Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10404-012-1125-1
Title: Microfluidic bolus induced gradient generator for live cell signalling
Authors: Ramji, R.
Roy, P. 
Keywords: Bound biomolecular cell surface gradients
Cell signalling
Gradient generation
Ligand binding
Mathematical modelling
Microfluidics
Issue Date: Jul-2013
Citation: Ramji, R., Roy, P. (2013-07). Microfluidic bolus induced gradient generator for live cell signalling. Microfluidics and Nanofluidics 15 (1) : 99-107. ScholarBank@NUS Repository. https://doi.org/10.1007/s10404-012-1125-1
Abstract: Major events in cell biology are initiated by the binding of ligands to cell surface receptors and/or their transport into cells. We present a study of a simple microchannel system that integrates a bolus generator and surface-Adhered cell culture domains. Our system allows the delivery of small packets or boluses of biomolecules to a cell population. Owing to pressure driven microfluidic flow of the bolus, a gradient of cell surface bound ligands is established along the length of the microchannel. Experimental data for the epidermal growth factor (EGF) binding to its receptor on A431 cells are presented. We highlight the effect of changing Peclet number (or flowrate), bolus shape, bolus volume and ligand concentration on the gradient formed longitudinally in the microchannel. A mathematical model describing the transient convection, diffusion, dispersion and binding of ligands to cell surface receptors is developed. The model provides essential design guidelines for our system with good qualitative agreement with experimental data. The results suggest ways to modulate the amount of bound ligand and the gradient independently. This simple microsystem is suitable for generating longer range gradients involving larger cell populations as compared to existing microfluidic systems. © 2012 Springer-Verlag Berlin Heidelberg.
Source Title: Microfluidics and Nanofluidics
URI: http://scholarbank.nus.edu.sg/handle/10635/67154
ISSN: 16134982
DOI: 10.1007/s10404-012-1125-1
Appears in Collections:Staff Publications

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