Comparative single-cell transcriptomes of dose and time dependent epithelial–mesenchymal spectrums

Abstract

Epithelial–mesenchymal transition (EMT) is a cellular process involved in development and disease progression. Intermediate EMT states were observed in tumors and fibrotic tissues, but previous in vitro studies focused on time-dependent responses with single doses of signals; it was unclear whether single-cell transcriptomes support stable intermediates observed in diseases. Here, we performed single-cell RNA-sequencing with human mammary epithelial cells treated with multiple doses of TGF-β. We found that dose-dependent EMT harbors multiple intermediate states at nearly steady state. Comparisons of dose- and time-dependent EMT transcriptomes revealed that the dose-dependent data enable higher sensitivity to detect genes associated with EMT. We identified cell clusters unique to time-dependent EMT, reflecting cells en route to stable states. Combining dose- and time-dependent cell clusters gave rise to accurate prognosis for cancer patients. Our transcriptomic data and analyses uncover a stable EMT continuum at the single-cell resolution, and complementary information of two types of single-cell experiments.

Cooperative RNA degradation stabilizes intermediate epithelial-mesenchymal states and supports a phenotypic continuum

“…To test this prediction, we next analyzed two single-cell RNA-sequencing (scRNA-seq) datasets from TGF-β-driven EMT. Transcriptome data for 3,568 A549 cells from a time course experiment ( Cook and Vanderhyden, 2020 ) and for 11,220 MCF10A cells from a dose-dependent, nearly steady-state experiment ( Panchy et al., 2022 ), were visualized using Uniform Mani-fold Approximation and Projection (UMAP). Consistent with earlier analyses ( Cook and Vanderhyden, 2020 ; Panchy et al., 2022 ), cells were distributed in continuous space for each dataset ( Figure 5 A), suggesting an EMT continuum.…”

“…Transcriptome data for 3,568 A549 cells from a time course experiment ( Cook and Vanderhyden, 2020 ) and for 11,220 MCF10A cells from a dose-dependent, nearly steady-state experiment ( Panchy et al., 2022 ), were visualized using Uniform Mani-fold Approximation and Projection (UMAP). Consistent with earlier analyses ( Cook and Vanderhyden, 2020 ; Panchy et al., 2022 ), cells were distributed in continuous space for each dataset ( Figure 5 A), suggesting an EMT continuum. Furthermore, median expression of ZEB1 positively correlated with the progression of EMT, whereas that of CDH1 had the opposite trend ( Figures 5 B and 5C) (the negative correlation of CDH1 in A549 cells was not significant due to low detection rate).…”

“…While it is expected that several gene regulatory mechanisms can generate multistable systems ( Angeli et al., 2004 ; Li et al., 2017 ; Markevich et al., 2004 ), the predicted co-existing cell states from cooperative RNA degradation models were not validated experimentally in this study, and they warrant future work. The observed EMT continuum at the transcriptome level ( Cook and Vanderhyden, 2020 ; Deshmukh et al., 2021 ; Panchy et al., 2022 ) does not exclude the possibility that only a few cell states emerge post-translationally to govern cellular phenotypes in a more discrete manner. Future work is needed to quantitatively characterize the continuity of EMT spectrum in terms of functional phenotypes.…”

“…The motivation to build our models derived from inconsistencies between existing EMT models that predict a paucity of EMT intermediate states, and experimental single-cell transcriptomic data that have been interpreted to support a wealth of states in a phenotypic continuum ( Cook and Vanderhyden, 2020 ; Deshmukh et al., 2021 ; Panchy et al., 2022 ). It should be noted that some continuum-like expression distributions revealed by scRNA-seq may be due to technical noise, whose effects on EMT progression warrant future investigation.…”

“…We analyzed two datasets for validating some predictions from our final model that includes miR-101. Single-cell RNA-sequencing data for TGF-β induced EMT in A549 lung epithelial cell line ( Cook and Vanderhyden, 2020 ) ( GSE147405 ), and in MCF10A breast epithelial cell line ( Panchy et al., 2022 ) ( GSE213753 ) were obtained from NCBI Gene Expression Omnibus (accessions in key resources table ). The A549 cells were treated with a single dose of TGF-β and their data have time labels of 0-7 days.…”