Genetic and Metabolomic Differentiation of Physalis Ixocarpa Brot. Populations in Michoacan State, Mexico

Physalis ixocarpa Brot. is a native species that is consumed in many localities of the Cienega-Chapala in Mexico's Michoacan state. These fruits are cultivated and collected into traditional maize crops. The fruits are similar to P. Philadelphica, but the differences are in the fruit size and organoleptic properties (flavor, sweetness). According to antecedents of domestication that this zone represents in Mexico, is possible that P. ixocarpa shows incipient differentiation signals in genetic structure and metabolomic fingerprinting. Our objective was find evidences of genetic and metabolomic differentiation among populations of P. ixocarpa in the Cienega-Chapala. We used the sequencing of the chloroplast intergenic sequences psbJ – petA and trnL – rpL32, and the metabolomic fingerprinting by GC-MS. The results showed that exist genetic differentiation (FST) and signatures of selection (Fu's Fs' neutrality test) among populations. Moreover the metabolomic fingerprinting showed differences among populations and an increase of aldehydes, aromatic aldehydes, ester, and alcohols related with organoleptic properties of P. ixocarpa. We conclude that P. ixocarpa is an important genetic resource with signatures of differentiation in the Cienega-Chapala, Michoacan state, Mexico that eventually could be related with domestication signatures.

A Serum Metabolomics Classifier Derived from Elderly Patients with Metastatic Colorectal Cancer Predicts Relapse in the Adjuvant Setting

Adjuvant treatment for patients with early stage colorectal cancer (eCRC) is currently based on suboptimal risk stratification, especially for elderly patients. Metabolomics may improve the identification of patients with residual micrometastases after surgery. In this retrospective study, we hypothesized that metabolomic fingerprinting could improve risk stratification in patients with eCRC. Serum samples obtained after surgery from 94 elderly patients with eCRC (65 relapse free and 29 relapsed, after 5-years median follow up), and from 75 elderly patients with metastatic colorectal cancer (mCRC) obtained before a new line of chemotherapy, were retrospectively analyzed via proton nuclear magnetic resonance spectroscopy. The prognostic role of metabolomics in patients with eCRC was assessed using Kaplan–Meier curves. PCA-CA-kNN could discriminate the metabolomic fingerprint of patients with relapse-free eCRC and mCRC (70.0% accuracy using NOESY spectra). This model was used to classify the samples of patients with relapsed eCRC: 69% of eCRC patients with relapse were predicted as metastatic. The metabolomic classification was strongly associated with prognosis (p-value 0.0005, HR 3.64), independently of tumor stage. In conclusion, metabolomics could be an innovative tool to refine risk stratification in elderly patients with eCRC. Based on these results, a prospective trial aimed at improving risk stratification by metabolomic fingerprinting (LIBIMET) is ongoing.

Detecting the effects of predator-induced stress on the global metabolism of an ungulate prey using fecal metabolomic fingerprinting

Few field tests have assessed the effects of predator-induced stress on prey fitness, particularly in large carnivore-ungulate systems. Because traditional measures of stress present limitations when applied to free-ranging animals, new strategies and systemic methodologies are needed. Recent studies have shown that stress and anxiety related behaviors can influence the metabolic activity of the gut microbiome in mammal hosts, and these metabolic alterations may aid in identification of stress. In this study, we used NMR-based fecal metabolomic fingerprinting to compare the fecal metabolome, a functional readout of the gut microbiome, of cattle herds grazing in low vs. high wolf-impacted areas within three wolf pack territories. Additionally, we evaluated if other factors (e.g., cattle nutritional state, climate, landscape) besides wolf presence were related to the variation in cattle metabolism. By collecting longitudinal fecal samples from GPS-collared cattle, we found relevant metabolic differences between cattle herds in areas where the probability of wolf pack interaction was higher. Moreover, cattle distance to GPS-collared wolves was the factor most correlated with this difference in cattle metabolism, potentially reflecting the variation in wolf predation risk. We further validated our results through a regression model that reconstructed cattle distances to GPS-collared wolves based on the metabolic difference between cattle herds. Although further research is needed to explore if similar patterns also hold at a finer scale, our results suggests that fecal metabolomic fingerprinting is a promising tool for assessing the physiological responses of prey to predation risk. This novel approach will help improve our knowledge of the consequences of predators beyond the direct effect of predation.

Identification of Quinone Degradation as a Triggering Event for Intense Pulsed Light-Elicited Metabolic Changes in Escherichia coli by Metabolomic Fingerprinting

Intense pulsed light (IPL) is becoming a new technical platform for disinfecting food against pathogenic bacteria. Metabolic changes are deemed to occur in bacteria as either the causes or the consequences of IPL-elicited bactericidal and bacteriostatic effects. However, little is known about the influences of IPL on bacterial metabolome. In this study, the IPL treatment was applied to E. coli K-12 for 0–20 s, leading to time- and dose-dependent reductions in colony-forming units (CFU) and morphological changes. Both membrane lipids and cytoplasmic metabolites of the control and IPL-treated E. coli were examined by the liquid chromatography-mass spectrometry (LC-MS)-based metabolomic fingerprinting. The results from multivariate modeling and marker identification indicate that the metabolites in electron transport chain (ETC), redox response, glycolysis, amino acid, and nucleotide metabolism were selectively affected by the IPL treatments. The time courses and scales of these metabolic changes, together with the biochemical connections among them, revealed a cascade of events that might be initiated by the degradation of quinone electron carriers and then followed by oxidative stress, disruption of intermediary metabolism, nucleotide degradation, and morphological changes. Therefore, the degradations of membrane quinones, especially the rapid depletion of menaquinone-8 (MK-8), can be considered as a triggering event in the IPL-elicited metabolic changes in E. coli.

A Tale of Two Biomarkers: Untargeted 1H NMR Metabolomic Fingerprinting of BHBA and NEFA in Early Lactation Dairy Cows

Disorders of energy metabolism, which can result from a failure to adapt to the period of negative energy balance immediately after calving, have significant negative effects on the health, welfare and profitability of dairy cows. The most common biomarkers of energy balance in dairy cows are β-hydroxybutyrate (BHBA) and non-esterified fatty acids (NEFA). While elevated concentrations of these biomarkers are associated with similar negative health and production outcomes, the phenotypic and genetic correlations between them are weak. In this study, we used an untargeted 1H NMR metabolomics approach to investigate the serum metabolomic fingerprints of BHBA and NEFA. Serum samples were collected from 298 cows in early lactation (calibration dataset N = 248, validation N = 50). Metabolomic fingerprinting was done by regressing 1H NMR spectra against BHBA and NEFA concentrations (determined using colorimetric assays) using orthogonal partial least squares regression. Prediction accuracies were high for BHBA models, and moderately high for NEFA models (R2 of external validation of 0.88 and 0.75, respectively). We identified 16 metabolites that were significantly (variable importance of projection score > 1) correlated with the concentration of one or both biomarkers. These metabolites were primarily intermediates of energy, phospholipid, and/or methyl donor metabolism. Of the significant metabolites identified; (1) two (acetate and creatine) were positively correlated with BHBA but negatively correlated with NEFA, (2) nine had similar associations with both BHBA and NEFA, (3) two were correlated with only BHBA concentration, and (4) three were only correlated with NEFA concentration. Overall, our results suggest that BHBA and NEFA are indicative of similar metabolic states in clinically healthy animals, but that several significant metabolic differences exist that help to explain the weak correlations between them. We also identified several metabolites that may be useful intermediate phenotypes in genomic selection for improved metabolic health.