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Auto Tag: Human microbiome

June 1, 2021  |  

SMRT Sequencing and assembly of the human microbiome project Mock Community sample – a feasibility project.

While the utility of Single Molecule, Real-Time (SMRT) Sequencing for de novo assembly and finishing of bacterial isolates is well established, this technology has not yet been widely applied to shotgun sequencing of microbial communities. In order to demonstrate the feasibility of this approach, we sequenced genomic DNA from the Microbial Mock Community B of the Human Microbiome Project

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June 1, 2021  |  

Developments in PacBio metagenome sequencing: Shotgun whole genomes and full-length 16S.

The assembly of metagenomes is dramatically improved by the long read lengths of SMRT Sequencing. This is demonstrated in an experimental design to sequence a mock community from the Human Microbiome Project, and assemble the data using the hierarchical genome assembly process (HGAP) at Pacific Biosciences. Results of this analysis are promising, and display much improved contiguity in the assembly of the mock community as compared to publicly available short-read data sets and assemblies. Additionally, the use of base modification information to make further associations between contigs provides additional data to improve assemblies, and to distinguish between members within a microbial community. The epigenetic approach is a novel validation method unique to SMRT Sequencing. In addition to whole-genome shotgun sequencing, SMRT Sequencing also offers improved classification resolution and reliability of metagenomic and microbiome samples by the full-length sequencing of 16S rRNA (~1500 bases long). Microbial communities can be detected at the species level in some cases, rather than being limited to the genus taxonomic classification as constrained by short-read technologies. The performance of SMRT Sequencing for these metagenomic samples achieved >99% predicted concordance to reference sequences in cecum, soil, water, and mock control investigations for bacterial 16S. Community samples are estimated to contain from 2.3 and up to 15 times as many species with abundance levels as low as 0.05% compared to the identification of phyla groups.

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June 1, 2021  |  

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.

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June 1, 2021  |  

How to Compare and Cluster Every Known Genome in about an Hour

Given a massive collection of sequences, it is infeasible to perform pairwise alignment for basic tasks like sequence clustering and search. To address this problem, we demonstrate that the MinHash technique, first applied to clustering web pages, can be applied to biological sequences with similar effect, and extend this idea to include biologically relevant distance and significance measures. Our new tool, Mash, uses MinHash locality-sensitive hashing to reduce large sequences to a representative sketch and rapidly estimate pairwise distances between genomes or metagenomes. Using Mash, we explored several use cases, including a 5,000-fold size reduction and clustering of all 55,000 NCBI RefSeq genomes in 46 CPU hours. The resulting 93 MB sketch database includes all RefSeq genomes, effectively delineates known species boundaries, reconstructs approximate phylogenies, and can be searched in seconds using assembled genomes or raw sequencing runs from Illumina, Pacific Biosciences, and Oxford Nanopore. For metagenomics, Mash scales to thousands of samples and can replicate Human Microbiome Project and Global Ocean Survey results in a fraction of the time. Other potential applications include any problem where an approximate, global sequence distance is acceptable, e.g. to triage and cluster sequence data, assign species labels to unknown genomes, quickly identify mis- tracked samples, and search massive genomic databases. In addition, the Mash distance metric is based on simple set intersections, which are compatible with homomorphic encryption schemes. To facilitate integration with other software, Mash is implemented as a lightweight C++ toolkit and freely released under a BSD license athttps://github.com/marbl/mash

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June 1, 2021  |  

Improving long-read assembly of microbial genomes and plasmids

Complete, high-quality microbial genomes are very valuable across a broad array of fields, from environmental studies, to human microbiome health, food pathogen surveillance, etc. Long-read sequencing enables accurate resolution of complex microbial genomes and is becoming the new standard. Here we report our novel Microbial Assembly pipeline to facilitate rapid, large-scale analysis of microbial genomes. We sequenced a 48-plex library with one SMRT Cell 8M on the Sequel II System, demultiplexed, then analyzed the data with Microbial Assembly.

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June 1, 2021  |  

Metagenomic analysis of type II diabetes gut microbiota using PacBio HiFi reads reveals taxonomic and functional differences

In the past decade, the human microbiome has been increasingly shown to play a major role in health. For example, imbalances in gut microbiota appear to be associated with Type II diabetes mellitus (T2DM) and cardiovascular disease. Coronary artery disease (CAD) is a major determinant of the long-term prognosis among T2DM patients, with a 2- to 4-fold increased mortality risk when present. However, the exact microbial strains or functions implicated in disease need further investigation. From a large study with 523 participants (185 healthy controls, 186 T2DM patients without CAD, and 106 T2DM patients with CAD), 3 samples from each patient group were selected for long read sequencing. Each sample was prepared and sequenced on one Sequel II System SMRT Cell, to assess whether long accurate PacBio HiFi reads could yield additional insights to those made using short reads. Each of the 9 samples was subject to metagenomic assembly and binning, taxonomic classification and functional profiling. Results from metagenomic assembly and binning show that it is possible to generate a significant number of complete MAGs (Metagenome Assembled Genomes) from each sample, with over half of the high-quality MAGs being represented by a single circular contig. We show that differences found in taxonomic and functional profiles of healthy versus diabetic patients in the small 9-sample study align with the results of the larger study, as well as with results reported in literature. For example, the abundances of beneficial short- chain fatty acid (SCFA) producers such as Phascolarctobacterium faecium and Faecalibacterium prausnitzii were decreased in T2DM gut microbiota in both studies, while the abundances of quinol and quinone biosynthesis pathways were increased as compared to healthy controls. In conclusion, metagenomic analysis of long accurate HiFi reads revealed important taxonomic and functional differences in T2DM versus healthy gut microbiota. Furthermore, metagenome assembly of long HiFi reads led to the recovery of many complete MAGs and a significant number of complete circular bacterial chromosome sequences.

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April 21, 2020  |  

High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution.

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.

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April 21, 2020  |  

Conventional culture methods with commercially available media unveil the presence of novel culturable bacteria.

Recent metagenomic analysis has revealed that our gut microbiota plays an important role in not only the maintenance of our health but also various diseases such as obesity, diabetes, inflammatory bowel disease, and allergy. However, most intestinal bacteria are considered ‘unculturable’ bacteria, and their functions remain unknown. Although culture-independent genomic approaches have enabled us to gain insight into their potential roles, culture-based approaches are still required to understand their characteristic features and phenotypes. To date, various culturing methods have been attempted to obtain these ‘unculturable’ bacteria, but most such methods require advanced techniques. Here, we have tried to isolate possible unculturable bacteria from a healthy Japanese individual by using commercially available media. A 16S rRNA (ribosomal RNA) gene metagenomic analysis revealed that each culture medium showed bacterial growth depending on its selective features and a possibility of the presence of novel bacterial species. Whole genome sequencing of these candidate strains suggested the isolation of 8 novel bacterial species classified in the Actinobacteria and Firmicutes phyla. Our approach indicates that a number of intestinal bacteria hitherto considered unculturable are potentially culturable and can be cultured on commercially available media. We have obtained novel gut bacteria from a healthy Japanese individual using a combination of comprehensive genomics and conventional culturing methods. We would expect that the discovery of such novel bacteria could illuminate pivotal roles for the gut microbiota in association with human health.

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April 21, 2020  |  

Genomic variation and strain-specific functional adaptation in the human gut microbiome during early life.

The human gut microbiome matures towards the adult composition during the first years of life and is implicated in early immune development. Here, we investigate the effects of microbial genomic diversity on gut microbiome development using integrated early childhood data sets collected in the DIABIMMUNE study in Finland, Estonia and Russian Karelia. We show that gut microbial diversity is associated with household location and linear growth of children. Single nucleotide polymorphism- and metagenomic assembly-based strain tracking revealed large and highly dynamic microbial pangenomes, especially in the genus Bacteroides, in which we identified evidence of variability deriving from Bacteroides-targeting bacteriophages. Our analyses revealed functional consequences of strain diversity; only 10% of Finnish infants harboured Bifidobacterium longum subsp. infantis, a subspecies specialized in human milk metabolism, whereas Russian infants commonly maintained a probiotic Bifidobacterium bifidum strain in infancy. Groups of bacteria contributing to diverse, characterized metabolic pathways converged to highly subject-specific configurations over the first two years of life. This longitudinal study extends the current view of early gut microbial community assembly based on strain-level genomic variation.

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April 21, 2020  |  

Phylogenetic barriers to horizontal transfer of antimicrobial peptide resistance genes in the human gut microbiota.

The human gut microbiota has adapted to the presence of antimicrobial peptides (AMPs), which are ancient components of immune defence. Despite its medical importance, it has remained unclear whether AMP resistance genes in the gut microbiome are available for genetic exchange between bacterial species. Here, we show that AMP resistance and antibiotic resistance genes differ in their mobilization patterns and functional compatibilities with new bacterial hosts. First, whereas AMP resistance genes are widespread in the gut microbiome, their rate of horizontal transfer is lower than that of antibiotic resistance genes. Second, gut microbiota culturing and functional metagenomics have revealed that AMP resistance genes originating from phylogenetically distant bacteria have only a limited potential to confer resistance in Escherichia coli, an intrinsically susceptible species. Taken together, functional compatibility with the new bacterial host emerges as a key factor limiting the genetic exchange of AMP resistance genes. Finally, our results suggest that AMPs induce highly specific changes in the composition of the human microbiota, with implications for disease risks.

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April 21, 2020  |  

MSC: a metagenomic sequence classification algorithm.

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.

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April 21, 2020  |  

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.

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April 21, 2020  |  

Metagenomic assembly through the lens of validation: recent advances in assessing and improving the quality of genomes assembled from metagenomes.

Metagenomic samples are snapshots of complex ecosystems at work. They comprise hundreds of known and unknown species, contain multiple strain variants and vary greatly within and across environments. Many microbes found in microbial communities are not easily grown in culture making their DNA sequence our only clue into their evolutionary history and biological function. Metagenomic assembly is a computational process aimed at reconstructing genes and genomes from metagenomic mixtures. Current methods have made significant strides in reconstructing DNA segments comprising operons, tandem gene arrays and syntenic blocks. Shorter, higher-throughput sequencing technologies have become the de facto standard in the field. Sequencers are now able to generate billions of short reads in only a few days. Multiple metagenomic assembly strategies, pipelines and assemblers have appeared in recent years. Owing to the inherent complexity of metagenome assembly, regardless of the assembly algorithm and sequencing method, metagenome assemblies contain errors. Recent developments in assembly validation tools have played a pivotal role in improving metagenomics assemblers. Here, we survey recent progress in the field of metagenomic assembly, provide an overview of key approaches for genomic and metagenomic assembly validation and demonstrate the insights that can be derived from assemblies through the use of assembly validation strategies. We also discuss the potential for impact of long-read technologies in metagenomics. We conclude with a discussion of future challenges and opportunities in the field of metagenomic assembly and validation. © The Author 2017. Published by Oxford University Press.

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