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Wildlife gut microbiomes of sympatric generalist species respond differently to anthropogenic landscape disturbances

Wildlife gut microbiomes of sympatric generalist species respond differently to anthropogenic... Background Human encroachment into nature and the accompanying environmental changes are a big concern for wildlife biodiversity and health. While changes on the macroecological scale, i.e. species community and abun- dance pattern, are well documented, impacts on the microecological scale, such as the host’s microbial community, remain understudied. Particularly, it is unclear if impacts of anthropogenic landscape modification on wildlife gut microbiomes are species-specific. Of special interest are sympatric, generalist species, assumed to be more resilient to environmental changes and which often are well-known pathogen reservoirs and drivers of spill-over events. Here, we analyzed the gut microbiome of three such sympatric, generalist species, one rodent (Proechimys semispinosus) and two marsupials (Didelphis marsupialis and Philander opossum), captured in 28 study sites in four different land- scapes in Panama characterized by different degrees of anthropogenic disturbance. Results Our results show species-specific gut microbial responses to the same landscape disturbances. The gut microbiome of P. semispinosus was less diverse and more heterogeneous in landscapes with close contact with humans, where it contained bacterial taxa associated with humans, their domesticated animals, and potential pathogens. The gut microbiome of D. marsupialis showed similar patterns, but only in the most disturbed landscape. P. opossum, in contrast, showed little gut microbial changes, however, this species’ absence in the most fragmented landscapes indicates its sensitivity to long-term isolation. Conclusion These results demonstrate that wildlife gut microbiomes even in generalist species with a large eco- logical plasticity are impacted by human encroachment into nature, but differ in resilience which can have critical implications on conservation efforts and One Health strategies. Keywords Gut microbiome, Phylogenetics, Anthropogenic disturbance, Landscape ecology, Proechimys semispinosus, Didelphis marsupialis, Philander opossum, Panama *Correspondence: Alexander Christoph Heni alexander.heni@gmail.com Simone Sommer simone.sommer@uni-ulm.de Full list of author information is available at the end of the article © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. Heni et al. Animal Microbiome (2023) 5:22 Page 2 of 18 the gut microbiome of howler monkeys living in frag- Introduction mented areas or in captivity had a lowered bacterial In the Anthropocene, a plethora of challenges have diversity [19], with several follow-up studies confirming forced wildlife to cope with environmental changes, such these findings in different settings and for different spe - as habitat fragmentation and modification [1]. While spe - cies [e.g. 20, 21]. However, these studies were not able cies that are highly susceptible to changes in their envi- to differentiate between true landscape effects and the ronment are likely to disappear, species that are more effects of change in diet and other anthropogenic dis - resilient to environmental change increase in numbers turbances. Specifically, whether habitat fragmentation and will probably become more dominant in local species per se or the combination of habitat fragmentation with assemblages [2]. The breaking apart of natural habitat additional anthropogenic disturbances such as contact into patches can have negative effects on the abundance with humans, domesticated animals, and their pathogens of species and their health [3, 4]. These so-called gener - dominate these changes and disrupts natural gut micro- alist species often thrive in or at edges of altered land- biota homeostasis was so far studied only in the Tome’s scapes and have contact with the matrix surrounding spiny rat (Proechimys semispinosus) [17]. In this study, the habitat fragments, often leading to closer contact to spiny rats inhabiting isolated but otherwise undisturbed humans, livestock and domesticated animals [5]. As a rainforest fragments showed a similar gut microbial com- consequence of inhabiting a wide range of habitats, gen- position as conspecifics living in undisturbed continuous eralist species are often important pathogen reservoirs forests, indicating that habitat fragmentation per se is not and act as vectors of zoonotic diseases, despite appearing the driving factor behind changes in the gut microbiome. phenotypically healthy [4]. Increasing contact rates with However, in general, gut microbiomes were less diverse humans and domesticated animals, as well as the exploi- and at the same time, individual microbiomes were tation of wildlife for food or medicine, amplify the risk of more heterogeneous in spiny rats inhabiting fragmented spillover events in both directions [6]. However, assessing and disturbed landscapes, with differences driven by wildlife health of generalist species coping with anthro- microbes associated with humans and domesticated ani- pogenic disturbances can be challenging because of the mals. However, whether these results are restricted to problems posed in macroecological studies in assessing this species or a common feature of generalist species liv- the internal (health) states in wild animals. Even com- ing in sympatry and independent of phylogeny is largely mon fitness indicators, such as body mass can point unknown, but of high importance [22]. into wrong directions if land use change requires dietary In the present study, we analyzed the gut microbiomes shifts of the surviving, apparently adaptable resilient spe- of three sympatric, generalist, neotropical, mammalian cies [7]. species (two marsupials Didelphis marsupialis and Phi- The gut microbiome, the assemblage of microbes and lander opossum, which might be renamed Philander mel- their genomes inhabiting the gut of a host, is an integral anurus in the future [23], and one rodent P. semispinosus) part of an animal’s well-being and is considered as a good inhabiting four landscapes in central Panama with dif- indicator of host health [8, 9]. Gut microbial communi- fering degrees of anthropogenic disturbances: protected ties carry a wide range of important functions ranging continuous tropical forests, protected forested islands from food processing, access to nutrients, production of in the Panama Canal, nearby unprotected forested frag- antibiotics, to the influence on behavior and the immune ments embedded in an agricultural matrix and teak system [10], and thus can play a key role in host adap- plantations. The three study species represent abundant tation to rapidly changing environments [11]. Shifts in generalists living in rainforests with a high tolerance for bacterial diversity beyond the ‘normal’ range can result in habitat modifications [24, 25]. P. semispinosus is a strictly dysbiosis, i.e., the depletion of commensal microbes and terrestrial rodent that mainly feeds on fruits, seeds and increase in pathogenic ones [12]. Both can have negative mycorrhiza and occupies rather small home ranges, often consequences on host immunity and health. Recent stud- representing one of the most abundant mammalian spe- ies in humans and wildlife highlighted that gut homeo- cies within its geographic range [26, 27]. D. marsupialis is stasis as subject to disturbances by viral infections, a common terrestrial, omnivorous marsupial with a large facilitating co-infections and the spread of zoonotic dis- home range [28, 29] and P. opossum is a semi-arboreal eases [13–15]. Dysbiosis has been linked to environmen- marsupial with an omnivorous diet including fruits, ver- tal change, with further influencing factors being stress, tebrates, and invertebrates with a home range of 0.34 ha shifts in diet, and species assemblage on the macroeco- in Panama [29–31]. All three species represent important logical scale [13, 14, 16–18]. pathogen reservoirs and hosts for zoonotic diseases of Indeed, recent studies have emphasized the negative clinical relevance, caused by Trypanosoma [32], Hepa- effects of landscape modifications and habitat fragmenta - civirus [24], mammalian delta virus [33], Schaalia [34] tion on host gut microbiome homeostasis. For example, Heni  et al. Animal Microbiome (2023) 5:22 Page 3 of 18 and Venezuelan equine encephalitis virus [35]. P. semis- gut microbiomes were dominated by the bacterial fami- pinosus and D. marsupialis are known to be consumed by lies Lachnospiraceae, Bacteroidaceae and Acidaminococ- humans as a source of protein, making them particularly cacae. Considering less frequent bacterial families in D. interesting in terms of their potential roles in spillover marsupialis, Diplorickettsiaceae were mainly found in events [36, 37]. This highlights the importance of under - landscape C, while Ruminococcaceae were mainly pre- standing any potential health impacts anthropogenic sent in the landscapes I, A and P. Oscillospiraceae were disturbances may have on these species. With this study detected in landscape I, while Clostridiaceae were mainly design, we aimed to investigate (1) to what degree, if any, present in the disturbed landscapes A and P. Fusobacte- do host species identity (i.e., phylogeny) and landscape riaceae and Peptostreptococcaceae were mainly detected modifications shape the gut microbiomes of three sym - in landscape P. In P. opossum, the gut microbiomes of patric, generalist species; (2) to which extent do the host individuals trapped in landscape C were characterized species differ in their resilience, i.e. responses to differ - by the presence of Clostridia_UCG-014, Enterobacte- ent degrees of anthropogenic disturbances; and finally (3) riaceae and Morganellacea, while Peptostreptococcaceae which gut bacteria are involved in driving any changes, and Clostridiaceae were mainly found in the gut micro- and are they similar for all three host species? Gaining biome of individuals inhabiting landscape A and the a better understanding of the gut microbial response to presence of Prevotellaceae was characteristic for land- anthropogenic disturbances is of high importance in scape P. Muribaculaceae (formerly known as S24-7 [38]), maintaining wildlife health, especially in generalist spe- Lachnospiraceae and Erysipelotrichaceae were the domi- cies that can act as vectors transmitting diseases among nant bacterial families in the gut of P. semispinosus. The wildlife, but also livestock, domestic animals and ulti- gut microbial composition of P. semispinosus differed mately humans. between the landscapes C and I by the addition of Oscil- lospiraceae in landscape I. Rodents trapped in the land- Results scapes A and P both lacked Clostridia_UCG-014 but Species community and abundance pattern harbored Gastranaerophilales instead (Fig. 1). During three field seasons, 1523 animals of 16 different species were captured in 28 study sites distributed across Gut bacterial composition is shaped by both host four landscapes (protected continuous tropical forests phylogeny and landscape type (=C), protected forested islands in the Panama Canal We first investigated if species identity and/or landscape (=I), nearby unprotected forested fragments embed- type shaped gut microbial beta diversity (both composi- ded in an agricultural matrix (=A) and teak plantations tion and dispersion) across all three sympatric species. (=P)) differing in degree of anthropogenic disturbance Using one model with host species identity and land- in Panama (Additional file  1: Figs. S1 and S2). The three scape type as fixed factors per distance matrix (weighted most common animals captured were P. semispino- and unweighted UniFrac distances), both species iden- sus (n = 1235), D. marsupialis (n = 137) and P. opossum tity (PERMANOVA: weighted Unifrac: df = 2, R = 0.23, (n = 72). P. semispinosus and D. marsupialis were cap- p ≤ 0.001; unweighted UniFrac: df = 2, R = 0.21, tured in all four landscapes, while P. opossum was absent p ≤ 0.001) and landscape type had significant effects on on landscape I. Fecal samples from 397 P. semispinosus, gut microbial composition (PERMANOVA: weighted 104 D. marsupialis, and 68 P. opossum were available for Unifrac: df = 3, R = 0.02, p ≤ 0.001; unweighted UniFrac: microbiome investigation (Additional file 2: Table S1). df = 3, R = 0.02, p ≤ 0.001; Fig.  2a, b). Based on effect sizes (Cohen’s d), the effect of phylogeny was larger than Gut bacterial composition of the three generalist species the effect of landscape type (range based on weighted After sequencing the 16S rRNA gene from fecal matter UniFrac distances: host phylogeny: 1.04–7.06, landscape: and rarefication a total of 6404 different bacterial ASVs 0–0.76; range based on unweighted UniFrac distances: were identified in the 569 samples kept after quality fil - host phylogeny: 2.82–6.19, landscape: 0.33–1.34; Fig.  2c, tering (Additional files 1 and 2: Fig. S3 and Table S1). The d). Moreover, pairwise comparisons of each host spe- two marsupial species, P. opossum and D. marsupials, cies pair showed the smallest differences in gut microbial had 1454 ASVs in common, whilst the ground-dwelling composition between both marsupials, and larger differ - species D. marsupialis and P. semispinosus shared 445 ences between either marsupial and the rodent (Fig.  2c, ASVs, and the microbiome of P. opossum and P. semis- d). The effect size for pairwise comparisons of landscape pinosus overlapped in only 252 ASVs (Additional file  1: type showed that each landscape was distinct from one Fig. S4). The two opossum species shared more dominant another, except for the comparison between the dis- bacterial families with each other than with the rodent turbed landscapes A and P using weighted UniFrac dis- species, P. semispinosus (Fig.  1). In the marsupials, the tances (Fig. 2c). In addition to the bacterial composition, Heni et al. Animal Microbiome (2023) 5:22 Page 4 of 18 Fig. 1 Gut bacterial composition (at the family level) of the two marsupials (D. marsupialis, P. opossum) and the spiny rat (P. semispinosus). Details on the landscapes C, I, A and P are provided in the methods and their locations are shown in Additional file 1: Fig. S1. Note that P. opossum was not captured in landscape I gut microbial dispersion was also significantly affected effect of landscape type on gut microbial composition by both host species identity (weighted UniFrac: df = 2, and dispersion (PERMANOVA: df = 3, R = 0.04, p = 0.1; F value = 174.93, p ≤ 0.001; unweighted UniFrac: df = 2, F PERMDISP: df = 3, F value = 0.43, p = 0.74, Fig. 4). How- value = 122.47, p ≤ 0.001, Fig.  2a, b) and landscape type ever, using unweighted UniFrac distances, gut microbial (weighted UniFrac: df = 3, F value = 29.62, p ≤ 0.001; composition (but not dispersion; PERMDISP: df = 3, F unweighted UniFrac: df = 2, F value = 33.38, p ≤ 0.001). value = 1.22, p = 0.30) was significantly affected by land - scape type (PERMANOVA: df = 3, R = 0.04, p ≤ 0.01, Species‑specific effects of landscape type on gut microbial Fig.  4) with plantations (landscape P) clearly differing alpha and beta diversity of sympatric generalist species from the other three landscapes C, I and A based on pair- To determine if landscape type had similar effects on wise comparisons (Additional file 2: Table S2). gut microbial alpha and beta diversity across three dif- In the second, partially arboreal, marsupial species P. ferent, yet sympatric species, we analyzed the effect of opossum that was never captured on landscape I, land- landscape type on gut microbial alpha diversity, com- scape type did not have a significant effect on Faith’s position, and dispersion for each species separately. In PD (Additional file  2: Table  S3, Fig.  3) or on gut bacte- the ground-dwelling marsupial D. marsupialis, all alpha rial community dispersion (PERMDISP: weighted Uni- diversity metrics were significantly impacted by land - Frac: df = 2, F value = 0.16, p = 0.21; unweighted UniFrac: scape type (Additional file  2: Table  S2), with individu- df = 2, F value = 2.72, p = 0.07). It did, however, signifi - als inhabiting landscape P having a significantly lower cantly affect gut microbial composition with regards to gut microbial alpha diversity than those living in the unweighted UniFrac distances (PERMANOVA: df = 2, other three landscape types (Additional file  2: Table  S2, R = 0.04, p ≤ 0.01, Fig.  4), with all landscapes differing depicted for Faith’s PD, Fig.  3). Beta diversity based on from one another based on post-hoc pairwise compari- weighted UniFrac distances did not show a significant sons, but not with regards to weighted UniFrac distances Heni  et al. Animal Microbiome (2023) 5:22 Page 5 of 18 Fig. 2 Differences in beta diversity between three sympatric generalist species, the marsupials D. marsupialis (Dm, green), P. opossum (Po, orange), and the rodent P. semispinosus (Ps, blue). The top row shows NMDS plots of a weighted and b unweighted UniFrac distances. The bottom row c, d displays corresponding forest plots with Cohen’s d effect sizes highlighting the phylogenetic signal and landscape effects, i.e. the different levels of anthropogenic disturbance. Details on the landscapes C, I, A and P are provided in the methods and their locations are shown in Additional file 1: Fig. S1 (PERMANOVA: df = 2, R = 0.04, p = 0.21; Fig.  4, Addi- file  2: Table  S4), with a clear separation between pro- tional file 2: Table S3). tected (landscapes C and I, without contact to humans, In the ground-dwelling, rodent species P. semispino- livestock and domestic animals) and unprotected (land- sus, landscape type had a significant effect on Faith’s scapes A and P, with contact to humans, livestock and PD (Additional file  2: Table  S4, Fig.  3) and pairwise domestic animals) landscape types (Fig. 4). Thus, the gut comparisons showed that each landscape type sig- microbiomes of generalists are affected by anthropogenic nificantly differed from one another, except for the two disturbances, but sympatric species show species-specific protected landscapes C and I as well as the two unpro- differences in their responses. tected landscapes A and P (Additional file  2: Table  S4, Fig.  3). Similarly, gut microbial beta diversity (compo- sition and dispersion) was significantly impacted by Landscape‑driven species‑specific taxonomic differences landscape type, regardless of distance metric (weighted in gut microbial beta diversity UniFrac: PERMANOVA: df = 3, R = 0.07, p ≤ 0.001; To gain a better understanding of which bacterial taxa PERMDISP: df = 3, F value = 13.21, p ≤ 0.001, pair wise are driving the differences in beta diversity between land - post-hoc test Additional file  2: Table  S4; unweighted scape types within each host species, we ran three differ - UniFrac: PERMANOVA: df = 3, R = 0.05, p ≤ 0.001; ent differential abundance analyses, one for each species, PERMDISP: df = 3, F value = 7.17, p ≤ 0.001, Additional Heni et al. Animal Microbiome (2023) 5:22 Page 6 of 18 Fig. 3 Landscape effects on alpha diversity (measured as Faith´s PD) of three sympatric generalist species, the marsupials D. marsupialis and P. opossum, and the spiny rat P. semispinosus. Individuals were trapped in protected continuous tropical forests (landscape C, green); protected forested islands in the Panama Canal (landscape I, blue); in the nearby unprotected forested fragments embedded in an agricultural matrix (landscape A, yellow) and in teak plantations (landscape P, red) using ANCOM [39]. Because this is a pairwise test, we hypothesis-driven assumption, comparing the two dis- grouped together individuals from landscape types that turbed landscapes against the protected control (landscape did not significantly differ in the aforementioned beta C). In doing so, we detected 24 differentially abundant diversity analyses, i.e., showed similar responses to land- ASVs from the bacterial classes Alphaproteobacteria, Bac- scape effects on beta diversity. teroida, Clostridia, Coriobacteriia and Vampirivibrionia First, for D. marsupialis, we compared gut microbiomes (Fig.  6). Lastly, for P. semispinosus, we compared the gut from individuals inhabiting landscapes C + I + A against microbial compositions of rodents inhabiting the pro- P and identified 27 differentially abundant ASVs from the tected landscapes C and I to those living in the unprotected bacterial classes Alphaproteobacteria, Bacilli, Bacteroida, landscapes A and P and found 481 differentially abundant Clostridia, and Gammaproteobacteria (Fig.  5). Second, ASVs from the bacterial classes Actinobacteria, Alphapro- for P. opossum, we compared the gut microbial communi- teobacteria, Bacilli, Bacteroida, Clostridia, Coriobacteriia, ties of individuals living in the control landscape C against Elusimicrobia, Gammaproteobacteria, Negativicutes, Spi- those from the disturbed landscapes A and P (this spe- rochaetia, Vampirivibrionia, and Verrucomicrobiae (Figs. 7 cies was not captured on landscape I). Because no clear and 8). separation of the microbial alpha- or beta-diversity based Among the ASVs identified were representatives, on landscape type was observed, we decided to use our such as Chrisensenellaceae R-7 group (D. marsupialis), (See figure on next page.) Fig. 4 NMDS plots visualizing landscape effects on beta diversity. Beta diversity is measured by a weighted and b unweighted UniFrac distances in the three sympatric generalist species, the marsupials D. marsupialis (top) and P. opossum (middle), and the spiny rat P. semispinosus (bottom). Distances to the group centroids are depicted in the inserted graphs in the top right corners and ellipses indicate 95% confident intervals. Individuals were trapped in protected continuous tropical forests (landscape C, green); protected forested islands in the Panama Canal (landscape I, blue); in the nearby unprotected forested fragments embedded in an agricultural matrix (landscape A, yellow) and in teak plantations (landscape P, red) Heni  et al. Animal Microbiome (2023) 5:22 Page 7 of 18 Fig. 4 (See legend on previous page.) Heni et al. Animal Microbiome (2023) 5:22 Page 8 of 18 Fig. 5 Differentially abundant ASVs (using ANCOM) in pairwise comparisons with landscape groupings based on similar responses in beta diversity to landscape modifications (Fig. 4) in D. marsupialis comparing landscape C + I + A against P. Colors represent the different bacterial classes. a Differential abundant ASVs according to the taxonomical assignment; b Volcano plot of differential abundant ASVs, depicting the F statistics and W-value Heni  et al. Animal Microbiome (2023) 5:22 Page 9 of 18 Fig. 6 Differentially abundant ASVs (using ANCOM) in pairwise comparisons with landscape groupings based on similar responses in beta diversity to landscape modifications (Fig. 4) in P. opossum comparing landscape C against A + P. Colors represent the different bacterial classes. a Differential abundant ASVs according to the taxonomical assignment; b Volcano plot of differential abundant ASVs, depicting the F statistics and W-value Heni et al. Animal Microbiome (2023) 5:22 Page 10 of 18 Fig. 7 First half of differentially abundant ASVs (using ANCOM) in pairwise comparisons with landscape groupings based on similar responses in beta diversity to landscape modifications (Fig. 4) in P. semispinosus comparing landscape C + I against A + P. Results split into two graphs. Colors represent the different bacterial classes. a Differential abundant ASVs according to the taxonomical assignment; b Volcano plot of differential abundant ASVs, depicting the F statistics and W-value Heni  et al. Animal Microbiome (2023) 5:22 Page 11 of 18 Fig. 8 Second half of differentially abundant ASVs (using ANCOM) in pairwise comparisons with landscape groupings based on similar responses in beta diversity to landscape modifications (Fig. 4) in P. semispinosus comparing landscape C + I against A + P. Results split into two graphs. Colors represent the different bacterial classes. a Differential abundant ASVs according to the taxonomical assignment; b Volcano plot of differential abundant ASVs, depicting the F statistics and W-value Heni et al. Animal Microbiome (2023) 5:22 Page 12 of 18 Chlostridium senu stricto I (D. marsupialis), Rikenella (D. disturbances each responded differently with regards to marsupialis), Vagococcus (D. marsupialis), Butyricoccus gut microbial diversity and that the gut microbiome of (P. opossum), Coprococcus (P. opossum), Peptococcus (P. sympatric species is determined by both phylogeny and opossum), Rikenella (P. opossum), Bacteroides (P. semispi- landscape. We observed species-specific gut microbial nosus), Allobaculum (P. semispinosus) and Dubsosiella (P. responses to different landscape types, with P. semis - semispinosus). pinosus showing the highest sensitivity to proximity to humans. In D. marsupials, however, only the landscape Discussion with a combination of human contact, fragmentation, Impact of habitat change on species with high ecological and complete changes in forest type (from lowland tropi- plasticity cal rainforest to teak plantation) led to changes in the gut In the Anthropocene, the selection pressures faced by microbiome. In contrast, P. opossum’s gut microbiome species worldwide have changed to favor species pos- showed the highest resilience, without a distinct pattern sessing ecological plasticity, with a higher tolerance to of change in the gut microbial alpha diversity or beta dis- anthropogenically modified environments [40], the so- persion. These species-specific responses were mirrored called generalist species [41]. Failure to adapt can espe- in our differential abundance analyses that showed the cially impact animals with narrow ecological niches, highest number of differentially abundant ASVs in P. sem - leading to changes in the composition of animal com- ispinosus versus the two other species. The gut microbi - munities [42]. Increases in the abundance of generalists omes of our three analyzed species were affected by both in disturbed landscapes at the cost of the decline of less species identity and landscape type, which is supported resilient species can be accompanied by negative conse- by other studies [49, 50]. quences for the ecosystem and increase the risk of disease Species identity can influence the gut microbiome not spread and spillover [43]. As anthropogenic selection only because of species-specific genetic constitutions, pressures will affect these pathogen reservoirs and dis - but also because species identity determines suitable ease vectors best adapted to living in close proximity to environment, food preferences and processing potential, human settlements, studies on generalists’ role in emerg- pathogen resistance, as well as adaptive potential [51]. ing infectious diseases from wildlife and their adaptabil- Similarly, landscape types can differ in food availability ity to global environmental changes are key in order to as well as exposure to pathogens, pesticides, and differ - understand the threat they are under and the threat they ent plant and animal communities. The gut microbiomes may pose [4, 44]. In fact, deforestation is considered one of the two opossum species were more similar to one of the main drivers of zoonotic diseases [45], yet, current another than they were to the spiny rat. A similar trend reforestation programs often rely on a few tree species or was shown in large African mammals, where gut micro- even monocultures, such as eucalyptus or teak planta- bial composition was closely correlated with phylogeny tions, which might accelerate the risk [46]. [52], as did the gut microbiome in some primates [53]. While some studies show the effect of species identity and environment on several species’ gut microbiomes, Phylogeny and landscape influence the microbiome [22, 49], they are often limited to extreme environmental of sympatric species situations [22, 54], thus only comparing extremely con- In central Panama, we investigated four landscapes dif- trasting conditions for the animals. However, landscape fering in their degree of anthropogenic disturbance which plays a large role in shaping the microbial community have been shown to have severe impacts on different lev - in humans and apes [55], and habitat fragmentation can els of diversity: species assemblages and abundance pat- have an influence on the gut microbiome through dietary terns [24, 42, 47], pathogen diversity and host infections changes [56]. Similar results have been discovered in dif- [18, 25, 48], neutral and adaptive genetic diversity [18, 25] ferent howler monkey species, where host species was a along with gut microbial community patterns [17, 18] dif- key predictor of the gut microbiota, but forest type, habi- fered according to landscape type. As a crucial factor in tat, and season explained species-specific variances [57]. host health, the gut microbiome has been put forward as a potentially vital component in helping wildlife to adapt Only extreme habitat perturbation changes D. marsupialis to fast-paced global changes [11]. However, whether this gut microbiomes holds true for a wider range of species facing the same Analyzing the three species separately showed that degrees of anthropogenic disturbance was the focus of changes in gut microbial composition in D. marsu- the present study. pialis occurred only in individuals inhabiting the most Here, we showed that three sympatric, generalist spe- disturbed landscape, namely teak plantations. Teak cies faced with the same landscape-level anthropogenic Heni  et al. Animal Microbiome (2023) 5:22 Page 13 of 18 plantations are defined by a different forest type in addi - driven by bacterial taxa associated with humans and tion to being fragmented and embedded in a matrix with domesticated animals, as well as increased dispersion of human contact. Because they are monocultures, teak the bacterial community in individuals from fragments plantations can alter the food availability of the inhabit- surrounded by agriculture [17]. All these features were ing animals and provide a harsher environment, e.g. due not detected in individuals sampled in continuous for- to increased risk of forest fires [58]. Additionally, the con - ests or protected forested islands [17]. While the impact version of natural habitats to teak plantations exposes of protected landscape types with no human contact animal communities to changes in microbial soil com- (continuous forests and islands) versus fragmented land- position [59]. D. marsupialis individuals living in these scapes with human contact (forest fragments embedded plantations either need to adapt to these changes and the in an agricultural matrix) on P. semispinosus gut micro- potential stress associated with them or use the planta- biomes have been discussed elsewhere [17], the apparent tions as a corridor for travel. similar behavior of the gut microbiome from individuals living in teak plantation to those inhabiting forest frag- High resilience of P. opossum gut microbiomes ments is noteworthy. Contrarily to forested fragments, to anthropogenic changes teak plantations also differ in the natural assembly of The second marsupial, P. opossum, however, showed a trees, with the dominant species being the from Asia different gut microbial response. Despite only occur - introduced teak tree (Tectona grandis). The gut micro - ring in three of the four sampled landscapes, P. opos- biome of D. marsupialis was only impacted in this land- sum individuals showed little change in gut microbial scape type, which we consider to be the most extreme composition with no clear patterns across the different landscape type, and therefore, we expected an additional landscape types. Changes in gut microbial composition impact on the P. semispinosus gut microbiome on top of between individuals inhabiting all three landscapes were the changes caused by the forest fragments. However, the only observed when using unweighted UniFrac distances, lack of a compounded impact could mean two things: (1) indicating that rare ASVs are likely responsible for these individuals from fragmented forests already display the changes. As a semi-arboreal habitat generalist, P. opos- most extreme gut microbial perturbation tolerable by this sum individuals could escape bacterial taxa introduced species, or (2) teak plantations provide a suitable forest by humans and livestock to soils. This could explain the habitat for P. semispinosus, despite being monocultures weakened gut microbial response compared to the more and lacking trees typical for rainforests. It also indicates closely-related D. marsupialis. Further risk of coming that the presence of humans and domesticated animals into contact with microbes from humans or domesti- in the matrix alone shapes the microbiome, and not frag- cated animals is reduced because part of P. opossum’s mentation or forest tree composition per se. diet consists of insects [60], meaning this host might be less exposed to bacteria in the ground or associated with Human‑vicinity‑associated ASVs drive gut microbial plants compared to, say, herbivorous hosts. The micro - changes biomes of animals and their environment are linked and Differential abundance analysis revealed a large differ - shape each other in both directions [61, 62]. Still, the fact ence in the number of ASVs determined to be differently that prolonged isolation and fragmentation possibly lead abundant between the landscapes when considering each to local extinction (as seen by their absence on islands) of the three species separately. While for the two opos- could indicate that P. opossum is not insensitive to land- sum species only a handful of differentially abundant scape changes. Because islands provide the harshest bacterial taxa were detected, many were discovered for P. matrix based on accessibility and usability as a corridor semispinosus. In general, detected bacteria often showed for movement, their extinction on islands could be due similarity to ones characterized in more detail in human to a past bottleneck event. However, there are interest- or domesticated animal microbiomes (e.g. Allobaculum ing dynamics of opossum species in the Panama Canal [64]). Most of the detected ASVs have already been dis- area with local disappearance as well as re-colonization cussed [17], theorizing that a large portion of the identi- of some small islands close to the mainland, thus opening fied bacteria could have been introduced by humans and the possibility for re-colonization [63]. their domesticated animals. In addition, in D. marsupia- lis, we detected ASVs assigned to the genus Vagococcus, Large impact of human vicinity on P. semispinosus gut which was first isolated from chicken feces [65], animals microbiomes that D. marsupials are known to get into close contact The gut microbiome of the common P. semispinosus is with because they prey on their eggs [36]. Landscapes A very sensitive to human contact, as was shown by the and P are in close vicinity to human settlements, there- reduced microbial diversity and shifts in composition, fore uptake of these human-driven taxa into their gut Heni et al. Animal Microbiome (2023) 5:22 Page 14 of 18 microbiomes is not unexpected and could cause harm to Material and methods the host by changing gut microbial composition. Study area and sampling This study was carried out in the Panama Canal area, Potential consequences of microbiome changes induced Panama. Animals were captured in 28 study sites grouped by anthropogenic landscape disturbance into four different landscapes based on their degree of D. marsupialis is known to be consumed by humans, anthropogenic disturbance (Additional file  1: Fig. S1, both for nutritional and cultural reasons [36]. Thus, not map created with ggmap [73]): (1) continuous rainforest only proximity, but also direct contact with humans can (=C, five capture sites), i.e., undisturbed and protected be an important pathway for pathogen transmission, and lowland tropical rainforest within the Barro Colorado a perturbed microbiome might have negative effects on Nature Monument; (2) forested islands (=I, six capture host immunity, given the microbiome’s interplay and sites) situated in the Gatún Lake and also protected by crosstalk with the host immune system [66]. Altered the Barro Colorado Nature Monument, i.e., fragmented microbial communities can facilitate pathogen infection but otherwise undisturbed landscape; (3) fragmented and [48] and vice versa pathogen infection can change the disturbed (i.e. contact to humans and domesticated ani- microbiome [13–15]. These perturbed microbiomes fur - mals) tropical lowland rainforest embedded in an agricul- ther increase the risk of horizontal gene transfer which tural matrix (=A, nine capture sites); and (4) fragmented could lead to pathogenic bacteria [67]. Close contact and disturbed teak plantations (=P, seven capture sites) between humans and domesticated animals can be dan- planted by humans and mainly consisting of Tectona gerous for wildlife and humans, as demonstrated with the grandis. spillover of Nipah virus, which made the jump from fly - Field work took place during three field seasons (Octo - ing foxes to humans through pigs as an intermediate host ber 2013 to May 2014, October 2014 to May 2015 and [68, 69]. Because land-use change can cause pandem- September 2016 to April 2017, alternating the order of ics and the emergence of new diseases [70] and because capture sites between seasons). At each capture site a rodents and marsupials represent a significant zoonotic trapping grid consisting of 100 stations was set up. Each disease risk in the future [71], these findings become station was separated by 20 m and consisted of three live even more important regarding the potential for the traps [one Tomahawk trap (size: 15.2 × 15.2 × 48.3  cm, origins and emergence of zoonotic diseases, and future www. livet rap. com) and two Sherman traps (size: studies will reveal how these microbiome changes impact 10.2 × 11.4 × 38.1  cm, www. sherm antra ps. com)], one of animal’s fitness in detail. Moreover, the loss of microbial which was placed above ground, if possible, i.e., on trees, diversity has been recognized as a potential threat to the lianas or similar, if available, to include arboreal species. discovery of new drugs or therapeutics in the field of Traps were opened at dusk and baited with a mixture of microbial biotechnology [72]. peanut butter, oatmeal, bird seeds, banana, and dog food to attract species with various dietary preferences and controlled at dawn of the next day. Then, captured ani - Conclusion mals were measured, individually marked to recognize Overall, we could show that the gut microbiomes of recaptures, and fecal samples were taken from animals sympatric species inhabiting landscapes with differ - during sampling. Afterwards, the animals were released ing degrees of anthropogenic disturbance are mainly at the capturing location (further details see [24]). Fecal shaped by host species identity, with landscape type play- samples were stored in collection tubes containing RNAl- ing a smaller but significant role. Interestingly, there is ater at − 20 °C until DNA extraction. a species-specific gut microbial response to landscape type, indicating that findings from one species cannot always be generalized to other species, even not to those DNA extraction, 16S rRNA gene amplification living in the same habitat or to those that are closely and sequencing related. This shows that these generalists’ gut microbi - A detailed summary of sample processing is described omes are sensitive to landscape-level changes, a fact not elsewhere [17]. In brief, we extracted DNA from fecal detected by biodiversity monitoring of vertebrates, and samples from a total of 793 samples (including extrac- that these changes are not uniform across host species. tion blanks and PCR controls) using NucleoSpin Soil- u Th s, even for generalists, environmental changes can Extraction Kit from Macherey–Nagel (Germany). The pose a big impact, which is an important finding as this final elution step was performed twice with 50 µl of elu - might directly cause consequences and the risk of emerg- tion buffer each time, resulting in a total volume of 100 µl. ing zoonoses not only for wildlife health, but also for the Following extraction, we amplified the 291 nucleotide- health of domesticated animals intended for human con- long V4 region of the 16S rRNA gene using the 515 F and sumption, and for humans themselves. 806 R primers [74, 75] applying a two-step polymerase Heni  et al. Animal Microbiome (2023) 5:22 Page 15 of 18 chain reaction (PCR). The first step was an initial dena - extracting the results from the PERMANOVA of the first turation of 600 s at 95 °C followed by 30 cycles with 95 °C two NMDS axes. for 30 s, 60° for 30 s and 72 °C for 45 s, followed by a final Second, to determine if the gut microbiome in each of elongation of 72  °C for 600  s. The second step consisted the three host species is similarly impacted by landscape of ten cycles for the barcoding with the same conditions type, we subset our data for each species. Both alpha as described above. The samples were sequenced on six diversity (observed number of ASVs, Shannon Diversity runs on an Illumina MiSeq at our Institute of Evolution- and Faith’s phylogenetic diversity, PD) and beta diversity ary Ecology and Conservation Genomics, Ulm Univer- metrics (weighted and unweighted UniFrac distances) sity, Germany. were calculated. For alpha diversity, we constructed gen- eralized linear models (GLMs) with landscape, season, and sex as factors explaining the alpha diversity indices Data processing and afterwards used contrasts to analyze pairwise com- Reads from all six Illumina runs were analyzed in QIIME parisons. For beta diversity, we applied PERMANOVAs 2 (Version 2020.6, August 2020) [76] with a total of and PERMDISPs as described above, followed by post- 14,489,625 sequences. DADA2 [77] was used to pro- hoc pairwise comparisons calculated for each landscape. cess the sequences and assemble these into amplicon Finally, to investigate which taxa were driving the dif- sequence variants (ASVs) and SILVA (version 1.38) [78] ferences in beta diversity, we performed differential was used as a taxonomic reference database. We removed abundance analyses using ANCOM (Analysis of Compo- a total of 194,432 sequences (roughly 0.83%) annotated sition of Microbiomes) [39] which allows two-level fac- as Archaea, mitochondria and chloroplast. Data were tor comparisons [17]. We chose a w of 0.7 as originally transferred into a phyloseq object [79] within the R envi- 0 described in [39]. Based on the results of the species-spe- ronment (version 4.0.2) [80] for further analyses. ASVs cific landscape effects on beta diversity (see Results), we identified in the blanks and controls (a total of 55,463 compared the landscapes C + I + A versus P for D. mar- ASVs, equivalent to 0.38%) were removed from samples supials, C versus A + P for P. opossum and C + I versus to avoid false results. We applied an additional filter to A + P for P. semispinosus for our two-level factor compar- remove rare ASVs with fewer than 50 reads across the isons. All graphs were plotted in the R environment using entire dataset and which occurred in only 2% of all the the ggplot2 package [85]. samples. Finally, we rarefied the data in order to control for uneven sequencing depth. Rarefaction was performed Supplementary Information using the rarefy_even_depth function from the phyloseq The online version contains supplementary material available at https:// doi. package and a sequencing depth of 10,000 reads was org/ 10. 1186/ s42523- 023- 00237-9. chosen based on rarefaction curves (Additional file  1: Fig. S3). After performing all the bioinformatic quality Additional file 1: Fig. S1. Location of the study area and 28 capture sites filtering steps at rarefaction, 569 samples (P. semispino - distributed across four landscapes differing in their anthropogenic impact in central Panama. Capture sites in the protected continuous tropical sus: n = 397 individuals; D. marsupialis: n = 104 individu- forests (landscape C) are marked in green; sites in the protected forested als; P. opossum: n = 68) remained for subsequent analysis islands in the Panama Canal (landscape I) are marked in blue; sites in the (Additional file 2: Table S1). nearby unprotected forested fragments embedded in an agricultural matrix (landscape A) are marked in yellow; and sites in teak plantations (landscape P) are marked in red. Map created with the R package ggmap Statistical analyses (Kahle and Wickham, 2013) with the origin of the map material being Google Maps. Fig. S2. Distribution of the captured species across the four Statistical analyses were separated into two parts based landscapes. Details on the landscapes C, I, A and P are provided in the on the study questions. First, to determine if phylogeny methods and their locations are shown in Additional file 1: Fig. S1. Fig. and/or landscape affect the gut microbial beta diversity S3. Rarefaction curves showing the number of detected ASVs in relation to 16S rRNA gene sequencing depth (i.e. total number of reads obtained in the three species, we used the whole dataset, consist- per individual after quality filtering) for Didelphis marsupialis (turquoise), ing of all three species and all four landscapes. Using Philander opossum (orange) and Proechimys semispinosus (light-blue). The weighted and unweighted UniFrac distances [81], we maximum diversity is reached at around 10,000 reads (vertical line). Fig. S4. Shared ASVs between Didelphis marsupialis (turquoise), Philander opos- tested for differences in gut microbial composition and sum (orange) and Proechimys semispinosus (light-blue). homogeneity according to landscape and host species Additional file 2: Table S1. Number of samples per species and using PERMANOVA (Permutational Analysis of Vari- landscape in the final dataset. Details on the landscapes C, I, A and P are ance, with 9999 permutations) and PERMDISP2 (Per- provided in the methods and their locations are shown in Additional file 1: mutational Analysis of Multivariate Dispersions) [82] Fig. S1. Table S2. Eec ff ts of landscape type on the gut bacterial diversity of D. marsupialis. Results from generalized linear models indicating the using the vegan package [83]. These tests were followed effects of landscape type, field season and sex on alpha diversity using a by post-hoc pairwise comparisons. Effect sizes (Cohen’s Faith’s PD; b Number of ASVs and c Shannon diversity. Results from pair- d) [84] for pairwise comparisons were calculated by wise comparisons (Contrasts) of landscapes using d Faith’s PD; e Number Heni et al. Animal Microbiome (2023) 5:22 Page 16 of 18 Author details of ASVs and f Shannon diversity. g Results from PERMANOVA for pairwise 1 Institute of Evolutionary Ecology and Conservation Genomics, Ulm University, comparisons of landscapes on beta diversity (weighted and unweighted 2 89081 Ulm, Germany. Smithsonian Tropical Research Institute, Balboa, Ancón, UniFrac). SE Standard error; df Degrees of freedom. Table S3. Eec ff ts of 3 Republic of Panama. Institute of Virology, Campus Charité Mitte, Charité landscape type on the gut bacterial diversity of P. opossum. Results from - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, generalized linear models indicating the effects of landscape type, field Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117 Berlin, season and sex on alpha diversity using a Faith’s PD; b Number of ASVs Germany. and c Shannon diversity. 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Sci Rep. 2019;9:13410. Availability of data and materials 15. Schmid DW, Fackelmann G, Wasimuddin, Rakotondranary J, Ratovona- The datasets generated and/or analyzed during the current study will be mana YR, Montero BK, et al. A framework for testing the impact of co- made available in upon acceptance. infections on host gut microbiomes. Anim Microbiome. 2022;4:48. 16. Ingala MR, Becker DJ, Holm JB, Kristiansen K, Simmons NB. Habitat frag- mentation is associated with dietary shifts and microbiota variability in Declarations common vampire bats. Ecol Evol. 2019;9(11):6508–23. 17. Fackelmann G, Gillingham MAF, Schmid J, Heni AC, Wilhelm K, Schwen- Ethics approval and consent to participate sow N, et al. Human encroachment into wildlife gut microbiomes. Com- Ethical approval was provided by the Smithsonian IACUC protocol 2013-0401- mun Biol. 2021;4:1–11. 2016-A1-A7 and 2016-0627-2019-A1-A2 and the exportation of the samples 18. 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Statistical power analysis for the behavioral sciences. 2nd ed. New York: Psychology Press; 2009. 85. Wickham H. ggplot2. New York, NY: Springer, New York; 2009. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in pub- lished maps and institutional affiliations. Re Read ady y to to submit y submit your our re researc search h ? Choose BMC and benefit fr ? Choose BMC and benefit from om: : fast, convenient online submission thorough peer review by experienced researchers in your field rapid publication on acceptance support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations maximum visibility for your research: over 100M website views per year At BMC, research is always in progress. Learn more biomedcentral.com/submissions http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Animal Microbiome Springer Journals

Wildlife gut microbiomes of sympatric generalist species respond differently to anthropogenic landscape disturbances

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Abstract

Background Human encroachment into nature and the accompanying environmental changes are a big concern for wildlife biodiversity and health. While changes on the macroecological scale, i.e. species community and abun- dance pattern, are well documented, impacts on the microecological scale, such as the host’s microbial community, remain understudied. Particularly, it is unclear if impacts of anthropogenic landscape modification on wildlife gut microbiomes are species-specific. Of special interest are sympatric, generalist species, assumed to be more resilient to environmental changes and which often are well-known pathogen reservoirs and drivers of spill-over events. Here, we analyzed the gut microbiome of three such sympatric, generalist species, one rodent (Proechimys semispinosus) and two marsupials (Didelphis marsupialis and Philander opossum), captured in 28 study sites in four different land- scapes in Panama characterized by different degrees of anthropogenic disturbance. Results Our results show species-specific gut microbial responses to the same landscape disturbances. The gut microbiome of P. semispinosus was less diverse and more heterogeneous in landscapes with close contact with humans, where it contained bacterial taxa associated with humans, their domesticated animals, and potential pathogens. The gut microbiome of D. marsupialis showed similar patterns, but only in the most disturbed landscape. P. opossum, in contrast, showed little gut microbial changes, however, this species’ absence in the most fragmented landscapes indicates its sensitivity to long-term isolation. Conclusion These results demonstrate that wildlife gut microbiomes even in generalist species with a large eco- logical plasticity are impacted by human encroachment into nature, but differ in resilience which can have critical implications on conservation efforts and One Health strategies. Keywords Gut microbiome, Phylogenetics, Anthropogenic disturbance, Landscape ecology, Proechimys semispinosus, Didelphis marsupialis, Philander opossum, Panama *Correspondence: Alexander Christoph Heni alexander.heni@gmail.com Simone Sommer simone.sommer@uni-ulm.de Full list of author information is available at the end of the article © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. Heni et al. Animal Microbiome (2023) 5:22 Page 2 of 18 the gut microbiome of howler monkeys living in frag- Introduction mented areas or in captivity had a lowered bacterial In the Anthropocene, a plethora of challenges have diversity [19], with several follow-up studies confirming forced wildlife to cope with environmental changes, such these findings in different settings and for different spe - as habitat fragmentation and modification [1]. While spe - cies [e.g. 20, 21]. However, these studies were not able cies that are highly susceptible to changes in their envi- to differentiate between true landscape effects and the ronment are likely to disappear, species that are more effects of change in diet and other anthropogenic dis - resilient to environmental change increase in numbers turbances. Specifically, whether habitat fragmentation and will probably become more dominant in local species per se or the combination of habitat fragmentation with assemblages [2]. The breaking apart of natural habitat additional anthropogenic disturbances such as contact into patches can have negative effects on the abundance with humans, domesticated animals, and their pathogens of species and their health [3, 4]. These so-called gener - dominate these changes and disrupts natural gut micro- alist species often thrive in or at edges of altered land- biota homeostasis was so far studied only in the Tome’s scapes and have contact with the matrix surrounding spiny rat (Proechimys semispinosus) [17]. In this study, the habitat fragments, often leading to closer contact to spiny rats inhabiting isolated but otherwise undisturbed humans, livestock and domesticated animals [5]. As a rainforest fragments showed a similar gut microbial com- consequence of inhabiting a wide range of habitats, gen- position as conspecifics living in undisturbed continuous eralist species are often important pathogen reservoirs forests, indicating that habitat fragmentation per se is not and act as vectors of zoonotic diseases, despite appearing the driving factor behind changes in the gut microbiome. phenotypically healthy [4]. Increasing contact rates with However, in general, gut microbiomes were less diverse humans and domesticated animals, as well as the exploi- and at the same time, individual microbiomes were tation of wildlife for food or medicine, amplify the risk of more heterogeneous in spiny rats inhabiting fragmented spillover events in both directions [6]. However, assessing and disturbed landscapes, with differences driven by wildlife health of generalist species coping with anthro- microbes associated with humans and domesticated ani- pogenic disturbances can be challenging because of the mals. However, whether these results are restricted to problems posed in macroecological studies in assessing this species or a common feature of generalist species liv- the internal (health) states in wild animals. Even com- ing in sympatry and independent of phylogeny is largely mon fitness indicators, such as body mass can point unknown, but of high importance [22]. into wrong directions if land use change requires dietary In the present study, we analyzed the gut microbiomes shifts of the surviving, apparently adaptable resilient spe- of three sympatric, generalist, neotropical, mammalian cies [7]. species (two marsupials Didelphis marsupialis and Phi- The gut microbiome, the assemblage of microbes and lander opossum, which might be renamed Philander mel- their genomes inhabiting the gut of a host, is an integral anurus in the future [23], and one rodent P. semispinosus) part of an animal’s well-being and is considered as a good inhabiting four landscapes in central Panama with dif- indicator of host health [8, 9]. Gut microbial communi- fering degrees of anthropogenic disturbances: protected ties carry a wide range of important functions ranging continuous tropical forests, protected forested islands from food processing, access to nutrients, production of in the Panama Canal, nearby unprotected forested frag- antibiotics, to the influence on behavior and the immune ments embedded in an agricultural matrix and teak system [10], and thus can play a key role in host adap- plantations. The three study species represent abundant tation to rapidly changing environments [11]. Shifts in generalists living in rainforests with a high tolerance for bacterial diversity beyond the ‘normal’ range can result in habitat modifications [24, 25]. P. semispinosus is a strictly dysbiosis, i.e., the depletion of commensal microbes and terrestrial rodent that mainly feeds on fruits, seeds and increase in pathogenic ones [12]. Both can have negative mycorrhiza and occupies rather small home ranges, often consequences on host immunity and health. Recent stud- representing one of the most abundant mammalian spe- ies in humans and wildlife highlighted that gut homeo- cies within its geographic range [26, 27]. D. marsupialis is stasis as subject to disturbances by viral infections, a common terrestrial, omnivorous marsupial with a large facilitating co-infections and the spread of zoonotic dis- home range [28, 29] and P. opossum is a semi-arboreal eases [13–15]. Dysbiosis has been linked to environmen- marsupial with an omnivorous diet including fruits, ver- tal change, with further influencing factors being stress, tebrates, and invertebrates with a home range of 0.34 ha shifts in diet, and species assemblage on the macroeco- in Panama [29–31]. All three species represent important logical scale [13, 14, 16–18]. pathogen reservoirs and hosts for zoonotic diseases of Indeed, recent studies have emphasized the negative clinical relevance, caused by Trypanosoma [32], Hepa- effects of landscape modifications and habitat fragmenta - civirus [24], mammalian delta virus [33], Schaalia [34] tion on host gut microbiome homeostasis. For example, Heni  et al. Animal Microbiome (2023) 5:22 Page 3 of 18 and Venezuelan equine encephalitis virus [35]. P. semis- gut microbiomes were dominated by the bacterial fami- pinosus and D. marsupialis are known to be consumed by lies Lachnospiraceae, Bacteroidaceae and Acidaminococ- humans as a source of protein, making them particularly cacae. Considering less frequent bacterial families in D. interesting in terms of their potential roles in spillover marsupialis, Diplorickettsiaceae were mainly found in events [36, 37]. This highlights the importance of under - landscape C, while Ruminococcaceae were mainly pre- standing any potential health impacts anthropogenic sent in the landscapes I, A and P. Oscillospiraceae were disturbances may have on these species. With this study detected in landscape I, while Clostridiaceae were mainly design, we aimed to investigate (1) to what degree, if any, present in the disturbed landscapes A and P. Fusobacte- do host species identity (i.e., phylogeny) and landscape riaceae and Peptostreptococcaceae were mainly detected modifications shape the gut microbiomes of three sym - in landscape P. In P. opossum, the gut microbiomes of patric, generalist species; (2) to which extent do the host individuals trapped in landscape C were characterized species differ in their resilience, i.e. responses to differ - by the presence of Clostridia_UCG-014, Enterobacte- ent degrees of anthropogenic disturbances; and finally (3) riaceae and Morganellacea, while Peptostreptococcaceae which gut bacteria are involved in driving any changes, and Clostridiaceae were mainly found in the gut micro- and are they similar for all three host species? Gaining biome of individuals inhabiting landscape A and the a better understanding of the gut microbial response to presence of Prevotellaceae was characteristic for land- anthropogenic disturbances is of high importance in scape P. Muribaculaceae (formerly known as S24-7 [38]), maintaining wildlife health, especially in generalist spe- Lachnospiraceae and Erysipelotrichaceae were the domi- cies that can act as vectors transmitting diseases among nant bacterial families in the gut of P. semispinosus. The wildlife, but also livestock, domestic animals and ulti- gut microbial composition of P. semispinosus differed mately humans. between the landscapes C and I by the addition of Oscil- lospiraceae in landscape I. Rodents trapped in the land- Results scapes A and P both lacked Clostridia_UCG-014 but Species community and abundance pattern harbored Gastranaerophilales instead (Fig. 1). During three field seasons, 1523 animals of 16 different species were captured in 28 study sites distributed across Gut bacterial composition is shaped by both host four landscapes (protected continuous tropical forests phylogeny and landscape type (=C), protected forested islands in the Panama Canal We first investigated if species identity and/or landscape (=I), nearby unprotected forested fragments embed- type shaped gut microbial beta diversity (both composi- ded in an agricultural matrix (=A) and teak plantations tion and dispersion) across all three sympatric species. (=P)) differing in degree of anthropogenic disturbance Using one model with host species identity and land- in Panama (Additional file  1: Figs. S1 and S2). The three scape type as fixed factors per distance matrix (weighted most common animals captured were P. semispino- and unweighted UniFrac distances), both species iden- sus (n = 1235), D. marsupialis (n = 137) and P. opossum tity (PERMANOVA: weighted Unifrac: df = 2, R = 0.23, (n = 72). P. semispinosus and D. marsupialis were cap- p ≤ 0.001; unweighted UniFrac: df = 2, R = 0.21, tured in all four landscapes, while P. opossum was absent p ≤ 0.001) and landscape type had significant effects on on landscape I. Fecal samples from 397 P. semispinosus, gut microbial composition (PERMANOVA: weighted 104 D. marsupialis, and 68 P. opossum were available for Unifrac: df = 3, R = 0.02, p ≤ 0.001; unweighted UniFrac: microbiome investigation (Additional file 2: Table S1). df = 3, R = 0.02, p ≤ 0.001; Fig.  2a, b). Based on effect sizes (Cohen’s d), the effect of phylogeny was larger than Gut bacterial composition of the three generalist species the effect of landscape type (range based on weighted After sequencing the 16S rRNA gene from fecal matter UniFrac distances: host phylogeny: 1.04–7.06, landscape: and rarefication a total of 6404 different bacterial ASVs 0–0.76; range based on unweighted UniFrac distances: were identified in the 569 samples kept after quality fil - host phylogeny: 2.82–6.19, landscape: 0.33–1.34; Fig.  2c, tering (Additional files 1 and 2: Fig. S3 and Table S1). The d). Moreover, pairwise comparisons of each host spe- two marsupial species, P. opossum and D. marsupials, cies pair showed the smallest differences in gut microbial had 1454 ASVs in common, whilst the ground-dwelling composition between both marsupials, and larger differ - species D. marsupialis and P. semispinosus shared 445 ences between either marsupial and the rodent (Fig.  2c, ASVs, and the microbiome of P. opossum and P. semis- d). The effect size for pairwise comparisons of landscape pinosus overlapped in only 252 ASVs (Additional file  1: type showed that each landscape was distinct from one Fig. S4). The two opossum species shared more dominant another, except for the comparison between the dis- bacterial families with each other than with the rodent turbed landscapes A and P using weighted UniFrac dis- species, P. semispinosus (Fig.  1). In the marsupials, the tances (Fig. 2c). In addition to the bacterial composition, Heni et al. Animal Microbiome (2023) 5:22 Page 4 of 18 Fig. 1 Gut bacterial composition (at the family level) of the two marsupials (D. marsupialis, P. opossum) and the spiny rat (P. semispinosus). Details on the landscapes C, I, A and P are provided in the methods and their locations are shown in Additional file 1: Fig. S1. Note that P. opossum was not captured in landscape I gut microbial dispersion was also significantly affected effect of landscape type on gut microbial composition by both host species identity (weighted UniFrac: df = 2, and dispersion (PERMANOVA: df = 3, R = 0.04, p = 0.1; F value = 174.93, p ≤ 0.001; unweighted UniFrac: df = 2, F PERMDISP: df = 3, F value = 0.43, p = 0.74, Fig. 4). How- value = 122.47, p ≤ 0.001, Fig.  2a, b) and landscape type ever, using unweighted UniFrac distances, gut microbial (weighted UniFrac: df = 3, F value = 29.62, p ≤ 0.001; composition (but not dispersion; PERMDISP: df = 3, F unweighted UniFrac: df = 2, F value = 33.38, p ≤ 0.001). value = 1.22, p = 0.30) was significantly affected by land - scape type (PERMANOVA: df = 3, R = 0.04, p ≤ 0.01, Species‑specific effects of landscape type on gut microbial Fig.  4) with plantations (landscape P) clearly differing alpha and beta diversity of sympatric generalist species from the other three landscapes C, I and A based on pair- To determine if landscape type had similar effects on wise comparisons (Additional file 2: Table S2). gut microbial alpha and beta diversity across three dif- In the second, partially arboreal, marsupial species P. ferent, yet sympatric species, we analyzed the effect of opossum that was never captured on landscape I, land- landscape type on gut microbial alpha diversity, com- scape type did not have a significant effect on Faith’s position, and dispersion for each species separately. In PD (Additional file  2: Table  S3, Fig.  3) or on gut bacte- the ground-dwelling marsupial D. marsupialis, all alpha rial community dispersion (PERMDISP: weighted Uni- diversity metrics were significantly impacted by land - Frac: df = 2, F value = 0.16, p = 0.21; unweighted UniFrac: scape type (Additional file  2: Table  S2), with individu- df = 2, F value = 2.72, p = 0.07). It did, however, signifi - als inhabiting landscape P having a significantly lower cantly affect gut microbial composition with regards to gut microbial alpha diversity than those living in the unweighted UniFrac distances (PERMANOVA: df = 2, other three landscape types (Additional file  2: Table  S2, R = 0.04, p ≤ 0.01, Fig.  4), with all landscapes differing depicted for Faith’s PD, Fig.  3). Beta diversity based on from one another based on post-hoc pairwise compari- weighted UniFrac distances did not show a significant sons, but not with regards to weighted UniFrac distances Heni  et al. Animal Microbiome (2023) 5:22 Page 5 of 18 Fig. 2 Differences in beta diversity between three sympatric generalist species, the marsupials D. marsupialis (Dm, green), P. opossum (Po, orange), and the rodent P. semispinosus (Ps, blue). The top row shows NMDS plots of a weighted and b unweighted UniFrac distances. The bottom row c, d displays corresponding forest plots with Cohen’s d effect sizes highlighting the phylogenetic signal and landscape effects, i.e. the different levels of anthropogenic disturbance. Details on the landscapes C, I, A and P are provided in the methods and their locations are shown in Additional file 1: Fig. S1 (PERMANOVA: df = 2, R = 0.04, p = 0.21; Fig.  4, Addi- file  2: Table  S4), with a clear separation between pro- tional file 2: Table S3). tected (landscapes C and I, without contact to humans, In the ground-dwelling, rodent species P. semispino- livestock and domestic animals) and unprotected (land- sus, landscape type had a significant effect on Faith’s scapes A and P, with contact to humans, livestock and PD (Additional file  2: Table  S4, Fig.  3) and pairwise domestic animals) landscape types (Fig. 4). Thus, the gut comparisons showed that each landscape type sig- microbiomes of generalists are affected by anthropogenic nificantly differed from one another, except for the two disturbances, but sympatric species show species-specific protected landscapes C and I as well as the two unpro- differences in their responses. tected landscapes A and P (Additional file  2: Table  S4, Fig.  3). Similarly, gut microbial beta diversity (compo- sition and dispersion) was significantly impacted by Landscape‑driven species‑specific taxonomic differences landscape type, regardless of distance metric (weighted in gut microbial beta diversity UniFrac: PERMANOVA: df = 3, R = 0.07, p ≤ 0.001; To gain a better understanding of which bacterial taxa PERMDISP: df = 3, F value = 13.21, p ≤ 0.001, pair wise are driving the differences in beta diversity between land - post-hoc test Additional file  2: Table  S4; unweighted scape types within each host species, we ran three differ - UniFrac: PERMANOVA: df = 3, R = 0.05, p ≤ 0.001; ent differential abundance analyses, one for each species, PERMDISP: df = 3, F value = 7.17, p ≤ 0.001, Additional Heni et al. Animal Microbiome (2023) 5:22 Page 6 of 18 Fig. 3 Landscape effects on alpha diversity (measured as Faith´s PD) of three sympatric generalist species, the marsupials D. marsupialis and P. opossum, and the spiny rat P. semispinosus. Individuals were trapped in protected continuous tropical forests (landscape C, green); protected forested islands in the Panama Canal (landscape I, blue); in the nearby unprotected forested fragments embedded in an agricultural matrix (landscape A, yellow) and in teak plantations (landscape P, red) using ANCOM [39]. Because this is a pairwise test, we hypothesis-driven assumption, comparing the two dis- grouped together individuals from landscape types that turbed landscapes against the protected control (landscape did not significantly differ in the aforementioned beta C). In doing so, we detected 24 differentially abundant diversity analyses, i.e., showed similar responses to land- ASVs from the bacterial classes Alphaproteobacteria, Bac- scape effects on beta diversity. teroida, Clostridia, Coriobacteriia and Vampirivibrionia First, for D. marsupialis, we compared gut microbiomes (Fig.  6). Lastly, for P. semispinosus, we compared the gut from individuals inhabiting landscapes C + I + A against microbial compositions of rodents inhabiting the pro- P and identified 27 differentially abundant ASVs from the tected landscapes C and I to those living in the unprotected bacterial classes Alphaproteobacteria, Bacilli, Bacteroida, landscapes A and P and found 481 differentially abundant Clostridia, and Gammaproteobacteria (Fig.  5). Second, ASVs from the bacterial classes Actinobacteria, Alphapro- for P. opossum, we compared the gut microbial communi- teobacteria, Bacilli, Bacteroida, Clostridia, Coriobacteriia, ties of individuals living in the control landscape C against Elusimicrobia, Gammaproteobacteria, Negativicutes, Spi- those from the disturbed landscapes A and P (this spe- rochaetia, Vampirivibrionia, and Verrucomicrobiae (Figs. 7 cies was not captured on landscape I). Because no clear and 8). separation of the microbial alpha- or beta-diversity based Among the ASVs identified were representatives, on landscape type was observed, we decided to use our such as Chrisensenellaceae R-7 group (D. marsupialis), (See figure on next page.) Fig. 4 NMDS plots visualizing landscape effects on beta diversity. Beta diversity is measured by a weighted and b unweighted UniFrac distances in the three sympatric generalist species, the marsupials D. marsupialis (top) and P. opossum (middle), and the spiny rat P. semispinosus (bottom). Distances to the group centroids are depicted in the inserted graphs in the top right corners and ellipses indicate 95% confident intervals. Individuals were trapped in protected continuous tropical forests (landscape C, green); protected forested islands in the Panama Canal (landscape I, blue); in the nearby unprotected forested fragments embedded in an agricultural matrix (landscape A, yellow) and in teak plantations (landscape P, red) Heni  et al. Animal Microbiome (2023) 5:22 Page 7 of 18 Fig. 4 (See legend on previous page.) Heni et al. Animal Microbiome (2023) 5:22 Page 8 of 18 Fig. 5 Differentially abundant ASVs (using ANCOM) in pairwise comparisons with landscape groupings based on similar responses in beta diversity to landscape modifications (Fig. 4) in D. marsupialis comparing landscape C + I + A against P. Colors represent the different bacterial classes. a Differential abundant ASVs according to the taxonomical assignment; b Volcano plot of differential abundant ASVs, depicting the F statistics and W-value Heni  et al. Animal Microbiome (2023) 5:22 Page 9 of 18 Fig. 6 Differentially abundant ASVs (using ANCOM) in pairwise comparisons with landscape groupings based on similar responses in beta diversity to landscape modifications (Fig. 4) in P. opossum comparing landscape C against A + P. Colors represent the different bacterial classes. a Differential abundant ASVs according to the taxonomical assignment; b Volcano plot of differential abundant ASVs, depicting the F statistics and W-value Heni et al. Animal Microbiome (2023) 5:22 Page 10 of 18 Fig. 7 First half of differentially abundant ASVs (using ANCOM) in pairwise comparisons with landscape groupings based on similar responses in beta diversity to landscape modifications (Fig. 4) in P. semispinosus comparing landscape C + I against A + P. Results split into two graphs. Colors represent the different bacterial classes. a Differential abundant ASVs according to the taxonomical assignment; b Volcano plot of differential abundant ASVs, depicting the F statistics and W-value Heni  et al. Animal Microbiome (2023) 5:22 Page 11 of 18 Fig. 8 Second half of differentially abundant ASVs (using ANCOM) in pairwise comparisons with landscape groupings based on similar responses in beta diversity to landscape modifications (Fig. 4) in P. semispinosus comparing landscape C + I against A + P. Results split into two graphs. Colors represent the different bacterial classes. a Differential abundant ASVs according to the taxonomical assignment; b Volcano plot of differential abundant ASVs, depicting the F statistics and W-value Heni et al. Animal Microbiome (2023) 5:22 Page 12 of 18 Chlostridium senu stricto I (D. marsupialis), Rikenella (D. disturbances each responded differently with regards to marsupialis), Vagococcus (D. marsupialis), Butyricoccus gut microbial diversity and that the gut microbiome of (P. opossum), Coprococcus (P. opossum), Peptococcus (P. sympatric species is determined by both phylogeny and opossum), Rikenella (P. opossum), Bacteroides (P. semispi- landscape. We observed species-specific gut microbial nosus), Allobaculum (P. semispinosus) and Dubsosiella (P. responses to different landscape types, with P. semis - semispinosus). pinosus showing the highest sensitivity to proximity to humans. In D. marsupials, however, only the landscape Discussion with a combination of human contact, fragmentation, Impact of habitat change on species with high ecological and complete changes in forest type (from lowland tropi- plasticity cal rainforest to teak plantation) led to changes in the gut In the Anthropocene, the selection pressures faced by microbiome. In contrast, P. opossum’s gut microbiome species worldwide have changed to favor species pos- showed the highest resilience, without a distinct pattern sessing ecological plasticity, with a higher tolerance to of change in the gut microbial alpha diversity or beta dis- anthropogenically modified environments [40], the so- persion. These species-specific responses were mirrored called generalist species [41]. Failure to adapt can espe- in our differential abundance analyses that showed the cially impact animals with narrow ecological niches, highest number of differentially abundant ASVs in P. sem - leading to changes in the composition of animal com- ispinosus versus the two other species. The gut microbi - munities [42]. Increases in the abundance of generalists omes of our three analyzed species were affected by both in disturbed landscapes at the cost of the decline of less species identity and landscape type, which is supported resilient species can be accompanied by negative conse- by other studies [49, 50]. quences for the ecosystem and increase the risk of disease Species identity can influence the gut microbiome not spread and spillover [43]. As anthropogenic selection only because of species-specific genetic constitutions, pressures will affect these pathogen reservoirs and dis - but also because species identity determines suitable ease vectors best adapted to living in close proximity to environment, food preferences and processing potential, human settlements, studies on generalists’ role in emerg- pathogen resistance, as well as adaptive potential [51]. ing infectious diseases from wildlife and their adaptabil- Similarly, landscape types can differ in food availability ity to global environmental changes are key in order to as well as exposure to pathogens, pesticides, and differ - understand the threat they are under and the threat they ent plant and animal communities. The gut microbiomes may pose [4, 44]. In fact, deforestation is considered one of the two opossum species were more similar to one of the main drivers of zoonotic diseases [45], yet, current another than they were to the spiny rat. A similar trend reforestation programs often rely on a few tree species or was shown in large African mammals, where gut micro- even monocultures, such as eucalyptus or teak planta- bial composition was closely correlated with phylogeny tions, which might accelerate the risk [46]. [52], as did the gut microbiome in some primates [53]. While some studies show the effect of species identity and environment on several species’ gut microbiomes, Phylogeny and landscape influence the microbiome [22, 49], they are often limited to extreme environmental of sympatric species situations [22, 54], thus only comparing extremely con- In central Panama, we investigated four landscapes dif- trasting conditions for the animals. However, landscape fering in their degree of anthropogenic disturbance which plays a large role in shaping the microbial community have been shown to have severe impacts on different lev - in humans and apes [55], and habitat fragmentation can els of diversity: species assemblages and abundance pat- have an influence on the gut microbiome through dietary terns [24, 42, 47], pathogen diversity and host infections changes [56]. Similar results have been discovered in dif- [18, 25, 48], neutral and adaptive genetic diversity [18, 25] ferent howler monkey species, where host species was a along with gut microbial community patterns [17, 18] dif- key predictor of the gut microbiota, but forest type, habi- fered according to landscape type. As a crucial factor in tat, and season explained species-specific variances [57]. host health, the gut microbiome has been put forward as a potentially vital component in helping wildlife to adapt Only extreme habitat perturbation changes D. marsupialis to fast-paced global changes [11]. However, whether this gut microbiomes holds true for a wider range of species facing the same Analyzing the three species separately showed that degrees of anthropogenic disturbance was the focus of changes in gut microbial composition in D. marsu- the present study. pialis occurred only in individuals inhabiting the most Here, we showed that three sympatric, generalist spe- disturbed landscape, namely teak plantations. Teak cies faced with the same landscape-level anthropogenic Heni  et al. Animal Microbiome (2023) 5:22 Page 13 of 18 plantations are defined by a different forest type in addi - driven by bacterial taxa associated with humans and tion to being fragmented and embedded in a matrix with domesticated animals, as well as increased dispersion of human contact. Because they are monocultures, teak the bacterial community in individuals from fragments plantations can alter the food availability of the inhabit- surrounded by agriculture [17]. All these features were ing animals and provide a harsher environment, e.g. due not detected in individuals sampled in continuous for- to increased risk of forest fires [58]. Additionally, the con - ests or protected forested islands [17]. While the impact version of natural habitats to teak plantations exposes of protected landscape types with no human contact animal communities to changes in microbial soil com- (continuous forests and islands) versus fragmented land- position [59]. D. marsupialis individuals living in these scapes with human contact (forest fragments embedded plantations either need to adapt to these changes and the in an agricultural matrix) on P. semispinosus gut micro- potential stress associated with them or use the planta- biomes have been discussed elsewhere [17], the apparent tions as a corridor for travel. similar behavior of the gut microbiome from individuals living in teak plantation to those inhabiting forest frag- High resilience of P. opossum gut microbiomes ments is noteworthy. Contrarily to forested fragments, to anthropogenic changes teak plantations also differ in the natural assembly of The second marsupial, P. opossum, however, showed a trees, with the dominant species being the from Asia different gut microbial response. Despite only occur - introduced teak tree (Tectona grandis). The gut micro - ring in three of the four sampled landscapes, P. opos- biome of D. marsupialis was only impacted in this land- sum individuals showed little change in gut microbial scape type, which we consider to be the most extreme composition with no clear patterns across the different landscape type, and therefore, we expected an additional landscape types. Changes in gut microbial composition impact on the P. semispinosus gut microbiome on top of between individuals inhabiting all three landscapes were the changes caused by the forest fragments. However, the only observed when using unweighted UniFrac distances, lack of a compounded impact could mean two things: (1) indicating that rare ASVs are likely responsible for these individuals from fragmented forests already display the changes. As a semi-arboreal habitat generalist, P. opos- most extreme gut microbial perturbation tolerable by this sum individuals could escape bacterial taxa introduced species, or (2) teak plantations provide a suitable forest by humans and livestock to soils. This could explain the habitat for P. semispinosus, despite being monocultures weakened gut microbial response compared to the more and lacking trees typical for rainforests. It also indicates closely-related D. marsupialis. Further risk of coming that the presence of humans and domesticated animals into contact with microbes from humans or domesti- in the matrix alone shapes the microbiome, and not frag- cated animals is reduced because part of P. opossum’s mentation or forest tree composition per se. diet consists of insects [60], meaning this host might be less exposed to bacteria in the ground or associated with Human‑vicinity‑associated ASVs drive gut microbial plants compared to, say, herbivorous hosts. The micro - changes biomes of animals and their environment are linked and Differential abundance analysis revealed a large differ - shape each other in both directions [61, 62]. Still, the fact ence in the number of ASVs determined to be differently that prolonged isolation and fragmentation possibly lead abundant between the landscapes when considering each to local extinction (as seen by their absence on islands) of the three species separately. While for the two opos- could indicate that P. opossum is not insensitive to land- sum species only a handful of differentially abundant scape changes. Because islands provide the harshest bacterial taxa were detected, many were discovered for P. matrix based on accessibility and usability as a corridor semispinosus. In general, detected bacteria often showed for movement, their extinction on islands could be due similarity to ones characterized in more detail in human to a past bottleneck event. However, there are interest- or domesticated animal microbiomes (e.g. Allobaculum ing dynamics of opossum species in the Panama Canal [64]). Most of the detected ASVs have already been dis- area with local disappearance as well as re-colonization cussed [17], theorizing that a large portion of the identi- of some small islands close to the mainland, thus opening fied bacteria could have been introduced by humans and the possibility for re-colonization [63]. their domesticated animals. In addition, in D. marsupia- lis, we detected ASVs assigned to the genus Vagococcus, Large impact of human vicinity on P. semispinosus gut which was first isolated from chicken feces [65], animals microbiomes that D. marsupials are known to get into close contact The gut microbiome of the common P. semispinosus is with because they prey on their eggs [36]. Landscapes A very sensitive to human contact, as was shown by the and P are in close vicinity to human settlements, there- reduced microbial diversity and shifts in composition, fore uptake of these human-driven taxa into their gut Heni et al. Animal Microbiome (2023) 5:22 Page 14 of 18 microbiomes is not unexpected and could cause harm to Material and methods the host by changing gut microbial composition. Study area and sampling This study was carried out in the Panama Canal area, Potential consequences of microbiome changes induced Panama. Animals were captured in 28 study sites grouped by anthropogenic landscape disturbance into four different landscapes based on their degree of D. marsupialis is known to be consumed by humans, anthropogenic disturbance (Additional file  1: Fig. S1, both for nutritional and cultural reasons [36]. Thus, not map created with ggmap [73]): (1) continuous rainforest only proximity, but also direct contact with humans can (=C, five capture sites), i.e., undisturbed and protected be an important pathway for pathogen transmission, and lowland tropical rainforest within the Barro Colorado a perturbed microbiome might have negative effects on Nature Monument; (2) forested islands (=I, six capture host immunity, given the microbiome’s interplay and sites) situated in the Gatún Lake and also protected by crosstalk with the host immune system [66]. Altered the Barro Colorado Nature Monument, i.e., fragmented microbial communities can facilitate pathogen infection but otherwise undisturbed landscape; (3) fragmented and [48] and vice versa pathogen infection can change the disturbed (i.e. contact to humans and domesticated ani- microbiome [13–15]. These perturbed microbiomes fur - mals) tropical lowland rainforest embedded in an agricul- ther increase the risk of horizontal gene transfer which tural matrix (=A, nine capture sites); and (4) fragmented could lead to pathogenic bacteria [67]. Close contact and disturbed teak plantations (=P, seven capture sites) between humans and domesticated animals can be dan- planted by humans and mainly consisting of Tectona gerous for wildlife and humans, as demonstrated with the grandis. spillover of Nipah virus, which made the jump from fly - Field work took place during three field seasons (Octo - ing foxes to humans through pigs as an intermediate host ber 2013 to May 2014, October 2014 to May 2015 and [68, 69]. Because land-use change can cause pandem- September 2016 to April 2017, alternating the order of ics and the emergence of new diseases [70] and because capture sites between seasons). At each capture site a rodents and marsupials represent a significant zoonotic trapping grid consisting of 100 stations was set up. Each disease risk in the future [71], these findings become station was separated by 20 m and consisted of three live even more important regarding the potential for the traps [one Tomahawk trap (size: 15.2 × 15.2 × 48.3  cm, origins and emergence of zoonotic diseases, and future www. livet rap. com) and two Sherman traps (size: studies will reveal how these microbiome changes impact 10.2 × 11.4 × 38.1  cm, www. sherm antra ps. com)], one of animal’s fitness in detail. Moreover, the loss of microbial which was placed above ground, if possible, i.e., on trees, diversity has been recognized as a potential threat to the lianas or similar, if available, to include arboreal species. discovery of new drugs or therapeutics in the field of Traps were opened at dusk and baited with a mixture of microbial biotechnology [72]. peanut butter, oatmeal, bird seeds, banana, and dog food to attract species with various dietary preferences and controlled at dawn of the next day. Then, captured ani - Conclusion mals were measured, individually marked to recognize Overall, we could show that the gut microbiomes of recaptures, and fecal samples were taken from animals sympatric species inhabiting landscapes with differ - during sampling. Afterwards, the animals were released ing degrees of anthropogenic disturbance are mainly at the capturing location (further details see [24]). Fecal shaped by host species identity, with landscape type play- samples were stored in collection tubes containing RNAl- ing a smaller but significant role. Interestingly, there is ater at − 20 °C until DNA extraction. a species-specific gut microbial response to landscape type, indicating that findings from one species cannot always be generalized to other species, even not to those DNA extraction, 16S rRNA gene amplification living in the same habitat or to those that are closely and sequencing related. This shows that these generalists’ gut microbi - A detailed summary of sample processing is described omes are sensitive to landscape-level changes, a fact not elsewhere [17]. In brief, we extracted DNA from fecal detected by biodiversity monitoring of vertebrates, and samples from a total of 793 samples (including extrac- that these changes are not uniform across host species. tion blanks and PCR controls) using NucleoSpin Soil- u Th s, even for generalists, environmental changes can Extraction Kit from Macherey–Nagel (Germany). The pose a big impact, which is an important finding as this final elution step was performed twice with 50 µl of elu - might directly cause consequences and the risk of emerg- tion buffer each time, resulting in a total volume of 100 µl. ing zoonoses not only for wildlife health, but also for the Following extraction, we amplified the 291 nucleotide- health of domesticated animals intended for human con- long V4 region of the 16S rRNA gene using the 515 F and sumption, and for humans themselves. 806 R primers [74, 75] applying a two-step polymerase Heni  et al. Animal Microbiome (2023) 5:22 Page 15 of 18 chain reaction (PCR). The first step was an initial dena - extracting the results from the PERMANOVA of the first turation of 600 s at 95 °C followed by 30 cycles with 95 °C two NMDS axes. for 30 s, 60° for 30 s and 72 °C for 45 s, followed by a final Second, to determine if the gut microbiome in each of elongation of 72  °C for 600  s. The second step consisted the three host species is similarly impacted by landscape of ten cycles for the barcoding with the same conditions type, we subset our data for each species. Both alpha as described above. The samples were sequenced on six diversity (observed number of ASVs, Shannon Diversity runs on an Illumina MiSeq at our Institute of Evolution- and Faith’s phylogenetic diversity, PD) and beta diversity ary Ecology and Conservation Genomics, Ulm Univer- metrics (weighted and unweighted UniFrac distances) sity, Germany. were calculated. For alpha diversity, we constructed gen- eralized linear models (GLMs) with landscape, season, and sex as factors explaining the alpha diversity indices Data processing and afterwards used contrasts to analyze pairwise com- Reads from all six Illumina runs were analyzed in QIIME parisons. For beta diversity, we applied PERMANOVAs 2 (Version 2020.6, August 2020) [76] with a total of and PERMDISPs as described above, followed by post- 14,489,625 sequences. DADA2 [77] was used to pro- hoc pairwise comparisons calculated for each landscape. cess the sequences and assemble these into amplicon Finally, to investigate which taxa were driving the dif- sequence variants (ASVs) and SILVA (version 1.38) [78] ferences in beta diversity, we performed differential was used as a taxonomic reference database. We removed abundance analyses using ANCOM (Analysis of Compo- a total of 194,432 sequences (roughly 0.83%) annotated sition of Microbiomes) [39] which allows two-level fac- as Archaea, mitochondria and chloroplast. Data were tor comparisons [17]. We chose a w of 0.7 as originally transferred into a phyloseq object [79] within the R envi- 0 described in [39]. Based on the results of the species-spe- ronment (version 4.0.2) [80] for further analyses. ASVs cific landscape effects on beta diversity (see Results), we identified in the blanks and controls (a total of 55,463 compared the landscapes C + I + A versus P for D. mar- ASVs, equivalent to 0.38%) were removed from samples supials, C versus A + P for P. opossum and C + I versus to avoid false results. We applied an additional filter to A + P for P. semispinosus for our two-level factor compar- remove rare ASVs with fewer than 50 reads across the isons. All graphs were plotted in the R environment using entire dataset and which occurred in only 2% of all the the ggplot2 package [85]. samples. Finally, we rarefied the data in order to control for uneven sequencing depth. Rarefaction was performed Supplementary Information using the rarefy_even_depth function from the phyloseq The online version contains supplementary material available at https:// doi. package and a sequencing depth of 10,000 reads was org/ 10. 1186/ s42523- 023- 00237-9. chosen based on rarefaction curves (Additional file  1: Fig. S3). After performing all the bioinformatic quality Additional file 1: Fig. S1. Location of the study area and 28 capture sites filtering steps at rarefaction, 569 samples (P. semispino - distributed across four landscapes differing in their anthropogenic impact in central Panama. Capture sites in the protected continuous tropical sus: n = 397 individuals; D. marsupialis: n = 104 individu- forests (landscape C) are marked in green; sites in the protected forested als; P. opossum: n = 68) remained for subsequent analysis islands in the Panama Canal (landscape I) are marked in blue; sites in the (Additional file 2: Table S1). nearby unprotected forested fragments embedded in an agricultural matrix (landscape A) are marked in yellow; and sites in teak plantations (landscape P) are marked in red. Map created with the R package ggmap Statistical analyses (Kahle and Wickham, 2013) with the origin of the map material being Google Maps. Fig. S2. Distribution of the captured species across the four Statistical analyses were separated into two parts based landscapes. Details on the landscapes C, I, A and P are provided in the on the study questions. First, to determine if phylogeny methods and their locations are shown in Additional file 1: Fig. S1. Fig. and/or landscape affect the gut microbial beta diversity S3. Rarefaction curves showing the number of detected ASVs in relation to 16S rRNA gene sequencing depth (i.e. total number of reads obtained in the three species, we used the whole dataset, consist- per individual after quality filtering) for Didelphis marsupialis (turquoise), ing of all three species and all four landscapes. Using Philander opossum (orange) and Proechimys semispinosus (light-blue). The weighted and unweighted UniFrac distances [81], we maximum diversity is reached at around 10,000 reads (vertical line). Fig. S4. Shared ASVs between Didelphis marsupialis (turquoise), Philander opos- tested for differences in gut microbial composition and sum (orange) and Proechimys semispinosus (light-blue). homogeneity according to landscape and host species Additional file 2: Table S1. Number of samples per species and using PERMANOVA (Permutational Analysis of Vari- landscape in the final dataset. Details on the landscapes C, I, A and P are ance, with 9999 permutations) and PERMDISP2 (Per- provided in the methods and their locations are shown in Additional file 1: mutational Analysis of Multivariate Dispersions) [82] Fig. S1. Table S2. Eec ff ts of landscape type on the gut bacterial diversity of D. marsupialis. Results from generalized linear models indicating the using the vegan package [83]. These tests were followed effects of landscape type, field season and sex on alpha diversity using a by post-hoc pairwise comparisons. Effect sizes (Cohen’s Faith’s PD; b Number of ASVs and c Shannon diversity. Results from pair- d) [84] for pairwise comparisons were calculated by wise comparisons (Contrasts) of landscapes using d Faith’s PD; e Number Heni et al. Animal Microbiome (2023) 5:22 Page 16 of 18 Author details of ASVs and f Shannon diversity. g Results from PERMANOVA for pairwise 1 Institute of Evolutionary Ecology and Conservation Genomics, Ulm University, comparisons of landscapes on beta diversity (weighted and unweighted 2 89081 Ulm, Germany. Smithsonian Tropical Research Institute, Balboa, Ancón, UniFrac). SE Standard error; df Degrees of freedom. Table S3. Eec ff ts of 3 Republic of Panama. Institute of Virology, Campus Charité Mitte, Charité landscape type on the gut bacterial diversity of P. opossum. Results from - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, generalized linear models indicating the effects of landscape type, field Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117 Berlin, season and sex on alpha diversity using a Faith’s PD; b Number of ASVs Germany. and c Shannon diversity. 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Journal

Animal Microbiome – Springer Journals

Published: Apr 6, 2023

Keywords: Gut microbiome; Phylogenetics; Anthropogenic disturbance; Landscape ecology; Proechimys semispinosus; Didelphis marsupialis; Philander opossum; Panama

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