SNMP1 is critical for sensitive detection of the desert locust aromatic courtship inhibition pheromone phenylacetonitrile.

BACKGROUND: Accurate detection of pheromones is crucial for chemical communication and reproduction in insects. In holometabolous flies and moths, the sensory neuron membrane protein 1 (SNMP1) is essential for detecting long-chain aliphatic pheromones by olfactory neurons. However, its function in hemimetabolous insects and its role for detecting pheromones of a different chemical nature remain elusive. Therefore, we investigated the relevance of SNMP1 for pheromone detection in a hemimetabolous insect pest of considerable economic importance, the desert locust Schistocerca gregaria, which moreover employs the aromatic pheromone phenylacetonitrile (PAN) to govern reproductive behaviors. RESULTS: Employing CRISPR/Cas-mediated gene editing, a mutant locust line lacking functional SNMP1 was established. In electroantennography experiments and single sensillum recordings, we found significantly decreased electrical responses to PAN in SNMP1-deficient (SNMP1-/-) locusts. Moreover, calcium imaging in the antennal lobe of the brain revealed a substantially reduced activation of projection neurons in SNMP1-/- individuals upon exposure to PAN, indicating that the diminished antennal responsiveness to PAN in mutants affects pheromone-evoked neuronal activity in the brain. Furthermore, in behavioral experiments, PAN-induced effects on pairing and mate choice were altered in SNMP1-/- locusts. CONCLUSIONS: Our findings emphasize the importance of SNMP1 for chemical communication in a hemimetabolous insect pest. Moreover, they show that SNMP1 plays a crucial role in pheromone detection that goes beyond long-chain aliphatic substances and includes aromatic compounds controlling reproductive behaviors.

CalciSeg: A versatile approach for unsupervised segmentation of calcium imaging data.

Recent advances in calcium imaging, including the development of fast and sensitive genetically encoded indicators, high-resolution camera chips for wide-field imaging, and resonant scanning mirrors in laser scanning microscopy, have notably improved the temporal and spatial resolution of functional imaging analysis. Nonetheless, the variability of imaging approaches and brain structures challenges the development of versatile and reliable segmentation methods. Standard techniques, such as manual selection of regions of interest or machine learning solutions, often fall short due to either user bias, non-transferability among systems, or computational demand. To overcome these issues, we developed CalciSeg, a data-driven and reproducible approach for unsupervised functional calcium imaging data segmentation. CalciSeg addresses the challenges associated with brain structure variability and user bias by offering a computationally efficient solution for automatic image segmentation based on two parameters: regions' size limits and number of refinement iterations. We evaluated CalciSeg efficacy on datasets of varied complexity, different insect species (locusts, bees, and cockroaches), and imaging systems (wide-field, confocal, and multiphoton), showing the robustness and generality of our approach. Finally, the user-friendly nature and open-source availability of CalciSeg facilitate the integration of this algorithm into existing analysis pipelines.

An effective hydrodynamic description of marching locusts.

A fundamental question in complex systems is how to relate interactions between individual components ('microscopic description') to the global properties of the system ('macroscopic description'). Furthermore, it is unclear whether such a macroscopic description exists and if such a description can capture large-scale properties. Here, we address the validity of a macroscopic description of a complex biological system using the collective motion of desert locusts as a canonical example. One of the world's most devastating insect plagues begins when flightless juvenile locusts form 'marching bands'. These bands display remarkable coordinated motion, moving through semiarid habitats in search of food. We investigated how well macroscopic physical models can describe the flow of locusts within a band. For this, we filmed locusts within marching bands during an outbreak in Kenya and automatically tracked all individuals passing through the camera frame. We first analyzed the spatial topology of nearest neighbors and found individuals to be isotropically distributed. Despite this apparent randomness, a local order was observed in regions of high density in the radial distribution function, akin to an ordered fluid. Furthermore, reconstructing individual locust trajectories revealed a highly aligned movement, consistent with the one-dimensional version of the Toner-Tu equations, a generalization of the Navier-Stokes equations for fluids, used to describe the equivalent macroscopic fluid properties of active particles. Using this effective Toner-Tu equation, which relates the gradient of the pressure to the acceleration, we show that the effective 'pressure' of locusts increases as a linear function of density in segments with the highest polarization (for which the one-dimensional approximation is most appropriate). Our study thus demonstrates an effective hydrodynamic description of flow dynamics in plague locust swarms.

Synergistic olfactory processing for social plasticity in desert locusts.

Desert locust plagues threaten the food security of millions. Central to their formation is crowding-induced plasticity, with social phenotypes changing from cryptic (solitarious) to swarming (gregarious). Here, we elucidate the implications of this transition on foraging decisions and corresponding neural circuits. We use behavioral experiments and Bayesian modeling to decompose the multi-modal facets of foraging, revealing olfactory social cues as critical. To this end, we investigate how corresponding odors are encoded in the locust olfactory system using in-vivo calcium imaging. We discover crowding-dependent synergistic interactions between food-related and social odors distributed across stable combinatorial response maps. The observed synergy was specific to the gregarious phase and manifested in distinct odor response motifs. Our results suggest a crowding-induced modulation of the locust olfactory system that enhances food detection in swarms. Overall, we demonstrate how linking sensory adaptations to behaviorally relevant tasks can improve our understanding of social modulation in non-model organisms.