
The genetic code now has a workable text editor - walterbell
https://aeon.co/essays/we-now-have-a-good-text-editor-for-your-genetic-code
======
arbitrage
What I would like to know, and haven't heard talked about in any of these
articles yet, is if it's possible to substantially alter the genome of an
already living creature.

This article touches on it briefly at the beginning, but doesn't elaborate on
the idea:

> This means it’s possible to create genetically modified plants or animals of
> practically any species, as well as to modify the cells of adult organisms,
> including humans.

But so far, I've seen every article go to great lengths to avoid a very
obvious question. Aside from medical cures, is it possible to use this
technology for cosmetic purposes? Will I be able to change my eye color
permanently? Cure baldness in adult humans? Alter metabolism?

~~~
toufka
>if it's possible to substantially alter the genome of an already living
creature.

Yes, but it's tricky right now. The delivery mechanisms are still rough. But
for certain applications, in certain tissues, for certain kinds of diseases it
is being done today (see Sangamo getting cleared for a gene therapy for
hemophilia last week)[1].

Currently we have two ways to direct a genetic payload - one is localized
(cellular) control of the actual delivery mechanism, the other is
(biologically-relevant) temporal control of when the payload gets 'fired' or
used.

Practically, we can strip some kinds of mammalian viruses of their own payload
(and their ability to replicate), and utilize their own DNA insertion
machinery (which is very nicely evolved to match our physiology) to insert a
desired payload into the genome of a live organism. Some tissues are better at
receiving specific payloads than others. (If you find a tissue and
corresponding virus that delivers a tissue-specific viral infection, we can
likely deliver a tissue-specific viral gene therapy to that tissue.)

Once the genetic payload is loaded into the genome we have other ways to
control when the payload is actually turned on. We can make the payload
sensitive to tissue-kind, or biological timing events, or sensitive to other
kinds of biologically relevant environmental cues.

Both of these methods alone, however, are generally leaky. If the changes you
are making are critical either for effect, or for preventing off-target
effects, then these two methods alone are likely insufficient for a general
population therapy to not be a dangerous gamble. The consequences of injecting
the wrong code (or the right code to the wrong place) can be fairly
catastrophic (induced, and immediate cancer). And that is precisely why a good
'text editor' is valuable.

One intervening point is that most viruses inject their payload into your
genome randomly. And if they happen to overwrite some required genetic code of
yours they cause cancer. Some viruses actually _intentionally_ overwrite the
code for your viral defense mechanisms (see HPV overwriting the P53 gene). In
general, random injection of genetic payload into a live organism's genome
(source code) is a bad idea.

The ability to have a good 'text editor' means we can now ensure that _if_ the
payload gets to the desired cells, then we can insert that payload into the
genome in a _desired_ location that is unlikely to cause problems. And since
we can further regulate when the payload is fired, we now have 3 levels of
control ( 1: localized cellular delivery, 2: localized genetic insertion, 3:
biologically controlled activation). And those three levels together can
significantly reduce the chance of mis-editing a live organism's genome.

Once these three regulatory mechanisms are made safe enough to not just be
used in situations where risk/reward ratio is skewed by the lethality a
disease, there is no reason they cannot also be used for an arbitrary
biological effect.

[1]
[http://investor.sangamo.com/releasedetail.cfm?releaseid=9448...](http://investor.sangamo.com/releasedetail.cfm?releaseid=944828)

~~~
rjsw
I made a bet to myself about 30 years ago that the mechanism for gene
expression would be found to be describable as a non-linear system. It doesn't
sound as if this is a solved problem yet.

~~~
toufka
We understand very well how gene expression works. It's the editing, with
precision, in trillions of living cells, without harm, on an entire
population, that's tricky. What do you mean by non-linear?

~~~
rjsw
> What do you mean by non-linear?

I mean in the mathematical sense [1], if modifying a piece of DNA can still
produce unpredictable results then I wouldn't really feel we should claim that
we understand how the whole process works.

[1]
[https://en.wikipedia.org/wiki/Nonlinear_system](https://en.wikipedia.org/wiki/Nonlinear_system)

~~~
toufka
>Wouldn't really feel we should claim that we understand how the whole process
works."

It's more like classical vs quantum mechanics [1]. Both are correct in their
limit. And yet we also know that neither is actually _True_. With respect to
genetic regulation we understand the largest terms in the non-linear system,
and many of the smaller terms. Does that mean we 'understand' it completely?
No, but like physics, we understand it 'completely enough' for many
engineering purposes. The fun of it is that there are still exceptions and
edge-cases to play with and learn from.

[1]
[https://en.wikipedia.org/wiki/Correspondence_principle](https://en.wikipedia.org/wiki/Correspondence_principle)

------
TeMPOraL
It's interesting that searching for "CRISPR" in the essay gives 0 results.

~~~
shoyer
Agreed. It's very strange that the article doesn't mention any of the very
real recent scientific advancements in this space. I expect better on HN :).

------
Animats
It will probably take a century or two of debugging to get human editing
right. Generations are just too long.

Backwards compatibility may be a problem. Pfizer people may not be able to
mate with Genentech people.

------
EGreg
Trying to use current computer science to work with biology is like using a
hammer to reliably modify the behavior of an ant colony. It may work but only
in some special cases.

Even with the Von Neumann model, we already have ecosystems where many things
are interdependent. And the difference is that the actors in the ecosystem are
all designed by people who coordinate and communicate in other channels. They
have common standards etc. Now imagine having some monolithic open source code
with all the libraries mixed into it that has been forked many times and
trying to have a process that will change some of the source code to achieve a
desired effect, reliably in even THREE random forks. How would you know the
side effects of all your changes? All you can do is make some very simple
change and gather statistics on how often your change leads to more
instability and crashes.

You can't just edit an organic system with tons of interdependencies. As
humans building software we specifically limit the scope of the dependencies,
we make protocols and conventions etc. So we can reason about the impact of a
change and make the source code we produce more maintainable. How would this
apply with DNA?

~~~
swiley
Computing theory and information theory apply to much more than just Von
Neumann architecture computers.

~~~
hyperbovine
...but to far less in the biological sciences than some computer scientists
care to admit. If I have to hear one more talk about how e.g. "natural
selection is a highly efficient algorithm", I'm going to shoot myself.

------
EGreg
Funny that Ctrl X followed by Ctrl V will paste what was there originally
after it was cut

------
carapace
I am firmly in the terrified camp. "Genetic engineering is not new." Oh yes it
is, and it's scary.

------
mteifel
How can one get started?

~~~
noname123
API Reference:
[https://www.addgene.org/crispr/](https://www.addgene.org/crispr/)

Tutorial/Cookbook:
[https://www.addgene.org/CRISPR/guide/](https://www.addgene.org/CRISPR/guide/)

------
suprjami
Next, vim-genetics

------
FreakyT
Relevant XKCD:

[http://xkcd.com/1605/](http://xkcd.com/1605/)

~~~
dnautics
The problem with DNA 'source code' is not that it's hard to read, it's that we
don't fully know how to read it. Yes, we know what protein sequence comes out
but the chemical consequences are not particularly well known. With google's
source code, you could, in theory, look at it long enough and have a working
understanding down to the level of electrons moving around specific spots in
the chips in the Google datacenter.

As a professional (wet) biochemist and also a coder, my personal feeling is
that biology is much, much shallower. However, the knowledge required is
broader but incomplete. If you're trying to, say optimize an enzyme, beyond
molecular biology, you'd do well to incorporate knowledge from biochemistry
(is this an active site amino acid? Maybe I shouldn't touch it. What sort of
yield changes can I expect if this enzyme catalyzes the rate-determining step
vs. not), cell biology (will adding this amino acid sequence send it to the
wrong compartment?), biophysics (will changing this residue mess up the
protein fold?), electrochemistry (is the electrical potential of this iron-
sulfur cluster consistent with the process I want?) etc etc.

A lot of 'biohackers' are script kiddies that just ctrl-c/ctrl-v gene
sequences and hope that it works. That's why you see a lot of gene synthesis
companies claim a offer of "codon optimizing" a gene. It's something that
sounds hard, sounds critical, and gets _something_ done. The rest of it is
much, much harder, and requires actual thought.

~~~
pazimzadeh
I'm not sure I understand what you mean when you say that "biology is much,
much shallower". Shallower than what, and in what way? What might it look like
if it were deeper?

~~~
silentplummet
When we use a computer programming language, we are directing an abstract
machine to interpret and manipulate data to get a result that we want. We have
all the knowledge we need about the machine because we conceived and designed
it ourselves.

DNA is like a programming language for a biological computer, a living cell.
However, we don't know nearly everything there is to know about a living cell.
We can't predict its mechanisms. There is no debugger. The compiler didn't
come with an instruction manual. The code bootstraps itself into its own
machine and runs in an environment we can't predict. And the syntax has been
obfuscated and optimized by a genetic algorithm that's been running in
parallel on quintillions of cores for a billion years.

Because the code executes on an unknown machine in an unpredictable physical
environment, many features we might expect to see in a programming language
are missing. This might be what he meant by "shallow".

~~~
dnautics
I mostly meant that there is tons of encapsulation in computer programming.
Like one could be a full-stack engineer that could go from soldering a
transistor (or designing an IC from scratch, to writing a web app that uses
web sockets that sit on top of HTTP which is on top of TCP/IP sockets, which
is served ruby sitting on top of linux which is virtualized by Amazon AWS
which is managed by a hypervisor sitting on top of a cluster of computers, all
talking to each other via TCP/IP..... etc.), and there are so many layers
'deep' to that cake.

And this is a personal feeling, but there is less encapsulation, in biology.
There are less 'categories' of things that build on top of each other that you
have to learn, but those categories are immense and the knowledge in each of
those is incomplete. I suppose you could say the knowledge in some of
programming is 'incomplete' by virtue of closed-source encapsulation (trust
us, this hardware works like you think it does), but that is somewhat
artificial.

~~~
pazimzadeh
Thanks for that explanation. Do you really think the stack is smaller in
biology? Biology has been optimized over three billion years - if we've
already invented more layers than there are in biology then are we not
overthinking it?

This is what I came up with in a hurry for biology:

    
    
      ...elements
      atoms
      chemicals
      nucleic acids
      genetic circuitry
      peptides
      proteins
      multiprotein complexes
      microcompartments
      organelles
      cells
      clusters of differentiation
      organs
      organisms
      communities...
    

Care to fill in or improve the list?

