FunRich: An open access standalone functional enrichment and interaction network analysis tool

Exosome and Microvesicle-Enriched Fractions Isolated from Mesenchymal Stem Cells by Gradient Separation Showed Different Molecular Signatures and Functions on Renal Tubular Epithelial Cells

Several studies have suggested that extracellular vesicles (EVs) released from mesenchymal stem cells (MSCs) may mediate MSC paracrine action on kidney regeneration. This activity has been, at least in part, ascribed to the transfer of proteins/transcription factors and different RNA species. Information on the RNA/protein content of different MSC EV subpopulations and the correlation with their biological activity is currently incomplete. The aim of this study was to evaluate the molecular composition and the functional properties on renal target cells of MSC EV sub-populations separated by gradient floatation. The results demonstrated heterogeneity in quantity and composition of MSC EVs. Two peaks of diameter were observed (90-110 and 170-190 nm). The distribution of exosomal markers and miRNAs evaluated in the twelve gradient fractions showed an enrichment in fractions with a flotation density of 1.08-1.14 g/mL. Based on this observation, we evaluated the biological activity on renal cell proliferation and apoptosis resistance of low (CF1), medium (CF2) and high (CF3) floatation density fractions. EVs derived from all fractions, were internalized by renal cells, CF1 and CF2 but not CF3 fraction stimulated significant cell proliferation. CF2 also inhibited apoptosis on renal tubular cells submitted to ischemia-reperfusion injury. Comparative miRNomic and proteomic profiles reveal a cluster of miRNAs and proteins common to all three fractions and an enrichment of selected molecules related to renal regeneration in CF2 fraction. In conclusion, the CF2 fraction enriched in exosomal markers was the most active on renal tubular cell proliferation and protection from apoptosis.

Molecular characterization of human osteoblast-derived extracellular vesicle mRNA using next-generation sequencing

Extracellular vesicles (EVs) are membrane-bound intercellular communication vehicles that transport proteins, lipids and nucleic acids with regulatory capacity between cells. RNA profiling using microarrays and sequencing technologies has revolutionized the discovery of EV-RNA content, which is crucial to understand the molecular mechanism of EV function. Recent studies have indicated that EVs are enriched with specific RNAs compared to the originating cells suggestive of an active sorting mechanism. Here, we present the comparative transcriptome analysis of human osteoblasts and their corresponding EVs using next-generation sequencing. We demonstrate that osteoblast-EVs are specifically depleted of cellular mRNAs that encode proteins involved in basic cellular activities, such as cytoskeletal functions, cell survival and apoptosis. In contrast, EVs are significantly enriched with 254 mRNAs that are associated with protein translation and RNA processing. Moreover, mRNAs enriched in EVs encode proteins important for communication with the neighboring cells, in particular with osteoclasts, adipocytes and hematopoietic stem cells. These findings provide the foundation for understanding the molecular mechanism and function of EV-mediated interactions between osteoblasts and the surrounding bone microenvironment.

Integrated analysis of genetic, behavioral, and biochemical data implicates neural stem cell-induced changes in immunity, neurotransmission and mitochondrial function in Dementia with Lewy Body mice

We previously demonstrated that transplantation of murine neural stem cells (NSCs) can improve motor and cognitive function in a transgenic model of Dementia with Lewy Bodies (DLB). These benefits occurred without changes in human α-synuclein pathology and were mediated in part by stem cell-induced elevation of brain-derived neurotrophic factor (BDNF). However, instrastriatal NSC transplantation likely alters the brain microenvironment via multiple mechanisms that may synergize to promote cognitive and motor recovery. The underlying neurobiology that mediates such restoration no doubt involves numerous genes acting in concert to modulate signaling within and between host brain cells and transplanted NSCs. In order to identify functionally connected gene networks and additional mechanisms that may contribute to stem cell-induced benefits, we performed weighted gene co-expression network analysis (WGCNA) on striatal tissue isolated from NSC- and vehicle-injected wild-type and DLB mice. Combining continuous behavioral and biochemical data with genome wide expression via network analysis proved to be a powerful approach; revealing significant alterations in immune response, neurotransmission, and mitochondria function. Taken together, these data shed further light on the gene network and biological processes that underlie the therapeutic effects of NSC transplantation on α-synuclein induced cognitive and motor impairments, thereby highlighting additional therapeutic targets for synucleinopathies.

GFD-Net: A novel semantic similarity methodology for the analysis of gene networks

Since the popularization of biological network inference methods, it has become crucial to create methods to validate the resulting models. Here we present GFD-Net, the first methodology that applies the concept of semantic similarity to gene network analysis. GFD-Net combines the concept of semantic similarity with the use of gene network topology to analyze the functional dissimilarity of gene networks based on Gene Ontology (GO). The main innovation of GFD-Net lies in the way that semantic similarity is used to analyze gene networks taking into account the network topology. GFD-Net selects a functionality for each gene (specified by a GO term), weights each edge according to the dissimilarity between the nodes at its ends and calculates a quantitative measure of the network functional dissimilarity, i.e. a quantitative value of the degree of dissimilarity between the connected genes. The robustness of GFD-Net as a gene network validation tool was demonstrated by performing a ROC analysis on several network repositories. Furthermore, a well-known network was analyzed showing that GFD-Net can also be used to infer knowledge. The relevance of GFD-Net becomes more evident in Section "GFD-Net applied to the study of human diseases" where an example of how GFD-Net can be applied to the study of human diseases is presented. GFD-Net is available as an open-source Cytoscape app which offers a user-friendly interface to configure and execute the algorithm as well as the ability to visualize and interact with the results(http://apps.cytoscape.org/apps/gfdnet).

High-throughput sequencing of two populations of extracellular vesicles provides an mRNA signature that can be detected in the circulation of breast cancer patients

Extracellular vesicles (EVs) contain a wide range of RNA types with a reported prevalence of non-coding RNA. To date a comprehensive characterization of the protein coding transcripts in EVs is still lacking. We performed RNA-Sequencing (RNA-Seq) of 2 EV populations and identified a small fraction of transcripts that were expressed at significantly different levels in large oncosomes and exosomes, suggesting they may mediate specialized functions. However, these 2 EV populations exhibited a common mRNA signature that, in comparison to their donor cells, was significantly enriched in mRNAs encoding E2F transcriptional targets and histone proteins. These mRNAs are primarily expressed in the S-phase of the cell cycle, suggesting that they may be packaged into EVs during S-phase. In silico analysis using subcellular compartment transcriptome data from the ENCODE cell line compendium revealed that EV mRNAs originate from a cytoplasmic RNA pool. The EV signature was independently identified in plasma of patients with breast cancer by RNA-Seq. Furthermore, several transcripts differentially expressed in EVs from patients versus controls mirrored differential expression between normal and breast cancer tissues. Altogether, this largest high-throughput profiling of EV mRNA demonstrates that EVs carry tumor-specific alterations and can be interrogated as a source of cancer-derived cargo.

SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells

Proteomics is the large-scale analysis of proteins. Proteomic techniques, such as liquid chromatography tandem mass spectroscopy (LC-MS/MS), can characterize thousands of proteins at a time. These powerful techniques allow us to have a systemic understanding of cellular changes, especially when cells are subjected to various stimuli, such as infections, stresses, and specific test conditions. Even with recent developments, analyzing the exosomal proteome is time-consuming and often involves complex methodologies. In addition, the resultant large dataset often needs robust and streamlined analysis in order for researchers to perform further downstream studies. Here, we describe a SILAC-based protocol for characterizing the exosomal proteome when cells are infected with HIV-1. The method is based on simple isotope labeling, isolation of exosomes from differentially labeled cells, and mass spectrometry analysis. This is followed by detailed data mining and bioinformatics analysis of the proteomic hits. The resultant datasets and candidates are easy to understand and often offer a wealth of information that is useful for downstream analysis. This protocol is applicable to other subcellular compartments and a wide range of test conditions.

OAS Gene Family Expression Is Associated with HIV-Related Neurocognitive Disorders

HIV-associated neurocognitive disorders are common in HIV-infected individuals, even in the combination antiretroviral therapy (c-ART) era. Several mechanisms are involved in neuronal damage, including chronic inflammation immune activation. Mammalian 2'-5'-oligoadenylate synthetase (OAS) genes are produced in response to interferon (IFN), mainly by monocytes, and exert their antiviral functions by activation of RNase L that degrades viral and cellular RNAs. In this study, we aimed at exploring OAS gene family RNA expression in simian immunodeficiency virus encephalitis (SIVE), in HIV-associated neurocognitive disorders (HAND), and in HIV-associate dementia (HAD). We analyzed three microarray datasets obtained from the NCBI in order to assess the expression levels of OAS gene family network in brain biopsies of macaques with SIVE vs uninfected animals, as well as post-mortem brain of individuals with HAND (on or off ART) vs uninfected controls and three brain regions of HIV-infected individuals with both neurocognitive impairment (HAD) and encephalitis (HIVE). All OAS genes were upregulated both in SIVE and in HAND. OAS expression was significantly higher in high-viremic individuals; increased expression levels persisted in cART subjects when compared to healthy controls. OAS gene network analysis showed that several genes belonging to the type I IFN pathway, especially CXCL10 and IFIT3, were similarly upregulated in SIVE/HAND. Furthermore, we identified a significant upregulation of OAS gene family RNA expression in basal ganglia, white matter, and frontal cortex of HIV-1, HAD, and HAD/HIVE patients compared to healthy subjects. OAS gene family expression is increased in brain sections from individuals with HAND, HAD, and HIVE as well as macaques with SIVE. OAS family expression is likely to be induced by IFN as a consequence of viral replication in the CNS. Its long-term upregulation may contribute to the chronic inflammatory status and neurocognitive impairment we still observe in virologically suppressed individuals on c-ART.

Regulation of Nitrogen Metabolism by GATA Zinc Finger Transcription Factors in Yarrowia lipolytica

Nitrogen source is commonly used to control lipid production in industrial fungi. Here we identified regulators of nitrogen catabolite repression in the oleaginous yeast Y. lipolytica to determine how the nitrogen source regulates lipid metabolism. We show that disruption of both activators and repressors of nitrogen catabolite repression leads to increased lipid accumulation via activation of carbon catabolite repression through an as yet uncharacterized method.

Fungi accumulate lipids in a manner dependent on the quantity and quality of the nitrogen source on which they are growing. In the oleaginous yeast Yarrowia lipolytica, growth on a complex source of nitrogen enables rapid growth and limited accumulation of neutral lipids, while growth on a simple nitrogen source promotes lipid accumulation in large lipid droplets. Here we examined the roles of nitrogen catabolite repression and its regulation by GATA zinc finger transcription factors on lipid metabolism in Y. lipolytica. Deletion of the GATA transcription factor genes gzf3 and gzf2 resulted in nitrogen source-specific growth defects and greater accumulation of lipids when the cells were growing on a simple nitrogen source. Deletion of gzf1, which is most similar to activators of genes repressed by nitrogen catabolite repression in filamentous ascomycetes, did not affect growth on the nitrogen sources tested. We examined gene expression of wild-type and GATA transcription factor mutants on simple and complex nitrogen sources and found that expression of enzymes involved in malate metabolism, beta-oxidation, and ammonia utilization are strongly upregulated on a simple nitrogen source. Deletion of gzf3 results in overexpression of genes with GATAA sites in their promoters, suggesting that it acts as a repressor, while gzf2 is required for expression of ammonia utilization genes but does not grossly affect the transcription level of genes predicted to be controlled by nitrogen catabolite repression. Both GATA transcription factor mutants exhibit decreased expression of genes controlled by carbon catabolite repression via the repressor mig1, including genes for beta-oxidation, highlighting the complex interplay between regulation of carbon, nitrogen, and lipid metabolism.

IMPORTANCE Nitrogen source is commonly used to control lipid production in industrial fungi. Here we identified regulators of nitrogen catabolite repression in the oleaginous yeast Y. lipolytica to determine how the nitrogen source regulates lipid metabolism. We show that disruption of both activators and repressors of nitrogen catabolite repression leads to increased lipid accumulation via activation of carbon catabolite repression through an as yet uncharacterized method.

The effects of glomerular and tubular renal progenitors and derived extracellular vesicles on recovery from acute kidney injury

Background

Mesenchymal stromal cells (MSCs) and renal stem/progenitors improve the recovery of acute kidney injury (AKI) mainly through the release of paracrine mediators including the extracellular vesicles (EVs). Several studies have reported the existence of a resident population of MSCs within the glomeruli (Gl-MSCs). However, their contribution towards kidney repair still remains to be elucidated. The aim of the present study was to evaluate whether Gl-MSCs and Gl-MSC-EVs promote the recovery of AKI induced by ischemia-reperfusion injury (IRI) in SCID mice. Moreover, the effects of Gl-MSCs and Gl-MSC-EVs were compared with those of CD133⁺ progenitor cells isolated from human tubules of the renal cortical tissue (T-CD133⁺ cells) and their EVs (T-CD133⁺-EVs).

Methods

IRI was performed in mice by clamping the left renal pedicle for 35 minutes together with a right nephrectomy. Immediately after reperfusion, the animals were divided in different groups to be treated with: Gl-MSCs, T-CD133⁺ cells, Gl-MSC-EVs, T-CD133⁺-EVs or vehicle. To assess the role of vesicular RNA, EVs were either isolated by floating to avoid contamination of non-vesicles-associated RNA or treated with a high dose of RNase. Mice were sacrificed 48 hours after surgery.

Results

Gl-MSCs, and Gl-MSC-EVs both ameliorate kidney function and reduce the ischemic damage post IRI by activating tubular epithelial cell proliferation. Furthermore, T-CD133⁺ cells, but not their EVs, also significantly contributed to the renal recovery after IRI compared to the controls. Floating EVs were effective while RNase-inactivated EVs were ineffective. Analysis of the EV miRnome revealed that Gl-MSC-EVs selectively expressed a group of miRNAs, compared to EVs derived from fibroblasts, which were biologically ineffective in IRI.

Conclusions

In this study, we demonstrate that Gl-MSCs may contribute in the recovery of mice with AKI induced by IRI primarily through the release of EVs.

Electronic supplementary material

The online version of this article (doi:10.1186/s13287-017-0478-5) contains supplementary material, which is available to authorized users.

Two factor-based reprogramming of rodent and human fibroblasts into Schwann cells

Schwann cells (SCs) generate the myelin wrapping of peripheral nerve axons and are promising candidates for cell therapy. However, to date a renewable source of SCs is lacking. In this study, we show the conversion of skin fibroblasts into induced Schwann cells (iSCs) by driving the expression of two transcription factors, Sox10 and Egr2. iSCs resembled primary SCs in global gene expression profiling and PNS identity. In vitro, iSCs wrapped axons generating compact myelin sheaths with regular nodal structures. Conversely, iSCs from Twitcher mice showed a severe loss in their myelinogenic potential, demonstrating that iSCs can be an attractive system for in vitro modelling of PNS diseases. The same two factors were sufficient to convert human fibroblasts into iSCs as defined by distinctive molecular and functional traits. Generating iSCs through direct conversion of somatic cells offers opportunities for in vitro disease modelling and regenerative therapies.

Schwann cells (SCs) myelinate peripheral nerve axons and offer opportunities for the treatment of injuries and demyelinating diseases but reliable and renewable sources of these cells are hard to come by. Here the authors reprogram rat, mouse and human fibroblasts into Schwann cells using two transcription factors.

Cellular Signaling Pathways in Insulin Resistance-Systems Biology Analyses of Microarray Dataset Reveals New Drug Target Gene Signatures of Type 2 Diabetes Mellitus

Purpose: Type 2 diabetes mellitus (T2DM) is a chronic and metabolic disorder affecting large set of population of the world. To widen the scope of understanding of genetic causes of this disease, we performed interactive and toxicogenomic based systems biology study to find potential T2DM related genes after cDNA differential analysis.

Methods: From the list of 50-differential expressed genes (p < 0.05), we found 9-T2DM related genes using extensive data mapping. In our constructed gene-network, T2DM-related differentially expressed seeder genes (9-genes) are found to interact with functionally related gene signatures (31-genes). The genetic interaction network of both T2DM-associated seeder as well as signature genes generally relates well with the disease condition based on toxicogenomic and data curation.

Results: These networks showed significant enrichment of insulin signaling, insulin secretion and other T2DM-related pathways including JAK-STAT, MAPK, TGF, Toll-like receptor, p53 and mTOR, adipocytokine, FOXO, PPAR, P13-AKT, and triglyceride metabolic pathways. We found some enriched pathways that are common in different conditions. We recognized 11-signaling pathways as a connecting link between gene signatures in insulin resistance and T2DM. Notably, in the drug-gene network, the interacting genes showed significant overlap with 13-FDA approved and few non-approved drugs. This study demonstrates the value of systems genetics for identifying 18 potential genes associated with T2DM that are probable drug targets.

Conclusions: This integrative and network based approaches for finding variants in genomic data expect to accelerate identification of new drug target molecules for different diseases and can speed up drug discovery outcomes.

In Silico Analysis Validates Proteomic Findings of Formalin-fixed Paraffin Embedded Cutaneous Squamous Cell Carcinoma Tissue

BACKGROUND

Cutaneous squamous cell carcinoma (cSCC) is a common type of skin cancer but there are no comprehensive proteomic studies on this entity.

MATERIALS AND METHODS

We employed liquid chromatography coupled with tandem mass spectrometry (MS/MS) using formalin-fixed paraffin-embedded (FFPE) cSCC material to study the tumor and normal skin tissue proteomes. Ingenuity Pathway Analysis (IPA) was used to interpret the role of altered proteins in cSCC pathophysiology. Results were validated using the Human Protein Atlas and Oncomine database in silico.

RESULTS

Of 1,310 unique proteins identified, expression of an average of 144 and 88 proteins were significantly (p<0.05) increased and decreased, respectively, in the tumor samples compared to their normal counterparts. IPA analysis revealed disruptions in proteins associated with cell proliferation, apoptosis, and migration. In silico analysis confirmed that proteins corresponding to 12 antibodies, and genes corresponding to 18 proteins were differentially expressed between the two categories, validating our proteomic measurements.

CONCLUSION

Label-free MS-based proteomics is useful for analyzing FFPE cSCC tissues.

Network Tools for the Analysis of Proteomic Data

Recent advancements in high-throughput technologies such as mass spectrometry have led to an increase in the rate at which data is generated and accumulated. As a result, standard statistical methods no longer suffice as a way of analyzing such gigantic amounts of data. Network analysis, the evaluation of how nodes relate to one another, has over the years become an integral tool for analyzing high throughput proteomic data as they provide a structure that helps reduce the complexity of the underlying data.Computational tools, including pathway databases and network building tools, have therefore been developed to store, analyze, interpret, and learn from proteomics data. These tools enable the visualization of proteins as networks of signaling, regulatory, and biochemical interactions. In this chapter, we provide an overview of networks and network theory fundamentals for the analysis of proteomics data. We further provide an overview of interaction databases and network tools which are frequently used for analyzing proteomics data.

Bioinformatics Methods to Deduce Biological Interpretation from Proteomics Data

High-throughput proteomics studies generate large amounts of data. Biological interpretation of these large scale datasets is often challenging. Over the years, several computational tools have been developed to facilitate meaningful interpretation of large-scale proteomics data. In this chapter, we describe various analyses that can be performed and bioinformatics tools and resources that enable users to do the analyses. Many Web-based and stand-alone tools are relatively user-friendly and can be used by most biologists without significant assistance.

Identification of Putative Transmembrane Proteins Involved in Salinity Tolerance in Chenopodium quinoa by Integrating Physiological Data, RNAseq, and SNP Analyses

Chenopodium quinoa (quinoa) is an emerging crop that produces nutritious grains with the potential to contribute to global food security. Quinoa can also grow on marginal lands, such as soils affected by high salinity. To identify candidate salt tolerance genes in the recently sequenced quinoa genome, we used a multifaceted approach integrating RNAseq analyses with comparative genomics and topology prediction. We identified 219 candidate genes by selecting those that were differentially expressed in response to salinity, were specific to or overrepresented in quinoa relative to other Amaranthaceae species, and had more than one predicted transmembrane domain. To determine whether these genes might underlie variation in salinity tolerance in quinoa and its close relatives, we compared the response to salinity stress in a panel of 21 Chenopodium accessions (14 C. quinoa, 5 C. berlandieri, and 2 C. hircinum). We found large variation in salinity tolerance, with one C. hircinum displaying the highest salinity tolerance. Using genome re-sequencing data from these accessions, we investigated single nucleotide polymorphisms and copy number variation (CNV) in the 219 candidate genes in accessions of contrasting salinity tolerance, and identified 15 genes that could contribute to the differences in salinity tolerance of these Chenopodium accessions.

Label-Based and Label-Free Strategies for Protein Quantitation

The precise quantification of changes between various physiological states in a biological system is highly complex in nature. Over the past few years, in combination with classical methods, mass spectrometry based approaches have become an indispensable tool in deciphering exact abundance of proteins in composite mixtures. The technique is now well established and employs both label-based and label-free quantitation strategies. Label-based quantitation methods utilize stable isotope labels which are incorporated within the peptides, introducing an expectable mass difference within the two or more experimental conditions. In contrast, label-free proteomics quantitates both relative and absolute protein quantity by utilizing signal intensity and spectral counting of peptides. This chapter focuses on the commonly used quantitative mass spectrometry methods for high-throughput proteomic analysis.

Secreted Glioblastoma Nanovesicles Contain Intracellular Signaling Proteins and Active Ras Incorporated in a Farnesylation-dependent Manner

Glioblastomas (GBMs) are malignant brain tumors with a median survival of less than 18 months. Redundancy of signaling pathways represented within GBMs contributes to their therapeutic resistance. Exosomes are extracellular nanovesicles released from cells and present in human biofluids that represent a possible biomarker of tumor signaling state that could aid in personalized treatment. Herein, we demonstrate that mouse GBM cell-derived extracellular nanovesicles resembling exosomes from an H-RasV12 myr-Akt mouse model for GBM are enriched for intracellular signaling cascade proteins (GO: 0007242) and Ras protein signal transduction (GO: 0007265), and contain active Ras. Active Ras isolated from human and mouse GBM extracellular nanovesicles lysates using the Ras-binding domain of Raf also coprecipitates with ESCRT (endosomal sorting complex required for transport)-associated exosome proteins Vps4a and Alix. Although we initially hypothesized a role for active Ras protein signaling in exosome biogenesis, we found that GTP binding of K-Ras was dispensable for its packaging within extracellular nanovesicles and for the release of Alix. By contrast, farnesylation of K-Ras was required for its packaging within extracellular nanovesicles, yet expressing a K-Ras farnesylation mutant did not decrease the number of nanovesicles or the amount of Alix protein released per cell. Overall, these results emphasize the primary importance of membrane association in packaging of extracellular nanovesicle factors and indicate that screening nanovesicles within human fluids could provide insight into tissue origin and the wiring of signaling proteins at membranes to predict onset and behavior of cancer and other diseases linked to deregulated membrane signaling states.

Glycosaminoglycanomics: where we are

Glycosaminoglycans regulate numerous physiopathological processes such as development, angiogenesis, innate immunity, cancer and neurodegenerative diseases. Cell surface GAGs are involved in cell-cell and cell-matrix interactions, cell adhesion and signaling, and host-pathogen interactions. GAGs contribute to the assembly of the extracellular matrix and heparan sulfate chains are able to sequester growth factors in the ECM. Their biological activities are regulated by their interactions with proteins. The structural heterogeneity of GAGs, mostly due to chemical modifications occurring during and after their synthesis, makes the development of analytical techniques for their profiling in cells, tissues, and biological fluids, and of computational tools for mining GAG-protein interaction data very challenging. We give here an overview of the experimental approaches used in glycosaminoglycomics, of the major GAG-protein interactomes characterized so far, and of the computational tools and databases available to analyze and store GAG structures and interactions.

Quantitative secretomic analysis of pancreatic cancer cells in serum-containing conditioned medium

Pancreatic cancer is a highly metastatic and chemo-resistant disease. Secreted proteins involved in cell-cell interactions play an important role in changing the tumor microenvironment. Previous studies generally focus on the secretome of cancer cell line from serum-free media, due to the serious interference of fetal bovine serum (FBS). However, serum-starvation may alter expression patterns of secreted proteins. Hence, efforts to decrease the interference of serum in proteomic analysis of serum-containing media have been hampered to quantitatively measure the tumor secretion levels. Recently, the metabolic labeling, protein equalization, protein fractionation and filter-aided sample preparation (FASP) strategy (MLEFF) has been successfully used to avoid the disturbance of serum on secretome analysis. Here, this efficient method was applied for comparative secretome analysis of two hamster pancreatic cancer cells with differentially metastatic potentials, enabling the observation of 161 differentially expressed proteins, including 106 proteins that had been previously reported and detected in plasma. By integrated analysis of our data and publicly available bioinformatics resources, we found that a combination panel consisting of CDH3, PLAU, and LFNG might improve the prognosis of overall pancreatic cancer survival. These secreted proteins may serve as a potential therapeutic targets for pancreatic cancer metastasis.

Protein content and functional characteristics of serum-purified exosomes from patients with colorectal cancer revealed by quantitative proteomics

Tumor cells of colorectal cancer (CRC) release exosomes into the circulation. These exosomes can mediate communication between cells and affect various tumor-related processes in their target cells. We present a quantitative proteomics analysis of the exosomes purified from serum of patients with CRC and normal volunteers; data are available via ProteomeXchange with identifier PXD003875. We identified 918 proteins with an overlap of 725 Gene IDs in the Exocarta proteins list. Compared with the serum-purified exosomes (SPEs) of normal volunteers, we found 36 proteins upregulated and 22 proteins downregulated in the SPEs of CRC patients. Bioinformatics analysis revealed that upregulated proteins are involved in processes that modulate the pretumorigenic microenvironment for metastasis. In contrast, differentially expressed proteins (DEPs) that play critical roles in tumor growth and cell survival were principally downregulated. Our study demonstrates that SPEs of CRC patients play a pivotal role in promoting the tumor invasiveness, but have minimal influence on putative alterations in tumor survival or proliferation. According to bioinformatics analysis, we speculate that the protein contents of exosomes might be associated with whether they are involved in premetastatic niche establishment or growth and survival of metastatic tumor cells. This information will be helpful in elucidating the pathophysiological functions of tumor-derived exosomes, and aid in the development of CRC diagnostics and therapeutics.

Extracellular vesicles in food: Experimental evidence of their secretion in grape fruits

In the last decade, the number of studies related with extracellular vesicles (EVs) has dramatically grown since their role as key part of intercellular communication has been confirmed. EVs, as transporter of distinct bioactive molecules, can take part in different physiological mechanisms and have been gaining attention as potential tools with a wide range of therapeutic effects. Whereas a high number of studies have been published related to mammalian derived EVs, including products as food source, the existence of EVs in plants still is controversial. Recent descriptions of vesicles derived from edible plants show that they might contain pharmacological active molecules. In this context, EVs from food are attracting increasing interest due to their relevance in modulating cellular processes (involved in health and disease), as well as therapeutic vehicles. The present work aims to summarize the current knowledge on exosomes in foods, actually limited to only four FAO groups (Milk, Starchy roots and tubers, Nuts and seeds, and Fruits). In addition, we have further characterized EVs isolated from grape berry juice by classical differential centrifugation, and described a preliminary dissection of their secretion in vivo.

Tissue enrichment analysis for C. elegans genomics

Background

Over the last ten years, there has been explosive development in methods for measuring gene expression. These methods can identify thousands of genes altered between conditions, but understanding these datasets and forming hypotheses based on them remains challenging. One way to analyze these datasets is to associate ontologies (hierarchical, descriptive vocabularies with controlled relations between terms) with genes and to look for enrichment of specific terms. Although Gene Ontology (GO) is available for Caenorhabditis elegans, it does not include anatomical information.

Results

We have developed a tool for identifying enrichment of C. elegans tissues among gene sets and generated a website GUI where users can access this tool. Since a common drawback to ontology enrichment analyses is its verbosity, we developed a very simple filtering algorithm to reduce the ontology size by an order of magnitude. We adjusted these filters and validated our tool using a set of 30 gold standards from Expression Cluster data in WormBase. We show our tool can even discriminate between embryonic and larval tissues and can even identify tissues down to the single-cell level. We used our tool to identify multiple neuronal tissues that are down-regulated due to pathogen infection in C. elegans.

Conclusions

Our Tissue Enrichment Analysis (TEA) can be found within WormBase, and can be downloaded using Python’s standard pip installer. It tests a slimmed-down C. elegans tissue ontology for enrichment of specific terms and provides users with a text and graphic representation of the results.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1229-9) contains supplementary material, which is available to authorized users.

GeneSCF: a real-time based functional enrichment tool with support for multiple organisms

Background

High-throughput technologies such as ChIP-sequencing, RNA-sequencing, DNA sequencing and quantitative metabolomics generate a huge volume of data. Researchers often rely on functional enrichment tools to interpret the biological significance of the affected genes from these high-throughput studies. However, currently available functional enrichment tools need to be updated frequently to adapt to new entries from the functional database repositories. Hence there is a need for a simplified tool that can perform functional enrichment analysis by using updated information directly from the source databases such as KEGG, Reactome or Gene Ontology etc.

Results

In this study, we focused on designing a command-line tool called GeneSCF (Gene Set Clustering based on Functional annotations), that can predict the functionally relevant biological information for a set of genes in a real-time updated manner. It is designed to handle information from more than 4000 organisms from freely available prominent functional databases like KEGG, Reactome and Gene Ontology. We successfully employed our tool on two of published datasets to predict the biologically relevant functional information. The core features of this tool were tested on Linux machines without the need for installation of more dependencies.

Conclusions

GeneSCF is more reliable compared to other enrichment tools because of its ability to use reference functional databases in real-time to perform enrichment analysis. It is an easy-to-integrate tool with other pipelines available for downstream analysis of high-throughput data. More importantly, GeneSCF can run multiple gene lists simultaneously on different organisms thereby saving time for the users. Since the tool is designed to be ready-to-use, there is no need for any complex compilation and installation procedures.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1250-z) contains supplementary material, which is available to authorized users.

Comprehensive Proteomic Analysis of Human Milk-derived Extracellular Vesicles Unveils a Novel Functional Proteome Distinct from Other Milk Components

Breast milk contains several macromolecular components with distinctive functions, whereby milk fat globules and casein micelles mainly provide nutrition to the newborn, and whey contains molecules that can stimulate the newborn's developing immune system and gastrointestinal tract. Although extracellular vesicles (EV) have been identified in breast milk, their physiological function and composition has not been addressed in detail. EV are submicron sized vehicles released by cells for intercellular communication via selectively incorporated lipids, nucleic acids, and proteins. Because of the difficulty in separating EV from other milk components, an in-depth analysis of the proteome of human milk-derived EV is lacking. In this study, an extensive LC-MS/MS proteomic analysis was performed of EV that had been purified from breast milk of seven individual donors using a recently established, optimized density-gradient-based EV isolation protocol. A total of 1963 proteins were identified in milk-derived EV, including EV-associated proteins like CD9, Annexin A5, and Flotillin-1, with a remarkable overlap between the different donors. Interestingly, 198 of the identified proteins are not present in the human EV database Vesiclepedia, indicating that milk-derived EV harbor proteins not yet identified in EV of different origin. Similarly, the proteome of milk-derived EV was compared with that of other milk components. For this, data from 38 published milk proteomic studies were combined in order to construct the total milk proteome, which consists of 2698 unique proteins. Remarkably, 633 proteins identified in milk-derived EV have not yet been identified in human milk to date. Interestingly, these novel proteins include proteins involved in regulation of cell growth and controlling inflammatory signaling pathways, suggesting that milk-derived EVs could support the newborn's developing gastrointestinal tract and immune system. Overall, this study provides an expansion of the whole milk proteome and illustrates that milk-derived EV are macromolecular components with a unique functional proteome.

Secretomic analysis of extracellular vesicles originating from polyomavirus-negative and polyomavirus-positive Merkel cell carcinoma cell lines

Extracellular vesicles or exosomes constitute an evolutionarily conserved mechanism of intercellular signaling. Exosomes are gaining an increasing amount of attention due to their role in pathologies, including malignancy, their importance as prognostic and diagnostic markers, and their potential as a therapeutic tool. Merkel cell carcinoma (MCC) is an aggressive form of skin cancer with a poor prognosis. Because an effective systemic treatment for this cancer type is currently not available, an exosome-based therapy was proposed. However, comprehensive secretome profiling has not been performed for MCC. To help unveil the putative contribution of exosomes in MCC, we studied the protein content of MCC-derived exosomes. Since approximately 80% of all MCC cases contain Merkel cell polyomavirus (MCPyV), the secretomes of two MCPyV-negative and two MCPyV-positive MCC cell lines were compared. We identified with high confidence 164 exosome-derived proteins common for all four cell lines that were annotated in ExoCarta and Vesiclepedia databases. These include proteins implicated in motility, metastasis and tumor progression, such as integrins and tetraspanins, intracellular signaling molecules, chaperones, proteasomal proteins, and translation factors. Additional virus-negative and virus-positive MCC cell lines should be examined to identify highly representative exosomal proteins that may provide reliable prognostic and diagnostic biomarkers, as well as targets for treatment in the future. Data are available via ProteomeXchange with identifier PXD004198.

Rectal 1% Tenofovir Gel Use Associates with Altered Epidermal Protein Expression

Rectal use of a 1% tenofovir (TFV) gel is currently being evaluated for HIV prevention. While careful assessment of mucosal safety of candidate microbicides is a primary concern, tools to assess mucosal toxicity are limited. Mass spectrometry-based proteomics is a sensitive and high-throughput technique that can provide in-depth information on inflammation processes in biological systems. In this study, we utilized a proteomics approach to characterize mucosal responses in study participants involved in a phase 1 clinical trial of a rectal TFV-based gel. Project Gel was a phase 1 randomized (1:1), double-blind, multisite, placebo-controlled trial in which 24 participants received rectal TFV or a universal placebo [hydroxyethyl cellulose (HEC)] over a course of 8 daily doses. Rectal mucosal swabs were collected after 0, 1, and 8 doses and were analyzed by label-free tandem mass spectrometry. Differential protein expression was evaluated using a combination of paired (time-effects) and unpaired (across study arm) t-tests, and multivariate [least absolute shrinkage and selection operator (LASSO)] modeling. Within the TFV arm, 7% (17/249, p < .05) and 10% (25/249, p < .05) of total proteins changed after 1 and 8 daily applications of TFV gel, respectively, compared to 3% (7/249, p < .05) and 6% (16/249, p < .05) in the HEC arm. Biofunctional analysis associated TFV use with a decrease in epidermal barrier proteins (adj. p = 1.21 × 10⁻¹⁰). Multivariate modeling identified 13 proteins that confidently separated TFV gel users (100% calibration and 96% cross-validation accuracy), including the epithelial integrity factors (FLMNB, CRNN, CALM), serpins (SPB13, SPB5), and cytoskeletal proteins (VILI, VIME, WRD1). This study suggested that daily rectal applications of a 1% TFV gel may be associated with mucosal proteome changes involving epidermal development. Further assessment of more extended use of TFV-gel is recommended to validate these initial associations.

The Role of Parathyroid Hormone-Related Protein (PTHrP) in Osteoblast Response to Microgravity: Mechanistic Implications for Osteoporosis Development

Prolonged skeletal unloading through bedrest results in bone loss similar to that observed in elderly osteoporotic patients, but with an accelerated timeframe. This rapid effect on weight-bearing bones is also observed in astronauts who can lose up to 2% of their bone mass per month spent in Space. Despite the important implications for Spaceflight travelers and bedridden patients, the exact mechanisms involved in disuse osteoporosis have not been elucidated. Parathyroid hormone-related protein (PTHrP) regulates many physiological processes including skeletal development, and has been proposed as a mechanosensor. To investigate the role of PTHrP in microgravity-induced bone loss, trabecular and calvarial osteoblasts (TOs and COs) from Pthrp^+/+ and ^-/- mice were subjected to actual Spaceflight for 6 days (Foton M3 satellite). Pthrp^+/+, ^+/- and ^-/- osteoblasts were also exposed to simulated microgravity for periods varying from 6 days to 6 weeks. While COs displayed little change in viability in 0g, viability of all TOs rapidly decreased in inverse proportion to PTHrP expression levels. Furthermore, Pthrp^+/+ TOs displayed a sharp viability decline after 2 weeks at 0g. Microarray analysis of Pthrp^+/+ TOs after 6 days in simulated 0g revealed expression changes in genes encoding prolactins, apoptosis/survival molecules, bone metabolism and extra-cellular matrix composition proteins, chemokines, insulin-like growth factor family members and Wnt-related signalling molecules. 88% of 0g-induced expression changes in Pthrp^+/+ cells overlapped those caused by Pthrp ablation in normal gravity, and pulsatile treatment with PTHrP_1-36 not only reversed a large proportion of 0g-induced effects in Pthrp^+/+ TOs but maintained viability over 6-week exposure to microgravity. Our results confirm PTHrP efficacy as an anabolic agent to prevent microgravity-induced cell death in TOs.

Network analysis reveals potential markers for pediatric adrenocortical carcinoma

Pediatric adrenocortical carcinoma (ACC) is a rare malignancy with a poor outcome. Molecular mechanisms of pediatric ACC oncogenesis and advancement are not well understood. Accurate and timely diagnosis of the disease requires identification of new markers for pediatric ACC. Differentially expressed genes (DEGs) were identified from the gene expression profile of pediatric ACC and obtained from Gene Expression Omnibus. Gene Ontology functional and pathway enrichment analysis was implemented to recognize the functions of DEGs. A protein–protein interaction (PPI) and gene–gene functional interaction (GGI) network of DEGs was constructed. Hub gene detection and enrichment analysis of functional modules were performed. Furthermore, a gene regulatory network incorporating DEGs–microRNAs–transcription factors was constructed and analyzed. A total of 431 DEGs including 228 upregulated and 203 downregulated DEGs were screened. These genes were largely involved in cell cycle, steroid biosynthesis, and p53 signaling pathways. Upregulated genes, CDK1, CCNB1, CDC20, and BUB1B, were identified as the common hubs of PPI and GGI networks. All the four common hub genes were also part of modules of the PPI network. Moreover, all the four genes were also present in the largest module of GGI network. A gene regulatory network consisting of 82 microRNAs and 100 transcription factors was also constructed. CDK1, CCNB1, CDC20, and BUB1B may serve as potential biomarker of pediatric ACC and as potential targets for therapeutic approach, although experimental studies are required to authenticate our findings.

Nanoparticle analysis sheds budding insights into genetic drivers of extracellular vesicle biogenesis

Background

Extracellular vesicles (EVs) are important mediators of cell-to-cell communication in healthy and pathological environments. Because EVs are present in a variety of biological fluids and contain molecular signatures of their cell or tissue of origin, they have great diagnostic and prognostic value. The ability of EVs to deliver biologically active proteins, RNAs and lipids to cells has generated interest in developing novel therapeutics. Despite their potential medical use, many of the mechanisms underlying EV biogenesis and secretion remain unknown.

Methods

Here, we characterized vesicle secretion across the NCI-60 panel of human cancer cells by nanoparticle tracking analysis. Using CellMiner, the quantity of EVs secreted by each cell line was compared to reference transcriptomics data to identify gene products associated with vesicle secretion.

Results

Gene products positively associated with the quantity of exosomal-sized vesicles included vesicular trafficking classes of proteins with Rab GTPase function and sphingolipid metabolism. Positive correlates of larger microvesicle-sized vesicle secretion included gene products involved in cytoskeletal dynamics and exocytosis, as well as Rab GTPase activation. One of the identified targets, CD63, was further evaluated for its role in vesicle secretion. Clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 knockout of the CD63 gene in HEK293 cells resulted in a decrease in small vesicle secretion, suggesting the importance of CD63 in exosome biogenesis.

Conclusion

These observations reveal new insights into genes involved in exosome and microvesicle formation, and may provide a means to distinguish EV sub-populations. This study offers a foundation for further exploration of targets involved in EV biogenesis and secretion.

Extracellular vesicles secreted by highly metastatic clonal variants of osteosarcoma preferentially localize to the lungs and induce metastatic behaviour in poorly metastatic clones

Osteosarcoma (OS) is the most common pediatric bone tumor and is associated with the emergence of pulmonary metastasis. Unfortunately, the mechanistic basis for metastasis remains unclear. Tumor-derived extracellular vesicles (EVs) have been shown to play critical roles in cell-to-cell communication and metastatic progression in other cancers, but their role in OS has not been explored. We show that EVs secreted by cells derived from a highly metastatic clonal variant of the KHOS cell line can be internalized by a poorly metastatic clonal variant of the same cell line and induce a migratory and invasive phenotype. This horizontal phenotypic transfer is unidirectional and provides evidence that metastatic potential may arise via interclonal co-operation. Proteomic analysis of the EVs secreted by highly metastatic OS clonal variants results in the identification of a number of proteins and G-protein coupled receptor signaling events as potential drivers of OS metastasis and novel therapeutic targets. Finally, multiphoton microscopy with fluorescence lifetime imaging in vivo, demonstrated a preferential seeding of lung tissue by EVs derived from highly metastatic OS clonal variants. Thus, we show that EVs derived from highly metastatic clonal variants of OS may drive metastatic behaviour via interclonal co-operation and preferential colonization of the lungs.

Secretome from resident cardiac stromal cells stimulates proliferation, cardiomyogenesis and angiogenesis of progenitor cells

In the heart, tissue-derived signals play a central role on recruiting/activating stem cell sources to induce cardiac lineage specification for maintenance of tissue homeostasis and repair. Cardiac resident stromal cells (CRSCs) may play a pivotal role in cardiac repair throughout their secretome. Here, we performed the characterization of CRSCs and their secretome by analyzing the composition of their culture-derived extracellular matrix (ECM) and conditioned medium (CM) and by investigating their potential effect on adipose-derived stem cell (ADSC) and progenitor cell behavior. We confirmed that CRSCs are a heterogeneous cell population whose secretome is composed by proteins related to cellular growth, immune response and cardiovascular development and function. We also observed that CRSC secretome was unable to change the behavior of ADSCs, except for proliferation. Additionally, CM from CRSCs demonstrated the potential to drive proliferation and cardiac differentiation of H9c2 cells and also the ability to induce angiogenesis in vitro. Our data suggest that the CRSCs can be a source of important modulating signals for cardiac progenitor cell recruitment/activation.

Proteomics analysis of vesicles isolated from plasma and urine of prostate cancer patients using a multiplex, aptamer-based protein array

Proteomics analysis of biofluid-derived vesicles holds enormous potential for discovering non-invasive disease markers. Obtaining vesicles of sufficient quality and quantity for profiling studies has, however, been a major problem, as samples are often replete with co-isolated material that can interfere with the identification of genuine low abundance, vesicle components. Here, we used a combination of ultracentrifugation and size-exclusion chromatography to isolate and analyse vesicles of plasma or urine origin. We describe a sample-handling workflow that gives reproducible, quality vesicle isolations sufficient for subsequent protein profiling. Using a semi-quantitative aptamer-based protein array, we identified around 1,000 proteins, of which almost 400 were present at comparable quantities in plasma versus urine vesicles. Significant differences were, however, apparent with elements like HSP90, integrin αVβ5 and Contactin-1 more prevalent in urinary vesicles, while hepatocyte growth factor activator, prostate-specific antigen–antichymotrypsin complex and many others were more abundant in plasma vesicles. This was also applied to a small set of specimens collected from men with metastatic prostate cancer, highlighting several proteins with the potential to indicate treatment refractory disease. The study provides a practical platform for furthering protein profiling of vesicles in prostate cancer, and, hopefully, many other disease scenarios.

Reliable FASP-based procedures for optimal quantitative proteomic and phosphoproteomic analysis on samples from acute myeloid leukemia patients

Background

Satisfactory sample preparation for mass spectrometry-based analysis is a critical step in the proteomics workflow. The quality and reproducibility of sample preparation can determine the coverage and confidence of proteomics results. Up to date, several methodologies have been described to produce suitable peptides for mass spectrometry analysis, followed by strategies for enrichment of post-translational modified peptides, if desired. Among them, the filter-aided sample preparation (FASP) has been introduced as a method to allow for removal of denaturants, reductants, alkylators, lipids and nucleic acids prior to trypsin digestion. Despite the high proteolytic digestion and contaminant removal efficiency described for this method, filter failure and consequently complete sample loss can discourage the use of this approach by the proteomic community.

Results

As judged by our quality controls, we were able to perform reliable and reproducible FASP for mass spectrometry analysis that allowed the quantification of 2141 proteins and 3694 phosphopeptides from as little as 20 and 320 μg of protein lysate from acute myeloid leukemia (AML) patients, respectively. Using the immobilized metal ion affinity chromatography (IMAC) method resulted in samples specifically enriched in phosphopeptides and allowed the quantification of a high number of both di- and multi-phosphopeptides in addition to the abundant mono-phosphopeptides. The workflows’ high reproducibility from three biological replicates was demonstrated by the similar number of quantified proteins and localized phosphosites, and confirmed by the similar distributions of their molecular functions. We found that the combination of the FASP procedure with StageTip mixed-mode fractionation and IMAC are excellent workflows for the reproducible and deep study of AML proteomes and phosphoproteomes, respectively.

Conclusions

The FASP procedure can be carried out without the risk of filter failure by performing a simple test of the filter quality before adding the protein sample. Herein, we demonstrate an efficient and reproducible FASP-based pipeline for the proteomic and phosphoproteomic analysis of AML patient samples which also can be used for the analysis of any other protein samples.

Electronic supplementary material

The online version of this article (doi:10.1186/s12575-016-0043-0) contains supplementary material, which is available to authorized users.

Bioinformatic analysis reveals the expression of unique transcriptomic signatures in Zika virus infected human neural stem cells

BACKGROUND

The single-stranded RNA Flavivirus, Zika virus (ZIKV), has recently re-emerged and spread rapidly across the western hemisphere's equatorial countries, primarily through Aedes mosquito transmission. While symptoms in adult infections appear to be self-limiting and mild, severe birth defects, such as microcephaly, have been linked to infection during early pregnancy. Recently, Tang et al. (Cell Stem Cell 2016, doi: 10.1016/j.stem.2016.02.016) demonstrated that ZIKV efficiently infects induced pluripotent stem cell (iPSC) derived human neural progenitor cells (hNPCs), resulting in cell cycle abnormalities and apoptosis. Consequently, hNPCs are a suggested ZIKV target.

METHODS

We analyzed the transcriptomic sequencing (RNA-seq) data (GEO: GSE78711) of ZIKV (Strain: MR766) infected hNPCs. For comparison to the ZIKV-infected hNPCs, the expression data from hNPCs infected with human cytomegalovirus (CMV) (Strain: AD169) was used (GEO: GSE35295). Utilizing a combination of Gene Ontology, database of human diseases, and pathway analysis, we generated a putative systemic model of infection supported by known molecular pathways of other highly related viruses.

RESULTS

We analyzed RNA-sequencing data for transcript expression alterations in ZIKV-infected hNPCs, and then compared them to expression patterns of iPSC-derived hNPCs infected with CMV, a virus that can also induce severe congenital neurological defects in developing fetuses. We demonstrate for the first time that many of cellular pathways correlate with clinical pathologies following ZIKV infection such as microcephaly, congenital nervous system disorders and epilepsy. Furthermore, ZIKV activates several inflammatory signals within infected hNPCs that are implicated in innate and acquired immune responses, while CMV-infected hNPCs showed limited representation of these pathways. Moreover, several genes related to pathogen responses are significantly upregulated upon ZIKV infection, but not perturbed in CMV-infected hNPCs.

CONCLUSION

The presented study is the first to report enrichment of numerous pro-inflammatory pathways in ZIKV-infected hNPCs, indicating that hNPCs are capable of signaling through canonical pro-inflammatory pathways following viral infection. By defining gene expression profiles, new factors in the pathogenesis of ZIKV were identified which could help develop new therapeutic strategies.

Peptide-mediated 'miniprep' isolation of extracellular vesicles is suitable for high-throughput proteomics

Extracellular vesicles (EVs) are cell-secreted membrane vesicles enclosed by a lipid bilayer derived from endosomes or from the plasma membrane. Since EVs are released into body fluids, and their cargo includes tissue-specific and disease-related molecules, they represent a rich source for disease biomarkers. However, standard ultracentrifugation methods for EV isolation are laborious, time-consuming, and require high inputs. Ghosh and co-workers recently described an isolation method utilizing Heat Shock Protein (HSP)-binding peptide Vn96 to aggregate HSP-decorated EVs, which can be performed at small 'miniprep' scale. Based on microscopic, immunoblot, and RNA sequencing analyses this method compared well with ultracentrifugation-mediated EV isolation, but a detailed proteomic comparison was lacking. Therefore, we compared both methods using label-free proteomics of replicate EV isolations from HT-29 cell-conditioned medium. Despite a 30-fold different scale (ultracentrifugation: 60 ml/Vn96-mediated aggregation: 2 ml) both methods yielded comparable numbers of identified proteins (3115/3085), with similar reproducibility of identification (72.5%/75.5%) and spectral count-based quantification (average CV: 31%/27%). EV fractions obtained with either method contained established EV markers and proteins linked to vesicle-related gene ontologies. Thus, Vn96 peptide-mediated aggregation is an advantageous, simple and rapid approach for EV isolation from small biological samples, enabling high-throughput analysis in a biomarker discovery setting.

Serum-derived exosomes from non-viremic animals previously exposed to the porcine respiratory and reproductive virus contain antigenic viral proteins

PRRSV is the etiological agent of one of the most important swine diseases with a significant economic burden worldwide and limitations in vaccinology. Exosomes are 30-100 nm vesicles of endocytic origin. Remarkably, immunizations with exosomes containing antigens from tumors or pathogens are capable of eliciting protective immune responses, albeit variably, in cancer and infectious diseases. Here we describe the isolation, molecular composition and immunogenicity of serum-derived exosomes from naïve animals, from PRRSV viremic animals and from animals previously PRRSV infected but already free of viruses (non viremic). Exosomes were isolated through size exclusion chromatography and characterized by different methodologies. Exosome-enriched fractions from naïve and natural infected animals contained classical tetraspanin exosomal markers (CD63 and CD81) and high concentrations of particles in the size-range of exosomes as detected by nanoparticle tracking analysis and cryo-TEM. NanoLC-MS/MS was used to identify viral antigens associated to exosomes. PRRSV-proteins were detected in serum samples from only viremic animals and from animals previously infected already free of viruses (non-viremic), but not in controls. Moreover, immune sera from pigs previously exposed to PRRSV specifically reacted against exosomes purified from non-viremic pig sera in a dose-dependent manner, a reactivity not detected when naïve sera was used in the assay. To facilitate future studies, a scaling-up process was implemented. To the best of our knowledge, this is the first molecular characterization of serum-derived exosomes from naïve pigs and pigs actively or previously infected with PRRSV. The presence of antigenic viral proteins in serum-derived exosomes free of virus, suggest their use as a novel vaccine approach against PRRSV.

Plasma-derived Extracellular Vesicles Contain Predictive Biomarkers and Potential Therapeutic Targets for Myocardial Ischemic (MI) Injury

Myocardial infarction (MI) triggers a potent inflammatory response via the release of circulatory mediators, including extracellular vesicles (EVs) by damaged cardiac cells, necessary for myocardial healing. Timely repression of inflammatory response are critical to prevent and minimize cardiac tissue injuries, nonetheless, progression in this aspect remains challenging. The ability of EVs to trigger a functional response upon delivery of carried bioactive cargos, have made them clinically attractive diagnostic biomarkers and vectors for therapeutic interventions. Using label-free quantitative proteomics approach, we compared the protein cargo of plasma EVs between patients with MI and from patients with stable angina (NMI). We report, for the first time, the proteomics profiling on 252 EV proteins that were modulated with >1.2-fold after MI. We identified six up-regulated biomarkers with potential for clinical applications; these reflected post-infarct pathways of complement activation (Complement C1q subcomponent subunit A (C1QA), 3.23-fold change, p = 0.012; Complement C5 (C5), 1.27-fold change, p = 0.087), lipoprotein metabolism (Apoliporotein D (APOD), 1.86-fold change, p = 0.033; Apolipoprotein C-III (APOCC3), 2.63-fold change, p = 0.029) and platelet activation (Platelet glycoprotein Ib alpha chain (GP1BA), 9.18-fold change, p < 0.0001; Platelet basic protein (PPBP), 4.72-fold change, p = 0.027). The data have been deposited to the ProteomeXchange with identifier PXD002950. This novel biomarker panel was validated in 43 patients using antibody-based assays (C1QA (p = 0.005); C5 (p = 0.0047), APOD (p = 0.0267); APOC3 (p = 0.0064); GP1BA (p = 0.0031); PPBP (p = 0.0465)). We further present that EV-derived fibrinogen components were paradoxically down-regulated in MI, suggesting that a compensatory mechanism may suppress post-infarct coagulation pathways, indicating potential for therapeutic targeting of this mechanism in MI. Taken together, these data demonstrated that plasma EVs contain novel diagnostic biomarkers and therapeutic targets that can be further developed for clinical use to benefit patients with coronary artery diseases (CADs).

Enrichment of extracellular vesicles from tissues of the central nervous system by PROSPR

BACKGROUND

Extracellular vesicles (EVs) act as key mediators of intercellular communication and are secreted and taken up by all cell types in the central nervous system (CNS). While detailed study of EV-based signaling is likely to significantly advance our understanding of human neurobiology, the technical challenges of isolating EVs from CNS tissues have limited their characterization using 'omics' technologies. We therefore developed a new Protein Organic Solvent Precipitation (PROSPR) method that can efficiently isolate the EV repertoire from human biological samples.

RESULTS

In the current report, we present a novel experimental workflow that outlines the process of sample extraction and enrichment of CNS-derived EVs using PROSPR. Subsequent LC-MS/MS-based proteomic profiling of EVs enriched from brain homogenates successfully identified 86 of the top 100 exosomal markers. Proteomic profiling of PROSPR-enriched CNS EVs indicated that > 75 % of the proteins identified matched previously reported exosomal and microvesicle cargoes, while also expanded the known human EV-associated proteome with 685 novel identifications. Similarly, lipidomic characterization of enriched CNS vesicles not only identified previously reported EV-specific lipid families (PS, SM, lysoPC, lysoPE) but also uncovered novel lipid isoforms not previously detected in human EVs. Finally, dedicated flow cytometry of PROSPR-CNS-EVs revealed that ~80 % of total microparticles observed were exosomes ranging in diameter from ≤100 nm to 300 nm.

CONCLUSIONS

These data demonstrate that the optimized use of PROSPR represents an easy-to-perform and inexpensive method of enriching EVs from human CNS tissues for detailed characterization by 'omics' technologies. We predict that widespread use of the methodology described herein will greatly accelerate the study of EVs biology in neuroscience.

Reducing the cost of semi-automated in-gel tryptic digestion and GeLC sample preparation for high-throughput proteomics

Peptide generation by trypsin digestion is typically the first step in mass spectrometry-based proteomics experiments, including 'bottom-up' discovery and targeted proteomics using multiple reaction monitoring. Manual tryptic digest and the subsequent clean-up steps can add variability even before the sample reaches the analytical platform. While specialized filter plates and tips have been designed for automated sample processing, the specialty reagents required may not be accessible or feasible due to their high cost. Here, we report a lower-cost semi-automated protocol for in-gel digestion and GeLC using standard 96-well microplates. Further cost savings were realized by re-using reagent tips with optimized sample ordering. To evaluate the methodology, we compared a simple mixture of 7 proteins and a complex cell-lysate sample. The results across three replicates showed that our semi-automated protocol had performance equal to or better than a manual in-gel digestion with respect to replicate variability and level of contamination. In this paper, we also provide the Agilent Bravo method file, which can be adapted to other liquid handlers. The simplicity, reproducibility, and cost-effectiveness of our semi-automated protocol make it ideal for routine in-gel and GeLC sample preparations, as well as high throughput processing of large clinical sample cohorts.

Plasma proteome coverage is increased by unique peptide recovery from sodium deoxycholate precipitate

The ionic detergent sodium deoxycholate (SDC) is compatible with in-solution tryptic digestion and LC-MS/MS-based shotgun proteomics by virtue of being easy to separate from the peptide products via precipitation in acidic buffers. However, it remains unclear whether unique human peptides co-precipitate with SDC during acid treatment of complex biological samples. In this study, we demonstrate for the first time that a large quantity of unique peptides in human blood plasma can be co-precipitated with SDC using an optimized sample preparation method prior to shotgun proteomic analysis. We show that the plasma peptides co-precipitated with SDC can be successfully recovered using a sequential re-solubilization and precipitation procedure, and that this approach is particularly efficient at the extraction of long peptides. Recovery of peptides from the SDC pellet dramatically increased overall proteome coverage (>60 %), thereby improving the identification of low-abundance proteins and enhancing the identification of protein components of membrane-bound organelles. In addition, when we analyzed the physiochemical properties of the co-precipitated peptides, we observed that SDC-based sample preparation improved the identification of mildly hydrophilic/hydrophobic proteins that would otherwise be lost upon discarding the pellet. These data demonstrate that the optimized SDC protocol is superior to sodium dodecyl sulfate (SDS)/urea treatment for identifying plasma biomarkers by shotgun proteomics.

Colorectal cancer atlas: An integrative resource for genomic and proteomic annotations from colorectal cancer cell lines and tissues

In order to advance our understanding of colorectal cancer (CRC) development and progression, biomedical researchers have generated large amounts of OMICS data from CRC patient samples and representative cell lines. However, these data are deposited in various repositories or in supplementary tables. A database which integrates data from heterogeneous resources and enables analysis of the multidimensional data sets, specifically pertaining to CRC is currently lacking. Here, we have developed Colorectal Cancer Atlas (http://www.colonatlas.org), an integrated web-based resource that catalogues the genomic and proteomic annotations identified in CRC tissues and cell lines. The data catalogued to-date include sequence variations as well as quantitative and non-quantitative protein expression data. The database enables the analysis of these data in the context of signaling pathways, protein–protein interactions, Gene Ontology terms, protein domains and post-translational modifications. Currently, Colorectal Cancer Atlas contains data for >13 711 CRC tissues, >165 CRC cell lines, 62 251 protein identifications, >8.3 million MS/MS spectra, >18 410 genes with sequence variations (404 278 entries) and 351 pathways with sequence variants. Overall, Colorectal Cancer Atlas has been designed to serve as a central resource to facilitate research in CRC.