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Accurate acquisition of spatially resolved gene expression profiles is crucial for understanding tissue heterogeneity in health and disease. Single-cell RNA sequencing (scRNA-seq) offers high cellular resolution1,2, but it loses native spatial context and may alter transcriptional profiles during tissue dissociation3,4. For cell types lacking publicly identified specific markers, obtaining pure populations using immunofluorescence-based sorting or immunomagnetic isolation remains difficult5,6. Spatial transcriptomics technologies such as Visium and GeoMx allow in situ capture of high-throughput gene expression data, but their spatial resolution is limited at the single-cell or subcellular level7,8. Conversely, imaging-based spatial transcriptomics can achieve nanometer-level resolution but has limited gene detection throughput9. This highlights a persistent gap for hypothesis-driven analysis of specific morphological regions.
Laser capture microdissection (LCM) allows microscope-guided selection and isolation of specific cells from tissue sections or live cell cultures based on observable phenotype. This approach preserves cellular structure and spatial information10. This technique has been extensively applied in liver disease research for downstream analyses. For instance, LCM has been used to collect biliary epithelial cells from liver biopsies to elucidate their immunoregulatory role in primary biliary cholangitis11. In addition, it has been used to isolate γ-glutamyl transferase (GGT)-positive tissue from experimental models to confirm site-specific Ggt1 gene expression12. But these studies have largely focused on fresh frozen tissues, which often lack clinical annotations or long-term follow-up13. In contrast, chemically fixed tissues offer advantages for histopathological diagnosis14. Although LCM-based RNA sequencing (RNA-Seq) has been successfully applied to archived, large-scale formalin-fixed and paraffin-embedded (FFPE) liver specimens15. However, a robust LCM-based gene expression profiling protocol specifically for microscale samples from paraformaldehyde (PFA)-fixed and Optimal Cutting Temperature (OCT) compound-embedded liver tissues is lacking.
To address this unmet need, a comprehensive protocol was optimized using PFA-fixed, OCT-embedded cryosections. This protocol addresses the limitations of FFPE workflows (e.g., prolonged processing and harsh chemicals) for sensitive LCM-RNA applications16. In contrast, the fixation and embedding process for PFA-fixed, OCT-embedded samples is relatively simpler and more flexible, enabling rapid preparation of high-quality sections that preserve both RNA integrity and tissue morphology. Furthermore, this protocol is performed using an ultraviolet (UV) laser-based LCM system. Compared to infrared systems, UV-LCM provides finer cutting resolution and enables direct, non-contact sample collection, minimizing contamination and making it suited for the precise isolation of microscale regions from complex tissue architectures17,18. Therefore, the operational value of this protocol lies in its ability to perform morphology-preserving capture of microscale regions (~1,000 cells) from PFA-fixed liver sections. It yields RNA suitable for targeted gene expression analysis, allowing direct correlation between histopathological features and local transcriptomic profiles.
Here, we describe a protocol for laser capture microdissection of microscale tissue (~1,000 cells) from PFA-fixed, OCT-embedded mouse liver sections, followed by RNA extraction and downstream analysis by quantitative reverse transcription PCR and RNA sequencing. These procedures can be completed within five days.
To guide readers in assessing the applicability of this protocol, the key scope and limitations are summarized below. This protocol is specifically optimized for hypothesis-driven, morphology-guided sampling of specific histological regions from PFA-fixed, OCT-embedded tissues, with a primary application in mouse liver. It is suited for researchers who need to correlate spatially resolved transcriptomic data with precise histopathological features preserved in fixed specimens. The workflow is particularly valuable when working with archived or clinically annotated fixed tissues where fresh-frozen samples are unavailable. However, this protocol is not ideal for studies requiring high-integrity, non-fragmented RNA (e.g., RNA integrity number (RIN) > 8), as the inherent fragmentation from chemical fixation limits its use in applications that depend on full-length transcripts.