Non-genetic differences underlie variability in proliferation among esophageal epithelial clones

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.

Authors

Institutions

Publication Details

Journal
PLoS Computational Biology
Published
2024-10-28
DOI
https://doi.org/10.1371/journal.pcbi.1012360
Citations
4
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.94

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Non-genetic differences underlie variability in proliferation among esophageal epithelial clones

Rodrigo A. Gier, Sydney M. Shaffer, Raúl A. Reyes Hueros
4 citations
PLoS Computational Biology
Single-cell and spatial transcriptomics
0.94
article

Non-genetic differences underlie variability in proliferation among esophageal epithelial clones

Rodrigo A. Gier, Sydney M. Shaffer, Raúl A. Reyes Hueros
article en
4 citations

Abstract

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.

PLoS Computational BiologyVol. 20(10)
University of Pennsylvania (US)
National Science Foundation, University of Pennsylvania, Institute for Translational Medicine and Therapeutics, National Institutes of Health, Perelman School of Medicine, University of Pennsylvania, National Center for Advancing Translational Sciences, Common Fund
Openalex Percentile: Top 25%
Single-cell and spatial transcriptomics
0.94
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.