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Blast-induced trauma is emerging as a serious threat due to its wide pathophysiology where not only the brain but also a spectrum of organs is being affected. In the present study, we aim to identify the plasma-based metabolic dysregulations along with the associated temporal changes at 5-6 h, day 1 and day 7 post-injury in a preclinical animal model for blast exposure, through liquid chromatography-mass spectrometry (LC-MS). Using significantly advanced metabolomic and statistical bioinformatic platforms, we were able to elucidate better and unravel the complex networks of blast-induced neurotrauma (BINT) and its interlinked systemic effects. Significant changes were evident at 5-6 h with maximal changes at day 1. Temporal analysis also depicted progressive changes which continued till day 7. Significant associations of metabolic markers belonging to the class of amino acids, energy-related molecules, lipids, vitamin, hormone, phenolic acid, keto and histidine derivatives, nucleic acid molecules, uremic toxins, and uronic acids were observed. Also, the present study is the first of its kind where comprehensive, detailed pathway dysregulations of amino acid metabolism and biosynthesis, perturbed nucleotides, lipid peroxidation, and nucleic acid damage followed by correlation networking and multiomics networking were explored on preclinical animal models exposed to mild blast trauma. In addition, markers for systemic changes (renal dysfunction) were also observed. Global pathway predictions of unannotated peaks also presented important insights into BINT pathophysiology. Conclusively, the present study depicts important findings that might help underpin the biological mechanisms of blast-induced brain or systemic trauma.

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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.

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INTRODUCTION AND OBJECTIVE: Taking into consideration the challenges of lipid analytics, present study aims to design the best high-throughput workflow for detection and annotation of lipids. MATERIAL AND METHODS: Serum lipid profiling was performed on CSH-C18 and EVO-C18 columns using UHPLC Q-TOF-MS and generated lipid features were annotated based on m/z and fragment ion using different software. RESULT AND DISCUSSION: Better detection of features was observed in CSH-C18 than EVO-C18 with enhanced resolution except for Glycerolipids (triacylglycerols) and Sphingolipids (sphingomyelin). CONCLUSION: The study revealed an optimized untargeted Lipidomics-workflow with comprehensive lipid profiling (CSH-C18 column) and confirmatory annotation (LipidBlast).

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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.

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