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The mRNA export factor UAP56 is required for dendrite and synapse pruning via actin regulation in drosophila

Neurite and synapse pruning are conserved mechanisms that adapt neuronal circuitry to different developmental stages. Drosophila sensory c4da neurons prune their larval dendrites and their presynaptic terminals during metamorphosis using a gene expression programme that is induced by the steroid hormone ecdysone and involves posttranscriptional regulation pathways. Here we show that loss of the helicase UAP56, an important mediator of nuclear mRNA export, causes strong dendrite and presynapse pruning defects. Loss of UAP56 is linked to actin regulation, as it causes defects in the ecdysone-induced expression of the actin severing enzyme Mical during metamorphosis and actin accumulation at pruning presynapses. In support of an important role of actin regulation during presynaptic pruning, we find that cofilin is required for this process. Our findings highlight the role of posttranscriptional regulation in neuronal remodeling and identify an actin disassembly factor required for presynapse pruning.

Quantifying Drosophila Feeding Behavior Using flyPAD and optoPAD

Quantifying feeding behavior with high temporal and spatial precision is critical for understanding how internal state, sensory cues, and neural activity shape food intake and dietary choice. Here, we describe a detailed protocol for performing consumption and dietary choice assays in Drosophila using the flyPAD/optoPAD system. This method enables simultaneous measurement of feeding events across multiple arenas while allowing precise control of gustatory stimuli and optogenetic stimulation. We provide step-by-step instructions for assay food preparation, flyPAD arena setup, data acquisition, and downstream data organization with suggested analyses. This approach is suitable for studying consumption, nutrient preference, learning, and state-dependent modulation of feeding behaviors, and can be readily adapted for optogenetic manipulations and comparative choice assays. Highlights ### Competing Interest Statement The authors have declared no competing interest. National Institute of General Medical Sciences, R35GM147504

Natural statistics of host odours predict species-specific olfactory behaviours in Drosophilids

Animals rely on olfaction to locate food, mates, and suitable habitats, yet natural odour environments contain thousands of volatile molecules, creating a high-dimensional sensory problem for both nervous systems and the researchers who study them. For example, a banana emits around 100 individual volatiles. It remains unclear which components of complex odour blends animals have evolved to use as behavioural cues. Here, combining fieldwork, chemical and behavioural analyses, we show across multiple Drosophila species that behaviourally relevant cues can be predicted directly from the statistical structure of natural odour environments. Animals preferentially respond to components that are most distinctive within their natural host odour blends, and therefore most ecologically informative. These cues can be either major or minor blend components. Our results indicate that host-guided olfactory behaviours have evolved to exploit the statistical structure of natural odour environments by selectively targeting the most informative features of odour blends. ### Competing Interest Statement The authors have declared no competing interest. European Research Council, https://ror.org/0472cxd90, 802531 Paul G. Allen Family Foundation, https://ror.org/01degd278, Distinguished investigator award International Human Frontier Science Program Organization, https://ror.org/02ebx7v45, RGY0052/2022 Vallee Foundation Chan Zuckerberg Initiative (United States), https://ror.org/02qenvm24, CP-2-1-Prieto-Godino The Francis Crick Institute, CC2067 Cancer Research UK, https://ror.org/054225q67, CC2067 Wellcome Trust, https://ror.org/029chgv08, CC2067 Medical Research Council, https://ror.org/03x94j517, CC2067

Environmental statistics and sensory experience shape patch foraging strategies in Drosophila larvae

Animals foraging in patchy environments must balance exploiting current resources with exploring for better alternatives to maximize resource intake and to survive. However, the neural and computational mechanisms underlying such adaptive decisions have just recently begun to be understood. Using Drosophila larvae as an experimentally tractable model, we combine long-timescale behavioral tracking in controlled patchy environments with varying statistics, along with quantitative analysis and computational modeling, to dissect foraging decision strategies. We show that larvae flexibly adjust their behavior according to both the quality and valence of available resources, shaped by prior foraging experience. A simple integration model recapitulates larval patch-leaving behavior, with model parameters tuned by environmental statistics and foraging history. Together, these findings establish Drosophila larvae as a powerful system for studying adaptive foraging and for uncovering the neural circuit mechanisms that implement experience-dependent foraging decisions. ### Competing Interest Statement The authors have declared no competing interest. Deutsche Forschungsgemeinschaft, EXC 2117-422037984 International Human Frontier Science Program Organization, RGP006/2025