Modeling seasonal immune dynamics of honey bee

The honey bee, Apis mellifera L., is one of the main pollinators worldwide. In a temperate climate, seasonality affects the life span, behavior, physiology, and immunity of honey bees. In consequence, it impacts their interaction with pathogens and parasites. In this study, we used Bayesian statisti...

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Bibliographic Details
Published in:PloS one 2024-10, Vol.19 (10), p.e0311415
Main Authors: Hurychová, Jana, Dostál, Jakub, Kunc, Martin, Sreibr, Sara, Dostálková, Silvie, Petrivalský, Marek, Hyrsl, Pavel, Titera, Dalibor, Danihlík, Jirí, Dobes, Pavel
Format: Article
Language:English
Subjects:
Analysis
Environmental aspects
Honeybee
Host-bacteria relationships
Immune response
Nocardia corallina
Physiological aspects
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Summary:The honey bee, Apis mellifera L., is one of the main pollinators worldwide. In a temperate climate, seasonality affects the life span, behavior, physiology, and immunity of honey bees. In consequence, it impacts their interaction with pathogens and parasites. In this study, we used Bayesian statistics and modeling to examine the immune response dynamics of summer and winter honey bee workers after injection with the heat-killed bacteria Serratia marcescens, an opportunistic honey bee pathogen. We investigated the humoral and cellular immune response at the transcriptional and functional levels using qPCR of selected immune genes, antimicrobial activity assay, and flow cytometric analysis of hemocyte concentration. Our data demonstrate increased antimicrobial activity at transcriptional and functional levels in summer and winter workers after injection, with a stronger immune response in winter bees. On the other hand, an increase in hemocyte concentration was observed only in the summer bee population. Our results indicate that the summer population mounts a cellular response when challenged with heat-killed S. marcescens, while winter honey bees predominantly rely on humoral immune reactions. We created a model describing the honey bee immune response dynamics to bacteria-derived components by applying Bayesian statistics to our data. This model can be employed in further research and facilitate the investigating of the honey bee immune system and its response to pathogens.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0311415