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

Stefan Scheuermann; Sarah Hücker; Annika Engel; Nicole Ludwig; Philipp Lebhardt; Jens Langejürgen; Stefan Kirsch

doi:10.1016/j.slast.2024.100133

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

SLAS Technol. 2024 Apr 6:100133. doi: 10.1016/j.slast.2024.100133. Online ahead of print.

Authors

Stefan Scheuermann¹, Sarah Hücker², Annika Engel³, Nicole Ludwig⁴, Philipp Lebhardt¹, Jens Langejürgen¹, Stefan Kirsch⁵

Affiliations

¹ Clinical Health Technologies, Fraunhofer IPA, Mannheim, Germany.
² Chair for Clinical Bioinformatics, Saarland University, Saarbrücken, Germany.
³ Clinical Bioinformatics, Saarland University, University Hospital, Saarbrücken, Germany.
⁴ Human Genetics, Saarland University, University Hospital, Saarbrücken, Germany.
⁵ Chair for Clinical Bioinformatics, Saarland University, Saarbrücken, Germany. Electronic address: stefan.kirsch@item.fraunhofer.de.

PMID: 38583803
DOI: 10.1016/j.slast.2024.100133

Abstract

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.

Keywords: Micro RNAs (miRNA) sequencing; Molecular characterization; Personalized medicine; Single-cell analysis, Enzyme-free tissue dissociation.