scholarly journals Assessing long-read sequencing with Nanopore R9, R10, and PacBio CCS to obtain high-quality metagenome assembled genomes from complex microbial communities

2021 ◽  
Author(s):  
Mantas Sereika ◽  
Rasmus Hansen Krikegaard ◽  
Søren Michael Karst ◽  
Thomas Yssing Michaelsen ◽  
Emil Aarre Sørensen ◽  
...  

Short-read DNA sequencing has led to a massive growth of genome databases but mainly with highly fragmented metagenome assembled genomes from environmental systems. The fragmentation is a result of closely related species, strains, and genome repeats that cannot be resolved with short reads. To confidently explore the functional potential of a microbial community, high-quality reference genomes are needed. In this study, we evaluated the use of different combinations of short (Illumina) and long-read technologies (Nanopore R9.4, R10.3, and PacBio CCS) for recovering high-quality metagenome assembled genomes (HQ MAGs) from a complex microbial community (anaerobic digester). Depending on the sequencing approach, 33 to 86 HQ MAGs (encompassing up to 34 % of the assembly and 49 % of the reads) were recovered using long reads, with Nanopore R9 featuring the lowest sequencing costs per HQ MAG recovered. PacBio CCS was also found to be an effective platform for genome-centric metagenomics (74 HQ MAGs) and produced HQ MAGs with the lowest fragmentation (median of 9 contigs) as a stand-alone technology. Using PacBio CCS MAGs as reference, we show that, although a high number of high-quality MAGs can be generated using Nanopore R9, systematic indel errors are still present, which can lead to truncated gene calling. However, polishing the Nanopore MAGs with short-read Illumina data, enabled recovery of MAGs with similar quality as MAGs from PacBio CCS.

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Seth Commichaux ◽  
Kiran Javkar ◽  
Padmini Ramachandran ◽  
Niranjan Nagarajan ◽  
Denis Bertrand ◽  
...  

Abstract Background Whole genome sequencing of cultured pathogens is the state of the art public health response for the bioinformatic source tracking of illness outbreaks. Quasimetagenomics can substantially reduce the amount of culturing needed before a high quality genome can be recovered. Highly accurate short read data is analyzed for single nucleotide polymorphisms and multi-locus sequence types to differentiate strains but cannot span many genomic repeats, resulting in highly fragmented assemblies. Long reads can span repeats, resulting in much more contiguous assemblies, but have lower accuracy than short reads. Results We evaluated the accuracy of Listeria monocytogenes assemblies from enrichments (quasimetagenomes) of naturally-contaminated ice cream using long read (Oxford Nanopore) and short read (Illumina) sequencing data. Accuracy of ten assembly approaches, over a range of sequencing depths, was evaluated by comparing sequence similarity of genes in assemblies to a complete reference genome. Long read assemblies reconstructed a circularized genome as well as a 71 kbp plasmid after 24 h of enrichment; however, high error rates prevented high fidelity gene assembly, even at 150X depth of coverage. Short read assemblies accurately reconstructed the core genes after 28 h of enrichment but produced highly fragmented genomes. Hybrid approaches demonstrated promising results but had biases based upon the initial assembly strategy. Short read assemblies scaffolded with long reads accurately assembled the core genes after just 24 h of enrichment, but were highly fragmented. Long read assemblies polished with short reads reconstructed a circularized genome and plasmid and assembled all the genes after 24 h enrichment but with less fidelity for the core genes than the short read assemblies. Conclusion The integration of long and short read sequencing of quasimetagenomes expedited the reconstruction of a high quality pathogen genome compared to either platform alone. A new and more complete level of information about genome structure, gene order and mobile elements can be added to the public health response by incorporating long read analyses with the standard short read WGS outbreak response.


mBio ◽  
2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Yu-Chih Tsai ◽  
Sean Conlan ◽  
Clayton Deming ◽  
Julia A. Segre ◽  
Heidi H. Kong ◽  
...  

ABSTRACT Deep metagenomic shotgun sequencing has emerged as a powerful tool to interrogate composition and function of complex microbial communities. Computational approaches to assemble genome fragments have been demonstrated to be an effective tool for de novo reconstruction of genomes from these communities. However, the resultant “genomes” are typically fragmented and incomplete due to the limited ability of short-read sequence data to assemble complex or low-coverage regions. Here, we use single-molecule, real-time (SMRT) sequencing to reconstruct a high-quality, closed genome of a previously uncharacterized Corynebacterium simulans and its companion bacteriophage from a skin metagenomic sample. Considerable improvement in assembly quality occurs in hybrid approaches incorporating short-read data, with even relatively small amounts of long-read data being sufficient to improve metagenome reconstruction. Using short-read data to evaluate strain variation of this C. simulans in its skin community at single-nucleotide resolution, we observed a dominant C. simulans strain with moderate allelic heterozygosity throughout the population. We demonstrate the utility of SMRT sequencing and hybrid approaches in metagenome quantitation, reconstruction, and annotation. IMPORTANCE The species comprising a microbial community are often difficult to deconvolute due to technical limitations inherent to most short-read sequencing technologies. Here, we leverage new advances in sequencing technology, single-molecule sequencing, to significantly improve reconstruction of a complex human skin microbial community. With this long-read technology, we were able to reconstruct and annotate a closed, high-quality genome of a previously uncharacterized skin species. We demonstrate that hybrid approaches with short-read technology are sufficiently powerful to reconstruct even single-nucleotide polymorphism level variation of species in this a community.


2021 ◽  
Vol 12 ◽  
Author(s):  
Min Tang ◽  
Suqun He ◽  
Xun Gong ◽  
Peng Lü ◽  
Rehab H. Taha ◽  
...  

The reference genomes of Bombyx mori (B. mori), Silkworm Knowledge-based database (SilkDB) and SilkBase, have served as the gold standard for nearly two decades. Their use has fundamentally shaped model organisms and accelerated relevant studies on lepidoptera. However, the current reference genomes of B. mori do not accurately represent the full set of genes for any single strain. As new genome-wide sequencing technologies have emerged and the cost of high-throughput sequencing technology has fallen, it is now possible for standard laboratories to perform full-genome assembly for specific strains. Here we present a high-quality de novo chromosome-level genome assembly of a single B. mori with nuclear polyhedrosis virus (BmNPV) resistance through the integration of PacBio long-read sequencing, Illumina short-read sequencing, and Hi-C sequencing. In addition, regular bioinformatics analyses, such as gene family, phylogenetic, and divergence analyses, were performed. The sample was from our unique B. mori species (NB), which has strong inborn resistance to BmNPV. Our genome assembly showed good collinearity with SilkDB and SilkBase and particular regions. To the best of our knowledge, this is the first genome assembly with BmNPV resistance, which should be a more accurate insect model for resistance studies.


2018 ◽  
Author(s):  
Denis Bertrand ◽  
Jim Shaw ◽  
Manesh Kalathiappan ◽  
Amanda Hui Qi Ng ◽  
Senthil Muthiah ◽  
...  

AbstractThe analysis of information rich whole-metagenome datasets acquired from complex microbial communities is often restricted by the fragmented nature of assembly from short-read sequencing. The availability of long-reads from third-generation sequencing technologies (e.g. PacBio or Oxford Nanopore) can help improve assembly quality in principle, but high error rates and low throughput have limited their application in metagenomics. In this work, we describe the first hybrid metagenomic assembler which combines the advantages of short and long-read technologies, providing an order of magnitude improvement in contiguity compared to short read assemblies, and high base-pair level accuracy. The proposed approach (OPERA-MS) integrates a novel assembly-based metagenome clustering technique with an exact scaffolding algorithm that can efficiently assemble repeat rich sequences. Based on evaluations with defined in vitro communities and virtual gut microbiomes, we show that it is possible to assemble near complete genomes from metagenomes with as little as 9× long read coverage, thus enabling high quality assembly of lowly abundant species (<1%). Furthermore, OPERA-MS’s fine-grained clustering is able to deconvolute and assemble multiple genomes of the same species in a single sample, allowing us to study the complex dynamics of the human microbiome at the sub-species level. Applying nanopore sequencing to gut metagenomes of patients undergoing antibiotic treatment, we show that long reads can be obtained from stool samples in clinical studies to produce more meaningful metagenomic assemblies (up to 200× improvement over short-read assemblies), including the closed assembly of >80 putative plasmid/phage sequences and a 263kbp jumbo phage. Our results highlight that high-quality hybrid assemblies provide an unprecedented view of the gut resistome in these patients, including strain dynamics and identification of novel plasmid sequences.


Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Benjamin J. Callahan ◽  
Dmitry Grinevich ◽  
Siddhartha Thakur ◽  
Michael A. Balamotis ◽  
Tuval Ben Yehezkel

Abstract Background Out of the many pathogenic bacterial species that are known, only a fraction are readily identifiable directly from a complex microbial community using standard next generation DNA sequencing. Long-read sequencing offers the potential to identify a wider range of species and to differentiate between strains within a species, but attaining sufficient accuracy in complex metagenomes remains a challenge. Methods Here, we describe and analytically validate LoopSeq, a commercially available synthetic long-read (SLR) sequencing technology that generates highly accurate long reads from standard short reads. Results LoopSeq reads are sufficiently long and accurate to identify microbial genes and species directly from complex samples. LoopSeq perfectly recovered the full diversity of 16S rRNA genes from known strains in a synthetic microbial community. Full-length LoopSeq reads had a per-base error rate of 0.005%, which exceeds the accuracy reported for other long-read sequencing technologies. 18S-ITS and genomic sequencing of fungal and bacterial isolates confirmed that LoopSeq sequencing maintains that accuracy for reads up to 6 kb in length. LoopSeq full-length 16S rRNA reads could accurately classify organisms down to the species level in rinsate from retail meat samples, and could differentiate strains within species identified by the CDC as potential foodborne pathogens. Conclusions The order-of-magnitude improvement in length and accuracy over standard Illumina amplicon sequencing achieved with LoopSeq enables accurate species-level and strain identification from complex- to low-biomass microbiome samples. The ability to generate accurate and long microbiome sequencing reads using standard short read sequencers will accelerate the building of quality microbial sequence databases and removes a significant hurdle on the path to precision microbial genomics.


2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Jean-Marc Aury ◽  
Benjamin Istace

Abstract Single-molecule sequencing technologies have recently been commercialized by Pacific Biosciences and Oxford Nanopore with the promise of sequencing long DNA fragments (kilobases to megabases order) and then, using efficient algorithms, provide high quality assemblies in terms of contiguity and completeness of repetitive regions. However, the error rate of long-read technologies is higher than that of short-read technologies. This has a direct consequence on the base quality of genome assemblies, particularly in coding regions where sequencing errors can disrupt the coding frame of genes. In the case of diploid genomes, the consensus of a given gene can be a mixture between the two haplotypes and can lead to premature stop codons. Several methods have been developed to polish genome assemblies using short reads and generally, they inspect the nucleotide one by one, and provide a correction for each nucleotide of the input assembly. As a result, these algorithms are not able to properly process diploid genomes and they typically switch from one haplotype to another. Herein we proposed Hapo-G (Haplotype-Aware Polishing Of Genomes), a new algorithm capable of incorporating phasing information from high-quality reads (short or long-reads) to polish genome assemblies and in particular assemblies of diploid and heterozygous genomes.


2020 ◽  
Author(s):  
Andrew J. Page ◽  
Nabil-Fareed Alikhan ◽  
Michael Strinden ◽  
Thanh Le Viet ◽  
Timofey Skvortsov

AbstractSpoligotyping of Mycobacterium tuberculosis provides a subspecies classification of this major human pathogen. Spoligotypes can be predicted from short read genome sequencing data; however, no methods exist for long read sequence data such as from Nanopore or PacBio. We present a novel software package Galru, which can rapidly detect the spoligotype of a Mycobacterium tuberculosis sample from as little as a single uncorrected long read. It allows for near real-time spoligotyping from long read data as it is being sequenced, giving rapid sample typing. We compare it to the existing state of the art software and find it performs identically to the results obtained from short read sequencing data. Galru is freely available from https://github.com/quadram-institute-bioscience/galru under the GPLv3 open source licence.


2020 ◽  
Author(s):  
Lauren Coombe ◽  
Vladimir Nikolić ◽  
Justin Chu ◽  
Inanc Birol ◽  
René L. Warren

AbstractSummaryThe ability to generate high-quality genome sequences is cornerstone to modern biological research. Even with recent advancements in sequencing technologies, many genome assemblies are still not achieving reference-grade. Here, we introduce ntJoin, a tool that leverages structural synteny between a draft assembly and reference sequence(s) to contiguate and correct the former with respect to the latter. Instead of alignments, ntJoin uses a lightweight mapping approach based on a graph data structure generated from ordered minimizer sketches. The tool can be used in a variety of different applications, including improving a draft assembly with a reference-grade genome, a short read assembly with a draft long read assembly, and a draft assembly with an assembly from a closely-related species. When scaffolding a human short read assembly using the reference human genome or a long read assembly, ntJoin improves the NGA50 length 23- and 13-fold, respectively, in under 13 m, using less than 11 GB of RAM. Compared to existing reference-guided assemblers, ntJoin generates highly contiguous assemblies faster and using less memory.Availability and implementationntJoin is written in C++ and Python, and is freely available at https://github.com/bcgsc/[email protected]


2020 ◽  
Author(s):  
Quang Tran ◽  
Vinhthuy Phan

Abstract Background: Most current metagenomic classifiers and profilers employ short reads to classify, bin and profile microbial genomes that are present in metagenomic samples. Many of these methods adopt techniques that aim to identify unique genomic regions of genomes so as to differentiate them. Because of this, short-read lengths might be suboptimal. Longer read lengths might improve the performance of classification and profiling. However, longer reads produced by current technology tend to have a higher rate of sequencing errors, compared to short reads. It is not clear if the trade-off between longer length versus higher sequencing errors will increase or decrease classification and profiling performance.Results: We compared performance of popular metagenomic classifiers on short reads and longer reads, which are assembled from the same short reads. When using a number of popular assemblers to assemble long reads from the short reads, we discovered that most classifiers made fewer predictions with longer reads and that they achieved higher classification performance on synthetic metagenomic data. Specifically, across most classifiers, we observed a significant increase in precision, while recall remained the same, resulting in higher overall classification performance. On real metagenomic data, we observed a similar trend that classifiers made fewer predictions. This suggested that they might have the same performance characteristics of having higher precision while maintaining the same recall with longer reads.Conclusions: This finding has two main implications. First, it suggests that classifying species in metagenomic environments can be achieved with higher overall performance simply by assembling short reads. This suggested that they might have the same performance characteristics of having higher precision while maintaining the same recall as shorter reads. Second, this finding suggests that it might be a good idea to consider utilizing long-read technologies in species classification for metagenomic applications. Current long-read technologies tend to have higher sequencing errors and are more expensive compared to short-read technologies. The trade-offs between the pros and cons should be investigated.


2020 ◽  
Author(s):  
Olivier Zablocki ◽  
Michelle Michelsen ◽  
Marie Burris ◽  
Natalie Solonenko ◽  
Joanna Warwick-Dugdale ◽  
...  

ABSTRACTMicrobes play fundamental roles in shaping natural ecosystem properties and functions, but do so under constraints imposed by their viral predators. However, studying viruses in nature can be challenging due to low biomass and the lack of universal gene markers. Though metagenomic short-read sequencing has greatly improved our virus ecology toolkit— and revealed many critical ecosystem roles for viruses — microdiverse populations and fine-scale genomic traits are missed. Some of these microdiverse populations are abundant and the missed regions may be of interest for identifying selection pressures that underpin evolutionary constraints associated with hosts and environments. Though long-read sequencing promises complete virus genomes on single reads, it currently suffers from high DNA requirements and sequencing errors that limit accurate gene prediction. Here we introduce VirION2, an integrated short- and long-read metagenomic wet-lab and informatics pipeline that updates our previous method (VirION) to further enhance the utility of long-read viral metagenomics. Using a viral mock community, we first optimized laboratory protocols (polymerase choice, DNA shearing size, PCR cycling) to enable 76% longer reads (now median length of 6,965 bp) from 100-fold less input DNA (now 1 nanogram). Using a virome from a natural seawater sample, we compared viromes generated with VirION2 against other library preparation options (unamplified, original VirION, and short-read), and optimized downstream informatics for improved long-read error correction and assembly. VirION2 assemblies combined with short-read based data (‘enhanced’viromes), provided significant improvements over VirION libraries in the recovery of longer and more complete viral genomes, and our optimized error-correction strategy using long- and short-read data achieved 99.97% accuracy. In the seawater virome, VirION2 assemblies captured 5,161 viral populations (including all of the virus populations observed in the other assemblies), 30% of which were uniquely assembled through inclusion of long-reads, and 22% of the top 10% most abundant virus populations derived from assembly of long-reads. Viral populations unique to VirION2 assemblies had significantly higher microdiversity, which may explain why short-read virome approaches failed to capture them. These findings suggest the VirION2 sample prep and workflow (updated at protocols.io) can help researchers better investigate the virosphere, even from challenging low-biomass samples. Our new protocols are available to the research community on protocols.io as a ‘living document’ to facilitate dissemination of updates to keep pace with the rapid evolution of long read sequencing technology. Taken together, the addition of long-reads uniquely enabled the recovery of 22% of the most abundant viruses—that would have been missed in short-read only assemblies.


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