Lactic acid-producing bacteria survive in distinct environments, but show common metabolic characteristics. Here we studied the dynamic interactions of the central metabolism in Lactococcus lactis, extensively used as a starter culture in the dairy industry, and Streptococcus pyogenes, a human pathogen. Glucose-pulse experiments and enzymatic measurements were performed to parameterize kinetic models of glycolysis. Significant improvements were made to existing kinetic models for L. lactis, which subsequently accelerated the development of the first kinetic model of S. pyogenes glycolysis. The models revealed an important role for extracellular phosphate in the regulation of central metabolism and the efficient use of glucose. Thus, phosphate, which is rarely taken into account as an independent species in models of central metabolism, should be considered more thoroughly in the analysis of metabolic systems in the future. Insufficient phosphate supply can lead to a strong inhibition of glycolysis at high glucose concentrations in both species, but this was more severe in S. pyogenes. S. pyogenes is more efficient at converting glucose to ATP, showing a higher tendency towards heterofermentative energy metabolism than L. lactis. Our comparative systems biology approach revealed that the glycolysis of L. lactis and S. pyogenes have similar characteristics, but are adapted to their individual natural habitats with respect to phosphate regulation. DatabaseThe mathematical models described here have been submitted to the Online Cellular Systems Modelling Database and can be accessed at http://jjj.biochem.sun.ac.za/database/Levering/ index.html free of charge.Abbreviations 2-PGA, 2-phosphoglycerate; 3-PGA, 3-phosphoglycerate; Fru(1,6)P 2, fructose 1,6-bisphosphate; GA3P, glyceraldehyde 3-phosphate; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; GAPN, non-phosphorylating NADP + -dependent glyceraldehyde-3-phosphate dehydrogenase;Glc6P, glucose 6-phosphate; HPr, a low-molecular-weight, heat-stable protein, part of PTS; HPr-ser-P, serine-phosphorylated HPr; LDH, L-lactate dehydrogenase; NTP, nucleoside triphosphate; PaseII, HPr(ser-P)-activated sugar-phosphate phosphatase II; P i, unbound inorganic phosphate; PTS, phosphotransferase system; triose-P, GA3P and dihydroxyacetone.

Maintenance of the endothelial cell (EC) layer of the vessel wall is essential for proper functioning of the vessel and prevention of vascular disorders. Replacement of damaged ECs could occur through division of surrounding ECs. Furthermore, EC progenitor cells (EPCs), derived from the bone marrow and circulating in the bloodstream, can differentiate into ECs. Therefore, these cells might also play a role in maintenance of the endothelial layer in the vascular system. The proliferative potential of both cell types is limited by shortening of telomeric DNA. Accelerated telomere shortening might lead to senescent vascular wall cells and eventually to the inability of the endothelium to maintain a continuous monolayer. The aim of this study was to describe the dynamics of EC damage and repair and telomere shortening by a mathematical model. In the model, ECs were integrated in a two-dimensional structure resembling the endothelium in a large artery. Telomere shortening was described as a stochastic process with oxidative damage as the main cause of attrition. Simulating the model illustrated that increased cellular turnover or elevated levels of oxidative stress could lead to critical telomere shortening and senescence at an age of 65 yr. The model predicted that under those conditions the EC layer could display defects, which could initiate severe vascular wall damage in reality. Furthermore, simulations showed that 5% progenitor cell homing/yr can significantly delay the EC layer defects. This stresses the potential importance of EPC number and function to the maintenance of vascular wall integrity during the human life span.

Long-chain fatty acids (FAs) are important substrates used by the heart to fulfil its energy requirements. Prior to mitochondrial oxidation, blood-borne FAs must pass through the cell membrane of the cardiac myocyte (sarcolemma). The mechanism underlying the sarcolemmal transport of FAs is incompletely understood. The aim of the present study was to estimate the trans-sarcolemmal FA uptake rate using a comprehensive computer model, in which the most relevant mechanisms proposed for cardiac FA uptake were incorporated. Our in silico findings show that diffusion of FA, present in its unbound form (uFA) in close proximity to the outer leaflet of the sarcolemma and serving as sole FA source, is insufficient to account for the physiological FA uptake rate. The inclusion of a hypothetical membrane-associated FA-TFPC (FA-transport-facilitating protein complex) in the model calculations substantially increased the FA uptake rate across the sarcolemma. The model requires that the biological properties of the FA-TFPC allow for increasing the rate of absorption of FA into the outer leaflet and the 'flip-flop' rate of FA from the outer to the inner leaflet of the sarcolemma. Experimental studies have identified various sarcolemma-associated proteins promoting cardiac FA uptake. It remains to be established whether these proteins possess the properties predicted by our model. Our findings also indicate that albumin receptors located on the outer leaflet of the sarcolemma facilitate the transfer of FA across the membrane to a significant extent. The outcomes of the computer simulations were verified with physiologically relevant FA uptake rates as assessed in the intact, beating heart in experimental studies.

Drugs that kill tumors through multiple mechanisms have the potential for broad clinical benefits. Here, we first developed an in silico multiomics approach (BipotentR) to find cancer cell–specific regulators that simultaneously modulate tumor immunity and another oncogenic pathway and then used it to identify 38 candidate immune–metabolic regulators. We show the tumor activities of these regulators stratify patients with melanoma by their response to anti–PD-1 using machine learning and deep neural approaches, which improve the predictive power of current biomarkers. The topmost identified regulator, ESRRA, is activated in immunotherapy-resistant tumors. Its inhibition killed tumors by suppressing energy metabolism and activating two immune mechanisms: (i) cytokine induction, causing proinflammatory macrophage polarization, and (ii) antigen-presentation stimulation, recruiting CD8+ T cells into tumors. We also demonstrate a wide utility of BipotentR by applying it to angiogenesis and growth suppressor evasion pathways. BipotentR (http://bipotentr.dfci.harvard.edu/) provides a resource for evaluating patient response and discovering drug targets that act simultaneously through multiple mechanisms. Significance: BipotentR presents resources for evaluating patient response and identifying targets for drugs that can kill tumors through multiple mechanisms concurrently. Inhibition of the topmost candidate target killed tumors by suppressing energy metabolism and effects on two immune mechanisms.