Host microbiome depletion attenuates biofluid metabolite responses following radiation exposure

Development of novel biodosimetry assays and medical countermeasures is needed to obtain a level of radiation preparedness in the event of malicious or accidental mass exposures to ionizing radiation (IR). For biodosimetry, metabolic profiling with mass spectrometry (MS) platforms has identified several small molecules in easily accessible biofluids that are promising for dose reconstruction. As our microbiome has profound effects on biofluid metabolite composition, it is of interest how variation in the host microbiome may affect metabolomics based biodosimetry. Here, we 'knocked out' the microbiome of male and female C57BL/6 mice (Abx mice) using antibiotics and then irradiated (0, 3, or 8 Gy) them to determine the role of the host microbiome on biofluid radiation signatures (1 and 3 d urine, 3 d serum). Biofluid metabolite levels were compared to a sham and irradiated group of mice with a normal microbiome (Abx-con mice). To compare post-irradiation effects in urine, we calculated the Spearman's correlation coefficients of metabolite levels with radiation dose. For selected metabolites of interest, we performed more detailed analyses using linear mixed effect models to determine the effects of radiation dose, time, and microbiome depletion. Serum metabolite levels were compared using an ANOVA. Several metabolites were affected after antibiotic administration in the tryptophan and amino acid pathways, sterol hormone, xenobiotic and bile acid pathways (urine) and lipid metabolism (serum), with a post-irradiation attenuative effect observed for Abx mice. In urine, dose×time interactions were supported for a defined radiation metabolite panel (carnitine, hexosamine-valine-isoleucine [Hex-V-I], creatine, citric acid, and Nε,Nε,Nε-trimethyllysine [TML]) and dose for N1-acetylspermidine, which also provided excellent (AUROC ≥ 0.90) to good (AUROC ≥ 0.80) sensitivity and specificity according to the area under the receiver operator characteristic curve (AUROC) analysis. In serum, a panel consisting of carnitine, citric acid, lysophosphatidylcholine (LysoPC) (14:0), LysoPC (20:3), and LysoPC (22:5) also gave excellent to good sensitivity and specificity for identifying post-irradiated individuals at 3 d. Although the microbiome affected the basal levels and/or post-irradiation levels of these metabolites, their utility in dose reconstruction irrespective of microbiome status is encouraging for the use of metabolomics as a novel biodosimetry assay.

Global LC-MS/MS targeted metabolomics using a combination of HILIC and RP LC separation modes on an organic monolithic column based on 1-vinyl-1,2,4-triazole

The paper presents an LC-MS/MS-based approach to targeted screening of both polar and non-polar metabolites using a synthesized monolithic column which is a copolymer of styrene, divinylbenzene, and 1-vinyl-1,2,4-triazole. It was shown that this column in combination with eluents 20 mM (NH4)2CO3 + NH3 (pH = 9.8, eluent A) and ACN (eluent B) allows for separation of metabolites of different nature in two modes, HILIC and RP LC, and these methods are mutually complementary. A combination of analyses based on these two modes was proposed, allowing detection of about 400 metabolites in a total time of less than 30 min. Comparison of the developed method with those utilizing commercially available columns with sorbents of various types showed that it could provide a broader metabolite coverage. Using the developed approach, metabolomic screening of dried blood spots samples of mice exposed with X-ray was performed, and metabolites that could be considered as possible markers of irradiation exposure and organ tissue damage were detected. Analysis of marker metabolites revealed metabolic pathways that were altered by radiation exposure. Comparison of the results with literature data showed the effectiveness of the developed metabolomic screening approach.

Biomarkers for Biodosimetry and Their Role in Predicting Radiation Injury

Radiation-related normal tissue injury sustained during cancer radiotherapy or in a radiological or mass casualty nuclear incident is a major health concern. Reducing the risk and mitigating consequences of radiation injury could have a broad impact on cancer patients and citizens. Efforts to discover biomarkers that can determine radiation dose, predict tissue damage, and aid medical triage are underway. Exposure to ionizing radiation causes changes in gene, protein, and metabolite expression that needs to be understood to provide a holistic picture for treating acute and chronic radiation-induced toxicities. We present evidence that both RNA (mRNA, microRNA, long noncoding RNA) and metabolomic assays may provide useful biomarkers of radiation injury. RNA markers may provide information on early pathway alterations after radiation injury that can predict damage and implicate downstream targets for mitigation. In contrast, metabolomics is impacted by changes in epigenetics, genetics, and proteomics and can be considered a downstream marker that incorporates all these changes to provide an assessment of what is currently happening within an organ. We highlight research from the past 10 years to understand how biomarkers may be used to improve personalized medicine in cancer therapy and medical decision-making in mass casualty scenarios.

The Radioprotective Activity of Resveratrol—Metabolomic Point of View

Resveratrol, a plant-derived polyphenol, is an intensively studied compound with widely documented positive effects on health. Antioxidant activity is the property most often mentioned as responsible for its beneficial effects. Therefore, since the adverse effect of ionizing radiation is primarily related to the induction of oxidative stress, the question arises of whether the use of resveratrol could have a radioprotective effect. This paper summarizes the data on the cytoprotective activity of resveratrol and pieces of evidence for the potential interplay between response to radiation and resveratrol activity. The paper focuses on changes in the metabolic profile of cells and organisms induced by ionizing radiation and exposure to resveratrol. The comparison of metabolic changes induced by both factors provides a rationale for the potential mechanism of the radioprotective effects of resveratrol.

Small Molecule Signatures of Mice Lacking T-cell p38 Alternate Activation, a Model for Immunosuppression Conditions, after Total-Body Irradiation

Several diagnostic biodosimetry tools have been in development that may aid in radiological/nuclear emergency responses. Of these, correlating changes in non-invasive biofluid small-molecule signatures to tissue damage from ionizing radiation exposure show promise for inclusion in predictive biodosimetry models. Integral to dose reconstruction has been determining how genotypic variation in the general population will affect model performance. Here, we used a mouse model that lacks the T-cell receptor specific alternative p38 pathway [p38αβY323F, double knock-in (DKI) mice] to determine how attenuated autoimmune and inflammatory responses may affect dose reconstruction. We exposed adult male DKI mice (8-10 weeks old) to 2 and 7 Gy in parallel with wild-type mice and assessed perturbations in urine (days 1, 3, 7) and serum (day 1) using a global metabolomics approach. A multidimensional scaling plot showed excellent separation of radiation-exposed groups in wild-type mice with slightly dampened responses in DKI mice. Validated metabolite panels were developed for urine [N6,N6,N6-trimethyllysine (TML), N1-acetylspermidine, spermidine, carnitine, acylcarnitine C21H35NO5, 4-aminohippuric acid] and serum [phenylalanine, glutamine, propionylcarnitine, lysophosphatidylcholine (LysoPC 14:0), LysoPC (22:5)] to determine the area under the receiver operating characteristic curve (AUROC). For both urine and serum, excellent sensitivity and specificity (AUROC > 0.90) was observed for 0 Gy vs. 7 Gy groups irrespective of genotype using identical metabolite panels. Similarly, excellent to fair classification (AUROC > 0.75) was observed for ≤2 Gy vs. 7 Gy mice for both genotypes, however, model performance declined (AUROC < 0.75) between genotypes after irradiation. Overall, these results suggest immunosuppression should not compromise small molecule multiplex panels used in dose reconstruction for biodosimetry.

Metabolic response to radiation therapy in cancer

Tumor metabolism has emerged as a hallmark of cancer and is involved in carcinogenesis and tumor growth. Reprogramming of tumor metabolism is necessary for cancer cells to sustain high proliferation rates and enhanced demands for nutrients. Recent studies suggest that metabolic plasticity in cancer cells can decrease the efficacy of anticancer therapies by enhancing antioxidant defenses and DNA repair mechanisms. Studying radiation-induced metabolic changes will lead to a better understanding of radiation response mechanisms as well as the identification of new therapeutic targets, but there are few robust studies characterizing the metabolic changes induced by radiation therapy in cancer. In this review, we will highlight studies that provide information on the metabolic changes induced by radiation and oxidative stress in cancer cells and the associated underlying mechanisms.

The Potential of Omics in Biological Dosimetry

Biological dosimetry is an internationally recognized method for quantifying and estimating radiation dose following suspected or verified excessive exposure to ionising radiation. In severe radiation accidents where a large number of people are potentially affected, it is possible to distinguish irradiated from non-irradiated people in order to initiate appropriate medical care if necessary. In addition to severe incidents caused by technical failure, environmental disasters, military actions, or criminal abuse, there are also radiation accidents in which only one or a few individuals are affected in the frame of occupational or medical exposure. The requirements for biological dosimetry are fundamentally different for these two scenarios. In particular, for large-scale radiation accidents, pre-screening methods are necessary to increase the throughput of samples for a rough first-dose categorization. The rapid development and increasing use of omics methods in research as well as in individual applications provides new opportunities for biological dosimetry. In addition to the discovery and search for new biomarkers, dosimetry assays based on omics technologies are becoming increasingly interesting and hold great potential, especially for large-scale dosimetry. In the following review, the different areas of biological dosimetry, the problems in finding suitable biomarkers, the current status of biomarker research based on omics, the potential applications of assays using omics technologies, and also the limitations for the different areas of biological dosimetry are discussed.

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.

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.

Comparative metabolic profiles of total and partial body radiation exposure in mice using an untargeted metabolomics approach

INTRODUCTION

A large scale population exposure to ionizing radiation during intentional or unintentional nuclear accidents undoubtedly generates a complex scenario with partial-body as well as total-body irradiated victims. A high throughput technique based rapid assessment method is an urgent necessity for stratification of exposed subjects independent of whether exposure is uniform total-body or non-homogenous partial-body.

OBJECTIVE

Here, we used Nuclear Magnetic Resonance (NMR) based metabolomics approach to compare and identify candidate metabolites differentially expressed in total and partially irradiated mice model.

METHODS

C57BL/6 male mice (8-10 weeks) were irradiated total-body or locally to thoracic, hind limb or abdominal regions with 10 Gy of gamma radiation. Urine samples collected at 24 h post irradiation were examined using high resolution NMR spectroscopy and the datasets were analysed using multivariate analysis.

RESULTS

Multivariate and metabolic pathway analysis in urine samples collected at 24 h post-radiation exhibited segregation of all irradiated groups from controls. Metabolites associated with energy metabolism, gut flora metabolism and taurine were common to partial and total-body irradiation, thus making them potential candidates for radiation exposure. Nevertheless, a distinct metabolic pattern was observed in partial-body exposed groups with maximum changes observed in the hind limb region indicating differential tissue associated radiation sensitivity. The organ-specific changes may provide an early warning regarding the physiological system at risk after radiation injury.

CONCLUSION

The study affirms potentiality of metabolite markers and comparative analysis could be an important piece of information for an integrated solution to a complex research question in terms of radiation biomarkers.

Radioprotection and Radiomitigation: From the Bench to Clinical Practice

The development of protective agents against harmful radiations has been a subject of investigation for decades. However, effective (ideal) radioprotectors and radiomitigators remain an unsolved problem. Because ionizing radiation-induced cellular damage is primarily attributed to free radicals, radical scavengers are promising as potential radioprotectors. Early development of such agents focused on thiol synthetic compounds, e.g., amifostine (2-(3-aminopropylamino) ethylsulfanylphosphonic acid), approved as a radioprotector by the Food and Drug Administration (FDA, USA) but for limited clinical indications and not for nonclinical uses. To date, no new chemical entity has been approved by the FDA as a radiation countermeasure for acute radiation syndrome (ARS). All FDA-approved radiation countermeasures (filgrastim, a recombinant DNA form of the naturally occurring granulocyte colony-stimulating factor, G-CSF; pegfilgrastim, a PEGylated form of the recombinant human G-CSF; sargramostim, a recombinant granulocyte macrophage colony-stimulating factor, GM-CSF) are classified as radiomitigators. No radioprotector that can be administered prior to exposure has been approved for ARS. This differentiates radioprotectors (reduce direct damage caused by radiation) and radiomitigators (minimize toxicity even after radiation has been delivered). Molecules under development with the aim of reaching clinical practice and other nonclinical applications are discussed. Assays to evaluate the biological effects of ionizing radiations are also analyzed.

Urine metabolomics based prediction model approach for radiation exposure

The radiological incidents and terrorism have demanded the need for the development of rapid, precise, and non-invasive technique for detection and quantification of exposed dose of radiation. Though radiation induced metabolic markers have been thoroughly investigated, but reproducibility still needs to be elucidated. The present study aims at assessing the reliability and reproducibility of markers using nuclear magnetic resonance (NMR) spectroscopy and further deriving a logistic regression model based on these markers. C57BL/6 male mice (8-10 weeks) whole body γ-irradiated and sham irradiated controls were used. Urine samples collected at 24 h post dose were investigated using high resolution NMR spectroscopy and the datasets were analyzed using multivariate analysis. Fifteen distinguishable metabolites and 3 metabolic pathways (TCA cycle, taurine and hypotaurine metabolism, primary bile acid biosynthesis) were found to be amended. ROC curve and logistic regression was used to establish a diagnostic model as Logit (p) = log (p/1 - p) = -0.498 + 13.771 (tau) - 3.412 (citrate) - 34.461 (α-KG) + 515.183 (fumarate) with a sensitivity and specificity of 1.00 and 0.964 respectively. The findings demonstrate the proof of concept and the potential of NMR based metabolomics to establish a prediction model that can be implemented as a promising mass screening tool during triage.

Metabolomics in Radiation Biodosimetry: Current Approaches and Advances

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.

Citrulline, A Potential Biomarker of Radiation-Induced Small Intestine Damage

Radiation damage assessment of the small intestine is important in nuclear accidents or routine radiotherapy of abdominal tumors. This article reviews the clinical symptoms and molecular mechanisms of radiation-induced small intestinal damage and summarizes recent research on biomarkers of such damage. Citrulline is the most promising biomarker for the evaluation of radiation-induced small intestinal damage caused by radiotherapy and nuclear accidents. This article also summarizes the factors influencing plasma citrulline measurement investigated in the latest research, as well as new findings on the concentration of citrulline in saliva and urine after different types of radiation.

A Systematic Review of Metabolomic and Lipidomic Candidates for Biomarkers in Radiation Injury

A large-scale nuclear event has the ability to inflict mass casualties requiring point-of-care and laboratory-based diagnostic and prognostic biomarkers to inform victim triage and appropriate medical intervention. Extensive progress has been made to develop post-exposure point-of-care biodosimetry assays and to identify biomarkers that may be used in early phase testing to predict the course of the disease. Screening for biomarkers has recently extended to identify specific metabolomic and lipidomic responses to radiation using animal models. The objective of this review was to determine which metabolites or lipids most frequently experienced perturbations post-ionizing irradiation (IR) in preclinical studies using animal models of acute radiation sickness (ARS) and delayed effects of acute radiation exposure (DEARE). Upon review of approximately 65 manuscripts published in the peer-reviewed literature, the most frequently referenced metabolites showing clear changes in IR induced injury were found to be citrulline, citric acid, creatine, taurine, carnitine, xanthine, creatinine, hypoxanthine, uric acid, and threonine. Each metabolite was evaluated by specific study parameters to determine whether trends were in agreement across several studies. A select few show agreement across variable animal models, IR doses and timepoints, indicating that they may be ubiquitous and appropriate for use in diagnostic or prognostic biomarker panels.

Radiation metabolomics in the quest of cardiotoxicity biomarkers: the review

Purpose: Ionizing radiation is a risk factor to the whole organism, including the heart. Cardiac damage is considered to be a late effect of radiation exposure. While the acute cardiotoxicity of high doses is well characterized, the knowledge about nature and magnitude of the cardiac risk following lower doses exposure is incomplete. It has been shown that the cardiotoxic effects of radiation are source-, dose- and time-dependent. This paper provides an overview on these dependencies with regard to the molecular responses at the cellular and tissue levels. Main focus is put on the Nuclear Magnetic Resonance (NMR)-based and Mass Spectrometry (MS)-based metabolomic approaches in search of toxicity markers of relatively small doses of radiation.Conclusions: Available literature indicates that radiation exposure affects metabolites associated with: energy production, degradation of proteins and cell membranes, expression of proteins and stress response. Such effects are common for both animal and human studies. However, the specific metabolic response depends on several factors, including the examined organ. Radiation metabolomics can be used to explain the mechanisms of development of radiation-induced heart disease and to find an organ-specific biomarker of radiation exposure. The main aim of this review was to collect the information on the human cardiotoxicity biomarkers. In addition it also summarizes results of the studies on the metabolic responses to ionizing radiation for other organs, as well as the comparative data concerning animal studies.

The hunt for radiation biomarkers: current situation

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.

Fabric Phase Sorptive Extraction-A Metabolomic Preprocessing Approach for Ionizing Radiation Exposure Assessment

The modern application of mass spectrometry-based metabolomics to the field of radiation assessment and biodosimetry has allowed for the development of prompt biomarker screenings for radiation exposure. Our previous work on radiation assessment, in easily accessible biofluids (such as urine, blood, saliva), has revealed unique metabolic perturbations in response to radiation quality, dose, and dose rate. Nevertheless, the employment of swift injury assessment in the case of a radiological disaster still remains a challenge as current sample processing can be time consuming and cause sample degradation. To address these concerns, we report a metabolomics workflow using a mass spectrometry-compatible fabric phase sorptive extraction (FPSE) technique. FPSE employs a matrix coated with sol-gel poly(caprolactone-b-dimethylsiloxane-b-caprolactone) that binds both polar and nonpolar metabolites in whole blood, eliminating serum processing steps. We confirm that the FPSE preparation technique combined with liquid chromatography-mass spectrometry can distinguish radiation exposure markers such as taurine, carnitine, arachidonic acid, α-linolenic acid, and oleic acid found 24 h after 8 Gy irradiation. We also note the effect of different membrane fibers on both metabolite extraction efficiency and the temporal stabilization of metabolites in whole blood at room temperature. These findings suggest that the FPSE approach could work in future technology to triage irradiated individuals accurately, via biomarker screening, by providing a novel method to stabilize biofluids between collection and sample analysis.

Temporal Effects on Radiation Responses in Nonhuman Primates: Identification of Biofluid Small Molecule Signatures by Gas Chromatography⁻Mass Spectrometry Metabolomics

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.

Ionizing radiation exposure: hazards, prevention, and biomarker screening

Radiation is a form of energy derived from a source that is propagated through material in space. It consists of ionizing radiation or nonionizing radiation. Ionizing radiation is a feature of the environment and an important tool in medical treatment, but it can cause serious damage to organisms. A number of protective measures and standards of protection have been proposed to protect against radiation. There is also a need for biomarkers to rapidly assess individual doses of radiation, which can not only estimate the dose of radiation but also determine its effects on health. Proteomics, genomics, metabolomics, and lipidomics have been widely used in the search for such biomarkers. These topics are discussed in depth in this review.

Urinary metabolic signatures and early triage of acute radiation exposure in rat model

After a large-scale radiological accident, early-response biomarkers to assess radiation exposure over a broad dose range are not only the basis of rapid radiation triage, but are also the key to the rational use of limited medical resources and to the improvement of treatment efficiency. Because of its high throughput, rapid assays and minimally invasive sample collection, metabolomics has been applied to research into radiation exposure biomarkers in recent years. Due to the complexity of radiobiological effects, most of the potential biomarkers are both dose-dependent and time-dependent. In reality, it is very difficult to find a single biomarker that is both sensitive and specific in a given radiation exposure scenario. Therefore, a multi-parameters approach for radiation exposure assessment is more realistic in real nuclear accidents. In this study, untargeted metabolomic profiling based on gas chromatography-mass spectrometry (GC-MS) and targeted amino acid profiling based on LC-MS/MS were combined to investigate early urinary metabolite responses within 48 h post-exposure in a rat model. A few of the key early-response metabolites for radiation exposure were identified, which revealed the most relevant metabolic pathways. Furthermore, a panel of potential urinary biomarkers was selected through a multi-criteria approach and applied to early triage following irradiation. Our study suggests that it is feasible to use a multi-parameters approach to triage radiation damage, and the urinary excretion levels of the relevant metabolites provide insights into radiation damage and repair.

Developing Human Radiation Biodosimetry Models: Testing Cross-Species Conversion Approaches Using an Ex Vivo Model System

In the event of a large-scale radiation exposure, accurate and quick assessment of radiation dose received would be critical for triage and medical treatment of large numbers of potentially exposed individuals. Current methods of biodosimetry, such as the dicentric chromosome assay, are time consuming and require sophisticated equipment and highly trained personnel. Therefore, scalable biodosimetry approaches, including gene expression profiles in peripheral blood cells, are being investigated. Due to the limited availability of appropriate human samples, biodosimetry development has relied heavily on mouse models, which are not directly applicable to human response. Therefore, to explore the feasibility of using non-human primate (NHP) models to build and test a biodosimetry algorithm for use in humans, we irradiated ex vivo peripheral blood samples from both humans and rhesus macaques with doses of 0, 2, 5, 6 and 7 Gy, and compared the gene expression profiles 24 h later using Agilent human microarrays. Among the dose-responsive genes in human and using non-human primate, 52 genes showed highly correlated expression patterns between the species, and were enriched in p53/DNA damage response, apoptosis and cell cycle-related genes. When these interspecies-correlated genes were used to build biodosimetry models with using NHP data, the mean prediction accuracy on non-human primate samples was about 90% within 1 Gy of delivered dose in leave-one-out cross-validation. However, tests on human samples suggested that human gene expression values may need to be adjusted prior to application of the NHP model. A "multi-gene" approach utilizing all gene values for cross-species conversion and applying the converted values on the NHP biodosimetry models, gave a leave-one-out cross-validation prediction accuracy for human samples highly comparable (up to 94%) to that for non-human primates. Overall, this study demonstrates that a robust NHP biodosimetry model can be built using interspecies-correlated genes, and that, by using multiple regression-based cross-species conversion of expression values, absorbed dose in human samples can be accurately predicted by the NHP model.

Metabolomic applications in radiation biodosimetry: exploring radiation effects through small molecules

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.

Hepcidin-2 in mouse urine as a candidate radiation-responsive molecule

We used high-performance liquid chromatography to separate urine obtained from whole-body gamma-irradiated mice (4 Gy) before analyzing each fraction with matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry to identify radiation-responsive molecules. We identified two candidates: hepcidin antimicrobial peptide 2 (hepcidin-2) and peptide fragments of kidney androgen-regulated protein (KAP). We observed that peak increases of hepcidin-2 in urine were delayed in a dose-dependent manner (1 Gy and above); however, the amount of KAP peptide fragments showed no correlation with radiation dose. In addition, an increase in hepcidin-2 after exposure to relatively low radiation doses (0.25 and 0.5 Gy, respectively) was biphasic (at 8-48 h and 120-168 h, respectively, after irradiation). The increase in hepcidin-2 paralleled an increase in hepcidin-2 gene (Hamp2) mRNA levels in the liver. These results suggest that radiation exposure directly or indirectly induces urinary excretion of hepcidin-2 at least in part by the upregulation of Hamp2 mRNA in the liver.

Use of biomarkers for assessing radiation injury and efficacy of countermeasures

Several candidate drugs for acute radiation syndrome (ARS) have been identified that have low toxicity and significant radioprotective and radiomitigative efficacy. Inasmuch as exposing healthy human volunteers to injurious levels of radiation is unethical, development and approval of new radiation countermeasures for ARS are therefore presently based on animal studies and Phase I safety study in healthy volunteers. The Animal Efficacy Rule, which underlies the Food and Drug Administration approval pathway, requires a sound understanding of the mechanisms of injury, drug efficacy, and efficacy biomarkers. In this context, it is important to identify biomarkers for radiation injury and drug efficacy that can extrapolate animal efficacy results, and can be used to convert drug doses deduced from animal studies to those that can be efficacious when used in humans. Here, we summarize the progress of studies to identify candidate biomarkers for the extent of radiation injury and for evaluation of countermeasure efficacy.

Exposure to ionizing radiation reveals global dose- and time-dependent changes in the urinary metabolome of rat

The potential for exposures to ionizing radiation has increased in recent years. Although advances have been made, understanding the global metabolic response as a function of both dose and exposure time is challenging considering the complexity of the responses. Herein we report our findings on the dose- and time-dependency of the urinary response to ionizing radiation in the male rat using radiation metabolomics. Urine samples were collected from adult male rats, exposed to 0.5 to 10 Gy γ-radiation, both before from 6 to 72 h following exposures. Samples were analyzed by liquid chromatography coupled with time-of-flight mass spectrometry, and deconvoluted mass chromatographic data were initially analyzed by principal component analysis. However, the breadth and complexity of the data necessitated the development of a novel approach to summarizing biofluid constituents after exposure, called Visual Analysis of Metabolomics Package (VAMP). VAMP revealed clear urine metabolite profile differences to as little as 0.5 Gy after 6 h exposure. Via VAMP, it was discovered that the response to radiation exposure found in rat urine is characterized by an overall net down-regulation of ion excretion with only a modest number of ions excreted in excess over pre-exposure levels. Our results show both similarities and differences with the published mouse urine response and a dose- and time-dependent net decrease in urine ion excretion associated with radiation exposure. These findings mark an important step in the development of minimally invasive radiation biodosimetry. VAMP should have general applicability in metabolomics to visualize overall differences and trends in many sample sets.

Radiation Dose-Rate Effects on Gene Expression in a Mouse Biodosimetry Model

In the event of a nuclear accident or radiological terrorist attack, there will be a pressing need for biodosimetry to triage a large, potentially exposed population and to assign individuals to appropriate treatment. Exposures from fallout are likely, resulting in protracted dose delivery that would, in turn, impact the extent of injury. Biodosimetry approaches that can distinguish such low-dose-rate (LDR) exposures from acute exposures have not yet been developed. In this study, we used the C57BL/6 mouse model in an initial investigation of the impact of low-dose-rate delivery on the transcriptomic response in blood. While a large number of the same genes responded to LDR and acute radiation exposures, for many genes the magnitude of response was lower after LDR exposures. Some genes, however, were differentially expressed (P < 0.001, false discovery rate <5%) in mice exposed to LDR compared with mice exposed to acute radiation. We identified a set of 164 genes that correctly classified 97% of the samples in this experiment as exposed to acute or LDR radiation using a support vector machine algorithm. Gene expression is a promising approach to radiation biodosimetry, enhanced greatly by this first demonstration of its potential for distinguishing between acute and LDR exposures. Further development of this aspect of radiation biodosimetry, either as part of a complete gene expression biodosimetry test or as an adjunct to other methods, could provide vital triage information in a mass radiological casualty event.

Effects of ionizing radiation on biological molecules--mechanisms of damage and emerging methods of detection

SIGNIFICANCE

The detrimental effects of ionizing radiation (IR) involve a highly orchestrated series of events that are amplified by endogenous signaling and culminating in oxidative damage to DNA, lipids, proteins, and many metabolites. Despite the global impact of IR, the molecular mechanisms underlying tissue damage reveal that many biomolecules are chemoselectively modified by IR.

RECENT ADVANCES

The development of high-throughput "omics" technologies for mapping DNA and protein modifications have revolutionized the study of IR effects on biological systems. Studies in cells, tissues, and biological fluids are used to identify molecular features or biomarkers of IR exposure and response and the molecular mechanisms that regulate their expression or synthesis.

CRITICAL ISSUES

In this review, chemical mechanisms are described for IR-induced modifications of biomolecules along with methods for their detection. Included with the detection methods are crucial experimental considerations and caveats for their use. Additional factors critical to the cellular response to radiation, including alterations in protein expression, metabolomics, and epigenetic factors, are also discussed.

FUTURE DIRECTIONS

Throughout the review, the synergy of combined "omics" technologies such as genomics and epigenomics, proteomics, and metabolomics is highlighted. These are anticipated to lead to new hypotheses to understand IR effects on biological systems and improve IR-based therapies.

Development of a metabolomic radiation signature in urine from patients undergoing total body irradiation

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.

Intestinal microbiota as novel biomarkers of prior radiation exposure

There is an urgent need for rapid, accurate, and sensitive diagnostic platforms to confirm exposure to radiation and estimate the dose absorbed by individuals subjected to acts of radiological terrorism, nuclear power plant accidents, or nuclear warfare. Clinical symptoms and physical dosimeters, even when available, do not provide adequate diagnostic information to triage and treat life-threatening radiation injuries. We hypothesized that intestinal microbiota act as novel biomarkers of prior radiation exposure. Adult male Wistar rats (n = 5/group) received single or multiple fraction total-body irradiation of 10.0 Gy and 18.0 Gy, respectively. Fresh fecal pellets were obtained from each rat prior to (day 0) and at days 4, 11, and 21 post-irradiation. Fecal microbiota composition was determined using microarray and quantitative PCR (polymerase chain reaction) analyses. The radiation exposure biomarkers consisted of increased 16S rRNA levels of 12 members of the Bacteroidales, Lactobacillaceae, and Streptococcaceae after radiation exposure, unchanged levels of 98 Clostridiaceae and Peptostreptococcaceae, and decreased levels of 47 separate Clostridiaceae members; these biomarkers are present in human and rat feces. As a result of the ubiquity of these biomarkers, this biomarker technique is non-invasive; microbiota provide a sustained level of reporting signals that are increased several-fold following exposure to radiation, and intestinal microbiota that are unaffected by radiation serve as internal controls. We conclude that intestinal microbiota serve as novel biomarkers of prior radiation exposure, and may be able to complement conventional chromosome aberrational analysis to significantly enhance biological dose assessments.