Age-specific variation in immune response in Drosophila melanogaster has a genetic basis

Abstract

Immunosenescence, the age-related decline in immune system function, is a general hallmark of aging. While much is known about the cellular and physiological changes that accompany immunosenescence, we know little about the genetic influences on this phenomenon. In this study we combined age-specific measurements of bacterial clearance ability following infection with whole-genome measurements of the transcriptional response to infection and wounding to identify genes that contribute to the natural variation in immunosenescence, using Drosophila melanogaster as a model system. Twenty inbred lines derived from nature were measured for their ability to clear an Escherichia coli infection at 1 and 4 weeks of age. We used microarrays to simultaneously determine genome-wide expression profiles in infected and wounded flies at each age for 12 of these lines. Lines exhibited significant genetically based variation in bacterial clearance at both ages; however, the genetic basis of this variation changed dramatically with age. Variation in gene expression was significantly correlated with bacterial clearance ability only in the older age group. At 4 weeks of age variation in the expression of 247 genes following infection was associated with genetic variation in bacterial clearance. Functional annotation analyses implicate genes involved in energy metabolism including those in the insulin signaling/TOR pathway as having significant associations with bacterial clearance in older individuals. Given the evolutionary conservation of the genes involved in energy metabolism, our results could have important implications for understanding immunosenescence in other organisms, including humans.

Figure 1

Mean colony counts (±SE) for the 20 lines screened for ability to clear E. coli infection at 1 and 4 weeks of age. The solid lines indicate the lines used in the microarray study. Note that a high colony count represents poor bacterial clearance ability whereas a lower colony counts represents better clearance ability.

Figure 2

Examples of candidate genes with significant correlations between variation in transcript level and bacterial-clearance ability at 4 weeks of age. Peptidoglycan receptor protein-LC (A) and 18 wheeler (B) are immune response candidate genes; Fatty acid synthase (C) and Gonadotropin-releasing hormone receptor (D) are lipid metabolism candidate genes; and RAC serine/threonine-protein kinase or Akt (E) and mos/CG8767 (F) are also shown. Note that variation in the expression of gonadotropin-releasing hormone receptor and mos was negatively correlated with colony counts and expression levels of the remaining candidates were positively correlated with colony counts.

Figure 3

Functional categorization of candidate genes with significant correlations between variation in transcript level and bacterial-clearance ability at 4 weeks of age. Functional groups shown contain ≥5 genes with similar molecular function gene ontology annotation terms according to FlyBase. The 260 candidate genes were categorized into 11 groups that included enzymes, transcription factors, transcriptional regulatory proteins, transport proteins, cytoskeletal-binding proteins, metal ion-binding proteins, nucleic acid-binding proteins, protein-binding proteins, unknown function, miscellaneous, and immune response. The miscellaneous group contains annotated genes that had <5 members and unknown genes had no recorded molecular function in FlyBase.