Pharmacological SERCA activation limits diet-induced steatohepatitis and restores liver metabolic function in mice.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common form of liver disease and poses significant health risks to patients who progress to metabolic dysfunction-associated steatohepatitis (MASH). Fatty acid (FA) overload alters endoplasmic reticulum (ER) calcium stores and induces mitochondrial oxidative stress in hepatocytes, leading to hepatocellular inflammation and apoptosis. Obese mice have impaired liver sarco/endoplasmic reticulum Ca2+-ATPase (SERCA) function, which normally maintains intracellular calcium homeostasis by transporting Ca2+ ions from the cytoplasm to ER. We hypothesized that restoration of SERCA activity would improve diet-induced steatohepatitis in mice by limiting ER stress and mitochondrial dysfunction. Wild-type and melanocortin-4 receptor knockout (Mc4r-/-) mice were placed on either chow or Western diet (WD) for 8 weeks. Half of the WD-fed mice were administered CDN1163 to activate SERCA, which reduced liver fibrosis and inflammation. SERCA activation also restored glucose tolerance and insulin sensitivity, improved histological markers of MASH, increased expression of antioxidant enzymes, and decreased expression of oxidative stress and ER stress genes. CDN1163 decreased hepatic citric acid cycle flux and liver pyruvate cycling, enhanced expression of mitochondrial respiratory genes, and shifted hepatocellular [NADH]/[NAD+] and [NADPH]/[NADP+] ratios to a less oxidized state, which was associated with elevated polyunsaturated fatty acid (PUFA) content of liver lipids. In sum, the data demonstrate that pharmacological SERCA activation limits MASLD progression and prevents metabolic dysfunction induced by WD feeding in mice.

Clocking out and letting go to unleash green biotech applications in a photosynthetic host.

Cyanobacteria are photosynthetic bacteria whose gene expression patterns are globally regulated by their circadian (daily) clocks. Due to their ability to use sunlight as their energy source, they are also attractive hosts for "green" production of pharmaceuticals, renewable fuels, and chemicals. However, despite the application of traditional genetic tools such as the identification of strong promoters to enhance the expression of heterologous genes, cyanobacteria have lagged behind other microorganisms such as Escherichia coli and yeast as economically efficient cell factories. The previous approaches have ignored large-scale constraints within cyanobacterial metabolic networks on transcription, predominantly the pervasive control of gene expression by the circadian (daily) clock. Here, we show that reprogramming gene expression by releasing circadian repressor elements in the transcriptional regulatory pathways coupled with inactivation of the central oscillating mechanism enables a dramatic enhancement of expression in cyanobacteria of heterologous genes encoding both catalytically active enzymes and polypeptides of biomedical significance.

Hepatic malonyl-CoA synthesis restrains gluconeogenesis by suppressing fat oxidation, pyruvate carboxylation, and amino acid availability.

Acetyl-CoA carboxylase (ACC) promotes prandial liver metabolism by producing malonyl-CoA, a substrate for de novo lipogenesis and an inhibitor of CPT-1-mediated fat oxidation. We report that inhibition of ACC also produces unexpected secondary effects on metabolism. Liver-specific double ACC1/2 knockout (LDKO) or pharmacologic inhibition of ACC increased anaplerosis, tricarboxylic acid (TCA) cycle intermediates, and gluconeogenesis by activating hepatic CPT-1 and pyruvate carboxylase flux in the fed state. Fasting should have marginalized the role of ACC, but LDKO mice maintained elevated TCA cycle intermediates and preserved glycemia during fasting. These effects were accompanied by a compensatory induction of proteolysis and increased amino acid supply for gluconeogenesis, which was offset by increased protein synthesis during feeding. Such adaptations may be related to Nrf2 activity, which was induced by ACC inhibition and correlated with fasting amino acids. The findings reveal unexpected roles for malonyl-CoA synthesis in liver and provide insight into the broader effects of pharmacologic ACC inhibition.

Metabolic Fluxes in the Renal Cortex are Dysregulated In Vivo in Response to High-Fat Diet.

Diabetes and obesity are risk factors for kidney disease. While 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 to chow-fed mice. Relative to the citric acid cycle, HF-feeding increased metabolic flux through pyruvate carboxylation (anaplerosis) and phosphoenolpyruvate carboxykinase (cataplerosis) while decreasing flux through the pyruvate dehydrogenase complex in the cortex. Furthermore, the relative flux from non-pyruvate 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.

Biochemical and metabolic characterization of a G6PC2 inhibitor.

Three glucose-6-phosphatase catalytic subunits, that hydrolyze glucose-6-phosphate (G6P) to glucose and inorganic phosphate, have been identified, designated G6PC1-3, but only G6PC1 and G6PC2 have been implicated in the regulation of fasting blood glucose (FBG). Elevated FBG has been associated with multiple adverse clinical outcomes, including increased risk for type 2 diabetes and various cancers. Therefore, G6PC1 and G6PC2 inhibitors that lower FBG may be of prophylactic value for the prevention of multiple conditions. The studies described here characterize a G6PC2 inhibitor, designated VU0945627, previously identified as Compound 3. We show that VU0945627 preferentially inhibits human G6PC2 versus human G6PC1 but activates human G6PC3. VU0945627 is a mixed G6PC2 inhibitor, increasing the Km but reducing the Vmax for G6P hydrolysis. PyRx virtual docking to an AlphaFold2-derived G6PC2 structural model suggests VU0945627 binds two sites in human G6PC2. Mutation of residues in these sites reduces the inhibitory effect of VU0945627. VU0945627 does not inhibit mouse G6PC2 despite its 84% sequence identity with human G6PC2. Mutagenesis studies suggest this lack of inhibition of mouse G6PC2 is due, in part, to a change in residue 318 from histidine in human G6PC2 to proline in mouse G6PC2. Surprisingly, VU0945627 still inhibited glucose cycling in the mouse islet-derived ßTC-3 cell line. Studies using intact mouse liver microsomes and PyRx docking suggest that this observation can be explained by an ability of VU0945627 to also inhibit the G6P transporter SLC37A4. These data will inform future computational modeling studies designed to identify G6PC isoform-specific inhibitors.

SIMPEL: using stable isotopes to elucidate dynamics of context specific metabolism.

The capacity to leverage high resolution mass spectrometry (HRMS) with transient isotope labeling experiments is an untapped opportunity to derive insights on context-specific metabolism, that is difficult to assess quantitatively. Tools are needed to comprehensively mine isotopologue information in an automated, high-throughput way without errors. We describe a tool, Stable Isotope-assisted Metabolomics for Pathway Elucidation (SIMPEL), to simplify analysis and interpretation of isotope-enriched HRMS datasets. The efficacy of SIMPEL is demonstrated through examples of central carbon and lipid metabolism. In the first description, a dual-isotope labeling experiment is paired with SIMPEL and isotopically nonstationary metabolic flux analysis (INST-MFA) to resolve fluxes in central metabolism that would be otherwise challenging to quantify. In the second example, SIMPEL was paired with HRMS-based lipidomics data to describe lipid metabolism based on a single labeling experiment. Available as an R package, SIMPEL extends metabolomics analyses to include isotopologue signatures necessary to quantify metabolic flux.

Bacteria- and fungus-derived PAMPs induce innate immune memory via similar functional, metabolic, and transcriptional adaptations.

Exposure to pathogen-associated molecular patterns (PAMPs) induces an augmented, broad-spectrum antimicrobial response to subsequent infection, a phenomenon termed innate immune memory. This study examined the effects of treatment with ß-glucan, a fungus-derived dectin-1 ligand, or monophosphoryl lipid A (MPLA), a bacteria-derived Toll-like receptor 4 ligand, on innate immune memory with a focus on identifying common cellular and molecular pathways activated by these diverse PAMPs. Treatment with either PAMP prepared the innate immune system to respond more robustly to Pseudomonas aeruginosa infection in vivo by facilitating mobilization of innate leukocytes into blood, recruitment of leukocytes to the site of infection, augmentation of microbial clearance, and attenuation of cytokine production. Examination of macrophages ex vivo showed amplification of metabolism, phagocytosis, and respiratory burst after treatment with either agent, although MPLA more robustly augmented these activities and more effectively facilitated killing of bacteria. Both agents activated gene expression pathways in macrophages that control inflammation, antimicrobial functions, and protein synthesis and suppressed pathways regulating cell division. ß-glucan treatment minimally altered macrophage differential gene expression in response to lipopolysaccharide (LPS) challenge, whereas MPLA attenuated the magnitude of the LPS-induced transcriptional response, especially cytokine gene expression. These results show that ß-glucan and MPLA similarly augment the innate response to infection in vivo. Yet, MPLA more potently induces alterations in macrophage metabolism, antimicrobial functions, gene transcription and the response to LPS.

Program for Integration and Rapid Analysis of Mass Isotopomer Distributions (PIRAMID).

SUMMARY: The analysis of stable isotope labeling experiments requires accurate, efficient, and reproducible quantification of mass isotopomer distributions (MIDs), which is not a core feature of general-purpose metabolomics software tools that are optimized to quantify metabolite abundance. Here, we present PIRAMID (Program for Integration and Rapid Analysis of Mass Isotopomer Distributions), a MATLAB-based tool that addresses this need by offering a user-friendly, graphical user interface-driven program to automate the extraction of isotopic information from mass spectrometry (MS) datasets. This tool can simultaneously extract ion chromatograms for various metabolites from multiple data files in common vendor-agnostic file formats, locate chromatographic peaks based on a targeted list of characteristic ions and retention times, and integrate MIDs for each target ion. These MIDs can be corrected for natural isotopic background based on the user-defined molecular formula of each ion. PIRAMID offers support for datasets acquired from low- or high-resolution MS, and single (MS) or tandem (MS/MS) instruments. It also enables the analysis of single or dual labeling experiments using a variety of isotopes (i.e. 2H, 13C, 15N, 18O, 34S). DATA AVAILABILITY AND IMPLEMENTATION: MATLAB p-code files are freely available for non-commercial use and can be downloaded from https://mfa.vueinnovations.com/. Commercial licenses are also available. All the data presented in this publication are available under the "Help_menu" folder of the PIRAMID software.

Metabolic engineering of Synechococcus elongatus 7942 for enhanced sucrose biosynthesis.

The capability of cyanobacteria to produce sucrose from CO2 and light has a remarkable societal and biotechnological impact since sucrose can serve as a carbon and energy source for a variety of heterotrophic organisms and can be converted into value-added products. However, most metabolic engineering efforts have focused on understanding local pathway alterations that drive sucrose biosynthesis and secretion in cyanobacteria rather than analyzing the global flux re-routing that occurs following induction of sucrose production by salt stress. Here, we investigated global metabolic flux alterations in a sucrose-secreting (cscB-overexpressing) strain relative to its wild-type Synechococcus elongatus 7942 parental strain. We used targeted metabolomics, 13C metabolic flux analysis (MFA), and genome-scale modeling (GSM) as complementary approaches to elucidate differences in cellular resource allocation by quantifying metabolic profiles of three cyanobacterial cultures - wild-type S. elongatus 7942 without salt stress (WT), wild-type with salt stress (WT/NaCl), and the cscB-overexpressing strain with salt stress (cscB/NaCl) - all under photoautotrophic conditions. We quantified the substantial rewiring of metabolic fluxes in WT/NaCl and cscB/NaCl cultures relative to WT and identified a metabolic bottleneck limiting carbon fixation and sucrose biosynthesis. This bottleneck was subsequently mitigated through heterologous overexpression of glyceraldehyde-3-phosphate dehydrogenase in an engineered sucrose-secreting strain. Our study also demonstrates that combining 13C-MFA and GSM is a useful strategy to both extend the coverage of MFA beyond central metabolism and to improve the accuracy of flux predictions provided by GSM.

MYC overrides HIF-1α to regulate proliferating primary cell metabolism in hypoxia.

Hypoxia requires metabolic adaptations to sustain energetically demanding cellular activities. While the metabolic consequences of hypoxia have been studied extensively in cancer cell models, comparatively little is known about how primary cell metabolism responds to hypoxia. Thus, we developed metabolic flux models for human lung fibroblast and pulmonary artery smooth muscle cells proliferating in hypoxia. Unexpectedly, we found that hypoxia decreased glycolysis despite activation of hypoxia-inducible factor 1α (HIF-1α) and increased glycolytic enzyme expression. While HIF-1α activation in normoxia by prolyl hydroxylase (PHD) inhibition did increase glycolysis, hypoxia blocked this effect. Multi-omic profiling revealed distinct molecular responses to hypoxia and PHD inhibition, and suggested a critical role for MYC in modulating HIF-1α responses to hypoxia. Consistent with this hypothesis, MYC knockdown in hypoxia increased glycolysis and MYC over-expression in normoxia decreased glycolysis stimulated by PHD inhibition. These data suggest that MYC signaling in hypoxia uncouples an increase in HIF-dependent glycolytic gene transcription from glycolytic flux.

Overexpression of peroxisome proliferator-activated receptor γ co-activator-1⍺ (PGC-1⍺) in Chinese hamster ovary cells increases oxidative metabolism and IgG productivity.

Chinese hamster ovary (CHO) cells are used extensively to produce protein therapeutics, such as monoclonal antibodies (mAbs), in the biopharmaceutical industry. MAbs are large proteins that are energetically demanding to synthesize and secrete; therefore, high-producing CHO cell lines that are engineered for maximum metabolic efficiency are needed to meet increasing demands for mAb production. Previous studies have identified that high-producing cell lines possess a distinct metabolic phenotype when compared to low-producing cell lines. In particular, it was found that high mAb production is correlated to lactate consumption and elevated TCA cycle flux. We hypothesized that enhancing flux through the mitochondrial TCA cycle and oxidative phosphorylation would lead to increased mAb productivities and final titers. To test this hypothesis, we overexpressed peroxisome proliferator-activated receptor γ co-activator-1⍺ (PGC-1⍺), a gene that promotes mitochondrial metabolism, in an IgG-producing parental CHO cell line. Stable cell pools overexpressing PGC-1⍺ exhibited increased oxygen consumption, indicating increased mitochondrial metabolism, as well as increased mAb specific productivity compared to the parental line. We also performed 13C metabolic flux analysis (MFA) to quantify how PGC-1⍺ overexpression alters intracellular metabolic fluxes, revealing not only increased TCA cycle flux, but global upregulation of cellular metabolic activity. This study demonstrates the potential of rationally engineering the metabolism of industrial cell lines to improve overall mAb productivity and to increase the abundance of high-producing clones in stable cell pools.

Metabolic flux phenotyping of secondary metabolism in cyanobacteria.

Cyanobacteria generate energy from photosynthesis and produce various secondary metabolites with diverse commercial and pharmaceutical applications. Unique metabolic and regulatory pathways in cyanobacteria present new challenges for researchers to enhance their product yields, titers, and rates. Therefore, further advancements are critically needed to establish cyanobacteria as a preferred bioproduction platform. Metabolic flux analysis (MFA) quantitatively determines the intracellular flows of carbon within complex biochemical networks, which elucidate the control of metabolic pathways by transcriptional, translational, and allosteric regulatory mechanisms. The emerging field of systems metabolic engineering (SME) involves the use of MFA and other omics technologies to guide the rational development of microbial production strains. This review highlights the potential of MFA and SME to optimize the production of cyanobacterial secondary metabolites and discusses the technical challenges that lie ahead.

Oxidation of hyperpolarized [1-13 C]pyruvate in isolated rat kidneys.

Kidneys play a central role in numerous disorders but current imaging methods have limited utility to probe renal metabolism. Hyperpolarized (HP) 13 C magnetic resonance imaging is uniquely suited to provide metabolite-specific information about key biochemical pathways and it offers the further advantage that renal imaging is practical in humans. This study evaluated the feasibility of hyperpolarization examinations in a widely used model for analysis of renal physiology, the isolated kidney, which enables isolation of renal metabolism from the effects of other organs and validation of HP results by independent measurements. Isolated rat kidneys were supplied with either HP [1-13 C]pyruvate only or HP [1-13 C]pyruvate plus octanoate. Metabolic activity in both groups was confirmed by stable renal oxygen consumption. HP [1-13 C]pyruvate was readily metabolized to [13 C]bicarbonate, [1-13 C]lactate, and [1-13 C]alanine, detectable seconds after HP [1-13 C]pyruvate was injected. Octanoate suppressed but did not eliminate the production of HP [13 C]bicarbonate from [1-13 C]pyruvate. Steady-state flux analyses using non-HP 13 C substrates validated the utilization of HP [1-13 C]pyruvate, as observed by HP 13 C NMR. In the presence of octanoate, lactate is generated from a tricarboxylic acid cycle intermediate, oxaloacetate. The isolated rat kidney may serve as an excellent model for investigating and establishing new HP 13 C metabolic probes for future kidney imaging applications.

AMPK activation is sufficient to increase skeletal muscle glucose uptake and glycogen synthesis but is not required for contraction-mediated increases in glucose metabolism.

The AMP-activated protein kinase (AMPK) is a cellular sensor of energetics and when activated in skeletal muscle during contraction can impart changes in skeletal muscle metabolism. Therapeutics that selectively activate AMPK have been developed to lower glucose levels through increased glucose disposal rates as an approach to abrogate the hyperglycemic state of diabetes; however, the metabolic fate of glucose following AMPK activation remains unclear. We have used a combination of in vivo evaluation of glucose homeostasis and ex vivo skeletal muscle incubation to systematically evaluate metabolism following pharmacological activation of AMPK with PF-739, comparing this with AMPK activation through sustained intermittent electrical stimulation of contraction. These methods to activate AMPK result in increased glucose uptake but divergent metabolism of glucose: pharmacological activation results in increased glycogen accumulation while contraction-induced glucose uptake results in increased lactate formation and glucose oxidation. These results provide additional evidence to support a role for AMPK in control of skeletal muscle metabolism and additional insight into the potential for AMPK stimulation with small molecule direct activators.

Manufactured extracellular vesicles as human therapeutics: challenges, advances, and opportunities.

Extracellular vesicles (EVs) have evolved across all phyla as an intercellular communication system. There are intrinsic advantages of leveraging this capability to deliver therapeutic cargo to treat disease, which have been demonstrated in numerous in vivo studies. As with other new modalities, the challenge has now shifted from proof of concept to developing reliable and efficient large-scale infrastructure to manufacture consistently pure and potent drug for broad-based patient access. This review focuses on how this challenge has been met with both existing and emerging technology platforms that are making impressive strides in the industrialization of EV manufacturing. In addition, we also highlight the gaps and opportunities that are beginning to be explored and addressed to hasten ushering in the era of therapeutic EVs.

13C-Isotope-Assisted Assessment of Metabolic Quenching During Sample Collection from Suspension Cell Cultures.

Metabolomics and fluxomics are core approaches to directly profile and interrogate cellular metabolism in response to various genetic or environmental perturbations. In order to accurately measure the abundance and isotope enrichment of intracellular metabolites, cell culture samples must be rapidly harvested and cold quenched to preserve the in vivo metabolic state of the cells at the time of sample collection. When dealing with suspension cultures, this process is complicated by the need to separate the liquid culture media from cellular biomass prior to metabolite extraction. Here, we examine the efficacy of several commonly used metabolic quenching methods, using the model cyanobacterium Synechocystis sp. PCC 6803 as an example. Multiple 13C-labeled compounds, including 13C-bicarbonate, 13C-glucose, and 13C-glutamine, were used as tracers during the sample collection and the cold-quenching process to assess the extent of metabolic turnover after cells were harvested from culture flasks. We show that the combination of rapid filtration followed by 100% cold (-80 °C) methanol quenching exhibits the highest quenching efficiency, while mixing cell samples with a partially frozen 30% methanol slurry (-24 °C) followed by centrifugation is slightly less effective at quenching metabolism but enables less laborious sample processing. By contrast, rapidly mixing the cells with a saline ice slurry (∼0 °C) is less effective, as indicated by high isotope-labeling rates after sample harvest, while mixing the cells with 60% cold methanol (-65 °C) prior to centrifugation causes significant metabolite loss. This study demonstrates a rigorous, quantitative, and broadly applicable method for assessing the metabolic quenching efficacy of protocols used for sample collection in metabolomics and fluxomics studies.

Attenuation of glutamine synthetase selection marker improves product titer and reduces glutamine overflow in Chinese hamster ovary cells.

The glutamine synthetase (GS) expression system is commonly used to ensure stable transgene integration and amplification in Chinese hamster ovary (CHO) host lines. Transfected cell populations are typically grown in the presence of the GS inhibitor, methionine sulfoximine (MSX), to further select for increased transgene copy number. However, high levels of GS activity produce excess glutamine. We hypothesized that attenuating the GS promoter while keeping the strong IgG promoter on the GS-IgG expression vector would result in a more efficient cellular metabolic phenotype. Herein, we characterized CHO cell lines expressing GS from either an attenuated promoter or an SV40 promoter and selected with/without MSX. CHO cells with the attenuated GS promoter had higher IgG specific productivity and lower glutamine production compared to cells with SV40-driven GS expression. Selection with MSX increased both specific productivity and glutamine production, regardless of GS promoter strength. 13 C metabolic flux analysis (MFA) was performed to further assess metabolic differences between these cell lines. Interestingly, central carbon metabolism was unaltered by the attenuated GS promoter while the fate of glutamate and glutamine varied depending on promoter strength and selection conditions. This study highlights the ability to optimize the GS expression system to improve IgG production and reduce wasteful glutamine overflow, without significantly altering central metabolism. Additionally, a detailed supplementary analysis of two "lactate runaway" reactors provides insight into the poorly understood phenomenon of excess lactate production by some CHO cell cultures.

Glucose-6-phosphatase catalytic subunit 2 negatively regulates glucose oxidation and insulin secretion in pancreatic ß-cells.

Elevated fasting blood glucose (FBG) is associated with increased risks of developing type 2 diabetes (T2D) and cardiovascular-associated mortality. G6PC2 is predominantly expressed in islets, encodes a glucose-6-phosphatase catalytic subunit that converts glucose-6-phosphate (G6P) to glucose, and has been linked with variations in FBG in genome-wide association studies. Deletion of G6pc2 in mice has been shown to lower FBG without affecting fasting plasma insulin levels in vivo. At 5 mM glucose, pancreatic islets from G6pc2 knockout (KO) mice exhibit no glucose cycling, increased glycolytic flux, and enhanced glucose-stimulated insulin secretion (GSIS). However, the broader effects of G6pc2 KO on ß-cell metabolism and redox regulation are unknown. Here we used CRISPR/Cas9 gene editing and metabolic flux analysis in ßTC3 cells, a murine pancreatic ß-cell line, to examine the role of G6pc2 in regulating glycolytic and mitochondrial fluxes. We found that deletion of G6pc2 led to ∼60% increases in glycolytic and citric acid cycle (CAC) fluxes at both 5 and 11 mM glucose concentrations. Furthermore, intracellular insulin content and GSIS were enhanced by approximately two-fold, along with increased cytosolic redox potential and reductive carboxylation flux. Normalization of fluxes relative to net glucose uptake revealed upregulation in two NADPH-producing pathways in the CAC. These results demonstrate that G6pc2 regulates GSIS by modulating not only glycolysis but also, independently, citric acid cycle activity in ß-cells. Overall, our findings implicate G6PC2 as a potential therapeutic target for enhancing insulin secretion and lowering FBG, which could benefit individuals with prediabetes, T2D, and obesity.

Pool size measurements improve precision of flux estimates but increase sensitivity to unmodeled reactions outside the core network in isotopically nonstationary metabolic flux analysis (INST-MFA).

Metabolic flux analysis (MFA) involves model-based estimation of metabolic reaction rates (i.e., fluxes) and, in some cases, metabolite content (i.e., pool sizes) from experimental measurements. Applying MFA to biological data helps determine the fate of substrates and the activity of specific pathways within metabolic networks. However, reliably estimating fluxes by using simplified "core" models to predict the dynamics of larger metabolic networks remains a challenge. One point of uncertainty relates to the advantages and potential pitfalls of including pool size measurements as experimental inputs for isotopically nonstationary MFA (INST-MFA). Here, we directly assessed the role of pool sizes using various core models and simulated datasets. To investigate the effects of pool size measurements on INST-MFA, we assessed the accuracy and precision of flux estimates obtained using different subsets of data (e.g., with or without pool size measurements) and simple network models that either matched or differed from the true network. The inclusion of pool size measurements provided incremental improvements to the precision of the flux estimates. However, adding pool size measurements increased the sensitivity of the flux solution to unmodeled reactions outside the core network. These results were confirmed using a large Escherichia coli model that is representative of realistic metabolic networks examined in MFA studies. Our findings indicate that accurate flux estimates can be obtained in the absence of pool size measurements, even when using core models that lack full network coverage. Addition of pool size measurements to INST-MFA datasets may reveal the activity of non-core reactions that influence the labeling dynamics and therefore necessitate network expansion in order to reconcile all available data to the model. Our findings also emphasize the key role that goodness-of-fit testing plays in assessing the quality of model fits obtained with INST-MFA.

INCA 2.0: A tool for integrated, dynamic modeling of NMR- and MS-based isotopomer measurements and rigorous metabolic flux analysis.

Metabolic flux analysis (MFA) combines experimental measurements and computational modeling to determine biochemical reaction rates in live biological systems. Advancements in analytical instrumentation, such as nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), have facilitated chemical separation and quantification of isotopically enriched metabolites. However, no software packages have been previously described that can integrate isotopomer measurements from both MS and NMR analytical platforms and have the flexibility to estimate metabolic fluxes from either isotopic steady-state or dynamic labeling experiments. By applying physiologically relevant cardiac and hepatic metabolic models to assess NMR isotopomer measurements, we herein test and validate new modeling capabilities of our enhanced flux analysis software tool, INCA 2.0. We demonstrate that INCA 2.0 can simulate and regress steady-state 13C NMR datasets from perfused hearts with an accuracy comparable to other established flux assessment tools. Furthermore, by simulating the infusion of three different 13C acetate tracers, we show that MFA based on dynamic 13C NMR measurements can more precisely resolve cardiac fluxes compared to isotopically steady-state flux analysis. Finally, we show that estimation of hepatic fluxes using combined 13C NMR and MS datasets improves the precision of estimated fluxes by up to 50%. Overall, our results illustrate how the recently added NMR data modeling capabilities of INCA 2.0 can enable entirely new experimental designs that lead to improved flux resolution and can be applied to a wide range of biological systems and measurement time courses.