DOI: 10.5061/dryad.q573n5tqv
title: Sleep deprivation drives brain-wide changes in cholinergic pre-synapse abundance in Drosophila melanogaster

description: Sleep is an evolutionarily conserved state that supports brain functions,
 including synaptic plasticity, in species across the animal kingdom. Here,
 we examine the neuroanatomical and cell-type distribution of pre-synaptic
 scaling in the fly brain after sleep loss. We previously found that sleep
 loss drives accumulation of the active zone scaffolding protein Bruchpilot
 (BRP) within cholinergic Kenyon cells of the Drosophila melanogaster
 mushroom body (MB), but not in other classes of MB neurons. To test
 whether similar cell-type specific trends in plasticity occur broadly
 across the brain, we used an flp-based genetic reporter to label
 pre-synaptic BRP in cholinergic, dopaminergic, GABAergic, or glutamatergic
 neurons. We then collected whole-brain confocal image stacks of BRP
 intensity to systematically quantify BRP, a marker of pre-synapse
 abundance, across 37 neuropil regions of the central fly brain. Our
 results indicate that sleep loss, either by overnight (12h) mechanical
 stimulation or chronic sleep disruption in insomniac mutants, broadly
 elevates cholinergic synapse abundance across the brain, while synapse
 abundance in neurons that produce other neurotransmitters undergoes
 weaker, if any, changes. Extending sleep deprivation to 24 hours drives
 brain-wide upscaling in glutamatergic, but not other, synapses. Finally,
 overnight male-male social pairings induce increased BRP in excitatory
 synapses despite male-female pairings eliciting more waking activity,
 suggesting experience-specific plasticity. Within neurotransmitter class
 and waking context, BRP changes are similar across the 37 neuropil
 domains, indicating that similar synaptic scaling rules may apply across
 the brain during acute sleep loss and that sleep need may broadly alter
 the excitatory-inhibitory balance in the central brain. 
description: 3-7 day old adult female flies were housed individually in 65mm
 borosilicate glass tubes (5mm diameter) containing fly food coated with
 paraffin wax on one end and a foam plug in the other. Locomotor activity
 was measured using Drosophila Activity Monitors from Trikinetics (Waltham
 MA, USA) and sleep was analyzed using Visual Basic macros in Microsoft
 Excel (1). Baseline sleep was monitored in all groups, and sleep
 deprivation was performed for 12 hours during the dark phase using
 mechanical stimulation via the SNAP method (1). All
 specimens were imaged on a Zeiss 880 laser scanning confocal microscope
 using a 20x objective with an optical slice thickness of 0.98 μm. Matching
 image acquisition settings were used for each brain within individual
 experiments. Whole brain confocal stacks were registered to an adult brain
 template (JFRC2010) from Janelia Research Campus (2) by performing affine
 and warp transformations within the CMTK Registration plugin for Fiji
 (3-5). Registered images were excluded from further analysis when we
 observed visible distortion or misalignment with the template stack. Each
 experiment was replicated using two to three independent batches of flies.
 Any neuropil region was excluded from analysis for an individual brain
 when at least 30% of pixels within that region were not successfully
 registered. References: 
 P. J. Shaw, G. Tononi, R. J. Greenspan, D. F. Robinson, Stress
 response genes protect against lethal effects of sleep deprivation in
 Drosophila. <em>Nature</em> <strong>417</strong>,
 287–291 (2002). A. Jenett, <em>et
 al.</em>, A GAL4-driver line resource for Drosophila neurobiology.
 <em>Cell Reports</em> <strong>2</strong>, 991–1001
 (2012). A. Ostrovsky, S. Cachero, G. S. X. E.
 Jefferis, Clonal Analysis of Olfaction in Drosophila: Image
 Registration. <em>Cold Spring Harb Protoc</em>
 <strong>2013</strong>, pdb.prot071738-pdb.prot071738
 (2013). S. Cachero, A. D. Ostrovsky, J. Y. Yu, B. J.
 Dickson, G. S. X. E. Jefferis, Sexual Dimorphism in the Fly
 Brain. <em>Curr Biol</em> <strong>20</strong>,
 1589–1601 (2010). J. Schindelin, <em>et
 al.</em>, Fiji: an open-source platform for biological-image
 analysis. <em>Nat Methods</em> <strong>9</strong>,
 676–682 (2012).
description: # Sleep deprivation drives brain-wide changes in cholinergic pre-synapse
 abundance in *Drosophila melanogaster*
 [https://doi.org/10.5061/dryad.q573n5tqv](https://doi.org/10.5061/dryad.q573n5tqv) Image segmentation and analysis code for fly brain images registered to JFRC2010 anatomical template (1). Python scripts were prepared in Jupyter Notebooks 6.4.3. Example confocal stacks imaged on Zeiss LSM 880, then registered to JFRC2010 template using affine and warp transformations in the CMTK Registration Template for FIJI (2-4). 1. A. Jenett, *et al.*, A GAL4-driver line resource for Drosophila neurobiology. *Cell Reports* 2, 209  991–1001 (2012). 2. A. Ostrovsky, S. Cachero, G. S. X. E. Jefferis, Clonal Analysis of Olfaction in Drosophila: Image Registration. *Cold Spring Harb Protoc* 2013, pdb.prot071738-pdb.prot071738 (2013). 3. S. Cachero, A. D. Ostrovsky, J. Y. Yu, B. J. Dickson, G. S. X. E. Jefferis, Sexual Dimorphism in the Fly Brain. *Curr Biol* 20, 1589–1601 (2010). 4. J. Schindelin, *et al.*, Fiji: an open-source platform for biological-image analysis. *Nat Methods*  9, 676–682 (2012). ## Description of the data and file structure **Sample Images.zip** contains experimental data from one cohort of registered images from Chat-2A-Gal4&gt;STaR flies that were either allowed ad libitum sleep (con) or 12h of overnight sleep deprivation (SD). **Sample outputted data.zip** contains files produced by using our Python scripts to analyze the image data contained within Sample Images.zip. Output files include: **1) Individual pixel intensity histograms:** * histobins_con_051923.csv - relative pixel fluorescence intensity for bins used to generate a histogram for control brains ( values normalized to mean pixel intensity from the control group) * histobins_sd_051923.csv - relative pixel fluorescence intensity for bins used to generate a histogram for SD brains (values normalized to mean pixel intensity from the control group) * histovalues_con_051923.csv - distribution of relative pixel intensities within bin sizes from "histobins_con_051923.csv" * histovalues_sd_051923.csv - distribution of relative pixel intensities within bin sizes from "histobins_sd_051923.csv" * histogram_sd_vs_con_normalizedScalar_051923.jpg - image file plotting histograms of normalized pixel intensities using values in files listed above **2) Neuropil region mean values and variances:** * sample_region_means_051923.csv - mean normalized pixel intensity values for each brain (rows) across local neuropil regions (columns). The second column denotes the experimental group (SD or con) for each brain. All values are normalized to the mean pixel intensity from the control group. * sample_region_vars_051923.csv - variance values for each brain (rows) across local neuropil regions (columns). The second column denotes the experimental group (SD or con) for each brain. * sample_con_region_means_051923.csv - mean normalized pixel intensity values for each brain (rows) across local neuropil regions (columns) for samples from the rested control group (con). All values are normalized to the mean pixel intensity from the control group. * sample_con_region_vars_051923.csv - variance values for each brain (rows) across local neuropil regions (columns) for samples from the rested control group (con). * sample_SD_region_means_051923.csv - mean normalized pixel intensity values for each brain (rows) across local neuropil regions (columns) for samples from the SD group. All values are normalized to the mean pixel intensity from the control group. * sample_SD_region_vars_051923.csv - variance values for each brain (rows) across local neuropil regions (columns) for samples from the SD group. * sample_batchnormalized_combinedbilaterals_region_means_con_051923.csv - mean normalized pixel intensity values for each brain (rows) across local neuropil regions (columns) for samples from the rested control group (con). In this file, neuropil regions with bilateral structures (L and R) are pooled into a single value. All values are normalized to the mean pixel intensity from the control group. * sample_batchnormalized_combinedbilaterals_region_means_SD_051923.csv - mean normalized pixel intensity values for each brain (rows) across local neuropil regions (columns) for samples from the SD group. In this file, neuropil regions with bilateral structures (L and R) are pooled into a single value. All values are normalized to the mean pixel intensity from the control group. * sample_batchnormalized_combinedbilaterals_region_vars_con_051923.csv - variance values for each brain (rows) across local neuropil regions (columns) for samples from the rested control group (con). In this file, neuropil regions with bilateral structures (L and R) are pooled into a single value. All values are normalized to the mean pixel intensity from the control group. * sample_batchnormalized_combinedbilaterals_region_vars_SD_051923.csv - variance values for each brain (rows) across local neuropil regions (columns) for samples from rested control group (con). In this file, neuropil regions with bilateral structures (L and R) are pooled into a single value. All values are normalized to the mean pixel intensity from the SD group. **3) Matrix files** * justcon_filled_051923.npy - Matrix file compiling individual pixel intensity values for each sample in the rested control group (con). * justsd_filled_051923.npy - Matrix file compiling individual pixel intensity values for each sample in the rested control group (SD). * justcon_filled_normalizedScalar_051923.npy - Matrix compiling individual pixel intensity values for each sample in the rested control group (con). Values are normalized to the overall mean pixel intensity value from the con group samples. * justsd_filled_normalizedScalar_051923.npy - Matrix compiling individual pixel intensity values for each sample in the SD group (SD). Values are normalized to the overall mean pixel intensity value from the con group samples. **general files for setup.zip** contains files required to segment whole brain pixel values into localized data for each neuropil region. **user guide.txt** includes step-by-step instructions for analyzing example image data using included Python code files. ## Code: Included Python code files (see user guide.txt for step-by-step usage instructions): * **1_Feature_Construction_SDvsControl_050423.ipynb** - accesses registered confocal images, reads pixel intensity values from each brain * **2_mean_variance_comparisons_SDvsControl_050423.ipynb** - normalizes pixel intensity values to mean intensity from control samples, segments whole brain data to regional neuropils, outputs region-by-region results * **3_pixel_intensity_distributions_050423.ipynb** - plots pixel intensity distributions into histograms * **functions_feature_construction.ipynb** - functions required to transform pixel intensity values from registered images into data vectors, sort values by neuropil region * **Mean_and_Variance_Comparisons.ipynb** - functions to generate mean and variance output files by neuropil region * **Region_Mean_Variable_Loadings_Central.ipynb** - functions related to PCA analysis of whole brain data * All Python code was generated, edited, and run in Jupyter Notebook.