Biology subjects

Law, R. C.

Publications and source records attributed to Law, R. C..

4 recordsLinked to original sources

bioRxiv2024

Robustness of mitochondrial biogenesis and respiration explain aerobic glycolysis

A long-standing observation is that in fast-growing cells, respiration rate declines with increasing growth rate and is compensated by an increase in fermentation, despite respiration being more efficient than fermentation. This apparent preference for fermentation even in the presence of oxygen is known as aerobic glycolysis, and occurs in bacteria, yeast, and cancer cells. Considerable work has focused on understanding the potential benefits that might justify this seemingly wasteful metabolic strategy, but its mechanistic basis remains unclear. Here we show that aerobic glycolysis results from the saturation of mitochondrial respiration and the decoupling of mitochondrial biogenesis from the production of other cellular components. Respiration rate is insensitive to acute perturbations of cellular energetic demands or nutrient supplies, and is explained simply by the amount of mitochondria per cell. Mitochondria accumulate at a nearly constant rate across different growth conditions, resulting in mitochondrial amount being largely determined by cell division time. In contrast, glucose uptake rate is not saturated, and is accurately predicted by the abundances and affinities of glucose transporters. Combining these models of glucose uptake and respiration provides a quantitative, mechanistic explanation for aerobic glycolysis. The robustness of specific respiration rate and mitochondrial biogenesis, paired with the flexibility of other bioenergetic and biosynthetic fluxes, may play a broad role in shaping eukaryotic cell metabolism.

systems biology↗

bioRxiv2023

Determination of Metabolic Fluxes by Deep Learning of Isotope Labeling Patterns

All life forms operate metabolism in constant flux. Metabolic fluxes offer a direct readout of cellular state, detailing the rates and driving forces of metabolic pathways. However, indirect, iterative solvers for mapping isotope patterns from tracing experiments onto metabolic fluxes leave much of cellular state uncharted. Here, we streamline metabolic flux quantitation by innovating a machine learning framework, ML-Flux, that deciphers complex isotope labeling patterns. We train neural networks using isotope pattern-flux pairs across central carbon metabolism from 26 key 13C-glucose, 2H-glucose, and 13C-glutamine tracers. ML-Flux takes variable-size isotope labeling patterns as input, imputes missing isotope patterns, and outputs mass-balanced metabolic fluxes. Computation of fluxes using ML-Flux is more accurate and faster than that of leading metabolic flux analysis software employing a least-squares method. Our biochemical networks and machine learning models constitute a curated and growing online knowledgebase of metabolic flux and free energy to democratize quantitative metabolic profiling.

systems biology↗

bioRxiv2023

Atlas of fetal metabolism during mid-to-late gestation and diabetic pregnancy

Mounting evidence supports an instructive role for metabolism in stem cell fate decisions. However, much is yet unknown about how fetal metabolism changes during mammalian development and how altered maternal metabolism shapes fetal metabolism. Here, we present a descriptive atlas of in vivo fetal murine metabolism during mid-to-late gestation in normal and diabetic pregnancy. Using 13C-glucose and LC-MS, we profiled the metabolism of fetal brains, hearts, livers, and placentas harvested from pregnant dams between embryonic days (E)10.5 and 18.5. Comparative analysis of our large metabolomics dataset revealed metabolic features specific to fetal tissues developed under a hyperglycemic environment as well as metabolic signatures that may denote developmental transitions during euglycemic development. We observed sorbitol accumulation in fetal tissues and altered neurotransmitter levels in fetal brains isolated from dams with maternal hyperglycemia. Tracing 13C-glucose revealed disparate nutrient sourcing in fetuses depending on maternal glycemic states. Regardless of glycemic state, histidine-derived metabolites accumulated during late development in fetal tissues and maternal plasma. Our rich dataset presents a comprehensive overview of in vivo fetal tissue metabolism and alterations occurring as a result of maternal hyperglycemia.

cell biology↗

bioRxiv2022

A parallel glycolysis supports rapid adaptation in dynamic environments

Glycolysis is a universal metabolic process that breaks down glucose to produce cellular energy currency ATP and biomass precursors1. The Entner-Doudoroff pathway is a glycolytic pathway that parallels the textbook glycolysis but yields half as many ATP2. In organisms that possess both glycolytic pathways, such as Escherichia coli, inactivating the less energy-efficient Entner-Doudoroff pathway does not alter growth rates3. The benefit of the Entner-Doudoroff pathway has instead been hypothesized to be metabolic flexibility as an auxiliary enzyme-efficient catabolic route4. However, its raison detre remains incompletely understood. Here we identify the advantage of employing parallel glycolytic pathways under dynamic nutrient environments. Upon carbon and nitrogen upshifts, wild-type cells accelerate growth faster than those with the Entner-Doudoroff pathway knocked out. Using stable isotope tracers and mass spectrometry, we find that the Entner-Doudoroff pathway flux increases disproportionately faster than that of the textbook glycolysis during nutrient upshifts. We attribute the fast response time of the Entner-Doudoroff pathway to its strong thermodynamic driving force and concerted regulation facilitating glucose uptake. Intermittent supply of nutrients manifests this evolutionary advantage of the parallel glycolysis. Thus, the dynamic nature of an ostensibly redundant pathways role in promoting rapid adaptation constitutes a metabolic design principle.

systems biology↗