High-performance proteomics as a tool in biomarker discovery

Biomarkers allowing early detection of disease or therapy control have a huge influence in curing a disease. A wide variety of methods were applied to find new biomarkers. In contrast to methods focused on DNA or mRNA techniques, approaches considering proteins as potential biomarker candidates have the advantage that proteins are more diverse than DNA or RNA and are more reflective of a biological system. Here, we present an approach for the identification of new biomarkers relying on our experience from the past 10 years of proteomics, outlining a concept of "high-performance proteomics" This approach is based on quantitative proteome analysis using a sufficient number of clinical samples and statistical validation of proteomics data by independent methods, such as Western blot analysis or immunohistochemistry.     

Proteomic study of the Arabidopsis thaliana chloroplastic envelope membrane utilizing alternatives to traditional two-dimensional electrophoresis

With the completion of the sequencing of the Arabidopsis genome and with the significant increase in the amount of other plant genome and expressed sequence tags (ESTs) data, plant proteomics is rapidly becoming a very active field. We have pursued a high-throughput mass spectrometry-based proteomics approach to identify and characterize membrane proteins localized to the Arabidopsis thaliana chloroplastic envelope membrane. In this study, chloroplasts were prepared from plate- or soil-grown Arabidopsis plants using a novel isolation procedure, and "mixed" envelopes were subsequently isolated using sucrose step gradients. We applied two alternative methodologies, off-line multidimensional protein identification technology (Off-line MUDPIT) and one-dimensional (1D) gel electrophoresis followed by proteolytic digestion and liquid chromatography coupled with tandem mass spectrometry (Gel-C-MS/MS), to identify envelope membrane proteins. This proteomic study enabled us to identify 392 nonredundant proteins.     

A proteomic analysis of human bile

We have carried out a comprehensive characterization of human bile to define the bile proteome. Our approach involved fractionation of bile by one-dimensional gel electrophoresis and lectin affinity chromatography followed by liquid chromatography tandem mass spectrometry. Overall, we identified 87 unique proteins, including several novel proteins as well as known proteins whose functions are unknown. A large majority of the identified proteins have not been previously described in bile. Using lectin affinity chromatography and enzymatically labeling of asparagine residues carrying glycan moieties by (18)O, we have identified a total of 33 glycosylation sites. The strategy described in this study should be generally applicable for a detailed proteomic analysis of most body fluids. In combination with "tagging" approaches for differential proteomics, our method could be used for identification of cancer biomarkers from any body fluid.     

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.     

GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data

Background  

Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge.     

Integrative Proteomic Analysis of Serum and Peritoneal Fluids Helps Identify Proteins that Are Up-Regulated in Serum of Women with Ovarian Cancer

Background

We used intensive modern proteomics approaches to identify predictive proteins in ovary cancer. We identify up-regulated proteins in both serum and peritoneal fluid. To evaluate the overall performance of the approach we track the behavior of 20 validated markers across these experiments.

Methodology

Mass spectrometry based quantitative proteomics following extensive protein fractionation was used to compare serum of women with serous ovarian cancer to healthy women and women with benign ovarian tumors. Quantitation was achieved by isotopically labeling cysteine amino acids. Label-free mass spectrometry was used to compare peritoneal fluid taken from women with serous ovarian cancer and those with benign tumors. All data were integrated and annotated based on whether the proteins have been previously validated using antibody-based assays.

Findings

We selected 54 quantified serum proteins and 358 peritoneal fluid proteins whose case-control differences exceeded a predefined threshold. Seventeen proteins were quantified in both materials and 14 are extracellular. Of 19 validated markers that were identified all were found in cancer peritoneal fluid and a subset of 7 were quantified in serum, with one of these proteins, IGFBP1, newly validated here.

Conclusion

Proteome profiling applied to symptomatic ovarian cancer cases identifies a large number of up-regulated serum proteins, many of which are or have been confirmed by immunoassays. The number of currently known validated markers is highest in peritoneal fluid, but they make up a higher percentage of the proteins observed in both serum and peritoneal fluid, suggesting that the 10 additional markers in this group may be high quality candidates.     

Monitoring the effects of drug treatment in rat models of disease by serum protein analysis

In this review we list from literature investigations on rat serum proteins using electrophoretic techniques in connection with drug testing. From our own research work, we provide annotated two-dimensional maps of rat serum proteins under control and experimental conditions. Emphasis is on species-specific components and on the effects of acute and chronic inflammation. We discuss our project of structural proteomics on rat serum as a minimally invasive approach to pharmacological investigation, and we outline a typical experimental plan for drug testing according to the above guidelines. We then report in detail on the results of our trials of anti-inflammatory drugs on adjuvant arthritis, an animal model of disease resembling in many aspects human rheumatoid arthritis. We demonstrate a correlation between biochemical parameters and therapeutic findings and outline the advantages of the chosen methodological approach, which proved also sensitive in revealing "side effects" of the test drugs. In an appendix we describe our experimental protocol when performing two-dimensional electrophoresis of rat serum.     

Comment on "Unbiased statistical analysis for multi-stage proteomic search strategies"

Everett et al. recently reported on a statistical bias that arises in the target-decoy approach to false discovery rate estimation in two-pass proteomics search strategies as exemplified by X!Tandem. This bias can cause serious underestimation of the false discovery rate. We argue here that the "unbiased" solution proposed by Everett et al., however, is also biased and under certain circumstances can also result in a serious underestimate of the FDR, especially at the protein level.     

From the item to the outcome: the promising prospects of PROMIS

Evaluation of patient reported outcomes, and in particular physical function, have gained increasing importance in research and therapy of patients with rheumatic diseases. Most instruments that are used for that purpose are rigid and suffer from floor and ceiling effects when used in patients whose physical function differs from the average. A new approach to the assessment of physical function uses computerised adaptive testing, by which precision and reliability of the measurement can be achieved for most patients, while even requiring less time for the assessment. Well calibrated and tested item and large item data banks are a prerequisite for this purpose, a process that is summarised in the present report by Bruce and colleagues.     

On the proper use of mass accuracy in proteomics

Mass measurement is the main outcome of mass spectrometry-based proteomics yet the potential of recent advances in accurate mass measurements remains largely unexploited. There is not even a clear definition of mass accuracy in the proteomics literature, and we identify at least three uses of this term: anecdotal mass accuracy, statistical mass accuracy, and the maximum mass deviation (MMD) allowed in a database search. We suggest using the second of these terms as the generic one. To make the best use of the mass precision offered by modern instruments we propose a series of simple steps involving recalibration of the data on "internal standards" contained in every proteomics data set. Each data set should be accompanied by a plot of mass errors from which the appropriate MMD can be chosen. More advanced uses of high mass accuracy include an MMD that depends on the signal abundance of each peptide. Adapting search engines to high mass accuracy in the MS/MS data is also a high priority. Proper use of high mass accuracy data can make MS-based proteomics one of the most "digital" and accurate post-genomics disciplines.     

Targeted proteomics using immunoblotting technique for studying dysregulation of ion transporters in renal disorders

Renal salt and water transport physiology has benefited tremendously from the rapid advance of proteomics. Proteomics developed as a fast-throughput means of screening for global changes in proteins in a selected tissue, organ or cell type, as a logical offshoot of similar comprehensive, messenger RNA array-type technology. Targeted proteomics utilizes similar techniques but examines a predetermined set of proteins. One approach that has been rigorously employed over the last 10 years to evaluate differences in renal protein abundances due to a treatment or genotype has been parallel semiquantitative immunoblotting using antibody arrays. This approach, and newer ones on the horizon, provide a rapid global overview of regulation of the individual proteins whose integrated action determines overall renal sodium or water reabsorption.     

Targeted proteomics using immunoblotting technique for studying dysregulation of ion transporters in renal disorders

Renal salt and water transport physiology has benefited tremendously from the rapid advance of proteomics. Proteomics developed as a fast-throughput means of screening for global changes in proteins in a selected tissue, organ or cell type, as a logical offshoot of similar comprehensive, messenger RNA array-type technology. Targeted proteomics utilizes similar techniques but examines a predetermined set of proteins. One approach that has been rigorously employed over the last 10 years to evaluate differences in renal protein abundances due to a treatment or genotype has been parallel semiquantitative immunoblotting using antibody arrays. This approach, and newer ones on the horizon, provide a rapid global overview of regulation of the individual proteins whose integrated action determines overall renal sodium or water reabsorption.     

Analytical strategies for the global quantification of intact proteins

The quantification of intact proteins is a relatively recent development in proteomics. In eukaryotic organisms, proteins are present as multiple isoforms as the result of variations in genetic code, alternative splicing, post-translational modification and other processing events. Understanding the identities and biological functions of these isoforms and how their concentrations vary across different states is the central goal of proteomics. To date, the bulk of proteomics research utilizes a "bottom-up" approach, digesting proteins into their more manageable constitutive peptides, but sacrificing information about the specific isoform and combinations of post-translational modifications present on the protein. Very specific strategies for protein quantification such as the enzyme-linked immunosorbent assay and Western blot are commonplace in laboratories and clinics, but impractical for the study of global biological changes. Herein, we describe strategies for the quantification of intact proteins, their distinct advantages, and challenges to their employment. Techniques contained in this review include the more traditional and widely employed methodology of differential gel electrophoresis and more recently developed mass spectrometry-based techniques including metabolic labeling, chemical labeling, and label-free methodologies.     

Maximum Entropy Reconstructions of Dynamic Signaling Networks from Quantitative Proteomics Data

Advances in mass spectrometry among other technologies have allowed for quantitative, reproducible, proteome-wide measurements of levels of phosphorylation as signals propagate through complex networks in response to external stimuli under different conditions. However, computational approaches to infer elements of the signaling network strictly from the quantitative aspects of proteomics data are not well established. We considered a method using the principle of maximum entropy to infer a network of interacting phosphotyrosine sites from pairwise correlations in a mass spectrometry data set and derive a phosphorylation-dependent interaction network solely from quantitative proteomics data. We first investigated the applicability of this approach by using a simulation of a model biochemical signaling network whose dynamics are governed by a large set of coupled differential equations. We found that in a simulated signaling system, the method detects interactions with significant accuracy. We then analyzed a growth factor mediated signaling network in a human mammary epithelial cell line that we inferred from mass spectrometry data and observe a biologically interpretable, small-world structure of signaling nodes, as well as a catalog of predictions regarding the interactions among previously uncharacterized phosphotyrosine sites. For example, the calculation places a recently identified tumor suppressor pathway through ARHGEF7 and Scribble, in the context of growth factor signaling. Our findings suggest that maximum entropy derived network models are an important tool for interpreting quantitative proteomics data.     

A systems biology-led insight into the role of the proteome in neurodegenerative diseases

Introduction: Multifactorial disorders are the result of nonlinear interactions of several factors; therefore, a reductionist approach does not appear to be appropriate. Proteomics is a global approach that can be efficiently used to investigate pathogenetic mechanisms of neurodegenerative diseases.

Areas covered: Here, we report a general introduction about the systems biology approach and mechanistic insights recently obtained by over-representation analysis of proteomics data of cellular and animal models of Alzheimer’s disease, Parkinson’s disease and other neurodegenerative disorders, as well as of affected human tissues.

Expert commentary: As an inductive method, proteomics is based on unbiased observations that further require validation of generated hypotheses. Pathway databases and over-representation analysis tools allow researchers to assign an expectation value to pathogenetic mechanisms linked to neurodegenerative diseases. The systems biology approach based on omics data may be the key to unravel the complex mechanisms underlying neurodegeneration.     

1st National Congress of the Italian Proteome Society

Transgelin is an abundant protein of smooth muscle cells, where its role has been primarily studied. As a protein affecting dynamics of the actin cytoskeleton via stabilization of actin filaments, transgelin is both directly and indirectly involved in many cancer-related processes such as migration, proliferation, differentiation or apoptosis. Transgelin was previously reviewed as a tumor suppressor; however, recent data based on a number of proteomics studies indicate its pro-tumorigenic role, for example, in colorectal or hepatocellular cancer. We summarize these contradictory observations in both clinical and functional proteomics projects and analyze the role of transgelin in tumors in detail. Generally, the expression and biological role of transgelin seem to differ among various types of tumor cells and stroma, and possibly change during tumor progression. We also overview the recent data on transgelin-2, a sequence homolog of transgelin, whose role in the tumor development might be contradictory to the role of transgelin.     

Exploring the pan-surfome of Streptococcus suis: Looking for common protein antigens

Streptococcus suis is a swine and human pathogen for which no commercial vaccine is still available. Conserved and broadly distributed surface proteins have become the chosen targets for the development of efficacious vaccines that could overcome the problems of non-heterologous protection of bacterins or capsule polysaccharide-based vaccines. In this work, we have analyzed by proteomics a collection of 39 strains obtained from infected pigs. The isolates belonged to 19 of the most prevalent serotypes during the last years. We have applied the "shaving" approach to define the "pan-surfome" or the set of both common and unique surface proteins identified in such strains. This set was constituted by 113 proteins. We have categorized them for their potential for further vaccination studies, based on their distribution among strains and their a priori accessibility to antibodies. According to these criteria, the cell-wall protein SsnA appears to be the best candidate from this list, as it was that with the widest distribution among the analyzed pathogen types, it showed to be highly immunogenic and highly accessible to antibodies, as demonstrated by flow cytometry.