Three-Dimensional Cell Metabolomics Deciphers the Anti-Angiogenic Properties of the Radioprotectant Amifostine

Modulatory effect of amifostine (WR-1065) against genotoxicity and oxidative stress induced by methotrexate in human umbilical vein endothelial cells (HUVECs)

Amifostine is used in chemotherapy and radiotherapy as a cytoprotective adjuvant alongside DNA-binding chemotherapeutic agents. It functions by reducing free radicals and detoxifying harmful metabolites. Methotrexate, as an antimetabolite drug has been considered for treating various cancers and autoimmune diseases. However, the cytotoxic effects of methotrexate extend beyond tumor cells to crucial organs, including the heart. This study applied the HUVEC cell line as a reference in vitro model for researching the characteristics of vascular endothelium and cardiotoxicity. The current study aimed to assess amifostine's potential cytoprotective properties against methotrexate-induced cellular damage. Cytotoxicity was measured using the MTT assay. Apoptotic rates were evaluated by Annexin V-FITC/PI staining via flow cytometry. The genoprotective effect of amifostine was determined using the comet assay. Cells were exposed to various amifostine doses (10-200 μg/mL) and methotrexate (2.5 μM) in pretreatment culture condition. Methotrexate at 2.5 μM revealed cytotoxicity, apoptosis, oxidative stress and genotoxicity while highlighting amifostine's cyto/geno protective properties on HUVECs. Amifostine significantly decreased the levels of ROS and LPO while preserving the status of GSH and SOD activity. Furthermore, it inhibited genotoxicity (tail length, %DNA in tail, and tail moment) in the comet assay. Amifostine markedly attenuated methotrexate-induced apoptotic cell death (early and late apoptotic rates). These findings convey that amifostine can operate as a cytoprotectant agent.

NMR-based metabolic profiling of children with premature adrenarche

INTRODUCTION

Premature adrenarche (PA) for long time was considered a benign condition but later has been connected to various diseases in childhood and adulthood which remains controversial.

OBJECTIVE

To investigate the effect of premature adrenarche on the metabolic phenotype, and correlate the clinical and biochemical data with the metabolic profile of children with PA.

METHODS

Nuclear magnetic resonance (NMR)-based untargeted and targeted metabolomic approach in combination with multivariate and univariate statistical analysis applied to study the metabolic profiles of children with PA. Plasma, serum, and urine samples were collected from fifty-two children with Idiopathic PA and forty-eight age-matched controls from the division of Pediatric Endocrinology of the University Hospital of Patras were enrolled.

RESULTS

Metabolomic results showed that plasma and serum glucose, myo-inositol, amino acids, a population of unsaturated lipids, and esterified cholesterol were higher and significantly different in PA children. In the metabolic profiles of children with PA and age-matched control group a gradual increase of glucose and myo-inositol levels was observed in serum and plasma, which was positively correlated their body mass index standard deviation score (BMI SDS) values respectively. Urine ¹H NMR metabolic fingerprint of PA children showed positive correlation and a clustering-dependent relationship with their BMI and bone age (BA) respectively.

CONCLUSION

This study provides evidence that PA driven metabolic changes begin during the childhood and PA may has an inductive role in a BMI-driven increase of specific metabolites. Finally, urine may be considered as the best biofluid for identification of the PA metabolism as it reflects more clearly the PA metabolic fingerprint.

An Automated Quantification Tool for Angiogenic Sprouting From Endothelial Spheroids

The process of sprouting angiogenesis can be measured in vitro using endothelial cells in sprouting assays such as the fibrin bead assay and the spheroid-based assay. While the technical aspects of these sprouting assays have been well-optimized, the analysis aspects have been limited to manual methods, which can be time-consuming and difficult to reproduce. Here, we developed an automated analysis tool called AQuTAS to quantify sprouting parameters from the spheroid-based sprouting assay. We trained and validated the algorithm on two subsets of data, and tested its sensitivity by measuring changes in sprouting parameters over a range of concentrations of pro- and antiangiogenic compounds. Our results demonstrate that the algorithm detects known differences in sprouting parameters in endothelial spheroids treated with pro- and antiangiogenic compounds. Moreover, it is sensitive to biological changes that are ≥40%. Among the five quantified parameters, cumulative sprout length is likely the most discriminative parameter for measuring differences in sprouting behavior because it had the highest effect size (>1.5 Cohen’s d). In summary, we have generated an automated tool that quantifies sprouting parameters from the spheroid-based assay in a reproducible and sensitive manner.

Metabolomics and health: from nutritional crops and plant-based pharmaceuticals to profiling of human biofluids

During the past decade metabolomics has emerged as one of the fastest developing branches of “-omics” technologies. Metabolomics involves documentation, identification, and quantification of metabolites through modern analytical platforms in various biological systems. Advanced analytical tools, such as gas chromatography–mass spectrometry (GC/MS), liquid chromatography–mass spectroscopy (LC/MS), and non-destructive nuclear magnetic resonance (NMR) spectroscopy, have facilitated metabolite profiling of complex biological matrices. Metabolomics, along with transcriptomics, has an influential role in discovering connections between genetic regulation, metabolite phenotyping and biomarkers identification. Comprehensive metabolite profiling allows integration of the summarized data towards manipulation of biosynthetic pathways, determination of nutritional quality markers, improvement in crop yield, selection of desired metabolites/genes, and their heritability in modern breeding. Along with that, metabolomics is invaluable in predicting the biological activity of medicinal plants, assisting the bioactivity-guided fractionation process and bioactive leads discovery, as well as serving as a tool for quality control and authentication of commercial plant-derived natural products. Metabolomic analysis of human biofluids is implemented in clinical practice to discriminate between physiological and pathological state in humans, to aid early disease biomarker discovery and predict individual response to drug therapy. Thus, metabolomics could be utilized to preserve human health by improving the nutritional quality of crops and accelerating plant-derived bioactive leads discovery through disease diagnostics, or through increasing the therapeutic efficacy of drugs via more personalized approach. Here, we attempt to explore the potential value of metabolite profiling comprising the above-mentioned applications of metabolomics in crop improvement, medicinal plants utilization, and, in the prognosis, diagnosis and management of complex diseases.