Inter-organ Wingless/Ror/Akt signaling regulates nutrient-dependent hyperarborization of somatosensory neurons.

Nutrition in early life has profound effects on an organism, altering processes such as organogenesis. However, little is known about how specific nutrients affect neuronal development. Dendrites of class IV dendritic arborization neurons in Drosophila larvae become more complex when the larvae are reared on a low-yeast diet compared to a high-yeast diet. Our systematic search for key nutrients revealed that the neurons increase their dendritic terminal densities in response to a combined deficiency in vitamins, metal ions, and cholesterol. The deficiency of these nutrients upregulates Wingless in a closely located tissue, body wall muscle. Muscle-derived Wingless activates Akt in the neurons through the receptor tyrosine kinase Ror, which promotes the dendrite branching. In larval muscles, the expression of wingless is regulated not only in this key nutrient-dependent manner, but also by the JAK/STAT signaling pathway. Additionally, the low-yeast diet blunts neuronal light responsiveness and light avoidance behavior, which may help larvae optimize their survival strategies under low-nutritional conditions. Together, our studies illustrate how the availability of specific nutrients affects neuronal development through inter-organ signaling.

Interspecies Comparative Analyses Reveal Distinct Carbohydrate-Responsive Systems among Drosophila Species.

During evolution, organisms have acquired variable feeding habits. Some species are nutritional generalists that adapt to various food resources, while others are specialists, feeding on specific resources. However, much remains to be discovered about how generalists adapt to diversified diets. We find that larvae of the generalists Drosophila melanogaster and D. simulans develop on three diets with different nutrient balances, whereas specialists D. sechellia and D. elegans cannot develop on carbohydrate-rich diets. The generalist D. melanogaster downregulates the expression of diverse metabolic genes systemically by transforming growth factor ß (TGF-ß)/Activin signaling, maintains metabolic homeostasis, and successfully adapts to the diets. In contrast, the specialist D. sechellia expresses those metabolic genes at higher levels and accumulates various metabolites on the carbohydrate-rich diet, culminating in reduced adaptation. Phenotypic similarities and differences strongly suggest that the robust carbohydrate-responsive regulatory systems are evolutionarily retained through genome-environment interactions in the generalists and contribute to their nutritional adaptabilities.

DeTerm: Software for automatic detection of neuronal dendritic branch terminals via an artificial neural network.

Dendrites of neurons receive and process synaptic or sensory inputs. The Drosophila class IV dendritic arborization (da) neuron is an established model system to explore molecular mechanisms of dendrite morphogenesis. The total number of dendritic branch terminals is one of the frequently employed parameters to characterize dendritic arborization complexity of class IV neurons. This parameter gives a useful phenotypic readout of arborization during neurogenesis, and it is typically determined by laborious manual analyses of numerous images. Ideally, an automated analysis would greatly reduce the workload; however, it is challenging to automatically discriminate dendritic branch terminals from signals of surrounding tissues in whole-mount live larvae. Here, we describe our newly developed software, called DeTerm, which automatically recognizes and quantifies dendrite branch terminals via an artificial neural network. Once we input an image file of a neuronal dendritic arbor and its region of interest information, DeTerm is capable of labeling terminals of larval class IV neurons with high precision, and it also provides positional data of individual terminals. We further show that DeTerm is applicable to other types of neurons, including mouse cerebellar Purkinje cells. DeTerm is freely available on the web and was successfully tested on Mac, Windows and Linux.