Image-Based Quantitation of Host Cell–Toxoplasma gondii Interplay Using HRMAn: A Host Response to Microbe Analysis Pipeline
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.
Key wordsToxoplasma gondii Host–pathogen interaction High-content image analysis Artificial intelligence Machine learning HRMAn KNIME Analytics platform
We thank all members of the Frickel lab for productive discussion. This work was supported by the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001076), the UK Medical Research Council (FC001076), and the Wellcome Trust (FC001076). E.M.F. was supported by a Wellcome Trust Career Development Fellowship (091664/B/10/Z). D.F. was supported by a Boehringer Ingelheim Fonds Ph.D. fellowship. A.Y. and J.M. were supported by core funding to the MRC Laboratory for Molecular Cell Biology at University College London (J.M.), the European Research Council (649101-UbiProPox), the UK Medical Research Council (MC_UU12018/7).
Author Contribution: D.F., B.C., and E.M.F. wrote the manuscript. All authors contributed to revising the manuscript.
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