Exposure to ionizing radiation disrupts metabolic pathways and causes oxidative stress, which can lead to organ damage. In this study, urinary metabolites from mice exposed to high-dose and low-dose whole-body irradiation (WBI HDR, WBI LDR) or partial-body irradiation (PBI BM2.5) were analyzed using targeted and untargeted metabolomics approaches. Significant metabolic changes particularly in oxidative stress pathways were observed on Day 2 post-radiation. By Day 30, the WBI HDR group showed persistent metabolic dysregulation, while the WBI LDR and PBI BM2.5 groups were similar to control mice. Machine learning models identified metabolites that were predictive of the type of radiation exposure with high accuracy, highlighting their potential use as biomarkers for radiation damage and oxidative stress.

Exposure to ionizing radiation, accidental or intentional, may lead to delayed effects of acute radiation exposure (DEARE) that manifest as injury to organ systems, including the kidney, heart, and brain. This study examines the role of activated protein C (APC), a known mitigator of radiation-induced early toxicity, in long-term plasma metabolite and lipid panels that may be associated with DEARE in APCHi mice. The APCHi mouse model used in the study was developed in a C57BL/6N background, expressing the D168F/N173K mouse analog of the hyper-activatable human D167F/D172K protein C variant. This modification enables increased circulating APC levels throughout the mouse’s lifetime. Male and female cohorts of C57BL/6N wild-type and APCHi transgenic mice were exposed to 9.5 Gy γ-rays with their hind legs shielded to allow long-term survival that is necessary to monitor DEARE, and plasma was collected at 6 months for LC-MS-based metabolomics and lipidomics. We observed significant dyslipidemia, indicative of inflammatory phenotype, upon radiation exposure. Additionally, observance of several other metabolic dysregulations was suggestive of gut damage, perturbations in TriCarboxylic Acid (TCA) and urea cycles, and arginine metabolism. We also observed gender- and genotype-modulated metabolic perturbations post radiation exposure. The APCHi mice showed near-normal abundance for several lipids. Moreover, restoration of plasma levels of some metabolites, including amino acids, citric acid, and hypoxanthine, in APCHi mice is indicative of APC-mediated protection from radiation injuries. With the help of these findings, the role of APC in plasma molecular events after acute γ-radiation exposure in a gender-specific manner can be established for the first time.

Accurate and reliable quantification of organic acids with carboxylic acid functional groups in complex biological samples remains a major analytical challenge in clinical chemistry. Issues such as spontaneous decarboxylation during ionization, poor chromatographic resolution, and retention on a reverse-phase column hinder sensitivity, specificity, and reproducibility in multiple-reaction monitoring (MRM)-based LC–MS assays. We report a targeted metabolomics method using phenylenediamine derivatization for quantifying carboxylic acid-containing metabolites (CCMs). This method achieves accurate and sensitive quantification in various biological matrices, with recovery rates from 90% to 105% and CVs ≤ 10%. It shows linearity from 0.1 ng/mL to 10 µg/mL with linear regression coefficients of 0.99 and LODs as low as 0.01 ng/mL. The library included a wide variety of structurally variant CCMs such as amino acids/conjugates, short- to medium-chain organic acids, di/tri-carboxylic acids/conjugates, fatty acids, and some ring-containing CCMs. Comparing CCM profiles of pancreatic cancer cells to normal pancreatic cells identified potential biomarkers and their correlation with key metabolic pathways. This method enables sensitive, specific, and high-throughput quantification of CCMs from small samples, supporting a wide range of applications in basic, clinical, and translational research.

Exposure to ionizing radiation, accidental or intentional, may lead to delayed effects of acute radiation exposure (DEARE) that manifest as injury to organ systems including kidney, heart, and brain. This study examines the role of activated protein C (APC), a known mitigator of radiation-induced early toxicity, in long-term plasma metabolite and lipid panels that may be associated with DEARE. Male and female cohorts of C57BL/6N wild-type and APCHi transgenic mice were exposed to 9.5 Gy γ-rays with their hind-legs shielded to allow long-term survival that is necessary to monitor DEARE, and plasma was collected at 6 months for LC-MS based metabolomics and lipidomics. We observed significant dyslipidemia, indicative of inflammatory phenotype, upon radiation exposure. Additionally, observance of several other metabolic dysregulations was suggestive of gut damage, perturbations in TCA and urea cycles, and arginine metabolism. We also observed gender and genotype modulated metabolic perturbations post radiation exposure. The APCHi mice showed near normal abundance for several lipids. Moreover, restoration of plasma levels of some metabolites including amino acids, citric acid, and hypoxanthine in APCHi mice are indicative of APC-mediated protection from radiation injuries. With the help of these findings the role of APC in plasma molecular events after acute -radiation exposure in a gender-specific manner can be established for the first time.

Metabolomics profiling for accurate and reliable quantification of organic acids that carry a carboxylic acid functional group in complex biological samples, remains a major analytical challenge in clinical chemistry research. Several procedural barriers associated with quantification of clinically important carboxylic containing metabolites (CCMs) including spontaneous decarboxylation during ionization, poor chromatographic resolution, and retention on a reverse-phase column, limit the sensitivity, specificity, and reproducibility of multiple-reaction monitoring (MRM) based LC-MS assay development. We report a targeted metabolomics-based analytical method for the quantification of CCMs using phenylenediamine derivatization. Accurate and sensitive quantification of CCMs is successfully demonstrated in an array of biological matrices. Recovery of metabolites from different matrices (plasma, serum, urine, saliva, tissues, and cell extracts), ranged from 90% to 105%, with all the CVs ≤ 10%. The method showed linearity over a broad dynamic range from 0.1 ng/mL to 10 µg/mL with linear regression coefficients of 0.99 for most of the metabolites tested herein, that covers broad-based applicability with the analysis of biological samples. In most cases the LODs were as low as 0.01 ng/mL. The phenylenediamine-based derivatization of carboxyl acid library consisting of more than 70 endogenous metabolites was constructed for metabolite identification, which spanned more than 40 biological pathways. The library included a wide-variety of structurally variant CCMs such as amino acids/conjugates, short to medium chain organic acids, di/tri-carboxylic acids/conjugates, fatty acids and some ring-containing CCMs. We compared the CCMs profiles of pancreatic cancer cells with normal pancreatic epithelial cells to test and validate the biological utility of this method. The comparative profiling between cancerous and normal cells resulted in the identification of potential biomarkers in pancreatic cancer, and their correlation with several key metabolic pathways such as central carbon energy metabolism, protein metabolism, including TCA cycle, glycolysis, Gln-Glu pathway, and biosynthesis of amino acids and unsaturated fatty acids was established. The method, described herein, for the first time enables the sensitive and highly specific quantification of CCMs on small sample size with high reproducibility in a high throughput manner. Given the biological and functional significance of this class of metabolites, this mass spectrometry based targeted quantitative assay, fills an important gap and is likely to support a wide range of applications for basic, clinical, and translational research.