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Thrilled to share my freshly "baked" Baker lab paper. We took a bottom-up approach to designing transcriptional regulators. Instead of relying on natural activation domains, we designed compact proteins that recruit specific cofactors. Activators for now, repressors to come!
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Will Chen retweeted
Our latest, sent on behalf of the outstanding but X-less Aidan Keith: OPTIMuS PRIME-Del uses paired prime editing to program targeted deletions at candidate enhancers, while concurrently replacing them w/ a molecular tag to verify & quantify deletions 1/7
biorxiv.org/content/10.648…
biorxiv.org/content/10.648…
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Will Chen retweeted
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.
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)
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Our compact binders (~65–85 aa) also proved to be potent CRISPRa effectors, outperforming VPR at several endogenous loci. A combination of these binders further boosts transcription activity.
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I would like to thank David @UWproteindesign
for his support and guidance. and @ruopu22 @kinasekid @isaacbhilton and other x-free authors for their help and discussions.
for his support and guidance. and @ruopu22 @kinasekid @isaacbhilton and other x-free authors for their help and discussions.
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@UWproteindesign @ruopu22 @kinasekid @isaacbhilton And most importantly, I need to thank @DamonRunyon for their support on this risky project!
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RFD4 is amazing!
Avengers assemble: 1 year BakerLab + NVIDIA GenAIR = 🔥 rfd4-proteina.org
Presenting RFD4-Proteina, our latest protein design model, significantly better and faster than everything we compared against, both in silico and in the lab! 1/30
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To test this experimentally, we designed p300 KIX binders with affinities ranging from nano- to micromolar and measured their transcriptional activity. We found a switch-like response around 500 nM! Stronger binding beyond this threshold provided little additional activation.
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Kinetic simulations suggest that two TADs engaging distinct interfaces of the same cofactor or cofactor complex can cooperate to achieve efficient recruitment, even when individual interactions are weak.
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Guided by these predicted interfaces, we used RFdiffusion to design proteins that specifically bind cofactors. Using a functional screen in cells, we identified more than 300 binders across 10 cofactors! These binders allow us to recruit cofactors individually or in combination.
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We first used AF3 to systematically map interactions between TADs and transcriptional cofactors. Interestingly, the predictions revealed distinct cofactor-binding preferences. Some cofactors were highly selective, whereas others showed broader interaction profiles.
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TFs recruit cofactors through transcriptional activation domains (TADs). These domains are often intrinsically disordered and engage cofactors through weak, promiscuous interactions. This makes it difficult to dissect and precisely control gene activation.
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Will Chen retweeted
Every cell in our body comes from 1 fertilized egg — & now we can trace that dev. #HHMIInvestigators Jonathan Weissman & Jay Shendure & teams have created new tools that generate maps of the origin & outcome of vast numbers of cells in a developing mouse: bit.ly/4dVhnhe
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What a wonderful day for recording community! Such beautiful paired work mapping the lineage from embryo to mouse! Let's decorate some "trees"
Exciting day for DNA Typewriter w/ 2 papers from the lab & SeaHub out today :)
1. Mouse lineage from E0 to E13.5
science.org/doi/10.1126/sc…
2. A fluctuation test for gastruloid heterogeneity
cell.com/cell/fulltext/…
Paper #1 covered in quoted thread. More on paper #2 here. 1/n
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Will Chen retweeted
Excited to share Shotgun Genetic Engineering, developed by @julie_trolle, out in @NatureBiotech!
Read on to learn how Julie enabled mammalian cells to grow without 2 essential amino acids for the first time in >500 million years using highly multiplexed metabolic engineering!
Read on to learn how Julie enabled mammalian cells to grow without 2 essential amino acids for the first time in >500 million years using highly multiplexed metabolic engineering!
Highly multiplexed mammalian metabolic engineering with a shotgun approach - @sudpinglay @JefBoeke nature.com/articles/s4158…
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Will Chen retweeted
Thrilled to post thread re: new single-cell lineage of mouse embryo reconstructed w/ DNA Typewriter. One animal, zygote to late organogenesis (E13.5). Tree has 1,340,794 transcriptionally profiled, annotated tips (cells), 1,142,588 dated internal nodes, rooted at zygote
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Will Chen retweeted
Could the folding of synthetic gene circuits in 3D shape how genes are expressed? Today @ScienceMagazine we report on the role of gene syntax in shaping feedback between transcriptional activity and genome folding for advanced circuit design🧵 (1/n)
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Will Chen retweeted
New preprint! @JShendure @CXchengxiangQIU Can we learn regulatory grammars of human cell types we'll never be able to profile - by training on mouse development and transferring across 241 mammalian genomes?biorxiv.org/content/10.648…
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