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Related Experiment Video

Updated: Jul 15, 2025

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

Efficient High-Quality Metagenome Assembly from Long Accurate Reads using Minimizer-space de Bruijn Graphs.

Gaëtan Benoit¹, Sébastien Raguideau¹, Robert James²

¹Organisms and Ecosystems, Earlham Institute, Norwich, NR4 7UZ, UK.

Biorxiv : the Preprint Server for Biology

|October 3, 2023

Summary

We developed metaMDBG, a new metagenomics assembler for long reads. It efficiently reconstructs complex microbial communities into high-quality genomes, improving upon existing methods.

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Area of Science:

Microbial genomics
Bioinformatics
Computational biology

Background:

Metagenomics enables the study of microbial communities directly from environmental samples.
Accurate assembly of long reads is crucial for reconstructing genomes from complex metagenomic data.
Existing assemblers face challenges with computational efficiency and strain complexity in diverse communities.

Approach:

Introduced metaMDBG, a novel metagenomics assembler utilizing de Bruijn graphs in minimizer space.
Implemented a multi-k approach to manage variations in genome coverage depth.
Employed an abundance-based filtering strategy to simplify strain complexity.

Key Points:

metaMDBG demonstrates 1.5 to 12 times greater speed and requires one-tenth to one-thirtieth of the memory compared to state-of-the-art assemblers.
Achieved up to double the number of high-quality circularized prokaryotic metagenome-assembled genomes (MAGs) from complex communities.
Showcased improved recovery of viruses and plasmids, performing robustly with strain diversity.

Conclusions:

metaMDBG offers a significant advancement in the efficiency and accuracy of metagenomic assembly for long reads.
Enables the efficient reconstruction of a majority of complex microbial communities into near-complete MAGs.
Facilitates deeper insights into microbial community structure and function.