Comparison of Oxford Nanopore Technologies and Illumina MiSeq sequencing with mock communities and agricultural soil.

Illumina MiSeq is the current standard for characterizing microbial communities in soil. The newer alternative, Oxford Nanopore Technologies MinION sequencer, is quickly gaining popularity because of the low initial cost and longer sequence reads. However, the accuracy of MinION, per base, is much lower than MiSeq (95% versus 99.9%). The effects of this difference in base-calling accuracy on taxonomic and diversity estimates remains unclear. We compared the effects of platform, primers, and bioinformatics on mock community and agricultural soil samples using short MiSeq, and short and full-length MinION 16S rRNA amplicon sequencing. For all three methods, we found that taxonomic assignments of the mock community at both the genus and species level matched expectations with minimal deviation (genus: 80.9-90.5%; species: 70.9-85.2% Bray-Curtis similarity); however, the short MiSeq with error correction (DADA2) resulted in the correct estimate of mock community species richness and much lower alpha diversity for soils. Several filtering strategies were tested to improve these estimates with varying results. The sequencing platform also had a significant influence on the relative abundances of taxa with MiSeq resulting in significantly higher abundances Actinobacteria, Chloroflexi, and Gemmatimonadetes and lower abundances of Acidobacteria, Bacteroides, Firmicutes, Proteobacteria, and Verrucomicrobia compared to the MinION platform. When comparing agricultural soils from two different sites (Fort Collins, CO and Pendleton, OR), methods varied in the taxa identified as significantly different between sites. At all taxonomic levels, the full-length MinION method had the highest similarity to the short MiSeq method with DADA2 correction with 73.2%, 69.3%, 74.1%, 79.3%, 79.4%, and 82.28% of the taxa at the phyla, class, order, family, genus, and species levels, respectively, showing similar patterns in differences between the sites. In summary, although both platforms appear suitable for 16S rRNA microbial community composition, biases for different taxa may make the comparison between studies problematic; and even with a single study (i.e., comparing sites or treatments), the sequencing platform can influence the differentially abundant taxa identified.

Stevens BM ，Creed TB ，Reardon CL ，Manter DK ... -  《Scientific Reports》

Comparison of Illumina versus Nanopore 16S rRNA Gene Sequencing of the Human Nasal Microbiota.

Heikema AP ，Horst-Kreft D ，Boers SA ，Jansen R ，Hiltemann SD ，de Koning W ，Kraaij R ，de Ridder MAJ ，van Houten CB ，Bont LJ ，Stubbs AP ，Hays JP ... -  《Genes》

MinION™ nanopore sequencing of environmental metagenomes: a synthetic approach.

Environmental metagenomic analysis is typically accomplished by assigning taxonomy and/or function from whole genome sequencing or 16S amplicon sequences. Both of these approaches are limited, however, by read length, among other technical and biological factors. A nanopore-based sequencing platform, MinION™, produces reads that are ≥1 × 104 bp in length, potentially providing for more precise assignment, thereby alleviating some of the limitations inherent in determining metagenome composition from short reads. We tested the ability of sequence data produced by MinION (R7.3 flow cells) to correctly assign taxonomy in single bacterial species runs and in three types of low-complexity synthetic communities: a mixture of DNA using equal mass from four species, a community with one relatively rare (1%) and three abundant (33% each) components, and a mixture of genomic DNA from 20 bacterial strains of staggered representation. Taxonomic composition of the low-complexity communities was assessed by analyzing the MinION sequence data with three different bioinformatic approaches: Kraken, MG-RAST, and One Codex. Results: Long read sequences generated from libraries prepared from single strains using the version 5 kit and chemistry, run on the original MinION device, yielded as few as 224 to as many as 3497 bidirectional high-quality (2D) reads with an average overall study length of 6000 bp. For the single-strain analyses, assignment of reads to the correct genus by different methods ranged from 53.1% to 99.5%, assignment to the correct species ranged from 23.9% to 99.5%, and the majority of misassigned reads were to closely related organisms. A synthetic metagenome sequenced with the same setup yielded 714 high quality 2D reads of approximately 5500 bp that were up to 98% correctly assigned to the species level. Synthetic metagenome MinION libraries generated using version 6 kit and chemistry yielded from 899 to 3497 2D reads with lengths averaging 5700 bp with up to 98% assignment accuracy at the species level. The observed community proportions for “equal” and “rare” synthetic libraries were close to the known proportions, deviating from 0.1% to 10% across all tests. For a 20-species mock community with staggered contributions, a sequencing run detected all but 3 species (each included at <0.05% of DNA in the total mixture), 91% of reads were assigned to the correct species, 93% of reads were assigned to the correct genus, and >99% of reads were assigned to the correct family. Conclusions: At the current level of output and sequence quality (just under 4 × 103 2D reads for a synthetic metagenome), MinION sequencing followed by Kraken or One Codex analysis has the potential to provide rapid and accurate metagenomic analysis where the consortium is comprised of a limited number of taxa. Important considerations noted in this study included: high sensitivity of the MinION platform to the quality of input DNA, high variability of sequencing results across libraries and flow cells, and relatively small numbers of 2D reads per analysis limit. Together, these limited detection of very rare components of the microbial consortia, and would likely limit the utility of MinION for the sequencing of high-complexity metagenomic communities where thousands of taxa are expected. Furthermore, the limitations of the currently available data analysis tools suggest there is considerable room for improvement in the analytical approaches for the characterization of microbial communities using long reads. Nevertheless, the fact that the accurate taxonomic assignment of high-quality reads generated by MinION is approaching 99.5% and, in most cases, the inferred community structure mirrors the known proportions of a synthetic mixture warrants further exploration of practical application to environmental metagenomics as the platform continues to develop and improve. With further improvement in sequence throughput and error rate reduction, this platform shows great promise for precise real-time analysis of the composition and structure of more complex microbial communities.

Brown BL ，Watson M ，Minot SS ，Rivera MC ，Franklin RB ... -  《GigaScience》

Evaluation of 16S rRNA amplicon sequencing using two next-generation sequencing technologies for phylogenetic analysis of the rumen bacterial community in steers.

Next generation sequencing technologies have vastly changed the approach of sequencing of the 16S rRNA gene for studies in microbial ecology. Three distinct technologies are available for large-scale 16S sequencing. All three are subject to biases introduced by sequencing error rates, amplification primer selection, and read length, which can affect the apparent microbial community. In this study, we compared short read 16S rRNA variable regions, V1-V3, with that of near-full length 16S regions, V1-V8, using highly diverse steer rumen microbial communities, in order to examine the impact of technology selection on phylogenetic profiles. Short paired-end reads from the Illumina MiSeq platform were used to generate V1-V3 sequence, while long "circular consensus" reads from the Pacific Biosciences RSII instrument were used to generate V1-V8 data. The two platforms revealed similar microbial operational taxonomic units (OTUs), as well as similar species richness, Good's coverage, and Shannon diversity metrics. However, the V1-V8 amplified ruminal community resulted in significant increases in several orders of taxa, such as phyla Proteobacteria and Verrucomicrobia (P < 0.05). Taxonomic classification accuracy was also greater in the near full-length read. UniFrac distance matrices using jackknifed UPGMA clustering also noted differences between the communities. These data support the consensus that longer reads result in a finer phylogenetic resolution that may not be achieved by shorter 16S rRNA gene fragments. Our work on the cattle rumen bacterial community demonstrates that utilizing near full-length 16S reads may be useful in conducting a more thorough study, or for developing a niche-specific database to use in analyzing data from shorter read technologies when budgetary constraints preclude use of near-full length 16S sequencing.

Myer PR ，Kim M ，Freetly HC ，Smith TPL ... -  《-》

The newest Oxford Nanopore R10.4.1 full-length 16S rRNA sequencing enables the accurate resolution of species-level microbial community profiling.

Zhang T ，Li H ，Ma S ，Cao J ，Liao H ，Huang Q ，Chen W ... -  《-》