Correlation of Professional Antigen-Presenting Tbet+CD11c+ B Cells With Bone Destruction in Untreated Rheumatoid Arthritis.

OBJECTIVE: Subsets of CD21-/low memory B cells (MBCs), including double-negative (DN, CD27-IgD-) and Tbet+CD11c+ cells, are expanded in chronic inflammatory diseases. In rheumatoid arthritis (RA), CD21-/low MBCs correlate with joint destruction. However, whether this is due to the Tbet+CD11c+ subset, its function and pathogenic contribution to RA are unknown. This study aims to investigate the association between CD21-/lowTbet+CD11c+ MBCs and joint destruction as well as other clinical parameters and to elucidate their functional properties in patients with untreated RA (uRA). METHODS: Clinical observations were combined with flow cytometry (n = 36) and single-cell RNA sequencing (scRNA-seq) and V(D)J sequencing (n = 4) of peripheral blood (PB) MBCs from patients with uRA. The transcriptome of circulating Tbet+CD11c+ MBCs was compared with scRNA-seq data of synovial B cells. In vitro coculture of Tbet+CD11c+ B cells with T cells was used to assess costimulatory capacity. RESULTS: CD21-/lowTbet+CD11c+ MBCs in PB correlated with bone destruction but no other clinical parameters analyzed. The Tbet+CD11c+ MBCs have undergone clonal expansion and express somatically mutated V genes. Gene expression analysis of these cells identified a unique signature of more than 150 up-regulated genes associated with antigen presentation functions, including B cell receptor activation and clathrin-mediated antigen internalization; regulation of actin filaments, endosomes, and lysosomes; antigen processing, loading, presentation, and costimulation; a transcriptome mirrored in their synovial tissue counterparts. In vitro, Tbet+CD11c+ B cells induced retinoic acid receptor-related orphan nuclear receptor γT expression in CD4+ T cells, thereby polarizing to Th17 cells, a T cell subset critical for osteoclastogenesis and associated with bone destruction. CONCLUSION: This study suggests that Tbet+CD11c+ MBCs contribute to the pathogenesis of RA by promoting bone destruction through antigen presentation, T cell activation, and Th17 polarization.

Identification of biomarker candidates for exfoliative glaucoma from autoimmunity profiling.

BACKGROUND: Exfoliative glaucoma (XFG) is a subtype of open-angle glaucoma characterized by distinctive extracellular fibrils and a yet unknown pathogenesis potentially involving immune-related factors. The aim of this exploratory study was to identify biomarkers for XFG using data from autoimmunity profiling performed on blood samples from a Scandinavian cohort of patients. METHODS: Autoantibody screening was analyzed against 258 different protein fragments in blood samples taken from 30 patients diagnosed with XFG and 30 healthy donors. The 258 protein fragments were selected based on a preliminary study performed on 3072 randomly selected antigens and antigens associated with the eye. The "limma" package was used to perform moderated t-tests on the proteomic data to identify differentially expressed reactivity between the groups. RESULTS: Multiple associated genes were highlighted as possible biomarker candidates including FUT2, CDH5, and the LOX family genes. Using seven variables, our binary logistic regression model was able to classify the cases from the controls with an AUC of 0.85, and our reduced model using only one variable corresponding to the FUT2 gene provided an AUC of 0.75, based on LOOCV. Furthermore, over-representation gene analysis was performed to identify pathways that were associated with antigens differentially bound to self-antibodies. This highlighted the enrichment of pathways related to collagen fibril formation and the regulatory molecules mir-3176 and mir-876-5p. CONCLUSIONS: This study suggests several potential biomarkers that may be useful in developing further models of the pathology of XFG. In particular, CDH5, FUT2, and the LOX family seem to have a relationship which merits additional exploration.

Defective peripheral B cell selection in common variable immune deficiency patients with autoimmune manifestations.

Common variable immune deficiency (CVID) is a heterogeneous disorder characterized by recurrent infections, low levels of serum immunoglobulins, and impaired vaccine responses. Autoimmune manifestations are common, but B cell central and peripheral selection mechanisms in CVID are incompletely understood. Here, we find that receptor editing, a measure of central tolerance, is increased in transitional B cells from CVID patients and that these cells have a higher immunoglobulin κ:λ ratio in CVID patients with autoimmune manifestations than in those with infection only. Contrariwise, the selection pressure in the germinal center on CD27bright memory B cells is decreased in CVID patients with autoimmune manifestations. Finally, functionally, T cell-dependent activation showed that naive B cells in CVID patients are badly equipped for activation and induction of mismatch repair genes. We conclude that central tolerance is functional whereas peripheral selection is defective in CVID patients with autoimmune manifestations, which could underpin the development of autoimmunity.

Benchmarking of two bioinformatic workflows for the analysis of whole-genome sequenced Staphylococcus aureus collected from patients with suspected sepsis.

BACKGROUND: The rapidly growing area of sequencing technologies, and more specifically bacterial whole-genome sequencing, could offer applications in clinical microbiology, including species identification of bacteria, prediction of genetic antibiotic susceptibility and virulence genes simultaneously. To accomplish the aforementioned points, the commercial cloud-based platform, 1928 platform (1928 Diagnostics, Gothenburg, Sweden) was benchmarked against an in-house developed bioinformatic pipeline as well as to reference methods in the clinical laboratory. METHODS: Whole-genome sequencing data retrieved from 264 Staphylococcus aureus isolates using the Illumina HiSeq X next-generation sequencing technology was used. The S. aureus isolates were collected during a prospective observational study of community-onset severe sepsis and septic shock in adults at Skaraborg Hospital, in the western region of Sweden. The collected isolates were characterized according to accredited laboratory methods i.e., species identification by MALDI-TOF MS analysis and phenotypic antibiotic susceptibility testing (AST) by following the EUCAST guidelines. Concordance between laboratory methods and bioinformatic tools, as well as concordance between the bioinformatic tools was assessed by calculating the percent of agreement. RESULTS: There was an overall high agreement between predicted genotypic AST and phenotypic AST results, 98.0% (989/1006, 95% CI 97.3-99.0). Nevertheless, the 1928 platform delivered predicted genotypic AST results with lower very major error rates but somewhat higher major error rates compared to the in-house pipeline. There were differences in processing times i.e., minutes versus hours, where the 1928 platform delivered the results faster. Furthermore, the bioinformatic workflows showed overall 99.4% (1267/1275, 95% CI 98.7-99.7) agreement in genetic prediction of the virulence gene characteristics and overall 97.9% (231/236, 95% CI 95.0-99.2%) agreement in predicting the sequence types (ST) of the S. aureus isolates. CONCLUSIONS: Altogether, the benchmarking disclosed that both bioinformatic workflows are able to deliver results with high accuracy aiding diagnostics of severe infections caused by S. aureus. It also illustrates the need of international agreement on quality control and metrics to facilitate standardization of analytical approaches for whole-genome sequencing based predictions.

Single-cell RNA sequencing analyses: interference by the genes that encode the B-cell and T-cell receptors.

B and T cells are integral parts of the immune system and are implicated in many diseases, e.g. autoimmunity. Towards understanding the biology of B and T cells and subsets thereof, their transcriptomes can be analyzed using single-cell RNA sequencing. In some studies, the V(D)J transcripts encoding the variable regions of the B- and T-cell antigen receptors have been removed before the analyses. However, a systematic analysis of the effects of including versus excluding these genes is currently lacking. We have investigated the effects of these transcripts on unsupervised clustering and down-stream analyses of single-cell RNA sequencing data from B and T cells. We found that exclusion of the B-/T-cell receptor genes prior to unsupervised clustering resulted in clusters that represented biologically meaningful subsets, such as subsets of memory B and memory T cells. Furthermore, pseudo-time and trajectory inference analyses of early B-lineage cells resulted in a developmental pathway from progenitor to immature B cells. In contrast, when the B-/T-cell receptor genes were not removed, with the PCs used for clustering consisting of up to 70% V-genes, this resulted in some clusters being defined exclusively by V-gene segments. These did not represent biologically meaningful subsets; for instance in the early B-lineage cells, these clusters contained cells representing all developmental stages. Thus, in studies of B and T cells, to derive biologically meaningful results, it is imperative to remove the gene sequences that encode B- and T-cell receptors.

Sequence-based genotyping of extra-intestinal pathogenic Escherichia coli isolates from patients with suspected community-onset sepsis, Sweden.

Extra-intestinal pathogenic Escherichia coli (ExPEC) strains are responsible for a large number of human infections globally. The management of infections caused by ExPEC has been complicated by the emergence of antimicrobial resistance, most importantly the increasing recognition of isolates producing extended-spectrum ß-lactamases (ESBL). Herein, we used whole-genome sequencing (WGS) on ExPEC isolates for a comprehensive genotypic characterization. Twenty-one ExPEC isolates, nine with and 12 without ESBL-production, from 16 patients with suspected sepsis were sequenced on an Illumina MiSeq platform. Analysis of WGS data was performed with widely used bioinformatics software and tools for genotypic characterization of the isolates. A higher number of plasmids, virulence and resistance genes were observed in the ESBL-producing isolates than the non-ESBL-producing, although not statistically significant due to the low sample size. All nine ESBL-producing ExPEC isolates presented with at least one bla gene, as did three of the 12 without ESBL-production. Multi-locus sequence typing analysis revealed a diversity of sequence types whereas phylogroup A prevailed among isolates both with and without ESBL-production. In conclusion, this limited study shows that analysis of WGS data can be used for genotypic characterization of ExPEC isolates to obtain in-depth information of clinical relevance.

Diversity of respiratory parameters and metabolic adaptation to low oxygen tension in mesenchymal stromal cells.

Objective: Cell metabolism has been shown to play an active role in regulation of stemness and fate decision. In order to identify favorable culture conditions for mesenchymal stromal cells (MSCs) prior to transplantation, this study aimed to characterize the metabolic function of MSCs from different developmental stages in response to different oxygen tension during expansion. Materials and methods: We cultured human fetal cardiac MSCs and human adult bone-marrow MSCs for a week under hypoxia (3% O2) and normoxia (20% O2). We performed mitochondrial characterization and assessed oxygen consumption- and extracellular acidification-rates (OCR and ECAR) in addition to oxygen-sensitive respiration and mitochondrial complex activities, using both the Seahorse and Oroboros systems. Results: Adult and fetal MSCs displayed similar basal respiration and mitochondrial amount, however fetal MSCs had lower spare respiratory capacity and apparent coupling efficiency. Fetal MSCs expanded in either hypoxia or normoxia demonstrated similar acidification rates, while adult MSCs downregulated their aerobic glycolysis in normoxia. Acute decrease in oxygen tension caused a higher respiratory inhibition in adult compared to fetal MSCs. In both sources of MSCs, minor changes in complex activities in normoxic and hypoxic cultures were found. Conclusions: In contrast to adult MSCs, fetal MSCs displayed similar respiration and aerobic glycolysis at different O2 culture concentrations during expansion. Adult MSCs adjusted their respiration to glycolytic activities, depending on the culture conditions thus displaying a more mature metabolic function. These findings are relevant for establishing optimal in vitro culturing conditions, with the aim to maximize engraftment and therapeutic outcome.

Spatiotemporal extracellular matrix modeling for in situ cell niche studies.

Extracellular matrix (ECM) components govern a range of cell functions, such as migration, proliferation, maintenance of stemness, and differentiation. Cell niches that harbor stem-/progenitor cells, with matching ECM, have been shown in a range of organs, although their presence in the heart is still under debate. Determining niches depends on a range of in vitro and in vivo models and techniques, where animal models are powerful tools for studying cell-ECM dynamics; however, they are costly and time-consuming to use. In vitro models based on recombinant ECM proteins lack the complexity of the in vivo ECM. To address these issues, we present the spatiotemporal extracellular matrix model for studies of cell-ECM dynamics, such as cell niches. This model combines gentle decellularization and sectioning of cardiac tissue, allowing retention of a complex ECM, with recellularization and subsequent image processing using image stitching, segmentation, automatic binning, and generation of cluster maps. We have thereby developed an in situ representation of the cardiac ECM that is useful for assessment of repopulation dynamics and to study the effect of local ECM composition on phenotype preservation of reseeded mesenchymal progenitor cells. This model provides a platform for studies of organ-specific cell-ECM dynamics and identification of potential cell niches.

Genotypic Characterization of Clinical Klebsiella spp. Isolates Collected From Patients With Suspected Community-Onset Sepsis, Sweden.

Klebsiella is a genus of Gram-negative bacteria known to be opportunistic pathogens that may cause a variety of infections in humans. Highly drug-resistant Klebsiella species, especially K. pneumoniae, have emerged rapidly and are becoming a major concern in clinical management. Although K. pneumoniae is considered the most important pathogen within the genus, the true clinical significance of the other species is likely underrecognized due to the inability of conventional microbiological methods to distinguish between the species leading to high rates of misidentification. Bacterial whole-genome sequencing (WGS) enables precise species identification and characterization that other technologies do not allow. Herein, we have characterized the diversity and traits of Klebsiella spp. in community-onset infections by WGS of clinical isolates (n = 105) collected during a prospective sepsis study in Sweden. The sequencing revealed that 32 of the 82 isolates (39.0%) initially identified as K. pneumoniae with routine microbiological methods based on cultures followed by matrix-assisted laser desorption-time of flight mass spectrometry (MALDI-TOF MS) had been misidentified. Of these, 23 were identified as Klebsiella variicola and nine as other members of the K. pneumoniae complex. Comparisons of the number of resistance genes showed that significantly fewer resistance genes were detected in Klebsiella oxytoca compared to K. pneumoniae and K. variicola (both values of p < 0.001). Moreover, a high proportion of the isolates within the K. pneumoniae complex were predicted to be genotypically multidrug-resistant (MDR; 79/84, 94.0%) in contrast to K. oxytoca (3/16, 18.8%) and Klebsiella michiganensis (0/4, 0.0%). All isolates predicted as genotypically MDR were found to harbor the combination of ß-lactam, fosfomycin, and quinolone resistance markers. Multi-locus sequence typing (MLST) revealed a high diversity of sequence types among the Klebsiella spp. with ST14 (10.0%) and ST5429 (10.0%) as the most prevalent ones for K. pneumoniae, ST146 for K. variicola (12.0%), and ST176 for K. oxytoca (25.0%). In conclusion, the results from this study highlight the importance of using high-resolution genotypic methods for identification and characterization of clinical Klebsiella spp. isolates. Our findings indicate that infections caused by other members of the K. pneumoniae complex than K. pneumoniae are a more common clinical problem than previously described, mainly due to high rates of misidentifications.

A cell topography-based mechanism for ligand discrimination by the T cell receptor.

The T cell receptor (TCR) initiates the elimination of pathogens and tumors by T cells. To avoid damage to the host, the receptor must be capable of discriminating between wild-type and mutated self and nonself peptide ligands presented by host cells. Exactly how the TCR does this is unknown. In resting T cells, the TCR is largely unphosphorylated due to the dominance of phosphatases over the kinases expressed at the cell surface. However, when agonist peptides are presented to the TCR by major histocompatibility complex proteins expressed by antigen-presenting cells (APCs), very fast receptor triggering, i.e., TCR phosphorylation, occurs. Recent work suggests that this depends on the local exclusion of the phosphatases from regions of contact of the T cells with the APCs. Here, we developed and tested a quantitative treatment of receptor triggering reliant only on TCR dwell time in phosphatase-depleted cell contacts constrained in area by cell topography. Using the model and experimentally derived parameters, we found that ligand discrimination likely depends crucially on individual contacts being ∼200 nm in radius, matching the dimensions of the surface protrusions used by T cells to interrogate their targets. The model not only correctly predicted the relative signaling potencies of known agonists and nonagonists but also achieved this in the absence of kinetic proofreading. Our work provides a simple, quantitative, and predictive molecular framework for understanding why TCR triggering is so selective and fast and reveals that, for some receptors, cell topography likely influences signaling outcomes.

Correlation and cluster analysis of immunomodulatory drugs based on cytokine profiles.

Drug discovery is a constant struggle to overcome hurdles posed by the complexity of biological systems. One of these hurdles is to find and understand the molecular target and the biological mechanism of action. Although the molecular target has been determined, the true biological effect may be unforeseen also for well-established drugs. Hence, there is a need for novel ways to increase the knowledge of the biological effects of drugs in the developmental process. In this study, we have determined cytokine profiles for 26 non-biological immunomodulatory drugs or drug candidates and used these profiles to cluster the compounds according to their effect in a preclinical ex vivo culture model of arthritis. This allows for prediction of functions and drug target of a novel drug candidate based on profiles obtained in this study. Results from the study showed that the JAK inhibitors tofacitinib and ruxolitinib formed a robust cluster and were found to have a distinct cytokine profile compared to the other drugs. Another robust cluster included the calcineurin inhibitors cyclosporine A and tacrolimus and the protein kinase inhibitors fostamatinib disodium and sotrastaurin acetate, which caused a strong overall inhibition of the cytokine production. The results of this methodology indicate that cytokine profiles can be used to provide a fingerprint-like identification of a drug as a tool to benchmark novel drugs and to improve descriptions of mode of action.

In situ and in silico kinetic analyses of programmed cell death-1 (PD-1) receptor, programmed cell death ligands, and B7-1 protein interaction network.

Programmed cell death-1 (PD-1) is an inhibitory receptor with an essential role in maintaining peripheral tolerance and is among the most promising immunotherapeutic targets for treating cancer, autoimmunity, and infectious diseases. A complete understanding of the consequences of PD-1 engagement by its ligands, PD-L1 and PD-L2, and of PD-L1 binding to B7-1 requires quantitative analysis of their interactions at the cell surface. We present here the first complete in situ kinetic analysis of the PD-1/PD-ligands/B7-1 system. Consistent with previous solution measurements, we observed higher in situ affinities for human (h) than murine (m) PD-1 interactions, stronger binding of hPD-1 to hPD-L2 than hPD-L1, and comparable binding of mPD-1 to both ligands. However, in contrast to the relatively weak solution affinities, the in situ affinities of PD-1 are as high as those of the T cell receptor for agonist pMHC and of LFA-1 (lymphocyte function-associated antigen 1) for ICAM-1 (intercellular adhesion molecule 1) but significantly lower than that of the B7-1/CTLA-4 interaction, suggesting a distinct basis for PD-1- versus CTLA-4-mediated inhibition. Notably, the in situ interactions of PD-1 are much stronger than that of B7-1 with PD-L1. Overall, the in situ affinity ranking greatly depends on the on-rate instead of the off-rate. In silico simulations predict that PD-1/PD-L1 interactions dominate at interfaces between activated T cells and mature dendritic cells and that these interactions will be highly sensitive to the dynamics of PD-L1 and PD-L2 expression. Our results provide a kinetic framework for better understanding inhibitory PD-1 activity in health and disease.

Cytokine correlation analysis based on drug perturbation.

Cytokines and chemokines play a crucial role in regulating the immune system. Understanding how these molecules are co-regulated is important to understand general immunology, and particularly their role in clinical applications such as development and evaluation of novel drug therapies. Cytokines are today widely used as therapeutic targets and as biomarkers to monitor effects of drug therapies and for prognosis and diagnosis of diseases. Therapies that target a specific cytokine are also likely to affect the production of other cytokines due to their cross-regulatory functions and because the cytokines are produced by common cell types. In this study, we have perturbated the production of 17 different cytokines in a preclinical rat model of autoimmune arthritis, using 55 commercially available immunomodulatory drugs and clinical candidates. The majority of the studied drugs was selected for their anti-inflammatory role and was confirmed to inhibit the production of IL-2 and IFN-γ in this model but was also found to increase the production of other cytokines compared to the untreated control. Correlation analysis identified 58 significant pairwise correlations between the cytokines. The strongest correlations found in this study were between IL-2 and IFN-γ (r=0.87) and between IL-18 and EPO (r=0.84). Cluster analysis identified two robust clusters: (1) IL-7, IL-18 and EPO, and (2) IL-2, IL-17 and IFN-γ. The results show that cytokines are highly co-regulated, which provide valuable information for how a therapeutic drug might affect clusters of cytokines. In addition, a cytokine that is used as a therapeutic biomarker could be combined with its related cytokines into a biomarker panel to improve diagnostic accuracy.