Glycolysis/gluconeogenesis specialization in microbes is driven by biochemical constraints of flux sensing.
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ABSTRACT:
SUBMITTER: Schink SJ
PROVIDER: S-EPMC8738977 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Central carbon metabolism is highly conserved across microbial species, but can catalyze very different pathways depending on the organism and their ecological niche. Here, we study the dynamic reorganization of central metabolism after switches between the two major opposing pathway configurations of central carbon metabolism, glycolysis, and gluconeogenesis in Escherichia coli, Pseudomonas aeruginosa, and Pseudomonas putida. We combined growth dynamics and dynamic changes in intracellular metabolite levels with a coarse-grained model that integrates fluxes, regulation, protein synthesis, and growth and uncovered fundamental limitations of the regulatory network: After nutrient shifts, metabolite concentrations collapse to their equilibrium, rendering the cell unable to sense which direction the flux is supposed to flow through the metabolic network. The cell can partially alleviate this by picking a preferred direction of regulation at the expense of increasing lag times in the opposite direction. Moreover, decreasing both lag times simultaneously comes at the cost of reduced growth rate or higher futile cycling between metabolic enzymes. These three trade-offs can explain why microorganisms specialize for either glycolytic or gluconeogenic substrates and can help elucidate the complex growth patterns exhibited by different microbial species.
2022-01-11 | MTBLS3887 | MetaboLights
Project description:We identify a connection between the structural features of mass-action networks and the robustness of their steady-state fluxes against rate constant variations. We find that in all positive steady states of so-called injective networks-networks that arise, for example, in metabolic and gene regulation contexts-there are certain firm bounds on the flux control coefficients. In particular, the control coefficient of the flux of a reaction, with respect to variation in its own rate constant, is delimited in a precise way. Moreover, for each pair of reactions, the flux of at least one of them must have a precisely delimited control coefficient with respect to variation in the rate constant of the other. The derived bounds can, however, be violated in noninjective networks, so for them a more pronounced lack of robustness could be exhibited. These results, which indicate a mechanism by which some degree of robustness is induced in the injective setting, also shed light on how robustness might evolve.
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Project description:Autophagy and glycolysis are two catabolic processes that manipulate pancreatic ductal adenocarcinoma (PDAC) development in response to hypoxia sensing, yet the underlying mechanism of how they are interlinked remain elusive. Methods: The functional roles of Unc-51 like kinase 1 and 2 (ULK1/2) in pyruvate kinase M2 (PKM2) transcription and glycolysis under hypoxia were assessed by chromatin immunoprecipitation, luciferase reporter, glucose consumption and lactate production assay. Co-immunoprecipitation, cellular ubiquitination, His-pulldown, in vitro protein kinase assay, immunofluorescence, immunohistochemistry, CRISPR technology, in silico studies were adopted to determine the molecular mechanism. Correlation analyses were performed in KPC (Pdx1-Cre; LSL-KrasG12D/+; Trp53fl/+) mice and clinical samples from PDAC patients. Therapeutic potential of ULK1/2 inhibitor and 2-deoxyglucose (2-DG) or 3-bromopyruvate (3-BP) was evaluated in cell-derived xenograft (CDX) and the patient-derived xenograft (PDX) models of nude mice. Results: ULK1/2, but not ULK3, augments hypoxic glycolysis in PDAC cells mediated by PKM2 independent of BCL2/adenovirus E1B 19 kDa interacting protein 3 (BNIP3). Mechanistically, hypoxia stimulates ULK1 to translocate into nucleus, where it interacts with and phosphorylates yes-associated protein (YAP) at Ser227, resulting in YAP stabilization through blockade of ubiquitin-proteasome system (UPS), which in turn facilitates PKM2 transcription, glycolysis, cell proliferation in vitro as well as PDAC growth in mice. ULK1/2 is positively correlated with YAP and PKM2 in tumor tissues from KPC mice and clinical samples from PDAC patients. Pharmacological deactivation of ULK1/2 potentiates the antineoplastic efficacy of 2-DG and 3-BP in CDX and PDX models. Conclusion: Our findings underscore the Ser227 autophosphorylation-dependent nuclear YAP stabilization as a central node that couples ULK1/2-initiated autophagy to hypoxic glycolysis during PDAC development and propose that targeting ULK1/2 combined with 2-DG or 3-BP might be a feasible therapeutic strategy against PDAC.
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Project description:Inhibition of glycolysis has been considered as a therapeutic approach in aggressive cancers including lung cancer. Abbreviated gluconeogenesis, mediated by phosphoenolpyruvate carboxykinase (PEPCK), was recently discovered to partially circumvent the need for glycolysis in lung cancer cells. However, the interplay of glycolysis and gluconeogenesis in lung cancer is still poorly understood. Here, we analyzed the expression of GLUT1, the prime glucose transporter, and of PCK1 and PCK2, the cytoplasmic and mitochondrial isoforms of PEPCK, in 450 samples of non-small cell lung cancer (NSCLC) and in 54 NSCLC metastases using tissue microarrays and whole tumor sections. Spatial distribution was assessed by automated image analysis. Additionally, glycolytic and gluconeogenic gene expression was inferred from The Cancer Genome Atlas (TCGA) datasets. We found that PCK2 was preferentially expressed in the lung adenocarcinoma subtype, while GLUT1 expression was higher in squamous cell carcinoma. GLUT1 and PCK2 were inversely correlated, GLUT1 showing elevated expression in larger tumors while PCK2 was highest in smaller tumors. However, a mixed phenotype showing the presence of both, glycolytic and gluconeogenic cancer cells was frequent. In lung adenocarcinoma, PCK2 expression was associated with significantly improved overall survival, while the opposite was found for GLUT1. The metabolic tumor microenvironment and the 3-dimensional context play an important role in modulating both pathways, since PCK2 expression preferentially occurred at the tumor margin and hypoxia regulated both, glycolysis and gluconeogenesis, in NSCLC cells in vitro, albeit in opposite directions. PCK1/2 expression was enhanced in metastases compared to primary tumors, possibly related to the different environment. The results of this study show that glycolysis and gluconeogenesis are activated in NSCLC in a tumor size and oxygenation modulated manner and differentially correlate with outcome. The frequent co-activation of gluconeogenesis and glycolysis in NSCLC should be considered in potential future therapeutic strategies targeting cancer cell metabolism.
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Project description:Synthesis of sugars from simple carbon sources is critical for survival of animals under limited nutrient availability. Thus, sugar-synthesizing enzymes should be present across the entire metazoan spectrum. Here, we explore the evolution of glucose and trehalose synthesis using a phylogenetic analysis of enzymes specific for the two pathways. Our analysis reveals that the production of trehalose is the more ancestral biochemical process, found in single cell organisms and primitive metazoans, but also in insects. The gluconeogenic-specific enzyme glucose-6-phosphatase (G6Pase) first appears in Cnidaria, but is also present in Echinodermata, Mollusca and Vertebrata. Intriguingly, some species of nematodes and arthropods possess the genes for both pathways. Moreover, expression data from Drosophila suggests that G6Pase and, hence, gluconeogenesis, initially had a neuronal function. We speculate that in insects-and possibly in some vertebrates-gluconeogenesis may be used as a means of neuronal signaling.
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Project description:Insulin governs systemic glucose metabolism, including glycolysis, gluconeogenesis and glycogenesis, through temporal change and absolute concentration. However, how insulin-signalling pathway selectively regulates glycolysis, gluconeogenesis and glycogenesis remains to be elucidated. To address this issue, we experimentally measured metabolites in glucose metabolism in response to insulin. Step stimulation of insulin induced transient response of glycolysis and glycogenesis, and sustained response of gluconeogenesis and extracellular glucose concentration (GLC(ex)). Based on the experimental results, we constructed a simple computational model that characterises response of insulin-signalling-dependent glucose metabolism. The model revealed that the network motifs of glycolysis and glycogenesis pathways constitute a feedforward (FF) with substrate depletion and incoherent feedforward loop (iFFL), respectively, enabling glycolysis and glycogenesis responsive to temporal changes of insulin rather than its absolute concentration. In contrast, the network motifs of gluconeogenesis pathway constituted a FF inhibition, enabling gluconeogenesis responsive to absolute concentration of insulin regardless of its temporal patterns. GLC(ex) was regulated by gluconeogenesis and glycolysis. These results demonstrate the selective control mechanism of glucose metabolism by temporal patterns of insulin.
| S-EPMC4039368 | biostudies-literature
Project description:Bacterial symbionts of eukaryotes often give up generalist lifestyles to specialize to particular hosts. The eusocial honey bees and bumble bees harbor two such specialized gut symbionts, Snodgrassella alvi and Gilliamella apicola. Not only are these microorganisms specific to bees, but different strains of these bacteria tend to assort according to host species. By using in-vivo microbial transplant experiments, we show that the observed specificity is, at least in part, due to evolved physiological barriers that limit compatibility between a host and a potential gut colonizer. How and why such specialization occurs is largely unstudied for gut microbes, despite strong evidence that it is a general feature in many gut communities. Here, we discuss the potential factors that favor the evolution of host specialization, and the parallels that can be drawn with parasites and other symbiont systems. We also address the potential of the bee gut as a model for exploring gut community evolution.
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Project description:The current state of the art for linear optimization in Flux Balance Analysis has been limited to single objective functions. Since mammalian systems perform various functions, a multiobjective approach is needed when seeking optimal flux distributions in these systems. In most of the available multiobjective optimization methods, there is a lack of understanding of when to use a particular objective, and how to combine and/or prioritize mutually competing objectives to achieve a truly optimal solution. To address these limitations we developed a soft constraints based linear physical programming-based flux balance analysis (LPPFBA) framework to obtain a multiobjective optimal solutions. The developed framework was first applied to compute a set of multiobjective optimal solutions for various pairs of objectives relevant to hepatocyte function (urea secretion, albumin, NADPH, and glutathione syntheses) in bioartificial liver systems. Next, simultaneous analysis of the optimal solutions for three objectives was carried out. Further, this framework was utilized to obtain true optimal conditions to improve the hepatic functions in a simulated bioartificial liver system. The combined quantitative and visualization framework of LPPFBA is applicable to any large-scale metabolic network system, including those derived by genomic analyses.
| S-EPMC2922426 | biostudies-literature
Project description:BackgroundThis study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response.MethodsData analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients.ResultsThirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients.ConclusionResults showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients.
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Project description:Metabolic reprogramming and elevated glycolysis levels are associated with tumor progression. However, despite cancer cells selectively inhibiting or expressing certain metabolic enzymes, it is unclear whether differences in gene profiles influence patient outcomes. Therefore, identifying the differences in enzyme action may facilitate discovery of gene ontology variations to characterize tumors. Fructose-1,6-bisphosphate (F-1,6-BP) is an important intermediate in glucose metabolism, particularly in cancer. Gluconeogenesis and glycolysis require fructose-1,6-bisphosphonates 1 (FBP1) and fructose-bisphosphate aldolase A (ALDOA), which participate in F-1,6-BP conversion. Increased expression of ALDOA and decreased expression of FBP1 are associated with the progression of various forms of cancer in humans. However, the exact molecular mechanism by which ALDOA and FBP1 are involved in the switching of F-1,6-BP is not yet known. As a result of their pancancer pattern, the relationship between ALDOA and FBP1 in patient prognosis is reversed, particularly in lung adenocarcinoma (LUAD) and liver hepatocellular carcinoma (LIHC). Using The Cancer Genome Atlas (TCGA), we observed that FBP1 expression was low in patients with LUAD and LIHC tumors, which was distinct from ALDOA. A similar trend was observed in the analysis of Cancer Cell Line Encyclopedia (CCLE) datasets. By dissecting downstream networks and possible upstream regulators, using ALDOA and FBP1 as the core, we identified common signatures and interaction events regulated by ALDOA and FBP1. Notably, the identified effectors dominated by ALDOA or FBP1 were distributed in opposite patterns and can be considered independent prognostic indicators for patients with LUAD and LIHC. Therefore, uncovering the effectors between ALDOA and FBP1 will lead to novel therapeutic strategies for cancer patients.
| S-EPMC9037270 | biostudies-literature