In this PacBio User Group Meeting presentation, PacBio scientist Meredith Ashby shared several examples of analysis — from full-length 16S sequencing to shotgun sequencing — showing how SMRT Sequencing enables…
Understanding interactions among plants and the complex communities of organisms living on, in and around them requires more than one experimental approach. A new method for de novo metagenome assembly,…
In this webinar, Dr. Ashby gives attendees a brief update on PacBio’s metagenomics solutions on the Sequel II System. Then, Dr. Ma, University of Maryland School of Medicine, discusses her…
Development of high-throughput sequencing techniques have greatly benefited our understanding about microbial ecology; yet the methods producing short reads suffer from species-level resolution and uncertainty of identification. Here we optimize PacBio-based metabarcoding protocols covering the Internal Transcribed Spacer (ITS region) and partial Small Subunit (SSU) of the rRNA gene for species-level identification of all eukaryotes, with a specific focus on Fungi (including Glomeromycota) and Stramenopila (particularly Oomycota). Based on tests on composite soil samples and mock communities, we propose best suitable degenerate primers, ITS9munngs + ITS4ngsUni for eukaryotes and selected groups therein and discuss pros and cons of long read-based identification of eukaryotes. This article is protected by copyright. All rights reserved.
Culture-based molecular identification methods have revolutionized detection of pathogens, yet these methods are slow and may yield inconclusive results from environmental materials. The second-generation sequencing tools have much-improved precision and sensitivity of detection, but these analyses are costly and may take several days to months. Of the third-generation sequencing techniques, the portable MinION device (Oxford Nanopore Technologies) has received much attention because of its small size and possibility of rapid analysis at reasonable cost. Here, we compare the relative performances of two third-generation sequencing instruments, MinION and Sequel (Pacific Biosciences), in identification and diagnostics of fungal and oomycete pathogens from conifer (Pinaceae) needles and potato (Solanum tuberosum) leaves and tubers. We demonstrate that the Sequel instrument is efficient for metabarcoding of complex samples, whereas MinION is not suited for this purpose due to a high error rate and multiple biases. However, we find that MinION can be utilized for rapid and accurate identification of dominant pathogenic organisms and other associated organisms from plant tissues following both amplicon-based and PCR-free metagenomics approaches. Using the metagenomics approach with shortened DNA extraction and incubation times, we performed the entire MinION workflow, from sample preparation through DNA extraction, sequencing, bioinformatics, and interpretation, in 2.5 h. We advocate the use of MinION for rapid diagnostics of pathogens and potentially other organisms, but care needs to be taken to control or account for multiple potential technical biases.IMPORTANCE Microbial pathogens cause enormous losses to agriculture and forestry, but current combined culturing- and molecular identification-based detection methods are too slow for rapid identification and application of countermeasures. Here, we develop new and rapid protocols for Oxford Nanopore MinION-based third-generation diagnostics of plant pathogens that greatly improve the speed of diagnostics. However, due to high error rate and technical biases in MinION, the Pacific BioSciences Sequel platform is more useful for in-depth amplicon-based biodiversity monitoring (metabarcoding) from complex environmental samples.Copyright © 2019 American Society for Microbiology.
Targeted PCR amplification and high-throughput sequencing (amplicon sequencing) of 16S rRNA gene fragments is widely used to profile microbial communities. New long-read sequencing technologies can sequence the entire 16S rRNA gene, but higher error rates have limited their attractiveness when accuracy is important. Here we present a high-throughput amplicon sequencing methodology based on PacBio circular consensus sequencing and the DADA2 sample inference method that measures the full-length 16S rRNA gene with single-nucleotide resolution and a near-zero error rate. In two artificial communities of known composition, our method recovered the full complement of full-length 16S sequence variants from expected community members without residual errors. The measured abundances of intra-genomic sequence variants were in the integral ratios expected from the genuine allelic variants within a genome. The full-length 16S gene sequences recovered by our approach allowed Escherichia coli strains to be correctly classified to the O157:H7 and K12 sub-species clades. In human fecal samples, our method showed strong technical replication and was able to recover the full complement of 16S rRNA alleles in several E. coli strains. There are likely many applications beyond microbial profiling for which high-throughput amplicon sequencing of complete genes with single-nucleotide resolution will be of use. © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
Application of organic fertilisers to soil prevents erosion, improves fertility and may suppress certain soil-borne plant pathogens, but it is still unclear how different trophic groups of fungi and oomycetes respond to long-term fertilisation treatment. The objective of the study was to examine the effect of different fertilisation regimes on fungal and oomycete pathogen- and mycorrhizal symbiont diversity and community structure in both soil and roots, using PacBio SMRT sequencing. The field experiment included three fertilisation treatments that have been applied since 1989: nitrogen fertilisation (WOM), nitrogen fertilisation with manure amendment (FYM) and alternative organic fertilisation (AOF), each applied at five different rates. Soil samples were collected three times during the growing season, while root samples were collected during the flowering stage. There was no influence of the studied variables on soil and root pathogen richness. Contrary to our hypothesis, pathogen relative abundance in both soil and roots was significantly higher in plots with the AOF treatment. Furthermore, richness and relative abundance of arbuscular mycorrhizal (AM) fungi decreased significantly in the AOF treatment. Permutational analysis of variance (PERMANOVA) demonstrated the effect of fertilisation treatment on pathogen community composition in both soil and roots. Our findings indicate that organic fertilisers may not always benefit soil microbial community composition. Therefore, further studies are needed to understand how fertilisation affects mycorrhizal mutualists and pathogens.
Metagenomics is the study of genetic materials directly sampled from natural habitats. It has the potential to reveal previously hidden diversity of microscopic life largely due to the existence of highly parallel and low-cost next-generation sequencing technology. Conventional approaches align metagenomic reads onto known reference genomes to identify microbes in the sample. Since such a collection of reference genomes is very large, the approach often needs high-end computing machines with large memory which is not often available to researchers. Alternative approaches follow an alignment-free methodology where the presence of a microbe is predicted using the information about the unique k-mers present in the microbial genomes. However, such approaches suffer from high false positives due to trading off the value of k with the computational resources. In this article, we propose a highly efficient metagenomic sequence classification (MSC) algorithm that is a hybrid of both approaches. Instead of aligning reads to the full genomes, MSC aligns reads onto a set of carefully chosen, shorter and highly discriminating model sequences built from the unique k-mers of each of the reference sequences.Microbiome researchers are generally interested in two objectives of a taxonomic classifier: (i) to detect prevalence, i.e. the taxa present in a sample, and (ii) to estimate their relative abundances. MSC is primarily designed to detect prevalence and experimental results show that MSC is indeed a more effective and efficient algorithm compared to the other state-of-the-art algorithms in terms of accuracy, memory and runtime. Moreover, MSC outputs an approximate estimate of the abundances.The implementations are freely available for non-commercial purposes. They can be downloaded from https://drive.google.com/open?id=1XirkAamkQ3ltWvI1W1igYQFusp9DHtVl. © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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.
Metagenomic sequence classification should be fast, accurate and information-rich. Emerging long-read sequencing technologies promise to improve the balance between these factors but most existing methods were designed for short reads. MetaMaps is a new method, specifically developed for long reads, capable of mapping a long-read metagenome to a comprehensive RefSeq database with >12,000 genomes in <16?GB or RAM on a laptop computer. Integrating approximate mapping with probabilistic scoring and EM-based estimation of sample composition, MetaMaps achieves >94% accuracy for species-level read assignment and r2?>?0.97 for the estimation of sample composition on both simulated and real data when the sample genomes or close relatives are present in the classification database. To address novel species and genera, which are comparatively harder to predict, MetaMaps outputs mapping locations and qualities for all classified reads, enabling functional studies (e.g. gene presence/absence) and detection of incongruities between sample and reference genomes.
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.
If you have a question, need to check the status of an order, or are interested in purchasing an instrument, we're here to help.