Prediction of partial membrane protein topologies using a consensus approach

Predicting Alpha Helical Transmembrane Proteins Using HMMs

Alpha helical transmembrane (TM) proteins constitute an important structural class of membrane proteins involved in a wide variety of cellular functions. The prediction of their transmembrane topology, as well as their discrimination in newly sequenced genomes, is of great importance for the elucidation of their structure and function. Several methods have been applied for the prediction of the transmembrane segments and the topology of alpha helical transmembrane proteins utilizing different algorithmic techniques. Hidden Markov Models (HMMs) have been efficiently used in the development of several computational methods used for this task. In this chapter we give a brief review of different available prediction methods for alpha helical transmembrane proteins pointing out sequence and structural features that should be incorporated in a prediction method. We then describe the procedure of the design and development of a Hidden Markov Model capable of predicting the transmembrane alpha helices in proteins and discriminating them from globular proteins.

Highly diversified expansions shaped the evolution of membrane bound proteins in metazoans

The dramatic increase in membrane proteome complexity is arguably one of the most pivotal evolutionary events that underpins the origin of multicellular animals. However, the origin of a significant number of membrane families involved in metazoan development has not been clarified. In this study, we have manually curated the membrane proteomes of 22 metazoan and 2 unicellular holozoan species. We identify 123,014 membrane proteins in these 24 eukaryotic species and classify 86% of the dataset. We determine 604 functional clusters that are present from the last holozoan common ancestor (LHCA) through many metazoan species. Intriguingly, we show that more than 70% of the metazoan membrane protein families have a premetazoan origin. The data show that enzymes are more highly represented in the LHCA and expand less than threefold throughout metazoan species; in contrast to receptors that are relatively few in the LHCA but expand nearly eight fold within metazoans. Expansions related to cell adhesion, communication, immune defence, and developmental processes are shown in conjunction with emerging biological systems, such as neuronal development, cytoskeleton organization, and the adaptive immune response. This study defines the possible LHCA membrane proteome and describes the fundamental functional clusters that underlie metazoan diversity and innovation.

Enquiry into the Topology of Plasma Membrane-Localized PIN Auxin Transport Components

Auxin directs plant ontogenesis via differential accumulation within tissues depending largely on the activity of PIN proteins that mediate auxin efflux from cells and its directional cell-to-cell transport. Regardless of the developmental importance of PINs, the structure of these transporters is poorly characterized. Here, we present experimental data concerning protein topology of plasma membrane-localized PINs. Utilizing approaches based on pH-dependent quenching of fluorescent reporters combined with immunolocalization techniques, we mapped the membrane topology of PINs and further cross-validated our results using available topology modeling software. We delineated the topology of PIN1 with two transmembrane (TM) bundles of five α-helices linked by a large intracellular loop and a C-terminus positioned outside the cytoplasm. Using constraints derived from our experimental data, we also provide an updated position of helical regions generating a verisimilitude model of PIN1. Since the canonical long PINs show a high degree of conservation in TM domains and auxin transport capacity has been demonstrated for Arabidopsis representatives of this group, this empirically enhanced topological model of PIN1 will be an important starting point for further studies on PIN structure-function relationships. In addition, we have established protocols that can be used to probe the topology of other plasma membrane proteins in plants.

HMMpTM: improving transmembrane protein topology prediction using phosphorylation and glycosylation site prediction

During the last two decades a large number of computational methods have been developed for predicting transmembrane protein topology. Current predictors rely on topogenic signals in the protein sequence, such as the distribution of positively charged residues in extra-membrane loops and the existence of N-terminal signals. However, phosphorylation and glycosylation are post-translational modifications (PTMs) that occur in a compartment-specific manner and therefore the presence of a phosphorylation or glycosylation site in a transmembrane protein provides topological information. We examine the combination of phosphorylation and glycosylation site prediction with transmembrane protein topology prediction. We report the development of a Hidden Markov Model based method, capable of predicting the topology of transmembrane proteins and the existence of kinase specific phosphorylation and N/O-linked glycosylation sites along the protein sequence. Our method integrates a novel feature in transmembrane protein topology prediction, which results in improved performance for topology prediction and reliable prediction of phosphorylation and glycosylation sites. The method is freely available at http://bioinformatics.biol.uoa.gr/HMMpTM.

Topological mapping methods for α-helical bacterial membrane proteins--an update and a guide

Integral membrane proteins with α-helical transmembrane segments (TMS) are known to play important and diverse roles in prokaryotic cell physiology. The net hydrophobicity of TMS directly corresponds to the observed difficulties in expressing and purifying these proteins, let alone producing sufficient yields for structural studies using two-/three-dimensional (2D/3D) crystallographic or nuclear magnetic resonance methods. To gain insight into the function of these integral membrane proteins, topological mapping has become an important tool to identify exposed and membrane-embedded protein domains. This approach has led to the discovery of protein tracts of functional importance and to the proposition of novel mechanistic hypotheses. In this review, we synthesize the various methods available for topological mapping of α-helical integral membrane proteins to provide investigators with a comprehensive reference for choosing techniques suited to their particular topological queries and available resources.

Wzx flippase-mediated membrane translocation of sugar polymer precursors in bacteria

Bacterial cell surface polysaccharides confer resistance to external stress and promote survival in biotic and abiotic environments. Glycan assembly often occurs at the periplasmic leaflet of the inner membrane (IM) from undecaprenyl pyrophosphate (UndPP)-linked polysaccharide units via the Wzx/Wzy-dependent pathway. Wzx is an integral IM protein found in Gram-negative and Gram-positive bacteria that mediates IM translocation of UndPP-linked sugar repeats from the cytoplasmic to the periplasmic leaflet; interaction of Wzx with other assembly proteins is indirectly supported by genetic evidence. Topological mapping has indicated 12 α-helical transmembrane segments (TMS), with the number of charged TMS residues fluctuating based on the mapping method used. A novel Wzx tertiary structure model has been built, allowing for substrate-binding or energy-coupling roles to be proposed for functionally important charged and aromatic TMS residues. It has also led to a proposed antiport-like mechanism of Wzx function. Exquisite substrate specificity of Wzx proteins was recently revealed in distinguishing between UndPP-linked substrates with identical main-chain sugar repeats, but differing in the chemical composition of a terminal sugar side-branch cap. The objective of this review is to synthesize the most up-to-date knowledge concerning Wzx flippases and to provide perspective for future investigations in this burgeoning field.

Revised transmembrane orientation of the NADH:quinone oxidoreductase subunit NuoA

NuoA is a small membrane spanning subunit of respiratory chain NADH:quinone oxidoreductase (complex I). Unlike the other complex I core protein subunits, the NuoA protein has no known homologue in other enzyme systems. The transmembrane orientation of NuoA cannot be unambiguously predicted, due to the small size of the polypeptide and the varying distribution of charged amino acid residues in NuoA from different organisms. Novel analyses of NuoA from Escherichia coli complex I expressed as fusion proteins to cytochrome c and to alkaline phosphatase demonstrated that the c-terminal end of the polypeptide is localized in the bacterial cytoplasm, in contrast to what was previously reported for the homologous NQO7 subunit from Paracoccus denitrificans complex I.

A protein oxidase catalysing disulfide bond formation is localized to the chloroplast thylakoids

In chloroplasts, thiol/disulfide-redox-regulated proteins have been linked to numerous metabolic pathways. However, the biochemical system for disulfide bond formation in chloroplasts remains undetermined. In the present study, we characterized an oxidoreductase, AtVKOR-DsbA, encoded by the gene At4g35760 as a potential disulfide bond oxidant in Arabidopsis. The gene product contains two distinct domains: an integral membrane domain homologous to the catalytic subunit of mammalian vitamin K epoxide reductase (VKOR) and a soluble DsbA-like domain. Transient expression of green fluorescent protein fusion in Arabidopsis protoplasts indicated that AtVKOR-DsbA is located in the chloroplast. The first 45 amino acids from the N-terminus were found to act as a transit peptide targeting the protein to the chloroplast. An immunoblot assay of chloroplast fractions revealed that AtVKOR-DsbA was localized in the thylakoid. A motility complementation assay showed that the full-length of AtVKOR-DsbA, if lacking its transit peptide, could catalyze the formation of disulfide bonds. Among the 10 cysteine residues present in the mature protein, eight cysteines (four in the AtVKOR domain and four in the AtDsbA domain) were found to be essential for promoting disulfide bond formation. The topological arrangement of AtVKOR-DsbA was assayed using alkaline phosphatase sandwich fusions. From these results, we developed a possible topology model of AtVKOR-DsbA in chloroplasts. We propose that the integral membrane domain of AtVKOR-DsbA contains four transmembrane helices, and that both termini and the cysteines involved in catalyzing the formation of disulfide bonds face the oxidative thylakoid lumen. These studies may help to resolve some of the issues surrounding the structure and function of AtVKOR-DsbA in Arabidopsis chloroplasts.

ExTopoDB: a database of experimentally derived topological models of transmembrane proteins

ExTopoDB is a publicly accessible database of experimentally derived topological models of transmembrane proteins. It contains information collected from studies in the literature that report the use of biochemical methods for the determination of the topology of α-helical transmembrane proteins. Transmembrane protein topology is highly important in order to understand their function and ExTopoDB provides an up to date, complete and comprehensive dataset of experimentally determined topologies of α-helical transmembrane proteins. Topological information is combined with transmembrane topology prediction resulting in more reliable topological models.

AVAILABILITY

http://bioinformatics.biol.uoa.gr/ExTopoDB.

Bioinformatic approaches for the structure and function of membrane proteins

Membrane proteins play important roles in the biology of the cell, including intercellular communication and molecular transport. Their well-established importance notwithstanding, the high-resolution structures of membrane proteins remain elusive due to difficulties in protein expression, purification and crystallization. Thus, accurate prediction of membrane protein topology can increase the understanding of membrane protein function. Here, we provide a brief review of the diverse computational methods for predicting membrane protein structure and function, including recent progress and essential bioinformatics tools. Our hope is that this review will be instructive to users studying membrane protein biology in their choice of appropriate bioinformatics methods.

Quantitative membrane proteomics applying narrow range peptide isoelectric focusing for studies of small cell lung cancer resistance mechanisms

Drug resistance is often associated with upregulation of membrane-associated drug-efflux systems, and thus global membrane proteomics methods are valuable tools in the search for novel components of drug resistance phenotypes. Herein we have compared the microsomal proteome from the lung cancer cell line H69 and its isogenic Doxorubicin-resistant subcell line H69AR. The method used includes microsome preparation, iTRAQ labeling followed by narrow range peptide IEF in an immobilized pH-gradient (IPG-IEF) and LC-MS/MS analysis. We demonstrate that the microsomal preparation and iTRAQ labeling is reproducible regarding protein content and composition. The rationale using narrow range peptide IPG-IEF separation is demonstrated by its ability to: (i) lowering the complexity of the sample by two-thirds while keeping high proteome coverage (96%), (ii) providing high separation efficiency, and (iii) allowing for peptide validation and possibly identifications of post-transcriptional modifications. After analyzing one-fifth of the IEF fractions (effective pH range of 4.0-4.5), a total of 3704 proteins were identified, among which 527 were predicted to be membrane proteins. One of the proteins found to be differentially expressed was Serca 2, a calcium pump located in the ER membrane that potentially could result in changes of apoptotic response toward Doxorubicin.

Transmembrane topology of the Acr3 family arsenite transporter from Bacillus subtilis

The transmembrane topology of the Acr3 family arsenite transporter Acr3 from Bacillus subtilis was analysed experimentally using translational fusions with alkaline phosphatase and green fluorescent protein and in silico by topology modelling. Initial topology prediction resulted in two models with 9 and 10 TM helices respectively. 32 fusion constructs were made between truncated forms of acr3 and the reporter genes at 17 different sites throughout the acr3 sequence to discriminate between these models. Nine strong reporter protein signals provided information about the majority of the locations of the cytoplasmic and extracellular loops of Acr3 and showed that both the N- and the C-termini are located in the cytoplasm. Two ambiguous data points indicated the possibility of an alternative 8 helix topology. This possibility was investigated using another 10 fusion variants, but no experimental support for the 8 TM topology was obtained. We therefore conclude that Acr3 has 10 transmembrane helices. Overall, the loops which connect the membrane spanning segments are short, with cytoplasmic loops being somewhat longer than the extracellular loops. The study provides the first ever experimentally derived structural information on a protein of the Acr3 family which constitutes one of the largest classes of arsenite transporters.

A chlorophyll-deficient rice mutant with impaired chlorophyllide esterification in chlorophyll biosynthesis

Chlorophyll (Chl) synthase catalyzes esterification of chlorophyllide to complete the last step of Chl biosynthesis. Although the Chl synthases and the corresponding genes from various organisms have been well characterized, Chl synthase mutants have not yet been reported in higher plants. In this study, a rice (Oryza Sativa) Chl-deficient mutant, yellow-green leaf1 (ygl1), was isolated, which showed yellow-green leaves in young plants with decreased Chl synthesis, increased level of tetrapyrrole intermediates, and delayed chloroplast development. Genetic analysis demonstrated that the phenotype of ygl1 was caused by a recessive mutation in a nuclear gene. The ygl1 locus was mapped to chromosome 5 and isolated by map-based cloning. Sequence analysis revealed that it encodes the Chl synthase and its identity was verified by transgenic complementation. A missense mutation was found in a highly conserved residue of YGL1 in the ygl1 mutant, resulting in reduction of the enzymatic activity. YGL1 is constitutively expressed in all tissues, and its expression is not significantly affected in the ygl1 mutant. Interestingly, the mRNA expression of the cab1R gene encoding the Chl a/b-binding protein was severely suppressed in the ygl1 mutant. Moreover, the expression of some nuclear genes associated with Chl biosynthesis or chloroplast development was also affected in ygl1 seedlings. These results indicate that the expression of nuclear genes encoding various chloroplast proteins might be feedback regulated by the level of Chl or Chl precursors.

Improving the accuracy of transmembrane protein topology prediction using evolutionary information

MOTIVATION

Many important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell-cell communication, cell recognition and cell adhesion are mediated by membrane proteins. Unfortunately, as these proteins are not water soluble, it is extremely hard to experimentally determine their structure. Therefore, improved methods for predicting the structure of these proteins are vital in biological research. In order to improve transmembrane topology prediction, we evaluate the combined use of both integrated signal peptide prediction and evolutionary information in a single algorithm.

RESULTS

A new method (MEMSAT3) for predicting transmembrane protein topology from sequence profiles is described and benchmarked with full cross-validation on a standard data set of 184 transmembrane proteins. The method is found to predict both the correct topology and the locations of transmembrane segments for 80% of the test set. This compares with accuracies of 62-72% for other popular methods on the same benchmark. By using a second neural network specifically to discriminate transmembrane from globular proteins, a very low overall false positive rate (0.5%) can also be achieved in detecting transmembrane proteins.

AVAILABILITY

An implementation of the described method is available both as a web server (http://www.psipred.net) and as downloadable source code from http://bioinf.cs.ucl.ac.uk/memsat. Both the server and source code files are free to non-commercial users. Benchmark and training data are also available from http://bioinf.cs.ucl.ac.uk/memsat.

EMD: an ensemble algorithm for discovering regulatory motifs in DNA sequences

Background

Understanding gene regulatory networks has become one of the central research problems in bioinformatics. More than thirty algorithms have been proposed to identify DNA regulatory sites during the past thirty years. However, the prediction accuracy of these algorithms is still quite low. Ensemble algorithms have emerged as an effective strategy in bioinformatics for improving the prediction accuracy by exploiting the synergetic prediction capability of multiple algorithms.

Results

We proposed a novel clustering-based ensemble algorithm named EMD for de novo motif discovery by combining multiple predictions from multiple runs of one or more base component algorithms. The ensemble approach is applied to the motif discovery problem for the first time. The algorithm is tested on a benchmark dataset generated from E. coli RegulonDB. The EMD algorithm has achieved 22.4% improvement in terms of the nucleotide level prediction accuracy over the best stand-alone component algorithm. The advantage of the EMD algorithm is more significant for shorter input sequences, but most importantly, it always outperforms or at least stays at the same performance level of the stand-alone component algorithms even for longer sequences.

Conclusion

We proposed an ensemble approach for the motif discovery problem by taking advantage of the availability of a large number of motif discovery programs. We have shown that the ensemble approach is an effective strategy for improving both sensitivity and specificity, thus the accuracy of the prediction. The advantage of the EMD algorithm is its flexibility in the sense that a new powerful algorithm can be easily added to the system.

Towards genome-scale structure prediction for transmembrane proteins

In this paper we briefly review some of the recent progress made by ourselves and others in developing methods for predicting the structures of transmembrane proteins from amino acid sequence. Transmembrane proteins are an important class of proteins involved in many diverse biological functions, many of which have great impact in terms of disease mechanism and drug discovery. Despite their biological importance, it has proven very difficult to solve the structures of these proteins by experimental techniques, and so there is a great deal of pressure to develop effective methods for predicting their structure. The methods we discuss range from methods for transmembrane topology prediction to new methods for low resolution folding simulations in a knowledge-based force field. This potential is designed to reproduce the properties of the lipid bilayer. Our eventual aim is to apply these methods in tandem so that useful three-dimensional models can be built for a large fraction of the transmembrane protein domains in whole proteomes.

Transmembrane domain prediction and consensus sequence identification of the oligopeptide transport family

Few polytopic membrane proteins have had their topology determined experimentally. Often, researchers turn to an algorithm to predict where the transmembrane domains might lie. Here we use a consensus method, using six different transmembrane domain prediction algorithms on six members of the oligopeptide transport family, all of which have been experimentally characterized. PSI-BLAST results indicate that the six chosen oligopeptide transport family members are distributed throughout most branches of the phylogram, suggesting that these members represent a broad view of the oligopeptide transport family. We combined the prediction algorithms with a multiple sequence alignment, and consensus transmembrane domains were assigned not only based on algorithmic output, but also based on conserved familial motifs found by analysis of the PSI-BLAST results. The consensus method combined with the "charge-difference rule" yields a model topology for the family containing 12 transmembrane domains with the N- and C-termini facing extracellular.

Structural insights into the function of human caveolin 1

Caveolin-1 (Cav-1) is emerging as the central protein controlling caveolae formation, caveolae trafficking, and cellular signalling. In particular, it is known that Cav-1 interacts and modulates the activity of several signalling proteins through the so-called caveolin scaffolding domain. In this paper, we used a bioinformatics approach to assess the validity of some long-standing structural features of Cav-1. We could confirm the existence of a membrane spanning region of Cav-1 and highlight an interesting pattern of palmitoylated cysteine residues explaining the structural features of the Cav-1 C-terminal region. Moreover, the scaffolding domain is predicted to have a different structure than previously reported.

Improved membrane protein topology prediction by domain assignments

Topology predictions for integral membrane proteins can be substantially improved if parts of the protein can be constrained to a given in/out location relative to the membrane using experimental data or other information. Here, we have identified a set of 367 domains in the SMART database that, when found in soluble proteins, have compartment-specific localization of a kind relevant for membrane protein topology prediction. Using these domains as prediction constraints, we are able to provide high-quality topology models for 11% of the membrane proteins extracted from 38 eukaryotic genomes. Two-thirds of these proteins are single spanning, a group of proteins for which current topology prediction methods perform particularly poorly.

Dynamic Membrane Topology of the Escherichia coli β-Glucoside Transporter BglF

The Escherichia coli BglF protein, a permease of the phosphoenolpyruvate-dependent phosphotransferase system, catalyzes transport and phosphorylation of beta-glucosides. In addition, BglF regulates bgl operon expression by controlling the activity of the transcriptional regulator BglG via reversible phosphorylation. BglF is composed of three domains; one is hydrophobic, which presumably forms the sugar translocation channel. We studied the topology of this domain by Cys-replacement mutagenesis and chemical modification by thiol reagents. Most Cys substitutions were well tolerated, as demonstrated by the ability of the mutant proteins to catalyze BglF activities. Our results suggest that the membrane domain contains eight transmembrane helices and an alleged cytoplasmic loop that contains two additional helices. The latter region forms a dynamic structure, as evidenced by the alternation of residues near its ends between faced-in and faced-out states. We suggest that this region, together with the two transmembrane helices encompassing it, forms the sugar translocation channel. BglF periplasmic loops are close to the membrane, the first being a reentrant loop. This is the first systematic topological study carried out with an intact phosphotransferase system permease and the first demonstration of a reentrant loop in this group of proteins.

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.

Reliability measures for membrane protein topology prediction algorithms

We have developed reliability scores for five widely used membrane protein topology prediction methods, and have applied them both on a test set of 92 bacterial plasma membrane proteins with experimentally determined topologies and on all predicted helix bundle membrane proteins in three fully sequenced genomes: Escherichia coli, Saccharomyces cerevisiae and Caenorhabditis elegans. We show that the reliability scores work well for the TMHMM and MEMSAT methods, and that they allow the probability that the predicted topology is correct to be estimated for any protein. We further show that the available test set is biased towards high-scoring proteins when compared to the genome-wide data sets, and provide estimates for the expected prediction accuracy of TMHMM across the three genomes. Finally, we show that the performance of TMHMM is considerably better when limited experimental information (such as the in/out location of a protein's C terminus) is available, and estimate that at least ten percentage points in overall accuracy in whole-genome predictions can be gained in this way.