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Spatial transcriptomics using combinatorial fluorescence spectral and lifetime encoding, imaging and analysis.

Authors :
Vu, Tam
Vu, Tam
Vallmitjana, Alexander
Gu, Joshua
La, Kieu
Xu, Qi
Flores, Jesus
Zimak, Jan
Shiu, Jessica
Hosohama, Linzi
Wu, Jie
Douglas, Christopher
Waterman, Marian L
Ganesan, Anand
Hedde, Per Niklas
Gratton, Enrico
Zhao, Weian
Vu, Tam
Vu, Tam
Vallmitjana, Alexander
Gu, Joshua
La, Kieu
Xu, Qi
Flores, Jesus
Zimak, Jan
Shiu, Jessica
Hosohama, Linzi
Wu, Jie
Douglas, Christopher
Waterman, Marian L
Ganesan, Anand
Hedde, Per Niklas
Gratton, Enrico
Zhao, Weian
Source :
Nature communications; vol 13, iss 1, 169; 2041-1723
Publication Year :
2022

Abstract

Multiplexed mRNA profiling in the spatial context provides new information enabling basic research and clinical applications. Unfortunately, existing spatial transcriptomics methods are limited due to either low multiplexing or complexity. Here, we introduce a spatialomics technology, termed Multi Omic Single-scan Assay with Integrated Combinatorial Analysis (MOSAICA), that integrates in situ labeling of mRNA and protein markers in cells or tissues with combinatorial fluorescence spectral and lifetime encoded probes, spectral and time-resolved fluorescence imaging, and machine learning-based decoding. We demonstrate MOSAICA's multiplexing scalability in detecting 10-plex targets in fixed colorectal cancer cells using combinatorial labeling of five fluorophores with facile error-detection and removal of autofluorescence. MOSAICA's analysis is strongly correlated with sequencing data (Pearson's r = 0.96) and was further benchmarked using RNAscopeTM and LGC StellarisTM. We further apply MOSAICA for multiplexed analysis of clinical melanoma Formalin-Fixed Paraffin-Embedded (FFPE) tissues. We finally demonstrate simultaneous co-detection of protein and mRNA in cancer cells.

Details

Database :
OAIster
Journal :
Nature communications; vol 13, iss 1, 169; 2041-1723
Notes :
application/pdf, Nature communications vol 13, iss 1, 169 2041-1723
Publication Type :
Electronic Resource
Accession number :
edsoai.on1298732787
Document Type :
Electronic Resource