A MALDI–MS Profiling to Address Honey Bee Health Status under Bacterial Challenge through Computational Modeling

International audienceHoney bees play a critical role in the maintenance of plant biodiversity and sustainability of food webs. In the past few decades, bees have been subjected to biotic and abiotic threats causing various colony disorders. Therefore, monitoring solutions to help beekeepers to improve bee health are necessary. Matrix‐assisted laser desorption ionization–mass spectrometry (MALDI–MS) profiling has emerged within this decade as a powerful tool to identify in routine micro‐organisms and is currently used in real‐time clinical diagnosis. MALDI BeeTyping is developed to monitor significant hemolymph molecular changes in honey bees upon infection with a series of entomopathogenic Gram‐positive and ‐negative bacteria. A Serratia marcescens strain isolated from one naturally infected honey bee collected from the field is also considered. A series of hemolymph molecular mass fingerprints is individually recorded and to the authors' knowledge, the first computational model harboring a predictive score of 97.92% and made of nine molecular signatures that discriminate and classify the honey bees’ systemic response to the bacteria is built. Hence, the model is challenged by classifying a training set of hemolymphs and an overall recognition of 91.93% is obtained. Through this work, a novel, time and cost saving high‐throughput strategy that addresses honey bee health on an individual scale is introduced