The γδ T Cell Club: bringing a global scientific community together in the age of Zoom.

Immunologists are very social people-they love to meet other immunologists and talk about immunology (and immunologists). Constantly! γδ T-cell researchers are no exception. On the contrary, as there are not so many of them compared to, say, researchers working on dendritic cells, they especially crave frequent interactions with like-minded scientists. This is where the technological solutions being developed during the coronavirus disease 2019 (COVID-19) pandemic come into play that have, almost overnight, allowed researchers to hold meetings and lectures online. We here describe how we set up the virtual 'γδ T Cell Club', a monthly webinar series that aims to bring the field closer together, and present our musings about what we have learned from this experience, which we hope is useful for other researchers interested in connecting online.

Conventional and unconventional T-cell responses contribute to the prediction of clinical outcome and causative bacterial pathogen in sepsis patients.

Sepsis is characterized by a dysfunctional host response to infection culminating in life-threatening organ failure that requires complex patient management and rapid intervention. Timely diagnosis of the underlying cause of sepsis is crucial, and identifying those at risk of complications and death is imperative for triaging treatment and resource allocation. Here, we explored the potential of explainable machine learning models to predict mortality and causative pathogen in sepsis patients. By using a modelling pipeline employing multiple feature selection algorithms, we demonstrate the feasibility of identifying integrative patterns from clinical parameters, plasma biomarkers, and extensive phenotyping of blood immune cells. While no single variable had sufficient predictive power, models that combined five and more features showed a macro area under the curve (AUC) of 0.85 to predict 90-day mortality after sepsis diagnosis, and a macro AUC of 0.86 to discriminate between Gram-positive and Gram-negative bacterial infections. Parameters associated with the cellular immune response contributed the most to models predictive of 90-day mortality, most notably, the proportion of T cells among PBMCs, together with expression of CXCR3 by CD4+ T cells and CD25 by mucosal-associated invariant T (MAIT) cells. Frequencies of Vδ2+ γδ T cells had the most profound impact on the prediction of Gram-negative infections, alongside other T-cell-related variables and total neutrophil count. Overall, our findings highlight the added value of measuring the proportion and activation patterns of conventional and unconventional T cells in the blood of sepsis patients in combination with other immunological, biochemical, and clinical parameters.

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

MOTIVATION: Clustering is an unsupervised method for identifying structure in unlabelled data. In the context of cytometry, it is typically used to categorize cells into subpopulations of similar phenotypes. 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. To the best of our knowledge, consensus clustering algorithms designed specifically for the analysis of cytometry data are lacking. RESULTS: We 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 single-cell RNA sequencing 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, visualization 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 IMPLEMENTATION: GeoWaVe is available as part of the CytoCluster package https://github.com/burtonrj/CytoCluster and published on the Python Package Index https://pypi.org/project/cytocluster. Benchmarking data described are available from https://doi.org/10.5281/zenodo.7134723. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

On the Influence of Humidity on a Thermal Conductivity Sensor for the Detection of Hydrogen.

Thermal conductivity sensors face an omnipresent cross-influence through varying humidity levels in real-life applications. We present the results of investigations on the influence of humidity on a hydrogen thermal conductivity sensor and approaches for predicting the behavior of thermal conductivity towards humidity. A literature search and comparison of different mixing equations for binary gas mixtures were carried out. The theoretical results were compared with experimental results from three different thermal conductivity sensors with mixtures of water vapor in nitrogen. The mixing equations show a large discrepancy between each other. Some of the models predict a continuously decreasing thermal conductivity and some predict an increasing thermal conductivity for increasing levels of humidity. Our measurements indicate an increase in thermal conductivity followed by a decrease after reaching a peak value. It is shown that the measured behavior is reproducible with different sensors. Depending on the sensor, this corresponds to an error up to 2 vol.% in the measured hydrogen value. The measured behavior is consistent with only one of the three models. Compared to this model, our own sensor shows a maximum deviation of 1.4%. Mixing equations for gas mixtures must be chosen carefully, taking into consideration whether mixing partners include polar or non-polar molecules. Some simplified mixing equations cannot be used to calculate the thermal conductivity of water vapor in air or nitrogen.

Overcoming the disconnect between scientific research and the public.

In biomedical research, there is no situation where public engagement (PE) and public involvement (PI) are not possible, important or even expected. Whether we work in the clinic or in the laboratory, all researchers have a duty to reach out, demonstrate the added value that science brings to society, and make a real difference to the way research is done. Here we outline the benefits of PE and PI for individual researchers and their employers, for members of the public, and for society at large. We offer solutions to overcome major challenges, including a step-by-step guide for researchers to embrace PE and PI in their career, and make a call to action for a cultural shift towards embedding PE and PI in our modern academic environment.

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 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/.

Anodically Bonded Photoacoustic Transducer: An Approach towards Wafer-Level Optical Gas Sensors.

We present a concept for a wafer-level manufactured photoacoustic transducer, suitable to be used in consumer-grade gas sensors. The transducer consists of an anodically bonded two-layer stack of a blank silicon wafer and an 11 µm membrane, which was wet-etched from a borosilicate wafer. The membrane separates two cavities; one of which was hermetically sealed and filled with CO2 during the anodic bonding and acts as an infrared absorber. The second cavity was designed to be connected to a standard MEMS microphone on PCB-level forming an infrared-sensitive photoacoustic detector. CO2 sensors consisting of the detector and a MEMS infrared emitter were built up and characterized towards their sensitivity and noise levels at six different component distance ranging from 3.0 mm to 15.5 mm. The signal response for the sample with the longest absorption path ranged from a decrease of 8.3% at a CO2 concentration of 9400 ppm to a decrease of 0.8% at a concentration of 560 ppm. A standard deviation of the measured values of 18 ppm was determined when the sensor was exposed to 1000 ppm CO2.

Control of neutrophil influx during peritonitis by transcriptional cross-regulation of chemokine CXCL1 by IL-17 and IFN-γ.

Neutrophil infiltration is a hallmark of peritoneal inflammation, but mechanisms regulating neutrophil recruitment in patients with peritoneal dialysis (PD)-related peritonitis are not fully defined. We examined 104 samples of PD effluent collected during acute peritonitis for correspondence between a broad range of soluble parameters and neutrophil counts. We observed an association between peritoneal IL-17 and neutrophil levels. This relationship was evident in effluent samples with low but not high IFN-γ levels, suggesting a differential effect of IFN-γ concentration on neutrophil infiltration. Surprisingly, there was no association of neutrophil numbers with the level of CXCL1, a key IL-17-induced neutrophil chemoattractant. We investigated therefore the production of CXCL1 by human peritoneal mesothelial cells (HPMCs) under in vitro conditions mimicking clinical peritonitis. Stimulation of HPMCs with IL-17 increased CXCL1 production through induction of transcription factor SP1 and activation of the SP1-binding region of the CXCL1 promoter. These effects were amplified by TNFα. In contrast, IFN-γ dose-dependently suppressed IL-17-induced SP1 activation and CXCL1 production through a transcriptional mechanism involving STAT1. The SP1-mediated induction of CXCL1 was also observed in HPMCs exposed to PD effluent collected during peritonitis and containing IL-17 and TNFα, but not IFN-γ. Supplementation of the effluent with IFN-γ led to a dose-dependent activation of STAT1 and a resultant inhibition of SP1-induced CXCL1 expression. Transmesothelial migration of neutrophils in vitro increased upon stimulation of HPMCs with IL-17 and was reduced by IFN-γ. In addition, HPMCs were capable of binding CXCL1 at their apical cell surface. These observations indicate that changes in relative peritoneal concentrations of IL-17 and IFN-γ can differently engage SP1-STAT1, impacting on mesothelial cell transcription of CXCL1, whose release and binding to HPMC surface may determine optimal neutrophil recruitment and retention during peritonitis. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

γδ T cell responses: How many ligands will it take till we know?

γδ T cells constitute a sizeable and non-redundant fraction of the total T cell pool in all jawed vertebrates, but in contrast to conventional αß T cells they are not restricted by classical MHC molecules. Progress in our understanding of the role of γδ T cells in the immune system has been hampered, and is being hampered, by the considerable lack of knowledge regarding the antigens γδ T cells respond to. The past few years have seen a wealth of data regarding the TCR repertoires of distinct γδ T cell populations and a growing list of confirmed and proposed molecules that are recognised by γδ T cells in different species. Yet, the physiological contexts underlying the often restricted TCR usage and the chemical diversity of γδ T cell ligands remain largely unclear, and only few structural studies have confirmed direct ligand recognition by the TCR. We here review the latest progress in the identification and validation of putative γδ T cell ligands and discuss the implications of such findings for γδ T cell responses in health and disease.

Zoledronate rescues immunosuppressed monocytes in sepsis patients.

Severe sepsis is often accompanied by a transient immune paralysis, which is associated with enhanced susceptibility to secondary infections and poor clinical outcomes. The functional impairment of antigen-presenting cells is considered to be a major hallmark of this septic immunosuppression, with reduced HLA-DR expression on circulating monocytes serving as predictor of mortality. Unconventional lymphocytes like γδ T-cells have the potential to restore immune defects in a variety of pathologies including cancer, but their use to rescue sepsis-induced immunosuppression has not been investigated. Our own previous work showed that Vγ9/Vδ2+ γδ T-cells are potent activators of monocytes from healthy volunteers in vitro, and in individuals with osteoporosis after first-time administration of the anti-bone resorption drug zoledronate in vivo. We show here that zoledronate readily induces upregulation of HLA-DR, CD40 and CD64 on monocytes from both healthy controls and sepsis patients, which could be abrogated by neutralising the pro-inflammatory cytokines interferon (IFN)-γ and tumour necrosis factor (TNF)-α in the cultures. In healthy controls, the upregulation of HLA-DR on monocytes was proportional to the baseline percentage of Vγ9/Vδ2 T-cells in the peripheral blood mononuclear cell population. Of note, a proportion of sepsis patients studied here did not show a demonstrable response to zoledronate, predominantly patients with microbiologically confirmed bloodstream infections, compared with sepsis patients with more localised infections marked by negative blood cultures. Taken together, our results suggest that zoledronate can, at least in some individuals, rescue immunosuppressed monocytes during acute sepsis and thus may help improve clinical outcomes during severe infection.

Measurement of innate immune response biomarkers in peritoneal dialysis effluent using a rapid diagnostic point-of-care device as a diagnostic indicator of peritonitis.

Peritonitis is the commonest complication of peritoneal dialysis and a major reason for treatment failure. Current diagnosis is based on clinical symptoms, cloudy effluent and a dialysate white cell count (over 100 cells/µl). A rapid point-of-care diagnostic test would accelerate diagnosis and potentially improve outcomes from infection. Here, in a clinical audit project, we used PERiPLEX®, a point-of-care device which detects when levels of matrix metalloproteinase-8 and interleukin-6 are elevated above a threshold within minutes in dialysis effluent, to assess whether it could confirm or exclude peritonitis in 107 patients undergoing peritoneal dialysis. Mean patient age was 64.6 years with a median duration of peritoneal dialysis of 13.3 months (interquartile range 6.3 - 33.5 months). Presence of peritonitis was confirmed by clinical criteria. There were 49 positive tests of which 41 patients had peritonitis, three had other causes of intra-peritoneal inflammation, three had severe urosepsis and two patients required no treatment. Fifty-eight tests were negative with one patient having a false negative result. The positive predictive value of the test was 83.7% (95% confidence interval 72.8 - 90.8) and the negative predictive value was 98.3% (89.1 - 99.8). Sensitivity and specificity were 97.6% (87.4 - 99.9) and 87.7% (77.2 - 94.5) respectively. Thus, PERiPLEX® could be used as a rapid point-of-care test that can aid the diagnosis or exclusion of peritonitis with a high negative predictive value.

Antigen recognition by human γδ T cells: one step closer to knowing.

Sensing of self and non-self phosphoantigens by human Vγ9/Vδ2 T cells in the context of the butyrophilin family members BTN2A1 and BTN3A1.

Antigen-Presenting Human γδ T Cells Promote Intestinal CD4+ T Cell Expression of IL-22 and Mucosal Release of Calprotectin.

The cytokine IL-22 plays a critical role in mucosal barrier defense, but the mechanisms that promote IL-22 expression in the human intestine remain poorly understood. As human microbe-responsive Vγ9/Vδ2 T cells are abundant in the gut and recognize microbiota-associated metabolites, we assessed their potential to induce IL-22 expression by intestinal CD4+ T cells. Vγ9/Vδ2 T cells with characteristics of APCs were generated from human blood and intestinal organ cultures, then cocultured with naive and memory CD4+ T cells obtained from human blood or the colon. The potency of blood and intestinal γδ T-APCs was compared with that of monocytes and dendritic cells, by assessing CD4+ T cell phenotypes and proliferation as well as cytokine and transcription factor profiles. Vγ9/Vδ2 T cells in human blood, colon, and terminal ileum acquired APC functions upon microbial activation in the presence of microenvironmental signals including IL-15, and were capable of polarizing both blood and colonic CD4+ T cells toward distinct effector fates. Unlike monocytes or dendritic cells, gut-homing γδ T-APCs employed an IL-6 independent mechanism to stimulate CD4+ T cell expression of IL-22 without upregulating IL-17. In human intestinal organ cultures, microbial activation of Vγ9/Vδ2 T cells promoted mucosal secretion of IL-22 and ICOSL/TNF-α-dependent release of the IL-22 inducible antimicrobial protein calprotectin without modulating IL-17 expression. In conclusion, human γδ T-APCs stimulate CD4+ T cell responses distinct from those induced by myeloid APCs to promote local barrier defense via mucosal release of IL-22 and calprotectin. Targeting of γδ T-APC functions may lead to the development of novel gut-directed immunotherapies and vaccines.

Using artificial intelligence to reduce diagnostic workload without compromising detection of urinary tract infections.

BACKGROUND: A substantial proportion of microbiological screening in diagnostic laboratories is due to suspected urinary tract infections (UTIs), yet approximately two thirds of urine samples typically yield negative culture results. By reducing the number of query samples to be cultured and enabling diagnostic services to concentrate on those in which there are true microbial infections, a significant improvement in efficiency of the service is possible. METHODOLOGY: Screening process for urine samples prior to culture was modelled in a single clinical microbiology laboratory covering three hospitals and community services across Bristol and Bath, UK. Retrospective analysis of all urine microscopy, culture, and sensitivity reports over one year was used to compare two methods of classification: a heuristic model using a combination of white blood cell count and bacterial count, and a machine learning approach testing three algorithms (Random Forest, Neural Network, Extreme Gradient Boosting) whilst factoring in independent variables including demographics, historical urine culture results, and clinical details provided with the specimen. RESULTS: A total of 212,554 urine reports were analysed. Initial findings demonstrated the potential for using machine learning algorithms, which outperformed the heuristic model in terms of relative workload reduction achieved at a classification sensitivity > 95%. Upon further analysis of classification sensitivity of subpopulations, we concluded that samples from pregnant patients and children (age 11 or younger) require independent evaluation. First the removal of pregnant patients and children from the classification process was investigated but this diminished the workload reduction achieved. The optimal solution was found to be three Extreme Gradient Boosting algorithms, trained independently for the classification of pregnant patients, children, and then all other patients. When combined, this system granted a relative workload reduction of 41% and a sensitivity of 95% for each of the stratified patient groups. CONCLUSION: Based on the considerable time and cost savings achieved, without compromising the diagnostic performance, the heuristic model was successfully implemented in routine clinical practice in the diagnostic laboratory at Severn Pathology, Bristol. Our work shows the potential application of supervised machine learning models in improving service efficiency at a time when demand often surpasses resources of public healthcare providers.

Unconventional Human T Cells Accumulate at the Site of Infection in Response to Microbial Ligands and Induce Local Tissue Remodeling.

The antimicrobial responsiveness and function of unconventional human T cells are poorly understood, with only limited access to relevant specimens from sites of infection. Peritonitis is a common and serious complication in individuals with end-stage kidney disease receiving peritoneal dialysis. By analyzing local and systemic immune responses in peritoneal dialysis patients presenting with acute bacterial peritonitis and monitoring individuals before and during defined infectious episodes, our data show that Vγ9/Vδ2(+) γδ T cells and mucosal-associated invariant T cells accumulate at the site of infection with organisms producing (E)-4-hydroxy-3-methyl-but-2-enyl pyrophosphate and vitamin B2, respectively. Such unconventional human T cells are major producers of IFN-γ and TNF-α in response to these ligands that are shared by many microbial pathogens and affect the cells lining the peritoneal cavity by triggering local inflammation and inducing tissue remodeling with consequences for peritoneal membrane integrity. Our data uncover a crucial role for Vγ9/Vδ2 T cells and mucosal-associated invariant T cells in bacterial infection and suggest that they represent a useful predictive marker for important clinical outcomes, which may inform future stratification and patient management. These findings are likely to be applicable to other acute infections where local activation of unconventional T cells contributes to the antimicrobial inflammatory response.

Toll-Like Receptors 2 and 4 Are Potential Therapeutic Targets in Peritoneal Dialysis-Associated Fibrosis.

Peritoneal dialysis (PD) remains limited by dialysis failure due to peritoneal membrane fibrosis driven by inflammation caused by infections or sterile cellular stress. Given the fundamental role of Toll-like receptors (TLRs) and complement in inflammation, we assessed the potential of peritoneal TLR2, TLR4 and C5a receptors, C5aR and C5L2, as therapeutic targets in PD-associated fibrosis. We detected TLR2-, TLR4-, and C5aR-mediated proinflammatory and fibrotic responses to bacteria that were consistent with the expression of these receptors in peritoneal macrophages (TLR2/4, C5aR) and mesothelial cells (TLR2, C5aR). Experiments in knockout mice revealed a major role for TLR2, a lesser role for TLR4, a supplementary role for C5aR, and no apparent activity of C5L2 in infection-induced peritoneal fibrosis. Similarly, antibody blockade of TLR2, TLR4, or C5aR differentially inhibited bacteria-induced profibrotic and inflammatory mediator production by peritoneal leukocytes isolated from the peritoneal dialysis effluent (PDE) of noninfected uremic patients. Additionally, antibodies against TLR2, TLR4, or the coreceptor CD14 reduced the profibrotic responses of uremic leukocytes to endogenous components present in the PDE of noninfected patients. Enhancing TLR2-mediated inflammation increased fibrosis in vivo Furthermore, soluble TLR2 (sTLR2), a negative modulator of TLRs that we detected in PDE, inhibited PDE-induced, TLR2- or TLR4-mediated profibrotic responses. Notably, sTLR2 treatment markedly reduced Gram-positive and -negative bacteria-induced fibrosis in vivo, inhibiting proinflammatory and fibrotic genes without affecting infection clearance. These findings reveal the influence of peritoneal TLR2 and TLR4 on PD-associated fibrosis and describe a therapeutic strategy against fibrosis.

The Antigen-Presenting Potential of Vγ9Vδ2 T Cells During Plasmodium falciparum Blood-Stage Infection.

During Plasmodium falciparum infections, erythrocyte-stage parasites inhibit dendritic cell maturation and function, compromising effective antimalarial adaptive immunity. Human Vγ9Vδ2 T cells can act in vitro as antigen-presenting cells (APCs) and induce αß T-cell activation. However, the relevance of this activity in vivo has remained elusive. Because Vγ9Vδ2 T cells are activated during the early immune response against P. falciparum infection, we investigated whether they could contribute to the instruction of adaptive immune responses toward malaria parasites. In P. falciparum-infected patients, Vγ9Vδ2 T cells presented increased surface expression of APC-associated markers HLA-DR and CD86. In response to infected red blood cells in vitro, Vγ9Vδ2 T cells upregulated surface expression of HLA-DR, HLA-ABC, CD40, CD80, CD83, and CD86, induced naive αß T-cell responses, and cross- presented soluble prototypical protein to antigen-specific CD8+ T cells. Our findings qualify Vγ9Vδ2 T cells as alternative APCs, which could be harnessed for therapeutic interventions and vaccine design.

Biomarker research to improve clinical outcomes of peritoneal dialysis: consensus of the European Training and Research in Peritoneal Dialysis (EuTRiPD) network.

Peritoneal dialysis (PD) therapy substantially requires biomarkers as tools to identify patients who are at the highest risk for PD-related complications and to guide personalized interventions that may improve clinical outcome in the individual patient. In this consensus article, members of the European Training and Research in Peritoneal Dialysis Network (EuTRiPD) review the current status of biomarker research in PD and suggest a selection of biomarkers that can be relevant to the care of PD patients and that are directly accessible in PD effluents. Currently used biomarkers such as interleukin-6, interleukin-8, ex vivo-stimulated interleukin-6 release, cancer antigen-125, and advanced oxidation protein products that were collected through a Delphi procedure were first triaged for inclusion as surrogate endpoints in a clinical trial. Next, novel biomarkers were selected as promising candidates for proof-of-concept studies and were differentiated into inflammation signatures (including interleukin-17, M1/M2 macrophages, and regulatory T cell/T helper 17), mesothelial-to-mesenchymal transition signatures (including microRNA-21 and microRNA-31), and signatures for senescence and inadequate cellular stress responses. Finally, the need for defining pathogen-specific immune fingerprints and phenotype-associated molecular signatures utilizing effluents from the clinical cohorts of PD patients and "omics" technologies and bioinformatics-biostatistics in future joint-research efforts was expressed. Biomarker research in PD offers the potential to develop valuable tools for improving patient management. However, for all biomarkers discussed in this consensus article, the association of biological rationales with relevant clinical outcomes remains to be rigorously validated in adequately powered, prospective, independent clinical studies.