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

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.

[1]  Taejeong Ha,et al.  mTORC1 accelerates retinal development via the immunoproteasome , 2018, Nature Communications.

[2]  Michael A Teitell,et al.  Pluripotent stem cell energy metabolism: an update , 2015, The EMBO journal.

[3]  Ben Lehner,et al.  Single cell functional genomics reveals the importance of mitochondria in cell-to-cell phenotypic variation , 2019, eLife.

[4]  Stanislas Leibler,et al.  Dynamic Persistence of Antibiotic-Stressed Mycobacteria , 2013, Science.

[5]  C. Parish,et al.  Fluorescent dyes for lymphocyte migration and proliferation studies , 1999, Immunology and cell biology.

[6]  C. Proud,et al.  mTORC1 signaling controls multiple steps in ribosome biogenesis. , 2014, Seminars in cell & developmental biology.

[7]  Eytan Ruppin,et al.  A Genome-Wide Systematic Analysis Reveals Different and Predictive Proliferation Expression Signatures of Cancerous vs. Non-Cancerous Cells , 2013, PLoS genetics.

[8]  Crystal S. Conn,et al.  Nutrient Signaling in Protein Homeostasis: An Increase in Quantity at the Expense of Quality , 2013, Science Signaling.

[9]  D. Cleveland,et al.  How to Survive Aneuploidy , 2010, Cell.

[10]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[11]  Myles A Brown,et al.  A recombinant murine retrovirus for simian virus 40 large T cDNA transforms mouse fibroblasts to anchorage-independent growth , 1986, Journal of virology.

[12]  D. Prober,et al.  Drosophila myc Regulates Cellular Growth during Development , 1999, Cell.

[13]  Ole Winther,et al.  Growth-rate regulated genes have profound impact on interpretation of transcriptome profiling in Saccharomyces cerevisiae , 2006, Genome Biology.

[14]  Lior Pachter,et al.  Erratum: Near-optimal probabilistic RNA-seq quantification , 2016, Nature Biotechnology.

[15]  Justin Guinney,et al.  GSVA: gene set variation analysis for microarray and RNA-Seq data , 2013, BMC Bioinformatics.

[16]  H. Niwa,et al.  Identification and characterization of subpopulations in undifferentiated ES cell culture , 2008, Development.

[17]  J. Baker,et al.  Gene expression across mammalian organ development , 2019, Nature.

[18]  F. Marincola,et al.  Mitochondrial Membrane Potential Identifies Cells with Enhanced Stemness for Cellular Therapy. , 2016, Cell metabolism.

[19]  A. Gautam,et al.  STATE , 2016, Intell. Serv. Robotics.

[20]  C. Tamm,et al.  A Comparative Study of Protocols for Mouse Embryonic Stem Cell Culturing , 2013, PloS one.

[21]  M. Saitou,et al.  Generation of eggs from mouse embryonic stem cells and induced pluripotent stem cells , 2013, Nature Protocols.

[22]  J. Nichols,et al.  Nanog safeguards pluripotency and mediates germline development , 2007, Nature.

[23]  D. Tranchina,et al.  Growth Rate-Dependent Global Amplification of Gene Expression , 2016, bioRxiv.

[24]  J. Nichols,et al.  The ability of inner-cell-mass cells to self-renew as embryonic stem cells is acquired following epiblast specification , 2014, Nature Cell Biology.

[25]  Richard D Riley,et al.  External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges , 2016, BMJ.

[26]  Bart De Moor,et al.  BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis , 2005, Bioinform..

[27]  James Chappell,et al.  Distinct Cell-Cycle Control in Two Different States of Mouse Pluripotency , 2017, Cell stem cell.

[28]  J. Sulston,et al.  The embryonic cell lineage of the nematode Caenorhabditis elegans. , 1983, Developmental biology.

[29]  S. Bhaumik,et al.  TOR Facilitates the Targeting of the 19S Proteasome Subcomplex To Enhance Transcription Complex Assembly at the Promoters of the Ribosomal Protein Genes , 2018, Molecular and Cellular Biology.

[30]  Gary D Bader,et al.  Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap , 2019, Nature Protocols.

[31]  Petr Svoboda,et al.  Stochastic NANOG fluctuations allow mouse embryonic stem cells to explore pluripotency , 2014, Development.

[32]  Paolo Romano,et al.  Cell Line Data Base: structure and recent improvements towards molecular authentication of human cell lines , 2008, Nucleic Acids Res..

[33]  B. Doble,et al.  The ground state of embryonic stem cell self-renewal , 2008, Nature.

[34]  Jeannie T. Lee,et al.  Chromosomes. A comprehensive Xist interactome reveals cohesin repulsion and an RNA-directed chromosome conformation. , 2015, Science.

[35]  Luca Magnani,et al.  Poised epigenetic states and acquired drug resistance in cancer , 2014, Nature Reviews Cancer.

[36]  K. Deisseroth,et al.  Dynamics of Retrieval Strategies for Remote Memories , 2011, Cell.

[37]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[38]  H. Ruohola-Baker,et al.  Metabolic remodeling during the loss and acquisition of pluripotency , 2017, Development.

[39]  N. Shoresh,et al.  Optimization of lag time underlies antibiotic tolerance in evolved bacterial populations , 2014, Nature.

[40]  B. Manning,et al.  Molecular logic of mTORC1 signalling as a metabolic rheostat , 2019, Nature Metabolism.

[41]  D. Felsher,et al.  MYC as a regulator of ribosome biogenesis and protein synthesis , 2010, Nature Reviews Cancer.

[42]  R. Irizarry,et al.  Missing data and technical variability in single‐cell RNA‐sequencing experiments , 2018, Biostatistics.

[43]  Fabian J Theis,et al.  Metabolic regulation of pluripotency and germ cell fate through α‐ketoglutarate , 2018, The EMBO journal.

[44]  D. Calvisi,et al.  A functional mammalian target of rapamycin complex 1 signaling is indispensable for c‐Myc‐driven hepatocarcinogenesis , 2017, Hepatology.

[45]  M. Eileen Dolan,et al.  Mixed Effects Modeling of Proliferation Rates in Cell-Based Models: Consequence for Pharmacogenomics and Cancer , 2012, PLoS genetics.

[46]  J. Gearhart,et al.  Pluripotency redux--advances in stem-cell research. , 2007, The New England journal of medicine.

[47]  D. Botstein,et al.  Coupling among growth rate response, metabolic cycle, and cell division cycle in yeast , 2011, Molecular biology of the cell.

[48]  S. Spencer,et al.  Spontaneously slow-cycling subpopulations of human cells originate from activation of stress-response pathways , 2019, PLoS biology.

[49]  D. Largaespada,et al.  mTORC1 Coordinates Protein Synthesis and Immunoproteasome Formation via PRAS40 to Prevent Accumulation of Protein Stress. , 2016, Molecular cell.

[50]  Andrew E. Jaffe,et al.  Bioinformatics Applications Note Gene Expression the Sva Package for Removing Batch Effects and Other Unwanted Variation in High-throughput Experiments , 2022 .

[52]  Jianzhu Chen,et al.  Homeostasis-Stimulated Proliferation Drives Naive T Cells to Differentiate Directly into Memory T Cells , 2000, The Journal of experimental medicine.

[53]  G. Lahav,et al.  Cell-to-Cell Variation in p53 Dynamics Leads to Fractional Killing , 2016, Cell.

[54]  A. Raj,et al.  Heterogeneous lineage marker expression in naive embryonic stem cells is mostly due to spontaneous differentiation , 2015, Scientific Reports.

[55]  Tatsunori B. Hashimoto,et al.  Quantifying Condition-Dependent Intracellular Protein Levels Enables High-Precision Fitness Estimates , 2013, PloS one.

[56]  David Venet,et al.  Most Random Gene Expression Signatures Are Significantly Associated with Breast Cancer Outcome , 2011, PLoS Comput. Biol..

[57]  A. Motter,et al.  Predicting growth rate from gene expression , 2018, Proceedings of the National Academy of Sciences.

[58]  Nick S. Jones,et al.  Connecting Variability in Global Transcription Rate to Mitochondrial Variability , 2010, PLoS biology.

[59]  E. Lander,et al.  Stochastic State Transitions Give Rise to Phenotypic Equilibrium in Populations of Cancer Cells , 2011, Cell.

[60]  A. Goldberg,et al.  Control of proteasomal proteolysis by mTOR , 2016, Nature.

[61]  Wouter Houthoofd,et al.  The embryonic cell lineage of the nematode Halicephalobus gingivalis (Nematoda: Cephalobina: Panagrolaimoidea) , 2007 .

[62]  J. Blenis,et al.  The mTORC1/S6K1 Pathway Regulates Glutamine Metabolism through the eIF4B-Dependent Control of c-Myc Translation , 2014, Current Biology.

[63]  Matthew J. Brauer,et al.  Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast. , 2008, Molecular biology of the cell.

[64]  Jialiang Liang,et al.  A mesenchymal-to-epithelial transition initiates and is required for the nuclear reprogramming of mouse fibroblasts. , 2010, Cell stem cell.

[65]  Aleksandra A. Kolodziejczyk,et al.  Single Cell RNA-Sequencing of Pluripotent States Unlocks Modular Transcriptional Variation , 2015, Cell stem cell.

[66]  Elliott Kieff,et al.  Genetic Analysis of Human Traits In Vitro: Drug Response and Gene Expression in Lymphoblastoid Cell Lines , 2008, PLoS genetics.

[67]  J. Wrana,et al.  Functional genomics reveals a BMP-driven mesenchymal-to-epithelial transition in the initiation of somatic cell reprogramming. , 2010, Cell stem cell.

[68]  C. Parish,et al.  New fluorescent dyes for lymphocyte migration studies. Analysis by flow cytometry and fluorescence microscopy. , 1990, Journal of immunological methods.

[69]  R. Sandberg,et al.  Single-Cell RNA-Seq Reveals Dynamic, Random Monoallelic Gene Expression in Mammalian Cells , 2014, Science.

[70]  Austin G Smith,et al.  The ground state of pluripotency. , 2010, Biochemical Society transactions.

[71]  Li Chen,et al.  Increased proteasome activity, ubiquitin-conjugating enzymes, and eEF1A translation factor detected in breast cancer tissue. , 2005, Cancer research.

[72]  A. Bishop,et al.  Embryonic stem cells , 2004, Cell proliferation.

[73]  K. Tanaka,et al.  Abnormally high expression of proteasomes in human leukemic cells. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[74]  Helga Thorvaldsdóttir,et al.  Molecular signatures database (MSigDB) 3.0 , 2011, Bioinform..

[75]  David van Dijk,et al.  Slow-growing cells within isogenic populations have increased RNA polymerase error rates and DNA damage , 2015, Nature Communications.

[76]  Edoardo M. Airoldi,et al.  Steady-state and dynamic gene expression programs in Saccharomyces cerevisiae in response to variation in environmental nitrogen , 2016, Molecular biology of the cell.

[77]  D. Pei,et al.  Metabolic switch and epithelial–mesenchymal transition cooperate to regulate pluripotency , 2020, The EMBO journal.

[78]  Jeannie T. Lee,et al.  Targeted Mutagenesis of Tsix Leads to Nonrandom X Inactivation , 1999, Cell.

[79]  C. Dang MYC, metabolism, cell growth, and tumorigenesis. , 2013, Cold Spring Harbor perspectives in medicine.

[80]  T. Hwa,et al.  Reduction of translating ribosomes enables Escherichia coli to maintain elongation rates during slow growth , 2016, Nature Microbiology.

[81]  S. Austad,et al.  Rapamycin extends life and health in C57BL/6 mice. , 2014, The journals of gerontology. Series A, Biological sciences and medical sciences.

[82]  M. Teitell,et al.  Alpha‐ketoglutarate: a “magic” metabolite in early germ cell development , 2018, The EMBO journal.

[83]  K. Polyak,et al.  Intra-tumour heterogeneity: a looking glass for cancer? , 2012, Nature Reviews Cancer.

[84]  N. Waterhouse,et al.  Measuring Mitochondrial Transmembrane Potential by TMRE Staining. , 2016, Cold Spring Harbor protocols.

[85]  N. Barkai,et al.  Coupling phenotypic persistence to DNA damage increases genetic diversity in severe stress , 2017, Nature Ecology &Evolution.

[86]  D. Kwiatkowski,et al.  Coordinated regulation of protein synthesis and degradation by mTORC1 , 2014, Nature.

[87]  D. Shore,et al.  Growth control and ribosome biogenesis. , 2009, Current opinion in cell biology.

[88]  Sasha F. Levy,et al.  Bet Hedging in Yeast by Heterogeneous, Age-Correlated Expression of a Stress Protectant , 2012, PLoS biology.

[89]  Iain G. Johnston,et al.  Mitochondrial Variability as a Source of Extrinsic Cellular Noise , 2011, PLoS Comput. Biol..

[90]  Shawn P. Driscoll,et al.  ES cell potency fluctuates with endogenous retrovirus activity , 2012, Nature.

[91]  Ben S. Wittner,et al.  Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1 , 2009, Nature.

[92]  F. Tang,et al.  Dynamic equilibrium and heterogeneity of mouse pluripotent stem cells with distinct functional and epigenetic states. , 2008, Cell stem cell.

[93]  J. Hampe,et al.  Increased proteasome subunit protein expression and proteasome activity in colon cancer relate to an enhanced activation of nuclear factor E2-related factor 2 (Nrf2) , 2009, Oncogene.

[94]  N. Balaban,et al.  A problem of persistence: still more questions than answers? , 2013, Nature Reviews Microbiology.

[95]  E. Birney,et al.  Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt , 2009, Nature Protocols.

[96]  Richard A Young,et al.  Control of the Embryonic Stem Cell State , 2011, Cell.

[97]  Jonathan S. Packer,et al.  A lineage-resolved molecular atlas of C. elegans embryogenesis at single-cell resolution , 2019, Science.

[98]  Gary D Bader,et al.  Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation , 2010, PloS one.

[99]  J. Nichols,et al.  Naive and primed pluripotent states. , 2009, Cell stem cell.