Cycle Flux Research Articles

Role of Exogenous Pyruvate in Maintaining Adenosine Triphosphate Production under High-Glucose Conditions through PARP-Dependent Glycolysis and PARP-Independent Tricarboxylic Acid Cycle.

Pyruvate serves as a key metabolite in energy production and as an anti-oxidant. In our previous study, exogenous pyruvate starvation under high-glucose conditions induced IMS32 Schwann cell death because of the reduced glycolysis-tricarboxylic acid (TCA) cycle flux and adenosine triphosphate (ATP) production. Thus, this study focused on poly-(ADP-ribose) polymerase (PARP) to investigate the detailed molecular mechanism of cell death. Rucaparib, a PARP inhibitor, protected Schwann cells against cell death and decreased glycolysis but not against an impaired TCA cycle under high-glucose conditions in the absence of pyruvate. Under such conditions, reduced pyruvate dehydrogenase (PDH) activity and glycolytic and mitochondrial ATP production were observed but not oxidative phosphorylation or the electric transfer chain. In addition, rucaparib supplementation restored glycolytic ATP production but not PDH activity and mitochondrial ATP production. No differences in the increased activity of caspase 3/7 and the localization of apoptosis-inducing factor were found among the experimental conditions. These results indicate that Schwann cells undergo necrosis rather than apoptosis or parthanatos under the aforementioned conditions. Exogenous pyruvate plays a pivotal role in maintaining the flux in PARP-dependent glycolysis and the PARP-independent TCA cycle in Schwann cells under high-glucose conditions.

Ecological adaptations of amphibians to environmental changes along an altitudinal gradient (Case Study: Bufo gargarizans) from phenotypic and genetic perspectives

BackgroundOrganisms have evolved a range of phenotypic and genetic adaptations to live in different environments along an altitudinal gradient. Herein, we studied the widely distributed Chinese toad, Bufo gargarizans, as a model and used an integrated phenotype-genotype approach to assess adaptations to different altitudinal environments.ResultsComparison of populations from four altitudes (50 m, 1200 m, 2300 m, and 3400 m) showed more effective defenses among high-altitude toads. These included thickened epidermis, more epidermal capillaries and granular glands, greater gland size in skin, and higher antioxidant enzyme activities in plasma. High-altitude toads also showed increased erythrocytes and hematocrit and elevated hemoglobin concentration, potentially improving oxygen delivery. Elevated altitude led to a metabolic shift from aerobic to anaerobic metabolism, and high-altitude populations favored carbohydrates over fatty acids to fuel for energy metabolism. Differentially expressed genes were associated with adaptive phenotypic changes. For instance, expression of genes associated with fatty acid metabolism showed greater suppression at high altitude (3400 m), consistent with decreased flux of β-hydroxybutyric acid and lower free fatty acids levels. Moreover, down-regulation of genes involved in carbon metabolism processes at high altitude (3400 m) were coincident with reduced TCA cycle flux. These results suggest that high-altitude toads adopt a metabolic suppression strategy for survival under harsh environmental conditions. Moreover, the hypoxia-inducible factor signaling cascade was activated at high altitude.ConclusionsCollectively, these results advance our comprehension of adaptation to high-altitude environments by revealing physiological and genetic mechanisms at work in Chinese toads living along altitudinal gradients.

12614 Induction Of Gpt2 During Metabolic Stress Is Associated With Reduced Incretin Responsiveness And Decreased β-cell Resilience To Metabolic Stress

Abstract Disclosure: S. Sen: None. A.V. Rozo: None. M. Haemmerle: None. J. Roman: None. A.V. Scota: None. J.A. Christine: None. E.M. Morrow: None. S.A. Tersey: None. C.B. Newgard: None. N.M. Doliba: None. D.A. Stoffers: None. Elevated blood glucose and lipids compromise pancreatic β-cell survival and function, but the underlying molecular mechanisms are ill-understood. We previously found that mitochondrial glutamate-pyruvate transaminase 2 (GPT2) is induced by ER and glucolipotoxic (GLT) stress. Here, we find that islets from type 2 diabetic donors exhibited markedly elevated levels of GPT2 compared to those of non-diabetic donors. GLT stress induced GPT2 in MIN6 cells, primary murine, and human non-diabetic islets. We generated β-cell specific Gpt2-deficient (Gpt2βKO) and Gpt2 floxed control (Gpt2f/f) mice to study the in vivo role of Gpt2 in β-cells. Intraperitoneal (IP) glucose tolerance (GTT) of Gpt2βKO mice was minimally affected on chow diet; therefore, we placed Gpt2f/f and Gpt2βKO mice on 45 kcal% high-fat and matched control diets. At 1 week, HFD-fed Gpt2βKO mice exhibited reduced β-cell death, measured by droplet digital PCR of circulating unmethylated preproinsulin DNA and by TUNEL analysis. Over 37 weeks, HFD-fed Gpt2βKO mice showed lower random blood glucose similar to Gpt2f/f mice under a control diet. While IPGTT was modestly improved in HFD-fed Gpt2βKO compared to HFD-fed Gpt2f/f mice, insulin secretion was not enhanced. Remarkably, oral glucose administration markedly improved glucose tolerance and enhanced insulin secretion of control- and HFD-fed Gpt2βKO mice compared to Gpt2f/f mice, while GLP-1 and GIP levels were unaltered, suggesting enhanced incretin action on the β-cell. Indeed, Gpt2βKO mice (under both control and high-fat diets) were more responsive to administration of GLP1R agonist Exendin-4 (Ex4) than Gpt2f/f mice. Isolated Gpt2βKO islets secreted more insulin when stimulated by Ex4 and GIP but not acetylcholine. Perifusion assay revealed markedly enhanced insulin secretion of Gpt2βKO islets in response to a stepwise exposure to increasing Ex4 doses, indicating enhanced incretin sensitivity. Metabolic flux analysis of Gpt2βKO and Gpt2f/f islets exposed to uniformly labeled glucose (U-13C glucose) under low (2.8mM), high (12mM) glucose, and high glucose with Ex4 conditions revealed elevated levels of key TCA cycle intermediates in Gpt2βKO islets under high glucose and high glucose+Ex4 conditions, indicating increased TCA cycle flux that likely enhances insulin secretion. Gpt2βKO mice had higher β cell mass than Gpt2f/f littermates under control diet and HFD feeding. Bulk islet RNA-seq from Gpt2f/f and Gpt2βKO mice exposed to GLT revealed upregulation of genes responsible for cell cycle and division pathways and downregulation of apoptosis and ER stress genes, consistent with enhanced survival of Gpt2βKO islets under stress conditions. In summary, β-cell GPT2 is increased during metabolic stress and T2D. Its deficiency induces a metabolic reprogramming that improves incretin sensitivity and protects pancreatic β-cells from metabolic stress. Presentation: 6/2/2024

Exponential or Unimodal Relationships Between Nighttime Ecosystem Respiration and Temperature at the Eddy Covariance Flux Tower Sites.

Ecosystem respiration is a key flux in the terrestrial carbon cycle and is affected substantially by temperature. This work analysed the time series data of nighttime net ecosystem exchange of carbon dioxide (NEEnight) from 196 FLUXNET2015 sites to re-evaluate the relationships between NEEnight and temperature. A total of 93 sites (48%) were identified to have a unimodal relationship between NEEnight and temperature. Site-specific apparent optimum temperature parameters were then estimated at these sites. We further assessed the impacts of using exponential or unimodal equations on NEEnight predictions. The predicted NEEnight values at high temperatures were substantially higher from the exponential-type equations (mean: ~200%) than from the unimodal equation (mean: ~30%), compared to the observed NEEnight. This study calls for using a unimodal equation to predict NEEnight (often considered as nighttime ecosystem respiration, ERnight), which could substantially improve the accuracy and reduce uncertainty in ER estimates, in particular under the scenario of global warming.

Global soil respiration predictions with associated uncertainties from different spatio-temporal data subsets

Soil respiration (Rs), the second-largest flux in the global carbon cycle, is a crucial but uncertain component. To improve the understanding of global Rs, we constructed single global models, and specific models classified by climate type, land cover type, year of the data record, and elevation range using the random forest algorithm to predict global Rs values and explore the associated uncertainty in the models. The results showed a similar overall predictive performance for the models, with an R-squared value greater than 0.63; however, significant differences were observed compared to the global Rs estimate (23 Pg C). All the models estimated larger values of Rs than the single global model, mainly owing to imbalances in the sample data on which the prediction models were based. One exception to this result is the land cover model, which estimates a smaller global Rs for 2020 (95.1 Pg C). Overall, the single global model estimates were closer to those obtained for temperate zones owing to differences in the training data distribution, which resulted in smaller global estimates than those of other classification-specific models. Prediction models using observations before 2000 tend to underestimate the global Rs. However, the use of classification-specific Rs models proved helpful in addressing the persistent temporal and spatial imbalances in Rs sampling. Expanding the coverage of Rs records both temporally and spatially and updating the global Rs database promptly would improve the estimation accuracy of global Rs prediction models while enhancing the understanding of the overall global carbon budget and the feedback of soil carbon with regard to climate warming.

Kinetic Diagram Analysis: A Python Library for Calculating Steady-State Observables of Biochemical Systems Analytically.

Kinetic diagrams are commonly used to represent biochemical systems in order to study phenomena such as free energy transduction and ion selectivity. While numerical methods are commonly used to analyze such kinetic networks, the diagram method by King, Altman and Hill makes it possible to construct exact algebraic expressions for steady-state observables in terms of the rate constants of the kinetic diagram. However, manually obtaining these expressions becomes infeasible for models of even modest complexity as the number of the required intermediate diagrams grows with the factorial of the number of states in the diagram. We developed Kinetic Diagram Analysis (KDA), a Python library that programmatically generates the relevant diagrams and expressions from a user-defined kinetic diagram. KDA outputs symbolic expressions for state probabilities and cycle fluxes at steady-state that can be symbolically manipulated and evaluated to quantify macroscopic system observables. We demonstrate the KDA approach for examples drawn from the biophysics of active secondary transmembrane transporters. For a generic 6-state antiporter model, we show how the introduction of a single leakage transition reduces transport efficiency by quantifying substrate turnover. We apply KDA to a real-world example, the 8-state free exchange model of the small multidrug resistance transporter EmrE of Hussey et al. (J. Gen. Physiol., 2020, 152, e201912437), where a change in transporter phenotype is achieved by biasing two different subsets of kinetic rates: alternating access and substrate unbinding rates. KDA is made available as open source software under the GNU General Public License version 3.

Uncovering underlying physical principles and driving forces of cell differentiation and reprogramming from single-cell transcriptomics

Recent advances in single-cell sequencing technology have revolutionized our ability to acquire whole transcriptome data. However, uncovering the underlying transcriptional drivers and nonequilibrium driving forces of cell function directly from these data remains challenging. We address this by learning cell state vector fields from discrete single-cell RNA velocity to quantify the single-cell global nonequilibrium driving forces as landscape and flux. From single-cell data, we quantified the Waddington landscape, showing that optimal paths for differentiation and reprogramming deviate from the naively expected landscape gradient paths and may not pass through landscape saddles at finite fluctuations, challenging conventional transition state estimation of kinetic rate for cell fate decisions due to the presence of the flux. A key insight from our study is that stem/progenitor cells necessitate greater energy dissipation for rapid cell cycles and self-renewal, maintaining pluripotency. We predict optimal developmental pathways and elucidate the nucleation mechanism of cell fate decisions, with transition states as nucleation sites and pioneer genes as nucleation seeds. The concept of loop flux quantifies the contributions of each cycle flux to cell state transitions, facilitating the understanding of cell dynamics and thermodynamic cost, and providing insights into optimizing biological functions. We also infer cell-cell interactions and cell-type-specific gene regulatory networks, encompassing feedback mechanisms and interaction intensities, predicting genetic perturbation effects on cell fate decisions from single-cell omics data. Essentially, our methodology validates the landscape and flux theory, along with its associated quantifications, offering a framework for exploring the physical principles underlying cellular differentiation and reprogramming and broader biological processes through high-throughput single-cell sequencing experiments.

Malic enzyme 2 maintains metabolic state and anti-tumor immunity of CD8+ T cells

The functional integrity of CD8+ Tcells is closely linked to metabolic reprogramming; therefore, understanding the metabolic basis of CD8+ Tcell activation and antitumor immunity could provide insights into tumor immunotherapy. Here, we report that ME2 is critical for mouse CD8+ Tcell activation and immune response against malignancy. ME2 deficiency suppresses CD8+ Tcell activation and anti-tumor immune response invitro and invivo. Mechanistically, ME2 depletion blocks the TCA cycle flux, leading to the accumulation of fumarate. Fumarate directly binds to DAPK1 and inhibits its activity by competing with ATP for binding. Notably, pharmacological inhibition of DAPK1 abolishes the anti-tumor function conferred by ME2 to CD8+ Tcells. Collectively, these findings demonstrate a role for ME2 in the regulation of CD8+ Tcell metabolism and effector functions as well as an unexpected function for fumarate as a metabolic signal in the inhibition of DAPK1.

Metabolic and transcriptomic reprogramming during contact inhibition-induced quiescence is mediated by YAP-dependent and YAP-independent mechanisms.

Metabolic rewiring during the proliferation-to-quiescence transition is poorly understood. Here, using a model of contact inhibition-induced quiescence, we conducted 13C-metabolic flux analysis in proliferating (P) and quiescent (Q) mouse embryonic fibroblasts (MEFs) to investigate this process. Q cells exhibit reduced glycolysis but increased TCA cycle flux and mitochondrial respiration. Reduced glycolytic flux in Q cells correlates with reduced glycolytic enzyme expression mediated by yes-associated protein (YAP) inhibition. The increased TCA cycle activity and respiration in Q cells is mediated by induced mitochondrial pyruvate carrier (MPC) expression, rendering them vulnerable to MPC inhibition. The malate-to-pyruvate flux, which generates NADPH, is markedly reduced by modulating malic enzyme 1 (ME1) dimerization in Q cells. Conversely, the malate dehydrogenase 1 (MDH1)-mediated oxaloacetate-to-malate flux is reversed and elevated in Q cells, driven by high mitochondrial-derived malate levels, reduced cytosolic oxaloacetate, elevated MDH1 levels, and a high cytoplasmic NAD+/NADH ratio. Transcriptomic analysis revealed large number of genes are induced in Q cells, many of which are associated with the extracellular matrix (ECM), while YAP-dependent and cell cycle-related genes are repressed. The results suggest that high TCA cycle flux and respiration in Q cells are required to generate ATP and amino acids to maintain de-novo ECM protein synthesis and secretion.

Hierarchical tricarboxylic acid cycle regulation by hepatocyte arginase 2 links the urea cycle to oxidative metabolism

Urea cycle impairment and its relationship to obesity and inflammation remained elusive, partly due to the dramatic clinical presentation of classical urea cycle defects. We generated mice with hepatocyte-specific arginase 2 deletion (Arg2LKO) and revealed a mild compensated urea cycle defect. Stable isotope tracing and respirometry revealed hepatocyte urea and TCA cycle flux defects, impaired mitochondrial oxidative metabolism, and glutamine anaplerosis despite normal energy and glucose homeostasis during early adulthood. Yet during middle adulthood, chow- and diet-induced obese Arg2LKO mice develop exaggerated glucose and lipid derangements, which are reversible by replacing the TCA cycle oxidative substrate nicotinamide adenine dinucleotide. Moreover, serum-based hallmarks of urea, TCA cycle, and mitochondrial derangements predict incident fibroinflammatory liver disease in 106,606 patients nearly a decade in advance. The data reveal hierarchical urea-TCA cycle control via ARG2 to drive oxidative metabolism. Moreover, perturbations in this circuit may causally link urea cycle compromise to fibroinflammatory liver disease.

Kinetic Diagram Analysis: A Python Library for Calculating Steady-State Observables of Biochemical Systems Analytically.

Kinetic diagrams are commonly used to represent biochemical systems in order to study phenomena such as free energy transduction and ion selectivity. While numerical methods are commonly used to analyze such kinetic networks, the diagram method by King, Altman and Hill makes it possible to construct exact algebraic expressions for steady-state observables in terms of the rate constants of the kinetic diagram. However, manually obtaining these expressions becomes infeasible for models of even modest complexity as the number of the required intermediate diagrams grows with the factorial of the number of states in the diagram. We developed Kinetic Diagram Analysis (KDA), a Python library that programmatically generates the relevant diagrams and expressions from a user-defined kinetic diagram. KDA outputs symbolic expressions for state probabilities and cycle fluxes at steady-state that can be symbolically manipulated and evaluated to quantify macroscopic system observables. We demonstrate the KDA approach for examples drawn from the biophysics of active secondary transmembrane transporters. For a generic 6-state antiporter model, we show how the introduction of a single leakage transition reduces transport efficiency by quantifying substrate turnover. We apply KDA to a real-world example, the 8-state free exchange model of the small multidrug resistance transporter EmrE of Hussey et al (J General Physiology 152 (2020), e201912437), where a change in transporter phenotype is achieved by biasing two different subsets of kinetic rates: alternating access and substrate unbinding rates. KDA is made available as open source software under the GNU General Public License version 3.

Emergent constraints on historical and future global gross primary productivity.

Terrestrial gross primary productivity (GPP) is the largest carbon flux in the global carbon cycle and plays a crucial role in terrestrial carbon sequestration. However, historical and future global GPP estimates still vary markedly. In this study, we reduced uncertainties in global GPP estimates by employing an innovative emergent constraint method on remote sensing-based GPP datasets (RS-GPP), using ground-based estimates of GPP from flux towers as the observational constraint. Using this approach, the global GPP in 2001-2014 was estimated to be 126.8 ± 6.4 PgC year-1, compared to the original RS-GPP ensemble mean of 120.9 ± 10.6 PgC year-1, which reduced the uncertainty range by 39.6%. Independent space- and time-based (different latitudinal zones, different vegetation types, and individual year) constraints further confirmed the robustness of the global GPP estimate. Building on these insights, we extended our constraints to project global GPP estimates in 2081-2100 under various Shared Socioeconomic Pathway (SSP) scenarios: SSP126 (140.6 ± 9.3 PgC year-1), SSP245 (153.5 ± 13.4 PgC year-1), SSP370 (170.7 ± 16.9 PgC year-1), and SSP585 (194.1 ± 23.2 PgC year-1). These findings have important implications for understanding and projecting climate change, helping to develop more effective climate policies and carbon reduction strategies.

The Algorithm of the Two Neutron Monitors for the Analysis of the Rigidity Spectrum Variations of Galactic Cosmic Ray Intensity Flux in Solar Cycle 24

The method of the two neutron monitors was used to analyze the parameters of the rigidity spectrum variations (RSV) of galactic cosmic ray intensity (GCR) flux in solar cycle 24 based on the data from the global network of neutron monitors. This method is an alternative to the least squares method when there are few monitors working stably in a given period, and their use in the least squares method is impossible. Analyses of the changes in exponent γ in the RSV of GCR flux from 2009 to 2019 were studied. The soft RSV (γ = 1.2–1.3) of the GCR flux around the maximum epoch and the hard RSV (γ = 0.6–0.9) around the minimum epoch of solar activity (SA) is the general feature of GCR modulation in the GeV energy scale (5, 50), to which neutron monitors were found to correspond. Therefore, various values of the RSV γ in the considered period show that during the decrease and increase period of SA, the essential changes in the large-scale structure of the heliospheric magnetic field (HMF) fluctuations/turbulence take place. The exponent γ of the RSV of the GCR flux can be considered a significant parameter to investigate the long-period changes in the GCR flux.

An Organism-Level Quantitative Flux Model of Energy Metabolism in Mice.

A flux model of energy metabolism integrating 13 C labeling of metabolites and CO 2 Circulating nutrients have characteristic partition between oxidation and storageCirculating nutrients' total cycling flux outweighs their total oxidation fluxCycling fluxes are extensively elevated in ob/ob but not in diet-induced obese mice.

Lactate promotes fatty acid oxidation by the tricarboxylic acid cycle and mitochondrial respiration in muscles of obese mice.

Lower oxidative capacity in skeletal muscles (SKMs) is a prevailing cause of metabolic diseases. Exercise not only enhances the fatty acid oxidation (FAO) capacity of SKMs but also increases lactate levels. Given that lactate may contribute to tricarboxylic acid cycle (TCA) flux and impact monocarboxylate transporter 1 in the SKMs, we hypothesize that lactate can influence glucose and fatty acid (FA) metabolism. To test this hypothesis, we investigated the mechanism underlying lactate-driven FAO regulation in the SKM of mice with diet-induced obesity (DIO). Lactate was administered to DIO mice immediately after exercise for over 3 wk. We found that increased lactate levels enhanced energy expenditure mediated by fat metabolism during exercise recovery and decreased triglyceride levels in DIO mice SKMs. To determine the lactate-specific effects without exercise, we administered lactate to mice on a high-fat diet (HFD) for 8 wk. Similar to our exercise conditions, lactate increased FAO, TCA cycle activity, and mitochondrial respiration in the SKMs of HFD-fed mice. In addition, under sufficient FA conditions, lactate increased uncoupling protein-3 abundance via the NADH-NAD+ shuttle. Conversely, ATP synthase abundance decreased in the SKMs of HFD mice. Taken together, our results suggest that lactate amplifies the adaptive increase in FAO capacity mediated by the TCA cycle and mitochondrial respiration in SKMs under sufficient FA abundance.NEW & NOTEWORTHY Lactate administration post-exercise promotes triglyceride content loss in skeletal muscles (SKMs) and reduced body weight. Lactate enhances fatty acid oxidation in the SKMs of high-fat diet (HFD)-fed mice due to enhanced mitochondrial oxygen consumption. In addition, lactate restores the malate-aspartate shuttle, which is reduced by a HFD, and activates the tricarboxylic acid cycle (TCA) cycle in SKMs. Interestingly, supraphysiological lactate facilitates uncoupling protein-3 expression through NADH/NAD+, which is enhanced under high-fat levels in SKMs.

Quantifying Drivers of Seasonal and Interannual Variability of Dissolved Oxygen in the Canada Basin Mixed Layer

AbstractAnalysis of dissolved oxygen (O2) in the Arctic's surface ocean provides insights into gas transfer between the atmosphere‐ice‐ocean system, water mass dynamics, and biogeochemical processes. In the Arctic Ocean's Canada Basin mixed layer, higher O2 concentrations are generally observed under sea ice compared to open water regions. Annual cycles of O2 and O2 saturation, increasing from summer through spring and then sharply declining to late summer, are tightly linked to sea ice cover. The primary fluxes that influence seasonal variability of O2 are modeled and compared to Ice‐Tethered Profiler O2 observations to understand the relative role of each flux in the annual cycle. Findings suggest that sea ice melt/growth dominates seasonal variations in mixed layer O2, with minor contributions from vertical entrainment and atmospheric exchange. While the influence of biological activity on O2 variability cannot be directly assessed, indirect evidence suggests relatively minor contributions, although with significant uncertainty. Past studies show that O2 molecules are expelled from sea ice during brine rejection; sea ice cover can then inhibit air‐sea gas exchange resulting in winter mixed layers that are super‐saturated. Decreasing mixed layer O2 concentrations and saturation levels are observed during winter months between 2007 and 2019 in the Canada Basin. Only a minor portion of the decreasing trend in wintertime O2 can be attributed to decreased solubility. This suggests the O2 decline may be linked to more efficient air‐sea exchange associated with increased open water areas in the winter sea ice pack that are not necessarily detectable via satellite observations.

Perturbations in mitochondrial metabolism associated with defective cardiolipin biosynthesis: An in-organello real-time NMR study.

Mitochondria are central to cellular metabolism; hence, their dysfunction contributes to a wide array of human diseases including cancer, cardiopathy, neurodegeneration, and heritable pathologies such as Barth syndrome. Cardiolipin, the signature phospholipid of the mitochondrion promotes proper cristae morphology, bioenergetic functions, and directly affects metabolic reactions carried out in mitochondrial membranes. To match tissue-specific metabolic demands, cardiolipin typically undergoes an acyl tail remodeling process with the final step carried out by the phospholipid-lysophospholipid transacylase tafazzin. Mutations in the tafazzin gene are the primary cause of Barth syndrome. Here, we investigated how defects in cardiolipin biosynthesis and remodeling impact metabolic flux through the tricarboxylic acid cycle and associated pathways in yeast. Nuclear magnetic resonance was used to monitor in real-time the metabolic fate of 13C3-pyruvate in isolated mitochondria from three isogenic yeast strains. We compared mitochondria from a wild-type strain to mitochondria from a Δtaz1 strain that lacks tafazzin and contains lower amounts of unremodeled cardiolipin, and mitochondria from a Δcrd1 strain that lacks cardiolipin synthase and cannot synthesize cardiolipin. We found that the 13C-label from the pyruvate substrate was distributed through about twelve metabolites. Several of the identified metabolites were specific to yeast pathways, including branched chain amino acids and fusel alcohol synthesis. Most metabolites showed similar kinetics amongst the different strains but mevalonate and α-ketoglutarate, as well as the NAD+/NADH couple measured in separate nuclear magnetic resonance experiments, showed pronounced differences. Taken together, the results show that cardiolipin remodeling influences pyruvate metabolism, tricarboxylic acid cycle flux, and the levels of mitochondrial nucleotides.

The stable sulfur isotope and abundance fluxes of reduced inorganic sulfur and organic sulfur phases recorded in the Permian-Triassic transition of the Meishan type section

Sulfur cycle fluxes implicated in the Permian-Triassic mass extinction have traditionally been studied by the sulfur phase abundances in sedimentary rocks and the stable sulfur isotopic value (δ34S) of seawater sulfate inferred from mineral sulfate analyses. This information might be complemented by studies of the reduced inorganic sulfur and organic sulfur produced following bacterial sulfate reduction. To explore this potential the δ34S and concentration analyses of total reduced inorganic sulfur (TRIS) and organic sulfur – separately in the forms of kerogen (Ker) and individual organosulfur compounds, specifically dibenzothiophenes (DBTs) – has been conducted on sediments across the Late Permian to Early Triassic marine type section of Meishan-1 (South China). The relatively steady δ34S profiles (e.g., < 5 ‰ variation) of all sulfur phases measured through much of the late Permian were indicative of a primary seawater sulfate control, but other biogeochemical modulators caused prominent δ34S fluctuations of TRIS and DBT adjacent to the extinction event. The late Triassic δ34STRIS profile of Meishan-1 displayed a notable 34S enrichment (+15 ‰ increase) in bed 22–24 sediments concomitant with lower δ34SDBT values (−7 ‰ decrease), whereas co-eval δ34SKerS values remained relatively constant. The contrasting δ34SDBT and δ34SKerS data suggests the dynamic behavior of specific diagenetic sulfurisation processes may be resolved by the δ34S of discrete organic sulfur compounds (i.e., dibenzothiophenes, DBTs), but dissipated by the sulfurisation collective represented by the bulk kerogen fraction. The inverse isotopic trend observed between DBT and TRIS resulted in negative Δδ34SDBT-TRIS values identifying an organic sulfurisation pathway(s) with an unusual preference over pyrite (FeS2) for the lighter stable sulfur isotope. A redox control of the δ34SDBTs and δ34STRIS deviations in the bed 22–24 extinction interval was confirmed by coincident variation in TRIS/(TRIS + KerS) and pyrite (Py) and highly reactive (HR) iron ratios (FePy/FeHR). The iron (Fe) speciation data indicated a transition to ferruginous conditions, ruling out Fe2+ limitation as a factor in the bias against 34S evident in DBT formation. The 34S depletion of the DBTs promoted by the ferruginous setting may arise from the rapid and irreversible reaction of organic substrates with labile sulfur anions (e.g. HS-) or be supported by an especially localised sediment–water depositional microenvironment. Our study highlights the potential of incorporating stable sulfur isotope analytics of reduced and organic sulfur phases, particularly of specific organic compounds, into a holistic assessment of the dynamic sulfur biochemical periods of Earth’s past.

Use of acetate as substrate for sustainable production of homoserine and threonine by Escherichia coli W3110: A modular metabolic engineering approach

Acetate, a promising yet underutilized carbon source for biological production, was explored for the efficient production of homoserine and threonine in Escherichia coli W. A modular metabolic engineering approach revealed the crucial roles of both acetate assimilation pathways (AckA/Pta and Acs), optimized TCA cycle flux and glyoxylate shunt activity, and enhanced CoA availability, mediated by increased pantothenate kinase activity, for efficient homoserine production. The engineered strain W–H22/pM2/pR1P exhibited a high acetate assimilation rate (5.47 mmol/g cell/h) and produced 44.1 g/L homoserine in 52 h with a 53% theoretical yield (0.18 mol/mol) in fed-batch fermentation. Similarly, strain W–H31/pM2/pR1P achieved 45.8 g/L threonine in 52 h with a 65% yield (0.22 mol/mol). These results represent the highest reported levels of amino acid production using acetate, highlighting its potential as a valuable and sustainable feedstock for biomanufacturing.

Deficits in brain glucose transport among younger adults with obesity.

Obesity is associated with alterations in eating behavior and neurocognitive function. In this study, we investigate the effect of obesity on brain energy utilization, including brain glucose transport and metabolism. A total of 11 lean participants and 7 young healthy participants with obesity (mean age, 27 years) underwent magnetic resonance spectroscopy scanning coupled with a hyperglycemic clamp (target, ~180 mg/dL) using [1-13C] glucose to measure brain glucose uptake and metabolism, as well as peripheral markers of insulin resistance. Individuals with obesity demonstrated an ~20% lower ratio of brain glucose uptake to cerebral glucose metabolic rate (Tmax/CMRglucose) than lean participants (2.12 ± 0.51 vs. 2.67 ± 0.51; p = 0.04). The cerebral tricarboxylic acid cycle flux (VTCA) was similar between the two groups (p = 0.64). There was a negative correlation between total nonesterified fatty acids and Tmax/CMRglucose (r = -0.477; p = 0.045). We conclude that CMRglucose is unlikely to differ between groups due to similar VTCA, and, therefore, the glucose transport Tmax is lower in individuals with obesity. These human findings suggest that obesity is associated with reduced cerebral glucose transport capacity even at a young age and in the absence of other cardiometabolic comorbidities, which may have implications for long-term brain function and health.