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Aleksandra Badura
Department of Neuroscience, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
Current phenotyping approaches for murine autism models often focus on one selected behavioral feature, making the translation onto a spectrum of autistic characteristics in humans challenging. Furthermore, sex and environmental factors are rarely considered. I will discuss our latest work in which we aimed to capture the full spectrum of behavioral manifestations in three autism mouse models to develop a “behavioral fingerprint” that takes environmental and sex influences under consideration. To this end, we employed a wide range of classical standardized behavioral tests and two multi-parametric behavioral assays: the Live Mouse Tracker and Motion Sequencing (MoSeq), on male and female Shank2, Tsc1 and Pcp2-Tsc1 mutant mice raised in standard or enriched environments. We found that most behavioral phenotypes were dependent on sex- and environment. Furthermore, multi-parametric behavioral assays enabled far more accurate classification of experimental groups compared to classical tests. Together, our results provide a complete phenotypic description of all tested groups, suggesting multi-parametic assays can capturing the entire spectrum of the heterogenous phenotype in autism mouse models.
V. Kovarova1,2, J. Bordes1, J. van Bergen1, L.M. Brix1,2, M. Springer1, H. Yang1, S. Narayan1, S. Mitra1, L. van Doeselaar1,2, M.V. Schmidt1
1Research Group Neurobiology of Stress Resilience, Max Planck Institute of Psychiatry, Munich, Germany
2International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
Stress-related psychiatric pathologies impose a substantial societal burden, characterized by a high prevalence and an ongoing challenge in finding effective treatments, particularly for depression. The complexity of these disorders is often also compounded by co-morbidities with metabolic disturbances. Investigating animal behaviour in this context has historically been intricate, particularly in translating findings to human studies. However, with the advent of machine learning methods and the introduction of advanced algorithms, unprecedented possibilities have emerged for phenotyping animals. My research focuses on leveraging supervised and unsupervised deep learning methods, employing tools such as DeepLabCut and DeepOF. Through these techniques, I aim to demonstrate an elevated proficiency in characterizing animal behaviour at the level of both individual and social interactions. Additionally, by conducting long-term observations of experimental animals, I demonstrate how these methods can discern nuanced variations in social behaviours that might go by conventional tests.
Funding: This project is funded by: die Deutsche Forschungsgemeinschaft (DFG)
Patrycja Ziuzia1,2, Bartosz Zglinicki1, Laura Bergauer3, Michał Ślęzak1
1Research Group Biology of Astrocytes, Life Sciences and Biotechnology Center, Łukasiewicz PORT – Polish Center for Technology Development, Wrocław, Poland
2Department of Biochemistry and Molecular Biology, Wroclaw University of Environmental and Life Sciences, Wrocław, Poland
3BioMed X Institute, Heidelberg, Germany
General approach in investigating Major Depressive Disorders (MDDs) is to find the relationship between selected genes and the phenotype, both in the biological and behavioral context. Disruptions in social interactions represent a characteristic feature across various psychiatric diseases, including depression. In MDD, one of the key features is disturbed hypothamalus-pituitary-adrenal (HPA) axis functioning, leading to increased concentration of secreted glucocorticoids (GCs) in the bloodstream and hyperactivation of glucocorticoid receptors (GRs) and affecting the stress response regulation mechanism. In the previously done classical behavioral tests, we noticed that CSDS caused expected alterations in the anxiety and social interaction of CTRL mice, but expected changes were not seen in mice with GR astroKO. Current project involved long-term observations of unknown conspecifics of male mice: wild type (C57Bl/6J background) and mutant (Aldh1l1-CreERT2 x GRflox/flox, C57Bl/6J background) with induced by chronic social defeat stress paradigm (CSDS) depressive-like behavior. Experiment, that was conducted in specially designed arenas indicating semi-naturalistic environment, shown a similar tendency in mice stress-response behavior, what may indicate that astrocytes are an important site of GR-dependent response in the central nervous system (CNS).
Funding: NCN OPUS grant 2021/41/B/NZ3/04099 'AstroSyCo' and HE Twinning 'SAME-NeuroID' grant No: 101079181
Julia Świderska1, Lali Kruashvili1, Błażej Ruszczycki2, Filip Polański1 and Kasia Radwańska1
1Laboratory of Molecular Basis of Behavior, Nencki Institute of Experimental Biology, Warsaw, Poland
2Department of Medical Physics and Biophysics, Faculty of Physics and Applied Informatics, AGH University of Krakow, Krakow, Poland
Most aspects of animal behavior are based on decisions. One of the most extensively researched type of decisions is spatial choice - that uses spatial information to suppress inappropriate behaviors (Bannerman et al. 2012). The population activity of place cells in the dCA1 area underlies spatial choice and memory. Place cell activity can be recorded when an animal is freely moving throughout the space. However, in the majority of studies on spatial choices, behavior is investigated with protocols that require direct involvement of the researcher. Additionally, traditional tools used for assessment of spatial choice do not have required dimensions to monitor changes within place cells’ activity using genetically encoded, and relatively slow, calcium indicators.
Here, we present a new system for monitoring mice activity and navigation with our recent findings on behavioral protocol that can be employed within it. This apparatus is built of integrated modules including camera system, cue display system, liquid reward dispensers and door control system. Animals are tested within 3 connected corridors, parted with automatic doors, where they can roam undisturbed and consume reward (sweet milk) at the end of reward arms from automatic dispensers. The automation of our task enables evaluation of spatial choices without the researcher's direct involvement. Additionally, an open construction of the maze allows for recording of the brain cell activity of a freely moving mouse with the use of a miniature microscopy and optogenetic tools along with recording of the animal’s behavior within the entire space.
Funding: This work is supported by National Science Centre Grant 2020/38/A/NZ4/00483 to K.Radwańska.
A. Yadav1, F. Haque2, M. Kalinowska1, M. Rycerz1, A. Bryksa1, A. Puścian1
1Laboratory of Emotions Neurobiology, BRAINCITY - Centre of Excellence for Neural Plasticity and Brain Disorders, Nencki Institute, Polish Academy of Sciences, Warsaw, Poland
2Artificial Intelligence Resource, Molecular Imaging Branch, National Cancer Institute, Bethesda, MD, USA
Identifying individuals from one's social group as in-groups members happens quickly and automatically, without conscious effort. Studying the neural mechanisms behind this phenomenon can be enhanced by conducting behavioural experiments that simulate naturalistic social interactions.
We present a novel method to investigate social bond formation between two groups of mice, who are genetically identical, however, unfamiliar. Mice were housed in Eco-HAB, an automated naturalistic environment, for 21 days. Initially, the habitat was divided into two sections, allocating each group its own territory for 7 days. Subsequently, the groups were combined, enabling unrestricted interaction.
Our results reveal an initial preference for familiar group members after merging, followed by a shift towards interacting more with unfamiliar animals. Social dynamics then evolved, with some mice maintaining original preference for familiar mice and others forming new bonds. Notably, activating PV cells chemogenetically in the prelimbic cortex reduced voluntary interactions with both, familiar and unfamiliar mice.
In summary, our study offers insights into the behavioural and neural processes of merging two separate groups into a cohesive social entity. These discoveries pave the way for deeper exploration of the neuronal mechanisms involved in forging new social bonds.
