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Title: Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBA predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.
Authors:
 [1] ;  [2] ;  [3] ;  [3] ;  [4] ;  [5]
  1. Sinopia Biosciences, San Diego, CA (United States)
  2. Univ. of California at San Diego, La Jolla, CA (United States)
  3. Univ. of Iceland, Reykjavik (Iceland)
  4. Landspitali-Univ. Hospital, Reykjavik (Iceland); Reykjavik Univ., Reykjavik (Iceland)
  5. Univ. of California, San Diego, La Jolla, CA (United States); The Technical Univ. of Denmark, Horsholm (Denmark)
Publication Date:
Grant/Contract Number:
SC0008701
Type:
Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 7; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Research Org:
Univ. of California at San Diego, La Jolla, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES
OSTI Identifier:
1366705