Back

Uranium-bearing dust induces differentiation and expansion of enteroendocrine cells in human colonoids

Atanga, R.; Appell, L. L.; Lauer, F. T.; Brearley, A.; Campen, M. J.; Castillo, E. F.; In, J. G.

2023-08-10 cell biology
10.1101/2023.08.10.552796 bioRxiv
Show abstract

Chronic exposure to environmental toxins and heavy metals has been associated with intestinal inflammation, increased susceptibility to pathogen-induced diseases, and higher incidences of colorectal cancer, all of which have been steadily increasing in prevalence for the past 40 years. The negative effects of heavy metals on barrier permeability and inhibition of intestinal epithelial healing have been described; however, transcriptomic changes within the intestinal epithelial cells and impacts on lineage differentiation are largely unknown. Uranium exposure remains an important environmental legacy and physiological health concern, with hundreds of abandoned uranium mines located in the Southwestern United States largely impacting underserved indigenous communities. Herein, using human colonoids, we defined the molecular and cellular changes that occur in response to uranium bearing dust (UBD) exposure. We used single cell RNA sequencing to define the molecular changes that occur to specific identities of colonic epithelial cells. We demonstrate that this environmental toxicant disrupts proliferation and induces hyperplastic differentiation of secretory lineage cells, particularly enteroendocrine cells (EEC). EECs respond to UBD exposure with increased differentiation into de novo EEC sub-types not found in control colonoids. This UBD-induced EEC differentiation does not occur via canonical transcription factors NEUROG3 or NEUROD1. These findings highlight the significance of crypts-based proliferative cells and secretory cell differentiation as major colonic responses to heavy metal-induced injury.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.