Locate/csbjReviewProteomics for systems toxicologyBjoern Titz ,1, Ashraf Elamin 1, Florian Martin, Thomas Schneider, Sophie Dijon, Nikolai V. Ivanov, Julia Hoeng, Manuel C. PeitschPhilip Morris International R D, Philip Morris Solutions S.A., Quai Jeanrenaud 5, 2000 Neuch el, Switzerlanda r t i c l ei n f oa b s t r a c tCurrent toxicology studies frequently lack measurements at molecular resolution to enable a much more mechanismbased and predictive toxicological assessment. Recently, a systems toxicology assessment framework has been proposed, which combines traditional toxicological assessment Linuron Autophagy techniques with system-wide measurement strategies and computational analysis approaches in the field of systems biology. Proteomic measurements are an integral element of this integrative strategy due to the fact protein alterations closely mirror biological effects, which include biological stress responses or global tissue alterations. Here, we offer an overview on the technical foundations and highlight pick applications of proteomics for systems toxicology studies. With a focus on mass spectrometry-based proteomics, we summarize the experimental techniques for quantitative proteomics and describe the computational approaches made use of to Picloram custom synthesis derive biological/mechanistic insights from these datasets. To illustrate how proteomics has been successfully employed to address mechanistic queries in toxicology, we summarized quite a few case studies. Overall, we deliver the technical and conceptual foundation for the integration of proteomic measurements inside a additional extensive systems toxicology assessment framework. We conclude that, owing for the important significance of protein-level measurements and recent technological advances, proteomics is going to be an integral part of integrative systems toxicology approaches within the future. 2014 Titz et al. Published by Elsevier B.V. on behalf in the Analysis Network of Computational and Structural Biotechnology. This can be an open access report below the CC BY license (http://creativecommons.org/licenses/by/4.0/).Available on the internet 27 August 2014 Key phrases: Systems toxicology Quantitative proteomics Computational analysisContents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1. Experimental and computational approaches for the quantitative evaluation of proteomic alterations . . . . . . . . . . . . . . . . . . 1.1.1. Experimental approaches for quantitative proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.two. Computational approaches for quantitative proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.two. How to derive biological insights from proteomic information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.two.1. Deriving insights protein-by-protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.two.2. Deriving insights by means of functional modules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.two.three. Deriving insights via network analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.two.4. Deriving insights through information integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3. Applying proteomics for systems toxicology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
