Comprehensive analysis of transmembrane topologies in prokaryotic genomes

A proteome-wide screen of Campylobacter jejuni using protein microarrays identifies novel and conformational antigens

Campylobacter jejuni (C. jejuni) is a foodborne intestinal pathogen and major cause of gastroenteritis worldwide. C. jejuni proteins that are immunogenic have been sought for their potential use in the development of biomarkers, diagnostic assays, or subunit vaccines for humans or livestock. To identify new immunogenic C. jejuni proteins, we used a native protein microarray approach. A protein chip, with over 1400 individually purified GST-tagged C. jejuni proteins, representing over 86% of the proteome, was constructed to screen for antibody titers present in test sera raised against whole C. jejuni cells. Dual detection of GST signals was incorporated as a way of normalizing the variation of protein concentrations contributing to the antibody staining intensities. We detected strong signals to 102 C. jejuni antigens. In addition to antigens recognized by antiserum raised against C. jejuni, parallel experiments were conducted to identify antigens cross-reactive to antiserum raised against various serotypes of E. coli or Salmonella or to healthy human sera. This led to the identification of 34 antigens specifically recognized by the C. jejuni antiserum, only four of which were previously known. The chip approach also allowed identification of conformational antigens. We demonstrate in the case of Cj1621 that antigen signals are lost to denaturing conditions commonly used in other approaches to identify immunogens. Antigens identified in this study include those possessing sequence features indicative of cell surface localization, as well as those that do not. Together, our results indicate that the unbiased chip-based screen can help reveal the full repertoire of host antibodies against microbial proteomes.

RepEx: A web server to extract sequence repeats from protein and DNA sequences

Evolution builds up new genetic material from existing ones, not in random, but in highly ordered and eloquent patterns. Most of these sequence repeats are revelatory of valuable information contributing to areas of disease research and function of macromolecules, to name a few. In the age of next generation genome sequencing, rapid and efficient extraction of all unbiased sequence repeats from macromolecules is the need of the hour. In view of this reckoning, an online web-based computing server, RepEx, has been developed to extract and display all possible repeats for DNA and protein sequences. Apart from exact or identical repeats, the server has been designed adeptly to identify and extract degenerate, inverted, everted and mirror repeats from both DNA and protein sequences. The server has striking output displays, featuring interactive graphs and comprehensive output files. In addition, RepEx has been accoutered with an easy-to-use interface and search filters to facilitate a user-defined query or search and is freely available and accessible via the World Wide Web at http://bioserver2.physics.iisc.ac.in/RepEx/.

Signal peptide discrimination and cleavage site identification using SVM and NN

About 15% of all proteins in a genome contain a signal peptide (SP) sequence, at the N-terminus, that targets the protein to intracellular secretory pathways. Once the protein is targeted correctly in the cell, the SP is cleaved, releasing the mature protein. Accurate prediction of the presence of these short amino-acid SP chains is crucial for modelling the topology of membrane proteins, since SP sequences can be confused with transmembrane domains due to similar composition of hydrophobic amino acids. This paper presents a cascaded Support Vector Machine (SVM)-Neural Network (NN) classification methodology for SP discrimination and cleavage site identification. The proposed method utilises a dual phase classification approach using SVM as a primary classifier to discriminate SP sequences from Non-SP. The methodology further employs NNs to predict the most suitable cleavage site candidates. In phase one, a SVM classification utilises hydrophobic propensities as a primary feature vector extraction using symmetric sliding window amino-acid sequence analysis for discrimination of SP and Non-SP. In phase two, a NN classification uses asymmetric sliding window sequence analysis for prediction of cleavage site identification. The proposed SVM-NN method was tested using Uni-Prot non-redundant datasets of eukaryotic and prokaryotic proteins with SP and Non-SP N-termini. Computer simulation results demonstrate an overall accuracy of 0.90 for SP and Non-SP discrimination based on Matthews Correlation Coefficient (MCC) tests using SVM. For SP cleavage site prediction, the overall accuracy is 91.5% based on cross-validation tests using the novel SVM-NN model.

Classification of α-helical membrane proteins using predicted helix architectures

Despite significant methodological advances in protein structure determination high-resolution structures of membrane proteins are still rare, leaving sequence-based predictions as the only option for exploring the structural variability of membrane proteins at large scale. Here, a new structural classification approach for α-helical membrane proteins is introduced based on the similarity of predicted helix interaction patterns. Its application to proteins with known 3D structure showed that it is able to reliably detect structurally similar proteins even in the absence of any sequence similarity, reproducing the SCOP and CATH classifications with a sensitivity of 65% at a specificity of 90%. We applied the new approach to enhance our comprehensive structural classification of α-helical membrane proteins (CAMPS), which is primarily based on sequence and topology similarity, in order to find protein clusters that describe the same fold in the absence of sequence similarity. The total of 151 helix architectures were delineated for proteins with more than four transmembrane segments. Interestingly, we observed that proteins with 8 and more transmembrane helices correspond to fewer different architectures than proteins with up to 7 helices, suggesting that in large membrane proteins the evolutionary tendency to re-use already available folds is more pronounced.

Tandem application of cationic colloidal silica and Triton X-114 for plasma membrane protein isolation and purification: towards developing an MDCK protein database

Plasma membrane (PM) proteins are attractive therapeutic targets because of their accessibility to drugs. Although genes encoding PM proteins represent 20-30% of eukaryotic genomes, a detailed characterisation of their encoded proteins is underrepresented, due, to their low copy number and the inherent difficulties in their isolation and purification as a consequence of their high hydrophobicity. We describe here a strategy that combines two orthogonal methods to isolate and purify PM proteins from Madin Darby canine kidney (MDCK) cells. In this two-step method, we first used cationic colloidal silica (CCS) to isolate adherent (Ad) and non-adherent (nAd) PM fractions, and then subjected each fraction to Triton X-114 (TX-114) phase partitioning to further enrich for hydrophobic proteins. While CCS alone identified 255/757 (34%) membrane proteins, CCS/TX-114 in combination yielded 453/745 (61%). Strikingly, of those proteins unique to CCS/TX-114, 277/393 (70%) had membrane annotation. Further characterisation of the CCS/TX-114 data set using Uniprot and transmembrane hidden Markov model revealed that 306/745 (41%) contained one or more transmembrane domains (TMDs), including proteins with 25 and 17 TMDs. Of the remaining proteins in the data set, 69/439 (16%) are known to contain lipid modifications. Of all membrane proteins identified, 93 had PM origin, including proteins that mediate cell adhesion, modulate transmembrane ion transport, and cell-cell communication. These studies reveal that the application of CCS to first isolate Ad and nAd PM fractions, followed by their detergent-phase TX-114 partitioning, to be a powerful method to isolate low-abundance PM proteins, and a useful adjunct for in-depth cell surface proteome analyses.

Establishment of a PF2D-MS/MS platform for rapid profiling and semiquantitative analysis of membrane protein biomarkers

Current proteome profiling techniques have identified relatively few mammalian membrane proteins despite their numerous important functions. To establish a standard throughput-potential profiling platform for membrane proteins, Triton X-100-solubilized rat liver microsomal proteins were separated on a 2-D separation system (2-D liquid phase fractionation (PF2D)) in two different pH ranges (4.0-8.5 and 7.0-10.5). This system produced 182 proteins with more than two transmembrane domain (TMD), including 16 TMDs with high confidence. Comparative 2-D liquid maps with high resolution and reproducibility have been constructed for liver microsome from the phenobarbital (PB) treated rats. PF2D was also found to be useful for the semiquantification of some representative cytochrome P450 family proteins (e.g., cytochrome P450 2B2) that were induced by PB treatment compared with untreated controls. Thus, the combination of both high-detection capacity and rapid preliminary semiquantification in a PF2D platform could become a standard system for the routine analysis of membrane proteins.

Inactivation of Lgt allows systematic characterization of lipoproteins from Listeria monocytogenes

Lipoprotein anchoring in bacteria is mediated by the prolipoprotein diacylglyceryl transferase (Lgt), which catalyzes the transfer of a diacylglyceryl moiety to the prospective N-terminal cysteine of the mature lipoprotein. Deletion of the lgt gene in the gram-positive pathogen Listeria monocytogenes (i) impairs intracellular growth of the bacterium in different eukaryotic cell lines and (ii) leads to increased release of lipoproteins into the culture supernatant. Comparative extracellular proteome analyses of the EGDe wild-type strain and the Delta lgt mutant provided systematic insight into the relative expression of lipoproteins. Twenty-six of the 68 predicted lipoproteins were specifically released into the extracellular proteome of the Delta lgt strain, and this proved that deletion of lgt is an excellent approach for experimental verification of listerial lipoproteins. Consequently, we generated Delta lgt Delta prfA double mutants to detect lipoproteins belonging to the main virulence regulon that is controlled by PrfA. Overall, we identified three lipoproteins whose extracellular levels are regulated and one lipoprotein that is posttranslationally modified depending on PrfA. It is noteworthy that in contrast to previous studies of Escherichia coli, we unambiguously demonstrated that lipidation by Lgt is not a prerequisite for activity of the lipoprotein-specific signal peptidase II (Lsp) in Listeria.

The ammonia channel protein AmtB from Escherichia coli is a polytopic membrane protein with a cleavable signal peptide

The Escherichia coli ammonia channel protein, AmtB, is a homotrimeric polytopic inner membrane protein in which each subunit has 11 transmembrane helices. We have shown that the structural gene amtB encodes a preprotein with a signal peptide that is cleaved off to produce a topology with the N-terminus in the periplasm and the C-terminus in the cytoplasm. Deletion of the signal peptide coding region results in significantly lower levels of AmtB accumulation in the membrane but modification of the signal peptidase cleavage site, leading to aberrant cleavage, does not prevent trimer formation and does not inactivate the protein. The presence of a signal peptide is apparently not a conserved feature of all prokaryotic Amt proteins. Comparison of predicted AmtB sequences suggests that while Amt proteins in Gram-negative organisms utilize a signal peptide, the homologous proteins in Gram-positive organisms do not.

LEGER: knowledge database and visualization tool for comparative genomics of pathogenic and non-pathogenic Listeria species

Listeria species are ubiquitous in the environment and often contaminate foods because they grow under conditions used for food preservation. Listeria monocytogenes, the human and animal pathogen, causes Listeriosis, an infection with a high mortality rate in risk groups such as immune-compromised individuals. Furthermore, L.monocytogenes is a model organism for the study of intracellular bacterial pathogens. The publication of its genome sequence and that of the non-pathogenic species Listeria innocua initiated numerous comparative studies and efforts to sequence all species comprising the genus. The Proteome database LEGER (http://leger2.gbf.de/cgi-bin/expLeger.pl) was developed to support functional genome analyses by combining information obtained by applying bioinformatics methods and from public databases to improve the original annotations. LEGER offers three unique key features: (i) it is the first comprehensive information system focusing on the functional assignment of genes and proteins; (ii) integrated visualization tools, KEGG pathway and Genome Viewer, alleviate the functional exploration of complex data; and (iii) LEGER presents results of systematic post-genome studies, thus facilitating analyses combining computational and experimental results. Moreover, LEGER provides an unpublished membrane proteome analysis of L.innocua and in total visualizes experimentally validated information about the subcellular localizations of 789 different listerial proteins.

Functional expression of eukaryotic membrane proteins in Lactococcus lactis

The overproduction of eukaryotic membrane proteins is a major impediment in their structural and functional characterization. Here we have used the nisin-inducible expression system of Lactococcus lactis for the overproduction of 11 mitochondrial transport proteins from yeast. They were expressed at high levels in a functional state in the cytoplasmic membrane. The results also show that the level of expression is influenced by the N-terminal regions of the transporters. Expression levels were improved >10-fold either by replacing or truncating these regions or by adding lactococcal signal peptides. The observed expression levels are now compatible with a realistic exploration of crystallization conditions. The lactococcal expression system may be used for the high-throughput functional characterization of eukaryotic membrane proteins and structural genomics.

A proteome-wide analysis of domain architectures of prokaryotic single-spanning transmembrane proteins

We performed a proteome-wide survey of the domain architectures in single-spanning transmembrane (TM) proteins (single-spannings) from 87 sequenced prokaryotic (Bacterial and Archaean) genomes by assigning Pfam domains to their N-tail and C-tail loops. Out of 14,625 single-spannings, 3,516 sequences have at least one domain assigned, and no domains were assigned to 7,850, with the remaining 3,259 with less reliable assignment. In the domain-assigned sequences, 3116 sequences are with at most two domains, and the other 400 sequences with more than two. The assigned domains distribute over 651 Pfam families, which account for 11.4% of the total Pfam-A families. Among the 651 families are mostly soluble-protein-originated ones, but only 21 families are unique to TM proteins. The occurrence frequency of the individual domain families follows a power-law, that is, 264 families occur only once, 106 just twice, and the families appeared more than 30 times are counted by only 39. It is found that the great majority of the sequences having one or two domains are of the type II topology with the C-tail loop containing domains on it. On the contrary, the N-tail loop of the same type topology seldom carries domains. Importantly, the assigned domains are always found on the tail loops longer than 60 residues, even for the small domains with less than 30 residues. There are still as many as 5,800 sequences without assigned domains in spite of having at least one long tail, on which no less than 1,000 novel domain families are expected most likely to lie concealed unknown yet. We also investigated the domain arrangement preference and the domain family combination patterns in 'singlets' (single-spannings with one assigned domain) and 'doublets' (with two domains).

YidC-dependent translocation of green fluorescence protein fused to the FliP cleavable signal peptide

Escherichia coli FliP is a rare bacterial polytopic membrane protein synthesized with a cleavable, highly hydrophobic signal peptide. More hydrophilic Tat-dependent or Sec-dependent signal peptide is functionally capable of substituting for the FliP signal peptide, but a signal anchor of inner membrane protein fails to do so. To assess the intrinsic characteristics of the FliP signal peptide in mediating protein translocation, we fused it to green fluorescence protein and observed that the translocation of the chimera (FliPss-GFP) was dependent of Ffh, SecA, SecY and SecD. In addition, we showed for the first time the involvement of YidC in protein translocation across the inner membrane.

Comparative analysis of amino acid distributions in integral membrane proteins from 107 genomes

We have performed a comparative analysis of amino acid distributions in predicted integral membrane proteins from a total of 107 genomes. A procedure for identification of membrane spanning helices was optimized on a homology-reduced data set of 170 multi-spanning membrane proteins with experimentally determined topologies. The optimized method was then used for extraction of highly reliable partial topologies from all predicted membrane proteins in each genome, and the average biases in amino acid distributions between loops on opposite sides of the membrane were calculated. The results strongly support the notion that a biased distribution of Lys and Arg residues between cytoplasmic and extra-cytoplasmic segments (the positive-inside rule) is present in most if not all organisms.

“LANESPECTOR”, a tool for membrane proteome profiling based on sodium dodecyl sulfate-polyacrylamide gel electrophoresis/liquid chromatography - tandem mass spectrometry analysis: Application toListeria monocytogenes membrane proteins

Proteomics is required to provide insight into any type of subproteome. While the workflow based on two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) can be applied for many subproteomes and comprises well-established strategies for data presentation and data analysis, the comprehensive investigation of membrane proteomes remains a challenging task. We present a number of procedures that provide an insight into such systems. We have established a novel protocol for the efficient preparation of membrane fractions, which is used here for the human pathogen Listeria monocytogenes that overcomes difficulties associated with ribosomes. Subsequently, we have used the combination of sodium dodecyl sulfate (SDS)-PAGE and liquid chromatography-tandem mass spectrometry for the characterization of the membrane proteome. Three hundred and one different membrane proteins could be identified, including 70 proteins that exhibited 2-15 transmembrane domains. However, a remarkably high ratio of proteins was detected in gel sections that were not in accordance with their expected migration behavior during SDS-PAGE. Protein identifications based on MASCOT significance criteria could be shown to be of high quality and therefore could not be the explanation of this observation. Consequently we have developed LaneSpector, a general visualization tool that allows the systematic comparison between apparent and calculated protein masses, which is routinely applicable to any high-throughput approach using a mass-dependent separation dimension prior to LC-MS/MS. The detailed presentation of the LaneSpector plot promotes the validation of the analytical process and might help to reveal relevant biological processes such as proteolysis or other post-translational modifications.

Comparative proteome analysis of secretory proteins from pathogenic and nonpathogenicListeriaspecies

Extracellular proteins of bacterial pathogens play a crucial role in the infection of the host. Here we present the first comprehensive validation of the secretory subproteome of the Gram positive pathogen Listeria monocytogenes using predictive bioinformatic and experimental proteomic approaches. The previous original signal peptide (SP) prediction (Glaser et al., Science 2001, 294, 849-852) has been greatly improved by an in-depth analysis using seven different bioinformatic tools. Subsequent careful classification of the resulting data gives a probability dependent annotation of 121 putatively secreted proteins of which 45 are novel. Complementary proteomic analysis using both two-dimensional gel electrophoresis/matrix assisted laser desorption/ionization mass spectrometry and high performance liquid chromatography/electrospray ionization-mass spectrometry has identified 105 proteins in the culture supernatant of L. monocytogenes. Among these, we were able to detect all the currently known virulence factors with an SP showing the importance of this subproteome and demonstrating the reliability of the techniques used. The comparison between the L. monocytogenes wildtype and the nonpathogenic species Listeria innocua was performed to reveal proteins probably involved in pathogenicity and/or the adaptation to their respective lifestyles. In addition to the eight known virulence factors, all of which have no orthologous genes in L. innocua, eight additional proteins have been identified that exhibit the typical key feature defining the known listerial virulence factors. Further significant differences between the two species are evident in the group of cell wall and secretory proteins that warrant further study. Our investigation clearly demonstrates that the major difference between the pathogenic and nonpathogenic species, noted in the comparative genome analysis, manifests itself strongest in the secretome.

Proteome-wide functional classification and identification of prokaryotic transmembrane proteins by transmembrane topology similarity comparison

We propose a new method for classifying and identifying transmembrane (TM) protein functions in proteome-scale by applying a single-linkage clustering method based on TM topology similarity, which is calculated simply from comparing the lengths of loop regions. In this study, we focused on 87 prokaryotic TM proteomes consisting of 31 proteobacteria, 22 gram-positive bacteria, 19 other bacteria, and 15 archaea. Prior to performing the clustering, we first categorized individual TM protein sequences as "known," "putative" (similar to "known" sequences), or "unknown" by using the homology search and the sequence similarity comparison against SWISS-PROT to assess the current status of the functional annotation of the TM proteomes based on sequence similarity only. More than three-quarters, that is, 75.7% of the TM protein sequences are functionally "unknown," with only 3.8% and 20.5% of them being classified as "known" and "putative," respectively. Using our clustering approach based on TM topology similarity, we succeeded in increasing the rate of TM protein sequences functionally classified and identified from 24.3% to 60.9%. Obtained clusters correspond well to functional superfamilies or families, and the functional classification and identification are successfully achieved by this approach. For example, in an obtained cluster of TM proteins with six TM segments, 109 sequences out of 119 sequences annotated as "ATP-binding cassette transporter" are properly included and 122 "unknown" sequences are also contained.

A cleavable signal peptide is required for the full function of the polytopic inner membrane protein FliP of Escherichia coli

FliP is a rare bacterial polytopic membrane protein synthesized with a cleavable highly hydrophobic signal peptide. It is essential for flagellum assembly and for bacterial motility. In this study, we assessed specificity of signal peptide for the FliP function. Like the wild type FliP, two altered FliPs with more hydrophilic Tat- or Sec-dependent signal peptides were both able to restore the motility of the DeltafliP mutant. Therefore, the Tat- and the Sec-dependent signal peptides seemed to be compatible with the FliP function. Moreover, deletion of the FliP signal peptide or replacing it with the transmembrane segment of MotA severely impaired the FliP function. Together these results showed that a cleavable signal peptide is required for the full function of FliP.

ConPred II: a consensus prediction method for obtaining transmembrane topology models with high reliability

ConPred II (http://bioinfo.si.hirosaki-u.ac.jp/~ConPred2/) is a server for the prediction of transmembrane (TM) topology [i.e. the number of TM segments (TMSs), TMS positions and N-tail location] based on a consensus approach by combining the results of several proposed methods. The ConPred II system is constructed from ConPred_elite and ConPred_all (previously named ConPred), proposed earlier by our group. The prediction accuracy of ConPred_elite is almost 100%, which is achieved by sacrificing the prediction coverage (20-30%). ConPred_all predicts TM topologies for all the input sequences with accuracies improved by up to 11% over individual proposed methods. In the ConPred II system, the TM topology prediction of input TM protein sequences is executed following a two-step process: (i) input sequences are first run through the ConPred_elite program; (ii) sequences for which ConPred_elite does not give the TM topology are delivered to the ConPred_all program for TM topology prediction. Users can get access to the ConPred II system automatically by submitting sequences to the server. The ConPred II server will return the predicted TM topology models and graphical representations of their contents (hydropathy plots, helical wheel diagrams of predicted TMSs and snake-like diagrams).

Internal gene duplication in the evolution of prokaryotic transmembrane proteins

We investigated the evolution of transmembrane (TM) topology by detecting partial sequence repeats in TM protein sequences and analyzing them in detail. A total of 377 sequences that seem to have evolved by internal gene duplication events were found among 38,124 predicted TM protein sequences (except for single-spannings) from 87 prokaryotic genomes. Various types of internal duplication patterns were identified in these sequences. The majority of them are diploid-type (including quasi-diploid-type) duplication in which a primordial protein sequence was duplicated internally to become an extant TM protein with twice as many TM segments as the primordial one, and the remaining ones are partial duplications including triploid-type. The diploid-type repeats are recognized in many 8-tms, 10-tms and 12-tms TM protein sequences, suggesting the diploid-type duplication was a principle mechanism in the evolutionary development of these types of TM proteins. The "positive-inside" rule is satisfied in whole sequences of both 10-tms and 8-tms TM proteins and in both halves of 10-tms proteins while not necessarily in the second half of 8-tms proteins, providing fit examples of "internal divergent topology evolution" likely occurred after a diploid-type internal duplication event. From analyzing the partial duplication patterns, several evolutionary pathways were recognized for 6-tms TM proteins, i.e. from primordial 2-tms, 3-tms and 4-tms TM proteins to extant 6-tms proteins. Similarly, the duplication pattern analysis revealed plausible evolution scenarios that 7-tms TM proteins have arisen from 3-tms, 4-tms and 5-tms TM protein precursors via partial internal gene duplications.

A combined transmembrane topology and signal peptide prediction method

An inherent problem in transmembrane protein topology prediction and signal peptide prediction is the high similarity between the hydrophobic regions of a transmembrane helix and that of a signal peptide, leading to cross-reaction between the two types of predictions. To improve predictions further, it is therefore important to make a predictor that aims to discriminate between the two classes. In addition, topology information can be gained when successfully predicting a signal peptide leading a transmembrane protein since it dictates that the N terminus of the mature protein must be on the non-cytoplasmic side of the membrane. Here, we present Phobius, a combined transmembrane protein topology and signal peptide predictor. The predictor is based on a hidden Markov model (HMM) that models the different sequence regions of a signal peptide and the different regions of a transmembrane protein in a series of interconnected states. Training was done on a newly assembled and curated dataset. Compared to TMHMM and SignalP, errors coming from cross-prediction between transmembrane segments and signal peptides were reduced substantially by Phobius. False classifications of signal peptides were reduced from 26.1% to 3.9% and false classifications of transmembrane helices were reduced from 19.0% to 7.7%. Phobius was applied to the proteomes of Homo sapiens and Escherichia coli. Here we also noted a drastic reduction of false classifications compared to TMHMM/SignalP, suggesting that Phobius is well suited for whole-genome annotation of signal peptides and transmembrane regions. The method is available at as well as at

ConPred_elite: a highly reliable approach to transmembrane topology predication

The function of transmembrane (TM) proteins is closely correlated to their TM topology; large quantities of highly reliable TM topology data are becoming increasingly required. We present a new consensus approach for TM topology prediction (ConPred_elite) that can predict the whole topology with accuracies of 0.98 for prokaryotic and 0.95 for eukaryotic proteins on a dataset of experimentally-characterized TM topologies. The predicted yield on the dataset is 30.4% for prokaryotic and 21.5% for eukaryotic proteins. Applying ConPred_elite to predicted TM proteins extracted from 29 prokaryotic and 10 eukaryotic proteomes, we obtained 3871 and 7271 highly reliable TM topologies (yields, 19.8 and 13.3%), respectively. The predicted TM topology data may contribute to further research into a comprehensive functional classification and identification of TM proteins based on information of the topology.