Abstract
Metataxonomic 16S rDNA based studies are a commonplace and useful tool in the research of the microbiome, but they do not provide the full investigative power of metagenomics and metatranscriptomics for revealing the functional potential of microbial communities. However, the use of metagenomic and metatranscriptomic technologies is hindered by high costs and skills barrier necessary to generate and interpret the data. To address this, a tool for Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was developed for inferring the functional potential of an observed microbiome profile, based on 16S data. This allows functional inferences to be made from metataxonomic 16S rDNA studies with little extra work or cost, but its accuracy relies on the availability of completely sequenced genomes of representative organisms from the community being investigated. The rumen microbiome is an example of a community traditionally underrepresented in genome and sequence databases, but recent efforts by projects such as the Global Rumen Census and Hungate 1000 have resulted in a wide sampling of 16S rDNA profiles and almost 500 fully sequenced microbial genomes from this environment. Using this information, we have developed “CowPI,” a focused version of the PICRUSt tool provided for use by the wider scientific community in the study of the rumen microbiome. We evaluated the accuracy of CowPI and PICRUSt using two 16S datasets from the rumen microbiome: one generated from rDNA and the other from rRNA where corresponding metagenomic and metatranscriptomic data was also available. We show that the functional profiles predicted by CowPI better match estimates for both the meta-genomic and transcriptomic datasets than PICRUSt, and capture the higher degree of genetic variation and larger pangenomes of rumen organisms. Nonetheless, whilst being closer in terms of predictive power for the rumen microbiome, there were differences when compared to both the metagenomic and metatranscriptome data and so we recommend, where possible, functional inferences from 16S data should not replace metagenomic and metatranscriptomic approaches. The tool can be accessed at http://www.cowpi.org and is provided to the wider scientific community for use in the study of the rumen microbiome.
Highlights
Ruminant livestock represent an important part of human nutrition as a major source of our meat and milk (Webb et al, 2011)
Comparison of PICRUSt and CowPI predicted metagenomes with the sequenced annotated observed metagenome resulted in 5901 KEGG ortholog (KO) that were predicted to be present in all three datasets (CowPI, PICRUSt and the metagenome)
Our results show that the functional predictions of metabolic activity in the rumen microbiome is improved when using CowPI compared to PICRUSt
Summary
Ruminant livestock represent an important part of human nutrition as a major source of our meat and milk (Webb et al, 2011). The majority of studies focus on metataxonomics using amplicon libraries of marker genes, such as the 16S rDNA gene, and assessing change in the community structure in relation to animal productivity in different ruminant species and breeds (Myer et al, 2015; De Mulder et al, 2017), and in response to dietary intervention (Yáñez-Ruiz et al, 2015; Belanche et al, 2016). Despite advancement of sequencing technology and analysis methodology to study the full metagenomic and metatranscriptomic profiles of ruminal microbiomes (Li et al, 2012; Kamke et al, 2016), this type of study remains computationally complex and a financially demanding undertaking, whereas metataxonomic studies are comparatively cheaper (Jovel et al, 2016)
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