The dummy's guide to engineering genes

Note: Yesterday we began Quinn Norton’s five-part series on Drew Endy and synthetic biology with “Everything you needed to know about human-created life forms but were afraid to ask.”

lego-dna.jpg Photo courtesy of Mike & Amanda Knowles, via flickr.

Dr. Drew Endy’s approach to the next generation of bio technology depends on engineers, programmers, hackers, social theorists, lawyers and so forth, to inform biology. He believes we can make genetic engineering, like computers, part of every facet of our lives, changing the way humans do their business.

He seeks to put synthetic biology into the hands of the interested, not merely the professional. The potential is to widen the range of goals, to extend this emerging tool to many disciplines.

The key, says Endy, is what computer scientists call abstraction.

Fundamental to what created modern software was that idea that no one should have to type in that monotonous stuff twice. Once something was there, it should just be reused, not re-created. More important, once it was done the programmer didn’t have to know how it worked to do it again. The common wisdom became that no one should have to know how a computer worked to make it do entirely new things.

Also: Dr Endy explains Abstraction (mp3, 4.9mg) and Standards (mp3, 3.1mg) for synthetic biology.

The language of genetic engineering is out of reach for most people, but the idea of making something do what they want is not. Along with famed MIT computer engineer Tom Knight, Endy is trying to bury the DNA and its nucleotides down the same deep hole that swallowed the 1s and 0s we users never have to thinks about. To do this, they are creating standards and a vocabulary defining a DNA language for programming organisms. Assembling basic gene codes into patterns that can be strung together and reused allows people with far less sophistication than modern genetic engineers to create cells that those modern genetic engineers would never have dreamed up. This puts the power of the Ph.Ds into the hands of the rest of us, and what was a multi-million dollar research task can become a high school science fair project. This path echos the success of computers from their enormous and expensive infant stage to their penny-cheap microscopic adulthood.

Tom Knight is one of the greybeards who watched much of that process, and came to understand how the history of computers and the internet worked. Knight recognized early that to do this in biology, he’d need a reliable way to categorize bits of DNA by what they did rather than their sequence, making the syntax of the programming language. In 2001, Knight invented the first standard for creating a genetic programming language and called it BioBricks. To build with BioBrick parts, one had to learn the basics of how they hooked together and what they did. From there it was a process of building up DNA like Lego.

No one has ever done anything like this. “It might not work,” Endy freely admits. But Endy sees value even in the failure of abstraction. “The ‘worst case scenario’ for synthetic biology is that we won’t be able to build anything useful, but our failures will highlight the most relevant unknowns in biology, (what) we should figure out next.” He adds that we are already beyond that scenario, but as we go further out, more issues of society intrude on issues of science. The history of GMOs suggests the biologist should try to keep the public informed of where they might meet the biologist’s work.

Tomorrow: The legal status of genes may ultimately be even more contentious.