کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5513538 1541214 2017 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Imaging flow cytometry analysis of intracellular pathogens
ترجمه فارسی عنوان
تجزیه و تحلیل جریان سیاتومتری تصویربرداری از پاتوژنهای داخل سلولی
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی زیست شیمی
چکیده انگلیسی


- Imaging flow cytometry (IFC) characterize hundreds thousands of cellular images using hundreds of measurements of morphological and fluorescence cellular features.
- Complex morphology of host-intracellular parasite interaction can be quantified in statistically robust manner using IFC.
- Feature Finder algorithm is useful in defining statistically significant differences in morphological and fluorescent features of cells.
- IFC revealed that M. tuberculosis internalized bacilli were co-localized to a greater degree at late endosome/lysosome CD107 and late endosome Rab7 compartment than Rab5 early endosome compartment.

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.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Methods - Volume 112, 1 January 2017, Pages 91-104
نویسندگان
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