Unnoticed evolution of humans

1) Suppose that the microbial community living inside us have a sufficiently long relationship with our own cells such that the microbes have an important role in a large majority of physiological functions, not just digestion.

2) As human societies have evolved, the variety of microbes that live in our environment have undoubtedly changed. Once humans wandered grasslands on bare-foot and ate raw food without even washing them. Now we buy processed food from supermarkets and even walk inside our houses with socks. The result is that the community of microbes that interact with and enter/exit our bodies has changed.

Combining (1) and (2) above leads to the possibility that the human physiology has indeed changed of the past several centuries, even though the change the human phenotype "appears" unchanged. The extent of evolution depends on the extent to which the microbial communities influence human physiology. If there are long-distance signaling molecules that are released by microbes which enter the blood and if the microbes are capable of receiving our signals, then...

Analogy for Protein Bursts

Consider this scenario:

Imagine a store that is open for a certain time interval during the day. In that time interval, several customers rush in to the store. Each customer buys several items. If someone would record the number of items sold as a function of time, he/she would probably observe bursts (one burst = items bought by one person). The time duration for which the store is open will correspond to the number of bursts. In other words, time duration maps to frequency of bursts.

Now, consider this transcription model:

Consider this mechanistic/intuitive model explaining how proteins are produced in bursts and how the frequency of bursts are controlled by the transcription factor:

1. transcription factor binds to promoter regions and opens the region for access by the polymerase

2. the region remains "open" for some time

3. during this time interval, the polymerase may initiate transcription multiple times

4. for each mRNA that the polymerase transcribes, multiple proteins are produced

So, in summary, the transcription factor "opens" the promoter region for the polymerase. Lets assume that upregulating the transcription factor affects the time duration of the "open" promoter. The longer the time interval, the more mRNA will be produced. Each mRNA creates a burst of proteins. Therefore, upregulating transcription factor affects frequency of bursts.

Stochasticity can lead to Stability

While we think of "noise" as a destabilizing force, we actually use noise many times to lead a system to the most stable position. Consider the scenario where you want to get all the items out of a hand bag very quickly; you would hold the bag up-side-down and shake, i.e. add noise. If you just tilt the bag up-side-down, there is a risk that some of the items would get stuck in the bag. Shaking ensures that such temporary "traps" (in mathematical terms, local minima) are avoided. In a sense, this is like stochastic optimization. When all the items are on the floor, they will remain there even if you shake the floor, because that is that is the most stable position.

Perhaps stochasticity in natural systems is a means of "shaking", i.e. a means by which natural systems reach the most stable states and avoid local traps. The most stable state remains relatively stable even at the presence of noise. Consider the situation when all the items from the bag are on the floor -- even shaking the floor would not change the situation significantly. Perhaps this is the nature of the "most stable state" -- it has a wide basin and thus can easily tolerate noise.

Centralized synthetic biology for the community

Vision:

Build a "fun" framework that would attract lots of young minds to ask interesting questions, engineer biological cells to answer those questions, and easily share their results and explanations with each other.

Problem:

1. providing the education to the masses... but I have some hope that young people are quite good are educating themselves, given the motivation

2. Resource

3. Safety

Possible solution:

One or two well maintained centralized robots with a fun interface for entering experiments and storing/visualizing the results. This is very much possible, except that it is expensive. But if the benefit is large enough, it is possible that government and/or companies might solve that issue.

But if such a programmable robot existed as a resource, I can imagine numerous researchers wanting to try new experiments and test new hypotheses. Since the data is centralized, there is a built-in benefit of data-integration, i.e. finding relationships between multiple experiments and drawing conclusions based on large number of experiments. It would be like a Facebook for biological experiments: everyone wants to dump their favorite hypothesis on it.

Exercise as a general solution to living systems

I heard the statement a couple of times that places in this world with more cleanliness tend to have more auto-immune illnesses such as allergies. One can imagine that the immune system also needs to "exercise" from time to time, just like the muscles in our body or the brain.

What if "exercise" is a more general theme? Perhaps every pathway in a living system needs some form of exercise (but not too much, of course). What if the error-checking mechanisms and all the other anti-cancer mechanisms in our body also need exercise... perhaps we can cure cancer by exercising anti-cancer pathways. Exercise against cancer would be very tricky. It would require producing small controllable (or self-limiting) tumors in our body from time to time. By doing so, the hypothesis is that the body's anti-cancer pathways would remain alert (well exercised). This might make the body better prepared against the real cancer or tumor.

The same theme of exercise can perhaps be applied to achieve other goals, e.g. directed evolution of microbes.

Possible functions to evolve using reaction networks

How would simulated evolution resolve the following challenges:

1) Measure the variance (noise) of a signal
2) Measure the frequency of a signal -- can be related to (1)
3) Reverse of (1), i.e. increase noise based on deterministic signal (without affecting mean)
4) Reverse of (2), i.e. increase frequency based on amplitude of an input signal
5) Control the width of a bimodal distribution based on a deterministic signal
6) Adapt to an external pattern of events (i.e. learn cause-delay-effect relationships) purely through the reaction network -- this would probably be a combination of signal processing + memory

Design by homologous recombination

Engineers have frequently used random mutations as a means of optimizing a protein or genetically engineered network. However, I don't think this is an effective optimization or design process. Planned mutations, such as the one used by the immune system, rely on homologous recombination rather than random mutations. Using recombination, we can plan the mutation events, therefore perform a much more predictable optimization. The optimization process can even be simulated computationally.