While metataxonomic 16S rDNA based studies are a commonplace tool in the research of the rumen microbiome, they do not provide the full investigative power of metagenomics and metatranscriptomics based analyses.
To address this PICRUSt1 was developed by the Huttenhower Lab to allow inference of the functional potential of an observed microbiome profile, based on the sequenced genomes of taxa closely related to those in the community being studied.
Based on a wide selection of microbial genomes from the Human commensulates (with some others) this has proved to be a very useful tool for human microbiome studies. However when applied to non-Human microbiome studies predictions of functional potential can be less accurate.
The rumen microbiome is a case in point, organisms from the rumen environment are traditionally underrepresented in genome and rRNA sequence databases. However, recent efforts by projects such as the Global Rumen Census2 (which generated global 16S rRNA-based census of rumen microbial constituents) and Hungate 10003 (Which has resulted in the culturing and sequencing of over 400 rumen microbial genomes) have presented an opportunity to develop a version of PICRUSt which is solely based on data from the rumen microbiome (CowPI4).
Using a phylogenetic tree based on the rRNA data from the Global rumen Census2 and linked to functional profiles based on the Hungate 1000 genomes3 CowPi4 uses the open source PICRUSt tool to allow Rumen-specific predictions of the functional potential of a community based on 16S rRNA data.
References:
1 Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Langille, M. G.I.*; Zaneveld, J.*; Caporaso, J. G.; McDonald, D.; Knights, D.; a Reyes, J.; Clemente, J. C.; Burkepile, D. E.; Vega Thurber, R. L.; Knight, R.; Beiko, R. G.; and Huttenhower, C. Nature Biotechnology, 1-10. 8 2013. Link
2 Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range. Henderson, G., Cox, F., Ganesh, S., Jonker, A., Young, W., Abecia, L., Angarita, E., Aravena, P., Arenas, G.N., Ariza, C. and Attwood, G.T., 2015. Scientific reports, 5, p.14567. Link
3 Cultivation and sequencing of rumen microbiome members from the Hungate1000 Collection. Seshadri, R., Leahy, S.C., Attwood, G.T., Teh, K.H., Lambie, S.C., Cookson, A.L., Eloe-Fadrosh, E.A., Pavlopoulos, G.A., Hadjithomas, M., Varghese, N.J. and Paez-Espino, D., 2018. Nature Biotechnology. Link
4 CowPI: A rumen microbiome focussed version of the PICRUSt functional inference software. Wilkinson, T.J., Huws, S.A., Edwards, J.E., Kingston-Smith, A., Siu Ting, K., Hughes, M., Rubino, F., Friedersdorff, M. and Creevey, C., 2018. Frontiers in Microbiology, 9, p.1095. Link
4 CowPI: A rumen microbiome focussed version of the PICRUSt functional inference software. Wilkinson, T.J., Huws, S.A., Edwards, J.E., Kingston-Smith, A., Siu Ting, K., Hughes, M., Rubino, F., Friedersdorff, M. and Creevey, C., 2018. Frontiers in Microbiology, 9, p.1095. Link