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1.
Nature ; 631(8021): 635-644, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38961291

ABSTRACT

Innate immune pattern recognition receptors, such as the Toll-like receptors (TLRs), are key mediators of the immune response to infection and central to our understanding of health and disease1. After microbial detection, these receptors activate inflammatory signal transduction pathways that involve IκB kinases, mitogen-activated protein kinases, ubiquitin ligases and other adaptor proteins. The mechanisms that connect the proteins in the TLR pathways are poorly defined. To delineate TLR pathway activities, we engineered macrophages to enable microscopy and proteomic analysis of the endogenous myddosome constituent MyD88. We found that myddosomes form transient contacts with activated TLRs and that TLR-free myddosomes are dynamic in size, number and composition over the course of 24 h. Analysis using super-resolution microscopy revealed that, within most myddosomes, MyD88 forms barrel-like structures that function as scaffolds for effector protein recruitment. Proteomic analysis demonstrated that myddosomes contain proteins that act at all stages and regulate all effector responses of the TLR pathways, and genetic analysis defined the epistatic relationship between these effector modules. Myddosome assembly was evident in cells infected with Listeria monocytogenes, but these bacteria evaded myddosome assembly and TLR signalling during cell-to-cell spread. On the basis of these findings, we propose that the entire TLR signalling pathway is executed from within the myddosome.


Subject(s)
Listeria monocytogenes , Macrophages , Myeloid Differentiation Factor 88 , Proteomics , Signal Transduction , Toll-Like Receptors , Toll-Like Receptors/metabolism , Myeloid Differentiation Factor 88/metabolism , Animals , Mice , Macrophages/metabolism , Macrophages/immunology , Macrophages/microbiology , Humans , Listeriosis/immunology , Listeriosis/microbiology , Listeriosis/metabolism , Female
2.
mSphere ; 8(6): e0051123, 2023 Dec 20.
Article in English | MEDLINE | ID: mdl-37975677

ABSTRACT

IMPORTANCE: Toxoplasma gondii (Tg) is a ubiquitous parasitic pathogen, infecting about one-third of the global population. Tg is controlled in immunocompetent people by mechanisms that are not fully understood. Tg infection drives the production of the inflammatory cytokine interferon gamma (IFNγ), which upregulates intracellular anti-pathogen defense pathways. In this study, we describe host proteins p97/VCP, UBXD1, and ANKRD13A that control Tg at the parasitophorous vacuole (PV) in IFNγ-stimulated endothelial cells. p97/VCP is an ATPase that interacts with a network of cofactors and is active in a wide range of ubiquitin-dependent cellular processes. We demonstrate that PV ubiquitination is a pre-requisite for recruitment of these host defense proteins, and their deposition directs Tg PVs to acidification in endothelial cells. We show that p97/VCP universally targets PVs in human cells and restricts Tg in different human cell types. Overall, these findings reveal new players of intracellular host defense of a vacuolated pathogen.


Subject(s)
Parasites , Toxoplasma , Animals , Humans , Toxoplasma/metabolism , Interferons/metabolism , Vacuoles/metabolism , Endothelial Cells , Interferon-gamma , Valosin Containing Protein/metabolism
3.
Science ; 382(6666): eadg2253, 2023 10 06.
Article in English | MEDLINE | ID: mdl-37797010

ABSTRACT

Disruption of cellular activities by pathogen virulence factors can trigger innate immune responses. Interferon-γ (IFN-γ)-inducible antimicrobial factors, such as the guanylate binding proteins (GBPs), promote cell-intrinsic defense by attacking intracellular pathogens and by inducing programmed cell death. Working in human macrophages, we discovered that GBP1 expression in the absence of IFN-γ killed the cells and induced Golgi fragmentation. IFN-γ exposure improved macrophage survival through the activity of the kinase PIM1. PIM1 phosphorylated GBP1, leading to its sequestration by 14-3-3σ, which thereby prevented GBP1 membrane association. During Toxoplasma gondii infection, the virulence protein TgIST interfered with IFN-γ signaling and depleted PIM1, thereby increasing GBP1 activity. Although infected cells can restrain pathogens in a GBP1-dependent manner, this mechanism can protect uninfected bystander cells. Thus, PIM1 can provide a bait for pathogen virulence factors, guarding the integrity of IFN-γ signaling.


Subject(s)
GTP-Binding Proteins , Host-Pathogen Interactions , Immunity, Innate , Interferon-gamma , Proto-Oncogene Proteins c-pim-1 , Toxoplasma , Toxoplasmosis , Humans , GTP-Binding Proteins/genetics , GTP-Binding Proteins/metabolism , Interferon-gamma/metabolism , Proto-Oncogene Proteins c-pim-1/metabolism , Toxoplasmosis/immunology , Virulence Factors/metabolism , Macrophages/immunology , 14-3-3 Proteins/metabolism , Host-Pathogen Interactions/immunology
4.
Pathog Dis ; 79(9)2022 01 07.
Article in English | MEDLINE | ID: mdl-34931666

ABSTRACT

Human guanylate binding proteins (GBPs) are key players of interferon-gamma (IFNγ)-induced cell intrinsic defense mechanisms targeting intracellular pathogens. In this study, we combine the well-established Toxoplasmagondii infection model with three in vitro macrophage culture systems to delineate the contribution of individual GBP family members to control this apicomplexan parasite. Use of high-throughput imaging assays and genome engineering allowed us to define a role for GBP1, 2 and 5 in parasite infection control. While GBP1 performs a pathogen-proximal, parasiticidal and growth-restricting function through accumulation at the parasitophorous vacuole of intracellular Toxoplasma, GBP2 and GBP5 perform a pathogen-distal, growth-restricting role. We further find that mutants of the GTPase or isoprenylation site of GBP1/2/5 affect their normal function in Toxoplasma control by leading to mis-localization of the proteins.


Subject(s)
GTP-Binding Proteins/metabolism , Macrophages/immunology , Macrophages/metabolism , Macrophages/parasitology , Toxoplasma/immunology , Toxoplasmosis/immunology , Toxoplasmosis/metabolism , Toxoplasmosis/parasitology , Biomarkers , Disease Susceptibility , Host-Parasite Interactions , Humans
5.
Cell Microbiol ; 23(7): e13349, 2021 07.
Article in English | MEDLINE | ID: mdl-33930228

ABSTRACT

To study the dynamics of infection processes, it is common to manually enumerate imaging-based infection assays. However, manual counting of events from imaging data is biased, error-prone and a laborious task. We recently presented HRMAn (Host Response to Microbe Analysis), an automated image analysis program using state-of-the-art machine learning and artificial intelligence algorithms to analyse pathogen growth and host defence behaviour. With HRMAn, we can quantify intracellular infection by pathogens such as Toxoplasma gondii and Salmonella in a variety of cell types in an unbiased and highly reproducible manner, measuring multiple parameters including pathogen growth, pathogen killing and activation of host cell defences. Since HRMAn is based on the KNIME Analytics platform, it can easily be adapted to work with other pathogens and produce more readouts from quantitative imaging data. Here we showcase improvements to HRMAn resulting in the release of HRMAn 2.0 and new applications of HRMAn 2.0 for the analysis of host-pathogen interactions using the established pathogen T. gondii and further extend it for use with the bacterial pathogen Chlamydia trachomatis and the fungal pathogen Cryptococcus neoformans.


Subject(s)
Chlamydia Infections/diagnostic imaging , Cryptococcosis/diagnostic imaging , Host-Pathogen Interactions , Image Processing, Computer-Assisted/methods , Toxoplasmosis/diagnostic imaging , Artificial Intelligence , Cell Line, Tumor , Humans
6.
Cell Mol Life Sci ; 78(7): 3637-3656, 2021 Apr.
Article in English | MEDLINE | ID: mdl-33555391

ABSTRACT

The opportunistic pathogen Pseudomonas aeruginosa has gained precedence over the years due to its ability to develop resistance to existing antibiotics, thereby necessitating alternative strategies to understand and combat the bacterium. Our previous work identified the interaction between the bacterial lectin LecA and its host cell glycosphingolipid receptor globotriaosylceramide (Gb3) as a crucial step for the engulfment of P. aeruginosa via the lipid zipper mechanism. In this study, we define the LecA-associated host cell membrane domain by pull-down and mass spectrometry analysis. We unraveled a predilection of LecA for binding to saturated, long fatty acyl chain-containing Gb3 species in the extracellular membrane leaflet and an induction of dynamic phosphatidylinositol (3,4,5)-trisphosphate (PIP3) clusters at the intracellular leaflet co-localizing with sites of LecA binding. We found flotillins and the GPI-anchored protein CD59 not only to be an integral part of the LecA-interacting membrane domain, but also majorly influencing bacterial invasion as depletion of either of these host cell proteins resulted in about 50% reduced invasiveness of the P. aeruginosa strain PAO1. In summary, we report that the LecA-Gb3 interaction at the extracellular leaflet induces the formation of a plasma membrane domain enriched in saturated Gb3 species, CD59, PIP3 and flotillin thereby facilitating efficient uptake of PAO1.


Subject(s)
CD59 Antigens/metabolism , Cell Membrane/metabolism , Host-Pathogen Interactions , Lung/microbiology , Membrane Proteins/metabolism , Pseudomonas aeruginosa/isolation & purification , Trihexosylceramides/metabolism , Biological Transport , CD59 Antigens/genetics , Endocytosis , Epithelial Cells/metabolism , Epithelial Cells/microbiology , Epithelial Cells/pathology , Humans , Lung/metabolism , Lung/pathology , Membrane Proteins/genetics , Pseudomonas aeruginosa/physiology , Signal Transduction
7.
Cell Rep ; 32(6): 108008, 2020 08 11.
Article in English | MEDLINE | ID: mdl-32783936

ABSTRACT

Interferon-inducible guanylate-binding proteins (GBPs) promote cell-intrinsic defense through host cell death. GBPs target pathogens and pathogen-containing vacuoles and promote membrane disruption for release of microbial molecules that activate inflammasomes. GBP1 mediates pyroptosis or atypical apoptosis of Salmonella Typhimurium (STm)- or Toxoplasma gondii (Tg)- infected human macrophages, respectively. The pathogen-proximal detection-mechanisms of GBP1 remain poorly understood, as humans lack functional immunity-related GTPases (IRGs) that assist murine Gbps. Here, we establish that GBP1 promotes the lysis of Tg-containing vacuoles and parasite plasma membranes, releasing Tg-DNA. In contrast, we show GBP1 targets cytosolic STm and recruits caspase-4 to the bacterial surface for its activation by lipopolysaccharide (LPS), but does not contribute to bacterial vacuole escape. Caspase-1 cleaves and inactivates GBP1, and a cleavage-deficient GBP1D192E mutant increases caspase-4-driven pyroptosis due to the absence of feedback inhibition. Our studies elucidate microbe-specific roles of GBP1 in infection detection and its triggering of the assembly of divergent caspase signaling platforms.


Subject(s)
Caspases/immunology , GTP-Binding Proteins/immunology , Salmonella typhimurium/immunology , Toxoplasma/immunology , Cell Death/immunology , HEK293 Cells , Humans , Inflammasomes/immunology , Interferon-gamma/pharmacology , Ligands , Salmonella Infections/immunology , Salmonella Infections/microbiology , THP-1 Cells , Toxoplasma/genetics , Toxoplasmosis/immunology , Toxoplasmosis/microbiology , Vacuoles/immunology
8.
Methods Mol Biol ; 2071: 411-433, 2020.
Article in English | MEDLINE | ID: mdl-31758464

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.


Subject(s)
Toxoplasma/pathogenicity , Algorithms , Artificial Intelligence , Host-Pathogen Interactions , Machine Learning , Microscopy, Fluorescence/methods
9.
PLoS Pathog ; 15(12): e1008097, 2019 12.
Article in English | MEDLINE | ID: mdl-31830133
10.
Wellcome Open Res ; 4: 124, 2019.
Article in English | MEDLINE | ID: mdl-31544161

ABSTRACT

Background: Infections cause the production of inflammatory cytokines such as Interferon gamma (IFNγ). IFNγ in turn prompts the upregulation of a range of host defence proteins including members of the family of guanylate binding proteins (Gbps). In humans and mice alike, GBPs restrict the intracellular replication of invasive microbes and promote inflammation. To study the physiological functions of Gbp family members, the most commonly chosen in vivo models are mice harbouring loss-of-function mutations in either individual Gbp genes or the entire Gbp gene cluster on mouse chromosome 3. Individual Gbp deletion strains differ in their design, as some strains exist on a pure C57BL/6 genetic background, while other strains contain a 129-derived genetic interval encompassing the Gbp gene cluster on an otherwise C57BL/6 genetic background. Methods: To determine whether the presence of 129 alleles of paralogous Gbps could influence the phenotypes of 129-congenic Gbp-deficient strains, we studied the expression of Gbps in both C57BL/6J and 129/Sv mice following in vivo stimulation with adjuvants and after infection with either Toxoplasma gondii or Shigella flexneri. Results: We show that C57BL/6J relative to 129/Sv mice display moderately elevated expression of Gbp2, but more prominently, are also defective for Gbp2b (formerly Gbp1) mRNA induction upon immune priming. Notably, Toxoplasma infections induce robust Gbp2b protein expression in both strains of mice, suggestive of a Toxoplasma-activated mechanism driving Gbp2b protein translation. We further find that the higher expression of Gbp2b mRNA in 129/Sv mice correlates with a gene duplication event at the Gbp2b locus resulting in two copies of the Gbp2b gene on the haploid genome of the 129/Sv strain. Conclusions: Our findings demonstrate functional differences between 129 and C57BL/6 Gbp alleles which need to be considered in the design and interpretation of studies utilizing mouse models, particularly for phenotypes influenced by Gbp2 or Gbp2b expression.

11.
EMBO J ; 38(13): e100926, 2019 07 01.
Article in English | MEDLINE | ID: mdl-31268602

ABSTRACT

The guanylate binding protein (GBP) family of interferon-inducible GTPases promotes antimicrobial immunity and cell death. During bacterial infection, multiple mouse Gbps, human GBP2, and GBP5 support the activation of caspase-1-containing inflammasome complexes or caspase-4 which trigger pyroptosis. Whether GBPs regulate other forms of cell death is not known. The apicomplexan parasite Toxoplasma gondii causes macrophage death through unidentified mechanisms. Here we report that Toxoplasma-induced death of human macrophages requires GBP1 and its ability to target Toxoplasma parasitophorous vacuoles through its GTPase activity and prenylation. Mechanistically, GBP1 promoted Toxoplasma detection by AIM2, which induced GSDMD-independent, ASC-, and caspase-8-dependent apoptosis. Identical molecular determinants targeted GBP1 to Salmonella-containing vacuoles. GBP1 facilitated caspase-4 recruitment to Salmonella leading to its enhanced activation and pyroptosis. Notably, GBP1 could be bypassed by the delivery of Toxoplasma DNA or bacterial LPS into the cytosol, pointing to its role in liberating microbial molecules. GBP1 thus acts as a gatekeeper of cell death pathways, which respond specifically to infecting microbes. Our findings expand the immune roles of human GBPs in regulating not only pyroptosis, but also apoptosis.


Subject(s)
GTP-Binding Proteins/metabolism , Macrophages/parasitology , Toxoplasma/pathogenicity , Toxoplasmosis/metabolism , Caspases, Initiator/metabolism , DNA-Binding Proteins/metabolism , Humans , Macrophages/metabolism , Protein Prenylation , Pyroptosis , THP-1 Cells , Toxoplasmosis/parasitology
12.
Elife ; 82019 02 12.
Article in English | MEDLINE | ID: mdl-30744806

ABSTRACT

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. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).


Subject(s)
Artificial Intelligence , Host-Pathogen Interactions , Image Processing, Computer-Assisted/methods , Microscopy, Fluorescence/methods , Salmonella typhimurium/growth & development , Single-Cell Analysis/methods , Toxoplasma/growth & development , HeLa Cells , Humans , Workflow
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