Grad student @MITBiology working on immunology, computational + systems Read my website for full sentences.
Joined August 2020
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Will Owens retweeted
Nitroduck designs new colors, flavors, and disease resistance into fruits and veggies. We integrate CRISPR into breeding through pollen, making any crop gene-editable.
Breeding a new specialty crop variety takes 8 - 16 years: breeders hope for random gene combinations and mutations, then spend years picking out the good ones. Meanwhile, consumer tastes, the climate trends, and pathogens change way faster.
Now, accessible genome sequencing and AI can tell breeders what to aim for instead of what to hope for, and CRISPR can turn random mutations into chosen ones. The catch is that CRISPR only works on about 15% of crops. It has to go into a single stem cell that’s then regrown into a whole plant, a process that has to be worked out for each variety, which is cost-prohibitive.
We skip the stem cell and put CRISPR into a pollen grain. The grain pollinates a flower, and out comes an edited seed - seamlessly tapping into how breeders already work.
Matúš, Miro, and I are plant synthetic biologists who made duckweed, the smallest and fastest-growing plant on Earth, genetically engineerable. For doing so we won the Grand Prize at iGEM, the “Olympics of biotech.” During our studies, we engineered 4x more plants than the average plant scientist does in a whole career. Now we’re building Nitroduck, The Crop Design Company, which will make pesticides obsolete by 2042.
Will Owens retweeted
As someone who did this kind of genome mining work during my PhD, some thoughts on this Anthropic announcement:
First, the very simplified version of what they did is that they noticed two genes (one known, one new) sitting next to a weird repeating piece of DNA. More specifically, they described an unusual reverse transcriptase (RT) associated with a repetitive DNA array and an unknown accessory protein. This kind of process was used to understand CRISPR back in 2002 and was key to the gene editing tools we use today.
To put this into context, though, people have been finding RTs associated with CRISPR arrays since 2008, and this general kind of genome-neighborhood mining has been used to discover new biological systems for decades. The basic genome-mining strategy is well established, and there are now mature tools and published pipelines for doing much of this. There are papers that discover and experimentally validate dozens of new systems using this approach in a single study. Doing it in bacteriophage genomes is also nothing new (eg CasPhi).
Finding a weird cluster of genes and repeats is often the easy part. The hard part, and where the real discoveries come from, is figuring out what the system actually does. Eg for the bridge-RNA discovery in 2024 from @arcinstitute or the discovery of CasPhi in 2020 from @DoudnaJennifer they figured out the pieces of the system and the rules for what makes it work so it can be used.
Anthropic does not yet know what this does. They’ve shown that the repeat array produces RNAs, but not what those RNAs do, what the RT does with them, or whether the system has any of the programmable properties that make the CRISPR comparison justified.
I’m genuinely rooting for all of the frontier labs to seriously get into biological discovery, and I’m excited about what comes out of it. But announcing these very early, incremental findings with the framing of a major discovery doesn’t help. I’d much rather they set the bar high now, so that when an AI actually discovers a fundamentally new biological mechanism, everyone appreciates how big a deal it is.
Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRISPR.
We don’t yet understand what this system does, but only a handful of known systems share its features, and all of them are able to cut, copy, and paste DNA. Historically, the discovery of such programmable systems has helped revolutionize medicine. CRISPR, for instance, is now the foundation of genetic medicines. But it will take much more work to learn what this system does, and whether it can be put to similar use.
Read more: anthropic.com/news/claude-di…
Will Owens retweeted
1. >10M people die of infectious diseases per year today. AI is already helping us get better at tackling that.
2. Many ways to create very dangerous bioweapons without any AI/synbio (and it was true for the last 50-75 years). The delta on risk is quite small imo.
Will Owens retweeted
Look at these pictures. Don't let the lab automation robot accounts fool you. Those OpenAI/Anthropic tokenmaxxing biologists don't want you to see this. The long tail of science execution in the US and worldwide is this. Its lab benches and older HPLCs. Its paper and Fedex boxes. This is what MGH looks like right now. There are MANY such examples worldwide.
This is why I have a tough time reconciling OpenAI/Anthropic against the long tail I've seen with my two eyes both in industry and academia.
ALT Gel electrophoresis for seeing DNA
ALT Typical lab bench in the US
ALT Fedex boxes of biological samples
Building a moonbase doesn't produce abundance, it simply shifts wealth from some (earth homeowners) to others (moon homeowners). On net, society is no better off.
My take on the #Abundance2025 movement. Most of it is fine, but it's mostly small beer that distracts us from the real tasks. Oh, and it's mostly redistribution, not growth. Other than that...
@ezraklein @DKThomp
itif.org/publications/2025/0…
Vids like this give me hope that content longer than 2 minutes isn’t dead
youtu.be/YGLNyHd2w10
Will Owens retweeted
Solving the "replication crisis" is dumb because (1) it's not a crisis, (2) the medicine is worse than the disease. Much of this is because people want science to be more like engineering, and it's not. It's fundamentally different and trying to treat engineering processes like scientific ones is going to turn out poorly.
I came into biology during the late 90's, when systems bio was taking off. Biologists aren't quantitative enough, and therefore we physicists, mathematicians, engineers, computer scientists will show you how it's done. Made lots of models of various processes such as immune responses to stress/insults.
None of them worked in retrospect. Not because the the math or code were wrong. The models themselves were missing key players that we didn't learn about until later. So the field as a whole was wrong (but again all replicable). How would one know that?
More recently, we've been working on a small molecule corrector of p53. We went through all the patents and literature. Almost all of it was wrong when we put everything across a fixed set of assays/cell types. It's not that these papers were all non-replicable, it was just a small part of a bigger picture that those papers didn't have. That's the generous conclusion, the not-so-generous one is that people are just crafting the best story they can, and will often explain away or just not do a negative result.
The problem isn't replicability, it's actually that most scientific results are likely lacking context, don't generalize, and are wrong in the more general sense of the word. There is a range of truth-seeking in practitioners, and it's true the most rigorous truth-seekers aren't always rewarded, but again, this is not something new. That's always been true in science, and well described in book's like Kuhn's Structure of Scientific Revolutions.
The potential solutions involve replication studies and publishing negative results. These things won't help the broader and more general problem. People want this the scientific process to be a very linear path full of incremental improvements that suddenly lead to a change. It's not how it works.
they made the framework laptop into a car
The people spoke. We built. Meet the radically simple, radically affordable Slate. Reserve yours at Slate.auto
Will Owens retweeted
yep boss, the promo video is going great. got the twitching humanoid robot strung up on a meat hook and flickering lights. they’ll love it
"I never see you at the club"
Cool, I never see you at the vegetative electron microscopy core
retractionwatch.com/2025/02/…
When you’re getting a tour through hell and the guide asks you to put your phone away
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