Abstract
Single-cell multiomics provides comprehensive insights into gene regulatory networks, cellular diversity, and temporal dynamics. Here, we introduce nanoSPLITS (nanodroplet SPlitting for Linked-multimodal Investigations of Trace Samples), an integrated platform that enables global profiling of the transcriptome and proteome from same single cells using RNA sequencing and mass spectrometry-based proteomics, respectively. Benchmarking of nanoSPLITS demonstrated excellent measurement precision, with deep proteomic and transcriptomic profiling of single-cells. We applied nanoSPLITS to cyclin-dependent kinase 1 inhibited cells and found phospho-signaling events could be quantified alongside global protein and mRNA measurements, providing new insights into cell cycle regulation. We also extended nanoSPLITS to single-cells isolated from human pancreatic islets, introducing an efficient approach for facile identification of unknown cell types, and detecting their protein markers by mapping transcriptomic data to existing large-scale single-cell RNA sequencing reference databases. Herein, we establish nanoSPLITS as a new multiomic technology incorporating global proteomics and anticipate the approach will be critical to furthering our understanding of single-cell systems.
Competing Interest Statement
J.C.B., J.W.B, and A.S. are employees of Scienion/Cellenion. Y.Z. is an employee of Genentech Inc. and shareholder of Roche Group. Battelle Memorial Institute has submitted a U.S. patent application for the design of nanoSPLITS devices and the associated operation methods (Application number: 17/954,834, filed 09/28/2022; Inventors: Y.Z., J. M. F., L.M.M., and L.P.T.; Status of application: Pending). Other authors declare no other competing interests.
Footnotes
We added new experiments to apply the technology in primary human cells and developed an efficient approach for facile identification of unknown cell types, and detecting their protein markers by mapping transcriptomic data to existing large-scale single-cell RNA sequencing reference databases.