The approach they used which is base editing doesn’t actually insert or remove DNA, it actually uses an enzyme to convert one base to another, which is much safer as this doesn’t require a double strand break in DNA: https://blog.addgene.org/single-base-editing-with-crispr
That is interesting, I didn't catch the difference my first time through the article.
I do still question their claim of 100% precise results though. At least based on that high level description I can definitely see it being safer, but I question any scientific claim that is an absolute.
Specific to the editing vs insertion mechanism, I question how it doesn't run into similar constraints where the mechanics of targeting exact portions of the DNA can occasionally miss or impact the wrong segment of DNA entirely.
I haven't dug as deeply down the base pair conversion though, so I could absolutely be wrong!
Essentially you can design an rna molecular that contains a 20 nucleotide long sequence that can target your region of interest, with the caveat that there is a standard recognition sequence proximal to your sequence of interest (PAM sequence)
Home lab, or even be able to sequence your genome at home, privately and securely without risking giving your genetic information to companies like 23andme
Forgive me, I'm just totally ignorant here. In order to sequence your own genome and do something like 23andme, I kinda just guessed that you'd need some kind of existing corpus and database to derive meaning from the results.
Is that true? And if so, is it all open source or free?
It's something that's kind of interesting to me. I really enjoyed biotech and chemistry in HS but ended up going in a different direction. If this is something that you can just get into now as a hobby maybe I'll jump down the rabbithole
Nearly everything in this space is OSS. From the aligners to the assembly and the databases.
Last I checked 23andMe didn't perform whole genome sequencing but looked at some number of point mutations. It depends on what information you want. Eg for the sake of interest of actional genomics data.
While it's true that most of the tools for genomics are OSS, there is some good software and in particular some databases that are commercial and quite pricey.
And the sequencing machines and chemicals also don't come cheap, as the market has long been dominated by one vendor.
There’s also people pursuing mRNA delivery systems to do this. Might be cheaper than viruses and there’s precedent now with COVID vaccines. https://www.capstantx.com/
There are research groups that are trying to encode genetic neural networks into cells like the example I have attached, but the neuronal approach from the post does seem to be different here. https://www.nature.com/articles/s41467-022-33288-8
There are definitely very solid attempts at least to make LLMs that encode biomedical knowledge such as BioGPT which is trained on Pubmed and other domain specific areas. Source: https://arxiv.org/abs/2210.10341
Spatial Transcriptomics. Being able to see gene expression at a resolution of a handful of cells in a cross section of tissue is revolutionizing disease research. https://www.nature.com/articles/s41592-020-01033-y
Cool I work in spatial transcriptomics, it's still early days but not too far off we're going to get great resolution and great capture. Especially for the brain, and maybe even tumor micro-environments it could be really cool
I am always fascinated by the ignorance that is blatantly displayed on HN when it comes to biotech advancements. Not even some actual criticism of the tech, or even the faint understanding that this sort of thing is exploratory research. Wonder why this sort of skepticism is never applied to cutting edge AI research whose ethical ramifications are much more severe and which is already being utilized by bad actors to facilitate genocide [1].
