Evidence map›Paper›PMID 34092959›Full record

ArticleBioinformation2021

Benchmarking of 16S rRNA gene databases using known strain sequences.

Kunal Dixit, Dimple Davray, Diptaraj Chaudhari, Pratik Kadam, Rudresh Kshirsagar, Yogesh Shouche, Dhiraj Dhotre, Sunil D Saroj

Abstract read
In one paragraph

Article in Bioinformation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Kunal DixitSymbiosis School of Biological Sciences (SSBS), Symbiosis International (Deemed University), Pune, India.
Dimple DavraySymbiosis School of Biological Sciences (SSBS), Symbiosis International (Deemed University), Pune, India.
Diptaraj ChaudhariNational Center for Microbial Resource (NCMR), National Center for Cell Science (NCCS), Pune, India.
Pratik KadamNational Center for Microbial Resource (NCMR), National Center for Cell Science (NCCS), Pune, India.
Rudresh KshirsagarNational Center for Microbial Resource (NCMR), National Center for Cell Science (NCCS), Pune, India.
Yogesh ShoucheNational Center for Microbial Resource (NCMR), National Center for Cell Science (NCCS), Pune, India.
Dhiraj DhotreReliance Life Sciences Pvt Ltd, Rabale, Mumbai, India.
Sunil D SarojSymbiosis School of Biological Sciences (SSBS), Symbiosis International (Deemed University), Pune, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

16S rRNA gene analysis is the most convenient and robust method for microbiome studies. Inaccurate taxonomic assignment of bacterial strains could have deleterious effects as all downstream analyses rely heavily on the accurate assessment of microbial taxonomy. The use of mock communities to check the reliability of the results has been suggested. However, often the mock communities used in most of the studies represent only a small fraction of taxa and are used mostly as validation of sequencing run to estimate sequencing artifacts. Moreover, a large number of databases and tools available for classification and taxonomic assignment of the 16S rRNA gene make it challenging to select the best-suited method for a particular dataset. In the present study, we used authentic and validly published 16S rRNA gene type strain sequences (full length, V3-V4 region) and analyzed them using a widely used QIIME pipeline along with different parameters of OTU clustering and QIIME compatible databases. Data Analysis Measures (DAM) revealed a high discrepancy in ratifying the taxonomy at different taxonomic hierarchies. Beta diversity analysis showed clear segregation of different DAMs. Limited differences were observed in reference data set analysis using partial (V3-V4) and full-length 16S rRNA gene sequences, which signify the reliability of partial 16S rRNA gene sequences in microbiome studies. Our analysis also highlights common discrepancies observed at various taxonomic levels using various methods and databases.

Indexed as

16S rRNA geneGenomic DatabasesQIIMETaxonomic Discrepancy

Identifiers

PMID34092959
PMCPMC8131573

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.