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Only limited data are available regarding the immunogenicity of the BNT162b2 mRNA vaccine in HIV-1+ patients. Therefore, we investigated the humoral immune response after BNT162b2-mRNA vaccination or SARS-CoV-2 infection in HIV-1+ patients on antiretroviral therapy compared to HIV-1-uninfected subjects. Serum and saliva samples were analysed by SARS-CoV-2 spike-specific IgG and IgA ELISAs and a surrogate neutralization assay. While all subjects developed anti-spike IgG and IgA and neutralizing antibodies in serum after two doses of BNT162b2 mRNA vaccine, the HIV-1+ subjects displayed significantly lower neutralizing capacity and anti-spike IgA in serum compared to HIV-1-uninfected subjects. Serum levels of anti-spike IgG and neutralizing activity were significantly higher in vaccinees compared to SARS-CoV-2 convalescents irrespective of HIV-1 status. Among SARS-CoV-2 convalescents, there was no significant difference in spike-specific antibody response between HIV-1+ and uninfected subjects. In saliva, anti-spike IgG and IgA antibodies were detected both in vaccinees and convalescents, albeit at lower frequencies compared to the serum and only rarely with detectable neutralizing activity. In summary, our study demonstrates that the BNT162b2 mRNA vaccine induces SARS-CoV-2-specific antibodies in HIV-1-infected patients on antiretroviral therapy, however, lower vaccine induced neutralization activity indicates a lower functionality of the humoral vaccine response in HIV-1+ patients.

The beta-coronavirus SARS-CoV-2 induces severe disease (COVID-19) mainly in elderly persons with risk factors, whereas the majority of patients experience a mild course of infection. As the circulating common cold coronaviruses OC43 and HKU1 share some homologous sequences with SARS-CoV-2, beta-coronavirus cross-reactive T-cell responses could influence the susceptibility to SARS-CoV-2 infection and the course of COVID-19. To investigate the role of beta-coronavirus cross-reactive T-cells, we analyzed the T-cell response against a 15 amino acid long peptide (SCoV-DP15: DLSPRWYFYYLGTGP) from the SARS-CoV-2 nucleoprotein sequence with a high homology to the corresponding sequence (QLLPRWYFYYLGTGP) in OC43 and HKU1. SCoV-DP15-specific T-cells were detected in 4 out of 23 (17.4%) SARS-CoV-2-seronegative healthy donors. As HIV-1 infection is a potential risk factor for COVID-19, we also studied a cohort of HIV-1-infected patients on antiretroviral therapy. 44 out of these 116 HIV-1-infected patients (37.9%) showed a specific recognition of the SCoV-DP15 peptide or of shorter peptides within SCoV-DP15 by CD4 + T-cells and/or by CD8 + T-cells. We could define several new cross-reactive HLA-I-restricted epitopes in the SARS-CoV-2 nucleoprotein such as SPRWYFYYL (HLA-B*07, HLA-B*35), DLSPRWYFYY (HLA-A*02), LSPRWYFYY (HLA-A*29), WYFYYLGTGP and WYFYYLGT. Epitope specific CD8 + T-cell lines recognized corresponding epitopes within OC43 and HKU1 to a similar degree or even at lower peptide concentrations suggesting that they were induced by infection with OC43 or HKU1. Our results confirm that SARS-CoV-2-seronegative subjects can target SARS-CoV-2 not only by beta-coronavirus cross-reactive CD4 + T-cells but also by cross-reactive CD8 + cytotoxic T-cells (CTL). The delineation of cross-reactive T-cell epitopes contributes to an efficient epitope-specific immunomonitoring of SARS-CoV-2-specific T-cells. Further prospective studies are needed to prove a protective role of cross-reactive T-cells and their restricting HLA alleles for control of SARS-CoV-2 infection. The frequent observation of SARS-CoV-2-reactive T-cells in HIV-1-infected subjects could be a reason that treated HIV-1 infection does not seem to be a strong risk factor for the development of severe COVID-19.

Inflammatory arthritis, including rheumatoid arthritis and psoriatic arthritis, is characterized by physical function impairment. This becomes apparent even before arthritis onset, as in psoriasis (PsO). Chronic inflammation triggers an accelerated remodeling of the extracellular matrix (ECM), resulting in released ECM fragments detectable in blood. We aimed to investigate levels of blood-based ECM biomarkers in patients with RA, PsA, PsO, and healthy controls and to explore the association of ECM biomarkers with hand function impairments. Patients with RA (n = 85), PsA (n = 115), PsO (n = 102) and controls (n = 110) were included in this cross-sectional study. ECM catabolic (C1M, C2M, C3M, C4M, PRO-C4, C6M, ARG), formation (PRO-C1, PRO-C3, PRO-C6) and inflammation biomarkers (VICM) were measured in serum from all patients. Objective hand function (fine motor skills (Moberg-Picking-Up Test), isometric grip strength (dynamometer) and patient-perceived hand function (Michigan Hand Questionnaire (MHQ)) were assessed. Patients with RA and PsA received treatment with disease-modifying anti-rheumatic drugs. VICM levels were higher in RA, PsA, and PsO than in controls (p < 0.0001). PsA and PsO showed higher C4M levels compared to controls (p < 0.0001, p < 0.0001), while C6M was lower in patients with RA, PsA and PsO than in controls (p < 0.0001, p < 0.001, p < 0.01). PsO presented with higher levels of C1M compared to controls and to RA (p < 0.001 and p < 0.0001). PRO-C6 correlated negatively with MHQ ( ρ  = -0.39, p < 0.01) and grip strength (ρ  = -0.31, p < 0.05) in PsO, while only weak correlations were observed between biomarkers and hand function scores for RA and PsA patients (all ρ  <  ± 0.2–0.3). Patients with RA, PsA, and PsO showed significant alterations in ECM remodeling biomarkers. Especially PsA and PsO had higher levels of inflammatory biomarkers compared to RA and controls, likely due to modulation by treatment. Predominantly in PsO, ECM formation biomarkers were associated with hand function impairments.

Background Glycosylation is an important posttranslational modification of proteins and in most cases indispensable for proper protein function. Like most soluble proteins, IgA, the second most prevalent antibody in human serum, contains several N- and O-glycosylation sites. While for IgG the impact of Fc glycosylation on effector functions and inflammatory potential has been studied intensively, only little is known for IgA. In addition, only glimpses exist regarding the regulation of IgA glycosylation. We have previously shown that IgA1 and IgA2 differ functionally and also show differences in their glycosylation pattern. The more pro-inflammatory IgA2 which is linked to autoimmune diseases displays decreased sialylation, galactosylation, fucosylation and bisection as compared to IgA1. In the present study, we aimed to investigate these differences in glycosylation in detail and to explore the mechanisms underlying them. Methods IgA1 and IgA2 was isolated from serum of 12 healthy donors. Site specific glycosylation was analyzed by mass spectrometry. In addition, human bone marrow plasma cells were investigated using single cell mRNA sequencing, flow cytometry and ELISpot. Results We found that certain glycoforms greatly differ in their abundance between IgA1 and IgA2 while others are equally abundant. Overall, the IgA2 glycans displayed a more immature phenotype with a higher prevalence of oligomannose and fewer fully processed glycans. Of note, these differences can’t be explained by differences in the glycosylation enzyme machinery as mRNA sequencing and flow cytometry analysis showed equal enzyme expression in IgA1 and IgA2 producing plasma cells. ELISpot analysis suggested a slightly increased antibody production rate in IgA2 producing plasma cells which might contribute to its lower glycan processing rates. But this difference was only minor, suggesting that further factors such as steric accessibility determine glycan processing. This is supported by the fact that glycans at different positions on the same IgA chain differ dramatically in fucosylation, sialylation and bisection. Conclusion In summary, our detailed overview of IgA1 and IgA2 glycosylation shows a class, subclass, and site-specific glycosylation fingerprint, most likely due to structural differences of the protein backbones.

The analysis of T-cell responses in HIV-1-infected controllers may contribute to a better understanding of the protective components of the immune system. Here, we analyzed the HIV-1-specific T-cell response in a 59-year-old HIV-1-infected controller, infected for at least seven years, who presented with low viral loads ranging from <20 copies/mL to 200 copies/mL and normal CD4 counts of >800 cells/µL. In γ-IFN-ELISpot assays using freshly isolated PBMCs, he displayed a very strong polyclonal T-cell response to eight epitopes in Gag, Nef and Rev; with the dominant responses directed against the HLA-B*57-epitope AISPRTLNAW and against a so-far-unknown epitope within Rev. Further analyses using peptide-stimulated T-cell lines in γ-IFN-ELISpot assays delineated the peptide RQRQIRSI (Rev-RI8) as a newly defined HLA-B*52-restricted epitope located within a functionally important region of Rev. Peptide-stimulation assays in 15 HLA-B*52-positive HIV-1-infected subjects, including the controller, demonstrated recognition of the Rev-RI8 epitope in 6/15 subjects. CD4 counts before the start of antiviral therapy were significantly higher in subjects with recognition of the Rev-RI8 epitope. Targeting of the Rev-RI8 epitope in Rev by CTL could contribute to the positive association of HLA-B*52 with a more favorable course of HIV-1-infection.

Purpose The Ad26.COV2.S vaccine is a replication-incompetent human adenovirus type 26 vector encoding the SARS-CoV-2 spike protein. In a phase 1-2a trial, a single dose of Ad26.COV2.S induced SARS-CoV-2 spike-specific antibodies in ≥ 96% of healthy adults. To investigate vaccine immunogenicity in HIV-1-infection, we measured SARS-CoV-2 spike-specific antibodies in Ad26.COV2.S vaccinated HIV-1-infected patients and analyzed the presence of pre-existing Ad26 neutralizing antibodies. Methods We included all Ad26.COV2.S vaccinated HIV-1-infected patients of Erlangen HIV cohort fulfilling all inclusion criteria. The study cohort consisted of 15 HIV-1-infected patients and three HIV-1-uninfected subjects who received the Ad26.COV2.S vaccine between April and November 2021. Pre-vaccination sera were collected between October 2014 and June 2021, post-vaccination sera between June and December 2021. Neutralizing antibodies towards Ad26 were determined by a FACS-based inhibition assay measuring the expression of SARS-CoV-2 spike and adenoviral proteins in HEK293T cells after in-vitro transduction with Ad26.COV2.S or the control ChAdOx1-S. Results Six out of 15 HIV-1-infected patients failed to develop SARS-CoV-2-specific antibodies and four patients developed weak antibody responses after vaccination with Ad26.COV2.S. Pre-vaccination sera of four of the six vaccine non-responders showed neutralizing activity towards Ad26.COV2.S but not toward the ChAdOx1-S vaccine at 1:50 dilution. After Ad26.COV2.S vaccination, 17 of the 18 subjects developed strong Ad26-neutralizing activity and only one of the 18 subjects showed neutralizing activity towards the ChAdOx1-S vaccine. Conclusion Ad26.COV2.S vaccination showed a high failure rate in HIV-1-infected patients. Pre-existing immunity against Ad26 could be an important contributor to poor vaccine efficacy in a subgroup of patients.

Background: Glycosylation is an important posttranslational modification of proteins and in most cases indispensable for proper protein function. Like most soluble proteins, IgA, the second most prevalent antibody in human serum, contains several N- and O-glycosylation sites. While for IgG the impact of Fc glycosylation on effector functions and inflammatory potential has been intensively studied, only little is known for IgA. In addition, only glimpses exist regarding the regulation of IgA glycosylation. We have previously shown that IgA1 and IgA2 differ functionally and also show differences in their glycosylation pattern. The more pro-inflammatory IgA2 which is linked to autoimmune diseases displays decreased sialylation, galactosylation, fucosylation and bisection as compared to IgA1. In the present study, we aimed to investigate these differences in glycosylation in detail and to explore the mechanisms underlying them. Methods: IgA1 and IgA2 was isolated from serum of 12 healthy donors. Site specific glycosylation was analyzed by mass spectrometry. In addition, human bone marrow plasma cells were investigated using single cell mRNA sequencing, flow cytometry and ELISpot. Results: We found that certain glycoforms greatly differ in their abundance between IgA1 and IgA2 while others are equally abundant. Overall, the IgA2 glycans displayed a more immature phenotype with a higher prevalence of oligomannose and fewer fully processed glycans. Of note, these differences cannot be explained by differences in the glycosylation enzyme machinery as mRNA sequencing and flow cytometry analysis showed equal enzyme expression in IgA1 and IgA2 producing plasma cells. ELISpot analysis suggested a slightly increased antibody production rate in IgA2 producing plasma cells which might contribute to its lower glycan processing rates. But this difference was only minor, suggesting that further factors such as steric accessibility determine glycan processing. This is supported by the fact that glycans at different positions on the same IgA chain differ dramatically in fucosylation, sialylation and bisection. Conclusion: In summary, our detailed overview of IgA1 and IgA2 glycosylation shows a class, subclass, and site-specific glycosylation fingerprint, most likely due to structural differences of the protein backbones.Competing Interest StatementThe authors have declared no competing interest.Footnotes* https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE282272

Rat bite fever (RBF) is a zoonotic disease caused primarily by Streptobacillus ( S .) moniliformis . Norway or brown rats ( Rattus [ R. ] norvegicus ) are the natural host for S. moniliformis and carry the bacterium in the nasopharynx without clinical disease. Transmission to humans often occurs through rat bites or scratches, but also through contact with the excreta of infected rats. Although human infections with S. moniliformis occur worldwide, they are rarely diagnosed. For decades, S. moniliformis was the only known member of the genus Streptobacillus . In recent years, however, four additional species were identified, two of which being zoonotic pathogens capable of causing symptoms identical to RBF in humans. The aim of this study was to develop a serological assay covering all known Streptobacillus species. A bead-based multiplex fluorescence immunoassay for S. moniliformis detection has been used for years in routine diagnostics of laboratory rodents. Here, this assay was adapted to enable the detection of antibodies against all currently known Streptobacillus species and tested with sera from experimentally inoculated mice and rats, and with negative sera from laboratory rodents. Using this assay, we broadly examined the prevalence of Streptobacillus spp. reactive antibodies in wild rodents. Transudates from a total of 107 Norway rats, 81 black or roof rats ( Rattus rattus ) and 110 house mice ( Mus musculus ) from different husbandries and wildlife populations within Germany were tested. Antibody prevalences of 41% in R. norvegicus and 83% in R. rattus suggest that Streptobacillus spp. are widespread in wild and captive rats in Germany, whereas wild mice seem to be free of infection. Due to its high throughput capacity and multiplex format, the Streptobacillus multiplex serology is well suited for large seroprevalence studies in rodents and has the potential, after adaptation, for use in humans, thereby allowing for the assessment of Streptobacillus infection risk and risk of RBF.

BackgroundThe optimal surgical approach for adenocarcinoma directly at the esophagogastric junction (AEG II) is still under debate. This study aims to evaluate the differences between right thoracoabdominal esophagectomy (TAE) (Ivor–Lewis operation) and transhiatal extended gastrectomy (THG) for AEG II.MethodsFrom a prospective database, 242 patients with AEG II (TAE, n = 56; THG, n = 186) were included and analyzed according to characteristics and perioperative morbidity and mortality and overall survival (chi-square, Mann–Whitney U, log-rank, Cox regression).ResultsGroups were comparable at baseline with exception of age. Patients older than 70 years were more frequently resected by THG (p = 0.003). No differences in perioperative morbidity (p = 0.197) and mortality (p = 0.711) were observed, including anastomotic leakages (p = 0.625) and pulmonary complications (p = 0.494). There was no significant difference in R0 resection (p = 0.719) and number of resected lymph nodes (p = 0.202). Overall median survival was 38.4 months. Survival after TAE was significantly longer than after THG (median OS not reached versus 33.6 months, p = 0.02). Multivariate analysis revealed pN-category (p < 0.001) and type of surgery (p = 0.017) as independent prognostic factors. The type of surgery was confirmed as prognostic factor in locally advanced AEG II (cT 3/4 or cN1), but not in cT1/2 and cN0 patients.ConclusionsOur single-center experience suggests that patients with (locally advanced) AEG II tumors may benefit from TAE compared to THG. For further evaluation, a randomized trial would be necessary.

Recognition that evolution operates on the same timescale as ecological processes has motivated growing interest in eco-evolutionary dynamics. Nonetheless, generating sufficient data to test predictions about eco-evolutionary dynamics has proved challenging, particularly in natural contexts. Here we argue that genomic data can be integrated into the study of eco-evolutionary dynamics in ways that deepen our understanding of the interplay between ecology and evolution. Specifically, we outline five major questions in the study of eco-evolutionary dynamics for which genomic data may provide answers. Although genomic data alone will not be sufficient to resolve these challenges, integrating genomic data can provide a more mechanistic understanding of the causes of phenotypic change, help elucidate the mechanisms driving eco-evolutionary dynamics, and lead to more accurate evolutionary predictions of eco-evolutionary dynamics in nature. Studying eco-evolutionary dynamics in nature is challenging. In this Perspective, the authors discuss how genomic data can be used to understand the mechanisms behind eco-evolutionary dynamics and lead to evolutionary and ecological predictions in nature.