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This is an interesting result. Basically cellular biologists debugging cells the same way folks who don't understand how a program works debug it, by chopping parts off until it fails and then adding back bits one by one until it works again :-).

At some point, not today and perhaps not in the next 20 years, humans will understand exactly how cells and DNA "work" from first principles to final behavior. At that point, humans will either cease to age and never suffer from disease (Venter would have liked that), or humanity will be wiped out by a malicious organism that is designed by a deranged practitioner.

Yet another technology produced Lady or the Tiger challenge.




There's a fun Smullyan book with that title.


There's also epigenetics to consider, like methylation and acetylation, which adds a whole extra layer of complexity. :/


I think it's really difficult not to underestimate the complexity, although software engineers have a unique perspective.

Have you ever maintained an application of vintage? You have some idea of how complex an application can get after a decade or two... Now, imagine an application which is X years old, where X is our age going back to the first ancestors...


We already understand exactly how cells and DNA "work", the problem is methabolic networks are very large and hard to simulate with sufficient certainty.


That's rather the point. Those metabolic networks are not meaningfully separable from "how cells and DNA work".


> We already understand exactly how cells and DNA "work"

I must have read your comment differently than you intended, since understanding exactly how cells and DNA work implies that the first cell v1.0 would have divided as intended and that it would not have taken 5 years of painstaking research for v2.0.

From the article, "Of the seven genes added to this organism for normal cell division, scientists know what only two of them do."


we understand the translation of DNA bases to amino acids, and we once though that was going to be enough to understand inheritance, but we're still unpicking additional mechanisms that regulate gene expression and post translation modification. There's heaps more turtles down there.


...and they also vary across groups of humans. We are not all the same.

Each of us is a n=1 genetic experiment.


Lol what are you talking about


Knowing how something works is not at all the same thing as knowing enough to make significant improvements. It's just a first step.


True, but knowing how something works enables you to walk the path to learn how to make improvements. It allows you to make reasoned changes vs random changes.


Maybe computer ‘will’, but not humans. We have had thousands of years to try to come up with a definition of life and free will, and we haven’t even managed that :)

https://www.quantamagazine.org/what-is-life-its-vast-diversi...


It is important not to mix philosophical questions with pragmatic ones. We don't have a solid definition of what "life" is, but as this group demonstrated creating something that is unequivocally "alive" by our extant definitions.

Much like the COVID-19 vaccines are the first widely distributed "product" of our understanding of messenger RNA, I would expect the first widely available products that come from our understanding of building and operating single cell organisms to be things like water purification, drug production, Etc.

For example, an organism that secretes vanilla extract would be a multi-billion dollar product. And "all"[1] it would have to do is mimic what the vanilla Orchid does when growing seeds.

[1] This is a deep and wide void of knowledge about how it does what it does, not trying to gloss that over, just making the case for single cell organisms as useful products.


Vanillin synthesis is mature technology.

E.g., France was said to export 12x as much "natural vanilla extract" as it imports, yet produce none at all.

Insulin production using microorganisms is likewise mature, although prices are kept artificially high.

Yeast produce rather a great deal of economically relevant ethanol.




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