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Microplastics contaminate environments worldwide and are ingested by numerous species, whose health is affected in multiple ways. A key dimension of health that may be affected is the gut microbiome, but these effects are relatively unexplored. Here, we investigated if microplastics are associated with changes in proventricular and cloacal microbiomes in two seabird species that chronically ingest microplastics: northern fulmars and Cory’s shearwaters. The amount of microplastics in the gut was significantly correlated with gut microbial diversity and composition: microplastics were associated with decreases in commensal microbiota and increases in (zoonotic) pathogens and antibiotic-resistant and plastic-degrading microbes. These results illustrate that environmentally relevant microplastic concentrations and mixtures are associated with changes in gut microbiomes in wild seabirds. Consuming microplastics is known to harm marine wildlife in several ways, but effects on the microbiome are understudied. Here the authors demonstrate that two species of wild seabirds with larger amounts of microplastic in their guts had fewer commensal gut microbial species but more pathogens.

In the Anthropocene, humans, domesticated animals, wildlife, and their environments are interconnected, especially as humans advance further into wildlife habitats. Wildlife gut microbiomes play a vital role in host health. Changes to wildlife gut microbiomes due to anthropogenic disturbances, such as habitat fragmentation, can disrupt natural gut microbiota homeostasis and make animals vulnerable to infections that may become zoonotic. However, it remains unclear whether the disruption to wildlife gut microbiomes is caused by habitat fragmentation per se or the combination of habitat fragmentation with additional anthropogenic disturbances, such as contact with humans, domesticated animals, invasive species, and their pathogens. Here, we show that habitat fragmentation per se does not impact the gut microbiome of a generalist rodent species native to Central America, Tome’s spiny rat Proechimys semispinosus, but additional anthropogenic disturbances do. Indeed, compared to protected continuous and fragmented forest landscapes that are largely untouched by other human activities, the gut microbiomes of spiny rats inhabiting human-disturbed fragmented landscapes revealed a reduced alpha diversity and a shifted and more dispersed beta diversity. Their microbiomes contained more taxa associated with domesticated animals and their potential pathogens, suggesting a shift in potential metagenome functions. On the one hand, the compositional shift could indicate a degree of gut microbial adaption known as metagenomic plasticity. On the other hand, the greater variation in community structure and reduced alpha diversity may signal a decline in beneficial microbial functions and illustrate that gut adaption may not catch up with anthropogenic disturbances, even in a generalist species with large phenotypic plasticity, with potentially harmful consequences to both wildlife and human health.Fackelmann et al. study the gut microbial composition of spiny rats across tropical forests in Panama with varying levels of protection and fragmentation in order to disentangle the relative influences of habitat fragmentation and anthropogenic disturbance on wildlife gut microbiomes. They find that habitat fragmentation on its own did not affect the gut microbiome, but the microbiomes of individuals inhabiting forest fragments affected by anthropogenic disturbance displayed a shift in community composition and structure, and were more likely to have microbiota associated with domesticated animals and their pathogens.

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 abundance 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 landscapes 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 ecological plasticity are impacted by human encroachment into nature, but differ in resilience which can have critical implications on conservation efforts and One Health strategies.

Understudied pet-associated microbiomes represent a rich source for the discovery of microbial taxa important for pet and human health. From a cohort of 23 dogs, we sampled and metagenomically sequenced 64 dental plaque microbiomes, generating 1945 metagenome-assembled genomes spanning 347 microbial species, including 277 undercharacterized species without cultivated representatives. Integration with human microbiome data revealed the dog plaque microbiome is more diverse than – and shows little overlap (5.9% species in common) with – the human plaque microbiome, even though some shared periodontal pathobionts arise as a potential concern.

Parasitic infections disturb gut microbial communities beyond their natural range of variation, possibly leading to dysbiosis. Yet it remains underappreciated that most infections are accompanied by one or more co-infections and their collective impact is largely unexplored. Here we developed a framework illustrating changes to the host gut microbiome following single infections, and build on it by describing the neutral, synergistic or antagonistic impacts on microbial α- and ß-diversity expected from co-infections. We tested the framework on microbiome data from a non-human primate population co-infected with helminths and Adenovirus, and matched patterns reported in published studies to the introduced framework. In this case study, α-diversity of co-infected Malagasy mouse lemurs ( Microcebus griseorufus ) did not differ in comparison with that of singly infected or uninfected individuals, even though community composition captured with ß-diversity metrices changed significantly. Explicitly, we record stochastic changes in dispersion, a sign of dysbiosis, following the Anna-Karenina principle rather than deterministic shifts in the microbial gut community. From the literature review and our case study, neutral and synergistic impacts emerged as common outcomes from co-infections, wherein both shifts and dispersion of microbial communities following co-infections were often more severe than after a single infection alone, but microbial α-diversity was not universally altered. Important functions of the microbiome may also suffer from such heavily altered, though no less species-rich microbial community. Lastly, we pose the hypothesis that the reshuffling of host-associated microbial communities due to the impact of various, often coinciding parasitic infections may become a source of novel or zoonotic diseases.

Characterization of gut metagenomes from 21,561 volunteers on omnivore, vegetarian or vegan diets shows how major food groups may shape the gut microbiome not only through the selection of microbes that aid in digestion, but also through the acquisition of microbes from foods themselves.

As plant-based diets gain traction, interest in their impacts on the gut microbiome is growing. However, little is known about diet-pattern-specific metagenomic profiles across populations. Here we considered 21,561 individuals spanning 5 independent, multinational, human cohorts to map how differences in diet pattern (omnivore, vegetarian and vegan) are reflected in gut microbiomes. Microbial profiles distinguished these common diet patterns well (mean AUC = 0.85). Red meat was a strong driver of omnivore microbiomes, with corresponding signature microbes (for example, Ruminococcus torques , Bilophila wadsworthia and Alistipes putredinis ) negatively correlated with host cardiometabolic health. Conversely, vegan signature microbes were correlated with favourable cardiometabolic markers and were enriched in omnivores consuming more plant-based foods. Diet-specific gut microbes partially overlapped with food microbiomes, especially with dairy microbes, for example, Streptococcus thermophilus , and typical soil microbes in vegans. The signatures of common western diet patterns can support future nutritional interventions and epidemiology. Using 21,561 individuals, the authors present a cross-sectional study of how gut microbiome signatures are associated with dietary intake patterns and with host health outcomes.

Proteins perform a large variety of functions in living organisms, thus playing a key role in biology. As of now, available learning algorithms to process protein data do not consider several particularities of such data and/or do not scale well for large protein conformations. To fill this gap, we propose two new learning operations enabling deep 3D analysis of large-scale protein data. First, we introduce a novel convolution operator which considers both, the intrinsic (invariant under protein folding) as well as extrinsic (invariant under bonding) structure, by using \\(n\\)-D convolutions defined on both the Euclidean distance, as well as multiple geodesic distances between atoms in a multi-graph. Second, we enable a multi-scale protein analysis by introducing hierarchical pooling operators, exploiting the fact that proteins are a recombination of a finite set of amino acids, which can be pooled using shared pooling matrices. Lastly, we evaluate the accuracy of our algorithms on several large-scale data sets for common protein analysis tasks, where we outperform state-of-the-art methods.