Micro-region transcriptomics profiling of cerebral organoids using a capillary-based microdissection system

Investigating the transcriptome while preserving cellular spatial information facilitates a comprehensive understanding of cellular fates in multicellular organisms. However, the precise and flexible isolation of micro-regions of interest (mROIs) for profiling spatial transcriptomics (ST) remains a challenge. We established a capillary-based tissue microdissection system (CMS), which enables the high-efficiency acquisition of mROIs from cultured cerebral organoids for mRNA sequencing (CMS-seq). Subsequently, neural progenitor cells (NPCs), intermediate progenitors (IPs), mature neurons, and astrocytes were annotated in the cerebral organoids at the stages of days 20 and 60, respectively. Furthermore, astrocytes in the samples from day 20 were found to exhibit a higher tendency to express the <i>SPARC</i> gene whereas those from day 60 showed a stronger tendency to express the <i>NTRK2</i> gene. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differentially expressed genes indicated a higher degree of neural development at the stage of day 60. Finally, a spatial annotation map of cell types of the mROIs was constructed, enabling rapid identification of the cellular composition in each mROI. Therefore, we established an efficient method for ST analysis in cerebral organoids and further exploration of the spatial developmental trajectory.

Authors

Institutions

Publication Details

Journal
Analytical Methods
Published
2025-01-01
DOI
https://doi.org/10.1039/d5ay00277j
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.81
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Micro-region transcriptomics profiling of cerebral organoids using a capillary-based microdissection system

Ning Chang, Jitao Xu, Dianhuai Meng, Qinyu Ge et al.
1 citations
Analytical Methods
Single-cell and spatial transcriptomics
0.81
article

Micro-region transcriptomics profiling of cerebral organoids using a capillary-based microdissection system

Ning Chang, Jitao Xu, Dianhuai Meng, Qinyu Ge, Yunxia Guo, Xiangwei Zhao, Kaiqiang Ye, Yan Huang, Xi Yang, Qingyang Qin
article en
1 citations

Abstract

Investigating the transcriptome while preserving cellular spatial information facilitates a comprehensive understanding of cellular fates in multicellular organisms. However, the precise and flexible isolation of micro-regions of interest (mROIs) for profiling spatial transcriptomics (ST) remains a challenge. We established a capillary-based tissue microdissection system (CMS), which enables the high-efficiency acquisition of mROIs from cultured cerebral organoids for mRNA sequencing (CMS-seq). Subsequently, neural progenitor cells (NPCs), intermediate progenitors (IPs), mature neurons, and astrocytes were annotated in the cerebral organoids at the stages of days 20 and 60, respectively. Furthermore, astrocytes in the samples from day 20 were found to exhibit a higher tendency to express the <i>SPARC</i> gene whereas those from day 60 showed a stronger tendency to express the <i>NTRK2</i> gene. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differentially expressed genes indicated a higher degree of neural development at the stage of day 60. Finally, a spatial annotation map of cell types of the mROIs was constructed, enabling rapid identification of the cellular composition in each mROI. Therefore, we established an efficient method for ST analysis in cerebral organoids and further exploration of the spatial developmental trajectory.

Analytical MethodsVol. 17(17)
Southeast University (BD), State Key Laboratory of Digital Medical Engineering (CN), Southeast University (CN), Yangzhou University (CN), Nanjing Medical University (CN)
Openalex Percentile: Top 30%
Single-cell and spatial transcriptomics
0.81
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.