Diversification of the VH3-53 immunoglobulin gene segment by somatic hypermutation results in neutralization of SARS-CoV-2 virus variants.

COVID-19 induces re-circulating long-lived memory B cells (MBC) that, upon re-encounter with the pathogen, are induced to mount immunoglobulin responses. During convalescence, antibodies are subjected to affinity maturation, which enhances the antibody binding strength and generates new specificities that neutralize virus variants. Here, we performed a single-cell RNA sequencing analysis of spike-specific B cells from a SARS-CoV-2 convalescent subject. After COVID-19 vaccination, matured infection-induced MBC underwent recall and differentiated into plasmablasts. Furthermore, the transcriptomic profiles of newly activated B cells transiently shifted toward the ones of atypical and CXCR3+ B cells and several B-cell clonotypes massively expanded. We expressed monoclonal antibodies (mAbs) from all B-cell clones from the largest clonotype that used the VH3-53 gene segment. The in vitro analysis revealed that some somatic hypermutations enhanced the neutralization breadth of mAbs in a putatively stochastic manner. Thus, somatic hypermutation of B-cell clonotypes generates an anticipatory memory that can neutralize new virus variants.

Structures and Dynamics of Complex Guest Molecules in Confinement, Revealed by Solid-State NMR, Molecular Dynamics, and Calorimetry.

This review gives an overview of current trends in the investigation of confined molecules such as water, small and higher alcohols, carbonic acids, ethylene glycol, and non-ionic surfactants, such as polyethylene glycol or Triton-X, as guest molecules in neat and functionalized mesoporous silica materials employing solid-state NMR spectroscopy, supported by calorimetry and molecular dynamics simulations. The combination of steric interactions, hydrogen bonds, and hydrophobic and hydrophilic interactions results in a fascinating phase behavior in the confinement. Combining solid-state NMR and relaxometry, DNP hyperpolarization, molecular dynamics simulations, and general physicochemical techniques, it is possible to monitor these confined molecules and gain deep insights into this phase behavior and the underlying molecular arrangements. In many cases, the competition between hydrogen bonding and electrostatic interactions between polar and non-polar moieties of the guests and the host leads to the formation of ordered structures, despite the cramped surroundings inside the pores.

Phosphatidylserine-exposing extracellular vesicles in body fluids are an innate defence against apoptotic mimicry viral pathogens.

Some viruses are rarely transmitted orally or sexually despite their presence in saliva, breast milk, or semen. We previously identified that extracellular vesicles (EVs) in semen and saliva inhibit Zika virus infection. However, the antiviral spectrum and underlying mechanism remained unclear. Here we applied lipidomics and flow cytometry to show that these EVs expose phosphatidylserine (PS). By blocking PS receptors, targeted by Zika virus in the process of apoptotic mimicry, they interfere with viral attachment and entry. Consequently, physiological concentrations of EVs applied in vitro efficiently inhibited infection by apoptotic mimicry dengue, West Nile, Chikungunya, Ebola and vesicular stomatitis viruses, but not severe acute respiratory syndrome coronavirus 2, human immunodeficiency virus 1, hepatitis C virus and herpesviruses that use other entry receptors. Our results identify the role of PS-rich EVs in body fluids in innate defence against infection via viral apoptotic mimicries, explaining why these viruses are primarily transmitted via PS-EV-deficient blood or blood-ingesting arthropods rather than direct human-to-human contact.

Cytoskeletal ß-tubulin and cysteine cathepsin L deregulation by SARS-CoV-2 spike protein interaction with the neuronal model cell line SH-SY5Y.

SARS-CoV-2 mainly infects the respiratory tract but can also target other organs, including the central nervous system. While it was recently shown that cells of the blood-brain-barrier are permissive to SARS-CoV-2 infection in vitro, it remains debated whether neurons can be infected. In this study, we demonstrate that vesicular stomatitis virus particles pseudotyped with the spike protein of SARS-CoV-2 variants WT, Alpha, Delta and Omicron enter the neuronal model cell line SH-SY5Y. Cell biological analyses of the pseudo-virus treated cultures showed marked alterations in microtubules of SH-SY5Y cells. Because the changes in ß-tubulin occurred in most cells, but only few were infected, we further asked whether interaction of the cells with spike protein might be sufficient to cause molecular and structural changes. For this, SH-SY5Y cells were incubated with trimeric spike proteins for time intervals of up to 24 h. CellProfiler™-based image analyses revealed changes in the intensities of microtubule staining in spike protein-incubated cells. Furthermore, expression of the spike protein-processing protease cathepsin L was found to be up-regulated by wild type, Alpha and Delta spike protein pseudotypes and cathepsin L was found to be secreted from spike protein-treated cells. We conclude that the mere interaction of the SARS-CoV-2 with neuronal cells can affect cellular architecture and proteolytic capacities. The molecular mechanisms underlying SARS-CoV-2 spike protein induced cytoskeletal changes in neuronal cells remain elusive and require future studies.

Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2.

Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we propose that RNA-seq should be considered a diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers insights into a patient's immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 196 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that-combined with sequence alignments and BLASTp-they could be used to classify a patient's disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.

Comprehensive benchmark of differential transcript usage analysis for static and dynamic conditions.

RNA sequencing offers unique insights into transcriptome diversity, and a plethora of tools have been developed to analyze alternative splicing. One important task is to detect changes in the relative transcript abundance in differential transcript usage (DTU) analysis. The choice of the right analysis tool is non-trivial and depends on experimental factors such as the availability of single- or paired-end and bulk or single-cell data. To help users select the most promising tool for their task, we performed a comprehensive benchmark of DTU detection tools. We cover a wide array of experimental settings, using simulated bulk and single-cell RNA-seq data as well as real transcriptomics datasets, including time-series data. Our results suggest that DEXSeq, edgeR, and LimmaDS are better choices for paired-end data, while DSGseq and DEXSeq can be used for single-end data. In single-cell simulation settings, we showed that satuRn performs better than DTUrtle. In addition, we showed that Spycone is optimal for time series DTU/IS analysis based on the evidence provided using GO terms enrichment analysis.

SARS-CoV-2 BA.2.86 enters lung cells and evades neutralizing antibodies with high efficiency.

BA.2.86, a recently identified descendant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.2 sublineage, contains ∼35 mutations in the spike (S) protein and spreads in multiple countries. Here, we investigated whether the virus exhibits altered biological traits, focusing on S protein-driven viral entry. Employing pseudotyped particles, we show that BA.2.86, unlike other Omicron sublineages, enters Calu-3 lung cells with high efficiency and in a serine- but not cysteine-protease-dependent manner. Robust lung cell infection was confirmed with authentic BA.2.86, but the virus exhibited low specific infectivity. Further, BA.2.86 was highly resistant against all therapeutic antibodies tested, efficiently evading neutralization by antibodies induced by non-adapted vaccines. In contrast, BA.2.86 and the currently circulating EG.5.1 sublineage were appreciably neutralized by antibodies induced by the XBB.1.5-adapted vaccine. Collectively, BA.2.86 has regained a trait characteristic of early SARS-CoV-2 lineages, robust lung cell entry, and evades neutralizing antibodies. However, BA.2.86 exhibits low specific infectivity, which might limit transmissibility.

A tetravalent bispecific antibody outperforms the combination of its parental antibodies and neutralizes diverse SARS-CoV-2 variants.

The devastating impact of COVID-19 on global health shows the need to increase our pandemic preparedness. Recombinant therapeutic antibodies were successfully used to treat and protect at-risk patients from COVID-19. However, the currently circulating Omicron subvariants of SARS-CoV-2 are largely resistant to therapeutic antibodies, and novel approaches to generate broadly neutralizing antibodies are urgently needed. Here, we describe a tetravalent bispecific antibody, A7A9 TVB, which actively neutralized many SARS-CoV-2 variants of concern, including early Omicron subvariants. Interestingly, A7A9 TVB neutralized more variants at lower concentration as compared to the combination of its parental monoclonal antibodies, A7K and A9L. A7A9 also reduced the viral load of authentic Omicron BA.1 virus in infected pseudostratified primary human nasal epithelial cells. Overall, A7A9 displayed the characteristics of a potent broadly neutralizing antibody, which may be suitable for prophylactic and therapeutic applications in the clinics, thus highlighting the usefulness of an effective antibody-designing approach.

Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2.

Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we argue that RNA-seq should be considered a routine diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers vital insights into a patient's immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 240 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that - combined with sequence alignments and pBLAST - they could be used to classify a patient's disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.

Network medicine-based epistasis detection in complex diseases: ready for quantum computing.

Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs)1-3. Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL (network-based epistasis detection via local search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL is the first application that demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies.

Systematical assessment of the impact of single spike mutations of SARS-CoV-2 Omicron sub-variants on the neutralization capacity of post-vaccination sera.

Introduction: The evolution of novel SARS-CoV-2 variants significantly affects vaccine effectiveness. While these effects can only be studied retrospectively, neutralizing antibody titers are most used as correlates of protection. However, studies assessing neutralizing antibody titers often show heterogeneous data. Methods: To address this, we investigated assay variance and identified virus infection time and dose as factors affecting assay robustness. We next measured neutralization against Omicron sub-variants in cohorts with hybrid or vaccine induced immunity, identifying a gradient of immune escape potential. To evaluate the effect of individual mutations on this immune escape potential of Omicron variants, we systematically assessed the effect of each individual mutation specific to Omicron BA.1, BA.2, BA.2.12.1, and BA.4/5. Results: We cloned a library of pseudo-viruses expressing spikes with single point mutations, and subjected it to pooled sera from vaccinated hosts, thereby identifying multiple mutations that independently affect neutralization potency. Discussion: These data might help to predict antigenic features of novel viral variants carrying these mutations and support the development of broad monoclonal antibodies.

Computational tools for inferring transcription factor activity.

Transcription factors (TFs) are essential players in orchestrating the regulatory landscape in cells. Still, their exact modes of action and dependencies on other regulatory aspects remain elusive. Since TFs act cell type-specific and each TF has its own characteristics, untangling their regulatory interactions from an experimental point of view is laborious and convoluted. Thus, there is an ongoing development of computational tools that estimate transcription factor activity (TFA) from a variety of data modalities, either based on a mapping of TFs to their putative target genes or in a genome-wide, gene-unspecific fashion. These tools can help to gain insights into TF regulation and to prioritize candidates for experimental validation. We want to give an overview of available computational tools that estimate TFA, illustrate examples of their application, debate common result validation strategies, and discuss assumptions and concomitant limitations.

Suppression of neutrophils by sodium exacerbates oxidative stress and arthritis.

Introduction: Typical Western diet, rich in salt, contributes to autoimmune disease development. However, conflicting reports exist about the effect of salt on neutrophil effector functions, also in the context of arthritis. Methods: We investigated the effect of sodium chloride (NaCl) on neutrophil viability and functions in vitro, and in vivo employing the murine K/BxN-serum transfer arthritis (STA) model. Results and discussion: The effects of NaCl and external reactive oxygen species (H2O2) were further examined on osteoclasts in vitro. Hypertonic sodium-rich media caused primary/secondary cell necrosis, altered the nuclear morphology, inhibited phagocytosis, degranulation, myeloperoxidase (MPO) peroxidation activity and neutrophil extracellular trap (NET) formation, while increasing total ROS production, mitochondrial ROS production, and neutrophil elastase (NE) activity. High salt diet (HSD) aggravated arthritis by increasing inflammation, bone erosion, and osteoclast differentiation, accompanied by increased NE expression and activity. Osteoclast differentiation was decreased with 25 mM NaCl or 100 nM H2O2 addition to isotonic media. In contrast to NaCl, external H2O2 had pro-resorptive effects in vitro. We postulate that in arthritis under HSD, increased bone erosion can be attributed to an enhanced oxidative milieu maintained by infiltrating neutrophils, rather than a direct effect of NaCl.

circRNA-sponging: a pipeline for extensive analysis of circRNA expression and their role in miRNA sponging.

Motivation: Circular RNAs (circRNAs) are long noncoding RNAs (lncRNAs) often associated with diseases and considered potential biomarkers for diagnosis and treatment. Among other functions, circRNAs have been shown to act as microRNA (miRNA) sponges, preventing the role of miRNAs that repress their targets. However, there is no pipeline to systematically assess the sponging potential of circRNAs. Results: We developed circRNA-sponging, a nextflow pipeline that (i) identifies circRNAs via backsplicing junctions detected in RNA-seq data, (ii) quantifies their expression values in relation to their linear counterparts spliced from the same gene, (iii) performs differential expression analysis, (iv) identifies and quantifies miRNA expression from miRNA-sequencing (miRNA-seq) data, (v) predicts miRNA binding sites on circRNAs, (vi) systematically investigates potential circRNA-miRNA sponging events, (vii) creates a network of competing endogenous RNAs and (viii) identifies potential circRNA biomarkers. We showed the functionality of the circRNA-sponging pipeline using RNA sequencing data from brain tissues, where we identified two distinct types of circRNAs characterized by a specific ratio of the number of the binding site to the length of the transcript. The circRNA-sponging pipeline is the first end-to-end pipeline to identify circRNAs and their sponging systematically with raw total RNA-seq and miRNA-seq files, allowing us to better indicate the functional impact of circRNAs as a routine aspect in transcriptomic research. Availability and implementation: https://github.com/biomedbigdata/circRNA-sponging. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Safety and immunogenicity against ancestral, Delta and Omicron virus variants following a booster dose of an inactivated whole-virus COVID-19 vaccine (VLA2001): Interim analysis of an open-label extension of the randomized, controlled, phase 3 COV-COMPARE trial.

OBJECTIVES: Booster doses for COVID-19 vaccinations have been shown to amplify the waning immune response after primary vaccination and to enhance protection against emerging variants of concern (VoCs). Here, we aimed to assess the immunogenicity and safety of a booster dose of an inactivated whole-virus COVID-19 vaccine (VLA2001) after primary vaccination with 2 doses of either VLA2001 or ChAdOx1-S (Oxford-Astra Zeneca), including the cross-neutralization capacity against the Delta and Omicron VoCs. METHODS: This interim analysis of an open-label extension of a randomized, controlled phase 3 trial assessed a single booster dose of an inactivated whole-virus COVID-19 vaccine (VLA2001) in healthy or medically stable adults aged 18 years and above, recruited in 21 clinical sites in the UK, who had previously received two doses of either VLA2001 or ChAdOx1-S. Safety outcomes were frequency and severity of solicited injection site and systemic reactions within 7 days after booster vaccination as well as frequency and severity of any unsolicited adverse events (AE) after up to 6 months. Immunogenicity outcomes were the immune response to ancestral SARS-CoV-2 assessed 14 days post booster expressed as geometric mean titres (GMT), GMT fold ratios and seroconversion of specific neutralizing antibodies and S-protein binding IgG antibodies. Immunogenicity against the Delta and Omicron VoCs was assessed as a post-hoc outcome with a pseudovirus neutralization antibody assay. This study is registered with ClinicalTrials.gov, NCT04864561, and is ongoing. RESULTS: A booster dose of VLA2001 was administered to 958 participants, of whom 712 had been primed with VLA2001, and 246 with ChAdOx1-S. Within 7 days following these booster doses, 607 (63.4%) participants reported solicited injection site reactions, and 487 (50.8%) reported solicited systemic reactions. Up to 14 days post booster, 751 (78.4%) participants reported at least one adverse event. The tolerability profile of a booster dose of VLA2001 was similar in VLA2001-primed and ChAdOx1-S-primed participants. In VLA2001-primed participants, the GMT (95% CI) of neutralizing antibodies increased from 32.5 (22.8, 46.3) immediately before to 521.5 (413.0, 658.6) 2 weeks after administration of the booster dose, this corresponds to a geometric mean fold rise (GMFR) of 27.7 (20.0, 38.5). Compared to 2 weeks after the second priming dose, the GMFR was 3.6 (2.8, 4.7). In the ChAdOx1-S primed group, the GMT (95% CI) of neutralizing antibodies increased from 65.8 (43.9, 98.4) immediately before to 188.3 (140.3, 252.8) 2 weeks after administration of the booster dose, a geometric mean fold rise (GMFR) of 3.0 (2.2, 4.0). Compared to 2 weeks after the second priming dose, the GMFR was 1.6 (1.1, 2.2). For S-protein binding IgG antibodies, the pre- versus post-booster GMT fold ratio (95% CI) was 34.6 (25.0, 48.0) in the VLA2001-primed group and 4.0 (3.0, 5.2) in the ChAdOx1-S-primed group. Compared to 2 weeks after the second priming dose, the GMT fold rise of IgG antibodies was 3.8 (3.2, 4.6) in the VLA2001-primed group and 1.2 (0.9, 1.6) in the ChAdOx1-S-primed group. The GMT against Delta (B.1.617.2) and Omicron (BA.4/5) increased from 4.2 to 260, and from 2.7 to 56.7, respectively, when boosting subjects previously primed with VLA2001. Following the boost, 97% of subjects primed with VLA2001 had detectable Delta- and 94% Omicron-neutralizing antibodies. In subjects primed with ChAdOx1-S, the GMT against Delta and Omicron titres increased from 9.1 to 92.5, and from 3.6 to 12.3, respectively. After boosting, 99% of subjects primed with ChAdOx1-S had detectable Delta- and 70% Omicron-neutralizing antibodies. In both VLA2001 and ChAdOx1-S primed subjects, the additional VLA2001 dose boosted T cell responses against SARS-CoV-2 antigens to levels above those observed before the booster dose. CONCLUSION: A booster dose of VLA2001 was safe and well tolerated after primary immunization with VLA2001 and ChAdOx1-S. The tolerability of a booster dose of VLA2001 was similar to the favourable profile observed after the first and second priming doses. Both in a homologous and a heterologous setting, boosting resulted in higher neutralizing antibody titres than after primary immunization and significant increases in cross-neutralization titres against Delta and Omicron were observed after the booster dose. These data support the use of VLA2001 in booster programmes in ChadOx1-S primed groups.

Polyvalent Nano-Lectin Potently Neutralizes SARS-CoV-2 by Targeting Glycans on the Viral Spike Protein.

Mutations in spike (S) protein epitopes allow SARS-CoV-2 variants to evade antibody responses induced by infection and/or vaccination. In contrast, mutations in glycosylation sites across SARS-CoV-2 variants are very rare, making glycans a potential robust target for developing antivirals. However, this target has not been adequately exploited for SARS-CoV-2, mostly due to intrinsically weak monovalent protein-glycan interactions. We hypothesize that polyvalent nano-lectins with flexibly linked carbohydrate recognition domains (CRDs) can adjust their relative positions and bind multivalently to S protein glycans, potentially exerting potent antiviral activity. Herein, we displayed the CRDs of DC-SIGN, a dendritic cell lectin known to bind to diverse viruses, polyvalently onto 13 nm gold nanoparticles (named G13-CRD). G13-CRD bound strongly and specifically to target glycan-coated quantum dots with sub-nM Kd. Moreover, G13-CRD neutralized particles pseudotyped with the S proteins of Wuhan Hu-1, B.1, Delta variant and Omicron subvariant BA.1 with low nM EC50. In contrast, natural tetrameric DC-SIGN and its G13 conjugate were ineffective. Further, G13-CRD potently inhibited authentic SARS-CoV-2 B.1 and BA.1, with <10 pM and <10 nM EC50, respectively. These results identify G13-CRD as the 1st polyvalent nano-lectin with broad activity against SARS-CoV-2 variants that merits further exploration as a novel approach to antiviral therapy.