Department of Electrical and Computer Engineering
University of Maryland
College Park, Maryland 20742, USA
Department of Mechanical Engineering
University of Maryland
College Park, Maryland 20742, USA
Abstract — We describe a CMOS capacitance sensor for measuring the capacitive coupling between living cells and the underlying substrate, a quantity that can be used to characterize cell adhesion strength and cell health. The capacitance sensor operates on the charge sharing principle, mapping sensed capacitance values to voltages. The sensor has been fabricated in a commercially available 0.5 µm, 2-poly 3metal CMOS technology. Experimental results are presented for bench tests using a micropositioned electrode and in vitro tests with cells cultured directly on the chip surface. The sensor achieves an empirical distance resolution of 3 nm and capacitance resolution of 135 aF. The sensors have been successfully used for long term monitoring of cell viability in vitro. and also cell morphological features such as their spreading behavior.
Capacitance sensing in combination with dielectrophoretic actuation has already been employed for cell detection and manipulation. Romani et al. developed a
CMOS Lab-on-a-chip incorporating a capacitance sensor array and dielectrophoretic cages for localization of bioparticles, wherein the sensors detect variations in the dielectric permittivity due to the presence of bioparticles in between the on-chip electrodes and an external conducting lid [2].
I.
I NTRODUCTION
Characterization of living cells using integrated microelectronic sensors [1] is rapidly gaining importance in a variety of biomedical and biosensing applications. These approaches offer many advantages in comparison to existing optical and chemical detection techniques. Firstly they are nondestructive and may be used to monitor responses of living cells in real time. Although living cells are sensitive to electrical stimuli, the capacitance sensing approach described involves very short term exposure of the cells to weak electrical fields for the purpose of briefly assessing cell viability in between long periods of incubation.
Microelectronic sensors also have the advantage of scaling down to match the physical dimensions of the living samples being studied. An integrated system-on-a-chip offers the long-term prospect of automated biosensing and analysis without requiring the infrastructure of a cell biology laboratory.
We have developed a CMOS biosensor for characterizing the surface adhesion of living cells by sensing the capacitive coupling between them and an underlying substrate. Healthy cells adhere more tightly to a surface than unhealthy or dead cells, which results in stronger capacitive coupling between the cells and underlying electrodes. Alternately variations in cell proximity to the chip surface translate into capacitive variations in the cell-substrate interface. This property can be exploited to monitor the interaction of cells with substrates
We have pursued an alternate approach employing a proximity detector for sensing the variations in capacitive coupling between on-chip electrodes and cells, as a means for characterizing cell adhesion and monitoring cell viability. For this purpose we have designed a CMOS capacitance sensor chip comprising an array of capacitance sensors for long term monitoring of their interaction with the underlying substrate.
The remainder of the paper is organized as follows.
Section II explains the significance of characterizing cell adhesion and reviews different techniques employed for this purpose. Section III describes the design of the capacitance sensor. Section IV presents results from experiments on the bench using a micropositioned electrode and in vitro with living cells cultured directly on the chip surface, focusing on the application of this sensor for monitoring on-chip cell viability. Section V summarizes the work.
II.
C ELL A DHESION
The mechanisms by which living cells adhere to substrates have been extensively studied in the fields of medicine, dentistry, bioengineering and environmental sciences. An example of the significance of cell adhesion is in understanding the formation of biofilms (a complex aggregation of microorganisms on solid surfaces), a biological phenomenon with important applications in food and water quality assessment [3].
Living cells exhibit various modes of attachment to substrates [4]. These mechanisms arise from interactions at
This research was supported by the National Science Foundation through
Awards 0225489 & 0238061 and by the Laboratory for Physical Sciences.
0-7803-8834-8/05/$20.00 ©2005 IEEE.
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the molecular level between the cell membrane and the substrate surface, giving rise to adhesive bonds through weak van der Waals forces. In addition to the molecular interactions, there are also extracellular and intracellular mechanical forces generated by anchoring structures which aid in the adhesion process. These enable cells to adapt and adhere to a wide range of surfaces under varying conditions.
The factors influencing this interaction between cells and surfaces can be determined by characterizing the adhesion of living cells.
M1 and M3 are off, redistributing the charges on C
C
N2
.
N1
and
In this direction, previous efforts employed techniques like centrifugation and shear flow measurements [5], where cells cultured on a substrate are subjected to centrifugal and flow forces respectively. The adhesion strength is directly related to the fraction of cells detached from the surface. This kind of macroscopic approach is disruptive to the growth of the cell culture and also provides limited information regarding the statistical variations among cells. Several microscopy techniques such as atomic force microscopy [6] and scanning electron microscopy [7] have also been employed for characterizing cell adhesion strength.
Figure 1. Capacitance sensor for cell proximity detection.
The joint nodal voltage V
N
as a result of the charge redistribution can be expressed as
V
N
=
( C
N 1
+ C cell
) +
C
N 1
+ C
N 2
+ C cell
(1)
All these approaches used specialized techniques and processes in order to characterize cell adhesion. The purpose of this work is to develop a microelectronic sensor that can be designed and fabricated using conventional
CMOS processes, for inexpensive, portable and reproducible characterization of cell adhesion properties, without the need for extensive laboratory infrastructure.
This approach also allows for long term monitoring of viability of cells in their living environment without subjecting them to external forces.
III.
C APACITANCE
A
S ENSING
DHESION S
F OR C HARACTERIZING
TRENGTH
C ELL
Capacitance sensors have been successfully used for applications such as fingerprint sensing [8], position sensing
[9] and interconnect characterization [10]. We report an adaptation of this technique to cell proximity detection for evaluating the surface adhesion properties of living cells. where C as C cell cell
is the capacitance being sensed. According to (1),
increases with increasing cell proximity to the surface so does V
N
. This determines the capacitance to voltage mapping. In order to maximize the sensitivity of the circuit, the parasitic nodal capacitances must be minimized. The sensor dynamic range also increases with increasing area of the metal electrode plate.
In our implementation the topmost metal layer, metal3, forms the sensing electrode. The fringe capacitances between the metal3 plate and the substrate are shielded by means of a larger area metal2 plate below the sensing electrode. The large capacitance between metal2 and metal3 plates is cancelled by driving the metal2 shield with a potential that tracks the sensing electrode potential using a unity-gain buffer as shown in Fig. 1.
A.
Sensor Design
A custom CMOS capacitance sensor for cell proximity detection has been designed using the topology shown in
Fig. 1 [11]. The physical principle underlying operation of the sensor is charge sharing. The coupling capacitance C cell is formed by the series combination of the capacitances between the cell and the passivation layer and between the passivation layer and the topmost metal electrode. C cell varies inversely with the distance of the cell from the chip surface.
The sensor has been designed for a supply voltage of +/-
1.5 V and has been fabricated in a commercially available
0.5 µm CMOS technology with 3 metal layers. Three sensors with electrode areas of 20 x 20 µm 2 , 30 x 30 µm 2 and 40 x 40
µm 2 have been designed and tested. Fig. 2 shows a photomicrograph of the fabricated sensors. biocompatible package & well containing cell culture
The sensor circuit has two nodes N1 and N2 with parasitic capacitances C
N1
and C
N2
. Charging and discharging of these nodes are controlled by a set of three
MOSFET switches M1, M2 and M3, in two phases of operation. In the reset phase, switches M1 and M3 are turned on, charging N1 to Vdd and N2 to Vss, while switch
M2 is off. In the evaluation phase, M2 is turned on, while
40x40 sensors 30x30 sensors 20x20 sensors sensor chip
Figure 2. Left, photomicrograph of the fabricated sensors. Right, photograph of the biocompatibly packaged sensor chip.
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B.
Sensed Capacitance Calibration
In order to translate the sensor outputs to sensed capacitance values, the output voltages during the evaluation phase are subtracted from their corresponding reset voltages for offset cancellation. It follows from (1) that the sensed capacitance depends on this voltage difference according to the expression
C cell
=
( − )
N 2
− V diff
( C
N 1
+ C
N 2
)
V diff
(2) where
V reset
V and diff
= eval
V reset
− V eval
and V reset
= Vdd . Here both
V refer to the voltages before the readout buffer. The gain of the readout buffer must be considered in computing V diff from the experimental readout values.
IV.
S ENSOR R ESULTS
A.
Sensor Testing Using an External Metal Electrode
The transducer has been calibrated by using an external metal electrode whose vertical positioning was controlled by means of a piezoelectric micropositioner. Fig. 3 shows the test results superimposed on the simulated sensor voltages.
The symbols represent experimental values of sensor voltage obtained by moving the micropositioned electrode in steps of 2 to 3 µm. The output voltage dynamic ranges for the 20x20, 30x30 and 40x40 sensors were found to be 100 mV, 200 mV and 400 mV respectively.
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
Simulation Parameters:
Passivation layer thickness = 1 um
Dielectric constant = 6
CN1=20 fF, CN2=18 fF
20x20 sensor
Experimental data
30x30 sensor
Experimental data
40x40 sensor
Experimental data
5 10 15 20 25
Distance of the electrode from the chip surface (um)
30
Figure 3. Variation of the sensor voltages with electrode distance
B.
Sensor Resolution Analysis
Sensitivity is a function of proximity to chip surface, with the sensor being highly sensitive to distance when the cell is closer to the surface. This characteristic is appropriate for the present application, since the cells are directly coupled to the chip surface. Capacitance resolution depends upon the noise performance of the circuit and the test setup.
Simulation of the sensor circuit gives an output noise level of 1 mV which corresponds to an expected capacitance resolution of 30 aF. Noise in the actual experimental setup was measured to be 5 mV which corresponds to a capacitance resolution of 135 aF. Distance resolution improves with increasing proximity to the surface, increasing electrode area and decreasing noise level. Fig. 4 shows a plot of distance resolution of the three sensors with different electrode areas as a function of proximity for the measured noise level of 5 mV. The sensors exhibit a distance resolution of under 3 nm when the sensed object is in close proximity to the chip surface.
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
Parameters used:
Passivation layer thickness = 1 um
Dielectric constant = 6
CN1=20 fF, CN2=18 fF
Noise level = 5 mV
0.5
20 x 20 sensor
30 x 30 sensor
40 x 40 sensor
1 1.5
2 2.5
3 3.5
Distance from the chip surface (um)
4 4.5
5
Figure 4. Sensor distance resolution as a function of cell proximity
C.
Sensor Response to Living Cells
The sensor chip in a 40 pin DIP ceramic package was encapsulated using a biocompatible material in order to insulate the bonding wires and to isolate the cells from toxic materials in the chip package. A well was formed on top of the chip surface for containing the cells in growth medium.
Fig. 2 shows a photograph of the final assembly. The cell culture medium is itself an ionic solution and forms a conducting layer above the surface. The sensor chip was first calibrated by adding the medium alone without cells and measuring the capacitive coupling between the solution and electrodes. The well was then loaded with bovine aortic smooth muscle cells (BAOSMC) and the sensor outputs were monitored over a period of 24 hours. In between measurements the fixture was maintained in an incubator at
37°C, 5% CO
2
. The fixture was loaded with a very concentrated solution of cells, so all sensors in the test array were exposed to similar conditions. Coupling of cells to every sensor was confirmed through visual observation.
The sensed capacitances were calibrated as discussed in section III B . Fig. 5 shows a plot of the average voltage differences for the three sensors, with all values aligned according to the zero sensed capacitance reference. Error bars indicate the standard deviation in response between all sensors of the same size. The voltage differences for all three sensors decreased with time, tracking the adhesion process as expected and indicating an increase in capacitive coupling between the cells and the on-chip electrodes after they were allowed to settle on the chip surface over a period of time. The sensor output voltages changed by an average of 125 mV, 150 mV and 175 mV for the 20x20, 30x30 and
40x40 sensors respectively, over the 24 hour period. Based
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upon these measurements the calibrated cell capacitances varied from sub-fF to around 10-20 fF, with different sensing ranges for the three sensors as shown in Fig. 5.
1500
1400
1300
1200
1100
Sensor Voltages reference voltage difference
20x20 growth medium
30x30 growth medium
20x20 cells
30x30 cells
40x40 growth medium
25
Calibrated Capacitance
20
15
10
40x40 cells
40x40 growth medium
1000
40x40 cells
30x30 cells
5
900 20x20 cells
30x30 growth medium
20x20 growth medium
800
0 5 10 15 20 25
0
0 5 10 15 20 25
Time (hrs) Time (hrs)
Figure 5. Sensor response to living cells and calibrated cell capacitances
A second experiment with BAOSMC cells monitored the sensor response to changes in cell viability. For this the above test procedure was repeated but this time with
BAOSMC cells stained with neutral red in a colorless growth medium. The sensors were monitored over a period of 48 hours. We assessed viability independently through visual inspection of the stained cells. Living healthy cells have the characteristic property of taking up and retaining neutral red stain whereas non-viable cells do not retain the stain [12]. Fig. 6 shows the sensor response over the 48 hour period. Over the first day the cells were able to retain the stain and the sensors showed an increase in capacitive coupling between cells and sensor electrodes. On the second day, however, it was observed that the cells no longer retained the stain and had released the dye into the growth medium, an indication of non-viability. Accordingly the sensors showed a decrement in the measured capacitance values.
Sensor Voltages Calibrated Capacitance
1500 20 reference voltage difference
1400
20x20 growth medium
30x30 growth medium
18
16 40x40 cells
1300
20x20 cells
30x30 cells
14
12
10
40x40 growth medium
1200
40x40 growth medium 8
1100
30x30 cells
6
20x20 cells
4
1000
40x40 cells
900
0 10 20 30
Time (hrs)
40 50
2
0
0
30x30 growth medium
20x20 growth medium
10 20 30
Time (hrs)
40
Figure 6. Sensor response to variations in cell viability
50
V.
C ONCLUSIONS
A CMOS capacitance sensor has been designed to measure cell-substrate capacitance, an indicator of cell health and morphology. Sensors with different electrode areas have been fabricated. The sensor chips have been tested on the bench using a micropositioned electrode and in vitro with cells placed on the chip surface and responses acquired over a period of 24 - 48 hours. Bench testing results show that the sensor achieves a distance resolution of
3 nm and capacitance resolution of 135 aF. In vitro test results show that the sensors are able to sense cell capacitance variations ranging from sub-fF values to tens of fF, with different sensing ranges for the three sensors. The sensors are effective in monitoring cell viability, a useful feature for a wide variety of cell monitoring applications including biocompatibility characterization, biochemical detection and medical diagnosis.
A CKNOWLEDGMENT
We thank the MOSIS service for providing chip fabrication; these chips will be used to teach an undergraduate course in mixed signal VLSI design. We thank Nicole M. Nelson for her valuable assistance with cell culture and Joel H. Van Sickel for his support during bench testing. This research was supported by the National
Science Foundation through Awards 0225489 & 0238061 and by the Laboratory for Physical Sciences.
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