The Diagnostic Value of qPCR Quantification of <i>Paenibacillus larvae</i> in Hive Debris and Adult Bees for Predicting the Onset of American Foulbrood

Abstract

American foulbrood (AFB) is a serious infectious disease of honeybees (Apis mellifera) caused by Paenibacillus larvae. Increased P. larvae count in hive-related material is associated with an increased risk of AFB. Here, we quantified P. larvae cells in 106 adult bee and 97 hive debris samples using quantitative PCR (qPCR); 66/106 adult bee and 66/97 hive debris samples were collected simultaneously from the same bee colony (paired-sample design). The corresponding bee colonies were also examined for the presence of AFB clinical signs. A binary logistic regression model to distinguish between AFB-affected and unaffected honeybee colonies showed a strong diagnostic accuracy of both sample types for predicting the onset of AFB based on P. larvae counts determined by qPCR. The colonies with a P. larvae count greater than 4.5 log cells/adult bee or 7.3 log cells/mL hive debris had a 50% probability of being clinically affected and were categorized as high-risk. The AFB-unaffected colonies had significantly lower P. larvae counts than the AFB-affected colonies, but the latter did not differ significantly in P. larvae counts in relation to the severity of clinical signs. Both bee-related sample types had a high diagnostic value for predicting disease outcome based on P. larvae counts. These results improve the understanding of the relationship between P. larvae counts and AFB occurrence, which is essential for early detection of high-risk colonies.

Keywords

• <i>Paenibacillus larvae</i>
• American foulbrood
• quantitative PCR
• logistic regression