title: Highly multiplexed and reproducible ion-current-based strategy for large-scale quantitative proteomics and the application to protein expression dynamics induced by methylprednisolone in 60 rats.
abstract: A proteome-level time-series study of drug effects (i.e., pharmacodynamics) is critical for understanding mechanisms of action and systems pharmacology, but is challenging, because of the requirement of a proteomics method for reliable quantification of many biological samples. Here, we describe a highly reproducible strategy, enabling a global, large-scale investigation of the expression dynamics of corticosteroid-regulated proteins in livers from adrenalectomized rats over 11 time points after drug dosing (0.5-66 h, N = 5/point). The analytical advances include (i) exhaustive tissue extraction with a Polytron/sonication procedure in a detergent cocktail buffer, and a cleanup/digestion procedure providing very consistent protein yields (relative standard deviation (RSD%) of 2.7%-6.4%) and peptide recoveries (4.1-9.0%) across the 60 animals; (ii) an ultrahigh-pressure nano-LC setup with substantially improved temperature stabilization, pump-noise suppression, and programmed interface cleaning, enabling excellent reproducibility for continuous analyses of numerous samples; (iii) separation on a 100-cm-long column (2-μm particles) with high reproducibility for days to enable both in-depth profiling and accurate peptide ion-current match; and (iv) well-controlled ion-current-based quantification. To obtain high-quality quantitative data necessary to describe the 11 time-points protein expression temporal profiles, strict criteria were used to define "quantifiable proteins". A total of 323 drug-responsive proteins were revealed with confidence, and the time profiles of these proteins provided new insights into the diverse temporal changes of biological cascades associated with hepatic metabolism, response to hormone stimuli, gluconeogenesis, inflammatory responses, and protein translation processes. Most profile changes persisted well after the drug was eliminated. The developed strategy can also be broadly applied in preclinical and clinical research, where the analysis of numerous biological replicates is crucial.
authors: Department of Pharmaceutical Sciences, University at Buffalo, State University of New York , Buffalo, New York 14214, United States.
authors: Eslam
authors: E
authors: Nouri-Nigjeh
authors: Siddharth
authors: S
authors: Sukumaran
authors: Chengjian
authors: C
authors: Tu
authors: Jun
authors: J
authors: Li
authors: Xiaomeng
authors: X
authors: Shen
authors: Xiaotao
authors: X
authors: Duan
authors: Debra C
authors: DC
authors: DuBois
authors: Richard R
authors: RR
authors: Almon
authors: William J
authors: WJ
authors: Jusko
authors: Jun
authors: J
authors: Qu
mesh_terms: D000818:Animals; D056148:Chromatography, Reverse-Phase / Q000379:methods; D005786:Gene Expression Regulation / Q000187:drug effects*; D063990:Gene Ontology; D005938:Glucocorticoids / Q000008:administration & dosage / Q000494:pharmacology*; D005943:Gluconeogenesis / Q000187:drug effects; D008099:Liver / Q000187:drug effects / Q000378:metabolism; D013058:Mass Spectrometry / Q000379:methods; D008775:Methylprednisolone / Q000008:administration & dosage / Q000494:pharmacology*; D011506:Proteins / Q000032:analysis / Q000235:genetics / Q000378:metabolism*; D040901:Proteomics / Q000379:methods*; D051381:Rats
chemical_list: D005938:Glucocorticoids; D011506:Proteins; D008775:Methylprednisolone