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Gut microbiota plasticity in insular lizards under reversed island syndrome
Animals living on small islands are more drastically exposed to environmental changes, such as food or water starvation, and rapid temperature shifts. Facing such conditions, and probably thank to adaptive plasticity mechanisms, some animals display a Reversed Island Syndrome (RIS), a suite of trait...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9314426/ https://www.ncbi.nlm.nih.gov/pubmed/35879521 http://dx.doi.org/10.1038/s41598-022-16955-0 |
Sumario: | Animals living on small islands are more drastically exposed to environmental changes, such as food or water starvation, and rapid temperature shifts. Facing such conditions, and probably thank to adaptive plasticity mechanisms, some animals display a Reversed Island Syndrome (RIS), a suite of traits, including skin pigmentation, voracity, sexual dimorphism, showed differently from mainland relatives. Here, we analyse a so far poorly explored aspect of RIS: the effect of this on the microbiota composition of host Italian wall lizard (Podarcis siculus), strongly influenced by the animal’s lifestyle, and conditioning the same. We compare mainland and island populations, assessing the difference between their microbial communities and their response under unexpected food, experimentally provided. Our observations showed a significant difference in microbiota communities between island and mainland groups, depended mainly from changes in relative abundance of the shared genera (difference due to decrease/increase). Exposure to experimental diet regimes resulted into significative reshaping of bacterial composition of microbiota and a greater variation in body mass only in the island population. Our results could be an evidence that gut microbial community contributes to adaptive plasticity mechanisms of island lizards under RIS to efficiently respond to unexpected changes. |
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