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

Effects of X-ray cranial irradiation on metabolomics and intestinal flora in mice

Cranial radiotherapy is an important treatment for intracranial and head and neck tumors. To investigate the effects of cranial irradiation (C-irradiation) on gut microbiota and metabolomic profile, the feces, plasma and cerebral cortex were isolated after exposing mice to cranial X-ray irradiation at a dose rate of 2.33 Gy/min (5 Gy/d for 4 d consecutively). The gut microorganisms and metabolites were detected by 16 S rRNA gene sequencing method and LC-MS method, respectively. We found that compared with sham group, the gut microbiota composition changed at 2 W and 4 W after C-irradiation at the genus level. The fecal metabolomics showed that compared with Sham group, 44 and 66 differential metabolites were found to be annotated into metabolism pathways at 2 W and 4 W after C-irradiation, which were significantly enriched in the arginine and proline metabolism. Metabolome analysis of serum and cerebral cortex showed that, at 4 W after C-irradiation, the expression pattern of metabolites in serum samples of mice was similar to that of sham group, and the cerebral cortex metabolites of the two groups were completely separated. KEGG functional analysis showed that serum and brain tissue differential metabolites were respectively enriched in tryptophan metabolism, and arginine proline metabolism. The correlation analysis showed that the changes of gut microbiota genera were significantly correlated with the changes of metabolism, especially Helicobacter, which was significantly correlated with many different metabolites at 4 W after C-irradiation. These data suggested that C-irradiation could affect the gut microbiota and metabolism profile, even at relatively long times after C-irradiation.

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.

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.

Machine learning approach for quantitative biodosimetry of partial-body or total-body radiation exposures by combining radiation-responsive biomarkers

During a large-scale radiological event such as an improvised nuclear device detonation, many survivors will be shielded from radiation by environmental objects, and experience only partial-body irradiation (PBI), which has different consequences, compared with total-body irradiation (TBI). In this study, we tested the hypothesis that applying machine learning to a combination of radiation-responsive biomarkers (ACTN1, DDB2, FDXR) and B and T cell counts will quantify and distinguish between PBI and TBI exposures. Adult C57BL/6 mice of both sexes were exposed to 0, 2.0-2.5 or 5.0 Gy of half-body PBI or TBI. The random forest (RF) algorithm trained on ½ of the data reconstructed the radiation dose on the remaining testing portion of the data with mean absolute error of 0.749 Gy and reconstructed the product of dose and exposure status (defined as 1.0 × Dose for TBI and 0.5 × Dose for PBI) with MAE of 0.472 Gy. Among irradiated samples, PBI could be distinguished from TBI: ROC curve AUC = 0.944 (95% CI: 0.844-1.0). Mouse sex did not significantly affect dose reconstruction. These results support the hypothesis that combinations of protein biomarkers and blood cell counts can complement existing methods for biodosimetry of PBI and TBI exposures.

Microbial compositions, ecological networks, and metabolomics in sediments of black-odour water in Dongguan, China

Black-odour water with organic compounds and heavy metals caused by domestic and industrial activities has aroused people's attention in recent years, yet little is known about the ecological effects on aquatic organisms, especially microorganisms in sediments. To explore the response of microbial communities to environmental factors, the community and metabolites of nine river sediments with different pollution in Dongguan city, China were investigated using 16S rRNA gene sequencing and liquid chromatography tandem-mass. The results revealed that the composition and structure of sedimentary microbial communities significantly changed in rivers with varying pollution levels. Cyanobacteria were the most abundant organisms in the sediment of black-odorous rivers, while the relative abundance of Thaumarchaeota was gradually increased with the river quality gets better. The relative abundance of organic acids (including amino acids), alcohols, esters, and ketones associated with microbial metabolism in sediments of polluted rivers was increased. The 16S rRNA gene sequencing-based molecular ecological network analysis indicated that the interactions amongst bacteria were enhanced in severely contaminated communities. Sphingomonadaceae and Cyanobacteria have important roles in bacterial community structures of polluted rivers and those with ongoing treatment. The correlation analysis showed significant metal resistance and/or tolerance of the following bacteria species Thalassiosira weissflogii, Aminicenantes bacterium clone OPB95, 'Candidatus Halomonas phosphatis', and archaeal species Methanolinea and unidentified Thermoplasmata. These results indicated that sedimentary microbial communities may shift in composition and structure, as well as their interaction network, to adapt and resist environmental contamination and promote restoration.

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.

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

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

Metabolomics-driven of relationships among kidney, bone marrow and bone of rats with postmenopausal osteoporosis

As a global public health problem, postmenopausal osteoporosis (PMOP) poses a great threat to old women's health. Bone is the target organ of PMOP, and the dynamic changes of bone marrow could affect the bone status. Kidney is the main organ regulating calcium and phosphorus homeostasis. Kidney, bone marrow and bone play crucial roles in PMOP, but the relationships of the three tissues in the disease have not been completely described. Here, metabolomics was employed to investigate the disease mechanism of PMOP from the perspectives of kidney, bone marrow and bone, and the relationships among the three tissues were also discussed. Six-month-old female Sprague-Dawley (SD) rats were randomly divided into ovariectomized (OVX) group (with bilateral ovariectomy) and sham group (with sham surgery). 13 weeks after surgery, gas chromatography-mass spectrometry (GC-MS) was performed to analyze the metabolic profiling of two groups. Multivariate statistical analysis revealed that the number of differential metabolites in kidney, bone marrow and bone between the two groups were 37, 16 and 17, respectively. The common differential metabolites of the three tissues were N-methyl-L-alanine. Kidney and bone marrow had common differential metabolites, including N-methyl-L-alanine, 2-hydroxybutyric acid, (R)-3-hydroxybutyric acid (β-hydroxybutyric acid, βHBA), urea and dodecanoic acid. There were three common differential metabolites between kidney and bone, including N-methyl-L-alanine, α-tocopherol and isofucostanol. The common differential metabolite of bone marrow and bone was N-methyl-L-alanine. Some common metabolic pathways were disturbed in multiple tissues of OVX rats, such as glycine, serine and threonine metabolism, purine metabolism, tryptophan metabolism, ubiquinone and other terpenoid-quinone biosynthesis and fatty acid biosynthesis. In conclusion, our study demonstrated that profound metabolic changes have taken place in the kidney, bone marrow and bone, involving common differential metabolites and metabolic pathways. The evaluation of differential metabolites strengthened the understanding of the kidney-bone axis and the metabolic relationships among the three tissues of OVX rats.

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.

Radiotherapy-induced alterations in vitreous humor: A new potential critical structure

Vitreous humor (VH) is not considered as a critical structure in the radiotherapy planning process. In the present study, an experimental animal model was performed to examine the effects of radiotherapy on VH. The right eyes of twelve New Zealand rabbits were irradiated to 60 Gy in 3 fractions in accordance with the scheme used in the treatment of uveal melanoma in our clinic, and contralateral (left) eyes were considered as control. Weekly ophthalmologic examination was performed after irradiation, for three months. At the end of the third month, enucleation and vitreous collection were conducted. The vitreous samples were subjected to metabolomic analyses, ELISA analyses, viscosity measurements, and electron microscopic examination. In control and experimental vitreous samples, 275 different metabolites were identified, and 34 were found to differ significantly between groups. In multivariate analyzes, a clear distinction was observed between control and irradiated vitreous samples. Pathway analysis revealed that nine pathways were affected, and these pathways were mainly related to amino acid metabolism. A significant decrease was observed in the expressions of type II, V, and XI collagens in protein level in the ELISA. There was a non-significant decrease in type IX collagen and viscosity. Electron microscopic examination revealed disrupted collagen fibrillar ultra-structure and dispersed collagen fragments in the experimental vitreous. An intact vitreous is essential for a healthy eye. In this study, we observed that radiation causes changes in the vitreous that may have long-term consequences.

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

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

NMR-Based Metabolomics in Investigation of the Radiation Induced Changes in Blood Serum of Head and Neck Cancer Patients and Its Correlation with the Tissue Volumes Exposed to the Particulate Doses

In the present study, we analyze the nuclear magnetic resonance (NMR) blood serum metabolic profiles of 106 head and neck squamous cell carcinoma (HNSCC) patients during radio (RT) and concurrent radio-chemotherapy (CHRT). Four different fractionation schemes were compared. The blood samples were collected weekly, from the day before the treatment until the last week of CHRT/RT. The NMR spectra were acquired on A Bruker 400 MHz spectrometer at 310 K and analyzed using multivariate methods. Seven metabolites were found significantly to be altered solely by radiotherapy: N-acetyl-glycoprotein (NAG), N-acetylcysteine, glycerol, glycolate and the lipids at 0.9, 1.3 and 3.2 ppm. The NMR results were correlated with the tissue volumes receiving a particular dose of radiation. The influence of the irradiated volume on the metabolic profile is weak and mainly limited to sparse correlations with the inflammatory markers, creatinine and the lymphocyte count in RT and the branched-chain amino-acids in CHRT. This is probably due to the optimal planning and delivery of radiotherapy improving sparing of the surrounding normal tissues and minimizing the differences between the patients (caused by the tumor location and size).