The abundance of short proteins in the mammalian proteome

Short proteins play key roles in cell signalling and other processes, but their abundance in the mammalian proteome is unknown. Current catalogues of mammalian proteins exhibit an artefactual discontinuity at a length of 100 aa, so that protein abundance peaks just above this length and falls off sharply below it. To clarify the abundance of short proteins, we identify proteins in the FANTOM collection of mouse cDNAs by analysing synonymous and nonsynonymous substitutions with the computer program CRITICA. This analysis confirms that there is no real discontinuity at length 100. Roughly 10% of mouse proteins are shorter than 100 aa, although the majority of these are variants of proteins longer than 100 aa. We identify many novel short proteins, including a dark matter'' subset containing ones that lack detectable homology to other known proteins. Translation assays confirm that some of these novel proteins can be translated and localised to the secretory pathway.

Development of a co-culture model of the human lungs for toxicity testing and identification of biomarkers of inhalation toxicity

The airway epithelium is the first point of contact in the lung for inhaled material, including infectious pathogens and particulate matter, and protects against toxicity from these substances by trapping and clearance via the mucociliary escalator, presence of a protective barrier with tight junctions and initiation of a local inflammatory response. The inflammatory response involves recruitment of phagocytic cells to neutralise and remove and invading materials and is oftern modelled using rodents. However, development of valid in vitro airway epithelial models is of great importance due to the restrictions on animal studies for cosmetic compound testing implicit in the 7th amendment to the European Union Cosmetics Directive. Further, rodent innate immune responses have fundamental differences to human. Pulmonary endothelial cells and leukocytes are also involved in the innate response initiated during pulmonary inflammation. Co-culture models of the airways, in particular where epithelial cells are cultured at air liquid interface with the presence of tight junctions and differentiated mucociliary cells, offer a solution to this problem. Ideally validated models will allow for detection of early biomarkers of response to exposure and investigation into inflammatory response during exposure. This thesis describes the approaches taken towards developing an in vitro epithelial/endothelial cell model of the human airways and identification biomarkers of response to exposure to xenobiotics. The model comprised normal human primary microvascular endothelial cells and the bronchial epithelial cell line BEAS-2B or normal human bronchial epithelial cells. BEAS-2B were chosen as their characterisation at air liquid interface is limited but they are robust in culture, thereby predicted to provide a more reliable test system. Proteomics analysis was undertaken on challenged cells to investigate biomarkers of exposure. BEAS-2B morphology was characterised at air liquid interface compared with normal human bronchial epithelial cells. The results indicate that BEAS-2B cells at an air liquid interface form tight junctions as shown by expression of the tight junction protein zonula occludens-1. To this author’s knowledge this is the first time this result has been reported. The inflammatory response of BEAS-2B (measured as secretion of the inflammatory mediators interleukin-8 and -6) air liquid interface mono-cultures to Escherichia coli lipopolysaccharide or particulate matter (fine and ultrafine titanium dioxide) was comparable to published data for epithelial cells. Cells were also exposed to polymers of “commercial interest” which were in the nanoparticle range (and referred to particles hereafter). BEAS-2B mono-cultures showed an increased secretion of inflammatory mediators after challenge. Inclusion of microvascular endothelial cells resulted in protection against LPS- and particle- induced epithelial toxicity, measured as cell viability and inflammatory response, indicating the importance of co-cultures for investigations into toxicity. Two-dimensional proteomic analysis of lysates from particle-challenged cells failed to identify biomarkers of toxicity due to assay interference and experimental variability. Separately, decreased plasma concentrations of serine protease inhibitors, and the negative acute phase proteins transthyretin, histidine-rich glycoprotein and alpha2-HS glycoprotein were identified as potential biomarkers of methyl methacrylate/ethyl methacrylate/butylacrylate treatment in rats.

Systematic identification of small molecule adjuvants

Introduction: Adjuvants potentiate immune responses, reducing the amount and dosing frequency of antigen required for inducing protective immunity. Adjuvants are of special importance when considering subunit, epitope-based or more unusual vaccine formulations lacking significant innate immunogenicity. While numerous adjuvants are known, only a few are licensed for human use; principally alum, and squalene-based oil-in-water adjuvants. Alum, the most commonly used, is suboptimal. There are many varieties of adjuvant: proteins, oligonucleotides, drug-like small molecules and liposome-based delivery systems with intrinsic adjuvant activity being perhaps the most prominent. Areas covered: This article focuses on small molecules acting as adjuvants, with the author reviewing their current status while highlighting their potential for systematic discovery and rational optimisation. Known small molecule adjuvants (SMAs) can be synthetically complex natural products, small oligonucleotides or drug-like synthetic molecules. The author provides examples of each class, discussing adjuvant mechanisms relevant to SMAs, and exploring the high-throughput discovery of SMAs. Expert opinion: SMAs, particularly synthetic drug-like adjuvants, are amenable to the plethora of drug-discovery techniques able to optimise the properties of biologically active small molecules. These range from laborious synthetic modifications to modern, rational, effort-efficient computational approaches, such as QSAR and structure-based drug design. In principal, any property or characteristic can thus be designed in or out of compounds, allowing us to tailor SMAs to specific biological functions, such as targeting specific cells or pathways, in turn affording the power to tailor SMAs to better address different diseases.

Proteins accessible to immune surveillance show significant T-cell epitope depletion:implications for vaccine design

T cell activation is the final step in a complex pathway through which pathogen-derived peptide fragments can elicit an immune response. For it to occur, peptides must form stable complexes with Major Histocompatibility Complex (MHC) molecules and be presented on the cell surface. Computational predictors of MHC binding are often used within in silico vaccine design pathways. We have previously shown that, paradoxically, most bacterial proteins known experimentally to elicit an immune response in disease models are depleted in peptides predicted to bind to human MHC alleles. The results presented here, derived using software proven through benchmarking to be the most accurate currently available, show that vaccine antigens contain fewer predicted MHC-binding peptides than control bacterial proteins from almost all subcellular locations with the exception of cell wall and some cytoplasmic proteins. This effect is too large to be explained from the undoubted lack of precision of the software or from the amino acid composition of the antigens. Instead, we propose that pathogens have evolved under the influence of the host immune system so that surface proteins are depleted in potential MHC-binding peptides, and suggest that identification of a protein likely to contain a single immuno-dominant epitope is likely to be a productive strategy for vaccine design.

In silico identification of novel G protein coupled receptors

G-protein coupled receptors (GPCRs) are a superfamily of membrane integral proteins responsible for a large number of physiological functions. Approximately 50% of marketed drugs are targeted toward a GPCR. Despite showing a high degree of structural homology, there is a large variance in sequence within the GPCR superfamily which has lead to difficulties in identifying and classifying potential new GPCR proteins. Here the various computational techniques that can be used to characterize a novel GPCR protein are discussed, including both alignment-based and alignment-free approaches. In addition, the application of homology modeling to building the three-dimensional structures of GPCRs is described.

Lipoxidation adducts with peptides and proteins:deleterious modifications or signalling mechanisms?

Protein lipoxidation refers to the modification by electrophilic lipid oxidation products to form covalent adducts, which for many years has been considered as a deleterious consequence of oxidative stress. Oxidized lipids or phospholipids containing carbonyl moieties react readily with lysine to form Schiff bases; alternatively, oxidation products containing α,β-unsaturated moieties are susceptible to nucleophilic attack by cysteine, histidine or lysine residues to yield Michael adducts, overall corresponding to a large number of possible protein adducts. The most common detection methods for lipoxidized proteins take advantage of the presence of reactive carbonyl groups to add labels, or use antibodies. These methods have limitations in terms of specificity and identification of the modification site. The latter question is satisfactorily addressed by mass spectrometry, which enables the characterization of the adduct structure. This has allowed the identification of lipoxidized proteins in physiological and pathological situations. While in many cases lipoxidation interferes with protein function, causing inhibition of enzymatic activity and increased immunogenicity, there are a small number of cases where lipoxidation results in gain of function or activity. For certain proteins lipoxidation may represent a form of redox signaling, although more work is required to confirm the physiological relevance and mechanisms of such processes. This article is part of a Special Issue entitled: Posttranslational Protein modifications in biology and Medicine. © 2013 Elsevier B.V.

Intermediate pyrolysis and product identification by TGA and Py-GC/MS of green microalgae and their extracted protein and lipid components

The thermo-chemical conversion of green microalgae Chlamydomonas reinhardtii wild type (CCAP 11/32C), its cell wall deficient mutant C. reinhardtii CW15 (CCAP 11/32CW15) and Chlorella vulgaris (CCAP 211/11B) as well as their proteins and lipids was studied under conditions of intermediate pyrolysis. The microalgae were characterised for ultimate and gross chemical composition, lipid composition and extracted products were analysed by Thermogravimetric analysis (TG/DTG) and Pyrolysis-gaschromatography/mass-spectrometry (Py-GC/MS). Proteins accounted for almost 50% and lipids 16-22 % of dry weight of cells with little difference in the lipid compositions between the C. reinhardtii wild type and the cell wall mutant. During TGA analysis, each biomass exhibited three stages of decomposition, namely dehydration, devolatilization and decomposition of carbonaceous solids. Py-GC/MS analysis revealed significant protein derived compounds from all algae including toluene, phenol, 4-methylphenol, 1H-indole, 1H-indole-3methyl. Lipid pyrolysis products derived from C. reinhardtii wild type and C. reinhardtii CW15 were almost identical and reflected the close similarity of the fatty acid profiles of both strains. Major products identified were phytol and phytol derivatives formed from the terpenoid chain of chlorophyll, benzoic acid alkyl ester derivative, benzenedicarboxylic acid alkyl ester derivative and squalene. In addition, octadecanoic acid octyl ester, hexadecanoic acid methyl ester and hydrocarbons including heptadecane, 1-nonadecene and heneicosane were detected from C. vulgaris pyrolysed lipids. These results contrast sharply with the types of pyrolytic products obtained from terrestrial lignocellulosic feedstocks and reveal that intermediate pyrolysis of algal biomass generates a range of useful products with wide ranging applications including bio fuels.

Identification and molecular mechanisms of the rapid tonicity-induced relocalization of the aquaporin 4 channel

The aquaporin family of integral membrane proteins is comprised of channels that mediate cellular water flow. Aquaporin 4 (AQP4) is highly expressed in the glial cells of the central nervous system and facilitates the osmotically-driven pathological brain swelling associated with stroke and traumatic brain injury. Here we show that AQP4 cell surface expression can be rapidly and reversibly regulated in response to changes of tonicity in primary cortical rat astrocytes and in transfected HEK293 cells. The translocation mechanism involves protein kinase A (PKA) activation, influx of extracellular calcium and activation of calmodulin. We identify five putative PKA phosphorylation sites and use site-directed mutagenesis to show that only phosphorylation at one of these sites, serine- 276, is necessary for the translocation response. We discuss our findings in the context of the identification of new therapeutic approaches to treating brain oedema.

TATPred:a Bayesian method for the identification of twin arginine translocation pathway signal sequences

The twin arginine translocation (TAT) system ferries folded proteins across the bacterial membrane. Proteins are directed into this system by the TAT signal peptide present at the amino terminus of the precursor protein, which contains the twin arginine residues that give the system its name. There are currently only two computational methods for the prediction of TAT translocated proteins from sequence. Both methods have limitations that make the creation of a new algorithm for TAT-translocated protein prediction desirable. We have developed TATPred, a new sequence-model method, based on a Nave-Bayesian network, for the prediction of TAT signal peptides. In this approach, a comprehensive range of models was tested to identify the most reliable and robust predictor. The best model comprised 12 residues: three residues prior to the twin arginines and the seven residues that follow them. We found a prediction sensitivity of 0.979 and a specificity of 0.942.

Molecular identification of 26 syntaxin genes and their assignment to the different trafficking pathways in Paramecium

SNARE proteins have been classified as vesicular (v)- and target (t)-SNAREs and play a central role in the various membrane interactions in eukaryotic cells. Based on the Paramecium genome project, we have identified a multigene family of at least 26 members encoding the t-SNARE syntaxin (PtSyx) that can be grouped into 15 subfamilies. Paramecium syntaxins match the classical build-up of syntaxins, being 'tail-anchored' membrane proteins with an N-terminal cytoplasmic domain and a membrane-bound single C-terminal hydrophobic domain. The membrane anchor is preceded by a conserved SNARE domain of approximately 60 amino acids that is supposed to participate in SNARE complex assembly. In a phylogenetic analysis, most of the Paramecium syntaxin genes were found to cluster in groups together with those from other organisms in a pathway-specific manner, allowing an assignment to different compartments in a homology-dependent way. However, some of them seem to have no counterparts in metazoans. In another approach, we fused one representative member of each of the syntaxin isoforms to green fluorescent protein and assessed the in vivo localization, which was further supported by immunolocalization of some syntaxins. This allowed us to assign syntaxins to all important trafficking pathways in Paramecium.

Engineering of a novel Saccharomyces cerevisiae wine strain with a respiratory phenotype at high external glucose concentrations

The recently described respiratory strain Saccharomyces cerevisiae KOY.TM6*P is, to our knowledge, the only reported strain of S. cerevisiae which completely redirects the flux of glucose from ethanol fermentation to respiration, even at high external glucose concentrations (27). In the KOY.TM6*P strain, portions of the genes encoding the predominant hexose transporter proteins, Hxt1 and Hxt7, were fused within the regions encoding transmembrane (TM) domain 6. The resulting chimeric gene, TM6*. encoded a chimera composed of the amino-terminal half of Hxt1 and the carboxy-terminal half of Hxt7. It was subsequently integrated into the genome of an hxt null strain. In this study, we have demonstrated the transferability of this respiratory phenotype to the V5 hxt1-7Δ strain, a derivative of a strain used in enology. We also show by using this mutant that it is not necessary to transform a complete hxt null strain with the TM6* construct to obtain a nonethanol-producing phenotype. The resulting V5.TM6*P strain, obtained by transformation of the V5 hxt1-7Δ strain with the TM6* chimeric gene, produced only minor amounts of ethanol when cultured on external glucose concentrations as high as 5%. Despite the fact that glucose flux was reduced to 30% in the V5.TM6*P strain compared with that of its parental strain, the V5.TM6*P strain produced biomass at a specific rate as high as 85% that of the V5 wild-type strain. Even more relevant for the potential use of such a strain for the production of heterologous proteins and also of low-alcohol beverages is the observation that the biomass yield increased 50% with the mutant compared to its parental strain. Copyright © 2005, American Society for Microbiology. All Rights Reserved.

Identification and relative quantification of tyrosine nitration in a model peptide using two-dimensional infrared spectroscopy

Nitration of tyrosine in proteins and peptides is a post-translational modification that occurs under conditions of oxidative stress. It is implicated in a variety of medical conditions, including neurodegenerative and cardiovascular diseases. However, monitoring tyrosine nitration and understanding its role in modifying biological function remains a major challenge. In this work, we investigate the use of electron-vibration-vibration (EVV) two-dimensional infrared (2DIR) spectroscopy for the study of tyrosine nitration in model peptides. We demonstrate the ability of EVV 2DIR spectroscopy to differentiate between the neutral and deprotonated states of 3-nitrotyrosine, and we characterize their spectral signatures using information obtained from quantum chemistry calculations and simulated EVV 2DIR spectra. To test the sensitivity of the technique, we use mixed-peptide samples containing various levels of tyrosine nitration, and we use mass spectrometry to independently verify the level of nitration. We conclude that EVV 2DIR spectroscopy is able to provide detailed spectroscopic information on peptide side-chain modifications and to detect nitration levels down to 1%. We further propose that lower nitration levels could be detected by introducing a resonant Raman probe step to increase the detection sensitivity of EVV 2DIR spectroscopy. (Graph Presented).

Mass spectrometry-based methods for identifying oxidized proteins in disease:advances and challenges

Many inflammatory diseases have an oxidative aetiology, which leads to oxidative damage to biomolecules, including proteins. It is now increasingly recognized that oxidative post-translational modifications (oxPTMs) of proteins affect cell signalling and behaviour, and can contribute to pathology. Moreover, oxidized proteins have potential as biomarkers for inflammatory diseases. Although many assays for generic protein oxidation and breakdown products of protein oxidation are available, only advanced tandem mass spectrometry approaches have the power to localize specific oxPTMs in identified proteins. While much work has been carried out using untargeted or discovery mass spectrometry approaches, identification of oxPTMs in disease has benefitted from the development of sophisticated targeted or semi-targeted scanning routines, combined with chemical labeling and enrichment approaches. Nevertheless, many potential pitfalls exist which can result in incorrect identifications. This review explains the limitations, advantages and challenges of all of these approaches to detecting oxidatively modified proteins, and provides an update on recent literature in which they have been used to detect and quantify protein oxidation in disease.

Event trigger identification for biomedical events extraction using domain knowledge

Motivation: In molecular biology, molecular events describe observable alterations of biomolecules, such as binding of proteins or RNA production. These events might be responsible for drug reactions or development of certain diseases. As such, biomedical event extraction, the process of automatically detecting description of molecular interactions in research articles, attracted substantial research interest recently. Event trigger identification, detecting the words describing the event types, is a crucial and prerequisite step in the pipeline process of biomedical event extraction. Taking the event types as classes, event trigger identification can be viewed as a classification task. For each word in a sentence, a trained classifier predicts whether the word corresponds to an event type and which event type based on the context features. Therefore, a well-designed feature set with a good level of discrimination and generalization is crucial for the performance of event trigger identification. Results: In this article, we propose a novel framework for event trigger identification. In particular, we learn biomedical domain knowledge from a large text corpus built from Medline and embed it into word features using neural language modeling. The embedded features are then combined with the syntactic and semantic context features using the multiple kernel learning method. The combined feature set is used for training the event trigger classifier. Experimental results on the golden standard corpus show that >2.5% improvement on F-score is achieved by the proposed framework when compared with the state-of-the-art approach, demonstrating the effectiveness of the proposed framework. © 2014 The Author 2014. The source code for the proposed framework is freely available and can be downloaded at http://cse.seu.edu.cn/people/zhoudeyu/ETI_Sourcecode.zip.