Nature CommunicationsBioengineeringPeer-reviewed journal article
Non-destructive transcriptomics via vesicular export
Niklas ArmbrustiD, Martin GrosshauseriD, Julian GeilenkeuseriD, Luisa Stroppel, Mattea Jozinovic, Hella Levermann, Tobias Panne, Jannick Wißmann, Lukas GoelitziD, Sebastian W. SchmidtiD, Tanja Orschmann, Ejona RushaiD, Emily Steinmaßl, Florenc WidenmeyeriD, Niklas Wilhelm Warsing, Melike Sabry, Asina SultanbaiiD, Tobias Heinrich Santl, Arie GeerlofiD, Oleksandr Berezin, Silviu‐Vasile BodeaiD, Alessandra Moretti, Steffen SchneideriD, Fabian Joachim TheisiD, Julien GagneuriD, , Gil G. WestmeyeriD
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Abstract
Transcriptomics enables comprehensive, multiplexed characterization of cellular states, yet prevailing methods typically require cell fixation or lysis, precluding longitudinal analysis of RNA expression in living cells. Here, we present non-destructive transcriptomics by vesicular export (NTVE), a platform for multi-time-point monitoring of RNA expression dynamics in living cells. Stabilized RNA reporter barcodes can be selectively packaged and exported from cells via virus-like particles (VLPs) bearing bioorthogonal affinity handles for convenient multichannel tracking of co-cultured cells. Using an engineered poly(A)-binding protein adapter, NTVE exports endogenous transcripts from inducible human and murine cell lines with high concordance to conventional lysate-derived RNA-seq. NTVE captures transcriptome changes in response to genetic and chemical perturbations within the same cells over time using standard sequencing workflows. NTVE can further be equipped with fusogens to deliver mRNA-encoded effectors or ribonucleoprotein gene editors from sender cells, activating gene reporters in co-cultured recipient cells. We demonstrate the utility of NTVE for monitoring hiPSC differentiation through daily non-destructive transcriptomic profiling of lineage-specific marker dynamics.
- organism: human
- organism: mouse
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: trajectory inference
- research focus: perturbation response prediction
- approach: experimental assay
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