Urine metabolomics based prediction model approach for radiation exposure

Effects of 4.9 GHz Radiofrequency Field Exposure on Brain Metabolomic and Proteomic Characterization in Mice

Electromagnetic exposure has become increasingly widespread, and its biological effects have received extensive attention. The purpose of this study was to explore changes in the metabolism profile of the brain and serum and to identify differentially expressed proteins in the brain after exposure to the 4.9 GHz radiofrequency (RF) field. C57BL/6 mice were randomly divided into a Sham group and an RF group, which were sham-exposed and continuously exposed to a 4.9 RF field for 35 d, 1 h/d, at an average power density (PD) of 50 W/m2. After exposure, untargeted metabolomics and Tandem Mass Tags (TMT) quantitative proteomics were performed. We found 104 and 153 up- and down-regulated differentially expressed metabolites (DEMs) in the RF_Brain group and RF_Serum group, and the DEMs were significantly enriched in glycerophospholipid metabolism. Moreover, 10 up-regulated and 51 down-regulated differentially expressed proteins (DEPs) were discovered in the RF group. Functional correlation analysis showed that most DEMs and DEPs showed a significant correlation. These results suggested that 4.9 GHz exposure induced disturbance of metabolism in the brain and serum, and caused deregulation of proteins in the brain.

Antiurolithiatic effect of triptonide in ethylene glycol-induced urolithiasis in rats

Urolithiasis is one of the most prevalent benign urological disorders globally with a high incidence rate. Male Sprague-Dawley rats were chemically induced to have urolithiasis and treated with triptonide and the standard antiurolithic drug cystone. Kidney weight was measured to detect calculi formation, and urinary parameters such as pH, 24-h urine volume, and protein content were measured to analyze the urolithiasis induction in rats. The inorganic ions, organic solutes, antioxidant levels, and inflammatory cytokines were measured in the experimental rats. Triptonide treatment significantly modulated the urinary pH, decreased the protein concentration, and increased the urinary outflow in urolithiasis induced rats. It also significantly decreased the urinary excretion of calcium and phosphorous and increased the excretion of magnesium, potassium, sodium, creatinine, and uric acid. SOD, CAT, and GPx levels were increased in triptonide-treated rats, and it significantly reduced the MDA levels. Triptonide treatment also decreased the levels of inflammatory cytokines and prevented the renal tissue from inflammation. To conclude, our results prove that triptonide significantly prevents calculi formation and protects renal tissue from urolithiasis-induced damage in rats. Further studies may prove triptonide a potent alternative to currently available antiurolithic drugs.

Urinary metabolic profile and its predictive indexes after MSG consumption in rat

Monosodium glutamate (MSG) is a widely used food additive with conflicting evidence regarding its potential effects on human health, with proposed relevance for obesity and metabolic syndrome (MetS) or chronic kidney disease. As being able to accurately quantify the MSG dietary intake would help clarify the open issues, we constructed a predictive formula to estimate the daily intake of MSG in a rat model based on the urinary metabolic profile. Adult male Wistar rats were divided into groups receiving different daily amounts of MSG in drinking water (0.5, 1.5, and 3.0 g%), no MSG, and MSG withdrawal after 3.0% MSG treatment for 4 weeks. We then analyzed 24-hour urine samples for chemistries and metabolites using 1H NMR spectrometry and observed a strong correlation between urine pH, sodium, bicarbonate, alpha-ketoglutarate, citrate, fumarate, glutamate, methylamine, N-methyl-4-pyridone-3-carboxamide, succinate, and taurine and the daily MSG intake. Following the multiple linear regression analysis a simple formula model based on urinary Na+, citrate, and glutamate was most accurate and could be validated for estimating daily MSG intake. In conclusion, we propose that the daily MSG intake correlates with urinary metabolites in a rat model and that this new tool for monitoring the impact of MSG on health measures.

Impact of Partial Body Shielding from Very High Dose Rates on Untargeted Metabolomics in Biodosimetry

A realistic exposure to ionizing radiation (IR) from an improvised nuclear device will likely include individuals who are partially shielded from the initial blast delivered at a very high dose rate (VHDR). As different tissues have varying levels of radiosensitivity, e.g., hematopoietic vs gastrointestinal tissues, the effects of shielding on radiation biomarkers need to be addressed. Here, we explore how biofluid (urine and serum) metabolite signatures from male and female C57BL/6 mice exposed to VHDR (5-10 Gy/s) total body irradiation (TBI, 0, 4, and 8 Gy) compare to individuals exposed to partial body irradiation (PBI) (lower body irradiated [LBI] or upper body irradiated [UBI] at an 8 Gy dose) using a data-independent acquisition untargeted metabolomics approach. Although sex differences were observed in the spatial groupings of urine signatures from TBI and PBI mice, a metabolite signature (N6,N6,N6-trimethyllysine, carnitine, propionylcarnitine, hexosamine-valine-isoleucine, taurine, and creatine) previously developed from variable dose rate experiments was able to identify individuals with high sensitivity and specificity, irrespective of radiation shielding. A panel of serum metabolites composed from previous untargeted studies on nonhuman primates had excellent performance for separating irradiated cohorts; however, a multiomic approach to complement the metabolome could increase dose estimation confidence intervals. Overall, these results support the inclusion of small-molecule markers in biodosimetry assays without substantial interference from the upper or lower body shielding.

Unraveling biomarkers of exposure for tenuazonic acid through urinary metabolomics

Mycotoxins are secondary metabolites produced by fungi such as Aspergillus, Alternaria, and Penicillium, affecting nearly 80% of global food crops. Tenuazonic acid (TeA) is the major mycotoxin produced by Alternaria alternata, a prevalent pathogen affecting plants, fruits, and vegetables. TeA is notably prevalent in European diets, however, TeA biomarkers of exposure and metabolites remain unknown. This research aims to bridge this knowledge-gap by gaining insights about human TeA exposure and metabolization. Nine subjects were divided into two groups. The first group received a single bolus of TeA at the Threshold of Toxicological Concern (TTC) to investigate the presence of TeA urinary biomarkers, while the second group served as a control. Sixty-nine urinary samples were prepared and analyzed using UPLC-Xevo TQ-XS for TeA quantification and UPLC-Orbitrap Exploris for polar metabolome acquisition. TeA was rapidly excreted during the first 13 h and the fraction extracted was 0.39 ± 0.22. The polar metabolome compounds effectively discriminating the two groups were filtered using Orthogonal Partial Least Squares-Discriminant Analysis and subsequently annotated (n = 122) at confidence level 4. Finally, the urinary metabolome was compared to in silico predicted TeA metabolites. Nine metabolites, including oxidized, N-alkylated, desaturated, glucuronidated, and sulfonated forms of TeA were detected.

Applications of photodynamic therapy in extramammary Paget's disease

Extramammary Paget's disease (EMPD) is a rare form of adenocarcinoma usually found in apocrine gland-containing cutaneous regions. EMPD affects the vulvar area most commonly, followed by the perianal area, scrotum, penis, and axillary region. In its initial form, EMPD presents as an erythematous plaque with well-defined edges, fine scaling, excoriations, exulcerations, and lichenification. Generally, a definitive diagnosis can be made through histopathological analysis. Importantly, associated malignancies should be investigated prior to treatment initiation. Photodynamic therapy (PDT) is a modern, noninvasive treatment strategy for non-oncological diseases as well as various cancers. In recent years, PDT has been widely used to treat EMPD. This present article presents a discussion of the diagnosis and treatment of EMPD as well as the usefulness of PDT in its management.

Metabolomics and transcriptomics based multi-omics integration reveals radiation-induced altered pathway networking and underlying mechanism

Recent advancement in integrated multi-omics has significantly contributed to many areas of the biomedical field. Radiation research has also grasped uprising omics technologies in biomarker identification to aid in triage management. Herein, we have used a combinatorial multi-omics approach based on transcriptomics together with metabolomics and lipidomics of blood from murine exposed to 1 Gy (LD) and 7.5 Gy (HD) of total-body irradiation (TBI) for a comprehensive understanding of biological processes through integrated pathways and networking. Both omics displayed demarcation of HD group from controls using multivariate analysis. Dysregulated amino acids, various PC, PE and carnitine were observed along with many dysregulated genes (Nos2, Hmgcs2, Oxct2a, etc.). Joint-Pathway Analysis and STITCH interaction showed radiation exposure resulted in changes in amino acid, carbohydrate, lipid, nucleotide, and fatty acid metabolism. Elicited immune response was also observed by Gene Ontology. BioPAN has predicted Elovl5, Elovl6 and Fads2 for fatty acid pathways, only in HD group. Collectively, the combined omics approach facilitated a better understanding of processes uncovering metabolic pathways. Presumably, this is the first in radiation metabolomics that utilized an integrated omics approach following TBI in mice. Our work showed that omics integration could be a valuable tool for better comprehending the mechanism as well as molecular interactions.

Variable Dose Rates in Realistic Radiation Exposures: Effects on Small Molecule Markers of Ionizing Radiation in the Murine Model

Novel biodosimetry assays for use in preparedness and response to potential malicious attacks or nuclear accidents would ideally provide accurate dose reconstruction independent of the idiosyncrasies of a complex exposure to ionizing radiation. Complex exposures will consist of dose rates spanning the low dose rates (LDR) to very high-dose rates (VHDR) that need to be tested for assay validation. Here, we investigate how a range of relevant dose rates affect metabolomic dose reconstruction at potentially lethal radiation exposures (8 Gy in mice) from an initial blast or subsequent fallout exposures compared to zero or sublethal exposures (0 or 3 Gy in mice) in the first 2 days, which corresponds to an integral time individuals will reach medical facilities after a radiological emergency. Biofluids (urine and serum) were collected from both male and female 9-10-week-old C57BL/6 mice at 1 and 2 days postirradiation (total doses of 0, 3 or 8 Gy) after a VHDR of 7 Gy/s. Additionally, samples were collected after a 2-day exposure consisting of a declining dose rate (1 to 0.004 Gy/min) recapitulating the 7:10 rule-of-thumb time dependency of nuclear fallout. Overall similar perturbations were observed in both urine and serum metabolite concentrations irrespective of sex or dose rate, with the exception of xanthurenic acid in urine (female specific) and taurine in serum (VHDR specific). In urine, we developed identical multiplex metabolite panels (N6, N6,N6-trimethyllysine, carnitine, propionylcarnitine, hexosamine-valine-isoleucine, and taurine) that could identify individuals receiving potentially lethal levels of radiation from the zero or sublethal cohorts with excellent sensitivity and specificity, with creatine increasing model performance at day 1. In serum, individuals receiving a 3 or 8 Gy exposure could be identified from their pre-irradiation samples with excellent sensitivity and specificity, however, due to a lower dose response the 3 vs. 8 Gy groups could not be distinguished from each other. Together with previous results, these data indicate that dose-rate-independent small molecule fingerprints have potential in novel biodosimetry assays.

Statistical methods and resources for biomarker discovery using metabolomics

Metabolomics is a dynamic tool for elucidating biochemical changes in human health and disease. Metabolic profiles provide a close insight into physiological states and are highly volatile to genetic and environmental perturbations. Variation in metabolic profiles can inform mechanisms of pathology, providing potential biomarkers for diagnosis and assessment of the risk of contracting a disease. With the advancement of high-throughput technologies, large-scale metabolomics data sources have become abundant. As such, careful statistical analysis of intricate metabolomics data is essential for deriving relevant and robust results that can be deployed in real-life clinical settings. Multiple tools have been developed for both data analysis and interpretations. In this review, we survey statistical approaches and corresponding statistical tools that are available for discovery of biomarkers using metabolomics.

Using Multivariate Data Analysis to Project Performance in Biathletes and Cross-Country Skiers

PURPOSE

To determine whether competitive performance, as defined by International Biathlon Union (IBU) and International Ski Federation (FIS) points in biathlon and cross-country (XC) skiing, respectively, can be projected using a combination of anthropometric and physiological metrics. Shooting accuracy was also included in the biathlon models.

METHODS

Data were analyzed using multivariate methods from 45 (23 female and 22 male) biathletes and 202 (86 female and 116 male) XC skiers who were all members of senior national teams, national development teams, or ski-university or high school invite-only programs (age range: 16-36 y). Anthropometric and physiological characteristics were assessed via dual-energy X-ray absorptiometry and incremental roller-ski treadmill tests, respectively. Shooting accuracy was assessed via an outdoor standardized testing protocol.

RESULTS

Valid projective models were identified for female biathletes' IBU points (R2 = .80/Q2 = .65) and female XC skiers' FIS distance (R2 = .81/Q2 = .74) and sprint (R2 = .81/Q2 = .70) points. No valid models were identified for the men. The most important variables for the projection of IBU points were shooting accuracy, speeds at blood lactate concentrations of 4 and 2 mmol·L-1, peak aerobic power, and lean mass. The most important variables for the projection of FIS distance and sprint points were speeds at blood lactate concentrations of 4 and 2 mmol·L-1 and peak aerobic power.

CONCLUSIONS

This study highlights the relative importance of specific anthropometric, physiological, and shooting-accuracy metrics in female biathletes and XC skiers. The data can help to identify the specific metrics that should be targeted when monitoring athletes' progression and designing training plans.

The Current Status of Photodynamic Therapy in Cancer Treatment

Although we have made great strides in treating deadly diseases over the years, cancer therapy still remains a daunting challenge. Among numerous anticancer methods, photodynamic therapy (PDT), a non-invasive therapeutic approach, has attracted much attention. PDT exhibits outstanding performance in cancer therapy, but some unavoidable disadvantages, including limited light penetration depth, poor tumor selectivity, as well as oxygen dependence, largely limit its therapeutic efficiency for solid tumors treatment. Thus, numerous strategies have gone into overcoming these obstacles, such as exploring new photosensitizers with higher photodynamic conversion efficiency, alleviating tumor hypoxia to fuel the generation of reactive oxygen species (ROS), designing tumor-targeted PS, and applying PDT-based combination strategies. In this review, we briefly summarized the PDT related tumor therapeutic approaches, which are mainly characterized by advanced PSs, these PSs have excellent conversion efficiency and additional refreshing features. We also briefly summarize PDT-based combination therapies with excellent therapeutic effects.

Exploration of urinary metabolite dynamicity for early detection of pregnancy in water buffaloes

Early and precise pregnancy diagnosis can reduce the calving interval by minimizing postpartum period. The present study explored the differential urinary metabolites between pregnant and non-pregnant Murrah buffaloes (Bubalus bubalis) during early gestation to identify potential pregnancy detection biomarkers. Urine samples were collected on day 0, 10, 18, 35 and 42 of gestation from the pregnant (n = 6) and on day 0, 10 and 18 post-insemination from the non-pregnant (n = 6) animals. ¹H-NMR-based untargeted metabolomics followed by multivariate analysis initially identified twenty-four differentially expressed metabolites, among them 3-Hydroxykynurenine, Anthranilate, Tyrosine and 5-Hydroxytryptophan depicted consistent trends and matched the selection criteria of potential biomarkers. Predictive ability of these individual biomarkers through ROC curve analyses yielded AUC values of 0.6–0.8. Subsequently, a logistic regression model was constructed using the most suitable metabolite combination to improve diagnostic accuracy. The combination of Anthranilate, 3-Hydroxykynurenine, and Tyrosine yielded the best AUC value of 0.804. Aromatic amino acid biosynthesis, Tryptophan metabolism, Phenylalanine and Tyrosine metabolism were identified as potential pathway modulations during early gestation. The identified biomarkers were either precursors or products of these metabolic pathways, thus justifying their relevance. The study facilitates precise non-invassive urinary metabolite-based pen-side early pregnancy diagnostics in buffaloes, eminently before 21 days post-insemination.

LC-MS-based metabolomics reveals metabolic changes in short- and long-term administration of Compound Danshen Dripping Pills against acute myocardial infarction in rats

BACKGROUND

Mild and systematically improving multiple metabolic disorders was a focused view for Compound Danshen Dripping Pills playing synergistic effects through multiple components and multiple targets. The difference in overall therapeutic effects and endogenous metabolic regulation between short- and long-term administration was still unclear.

PURPOSE

This study aimed to explore the difference in endogenous metabolic regulation between short- and long-term Compound Danshen Dripping Pills (CDDP) administration against acute myocardial infarction (AMI).

METHODS

The model of AMI was induced by ligating the left anterior descending coronary artery. The cardiac protection effects of CDDP were investigated by echocardiography, 1- or 2-week were defined as short- and long-term based on desirable efficacy variability. The entire metabolic changes between short- and long-term administration of CDDP were profiled by UPLC-Q-TOF-MS. In addition, the metabolic regulatory network of CDDP administration against myocardial infarction rats was also compared with those of a typical chemical drug isosorbide 5-mononitrate (ISMN).

RESULTS

After 1- or 2-week continuous oral administration, CDDP could significantly alleviate AMI-induced cardiac dysfunction. By using LC-MS-based metabolomics analyses, we systematically investigated the metabolic profiles of plasma and heart tissue samples at fixed exposure time-points (2 h, 24 h) from AMI rats with CDDP treatment. Most interestingly, global endogenous metabolic changes were observed in cardiac samples collected at different stages post consecutive CDDP administration, fluctuating at 2 and 24 h after 1 week but stabilizing after 2 weeks. The disrupted metabolic pathways such as glycerophospholipid, amino acids, fatty acids, and arachidonic acid metabolism were reconstructed after both short- and long-term CDDP treatment, while taurine and hypotaurine metabolism and purine metabolism contributed to the whole efficacy after long-term CDDP administration.

CONCLUSION

Long-term CDDP treatment plays prolonged and stable efficacy against AMI compared with short-term treatment by specifically regulating purine and taurine and hypotaurine metabolism and systematically redressing metabolic disorders.

Metabolomics as a valid analytical technique in environmental exposure research: application and progress

BACKGROUND

In recent years, studies have shown that exposure to environmental pollutants (e.g., radiation, heavy metal substances, air pollutants, organic pollutants) is a leading cause of human non-communicable diseases. The key to disease prevention is to clarify the harmful mechanisms and toxic effects of environmental pollutants on the body. Metabolomics is a high-sensitivity, high-throughput omics technology that can obtain detailed metabolite information of an organism. It is a crucial tool for gaining a comprehensive understanding of the pathway network regulation mechanism of the organism. Its application is widespread in many research fields such as environmental exposure assessment, medicine, systems biology, and biomarker discovery.

AIM OF REVIEW

Recent findings show that metabolomics can be used to obtain molecular snapshots of organisms after environmental exposure, to help understand the interaction between environmental exposure and organisms, and to identify potential biomarkers and biological mechanisms.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review focuses on the application of metabolomics to understand the biological effects of radiation, heavy metals, air pollution, and persistent organic pollutants exposure, and examines some potential biomarkers and toxicity mechanisms.

Urinary metabolic modulation in human participants residing in Siachen: a 1H NMR metabolomics approach

The main physiological challenge in high altitude environment is hypoxia which affects the aerobic metabolism reducing the energy supply. These changes may further progress toward extreme environment-related diseases. These are further reflected in changes in small molecular weight metabolites and metabolic pathways. In the present study, metabolic changes due to chronic environmental hypoxia were assessed using 1H NMR metabolomics by analysing the urinary metabolic profile of 70 people at sea level and 40 people at Siachen camp (3700 m) for 1 year. Multivariate statistical analysis was carried out, and PLSDA detected 15 metabolites based on VIP score > 1. ROC analysis detected cis-aconitate, Nicotinamide Mononucleotide, Tyrosine, Choline and Creatinine metabolites with a high range of sensitivity and specificity. Pathway analysis revealed 16 pathways impact > 0.05, and phenylalanine tyrosine and tryptophan biosynthesis was the most prominent altered pathway indicating metabolic remodelling to meet the energy requirements. TCA cycle, Glycine serine and Threonine metabolism, Glutathione metabolism and Cysteine alterations were other metabolic pathways affected during long-term high-altitude hypoxia exposure. Present findings will help unlock a new dimension for the potential application of NMR metabolomics to address extreme environment-related health problems, early detection and developing strategies to combat high altitude hypoxia.

Studies on Metabolic Alterations due to Hypobaric Hypoxia in Serum using NMR Spectroscopy

Introduction The main physiological challenge in high altitude environment is hypoxia which affects the aerobic metabolism reducing the energy supply. These changes may further progress towards extreme environment related diseases. Rarely has the high-altitude biology been studied using system sciences and omics high-throughput technologies.Objective In the present study, 1H-NMR-based metabolomics, along with multivariate analysis, were employed in a preclinical rat model to characterize the serum metabolic changes under chronic hypobaric hypoxia (HH) stress.Material & Methods Rats were exposed to simulated hypobaric hypoxia equivalent of 6700 m above the sea level. The serum samples were collected from control and HH-exposure (7, 14, and 21 days) of hypobaric hypoxia.Results & Discussion The 1H-NMR metabolomics of the serum showed alterations in the metabolism of membranes, amino-acids altered cellular bioenergetics and osmoregulation. Multivariate statistical analysis revealed alterations in acetoacetate, choline, glutamine, acetate, betaine, ketone bodies & branched amino acid metabolites.Conclusion Present findings establishes the fingerprint biomarkers for chronic environmental hypoxia which will help in understanding extreme environment related health problems, early detection and developing strategies to clinically address high altitude hypoxia.

The Association of Urine Creatinine With Kidney Stone Prevalence in US Adults: Data From NHANES 2009-2018

Background

The primary objective of this project is to explore the association of urine creatinine (UCR) with the prevalence rate of kidney stones.

Method

The National Health and Nutrition Examination Survey (NHANES) database was employed to conduct a cross-sectional study. The analysis samples included adults aged ≥20 years from five consecutive cycles of the NHANES 2009–2018. The association between UCR and kidney stones was detected using univariate and multivariate logistic regression analyses. Further, subgroup analyses were performed to evaluate the subgroup effects.

Results

After adjustment for all confounders, multiple logistic regression analysis revealed a weak positive relationship between UCR and kidney stone (OR = 1.015, 95% CI: 1.008–1.021). In the subgroup analysis stratified by sex, age, or race, the risk further increased in men (OR = 1.014, 95% CI: 1.005–1.023), women (OR = 1.015, 95% CI: 1.005–1.025), white race (OR = 1.022, 95% CI: 1.013–1.030), aged 40–59 years (OR = 1.017, 95% CI: 1.006–1.028), and aged 60–80 years (OR = 1.017, 95% CI: 1.006–1.028).

Conclusions

Our results confirmed a moderately increased risk of kidney stone formation attributed to high levels of UCR, especially in middle-aged and older adults and the white race. However, because of the cross-sectional design of the study, causal inferences cannot be made.

An integrative chemometric approach and correlative metabolite networking of LC-MS and 1H NMR based urine metabolomics for radiation signatures

The increasing threat of nuclear terrorism or radiological accident has made high throughput radiation biodosimetry a requisite for the immediate response for triage. Owing to detection of subtle alterations in biological pathways before the onset of clinical conditions, metabolomics has become an important tool for studying biomarkers and the related mechanisms for radiation induced damage. Here, we have attempted to combine two detection techniques, LC-MS and ¹H NMR spectroscopy, to obtain a comprehensive metabolite profile of urine at 24 h following lethal (7.5 Gy) and sub-lethal (5 Gy) irradiation in mice. Integrated data analytics using multiblock-OPLSDA (MB-OPLSDA), correlation networking and pathway analysis was used to identify metabolic disturbances associated with radiation exposure. MB-OPLSDA revealed better clustering and separation of irradiated groups compared with controls without overfitting (p-value of CV-ANOVA: 1.5 × 10^-3). Metabolites identified through MB-OPLSDA, namely, taurine, creatine, citrate and 2-oxoglutarate, were found to be dose independent markers and further support and validate our earlier findings as potential radiation injury biomarkers. Integrated analysis resulted in the enhanced coverage of metabolites and better correlation networking in energy, taurine, gut flora, L-carnitine and nucleotide metabolism observed post irradiation in urine. Our study thus emphasizes the major advantage of using the two detection techniques along with integrated analysis for better detection and comprehensive understanding of disturbed metabolites in biological pathways.

1H-NMR Metabolomics as a Tool for Winemaking Monitoring

The chemical composition of wine is known to be influenced by multiple factors including some viticulture practices and winemaking processes. 1H-NMR metabolomics has been successfully applied to the study of wine authenticity. In the present study, 1H-NMR metabolomics in combination with multivariate analysis was applied to investigate the effects of grape maturity and enzyme and fining treatments on Cabernet Sauvignon wines. A total of forty wine metabolites were quantified. Three different stages of maturity were studied (under-maturity, maturity and over-maturity). Enzyme treatments were carried out using two pectolytic enzymes (E1 and E2). Finally, two proteinaceous fining treatments were compared (vegetable protein, fining F1; pea protein and PVPP, fining F2). The results show a clear difference between the three stages of maturity, with an impact on different classes of metabolites including amino acids, organic acids, sugars, phenolic compounds, alcohols and esters. A clear separation between enzymes E1 and E2 was observed. Both fining agents had a significant effect on metabolite concentrations. The results demonstrate that 1H-NMR metabolomics provides a fast and robust approach to study the effect of winemaking processes on wine metabolites. These results support the interest to pursue the development of 1H-NMR metabolomics to investigate the effects of winemaking on wine quality.

Biofluid Metabolomics of Mice Exposed to External Low-Dose Rate Radiation in a Novel Irradiation System, the Variable Dose-Rate External 137Cs Irradiator

An important component of ionizing radiation (IR) exposure after a radiological incident may include low-dose rate (LDR) exposures either externally or internally, such as from ¹³⁷Cs deposition. In this study, a novel irradiation system, VAriable Dose-rate External ¹³⁷Cs irradiatoR (VADER), was used to expose male and female mice to a variable LDR irradiation over a 30 d time span to simulate fall-out-type exposures in addition to biofluid collection from a reference dose rate (0.8 Gy/min). Radiation markers were identified by untargeted metabolomics and random forests. Mice exposed to LDR exposures were successfully identified from control groups based on their urine and serum metabolite profiles. In addition to metabolites commonly perturbed after IR exposure, we identified and validated a novel metabolite (hexosamine-valine-isoleucine-OH) that increased up to 150-fold after LDR and 80-fold after conventional exposures in urine. A multiplex panel consisting of hexosamine-valine-isoleucine-OH with other urinary metabolites (N6,N6,N6-trimethyllysine, carnitine, 1-methylnicotinamide, and α-ketoglutaric acid) achieved robust classification performance using receiver operating characteristic curve analysis, irrespective of the dose rate or sex. These results show that in terms of biodosimetry, dysregulated energy metabolism is associated with IR exposure for both LDR and conventional IR exposures. These mass spectrometry data have been deposited to the NIH data repository via Metabolomics Workbench with study IDs ST001790, ST001791, ST001792, ST001793, and ST001806.

Radiation exposure induces cross-species temporal metabolic changes that are mitigated in mice by amifostine

Exposure to acute, damaging radiation may occur through a variety of events from cancer therapy and industrial accidents to terrorist attacks and military actions. Our understanding of how to protect individuals and mitigate the effects of radiation injury or Acute Radiation Syndrome (ARS) is still limited. There are only a few Food and Drug Administration-approved therapies for ARS; whereas, amifostine is limited to treating low dose (0.7-6 Gy) radiation poisoning arising from cancer radiotherapy. An early intervention is critical to treat ARS, which necessitates identifying diagnostic biomarkers to quickly characterize radiation exposure. Towards this end, a multiplatform metabolomics study was performed to comprehensively characterize the temporal changes in metabolite levels from mice and non-human primate serum samples following γ-irradiation. The metabolomic signature of amifostine was also evaluated in mice as a model for radioprotection. The NMR and mass spectrometry metabolomics analysis identified 23 dysregulated pathways resulting from the radiation exposure. These metabolomic alterations exhibited distinct trajectories within glucose metabolism, phospholipid biosynthesis, and nucleotide metabolism. A return to baseline levels with amifostine treatment occurred for these pathways within a week of radiation exposure. Together, our data suggests a unique physiological change that is independent of radiation dose or species. Furthermore, a metabolic signature of radioprotection was observed through the use of amifostine prophylaxis of ARS.