scholarly journals An integrated metagenome catalog reveals novel insights into the murine gut microbiome

2019 ◽  
Author(s):  
Till Robin Lesker ◽  
Abilash Chakravarthy ◽  
Eric. J.C. Gálvez ◽  
Ilias Lagkouvardos ◽  
John F. Baines ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Taxonomic Resolution ◽  
Specific Gene ◽  
Rrna Gene ◽  
Community Members ◽  
Microbial Ecosystems ◽  
Gene Data ◽  
Functional Profiles ◽  
Gut Metagenome

AbstractThe vast complexity of host-associated microbial ecosystems requires generation of host-specific gene catalogs to survey the functions and diversity of these communities. We generated a comprehensive resource, the integrated mouse gut metagenome catalog (iMGMC), comprising 4.6 million unique genes and 660 high-quality metagenome-assembled genomes (MAGs) linked to reconstructed full-length 16S rRNA gene sequences. iMGMC enables unprecedented coverage and taxonomic resolution, i.e. more than 89% of the identified taxa are not represented in any other databases. The tool (github.com/tillrobin/iMGMC) allowed characterizing the diversity and functions of prevalent and previously unknown microbial community members along the gastrointestinal tract. Moreover, we show that integration of MAGs and 16S rRNA gene data allows a more accurate prediction of functional profiles of communities than based on 16S rRNA amplicons alone. Integrated gene catalogs such as iMGMC are needed to enhance the resolution of numerous existing and future sequencing-based studies.

Chilling and cultivar type affect the diversity of bacterial endophytes colonizing sweet pepper (Capsicum anuumL.)

2006 ◽  
Vol 52 (11) ◽  
pp. 1036-1045 ◽  
Author(s):  
Frank Rasche ◽  
Robert Trondl ◽  
Christina Naglreiter ◽  
Thomas G Reichenauer ◽  
Angela Sessitsch
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Sweet Pepper ◽  
Gene Analysis ◽  
Rrna Gene ◽  
Temperature Sensitive ◽  
Bacterial Endophytes ◽  
Community Members ◽  
16S Rrna Gene Analysis ◽  
Gene Libraries

A climate chamber experiment was conducted to assay the effect of low temperatures (chilling) on the diversity of bacteria colonizing the endospheres of two thermophilic sweet pepper (Capsicum anuum L.) cultivars, Milder Spiral and Ziegenhorn Bello. Structural diversity was analyzed by 16S rRNA-based terminal restriction fragment length polymorphism (T-RFLP) analysis and by the generation of 16S rRNA gene libraries to determine dominant community members in T-RFLP profiles. Cultivable community members colonizing lines Milder Spiral and Ziegenhorn Bello were identified by 16S rRNA gene analysis. T-RFLP profiles and 16S rRNA gene libraries revealed a high heterogeneity of community composition due to chilling and suggested further the existence of cultivar-specific communities. The majority of isolates obtained from the cultivar Milder Spiral were assigned as high-G+C Gram-positive bacteria (Microbacterium sp., Micrococcus sp., Rhodococcus sp.) and Firmicutes (Staphylococcus sp.). Of the isolated endophytes obtained from cultivar Zeigenhorn Bello, 93% were affiliated with Staphylococcus aureus and Bacillus sp. (Firmicutes). The experimental set-up was suited to demonstrate that chilling and cultivar type can influence the diversity of bacterial endophytes colonizing sweet pepper. We propose additional chilling experiments to investigate the effect of chilling on functional, plant-beneficial abilities of bacterial endophytes associated with low-temperature-sensitive crops, such as sweet pepper.Key words: chilling, thermophilic sweet pepper, bacterial endophyte diversity, 16S rRNA gene analysis.

scholarly journals Balance Trees Reveal Microbial Niche Differentiation

mSystems ◽  
2017 ◽  
Vol 2 (1) ◽  
Author(s):  
James T. Morton ◽  
Jon Sanders ◽  
Robert A. Quinn ◽  
Daniel McDonald ◽  
Antonio Gonzalez ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Open Source ◽  
Niche Differentiation ◽  
Difficult Problem ◽  
Individual Species ◽  
Rrna Gene ◽  
Link Type ◽  
Open Source License ◽  
Gene Data

ABSTRACT By explicitly accounting for the compositional nature of 16S rRNA gene data through the concept of balances, balance trees yield novel biological insights into niche differentiation. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/gneiss . Advances in sequencing technologies have enabled novel insights into microbial niche differentiation, from analyzing environmental samples to understanding human diseases and informing dietary studies. However, identifying the microbial taxa that differentiate these samples can be challenging. These issues stem from the compositional nature of 16S rRNA gene data (or, more generally, taxon or functional gene data); the changes in the relative abundance of one taxon influence the apparent abundances of the others. Here we acknowledge that inferring properties of individual bacteria is a difficult problem and instead introduce the concept of balances to infer meaningful properties of subcommunities, rather than properties of individual species. We show that balances can yield insights about niche differentiation across multiple microbial environments, including soil environments and lung sputum. These techniques have the potential to reshape how we carry out future ecological analyses aimed at revealing differences in relative taxonomic abundances across different samples. IMPORTANCE By explicitly accounting for the compositional nature of 16S rRNA gene data through the concept of balances, balance trees yield novel biological insights into niche differentiation. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/gneiss . Author Video: An author video summary of this article is available.

scholarly journals Accounting for 16S rRNA copy number prediction uncertainty and its implications in microbial diversity analyses

2021 ◽  
Author(s):  
Yingnan Gao ◽  
Martin Wu
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Diversity ◽  
Bacterial Communities ◽  
Beta Diversity ◽  
Copy Number ◽  
Rrna Gene ◽  
Prediction Uncertainty ◽  
Functional Profiles ◽  
Diversity Studies

Background: 16S rRNA gene has been widely used in microbial diversity studies to determine the community composition and structure. 16S rRNA gene copy number (16S GCN) varies among microbial species and this variation introduces biases to the relative cell abundance estimated using 16S rRNA read counts. To correct the biases, methods (e.g., PICRUST2) have been developed to predict 16S GCN. 16S GCN predictions come with inherent uncertainty, which is often ignored in the downstream analyses. However, a recent study suggests that the uncertainty can be so great that copy number correction is not justified in practice. Despite the significant implications in 16S rRNA based microbial diversity studies, the uncertainty associated with 16S GCN predictions has not been well characterized and its impact on microbial diversity studies needs to be investigated. Results: Here we develop RasperGade16S, a novel method and software to better model and capture the inherent uncertainty in 16S rRNA GCN prediction. RasperGade16S implements a maximum likelihood framework of pulsed evolution model and explicitly accounts for intraspecific GCN variation and heterogeneous GCN evolution rates among species. Using cross validation, we show that our method provides robust confidence estimates for the GCN predictions and outperforms PICRUST2 in both precision and recall. We have predicted GCN for 592605 OTUs in the SILVA database and tested 113842 bacterial communities that represent an exhaustive and diverse list of engineered and natural environments. We found that the prediction uncertainty is small enough for 99% of the communities that 16S GCN correction should improve their compositional and functional profiles estimated using 16S rRNA reads. On the other hand, we found that GCN variation has limited impacts on beta-diversity analyses such as PCoA, PERMANOVA and random forest test. Conclusion: We have developed a method to accurately account for uncertainty in 16S rRNA GCN predictions and the downstream analyses. For almost all 16S rRNA surveyed bacterial communities, correction of 16S GCN should improve the results when estimating their compositional and functional profiles. However, such correction is not necessary for beta-diversity analyses.

scholarly journals Establishment and Assessment of An Amplicon Sequencing Method Targeting The 16S-ITS-23S rRNA Operon For Analysis of The Equine Gut Microbiome

2021 ◽  
Author(s):  
Yuta Kinoshita ◽  
Hidekazu NIWA ◽  
Eri UCHIDA-FUJII ◽  
Toshio NUKADA
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Amplicon Sequencing ◽  
Full Length ◽  
Rrna Operon ◽  
Rrna Genes ◽  
Taxonomic Resolution ◽  
23S Rrna ◽  
Rrna Gene ◽  
Fecal Samples

Abstract Microbial communities are commonly studied by using amplicon sequencing of part of the 16S rRNA gene. Sequencing of the full-length 16S rRNA gene can provide higher taxonomic resolution and accuracy. To obtain even higher taxonomic resolution, with as few false-positives as possible, we assessed a method using long amplicon sequencing targeting the rRNA operon combined with a CCMetagen pipeline. Taxonomic assignment had >90% accuracy at the species level in a mock sample and at the family level in equine fecal samples, generating similar taxonomic composition as shotgun sequencing. The rRNA operon amplicon sequencing of equine fecal samples underestimated compositional percentages of bacterial strains containing unlinked rRNA genes by a third to almost a half, but unlinked rRNA genes had a limited effect on the overall results. The rRNA operon amplicon sequencing with the A519F + U2428R primer set was able to reflect archaeal genomes, whereas full-length 16S rRNA with 27F + 1492R could not. Therefore, we conclude that amplicon sequencing targeting the rRNA operon captures more detailed variations of bacterial and archaeal microbiota.

scholarly journals Species-level resolution of 16S rRNA gene amplicons sequenced through the MinIONTM portable nanopore sequencer

2015 ◽  
Author(s):  
Alfonso Benítez-Páez ◽  
Kevin J. Portune ◽  
Yolanda Sanz
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Diversity ◽  
Amplicon Sequencing ◽  
Species Level ◽  
Taxonomic Resolution ◽  
Universal Primers ◽  
Rrna Gene ◽  
Rdna Sequences ◽  
Dna Sequencer

AbstractBackgroundThe miniaturised and portable DNA sequencer MinIONTM has been released to the scientific community within the framework of an early access programme to evaluate its application for a wide variety of genetic approaches. This technology has demonstrated great potential, especially in genome-wide analyses. In this study, we tested the ability of the MinIONTM system to perform amplicon sequencing in order to design new approaches to study microbial diversity using nearly full-length 16S rDNA sequences.ResultsUsing R7.3 chemistry, we generated more than 3.8 million events (nt) during a single sequencing run. These data were sufficient to reconstruct more than 90% of the 16S rRNA gene sequences for 20 different species present in a mock reference community. After read mapping and 16S rRNA gene assembly, consensus sequences and 2d reads were recovered to assign taxonomic classification down to the species level. Additionally, we were able to measure the relative abundance of all the species present in a mock community and detected a biased species distribution originating from the PCR reaction using ‘universal’ primers.ConclusionsAlthough nanopore-based sequencing produces reads with lower per-base accuracy compared with other platforms, the MinIONTM DNA sequencer is valuable for both high taxonomic resolution and microbial diversity analysis. Improvements in nanopore chemistry, such as minimising base-calling errors and the nucleotide bias reported here for 16S amplicon sequencing, will further deliver more reliable information that is useful for the specific detection of microbial species and strains in complex ecosystems.

scholarly journals TaxAss: Leveraging a Custom Freshwater Database Achieves Fine-Scale Taxonomic Resolution

mSphere ◽  
2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Robin R. Rohwer ◽  
Joshua J. Hamilton ◽  
Ryan J. Newton ◽  
Katherine D. McMahon
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Microbial Community Composition ◽  
Taxonomic Resolution ◽  
Rrna Gene ◽  
Data Sets ◽  
Data Set ◽  
Comprehensive Database ◽  
Fine Resolution

ABSTRACT Taxonomy assignment of freshwater microbial communities is limited by the minimally curated phylogenies used for large taxonomy databases. Here we introduce TaxAss, a taxonomy assignment workflow that classifies 16S rRNA gene amplicon data using two taxonomy reference databases: a large comprehensive database and a small ecosystem-specific database rigorously curated by scientists within a field. We applied TaxAss to five different freshwater data sets using the comprehensive SILVA database and the freshwater-specific FreshTrain database. TaxAss increased the percentage of the data set classified compared to using only SILVA, especially at fine-resolution family to species taxon levels, while across the freshwater test data sets classifications increased by as much as 11 to 40% of total reads. A similar increase in classifications was not observed in a control mouse gut data set, which was not expected to contain freshwater bacteria. TaxAss also maintained taxonomic richness compared to using only the FreshTrain across all taxon levels from phylum to species. Without TaxAss, most organisms not represented in the FreshTrain were unclassified, but at fine taxon levels, incorrect classifications became significant. We validated TaxAss using simulated amplicon data derived from full-length clone libraries and found that 96 to 99% of test sequences were correctly classified at fine resolution. TaxAss splits a data set’s sequences into two groups based on their percent identity to reference sequences in the ecosystem-specific database. Sequences with high similarity to sequences in the ecosystem-specific database are classified using that database, and the others are classified using the comprehensive database. TaxAss is free and open source and is available at https://www.github.com/McMahonLab/TaxAss. IMPORTANCE Microbial communities drive ecosystem processes, but microbial community composition analyses using 16S rRNA gene amplicon data sets are limited by the lack of fine-resolution taxonomy classifications. Coarse taxonomic groupings at the phylum, class, and order levels lump ecologically distinct organisms together. To avoid this, many researchers define operational taxonomic units (OTUs) based on clustered sequences, sequence variants, or unique sequences. These fine-resolution groupings are more ecologically relevant, but OTU definitions are data set dependent and cannot be compared between data sets. Microbial ecologists studying freshwater have curated a small, ecosystem-specific taxonomy database to provide consistent and up-to-date terminology. We created TaxAss, a workflow that leverages this database to assign taxonomy. We found that TaxAss improves fine-resolution taxonomic classifications (family, genus, and species). Fine taxonomic groupings are more ecologically relevant, so they provide an alternative to OTU-based analyses that is consistent and comparable between data sets.

scholarly journals From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification

2010 ◽  
Vol 11 (1) ◽  
Author(s):  
Bram Slabbinck ◽  
Willem Waegeman ◽  
Peter Dawyndt ◽  
Paul De Vos ◽  
Bernard De Baets
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Rrna Gene ◽  
Bacterial Classification ◽  
Gene Data ◽  
Phylogenetic Learning
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