Interaction of EHV1 with equine dendritic cells and mesenchymal stem cells

Equine herpesvirus (EHV) 1 is an α-herpesvirus which is endemic in horse populations worldwide and can induce respiratory disease, reproductive disorders (e.g. abortion) and central nervous disorders (e.g. equine herpesvirus myeloencephalopathy, EHM). After inhalation of the virus, EHV1 will replicate in the upper respiratory epithelium and can subsequently spread via a cell-associated viremia towards the other target organs. Recent studies demonstrated that the majority of the EHV1-infected cells in the respiratory tissue, the draining lymph nodes and the blood were positive for the cell surface marker CD172a and have led to the assumption that EHV1 ‘hijacks’ CD172a+ cells as carrier cells to spread the virus in the host. The respiratory tract harbors several cell populations, including two highly migratory (potentially) CD172a+ cell types, namely the dendritic cell (DC) and the mesenchymal stem cell (MSC). Although MSC have been demonstrated to be CD172a+ in man and rodent, this had not yet been analyzed in horse. In addition, although DC have been shown before to be susceptible to EHV1 infection, this had not yet been investigated for MSC. Infection of DC/MSC with EHV1 may substantially affect the biological activities of these cell types. Indeed, it was previously shown that EHV1 infection of equine DC resulted in a reduced capacity of these cells to support T-proliferation. However, it was not known if, as is the case with other herpesviruses, EHV1 infection of equine DC results in a modulation of cell surface markers associated with antigen (Ag) presentation, co-stimulation and adhesion. Likewise, for equine MSC, it was unknown what the impact of a putative infection could be on the expression pattern of typical MSC cell surface markers. Therefore, the aims of this thesis were to (i) evaluate CD172a expression and EHV1 susceptibility of equine MSC, (ii) determine the effect of EHV1 infection on different cell surface markers on equine monocyte-derived dendritic cells (MDDC) and MSC, and (iii) investigate the potential involvement of viral factors and cellular mechanisms that may underlie such cell surface marker modulation. In Chapter 1, a general introduction is provided on the classification, virion structure, and viral replication of EHV-1 and the epidemiology, prevention, and treatment of EHV1 infection. Next, we discussed the immunological response against EHV1 infection and the viral mechanisms to avoid this response. Specifically, we focused on viral factors that are of particular importance for this thesis with regard to their putative role in the modulation of cell surface proteins. We finished by discussing the potential role of the two CD172a positive cell types that were investigated in this thesis, namely the DC and the MSC, in the pathogenesis of and immune response against herpesviruses. In Chapter 2, a general outline of the thesis is given. In Chapter 3, we found that EHV1-infected equine MDDC showed drastic downregulation of major histocompability complex (MHC) I and CD83, substantial reduction of CD29, CD86 and CD206, and moderate lowering of CD172a. However, MHCII and lymphocyte function associated antigen (LFA) 1 were not modulated on EHV1-infected equine MDDC. In addition, virus-free supernatant of EHV1-infected MDDC was unable to induce any of the downregulations observed with wild type EHV1 and only induced a very slight upregulation of MHCI on mock-infected MDDC. Next, we evaluated the role of the viral proteins virion host-shutoff (VHS), unique long protein (pUL) 49.5, EHV1’ infected cell protein (EICP) 0 (only CD83 evaluated) and pUL56 in downregulation of cell surface proteins. We found no involvement of VHS in the downregulation of any of the evaluated cell surface markers on EHV1-infected equine MDDC, despite previous report showing that VHS is involved in downregulation of CD83 and CD86 in HSV1-infected MDDC. Also, no role for EICP0 was found in reducing CD83 on EHV1-infected equine MDDC, in contrast to the role of the HSV1 ICP0 homolog in downregulating CD83 in human MDDC. Moreover, neither pUL49.5 nor pUL56 were involved in downregulation of equine MDDC cell surface proteins, with the exception of a partial elevation of CD83 and CD86 in a pUL56 deletion mutant virus compared to wild type EHV1. For CD29 we found a minor involvement of pUL56 in EHV1-mediated downregulation. In Chapter 4, we started to explore the cellular mechanism (mis)used by EHV1 to downregulate MHCI on equine MDDC. Despite the fact that MHCI is an EHV1 entry receptor for certain equine cell types and that other entry receptors were previously shown to be downregulated upon entry of other α-herpesviruses, we found that MHCI downregulation on equine MDDC is not a direct entry-associated event. We did, however, demonstrate that EHV1 downregulates MHCI on equine MDDC by enhancing internalization of cell surface residing MHCI, which is in line with previous findings in EHV1-infected equine fibroblasts and various Kaposi’s sarcoma herpesvirus (KSHV) infected cell types. MHCI internalization in EHV1-infected equine fibroblasts has been reported to depend on dynamin, but not clathrin and this contrasts MHCI internalization in KSHV-infected cells, which depends on both clathrin and dynamin. To evaluate the possible endocytosis mechanism(s) involved in MHCI downregulation in EHV1-infected equine MDDC, we performed a screening with several inhibitors of endocytic pathways. This led to the additional finding that EHV1 entry in equine MDDC probably depends on macropinocytosis. Furthermore, these inhibitor experiments pointed towards the involvement of clathrin-dependent endocytosis in downregulation of MHCI during EHV1 infection of equine MDDC, as we found partial reversion of MHCI downregulation upon applying inhibitors for clathrin and dynamin. In Chapter 5, we found that equine MSC are CD172a positive, susceptible to EHV1 infection and that such infection resulted in the downregulation of select cell surface markers in a pUL56-dependent fashion. While EHV1 infection of equine MSC did drastically downregulate cell surface MHCI and substantially reduced CD29 and CD105, we found no modulation of CD44 or CD90 upon EHV1 infection. EHV1-infected equine MSC also showed a variable and moderate downregulation of CD172a. We found that virus-free supernatant of EHV1-infected MSC was unable to induce any of the modulations found after infection of MSC with EHV1 and this in contrast to human cytomegalovirus (HCMV)-mediated modulation of MSC cell surface proteins. In line with previous findings in other EHV1-infected cell types, we also found that MHCI downregulation in EHV1-infected equine MSC depends on the expression of pUL56. In addition, we found for the first time in an equine cell type that expression of EHV1 pUL56 is required for downregulation of CD29 and CD105 and contributes to downregulation of CD172a. In Chapter 6, a general discussion is given on the results shown in this thesis. Conclusion: In conclusion, the results from this thesis show that EHV1 infects CD172a+ cell populations, including DC and MSC, and causes downregulation of several important cell surface proteins on these infected cells. Although the exact underlying mechanisms and viral proteins involved in this downregulation need to be further defined, the results from this thesis add to our understanding of how EHV1 highjacks and manipulates its target cells for its own benefits

Using crop-pathogen modeling to identify plant traits to control Zymoseptoria tritici epidemics on wheat

Diversification in pathogen control methods to reduce the severity of economically important foliar diseases such as Zymoseptoria tritici on wheat is needed. One way is to identify plant physiological and architectural traits that influence disease development and that can be selected in the process of crop breeding. Such traits may be used for improving tolerance or disease escape. Traits favoring disease escape, the focus of our work, may significantly decrease crop epidemics (Robert et al., 2018). However, understanding the role of such traits in crop-pathogen interactions is a daunting task because the interactions are multiple and dynamic in time. To characterize and quantify crop-pathogen interactions, an innovative trait-based and resource-based modeling framework was developed (Precigout et al., 2017). In this framework, the pathosystem is assumed to respond dynamically to both architecture and physiological status of the host canopy. A canopy consists of plenty of small patches, i.e. small functional and infectable units of leaf tissue. Production of new patches, for canopy growth and renewal of photosynthetically active plant tissues, is a function of the available resources produced by the other patches. Pathogen spores can contaminate nearby healthy patches. The definition of patch proximity depends on dispersal abilities of the pathogen and canopy architecture. We used and adapted this modeling framework to quantify the effects of several plant traits on Zymoseptoria tritici epidemics for varied climate scenarios. The complex infection cycle of Z. tritici characterized by a long symptomless incubation period was implemented in the model. We studied plant architectural traits such as leaf size or stem height, and plant physiological traits such as leaf lifespan or leaf metabolite contents. In our simulations, these traits impacted the epidemics dynamics though their effects on pathogen dispersal and on the amount of resources available for the pathogen. Sensitivity analyses showed how disease severity depended on plant traits and pathogen virulence. The importance of several plant and pathogen traits could be linked to the pathogen’s ability to manage the race for the colonization of the canopy in the face of canopy growth. Playing on host traits also made it possible to simulate different wheat varieties - with contrasted heights, pathogen resistance or precocity - to characterize the behavior of the pathosystem of interest for different host ideotypes. We argue that this kind of trait-based modeling approach is a valuable tool to identify plant traits promoting more resilient agroecosystems in particular for crop breeding in a context of innovative and sustainable crop protection

Screening for Toxic Amyloid in Yeast Exemplifies the Role of Alternative Pathway Responsible for Cytotoxicity

The relationship between amyloid and toxic species is a central problem since the discovery of amyloid structures in different diseases. Despite intensive efforts in the field, the deleterious species remains unknown at the molecular level. This may reflect the lack of any structure-toxicity study based on a genetic approach. Here we show that a structure-toxicity study without any biochemical prerequisite can be successfully achieved in yeast. A PCR mutagenesis of the amyloid domain of HET-s leads to the identification of a mutant that might impair cellular viability. Cellular and biochemical analyses demonstrate that this toxic mutant forms GFP-amyloid aggregates that differ from the wild-type aggregates in their shape, size and molecular organization. The chaperone Hsp104 that helps to disassemble protein aggregates is strictly required for the cellular toxicity. Our structure-toxicity study suggests that the smallest aggregates are the most toxic, and opens a new way to analyze the relationship between structure and toxicity of amyloid species

Using crop-pathogen modeling to identify plant traits to control Zymoseptoria tritici epidemics on wheat

Diversification in pathogen control methods to reduce the severity of economically important foliar diseases such as Zymoseptoria tritici on wheat is needed. One way is to identify plant physiological and architectural traits that influence disease development and that can be selected in the process of crop breeding. Such traits may be used for improving tolerance or disease escape. Traits favoring disease escape, the focus of our work, may significantly decrease crop epidemics (Robert et al., 2018). However, understanding the role of such traits in crop-pathogen interactions is a daunting task because the interactions are multiple and dynamic in time. To characterize and quantify crop-pathogen interactions, an innovative trait-based and resource-based modeling framework was developed (Precigout et al., 2017). In this framework, the pathosystem is assumed to respond dynamically to both architecture and physiological status of the host canopy. A canopy consists of plenty of small patches, i.e. small functional and infectable units of leaf tissue. Production of new patches, for canopy growth and renewal of photosynthetically active plant tissues, is a function of the available resources produced by the other patches. Pathogen spores can contaminate nearby healthy patches. The definition of patch proximity depends on dispersal abilities of the pathogen and canopy architecture. We used and adapted this modeling framework to quantify the effects of several plant traits on Zymoseptoria tritici epidemics for varied climate scenarios. The complex infection cycle of Z. tritici characterized by a long symptomless incubation period was implemented in the model. We studied plant architectural traits such as leaf size or stem height, and plant physiological traits such as leaf lifespan or leaf metabolite contents. In our simulations, these traits impacted the epidemics dynamics though their effects on pathogen dispersal and on the amount of resources available for the pathogen. Sensitivity analyses showed how disease severity depended on plant traits and pathogen virulence. The importance of several plant and pathogen traits could be linked to the pathogen’s ability to manage the race for the colonization of the canopy in the face of canopy growth. Playing on host traits also made it possible to simulate different wheat varieties - with contrasted heights, pathogen resistance or precocity - to characterize the behavior of the pathosystem of interest for different host ideotypes. We argue that this kind of trait-based modeling approach is a valuable tool to identify plant traits promoting more resilient agroecosystems in particular for crop breeding in a context of innovative and sustainable crop protection

Using physiologically and spatially structured consumer- resource population models to address current issues in plant pathology

Epidemiologists and pathologists for addressing topical questions about, for example, the efficiency of agroecological solutions to mitigating crop diseases or their impact on pathogen evolution. We propose here to showcase two modeling approaches that our team is currently using in this context. Firstly, based on the framework of physiologically structured population models and its numerical implementation (referred to as the EBTtool) we represent a (multi-) seasonally growing crop canopy as a dynamic collection of small infectable patches of leaf tissue with intrinsic and dynamic properties (e.g. age, position in the canopy, nutrient content, infection status). Dynamics of predicted disease epidemics depend on the dynamic properties of all the patches over time. Secondly, the agent-based modeling environment NetLogo provides a conceptual framework to model spatially extended dynamics of disease progression in explicit landscapes with different spatial arrangements of crops that are not necessarily static over the cropping seasons. We are using these two modeling approaches to study resource dynamics at the canopy and landscape scales as a way to explore the potential of regulating crop pathogens by reducing or diversifying nitrogen fertilization practices in the pathosystems wheat/rusts and wheat/septoria tritici blotch. These modeling approaches offer the opportunity to (1) predict short and long term epidemiological dynamics based on assumptions on the consumer-resource interactions at the lesion scale, (2) to reveal pathogen trade-offs (transmission, virulence, aggressiveness) that emerge from the interactions between the pathogen and ecophysiological and morphological dynamics of the crop canopy, (3) to study the effect of spatial resource heterogeneity on pathogen dynamics, adaptation and maladaptation

Modelling interaction dynamics between two foliar pathogens in wheat: a multi-scale approach

International audienceBackground and AimsDisease models can improve our understanding of dynamic interactions in pathosystems and thus support the design of innovative and sustainable strategies of crop protections. However, most epidemiological models focus on a single type of pathogen, ignoring the interactions between different parasites competing on the same host and how they are impacted by properties of the canopy. This study presents a new model of a disease complex coupling two wheat fungal diseases, caused by Zymoseptoria tritici (septoria) and Puccinia triticina (brown rust), respectively, combined with a functional–structural plant model of wheat.MethodsAt the leaf scale, our model is a combination of two sub-models of the infection cycles for the two fungal pathogens with a sub-model of competition between lesions. We assume that the leaf area is the resource available for both fungi. Due to the necrotic period of septoria, it has a competitive advantage on biotrophic lesions of rust. Assumptions on lesion competition are first tested developing a geometrically explicit model on a simplified rectangular shape, representing a leaf on which lesions grow and interact according to a set of rules derived from the literature. Then a descriptive statistical model at the leaf scale was designed by upscaling the previous mechanistic model, and both models were compared. Finally, the simplified statistical model has been used in a 3-D epidemiological canopy growth model to simulate the diseases dynamics and the interactions at the canopy scale.Key ResultsAt the leaf scale, the statistical model was a satisfactory metamodel of the complex geometrical model. At the canopy scale, the disease dynamics for each fungus alone and together were explored in different weather scenarios. Rust and septoria epidemics showed different behaviours. Simulated epidemics of brown rust were greatly affected by the presence of septoria for almost all the tested scenarios, but the reverse was not the case. However, shortening the rust latent period or advancing the rust inoculum shifted the competition more in favour of rust, and epidemics became more balanced.ConclusionsThis study is a first step towards the integration of several diseases within virtual plant models and should prompt new research to understand the interactions between canopy properties and competing pathogens