DOI: 10.5061/dryad.j9kd51c7k
title: Microbial associations and spatial proximity predict North American moose (Alces alces) gastrointestinal community composition

description: Microbial communities are increasingly recognised as crucial for animal
 health. However, our understanding of how microbial communities are
 structured across wildlife populations is poor. Mechanisms such as
 interspecific associations are important in structuring free-living
 communities, but we still lack an understanding of how important
 interspecific associations are in structuring gut microbial communities in
 comparison to other factors such as host characteristics or spatial
 proximity of hosts.   Here we ask how gut microbial communities
 are structured in a population of North American moose (Alces alces). We
 identify key microbial interspecific associations within the moose gut and
 quantify how important they are relative to key host characteristics, such
 as body condition, for predicting microbial community composition.
   We sampled gut microbial communities from 55 moose in a
 population experiencing decline due to a myriad of factors, including
 pathogens and malnutrition. We examined microbial community dynamics in
 this population utilizing novel graphical network models that can
 explicitly incorporate spatial information.   We found that
 interspecific associations were the most important mechanism structuring
 gut microbial communities in moose and detected both positive and negative
 associations. Models only accounting for associations between microbes had
 higher predictive value compared to models including moose sex, evidence
 of previous pathogen exposure, or body condition. Adding spatial
 information on moose location further strengthened our model and allowed
 us to predict microbe occurrences with ~90% accuracy.  
 Collectively, our results suggest that microbial interspecific
 associations coupled with host spatial proximity are vital in shaping gut
 microbial communities in a large herbivore. In this case, previous
 pathogen exposure and moose body condition were not as important in
 predicting gut microbial community composition. The approach applied here
 can be used to quantify interspecific associations and gain a more nuanced
 understanding of the spatial and host factors shaping microbial
 communities in non-model hosts.
description: The data was collected from fecal samples taken from live
 captured moose (55 individuals). Amplicons were sequenced sequenced on the
 Illumina MiSeq platform. Raw sequencing reads were
 processed using the University of Minnesota’s metagenomics-pipeline (a
 complete description of the pipeline can be found at https://bitbucket.org/jgarbe/gopher-pipelines/wiki/metagenomics-pipeline.rst) Representative OTU sequences were aligned against the Greengenes version 13_8 core set (DeSantis et al., 2006b) using UCLUST (Edgar, 2010) with QIIME default parameters.   See <strong>Appendix 1 & 2 </strong>for details on the analyical pipeline used.
description: <strong>OTU_taxonomy_updated.csv</strong> - OTU data
 from the MiSeq runs. Singletons are removed and the table rarified to
 100,859 reads. <strong>envAll.csv</strong>
 - host and environmental data from the moose in this study
 <strong>otu_jaccard.csv </strong>- functional
 information from a sepparate PiCRUST analysis.
 <strong>Appendix1_GitHubCode.R</strong>  -  R Code
 used to conduct our analysis.
 <strong>ggordiplot.R</strong>  - extra code used to
 overal a dendrogram onto a nMDS ordination.