Question

Similarities and differences between the domains provide contradictory information about their

potential origins. How do lipid structures contribute to this controversy

Answer 1

Lipids

Lipids are a diverse and ubiquitous group of compounds which have many key biological functions, such as acting as structural components of cell membranes, serving as energy storage sources and participating in signaling pathways. 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 post-genomic revolution and systems biology. The word “lipidome” is used to describe the complete lipid profile within a cell, tissue or organism and is a subset of the “metabolome” which also includes the three other major classes of biological molecules: amino-acids, sugars and nucleic acids. Lipidomics is a relatively recent research field that has been driven by rapid advances in a number of analytical technologies, in particular mass spectrometry (MS), and computational methods, coupled with the recognition of the role of lipids in many metabolic diseases such as obesity, atherosclerosis, stroke, hypertension and diabetes. This rapidly expanding field complements the huge progress made in genomics and proteomics, all of which constitute the family of systems biology. The diversity in lipid function is reflected by an enormous variation in the structures of lipid molecules.

Unlike the case of genes and proteins which are primarily composed of linear combinations of 4 nucleic acids and 20 amino acids, respectively, lipid structures are generally much more complex due to the number of different biochemical transformations which occur during their biosynthesis. This level of diversity makes it important to develop a comprehensive classification, nomenclature, and chemical representation system to accommodate the myriad lipids that exist in nature. A modern, robust classification system in turn paves the way for creation of a comprehensive bioinformatics infrastructure that includes databases of lipids and lipid-associated genes, tools for representing lipid structures, interfaces for analyzing lipidomic experimental data and methodologies for studying lipids at a systems-biology level. This article summarizes the efforts of the LIPID MAPS consortium to address these informatics challenges and play a part in the establishment of lipidomics as a field of emerging importance in biology.

Lipid structures

Lipids display remarkable structural diversity, driven by factors such as variable chain length, a multitude of oxidative, reductive, substitutional and ring-forming biochemical transformations as well as modification with sugar residues and other functional groups of different biosynthetic origin. There are no reliable estimates of the number of discrete lipid structures in nature, due to the technical challenges of elucidating chemical structures. Estimates in the order of 200,000, based on acyl/alkyl chain and glycan permutations for glycerolipids, glycerophospholipids and sphingolipids are almost certainly on the conservative end [14]. This number is actually exceeded by the list of known natural products, most of which are of either prenol or polyketide origin [15]. Given the importance of these molecules in cellular function and pathology, it is essential to have well-organized databases of lipids with relevant structural information and related features.

The field of lipidomics has made rapid progress on many fronts over the past two decades although it has still to achieve the same level of advancement and knowledge as genomics and proteomics. The diversity of lipid chemical structures presents a challenge both from the experimental and informatics standpoints. The need for a robust, scalable bioinformatics infrastructure is high at a number of different levels:

• establishment of a globally accepted classification system, creation of databases of lipid structures, lipid-related genes and proteins,
• efficient analysis of experimental data,
• efficient management of metadata and protocols,
• integration of experimental data and existing knowledge into metabolic and signaling pathways,
• development of informatics software for efficient searching, display and analysis of lipidomic data. The study of mammalian lipdomes has been complemented in recent years by comprehensive lipidomic analyses of yeast, mycobacteria, archaebacteria and plants, each with its own set of challenges and insights which will need to be addressed by collaborative efforts between biology, chemistry and bioinformatics.

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