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

Dynamic Metabolic Characterization of Lung Tissues in Rats Exposed to Whole-Thorax Irradiation Based on GC-MS

An animal model of radiation-induced lung injury (RILI) was established using female rats given sublethal whole-thorax X-ray irradiation (15 Gy) at a dose rate of 2.7 Gy/min. The rats were studied for up to day 45 and compared with sham-irradiated controls. Time-series lung tissue samples during the progression of RILI were collected for dynamic metabolomics studies based on gas chromatography-mass spectrometry (GC-MS). Differential metabolites associated with radiation-induced lung injury were identified, followed by metabolite set enrichment analysis to uncover pathway changes in RILI. The results revealed dynamic metabolic alterations in the progression of RILI, primarily involving in glycine and serine metabolism, the urea cycle, the Warburg effect, glutamate metabolism, arginine and proline metabolism, glucose-alanine cycle, and ammonia recycling. In addition, the potential panel of biomarkers including taurine, lysine, and tyrosine of RILI was selected and then applied to evaluate the diagnostic potential for RILI based on the receiving operator characteristic curve (ROC) at the early-stage of RILI. The better sensitivity, specificity, and accuracy indicate the potential of early diagnosis for RILI. These findings suggest that dynamic metabolomics data could provide new insights into understanding the complex metabolic dysregulation underlying RILI, facilitating the selection of biomarkers for early diagnosis.

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

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

Differences in the Establishment of Gut Microbiota and Metabolome Characteristics Between Balb/c and C57BL/6J Mice After Proton Irradiation

Although proton irradiation is ubiquitous in outer space as well as in the treatment of human diseases, its effects remain largely unclear. This work aimed to investigate and compare the composition of gut microbiota composition of mice in different species exposed to high-dose radiation. Male Balb/c mice and C57BL/6J mice were irradiated at a high dose (5Gy). Fecal specimens before and after irradiation were subjected to high-throughput sequencing (HTS) for the amplification of 16S rRNA gene sequences. We observed substantial changes in gut microbial composition among mice irradiated at high doses compared to non-irradiated controls. The changes included both the alpha and beta diversities. Furthermore, there were 11 distinct alterations in the irradiation group compared to the non-radiation control, including the families Muribaculaceae, Ruminococcaceae, Lactobacillus, Lachnospiraceae_NK4A136, Bacteroides, Alistipes, Clostridiales, Muribaculum, and Alloprevotella. Such alterations in the gut microbiome were accompanied by alterations in metabolite abundances, while at the metabolic level, 32 metabolites were likely to be potential biomarkers. Some alterations may have a positive effect on the repair of intestinal damage. Simultaneously, metabolites were predicted to involve multiple signal pathways, such as Urea Cycle, Ammonia Recycling, Alpha Linolenic Acid and Linoleic Acid Metabolism, Ketone Body Metabolism, Aspartate Metabolism, Phenylacetate Metabolism, Malate-Aspartate Shuttle, Arginine and Proline Metabolism and Carnitine Synthesis. Metabolites produced by proton irradiation in the microbial region play a positive role in repairing damage, making this area worthy of further experimental exploration. The present work offers an analytical and theoretical foundation to investigate how proton radiation affects the treatment of human diseases and identifies potential biomarkers to address the adverse effects of radiation.

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

BACKGROUND

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

AIM OF REVIEW

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

KEY SCIENTIFIC CONCEPTS OF REVIEW

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

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.

Comprehensive Analysis of Serum Metabolites Profiles in Acute Radiation Enteritis Rats by Untargeted Metabolomics

Acute radiation enteritis is a common complication occurring in patients with pelvic and abdominal tumors who receive radiotherapy. Acute radiation enteritis seriously reduces the life quality, even threatens the lives of patients. Untargeted metabolomics is an emerging strategy to explore the novel biomarkers and uncover potential pathogenesis of acute radiation enteritis. Acute radiation enteritis rat model was established by single abdominal irradiation with a gamma-ray dose of 10 Gy. Serum from 15 acute radiation enteritis rats and 10 controls was extracted for metabolomics analysis by UHPLC-Q-TOF/MS. Clinical manifestations and morphological alterations of intestine confirmed the successful establishment of acute radiation enteritis. According to the metabolomics data, 6,044 positive peaks and 4,241 negative peaks were extracted from each specimen. OPLS-DA analysis and the heat map for cluster analysis showed satisfactory discriminatory power between acute radiation enteritis rats and controls. Subsequent analysis extracted 66 significantly differentially expressed metabolites, which might be potential biomarkers for acute radiation enteritis diagnosis. Moreover, Kyoto Encyclopedia of Genes and Genomes enrichment analyses uncovered the potential mechanisms through which differentially expressed metabolites participated in acute radiation enteritis pathogenesis. To sum up, we summarized several differentially expressed serum metabolites as potential biomarkers for diagnosis of acute radiation enteritis and provide latent clues for elucidating acute radiation enteritis pathology.

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.

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.

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.

Plasma Derived Exosomal Biomarkers of Exposure to Ionizing Radiation in Nonhuman Primates

Exposure to ionizing radiation induces a cascade of molecular events that ultimately impact endogenous metabolism. Qualitative and quantitative characterization of metabolomic profiles is a pragmatic approach to studying the risks of radiation exposure since it provides a phenotypic readout. Studies were conducted in irradiated nonhuman primates (NHP) to investigate metabolic changes in plasma and plasma-derived exosomes. Specifically, rhesus macaques (Macaca mulatta) were exposed to cobalt-60 gamma-radiation and plasma samples were collected prior to and after exposure to 5.8 Gy or 6.5 Gy radiation. Exosomes were isolated using ultracentrifugation and analyzed by untargeted profiling via ultra-performance liquid chromatography mass spectrometry (UPLC-MS) based metabolomic and lipidomic analyses, with the goal of identifying a molecular signature of irradiation. The enrichment of an exosomal fraction was confirmed using quantitative ELISA. Plasma profiling showed markers of dyslipidemia, inflammation and oxidative stress post-irradiation. Exosomal profiling, on the other hand, enabled detection and identification of low abundance metabolites that comprise exosomal cargo which would otherwise get obscured with plasma profiling. We discovered enrichment of different classes of metabolites including N-acyl-amino acids, Fatty Acid ester of Hydroxyl Fatty Acids (FAHFA’s), glycolipids and triglycerides as compared to the plasma metabolome composition with implications in mediation of systemic response to radiation induced stress signaling.

Long non-coding RNA CRYBG3 regulates glycolysis of lung cancer cells by interacting with lactate dehydrogenase A

Cancer cells usually utilize glucose as a carbon source for aerobic glycolysis, a phenomenon known as the Warburg effect. And a high rate of glycolysis has been observed in lung cancer cells. The growing evidence indicates that long non-coding RNAs (lncRNAs) are important players in lung cancer initiation and progression. However, the correlation between lncRNAs and glycolysis remains unclear. In this study, we recognized a lncRNA, LNC CRYBG3, which can interact with lactate dehydrogenase A (LDHA), a vital enzyme of glycolysis, is highly upregulated in both clinical lung cancer tissues and in vitro cultured lung cancer cell lines. A positive correlation between the expression level of LNC CRYBG3 and LDHA expression levels is observed. In another hand, LNC CRYBG3 is a regulator of glycolysis and its overexpression promoted the uptake of glucose and the production of lactate whereas the knockdown of LNC CRYBG3 led to opposite results and suppressed cell proliferation. These results indicated that LNC CRYBG3 might be a novel target for lung cancer treatment.

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.

Prediction of acute GVHD and relapse by metabolic biomarkers after allogeneic hematopoietic stem cell transplantation

BACKGROUND

There are very few studies investigating metabolic biomarkers to predict acute graft-versus-host disease (aGVHD) after allogeneic hematopoietic stem cell transplantation (HSCT). Metabolic models can provide a framework for analyzing the information-rich omics data sets in this setting.

METHODS

Four hundred and fifty-six samples from one hundred and fourteen consecutive patients who underwent HSCT from January 2012 to May 2014 were collected for this study. The changes in serum metabolite levels were investigated using a gas chromatography-mass spectrometry-based metabolomics approach and underwent statistical analysis.

RESULTS

Significant metabolic changes were observed on day 7. The stearic acid/palmitic acid (SA/PA) ratio was effective in the diagnosis of grade II-IV aGVHD. Multivariate analysis showed that patients with high SA/PA ratios on day 7 after HSCT were less likely to develop II-IV aGVHD than patients with low SA/PA ratios (odds ratio [OR] = 0.06, 95% CI 0.02-0.18, P < 0.001). After the adjustment for clinical characteristics, the SA/PA ratio had no significant effect on overall survival (hazard ratio [HR] = 1.95, 95% CI 0.92-4.14, P = 0.08), and patients in the high SA/PA ratio group were significantly more likely to relapse than those in the low ratio group (HR = 2.26, 95% CI 1.04-4.91, P = 0.04).

CONCLUSION

Our findings suggest that the SA/PA ratio on day 7 after HSCT is an excellent biomarker to predict both aGVHD and relapse. The serum SA/PA ratio measured on day 7 after transplantation may improve risk stratification for aGVHD and relapse after allogeneic stem cell transplantation.

FUNDING

National Natural Science Foundation of China (81470346, 81773361), Priority Academic Program Development of Jiangsu Higher Education Institutions, Jiangsu Natural Science Foundation (BK20161204), Innovation Capability Development Project of Jiangsu Province (BM2015004), Jiangsu Medical Junior Talent Person award (QNRC2016707), and NIH (AI129582 and NS106170).

Monitoring tyrosine kinase inhibitor therapeutic responses with a panel of metabolic biomarkers in chronic myeloid leukemia patients

The aim of this study is to investigate the potential biomarkers associated with chronic myeloid leukemia (CML), reveal the metabolite changes related to the continuous phases of tyrosine kinase inhibitors (TKIs), and find the potential biomarkers associated with treatment effects. Fifty‐two patients with CML and 26 matched healthy people were enrolled as the discovery set. Another 194 randomly selected CML patients treated with TKI were chosen as the external validation set. Plasma samples from the patients and controls were profiled using the gas chromatography‐mass spectrometry‐based metabonomic approach. Multivariate and univariate statistical analyses were combined to select the differential metabolic features. The gas chromatography‐mass spectrometry‐based metabolomics showed a clear clustering and separation of metabolic patterns from healthy controls and pre‐ and post‐TKI treatment CML patients in the discovery set. We identified 9 metabolites that differentiated CML patients from healthy controls, including lactic acid, isoleucine, glycerol, glycine, myristic acid, d‐sorbitol, d‐galactose, d‐glucose, and myo‐inositol. Among the 9 markers, glycerol and myristic acid had the most significant association with TKI treatment effects in both discovery and external validation sets. In the receiver operating characteristic analysis, the combination of glycerol and myristic acid showed a better discrimination performance compared to a single biomarker. The results indicated that metabolic profiling has the potential for diagnosis of CML and the panel of biomarkers including myristic acid and glycerol could be useful in monitoring TKI therapeutic responses.

Gas Chromatography/Mass Spectrometry Metabolomics of Urine and Serum from Nonhuman Primates Exposed to Ionizing Radiation: Impacts on the Tricarboxylic Acid Cycle and Protein Metabolism

Ionizing radiation (IR) directly damages cells and tissues or indirectly damages them through reactive free radicals that may lead to longer term adverse sequelae such as cancers, persistent inflammation, or possible death. Potential exposures include nuclear reactor accidents, improper disposal of equipment containing radioactive materials or medical errors, and terrorist attacks. Metabolomics (comprehensive analysis of compounds <1 kDa) by mass spectrometry (MS) has been proposed as a tool for high-throughput biodosimetry and rapid assessment of exposed dose and triage needed. While multiple studies have been dedicated to radiation biomarker discovery, many have utilized liquid chromatography (LC) MS platforms that may not detect particular compounds (e.g., small carboxylic acids or isomers) that complementary analytical tools, such as gas chromatography (GC) time-of-flight (TOF) MS, are ideal for. The current study uses global GC-TOF-MS metabolomics to complement previous LC-MS analyses on nonhuman primate biofluids (urine and serum) 7 days after exposure to 2, 4, 6, 7, and 10 Gy IR. Multivariate data analysis was used to visualize differences between control and IR exposed groups. Univariate analysis was used to determine a combined 26 biomarkers in urine and serum that significantly changed after exposure to IR. We found several metabolites involved in tricarboxylic acid cycle function, amino acid metabolism, and host microbiota that were not previously detected by global and targeted LC-MS studies.