Benchmarking second and third-generation sequencing platforms for microbial metagenomics

• Published in: Scientific data Vol. 9; no. 1; p. 694
• Main Authors: Meslier, Victoria, Quinquis, Benoit, Da Silva, Kévin, Plaza Oñate, Florian, Pons, Nicolas, Roume, Hugo, Podar, Mircea, Almeida, Mathieu
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 11.11.2022; Nature Publishing Group UK; Nature Portfolio
• Subjects: BASIC BIOLOGICAL SCIENCES; Benchmarking; Bioinformatics; Cellular Biology; Data Descriptor; data publication and archiving; Gene mapping; Genomes; High-Throughput Nucleotide Sequencing - methods; Life Sciences; Metagenome; Metagenomics; Metagenomics - methods; Microbiota - genetics; Phylogenetics; Quality control; Sequence Analysis, DNA - methods; Taxonomy; Technology
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-022-01762-z

Shotgun metagenomic sequencing is a common approach for studying the taxonomic diversity and metabolic potential of complex microbial communities. Current methods primarily use second generation short read sequencing, yet advances in third generation long read technologies provide opportunities to overcome some of the limitations of short read sequencing. Here, we compared seven platforms, encompassing second generation sequencers (Illumina HiSeq 300, MGI DNBSEQ-G400 and DNBSEQ-T7, ThermoFisher Ion GeneStudio S5 and Ion Proton P1) and third generation sequencers (Oxford Nanopore Technologies MinION R9 and Pacific Biosciences Sequel II). We constructed three uneven synthetic microbial communities composed of up to 87 genomic microbial strains DNAs per mock, spanning 29 bacterial and archaeal phyla, and representing the most complex and diverse synthetic communities used for sequencing technology comparisons. Our results demonstrate that third generation sequencing have advantages over second generation platforms in analyzing complex microbial communities, but require careful sequencing library preparation for optimal quantitative metagenomic analysis. Our sequencing data also provides a valuable resource for testing and benchmarking bioinformatics software for metagenomics.