No abstract

We carried out a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in LC-MS-based proteomics. We distributed a test sample consisting of an equimolar mix of 20 highly purified recombinant human proteins, to 27 laboratories for identification. Each protein contained one or more unique tryptic peptides of 1250 Da to also test for ion selection and sampling in the mass spectrometer. Of the 27 labs, initially only 7 labs reported all 20 proteins correctly, and only 1 lab reported all the tryptic peptides of 1250 Da. Nevertheless, a subsequent centralized analysis of the raw data revealed that all 20 proteins and most of the 1250 Da peptides had in fact been detected by all 27 labs. The centralized analysis allowed us to determine sources of problems encountered in the study, which include missed identifications (false negatives), environmental contamination, database matching, and curation of protein identifications. Improved search engines and databases are likely to increase the fidelity of mass spectrometry-based proteomics.

The PRIDE (http://www.ebi.ac.uk/pride) database of protein and peptide identifications was previously described in the NAR Database Special Edition in 2006. Since this publication, the volume of public data in the PRIDE relational database has increased by more than an order of magnitude. Several significant public datasets have been added, including identifications and processed mass spectra generated by the HUPO Brain Proteome Project and the HUPO Liver Proteome Project. The PRIDE software development team has made several significant changes and additions to the user interface and tool set associated with PRIDE. The focus of these changes has been to facilitate the submission process and to improve the mechanisms by which PRIDE can be queried. The PRIDE team has developed a Microsoft Excel workbook that allows the required data to be collated in a series of relatively simple spreadsheets, with automatic generation of PRIDE XML at the end of the process. The ability to query PRIDE has been augmented by the addition of a BioMart interface allowing complex queries to be constructed. Collaboration with groups outside the EBI has been fruitful in extending PRIDE, including an approach to encode iTRAQ quantitative data in PRIDE XML.

Sterol Delta8-Delta7 isomerases (SIs) catalyze the shift of the double bond from C8-9 to C7-8 in the B-ring of sterols. Surprisingly, the isoenzymes in fungi (ERG2p) and vertebrates [emopamil binding protein (EBP)] are structurally completely unrelated, whereas the sigma1 receptor, a mammalian protein of unknown function, bears significant similarity with the yeast ERG2p. Here, we compare the drug binding properties of SIs and related proteins with [3H]ifenprodil as a common high affinity radioligand (Kd = 1.4-19 nM), demonstrating an intimate pharmacological relationship among ERG2p, sigma1 receptor, and EBP. This renders SIs a remarkable example for structurally diverse enzymes with similar pharmacological profiles and the propensity to bind drugs from different chemical groups with high affinity. We identified a variety of experimental drugs with nanomolar affinity for the human EBP (Ki = 0.5-14 nM) such as MDL28815, AY9944, triparanol, and U18666A. These compounds, as well as the fungicide tridemorph and the clinically used drugs tamoxifen, clomiphene, amiodarone, and opipramol, inhibit the in vitro activity of the recombinant human EBP (IC50 = 0.015-54 microM). The high affinity of the human EBP for 3H-tamoxifen (Kd = 3 +/- 2 nM) implies that the EBP carries the previously described microsomal antiestrogen binding site. Interactions of the EBP with structurally diverse lipophilic amines suggest that novel compounds of related structure should be counterscreened for inhibition of the enzyme to avoid interference with sterol Delta8-Delta7 isomerization.

To identify and characterize a serologic glycoprotein biomarker for hepatocellular carcinoma (HCC), multi-lectin affinity chromatography was used to isolate intracellular N-linked glycoprotein fractions from five paired non-tumor and tumor tissues. From the series of 2-D DIGE targeted differentially expressed N-linked glycoproteins, we identified human liver carboxylesterase 1 (hCE1), which was remarkably down-regulated in tumor tissues, a finding confirmed by Western blot, a quantitative real-time RT-PCR, and immunohistochemical staining of non-tumor and tumor tissues from total 58 HCC patients. To investigate whether hCE1 is also present in human plasma, we employed a magnetic bead-based immunoprecipitation followed by nano-LC-MS/MS analysis, and we found for the first time that hCE1 is present in human plasma as opposed to that in liver tissues. That is, from normalization of hCE1 signal by the immunoprecipitation and Western blot analysis, hCE1 levels were increased in plasma specimens from HCC patients than in plasma from other disease patient groups (e.g. liver cirrhosis, chronic hepatitis, cholangiocarcinoma, stomach cancer, and pancreatic cancer). From the receiver operating characteristic analysis in HCC, both sensitivity and specificity were shown to be greater than 70.0 and 85.0%, respectively. Thus, the high-resolution proteomic approach demonstrates that hCE1 is a good candidate for further validation as a serologic glycoprotein biomarker for HCC.

Human plasma is the most clinically valuable specimen, containing not only a dynamic concentration range of protein components, but also several groups of high-abundance proteins that seriously interfere with the detection of low-abundance potential biomarker proteins. To establish a high-throughput method for efficient depletion of high-abundance proteins and subsequent fractionation, prior to molecular analysis of proteins, we explored how coupled immunoaffinity columns, commercially available as multiple affinity removal columns (MARC) and free flow electrophoresis (FFE), could apply to the HUPO plasma proteome project. Here we report identification of proteins and construction of a human plasma 2-DE map devoid of six major abundance proteins (albumin, transferrin, IgG, IgA, haptoglobin, and antitrypsin) using MARC. The proteins were identified by PMF, matching with various internal 2-DE maps, resulting in a total of 144 nonredundant proteins that were identified from 398 spots. Tissue plasminogen activator, usually present at 10-60 ng/mL plasma, was also identified, indicative of a potentially low-abundance biomarker. Comparison of representative 2-D gel images of three ethnic groups (Caucasian, Asian-American, African-American) plasma exhibited minor differences in certain proteins between races and sample pretreatment. To establish a throughput fractionation of plasma samples by FFE, either MARC flow-through fractions or untreated samples of Korean serum were subjected to FFE. After separation of samples on FFE, an aliquot of each fraction was analyzed by 1-D gel, in which MARC separation was a prerequisite for FFE work. Thus, a working scheme of MARC --> FFE --> 1-D PAGE --> 2-D-nanoLC-MS/MS may be considered as a widely applicable standard platform technology for fractionation of complex samples like plasma.

Policies supporting the rapid and open sharing of genomic data have directly fueled the accelerated pace of discovery in large-scale genomics research. The proteomics community is starting to implement analogous policies and infrastructure for making large-scale proteomics data widely available on a pre-competitive basis. On August 14, 2008, the National Cancer Institute (NCI) convened the “International Summit on Proteomics Data Release and Sharing Policy” in Amsterdam, the Netherlands, to identify and address potential roadblocks to rapid and open access to data. The six principles agreed upon by key stakeholders at the summit addressed issues surrounding 1) timing, 2) comprehensiveness, 3) format, 4) deposition to repositories, 5) quality metrics, and 6) responsibility for proteomics data release. This summit report explores various approaches to develop a framework of data release and sharing principles that will most effectively fulfill the needs of the funding agencies and the research community.

1 Efforts to determine the role of stretch-dependent K þ (SDK) channels in enteric inhibitory neural responses in gastrointestinal muscles are difficult due to a lack of blocking drugs for SDK channels. 2 SDK channels are blocked by sulfur-containing amino acids. These compounds reduced the open probability of SDK channels in on and off-cell patches of murine colonic myocytes. L-Methionine was the most selective and had little or no effect on other known K þ conductances in colonic myocytes.