Paper
5 March 2013 Microscale tools for measuring spatiotemporal chemical gradients in biological systems
John B. Wydallis, Charles S. Henry, David S. Dandy, Stuart Tobet
Author Affiliations +
Abstract
Chemical gradients drive many processes in biology, ranging from nerve signal transduction to ovulation. At present, microscopy is the primary tool used to understand these gradients. Microscopy has provided many important breakthroughs in our understanding of the fundamental biology, but is limited due to the need to incorporate fluorescent molecules into a biological system. As a result, there is a need to develop tools that can measure chemical gradient formation in biological systems that do not require fluorescent modification of the molecules in question, can be multiplexed to measure more than one molecule and is compatible with a variety of biological sample types, including in vitro cell cultures and ex vivo tissue slices. Work from our group centered on the development of microscale tools to measure chemical gradients will be presented. In this project, we have developed a microfluidic interface that allows for sampling from underneath a tissue slice or in vitro cell culture system. The sampling system can resolve up to 19 different ports and can be interfaced with either electrochemical or fluorescence-based detection methods. Using these two detection methods, we are capable of analyzing the release of either small molecule metabolites or proteins and peptides using immunoassays.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John B. Wydallis, Charles S. Henry, David S. Dandy, and Stuart Tobet "Microscale tools for measuring spatiotemporal chemical gradients in biological systems", Proc. SPIE 8570, Frontiers in Biological Detection: From Nanosensors to Systems V, 857009 (5 March 2013); https://doi.org/10.1117/12.2005640
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KEYWORDS
Ovary

Tissues

Electrodes

Molecules

Microfluidics

Chemical analysis

Microscopy

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