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Imaging flow cytometry analysis of intracellular pathogens

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dc.contributor.author Haridas, Viraga
dc.contributor.author Ranjbar, Shahin
dc.contributor.author Vorobjev, Ivan A.
dc.contributor.author Goldfeld, Anne E.
dc.contributor.author Barteneva, Natasha S.
dc.creator Viraga, Haridas
dc.date.accessioned 2017-12-22T08:57:24Z
dc.date.available 2017-12-22T08:57:24Z
dc.date.issued 2017-01-01
dc.identifier DOI:10.1016/j.ymeth.2016.09.007
dc.identifier.citation Viraga Haridas, Shahin Ranjbar, Ivan A. Vorobjev, Anne E. Goldfeld, Natasha S. Barteneva, Imaging flow cytometry analysis of intracellular pathogens, In Methods, Volume 112, 2017, Pages 91-104 en_US
dc.identifier.issn 10462023
dc.identifier.uri https://www.sciencedirect.com/science/article/pii/S1046202316303115
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/3054
dc.description.abstract Abstract Imaging flow cytometry has been applied to address questions in infection biology, in particular, infections induced by intracellular pathogens. This methodology, which utilizes specialized analytic software makes it possible to analyze hundreds of quantified features for hundreds of thousands of individual cellular or subcellular events in a single experiment. Imaging flow cytometry analysis of host cell-pathogen interaction can thus quantitatively addresses a variety of biological questions related to intracellular infection, including cell counting, internalization score, and subcellular patterns of co-localization. Here, we provide an overview of recent achievements in the use of fluorescently labeled prokaryotic or eukaryotic pathogens in human cellular infections in analysis of host-pathogen interactions. Specifically, we give examples of Imagestream-based analysis of cell lines infected with Toxoplasma gondii or Mycobacterium tuberculosis. Furthermore, we illustrate the capabilities of imaging flow cytometry using a combination of standard IDEAS™ software and the more recently developed Feature Finder algorithm, which is capable of identifying statistically significant differences between researcher-defined image galleries. We argue that the combination of imaging flow cytometry with these software platforms provides a powerful new approach to understanding host control of intracellular pathogens. en_US
dc.language.iso en en_US
dc.publisher Methods en_US
dc.relation.ispartof Methods
dc.subject Imaging flow cytometry en_US
dc.subject Fluorescent protein en_US
dc.subject Intracellular pathogen en_US
dc.subject Mycobacteria tuberculosis en_US
dc.subject Toxoplasma gondii en_US
dc.subject Feature Finder en_US
dc.subject Cellular heterogeneity en_US
dc.subject Colocalization en_US
dc.subject Phagosome maturation en_US
dc.subject Rab5 en_US
dc.subject Rab7 en_US
dc.title Imaging flow cytometry analysis of intracellular pathogens en_US
dc.type Article en_US
dc.rights.license © 2016 Elsevier Inc. All rights reserved.
elsevier.identifier.doi 10.1016/j.ymeth.2016.09.007
elsevier.identifier.eid 1-s2.0-S1046202316303115
elsevier.identifier.pii S1046-2023(16)30311-5
elsevier.identifier.scopusid 84994494300
elsevier.volume 112
elsevier.issue.name Flow Cytometry
elsevier.coverdate 2017-01-01
elsevier.coverdisplaydate 1 January 2017
elsevier.startingpage 91
elsevier.endingpage 104
elsevier.openaccess 0
elsevier.openaccessarticle false
elsevier.openarchivearticle false
elsevier.teaser Imaging flow cytometry has been applied to address questions in infection biology, in particular, infections induced by intracellular pathogens. This methodology, which utilizes specialized analytic...
elsevier.aggregationtype Journal
workflow.import.source science

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