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Although classical molecular biology assays can provide a measure of cellular response to chemical challenges, they rely on a single biological phenomenon to infer a broader measure of cellular metabolic response. These methods do not always afford the necessary sensitivity to answer questions of subcytotoxic effects, nor do they work for all cell types. Likewise, boutique assays such as cardiomyocyte beat rate may indirectly measure cellular metabolic response, but they too, are limited to measuring a specific biological phenomenon and are often limited to a single cell type. For these reasons, toxicological researchers need new approaches to determine metabolic changes across various doses in differing cell types, especially within the low-dose regime. The data collected herein demonstrate that LC-MS/MS-based untargeted metabolomics with a feature-agnostic view of the data, combined with a suite of statistical methods including an adapted environmental threshold analysis, provides a versatile, robust, and holistic approach to directly monitoring the overall cellular metabolomic response to pesticides. When employing this method in investigating two different cell types, human cardiomyocytes and neurons, this approach revealed separate subcytotoxic metabolomic responses at doses of 0.1 and 1 µM of chlorpyrifos and carbaryl. These findings suggest that this agnostic approach to untargeted metabolomics can provide a new tool for determining effective dose by metabolomics of chemical challenges, such as pesticides, in a direct measurement of metabolomic response that is not cell type-specific or observable using traditional assays. [ABSTRACT FROM AUTHOR]

Despite the recent epidemic of fentanyl abuse, there are few validated assays capable of rapidly detecting these compounds. In order to improve the ability to detect carfentanil at physiologically relevant concentrations, we developed a systems biology approach to discover host-based markers which are specifically amplified upon exposure in a rabbit model. For this work, two "omics" pipelines utilizing mass spectrometry were developed and leveraged. First, a proteomics pipeline was developed to interrogate the blood plasma for protein-based biomarkers. Due to the incredible dynamic range of the plasma protein content, a multi-dimensional fractionation technique was used to partition and more accurately investigate the circulating plasma proteome. Isobaric tandem mass tags were integrated into the workflow to make quantitative assessments across all animals for an extended time course post-exposure. In addition to the proteomics efforts, blood plasma was also processed through an untargeted metabolomics pipeline. This approach allows for the identification of >800 small molecule features. By processing and analyzing data sets in parallel, we were able to identify a unique fingerprint of protein and metabolite perturbations that manifest following exposure to carfentanil. [ABSTRACT FROM AUTHOR]