A combined metabonomic and transcriptomic approach to investigate metabolism during development in the chick chorioallantoic membrane.
The chick chorioallantoic membrane (CAM) is a powerful alternative to rodent models for the study of physiological or pathological angiogenesis. We investigated metabolic changes during the maturation of the CAM by (1)H NMR-based metabolic profiling (metabonomics/metabolomics), allowing simultaneous measurements of many metabolites in an untargeted fashion. Specifically, we examined the time course of the measured metabolites to elucidate common patterns of regulation. Three clusters of metabolites were observed that correspond to essential biological processes active in the CAM with similar dynamics. The time courses common to the metabolite clusters distinguished specific stages of vessel growth, identifying waste product metabolites being stored in the CAM and energy-related substrates decreasing during embryonic growth. Using this top-down approach, combined with existing microarray data, we could link gene expression to metabolic consequences during the growth of a vascularized organ. For example, transcriptomic analysis demonstrated that many transcripts involved in the TCA cycle were down-regulated during CAM development, which correlated with the decrease in levels of TCA precursors and intermediates seen in the metabolite data. Taken together, this paper provides the first metabonomic study in an embryonic tissue where vessel development is the most active morphogenic process.
Cavill
Rachel
R
Biomolecular Medicine, Department of Surgery and Cancer, Faculty of Medicine, Sir Alexander Fleming Building, Imperial College London, London.
Sidhu
Jasmin K
JK
Kilarski
Witold
W
Javerzat
Sophie
S
Hagedorn
Martin
M
Ebbels
Timothy M D
TM
Bikfalvi
Andreas
A
Keun
Hector C
HC
D000818:Animals; D002642:Chick Embryo; D002645:Chickens; D049033:Chorioallantoic Membrane / Q000737:chemistry* / Q000254:growth & development / Q000378:metabolism*; D016000:Cluster Analysis; D020869:Gene Expression Profiling / Q000379:methods*; D055432:Metabolomics / Q000379:methods*; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods