Twitter account for the lab of UC Berkeley Professor @JayKeasling at @JBEI. Tweets by lab members π§¬
Emeryville, CA
Joined August 2017
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Keasling Lab π³οΈβππ³οΈββ§οΈ retweeted
What principles of TF activity have survived a billion years of evolution?
New Shih lab preprint! We used ENTRAP-seq to map activation and repression domains across Arabidopsis TFs and compared their activity in plants and yeast .
πβοΈπ±
biorxiv.org/content/10.64898β¦
Our new paper in @NatureChemistry expands what chemistry living cells can perform, using engineered enzymes for unnatural biosynthesis to generate and transfer nitrenes, producing previously inaccessible nitrogenous compounds. Check it out: nature.com/articles/s41557-0β¦
Keasling Lab π³οΈβππ³οΈββ§οΈ retweeted
We're thrilled to share our new manuscript in @NatureBiotech, led by former postdoc Zilong Wang! We engineered #PolyketideSynthases to produce renewable monomers for plastics with programmable properties, enabling materials-by-design for a circular and sustainable future. 1/2
Keasling Lab π³οΈβππ³οΈββ§οΈ retweeted
Important work by Jay Keasling et al. in Nature Biotechnology, Nature Portfolio
@jaykeasling
@Keasling_Lab
@NatureBiotech
nature.com/articles/s41587-0β¦
We're thrilled to share our new manuscript in @NatureBiotech, led by former postdoc Zilong Wang! We engineered #PolyketideSynthases to produce renewable monomers for plastics with programmable properties, enabling materials-by-design for a circular and sustainable future. 1/2
2/2 The team achieved titers of 1.84 g/L and showed that these #renewablemonomers can be used to create recyclable plastics with tunable thermal and mechanical properties.
Congratulations to the entire team on this incredible achievement!
Read it here: nature.com/articles/s41587-0β¦
Check out our latest research in @J_A_C_S from postdoctoral fellows Dr. @PeterWinegar and Dr. Graham Hudson, where they built a versatile synthetic method to diversify saponins! [1/2] doi.org/10.1021/jacs.6c07628
#Biocatalysis #SyntheticBiology #NaturalProducts #ChemBio #Glycoscience
Excited to share our latest publication in @NatureComms! We developed a PKS-based platform for the controlled biosynthesis of high-energy fuel molecules with tunable cyclopropanation patterns. Congratulations to Dr. Kevin Yin for leading this work!
nature.com/articles/s41467-0β¦
Happy to share our new paper out in #MetabolicEngineering! We developed a strategy to tie redox activity to the growth rate of E. coli. Growth coupling enables enrichment of high-activity variants from large mutagenesis libraries for protein engineering. sciencedirect.com/science/arβ¦
Each year, the Keasling Lab gathers in Lake Tahoe to reflect on our progress, share goals, and think collectively about where our science can have the greatest societal impact. Proud of what we accomplished togetherβthank you to everyone who makes this work possible!
We are proud to have trained many generations of scientists, educators, founders, policymakers, and more! Happy Holidays from the Keasling Lab--with a record of attendees! π May 2026 be full of scientific achievements, education, and social impact. π§¬π
π§: Can you find Jay?
Our latest manuscript, led by @PeterWinegar et al., highlights key advances in microbial terpenoid biosynthesis and how emerging technologies will drive the next generation of designed, new-to-nature molecules. Read it now: sciencedirect.com/science/arβ¦
Keasling Lab π³οΈβππ³οΈββ§οΈ retweeted
Our lab's new paper is out!
We introduce ENTRAP-seq, a high-throughput in planta assay for multiplexed profiling of protein-coding libraries. Using ENTRAP-seq and machine learning, we discovered transcriptional regulators from ~1,500 plant viral genomes.
go.nature.com/4pw5cL1
Excited to share the work of our PhD candidate, Leah Keiser. Leah engineered polyketide synthases (PKSs) to control stereochemistry. Her work provides insights into the biosynthesis of complex molecules with tunable stereocenters π©βπ¬π§ͺCheck it out: pubs.acs.org/doi/full/10.102β¦
Keasling Lab π³οΈβππ³οΈββ§οΈ retweeted
We're excited to share FolDE, a low-N protein optimization method. In simulation, we found that FolDE is 55% more likely to identify top-1% hits than current baseline methods. FolDE is open and can be set up on a personal computer with a single command.
arxiv.org/abs/2510.24053
We're excited to share FolDE, a low-N protein optimization method. In simulation, we found that FolDE is 55% more likely to identify top-1% hits than current baseline methods. FolDE is open and can be set up on a personal computer with a single command.
arxiv.org/abs/2510.24053
This method is now built into Foldy, our lab's open-source protein engineering platform. Other updates: Foldy uses Boltz-2x for structure prediction, runs ESM family models, and is deployable with a single command. Setup instructions: github.com/JBEI/foldy
This work was led by @jacoberts in collaboration with @beneysenbach and @cathyji. It would not have been possible without funding from the United States federal government, via the NIH, NSF, DOE, and AFOSR.