I'm a non scientist and have been excited to learn more about this field, but to find out the most exciting stuff you need to read scientific papers. The details are the coolest parts IMO. A bit of self promo here, but I recently wrote a blog post summarizing a Stanford synbio paper in layman's terms .
The field really doesn't do blog posts, it's a shame.
For some interesting stuff in synbio that's approachable to your prototypical HNer, check out , a Verilog-to-DNA compiler that works with small logic circuits.  (Not really synbio) but using reed solomon codes to better do High-Throughput Screening.  PACE, a way to ask evolution to implement a particle filter for us.  A remapping of the base pair 3-tuple to amino acid that maximizes edit distance, filling in the gaps with STOP codons - stopping something from evolving, and  some cool people working on wholly synthetic cells.
 Nielsen, A. A. K., Der, B. S., Shin, J., Vaidyanathan, P., Paralanov, V., Strychalski, E. A., … Voigt, C. A. (2016). Genetic circuit design automation. Science, 352(6281). https://doi.org/10.1126/science.aac7341
 Erlich, Y., Gilbert, A., Ngo, H., Rudra, A., Thierry-Mieg, N., Wootters, M., … Zuk, O. (2015). Biological screens from linear codes: theory and tools. BioRxiv, I(1), 35352.
 Dickinson, B. C., Leconte, A. M., Allen, B., Esvelt, K. M., & Liu, D. R. (2013). Experimental interrogation of the path dependence and stochasticity of protein evolution using phage-assisted continuous evolution. Proceedings of the National Academy of Sciences, 110(22), 9007–9012.
Esvelt, K. M., Carlson, J. C., & Liu, D. R. (2011). A system for the continuous directed evolution of biomolecules. Nature, 472(7344), 499–503. https://doi.org/10.1038/nature09929
I have some unanswered questions about what is feasible in DNA editing, maybe your knowledge could enlighten me?
I would like an answer for e.g:
You might be interested by my analysis on how to cure ageing.
>AGI gets a lot of press
Yes AGI in sci-fi (e.g matrix) is not new.
But the medias and even the AI journals do almost 0 press about AGI.
Narrow (specialized) AI is now mainstream, especially the deep learning paradigm.
But clearly solving an NLP task is not building an AGI.. At best it's solving a constituent of an AGI.
But many constituents of an AGI does not have an NLP task, which means mostly nobody work on it.
An AGI, to be implemented need a big, sound, cognitive architecture.
AGI gets a lot of press
So, can you name at least one AGI architecture?
Nobody knows nor talk about them. To name the two most promising:
Cyc and opencog.
Well currently the website is down... But it is enlightening to read such an architecture.
DNA isn't the only thing that has to stay mutation free for an organism to not age. Lots of the cellular machinery will propagate error to future generations. For a simple example see prion diseases. Sure they seem big scary and rare, but I'd suspect in reality this sort of thing happens way more often than we probably realize just in ways that can't be spread person to person even via cannibalism or that has much lower consequences.
Keep in mind also that ending aging is striving against not just entropy but evolution. Cancer cells are selected for. Obviously not on a species level, but if even just one cell messes and starts reproducing out of control it will quickly take over. You can implement more checks along the way and repair damage as it comes up, but the point remains that if even just one cell somehow isn't effected, it will be selected for among all the cells that make you up.
DNA isn't the only thing that has to stay mutation free for an organism to not age.
Could we draw a list?
Your example on prion is incorrect as prion are misfolded proteins made by buggy DNA genes.
Another thing that I identify as contributing to aging other than cell DNA is mitochondrial DNA (it's weird to realize we have two different DNA in each cells)
Does other organelles apply?
I fking don't know and how could I? :(
Regardless, curing cell aging is only the first step in "curing" aging. Some cell types simply stop dividing as a natural part of the lifecycle, and it isn't necessarily telomere related.
Additionally, the only cells that don't shorten telomeres over time are cancer cells. Aging is a complicated process we don't understand.
Aging is a complicated process we don't understand.
I mostly disagree, while it is unknown how much of ageing is not a cause of DNA damage, I expect by far most of it come from DNA damage.
Btw: are organelles just protein complexes?
If so organelles are made by DNA too.
Also, the hayflick limit has little to do with DNA damage per se, but rather is about telomere shortening. DNA is replicated in a ssomewhat asymmetrical fashion, and at the end of the chromosome, and needs the telomere to act as a buffer. Eventually you run out of buffer because every replication loses a little bit. But there's no innate damage to the DNA related to telomere shortening - all of the generic code still is maintained.
>Btw: are organelles just protein complexes? If so organelles are made by DNA too.
No... Not even close. There are some proteins in them and proteins interact with them but organelles are extremely complex. They are structures made of lipids, proteins, minerals, RNA, etc.
That's why they have to run through a lot of source material before they get the right dna cuts they one, then they isolate those strands and let them proliferate.
By the way, there are things that reduce the damage of mutations that happen in cells. Check out xanthohumol. https://www.lifeextension.com/magazine/2018/3/protect-your-h...
You can also have your body clean up the older/damaged cells via autophagy.
Honestly I feel that epigenetics will be the answer to ending aging. Since the body is capable of producing new stem cells all you would have to do is map out the genetic triggers for creating those to replace older cells, and instigating autophagy to clean out the garbage.
For instance, with skin, the "aging" saggy, wrinkly, thinning skin is a result of the body no longer producing enough elastin, and collagen deficiency.
People believe that it's natural for the body to stop elastin production, but I've seen studies where scientists were able to trigger the genes in the dna that're responsible for creating the stuff needed to create elastin.
The cells were perfectly healthy, they simply stopped producing elastin, but when you introduce the trigger compound into the system the genes react to the trigger and you get elastin production.
If you can't pinpoint one gene that goes inactive in the dna that's the sole cause of aging, simply keep replacing damaged genes with fresh ones, and then piecemeal activate any inactive genes necessary to maintain a certain biological age.
So you could have a chronological age of say, 1,000 but your biological age is twenty.
I found this page because I have a google alert set up for "synthetic biology" I have no idea what this website is about honestly.
Rationalist, I'd love to talk to you about this more. send me a dm on linkedin, or facebook. https://www.linkedin.com/in/kendrick-bowman-91b9b716b/
Exchanging emails or contact info on a public site would be a bit crazy, but I'd love to talk to you about this more. I'm not planning to just theorize about this. I eventually want to get my own lab and put in some work!
CRISPR seems to solve the problem of editing DNA to contain arbitrary human-designed data. Are there major caveats or limitations to this that people outside the field don't recognize? e.g. is delivery to the right cells a major obstacle?
If editing is solved, it seems like the major remaining problem is designing the right data to insert. I'd imagine this is a much vaster problem than editing. What are the major subproblems there? What does the frontier look like?
Besides the mechanics of editing and designing the sequences to insert, what other major problems stand in the way of sci-fi level genetic engineering?
In short, there are huge limitations.
The first issue is how to edit people reliably. Cas9 simply isn't accurate nearly enough of the time. It's not a system that could be employed in a living human being without risking mistarget effects. How severe those would be is something that still isn't known, and would be difficult to model because where you miss would likely depend on the target gene.
There's a few thought processes on how to do it more safely. One is to make the edits in lab, verify the changes, propagate them. This is by far the safest route, but leaves other issues. How do you propagate the changes? We don't know how to propagate the changes to an adult human whatsoever. Stem cells get floated but that's still an underexplored field so it's difficult to say what's going to happen, or if it's even possible.
Regarding that to put in, that's the easy part. We've been designing sequences for artificial proteins for decades. Researchers at CalTech just published a paper last November where they designed a system of viral proteases (proteins that chop up other proteins) in such a way that they could perform logic circuits in a living cell, and do things like kill the cell if it developed cancer.
The first things to come will be targeted drug delivery, biomarkers, and cancer prevention.
However we are still a long way from propagating changes throughout an adult human, if it's even even possible with CRISPR.
Delivery is a major obstacle. DNA, RNA and proteins don't typically get into cells on their own. Typically you use vectors, often viruses or lipid nanoparticles, to get DNA into cells, but these vectors have their own challenges. One of which is that they aren't typically very specific to particular cell types. It can also be tough to get vectors to the right tissue. So most early gene therapy efforts focus on blood disease, liver disease and eye disease because it is easier to deliver to those areas. CNS has also become a popular target because a particular viral vector, AAV9, tends to get into neurons pretty well
But viral vectors are commonly "immunogenic", ie the immune system learns to reject them as foreign after one dose. These are viruses after all, and the body is designed to reject them. Some people have pre-existing antibodies to many popular vectors. And often you can only dose a viral vector once, so if you don't dose it right, or if the effect isn't permanent, you don't get another shot
I can't speak to some of the other more technical problems, but one limitation is that you are limited as to how large your DNA payload can be. But it seems this paper is a big step towards removing that barrier. Which I believe is why this paper is such a big deal (others more knowledgable should correct me)
Also CRISPR works best to cut DNA as of now (which renders a gene non-functional), but it is a bit harder to insert DNA reliably from what I understand. Again, a scientist in this field would much better understand the state of the art than I do, but this is my understanding
Another major unknown is the degree to which gene editing tech causes off-target edits. If your DNA editing tool accidentally snips a gene that protects you from getting cancer, it can lead to cancer. I'm not close enough to the science to know what current thinking is on this risk or how to best mitigate it, but it is very real. More primitive gene therapies did in fact cause cancer in patients (often children)
In many ways sci-fi level genetic engineering is possible. We just don't do it because we don't know the risks, and the risks are huge. We can already genetically modify human embryos, and our toolkit for doing so grows every day. Editing human embryos is a very scary proposition.
EDIT: I will also add that if you are interested in learning about this field, try reading / struggling through a couple scientific papers, really trying to understand every detail. Ideally with the help of a scientist friend. It is time consuming and daunting to get through all of the jargon, but the papers lay out the design, engineering and testing process in some detail. Often they provide the derivation of the mathematical models used and the specific DNA sequences used. You can begin to appreciate how amazing this work is when you get into these details
Related to both the idea of inserting DNA and off target effects - the issue is that scientists can engineer a cut, but then rely on the cell’s repair mechanisms to “stitch” the cut DNA back together. These mechanisms are inherently stochastic and error prone and are how many somatic mutations, such as those in cancer cells, arise. So for off target effects, even if you make the cut at the right place, you can still end up with new unintended SNPs and indels nearby. And for inserting new DNA, it’s not a guarantee. You can provide the template that you want to incorporate, but it might get missed, or get copied in more than once or in the wrong orientation.
Here's an example...
APOE e4 is associated with Alzheimer's disease risk. People in Guatemala have a high prevalence of this allele. Some researchers from the US might decide it's a good idea to fly down to Guatemala and launch a CRISPR clinical trial to 'protect' newborn Guatemalans from this increased risk of Alzheimer's. So they do; come back to the US, have a toast to longevity for these children. It has recently come to light however, that APOE e4 confers protection against Malaria parasites. Not a big deal if you live in Norway - huge deal if you live in Guatemala. Suddenly, the risk of developing an age related dementia doesn't seem all that pertinent.
So, my 2 cents is that, if we're really going to start CRISPRing babies, we'd better be doing our due diligence, and for now limit to diseases that significantly and immediately impair wellbeing.
May also be interesting to read this paper on a gene editing tech, which ending up being irreproducible.
original paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6077703/
biorxiv manuscript showing science isnt reproducible: https://www.biorxiv.org/content/10.1101/704197v1
article summarizing the above papers: https://blogs.sciencemag.org/pipeline/archives/2019/07/26/vi...
Other labs that off the top of my head that are active in gene editing are Feng Zhang, David Liu, Matthew Porteus. Of course I am missing most of the important labs but these are some important players
It's better to screen beforehand.
That's all true (and I agree), but that's a practical/technical issue. That may be solvable, but even in that case, that's not the whole story. There are also developmental biology issues at play once you have a full organism (or even an embryo that is just a few cell divisions in). The way our bodies operate as adults is just as much a function of how our cells developed and grew as it is a product of genetics. There are a lot of processes that happen only at very specific timepoints in development. And once you're past those points, editing the genes required won't have any phenotypic effect.
We can alter genetics with CRISPR. We can't alter morphology in the same way. For example, in certain eye diseases, you can have a loss of a gene that is involved in how the retina processes light. But, the same gene is also involved in how the optic nerve is formed (or migrates) in the brain. You could use gene editing approaches to knock in a good copy of the gene, which might help the retina absorb light, but the nerves have already formed and are already in place. That isn't going to change.
And none of that actually addresses the ethics involved in changing the genetics of a person, which is non-trivial to say the least.
Doing this a a living person would be pure madness, given the fact that we can't yet CRISPR even simple edits and deleting a chromosome (how would you even target just one of the copies?) is something much more complicated.
even if you could edit the critical cells, you'd end up with a chimeric cell makeup, and what does that mean in the long-term? then you have to tackle ethics, psychological effects, physiological effects, etc.
not trying to squelch the thought or effort, but that seems like a very long, hard road.
1. DNA is the hardware
2. DNA is the software
CRISPR gets a lot of press because it seems to give biologists exactly what they've always wanted - a tool to mess with the DNA - to alter the hardware, i.e. move around transistors
Biologists love CRISPR because they are hardware people - that's how they were trained, that's how they think, and there are millions of them all thinking the same thing, yearning for the same.
Then there are the others who think DNA is software, the genes themselves are "merely" the CPU. For them, the hype around CRISPR is a distraction, and it only sets back scientific progress as it keeps channeling the focus and attention to the mere physical act of cutting pasting DNA as if that would ever explain anything.
In a nutshell, genes are probably not that important, it is the repetitive and seemingly senseless elements in between then that regulate the individual pieces. For an analogy think about how you can run radically different software of the same hardware.
See: "A 21st century view of evolution: genome system architecture, repetitive DNA, and natural genetic engineering"
Genes encode for proteins, which seem pretty crucial to biological functions of the cell.
The software/hardware paradigms don't fit exactly. They are useful is certain situations. The most useful of these is that DNA can be described as a linear sequence of a discrete set of symbols (to a first approximation).
(Richard Feynman - Why)
DNA is a physical thing, whereas genes are underdefined concepts on top of DNA. Every single thing people call a gene has a different name as well. What someone calls gene might be a protein, might be a transcript, might be the superset of all coding exons of a family of transcripts and so on ... so what is a gene then? I have come to believe that "gene" is a word everyone likes to us yet very few if any understand.
Find any definition of gene and it is either quite circuitous or wrong. For example take the Wikipedia page for gene. The definition devolves into that of a primary transcript. In reality transcripts code for molecules, and multiple transcripts may be labeled as the same gene. Note how genes do not actually exist in the same way as transcript do... the wikipedia page never makes it clear that a gene is a mere label and grouping of the existing transcripts.
Fundamentally, of course, the hardware/software are a metaphor - it does not really work as a hardware nor software.
The point I was making is that the information processing that takes place on DNA is what differentiates the different life forms, not the actual base identity.
In all seriousness though this is pretty amazing. Especially in light of how fast this technology appears to be progressing. Seems like we are rapidly approaching being able to utilize biological factories at a small scale.
For folks looking to learn more about Genes in general I recommend the book below.
The Gene: An Intimate History
But... it's not clear to me that this will work. You'd have all kinds of issues with the viral population mutating. I'd guess the virus would in most cases not kill the host before their natural defenses kick it. Not really spreading in the population etc.