MetaBolt: A computationally efficient pipeline for the rapid recovery of metagenome-assembled genomes

Metagenome-resolved metagenomics refers to the recovery of metagenome-assembled genomes from the metagenomic datasets. It is a multi-step and laborious process that requires substantial computational resources and technical expertise. Though various semi-automated pipelines have been developed to automate the recovery process, high computational requirements remain a major bottleneck. Since de novo assembly is the key step that consumes higher computational time and resources, optimizing this step can address the underlying challenges. Hence, to address these limitations, we introduce MetaBolt, an automated Nextflow-based pipeline designed for the rapid recovery of metagenome-assembled genomes from short-read metagenomic datasets. Based on an empirically optimized set of k-mers for MEGAHIT-based assembly, this pipeline offers a unique solution. When tested on both real and simulated metagenomic datasets, it consistently exhibited efficient performance within reduced computational time. From gut metagenomes, MetaBolt recovered MAGs at a 2.3 and 3.8-times faster rate than nf-core/mag and MetaWRAP, respectively, while recovering ∼5% more high-quality MAGs compared to the other two pipelines. Whereas, in the case of real metagenome samples, it reduced the computational times to 2-4%, particularly for low-biomass samples. By integrating optimized assembly parameters with automated workflow management, MetaBolt lowers computational barriers to genome-resolved metagenomics without compromising output quality. MetaBolt is available on the web at https://github.com/muneebdev7/metabolt.