Identification of Plasma Lipidome Changes Associated with Low Dose Space-Type Radiation Exposure in a Murine Model

Metabolomic Changes in Plasma of Preterminal Stage of Rhesus Nonhuman Primates Exposed to Lethal Dose of Radiation

Ionizing radiation exposure is known to induce molecular and cellular injury, inflicting a cascade of potentially catastrophic events leading to tissue and organ damage. Metabolomic analysis allows for the identification and quantification of small molecules downstream of genomic changes induced by radiation exposure. We aimed to characterize metabolomic changes that underscore the prefinal stage of lethally irradiated rhesus nonhuman primates (NHPs). Peripheral blood was drawn at baseline, post-exposure, as well as at the preterminal stage in NHPs (immediately prior to death in moribund NHPs) that did not survive exposure with 7.2 Gy total-body radiation (LD70/60). Herein, we analyzed global metabolomic changes using ultra-performance liquid chromatography (UPLC) quadrupole time-of-flight mass spectrometry (QTOF-MS) in plasma samples of NHPs collected at various timepoints in relation to irradiation. The overall goal was to identify metabolic shifts present immediately prior to death. Our findings showed radiation induced significant time-dependent metabolic perturbations when compared to pre-irradiation profiles, particularly in glycerophospholipid metabolism and steroid hormone biosynthesis and metabolism pathways. These findings provide valuable insights for identifying biomarkers for lethality, which may be helpful for triage during a mass casualty scenario.

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

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

Urinary Metabolomics for the Prediction of Radiation-Induced Cardiac Dysfunction

Survivors of acute radiation exposures are likely to experience delayed effects that manifest as injury in late-responding organs such as the heart. Noninvasive indicators of radiation-induced cardiac dysfunction are important in the prediction and diagnosis of this disease. In this study, we aimed to identify urinary metabolites indicative of radiation-induced cardiac damage by analyzing previously collected urine samples from a published study. The samples were collected from male and female wild-type (C57BL/6N) and transgenic mice constitutively expressing Activated Protein C (APCHi), a circulating protein with potential cardiac protective properties, that were exposed to 9.5 Gy of γ-rays. We utilized LC-MS-based metabolomics and lipidomics for the analysis of urine samples collected at 24 h, 1 week, 1 month, 3 months, and 6 months post-irradiation. Radiation caused perturbations in the TCA cycle, glycosphingolipid metabolism, fatty acid oxidation, purine catabolism, and amino acid metabolites, which were more prominent in wild-type (WT) mice compared to APCHi mice, suggesting a differential response between the two genotypes. After combining genotypes and sexes, we identified a multi-analyte urinary panel at early post-irradiation time points that predicted heart dysfunction using a logistic regression model with a discovery validation study design. These studies demonstrate the utility of a molecular phenotyping approach to develop a urinary biomarker panel predictive of delayed effects of ionizing radiation. It is important to note that no live mice were used or assessed in this study; instead, we focused solely on analyzing previously collected urine samples.

UHPLC/MS-Based Serum Metabolomics Reveals the Mechanism of Radiation-Induced Thrombocytopenia in Mice

Radiation-induced thrombocytopenia is a common and life-threatening side effect of ionizing radiation (IR) therapy. However, the underlying pathological mechanisms remain unclear. In the present study, irradiation was demonstrated to significantly reduce platelet levels, inhibit megakaryocyte differentiation, and promote the apoptosis of bone marrow (BM) cells. A metabolomics approach and a UHPLC-QTOF MS system were subsequently employed for the comprehensive analysis of serum metabolic profiles of normal and irradiated mice. A total of 66 metabolites were significantly altered, of which 56 were up-regulated and 10 were down-regulated in irradiated mice compared to normal mice on day 11 after irradiation. Pathway analysis revealed that disorders in glycerophospholipid metabolism, nicotinate and nicotinamide metabolism, sphingolipid metabolism, inositol phosphate metabolism, and tryptophan metabolism were involved in radiation-induced thrombocytopenia. In addition, three important differential metabolites, namely L-tryptophan, LysoPC (17:0), and D-sphinganine, which were up-regulated in irradiated mice, significantly induced the apoptosis of K562 cells. L-tryptophan inhibited megakaryocyte differentiation of K562 cells. Finally, serum metabolomics was performed on day 30 (i.e., when the platelet levels in irradiated mice recovered to normal levels). The contents of L-tryptophan, LysoPC (17:0), and D-sphinganine in normal and irradiated mice did not significantly differ on day 30 after irradiation. In conclusion, radiation can cause metabolic disorders, which are highly correlated with the apoptosis of hematopoietic cells and inhibition of megakaryocyte differentiation, ultimately resulting in thrombocytopenia. Further, the metabolites, L-tryptophan, LysoPC (17:0), and D-sphinganine can serve as biomarkers for radiation-induced thrombocytopenia.

Identification of novel biomarkers for acute radiation injury using multi-omics approach and nonhuman primate model

PURPOSE

The availability of validated biomarkers to assess radiation exposure and to assist in developing medical countermeasures remains an unmet need.

METHODS AND MATERIALS

We used a cobalt-60 gamma-irradiated nonhuman primate (NHP) model to delineate a multi-omics-based serum probability index of radiation exposure. Both male and female NHPs were irradiated with different doses ranging from 6.0 to 8.5 Gy, with 0.5 Gy increments between doses. We leveraged high-resolution mass spectrometry for analysis of metabolites, lipids, and proteins at 1, 2, and 6 days post-irradiation in NHP serum.

RESULTS

A logistic regression model was implemented to develop a 4-analyte panel to stratify irradiated NHPs from unirradiated with high accuracy that was agnostic for all doses of gamma-rays tested in the study, up to six days after exposure. This panel was comprised of Serpin Family A9, acetylcarnitine, PC (16:0/22:6), and suberylglycine, which showed 2 - 4-fold elevation in serum abundance upon irradiation in NHPs and can potentially be translated as a molecular diagnostic for human use following larger validation studies.

CONCLUSIONS

Taken together, this study, for the first time, demonstrates the utility of a combinatorial molecular characterization approach using an NHP model for developing minimally invasive assays from small volumes of blood that can be effectively used for radiation exposure assessments.

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.

Persistent elevation of lysophosphatidylcholine promotes radiation brain necrosis with microglial recruitment by P2RX4 activation

Brain radiation necrosis (RN) or neurocognitive disorder is a severe adverse effect that may occur after radiation therapy for malignant brain tumors or head and neck cancers. RN accompanies inflammation which causes edema or micro-bleeding, and no fundamental treatment has been developed. In inflammation, lysophospholipids (LPLs) are produced by phospholipase A₂ and function as bioactive lipids involved in sterile inflammation in atherosclerosis or brain disorders. To elucidate its underlying mechanisms, we investigated the possible associations between lysophospholipids (LPLs) and RN development in terms of microglial activation with the purinergic receptor P2X purinoceptor 4 (P2RX4). We previously developed a mouse model of RN and in this study, measured phospholipids and LPLs in the brains of RN model by liquid chromatography tandem mass spectrometry (LC–MS/MS) analyses. We immune-stained microglia and the P2RX4 in the brains of RN model with time-course. We treated RN model mice with ivermectin, an allosteric modulator of P2RX4 and investigate the effect on microglial activation with P2RX4 and LPLs’ production, and resulting effects on overall survival and working memory. We revealed that LPLs (lysophosphatidylcholine (LPC), lysophosphatidyl acid, lysophosphatidylserine, lysophosphatidylethanolamine, lysophosphatidylinositol, and lysophosphatidylglycerol) remained at high levels during the progression of RN with microglial accumulation, though phospholipids elevations were limited. Both microglial accumulation and activation of the P2RX4 were attenuated by ivermectin. Moreover, the elevation of all LPLs except LPC was also attenuated by ivermectin. However, there was limited prolongation of survival time and improvement of working memory disorders. Our findings suggest that uncontrollable increased LPC, even with ivermectin treatment, promoted the development of RN and working memory disorders. Therefore, LPC suppression will be essential for controlling RN and neurocognitive disorder after radiation therapy.

An optimized method for the isolation of urinary extracellular vesicles for molecular phenotyping: detection of biomarkers for radiation exposure

Background

Urinary extracellular vesicles (EVs) are a source of biomarkers with broad potential applications across clinical research, including monitoring radiation exposure. A key limitation to their implementation is minimal standardization in EV isolation and analytical methods. Further, most urinary EV isolation protocols necessitate large volumes of sample. This study aimed to compare and optimize isolation and analytical methods for EVs from small volumes of urine.

Methods

3 EV isolation methods were compared: ultracentrifugation, magnetic bead-based, and size-exclusion chromatography from 0.5 mL or 1 mL of rat and human urine. EV yield and mass spectrometry signals (Q-ToF and Triple Quad) were evaluated from each method. Metabolomic profiling was performed on EVs isolated from the urine of rats exposed to ionizing radiation 1-, 14-, 30- or 90-days post-exposure, and human urine from patients receiving thoracic radiotherapy for the treatment of lung cancer pre- and post-treatment.

Results

Size-exclusion chromatography is the preferred method for EV isolation from 0.5 mL of urine. Mass spectrometry-based metabolomic analyses of EV cargo identified biochemical changes induced by radiation, including altered nucleotide, folate, and lipid metabolism. We have provided standard operating procedures for implementation of these methods in other laboratories.

Conclusions

We demonstrate that EVs can be isolated from small volumes of urine and analytically investigated for their biochemical contents to detect radiation induced metabolomic changes. These findings lay a groundwork for future development of methods to monitor response to radiotherapy and can be extended to an array of molecular phenotyping studies aimed at characterizing EV cargo.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03414-7.

Plasma Proteins As Biodosimetric Markers of Low-Dose Radiation in Mice

Long-term exposures to low-dose radiation (LDR) may trigger several specific biological responses, including dysregulation of the immune and inflammatory systems. Here, we examined whether biodosimetry of LDR can be used to protect tissues from radiation or assess cancer risk. Mice were subjected to gamma-irradiation with repeated or single-dose LDR, and then the organ indices, peripheral hemogram, and blood biochemistry were analyzed. An antibody array was applied followed by enzyme-linked immunosorbent assay to evaluate the utility of multiple plasma proteins as biomarkers of repeated LDR in a murine model. LDR induced inapparent symptoms but slight variations in peripheral blood cell counts and alterations in blood biochemical indicator levels. Specific plasma proteins in the LDR groups were altered in response to a higher dose of irradiation at the same time points or a single-dose equivalent to the same total dose. Plasma levels of interleukin (IL)-5, IL-12p40, P-selectin, and serum amyloid A1 were associated with the LDR dose and thus may be useful as dosimetric predictors of LDR in mice. Estimating the levels of certain plasma proteins may yield promising biodosimetry parameters to accurately identify individuals exposed to LDR, facilitating risk assessment of long-term LDR exposure in individuals.

Effects of Low Dose Space Radiation Exposures on the Splenic Metabolome

Future space missions will include a return to the Moon and long duration deep space roundtrip missions to Mars. Leaving the protection that Low Earth Orbit provides will unavoidably expose astronauts to higher cumulative doses of space radiation, in addition to other stressors, e.g., microgravity. Immune regulation is known to be impacted by both radiation and spaceflight and it remains to be seen whether prolonged effects that will be encountered in deep space can have an adverse impact on health. In this study, we investigated the effects in the overall metabolism of three different low dose radiation exposures (γ-rays, 16O, and 56Fe) in spleens from male C57BL/6 mice at 1, 2, and 4 months after exposure. Forty metabolites were identified with significant enrichment in purine metabolism, tricarboxylic acid cycle, fatty acids, acylcarnitines, and amino acids. Early perturbations were more prominent in the γ irradiated samples, while later responses shifted towards more prominent responses in groups with high energy particle irradiations. Regression analysis showed a positive correlation of the abundance of identified fatty acids with time and a negative association with γ-rays, while the degradation pathway of purines was positively associated with time. Taken together, there is a strong suggestion of mitochondrial implication and the possibility of long-term effects on DNA repair and nucleotide pools following radiation exposure.