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Morphological profiling by high-throughput single-cell biophysical fractometry

Zhang, Z.; Lee, K. C. M.; Siu, D. M. D.; Lai, Q. T. K.; Lam, E. Y. M.; Tsia, K. K. M.

2022-05-24 cell biology
10.1101/2022.05.24.493226 bioRxiv
Show abstract

Complex and irregular cell architecture is known to statistically exhibit fractal geometry, i.e., a pattern resembles a smaller part of itself. Although fractal variations in cells are proven to be closely associated with the disease-related phenotypes that are otherwise obscured in the standard cell-based assays, fractal analysis with single-cell precision remains largely unexplored. To close this gap, here we develop an image-based approach that quantifies a multitude of single-cell biophysical fractal-related properties at subcellular resolution. Taking together with its high-throughput single-cell imaging performance (~10,000 cells/sec), this technique, termed single-cell biophysical fractometry, offers sufficient statistical power for delineating the cellular heterogeneity, in the context of classification of lung-cancer cell subtypes and tracking of cell-cycle progression. Further correlative fractal analysis shows that single-cell biophysical fractometry can enrich the standard morphological profiling depth and spearhead systematic fractal analysis of how cell morphology encodes cellular health and pathological conditions.

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