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Developing a Mitochondrial Toxicity Pathway-based Framework for Chemical Safety Assessment: A Case Study of PGC-1α-mediated Network Perturbation with Doxorubicin Haitao Yuan1 † , Qiang Zhang2 † , 1Jiabin Guo1 † , Tingfen Zhang1, Mingyue Hou1, Jun Zhao1, Jin Li3, Andrew White3, Paul L. Carmichael3, Carl Westmorelandand3, and Shuangqing Peng1 1 Evaluation and Research Centre for Toxicology, Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, 100071, China 2 Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA 3 Unilever Safety and Environmental Assurance Center, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK ou 1 , Jun Zhao 1 , Jin Li 3 , Andrew White 3 , Paul L. Carmichael 3 , Carl Peng 1 Introduction As toxicity testing of chemicals is moving toward a multidisciplinary approach based on in vitro cell assays anchored on toxicity pathways, a recurring challenge is how to reliably determine point of departure (POD), given well- defined biomarkers that can indicate the health and functional state of cells. In this study, we use doxorubicin(DOX) as a prototype chemical to develop “fit- for-purpose” in vitro assays focusing on the PGC-1α pathway. Our in vitro data and computational modeling collectively supported the notion that saturation of the induction of the PGC-1α-mediated transcriptional network is responsible for the cellular transition from adaptive to adverse responses. This transition corresponds to a POD, suggesting sensitive biomarkers for monitoring mitochondrial toxicity can be found within the set of genes being controlled by PGC-1α for mitochondrial homeostasis. Our work shows the value of combining data collection on cellular adaptive responses and mechanistic pathway modeling. The integrated approach represents an emerging direction in which computational modeling of pathway perturbation is used to mechanistically interpret in vitro toxicity data and make quantitative predictions. Protein and mRNA expression: Western blot analyses and qRT-PCR. Mitochondrial superoxide and MMP: MitoSox and TMRM fluorescent dye. ATP assays: based on luciferase enzyme luminescence. The deterministic model was constructed in Berkeley Madonna TM and solved numerically with the Rosenbrock stiff solver. The model contains components and processes that conform to the general network scheme illustrated in Fig.1. Fig 1. Model framework. PGC-1α- mediated transcriptional network underlying redox and ATP homeostasis. Green lines denote adaptive feedback loops responsible for ATP homeostasis; red lines denote adaptive feedback loops responsible for redox homeostasis. Results Methods A human cell line of cardiac origin, AC16 cell, was used in this study. DOX was dissolved in deionized water (2mM stock solutions) and further dilutions were made with culture medium. Cytotoxicity assay: MTT assay and LDH release assay. A B C Fig 2. DOX-induced cytotoxicity and mitochondrial toxicity in AC16 cells. (A) Cell viability and rate of LDH release, (B) MitoROS and (C) Mitochondrial membrane potential and (D) Cellular ATP content were measured following treatment of AC16 cells with various concentrations of DOX for 12h. D A B C D Fig 3. Effects of DOX on mitochondrial biogenesis in AC16 cells. Concentration-response for (A) the ratios of mitochondrial-specific protein COX-1 to nDNA-specific protein SDH-A (square) or to β-actin (circle), (B) MnSOD and UCP-2 protein, (C) PGC-1ɑ and NRF-1 protein, and (D) mitochondrial DNA copy number were determined following treatment of AC16 cells with various concentrations of DOX for 12 h. A B C Fig 4. Simulation results of computational modeling (A) Simulation results of concentration-response of ROS, ATP, PGC-1ɑ, its target proteins, and mitochondrial mass at 12h. (B) Expression levels of PGC-1ɑ protein in AC16 cells transfected with PGC-1ɑ siRNA (0-80pM) for 24 h. (C) Simulated concentration-response of ROS, ATP, PGC- 1ɑ, its target proteins, and mitochondrial mass with 50% PGC-1ɑ knockdown in response to DOX perturbation. A B C Fig 5. PGC-1ɑ knockdown aggravated DOX-induced cytotoxicity. (A) Cell viability and (B) MMP were reduced significantly in PGC-1ɑ knockdown cells. (C) MitoROS was increased significantly in PGC-1ɑ knockdown cells. Conclusions This study demonstrates that combining pathway-focused in vitro assays and computational simulation is synergistic for understanding low-dose behaviors and identifying POD. The knowledge gained from the research as in the present study, along with evidence from other relevant toxicity pathways, will provide valuable information for the development of novel pathway mechanism-based in vitro approaches for risk assessment. † The three authors contributed to the work equally. Acknowledgements: This project was supported by Unilever International Collaborative Project (CH-2011-1318), and the National Key Project on Drug Development from the Ministry of Science and Technology of China (2009ZX09501-034). Corresponding Author: Shuangqing Peng, [email protected]
Transcript of Safety Homepage « Safety Science in the 21st Century ......3 Unilever Safety and Environmental...
Developing a Mitochondrial Toxicity Pathway-based Framework for Chemical Safety Assessment:
A Case Study of PGC-1α-mediated Network Perturbation with DoxorubicinHaitao Yuan1 †, Qiang Zhang2 †, 1Jiabin Guo1 †, Tingfen Zhang1, Mingyue Hou1, Jun Zhao1, Jin Li3, Andrew White3, Paul L. Carmichael3, Carl Westmorelandand3, and Shuangqing Peng1
1Evaluation and Research Centre for Toxicology, Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, 100071, China2Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
3 Unilever Safety and Environmental Assurance Center, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
ou1, Jun Zhao1, Jin Li3, Andrew White3, Paul L. Carmichael3, Carl Peng1Introduction
As toxicity testing of chemicals is moving toward a multidisciplinary approachbased on in vitro cell assays anchored on toxicity pathways, a recurringchallenge is how to reliably determine point of departure (POD), given well-defined biomarkers that can indicate the health and functional state of cells.
In this study, we use doxorubicin(DOX) as a prototype chemical to develop “fit-for-purpose” in vitro assays focusing on the PGC-1α pathway. Our in vitro dataand computational modeling collectively supported the notion that saturationof the induction of the PGC-1α-mediated transcriptional network is responsiblefor the cellular transition from adaptive to adverse responses. This transitioncorresponds to a POD, suggesting sensitive biomarkers for monitoringmitochondrial toxicity can be found within the set of genes being controlled byPGC-1α for mitochondrial homeostasis.
Our work shows the value of combining data collection on cellular adaptiveresponses and mechanistic pathway modeling.
The integrated approach represents an emerging direction in whichcomputational modeling of pathway perturbation is used to mechanisticallyinterpret in vitro toxicity data and make quantitative predictions.
Protein and mRNA expression: Western blot analyses and qRT-PCR.
Mitochondrial superoxide and MMP: MitoSox and TMRM fluorescent dye.
ATP assays: based on luciferase enzyme luminescence.
The deterministic model was constructed in Berkeley MadonnaTM and solvednumerically with the Rosenbrock stiff solver. The model contains componentsand processes that conform to the general network scheme illustrated in Fig.1.
Fig 1. Model framework. PGC-1α-mediated transcriptional networkunderlying redox and ATP homeostasis.Green lines denote adaptive feedbackloops responsible for ATP homeostasis; redlines denote adaptive feedback loopsresponsible for redox homeostasis.
Results
Methods A human cell line of cardiac origin, AC16 cell, was used in this study.
DOX was dissolved in deionized water (2mM stock solutions) and furtherdilutions were made with culture medium.
Cytotoxicity assay: MTT assay and LDH release assay.
A B C
Fig 2. DOX-induced cytotoxicity and mitochondrial toxicity in AC16 cells.
(A) Cell viability and rate of LDH release, (B) MitoROS and (C) Mitochondrial membrane potentialand (D) Cellular ATP content were measured following treatment of AC16 cells with variousconcentrations of DOX for 12h.
D
A B C D
Fig 3. Effects of DOX on mitochondrial biogenesis in AC16 cells.
Concentration-response for (A) the ratios of mitochondrial-specific protein COX-1 to nDNA-specificprotein SDH-A (square) or to β-actin (circle), (B) MnSOD and UCP-2 protein, (C) PGC-1ɑ and NRF-1protein, and (D) mitochondrial DNA copy number were determined following treatment of AC16cells with various concentrations of DOX for 12 h.
A B CFig 4. Simulation results of computational modeling
(A) Simulation results of concentration-response of ROS, ATP, PGC-1ɑ, its target proteins, andmitochondrial mass at 12h. (B) Expression levels of PGC-1ɑ protein in AC16 cells transfectedwith PGC-1ɑ siRNA (0-80pM) for 24 h. (C) Simulated concentration-response of ROS, ATP, PGC-1ɑ, its target proteins, and mitochondrial mass with 50% PGC-1ɑ knockdown in response toDOX perturbation.
A B CFig 5. PGC-1ɑ knockdown aggravated DOX-induced cytotoxicity.
(A) Cell viability and (B) MMP were reduced significantly in PGC-1ɑ knockdown cells. (C)MitoROS was increased significantly in PGC-1ɑ knockdown cells.
Conclusions This study demonstrates that combining pathway-focused in vitro assays
and computational simulation is synergistic for understanding low-dosebehaviors and identifying POD.
The knowledge gained from the research as in the present study, alongwith evidence from other relevant toxicity pathways, will provide valuableinformation for the development of novel pathway mechanism-based invitro approaches for risk assessment.
† The three authors contributed to the work equally. Acknowledgements: This project was supported by Unilever International Collaborative Project (CH-2011-1318), and the National Key Project on Drug Development from the Ministry of Science and Technology of China (2009ZX09501-034). Corresponding Author: Shuangqing Peng, [email protected]
