Identification of sensitive and specific biomarkers with clinical and translational utility will require smart experimental strategies that would augment expanding the breadth and depth of molecular measurements within the constraints of currently available technologies. Exosomes represent an information rich matrix to discern novel disease mechanisms that are thought to contribute to pathologies such as dementia and cancer. Although proteomics and transcriptomic studies have been reported using Exosomes-Like Vesicles (ELVs) from different sources, exosomal metabolome characterization and its modulation in health and disease remains to be elucidated. Here we describe methodologies for UPLC-ESI-MS based small molecule profiling of ELVs from human plasma and cell culture media. In this study, we present evidence that indeed ELVs carry a rich metabolome that could not only augment the discovery of low abundance biomarkers but may also help explain the molecular basis of disease progression. This approach could be easily translated to other studies seeking to develop predictive biomarkers that can subsequently be used with simplified targeted approaches.

BackgroundSpace travel is associated with continuous low dose rate exposure to high linear energy transfer (LET) radiation. Pathophysiological manifestations after low dose radiation exposure are strongly influenced by non-cytocidal radiation effects, including changes in the microbiome and host gene expression. Although the importance of the gut microbiome in the maintenance of human health is well established, little is known about the role of radiation in altering the microbiome during deep-space travel.ResultsUsing a mouse model for exposure to high LET radiation, we observed substantial changes in the composition and functional potential of the gut microbiome. These were accompanied by changes in the abundance of multiple metabolites, which were related to the enzymatic activity of the predicted metagenome by means of metabolic network modeling. There was a complex dynamic in microbial and metabolic composition at different radiation doses, suggestive of transient, dose-dependent interactions between microbial ecology and signals from the host’s cellular damage repair processes. The observed radiation-induced changes in microbiota diversity and composition were analyzed at the functional level. A constitutive change in activity was found for several pathways dominated by microbiome-specific enzymatic reactions like carbohydrate digestion and absorption and lipopolysaccharide biosynthesis, while the activity in other radiation-responsive pathways like phosphatidylinositol signaling could be linked to dose-dependent changes in the abundance of specific taxa.ConclusionsThe implication of microbiome-mediated pathophysiology after low dose ionizing radiation may be an unappreciated biologic hazard of space travel and deserves experimental validation. This study provides a conceptual and analytical basis of further investigations to increase our understanding of the chronic effects of space radiation on human health, and points to potential new targets for intervention in adverse radiation effects.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-017-0325-z) contains supplementary material, which is available to authorized users.

Endometrial cancer (EC) remains the most common malignancy of the genital tract among women in developed countries. Although much research has been performed at genomic, transcriptomic and proteomic level, there is still a significant gap in the metabolomic studies of EC. In order to gain insights into altered metabolic pathways in the onset and progression of EC carcinogenesis, we used high resolution mass spectrometry to characterize the metabolomic and lipidomic profile of 39 human EC and 17 healthy endometrial tissue samples. Several pathways including lipids, Kynurenine pathway, endocannabinoids signaling pathway and the RNA editing pathway were found to be dysregulated in EC. The dysregulation of the RNA editing pathway was further investigated in an independent set of 183 human EC tissues and matched controls, using orthogonal approaches. We found that ADAR2 is overexpressed in EC and that the increase in expression positively correlates with the aggressiveness of the tumor. Furthermore, silencing of ADAR2 in three EC cell lines resulted in a decreased proliferation rate, increased apoptosis, and reduced migration capabilities in vitro. Taken together, our results suggest that ADAR2 functions as an oncogene in endometrial carcinogenesis and could be a potential target for improving EC treatment strategies.

Serum metabolite profiling in Duchenne muscular dystrophy (DMD) may enable discovery of valuable molecular markers for disease progression and treatment response. Serum samples from 51 DMD patients from a natural history study and 22 age-matched healthy volunteers were profiled using liquid chromatography coupled to mass spectrometry (LC-MS) for discovery of novel circulating serum metabolites associated with DMD. Fourteen metabolites were found significantly altered (1% false discovery rate) in their levels between DMD patients and healthy controls while adjusting for age and study site and allowing for an interaction between disease status and age. Increased metabolites included arginine, creatine and unknown compounds at m/z of 357 and 312 while decreased metabolites included creatinine, androgen derivatives and other unknown yet to be identified compounds. Furthermore, the creatine to creatinine ratio is significantly associated with disease progression in DMD patients. This ratio sharply increased with age in DMD patients while it decreased with age in healthy controls. Overall, this study yielded promising metabolic signatures that could prove useful to monitor DMD disease progression and response to therapies in the future.

Rapid assessment of radiation signatures in non-invasive biofluids may aid in assigning proper medical treatments for acute radiation syndrome (ARS) and delegating limited resources after a nuclear disaster. Metabolomic platforms allow for rapid screening of biofluid signatures and show promise in differentiating radiation quality and time postexposure. Here, we use global metabolomics to differentiate temporal effects (1-60 d) found in nonhuman primate (NHP) urine and serum small molecule signatures after a 4 Gy total body irradiation. Random Forests analysis differentially classifies biofluid signatures according to days post 4 Gy exposure. Eight compounds involved in protein metabolism, fatty acid β oxidation, DNA base deamination, and general energy metabolism were identified in each urine and serum sample and validated through tandem MS. The greatest perturbations were seen at 1 d in urine and 1-21 d in serum. Furthermore, we developed a targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) with multiple reaction monitoring (MRM) method to quantify a six compound panel (hypoxanthine, carnitine, acetylcarnitine, proline, taurine, and citrulline) identified in a previous training cohort at 7 d after a 4 Gy exposure. The highest sensitivity and specificity for classifying exposure at 7 d after a 4 Gy exposure included carnitine and acetylcarnitine in urine and taurine, carnitine, and hypoxanthine in serum. Receiver operator characteristic (ROC) curve analysis using *