Image-Based Quantitation of Host Cell–Toxoplasma gondii Interplay Using HRMAn: A Host Response to Microbe Analysis Pipeline

Research output: Chapter in Book/Report/Conference proceedingChapter

Authors

  • Daniel Fisch
  • Artur Yakimovich
  • Barbara Clough
  • Jason Mercer
  • Eva Maria Frickel

Colleges, School and Institutes

External organisations

  • The Francis Crick Institute
  • UCL
  • MRC-Laboratory for Molecular Cell Biology

Abstract

Research on Toxoplasma gondii and its interplay with the host is often performed using fluorescence microscopy-based imaging experiments combined with manual quantification of acquired images. We present here an accurate and unbiased quantification method for host–pathogen interactions. We describe how to plan experiments and prepare, stain and image infected specimens and analyze them with the program HRMAn (Host Response to Microbe Analysis). HRMAn is a high-content image analysis method based on KNIME Analytics Platform. Users of this guide will be able to perform infection studies in high-throughput volume and to a greater level of detail. Relying on cutting edge machine learning algorithms, HRMAn can be trained and tailored to many experimental settings and questions.

Details

Original languageEnglish
Title of host publicationMethods in Molecular Biology
EditorsChristopher J Tonkin
Publication statusPublished - 23 Nov 2019

Publication series

NameMethods in Molecular Biology
Volume2071
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Artificial intelligence, High-content image analysis, Host–pathogen interaction, HRMAn, KNIME Analytics platform, Machine learning, Toxoplasma gondii

ASJC Scopus subject areas