Comparison of quantitation methods in proteomics to define relevant toxicological information on AhR activation of HepG2 cells by BaP. (30th January 2021)

• Record Type: Journal Article
• Authors: Wang, Zhipeng; Karkossa, Isabel; Großkopf, Henning; Rolle-Kampczyk, Ulrike; Hackermüller, Jörg; von Bergen, Martin; Schubert, Kristin
• Is Part Of: Toxicology. Volume 448(2021)
• Publication Date: 2021-01-30
• Subjects: Toxicoproteomics -- Hepatocytes -- BaP -- AhR -- Mode of action; Toxicology -- Periodicals; Chemicals -- Physiological effect -- Periodicals; 615.9005
• DOI: 10.1016/j.tox.2020.152652
• Languages: English
• ISSNs: 0300-483X

Abstract

Highlights: Proteomics reveal insights into the modes of action of xenobiotics. Both TMT- and LFQ-based proteomics approaches are suitable to unravel toxicological questions. TMT allows a more robust identification of affected pathways. Abstract: The application of quantitative proteomics provides a new and promising tool for standardized toxicological research. However, choosing a suitable quantitative method still puzzles many researchers because the optimal method needs to be determined. In this study, we investigated the advantages and limitations of two of the most commonly used global quantitative proteomics methods, namely label-free quantitation (LFQ) and tandem mass tags (TMT). As a case study, we exposed hepatocytes (HepG2) to the environmental contaminant benzo[ a ]pyrene (BaP) using a concentration of 2 μM. Our results revealed that both methods yield a similar proteome coverage, in which for LFQ a wider range of fold changes was observed but with less significant p-values compared to TMT. We detected 37 and 47 significantly enriched pathways by LFQ and TMT, respectively, with 17 overlapping pathways. To define the minimally required effort in proteomics as a benchmark, we artificially reduced the LFQ, and TMT data sets stepwise and compared the pathway enrichment. Thereby, we found that fewer proteins are necessary for detecting significant enrichment of pathways in TMT compared to LFQ, which might be explained by the higher reproducibility of the TMT data that was observed. In summary, we showed that the TMT approach is the preferable one when investigating toxicological questions because it offers a high reproducibility and sufficient proteome coverage in a comparably short time.