Drosophila TRPγ is required in neuroendocrine cells for post-ingestive food selection

The mechanism through which the brain senses the metabolic state, enabling an animal to regulate food consumption, and discriminate between nutritional and non-nutritional foods is a fundamental question. Flies choose the sweeter non-nutritive sugar, L-glucose, over the nutritive D-glucose if they are not starved. However, under starvation conditions, they switch their preference to D-glucose, and this occurs independent of peripheral taste neurons. Here, we found that eliminating the TRPγ channel impairs the ability of starved flies to choose D-glucose. This food selection depends on trpγ expression in neurosecretory cells in the brain that express diuretic hormone 44 (DH44). Loss of trpγ increases feeding, alters the physiology of the crop, which is the fly stomach equivalent, and decreases intracellular sugars and glycogen levels. Moreover, survival of starved trpγ flies is reduced. Expression of trpγ in DH44 neurons reverses these deficits. These results highlight roles for TRPγ in coordinating feeding with the metabolic state through expression in DH44 neuroendocrine cells.


Sample-size estimation
• You should state whether an appropriate sample size was computed when the study was being designed • You should state the statistical method of sample size computation and any required assumptions • If no explicit power analysis was used, you should describe how you decided what sample (replicate) size (number) to use Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission:

Replicates
• You should report how often each experiment was performed • You should include a definition of biological versus technical replication • The data obtained should be provided and sufficient information should be provided to indicate the number of independent biological and/or technical replicates • If you encountered any outliers, you should describe how these were handled • Criteria for exclusion/inclusion of data should be clearly stated • High-throughput sequence data should be uploaded before submission, with a private link for reviewers provided (these are available from both GEO and ArrayExpress) Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: No statistical methods were used to pre-determine sample sizes. We used similar sample sizes as has been reported in previous publications from multiple research groups. The information is presented in the "Statistical analyses" section of the Methods.
We provide all the n value in Figure legends for each experiment. Furthermore, the information is provided in the "source data" as well.

Statistical reporting
• Statistical analysis methods should be described and justified • Raw data should be presented in figures whenever informative to do so (typically when N per group is less than 10) • For each experiment, you should identify the statistical tests used, exact values of N, definitions of center, methods of multiple test correction, and dispersion and precision measures (e.g., mean, median, SD, SEM, confidence intervals; and, for the major substantive results, a measure of effect size (e.g., Pearson's r, Cohen's d) • Report exact p-values wherever possible alongside the summary statistics and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05.
Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: (For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
• Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied • Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Additional data files ("source data") • We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table • Where provided, these should be in the most useful format, and they can be uploaded as "Source data" files linked to a main figure or table • Include model definition files including the full list of parameters used • Include code used for data analysis (e.g., R, MatLab) • Avoid stating that data files are "available upon request" Please indicate the figures or tables for which source data files have been provided: The methods for the Statistical analysis are described in "Statistical analyses" section of the Materials and Methods. The statistical tests used in each experiment are described the figure legends. We used scatter plots to present the raw data. Individual data points were identified as dots with bar graphs. The exact n values are provided in figure legends. The bars represent the means and SEMs, and this information is provided in the figure legends. The exact P-values are reported in the summary statistics table, which is provided as a "source data" file.
The group allocation information is presented in "Group allocation" section in the Methods.