A conserved expression signature predicts growth rate and reveals cell & lineage-specific differences.

Elana J Fertig,Zhisheng Jiang,Lucas B Carey,Bernhard Payer,Marta Badia,Serena F Generoso

doi:10.1371/journal.pcbi.1009582

Abstract

Isogenic cells cultured together show heterogeneity in their proliferation rate. To determine the differences between fast and slow-proliferating cells, we developed a method to sort cells by proliferation rate, and performed RNA-seq on slow and fast proliferating subpopulations of pluripotent mouse embryonic stem cells (mESCs) and mouse fibroblasts. We found that slowly proliferating mESCs have a more naïve pluripotent character. We identified an evolutionarily conserved proliferation-correlated transcriptomic signature that is common to all eukaryotes: fast cells have higher expression of genes for protein synthesis and protein degradation. This signature accurately predicted growth rate in yeast and cancer cells, and identified lineage-specific proliferation dynamics during development, using C. elegans scRNA-seq data. In contrast, sorting by mitochondria membrane potential revealed a highly cell-type specific mitochondria-state related transcriptome. mESCs with hyperpolarized mitochondria are fast proliferating, while the opposite is true for fibroblasts. The mitochondrial electron transport chain inhibitor antimycin affected slow and fast subpopulations differently. While a major transcriptional-signature associated with cell-to-cell heterogeneity in proliferation is conserved, the metabolic and energetic dependency of cell proliferation is cell-type specific.

Highlights

Rates of cell growth and division vary greatly, even among isogenic cells of a single cell-type, cultured in the same optimal environment [1]
By performing RNA sequencing on cells sorted by their proliferation rate, this study identifies a gene expression signature capable of predicting proliferation rates in diverse eukaryotic cell types and species
To understand the causes and consequences of intrapopulation cell-to-cell heterogeneity in proliferation rate in mammalian cells we developed a method for sorting single mammalian cells by their proliferation rate (Figs 1 and S1)

Summary

Introduction

Rates of cell growth and division vary greatly, even among isogenic cells of a single cell-type, cultured in the same optimal environment [1]. Cell-to-cell heterogeneity in proliferation rate has important consequences for population survival in bacterial antibiotic resistance, stress resistance in budding yeast, and chemo-resistance in cancer [2,3,4,5,6,7,8,9,10]. A recent study has demonstrated semi-heritable cell-to-cell heterogeneity in gene expression in mammalian cells, which is associated with drug resistance in cancer [11] and time-lapse fluorescence microscopy has shown that cell-to-cell variability in the expression of some genes, such as p53 and p21, is associated with cell-to-cell variability in proliferation and survival [1,12]. Single-cell RNA sequencing measures transcriptomelevel heterogeneity but does not directly link this to cell-biological heterogeneity in organelle state, or dynamic heterogeneity in proliferation or drug resistance. While the presence of intrapopulation variation in proliferation, transcriptome, and organelle-state in both steady-state and in differentiation populations is well established, the relationship among the three remains unclear

Methods

Results

Discussion

Conclusion