Left-right (LR) asymmetry is a biologically conserved property in living organisms that can be observed in the asymmetrical arrangement of organs and tissues and in tissue morphogenesis, such as the directional looping of the gastrointestinal tract and heart. The expression of LR asymmetry in embryonic tissues can be appreciated in biased cell alignment. Previously an in vitro chirality assay was reported by patterning multiple cells on microscale defined geometries and quantified the cell phenotype–dependent LR asymmetry, or cell chirality. However, morphology and chirality of individual cells on micropatterned surfaces has not been well characterized. Here, a Python-based algorithm was developed to identify and quantify immunofluorescence stained individual epithelial cells on multicellular patterns. This approach not only produces results similar to the image intensity gradient-based method reported previously, but also can capture properties of single cells such as area and aspect ratio. We also found that cell nuclei exhibited biased alignment. Around 35% cells were misaligned and were typically smaller and less elongated. This new imaging analysis approach is an effective tool for measuring single cell chirality inside multicellular structures and can potentially help unveil biophysical mechanisms underlying cellular chiral bias both in vitro and in vivo.
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