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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.

BACKGROUND: Platelet concentrates (PCs) can be prepared using three methods: platelet (PLT)-rich plasma, apheresis, and buffy coat. The aim of this study was to obtain a comprehensive data set that describes metabolism of buffy coat-derived PLTs during storage and to compare it with a previously published parallel data set obtained for apheresis-derived PLTs. STUDY DESIGN AND METHODS: During storage we measured more than 150 variables in 8 PLT units, prepared by the buffy coat method. Samples were collected at seven different time points resulting in a data set containing more than 8000 measurements. This data set was obtained by combining a series of standard quality control assays to monitor the quality of stored PLTs and a deep coverage metabolomics study using liquid chromatography coupled with mass spectrometry. RESULTS: Stored PLTs showed a distinct metabolic transition occurring 4 days after their collection. The transition was evident in PLT produced by both production methods. Apheresis-derived PLTs showed a clearer phenotype of PLT activation during early days of storage. The activated phenotype of apheresis PLTs was accompanied by a higher metabolic activity, especially related to glycolysis and the tricarboxylic acid cycle. Moreover, the extent of the activation differed between bags resulting in interbag variability in the storage lesion of apheresis-prepared PLTs. This may be related to donor-related polymorphism. CONCLUSION: This study demonstrated two discrete metabolic phenotypes in stored PLTs prepared with both apheresis and buffy coat methods. PLT activation occurs during the first metabolic phenotype and might lead to a low reproducibility of the apheresis PCs. [ABSTRACT FROM AUTHOR]

Background Platelet ( PLT) concentrates are routinely stored for 5 to 7 days. During storage they exhibit what has been termed PLT storage lesion ( PSL), which is evident by a loss of hemostatic function when transfused into patients. The overall goal of this study was to obtain a comprehensive data set describing PLT metabolism during storage. Study Design and Methods The experimental approach adopted to achieve this goal combined a series of standard assays to monitor the quality of stored PLTs and a deep-coverage metabolomics study using liquid chromatography coupled with mass spectrometry performed on both the extracellular and the intracellular environments. During storage we measured 174 different variables in 6 PLT units, collected by apheresis. Samples were collected at eight different time points resulting in a data set containing more than 8000 measurements. Results Stored PLTs did not undergo a monotonic decay, but experienced systematic changes in metabolism reflected in three discrete metabolic phenotypes: The first ( Days 0-3) was associated with active glycolysis, pentose phosphate pathway, and glutathione metabolism and down regulation of tricarboxylic acid ( TCA) cycle. The second ( Days 4-6) was associated with a more active TCA cycle as well as increased purine metabolism. A third metabolic phenotype of less clinical relevance ( Days 7-10) was associated with a faster decay of cellular metabolism. Conclusion PSL is not associated with a linear decay of metabolism, but rather with successive metabolic shifts. These findings may give new insight into the mechanisms underlying PSL and encourage the deployment of systems biology methods to PSL. [ABSTRACT FROM AUTHOR]

Motivation: A genome-scale reconstruction of human metabolism, Recon 2, is available but no interface exists to interactively visualize its content integrated with omics data and simulation results. Results: We manually drew a comprehensive map, ReconMap 2.0, that is consistent with the content of Recon 2. We present it within a web interface that allows content query, visualization of custom datasets and submission of feedback to manual curators. [ABSTRACT FROM AUTHOR]

To convert waste CO 2 from flue gases of power plants into value-added products, bio-mitigation technologies show promise. In this study, we cultivated a fast-growing species of green microalgae, Chlorella vulgaris, in different sizes of photobioreactors (PBRs) and developed a strategy using small doses of sugars for enhancing CO 2 sequestration under light-emitting diode illumination. Glucose supplementation at low levels resulted in an increase of photoautotrophic growth-driven biomass generation as well as CO 2 capture by 10% and its enhancement corresponded to an increase of supplied photon flux. The utilization of urea instead of nitrate as the sole nitrogen source increased photoautotrophic growth by 14%, but change of nitrogen source didn't compromise glucose-induced enhancement of photoautotrophic growth. The optimized biomass productivity achieved was 30.4% higher than the initial productivity of purely photoautotrophic culture. The major pigments in the obtained algal biomass were found comparable to its photoautotrophic counterpart and a high neutral lipids productivity of 516.6 mg/(L·day) was achieved after optimization. A techno-economic model was also developed, indicating that LED-based PBRs represent a feasible strategy for converting CO 2 into value-added algal biomass., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The data presented in this article are related to the research article entitled "Sugar-stimulated CO 2 sequestration by the green microalga Chlorella vulgaris " (Fu et al., 2019) [1]. The data describe a rational design and scale-up of LED-based photobioreactors for producing value-added algal biomass while removing waste CO 2 from flu gases from power plants. The dataset were created from growth rate experiments for biomass production including direct biomass productivity data, PBR size and setup parameters, medium composition as well as indirect energy cost and overhead in Iceland. A complete economic analysis is formed through a cost breakdown as well as PBR scalability predictions.