bioRxiv Science⌕ Search

bioRxiv · 10.1101/2023.03.10.532130

Patterns of Neural Activation During an Initial Social Stress Encounter are Predictive of Future Susceptibility or Resilience: A FosTRAP2 Study

Abstract

Repeated social stress is a significant factor in triggering depression in vulnerable individuals, and genetic and environmental factors interact to contribute to this vulnerability. Interestingly, the role of experience in shaping vulnerability is not well studied. To what extent does an individuals initial reaction to a given stressor influence their response to similar stressors in the future? And how is this initial response encoded at the neural level to bias towards future susceptibility or resilience? The Chronic Social Defeat Stress (CSDS) mouse model offers an ideal opportunity to address these questions. Following 10 days of repeated social defeat, mice diverge into two distinct populations of social reactivity: resilient (interactive) and susceptible (avoidant). It is notable that the CSDS paradigm traditionally uses genetically inbred mice, indicating that this divergence is not genetically determined. Furthermore, the emergence of the two phenotypes only occurs following several days of exposure to stress, suggesting that the repeated experience of social defeat influences future susceptibility or resilience. In this study, we asked whether specific patterns of neural activation during the initial exposure to the social defeat stress can predict whether an individual will eventually emerge as resilient or susceptible. To address this question, we used Fos-TRAP2 mouse technology to capture brain-wide neural activation patterns elicited during the initial stress exposure, while allowing the mice to go on to experience the full course of CSDS and diverge into resilient and susceptible populations. Using a high-throughput brain-wide cell counting approach, we identified the bed nucleus of the stria terminalis and lateral septal nucleus as key hubs for encoding social defeat. We also identified the basomedial amygdala as a hub for encoding future susceptibility, and the hippocampal CA1 area and medial habenula for encoding future resilience. Our findings demonstrate that the initial experience with social stress induces a distinct brain-wide pattern of neural activation associated with defeat, as well as unique activation patterns that appear to set the stage for future resilience or susceptibility. This highly orchestrated response to defeat is seen especially in animals that emerge as resilient compared to susceptible. Overall, our work represents a critical starting place for elucidating mechanisms whereby early experiences can shape vulnerability to affective disorders.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Murra, D., Hilde, K. L., Khalil, H., Watson, S. J., Akil, H.. 2023-03-12. Patterns of Neural Activation During an Initial Social Stress Encounter are Predictive of Future Susceptibility or Resilience: A FosTRAP2 Study. https://doi.org/10.1101/2023.03.10.532130

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗