Evidence map›Paper›PMID 31286860›Full record

ArticleBMC genomics2019

DAIRYdb: a manually curated reference database for improved taxonomy annotation of 16S rRNA gene sequences from dairy products.

Marco Meola, Etienne Rifa, Noam Shani, Céline Delbès, Hélène Berthoud, Christophe Chassard

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
3.1field-weighted citation impact, top 7% of its field
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

24 citing papers in PubMed, 65 citations in OpenAlex.

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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

6 authors at 2 institutions in 2 countries.

Marco MeolaAgroscope, Competence Division Methods Development and Analytics, Research Group Fermenting Organisms, Schwarzenburgstrasse 161, Bern, 3003, Switzerland. marco.meola@agroscope.admin.ch.ORCID http://orcid.org/0000-0002-8951-1514
Etienne RifaUniversité Clermont Auvergne, INRA, VetAgro Sup, UMRF, 20 côte de Reyne, Aurillac, 15000, France.
Noam ShaniAgroscope, Competence Division Methods Development and Analytics, Research Group Fermenting Organisms, Schwarzenburgstrasse 161, Bern, 3003, Switzerland.
Céline DelbèsUniversité Clermont Auvergne, INRA, VetAgro Sup, UMRF, 20 côte de Reyne, Aurillac, 15000, France.
Hélène BerthoudAgroscope, Competence Division Methods Development and Analytics, Research Group Fermenting Organisms, Schwarzenburgstrasse 161, Bern, 3003, Switzerland.
Christophe ChassardUniversité Clermont Auvergne, INRA, VetAgro Sup, UMRF, 20 côte de Reyne, Aurillac, 15000, France.
Agroscope · CHUniversité Clermont Auvergne · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReads assignment to taxonomic units is a key step in microbiome analysis pipelines. To date, accurate taxonomy annotation of 16S reads, particularly at species rank, is still challenging due to the short size of read sequences and differently curated classification databases. The close phylogenetic relationship between species encountered in dairy products, however, makes it crucial to annotate species accurately to achieve sufficient phylogenetic resolution for further downstream ecological studies or for food diagnostics. Curated databases dedicated to the environment of interest are expected to improve the accuracy and resolution of taxonomy annotation.

resultsWe provide a manually curated database composed of 10'290 full-length 16S rRNA gene sequences from prokaryotes tailored for dairy products analysis ( https://github.com/marcomeola/DAIRYdb ). The performance of the DAIRYdb was compared with the universal databases Silva, LTP, RDP and Greengenes. The DAIRYdb significantly outperformed all other databases independently of the classification algorithm by enabling higher accurate taxonomy annotation down to the species rank. The DAIRYdb accurately annotates over 90% of the sequences of either single or paired hypervariable regions automatically. The manually curated DAIRYdb strongly improves taxonomic annotation accuracy for microbiome studies in dairy environments. The DAIRYdb is a practical solution that enables automatization of this key step, thus facilitating the routine application of NGS microbiome analyses for microbial ecology studies and diagnostics in dairy products.

Indexed as

Databases, GeneticClassificationDairy ProductsMicrobiotaPhylogenyRNA, Ribosomal, 16SRNA, Ribosomal, 16S16SAccuracyCheeseDairyDatabaseMicrobiomeMilkOTU classificationStarterTaxonomy annotationTeatWhey

Identifiers

PMID31286860
PMCPMC6615214
OpenAlexW2962243765

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.