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Auto Tag: Metagenomics

September 22, 2019

A near complete snapshot of the Zea mays seedling transcriptome revealed from ultra-deep sequencing.

RNA-sequencing (RNA-seq) enables in-depth exploration of transcriptomes, but typical sequencing depth often limits its comprehensiveness. In this study, we generated nearly 3 billion RNA-Seq reads, totaling 341 Gb of sequence, from a Zea mays seedling sample. At this depth, a near complete snapshot of the transcriptome was observed consisting of over 90% of the annotated transcripts, including lowly expressed transcription factors. A novel hybrid strategy combining de novo and reference-based assemblies yielded a transcriptome consisting of 126,708 transcripts with 88% of expressed known genes assembled to full-length. We improved current annotations by adding 4,842 previously unannotated transcript variants and many new features, including 212 maize transcripts, 201 genes, 10 genes with undocumented potential roles in seedlings as well as maize lineage specific gene fusion events. We demonstrated the power of deep sequencing for large transcriptome studies by generating a high quality transcriptome, which provides a rich resource for the research community.

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September 22, 2019

Draft genome sequence of Sulfurospirillum sp. strain MES, reconstructed from the metagenome of a microbial electrosynthesis system.

A draft genome of Sulfurospirillum sp. strain MES was isolated through taxonomic binning of a metagenome sequenced from a microbial electrosynthesis system (MES) actively producing acetate and hydrogen. The genome contains the nosZDFLY genes, which are involved in nitrous oxide reduction, suggesting the potential role of this strain in denitrification. Copyright © 2015 Ross et al.

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September 22, 2019

Moving beyond microbiome-wide associations to causal microbe identification.

Microbiome-wide association studies have established that numerous diseases are associated with changes in the microbiota. These studies typically generate a long list of commensals implicated as biomarkers of disease, with no clear relevance to disease pathogenesis. If the field is to move beyond correlations and begin to address causation, an effective system is needed for refining this catalogue of differentially abundant microbes and to allow subsequent mechanistic studies. Here we demonstrate that triangulation of microbe-phenotype relationships is an effective method for reducing the noise inherent in microbiota studies and enabling identification of causal microbes. We found that gnotobiotic mice harbouring different microbial communities exhibited differential survival in a colitis model. Co-housing of these mice generated animals that had hybrid microbiotas and displayed intermediate susceptibility to colitis. Mapping of microbe-phenotype relationships in parental mouse strains and in mice with hybrid microbiotas identified the bacterial family Lachnospiraceae as a correlate for protection from disease. Using directed microbial culture techniques, we discovered Clostridium immunis, a previously unknown bacterial species from this family, that-when administered to colitis-prone mice-protected them against colitis-associated death. To demonstrate the generalizability of our approach, we used it to identify several commensal organisms that induce intestinal expression of an antimicrobial peptide. Thus, we have used microbe-phenotype triangulation to move beyond the standard correlative microbiome study and identify causal microbes for two completely distinct phenotypes. Identification of disease-modulating commensals by microbe-phenotype triangulation may be more broadly applicable to human microbiome studies.

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September 22, 2019

Advantages of genome sequencing by long-read sequencer using SMRT technology in medical area.

PacBio RS II is the first commercialized third-generation DNA sequencer able to sequence a single molecule DNA in real-time without amplification. PacBio RS II’s sequencing technology is novel and unique, enabling the direct observation of DNA synthesis by DNA polymerase. PacBio RS II confers four major advantages compared to other sequencing technologies: long read lengths, high consensus accuracy, a low degree of bias, and simultaneous capability of epigenetic characterization. These advantages surmount the obstacle of sequencing genomic regions such as high/low G+C, tandem repeat, and interspersed repeat regions. Moreover, PacBio RS II is ideal for whole genome sequencing, targeted sequencing, complex population analysis, RNA sequencing, and epigenetics characterization. With PacBio RS II, we have sequenced and analyzed the genomes of many species, from viruses to humans. Herein, we summarize and review some of our key genome sequencing projects, including full-length viral sequencing, complete bacterial genome and almost-complete plant genome assemblies, and long amplicon sequencing of a disease-associated gene region. We believe that PacBio RS II is not only an effective tool for use in the basic biological sciences but also in the medical/clinical setting.

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September 22, 2019

BIGMAC : breaking inaccurate genomes and merging assembled contigs for long read metagenomic assembly.

The problem of de-novo assembly for metagenomes using only long reads is gaining attention. We study whether post-processing metagenomic assemblies with the original input long reads can result in quality improvement. Previous approaches have focused on pre-processing reads and optimizing assemblers. BIGMAC takes an alternative perspective to focus on the post-processing step.Using both the assembled contigs and original long reads as input, BIGMAC first breaks the contigs at potentially mis-assembled locations and subsequently scaffolds contigs. Our experiments on metagenomes assembled from long reads show that BIGMAC can improve assembly quality by reducing the number of mis-assemblies while maintaining or increasing N50 and N75. Moreover, BIGMAC shows the largest N75 to number of mis-assemblies ratio on all tested datasets when compared to other post-processing tools. BIGMAC demonstrates the effectiveness of the post-processing approach in improving the quality of metagenomic assemblies.

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September 22, 2019

Carbohydrate staple food modulates gut microbiota of Mongolians in China.

Gut microbiota is a determining factor in human physiological functions and health. It is commonly accepted that diet has a major influence on the gut microbial community, however, the effects of diet is not fully understood. The typical Mongolian diet is characterized by high and frequent consumption of fermented dairy products and red meat, and low level of carbohydrates. In this study, the gut microbiota profile of 26 Mongolians whom consumed wheat, rice and oat as the sole carbohydrate staple food for a week each consecutively was determined. It was observed that changes in staple carbohydrate rapidly (within a week) altered gut microbial community structure and metabolic pathway of the subjects. Wheat and oat favored bifidobacteria (Bifidobacterium catenulatum, Bifodobacteriumbifidum, Bifidobacterium adolescentis); whereas rice suppressed bifidobacteria (Bifidobacterium longum, Bifidobacterium adolescentis) and wheat suppresses Lactobaciilus, Ruminococcus and Bacteroides. The study exhibited two gut microbial clustering patterns with the preference of fucosyllactose utilization linking to fucosidase genes (glycoside hydrolase family classifications: GH95 and GH29) encoded by Bifidobacterium, and xylan and arabinoxylan utilization linking to xylanase and arabinoxylanase genes encoded by Bacteroides. There was also a correlation between Lactobacillus ruminis and sialidase, as well as Butyrivibrio crossotus and xylanase/xylosidase. Meanwhile, a strong concordance was found between the gastrointestinal bacterial microbiome and the intestinal virome. Present research will contribute to understanding the impacts of the dietary carbohydrate on human gut microbiome, which will ultimately help understand relationships between dietary factor, microbial populations, and the health of global humans.

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September 22, 2019

16S rRNA long-read sequencing of the granulation tissue from nonsmokers and smokers-severe chronic periodontitis patients

Smoking has been associated with increased risk of periodontitis. The aim of the present study was to compare the periodontal disease severity among smokers and nonsmokers which may help in better understanding of predisposition to this chronic inflammation mediated diseases. We selected deep-seated infected granulation tissue removed during periodontal flap surgery procedures for identification and differential abundance of residential bacterial species among smokers and nonsmokers through long-read sequencing technology targeting full-length 16S rRNA gene. A total of 8 phyla were identified among which Firmicutes and Bacteroidetes were most dominating. Differential abundance analysis of OTUs through PICRUST showed significant (p>0.05) abundance of Phyla-Fusobacteria (Streptobacillus moniliformis); Phyla-Firmicutes (Streptococcus equi), and Phyla Proteobacteria (Enhydrobacter aerosaccus) in nonsmokers compared to smokers. The differential abundance of oral metagenomes in smokers showed significant enrichment of host genes modulating pathways involving primary immunodeficiency, citrate cycle, streptomycin biosynthesis, vitamin B6 metabolism, butanoate metabolism, glycine, serine, and threonine metabolism pathways. While thiamine metabolism, amino acid metabolism, homologous recombination, epithelial cell signaling, aminoacyl-tRNA biosynthesis, phosphonate/phosphinate metabolism, polycyclic aromatic hydrocarbon degradation, synthesis and degradation of ketone bodies, translation factors, Ascorbate and aldarate metabolism, and DNA replication pathways were significantly enriched in nonsmokers, modulation of these pathways in oral cavities due to differential enrichment of metagenomes in smokers may lead to an increased susceptibility to infections and/or higher formation of DNA adducts, which may increase the risk of carcinogenesis.

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September 22, 2019

Metagenomic binning and association of plasmids with bacterial host genomes using DNA methylation.

Shotgun metagenomics methods enable characterization of microbial communities in human microbiome and environmental samples. Assembly of metagenome sequences does not output whole genomes, so computational binning methods have been developed to cluster sequences into genome ‘bins’. These methods exploit sequence composition, species abundance, or chromosome organization but cannot fully distinguish closely related species and strains. We present a binning method that incorporates bacterial DNA methylation signatures, which are detected using single-molecule real-time sequencing. Our method takes advantage of these endogenous epigenetic barcodes to resolve individual reads and assembled contigs into species- and strain-level bins. We validate our method using synthetic and real microbiome sequences. In addition to genome binning, we show that our method links plasmids and other mobile genetic elements to their host species in a real microbiome sample. Incorporation of DNA methylation information into shotgun metagenomics analyses will complement existing methods to enable more accurate sequence binning.

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September 22, 2019

Profiling of oral microbiota in early childhood caries using Single-Molecule Real-Time Sequencing

Background: Alterations of oral microbiota are the main cause of the progression of caries. The goal of this study was to characterize the oral microbiota in childhood caries based on single-molecule real-time sequencing. Methods: A total of 21 preschoolers, aged 3-5 years old with severe early childhood caries, and 20 age-matched, caries-free children as controls were recruited. Saliva samples were collected, followed by DNA extraction, Pacbio sequencing and phylogenetic analyses of the oral microbial communities. Results: 876 species derived from 13 known bacterial phyla and 110 genera were detected from 41 children using Pacbio sequencing. At the species level, 38 species, including Veillonella spp., Streptococcus spp., Prevotella spp. and Lactobacillus spp., showed higher abundance in the caries group compared to the caries-free group (p<0.05). The core microbiota at the genus and species levels was more stable in the caries-free micro-ecological niche. At follow-up, oral examinations 6 months after sample collection, development of new dental caries was observed in 5 children (the transitional group) among the 21 caries free children. Compared with the caries-free children, in the transitional and caries groups, 6 species, which were more abundant in the caries-free group, exhibited a relatively low abundance in both the caries group and the transitional group (p<0.05). We conclude that Abiotrophia spp., Neisseria spp. and Veillonella spp., are essential for maintaining a healthy oral microbial ecosystem. Prevotella spp., Lactobacillus spp., Dialister spp. and Filifactor spp. may be related to the pathogenesis and progression of dental caries.

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September 22, 2019

Comprehensive exploration of the rumen microbial ecosystem with advancements in metagenomics

Ruminant farming and its environmental impact has long remained an economic concern. Metagenomics unravel the vast structural and functional diversity of the rumen microbial community that plays a major role in animal nutrition. Hereby, we summarize rumen metagenomic studies that have enhanced the knowledge of rumen microbe dynamics subsequently leading to development of better feed strategies to improve livestock production and reduce methane emissions.

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September 22, 2019

Clinical PathoScope: rapid alignment and filtration for accurate pathogen identification in clinical samples using unassembled sequencing data.

The use of sequencing technologies to investigate the microbiome of a sample can positively impact patient healthcare by providing therapeutic targets for personalized disease treatment. However, these samples contain genomic sequences from various sources that complicate the identification of pathogens.Here we present Clinical PathoScope, a pipeline to rapidly and accurately remove host contamination, isolate microbial reads, and identify potential disease-causing pathogens. We have accomplished three essential tasks in the development of Clinical PathoScope. First, we developed an optimized framework for pathogen identification using a computational subtraction methodology in concordance with read trimming and ambiguous read reassignment. Second, we have demonstrated the ability of our approach to identify multiple pathogens in a single clinical sample, accurately identify pathogens at the subspecies level, and determine the nearest phylogenetic neighbor of novel or highly mutated pathogens using real clinical sequencing data. Finally, we have shown that Clinical PathoScope outperforms previously published pathogen identification methods with regard to computational speed, sensitivity, and specificity.Clinical PathoScope is the only pathogen identification method currently available that can identify multiple pathogens from mixed samples and distinguish between very closely related species and strains in samples with very few reads per pathogen. Furthermore, Clinical PathoScope does not rely on genome assembly and thus can more rapidly complete the analysis of a clinical sample when compared with current assembly-based methods. Clinical PathoScope is freely available at: http://sourceforge.net/projects/pathoscope/.

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September 22, 2019

Evolution of selective-sequencing approaches for virus discovery and virome analysis.

Recent advances in sequencing technologies have transformed the field of virus discovery and virome analysis. Once mostly confined to the traditional Sanger sequencing based individual virus discovery, is now entirely replaced by high throughput sequencing (HTS) based virus metagenomics that can be used to characterize the nature and composition of entire viromes. To better harness the potential of HTS for the study of viromes, sample preparation methodologies use different approaches to exclude amplification of non-viral components that can overshadow low-titer viruses. These virus-sequence enrichment approaches mostly focus on the sample preparation methods, like enzymatic digestion of non-viral nucleic acids and size exclusion of non-viral constituents by column filtration, ultrafiltration or density gradient centrifugation. However, recently a new approach of virus-sequence enrichment called virome-capture sequencing, focused on the amplification or HTS library preparation stage, was developed to increase the ability of virome characterization. This new approach has the potential to further transform the field of virus discovery and virome analysis, but its technical complexity and sequence-dependence warrants further improvements. In this review we discuss the different methods, their applications and evolution, for selective sequencing based virome analysis and also propose refinements needed to harness the full potential of HTS for virome analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

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September 22, 2019

The methylome of the gut microbiome: disparate Dam methylation patterns in intestinal Bacteroides dorei

Despite the large interest in the human microbiome in recent years, there are no reports of bacterial DNA methylation in the microbiome. Here metagenomic sequencing using the Pacific Biosciences platform allowed for rapid identification of bacterial GATC methylation status of a bacterial species in human stool samples. For this work, two stool samples were chosen that were dominated by a single species, Bacteroides dorei. Based on 16S rRNA analysis, this species represented over 45% of the bacteria present in these two samples. The B. dorei genome sequence from these samples was determined and the GATC methylation sites mapped. The Bacteroides dorei genome from one subject lacked any GATC methylation and lacked the DNA adenine methyltransferase genes. In contrast, B. dorei from another subject contained 20,551 methylated GATC sites. Of the 4970 open reading frames identified in the GATC methylated B. dorei genome, 3184 genes were methylated as well as 1735 GATC methylations in intergenic regions. These results suggest that DNA methylation patterns are important to consider in multi-omic analyses of microbiome samples seeking to discover the diversity of bacterial functions and may differ between disease states.

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September 22, 2019

Improved OTU-picking using long-read 16S rRNA gene amplicon sequencing and generic hierarchical clustering

BACKGROUND: High-throughput bacterial 16S rRNA gene sequencing followed by clustering of short sequences into operational taxonomic units (OTUs) is widely used for microbiome profiling. However, clustering of short 16S rRNA gene reads into biologically meaningful OTUs is challenging, in part because nucleotide variation along the 16S rRNA gene is only partially captured by short reads. The recent emergence of long-read platforms, such as single-molecule real-time (SMRT) sequencing from Pacific Biosciences, offers the potential for improved taxonomic and phylogenetic profiling. Here, we evaluate the performance of long- and short-read 16S rRNA gene sequencing using simulated and experimental data, followed by OTU inference using computational pipelines based on heuristic and complete-linkage hierarchical clustering. RESULTS: In simulated data, long-read sequencing was shown to improve OTU quality and decrease variance. We then profiled 40 human gut microbiome samples using a combination of Illumina MiSeq and Blautia-specific SMRT sequencing, further supporting the notion that long reads can identify additional OTUs. We implemented a complete-linkage hierarchical clustering strategy using a flexible computational pipeline, tailored specifically for PacBio circular consensus sequencing (CCS) data that outperforms heuristic methods in most settings: https://github.com/oscar-franzen/oclust/. CONCLUSION: Our data demonstrate that long reads can improve OTU inference; however, the choice of clustering algorithm and associated clustering thresholds has significant impact on performance.

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September 22, 2019

MetaSort untangles metagenome assembly by reducing microbial community complexity.

Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities.

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