DOI: 10.5061/dryad.rv15dv4k2
title: Data from: Identification of two odorant receptors tuned to alarm pheromone in the honey bee <em>Apis mellifera</em>

description: Being social insects, honey bees use an array of pheromones to facilitate
 intraspecific communication, ensuring colony cohesion in a wide range of
 contexts. The honey bee represents an attractive model for studying the
 neurobiological basis of pheromonal processing, given that the honey bee
 pheromones are well characterized and their olfactory pathway has been
 extensively studied. Despite substantial knowledge acquired on olfactory
 processing in this species, the mechanism of pheromonal coding remains
 poorly understood. In particular, olfactory receptors (ORs) detecting
 social pheromones are still unknown. In this study, we used heterologous
 expression in the Drosophila “empty neuron system,” coupled with
 transcuticular calcium imaging and electrophysiology. We deorphanized two
 odorant receptors, AmelOR136 and AmelOR109, which detect constituents of
 the alarm pheromone. AmelOR136 exhibits a sparse coding strategy,
 suggesting a finely tuned mechanism for efficient communication in alarm
 situations. In contrast, AmelOR109 is a more broadly-tuned receptor,
 responding to diverse odorants, including pheromones.
description: # README File for "Suppdata_AmOR.zip" including AmelOR109 and
 AmelOR136 Data Analysis This README file describes the data and methods
 used in the study "Identification of two odorant receptors tuned to
 alarm pheromone in the honey bee *Apis mellifera*". The study
 investigated the responses of two odorant receptors, AmelOR109 and
 AmelOR136, to various pheromonal blends, individual compounds, and a panel
 of diverse odorants using heterologous expression in *Drosophila
 melanogaster*, coupled with transcuticular calcium imaging and single
 sensillum recordings (SSR). ## Data Files and Sheets The primary data
 generated in this study consists of electrophysiological recordings (SSR)
 and calcium imaging data. Specific data files are not explicitly named in
 the manuscript; however, the data are summarized in the figures and
 corresponding statistical analyses. This data set contains multiple
 sheets, and each sheet contains individual-level measurements for each
 stimulus.Below is a description of each file and sheet. **A. Pheromonal
 Blends (ΔF/F0) – Calcium Imaging** : This sheet contains calcium imaging
 responses (ΔF/F0) of AmelOR136 and AmelOR109 to a panel of pheromonal
 blends: Alarm pheromone, Aggregation pheromone, Brood pheromone, Queen
 mandibular pheromone (QMP), Queen retinue pheromone (QRP) and Waggle dance
 pheromone (Ethyl hexanoate and air are control stimulation).Associated
 manuscript figures: Figure 1A and Figure 1D. **B. Individual Compounds
 (ΔF/F0) – Calcium Imaging** :This sheet includes time courses and mean
 ΔF/F0 responses to individual pheromonal compounds tested at 1000 µg.
 Associated manuscript figures: Figure 1C & 1F: Mean responses to
 individual compounds. **C. Specificity to 42 Odorants (spikes/s) – SSR**:
 This sheet contains single sensillum recording (SSR) data for AmelOR136
 and AmelOR109 exposed to 42 compounds across 6 chemical families.
 Associated manuscript figure: Figure 2A–B. **D. Specificity to Acetate
 Derivatives (spikes/s) – SSR**:This sheet includes SSR data for 18 acetate
 derivatives, each tested at 1000 µg. Associated manuscript figure: Figure
 3. **E. Dose–Response Curves (spikes/s) – SSR**: This sheet provides
 dose–response recordings for four compounds tested at five doses (1, 10,
 100, 1000, 2000 µg). Associated manuscript figure: Figure 5. ## Data
 Description and Analysis ### Calcium Imaging Data **dF-F0:** Represents
 the change in fluorescence intensity. Calculated as `(F(t) - F(0)) /
 F(0)`, where `F(t)` is the fluorescence intensity at time t, and `F(0)` is
 the average fluorescence intensity of the 5 frames immediately before odor
 stimulation (frames 11-15). ### Single Sensillum Recording (SSR) Data *
 **Peri-stimulus Time Histograms:** Generated by dividing the 15-second
 recording into 100 ms bins. The average number of spikes per bin was
 calculated for all odorants. * **Odor Response Window:** Odor responses
 were observed between 6.3s and 8.1s, with a peak at 7s. * **Firing Rate
 Calculation:** The firing rate during odorant stimulation was calculated
 by averaging the number of spikes within a 1.8-second window (6.3s-8.1s).
 * **Spontaneous Firing Rate:** Measured during a 1.8-second window before
 stimulation onset. * **Response Quantification:** The response intensity
 was calculated by subtracting the spontaneous firing rate from the firing
 rate during odorant stimulation. Units are in spikes per second (spike-s).
 ### Additional Metrics **Lifetime Sparseness (S):** A measure of receptor
 specificity, ranging from 0 (unselective) to 1 (maximally selective).
 Calculated using the responses to all SSR tested compounds. Formula
 provided in the manuscript. ## Experimental Details * **OR Selection:**
 ORs were selected based on their expression level in antennae and
 phylogenetic position, using published data (Jain and Brockmann, 2020;
 Brand et al., 2017; Karpe et al., 2016; Robertson and Wanner 2006). *
 **Heterologous Expression:** AmelOR136 and AmelOR109 were expressed in
 ab3A OSNs of *Drosophila melanogaster* lacking endogenous receptors
 DmelOR22a and DmelOR22b. * **Fly Containment:** Flies were secured in
 pipette tips, allowing antennae exposure. * **Olfactory Stimulation:**
 Constant airflow of 3 L/min, with 500 mL/min redirected through
 stimulation cartridges containing filter paper soaked with 10 μL of
 odorant solution (100 μg/μL in mineral oil, unless otherwise stated).
 Control stimuli included mineral oil and ethyl hexanoate. * **Odorant
 Stimuli:** Six pheromonal blends (alarm, queen mandibular, queen retinue,
 aggregation, waggle dance, brood), unitary compounds contained in these
 blends and a panel of 42 individual odorants (followed by a panel of 18
 esters) were used. Specific compounds and ratios are listed in the
 manuscript. * **Explanation of Missing Values:** Several reasons explain
 the presence of missing values (NA) in the dataset: **(1) Biological
 preparation stability**: Maintaining the flies alive and physiologically
 stable throughout the entire stimulation sequence is not always
 guaranteed. Occasional instabilities or loss of signal during the
 experiment resulted in gaps in the dataset, recorded as NA. **(2)
 Compounds added later in the experimental pipeline**: Some odorant
 compounds were not included in the earliest experimental batches and were
 introduced in later sessions. Individuals recorded before the addition of
 these compounds therefore have NA values for those specific stimuli. **(3)
 Acquisition-related issues**: A few individuals exhibit NA values due to
 technical difficulties within the acquisition setup (e.g., unstable
 baseline, brief loss of recording, or mechanical issues). However, these
 individuals still produced reliable and biologically meaningful responses
 for other compounds. We therefore retained them in the dataset rather than
 removing entire recordings due to a limited number of missing values. NA
 thus indicates missing data due to biological or technical constraints,
 not hidden data. * **Statistical Analysis:** Friedman ANOVA followed by
 Wilcoxon post-hoc tests were used to compare responses. Benjamini-Hochberg
 correction was applied for multiple comparisons. Dose-response data were
 analyzed using Generalized Linear Mixed-Effects Models (GLMM). The
 analysis likely involved the following software and packages (although
 specific scripts are not provided with the dataset): * **R (version 4.0.0
 or higher)**: For statistical computing and data visualization. *R
 Packages*: * \\`tidyverse (ggplot2, dplyr, tidyr, readr`): For data
 manipulation, visualization, and reading data files.  *  \\`ggpubr`: For
 creating publication-ready plots.  *  \\`rstatix`: For statistical
 functions and post-hoc analyses.  *  \\`xlsx`: For working with Excel
 files.  *  \\`lme4`: For fitting generalized linear mixed-effects models
 (GLMM). *  'rstatix': To perform
 'pairwise_wilcox_test', and 'friedman_test' ## Data
 Interpretation The study identified AmelOR136 and AmelOR109 as receptors
 responsive to alarm pheromone components. AmelOR136 exhibited high
 specificity, primarily responding to isopentyl acetate. AmelOR109 showed a
 broader response profile, activated by multiple pheromone components and
 other odorants. Lifetime sparseness calculations supported the higher
 specificity of AmelOR136. Dose-response experiments were conducted to
 assess the sensitivity of AmelOR136 to its key ligands. This README
 provides a summary of the data and methods. For questions regarding the
 data, please contact
 [benjamin.andreu@sorbonne-universite.fr](mailto:benjamin.andreu@sorbonne-universite.fr) or see more contacts in the article.