Biology subjects

van Doeselaar, L.

Publications and source records attributed to van Doeselaar, L..

2 recordsLinked to original sources

bioRxiv2024

Sex-specific fear acquisition following early life stress is linked to amygdala glutamate metabolism

Early life stress (ELS) adversely affects physiological and behavioral outcomes, increasing the vulnerability to stress-related disorders, such as post-traumatic stress disorder (PTSD). PTSD prevalence is significantly higher in women and is partially mediated by genetic risk variants. Understanding how sex influences the interaction of PTSD risk genes, such as FKBP5, with trauma-related behaviors is crucial for uncovering PTSDs neurobiological pathways. The development of in-depth behavioral analysis tools using unsupervised behavioral classification is thereby a crucial tool to increase the understanding of the behavioral outcomes related to stress-induced fear memory formation. The current study investigates the sex-specific effects of ELS exposure by using the limited bedding and nesting (LBN) paradigm. The LBN exposure disrupted different facets of the hypothalamic-pituitary-adrenal (HPA) axis in a sex-specific manner directly after stress and at adult age. Moreover, freezing was altered by LBN exposure in both the acquisition and the retrieval of fear in a sex-dependent manner. Unsupervised behavioral analysis revealed a higher active fear response after LBN exposure during fear acquisition in females, but not in males. The regulation of the HPA axis is closely intertwined with cellular metabolism and core regulatory cascades. To investigate the impact of LBN exposure on tissue-specific metabolism, a metabolomic pathway analysis in the basolateral amygdala revealed a specific sex- and stress-dependent effect on purine, pyrimidine, and glutamate metabolism. The present study highlights the intricate interplay between metabolic pathways and the neurobiological substrates implicated in fear memory formation and stress regulation. Overall, these findings highlight the importance of considering sex-specific metabolic alterations in understanding the neurobiological mechanisms underlying stress-related disorders and offer potential avenues for targeted interventions.

animal behavior and cognition↗

bioRxiv2022

Automatically annotated motion tracking identifies a distinct social behavioral profile following chronic social defeat stress

Severe stress exposure is a global problem with long-lasting negative behavioral and physiological consequences, increasing the risk of stress-related disorders such as major depressive disorder (MDD). An essential characteristic of MDD is the impairment of social functioning and lack of social motivation. Chronic social defeat stress is an established animal model for MDD research, which induces a cascade of physiological and social behavioral changes. The current developments of markerless pose estimation tools allow for more complex and socially relevant behavioral tests, but the application of these tools to social behavior remains to be explored. Here, we introduce the open-source tool "DeepOF" to investigate the individual and social behavioral profile in mice by providing supervised and unsupervised pipelines using DeepLabCut annotated pose estimation data. The supervised pipeline relies on pre-trained classifiers to detect defined traits for both single and dyadic animal behavior. Subsequently, the unsupervised pipeline explores the behavioral repertoire of the animals without label priming, which has the potential of pointing towards previously unrecognized motion motifs that are systematically different across conditions. We here provide evidence that the DeepOF supervised and unsupervised pipelines detect a distinct stress-induced social behavioral pattern, which was particularly observed at the beginning of a novel social encounter. The stress-induced social behavior shows a state of arousal that fades with time due to habituation. In addition, while the classical social avoidance task does identify the stress-induced social behavioral differences, both DeepOF behavioral pipelines provide a clearer and more detailed profile. DeepOF aims to facilitate reproducibility and unification of behavioral classification of social behavior by providing an open-source tool, which can significantly advance the study of rodent individual and social behavior, thereby enabling novel biological insights as well as drug development for psychiatric disorders.

neuroscience↗