Metabolic rewiring of macrophages by epidermal-derived lactate promotes sterile inflammation in the murine skin.

Dysregulated macrophage responses and changes in tissue metabolism are hallmarks of chronic inflammation in the skin. However, the metabolic cues that direct and support macrophage functions in the skin are poorly understood. Here, we show that during sterile skin inflammation, the epidermis and macrophages uniquely depend on glycolysis and the TCA cycle, respectively. This compartmentalisation is initiated by ROS-induced HIF-1α stabilization leading to enhanced glycolysis in the epidermis. The end-product of glycolysis, lactate, is then exported by epithelial cells and utilized by the dermal macrophages to induce their M2-like fates through NF-κB pathway activation. In addition, we show that psoriatic skin disorder is also driven by such lactate metabolite-mediated crosstalk between the epidermis and macrophages. Notably, small-molecule inhibitors of lactate transport in this setting attenuate sterile inflammation and psoriasis disease burden, and suppress M2-like fate acquisition in dermal macrophages. Our study identifies an essential role for the metabolite lactate in regulating macrophage responses to inflammation, which may be effectively targeted to treat inflammatory skin disorders such as psoriasis.

Lactate supports cell-autonomous ECM production to sustain metastatic behavior in prostate cancer.

Extracellular matrix (ECM) is a major component of the tumor environment, promoting the establishment of a pro-invasive behavior. Such environment is supported by both tumor- and stromal-derived metabolites, particularly lactate. In prostate cancer (PCa), cancer-associated fibroblasts (CAFs) are major contributors of secreted lactate, able to impact on metabolic and transcriptional regulation in cancer cells. Here, we describe a mechanism by which CAF-secreted lactate promotes in PCa cells the expression of genes coding for the collagen family. Lactate-exploiting PCa cells rely on increased α-ketoglutarate (α-KG) which activates the α-KG-dependent collagen prolyl-4-hydroxylase (P4HA1) to support collagen hydroxylation. De novo synthetized collagen plays a signaling role by activating discoidin domain receptor 1 (DDR1), supporting stem-like and invasive features of PCa cells. Inhibition of lactate-induced collagen hydroxylation and DDR1 activation reduces the metastatic colonization of PCa cells. Overall, these results provide a new understanding of the link between collagen remodeling/signaling and the nutrient environment exploited by PCa.

A bright red fluorescent genetically encoded sensor for lactate imaging.

Lactate plays a crucial role in energy metabolism and greatly impacts protein activities, exerting diverse physiological and pathological effects. Therefore, convenient lactate assays for tracking spatiotemporal dynamics in living cells are desirable. In this paper, we engineered and optimized a red fluorescent protein sensor for l-lactate named FiLa-Red. This indicator exhibited a maximal fluorescence change of 730 % and an apparent dissociation constant (Kd) of approximately 460 µM. By utilizing FiLa-Red and other sensors, we monitored energy metabolism in a multiplex manner by simultaneously tracking lactate and NAD+/NADH abundance in the cytoplasm, nucleus, and mitochondria. The FiLa-Red sensor is expected to be a useful tool for performing metabolic analysis in vitro, in living cells and in vivo.

Distinct lactate metabolism between hepatocytes and myotubes revealed by live cell imaging with genetically encoded indicators.

The process of glycolysis breaks down glycogen stored in muscles, producing lactate through pyruvate to generate energy. Excess lactate is then released into the bloodstream. When lactate reaches the liver, it is converted to glucose, which muscles utilize as a substrate to generate ATP. Although the biochemical study of lactate metabolism in hepatocytes and skeletal muscle cells has been extensive, the spatial and temporal dynamics of this metabolism in live cells are still unknown. We observed the dynamics of metabolism-related molecules in primary cultured hepatocytes and a skeletal muscle cell line upon lactate overload. Our observations revealed an increase in cytoplasmic pyruvate concentration in hepatocytes, which led to glucose release. Skeletal muscle cells exhibited elevated levels of lactate and pyruvate levels in both the cytoplasm and mitochondrial matrix. However, mitochondrial ATP levels remained unaffected, indicating that the increased lactate can be converted to pyruvate but is unlikely to be utilized for ATP production. The findings suggest that excess lactate in skeletal muscle cells is taken up into mitochondria with little contribution to ATP production. Meanwhile, lactate released into the bloodstream can be converted to glucose in hepatocytes for subsequent utilization in skeletal muscle cells.

Novel hypoxia- and lactate metabolism-related molecular subtyping and prognostic signature for colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a serious global health burden because of its high morbidity and mortality rates. Hypoxia and massive lactate production are hallmarks of the CRC microenvironment. However, the effects of hypoxia and lactate metabolism on CRC have not been fully elucidated. This study aimed to develop a novel molecular subtyping based on hypoxia-related genes (HRGs) and lactate metabolism-related genes (LMRGs) and construct a signature to predict the prognosis of patients with CRC and treatment efficacy. METHODS: Bulk and single-cell RNA-sequencing and clinical data of CRC were downloaded from the TCGA and GEO databases. HRGs and LMRGs were obtained from the Molecular Signatures Database. The R software package DESeq2 was used to perform differential expression analysis. Molecular subtyping was performed using unsupervised clustering. A predictive signature was developed using univariate Cox regression, random forest model, LASSO, and multivariate Cox regression analyses. Finally, the sensitivity of tumor cells to chemotherapeutic agents before and after hypoxia was verified using in vitro experiments. RESULTS: We classified 575 patients with CRC into three molecular subtypes and were able to distinguish their prognoses clearly. The C1 subtype, which exhibits high levels of hypoxia, has a low proportion of CD8 + T cells and a high proportion of macrophages. The expression of immune checkpoint genes is generally elevated in C1 patients with severe immune dysfunction. Subsequently, we constructed a predictive model, the HLM score, which effectively predicts the prognosis of patients with CRC and the efficacy of immunotherapy. The HLM score was validated in GSE39582, GSE106584, GSE17536, and IMvigor210 datasets. Patients with high HLM scores exhibit high infiltration of CD8 + exhausted T cells (Tex), especially terminal Tex, and oxidative phosphorylation (OXPHOS)-Tex in the immune microenvironment. Finally, in vitro experiments confirmed that CRC cell lines were less sensitive to 5-fluorouracil, oxaliplatin, and irinotecan under hypoxic conditions. CONCLUSION: We constructed novel hypoxia- and lactate metabolism-related molecular subtypes and revealed their immunological and genetic characteristics. We also developed an HLM scoring system that could be used to predict the prognosis and efficacy of immunotherapy in patients with CRC.

Unravelling the metabolic landscape of cutaneous melanoma: Insights from single-cell sequencing analysis and machine learning for prognostic assessment of lactate metabolism.

This manuscript presents a comprehensive investigation into the role of lactate metabolism-related genes as potential prognostic markers in skin cutaneous melanoma (SKCM). Bulk-transcriptome data from The Cancer Genome Atlas (TCGA) and GSE19234, GSE22153, and GSE65904 cohorts from GEO database were processed and harmonized to mitigate batch effects. Lactate metabolism scores were assigned to individual cells using the 'AUCell' package. Weighted Co-expression Network Analysis (WGCNA) was employed to identify gene modules correlated with lactate metabolism. Machine learning algorithms were applied to construct a prognostic model, and its performance was evaluated in multiple cohorts. Immune correlation, mutation analysis, and enrichment analysis were conducted to further characterize the prognostic model's biological implications. Finally, the function of key gene NDUFS7 was verified by cell experiments. Machine learning resulted in an optimal prognostic model, demonstrating significant prognostic value across various cohorts. In the different cohorts, the high-risk group showed a poor prognosis. Immune analysis indicated differences in immune cell infiltration and checkpoint gene expression between risk groups. Mutation analysis identified genes with high mutation loads in SKCM. Enrichment analysis unveiled enriched pathways and biological processes in high-risk SKCM patients. NDUFS7 was found to be a hub gene in the protein-protein interaction network. After the expression of NDUFS7 was reduced by siRNA knockdown, CCK-8, colony formation, transwell and wound healing tests showed that the activity, proliferation and migration of A375 and WM115 cell lines were significantly decreased. This study offers insights into the prognostic significance of lactate metabolism-related genes in SKCM.

Lactate oxidation in Paracoccus denitrificans.

Paracoccus denitrificans has a classical cytochrome-dependent electron transport chain and two alternative oxidases. The classical transport chain is very similar to that in eukaryotic mitochondria. Thus, P. denitrificans can serve as a model of the mammalian mitochondrion that may be more tractable in elucidating mechanisms of regulation of energy production than are mitochondria. In a previous publication we reported detailed studies on respiration in P. denitrificans grown aerobically on glucose or malate. We noted that P. denitrificans has large stores of lactate under various growth conditions. This is surprising because P. denitrificans lacks an NAD+-dependent lactate dehydrogenase. The aim of this study was to investigate the mechanisms of lactate oxidation in P. denitrificans. We found that the bacterium grows well on either d-lactate or l-lactate. Growth on lactate supported a rate of maximum respiration that was equal to that of cells grown on glucose or malate. We report proteomic, metabolomic, and biochemical studies that establish that the metabolism of lactate by P. denitrificans is mediated by two non-NAD+-dependent lactate dehydrogenases. One prefers d-lactate over l-lactate (D-iLDH) and the other prefers l-lactate (L-iLDH). We cloned and produced the D-iLDH and characterized it. The Km for d-lactate was 34 µM, and for l-lactate it was 3.7 mM. Pyruvate was not a substrate, rendering the reaction unidirectional with lactate being converted to pyruvate for entry into the TCA cycle. The intracellular lactate was ∼14 mM such that both isomers could be metabolized by the enzyme. The enzyme has 1 FAD per molecule and utilizes a quinone rather than NAD + as an electron acceptor. D-iLDH provides a direct entry of lactate reducing equivalents into the cytochrome chain, potentially explaining the high respiratory capacity of P. denitrificans in the presence of lactate.

Emerging roles of lactate in acute and chronic inflammation.

Traditionally, lactate has been considered a 'waste product' of cellular metabolism. Recent findings have shown that lactate is a substance that plays an indispensable role in various physiological cellular functions and contributes to energy metabolism and signal transduction during immune and inflammatory responses. The discovery of lactylation further revealed the role of lactate in regulating inflammatory processes. In this review, we comprehensively summarize the paradoxical characteristics of lactate metabolism in the inflammatory microenvironment and highlight the pivotal roles of lactate homeostasis, the lactate shuttle, and lactylation ('lactate clock') in acute and chronic inflammatory responses from a molecular perspective. We especially focused on lactate and lactate receptors with either proinflammatory or anti-inflammatory effects on complex molecular biological signalling pathways and investigated the dynamic changes in inflammatory immune cells in the lactate-related inflammatory microenvironment. Moreover, we reviewed progress on the use of lactate as a therapeutic target for regulating the inflammatory response, which may provide a new perspective for treating inflammation-related diseases.

A prognostic risk model based on lactate metabolism and transport-related lncRNAs for gastric adenocarcinoma.

BACKGROUND: Increased lactate levels and metastasis in tumours are strongly associated with dismal outcomes. But prognostic value of lactate metabolism and transport-related lncRNAs in gastric adenocarcinoma (GA) patients remains unaddressed. METHODS: Gene expression data of GA were provided by The Cancer Genome Atlas. Lactate metabolism and transport-related gene data were accessed from GSEA. LncRNAs related to lactate metabolism and transport were identified by correlation analysis. A prognostic model was built by regression analysis. Validity of prognostic model was confirmed through survival analysis and receiver operating characteristic (ROC) curve. Immunity of each risk group was evaluated by immune correlation analysis .LncRNA-mRNA network was built by correlation analysis using Cytoscape software. RESULTS: A 12-gene prognostic model based on lactate metabolism and transport-related lncRNAs was built in GA. Median riskscore was utilized to classify GA samples into high- and low-risk groups. Survival analysis and ROC curves demonstrated validity of prognostic model. Most immune checkpoint molecules and TIDE scores were lower in the low-risk group. LINC01303 and LINC01545 may be the key prognostic factors in patients with GA. CONCLUSION: This study successfully built a prognostic model of lactate metabolism and transport-related lncRNAs in GA. The findings guide prognostic management of GA patients.

Metformin confers sensitisation to syrosingopine in multiple myeloma cells by metabolic blockage and inhibition of protein synthesis.

Multiple myeloma (MM) remains an incurable haematological malignancy despite substantial advances in therapy. Hypoxic bone marrow induces metabolic rewiring in MM cells contributing to survival and drug resistance. Therefore, targeting metabolic pathways may offer an alternative treatment option. In this study, we repurpose two FDA-approved drugs, syrosingopine and metformin. Syrosingopine was used as a dual inhibitor of monocarboxylate transporter 1 and 4 (MCT1/4) and metformin as an inhibitor for oxidative phosphorylation (OXPHOS). Anti-tumour effects were evaluated for single agents and in combination therapy. Survival and expression data for MCT1/MCT4 were obtained from the Total Therapy 2, Mulligan, and Multiple Myeloma Research Foundation cohorts. Cell death, viability, and proliferation were measured using Annexin V/7-AAD, CellTiterGlo, and BrdU, respectively. Metabolic effects were assessed using Seahorse Glycolytic Rate assays and LactateGlo assays. Differential protein expression was determined using western blotting, and the SUnSET method was implemented to quantify protein synthesis. Finally, the syngeneic 5T33MMvv model was used for in vivo analysis. High-level expression of MCT1 and MCT4 both correlated with a significantly lower overall survival of patients. Lactate production as well as MCT1/MCT4 expression were significantly upregulated in hypoxia, confirming the Warburg effect in MM. Dual inhibition of MCT1/4 with syrosingopine resulted in intracellular lactate accumulation and reduced cell viability and proliferation. However, only at higher doses (>10 µm) was syrosingopine able to induce cell death. By contrast, combination treatment of syrosingopine with metformin was highly cytotoxic for MM cell lines and primary patient samples and resulted in a suppression of both glycolysis and OXPHOS. Moreover, pathway analysis revealed an upregulation of the energy sensor p-AMPKα and more downstream a reduction in protein synthesis. Finally, the combination treatment resulted in a significant reduction in tumour burden in vivo. This study proposes an alternative combination treatment for MM and provides insight into intracellular effects. © 2023 The Pathological Society of Great Britain and Ireland.

Identification of a combined hypoxia and lactate metabolism prognostic signature in lung adenocarcinoma : Author.

BACKGROUND: In the tumor microenvironment (TME), a bidirectional relationship exists between hypoxia and lactate metabolism, with each component exerting a reciprocal influence on the other, forming an inextricable link. The aim of the present investigation was to develop a prognostic model by amalgamating genes associated with hypoxia and lactate metabolism. This model is intended to serve as a tool for predicting patient outcomes, including survival rates, the status of the immune microenvironment, and responsiveness to therapy in patients with lung adenocarcinoma (LUAD). METHODS: Transcriptomic sequencing data and patient clinical information specific to LUAD were obtained from comprehensive repositories of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A compendium of genes implicated in hypoxia and lactate metabolism was assembled from an array of accessible datasets. Univariate and multivariate Cox regression analyses were employed. Additional investigative procedures, including tumor mutational load (TMB), microsatellite instability (MSI), functional enrichment assessments and the ESTIMATE, CIBERSORT, and TIDE algorithms, were used to evaluate drug sensitivity and predict the efficacy of immune-based therapies. RESULTS: A novel prognostic signature comprising five lactate and hypoxia-related genes (LHRGs), PKFP, SLC2A1, BCAN, CDKN3, and ANLN, was established. This model demonstrated that LUAD patients with elevated LHRG-related risk scores exhibited significantly reduced survival rates. Both univariate and multivariate Cox analyses confirmed that the risk score was a robust prognostic indicator of overall survival. Immunophenotyping revealed increased infiltration of memory CD4 + T cells, dendritic cells and NK cells in patients classified within the high-risk category compared to their low-risk counterparts. Higher probability of mutations in lung adenocarcinoma driver genes in high-risk groups, and the MSI was associated with the risk-score. Functional enrichment analyses indicated a predominance of cell cycle-related pathways in the high-risk group, whereas metabolic pathways were more prevalent in the low-risk group. Moreover, drug sensitivity analyses revealed increased sensitivity to a variety of drugs in the high-risk group, especially inhibitors of the PI3K-AKT, EGFR, and ELK pathways. CONCLUSIONS: This prognostic model integrates lactate metabolism and hypoxia parameters, offering predictive insights regarding survival, immune cell infiltration and functionality, as well as therapeutic responsiveness in LUAD patients. This model may facilitate personalized treatment strategies, tailoring interventions to the unique molecular profile of each patient's disease.

Bulk-RNA and single-nuclei RNA seq analyses reveal the role of lactate metabolism-related genes in Alzheimer's disease.

Dysfunctional lactate metabolism in the brain has been implicated in neuroinflammation, Aß deposition, and cell disturbance, all of which play a significant role in the pathogenesis of Alzheimer's disease (AD). In this study, we aimed to investigate the lactate metabolism-related genes (LMRGs) in AD via an integrated bulk RNA and single-nuclei RNA sequencing (snRNA-seq) analysis, with a specific focus on microglia. We obtained 26 HC and 24 AD snRNA-seq samples originated from human prefrontal cortex in Gene Expression Omnibus (GEO) database and collected 873 LMRGs from three databases, namely MSigDB, The Human Protein Atlas and GeneCards. Bulk RNA was analyzed with LMRG characteristics in AD by using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), the protein-protein interaction (PPI), CytoHubba-MCC, Support Vector Machine (SVM) algorithms analyses. Then we conducted the Receiver Operating Characteristic (ROC) curve, correlation, and connection network analyses for biomarkers. Their differential expression validation was performed using AlzData database. The single-nuclei RNA analysis of microglia was applied to identify hub genes and pathways using cell-cell communication analysis and high dimensional Weighted Gene Co-Expression Network Analysis (hdWGCNA). Support Vector Machine (SVM) algorithm showed an AUC of 0.967, a sensitivity of 93.30% and a specificity of 100.00%. Our analysis identified biomarkers with LMRG characteristics, namely INSR, CDKL1, and PNISR. ROC analysis revealed that each of these biomarkers exhibited excellent diagnostic potential, as evidenced by their respective area under the curve (AUC) values: INSR (AUC: 0.679), CDKL1 (AUC: 0.788), and PNISR (AUC: 0.724). Correlation analysis showed that biomarkers exhibited a positive correlation with each other. Connection network illustrated their shared biological processes: aging, phosphorylation, metabolic process, and apoptosis. Cell-cell communication analysis revealed that GALECTIN signaling pathway was exclusively expressed in AD microglia, and only LGALS9 exhibited significant overexpression. HdWGCNA identified FTH1 as a hub gene enriched in ferroptosis and mineral absorption pathways within microglia. The roles of INSR, CDKL1, PNISR, LGALS9, and FTH1 should be taken into account to enhance our understanding of lactate metabolism in the context of AD.

Modulation of brain energy metabolism in hepatic encephalopathy: impact of glucose metabolic dysfunction.

Cerebral function is linked to a high level of metabolic activity and relies on glucose as its primary energy source. Glucose aids in the maintenance of physiological brain activities; as a result, a disruption in metabolism has a significant impact on brain function, launching a chain of events that leads to neuronal death. This metabolic insufficiency has been observed in a variety of brain diseases and neuroexcitotoxicity disorders, including hepatic encephalopathy. It is a significant neurological complication that develops in people with liver disease, ranging from asymptomatic abnormalities to coma. Hyperammonemia is the main neurotoxic villain in the development of hepatic encephalopathy and induces a wide range of complications in the brain. The neurotoxic effects of ammonia on brain function are thought to be mediated by impaired glucose metabolism. Accordingly, in this review, we provide an understanding of deranged brain energy metabolism, emphasizing the role of glucose metabolic dysfunction in the pathogenesis of hepatic encephalopathy. We also highlighted the differential metabolic profiles of brain cells and the status of metabolic cooperation between them. The major metabolic pathways that have been explored are glycolysis, glycogen metabolism, lactate metabolism, the pentose phosphate pathway, and the Krebs cycle. Furthermore, the lack of efficacy in current hepatic encephalopathy treatment methods highlights the need to investigate potential therapeutic targets for hepatic encephalopathy, with regulating deficient bioenergetics being a viable alternative in this case. This review also demonstrates the importance of the development of glucose metabolism-focused disease diagnostics and treatments, which are now being pursued for many ailments.

Construction and Validation of a Prognostic Risk Prediction Model for Lactate Metabolism-Related lncRNA in Endometrial Cancer.

Endometrial cancer (EC) is a common group of malignant epithelial tumors that mainly occur in the female endometrium. Lactate is a key regulator of signal pathways in normal and malignant tissues. However, there is still no research on lactate metabolism-related lncRNA in EC. Here, we intended to establish a prognostic risk model for EC based on lactate metabolism-related lncRNA to forecast the prognosis of EC patients. First, we found that 38 lactate metabolism-associated lncRNAs were significantly overall survival through univariate Cox regression analysis. Using minimum absolute contraction and selection operator (LASSO) regression analysis and multivariate Cox regression analysis, six lactate metabolism-related lncRNAs were established as independent predictor in EC patients and were used to establish a prognostic risk signature. We next used multifactorial COX regression analysis and receiver operating characteristic (ROC) curve analysis to confirm that risk score was an independent prognostic factor of overall patient survival. The survival time of patients with EC in different high-risk populations was obviously related to clinicopathological factors. In addition, lactate metabolism-related lncRNA in high-risk population participated in multiple aspects of EC malignant progress through Gene Set Enrichment Analysis, Genomes pathway and Kyoto Encyclopedia of Genes and Gene Ontology. And risk scores were strongly associated with tumor mutation burden, immunotherapy response and microsatellite instability. Finally, we chose a lncRNA SRP14-AS1 to validate the model we have constructed. Interestingly, we observed that the expression degree of SRP14-AS1 was lower in tumor tissues of EC patients than in normal tissues, which was consistent with our findings in the TCGA database. In conclusion, our study constructed a prognostic risk model through lactate metabolism-related lncRNA and validated the model, confirming that the model can be used to predict the prognosis of EC patients and providing a molecular analysis of potential prognostic lncRNA for EC.

All Three AKT Isoforms Can Upregulate Oxygen Metabolism and Lactate Production in Human Hepatocellular Carcinoma Cell Lines.

Hepatocellular carcinoma (HCC), the main pathological type of liver cancer, is related to risk factors such as viral hepatitis, alcohol intake, and non-alcoholic fatty liver disease (NAFLD). The constitutive activation of the PI3K/AKT signaling pathway is common in HCC and has essential involvement in tumor progression. The serine/threonine kinase AKT has several downstream substrates, which have been implicated in the regulation of cellular metabolism. However, the contribution of each of the three AKT isoforms, i.e., AKT1, AKT2 and AKT3, to HCC metabolism has not been comprehensively investigated. In this study, we analyzed the functional role of AKT1, AKT2 and AKT3 in HCC metabolism. The overexpression of activated AKT1, AKT2 and AKT3 isoforms in the human HCC cell lines Hep3B and Huh7 resulted in higher oxygen consumption rate (OCR), ATP production, maximal respiration and spare respiratory capacity in comparison to vector-transduced cells. Vice versa, lentiviral vector-mediated knockdowns of each AKT isoform reduced OCR in both cell lines. Reduced OCR rates observed in the three AKT isoform knockdowns were associated with reduced extracellular acidification rates (ECAR) and reduced lactate production in both analyzed cell lines. Mechanistically, the downregulation of OCR by AKT isoform knockdowns correlated with an increased phosphorylation of the pyruvate dehydrogenase on Ser232, which negatively regulates the activity of this crucial gatekeeper of mitochondrial respiration. In summary, our data indicate that each of the three AKT isoforms is able to upregulate OCR, ECAR and lactate production independently of each other in human HCC cells through the regulation of the pyruvate dehydrogenase.

In vivo calibration of genetically encoded metabolite biosensors must account for metabolite metabolism during calibration and cellular volume.

Isotopic assays of brain glucose utilization rates have been used for more than four decades to establish relationships between energetics, functional activity, and neurotransmitter cycling. Limitations of these methods include the relatively long time (1-60 min) for the determination of labeled metabolite levels and the lack of cellular resolution. Identification and quantification of fuels for neurons and astrocytes that support activation and higher brain functions are a major, unresolved issues. Glycolysis is preferentially up-regulated during activation even though oxygen level and supply are adequate, causing lactate concentrations to quickly rise during alerting, sensory processing, cognitive tasks, and memory consolidation. However, the fate of lactate (rapid release from brain or cell-cell shuttling coupled with local oxidation) is long disputed. Genetically encoded biosensors can determine intracellular metabolite concentrations and report real-time lactate level responses to sensory, behavioral, and biochemical challenges at the cellular level. Kinetics and time courses of cellular lactate concentration changes are informative, but accurate biosensor calibration is required for quantitative comparisons of lactate levels in astrocytes and neurons. An in vivo calibration procedure for the Laconic lactate biosensor involves intracellular lactate depletion by intravenous pyruvate-mediated trans-acceleration of lactate efflux followed by sensor saturation by intravenous infusion of high doses of lactate plus ammonium chloride. In the present paper, the validity of this procedure is questioned because rapid lactate-pyruvate interconversion in blood, preferential neuronal oxidation of both monocarboxylates, on-going glycolytic metabolism, and cellular volumes were not taken into account. Calibration pitfalls for the Laconic lactate biosensor also apply to other metabolite biosensors that are standardized in vivo by infusion of substrates that can be metabolized in peripheral tissues. We discuss how technical shortcomings negate the conclusion that Laconic sensor calibrations support the existence of an in vivo astrocyte-neuron lactate concentration gradient linked to lactate shuttling from astrocytes to neurons to fuel neuronal activity.

The dentate gyrus differentially metabolizes glucose and alternative fuels during rest and stimulation.

The metabolic demands of neuronal activity are both temporally and spatially dynamic, and neurons are particularly sensitive to disruptions in fuel and oxygen supply. Glucose is considered an obligate fuel for supporting brain metabolism. Although alternative fuels are often available, the extent of their contribution to central carbon metabolism remains debated. Differential fuel metabolism likely depends on cell type, location, and activity state, complicating its study. While biosensors provide excellent spatial and temporal information, they are limited to observations of only a few metabolites. On the other hand, mass spectrometry is rich in chemical information, but traditionally relies on cell culture or homogenized tissue samples. Here, we use mass spectrometry imaging (MALDI-MSI) to focus on the fuel metabolism of the dentate granule cell (DGC) layer in murine hippocampal slices. Using stable isotopes, we explore labeling dynamics at baseline, as well as in response to brief stimulation or fuel competition. We find that at rest, glucose is the predominant fuel metabolized through glycolysis, with little to no measurable contribution from glycerol or fructose. However, lactate/pyruvate, ß-hydroxybutyrate (ßHB), octanoate, and glutamine can contribute to TCA metabolism to varying degrees. In response to brief depolarization with 50 mM KCl, glucose metabolism was preferentially increased relative to the metabolism of alternative fuels. With an increased supply of alternative fuels, both lactate/pyruvate and ßHB can outcompete glucose for TCA cycle entry. While lactate/pyruvate modestly reduced glucose contribution to glycolysis, ßHB caused little change in glycolysis. This approach achieves broad metabolite coverage from a spatially defined region of physiological tissue, in which metabolic states are rapidly preserved following experimental manipulation. Using this powerful methodology, we investigated metabolism within the dentate gyrus not only at rest, but also in response to the energetic demand of activation, and in states of fuel competition.

Sodium oxamate reduces lactate production to improve the glucose homeostasis of Micropterus salmoides fed high-carbohydrate diets.

The study was performed to evaluate the effects of the reduced lactate production by sodium oxamate (SO) on growth performance, lactate and glucose and lipid metabolism, and glucose tolerance of Micropterus salmoides fed high-carbohydrate (CHO) diets. In in vitro study, primary hepatocytes were incubated for 48 h in a control medium (5.5 mM glucose), a high-glucose medium (25 mM glucose, HG), or a SO-containing high-glucose medium (25 mM glucose + 50 mM SO, HG-SO). Results indicated lactate and triglyceride (TG) levels, and lactate dehydrogenase a (LDH-a) expression in the HG-SO group were remarkably lower than those of the HG group. In in vivo study, M. salmoides (5.23 ± 0.03 g) were fed four diets containing a control diet (10% CHO, C) and three SO contents [0 (HC), 100 (HC-SO1), and 200 (HC-SO2) mg·kg-1, respectively] of high-CHO diets (20% CHO) for 11 wk. High-CHO diets significantly reduced weight gain rate (WGR), specific growth rate (SGR), p-AMPK-to-t-AMPK ratio, and expression of insulin receptor substrate 1 (IRS1), insulin-like growth factor I (IGF-I), insulin-like growth factor I receptor (IGF-IR), fructose-1,6-biphosphatase (FBPase), peroxisome proliferator-activated receptor α (PPARα), and carnitine palmitoyl transferase 1α (CPT1α) compared with the C group, whereas the opposite was true for plasma levels of glucose, TG, lactate, tissue glycogen, and lipid contents, and expression of LDH-a, monocarboxylate transporter 1 and 4 (MCT1 and MCT4), insulin, glucokinase (GK), pyruvate dehydrogenase E1 subunit (PDH), sterol-regulatory element-binding protein 1 (SREBP1), fatty acid synthase (FAS). The HC-SO2 diets remarkably increased WGR, SGR, p-AMPK-to-t-AMPK ratio, and expression of IRS1, IGF-I, IGF-IR, GK, PDHα, PDHß, FAS, acetyl-CoA carboxylase 1 (ACC1), PPARα, and CPT1α compared with the HC group. Besides, HC-SO2 diets also enhanced glucose tolerance of fish after a glucose loading. Overall, the reduced lactate production by SO benefits growth performance and glucose homeostasis of high-CHO-fed M. salmoides through the enhancement of glycolysis, lipogenesis, and fatty acid ß-oxidation coupled with the suppression of glycogenesis and gluconeogenesis.

Lactate metabolism-related genes to predict the clinical outcome and molecular characteristics of endometrial cancer.

BACKGROUND: Metabolic reprogramming is one of hallmarks of cancer progression and is of great importance for the tumor microenvironment (TME). As an abundant metabolite, lactate has been found to play a critical role in cancer development and immunosuppression of TME. However, the potential role of lactate metabolism-related genes in endometrial cancer (EC) remains obscure. METHODS: RNA sequencing data and clinical information of EC were obtained from The Cancer Genome Atlas (TCGA) database. Lactate metabolism-related genes (LMRGs) WERE from Molecular Signature Database v7.4 and then compared the candidate genes from TCGA to obtain final genes. Univariate analysis and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression were performed to screen prognostic genes. A lactate metabolism-related risk profile was constructed using multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analysis and Kaplan-Meier analysis. The relationship between the risk score and age, grade, stage, tumor microenvironmental characteristics, and drug sensitivity was as well explored by correlation analyses. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional analysis between the high and low-risk groups were performed. CCK8, EdU, and clone formation assays were applied to detect the proliferation ability of EC cells, Transwell assay was performed to detect the migration ability of EC cells, and intracellular lactate and glucose content was used to asses lactate metabolism. RESULTS: We constructed a risk signature based on 18 LMRGs. Kaplan-Meier curves confirmed that the high-risk group had poorer prognosis compared to the low-risk group. A nomogram was then constructed to predict the probability of EC survival. We also performed GO enrichment analysis and KEGG pathway functional analysis between the high and low-risk groups, and the outcome revealed that the features were significantly associated with energy metabolism. There was a significant correspondence between LMRGs and tumor mutational load, checkpoints and immune cell infiltration. C1, C2, and C4 were the most infiltrated in the high-risk group. The high-risk group showed increased dendritic cell activation, while the low-risk group showed increased plasma cells and Treg cells. Drug sensitivity analysis showed LMRGs risk was more resistant to Scr kinase inhibitors. We further proved that one of the lactate metabolism related genes, TIMM50 could promote EC cell proliferation, migration and lactate metabolism. CONCLUSION: In conclusion, we have established an effective prognostic signature based on LMRG expression patterns, which may greatly facilitate the assessment of prognosis, molecular features and treatment modalities in EC patients and may be useful in the future translation to clinical applications. TIMM50 was identified as a novel molecule that mediates lactate metabolism in vitro and in vivo, maybe a promising target for EC prognosis.

Low CO2 partial pressure steers CHO cells into a defective metabolic state.

PURPOSE: The accumulation of carbon dioxide during large-scale culture of animal cells brings adverse effects, appropriate aeration strategies alleviate CO2 accumulation while improper reactor operation may lead to the presence of low CO2 partial pressure (pCO2) condition as occurs in many industrial cases. Thus, this study aims to reveal the in-depth influence of low pCO2 on Chinese Hamster Ovary (CHO) cells for providing a reference for design space determination of CO2 control with regard to the Quality by Design (QbD) guidelines. METHODS AND RESULTS: The headspace air over purging caused the ultra-low pCO2 (ULC) where the monoclonal antibody production as well as the aerobic metabolic activity were reduced. Intracellular metabolomics analysis indicated a less efficient aerobic glucose metabolic state under ULC conditions. Based on the increase of intracellular pH and lactate dehydrogenase activity, the shortage of intracellular pyruvate could be the cause of the deficient aerobic metabolism, which could be partially mitigated by pyruvate addition under ULC conditions. Finally, a semi-empirical mathematical model was used to better understand, predict and control the occurrence of extreme pCO2 conditions during the cultures of CHO cells. CONCLUSION: Low pCO2 steers CHO cells into a defective metabolic state. A predictive relation among pCO2, lactate, and pH control was applied to get new insights into CHO cell culture for better and more robust metabolic behavior and process performance and the determination of QbD design space for CO2 control.