The effect of 16S rRNA region choice on bacterial community metabarcoding results

Bukin, Yu. S.; Galachyants, Yuri P.; Морозов, И. В.; Bukin, S. V.; Zakharenko, А. S.; Zemskaya, Т. I.

doi:10.1038/sdata.2019.7

Cited by 286 publications

(229 citation statements)

References 57 publications

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“…As an example, the included studies mostly spanned regions V1–V2 and V3–V4 (Figure ). Regions V1–V2, however, were suggested to yield less reproducible results and to potentially underestimate certain taxa such as Bifidobacterium . Finally, raw sequencing data require several bioinformatic steps to render them interpretable.…”

Section: Discussionmentioning

confidence: 99%

A Systematic Review of the Root Canal Microbiota Associated with Apical Periodontitis: Lessons from Next‐Generation Sequencing

Manoil

Al‐Manei

Belibasakis

2020

Proteomics Clinical Apps

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Next-generation sequencing (NGS) has now been applied for a decade to characterize the microbiota composition of infected dental root canals associated with apical periodontitis. Here, the study aims at systematically and critically reviewing these reports within the outcome of interest selected; the microbiota composition in different endodontic infection types. Standard methodological guidelines as stated by the PRISMA and the Joanna Briggs Institute are followed, including a risk of bias assessment. A literature search is conducted using the PubMed Advanced-Search Builder on April 8, 2019; only original research articles that investigated the microbiota of infected root-canals by means of NGS are screened. Among the 26 articles initially identified, 18 are included and evaluated for the following parameters; sampling protocol, sequencing strategy, and microbiota composition. The endodontic infections include primary apical periodontitis (PAP), secondary apical periodontitis (SAP), and apical abscess (AA). All infection types are associated with a highly diverse microbiota. Although some taxa appear differentially abundant between PAPs, SAPs, and AAs, no evident clustering of the microbiota by infection type is observed. These studies collectively formulate a comprehensive map of the taxa associated with endodontic infections and provide evidence of compositionally unspecific, yet abundance differentiates, community profiles according to clinical diagnosis.The ORCID identification number(s) for the author(s) of this article can be found under https://doi.

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Section: Discussionmentioning

confidence: 99%

A Systematic Review of the Root Canal Microbiota Associated with Apical Periodontitis: Lessons from Next‐Generation Sequencing

Manoil

Al‐Manei

Belibasakis

2020

Proteomics Clinical Apps

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“…The choice of the 16S rRNA gene region(s) for short-read sequencing places an upper bound on the amount of species-level resolution that is achievable within a dataset [38-41]. Therefore, it is key to determine which regions provide the most information for distinguishing bacterial species that are common to that specific ecosystem.…”

Section: Resultsmentioning

confidence: 99%

Construction of habitat-specific training sets to achieve species-level assignment in 16S rRNA gene datasets

Escapa

Huang

Chen

et al. 2019

Preprint

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18 Background: The low cost of 16S rRNA gene sequencing facilitates population-scale 19 molecular epidemiological studies. Existing computational algorithms can parse 16S 20rRNA gene sequences to high-resolution Amplicon Sequence Variants (ASVs), which 21 represent ecologically coherent entities. Assigning species-level taxonomy to these ASVs 22is the critical remaining barrier to drawing ecologically/clinically relevant inferences from 23 and comparing data across 16S rRNA gene-based microbiota studies. 24Results: To overcome this barrier, we developed a broadly applicable method for 25 constructing a phylogeny-based, high-resolution, habitat-specific training set. When used 26 with the naïve Bayesian Ribosomal Database Project (RDP) Classifier, this training set 27 achieved species/supraspecies-level taxonomic assignment to 16S rRNA gene-derived 28ASVs. The key steps for generating such a training set are 1) constructing an accurate 29 and comprehensive phylogenetic-based, habitat-specific database; 2) compiling multiple 30 16S rRNA gene sequences to represent the natural sequence variability of each taxon in 31 the database; 3) trimming the training set to match the sequenced regions if necessary; 32 and 4) placing species sharing closely related sequences into a supraspecies taxonomic 33 level to maintain subgenus resolution. As proof of principle, we developed a V1-V3 region 34 training set for the bacterial microbiota of the human aerodigestive tract using our 35 expanded Human Oral Microbiome Database (eHOMD). In addition, we overcame 36 technical limitations to successfully use Illumina sequences for the 16S rRNA gene V1-37 V3 region, the most informative segment for classifying bacteria native to the human 38 aerodigestive tract. We also generated a full-length eHOMD 16S rRNA gene training set, 39 which we used in conjunction with an independent PacBio Single Molecule, Real-Time 40 (SMRT)-sequenced sinonasal dataset to validate the representation of species in our 41 training set. The latter also established the effectiveness of a full-length training set for 42 assigning taxonomy of long-read 16S rRNA gene datasets. 43Conclusion: Here, we present a systematic approach for constructing a phylogeny-44 based, high-resolution, habitat-specific training set that permits species/supraspecies-45 level taxonomic assignment to short-and long-read 16S rRNA gene-derived ASVs. This 46 advancement enhances the ecological and/or clinical relevance of 16S rRNA gene-based 47 microbiota studies. 48In microbiota studies of most ecosystems and/or habitats, achieving ecologically and/or 53 clinically relevant results requires species-level identification of constituents. For 54 example, species-level identification is often critically important for host-associated 55 microbial communities because these often include commensal and pathogenic species 56 of the same genus, e.g., [1, 2]. Also, some microbial genera include species that are site 57 specialists and inhabit distinct niches of a given environment [3]. Although hig...

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“…Also, as with other 16S rRNA gene sequencing studies, the taxonomic assignment and resolution is influenced by the particular primer set selected for amplifying the variable regions of the 16S rRNA gene, which may limit comparability with studies based on other primer sets. 85 Second, although 110 women is a relatively large cohort compared to many earlier studies, it is not large enough to detect small effect sizes. Nor was this sample size adequate for us to evaluate whether other health exposures and behaviors that associate with measures of socioeconomic status affect the stability of the microbiota in pregnancy.…”

Section: Strengths and Limitationsmentioning

confidence: 92%

Peer Review #2 of "Stability of the vaginal, oral, and gut microbiota across pregnancy among African American women: the effect of socioeconomic status and antibiotic exposure (v0.1)"

2019

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Objective. A growing body of research has investigated the human microbiota and pregnancy outcomes, especially preterm birth. Most studies of the prenatal microbiota have focused on the vagina, with fewer investigating other body sites during pregnancy. Although pregnancy involves profound hormonal, immunological and metabolic changes, few studies have investigated either shifts in microbiota composition across pregnancy at different body sites or variation in composition at any site thatmay be explained by maternal characteristics. The purpose of this study was to investigate: (1) thestability of the vaginal, oral, and gut microbiota from early (8-14 weeks) through later (24-30 weeks) pregnancy among African American women according to measures of socioeconomic status, accounting for prenatal antibiotic use; (2) whether measures of socioeconomic status are associated with changes in microbiota composition over pregnancy; and (3) whether exposure to prenatal antibiotics mediate any observed associations between measures of socioeconomic status and stability of the vaginal, oral, and gut microbiota across pregnancy. Methods. We used paired vaginal, oral, or gut samples available for 16S rRNA gene sequencing from two time points in pregnancy (8-14 and 24-30 weeks) to compare within-woman changes in measures ofalpha diversity (Shannon and Chao1) and beta-diversity (Bray-Curtis dissimilarity) among pregnant African American women (n = 110). Multivariable linear regression was used to examine the effect of level of education and prenatal health insurance as explanatory variables for changes in diversity,

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The effect of 16S rRNA region choice on bacterial community metabarcoding results

Cited by 286 publications

References 57 publications

A Systematic Review of the Root Canal Microbiota Associated with Apical Periodontitis: Lessons from Next‐Generation Sequencing

A Systematic Review of the Root Canal Microbiota Associated with Apical Periodontitis: Lessons from Next‐Generation Sequencing

Construction of habitat-specific training sets to achieve species-level assignment in 16S rRNA gene datasets

Peer Review #2 of "Stability of the vaginal, oral, and gut microbiota across pregnancy among African American women: the effect of socioeconomic status and antibiotic exposure (v0.1)"

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