A chemical waveform synthesizer

Olofsson, Jessica; Bridle, Helen; Sinclair, Jon; Granfeldt, Daniel; Sahlin, Eskil; Orwar, Owe

doi:10.1073/pnas.0500230102

Cited by 47 publications

(53 citation statements)

References 38 publications

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“…The observed rise time ͑0%-90% of max concentration͒ is less than 33 ms, which is the time between consecutive frames for our video acquisition. This result is on par with previously published results using mechanical scanning, 9 and is one order of magnitude faster than the previously reported microfluidic reagent exchange. 3 Reagent consumption per data point is proportional with the flow rate of the reagent in the injection channel and the time of reagent application to the trapped cells.…”

supporting

confidence: 89%

“…8 In order to increase the throughput of this technique, Orwar and co-workers replaced the dual stream scanning probe with several parallel microfluidic channels that create different laminar flowing streams in open volumes to study fast kinetic interactions on the cell surface. 9 Because it is difficult to maintain a fixed distance between the trapped cell and the perfusion exit ports, it is difficult to collect accurate data using mechanical scanning. The drawbacks to this technique are the relatively low throughput and complex experimental setup.…”

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confidence: 99%

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Soft-state biomicrofluidic pulse generator for single cell analysis

Sabounchi

Ionescu-Zanetti

Chen

et al. 2006

Applied Physics Letters

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We present the design, fabrication, and characterization of a soft-state biomicrofluidic pulse generator for single cell analysis. Hydrodynamic cell trapping via lateral microfluidic junctions allows the trapping of single cells from a bulk suspension. Microfluidic injection sites adjacent to the cell-trapping channels enable the pulsed delivery of nanoliter volumes of biochemical reagent. We demonstrated the application and removal of reagent at a frequency of 10Hz with a rise time of less than 33ms and a reagent consumption rate of 0.2nL∕s. It is shown that this system operates as a low-pass filter with a cutoff frequency of 7Hz.

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supporting

confidence: 89%

mentioning

confidence: 99%

Soft-state biomicrofluidic pulse generator for single cell analysis

Sabounchi

Ionescu-Zanetti

Chen

et al. 2006

Applied Physics Letters

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“…The spatiotemporal dynamics of such networks (2, 4) is especially challenging and interesting to understand, and to reproduce in synthetic model systems (2,3,5,(9)(10)(11). Simplified physical or chemical model systems are attractive for understanding biological complexity because these models can be made simple to probe, analyze, and understand.…”

mentioning

confidence: 99%

Modular chemical mechanism predicts spatiotemporal dynamics of initiation in the complex network of hemostasis

Kastrup

Runyon

Shen

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

103

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This article demonstrates that a simple chemical model system, built by using a modular approach, may be used to predict the spatiotemporal dynamics of initiation of blood clotting in the complex network of hemostasis. Microfluidics was used to create in vitro environments that expose both the complex network and the model system to surfaces patterned with patches presenting clotting stimuli. Both systems displayed a threshold response, with clotting initiating only on isolated patches larger than a threshold size. The magnitude of the threshold patch size for both systems was described by the Damkö hler number, measuring competition of reaction and diffusion. Reaction produces activators at the patch, and diffusion removes activators from the patch. The chemical model made additional predictions that were validated experimentally with human blood plasma. These experiments show that blood can be exposed to significant amounts of clot-inducing stimuli, such as tissue factor, without initiating clotting. Overall, these results demonstrate that such chemical model systems, implemented with microfluidics, may be used to predict spatiotemporal dynamics of complex biochemical networks.complexity ͉ microfluidics ͉ networks ͉ tissue factor ͉ nonlinear

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“…Recent efforts have resulted in the development of microfluidic platforms with rapid pattern switching for single-cell studies [''chemical waveform synthesizer'' (Olofsson et al 2005)] or slower pattern switching for higher throughput characterizations [''flow-encoded switching'' (King et al 2008)]; the setup developed by Gomez-Sjoberg et al (2007) provided a means for long-term maintenance of mammalian cell cultures (up to several weeks) in an automated, highthroughput fashion. An emerging niche for microfluidics in biological investigations has been for testing cellular network architectures under dynamic stimulation conditions, providing an optimal platform for scrutinizing existing mathematical and computer models of cellular signaling pathways to a greater degree, compared to conventional methods (Bennett et al 2008;Hersen et al 2008;Mettetal et al 2008).…”

Section: Discussionmentioning

confidence: 99%

Timing is everything: using fluidics to understand the role of temporal dynamics in cellular systems

Jovic

Howell

Takayama

2009

Microfluid Nanofluid

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In biology, it is not only the magnitude of a chemical stimulus that determines cellular response; it is becoming increasingly clear that the timing of the stimulus is vastly important as well. Currently there is a paucity of data regarding cell behavior under dynamic stimulation conditions that are representative of what occurs in vivo. This is, at least in part, attributed to the lack of appropriate tools for generating time-varying stimulatory signals in highly diverse patterns. Fluidics on the macro and micro scale has provided a practical platform for dynamically stimulating cells in a highly controllable manner at physiological and supra-physiological time scales (seconds to a few hours). These fluidic systems have contributed substantially to our understanding of how cells process and react to dynamic stimulatory environments; while these setups provide the means to analyze and manipulate cellular behavior in these types of environments on the singlecell level and on a high-throughput level, improvements can be made to these platforms to enhance their utility for high-impact biological investigations of temporal dynamics.

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A chemical waveform synthesizer

Abstract: bio-mimicking ͉ microfluidics ͉ oscillations ͉ waveform synthesis

Cited by 47 publications

References 38 publications

Soft-state biomicrofluidic pulse generator for single cell analysis

Soft-state biomicrofluidic pulse generator for single cell analysis

Modular chemical mechanism predicts spatiotemporal dynamics of initiation in the complex network of hemostasis

Timing is everything: using fluidics to understand the role of temporal dynamics in cellular systems

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