Abstract
Our understanding of complex microbial communities, such as those residing in the rumen, has drastically advanced through the use of high throughput sequencing (HTS) technologies. Indeed, with the use of barcoded amplicon sequencing, it is now cost effective and computationally feasible to identify individual rumen microbial genera associated with ruminant livestock nutrition, genetics, performance and greenhouse gas production. However, across all disciplines of microbial ecology, there is currently little reporting of the use of internal controls for validating HTS results. Furthermore, there is little consensus of the most appropriate reference database for analyzing rumen microbiota amplicon sequencing data. Therefore, in this study, a synthetic rumen-specific sequencing standard was used to assess the effects of database choice on results obtained from rumen microbial amplicon sequencing. Four DADA2 reference training sets (RDP, SILVA, GTDB, and RefSeq + RDP) were compared to assess their ability to correctly classify sequences included in the rumen-specific sequencing standard. In addition, two thresholds of phylogenetic bootstrapping, 50 and 80, were applied to investigate the effect of increasing stringency. Sequence classification differences were apparent amongst the databases. For example the classification of Clostridium differed between all databases, thus highlighting the need for a consistent approach to nomenclature amongst different reference databases. It is hoped the effect of database on taxonomic classification observed in this study, will encourage research groups across various microbial disciplines to develop and routinely use their own microbiome-specific reference standard to validate analysis pipelines and database choice.
Highlights
The ability of ruminant animals to obtain nutrition from complex plant carbohydrates stems from their co-evolution with the microbial community residing in their rumen (Sasson et al, 2017)
The full length 16S ribosomal RNA (rRNA) gene sequences of 13 different species of bacteria and 3 different species of archaea, identified as representative of the rumen microbial composition from the Global Rumen Census (GRC) project or prior studies and isolated from the rumen with their genome sequenced where possible, were synthesized based on sequence information obtained from GenBank by Integrated DNA Technologies (Leuven, Belgium)
Four independent applications of the DADA2 pipeline, each time with either the SILVA, Ribosomal Database Project (RDP), RefSeq + RDP or Genome Taxonomy Database (GTDB) databases, resulted in the identification of the expected 16 amplicon sequence variant (ASV), which represented ∼99.5% of all the ASVs identified across the sequencing runs
Summary
The ability of ruminant animals to obtain nutrition from complex plant carbohydrates stems from their co-evolution with the microbial community residing in their rumen (Sasson et al, 2017). The rumen microbiome was investigated using culture based methods such as those pioneered by Hungate (1966). The widespread availability of high throughput sequencing (HTS) technology after the turn of the 21st century has advanced our understanding of numerous complex microbial communities, including that which inhabits the rumen (Knight et al, 2018). Popular phylogenetic marker genes used to investigate microbial communities include; 16S ribosomal RNA (rRNA) (bacteria and archaea), 18S rRNA (protozoa) and the internal transcribed spacer region (fungi)
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