Luke Lambourne

@lukelambourne.bsky.social

Scientist at Dana-Farber Cancer Institute / Harvard Medical School

Yours truly is a proper scientist now! TL;DR: we used AI to redesign parts of essential cell machinery with only 19 canonical amino acids instead of 20. Why? Great thread by @harriswang.bsky.social provides more context and details. Let me talk a bit about the AI design part of this. 1/

Harris Wang@harriswang.bsky.social · 3mo ago

1/ Excited to share our new paper in Science @science.org: “Toward life with a 19-amino acid alphabet through generative artificial intelligence design.” A great collab w/ Sergey's group @sokrypton.org at MIT @columbiasysbio.bsky.social science.org/doi/10.1126/... 🦠🧬🛠️🖥️💥

New work led by Hasan Cubuk: moving from interpreting variants individually to combining both alleles in recessive disease. DMS of >8000 ADSL variants → inferred enzyme activity → additive biallelic scores that track patient phenotypes. Great collab with the Kudla lab! www.cell.com/cell-systems...

Mechanistic modeling of recessive disease through allelic integration of variant effects

Recessive diseases arise from the combined effects of two alleles, yet most variant interpretation methods consider variants individually. Çubuk et al. map more than 8,000 variants in the recessive en...

cell.com

delighted to share our review, out today in @cp-trendsgenetics.bsky.social! check it out if you're curious about how recent advances in technology & biology have contributed to our understanding of how alternative isoforms diversify the proteome.

Trends in Genetics@cp-trendsgenetics.bsky.social · 8mo ago

"Beyond the Gene: Decoding Alternative Isoforms" by Kaia Mattioli (@kaiamattioli.bsky.social) & Martha Bulyk "The degree to which alternative isoforms actually contribute to the complexity of the human proteome in their endogenous contexts has been the subject of much debate..." shorturl.at/YbNoB

Figure 2. Key figure. Possible functional consequences of alternative isoforms.

Excited to share this collaborative review with @dsegre.bsky.social and @devmoy.bsky.social. We discuss common issues with context-specific genome-scale metabolic network models and provide recommendation for future model development.

Daniel Segrè@dsegre.bsky.social · 12mo ago

Just published @cp-trendsbiotech: Flux sampling and context-specific genome-scale metabolic models for biotechnological applications: www.cell.com/trends/biote... by @devmoy, with @fuxmanlab

reposting the 🧵 from the other site that I wrote when the preprint came out: TFs, like most genes, are frequently expressed as a series of multiple distinct isoforms. these isoforms (by definition) differ in sequence -- often in annotated protein domain regions (e.g. DNA-binding & effector domains)

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The STARLING has landed - excited to share new work from @bornanovak.bsky.social and @jefflotthammer.bsky.social in what is also Borna's first Bluesky post! If you're at BPS, I'll be speaking about this this afternoon in IDP SG, and Borna and Jeff both have posters (Sunday B112 and Wed B152).

Borna Novak@bornanovak.bsky.social · last yr.

Excited to announce the newest member of the flock - STARLING (conSTruction of intrinsicAlly disoRdered proteins ensembles efficientLy vIa multi-dimeNsional Generative models). www.biorxiv.org/content/10.1...