Brian Hie

Milot’s venture into establishing his own lab is incredibly excitinge. I highly recommend to join Milot on his mission to advance molecular biology through open-source bioinformatics.

Semantic design of functional de novo genes from a genomic language model - Nature By learning a semantics of gene function based on genomic context, the genomic language model Evo autocompletes DNA prompts to generate novel genes encoding protein and RNA molecules with defined activities, whose sequences generalize beyond those found in nature.

Nature research paper: Semantic design of functional de novo genes from a genomic language model

go.nature.com/48uEnAn

Immunopeptidomics can inform the design of mRNA vaccines for the delivery of Mycobacterium tuberculosis MHC class II antigens MHC class II immunopeptidomics in human phagocytes infected with Mycobacterium tuberculosis enables vaccine immunogen design and optimization.

Excited to share our newest manuscript on antigen discovery and vaccine design for tuberculosis lead by Owen Leddy (everyone hiring new faculty in a few years, remember this name!)

www.science.org/doi/10.1126/... #TBsky

Systems analysis reveals alternate metabolic states adopted by Mycobacterium tuberculosis across species Mycobacterium tuberculosis (Mtb) persists within macrophages, yet how different host species shape bacterial state remains poorly understood. Here, we directly compared the intracellular transcriptome...

Excited to share our lab's newest preprint (strap in if you're excited about metabolism, species differences, or Mtb gene expression): www.biorxiv.org/content/10.1...

Published today in @nature.com, @adititm.bsky.social & researchers from the @brianhie.bsky.social lab report that the large-scale genomic model, Evo, is capable of using surrounding genomic context to produce novel, functional genes, enabling an an emergent approach they've termed 'semantic design'.

What if we could autocomplete DNA based on function?

Today in @Nature, we share semantic design—a strategy for function-guided design with genomic language models that leverages genomic context to create de novo genes and systems with desired functions. 🧵

www.nature.com/articles/s41...

Aditi Merchant on X: "What if we could autocomplete DNA based on function? Today in @Nature, we share semantic design—a strategy for function-guided design with genomic language models that leverages genomic context to create de novo genes with desired functions.🧵 https://t.co/P5qVJB3qIY https://t.co/VTBYNdERzR" / X What if we could autocomplete DNA based on function? Today in @Nature, we share semantic design—a strategy for function-guided design with genomic language models that leverages genomic context to create de novo genes with desired functions.🧵 https://t.co/P5qVJB3qIY https://t.co/VTBYNdERzR

See this thread by @adititm.bsky.social for more information about the paper!

x.com/aditimerch/s...

Today in @nature.com, in work led by @adititm.bsky.social, we report the ability to prompt Evo to generate functional de novo genes.

You shall know a gene by the company it keeps!

Combine multimer structure prediction and an antibody language model to design de novo antibodies with nanomolar binding affinity.

@synbiogaolab.bsky.social @brianhie.bsky.social

www.biorxiv.org/content/10.1...

Having often dealt with the frustration of binder-limited projects, we sought a more accessible source for nanobodies than yeast display or llama. Here we introduce Germinal, computationally designing antibody-like binders with such a hit rate that only tens need to be screened for each target.

In another preprint from the @brianhie.bsky.social Lab and @synbiogaolab.bsky.social, they introduce Germinal, a generative AI system for de novo antibody design.

Germinal produces functional nanobodies in just dozens of tests, making custom antibody design more accessible than ever before.

Generative design of novel bacteriophages with genome language models Many important biological functions arise not from single genes, but from complex interactions encoded by entire genomes. Genome language models have emerged as a promising strategy for designing biol...

A landmark paper from Brian Hie’s group at the Arc Institute. The de novo design of the synthetic genome of an entirely novel biological entity

www.biorxiv.org/content/10.1...

Genome language models can generate new, high-fitness bacteriophages!

@samuelhking.bsky.social @claudiadriscoll.bsky.social
@david-li.bsky.social @danguo.bsky.social @adititm.bsky.social Garyk Brixi @maxewilkinson.bsky.social @brianhie.bsky.social

www.biorxiv.org/content/10.1...

Generative design of novel bacteriophages with genome language models Many important biological functions arise not from single genes, but from complex interactions encoded by entire genomes. Genome language models have emerged as a promising strategy for designing biol...

This is super cool from @brianhie.bsky.social et al-
Generative design of novel bacteriophages with genome language models www.biorxiv.org/content/10.1...

In a new preprint from @brianhie.bsky.social's lab, the team reports the first generative design of viable bacteriophage genomes.

Leveraging Evo 1 & Evo 2, they generated whole genome sequences, resulting in 16 viable phages with distinct genomic architectures.

Many of the most complex and useful functions in biology emerge at the scale of whole genomes.

Today, we share our preprint “Generative design of novel bacteriophages with genome language models”, where we validate the first, functional AI-generated genomes 🧵

#AI is transforming #biology, enabling rapid innovation — but with progress comes risk.

A new National Academies report examines how AI-driven biological tools could impact #biosecurity, from potential misuse to their role in risk mitigation.

Read: buff.ly/2unawE4

YouTube video by Valence Labs Genome modeling and design across all domains of life with Evo 2 | Garyk Brixi

Video is up!
"Genome modeling and design across all domains of life with Evo 2" youtu.be/Rarn97Wpl1A
With the author Garyk Brixi!

Overview of evo2

Evo2: a fully open genome language model that can predict the functional effects of variation and generate large genomic segments

@garykbrixi.bsky.social @matthewdurrant.com @michaelpoli.bsky.social @genophoria.bsky.social @pdhsu.bsky.social @brianhie.bsky.social

www.biorxiv.org/content/10.1...

FAMPNN architecture

All-atom fixed backbone protein sequence design with FAMPNN

@richardshuai.bsky.social Talal Widatalla @possuhuanglab.bsky.social @brianhie.bsky.social

www.biorxiv.org/content/10.1...

Paper: arcinstitute.org/manuscripts/...

Blog: arcinstitute.org/news/blog/evo2

GitHub: github.com/ArcInstitute...

We trained a genomic language model on all observed evolution, which we are calling Evo 2.

The model achieves an unprecedented breadth in capabilities, enabling prediction and design tasks from molecular to genome scale and across all three domains of life.

The Poetry Fan Who Taught an LLM to Read and Write DNA | Quanta Magazine By treating DNA as a language, Brian Hie’s “ChatGPT for genomes” could pick up patterns that humans can’t see, accelerating biological design.

Brian Hie harnessed the powerful parallels between DNA and human language to create an AI tool that interprets genomes. Read his conversation with Ingrid Wickelgren: www.quantamagazine.org/the-poetry-f...

Thanks Eric!

The 2024 Good Tech Awards, spotlighted by @kevinroose.com for #AI/Science
nytimes.com/2024/12/30/t...
congrats!
@arcinstitute.org @brianhie.bsky.social @patrickhsuu.bsky.social @jameszou.bsky.social and the others for well deserved recognition

Institute Scholar Peter Kim, Brian Hie, Varun Shanker, and team’s new AI approach optimizes development of antibody drugs.

#YearInReview An AI-based method to develop better antibody medicines faster: https://buff.ly/3P74SCo
@brianhie.bsky.social

New @biorxiv-synthbio.bsky.social on #Evo 👀⤵️🧵 introducing Evo 1.5 for semantic mining + SynGenome - an AI-generated genomics database #AI #synbio #LLM🧬 @adititm.bsky.social @brianhie.bsky.social et al. @arcinstitute.org

Yes they appear to be having server problems, here is a link to the paper PDF: evodesign.org/Semantic_Min...

Excited to have the first project of my PhD out!! By leveraging genomic language model Evo’s ability to learn relationships across genes (i.e., "know a gene by the company it keeps"), we show that we can use prompt-engineering to generate highly divergent proteins with retained functionality. 🧵1/N

In-context genomic modeling and design with Evo.

120 billion base pairs of AI-generated genomic sequences with SynGenome.

Evo generates functional anti-CRISPR proteins with no homology to known proteins.

Evo generates functional toxin-antitoxin protein-protein interactions with remote homology to nature.

A protein's position in the genome in relation to other genes is informative about function, so a genomic language model can be prompted to generate
- toxin/antitoxin pairs
- anti-CRISPR proteins

+ a database of 120B synthetic base pairs

www.biorxiv.org/content/10.1...

@brianhie.bsky.social