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 peroxisome represents a ubiquitous single membrane-bound key organelle that executes various metabolic pathways such as fatty acid degradation by ␣-and -oxidation, ether-phospholipid biosynthesis, metabolism of reactive oxygen species, and detoxification of glyoxylate in mammals. To fulfil this vast array of metabolic functions, peroxisomes accommodate ϳ50 different enzymes at least as identified until now. Interest in peroxisomes has been fueled by the discovery of a group of genetic diseases in humans, which are caused by either a defect in peroxisome biogenesis or the deficient activity of a distinct peroxisomal enzyme or transporter. Although this research has greatly improved our understanding of peroxisomes and their role in mammalian metabolism, deeper insight into biochemistry and functions of peroxisomes is required to expand our knowledge of this low abundance but vital organelle. In this work, we used classical subcellular fractionation in combination with MS-based proteomics methodologies to characterize the proteome of mouse kidney peroxisomes. We could identify virtually all known components involved in peroxisomal metabolism and biogenesis. Moreover through protein localization studies by using a quantitative MS screen combined with statistical analyses, we identified 15 new peroxisomal candidates. Of these, we further investigated five candidates by immunocytochemistry, which confirmed their localization in peroxisomes. As a result of this joint effort, we believe to have compiled the so far most comprehensive protein catalogue of mammalian peroxisomes.
Proteomics-based clinical studies have been shown to be promising strategies for the discovery of novel biomarkers of a particular disease. Here, we present a study of hepatocellular carcinoma (HCC) that combines complementary two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography (LC-MS)-based approaches of quantitative proteomics. In our proteomic experiments, we analyzed a set of 14 samples (7 ؋ HCC versus 7 ؋ nontumorous liver tissue) with both techniques. Thereby we identified 573 proteins that were differentially expressed between the experimental groups. Among these, only 51 differentially expressed proteins were identified irrespective of the applied approach. Using Western blotting and immunohistochemical analysis the regulation patterns of six selected proteins from the study overlap (inorganic pyrophosphatase 1 (PPA1), tumor necrosis factor type 1 receptor-associated protein 1 (TRAP1), betaine-homocysteine S-methyltransferase 1 (BHMT)) were successfully verified within the same sample set. In addition, the up-regulations of selected proteins from the complements of both approaches (major vault protein (MVP), gelsolin (GSN), chloride intracellular channel protein 1 (CLIC1)) were also reproducible. Within a second independent verification set (n ؍ 33) the altered protein expression levels of major vault protein and betaine-homocysteine S-methyltransferase were further confirmed by Western blots quantitatively analyzed via densitometry. For the other candidates slight but nonsignificant trends were detectable in this independent cohort. Based on these results we assume that major vault protein and betaine-homocysteine S-methyltransferase have the potential to act as diagnostic HCC biomarker candidates that are worth to be followed in further validation studies. Hepatocellular carcinoma (HCC)1 currently is the fifth most common malignancy worldwide with an annual incidence up to 500 per 100,000 individuals depending on the geographic region investigated. Whereas 80% of new cases occur in developing countries, the incidence increases in industrialized nations including Western Europe, Japan, and the United States (1). To manage patients with HCC, tumor markers are very important tools for diagnosis, indicators of disease progression, outcome prediction, and evaluation of treatment efficacy. Several tumor markers have been reported for HCC, including ␣-fetoprotein (AFP) (2), Lens culinaris agglutininreactive fraction of AFP (AFP-L3) (3), and des-␥-carboxyl prothrombin (DCP) (4). However, none of these tumor markers show 100% sensitivity or specificity, which calls for new and better biomarkers.To identify novel biomarkers of HCC, many clinical studies using "omics"-based methods have been reported over the past decade (5-6). In particular, the proteomics-based approach has turned out to be a promising one, offering several quantification techniques to reveal differences in protein expression that are caused by a particular disease. In most studies, the well-established 2D-D...
Improved non-invasive strategies for early cancer detection are urgently needed to reduce morbidity and mortality. Non-coding RNAs, such as microRNAs and small nucleolar RNAs, have been proposed as biomarkers for non-invasive cancer diagnosis. Analyzing serum derived from nude mice implanted with primary human pancreatic ductal adenocarcinoma (PDAC), we identified 15 diagnostic microRNA candidates. Of those miR-1246 was selected based on its high abundance in serum of tumor carrying mice. Subsequently, we noted a cross reactivity of the established miR-1246 assays with RNA fragments derived from U2 small nuclear RNA (RNU2-1). Importantly, we found that the assay signal discriminating tumor from controls was derived from U2 small nuclear RNA (snRNA) fragments (RNU2-1f) and not from miR-1246. In addition, we observed a remarkable stability of RNU2-1f in serum and provide experimental evidence that hsa-miR-1246 is likely a pseudo microRNA. In a next step, RNU2-1f was measured by qRT-PCR and normalized to cel-54 in 191 serum/plasma samples from PDAC and colorectal carcinoma (CRC) patients. In comparison to 129 controls, we were able to classify samples as cancerous with a sensitivity and specificity of 97.7% [95% CI 5 (87.7, 99.9)] and 90.6% [95% CI 5 (80.7, 96.5)], respectively [area under the ROC curve 0.972]. Of note, patients with CRC were detected with our assay as early as UICC Stage II with a sensitivity of 81%. In conclusion, this is the first report showing that fragments of U2 snRNA are highly stable in serum and plasma and may serve as novel diagnostic biomarker for PDAC and CRC for future prospective screening studies.
Filaminopathy is a subtype of myofibrillar myopathy caused by mutations in FLNC, the gene encoding filamin C, and histologically characterized by pathologic accumulation of several proteins within skeletal muscle fibers. With the aim to get new insights in aggregate composition, we collected aggregates and control tissue from skeletal muscle biopsies of six myofibrillar myopathy patients harboring three different FLNC mutations by laser microdissection and analyzed the samples by a label-free mass spectrometry approach. A total of 390 proteins were identified, and 31 of those showed significantly higher spectral indices in aggregates compared with patient controls with a ratio >1.8. These proteins included filamin C, other known myofibrillar myopathy associated proteins, and a striking number of filamin C binding partners. Across the patients the patterns were extremely homogeneous. Xin actin-binding repeat containing protein 2, heat shock protein 27, nebulin-related-anchoring protein, and Rab35 could be verified as new filaminopathy biomarker candidates. In addition, further experiments identified heat shock protein 27 and Xin actin-binding repeat containing protein 2 as novel filamin C interaction partners and we could show that Xin actin-binding repeat containing protein 2 and the known interaction partner Xin actinbinding repeat containing protein 1 simultaneously associate with filamin C. Ten proteins showed significant lower spectral indices in aggregate samples compared with patient controls (ratio <0.56) including M-band proteins myomesin-1 and myomesin-2. Proteomic findings were consistent with previous and novel immunolocalization data. Our findings suggest that aggregates in filaminopathy have a largely organized structure of proteins also interacting under physiological conditions. Different filamin C mutations seem to lead to almost identical aggregate compositions. The finding that filamin C was detected as highly abundant protein in aggregates in filaminopathy indicates that our proteomic approach may be suitable to identify new candidate genes among the many MFM patients with so far unknown mutation. Molecular & Cellular Proteomics
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