Human Proteinpedia enables sharing of human protein data

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.

Overexpression of ribosome binding protein 1 (RRBP1) in breast cancer

The molecular events that lead to malignant transformation and subsequent metastasis of breast carcinoma include alterations in the cells at genome, transcriptome and proteome levels. In this study, we used publicly available gene expression databases to identify those candidate genes which are upregulated at the mRNA level in breast cancers but have not been systematically validated at the protein level. Based on an extensive literature search, we identified ribosome binding protein 1 (RRBP1) as a candidate that is upregulated at the mRNA level in five different studies but its protein expression had not been investigated. Immunohistochemical labeling of breast cancer tissue microarrays was carried out to determine the expression of RRBP1 in a large panel of breast cancers. We found that RRBP1 was overexpressed in 84% (177/219) of breast carcinoma cases tested. The subcellular localization of RRBP1 was mainly observed to be in the cytoplasm with intense staining in the perinuclear region. Our findings suggest that RRBP1 is an interesting molecule that can be further studied for its potential to serve as a breast cancer biomarker. This study also demonstrates how the integration of biological data from available resources in conjunction with systematic evaluation approaches can be successfully applied to clinical proteomics.

Overexpression of Kinesin Associated Protein 3 (KIFAP3) in Breast Cancer

Gene expression profiling studies on breast cancer have generated catalogs of differentially expressed genes. However, many of these genes have not been investigated for their expression at the protein level. It is possible to systematically evaluate such genes in a high-throughput fashion for their overexpression at the protein level using breast cancer tissue microarrays. Our strategy involved integration of information from publicly available repositories of gene expression to prepare a list of genes upregulated at the mRNA level in breast cancer followed by curation of the published literature to identify those genes that were not tested for overexpression at the protein level. We identified Kinesin Associated Protein 3 (KIFAP3) as one such molecule for further validation at the protein level. Immunohistochemical labeling of KIFAP3 using breast cancer tissue microarrays revealed overexpression of KIFAP3 protein in 84% (240/285) of breast cancers indicating the utility of our integrated approach of combining computational analysis with experimental biology.

ExoCarta as a resource for exosomal research

Exosomes are a class of extracellular vesicles that are secreted by various cell types. Unlike other extracellular vesicles (ectosomes and apoptotic blebs), exosomes are of endocytic origin. The roles of exosomes in vaccine/drug delivery, intercellular communication and as a possible source of disease biomarkers have sparked immense interest in them, resulting in a plethora of studies. Whilst multidimensional datasets are continuously generated, it is difficult to harness the true potential of the data until they are compiled and made accessible to the biomedical researchers. Here, we describe ExoCarta (http://www.exocarta.org), a manually curated database of exosomal proteins, RNA and lipids. Datasets currently present in ExoCarta are integrated from both published and unpublished exosomal studies. Since its launch in 2009, ExoCarta has been accessed by more than 16,000 unique users. In this article, we discuss the utility of ExoCarta for exosomal research and urge biomedical researchers in the field to deposit their datasets directly to ExoCarta.

Multiplex targeted proteomic assay for biomarker detection in plasma: a pancreatic cancer biomarker case study

Biomarkers are most frequently proteins that are measured in the blood. Their development largely relies on antibody creation to test the protein candidate performance in blood samples of diseased versus nondiseased patients. The creation of such antibody assays has been a bottleneck in biomarker progress due to the cost, extensive time, and effort required to complete the task. Targeted proteomics is an emerging technology that is playing an increasingly important role to facilitate disease biomarker development. In this study, we applied a SRM-based targeted proteomics platform to directly detect candidate biomarker proteins in plasma to evaluate their clinical utility for pancreatic cancer detection. The characterization of these protein candidates used a clinically well-characterized cohort that included plasma samples from patients with pancreatic cancer, chronic pancreatitis, and healthy age-matched controls. Three of the five candidate proteins, including gelsolin, lumican, and tissue inhibitor of metalloproteinase 1, demonstrated an AUC value greater than 0.75 in distinguishing pancreatic cancer from the controls. In addition, we provide an analysis of the reproducibility, accuracy, and robustness of the SRM-based proteomics platform. This information addresses important technical issues that could aid in the adoption of the targeted proteomics platform for practical clinical utility.

Proteomics and pluripotency

The fields of mass spectrometry (MS) and stem cell biology have expanded greatly in the past twenty years. Taken alone, these fields occupy entirely different branches of science; however, the points where they overlap provide valuable insight, both in the biological and technical arenas. From a biological perspective, MS-based proteomics offers the capacity to follow post-transcriptional regulation and signaling that are (1) fundamental to pluripotency and differentiation, (2) largely beyond the reach of genomic technologies, and (3) otherwise difficult or impossible to examine on a large scale. At the same time, addressing questions fundamental to stem cell biology has compelled proteomic researchers to pursue more sensitive and creative ways to probe the proteome, both in a targeted and high-throughput manner. Here, we highlight experiments that straddle proteomics and stem cell biology, with an emphasis on studies that apply mass spectrometry to dissect pluripotency and differentiation.

An activation force-based affinity measure for analyzing complex networks

Affinity measure is a key factor that determines the quality of the analysis of a complex network. Here, we introduce a type of statistics, activation forces, to weight the links of a complex network and thereby develop a desired affinity measure. We show that the approach is superior in facilitating the analysis through experiments on a large-scale word network and a protein-protein interaction (PPI) network consisting of ∼5,000 human proteins. The experiment on the word network verifies that the measured word affinities are highly consistent with human knowledge. Further, the experiment on the PPI network verifies the measure and presents a general method for the identification of functionally similar proteins based on PPIs. Most strikingly, we find an affinity network that compactly connects the cancer-associated proteins to each other, which may reveal novel information for cancer study; this includes likely protein interactions and key proteins in cancer-related signal transduction pathways.

ExoCarta 2012: database of exosomal proteins, RNA and lipids

Exosomes are membraneous nanovesicles of endocytic origin released by most cell types from diverse organisms; they play a critical role in cell-cell communication. ExoCarta (http://www.exocarta.org) is a manually curated database of exosomal proteins, RNA and lipids. The database catalogs information from both published and unpublished exosomal studies. The mode of exosomal purification and characterization, the biophysical and molecular properties are listed in the database aiding biomedical scientists in assessing the quality of the exosomal preparation and the corresponding data obtained. Currently, ExoCarta (Version 3.1) contains information on 11,261 protein entries, 2375 mRNA entries and 764 miRNA entries that were obtained from 134 exosomal studies. In addition to the data update, as a new feature, lipids identified in exosomes are added to ExoCarta. We believe that this free web-based community resource will aid researchers in identifying molecular signatures (proteins/RNA/lipids) that are specific to certain tissue/cell type derived exosomes and trigger new exosomal studies.

Quantitative tissue proteomics of esophageal squamous cell carcinoma for novel biomarker discovery

Esophageal squamous cell carcinoma (ESCC) is among the top ten most frequent malignancies worldwide. In this study, our objective was to identify potential biomarkers for ESCC through a quantitative proteomic approach using the isobaric tags for relative and absolute quantitation (iTRAQ) approach. We compared the protein expression profiles of ESCC tumor tissues with the corresponding adjacent normal tissue from ten patients. LC-MS/MS analysis of strong cation exchange chromatography fractions was carried out on an Accurate Mass QTOF mass spectrometer, which led to the identification of 687 proteins. In all, 257 proteins were identified as differentially expressed in ESCC as compared to normal. We found several previously known protein biomarkers to be upregulated in ESCC including thrombospondin 1 (THBS1), periostin 1 (POSTN) and heat shock 70 kDa protein 9 (HSPA9) confirming the validity of our approach. In addition, several novel proteins that had not been reported previously were identified in our screen. These novel biomarker candidates included prosaposin (PSAP), plectin 1 (PLEC1) and protein disulfide isomerase A 4 (PDIA4) that were further validated to be overexpressed by immunohistochemical labeling using tissue microarrays. The success of our study shows that this mass spectrometric strategy can be applied to cancers in general to develop a panel of candidate biomarkers, which can then be validated by other techniques.

Human protein reference database and human proteinpedia as discovery resources for molecular biotechnology

In the recent years, research in molecular biotechnology has transformed from being small scale studies targeted at a single or a small set of molecule(s) into a combination of high throughput discovery platforms and extensive validations. Such a discovery platform provided an unbiased approach which resulted in the identification of several novel genetic and protein biomarkers. High throughput nature of these investigations coupled with higher sensitivity and specificity of Next Generation technologies provided qualitatively and quantitatively richer biological data. These developments have also revolutionized biological research and speed of data generation. However, it is becoming difficult for individual investigators to directly benefit from this data because they are not easily accessible. Data resources became necessary to assimilate, store and disseminate information that could allow future discoveries. We have developed two resources--Human Protein Reference Database (HPRD) and Human Proteinpedia, which integrate knowledge relevant to human proteins. A number of protein features including protein-protein interactions, post-translational modifications, subcellular localization, and tissue expression, which have been studied using different strategies were incorporated in these databases. Human Proteinpedia also provides a portal for community participation to annotate and share proteomic data and uses HPRD as the scaffold for data processing. Proteomic investigators can even share unpublished data in Human Proteinpedia, which provides a meaningful platform for data sharing. As proteomic information reflects a direct view of cellular systems, proteomics is expected to complement other areas of biology such as genomics, transcriptomics, molecular biology, cloning, and classical genetics in understanding the relationships among multiple facets of biological systems.

A comprehensive map of the human urinary proteome

The study of the human urinary proteome has the potential to offer significant insights into normal physiology as well as disease pathology. The information obtained from such studies could be applied to the diagnosis of various diseases. The high sensitivity, resolution, and mass accuracy of the latest generation of mass spectrometers provides an opportunity to accurately catalog the proteins present in human urine, including those present at low levels. To this end, we carried out a comprehensive analysis of human urinary proteome from healthy individuals using high-resolution Fourier transform mass spectrometry. Importantly, we used the Orbitrap for detecting ions in both MS (resolution 60 000) and MS/MS (resolution 15 000) modes. To increase the depth of our analysis, we characterized both unfractionated as well as lectin-enriched proteins in our experiments. In all, we identified 1,823 proteins with less than 1% false discovery rate, of which 671 proteins have not previously been reported as constituents of human urine. This data set should serve as a comprehensive reference list for future studies aimed at identification and characterization of urinary biomarkers for various diseases.

Proteomic approaches to understanding the role of the cytoskeleton in host-defense mechanisms

The cytoskeleton is a cellular scaffolding system whose functions include maintenance of cellular shape, enabling cellular migration, division, intracellular transport, signaling and membrane organization. In addition, in immune cells, the cytoskeleton is essential for phagocytosis. Following the advances in proteomics technology over the past two decades, cytoskeleton proteome analysis in resting and activated immune cells has emerged as a possible powerful approach to expand our understanding of cytoskeletal composition and function. However, so far there have only been a handful of studies of the cytoskeleton proteome in immune cells. This article considers promising proteomics strategies that could augment our understanding of the role of the cytoskeleton in host-defense mechanisms.

Proteomics for development of vaccine

The success of genome projects has provided us with a vast amount of information on genes of many pathogenic species and has raised hopes for rapid progress in combating infectious diseases, both by construction of new effective vaccines and by creating a new generation of therapeutic drugs. Proteomics, a strategy complementary to the genomic-based approach, when combined with immunomics (looking for immunogenic proteins) and vaccinomics (characterization of host response to immunization), delivers valuable information on pathogen-host cell interaction. It also speeds the identification and detailed characterization of new antigens, which are potential candidates for vaccine development. This review begins with an overview of the global status of vaccinology based on WHO data. The main part of this review describes the impact of proteomic strategies on advancements in constructing effective antibacterial, antiviral and anticancer vaccines. Diverse aspects of disease mechanisms and disease preventions have been investigated by proteomics.

Absolute quantification of protein and post-translational modification abundance with stable isotope-labeled synthetic peptides

In the analysis of biological systems, it is of interest to identify the components of the system and to monitor their changes in abundance under different conditions. The AQUA (for 'absolute quantification') method allows sensitive and specific targeted quantification of protein and post-translational modifications in complex protein mixtures using stable isotope-labeled peptides as internal standards. Each AQUA experiment is composed of two stages: method development and application to a biological scenario. In the method development stage, peptides from the protein of interest are chosen and then synthesized with stable isotopes such as (13)C, (2)H or (15)N. The abundance of these internal standards and their endogenous counterparts can be measured by mass spectrometry with selected reaction monitoring or selected ion monitoring methods. Once an AQUA method is established, it can be rapidly applied to a wide range of biological samples, from tissue culture cells to human plasma and tissue. After AQUA peptide synthesis, the development, optimization and application of AQUA analyses to a specific biological problem can be achieved in ~1 week. Here we demonstrate the usefulness of this method by monitoring both Polo-like kinase 1 (Plk1) protein abundance in multiple lung cancer cell lines and the extent of Plk1 activation loop phosphorylation (pThr-210) during release from S phase.

Proteomic analysis of native hepatocyte nuclear factor-4α (HNF4α) isoforms, phosphorylation status, and interactive cofactors

Hepatocyte nuclear factor-4α (HNF4α, NR2A1) is a nuclear receptor that has a critical role in hepatocyte differentiation and the maintenance of homeostasis in the adult liver. However, a detailed understanding of native HNF4α in the steady-state remains to be elucidated. Here we report the native HNF4α isoform, phosphorylation status, and complexes in the steady-state, as shown by shotgun proteomics in HepG2 hepatocarcinoma cells. Shotgun proteomic analysis revealed the complexity of native HNF4α, including multiple phosphorylation sites and inter-isoform heterodimerization. The associating complexes identified by label-free semiquantitative proteomic analysis include the following: the DNA-dependent protein kinase catalytic subunit, histone acetyltransferase complexes, mRNA splicing complex, other nuclear receptor coactivator complexes, the chromatin remodeling complex, and the nucleosome remodeling and histone deacetylation complex. Among the associating proteins, GRB10 interacting GYF protein 2 (GIGYF2, PERQ2) is a new candidate cofactor in metabolic regulation. Moreover, an unexpected heterodimerization of HNF4α and hepatocyte nuclear factor-4γ was found. A biochemical and genomewide analysis of transcriptional regulation showed that this heterodimerization activates gene transcription. The genes thus transcribed include the cell death-inducing DEF45-like effector b (CIDEB) gene, which is an important regulator of lipid metabolism in the liver. This suggests that the analysis of the distinctive stoichiometric balance of native HNF4α and its cofactor complexes described here are important for an accurate understanding of transcriptional regulation.

Proteomics databases and repositories

With the advent of more powerful and sensitive analytical techniques and instruments, the field of mass spectrometry based proteomics has seen a considerable increase in the amount of generated data. Correspondingly, the need to make these data publicly available in centralized online databases has also become more pressing. As a result, several such databases have been created, and steps are currently being taken to integrate these different systems under a single worldwide data-sharing umbrella. This chapter will discuss the importance of such databases and the necessary infrastructure that these databases require for efficient operation. Furthermore, the various kinds of information that proteomics databases can store will be described, along with the different types of databases that are available today. Finally, a selection of prominent repositories will be described in more detail, together with the international ProteomExchange consortium that is aimed at uniting all the different databases in a global data sharing collaboration.

Temporal profiling of the secretome during adipogenesis in humans

Adipose tissue plays a key role as a fat-storage depot and as an endocrine organ. Although mouse adipogenesis has been studied extensively, limited studies have been conducted to characterize this process in humans. We carried out a temporal proteomic analysis to interrogate the dynamic changes in the secretome of primary human preadipocytes as they differentiate into mature adipocytes. Using iTRAQ-based quantitative proteomics, we identified and quantified 420 proteins from the secretome of differentiated human adipocytes. Our results revealed that the majority of proteins showed differential expression during the course of differentiation. In addition to adipokines known to be differentially secreted in the course of adipocyte differentiation, we identified a number of proteins whose dynamic expression in this process has not been previously documented. They include collagen triple helix repeat containing 1, cytokine receptor-like factor 1, glypican-1, hepatoma-derived growth factor, SPARC related modular calcium binding protein 1, SPOCK 1, and sushi repeat-containing protein. A bioinformatics analysis using Human Protein Reference Database and Human Proteinpedia revealed that of the 420 proteins identified, 164 proteins possess signal peptides and 148 proteins are localized to the extracellular compartment. Additionally, we employed antibody arrays to quantify changes in the levels of 182 adipokines during human adipogenesis. This is the first large-scale quantitative proteomic study that combines two platforms, mass spectrometry and antibody arrays, to analyze the changes in the secretome during the course of adipogenesis in humans.

The secretome of adipocytes is regulated during the differentiation of preadipocytes into adipocytes. Using iTRAQ-based quantitative proteomics, we identified and quantified 420 proteins. Additionally, we employed antibody arrays to quantify changes in the levels of 182 adipokines. This is the first large-scale quantitative proteomic study that combines two platforms, mass spectrometry and antibody arrays, to analyze the changes in the secretome during the course of adipogenesis in humans.

Proteomics data repositories: providing a safe haven for your data and acting as a springboard for further research

Despite the fact that data deposition is not a generalised fact yet in the field of proteomics, several mass spectrometry (MS) based proteomics repositories are publicly available for the scientific community. The main existing resources are: the Global Proteome Machine Database (GPMDB), PeptideAtlas, the PRoteomics IDEntifications database (PRIDE), Tranche, and NCBI Peptidome. In this review the capabilities of each of these will be described, paying special attention to four key properties: data types stored, applicable data submission strategies, supported formats, and available data mining and visualization tools. Additionally, the data contents from model organisms will be enumerated for each resource. There are other valuable smaller and/or more specialized repositories but they will not be covered in this review. Finally, the concept behind the ProteomeXchange consortium, a collaborative effort among the main resources in the field, will be introduced.

Cancer secretomics reveal pathophysiological pathways in cancer molecular oncology

Emerging proteomic tools and mass spectrometry play pivotal roles in protein identification, quantification and characterization, even in complex biological samples. The cancer secretome, namely the whole collection of proteins secreted by cancer cells through various secretory pathways, has only recently been shown to have significant potential for diverse applications in oncoproteomics. For example, secreted proteins might represent putative tumor biomarkers or therapeutic targets for various types of cancer. Consequently, many proteomic strategies for secretome analysis have been extensively deployed over the last few years. These efforts generated a large amount of information awaiting deeper mining, better understanding and careful interpretation. Distinct sub-fields, such as degradomics, exosome proteomics and tumor-host cell interactions have been developed, in an attempt to provide certain answers to partially elucidated mechanisms of cancer pathobiology. In this review, advances, concerns and challenges in the field of secretome analysis as well as possible clinical applications are discussed.

The grand challenge to decipher the cancer proteome

The quest to decipher protein alterations in cancer has spanned well over half a century. The vast dynamic range of protein abundance coupled with a plethora of isoforms and disease heterogeneity have been formidable challenges. Progress in cancer proteomics has substantially paralleled technological developments. Advances in analytical techniques and the implementation of strategies to de-complex the proteome into manageable components have allowed proteins across a wide dynamic range to be explored. The massive amounts of data that can currently be collected through proteomics allow the near-complete definition of cancer subproteomes, which reveals the alterations in signalling and developmental pathways. This allows the discovery of predictive biomarkers and the annotation of the cancer genome based on proteomic findings. There remains a considerable need for infrastructure development and the organized collaborative efforts to efficiently mine the cancer proteome.

PDBWiki: added value through community annotation of the Protein Data Bank

The success of community projects such as Wikipedia has recently prompted a discussion about the applicability of such tools in the life sciences. Currently, there are several such ‘science-wikis’ that aim to collect specialist knowledge from the community into centralized resources. However, there is no consensus about how to achieve this goal. For example, it is not clear how to best integrate data from established, centralized databases with that provided by ‘community annotation’. We created PDBWiki, a scientific wiki for the community annotation of protein structures. The wiki consists of one structured page for each entry in the the Protein Data Bank (PDB) and allows the user to attach categorized comments to the entries. Additionally, each page includes a user editable list of cross-references to external resources. As in a database, it is possible to produce tabular reports and ‘structure galleries’ based on user-defined queries or lists of entries. PDBWiki runs in parallel to the PDB, separating original database content from user annotations. PDBWiki demonstrates how collaboration features can be integrated with primary data from a biological database. It can be used as a system for better understanding how to capture community knowledge in the biological sciences. For users of the PDB, PDBWiki provides a bug-tracker, discussion forum and community annotation system. To date, user participation has been modest, but is increasing. The user editable cross-references section has proven popular, with the number of linked resources more than doubling from 17 originally to 39 today.

Database URL: http://www.pdbwiki.org

Dominant processes during human dendritic cell maturation revealed by integration of proteome and transcriptome at the pathway level

Gene expression is commonly used to study the activation of dendritic cells (DCs) to identify proteins that determine whether these cells induce an immunostimulatory or tolerogenic immune response. RNA expression, however, does not necessarily predict protein abundance and often requires large numbers of experiments for statistical significance. Proteomics provides a direct view on protein expression but is costly and time consuming. Here, we combined a comprehensive quantitative proteome and transcriptome analysis on a single batch of immature and cytokine cocktail matured human DCs and integrated resulting data sets at the pathway level. Although overall correlation between differential mRNA and protein expression was low, correlation between components of DC relevant pathways was significantly higher. Differentially expressed proteins and genes partly mapped to identical but also to different pathway components demonstrating that RNA and protein data not only supported but also complemented each other. We identified 5 dominant pathways, which confirmed the importance of cytokines, cell adhesion, and migration in DC maturation and also indicated a fundamental role for lipid metabolism. From these pathways we extracted novel maturation markers that might improve DC vaccine design. For several of the candidate markers we confirmed widespread significance examining DCs from multiple individuals, underscoring the validity of our approach. We conclude that integration of different but related data sets at the pathway level can significantly increase the predictive power of multi "omics" analyses.

Stress-induced phosphoprotein 1 as a secreted biomarker for human ovarian cancer promotes cancer cell proliferation

Ovarian cancers are frequently not diagnosed until advanced stages, resulting in a high case fatality rate. Because of this, more tumor markers, in addition to CA125, for detecting and monitoring ovarian cancer are needed. During a systematic search for potential biomarkers of ovarian cancer, we compared the protein profiles between tumor interstitial fluid and normal interstitial fluid of ovaries, rationalizing that abnormal levels of proteins in tumor interstitial fluid may be detected in peripheral blood and thus serve as easily accessible tumor markers. Here, we show that stress-induced phosphoprotein 1 (STIP1) was secreted by ovarian cancer tissues into the peripheral blood of patients, resulting in a significant increase of serum levels of STIP1 in cancer patients compared with those in age-matched normal controls. Our results further indicated that combined use of CA125 and STIP1 may increase early detection of ovarian cancer. Functionally, recombinant STIP1 significantly induced ERK phosphorylation, promoted DNA synthesis, and increased Ki-67 immunoreactivity in ovarian cancer cells, suggesting that STIP1 in vitro promotes cell proliferation. Colocalization of STIP1 and phospho-ERK in human ovarian cancer tissues also supports an in vivo activation of ERK by STIP1. Further understanding of molecular roles of STIP1 in human ovarian cancer may shed light on its pathophysiology and development of novel therapeutic strategies.

Helicobacter pylori proteomics by 2-DE/MS, 1-DE-LC/MS and functional data mining

With its predicted proteome of 1550 proteins (data set Etalon) Helicobacter pylori 26695 represents a perfect model system of medium complexity for investigating basic questions in proteomics. We analyzed urea-solubilized proteins by 2-DE/MS (data set 2-DE) and by 1-DE-LC/MS (Supprot); proteins insoluble in 9 M urea but solubilized by SDS (Pellet); proteins precipitating in the Sephadex layer at the application side of IEF (Sephadex) by 1-DE-LC/MS; and proteins precipitating close to the application side within the IEF gel by LC/MS (Startline). The experimental proteomics data of H. pylori comprising 567 proteins (protein coverage: 36.6%) were stored in the Proteome Database System for Microbial Research (http://www.mpiib-berlin.mpg.de/2D-PAGE/), which gives access to raw mass spectra (MALDI-TOF/TOF) in T2D format, as well as to text files of peak lists. For data mining the protein mapping and comparison tool PROMPT (http://webclu.bio.wzw.tum.de/prompt/) was used. The percentage of proteins with transmembrane regions, relative to all proteins detected, was 0, 0.2, 0, 0.5, 3.8 and 6.3% for 2-DE, Supprot, Startline, Sephadex, Pellet, and Etalon, respectively. 2-DE does not separate membrane proteins because they are insoluble in 9 M urea/70 mM DTT and 2% CHAPS. SDS solubilizes a considerable portion of the urea-insoluble proteins and makes them accessible for separation by SDS-PAGE and LC. The 2-DE/MS analysis with urea-solubilized proteins and the 1-DE-LC/MS analysis with the urea-insoluble protein fraction (Pellet) are complementary procedures in the pursuit of a complete proteome analysis. Access to the PROMPT-generated diagrams in the Proteome Database allows the mining of experimental data with respect to other functional aspects.

PeptideDepot: flexible relational database for visual analysis of quantitative proteomic data and integration of existing protein information

Recently, dramatic progress has been achieved in expanding the sensitivity, resolution, mass accuracy, and scan rate of mass spectrometers able to fragment and identify peptides through MS/MS. Unfortunately, this enhanced ability to acquire proteomic data has not been accompanied by a concomitant increase in the availability of flexible tools allowing users to rapidly assimilate, explore, and analyze this data and adapt to various experimental workflows with minimal user intervention. Here we fill this critical gap by providing a flexible relational database called PeptideDepot for organization of expansive proteomic data sets, collation of proteomic data with available protein information resources, and visual comparison of multiple quantitative proteomic experiments. Our software design, built upon the synergistic combination of a MySQL database for safe warehousing of proteomic data with a FileMaker-driven graphical user interface for flexible adaptation to diverse workflows, enables proteomic end-users to directly tailor the presentation of proteomic data to the unique analysis requirements of the individual proteomics lab. PeptideDepot may be deployed as an independent software tool or integrated directly with our high throughput autonomous proteomic pipeline used in the automated acquisition and post-acquisition analysis of proteomic data.

Proteomics data repositories

The field of proteomics, particularly the application of MS analysis to protein samples, is well established and growing rapidly. Proteomic studies generate large volumes of raw experimental data and inferred biological results. To facilitate the dissemination of these data, centralized data repositories have been developed that make the data and results accessible to proteomic researchers and biologists alike. This review of proteomics data repositories focuses exclusively on freely available, centralized data resources that disseminate or store experimental MS data and results. The resources chosen reflect a current "snapshot" of the state of resources available with an emphasis placed on resources that may be of particular interest to yeast researchers. Resources are described in terms of their intended purpose and the features and functionality provided to users.

Protein microarrays for personalized medicine

BACKGROUND

Over the last 10 years, DNA microarrays have achieved a robust analytical performance, enabling their use for analyzing the whole transcriptome or for screening thousands of single-nucleotide polymorphisms in a single experiment. DNA microarrays allow scientists to correlate gene expression signatures with disease progression, to screen for disease-specific mutations, and to treat patients according to their individual genetic profiles; however, the real key is proteins and their manifold functions. It is necessary to achieve a greater understanding of not only protein function and abundance but also their role in the development of diseases. Protein concentrations have been shown to reflect the physiological and pathologic state of an organ, tissue, or cells far more directly than DNA, and proteins can be profiled effectively with protein microarrays, which require only a small amount of sample material.

CONTENT

Protein microarrays have become well-established tools in basic and applied research, and the first products have already entered the in vitro diagnostics market. This review focuses on protein microarray applications for biomarker discovery and validation, disease diagnosis, and use within the area of personalized medicine.

SUMMARY

Protein microarrays have proved to be reliable research tools in screening for a multitude of parameters with only a minimal quantity of sample and have enormous potential in applications for diagnostic and personalized medicine.

Bioinformatics for LC-MS/MS-based proteomics

Mass spectrometry instrumentation has continued to develop rapidly in the last two decades, enabled in part by advances in microelectronic hardware controllers and computerized control and data acquisition systems. The wealth and complexity of data produced by a modern instrument is such that the data can no longer be analyzed manually. Computerized data analysis has become de rigueur and the bioinformatics field has expanded to provide software applications for all aspects of the data analysis needed by LC-MS/MS. The bioinformatics field is evolving rapidly and software applications are continually being improved or replaced for existing applications as well as developed to support new types of experiments and analysis enabled by modern instrumentation. Entire books have been written on MS data analysis in proteomics but this review will be necessarily brief. In this chapter we will review the bioinformatics software applications available for different LC-MS/MS analysis tasks.

Neuroscience in the era of functional genomics and systems biology

Advances in genetics and genomics have fuelled a revolution in discovery-based, or hypothesis-generating, research that provides a powerful complement to the more directly hypothesis-driven molecular, cellular and systems neuroscience. Genetic and functional genomic studies have already yielded important insights into neuronal diversity and function, as well as disease. One of the most exciting and challenging frontiers in neuroscience involves harnessing the power of large-scale genetic, genomic and phenotypic data sets, and the development of tools for data integration and mining. Methods for network analysis and systems biology offer the promise of integrating these multiple levels of data, connecting molecular pathways to nervous system function.

Alternative paths in HIV-1 targeted human signal transduction pathways

Background

Human immunodeficiency virus-1 (HIV-1) has a minimal genome of only 9 genes, which encode 15 proteins. HIV-1 thus depends on the human host for virtually every aspect of its life cycle. The universal language of communication in biological systems, including between pathogen and host, is via signal transduction pathways. The fundamental units of these pathways are protein protein interactions. Understanding the functional significance of HIV-1, human interactions requires viewing them in the context of human signal transduction pathways.

Results

Integration of HIV-1, human interactions with known signal transduction pathways indicates that the majority of known human pathways have the potential to be effected through at least one interaction with an HIV-1 protein at some point during the HIV-1 life cycle. For each pathway, we define simple paths between start points (i.e. no edges going into a node) and end points (i.e. no edges leaving a node). We then identify the paths that pass through human proteins that interact with HIV-1 proteins. We supplement the combined map with functional information, including which proteins are known drug targets and which proteins contribute significantly to HIV-1 function as revealed by recent siRNA screens. We find that there are often alternative paths starting and ending at the same proteins but circumventing the intermediate steps disrupted by HIV-1.

Conclusion

A mapping of HIV-1, human interactions to human signal transduction pathways is presented here to link interactions with functions. We proposed a new way of analyzing the virus host interactions by identifying HIV-1 targets as well as alternative paths bypassing the HIV-1 targeted steps. This approach yields numerous experimentally testable hypotheses on how HIV-1 function may be compromised and human cellular function restored by pharmacological approaches. We are making the full set of pathway analysis results available to the community.

NCBI Peptidome: a new repository for mass spectrometry proteomics data

Peptidome is a public repository that archives and freely distributes tandem mass spectrometry peptide and protein identification data generated by the scientific community. Data from all stages of a mass spectrometry experiment are captured, including original mass spectra files, experimental metadata and conclusion-level results. The submission process is facilitated through acceptance of data in commonly used open formats, and all submissions undergo syntactic validation and curation in an effort to uphold data integrity and quality. Peptidome is not restricted to specific organisms, instruments or experiment types; data from any tandem mass spectrometry experiment from any species are accepted. In addition to data storage, web-based interfaces are available to help users query, browse and explore individual peptides, proteins or entire Samples and Studies. Results are integrated and linked with other NCBI resources to ensure dissemination of the information beyond the mass spectroscopy proteomics community. Peptidome is freely accessible at http://www.ncbi.nlm.nih.gov/peptidome.

Evaluation of several MS/MS search algorithms for analysis of spectra derived from electron transfer dissociation experiments

Electron transfer dissociation (ETD) is increasingly becoming popular for high-throughput experiments especially in the identification of the labile post-translational modifications. Most search algorithms that are currently in use for querying MS/MS data against protein databases have been optimized on the basis of matching fragment ions derived from collision induced dissociation of peptides, which are dominated by b and y ions. However, electron transfer dissociation of peptides generates completely different types of fragments: c and z ions. The goal of our study was to test the ability of different search algorithms to handle data from this fragmentation method. We compared four MS/MS search algorithms (OMSSA, Mascot, Spectrum Mill, and X!Tandem) using approximately 170,000 spectra generated from a standard protein mix, as well as from complex proteomic samples which included a large number of phosphopeptides. Our analysis revealed (1) greater differences between algorithms than has been previously reported for CID data, (2) a significant charge state bias resulting in >60-fold difference in the numbers of matched doubly charged peptides, and (3) identification of 70% more peptides by the best performing algorithm than the algorithm identifying the least number of peptides. Our results indicate that the search engines for analyzing ETD derived MS/MS spectra are still in their early days and that multiple search engines could be used to reduce individual biases of algorithms.

Proteomics analysis of A33 immunoaffinity-purified exosomes released from the human colon tumor cell line LIM1215 reveals a tissue-specific protein signature

Exosomes are 40-100-nm-diameter nanovesicles of endocytic origin that are released from diverse cell types. To better understand the biological role of exosomes and to avoid confounding data arising from proteinaceous contaminants, it is important to work with highly purified material. Here, we describe an immunoaffinity capture method using the colon epithelial cell-specific A33 antibody to purify colorectal cancer cell (LIM1215)-derived exosomes. LC-MS/MS revealed 394 unique exosomal proteins of which 112 proteins (28%) contained signal peptides and a significant enrichment of proteins containing coiled coil, RAS, and MIRO domains. A comparative protein profiling analysis of LIM1215-, murine mast cell-, and human urine-derived exosomes revealed a subset of proteins common to all exosomes such as endosomal sorting complex required for transport (ESCRT) proteins, tetraspanins, signaling, trafficking, and cytoskeletal proteins. A conspicuous finding of this comparative analysis was the presence of host cell-specific (LIM1215 exosome) proteins such as A33, cadherin-17, carcinoembryonic antigen, epithelial cell surface antigen (EpCAM), proliferating cell nuclear antigen, epidermal growth factor receptor, mucin 13, misshapen-like kinase 1, keratin 18, mitogen-activated protein kinase 4, claudins (1, 3, and 7), centrosomal protein 55 kDa, and ephrin-B1 and -B2. Furthermore, we report the presence of the enzyme phospholipid scramblase implicated in transbilayer lipid distribution membrane remodeling. The LIM1215-specific exosomal proteins identified in this study may provide insights into colon cancer biology and potential diagnostic biomarkers.

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.

Recent developments in public proteomic MS repositories and pipelines

This article provides an overview of publicly available proteomic data repositories in a single document with a particular focus on the latest developments, many of which are not announced through traditional publications. The review is intended to inform the proteomics practitioner of the options for storage and dissemination of their MS/MS data in the public domain, and to help those who want to mine proteomic data generated by others. The latter area has arguably seen the most development in recent times, as repositories have sprouted new tools for data analysis, visualisation and experimental design. We also highlight key biological datasets available at each repository, including standard datasets. Finally, we touch upon areas of significant challenge and future directions.

Stable isotope labeling by amino acids in cell culture (SILAC) and quantitative comparison of the membrane proteomes of self-renewing and differentiating human embryonic stem cells

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful quantitative proteomics platform for comprehensive characterization of complex biological systems. However, the potential of SILAC-based approaches has not been fully utilized in human embryonic stem cell (hESC) research mainly because of the complex nature of hESC culture conditions. Here we describe complete SILAC labeling of hESCs with fully preserved pluripotency, self-renewal capabilities, and overall proteome status that was quantitatively analyzed to a depth of 1556 proteins and 527 phosphorylation events. SILAC-labeled hESCs appear to be perfectly suitable for functional studies, and we exploited a SILAC-based proteomics strategy for discovery of hESC-specific surface markers. We determined and quantitatively compared the membrane proteomes of the self-renewing versus differentiating cells of two distinct human embryonic stem cell lines. Of the 811 identified membrane proteins, six displayed significantly higher expression levels in the undifferentiated state compared with differentiating cells. This group includes the established marker CD133/Prominin-1 as well as novel candidates for hESC surface markers: Glypican-4, Neuroligin-4, ErbB2, receptor-type tyrosine-protein phosphatase zeta (PTPRZ), and Glycoprotein M6B. Our study also revealed 17 potential markers of hESC differentiation as their corresponding protein expression levels displayed a dramatic increase in differentiated embryonic stem cell populations.

A compendium of potential biomarkers of pancreatic cancer

Akhilesh Pandey and colleagues describe a compendium of potential biomarkers that can be systematically validated by the pancreatic cancer community.

Assessment of PARP-3 distribution in tissues of cynomolgous monkeys

Poly(ADP-ribose) polymerase 3 (PARP-3) is a newly characterized PARP. In contrast to the two best-studied nuclear PARPs, PARP-1 and PARP-2, PARP-3 activity is apparently not stimulated by DNA damage. However, our previous work has demonstrated that PARP-3 interacts with several DNA damage response proteins, including Ku70/Ku80, DNA-PK, and PARP-1, suggesting that it contributes to the DNA damage response. Furthermore, a possible function for PARP-3 in the regulation of gene expression has been inferred from our observations that it associates with polycomb group proteins, which are responsible for epigenetic modifications leading to gene silencing. In this report, we extend our characterization of PARP-3 by revealing its distribution in the tissues and cell types of adult cynomolgous monkeys using a well-characterized PARP-3 polyclonal antibody. This study is the first to demonstrate that PARP-3 is genuinely expressed in most of the examined tissues. However, its expression is highly restricted to specific cell types of each tissue, indicating that PARP-3 expression is tightly regulated. One of the key findings of this study is that PARP-3 is highly expressed in the nuclei of epithelial cells forming the ducts of prostate, salivary glands, liver, and pancreas and in the neurons of terminal ganglia.

High-throughput proteomics detection of novel splice isoforms in human platelets

Alternative splicing (AS) is an intrinsic regulatory mechanism of all metazoans. Recent findings suggest that 100% of multiexonic human genes give rise to splice isoforms. AS can be specific to tissue type, environment or developmentally regulated. Splice variants have also been implicated in various diseases including cancer. Detection of these variants will enhance our understanding of the complexity of the human genome and provide disease-specific and prognostic biomarkers. We adopted a proteomics approach to identify exon skip events - the most common form of AS. We constructed a database harboring the peptide sequences derived from all hypothetical exon skip junctions in the human genome. Searching tandem mass spectrometry (MS/MS) data against the database allows the detection of exon skip events, directly at the protein level. Here we describe the application of this approach to human platelets, including the mRNA-based verification of novel splice isoforms of ITGA2, NPEPPS and FH. This methodology is applicable to all new or existing MS/MS datasets.

Temporal analysis of neural differentiation using quantitative proteomics

The ability to derive neural progenitors, differentiated neurons and glial cells from human embryonic stem cells (hESCs) with high efficiency holds promise for a number of clinical applications. However, investigating the temporal events is crucial for defining the underlying mechanisms that drive this process of differentiation along different lineages. We carried out quantitative proteomic profiling using a multiplexed approach capable of analyzing eight different samples simultaneously to monitor the temporal dynamics of protein abundance as human embryonic stem cells differentiate into motor neurons or astrocytes. With this approach, a catalog of approximately 1200 proteins along with their relative quantitative expression patterns was generated. The differential expression of the large majority of these proteins has not previously been reported or studied in the context of neural differentiation. As expected, two of the widely used markers of pluripotency, alkaline phosphatase (ALPL) and LIN28, were found to be downregulated during differentiation, while S-100 and tenascin C were upregulated in astrocytes. Neurofilament 3 protein, doublecortin and CAM kinase-like 1 and nestin proteins were upregulated during motor neuron differentiation. We identified a number of proteins whose expression was largely confined to specific cell types, embryonic stem cells, embryoid bodies and differentiating motor neurons. For example, glycogen phosphorylase (PYGL) and fatty acid binding protein 5 (FABP5) were enriched in ESCs, while beta spectrin (SPTBN5) was highly expressed in embryoid bodies. Karyopherin, heat shock 27 kDa protein 1 and cellular retinoic acid binding protein 2 (CRABP2) were upregulated in differentiating motor neurons but were downregulated in mature motor neurons. We validated some of the novel markers of the differentiation process using immunoblotting and immunocytochemical labeling. To our knowledge, this is the first large-scale temporal proteomic profiling of human stem cell differentiation into neural cell types highlighting proteins with limited or undefined roles in neural fate.

Chemical biology approaches to probe the proteome

Understanding disease-associated cellular defects at a molecular level is critical for the development of pharmacological intervention strategies. Recent breakthroughs in microarray and sequencing technologies have provided powerful tools to rapidly reveal the cellular defects caused by alterations in the genome or transcriptome. However, the picture of how the cellular proteome is affected in a disease state and how changes in DNA and RNA affect protein function is often incomplete. This is perhaps not surprising because the functions of proteins are not just determined by primary sequence and abundance, but are under the control of many regulatory mechanisms. Here, we highlight several recent advances in proteomics technologies that are being developed to generate comprehensive human proteome maps and discuss them in the context of strategies that have been developed in simple model organisms. Chemical biology will play a critical role in drafting a map of the proteome with functional information. Chemical genetic approaches that use high-throughput small molecule screening have resulted in the public availability of small molecule datasets through web interfaces such as PubChem. With such approaches, the opportunities to investigate disease and to explore the proteome with chemistry are rapidly increasing. In addition, new tools are being developed to probe protein function. Here we highlight recent developments in chemical biology and the exciting opportunities that are arising with them.