To advance regenerative medicine towards recapitulating the structures and functions of human tissues at physi- ologic length scales and with relevant cell densities, strategies must be developed to meet their unrelenting metabolic demands. In order to effectively and ef?ciently oxygenate functional engineered tissues, we must understand how changes in oxygen tension modulate cell viability, proliferation, and phenotype. Decades of studying cell cultures incubated under low oxygen levels have unveiled some aspects of the hypoxic response and many key in- sights into its mechanism. Separately, an astonishing array of biomaterials have been developed which can support cells in 3D environments and can recapitulate native cell morphologies and functions to a much greater extent than 2D culture. However, as emerging areas such as regenerative medicine have sought to incorporate cells within these materials, new questions have emerged regarding the roles played by oxygen transport and hypoxia in directing the density and function of the cell populations. Currently, we lack a comprehensive framework to describe and pre- dict how cell populations will alter their densities and functions over time in the presence of spatiotemporally heterogeneous oxygen gradients. We need to extend our knowledge of cellular responses to hypoxia into 3D and we need to pro?le how tissue-speci?c cell functions are impacted by local oxygen cues. In this proposal, I and a sup- porting team of experts in biomaterials, computational modeling, and liver biology will unify computational models of hypoxic response with engineered model tissues to link oxygen transport with tissue function in 3D. Our ?ndings will be incorporated into an experimentally validated model capable of predicting how cell popula- tions change in density and function in response to speci?ed oxygen gradients. Cellular responses to hypoxia will be parameterized by cell-speci?c response functions and integrated with oxygen transport equations in an agent-based computational model. We will ?t parameters using advanced volumetric imaging and image segmentation along with biochemical assays to map cellular markers of viability, proliferation, hypoxia, and phenotype within 3D hydrogels containing HepG2 liver cells, a well-de?ned model cell type from a highly metabolic tissue. I hypothesize that our closed-loop computational and experimental work?ow will yield a scalable model of cell behavior at the tissue level which captures previously unstudied functional responses to hypoxia. Finally, to broadly pro?le the phe- notypic landscape of cells growing in the presence of oxygen gradients, we will use RNA sequencing to map spatial zonation of cell phenotypes along axial and radial oxygen gradients in perfused hydrogels. Controlled encapsulation of cells within hydrogels of reproducible architecture will enable us to evaluate these spatial patterns in gene expres- sion with a degree of experimental control and reproducibility beyond the capabilities of in vivo approaches. Taken together, these studies will provide fundamental insights into how cells respond to local oxygen gradients in 3D environments. Analysis of the spatial heterogeneity introduced by oxygen gradients is also expected to inspire new paradigms for engineering zones of cell function within tissues.

Public Health Relevance

This proposal aims to investigate, using computational and experimental techniques, the effects exerted by hypoxia on cell populations in 3D engineered tissues in terms of their viability, proliferation, metabolism, and cell phenotypes. These studies will yield fundamental insights into the biology of hypoxic response in 3D and determine feasibility of new paradigms for engineering patterns of cell function in tissues.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Predoctoral Individual National Research Service Award (F31)
Project #
1F31HL140905-01
Application #
9470651
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Lidman, Karin Fredriksson
Project Start
2018-04-16
Project End
2020-08-15
Budget Start
2018-04-16
Budget End
2019-04-15
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Rice University
Department
Biomedical Engineering
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
050299031
City
Houston
State
TX
Country
United States
Zip Code
77005