Jazz Ghataora, PhD

PDRA in the Tom Ellis Lab @ImperialCollegeLondon exploring environmental synthetic biology things 🧬

[Holobiont/Hologenome @Hologenomes]

Fact: 2026 will be the most prolific year to date 📶

[Eric Kernfeld @ekernf01]

this is fucking amazing. https://t.co/Z18T2bDEt5

[Jazz Ghataora, PhD @JazzSynBio]

This is actually incredible!!!!!!!

[Huang_Nanopore @Huang_Nanopore]

New Huang lab publication at Nature. Our newly developed technique: transient Pore Analyte Looping (tPAL) now achieves “chop and measure” nanopore sequencing of peptide, in an amino acid by amino acid manner. https://t.co/YMUPMckpnx

[good papers @paperperday]

De Novo Design of Protein Nanopores:
From Minimal Peptides to AI-Driven Design
https://t.co/bHy2CISaUv

[Holobiont/Hologenome @Hologenomes]

We are a holobiont partially running on a light-based operating system. Sun exposure calibrates your entire gut microbiome, skin, and brain via melanin.

https://t.co/0krluBlbE9

[Ran Blekhman @blekhman]

Claude Science is incredible. I gave it some sequencing data, and in 8 hours it did a full analysis, generated figures, wrote a paper, submitted it for publication, got rejected, revised and resubmitted, got rejected again, it is now applying for positions in industry

[Andrew—#IAmTheResistance @AmoneyResists]

When you don’t realize that hydrogen peroxide is a paint remover…☠️

[Sebastian S. Cocioba🪄🌷 @ATinyGreenCell]

I made a webpage to try SpliceCraft out directly in your browser in a little sandbox. No download or install needed to try it. Gonna make a tutorial mode to walk people through the features soon. Enjoy!

https://t.co/ksJhwbDtqe

[Jazz Ghataora, PhD @JazzSynBio]

@ATinyGreenCell I'm sure it was the Salmonella poisoning by that Rajneeshee cult in the 80s? Netflix has a series about it!

[Sebastian S. Cocioba🪄🌷 @ATinyGreenCell]

SPLICECRAFT v1.0 IS LIVE!!!!!!!!!!!!

Open your terminal and type in "pipx install splicecraft" if you want to try it out, then spam "splicecraft update" often as I push updates frequently. A labor of love for the community I adore. Enjoy! 💚

[Jazz Ghataora, PhD @JazzSynBio]

Postdoc position available in an awesome lab!

[sui @birdabo]

everybody calm down.

i got this.

[Nature Biotechnology @NatureBiotech]

Genome editing of phylogenetically distinct bacteria using cross-species retron-mediated recombineering https://t.co/JOIf2AUurQ

[Zane Koch @zanehkoch]

ok actually insane paper published yesterday

a research group in Korea built a gene switch you can control wirelessly using electromagnetic fields

they exposed mice to 60 hz EMF (same frequency as your wall outlet) using a pair of large coils that generate a uniform magnetic field around the animal, for cyclic 3-day on / 4-day off pulses

they showed this could:
- activate OSK to do epigenetic reprogramming in progeroid and aged mice, extending lifespan and reversing aging markers across multiple tissues
- conditionally switch on mutant amyloid genes only in aged mouse brains, letting them separate aging effects from amyloid effects to study AD biology in a way previous models couldn't

no drugs, no impacts, just a magnetic field from outside the body

[Sebastian S. Cocioba🪄🌷 @ATinyGreenCell]

Cranking out some heavy updates to my TUI plasmid viewer. Golden Braid part domesticator and MoClo assembly automation. All the tools I ever dreamed of are coming to fruition. Really thankful for Claude Code. Follow along here; rapidly changin development

https://t.co/3mkWtVqa1T

[Vega Shah @dr_alphalyrae]

DefensePredictor - a machine learning model to discover novel CRISPR-like systems in bacteria | Science https://t.co/rpvHGz5ZN9

[Jazz Ghataora, PhD @JazzSynBio]

Okay, this is very cool! 😍 https://t.co/Wirt6E6xNI

[LomvardasLab @LomvardasLab]

https://t.co/40YUA40L0n
Another great paper by @shsternberg @ColumbiaBiochem Congrats to all!

[Jorge Bravo Abad @bravo_abad]

What happens when you train a transformer on 123 million bacterial proteins

Bacteria have been fighting viruses for billions of years. To do it, they have evolved a remarkable diversity of antiphage defense systems — molecular immune machines that detect and destroy invading phages. Yet fewer than 250 such systems had been experimentally validated. A new study in Science suggests we've barely scratched the surface.

Mordret and coauthors asked a simple but powerful question: can language models trained on protein sequences and genomic context learn the "grammar" of bacterial immunity well enough to predict entirely unknown defense systems at scale?

They developed three complementary deep learning models. ALBERTDF adapts the ALBERT transformer architecture to treat genes as words and genome neighborhoods as sentences — learning defensiveness from genomic context alone, without any sequence information. ESMDF fine-tunes the ESM2 protein language model with LoRA adapters to classify proteins as defensive or non-defensive directly from amino acid sequence — trained on a dataset of 123 million proteins drawn from 32,000 bacterial genomes. GeneCLRDF combines both signals through contrastive learning: it teaches the model that a gene's identity can be inferred either from its sequence or from the genomic neighborhood where it lives. This joint embedding achieves 99% precision and 92% recall on held-out benchmarks — far outperforming each approach independently.

The models aren't just impressive on paper. The authors experimentally validated 12 antiphage systems with no prior link to immunity, in both E. coli and Streptomyces albus. Some carry canonical defense domains; others involve proteins with no known association to antiphage function whatsoever.

Applied to over 32,000 bacterial genomes, GeneCLRDF predicts 2.39 million antiphage proteins. Around 1.5% of a typical bacterial genome is devoted to defense — three times previous estimates — and more than 85% of predicted protein families have no prior link to immunity.

The implications are immediate. The predicted atlas — including ~23,000 candidate operon families — is a ready-made discovery pipeline for novel nucleases, molecular effectors, and antimicrobial mechanisms directly relevant to phage therapy and programmable biologics. Language models are turning the bacterial pangenome into an actionable resource.

Paper: Mordret et al., Science (2026) — Science license | https://t.co/CzpyZWPNbO