Research in ISBET

Research in ISBET

ISBET researchers aim to define a synthesis of tissue engineering and systems biology. We are using large-scale transcriptomic, proteomic, metabolomic, and imaging data to build phenomenological, system-level models of engineered tissues. Our focus is in the area of liver tissue engineering and interfacial tissue engineering. We are developing foundational phenomenological models of three-dimensional engineered liver mimics, using these models to probe how different cell types communicate with each other; using liver mimics to study the effect of toxins, nanoparticles, and pathogens on the human body and as models of metastasis; and transfering the resulting improved understanding to animal models. We are basing these phenomenological models on the analysis of transcriptional, proteomic, metabolic, and imaging data situated in the context of molecular interaction networks. These models reconstruct molecular machines that act in concert within the cell, reverse engineer the interactions among such modules, and represent the cell’s response to internal and external signals. We describe some of our specific research projects below. We gratefully acknowledge our sources of funding (NSF, NIH, EPA) for supporting our research.

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Areas of Research in ISBET

1 3D Liver Mimics

The liver is one of the important organs in our bodies, playing a vital role in glucose homeostasis, the synthesis of bile acids for the metabolism of cholesterol, and the secretion of proteins to aid clotting. The liver is also primarily responsible environmental toxins, alcohol, cigarette smoke, and for the detoxification of foreign substances (xenobiotics), including drugs. The deterioration in any of its functions can lead to serious health conditions. Hepatocytes are the principal cells in the liver, comprising over 80% of its mass and performing several characteristic functions of this organ. The remaining 30% of the cells are comprised of LSECs, Kupffer cells, and hepatic stellate cells.

Since the liver performs a wide range of complex physiological functions, the definition of a liver mimic has been widely debated. Liver sinusoids in vivo contain layers of hepatocytes and LSECs separated by the Space of Disse, a region comprised primarily of collagen fibers. Oxygen-rich blood from the hepatic artery and the nutrient-rich blood from the portal vein pass through the sinusoids, making them critical to liver function. Furthermore, heterotypic cell-cell interactions between hepatocytes, LSECs and other hepatic cell types occur at the sinusoids. Hence, this region could serve as a reliable hepatic model.

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Schematic of a 3D liver mimic. Hepatocytes (squares) are separated from LSECs (ovals) by a polyelectrolyte multi-layer scaffold.

Rajagopalan has designed an in vitro hepatic model based on the principle that a biocompatible polyelectrolyte multilayer might serve to mimic the Space of Disse. These model hepatic constructs are comprised of primary rat hepatocytes, an intermediate chitosan-hyaluronic acid polyelectrolyte multilayer (PEM) scaffold, and either primary human Liver Sinusoidal Endothelial Cells (LSECs) or primary rat LSECs. These 3D liver models maintain the phenotype of both cell types simultaneously for up to 4 weeks. The activities of important drug metabolizing Cytochrome P450 enzymes CYP 1A1/2 and CYP3A are three–six fold higher in 3D liver mimics than in other liver models. Bile acids are the primary route for cholesterol as well as for the removal of foreign chemicals from the liver. 3D liver mimics exhibit significantly better bile acid metabolic activity than other in vitro cultures.

2 Models of metastasis

Soker has recently developed a 3D liver organoid comprised of human umbilical vein endothelial cells (hUVECs) and human fetal liver cells (hFLCs). This novel organoid is obtained by perfusing hUVECs and hFLCs into intact acellular whole liver scaffolds. The decellularized liver scaffolds contain multiple cross-linked extracellular matrix proteins and maintain characteristic 3D topography. Remarkably, the channels of the vascular network appear patent. hUVECs line the blood vessles in the liver scaffold. hFLCs organize and differentiate into hepatocyte clusters. These organoids consistently express several key hepatic markers such as the drug metabolizing cytochrome P450 enzymes and show enhanced urea and albumin production.

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Liver organoid metastasis model. Liver ECM scaffold (top right) is seeded with hepatic and endothelial cells (EC) to yield organoid (lower left). The EC localize to vascular channels and hepatocytes to the parenchyma (brown and pink, respectively, lower right). Red fluorescent protein (RFP)- labeled metastatic colon carcinoma cells (red) will be infused via portal vein and will migrate from vasculature.

We hypothesize that this bioengineered 3D liver organoid will provide a permissive environment for the invasion and growth of human cancer cells. We predict that such a system will serve as a biologically accurate model in which to study critical aspects of metastasis. We are utilizing human carcinoma cell lines established from metastases to liver. The system should allow unprecedented observations and mechanistic analysis at the cellular and molecular levels of host-tumor interactions during: 1) extravasation through the organoid’s vascular network, 2) metastasis growth in a specific niche and 3) interaction of tumor cells with the microenvironment of the organoid parenchyma. By collecting genomewide DNA microarray measurements at carefully selected time points, we aim to identify response networks and biological processes that are changed during the establishment of liver metastasis.

3 Cellular response networks

Murali and Rajagopalan have developed a novel approach called ``Contextual Biological process Linkage Networks'' (CBPLNs) that computes which processes in the cell are transcriptionally perturbed in a particular context and how these processes are linked to each other by interactions among genes and gene products. Our approach is predicated on the belief that high-level linkages between pathways and processes make identification of important biological trends more tractable and intuitive than through interactions between individual genes and molecules alone. Multiple phenomena captured by CBPLNs at the process level such as regulation, downstream effects, and feedback loops have well described counterparts at the gene and protein level. Our approach may provide a new route to explore, analyze, and understand cellular responses to internal and external cues within the context of the intricate networks of molecular interactions that control cellular behavior.

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The CBPLN between four liver-related gene sets that captures two intrinsically linked functions that hepatocytes carry out: lipid homeostasis and bile acid synthesis. Each node is a gene set. A blue edge connects two gene sets that are significantly linked.

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The genes and interactions that yield the link between "Nuclear Receptors" and the "PPAR Signaling pathway." Each ellipse is a nuclear receptor, each rectangle is a member of the PPAR signaling pathway, and house-shaped genes are in both sets. The darker the color of a gene or a gene set, the more up-regulated it is.

4 Inter-cellular signaling

The in vitro liver models developed by Soker and by Rajagopalan incorporate multiple cell types found in the liver. Communication between these cell types contributes to the enhanced phenotypic activity of these liver models. However, the precise pathways of communication are not completely understood. We are developing a combined experimental and computational strategy to discover these communication channels.

One of the major modes of cell communication is initiated by the secretion of signaling proteins such as cytokines and chemokines, which bind to receptors, trigger protein signaling cascades, activate transcription factors, and culminate in the perturbation of target genes and subsequent downstream events. Transcriptional measurements capture changes in the expression levels of direct and indirect targets of activated transcription factors but may miss upstream signaling events. Therefore, we are developing novel computational techniques that will analyze transcriptomic datasets in the context of molecular interaction networks in order to prioritize signaling pathways that would be useful to study experimentally at the protein level.

5 Computational liver toxicology

Our goal is to establish the in vitro three-dimensional liver mimic developed by Rajagopalan as an effective model for studying the effects of toxicants on the liver. We are developing phenomenological concentration-response models that integrate molecular profiling data from DNA microarrays with comprehensive signaling, interaction, regulatory, and metabolic networks to capture perturbed cellular pathways in the liver. We are using this approach to enable the discovery of response pathways that are perturbed in liver mimics due to single toxicants or combinations thereof.

6 3D models of tumor stress response

Cancer progression is largely a process of somatic evolution, in which populations of cells compete for survival within a microscale tissue ecosystem. While genetic changes within cells play a central role in tumor initiation and growth, the role of microenvironmental stresses in driving this evolutionary process remains less well understood. In the Verbridge lab, we are interested in using 3D in-vitro culture platforms to apply as well as quantitatively monitor well defined stresses, in order to ask several types of questions, including: 1) How do these stresses influence cellular heterogeneity, 2) what are the dynamics of the selection process in response to stress barriers, and what are the resulting phenotypes, and 3) what modes of cell-cell coupling are implicated in this process. We are interested in studying response to stresses inherent in the tumor microenvironment (hypoxia, acidosis) as well as those resulting from therapeutic intervention (cytotoxic drugs, radiation, heat, electric fields).

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Schematic (left) of a 3D hydrogel tumor culture, fed via microfluidic channel and sealed on the remaining boundaries. A spontaneous gradient in oxygen develops as a result of a balancing of microfluidic nutrient delivery from the left side of the scaffold, molecular diffusion, and cellular consumption. The oxygen gradient (normoxic-red to hypoxic-blue) is imaged and quantified (right) using integrated phosphorescent nanoparticles, enabling a probing of the oxygen microenvironment with subcellular resolution.