Kosuke Seki

i kill a lot of e coli. protein design, cell free systems, genetic code expansion. currently postdoc @kortemmelab, phd with @michaelcjewett

[Asimov Press @AsimovPress]

New Essay: Inventing the Methods Section

Many science methods are difficult to understand or replicate. The U.S. alone invests ~$28 billion annually in irreproducible biomedical research.

How have methods evolved over four millennia, and how can we make them better? By @Andrew_C_Hunt.

Read: https://t.co/S2cSKwhror

[Kosuke Seki @kosuke_seki]

There's also lots of other interesting findings: many orthogonal tRNAs for UAG and UGA, a candidate Gln-based OTS for UAG, and a useful in vitro method to express tRNAs very easily.

[Kosuke Seki @kosuke_seki]

We discovered a new orthogonal translation system specific for the UGA codon and engineered it to incorporate non-canonical amino acids. I am so grateful to my collaborators Petar, Michael, Farren, and Jill who contributed incredible work. Check it out!

[bioRxiv Synthetic Biology @bioRxiv_synbio]

Engineered orthogonal translation systems from metagenomic libraries expand the genetic code https://t.co/mgojp3E2cb #biorxiv_synbio

[Michael C. Jewett @MichaelCJewett]

In a wonderful collaboration with Farren Isaacs and Jill Banfield, Kosuke Seki led work to discover a new orthogonal translation system from metagenomic data that suppresses the UGA codon, and then demonstrated we could evolve it.

https://t.co/2yaRJqbxN6

[bioRxiv Synthetic Biology @bioRxiv_synbio]

Engineered orthogonal translation systems from metagenomic libraries expand the genetic code https://t.co/mgojp3E2cb #biorxiv_synbio

[Kosuke Seki @kosuke_seki]

Some new work from my postdoc about using deep learning to learn about sequence-function relationships!

[biorxiv_biochem @biorxiv_biochem]

A combinatorial mutational map of active non-native protein kinases by deep learning guided sequence design https://t.co/sAnzQMXuUs #biorxiv_biochem

[biorxiv_biochem @biorxiv_biochem]

A combinatorial mutational map of active non-native protein kinases by deep learning guided sequence design https://t.co/sAnzQMXuUs #biorxiv_biochem

[Andrew Hunt @Andrew_C_Hunt]

Curious about cell-free systems? Check out our new review in @ACSChemRev! This is the guide I wish I’d had when I started my PhD. Grateful to my coauthors and reviewers for helping tackle this giant project. We hope you find it helpful!

https://t.co/OdzefKw2LO

[Michael C. Jewett @MichaelCJewett]

Congrats ⁦@NUSynBio⁩ ⁦@NorthwesternEng⁩ grads!

[Kosuke Seki @kosuke_seki]

I was lucky enough to contribute to Frame2seq and help show how it can be used to access protein sequences far from outside of native ones. Cool stuff is upcoming 👀

[Deniz Akpinaroglu @DenizAkpinaro]

Super excited to share our model Frame2seq and our preprint “Structure-conditioned masked language models for protein sequence design generalize beyond the native sequence space” https://t.co/Rs6IsTQSwY 1/n

[Kosuke Seki @kosuke_seki]

Excited to see my work on engineering enzymes with non-canonical amino acids out. Very thankful for an awesome collaboration with my co-authors!

[Michael C. Jewett @MichaelCJewett]

What's your favorite strategy to dynamically control protein function in #synbio? Just out @NatureComms. @NUSynBio and @JCLewisLab show we can use metal-responsive chemical switches, enabled by non-canonical amino acids and a #cellfree workflow.

https://t.co/oIXYPllxRC

[Kosuke Seki @kosuke_seki]

Some of my work on engineering enzymes in cell-free with non-canonical amino acids is available to read. Very excited to see this work come out and very thankful for my partners in crime, Yasmine and Ying, for everything!