Multilayer Networks Assisting to Untangle Direct and Indirect Pathogen Transmission in Bats

• Autor(a) principal: Alcantara, Daniel Maximo Correa
• Data de Publicação: 2022
• Outros Autores: Ikeda, Priscila [UNESP], Souza, Camila Silveira, de Mello, Victória Valente Califre [UNESP], Torres, Jaire Marinho, Lourenço, Elizabete Captivo, Bassini-Silva, Ricardo, Herrera, Heitor Miraglia, Machado, Rosangela Zacarias [UNESP], Barros-Battesti, Darci Moraes, Graciolli, Gustavo, André, Marcos Rogério [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1007/s00248-022-02108-3; http://hdl.handle.net/11449/247693
• topic: Bartonella; Chiroptera; Ehrlichia; Hemoplasmas; Host-parasite association; Neorickettsia

The importance of species that connect the different types of interactions is becoming increasingly recognized, and this role may be related to specific attributes of these species. Multilayer networks have two or more layers, which represent different types of interactions, for example, between different parasites and hosts that are nonetheless connected. The understanding of the ecological relationship between bats, ectoparasites, and vector-borne bacteria could shed some light on the complex transmission cycles of these pathogens. In this study, we investigated a multilayer network in Brazil formed by interactions between bat-bacteria, bat-ectoparasite, and ectoparasite-bacteria, and asked how these interactions overlap considering different groups and transmission modes. The multilayer network was composed of 31 nodes (12 bat species, 14 ectoparasite species, and five bacteria genera) and 334 links, distributed over three layers. The multilayer network has low modularity and shows a core-periphery organization, that is, composed of a few generalist species with many interactions and many specialist species participating in few interactions in the multilayer network. The three layers were needed to accurately describe the multilayer structure, while aggregation leads to loss of information. Our findings also demonstrated that the multilayer network is influenced by a specific set of species that can easily be connected to the behavior, life cycle, and type of existing interactions of these species. Four bat species (Artibeus lituratus, A. planirostris, Phyllostomus discolor, and Platyrrhinus lineatus), one ectoparasite species (Steatonyssus) and three bacteria genera (Ehrlichia, hemotropic Mycoplasma and Neorickettsia) are the most important species for the multilayer network structure. Finally, our study brings an ecological perspective under a multilayer network approach on the interactions between bats, ectoparasites, and pathogens. By using a multilayer approach (different types of interactions), it was possible to better understand these different ecological interactions and how they affect each other, advancing our knowledge on the role of bats and ectoparasites as potential pathogen vectors and reservoirs, as well as the modes of transmission of these pathogens.