In the same cell, the proteome defines cellular state and the transcriptome marks transitions
TL;DR
A scalable technology is introduced that quantifies thousands of proteins and transcripts in the same cell, separating RNA from protein by tip-based C18 capture and pairing full-length RNA sequencing with latest-generation mass spectrometry to yield deep proteome and transcriptome from the same cells.
Abstract
Bulk transcriptome and proteome correlate only modestly, but this has not been investigated in the same cell or across cell-state changes. Here we introduce a scalable technology that quantifies thousands of proteins and transcripts in the same cell, separating RNA from protein by tip-based C18 capture and pairing full-length RNA sequencing with latest-generation mass spectrometry. In HeLa cells, transcript and protein abundances agree on the broad ranking within a cell (r = 0.45), but do not co-vary across the population (r = 0.038). In pluripotency transitions, only a third of matched transcripts and proteins change synchronously, yet the transcription factors defining each state stay tightly co-regulated. Transcript variance is several-fold larger than protein variance, reflecting transcriptional bursting and mRNA sampling noise. The proteome is thus the stable, low-noise definition of cell state, while the transcriptome marks cellular transitions; consequently, the proteome defines cell-state from far fewer cells. Highlights Multimodal workflow yields deep proteome and transcriptome from the same cells Transcript and protein rank similarly within a cell but are uncoupled across cells Only a third of RNA-protein pairs change together, yet state-defining TFs stay coupled Protein varies several-fold less than mRNA, defining state from far fewer cells
