Identifying cell-to-cell variability in internalization using flow cytometry. Issue 190 (25th May 2022)

• Record Type: Journal Article
• Authors: Browning, Alexander P.; Ansari, Niloufar; Drovandi, Christopher; Johnston, Angus P. R.; Simpson, Matthew J.; Jenner, Adrianne L.
• Is Part Of: Journal of the Royal Society interface. Volume 19:Issue 190(2022)
• Publication Date: 2022-05-25
• Subjects: heterogeneity -- flow cytometry -- internalization -- endocytosis -- noise -- approximate Bayesian computation; Physical sciences -- Research -- Periodicals; Life sciences -- Research -- Periodicals; Interdisciplinary research -- Periodicals; 570.5
• DOI: 10.1098/rsif.2022.0019
• Languages: English
• ISSNs: 1742-5689

Abstract

Abstract : Biological heterogeneity is a primary contributor to the variation observed in experiments that probe dynamical processes, such as the internalization of material by cells. Given that internalization is a critical process by which many therapeutics and viruses reach their intracellular site of action, quantifying cell-to-cell variability in internalization is of high biological interest. Yet, it is common for studies of internalization to neglect cell-to-cell variability. We develop a simple mathematical model of internalization that captures the dynamical behaviour, cell-to-cell variation, and extrinsic noise introduced by flow cytometry. We calibrate our model through a novel distribution-matching approximate Bayesian computation algorithm to flow cytometry data of internalization of anti-transferrin receptor antibody in a human B-cell lymphoblastoid cell line. This approach provides information relating to the region of the parameter space, and consequentially the nature of cell-to-cell variability, that produces model realizations consistent with the experimental data. Given that our approach is agnostic to sample size and signal-to-noise ratio, our modelling framework is broadly applicable to identify biological variability in single-cell data from internalization assays and similar experiments that probe cellular dynamical processes.