Assessing the gut microbiome and the influence of host genetics on a critically endangered primate, the Northern muriqui (Brachyteles hypoxanthus)

doi:10.21203/rs.3.rs-2583209/v1

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Assessing the gut microbiome and the influence of host genetics on a critically endangered primate, the Northern muriqui (Brachyteles hypoxanthus)

https://doi.org/10.21203/rs.3.rs-2583209/v1

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Background

The Northern muriqui (Brachyteles hypoxanthus) is one of the world’s most critically endangered primates, currently represented by only ~ 1000 remaining mature individuals in the wild. The largest new world primate, this endemic herbivore plays an important role in seed dispersal in the Brazilian Atlantic Forest. However, due to several threats such as habitat loss and hunting, the species is in sharp decline and conservation actions are paramount to safeguarding its persistence. Analyses of gut microbiomes in wild populations can contribute to assessing the health status of the host species through the identification of microbial community changes which could lead to increased host vulnerability and disease. This can ultimately contribute to baseline knowledge towards improving conservation programmes and reintroduction efforts.

Results

In this study, we analysed the microbiome (using 16S rRNA metabarcoding) of faecal samples belonging to 53 uniquely genotyped individuals from three social groups located in a protected area (Caparaó National Park) aiming to provide the first assessment of the microbiome diversity and composition for this species. Our results showed the muriqui gut microbiome was predominantly composed of the phyla Bacteroidetes and Firmicutes, with the dominant classes represented by Bacteroidia and Clostridia. High similarity in both alpha and beta diversities was found for individuals from distinct groups, suggesting a lower environmental filtering effect on microbiota composition and a negligible geographical effect at the fine spatial scale analysed. Additionally, no significant effect of heterozygosity levels on microbiota diversity was recovered, but a significant influence of genetic distance on microbiota community structure and composition was demonstrated.

Conclusions

Here, we showed the importance of host genetics on the microbiome and highlighted that although the analysed populations are deemed isolated due to putative environmental barriers, they host a similar microbiome composition, with faecal microbiome stability possibly associated with host genetics, and the linked shared feeding strategies. Furthermore, the detailed wild Northern muriqui microbiome assessment herein included might be used for subsequent management and conservation actions considering future anthropogenic impact assessments on the species and animal relocations and/or reintroductions.

16S rRNA

Atlantic Forest

amplicon sequencing

bacteria

endemic

microbiota

threatened species

Recent assessments on global biodiversity have seen a steep rise in the number of endangered species, forecasting overwhelming and unprecedented extinction rates in the near future. According to the latest IUCN report, over 42,000 species are threatened with extinction (IPBES, 2019; IUCN, 2022). Habitat fragmentation and hunting are among the main threats to species survival, and in one of the world’s biodiversity hotspots, the Atlantic Forest, the impact of these threats has pushed several species close to the brink of extinction (Ribeiro et al., 2009). Among these highly threatened species is the Northern muriqui (Brachyteles hypoxanthus), the largest extant species of the new world monkeys. This primate, endemic to the Brazilian Atlantic Forest, is currently one of the world's most critically endangered primates, with an estimated population of less than 1000 mature individuals left in only a dozen forest fragments (de Melo et al., 2021; Strier et al., 2017).

Contemporary conservation strategies, aiming at protecting threatened species, are crucial and have targeted multiple approaches including the creation of forest corridors, translocation of individuals to increase genetic diversity between populations, and ex-situ breeding programmes (Franquesa-Soller et al., 2022; Chazdon et al., 2020; Kierulff et al., 2012). Nevertheless, these efforts might be disrupted not only by the limited availability of habitat but also due to low success rates in both translocation actions and captivity/post-release scenarios related to animal reproduction and health (Campera et al., 2020; Beck, 2019).

Recently, the role of microorganisms in influencing animal health has led to a discussion of the importance of microbiome studies in threatened species conservation (West et al., 2019). Host-microbiome interactions are known to exert powerful influences on the health, physiology, behaviour, and fitness of its host, and due to the complexity of these relationships, the host and its associated microbiota might often be considered metaorganisms (Lynch and Hsiao, 2022; Bosch and McFall-Ngai, 2011). The microbiome plays a key functional role within the host organism with many types of bacteria being present in the gut microbiota. These include commensal bacteria known to act on the host’s immunological system (Forsythe and Bienenstock, 2010), beneficial bacteria which provide an essential function for health (e.g., acting on vitamin and short-chain fatty acids synthesis - McKenney et al., 2018), or the opportunistic ones that might be linked to the onset of diseases (West et al., 2019). Thus, fluctuations in microbiota composition might lead to host phenotype changes, with healthier individuals showing highly dynamic microbial communities whereas the onset or development of diseases may be due to dysbiosis of the microbiota (Gilbert et al., 2016; McKenzie et al., 2018).

The importance of determining the microbiome of both captive and wild animals, linking certain groups of bacteria to chronic diseases has been recently demonstrated for Neotropical primates (Richards-Rios et al., 2021). Whereas, for the endangered Tasmanian devil (Sarcophilus harrisii), the first assessment of the microbiome for this species revealed shifts during translocations with significant temporal changes and captive animals showing a lower bacterial diversity compared to wild individuals (Cheng et al., 2019). It is suggested that changes in the microbiome can affect animals' ability to adapt and survive, thus stressing the importance of incorporating microbiome monitoring into species’ recovery programmes.

Given the host-microbiome interaction, investigating the microbiome linked to the host’s biological information and habitat might shed light on the responses to environmental changes, and subsequently direct required species management and conservation actions (Couch and Epps, 2022). In this context, microbiome research has great potential to improve conservation efforts and its application in a more ecological context might increase the understanding of the effect of several factors such as climate and land-use changes, infectious disease, and captivity and translocations on species' response and survival (Trevelline et al., 2019). These efforts combined might represent a turning point for conservation outcomes, much needed in the face of the current biodiversity crisis. Despite the current understanding of the microbiome’s significance on species conservation, studies addressing its role remain mostly restricted to research on humans (The Integrative HMP Research Network Consortium, 2019), whereas the understanding of the microbiome in threatened species and its effect on host health, fitness and survival are still in their infancy (Bahrndorff et al., 2016, West et al., 2019). Therefore, there is an urge to gather novel non-invasive information, providing baseline knowledge to help inform management decisions and conservation action plans. Due to intense deforestation and fragmentation, connectivity between habitats can be severely impacted, leading to the isolation of entire populations or individuals. This is especially relevant to the Critically Endangered muriqui, with females being unable to disperse in search of new conspecific groups (i.e., due to the absence of suitable habitats or barriers to migration). Therefore, translocations are likely to be vital for the long-term persistence of this species (Oliveira et al., 2020). Amongst the few forest remnants known to harbour muriqui populations, the Caparaó National Park harbours newly identified groups of muriqui that were recently discovered, and it is now considered one of the key areas for this species' persistence (Kaizer et al. 2022).

In this study, we characterised the muriqui gut microbiome diversity and provided a comparison among different groups inhabiting both sides of the Caparaó National Park to evaluate the similarities and discrepancies in their microbiota composition. Additionally, to investigate the potential influence of host genetic diversity on the microbiome, the effect of individual homozygosity on the microbiota’s alpha diversity and the influence of genetic distance on the structural bacterial diversity were analysed. Considering the lack of knowledge about the microbiota of this and other endangered species in general, this study has the potential to advance management practices to increase the success of conservation actions and/or future animal translocations.

2.1 Field Sampling

Samples were collected at Caparaó National Park (CNP) (Southeastern Brazil, 20°37’- 20°19’ S; 41°43’- 41°55’ W) between 2018 and 2020. This protected area is characterised by the presence of a chain of mountains dividing the park into two areas, harbouring unhabituated groups of the Northern muriqui (B. hypoxanthus) known to occur on both sides of the park. In this study, samples from three groups were analysed, including one muriqui group inhabiting the western side of the park (Vale do Aleixo, VA, n = 37 samples), and two groups occurring in two different valleys on the eastern side of the park including Vale do Santa Marta (VSM, n = 10 samples) and Vale do Facão de Pedra (VFP, n = 6 samples) (Fig. 1, Table S1). The vegetation for the western side of the park (i.e., VA site) is characterised by a seasonal semi-deciduous montane forest, whereas the eastern side (i.e., VSM and VFP sites) comprises a montane ombrophilous dense forest (Kaizer et al., 2022).

To characterise the gut microbiome of individuals from this critically endangered species, faecal samples were collected opportunistically at three different sites (Table S1), under the approved licence (SISBIO 54795-1). All samples were collected non-invasively and fresh beneath animals that had recently defecated and were obtained without disturbing the animals. Upon collection, samples were immediately stored in RNAlater (Ambion) using equal volumes and kept at -20°C until shipment on dry ice to the UK before DNA extraction.

2.2 Individual And Population Genetic Analyses

All individuals included in the microbiome analyses were genotyped using a set of 14 nuclear microsatellite loci (see Table S2). DNA was extracted using the QIAamp Fast DNA Stool Mini Kit (Qiagen) following the human DNA analysis protocol. For full details of the genotyping protocol, see the Supplementary Material.

Individual identity was estimated in CERVUS v 3.0.7 (Kalinowski et al., 2007). To ensure samples represented different individuals, duplicates were identified by searching for matching genotypes using the probability of identity assuming a full-sibling relationship (PIDsib, < 0.05) and removing genotypes if they matched at ten or more loci, without mismatches.

Individual and social group-level observed heterozygosity (Ho) and homozygosity by loci (HL) were calculated using Cernicalin (Aparicio et al., 2006), and pairwise Nei’s genetic distances were calculated in GenAlEx 6.5 (Peakall and Smouse, 2012), for all groups and all individuals.

2.4 16S rRNA amplicon sequencing

Characterisation of bacterial communities was conducted based on the amplicon sequencing of ~ 250 bp of the 16S rRNA region using the 515F and 806R primers (Caporaso et al., 2011). Briefly, PCRs were conducted in duplicates in a final volume of 15 µL per reaction, using the Solis BioDyne 5x HOT FIREPol® Blend Master Mix (3 µl), 2 µM primers (4 µL), 2 µL of sample DNA. Thermocycler conditions were as described in Antwis et al. (2021): 95°C for 10 min; 25 cycles of 95°C for 30 s, 55°C for 20 s and 72°C for 30 s; and a final extension of 72°C for 8 min. Negative (PCR blanks, N = 2) and positive (ZymoBIOMICS Microbial Community DNA Standard, N = 1) controls were also included, totalling 56 samples. PCR replicates were combined and purified using HighPrepTM PCR clean-up beads (MagBio) using a 1:1.5X ratio, according to the manufacturer's instructions. PCR products were checked on an Agilent 2200 TapeStation, DNA concentration was measured by fluorometric analysis (Qubit, Thermo Fisher Scientific) and samples were equimolarly pooled (normalised to 30 ng per sample). The final library was sequenced using the Illumina platform (2 × 300 bp, MiSeq v3 kit) along with samples from an unrelated project.

2.5 Bioinformatics And Statistical Analysis

Bioinformatics analyses were conducted in RStudio (v. 3.3, 2020), following the DADA2 workflow (Callahan et al. 2016, please see Supp. Material for detailed information on the filtering steps). The 16S rRNA gene amplicon sequencing yielded a total of 2,502,995 raw sequence reads, with a contig length of ~ 253bp after merging paired-end reads. Sequence variants (SVs) with lengths > 260 bp (0.004% of total sequences) along with chimaeras (0.031% of total reads) were removed. Taxonomic assignment was based on the SILVA v132 database (Quast et al., 2013; Yilmaz et al., 2014). DADA2 identified 10 unique SVs in the sequenced mock community sample including the 8 bacterial isolates (Pseudomonas aeruginosa, Escherichia coli, Salmonella enterica, Lactobacillus fermentum, Enterococcus faecalis, Staphylococcus aureus, Listeria monocytogenes, Bacillus subtilis) and 2 yeasts (Saccharomyces cerevisiae, Cryptococcus neoformans). After all filtering steps, the final SV table, taxonomy table and sample metadata were exported to the phyloseq package (McMurdie and Holmes, 2013), including a total of 1,954,164 reads and a mean of 34,394 reads per sample (ranging from 5,950 to 61,008 reads/sample).

Statistical analyses and data visualisation were performed in RStudio v461 using the phyloseq, vegan and ggplot2 packages (R Core Team, 2016; Oksanen et al., 2007; McMurdie and Holmes, 2013). Rarefaction curves were used to analyse the expected number of amplicon sequence variants (ASVs) detected per sample according to the sequencing depth. To account for differences in sequencing depth (Fig. S1), diversity indices were computed through rarefaction of the dataset at a subsampling depth of 12,300 reads and thus, one sample with < 12,300 reads was excluded from the rarefied dataset and downstream analyses. Accumulation curves were obtained for rarefied data, including all samples analysed, to visualise the expected number of taxa detected according to the sampling size (Fig. S2).

2.6 Alpha And Beta Diversity Analyses

To determine the diversity and composition of bacterial communities, bar plots of relative read abundance were obtained for Phyla and Class, and alpha and beta diversity indices were calculated at the ASV level. Alpha diversity was estimated using four indices (observed richness, Chao1, Shannon’s and Simpson diversity), and the association between studied sites and the alpha diversity matrices was investigated using the Kruskal-Wallis test, following Shapiro-Wilk normality test results (all p = < 0.05). To investigate the association between alpha diversity and individual-level observed homozygosity (Ho), a Pearson’s correlation test was used.

Beta diversity was calculated using the Bray-Curtis and UniFrac distance metrics (weighted and unweighted, Hamadyet al., 2009). The Bray-Curtis is a dissimilarity measure based on abundance data, whereas the Unweighted UniFrac distances are based on the presence/absence of different taxa considering the phylogenetic relationships, and the Weighted UniFrac additionally incorporates the taxa abundance information. For the latter analyses, phylogenetic trees were obtained using the ape package. The betadisper function was used to test the multivariate homogeneity of group dispersion, and the statistical difference in beta dispersion between groups was investigated through the permutest. Due to the varied sample sizes and unequal beta dispersion between groups, the ANOSIM (Analysis of Similarities) test was used to assess statistical differences in microbial beta diversity across different locations, using 999 permutations. Patterns of separation between samples were visualised through Principal Coordinates Analysis (PCoA) based on the Bray-Curtis, Unweighted and Weighted UniFrac dissimilarity matrices.

Differential taxa abundance analysis was used to identify genus-level ASVs showing significant differences in the microbiome for muriquis from distinct social groups. A Wald test with Benjamini-Hochberg adjustment as implemented in DESeq2 (Love et al., 2014) and only ASVs remaining statistically significant (p < 0.05) were retained.

Analysis of the effect of geographical distance on microbiome compositions was conducted considering the dissimilarity between groups (i.e., herein represented by using distinct social groups sampled in different locations inhabiting both east and west sides of the park) for both alpha and beta diversity indices. The association between the microbiome composition (UniFrac/Bray-Curtis distances) and the influence of host genetics on microbial community structure was investigated through the Mantel test based on Spearman's rank correlations (999 permutations), testing the relationship between individual-level genetic distances and Bray-Curtis/UniFrac distances.

In total, muriqui faecal samples from 53 uniquely identified individuals (inferred from microsatellite genotyping) were successfully sequenced and the curated 16S rRNA dataset included 651,900 reads after all quality control filtering, classification, and rarefaction. Across the microbiota of all muriqui sampled in this study, 1339 ASVs were retrieved, representing at least nine Phyla, 18 Classes, and 56 Orders.

The bacterial microbiota profile obtained for all analysed groups revealed Bacteroidetes as the most abundant phylum accounting for 58.33% of all sequences, Firmicutes were about half as abundant with 25.77% of the reads, followed by Proteobacteria (9.55%), Tenericutes (2.71%) and Cyanobacteria (1.95%) (Fig. 2, Tables S3-S5). A similar pattern of phyla compositional abundance was obtained across most of the individuals analysed, with only four individuals showing a read abundance > 20% for Proteobacteria, from which two individuals showed a higher abundance of this phylum over Bacteroidetes/Firmicutes (MC104, MC112 - Fig. 2A). When comparing the social groups analysed, only samples collected from Vale do Aleixo had a visible presence of Actinobacteria.

Overall, the microbiota profile at the Class level was also very similar across most individuals sampled. The Bacteroidetes retrieved from the muriqui gut represented a diverse array of Families, the great majority from the Bacteroidia which was also the most abundant Class with 99.99% of the reads recovered for this Phylum. For the Firmicutes, most of the highly abundant families belonged to the Clostridia (76.23%) and Erysipelotrichia (12.39%) Classes. Although accounting for only 4.85% of the total reads recovered for Firmicutes, Bacilli showed a greater predominance in one of the analysed individuals (MC10). Gammaproteobacteria which was the most abundant for the Proteobacteria (92.31% of the reads), was also predominant in two of the analysed samples (MC104, MC112), and for all other individuals, Bacteroidia was the most abundant (i.e., 51/53–96% of the samples analysed) (Fig. 2B, Table S4).

Analyses of microbial community alpha diversity, based on the ASV level, showed similar ASV richness for all groups analysed (Fig. 3, Table S5). The VFP site had the highest diversity for the observed and Shannon indices (Observed = 277.33 ± 53.65, Shannon = 4.41 ± 0.51), followed by VSM for the Observed and Chao1 indices, respectively (252.40 ± 37.43, 259.40 ± 40.23) and VA for the Simpson, alongside VFP (0.95 ± 0.04, 0.95 ± 0.05, respectively). Yet, no significant statistical differences were found amongst the analysed groups for the four indices (Observed p = 0.549, Chao1 p = 0.517, Shannon p = 0.135, Simpson p = 0.121, Table S6).

To determine whether the social group influenced the community composition of the microbiome, three beta diversity measures (Bray-Curtis, Unweighted and Weighted UniFrac) were obtained and compared across the analysed groups (Table S7). Although significant differences were retrieved from the PERMANOVA test (p = 0.001–0.084), the variance partitioning test (PERMUTEST) showed a greater compositional variance within the groups, with significantly different dispersions retrieved between VFP-VA and VFP-VSM (overall, Bray-Curtis p = 0.006, Unweighted UniFrac p = 0.034, and Weighted UniFrac p = 0.018). A further comparison obtained through the ANOSIM test revealed no significant difference across the analysed groups (Bray-Curtis p = 0.311, Unweighted UniFrac p = 0.284, Weighted UniFrac p = 0.534). Therefore, the composition of muriqui gut microbial communities showed similarities across the three analysed sites, as revealed by beta diversity showing the overlap between individuals from different groups and with no clustering by sampling location (Fig. 4).

Despite not showing a significantly different microbiota community, the distribution of social groups influenced the abundance of a few taxa with several genus-level ASVs being differentially abundant (p < 0.05) across individuals from VSM, VFP and VA groups (Fig. 5). VFP represented the social group with the greatest amount of ASVs showing a differential abundance, including the families Ruminococcaceae, Erysipelotrichaceae, Lachnospiraceae (including 2 ASVs belonging to Shuttleworthia), Muribaculaceaea, Atopobiaceae, Prevotellaceae and a non-identified family belonging to the Order Bacteroidales. For the VSM group, the ASV showing a higher abundance when compared to the other two groups was identified as the genus Staphylococcus, whereas for the VA group, the genus Mycoplasma showed a higher differential abundance. Interestingly, VA had a greater number of ASVs indicating a lower abundance when compared to the other groups, and these included the families Atopobiaceae, Eggerthellaceae, Prevotellaceae, Ruminococcaceae and the genera Selenomonas and Dialister.

Finally, the interplay between host genetics and the gut microbiome was investigated using both alpha and beta microbial diversities. The homozygosity coefficients under investigation in this study (Ho – observed homozygosity per individual, HL – homozygosity by loci) did not indicate a relationship with bacterial ASV richness for any of the indices analysed (Observed, Chao1, Shannon, Simpson, all p = > 0.05, Table S8). However, a significant correlation was retrieved when comparing genetic distances and beta diversity distances (Mantel test, Bray-Curtis p = 0.003 r = 0.22; Unweighted UniFrac p = 0.04 r = 0.13; Weighted UniFrac p = 0.002 r = 0.25, Table S9). Stronger positive correlations were found when comparing the muriqui genetic distances to beta diversity dissimilarity metrics that take into account the abundance (i.e., Weighted UniFrac and bray-Curtis), with the highest r value obtained for the Weighted UniFrac distance, which considers the taxa abundance and phylogenetic relationships (r = 0.25), followed by Bray-Curtis distance (r = 0.22) and Unweighted UniFrac (r = 0.13).

Therefore, these results demonstrate that although heterozygosity does not seem to affect the microbiota alpha diversity, there is an influence of genetic relatedness on microbial community structure, considering both microbiome composition measured through beta diversity estimates and genetic distance between individuals.

Investigations into the gut microbiome of wild populations are considered an emerging priority for assessing the health of these populations in the face of ever-increasing anthropogenic disturbances (West et al., 2019). Identifying potential endogenous and exogenous factors that might play a role in shaping the microbiome is paramount, especially when considering the effect of microbiota on an animal’s health status and the possible implications for the conservation and management of endangered species (Bahrndorff et al., 2016; Jiménez and Sommer, 2016). In this context, we analysed the gut microbiome of 53 muriqui individuals from the Caparaó National Park, Brazil. We aimed to provide an initial assessment of this critically endangered species’ microbiome and in particular, to investigate the putative effect of group distribution (i.e., geographical location) and host genetics on their microbial structure and composition.

Overall, we observed that Bacteroidetes was the predominant phyla followed by Firmicutes, with the dominant classes represented by Bacteroidia and Clostridia, with both phyla and classes being commonly found in primate guts (Clayton et al. 2018, Nagpal et al. 2018, Yao et al., 2021, Zhao et al., 2023). Amongst the individuals analysed, 7.40% (n = 4, MC10, MC104, MC112 and MC41) showed differences in their bacterial community composition, with the abundance of phylum Proteobacteria (class Gammaproteobacteria) accounting for > 20% of the total reads. Overgrowth of Proteobacteria, which include numerous pathogenic genera of bacteria, has been suggested as a signature of dysbiosis and disease in humans, including metabolic disorders, inflammation, and cancer (Shin et al., 2015, Rizzatti et al., 2017). This compositional shift might reflect host or environmental changes that could lead to dysbiotic gut microbiomes or natural variations in the group such as different feeding strategies (Mallott et al., 2018), the age of the individuals (Reveles et al., 2019), reproductive state (Sun et al., 2020), or social status (Rudolph et al., 2022) for example. A comparison of the three social groups showed the presence of Actinobacteria only in individuals inhabiting Vale do Aleixo. Actinobacteria, even though usually found in low abundance, has a major role in maintaining gut homeostasis (Binda et al., 2018, Sakarkar, 2022).

Two out of the four individuals (MC104 and MC112) had the lowest alpha diversity values recovered among the analysed groups (MC104/MC112 – Observed = 40/88, Chao1 = 40/92.5, Shannon = 2.17/2.63, Simpson = 0.78/0.88). Low alpha diversity has been previously detected together with dysbiosis of the gut microbiome for captive primates and linked to dietary changes and increased stress levels (McKenzie et al, 2017, Frankel et al., 2019). However, dysbiosis remains poorly reported for wild primates (and indeed, most wild species) and further investigations are required to understand patterns in wildlife populations more generally (Ghosh et al., 2021). Dietary changes could also be linked to compositional shifts found for the other two individuals showing higher bacterial diversity (MC10 and MC41). Similar compositional shifts between Bacteroidetes and Proteobacteria have been previously reported and linked to distinct food intakes for the Arunachal macaque, with a high prevalence of Bacteroidetes in animals who foraged upon cultivated crops in contrast to an enriched Proteobacteria for groups feeding on human leftover food remains (Ghosh et al., 2021).

A predominantly folivorous and frugivorous diet is known for muriquis. Studies assessing the muriqui’s diet showed a diet composition including resources such as leaves, fruits, flowers, and additional items (e.g., twigs, tree barks, stem) (Carvalho-Jr et al., 2004). Knowledge in feeding behaviour remains limited for Brachyteles, especially for the Northern muriqui. However, variation in the percentage of feeding records was previously recorded for groups inhabiting distinct areas (i.e., higher intake of lowers in Fazenda Esmeralda than in Estação Biológica de Caratinga which had a comparatively higher proportion of fruit consumption; Rímoli and Ades, 1997, Carvalho-Jr et al., 2004), and shifts towards a more folivorous diet when fruits are scarce were reported and linked possibly to changes in rainfall and food resource availability (Strier, 1991). Yet, the diet of muriquis inhabiting the CNP and possible diet shifts remains largely unknown to date.

Although no significant difference was found for the alpha diversity measures recovered among the analysed groups, the overall values were lower than reported for other primates of the Atelidae family (McKenzie et al., 2017, West et al., 2019). In this study, the muriqui showed Shannon bacterial diversity ranging from 3.93 to 4.41, whereas for both Alouatta spp. and Ateles spp. with values above 6 recovered for wild individuals and values above 4 were retrieved for individuals in captivity (McKenzie et al., 2017). Still, a lowered bacterial diversity has been observed in primates living in captivity or fragmented areas (Amato et al., 2013; Barelli et al., 2020, Trosvik et al., 2018, Zhao et al., 2023) and the small group sizes inhabiting this forest remnant might have contributed to this reduction in gut microbial diversity. It is important to note, however, that the alpha diversity values herein retrieved were in line with results obtained by Harrison et al. (2021), in which values < 4 (Shannon diversity) were retrieved for muriqui, with this species showing a more diverse microbial community when compared to other mammal species (e.g., capuchin monkey, eastern black rhino). Therefore, a more in-depth comparative analysis of wild primate bacterial diversity, alongside an investigation of the underlying factors responsible for shaping microbiome diversity, is needed.

Although no significant differences in microbial community composition were found across analysed groups, a differential abundance was recovered for some of these groups. The highest amount of over-represented taxa was seen in the VFP group, including the families Ruminococcaceae, Erysipelotrichaceae, Muribaculaceae, Atopobiaceae, Prevotellaceae and Lachnospiraceae which included 2 ASVs belonging to Shuttleworthia. In contrast to that, the VSM groups had only one over-represented ASV with Staphylococcus being detected in a significantly greater amount when contrasted to the other two groups. In the VA group, only Mycoplasma showed a significantly greater abundance in comparison with the VFP and VSM groups, with several taxa underrepresented in this group when compared to the remaining ones. Taxa showing a lower abundance in VA included the families Atopobiaceae, Eggerthellaceae, Prevotellaceae, Ruminococcaceae and the genera Selenomonas and Dialister. Across these families, several taxa have been previously linked to gut health such as playing an important role in plant secondary compound metabolism (e.g., Eggerthellaceae, Greene et al., 2020), acting in the production of butyrate and other short-chain fatty acids (previously associated to neuro-immunoendocrine regulation) through bacterial fermentation of dietary fibres (e.g., Ruminococcaceae, Silva et al., 2020), and playing a role in host lipid metabolism or inflammatory diseases (e.g., Erysipelotrichaceae, Kaakoush, 2015). These taxa were highly abundant in VFP individuals in contrast to the other groups. Staphylococcus, the only genus differentially abundant in the VSM group comprises over 40 species, including the pathogenic S. aureus which has recently been of concern due to its putative zoonotic transmission and impact on wildlife health (Tang et a., 2021). In this case, more accurate identification is paramount to understanding the impact of a greater abundance of this genus/species on the investigated social group. In regard to the VA group, the highly abundant Mycoplasma represent a commensal group of bacteria widely detected in association with the mucous membrane of mammals, however, the occurrence of potential opportunistic infections associated with this bacteria has been previously reported including Neotropical primates (e.g., detection of Mycoplasma sp. in an Alouatta caraya individual showing normochromic and macrocytic anaemia, Bonato et al., 2015). Besides that, this group also had an underrepresentation of Selenomonas and Dialister, with the first including species associated with fibre digestion in ruminants and/or fermentation of lactate and soluble sugars (Sawanon et al., 2011, Hespell et al., 2006). The latter, Dialister, a lactic acid and fermentative bacteria, shows a lower abundance in wild colobine primates when compared to captive individuals, with decreased levels being further associated with lower levels of social integration and increased dysbiosis (Amato et al., 2016, Garber et al., 2019, Pinacho-Guendulain et al., 2022). These differential abundances could provide some insights in regards to animals' gut health and/or the effect of environmental conditions, including food availability and foraging behaviour. On that account, a more detailed functional analysis of bacterial communities including metagenomic analysis and metabolomic profiling is key.

The gut microbiome itself is shaped not only by extrinsic conditions (i.e., diet, lifestyle, habitat heterogeneity) but also by intrinsic factors (i.e., sex, age, genotype) (Amato et al, 2013, Bahrndorff et al., 2016, Dubois et al., 2017; Wasimuddin et al., 2017). In this context, the host microbiome has a two-way route, both influencing the host’s immune system and being influenced by the host's genetic diversity (Montero et al., 2021). The association between genetic differences among hosts and in shaping their susceptibility to pathogens is well known. Yet, the contribution of host genes to the microbiome remains mostly unclear (Tabrett and Horton, 2020).

Considering the role of geography in shaping the gut microbiome has not been seen herein at this microgeographic scale, an investigation of the correlation between host genetics and microbiome diversity and composition was performed. In this study, 14 nuclear microsatellite loci were used to investigate the association between the genetic makeup and gut bacterial communities of the host. No effect of muriqui genetic diversity on microbial diversity was obtained, as demonstrated by the absence of a correlation between individual heterozygosity (Ho – observed heterozygosity, HL – homozygosity by loci) and bacterial ASV richness (Observed, Chao1, Shannon, Simpson, all p = > 0.05). However, the influence of host genetics on microbiome was demonstrated through a significant positive correlation retrieved between beta diversity indices and genetic distances (Mantel test, p < 0.05), with the highest r value retrieved for the Weighted UniFrac distance, highlighting the importance of considering taxa abundance and phylogenetic relationships. These results demonstrate that microbial community structure may be influenced by genetic relatedness, as previously reported by Grieneisen et al. (2021) where a high gut microbiome heritability was demonstrated after analysing 16,000 baboon gut microbiome profiles obtained for 585 individuals during a 14-year-long study.

The results obtained herein offer an interesting insight into the Northern muriqui’s management and conservation. The demonstrated influence of host genetics on the microbiome and the absence of geographic filtering (no difference retrieved between analysed social groups) might indicate a possible flow of individuals between these groups. Female muriquis are known to emigrate from their natal groups, a rare life history strategy amongst primates (Strier et al., 2015). This dispersal pattern could help explain the similarities found amongst the analysed groups due to genetic and microbiota exchange, thus, indicating the possible dispersal of females between groups despite the geographical barriers (i.e., a mountain chain splitting the area into two sides - western and eastern; Fig. 1).

Anthropogenic disturbances are known to heavily impact wildlife populations in a plethora of forms, including changes in host microbiomes (Zhu et al., 2021). Disruptions in the gut microbiome composition have been demonstrated, including the domestication and ‘humanization’ of the wildlife gut microbiome (Dillard et al., 2022; Prabhu et al., 2020), and the shift in the microbiota community composition due to an increase in disease-associated taxa and a decrease of beneficial bacteria (Wasimuddin et al., 2022). On top of that, population bottlenecks lead to the loss of genetic variation, increased inbreeding and therefore, resulting in a less diverse microbiome. The constrained microbiome diversity must be the focus of discussion, alongside population size and genetic diversity, when dealing with threatened populations, as it may play a significant role in host fitness and adaptability (Ørsted et al., 2022). Species reintroductions/translocations represent one of the key effective strategies deployed towards the conservation of threatened species with reduced population sizes (Zhul et al., 2021). Despite the efforts made in implementing ex-situ programmes mimicking natural conditions, captive animals are often kept under various conditions that might greatly differ from their natural environments. In this context, investigating their wildlife microbiome is paramount to provide subsidies for comparisons with animals kept in captivity before the start of release programmes, especially considering the role of microbiota in nutrition uptaking and general host health.

Here, we have provided a characterisation of the gut microbiome of one the world’s most endangered primates, the Northern muriqui. No effect of geographic distance on the microbiota composition was detected, as high similarities for both alpha and beta diversities were recovered amongst the three groups inhabiting the Caparaó National Park. Host heterozygosity recovered from neutral nuclear markers (i.e., microsatellites) also did not seem to exert any influence on microbiota diversity. However, an association between microbiome composition and genetic distance was demonstrated. Therefore, the microbiome did not seem to be affected by the geographic distance but may be associated with genetic relatedness, indicating a possible exchange of individuals between groups due to female dispersal.

Considering the baseline microbiome data provided herein, further investigations should be carried out to more fully understand the change in microbiota putatively associated with the human encroachment that might disturb the host microbiome and consequently, lead to a decline in the population’s health status. In this context, the microbiome could then be used as an early warning of threats to muriqui, since negative changes in the microbiome composition might render these animals susceptible to diseases, facilitating co-infections and the spread of zoonotic diseases, ultimately jeopardising the species' survival (Wasimuddin et al., 2018).

ASV - Amplicon Sequence Variants

CNP - Caparaó National Park

VA - Vale do Aleixo

VFP - Vale do Facão de Pedra

VSM - Vale do Santa Marta

Acknowledgements

We acknowledge the support provided by the Caparaó National Park, and Claudio Novaes for the invaluable help in data collection.

Availability of data and materials

The datasets generated and analysed during this study are available in the Figshare repository, alongside RScripts and metadata. Doi: 10.6084/m9.figshare.22086218

Contributions

NGS and ADM conceptualised and designed the study. MCK collected the faecal samples and performed laboratory work concerning microsatellite genotyping. NGS performed the lab analyses concerning the microbiome. NGS processed the sequence data and performed the statistical analysis. SSB advised on the laboratory work and statistical analyses. NGS, ADM, and SIG wrote the original draft. All authors contributed to writing, reviewing and editing the text.

Ethics declaration

Ethics approval

Data collection was conducted with the permission of Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio/SISBIO No: 54795), and Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA)/ Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), and Department for Environment, Food & Rural Affairs (DEFRA, Authorization No: ITIMP17.1302). Under the Brazilian Genetic Heritage Management Council (Registration No: A5C63DC), Nagoya Protocol, all institutional animal care and use guidelines of Great Britain and Brazilian regulations, and the University of Salford ethical approval (STR1718-14).

Consent for publication

Not applicable

Competing interests

The authors declare no competing interests.

Funding

Not applicable

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Assessing the gut microbiome and the influence of host genetics on a critically endangered primate, the Northern muriqui (Brachyteles hypoxanthus)

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2.1 Field Sampling

2.2 Individual And Population Genetic Analyses

2.4 16S rRNA amplicon sequencing

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2.6 Alpha And Beta Diversity Analyses

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