Cell type-specific modulation of metabolic, immune-regulatory, and anti-microbial pathways by CD101.

T lymphocytes and myeloid cells express the immunoglobulin-like glycoprotein cluster of differentiation (CD)101, notably in the gut. Here, we investigated the cell-specific functions of CD101 during dextran sulfate sodium (DSS)-induced colitis and Salmonella enterica Typhimurium infection. Similar to conventional CD101-/- mice, animals with a regulatory T cell-specific Cd101 deletion developed more severe intestinal pathology than littermate controls in both models. While the accumulation of T helper 1 cytokines in a CD101-deficient environment entertained DSS-induced colitis, it impeded the replication of Salmonella as revealed by studying CD101-/- x interferon-g-/- mice. Moreover, CD101-expressing neutrophils were capable to restrain Salmonella infection in vitro and in vivo. Both cell-intrinsic and -extrinsic mechanisms of CD101 contributed to the control of bacterial growth and spreading. The CD101-dependent containment of Salmonella infection required the expression of Irg-1 and Nox2 and the production of itaconate and reactive oxygen species. The level of intestinal microbial antigens in the sera of inflammatory bowel disease patients correlated inversely with the expression of CD101 on myeloid cells, which is in line with the suppression of CD101 seen in mice following DSS application or Salmonella infection. Thus, depending on the experimental or clinical setting, CD101 helps to limit inflammatory insults or bacterial infections due to cell type-specific modulation of metabolic, immune-regulatory, and anti-microbial pathways.

Inflammatory tissue priming: novel insights and therapeutic opportunities for inflammatory rheumatic diseases.

Due to optimised treatment strategies and the availability of new therapies during the last decades, formerly devastating chronic inflammatory diseases such as rheumatoid arthritis or systemic sclerosis (SSc) have become less menacing. However, in many patients, even state-of-the-art treatment cannot induce remission. Moreover, the risk for flares strongly increases once anti-inflammatory therapy is tapered or withdrawn, suggesting that underlying pathological processes remain active even in the absence of overt inflammation. It has become evident that tissues have the ability to remember past encounters with pathogens, wounds and other irritants, and to react more strongly and/or persistently to the next occurrence. This priming of the tissue bears a paramount role in defence from microbes, but on the other hand drives inflammatory pathologies (the Dr Jekyll and Mr Hyde aspect of tissue adaptation). Emerging evidence suggests that long-lived tissue-resident cells, such as fibroblasts, macrophages, long-lived plasma cells and tissue-resident memory T cells, determine inflammatory tissue priming in an interplay with infiltrating immune cells of lymphoid and myeloid origin, and with systemically acting factors such as cytokines, extracellular vesicles and antibodies. Here, we review the current state of science on inflammatory tissue priming, focusing on tissue-resident and tissue-occupying cells in arthritis and SSc, and reflect on the most promising treatment options targeting the maladapted tissue response during these diseases.

Molecular Dynamics Study of the Green Solvent Polyethylene Glycol with Water Impurities.

Polyethylene glycol (PEG) is one of the environmentally benign solvent options for green chemistry. It readily absorbs water when exposed to the atmosphere. The Molecular Dynamics (MD) simulations of PEG200, a commercial mixture of low molecular weight polyethyelene glycol oligomers, as well as di-, tetra-, and hexaethylene glycol are presented to study the effect of added water impurities up to a weight fraction of 0.020, which covers the typical range of water impurities due to water absorption from the atmosphere. Each system was simulated a total of four times using different combinations of two force fields for the water (SPC/E and TIP4P/2005) and two force fields for the PEG and oligomer (OPLS-AA and modified OPLS-AA). The observed trends in the effects of water addition were qualitatively quite robust with respect to these force field combinations and showed that the water does not aggregate but forms hydrogen bonds at most between two water molecules. In general, the added water causes overall either no or very small and nuanced effects in the simulation results. Specifically, the obtained water RDFs are mostly identical regardless of the water content. The added water reduces oligomer hydrogen bonding interactions overall as it competes and forms hydrogen bonds with the oligomers. The loss of intramolecular oligomer hydrogen bonding is in part compensated by oligomers switching from inter- to intramolecular hydrogen bonding. The interplay of the competing hydrogen bonding interactions leads to the presence of shallow extrema with respect to the water weight fraction dependencies for densities, viscosities, and self-diffusion coefficients, in contrast to experimental measurements, which show monotonous dependencies. However, these trends are very small in magnitude and thus confirm the experimentally observed insensitivity of these physical properties to the presence of water impurities.

Drugst.One - a plug-and-play solution for online systems medicine and network-based drug repurposing.

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.

Rapid spread of the SARS-CoV-2 JN.1 lineage is associated with increased neutralization evasion.

In July/August 2023, the highly mutated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) BA.2.86 lineage emerged and its descendant JN.1 is on track to become the dominant SARS-CoV-2 lineage globally. Compared to the spike (S) protein of the parental BA.2.86 lineage, the JN.1 S protein contains one mutation, L455S, which may affect receptor binding and antibody evasion. Here, we performed a virological assessment of the JN.1 lineage employing pseudovirus particles bearing diverse SARS-CoV-2 S proteins. Using this strategy, it was found that S protein mutation L455S confers increased neutralization resistance but reduces ACE2 binding capacity and S protein-driven cell entry efficiency. Altogether, these data suggest that the benefit of increased antibody evasion outweighs the reduced ACE2 binding capacity and further enabled the JN.1 lineage to effectively spread in the human population.

Virological Traits of the SARS-CoV-2 BA.2.87.1 Lineage.

Transmissibility and immune evasion of the recently emerged, highly mutated SARS-CoV-2 BA.2.87.1 are unknown. Here, we report that BA.2.87.1 efficiently enters human cells but is more sensitive to antibody-mediated neutralization than the currently dominating JN.1 variant. Acquisition of adaptive mutations might thus be needed for efficient spread in the population.

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.

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.

The Inhibition of Gag-Pol Expression by the Restriction Factor Shiftless Is Dispensable for the Restriction of HIV-1 Infection.

The interferon-induced host cell protein Shiftless (SFL) inhibits -1 programmed ribosomal frameshifting (-1PRF) required for the expression of HIV-1 Gal-Pol and the formation of infectious HIV-1 particles. However, the specific regions in SFL required for antiviral activity and the mechanism by which SFL inhibits -1PRF remain unclear. Employing alanine scanning mutagenesis, we found that basic amino acids in the predicted zinc ribbon motif of SFL are essential for the suppression of Gag-Pol expression but dispensable for anti-HIV-1 activity. We have shown that SFL inhibits the expression of the murine leukemia virus (MLV) Gag-Pol polyprotein and the formation of infectious MLV particles, although Gag-Pol expression of MLV is independent of -1PRF but requires readthrough of a stop codon. These findings indicate that SFL might inhibit HIV-1 infection by more than one mechanism and that SFL might target programmed translational readthrough as well as -1PRF signals, both of which are regulated by mRNA secondary structure elements.

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.

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.

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.

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.