Department of Veterinary Population Medicine, University of Minnesota, St Paul, MN, USA.
UQ Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Gatton, Qld, Australia.
J Anim Ecol. 2020 Mar;89(3):817-828. doi: 10.1111/1365-2656.13154. Epub 2020 Jan 26.
Microbial communities are increasingly recognized 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 with 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.
微生物群落越来越被认为对动物健康至关重要。然而，我们对野生动物种群中微生物群落的结构方式了解甚少。种间关联等机制对于自由生活群落的结构很重要，但我们仍然缺乏了解，与宿主特征或宿主空间接近度等其他因素相比，种间关联在构建肠道微生物群落方面有多么重要。在这里，我们研究了北美的北美驼鹿（Alces alces）种群中的肠道微生物群落是如何构建的。我们确定了驼鹿肠道内的关键微生物种间关联，并量化了它们相对于关键宿主特征（如身体状况）在预测微生物群落组成方面的重要性。我们从一个因多种因素（包括病原体和营养不良）而数量下降的驼鹿种群中采集了 55 只驼鹿的肠道微生物群落样本。我们利用新颖的图形网络模型研究了该种群中的微生物群落动态，这些模型可以明确纳入空间信息。我们发现，种间关联是塑造驼鹿肠道微生物群落的最重要机制，并且检测到了正相关和负相关的关联。仅考虑微生物之间关联的模型比包括驼鹿性别、先前病原体暴露或身体状况的模型具有更高的预测价值。添加关于驼鹿位置的空间信息进一步增强了我们的模型，并使我们能够以约 90%的准确度预测微生物的出现。总的来说，我们的结果表明，微生物种间关联加上宿主空间接近度对于塑造大型草食动物的肠道微生物群落至关重要。在这种情况下，先前的病原体暴露和驼鹿的身体状况对于预测肠道微生物群落组成并不重要。这里应用的方法可以用来量化种间关联，并更细致地了解塑造非模型宿主微生物群落的空间和宿主因素。
