Geonhu Lee

Ph.D., Synthetic biologist, Postdoctoral Scholar @synbiogaolab at @Stanford

[Christopher Reinkemeier @ReinkemeierCD]

Ever wondered what a cell has experienced in the past? This is in general hard to measure. Here we introduce the recordanelle, to equip cells with a tool that lets them record their own history.
https://t.co/JVM3yOit8s
@NatureBiotech @ETH @randall_platt @ETH_BSSE

[Geonhu Lee @Geonhu_Lee]

My favorite is the renin engineering work. I still remember the shock I felt when I joined the lab and saw the wet-lab data.

[Geonhu Lee @Geonhu_Lee]

Many AI-based protein design and engineering examples are exciting, but what we really want to see is success in areas that have been difficult to tackle with existing approaches.
They present a simple, powerful framework with truly impressive applications.

[Xiaowei Zhang @Xiaowei0402]

We deimmunized a clinical CD19 CAR binder with experimentally detected HLA-I epitope depletion while retaining tumor killing, and rescued a secreted protease to function in the cytosol.

Both done with one unified design framework: ProVADA.

How it works and what we tested 🧵 (1/11)

[Xiaowei Zhang @Xiaowei0402]

We deimmunized a clinical CD19 CAR binder with experimentally detected HLA-I epitope depletion while retaining tumor killing, and rescued a secreted protease to function in the cytosol.

Both done with one unified design framework: ProVADA.

How it works and what we tested 🧵 (1/11)

[Xiaojing Gao @SynBioGaoLab]

Numerous biotech innovations started with adapting a protein to its non-native context, which often requires substantial experimental optimizations. Here’s a breakdown by our lead, @Xiaowei0402, on a versatile, efficient computational framework to facilitate such adaptations.

[Ben Viggiano @bviggiano_13]

Very excited to release ProVADA! It was so much fun working with the incredible @Xiaowei0402, @sluu_06, and the rest of the team. Check out Xiaowei's thread for more details!

[Xiaowei Zhang @Xiaowei0402]

Lastly, it’s indeed an intellectual inspiring journey working on this multidisciplinary project with everyone in this amazing team!

Can’t be more grateful to the co-leads: @sluu_06 on the algorithmic and statistical foundation, and @bviggiano_13 on the codebase and benchmarks!

Special thanks to Laura Yang and Prof. @BingfeiY for supporting ESCAPE-seq; Kevin Reynolds and Elena Sotillo with Prof. Crystal Mackall for all the CAR-T experiments; @sophiaburick, @haoyu_dai_dhy and @santimillef on the renin designs and validations; as well as @Geonhu_Lee and Zi for deimmunization validations!

In the end, huge thanks to Xiaojing and Wing, this work would not be possible without your guidance and dedication!

Read the preprint: https://t.co/ANibUVz4RD
(11/11)

[Karen Zhang @thekarenzhang]

Out now in Molecular Cell! Retrons protect bacteria from phage infection, and this one has one of the craziest mechanisms we’ve ever seen. (1/8) https://t.co/LXIxdKtNC0

[Jihoon Han @jihoon_han_phd]

Detectrons are now published in Nature Biotechnology!
Programmable RNA sensing meets DNA barcode production in living bacteria.
https://t.co/MravsG9pdx

[Xiaojing Gao @SynBioGaoLab]

Congrats, Brian and team. It never ceases to amaze me what you guys can do with the language models!

[David Li @_David_Li]

Excited to share Minerva, our approach using genome language models for biological discovery! Using Minerva, we find that UG27 reverse transcriptase systems encode variable arrays of diverse ncRNAs with a shared structure, each templating a short DNA hairpin. With @garykbrixi.

[Brian Hie @BrianHie]

Cool to see Germinal successfully design VHH antibodies with in vivo protection against cobra venom. Congrats to the team!

https://t.co/DMmyk84zCN

[Brian Hie @BrianHie]

You can now use Proto in ChatGPT!

Here is de novo nanobody design with Germinal (https://t.co/OSjF4ao1I2) and semantic design with Evo 2 (https://t.co/xbX9iUyb6i).

Check out the Rosalind Workbench Research Preview: https://t.co/0PZtDS8PhP

[Samuel King @samuelhking]

Today in @ScienceMagazine, we report the first functional AI-generated genomes. 🧵

https://t.co/HCwWfenIc0

[Arc Institute @arcinstitute]

One of our most popular preprints of 2025 is now published in @ScienceMagazine. Congrats to @BrianHie, @samuelhking, and team on establishing a framework for generating and evaluating AI-generated genomes.

- Access the paper: https://t.co/p5qMhTroK2

[Xiaojing Gao @SynBioGaoLab]

Heading to mSBW? Check out work by @cnnrcall (Poster 47, genetically encoded urinary reporter to noninvasively monitor live molecular events), JS (Poster 46, efficient biophysical design of orthogonal DNA duplex libraries), and @mengzhang668 (talk, ablating cancer using RADAR).

[nature @Nature]

Nature research paper: Diverse bacterial pattern recognition receptors sense the core phage proteome

https://t.co/tvTTGefi2f

[Yang Liu @YangLiu_LMB]

When we talk with AI researchers, one question comes up most frequently: do you have datasets focused on mutations at key protein positions?

Until now, building libraries for that usually meant a lot of DNA synthesis. We developed HGT-DGR as a faster and cheaper way to make them.
https://t.co/MWiRth0OU6

[Seth Shipman @seth_shipman]

Been working on a really strange retron bacterial immune system, here's the preprint: https://t.co/iWP8qH1Fe7
Type VI retrons are unlike any other. Phage infection triggers reverse transcription of a DNA fragment that activates translation of a toxin to kill the infected cell.

[Nature Biotechnology @NatureBiotech]

Discovery and engineering of retrons for precise genome editing - @IlyaFinkelstein https://t.co/cJ3IxI5OWn