Study on Mouse Sepsis-Associated Encephalopathy Based on Single Cell and Spatial Transcriptomics

Background

Organ dysfunction leading to death in sepsis is related to an imbalance in the host’s response to infection, and it has a high global mortality rate. Recent studies have shown that sepsis can cause brain dysfunction, known as sepsis-associated encephalopathy (SAE). Symptoms of SAE include changes in consciousness, cognitive impairments, and neuromuscular disorders, leading to higher mortality rates and long-term neurological damage. Despite research into mechanisms such as oxidative stress and cytokine proliferation, the specific pathophysiology of SAE remains unclear, necessitating further research. Single-nucleus RNA sequencing (snRNA-seq) helps in dissecting the complex cellular heterogeneity for the discovery of disease-specific single cell markers. However, traditional transcriptomic methods ignore spatial information during tissue dissociation, limiting our understanding of the mechanisms of tissue damage and inflammatory cell recruitment. Spatial transcriptomics, on the other hand, provide a means to assess gene expression in tissue sections, preserving spatial information in situ.

Paper Source

This study, with Yan-yan Zhu and Yin Zhang as co-first authors and Ping-sen Zhao as the main contact, was published in the “Journal of Neuroinflammation” in 2024. The research team consists of members from multiple scientific research institutions, with primary authors including: Yan-yan Zhu, Yin Zhang, Sheng He, San-jun Yi, Hao Feng, Xian-su Xia, Xiao-dong Fang, Xiao-qian Gong, Ping-sen Zhao.

Research Content and Methods

The study established a mouse model of intraperitoneal lipopolysaccharide (LPS) injection and monitored brain tissue changes at 0, 12, 24, and 72 hours post-injection. Using advanced snRNA-seq and stereo-seq technologies, the study comprehensively described the cellular responses and molecular patterns in the brain. The differences between the responses of wild-type mice and mice lacking the ANXA1 gene were compared. Researchers carried out cell type deconvolution and co-localization analysis using spatial transcriptomics scripts (sptran), revealing interactions between astro-2, micro-2, and vas-1 cells in the V1A2M2 region. Additionally, a ligand-receptor analysis involving 2033 paired tests identified key interactions between TIMP1 and CD63, ITGB1, and LRP1.

Study Results

The study found that the proportion of Astro-2 and Micro-2 cells in the brains of ANXA1 knockout mice (LPS model) significantly increased at 12 and 24 hours post-injection. These two types of cells co-localized with vascular cells (vas-1), forming a special region V1A2M2. It was discovered that paired expressions such as TIMP1-CD63, CCL2-ACKR1, and CXCL2-ACKR1 were upregulated within this region. The knockout of ANXA1 increased the mortality rate in the model, but no significant differences were observed in other brain cell types, quantities, and distributions. The study also found that the expression of ANXA1 in the brain increased after the LPS challenge, proposing that the increased relevance of cell co-localization and ligand-receptor pairs may be a potential mechanism for SAE.

Study Conclusions

The study successfully identified a unique cell co-localization, a pathological region comprising astro-2, micro-2, and vas-1 cells, and observed that the related ligand-receptor pairs in these cells were upregulated. Changes related to the increase in mortality rate were observed in ANXA1 knockout mice, suggesting that this cell arrangement is related to the potential mechanism of the observed increase in mortality rate with SAE or ANXA1 knockout mice.

Research Significance

This study provides scientific value and potential clinical applications for the unique cell types associated with the pathogenesis of SAE, laying an important foundation for the development of future treatment strategies. By integrating snRNA-seq with spatial transcriptomics to map molecular markers in the brain, the study not only advances our understanding of SAE but also provides spatial information on cell activation in neuroinflammatory conditions, which is expected to greatly deepen our knowledge of the complex mechanisms of neuroinflammation.