Identification of astrocyte secreted proteins with a combination of shotgun proteomics and bioinformatics.
ABSTRACT: Astrocytes are important regulators of normal brain function in mammals, including roles in synaptic signaling, synapse formation, and neuronal health and survival. Many of these functions are executed via secreted proteins. To analyze the astrocyte secretome, a combination of shotgun proteomics and bioinformatics was employed to analyze conditioned media from primary murine astrocyte cultures. Both two- and one-dimensional LC-MS/MS were used to analyze astrocyte secreted proteins, resulting in the identification of over 420 proteins. To refine our results, the intracellular protein contaminants were removed in silico using a cytoplasmic control. In additional rounds of refinement, putative secreted proteins were subjected to analysis by SignalP, SecretomeP, and gene ontology analysis, yielding a refined list of 187 secreted proteins. In conclusion, the use of shotgun proteomics combined with multiple rounds of data refinement produced a high quality catalog of astrocyte secreted proteins.
Project description:Methylglyoxal (MG), a glycolytic intermediate and reactive dicarbonyl, is responsible for exacerbation of insulin resistance and diabetic complication. In this study, MG-induced secretome of rat muscle cells was identified and relatively quantified by SWATH-MS. A total of 643 proteins were identified in MG-induced secretome, of which 82 proteins were upregulated and 99 proteins were downregulated by more than 1.3-fold in SWATH analysis. Further, secretory proteins from the classical secretory pathway and nonclassical secretory pathway were identified using SignalP and SecretomeP, respectively. A total of 180 proteins were identified with SignalP, and 113 proteins were identified with SecretomeP. The differentially expressed proteins were functionally annotated by KEGG pathway analysis using Cytoscape software with plugin clusterMaker. The differentially expressed proteins were found to be involved in various pathways like extracellular matrix (ECM)-receptor interaction, leukocyte transendothelial migration, fluid shear stress and atherosclerosis, complement and coagulation cascades, and lysosomal pathway. Since the MG levels are high in diabetic conditions, the presence of MG-induced secreted proteins was inspected by profiling human plasma of healthy and diabetic subjects (n = 10 each). CD44, a predominant MG-induced secreted protein, was found to be elevated in the diabetic plasma and to have a role in the development of insulin resistance.
Project description:<h4>Background</h4>The secretion time course of Bacillus anthracis strain RA3R (pXO1+/pXO2-) during early, mid, and late log phase were investigated under conditions that simulate those encountered in the host. All of the identified proteins were analyzed by different software algorithms to characterize their predicted mode of secretion and cellular localization. In addition, immunogenic proteins were identified using sera from humans with cutaneous anthrax.<h4>Results</h4>A total of 275 extracellular proteins were identified by a combination of LC MS/MS and MALDI-TOF MS. All of the identified proteins were analyzed by SignalP, SecretomeP, PSORT, LipoP, TMHMM, and PROSITE to characterize their predicted mode of secretion, cellular localization, and protein domains. Fifty-three proteins were predicted by SignalP to harbor the cleavable N-terminal signal peptides and were therefore secreted via the classical Sec pathway. Twenty-three proteins were predicted by SecretomeP for secretion by the alternative Sec pathway characterized by the lack of typical export signal. In contrast to SignalP and SecretomeP predictions, PSORT predicted 171 extracellular proteins, 7 cell wall-associated proteins, and 6 cytoplasmic proteins. Moreover, 51 proteins were predicted by LipoP to contain putative Sec signal peptides (38 have SpI sites), lipoprotein signal peptides (13 have SpII sites), and N-terminal membrane helices (9 have transmembrane helices). The TMHMM algorithm predicted 25 membrane-associated proteins with one to ten transmembrane helices. Immunogenic proteins were also identified using sera from patients who have recovered from anthrax. The charge variants (83 and 63 kDa) of protective antigen (PA) were the most immunodominant secreted antigens, followed by charge variants of enolase and transketolase.<h4>Conclusion</h4>This is the first description of the time course of protein secretion for the pathogen Bacillus anthracis. Time course studies of protein secretion and accumulation may be relevant in elucidation of the progression of pathogenicity, identification of therapeutics and diagnostic markers, and vaccine development. This study also adds to the continuously growing list of identified Bacillus anthracis secretome proteins.
Project description:Toxoplasma gondii uses epigenetic mechanisms to regulate both endogenous and host cell gene expression. To identify genes with putative epigenetic functions, we developed an in silico pipeline to interrogate the T. gondii proteome of 8313 proteins. Step 1 employs PredictNLS and NucPred to identify genes predicted to target eukaryotic nuclei. Step 2 uses GOLink to identify proteins of epigenetic function based on Gene Ontology terms. This resulted in 611 putative nuclear localised proteins with predicted epigenetic functions. Step 3 filtered for secretory proteins using SignalP, SecretomeP, and experimental data. This identified 57 of the 611 putative epigenetic proteins as likely to be secreted. The pipeline is freely available online, uses open access tools and software with user-friendly Perl scripts to automate and manage the results, and is readily adaptable to undertake any such in silico search for genes contributing to particular functions.
Project description:Chinese hamster ovary (CHO) cells are the preferred host cell line for manufacturing a variety of complex biotherapeutic drugs including monoclonal antibodies. We performed a proteomics and bioinformatics analysis on the spent medium from adherent CHO cells. Supernatant from CHO-K1 culture was collected and subjected to in-solution digestion followed by LC/LC-MS/MS analysis, which allowed the identification of 3281 different host cell proteins (HCPs). To functionally categorize them, we applied multiple bioinformatics tools to the proteins identified in our study including SignalP, TargetP, SecretomeP, TMHMM, WoLF PSORT, and Phobius. This analysis provided information on the presence of signal peptides, transmembrane domains, and cellular localization and showed that both secreted and intracellular proteins were constituents of the supernatant. Identified proteins were shown to be localized to the secretory pathway including ones playing roles in cell growth, proliferation, and folding as well as those involved in protein degradation and removal. After combining proteins predicted to be secreted or having a signal peptide, we identified 1015 proteins, which we termed as CHO supernatant-ome (CHO-SO), or superome. As a part of this effort, we created a publically accessible web-based tool called GO-CHO to functionally categorize proteins found in CHO-SO and identify enriched molecular functions, biological processes, and cellular components. We also used a tool to evaluate the immunogenicity potential of high-abundance HCPs. Among enriched functions were catalytic activity and structural constituents of the cytoskeleton. Various transport related biological processes, such as vesicle mediated transport, were found to be highly enriched. Extracellular space and vesicular exosome associated proteins were found to be the most enriched cellular components. The superome also contained proteins secreted from both classical and nonclassical secretory pathways. The work and database described in our study will enable the CHO community to rapidly identify high-abundance HCPs in their cultures and therefore help assess process and purification methods used in the production of biologic drugs.
Project description:The proteome of extremely thermophilic microorganisms affords a glimpse into the dynamics of microbial ecology of high temperature environments. The secretome, or extracellular proteome of these microorganisms, no doubt harbors technologically important enzymes and other thermostable biomolecules that, to date, have been characterized only to a limited extent. In the first of a two-part study on selected thermophiles, defining the secretome requires a sample preparation method that has no negative impact on all downstream experiments. Following efficient secretome purification, GeLC-MS(2) analysis and prediction servers suggested probable protein secretion to complement experimental data. In an effort to define the extracellular proteome of the extreme thermophilic bacterium Caldicellulosiruptor saccharolyticus, several techniques were considered regarding sample processing to achieve the most in-depth analysis of secreted proteins. Order of operation experiments, all including the C(18) bead technique, demonstrated that two levels of sample purification were necessary to effectively desalt the sample and provide sufficient protein identifications. Five sample preparation combinations yielded 71 proteins and the majority described, as enzymatic and putative uncharacterized proteins, anticipate consolidated bioprocessing applications. Nineteen proteins were predicted by Phobius, SignalP, SecretomeP, or TatP for extracellular secretion, and 11 contained transmembrane domain stretches suggested by Phobius and transmembrane hidden Markov model. The sample preparation technique demonstrating the most effective outcome for C. saccharolyticus secreted proteins in this study, involved acetone precipitation followed by the C(18) bead method in which 2.4% (63 proteins) of the predicted proteome was identified, including proteins suggested to have secretion and transmembrane moieties.
Project description:The flatworm Taenia solium causes human and pig cysticercosis. When cysticerci are established in the human central nervous system, they cause neurocysticercosis, a potentially fatal disease. Neurocysticercosis is a persisting public health problem in rural regions of Mexico and other developing countries of Latin America, Asia, and Africa, where the infection is endemic. The great variability observed in the phenotypic and genotypic traits of cysticerci result in a great heterogeneity in the patterns of molecules secreted by them within their host. This work is aimed to identify and characterize cysticercal secretion proteins of T. solium cysticerci obtained from 5 naturally infected pigs from Guerrero, Mexico, using 2D-PAGE proteomic analysis. The isoelectric point (IP) and molecular weight (MW) of the spots were identified using the software ImageMaster 2D Platinum v.7.0. Since most secreted proteins are impossible to identify by mass spectrometry (MS) due to their low concentration in the sample, a novel strategy to predict their sequence was applied. In total, 108 conserved and 186 differential proteins were identified in five cysticercus cultures. Interestingly, we predicted the sequence of 14 proteins that were common in four out of five cysticercus cultures, which could be used to design vaccines or diagnostic methods for neurocysticercosis. A functional characterization of all sequences was performed using the algorithms SecretomeP, SignalP, and BlastKOALA. We found a possible link between signal transduction pathways in parasite cells and human cancer due to deregulation in signal transduction pathways. Bioinformatics analysis also demonstrated that the parasite release proteins by an exosome-like mechanism, which could be of biological interest.
Project description:Astrocytes play an important role in neuronal development through the release of soluble factors that affect neuronal maturation. Shotgun proteomics followed by gene ontology analysis was used in this study to identify proteins present in the conditioned medium of primary rat astrocytes. One hundred and thirty three secreted proteins were identified, the majority of which were never before reported to be produced by astrocytes. Extracellular proteins were classified based on their biological and molecular functions; most of the identified proteins were involved in neuronal development. Semi-quantitative proteomic analysis was carried out to identify changes in the levels of proteins released by astrocytes after stimulation with the cholinergic agonist carbachol, as we have previously reported that carbachol-treated astrocytes elicit neuritogenesis in hippocampal neurons through the release of soluble factors. Carbachol up-regulated secretion of 15 proteins and down-regulated the release of 17 proteins. Changes in the levels of four proteins involved in neuronal differentiation (thrombospondin-1, fibronectin, plasminogen activator inhibitor-1, and plasminogen activator urokinase) were verified by western blot or ELISA. In conclusion, this study identified a large number of proteins involved in neuronal development in the astrocyte secretome and implicated extracellular matrix proteins and protease systems in neuronal development induced by astrocyte cholinergic stimulation.
Project description:In proteomic analyses of the plant secretome, the presence of putative leaderless secretory proteins (LSPs) is difficult to confirm due to the possibility of contamination from other sub-cellular compartments. In the absence of a plant-specific tool for predicting LSPs, the mammalian-trained SecretomeP has been applied to plant proteins in multiple studies to identify the most likely LSPs. This study investigates the effectiveness of using SecretomeP on plant proteins, identifies its limitations and provides a benchmark for its use. In the absence of experimentally verified LSPs we exploit the common-feature hypothesis behind SecretomeP and use known classically secreted proteins (CSPs) of plants as a proxy to evaluate its accuracy. We show that, contrary to the common-feature hypothesis, plant CSPs are a poor proxy for evaluating LSP detection due to variation in the SecretomeP prediction scores when the signal peptide (SP) is modified. Removing the SP region from CSPs and comparing the predictive performance against non-secretory proteins indicates that commonly used threshold scores of 0.5 and 0.6 result in false-positive rates in excess of 0.3 when applied to plants proteins. Setting the false-positive rate to 0.05, consistent with the original mammalian performance of SecretomeP, yields only a marginally higher true positive rate compared to false positives. Therefore the use of SecretomeP on plant proteins is not recommended. This study investigates the trade-offs of using SecretomeP on plant proteins and provides insights into predictive features for future development of plant-specific common-feature tools.
Project description:Genomics experiments are widely acknowledged to produce a huge amount of data to be analysed. The challenge is to extract meaningful biological context for proteins or genes which is currently difficult because of the lack of an integrative workflow that hinders the efficiency and the robustness of data mining performed by biologists working on ruminants. Thus, we designed ProteINSIDE, a free web service (www.proteinside.org) that (I) provides an overview of the biological information stored in public databases or provided by annotations according to the Gene Ontology, (II) predicts proteins that are secreted to search for proteins that mediate signalisation between cells or tissues, and (III) analyses protein-protein interactions to identify proteins contributing to a process or to visualize functional pathways. Using lists of proteins or genes as a unique input, ProteINSIDE is an original all-in-one tool that merges data from these searches to present a fast overview and integrative analysis of genomic and proteomic data from Bovine, Ovine, Caprine, Human, Rat, and Murine species. ProteINSIDE was bench tested with 1000 proteins identifiers from each species by comparison with DAVID, BioMyn, AgBase, PrediSi, and Phobius. Compared to DAVID or BioMyn, identifications and annotations provided by ProteINSIDE were similar from monogastric proteins but more numerous and relevant for ruminants proteins. ProteINSIDE, thanks to SignalP, listed less proteins potentially secreted with a signal peptide than PrediSi and Phobius, in agreement with the low false positive rate of SignalP. In addition ProteINSIDE is the only resource that predicts proteins secreted by cellular processes that do not involve a signal peptide. Lastly, we reported the usefulness of ProteINSIDE to bring new biological hypotheses of research from proteomics data: the biological meaning of the uptake of adiponectin by the foetal muscle and a role for autophagy during ontogenesis of adipose and muscle tissues.
Project description:The Skeletal muscle is a metabolic active tissue that secretes various proteins. These so called myokines act auto-, para- and endocrine affecting muscle physiology and exert systemic effects on other tissues and organs. Myokines are also described to play a crucial role in the pathophysiology of metabolic diseases. Combining three different mass spectrometry based non-targeted and one antibody based targeted approach we investigated the secretome of differentiated primary human skeletal muscle cells derived from adult donors. A total of 548 non-redundant proteins were detected by combined proteomic profiling. Expression was confirmed on mRNA level for 501. Stringent consecutive filtering recruiting several database, i.e. SignalP, SecretomeP and ER_retention signals, the computational analysis assigned 306 as secretory proteins including 33 potentially novel myokines. This comprehensive profiling study of the human skeletal muscle secretome expands our knowledge of the composition of the human myokinome and further highlights the pivotal role of myokines in the regulation of multiple biological processes. We performed gene expression microarray analysis of primary human myotubes derived from twelve healthy individuals