Comparative proteomics of a versatile, marine, iron-oxidizing chemolithoautotroph

This study conducted a comparative proteomic analysis to identify potential genetic markers for the biological function of chemolithoautotrophic iron oxidation in the marine bacterium Ghiorsea bivora. To date, this is the only characterized species in the class Zetaproteobacteria that is not an obligate iron-oxidizer, providing a unique opportunity to investigate differential protein expression to identify key genes involved in iron-oxidation at circumneutral pH. Over 1000 proteins were identified under both iron- and hydrogen-oxidizing conditions, with differentially expressed proteins found in both treatments. Notably, a gene cluster upregulated during iron oxidation was identified. This cluster contains genes encoding for cytochromes that share sequence similarity with the known iron-oxidase, Cyc2. Interestingly, these cytochromes, conserved in both Bacteria and Archaea, do not exhibit the typical β-barrel structure of Cyc2. This cluster potentially encodes a biological nanowire-like transmembrane complex containing multiple redox proteins spanning the inner membrane, periplasm, outer membrane, and extracellular space. The upregulation of key genes associated with this complex during iron-oxidizing conditions was confirmed by quantitative reverse transcription-PCR. These findings were further supported by electromicrobiological methods, which demonstrated negative current production by G. bivora in a three-electrode system poised at a cathodic potential. This research provides significant insights into the biological function of chemolithoautotrophic iron oxidation.

NMPFamsDB: a database of novel protein families from microbial metagenomes and metatranscriptomes

The Novel Metagenome Protein Families Database (NMPFamsDB) is a database of metagenome- and metatranscriptome-derived protein families, whose members have no hits to proteins of reference genomes or Pfam domains. Each protein family is accompanied by multiple sequence alignments, Hidden Markov Models, taxonomic information, ecosystem and geolocation metadata, sequence and structure predictions, as well as 3D structure models predicted with AlphaFold2. In its current version, NMPFamsDB hosts over 100 000 protein families, each with at least 100 members. The reported protein families significantly expand (more than double) the number of known protein sequence clusters from reference genomes and reveal new insights into their habitat distribution, origins, functions and taxonomy. We expect NMPFamsDB to be a valuable resource for microbial proteome-wide analyses and for further discovery and characterization of novel functions. NMPFamsDB is publicly available in http://www.nmpfamsdb.org/ or https://bib.fleming.gr/NMPFamsDB.

Outer membrane β-barrel structure prediction through the lens of AlphaFold2

Most proteins found in the outer membrane of gram-negative bacteria share a common domain: the transmembrane β-barrel. These outer membrane β-barrels (OMBBs) occur in multiple sizes and different families with a wide range of functions evolved independently by amplification from a pool of homologous ancestral ββ-hairpins. This is part of the reason why predicting their three-dimensional (3D) structure, especially by homology modeling, is a major challenge. Recently, DeepMind's AlphaFold v2 (AF2) became the first structure prediction method to reach close-to-experimental atomic accuracy in CASP even for difficult targets. However, membrane proteins, especially OMBBs, were not abundant during their training, raising the question of how accurate the predictions are for these families. In this study, we assessed the performance of AF2 in the prediction of OMBBs and OMBB-like folds of various topologies using an in-house-developed tool for the analysis of OMBB 3D structures, and barrOs. In agreement with previous studies on other membrane protein classes, our results indicate that AF2 predicts transmembrane β-barrel structures at high accuracy independently of the use of templates, even for novel topologies absent from the training set. These results provide confidence on the models generated by AF2 and open the door to the structural elucidation of novel transmembrane β-barrel topologies identified in high-throughput OMBB annotation studies or designed de novo.

A novel vaccine candidate against A. baumannii based on a new OmpW family protein (OmpW2); structural characterization, antigenicity and epitope investigation, and in-vivo analysis

A. baumannii is an MDR pathogen whose SARS-CoV-2 has recently increased its mortality rate in hospitalized patients. So, the virulence factors investigation and design of a vaccine against this bacterium seem to be critical. In this regard, the OmpW2 protein was structurally characterized by this study, and its B-T cell epitopes were mapped by bioinformatic tools. In-vivo analyses were employed to verify the immunogenicity of this protein and its selected epitopes. The results indicated that OmpW2 is a conserved virulent antigen, not toxic for the host, and not similar to the human or mouse proteome. A putative interaction between OmpW2 and a Fe-S-cluster redox enzyme was detected. Based on the results, OmpW2 belongs to the OmpW superfamily and eight beta sheets have been predicted in its tight beta-barrel structure. Several exposed epitopes were detected in the OmpW2 sequence and structure, and a sub-unit potential vaccine was generated based on the epitopes. The ELISA results indicated that after the second booster vaccination of BALB/c mice with the whole OmpW2 protein or its sub-unit fragment, the IgG titer significantly raised (p < 0.05). The mortality rate and the bacterial burden in the lung, liver, kidney, and spleen in both passive and active immunized mice were significantly decreased (p ≤ 0.001). In-vivo experiments confirmed that the OmpW2 whole protein and its sub-unit fragment induce the host immune system and can be applied to design a commercial vaccine or diagnostic kit.

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.

The cell envelope of Thermotogae suggests a mechanism for outer membrane biogenesis

The presence of a cell membrane is one of the major structural components defining life. Recent phylogenomic analyses have supported the hypothesis that the last universal common ancestor (LUCA) was likely a diderm. Yet, the mechanisms that guided outer membrane (OM) biogenesis remain unknown. Thermotogae is an early-branching phylum with a unique OM, the toga. Here, we use cryo-electron tomography to characterize the in situ cell envelope architecture of Thermotoga maritima and show that the toga is made of extended sheaths of β-barrel trimers supporting small (~200 nm) membrane patches. Lipidomic analyses identified the same major lipid species in the inner membrane (IM) and toga, including the rare to bacteria membrane-spanning ether-bound diabolic acids (DAs). Proteomic analyses revealed that the toga was composed of multiple SLH-domain containing Ompα and novel β-barrel proteins, and homology searches detected variable conservations of these proteins across the phylum. These results highlight that, in contrast to the SlpA/OmpM superfamily of proteins, Thermotoga possess a highly diverse bipartite OM-tethering system. We discuss the implications of our findings with respect to other early-branching phyla and propose that a toga-like intermediate may have facilitated monoderm-to-diderm cell envelope transitions.

3D-BMPP: 3D Beta-Barrel Membrane Protein Predictor

β-barrel membrane proteins (βMPs), found in the outer membrane of gram-negative bacteria, mitochondria, and chloroplasts, play important roles in membrane anchoring, pore formation, and enzyme activities. However, it is often difficult to determine their structures experimentally, and the knowledge of their structures is currently limited. We have developed a method to predict the 3D architectures of βMPs. We can accurately construct transmembrane domains of βMPs by predicting their strand registers, from which full 3D atomic structures are derived. Using 3D Beta-barrel Membrane Protein Predictor (3D-BMPP), we can further accurately model the extended beta barrels and loops in non-TM regions with overall greater structure prediction coverage. 3DBMPP is a general technique that can be applied to protein families with limited sequences as well as proteins with novel folds. Applications of 3DBMPP can be broadly applied to genome-wide βMPs structure prediction.

Conservation of Energetic Pathways for Electroautotrophy in the Uncultivated Candidate Order Tenderiales

Electromicrobiology can be used to understand extracellular electron uptake in previously undescribed chemolithotrophs. Enrichment and characterization of the uncultivated electroautotroph "Candidatus Tenderia electrophaga" using electromicrobiology led to the designation of the order Tenderiales. Representative Tenderiales metagenome-assembled genomes (MAGs) have been identified in a number of environmental surveys, yet a comprehensive characterization of conserved genes for extracellular electron uptake has thus far not been conducted. Using comparative genomics, we identified conserved orthologous genes within the Tenderiales and nearest-neighbor orders important for extracellular electron uptake based on a previously proposed pathway from "Ca. Tenderia electrophaga." The Tenderiales contained a conserved cluster we designated uetABCDEFGHIJ, which encodes proteins containing features that would enable transport of extracellular electrons to cytoplasmic membrane-bound energy-transducing complexes such as two conserved cytochrome cbb₃ oxidases. For example, UetJ is predicted to be an extracellular undecaheme c-type cytochrome that forms a heme wire. We also identified clusters of genes predicted to facilitate assembly and maturation of electron transport proteins, as well as cellular attachment to surfaces. Autotrophy among the Tenderiales is supported by the presence of carbon fixation and stress response pathways that could allow cellular growth by extracellular electron uptake. Key differences between the Tenderiales and other known neutrophilic iron oxidizers were revealed, including very few Cyc2 genes in the Tenderiales. Our results reveal a possible conserved pathway for extracellular electron uptake and suggest that the Tenderiales have an ecological role in coupling metal or mineral redox chemistry and the carbon cycle in marine and brackish sediments. IMPORTANCE Chemolithotrophic bacteria capable of extracellular electron uptake to drive energy metabolism and CO₂ fixation are known as electroautotrophs. The recently described order Tenderiales contains the uncultivated electroautotroph "Ca. Tenderia electrophaga." The "Ca. Tenderia electrophaga" genome contains genes proposed to make up a previously undescribed extracellular electron uptake pathway. Here, we use comparative genomics to show that this pathway is well conserved among Tenderiales spp. recovered by metagenome-assembled genomes. This conservation extends to near neighbors of the Tenderiales but not to other well-studied chemolithotrophs, including iron and sulfur oxidizers, indicating that these genes may be useful markers of growth using insoluble extracellular electron donors. Our findings suggest that extracellular electron uptake and electroautotrophy may be pervasive among the Tenderiales, and the geographic locations from which metagenome-assembled genomes were recovered offer clues to their natural ecological niche.

Biological Role of the 3β-Corner Structural Motif in Proteins

In this study, we analyze the occurrence of the unique structural motif, the 3β-corner, belonging to the Structural Classification of Proteins (SCOP) folds, in proteins of various origins. We further assess the structural and functional role of this motif as well as the clustering of the biological functions of proteins in which it occurs. It has been shown previously that the 3β-corner occurs with different probabilities in all beta proteins, alpha and beta proteins (α + β and α/β), and alpha classes occur most often in the composition of β-proteins. The 3β-corner is often found as a building block in protein structures, such as β-barrels, -sandwiches, and -sheets/-layers.

Evidence for a Widespread Third System for Bacterial Polysaccharide Export across the Outer Membrane Comprising a Composite OPX/β-Barrel Translocon

In Gram-negative bacteria, secreted polysaccharides have multiple critical functions. In Wzx/Wzy- and ABC transporter-dependent pathways, an outer membrane (OM) polysaccharide export (OPX) type translocon exports the polysaccharide across the OM. The paradigm OPX protein Wza of Escherichia coli is an octamer in which the eight C-terminal domains form an α-helical OM pore and the eight copies of the three N-terminal domains (D1 to D3) form a periplasmic cavity. In synthase-dependent pathways, the OM translocon is a 16- to 18-stranded β-barrel protein. In Myxococcus xanthus, the secreted polysaccharide EPS (exopolysaccharide) is synthesized in a Wzx/Wzy-dependent pathway. Here, using experiments, phylogenomics, and computational structural biology, we identify and characterize EpsX as an OM 18-stranded β-barrel protein important for EPS synthesis and identify AlgE, a β-barrel translocon of a synthase-dependent pathway, as its closest structural homolog. We also find that EpsY, the OPX protein of the EPS pathway, consists only of the periplasmic D1 and D2 domains and completely lacks the domain for spanning the OM (herein termed a ^D1D2OPX protein). In vivo, EpsX and EpsY mutually stabilize each other and interact in in vivo pulldown experiments supporting their direct interaction. Based on these observations, we propose that EpsY and EpsX make up and represent a third type of translocon for polysaccharide export across the OM. Specifically, in this composite translocon, EpsX functions as the OM-spanning β-barrel translocon together with the periplasmic ^D1D2OPX protein EpsY. Based on computational genomics, similar composite systems are widespread in Gram-negative bacteria. IMPORTANCE Bacteria secrete a wide variety of polysaccharides that have critical functions in, e.g., fitness, surface colonization, and biofilm formation and in beneficial and pathogenic human-, animal-, and plant-microbe interactions. In Gram-negative bacteria, export of these chemically diverse polysaccharides across the outer membrane depends on two known translocons, i.e., an outer membrane OPX protein in Wzx/Wzy- and ABC transporter-dependent pathways and an outer membrane 16- to 18-stranded β-barrel protein in synthase-dependent pathways. Here, using a combination of experiments in Myxococcus xanthus, phylogenomics, and computational structural biology, we provide evidence supporting that a third type of translocon can export polysaccharides across the outer membrane. Specifically, in this translocon, an outer membrane-spanning β-barrel protein functions together with an entirely periplasmic OPX protein that completely lacks the domain for spanning the OM. Computational genomics support that similar composite systems are widespread in Gram-negative bacteria.

TMbed: transmembrane proteins predicted through language model embeddings

BACKGROUND

Despite the immense importance of transmembrane proteins (TMP) for molecular biology and medicine, experimental 3D structures for TMPs remain about 4-5 times underrepresented compared to non-TMPs. Today's top methods such as AlphaFold2 accurately predict 3D structures for many TMPs, but annotating transmembrane regions remains a limiting step for proteome-wide predictions.

RESULTS

Here, we present TMbed, a novel method inputting embeddings from protein Language Models (pLMs, here ProtT5), to predict for each residue one of four classes: transmembrane helix (TMH), transmembrane strand (TMB), signal peptide, or other. TMbed completes predictions for entire proteomes within hours on a single consumer-grade desktop machine at performance levels similar or better than methods, which are using evolutionary information from multiple sequence alignments (MSAs) of protein families. On the per-protein level, TMbed correctly identified 94 ± 8% of the beta barrel TMPs (53 of 57) and 98 ± 1% of the alpha helical TMPs (557 of 571) in a non-redundant data set, at false positive rates well below 1% (erred on 30 of 5654 non-membrane proteins). On the per-segment level, TMbed correctly placed, on average, 9 of 10 transmembrane segments within five residues of the experimental observation. Our method can handle sequences of up to 4200 residues on standard graphics cards used in desktop PCs (e.g., NVIDIA GeForce RTX 3060).

CONCLUSIONS

Based on embeddings from pLMs and two novel filters (Gaussian and Viterbi), TMbed predicts alpha helical and beta barrel TMPs at least as accurately as any other method but at lower false positive rates. Given the few false positives and its outstanding speed, TMbed might be ideal to sieve through millions of 3D structures soon to be predicted, e.g., by AlphaFold2.

Phylogenomic analysis and metabolic role reconstruction of mutualistic Rhizobiales hindgut symbionts of Acromyrmex leaf-cutting ants

Rhizobiales are well-known plant-root nitrogen-fixing symbionts, but the functions of insect-associated Rhizobiales are poorly understood. We obtained genomes of three strains associated with Acromyrmex leaf-cutting ants and show that, in spite of being extracellular gut symbionts, they lost all pathways for essential amino acid biosynthesis, making them fully dependent on their hosts. Comparison with 54 Rhizobiales genomes showed that all insect-associated Rhizobiales lost the ability to fix nitrogen and that the Acromyrmex symbionts had exceptionally also lost the urease genes. However, the Acromyrmex strains share biosynthesis pathways for riboflavin vitamin, queuosine and a wide range of antioxidant enzymes likely to be beneficial for the ant fungus-farming symbiosis. We infer that the Rhizobiales symbionts catabolize excess of fungus-garden-derived arginine to urea, supplementing complementary Mollicutes symbionts that turn arginine into ammonia and infer that these combined symbiont activities stabilize the fungus-farming mutualism. Similar to the Mollicutes symbionts, the Rhizobiales species have fully functional CRISPR/Cas and R-M phage defenses, suggesting that these symbionts are important enough for the ant hosts to have precluded the evolution of metabolically cheaper defenseless strains.

Characterization of the Putative Acylated Cellulose Synthase Operon in Komagataeibacter xylinus E25

Bacterial cellulose is a natural polymer with an expanding array of applications. Because of this, the main cellulose producers of the Komagataeibacter genus have been extensively studied with the aim to increase its synthesis or to customize its physicochemical features. Up to now, the genetic studies in Komagataeibacter have focused on the first cellulose synthase operon (bcsI) encoding the main enzyme complex. However, the role of other accessory cellulose operons has been understudied. Here we aimed to fill this gap by performing a detailed analysis of the second cellulose synthase operon (bcsII), which is putatively linked with cellulose acylation. In this study we harnessed the genome sequence, gene expression and protein structure information of K. xylinus E25 and other Komagataeibacter species to discuss the probable features of bcsII and the biochemical function of its main protein products. The results of our study support the previous hypothesis that bcsII is involved in the synthesis of the acylated polymer and expand it by presenting the evidence that it may also function in the regulation of its attachment to the cell surface and to the crystalline cellulose fibers.

A unique antigen against SARS-CoV-2, Acinetobacter baumannii, and Pseudomonas aeruginosa

The recent outbreak of COVID-19 has increased hospital admissions, which could elevate the risk of nosocomial infections, such as A. baumannii and P. aeruginosa infections. Although effective vaccines have been developed against SARS-CoV-2, no approved treatment option is still available against antimicrobial-resistant strains of A. baumannii and P. aeruginosa. In the current study, an all-in-one antigen was designed based on an innovative, state-of-the-art strategy. In this regard, experimentally validated linear epitopes of spike protein (SARS-CoV-2), OmpA (A. baumannii), and OprF (P. aeruginosa) were selected to be harbored by mature OmpA as a scaffold. The selected epitopes were used to replace the loops and turns of the barrel domain in OmpA; OprF_311–341 replaced the most similar sequence within the OmpA, and three validated epitopes of OmpA were retained intact. The obtained antigen encompasses five antigenic peptides of spike protein, which are involved in SARS-CoV-2 pathogenicity. One of these epitopes, viz. QTQTNSPRRARSV could trigger antibodies preventing super-antigenic characteristics of spike and alleviating probable autoimmune responses. The designed antigen could raise antibodies neutralizing emerging variants of SARS-CoV-2 since at least two epitopes are consensus. In conclusion, the designed antigen is expected to raise protective antibodies against SARS-CoV-2, A. baumannii, and P. aeruginosa.

Drosophila nicotinic acetylcholine receptor subunits and their native interactions with insecticidal peptide toxins

Drosophila nicotinic acetylcholine receptors (nAChRs) are ligand-gated ion channels that represent a target for insecticides. Peptide neurotoxins are known to block nAChRs by binding to their target subunits, however, a better understanding of this mechanism is needed for effective insecticide design. To facilitate the analysis of nAChRs we used a CRISPR/Cas9 strategy to generate null alleles for all ten nAChR subunit genes in a common genetic background. We studied interactions of nAChR subunits with peptide neurotoxins by larval injections and styrene maleic acid lipid particles (SMALPs) pull-down assays. For the null alleles, we determined the effects of α-Bungarotoxin (α-Btx) and ω-Hexatoxin-Hv1a (Hv1a) administration, identifying potential receptor subunits implicated in the binding of these toxins. We employed pull-down assays to confirm α-Btx interactions with the Drosophila α5 (Dα5), Dα6, Dα7 subunits. Finally, we report the localisation of fluorescent tagged endogenous Dα6 during Drosophila CNS development. Taken together, this study elucidates native Drosophila nAChR subunit interactions with insecticidal peptide toxins and provides a resource for the in vivo analysis of insect nAChRs.

An ancient divide in outer membrane tethering systems in bacteria suggests a mechanism for the diderm-to-monoderm transition

Recent data support the hypothesis that Gram-positive bacteria (monoderms) arose from Gram-negative ones (diderms) through loss of the outer membrane (OM), but how this happened remains unknown. As tethering of the OM is essential for cell envelope stability in diderm bacteria, its destabilization may have been involved in this transition. In the present study, we present an in-depth analysis of the four known main OM-tethering systems across the Tree of Bacteria (ToB). We show that the presence of such systems follows the ToB with a bimodal distribution matching the deepest phylogenetic divergence between Terrabacteria and Gracilicutes. Whereas the lipoprotein peptidoglycan-associated lipoprotein (Pal) is restricted to the Gracilicutes, along with a more sporadic occurrence of OmpA, and Braun's lipoprotein is present only in a subclade of Gammaproteobacteria, diderm Terrabacteria display, as the main system, the OmpM protein. We propose an evolutionary scenario whereby OmpM represents a simple, ancestral OM-tethering system that was later replaced by one based on Pal after the emergence of the Lol machinery to deliver lipoproteins to the OM, with OmpA as a possible transition state. We speculate that the existence of only one main OM-tethering system in the Terrabacteria would have allowed the multiple OM losses specifically inferred in this clade through OmpM perturbation, and we provide experimental support for this hypothesis by inactivating all four ompM gene copies in the genetically tractable diderm Firmicute Veillonella parvula. High-resolution imaging and tomogram reconstructions reveal a non-lethal phenotype in which vast portions of the OM detach from the cells, forming huge vesicles with an inflated periplasm shared by multiple dividing cells. Together, our results highlight an ancient shift of OM-tethering systems in bacterial evolution and suggest a mechanism for OM loss and the multiple emergences of the monoderm phenotype from diderm ancestors.

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.

A Multitask Deep-Learning Method for Predicting Membrane Associations and Secondary Structures of Proteins

Prediction of residue-level structural attributes and protein-level structural classes helps model protein tertiary structures and understand protein functions. Existing methods are either specialized on only one class of proteins or developed to predict only a specific type of residue-level attribute. In this work, we develop a new deep-learning method, named Membrane Association and Secondary Structure Predictor (MASSP), for accurately predicting both residue-level structural attributes (secondary structure, location, orientation, and topology) and protein-level structural classes (bitopic, α-helical, β-barrel, and soluble). MASSP integrates a multilayer two-dimensional convolutional neural network (2D-CNN) with a long short-term memory (LSTM) neural network into a multitasking framework. Our comparison shows that MASSP performs equally well or better than the state-of-the-art methods in predicting residue-level secondary structures, boundaries of transmembrane segments, and topology. Furthermore, it achieves outstanding accuracy in predicting protein-level structural classes. MASSP automatically distinguishes the structural classes of input sequences and identifies transmembrane segments and topologies if present, making it broadly applicable to different classes of proteins. In summary, MASSP's good performance and broad applicability make it well suited for annotating residue-level attributes and protein-level structural classes at the proteome scale.

A Glycoside Hydrolase Family 99-Like Domain-Containing Protein Modifies Outer Membrane Proteins to Maintain Xanthomonas Pathogenicity and Viability in Stressful Environments

Protein glycosylation is an essential process that plays an important role in proteome stability, protein structure, and protein function modulation in eukaryotes. However, in bacteria, especially plant pathogenic bacteria, similar studies are lacking. Here, we investigated the relationship between protein glycosylation and pathogenicity by using Xanthomonas oryzae pv. oryzae, the causal agent of bacterial leaf blight in rice, as a well-defined example. In our previous work, we identified a virulence-related hypothetical protein, PXO_03177, but how this protein regulates X. oryzae pv. oryzae virulence has remained unclear. BLAST analysis showed that most homologous proteins of PXO_03177 are glycoside hydrolase family 99-like domain-containing proteins. In the current study, we found that the outer membrane integrity of ΔPXO_03177 appeared to be disrupted. Extracting the outer membrane proteins (OMPs) and performing comparative proteomics and sodium dodecyl sulphate-polyacrylamide gel electrophoresis gel staining analyses revealed that PXO_03177 deletion altered the protein levels of 13 OMPs. Western blot analyses showed that the protein level and glycosylation modification of PXO_02523, a related OmpA family-like protein, was changed in the ΔPXO_03177 mutant background strain. Additionally, the interaction between PXO_03177 and PXO_02523 was confirmed by coimmunoprecipitation. Both PXO_03177 and PXO_02523 play important roles in regulating pathogen virulence and viability in stressful environments. This work provides the first evidence that protein glycosylation is necessary for the virulence of plant pathogenic bacteria.

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.

Expansion and re-classification of the extracytoplasmic function (ECF) σ factor family

Extracytoplasmic function σ factors (ECFs) represent one of the major bacterial signal transduction mechanisms in terms of abundance, diversity and importance, particularly in mediating stress responses. Here, we performed a comprehensive phylogenetic analysis of this protein family by scrutinizing all proteins in the NCBI database. As a result, we identified an average of ∼10 ECFs per bacterial genome and 157 phylogenetic ECF groups that feature a conserved genetic neighborhood and a similar regulation mechanism. Our analysis expands previous classification efforts ∼50-fold, enriches many original ECF groups with previously unclassified proteins and identifies 22 entirely new ECF groups. The ECF groups are hierarchically related to each other and are further composed of subgroups with closely related sequences. This two-tiered classification allows for the accurate prediction of common promoter motifs and the inference of putative regulatory mechanisms across subgroups composing an ECF group. This comprehensive, high-resolution description of the phylogenetic distribution of the ECF family, together with the massive expansion of classified ECF sequences and an openly accessible data repository called ‘ECF Hub’ (https://www.computational.bio.uni-giessen.de/ecfhub), will serve as a powerful hypothesis-generator to guide future research in the field.

The Two TpsB-Like Proteins in Anabaena sp. Strain PCC 7120 Are Involved in Secretion of Selected Substrates

The outer membrane of Gram-negative bacteria acts as an initial diffusion barrier that shields the cell from the environment. It contains many membrane-embedded proteins required for functionality of this system. These proteins serve as solute and lipid transporters or as machines for membrane insertion or secretion of proteins. The genome of Anabaena sp. strain PCC 7120 codes for two outer membrane transporters termed TpsB1 and TpsB2. They belong to the family of the two-partner secretion system proteins which are characteristic of pathogenic bacteria. Because pathogenicity of Anabaena sp. strain PCC 7120 has not been reported, the function of these two cyanobacterial TpsB proteins was analyzed. TpsB1 is encoded by alr1659, while TpsB2 is encoded by all5116 The latter is part of a genomic region containing 11 genes encoding TpsA-like proteins. However, tpsB2 is transcribed independently of a tpsA gene cluster. Bioinformatics analysis revealed the presence of at least 22 genes in Anabaena sp. strain PCC 7120 putatively coding for substrates of the TpsB system, suggesting a rather global function of the two TpsB proteins. Insertion of a plasmid into each of the two genes resulted in altered outer membrane integrity and antibiotic resistance. In addition, the expression of genes coding for the Clp and Deg proteases is dysregulated in these mutants. Moreover, for two of the putative substrates, a dependence of the secretion on functional TpsB proteins could be confirmed. We confirm the existence of a two-partner secretion system in Anabaena sp. strain PCC 7120 and predict a large pool of putative substrates.IMPORTANCE Cyanobacteria are important organisms for the ecosystem, considering their contribution to carbon fixation and oxygen production, while at the same time some species produce compounds that are toxic to their environment. As a consequence, cyanobacterial overpopulation might negatively impact the diversity of natural communities. Thus, a detailed understanding of cyanobacterial interaction with the environment, including other organisms, is required to define their impact on ecosystems. While two-partner secretion systems in pathogenic bacteria are well known, we provide a first description of the cyanobacterial two-partner secretion system.

Identification and genetic diversity analysis of a male-sterile gene (MS1) in Japanese cedar (Cryptomeria japonica D. Don)

Identifying causative genes for a target trait in conifer reproduction is challenging for species lacking whole-genome sequences. In this study, we searched for the male-sterility gene (MS1) in Cryptomeria japonica, aiming to promote marker-assisted selection (MAS) of male-sterile C. japonica to reduce the pollinosis caused by pollen dispersal from artificial C. japonica forests in Japan. We searched for mRNA sequences expressed in male strobili and found the gene CJt020762, coding for a lipid transfer protein containing a 4-bp deletion specific to male-sterile individuals. We also found a 30-bp deletion by sequencing the entire gene of another individual with the ms1. All nine breeding materials with the allele ms1 had either a 4-bp or 30-bp deletion in gene CJt020762, both of which are expected to result in faulty gene transcription and function. Furthermore, the 30-bp deletion was detected from three of five individuals in the Ishinomaki natural forest. From our findings, CJt020762 was considered to be the causative gene of MS1. Thus, by performing MAS using two deletion mutations as a DNA marker, it will be possible to find novel breeding materials of C. japonica with the allele ms1 adapted to the unique environment of each region of the Japanese archipelago.

Integrative approach for detecting membrane proteins

Background

Membrane proteins are key gates that control various vital cellular functions. Membrane proteins are often detected using transmembrane topology prediction tools. While transmembrane topology prediction tools can detect integral membrane proteins, they do not address surface-bound proteins. In this study, we focused on finding the best techniques for distinguishing all types of membrane proteins.

Results

This research first demonstrates the shortcomings of merely using transmembrane topology prediction tools to detect all types of membrane proteins. Then, the performance of various feature extraction techniques in combination with different machine learning algorithms was explored. The experimental results obtained by cross-validation and independent testing suggest that applying an integrative approach that combines the results of transmembrane topology prediction and position-specific scoring matrix (Pse-PSSM) optimized evidence-theoretic k nearest neighbor (OET-KNN) predictors yields the best performance.

Conclusion

The integrative approach outperforms the state-of-the-art methods in terms of accuracy and MCC, where the accuracy reached a 92.51% in independent testing, compared to the 89.53% and 79.42% accuracies achieved by the state-of-the-art methods.

BetAware-Deep: An Accurate Web Server for Discrimination and Topology Prediction of Prokaryotic Transmembrane β-barrel Proteins

TransMembrane β-Barrel (TMBB) proteins located in the outer membranes of Gram-negative bacteria are crucial for many important biological processes and primary candidates as drug targets. Structure determination of TMBB proteins is challenging and hence computational methods devised for the analysis of TMBB proteins are important for complementing experimental approaches. Here, we present a novel web server called BetAware-Deep that is able to accurately identify the topology of TMBB proteins (i.e. the number and orientation of membrane-spanning segments along the protein sequence) and to discriminate them from other protein types. The method in BetAware-Deep defines new features by exploiting a non-canonical computation of the hydrophobic moment and by adopting sequence-profile weighting of the White&Wimley hydrophobicity scale. These features are processed using a two-step approach based on deep learning and probabilistic graphical models. BetAware-Deep has been trained on a dataset comprising 58 TMBBs and benchmarked on a novel set of 15 TMBB proteins. Results showed that BetAware-Deep outperforms two recently released state-of-the-art methods for topology prediction, predicting correct topologies of 10 out of 15 proteins. TMBB detection was also assessed on a larger dataset comprising 1009 TMBB proteins and 7571 non-TMBB proteins. Even in this benchmark, BetAware-Deep scored at the level of top-performing methods. A web server has been developed allowing users to analyze input protein sequences and providing topology prediction together with a rich set of information including a graphical representation of the residue-level annotations and prediction probabilities. BetAware-Deep is available at https://busca.biocomp.unibo.it/betaware2.

Cascading classifier application for topology prediction of transmembrane beta-barrel proteins

Membrane proteins are a major focus for new drug discovery. Transmembrane beta-barrel (TMB) proteins play key roles in the translocation machinery, pore formation, membrane anchoring and ion exchange. Given their key roles and the difficulty in membrane protein structure determination, the use of computational modeling is essential. This paper focuses on the topology prediction of TMB proteins. In the field of bioinformatics, many years of research has been spent on the topology prediction of transmembrane alpha-helices. The efforts to TMB proteins topology prediction have been overshadowed and the prediction accuracy could be improved with further research. Various methodologies have been developed in the past for the prediction of TMB protein topology, however, the use of cascading classifier has never been fully explored. This research presents a novel approach to TMB topology prediction with the use of a cascading classifier. The MATLAB computer simulation results show that the proposed methodology predicts TMB proteins topologies with high accuracy for randomly selected proteins. By using the cascading classifier approach, the best overall accuracy is 76.3% with a precision of 0.831 and recall or probability of detection of 0.799 for TMB topology prediction. The accuracy of 76.3% is achieved using a two-layers cascading classifier.

Differences between predicted outer membrane proteins of genotype 1 and 2 Mannheimia haemolytica

BACKGROUND

Mannheimia haemolytica strains isolated from North American cattle have been classified into two genotypes (1 and 2). Although members of both genotypes have been isolated from the upper and lower respiratory tracts of cattle with or without bovine respiratory disease (BRD), genotype 2 strains are much more frequently isolated from diseased lungs than genotype 1 strains. The mechanisms behind the increased association of genotype 2 M. haemolytica with BRD are not fully understood. To address that, and to search for interventions against genotype 2 M. haemolytica, complete, closed chromosome assemblies for 35 genotype 1 and 34 genotype 2 strains were generated and compared. Searches were conducted for the pan genome, core genes shared between the genotypes, and for genes specific to either genotype. Additionally, genes encoding outer membrane proteins (OMPs) specific to genotype 2 M. haemolytica were identified, and the diversity of their protein isoforms was characterized with predominantly unassembled, short-read genomic sequences for up to 1075 additional strains.

RESULTS

The pan genome of the 69 sequenced M. haemolytica strains consisted of 3111 genes, of which 1880 comprised a shared core between the genotypes. A core of 112 and 179 genes or gene variants were specific to genotype 1 and 2, respectively. Seven genes encoding predicted OMPs; a peptidase S6, a ligand-gated channel, an autotransporter outer membrane beta-barrel domain-containing protein (AOMB-BD-CP), a porin, and three different trimeric autotransporter adhesins were specific to genotype 2 as their genotype 1 homologs were either pseudogenes, or not detected. The AOMB-BD-CP gene, however, appeared to be truncated across all examined genotype 2 strains and to likely encode dysfunctional protein. Homologous gene sequences from additional M. haemolytica strains confirmed the specificity of the remaining six genotype 2 OMP genes and revealed they encoded low isoform diversity at the population level.

CONCLUSION

Genotype 2 M. haemolytica possess genes encoding conserved OMPs not found intact in more commensally prone genotype 1 strains. Some of the genotype 2 specific genes identified in this study are likely to have important biological roles in the pathogenicity of genotype 2 M. haemolytica, which is the primary bacterial cause of BRD.

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.

MPTherm: database for membrane protein thermodynamics for understanding folding and stability

The functions of membrane proteins (MPs) are attributed to their structure and stability. Factors influencing the stability of MPs differ from globular proteins due to the presence of membrane spanning regions. Thermodynamic data of MPs aid to understand the relationship among their structure, stability and function. Although a wealth of experimental data on thermodynamics of MPs are reported in the literature, there is no database available explicitly for MPs. In this work, we have developed a database for MP thermodynamics, MPTherm, which contains more than 7000 thermodynamic data from about 320 MPs. Each entry contains protein sequence and structural information, membrane topology, experimental conditions, thermodynamic parameters such as melting temperature, free energy, enthalpy etc. and literature information. MPTherm assists users to retrieve the data by using different search and display options. We have also provided the sequence and structure visualization as well as cross-links to UniProt and PDB databases. MPTherm database is freely available at http://www.iitm.ac.in/bioinfo/mptherm/. It is implemented in HTML, PHP, MySQL and JavaScript, and supports the latest versions of major browsers, such as Firefox, Chrome and Opera. MPTherm would serve as an effective resource for understanding the stability of MPs, development of prediction tools and identifying drug targets for diseases associated with MPs.

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.

TranCEP: Predicting the substrate class of transmembrane transport proteins using compositional, evolutionary, and positional information

Transporters mediate the movement of compounds across the membranes that separate the cell from its environment and across the inner membranes surrounding cellular compartments. It is estimated that one third of a proteome consists of membrane proteins, and many of these are transport proteins. Given the increase in the number of genomes being sequenced, there is a need for computational tools that predict the substrates that are transported by the transmembrane transport proteins. In this paper, we present TranCEP, a predictor of the type of substrate transported by a transmembrane transport protein. TranCEP combines the traditional use of the amino acid composition of the protein, with evolutionary information captured in a multiple sequence alignment (MSA), and restriction to important positions of the alignment that play a role in determining the specificity of the protein. Our experimental results show that TranCEP significantly outperforms the state-of-the-art predictors. The results quantify the contribution made by each type of information used.

Enzymes contributing to the hydrogen peroxide signal dynamics that regulate wall labyrinth formation in transfer cells

Transfer cells are characterized by an amplified plasma membrane area supported on a wall labyrinth composed of a uniform wall layer (UWL) from which wall ingrowth (WI) papillae arise. Adaxial epidermal cells of developing Vicia faba cotyledons, when placed in culture, undergo a rapid (hours) trans-differentiation to a functional epidermal transfer cell (ETC) phenotype. The trans-differentiation event is controlled by a signalling cascade comprising auxin, ethylene, apoplasmic reactive oxygen species (apoROS), and cytosolic Ca2+. Apoplasmic hydrogen peroxide (apoH2O2) was confirmed as the apoROS regulating UWL and WI papillae formation. Informed by an ETC-specific transcriptome, a pharmacological approach identified a temporally changing cohort of H2O2 biosynthetic enzymes. The cohort contained a respiratory burst oxidase homologue, polyamine oxidase, copper amine oxidase, and a suite of class III peroxidases. Collectively these generated two consecutive bursts in apoH2O2 production. Spatial organization of biosynthetic/catabolic enzymes was deduced from responses to pharmacologically blocking their activities on the cellular and subcellular distribution of apoH2O2. The findings were consistent with catalase activity constraining the apoH2O2 signal to the outer periclinal wall of the ETCs. Strategic positioning of class III peroxidases in this outer domain shaped subcellular apoH2O2 signatures that differed during assembly of the UWL and WI papillae.

Spectroscopic analysis of chlamydial major outer membrane protein in support of structure elucidation

Chlamydial major outer membrane protein (MOMP) is the major protein constituent of the bacterial pathogen Chlamydia trachomatis. Chlamydia trachomatis Serovars D–K are the leading cause of genital tract infections which can lead to infertility or ectopic pregnancies. A vaccine against Chlamydia is highly desirable but currently not available. MOMP accounts for ~ 60% of the chlamydial protein mass and is considered to be one of the lead vaccine candidates against C. trachomatis. We report on the spectroscopic analysis of C. trachomatis native MOMP Serovars D, E, F, and J as well as C. muridarum MOMP by size exclusion chromatography multi angle light scattering (SEC MALS), circular dichroism (CD) and attenuated total reflectance Fourier transform infrared spectroscopy (ATR‐FTIR). MOMP was purified from the native bacterium grown in either adherent HeLa cells or in different suspension cell lines. Our results confirm that MOMP forms homo‐trimers in detergent micelles. The secondary structure composition of C. trachomatis MOMP was conserved across serovars, but different from composition of C. muridarum MOMP with a 13% (CD) to 18% (ATR‐FTIR) reduction in β‐sheet conformation for C. trachomatis MOMP. When Serovar E MOMP was isolated from suspension cell lines the α‐helix content increased by 7% (CD) to 13% (ATIR‐FTIR). Maintenance of a native‐like tertiary and quaternary structure in subunit vaccines is important for the generation of protective antibodies. This biophysical characterization of MOMP presented here serves, in the absence of functional assays, as a method for monitoring the structural integrity of MOMP.

Comparative Study on A Novel Pathogen of European Seabass. Diversity of Aeromonas veronii in the Aegean Sea

Aeromonas veronii is an emerging pathogen causing severe pathology and mortalities in European seabass aquaculture in the Aegean Sea, Mediterranean. More than 50 strains of the pathogen were characterized biochemically and genetically in order to study the epidemiology of the disease, as well as the phylogeny and virulence of the bacterium. Based on the phenotypic characteristics, the isolates form three groups consisting of: (a) the West Aegean Sea, non-motile, non-pigment-producing strains, (b) the West Aegean Sea, motile, and pigment-producing strains and (c) the East Aegean Sea motile strains that produce minute amounts of pigment. All strains were highly similar at the genomic level; however, the pattern of West/East geographic origin was reflected in biochemical properties, in general genomic level comparison and in the putative virulent factors studied. Type VI secretion system was not detected in the western strains. The outer membrane protein (OMP) profile which contains proteins that are putative antigenic factors, was very similar between strains from the different areas. Although most of the OMPs were detected in all strains with great sequence similarity, diversification according to geographic origin was evident in known antigenic factors such as the maltoporin LamB. A systematic comparative analysis of the strains is presented and discussed in view of the emergence of A. veronii as a significant pathogen for the Mediterranean aquaculture.

Adaptive Evolution of Sphingobium hydrophobicum C1T in Electronic Waste Contaminated River Sediment

Electronic waste (e-waste) has caused a severe worldwide pollution problem. Despite increasing isolation of degradative microorganisms from e-waste contaminated environments, the mechanisms underlying their adaptive evolution in such habitats remain unclear. Sphingomonads generally have xenobiotic-degrading ability and may play important roles in bioremediation. Sphingobium hydrophobicum C1^T, characterized with superior cell surface hydrophobicity, was recently isolated from e-waste contaminated river sediment. To dissect the mechanisms driving its adaptive evolution, we evaluated its stress resistance, sequenced its genome and performed comparative genomic analysis with 19 other Sphingobium strains. Strain C1^T can feed on several kinds of e-waste-derived xenobiotics, exhibits a great resistance to heavy metals and possesses a high colonization ability. It harbors abundant genes involved in environmental adaptation, some of which are intrinsic prior to experiencing e-waste contamination. The extensive genomic variations between strain C1^T and other Sphingobium strains, numerous C1^T-unique genes, massive mobile elements and frequent genome rearrangements reflect a high genome plasticity. Positive selection, gene duplication, and especially horizontal gene transfer drive the adaptive evolution of strain C1^T. Moreover, presence of type IV secretion systems may allow strain C1^T to be a source of beneficial genes for surrounding microorganisms. This study provides new insights into the adaptive evolution of sphingomonads, and potentially guides bioremediation strategies.

Omp19 Enables Brucella abortus to Evade the Antimicrobial Activity From Host's Proteolytic Defense System

Pathogenic microorganisms confront several proteolytic events in the molecular interplay with their host, highlighting that proteolysis and its regulation play an important role during infection. Microbial inhibitors, along with their target endogenous/exogenous enzymes, may directly affect the host's defense mechanisms and promote infection. Omp19 is a Brucella spp. conserved lipoprotein anchored by the lipid portion in the Brucella outer membrane. Previous work demonstrated that purified unlipidated Omp19 (U-Omp19) has protease inhibitor activity against gastrointestinal and lysosomal proteases. In this work, we found that a Brucella omp19 deletion mutant is highly attenuated in mice when infecting by the oral route. This attenuation can be explained by bacterial increased susceptibility to host proteases met by the bacteria during establishment of infection. Omp19 deletion mutant has a cell division defect when exposed to pancreatic proteases that is linked to cell-cycle arrest in G1-phase, Omp25 degradation on the cell envelope and CtrA accumulation. Moreover, Omp19 deletion mutant is more susceptible to killing by macrophage derived microsomes than wt strain. Preincubation with gastrointestinal proteases led to an increased susceptibility of Omp19 deletion mutant to macrophage intracellular killing. Thus, in this work, we describe for the first time a physiological function of B. abortus Omp19. This activity enables Brucella to better thrive in the harsh gastrointestinal tract, where protection from proteolytic degradation can be a matter of life or death, and afterwards invade the host and bypass intracellular proteases to establish the chronic infection.

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.

Novel lineage-specific transmembrane β-barrel proteins in the endoplasmic reticulum of Entamoeba histolytica

β-barrel outer membrane proteins (BOMPs) are essential components of outer membranes of Gram-negative bacteria and endosymbiotic organelles, usually involved in the transport of proteins and substrates across the membrane. Based on the analysis of our in silico BOMP predictor data for the Entamoeba histolytica genome, we detected a new transmembrane β-barrel domain-containing protein, EHI_192610. Sequence analysis revealed that this protein is unique to Entamoeba species, and it exclusively clusters with a homolog, EHI_099780, which is similarly lineage specific. Both proteins possess an N-terminal signal peptide sequence as well as multiple repeats that contain dyad hydrophobic periodicities. Data from immunofluorescence assay of trophozoites expressing the respective candidates showed the absence of colocalization with mitosomal marker, and interestingly demonstrated partial colocalization with endoplasmic reticulum (ER) proteins instead. Integration to organellar membrane was supported by carbonate fractionation assay and immunoelectron microscopy. CD analysis of reconstituted proteoliposomes containing EHI_192610 showed a spectrum demonstrating a predominant β-sheet structure, suggesting that this protein is β-strand rich. Furthermore, the presence of repeat regions with predicted transmembrane β-strand pairs in both EHI_192610 and EHI_099780, is consistent with the hypothesis that BOMPs originated from the amplification of ββ-hairpin modules, suggesting that the two Entamoeba-specific proteins are novel β-barrels, intriguingly localized partially to the ER membrane.

Occurrence and Function of the Na+-Translocating NADH:Quinone Oxidoreductase in Prevotella spp

Strictly anaerobic Prevotella spp. are characterized by their vast metabolic potential. As members of the Prevotellaceae family, they represent the most abundant organisms in the rumen and are typically found in monogastrics such as pigs and humans. Within their largely anoxic habitats, these bacteria are considered to rely primarily on fermentation for energy conservation. A recent study of the rumen microbiome identified multiple subunits of the Na⁺-translocating NADH:quinone oxidoreductase (NQR) belonging to different Prevotella spp. Commonly, the NQR is associated with biochemical energy generation by respiration. The existence of this Na⁺ pump in Prevotella spp. may indicate an important role for electrochemical Na⁺ gradients in their anaerobic metabolism. However, detailed information about the potential activity of the NQR in Prevotella spp. is not available. Here, the presence of a functioning NQR in the strictly anaerobic model organism P. bryantii B₁4 was verified by conducting mass spectrometric, biochemical, and kinetic experiments. Our findings propose that P. bryantii B₁4 and other Prevotella spp. retrieved from the rumen operate a respiratory NQR together with a fumarate reductase which suggests that these ruminal bacteria utilize a sodium motive force generated during respiratory NADH:fumarate oxidoreduction.

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.

Proteomic characterization of outer membrane vesicles from gut mucosa-derived fusobacterium nucleatum

Fusobacterium nucleatum is a Gram-negative bacterium commonly found in the oral cavity and is often involved in periodontal diseases. Recent studies have shown increased F. nucleatum prevalence in colorectal cancer (CRC) tissues, and causal data has linked this bacterium to CRC tumorigenesis. Immune-based approaches to contain, reduce or eradicate its gut colonization may prevent CRC. Outer membrane vesicles (OMVs) are naturally produced by Gram-negative bacteria, typically contain multiple putative virulence factors and may elicit protective immune responses if used as vaccines. Here, OMVs were isolated from F. nucleatum cultures and purified using gradient centrifugation. Proteins contained within the OMVs were identified by nano LC/MS/MS analysis. Of 98 proteins consistently identified from duplicate analyses, 60 were predicted to localize to the outer membrane or periplasm via signal peptide driven translocation. Of these, six autotransporter proteins, which constitute the majority of protein mass of OMVs, were associated with Type V secretion system. In addition, other putative virulence factor proteins with functional domains, including FadA, MORN2 and YadA-like domain, were identified with multiple exposed epitope sites as determined by in silico analysis. Altogether, the non-replicative OMVs of F. nucleatum contain multiple antigenic virulence factors that may play important roles in the design and development of vaccines against F. nucleatum. SIGNIFICANCE: Fusobacterium nulceatum has been proved playing significant role in colorectal carcinogenesis. Outer membrane vesicles are nanoparticles that naturally secreted by Gram-negative bacterial containing various antigenic components, which provides new insight in vaccine development. Understanding the constituents of F. nucleatum OMVs will provide fundamental information and potential strategies for OMV-based F. nucleatum vaccines design. Based on our knowledge this is the first proteomic study of OMVs from F. nucleatum.

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/ .

Comparative Analysis of TM and Cytoplasmic β-barrel Conformations Using Joint Descriptor

Macroscopic descriptors have become valuable as coarse-grained features of complex proteins and are complementary to microscopic descriptors. Proteins macroscopic geometric features provide effective clues in the quantification of distant similarity and close dissimilarity searches for structural comparisons. In this study, we performed a systematic comparison of β-barrels, one of the important classes of protein folds in various transmembrane (TM) proteins against cytoplasmic barrels to estimate the conformational features using a joint-based descriptor. The approach uses joint coordinates and dihedral angles (β and γ) based on the β-strand joints and loops to determine the arrangements and propensities at the local and global levels. We then confirmed that there is a clear preference in the overall β and γ distribution, arrangements of β-strands and loops, signature patterns, and the number of strand effects between TM and cytoplasmic β-barrel geometries. As a robust and simple approach, we determine that the joint-based descriptor could provide a reliable static structural comparison aimed at macroscopic level between complex protein conformations.

Efficient computation of transfer free energies of amino acids in beta-barrel membrane proteins

Motivation

Transmembrane beta-barrel proteins (TMBs) serve a multitude of essential cellular functions in Gram-negative bacteria, mitochondria and chloroplasts. Transfer free energies (TFEs) of residues in the transmembrane (TM) region provides fundamental quantifications of thermodynamic stabilities of TMBs, which are important for the folding and the membrane insertion processes, and may help in understanding the structure-function relationship. However, experimental measurement of TFEs of TMBs is challenging. Although a recent computational method can be used to calculate TFEs, the results of which are in excellent agreement with experimentally measured values, this method does not scale up, and is limited to small TMBs.

Results

We have developed an approximation method that calculates TFEs of TM residues in TMBs accurately, with which depth-dependent transfer free energy profiles can be derived. Our results are in excellent agreement with experimental measurements. This method is efficient and applicable to all bacterial TMBs regardless of the size of the protein.

Availability and Implementation

An online webserver is available at http://tanto.bioe.uic.edu/tmb-tfe .

Contact

: jliang@uic.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

"Candidatus Paraporphyromonas polyenzymogenes" encodes multi-modular cellulases linked to the type IX secretion system

BACKGROUND

In nature, obligate herbivorous ruminants have a close symbiotic relationship with their gastrointestinal microbiome, which proficiently deconstructs plant biomass. Despite decades of research, lignocellulose degradation in the rumen has thus far been attributed to a limited number of culturable microorganisms. Here, we combine meta-omics and enzymology to identify and describe a novel Bacteroidetes family ("Candidatus MH11") composed entirely of uncultivated strains that are predominant in ruminants and only distantly related to previously characterized taxa.

RESULTS

The first metabolic reconstruction of Ca. MH11-affiliated genome bins, with a particular focus on the provisionally named "Candidatus Paraporphyromonas polyenzymogenes", illustrated their capacity to degrade various lignocellulosic substrates via comprehensive inventories of singular and multi-modular carbohydrate active enzymes (CAZymes). Closer examination revealed an absence of archetypical polysaccharide utilization loci found in human gut microbiota. Instead, we identified many multi-modular CAZymes putatively secreted via the Bacteroidetes-specific type IX secretion system (T9SS). This included cellulases with two or more catalytic domains, which are modular arrangements that are unique to Bacteroidetes species studied to date. Core metabolic proteins from Ca. P. polyenzymogenes were detected in metaproteomic data and were enriched in rumen-incubated plant biomass, indicating that active saccharification and fermentation of complex carbohydrates could be assigned to members of this novel family. Biochemical analysis of selected Ca. P. polyenzymogenes CAZymes further iterated the cellulolytic activity of this hitherto uncultured bacterium towards linear polymers, such as amorphous and crystalline cellulose as well as mixed linkage β-glucans.

CONCLUSION

We propose that Ca. P. polyenzymogene genotypes and other Ca. MH11 members actively degrade plant biomass in the rumen of cows, sheep and most likely other ruminants, utilizing singular and multi-domain catalytic CAZymes secreted through the T9SS. The discovery of a prominent role of multi-modular cellulases in the Gram-negative Bacteroidetes, together with similar findings for Gram-positive cellulosomal bacteria (Ruminococcus flavefaciens) and anaerobic fungi (Orpinomyces sp.), suggests that complex enzymes are essential and have evolved within all major cellulolytic dominions inherent to the rumen.