IGF1R signalling is a guardian of self-tolerance restricting autoantibody production

Objective: Insulin-like growth factor 1 receptor (IGF1R) acts at the crossroad between immunity and cancer, being an attractive therapeutic target in these areas. IGF1R is broadly expressed by antigen-presenting cells (APC). Using mice immunised with the methylated albumin from bovine serum (BSA-immunised mice) and human CD14+ APCs, we investigated the role that IGF1R plays during adaptive immune responses. Methods: The mBSA-immunised mice were treated with synthetic inhibitor NT157 or short hairpin RNA to inhibit IGF1R signalling, and spleens were analysed by immunohistology and flow cytometry. The levels of autoantibody and cytokine production were measured by microarray or conventional ELISA. The transcriptional profile of CD14+ cells from blood of 55 patients with rheumatoid arthritis (RA) was analysed with RNA-sequencing. Results: Inhibition of IGF1R resulted in perifollicular infiltration of functionally compromised S256-phosphorylated FoxO1+ APCs, and an increased frequency of IgM+CD21+ B cells, which enlarged the marginal zone (MZ). Enlargement of MHCII+CD11b+ APCs ensured favourable conditions for their communication with IgM+ B cells in the MZ. The reduced expression of ICOSL and CXCR5 by APCs after IGF1R inhibition led to impaired T cell control, which resulted in autoreactivity of extra-follicular B cells and autoantibody production. In the clinical setting, the low expression of IGF1R on CD14+ APCs was associated with an involuted FOXO pathway, non-inflammatory cell metabolism and a high IL10 production characteristic for tolerogenic macrophages. Furthermore, autoantibody positivity was associated with low IGF1R signalling in CD14+ APCs. Conclusions: In experimental model and in patient material, this study demonstrates that IGF1R plays an important role in preventing autoimmunity. The study raises awareness of that immune tolerance may be broken during therapeutic IGF1R targeting

Serum-IgG responses to SARS-CoV-2 after mild and severe COVID-19 infection and analysis of IgG non-responders

Background To accurately interpret COVID-19 seroprevalence surveys, knowledge of serum-IgG responses to SARS-CoV-2 with a better understanding of patients who do not seroconvert, is imperative. This study aimed to describe serum-IgG responses to SARS-CoV-2 in a cohort of patients with both severe and mild COVID-19, including extended studies of patients who remained seronegative more than 90 days post symptom onset. Methods SARS-CoV-2-specific IgG antibody levels were quantified using two clinically validated and widely used commercial serological assays (Architect, Abbott Laboratories and iFlash 1800, YHLO), detecting antibodies against the spike and nucleocapsid proteins. Results Forty-seven patients (mean age 49 years, 38% female) were included. All (15/15) patients with severe symptoms and 29/32 (90.6%) patients with mild symptoms of COVID-19 developed SARS-CoV-2-specific IgG antibodies in serum. Time to seroconversion was significantly shorter (median 11 vs. 22 days, P= 0.04) in patients with severe compared to mild symptoms. Of the three patients without detectable IgG-responses after >90 days, all had detectable virus-neutralizing antibodies and in two, spike-protein receptor binding domain-specific IgG was detected with an in-house assay. Antibody titers were preserved during follow-up and all patients who seroconverted, irrespective of the severity of symptoms, still had detectable IgG levels >75 days post symptom onset. Conclusions Patients with severe COVID-19 both seroconvert earlier and develop higher concentrations of SARS-CoV-2-specific IgG than patients with mild symptoms. Of those patients who not develop detectable IgG antibodies, all have detectable virus-neutralizing antibodies, suggesting immunity. Our results showing that not all COVID-19 patients develop detectable IgG using two validated commercial clinical methods, even over time, are vital for the interpretation of COVID-19 seroprevalence surveys

Polζ ablation in B cells impairs the germinal center reaction, class switch recombination, DNA break repair, and genome stability

Polζ is an error-prone DNA polymerase that is critical for embryonic development and maintenance of genome stability. To analyze its suggested role in somatic hypermutation (SHM) and possible contribution to DNA double-strand break (DSB) repair in class switch recombination (CSR), we ablated Rev3, the catalytic subunit of Polζ, selectively in mature B cells in vivo. The frequency of somatic mutation was reduced in the mutant cells but the pattern of SHM was unaffected. Rev3-deficient B cells also exhibited pronounced chromosomal instability and impaired proliferation capacity. Although the data thus argue against a direct role of Polζ in SHM, Polζ deficiency directly interfered with CSR in that activated Rev3-deficient B cells exhibited a reduced efficiency of CSR and an increased frequency of DNA breaks in the immunoglobulin H locus. Based on our results, we suggest a nonredundant role of Polζ in DNA DSB repair through nonhomologous end joining

Single-cell BCR and transcriptome analysis after influenza infection reveals spatiotemporal dynamics of antigen-specific B cells

B cell responses are critical for antiviral immunity. However, a comprehensive picture of antigen-specific B cell differentiation, clonal proliferation, and dynamics in different organs after infection is lacking. Here, by combining single-cell RNA and B cell receptor (BCR) sequencing of antigen-specific cells in lymph nodes, spleen, and lungs after influenza infection in mice, we identify several germinal center (GC) B cell subpopulations and organ-specific differences that persist over the course of the response. We discover transcriptional differences between memory cells in lungs and lymphoid organs and organ-restricted clonal expansion. Remarkably, we find significant clonal overlap between GC-derived memory and plasma cells. By combining BCR-mutational analyses with monoclonal antibody (mAb) expression and affinity measurements, we find that memory B cells are highly diverse and can be selected from both low- and high-affinity precursors. By linking antigen recognition with transcriptional programming, clonal proliferation, and differentiation, these finding provide important advances in our understanding of antiviral immunity

Human marginal zone B cell development from early T2 progenitors.

B cells emerge from the bone marrow as transitional (TS) B cells that differentiate through T1, T2, and T3 stages to become naive B cells. We have identified a bifurcation of human B cell maturation from the T1 stage forming IgMhi and IgMlo developmental trajectories. IgMhi T2 cells have higher expression of α4β7 integrin and lower expression of IL-4 receptor (IL4R) compared with the IgMlo branch and are selectively recruited into gut-associated lymphoid tissue. IgMhi T2 cells also share transcriptomic features with marginal zone B cells (MZBs). Lineage progression from T1 cells to MZBs via an IgMhi trajectory is identified by pseudotime analysis of scRNA-sequencing data. Reduced frequency of IgMhi gut-homing T2 cells is observed in severe SLE and is associated with reduction of MZBs and their putative IgMhi precursors. The collapse of the gut-associated MZB maturational axis in severe SLE affirms its existence in health

Caffeine Abolishes the Ultraviolet-Induced REV3 Translesion Replication Pathway in Mouse Cells

When a replicative DNA polymerase stalls upon encountering a photoproduct on the template strand, it is relieved by other low-processivity polymerase(s), which insert nucleotide(s) opposite the lesion. Using an alkaline sucrose density gradient sedimentation technique, we previously classified this process termed UV-induced translesion replication (UV-TLS) into two types. In human cancer cells or xeroderma pigmentosum variant (XP-V) cells, UV-TLS was inhibited by caffeine or proteasome inhibitors. However, in normal human cells, the process was insensitive to these reagents. Reportedly, in yeast or mammalian cells, REV3 protein (a catalytic subunit of DNA polymerase ζ) is predominantly involved in the former type of TLS. Here, we studied UV-TLS in fibroblasts derived from the Rev3-knockout mouse embryo (Rev3KO-MEF). In the wild-type MEF, UV-TLS was slow (similar to that of human cancer cells or XP-V cells), and was abolished by caffeine or MG-262. In 2 cell lines of Rev3KO-MEF (Rev3−/− p53−/−), UV-TLS was not observed. In p53KO-MEF, which is a strict control for Rev3KO-MEF, the UV-TLS response was similar to that of the wild-type. Introduction of the Rev3 expression plasmid into Rev3KO-MEF restored the UV-TLS response in selected stable transformants. In some transformants, viability to UV was the same as that in the wild-type, and the death rate was increased by caffeine. Our findings indicate that REV3 is predominantly involved in UV-TLS in mouse cells, and that the REV3 translesion pathway is suppressed by caffeine or proteasome inhibitors

A role for gut-associated lymphoid tissue in shaping the human B cell repertoire

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A classification model for distinguishing copy number variants from cancer-related alterations

<p>Abstract</p> <p>Background</p> <p>Both somatic copy number alterations (CNAs) and germline copy number variants (CNVs) that are prevalent in healthy individuals can appear as recurrent changes in comparative genomic hybridization (CGH) analyses of tumors. In order to identify important cancer genes CNAs and CNVs must be distinguished. Although the Database of Genomic Variants (DGV) contains a list of all known CNVs, there is no standard methodology to use the database effectively.</p> <p>Results</p> <p>We develop a prediction model that distinguishes CNVs from CNAs based on the information contained in the DGV and several other variables, including segment's length, height, closeness to a telomere or centromere and occurrence in other patients. The models are fitted on data from glioblastoma and their corresponding normal samples that were collected as part of The Cancer Genome Atlas project and hybridized to Agilent 244 K arrays.</p> <p>Conclusions</p> <p>Using the DGV alone CNVs in the test set can be correctly identified with about 85% accuracy if the outliers are removed before segmentation and with 72% accuracy if the outliers are included, and additional variables improve the prediction by about 2-3% and 12%, respectively. Final models applied to data from ovarian tumors have about 90% accuracy with all the variables and 86% accuracy with the DGV alone.</p