Gene-Wei Li's lab @MITBiology, studying the quantitative biology of gene expression. Account run by lab members.
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In our latest study, published in @MolecularCell, we reveal that mRNA sequences hundreds of nucleotides from the start codon can act as potent repressors of gene expression through long-range base pairing to the ribosome binding site (RBS)... (1/4)
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While bacterial gene expression was known to be strongly influenced by local mRNA secondary structure, our findings now establish that long-range mRNA folding is a conserved force shaping gene expression and constrains sequence evolution. (3/4)
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Link: cell.com/molecular-cell/abst…
@ElsevierConnect free share link: authors.elsevier.com/c/1nkzn…
@ScienceMIT @MITBiology @hhmi_science (4/4)
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Gene-Wei Li Lab retweeted
Excited to announce that the Rikki Garner lab has opened its doors in beautiful Austin, TX! Our interdisciplinary lab @UTAustin @UT_MBS investigates tissue fluidity as a universal physical regulator of multicellular patterning in health and disease. rikkigarnerlab.org/ 1/n
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Excited to celebrate former Li Lab postdoc @bioSavinov opening his own lab at @UTAustin!
Congratulations to Andrew and the Savinov lab — you're already doing amazing science, and we can't wait to see what's next.
Thrilled to announce that the Savinov lab is now live at @UTAustin! Our lab @UT_MBS employs massively parallel experimental and AI methods to discover and design protein fragments as universal regulators of protein interactions in health and disease. savinovlab.com/ (1/n)
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We're excited to share our latest publication, from graduate student Julia Dierksheide in the lab! In B. subtilis, the fast-moving RNA polymerase outpaces the leading ribosome, leaving mRNA transcripts vulnerable to the transcription termination factor Rho. (1/2)
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Here we show that widespread biases in coding strand sequence composition allow mRNAs to escape premature termination, while simultaneously suppressing antisense transcription -- sculpting bacterial genomes across lineages. nature.com/articles/s41564-0…
@MITBiology @hhmi_science (2/2)
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Gene-Wei Li Lab retweeted
Check out this fantastic new paper spearheaded by my postdoc colleague Bob Battaglia @RNABob! With Ebru Ermis and Expery Omollo @expery_.
This work reveals a previously hidden element defining the core regulatory grammar of transcription termination.
Thrilled to announce our latest work, from postdoctoral fellow Bob Battaglia @RNABob in the lab! Transcription termination is a key determinant of gene expression. However, the sequence grammar defining transcription termination has long been elusive. (1/2)
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Thrilled to announce our latest work, from postdoctoral fellow Bob Battaglia @RNABob in the lab! Transcription termination is a key determinant of gene expression. However, the sequence grammar defining transcription termination has long been elusive. (1/2)
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Here, we employ precise termination site mapping on a massively parallel scale to reveal the HUB (hairpin, U-tract, & bubble-edge sequences) as the defining element of intrinsic terminators, across diverse bacterial phyla.
@MITBiology @hhmi_science (2/2)
biorxiv.org/content/10.64898…
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Excited to share our recent work expanding our understanding of transcription termination, from Jenny Cascino in the lab! Here we show that transcription termination in cyanobacteria proceeds largely outside of known, canonical mechanisms.
journals.asm.org/doi/10.1128…
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Great to collaborate with @BabitzkePaul and Katsuhiko Murakami on this work.
@MITBiology @ScienceMIT @MIT @hhmi_science (2/2)
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Thrilled to share the latest from @bioSavinov, K99 fellow in the lab & corresponding on this work together w/ @LinsdayCase19. Andrew & @jibin_sadasivan show that protein fragments discovered with our FragFold AI method act as generalizable regulators of biomolecular condensates!
Interested in genetically encodable inhibitors of your favorite biomolecular condensate? Excited to announce our latest work, w/ @jibin_sadasivan, @GeneWeiLiLab, & @LindsayCase19, on protein fragments as generalizable regulators of phase separation. (1/n)
biorxiv.org/content/10.64898…
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Gene-Wei Li Lab retweeted
What a fantastic visit. Thanks to @omenndarlingbio and @PrincetonMolBio for hosting!
Today we and @PrincetonMolBio welcome Andrew Savinov (@bioSavinov) from @MIT for a special seminar on “Massively parallel discovery of peptides to control cellular protein interactions”
ALT Andrew Savinov at front of lecture hall
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Gene-Wei Li Lab retweeted
Thrilled to contribute to this exciting work on protein binder design together w/ @HannesStaerk, @felix_faltings, @BarzilayRegina, Tommi Jaakkola, and co. We applied BoltzGen to design novel antimicrobial peptides targeting DNA gyrase based on inhibitory protein fragments. (1/n)
Excited to release BoltzGen which brings SOTA folding performance to binder design! The best part of this project has been collaborating with many leading biologists who tested BoltzGen at an unprecedented scale, showing success on many novel targets and pushing its limits! 🧵..
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Gene-Wei Li Lab retweeted
Agreed, Yunha. Fantastic to discuss the interplay of AI & biology with you, Teja, & great attendees @BostonBacteria. Many thanks to David for moderating.
Opportunities for new discoveries are vast, esp. if we keep pushing systematic experimental measurements alongside AI models!
Grateful for the opportunity to speak at the @BostonBacterial Meeting yesterday on a panel about how we can best apply AI to microbiology research!
Much of the discussion was focused on how existing AI tools can help researchers. But perhaps the more important question we should be asking ourselves as researchers is how the data that we generate in our labs can improve the very AI tools we use.
Building a living infrastructure of biological data that evolves real-time with scientific progress is more critical than ever. Stay tuned for updates on what we are building next at @tatta_bio : tattabio.substack.com/p/toda…
Big thanks to David Giacalone, @bioSavinov & Teja Jammalamadaka for keeping the conversation engaging!
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An exciting step towards connecting proteomes with one of the most basic phenotypes of a cell! Work led by @scottmccain5 w/ @GeneWeiLiLab @gregorybritten Sean Hackett and Mick Follows. @MIT @MITBiology @HHMINEWS
What are cells doing?? Here we showed that proteomic composition encodes information about cellular reaction rates. This is a step forward to reconstructing these important activities using protein-based observations.
academic.oup.com/ismej/advan…
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Gene-Wei Li Lab retweeted
Hot on the heels of excellent work from @SvenssonLab, more evidence of large-scale generation of functional protein fragments by proteolysis nature.com/articles/s41586-0…
Very exciting to see this convergence with our work showing pervasive function of protein fragments in vivo! (1/2)
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Gene-Wei Li Lab retweeted
Fantastic to see these physiologically functional protein fragments, congrats all!
This aligns with our work demonstrating pervasive functionality of protein fragments in living cells (& ability to predict their binding partners): pnas.org/doi/10.1073/pnas.23… pnas.org/doi/10.1073/pnas.22…
Today in @Nature, we share our latest paper. We developed an algorithm to predict novel peptides cleaved by proconvertases across all human tissues. Using this method, we identified BRP, a brain-derived anti-obesity peptide.
nature.com/articles/s41586-0…
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