Title

Dissecting Particle Uptake Heterogeneity in a Cell Population using Bayesian Analysis

Abstract

Individual cells in a solution display variable uptake of nanomaterials, peptides, and nutrients. Such variability reflects their heterogeneity in endocytic capacity. In a recent work, we have shown that the endocytic capacity of a cell depends on its size and surface density of endocytic components (transporters). We also demonstrated that in MDA-MB-231 breast cancer cells, the cell-surface transporter density (n) may decay with cell radius (r) following the power rule n ~ rα, where α ≈ −1. In this work, we investigate how n and r may independently contribute to the endocytic heterogeneity of a cell population. Our analysis indicates that the smaller cells display more heterogeneity because of the higher stochastic variations in n. By contrast, the larger cells display a more uniform uptake, reflecting less-stochastic variations in n. We provide analyses of these dependencies by establishing a stochastic model. Our analysis reveals that the exponent α in the above relationship is not a constant; rather, it is a random variable whose distribution depends on cell size r. Using Bayesian analysis, we characterize the cell-size-dependent distributions of α that accurately capture the particle uptake heterogeneity of MDA-MB-231 cells.

Department(s)

Chemical and Biochemical Engineering

Comments

Research presented in this work was partly supported by the National Science Foundation CBET-CDS&E grant No. 1609642.

International Standard Serial Number (ISSN)

0006-3495; 1542-0086

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2020 Biophysical Society, All rights reserved.

Publication Date

01 Apr 2020

PubMed ID

32101713

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