In the current state of the art, microfluidic gradient generators are the only

ABSTRACT

Biomolecular concentration gradients play a relevant role in many biological phenomena including cell development, inflammation, wound healing, and cancer. In order to better investigate and elucidate these aspects, several in vitro systems have been defined for exposing cells to chemical gradients. In combination with in vivo studies, these methods have revealed gradient signalling to be an intricate, highly-regulated process, in which the ultimate cellular response is determined by the concentration, and spatiotemporal characteristics of the gradients to which the cells are exposed [1]. A complete understanding of gradient effects on cellular behaviour is still on going and more technological platforms mimicking the in vivo chemical environment are required in order to increase the knowledge of many cellular mechanisms.

In the current state of the art, microfluidic gradient generators are the only

systems able to accept the previous challenge. In fact, they can provide a

way to create predictable, reproducible, and easily-quantified biomolecule

gradients in vitro [1]. Indeed, microfluidic systems allow in principle the

creation of multiple biomolecule gradients on a single chip, each with its

own user-defined spatial and temporal distribution. A few recent prototypes

[2], [3] demonstrated the possibility to generate gradients with limited

lifetime, which is determined by the biomolecule diffusion coefficient and

by the device geometry. Unfortunately, this characteristic limits the use of

these systems exclusively to short-term experiments. Moreover, complex

gradient geometries have not yet reproduced. These limitations can be

overcome by steady-state gradient generators (as in [4], [5]). These systems

can create complex geometries of gradients, but high reagent consumption

and high shear stresses are avoiding their widespread use. A few of these

devices ([6], [7], [8]) have been also coupled with patterned substrates in

order to complete the artificial environment with specific topographies.

Surface patterning can be obtained by standard microfabrication methods (photolithography [9], electron beam lithography and/or and soft lithography) that, combined with advanced surface chemistry, enable to reproduce and control the cell micro-environment with unprecedented fidelity.

The aim of this thesis is to design, fabricate and test an original microfluidic gradient generator capable to produce complex and dynamic chemical gradients within a specific chip area (called chamber) compatible with micro /nano-engineered surfaces.

In this work, two main objectives have been defined:

I. Development of the gradient generator: demonstration of complex biomolecule gradients production and study of cellular viability inside the chamber.

II. Development of a micropatterned substrate: demonstration of protein micropatterning and cell immobilization characterization.

Starting from the technology demonstrated by Chung and colleagues [3], it was exploited the superimposing gradient profiles generated by fluid flows from orthogonal microchannels in order to build complex, user-defined 2D concentration patterns. To complete this system, special efforts were finally dedicated to the fabrication and test of a specific micropatterned substrate for cell-immobilization. This surface was designed to constitute the bottom layer of the chamber.

The chip realization required the optimization of conventional (photo-

lithography) and non-conventional (soft-lithography) fabrication

techniques. MultiLayer Soft Lithography was used for the fluidic layers,

whereas micro-Contact Printing was employed to generate a substrate with cell

adherent (made of fibronectin) and cell repellent (made of PLL-g-PEG)

areas. Transparent materials were used to maintain the compatibility with

standard optical microscopy [10]. Thus, the chip was conceived to be

entirely made of Polydimethylsiloxane (PDMS) bonded to a thin coverglass (24 x 50 mm ² , 0.15 mm thick).

For the chip development, two PDMS layers were necessary. They were overlapped in order to form a fluidic circuit controlled by soft active valves [11]. The bottom layer formed the fluidic channels, the top one was used for the control channels. The overlapping of the two channels formed the control valve which is the essential element for the gradient generation (figure 1). When the upper channel is pressurized, the membrane between the channels is deflected downwards and the flow in the lower channel is reduced or shut off (figure 2).

Figure 1 Geometry of the active valve.

Figure 2 a) Valve cross section. b) Pressurizing the control channel leads to the

occlusion of the fluidic channel.

The system has 8 fluidic channels (numbered in figure 3 a with F subscript) each one with its own control channel (numbered in figure 3 a with C subscript) and 4 outlets for waste removal. The PDMS structure obtained is depicted in figure 3 b and d. The 3D sketch of the chamber is depicted in figure 3 c.

a) b)

c) d)

Figure 3 a) 3D sketch of the microfluidic chip. b) Low-magnification image of the PDMS microfluid chip. c) 3D sketch showing the chamber for cell culturing. d) High-magnification image of the final microfluidic chip (chamber area). The 8 valves and 4 channels for waste removal are visible. Some crosses are also visible:

they help the alignment of the top layer to the bottom one.

Some tests were required to assess the performance of the soft valves.

These tests demonstrated that:

1. the minimum pressure to apply to the control channel in order to close completely the fluidic channel is 5 psi ¹

2. the maximum valve operation frequency is 3 Hz (50 % duty cycle).

It was also evaluated that a fluidic channels delivers 1.8 μl/h of fluid at a

pressurized at 15 psi. Using these working conditions, it was demonstrated the generation of complex gradient. To visualize the concentration gradient, a fluorescein isothiocyanate solution was used as delivered fluid and fluorescence microscopy was carried out. The system was tested at different fluidic pressures: 5, 10 and 15 psi. At 100 μm from the outlet of a selected fluidic channel, the fluorescence intensity signal over time was measured.

Figure 4 a reports several concentration profiles obtained during this experiment. Figure 4 b shows the trend of the intensity signal over time.

Each frame has fluorescence intensity signal normalized to the white value.

After the transient period, the curves show a cyclic trend with different mean values, which are related to the different pressures that regulate the volumetric rate of fluid delivery.

a) b)

Figure 4 a) Fluorescence signal at different times and for different pressures. b)

Fluorescence intensity as a function of time at different pressures. The measure is

taken 100 μm distant from the outlet of selected channel (along the white dashed

direction of figure 4a).

The 2D fluorescence intensity profiles (figure 5) were obtained by plotting the mean fluorescence intensity values (for t > 50 s) as a function of the distance from the fluidic channel.

Figure 5 Fluorescence intensity profile along the fluidic channel direction (dashed line of figure 4 a) at different pressures. The experimental data (mean values over 3 minutes) were fitted with exponential curves which express the 99 % of similarity with the experimental data.

To show a possible multi-channel working configuration, two orthogonal fluidic channels were pressurized. The fluidic pressures were set at 10 psi.

Figure 6 a presents some frames at different times of the experiment while

figure 6 b shows a comparison with the single channel data. Near the upper

channel outlet, the trends are similar. Differently, approaching to the centre

of the chamber and precisely at 250 μm from the upper channel outlet the

composition of the two gradients leads to a clear deviation from the single

channel concentration profile.

a) b)

0 0,1 0,2 0,3 0,4 0,5 0,6 0,7

100 150 200 250 270 300 350

DISTANCE FROM SOURCE (um)

NORMALIZED MEAN INTENSITY (A.U.)

Figure 6 a) Fluorescence signal at different times (fluidic pressure = 10 psi). b) Fluorescence intensity profile of two orthogonal channels (pressurized at 10 psi) along white dashed direction of figure 6 a (blue curve) compared to the only channel gradient profile (pink curve).

Finally, the ability of the developed system to sustain experiments with cells was demonstrated. A cell suspension was loaded in the chip chamber through a syringe, using a little manual pressure, after connecting the syringe tip to the cell input port with a metallic pin (figure 7 a). Cells did not appear damaged by the injection procedure: any lysed or apoptotic cells could be found in the fluorescence image (figure 7 b), where the stained cellular nuclei appear clearly defined. The cell density in the chamber, starting from a solution of 5 x 10 ⁵ cells/ml, was around 300 cells/mm ² .

a) b)

Figure 7 a) Cell suspension loading. The REF cell suspension was made of 900 μl of medium culture and 100 μl of Hoechst stain; b) fluorescence image of cells in

the chip chamber.

To monitor the cell vitality inside the chip a time lapse microscopy was performed. The chip was mounted in the thermostatic chamber and observed with a 20x objective for 5 hours. This test provided a preliminary evaluation of the compatibility of the PDMS chip: cells were maintained viable for at least 5 hours. This experiment suggested that, renewing the culture medium, the microsystem can be useful for future long term studies and cell analysis. Furthermore, the selected cell density (300 cells/mm ² ) represents an optimal starting value for seeding cells, in particular for short term experiments and analysis (up to 12 h).

The second part of this work was related to the micro-contact printing of fibronectin on glass. Once optimised, this procedure turned out to be reliable and reproducible. The areas where fibronectin was not deposited were passivated with PLL-g-PEG in order to efficiently prevent cell adhesion (figure 8) [12].

Figure 8 A cover glass with fibronectin pattern (dark stripes) and passivated with PLL-g-PEG labelled with rhodamin (red). The pattern is composed of parallel

stripes 10 μm wide.

Two cellular types were immobilized: REF (rat embryoblast fibroblast) and

SH-SY5Y (human neuroblastoma cell line). The cells were seeded at

different densities, 8000 cells/cm ^-2 and 80000 cells/cm ^-2 respectively. REFs

express fluorescent paxillin; its distribution can be easily imaged by

fluorescence microscopy (figure 9 a). In both cases the pattern was stable

for three days of culture (figure 9 b). It was observed that patterns wider

a) b)

Figure 9 a) REF adhesion one day after the seeding. They were previously washed with PBS and then imaged. Figure shows a clear cell protrusion along the patterned stripe. b) Attached SH-SY5Ys on fibronectin stripes after three days of culture. They are visible some rounded cells forming clusters because they were not able to adhere on PLL-g-PEG areas

Thanks to the simplicity of micro contact printing, plenty of patterns can be designed and used with this system. The objectives of future work aim to assembly such substrates to the designed complex gradient generator and to use this system for research purposes.

REFERENCES

[1] T. M. Keenan and A. Folch, Biomolecular gradients in cell culture systems Folch, Lab Chip, 8: 34 – 57, 2008.

[2] V. V. Abhyankar, M. A. Lokuta, A. Huttenlocher and D. J. Beebe, Characterization of a membrane-based gradient generator for use in cell- signaling studies, Lab Chip, 6(3): 389–393, 2006.

[3] B. G. Chung, F. Lin and N. L. Jeon, A microfluidic multi-injector for gradient generation, Lab Chip , 6(6): 764–768, 2006.

[4] A. E. Kamholz, B. H. Weigl, B. A. Finlayson and P. Yager, Quantitative

analysis of molecular interaction in a microfluidic channel: the T-sensor,

Anal. Chem., 71(23): 5340–5347, 1999.

[5] N. L. Jeon, S. K. W. Dertinger, D. T. Chiu, I. S. Choi, A. D. Stroock, and G. M. Whitesides, Generation of solution and surface gradients using microfluidic systems, Langmuir, 16(22): 8311–8316, 2000.

[6] C. J. Wang, X. Li, B. Lin, S. Shim, G-L Ming and A. Levchenko, A microfluidic-based turning assay reveals complex growth cone responses to integrated gradients of substrate-bound ECM molecules and diffusible guidance cues. Lab Chip 8: 227-237, 2008.

[7] S. W. Rhee, A. M. Taylor, C. H. Tu, D. H. Cribbs, C. W. Cotman and N.

L. Jeon, Patterned cell culture inside microfluidic devices, Lab Chip, 4, 2004.

[8] M. Goto, T. Tsukahara, K. Sato and T. Kitamori, Micro- and nanometer-scale patterned surface in a microchannel for cell culture in microfluidic devices, Anal Bioanal Chem 390: 817-823, 2008.

[9] F. Patolsky, B. P. Timko, G. Yu, Y. Fang, A. B. Greytak, G. Zheng and C. M. Lieber, Detection, Stimulation, and Inhibition of neuronal Signals with High-Density Nanowire Transistor Arrays, Science 313: 1100-1104, 2006.

[10] J.C. McDonald and G. M. Whitesides, Poly(dimethylsiloxane) as a material for fabricating microfluidic devices, Acc Chem Res 35(7): 491-499, 2002.

[11] J. Melin and S. Quake, Microfluidic Large-scale integration: the evolution of design rules for biologica automation, Annu. Rev. Biophys.

Biomol. Struct., 36: 213-231, 2007.

[12] J. Fink, M. Théry, A. Azioune, R. Dupont, F. Chatelain, M. Bornens

and M. Piel, Comparative study and improvement of current cell micro-

patterning techniques, Lab Chip, 7, 672-680, 2007.