Abstracts (first author)

Talk 

Immune-based maternal effects in response to experimental manipulation of bacterial load in tree swallow nests

Author(s): Forsman AM

Summary:

Birds encounter a variety of bacteria in their environment on a daily basis. The vast majority of these organisms likely exert minimal direct effects on avian fitness, while others may exert negative pathogenic effects or conversely, positive probiotic effects. Regardless of pathogenicity, the antigenic properties of many bacteria likely contribute to variation in immune status among individual birds at any given time. Some of this variation may in turn be inherited from mother to offspring through the deposition of protective immune compounds into eggs. Neonates may be especially sensitive to environmental bacteria during the first weeks of life, before the immune system is fully developed and the gut microbiota established. And thus, variation in female exposure to bacteria prior to egg-laying may result in indirect fitness consequences through maternal effects on early offspring immune phenotype. In this study, I manipulated bacterial load in tree swallow nests during nest-building and egg-laying to explore bacterial effects on female investment in egg defenses and on offspring growth and immune status. Contrary to my predictions, eggs collected from nestboxes with added bacteria contained lower concentrations and total amounts of yolk antibodies than eggs from control nests. These patterns, observed for total yolk antibodies, were also reflected in nestling plasma samples. Nestlings whose mothers were exposed to increased bacterial load also exhibited lower bactericidal capacity than control nestlings at six days post-hatch, but not at twelve days post-hatch. No differences in nestling size, growth, or PHA responsiveness were observed among treatment groups.



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Address

XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon
Portugal

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Computational Biology & Population Genomics Group 
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