Hunting for protein markers of hypoxia by combining plasma membrane enrichment with a new approach to membrane protein analysis.

Nontransient hypoxia is strongly associated with malignant lesions, resulting in aggressive behavior and resistance to treatment. We present an analysis of mRNA and protein expression changes in neuroblastoma cell lines occurring upon the transition from normoxia to hypoxia. The correlation between mRNA and protein level changes was poor, although some known hypoxia-driven genes and proteins correlated well. We present previously undescribed membrane proteins expressed under hypoxic conditions that are candidates for evaluation as biomarkers.

Omics analyses reveal a potential link between hormone-sensitive lipase and polyamine metabolism.

Hormone-sensitive lipase (HSL), a key enzyme in fatty acid mobilization from lipid stores, is expressed in the liver and decreased hepatic insulin sensitivity has been reported in our HSL null mouse model. Here, an integrated approach, comprising transcriptomics and proteomics together with targeted metabolite analysis, was used to investigate the liver phenotype of HSL null mice. Oligonucleotide microarray analysis revealed altered expression of genes involved in lipid and polyamine metabolism in HSL null mice compared with wild-type mice and in genes controlling the immune system in mice on high-fat diet versus mice on normal diet. Two-dimensional gel electrophoresis followed by MS and/or MS/MS allowed identification of 52 and 22 unique proteins differentially regulated according to the genotype and diet, respectively. Changes were observed mainly for proteins related to metabolism, including several proteins involved in polyamine metabolism or exhibiting methyl transferase activity. Despite the coordinated changes in mRNA and protein levels in polyamine pathways, no significant differences in levels of key polyamine metabolites were detected between the two genotypes. This study identifies a link between HSL and polyamine metabolism, which deserves further attention in view of the emerging data suggesting that disturbances in polyamine metabolism may affect insulin sensitivity. The present work also describes a limited correlation between mRNA, protein and metabolite levels, thus, underscoring the importance of integrated approaches.

The proteios software environment: an extensible multiuser platform for management and analysis of proteomics data.

Proteome analysis involves many steps that generate large quantities of data in different formats. This creates a need for automatic data merging and extraction of important features from data. Furthermore, metadata need to be collected and reported to enable critical evaluation of results. Many data analysis tools are developed locally in research laboratories and are nontrivial to adapt for other laboratories, preventing optimal exploitation of generated data. The proteomics field would benefit from user-friendly analysis and data management platforms in which method developers can make their analysis tools available for the community. Here, we describe the Proteios Software Environment (ProSE) that is built around a Web-based local data repository for proteomics experiments. The application features sample tracking, project sharing between multiple users, and automated data merging and analysis. ProSE has built-in support for several quantitative proteomics workflows, and integrates searching in several search engines, automated combination of the search results with predetermined false discovery rates, annotation of proteins and submission of results to public repositories. ProSE also provides a programming interface to enable local extensions, as well as database access using Web services. ProSE provides an analysis platform for proteomics research and is targeted for multiuser projects with needs to share data, sample tracking, and analysis result. ProSE is open source software available at http://www.proteios.org .

Membrane protein identification: N-terminal labeling of nontryptic membrane protein peptides facilitates database searching.

Membrane proteins are fairly refractory to digestion especially by trypsin, and less specific proteases, such as elastase and pepsin, are much more effective. However, database searching using nontryptic peptides is much less effective because of the lack of charge localization at the N and C termini and the absence of sequence specificity. We describe a method for N-terminal-specific labeling of peptides from nontryptic digestions of membrane proteins, which facilitates Mascot database searching and can be used for relative quantitation. The conditions for digestion have been optimized to obtain peptides of a suitable length for mass spectrometry (MS) fragmentation. We show the effectiveness of the method using a plasma membrane preparation from a leukemia cell line and demonstrate a large increase in the number of membrane proteins, with small extra-membranar domains being identified in comparison to previous published methods.

Metabolomic and proteomic analysis of a clonal insulin-producing beta-cell line (INS-1 832/13).

Metabolites generated from fuel metabolism in pancreatic beta-cells control exocytosis of insulin, a process which fails in type 2 diabetes. To identify and quantify these metabolites, global and unbiased analysis of cellular metabolism is required. To this end, polar metabolites, extracted from the clonal 832/13 beta-cell line cultured at 2.8 and 16.7 mM glucose for 48 h, were derivatized followed by identification and quantification, using gas chromatography (GC) and mass spectrometry (MS). After culture at 16.7 mM glucose for 48 h, 832/13 beta-cells exhibited a phenotype reminiscent of glucotoxicity with decreased content and secretion of insulin. The metabolomic analysis revealed alterations in the levels of 7 metabolites derived from glycolysis, the TCA cycle and pentose phosphate shunt, and 4 amino acids. Principal component analysis of the metabolite data showed two clusters, corresponding to the cells cultured at 2.8 and 16.7 mM glucose, respectively. Concurrent changes in protein expression were analyzed by 2-D gel electrophoresis followed by LC-MS/MS. The identities of 86 spots corresponding to 75 unique proteins that were significantly different in 832/13 beta-cells cultured at 16.7 mM glucose were established. Only 5 of these were found to be metabolic enzymes that could be involved in the metabolomic alterations observed. Anticipated changes in metabolite levels in cells exposed to increased glucose were observed, while changes in enzyme levels were much less profound. This suggests that substrate availability, allosteric regulation, and/or post-translational modifications are more important determinants of metabolite levels than enzyme expression at the protein level.

Development of reagents for differential protein quantitation by subtractive parent (precursor) ion scanning.

We present a generic approach for quantitative differential proteomics that reduces data complexity in proteome analysis by automated selection of peptides for MS/MS analysis according to their isotope-labeling ratio. Isotopic reagents were developed that give products which fragment easily to generate a unique pair of signature ions. Using the ion-pair ratio, we show that it is possible to select only BSA peptides (with a 3:1 light heavy isotope ratio) for MS/MS when spiked in a whole yeast extract using Parent (precursor) Ion Quantitation Scanning (PIQS) for MS/MS.

Automated reporting from gel-based proteomics experiments using the open source Proteios database application.

The assembly of data from different parts of proteomics workflow is often a major bottleneck in proteomics. Furthermore, there is an increasing demand for the publication of details about protein identifications due to the problems with false-positive and false-negative identifications. In this report, we describe how the open-source Proteios software has been expanded to automate the assembly of the different parts of a gel-based proteomics workflow. In Proteios it is possible to generate protein identification reports that contain all the information currently required by proteomics journals. It is also possible for the user to specify maximum allowed false positive ratios, and reports are automatically generated with the corresponding score cut-offs calculated. When protein identification is conducted using multiple search engines, the score thresholds that correlate to the predetermined error rate are also explicitly calculated for proteins that appear on the result lists of more than one search engine.