Background: Microbial ecology is reshaping our understanding of the natural world by revealing the large phylogenetic and functional diversity of microbial life. However the vast majority of these microorganisms remain poorly understood, as most cultivated representatives belong to just four phylogenetic groups and more than half of all identified phyla remain uncultivated. Characterization of this microbial ‘dark matter’ will thus greatly benefit from new metagenomic methods for in situ analysis. For example, sensitive high throughput methods for the characterization of community composition and structure from the sequencing of conserved marker genes. Methods: Here we utilize Single Molecule Real-Time (SMRT) sequencing of full-length 16S rRNA amplicons to phylogenetically profile microbial communities to below the genus-level. We test this method on a mock community of known composition, as well as a previously studied microbial community from a lake known to predominantly contain poorly characterized phyla. These results are compared to traditional 16S tag sequencing from short-read technologies and subsets of the full-length data corresponding to the same regions of the 16S gene. Results: We explore the benefits of using full-length amplicons for estimating community structure and diversity. In addition, we investigate the possible effects of context-specific and GC-content biases known to affect short-read sequencing technologies on the predicted community structure. We characterize the potential benefits of profiling metagenomic communities with full-length 16S rRNA genes from SMRT sequencing relative to standard methods.
Profiling metagenomic communities using circular consensus and Single Molecule, Real-Time Sequencing
There are many sequencing-based approaches to understanding complex metagenomic communities, spanning targeted amplification to whole-sample shotgun sequencing. While targeted approaches provide valuable data at low sequencing depth, they are limited by primer design and PCR amplification. Whole-sample shotgun experiments require a high depth of coverage. As such, rare community members may not be represented in the resulting assembly. Circular-consensus, Single Molecule, Real-Time (SMRT) Sequencing reads in the 1-2 kb range, with >99% consensus accuracy, can be efficiently generated for low amounts of input DNA, e.g. as little as 10 ng of input DNA sequenced in 4 SMRT Cells can generate >100,000 such reads. While throughput is low compared to second-generation sequencing, the reads are a true random sampling of the underlying community. Long read lengths translate to a high number of the reads harboring full genes or even full operons for downstream analysis. Here we present the results of circular-consensus sequencing on a mock metagenomic community with an abundance range of multiple orders of magnitude, and compare the results with both 16S and shotgun assembly methods. We show that even with relatively low sequencing depth, the long-read, assembly-free, random sampling allows to elucidate meaningful information from the very low-abundance community members. For example, given the above low-input sequencing approach, a community member at 1/1,000 relative abundance would generate 100 1-2 kb sequence fragments having 99% consensus accuracy, with a high probability of containing a gene fragment useful for taxonomic classification or functional insight.
Confident phylogenetic identification of uncultured prokaryotes through long read amplicon sequencing of the 16S-ITS-23S rRNA operon.
Amplicon sequencing of the 16S rRNA gene is the predominant method to quantify microbial compositions and to discover novel lineages. However, traditional short amplicons often do not contain enough information to confidently resolve their phylogeny. Here we present a cost-effective protocol that amplifies a large part of the rRNA operon and sequences the amplicons with PacBio technology. We tested our method on a mock community and developed a read-curation pipeline that reduces the overall read error rate to 0.18%. Applying our method on four environmental samples, we captured near full-length rRNA operon amplicons from a large diversity of prokaryotes. The method operated at moderately high-throughput (22286-37,850 raw ccs reads) and generated a large amount of putative novel archaeal 23S rRNA gene sequences compared to the archaeal SILVA database. These long amplicons allowed for higher resolution during taxonomic classification by means of long (~1000 bp) 16S rRNA gene fragments and for substantially more confident phylogenies by means of combined near full-length 16S and 23S rRNA gene sequences, compared to shorter traditional amplicons (250 bp of the 16S rRNA gene). We recommend our method to those who wish to cost-effectively and confidently estimate the phylogenetic diversity of prokaryotes in environmental samples at high throughput. © 2019 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.
Metaepigenomic analysis reveals the unexplored diversity of DNA methylation in an environmental prokaryotic community.
DNA methylation plays important roles in prokaryotes, and their genomic landscapes-prokaryotic epigenomes-have recently begun to be disclosed. However, our knowledge of prokaryotic methylation systems is focused on those of culturable microbes, which are rare in nature. Here, we used single-molecule real-time and circular consensus sequencing techniques to reveal the ‘metaepigenomes’ of a microbial community in the largest lake in Japan, Lake Biwa. We reconstructed 19 draft genomes from diverse bacterial and archaeal groups, most of which are yet to be cultured. The analysis of DNA chemical modifications in those genomes revealed 22 methylated motifs, nine of which were novel. We identified methyltransferase genes likely responsible for methylation of the novel motifs, and confirmed the catalytic specificities of four of them via transformation experiments using synthetic genes. Our study highlights metaepigenomics as a powerful approach for identification of the vast unexplored variety of prokaryotic DNA methylation systems in nature.