The future challenges of lipidomics include the development of chemistries and technologies to increase the penetrance into the lipidome, identification of the subcellular compartments or domains where alterations are manifest during cellular adaptation or disease, and the development of bioinformatic approaches to define changes in lipid metabolic networks that can predict the onset of disease, identify disease progression and evaluate treatment efficacy. The development of increasingly sophisticated databases that contain the exact mass, fragmentation patterns and HPLC elution characteristics of each lipid molecular species is essential for the continued development of lipidomics and in its application to biomedical research. Currently there are three main databases that are routinely utilized for lipidomics research including METLIN (Smith et al., 2005
), The Human Metabolome Database (Wishart et al., 2008
), and LIPID MAPS (Sud et al., 2007
). Through the use of ESI in conjunction with time of flight mass spectrometry, Shevchenko et al. used a Shotgun Lipidomics strategy in conjunction with custom software to identify over 250 lipids from yeast (Ejsing et al., 2009
). Dennis et al identified over 400 lipids in RAW 267.2 cells using the LIPID MAPS database and demonstrated alterations in multiple lipid classes and molecular species after cellular stimulation (Dennis et al., 2010
). Siuzdak et al. identified over 150 lipids in stem cells during differentiation and found increases in the unsaturation index of aliphatic chains that alter membrane structure and dynamics during differentiation (Yanes et al., 2010
). Collectively, these studies demonstrate the dynamic role of alterations in lipid molecular species content and membrane composition that serve to facilitate cellular differentiation and cellular activation. Through orchestrating changes in membrane lipid composition, molecular structure and membrane dynamics the execution of intrinsic biologic programs (e.g., differentiation) or responses to external perturbations necessary for life processes are facilitated.
Many other methods for ionization of lipids for mass spectrometry have been used with great success. In pioneering work, Marshall et al. demonstrated the utility of matrix assisted laser desorption/ionization (MALDI) for lipid analysis in conjunction with high mass accuracy using FT-ICR (Marto et al., 1995
). The use of laser-based methods have the obvious advantage of allowing high throughput analyses with rapid repetition rate lasers that are unencumbered by the time constraints normally encountered using fluid-based methods for mass spectrometry. The use of MALDI/TOF-TOF mass spectrometry for lipidomic analysis of biologic tissues has recently been further developed for high throughput lipidomics where many dozens of samples can be directly analyzed within minutes facilitating the large scale application of lipidomics to human disease through this high throughput approach (Sun, et al., 2008
). Moreover, laser or beam ionization methods provide a platform for innovative chemical strategies for matrix construction that can be exploited for selective ionization (e.g., the selective ionization/desorption of discrete lipid classes) or can be used for non-biased identification and quantitation of analytes. In elegant work, Siuzdak et al. engineered nanostructured surfaces to trap fluorinated siloxanes that desorb analytes upon laser-induced vaporization (e.g., Northen et al., 2007
). Through multiplexing different surface-based technologies, doping with selected cavitands and the construction of engineered charge transfer complexes to facilitate class-specific ionization, the future growth of MALDI TOF/TOF mass spectrometry is assured. Moreover, recent success with MALDI imaging (Reyzer and Caprioli, 2005
), desorption ESI (DESI) imaging (Takats et al., 2004
) techniques, and nanostructured surfaces (Patti et al., 2010
) has led to new insights into the spatial distribution of lipids in tissues, but at present these methods are limited by constraints on spatial resolution. A prominent issue in lipidomics is the identification of methods to delineate alterations in membrane composition in discrete subcellular loci or within specific membrane domains. Thus, the development of methods which precisely localize changes in specific compartments or domains in intact cells is a fundamental goal of future lipidomics research. The use of secondary ion mass spectrometry using ion beams has greatly enhanced spatial resolution to the order of 100 nm that can identify lipids in specific membrane domains (Winograd and Garrison, 2010
). Additional technologic advances are anticipated in these fields that will define spatially privileged domains within cell membranes and subcellular compartments, identify unknown lipids and greatly facilitate our understanding of membrane structure and function.
Nuclear magnetic resonance (NMR) spectroscopy has been used to identify a wide variety of lipids in biological systems (e.g., Lindon and Nicholson, 2008
and references therein). Mountford and colleagues used 1
H NMR to distinguish invasive breast cancer from benign lesions on the basis of increased total choline phospholipid species (Mackinnon et al., 1997
). While NMR is a nondestructive and nonselective technique that provides unique information pertaining to molecular structure and dynamics, its modest sensitivity and resolving power to distinguish individual chemical species in comparison to mass spectrometry has limited utilization of NMR in lipidomics investigations. NMR interpretation is also complicated by the considerable number of spin-coupled multiplets that result in spectral crowding. Recently this problem has been addressed by using two-dimensional J
-resolved NMR spectroscopy to visualize metabolite chemical shifts and J
-couplings along different spectral dimensions and thereby increase peak dispersion (Ludwig and Viant, 2010
). An advantage of magnetic resonance approaches is the ability to analyze lipids non-invasively in intact cells and tissues without losing chemical information about the analyte environment (Beckonert et al., 2010
). A review of the methods used in high-resolution magic-angle spinning NMR, their application to lipidomics and their potential biomedical uses have been discussed recently (Fonville et al., 2010
). Moreover, selective recoupling of dipolar and chemical-shift interactions removed by magic-angle spinning in the solid state allows for the characterization of regulatory interactions, dynamics, and ion channels within biological membranes (Guillion and Schaefer, 1989
; deAzevedo et al., 1999
; Kim et al., 2009
; and Cady et al., 2010
). Since NMR is a non-destructive technique it can be used to interrogate alterations in lipid structure and dynamics in biochemically functioning cells. Thus, it is anticipated that future developments will provide critical information on alterations in membrane structure and function through the synergistic application of a variety of solution state and solid state NMR approaches.
The past decades have witnessed the rapid growth and development of lipidomics, which has now become an essential part of Systems Biology. MultiDimensional Mass Spectrometry-based Shotgun Lipidomics has now been developed into a robust technology that can be used to provide rapid access to the mechanisms underlying diverse disease states. Continuing advances in ionization technologies, use of high mass accuracy lipidomics, novel fragmentation strategies, improvements in enrichment approaches and enhanced spatial resolution in conjunction with NMR-based approaches will collectively lead to the development of a comprehensive understanding of the pleiotropic roles of lipids in cellular function.