactions in Protein Data Bank, 1347 PTM substrate sites are associated with protein-protein interactions for 773 TM proteins. The database content is regularly updated on publication of new data by continuous surveys of research articles and available resources.