Title |
An Automated Microfluidic Multiplexer for Fast Delivery of C. elegans Populations from Multiwells
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Published in |
PLOS ONE, September 2013
|
DOI | 10.1371/journal.pone.0074480 |
Pubmed ID | |
Authors |
Navid Ghorashian, Sertan Kutal Gökçe, Sam Xun Guo, William Neil Everett, Adela Ben-Yakar |
Abstract |
Automated biosorter platforms, including recently developed microfluidic devices, enable and accelerate high-throughput and/or high-resolution bioassays on small animal models. However, time-consuming delivery of different organism populations to these systems introduces a major bottleneck to executing large-scale screens. Current population delivery strategies rely on suction from conventional well plates through tubing periodically exposed to air, leading to certain disadvantages: 1) bubble introduction to the sample, interfering with analysis in the downstream system, 2) substantial time drain from added bubble-cleaning steps, and 3) the need for complex mechanical systems to manipulate well plate position. To address these concerns, we developed a multiwell-format microfluidic platform that can deliver multiple distinct animal populations from on-chip wells using multiplexed valve control. This Population Delivery Chip could operate autonomously as part of a relatively simple setup that did not require any of the major mechanical moving parts typical of plate-handling systems to address a given well. We demonstrated automatic serial delivery of 16 distinct C. elegans worm populations to a single outlet without introducing any bubbles to the samples, causing cross-contamination, or damaging the animals. The device achieved delivery of more than 90% of the population preloaded into a given well in 4.7 seconds; an order of magnitude faster than delivery modalities in current use. This platform could potentially handle other similarly sized model organisms, such as zebrafish and drosophila larvae or cellular micro-colonies. The device's architecture and microchannel dimensions allow simple expansion for processing larger numbers of populations. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 4% |
Unknown | 48 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 14 | 28% |
Researcher | 7 | 14% |
Student > Bachelor | 5 | 10% |
Student > Doctoral Student | 4 | 8% |
Professor > Associate Professor | 4 | 8% |
Other | 9 | 18% |
Unknown | 7 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 16 | 32% |
Chemical Engineering | 5 | 10% |
Agricultural and Biological Sciences | 5 | 10% |
Biochemistry, Genetics and Molecular Biology | 4 | 8% |
Physics and Astronomy | 3 | 6% |
Other | 11 | 22% |
Unknown | 6 | 12% |