abstract: Within the last decade there has been remarkable interest in single-cell metabolic analysis as a key technology for understanding cellular heterogeneity, disease initiation, progression, and drug resistance. Technologies have been developed for oxygen consumption rate (OCR) measurements using various configurations of microfluidic devices. The technical challenges of current approaches include: (1) deposition of multiple sensors for multi-parameter metabolic measurements, e.g. oxygen, pH, etc.; (2) tedious and labor-intensive microwell array fabrication processes; (3) low yield of hermetic sealing between two rigid fused silica parts, even with a compliance layer of PDMS or Parylene-C. In this thesis, several improved microfabrication technologies are developed and demonstrated for analyzing multiple metabolic parameters from single cells, including (1) a modified "lid-on-top" configuration with a multiple sensor trapping (MST) lid which spatially confines multiple sensors to micro-pockets enclosed by lips for hermetic sealing of wells; (2) a multiple step photo-polymerization method for patterning three optical sensors (oxygen, pH and reference) on fused silica and on a polyethylene terephthalate (PET) surface; (3) a photo-polymerization method for patterning tri-color (oxygen, pH and reference) optical sensors on both fused silica and on the PET surface; (4) improved KMPR/SU-8 microfabrication protocols for fabricating microwell arrays that can withstand cell culture conditions. Implementation of these improved microfabrication methods should address the aforementioned challenges and provide a high throughput and multi-parameter single cell metabolic analysis platform. / Dissertation/Thesis / M.S. Electrical Engineering 2014
Identifer | oai:union.ndltd.org:asu.edu/item:25107 |
Date | January 2014 |
Contributors | Song, Ganquan (Author), Meldrum, Deirdre R (Advisor), Goryll, Michael (Committee member), Wang, Hong (Committee member), Tian, Yanqing (Committee member), Arizona State University (Publisher) |
Source Sets | Arizona State University |
Language | English |
Detected Language | English |
Type | Masters Thesis |
Format | 87 pages |
Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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