Prediction of Molecular Initiating Events for Adverse Outcome Pathways Using High-Throughput Identification of Chemical Targets

Abstract

The impact of exposure to multiple chemicals raises concerns for human and environmental health. The adverse outcome pathway method offers a framework to support mechanism-based assessment in environmental health starting by describing which mechanisms are triggered upon interaction with different stressors. The identification of the molecular initiating event and the molecular interaction between a chemical and a protein target is still a challenge for the development of adverse outcome pathways. The cellular response to chemical exposure studied with omics could not directly identify the protein targets. However, recent mass spectrometry-based methods are offering a proteome-wide identification of protein targets interacting with s but unrevealing a molecular initiating event from a set of targets is still dependent on available knowledge. Here, we directly coupled the target identification findings from the proteome integral solubility alteration assay with an analytical hierarchy process for the prediction of a prioritized molecular initiating event. We demonstrate the applicability of this combination of methodologies with a test compound (TCDD), and it could be further studied and integrated into AOPs. From the eight protein targets identified by the proteome integral solubility alteration assay after analyzing 2824 human hepatic proteins, the analytical hierarchy process can select the most suitable protein for an AOP. Our combined method solves the missing links between high-throughput target identification and prediction of the molecular initiating event. We anticipate its utility to decipher new molecular initiating events and support more sustainable methodologies to gain time and resources in chemical assessment.

Predictive toxicology of chemical mixtures using proteome-wide thermal profiling and protein target properties

“…In previous studies, we successfully demonstrated the effectiveness of the PISA assay in identifying protein interactions from individual chemicals from cell lines 26 and both single chemical and chemical mixture in zebrafish embryo model organism 15 . In this study, we opted for the 2D PISA approach, as opposed to the one-dimensional PISA utilized previously, to enhance the robustness of target identification.…”

“…This was done by laying out the local priorities of the alternatives concerning each criterion in a matrix (by pairwise comparison judgments using a scale from 1 to 9). Equations for the calculations are described in detail in our previous study 26 . The alternative with the highest global priority was ranked first, meaning that proteins with lower number in the rank could produce a higher disturbance of cellular function when they bind to the mixture.…”

“…While expertise knowledge is valuable, this approach minimizes reliance on preexisting mechanistic understanding of individual chemicals within the mixture. Multi-criteria decision-making techniques have previously been used for various applications, such as prioritizing among different dust sources based on toxicity 22 , ranking chemicals for toxicological impact assessments 23,24 , assessing the risk from multi-ingredient dietary supplements 25 , and integrating PISA data of individual chemicals into the AOP framework 26 . However, to the extent of our knowledge, this approach has not been previously applied to assessing unknown chemical mixtures.…”

The 2023 Report on the Proteome from the HUPO Human Proteome Project

“…38 Targeted proteomics, in which 3001 dynamic MRM transitions were monitored, revealed the precise molecular effects of Cd, Ag, and Zn metal exposures on the cecal proteome of Gammarus fossarum. 39 A new methodology has been proposed to identify the initiating molecular events when model cell lines are exposed to toxic substances, 40 starting with the demonstration of altered solubility of the integral proteome of HepG2 cells exposed to tetrachlorinated dioxins. Proteomics has also identified a circadian clock in cyanobacteria, a key biological mechanism in new prokaryotic models.…”