BioMEMS Case Study: Microdevices for PCR Joel Voldman* Massachusetts Institute of Technology

BioMEMS Case Study: Microdevices for

PCR

Joel Voldman*

Massachusetts Institute of Technology

*with thanks to SDS

Cite as: Joel Voldman, course materials for 6.777J / 2.372J Design and Fabrication of Microelectromechanical Devices, Spring 2007. MIT

OpenCourseWare (http://ocw.mit.edu/), Massachusetts Institute of Technology. Downloaded on [DD Month YYYY].

JV: 2.372J/6.777J Spring 2007, Lecture 25 - 1

Outline

> What is hard about BioMEMS

> BioMEMS success stories

> DNA amplification and PCR

> Two designs

• A static PCR thermocycler

• A flow-thru design

• Comparison

> Design evolution of static approach

> Conclusions




BioMEMS

> Applications of microsystems to bioscience

• Neural probes

• Capillary electrophoresis

• Drug delivery

• Cellular engineering

• Tissue engineering

Univ. Michigan

Courtesy of Kensall D. Wise.

Used with permission.

Berkeley

Courtesy of Richard A. Mathies.


Image removed due to copyright restrictions.






What is hard about BioMEMS

> The biological system is poorly defined

• We fundamentally understand physics

• We DON’T fundamentally understand biology

• Thus, only part of system can be truly predictively designed

> “Intrinsic” biological limitations can dictate system performance

• Protein-protein interaction kinetics

• Polymerase error rates

> The materials (and thus processes) are often NOT silicon (and thus harder)

• We must move away from the most established fabrication technologies




BioMEMS success stories

> Depending on the definition, there are very few

> Commercial successes

• Blood pressure sensors

» Low-cost “widget” allows devices to be disposable

• Affymetrix DNA microarrays

» Vastly decreases time and cost for analyzing nucleic acids

» But these are not really bioMEMS


PCB-mountable pressure sensor for medical applications.





> Depending on the definition, there are very few

> Commercial successes

• Blood pressure sensors

» Low-cost “widget” allows devices to be disposable

• Affymetrix DNA microarrays

» Vastly decreases time and cost for analyzing nucleic acids

» But these are not really bioMEMS

Courtesy of Affymetrix,

Inc. Used with permission.

Courtesy of Affymetrix, Inc. Used with permission.

Courtesy of Affymetrix, Inc. Used with permission.





> In the commercial sector, there has been lots of hype

• Success is uncertain

> Caliper/Aclara

• Lab-on-a-chip

> I-stat

• Portable blood analyzer

• Uses ion-selective electrodes, conductivity, etc. to measure salts, glucose, etc.

• Introduced ~1997

• Purchased by Abbott


Lab-on-a-chip is about the size of a U. S. dime.






> Away from commercial sector and into basic science, more successes arise

> Success can be defined as having impact on the target audience

> Ken Wise’s neural probes

• CMOS + bulk micromachining

Univ. Michigan

Courtesy of Kensall D. Wise.


• Puts op-amp right near neural recording sites Î amplifies and buffers weak (~ μ V) signals

• These are being used by neuroscientists in actual experiments




Outline




> Two designs



• Comparison


> Conclusions




DNA (deoxyribonucleic acid)

> DNA contains the genetic information (genotype) that determines phenotype (i.e., you)

> It consists of a two antiparallel helical strands

• Read 5’ to 3’

• A sugar-phosphate backbone

• Specific bases (A, C, G, T) that contain genetic code

> This code determines the sequence of amino acids in proteins

(B)

-O

O

3'

P

O

3'

4'

2'

1'

O

CH

3

O

5

6

N

1

T

4

2

3 N

O

H

H

H

N

N 1

6

2

A

5

3

N

4

N

7

H

8

9

N

-O

O

-O

-O

O

O

P

P

O

O

O

O

3' 2'

4'

1'

O

3' 2'

4'

O

1'

N

8

9

N

7

N

8

9

N

7

O

H

4

5

3

G

6

2

N

1

N

N

H

N

H

5

4

H

N

3

A

6

2

1 N

P

O

O

N

6

N

5 4

C

1 2

3

O

N

H

H

H

CH

2

3' 2'

4'

1'

O

H

H

H

H

O

N

N

1

6

G

2 3

5

4

N

H

N

N 3

4

2

C

5

6

1

N

O

O

N

9

N

N

O

N 3

4

2

T

5

1

6

N

O

1'

2'

O

1'

2'

4'

3'

O

O

O

4'

3'

O

1'

2'

O

4'

3'

P

O

P

P

5'

1'

5'

O

2'

4'

3'

O

CH

2

O

P

-O

O

O

-O

O

-O

O

-O

5' 3'

Lodish, MCB

Image by MIT OpenCourseWare.




DNA Amplification

> The bases pair specifically

• A with T

• C with G

> Specific enzymes (DNA polymerases) can add complementary nucleotides to an existing template + primer

• This is done in vivo in DNA replication

> Was capitalized in vitro in polymerase chain reaction (PCR)

• Invented in 1985, Nobel Prize in

1993

Incoming deoxyribonucleoside triphosphate

5'

3'

Template strand

3'

Gap in helix

Repaired

DNA helix


Alberts, MBC




Polymerase chain reaction (PCR)

> Specifically amplify DNA starting from 1 doublestranded copy

5'

3'

5'

3'

5'

3'

3'

3'

{

{

Region to be amplified

Primer 1

5'

5'

}

Add excess primers 1 and 2, dNTPs, and Taq polymerase

Heat to 95 o

Cool to 60 o

C to melt strands

C to anneal primers

3'

5'

Primer 2

Primers extended by Taq polymerase at 72 o

C

3'

Heat to 95 o

Cool to 60 o

5'

C to melt strands

C to anneal primers

5'

3'


C

5'

Heat to 95 o

3'

Cool to 60 o

C to melt strands

C to anneal primers


Lodish, MCB




Polymerase chain reaction (PCR)

{

Cool to 60 o

C to anneal primers


C

Heat to 95

Cool to 60 o

C to melt strands o C to anneal primers

And so on

{

Primers extended by polymerase at 72 o

C

Taq


Lodish, MCB




PCR

> Key technological improvement was use of polymerase that could withstand high temperatures

• Isolated from Thermus aquaticus

( Taq )

• Don’t have to add new polymerase at each step

> The device is a simple thermocycler

> Allows amplification and detection of small quantities of DNA


PCR machine by MJ Research.




PCR cycles

> Taq extension rate ~60 nt/sec

> PCR products are typically a few hundred bases

• Need ~5 sec for extension

• Plus time for diffusion

> Typical protocols

• ~25-35 cycles at 1-3 min/cycle

• ~30 cycles Æ 75 minutes

100

Step 1: Denature template

90

80

Step 3:

Primer extension

70

60

50

40

30

0

Step 2:

Anneal primer

One " Cycle"

2 4 6 8

Minutes

10 12 14 16





PCR

> Cycle time is dominated by ramp times due to thermal inertia

• Usually much longer than kinetically needed

> Transient and steady-state temperature uniformity limits cycle time & specificity

Property Spec

Temp range

Set-point accuracy

5-105 ºC

± 0.25 ºC

Temperature uniformity ± 0.4 ºC within 30 sec

Heating/cooling rate ~ 3 ºC/sec

Sample volume 50 μ l

Number of samples 96

Power required 850 W

BioRad DNA Engine




Outline




> Two designs



• Comparison


> Conclusions




Two approaches to miniaturization

> Decrease size of chamber

• Vary temperature in time

> Use a flow-thru approach

• Vary temperature in space (and therefore time)

> In both cases, the device is a thermal MEMS device and the key is to reduce thermal response times




Batch PCR

> First reported by Northrup et al.

in 1993

• Essentially a miniaturized thermal cycler

Cover glass

Polyethylene tubing

0.5 mm

10 mm Silicone rubber

Silicon

Low-stress silicon nitride

Aluminum bond pad

Polysilicon heater


Adapted from Northrup, M. A., M. T. Ching, R. M. White, and R. T. Watson. "DNA Amplification with a

Microfabricated Reaction Chamber." In Transducers '93: the 7th International Conference on Solid-State

Sensors and Actuators: digest of technical papers: June 7-10, 1993, PACIFICO, Yokohama, Japan . Japan:

Hiroyuki Fujita, 1993, p. 924-926. ISBN: 9784990024727.

Northrup et al., Transducers ’93, p924




> Daniel et al.

improved thermal isolation

Batch PCR

Courtesy of Elsevier, Inc., ___________________ . Used with permission.

Figure 5 on p. 84 in: Daniel, J. H., S. Iqbal, R.

B. Millington, D.

F. Moore, C.

R. Lowe,

D.

L. Leslie, M.

A. Lee , and M.

J. Pearce. "Silicon Microchambers for DNA Amplification.“

Sensors and Actuators A, Physical 71, nos. 1-2 (November 1998): 81-88.

mesh isolati on chamber beams

Courtesy of Elsevier, Inc., ___________________ . Used with permission.

Figure 3 on p. 83 in: Daniel, J. H., S. Iqbal, R.

B. Millington, D.

F. Moore, C.

R. Lowe,

D.

L. Leslie, M.

A. Lee , and M.

J. Pearce. "Silicon Microchambers for DNA Amplification.“

Sensors and Actuators A, Physical 71, nos. 1-2 (November 1998): 81-88.




Continuous-flow PCR

> Developed by Kopp et al.

in 1998

Buffer in Sample in Product out

Output capillary

60 o

C MM

Input capillaries

77 o C

95 o

C

Annealing

zone

Extension zone

Denaturing zone

Two-layer glass with etched flow channels


Adapted from Figure 1 on p. 1046 in Kopp, M. U., A. J. de Mello, and

A. Manz. "Chemical Amplification: Continuous-flow PCR on a Chip."

Science, New Series 280, no. 5366 (May 15, 1998): 1046-1048.


Adapted from Kopp, M. U., A. J. de Mello, and A. Manz. "Chemical Amplification:

Continuous-flow PCR on a Chip." Science, New Series 280, no. 5366 (May 15,

1998): 1046-1048.




Batch PCR

> Daniel reactor

• SiN mesh structure, undercut with KOH

» Made hydrophobic to keep water in chamber during loading

• Platinum heater resistors heat up beams

• Two temperature sensing resistors

» One on beams for feedback control

» One on membrane to sense “liquid” temp

• Use oil drop on top of liquid to prevent evaporation

Courtesy of Elsevier, Inc., ___________________ .

Used with permission. Figure 3 on p. 83 in: Daniel, J. H.,

S. Iqbal, R. B. Millington, D. F. Moore, C. R. Lowe, D. L. Leslie,

M. A. Lee, and M. J. Pearce. "Silicon Microchambers for DNA

Amplification." Sensors and Actuators A, Physical 71, nos. 1-2 (November 1998): 81-88.




Thermal modeling – batch system

> Three steps

> Model chamber

> Model beams

> Combine the two, with heating at beams substrate chamber substrate beams





> Chamber model y

> Assume rectangular crossx section

> Assume dominant heat loss through beams

Î 2-D heat flow problem

• Neglect conduction along top and bottom

• Temperature does not vary in z

> Interested in dominant time constant

Eigenfunction expansion solution to heat-flow eqn.

=

∑∑

n m

( , , ) = A

1

A cos

⎛

⎝

π

L

⎞

⎠ cos

⎛

⎝ L ⎠ e − α cos

⎜

π

L x

⎟ cos

⎜

π

L y

⎟ e − α

1 t

Lowest mode t

τ f

=

1

α

1

=

2 π

L 2

2 D

=

L 2

2 π m

2

ρ

κ m





> Obtain lumped heat capacity by weighing over mode volume

C f

> Extract thermal resistance from time constant

> Thermal resistance same as zeroth-order model

R f suggests

=

1

κ length ⋅ area

1

4

=

L

κ

2

1

LH

4

=

1

8 κ H

C f

C f

τ f

=

=

=

ρ m

ρ m m

~ m

−

L

L

/

/

2

−

L

L

/

∫ ∫ ∫

2

2 H

2 L

π

2 L

π

H cos

⎛

⎝

π x

L

4 ρ m

π m

2

L 2 H

= R f

C f

⇒ R f cos

⎛

⎝

π y

L

=

1

8 κ H dxdydz

> For L =2 mm, τ= 1.4 s

> H =400 μ m, volume = 2 μ l





> Lumped elements for beams

• Include beam capacitance

> Two circuits to model beams

• Capacitor in center

• Capacitor at edge

> Both circuits contain same energy in capacitor at steady state

• Capacitor at edge is simpler

R b

C b

=

=

1

4

ρ

1 length m

κ

~ m area volume substrate wall beam

Substrate

R b

/ 2 R b

/ 2

Wall

C b

Substrate

R b

Wall

C b

/ 2


Adapted from Figure 22.14 in Senturia, Stephen D. Microsystem Design . Boston, MA: Kluwer

Academic Publishers, 2001, p. 617. ISBN: 9780792372462.





> Lumped circuit model of reactor

> First-order lag between wall and fluid temperature

T f

=

1 +

1

τ f s

T w

τ f

=

2 π

L 2

2 D substrate

R b wall

+

R f fluid

+

> Making L smaller reduces lag

P T w

-

C b

/2 T f

-

C f

Substrate Wall Fluid in chamber


Adapted from Figure 22.15 in Senturia, Stephen D. Microsystem Design . Boston, MA: Kluwer

Academic Publishers, 2001, p. 618. ISBN: 9780792372462.





> Simulink proportional control circuit

> Saturation needed for maximum +/- voltage swing

• Set to 0 to 15 V

Signal 1

Signal builder

-

+ As0 s + As0/K

Op-amp gain K

Saturation u[1]^2/Rh

Joule heat P

Switch

Fluid

1

Rf*Cf.s + 1

Fluid temp

0 Select feedback

Wall

Rb*Rf*Cf.s + Rb

Rb*Rf*Cf*Cb/2.s

2 + (Rb *Cb/2 + (Rf + Rb) *Cf)s + 1

Transfer Fcn


Adapted from Figure 22.16 in Senturia, Stephen D. Microsystem Design . Boston, MA: Kluwer Academic Publishers, 2001, p. 619. ISBN: 9780792372462.




.

Simulation response

> Wall temperature can be controlled very quickly

> Wall to fluid heat transfer limits performance

> Sensing fluid temperature marginally reduces response times

• But creates high-temp regions at chamber wall

100

90

80

70

60

50

40

30

20

0

120

100

80

10 20

T (s)

30 40

Control

Fluid

Wall

60

40

20

0 10 20

T (s)

30 40


Adapted from Figure 22.17 in Senturia, Stephen D. Microsystem Design . Boston,

MA: Kluwer Academic Publishers, 2001, p. 620. ISBN: 9780792372462.




Continuous-flow device

> System partitioning: put heaters off-chip

> Etch channels in glass, bond glass cover

Buffer in Sample in Product out

60 o C

77 o

C

95 o C

Two-layer glass with etched flow channels


Adapted from Figure 1 on p. 1046 in Kopp, M. U., A. J. de Mello, and A. Manz.

"Chemical Amplification: Continuous-flow PCR on a Chip." Science, New Series

280, no. 5366 (May 15, 1998): 1046-1048.




Thermal model of continuous-flow device

> Wall-to-fluid time constant is same as in batch device

>

L

1

=40 μ m,

L

2

=90 μ m

>

D

=1.4x10

-7 m 2 /s

> τ f

= 1.2 ms

> 1000 × faster than batch device!

τ

f

=

2

L

1

π

2

L

2

D

> Entrance length for thermal equilibration

L e

≈

3 v f

τ

f

> Average flow velocity v f

=

Q f area

=

20 mm/s

L

1

L e

≈

60

μ

m

This is much smaller than zone lengths

> Thermal Pe number is ~10 -3

L

2




Continuous-flow device

> What about Taylor dispersion?

> Pressure-driven may cause multiple samples to coalesce

> Hydrodynamic radius of 1 kb

DNA ~ 50 nm

> Dispersivity is dominated by convection

• Samples will spread out a lot, limiting usefulness for multiple samples

D =

6 k

B

T

πη R

Pe =

LU

D

K

=

=

( 40 μ m )( 0 .

02 m

4 .

4 x 10 − 8 cm 2 /

/ s s )

D

⎛

⎝

1 +

Pe 2

210

⎞

⎟⎟ f

⎛

⎜⎜

L

1

L

2

⎞

⎟⎟

~ 2 x 10 5

K

L

1

L

2

~

~ 0 .

4

8 x 10 8

→

⋅ D f

⎛

⎜⎜

L

L

1

2

⎞

⎟⎟

=

~ 35 cm 2

4

/ s




Thermal lessons

> Wall temperature in most microsystems can be quickly controlled

> Limiting step is wall-to-fluid heat transfer

> Solution is to minimize fluid characteristic length for heat diffusion




Detecting PCR products

> Speeding up amplification is only half the battle…

> DNA is not normally visible

> In conventional PCR, detect products by separating stained DNA using electrophoresis in gel sieving matrix

• This can take 0.5-2 hrs


Loading gel in electrophoresis apparatus.


Photograph of an illuminated gel after electrophoresis.





> Newer techniques allow real-time detection

• “Real-time PCR”

> Integrate illumination/detection optics, thermal cycler, and chemistry

Polymerization Cleavage

R

R Q

5'

3'

5'

Forward primer

Reverse primer

5'

3'

5'

3'

5'

Q

5'

3'

5'

5'

3'

5'

Strand displacement

R

Q


5'

3'

5'

5'

3'

5'

3'

Polymerization completed

R

Q

ABI Taqman assay

5'

3'

5'

3'





Roche LightCycler > Real-time thermocycler

> 1.5 mm-wide capillaries

> τ ~2-3 sec up and down

Images removed due to copyright restrictions.

Schematic of the thermal chamber for the LightCycler(R) 2.0.




Comparison of two microfluidic PCR approaches

Continuous flow

Faster thermal response

No temp overshoot

Static protocol

Taylor dispersion effects, and sample carryover

Optical detection more complicated

Batch

Slower

Depends on control system

Can change protocol easily

Sample carryover only

Simpler optical detection




Materials issues

> Reactor surface must be compatible with PCR reagents

• DNA, nucleoside triphosphates, polymerase, buffers

> Decreasing length scale and increasing SA/V hurts here

• More molecules start to interact with surface

> Bare Si or SiN inhibits PCR

• Probably due to denaturing of polymerase at surface

• Silanizing or depositing/growing SiO

2 helps

• Add carrier protein (e.g., BSA) to “block” surface

> Kopp uses glass, silanization, surfactant, and buffer!

> Northrup use deposited SiO

2 plus BSA




Outline




> Two designs



• Comparison


> Conclusions




Evolution of chamber device

> Initial device introduced in

1993

Cover glass

Polyethylene tubing

10 mm Silicone rubber

Silicon

> 1995-6 0.5 mm

• Two-heater chambers

• Improved surface coating: silanize+BSA+polypro insert

Aluminum bond pad

Polysilicon heater


Adapted from Northrup, M. A., M. T. Ching, R. M. White, and R. T. Watson. "DNA Amplification with a

• Fan for cooling

Hiroyuki Fujita, 1993, p. 924-926. ISBN: 9784990024727.

Low-stress silicon nitride

Microfabricated Reaction Chamber." In Transducers '93: the 7th International Conference on Solid-State

Sensors and Actuators: digest of technical papers: June 7-10, 1993, PACIFICO, Yokohama, Japan . Japan:

• Chamber volume 20 μ l

• 30 sec cycle time

• ~10 ºC/s up, 2.5 ºC/s down

• “Real time”-PCR via coupled electrophoresis



• Cepheid formed





> 1998

> Same two-heater chambers

> Portable application

> Up to 30 ºC/s up, 4 ºC/s down

> 17 sec minimum cycle time

> Usually use 35+ sec






Heater - rapid, precise temperature control > 2001 to present

> Abandoned Silicon Î Move to plastic and NOT microfabricated

> Tubes are disposable thin-wall

(50 μ m) plastic that expands upon introduction

> Tube is flat to decrease thermal response

> ~30 sec cycle time

> Ceramic chamber with thin film heater

> Thermistor temp sensor


Ex cit ati on

Optics blocks - optical analysis, detect and quantify up to four different DNA targets simultaneously

Thin-film wall

Optical excitation window

B

Optical detection window

Dete ctio n

Circuitry - passes optical information to computer for analysis and display





Conclusions

> BioMEMS commerical successes are still not here

> Designing the engineered part is often routine

> Interfacing with biology is where it gets hard

> Sometimes the right solution is to NOT microfab




BioMEMS Case Study: Microdevices for PCR Joel Voldman* Massachusetts Institute of Technology

BioMEMS Case Study: Microdevices for

PCR

Outline

BioMEMS

What is hard about BioMEMS

BioMEMS success stories

BioMEMS success stories

BioMEMS success stories

BioMEMS success stories

Outline

DNA (deoxyribonucleic acid)

DNA Amplification

Polymerase chain reaction (PCR)

Polymerase chain reaction (PCR)

PCR

PCR cycles

PCR

Outline

Two approaches to miniaturization

Batch PCR

Batch PCR

Continuous-flow PCR

Batch PCR

Thermal modeling – batch system

Thermal modeling – batch system

∑∑

Thermal modeling – batch system

∫ ∫ ∫

Thermal modeling – batch system

Thermal modeling – batch system

Thermal modeling – batch system

Simulation response

Continuous-flow device

Thermal model of continuous-flow device

τ

π

≈

τ

=

=

≈

μ

Continuous-flow device

Thermal lessons

Detecting PCR products

Detecting PCR products

Detecting PCR products

Materials issues

Outline

Evolution of chamber device

Evolution of chamber device

Evolution of chamber device

Conclusions

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