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.
Keywords: Artificial intelligence; HRMAn; High-content image analysis; Host–pathogen interaction; KNIME Analytics platform; Machine learning; Toxoplasma gondii.