scholarly journals Evaluation of the RDP Classifier Accuracy Using 16S rRNA Gene Variable Regions

Metagenomics ◽  
2012 ◽  
Vol 1 ◽  
pp. 1-5 ◽  
Author(s):  
Claudia Vilo ◽  
Qunfeng Dong
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Rrna Gene ◽  
Variable Regions

scholarly journals Intrinsic challenges in ancient microbiome reconstruction using 16S rRNA gene amplification

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Kirsten A. Ziesemer ◽  
Allison E. Mann ◽  
Krithivasan Sankaranarayanan ◽  
Hannes Schroeder ◽  
Andrew T. Ozga ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Dna Amplification ◽  
Amplicon Sequencing ◽  
Universal Primers ◽  
Rrna Gene ◽  
Dental Calculus ◽  
Shotgun Metagenomics ◽  
Variable Regions ◽  
V3 Region

Abstract To date, characterization of ancient oral (dental calculus) and gut (coprolite) microbiota has been primarily accomplished through a metataxonomic approach involving targeted amplification of one or more variable regions in the 16S rRNA gene. Specifically, the V3 region (E. coli 341–534) of this gene has been suggested as an excellent candidate for ancient DNA amplification and microbial community reconstruction. However, in practice this metataxonomic approach often produces highly skewed taxonomic frequency data. In this study, we use non-targeted (shotgun metagenomics) sequencing methods to better understand skewed microbial profiles observed in four ancient dental calculus specimens previously analyzed by amplicon sequencing. Through comparisons of microbial taxonomic counts from paired amplicon (V3 U341F/534R) and shotgun sequencing datasets, we demonstrate that extensive length polymorphisms in the V3 region are a consistent and major cause of differential amplification leading to taxonomic bias in ancient microbiome reconstructions based on amplicon sequencing. We conclude that systematic amplification bias confounds attempts to accurately reconstruct microbiome taxonomic profiles from 16S rRNA V3 amplicon data generated using universal primers. Because in silico analysis indicates that alternative 16S rRNA hypervariable regions will present similar challenges, we advocate for the use of a shotgun metagenomics approach in ancient microbiome reconstructions.

Genetic profiling of noncultivated bacteria from the rhizospheres of sugar beet (Beta vulgaris) reveal field and annual variability but no effect of a transgenic herbicide resistance

2003 ◽  
Vol 49 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Achim Schmalenberger ◽  
Christoph C Tebbe
Keyword(s):  
16S Rrna ◽  
Sugar Beet ◽  
16S Rrna Gene ◽  
Beta Vulgaris ◽  
Herbicide Resistance ◽  
Microbial Community Analysis ◽  
Rrna Genes ◽  
Rrna Gene ◽  
Variable Regions ◽  
Genetic Profiling

In this field study, we compared the bacterial communities inhabiting the rhizosphere of a transgenic, herbicide-resistant sugar beet (Beta vulgaris) cultivar with those of its nonengineered counterpart, using a genetic profiling technique based on PCR amplifications of partial 16S rRNA gene sequences and single-strand conformation polymorphism (SSCP). As a control for the plasticity of the bacterial community, we also analyzed the influence of herbicides, the field heterogeneity, and the annual variation. DNA was isolated from bacterial cell consortia that were directly collected from root material. PCR was carried out with primers that hybridized to evolutionarily conserved regions flanking variable regions 4 and 5 of the 16S rRNA gene. SSCP patterns of these PCR products were composed of approximately 50 distinguishable bands, as detected by silver staining of the gels after electrophoresis. Patterns of the replicates and the different treatments were highly similar, but digital image and similarity analyses revealed differences that corresponded to the positions of the replicates in the field. In addition, communities collected from sugar beet in two successive growing seasons could be distinguished. In contrast, no effect of the transgenic herbicide resistance was detectable. Sequencing of 24 dominant products of the SSCP profiles indicated the presence of bacteria from different phylogenetic groups, with Proteobacteria and members of the Cytophaga–Flavobacterium–Bacteroides group being most abundant.Key words: genetic profiles, rRNA genes, transgenic sugar beet, risk assessment, rhizosphere, PCR–SSCP, microbial community analysis, glufosinate, phosphinothricin.

scholarly journals Combining 16S rRNA gene variable regions enables high-resolution microbial community profiling

2017 ◽  
Author(s):  
Garold Fuks ◽  
Michael Elgart ◽  
Amnon Amir ◽  
Amit Zeisel ◽  
Peter J. Turnbaugh ◽  
...  
Keyword(s):  
High Resolution ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Read Length ◽  
Rrna Gene ◽  
Sample Number ◽  
Variable Regions ◽  
Total Length ◽  
Fragmented Dna ◽  
The 16S Rrna Gene

AbstractBackgroundMost of our knowledge about the remarkable microbial diversity on Earth comes from sequencing the 16S rRNA gene. The use of next-generation sequencing methods has increased sample number and sequencing depth, but the read length of the most widely used sequencing platforms today is quite short, requiring the researcher to choose a subset of the gene to sequence (typically 16-33% of the total length). Thus, many bacteria may share the same amplified region and the resolution of profiling is inherently limited. Platforms that offer ultra long read lengths, whole genome shotgun sequencing approaches, and computational frameworks formerly suggested by us and by others, all allow different ways to circumvent this problem yet suffer various shortcomings. There is need for a simple and low cost 16S rRNA gene based profiling approach that harnesses the short read length to provide a much larger coverage of the gene to allow for high resolution, even in harsh conditions of low bacterial biomass and fragmented DNA.ResultsThis manuscript suggests Short MUltiple Regions Framework (SMURF), a method to combine sequencing results from different PCR-amplified regions to provide one coherent profiling. The de facto amplicon length is the total length of all amplified regions, thus providing much higher resolution compared to current techniques. Computationally, the method solves a convex optimization problem that allows extremely fast reconstruction and requires only moderate memory. We demonstrate the increase in resolution by in silico simulations and by profiling two mock mixtures and real-world biological samples. Reanalyzing a mock mixture from the Human Microbiome Project achieved about two-fold improvement in resolution when combing two independent regions. Using a custom set of six primer pairs spanning about 1200bp (80%) of the 16S rRNA gene we were able to achieve ~100 fold improvement in resolution compared to a single region, over a mock mixture of common human gut bacterial isolates. Finally, profiling of a Drosophila melanogaster microbiome using the set of six primer pairs provided a ~100 fold increase in resolution, and thus enabling efficient downstream analysis.ConclusionsSMURF enables identification of near full-length 16S rRNA gene sequences in microbial communities, having resolution superior compared to current techniques. It may be applied to standard sample preparation protocols with very little modifications. SMURF also paves the way to high-resolution profiling of low-biomass and fragmented DNA, e.g., in the case of Formalin-fixed and Paraffin-embedded samples, fossil-derived DNA or DNA exposed to other degrading conditions. The approach is not restricted to combining amplicons of the 16S rRNA gene and may be applied to any set of amplicons, e.g., in Multilocus Sequence Typing (MLST).

scholarly journals Resolving microbial microdiversity with high accuracy full length 16S rRNA Illumina sequencing

2014 ◽  
Author(s):  
Catherine Burke ◽  
Aaron E Darling
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Single Molecule ◽  
Illumina Miseq ◽  
Full Length ◽  
Rrna Gene ◽  
Variable Regions ◽  
Phylogenetic Resolution ◽  
Miseq Platform ◽  
The 16S Rrna Gene

We describe a method for sequencing full-length 16S rRNA gene amplicons using the high throughput Illumina MiSeq platform. The resulting sequences have about 100-fold higher accuracy than standard Illumina reads and are chimera filtered using information from a single molecule dual tagging scheme that boosts the signal available for chimera detection. We demonstrate that the data provides fine scale phylogenetic resolution not available from Illumina amplicon methods targeting smaller variable regions of the 16S rRNA gene.

scholarly journals Combining 16S rRNA gene variable regions enables high-resolution microbial community profiling

Microbiome ◽  
2018 ◽  
Vol 6 (1) ◽  
Author(s):  
Garold Fuks ◽  
Michael Elgart ◽  
Amnon Amir ◽  
Amit Zeisel ◽  
Peter J. Turnbaugh ◽  
...  
Keyword(s):  
Microbial Community ◽  
High Resolution ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Rrna Gene ◽  
Variable Regions ◽  
Microbial Community Profiling ◽  
Community Profiling

Metasequencing of V3-V4 Variable Regions of 16S rRNA Gene in Opportunistic Microbiota and Gut Biocenosis in Obese Adolescents

2021 ◽  
Vol 170 (3) ◽  
pp. 321-325
Author(s):  
E. V. Grigorova ◽  
N. L. Belkova ◽  
U. M. Nemchenko ◽  
E. S. Klimenko ◽  
A. V. Pogodina ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Rrna Gene ◽  
Variable Regions ◽  
Obese Adolescents

scholarly journals Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy

2007 ◽  
Vol 73 (16) ◽  
pp. 5261-5267 ◽  
Author(s):  
Qiong Wang ◽  
George M. Garrity ◽  
James M. Tiedje ◽  
James R. Cole
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Higher Order ◽  
Error Rates ◽  
Bayesian Classifier ◽  
Rrna Gene ◽  
Ribosomal Database Project ◽  
Bacterial Taxonomy ◽  
Variable Regions ◽  
Rrna Sequences

ABSTRACT The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (≥95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/ .

scholarly journals Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Jethro S. Johnson ◽  
Daniel J. Spakowicz ◽  
Bo-Young Hong ◽  
Lauren M. Petersen ◽  
Patrick Demkowicz ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
High Throughput Sequencing ◽  
Full Length ◽  
Strain Level ◽  
Taxonomic Resolution ◽  
Rrna Gene ◽  
Variable Regions ◽  
16S Gene ◽  
Sequencing Platforms

Abstract The 16S rRNA gene has been a mainstay of sequence-based bacterial analysis for decades. However, high-throughput sequencing of the full gene has only recently become a realistic prospect. Here, we use in silico and sequence-based experiments to critically re-evaluate the potential of the 16S gene to provide taxonomic resolution at species and strain level. We demonstrate that targeting of 16S variable regions with short-read sequencing platforms cannot achieve the taxonomic resolution afforded by sequencing the entire (~1500 bp) gene. We further demonstrate that full-length sequencing platforms are sufficiently accurate to resolve subtle nucleotide substitutions (but not insertions/deletions) that exist between intragenomic copies of the 16S gene. In consequence, we argue that modern analysis approaches must necessarily account for intragenomic variation between 16S gene copies. In particular, we demonstrate that appropriate treatment of full-length 16S intragenomic copy variants has the potential to provide taxonomic resolution of bacterial communities at species and strain level.

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