ReviewTracer-based metabolomics: Concepts and practices
Introduction
Recent developments in high throughput technologies have enabled profiling of mRNA, proteins and metabolites giving rise to the fields of transcriptomics, proteomics and metabolomics. Metabolomics (metabonomics) being the latest addition to the “-omics” was initially conceived by an industrial and academic consortium (Consortium for Metabonomic Toxicology; COMET) for rapid screening of drug toxicity using nuclear magnetic resonance (NMR) technology [1], [2]. The formation of metabolites being the final manifestation of gene expressions makes the profiling of these metabolic products a useful tool for characterization of phenotype. For such reasoning, metabolomics (metabolite profiling) has found its use in genotype–phenotype correlations and biomarker discoveries in addition to its use in toxicology and drug development [3], [4]. In the intervening years since COMET, improvement in the sensitivity and mass accuracy in mass spectrometry has made mass spectrometry the choice instrumentation in compound identification and quantitation of metabolites in biological samples [5], [6]. Significant progress in metabolomics has been made in the first publication of the human metabolome and the establishment of many reference databases such as Human Metabolome Database [7] (www.hmdb.ca) and LIPIDMAP (www.lipidmap.org ). Other web-based tools for data processing and data presentation have been developed [8], [9], [10].
Despite successes in improved compound identification and quantitation, there still remain conceptual challenges and technical limitations typical to the use of mass spectrometry in quantitative analysis [11], [12]. For non-targeted analyses, the wide range of metabolite concentrations from millimolar to picomolar range requires conscious choices to either develop algorithms to increase the number of compounds detected, or narrowing the profile to compounds in a pre-determined range of molecular weights or classes. For targeted analyses, in the absence of isotope recovery standards, issues such as matrix effect and ion-suppression present huge challenges to quantitative analysis. There are also considerations that are common to other biological investigations such as experimental design, sampling procedure, sample preparation and convention in data presentation (dimension or unit of measure). Given these limitations, results from metabolomics are mostly semiquantitative in nature and are useful for analysis by principal component analysis (PCA) for identifying special features of a metabolic phenotype, and partial least squares analysis (PLS) for comparison of two phenotypes [13], [14].
Tracer-based metabolomics is a special form of targeted metabolomics in which the distribution of 13C from a labeled precursor among various metabolic intermediates is determined [15], [16], [17]. The use of stable isotope tracers and mass isotopomer analysis helps to define the metabolic intermediates relevant to the objective of the study. The known metabolic pathways allow interpretation of precursor-product relationship of compounds, and the distribution of 13C allows the determination of quantitative relationship between precursor and product [18]. The data from tracer-based metabolomics can be analyzed and interpreted using constraint based modeling and phenotypic phase plane analysis [16], [17] providing tracer-based metabolomics the capability of quantitative comparison of phenotypes making it a truly systems biology approach. In this review, the concepts of tracer-based metabolomics are outlined, and examples of its application in studies of metabolic responses of cells to pharmacological agents and nutrient environment changes are presented.
Section snippets
Application of stable isotope tracers and mass isotopomer analysis
Radioactive and non-radioactive isotopes have been the principal tools for the study of kinetics of biochemical reactions. Traditionally, radioisotopes have been used for their high sensitivity. Many of these radioisotope applications such as incorporation of radioactive thymidine in determining DNA synthesis are still in use today. The appearance of radioactivity in the product or the disappearance of radioactivity in the precursors over time is used to determine the rate of reaction of
Quantitative aspects of isotopomer analysis
In quantitative analysis, the unit of measure (dimension) is important in the calculation of synthesis or degradation rate. The unit of measure used in tracer-based metabolomics is expressed in terms of isotopomer molar fraction (or ratios), and isotopic enrichment per molecule (or per carbon atom) of metabolites rather than relative concentrations (activities) of metabolites in a sample as in many metabolomics studies. In cases where absolute concentration of a metabolite is determined, the
Constraint based modeling and phenotypic phase plane analysis
In the past decade, the combination of pathway analysis and flux balance analysis has been applied in metabolic studies [41], [42], [43]. Such a combined approach is known as constraint-based modeling [44]. There are three basic meanings of constraint-based modeling. The first meaning is derived from the fact that every reaction in a cell is connected to another reaction of the network. Thus every biochemical reaction is constrained by every other reaction through shared co-factors, substrates
Modeling of mass isotopomer data in tracer-based metabolomics
The use of stable isotope in tracer-based metabolomics generates a large amount of isotopomer data. Each isotopomer of a metabolite is essentially a measure of an “extreme pathway.” Therefore, tracer-based metabolomics is a quantitative analysis of metabolic phenotypes among the various approaches in metabolomics [15], [16], [17]. Unlike the application of stable isotope as recovery standards [49], the use of 13C labeled precursor to trace metabolic pathways to their final product provides a
Concluding remarks
Metabolomics, proteomics, and transcriptomics are technology-driven profiling approaches that provide method dependent4 “quantitative” data. Metabolomics (metabolite profiling), just as other profiling -omics, is a systems biology approach, where the system is defined by the collection of elements (metabolites) sampled and
Acknowledgments
Supported by the Biomedical Mass Spectrometry Laboratory of the GCRC (PHS M01-RR00425) and the Metabolomics Core Laboratory of the UCLA Center of Excellence in Pancreatic Diseases (P01 AT003960).
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