Learning to Program DNA
Drew Endy (MIT)
Colloquium
Tuesday, April 22, 2008, 3:30 pm
EEB-105
Abstract
Ongoing improvements in DNA sequencing and DNA synthesis technologies are making genetic material (physical DNA molecules) and genetic information (DNA sequence data) interconvertible. For example, researchers have demonstrated the construction of DNA molecules up to 7,700,000 base pairs, a length that is long enough to encode all known viruses, most important bacteria, and almost the entire genome of S. cerevisiae (baker's yeast). As a second example, a thousand high school and college students now meet annually via the International Genetically Engineered Machines Competition, typically presenting engineered biological systems comprised of dozens of unique genetically encoded functions; in support of their projects hundreds of thousands of standard biological parts (e.g., BioBrick parts) are freely shared across over 30 countries. What past lessons from other fields of engineering are now informing the engineering of biology (e.g., could we develop an electronic design automation framework that supports VLSI genetic engineering?)? What new engineering challenges arise within the substrate of biology? What about dealing with the consequences of success?
Bio:
Drew Endy has been helping to start the Department of Biological Engineering at MIT. He is also a co-founder of Codon Devices, Inc. and president of the BioBricks Foundation, a not-for-profit organization promoting open access to biological technologies. He started and leads the organization of the International Meeting on Synthetic Biology conference series, and advises various government and private organizations on matters related to the ongoing development of biological technologies. At MIT, Dr. Endy´s lab research has resulted in (a) the first example of refactoring the genome of a natural biological system, (b) an abstraction hierarchy for engineering genetic devices, including a common signal carrier for transcription-based devices, and (c) experiments suggesting that the behavior of natural molecular biological systems is determinable, and perhaps not so stochastic. His future research interests are implementing reliable behavior in engineered biological devices, and developing a practical framework for designing reproducing machines whose designs are readily understandable by humans. More via Drew Endy