Submitted to: Apidologie
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/7/2001
Publication Date: N/A
Interpretive Summary: Genetic approaches have long been used to improve honey bee breeding stock. New approaches in molecular biology can speed the search for genes involved with honey bee disease resistance or tolerance. One such approach is to measure the expression (activity) patterns of specific genes that respond to diseases or stress. Here I use nylon-membrane, or 'macro-array', analyses of gene expression to search for genes involved with disease responses in honey bees. This technique shows promise as an inexpensive way to identify useful disease-related genes in honey bees. Government and University scientists can then use these identified genes to improve the breeding stock of honey bees through selective breeding.
Technical Abstract: Numerous genes have been characterized whose expression patterns vary with the age, sex, and caste of developing female honey bees. Some of these genes might also be more general indicators of honey bee stress and nutritional health. For example, we have identified two novel heat-shock proteins, in the hsp70 and hsp90 families, respectively. These proteins are implicated in both larval stress responses and the packaging of new proteins by larvae. Consequently, they might provide needed indicators of honey bee health or disease pathology. We have also characterized several members of the hexamerin family of storage proteins. In other social insects, and in insects generally, storage proteins play a role in packaging amino acids during larval development, for use in metamorphosis. More generally, screenings of this sort for differential gene expression should compliment ongoing efforts to identify disease response genes in honey bees. With the identification of such genes, tests across honey bee stocks for their expression levels should aid honey bee breeding programs and a general understanding of the tolerance or susceptibility of honey bees to disease.