Time-resolved limited proteolysis of mitogen-activated protein kinase-activated protein kinase-2 determined by LC/MS only.

Mass spectrometry has gained prominence in limited proteolysis studies largely due to its unparalleled precision in determining protein molecular mass. However, proteolytic fragments usually cannot be identified through direct mass measurement, since multiple subsequences of a protein can frequently be matched to observed masses of proteolytic fragments. Therefore, additional information from N-terminal sequencing is often needed. Here we demonstrate that mass spectrometry analysis of the time course of limited proteolysis reactions provides new information that is self-sufficient to identify all proteolytic fragments. The method uses a non-specific protease like subtilisin and exploits information contained in the time-resolved dataset such as: increased likelihood of identifying larger fragments generated during initial proteolysis solely by their masses, additivity of the masses of two mutually exclusive sequence regions that generate the full-length molecule (or an already assigned subfragment), and analyses of the proteolytic subfragment patterns that are facilitated by having established the initial cleavage sites. We show that the identities of the observed proteolytic fragments can be determined by LC/MS alone because enough constraints exist in the time-resolved dataset. For a medium-sized protein, it takes about 8 h to complete the study, a significant improvement over the traditional SDS-PAGE and N-terminal sequencing method, which usually takes several days. We illustrate this method with application to the catalytic domain of mitogen-activated protein kinase-activated protein kinase-2, and compare the results with N-terminal sequencing data and the known X-ray crystal structure.

Identification of in vitro protein biomarkers of idiosyncratic liver toxicity.

Drug-induced idiosyncratic hepatotoxicity continues to be an important safety issue for the pharmaceutical industry. This toxicity is due, in part, to the limited predictive nature of current pre-clinical study systems. A hypothesis was formed that treatment of existing in vitro hepatocyte cultures with drugs clinically linked to idiosyncratic hepatotoxicity would result in the release of extracellular protein biomarkers indicative of liver toxicity. To test this hypothesis, a combination of proteomic and immunological techniques were used to first identify, and subsequently verify, components of the protein-laden conditioned culture media from immortalized human hepatocytes which overexpressed cytochrome p450 3A4. These cells were treated separately with seven individual compounds made up of a combination of thiazolidinedione and l-tyrosine PPARgamma agonists and HIV protease inhibitors, plus a vehicle control (dimethyl sulfoxide). For each drug class, clinically determined hepatotoxic and non-hepatotoxic compounds were compared. Two proteins, BMS-PTX-265 and BMS-PTX-837, were reproducibly and significantly increased in the conditioned media from cells treated with each of the toxic compounds as compared to media from cells treated with the non-toxic compounds (and vehicle). This result supported the hypothesis, and so a series of successive assays (western blots and enzyme linked immunosorbent assays) were used to measure the response of these two proteins as a function of an expanded set of 20 compounds. For all 20 drugs, elevations of BMS-PTX-265 correlated exactly with the known safety profile; whereas changes in BMS-PTX-837 correctly predicted the safety profile in 19 of 20 drugs (one false negative). In summary, the data supports both the pre-clinical in vitro method as a means to identify new biomarkers of liver toxicity, as well as the validity of the biomarkers themselves.

Biomarker discovery in biological fluids.

Discovery of novel protein biomarkers is essential for successful drug discovery and development. These novel protein biomarkers may aid accelerated drug efficacy, response, or toxicity decision making based on their enhanced sensitivity and/or specificity. These biomarkers, if necessary, could eventually be converted into novel diagnostic marker assays. Proteomic platforms developed over the past few years have given us the ability to rapidly identify novel protein biomarkers in various biological matrices from cell cultures (lysates, supernatants) to human clinical samples (serum, plasma, and urine). In this article, we delineate an approach to biomarker discovery. This approach is divided into three steps, (i) identification of markers, (ii) prioritization of identified markers, and (iii) preliminary validation (qualification) of prioritized markers. Using drug-induced idiosyncratic hepatotoxicity as a case study, the article elaborates methods and techniques utilized during the three steps of biomarker discovery process. The first step involves identification of markers using multi-dimensional protein identification technology. The second step involves prioritization of a subset of marker candidates based on several criteria such as availability of reagent set for assay development and literature association to disease biology. The last step of biomarker discovery involves development of preliminary assays to confirm the bio-analytical measurements from the first step, as well as qualify the marker(s) in pre-clinical models, to initiate future marker validation and development.

Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

Changes in the protein expression of yeast as a function of carbon source.

Protein expression trends in yeast were monitored as a function of carbon source (glucose versus galactose) using multidimensional high performance liquid chromatography (HPLC) coupled to gas-phase fractionation, using relative intensity triggering (GPFri). Size exclusion HPLC was used to separate whole cell lysates, and following proteolysis of these fractions, each was separated by reversed phase HPLC, which was coupled on-line via electrospray to an ion trap mass spectrometer. The GPFri technique increased the dynamic range of proteins detected by increasing the number of peptide ions subjected to low energy collision induced dissociation to the 24 most intense ions in each of the survey scans. No protein or peptide labeling was used; instead, the number of SEQUEST identifications for each peptide (previously termed "hits") were used as a semiquantitative means of assessing both the direction (increase vs decrease) and significance of change in protein abundance. None of the traditional SEQUEST filters, e.g., Xcorr, DelCn, Sp, Rsp, etc., were employed in this study. Instead, a Student's t-test was used to distinguish those proteins that significantly and reproducibly changed between carbon sources from those that did not. This relied on the SEQUEST misassignments occurring in equal proportion between treatments and thereby negating each other; statistically significant changes in SEQUEST assignments were nonrandom events by definition and therefore reflective of correct identifications. This method of data analysis showed a large degree of concordance with results reported by other groups in similar transcriptional profiling and proteomic experiments. In all, 176 and 231 (fold-change > or = 1.1; p < or = 0.05) proteins were identified as being increased in peptide hit number when the yeast cells' source of carbon was changed between glucose and galactose, respectively.

Biomarker discovery in urine by proteomics.

A hypothesis was formed that it would be possible to isolate an adequate amount of protein from a patient, having normal renal function, to identify biological markers of a particular disease state using a variety of proteomics techniques. To support this hypothesis, three samples of urine were collected from a volunteer: first when healthy, later when experiencing acute inflammation due to a pilonidal abcess, and again later still after successful recovery from the condition. The urine from these samples was processed by solid-phase extraction to concentrate and desalt the endogenous proteins and peptides. The proteins and peptides from these urine samples were analyzed in three different experiments: (1) traditional two-dimensional gel electrophoresis followed by proteolysis and mass spectrometric identification of various protein spots, (2) whole mixture proteolysis followed by one-dimensional packed capillary liquid chromatography and tandem mass spectrometry, (3) whole mixture proteolysis followed by two-dimensional capillary liquid chromatography and tandem mass spectrometry. In all three cases, a set of proteins was identified representing putative biomarkers. Each of these proteins was then found to have been previously linked in the scientific literature to inflammation. One acute phase reactant in particular, orosomucoid, was readily observed in all three experiments to dramatically increase in abundance, thereby supporting the hypothesis.

A high-yield method to extract peptides from rat brain tissue.

A process to extract and enrich extracellular peptides and proteins from tissues should have broad utility in the burgeoning proteomics field. To address this need, a novel three-step protocol was developed to extract polypeptides from whole tissue samples and enrich the extracellular components. The initial homogenization of rat brain was carried out at neutral pH to optimize protein and peptide stability and solubility. Subsequent covalent chromatography on an activated thiopropyl resin was employed to debulk the tissue extract by selectively removing a substantial fraction of the intracellular protein component under nondenaturing conditions. Finally, extraction with 0.1% trifluoroacetic acid was used to selectively precipitate large proteins while enhancing the solubility of smaller proteins and peptides. The fractions from each step in the process were compared to a single extract obtained by homogenization in 0.5 M acetic acid. The recovery and yields of endogenous neuropeptides and an exogenously added peptide were evaluated by enzyme immunoassay and Western blotting, respectively. In summary, the three-step protocol was superior to the extraction of tissue with 0.5 M acetic acid in terms of peptide recovery, enrichment, and sample stability. Enrichment of the extracellular protein compartment from tissues should be valuable in proteomics experiments aimed at identifying biomarkers that can partition into serum.

In vitro biomarker discovery for atherosclerosis by proteomics.

The purpose of this study was to identify in vitro and then prioritize a tractable set of protein biomarker candidates of atherosclerosis that may eventually be developed to measure the extent, progression, regression, and stability of atherosclerotic lesions. A study was conducted using an in vitro"foam cell" model based on the stimulation of differentiated THP1 cells with oxidized low-density lipoprotein (oxidized LDL) as compared with low-density lipoprotein (LDL). Analysis of the proteins contained in the cell supernatant using proteome scanning technology identified 59 proteins as being increased, 57 with no statistically measurable difference, and 17 decreasing in abundance following treatment with oxidized LDL, as compared with LDL. From the up-regulated list, proteins were prioritized based on their analytical confidence as well as their relevance to atherosclerosis pathways. Within the group of increased abundance, seven families of proteins were of particular interest: fatty acid-binding proteins, chitinase-like enzymes, cyclophilins, cathepsins, proteoglycans, urokinase-type plasminogen activator receptor, and a macrophage scavenger receptor.