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J Biol Chem. 2017 Dec 1;292(48):19556-19564. doi: 10.1074/jbc.M117.804914. Epub 2017 Oct 13.

Quantitative time-course metabolomics in human red blood cells reveal the temperature dependence of human metabolic networks.

Author information

1
From the Departments of Bioengineering and.
2
Bioinformatics and Systems Biology Program, and.
3
Institute for Biomedicine, EURAC Research, Viale Druso Drususallee 1, 39100 Bolzano, Bozen, Italy.
4
Center for Systems Biology, University of Iceland, Sturlugata 8, IS-101 Reykjavík, Iceland.
5
The Blood Bank, Landspítali-University Hospital, Snorrabraut 60, 105 Reykjavík, Iceland.
6
School of Science and Engineering, Reykjavík University, Menntavegur 1, IS-101 Reykjavík, Iceland, and.
7
Division of Biological Sciences, University of California, San Diego, La Jolla, California 92093.
8
Sinopia Biosciences, San Diego, California 92101.
9
From the Departments of Bioengineering and palsson@ucsd.edu.
10
Pediatrics.

Abstract

The temperature dependence of biological processes has been studied at the levels of individual biochemical reactions and organism physiology (e.g. basal metabolic rates) but has not been examined at the metabolic network level. Here, we used a systems biology approach to characterize the temperature dependence of the human red blood cell (RBC) metabolic network between 4 and 37 °C through absolutely quantified exo- and endometabolomics data. We used an Arrhenius-type model (Q10) to describe how the rate of a biochemical process changes with every 10 °C change in temperature. Multivariate statistical analysis of the metabolomics data revealed that the same metabolic network-level trends previously reported for RBCs at 4 °C were conserved but accelerated with increasing temperature. We calculated a median Q10 coefficient of 2.89 ± 1.03, within the expected range of 2-3 for biological processes, for 48 individual metabolite concentrations. We then integrated these metabolomics measurements into a cell-scale metabolic model to study pathway usage, calculating a median Q10 coefficient of 2.73 ± 0.75 for 35 reaction fluxes. The relative fluxes through glycolysis and nucleotide metabolism pathways were consistent across the studied temperature range despite the non-uniform distributions of Q10 coefficients of individual metabolites and reaction fluxes. Together, these results indicate that the rate of change of network-level responses to temperature differences in RBC metabolism is consistent between 4 and 37 °C. More broadly, we provide a baseline characterization of a biochemical network given no transcriptional or translational regulation that can be used to explore the temperature dependence of metabolism.

KEYWORDS:

computational biology; erythrocyte; metabolism; metabolomics; systems biology

PMID:
29030425
PMCID:
PMC5712598
[Available on 2018-12-01]
DOI:
10.1074/jbc.M117.804914
[Indexed for MEDLINE]

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