Unraveling differences in fecal microbiota stability in mammals: from high variable carnivores and consistently stable herbivores

Abstract

Background Through the rapid development in DNA sequencing methods and tools, microbiome studies on a various number of species were performed during the last decade. This advance makes it possible to analyze hundreds of samples from different species at the same time in order to obtain a general overview of the microbiota. However, there is still uncertainty on the variability of the microbiota of different animal orders and on whether certain bacteria within a species are subject to greater fluctuations than others. This is largely due to the fact that the analysis in most extensive comparative studies is based on only a few samples per species or per study site. In our study, we aim to close this knowledge gap by analyzing multiple individual samples per species including two carnivore suborders Canoidea and Feloidea as well as the orders of herbivore Perissodactyla and Artiodactyla held in different zoos. To assess microbial diversity, 621 fecal samples from 31 species were characterized by sequencing the V3–V4 region of the 16S rRNA gene using Illumina MiSeq. Results We found significant differences in the consistency of microbiota composition and in fecal microbial diversity between carnivore and herbivore species. Whereas the microbiota of Carnivora is highly variable and inconsistent within and between species, Perissodactyla and Ruminantia show fewer differences across species boundaries. Furthermore, low-abundance bacterial families show higher fluctuations in the fecal microbiota than high-abundance ones. Conclusions Our data suggest that microbial diversity is significantly higher in herbivores than in carnivores, whereas the microbiota in carnivores, unlike in herbivores, varies widely even within species. This high variability has methodological implications and underlines the need to analyze a minimum amount of about 10 samples per species. In our study, we found considerable differences in the occurrence of different bacterial families when looking at just three and six samples. However, from a sample number of 10 onwards, these within-species fluctuations balanced out in most cases and led to constant and more reliable results.

Explorando la microbiota bacteriana fecal bovina en la Reserva de la Biosfera de Mapimí, norte de México

“…The presence of other bacterial genera reported in this study could be the result of environmental and genetic factors, age, breed, diet, phylogeny, among others (56,57,58) . Recently (56,59,60) , was demonstrated that herbivorous animals have the most diverse microbiota since they depend on microbial metabolic pathways to maximize energy and nutrient extraction from feeding (61) . Although the gut microbiome usually remains stable over time assisting as a system against pathogens and other disease-causing agents in the host, the disturbance of this community can lead to animal disease (62,63) .…”

Combining methods for non-invasive fecal DNA enables whole genome and metagenomic analyses in wildlife biology

“…However, researchers should consider the taxon and study system of interest when developing research projects as taxon-specific factors might impact study outcomes. For example, Zoelzer et al (2021) show that fecal microbiome diversity is significantly higher in herbivores than in carnivores, whereas intraspecific microbiome variation is high in carnivores but not in herbivores. Considering taxon-specific factors (e.g., diet and ecological context of the environment in which organisms occur) can therefore help ensure the success of research initiatives.…”

Rapid Oxford Nanopore Technologies MinION Sequencing Workflow for Campylobacter jejuni Identification in Broilers on Site—A Proof-of-Concept Study

“…In addition, this workflow makes it possible to analyse several samples at the same time in order to obtain a general overview of the microbiota, which could be useful for routine surveillance and early detection of foodborne pathogens [ 36 ]. Beyond that, as the microbiota influences various physiological and behavioural processes, a healthy microbiota would be correlated with an animal’s fitness, making it possible to identify health and welfare deviations in the animals [ 71 ]. Though the workflow proposed here was based on data analysed after complete data collection, taxonomy sequences were obtained a posteriori, after the sequencing process finished, using per-sequence timestamps added by the nanopore sequencing system itself to each read.…”