Biology subjects

Abrignani, S.

Publications and source records attributed to Abrignani, S..

6 recordsLinked to original sources

bioRxiv2024

Autosomal Dominant-Hyper-IgE Syndrome patients contain pre-Th17-cells that are activated by opportunistic pathogens to produce IL-10

BackgroundAutosomal Dominant-Hyper-IgE Syndrome (AD-HIES) is caused by dominant-negative (DN) STAT3 mutations and characterized by high IgE levels, a lack of Th17-cells and recurrent infections with extracellular pathogens. We previously identified an enigmatic population of IL-10 producing CCR6+B-helper T-cells and investigated here their relationship to Th17-cells and STAT3 signalling requirements. MethodsHuman blood lymphocytes were analysed by multiparametric flow cytometry in healthy donors and AD-HIES patients. Analysis was performed by conventional gating or with bioinformatic tools. FACS-purified T-cell subsets were activated in vitro and Th17 differentiation assessed. T-cell antigen specificities were assessed by activation with heat-killed pathogens or antigenic peptide pools. B helper capacities were determined according to antibody secretion in B-T co-cultures by ELISA. ResultsCCR6+Th-cells that lacked subset-defining differentiation markers were mostly non-polarised central memory T-cells (TCM) that produced IL-10 and expressed ROR{gamma}t. They were pre-committed to a Th17 fate, since TCR stimulation in the absence of polarising cytokines induced efficient Th17 differentiation. The latter was promoted by an autocrine loop of STAT3-activating cytokines. CCR6+Th-cells were reduced in patients with DN-STAT3 mutations but contained activated CCR6+TCM that produced IL-10 and responded vigorously to AD-HIES-associated pathogens. These residual CCR6+Th-cells provided B-cell help for IgG and IgE production. ConclusionsTh17 differentiation in AD-HIES patients was not completely impaired but arrested at an intermediate stage of IL-10 producing "pre-Th17"-cells. Surprisingly, DN-STAT3 mutations did not inhibit IL-10 production by CD4+T-cells. Pre-Th17-cells were activated by AD-HIES-associated pathogens and possessed B-helper functions, suggesting that they are not protective but promote aberrant IgE production.

immunology↗

bioRxiv2024

Regulatory T-cells in multiple sclerosis are activated by Epstein-Barr Virus and produce IL-10 in the central nervous system

Regulatory T-cells (Tregs) maintain immune homeostasis, but antigens activating adaptive Tregs in human pathologies are ill-defined. EOMES+type-1 regulatory (Tr1)-like T-cells had a dysregulated homeostasis in multiple sclerosis (MS), which was related to their activation in the central nervous system (CNS). EOMES+Tr1-like cells were enriched and clonally expanded in patients cerebrospinal fluid (CSF) and were the major IL-10-producing T-cell subset in the CNS. Regulatory T-cells from PwMS produced IL-10 and IFN-{gamma} with antigens derived from Epstein-Barr Virus (EBV), but not from myelin. EOMES+Tr1-like cells responded selectively to the latency-associated antigen EBNA1, whereas FOXP3+Tregs and Th1-cells responded also to lytic EBV antigens. EBNA1-specific EOMES+Tr1-like cells were present in patients carrying the HLA-DRB1*15:01 risk allele, were associated with anti-EBNA1 IgG and disappeared upon therapeutic B-cell depletion. IL-10+EOMES+Tr1-like were present in MS brain lesions, and some were in the vicinity of EBV-infected B-cells and CD8+T-cells. Notably, EOMES+Tr1-like cells suppressed CD8+T-cell activation by EBV-infected B-cells. We propose that the insufficient protective functions of Tregs in MS are due to their aberrant anti-viral specificities that promote immune escape of a disease-associated virus.

immunology↗

bioRxiv2023

CIA: a Cluster Independent Annotation method to investigate cell identities in scRNA-seq data

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of the transcriptional landscape of complex tissues, enabling the discovery of novel cell types and biological functions. However, the identification and classification of cells from scRNA-seq datasets remain significant challenges. To address this, we developed a new computational tool called CIA (Cluster Independent Annotation), which accurately identifies cell types across different datasets without requiring a fully annotated reference dataset or complex machine learning processes. Based on predefined cell type signatures, CIA provides a highly user-friendly and practical solution to functional annotation of single cells. Our results demonstrate that CIA outperforms other state-of-the-art approaches, while also having significantly lower computational running time. Overall, CIA simplifies the process of obtaining reproducible signature-based cell assignments that can be easily interpreted through graphical summaries providing researchers with a powerful tool to explore the complex transcriptional landscape of single cells. The CIA framework is implemented in both the Python and R programming languages, making it applicable to all main single-cell analysis frameworks, and it is available under the MIT license with its documentation at the following links: Python package: https://pypi.org/project/cia-python/ Python tutorial: https://cia-python.readthedocs.io/en/latest/tutorial/Cluster_Independent_Annotation.html R package and tutorial: https://github.com/ingmbioinfo/CIA_R

bioinformatics↗

bioRxiv2022

Combinatorial selection of biomarkers to optimize gene signatures in diagnostics and single cell applications

Here we present the combiroc R package, for signatures refinement in high throughput omics. Based on a ROC-driven marker selection, it can be used to find powerful smaller sub-signatures from scRNAseq experiments and to annotate cells using fewer markers. Trained on PBMC dataset, combiroc found NK marker combinations with high cell-discriminating power, in agreement with human protein atlas and that were validated both computationally and experimentally on independent datasets.

bioinformatics↗

bioRxiv2021

Maturation signatures of conventional dendritic cells in COVID-19 reflect direct viral sensing

Growing evidence suggests that conventional dendritic cells (cDCs) undergo aberrant maturation in COVID-19 and this negatively affects T cell activation. The presence of functional effector T cells in mild patients and dysfunctional T cells in severely ill patients suggests that adequate T cell responses are needed to limit disease severity. Therefore, understanding how cDCs cope with SARS-CoV-2 infections can help elucidate the mechanism of generation of protective immune responses. Here, we report that cDC2 subtypes exhibit similar infection-induced gene signatures with the up-regulation of interferon-stimulated genes and IL-6 signaling pathways. The main difference observed between DC2s and DC3s is the up-regulation of anti-apoptotic genes in DC3s, which explains their accumulation during infection. Furthermore, comparing cDCs between severe and mild patients, we find in the former a profound down-regulation of genes encoding molecules involved in antigen presentation, such as major histocompatibility complex class II (MHCII) molecules, {beta}2 microglobulin, TAP and costimulatory proteins, while an opposite trend is observed for proinflammatory molecules, such as complement and coagulation factors. Therefore, as the severity of the disease increases, cDC2s enhance their inflammatory properties and lose their main function, which is the antigen presentation capacity. In vitro, direct exposure of cDC2s to the virus recapitulates the type of activation observed in vivo. Our findings provide evidence that SARS-CoV-2 can interact directly with cDC2s and, by inducing the down-regulation of crucial molecules required for T cell activation, implements an efficient immune escape mechanism that correlates with disease severity.

immunology↗

bioRxiv2019

The Endless Frontier? The Recent Upsurge of R&D Productivity in Pharmaceuticals

Analyses of pharmaceutical pipelines of drug development in the 1990-2010 documented progressively increasing attrition rates and duration of clinical trials, leading to a diffuse perception of a \"productivity crisis\". We produced a new set of analyses for the last decade, using an extensive data of more than 45,000 projects between 1990 and 2017, and report a recent upsurge of R&D productivity within the industry. First, we investigated how R&D projects are allocated across therapeutic areas and found a polarization towards high-risk/high-reward indications, with a strong focus on oncology. Importantly, attrition rates have been decreasing at all clinical stages in recent years. In parallel, we observed an increase of early failures in preclinical research, and a significant reduction of time required to identify projects to be discontinued. Notably, more recent projects are increasingly based on novel mechanisms of action and target indications with small patient populations. Finally, by analyses of the relative contribution of different institutional types and development companies, we show that the observed increased performance in clinical trials is mostly due to the contribution of biotech-nological companies, while pharmaceutical companies have significantly improved their performances in identifying false positives in preclinical research.

pharmacology and toxicology↗