Pyruvate dehydrogenase kinase/lactate axis: a therapeutic target for neovascular age-related macular degeneration identified by metabolomics.

Neovascular age-related macular degeneration (nAMD) is the leading cause of blindness in aging populations. Here, we applied metabolomics to human sera of patients with nAMD during an active (exudative) phase of the pathology and found higher lactate levels and a shift in the lipoprotein profile (increased VLDL-LDL/HDL ratio). Similar metabolomics changes were detected in the sera of mice subjected to laser-induced choroidal neovascularization (CNV). In this experimental model, we provide evidence for two sites of lactate production: first, a local one in the injured eye, and second a systemic site associated with the recruitment of bone marrow-derived inflammatory cells. Mechanistically, lactate promotes the angiogenic response and M2-like macrophage accumulation in the eyes. The therapeutic potential of our findings is demonstrated by the pharmacological control of lactate levels through pyruvate dehydrogenase kinase (PDK) inhibition by dichloroacetic acid (DCA). Mice treated with DCA exhibited normalized lactate levels and lipoprotein profiles, and inhibited CNV formation. Collectively, our findings implicate the key role of the PDK/lactate axis in AMD pathogenesis and reveal that the regulation of PDK activity has potential therapeutic value in this ocular disease. The results indicate that the lipoprotein profile is a traceable pattern that is worth considering for patient follow-up. KEY MESSAGES: Lactate and lipoprotein profile are associated with the active phase of AMD and CNV development. Lactate is a relevant and functional metabolite correlated with AMD progression. Modulating lactate through pyruvate dehydrogenase kinase led to a decrease of CNV progression. Pyruvate dehydrogenase kinase is a new therapeutic target for neovascular AMD.

Benchtop Low-Frequency 60 MHz NMR Analysis of Urine: A Comparative Metabolomics Investigation.

Metabolomics techniques are now applied in numerous fields, with the ability to provide information concerning a large number of metabolites from a single sample in a short timeframe. Although high-frequency (HF) nuclear magnetic resonance (NMR) analysis represents a common method of choice to perform such studies, few investigations employing low-frequency (LF) NMR spectrometers have yet been published. Herein, we apply and contrast LF and HF 1H-NMR metabolomics approaches to the study of urine samples collected from type 2 diabetic patients (T2D), and apply a comparative investigation with healthy controls. Additionally, we explore the capabilities of LF 1H-1H 2D correlation spectroscopy (COSY) experiments regarding the determination of metabolites, their resolution and associated analyses in human urine samples. T2D samples were readily distinguishable from controls, with several metabolites, particularly glucose, being associated with this distinction. Comparable results were obtained with HF and LF spectrometers. Linear correlation analyses were performed to derive relationships between the intensities of 1D and 2D resonances of several metabolites, and R2 values obtained were able to confirm these, an observation attesting to the validity of employing 2D LF experiments for future applications in metabolomics studies. Our data suggest that LF spectrometers may prove to be easy-to-use, compact and inexpensive tools to perform routine metabolomics analyses in laboratories and 'point-of-care' sites. Furthermore, the quality of 2D spectra obtained from these instruments in half an hour would broaden the horizon of their potential applications.

Potential Adverse Public Health Effects Afforded by the Ingestion of Dietary Lipid Oxidation Product Toxins: Significance of Fried Food Sources.

Exposure of polyunsaturated fatty acid (PUFA)-rich culinary oils (COs) to high temperature frying practices generates high concentrations of cytotoxic and genotoxic lipid oxidation products (LOPs) via oxygen-fueled, recycling peroxidative bursts. These toxins, including aldehydes and epoxy-fatty acids, readily penetrate into fried foods and hence are available for human consumption; therefore, they may pose substantial health hazards. Although previous reports have claimed health benefits offered by the use of PUFA-laden COs for frying purposes, these may be erroneous in view of their failure to consider the negating adverse public health threats presented by food-transferable LOPs therein. When absorbed from the gastrointestinal (GI) system into the systemic circulation, such LOPs may significantly contribute to enhanced risks of chronic non-communicable diseases (NCDs), e.g. cancer, along with cardiovascular and neurological diseases. Herein, we provide a comprehensive rationale relating to the public health threats posed by the dietary ingestion of LOPs in fried foods. We begin with an introduction to sequential lipid peroxidation processes, describing the noxious effects of LOP toxins generated therefrom. We continue to discuss GI system interactions, the metabolism and biotransformation of primary lipid hydroperoxide LOPs and their secondary products, and the toxicological properties of these agents, prior to providing a narrative on chemically-reactive, secondary aldehydic LOPs available for human ingestion. In view of a range of previous studies focused on their deleterious health effects in animal and cellular model systems, some emphasis is placed on the physiological fate of the more prevalent and toxic α,ß-unsaturated aldehydes. We conclude with a description of targeted nutritional and interventional strategies, whilst highlighting the urgent and unmet clinical need for nutritional and epidemiological trials probing relationships between the incidence of NCDs, and the frequency and estimated quantities of dietary LOP intake.

Combining rapid 2D NMR experiments with novel pre-processing workflows and MIC quality measures for metabolomics.

INTRODUCTION: The use of 2D NMR data sources (COSY in this paper) allows to reach general metabolomics results which are at least as good as the results obtained with 1D NMR data, and this with a less advanced and less complex level of pre-processing. But a major issue still exists and can largely slow down a generalized use of 2D data sources in metabolomics: the experiment duration. OBJECTIVE: The goal of this paper is to overcome the experiment duration issue in our recently published MIC strategy by considering faster 2D COSY acquisition techniques: a conventional COSY with a reduced number of transients and the use of the Non-Uniform Sampling (NUS) method. These faster alternatives are all submitted to novel 2D pre-processing workflows and to Metabolomic Informative Content analyses. Eventually, results are compared to those obtained with conventional COSY spectra. METHODS: To pre-process the 2D data sources, the Global Peak List (GPL) workflow and the Vectorization workflow are used. To compare this data sources and to detect the more informative one(s), MIC (Metabolomic Informative Content) indexes are used, based on clustering and inertia measures of quality. RESULTS: Results are discussed according to a multi-factor experimental design (which is unsupervised and based on human urine samples). Descriptive PCA results and MIC indexes are shown, leading to the direct and objective comparison of the different data sets. CONCLUSION: In conclusion, it is demonstrated that conventional COSY spectra recorded with only one transient per increment and COSY spectra recorded with 50% of non-uniform sampling provide very similar MIC results as the initial COSY recorded with four transients, but in a much shorter time. Consequently, using techniques like the reduction of the number of transients or NUS can really open the door to a potential high-throughput use of 2D COSY spectra in metabolomics.

Gut Microbiota and Fecal Levels of Short-Chain Fatty Acids Differ Upon 24-Hour Blood Pressure Levels in Men.

Gut microbiota may influence blood pressure (BP), namely via end products of carbohydrate fermentation. After informed consent, male volunteers were prospectively categorized into 3 groups upon European Society of Hypertension criteria based on 24-hour ambulatory BP measurements: (1) hypertension, (2) borderline hypertension, and (3) normotension. Stool, urine and serum samples were collected in fasting conditions. Gut microbiota was characterized by 16S amplicon sequencing. Metabolomics, including quantification of short-chain fatty acids, was conducted using nuclear magnetic resonance. Two-way ANOVA combined with Tukey post hoc test, as well as multiple permutation test and Benjamini-Hochberg-Yekutieli false discovery rate procedure, was used. The cohort included 54 males: 38 hypertensive (including 21 under treatment), 7 borderline, and 9 normotensive. No significant difference was observed between groups concerning age, body mass index, smoking habits, and weekly alcohol consumption. The genus Clostridium sensu stricto 1 positively correlated with BP levels in nontreated patients (n=33). This correlation was significant after multiple permutation tests but was not substantiated following false discovery rate adjustment. Short-chain fatty acid levels were significantly different among groups, with higher stool levels of acetate, butyrate, and propionate in hypertensive versus normotensive individuals. No difference was observed in serum and urine metabolomes. Correlation between stool metabolome and 24-hour BP levels was evidenced, with R2 reaching 0.9. Our pilot study based on 24-hour ambulatory BP measurements, 16S amplicon sequencing, and metabolomics supports an association between gut microbiota and BP homeostasis, with changes in stool abundance of short-chain fatty acids.

Two data pre-processing workflows to facilitate the discovery of biomarkers by 2D NMR metabolomics.

INTRODUCTION: The pre-processing of analytical data in metabolomics must be considered as a whole to allow the construction of a global and unique object for any further simultaneous data analysis or multivariate statistical modelling. For 1D 1H-NMR metabolomics experiments, best practices for data pre-processing are well defined, but not yet for 2D experiments (for instance COSY in this paper). OBJECTIVE: By considering the added value of a second dimension, the objective is to propose two workflows dedicated to 2D NMR data handling and preparation (the Global Peak List and Vectorization approaches) and to compare them (with respect to each other and with 1D standards). This will allow to detect which methodology is the best in terms of amount of metabolomic content and to explore the advantages of the selected workflow in distinguishing among treatment groups and identifying relevant biomarkers. Therefore, this paper explores both the necessity of novel 2D pre-processing workflows, the evaluation of their quality and the evaluation of their performance in the subsequent determination of accurate (2D) biomarkers. METHODS: To select the more informative data source, MIC (Metabolomic Informative Content) indexes are used, based on clustering and inertia measures of quality. Then, to highlight biomarkers or critical spectral zones, the PLS-DA model is used, along with more advanced sparse algorithms (sPLS and L-sOPLS). RESULTS: Results are discussed according to two different experimental designs (one which is unsupervised and based on human urine samples, and the other which is controlled and based on spiked serum media). MIC indexes are shown, leading to the choice of the more relevant workflow to use thereafter. Finally, biomarkers are provided for each case and the predictive power of each candidate model is assessed with cross-validated measures of RMSEP. CONCLUSION: In conclusion, it is shown that no solution can be universally the best in every case, but that 2D experiments allow to clearly find relevant cross peak biomarkers even with a poor initial separability between groups. The MIC measures linked with the candidate workflows (2D GPL, 2D vectorization, 1D, and with specific parameters) lead to visualize which data set must be used as a priority to more easily find biomarkers. The diversity of data sources, mainly 1D versus 2D, may often lead to complementary or confirmatory results.

Transforming growth factor beta-induced, an extracellular matrix interacting protein, enhances glycolysis and promotes pancreatic cancer cell migration.

Pancreatic ductal adenocarcinoma (PDAC) remains a deadly malignancy with no efficient therapy available up-to-date. Glycolysis is the main provider of energetic substrates to sustain cancer dissemination of PDAC. Accordingly, altering the glycolytic pathway is foreseen as a sound approach to trigger pancreatic cancer regression. Here, we show for the first time that high transforming growth factor beta-induced (TGFBI) expression in PDAC patients is associated with a poor outcome. We demonstrate that, although usually secreted by stromal cells, PDAC cells synthesize and secrete TGFBI in quantity correlated with their migratory capacity. Mechanistically, we show that TGFBI activates focal adhesion kinase signaling pathway through its binding to integrin αVß5, leading to a significant enhancement of glycolysis and to the acquisition of an invasive phenotype. Finally, we show that TGFBI silencing significantly inhibits PDAC tumor development in a chick chorioallantoic membrane assay model. Our study highlights TGFBI as an oncogenic extracellular matrix interacting protein that bears the potential to serve as a target for new anti-PDAC therapeutic strategies.

CXCL12 and MYC control energy metabolism to support adaptive responses after kidney injury.

Kidney injury is a common complication of severe disease. Here, we report that injuries of the zebrafish embryonal kidney are rapidly repaired by a migratory response in 2-, but not in 1-day-old embryos. Gene expression profiles between these two developmental stages identify cxcl12a and myca as candidates involved in the repair process. Zebrafish embryos with cxcl12a, cxcr4b, or myca deficiency display repair abnormalities, confirming their role in response to injury. In mice with a kidney-specific knockout, Cxcl12 and Myc gene deletions suppress mitochondrial metabolism and glycolysis, and delay the recovery after ischemia/reperfusion injury. Probing these observations in zebrafish reveal that inhibition of glycolysis slows fast migrating cells and delays the repair after injury, but does not affect the slow cell movements during kidney development. Our findings demonstrate that Cxcl12 and Myc facilitate glycolysis to promote fast migratory responses during development and repair, and potentially also during tumor invasion and metastasis.

PepsNMR for 1H NMR metabolomic data pre-processing.

In the analysis of biological samples, control over experimental design and data acquisition procedures alone cannot ensure well-conditioned 1H NMR spectra with maximal information recovery for data analysis. A third major element affects the accuracy and robustness of results: the data pre-processing/pre-treatment for which not enough attention is usually devoted, in particular in metabolomic studies. The usual approach is to use proprietary software provided by the analytical instruments' manufacturers to conduct the entire pre-processing strategy. This widespread practice has a number of advantages such as a user-friendly interface with graphical facilities, but it involves non-negligible drawbacks: a lack of methodological information and automation, a dependency of subjective human choices, only standard processing possibilities and an absence of objective quality criteria to evaluate pre-processing quality. This paper introduces PepsNMR to meet these needs, an R package dedicated to the whole processing chain prior to multivariate data analysis, including, among other tools, solvent signal suppression, internal calibration, phase, baseline and misalignment corrections, bucketing and normalisation. Methodological aspects are discussed and the package is compared to the gold standard procedure with two metabolomic case studies. The use of PepsNMR on these data shows better information recovery and predictive power based on objective and quantitative quality criteria. Other key assets of the package are workflow processing speed, reproducibility, reporting and flexibility, graphical outputs and documented routines.

Radiotherapy-Activated Cancer-Associated Fibroblasts Promote Tumor Progression through Paracrine IGF1R Activation.

Preoperative radiotherapy (RT) is a mainstay in the management of rectal cancer, a tumor characterized by desmoplastic stroma containing cancer-associated fibroblasts (CAF). Although CAFs are abundantly present, the effects of RT to CAF and its impact on cancer cells are unknown. We evaluated the damage responses of CAF to RT and investigated changes in colorectal cancer cell growth, transcriptome, metabolome, and kinome in response to paracrine signals emerging from irradiated CAF. RT to CAF induced DNA damage, p53 activation, cell-cycle arrest, and secretion of paracrine mediators, including insulin-like growth factor-1 (IGF1). Subsequently, RT-activated CAFs promoted survival of colorectal cancer cells, as well as a metabolic switch favoring glutamine consumption through IGF1 receptor (IGF1R) activation. RT followed by IGF1R neutralization in orthotopic colorectal cancer models reduced the number of mice with organ metastases. Activation of the downstream IGF1R mediator mTOR was significantly higher in matched (intrapatient) samples and in unmatched (interpatient) samples from rectal cancer patients after neoadjuvant chemoradiotherapy. Taken together, our data support the notion that paracrine IGF1/IGF1R signaling initiated by RT-activated CAF worsens colorectal cancer progression, establishing a preclinical rationale to target this activation loop to further improve clinical responses and patient survival.Significance: These findings reveal that paracrine IGF1/IGF1R signaling promotes colorectal cancer progression, establishing a preclinical rationale to target this activation loop. Cancer Res; 78(3); 659-70. ©2017 AACR.

Methylglyoxal, a glycolysis side-product, induces Hsp90 glycation and YAP-mediated tumor growth and metastasis.

Metabolic reprogramming toward aerobic glycolysis unavoidably induces methylglyoxal (MG) formation in cancer cells. MG mediates the glycation of proteins to form advanced glycation end products (AGEs). We have recently demonstrated that MG-induced AGEs are a common feature of breast cancer. Little is known regarding the impact of MG-mediated carbonyl stress on tumor progression. Breast tumors with MG stress presented with high nuclear YAP, a key transcriptional co-activator regulating tumor growth and invasion. Elevated MG levels resulted in sustained YAP nuclear localization/activity that could be reverted using Carnosine, a scavenger for MG. MG treatment affected Hsp90 chaperone activity and decreased its binding to LATS1, a key kinase of the Hippo pathway. Cancer cells with high MG stress showed enhanced growth and metastatic potential in vivo. These findings reinforce the cumulative evidence pointing to hyperglycemia as a risk factor for cancer incidence and bring renewed interest in MG scavengers for cancer treatment.

Nuclear Magnetic Resonance Metabolomic Profiling of Mouse Kidney, Urine and Serum Following Renal Ischemia/Reperfusion Injury.

BACKGROUND: Ischemia/reperfusion (I/R) is the most common cause of acute kidney injury (AKI). Its pathophysiology remains unclear. Metabolomics is dedicated to identify metabolites involved in (patho)physiological changes of integrated living systems. Here, we performed 1H-Nuclear Magnetic Resonance metabolomics using urine, serum and kidney samples from a mouse model of renal I/R. METHODS: Renal 30-min ischemia was induced in 12-week-old C57BL/6J male mice by bilaterally clamping vascular pedicles, and was followed by 6, 24 or 48-hour reperfusion (n = 12/group). Sham-operated mice were used as controls. Statistical discriminant analyses, i.e. principal component analysis and orthogonal projections to latent structures (OPLS-DA), were performed on urine, serum and kidney lysates at each time-point. Multivariate receiver operating characteristic (ROC) curves were drawn, and sensitivity and specificity were calculated from ROC confusion matrix (with averaged class probabilities across 100 cross-validations). RESULTS: Urine OPLS-DA analysis showed a net separation between I/R and sham groups, with significant variations in levels of taurine, di- and tri-methylamine, creatine and lactate. Such changes were observed as early as 6 hours post reperfusion. Major metabolome modifications occurred at 24h post reperfusion. At this time-point, correlation coefficients between urine spectra and conventional AKI biomarkers, i.e. serum creatinine and urea levels, reached 0.94 and 0.95, respectively. The area under ROC curve at 6h, 24h and 48h post surgery were 0.73, 0.98 and 0.97, respectively. Similar discriminations were found in kidney samples, with changes in levels of lactate, fatty acids, choline and taurine. By contrast, serum OPLS-DA analysis could not discriminate sham-operated from I/R-exposed animals. CONCLUSIONS: Our study demonstrates that renal I/R in mouse causes early and sustained metabolomic changes in urine and kidney composition. The most implicated pathways at 6h and 24h post reperfusion include gluconeogenesis, taurine and hypotaurine metabolism, whereas protein biosynthesis, glycolysis, and galactose and arginine metabolism are key at 48h post reperfusion.

Nuclear magnetic resonance: a key metabolomics platform in the drug discovery process.

Metabolomics is an innovative tool that is now emerging in the drug discovery process. Indeed, its ability to follow the dynamic perturbations in the metabolome resulting from pathologies but also from drug treatment and or/toxicity is of value for the development of new therapeutic approaches. Nuclear magnetic resonance (NMR) spectroscopy, which is an important analytical technique for several steps of the lead discovery, validation and optimization processes, has been described, together with mass spectrometry (MS) as one of the major platform that could be used for metabolomics studies. This review highlights why NMR could be considered a key tool for the application of metabolomics in drug discovery.