Rezaei, E. | Search bioRxiv

bioRxiv2025

Characterization of iGABASnFR2 for in vivo mesoscale imaging of intracortical GABA dynamics

While genetically encoded sensors have advanced the study of cortical excitation, tools for large-scale imaging of inhibition remain limited. Visualizing extracellular GABA dynamics in vivo is essential for understanding how inhibitory networks shape brain activity across sensory, behavioral, and pharmacological states. To validate and apply the genetically encoded sensor iGABASnFR2 for wide-field imaging of extracellular GABA, and to characterize how cortical inhibition reorganizes across brain states, sensory modalities, and after GABA transporter blockade. We performed mesoscale imaging in head-fixed C57BL/6 mice systemically expressing iGABASnFR2. Recordings were conducted under isoflurane anesthesia, during quiet wakefulness, natural sleep (NREM and REM), and after administration of the GAT-1 inhibitor Tiagabine. We analyzed both sensory-evoked and spontaneous GABA signals using time-series, spectral, and seed-pixel correlation analyses. iGABASnFR2 demonstrated strong and modality-specific GABAergic responses to sensory stimulation, with faster and stronger activation in the contralateral cortex. Although the general spatial patterns of sensory-evoked GABA responses were consistent across anesthesia and quiet wakefulness, the amplitude, timing, and spread of these responses were significantly greater during wakefulness. During spontaneous activity, cortical GABA levels and connectivity modulated by brain state: GABA amplitude and interhemispheric synchrony were highest during quiet wakefulness but reduced during NREM sleep. Tiagabine elevated baseline GABA levels, abolished stimulus-evoked responses, and enhanced local and long-range inhibitory synchrony. iGABASnFR2 enables reliable, high-resolution imaging of cortical GABA dynamics in vivo. These results demonstrate that inhibitory signaling is dynamically structured across brain states and can be pharmacologically modulated. This tool offers new opportunities to explore the role of inhibition in health and disease at the mesoscale level.

neuroscience↗

bioRxiv2023

An efficient behavioral screening platform classifies natural products and other chemical cues according to their chemosensory valence in C. elegans

Throughout history, humans have relied on plants as a source of medication, flavoring, and food. Plants synthesize large chemical libraries and release many of these compounds into the rhizosphere and atmosphere where they affect animal and microbe behavior. To survive, nematodes must have evolved the sensory capacity to distinguish plant-made small molecules (SMs) that are harmful and must be avoided from those that are beneficial and should be sought. This ability to classify chemical cues as a function of their value is fundamental to olfaction, and represents a capacity shared by many animals, including humans. Here, we present an efficient platform based on multi-well plates, liquid handling instrumentation, inexpensive optical scanners, and bespoke software that can efficiently determine the valence (attraction or repulsion) of single SMs in the model nematode, Caenorhabditis elegans. Using this integrated hardware-wetware-software platform, we screened 90 plant SMs and identified 37 that attracted or repelled wild-type animals, but had no effect on mutants defective in chemosensory transduction. Genetic dissection indicates that for at least 10 of these SMs, response valence emerges from the integration of opposing signals, arguing that olfactory valence is often determined by integrating chemosensory signals over multiple lines of information. This study establishes that C. elegans is an effective discovery engine for determining chemotaxis valence and for identifying natural products detected by the chemosensory nervous system.

neuroscience↗