Abstract High-Linear Energy Transfer (LET) ion radiation, such as 28Si ions, is densely ionizing and poses a significant risk to astronauts during long-duration space missions. We previously showed that mice exposed to high-LET ionizing radiation (IR) exhibit greater accumulation of senescent cells in the intestine than those exposed to equivalent doses of low-LET γ-rays. However, the mechanisms driving this persistent senescence remain unclear. Given the role of Natural killer (NK) cells in senescent cell clearance, we investigated the impact of IR on intestinal NK cell function. At 60 days post-irradiation, intestinal tissues from 28Si-exposed mice showed a significant reduction in NKp46⁺ NK cells and decreased expression of molecules associated with NK activation and epithelial interactions. NK cell subtype analysis further revealed a decline in functionally mature populations involved in recognizing stressed cells. In parallel, intestinal epithelial cells (IECs) displayed altered expression of NK cell regulatory ligands, including reduced activating signals and increased inhibitory signaling associated with Qa-1b (non-classical MHC class Ib). Mechanistically, these changes were linked to activation of p38 Mitogen-Activated Protein Kinase (MAPK) signaling. Using irradiated intestinal organoids, we observed that pharmacological inhibition of the p38 MAPK pathway decreased Qa-1b expression and enhanced NK cell cytotoxic activity. Causality experiments further demonstrated that Qa-1b directly regulates NK cell–mediated cytotoxicity against senescent IECs. Collectively, these findings indicate that high-LET IR compromises intestinal immune surveillance by impairing NK cell function through a p38 MAPK–Qa-1b signaling axis, providing mechanistic insight into radiation-induced immune dysregulation.

T cells, which are generally highly sensitive to DNA damage-induced cell death, exhibit distinct responses to ionizing radiation (IR) depending on their differentiation state. In this study, we investigated the heightened radiosensitivity of naïve T cells (Tn) compared to memory T cells (Tm) through in vivo and in vitro models. Following whole-body irradiation (WBI), naïve T cells, particularly naïve CD8+ T cells, displayed significant depletion and delayed recovery, compared to their Tm counterparts. Transcriptomic analyses revealed similar p53 pathway activation in both Tn and Tm postirradiation but highlighted key differences in cytokine signaling and metabolic profiles between these two cell states. Tm cells showed elevated expression of survival-promoting cytokine receptors, anti-apoptotic genes, and mitochondrial respiratory activity, coupled with robust antioxidative defense systems, including increased glutathione synthesis and thioredoxin reductase activity. Supplementation with N-acetylcysteine, a reactive oxygen species (ROS) scavenger, partially mitigated Tn depletion after WBI, underscoring the role of oxidative stress in Tn radiosensitivity. These findings suggest that the metabolic and antioxidative adaptations of Tm confer greater intrinsic resilience against radiation-induced damage than those of Tn. This disparity underscores the importance of targeted interventions to preserve naïve T cell populations and maintain immune balance after radiation exposure.

Hepatic ischemia-reperfusion injury (IRI) is a complex event influenced by interconnected immune and metabolic processes. Steatotic livers are especially sensitive to IRI, but the crosstalk between innate inflammatory responses and lipid metabolic dysregulation in this context is not well understood. Using transcriptomic profiling in a murine high-fat diet (HFD) model, we assessed immune and metabolic responses to hepatic IRI and examined the effects of N-acetylcysteine (NAC). In steatotic livers, IRI induced the upregulation of inflammatory mediators, including TLR/NF-κB-associated genes (Tlr2, Tlr4, Irf1) and neutrophil-associated genes (S100a8, S100a9, Lcn2), accompanied by the downregulation of lipid and cholesterol metabolism-related genes, including Cyp7a1, Cyp8b1, Cyp27a1, and Hmgcr. NAC supplementation attenuated inflammatory gene expression and restored key lipid biosynthetic regulators. We then performed targeted lipidomic analysis to determine whether NAC-mediated transcriptional changes were reflected at the lipid level and observed a significant increase in total phosphatidylcholine and sphingomyelin in steatotic livers following IRI. Finally, to assess the contribution of innate immune cells to hepatic IRI, we quantified neutrophils and macrophages in HFD+NAC IRI and HFD IRI livers. We found that NAC supplementation reduced hepatic neutrophil accumulation and markedly decreased LCN2 expression following IRI.

In addition to immediate cell lethality, radiation exposure has long-term effects on the immune system, particularly T lymphocytes, causing persistent functional abnormalities post-exposure. Uncertainties remain regarding the long-lasting consequences on T cell immunity in survivors of the acute radiation syndrome and the underlying mechanisms of those consequences. Here, we investigated delayed effects of acute radiation exposure on CD8+ T cell immunity using the Listeria monocytogenes infection model. Impaired CD8+ T cell activation, reduced terminal effector formation upon infection, and exacerbated listeriosis were found in mice at 4 weeks postirradiation with sublethal doses. To elucidate how radiation affects the functionality of CD8+ T cells at various differentiation stages, we performed single-cell transcriptomic profiling. Radiation altered cluster distribution pre-infection and impaired terminal effector and memory precursor effector formation post-infection. Differential gene analysis highlighted radiation-induced gene expression changes, including cytokines and mitochondrial proteins, in a cluster-specific manner post-infection. The study demonstrates dysfunction of newly replenished naïve T cells, which results in impaired CD8+ T cell immunity after irradiation.

Accurate biodosimetry is essential for medical response during nuclear emergencies. However, mixed-field radiation and secondary infections create significant diagnostic challenges. This study aimed to characterize persistent serum lipidomic alterations following mixed-field exposures at long-term time points and evaluate the impact of a delayed secondary infection on radiation-associated signatures to determine the feasibility of serum biomarkers for complex biodosimetry. Target serum lipidomics and untargeted metabolomics were performed on male C57BL/6 mice 6 weeks after a 3 Gy total body irradiation (TBI) with X rays or mixed γ-ray/neutron fields (5

The current genotoxicity testing paradigm provides little mechanistic information, has poor specificity in predicting carcinogenicity in humans, and is not suited to assessing a large number of chemicals. Genomic technologies enable the characterization of genome-wide transcriptional changes in response to chemical treatments that can inform mechanisms or modes of action. These technologies provided an impetus to develop transcriptomic biomarkers that could transform genotoxicity hazard assessment for drugs, cosmetics, and environmental and industrial chemicals. In August 2022, the International Workshops on Genotoxicity Testing (IWGT) held a workshop to critically review progress in the development and application of transcriptomic biomarkers in genotoxicity testing. Here, we describe the findings of this workshop's subgroup that conducted a systematized review and analysis of in vitro transcriptomic biomarkers for evaluating genotoxicity. Although there is a multitude of published reports exploring transcriptomics in genetic toxicology, the working group identified only five in vitro transcriptomic biomarker candidates, of which three (GENOMARK, TGx-DDI, and MU2012) were independently developed with sufficiently defined context of use, validation data, and supporting case studies that warranted inclusion in the review. Although these in vitro biomarkers were developed independently and for different classes of chemicals (TGx-DDI for pharmaceuticals, GENOMARK for cosmetics, and MU2012 for medical and environmental chemicals), they all address the same shortfall of the standard in vitro genotoxicity testing battery, that is, lack of specificity by genotoxicity-induced stress response at the transcriptomic level. In this review, we discuss the development of these in vitro biomarkers, including challenges and progress toward achieving regulatory acceptance.

Rapid biodosimetry tools are needed to assess radiation exposure in scenarios complicated by secondary infections. This study evaluated how Listeria monocytogenes infection impacts metabolite-based biodosimetry in male C57BL/6 mice. The mice were infected and exposed to 0, 2, or 6 Gy X-rays at 4 days postinfection. Untargeted metabolomics was performed on serum and urine at 1 day postirradiation. We found that the effect of bacterial infection increased white blood cell counts and altered metabolomic signatures in a biofluid- and compound-specific manner. Infection alone altered select serum lipids and urinary TCA intermediates. Some urinary metabolites displayed additive effects in infected animals exposed to 6 Gy. The best model for combined biofluids (serum: lysophosphatidylcholines [14:0] and [22:5], glycerophosphatidylcholines [42:8] and [42:11] and citrate; urine: glutamic acid, creatine, propionylcarnitine, acetylspermidine, and hexanoylglycine) was determined with a multivariate random forest analysis model. A combined biofluid random forest model predicted the radiation dose and infection status with 90% accuracy (RMSE = 1.31 Gy). These findings support the development of robust, multiplexed biodosimetry panels capable of accounting for real-world confounders like infection. Such models can improve the precision of triage decisions following radiological emergencies (raw data available at Metabolomics Workbench Study IDs ST004101 and ST004100).

Gene expression biomarkers have the potential to identify genotoxic and non-genotoxic carcinogens, providing opportunities for integrated testing and reducing animal use. In August 2022, an International Workshops on Genotoxicity Testing (IWGT) workshop was held to critically review current methods to identify genotoxicants using transcriptomic profiling. Here, we summarize the findings of the workgroup on the state of the science regarding the use of transcriptomic biomarkers to identify genotoxic chemicals in vitro and in vivo. A total of 1341 papers were examined to identify the biomarkers that show the most promise for identifying genotoxicants. This analysis revealed two independently derived in vivo biomarkers and three in vitro biomarkers that, when used in conjunction with standard computational techniques, can identify genotoxic chemicals in vivo (rat or mouse liver) or in human cells in culture using different gene expression profiling platforms, with predictive accuracies of ≥92%. These biomarkers have been validated to differing degrees but typically show high reproducibility across transcriptomic platforms and model systems. They offer several advantages for applications in different contexts of use in genotoxicity testing including: early signal detection, moderate-to-high-throughput screening capacity, adaptability to different cell types and tissues, and insights on mechanistic information on DNA-damage response. Workshop participants agreed on consensus statements to advance the regulatory adoption of transcriptomic biomarkers for genotoxicity. The participants agreed that transcriptomic biomarkers have the potential to be used in conjunction with other biomarkers in integrated test strategies in vitro and using short-term rodent exposures to identify genotoxic and non-genotoxic chemicals that may cause cancer and heritable genetic effects. Following are the consensus statements from the workgroup. Transcriptomic biomarkers for genotoxicity can be used in Weight of Evidence (WoE) evaluation to: determine potential genotoxic mechanisms and hazards; identify misleading positives from in vitro genotoxicity assays; serve as new approach methodologies (NAMs) integrated into the standard battery of genotoxicity tests. Several transcriptomic biomarkers have been developed from sufficiently robust training data sets, validated with external test sets, and have demonstrated performance in multiple laboratories. These transcriptomic biomarkers can be used following established study designs and models designated through existing validation exercises in WoE evaluation. Bridging studies using a selection of training and test chemicals are needed to deviate from the established protocols to confirm performance when a transcriptomic biomarker is being applied in other: tissues, cell models, or gene expression platforms. Top dose selection and time of gene expression analysis are critical and should be established during transcriptomic biomarker development. These conditions are the only ones suited for transcriptomic biomarker use unless additional bridging or pharmacokinetic studies are conducted. Temporal effects for genotoxicants that operate via distinct mechanisms should be considered in data interpretation. Fixed transcriptomic biomarker gene sets and analytical processes do not need to be independently rederived in biomarker validation. Validation should focus on the performance of the gene set in external test sets. Robust external testing should ensure a minimum of additional chemicals spanning genotoxic and non-genotoxic modes of action. Genes in the transcriptomic biomarker do not need to be known to be mechanistically involved in genotoxicity responses. Existing frameworks described for NAMs could be applied for validation of transcriptomic biomarkers. Reproducibility of bioinformatic analysis is critical for the regulatory application of transcriptomic biomarkers. A bioinformatics expert should be involved with creating reproducible methods for the qualification and application of each transcriptomic biomarker.

Standard in vitro genotoxicity assays often suffer from low specificity, leading to irrelevant positive findings that require costly in vivo follow-up studies. The TGx-DDI (Toxicogenomic DNA Damage-Inducing) transcriptomic biomarker was developed to address this limitation by identifying DNA damage-inducing compounds through gene expression profiling in human TK6 lymphoblastoid cells. To qualify TGx-DDI as a reliable, reproducible biomarker for augmenting genotoxicity hazard assessment, a multi-site ring-trial was conducted across four laboratories using 14 blinded test compounds and standardized protocols. TK6 cells were exposed to three concentrations of each compound, followed by RNA extraction and digital nucleic acid counting using the NanoString nCounter platform. A three-pronged bioinformatics approach-Nearest Shrunken Centroid Probability Analysis, Principal Component Analysis, and Hierarchical Clustering-was used to assign DDI or non-DDI classifications. TGx-DDI demonstrated 100% sensitivity, 86% specificity, and 91% accuracy in distinguishing DDI from non-DDI compounds under validated test conditions. High interlaboratory concordance was observed (agreement coefficients ≥0.61), and transcriptomic data showed strong cross-site correlation (Pearson r > 0.84). The biomarker reproducibly classified test agents even when conducted across study sites. These results demonstrate that TGx-DDI is a robust and reproducible transcriptomic biomarker that enhances the specificity of genotoxicity testing by distinguishing biologically relevant DNA damage responses. Its integration into genotoxicity testing strategies can support regulatory decision-making, reduce unnecessary animal use, and improve the assessment of human health risks.

This review focuses on early discoveries that contributed to our understanding and the scope of transcriptional responses after radiation damage. Before the development of modern approaches to assess overall global transcriptomic responses, the idea that mammalian cells could respond to DNA-damaging agents in a manner analogous to bacteria was not generally accepted. To investigate this possibility, the development of technology to identify differentially expressed low-abundance transcripts substantially facilitated our appreciation that DNA damaging agents like UV radiation and subsequently ionizing radiation did in fact produce robust transcriptional responses. Here we focus on our identification and characterization of radiation-inducible genes, and how even early studies on stress gene signaling highlighted the broad scope of transcriptional responses to radiation damage. Since then, the central role of transcriptional responses to radiation injury in maintaining genome integrity has been highlighted in many processes, including cell cycle checkpoint control, resistance to cancer by p53 and other key factors, cell senescence, and metabolism.

Development of novel biodosimetry assays and medical countermeasures is needed to obtain a level of radiation preparedness in the event of malicious or accidental mass exposures to ionizing radiation (IR). For biodosimetry, metabolic profiling with mass spectrometry (MS) platforms has identified several small molecules in easily accessible biofluids that are promising for dose reconstruction. As our microbiome has profound effects on biofluid metabolite composition, it is of interest how variation in the host microbiome may affect metabolomics based biodosimetry. Here, we ‘knocked out’ the microbiome of male and female C57BL/6 mice (Abx mice) using antibiotics and then irradiated (0, 3, or 8 Gy) them to determine the role of the host microbiome on biofluid radiation signatures (1 and 3 d urine, 3 d serum). Biofluid metabolite levels were compared to a sham and irradiated group of mice with a normal microbiome (Abx-con mice). To compare post-irradiation effects in urine, we calculated the Spearman’s correlation coefficients of metabolite levels with radiation dose. For selected metabolites of interest, we performed more detailed analyses using linear mixed effect models to determine the effects of radiation dose, time, and microbiome depletion. Serum metabolite levels were compared using an ANOVA. Several metabolites were affected after antibiotic administration in the tryptophan and amino acid pathways, sterol hormone, xenobiotic and bile acid pathways (urine) and lipid metabolism (serum), with a post-irradiation attenuative effect observed for Abx mice. In urine, dose×time interactions were supported for a defined radiation metabolite panel (carnitine, hexosamine-valine-isoleucine [Hex-V-I], creatine, citric acid, and Nε,Nε,Nε-trimethyllysine [TML]) and dose for N1-acetylspermidine, which also provided excellent (AUROC ≥ 0.90) to good (AUROC ≥ 0.80) sensitivity and specificity according to the area under the receiver operator characteristic curve (AUROC) analysis. In serum, a panel consisting of carnitine, citric acid, lysophosphatidylcholine (LysoPC) (14:0), LysoPC (20:3), and LysoPC (22:5) also gave excellent to good sensitivity and specificity for identifying post-irradiated individuals at 3 d. Although the microbiome affected the basal levels and/or post-irradiation levels of these metabolites, their utility in dose reconstruction irrespective of microbiome status is encouraging for the use of metabolomics as a novel biodosimetry assay.

Supplementary Figure 1A from Wip1 Directly Dephosphorylates γ-H2AX and Attenuates the DNA Damage Response

Radiation therapy is an effective cancer treatment, although damage to healthy tissues is common. Here we analyzed cell-free, methylated DNA released from dying cells into the circulation to evaluate radiation-induced cellular damage in different tissues. To map the circulating DNA fragments to human and mouse tissues, we established sequencing-based, cell-type-specific reference DNA methylation atlases. We found that cell-type-specific DNA blocks were mostly hypomethylated and located within signature genes of cellular identity. Cell-free DNA fragments were captured from serum samples by hybridization to CpG-rich DNA panels and mapped to the DNA methylation atlases. In a mouse model, thoracic radiation-induced tissue damage was reflected by dose-dependent increases in lung endothelial and cardiomyocyte methylated DNA in serum. The analysis of serum samples from patients with breast cancer undergoing radiation treatment revealed distinct dose-dependent and tissue-specific epithelial and endothelial responses to radiation across multiple organs. Strikingly, patients treated for right-sided breast cancers also showed increased hepatocyte and liver endothelial DNA in the circulation, indicating the impact on liver tissues. Thus, changes in cell-free methylated DNA can uncover cell-type-specific effects of radiation and provide a readout of the biologically effective radiation dose received by healthy tissues.

Type 1 Natural Killer T-cells (NKT1 cells) play a critical role in mediating hepatic ischemia-reperfusion injury (IRI). Although hepatic steatosis is a major risk factor for preservation type injury, how NKT cells impact this is understudied. Given NKT1 cell activation by phospholipid ligands recognized presented by CD1d, we hypothesized that NKT1 cells are key modulators of hepatic IRI because of the increased frequency of activating ligands in the setting of hepatic steatosis. We first demonstrate that IRI is exacerbated by a high-fat diet (HFD) in experimental murine models of warm partial ischemia. This is evident in the evaluation of ALT levels and Phasor-Fluorescence Lifetime (Phasor-FLIM) Imaging for glycolytic stress. Polychromatic flow cytometry identified pronounced increases in CD45+CD3+NK1.1+NKT1 cells in HFD fed mice when compared to mice fed a normal diet (ND). This observation is further extended to IRI, measuring ex vivo cytokine expression in the HFD and ND. Much higher interferon-gamma (IFN-γ) expression is noted in the HFD mice after IRI. We further tested our hypothesis by performing a lipidomic analysis of hepatic tissue and compared this to Phasor-FLIM imaging using "long lifetime species", a byproduct of lipid oxidation. There are higher levels of triacylglycerols and phospholipids in HFD mice. Since N-acetylcysteine (NAC) is able to limit hepatic steatosis, we tested how oral NAC supplementation in HFD mice impacted IRI. Interestingly, oral NAC supplementation in HFD mice results in improved hepatic enhancement using contrast-enhanced magnetic resonance imaging (MRI) compared to HFD control mice and normalization of glycolysis demonstrated by Phasor-FLIM imaging. This correlated with improved biochemical serum levels and a decrease in IFN-γ expression at a tissue level and from CD45+CD3+CD1d+ cells. Lipidomic evaluation of tissue in the HFD+NAC mice demonstrated a drastic decrease in triacylglycerol, suggesting downregulation of the PPAR-γ pathway.

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, 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.

The increasing number of compounds under development and chemicals in commerce that require safety assessments pose a serious challenge for regulatory agencies worldwide. In vitro screening using toxicogenomic biomarkers has been proposed as a first-tier screen in chemical assessment and has been endorsed internationally. We previously developed, evaluated, and validated an in vitro transcriptomic biomarker responsive to DNA damage-inducing (DDI) agents, namely TGx-DDI, for genotoxicity testing in human cells and demonstrated the feasibility of using TGx-DDI in a medium-throughput, cell-based genotoxicity testing system by implementing this biomarker with the Nanostring nCounter system. In this current study, we took advantage of Nanostring nCounter Plexset technology to develop a highly auto­mated, multiplexed, and high-throughput genotoxicity testing assay, designated the TGx-DDI Plexset assay, which can increase the screening efficiency eight-fold compared to standard nCounter technology while decreasing the hands-on time. We demonstrate the high-throughput capability of this assay by eliminating concentration determination and RNA extraction steps without compromising the specificity and sensitivity of TGx-DDI. Thus, we propose that this simple, highly automated, multiplexed high-throughput pipeline can be widely used in chemical screening and assessment.