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Label-Free but Still Constrained: Assessment of Global Proteomic Strategies for the Quantification of Hepatic Enzymes and Transporters

Jill Barber, Zubida M. Al-Majdoub, Narciso Couto, Areti-Maria Vasilogianni, Annika Tillmann, Sarah Alrubia, Amin Rostami-Hodjegan and Brahim Achour
Drug Metabolism and Disposition March 20, 2022, DMD-AR-2021-000780; DOI: https://doi.org/10.1124/dmd.121.000780
Jill Barber
1Pharmacy and Pharmaceutical Sciences, University of Manchester, United Kingdom
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Zubida M. Al-Majdoub
2Division of Pharmacy and Optometry, University of Manchester, United Kingdom
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Narciso Couto
3Department of Chemical and Biological Engineering, University of Sheffield, United Kingdom
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Areti-Maria Vasilogianni
4University of Manchester, United Kingdom
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Annika Tillmann
5Centre for Applied Pharmacokinetic Research, University of Manchester, United Kingdom
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Sarah Alrubia
5Centre for Applied Pharmacokinetic Research, University of Manchester, United Kingdom
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Amin Rostami-Hodjegan
6Systems Pharmacology, Manchester Pharmacy School, University of Manchester, United Kingdom
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Brahim Achour
5Centre for Applied Pharmacokinetic Research, University of Manchester, United Kingdom
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  • For correspondence: brahim.achour@manchester.ac.uk
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Abstract

Building and refining pharmacology models require 'system' data derived from tissues and in vitro systems analysed by quantitative proteomics. Label-free global proteomics offers a wide scope of analysis, allowing simultaneous quantification of thousands of proteins per sample. The data generated from such analysis offer comprehensive protein expression profiles that can address existing gaps in models. In this study, we assessed the performance of three widely used label-free proteomic methods, 'high N' ion intensity approach (HiN), intensity-based absolute quantification (iBAQ) and total protein approach (TPA), in relation to the quantification of enzymes and transporters in 27 human liver microsomal samples. Global correlations between the three methods were highly significant (R2 > 0.70, p < 0.001, n = 2232 proteins). Absolute abundances of 57 pharmacokinetic targets measured by standard-based label-free methods (HiN and iBAQ) showed good agreement, while the TPA overestimated abundances by 2-3 fold. Relative abundance distribution of enzymes was similar for the three methods, while differences were observed with TPA in the case of transporters. Variability (CV) was similar across the methods, with consistent between-sample relative quantification regardless of methodology. The back-calculated amount of protein in the samples based on each method was compared with the nominal protein amount analysed in the proteomic workflow, revealing overall agreement with data from the HiN method with bovine serum albumin as standard. The findings herein present a critique of label-free proteomic data relevant to pharmacokinetics and evaluate the possibility of retrospective analysis of historic datasets.

Significance Statement This study provides useful insights for using label-free methods to generate abundance data applicable for populating pharmacokinetic models. The data demonstrated overall correlation between intensity-based label-free proteomic methods (HiN, iBAQ and TPA), while iBAQ and TPA overestimated the total amount of protein in the sample. The extent of overestimation can provide a means of normalization to support absolute quantification. Importantly, between-sample relative quantification was consistent (similar variability) across methods.

  • physiologically-based pharmacokinetic modeling/PBPK
  • proteomics
  • systems pharmacology
  • Copyright © 2020 American Society for Pharmacology and Experimental Therapeutics
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Drug Metabolism and Disposition: 51 (2)
Drug Metabolism and Disposition
Vol. 51, Issue 2
1 Feb 2023
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Critique of Label-Free Proteomics of Pharmacokinetic Targets

Jill Barber, Zubida M. Al-Majdoub, Narciso Couto, Areti-Maria Vasilogianni, Annika Tillmann, Sarah Alrubia, Amin Rostami-Hodjegan and Brahim Achour
Drug Metabolism and Disposition March 20, 2022, DMD-AR-2021-000780; DOI: https://doi.org/10.1124/dmd.121.000780

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Critique of Label-Free Proteomics of Pharmacokinetic Targets

Jill Barber, Zubida M. Al-Majdoub, Narciso Couto, Areti-Maria Vasilogianni, Annika Tillmann, Sarah Alrubia, Amin Rostami-Hodjegan and Brahim Achour
Drug Metabolism and Disposition March 20, 2022, DMD-AR-2021-000780; DOI: https://doi.org/10.1124/dmd.121.000780
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