Comprehensive Spatial Profiling of Species-agnostic Transcriptomes <em>via</em> Stereo-seq

The spatial composition of cells within the host, as well as the bacteria or viral loads within the tissue, can impact the interaction of cell types and analytes that drive the cell through cell-type-specific processes. Stereo-seq for FFPE tissues uses random priming to spatial barcodes, which is different from standard spatial transcriptomics methods, which use A'tailing to capture messenger RNA (mRNA) or probe-based to capture species-specific transcripts. These methods do not embrace the more current knowledge about the impact and importance of other types of RNA from long non-coding RNA, mitochondrial RNA, microRNA, or other species, RNA, such as microbial, viral, and fungal. Outlined here is a step-by-step procedure from tissue sectioning through library preparation for spatial species-agnostic stereo-seq application with RNA detection using a randomer probe methodology, which is compatible with formalin fixed paraffin embedded (FFPE) tissues. This Stereo-seq method has a random capture bead of 0.22 µm in size that reoccurs in an array every 0.5 µm, allowing for subcellular resolution from a sequencing-based technology. As this method detects both host and non-host RNA, the protocol requires specific considerations to allow for the determination of what is inside the tissue versus what was deposited on the tissue during the collection, preservation, cutting, and detection process (i.e., environmental and handling contaminants). Lastly, this protocol allows one to have high (single-cell) level resolution of multi-RNA species within a spatial context, providing insight into the intra- and inter-actome of cell types and pathological species.

Authors

Institutions

Publication Details

Journal
Journal of Visualized Experiments
Published
2025-10-31
DOI
https://doi.org/10.3791/68619
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Jared K. Burks, Samuel C. Mok, Boyu Zhang, Thomas V. Huynh et al.
Journal of Visualized Experiments
Single-cell and spatial transcriptomics
article

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Jared K. Burks, Samuel C. Mok, Boyu Zhang, Thomas V. Huynh, Clay T. Brasuell, Erika J. Thompson, Sammy Ferri‐Borgogno, Danielle L. Stolley, Tod D. Casasent, Basant T. Gamal, Vincent Li, Lidia Rocha, Arizona T. Nguyen, Arnold Dahay
article en

Abstract

The spatial composition of cells within the host, as well as the bacteria or viral loads within the tissue, can impact the interaction of cell types and analytes that drive the cell through cell-type-specific processes. Stereo-seq for FFPE tissues uses random priming to spatial barcodes, which is different from standard spatial transcriptomics methods, which use A'tailing to capture messenger RNA (mRNA) or probe-based to capture species-specific transcripts. These methods do not embrace the more current knowledge about the impact and importance of other types of RNA from long non-coding RNA, mitochondrial RNA, microRNA, or other species, RNA, such as microbial, viral, and fungal. Outlined here is a step-by-step procedure from tissue sectioning through library preparation for spatial species-agnostic stereo-seq application with RNA detection using a randomer probe methodology, which is compatible with formalin fixed paraffin embedded (FFPE) tissues. This Stereo-seq method has a random capture bead of 0.22 µm in size that reoccurs in an array every 0.5 µm, allowing for subcellular resolution from a sequencing-based technology. As this method detects both host and non-host RNA, the protocol requires specific considerations to allow for the determination of what is inside the tissue versus what was deposited on the tissue during the collection, preservation, cutting, and detection process (i.e., environmental and handling contaminants). Lastly, this protocol allows one to have high (single-cell) level resolution of multi-RNA species within a spatial context, providing insight into the intra- and inter-actome of cell types and pathological species.

Journal of Visualized Experiments(224)
The University of Texas MD Anderson Cancer Center (US)
Openalex Percentile: Top 71%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.