Metabolism 2000: the emperor needs new clothes.
Metabolism is one of the corner stones of nutritional science. As biology enters the post-genomic era and with functional genomics beginning to takeoff, we anticipate that the study of metabolism will play an increasingly important role in helping to link advances made via the reductionist paradigm, that has been so successful in molecular and cellular biology, with those emerging from observational studies in animals and human subjects. A reconstructive metabolically-focused approach offers a timely paradigm for enhancing the elegance of nutritional science. Here we give particular attention to the use of tracers as phenotyping tools and discuss the application of our metaprobe concepts with respect to some novel features of metabolism, including 'underground metabolism', 'metabolic hijacking', 'catalytic promiscuity' and 'moonlighting proteins'. The opportunities for enhancing the study of metabolism by new and emerging technologies, and the importance of the interdisciplinary research enterprise are also touched upon. We conclude that: (1) the metaprobe concepts and approach, discussed herein, potentially yield a quantitative physiological (metabolic) phenotype against which to elaborate partial or focused genotypes; (2) physiological (metabolic) phenotypes which have a whole-body or kinetically-discernible inter-organ tissue-directed metabolic signature are an ideal target for this directed tracer-based definition of the 'functional' genotype; (3) metabolism, probed with tracer tool kits suitable for measuring rates of turnover, change and conversion, becomes in the current sociology of the 'Net', like AOL, Yahoo. Alta Vista, Lycos or Ask Jeeves, the portal for an exploration of the metabolic characteristics of the 'Genomics Internet'.
Young
V R
VR
Laboratory of Human Nutrition, School of Science and Clinical Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. vryoung@mit.edu
Ajami
A M
AM
D000375:Aging / Q000378:metabolism*; D015415:Biomarkers; D004734:Energy Metabolism / Q000235:genetics; D005838:Genotype; D006801:Humans; D020407:Internet; D010641:Phenotype
D015415:Biomarkers