# 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 Delbes, Hélène Berthoud, Christophe Chassard

## ► To cite this version:

Marco Meola, Etienne Rifa, Noam Shani, Céline Delbes, Hélène Berthoud, et al.. DAIRYdb: a manually curated reference database for improved taxonomy annotation of 16S rRNA gene sequences from dairy products. 5. Colloque de Génomique Environnementale, Oct 2019, La Rochelle, France. hal-02340447

HAL Id: hal-02340447

https://hal.science/hal-02340447

Submitted on 5 Jun 2020

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

Marco Meola<sup>a*</sup>, Etienne Rifa<sup>b*</sup>, Noam Shani<sup>a</sup>, Céline Delbès<sup>b</sup>, Hélène Berthouda<sup>a</sup>, Christophe Chassard<sup>b</sup>

<sup>a</sup> Agroscope, Research Group Fermenting Organisms, Schwarzenburgstrasse 161; CH-3003 Bern; Suisse

<sup>b</sup> Université Clermont Auvergne, INRA, VetAgro Sup, UMRF, 20 côte de Reyne, Aurillac, 15000, France

* M. Meola and E. Rifa contributed equally to this work.

## Context

Taxonomic assignment of amplicon sequence variants (ASV) is a key step in the metabarcoding data analysis for microbial community studies of cheese and dairy products. The taxonomic assignment depends mainly on the quality of the reference database. Current databases such as SILVA, RDP or Greengenes (GG) are complete and produce reliable assignments but do not allow to obtain an accurate taxonomic assignment of ASVs at species rank [1]. These databases also contain partial sequences of 16S rRNA with incomplete or erroneous taxonomy which impacts the assignment accuracy. Only a few percentage of their representative sequences present assignation at species rank.

DAIRYdb is a database built from complete and good quality 16S rRNA sequences from bacteria commonly found in cheese and dairy products. Thanks to the different bioinformatic treatments, we obtained a reduced database containing about 10,000 sequences. This allowed us to manually correct their taxonomy and then increase the assignment accuracy of ASVs from dairy products.

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Published by
2019, july

BMC
Genomics

DOI: 10.1186/s12864-019-5914-8

## 1. Construction

Sequences from NCBI[2]
EMBL[3] and real samples

Aligning and extracting
sequences from existing 16S
databases (vsearch [4])

First database with errors,
redundances etc...

vsearch, uchime [5], SINA [6], ARB [7]

Reduced database
containing high
quality sequences

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Dereplication
Short sequences filtering
Chimera filtering
Clustering 97 %
Type strains extraction

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390k seq.

10k seq.

## 2. Curation

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## 3. Validation

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Taxonomic assignment on
multiple reference databases
[12, 13, 14] and tools

Sintax, Blast, Metaxa ...

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## 4. Curation

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* DAIRYdb is composed of over 10000 sequences
* High diversity
* 38 % Firmicutes, 22 % Proteobacteria, 14 % Bacteroidetes, 9 % Actinobacteria

Kingdom 2
Phylum 46
Class 133
Order 244
Family 462
Genus 1754
Species 4027

* Assignment on each HVR

* DAIRYdb significantly improves taxonomic assignment at each rank.

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Sintax assignment accuracy boxplot on every HVR
(V1 to V9) tested on 5 different databases.

## Conclusions

* DAIRYdb shows better taxonomic assignment accuracy up to species rank than standard databases.

* An environment specific reference database with authoritative full-length 16S sequences covering the diversity of dairy products.

* The reduced number of representative sequences, decreases risk of conflict (high identity and different taxonomy).

## References

[1] Ritari, J. et al. (2015). Improved taxonomic assignment of human intestinal 16S rRNA sequences by a dedicated reference database. BMC Genomics 16, 1056.;

[2] Nucleotide [Internet]. Bethesda (MD): National Library of Medicine (US), National Bioinformatic Institute (UK), 2017; https://www.ebi.ac.uk/ena ; [3] Torbjørn Rognes et al. (2016). VSEARCH: a versatile open source tool for metagenomics.; [4] Edgar, R.C. et al. (2011). UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194-2200. ;

[6] Pruesse, E. et al. (2012). SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 28, 1823-1829. ;

[7] Ludwig, W. et al. (2004). ARB: a software environment for sequence data. Nucleic Acids Res. 32, 1363-1371. ; [8] Bengtsson, J. et al. (2011).

Metaxa: a software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets. Antonie Van Leeuwenhoek 100, 471-475. ;

[9] Edgar, R. (2016). SINTAX: a simple non-Bayesian taxonomy classifier for 16S and ITS sequences. bioRxiv 74161. ; [10] Kozlov, A.M. et al. (2016).

Phylogeny-aware identification and correction of taxonomically mislabeled sequences. Nucleic Acids Res 44, 5022-5033.; [11] Hartmann, M. et al. (2010). V-Xtractor: an open-source, high-throughput software tool to identify and extract hypervariable regions of small subunit (16S/18S) ribosomal RNA sequences and web-based tools. Nucleic Acids Res 41, D590-D596. ; [12] Quast, C. et al. (2013). The SILVA ribosomal RNA sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets. Antonie Van Leeuwenhoek 100, 471-475. ;

[13] Cole, J.R. et al. (2009). The Ribosomal Database Project: improved

alignments and new tools for rRNA analysis. Nucleic Acids Res 37, D141-D145. ; [14] DeSantis, T.Z. et al. (2006). Greengenes, a Chimera-Checked

16S rRNA Gene Database and Workbench Compatible with ARB. Appl Environ Microbiol 72, 5069-5072. ; [15] Ondov, B.D. et al. (2011). Interactive

metagenomic visualization in a Web browser. BMC Bioinformatics 12, 385.

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