Abstract:In the event of an improvised nuclear device or "dirty bomb" in a highly populated area, potentially hundreds of thousands of people will require screening to ensure that exposed individuals receive appropriate treatment. For this reason, there is a need to develop tools for high-throughput radiation biodosimetry. Gene expression represents an emerging approach to biodosimetry and could potentially provide an estimate of both absorbed dose and individual radiation-induced injury. Since approximately 2-4% of hu… Show more
“…In a previous study, we had shown that genes selected from WT mice performed poorly in detecting exposure to an LD 50/30 radiation dose in two mouse models of DNA repair deficiency ( Atm −/− and Prkdc scid ), but that inclusion of both WT and DNA repair deficient mice in the training set improved performance on both mutant and WT test sets to 100% [47]. We tested the ability of this earlier signature to predict radiation exposure in Il10 −/− mice.…”
Background
Ionizing Radiation (IR) is a known pro-inflammatory agent and in the process of development of biomarkers for radiation biodosimetry, a chronic inflammatory disease condition could act as a confounding factor. Hence, it is important to develop radiation signatures that can distinguish between IR-induced inflammatory responses and pre-existing disease. In this study, we compared the gene expression response of a genetically modified mouse model of inflammatory bowel disease (
Il10
−/−
)
with that of a normal wild-type mouse to potentially develop transcriptomics-based biodosimetry markers that can predict radiation exposure in individuals regardless of pre-existing inflammatory condition.
Results
Wild-type (WT) and
Il10
−/−
mice were exposed to whole body irradiation of 7 Gy X-rays. Gene expression responses were studied using high throughput whole genome microarrays in peripheral blood 24 h post-irradiation. Analysis resulted in identification of 1962 and 1844 genes differentially expressed (
p
< 0.001, FDR < 10%) after radiation exposure in
Il10
−/−
and WT mice respectively. A set of 155 genes was also identified as differentially expressed between WT and
Il10
−/−
mice at the baseline pre-irradiation level. Gene ontology analysis revealed that the 155 baseline differentially expressed genes were mainly involved in inflammatory response, glutathione metabolism and collagen deposition. Analysis of radiation responsive genes revealed that innate immune response and p53 signaling processes were strongly associated with up-regulated genes, whereas B-cell development process was found to be significant amongst downregulated genes in the two genotypes. However, specific immune response pathways like MHC based antigen presentation, interferon signaling and hepatic fibrosis were associated with radiation responsive genes in
Il10
−/−
mice but not WT mice. Further analysis using the IPA prediction tool revealed significant differences in the predicted activation status of T-cell mediated signaling as well as regulators of inflammation between WT and
Il10
−/−
after irradiation.
Conclusions
Using a mouse model we established that an inflammatory disease condition could affect the expression of many radiation responsive genes. Nevertheless, we identified a panel of genes that, regardless of disease condition, could predict radiation exposure. Our results highlight the need for consideration of pre-existing conditions in the population in the process of development of reliable biodosimetry markers.
Electronic supplementary material
The online version of this article (10.1186/s12864-019-5689-y) contain...
“…In a previous study, we had shown that genes selected from WT mice performed poorly in detecting exposure to an LD 50/30 radiation dose in two mouse models of DNA repair deficiency ( Atm −/− and Prkdc scid ), but that inclusion of both WT and DNA repair deficient mice in the training set improved performance on both mutant and WT test sets to 100% [47]. We tested the ability of this earlier signature to predict radiation exposure in Il10 −/− mice.…”
Background
Ionizing Radiation (IR) is a known pro-inflammatory agent and in the process of development of biomarkers for radiation biodosimetry, a chronic inflammatory disease condition could act as a confounding factor. Hence, it is important to develop radiation signatures that can distinguish between IR-induced inflammatory responses and pre-existing disease. In this study, we compared the gene expression response of a genetically modified mouse model of inflammatory bowel disease (
Il10
−/−
)
with that of a normal wild-type mouse to potentially develop transcriptomics-based biodosimetry markers that can predict radiation exposure in individuals regardless of pre-existing inflammatory condition.
Results
Wild-type (WT) and
Il10
−/−
mice were exposed to whole body irradiation of 7 Gy X-rays. Gene expression responses were studied using high throughput whole genome microarrays in peripheral blood 24 h post-irradiation. Analysis resulted in identification of 1962 and 1844 genes differentially expressed (
p
< 0.001, FDR < 10%) after radiation exposure in
Il10
−/−
and WT mice respectively. A set of 155 genes was also identified as differentially expressed between WT and
Il10
−/−
mice at the baseline pre-irradiation level. Gene ontology analysis revealed that the 155 baseline differentially expressed genes were mainly involved in inflammatory response, glutathione metabolism and collagen deposition. Analysis of radiation responsive genes revealed that innate immune response and p53 signaling processes were strongly associated with up-regulated genes, whereas B-cell development process was found to be significant amongst downregulated genes in the two genotypes. However, specific immune response pathways like MHC based antigen presentation, interferon signaling and hepatic fibrosis were associated with radiation responsive genes in
Il10
−/−
mice but not WT mice. Further analysis using the IPA prediction tool revealed significant differences in the predicted activation status of T-cell mediated signaling as well as regulators of inflammation between WT and
Il10
−/−
after irradiation.
Conclusions
Using a mouse model we established that an inflammatory disease condition could affect the expression of many radiation responsive genes. Nevertheless, we identified a panel of genes that, regardless of disease condition, could predict radiation exposure. Our results highlight the need for consideration of pre-existing conditions in the population in the process of development of reliable biodosimetry markers.
Electronic supplementary material
The online version of this article (10.1186/s12864-019-5689-y) contain...
“…Gene ontology analysis of the set of 381 sustained response genes using PANTHER indicated significant enrichment of pathways and processes related to immune functions, as well as apoptotic processes and p53 signalling (Supplementary File 2). These processes have previously been shown to be prominent in both the mouse and human response to radiation during the first week after in vivo exposure, with similar patterns of increasing duration of effect at increasing doses 13,25,37–39 .…”
Due to limitations of available human models for development of gene expression based radiation biodosimetry, many such studies have made use of mouse models. To provide a broad view of the gene expression response to irradiation in the mouse, we have exposed male C57BL/6 mice to 0, 1.5, 3, 6 or 10 Gy of gamma rays, sacrificing groups of the mice at 1, 2, 3, 5, or 7 days after exposure. We then profiled global gene expression in blood from individual mice using Agilent microarrays. In general, we found increasing numbers of genes differentially expressed with increasing dose, with more prolonged responses after the higher doses. Gene ontology analysis showed a similar pattern, with more biological processes enriched among the genes responding to higher doses, and at later times after exposure. Clustering the timecourse expression data using maSigPro identified four broad patterns of response, representing different gene ontology functions. The largest of these clusters included genes with initially decreased expression followed by increased expression at later times, a pattern of expression previously reported for several genes following neutron exposure. Another gene cluster showing consistent down regulation suggests genes useful for biodosimetry throughout the first week after exposure can be identified.
“…We were, therefore, interested in comparing gene expression between these two species to determine the extent of these differences, as well as better defining the similarities between the two species in order to improve the translatability of radiation signatures between mice and humans. We started by using the datasets summarized in Table 1, which allowed us to compare similar doses in human samples both in vivo (3.75 Gy) 18 and ex vivo (8 Gy) 3 ; and mouse in vivo samples at 4 Gy 23 and 8 Gy 31 . After identifying the genes that were differentially regulated and comparing these side-by-side between the two species (Fig.…”
Section: Resultsmentioning
confidence: 99%
“…3 Mouse 8 Gy780GSE99176Rudqvist et al . 31 *Benjamini-Hochberg false discovery rate.All studies were performed on whole blood samples, irradiated with the dose indicated (Gy), and RNA isolated 24 hr later.Figure 1Heat map of gene expression changes from human and mouse microarray studies. ( a ) Similar response patterns in human and mouse.…”
The mouse (Mus musculus) is an extensively used model of human disease and responses to stresses such as ionizing radiation. As part of our work developing gene expression biomarkers of radiation exposure, dose, and injury, we have found many genes are either up-regulated (e.g. CDKN1A, MDM2, BBC3, and CCNG1) or down-regulated (e.g. TCF4 and MYC) in both species after irradiation at ~4 and 8 Gy. However, we have also found genes that are consistently up-regulated in humans and down-regulated in mice (e.g. DDB2, PCNA, GADD45A, SESN1, RRM2B, KCNN4, IFI30, and PTPRO). Here we test a hematopoietically humanized mouse as a potential in vivo model for biodosimetry studies, measuring the response of these 14 genes one day after irradiation at 2 and 4 Gy, and comparing it with that of human blood irradiated ex vivo, and blood from whole body irradiated mice. We found that human blood cells in the hematopoietically humanized mouse in vivo environment recapitulated the gene expression pattern expected from human cells, not the pattern seen from in vivo irradiated normal mice. The results of this study support the use of hematopoietically humanized mice as an in vivo model for screening of radiation response genes relevant to humans.
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