This is part two in a five-part series called "The Limits of Accelerating Returns" that focuses on the limitations of Ray Kurzweil's Law of Accelerating Returns when applied to molecular biology and biomedical technology, including longevity treatments. The other articles in the series are "The Limits of Accelerating Returns," "Garbage In, Garbage Out," "Some Rates are Fixed," and "Implications of Fixed Returns."
A logical way to understand biology as an information technology is to find the commonalities between biology and the everyday computer. Biology has its central dogma, which basically says: DNA stores the instructions for life, RNA carries the instructions, and proteins execute the instructions. If we apply these functions to the components of a computer, we see that DNA is like a hard drive, RNA is the computer’s RAM, and the proteins become the CPU.
Kurzweil appears to regard each gene as its own “program” that is easily turned on or off, just like opening and closing Microsoft Word:
[W]hen the fat insulin receptor gene was turned off in mice, they were able to eat ravenously yet remain slim and obtain the health benefits of being slim. They didn’t get heart disease or diabetes and lived 20 percent longer…
I’m an adviser to a company that removes lung cells, adds a new gene, reproduces the gene-enhanced cell a million-fold and then injects it back into the body where it returns to the lungs. This has cured a fatal disease, pulmonary hypertension, in animals and is now undergoing human trials.
For a gene to work properly, however, there may be a number of other factors and dependencies that come into play, just as launching Word requires your computer to access a number of other files on which Word depends. In the simplest case, the protein produced by a gene is not functional by itself but is a subunit of a larger protein. In order for it to work, the cell also needs the genes for the other subunits.
A more complex example of a gene’s dependencies is a protein that needs additional chemical modifications, after its assembly by the cell’s protein-making machinery, to become active. If the cell doesn’t have the additional enzymes to perform the necessary chemical modifications, then the gene’s program won’t be executed. This is the case for insulin. Simply taking the gene from a human and inserting it into bacteria won’t get the bacteria to properly produce insulin because they are incapable of making the requisite chemical modifications to the raw, unprocessed insulin protein.
Another important difference between genes and a computer program is that genes are not binary. That is, they are not either ‘on’ or ‘off,’ like a lightswitch. Instead, genes are more like a dimmer switch. They can be ‘on’ a little bit or a lot.
For some genes, the difference between a little bit of activity and a lot can have a big effect on the cell. These central control genes produce proteins that turn other genes on, and those genes’ proteins turn on other genes, and so on. The effect is an exponential activation of genes. Turning the dimmer switch of these central control genes to just the right setting will be a critical step for any sort of therapy—such as a longevity treatment or limb regeneration—that wants to reactivate this type of gene.
To further complicate the situation, turning a gene ‘on’ is not the only level of regulation. Copying information from DNA to RNA is called transcription, and activating this process is normally what we think of when we talk about a gene being on. But a protein must be made from that RNA—a process called translation—in order for the gene’s program to be executed. At least 30% of the total genetic control in a cell regulates translation. So if a gene is inserted into a cell and it gets transcribed, it still may not have any effect because its translation is blocked.
Even if a protein is made, it may not be active. Some proteins have to be “cut” before they become active, sort of like cracking a glow-stick to turn it on. Others require a final chemical switch or need energy input. If these supporting system are missing or inactive in a cell receiving a new gene, then the gene won’t have any effect.
Clearly, genetic regulation is a very complicated affair, and reprogramming biology, which is a necessary part of medicine becoming an information technology, is not always as easy as launching a program on your computer. Any attempt at reprogramming is subject to a cell’s regulatory networks, and there’s a lot about regulatory networks that we don’t know. Not just all the parts and how they interact. It turns out that if you rewire these networks in bacteria, the cells don’t die, like you would expect. They generally survive, and some even do better than their unaltered cousins. It is true that in some cases, turning one or two genes on or off can have very desirable effects. But to do really amazing things—like growing a new liver to replace a diseased one—we’ll need to take control of a large number of genes.
What do you think? Is this an obstacle, even a minor one, to Kurzweil’s predictions, or am I just not getting it? I’d love to get a debate going in the comments.
