(596d) Oxygen Sensing and Control of Engineered Tissue

Introduction

To properly model
physiological processes with heterogeneous oxygenation conditions, an
experimental platform is needed that can dynamically control and measure the
oxygenation of 3D cell culture. Many studies
have demonstrated that ambient oxygen concentrations can differ significantly
from the concentrations that cells actually experience in 2D culture. The inherent diffusion limitation of 3D culture, particularly at
clinically relevant dimensions (> 1 mm), adds an additional hurdle for oxygen
transport. Here we present an experimental platform that offers simultaneous
dynamic oxygen control and measurement of oxygen diffusion through 3D
engineered tissue. The platform, in conjunction with a non-steady state
mathematical model for oxygen diffusion, enables quantification of the oxygen diffusion
coefficient and cellular oxygen consumption rate, while also predicting the
temporal and spatial distributions of oxygen in a thick tissue subject to time-varying
oxygenation conditions.

Materials and Methods

An oxygen control chamber system was fabricated to function
as a miniature cell culture incubator with programmable oxygen tension in the
gas phase. An oxygen sensor patch (Presens, Germany)
was placed at the base of a cylindrical well, and a 2.5mg/mL fibrin tissue (3
million normal human lung fibroblasts per mL) was
constructed on top of the patch (Figure 1). The well was then placed inside the
oxygen control chamber, where an external oxygen probe non-invasively provides
real-time measurements of the oxygen concentration at the base of the tissue. Michaelis-Menten kinetics was used to model oxygen
consumption, and numerical techniques were performed to determine values for
the oxygen consumption rate. Finite element analysis (FEA) software was then
used to predict detailed spatial and temporal oxygen concentration.

Results

The
oxygen control system achieves gas equilibration (90% response time) within 60
seconds, and can be programmed to deliver 0-100% O₂. The Michaelis Menten parameters were
found to be: V_max= 1.1e-4 mol/m³/s
and K_m= 0.036 mol/m³. FEA modeling provides temporal
(Figure 2A) and spatial (Figure 2B) oxygen diffusion information.

Discussion and Conclusions

Through the simultaneous
control and measurement of local tissue oxygen levels at the boundaries (top
and base), a system has been developed that can predict the temporal and
spatial oxygenation of 3D culture. While most mathematical models of 3D culture
have relied on steady state assumptions and constant boundary conditions, the
present model employs non-steady state analysis and allows for time varying
boundary conditions consistent with in vivo
observations of intermittent hypoxia.

A)                                                                                       B)

Figure 2: A) A square wave
oxygen exposure profile at the top of the tissue (dashed line) has a
significantly attenuated effect on the oxygenation at the base of a 2mm thick
cellular tissue (solid, dotted lines). B)
Sample spatial distribution of oxygen in model tissue (top layer: ambient
gas, bottom layer: fibrin gel).