Comparative gut microbiome research through the lens of ecology: theoretical considerations and best practices

Comparative approaches in animal gut microbiome research have revealed patterns of phylosymbiosis, dietary and physiological convergences, and environment-host interactions. However, most large-scale comparative studies, especially those that are highly cited, have focused on mammals, and efforts to integrate comparative approaches with existing ecological frameworks are lacking. While mammals serve as useful model organisms, developing generalised principles of how animal gut microbiomes are shaped and how these microbiomes interact bidirectionally with host ecology and evolution requires a more complete sampling of the animal kingdom. Here, we provide an overview of what past comparative studies have taught us about the gut microbiome, and how community ecology theory may help resolve certain contradictions in comparative gut microbiome research. We explore whether certain hypotheses are supported across clades, and how the disproportionate focus on mammals has introduced potential bias into gut microbiome theory. We then introduce a methodological solution by which public gut microbiome data of understudied hosts can be compiled and analysed in a comparative context. Our aggregation and analysis of 179 studies shows that generating data sets with rich host diversity is possible with public data and that key gut microbes associated with mammals are widespread across the animal kingdom. We also show the effects that sample size and taxonomic rank have on comparative gut microbiome studies and that results of multivariate analyses can vary significantly with these two parameters. While challenges remain in developing a universal model of the animal gut microbiome, we show that existing ecological frameworks can help bring us one step closer to integrating the gut microbiome into animal ecology and evolution.

Mock community as an in situ positive control for amplicon sequencing of microbiotas from the same ecosystem

Metataxonomy has become the standard for characterizing the diversity and composition of microbial communities associated with multicellular organisms and their environment. Currently available protocols for metataxonomy assume a uniform DNA extraction, amplification and sequencing efficiency for all sample types and taxa. It has been suggested that the addition of a mock community (MC) to biological samples before the DNA extraction step could aid identification of technical biases during processing and support direct comparisons of microbiota composition, but the impact of MC on diversity estimates of samples is unknown. Here, large and small aliquots of pulverized bovine fecal samples were extracted with no, low or high doses of MC, characterized using standard Illumina technology for metataxonomics, and analysed with custom bioinformatic pipelines. We demonstrated that sample diversity estimates were distorted only if MC dose was high compared to sample mass (i.e. when MC > 10% of sample reads). We also showed that MC was an informative in situ positive control, permitting an estimation of the sample 16S copy number, and detecting sample outliers. We tested this approach on a range of sample types from a terrestrial ecosystem, including rhizosphere soil, whole invertebrates, and wild vertebrate fecal samples, and discuss possible clinical applications.