Interferon titration A549 cells

This dataset can be used to study the effect of IFNg treatment on Toxoplasma replication in human A549 cells using HRMAn. A description of the dataset and an instruction on how to use it can be found in the README file contained in the archive

Protein translocation

This dataset can be used to study translocation of Toxoplasma effector proteins to the nucleus of the infected host cell using HRMAn. A description of the dataset and an instruction on how to use it can be found in the README file contained in the archive

GBP recruitment

This dataset can be used to study recruitment of murine Gbps to Toxoplasma vacuoles using HRMAn. A description of the dataset and an instruction on how to use it can be found in the README file contained in the archive

Data from: Defining host–pathogen interactions employing an artificial intelligence workflow

For image-based infection biology, accurate unbiased quantification of host–pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentation. Host protein recruitment to pathogens is often refractory to accurate automated assessment due to its heterogeneous nature. An intuitive intelligent image analysis program to assess host protein recruitment within general cellular pathogen defense is lacking. We present HRMAn (Host Response to Microbe Analysis), an open-source image analysis platform based on machine learning algorithms and deep learning. We show that HRMAn has the capacity to learn phenotypes from the data, without relying on researcher-based assumptions. Using Toxoplasma gondii and Salmonella enterica Typhimurium we demonstrate HRMAn’s capacity to recognize, classify and quantify pathogen killing, replication and cellular defense responses. HRMAn thus presents the only intelligent solution operating at human capacity suitable for both single image and high content image analysis

Salmonella ubiquitination

This dataset can be used to study ubiquitination of Salmonella enterica Typhimurium in HeLa cells using HRMAn. A description of the dataset and an instruction on how to use it can be found in the README file contained in the archive

Data from: Defining host–pathogen interactions employing an artificial intelligence workflow

For image-based infection biology, accurate unbiased quantification of host–pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentation. Host protein recruitment to pathogens is often refractory to accurate automated assessment due to its heterogeneous nature. An intuitive intelligent image analysis program to assess host protein recruitment within general cellular pathogen defense is lacking. We present HRMAn (Host Response to Microbe Analysis), an open-source image analysis platform based on machine learning algorithms and deep learning. We show that HRMAn has the capacity to learn phenotypes from the data, without relying on researcher-based assumptions. Using Toxoplasma gondii and Salmonella enterica Typhimurium we demonstrate HRMAn’s capacity to recognize, classify and quantify pathogen killing, replication and cellular defense responses. HRMAn thus presents the only intelligent solution operating at human capacity suitable for both single image and high content image analysis

Cysteine-reactive free ISG15 generates IL-1b–Producing CD8a⁺ dendritic cells at the site of infection

Abstract IFN-stimulated gene (ISG) 15 is a ubiquitin-like protein induced after type I IFN stimulation. There is a dearth of in vivo models to study free unconjugated ISG15 function. We found that free ISG15 enhances the production of IFN-γ and IL-1β during murine infection with Toxoplasma gondii. In our model, ISG15 is induced in a type I IFN–dependent fashion and released into the serum. Increased ISG15 levels are dependent on an actively invading and replicating parasite. Two cysteine residues in the hinge domain are necessary determinants for ISG15 to induce increased cytokine levels during infection. Increased ISG15 is concurrent with an influx of IL-1β–producing CD8α+ dendritic cells to the site of infection. In this article, we present Toxoplasma infection as a novel in vivo murine model to study the immunomodulatory properties of free ISG15 and uniquely link it to IL-1β production by CD8α+ dendritic cells driven by two cysteines in the hinge region of the protein.</jats:p

Recurrence and Variability of Germline EPCAM Deletions in Lynch Syndrome

Contains fulltext : 96266.pdf (publisher's version ) (Closed access)Recently, we identified 3' end deletions in the EPCAM gene as a novel cause of Lynch syndrome. These truncating EPCAM deletions cause allele-specific epigenetic silencing of the neighboring DNA mismatch repair gene MSH2 in tissues expressing EPCAM. Here we screened a cohort of unexplained Lynch-like families for the presence of EPCAM deletions. We identified 27 novel independent MSH2-deficient families from multiple geographical origins with varying deletions all encompassing the 3' end of EPCAM, but leaving the MSH2 gene intact. Within The Netherlands and Germany, EPCAM deletions appeared to represent at least 2.8% and 1.1% of the confirmed Lynch syndrome families, respectively. MSH2 promoter methylation was observed in epithelial tissues of all deletion carriers tested, thus confirming silencing of MSH2 as the causative defect. In a total of 45 families, 19 different deletions were found, all including the last two exons and the transcription termination signal of EPCAM. All deletions appeared to originate from Alu-repeat mediated recombination events. In 17 cases regions of microhomology around the breakpoints were found, suggesting nonallelic homologous recombination as the most likely mechanism. We conclude that 3' end EPCAM deletions are a recurrent cause of Lynch syndrome, which should be implemented in routine Lynch syndrome diagnostics