Biology subjects

Bykerk, V. P.

Publications and source records attributed to Bykerk, V. P..

7 recordsLinked to original sources

bioRxiv2023

Clonal associations of lymphocyte subsets and functional states revealed by single cell antigen receptor profiling of T and B cells in rheumatoid arthritis synovium

Rheumatoid arthritis (RA) is an autoimmune disease initiated by antigen-specific T cells and B cells, which promote synovial inflammation through a complex set of interactions with innate immune and stromal cells. To better understand the phenotypes and clonal relationships of synovial T and B cells, we performed single-cell RNA and repertoire sequencing on paired synovial tissue and peripheral blood samples from 12 donors with seropositive RA ranging from early to chronic disease. Paired transcriptomic-repertoire analyses highlighted 3 clonally distinct CD4 T cells populations that were enriched in RA synovium: T peripheral helper (Tph) and T follicular helper (Tfh) cells, CCL5+ T cells, and T regulatory cells (Tregs). Among these cells, Tph cells showed a unique transcriptomic signature of recent T cell receptor (TCR) activation, and clonally expanded Tph cells expressed an elevated transcriptomic effector signature compared to non-expanded Tph cells. CD8 T cells showed higher oligoclonality than CD4 T cells, and the largest CD8 T cell clones in synovium were highly enriched in GZMK+ cells. TCR analyses revealed CD8 T cells with likely viral-reactive TCRs distributed across transcriptomic clusters and definitively identified MAIT cells in synovium, which showed transcriptomic features of TCR activation. Among B cells, non-naive B cells including age-associated B cells (ABC), NR4A1+ activated B cells, and plasma cells, were enriched in synovium and had higher somatic hypermutation rates compared to blood B cells. Synovial B cells demonstrated substantial clonal expansion, with ABC, memory, and activated B cells clonally linked to synovial plasma cells. Together, these results reveal clonal relationships between functionally distinct lymphocyte populations that infiltrate RA synovium.

immunology↗

bioRxiv2019

HBEGF+ macrophages identified in rheumatoid arthritis promote joint tissue invasiveness and are reshaped differentially by medications

Macrophages tailor their function to the signals found in tissue microenvironments, taking on a wide spectrum of phenotypes. In human tissues, a detailed understanding of macrophage phenotypes is limited. Using single-cell RNA-sequencing, we define distinct macrophage subsets in the joints of patients with the autoimmune disease rheumatoid arthritis (RA), which affects ~1% of the population. The subset we refer to as HBEGF+ inflammatory macrophages is enriched in RA tissues and shaped by resident fibroblasts and the cytokine TNF. These macrophages promote fibroblast invasiveness in an EGF receptor dependent manner, indicating that inflammatory intercellular crosstalk reshapes both cell types and contributes to fibroblast-mediated joint destruction. In an ex vivo tissue assay, the HBEGF+ inflammatory macrophage is targeted by several anti-inflammatory RA medications, however, COX inhibition redirects it towards a different inflammatory phenotype that is also expected to perpetuate pathology. These data highlight advances in understanding the pathophysiology and drug mechanisms in chronic inflammatory disorders can be achieved by focusing on macrophage phenotypes in the context of complex interactions in human tissues. One Sentence SummaryA newly identified human macrophage phenotype from patients with the autoimmune condition RA is found to promote joint tissue invasiveness and demonstrates variable sensitivities to anti-inflammatory medications used to treat the disease.

immunology↗

bioRxiv2018

Defining Inflammatory Cell States in Rheumatoid Arthritis Joint Synovial Tissues by Integrating Single-cell Transcriptomics and Mass Cytometry

To define the cell populations in rheumatoid arthritis (RA) driving joint inflammation, we applied single-cell RNA-seq (scRNA-seq), mass cytometry, bulk RNA-seq, and flow cytometry to sorted T cells, B cells, monocytes, and fibroblasts from 51 synovial tissue RA and osteoarthritis (OA) patient samples. Utilizing an integrated computational strategy based on canonical correlation analysis to 5,452 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics together revealed cell states expanded in RA synovia: THY1+HLAhigh sublining fibroblasts (OR=33.8), IL1B+ pro-inflammatory monocytes (OR=7.8), CD11c+T-bet+ autoimmune-associated B cells (OR=5.7), and PD-1+Tph/Tfh (OR=3.0). We also defined CD8+ T cell subsets characterized by GZMK+, GZMB+, and GNLY+ expression. Using bulk and single-cell data, we mapped inflammatory mediators to source cell populations, for example attributing IL6 production to THY1+HLAhigh fibroblasts and naive B cells, and IL1B to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis.

immunology↗

bioRxiv2018

High dimensional analyses of cells dissociated from cryopreserved synovial tissue

BackgroundDetailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership (AMP) RA/SLE network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples.\n\nMethodsMultiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10%-DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T cell, B cell, and macrophage suspensions for bulk population RNA-seq and plate-based single cell CEL-Seq2 RNA-seq.\n\nResultsUpon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with [~]30 arthroplasty and [~]20 biopsy samples yielded a consensus digestion protocol using 100{micro}g/mL of Liberase TL enzyme. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished: 1) diverse fibroblast phenotypes, 2) distinct populations of memory B cells and antibody-secreting cells, and 3) multiple CD4+ and CD8+ T cell activation states. Bulk RNA sequencing of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified.\n\nConclusionWe have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers.

immunology↗

bioRxiv2017

Reverse Association Of Single Cells To Rheumatoid Arthritis Accounting For Mixed Effects Identifies An Expanded CD27- HLA-DR+ Effector Memory CD4+ T Cell Population

AO_SCPLOWBSTRACTC_SCPLOWHigh dimensional single-cell analyses have dramatically improved the ability to resolve complex mixtures of cells from human disease samples; however, identifying disease-associated cell types or cell states in patient samples remains challenging due to technical and inter-individual variation. Here we present Mixed effects modeling of Associations of Single Cells (MASC), a novel reverse single cell association strategy for testing whether case-control status influences the membership of single cells in any of multiple cellular subsets while accounting for technical confounds and biological variation. Applying MASC to mass cytometry analyses of CD4+ T cells from blood of rheumatoid arthritis (RA) patients and controls revealed a significantly expanded population of CD4+ T cells, identified as CD27- HLA-DR+ effector memory cells, in RA patients (OR = 1.7; p = 1.1 x 10-3). The frequency of CD27- HLA-DR+ cells was similarly elevated in blood samples from a second RA patient cohort, and CD27- HLA-DR+ cell frequency decreased in RA patients who respond to immunosuppressive therapy. Compared to peripheral blood, synovial fluid and synovial tissue samples from RA patients contained [~]5-fold higher frequencies of CD27- HLA-DR+ cells, which comprised [~]10% of synovial CD4+ T cells. We find that CD27- HLA-DR+ cells are abundant producers of IFN-{gamma} and also express perforin and granzyme A at elevated levels. Thus MASC identified the expansion of a unique Th1 skewed effector T cell population with cytotoxic capacity in RA. We propose that MASC is a broadly applicable method to identify disease-associated cell populations in high-dimensional single cell data.\n\nOO_SCPLOWNEC_SCPLOW SO_SCPLOWENTENCEC_SCPLOW SO_SCPLOWUMMARYC_SCPLOWMixed-effects regression of single cells identifies a cytotoxic Th1-like CD4+ T cell subset while accounting for inter-individual and technical variation.

bioinformatics↗

bioRxiv2017

Single Cell Transcriptomics And Flow Cytometry Reveal Disease-Associated Fibroblast Subsets In Rheumatoid Arthritis

Fibroblasts mediate normal tissue matrix remodeling, but they can cause fibrosis or tissue destruction following chronic inflammation. In rheumatoid arthritis (RA), synovial fibroblasts expand, degrade cartilage, and drive joint inflammation. Little is known about fibroblast heterogeneity or if aberrations in fibroblast subsets relate to disease pathology. Here, we used an integrative strategy, including bulk transcriptomics on targeted subpopulations and unbiased single-cell transcriptomics, to analyze fibroblasts from synovial tissues. We identify 7 phenotypic fibroblast subsets with distinct surface protein phenotypes, and these collapsed into 3 subsets based on transcriptomics data. One subset expressing PDPN, THY1, but lacking CD34 was 3-fold expanded in RA relative to osteoarthritis (P=0.007); most of these cells expressed CDH11. The subsets were found to differ in expression of cytokines and matrix metalloproteinases, localization in synovial microanatomy, and in response to TNF. Our approach provides a template to identify pathogenic stromal cellular subsets in complex diseases.

immunology↗

bioRxiv2017

Single-Cell RNA-Seq Of Rheumatoid Arthritis Synovial Tissue Using Low Cost Microfluidic Instrumentation

Droplet-based single cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While these approaches offer the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective, reliable, and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we have developed a microfluidic control instrument that can be easily assembled from 3D printed parts and commercially available components costing approximately $540. We adapted this instrument for massively parallel scRNA-seq and deployed it in a clinical environment to perform single cell transcriptome profiling of disaggregated synovial tissue from a rheumatoid arthritis patient. We sequenced 8,716 single cells from a synovectomy, revealing 16 transcriptomically distinct clusters. These encompass a comprehensive and unbiased characterization of the autoimmune infiltrate, including inflammatory T and NK subsets that contribute to disease biology. Additionally, we identified fibroblast subpopulations that are demarcated via THY1 (CD90) and CD55 expression. Further experiments confirm that these represent synovial fibroblasts residing within the synovial intimal lining and subintimal lining, respectively, each under the influence of differing microenvironments. We envision that this instrument will have broad utility in basic and clinical settings, enabling low-cost and routine application of microfluidic techniques, and in particular single-cell transcriptome profiling.

genomics↗