Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics [electronic resource]

 0 Người đánh giá. Xếp hạng trung bình 0

Tác giả:

Ngôn ngữ: eng

Ký hiệu phân loại: 615.8 Specific therapies and kinds of therapies

Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. Dept. of Energy. Office of Science ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2017

Mô tả vật lý: Size: Article No. 46249 : , digital, PDF file.

Bộ sưu tập: Metadata

ID: 260543

 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 <
 i>
 Saccharomyces cerevisiae<
 /i>
 . 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 <
 sup>
 13<
 /sup>
 C 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.
Tạo bộ sưu tập với mã QR

THƯ VIỆN - TRƯỜNG ĐẠI HỌC CÔNG NGHỆ TP.HCM

ĐT: (028) 71010608 | Email: tt.thuvien@hutech.edu.vn

Copyright @2024 THƯ VIỆN HUTECH