From host individual traits to community structure and composition: Bartonella infection insights
Background. Phylogeny, combined with trait-based measures, offers insights into parasite sharing among hosts. However, the specific traits that mediate transmission and the aspects of host community diversity that most effectively explain parasite infection rates remain unclear, even for the Bartone...
| Authors: | , , , , |
|---|---|
| Format: | article |
| Publication Date: | 2024 |
| Country: | España |
| Institution: | Universidad Complutense de Madrid (UCM) |
| Repository: | Docta Complutense |
| Language: | English |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/111122 |
| Online Access: | https://hdl.handle.net/20.500.14352/111122 |
| Access Level: | Open access |
| Keyword: | 579.881.2 599 591.5 Bartonella Functional diversity Host trait Interaction network Mammal Phylogeny Microbiología (Biología) Zoología Mamíferos Ecología (Biología) 2414 Microbiología 2401 Biología Animal (Zoología) 2401.18 Mamíferos 2401.06 Ecología Animal |
| Summary: | Background. Phylogeny, combined with trait-based measures, offers insights into parasite sharing among hosts. However, the specific traits that mediate transmission and the aspects of host community diversity that most effectively explain parasite infection rates remain unclear, even for the Bartonella genus, a vector-borne bacteria that causes persistent blood infections in vertebrates. Methods. This study investigated the association between rodent host traits and Bartonella infection, as well as how rodent community diversity affects the odds of infection in the Atlantic Forest, using generalized linear models. Additionally, we assessed how host traits and phylogenetic similarities influence Bartonella infection among mammal species in Brazil. To this end, rodents were sampled from ten municipalities in Rio de Janeiro, southeastern Brazil. Then, we calculated several diversity indices for each community, including Rényi’s diversity profiles, Fisher’s alpha, Rao’s quadratic entropy (RaoQ), Functional Diversity (FDis), Functional Richness (FRic), and Functional Evenness (FEve). Finally, we compiled a network encompassing all known interactions between mammal species and Bartonella lineages recorded in Brazil. Results. We found no significant relationship between diversity indices and the odds of Bartonella infection in rodent communities. Furthermore, there was no statistical support for the influence of individual-level traits (e.g., body length, sex, and age) or species-level ecological traits (e.g., locomotor habitat, dietary guild, and activity period) on Bartonella infection in rodents. A country-scale analysis, considering all mammal species, revealed no effect of host traits or phylogeny on Bartonella infection. Conclusions. This study highlighted wild mammals that share Bartonella lineages with livestock, synanthropic, and domestic animals, underscoring the complexity of their maintenance cycle within the One Health framework. A key question arising from our findings is whether molecular host–cell interactions outweigh host body mass and ecological traits in influencing Bartonella infection, potentially opening new avenues for understanding host–parasite relationships and infection ecology. |
|---|