Biology subjects

Eberl, M.

Publications and source records attributed to Eberl, M..

7 recordsLinked to original sources

bioRxiv2025

Bacterial suppression of intestinal fungi via activation of human gut γδ T-cells

Gut symbionts condition mucosal immunity to resist infection by enteropathogens, but the specific microbes and mechanisms involved differ significantly between host species. In higher primates, bacterial metabolite HMB-PP is sensed by a specialized population of V{gamma}9V{delta}2+T-cells, which we now report can potently suppress growth of endogenous fungi in human intestinal organ cultures. In healthy intestine, HMB-PP-stimulated V{delta}2+T-cells restricted outgrowth of keystone fungus Candida albicans via a mechanism that required IL-22. In contrast, Crohns disease (CD) patients with reduced V{delta}2+T-cell numbers displayed outgrowth of C. albicans strains that readily formed toxin-producing filaments, triggered neutrophil extracellular traps, and induced macrophage IL-1{beta} release ex vivo. Genomic and proteomic analysis of the Candida isolates suggested increased tissue adhesion of CD-derived strains, which rapidly invaded the gut barrier in an intestine-on-a-chip model. These data reveal that bacterial activation of V{delta}2+T-cells suppresses fungal pathobionts in human gut via an IL-22-dependent mechanism that is dysregulated in CD.

immunology↗

bioRxiv2024

NKG2A-mediated immune modulation of natural killer cells by Staphylococcus aureus

Natural killer (NK) cells are specialized lymphocytes that help protect against viruses and cancer. However, in the context of bacterial infections, NK cells can be harmful, rather than protective. Such immune pathogenesis by NK cells has been linked to the over-production of pro-inflammatory cytokines like interferon-{gamma} (IFN-{gamma}). In this context, IFN-{gamma}-deficient mice display increased survival rates in response to Staphylococcus aureus (S. aureus), which causes life-threatening, invasive systemic infections with high mortality rates in humans. However, little is known about how NK cells respond to S. aureus in humans. In this study, we found that the peripheral blood of patients with bloodstream S. aureus infection was enriched for NKG2A+ NK cells with greater cytokine producing capacity, compared to those hospitalized with Escherichia coli bloodstream infections. As a possible mechanistic cause, superantigens from S. aureus promoted the expansion of CD57- NKG2A+ NK cells which produced IFN-{gamma} through an IL-12-independent mechanism and exhibited reduced levels of CD16 compared to unstimulated NK cells. These data suggest that S. aureus bloodstream infection in humans promotes a phenotypic shift towards NKG2A+ NK cells with greater IFN-{gamma} producing capacity, providing a plausible way to promote inflammation-driven disease pathogenesis. AUTHOR SUMMARYNatural Killer (NK) cells are specialized immune cells that provide crucial defence against viruses but can also respond to bacterial infections, especially in humans. During bloodstream infection by Staphylococcus aureus, a Gram-positive bacterial pathogen that causes life-threatening infections in humans, NK cells may actually be harmful, rather than protective, to the host. However, very little is known about the NK cell response to invasive Staphylococcus aureus infections in humans. Here, we show that human patients with bloodstream Staphylococcus aureus, but not Escherichia coli, infections have an increased frequency of NK cells with increased pro-inflammatory capacity. Furthermore, we show that toxins produced by Staphylococcus aureus, which help the bacteria evade the protective effects of T cells the immune system ("superantigens"), promoted the expansion of these pro-inflammatory NK cells, providing a possible mechanistic cause for their increased presence in patients with bloodstream Staphylococcus aureus infections. Collectively, these results suggest that Staphylococcus aureus infection triggers phenotypic and functional changes in NK cells that provide a plausible way to promote inflammation-driven disease pathogenesis

immunology↗

bioRxiv2023

Superbugs online: Co-production of an educational website to increase public understanding of the microbial world in, on and around us

1.Digital tools and online presence have become a cornerstone to public engagement and involvement strategy and delivery. We here describe the co-production process behind launching a new multilingual resource for schools in the UK and beyond, jointly between university scientists, engagement professionals, primary and secondary teachers, and web designers. The Superbugs website aims at raising awareness and increasing public understanding of the microbial world in, on and around us, and has attracted >19,000 online visitors, >33,500 page views and >775,000 Twitter impressions over the past 24 months. Superbugs.online is available in English, Welsh, Irish and Scottish Gaelic, thus making it accessible to everyone in the UK and Ireland, regardless of the language in which they receive and deliver their science education. The website is easy to navigate and features background information, quizzes, animations, videos, illustrated stories, interactive timelines, games and protocols for home experiments. All materials are presented in a non-prescriptive way, aimed at allowing flexibility for the materials to be adapted to the individual needs of teachers and pupils alike. Our work has led to demonstrable impact on the co-production team and on pupils and teachers as key stakeholders, based on a comprehensive evaluation of the co-production process itself, the impact of the end product, and the creation of lasting relationships with stakeholders and co-producers, for the mutual benefit of everyone involved. 2. Data summaryThe authors confirm all supporting data have been provided within the article or through supplementary data files.

microbiology↗

bioRxiv2022

GeoWaVe: Geometric median clustering with weighted voting for ensemble clustering of cytometry data

MotivationClustering is an unsupervised method for identifying structure in unlabelled data. In the context of cytometry, is typically used to categorise cells into subpopulations of similar phenotype. However, clustering is greatly dependent on hyperparameters and the data to which it is applied as each algorithm makes different assumptions and generates a different view of the dataset. As such, the choice of clustering algorithm can significantly influence results, and there is often not one preferred method but different insights to be obtained from different methods. To overcome these limitations, consensus approaches are needed that directly address the effect of competing algorithms, which to our knowledge has not been applied to cytometry. ResultsWe present a novel ensemble clustering methodology based on geometric median clustering with weighted voting (GeoWaVe). Compared to graph ensemble clustering methods that have gained popularity in scRNA-seq analysis, GeoWaVe performed favourably on different sets of high-dimensional mass and flow cytometry data. Our findings provide proof of concept for the power of consensus methods to make the analysis, visualisation and interpretation of cytometry data more robust and reproducible. The wide availability of ensemble clustering methods is likely to have a profound impact on our understanding of cellular responses, clinical conditions, and therapeutic and diagnostic options. Availability and implementationGeoWaVe is available as part of the CytoCluster package https://github.com/burtonrj/CytoCluster. ContactRoss.Burton@wales.nhs.uk

bioinformatics↗

bioRxiv2021

'Superbugs: A Pop-up Science Shop': Increasing public awareness and knowledge of antimicrobial resistance by taking science to the city

Superbugs: A Pop-up Science Shop was a public engagement event in the school summer holidays of 2019, organised by members of Cardiff Universitys School of Medicine. We transformed an empty retail unit in the centre of Wales largest shopping centre into an interactive and immersive microbiology experience. We aimed to facilitate opportunities for two-way dialogue to impart positive impact on the awareness of antibiotic resistance, whilst concurrently evaluating the efficacy of an engagement strategy focused on the utilisation of public spaces to attract public demographics diverse to those who would normally engage with STEM outreach. Over the course of 14 days, we welcomed 6,566 visitors, with 67% attending as part of the natural footfall of the shopping centre. We created 1,625 young Antibiotic Resistance Champions, located in over 200 schools. Through a multi-lateral evaluation strategy, we were able to collect quantitative and qualitative feedback on the success of our delivery model, and the impact on our stakeholders. Herein, we will discuss the evolution of Superbugs from concept, planning and design, to the logistics of delivering an engagement event of this scale. We will focus in particular on the learning outcomes of the project, and how this will shape the future of our Superbugs project, and engagement events beyond. Key MessagesO_LICreating a multi-disciplinary core team is essential to the success of large-scale engagement events as well as the support and development of large numbers of colleagues/volunteers C_LIO_LIUtilising themes of exhibition and gameplay alongside strong fear-empowerment messages is an impactful way to confer positive influence and behaviour around antimicrobial resistance (AMR) and the use of antibiotics C_LIO_LI Pop-up shop is an effective mode of delivery to capture diverse public demographics far beyond those who would traditionally engage with scientific outreach and science engagement. C_LI

scientific communication and education↗

bioRxiv2021

ADNKA overcomes SARS-CoV2-mediated NK cell inhibition through non-spike antibodies

The outcome of infection is dependent on the ability of viruses to manipulate the infected cell to evade immunity, and the ability of the immune response to overcome this evasion. Understanding this process is key to understanding pathogenesis, genetic risk factors, and both natural and vaccine-induced immunity. SARS-CoV-2 antagonises the innate interferon response, but whether it manipulates innate cellular immunity is unclear. An unbiased proteomic analysis determined how cell surface protein expression is altered on SARS-CoV-2-infected lung epithelial cells, showing downregulation of activating NK ligands B7-H6, MICA, ULBP2, and Nectin1, with minimal effects on MHC-I. This correlated with a reduction in NK cell activation, identifying a novel mechanism by which SARS-CoV2 antagonises innate immunity. Later in the disease process, strong antibody-dependent NK cell activation (ADNKA) developed. These responses were sustained for at least 6 months in most patients, and led to high levels of pro-inflammatory cytokine production. Depletion of spike-specific antibodies confirmed their dominant role in neutralisation, but these antibodies played only a minor role in ADNKA compared to antibodies to other proteins, including ORF3a, Membrane, and Nucleocapsid. In contrast, ADNKA induced following vaccination was focussed solely on spike, was weaker than ADNKA following natural infection, and was not boosted by the second dose. These insights have important implications for understanding disease progression, vaccine efficacy, and vaccine design.

immunology↗

bioRxiv2020

CytoPy: an autonomous cytometry analysis framework

Cytometry analysis has seen a considerable expansion in recent years in the maximum number of parameters that can be acquired in a single experiment. In response to this technological advance there has been an increased effort to develop new computational methodologies for handling high-dimensional single cell data acquired by flow or mass cytometry. Despite the success of numerous algorithms and published packages to replicate and outperform traditional manual analysis, widespread adoption of these techniques has yet to be realised in the field of immunology. Here we present CytoPy, a Python framework for automated analysis of cytometry data that integrates a document-based database for a data-centric and iterative analytical environment. In addition, our algorithm agnostic design provides a platform for open-source cytometry bioinformatics in the Python ecosystem. We demonstrate the ability of CytoPy to phenotype T cell subsets in whole blood samples even in the presence of significant batch effects due to technical and user variation. The complete analytical pipeline was then used to immunophenotype the local inflammatory infiltrate in individuals with and without acute bacterial infection. CytoPy is open-source and licensed under the MIT license. CytoPy is open source and available at https://github.com/burtonrj/CytoPy, with notebooks accompanying this manuscript (https://github.com/burtonrj/CytoPyManuscript) and software documentation at https://cytopy.readthedocs.io/.

bioinformatics↗