Although the transcriptome, proteome, and interactome of several eukaryotic model organisms have been described in detail, lipidomes remain relatively uncharacterized. Using Saccharomyces cerevisiae as an example, we demonstrate that automated shotgun lipidomics analysis enabled lipidome-wide absolute quantification of individual molecular lipid species by streamlined processing of a single sample of only 2 million yeast cells. By comparative lipidomics, we achieved the absolute quantification of 250 molecular lipid species covering 21 major lipid classes. This analysis provided Ϸ95% coverage of the yeast lipidome achieved with 125-fold improvement in sensitivity compared with previous approaches. Comparative lipidomics demonstrated that growth temperature and defects in lipid biosynthesis induce ripple effects throughout the molecular composition of the yeast lipidome. This work serves as a resource for molecular characterization of eukaryotic lipidomes, and establishes shotgun lipidomics as a powerful platform for complementing biochemical studies and other systems-level approaches.fatty acid elongation ͉ S. cerevisiae ͉ shotgun lipidomics T he lipidome of eukaryotic cells consists of hundreds to thousands of individual lipid species that constitute membranes, store metabolic energy and function as bioactive molecules (1-3). Despite the extensive characterization of proteins, their association into complexes and activities (4-6), it is still difficult to assess how perturbations within the lipid metabolic network affect the full lipidome of cells. This work shows that lipidome-wide quantification of individual molecular lipid species (molecules with defined chemical structure) by absolute quantification (expressed in mol or mol%) provides a new approach to relate lipidomics and functional genomics studies.The yeast Saccharomyces cerevisiae serves as a prime model organism for studying the molecular organization and regulatory circuitry of eukaryotic lipidomes (7-9). It uses a relatively simple and conserved network of lipid metabolic pathways (Fig. 1) that synthesize a few hundred molecular lipid species constituting its full lipidome (3). The lipidome diversity is primarily determined by the fatty acid synthase (10), the ⌬-9 desaturase (11) and the fatty acid elongation complex (12) that produce only saturated or mono-unsaturated fatty acids having 10 to 26 carbon atoms for the biosynthesis of glycerolipids, glycerophospholipids, and sphingolipids. Importantly, several metabolic conversions interlink sphingolipid, glycerophospholipid, and glycerolipid metabolism such that any perturbation within the metabolic network is prone to induce lipidome-wide ripple effects. Remarkably, numerous genes involved in lipid metabolism and trafficking can be mutated or deleted without apparent physiological consequences (Fig. 1).Despite remarkable methodological advances, lipidomics seldom complements functional genomics efforts owing to three major factors. First, analysis of glycerophospholipids and sphingolipids requires ...

Human Protein Reference Database (HPRD) is an object database that integrates a wealth of information relevant to the function of human proteins in health and disease. Data pertaining to thousands of protein-protein interactions, posttranslational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localization were extracted from the literature for a nonredundant set of 2750 human proteins. Almost all the information was obtained manually by biologists who read and interpreted >300,000 published articles during the annotation process. This database, which has an intuitive query interface allowing easy access to all the features of proteins, was built by using open source technologies and will be freely available at http://www.hprd.org to the academic community. This unified bioinformatics platform will be useful in cataloging and mining the large number of proteomic interactions and alterations that will be discovered in the postgenomic era.

The rapid pace at which genomic and proteomic data is being generated necessitates the development of tools and resources for managing data that allow integration of information from disparate sources. The Human Protein Reference Database (http://www.hprd.org) is a web-based resource based on open source technologies for protein information about several aspects of human proteins including protein-protein interactions, post-translational modifications, enzyme-substrate relationships and disease associations. This information was derived manually by a critical reading of the published literature by expert biologists and through bioinformatics analyses of the protein sequence. This database will assist in biomedical discoveries by serving as a resource of genomic and proteomic information and providing an integrated view of sequence, structure, function and protein networks in health and disease.

Cell division is fundamental for all organisms. Here we report a genome-scale RNA-mediated interference screen in HeLa cells designed to identify human genes that are important for cell division. We have used a library of endoribonuclease-prepared short interfering RNAs for gene silencing and have used DNA content analysis to identify genes that induced cell cycle arrest or altered ploidy on silencing. Validation and secondary assays were performed to generate a nine-parameter loss-of-function phenoprint for each of the genes. These phenotypic signatures allowed the assignment of genes to specific functional classes by combining hierarchical clustering, cross-species analysis and proteomic data mining. We highlight the richness of our dataset by ascribing novel functions to genes in mitosis and cytokinesis. In particular, we identify two evolutionarily conserved transcriptional regulatory networks that govern cytokinesis. Our work provides an experimental framework from which the systematic analysis of novel genes necessary for cell division in human cells can begin.

Direct profiling of total lipid extracts on a hybrid LTQ Orbitrap mass spectrometer by high-resolution survey spectra clusters species of 11 major lipid classes into 7 groups, which are distinguished by their sum compositions and could be identified by accurately determined masses. Rapid acquisition of survey spectra was employed as a "top-down" screening tool that, together with the computational method of principal component analysis, revealed pronounced perturbations in the abundance of lipid precursors within the entire series of experiments. Altered lipid precursors were subsequently identified either by accurately determined masses or by in-depth MS/MS characterization that was performed on the same instrument. Hence, the sensitivity, throughput and robustness of lipidomics screens were improved without compromising the accuracy and specificity of molecular species identification. The top-down lipidomics strategy lends itself for high-throughput screens complementing ongoing functional genomics efforts.