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Metabolomics--a new exciting field within the "omics" sciences.

Metabolomics--a new exciting field within the "omics" sciences. Perspectives Editorial Guest Editorial Metabolomics—A New Exciting Field within the “omics” Sciences Metabolomics is an emerging field in analytical biochemistry and can “omics” approach. be regarded as the end point of the “omics” cascade. Whereas However, the tremen- genomics deals with the analysis of the complete genome in order to dous advances in understand the function of single genes, the majority of functional technology over the genomics studies are currently based on the analysis of gene expres- past years allow the Katja Dettmer Bruce D. Hammock sion (transcriptomics) and comprehensive protein analysis (pro- constant expansion of teomics). As we are amassing knowledge of the genome, the the number of analytes quantified simultaneously. Technologically, we transcriptome, and the proteome, we have largely forgotten the are at a point where it is often as simple to measure many compounds metabolome. However, changes in the metabolome are the ultimate as to measure one. If we take one step further and assemble a suite of answer of an organism to genetic alterations, disease, or environmen- quantitative methods analyzing key metabolites from different bio- tal influences. The metabolome is therefore most predictive of chemical pathways, we can transform metabolic profiling into phenotype (Fiehn 2002; Weckwerth 2003). Consequently, the com- metabolomics. prehensive and quantitative study of metabolites, or metabolomics, is The second approach is metabolic fingerprinting. In such a desirable tool for either diagnosing disease or studying the effects of metabolomic investigations, the intention is not to identify each toxicants on phenotype. observed compound but to compare patterns or fingerprints of One of course wonders why metabolomics has lagged behind metabolites that change in response to disease or toxin exposure. other “omics” technologies. Possibly this is because the number of Comparison of fingerprints, often NMR or mass spectra or chro- metabolites varies dramatically based on how they are counted. matograms, is performed using statistical tools such as hierarchical Investigators also debate about what compounds are considered cluster analysis or principal component analysis. If these types of metabolites; for example, should vitamins or smaller peptides be analyse results in sample segregation into unique metabolic clus- included? According to a simple and widely used definition, a ters, further efforts can be made to elucidate the discriminating metabolite is any substance involved in metabolism either as a compounds and subsequently to evaluate these monocytes as product of metabolism or necessary for metabolism. In any case potential biomarkers. Being semiquantitative and simultaneously 3,000 major metabolites seem a reasonable number. If we attempt applicable to a wide range of metabolites—this is a true “omics” a global and quantitative evaluation, the technology involved is approach. Such methods are attractive, as they allow investigators daunting because the physical properties of the compounds are so to cast a wide net both generating and testing hypotheses. divergent and they vary dramatically in concentration. Moreover, However, the nature of the data makes the observations instru- the metabolome is a dynamic system subjected to significant ment/platform dependent. The implementation of NMR-based environmental influences, for example, temporal or dietary. metabolic fingerprinting has marked the beginning of a It is difficult to envision a single platform being developed in metabolomics approach as a tool in biochemistry and has proven to the near future that is able to analyze quantitatively all metabolites be a powerful technique (Nicholson et al. 2002). However, it will simultaneously. Thus with all metabolites as our goal, the techno- only detect high abundance metabolites. Complementary to NMR, logical hurdle seems to be the limiting step. At the other extreme, mass spectrometry–based tools will provide coverage for metabolic metabolomics can be seen as metabolite profiling or “just” analyti- fingerprinting in a lower concentration range, and their use is cal chemistry. So it is nothing new, simply multi-analyte chemistry increasing steadily (Plumb et al. 2003). that biochemists have been doing for decades. Of course The combination of metabolic profiling and fingerprinting will metabolomics is simultaneously both and neither of these. lead to the realization of metabolomics. In one approach, changes Although an “omics” or global view of metabolism is a goal, by no in fingerprints correlating to metabolite profiles will be linked to a means is universal coverage of all metabolites required for tremen- physiological state, without exact knowledge of fingerprint compo- dous biological insight. Also whether we work on complete cover- nents. In another approach, discriminating compounds identified age of a single metabolic pathway or on a more global approach to in fingerprints will become the focus for quantitative metabolite examine multiple metabolites, such multi-analyte analysis is by no analyses. Therefore, metabolomics will contribute to our biological means trivial. Nevertheless, successful implementation of understanding both in a mechanistic as well as a predictive metabolomics requires analytical instrumentation that offers high manner. However, it could also assist us in improving human throughput, resolution, reproducibility, and sensitivity, and only health and may be among the first of the “omics” technologies to an assembly of different analytical platforms will currently provide reach the clinic. Through multiple metabolomics projects, a pow- maximum coverage of the metabolome. To date, metabolomics- erful list of likely markers of variations in health can evolve type studies rely primarily on nuclear magnetic resonance (NMR) (Watkins and German 2002). Analyzing this set of biomarkers in a or mass spectrometry coupled to chromatography. single high throughput assay will provide the clinician with a Currently, two complementary approaches are used for powerful diagnostic tool. metabolomic investigations. In one approach—metabolic profil- In genomics and transcriptomics we saw economies of scale as ing—quantitative analytical methods are developed for metabolites institutional support developed generating infrastructure behind in a pathway or for a class of compounds. This approach produces the technologies. Similar support will be necessary to advance independent information that can be interpreted in terms of metabolomics. For example, a centralized effort to provide iso- known biochemical pathways and physiological interactions. These topic-labeled standards for a wide range of metabolites would data represent an independent legacy database since they are quan- tremendously accelerate work in metabolomics as would the devel- titative. The disadvantage is that the system is not a universal or opment of an integrated pathway map to aid in data interpretation. A 396 VOLUME 112 | NUMBER 7 | May 2004 • Environmental Health Perspectives Guest Editorial Metabolomics can be regarded as the end point of the “omics” cascade. Such a map would introduce us also to the next level of measuring Katja Dettmer is a postdoctoral researcher in professor Bruce flux through pathways. Hammock’s laboratory at the University of California, Davis. She is Although metabolomics is still in an early evolutionary stage, conducting research in the field of metabolomics, focusing on the devel- we can expect to see exciting new developments in the near future. opment of mass spectrometry–based tools for metabolic fingerprinting As more quantitative metabolomic databases evolve, we can inte- in biofluids as well as metabolic profiling methods. grate them with data sets from the other “omics” technologies to enhance the data value and provide greater biological insight than Bruce Hammock is a Distinguished Professor of Entomology and a sci- any one “omics” technique alone can offer. entist in the Cancer Research Center at the University of California, Davis. He directs an analytical–metabolomics laboratory that pio- Katja Dettmer neered the use of immunochemical diagnostics in the environmental Bruce D. Hammock field. His research interests include development of recombinant viral Cancer Research Center pesticides, mammalian xenobiotic metabolism, environmental chem- University of California, Davis istry, and biosensor development. Davis, California EFERENCES E-mail: [email protected] Fiehn O. 2002. Metabolomics—the link between genotypes and phenotypes. Plant Mol Biol 48:155–171. Plumb RS, Stumpf CL, Granger JH, Castro-Perez J, Haselden JN, Dear GJ. 2003. Use of liquid chromatography/time-of-flight mass spectrometry and multivariate statistical analysis shows promise for the detection of drug metabolites in biological fluids. Rapid Commun Mass Spectrom 17:2632–2638. Nicholson JK, Connelly J, Lindon JC, Holmes E. 2002. Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov 1:153–161. Watkins SM, German J B. 2002. Toward the implementation of metabolomic assess- ments of human health and nutrition. Curr Opin Biotechnol 13:512–516. Weckwerth W. 2003. Metabolomics in systems biology. Annu Rev Plant Biol 54:669–689. Environmental Health Perspectives • VOLUME 112 | NUMBER 7 | May 2004 A 397 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental Health Perspectives Unpaywall

Metabolomics--a new exciting field within the "omics" sciences.

Dettmer, Katja; Hammock, Bruce D
Environmental Health Perspectives – May 1, 2004
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Abstract

Perspectives Editorial Guest Editorial Metabolomics—A New Exciting Field within the “omics” Sciences Metabolomics is an emerging field in analytical biochemistry and can “omics” approach. be regarded as the end point of the “omics” cascade. Whereas However, the tremen- genomics deals with the analysis of the complete genome in order to dous advances in understand the function of single genes, the majority of functional technology over the genomics studies are currently based on the analysis of gene expres- past years allow the Katja Dettmer Bruce D. Hammock sion (transcriptomics) and comprehensive protein analysis (pro- constant expansion of teomics). As we are amassing knowledge of the genome, the the number of analytes quantified simultaneously. Technologically, we transcriptome, and the proteome, we have largely forgotten the are at a point where it is often as simple to measure many compounds metabolome. However, changes in the metabolome are the ultimate as to measure one. If we take one step further and assemble a suite of answer of an organism to genetic alterations, disease, or environmen- quantitative methods analyzing key metabolites from different bio- tal influences. The metabolome is therefore most predictive of chemical pathways, we can transform metabolic profiling into phenotype (Fiehn 2002; Weckwerth 2003). Consequently, the com- metabolomics. prehensive and quantitative study of metabolites, or metabolomics, is The second approach is metabolic fingerprinting. In such a desirable tool for either diagnosing disease or studying the effects of metabolomic investigations, the intention is not to identify each toxicants on phenotype. observed compound but to compare patterns or fingerprints of One of course wonders why metabolomics has lagged behind metabolites that change in response to disease or toxin exposure. other “omics” technologies. Possibly this is because the number of Comparison of fingerprints, often NMR or mass spectra or chro- metabolites varies dramatically based on how they are counted. matograms, is performed using statistical tools such as hierarchical Investigators also debate about what compounds are considered cluster analysis or principal component analysis. If these types of metabolites; for example, should vitamins or smaller peptides be analyse results in sample segregation into unique metabolic clus- included? According to a simple and widely used definition, a ters, further efforts can be made to elucidate the discriminating metabolite is any substance involved in metabolism either as a compounds and subsequently to evaluate these monocytes as product of metabolism or necessary for metabolism. In any case potential biomarkers. Being semiquantitative and simultaneously 3,000 major metabolites seem a reasonable number. If we attempt applicable to a wide range of metabolites—this is a true “omics” a global and quantitative evaluation, the technology involved is approach. Such methods are attractive, as they allow investigators daunting because the physical properties of the compounds are so to cast a wide net both generating and testing hypotheses. divergent and they vary dramatically in concentration. Moreover, However, the nature of the data makes the observations instru- the metabolome is a dynamic system subjected to significant ment/platform dependent. The implementation of NMR-based environmental influences, for example, temporal or dietary. metabolic fingerprinting has marked the beginning of a It is difficult to envision a single platform being developed in metabolomics approach as a tool in biochemistry and has proven to the near future that is able to analyze quantitatively all metabolites be a powerful technique (Nicholson et al. 2002). However, it will simultaneously. Thus with all metabolites as our goal, the techno- only detect high abundance metabolites. Complementary to NMR, logical hurdle seems to be the limiting step. At the other extreme, mass spectrometry–based tools will provide coverage for metabolic metabolomics can be seen as metabolite profiling or “just” analyti- fingerprinting in a lower concentration range, and their use is cal chemistry. So it is nothing new, simply multi-analyte chemistry increasing steadily (Plumb et al. 2003). that biochemists have been doing for decades. Of course The combination of metabolic profiling and fingerprinting will metabolomics is simultaneously both and neither of these. lead to the realization of metabolomics. In one approach, changes Although an “omics” or global view of metabolism is a goal, by no in fingerprints correlating to metabolite profiles will be linked to a means is universal coverage of all metabolites required for tremen- physiological state, without exact knowledge of fingerprint compo- dous biological insight. Also whether we work on complete cover- nents. In another approach, discriminating compounds identified age of a single metabolic pathway or on a more global approach to in fingerprints will become the focus for quantitative metabolite examine multiple metabolites, such multi-analyte analysis is by no analyses. Therefore, metabolomics will contribute to our biological means trivial. Nevertheless, successful implementation of understanding both in a mechanistic as well as a predictive metabolomics requires analytical instrumentation that offers high manner. However, it could also assist us in improving human throughput, resolution, reproducibility, and sensitivity, and only health and may be among the first of the “omics” technologies to an assembly of different analytical platforms will currently provide reach the clinic. Through multiple metabolomics projects, a pow- maximum coverage of the metabolome. To date, metabolomics- erful list of likely markers of variations in health can evolve type studies rely primarily on nuclear magnetic resonance (NMR) (Watkins and German 2002). Analyzing this set of biomarkers in a or mass spectrometry coupled to chromatography. single high throughput assay will provide the clinician with a Currently, two complementary approaches are used for powerful diagnostic tool. metabolomic investigations. In one approach—metabolic profil- In genomics and transcriptomics we saw economies of scale as ing—quantitative analytical methods are developed for metabolites institutional support developed generating infrastructure behind in a pathway or for a class of compounds. This approach produces the technologies. Similar support will be necessary to advance independent information that can be interpreted in terms of metabolomics. For example, a centralized effort to provide iso- known biochemical pathways and physiological interactions. These topic-labeled standards for a wide range of metabolites would data represent an independent legacy database since they are quan- tremendously accelerate work in metabolomics as would the devel- titative. The disadvantage is that the system is not a universal or opment of an integrated pathway map to aid in data interpretation. A 396 VOLUME 112 | NUMBER 7 | May 2004 • Environmental Health Perspectives Guest Editorial Metabolomics can be regarded as the end point of the “omics” cascade. Such a map would introduce us also to the next level of measuring Katja Dettmer is a postdoctoral researcher in professor Bruce flux through pathways. Hammock’s laboratory at the University of California, Davis. She is Although metabolomics is still in an early evolutionary stage, conducting research in the field of metabolomics, focusing on the devel- we can expect to see exciting new developments in the near future. opment of mass spectrometry–based tools for metabolic fingerprinting As more quantitative metabolomic databases evolve, we can inte- in biofluids as well as metabolic profiling methods. grate them with data sets from the other “omics” technologies to enhance the data value and provide greater biological insight than Bruce Hammock is a Distinguished Professor of Entomology and a sci- any one “omics” technique alone can offer. entist in the Cancer Research Center at the University of California, Davis. He directs an analytical–metabolomics laboratory that pio- Katja Dettmer neered the use of immunochemical diagnostics in the environmental Bruce D. Hammock field. His research interests include development of recombinant viral Cancer Research Center pesticides, mammalian xenobiotic metabolism, environmental chem- University of California, Davis istry, and biosensor development. Davis, California EFERENCES E-mail: [email protected] Fiehn O. 2002. Metabolomics—the link between genotypes and phenotypes. Plant Mol Biol 48:155–171. Plumb RS, Stumpf CL, Granger JH, Castro-Perez J, Haselden JN, Dear GJ. 2003. Use of liquid chromatography/time-of-flight mass spectrometry and multivariate statistical analysis shows promise for the detection of drug metabolites in biological fluids. Rapid Commun Mass Spectrom 17:2632–2638. Nicholson JK, Connelly J, Lindon JC, Holmes E. 2002. Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov 1:153–161. Watkins SM, German J B. 2002. Toward the implementation of metabolomic assess- ments of human health and nutrition. Curr Opin Biotechnol 13:512–516. Weckwerth W. 2003. Metabolomics in systems biology. Annu Rev Plant Biol 54:669–689. Environmental Health Perspectives • VOLUME 112 | NUMBER 7 | May 2004 A 397

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Published: May 1, 2004

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