By Aaron Kimball
The panel submission deck: http://www.slideshare.net/WhitneyJencks/zymergen-sxsw-2016-submission
Additional Background: http://www.pbs.org/wgbh/nova/next/evolution/crispr-gene-drives/
The problem: DNA is incredibly complex and it presents a data challenge. It is not possible to test every combination in which the base pairs arrange themselves.
While the cost of sequencing has fallen, it is not simple to figure out what any particular sequence of symbols does. Interpreting DNA is hard – the conventional method sees scientists try out different hypotheses, experimenting in wet labs, with potential combinations. The downside – of 10,000 attempts we might see a minor result in one. This makes this whole process hard, expensive, and time consuming.
Zymergen has built out a robotic process to automate this, allowing for many experiments to be run in parallel.
The problem is the amount, and kind, of data being generated.
Fun fact: 93% of all chemicals in use comes from petroleum. Only 6% come from industrial fermentation. However as oil runs out, microbe-based chemical production processes becomes super important. But that needs us to be able to manipulate genes in microbes, designing better microbes.
A sequence looks like this – promoter + gene + terminator. The promoter defines how much the gene expresses itself. For example, how blonde will your hair be – platinum or just a dirty yellow.
The language allows scientists to very quickly create experiments that can test multiple permutations
The rest of the process allows for automation, speed and quick analysis on the data using a sophisticated software stack.
There are inbuilt decision trees based off previous non-machine test results.
The expected outcome is better chemicals that can lead to safer pesticides, plastics that break down, even better medicines.