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A novel approach to generate enzyme-free single cell suspensions from archived tissues for miRNA sequencing

Obtaining high-quality omics data at the single-cell level from archived human tissue samples is crucial for gaining insights into cellular heterogeneity and pushing the field of personalized medicine forward. In this technical brief we present a comprehensive methodological framework for the effici...

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Main Authors: Scheuermann, Stefan (Author) , Hücker, Sarah (Author) , Engel, Annika (Author) , Ludwig, Nicole (Author) , Lebhardt, Philipp (Author) , Langejürgen, Jens (Author) , Kirsch, Stefan (Author)
Format: Article (Journal)
Language:English
Published: June 2024
In: SLAS technology
Year: 2024, Volume: 29, Issue: 3, Pages: 1-7
ISSN:2472-6311
DOI:10.1016/j.slast.2024.100133
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.slast.2024.100133
Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S2472630324000153
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Author Notes:Stefan Scheuermann, Sarah Hücker, Annika Engel, Nicole Ludwig, Philipp Lebhardt, Jens Langejürgen, Stefan Kirsch
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Summary:Obtaining high-quality omics data at the single-cell level from archived human tissue samples is crucial for gaining insights into cellular heterogeneity and pushing the field of personalized medicine forward. In this technical brief we present a comprehensive methodological framework for the efficient enzyme-free preparation of tissue-derived single cell suspensions and their conversion into single-cell miRNA sequencing libraries. The resulting data from this study have the potential to deepen our understanding of miRNA expression at the single-cell level and its relevance in the context of the examined tissues. The workflow encompasses tissue collection, RNALater immersion, storage, thawing, TissueGrinder-mediated dissociation, miRNA lysis, library preparation, sequencing, and data analysis. Quality control measures ensure reliable miRNA data, with specific attention to sample quality. The UMAP analysis reveals tissue-specific cell clustering, while miRNA diversity reflects tissue variations. The presented workflow effectively processes preserved tissues, extending opportunities for retrospective analysis and biobank utilization.
Item Description:Online verfügbar: 6. April 2024, Artikelversion: 8. Juni 2024
Gesehen am 21.01.2025
Physical Description:Online Resource
ISSN:2472-6311
DOI:10.1016/j.slast.2024.100133

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