Alberto Bégué

Research Engineer @instadeepai Bio AI

[Karim Beguir @kbeguir]

Ai Day last week was a blast! I had a great time presenting alongside many colleagues from @instadeepai and @BioNTech_Group, some of our ongoing Bio+AI initiatives.

We made several announcements, introducing Kyber, our new supercomputing cluster (more on this soon), as well as BFN, our new paradigm for generative AI, with competitive results on protein and antibody generation.

During Ai Day we also delivered two live demos of Laila, our new AI agent, including one from BioNTech's TechLab in Mainz, Germany!

To our knowledge, this was one of the first demos of its kind featuring a GPT-4 level AI agent acting in the Lab, interacting with scientists and technicians and helping them enhance their productivity!

Ai Day was a significant moment for all of us, and it was exciting to see both the event and Laila featured by several publications including @FT (https://t.co/rhs9VSxDx3).

Curious to see it in action? Check out the recording of the Laila in the Lab demo below, worth watching and don't miss the end! 😉

[Alberto Bégué @Alberto_Begue_]

@ChalumeauFelix @instadeepai @RefiloeShabe @ArnuPretorius @tomdbarrett @NGrinsztajn Congrats buddy 😍

[Patrick Collison @patrickc]

This morning, Nature published two papers on bridge editing, the new genome engineering technology from @ArcInstitute: https://t.co/IL23V7nYoW, https://t.co/tOE10YZakn. I'm quite excited about its potential!

Since the whole thing is pretty arcane, I fed the blog post (https://t.co/tZZWNRUBdU) to Claude 3.5, and asked it to write an introduction. Below is the rather impressive (unedited) result.

Genome Design: The Bridge to Our Biological Future

I.

Imagine you're trying to edit a document, but instead of a cursor, you have a pair of scissors. You can cut out words you don't like, maybe paste in a few new ones, but precise editing? Forget about it. Now imagine someone hands you a pen. Suddenly, you can write whatever you want, wherever you want. This is the kind of leap we're seeing in the world of genome editing.

For the past few decades, we've been snipping away at genomes with tools like CRISPR, making impressive progress but always constrained by the fundamental nature of our tools: they cut DNA. But what if we could write directly into the genome, inserting whatever we want, wherever we want, without ever making a single cut?

This isn't just a "wouldn't it be nice" daydream anymore. Researchers at the Arc Institute have discovered a new system that does exactly that. They're calling it "bridge recombination," and it might just be the biggest revolution in genetic engineering since CRISPR.

II.

To understand why this is such a big deal, we need to take a quick tour through the history of genetic manipulation.

In the late 1990s, we discovered RNA interference (RNAi). This was our first real taste of programmable biology. We could use short RNA sequences to target and shut down specific genes. It was like having a universal remote control for gene expression. Cool, right?

Then came CRISPR in the early 2010s. Suddenly, we could not just turn genes off, but edit them directly. It was like upgrading from a remote control to a basic text editor. We could cut out bad genes and paste in good ones. But there was always a catch: CRISPR works by cutting DNA, and cells don't always repair those cuts exactly the way we want them to.

Both of these systems were revolutionary, but they shared a common limitation: they were destructive. They worked by breaking things – either the RNA transcripts of genes (in the case of RNAi) or the DNA itself (in the case of CRISPR).

III.

Enter the bridge recombination system.

The researchers at Arc Institute, led by Dr. Patrick Hsu, were poking around in the genomes of bacteria, looking at transposable elements. These are sometimes called "jumping genes" because they can cut themselves out of one part of a genome and paste themselves into another.

They were particularly interested in a group called IS110 elements. These are about as minimalist as you can get while still being functional – just a gene for the enzyme that does the cutting and pasting, plus some mysterious flanking DNA segments.

What they found was surprising. When an IS110 element cuts itself out of a genome, those mysterious flanking segments join up to form an RNA molecule. This RNA folds into two loops, one that binds to the IS110 element itself, and another that binds to the target DNA where the element will insert itself.

This RNA – which they've dubbed "bridge RNA" – is the key to the whole system. It's like a set of instructions, telling the enzyme exactly where to insert the DNA and what DNA to insert.

IV.

Now, you might be thinking, "Okay, that's neat, but how is this different from CRISPR?" The key is in how the insertion happens.

CRISPR works by making a cut in the DNA and then relying on the cell's repair mechanisms to insert the new DNA. It's effective, but it's also a bit like performing surgery with a chainsaw. Sometimes you get exactly what you want, but often you end up with small errors or unwanted insertions or deletions.

The bridge recombination system, on the other hand, doesn't cut the DNA at all. It unzips a small section, inserts the new DNA, and zips it back up again. No broken DNA strands, no relying on error-prone repair mechanisms. It's precise in a way that CRISPR can only dream of.

But the real magic is in the programmability. Remember those two loops in the bridge RNA? They can be programmed to recognize any DNA sequence. This means you can tell the system to insert any piece of DNA into any location in the genome. It's like having a word processor for DNA.

V.

The implications of this are staggering. Here are just a few possibilities:

• Gene Therapy 2.0: Current gene therapy approaches often rely on somewhat random insertion of therapeutic genes. With bridge recombination, we could insert corrective genes exactly where they need to go, without risking disruption of other important genes.
• Synthetic Biology: Want to give an organism a completely new capability? Just design the gene and insert it precisely where you want it.
• Evolutionary Biology: We could insert reporter genes at specific locations across the genome, allowing us to watch evolution happen in real time.
• Agricultural Improvements: We could insert beneficial genes into crops with unprecedented precision, potentially revolutionizing our ability to create drought-resistant or nutrient-enhanced plants.
• Bioengineering: Imagine being able to design and build entire genetic circuits, inserting each component exactly where it needs to be for optimal function.

VI.

In the grand scheme of things, the discovery of bridge recombination feels like a pivotal moment. It's as if we've been trying to write the book of life with a typewriter, and someone just handed us a word processor.

The researchers at Arc Institute have opened a door to a new era of genome design. As with any breakthrough of this magnitude, it's hard to predict exactly where it will lead. But one thing is certain: the future of biology just got a lot more interesting.

As we stand on the brink of this new frontier, I'm reminded of a quote from Arthur C. Clarke: "Any sufficiently advanced technology is indistinguishable from magic." With bridge recombination, we're not just editing the genome anymore. We're writing it. And that, my friends, is pretty close to magic.

[Alberto Bégué @Alberto_Begue_]

@julien_c And I was born to be fast, I was born to run 🎶

[InstaDeep @instadeepai]

We're proud to be empowering the next generation of AI talent🎦Now you can watch the full documentary #CapeToCarthage at https://t.co/22PTUpbw6s

[Alberto Bégué @Alberto_Begue_]

@Rainmaker1973 What was between 3 and 4 in the XV century? 😅

[InstaDeep @instadeepai]

It’s official! 🎉Today InstaDeep becomes a proud member of the BioNTech family. Want to apply your AI skills to make a difference? Join us, we’re hiring!

[Alberto Bégué @Alberto_Begue_]

@yudapearl @HannesMalmberg1 This is GPT-4 from OpenAI (with a « Plus » membership). I just tried this example too and it’s pretty robust e.g. it answers correctly to « What if A and the prisonner are the same person? ». But this isn’t proof it’s actually performing counterfactual reasoning.

[Thomas Pierrot @thomas_pierrot]

We are happy to open-source our 4 Nucleotide Transformer models, the new SOTA genomics #LLMs 🧬. This has been an amazing journey involving many teams inside @instadeepai and @nvidia 🙌. Want to work on a project like this one? Contact me or check out directly our open positions.

[InstaDeep @instadeepai]

1/ We are happy to announce the open-source release of the inference code and weights of our four genomics #LLM, the nucleotide transformers, ranging from 500M to 2.5B parameters, trained in collaboration with @nvidia and @TU_Munchen 🧬
https://t.co/3iniH4ZjCK

[Alberto Bégué @Alberto_Begue_]

Big news at the office today!

[InstaDeep @instadeepai]

Our mission to build AI that benefits everyone just took a giant leap forward! @BioNTech_Group is to acquire InstaDeep in a £362M deal🚀to accelerate AI-driven discovery, design & development of next-gen immunotherapies & vaccines at global scale!🌍1/N https://t.co/OHFI70khhx

[BioNTech SE @BioNTech_Group]

We aim to strengthen the “tech” in BioNTech with our agreement to acquire @instadeepai to support our strategy to build world leading capabilities in #AI- and #ML-driven #drugdiscovery and development of next-generation immunotherapies and vaccines. https://t.co/xIfF7mvZMB

[InstaDeep @instadeepai]

2022 was an incredible year for InstaDeep!
From start to finish, the year was filled with achievements and successes.

We're grateful for this past year and are ready for even more growth in 2023!

Read our end of year recap here: https://t.co/xNq9dua1J3

[Amelia Villegas @amelvim_]

Happy to share our ManyFold paper, now published on @OUPBioinfo! https://t.co/hnoV4CBZIX

This work is part of my internship at @instadeepai, with amazing collaborators @tomdbarrett @LouisBRobinson @arthur_flajolet.

[Alberto Bégué @Alberto_Begue_]

@drchristhorpe Thank you @drchristhorpe but we cannot share them, I'm afraid.

[Alberto Bégué @Alberto_Begue_]

Our work on leveraging GNN for peptide-MHC structure prediction has been accepted @workshopmlsb!

📜https://t.co/p8PmlrXjrP
TLDR: Some biological constraints are better respected by our GNN's predictions than by AlphaFold's, while achieving similar accuracy with fewer parameters

[InstaDeep @instadeepai]

In “Peptide-MHC Structure Prediction With Mixed Residue and Atom Graph Neural Network” (accepted at @workshopmlsb) with @BioNTech_Group, we introduce a GNN to predict pMHC structures with comparable results to AlphaFold 2 with <2% of its parameters. https://t.co/2LrjJZTlTJ (5/7)

[Alberto Bégué @Alberto_Begue_]

It's been a very exciting few months for me since I joined @instadeepai. The team (@ap_dln, @mathpluscode, @robert_mchardy and many others) is extremely talented and we're working on fascinating challenges. I'm very proud to be (a small) part of it!

P.S: We're recruiting ;)

[Alberto Bégué @Alberto_Begue_]

@workshopmlsb By similar accuracy, we mean in terms of backbone RMSD and by biological constraints, we mean binding pocket distances and energy scores.

[InstaDeep @instadeepai]

If you are at the #AIforHealthSummit at @joinstationf this week, come and say hello! We're talking about everything BioAI at our booth, and @NicoLopezCarran has also presented a corporate masterclass on the lessons learnt from our extensive experience in decision-making AI.

[InstaDeep @instadeepai]

1/ We’re happy to announce our latest contribution to the open-source ecosystem and RL community! We are releasing Jumanji, a suite of Industry-Driven Reinforcement Learning environments written in #JAX

📚 Doc: https://t.co/5lO8wMsLU8
⭐ Github: https://t.co/XCU7QAH43u