scholarly journals Technical note: overcoming host contamination in bovine vaginal metagenomic samples with Nanopore adaptive sequencing

2021 ◽  
Author(s):  
Chian Teng Ong ◽  
Elizabeth M Ross ◽  
Gry B Boe-Hansen ◽  
Conny Turni ◽  
Ben J Hayes ◽  
...  
Keyword(s):  
16S Rdna ◽  
Sequence Data ◽  
Amplicon Sequencing ◽  
Technical Note ◽  
Metagenomic Data ◽  
High Coverage ◽  
Long Reads ◽  
Oxford Nanopore ◽  
16S Rdna Amplicon Sequencing ◽  
Functional Profiles

Abstract Animal metagenomic studies, in which host-associated microbiomes are profiled, are an increasingly important contribution to our understanding of the physiological functions, health and susceptibility to diseases of livestock. One of the major challenges in these studies is host DNA contamination, which limits the sequencing capacity for metagenomic content and reduces the accuracy of metagenomic profiling. This is the first study comparing the effectiveness of different sequencing methods for profiling bovine vaginal metagenomic samples. We compared the new method of Oxford Nanopore Technologies (ONT) adaptive sequencing, which can be used to target or eliminate defined genetic sequences, to standard ONT sequencing, Illumina 16S rDNA amplicon sequencing, and Illumina shotgun sequencing. The efficiency of each method in recovering the metagenomic data and recalling the metagenomic profiles was assessed. ONT adaptive sequencing yielded a higher amount of metagenomic data than the other methods per 1 Gb of sequence data. The increased sequencing efficiency of ONT adaptive sequencing consequently reduced the amount of raw data needed to provide sufficient coverage for the metagenomic samples with high host-to-microbe DNA ratio. Additionally, the long reads generated by ONT adaptive sequencing retained the continuity of read information, which benefited the in-depth annotations for both taxonomical and functional profiles of the metagenome. The different methods resulted in the identification of different taxa. Genera Clostridium, which was identified at low abundances and categorised under Order “Unclassified Clostridiales” when using the 16S rDNA amplicon sequencing method, was identified to be the dominant genera in the sample when sequenced with the three other methods. Additionally, higher numbers of annotated genes were identified with ONT adaptive sequencing, which also produced high coverage on most of the commonly annotated genes. This study illustrates the advantages of ONT adaptive sequencing in improving the amount of metagenomic data derived from microbiome samples with high host-to-microbe DNA ratio and the advantage of long reads in preserving intact information for accurate annotations.

scholarly journals A long reads-based de-novo assembly of the genome of the Arlee homozygous line reveals chromosomal rearrangements in rainbow trout

2021 ◽  
Author(s):  
Guangtu Gao ◽  
Susana Magadan ◽  
Geoffrey C Waldbieser ◽  
Ramey C Youngblood ◽  
Paul A Wheeler ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Chromosome Number ◽  
Genome Assembly ◽  
De Novo Assembly ◽  
De Novo ◽  
Sequence Data ◽  
Structural Variations ◽  
High Coverage ◽  
Haploid Chromosome Number ◽  
Long Reads

Abstract Currently, there is still a need to improve the contiguity of the rainbow trout reference genome and to use multiple genetic backgrounds that will represent the genetic diversity of this species. The Arlee doubled haploid line was originated from a domesticated hatchery strain that was originally collected from the northern California coast. The Canu pipeline was used to generate the Arlee line genome de-novo assembly from high coverage PacBio long-reads sequence data. The assembly was further improved with Bionano optical maps and Hi-C proximity ligation sequence data to generate 32 major scaffolds corresponding to the karyotype of the Arlee line (2 N = 64). It is composed of 938 scaffolds with N50 of 39.16 Mb and a total length of 2.33 Gb, of which ∼95% was in 32 chromosome sequences with only 438 gaps between contigs and scaffolds. In rainbow trout the haploid chromosome number can vary from 29 to 32. In the Arlee karyotype the haploid chromosome number is 32 because chromosomes Omy04, 14 and 25 are divided into six acrocentric chromosomes. Additional structural variations that were identified in the Arlee genome included the major inversions on chromosomes Omy05 and Omy20 and additional 15 smaller inversions that will require further validation. This is also the first rainbow trout genome assembly that includes a scaffold with the sex-determination gene (sdY) in the chromosome Y sequence. The utility of this genome assembly is demonstrated through the improved annotation of the duplicated genome loci that harbor the IGH genes on chromosomes Omy12 and Omy13.

scholarly journals Composition and Diversity of the Ocular Surface Microbiota in Patients With Blepharitis in Northwestern China

2021 ◽  
Vol 8 ◽  
Author(s):  
Changhao Wang ◽  
Xiuhong Dou ◽  
Jian Li ◽  
Jie Wu ◽  
Yan Cheng ◽  
...  
Keyword(s):  
16S Rdna ◽  
Relative Abundance ◽  
Ocular Surface ◽  
Amplicon Sequencing ◽  
Northwestern China ◽  
Healthy Control Group ◽  
Control Group ◽  
Eyelid Margin ◽  
16S Rdna Amplicon Sequencing ◽  
Healthy Control

Purpose: To investigate the composition and diversity of the microbiota on the ocular surface of patients with blepharitis in northwestern China via 16S rDNA amplicon sequencing.Methods: Thirty-seven patients with blepharitis divided into groups of anterior, posterior and mixed blepharitis and twenty healthy controls from northwestern China were enrolled in the study. Samples were collected from the eyelid margin and conjunctival sac of each participant. The V3–V4 region of bacterial 16S rDNA in each sample was amplified and sequenced on the Illumina HiSeq 2500 sequencing platform, and the differences in taxonomy and diversity among different groups were compared.Results: The composition of the ocular surface microbiota of patients with blepharitis was similar to that of healthy subjects, but there were differences in the relative abundance of each bacterium. At the phylum level, the abundances of Actinobacteria, Cyanobacteria, Verrucomicrobia, Acidobacteria, Chloroflexi, and Atribacteria were significantly higher in the blepharitis group than in the healthy control group, while the relative abundance of Firmicutes was significantly lower (p < 0.05, Mann-Whitney U). At the genus level, the abundances of Lactobacillus, Ralstonia, Bacteroides, Akkermansia, Bifidobacterium, Escherichia-Shigella, Faecalibacterium, and Brevibacterium were significantly higher in the blepharitis group than in the healthy control group, while the relative abundances of Bacillus, Staphylococcus, Streptococcus, and Acinetobacter were significantly lower in the blepharitis group (p < 0.05, Mann-Whitney U). The microbiota of anterior blepharitis was similar to that of mixed blepharitis but different from that of posterior blepharitis. Lactobacillus and Bifidobacterium are biomarkers of posterior blepharitis, and Ralstonia is a biomarker of mixed blepharitis. There was no significant difference in the ocular surface microbiota between the eyelid margin and conjunctival sac with or without blepharitis.Conclusion: The ocular surface microbiota of patients with blepharitis varied among different study groups, according to 16S rDNA amplicon sequencing analysis. The reason might be due to the participants being from different environments and having different lifestyles. Lactobacillus, Bifidobacterium, Akkermansia, Ralstonia, and Bacteroides may play important roles in the pathogenesis of blepharitis.

scholarly journals BleTIES: Annotation of natural genome editing in ciliates using long read sequencing

2021 ◽  
Author(s):  
Brandon K. B. Seah ◽  
Estienne C. Swart
Keyword(s):  
Dna Sequences ◽  
Sequence Data ◽  
Low Complexity ◽  
Supplementary Information ◽  
Neighboring Element ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Long Read ◽  
Element Elimination

Ciliates are single-celled eukaryotes that eliminate specific, interspersed DNA sequences (internally eliminated sequences, IESs) from their genomes during development. These are challenging to annotate and assemble because IES-containing sequences are much less abundant in the cell than those without, and IES sequences themselves often contain repetitive and low-complexity sequences. Long read sequencing technologies from Pacific Biosciences and Oxford Nanopore have the potential to reconstruct longer IESs than has been possible with short reads, and also the ability to detect correlations of neighboring element elimination. Here we present BleTIES, a software toolkit for detecting, assembling, and analyzing IESs using mapped long reads. Availability and implementation: BleTIES is implemented in Python 3. Source code is available at https://github.com/Swart-lab/bleties (MIT license), and also distributed via Bioconda. Contact: [email protected] Supplementary information: Benchmarking of BleTIES with published sequence data.

scholarly journals Metagenomic Analysis of Slovak Bryndza Cheese Using Next-Generation 16S rDNA Amplicon Sequencing

2016 ◽  
Vol 15 (1) ◽  
pp. 23-34 ◽  
Author(s):  
Matej Planý ◽  
Tomáš Kuchta ◽  
Katarína Šoltýs ◽  
Tomáš Szemes ◽  
Domenico Pangallo ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rdna ◽  
Lactococcus Lactis ◽  
Microbial Population ◽  
Starter Culture ◽  
Amplicon Sequencing ◽  
16S Rrna Genes ◽  
Rrna Genes ◽  
Next Generation ◽  
16S Rdna Amplicon Sequencing

Abstract Knowledge about diversity and taxonomic structure of the microbial population present in traditional fermented foods plays a key role in starter culture selection, safety improvement and quality enhancement of the end product. Aim of this study was to investigate microbial consortia composition in Slovak bryndza cheese. For this purpose, we used culture-independent approach based on 16S rDNA amplicon sequencing using next generation sequencing platform. Results obtained by the analysis of three commercial (produced on industrial scale in winter season) and one traditional (artisanal, most valued, produced in May) Slovak bryndza cheese sample were compared. A diverse prokaryotic microflora composed mostly of the genera Lactococcus, Streptococcus, Lactobacillus, and Enterococcus was identified. Lactococcus lactis subsp. lactis and Lactococcus lactis subsp. cremoris were the dominant taxons in all tested samples. Second most abundant species, detected in all bryndza cheeses, were Lactococcus fujiensis and Lactococcus taiwanensis, independently by two different approaches, using different reference 16S rRNA genes databases (Greengenes and NCBI respectively). They have been detected in bryndza cheese samples in substantial amount for the first time. The narrowest microbial diversity was observed in a sample made with a starter culture from pasteurised milk. Metagenomic analysis by high-throughput sequencing using 16S rRNA genes seems to be a powerful tool for studying the structure of the microbial population in cheeses.

scholarly journals Near-complete Lokiarchaeota genomes from complex environmental samples using long and short read metagenomic analyses

2019 ◽  
Author(s):  
Eva F. Caceres ◽  
William H. Lewis ◽  
Felix Homa ◽  
Tom Martin ◽  
Andreas Schramm ◽  
...  
Keyword(s):  
Large Scale ◽  
Phylogenetic Analyses ◽  
Metagenomic Data ◽  
Endosomal Sorting ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Complete Genomes ◽  
Culture Independent ◽  
Long Read

AbstractAsgard archaea is a recently proposed superphylum currently comprised of five recognised phyla: Lokiarchaeota, Thorarchaeota, Odinarchaeota, Heimdallarchaeota and Helarchaeota. Members of this group have been identified based on culture-independent approaches with several metagenome-assembled genomes (MAGs) reconstructed to date. However, most of these genomes consist of several relatively small contigs, and, until recently, no complete Asgard archaea genome is yet available. Large scale phylogenetic analyses suggest that Asgard archaea represent the closest archaeal relatives of eukaryotes. In addition, members of this superphylum encode proteins that were originally thought to be specific to eukaryotes, including components of the trafficking machinery, cytoskeleton and endosomal sorting complexes required for transport (ESCRT). Yet, these findings have been questioned on the basis that the genome sequences that underpin them were assembled from metagenomic data, and could have been subjected to contamination and other assembly artefacts. Even though several lines of evidence indicate that the previously reported findings were not affected by these issues, having access to high-quality and preferentially fully closed Asgard archaea genomes is needed to definitively close this debate. Current long-read sequencing technologies such as Oxford Nanopore allow the generation of long reads in a high-throughput manner making them suitable for their use in metagenomics. Although the use of long reads is still limited in this field, recent analyses have shown that it is feasible to obtain complete or near-complete genomes of abundant members of mock communities and metagenomes of various level of complexity. Here, we show that long read metagenomics can be successfully applied to obtain near-complete genomes of low-abundant members of complex communities from sediment samples. We were able to reconstruct six MAGs from different Lokiarchaeota lineages that show high completeness and low fragmentation, with one of them being a near-complete genome only consisting of three contigs. Our analyses confirm that the eukaryote-like features previously associated with Lokiarchaeota are not the result of contamination or assembly artefacts, and can indeed be found in the newly reconstructed genomes.

scholarly journals Sediment-associated microbial community profiling: sample pre-processing through sequential membrane filtration for 16s rDNA amplicon sequencing

2020 ◽  
Author(s):  
Joeselle M. Serrana ◽  
Kozo Watanabe
Keyword(s):  
Microbial Community ◽  
16S Rdna ◽  
Community Composition ◽  
Membrane Filtration ◽  
Amplicon Sequencing ◽  
Sediment Samples ◽  
Community Profiling ◽  
Significant Difference ◽  
16S Rdna Amplicon Sequencing ◽  
Read Abundance

ABSTRACTSequential membrane filtration as a pre-processing step for the isolation of microorganisms could provide good quality and integrity DNA that can be preserved and kept at ambient temperatures before community profiling through culture-independent molecular techniques, e.g., 16s rDNA amplicon sequencing. Here, we assessed the impact of pre-processing sediment samples by sequential membrane filtration (from 10, 5 to 0.22 μm pore size membrane filters) for 16s rDNA-based community profiling of sediment-associated microorganisms. Specifically, we examined if there would be method-driven differences between non- and pre-processed sediment samples regarding the quality and quantity of extracted DNA, PCR amplicon, resulting high-throughput sequencing reads, microbial diversity, and community composition. We found no significant difference in the quality and quantity of extracted DNA and PCR amplicons between the two methods. Although we found a significant difference in raw and quality-filtered reads, read abundance after bioinformatics processing (i.e., denoising and the chimeric-read filtering steps) were not significantly different. These results suggest that read abundance after these read processing steps were not influenced by sediment processing or lack thereof. Although the non- and pre-processed sediment samples had more unique than shared amplicon sequence variants (ASVs), we report that their shared ASVs accounted for 74% of both methods’ absolute read abundance. More so at the genus level, the final collection filter identified most of the genera (95% of the reads) captured from the non-processed samples, with a total of 51 false-negative (2%) and 59 false-positive genera (3%). Accordingly, the diversity estimates and community composition were not significantly different between the non- and pre-processed samples. We demonstrate that while there were differences in shared and unique taxa, both methods revealed comparable microbial diversity and community composition. We also suggest the inclusion of sequential filters (i.e., pre- and mid-filters) in the community profiling, given the additional taxa not detected from the non-processed and the final collection filter. Our observations highlight the feasibility of pre-processing sediment samples for community analysis and the need to further assess sampling strategies to help conceptualize appropriate study designs for sediment-associated microbial community profiling.

scholarly journals Testing the advantages and disadvantages of short- and long- read eukaryotic metagenomics using simulated reads

2020 ◽  
Author(s):  
William S Pearman ◽  
Nikki E Freed ◽  
Olin K Silander
Keyword(s):  
Microbial Communities ◽  
Classification Accuracy ◽  
Community Diversity ◽  
Read Length ◽  
Metagenomic Data ◽  
Taxonomic Resolution ◽  
Sequence Length ◽  
Advantages And Disadvantages ◽  
Long Reads ◽  
Oxford Nanopore

Abstract Background The first step in understanding ecological community diversity and dynamics is quantifying community membership. An increasingly common method for doing so is through metagenomics. Because of the rapidly increasing popularity of this approach, a large number of computational tools and pipelines are available for analysing metagenomic data. However, the majority of these tools have been designed and benchmarked using highly accurate short read data (i.e. Illumina), with few studies benchmarking classification accuracy for long error-prone reads (PacBio or Oxford Nanopore). In addition, few tools have been benchmarked for non-microbial communities. Results Here we compare simulated long reads from Oxford Nanopore and Pacific Biosciences with high accuracy Illumina read sets to systematically investigate the effects of sequence length and taxon type on classification accuracy for metagenomic data from both microbial and non-microbial communities. We show that very generally, classification accuracy is far lower for non-microbial communities, even at low taxonomic resolution (e.g. family rather than genus). We then show that for two popular taxonomic classifiers, long reads can significantly increase classification accuracy, and this is most pronounced for non-microbial communities. Conclusions This work provides insight on the expected accuracy for metagenomic analyses for different taxonomic groups, and establishes the point at which read length becomes more important than error rate for assigning the correct taxon.

scholarly journals Comparing 16S rDNA amplicon sequencing and hybridization capture for pea aphid microbiota diversity analysis

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Marie Cariou ◽  
Céline Ribière ◽  
Stéphanie Morlière ◽  
Jean-Pierre Gauthier ◽  
Jean-Christophe Simon ◽  
...  
Keyword(s):  
16S Rdna ◽  
Amplicon Sequencing ◽  
Pea Aphid ◽  
Diversity Analysis ◽  
Hybridization Capture ◽  
16S Rdna Amplicon Sequencing ◽  
Microbiota Diversity

scholarly journals MetaLAFFA: a flexible, end-to-end, distributed computing-compatible metagenomic functional annotation pipeline

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Alexander Eng ◽  
Adrian J. Verster ◽  
Elhanan Borenstein
Keyword(s):  
Distributed Computing ◽  
Functional Annotation ◽  
Sequence Data ◽  
Metagenomic Data ◽  
Metagenomic Sequencing ◽  
Distributed Computing Systems ◽  
Annotation Pipeline ◽  
Shotgun Metagenomic Sequencing ◽  
End To End ◽  
Functional Profiles

Abstract Background Microbial communities have become an important subject of research across multiple disciplines in recent years. These communities are often examined via shotgun metagenomic sequencing, a technology which can offer unique insights into the genomic content of a microbial community. Functional annotation of shotgun metagenomic data has become an increasingly popular method for identifying the aggregate functional capacities encoded by the community’s constituent microbes. Currently available metagenomic functional annotation pipelines, however, suffer from several shortcomings, including limited pipeline customization options, lack of standard raw sequence data pre-processing, and insufficient capabilities for integration with distributed computing systems. Results Here we introduce MetaLAFFA, a functional annotation pipeline designed to take unfiltered shotgun metagenomic data as input and generate functional profiles. MetaLAFFA is implemented as a Snakemake pipeline, which enables convenient integration with distributed computing clusters, allowing users to take full advantage of available computing resources. Default pipeline settings allow new users to run MetaLAFFA according to common practices while a Python module-based configuration system provides advanced users with a flexible interface for pipeline customization. MetaLAFFA also generates summary statistics for each step in the pipeline so that users can better understand pre-processing and annotation quality. Conclusions MetaLAFFA is a new end-to-end metagenomic functional annotation pipeline with distributed computing compatibility and flexible customization options. MetaLAFFA source code is available at https://github.com/borenstein-lab/MetaLAFFA and can be installed via Conda as described in the accompanying documentation.

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