New organisms have been formed using the first ever 6-letter genetic code
sciencealert.com
sciencealert.com
https://en.wikipedia.org/wiki/Dominion_(Star_Trek) http://memory-alpha.wikia.com/wiki/Ketracel-white
If my reading of the paper is correct, the unnatural XY base pair doesn't have any function per se, but without it the organism fails to replicate its DNA and quickly dies. Hence you can argue that after introducing it, the XY base pair has a vital function, as without it the organism can't survive anymore. And since the organism has no way to synthesize X & Y itself, it needs to be supplied from the outside for its whole lifetime. This, in turn, provides a neat way to build "self-terminating" organisms that depend on a steady supplement of the given substance. One could of course argue that vitamins are exactly the same, but contrary to those the artificial base pairs would not be found in the wild, so supply could be controlled more easily.
Genetically modified organisms are a bit scary, but genetically modified organisms that replicate autonomously are more than a bit scary. As programmers - a profession that managed to spread Shellshock, the dumbest imaginable backdoor, so widely as to make much of human population vulnerable, we should understand this better than others. We have no idea what happens in our own code, code that we copy from place to place ourselves, written in languages we designed and running on machines we designed, and there's nothing like mutation and self-replication with this stuff, for the most part. I kinda doubt that biologists modifying "code" which is actually pretty large molecules existing and interacting in a 3D space with a lot of forces pulling and pushing things, and without the benefit of comments or design documents, can make something that can be trusted to autonomously replicate and gradually mutate.
That's an overstatement. Sure code can be very complex but we actually can see exactly what's going on whenever we really want to. It's just that we cannot see what's going on with all the code all the time.
Simple example: can you tell me if this snippet of (python) code will ever terminate or not?
x=0.5
while x<0.6 or x>0.7:
x=3.59*x*(1-x)
print x
The original poster seems to imply that knowing the code means that you can know the behaviour of the system; I do not think that is the case, and my simple (chaotic) example tries to demonstrate this.
The issue is not so much how this code is translated from higher abstraction level to lower abstraction level... the issue is, that this code represents a simple chaotic function (the logistic map). As such, for a simple few lines of code the behaviour is very complex and virtually impossible to predict; for certain values of the controlling number it will (1) halt relatively quickly, (2) never halt, or (3) halt after a very long time... but good luck in distinguishing between cases 2 and 3!
What my code snippet is doing is running a sample of a particular chaotic function that was originally inspired by biology (a simple predator/prey model). Ultimately, what happens is that you just cannot predict how the function will behave - it is chaotic.
Ultimately most complex systems start to show some chaotic behaviour, which basically means that the behaviour of the system cannot be predicted in detail, even if virtually everything is known about the system in advance.
One example is if you try saving a simulation to disk you need to copy all internal state or you get a different output.
In "practice", if you could call it such, a computer with limited memory becomes a "linear bounded automaton" and the Halting Problem is decidable; cf. http://cs.stackexchange.com/q/22925
Of course, big enough memory can mean that it can be impossible to detect termination before the heat death of the universe - we are talking theory here.
PS: The halting problem is only undecidable when running with unlimited memory.
For the Collatz problem you can simply run a (fixed version) of that program with arbitrary-precision arithmetic and it would pretty much run until you run out of memory, which is on the order of 2^RAM. For me that would be about 2^8000000000.
I think an important argument that hasn't been made is the simulation speed. If we want to make sure a program running at clock C never ill-behaves, it suffices to simulate it at a clock C'>C and halt it if and when it misbehaves. Any constant factor speedup is sufficient to manage that even in the same hardware. A problem starts to occur if C is susceptible to random mutations, with a branching factor B every T seconds. Then to simulate t seconds into the future requires B^T/t more computing power. If there's one 1-bit mutation per second, it gets unpredictible less than 1 hour in the future.
x=5
y=5
while True:
if y%2 == 0:
y=y/2
else:
y=3y+1
if y == 1:
x=x+1
y=x
if y==x:
return x
PS: Don't waste time checking x values less than 1000000000000000000
If your asking the underlying math problem, yes that is true for all positive integers. It's much more obvious in base 3.
That said, we can still see what that code does, even if we don't know precisely what code path it takes. Great example though!
It's not merely an attack of people with stupid uninformed opinions. It's a tobacco industry style propaganda campaign that attacks anyone that is not 100% patriotically behind GMOs.
Also, if they get powerful enough that they can take over your synthesis facility...
Documented: Computer viruses mutating in the wild by two different viruses accidentally copying themselves into overlapping regions of memory.
Genetically modified organisms are a bit scary...
Foods have ingredient lists for a reason.
Assume your code will be disassembled at some point by a bad actor. Don't assume that any code distributed to a client is safe or trustworthy, and expect that any data, methods, or secrets contained in that code are now public knowledge. To secure your environment systems under any other assumption is a dangerous falsehood.
There's a good hook for a sci-fi story. Some low-level manager in a biochem company starts siphoning off XY juice to sell on the black market, and doesn't realise that by slowly ramping up their thievery they're evolving the killswitch out of their engineered organisms...
And speaking of the Jem'Hadar, there was an episode of Deep Space Nine based on this idea:
http://memory-alpha.wikia.com/wiki/Hippocratic_Oath_(episode...
That's the premise of Jurassic Park 1, except with an amino acid.
Crabs On The Island (Russian 1958, English 1968) (original: Kraby idut po ostrovu), by Anatoly Dneprov
That's actually differently to how I've read it - it appears to me that the XY pairing is stable and not harmful to the host and so is not degraded or removed (recognised as foreign by mis-sense DNA proof readers) but is therwise not performing any function, although some of the technical details are missing.
As to your second point, we already have highly perfected 'terminator' technology, currently in 3 forms:
1) the infamous Monsanto terminator technology, where second generation seeds would not be viable (which, incidentally, would be a significant benefit to some farmers growing genetically engineered cotton and potentially their crops, as spilt seed from harvest would not germinate)
2) in bacteria and other organisms etc in the form that you describe above - ie lack of a substance is fatal - usually this substance is some generic low dose antibiotic that triggers a genetic switch when present
3) as you suggest, removing an organisms ability to synthesise a particular amino acid and having it dependent on food
Such a mechanism would also do for an explanation for a Blade Runner style replicant that had an extendable lifespan.
This is how the plot of every horror/disaster movie starts.
Because its a trope. Can you explain how it gets wildly out of hand beyond speculation?
Unknown unknowns. You can know your specific problem domain inside and out, and still have other things show up that rapidly invalidate your assumptions about the set of possible outcomes.
So in order to protect us from getting whiped out by rogue bacteria from a research lab we MUST ban disaster movies NOW!
Its entirely possible that there were other self-replicating molecules on Earth that evolved first, but DNA simply out-competed them to extinction.
If we ever produce a competitor to DNA that was more 'virulent' than DNA, it would similarly out-compete DNA.
It would be the most pandemic of plagues that would affect every form of life. Even if we could protect our own DNA against attack somehow, it would attack all the bacteria that is symbiotic with us and which we need to survive.
Addressing the other comments about this leading to some crazy scifi scenario, imagine telling someone you used machine learning to identify spam emails and they started freaking out about how you're going to start Skynet. If you understand how things really work you can see it's not just implausible, it's that things fundamentally don't work that way.
Biological systems are relatively unpredictable, and based on rules that we didn't design and cannot begin to claim we fully understand.
Your analogy therefore strongly predicts negative unforeseen consequences.
If the field "cannot begin to claim we don't fully understand" things now, when do we reach the point where we suddenly "know enough to begin to do things", and why should we be listening to you about that point instead of experts in the field?
The reality is that this system is highly predictable in the way it was intended, and the changes made are understood extremely well at a molecule and cellular level. You can't come up with a specific concern with this system because you don't have a clue about it. Anyone who does cannot come up with a specific concern of this system because it is extremely predictable.
This anti-scientific Taleb-esque argument is just used by people who have no idea what they're talking about to try and speak over those who do, and is anti-intellectual and anti-scientific to its core. The OP's comment holds very well- this is no different from a layperson worrying about someone implementing an SVM on some dataset "becoming skynet, because computers aren't always predictable!" - it's nonsensical the minute you have any idea what you're talking about.
To suggest that accurately gauging the limits of our current knowledge about biological systems is 'anti-scientific' or 'anti-intellectual' goes against everything science stands for, and firmly crosses the line into blind scientism.
It remains absolutely true that we understand the software systems we build far better than we understand the biological systems that we are intervening in.
There is also a straw man in the suggestion that I have said we shouldn't 'do things' until we know more. I never said that.
I simply think that pretending that our understanding of software systems is representative of our understanding of biological systems is a delusion.
Again, the original analogy is perfect because the same statement could be made by the hypothetical "anti-software" person - this person could say "You're just appealing to the authority of these computer scientists! They don't know everything, software bugs happen all of the time!"
>To suggest that accurately gauging the limits of our current knowledge about biological systems is 'anti-scientific' or 'anti-intellectual' goes against everything science stands for, and firmly crosses the line into blind scientism.
Yes, of course it does. My point is that you are not in a position to accurately gauge our current knowledge about biological systems, and that everyone who is in that position does not agree with you.
There are plenty of legitimate dangerous and ethical issues in regards to biotech development, even in the near future (just like there are legitimate issues in regards to generalized AI) - but essentially nobody with any field knowledge thinks that on-going research in this category (along with GMO research and synthetic biology) will "accidentally cause a catastrophe, in the same way that while many computer scientists may push for caution with generalized AI, they don't think current ML methods and software will accidentally cause a catastrophe.
>It remains absolutely true that we understand the software systems we build far better than we understand the biological systems that we are intervening in.
I did not suggest that it does not. That is obviously true. However, the original analogy still holds: it really is roughly accurate to claim that the chance of catastrophe occurring from this research should be treated similarly to the chance of catastrophe occurring from ML implementations. While it is impossible to quantify the true chance of catastrophe in either case, both are so considered ludicrously low, unimaginable, and counter to our understanding of the system that experts in the field do not consider it to be a serious threat.
When I say it is "unimaginable", it is because it really is- I can not imagine a scenario where this technology results in some kind of catastrophe. It is actually easier for me to imagine a possibility for the software case, such as a predictive neural network involved in controlling the power grid that gets some unexpected input and creates some unexpected output that causes serious grid malfunctions for millions of people. While that may not be 100% "how things work", it at least seems more plausible than like, this research resulting in catastrophe.
>There is also a straw man in the suggestion that I have said we shouldn't 'do things' until we know more. I never said that.
You may not have, but many people (including here on HN) use similar arguments in order to advocate for suppressing research and progress in biotechnology (with Nassim Taleb being the most public of these people). If you are pro-biotechnology, then great!
I'm not anti-biotech. I'm against using the spurious analogy with software as a way to establish risk levels. I do think that it's an anti-scientific argument, and frankly one that undermines your cause.
If as you say, only experts in biotech are in a position to understand that the risk level is similar to the software case, this proves my point because it means that the analogy is just a way of conveying the opinions of those experts without being open it.
Far from being antiscientific, it's a rather straightforward observation that borders on self evident. What would be unscientific would be claiming such things can never be understood, even in principle. But that's not the claim that was made.
The original claim was that to against this research or cautious about this research "because we don't always predict what biological systems will do" is on the same order of magnitude analogous to claiming we should be against or cautious about people implementing machine learning algorithms because "we can't always predict what software will do, especially AI!". I believe that this comparison is 100% valid and useful for explaining why the original reasoning is flawed to those in computer science who are pretty uninformed on biology.
The actual "chances of something going wrong" might not be the same - it might be a 10^-25 chance that you made a mistake in your implemented SVM that, err, causes a catastrophic error that has serious consequences for humanity, possibly because "the internet is all connected, man" (if this sounds ludicrous to you, that is how the other side sounds to me on these cases of biology!) and a 10^-24 chance that this research results in some organism that, err, causes a catastrophic error that has serious consequences for humanity (it is equally difficult for me to envision this), but the point is that both are cases where we can be so confident that some absurd catastrophe will occur because we have studied .
If you have specific predictions about how on Earth this research could result in catastrophe, make them and we can discuss how possible they are. If not, it really is anti-scientific fear-mongering: you aren't making any positive claim about a legitimate possible issue, you are simply saying "I have this gut feeling that like something could go wrong with that and it could like spread and be bad", even though we have excellent reasons to assume this is not the case and no reason to assume it is, and that everyone with any field knowledge strongly disagrees with your personal assessment, and the situation really is analogous to the person worrying about the SVM.
Edit: And to further explain why this is "anti-science" - it is because you are not making any testable claims, you are simply saying "We don't know everything that can go wrong, there could be something you haven't thought of!" and using that impossible to disprove hypothesis to shut down research and development, e.g. the process of science itself.
There's also nothing about the interaction of these pairs with existing mechanisms, like transcription (DNA-->RNA) and translation (RNA-->protein). Could the new new pair increase the space of aminoacids from which proteins can be formed?
The achievement is that the E. Coli lifetime is not affected. The XY's are probably inserted in a part of the DNA that is not transcribed.
However, there are no corresponding RNA unnatural bases, and there's no tRNA that would recognize that even if there were. So it's going to take a lot more work before you can use these for coding for noncanonical amino acids.
This really is just a proof of concept.
Along with the recent article about pig embryos, I wonder if the not-too-distant future will lead to bizarre custom pets, like something out of the Spore video game.
In practice, it's probably going to be used as tools for manipulating organisms for experimental purposes, since scientists can do things to the synthetic bases that can't be done to real ones (or that effect natural and synthetic bases differently.)
My guess is that it would be considered an error by the RNA and corrected but your parent suggest that the RNA is just treating it like it would one of the other four molecules with is also a possibility.
e coli: http://www.nature.com/nmeth/journal/v3/n4/full/nmeth864.html
yeast: http://link.springer.com/protocol/10.1007%2F978-1-61779-331-...
mammalian cells (very very very very very hard): http://www.nature.com/nmeth/journal/v4/n3/full/nmeth1016.htm...
[0] the trick is to steal a tRNA from an archaeon; scuttlebutt is that the postdoc on the paper stole the idea from the lab across the hall, which was actually working on that archaeon.
* In order to reproduce (and maintain the new bases in its DNA), does the organism need a source of these nucleotides in its growth medium? (i.e. in its food?) The alternative would be to produce them itself, but that would require scarily advanced genetic engineering, I think.
* If one of these bases is in a gene, what happens during mRNA transcription? Total failure?
Point 1 at least should more-or-less ensure this can't escape the lab.
While it might not be useful to the organism, could the synthetic base pairs lead to a way to store data? Imagine a bacteria that can be used as a living, self-healing datastore.
> Finally, the team used the revolutionary gene-editing tool, CRISPR-Cas9 to engineer E. coli that don’t register the X and Y molecules as a foreign invader.
> "This will blow open what we can do with proteins."
> [The base pairs] can't be read and processed into something of value by the bacteria - it's just a proof-of-concept that we can get a life form to take on 'alien' bases and keep them.
> ...have not been designed to work at all in complex organisms, and seeing as they're like nothing found in nature, there's little chance that this could get wildly out of hand.
To quote Jeff Goldblum, "life, uh... finds a way".
I'm not at all sure whether or not denser information and thus bigger-step mutations are evolutionary advantageous.
A:T T:A C:G G:C P:P