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-anticoagulated 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 multi- 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.
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-anticoagulated 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 multi
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.
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.
A microcapillary liquid chromatography (HPLC) system designed for the gradient elution of peptide and protein samples at flow rates < 1 microL/min has been coupled to a triple-sector quadrupole mass spectrometer via a simple sheathless electrospray interface (microspray). The microspray interface used a flame-drawn, uncoated, fused silica needle with tip outer diameters in the range of 15-20 microm and an opening less than 5 microm in diameter. Online sample filtration to prevent clogging of the drawn needle was accomplished by using a hydrophilic PVDF membrane filter integrated into the needle assembly. The spray potential (0.5-1 kV) was applied directly to the sample stream through the capillary union. Stable electrospray conditions were obtained over the full range of the gradient (0-90% acetonitrile in water) and was generally independent of flow rate. Both off-line and online analyses of proteins and peptide digest mixtures were performed at sample levels less than 10 fmol. HPLC parameters could be optimized for either rapid LC/MS analysis or enhanced performance in LC/MS/MS experiments by modulation of the eluting peak widths. Additionally, flow could be greatly reduced as selected components pass through the interface to prolong the time available to collect mass spectral data. The reduced spectral background and peak width manipulation facilitated the acquisition of peptide production spectra (MS/MS) using real-time, automated instrument control procedures.
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