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Proceedings Paper

A novel method for multiparameter physiological phenotype characterization at the single-cell level
Author(s): Laimonas Kelbauskas; Shashanka Ashili; Jeff Houkal; Dean Smith; Aida Mohammadreza; Kristen Lee; Ashok Kumar; Yasser Anis; Tom Paulson; Cody Youngbull; Yanqing Tian; Roger Johnson; Mark Holl; Deirdre Meldrum
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Paper Abstract

Non-genetic intercellular heterogeneity has been increasingly recognized as one of the key factors in a variety of core cellular processes including proliferation, stimulus response, carcinogenesis and drug resistance. Many diseases, including cancer, originate in a single or a few cells. Early detection and characterization of these abnormal cells can provide new insights into the pathogenesis and serve as a tool for better disease diagnosis and treatment. We report on a novel technology for multiparameter physiological phenotype characterization at the single-cell level. It is based on real-time measurements of concentrations of several metabolites by means of extracellular optical sensors in microchambers of sub-nL volume containing single cells. In its current configuration, the measurement platform features the capability to detect oxygen consumption rate and pH changes under normoxic and hypoxic conditions at the single-cell level. We have conceived, designed and developed a semi-automated method for single-cell manipulation and loading into microwells utilizing custom, high-precision fluid handling at the nanoliter scale. We present the results of a series of measurements of oxygen consumption rates (OCRs) of single human metaplastic esophageal epithelial cells. In addition, to assess the effects of cell-to-cell interactions, we have measured OCRs of two and three cells placed in a single well. The major advantages of the approach are a) multiplexed characterization of cell phenotype at the single-cell level, b) minimal invasiveness due to the distant positioning of sensors, and c) flexibility in terms of accommodating measurements of other metabolites or biomolecules of interest.

Paper Details

Date Published: 11 February 2011
PDF: 9 pages
Proc. SPIE 7902, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IX, 79021Q (11 February 2011); doi: 10.1117/12.875483
Show Author Affiliations
Laimonas Kelbauskas, Arizona State Univ. (United States)
Shashanka Ashili, Arizona State Univ. (United States)
Jeff Houkal, Arizona State Univ. (United States)
Dean Smith, Arizona State Univ. (United States)
Aida Mohammadreza, Arizona State Univ. (United States)
Kristen Lee, Arizona State Univ. (United States)
Ashok Kumar, Arizona State Univ. (United States)
Yasser Anis, Cairo Univ. (Egypt)
Tom Paulson, Fred Hutchinson Cancer Research Ctr. (United States)
Cody Youngbull, Arizona State Univ. (United States)
Yanqing Tian, Arizona State Univ. (United States)
Roger Johnson, Arizona State Univ. (United States)
Mark Holl, Arizona State Univ. (United States)
Deirdre Meldrum, Arizona State Univ. (United States)


Published in SPIE Proceedings Vol. 7902:
Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IX
Daniel L. Farkas; Dan V. Nicolau; Robert C. Leif, Editor(s)

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