TL1A is an epithelial alarmin that cooperates with IL-33 for initiation of allergic airway inflammation.

Epithelium-derived cytokines or alarmins, such as interleukin-33 (IL-33) and thymic stromal lymphopoietin (TSLP), are major players in type 2 immunity and asthma. Here, we demonstrate that TNF-like ligand 1A (TL1A) is an epithelial alarmin, constitutively expressed in alveolar epithelium at steady state in both mice and humans, which cooperates with IL-33 for early induction of IL-9high ILC2s during the initiation of allergic airway inflammation. Upon synergistic activation by IL-33 and TL1A, lung ILC2s acquire a transient IL-9highGATA3low "ILC9" phenotype and produce prodigious amounts of IL-9. A combination of large-scale proteomic analyses, lung intravital microscopy, and adoptive transfer of ILC9 cells revealed that high IL-9 expression distinguishes a multicytokine-producing state-of-activated ILC2s with an increased capacity to initiate IL-5-dependent allergic airway inflammation. Similar to IL-33 and TSLP, TL1A is expressed in airway basal cells in healthy and asthmatic human lungs. Together, these results indicate that TL1A is an epithelium-derived cytokine and an important cofactor of IL-33 in the airways.

Nasal vaccines for pertussis.

Whooping cough, caused by Bordetella pertussis, is still a major cause of morbidity and mortality worldwide. Current acellular pertussis (aP) vaccines induce potent circulating IgG and prevent severe disease in children/adults and in infants born to vaccinated mothers. However, they do not prevent nasal infection, allowing asymptomatic transmission of B. pertussis. Studies in animal models have demonstrated that, unlike natural infection, immunization with aP vaccines fails to induce secretory immunoglobulin A (IgA) or interleukin-17 (IL-17)-secreting tissue-resident memory CD4 T (TRM) cells, required for sustained sterilizing immunity in the nasal mucosa. Live-attenuated vaccines or aP vaccines formulated with novel adjuvants that induce respiratory IgA and TRM cells, especially when delivered by the nasal route, are in development and have considerable promise as next-generation vaccines against pertussis.

Intranasal COVID-19 vaccine induces respiratory memory T cells and protects K18-hACE mice against SARS-CoV-2 infection.

Current COVID-19 vaccines prevent severe disease, but do not induce mucosal immunity or prevent infection with SARS-CoV-2, especially with recent variants. Furthermore, serum antibody responses wane soon after immunization. We assessed the immunogenicity and protective efficacy of an experimental COVID-19 vaccine based on the SARS-CoV-2 Spike trimer formulated with a novel adjuvant LP-GMP, comprising TLR2 and STING agonists. We demonstrated that immunization of mice twice by the intranasal (i.n.) route or by heterologous intramuscular (i.m.) prime and i.n. boost with the Spike-LP-GMP vaccine generated potent Spike-specific IgG, IgA and tissue-resident memory (TRM) T cells in the lungs and nasal mucosa that persisted for at least 3 months. Furthermore, Spike-LP-GMP vaccine delivered by i.n./i.n., i.m./i.n., or i.m./i.m. routes protected human ACE-2 transgenic mice against respiratory infection and COVID-19-like disease following lethal challenge with ancestral or Delta strains of SARS-CoV-2. Our findings underscore the potential for nasal vaccines in preventing infection with SARS-CoV-2 and other respiratory pathogen.

GReNaDIne: A Data-Driven Python Library to Infer Gene Regulatory Networks from Gene Expression Data.

Context: Inferring gene regulatory networks (GRN) from high-throughput gene expression data is a challenging task for which different strategies have been developed. Nevertheless, no ever-winning method exists, and each method has its advantages, intrinsic biases, and application domains. Thus, in order to analyze a dataset, users should be able to test different techniques and choose the most appropriate one. This step can be particularly difficult and time consuming, since most methods' implementations are made available independently, possibly in different programming languages. The implementation of an open-source library containing different inference methods within a common framework is expected to be a valuable toolkit for the systems biology community. Results: In this work, we introduce GReNaDIne (Gene Regulatory Network Data-driven Inference), a Python package that implements 18 machine learning data-driven gene regulatory network inference methods. It also includes eight generalist preprocessing techniques, suitable for both RNA-seq and microarray dataset analysis, as well as four normalization techniques dedicated to RNA-seq. In addition, this package implements the possibility to combine the results of different inference tools to form robust and efficient ensembles. This package has been successfully assessed under the DREAM5 challenge benchmark dataset. The open-source GReNaDIne Python package is made freely available in a dedicated GitLab repository, as well as in the official third-party software repository PyPI Python Package Index. The latest documentation on the GReNaDIne library is also available at Read the Docs, an open-source software documentation hosting platform. Contribution: The GReNaDIne tool represents a technological contribution to the field of systems biology. This package can be used to infer gene regulatory networks from high-throughput gene expression data using different algorithms within the same framework. In order to analyze their datasets, users can apply a battery of preprocessing and postprocessing tools and choose the most adapted inference method from the GReNaDIne library and even combine the output of different methods to obtain more robust results. The results format provided by GReNaDIne is compatible with well-known complementary refinement tools such as PYSCENIC.

Extent of intrinsic disorder and NMR chemical shift assignments of the distal N-termini from human TRPV1, TRPV2 and TRPV3 ion channels.

The mammalian Transient Receptor Potential Vanilloid (TRPV) channels are a family of six tetrameric ion channels localized at the plasma membrane. The group I members of the family, TRPV1 through TRPV4, are heat-activated and exhibit remarkable polymodality. The distal N-termini of group I TRPV channels contain large intrinsically disordered regions (IDRs), ranging from ~ 75 amino acids (TRPV2) to ~ 150 amino acids (TRPV4), the vast majority of which is invisible in the structural models published so far. These IDRs provide important binding sites for cytosolic partners, and their deletion is detrimental to channel activity and regulation. Recently, we reported the NMR backbone assignments of the distal TRPV4 N-terminus and noticed some discrepancies between the extent of disorder predicted solely based on protein sequence and from experimentally determined chemical shifts. Thus, for an analysis of the extent of disorder in the distal N-termini of all group I TRPV channels, we now report the NMR assignments for the human TRPV1, TRPV2 and TRPV3 IDRs.

[Interleukin-33: from biology to potential treatments]. / L'interleukine 33 - De la biologie aux implications thérapeutiques.

Interleukin-33 is a member of the IL-1 cytokine family, expressed in the nucleus of endothelial cells and epithelial cells of barrier tissues. After cellular damage, IL-33 is released in the extracellular space and functions as an alarmin that alerts the immune system. IL-33 plays a critical role in type-2 innate immunity and allergic inflammation, by activating various target cells including mast cells and innate lymphoid cells that secrete high amounts of IL-5 and IL-13, two cytokines involved in allergic reactions. Recent studies suggest that IL-33 can also play other important roles, for example in homeostasis and during viral infection. It is implicated in numerous diseases, including allergic, inflammatory and infectious diseases and it constitutes a promising therapeutic target for treatment of severe asthma.

Environmental allergens induce allergic inflammation through proteolytic maturation of IL-33.

Allergic inflammation has crucial roles in allergic diseases such as asthma. It is therefore important to understand why and how the immune system responds to allergens. Here we found that full-length interleukin 33 (IL-33FL), an alarmin cytokine with critical roles in type 2 immunity and asthma, functioned as a protease sensor that detected proteolytic activities associated with various environmental allergens across four kingdoms, including fungi, house dust mites, bacteria and pollens. When exposed to allergen proteases, IL-33FL was rapidly cleaved in its central 'sensor' domain, which led to activation of the production of type 2 cytokines in group 2 innate lymphoid cells. Preventing cleavage of IL-33FL reduced allergic airway inflammation. Our findings reveal a molecular mechanism for the rapid induction of allergic type 2 inflammation following allergen exposure, with important implications for allergic diseases.

Isolation and Culture of Mouse Lung ILC2s.

Group 2 Innate Lymphoid Cells (ILC2) play an important role in immune responses at barrier surfaces, notably in the lung during airway allergic inflammation or asthma. Several studies have described methods to isolate ILC2s from wild-type naive mice, most of them using cell sorting to obtain a pure population. Here, we describe in detail, a simple, efficient method for isolation and culture of lung mouse ILC2s. Lungs from Rag2-/- mice pretreated with IL-33 are collected and processed into single cell suspensions. Lymphoid cells are then recovered by density gradient separation. Lin-CD45+ cells are selected by depletion of lineage positive cells followed by positive selection of CD45+ cells. Culture of the isolated cells for several days results in a highly purified ILC2 population expressing typical cell surface markers (CD90.2, Sca1, CD25, CD127, and IL-33R). These cells can be expanded in culture for up to 10 days and used for diverse ex vivo assays or in vivo adoptive transfer experiments.