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<p>Spatial transcriptomics has advanced our understanding of cellular heterogeneity at single-cell resolution. Here, we assess the suitability of in situ sequencing (ISS) for analyzing formalin-fixed, paraffin-embedded (FFPE) postmortem human brain tissue. A key challenge in ISS data analysis is optimizing transcript allocation while minimizing misallocation, particularly in the morphologically complex central nervous system (CNS). We compared geospatial methods using nuclear and expanded nuclear boundaries for segmentation and transcript allocation. While overall cell-type proportions remained comparable, transcript allocation methods affected specific cell types, including microglia, neurons, and neurovascular cells. To enhance specificity, we integrated fluorescent imaging data targeting 18S RNA and IBA1 protein to direct transcript allocation toward RNA-rich cells (e.g., neurons) and microglia, respectively. We demonstrate how this approach, paired with secondary allocation of transcripts outside imaging masks, improved both the number of microglia detected and the specificity of microglial transcripts assigned. Our method offers a flexible and efficient strategy for targeted transcript allocation based on cellular morphology, optimizing CNS cell segmentation in FFPE-preserved human brain tissue.</p>

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Beyond the nuclear border: single-cell analysis of in situ sequenced human brain tissue using cellular features

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月22日

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  • Janssen M. Kotah,
  • Thomas Rust,
  • Hilmar R. J. van Weering,
  • Janneke Bosma,
  • Amber L. Woudstra,
  • Susanne M. Kooistra,
  • Bart J. L. Eggen

摘要

Spatial transcriptomics has advanced our understanding of cellular heterogeneity at single-cell resolution. Here, we assess the suitability of in situ sequencing (ISS) for analyzing formalin-fixed, paraffin-embedded (FFPE) postmortem human brain tissue. A key challenge in ISS data analysis is optimizing transcript allocation while minimizing misallocation, particularly in the morphologically complex central nervous system (CNS). We compared geospatial methods using nuclear and expanded nuclear boundaries for segmentation and transcript allocation. While overall cell-type proportions remained comparable, transcript allocation methods affected specific cell types, including microglia, neurons, and neurovascular cells. To enhance specificity, we integrated fluorescent imaging data targeting 18S RNA and IBA1 protein to direct transcript allocation toward RNA-rich cells (e.g., neurons) and microglia, respectively. We demonstrate how this approach, paired with secondary allocation of transcripts outside imaging masks, improved both the number of microglia detected and the specificity of microglial transcripts assigned. Our method offers a flexible and efficient strategy for targeted transcript allocation based on cellular morphology, optimizing CNS cell segmentation in FFPE-preserved human brain tissue.