Biomedical subjects

Gregory J Opiteck

Publications and source records attributed to Gregory J Opiteck.

7 recordsLinked to original sources

PubMed2005

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.

14-3-3 Proteins↗

PubMed2005

Guidelines for the routine application of the peptide hits technique.

A set of guidelines has been developed for using the peptide hits technique (PHT) as a semi-quantitative screening tool for the identification of proteins that change in abundance in a complex mixture. The dataset that formed the basis for these experiments was created using a cell lysate derived from the yeast Saccharomyces cerevisiae, spiked at various levels with serum albumin (BSA), and analyzed by LC/MS/MS and SEQUEST. Knowing that the level of only one protein (BSA) actually changed in the mixture allowed for the development and refinement of the necessary bioinformatics and statistical analyses, e.g., principal component analysis (PCA), normalization, and analysis of variation (ANOVA). As expected, the number of BSA peptide hits changed in proportion to the amount of BSA added to the sample. PCA was able to clearly distinguish between the spiked samples and the untreated sample, indicating that PCA may be able to classify samples, e.g., healthy versus diseased, in future experiments. The use of an endogenous "housekeeping" protein was found to be superior to the use of total hits for data normalization prior to analysis. An ANOVA based model readily identified BSA as a protein of interest, that is, one likely to be changing from amongst the background proteins, indicating that an ANOVA model may be able to identify individual proteins in target or biomarker discovery experiments. General guidelines based on these combined observations are set forth for future analyses and the rapid screening for candidate proteins of interest.

Analysis of Variance↗

PubMed2004

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.

Amino Acid Sequence↗

PubMed2004

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.

Biomarkers↗

PubMed2004

Target class strategies in mass spectrometry-based proteomics.

The cornerstone of proteomics resides in using traditional methods of protein chemistry, to extract and resolve complex mixtures, in concert with the powerful engines of mass spectrometry to decipher peptide and protein identities. The broad utility of proteomics technologies to map protein interactions, understand regulatory mechanisms and identify biomarkers associated with disease states and drug treatments necessitates a targeted biochemical approach tailored to the characteristics of the tissue, fluid or cellular extract being studied. The application of affinity methods in proteomic studies to focus on particular classes of molecules is being used with increasing frequency and comprises the subject of this review. An overview of successfully applied affinity methods is provided, along with speculation on the use of innovative approaches. Sample preparation and processing are critical for proteomics with affinity reagents, as only functional and active proteins can be isolated in most cases. Considerations for methods of sample preparation to optimize affinity capture and release are also discussed.

Animals↗

PubMed2003

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.

Animals↗

PubMedDate not supplied

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.

Algorithms↗