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Lactate Metabolic Flux Analysis and Metabolic Control Analysis: Quantitative Evaluation Method of Functional Foods

LI Yang, WANG Xingya, WANG Xixi, PANG Guangchang*   

  1. Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce,Tianjin 300134, China
  • Online:2015-01-15 Published:2015-01-16


The effects of food on the body are mediated mainly through its influence on the metabolic and metabolic
networks after being ingested and absorbed. This study aimed to develop a new experimental method to quantitatively
evaluate the effects of food on metabolic and metabolic networks. Peripheral blood samples were collected from volunteers
with four kinds of physiological states including basic state (or sleeping state), learning state, motion state and fever state,
and their changes in lactate metabolic flux were studied as well as the role of 15 enzymes involved in the central metabolic
pathways in controlling lactate metabolic flux. The results indicated that lactate metabolic flux in the four states were quite
different, following the increasing order: basic, learning, motion and fever, which was consistent with that observed for
the catabolism. A combination of correlation analysis and principal component analysis was used to determine the control
coefficient of lactate metabolic flux. The results showed that pyruvate kinase (PK, CpPK = 0.221 6), pyruvate dehydrogenase
complex (PDHC, CpPDHC = 0.206 4), lactate dehydrogenase (LDH, CpLDH = 0.162 6), transketolase (TKL, CpTKL = 0.206 0)
played major roles in controlling lactate metabolic flux, among which, PK played the most important role. Peripheral
blood samples collected from healthy volunteers before and after eating modified rice starch were then analyzed by
applying the experimental methods mentioned above and the results indicated that lactate flux was obviously enhanced
after eating modified starch as compared with that before eating and as the same effect was observed on the catabolism.
On the contrary, the anabolism decreased. PK gene expression was significantly increased (P = 0.01) whereas PDHC gene
expression (synthetic) was significantly reduced (P = 0.003). The present study showed that the gene expression profiles of
enzymes were fitted with the predicted lactate flux well. These results have demonstrated that this method could be used to
quantitatively evaluate the effects of food on metabolism by collecting appropriate peripheral blood samples after eating it.

Key words: functional foods, evaluation methodology, physiological states, lactate metabolic flux, metabolic control analysis

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