Microbial associations and spatial proximity predict North American moose (Alces alces) gastrointestinal community composition

Abstract

1. 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.2. 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.3. 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.\ 4. 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. 5. Collectively, our results suggest that microbial interspecific associations coupled with host spatial proximity are vital in shaping infra 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.

Non‐invasive monitoring of multiple wildlife health factors by fecal microbiome analysis

“…Our positive model results are unique compared to some other studies attempting to associate the microbiomes of host animals to body condition, sex, and age (Bennett et al, 2016; Fountain‐Jones et al, 2020; Mshelia et al, 2018a). For example, previous studies found either no significant connection between the microbiome, host age, social group, and environment (Bennett et al, 2016), or incomplete support (Fountain‐Jones et al, 2020; Mshelia et al, 2018a; Ren et al, 2017). Substantive differences between our study methods and bioinformatic approaches likely contributed to these seemingly contradictory outcomes.…”

“…Classifier accuracies for sex and body‐fat were high, despite combining data from multiple elk populations that, as discussed, included the strong (and potentially confounding) signal of biogeographic diversity in the total microbiome. Our positive model results are unique compared to some other studies attempting to associate the microbiomes of host animals to body condition, sex, and age (Bennett et al, 2016; Fountain‐Jones et al, 2020; Mshelia et al, 2018a). For example, previous studies found either no significant connection between the microbiome, host age, social group, and environment (Bennett et al, 2016), or incomplete support (Fountain‐Jones et al, 2020; Mshelia et al, 2018a; Ren et al, 2017).…”

“…This study provides strong evidence for linkages between several elk physiological measurements and the host microbiome, as well as support for biogeographical structuring of the host microbiome. Analyses attempting to discover various individual factors influencing host‐microbiome structure in animals are common (Corl et al, 2020; Fountain‐Jones et al, 2020; Ren et al, 2017; Yuan et al, 2015), with previous research supporting both biogeographic structuring (Martiny et al, 2006; Moeller et al, 2017) and host‐associated responses (Cho & Blaser, 2012; Mshelia et al, 2018a). Despite a strong theoretical expectation, synergistic support for multiple intrinsic and extrinsic factors structuring host‐microbiomes is rarely demonstrated in a single study as demonstrated here.…”

Microbial associations and spatial proximity predict North American moose (Alces alces) gastrointestinal community composition

“…All code and data are available on GitHub: https://github.com/nfj1380/MRF_microbiome and Dryad Digital Repository: https://doi.org/10.5061/dryad.j9kd51c7k (Fountain‐Jones et al, ).…”

Positive associations matter: microbial relationships drive tick microbiome composition

“…Host factors such as sex and age as well as the spatial relationships between hosts are increasingly considered important in determining within-host microbial communities (hereafter 'microbiomes') [e.g., [6][7][8]. For example, hosts closer in space tend to have more similar microbiomes compared to those further away indicating that microbial dispersal can be important in structuring animal microbiomes [e.g.…”