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Background: This study is motivated by the following three considerations: a) the physico-chemical properties of transmembrane (TM) proteins are distinctly different from those of globular proteins, necessitating the development of specialized structure prediction techniques, b) for many structural features no specialized predictors for TM proteins are available at all, and c) deep learning algorithms allow to automate the feature engineering process and thus facilitate the development of multi-target methods for predicting several protein properties at once. Results: We present AllesTM, an integrated tool to predict almost all structural features of transmembrane proteins that can be extracted from atomic coordinate data. It blends several machine learning algorithms: random forests and gradient boosting machines, convolutional neural networks in their original form as well as those enhanced by dilated convolutions and residual connections, and, finally, long short-term memory architectures. AllesTM outperforms other available methods in predicting residue depth in the membrane, flexibility, topology, relative solvent accessibility in its bound state, while in torsion angles, secondary structure and monomer relative solvent accessibility prediction it lags only slightly behind the currently leading technique SPOT-1D. High accuracy on a multitude of prediction targets and easy installation make AllesTM a one-stop shop for many typical problems in the structural bioinformatics of transmembrane proteins. Conclusions: In addition to presenting a highly accurate prediction method and eliminating the need to install and maintain many different software tools, we also provide a comprehensive overview of the impact of different machine learning algorithms and parameter choices on the prediction performance. AllesTM is freely available at https://github.com/phngs/allestm. [ABSTRACT FROM AUTHOR]

Background: To achieve synthetic control over how a cell responds to other cells or the extracellular environment, it is important to reliably engineer proteins that can traffic and span the plasma membrane. Using a modular approach to assemble proteins, we identified the minimum necessary components required to engineer such membrane-spanning proteins with predictable orientation in mammalian cells. Results: While a transmembrane domain (TM) fused to the N-terminus of a protein is sufficient to traffic it to the endoplasmic reticulum (ER), an additional signal peptidase cleavage site downstream of this TM enhanced sorting out of the ER. Next, a second TM in the synthetic protein helped anchor and accumulate the membrane-spanning protein on the plasma membrane. The orientation of the components of the synthetic protein were determined through measuring intracellular Ca2+ signaling using the R-GECO biosensor and through measuring extracellular quenching of yellow fluorescent protein variants by saturating acidic and salt conditions. Conclusions: This work forms the basis of engineering novel proteins that span the plasma membrane to potentially control intracellular responses to extracellular conditions. [ABSTRACT FROM AUTHOR]

Background: Viruses are the most abundant and genetically diverse biological entities on earth, yet the repertoire of viral proteins remains poorly explored. As the number of sequenced virus genomes grows into the thousands, and the number of viral proteins into the hundreds of thousands, we report a systematic computational analysis of the point of first-contact between viruses and their hosts, namely viral transmembrane (TM) proteins. Results: The complement of α-helical TM proteins in double-stranded DNA viruses infecting bacteria and archaea reveals large-scale trends that differ from those of their hosts. Viruses typically encode a substantially lower fraction of TM proteins than archaea or bacteria, with the notable exception of viruses with virions containing a lipid component such as a lipid envelope, internal lipid core, or inner membrane vesicle. Compared to bacteriophages, archaeal viruses are substantially enriched in membrane proteins. However, this feature is not always stable throughout the evolution of a viral lineage; for example, TM proteins are not part of the common heritage shared between Lipothrixviridae and Rudiviridae. In contrast to bacteria and archaea, viruses almost completely lack proteins with complicated membrane topologies composed of more than 4 TM segments, with the few detected exceptions being obvious cases of relatively recent horizontal transfer from the host. Conclusions: The dramatic differences between the membrane proteomes of cells and viruses stem from the fact that viruses do not depend on essential membranes for energy transformation, ion homeostasis, nutrient transport and signaling. [ABSTRACT FROM AUTHOR]

Background: VHL inactivation is the most established molecular characteristic of clear cell renal cell carcinoma (ccRCC), with only a few additional genes implicated in development of this kidney tumor. In recently published ccRCC gene expression meta-analysis study we identified a number of deregulated genes with limited information available concerning their biological role, represented by gene transcripts belonging to transmembrane proteins family (TMEMs). TMEMs are predicted to be components of cellular membranes, such as mitochondrial membranes, ER, lysosomes and Golgi apparatus. Interestingly, the function of majority of TMEMs remains unclear. Here, we analyzed expression of ten TMEM genes in the context of ccRCC progression and development, and characterized these proteins bioinformatically. Methods: The expression of ten TMEMs (RTP3, SLC35G2, TMEM30B, TMEM45A, TMEM45B, TMEM61, TMEM72, TMEM116, TMEM207 and TMEM213) was measured by qPCR. T-test, Pearson correlation, univariate and multivariate logistic and Cox regression were used in statistical analysis. The topology of studied proteins was predicted with Metaserver, together with PSORTII, Pfam and Localizome tools. Results: We observed significant deregulation of expression of 10 analyzed TMEMs in ccRCC tumors. Cluster analysis of expression data suggested the down-regulation of all tested TMEMs to be a descriptor of the most advanced tumors. Logistic and Cox regression potentially linked TMEM expression to clinical parameters such as: metastasis, Fuhrman grade and overall survival. Topology predictions classified majority of analyzed TMEMs as type 3 and type 1 transmembrane proteins, with predicted localization mainly in ER. Conclusions: The massive down-regulation of expression of TMEM family members suggests their importance in the pathogenesis of ccRCC and the bioinformatic analysis of TMEM topology implies a significant involvement of ER proteins in ccRCC pathology. [ABSTRACT FROM AUTHOR]

Background: The worldwide distributed hematophagous poultry red mite Dermanyssus gallinae (De Geer, 1778) is one of the most important pests of poultry. Even though 35 acaricide compounds are available, control of D. gallinae remains difficult due to acaricide resistances as well as food safety regulations. The current study was carried out to identify putative excretory/secretory (pES) proteins of D. gallinae since these proteins play an important role in the host-parasite interaction and therefore represent potential targets for the development of novel intervention strategies. Additionally, putative transmembrane proteins (pTM) of D. gallinae were analyzed as representatives of this protein group also serve as promising targets for new control strategies. Methods: D. gallinae pES and pTM protein prediction was based on putative protein sequences of whole transcriptome data which was parsed to different bioinformatical servers (SignalP, SecretomeP, TMHMM and TargetP). Subsequently, pES and pTM protein sequences were functionally annotated by different computational tools. Results: Computational analysis of the D. gallinae proteins identified 3,091 pES (5.6%) and 7,361 pTM proteins (13.4%). A significant proportion of pES proteins are considered to be involved in blood feeding and digestion such as salivary proteins, proteases, lipases and carbohydrases. The cysteine proteases cathepsin D and L as well as legumain, enzymes that cleave hemoglobin during blood digestion of the near related ticks, represented 6 of the top-30 BLASTP matches of the poultry red mite's secretome. Identified pTM proteins may be involved in many important biological processes including cell signaling, transport of membrane-impermeable molecules and cell recognition. Ninjurin-like proteins, whose functions in mites are still unknown, represent the most frequently occurring pTM. Conclusion: The current study is the first providing a mite's secretome as well as transmembranome and provides valuable insights into D. gallinae pES and pTM proteins operating in different metabolic pathways. Identifying a variety of molecules putatively involved in blood feeding may significantly contribute to the development of new therapeutic targets or vaccines against this poultry pest [ABSTRACT FROM AUTHOR]

Background: Almost half of the Caenorhabditis elegans genome encodes proteins with either a signal peptide or a transmembrane domain. Therefore a substantial fraction of the proteins are localized to membranes, reside in the secretory pathway or are secreted. While these proteins are of interest to a variety of different researchers ranging from developmental biologists to immunologists, most of secreted proteins have not been functionally characterized so far. Results: We grouped proteins containing a signal peptide or a transmembrane domain using various criteria including evolutionary origin, common domain organization and functional categories. We found that putative secreted proteins are enriched for small proteins and nematode-specific proteins. Many secreted proteins are predominantly expressed in specific life stages or in one of the two sexes suggesting stage- or sex-specific functions. More than a third of the putative secreted proteins are upregulated upon exposure to pathogens, indicating that a substantial fraction may have a role in immune response. Slightly more than half of the transmembrane proteins can be grouped into broad functional categories based on sequence similarity to proteins with known function. By far the largest groups are channels and transporters, various classes of enzymes and putative receptors with signaling function. Conclusion: Our analysis provides an overview of all putative secreted and transmembrane proteins in C. elegans. This can serve as a basis for selecting groups of proteins for large-scale functional analysis using reverse genetic approaches. [ABSTRACT FROM AUTHOR]