Analysis of the metabolomic profile in serum of irradiated nonhuman primates treated with BIO 300-1, a radiation countermeasure
Mentor: Dr. Amrita Cheema, Professor of Oncology/ Associate Director: Center for Metabolomic Studies, Lombardi Comprehensive Cancer Center, Georgetown University
Date/Time: August 23rd, 2022 at 2:20pm.
Abstract: Multiple radiation countermeasures are being investigated to protect against the adverse effects of irradiation. BIO 301 is a promising candidate in the advanced development stage. The purpose of this study is to investigate the radiation protective effect of BIO 301 using a mouse model by leveraging comparative metabolomics analysis of three different routes of drug administration over time.
Specifically, for this study, 78 serum samples from 2 groups of NHPs (non-human primates) exposed to Cobalt-60 radiation of 5.8 Gy, were analyzed using high resolution mass spectrometry. Based on our previous studies, acute exposure to radiation is known to cause robust changes in the serum metabolomic profiles of NHP’s. One of the objectives of this study was therefore, to investigate the specific changes in the expression level of samples’ metabolites. Further, we were interested in investigating if administration of BIO 301, prior to irradiation would alleviate radiation induced metabolic dysregulation caused by irradiation. Therefore, the other objective of this study is to investigate the radio-protection effects of BIO 301.
Untargeted LCMS (Liquid Chromatographic-Mass Spectrometry) based metabolomics were performed to detect differential expression of the metabolites in longitudinal serum samples collected from NHPs. Subsequently, a mature pipeline (XCMS R script) was utilized to calibrate and normalize the raw data to the intensity of debrisoquine internal standard for positive mode and 4-nitro benzoic acid for negative mode, the quality control samples (QC) and protein quantification. I was able to develop a new workflow of statistical analysis based on R that enabled multivariable analysis to compare different groups. This helped delineate significant m/z_rt (retention time) values were using p-value and fold change as criteria for metabolic dysregulation. After significant m/z_rt values identified, a database search was performed to identify the specific metabolites corresponding to each m/z_rt value using Mummichog, Metlin, HMDB, LIPID MAPS, and MMCD. For next step, pathways discovery was performed, and significantly affected pathways (E.g., C21-steroid hormone biosynthesis and metabolism, Prostaglandin formation from arachidonate, Androgen and estrogen biosynthesis and metabolism) were discovered through enrichment analysis on the metabolites. The expression level of the metabolites involved in these biological pathways are found to be significantly affected if comparing pre-irradiation and after-irradiation, indicating that these pathways are dysregulated. Nevertheless, through analyzing the metabolites of BIO 301 treated samples, we detected slight correction on the expression level of metabolites in the corresponding pathways compared to vehicle samples. This indicates that we were able to see partial protective effects of BIO 301 via examining changes in biological pathways….
Taken together this internship enabled me to learn the entire metabolomics workflow encompassing sample preparation, LC-MS analysis, raw data deconvolution, data preprocessing (normalization and log transformation) and post-processing (multivariate analysis). We were able to successfully correlate the changes in abundance of metabolites to specific biological pathways, which is very meaningful in future clinical therapy or biomedical research. Also, our promising candidate BIO 301 shows expected radiation-protective effects on irradiation-exposed NHP samples, although further exploration for its clinical effect is still required.