OBJECTIVES: Drug transporters affect antiretroviral therapy (ART) tissue disposition, but quantitative measures of drug transporter protein expression across preclinical species are not available. Our objective was to use proteomics to obtain absolute transporter concentrations and assess agreement with corresponding gene and immunometric protein data. DESIGN: In order to make interspecies comparisons, two humanized mouse [hu-HSC-Rag (n = 41); bone marrow-liver-thymus (n = 13)] and one primate [rhesus macaque (nonhuman primate, n = 12)] models were dosed to steady state with combination ART. Ileum and rectum were collected at necropsy and snap frozen for analysis. METHODS: Tissues were analyzed for gene (quantitative PCR) and protein [liquid chromatography-mass spectrometry (LC-MS) proteomics and western blot] expression and localization (immunohistochemistry) of ART efflux and uptake transporters. Drug concentrations were measured by LC-MS/MS. Multivariable regression was used to determine the ability of transporter data to predict tissue ART penetration. RESULTS: Analytical methods did not agree, with different trends observed for gene and protein expression. For example, quantitative PCR analysis showed a two-fold increase in permeability glycoprotein expression in nonhuman primates versus mice; however, proteomics showed a 200-fold difference in the opposite direction. Proteomics results were supported by immunohistochemistry staining showing extensive efflux transporter localization on the luminal surface of these tissues. ART tissue concentration was variable between species, and multivariable regression showed poor predictive power of transporter data. CONCLUSION: Lack of agreement between analytical techniques suggests that resources should be focused on generating downstream measures of protein expression to predict drug exposure. Taken together, these data inform the use of preclinical models for studying ART distribution and the design of targeted therapies for HIV eradication.
OBJECTIVES: Drug transporters affect antiretroviral therapy (ART) tissue disposition, but quantitative measures of drug transporter protein expression across preclinical species are not available. Our objective was to use proteomics to obtain absolute transporter concentrations and assess agreement with corresponding gene and immunometric protein data. DESIGN: In order to make interspecies comparisons, two humanized mouse [hu-HSC-Rag (n = 41); bone marrow-liver-thymus (n = 13)] and one primate [rhesus macaque (nonhuman primate, n = 12)] models were dosed to steady state with combination ART. Ileum and rectum were collected at necropsy and snap frozen for analysis. METHODS: Tissues were analyzed for gene (quantitative PCR) and protein [liquid chromatography-mass spectrometry (LC-MS) proteomics and western blot] expression and localization (immunohistochemistry) of ART efflux and uptake transporters. Drug concentrations were measured by LC-MS/MS. Multivariable regression was used to determine the ability of transporter data to predict tissue ART penetration. RESULTS: Analytical methods did not agree, with different trends observed for gene and protein expression. For example, quantitative PCR analysis showed a two-fold increase in permeability glycoprotein expression in nonhuman primates versus mice; however, proteomics showed a 200-fold difference in the opposite direction. Proteomics results were supported by immunohistochemistry staining showing extensive efflux transporter localization on the luminal surface of these tissues. ART tissue concentration was variable between species, and multivariable regression showed poor predictive power of transporter data. CONCLUSION: Lack of agreement between analytical techniques suggests that resources should be focused on generating downstream measures of protein expression to predict drug exposure. Taken together, these data inform the use of preclinical models for studying ART distribution and the design of targeted therapies for HIV eradication.
Authors: J William Higgins; Jing Q Bao; Alice B Ke; Jason R Manro; John K Fallon; Philip C Smith; Maciej J Zamek-Gliszczynski Journal: Drug Metab Dispos Date: 2013-11-05 Impact factor: 3.922
Authors: Erin Burgunder; John K Fallon; Nicole White; Amanda P Schauer; Craig Sykes; Leila Remling-Mulder; Martina Kovarova; Lourdes Adamson; Paul Luciw; J Victor Garcia; Ramesh Akkina; Philip C Smith; Angela D M Kashuba Journal: J Pharmacol Exp Ther Date: 2019-06-24 Impact factor: 4.030
Authors: Aaron S Devanathan; John K Fallon; Nicole R White; Amanda P Schauer; Brian Van Horne; Kimberly Blake; Craig Sykes; Martina Kovarova; Lourdes Adamson; Leila Remling-Mulder; Paul Luciw; J Victor Garcia; Ramesh Akkina; Jason R Pirone; Philip C Smith; Angela D M Kashuba Journal: Antimicrob Agents Chemother Date: 2020-09-21 Impact factor: 5.191
Authors: Nithya Srinivas; Mackenzie Cottrell; Kaitlyn Maffuid; Heather A Prince; Julie A E Nelson; Nicole White; Craig Sykes; Evan S Dellon; Ryan D Madanick; Nicholas J Shaheen; Daniel Gonzalez; Angela D M Kashuba Journal: Antimicrob Agents Chemother Date: 2020-01-27 Impact factor: 5.191
Authors: Aaron S Devanathan; Jason R Pirone; Ramesh Akkina; Leila Remling-Mulder; Paul Luciw; Lourdes Adamson; J Victor Garcia; Martina Kovarova; Nicole R White; Amanda P Schauer; Kimberly Blake; Craig Sykes; Erin M Burgunder; Nithya Srinivas; Elias P Rosen; Angela D M Kashuba Journal: Antimicrob Agents Chemother Date: 2019-12-20 Impact factor: 5.191
Authors: Cen Guo; Carl LaCerte; Jeffrey E Edwards; Kenneth R Brouwer; Kim L R Brouwer Journal: J Pharmacol Exp Ther Date: 2018-02-27 Impact factor: 4.030
Authors: Nithya Srinivas; Elias P Rosen; William M Gilliland; Martina Kovarova; Leila Remling-Mulder; Gabriela De La Cruz; Nicole White; Lourdes Adamson; Amanda P Schauer; Craig Sykes; Paul Luciw; J Victor Garcia; Ramesh Akkina; Angela D M Kashuba Journal: Xenobiotica Date: 2018-12-17 Impact factor: 1.908
Authors: Elias P Rosen; Claire Deleage; Nicole White; Craig Sykes; Catherine Brands; Lourdes Adamson; Paul Luciw; Jacob D Estes; Angela D M Kashuba Journal: J Int AIDS Soc Date: 2022-04 Impact factor: 6.707