Disentangling the Possible Drivers of Indri indri Microbiome: A Threatened Lemur Species of Madagascar

Research on the gut microbiome may help with increasing our understanding of primate health with species’ ecology, evolution, and behavior. In particular, microbiome-related information has the potential to clarify ecology issues, providing knowledge in support of wild primates conservation and their associated habitats. Indri (Indri indri) is the largest extant living lemur of Madagascar. This species is classified as “critically endangered” by the IUCN Red List of Threatened Species, representing one of the world’s 25 most endangered primates. Indris diet is mainly folivorous, but these primates frequently and voluntarily engage in geophagy. Indris have never been successfully bred under human care, suggesting that some behavioral and/or ecological factors are still not considered from the ex situ conservation protocols. Here, we explored gut microbiome composition of 18 indris belonging to 5 different family groups. The most represented phyla were Proteobacteria 40.1 ± 9.5%, Bacteroidetes 28.7 ± 2.8%, Synergistetes 16.7 ± 4.5%, and Firmicutes 11.1 ± 1.9%. Further, our results revealed that bacterial alpha and beta diversity were influenced by indri family group and sex. In addition, we investigated the chemical composition of geophagic soil to explore the possible ecological value of soil as a nutrient supply. The quite acidic pH and high levels of secondary oxide-hydroxides of the soils could play a role in the folivorous diet’s gut detoxification activity. In addition, the high contents of iron and manganese found the soils could act as micronutrients in the indris’ diet. Nevertheless, the concentration of a few elements (i.e., calcium, sulfur, boron, nickel, sodium, and chromium) was higher in non-geophagic than in geophagic soils. In conclusion, the data presented herein provide a baseline for outlining some possible drivers responsible for the gut microbiome diversity in indris, thus laying the foundations for developing further strategies involved in indris’ conservation.

I Like the Way You Eat It: Lemur (Indri indri) Gut Mycobiome and Geophagy

Here, we investigated the possible linkages among geophagy, soil characteristics, and gut mycobiome of indri (Indri indri), an endangered lemur species able to survive only in wild conditions. The soil eaten by indri resulted in enriched secondary oxide-hydroxides and clays, together with a high concentration of specific essential micronutrients. This could partially explain the role of the soil in detoxification and as a nutrient supply. Besides, we found that soil subject to geophagy and indris’ faeces shared about 8.9% of the fungal OTUs. Also, several genera (e.g. Fusarium, Aspergillus and Penicillium) commonly associated with soil and plant material were found in both geophagic soil and indri samples. On the contrary, some taxa with pathogenic potentials, such as Cryptococcus, were only found in indri samples. Further, many saprotrophs and plant-associated fungal taxa were detected in the indri faeces. These fungal species may be involved in the digestion processes of leaves and could have a beneficial role in their health. In conclusion, we found an intimate connection between gut mycobiome and soil, highlighting, once again, the potential consequent impacts on the wider habitat.

Sex dimorphic phrase combinatorics in the song of the indris (Indri indri)

We used a logic distance to investigate intra and inter-individual variation in the phrase combinatorics of a singing primate, the indri, which inhabits the montane rain forests of Madagascar. Indris combine long notes, short single notes, and phrases consisting of two, three, four, or five units with slightly descending frequency. We calculated the similarity across different individual songs using the Levenshtein distance. We then analyzed the degree of similarity within and between individuals and found that: i) the phrase structure of songs varied between reproductive males and females; ii) male contributions to the song are overall more similar to those of other males; iii) male contributions are more stereotyped than females' ones. The picture emerging from phrase combinatorics in the indris is in agreement with previous findings of rhythmic features and repertoire size, which also suggested that female songs are potentially more distinctive than those of males.

Sex dimorphic phrase combinatorics in the song of the indris (Indri indri)

We used a logic distance to investigate intra and inter-individual variation in the phrase combinatorics of a singing primate, the indri, which inhabits the montane rain forests of Madagascar. Indris combine long notes, short single notes, and phrases consisting of two, three, four, or five units with slightly descending frequency. We calculated the similarity across different individual songs using the Levenshtein distance. We then analyzed the degree of similarity within and between individuals and found that: i) the phrase structure of songs varied between reproductive males and females; ii) male contributions to the song are overall more similar to those of other males; iii) male contributions are more stereotyped than females' ones. The picture emerging from phrase combinatorics in the indris is in agreement with previous findings of rhythmic features and repertoire size, which also suggested that female songs are potentially more distinctive than those of males.

Finding Meanings in Low Dimensional Structures: Stochastic Neighbor Embedding Applied to the Analysis of Indri indri Vocal Repertoire

Although there is a growing number of researches focusing on acoustic communication, the lack of shared analytic approaches leads to inconsistency among studies. Here, we introduced a computational method used to examine 3360 calls recorded from wild indris (Indri indri) from 2005–2018. We split each sound into ten portions of equal length and, from each portion we extracted spectral coefficients, considering frequency values up to 15,000 Hz. We submitted the set of acoustic features first to a t-distributed stochastic neighbor embedding algorithm, then to a hard-clustering procedure using a k-means algorithm. The t-distributed stochastic neighbor embedding (t-SNE) mapping indicated the presence of eight different groups, consistent with the acoustic structure of the a priori identification of calls, while the cluster analysis revealed that an overlay between distinct call types might exist. Our results indicated that the t-distributed stochastic neighbor embedding (t-SNE), successfully been employed in several studies, showed a good performance also in the analysis of indris’ repertoire and may open new perspectives towards the achievement of shared methodical techniques for the comparison of animal vocal repertoires.