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Author Notes:

Hang Lu: Georgia Institute of Technology, School of Chemical & Biomolecular Engineering, 311 Ferst Drive, N.W., Atlanta, GA 30332-0100. Fax: 404 894 4200; Tel: 404 894 8473; hang.lu@chbe.gatech.edu.



  • Science & Technology
  • Life Sciences & Biomedicine
  • Physical Sciences
  • Biochemical Research Methods
  • Chemistry, Multidisciplinary
  • Chemistry, Analytical
  • Nanoscience & Nanotechnology
  • Biochemistry & Molecular Biology
  • Chemistry
  • Science & Technology - Other Topics
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Parallel multi-time point cell stimulation and lysis on-chip for studying early signaling events in T cell activation


Journal Title:

Lab on a Chip


Volume 9, Number 4


, Pages 536-544

Type of Work:

Article | Post-print: After Peer Review


Dynamics of complex signaling networks are important to many biological problems. Quantitative data at early time points after cellular stimulation are necessary for accurate model generation. However, the large amount of data needed is often extremely time-consuming and expensive to acquire with conventional methods. We present a two-module microfluidic platform for simultaneous multi-time point stimulation and lysis of T cells for early time point signaling activation with a resolution down to 20 s using only small amounts of cells and reagents. The key design features are rapid mixing of reagents and uniform splitting into eight channels for simultaneous collection of multi-time point data. Chaotic mixing was investigated via computational fluid dynamic modeling, and was used to achieve rapid and complete mixing. This modular device is flexible - with easy adjustment of the setup, a wide range of time points can be achieved. We show that treatment in the device does not elicit adverse cellular stress in Jurkat cells. The activation of six important proteins in the signaling cascade was quantified upon stimulation with a soluble form of α-CD3. The dynamics from device and conventional methods are similar, but the microdevice exhibits significantly less error between experiments. We envision this high-throughput format to enable simple and fast generation of large sets of quantitative data, with consistent sample handling, for many complex biological systems.

Copyright information:

© The Royal Society of Chemistry.

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