Grantee Research Project Results
Final Report: Model of Toxicant Response in Engineered Liver
EPA Grant Number: R834998Title: Model of Toxicant Response in Engineered Liver
Investigators: Rajagopalan, Padmavathy , Murali, T. M. , Ehrich, Marion
Institution: Virginia Tech
EPA Project Officer: Chung, Serena
Project Period: June 1, 2011 through May 30, 2015
Project Amount: $750,000
RFA: Computational Toxicology: Biologically-Based Multi-Scale Modeling (2010) RFA Text | Recipients Lists
Research Category: Chemical Safety for Sustainability
Summary/Accomplishments (Outputs/Outcomes):
Objective 1.
We have designed 3D organotypic liver models using primary rat hepatocytes, liver sinusoidal endothelial cells and Kupffer cells. We reported the assembly of a novel three-dimensional (3D) organotypic liver model incorporating three different cell types (hepatocytes, liver sinusoidal endothelial cells, and Kupffer cells) and a polymeric interface that mimics the Space of Disse. The nanoscale interface is detachable, optically transparent, derived from self-assembled polyelectrolyte multilayers, and exhibits a Young’s modulus similar to in vivo values for liver tissue. Only the 3D liver models simultaneously maintain hepatic phenotype and elicit proliferation, while achieving cellular ratios found in vivo. The nanoscale detachable polymeric interfaces can be modulated to mimic basement membranes that exhibit a wide range of physical properties. This facile approach offers a versatile new avenue in the assembly of engineered tissues. These results demonstrate the ability of the tri-cellular 3D cultures to serve as an organotypic hepatic model that elicits proliferation and maintenance of phenotype and in vivo -like cellular ratios. We reported the design of multi-cellular three-dimensional (3D) organotypic liver models assembled using primary rat hepatocytes, liver sinusoidal endothelial cells (LSECs) and Kupffer cells (KCs). These models emulate critical features of hepatic sinusoidal architecture and composition. Acetaminophen (APAP) induced changes to cellular function and phenotype were investigated and compared to two-dimensional (2D) hepatocyte monocultures and co-cultures (manuscript in review). At 10 and 20 mM APAP, only 3D models exhibited cell death, primarily through necrosis. In contrast, hepatocyte monolayers exhibited significant apoptosis. Expression of CD32b, an LSEC-specific marker, was maintained only in the 3D models. In these models, LSECs and KCs exhibited up to 72% and 47% cell death at 40 mM APAP, respectively. No death occurred in the corresponding NPC monolayers. Upon APAP administration, KCs in the 3D models exhibited decreased interleukin-10 and increased tumor necrosis factor and interferon-gamma. These trends indicate phenotypic changes in KCs and subsequent alterations to hepatocyte functions. The 3D cultures demonstrate significant potential as models for hepatotoxicity studies.
Objective 2. The second objective of the grant was to "Compute biological process linkage networks that anchor phenotypes triggered by carbon tetrachloride and dichloroethylene to gene expression profiles." We developed several computational methods to perform these types of analyses. We developed a method to summarize differential gene expression measurements using a highly non-redundant set of links between processes that describe the molecular interactions that are perturbed under a specific biological context. Each link in the BPN represents the perturbed interactions that serve as the interfaces between the two processes connected by the link.
We have reported a novel representation of signaling reactions that we call a signaling hypergraph. We formulated a problem that asks what proteins and interactions must be involved in order to stimulate a specific response downstream of a signaling pathway. We demonstrated that the shortest hyperpaths computed in signaling hypergraphs are far more informative than shortest paths found in corresponding graph representations.
We reported XTALK, a path-based approach for identifying pairs of pathways that may crosstalk. XTALK computes the statistical significance of the average length of multiple short paths that connect receptors in one pathway to the transcription factors in another. By design, XTALK reports the precise interactions and mechanisms that support the identified crosstalk.
We reported PATHLINKER, a new computational method to reconstruct the interactions in a signaling pathway of interest. PATHLINKER efficiently computes multiple short paths from the receptors to transcriptional regulators in a pathway within a background protein interaction network. We use PATHLINKER to accurately reconstruct a comprehensive set of signaling pathways from the NetPath and KEGG databases.
Objective 3.
Experiments were conducted investigating the effects of the co-administration of acetaminophen (APAP), perfluorooctanoic acid and troglitazone (TGZ) on 3D organotypic liver cultures.. The drugs were administered for 24 hours and compared to the predicted additive toxicities of the single drugs. Changes to overall viability, LSEC counts and KC counts were analyzed for the 3D models containing hepatocytes and LSECs (3DHL) and hepatocytes, LSECs and KCs (3DHLK). Hepatocyte monolayer (HM) and collagen sandwich (CS) cultures were used as controls for the overall viability. The 3DHL and 3DHLK cultures exhibited the highest sensitivity to the coadministered toxicants. A manuscript on this work is under preparation.
Conclusions:
The liver is one of the major organs that is involved in biotransformation and detoxification. In order to understand how liver cells work in a coordinated manner to conduct such functions, in vitro models are needed. We have designed three-dimensional liver models that contain three liver cells types. We have demonstrated that the response of these liver models is similar to results obtained from rats.
Journal Articles on this Report : 10 Displayed | Download in RIS Format
| Other project views: | All 34 publications | 14 publications in selected types | All 13 journal articles |
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Larkin AL, Rodrigues RR, Murali TM, Rajagopalan P. Designing a multicellular organotypic 3D liver model with a detachable, nanoscale polymeric Space of Disse. Tissue Engineering Part C: Methods 2013;19(11):875-884. |
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Lasher CD, Rajagopalan P, Murali TM. Summarizing cellular responses as biological process networks. BMC Systems Biology 2013;7:68. |
R834998 (2012) R834998 (2013) R834998 (Final) |
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Rajagopalan P, Kasif S, Murali TM. Systems biology characterization of engineered tissues. Annual Review of Biomedical Engineering 2013;15:55-70. |
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Rita A, Poirel C, Tegge A, Sharp N, Simmons K, Powell A, Kale S, Murali T. Pathways on demand: automated reconstruction of human signaling networks. SYSTEMS BIOLOGY AND APPLICATIONS 2016;2(16002) |
R834998 (2013) R834998 (Final) |
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Tegge AN, Sharp N, Murali TM. XTALK: a path-based approach for identifying crosstalk between signaling pathways. Bioinformatics 2016;32(2):242-251. |
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Vu LT, Less RR, Rajagopalan P. The promise of organotypic hepatic and gastrointestinal models. Trends in Biotechnology 2014;32(8):406-413. |
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Vu L, Orbach S, Ray W, Cassin ME, Rajagopalan P, Helm R. The hepatocyte proteome in organotypic rat liver models and the influence of the local microenvironment. PROTEOME SCIENCE 2017;15(12) |
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Orbach SM, Cassin ME, Ehrich MF, Rajagopalan P. Investigating acetaminophen hepatotoxicity in multi-cellular organotypic liver models. Toxicology in Vitro 2017;42:10-20. |
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Orbach SM, Ehrich MF, Rajagopalan P. High-throughput toxicity testing of chemicals and mixtures in organotypic multi-cellular cultures of primary human hepatic cells. Toxicology in Vitro 2018;51:83-94. |
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Tegge AN, Rodrigues RR, Larkin AL, Vu L, Murali TM, Rajagopalan P. Transcriptomic analysis of hepatic cells in multicellular organotypic liver models. Scientific Reports 2018;8(1):11306. |
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Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.