FUSARIUM HEAD BLIGHTWheat
$2.9B
estimated loss

We find them in disease-suppressive soils, reconstruct their genomes and mine them for new ways to control crop pathogens.
Source: Savary et al., Nature Ecology & Evolution, 2019.
Crop protection needs new modes of action.
Resistance is rising. Established active ingredients are being withdrawn. New solutions are not arriving fast enough.
Source: Pest Management Science, DOI 10.1002/ps.70522
FUSARIUM HEAD BLIGHTWheat
$2.9B
estimated loss
Soybean rustSoybean
>$2B
annual impact
Late blightPotato
~$6.1B
annual impact
Rice blastRice
>$2B
annual impact
A family of genomic language models (gLMs) trained on the DNA of soil microbial communities. Trained on about 67.5 billion DNA bases from 15,640 public long-read microbial genomes, with a context window long enough to use genomic context across several thousand bases.
Infer what genes and biological systems do.
Identify peptides and proteins that may inhibit pathogens.
Prioritise the most promising sequences.
Generate and optimise sequences for a target activity.
All models were trained on the same corpus and setup. Performance rises with model size on variant effect and enzyme function, and levels off on gene essentiality.
We change one letter of a bacterial gene and test whether the model's surprise at the change tracks its measured effect on the organism.
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1 October 2026

1 October 2026
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