Human Proteinpedia as a resource for clinical proteomics

Neurodevelopmental and neuropsychiatric disorders represent an interconnected molecular system

Many putative genetic factors that confer risk to neurodevelopmental disorders such as autism spectrum disorders (ASDs) and X-linked intellectual disability (XLID), and to neuropsychiatric disorders including attention deficit hyperactivity disorder (ADHD) and schizophrenia (SZ) have been identified in individuals from diverse human populations. Although there is significant aetiological heterogeneity within and between these conditions, recent data show that genetic factors contribute to their comorbidity. Many studies have identified candidate gene associations for these mental health disorders, albeit this is often done in a piecemeal fashion with little regard to the inherent molecular complexity. Here, we sought to abstract relationships from our knowledge of systems level biology to help understand the unique and common genetic drivers of these conditions. We undertook a global and systematic approach to build and integrate available data in gene networks associated with ASDs, XLID, ADHD and SZ. Complex network concepts and computational methods were used to investigate whether candidate genes associated with these conditions were related through mechanisms of gene regulation, functional protein-protein interactions, transcription factor (TF) and microRNA (miRNA) binding sites. Although our analyses show that genetic variations associated with the four disorders can occur in the same molecular pathways and functional domains, including synaptic transmission, there are patterns of variation that define significant differences between disorders. Of particular interest is DNA variations located in intergenic regions that comprise regulatory sites for TFs or miRNA. Our approach provides a hypothetical framework, which will help discovery and analysis of candidate genes associated with neurodevelopmental and neuropsychiatric disorders.

A multilectin affinity approach for comparative glycoprotein profiling of rheumatoid arthritis and spondyloarthropathy

Background

Arthritis refers to inflammation of joints and includes common disorders such as rheumatoid arthritis (RA) and spondyloarthropathies (SpAs). These diseases differ mainly in terms of their clinical manifestations and the underlying pathogenesis. Glycoproteins in synovial fluid might reflect the disease activity status in the joints affected by arthritis; yet they have not been systematically studied previously. Although markers have been described for assisting in the diagnosis of RA, there are currently no known biomarkers for SpA.

Materials and methods

We sought to determine the relative abundance of glycoproteins in RA and SpA by lectin affinity chromatography coupled to iTRAQ labeling and LC-MS/MS analysis. We also used ELISA to validate the overexpression of VCAM-1, one of the candidate proteins identified in this study, in synovial fluid from RA patients.

Results and discussion

We identified proteins that were previously reported to be overexpressed in RA including metalloproteinase inhibitor 1 (TIMP1), myeloperoxidase (MPO) and several S100 proteins. In addition, we discovered several novel candidates that were overexpressed in SpA including Apolipoproteins C-II and C-III and the SUN domain-containing protein 3 (SUN3). Novel molecules found overexpressed in RA included extracellular matrix protein 1 (ECM1) and lumican (LUM). We validated one of the candidate biomarkers, vascular cell adhesion molecule 1 (VCAM1), in 20 RA and SpA samples using ELISA and confirmed its overexpression in RA (p-value <0.01). Our quantitative glycoproteomic approach to study arthritic disorders should open up new avenues for additional proteomics-based discovery studies in rheumatological disorders.

Vesiclepedia: a compendium for extracellular vesicles with continuous community annotation

Extracellular vesicles (EVs) are membraneous vesicles released by a variety of cells into their microenvironment. Recent studies have elucidated the role of EVs in intercellular communication, pathogenesis, drug, vaccine and gene-vector delivery, and as possible reservoirs of biomarkers. These findings have generated immense interest, along with an exponential increase in molecular data pertaining to EVs. Here, we describe Vesiclepedia, a manually curated compendium of molecular data (lipid, RNA, and protein) identified in different classes of EVs from more than 300 independent studies published over the past several years. Even though databases are indispensable resources for the scientific community, recent studies have shown that more than 50% of the databases are not regularly updated. In addition, more than 20% of the database links are inactive. To prevent such database and link decay, we have initiated a continuous community annotation project with the active involvement of EV researchers. The EV research community can set a gold standard in data sharing with Vesiclepedia, which could evolve as a primary resource for the field.

The development of selected reaction monitoring methods for targeted proteomics via empirical refinement

Software advancements in the last several years have had a significant impact on proteomics from method development to data analysis. Herein, we detail a method, which uses our in-house developed software tool termed Skyline, for empirical refinement of candidate peptides from targeted proteins. The method consists of four main steps from generation of a testable hypothesis, method development, peptide refinement, to peptide validation. The ultimate goal is to identify the best performing peptide in terms of ionization efficiency, reproducibility, specificity, and chromatographic characteristics to monitor as a proxy for protein abundance. It is important to emphasize that this method allows the user to perform this refinement procedure in the sample matrix and organism of interest with the instrumentation available. Finally, the method is demonstrated in a case study to determine the best peptide to monitor the abundance of surfactant protein B in lung aspirates.

Identifying mutated proteins secreted by colon cancer cell lines using mass spectrometry

Secreted proteins encoded by mutated genes (mutant proteins) are a particularly rich source of biomarkers being not only components of the cancer secretome but also actually implicated in tumorigenesis. One of the challenges of proteomics-driven biomarker discovery research is that the bulk of secreted mutant proteins cannot be identified directly and quantified by mass spectrometry due to the lack of mutated peptide information in extant proteomics databases. Here we identify, using an integrated genomics and proteomics strategy (referred to iMASp - identification of Mutated And Secreted proteins), 112 putative mutated tryptic peptides (corresponding to 57 proteins) in the collective secretomes derived from a panel of 18 human colorectal cancer (CRC) cell lines. Central to this iMASp was the creation of Human Protein Mutant Database (HPMD), against which experimentally-derived secretome peptide spectra were searched. Eight of the identified mutated tryptic peptides were confirmed by RT-PCR and cDNA sequencing of RNA extracted from those CRC cells from which the mutation was identified by mass spectrometry. The iMASp technology promises to improve the link between proteomics and genomic mutation data thereby providing an effective tool for targeting tryptic peptides with mutated amino acids as potential cancer biomarker candidates. This article is part of a Special Issue entitled: Integrated omics.

Investigating protein isoforms via proteomics: a feasibility study

Alternative splicing (AS) and processing of pre-messenger RNAs explains the discrepancy between the number of genes and proteome complexity in multicellular eukaryotic organisms. However, relatively few alternative protein isoforms have been experimentally identified, particularly at the protein level. In this study, we assess the ability of proteomics to inform on differently spliced protein isoforms in human and four other model eukaryotes. The number of Ensembl-annotated genes for which proteomic data exists that informs on AS exceeds 33% of the alternately spliced genes in the human and worm genomes. Examining AS in chicken via proteomics for the first time, we find support for over 600 AS genes. However, although peptide identifications support only a small fraction of alternative protein isoforms that are annotated in Ensembl, many more variants are amenable to proteomic identification. There remains a sizeable gap between these existing identifications (10-52% of AS genes) and those that are theoretically feasible (90-99%). We also compare annotations between Swiss-Prot and Ensembl, recommending use of both to maximize coverage of AS. We propose that targeted proteomic experiments using selected reactions and standards are essential to uncover further alternative isoforms and discuss the issues surrounding these strategies.

Exosomes: proteomic insights and diagnostic potential

Exosomes are 40-100-nm diameter membrane vesicles of endocytic origin that are released by most cell types upon fusion of multivesicular bodies with the plasma membrane, presumably as a vehicle for cell-free intercellular communication. While early studies focused on their secretion from diverse cell types in vitro, exosomes have now been identified in body fluids such as urine, amniotic fluid, malignant ascites, bronchoalveolar lavage fluid, synovial fluid, breast milk, saliva and blood. Exosomes have pleiotropic biological functions, including immune response, antigen presentation, intracellular communication and the transfer of RNA and proteins. While they have also been implicated in the transport and propagation of infectious cargo, such as prions, and retroviruses, including HIV, suggesting a role in pathological situations, recent studies suggest that the presence of such infectious cargo may be artefacts of exosome-purification strategies. Improvements in mass spectrometry-based proteomic tools, both hardware and software, coupled with improved purification schemes for exosomes, has allowed more in-depth proteome analyses, contributing immensely to our understanding of the molecular composition of exosomes. Proteomic cataloguing of exosomes from diverse cell types has revealed a common set of membrane and cytosolic proteins, suggesting the evolutionary importance of these membrane particles. Additionally, exosomes express an array of proteins that reflect the originating host cell. Recent findings that exosomes contain inactive forms of both mRNA and microRNA that can be transferred to another cell and be functional in that new environment, have initiated many microRNA profiling studies of exosomes circulating in blood. These studies highlight the potential of exosomal microRNA profiles for use as diagnostic biomarkers of disease through a noninvasive blood test. The exacerbated release of exosomes in tumor cells, as evidenced by their increased levels in blood during the late stage of a disease and their overexpression of certain tumor cell biomarkers, suggests an important role of exosomes in diagnosis and biomarker studies. The aim of this article is to provide a brief overview of exosomes, including methods used to isolate and characterize exosomes. New advances in proteomic methods, and both mass spectrometry hardware and informatics tools will be covered briefly.

SysPIMP: the web-based systematical platform for identifying human disease-related mutated sequences from mass spectrometry

Some mutations resulting in protein sequence change might be tightly related to certain human diseases by affecting its roles, such as sickle cell anemia. Until now several databases, such as PMD, OMIM and HGMD, have been developed, providing useful information about human disease-related mutation. Tandem mass spectrometry (MS) has been used for characterizing proteins in various conditions; however, there is no system in place for finding disease-related mutated proteins within the MS results. Here, a Systematical Platform for Identifying Mutated Proteins (SysPIMP; http://pimp.starflr.info/) was developed to efficiently identify human disease-related mutated proteins within MS results. SysPIMP comprises of three layers: (i) a standardized data warehouse, (ii) a pipeline layer for maintaining human disease databases and X!Tandem and BLAST and (iii) a web-based interface. From OMIM AV part, PMD and SwissProt databases, 35,497 non-redundant human disease-related mutated sequences were collected with disease information described by OMIM terms. With the interfaces to browse sequences archived in SysPIMP, X!Tandem, an open source database-search engine used to identify proteins within MS data, was integrated into SysPIMP to help support the detection of potential human disease-related mutants in MS results. In addition, together with non-redundant disease-related mutated sequences, original non-mutated sequences are also provided in SysPIMP for comparative research. Based on this system, SysPIMP will be the platform for efficiently and intensively studying human diseases caused by mutation.

The use of gene array technology and proteomics in the search of new targets of diseases for therapeutics

The advent of functional genomics has been greatly broadening our view and accelerating our way in numerous medical research fields. The complete genomic data acquired from the human genome project and the desperate clinical need of comprehensive analytical tools to study complex diseases, has allowed rapid evolution of genomic and proteomic technologies, speeding the rate and number of discoveries in new biomarkers. By jointly using genomics, proteomics and bioinformatics there is a great potential to make considerable contribution to biomarker identification and to revolutionize both the development of new therapies and drug development process.

Integrating genomics across drug discovery and development

The sequencing of the human genome was an exceptional achievement, but it was not an end in itself as it set the foundation for building new knowledge in biology and medicine. The laborious, multifaceted science of drug discovery and development also draws tremendous benefits from mining the human genome and exploiting the large palette of genomic technologies. This article discusses how diverse genomic tools have been used to date and how they will continue to be utilized in the future to impact drug discovery and development. Integrating genomics across drug discovery and development will undoubtedly help to shorten timelines, increase success rates at all stages and ultimately bring the right drugs to the right patients at the right times.