Biological Large Scale Integration

In the first part of the 20th century, engineers faced a problem commonly called the “Tyranny of Numbers”: there is a practical limit to the complexity of macroscopically assembled systems. Using discrete components such as vacuum tubes, complex circuits quickly became very expensive to build and operate. The ENIAC I, created at the University of Pennsylvania in 1946, consisted of 19,000 vacuum tubes, weighed thirty tons, and used 200 kilowatts of power. The transistor was invented at Bell Laboratories in 1947 and went on to replace the bulky vacuum tubes in circuits, but connectivity remained a problem. Although engineers could in principle design increasingly complex circuits consisting of hundreds of thousands of transistors, each component within the circuit had to be hand-soldered: an expensive, labor-intensive process. Adding more components to the circuit decreased its reliability as even a single cold solder joint rendered the circuit useless.

In the late 1950s Kilby and Noyce solved the “Tyranny of Numbers” problem for electronics by inventing the integrated circuit. By batch fabricating all of the components on a single semiconductor wafer, Kilby and Noyce created circuits consisting of transistors, capacitors, resistors and their corresponding interconnects in situ, eliminating the need for manual assembly. By the mid-1970s, improved technology led to the development of large scale integration (LSI): complex integrated circuits containing hundreds to thousands of individual components. This technology completely revolutionized the role of automation in computation, and automated computers became so powerful and inexpensive that people realized their applications could reach far beyond simple scientific calculations. As a consequence, today computation is a ubiquitous part of our lives and is used as a tool not just for science, but also medicine, communication, entertainment and commerce. In addition to these practical effects, another important consequence of the automation of computation is the development of formal approaches to algorithms, i.e. computer science.

A natural question to ask is whether it is possible to automate biology to a similar extent, and if so, would the consequences be as dramatic? The current industrial approach to addressing biological integration has come in the form of enormous robotic fluidic workstations that take up entire laboratories and require considerable expense, space and labor, reminiscent of the macroscopic approach to circuits consisting of massive vacuum-tube based arrays in the early twentieth century. This automation has been highly productive and led to whole genome sequencing and analysis – a new revolution in biology. My group has developed microfluidic technologies that may allow the automation of biology to proceed to a scale comparable to modern integrated circuits. Microfluidics, which is essentially miniaturized plumbing, offers the possibility of solving outstanding system integration issues for biology and chemistry. We recently developed the first microfluidic large scale integration, in which we have shown how to fabricate chips with thousands of mechanical valves (1,2) These chips have proven to have value for high throughput measurements of single cell biochemistry (3), single cell genetic analysis (4), highly parallel genetic analysis (5), and protein crystallization screening (6). Besides the expected economies of scale that accompany the miniaturization and parallelization inherent in these devices, there have also been unexpected discoveries about how the unique physics of fluids in small dimensions can be used to achieve performance that is impossible with benchtop laboratory devices (7,8).

This technology is finding applications that address a number of exciting scientific and medical problems. We collaborate broadly to explore the use of microfluidic technology, and some areas of interest in which we are pursuing pilot projects include:

Single Molecule Biophysics

Single molecule techniques allow one to analyze and deconstruct complex macromolecular behavior by studying molecules one at a time – thus allowing their classification into functional subpopulations according to their trajectories. They also allow measurement of properties that are difficult to analyze with conventional techniques, such as force and topology. My group developed a new technique of force spectroscopy that has allowed us to make some of the most sensitive time-resolved force measurements ever performed in biophysical systems, with 6 femtoNewton sensitivity and millisecond time resolution. We used this method to investigate problems in colloidal dynamics (11) and polymer physics through the manipulation of single DNA molecules (12). We also used these manipulation abilities to tie single DNA molecules into well-defined knots, and have thereby been able to directly study the effects of topology (13). We recently published the first ever single molecule DNA sequencing results (14). This proof of principle experiment may pave the way towards revolutionary new DNA sequencing technology that will make sequencing of an individual's personal genome economically feasible, thus allowing massive sequencing of human diversity. It may also open the door to a new series of single molecule measurements that will allow us to investigate with single base resolution the mechanism of various molecular machines that interact with DNA, such as DNA polymerase. Finally, we have developed an apertureless near field microscope capable of imaging single molecules with better than 10 nanometer resolution; this tool should have many applications in both the life sciences and nanotechnology.

Gallery (Coming soon)

References:

1. M. Unger, H.P. Chou, T. Thorsen, A. Scherer and S. Quake, “Monolithic Microfabricated Valves and Pumps by Multilayer Soft Lithography”, Science 288 , 113 (2000).
2. J.W. Hong and S.R. Quake, “Integrated Nanoliter Systems”, Nature Biotechnology 21: 1179-83 (2003).
3. T. Thorsen, S.J. Maerkl, and S.R. Quake, "Microfluidic Large Scale Integration", Science 298: 580-584 (2002).
4. J.W. Hong, V. Studer, G. Hang, W.F. Anderson, and S.R. Quake, “A nanoliter-scale nucleic acid processor with parallel architecture”, Nature Biotech. 22: 435-439 (2004).
5. J. Liu, C. Hansen, and S.R. Quake, “Solving the "world-to-chip" interface problem with a microfluidic matrix”, Anal. Chem. 75: 4718-4723 (2003).
6. C.L. Hansen, E. Skordalakes, J.M. Berger, and S.R. Quake, "A Robust and Scalable Microfluidic Metering Method that Allows Protein Crystal Growth by Free Interface Diffusion", Proc. Nat'l Acad. Sci. 99: 16531-6 (2002).
7. C. Hansen and S.R. Quake, “Microfluidics in Structural Biology: Smaller, Faster… Better”, Current Opinion in Structural Biology 13: 538-544 (2003).
8. A. Groisman, M. Enzelberger, and S.R. Quake, “Microfluidic Logic and Control Devices”, Science , 300: 955-8 (2003).
9. J.P. Rolland, R.M. Van Dam, D.A. Schorzman, S.R. Quake, J.M. DeSimone, “Solvent-resistant photocurable "liquid teflon" for microfluidic device fabrication” J.A.C.S. 126: 2322-2323 (2004).
10. C.L. Hansen, M.O.A. Sommer, and S.R. Quake, Proc. Nat'l Acad. Sci., in press.
11. J.C. Meiners and S.R. Quake, “A Direct Measurement of the Hydrodynamic Interaction Between Two Particles”, Phys. Rev. Lett . 82 , 2211-4 (1999).
12. J.C. Meiners and S.R. Quake, “FemtoNewton Force Spectroscopy of Single Extended DNA Molecules”, Physical Review Letters 84 , 5014-7 (2000).
13. X.Y.R. Bao, H.J. Lee and S.R. Quake, “Behavior of complex knots in single DNA molecules”, Phys. Rev. Lett. 91 (26): pp. 265506-1 – 265506-4 (2003).
14. I. Braslavsky, B. Hebert, and S.R. Quake, “Sequence Information Can Be Obtained From Single DNA Molecules”, Proc. Nat'l Acad. Sci. 100: 3960-4 (2003).