Challenges and Strategies in Post-Mortem Spatial Transcriptomics of the Human Brain

Overview

Spatial transcriptomics (ST) technologies provide high-resolution insights into gene expression in the human brain, enabling unprecedented understanding of cellular organization and disease mechanisms. However, applying these methods to post-mortem human brain tissue presents unique challenges related to tissue preservation, transcript integrity, and spatial resolution.

Background

The human brain is a highly heterogeneous organ with diverse cell types and regional specializations, historically studied through histological and protein-based spatial analyses. Advances in RNA sequencing, including bulk RNA-seq and single-cell/nucleus RNA-seq, have enhanced molecular characterization but have limitations such as cell dissociation bias and incomplete transcript profiling. Spatial transcriptomics overcomes these by preserving spatial context and enabling whole-transcriptome profiling without dissociation, offering new opportunities to study brain architecture and pathology in situ.

Data Highlights

Sequencing-based ST platforms capture mRNA transcripts on specialized slides with spatial barcodes and unique molecular identifiers, allowing whole-transcriptome sequencing with spatial localization. Variations exist in spot size and spacing, affecting spatial resolution. Imaging-based ST methods use in situ hybridization for targeted transcript detection, often with higher spatial resolution but limited transcript coverage. Challenges include compatibility with formalin-fixed paraffin-embedded (FFPE) tissues, tissue size limitations, and potential biases in probe-based capture methods.

Key Findings

• Sequencing-based ST provides unbiased whole-transcriptome coverage but is limited by spot size and tissue area constraints.
• Imaging-based ST offers higher spatial resolution but typically targets a limited number of transcripts.
• Post-mortem human brain tissue presents challenges such as RNA degradation and variability in tissue preservation affecting data quality.
• Probe-based capture methods improve sensitivity and FFPE compatibility but may introduce bias by targeting specific transcripts.
• Single-nucleus RNA sequencing circumvents dissociation bias but does not capture cytoplasmic mRNA, limiting transcriptome completeness.
• Customized capture areas can address tissue size limitations but increase costs.

Clinical Implications

Understanding the strengths and limitations of different spatial transcriptomic platforms is critical for designing studies on post-mortem human brain tissue. Careful consideration of tissue preservation, platform selection, and data interpretation can enhance insights into brain organization and disease mechanisms. These advances may ultimately inform the development of targeted therapies for neurological disorders by elucidating spatial gene expression patterns in affected brain regions.

Conclusion

Spatial transcriptomics represents a transformative approach to studying the human brain's molecular architecture, despite challenges inherent to post-mortem tissue analysis. Strategic application of sequencing- and imaging-based methods can overcome these obstacles, advancing neuroscience research and clinical understanding of brain diseases.

References

1. Investigating the Human Brain: Challenges and Strategies in Post-Mortem Spatial Transcriptomics Analysis