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

Tam Vu, Alexander Vallmitjana, Joshua Gu, Kieu La, Qi Xu, Jesus Flores, Jan Zimak, Jessica Shiu, Linzi Hosohama, Jie Wu, Christopher Douglas, Marian L. Waterman, Anand Ganesan, Per Niklas Hedde, Enrico Gratton () and Weian Zhao ()
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Tam Vu: University of California, Irvine
Alexander Vallmitjana: University of California, Irvine
Joshua Gu: University of California, Irvine
Kieu La: University of California, Irvine
Qi Xu: University of California, Irvine
Jesus Flores: University of California, Irvine
Jan Zimak: University of California, Irvine
Jessica Shiu: University of California, Irvine
Linzi Hosohama: University of California, Irvine
Jie Wu: University of California, Irvine
Christopher Douglas: University of California, Irvine
Marian L. Waterman: University of California, Irvine
Anand Ganesan: University of California, Irvine
Per Niklas Hedde: University of California, Irvine
Enrico Gratton: University of California, Irvine
Weian Zhao: University of California, Irvine

Nature Communications, 2022, vol. 13, issue 1, 1-14

Abstract: 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.

Date: 2022
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DOI: 10.1038/s41467-021-27798-0

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