Introducing CowPi: A rumen microbiome focussed version of the PICRUSt functional inference software


We've just release our version of PICRUSt for the rumen microbiome. This software uses the 16S sequences from the Global Rumen Census and the nearly 500 published genomes from cultured rumen organisms currently available (most from the Hungate 1000 project) to allow functional inferences from 16S meta-taxonomic studies and can be found at www.cowpi.org.

The paper has now been published in Frontiers in Microbiology here as part of a special research topic on "Metaomic Approaches to Study the Rumen Microbiome: Challenges and Innovation". We demonstrate how using the data directly from the Rumen allows a better prediction of the abundance of functional units (for example see figure 1 from the paper, reproduced here).

FIGURE 1. Prediction accuracy on the Hess et al. (2011) dataset. (A) Metagenome compared with PICRUSt and (B) Metagenome compared with CowPI. Points represent the relative abundance of KOs in the observed (y-axis) and predicted (x-axis) dataset

The data behind the tool can be downloaded at Zenodo under this DOI: DOI but we have also implemented a workflow on the publicly accessible GALAXY implementation from Aberystwyth University here. This is designed to make functional predictions from Rumen 16S metataxonomic data as simple as possible.

All users of this system will need to register and set up their account (walk through tutorial here). Once set up the impatient users can assess a rapid overview of using the system here and a more detailed explanation of each step of the workflow can be found here.

We would welcome feedback from the community and would encourage other groups to implement external-facing version for other groups to use so please get in touch if you have any questions/suggestions.




Detecting microbial niches in Metagenomic data


Microbes colonising the surface of grass.
The image was taken using a Hitachi S-4700 FESEM scanning electron microscope by Alan Cookson 
at the IBERS Advanced Microscopy and Bio-Imaging Laboratory, Edward Llwyd building, Penglais.
In collaboration with the Agriculture and Food Development Authority in Ireland (Teagasc) we recently published a new way of identifying how different types of microbes can survive when competing for resources in the same environment.

The paper by former PhD student in the group, Dr Francesco Rubino, identifies what is known as ‘niche specialisation’  and is published in the Nature Publishing Group (NPG) ‘Multidisciplinary Journal of Microbial Ecology’: The ISME Journal. dx.doi.org/10.1038/ismej.2016.172

Niche specialisation is the process by which, through natural selection, a species becomes better adapted to the specific characteristics of a particular habitat.
These organisms can be the principal drivers of important processes in the community and therefore are prime targets for researchers looking to engineer microbial communities to achieve desired outcomes.

It has long been thought that ecological principles developed for the study of large organisms should also be applicable to micro-organisms and while processes such as successional change and competition are known to occur in microbial communities, identifying signatures of niche specialisation remains a challenge.

Despite the large numbers of microbiome studies that have been generated from the microbial populations found in the gut, the soil, the sea and human skin, we still lack a clear understanding of the ecology of the micro-organisms that have an essential role to play in everything from human health to earth system processes.

We were looking to identify what resources different micro-organisms compete over when they are present in the same environment. Developing such an understanding is essential to meet many of the major challenges facing human society today, such as management of natural ecosystems and mitigation of climate change.

This study examined the signatures of niche specialisation between some of the most abundant organisms in the rumen microbiome of cattle, a major source of methane – the second most significant greenhouse gas in the UK.

We used a novel computational biology approach implemented in MGKit and based on evolutionary methods to identify the genes and functions that play an important role in maintaining niche specialisation.

The results identified the specific functions important for each organism within the microbial community to maintain its niche in the rumen of cattle and represent novel targets for engineering this microbiome for desirable outputs (such as reducing greenhouse gasses).
This represents the first use of evolutionary approaches in this context and will open avenues of further research to both identify niche specialisation in any microbiome and to identify the organisms important for specific functions in any microbial community.

This work was funded by the Biotechnology and Biological Sciences Research Council (BBSRC), EU Seventh Framework Programme and Science Foundation Ireland. 

Transcriptomics, Genetic maps & Microbiomes - The latest papers from the group

A quick catchup on the latest papers from the group:


Fertility transcriptomics:


Former PhD student Dr. Bruce Moran's article on the temporal transcriptomic changes in liver and Muscle in cattle genetically divergent for fertility appeared in BMC Genomics.

Bruce's work identified a genes related to immune and metabolic functions and lipid and carbohydrate binding differentially expressed. In particular his results suggest that an increased burden of reactive oxygen species, coupled with a chronic inflammatory state are impacting dairy cow fertility in the model studies. This information will be used to further  direct efforts to increase fertility in this important agricultural species. See the full paper here.



Genetic map of Rye Grass:


In collaboration with Dr. Janaki Velmurugan from the Oakpark Crop Research Centre in the Irish Agriculture and Food Development Authority, (Teagasc), we published a high density single nucleotide polymorphism (SNP) genetic linkage map for perennial ryegrass (Lolium perenne) in the journal Annals of Botany

Rye grasses are the most widely grown cool-season grasses in the world. They have a long growing season and high yielding under favourable conditions.  There is much interest in understanding the genomic factors that underpin the success of this species and to utilise genetic markers to select for favourable traits. This genetic linkage map is the first step toward achieving this goal and will allow plant breeders to select for the genetic components underlying desirable traits. See the full paper here.


Temporal dynamics of a microbiome:


In conjunction with Dr. Sharon Huws and Dr. Joan Edwards and researchers from the Herbivore Gut Ecosystems Group in IBERS we have recently published a study in FEMS Microbiology Ecology which investigates the early contribution of different microbes to the fermentation of perennial ryegrass in the rumen.

Using 16S rRNA markers over a time series spanning the first 8 hours following ingestion of biomass by the host, we demonstrated that ecological successional changes played an important role in the fermentation process during this timeframe, and involved some of the most abundant bacterial species from the rumen. See the full paper here.