Reconciliation between operational taxonomic units and species boundaries.
The development of high-throughput sequencing technologies has revolutionised the field of microbial ecology via 16S rRNA gene amplicon sequencing approaches. Clustering those amplicon sequencing reads into operational taxonomic units (OTUs) using a fixed cut-off is a commonly used approach to estimate microbial diversity. A 97% threshold was chosen with the intended purpose that resulting OTUs could be interpreted as a proxy for bacterial species. Our results show that the robustness of such a generalised cut-off is questionable when applied to short amplicons only covering one or two variable regions of the 16S rRNA gene. It will lead to biases in diversity metrics and makes it hard to compare results obtained with amplicons derived with different primer sets. The method introduced within this work takes into account the differential evolutional rates of taxonomic lineages in order to define a dynamic and taxonomic-dependent OTU clustering cut-off score. For a taxonomic family consisting of species showing high evolutionary conservation in the amplified variable regions, the cut-off will be more stringent than 97%. By taking into consideration the amplified variable regions and the taxonomic family when defining this cut-off, such a threshold will lead to more robust results and closer correspondence between OTUs and species. This approach has been implemented in a publicly available software package called DynamiC.
Unit of Microbiology, Belgian Nuclear Research Centre (SCK-CEN), 2400 Mol, Belgium.|Department of Bio-Engineering sciences, Vrije Universiteit Brussel (VUB), 1050 Brussels, Belgium.|VIB lab for Bioinformatics and (eco-)systems biology, VIB, 3000 Leuven, Belgium.|Department of Microbiology and Immunology, REGA institute, KU Leuven, 3000 Leuven, Belgium.
Mohamed
M
Mysara
Department of Biochemistry and microbiology, Ghent University, 9000 Ghent, Belgium.
Peter
P
Vandamme
Department of Biochemical and microbial technology, Ghent University, 9000 Ghent, Belgium.
Ruben
R
Props
Department of Biochemical and microbial technology, Ghent University, 9000 Ghent, Belgium.
Frederiek-Maarten
FM
Kerckhof
Unit of Microbiology, Belgian Nuclear Research Centre (SCK-CEN), 2400 Mol, Belgium.
Natalie
N
Leys
Department of Biochemical and microbial technology, Ghent University, 9000 Ghent, Belgium.
Nico
N
Boon
VIB lab for Bioinformatics and (eco-)systems biology, VIB, 3000 Leuven, Belgium.|Department of Microbiology and Immunology, REGA institute, KU Leuven, 3000 Leuven, Belgium.
Jeroen
J
Raes
Unit of Microbiology, Belgian Nuclear Research Centre (SCK-CEN), 2400 Mol, Belgium.
Pieter
P
Monsieurs
D005075:Biological Evolution; D002965:Classification; D016000:Cluster Analysis; D017931:DNA Primers; D014644:Genetic Variation; D059014:High-Throughput Nucleotide Sequencing; D012336:RNA, Ribosomal, 16S / Q000235:genetics
D017931:DNA Primers; D012336:RNA, Ribosomal, 16S
16S rRNA amplicon sequencing; 16S rRNA metagenomics; DynamiC; OTU clustering; microbial biodiversity; next generation sequencing; operational taxonomic units (OTUs)