Biology subjects

Leboulleux, Q.

Publications and source records attributed to Leboulleux, Q..

4 recordsLinked to original sources

bioRxiv2025

TARGETING 5-HT7 RECEPTOR WITH BIASED LIGANDS TO ALLEVIATE PAIN AND SPINAL NEUROINFLAMMATION

The serotonin 5-HT7 receptor (5-HT7R), a member of the rhodopsin-like family of G protein-coupled receptors (GPCRs) is highly expressed in the central nervous system (CNS) and represents a promising target for treating CNS disorders such as sleep disturbances, migraine, neuropsychiatric conditions, and neuropathic pain. Owing to its therapeutic potential, extensive efforts have focused on developing selective 5-HT7R ligands. In the last decades, biased signalling has emerged as a key concept in GPCR pharmacology as biased ligands can stabilize specific active states of the receptor and trigger selective activation of downstream signaling pathways. In this context, we recently identified two biased 5-HT7R ligands, Serodolin and MOA51, from different chemical series. Here, we aimed to compare the pharmacological and safety profiles of these ligands and to assess their effect on pain-related behaviors and spinal neuroinflammation. In inflammatory pain models (acid acetic writhing, formalin and CFA tests), both serodolin and MOA51 effectively attenuated pain responses to a similar extend. Furthermore, in neuropathic pain models, spinal nerve injury (SNI) and Cuff model, both ligands reversed mechanical allodynia. Interestingly, unlike pregabalin, a clinically used reference drug, neither Serodolin nor MOA51 induced apparent tolerance after 10 consecutive days of administration. Treatment with these 5-HT7R ligands also reduced spinal microglial and attenuated neuronal hyperactivity in the spinal cord. Altogether these findings highlight the potential of 5-HT7R-biased ligands as promising analgesic candidates capable of modulating neuroinflammatory processes and mitigating both inflammatory and neuropathic pain.

neuroscience↗

bioRxiv2024

PrecisionTrack: Reliable Tracking of Large Groups of Animals Interacting in Complex Environments Over Extended Periods

Large-scale ethological behavioral studies can provide insights into the neuronal processes underlying complex and social behaviors, potentially opening new avenues for mental health research. However, studying socially interacting animals in naturalistic environments remains technically challenging, as current approaches struggle to simultaneously maintain subject identity, extract behavior, and characterize social interactions over prolonged periods. Here, we present PrecisionTrack, an open-source and fully integrated framework designed for real-time multi-animal tracking, behavioral analysis, and social interaction inference in large groups of interacting animals. PrecisionTrack achieves high spatiotemporal accuracy in crowded and highly occlusive environments while maintaining robust long-term identity tracking and low-latency processing. To extend behavioral inference beyond pose estimation, we developed the Multi-animal Action Recognition Transformer (MART), a transformer-based architecture enabling real-time subject-level action recognition, and Graph-MART (G-MART), a graph neural network module that infers directed social interactions and interaction partners within groups. In addition, PrecisionTrack supports quantitative analysis of evolving social networks across time, enabling investigation of the temporal organization and stability of social dynamics in naturalistic settings. The entire framework is open source and accompanied by standardized workflows and documentation, enabling users to train, evaluate, and deploy custom behavioral analysis pipelines across species and experimental contexts. PrecisionTrack provides a scalable platform for quantitative investigation of complex social behaviors at a resolution and duration not accessible with existing methods.

neuroscience↗

bioRxiv2024

The Tailtag System: Tracking Multiple Mice in a Complex Environment Over a Prolonged Period Using ArUco Markers.

Despite recent advancements, safely and reliably tracking individual movements over extended periods, particularly within complex social groups, remains challenging. Traditional methods like colour coding, tagging, and RFID tracking, while effective, have notable practical limitations. State-of-the-art neural network-based trackers often struggle to maintain individual identities in large groups for more than a few seconds. Fiducial tags like ArUco codes present a potential solution by enabling accurate tracking and identity management, yet their topical application on mammals has proven difficult without frequent human intervention. In this study, we introduce the Tailtag system: a non-invasive, ergonomic tail ring embedded with an ArUco marker. This system includes a comprehensive parameter optimization guide along with practical guidelines on marker selection. Our Tailtag system demonstrated the ability to automatically and reliably track individual mice in social colonies of up to 20 individuals over a period of seven days without performance degradation, facilitating a detailed analysis of social dynamics in naturalized environments.

animal behavior and cognition↗

bioRxiv2024

Transcriptional profiling of the cortico-accumbal pathway reveals sex-specific alterations underlying stress susceptibility

Anxiety and depressive disorders, including major depressive disorder (MDD), affect millions of people every year, imposing significant socio-economic burdens. In this scenario, current treatments for MDD show limited efficacy, highlighting the need to better understand its molecular mechanisms. The medial prefrontal cortex (mPFC) has been identified as a critical brain region in MDD pathology, displaying altered activity and morphology. This study targets the mPFC-to-nucleus accumbens (NAc) pathway, which is implicated in the regulation of emotional behavior. We used a pathway-specific approach to uncover transcriptional profiles in mPFC neurons projecting to the NAc in stressed male and female mice. Using the RiboTag technique and RNA sequencing, we identified sex-specific gene expression changes, revealing potential roles in stress susceptibility. Differential expression and weighted gene co-expression network analyses revealed distinct transcriptional responses to chronic stress in males and females. Key findings include the identification of the X-linked lymphocyte-regulated 4B (Xlr4b) gene, within a highly relevant gene module, as a stress susceptibility driver in males. By experimentally overexpressing the Xlr4b gene, we characterized its crucial role in regulating neuronal firing and influencing arborization patterns to promote anxiety-like behavior in a sex-specific fashion. These findings suggest that chronic stress induces unique and shared transcriptional alterations in mPFC neurons projecting to the NAc. Some of these alterations change the morphological and functional properties of neuronal pathways ultimately contributing to the differential manifestation of anxiety-like and depressive-like behaviors in male and female mice.

neuroscience↗