Search bioRxiv⌕ Search

Biology subjects

Gerding, A.

Publications and source records attributed to Gerding, A..

4 recordsLinked to original sources

Glutamine-derived NADH fuels lactate production to maximize ATP yield under oxygen consumption constraints in head and neck cancer

Metabolic reprogramming is one of the hallmarks of cancer. A well-known change is the Warburg effect: glucose is consumed at increased rates and fermented to lactate instead of being respired to carbon dioxide, despite the presence of sufficient oxygen (O2). We show that head and neck squamous cell carcinoma (HNSCC) cells excrete more carbon in the form of lactate than is consumed as glucose, indicating the presence of additional carbon sources for lactate. Amino acid uptake and [U-13C]-glutamine labelling data show that glutamine is highly consumed and oxidized in the tricarboxylic acid (TCA) cycle, but remarkably does not contribute to lactate carbon. To explain these observations, we generated a cell-line specific metabolic model to understand the link between lactate production and glutamine metabolism. In the model, we show how low cellular O2 consumption capacity can cause increased lactate production with glutamine as NADH source. The model suggests that ATP production under limited O2 consumption is augmented by increased glutamine oxidation which yields ATP, FADH2 and NADH. FADH2 can only be respired, despite yielding less ATP than NADH respiration. NADH can be exported from the mitochondrion to be reoxidized by lactate dehydrogenase, permitting more cycles of glutamine oxidation, thereby increasing the total ATP yield. By experimentally inhibiting mitochondrial respiration, we confirmed that non-glucose carbon sources are used for lactate production under decreased O2 consumption capacity. This unexpected feature of O2-constrained ATP production provides a credible mechanism for the increased lactate production via a novel redox cycle in HNSCC cells.

systems biology↗

Proteomics profiling of serum and liver in GSD Ia and Ib patients: insights into complication mechanisms and circulation biomarkers

BackgroundGlycogen Storage Disease (GSD) Types Ia and Ib are rare metabolic diseases caused by gene variants in G6PC1 and SLC37A4, respectively. Although life-threatening fasting hypoglycemia can be controlled by a strict diet, patients often suffer from multiple metabolic abnormalities and severe long-term complications. However, the underlying mechanisms remain incompletely understood, and the lack of effective monitoring biomarkers makes it a challenge to treat patients. Therefore, the aims of this study are to investigate the pathological mechanisms of the disease and disease complications in GSD I and identify potential protein biomarkers. MethodsIn this study, we employed comprehensive untargeted proteomics on stored samples: 26 serum or plasma samples from 18 GSD Ia and 8 GSD Ib patients with 21 matched control sera, complemented by 4 liver samples from 2 GSD Ia patients who received liver transplantation (from the one patient with hepatocellular carcinoma we obtained tissue from both the carcinoma tissue and the adjacent non-carcinoma tissue), and 1 from a GSD Ib patient, compared to 10 donor liver samples. ResultsWe identified a total of 415 proteins in our analyses. Pathway analysis of the differentially regulated proteins revealed distinct changes in serum/plasma of GSD Ia and Ib. The coagulation pathway was the most significantly changed biological process in the GSD Ia patients. Immune response-associated proteins, especially a large number of immunoglobulins, were increased in GSD Ib specifically. Proteins related to liver injury, cholesterol, and amyloidosis were altered in two subtypes, though more pronounced in GSD Ia. Potential biomarkers with significant alterations both in the circulation as well as in the liver tissue were identified specifically for monitoring GSD I subtypes and prognosing liver deterioration, namely GSD Ia (COL163 and PROC), GSD Ib (F11 and CD163), and hepatocellular carcinoma (HCC) in GSD Ia patients (ALDOB and CFHR5). ConclusionsThese findings provide new insights into the differences between the two GSD I subtypes and the pathogenesis of GSD I-related complications, as well as highlighting the potential of protein circulating biomarkers for monitoring complication progression in GSD I and assessing HCC risk in GSD Ia patients. Trial registrationNot applicable. A concise 1 sentence take-home message (synopsis) of the articleThis comprehensive in-depth proteomics study on blood and liver GSD Ia and Ib patient samples provided novel insights into understanding of the disease subtypes as well as the the pathogenesis of GSD I-related complications, such as HCC risk in GSD Ia patients and identified potential biomarkers for the disease subtypes and complications.

systems biology↗

Spontaneous liver disease in wild-type C57BL/6JOlaHsd mice fed semisynthetic diet

Mouse models are frequently used to study mechanisms of human diseases. Recently, we observed a spontaneous bimodal variation in liver weight in C57BL/6JOlaHsd mice fed a semisynthetic diet. We now characterized the spontaneous variation in liver weight and its relationship with parameters of hepatic lipid and bile acid (BA) metabolism. In male C57BL/6JOlaHsd mice fed AIN-93G from birth to postnatal day (PN)70, we measured plasma BA, lipids, Very low-density lipoprotein (VLDL)-triglyceride (TG) secretion, and hepatic mRNA expression patterns. Mice were sacrificed at PN21, PN42, PN63 and PN70. Liver weight distribution was bimodal at PN70. Mice could be subdivided into two nonoverlapping groups based on liver weight: 0.6 SD 0.1 g (approximately one-third of mice, small liver; SL), and 1.0 SD 0.1 g (normal liver; NL; p<0.05). Liver histology showed a higher steatosis grade, inflammation score, more mitotic figures and more fibrosis in the SL versus the NL group. Plasma BA concentration was 14-fold higher in SL (p<0.001). VLDL-TG secretion rate was lower in SL mice, both absolutely (-66%, p<0.001) and upon correction for liver weight (-44%, p<0.001). Mice that would later have the SL-phenotype showed lower food efficiency ratios during PN21-28, suggesting the cause of the SL phenotype is present at weaning (PN21). Our data show that approximately one-third of C57BL/6JOlaHsd mice fed semisynthetic diet develop spontaneous liver disease with aberrant histology and parameters of hepatic lipid, bile acid and lipoprotein metabolism. Study designs involving this mouse strain on semisynthetic diets need to take the SL phenotype into account. Plasma lipids may serve as markers for the identification of the SL phenotype.

pathology↗

Fibroblast-specific genome-scale modelling predicts an imbalance in amino acid metabolism in Refsum disease

Refsum disease is an inborn error of metabolism that is characterised by a defect in peroxisomal -oxidation of the branched-chain fatty acid phytanic acid. The disorder presents with late-onset progressive retinitis pigmentosa and polyneuropathy and can be diagnosed biochemically by elevated levels of phytanic acid in plasma and tissues of patients. To date, no cure exists for Refsum disease, but phytanic acid levels in patients can be reduced by plasmapheresis and a strict diet.\n\nIn this study, we reconstructed a fibroblast-specific genome-scale model based on the recently published, FAD-curated model, based on Recon3D reconstruction. We used transcriptomics (available via GEO database with identifier GSE138379), metabolomics, and proteomics data (available via ProteomeXchange with identifier PXD015518), which we obtained from healthy controls and Refsum disease patient fibroblasts incubated with phytol, a precursor of phytanic acid.\n\nOur model correctly represents the metabolism of phytanic acid and displays fibroblast-specific metabolic functions. Using this model, we investigated the metabolic phenotype of Refsum disease at the genome-scale, and we studied the effect of phytanic acid on cell metabolism. We identified 53 metabolites that were predicted to discriminate between Healthy and Refsum disease patients, several of which with a link to amino acid metabolism. Ultimately, these insights in metabolic changes may provide leads for pathophysiology and therapy.

systems biology↗