The synthesis and excretion of bile acids comprise the major pathway of cholesterol catabolism in mammals. Synthesis provides a direct means of converting cholesterol, which is both hydrophobic and insoluble, into a water-soluble and readily excreted molecule, the bile acid. The biosynthetic steps that accomplish this transformation also confer detergent properties to the bile acid, which are exploited by the body to facilitate the secretion of cholesterol from the liver. This role in the elimination of cholesterol is counterbalanced by the ability of bile acids to solubilize dietary cholesterol and essential nutrients and to promote their delivery to the liver. The synthesis of a full complement of bile acids requires 17 enzymes. The expression of selected enzymes in the pathway is tightly regulated by nuclear hormone receptors and other transcription factors, which ensure a constant supply of bile acids in an ever changing metabolic environment. Inherited mutations that impair bile acid synthesis cause a spectrum of human disease; this ranges from liver failure in early childhood to progressive neuropathy in adults.

In this era of genomics, transcriptomics, and proteomics, metabolomics is emerging as an important component of the omics evolution ( 1 ). Of the four kinds of biological molecules that comprise the human body, i.e., nucleic acids, amino acids (proteins), carbohydrates (sugars), and lipids (fats), lipids stand out among the various cellular metabolites in the sheer number of distinct molecular species. Using state-of-the-art lipidomics approaches made possible by newly developed instrumentation, protocols, and bioinformatics tools ( 2 ), the LIPID MAPS Consortium Abstract The focus of the present study was to defi ne the human plasma lipidome and to establish novel analytical methodologies to quantify the large spectrum of plasma lipids. Partial lipid analysis is now a regular part of every patient's blood test and physicians readily and regularly prescribe drugs that alter the levels of major plasma lipids such as cholesterol and triglycerides. Plasma contains many thousands of distinct lipid molecular species that fall into six main categories including fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterols, and prenols. The physiological contributions of these diverse lipids and how their levels change in response to therapy remain largely unknown. As a fi rst step toward answering these questions, we provide herein an in-depth lipidomics analysis of a pooled human plasma obtained from healthy individuals after overnight fasting and with a gender balance and an ethnic distribution that is representative of the US population. In total, we quantitatively assessed the levels of over 500 distinct molecular species distributed among the main lipid categories. As more information is obtained regarding the roles of individual lipids in health and disease, it seems likely that future blood tests will include an ever increasing number of these lipid molecules. -Quehenberger, O., A.

Here we describe the cloning and characterization of a PAS domain transcription factor termed endothelial PAS-1 (EPAS1). This protein shares 48% sequence identity with hypoxia inducible factor (HIF-I~) and lesser similarity with other members of the basic helix-loop-helix/PAS domain family of transcription factors. Like HIF-lc~, EPAS1 binds to and activates transcription from a DNA element originally isolated from the erythropoietin gene and containing the sequence 5'-GCCCTACGTGCTGTCTCA-3'. Activation by both HIF-I~ and EPAS1 is stimulated by hypoxic conditions. EPAS1 forms a heterodimeric complex with the aryl hydrocarbon nuclear transporter prior to transcriptional activation of target genes. EPAS1 expression is limited to the endothelium of mouse embryos and, in agreement with its cell type-specific expression pattern, is capable of specifically activating the transcription of the endothelial tyrosine kinase gene Tie-2. These observations raise the possibility that EPAS1 may represent an important regulator of vascularization, perhaps involving the regulation of endothelial cell gene expression in response to hypoxia.[Key Words: PAS domain proteins; endothelial cell transcription; receptor tyrpsine kinase; Tie-2; hypoxia inducible factor; chromosome 2p [16][17][18][19][20][21]

The LIPID MAPS Structure Database (LMSD) is a relational database encompassing structures and annotations of biologically relevant lipids. Structures of lipids in the database come from four sources: (i) LIPID MAPS Consortium's core laboratories and partners; (ii) lipids identified by LIPID MAPS experiments; (iii) computationally generated structures for appropriate lipid classes; (iv) biologically relevant lipids manually curated from LIPID BANK, LIPIDAT and other public sources. All the lipid structures in LMSD are drawn in a consistent fashion. In addition to a classification-based retrieval of lipids, users can search LMSD using either text-based or structure-based search options. The text-based search implementation supports data retrieval by any combination of these data fields: LIPID MAPS ID, systematic or common name, mass, formula, category, main class, and subclass data fields. The structure-based search, in conjunction with optional data fields, provides the capability to perform a substructure search or exact match for the structure drawn by the user. Search results, in addition to structure and annotations, also include relevant links to external databases. The LMSD is publicly available at

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Lipids are produced, transported, and recognized by the concerted actions of numerous enzymes, binding proteins, and receptors. A comprehensive analysis of lipid molecules, "lipidomics," in the context of genomics and proteomics is crucial to understanding cellular physiology and pathology; consequently, lipid biology has become a major research target of the postgenomic revolution and systems biology. To facilitate international communication about lipids, a comprehensive classification of lipids with a common platform that is compatible with informatics requirements has been developed to deal with the massive amounts of data that will be generated by our lipid community. As an initial step in this development, we divide lipids into eight categories (fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids, prenol lipids, saccharolipids, and polyketides) containing distinct classes and subclasses of molecules, The goal of collecting data on lipids using a "systems biology" approach to lipidomics requires the development of a comprehensive classification, nomenclature, and chemical representation system to accommodate the myriad lipids that exist in nature. Lipids have been loosely defined as biological substances that are generally hydrophobic in nature and in many cases soluble in organic solvents (1). These chemical properties cover a broad range of mole-

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