Qi Xu

CRISPR/Cas technologies have revolutionized the ability to redesign genomic information and tailor endogenous gene expression. Nevertheless, the discovery and development of new CRISPR/Cas systems has resulted in a lack of clarity surrounding the relative efficacies among these technologies in human cells. This deficit makes the optimal selection of CRISPR/Cas technologies in human cells unnecessarily challenging, which in turn hampers their adoption, and thus ultimately limits their utility. Here, we designed a series of endogenous testbed systems to methodically quantify and compare the genome editing, CRISPRi, and CRISPRa capabilities among 10 different natural and engineered Cas protein variants spanning Type II and Type V CRISPR/Cas families. We show that although all Cas protein variants are capable of genome editing and transcriptional control in human cells, hierarchies exist, particularly for genome editing and CRISPRa applications, wherein Cas9 ≥ Cas12a > Cas12e/Cas12j. Our findings also highlight the utility of our modular testbed platforms to rapidly and systematically quantify the functionality of practically any natural or engineered genomic-targeting Cas protein in human cells.

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^TMand 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.