DOI: 10.5061/dryad.t4b8gtj77
title: Data from: An essential experimental control for functional connectivity mapping with optogenetics

description: To establish functional connectivity between two candidate neurons that
 might form a circuit element, a common approach is to activate an
 optogenetic tool such as Chrimson in the candidate pre-synaptic neuron and
 monitor fluorescence of the calcium-sensitive indicator GCaMP in a
 candidate post-synaptic neuron. While performing such experiments in
 Drosophila, we found that low levels of leaky Chrimson expression can lead
 to strong artifactual GCaMP signals in presumptive postsynaptic neurons
 even when Chrimson is not intentionally expressed in any particular
 neurons. Withholding all-trans retinal, the chromophore required as a
 co-factor for Chrimson response to light, eliminates GCaMP signal but does
 not provide an experimental control for leaky Chrimson expression. Leaky
 Chrimson expression appears to be an inherent feature of current Chrimson
 transgenes, since artifactual connectivity was detected with Chrimson
 transgenes integrated into multiple genomic locations. While these
 false-positive signals may complicate the interpretation of functional
 connectivity experiments, we illustrate how a no-Gal4 negative control
 improves interpretability of functional connectivity assays. We also
 propose a simple but effective procedure to identify experimental
 conditions that minimize potentially incorrect interpretations caused by
 leaky Chrimson expression.
description: <strong>Calcium imaging in the
 larva</strong> The CNS of larvae at the
 3<sup>rd</sup> instar developmental stage was dissected in
 saline (135 mM NaCl, 5 mM KCl, 4 mM MgCl2, 1.8 mM Trehalose, 12.6mM
 Sucrose, 2mM CaCl2) and placed dorsal side down on a lysine-coated
 coverslip. We used a Hyperscope two-photon scanning microscope
 (Scientifica, UK) with a MaiTai laser (Spectra Physics, CA, USA). For
 imaging, we used a two-photon excitation wavelength of 920 nm. When
 CsChrimson was stimulated with 590nm (e.g., Figure 1b), an amber LED
 (LCS-0590-03-22, Mightex, Canada) with peak wavelength at 590 nm and a
 605/55 bandpass filter (Chroma, VT, US) was used. In Figure 3, CsChrimson
 was activated with a red LED (LCS-0656-03-22, Mightex, Canada) with peak
 wavelength at 656 nm and a 650/10 bandpass filter (Chroma, VT, US). To
 feed the CsChrimson excitation light into the light path, we used a 560LP
 dichroic (T560LPXRXT-UF1, Chroma, VT, USA). The power of the LED from the
 objective was measured with a PM100D Power meter with an S170C Power
 sensor (Thorlabs, NJ, USA). To estimate the power at the larval brain, we
 divided the measured total LED power by the area of the field of view of
 the objective (XLPLN25XWMP2, Olympus, Japan). For each
 trial, the neuron was observed for 20 seconds. Each trial was repeated 5
 times. Data was analyzed using custom python scripts. Raw data was first
 filtered using a Savitzky-Golay filter (1-second window length,
 2<sup>nd</sup> order polynomial). The signal was calculated as
 described previously (Jia et al., 2011). Briefly, an ROI was chosen to
 contain a segment of the axonal branch. A second ROI away from the neuron
 was defined as the background. The background was subtracted from the ROI
 to correct for stimulus light bleed-through. Next, for each frame
 F<sub>i</sub>, signals were computed as the relative change in
 fluorescence intensity from the baseline: ΔF/F<sub>0 </sub>=
 (F<sub>i</sub>-F<sub>0</sub>)/F<sub>0</sub>. Baseline fluorescence F<sub>0</sub> was defined as the mean pixel intensity of the 3-second time window preceding the optogenetic stimulus. Preliminary experiments showed that many but not all preparations show calcium transients. For the larva (Figures 1, 3, and 6), the experiments were performed using the algorithm described in Figure S1: each dissected brain was stimulated using the same 2-second 73 uW/mm2 step stimulus. If an obvious response was detected the whole dataset was acquired. If no obvious response was detected, the brain was discarded, and another brain was dissected and tested. For the 6<sup>th</sup> preparation in a row, imaging was performed irrespective of the presence of a response to initial 2-second step stimulus at one of the four chosen ROIs at random. This allowed us to efficiently scan through 30 samples to minimize the chances of missing false positives in unexpected conditions. Table 5 shows the number of brains dissected and recorded. <strong>Immunostaining</strong> Female flies (10 days post-eclosion) were dissected for analysis. Samples were dissected in 4 °C 1X PBS (10173433, Fisher Scientific, UK) after a quick passage through EtOH (4146052, Carlo Elba), and were then transferred to formaldehyde solution (4% paraformaldehyde, P6148, Sigma-Aldrich in 1X PBS + 10% Triton-X, X100, Sigma-Aldrich) and incubated for 20–30 min at room temperature. Samples were then washed three times in PBST (0.5% Triton-X in PBS) and then blocked with 10% normal goat serum (16210-064, Invitrogen) in PBST for 15–60 min at room temperature. Samples were then incubated in primary antibody solutions (Rabbit anti-dsRed, 632496, Takara at 1:500 and Mouse anti-NC82, Developmental Studies Hybridoma Bank at 1:10 in 5% normal goat serum in PBST). Primary antibody incubations were performed for 3 days at 4 °C with rocking. They were then washed in PBST 3 times for 15 min at room temperature. The secondary antibodies were applied (Anti-mouse A594, A11032, Invitrogen at 1:500 and Anti-rabbit A488, A11008, Invitrogen at 1:500 in 5% normal goat serum in PBST) and brains were then incubated for 3 days at 4 °C with rocking. They were again washed in PBST 3 times for 15 min at room temperature. Samples were mounted in Vectashield Mounting Medium (H-1000, Vector Laboratories). Images were captured on an inverted Zeiss LSM 980 (Carl Zeiss Co., Oberkochen, Germany) using a Plan-ApoChromat 20X/0.8 air lens objective (Carl Zeiss Co., Oberkochen, Germany) and A GaAsP detector. The same laser intensity and detector gain were used to scan both the Gal4+<sup> </sup>and Gal4- conditions. z-Correction was performed to compensate for the signal loss due to section depth.
description: # Data from: An essential experimental control for functional connectivity
 mapping with optogenetics Dataset DOI:
 [10.5061/dryad.t4b8gtj77](10.5061/dryad.t4b8gtj77) ## Description of the
 data and file structure **Data from: An essential experimental control for
 functional connectivity mapping with optogenetics** This repository
 contains raw data of larval calcium imaging and adult immunohistochemistry
 files shown in the paper titled 'An essential experimental control
 for functional connectivity mapping with optogenetics' ### Files and
 variables **High level overview** Folder 'IHC_data.zip' contains
 both the raw and processed immunohistochemistry data shown in Figure 5.
 Folder 'larval_ca_data.zip' contains both the raw and the
 preprocessed calcium imaging data shown in Figures 1, 3, and 6. The
 `leaky_expression_publication` folder (on Zenodo) contains preprocessed
 data and the scripts used to create Figures 1, 2, 3, 4, and 6 of the
 manuscript. **Detailed information about each file type found in this
 repository** The zip file 'IHC_data' contains the following
 data: * folder: 'IHC_data' * file: imaging file (e.g.,
 attp1_02.czi) * file: save_UEP_Fiji_macro.ijm -&gt; This file was used to
 process the imaging files using the program 'Fiji'
 ([https://imagej.net/software/fiji/](https://imagej.net/software/fiji/)) *
 folder: NC82_jpegs * processed imaging file of the structural marker NC82
 (e.g., MAXattp1_01.jpg) * folder: tdtomato_jpegs * processed imaging file
 of the experimental marker (e.g., MAXattp1_01.jpg) The zip file
 `larval_ca_data` contains the following folder structure and file types: *
 folder: larval_ca_data * folder: genotype and ATR status. (e.g.,
 FDT106xFDT355_ATR-). * folder: light intensity used (e.g., 8uW_1s) *
 folder: experimental folder (e.g., 2021-01-30_18-22-26_0point5V_1s_step)
 -&gt; This folder contains both 'raw' files created at the time
 of the experiment and 'preprocessed files'. * Raw files: * file:
 0point5V_1s_step.npy -&gt; Stimulus file used for this experiment. Values
 indicate voltage delivered to stimulus LED at a frequency of 1kHz. *
 files: XX.tiff -&gt; imaging data from the microscope. Each tiff file is
 one experiment, the number of tiff files indicates the number of repeats.
 * Preprocessed files: * background_ROI.npy -&gt; manually selected
 rectangular region used to subtract stimulus light bleedthrough. *
 signal_ROI.npy -&gt; manually selected rectangular region of interest *
 XX.csv (e.g., 2021-01-30_18-22-26_0point5V_1s_step_dF_over_F.csv) -&gt;
 csv file with 7 columns: * Time [s]: time relative to the start of the
 repeat. * Stimulation [V]: Stimulation in voltage * dF/F no 1-5: Change in
 fluorescence (background subtracted using
 signal_ROI.npy-background_ROI.npy) of each repeat. * XX.jpg (e.g.,
 2021-01-30_18-22-26_0point5V_1s_stepdF_over_F.png) -&gt; overview of
 what's shown in the XX.csv file, background_ROI.npy and
 signal_ROI.npy file. The folder `leaky_expression_publication` contains
 the following folder structure: * file: README.md -&gt; Contains
 information on how to run the scripts contained in this repository * file:
 XX.ipynb -&gt; Python Jupyter Notebook used to prepare data (i.e.
 'combine_data.ipynb') or to create the plot(s) of the figure
 indicated in the name of the file (e.g. 'Fig 1BCEF (attP1
 traces).ipynb`) * file: XX.py -&gt; Python modules loaded by the Python
 Jupyter Notebook. These files contain commonly used functions. * folder:
 'Figure X' (e.g. Figure 1) -&gt; Indicates the Figure in the
 manuscript the scripts in this folder are referring to. * file: `Fig
 X.ipnyb` (i.e. `Fig 1BCEF (attP1 traces).ipynb`): Python Jupyter Notebook
 used to create the plot(s) in the figure(s) indicated in the name of the
 file. * file `FigS4A - klapoetke 2014 addendum Fig 1b digizelt.dig`: File
 to be used with the software DigiZeit
 ([https://www.digitizeit.xyz/](https://www.digitizeit.xyz/)) to extract
 datapoints from Klapoetke et al., 2014 as indicated in the Methods of the
 paper. * folder: `FigX_data` -&gt; Preprocessed data created by
 `combine_data.ipynb` used by the Python Jupyter notebook in the parent
 folder * file: `FigX.txt` -&gt; Metadata for the corresponding `FigX.npy`
 * file `FigX.npy` -&gt; data refered to by Python Jupyter notebook in
 parent folder.