Using multispectral imaging flow cytometry to assess an in vitro intracellular Burkholderia thailandensis infection model. (3rd February 2016)

• Record Type: Journal Article
• Authors: Jenner, Dominic; Ducker, Catherine; Clark, Graeme; Prior, Jo; Rowland, Caroline A.
• Is Part Of: Cytometry. Volume 89:Number 4(2016)
• Page Start: 328
• Page End: 337
• Publication Date: 2016-02-03
• Subjects: multispectral imaging flow cytometry -- ImageStream X MkII -- Burkholderia thailandensis -- in vitro intracellular infection models; Flow cytometry -- Periodicals; Imaging systems in biology -- Periodicals; Imaging systems in medicine -- Periodicals; Diagnostic imaging -- Periodicals; 571.605
• DOI: 10.1002/cyto.a.22809
• Languages: English
• ISSNs: 1552-4922

Abstract

Abstract: The use of in vitro models to understand the interaction of bacteria with host cells is well established. In vitro bacterial infection models are often used to quantify intracellular bacterial load by lysing cell populations and subsequently enumerating the bacteria. Modern established techniques employ the use of fluorescence technologies such as flow cytometry, fluorescent microscopy, and/or confocal microscopy. However, these techniques often lack either the quantification of large data sets (microscopy) or use of gross fluorescence signal which lacks the visual confirmation that can provide additional confidence in data sets. Multispectral imaging flow cytometry (MIFC) is a novel emerging field of technology. This technology captures a bright field and fluorescence image of cells in a flow using a charged coupled device camera. It allows the analysis of tens of thousands of single cell images, making it an extremely powerful technology. Here MIFC was used as an alternative method of analyzing intracellular bacterial infection using Burkholderia thailandensis E555 as a model organism. It has been demonstrated that the data produced using traditional enumeration is comparable to data analyzed using MIFC. It has also been shown that by using MIFC it is possible to generate other data on the dynamics of the infection model rather than viable counts alone. It has been demonstrated that it is possible to inhibit the uptake of bacteria into mammalian cells and identify differences between treated and untreated cell populations. The authors believe this to be the first use of MIFC to analyze a Burkholderia bacterial species during intracellular infection. © 2016 Crown copyright. Published by Wiley Periodicals Inc. on behalf of ISAC.