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 J. Douglas, Marian L. Waterman, Anand K. Ganesan, Per Niklas Hedde, Enrico Gratton, Weian Zhao
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 RNAscope TM and LGC Stellaris TM . 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.