Maintenance of biological functions under negative energy balance depends on mobilization of storage lipids and carbohydrates in animals. In mammals, glucagon and glucocorticoid signaling mobilizes energy reserves, whereas adipokinetic hormones (AKHs) play a homologous role in insects. Numerous studies based on AKH injections and correlative studies in a broad range of insect species established the view that AKH acts as master regulator of energy mobilization during development, reproduction, and stress. In contrast to AKH, the second peptide, which is processed from the Akh encoded prohormone [termed "adipokinetic hormone precursor-related peptide" (APRP)] is functionally orphan. APRP is discussed as ecdysiotropic hormone or as scaffold peptide during AKH prohormone processing. However, as in the case of AKH, final evidence for APRP functions requires genetic mutant analysis. Here we employed CRISPR/Cas9-mediated genome engineering to create AKH and AKH plus APRP-specific mutants in the model insect Drosophila melanogaster. Lack of APRP did not affect any of the tested steroid-dependent processes. Similarly, Drosophila AKH signaling is dispensable for ontogenesis, locomotion, oogenesis, and homeostasis of lipid or carbohydrate storage until up to the end of metamorphosis. During adulthood, however, AKH regulates body fat content and the hemolymph sugar level as well as nutritional and oxidative stress responses. Finally, we provide evidence for a negative autoregulatory loop in Akh gene regulation.KEYWORDS Drosophila; adipokinetic hormone; adipokinetic hormone precursor-related peptide; energy homeostasis; stress resistance E NERGY homeostasis requires continuous compensation for fluctuations in the energy expenditure and availability of food resources. Organisms thus build up reserves under positive energy balance and catabolize them when the balance turns negative to retain stable levels of circulating energy fuel. Insulin signaling induces the uptake of excessive circulating sugars, thus promoting reserve accumulation (reviewed, e.g., in Saltiel and Kahn 2001; Cohen 2006), whereas energy mobilization is under the control of glucagon and glucocorticoid signaling in mammals (reviewed, e.g., in Rui 2014;Charron and Vuguin 2015) and adipokinetic hormone (AKH) signaling in insects (reviewed, e.g., in Van der Horst 2003;Lorenz and Gäde 2009;Bednářová et al. 2013a). Consistent with their fundamental physiological function in energy mobilization, AKHs are found not only in insects, but are common in Protostomia, where they have been identified both in Ecdyszoa (in Arthropoda, Tardigrada, and Priapulida) and Lophotrochozoa (in Mollusca, Rotifera, and Annelida) (Gäde 2009;Hauser and Grimmelikhuijzen 2014). Nevertheless, physiological functions of AKHs have been studied mainly in Arthropoda. Similar to mammals, also insects store lipids in the form of triacylglycerides (TGs) and as carbohydrates in the form of glycogen. The main storage organ for lipid and glycogen in insects is the fat body, which can thus b...

Much has been learned about the genetics of aging from studies in model organisms, but still little is known about naturally occurring alleles that contribute to variation in longevity. For example, analysis of mutants and transgenes has identified insulin signaling as a major regulator of longevity, yet whether standing variation in this pathway underlies microevolutionary changes in lifespan and correlated fitness traits remains largely unclear. Here, we have analyzed the genomes of a set of Drosophila melanogaster lines that have been maintained under direct selection for postponed reproduction and indirect selection for longevity, relative to unselected control lines, for over 35 years. We identified many candidate loci shaped by selection for longevity and late‐life fertility, but – contrary to expectation – we did not find overrepresentation of canonical longevity genes. Instead, we found an enrichment of immunity genes, particularly in the Toll pathway, suggesting that evolutionary changes in immune function might underpin – in part – the evolution of late‐life fertility and longevity. To test whether this genomic signature is causative, we performed functional experiments. In contrast to control flies, long‐lived flies tended to downregulate the expression of antimicrobial peptides upon infection with age yet survived fungal, bacterial, and viral infections significantly better, consistent with alleviated immunosenescence. To examine whether genes of the Toll pathway directly affect longevity, we employed conditional knockdown using in vivo RNAi. In adults, RNAi against the Toll receptor extended lifespan, whereas silencing the pathway antagonist cactus‐–causing immune hyperactivation – dramatically shortened lifespan. Together, our results suggest that genetic changes in the age‐dependent regulation of immune homeostasis might contribute to the evolution of longer life.

The major goal of evolutionary thermal biology is to understand how variation in temperature shapes phenotypic evolution. Temperature is a crucial environmental factor that affects all biological processes and has major effects on physiology and fitness of ectotherms. Insights into how organisms adapt to different thermal environments are particularly important for a better understanding of life-history variation in ectotherms (Clarke 1993;Angilletta 2009). The effects of temperature on performance are usually and most completely described by thermal performance curves, a type of thermal reaction norm (Huey and Stevenson 1979; Fig. S1). Thermal performance curves are defined by several biologically important parameters: the temperature at which performance is maximal, the optimal temperature (T opt ); the breadth of the range over which performance is above some arbitrary level, called performance breadth (B, i.e., a measure of spread of the curve); and the critical thermal limits that permit performance (CT min and CT max ; Angilletta et al. 2002). Thermal performance curves are usually asymmetrically bell shaped, with a gradual increase from the lowest temperature up to the optimal temperature where performance is maximal, followed by a steep decline in performance for temperatures higher than the optimal temperature (Dewitt and Friedmann 1979). Physiologically, two phases Comparing thermal reaction norms among populations from different thermal environments allows us to gain insights into

The life history of the fruit fly (Drosophila melanogaster) is well understood, but fitness components are rarely measured by following single individuals over their lifetime, thereby limiting insights into lifetime reproductive success, reproductive senescence and post-reproductive lifespan. Moreover, most studies have examined long-established laboratory strains rather than freshly caught individuals and may thus be confounded by adaptation to laboratory culture, inbreeding or mutation accumulation. Here, we have followed the life histories of individual females from three recently caught, non-laboratory-adapted wild populations of D. melanogaster. Populations varied in a number of life-history traits, including ovariole number, fecundity, hatchability and lifespan. To describe individual patterns of age-specific fecundity, we developed a new model that allowed us to distinguish four phases during a female's life: a phase of reproductive maturation, followed by a period of linear and then exponential decline in fecundity and, finally, a post-ovipository period. Individual females exhibited clear-cut fecundity peaks, which contrasts with previous analyses, and post-peak levels of fecundity declined independently of how long females lived. Notably, females had a pronounced post-reproductive lifespan, which on average made up 40% of total lifespan. Post-reproductive lifespan did not differ among populations and was not correlated with reproductive fitness components, supporting the hypothesis that this period is a highly variable, random 'add-on' at the end of reproductive life rather than a correlate of selection on reproductive fitness. Most life-history traits were positively correlated, a pattern that might be due to genotype by environment interactions when wild flies are brought into a novel laboratory environment but that is unlikely explained by inbreeding or positive mutational covariance caused by mutation accumulation.