Dataset Information

Lung transcriptome of nonhuman primates exposed to total- and partial-body irradiation.

ABSTRACT: The focus of radiation biodosimetry has changed recently, and a paradigm shift for using molecular technologies of omic platforms in addition to cytogenetic techniques has been observed. In our study, we have used a nonhuman primate model to investigate the impact of a supralethal dose of 12 Gy radiation on alterations in the lung transcriptome. We used 6 healthy and 32 irradiated animal samples to delineate radiation-induced changes. We also used a medical countermeasure, γ-tocotrienol (GT3), to observe any changes. We demonstrate significant radiation-induced changes in the lung transcriptome for total-body irradiation (TBI) and partial-body irradiation (PBI). However, no major influence of GT3 on radiation was noted in either comparison. Several common signaling pathways, including PI3K/AKT, GADD45, and p53, were upregulated in both exposures. TBI activated DNA-damage-related pathways in the lungs, whereas PTEN signaling was activated after PBI. Our study highlights the various transcriptional profiles associated with γ- and X-ray exposures, and the associated pathways include LXR/RXR activation in TBI, whereas pulmonary wound-healing and pulmonary fibrosis signaling was repressed in PBI. Our study provides important insights into the molecular pathways associated with irradiation that can be further investigated for biomarker discovery.

SUBMITTER: Vellichirammal NN

PROVIDER: S-EPMC9418744 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Lung transcriptome of nonhuman primates exposed to total- and partial-body irradiation.

Vellichirammal Neetha Nanoth NN Sethi Sahil S Pandey Sanjit S Singh Jatinder J Wise Stephen Y SY Carpenter Alana D AD Fatanmi Oluseyi O OO Guda Chittibabu C Singh Vijay K VK

Molecular therapy. Nucleic acids 20220804

The focus of radiation biodosimetry has changed recently, and a paradigm shift for using molecular technologies of omic platforms in addition to cytogenetic techniques has been observed. In our study, we have used a nonhuman primate model to investigate the impact of a supralethal dose of 12 Gy radiation on alterations in the lung transcriptome. We used 6 healthy and 32 irradiated animal samples to delineate radiation-induced changes. We also used a medical countermeasure, γ-tocotrienol (GT3), t ...[more]

PMID: 36090752

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

Project description:In the event of a radiological or nuclear attack, advanced clinical countermeasures are needed for screening and medical management of the exposed population. In such a scenario, minimally invasive biomarkers that can accurately quantify radiation exposure would be useful for triage management by first responders. In this murine study, we evaluated the efficacy of a novel combination of radiation responsive proteins, Flt3 ligand (FL), serum amyloid A (SAA), matrix metalloproteinase 9 (MMP9), fibrinogen beta (FGB) and pentraxin 3 (PTX3) to predict the received dose after whole- or partial-body irradiation. Ten-week-old female C57BL6 mice received a single whole-body or partial-body dose of 18 Gy from a Pantak X-ray source at a dose rate of 2.28 Gy/min. Plasma was collected by cardiac puncture at 24, 48, 72 h and 1 week postirradiation. Plasma protein levels were determined via commercially available ELISA assay. A multivariate discriminant analysis was utilized to generate best-fit dose prediction models for whole-body exposures using the selected biomarker panel and its potential application to partial-body exposures was examined. The combination of values from FL, SAA, MMP9, FGB and PTX3 between 24 h and 1 week postirradiation yielded novel dose-response relationships. For day 1 postirradiation, the best-fit model yielded a predictive accuracy of 81% utilizing FL alone. The use of additional proteins did not enhance the model accuracy whereas, at day 2 postirradiation, the addition of PTX3 and FGB to FL increased the accuracy to 100%. At day 3 the use of FL and PTX3 yielded a predictive accuracy of 93% and at day 7 use of FL and SAA had an accuracy of 90%. Dose prediction of partial-body exposures based on the TBI model had a higher predictive accuracy when the percentage of the body exposed to radiation increased. Our findings indicate that this novel combination of radiation responsive biomarker proteins are an efficient method for predicting radiation exposure and are more accurate when used in concert compared to using any single biomarker protein alone.

Dataset Information

Lung transcriptome of nonhuman primates exposed to total- and partial-body irradiation.

Publications

Lung transcriptome of nonhuman primates exposed to total- and partial-body irradiation.

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