Miriuka, S. G. | Search bioRxiv

bioRxiv2020

Downregulation of E-cadherin in pluripotent stem cells triggers partial EMT

Epithelial to mesenchymal transition (EMT) is a critical cellular process that has been well characterized during embryonic development and cancer metastasis and it also is implicated in several physiological and pathological events including embryonic stem cell differentiation. During early stages of differentiation, human embryonic stem cells pass through EMT where deeper morphological, molecular and biochemical changes occur. Though initially considered as a decision between two states, EMT process is now regarded as a fluid transition where cells exist on a spectrum of intermediate states. In this work, using a CRISPR interference system in human embryonic stem cells, we describe a molecular characterization of the effects of downregulation of E-cadherin, one of the main initiation events of EMT, as a unique start signal. Our results suggest that the decrease and delocalization of E-cadherin causes an incomplete EMT where cells retain their undifferentiated state while expressing several characteristics of a mesenchymal-like pheno-type. Namely, we found that E-cadherin downregulation induces SNAI1 and SNAI2 upregulation, promotes MALAT1 and LINC-ROR downregulation, modulates the expression of tight junction occludin 1 and gap junction connexin 43, increases human embryonic stem cells migratory capacity and delocalize b-catenin. Altogether, we believe our results provide a useful tool to model the molecular events of an unstable intermediate state and further identify multiple layers of molecular changes that occur during partial EMT.

cell biology↗

bioRxiv2020

celldeath: a tool for simple detection of cell death in transmitted light microscopy images by visual deep learning analysis

Cell death experiments are routinely done in many labs around the world, these experiments are the backbone of many assays for drug development. Cell death detection is usually performed in many ways, and requires time and reagents. However, cell death is preceded by slight morphological changes in cell shape and texture. In this paper, we trained a neural network to classify cells undergoing cell death. We found that the network was able to highly predict cell death after one hour of exposure to camptothecin. Moreover, this prediction largely outperforms human ability. Finally, we provide a simple python tool that can broadly be used to detect cell death.

cell biology↗