Literature DB >> 18094768

Microfluidic flow-encoded switching for parallel control of dynamic cellular microenvironments.

Kevin R King1, Sihong Wang, Arul Jayaraman, Martin L Yarmush, Mehmet Toner.   

Abstract

The temporal pattern of a biological stimulus is an important determinant of the resulting cellular response. We present a microfluidic parallel perfusion culture system for controlling the dynamics of soluble cell microenvironments while simultaneously performing live-cell imaging of cellular responses. A "Flow-encoded Switching" (FES) design strategy is developed to simultaneously deliver many different temporal profiles of stimuli, including pulse train widths, lengths, and frequencies, to downstream adherent cells using a single input control. The design strategy uses principles of laminar flow and diffusion-limited mixing to encode the state of the network (the instantaneous stimulus concentrations in each channel) into the ratio of two flow rates, which is controlled by a single differential pressure. To demonstrate the utility of this experimental system, we investigated the effect of dynamic stimuli on NFkappaB transcriptional activation and cell fate determination. Our results illustrate that transcriptional responses and cell fate decisions depend both quantitatively and qualitatively on the timing of the stimulus. In summary, by encoding dynamic stimuli in a single input pressure, microfluidic flow-encoded switching offers a scalable experimental method for systematically probing the functional significance of temporally patterned cellular environments.

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Year:  2007        PMID: 18094768     DOI: 10.1039/b716962k

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  30 in total

Review 1.  Microfluidic technologies for temporal perturbations of chemotaxis.

Authors:  Daniel Irimia
Journal:  Annu Rev Biomed Eng       Date:  2010-08-15       Impact factor: 9.590

2.  Solving medical problems with BioMEMS.

Authors:  Erkin Seker; Jong Hwan Sung; Michael L Shuler; Martin L Yarmush
Journal:  IEEE Pulse       Date:  2011-11       Impact factor: 0.924

Review 3.  Opportunities for microfluidic technologies in synthetic biology.

Authors:  Shelly Gulati; Vincent Rouilly; Xize Niu; James Chappell; Richard I Kitney; Joshua B Edel; Paul S Freemont; Andrew J deMello
Journal:  J R Soc Interface       Date:  2009-05-27       Impact factor: 4.118

4.  Linear conversion of pressure into concentration, rapid switching of concentration, and generation of linear ramps of concentration in a microfluidic device.

Authors:  Micha Adler; Alex Groisman
Journal:  Biomicrofluidics       Date:  2012-04-13       Impact factor: 2.800

Review 5.  Concise review: microfluidic technology platforms: poised to accelerate development and translation of stem cell-derived therapies.

Authors:  Drew M Titmarsh; Huaying Chen; Nick R Glass; Justin J Cooper-White
Journal:  Stem Cells Transl Med       Date:  2013-12-05       Impact factor: 6.940

Review 6.  Physiologically relevant organs on chips.

Authors:  Kyungsuk Yum; Soon Gweon Hong; Kevin E Healy; Luke P Lee
Journal:  Biotechnol J       Date:  2013-12-04       Impact factor: 4.677

7.  Microfluidic perfusion system for automated delivery of temporal gradients to islets of Langerhans.

Authors:  Xinyu Zhang; Michael G Roper
Journal:  Anal Chem       Date:  2009-02-01       Impact factor: 6.986

8.  Transcription factor network reconstruction using the living cell array.

Authors:  Eric Yang; Martin L Yarmush; Ioannis P Androulakis
Journal:  J Theor Biol       Date:  2008-10-22       Impact factor: 2.691

9.  Vacuum-assisted cell loading enables shear-free mammalian microfluidic culture.

Authors:  Martin Kolnik; Lev S Tsimring; Jeff Hasty
Journal:  Lab Chip       Date:  2012-11-21       Impact factor: 6.799

10.  Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering.

Authors:  Filippo Menolascina; Domenico Bellomo; Thomas Maiwald; Vitoantonio Bevilacqua; Caterina Ciminelli; Angelo Paradiso; Stefania Tommasi
Journal:  BMC Bioinformatics       Date:  2009-10-15       Impact factor: 3.169

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