42nd AIAA Aerospace Sciences Meeting and Exhibit Paper Number: AIAA-2004-1320

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Copyright 2003 by John Kizito. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. *Staff Scientist, National Center for Microgravity Research, NASA John H. Glenn Research Center. AIAA member and corresponding author. John.Kizito@grc.nasa.gov ‡Research Associate, National Center for Microgravity Research, NASA John H. Glenn Research Center. †Research Associate, National Center for Microgravity Research, NASA John H. Glenn Research Center. §Electro-optical Sensor Systems Engineer, NASA Glenn Research Center.

CHARACTERIZATION OF ENVIRONMENT IN MICRO-BIOREACTOR FOR BONE CELLS

J.P. Kizito*, K.L. Barlow‡ , J.R. Adamson† National Center for Microgravity Research, NASA Glenn Research Center, Cleveland, OH 44135

and D.W. Griffin§

NASA Glenn Research Center, Cleveland, OH 44135

ABSTRACT

The present paper highlights our efforts in the bio-physicochemical transport process characterization of microbioreactors designed for bone cells studies. The purpose of this effort is to guide our biological testing for cell viability, growth, and morphology markers. We present a microbioreactor design that has been fabricated and tested to ensure that the flow is uniform in the direction of flow. Transport characterization results are obtained using a variety of methods: numerical results presented are the shear rate distribution, dissolved oxygen transport from the inlet to the outlet of the microbioreactor and the transport of dissolved carbon dioxide from a monolayer to the outlet and velocity vector map at the mid section plane of the microbioreactor; also, the theoretical velocity field map compares well to experimental PIV test data; finally, we present data to show that our present design can support bone cell growth.

INTRODUCTION

Chronic weightlessness, the result of microgravity exposure, leads to a significant decrease in bone mass.1,2,3,4,5,6,7,8 Bone tissue consists mainly of bone-forming cells (osteoblasts), bone resorption cells (osteoclasts), mineralized structure with entombed osteocytes, interstitial fluid, and blood vessels. Bone tissue consists of 25% fluid.9 The bone mass reductions are most severe in skeletal sites associated with primary bone formation.10,11,12,13,14 Research clearly demonstrates that while the rate of bone resorption is essentially unchanged, there is a decrease in the bone formation rate in microgravity.6 Although the work cited above provides convincing evidence that space travel decreases bone mass, it is not clear whether the

diminished rate of bone formation is a direct effect of microgravity at the cellular level, or it is an indirect result of fluid convection forces at the organ or organism level3,5. Recently, space flight investigations observed that a microgravity environment alters the appearance of cultured osteoblasts from that of their terrestrial counterparts and diminishes the proliferation of cultured osteoblasts,15 as well as their osteogenic gene expression.16,17,18,19 One microgravity study16 controlled fluid convection forces by providing a constant, linear low-flow rate through hollow fiber cartridge cultures during the entire incubation period, yet still observed significant reductions in type I collagen and osteocalcin gene expression during space flight. These studies argue that a microgravity environment may directly diminish a bone forming cell’s capacity to maintain its osteogenic phenotype. However, none of these studies separated the effect of increased or decreased mechanical forces such as shear stress from a concomitant increase or decrease in the mass transport of nutrients. Therefore, the results are ambiguous and may well confuse clinicians devising countermeasures against disuse osteopenia.

In normal gravity, cyclic impact mechanical loading occurs with regular movement to maintain the bone’s integrity. The mechanical loading generates a series of different types of stresses and transport of interstitial fluid that may stimulate bone remodeling. The load causes a bending force producing compressive and tensile stresses within the bone structure. The bone structure will physiologically deform according to Hooke’s law, thereby changing the tissue porosity. The dynamic differential porosity will similarly cause fluid flow leading to interstitial fluid redistribution. The cyclic movement of bone interstitial fluid has two impacts on the bone structure: shear stress20 and biochemotransport.21 These studies show shear stress affects cells and suggest that biochemotransport has a role in mechanotransduction. In a reduced-gravity environment, these forces and associated flows are negligible, possibly leading to microgravity-induced osteopenia. We present methods used to measure shear stress on bone cell monolayer.

The most important issue in characterizing the effects of gravity on any system is to adequately isolate,

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AIAA 2004-1320

Copyright © 2004 by John Kizito. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.

42nd AIAA Aerospace Sciences Meeting and Exhibit Paper Number: AIAA-2004-1320

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quantify and measure parameters which will unambiguously describe the gravitational environment. Effects of gravity on living cells and microorganisms are two-fold: first, gravitational fields will modify intracellular structure (i.e. cytoskeleton reorganization)13,22 and second, gravitational fields will modify the cells’ environment by causing buoyancy driven convection, bioconvection, and sedimentation. The transport of nutrients and gases to the cells and the removal of metabolic products are affected by the new environment and play a role in the way cells react to gravity. Lastly, we present the methodology for determining the dissolved oxygen transport within the bioreactor.

Previous research has shown that proper mechanical loading of bone tissue has beneficial effects on its growth and maintenance. However, the understanding of the mechanism(s) by which bone atrophies in microgravity due to disuse is limited. Consequently, there are no effective and proven countermeasures to deter bone loss among astronauts who have prolonged exposure to microgravity. To resolve this widely recognized problem, we report on one of the methods used to understand the type and effects of mechanical loading forces and their associated fluid transport phenomena. We have designed a microbioreactor that allows us to separate the effects of mass transport from those of direct mechanical stimuli on bone cells. In particular, the present paper highlights our efforts in the characterization phase of the project using both numerical and experimental methods that provide new insight and techniques to overcome bone density loss experienced by the astronauts whose health and well-being is critical to the NASA mission. The purpose of this effort is to guide our biological testing for cell viability, growth, and morphology markers. In the present paper, we report on cell viability in the microbioreactors.

THEORETICAL CONSIDERATIONS

Transport Phenomena The equations that describe transport of momentum

and species can be written for a simple limiting heterogeneous metabolic reaction. Oxygen is transported by the fluid flow to the interface of a monolayer of cells where the cells produce carbon dioxide. In the present analysis, we assume that the glucose concentration is constant. These types of reactions are used in the design of bioreactor for batch-type reactions. We assume that a monolayer of cells have similar metabolic reactions described in the equations below. Equation 1 is a compact form describing the transport of parameter C undergoing both diffusion and convection in the presence of a source term, S. The boundary conditions are Equation

2. In this paper, we consider only the transport of oxygen and carbon dioxide. The parameter C, in Equation 1, represents the velocity vector and species (oxygen, and carbon dioxide) concentrations. The term Do, in Equation 1, represents the diffusion coefficients of momentum and species. The source term for momentum transport represents the pressure gradient and the gravity term written as a function of density difference. The source term for the species represents either the production or the consumption of the indexed species. For the boundary conditions at monolayer interface, we impose the no slip boundary condition for the momentum transport. For the dissolved gas boundary conditions, O2 concentration is a maximum at the inlet and CO2 concentration is a maximum at the monolayer and the walls are impermeable to gases (akin to thermal insulation). The equations of momentum and species are coupled through g, the gravitational vector, and the convective velocity. The transport equation in compact form is

2 ( )o

CU C D C S t

t∂

+ ⋅∇ = ∇ +∂

r (1)

where,

2 2

2 2

o

1

, , ( ) 0

0O O

CO CO

g pU

C C D D S t

C D

ρρ ρν

∆− ∇ = = =

rr.

Boundary conditions are 0, and 0u c= ∇ =

v (2)

2

2

1 at the inlet

1 at the monolayer

C 0 at the walls.

O

CO

C

C

=

=

∂ =∂n

(3)

The symbols are defined as follows:

velocity vectortime

= spatial gradientdynamic pressure.

Ut

p

==

∇=

r

The shear stress is determined by the equation

τ µ γ= ⋅ . (4)

Here, τ is the shear stress, µ is the fluid dynamic viscosity (~.001 (Pa s)), and γ is the shear rate or velocity gradient, (∂u/∂y). Scaling Analysis

In general, we can use a solutal Grashof number (Grs) to assess the relative importance of forces caused by buoyancy driven convection to viscous damping forces in various parts of the bone tissue and

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bioreactors. The table below shows how the Grs varies with aspect ratio. The solutal Grashof number is defined by Equation 4 as:

( ) 3

2s

LGr

ρ ρν

∆=

g (5)

here, g is the gravitational vector, ( )ρ ρ∆ is the ratio

of density difference between the media and water to density of water and L is the characteristic length scale measured in the direction of gravity. Also, ν is the kinematic viscosity.

A cell culture flask of 3mm in height is compared to microbioreactor whose height is 100 micrometer in Table 1. This table shows that length scales on the order of 100 micrometers are sufficient to minimize the buoyancy driven convection. At 37oC, given 1% density difference ratio, Grashof number changes by 3 orders of magnitude.

Table 1 Effect of the Length Scale on Buoyancy Driven Convection.

Area Flask Microbioreactor

Length Scale (m) 0.003 0.0001

Grs 6,652.3 0.25

MATERIALS & METHODS

Numerical Methods

We perform computational fluid dynamics (CFD) calculations using a commercial finite element code called FIDAP. CFD is used as a design tool to predict the magnitude and type of velocities, stresses, transport of dissolved gases and pressures found in the growth wells. The methods and techniques for CFD are outlined in the user manual.23 The goal of using CFD is to solve coupled Equation 1 subjected to appropriate boundary conditions. We calculate the shear rate distribution, concentration distributions and all hydrodynamic quantities that describe the cell environment. The schematic illustration of the computational domain is shown in Figure 1 and the finite mesh domain shown in Figure 2 consists of 400000 3-D elements. Microbioreactor fabrication

The design of the microfluidic pathway of the bioreactor was selected due to its simplicity and ability to fulfill two fundamental needs: to provide an area in which the cells can attach, as well as a fluid inlet and outlet whereby fresh media can be supplied to both nourish the cells, and generate shear stress stimuli. Inlet and outlet channels are 1 mm diameter (di, and do), the circular cell culture region is 2 mm in diameter (dw), and all regions have a height (h) of 100 µm as shown in Figure 1.

The microbioreactor is composed of a cell culture well, 100 µm in height, 1000 µm radius connected to flow channels with a 100 µm by 100 µm cross-section. The high aspect ratio of the cell culture-well (radius/height) is specifically designed to ensure that the flow is uniform in the direction of flow.

The microfluidic pathway design was patterned onto 75x55 mm glass slides using soft photolithography techniques, providing the mold upon which the liquid mixture of uncured PDMS and curing agent (Dow Corning, Sylgard 184) was poured. After 48 hours, the hardened PDMS was removed from its mold and any remaining curing agent was baked off at 75°C. Fluid access ports were created at the inlet and outlet entrances and exits, respectively, by piercing the PDMS with a square-tipped syringe needle. The PDMS mold was finally bonded with a clean glass slide by nitrogen plasma treatment of the bonded surfaces.

The completed microbioreactors were sterilized in an autoclave to prepare them for cell culture. To provide an appropriate binding surface for the cells, the microfluidic channels were treated with 50µg/mL collagen in 0.02N acetic acid. The acetic acid was allowed to evaporate overnight in a 37°C humidified CO2 incubator, after which any remaining solution was aspirated. The microfluidic channels were then washed several times with sterile phosphate buffered saline (PBS) to remove any remaining acid. Fluid Flow PIV Experiments

Water seeded with 1 µm particles was pumped through the chamber manually via a microliter syringe and capillary tubing. Fluid flow was observed using an Olympus CKX-40 microscope fitted with 20x and 4x phase objectives and images were acquired with an Olympus CC12 digital CCD camera. Images were analyzed using PIVPROC© software in cross-correlation mode. The average velocity was 1.5µm/s with the highest velocities of approximately 2.5µm/s at the inlet. Video images were recorded at 40 Hz using CCD attached to an Olympus CKX-41 microscope with a N.A. 0.4, 20X objective, and the images were sectioned into 3µm slices using the depth of field inherent to the objective.

Outlet Inlet

Cell culture well u

do di

u

dw

O2

Monolayer CO2 O2

h

Flow Channels

Figure 1. Schematic illustration of computational domain and microbioreactor model.

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Cell culture

UMR-106 BSP+ rat osteosarcoma cells were routinely passaged in T-75 culture flasks every three days, according to the protocol developed by Midura et al.24 Subculturing to the microbioreactors was achieved by briefly washing the confluent cell layer in a T-75 flask with Hanks’ balanced salt solution (HBSS) without Ca2+ or Mg2+ followed by trypsinization (0.05% trypsin plus 0.53mM EDTA in HBSS at 37°C). Cells were counted using a hemocytometer and seeded at 2000 cells/mm2 in the prepared microbioreactors.

RESULTS

The high aspect ratio of the cell culture-well (radius/height) is specifically designed to ensure that the flow is uniform in the direction of flow. We use scaling laws to infe r conditions at length scales of 10 µm. Hence, this microbioreactor is an excellent geometrical model of vascular and lacunar-canalicular vessels.

Preliminary results of the transport characterization were obtained using a variety of methods. First, numerical results were obtained from simulations using FIDAP. Results in Figure 3 show the shear rate distribution map at the monolayer due to a flow rate of 119µL/min. The shear stress map is cropped for clarity. This figure shows that most of the cells grown in the well are not exposed to the high shear stress found in the microchannels. Equation 3 can be used to estimate the shear stress magnitude. Less than 1% of the monolayer is exposed to stress greater than 1 N/m2 or 10 dynes/cm2.

Figure 4. The contour plot of the relative dissolved gases concentration distributions at various times after initiation of perfusion. Figures (a) and (c) show the

Relative dissolved gas concentration

(c) CO2 distribution at 119 µL/min and time=1.5 seconds

(a) CO2 distribution at 0.1 µL/min and time=6.75 seconds

(b) O2 distribution at 119 µL/min and time=1.5 seconds

Figure 2 Computational mesh showing half of the symmetric domain. The computational mesh is composed of 400,000 hexagonal elements.

Figure 3. Shear stress maps due to perfusion of medium at a rate of 119µl/min

Shear Rate (1/s)

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relative carbon dioxide distribution due to monolayer generation and the effect of low perfusion rate.

Figure 4 shows the calculated distribution of dissolved oxygen and carbon dioxide in the microbioreactor at various times after initiation of the perfusion process. Figure 4a shows that at a low perfusion rate, the well is filled with CO2 6.75 seconds after initiation of perfusion, a condition which is not conducive for cellular growth. When the flow rate is increased as shown in Figures 4(b) and (c), the O2 concentration at the well is adequately distributed and the generated CO2 can be easily transported to the exit port.

Figure 5 Velocity vector map (m/s) due to a perfusion rate of 119µl/min.

All concentration magnitudes are scaled to the inlet concentration (maximum value of 1), which is the saturation value for dissolved oxygen or carbon dioxide in water. These figures show that the design adequately provides for the necessary O2 and metabolic CO2

removal without creating stagnation zone or accumulation above a certain flow rate.

Figure 5 shows a velocity vector map cropped for clarity from 0.001m/s to 0.01m/s. The figure on the left shows the velocity profile at the mid -symmetrical plane and the figure on the right shows the velocity map at mid-height of the cell culture well. The maximum velocity of 0.0339m/s occurs within the square channels due to a perfusion rate of 119µl/min. The theoretical average velocity is 0.0198m/s. The simulated results reasonably agree with the theory because, in pipe flow, the average velocity is one half of maximum and in parallel plate flow, the average velocity is two thirds of maximum velocity. In addition, the velocity field qualitatively compares well with experimental flow velocity test data obtained by using particle image velocimetry (PIV) shown in Figure 6.

Figure 6 shows an image of the microbioreactor, where the inset roughly denotes the exit region of the well: the velocity vectors are imbedded in the image show in the PIV flow map. Video images were recorded at 40 Hz using CCD attached to an Olympus CKX-41 microscope with a N.A. 0.4, 20X objective, and the images were sectioned into 3µm slices using the depth of field inherent to the objective. Thus, via calculation and measurement, we experimentally determined the flow velocity in the neighborhood of cell growth areas.

Cells Cultured in Microbioreactors We have successfully grown cells in

microbioreactors constructed of polydimethylsiloxane (PDMS) on glass substrates using soft lithography techniques. The design goal for the microbioreactors is to independently control the fluid flow rate and stresses or pressure within the growth wells. Subsequent to fabrication and sterilization, the exposed glass substrate in the microfluidic channels of our in-house microbioreactors is collagen coated to provide a substrate conducive to cell attachment. The attachment of bone cells to the substrate presented here shows that the protocol we have developed is favorable to support cell growth.

The images in Figure 7 show the results of the aforementioned biological experiment. The images show that cells can grow in these microbioreactors, much like they would in a standard cell culture vessel, Figure 8.

Figure 6 Microbioreactor and velocity vector map (in green) derived from PIV data.

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CONCLUSION We have presented a microbioreactor design that

shows promising biology results. The data presented shows that our present design can support bone cell growth. In addition, we have characterized the microbioreactor for bio-physicochemical transport processes. The design length scales provide an environment that minimizes buoyancy driven convection. The shear stress distribution in the growth well is within the limits that bone cells can tolerate. The fluid flow rate which transports dissolved gases has been shown to be adequate for oxygen supply to a monolayer and removal of metabolic carbon dioxide from the monolayer to the outlet port. The numerical velocity maximum compares favorably with the theoretical value. Our experimental PIV velocity profile compares satisfactorily with the numerical data.

ACKNOWLEDGEMENT The research is supported by SRF Glenn Research Center 2201SR0049. In addition, the authors gratefully acknowledge Dr Jeff Allen and Dr Andy Resnick for assistance with PDMS construction. We are also grateful to Dr Midura of the Cleveland Clinic Foundation for the bone cells.

Disclaimer

Trade names or manufacturers’ names are used for identification only. This usage does not constitute an official endorsement, either expressed or implied by either the National Aeronautics and Space Administration or The National Center for Microgravity Research.

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Figure 8. Phase contrast image (10x) of UMR-106 BSP+ osteoblast-like cells grown in a standard cell culture flask

Figure 7. UMR-106 BSP+ osteoblast-like cells grown in a microbioreactor imaged at 10x (left), and an enlarged image of a microfluidic channel and growth well in the microbioreactor under the same growth conditions as Figure 8 (below).

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