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Some nascent proteins that fold within the endoplasmic reticulum (ER) never reach their native state. Misfolded proteins are removed from the folding machinery, dislocated from the ER into the cytosol, and degraded in a series of pathways collectively referred to as ER-associated degradation (ERAD). Distinct ERAD pathways centered on different E3 ubiquitin ligases survey the range of potential substrates. We now know many of the components of the ERAD machinery and pathways used to detect substrates and target them for degradation. Much less is known about the features used to identify terminally misfolded conformations and the broader role of these pathways in regulating protein half-lives.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease linked to the misfolding of Cu/Zn superoxide dismutase (SOD1). ALS-related defects in SOD1 result in a gain of toxic function that coincides with aberrant oligomerization. The structural events triggering oligomerization have remained enigmatic, however, as is the case in other protein-misfolding diseases. Here, we target the critical conformational change that defines the earliest step toward aggregation. Using nuclear spin relaxation dispersion experiments, we identified a short-lived (0.4 ms) and weakly populated (0.7%) conformation of metal-depleted SOD1 that triggers aberrant oligomerization. This excited state emanates from the folded ground state and is suppressed by metal binding, but is present in both the disulfide-oxidized and disulfide-reduced forms of the protein. Our results pinpoint a perturbed region of the excited-state structure that forms intermolecular contacts in the earliest nonnative dimer/oligomer. The conformational transition that triggers oligomerization is a common feature of WT SOD1 and ALS-associated mutants that have widely different physicochemical properties. But compared with WT SOD1, the mutants have enhanced structural distortions in their excited states, and in some cases slightly higher excited-state populations and lower kinetic barriers, implying increased susceptibility to oligomerization. Our results provide a unified picture that highlights both (i) a common denominator among different SOD1 variants that may explain why diverse mutations cause the same disease, and (ii) a structural basis that may aid in understanding how different mutations affect disease propensity and progression.

Objective Fatigue is important for patients with rheumatoid arthritis (RA) but is poorly understood. We sought to study associations of fatigue with clinical features, disease activity, and synovial histology. Methods Patients meeting the American College of Rheumatology/EULAR 1987 and/or 2010 RA criteria were recruited before elective total joint replacement. Demographics, RA characteristics, tender and swollen joints, erythrocyte sedimentation rate (ESR) and C‐reactive protein, and patient‐reported fatigue, categorized as mild, moderate, or severe, were collected. Hematoxylin and eosin stains of sectioned synovium were systematically scored by a pathologist. Relationships between fatigue and studied variables were evaluated with Kendall's tau. A directed acyclic graph (DAG) was used to illustrate associations of exposures, outcome variables, mediators, and confounders. Multivariable ordered logistic regression was used to further study associations. Results Of 160 included patients, 85.6% were women, with a median age of 63.5 (55.25–71.40) and mean disease activity scores in 28 joints using ESR (DAS28‐ESR) of 3.91 (SD 1.3). There were no differences in comorbidities across fatigue categories. Fatigue correlated with DAS28‐ESR, synovial lining hyperplasia (SLH), anxiety, depression, and pain. In the DAG, DAS28‐ESR was associated with fatigue, full mediation by pain, partial mediation by depression and anxiety, and confounding by female sex. SLH was independently associated with fatigue but did not confound the relationship between DAS28‐ESR and fatigue. SLH was affected by synovial lymphocytic inflammation. In multivariable models, female sex, DAS28‐ESR, and SLH were all associated with higher fatigue. Conclusion Although fatigue is associated with DAS28‐ESR, it is also associated with SLH independently of disease activity.

Inflammation of non-barrier immunologically quiescent tissues is associated with a massive influx of blood-borne innate and adaptive immune cells. Cues from the latter are likely to alter and expand activated states of the resident cells. However, local communications between immigrant and resident cell types in human inflammatory disease remain poorly understood. Here, we explored drivers of fibroblast-like synoviocyte (FLS) heterogeneity in inflamed joints of patients with rheumatoid arthritis using paired single-cell RNA and ATAC sequencing, multiplexed imaging and spatial transcriptomics along with in vitro modeling of cell-extrinsic factor signaling. These analyses suggest that local exposures to myeloid and T cell-derived cytokines, TNF, IFN-γ, IL-1β or lack thereof, drive four distinct FLS states some of which closely resemble fibroblast states in other disease-affected tissues including skin and colon. Our results highlight a role for concurrent, spatially distributed cytokine signaling within the inflamed synovium. Smith et al. present a resource detailing drivers of transcriptional heterogeneity of synovial fibroblasts cell states in the inflamed joints of human patients with rheumatoid arthritis.

In the rheumatoid arthritis (RA) synovium, resident fibroblast-like synoviocytes (FLS) express MHC class II molecules (HLA-D) but lack the costimulatory signals typically required for T cell activation. Here, we demonstrate that antigen presentation by FLS induces a distinct T cell activation state characterized by high CD69 yet reduced CD25 and HLA-DR expression, suppressed proliferation, and decreased effector cytokine production compared with professional antigen-presenting cells (APCs), such as macrophages. FLS were also capable of suppressing macrophage-induced T cell activation, underscoring their dominant immunomodulatory role in the synovial microenvironment. Mechanistically, we identify indoleamine 2,3-dioxygenase-mediated (IDO1-mediated) tryptophan depletion as the primary driver of FLS-induced T cell hyporesponsiveness. Spatial transcriptomics revealed colocalization of IDO1 and CD69 within ectopic lymphoid structures in RA synovium, further supporting the in vivo relevance of this pathway. These findings provide the groundwork for positioning FLS as critical T cell regulators in RA and highlight the importance of preserving their immunosuppressive properties when therapeutically targeting pathogenic FLS functions.

[ PSI+ ] is a well-studied prion from budding yeast. Here the dominant-negative effects of mutation G58D are found to depend on the prion conformation. Moreover, the curing effect of G58D on one particular prion conformation is attributed to an impact on the delivery of infectious particles from the mother to the daughter cells. Prion proteins can adopt multiple infectious strain conformations. Here we investigate how the sequence of a prion protein affects its capacity to propagate specific conformations by exploiting our ability to create two distinct infectious conformations of the yeast [ PSI + ] prion protein Sup35, termed Sc4 and Sc37. PNM2, a G58D point mutant of Sup35 that was originally identified for its dominant interference with prion propagation, leads to rapid, recessive loss of Sc4 but does not interfere with propagation of Sc37. PNM2 destabilizes the amyloid core of Sc37 and causes compensatory effects that slow prion growth but aid prion division and result in robust propagation of Sc37. By contrast, PNM2 does not affect the structure or chaperone-mediated division of Sc4 but interferes with its delivery to daughter cells. Thus, effective delivery of infectious particles during cell division is a crucial and conformation-dependent step in prion inheritance.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction 1 . There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity 1 , 2 . Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments. Single-cell transcriptomic and proteomic data from synovial tissue from individuals with rheumatoid arthritis classify patients into groups based on abundance of cell states that can provide insights into pathology and predict individual treatment responses.

Rheumatoid arthritis (RA) is an autoimmune disease involving antigen-specific T and B cells. Here, we perform single-cell RNA and repertoire sequencing on paired synovial tissue and blood samples from 12 seropositive RA patients. We identify clonally expanded CD4 + T cells, including CCL5+ cells and T peripheral helper (Tph) cells, which show a prominent transcriptomic signature of recent activation and effector function. CD8 + T cells show higher oligoclonality than CD4 + T cells, with the largest synovial clones enriched in GZMK+ cells. CD8 + T cells with possibly virus-reactive TCRs are distributed across transcriptomic clusters. In the B cell compartment, NR4A1+ activated B cells, and plasma cells are enriched in the synovium and demonstrate substantial clonal expansion. We identify synovial plasma cells that share BCRs with synovial ABC, memory, and activated B cells. Receptor-ligand analysis predicted IFNG and TNFRSF members as mediators of synovial Tph-B cell interactions. Together, these results reveal clonal relationships between functionally distinct lymphocyte populations that infiltrate the synovium of patients with RA. Activated B cells and T cells accumulate within joints of patients with rheumatoid arthritis. Here, the authors use single-cell transcriptome and repertoire profiling to identify clonally expanded synovial B cells and T cells and define their phenotypes and predicted cell-cell interactions.

Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer–gene maps from disease-relevant tissues. Building enhancer–gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer–gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer–gene maps, essential for defining noncoding variant function. SCENT is a nonparametric method that models association between chromatin accessibility and gene expression in single-cell multimodal datasets, enabling construction of cell-type-specific enhancer–gene maps to aid mapping of candidate causal variants and genes for common diseases.

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis- eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses. scHLApers is an analysis pipeline that quantifies single-cell expression of HLA genes using a personalized genomic reference. Mapping of HLA expression quantitative trait loci at single-cell resolution identifies dynamic effects across cell states.