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Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Biological DOOM: a brief overview of biological computation, published by Metacelsus on April 29, 2023 on LessWrong.
(no, not that kind of biological doom)
DOOM is a classic first-person shooter game released in 1993 by id Software. Because it’s from 1993, it doesn’t require much computing power compared to modern games. Additionally, the code (written in C) is easy to compile to run on a variety of processors.
Over the years, hackers have made DOOM run on things such as an ATM, a touchbar of a MacBook, a Porsche 911, and even a TI-84 calculator powered by potato batteries.
But what about cells?
Requirements for DOOM
The inputs to DOOM are based on button presses, traditionally on a keyboard. 9 keys in total are required (assuming “switch weapon” is implemented as one key that cycles through weapons).
For computation, the original 1993 release required:
4 MB of RAM and 12 MB of hard-drive storage
Intel 386 (bare minimum) or 486 processor.
There is some flexibility regarding the processor, but slower processors will have worse frame-rates. The Intel 386 had 275,000 transistors in its most basic configuration.
DOOM also requires a graphical output. The smallest resolution I’ve seen is 128x32 pixels, and that was cutting it a bit close. We’ll assume we need 4096 black-and-white pixels for the display.
Finally, DOOM has audio. For the purposes of this thought experiment, we can ignore this output. Although the soundtrack is great, it’s not strictly required to play the game.
Approaches to biological computation
So, how could we potentially run DOOM? Biological systems can perform computations in several ways:
Nucleic acid hybridization
These logic gates are based on strand displacement between complementary DNA sequences. A recent paper demonstrated a set of DNA-based logic gates that could add two 6-bit binary numbers.
Pros and cons:
Memory capacity is good (encoded in DNA or RNA)
Switching speed is OK (rate constants vary by design but are typically around 106M−1s−1)
Visual output could be provided by fluorophore/quencher conjugated oligonucleotides, but . . .
Coupling to a macroscopic output display would be far too slow, because it would have to rely on diffusion (taking a few minutes to cover a millimeter-scale distance). So, the game would have to be played using a microscope.
It’s hard to “reset” gates after using them, this requires coupling to some energy source
It’s also hard to integrate DNA-based logic gates into other biological systems, since not many organisms use short pieces of ssDNA. RNA might be used instead.
Transcription and translation
These logic gates use the same tools that cells use to regulate gene expression. For example, the classic lac operon in bacteria implements:
Biologists have exploited similar systems to build logic gates, as well as systems involving the regulation of translation (the production of proteins using mRNAs as templates). A recent paper used Cas9 binding to a sgRNA-like sequence inserted in an mRNA to control its translation. To form a NAND gate, they split Cas9 into two fragments; if both were present, the output protein was not produced.
Pros and cons:
Memory capacity is acceptable (encoded in DNA or RNA)
There will be challenges with implementing the number of logic gates required while avoiding cross-talk
The dealbreaker: far too slow to run DOOM. RNA and protein half-lives are on the order of minutes to hours.
Protein phosphorylation (kinases/phosphatases)
Many cell signaling pathways use protein phosphorylation as a signal. This is much faster than transcription and translation, since no new RNAs or proteins need to be produced. A paper in 2021 built a toggle switch in yeast out of several kinases and phosphatases.
Pros and cons:
Response speed is adequate, similar to nucleic acid hybridization gates (i.e., largely l...
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