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The emergence of the threat of radiological terrorism and other radiological incidents has led to the need for development of fast, accurate and noninvasive methods for detection of radiation exposure. The purpose of this study was to extend radiation metabolomic biomarker discovery to humans, as previous studies have focused on mice. Urine was collected from patients undergoing total body irradiation at Memorial Sloan-Kettering Cancer Center prior to hematopoietic stem cell transplantation at 4-6 h postirradiation (a single dose of 1.25 Gy) and 24 h (three fractions of 1.25 Gy each). Global metabolomic profiling was obtained through analysis with ultra performance liquid chromatography coupled to time-of-flight mass spectrometry (TOFMS). Prior to further analyses, each sample was normalized to its respective creatinine level. Statistical analysis was conducted by the nonparametric Kolmogorov-Smirnov test and the Fisher's exact test and markers were validated against pure standards. Seven markers showed distinct differences between pre- and post-exposure samples. Of those, trimethyl-l-lysine and the carnitine conjugates acetylcarnitine, decanoylcarnitine and octanoylcarnitine play an important role in the transportation of fatty acids across mitochondria for subsequent fatty acid β-oxidation. The remaining metabolites, hypoxanthine, xanthine and uric acid are the final products of the purine catabolism pathway, and high levels of excretion have been associated with increased oxidative stress and radiation induced DNA damage. Further analysis revealed sex differences in the patterns of excretion of the markers, demonstrating that generation of a sex-specific metabolomic signature will be informative and can provide a quick and reliable assessment of individuals in a radiological scenario. This is the first radiation metabolomics study in human urine laying the foundation for the use of metabolomics in biodosimetry and providing confidence in biomarker identification based on the overlap between animal models and humans.

Administration of hormonal compounds as growth promoters in livestock farming was banned by Council Directive 93/22/EC, however, this kind of substances are sometimes reported within the framework of European monitoring residue plans. Various analytical methods have been previously developed to screen for their misuse, and they are now especially efficient for monitoring the illegal administration of synthetic and semi-synthetic hormones. Nevertheless, proving an exogenous administration of hormones from natural origin (i.e. estradiol-17β or progesterone) still remains a challenging task for European authorities. As a result of their origin, these target compounds are indeed always present in the analytical matrix, and because the concentration levels of natural steroids are extremely variable from one animal to another, the establishment of reference thresholds appears very difficult. During this preliminary study, metabolomic data was acquired on a high performance liquid chromatography system coupled to high resolution mass spectrometer (HPLC-LTQ-Orbitrap). Serum samples were collected from dairy cows treated or not with sex steroid hormones commonly employed in animal husbandry: estradiol-17β (or its ester estradiol benzoate) and progesterone. After appropriate data processing and multivariate statistical analyses (OPLS-DA), it was possible to highlight significant metabolic modifications in serum consecutively to the administration of estradiol and/or progesterone. Those differences were used to build predictive models able to suspect illegal administration of these hormones in cattle. Potential biomarker candidates of estradiol and/or progesterone were pointed out, that remains to be structurally elucidated., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Evidence of the continuous rise of novel doping agents and novel doping strategies calls for the development of more accurate multi-target screening methods. Direct multi-target screening approaches are restricted to the targeted substances and their turnover. The development of effective "indirect" screening methods requires a priori a deep understanding of the metabolism of the substance. The biological passport has been demonstrated to be very effective, but it is limited to about 20 indirect parameters. The standard antidoping analytical methods are hence targeted and do not aim directly to identify unknown substances. Also, the detection of doping agents is limited by the excretion of the substance. This study considers metabolomics for the screening of performance enhancing hormone abuse by athletes, based on the following pieces of evidence: (1) hormones have a strong influence on human metabolism, changing several parameters in many tissues, organs, and bio-fluids; (2) metabolomics has been demonstrated to be a very accurate tool to depict the metabolic status of several organisms, tissues, and for several human diseases, including hormone deficiencies; (3) metabolomics has been demonstrated to be able to distinguish hormone-treated animals from controls in many species, without the need for a priori knowledge of the metabolism for the specific substance. The literature shows that metabolomics could be an appropriate tool to detect hormone abuse, keeping in mind the strength and the limitation of such an approach., (© 2020 John Wiley & Sons, Ltd.)

Bloodstains found at crime scenes contain immense information about the crime; thus, studies involving analysis of small molecules in bloodstains have been conducted. However, most of these studies have not accounted for the difference in the results of small molecule analysis due to the surface of bloodstains. To evaluate the "surface effect," we prepared bloodstains on seven surfaces, including both absorbent and non-absorbent surfaces, and performed global small molecule analysis by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). We used three indicators: (1) count recovery rate (%) of molecular features (MFs), (2) the number of MFs extracted from the surface without bloodstains, and (3) difference in abundance recovery rate (%) of MFs, to determine the ranking of the seven surfaces in the order of their similarity with blood. We also confirmed the correlation between each surface and blood through multivariate analysis. We found that the non-absorbent surfaces ranked better than the absorbent surfaces; wooden flooring was ranked as the most efficient surface, followed by stainless, vinyl flooring, glass, tile, filter paper, and mixed cotton. This study will help in the selection of the most efficient surface for collection of bloodstains for small molecule analysis from a crime scene. This is the first study to identify the effects of surface on extraction of global small molecules from bloodstains; it will help forensic scientists in obtaining more accurate information from small molecules present in the bloodstains collected at the field. Graphical abstract.

Advancements in the Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS) along with recent developments in omics sciences have resulted in a better understanding of molecular mechanisms and pathways associated with the physio-pathological state of the animal. Metabolomics is a post-genomics tool that deals with small molecular metabolites in a given set of time which provides clear information about the status of an organism. Recently many researchers mainly focus their research on metabolomics studies due to its valuable information in the various fields of livestock management and precision dairying. The main aim of the present review is to provide an insight into the current research output from different sources and application of metabolomics in various areas of livestock including nutri-metabolomics, disease diagnosis advancements, reproductive disorders, pharmaco-metabolomics, genomics studies, and dairy production studies. The present review would be helpful in understanding the metabolomics methodologies and use of livestock metabolomics in various areas in a brief way. [ABSTRACT FROM AUTHOR]

The lung has raised significant concerns because of its radiosensitivity. Radiation-induced lung injury (RILI) has a serious impact on the quality of patients' lives and limits the effect of radiotherapy on chest tumors. In clinical practice, effective drug intervention for RILI remains to be fully elucidated. Therefore, an in-depth understanding of the biological characteristics is essential to reveal the mechanisms underlying the complex biological processes and discover novel therapeutic targets in RILI. In this study, Wistar rats received 0, 10, 20 or 35 Gy whole-thorax irradiation (WTI). Lung and plasma samples were collected within 5 days post-irradiation. Then, these samples were processed using liquid chromatography–mass spectrometry (LC-MS). A panel of potential plasma metabolic markers was selected by correlation analysis between the lung tissue and plasma metabolic features, followed by the evaluation of radiation injury levels within 5 days following whole-thorax irradiation (WTI). In addition, the multiple metabolic dysregulations primarily involved amino acids, bile acids and lipid and fatty acid β-oxidation-related metabolites, implying disturbances in the urea cycle, intestinal flora metabolism and mitochondrial dysfunction. In particular, the accumulation of long-chain acylcarnitines (ACs) was observed as early as 2 d post-WTI by dynamic plasma metabolic data analysis. Our findings indicate that plasma metabolic markers have the potential for RILI assessment. These results reveal metabolic characteristics following WTI and provide new insights into therapeutic interventions for RILI. [ABSTRACT FROM AUTHOR]

Epidemiological studies have indicated that exposure of the heart to doses of ionizing radiation as low as 0.5 Gy increases the risk of cardiac morbidity and mortality with a latency period of decades. The damaging effects of radiation to myocardial and endothelial structures and functions have been confirmed radiobiologically at high dose, but much less are known at low dose. Integration of radiation biology and epidemiology data is a recommended approach to improve the radiation risk assessment process. The adverse outcome pathway (AOP) framework offers a comprehensive tool to compile and translate mechanistic information into pathological endpoints which may be relevant for risk assessment at the different levels of a biological system. Omics technologies enable the generation of large volumes of biological data at various levels of complexity, from molecular pathways to functional organisms. Given the quality and quantity of available data across levels of biology, omics data can be attractive sources of information for use within the AOP framework. It is anticipated that radiation omics studies could improve our understanding of the molecular mechanisms behind the adverse effects of radiation on the cardiovascular system. In this review, we explored the available omics studies on radiation-induced cardiovascular disease (CVD) and their applicability to the proposed AOP for CVD. The results of 80 omics studies published on radiation-induced CVD over the past 20 years have been discussed in the context of the AOP of CVD proposed by Chauhan et al. Most of the available omics data on radiation-induced CVD are from proteomics, transcriptomics, and metabolomics, whereas few datasets were available from epigenomics and multi-omics. The omics data presented here show great promise in providing information for several key events (KEs) of the proposed AOP of CVD, particularly oxidative stress, alterations of energy metabolism, extracellular matrix (ECM), and vascular remodeling. The omics data presented here shows promise to inform the various levels of the proposed AOP of CVD. However, the data highlight the urgent need of designing omics studies to address the knowledge gap concerning different radiation scenarios, time after exposure, and experimental models. This review presents the evidence to build a qualitative omics-informed AOP and provides views on the potential benefits and challenges in using omics data to assess risk-related outcomes. [ABSTRACT FROM AUTHOR]

With the development of radiation metabolomics, a large number of radiation-related metabolic biomarkers have been identified and validated. The L-carnitine and acylcarnitines have the potential to be the new promising candidate indicators of radiation exposure. This review summarizes the effect of carnitine shuttle system on the profile of acylcarnitines and correlates the radiation effects on upstream regulators of carnitine shuttle system with the change characteristics of L-carnitine and acylcarnitines after irradiation across different animal models as well as a few humans. Studies report that acylcarnitines were ubiquitously elevated after irradiation, especially the free L-carnitine and short-chain acylcarnitines (C2–C5). However, the molecular mechanism underlying acylcarnitine alterations after irradiation is not fully investigated, and further studies are needed to explore the biological effect and its mechanism. The activity of the carnitine shuttle system plays a key role in the alteration of L-carnitine and acylcarnitines, and the upstream regulators of the system are known to be affected by irradiation. These evidences indicate that that there is a logistic role of carnitine shuttle system on radiation-induced L-carnitine and acylcarnitines alteration. [ABSTRACT FROM AUTHOR]

Rationale: This work demonstrates the high potential of combining high-resolution mass spectrometry with chemometric tools, using metabolomics as a guided tool for anti-doping analysis. The administration of 7-keto-DHEA was studied as a proofof-concept of the effectiveness of the combination of knowledge-based and machine-learning approaches to differentiate the changes due to the athletic activities from those due to the recourse to doping substances and methods. Methods: Urine samples were collected from five healthy volunteers before and after an oral administration by identifying three time intervals. Raw data were acquired by injecting less than 1 μL of derivatized samples into a model 8890 gas chromatograph coupled to a model 7250 accurate-mass quadrupole time-of-flight analyzer (both from Agilent Technologies), by using a low-energy electron ionization source; the samples were then preprocessed to align peak retention times with the same accurate mass. The resulting data table was subjected to multivariate analysis. Results: Multivariate analysis showed a high similarity between the samples belonging to the same collection interval and a clear separation between the different excretion intervals. The discrimination between blank and long excretion groups may suggest the presence of long excretion markers, which are particularly significant in anti-doping analysis. Furthermore, matching the most significant features with some of the metabolites reported in the literature data demonstrated the rationality of the proposed metabolomics-based approach. Conclusions: The application of metabolomics tools as an investigation strategy could reduce the time and resources required to identify and characterize intake markers maximizing the information that can be extracted from the data and extending the research field by avoiding a priori bias. Therefore, metabolic fingerprinting of prohibited substance intakes could be an appropriate analytical approach to reduce the risk of false-positive/negative results, aiding in the interpretation of "abnormal" profiles and discrimination of pseudo-endogenous steroid intake in the anti-doping field. [ABSTRACT FROM AUTHOR]

Purpose: The possibility of a large-scale acute radiation exposure necessitates the development of new methods that could provide a rapid assessment of the doses received by individuals using high-throughput technologies. There is also a great interest in developing new biomarkers of dose exposure, which could be used in large molecular epidemiological studies in order to correlate estimated doses received and health effects. The goal of this review was to summarize current literature focused on biological dosimetry, namely radiation-responsive biomarkers. Methods: The studies involved in this review were thoroughly selected according to the determined criteria and PRISMA guidelines. Results: We described briefly recent advances in radiation genomics and metabolomics, giving particular emphasis to proteomic analysis. The majority of studies were performed on animal models (rats, mice, and non-human primates). They have provided much beneficial information, but the most relevant tests have been done on human (oncological) patients. By inspecting the radiaiton biodosimetry literate of the last 10 years, we identified a panel of candidate markers for each –omic approach involved. Conslusions: We reviewed different methodological approaches and various biological materials, which can be exploited for dose-effect prediction. The protein biomarkers from human plasma are ideal for this specific purpose. From a plethora of candidate markers, FDXR is a very promising transcriptomic candidate, and importantly this biomarker was also confirmed by some studies at protein level in humans. [ABSTRACT FROM AUTHOR]

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common form of cancer worldwide. Radiotherapy, with or without surgery, represents the major approach to curative treatment. However, not all tumors are equally sensitive to irradiation. It is therefore of interest to apply newer system biology approaches (e.g., metabolic profiling) in squamous cancer cells with different radiosensitivities in order to provide new insights on the mechanisms of radiation response. In this study, two cultured HNSCC cell lines from the same donor, UM-SCC-74A and UM-SCC-74B, were first genotyped using Short Tandem Repeat (STR), and assessed for radiation response by the means of clonogenic survival and growth inhibition assays. Thereafter, cells were cultured, irradiated and collected for subsequent metabolic profiling analyses using liquid chromatography-mass spectrometry (LC-MS). STR verified the similarity of UM-SCC-74A and UM-SCC-74B cells, and three independent assays proved UM-SCC-74B to be clearly more radioresistant than UM-SCC-74A. The LC-MS metabolic profiling demonstrated significant differences in the intracellular metabolome of the two cell lines before irradiation, as well as significant alterations after irradiation. The most important differences between the two cell lines before irradiation were connected to nicotinic acid and nicotinamide metabolism and purine metabolism. In the more radiosensitive UM-SCC-74A cells, the most significant alterations after irradiation were linked to tryptophan metabolism. In the more radioresistant UM-SCC-74B cells, the major alterations after irradiation were connected to nicotinic acid and nicotinamide metabolism, purine metabolism, the methionine cycle as well as the serine, and glycine metabolism. The data suggest that the more radioresistant cell line UM-SCC-74B altered the metabolism to control redox-status, manage DNA-repair, and change DNA methylation after irradiation. This provides new insights on the mechanisms of radiation response, which may aid future identification of biomarkers associated with radioresistance of cancer cells. [ABSTRACT FROM AUTHOR]

Threats of nuclear terrorism coupled with potential unintentional ionizing radiation exposures have necessitated the need for large-scale response efforts of such events, including high-throughput biodosimetry for medical triage. Global metabolomics utilizing mass spectrometry (MS) platforms has proven an ideal tool for generating large compound databases with relative quantification and structural information in a short amount of time. Determining metabolite panels for biodosimetry requires experimentation to evaluate the many factors associated with compound concentrations in biofluids after radiation exposures, including temporal changes, pre-existing conditions, dietary intake, partial- vs. total-body irradiation (TBI), among others. Here, we utilize a nonhuman primate (NHP) model and identify metabolites perturbed in serum after 7.2 Gy TBI without supportive care [LD70/60, hematologic (hematopoietic) acute radiation syndrome (HARS) level H3] at 24, 36, 48 and 96 h compared to preirradiation samples with an ultra-performance liquid chromatography quadrupole time-of-flight (UPLC-QTOF) MS platform. Additionally, we document changes in cytokine levels. Temporal changes observed in serum carnitine, acylcarnitines, amino acids, lipids, deaminated purines and increases in pro-inflammatory cytokines indicate clear metabolic dysfunction after radiation exposure. Multivariate data analysis shows distinct separation from preirradiation groups and receiver operator characteristic curve analysis indicates high specificity and sensitivity based on area under the curve at all time points after 7.2 Gy irradiation. Finally, a comparison to a 6.5 Gy (LD50/60, HARS level H2) cohort after 24 h postirradiation revealed distinctly increased separations from the 7.2 Gy cohort based on multivariate data models and higher compound fold changes. These results highlight the utility of MS platforms to differentiate time and absorbed dose after a potential radiation exposure that may aid in assigning specific medical interventions and contribute as additional biodosimetry tools. [ABSTRACT FROM AUTHOR]

In the European Union, the use of thyreostats for animal fattening purposes has been banned and monitoring plans have been established to detect potential abuse. However, this is not always straightforward as thyreostats such as thiouracil may also have a semi-endogenous origin. Therefore, this study aimed at defining urinary metabolites, which may aid in defining the origin of detected thiouracil. Hereto, a parallel-like randomized in vivo study was conducted in which calves (n = 8) and cows (n = 8) were subjected to either a control treatment, rapeseed-enriched diet to induce semi-endogenous formation, or thiouracil treatment. Urine samples (n = 330) were assessed through metabolic fingerprinting, employing liquid-chromatography and Q-ExactiveTM Orbitrap mass spectrometry. Urinary fingerprints comprised up to 40,000 features whereby multivariate discriminant analysis was able to point out significant metabolome differences between treatments (Q2(Y) ≥ 0.873). Using the validated models, a total of twelve metabolites (including thiouracil) were assigned marker potential. Combining these markers into age-dependent biomarker panels rendered a tool by which sample classification could be improved in comparison with thiouracil-based thresholds, and this during on-going thiouracil treatment (specificities ≥ 95.2% and sensitivities ≥ 85.7%), post-treatment (sensitivities ≥ 80% for ≥ 24 h after last administration), and simulated low-dose thiouracil treatment (exogenous thiouracil below 30 ng μL-1). Moreover, the metabolic relevance of revealed markers was supported by the suggested identities, for which a structural link with thiouracil could be determined in most cases. The proposed biomarker panels may contribute to a more justified decision-making in monitoring thiouracil abuse. [ABSTRACT FROM AUTHOR]

Purpose: Exposure of the general population to ionizing radiation has increased in the past decades, primarily due to long distance travel and medical procedures. On the other hand, accidental exposures, nuclear accidents, and elevated threats of terrorism with the potential detonation of a radiological dispersal device or improvised nuclear device in a major city, all have led to increased needs for rapid biodosimetry and assessment of exposure to different radiation qualities and scenarios. Metabolomics, the qualitative and quantitative assessment of small molecules in a given biological specimen, has emerged as a promising technology to allow for rapid determination of an individual's exposure level and metabolic phenotype. Advancements in mass spectrometry techniques have led to untargeted (discovery phase, global assessment) and targeted (quantitative phase) methods not only to identify biomarkers of radiation exposure, but also to assess general perturbations of metabolism with potential long-term consequences, such as cancer, cardiovascular, and pulmonary disease. Conclusions: Metabolomics of radiation exposure has provided a highly informative snapshot of metabolic dysregulation. Biomarkers in easily accessible biofluids and biospecimens (urine, blood, saliva, sebum, fecal material) from mouse, rat, and minipig models, to non-human primates and humans have provided the basis for determination of a radiation signature to assess the need for medical intervention. Here we provide a comprehensive description of the current status of radiation metabolomic studies for the purpose of rapid high-throughput radiation biodosimetry in easily accessible biofluids and discuss future directions of radiation metabolomics research. [ABSTRACT FROM AUTHOR]

Introduction: Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites. Objectives: In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting. Methods: The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces. Results: A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed. Conclusion: The workflow generated repeatable and informative fingerprints for robust metabolome characterization. [ABSTRACT FROM AUTHOR]

Metabolomic analysis of easily accessible biofluids has provided numerous biomarkers in urine and blood for biodosimetric purposes. In this pilot study we assessed saliva for its utility in biodosimetry using a mouse model. Mice were exposed to 0.5, 3 and 8 Gy total-body gamma irradiation and saliva was collected on day 1 and 7 postirradiation. Global metabolomic profiling was conducted through liquid chromatography mass spectrometry and metabolites were positively identified using tandem mass spectrometry. Multivariate data analysis revealed distinct metabolic profiles for all groups at day 1, whereas at day 7 the two lower dose profiles appeared to have minimal differences. Metabolites that were identified include amino acids and fatty acids, and intermediates of the nicotinate and nicotinamide metabolism. The specificity and sensitivity of the radiation signature, as expected, was higher for the 8 Gy dose at both time points, as determined through generation of receiver operating characteristic curves. To the best of our knowledge, this is the first metabolomics study in saliva of irradiated mice to demonstrate the utility of this biofluid as a potential matrix for identification of radiation and dose-specific biomarkers. [ABSTRACT FROM AUTHOR]

Introduction: Due to dangers associated with potential accidents from nuclear energy and terrorist threats, there is a need for high-throughput biodosimetry to rapidly assess individual doses of radiation exposure. Lipidomics and metabolomics are becoming common tools for determining global signatures after disease or other physical insult and provide a 'snapshot' of potential cellular damage. Objectives: The current study assesses changes in the nonhuman primate (NHP) serum lipidome and metabolome 7 days following exposure to ionizing radiation (IR). Methods: Serum sample lipids and metabolites were extracted using a biphasic liquid-liquid extraction and analyzed by ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry. Global radiation signatures were acquired in data-independent mode. Results: Radiation exposure caused significant perturbations in lipid metabolism, affecting all major lipid species, including free fatty acids, glycerolipids, glycerophospholipids and esterified sterols. In particular, we observed a significant increase in the levels of polyunsaturated fatty acids (PUFA)-containing lipids in the serum of NHPs exposed to 10 Gy radiation, suggesting a primary role played by PUFAs in the physiological response to IR. Metabolomics profiling indicated an increase in the levels of amino acids, carnitine, and purine metabolites in the serum of NHPs exposed to 10 Gy radiation, suggesting perturbations to protein digestion/absorption, biological oxidations, and fatty acid β-oxidation. Conclusions: This is the first report to determine changes in the global NHP serum lipidome and metabolome following radiation exposure and provides information for developing metabolomic biomarker panels in human-based biodosimetry. [ABSTRACT FROM AUTHOR]

Human exposure to ionizing radiation (IR) disrupts normal metabolic processes in cells and organs by inducing complex biological responses that interfere with gene and protein expression. Conventional dosimetry, monitoring of prodromal symptoms, and peripheral lymphocyte counts are of limited value as organ- and tissue-specific biomarkers for personnel exposed to radiation, particularly, weeks or months after exposure. Analysis of metabolites generated in known stress-responsive pathways by molecular profiling helps to predict the physiological status of an individual in response to environmental or genetic perturbations. Thus, a multi-metabolite profile obtained from a high-resolution mass spectrometry-based metabolomics platform offers potential for identification of robust biomarkers to predict radiation toxicity of organs and tissues resulting from exposures to therapeutic or non-therapeutic IR. Here, we review the status of radiation metabolomics and explore applications as a standalone technology, as well as its integration in systems biology, to facilitate a better understanding of the molecular basis of radiation response. Finally, we draw attention to the identification of specific pathways that can be targeted for the development of therapeutics to alleviate or mitigate harmful effects of radiation exposure. [ABSTRACT FROM AUTHOR]

Due to concerns surrounding potential large-scale radiological events, there is a need to determine robust radiation signatures for the rapid identification of exposed individuals, which can then be used to guide the development of compact field deployable instruments to assess individual dose. Metabolomics provides a technology to process easily accessible biofluids and determine rigorous quantitative radiation biomarkers with mass spectrometry (MS) platforms. While multiple studies have utilized murine models to determine radiation biomarkers, limited studies have profiled nonhuman primate (NHP) metabolic radiation signatures. In addition, these studies have concentrated on short-term biomarkers (i.e., <72 h). The current study addresses the need for biomarkers beyond 72 h using a NHP model. Urine samples were collected at 7 days postirradiation (2, 4, 6, 7 and 10 Gy) and processed with ultra-performance liquid chromatography (UPLC) quadrupole time-of-flight (QTOF) MS, acquiring global metabolomic radiation signatures. Multivariate data analysis revealed clear separation between control and irradiated groups. Thirteen biomarkers exhibiting a dose response were validated with tandem MS. There was significantly higher excretion of l-carnitine, l-acetylcarnitine, xanthine and xanthosine in males versus females. Metabolites validated in this study suggest perturbation of several pathways including fatty acid β oxidation, tryptophan metabolism, purine catabolism, taurine metabolism and steroid hormone biosynthesis. In this novel study we detected long-term biomarkers in a NHP model after exposure to radiation and demonstrate differences between sexes using UPLC-QTOF-MS-based metabolomics technology. [ABSTRACT FROM AUTHOR]

The applications of metabolomics as a methodology for providing better treatment and understanding human disease continue to expand rapidly. In this review, covering the last two years, the focus is on liquid chromatography-mass spectrometry (LC-MS) profiling of metabolites in urine. In LC-MS based metabolomics there are still problems with regard to: chromatographic separation, peak picking and alignment, metabolite identification, metabolite coverage, instrument sensitivity and data interpretation and in the case of urine sample normalisation. Progress has been made with regard to all of these issues during the period of the review. Of particular interest are the increasing use of orthogonal chromatographic methods for optimal metabolite coverage and the increasing adoption of receiver operator characteristic (ROC) curves for biomarker validation. [ABSTRACT FROM AUTHOR]

A study was performed to determine if untargeted metabolomics of urine could be used to establish a predictive tool for identifying β-agonists misuse in cattle. Although prohibited for more than 20 years within the EU, growth promoting practices for livestock fattening purposes are still suspected. Methods based on gas- or liquid chromatography coupled to (tandem) mass spectrometry are today considered as the state-of-the-art to monitor, in a targeted approach, residues of known drugs. To overcome the detection of anabolic practices, new synthetic xenobiotic growth promoters have been designed and new ways of applications, such as the administration of low dose cocktails, have been developed. In this context, innovative screening strategies are urgently needed to enable efficient control of such practices. Omic technologies have recently shown their relevance in highlighting physiological response resulting from anabolic compounds administration. LC-HRMS based metabolomics is one of the approaches allowing profiling biological matrices to reveal biological effects of a drug. In the present work, a metabolomics study performed on urine samples collected in the frame of several independent experiments involving different animals, different β-agonists treatments and different parameters (doses, compounds mixture, treatment length), allowed highlighting biomarkers of interest and implementing a robust statistical model to predict for β-agonists treated bovines. Performances of the proposed model fit with EU requirements for screening methods. [ABSTRACT FROM AUTHOR]

As space travel is expanding to include private tourism and travel beyond low-Earth orbit, so is the risk of exposure to space radiation. Galactic cosmic rays and solar particle events have the potential to expose space travelers to significant doses of radiation that can lead to increased cancer risk and other adverse health consequences. Metabolomics has the potential to assess an individual's risk by exploring the metabolic perturbations in a biofluid or tissue. In this study, C57BL/6 mice were exposed to 0.5 and 2 Gy of 1 GeV/nucleon of protons and the levels of metabolites were evaluated in urine at 4 h after radiation exposure through liquid chromatography coupled to time-of-flight mass spectrometry. Significant differences were identified in metabolites that map to the tricarboxylic acid (TCA) cycle and fatty acid metabolism, suggesting that energy metabolism is severely impacted after exposure to protons. Additionally, various pathways of amino acid metabolism (tryptophan, tyrosine, arginine and proline and phenylalanine) were affected with potential implications for DNA damage repair and cognitive impairment. Finally, presence of products of purine and pyrimidine metabolism points to direct DNA damage or increased apoptosis. Comparison of these metabolomic data to previously published data from our laboratory with gamma radiation strongly suggests a more pronounced effect on metabolism with protons. This is the first metabolomics study with space radiation in an easily accessible biofluid such as urine that further investigates and exemplifies the biological differences at early time points after exposure to different radiation qualities. [ABSTRACT FROM AUTHOR]

The use of anabolic agents in meat producing animals is forbidden in Europe since 1988. Nevertheless, the possibility of widespread abuse of hormonal substances still exists, mainly due to economical benefits. The use of 'omics' approach is a promising strategy to highlight anabolic hormone abuse by indirectly detecting their physiological action. In this context, the aim of this work was to set up a liquid chromatography - high resolution mass spectrometry based metabolomics workflow for the screening of a combined trenbolone acetate/estradiol implant abuse in cattle urine. Therefore, an untargeted metabolomics approach combining the information provided by reverse-phase liquid chromatography and hydrophilic interaction chromatography both coupled to high resolution mass spectrometry was developed and applied to characterize and compare cattle urinary metabolic profiles from non-implanted and implanted animals. The combination of both separation modes improved the metabolite information richness. Discrimination between treated and untreated animals was observed by application of multivariate statistical analysis. Moreover, OPLS models permitted to highlight the candidate biomarkers appearing as the ions which contribute the most in the observed discrimination. From the results obtained, metabolomics approaches can be considered as a powerful strategy for the detection of fraudulent anabolic treatments in cattle since global urinary metabolic response provides helpful discrimination. [ABSTRACT FROM AUTHOR]

Simple Summary: Exosomes could be used as biomarkers to predict and monitor the response to anti-cancer treatment, yet relevant knowledge is very limited in the case of rectal cancer. Here we applied a combined proteomic and metabolomic approach to reveal exosome components connected with different responses to neoadjuvant radiotherapy in this group of patients and processes associated with identified discriminatory molecules. Moreover, the composition of serum-derived exosomes and a whole plasma was analyzed in parallel to compare the biomarker potential of both specimens, which revealed the highest capacity of exosome proteome to discriminate samples of patients with different responses to radiotherapy. Identification of biomarkers that could be used for the prediction of the response to neoadjuvant radiotherapy (neo-RT) in locally advanced rectal cancer remains a challenge addressed by different experimental approaches. Exosomes and other classes of extracellular vesicles circulating in patients' blood represent a novel type of liquid biopsy and a source of cancer biomarkers. Here, we used a combined proteomic and metabolomic approach based on mass spectrometry techniques for studying the molecular components of exosomes isolated from the serum of rectal cancer patients with different responses to neo-RT. This allowed revealing several proteins and metabolites associated with common pathways relevant for the response of rectal cancer patients to neo-RT, including immune system response, complement activation cascade, platelet functions, metabolism of lipids, metabolism of glucose, and cancer-related signaling pathways. Moreover, the composition of serum-derived exosomes and a whole serum was analyzed in parallel to compare the biomarker potential of both specimens. Among proteins that the most properly discriminated good and poor responders were GPLD1 (AUC = 0.85, accuracy of 74%) identified in plasma as well as C8G (AUC = 0.91, accuracy 81%), SERPINF2 (AUC = 0.91, accuracy 79%) and CFHR3 (AUC = 0.90, accuracy 81%) identified in exosomes. We found that the proteome component of serum-derived exosomes has the highest capacity to discriminate samples of patients with different responses to neo-RT when compared to the whole plasma proteome and metabolome. We concluded that the molecular components of exosomes are associated with the response of rectal cancer patients to neo-RT and could be used for the prediction of such response. [ABSTRACT FROM AUTHOR]

Simple Summary: Radical hemithoracic radiotherapy represents a promising new advance in the field of radiation oncology and encouraging results have been achieved in the treatment of malignant pleural mesothelioma patients. This study showed that this radiotherapy modality produces significant changes in serum metabolomics profile mainly affecting arginine and polyamine biosynthesis pathways. Interestingly, individual metabolomics alterations were found associated with the clinical overall survival outcome of the radiotherapy treatment. These results highlight metabolomics profile analysis as a powerful prognostic tool useful to better understand the mechanisms underlying the interpatients variability and to identify patients who may receive the best benefit from this specific radiotherapy treatment. Radical hemithoracic radiotherapy (RHRT) represents an advanced therapeutic option able to improve overall survival of malignant pleural mesothelioma patients. This study aims to investigate the systemic effects of this radiotherapy modality on the serum metabolome and their potential implications in determining the individual clinical outcome. Nineteen patients undergoing RHRT at the dose of 50 Gy in 25 fractions were enrolled. Serum targeted metabolomics profiles were investigated at baseline and the end of radiotherapy by liquid chromatography and tandem mass spectrometry. Univariate and multivariate OPLS-DA analyses were applied to study the serum metabolomics changes induced by RHRT while PLS regression analysis to evaluate the association between such changes and overall survival. RHRT was found to affect almost all investigated metabolites classes, in particular, the amino acids citrulline and taurine, the C14, C18:1 and C18:2 acyl-carnitines as well as the unsaturated long chain phosphatidylcholines PC ae 42:5, PC ae 44:5 and PC ae 44:6 were significantly decreased. The enrichment analysis showed arginine metabolism and the polyamine biosynthesis as the most perturbed pathways. Moreover, specific metabolic changes encompassing the amino acids and acyl-carnitines resulted in association with the clinical outcome accounting for about 60% of the interpatients overall survival variability. This study highlighted that RHRT can induce profound systemic metabolic effects some of which may have a significant prognostic value. The integration of metabolomics in the clinical assessment of the malignant pleural mesothelioma could be useful to better identify the patients who can achieve the best benefit from the RHRT treatment. [ABSTRACT FROM AUTHOR]

Triage and medical intervention strategies for unanticipated exposure during a radiation incident benefit from the early, rapid and accurate assessment of dose level. Radiation exposure results in complex and persistent molecular and cellular responses that ultimately alter the levels of many biological markers, including the metabolomic phenotype. Metabolomics is an emerging field that promises the determination of radiation exposure by the qualitative and quantitative measurements of small molecules in a biological sample. This review highlights the current role of metabolomics in assessing radiation injury, as well as considerations for the diverse range of bioanalytical and sampling technologies that are being used to detect these changes. The authors also address the influence of the physiological status of an individual, the animal models studied, the technology and analysis employed in interrogating response to the radiation insult, and variables that factor into discovery and development of robust biomarker signatures. Furthermore, available databases for these studies have been reviewed, and existing regulatory guidance for metabolomics are discussed, with the ultimate goal of providing both context for this area of radiation research and the consideration of pathways for continued development. [ABSTRACT FROM AUTHOR]

Anticancer treatment induces systemic molecular changes that could be detected at the level of biofluids. Understanding how human metabolism is influenced by these treatments is crucial to predict the individual response and adjust personalized therapies. Here, we aimed to compare profiles of metabolites in serum of head and neck cancer patients treated with concurrent chemo-radiotherapy, radiotherapy alone, or induction chemotherapy. Serum samples were analyzed by a targeted quantitative approach using combined direct flow injection and liquid chromatography coupled to tandem mass spectrometry, which allowed simultaneous quantification of 149 metabolites. There were 45 metabolites whose levels were significantly changed between pretreatment and within- or post-treatment serum samples, including 38 phospholipids. Concurrent chemo-radiotherapy induced faster and stronger effects than radiotherapy alone. On the other hand, chemotherapy alone did not result in significant changes. The decreased level of total phospholipids was the most apparent effect observed during the first step of the treatment. This corresponded to the loss of patients' body mass, yet no correlation between both parameters was observed for individual patients. We concluded that different molecular changes were measured at the level of serum metabolome in response to different treatment modalities. [ABSTRACT FROM AUTHOR]

Whole body exposure to ionizing radiation damages tissues leading to physical symptoms which contribute to acute radiation syndrome. Radiation biodosimetry aims to determine characteristic early biomarkers indicative of radiation exposure and is necessary for effective triage after an unanticipated radiological incident. Radiation metabolomics can address this aim by assessing metabolic perturbations following exposure. Gas chromatography–mass spectrometry (GC-MS) is a standardized platform ideal for compound identification. We performed GC time-of-flight MS for the global profiling of nonhuman primate urine and serum samples up to 60 d after a single 4 Gy γ-ray total body exposure. Multivariate statistical analysis showed higher group separation in urine vs. serum. We identified biofluid markers involved in amino acid, lipid, purine, and serotonin metabolism, some of which may indicate host microbiome dysbiosis. Sex differences were observed for amino acid fold changes in serum samples. Additionally, we explored mitochondrial dysfunction by tricarboxylic acid intermediate analysis in the first week with a GC tandem quadrupole MS platform. By adding this temporal component to our previous work exploring dose effects at 7 d, we observed the highest fold changes occurring at 3 d, returning closer to basal levels by 7 d. These results emphasize the utility of both MS-based metabolomics for biodosimetry and complementary analytical platforms for increased metabolome coverage. [ABSTRACT FROM AUTHOR]

In this study, we elucidate that polyamine metabolite is a powerful biomarker to study post-radiation changes. Metabolomics in radiation biodosimetry, the application of a metabolomics analysis to the field of radiobiology, promises to increase the understanding of biological responses by ionizing radiation (IR). Radiation exposure triggers a complex network of molecular and cellular responses that impacts metabolic processes and alters the levels of metabolites. Such metabolites have potential as biomarkers for radiation dosimetry. Among metabolites, polyamine is one of many potential biomarkers to estimate radiation response. In addition, this review provides an opportunity for the understanding of a radiation metabolomics in biodosimetry and a polyamine case study. [ABSTRACT FROM AUTHOR]

We have detected differences in metabolite levels between doped athletes, clean athletes, and volunteers (non athletes). This outcome is obtained by comparing results of measurements from two analytical platforms: UHPLC-QTOF/MS and FT-ICR/MS. Twenty-seven urine samples tested positive for glucocorticoids or beta-2-agonists and twenty samples coming from volunteers and clean athletes were analyzed with the two different mass spectrometry approaches using both positive and negative electrospray ionization modes. Urine is a highly complex matrix containing thousands of metabolites having different chemical properties and a high dynamic range. We used multivariate analysis techniques to unravel this huge data set. Thus, the several groups we created were studied by Principal Components Analysis (PCA) and Partial Least Square regression (PLS-DA and OPLS) in the search of discriminating m/z values. The selected variables were annotated and placed on pathway by using MassTRIX. [ABSTRACT FROM AUTHOR]