Differential regulation of IL-17A and IL-17F via STAT5 contributes to psoriatic disease.

BACKGROUND: IL-17A plays a pivotal pathogenic role in several immune-mediated inflammatory diseases. Despite sharing 50% sequence homology with IL-17A, the role of IL-17F remains less clear. Clinical findings suggest that dual inhibition of IL-17A and IL-17F in psoriatic disease is more efficacious than IL-17A inhibition alone, positing a pathogenic role for IL-17F. OBJECTIVE: We characterized the regulation of IL-17A and IL-17F in psoriatic disease. METHODS: Using both in vitro systems and lesional skin tissue from patients, we interrogated the chromosomal, transcriptional, and protein expression landscape of IL-17A+ and IL-17F+ TH17 cells. Alongside established assays such as single-cell RNA sequencing, we developed a novel cytokine-capture technique that was combined with chromatin immunoprecipitation sequencing and RNA sequencing. RESULTS: We confirm a preferential elevation of IL-17F over IL-17A in psoriatic disease and show that expression of each isoform predominantly occurs in distinct cell populations. The expression of both IL-17A and IL-17F exhibited a high degree of plasticity, with the balance between the 2 isoforms influenced by proinflammatory signaling and by anti-inflammatory drugs such as methylprednisolone. This plasticity was reflected in a broad H3K4me3 region at the IL17A-F locus, while opposing effects of STAT5/IL-2 signaling were observed for each of the 2 genes. Functionally, higher IL17F expression was linked to greater cell proliferation. CONCLUSION: There are key differences in the regulation of IL-17A and IL-17F in psoriatic disease, leading to distinct inflammatory cell populations. As such, we propose that both IL-17A and IL-17F neutralization may be required to maximally inhibit IL-17-driven pathology.

Profiles of autism characteristics in thirteen genetic syndromes: a machine learning approach.

BACKGROUND: Phenotypic studies have identified distinct patterns of autistic characteristics in genetic syndromes associated with intellectual disability (ID), leading to diagnostic uncertainty and compromised access to autism-related support. Previous research has tended to include small samples and diverse measures, which limits the generalisability of findings. In this study, we generated detailed profiles of autistic characteristics in a large sample of > 1500 individuals with rare genetic syndromes. METHODS: Profiles of autistic characteristics based on the Social Communication Questionnaire (SCQ) scores were generated for thirteen genetic syndrome groups (Angelman n = 154, Cri du Chat n = 75, Cornelia de Lange n = 199, fragile X n = 297, Prader-Willi n = 278, Lowe n = 89, Smith-Magenis n = 54, Down n = 135, Sotos n = 40, Rubinstein-Taybi n = 102, 1p36 deletion n = 41, tuberous sclerosis complex n = 83 and Phelan-McDermid n = 35 syndromes). It was hypothesised that each syndrome group would evidence a degree of specificity in autistic characteristics. To test this hypothesis, a classification algorithm via support vector machine (SVM) learning was applied to scores from over 1500 individuals diagnosed with one of the thirteen genetic syndromes and autistic individuals who did not have a known genetic syndrome (ASD; n = 254). Self-help skills were included as an additional predictor. RESULTS: Genetic syndromes were associated with different but overlapping autism-related profiles, indicated by the substantial accuracy of the entire, multiclass SVM model (55% correctly classified individuals). Syndrome groups such as Angelman, fragile X, Prader-Willi, Rubinstein-Taybi and Cornelia de Lange showed greater phenotypic specificity than groups such as Cri du Chat, Lowe, Smith-Magenis, tuberous sclerosis complex, Sotos and Phelan-McDermid. The inclusion of the ASD reference group and self-help skills did not change the model accuracy. LIMITATIONS: The key limitations of our study include a cross-sectional design, reliance on a screening tool which focuses primarily on social communication skills and imbalanced sample size across syndrome groups. CONCLUSIONS: These findings replicate and extend previous work, demonstrating syndrome-specific profiles of autistic characteristics in people with genetic syndromes compared to autistic individuals without a genetic syndrome. This work calls for greater precision of assessment of autistic characteristics in individuals with genetic syndromes associated with ID.

Machine learning approach towards explaining water quality dynamics in an urbanised river.

Human activities alter river water quality and quantity, with consequences for the ecosystems of urbanised rivers. Quantifying the role of human-induced drivers in controlling spatio-temporal patterns in water quality is critical to develop successful strategies for improving the ecological health of urban rivers. Here, we analyse high-frequency electrical conductivity and temperature data collected from the River Chess in South-East England during a Citizen Science project. Utilizing machine learning, we find that boosted trees outperform GAM and accurately describe water quality dynamics with less than 1% error. SHapley Additive exPlanations reveal the importance of and the (inter)dependencies between the individual variables, such as river level and Wastewater Treatment Works (WWTW) outflow. WWTW outflows give rise to diurnal variations in electrical conductivity, which are detectable throughout the year, and to an increase in average water temperature of 1 [Formula: see text] in a 2 km reach downstream of the wastewater treatment works during low flows. Overall, we showcase how high-frequency water quality measurements initiated by a Citizen Science project, together with machine learning techniques, can help untangle key drivers of water quality dynamics in an urbanised chalk stream.

Single cell analyses identify a highly regenerative and homogenous human CD34+ hematopoietic stem cell population.

The heterogeneous nature of human CD34+ hematopoietic stem cells (HSCs) has hampered our understanding of the cellular and molecular trajectories that HSCs navigate during lineage commitment. Using various platforms including single cell RNA-sequencing and extensive xenotransplantation, we have uncovered an uncharacterized human CD34+ HSC population. These CD34+EPCR+(CD38/CD45RA)- (simply as EPCR+) HSCs have a high repopulating and self-renewal abilities, reaching a stem cell frequency of ~1 in 3 cells, the highest described to date. Their unique transcriptomic wiring in which many gene modules associated with differentiated cell lineages confers their multilineage lineage output both in vivo and in vitro. At the single cell level, EPCR+ HSCs are the most transcriptomically and functionally homogenous human HSC population defined to date and can also be easily identified in post-natal tissues. Therefore, this EPCR+ population not only offers a high human HSC resolution but also a well-structured human hematopoietic hierarchical organization at the most primitive level.

Fluctuations of water quality time series in rivers follow superstatistics.

Superstatistics is a general method from nonequilibrium statistical physics which has been applied to a variety of complex systems, ranging from hydrodynamic turbulence to traffic delays and air pollution dynamics. Here, we investigate water quality time series (such as dissolved oxygen concentrations and electrical conductivity) as measured in rivers and provide evidence that they exhibit superstatistical behavior. Our main example is time series as recorded in the River Chess in South East England. Specifically, we use seasonal detrending and empirical mode decomposition to separate trends from fluctuations for the measured data. With either detrending method, we observe heavy-tailed fluctuation distributions, which are well described by log-normal superstatistics for dissolved oxygen. Contrarily, we find a double peaked non-standard superstatistics for the electrical conductivity data, which we model using two combined χ 2 -distributions.

SARS-CoV-2 can recruit a heme metabolite to evade antibody immunity.

The coronaviral spike is the dominant viral antigen and the target of neutralizing antibodies. We show that SARS-CoV-2 spike binds biliverdin and bilirubin, the tetrapyrrole products of heme metabolism, with nanomolar affinity. Using cryo-electron microscopy and x-ray crystallography, we mapped the tetrapyrrole interaction pocket to a deep cleft on the spike N-terminal domain (NTD). At physiological concentrations, biliverdin significantly dampened the reactivity of SARS-CoV-2 spike with immune sera and inhibited a subset of neutralizing antibodies. Access to the tetrapyrrole-sensitive epitope is gated by a flexible loop on the distal face of the NTD. Accompanied by profound conformational changes in the NTD, antibody binding requires relocation of the gating loop, which folds into the cleft vacated by the metabolite. Our results indicate that SARS-CoV-2 spike NTD harbors a dominant epitope, access to which can be controlled by an allosteric mechanism that is regulated through recruitment of a metabolite.

SARS-CoV-2 recruits a haem metabolite to evade antibody immunity.

The coronaviral spike is the dominant viral antigen and the target of neutralizing antibodies. We show that SARS-CoV-2 spike binds biliverdin and bilirubin, the tetrapyrrole products of haem metabolism, with nanomolar affinity. Using cryo-electron microscopy and X-ray crystallography we mapped the tetrapyrrole interaction pocket to a deep cleft on the spike N-terminal domain (NTD). At physiological concentrations, biliverdin significantly dampened the reactivity of SARS-CoV-2 spike with immune sera and inhibited a subset of neutralizing antibodies. Access to the tetrapyrrole-sensitive epitope is gated by a flexible loop on the distal face of the NTD. Accompanied by profound conformational changes in the NTD, antibody binding requires relocation of the gating loop, which folds into the cleft vacated by the metabolite. Our results indicate that the virus co-opts the haem metabolite for the evasion of humoral immunity via allosteric shielding of a sensitive epitope and demonstrate the remarkable structural plasticity of the NTD.

Extracellular Vesicles Derived From Human Corneal Endothelial Cells Inhibit Proliferation of Human Corneal Endothelial Cells.

Corneal endothelial cells (CEnCs) are a monolayer of hexagonal cells that are responsible for maintaining the function and transparency of the cornea. Damage or dysfunction of CEnCs could lead to blindness. Human CEnCs (HCEnCs) have shown limited proliferative capacity in vivo hence, their maintenance is crucial. Extracellular vesicles (EVs) are responsible for inter- and intra-cellular communication, proliferation, cell-differentiation, migration, and many other complex biological processes. Therefore, we investigated the effect of EVs (derived from human corneal endothelial cell line-HCEC-12) on corneal endothelial cells. HCEC-12 cells were starved with serum-depleted media for 72 h. The media was ultracentrifuged at 100,000xg to isolate the EVs. EV counting, characterization, internalization and localization were performed using NanoSight, flow cytometry, Dil labeling and confocal microscopy respectively. HCEC-12 and HCEnCs were cultured with media supplemented with EVs. Extracted EVs showed a homogeneous mixture of exosomes and microvesicles. Cells with EVs decreased the proliferation rate; increased apoptosis and cell size; showed poor wound healing response in vitro and on ex vivo human, porcine, and rabbit CECs. Thirteen miRNAs were found in the EV sample using next generation sequencing. We observed that increased cellular uptake of EVs by CECs limit the proliferative capacity of HCEnCs. These preliminary data may help in understanding the pathology of corneal endothelial dysfunction and provide further insights in the development of future therapeutic treatment options.

Adapting to the Coronavirus Pandemic: Building and Incorporating a Diagnostic Pipeline in a Shared Resource Laboratory.

In March 2020, with lockdown due to the coronavirus pandemic underway, the Francis Crick Institute (the Crick) regeared its research laboratories into clinical testing facilities. Two pipelines were established, one for polymerase chain reaction and the other for Serology. This article discusses the Cricks Flow Cytometry Science Technology Platform (Flow STP) role in setting up the Serology pipeline. Pipeline here referring to the overarching processes in place to facilitate the receipt of human sera through to a SARs-CoV-2 enzyme-linked immunosorbent assay result. We examine the challenges that had to be overcome by a research laboratory to incorporate clinical diagnostics and the processes by which this was achieved. It describes the governance required to run the service, the design of the standard operating procedures (SOPs) and pipeline, the setting up of the assay, the validation required to show the robustness of the pipeline and reporting the results of the assay. Finally, as the lockdown started to ease in June 2020, it examines how this new service affects the daily running of the Flow STP. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals LLC on behalf of International Society for Advancement of Cytometry.

The receptor DNGR-1 signals for phagosomal rupture to promote cross-presentation of dead-cell-associated antigens.

Type 1 conventional dendritic (cDC1) cells are necessary for cross-presentation of many viral and tumor antigens to CD8+ T cells. cDC1 cells can be identified in mice and humans by high expression of DNGR-1 (also known as CLEC9A), a receptor that binds dead-cell debris and facilitates XP of corpse-associated antigens. Here, we show that DNGR-1 is a dedicated XP receptor that signals upon ligand engagement to promote phagosomal rupture. This allows escape of phagosomal contents into the cytosol, where they access the endogenous major histocompatibility complex class I antigen processing pathway. The activity of DNGR-1 maps to its signaling domain, which activates SYK and NADPH oxidase to cause phagosomal damage even when spliced into a heterologous receptor and expressed in heterologous cells. Our data reveal the existence of innate immune receptors that couple ligand binding to endocytic vesicle damage to permit MHC class I antigen presentation of exogenous antigens and to regulate adaptive immunity.

Tracking immunodynamics by identification of S-G2/M-phase T cells in human peripheral blood.

The ready availability of human blood makes it the first choice for immuno-monitoring. However, this has been largely confined to static metrics, particularly resting T cell phenotypes. Conversely, dynamic assessments have mostly relied on cell stimulation in vitro which is subject to multiple variables. Here, immunodynamic insights from the peripheral blood are shown to be obtainable by applying a revised approach to cell-cycle analysis. Specifically, refined flow cytometric protocols were employed, assuring the reliable quantification of T cells in the S-G2/M phases of the cell-cycle (collectively termed "T Double S" for T cells in S-phase in Sanguine: in short "TDS" cells). Without protocol refinement, TDS could be either missed, as most of them layed out of the conventional lymphocyte gates, or confused with cell doublets artefactually displaying high DNA-content. To illustrate the nature of TDS cells, and their relationship to different immunodynamic scenarios, we examined them in healthy donors (HD); infectious mononucleosis (IM) patients versus asymptomatic EBV+ carriers; and recently-diagnosed T1D patients. TDS were reproducibly more abundant among CD8+ T cells and a defined subset of T-regulatory CD4+ T cells, and were substantially increased in IM and a subset of T1D patients. Of note, islet antigen-reactive TDS cell frequencies were associated with an aggressive T cell effector phenotype, suggesting that peripheral blood can reflect immune events within tissues in T1D, and possibly in other organ-specific autoimmune diseases. Our results suggest that tracking TDS cells may provide a widely applicable means of gaining insight into ongoing immune response dynamics in a variety of settings, including tissue immunopathologies where the peripheral blood has often not been considered insightful.

Targeting Extracellular Vesicles to the Arthritic Joint Using a Damaged Cartilage-Specific Antibody.

The targeted delivery of therapies to diseased tissues offers a safe opportunity to achieve optimal efficacy while limiting systemic exposure. These considerations apply to many disease indications but are especially relevant for rheumatoid arthritis (RA), as RA is a systemic autoimmune disease which affects multiple joints. We have identified an antibody that is specific to damaged arthritic cartilage (anti-ROS-CII) that can be used to deliver treatments specifically to arthritic joints, yielding augmented efficacy in experimental arthritis. In the current study, we demonstrate that scaffolds enriched with bioactive payloads can be delivered precisely to an inflamed joint and achieve superior efficacy outcomes consistent with the pharmacological properties of these payloads. As a scaffold, we have used extracellular vesicles (EVs) prepared from human neutrophils (PMNs), which possess intrinsic anti-inflammatory properties and the ability to penetrate inflamed arthritic cartilage. EV fortified with anti-ROS-CII (EV/anti-ROS-CII) retained anti-ROS-CII specificity and bound exclusively to the damaged cartilage. Following systemic administration, EV/anti-ROS-CII (a) exhibited the ability to localize specifically in the arthritic joint in vivo and (b) was able to specifically target single (viral IL-10 or anti-TNF) or combined (viral IL-10 and anti-TNF) anti-inflammatory treatments to the arthritic joint, which accelerated attenuation of clinical and synovial inflammation. Overall, this study demonstrates the attainability of targeting a pro-resolving biological scaffold to the arthritic joint. The potential of targeting scaffolds such as EV, nanoparticles, or a combination thereof alongside combined therapeutics is paramount for designing systemically administered broad-spectrum of anti-inflammatory treatments.

A HIF-LIMD1 negative feedback mechanism mitigates the pro-tumorigenic effects of hypoxia.

The adaptive cellular response to low oxygen tensions is mediated by the hypoxia-inducible factors (HIFs), a family of heterodimeric transcription factors composed of HIF-α and HIF-ß subunits. Prolonged HIF expression is a key contributor to cellular transformation, tumorigenesis and metastasis. As such, HIF degradation under hypoxic conditions is an essential homeostatic and tumour-suppressive mechanism. LIMD1 complexes with PHD2 and VHL in physiological oxygen levels (normoxia) to facilitate proteasomal degradation of the HIF-α subunit. Here, we identify LIMD1 as a HIF-1 target gene, which mediates a previously uncharacterised, negative regulatory feedback mechanism for hypoxic HIF-α degradation by modulating PHD2-LIMD1-VHL complex formation. Hypoxic induction of LIMD1 expression results in increased HIF-α protein degradation, inhibiting HIF-1 target gene expression, tumour growth and vascularisation. Furthermore, we report that copy number variation at the LIMD1 locus occurs in 47.1% of lung adenocarcinoma patients, correlates with enhanced expression of a HIF target gene signature and is a negative prognostic indicator. Taken together, our data open a new field of research into the aetiology, diagnosis and prognosis of LIMD1-negative lung cancers.

Neutrophil Microvesicles from Healthy Control and Rheumatoid Arthritis Patients Prevent the Inflammatory Activation of Macrophages.

Microvesicles (MVs) are emerging as a novel means to enact cell-to-cell communication in inflammation. Here, we aimed to ascertain the ability of neutrophil-derived MVs to modulate target cell behaviour, the focus being the macrophage. MVs were generated in response to tumour necrosis factor-α, from healthy control neutrophils or those from rheumatoid arthritis patients. MVs were used to stimulate human monocyte-derived macrophages in vitro, or administered intra-articularly in the K/BxN mouse model of arthritis. A macrophage/fibroblast-like synoviocyte co-culture system was used to study the effects of vesicles on the crosstalk between these cells. We demonstrate a direct role for phosphatidylserine and annexin-A1 exposed by the MVs to counteract classical activation of the macrophages, and promote the release of transforming growth factor-ß, respectively. Classically-activated macrophages exposed to neutrophil MVs no longer activated fibroblast-like synoviocytes in subsequent co-culture settings. Finally, intra-articular administration of neutrophil MVs from rheumatoid arthritis patients in arthritic mice affected the phenotype of joint macrophages. Altogether these data, with the identification of specific MV determinants, open new opportunities to modulate on-going inflammation in the synovia - mainly by affecting macrophage polarization and potentially also fibroblast-like synoviocytes - through the delivery of autologous or heterologous MVs produced from neutrophils.