Thursday, March 18, 2010

Microbial ecosystem programming

There is a lot of hype about programming single cells by editing their genetic code, which in turn alters the dynamics of their regulatory or metabolic networks. However, using these engineered microbes in the real world is a very skeptical step, simply because we cannot predict exactly what can happen.

An alternative is to not edit the microbes themselves at all. Instead of building networks using enzymes inside the microbe, why not see a cell itself as a complex catalyst. A living cell converts some chemicals into others (environmental conditions apply).

Using microfluidics, it might be possible to completely characterize the "catalytic" profile of hundreds of microbial species, including bacteria, fungi, amoeba, algae, archaea. Then, build a "network" of different species such that the whole system is stable and performs some metabolic process that is of use to us, such as bio-remediation. This "engineered" network should be safer in the real world.

Saturday, March 13, 2010

Reducing stochasticity in biology

Suppose we are diagnosing a set of symptoms of a disease. If there is only one symptom, we will give our conclusion very little weight because that one symptom could be due to random chance. However, if we see multiple symptoms, then it is probably not due to random chance but due to some cause.

This simple rule is sufficient to eliminate stochastic effects in the final decision: make decisions based on multiple observations rather than a single observation.

In a cell, a "decision" can be something like upregulating a gene. If this decision is made by a single transcription factor that detects some sort of environment, then the decision (transcription) will be noisy. In contract, if multiple transcription factors that all respond to the same environment are used, then the transcription process will be a function of the sum of multiple stochastic processes. The sum will always have a lower variance. Unfortunately, multiple regulators means the there are multiple association/dissociation events, which would add more noise. The solution would have to be a bit more clever than this, but the general idea holds.