Project description:Individual cells grown in culture exhibit remarkable differences in their growth, with some cells capable of forming large clusters, while others are limited or fail to grow at all. While these differences have been observed across cell lines and human samples, the growth dynamics and associated cell states remain poorly understood. In this study, we performed clonal tracing through imaging and cellular barcoding of an in vitro model of esophageal epithelial cells (EPC2-hTERT). We found that about 10% of clones grow exponentially, while the remaining have cells that become non-proliferative leading to a halt in the growth rate. Using mathematical models, we demonstrate two distinct growth behaviors: exponential and logistic. Further, we discovered that the propensity to grow exponentially is largely heritable through four doublings and that the less proliferative clones can become highly proliferative through increasing plating density. Combining barcoding with single-cell RNA-sequencing (scRNA-seq), we identified the cellular states associated with the highly proliferative clones, which include genes in the WNT and PI3K pathways. Finally, we identified an enrichment of cells resembling the highly proliferative cell state in the proliferating healthy human esophageal epithelium.
Project description:Stochastic differences among clonal cells can initiate cell fate decisions in development or cause cell-to-cell differences in the responses to drugs or extracellular ligands. We hypothesize that some of this phenotypic variability is caused by stochastic fluctuations in the activities of transcription factors. We tested this hypothesis in NIH3T3-CG cells using the response to Hedgehog signaling as a model cellular response. Here we present evidence for the existence of distinct fast and slow responding substates of NIH3T3-CG cells. These two substates have distinct expression profiles, and fluctuations in the activity of the Prrx1 transcription factor (TF) underlie some of the differences in expression and responsiveness between fast and slow cells. We speculate that similar variability in other TFs may underlie other phenotypic differences among genetically identical cells.
Project description:Stochastic differences among clonal cells can initiate cell fate decisions in development or cause cell-to-cell differences in the responses to drugs or extracellular ligands. We hypothesize that some of this phenotypic variability is caused by stochastic fluctuations in the activities of transcription factors. We tested this hypothesis in NIH3T3-CG cells using the response to Hedgehog signaling as a model cellular response. Here we present evidence for the existence of distinct fast and slow responding substates of NIH3T3-CG cells. These two substates have distinct expression profiles, and fluctuations in the activity of the Prrx1 transcription factor (TF) underlie some of the differences in expression and responsiveness between fast and slow cells. We speculate that similar variability in other TFs may underlie other phenotypic differences among genetically identical cells.
Project description:Phenotypic variability among different knockout clones of the same gene is a common problem confounding the establishment of robust genotype-phenotype correlations. Optimized genome editing protocols to enhance reproducibility include measures to reduce off-target effects. However, even if current state-of-the-art protocols are applied phenotypic variability is frequently observed. Here we identify heterogeneity of wild-type cells as an important and often neglected confounding factor in genome-editing experiments. We demonstrate that isolation of individual wild-type clones from an apparently homogenous stable cell line uncovers significant phenotypic differences between clones. Strikingly, we observe hundreds of differentially regulated transcripts when comparing two populations of wild-type cells. Heterogeneity of wild-type cells thus contributes to variability in genome-edited cells when these are generated through isolation of clones. We show that the generation of monoclonal isogenic wild-type cells prior to genomic manipulation reduces phenotypic variability.
Project description:Due to rapid cell turnover, the esophageal stratified squamous epithelium must maintain homeostasis. This process is insured by a long-lived subpopulation of basal stem cells that express Keratin 15 (Krt15). However, the mechanisms that specifically control their characteristics, i.e. self-renewal, multipotency and regeneration, remain unknown. Interestingly, MutS Homolog 2 (Msh2), implicated in the mismatch repair pathway, is the most upregulated gene in Krt15+ esophageal stem cells compared to Krt15- cells. Accentuated DNA repair capacity is often observed in stem cells to maintain their genomic integrity and avoid acquisition of mutations. Hence, the aim of this study was to evaluate the effects of Msh2 loss on stem cell functions such as differentiation, clonogenicity and proliferation in murine esophageal organoids. Msh2-depleted organoids were generated by CRISPR/Cas9. They displayed morphogenic alterations and major homeostasis perturbations. Cell differentiation was decreased while clonogenicity and proliferation were increased. Loss of Msh2 also caused lower expression levels of stem cell markers and changes in resistance to chemotherapy drugs. Proteomic analysis confirmed variations in epithelial cell differentiation and showed major changes in proteins associated with metabolic processes. In line with these results, metabolomic analysis confirmed altered abundance of various metabolites of the TCA cycle and biosynthetic pathways. In conclusion, these results showed that Msh2 is implicated in the homeostasis of esophageal organoids potentially through metabolic rewiring.
Project description:Cancer cells exhibit dramatic differences in gene expression at the single-cell level which can predict whether they become resistant to treatment. Treatment perpetuates this heterogeneity, resulting in a diversity of cell states among resistant clones. However, it remains unclear whether these differences lead to distinct responses when another treatment is applied or the same treatment is continued. In this study, we combined single-cell RNA-sequencing with barcoding to track resistant clones through prolonged and sequential treatments. We found that cells within the same clone have similar gene expression states after multiple rounds of treatment. Moreover, we demonstrated that individual clones have distinct and differing fates, including growth, survival, or death, when subjected to a second treatment or when the first treatment is continued. By identifying gene expression states that predict clone survival, this work provides a foundation for selecting optimal therapies that target the most aggressive resistant clones within a tumor.
Project description:This SuperSeries is composed of the following subset Series: GSE37200: Gene expression profiling of Barrett’s esophageal tissues and esophageal adenocarcinoma specimens GSE37201: Gene expression profiling of esophageal adenocarcinoma Refer to individual Series