metaSMASH: Scalable Biosynthetic Gene Cluster Detection for Large Metagenomic Assemblies

Abstract

antiSMASH is widely used for biosynthetic gene cluster (BGC) detection and annotation, but its standard workflow is poorly suited to large metagenomic assemblies, where massive contig counts create severe runtime bottlenecks and complicate downstream result exploration. We present metaSMASH, a re-engineered fork of antiSMASH for metagenome-scale BGC analysis. metaSMASH preserves the original antiSMASH detection and annotation logic while introducing streaming, memory-bounded execution, record-level parallelisation, optional output filtering, and an interactive dashboard for large result sets. Across 25 benchmark metagenome datasets, metaSMASH reproduced identical BGC detection results while dramatically reducing computational cost. Relative to the default antiSMASH configuration, metaSMASH was a geometric-mean 38× faster. It also outperformed an ad hoc chunked antiSMASH workflow: in the default configuration it achieved a geometric-mean 2.9 × speed-up and 1.7 × lower peak memory, and with extended-analysis modules enabled it was 2.7 × faster and used 3.1 × less memory while completing all datasets, whereas the ad hoc workflow ran out of memory on the two largest assemblies. By substantially reducing the computational burden of large-scale metagenome analysis without sacrificing result equivalence, metaSMASH makes routine mining of assembled metagenomes more practical and provides a scalable foundation for natural product discovery from complex microbial communities. Graphical Abstract