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

Mounting evidence suggests metabolism instructs stem cell fate decisions. However, how fetal metabolism changes during development and how altered maternal metabolism shapes fetal metabolism remain unexplored. We present a descriptive atlas of in vivo fetal murine metabolism during mid-to-late gestation in normal and diabetic pregnancy. Using 13C-glucose and liquid chromatography-mass spectrometry (LC-MS), we profiled the metabolism of fetal brains, hearts, livers, and placentas harvested from pregnant dams between embryonic days (E)10.5 and 18.5. Our analysis revealed metabolic features specific to a hyperglycemic environment and signatures that may denote developmental transitions during euglycemic development. We observed sorbitol accumulation in fetal tissues and altered neurotransmitter levels in fetal brains isolated from hyperglycemic dams. Tracing 13C-glucose revealed disparate fetal nutrient sourcing depending on maternal glycemic states. Regardless of glycemic state, histidine-derived metabolites accumulated in late-stage fetal tissues. Our rich dataset presents a comprehensive overview of in vivo fetal tissue metabolism and alterations due to maternal hyperglycemia.

A parallel glycolysis provides a selective advantage through rapid growth acceleration.

Glycolysis is a universal metabolic process that breaks down glucose to produce adenosine triphosphate (ATP) and biomass precursors. The Entner-Doudoroff (ED) pathway is a glycolytic pathway that parallels textbook glycolysis but yields half as much ATP. Accordingly, in organisms that possess both glycolytic pathways (for example, Escherichia coli), its raison d'être remains a mystery. In this study, we found that the ED pathway provides a selective advantage during growth acceleration. Upon carbon and nitrogen upshifts, E. coli accelerates growth faster with than without the ED pathway. Concurrent isotope tracing reveals that the ED pathway flux increases faster than that of textbook glycolysis. We attribute the fast response time of the ED pathway to its strong thermodynamic driving force and streamlining of glucose import. Intermittent nutrient supply manifests the evolutionary advantage of the parallel glycolysis; thus, the dynamic nature of an ostensibly redundant pathway's role in promoting rapid adaptation constitutes a metabolic design principle.

Unexpected metabolic rewiring of CO2 fixation in H2-mediated materials-biology hybrids.

A hybrid approach combining water-splitting electrochemistry and H2-oxidizing, CO2-fixing microorganisms offers a viable solution for producing value-added chemicals from sunlight, water, and air. The classic wisdom without thorough examination to date assumes that the electrochemistry in such a H2-mediated process is innocent of altering microbial behavior. Here, we report unexpected metabolic rewiring induced by water-splitting electrochemistry in H2-oxidizing acetogenic bacterium Sporomusa ovata that challenges such a classic view. We found that the planktonic S. ovata is more efficient in utilizing reducing equivalent for ATP generation in the materials-biology hybrids than cells grown with H2 supply, supported by our metabolomic and proteomic studies. The efficiency of utilizing reducing equivalents and fixing CO2 into acetate has increased from less than 80% of chemoautotrophy to more than 95% under electroautotrophic conditions. These observations unravel previously underappreciated materials' impact on microbial metabolism in seemingly simply H2-mediated charge transfer between biotic and abiotic components. Such a deeper understanding of the materials-biology interface will foster advanced design of hybrid systems for sustainable chemical transformation.

Near-equilibrium glycolysis supports metabolic homeostasis and energy yield.

Glycolysis plays a central role in producing ATP and biomass. Its control principles, however, remain incompletely understood. Here, we develop a method that combines 2H and 13C tracers to determine glycolytic thermodynamics. Using this method, we show that, in conditions and organisms with relatively slow fluxes, multiple steps in glycolysis are near to equilibrium, reflecting spare enzyme capacity. In Escherichia coli, nitrogen or phosphorus upshift rapidly increases the thermodynamic driving force, deploying the spare enzyme capacity to increase flux. Similarly, respiration inhibition in mammalian cells rapidly increases both glycolytic flux and the thermodynamic driving force. The thermodynamic shift allows flux to increase with only small metabolite concentration changes. Finally, we find that the cellulose-degrading anaerobe Clostridium cellulolyticum exhibits slow, near-equilibrium glycolysis due to the use of pyrophosphate rather than ATP for fructose-bisphosphate production, resulting in enhanced per-glucose ATP yield. Thus, near-equilibrium steps of glycolysis promote both rapid flux adaptation and energy efficiency.

Malic enzyme tracers reveal hypoxia-induced switch in adipocyte NADPH pathway usage.

The critical cellular hydride donor NADPH is produced through various means, including the oxidative pentose phosphate pathway (oxPPP), folate metabolism and malic enzyme. In growing cells, it is efficient to produce NADPH via the oxPPP and folate metabolism, which also make nucleotide precursors. In nonproliferating adipocytes, a metabolic cycle involving malic enzyme holds the potential to make both NADPH and two-carbon units for fat synthesis. Recently developed deuterium ((2)H) tracer methods have enabled direct measurement of NADPH production by the oxPPP and folate metabolism. Here we enable tracking of NADPH production by malic enzyme with [2,2,3,3-(2)H]dimethyl-succinate and [4-(2)H]glucose. Using these tracers, we show that most NADPH in differentiating 3T3-L1 mouse adipocytes is made by malic enzyme. The associated metabolic cycle is disrupted by hypoxia, which switches the main adipocyte NADPH source to the oxPPP. Thus, (2)H-labeled tracers enable dissection of NADPH production routes across cell types and environmental conditions.

Metabolite concentrations, fluxes and free energies imply efficient enzyme usage.

In metabolism, available free energy is limited and must be divided across pathway steps to maintain a negative ΔG throughout. For each reaction, ΔG is log proportional both to a concentration ratio (reaction quotient to equilibrium constant) and to a flux ratio (backward to forward flux). Here we use isotope labeling to measure absolute metabolite concentrations and fluxes in Escherichia coli, yeast and a mammalian cell line. We then integrate this information to obtain a unified set of concentrations and ΔG for each organism. In glycolysis, we find that free energy is partitioned so as to mitigate unproductive backward fluxes associated with ΔG near zero. Across metabolism, we observe that absolute metabolite concentrations and ΔG are substantially conserved and that most substrate (but not inhibitor) concentrations exceed the associated enzyme binding site dissociation constant (Km or Ki). The observed conservation of metabolite concentrations is consistent with an evolutionary drive to utilize enzymes efficiently given thermodynamic and osmotic constraints.

Hierarchy in pentose sugar metabolism in Clostridium acetobutylicum.

Bacterial metabolism of polysaccharides from plant detritus into acids and solvents is an essential component of the terrestrial carbon cycle. Understanding the underlying metabolic pathways can also contribute to improved production of biofuels. Using a metabolomics approach involving liquid chromatography-mass spectrometry, we investigated the metabolism of mixtures of the cellulosic hexose sugar (glucose) and hemicellulosic pentose sugars (xylose and arabinose) in the anaerobic soil bacterium Clostridium acetobutylicum. Simultaneous feeding of stable isotope-labeled glucose and unlabeled xylose or arabinose revealed that,as expected, glucose was preferentially used as the carbon source. Assimilated pentose sugars accumulated in pentose phosphate pathway (PPP) intermediates with minimal flux into glycolysis. Simultaneous feeding of xylose and arabinose revealed an unexpected hierarchy among the pentose sugars, with arabinose utilized preferentially over xylose. The phosphoketolase pathway (PKP) provides an alternative route of pentose catabolism in C. acetobutylicum that directly converts xylulose-5-phosphate into acetyl-phosphate and glyceraldehyde-3-phosphate, bypassing most of the PPP. When feeding the mixture of pentose sugars, the labeling patterns of lower glycolytic intermediates indicated more flux through the PKP than through the PPP and upper glycolysis, and this was confirmed by quantitative flux modeling. Consistent with direct acetyl-phosphate production from the PKP, growth on the pentose mixture resulted in enhanced acetate excretion. Taken collectively, these findings reveal two hierarchies in clostridial pentose metabolism: xylose is subordinate to arabinose, and the PPP is used less than the PKP.

Extracellular domains of CARs reprogramme T cell metabolism without antigen stimulation.

Metabolism is an indispensable part of T cell proliferation, activation and exhaustion, yet the metabolism of chimeric antigen receptor (CAR)-T cells remains incompletely understood. CARs are composed of extracellular domains-often single-chain variable fragments (scFvs)-that determine ligand specificity and intracellular domains that trigger signalling following antigen binding. Here, we show that CARs differing only in the scFv variously reprogramme T cell metabolism. Even without exposure to antigens, some CARs increase proliferation and nutrient uptake in T cells. Using stable isotope tracers and mass spectrometry, we observed basal metabolic fluxes through glycolysis doubling and amino acid uptake overtaking anaplerosis in CAR-T cells harbouring a rituximab scFv, unlike other similar anti-CD20 scFvs. Disparate rituximab and 14G2a-based anti-GD2 CAR-T cells are similarly hypermetabolic and channel excess nutrients to nitrogen overflow metabolism. Modest overflow metabolism of CAR-T cells and metabolic compatibility between cancer cells and CAR-T cells are identified as features of efficacious CAR-T cell therapy.

Neutrophil diversity is associated with T-cell immunity and clinical relevance in patients with thyroid cancer.

Neutrophil heterogeneity is involved in autoimmune diseases, sepsis, and several cancers. However, the link between neutrophil heterogeneity and T-cell immunity in thyroid cancer is incompletely understood. We investigated the circulating neutrophil heterogeneity in 3 undifferentiated thyroid cancer (UTC), 14 differentiated thyroid cancer (DTC) (4 Stage IV, 10 Stage I-II), and healthy controls (n = 10) by transcriptomic data and cytometry. Participants with UTC had a significantly higher proportion of immature high-density neutrophils (HDN) and lower proportion of mature HDN in peripheral blood compared to DTC. The proportion of circulating PD-L1+ immature neutrophils were significantly increased in advanced cancer patients. Unsupervised analysis of transcriptomics data from circulating HDN revealed downregulation of innate immune response and T-cell receptor signaling pathway in cancer patients. Moreover, UTC patients revealed the upregulation of glycolytic process and glutamate receptor signaling pathway. Comparative analysis across tumor types and stages revealed the downregulation of various T-cell-related pathways, such as T-cell receptor signaling pathway and T-cell proliferation in advanced cancer patients. Moreover, the proportions of CD8+ and CD4+ T effector memory CD45RA+ (TEMRA) cells from peripheral blood were significantly decreased in UTC patients compared to DTC patients. Finally, we demonstrated that proportions of tumor-infiltrated neutrophils were increased and related with poor prognosis in advanced thyroid cancer using data from our RNA-seq and TCGA (The Cancer Genome Atlas) data. In conclusion, observed prevalence of circulating immature high-density neutrophils and their immunosuppressive features in undifferentiated thyroid cancers underscore the importance of understanding neutrophil dynamics in the context of tumor progression in thyroid cancer.

Transcriptomic characteristics according to tumor size and SUVmax in papillary thyroid cancer patients.

The SUVmax is a measure of FDG uptake and is related with tumor aggressiveness in thyroid cancer, however, its association with molecular pathways is unclear. Here, we investigated the relationship between SUVmax and gene expression profiles in 80 papillary thyroid cancer (PTC) patients. We conducted an analysis of DEGs and enriched pathways in relation to SUVmax and tumor size. SUVmax showed a positive correlation with tumor size and correlated with glucose metabolic process. The genes that indicate thyroid differentiation, such as SLC5A5 and TPO, were negatively correlated with SUVmax. Unsupervised analysis revealed that SUVmax positively correlated with DNA replication(r = 0.29, p = 0.009), pyrimidine metabolism(r = 0.50, p < 0.0001) and purine metabolism (r = 0.42, p = 0.0001). Based on subgroups analysis, we identified that PSG5, TFF3, SOX2, SL5A5, SLC5A7, HOXD10, FER1L6, and IFNA1 genes were found to be significantly associated with tumor aggressiveness. Both high SUVmax PTMC and macro-PTC are enriched in pathways of DNA replication and cell cycle, however, gene sets for purine metabolic pathways are enriched only in high SUVmax macro-PTC but not in high SUVmax PTMC. Our findings demonstrate the molecular characteristics of high SUVmax tumor and metabolism involved in tumor growth in differentiated thyroid cancer.

Unraveling the role of the mitochondrial one-carbon pathway in undifferentiated thyroid cancer by multi-omics analyses.

The role of the serine/glycine metabolic pathway (SGP) has recently been demonstrated in tumors; however, the pathological relevance of the SGP in thyroid cancer remains unexplored. Here, we perform metabolomic profiling of 17 tumor-normal pairs; bulk transcriptomics of 263 normal thyroid, 348 papillary, and 21 undifferentiated thyroid cancer samples; and single-cell transcriptomes from 15 cases, showing the impact of mitochondrial one-carbon metabolism in thyroid tumors. High expression of serine hydroxymethyltransferase-2 (SHMT2) and methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is associated with low thyroid differentiation scores and poor clinical features. A subpopulation of tumor cells with high mitochondrial one-carbon pathway activity is observed in the single-cell dataset. SHMT2 inhibition significantly compromises mitochondrial respiration and decreases cell proliferation and tumor size in vitro and in vivo. Collectively, our results highlight the importance of the mitochondrial one-carbon pathway in undifferentiated thyroid cancer and suggest that SHMT2 is a potent therapeutic target.

Sustainable metabolic engineering requires a perfect trifecta.

The versatility of cellular metabolism in converting various substrates to products inspires sustainable alternatives to conventional chemical processes. Metabolism can be engineered to maximize the yield, rate, and titer of product generation. However, the numerous combinations of substrate, product, and organism make metabolic engineering projects difficult to navigate. A perfect trifecta of substrate, product, and organism is prerequisite for an environmentally and economically sustainable metabolic engineering endeavor. As a step toward this endeavor, we propose a reverse engineering strategy that starts with product selection, followed by substrate and organism pairing. While a large bioproduct space has been explored, the top-ten compounds have been synthesized mainly using glucose and model organisms. Unconventional feedstocks (e.g. hemicellulosic sugars and CO2) and non-model organisms are increasingly gaining traction for advanced bioproduct synthesis due to their specialized metabolic modes. Judicious selection of the substrate-organism-product combination will illuminate the untapped territory of sustainable metabolic engineering.

Toward Systems-Level Metabolic Analysis in Endocrine Disorders and Cancer.

Metabolism is a dynamic network of biochemical reactions that support systemic homeostasis amidst changing nutritional, environmental, and physical activity factors. The circulatory system facilitates metabolite exchange among organs, while the endocrine system finely tunes metabolism through hormone release. Endocrine disorders like obesity, diabetes, and Cushing's syndrome disrupt this balance, contributing to systemic inflammation and global health burdens. They accompany metabolic changes on multiple levels from molecular interactions to individual organs to the whole body. Understanding how metabolic fluxes relate to endocrine disorders illuminates the underlying dysregulation. Cancer is increasingly considered a systemic disorder because it not only affects cells in localized tumors but also the whole body, especially in metastasis. In tumorigenesis, cancer-specific mutations and nutrient availability in the tumor microenvironment reprogram cellular metabolism to meet increased energy and biosynthesis needs. Cancer cachexia results in metabolic changes to other organs like muscle, adipose tissue, and liver. This review explores the interplay between the endocrine system and systems-level metabolism in health and disease. We highlight metabolic fluxes in conditions like obesity, diabetes, Cushing's syndrome, and cancers. Recent advances in metabolomics, fluxomics, and systems biology promise new insights into dynamic metabolism, offering potential biomarkers, therapeutic targets, and personalized medicine.

Extracellular Domains of CAR Reprogram T-Cell Metabolism Without Antigen Stimulation.

Metabolism is an indispensable part of T-cell proliferation, activation, and exhaustion, yet the metabolism of chimeric antigen receptor (CAR)-T cells remains incompletely understood. CARs are comprised of extracellular domains that determine cancer specificity, often using single-chain variable fragments (scFvs), and intracellular domains that trigger signaling upon antigen binding. Here we show that CARs differing only in the scFv reprogram T-cell metabolism differently. Even in the absence of antigens, some CARs increase proliferation and nutrient uptake in T cells. Using stable isotope tracers and mass spectrometry, we observe basal metabolic fluxes through glycolysis doubling and amino acid uptake overtaking anaplerosis in CAR-T cells harboring rituximab scFv, unlike other similar anti-CD20 scFvs. Disparate rituximab and 14g2a-based anti-GD2 CAR-T cells are similarly hypermetabolic and channel excess nutrients to nitrogen overflow metabolism. Since CAR-dependent metabolic reprogramming alters cellular energetics, nutrient utilization, and proliferation, metabolic profiling should be an integral part of CAR-T cell development.

Determination of Metabolic Fluxes by Deep Learning of Isotope Labeling Patterns.

Fluxomics offers a direct readout of metabolic state but relies on indirect measurement. Stable isotope tracers imprint flux-dependent isotope labeling patterns on metabolites we measure; however, the relationship between labeling patterns and fluxes remains elusive. Here we innovate a two-stage machine learning framework termed ML-Flux that streamlines metabolic flux quantitation from isotope tracing. We train machine learning models by simulating atom transitions across five universal metabolic models starting from 26 13C-glucose, 2H-glucose, and 13C-glutamine tracers within feasible flux space. ML-Flux employs deep-learning-based imputation to take variable measurements of labeling patterns as input and successive neural networks to convert the ensuing comprehensive labeling information into metabolic fluxes. Using ML-Flux with multi-isotope tracing, we obtain fluxes through central carbon metabolism that are comparable to those from a least-squares method but orders-of-magnitude faster. ML-Flux is deployed as a webtool to expand the accessibility of metabolic flux quantitation and afford actionable information on metabolism.

M2 isoform of pyruvate kinase rewires glucose metabolism during radiation therapy to promote an antioxidant response and glioblastoma radioresistance.

BACKGROUND: Resistance to existing therapies is a significant challenge in improving outcomes for glioblastoma (GBM) patients. Metabolic plasticity has emerged as an important contributor to therapy resistance, including radiation therapy (RT). Here, we investigated how GBM cells reprogram their glucose metabolism in response to RT to promote radiation resistance. METHODS: Effects of radiation on glucose metabolism of human GBM specimens were examined in vitro and in vivo with the use of metabolic and enzymatic assays, targeted metabolomics, and FDG-PET. Radiosensitization potential of interfering with M2 isoform of pyruvate kinase (PKM2) activity was tested via gliomasphere formation assays and in vivo human GBM models. RESULTS: Here, we show that RT induces increased glucose utilization by GBM cells, and this is accompanied with translocation of GLUT3 transporters to the cell membrane. Irradiated GBM cells route glucose carbons through the pentose phosphate pathway (PPP) to harness the antioxidant power of the PPP and support survival after radiation. This response is regulated in part by the PKM2. Activators of PKM2 can antagonize the radiation-induced rewiring of glucose metabolism and radiosensitize GBM cells in vitro and in vivo. CONCLUSIONS: These findings open the possibility that interventions designed to target cancer-specific regulators of metabolic plasticity, such as PKM2, rather than specific metabolic pathways, have the potential to improve the radiotherapeutic outcomes in GBM patients.

Integrative metabolic flux analysis reveals an indispensable dimension of phenotypes.

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.

Maximizing light-driven CO2 and N2 fixation efficiency in quantum dot-bacteria hybrids.

Integrating light-harvesting materials with microbial biochemistry is a viable approach to produce chemicals with high efficiency from the air, water, and sunlight. Yet it remains unclear whether all absorbed photons in the materials can be transferred through the material-biology interface for solar-to-chemical production and whether the presence of materials beneficially affect the microbial metabolism. Here we report a microbe-semiconductor hybrid by interfacing CO2/N2-fixing bacterium Xanthobacter autotrophicus with CdTe quantum dots for light-driven CO2 and N2 fixation with internal quantum efficiencies of 47.2 ± 7.3% and 7.1 ± 1.1%, respectively, reaching the biochemical limits of 46.1% and 6.9% imposed by the stoichiometry in biochemical pathways. Photophysical studies suggest fast charge-transfer kinetics at the microbe-semiconductor interfaces, while proteomics and metabolomics indicate a material-induced regulation of microbial metabolism favoring higher quantum efficiencies compared to the biological counterparts alone.

BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions.

BACKGROUND: Genome-scale metabolic reconstructions under the Constraint Based Reconstruction and Analysis (COBRA) framework are valuable tools for analyzing the metabolic capabilities of organisms and interpreting experimental data. As the number of such reconstructions and analysis methods increases, there is a greater need for data uniformity and ease of distribution and use. DESCRIPTION: We describe BiGG, a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest. CONCLUSIONS: BiGG addresses a need in the systems biology community to have access to high quality curated metabolic models and reconstructions. It is freely available for academic use at http://bigg.ucsd.edu.

Light-Independent Biological Conversion of CO2.

Sevcan Ersan is a postdoctoral researcher at UCLA. Previously, she conducted postdoctoral research at the University of Hohenheim in Germany. She received her PhD in biotechnology from Yeditepe University, Turkey, and her bachelor's and master's degrees in food engineering from Istanbul Technical University, Turkey. She is experienced in waste utilization, bioprocessing technologies, and biological activities associated with phytochemicals. Her current research focuses on natural product chemistry and sustainable biotechnology. Junyoung Park is an assistant professor of Chemical and Biomolecular Engineering and co-director of the Metabolomics Center at UCLA. His research group focuses on systems-level analysis of metabolic networks to elucidate regulatory mechanisms and engineer metabolism. He aims to apply this knowledge to solving energy and environmental problems and curing human diseases such as cancer and diabetes. Before moving to Los Angeles, he conducted postdoctoral research at MIT. He received his bachelor's degrees in mathematics and bioengineering from UC San Diego and a master's and PhD in chemical engineering from Princeton University.