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Liver metabolism is central to human physiology and influences the pathogenesis of common metabolic diseases. Yet, our understanding of human liver metabolism remains incomplete, with much of current knowledge based on animal or cell culture models that do not fully recapitulate human physiology. Here, we perform in-depth measurement of metabolism in intact human liver tissue ex vivo using global 13C tracing, non-targeted mass spectrometry and model-based metabolic flux analysis. Isotope tracing allowed qualitative assessment of a wide range of metabolic pathways within a single experiment, confirming well-known features of liver metabolism but also revealing unexpected metabolic activities such as de novo creatine synthesis and branched-chain amino acid transamination, where human liver appears to differ from rodent models. Glucose production ex vivo correlated with donor plasma glucose, suggesting that cultured liver tissue retains individual metabolic phenotypes, and could be suppressed by postprandial levels of nutrients and insulin, and also by pharmacological inhibition of glycogen utilization. Isotope tracing ex vivo allows measuring human liver metabolism with great depth and resolution in an experimentally tractable system.

Background: Myceliophthora thermophila has been engineered as a significant cell factory for malic acid production, yet strategies to further enhance production remain unclear and lack rational guidance. 13C-MFA (13C metabolic flux analysis) offers a means to analyze cellular metabolic mechanisms and pinpoint critical nodes for improving product synthesis. Here, we employed 13C-MFA to investigate the metabolic flux distribution of a high-malic acid-producing strain of M. thermophila and attempted to decipher the crucial bottlenecks in the metabolic pathways. Results: Compared with the wild-type strain, the high-Malic acid-producing strain M. thermophila JG207 exhibited greater glucose uptake and carbon dioxide evolution rates but lower oxygen uptake rates and biomass yields. Consistent with these phenotypes, the 13C-MFA results showed that JG207 displayed elevated flux through the EMP pathway and downstream TCA cycle, along with reduced oxidative phosphorylation flux, thereby providing more precursors and NADH for malic acid synthesis. Furthermore, based on the 13C-MFA results, we conducted oxygen-limited culture and nicotinamide nucleotide transhydrogenase (NNT) gene knockout experiments to increase the cytoplasmic NADH level, both of which were shown to be beneficial for malic acid accumulation. Conclusions: This work elucidates and validates the key node for achieving high malic acid production in M. thermophila. We propose effective fermentation strategies and genetic modifications for enhancing malic acid production. These findings offer valuable guidance for the rational design of future cell factories aimed at improving malic acid yields. [ABSTRACT FROM AUTHOR]

Nonresolving inflammation causes irreversible damage to periodontal ligament stem cells (PDLSCs) and impedes alveolar bone restoration. The impaired tissue regeneration ability of stem cells is associated with abnormal mitochondrial metabolism. However, the impact of specific metabolic alterations on the differentiation process of PDLSCs remains to be understood. In this study, we found that inflammation altered the metabolic flux of the tricarboxylic acid cycle and induced the accumulation of fumarate through metabolic testing and metabolic flux analysis. Transcriptome sequencing revealed the potential of fumarate in modulating epigenetics. Specifically, histone methylation typically suppresses the expression of genes related to osteogenesis. Fumarate was found to impede the osteogenic differentiation of PDLSCs that exhibited high levels of H3K9me3. Various techniques, including assay for transposase-accessible chromatin with high-throughput sequencing, chromatin immunoprecipitation sequencing, and RNA sequencing, were used to identify the target genes regulated by H3K9me3. Mechanistically, accumulated fumarate inhibited lysine-specific demethylase 4B (KDM4B) activity and increased H3K9 methylation, thus silencing asporin gene transcription. Preventing fumarate from binding to the histone demethylase KDM4B with α-ketoglutarate effectively restored the impaired osteogenic capacity of PDLSCs and improved alveolar bone recovery. Collectively, our research has revealed the significant impact of accumulated fumarate on the regulation of osteogenesis in stem cells, suggesting that inhibiting fumarate production could be a viable therapeutic approach for treating periodontal diseases. [ABSTRACT FROM AUTHOR]

Comparative transcriptomics uncovered distinct expression patterns of genes associated with cofactor and vitamin metabolism in the high-yielding mutant strain Saccharopolyspora erythraea HL3168 E3, as compared to the wild-type NRRL 2338. An in-depth analysis was conducted on the effects of nine vitamins, and it was determined that thiamine pyrophosphate (TPP), vitamin B2, vitamin B6, vitamin B9, vitamin B12, and hemin are key enhancers in erythromycin production in E3, increasing the erythromycin titer by 7.96–12.66%. Then, the Plackett-Burman design and the path of steepest ascent were applied to further optimize the vitamin combination for maximum production efficiency, enhancing the erythromycin titer in shake flasks by 39.2%. Otherwise, targeted metabolomics and metabolic flux analysis illuminated how vitamin supplementation modulates the central carbon metabolism with notable effects on the TCA cycle and methionine synthesis to augment the provision of energy and precursors essential for erythromycin synthesis. This work highlights the capacity for precise vitamin supplementation to refine metabolic pathways, thereby boosting erythromycin production, and provides valuable directions for application on an industrial scale. [ABSTRACT FROM AUTHOR]

The metabolic networks of microorganisms are remarkably robust to genetic and environmental perturbations. This robustness stems from redundancies such as gene duplications, isoenzymes, alternative metabolic pathways, and also from non‐enzymatic reactions. In the oxidative branch of the pentose phosphate pathway (oxPPP), 6‐phosphogluconolactone hydrolysis into 6‐phosphogluconate is catalysed by 6‐phosphogluconolactonase (Pgl) but in the absence of the latter, the oxPPP flux is thought to be maintained by spontaneous hydrolysis. However, in Δpgl Escherichia coli, an extracellular pathway can also contribute to pentose phosphate synthesis. This raises question as to whether the intracellular non‐enzymatic reaction can compensate for the absence of 6‐phosphogluconolactonase and, ultimately, on the role of 6‐phosphogluconolactonase in central metabolism. Our results validate that the bypass pathway is active in the absence of Pgl, specifically involving the extracellular spontaneous hydrolysis of gluconolactones to gluconate. Under these conditions, metabolic flux analysis reveals that this bypass pathway accounts for the entire flux into the oxPPP. This alternative metabolic route—partially extracellular—sustains the flux through the oxPPP necessary for cell growth, albeit at a reduced rate in the absence of Pgl. Importantly, these findings imply that intracellular non‐enzymatic hydrolysis of 6‐phosphogluconolactone does not compensate for the absence of Pgl. This underscores the crucial role of Pgl in ensuring the efficient functioning of the oxPPP. [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Nutrition and physiological state affect hepatic metabolism. Our objective was to determine whether feeding flaxseed oil (∼50% C18:3n-3 cis), high oleic soybean oil (∼70% C18:1 cis -9), or milk fat (∼50% C16:0) alters hepatic expression of PC , PCK1 , and PCK2 and the flow of carbons from propionate and pyruvate into the tricarboxylic acid (TCA) cycle in preruminating calves. Male Holstein calves (n = 40) were assigned to a diet of skim milk with either: 3% milk fat (MF; n = 8), 3% flaxseed oil (Flax; n = 8), 3% high oleic soybean oil (HOSO; n = 8), 1.5% MF + 1.5% high oleic soybean oil (MF-HOSO; n = 8), or 1.5% MF + 1.5% flaxseed oil (MF-Flax; n = 8) from d 14 to d 21 postnatal. At d 21 postnatal, a liver biopsy was taken for gene expression and metabolic flux analysis. Liver explants were incubated in [U-13C] propionate and [U-13C] pyruvate to trace carbon flux through TCA cycle intermediates or with [U-14C] lactate, [1-14C] palmitic acid, or [2-14C] propionate to quantify substrate oxidation to CO 2 and acid-soluble products. Compared with other treatments, plasma C18:3n-3 cis was 10 times higher and C18:1 cis -9 was 3 times lower in both Flax (Flax and MF-Flax) treatments. PC , PCK1 , and PCK2 expression and flux of [U-13C] pyruvate as well as [U-13C] propionate were not different among treatments. PC expression was negatively correlated with the enrichment of citrate M+5 and malate M+3, and PCK2 was negatively correlated with citrate M+5, suggesting that when expression of these enzymes is increased, carbon from pyruvate enters the TCA cycle via PC-mediated carboxylation, and then oxaloacetate is converted to phosphoenolpyruvate via PCK2. Acid-soluble product formation and PC expression were reduced in HOSO (MF-HOSO and HOSO) treatments compared with Flax (MF-Flax and Flax), indicating that fatty acids regulate PC expression and carbon flux, but that fatty acid flux control points are not connected to PC , PCK1 , or PCK2. In conclusion, fatty acids regulate hepatic expression of PC , PCK1 , and PCK2 , and carbon flux, but the point of control is distinct. [ABSTRACT FROM AUTHOR]

Summary: Even though they share many thematical overlaps, plant metabolomics and stable isotope ecology have been rather separate fields mainly due to different mass spectrometry demands. New high‐resolution bioanalytical mass spectrometers are now not only offering high‐throughput metabolite identification but are also suitable for compound‐ and intramolecular position‐specific isotope analysis in the natural isotope abundance range. In plant metabolomics, label‐free metabolic pathway and metabolic flux analysis might become possible when applying this new technology. This is because changes in the commitment of substrates to particular metabolic pathways and the activation or deactivation of others alter enzyme‐specific isotope effects. This leads to differences in intramolecular and compound‐specific isotope compositions. In plant isotope ecology, position‐specific isotope analysis in plant archives informed by metabolic pathway analysis could be used to reconstruct and separate environmental impacts on complex metabolic processes. A technology‐driven linkage between the two disciplines could allow us to extract information on environment–metabolism interaction from plant archives such as tree rings but also within ecosystems. This would contribute to a holistic understanding of how plants react to environmental drivers, thus also providing helpful information on the trajectories of the vegetation under the conditions to come. [ABSTRACT FROM AUTHOR]

The microenvironment within solid tumors often becomes acidic due to various factors associated with abnormal metabolism and cellular activities, including increased lactate production as a result of dysregulated tumor glycolysis. Recently, we have identified multiple tumor microenvironment (TME) factors that potentiate regulatory T (T reg) cell function in evading anti-tumor immunosurveillance. Despite the strong correlation between lactate and acidity, the potential roles of acidity in intratumoral T reg cell adaptation and underlying molecular mechanisms have gone largely unstudied. In this study, we demonstrate that acidity significantly enhances immunosuppressive functions of nT reg cells, but not iT reg cells, without altering the expression of either FoxP3 or the cell surface receptors CD25, CTLA4, or GITR in these cells. Surprisingly, the addition of lactate, often considered a major contributor to increased acidity of the TME, completely abolished the acidity-induced enhancement of nT reg suppressive functions. Consistently, metabolic flux analyses showed elevated basal mitochondrial respiratory capacity and ATP-coupled respiration in acidity-treated nT reg cells without altering glycolytic capacity. Genome-wide transcriptome and metabolomics analyses revealed alterations in multiple metabolic pathways, particularly the one-carbon folate metabolism pathway, with reduced SAM, folate, and glutathione, in nT reg cells exposed to low pH conditions. Addition of a one-carbon metabolic contributor, formate, diminished the acidity-induced enhancement in nT reg cell suppressive functions, but neither SAM nor glutathione could reverse the phenotype. Remarkably, in vitro transient treatment of nT reg cells resulted in sustained enhancement of their functions, as evidenced by more vigorous tumor growth observed in mice adoptively receiving acidity-treated nT reg cells. Further analysis of intratumoral infiltrated T cells confirmed a significant reduction in CD8+ T cell frequency and their granzyme B production. In summary, our study elucidates how acidity-mediated metabolic reprogramming leads to sustained Treg-mediated tumor immune evasion. • Acidity enhances T reg cell suppressive functions independent of lactate in vitro and in vivo. • T reg cell oxidative metabolic capacity increases as a result of exposure to acidity. • Treatment with acidity results in T reg cell transcriptional and metabolic changes in one-carbon folate metabolism. • Exposure to acidity ex vivo for 48 hours facilitates increased T reg suppressive functions against T eff cells in the TME and promotes tumor growth in the MC38 colon cancer model. • Treatment of T reg cells with acidity and formate restores suppressive capacity induced by acidity and decreases tumor burden in the MC38 colon cancer model. [ABSTRACT FROM AUTHOR]

Abstract Comparative transcriptomics uncovered distinct expression patterns of genes associated with cofactor and vitamin metabolism in the high-yielding mutant strain Saccharopolyspora erythraea HL3168 E3, as compared to the wild-type NRRL 2338. An in-depth analysis was conducted on the effects of nine vitamins, and it was determined that thiamine pyrophosphate (TPP), vitamin B2, vitamin B6, vitamin B9, vitamin B12, and hemin are key enhancers in erythromycin production in E3, increasing the erythromycin titer by 7.96–12.66%. Then, the Plackett-Burman design and the path of steepest ascent were applied to further optimize the vitamin combination for maximum production efficiency, enhancing the erythromycin titer in shake flasks by 39.2%. Otherwise, targeted metabolomics and metabolic flux analysis illuminated how vitamin supplementation modulates the central carbon metabolism with notable effects on the TCA cycle and methionine synthesis to augment the provision of energy and precursors essential for erythromycin synthesis. This work highlights the capacity for precise vitamin supplementation to refine metabolic pathways, thereby boosting erythromycin production, and provides valuable directions for application on an industrial scale. Graphical Abstract

In order to further understand the effect of product inhibition on the metabolism of hydrogen production bacteria, and to seek an effective way to increase the hydrogen yield in fermentation, a simplified metabolic model of Ethanoligenens harbinense B49 was constructed to analyse the metabolic flux under acetate and ethanol inhibition separately and to analyse the flux changes of the nodes. Based on the changes in metabolic flux distribution, Glucose 6-phosphate (G6P), Pyruvate (PYR), and Acetyl-CoA (AcCoA) were identified as key nodes of hydrogen production in the metabolic network. Robustness analysis showed that G6P was flexible, while AcCoA and PYR were weakly rigid, indicating that acetate flux could be increased by adding inhibitors or using genetic manipulation. Furthermore, releasing inhibition of acetate could effectively increase hydrogen production. These findings suggested that the addition of acetate separation in ethanol-type fermentation process is expected to improve hydrogen production, which might be a promising way to full-scale produce biohydrogen in industrial applications. Further, for the first time, we report the effect of product inhibition on key nodes in the E. harbinense B49 hydrogen production metabolism network. [ABSTRACT FROM AUTHOR]

Cell-free protein synthesis (CFPS) has emerged as a powerful tool for protein production, with applications ranging from basic research to biotechnology and pharmaceutical development. However, enhancing the efficiency of CFPS systems remains a crucial challenge for realizing their full potential. Computational strategies offer promising avenues for optimizing CFPS efficiency by providing insights into complex biological processes and enabling rational design approaches. This review provides a comprehensive overview of the computational approaches aimed at enhancing CFPS efficiency. The introduction outlines the significance of CFPS and the role of computational methods in addressing efficiency limitations. It discusses mathematical modeling and simulation-based approaches for predicting protein synthesis kinetics and optimizing CFPS reactions. The review also delves into the design of DNA templates, including codon optimization strategies and mRNA secondary structure prediction tools, to improve protein synthesis efficiency. Furthermore, it explores computational techniques for engineering cell-free transcription and translation machinery, such as the rational design of expression systems and the predictive modeling of ribosome dynamics. The predictive modeling of metabolic pathways and the energy utilization in CFPS systems is also discussed, highlighting metabolic flux analysis and resource allocation strategies. Machine learning and artificial intelligence approaches are being increasingly employed for CFPS optimization, including neural network models, deep learning algorithms, and reinforcement learning for adaptive control. This review presents case studies showcasing successful CFPS optimization using computational methods and discusses applications in synthetic biology, biotechnology, and pharmaceuticals. The challenges and limitations of current computational approaches are addressed, along with future perspectives and emerging trends, such as the integration of multi-omics data and advances in high-throughput screening. The conclusion summarizes key findings, discusses implications for future research directions and applications, and emphasizes opportunities for interdisciplinary collaboration. This review offers valuable insights and prospects regarding computational strategies to enhance CFPS efficiency. It serves as a comprehensive resource, consolidating current knowledge in the field and guiding further advancements. [ABSTRACT FROM AUTHOR]

Aims: Incidence of acute mountain sickness (AMS) ranges from 40%–90%, with high‐altitude cerebral edema (HACE) representing a life‐threatening end stage of severe AMS. However, practical and convenient preventive strategies for HACE are lacking. Remote ischemic preconditioning (RIPC) has demonstrated preventive effects on ischemia‐ or hypoxia‐induced cardiovascular and cerebrovascular diseases. This study aimed to investigate the potential molecular mechanism of HACE and the application of RIPC in preventing HACE onset. Methods: A hypobaric hypoxia chamber was used to simulate a high‐altitude environment of 7000 meters. Metabolomics and metabolic flux analysis were employed to assay metabolite levels. Transcriptomics and quantitative real‐time PCR (q‐PCR) were used to investigate gene expression levels. Immunofluorescence staining was performed on neurons to label cellular proteins. The fluorescent probes Mito‐Dendra2, iATPSnFR1.0, and CMTMRos were used to observe mitochondria, ATP, and membrane potential in cultured neurons, respectively. TUNEL staining was performed to detect and quantify apoptotic cell death. Hematoxylin and eosin (H&E) staining was utilized to analyze pathological changes, such as tissue swelling in cerebral cortex samples. The Rotarod test was performed to assess motor coordination and balance in rats. Oxygen–glucose deprivation (OGD) of cultured cells was employed as an in vitro model to simulate the hypoxia and hypoglycemia induced by RIPC in animal experiments. Results: We revealed a causative perturbation of glucose metabolism in the brain preceding cerebral edema. Ischemic preconditioning treatment significantly reprograms glucose metabolism, ameliorating cell apoptosis and hypoxia‐induced energy deprivation. Notably, ischemic preconditioning improves mitochondrial membrane potential and ATP production through enhanced glucose‐coupled mitochondrial metabolism. In vivo studies confirm that RIPC alleviates cerebral edema, reduces cell apoptosis induced by high‐altitude hypoxia, and improves motor dysfunction resulting from cerebral edema. Conclusions: Our study elucidates the metabolic basis of HACE pathogenesis. This study provides a new strategy for preventing HACE that RIPC reduces brain edema through reprogramming metabolism, highlighting the potential of targeting metabolic reprogramming for neuroprotective interventions in neurological diseases caused by ischemia or hypoxia. [ABSTRACT FROM AUTHOR]

Severe dry eye disease causes ocular surface damage, which is highly associated with mitochondrial dysfunction. Mitochondrial transcription factor A (TFAM) is essential for packaging mitochondrial DNA (mtDNA) and is crucial for maintaining mitochondrial function. Herein, we aimed to explore the effect of a decreased TFAM expression on ocular surface damage. Female C57BL/6 mice were induced ocular surface injury by topical administrating benzalkonium chloride (BAC). Immortalized human corneal epithelial cells (HCECs) were stimulated by tert -butyl hydroperoxide (t-BHP) to create oxidative stress damage. HCECs with TFAM knockdown were established. RNA sequencing was employed to analyze the whole-genome expression. Mitochondrial changes were measured by transmission electron microscopy, Seahorse metabolic flux analysis, mitochondrial membrane potential, and mtDNA copy number. TFAM expression and inflammatory cytokines were determined using RT-qPCR, immunohistochemistry, immunofluorescence, and immunoblotting. In both the corneas of BAC-treated mice and t-BHP-induced HCECs, we observed impaired TFAM expression, accompanied by mitochondrial structure and function defects. TFAM downregulation in HCECs suppressed mitochondrial respiratory capacity, reduced mtDNA content, induced mtDNA leakage into the cytoplasm, and led to inflammation. RNA sequencing revealed the absent in melanoma 2 (AIM2) inflammasome was activated in the corneas of BAC-treated mice. The AIM2 inflammasome activation was confirmed in TFAM knockdown HCECs. TFAM knockdown in t-BHP-stimulated HCECs aggravated mitochondrial dysfunction and the AIM2 inflammasome activation, thereby further triggering the secretion of inflammatory factors such as interleukin (IL) -1β and IL-18. TFAM reduction impaired mitochondrial function, activated AIM2 inflammasome and promoted ocular surface inflammation, revealing an underlying molecular mechanism for ocular surface disorders. [Display omitted] • TFAM reduction is a factor that promotes progression of ocular surface damage. • Impaired TFAM expression may exacerbate ocular surface injury by disrupting mitochondrial function and further promoting inflammation. • AIM2 inflammasome activation may be involved in ocular surface inflammation induced by TFAM reduction. • TFAM may serve as a promising therapeutic approach for addressing ocular surface disorders, such as dry eye disease. [ABSTRACT FROM AUTHOR]

AbstractMicrobes have been extensively utilized for their sustainable and scalable properties in synthesizing desired bio-products. However, insufficient knowledge about intracellular metabolism has impeded further microbial applications. The genome-scale metabolic models (GEMs) play a pivotal role in facilitating a global understanding of cellular metabolic mechanisms. These models enable rational modification by exploring metabolic pathways and predicting potential targets in microorganisms, enabling precise cell regulation without experimental costs. Nonetheless, simplified GEM only considers genome information and network stoichiometry while neglecting other important bio-information, such as enzyme functions, thermodynamic properties, and kinetic parameters. Consequently, uncertainties persist particularly when predicting microbial behaviors in complex and fluctuant systems. The advent of the omics era with its massive quantification of genes, proteins, and metabolites under various conditions has led to the flourishing of multi-constrained models and updated algorithms with improved predicting power and broadened dimension. Meanwhile, machine learning (ML) has demonstrated exceptional analytical and predictive capacities when applied to training sets of biological big data. Incorporating the discriminant strength of ML with GEM facilitates mechanistic modeling efficiency and improves predictive accuracy. This paper provides an overview of research innovations in the GEM, including multi-constrained modeling, analytical approaches, and the latest applications of ML, which may contribute comprehensive knowledge toward genetic refinement, strain development, and yield enhancement for a broad range of biomolecules. [ABSTRACT FROM AUTHOR]

Metabolic engineering provides a more sustainable alternative by using complex metabolic processes to generate valuable compounds by exploiting nature's metabolic networks. Metabolic flux analysis is frequently used in metabolic engineering to improve production yields and selectivity of compounds including biofuels, medicines, and industrial chemicals. It analyzes metabolic pathways and flux distribution to identify essential steps and targets for optimization, mainly to increase biopolymer synthesis, including polyhydroxybutyrate (PHB). PHB is a significant carbon reservoir due to its capacity to store carbon in a biodegradable polymer form in sectors such as packaging, biomedicine, and environmental remediation, making it an economically and environmentally friendly substitute to existing nonrenewable resources. Metabolic flux analysis and metabolic engineering are essential in synthesizing PHB, a biodegradable polymer with several uses. By combining these techniques, researchers can enhance efficiency, boost yields, and develop microorganisms with improved PHB synthesis capabilities. Metabolic flux analysis can identify rate-limiting steps in the PHB biosynthesis pathway and evaluate flux distribution, enabling the identification of metabolic engineering targets that may increase PHB production. Metabolic engineering may also increase the expression of PHB biosynthesis genes or add new genes to the pathway. The study analyzed here examines the significance of combining metabolic flux analysis and metabolic engineering, as well as their potential to considerably increase PHB production and improve the economic feasibility of this key biopolymer. [ABSTRACT FROM AUTHOR]

Among plant pathogens, the necrotrophic fungus Botrytis cinerea is one of the most prevalent, leading to severe crop damage. Studies related to its colonization of different plant species have reported variable host metabolic responses to infection. In tomato, high N availability leads to decreased susceptibility. Metabolic flux analysis can be used as an integrated method to better understand which metabolic adaptations lead to effective host defence and resistance. Here, we investigated the metabolic response of tomato infected by B. cinerea in symptomless stem tissues proximal to the lesions for 7 d post-inoculation, using a reconstructed metabolic model constrained by a large and consistent metabolic dataset acquired under four different N supplies. An overall comparison of 48 flux solution vectors of Botrytis - and mock-inoculated plants showed that fluxes were higher in Botrytis -inoculated plants, and the difference increased with a reduction in available N, accompanying an unexpected increase in radial growth. Despite higher fluxes, such as those involved in cell wall synthesis and other pathways, fluxes related to glycolysis, the tricarboxylic acid cycle, and amino acid and protein synthesis were limited under very low N, which might explain the enhanced susceptibility. Limiting starch synthesis and enhancing fluxes towards redox and specialized metabolism also contributed to defence independent of N supply. [ABSTRACT FROM AUTHOR]

Viruses are obligate intracellular parasites that rely on host cell metabolism for successful replication. Thus, viruses rewire host cell pathways involved in central carbon metabolism to increase the availability of building blocks for successful propagation. However, the underlying mechanisms of virus-induced alterations to host metabolism are largely unknown. Noroviruses (NoVs) are highly prevalent pathogens that cause sporadic and epidemic viral gastroenteritis. In the present study, we uncovered several strain-specific and shared host cell metabolic requirements of three murine norovirus (MNV) strains, MNV-1, CR3, and CR6. While all three strains required glycolysis, glutaminolysis, and the pentose phosphate pathway for optimal infection of macrophages, only MNV-1 relied on host oxidative phosphorylation. Furthermore, the first metabolic flux analysis of NoV-infected cells revealed that both glycolysis and glutaminolysis are upregulated during MNV-1 infection of macrophages. Glutamine deprivation affected the viral lifecycle at the stage of genome replication, resulting in decreased non-structural and structural protein synthesis, viral assembly, and egress. Mechanistic studies further showed that MNV infection and overexpression of the non-structural protein NS1/2 increased the enzymatic activity of the rate-limiting enzyme glutaminase. In conclusion, the inaugural investigation of NoV-induced alterations to host glutaminolysis identified NS1/2 as the first viral molecule for RNA viruses that regulates glutaminolysis either directly or indirectly. This increases our fundamental understanding of virus-induced metabolic alterations and may lead to improvements in the cultivation of human NoVs. Author summary: All viruses critically depend on the host cells they infect to provide the necessary machinery and building blocks for successful replication. Thus, viruses often alter host metabolic pathways to increase the availability of key metabolites they require. Human noroviruses (HNoVs) are a major cause of acute non-bacterial gastroenteritis, leading to significant morbidity and economic burdens. To date, no vaccines or antivirals are approved against NoVs, which demonstrates a need to better understand NoV biology, including the role host metabolism plays during infection. Using the murine norovirus (MNV) model, we show that host cell glutaminolysis is upregulated and required for optimal virus infection. Additional data point to a model whereby the viral non-structural protein NS1/2 upregulates the enzymatic activity of glutaminase, the rate-limiting enzyme in glutaminolysis. Insights gained through investigating the role host metabolism plays in MNV replication may assist with improving HNoV cultivation methods and development of novel therapies. [ABSTRACT FROM AUTHOR]

The mitochondrial translocator protein 18 kDa (TSPO) has been linked to functions from steroidogenesis to regulation of cellular metabolism and is an attractive therapeutic target for chronic CNS inflammation. Studies in Leydig cells and microglia indicate that TSPO function may vary between cells depending on their specialized roles. Astrocytes are critical for providing trophic and metabolic support in the brain. Recent work has highlighted that TSPO expression increases in astrocytes under inflamed conditions and may drive astrocyte reactivity. Relatively little is known about the role TSPO plays in regulating astrocyte metabolism and whether this protein is involved in immunometabolic processes in these cells. Using TSPO‐deficient (TSPO−/−) mouse primary astrocytes in vitro (MPAs) and a human astrocytoma cell line (U373 cells), we performed extracellular metabolic flux analyses. We found that TSPO deficiency reduced basal cellular respiration and attenuated the bioenergetic response to glucopenia. Fatty acid oxidation was increased, and lactate production was reduced in TSPO−/− MPAs and U373 cells. Co‐immunoprecipitation studies revealed that TSPO forms a complex with carnitine palmitoyltransferase 1a in U373 and MPAs, presenting a mechanism wherein TSPO may regulate FAO in these cells. Compared to TSPO+/+ cells, in TSPO−/− MPAs we observed attenuated tumor necrosis factor release following 3 h lipopolysaccharide (LPS) stimulation, which was enhanced at 24 h post‐LPS stimulation. Together these data suggest that while TSPO acts as a regulator of metabolic flexibility, TSPO deficiency does not appear to modulate the metabolic response of MPAs to inflammation, at least in response to the model used in this study. [ABSTRACT FROM AUTHOR]

Glutathione is a tripeptide of excellent value in the pharmaceutical, food, and cosmetic industries that is currently produced during yeast fermentation. In this case, glutathione accumulates intracellularly, which hinders high production. Here, we engineered Escherichia coli for the efficient production of glutathione. A total of 4.3 g/L glutathione was produced by overexpressing gshA and gshB , which encode cysteine glutamate ligase and glutathione synthetase, respectively, and most of the glutathione was excreted into the culture medium. Further improvements were achieved by inhibiting degradation (Δ ggt and Δ pepT); deleting gor (Δ gor), which encodes glutathione oxide reductase; attenuating glutathione uptake (Δ yliABCD); and enhancing cysteine production (P ompF -cysE). The engineered strain KG06 produced 19.6 g/L glutathione after 48 h of fed-batch fermentation with continuous addition of ammonium sulfate as the sulfur source. We also found that continuous feeding of glycine had a crucial role for effective glutathione production. The results of metabolic flux and metabolomic analyses suggested that the conversion of O -acetylserine to cysteine is the rate-limiting step in glutathione production by KG06. The use of sodium thiosulfate largely overcame this limitation, increasing the glutathione titer to 22.0 g/L, which is, to our knowledge, the highest titer reported to date in the literature. This study is the first report of glutathione fermentation without adding cysteine in E. coli. Our findings provide a great potential of E. coli fermentation process for the industrial production of glutathione. [Display omitted] • Glutathione was produced by E. coli fermentation without cysteine addition. • In our process, most glutathione was excreted into the culture supernatants. • Genetic modifications improved glutathione production. • Optimal glycine and sulfur supplementation led to 22.0 g/L glutathione production. [ABSTRACT FROM AUTHOR]

Chondrocytes, which typically rely on anaerobic metabolism, exhibit upregulated biosynthetic activity when subjected to conditions that elicit mixed aerobic-anaerobic metabolism. Previously, we observed that increasing media volume resulted in the transition from anaerobic to mixed aerobic-anaerobic metabolism. Maximal extracellular matrix (ECM) accumulation occurred at this transition as a result of changes in hypoxia-inducible factor 1α signaling and associated hypoxic gene expression. This study aimed to explore the effect of further increases in media availability on ECM synthesis and chondrocyte metabolism. Primary bovine chondrocytes were grown in 3D high-density tissue culture under varying levels of media availability (4–16 mL/106 cells). Changes in ECM accumulation and metabolism were determined through biochemical assays and 13C-metabolic flux analysis (13C-MFA). Increasing media volumes resulted in higher accumulation of cartilaginous ECM (collagen and proteoglycans) and cellularity. Extracellular metabolite measurements revealed that elevated media availability led to increased glucose and glutamine metabolism, along with increased anaerobic activity. 13C-MFA utilizing [U-13C] glucose demonstrated that increased media availability significantly impacted central carbon metabolism, upregulating all glucose-related metabolic pathways (glycolysis, lactate fermentation, the tricarboxylic acid (TCA) cycle, hexosamine biosynthetic pathway, and the malate-aspartate shuttle). Furthermore, 13C-MFA indicated that glutamine was donating carbons to the TCA cycle, and additional studies involving [U-13C] glutamine tracing supported this notion. Elevated media availability upregulates ECM synthesis and leads to significant changes in metabolic phenotype. Glutamine plays an important role in chondrocyte metabolism and increases in glutamine metabolism correlate with increases in ECM accumulation. [ABSTRACT FROM AUTHOR]

TRIMER, Transcription Regulation Integrated with MEtabolic Regulation, is a genome-scale modeling pipeline targeting at metabolic engineering applications. Using TRIMER, regulated metabolic reactions can be effectively predicted by integrative modeling of metabolic reactions with a transcription factor-gene regulatory network (TRN), which is modeled through a Bayesian network (BN). In this article, we focus on sensitivity analysis of metabolic flux prediction for uncertainty quantification of BN structures for TRN modeling in TRIMER. We propose a computational strategy to construct the uncertainty class of TRN models based on the inferred regulatory order uncertainty given transcriptomic expression data. With that, we analyze the prediction sensitivity of the TRIMER pipeline for the metabolite yields of interest. The obtained sensitivity analyses can guide optimal experimental design (OED) to help acquire new data that can enhance TRN modeling and achieve specific metabolic engineering objectives, including metabolite yield alterations. We have performed small- and large-scale simulated experiments, demonstrating the effectiveness of our developed sensitivity analysis strategy for BN structure learning to quantify the edge importance in terms of metabolic flux prediction uncertainty reduction and its potential to effectively guide OED.

Objectives: Histone acetylation is an important epigenetic modification that regulates various biological processes and cell homeostasis. Acetyl-CoA, a hub molecule of metabolism, is the substrate for histone acetylation, thus linking metabolism with epigenetic regulation. However, still relatively little is known about the dynamics of histone acetylation and its dependence on metabolic processes, due to the lack of integrated methods that can capture site-specific histone acetylation and deacetylation reactions together with the dynamics of acetyl-CoA synthesis. Methods: In this study, we present a novel proteo-metabo-flux approach that combines mass spectrometry-based metabolic flux analysis of acetyl-CoA and histone acetylation with computational modelling. We developed a mathematical model to describe metabolic label incorporation into acetyl-CoA and histone acetylation based on experimentally measured relative abundances. Results: We demonstrate that our approach is able to determine acetyl-CoA synthesis dynamics and site-specific histone acetylation and deacetylation reaction rate constants, and that consideration of the metabolically labelled acetyl-CoA fraction is essential for accurate determination of histone acetylation dynamics. Furthermore, we show that without correction, changes in metabolic fluxes would be misinterpreted as changes in histone acetylation dynamics, whereas our proteo-metabo-flux approach allows to distinguish between the two processes. Conclusions: Our proteo-metabo-flux approach expands the repertoire of metabolic flux analysis and cross-omics and represents a valuable approach to study the regulatory interplay between metabolism and epigenetic regulation by histone acetylation.

Metabolic fluxes, the number of metabolites traversing each biochemical reaction in a cell per unit time, are crucial for assessing and understanding cell function. 13C Metabolic Flux Analysis (13C MFA) is considered to be the gold standard for measuring metabolic fluxes. 13C MFA typically works by leveraging extracellular exchange fluxes as well as data from 13C labeling experiments to calculate the flux profile which best fit the data for a small, central carbon, metabolic model. However, the nonlinear nature of the 13C MFA fitting procedure means that several flux profiles fit the experimental data within the experimental error, and traditional optimization methods offer only a partial or skewed picture, especially in "non-gaussian" situations where multiple very distinct flux regions fit the data equally well. Here, we present a method for flux space sampling through Bayesian inference (BayFlux), that identifies the full distribution of fluxes compatible with experimental data for a comprehensive genome-scale model. This Bayesian approach allows us to accurately quantify uncertainty in calculated fluxes. We also find that, surprisingly, the genome-scale model of metabolism produces narrower flux distributions (reduced uncertainty) than the small core metabolic models traditionally used in 13C MFA. The different results for some reactions when using genome-scale models vs core metabolic models advise caution in assuming strong inferences from 13C MFA since the results may depend significantly on the completeness of the model used. Based on BayFlux, we developed and evaluated novel methods (P-13C MOMA and P-13C ROOM) to predict the biological results of a gene knockout, that improve on the traditional MOMA and ROOM methods by quantifying prediction uncertainty.

Cellular senescence is a state of proliferative arrest, and the development of carcinoma can be suppressed by conferring tumor cell senescence. Recently, we found that carnitine palmitoyltransferase 1C (CPT1C) controls tumor cell proliferation and senescence via regulating lipid metabolism and mitochondrial function. Here, 13C-metabolic flux analysis (13C-MFA) was performed and the results revealed that CPT1C knockdown in MDA-MB-231 cells significantly induced cellular senescence accompanied by altered fatty acid metabolism. Strikingly, stearate synthesis was decreased while oleate was increased. Furthermore, stearate significantly inhibited proliferation while oleate reversed the senescent phenotype induced by silencing CPT1C in MDA-MB-231 cells as well as PANC-1 cells. A939572, an inhibitor of stearoyl-Coenzyme A desaturase 1, had the same effect as stearate to inhibit cellular proliferation. These results demonstrated that stearate and oleate are involved in CPT1C-mediated tumor cellular senescence, and the regulation of stearate/oleate rate via inhibition of SCD-1 could be an additional strategy with depletion of CPT1C for cancer therapy.

Once considered as a "metabolic waste," lactate is now recognized as a major fuel for tricarboxylic acid (TCA) cycle. Our metabolic flux analysis reveals that skeletal muscle mainly uses lactate to fuel TCA cycle. Lactate is transported through the cell membrane via monocarboxylate transporters (MCTs) in which MCT1 is highly expressed in the muscle. We analyzed how MCT1 affects muscle functions using mice with specific deletion of MCT1 in skeletal muscle. MCT1 deletion enhances running performance, increases oxidative fibers while decreasing glycolytic fibers, and enhances flux of glucose to TCA cycle. MCT1 deficiency increases the expression of mitochondrial proteins, augments cell respiration rate, and elevates mitochondrial activity in the muscle. Mechanistically, the protein level of PGC-1α, a master regulator of mitochondrial biogenesis, is elevated upon loss of MCT1 via increases in cellular NAD+ level and SIRT1 activity. Collectively, these results demonstrate that MCT1-mediated lactate shuttle plays a key role in regulating muscle functions by modulating mitochondrial biogenesis and TCA flux. [ABSTRACT FROM AUTHOR]

This article, titled "Mitochondrial Damage Induced by Excess Growth Hormone in Glomerular Podocytes: Implications in Diabetic Nephropathy," explores the role of growth hormone (GH) in podocyte injury and its connection to diabetic nephropathy. The study investigates the effects of GH on podocyte morphology and function using in vivo and in vitro models. The findings suggest that GH leads to enhanced intracellular calcium influx, altered mitochondrial dynamics, and decreased ATP production in podocytes. The authors propose that targeting mitochondrial damage could be a potential therapeutic approach to prevent diabetic nephropathy. [Extracted from the article]

Summary: Metabolic flux analysis (MFA) is a valuable tool for quantifying cellular phenotypes and to guide plant metabolic engineering. By introducing stable isotopic tracers and employing mathematical models, MFA can quantify the rates of metabolic reactions through biochemical pathways. Recent applications of isotopically nonstationary MFA (INST‐MFA) to plants have elucidated nonintuitive metabolism in leaves under optimal and stress conditions, described coupled fluxes for fast‐growing algae, and produced a synergistic multi‐organ flux map that is a first in MFA for any biological system. These insights could not be elucidated through other approaches and show the potential of INST‐MFA to correct an oversimplified understanding of plant metabolism. [ABSTRACT FROM AUTHOR]

Vitamin B6 plays a crucial role in cellular metabolism and stress response, making it an essential component for growth in all known organisms. However, achieving efficient biosynthesis of vitamin B6 faces the challenge of maintaining a balanced distribution of metabolic flux between growth and production. In this study, our focus is on addressing this challenge through the engineering of phosphoserine aminotransferase (SerC) to resolve its redundancy and promiscuity. The enzyme SerC was semi-designed and screened based on sequences and predicted kcat values, respectively. Mutants and heterologous proteins showing potential were then fine-tuned to optimize the production of vitamin B6. The resulting strain enhances the production of vitamin B6, indicating that different fluxes are distributed to the biosynthesis pathway of serine and vitamin B6. This study presents a promising strategy to address the challenge posed by multifunctional enzymes, with significant implications for enhancing biochemical production through engineering processes. [ABSTRACT FROM AUTHOR]

Diabetes and obesity are risk factors for kidney disease. Whereas renal glucose production increases in diabetes, recent data suggest that gluconeogenic and oxidative capacity decline in kidney disease. Thus, metabolic dysregulation caused by diet-induced insulin resistance may sensitize the kidney for a loss in function. Here, we examined how diet-induced insulin resistance disrupts mitochondrial metabolic fluxes in the renal cortex in vivo. C57BL/6J mice were rendered insulin resistant through high-fat (HF) feeding; anaplerotic, cataplerotic, and oxidative metabolic fluxes in the cortex were quantified through 13C-isotope tracing during a hyperinsulinemic-euglycemic clamp. As expected, HF-fed mice exhibited increased body weight, gluconeogenesis, and systemic insulin resistance compared with chow-fed mice. Relative to the citric acid cycle, HF feeding increased metabolic flux through pyruvate carboxylation (anaplerosis) and phosphoenolpyruvate carboxykinase (cataplerosis) and decreased flux through the pyruvate dehydrogenase complex in the cortex. Furthermore, the relative flux from nonpyruvate sources of acetyl-CoA profoundly increased in the cortex of HF-fed mice, correlating with a marker of oxidative stress. The data demonstrate that HF feeding spares pyruvate from dehydrogenation at the expense of increasing cataplerosis, which may underpin renal gluconeogenesis during insulin resistance; the results also support the hypothesis that dysregulated oxidative metabolism in the kidney contributes to metabolic disease. Article Highlights: Diabetes and obesity are risk factors for kidney disease, yet the impact of diet-induced insulin resistance on renal metabolism is incompletely characterized. In vivo metabolic flux analysis of the renal cortex was performed in mice fed chow or high-fat diet that underwent a hyperinsulinemic-euglycemic clamp. In diet-induced insulin resistance, increased acetyl-CoA flux was derived from nonpyruvate substrates; this switch coincided with increased anaplerosis and accumulation of peroxidized lipid products in the renal cortex. The dysregulation in renal metabolic fluxes observed in diet-induced insulin resistance may instigate oxidative stress that sensitizes the kidney to injury. [ABSTRACT FROM AUTHOR]

Metabolic reprogramming is critical in the onset of pressure overload-induced cardiac remodeling. Our study reveals that proline dehydrogenase (PRODH), the key enzyme in proline metabolism, reprograms cardiomyocyte metabolism to protect against cardiac remodeling. We induced cardiac remodeling using transverse aortic constriction (TAC) in both cardiac-specific PRODH knockout and overexpression mice. Our results indicate that PRODH expression is suppressed after TAC. Cardiac-specific PRODH knockout mice exhibited worsened cardiac dysfunction, while mice with PRODH overexpression demonstrated a protective effect. In addition, we simulated cardiomyocyte hypertrophy in vitro using neonatal rat ventricular myocytes treated with phenylephrine. Through RNA sequencing, metabolomics, and metabolic flux analysis, we elucidated that PRODH overexpression in cardiomyocytes redirects proline catabolism to replenish tricarboxylic acid cycle intermediates, enhance energy production, and restore glutathione redox balance. Our findings suggest PRODH as a modulator of cardiac bioenergetics and redox homeostasis during cardiac remodeling induced by pressure overload. This highlights the potential of PRODH as a therapeutic target for cardiac remodeling. [ABSTRACT FROM AUTHOR]

Metabolic reaction rates (fluxes) play a crucial role in comprehending cellular phenotypes and are essential in areas such as metabolic engineering, biotechnology, and biomedical research. The state-of-the-art technique for estimating fluxes is metabolic flux analysis using isotopic labelling (13C-MFA), which uses a dataset-model combination to determine the fluxes. Bayesian statistical methods are gaining popularity in the field of life sciences, but the use of 13C-MFA is still dominated by conventional best-fit approaches. The slow take-up of Bayesian approaches is, at least partly, due to the unfamiliarity of Bayesian methods to metabolic engineering researchers. To address this unfamiliarity, we here outline similarities and differences between the two approaches and highlight particular advantages of the Bayesian way of flux analysis. With a real-life example, re-analysing a moderately informative labelling dataset of E. coli, we identify situations in which Bayesian methods are advantageous and more informative, pointing to potential pitfalls of current 13C-MFA evaluation approaches. We propose the use of Bayesian model averaging (BMA) for flux inference as a means of overcoming the problem of model uncertainty through its tendency to assign low probabilities to both, models that are unsupported by data, and models that are overly complex. In this capacity, BMA resembles a tempered Ockham's razor. With the tempered razor as a guide, BMA-based 13C-MFA alleviates the problem of model selection uncertainty and is thereby capable of becoming a game changer for metabolic engineering by uncovering new insights and inspiring novel approaches. • Bayesian tools extend flux estimation capabilities of 13C-Metabolic Flux Analysis. • Data and model selection uncertainty are unified in the Bayesian framework. • Multi-model flux inference is robust, in contrast to single-model inference. • Bayesian Model Averaging resembles a tempered Ockham's razor. • Modelling of bidirectional steps becomes statistically testable. [ABSTRACT FROM AUTHOR]

Lignin is an abundant phenolic polymer present in plant cell walls that aids water transport and plays crucial roles in protecting plants from environmental stresses. There is a growing interest in lignin as a potential source of sustainable bioproducts, including bioplastics, chemicals, carbon materials, and biofuels. The aim of modeling lignin metabolism is to predict the dynamics of lignin synthesis to facilitate plant genetic engineering strategies and ultimately improved lignin utilization. Recurring challenges associated with this goal are the lack of an integrated understanding of the lignin biosynthetic network and acquiring reliable metabolic data with cellular and subcellular resolution. While genome-scale metabolic models have been developed in microbial systems, their use in plants remains challenging due to their compartmentalized metabolism and cross-communication between organelles. Plant biomass contains lignin that can be converted into high-value-added chemicals, fuels, and materials. The precise genetic manipulation of lignin content and composition in plant cells offers substantial environmental and economic benefits. However, the intricate regulatory mechanisms governing lignin formation challenge the development of crops with specific lignin profiles. Mathematical models and computational simulations have recently been employed to gain fundamental understanding of the metabolism of lignin and related phenolic compounds. This review article discusses the strategies used for modeling plant metabolic networks, focusing on the application of mathematical modeling for flux network analysis in monolignol biosynthesis. Furthermore, we highlight how current challenges might be overcome to optimize the use of metabolic modeling approaches for developing lignin-engineered plants. [ABSTRACT FROM AUTHOR]

Hyperpolarized carbon‐13 labeled compounds are increasingly being used in medical MR imaging (MRI) and MR imaging (MRI) and spectroscopy (MRS) research, due to its ability to monitor tissue and cell metabolism in real‐time. Although radiological biomarkers are increasingly being considered as clinical indicators, biopsies are still considered the gold standard for a large variety of indications. Bioreactor systems can play an important role in biopsy examinations because of their ability to provide a physiochemical environment that is conducive for therapeutic response monitoring ex vivo. We demonstrate here a proof‐of‐concept bioreactor and microcoil receive array setup that allows for ex vivo preservation and metabolic NMR spectroscopy on up to three biopsy samples simultaneously, creating an easy‐to‐use and robust way to simultaneously run multisample carbon‐13 hyperpolarization experiments. Experiments using hyperpolarized [1‐13C]pyruvate on ML‐1 leukemic cells in the bioreactor setup were performed and the kinetic pyruvate‐to‐lactate rate constants (kPL) extracted. The coefficient of variation of the experimentally found kPLs for five repeated experiments was CV=35%. With this statistical power, treatment effects of 30%–40% change in lactate production could be easily differentiable with only a few hyperpolarization dissolutions on this setup. Furthermore, longitudinal experiments showed preservation of ML‐1 cells in the bioreactor setup for at least 6 h. Rat brain tissue slices were also seen to be preserved within the bioreactor for at least 1 h. This validation serves as the basis for further optimization and upscaling of the setup, which undoubtedly has huge potential in high‐throughput studies with various biomarkers and tissue types. [ABSTRACT FROM AUTHOR]

Metabolic pathways are plastic and rapidly change in response to stress or perturbation. Current metabolic profiling techniques require lysis of many cells, complicating the tracking of metabolic changes over time after stress in rare cells such as hematopoietic stem cells (HSCs). Here, we aimed to identify the key metabolic enzymes that define differences in glycolytic metabolism between steady- state and stress conditions in murine HSCs and elucidate their regulatory mechanisms. Through quantitative 13C metabolic flux analysis of glucose metabolism using high- sensitivity glucose tracing and mathematical modeling, we found that HSCs activate the glycolytic rate- limiting enzyme phosphofructokinase (PFK) during proliferation and oxidative phosphorylation (OXPHOS) inhibition. Real- time measurement of ATP levels in single HSCs demonstrated that proliferative stress or OXPHOS inhibition led to accelerated glycolysis via increased activity of PFKFB3, the enzyme regulating an allosteric PFK activator, within seconds to meet ATP requirements. Furthermore, varying stresses differentially activated PFKFB3 via PRMT1- dependent methylation during proliferative stress and via AMPK- dependent phosphorylation during OXPHOS inhibition. Overexpression of Pfkfb3 induced HSC proliferation and promoted differentiated cell production, whereas inhibition or loss of Pfkfb3 suppressed them. This study reveals the flexible and multilayered regulation of HSC glycolytic metabolism to sustain hematopoiesis under stress and provides techniques to better understand the physiological metabolism of rare hematopoietic cells. [ABSTRACT FROM AUTHOR]

Exercise robustly increases the glucose demands of skeletal muscle. This demand is met by not only muscle glycogenolysis but also accelerated liver glucose production from hepatic glycogenolysis and gluconeogenesis to fuel mechanical work and prevent hypoglycemia during exercise. Hepatic gluconeogenesis during exercise is dependent on highly coordinated responses within and between muscle and liver. Specifically, exercise increases the rate at which gluconeogenic precursors such as pyruvate/lactate or amino acids are delivered from muscle to the liver, extracted by the liver, and channeled into glucose. Herein, we examined the effects of interrupting hepatic gluconeogenic efficiency and capacity on exercise performance by deleting mitochondrial pyruvate carrier 2 (MPC2) and/or alanine transaminase 2 (ALT2) in the liver of mice. We found that deletion of MPC2 or ALT2 alone did not significantly affect time to exhaustion or postexercise glucose concentrations in treadmill exercise tests, but mice lacking both MPC2 and ALT2 in hepatocytes (double knockout, DKO) reached exhaustion faster and exhibited lower circulating glucose during and after exercise. Use of 2H/13C metabolic flux analyses demonstrated that DKO mice exhibited lower endogenous glucose production owing to decreased glycogenolysis and gluconeogenesis at rest and during exercise. Decreased gluconeogenesis was accompanied by lower anaplerotic, cataplerotic, and TCA cycle fluxes. Collectively, these findings demonstrate that the transition of the liver to the gluconeogenic mode is critical for preventing hypoglycemia and sustaining performance during exercise. The results also illustrate the need for interorgan cross talk during exercise as described by the Cahill and Cori cycles. NEW & NOTEWORTHY Martino and colleagues examined the effects of inhibiting hepatic gluconeogenesis on exercise performance and systemic metabolism during treadmill exercise in mice. Combined inhibition of gluconeogenesis from lactate/pyruvate and alanine impaired exercise endurance and led to hypoglycemia during and after exercise. In contrast, suppressing either pyruvate-mediated or alanine-mediated gluconeogenesis alone had no effect on these parameters. These findings provide new insight into the molecular nodes that coordinate the metabolic responses of muscle and liver during exercise. [ABSTRACT FROM AUTHOR]

Due to their high specificity, monoclonal antibodies (mAbs) have garnered significant attention in recent decades, with advancements in production processes, such as high-seeding-density (HSD) strategies, contributing to improved titers. This study provides a thorough investigation of high seeding processes for mAb production in Chinese hamster ovary (CHO) cells, focused on identifying significant metabolites and their interactions. We observed high glycolytic fluxes, the depletion of asparagine, and a shift from lactate production to consumption. Using a metabolic network and flux analysis, we compared the standard fed-batch (STD FB) with HSD cultivations, exploring supplementary lactate and cysteine, and a bolus medium enriched with amino acids. We reconstructed a metabolic network and kinetic models based on the observations and explored the effects of different feeding strategies on CHO cell metabolism. Our findings revealed that the addition of a bolus medium (BM) containing asparagine improved final titers. However, increasing the asparagine concentration in the feed further prevented the lactate shift, indicating a need to find a balance between increased asparagine to counteract limitations and lower asparagine to preserve the shift in lactate metabolism. [ABSTRACT FROM AUTHOR]

Flux balance analysis (FBA) is an optimization based approach to find the optimal steady state of a metabolic network, commonly of microorganisms such as yeast strains and Escherichia coli. However, the resulting solution from an FBA is typically not unique, as the optimization problem is, more often than not, degenerate. Flux variability analysis (FVA) is a method to determine the range of possible reaction fluxes that still satisfy, within some optimality factor, the original FBA problem. The resulting range of reaction fluxes can be utilized to determine metabolic reactions of high importance, amongst other analyses. In the literature, this has been done by solving [Formula: see text] linear programs (LPs), with n being the number of reactions in the metabolic network. However, FVA can be solved with less than [Formula: see text] LPs by utilizing the basic feasible solution property of bounded LPs to reduce the number of LPs that are needed to be solved. In this work, a new algorithm is proposed to solve FVA that requires less than [Formula: see text] LPs. The proposed algorithm is benchmarked on a problem set of 112 metabolic network models ranging from single cell organisms (iMM904, ect) to a human metabolic system (Recon3D). Showing a reduction in the number of LPs required to solve the FVA problem and thus the time to solve an FVA problem.

Introduction: Desulfovibrio vulgaris Hildenborough is a gram-negative anaerobic bacterium belonging to the sulfate-reducing bacteria that exhibits highly versatile metabolism. By switching from one energy mode to another depending on nutrients availability in the environments„ it plays a central role in shaping ecosystems. Despite intensive efforts to study D. vulgaris energy metabolism at the genomic, biochemical and ecological level, bioenergetics in this microorganism remain far from being fully understood. Alternatively, metabolic modeling is a powerful tool to understand bioenergetics. However, all the current models for D. vulgaris appeared to be not easily adaptable to various environmental conditions. Methods: To lift off these limitations, here we constructed a novel transparent and robust metabolic model to explain D. vulgaris bioenergetics by combining whole-cell proteomic analysis with modeling approaches (Flux Balance Analysis). Results: The iDvu71 model showed over 0.95 correlation with experimental data. Further simulations allowed a detailed description of D. vulgaris metabolism in various conditions of growth. Altogether, the simulations run in this study highlighted the sulfate-to-lactate consumption ratio as a pivotal factor in D. vulgaris energy metabolism. Discussion: In particular, the impact on the hydrogen/formate balance and biomass synthesis is discussed. Overall, this study provides a novel insight into D. vulgaris metabolic flexibility. [ABSTRACT FROM AUTHOR]

Metabolic fluxes and their control mechanisms are fundamental in cellular metabolism, offering insights for the study of biological systems and biotechnological applications. However, quantitative and predictive understanding of controlling biochemical reactions in microbial cell factories, especially at the system level, is limited. In this work, we present ARCTICA, a computational framework that integrates constraint-based modelling with machine learning tools to address this challenge. Using the model cyanobacterium Synechocystis sp. PCC 6803 as chassis, we demonstrate that ARCTICA effectively simulates global-scale metabolic flux control. Key findings are that (i) the photosynthetic bioproduction is mainly governed by enzymes within the Calvin–Benson–Bassham (CBB) cycle, rather than by those involve in the biosynthesis of the end-product, (ii) the catalytic capacity of the CBB cycle limits the photosynthetic activity and downstream pathways and (iii) ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is a major, but not the most, limiting step within the CBB cycle. Predicted metabolic reactions qualitatively align with prior experimental observations, validating our modelling approach. ARCTICA serves as a valuable pipeline for understanding cellular physiology and predicting rate-limiting steps in genome-scale metabolic networks, and thus provides guidance for bioengineering of cyanobacteria. • A workflow for metabolic flux control analysis in Synechocystis sp. PCC 6803. • Machine learning with features derived from genome-scale metabolic modelling. • Identification of potential key reactions for metabolic adaptations and cell bioengineering. [ABSTRACT FROM AUTHOR]

Evidence indicates that metabolic reprogramming characterized by the changes in cellular metabolic patterns contributes to the pathogenesis of pulmonary fibrosis (PF). It is considered as a promising therapeutic target anti-PF. The well-documented against PF properties of Tanshinone IIA (Tan IIA) have been primarily attributed to its antioxidant and anti-inflammatory potency. Emerging evidence suggests that Tan IIA may target energy metabolism pathways, including glycolysis and tricarboxylic acid (TCA) cycle. However, the detailed and advanced mechanisms underlying the anti-PF activities remain obscure. In this study, we applied [U-13C]-glucose metabolic flux analysis (MFA) to examine metabolism flux disruption and modulation nodes of Tan IIA in PF. We identified that Tan IIA inhibited the glycolysis and TCA flux, thereby suppressing the production of transforming growth factor-β1 (TGF-β1)-dependent extracellular matrix and the differentiation and proliferation of myofibroblasts in vitro. We further revealed that Tan IIA inhibited the expression of key metabolic enzyme hexokinase 2 (HK2) by inhibiting phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR)/hypoxia-inducible factor 1α (HIF-1α) pathway activities, which decreased the accumulation of abnormal metabolites. Notably, we demonstrated that Tan IIA inhibited ATP citrate lyase (ACLY) activity, which reduced the collagen synthesis pathway caused by cytosol citrate consumption. Further, these results were validated in a mouse model of bleomycin-induced PF. This study was novel in exploring the mechanism of the occurrence and development of Tan IIA in treating PF using 13C-MFA technology. It provided a novel understanding of the mechanism of Tan IIA against PF from the perspective of metabolic reprogramming. [Display omitted] • Dysregulation of glycolysis and TCA cycle metabolic flux in PF. • Tan IIA improved PF by inhibiting energy metabolism flux. • Tan IIA inhibited collagen synthesis by inhibiting cytosol citrate consumption. [ABSTRACT FROM AUTHOR]

This study examined the effect of conductive materials (softwood pellet biochar pyrolyzed at 550 °C and 700 °C , powdered activated carbon and stainless-steel) on the two series of batch biohydrogen production inoculated with three types of heated-treated anaerobic digester sludge. Biochar pyrolyzed at 550 °C and stainless-steel exhibited the highest enhanced hydrogen yield up to 117 % in the first and second series of experiments, respectively. Importantly, the enhancement effect by the introduction of conductive materials was significantly affected by the microbial population in inoculum, particularly the relative abundance of electroactive H 2 -producing Clostridium sp. Metabolic flux analysis revealed that the enhanced H 2 yield was concurrent with the decrease of lactate production and the increase of H 2 -producing acetogenesis. Conductive materials also improved electron transport system activity and NADH/NAD+ ratio, which are related with the metabolic activity. This study shows that introducing conductive material can control intracellular redox environment, thereby reinforcing the metabolic activity selectively. [Display omitted] • Effect of conductive matter depends on the inoculum electroactive microbe abundance. • Biochar pyrolyzed at 550 °C and stainless-steel raise H 2 yield up to 117.6 %. • Conductive materials increase metabolic activity as well as H 2 yield. • Redox-active groups and conductivity increases microbial electroactivity. [ABSTRACT FROM AUTHOR]

Chromochloris zofingiensis is a potential source of natural astaxanthin; however, its rapid growth and astaxanthin enrichment cannot be achieved simultaneously. This study established autotrophic, mixotrophic, and heterotrophic preculture patterns to assess their ameliorative effect on the C. zofingiensis heterotrophic growth state. In comparison, mixotrophic preculture (MP) exhibited the best improving effect on heterotrophic biomass concentration of C. zofingiensis (up to 121.5 g L−1) in a 20 L fermenter, reaching the global leading level. The astaxanthin productivity achieved 111 mg L−1 day−1, 7.4-fold higher than the best record. The transcriptome and 13C tracer-based metabolic flux analysis were used for mechanism inquiry. The results revealed that MP promoted carotenoid and lipid synthesis, and supported synthesis preference of low unsaturated fatty acids represented by C18:1 and C16:0. The MP group maintained the best astaxanthin productivity via mastering the balance between increasing glucose metabolism and inhibition of carotenoid synthesis. The MP strategy optimized the physiological state of C. zofingiensis and realized its heterotrophic high-density growth for an excellent astaxanthin yield on a pilot scale. This strategy exhibits great application potential in the microalgae-related industry. Key points: • Preculture strategies changed carbon flux and gene expression in C. zofingiensis • C. zofingiensis realized a high-density culture with MP and fed-batch culture (FBC) • Astaxanthin productivity achieved 0.111 g L−1day−1with MP and FBC [ABSTRACT FROM AUTHOR]

Regular exercise elicits adaptations in glucose and lipid metabolism that allow the body to meet energy demands of subsequent exercise bouts more effectively and mitigate metabolic diseases including fatty liver. Energy discharged during the acute exercise bouts that comprise exercise training may be a catalyst for liver adaptations. During acute exercise, liver glycogenolysis and gluconeogenesis are accelerated to supply glucose to working muscle. Lower liver energy state imposed by gluconeogenesis and related pathways activates AMP-activated protein kinase (AMPK), which conserves ATP partly by promoting lipid oxidation. This study tested the hypothesis that AMPK is necessary for liver glucose and lipid adaptations to training. Liver-specific AMPKα1α2 knockout (AMPKα1α2fl/fl+AlbCre) mice and littermate controls (AMPKα1α2fl/fl) completed sedentary and exercise training protocols. Liver nutrient fluxes were quantified at rest or during acute exercise following training. Liver metabolites and molecular regulators of metabolism were assessed. Training increased liver glycogen in AMPKα1α2fl/fl mice, but not in AMPKα1α2fl/fl+AlbCre mice. The inability to increase glycogen led to lower glycogenolysis, glucose production, and circulating glucose during acute exercise in trained AMPKα1α2fl/fl+AlbCre mice. Deletion of AMPKα1α2 attenuated training-induced declines in liver diacylglycerides. In particular, training lowered the concentration of unsaturated and elongated fatty acids comprising diacylglycerides in AMPKα1α2fl/fl mice, but not in AMPKα1α2fl/fl+AlbCre mice. Training increased liver triacylglycerides and the desaturation and elongation of fatty acids in triacylglycerides of AMPKα1α2fl/fl+AlbCre mice. These lipid responses were independent of differences in tricarboxylic acid cycle fluxes. In conclusion, AMPK is required for liver training adaptations that are critical to glucose and lipid metabolism. NEW & NOTEWORTHY: This study shows that the energy sensor and transducer, AMP-activated protein kinase (AMPK), is necessary for an exercise training-induced: 1) increase in liver glycogen that is necessary for accelerated glycogenolysis during exercise, 2) decrease in liver glycerolipids independent of tricarboxylic acid (TCA) cycle flux, and 3) decline in the desaturation and elongation of fatty acids comprising liver diacylglycerides. The mechanisms defined in these studies have implications for use of regular exercise or AMPK-activators in patients with fatty liver. [ABSTRACT FROM AUTHOR]

Plasma nucleosides-pseudouridine (PU) and N²N²-dimethyl guanosine (DMG) predict the progression of type 2 diabetic kidney disease (DKD) to end-stage renal disease, but the mechanisms underlying this relationship are not well understood. We used a well-characterized model of type 2 diabetes (db/db mice) and control nondiabetic mice (db/m mice) to characterize the production and excretion of PU and DMG levels using liquid chromatography-mass spectrometry. The fractional excretion of PU and DMG was decreased in db/db mice compared with control mice at 24 wk before any changes to renal function. We then examined the dynamic changes in nucleoside metabolism using in vivo metabolic flux analysis with the injection of labeled nucleoside precursors. Metabolic flux analysis revealed significant decreases in the ratio of urine-to-plasma labeling of PU and DMG in db/db mice compared with db/m mice, indicating significant tubular dysfunction in diabetic kidney disease. We observed that the gene and protein expression of the renal tubular transporters involved with nucleoside transport in diabetic kidneys in mice and humans was reduced. In conclusion, this study strongly suggests that tubular handling of nucleosides is altered in early DKD, in part explaining the association of PU and DMG with human DKD progression observed in previous studies. [ABSTRACT FROM AUTHOR]

13C‐Metabolic Flux Analysis (13C‐MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both methods use metabolic reaction network models of metabolism operating at steady state so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. These fluxes can shed light on basic biology and have been successfully used to inform metabolic engineering strategies. Several approaches have been taken to test the reliability of estimates and predictions from constraint‐based methods and to compare alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, such as the quantification of flux estimate uncertainty, validation and model selection methods have been underappreciated and underexplored. We review the history and state‐of‐the‐art in constraint‐based metabolic model validation and model selection. Applications and limitations of the χ2‐test of goodness‐of‐fit, the most widely used quantitative validation and selection approach in 13C‐MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C‐MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how adopting robust validation and selection procedures can enhance confidence in constraint‐based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology. [ABSTRACT FROM AUTHOR]

ε-Poly-L-lysine (ε-PL) is a natural and safe food preservative mainly produced by the aerobic, filamentous bacterium Streptomyces albulus. Therefore, it is crucial to breed superior ε-PL-producing strains to enhance fermentation efficiency to reduce production costs. Metabolic engineering is an effective measure for strain modification, but there are few reports on key genes for ε-PL biosynthesis. In this study, metabolic flux analysis was employed to identify potential key genes in ε-PL biosynthesis in S. albulus WG-608. A total of six potential key genes were identified. Three effective key genes (ppc, pyc and pls) were identified for the first time in ε-PL biosynthesis through overexpression experiments. It also presents the first demonstration of the promoting effects of ppc and pyc on ε-PL biosynthesis. Three genes were then co-expressed in S. albulus WG-608 to obtain OE-ppc-pyc-pls, which exhibited an 11.4% increase in ε-PL production compared to S. albulus WG-608, with a 25.5% increase in specific ε-PL production. Finally, the metabolic flux analysis of OE-ppc-pyc-pls compared to S. albulus WG-608 demonstrated that OE-ppc-pyc-pls successfully altered the metabolic flux as expected. This study not only provides a theoretical basis for the metabolic engineering of ε-PL-producing strains but also provides an effective approach for the metabolic engineering of other metabolites. [ABSTRACT FROM AUTHOR]

Summary: Environmental enteric dysfunction (EED) is a subclinical enteropathy challenging to diagnose due to an overlap of tissue features with other inflammatory enteropathies. EED subjects (n = 52) from Pakistan, controls (n = 25), and a validation EED cohort (n = 30) from Zambia were used to develop a machine-learning-based image analysis classification model. We extracted histologic feature representations from the Pakistan EED model and correlated them to transcriptomics and clinical biomarkers. In-silico metabolic network modeling was used to characterize alterations in metabolic flux between EED and controls and validated using untargeted lipidomics. Genes encoding beta-ureidopropionase, CYP4F3, and epoxide hydrolase 1 correlated to numerous tissue feature representations. Fatty acid and glycerophospholipid metabolism-related reactions showed altered flux. Increased phosphatidylcholine, lysophosphatidylcholine (LPC), and ether-linked LPCs, and decreased ester-linked LPCs were observed in the duodenal lipidome of Pakistan EED subjects, while plasma levels of glycine-conjugated bile acids were significantly increased. Together, these findings elucidate a multi-omic signature of EED.

Human Embryonic Kidney cells (HEK293) are a popular host for recombinant protein expression and production in the biotechnological industry. This has driven within both, the scientific and the engineering communities, the search for strategies to increase their protein productivity. The present work is inserted into this search exploring the impact of adding sodium acetate (NaAc) into a batch culture of HEK293 cells. We monitored, as a function of time, the cell density, many external metabolites, and the supernatant concentration of the heterologous extra-cellular domain ECD-Her1 protein, a protein used to produce a candidate prostate cancer vaccine. We observed that by adding different concentrations of NaAc (0, 4, 6 and 8 mM), the production of ECD-Her1 protein increases consistently with increasing concentration, whereas the carrying capacity of the medium decreases. To understand these results we exploited a combination of experimental and computational techniques. Metabolic Flux Analysis (MFA) was used to infer intracellular metabolic fluxes from the concentration of external metabolites. Moreover, we measured independently the extracellular acidification rate and oxygen consumption rate of the cells. Both approaches support the idea that the addition of NaAc to the culture has a significant impact on the metabolism of the HEK293 cells and that, if properly tuned, enhances the productivity of the heterologous ECD-Her1 protein.

Complete understanding of a biological system requires quantitation of metabolic fluxes that reflect its dynamic state. Various analytical chemistry tools, enzyme-based probes, and microscopy enable flux measurement. However, any method alone falls short of comprehensive flux quantitation. Here we show that integrating these techniques results in a systems-level quantitative map of absolute metabolic fluxes that constitute an indispensable dimension of characterizing phenotypes. Stable isotopes, mass spectrometry, and NMR spectroscopy reveal relative pathway fluxes. Biochemical probes reveal the physical rate of environmental changes. FRET-based and SRS-based microscopy reveal targeted metabolite and chemical bond formation. These techniques are complementary and can be computationally integrated to reveal actionable information on metabolism. Integrative metabolic flux analysis using various quantitative techniques advances biotechnology and medicine.

Abstract Background Duckweeds are small, rapidly growing aquatic flowering plants. Due to their ability for biomass production at high rates they represent promising candidates for biofuel feedstocks. Duckweeds are also excellent model organisms because they can be maintained in well-defined liquid media, usually reproduce asexually, and because genomic resources are becoming increasingly available. To demonstrate the utility of duckweed for integrated metabolic studies, we examined the metabolic adaptation of growing Lemna gibba cultures to different nutritional conditions. Results To establish a framework for quantitative metabolic research in duckweeds we derived a central carbon metabolism network model of Lemna gibba based on its draft genome. Lemna gibba fronds were grown with nitrate or glutamine as nitrogen source. The two conditions were compared by quantification of growth kinetics, metabolite levels, transcript abundance, as well as by 13C-metabolic flux analysis. While growing with glutamine, the fronds grew 1.4 times faster and accumulated more protein and less cell wall components compared to plants grown on nitrate. Characterization of photomixotrophic growth by 13C-metabolic flux analysis showed that, under both metabolic growth conditions, the Calvin-Benson-Bassham cycle and the oxidative pentose-phosphate pathway are highly active, creating a futile cycle with net ATP consumption. Depending on the nitrogen source, substantial reorganization of fluxes around the tricarboxylic acid cycle took place, leading to differential formation of the biosynthetic precursors of the Asp and Gln families of proteinogenic amino acids. Despite the substantial reorganization of fluxes around the tricarboxylic acid cycle, flux changes could largely not be associated with changes in transcripts. Conclusions Through integrated analysis of growth rate, biomass composition, metabolite levels, and metabolic flux, we show that Lemna gibba is an excellent system for quantitative metabolic studies in plants. Our study showed that Lemna gibba adjusts to different nitrogen sources by reorganizing central metabolism. The observed disconnect between gene expression regulation and metabolism underscores the importance of metabolic flux analysis as a tool in such studies.