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Identification of a novel gene signature of ES cells self-renewal fluctuation through system-wide analysis.

ABSTRACT: Embryonic Stem cells (ESCs) can be differentiated into ectoderm, endoderm, and mesoderm derivatives, producing the majority of cell types. In regular culture conditions, ESCs' self-renewal is maintained through molecules that inhibit spontaneous differentiation enabling long-term cellular expansion. This undifferentiating condition is characterized by multiple metastable states that fluctuate between self-renewal and differentiation balance. Here, we aim to characterize the high-pluripotent ESC metastate marked by the expression of Zscan4 through a supervised machine learning framework based on an ensemble of support vector machine (SVM) classifiers. Our study revealed a leukaemia inhibitor factor (Lif) dependent not-canonical pluripotency signature (AF067063, BC061212, Dub1, Eif1a, Gm12794, Gm13871, Gm4340, Gm4850, Tcstv1/3, and Zfp352), that specifically marks Zscan4 ESCs' fluctuation. This novel ESC metastate is enhanced by high-pluripotency culture conditions obtained through Extracellular signal Regulated-Kinase (ERK) and Glycogen synthase kinase-3 (Gsk-3) signaling inhibition (2i). Significantly, we reported that the conditional ablation of the novel ESC metastate marked by the expression of Gm12794 is required for ESCs self-renewal maintenance. In conclusion, we extend the comprehension of ESCs biology through the identification of a novel molecular signature associated to pluripotency programming.

SUBMITTER: Cerulo L

PROVIDER: S-EPMC3879232 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Identification of a novel gene signature of ES cells self-renewal fluctuation through system-wide analysis.

Cerulo Luigi L Tagliaferri Daniela D Marotta Pina P Zoppoli Pietro P Russo Filomena F Mazio Claudia C DeFelice Mario M Ceccarelli Michele M Falco Geppino G

PloS one 20140102 1

Embryonic Stem cells (ESCs) can be differentiated into ectoderm, endoderm, and mesoderm derivatives, producing the majority of cell types. In regular culture conditions, ESCs' self-renewal is maintained through molecules that inhibit spontaneous differentiation enabling long-term cellular expansion. This undifferentiating condition is characterized by multiple metastable states that fluctuate between self-renewal and differentiation balance. Here, we aim to characterize the high-pluripotent ESC ...[more]

PMID: 24392082

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Project description:Embryonic stem cells (ESCs), characterized by their ability to both self-renew and differentiate into multiple cell lineages, are a powerful model for biomedical research and developmental biology. Human and mouse ESCs share many features, yet have distinctive aspects, including fundamental differences in the signaling pathways and cell cycle controls that support self-renewal. Here, we explore the molecular basis of human ESC self-renewal using Bayesian network machine learning to integrate cell-type-specific, high-throughput data for gene function discovery. We integrated high-throughput ESC data from 83 human studies (~1.8 million data points collected under 1,100 conditions) and 62 mouse studies (~2.4 million data points collected under 1,085 conditions) into separate human and mouse predictive networks focused on ESC self-renewal to analyze shared and distinct functional relationships among protein-coding gene orthologs. Computational evaluations show that these networks are highly accurate, literature validation confirms their biological relevance, and reverse transcriptase polymerase chain reaction (RT-PCR) validation supports our predictions. Our results reflect the importance of key regulatory genes known to be strongly associated with self-renewal and pluripotency in both species (e.g., POU5F1, SOX2, and NANOG), identify metabolic differences between species (e.g., threonine metabolism), clarify differences between human and mouse ESC developmental signaling pathways (e.g., leukemia inhibitory factor (LIF)-activated JAK/STAT in mouse; NODAL/ACTIVIN-A-activated fibroblast growth factor in human), and reveal many novel genes and pathways predicted to be functionally associated with self-renewal in each species. These interactive networks are available online at www.StemSight.org for stem cell researchers to develop new hypotheses, discover potential mechanisms involving sparsely annotated genes, and prioritize genes of interest for experimental validation.

Dataset Information

Identification of a novel gene signature of ES cells self-renewal fluctuation through system-wide analysis.

Publications

Identification of a novel gene signature of ES cells self-renewal fluctuation through system-wide analysis.

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