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Raychaudhuri, S.

Publications and source records attributed to Raychaudhuri, S..

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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↗

Cytoplasmic sequestration of the RhoA effector mDiaphanous1 by Prohibitin2 promotes muscle differentiation

Adhesion and growth factor dependent signalling control muscle gene expression through common effectors, coupling cytoskeletal dynamics to transcriptional activation. Earlier, we showed that mDiaphanous1, an effector of adhesion-dependent RhoA-signalling promotes MyoD expression in myoblasts, linking contractility to lineage determination. Here, we report that paradoxically, mDia1 negatively regulates MyoD function in myotubes. Knockdown of endogenous mDia1 during differentiation enhances MyoD and Myogenin expression, while over-expression of mDia1{Delta}N3, a RhoA-independent mutant, suppresses Myogenin promoter activity and expression. We investigated mechanisms that may counteract mDia1 to promote Myogenin expression and timely differentiation by analysing mDia1-interacting proteins. We report that mDia1 has a stage-specific interactome, including Prohibitin2, MyoD, Akt2, and {beta}-Catenin, of which Prohibitin2 colocalises with mDia1 in cytoplasmic punctae and opposes mDia1 function in myotubes. Co-expression of mDia1-binding domains of Prohibitin2 reverses the anti-myogenic effects of mDia1{Delta}N3. Our results suggest that Prohibitin2 sequesters mDiaphanous1 to dampen its activity and finetune RhoA-mDiaphanous1 signalling to promote differentiation. Overall, we report that mDia1 is multi-functional signaling effector with opposing functions in different cellular stages, but is modulated by a differentiation-dependent interactome.\n\nSummary statementmDia1 has common and stage-specific functions in muscle cells. In myotubes, mDia1 is sequestered by an interacting protein Prohibitin2, which promotes Myogenin expression and mitigates mDia1s inhibitory effects on differentiation.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC=\"FIGDIR/small/283044v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (28K):\norg.highwire.dtl.DTLVardef@1b1578eorg.highwire.dtl.DTLVardef@1eb6b13org.highwire.dtl.DTLVardef@c2c913org.highwire.dtl.DTLVardef@1f1f9c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

A genome-wide innateness gradient defines the functional state of human innate T cells

Innate T cells (ITCs), including invariant natural killer T (iNKT) cells, mucosal-associated invariant T (MAIT) cells, and {gamma}{delta} T cell populations, use conserved antigen receptors generated by somatic recombination to respond to non-peptide antigens in an innate-like manner. Understanding where these cells fit in the scheme of immunity has been a puzzle since their discovery. Here, immunophenotyping of 101 individuals revealed that these populations account for as much as 25% of peripheral human T cells. To better understand these cells, we generated detailed gene expression profiles using low-input RNA-seq and confirmed key findings through protein-level and functional validation. Unbiased transcriptomic analyses revealed a continuous innateness gradient with adaptive T cells at one end followed by MAIT, iNKT, V{delta}1+ T, V{delta}2+ T, and natural killer cells at the other end. Innateness was characterized by decreased expression of translational machinery genes and reduced proliferative potential, which allowed for prioritization of effector functions, including rapid cytokine and chemokine production, and cytotoxicity. Thus, global transcriptional programs uncovered rapid proliferation and rapid effector functions as competing goals that respectively define adaptive and innate states.\n\nOne Sentence SummaryAdaptive and innate T cells align along a continuous innateness gradient, reflecting a trade-off between effector function and proliferative capacity.

immunology↗

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↗

Fine-mapping identifies causal variants for RA and T1D in DNASE1L3, SIRPG, MEG3, TNFAIP3 and CD28/CTLA4 loci

We fine-mapped 76 rheumatoid arthritis (RA) and type 1 diabetes (T1D) loci outside of the MHC. After sequencing 799 1kb regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We fine-mapped1,2 these loci in RA (11,475 cases, 15,870 controls)3, T1D (9,334 cases and 11,111 controls) 4 and combined datasets. We reduced the number of potential causal variants to [≤]5 in 8 RA and 11 T1D loci. We identified causal missense variants in five loci (DNASE1L3, SIRPG, PTPN22, SH2B3 and TYK2) and likely causal non-coding variants in six loci (MEG3, TNFAIP3, CD28/CTLA4, ANKRD55, IL2RA, REL/PUS10). Functional analysis confirmed allele specific binding and differential enhancer activity for three variants: the CD28/CTLA4 rs117701653 SNP, the TNFAIP3 rs35926684 indel, and the MEG3 rs34552516 indel. This study demonstrates the potential for dense genotyping and imputation to pinpoint missense and non-coding causal alleles.

genetics↗

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↗

Identification of drug eQTL interactions from repeat transcriptional and environmental measurements in a lupus clinical trial

BackgroundCytokines are critical to human disease and are attractive therapeutic targets given their widespread influence on gene regulation and transcription. Defining the downstream regulatory mechanisms influenced by cytokines is central to defining drug and disease mechanisms. One promising strategy is to use interactions between expression quantitative trait loci (eQTLs) and cytokine levels to define target genes and mechanisms.\n\nResultsIn a clinical trial for anti-IL-6 in patients with systemic lupus erythematosus we measured interferon (IFN) status, anti-IL-6 drug exposure and genome-wide gene expression at three time points (379 samples from 157 individuals). First, we show that repeat transcriptomic measurements increases the number of cis eQTLs identified compared to using a single time point by 64%. Then, after identifying 4,818 cis-eQTLs, we observed a statistically significant enrichment of in vivo eQTL interactions with IFN status (p<0.001 by permutation) and anti-IL-6 drug exposure (p<0.001). We observed 210 and 72 interactions for IFN and anti-IL-6 respectively (FDR<20%). Anti-IL-6 interactions have not yet been described while 99 of the IFN interactions are novel. Finally, we found transcription factor binding motifs interrupted by eQTL interaction SNPs, pointing to key regulatory mediators of these environmental stimuli and therefore potential therapeutic targets for autoimmune diseases. In particular, genes with IFN interactions are enriched for ISRE binding site motifs, while those with anti-IL-6 interactions are enriched for IRF4 motifs.\n\nConclusionThis study highlights the potential to exploit clinical trial data to discover in vivo eQTL interactions with therapeutically relevant environmental variables.

genomics↗

Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

Genetics can provide a systematic approach to discovering the tissues and cell types relevant for a complex disease or trait. Identifying these tissues and cell types is critical for following up on non-coding allelic function, developing ex-vivo models, and identifying therapeutic targets. Here, we analyze gene expression data from several sources, including the GTEx and PsychENCODE consortia, together with genome-wide association study (GWAS) summary statistics for 48 diseases and traits with an average sample size of 169,331, to identify disease-relevant tissues and cell types. We develop and apply an approach that uses stratified LD score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We detect tissue-specific enrichments at FDR < 5% for 34 diseases and traits across a broad range of tissues that recapitulate known biology. In our analysis of traits with observed central nervous system enrichment, we detect an enrichment of neurons over other brain cell types for several brain-related traits, enrichment of inhibitory over excitatory neurons for bipolar disorder but excitatory over inhibitory neurons for schizophrenia and body mass index, and enrichments in the cortex for schizophrenia and in the striatum for migraine. In our analysis of traits with observed immunological enrichment, we identify enrichments of T cells for asthma and eczema, B cells for primary biliary cirrhosis, and myeloid cells for Alzheimer's disease, which we validated with independent chromatin data. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signal.

genetics↗