Deformability-based cell selection with downstream immunofluorescence analysis. Issue 5 (21st March 2016)

• Record Type: Journal Article
• Authors: Shaw Bagnall, Josephine; Byun, Sangwon; Miyamoto, David T.; Kang, Joon Ho; Maheswaran, Shyamala; Stott, Shannon L.; Toner, Mehmet; Manalis, Scott R.
• Is Part Of: Integrative biology. Volume 8:Issue 5(2016:May)
• Page Start: 654
• Page End: 664
• Publication Date: 2016-03-21
• Subjects: Biology -- Periodicals; Technology -- Periodicals; Biological systems -- Periodicals; 570.5
• DOI: 10.1039/c5ib00284b
• Languages: English
• ISSNs: 1757-9694

Abstract

Abstract : The presented method relates cell biophysical properties to molecular traits by identifying cells of interest based on their individual passage times through a constriction and subsequently collecting them off-chip for downstream immunofluorescence imaging. Abstract : Mechanical properties of single cells have been shown to relate to cell phenotype and malignancy. However, until recently, it has been difficult to directly correlate each cell's biophysical characteristics to its molecular traits. Here, we present a cell sorting technique for use with a suspended microchannel resonator (SMR), which can measure biophysical characteristics of a single cell based on the sensor's record of its buoyant mass as well as its precise position while it traverses through a constricted microfluidic channel. The measurement provides information regarding the amount of time a cell takes to pass through a constriction (passage time), as related to the cell's deformability and surface friction, as well as the particular manner in which it passes through. In the method presented here, cells of interest are determined based on passage time, and are collected off-chip for downstream immunofluorescence imaging. The biophysical single-cell SMR measurement can then be correlated to the molecular expression of the collected cell. This proof-of-principle is demonstrated by sorting and collecting tumor cells from cell line-spiked blood samples as well as a metastatic prostate cancer patient blood sample, identifying them by their surface protein expression and relating them to distinct SMR signal trajectories.