Dietary shifts and social interactions drive temporal fluctuations of the gut microbiome from wild redfronted lemurs

Abstract

Animals living in highly seasonal environments adapt their diets accordingly to changes in food availability. The gut microbiome as an active participant in the metabolization of the host's diet should adapt and change with temporal diet fluctuations, but dietary shifts can be short-term and, hence, difficult to detect in cross-sectional studies. Therefore, we performed a longitudinal study combining repeated sampling of fecal samples with observations of feeding behavior in wild redfronted lemurs. We amplified taxonomical marker genes for assessing the bacteria, archaea, protozoa, helminths, and fungi, as well as the active bacterial community inhabiting their gut. We found that the most abundant protozoans were Trichostomatia and Trichomonadida, and the most abundant helminths were Chromadorea. We detected known members of the gut mycobiome from humans but in low abundances. The archaeal community is composed only of members of Methanomethylophilaceae. The predominant phyla in the entire bacterial community were Bacteroidota and Firmicutes while the most abundant genera harbor so far unknown bacteria. Temporal fluctuations at the entire community level were driven by consumption of fruits and flowers, and affiliative interactions. Changes in alpha diversity correlated only with the consumption of flowers and leaves. The composition of the entire and active bacterial community was not significantly different, but the most abundant taxa differed. Our study revealed that monthly changes in the bacterial community composition were linked to fruit and flower consumption and affiliative interactions. Thus, portraying the importance of longitudinal studies for understanding the adaptations and alterations of the gut microbiome to temporal fluctuations.

Fig. 1. Prokaryotic and eukaryotic communities from the gut of redfronted lemurs during the study period from May 2018 until April 2019.

A Monthly relative abundances of bacterial phyla for the five studied individuals as determined from 16 S rRNA gene sequencing. Bar charts depict relative abundances of bacterial phyla from normalized counts for each individual per month. All phyla with abundances <2% were grouped as rare taxa. B Eukaryotic organisms detected in the fecal samples through 18 S rRNA gene sequencing. Bar charts show monthly relative abundances of eukaryotic classes from normalized counts. All phyla with abundances <2% were grouped as rare taxa. C Monthly fluctuations in the relative abundances of Chromadorea, Trichostomatia, and Trichomonadida. Linecharts depict relative abundances of normalized counts of the detected eukaryotic parasites or endosymbionts in the fecal samples. D Fungal organisms detected in the fecal samples through ITS2 sequencing. Barcharts display monthly relative abundances of fungal orders from normalized counts. All taxa with abundances <2% were unified as rare taxa. E Maximum likelihood phylogenetic tree of the unclassified ITS2 ASVs against representative Fungi.

Fig. 2. Monthly fluctuations in most abundant bacterial genera and alpha diversity detected in fecal samples from redfronted lemurs from May 2018 to April 2019.

A Top 5 most abundant bacterial genera and their monthly changes for all studied individuals. Line charts display relative abundances from normalized counts. B Mean monthly precipitation calculated from records of daily precipitation and seasons from the study period. C Monthly feeding rates on fruits, leaves, and flowers determined through behavioral focal observations. D Monthly variations in alpha diversity measured by Faith’s Phylogenetic Diversity Index of all studied individuals.

Fig. 3. Seasonal variations of bacterial genera, beta diversity, and composition of the entire gut bacterial community of redfronted lemurs from May 2018 until April 2019.

A Log2f fold changes in the mean abundances of bacterial genera between dry and rainy season as detected with ANCOM 2.1. B PCoA based on weighted Unifrac of the bacterial community and environmental fit analysis depicting significant correlations between temporal fluctuations in beta diversity and the environmental, diet and social factors investigated. C Heatmap showing the 20 bacterial genera for which taxon-specific effects differed most from the average across all taxa as detected in a LMM estimating the effects of diet and affiliative interactions on community composition. The image displays the test predictors for which an effect was detected, feeding on flowers and fruits, and affiliation rates. Precipitation was included as the control predictor. Positive effects are depicted with orange, whereas negative effects are colored in purple.

Fig. 4. Environmental and dietary factors driving the monthly fluctuations in alpha diversity of the entire bacterial community measured with the Faith’s Phylogenetic Diversity index.

A Monthly rates of flower consumption (min/h) correlate negatively with alpha diversity. B Monthly rates of leaves feeding (min/h) correlate positively with a higher alpha diversity. C Mean monthly precipitation correlates negatively with alpha diversity. The effects of diet, affiliation rates and precipitation were determined with a LMM.

Fig. 5. Monthly fluctuations in the bacterial composition and alpha diversity of the active bacterial community in fecal samples from redfronted lemurs from May 2018 to April 2019.

A Top five most abundant bacterial genera and their monthly changes for all studied individuals. Line charts display relative abundances from normalized counts. B Monthly variations in alpha diversity measured by Faith’s Phylogenetic Diversity Index in all studied individuals. C PCoA from WUnifrac of the bacterial community and environmental fit analysis depicting significant correlations between temporal fluctuations in beta diversity and the environmental, diet and social factors investigated. D Monthly rates of flower consumption (min/h) correlate negatively with alpha diversity. The effects of diet, affiliation rates and precipitation on alpha diversity were determined with an LMM.