Multiplatform metabolomic interlaboratory study of a whole human stool candidate reference material from omnivore and vegan donors.

Introduction: Human metabolomics has made significant strides in understanding metabolic changes and their implications for human health, with promising applications in diagnostics and treatment, particularly regarding the gut microbiome. However, progress is hampered by issues with data comparability and reproducibility across studies, limiting the translation of these discoveries into practical applications.

Objectives: This study aims to evaluate the fit-for-purpose of a suite of human stool samples as potential candidate reference materials (RMs) and assess the state of the field regarding harmonizing gut metabolomics measurements.

Ketogenic diets slow melanoma growth in vivo regardless of tumor genetics and metabolic plasticity.

Background: Growing evidence supports the use of low-carbohydrate/high-fat ketogenic diets as an adjunctive cancer therapy. However, it is unclear which genetic, metabolic, or immunological factors contribute to the beneficial effect of ketogenic diets. Therefore, we investigated the effect of ketogenic diets on the progression and metabolism of genetically and metabolically heterogeneous melanoma xenografts, as well as on the development of melanoma metastases in mice with a functional immune system.

Targeted Metabolomics Identifies Plasma Biomarkers in Mice with Metabolically Heterogeneous Melanoma Xenografts.

Melanomas are genetically and metabolically heterogeneous, which influences therapeutic efficacy and contributes to the development of treatment resistance in patients with metastatic disease. Metabolite phenotyping helps to better understand complex metabolic diseases, such as melanoma, and facilitates the development of novel therapies. Our aim was to characterize the tumor and plasma metabolomes of mice bearing genetically different melanoma xenografts.

Role of coenzymes in cancer metabolism.

Cancer is a heterogeneous set of diseases characterized by the rewiring of cellular signaling and the reprogramming of metabolic pathways to sustain growth and proliferation. In past decades, studies were focused primarily on the genetic complexity of cancer. Recently, increasing number of studies have discovered several mutations among metabolic enzymes in different tumor cells.

Ldlr and ApoE mice better mimic the human metabolite signature of increased carotid intima media thickness compared to other animal models of cardiovascular disease.

Background And Aims: Preclinical experiments on animal models are essential to understand the mechanisms of cardiovascular disease (CVD). Metabolomics allows access to the metabolic perturbations associated with CVD in heart and vessels. Here we assessed which potential animal CVD model most closely mimics the serum metabolite signature of increased carotid intima-media thickness (cIMT) in humans, a clinical parameter widely accepted as a surrogate of CVD.

Model-driven discovery of long-chain fatty acid metabolic reprogramming in heterogeneous prostate cancer cells.

Epithelial-mesenchymal-transition promotes intra-tumoral heterogeneity, by enhancing tumor cell invasiveness and promoting drug resistance. We integrated transcriptomic data for two clonal subpopulations from a prostate cancer cell line (PC-3) into a genome-scale metabolic network model to explore their metabolic differences and potential vulnerabilities. In this dual cell model, PC-3/S cells express Epithelial-mesenchymal-transition markers and display high invasiveness and low metastatic potential, while PC-3/M cells present the opposite phenotype and higher proliferative rate.

Persistently Altered Metabolic Phenotype following Perinatal Excitotoxic Brain Injury.

Excitotoxicity plays a key role during insults to the developing brain such as neonatal encephalopathy, stroke, and encephalopathy of prematurity. Such insults affect many thousands of infants each year. Excitotoxicity causes frank lesions due to cell death and gliosis and disturbs normal developmental process, leading to deficits in learning, memory, and social integration that persist into adulthood.

Metabolic network failures in Alzheimer's disease: A biochemical road map.

Introduction: The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer's disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance.

Serum metabolites predict response to angiotensin II receptor blockers in patients with diabetes mellitus.

Background: Individual patients show a large variability in albuminuria response to angiotensin receptor blockers (ARB). Identifying novel biomarkers that predict ARB response may help tailor therapy. We aimed to discover and validate a serum metabolite classifier that predicts albuminuria response to ARBs in patients with diabetes mellitus and micro- or macroalbuminuria.

The ratio of phosphatidylcholines to lysophosphatidylcholines in plasma differentiates healthy controls from patients with Alzheimer's disease and mild cognitive impairment.

Background: Metabolomic processes have been identified as being strongly linked to the development of Alzheimer's disease (AD). Thus, lipid metabolites appear to be highly useful as diagnostic substrates for the diagnosis of AD and mild cognitive impairment (MCI) in plasma.

Methods: We analyzed plasma samples from controls (n = 35), MCI (n = 33), and AD patients (n = 43) using the AbsoluteIDQ p180 Kit (Biocrates Life Sciences), which included quantitative analysis of 40 acylcarnitines, 21 amino acids, 19 biogenic amines, 15 sphingolipids, 90 glycerophospholipids, and sum of hexoses.

Prognostic clinical and molecular biomarkers of renal disease in type 2 diabetes.

Diabetic kidney disease occurs in ∼ 25-40% of patients with type 2 diabetes. Given the high risk of progressive renal function loss and end-stage renal disease, early identification of patients with a renal risk is important. Novel biomarkers may aid in improving renal risk stratification.

Alterations in Human Liver Metabolome during Prolonged Cryostorage.

Tissue metabolomics requires high sample quality that crucially depends on the biobanking storage protocol. Hence, we systematically analyzed the influence of realistic storage scenarios on the liver metabolome with different storage temperatures and repeated transfer of samples between storage and retrieval environments, simulating the repeated temperature changes affecting unrelated samples stored in the same container as the sample that is to be retrieved. By cycling between storage (-80 °C freezer, liquid nitrogen, cold nitrogen gas) and retrieval (room temperature, -80 °C), assuming three cycles per day and sample, we simulated biobank storage between 3 months and 10 years.

Complexity and pitfalls of mass spectrometry-based targeted metabolomics in brain research.

Current quantitative metabolomic research in brain tissue is challenged by several analytical issues. To compare data of metabolite pattern, ratios of individual metabolite concentrations and composed classifiers characterizing a distinct state, standardized workup conditions, and extraction medium are crucial. Differences in physicochemical properties of individual compounds and compound classes such as polarity determine extraction yields and, thus, ratios of compounds with varying properties.

Stereo- and regiospecificity of yeast phytases-chemical synthesis and enzymatic conversion of the substrate analogues neo- and L-chiro-inositol hexakisphosphate.

Phytases are enzymes that catalyze the hydrolysis of phosphate esters in myo-inositol hexakisphosphate (phytic acid). The precise routes of enzymatic dephosphorylation by phytases of the yeast strains Saccharomyces cerevisiae and Pichia rhodanensis have been investigated up to the myo-inositol trisphosphate level, including the absolute configuration of the intermediates. Stereoselective assignment of the myo-inositol pentakisphosphates (D-myo-inositol 1,2,4,5,6-pentakisphosphate and D-myo-inositol 1,2,3,4,5-pentakisphosphate) generated was accomplished by a new method based on enantiospecific enzymatic conversion and HPLC analysis.