MicroDUET: a dual-headed genomic foundation model for pathogen surveillance
Michael BarberiD, Carl J. E. SusteriD, Jingyi Lei, Marya GetchelliD, Suci WulandariiD, Vitali SintchenkoiD, Paul M. PronykiD
Abstract
Pathogen genomic surveillance works from raw reads, assembled genomes and alignments, representations that are slow and costly to compare at scale. Compact embeddings from genomic language models offer an alternative, but surveillance requires resolving both evolutionary ancestry (phylogeny) and phenotypic capability (function) - which need not co-vary. Here we present MicroDUET, which adapts a 26.6-million-parameter ProkBERT backbone with two 3.5-million-parameter adapter heads: a phylogeny head trained contrastively on genome windows from the same microbes, and a function head trained to identify genes across taxa. On held-out retrieval benchmarks, the phylogeny head returned the correct species for 80.3% and 66.6% of cellular and viral queries, and the function head the correct gene family for 97.3% and 97.2%, reaching 74.4% accuracy on an independent antimicrobial resistance-class benchmark. Across all three benchmarks MicroDUET outranked 17 other genomic encoders. Without training on lineage, clade or drug-susceptibility tasks, MicroDUET identified Mycobacterium tuberculosis and mpox virus lineages and clades (0.965, 0.975 accuracy), discriminated rifampicin resistance without lineage adjustment (AUROC 0.985), and retrospectively identified an emerging mpox lineage as anomalous (AUROC 0.974). MicroDUET operates 10^3 - 10^4 times faster than single-threaded sequence-based alignments. MicroDUET therefore provides a compact, reusable representation for scalable pathogen surveillance and sequence triage.
02 /Specification & Classification
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