Abstract
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.
Original language | English |
---|---|
Article number | 694 |
Journal | Scientific Data |
Volume | 9 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2022 |
Funding
This work was supported by the European FP7 Marie Skłodowska-Curie actions AgreenSkillsPlus PCOFUND-GA-2013-609398 grant to MA. Additional funding was from the Metagenopolis grant ANR-11-DPBS-0001. MP was supported by the U.S. Department of Energy, Office of Science, Biological, and Environmental Research as part of the Genomic Science Program (the Plant Microbe Interfaces SFA), by the Subsurface Biogeochemical Research Program (Biogeochemical Transformations at Critical Interfaces SFA) and by grant R01DE024463 from the National Institute of Dental and Craniofacial Research of the US National Institutes of Health. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. We thank Dr. Cynthia Gilmour (Smithsonian Research Institute, Edgewater, Maryland, USA) for providing some of the purified gDNA used in this study. We also thank David Stucki, Deborah Moine and Jules Bourgon (Pacific Biosciences, Menlo Park, California, USA) for PacBio sequencing, Jihua Sun and Yong Hou (BGI, Shenzhen, Guangdong, China) for DNBseq sequencing and Clemence Genthon (Plateforme Génomique GeT INRAE Transfert, Toulouse, France) for Illumina sequencing. This work was supported by the European FP7 Marie Skłodowska-Curie actions AgreenSkillsPlus PCOFUND-GA-2013-609398 grant to MA. Additional funding was from the Metagenopolis grant ANR-11-DPBS-0001. MP was supported by the U.S. Department of Energy, Office of Science, Biological, and Environmental Research as part of the Genomic Science Program (the Plant Microbe Interfaces SFA), by the Subsurface Biogeochemical Research Program (Biogeochemical Transformations at Critical Interfaces SFA) and by grant R01DE024463 from the National Institute of Dental and Craniofacial Research of the US National Institutes of Health. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. We thank Dr. Cynthia Gilmour (Smithsonian Research Institute, Edgewater, Maryland, USA) for providing some of the purified gDNA used in this study. We also thank David Stucki, Deborah Moine and Jules Bourgon (Pacific Biosciences, Menlo Park, California, USA) for PacBio sequencing, Jihua Sun and Yong Hou (BGI, Shenzhen, Guangdong, China) for DNBseq sequencing and Clemence Genthon (Plateforme Génomique GeT INRAE Transfert, Toulouse, France) for Illumina sequencing.