Ciro Santilli @cirosantilli 34

Most of these are going to be Whole-genome sequencing of some model organism:

github.com/CovertLab/WholeCellEcoliRelease is a whole cell simulation model created by Covert Lab and other collaborators.

The project is written in Python, hurray! But according to te README, it seems to be the use a code drop model with on-request access to master, very meh, asked rationale on GitHub discussion, and they confirmed as expected that it is to:Oh well.

The project is a followup to the earlier M. genitalium whole cell model by Covert lab which modelled Mycoplasma genitalium. E. Coli has 8x more genes (500 vs 4k), but it the undisputed bacterial model organism and as such has been studied much more thoroughly. It also reproduces faster than Mycoplasma (20 minutes vs a few hours), which is a huge advantages for validation/exploratory experiments.

The project has a partial dependency on the proprietary optimization software CPLEX which is freeware, for students, not sure what it is used for exactly, from the comment in the requirements.txt the dependency is only partial.

This project makes Ciro Santilli think of the E. Coli as an optimization problem. Given such external nutrient/temperature condition, which DNA sequence makes the cell grow the fastest? Balancing metabolites feels like designing a Factorio speedrun.

There is one major thing missing thing in the current model: promoters/transcription factor interactions are not modelled due to lack/low quality of experimental data: github.com/CovertLab/WholeCellEcoliRelease/issues/21. They just have a magic direct "transcription factor to gene" relationship, encoded at reconstruction/ecoli/flat/foldChanges.tsv in terms of type "if this is present, such protein is expressed 10x more". Transcription units are not implemented at all it appears.

Everything in this section refers to version 7e4cc9e57de76752df0f4e32eca95fb653ea64e4, the code drop from November 2020, and was tested on Ubuntu 21.04 with a docker install of docker.pkg.github.com/covertlab/wholecellecolirelease/wcm-full with image id 502c3e604265, unless otherwise noted.

See also: github.com/cirosantilli/awesome-whole-cell-simulation

As of 2019, the silicon industry is ending, and molecular biology technology is one of the most promising and growing field of engineering.

Such advances could one day lead to both biological super-AGI and immortality.

Ciro Santilli is especially excited about DNA-related technologies, because DNA is the centerpiece of biology, and it is programmable.

First, during the 2000's, the cost of DNA sequencing fell to about 1000 USD per genome in the end of the 2010's: Figure 2. "Cost per genome vs Moore's law from 2000 to 2019", largely due to "Illumina's" technology.

The medical consequences of this revolution are still trickling down towards medical applications of 2019, inevitably, but somewhat slowly due to tight privacy control of medical records.

Ciro Santilli predicts that when the 100 dollar mark is reached, every person of the First world will have their genome sequenced, and then medical applications will be closer at hand than ever.

But even 100 dollars is not enough. Sequencing power is like computing power: humankind can never have enough. Sequencing is not a one per person thing. For example, as of 2019 tumors are already being sequenced to help understand and treat them, and scientists/doctors will sequence as many tumor cells as budget allows.

Then, in the 2010's, CRISPR/Cas9 gene editing started opening up the way to actually modifying the genome that we could now see through sequencing.

What's next?

Ciro believes that the next step in the revolution could be could be: de novo DNA synthesis.

This technology could be the key to the one of the ultimate dream of biologists: cheap programmable biology with push-button organism bootstrap!

Just imagine this: at the comfort of your own garage, you take some model organism of interest, maybe start humble with Escherichia coli. Then you modify its DNA to your liking, and upload it to a 3D printer sized machine on your workbench, which automatically synthesizes the DNA, and injects into a bootstrapped cell.

You then make experiments to check if the modified cell achieves your desired new properties, e.g. production of some protein, and if not reiterate, just like a software engineer.

Of course, even if we were able to do the bootstrap, the debugging process then becomes key, as visibility is the key limitation of biology, maybe we need other cheap technologies to come in at that point.

This a place point we see the beauty of evolution the brightest: evolution does not require observability. But it also implies that if your changes to the organism make it less fit, then your mutation will also likely be lost. This has to be one of the considerations done when designing your organism.

Other cool topic include:

It's weird, cells feel a lot like embedded systems: small, complex, hard to observe, and profound.

Ciro is sad that by the time he dies, humanity won't have understood the human brain, maybe not even a measly Escherichia coli... Heck, even key molecular biology events are not yet fully understood, see e.g. transcription regulation.

One of the most exciting aspects of molecular biology technologies is their relatively low entry cost, compared for example to other areas such as fusion energy and quantum computing.

One of the simplest known seems to be: en.wikipedia.org/wiki/Trichoplax

www.u-tokyo.ac.jp/focus/en/articles/a_00220.html "The simplest multicellular organism unveiled" from 2013 mentions Tetrabaena socialis.

Then of course: Caenorhabditis elegans is a relatively simple and widely studied model organism.