Biology subjects

Raychaudhuri, S.

Publications and source records attributed to Raychaudhuri, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2021

Neutrophil-associated responses to Vibrio cholerae infection in a natural host model

Vibrio cholerae, the cause of human cholera, is an aquatic bacterium found in association with a variety of animals in the environment, including many teleost fish species. V. cholerae infection induces a pro-inflammatory response followed by a non-inflammatory convalescent phase. Neutrophils are integral to this early immune response. However, the relationship between the neutrophil-associated protein calprotectin and V. cholerae has not been investigated, nor have the effects of limiting transition metals on V. cholerae growth. Zebrafish are useful as a natural V. cholerae model as the entire infectious cycle can be recapitulated in the presence of an intact intestinal microbiome and mature immune responses. Here, we demonstrate that zebrafish produce a significant neutrophil, IL-8, and calprotectin response following V. cholerae infection. Bacterial growth was completely inhibited by purified calprotectin protein or the chemical chelator TPEN, but growth was recovered by addition of transition metals zinc and manganese. Expression of downstream calprotectin targets also significantly increased in the zebrafish. These findings are the first to illuminate the role of calprotectin and nutritional immunity in combating V. cholerae infection. Inhibition of V. cholerae growth through metal limitation may provide new approaches in the development of anti-V. cholerae therapeutics. This study also establishes a major role for calprotectin in combating infectious diseases in zebrafish.

microbiology↗

bioRxiv2021

Modeling memory T cell states at single-cell resolution identifies in vivo state-dependence of eQTLs influencing disease

Many non-coding genetic variants cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated by gene-regulation differences between cell states. T cells, for example, have fluid, multifaceted functional states in vivo that cannot be modeled in eQTL studies that aggregate cells. Here, we modeled T cell states and eQTLs at single-cell resolution. Using >500,000 resting memory T cells from 259 Peruvians, we found over one-third of the 6,511 cis-eQTLs had state-dependent effects. By integrating single-cell RNA and surface protein measurements, we defined continuous cell states that explained more eQTL variation than discrete states like CD4+ or CD8+ T cells and could have opposing effects on independent eQTL variants in a locus. Autoimmune variants were enriched in cell-state-dependent eQTLs, such as a rheumatoid-arthritis variant near ORMDL3 strongest in cytotoxic CD8+ T cells. These results argue that fine-grained cell state context is crucial to understanding disease-associated eQTLs.

genetics↗

bioRxiv2021

Repertoire analyses reveal TCR sequence features that influence T cell fate

T cells acquire a regulatory phenotype when their T cell receptors (TCRs) experience an intermediate-high affinity interaction with a self-peptide presented on MHC. Using TCR sequences from FACS-sorted human cells, we identified TCR features that shape affinity to these self-peptide-MHC complexes, finding that 1) CDR3{beta} hydrophobicity and 2) certain TRBV genes promote Treg fate. We developed a scoring system for TCR-intrinsic regulatory potential (TiRP) and found that within the tumor microenvironment clones exhibiting Treg-Tconv plasticity had higher TiRP than expanded clones maintaining the Tconv phenotype. To elucidate drivers of these predictive TCR features, we examined the two elements of the Treg TCR ligand separately: the self-peptide via murine Tregs, and the human MHC II molecule via human memory Tconvs. These analyses revealed that CDR3{beta} hydrophobicity promotes reactivity to self-peptides, while TRBV gene usage shapes the TCRs general propensity for MHC II-restricted activation.

immunology↗

bioRxiv2021

Leveraging single-cell ATAC-seq to identify disease-critical fetal and adult brain cell types

Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and early work on integrating GWAS with scRNA-seq has shown promise, but work on integrating GWAS with scATAC-seq has been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases and traits (average N =298K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (resp. adult) brain cell types for 22 (resp. 23) of 28 traits using scATAC-seq data, and for 8 (resp. 17) of 28 traits using scRNA-seq data. Notable findings using scATAC-seq data included highly significant enrichments of fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases and traits, and inform future analyses of other diseases/traits.

genetics↗

bioRxiv2021

Single cell analysis of RA synovial B cells reveals a dynamic spectrum of ectopic lymphoid B cell activation and hypermutation characterized by NR4A nuclear receptor expression

Ectopic lymphoid structures (ELS) can develop in rheumatoid arthritis (RA) synovial tissue, but the precise pathways of B cell activation and selection are not well understood. Here, we identified a unique B cell population in the synovium characterized by co-expression of a family of orphan nuclear receptors, NR4A1 (also known as NUR77), NR4A2 (NURR1) and NR4A3 (NOR1), that is highly enriched at both early and late stages of RA. NR4A B cells are rare in healthy peripheral blood, RA blood, and SLE kidney, but share markers with blood transcriptomic signatures that peak during RA disease flare. Using combined single cell transcriptomics and B cell receptor (BCR) sequencing, we demonstrate that NR4A synovial B cells have an activated transcriptomic profile that significantly overlaps with germinal center (GC) light zone (LZ) B cells and an accrual of somatic hypermutation that correlates with loss of naive B cell status. NR4A B cells uniquely co-express lymphotoxin {beta} and IL6, supporting important functions in ELS promotion and pro-inflammatory cytokine production. Further, the presence of shared clones in this activated B cell state and NR4A expressing synovial plasma cells (PC) and the rapid up-regulation with BCR stimulation points to in situ differentiation. Taken together, we identified a dynamic progression of B cell activation in RA synovial ELS, with NR4A transcription factors having an important role in antigen activation and local adaptive immune responses. One sentence summaryB cells in the rheumatoid arthritis synovium undergo a spectrum of in situ activation, with the NR4A family of transcription factors having an important role in antigen stimulation, local adaptive immunity, and pathological B cell responses.

immunology↗

bioRxiv2021

A sex-specific evolutionary interaction between ADCY9 and CETP

Pharmacogenomic studies have revealed associations between rs1967309 in the adenylyl cyclase type 9 (ADCY9) gene and clinical responses to the cholesteryl ester transfer protein (CETP) modulator dalcetrapib, however, the mechanism behind this interaction is still unknown. Here, we characterized selective signals at the locus associated with the pharmacogenomic response in human populations and we show that rs1967309 region exhibits signatures of positive selection in several human populations. Furthermore, we identified a variant in CETP, rs158477, which is in long-range linkage disequilibrium with rs1967309 in the Peruvian population. The signal is mainly seen in males, a sex-specific result that is replicated in the LIMAA cohort of over 3,400 Peruvians. Analyses of RNA-seq data further suggest an epistatic interaction on CETP expression levels between the two SNPs in multiple tissues, which also differs between males and females. We also detected interaction effects of the two SNPs with sex on cardiovascular phenotypes in the UK Biobank, in line with the sex-specific genotype associations found in Peruvians at these loci. We propose that ADCY9 and CETP coevolved during recent human evolution due to sex-specific selection, which points towards a biological link between dalcetrapibs pharmacogene ADCY9 and its therapeutic target CETP.

genetics↗

bioRxiv2021

Axes of inter-sample variability among transcriptional neighborhoods reveal disease associated cell states in single-cell data

As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples and associate with sample attributes like clinical phenotypes. Current statistical approaches typically map cells to cell-type clusters and examine sample differences through that lens alone. Here we present covarying neighborhood analysis (CNA), an unbiased method to identify cell populations of interest with greater flexibility and granularity. CNA characterizes dominant axes of variation across samples by identifying groups of very small regions in transcriptional space--termed neighborhoods--that covary in abundance across samples, suggesting shared function or regulation. CNA can then rigorously test for associations between any sample-level attribute and the abundances of these covarying neighborhood groups. We show in simulation that CNA enables more powerful and accurate identification of disease-associated cell states than a cluster-based approach. When applied to published datasets, CNA captures a Notch activation signature in rheumatoid arthritis, redefines monocyte populations expanded in sepsis, and identifies a previously undiscovered T-cell population associated with progression to active tuberculosis.

bioinformatics↗

bioRxiv2021

Dynamin is primed at endocytic sites for ultrafast endocytosis

Dynamin mediates fission of vesicles from the plasma membrane during endocytosis. Typically, dynamin is recruited from the cytosol to endocytic sites, requiring seconds to tens of seconds. However, ultrafast endocytosis in neurons internalizes vesicles as quickly as 50 ms during synaptic vesicle recycling. Here we demonstrate that Dynamin 1 is pre-recruited to endocytic sites for ultrafast endocytosis. Specifically, Dynamin 1xA, a splice variant of Dynamin 1, interacts with Syndapin 1 to form molecular condensates on the plasma membrane when the proline-rich domain of this variant is dephosphorylated. When this domain is mutated to include phosphomimetic residues or Syndapin 1s dynamin-interacting domain is mutated, Dynamin 1xA becomes diffuse, and consequently, ultrafast endocytosis slows down by [~]100-fold. Mechanistically, Syndapin 1 acts as an adaptor by binding the plasma membrane and stores Dynamin 1xA at endocytic sites. This cache bypasses the recruitment step and accelerates endocytosis at synapses.

neuroscience↗

bioRxiv2021

IL-1-driven stromal-neutrophil interaction in deep ulcers defines a pathotype of therapy non-responsive inflammatory bowel disease

Current inflammatory bowel disease (IBD) therapies are ineffective in a high proportion of patients. Combining bulk and single-cell transcriptomics, quantitative histopathology, and in situ localisation, we describe heterogeneity of the tissular inflammatory response in IBD treatment failure. Among inflammatory pathotypes, we found high neutrophil infiltration, activation of fibroblasts, and vascular remodelling at sites of deep ulceration was a feature of non-response to several anti-inflammatory therapies. Activated fibroblasts in the ulcer bed display neutrophil chemoattractant properties that are IL-1R- but not TNF-dependent. The identification of distinct, localised, tissular pathotypes associated with treatment non-response will aid precision targeting of current therapeutics and provide a biological rationale for IL-1 signalling blockade in ulcerating disease.

immunology↗

bioRxiv2021

Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases

Pro-inflammatory fibroblasts are critical to pathogenesis in rheumatoid arthritis, inflammatory bowel disease, interstitial lung disease, and Sjogrens syndrome, and represent a novel therapeutic target for chronic inflammatory disease. However, the heterogeneity of fibroblast phenotypes, exacerbated by the lack of a common cross-tissue taxonomy, has limited the understanding of which pathways are shared by multiple diseases. To investigate, we profiled patient-derived fibroblasts from inflamed and non-inflamed synovium, intestine, lung, and salivary glands with single-cell RNA-sequencing. We integrated all fibroblasts into a multi-tissue atlas to characterize shared and tissue-specific phenotypes. Two shared clusters, CXCL10+CCL19+ immune-interacting and SPARC+COL3A1+ vascular-interacting fibroblasts were expanded in all inflamed tissues and additionally mapped to dermal analogues in a public atopic dermatitis atlas. We further confirmed these human pro-inflammatory fibroblasts in animal models of lung, joint, and intestinal inflammation. This work represents the first cross-tissue, single-cell fibroblast atlas revealing shared pathogenic activation states across four chronic inflammatory diseases.

genomics↗

bioRxiv2020

Maximizing statistical power to detect clinically associated cell states with scPOST

As advances in single-cell technologies enable the unbiased assay of thousands of cells simultaneously, human disease studies are able to identify clinically associated cell states using case-control study designs. These studies require precious clinical samples and costly technologies; therefore, it is critical to employ study design principles that maximize power to detect cell state frequency shifts between conditions, such as disease versus healthy. Here, we present single-cell Power Simulation Tool (scPOST), a method that enables users to estimate power under different study designs. To approximate the specific experimental and clinical scenarios being investigated, scPOST takes prototype (public or pilot) single-cell data as input and generates large numbers of single-cell datasets in silico. We use scPOST to perform power analyses on three independent single-cell datasets that span diverse experimental conditions: a batch-corrected 21-sample rheumatoid arthritis dataset (5,265 cells) from synovial tissue, a 259-sample tuberculosis progression dataset (496,517 memory T cells) from peripheral blood mononuclear cells (PBMCs), and a 30-sample ulcerative colitis dataset (235,229 cells) from intestinal biopsies. Over thousands of simulations, we consistently observe that power to detect frequency shifts in cell states is maximized by larger numbers of independent clinical samples, reduced batch effects, and smaller variation in a cell states frequency across samples.

bioinformatics↗

bioRxiv2020

Efficient and precise single-cell reference atlas mapping with Symphony

Recent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map query cells onto complex, multimillion-cell reference atlases to rapidly identify relevant cell states and phenotypes. We present Symphony (https://github.com/immunogenomics/symphony), an algorithm for building integrated reference atlases of millions of cells in a convenient, portable format that enables efficient query mapping within seconds. Symphony localizes query cells within a stable low-dimensional reference embedding, facilitating reproducible downstream transfer of reference-defined annotations to the query. We demonstrate the power of Symphony by (1) mapping a multi-donor, multi-species query to predict pancreatic cell types, (2) localizing query cells along a developmental trajectory of human fetal liver hematopoiesis, and (3) inferring surface protein expression with a multimodal CITE-seq atlas of memory T cells.

bioinformatics↗

bioRxiv2020

Localized Proteotoxic Stress in Mitochondrial Intermembrane Space and Matrix Elicits Sub-compartment Specific Response Pathways Governed by Unique Modulators

The double-membrane-bound architecture of mitochondria, essential for ATP production, sub-divides the organelle into inter-membrane space (IMS) and matrix. IMS and matrix possess contrasting oxido-reductive environments and distinct protein quality control (PQC) machineries resulting different protein folding environments. To understand the nature of stress response elicited by equivalent proteotoxic stress to sub-mitochondrial compartments, we fused well-described bipartite or matrix-targeting signal sequences to misfolding and aggregation-prone stressor proteins to target and impart stress to yeast mitochondrial IMS or matrix. We show, mitochondrial proteotoxicity leads to growth arrest of yeast cells of varying degrees depending on nature of stressor proteins and the intra-mitochondrial location of stress. Next, using transcriptomics and proteomics, we report a comprehensive stress response elicited by two types of targeting signal-fused stressor proteins. Among global responses by mitochondria-targeted stressors by both types of signal sequences, an adaptive response of abrogated mitochondrial respiration and concomitant upregulation of glycolysis is uncovered. Beyond shared stress responses, specific signatures due to stress within mitochondrial sub-compartments are also revealed. We report that bipartite signal sequence-fused stressor proteins eliciting stress to IMS, leads to specific upregulation of IMS-chaperones and TOM complex components. In contrast, matrix-targeted stressors lead to specific upregulation of matrix-chaperones and cytosolic PQC components. Finally, by systematic genetic interaction using deletion strains of differentially upregulated genes, we found prominent modulatory role of TOM complex components during IMS-stress response. In contrast, VMS1 markedly modulates the stress response originated from matrix.

cell biology↗

bioRxiv2020

IFN-γ and TNF-α drive a CXCL10+ CCL2+ macrophage phenotype expanded in severe COVID-19 and other diseases with tissue inflammation

Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies. Using an integrative strategy, we built a reference by meta-analyzing > 300,000 immune cells from COVID-19 and 5 inflammatory diseases including rheumatoid arthritis (RA), Crohns disease (CD), ulcerative colitis (UC), lupus, and interstitial lung disease. Our cross-disease analysis revealed that an FCN1+ inflammatory macrophage state is common to COVID-19 bronchoalveolar lavage samples, RA synovium, CD ileum, and UC colon. We also observed that a CXCL10+ CCL2+ inflammatory macrophage state is abundant in severe COVID-19, inflamed CD and RA, and expresses inflammatory genes such as GBP1, STAT1, and IL1B. We found that the CXCL10+ CCL2+ macrophages are transcriptionally similar to blood-derived macrophages stimulated with TNF- and IFN-{gamma} ex vivo. Our findings suggest that IFN-{gamma}, alongside TNF-, might be a key driver of this abundant inflammatory macrophage phenotype in severe COVID-19 and other inflammatory diseases, which may be targeted by existing immunomodulatory therapies.

genomics↗

bioRxiv2020

Release sites are positioned to activate NMDA receptors

Neurotransmitter is released synchronously and asynchronously following an action potential. The release sites of these two phases are segregated within an active zone, with asynchronous release sites enriched near the center. Here we demonstrate that synchronous and asynchronous release sites are aligned with AMPA receptor and NMDA receptor clusters, respectively. Computational simulations indicate that this spatial and temporal arrangement of release ensures maximal membrane depolarization through AMPA receptors, alleviating the pore-blocking magnesium leading to greater activation of NMDA receptors. Together, these results suggest that release sites are organized to efficiently activate NMDA receptors.

neuroscience↗

bioRxiv2020

Multimodal memory T cell profiling identifies a reduction in a polyfunctional Th17 state associated with tuberculosis progression

Mycobacterium tuberculosis (M.tb) results in 10 million active tuberculosis (TB) cases and 1.5 million deaths each year1, making it the worlds leading infectious cause of death2. Infection leads to either an asymptomatic latent state or TB disease. Memory T cells have been implicated in TB disease progression, but the specific cell states involved have not yet been delineated because of the limited scope of traditional profiling strategies. Furthermore, immune activation during infection confounds underlying differences in T cell state distributions that influence risk of progression. Here, we used a multimodal single-cell approach to integrate measurements of transcripts and 30 functionally relevant surface proteins to comprehensively define the memory T cell landscape at steady state (i.e., outside of active infection). We profiled 500,000 memory T cells from 259 Peruvians > 4.7 years after they had either latent M.tb infection or active disease and defined 31 distinct memory T cell states, including a CD4+CD26+CD161+CCR6+ effector memory state that was significantly reduced in patients who had developed active TB (OR = 0.80, 95% CI: 0.73-0.87, p = 1.21 x 10-6). This state was also polyfunctional; in ex vivo stimulation, it was enriched for IL-17 and IL-22 production, consistent with a Th17-skewed phenotype, but also had more capacity to produce IFN{gamma} than other CD161+CCR6+ Th17 cells. Additionally, in progressors, IL-17 and IL-22 production in this cell state was significantly lower than in non-progressors. Reduced abundance and function of this state may be an important factor in failure to control M.tb infection.

immunology↗

bioRxiv2020

Genome-wide study identifies association between HLA-B*55:01 and penicillin allergy

BackgroundHypersensitivity reactions to drugs are often unpredictable and can be life-threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. MethodsWe extracted data from the electronic health records of 52,000 Estonian and 500,000 UK biobank participants to study the role of genetic variation in the occurrence of penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from up to 22,554 and 488,377 individuals from the Estonian and UK cohorts, respectively, to further fine-map the human leukocyte antigen (HLA) association and replicated our results in two additional cohorts involving a total of 1.14 million individuals. ResultsGenome-wide meta-analysis of penicillin allergy revealed a significant association located in the HLA region on chromosome 6. The signal was further fine-mapped to the HLA-B*55:01 allele (OR 1.47 95% CI 1.37-1.58, P-value 4.63x10-26) and confirmed by independent replication in two cohorts. The meta-analysis of all four cohorts in the study revealed a strong association of HLA-B*55:01 allele with penicillin allergy (OR 1.33 95% CI 1.29-1.37, P-value 2.23x10-72). In silico follow-up suggests a potential effect on T lymphocytes at HLA-B*55:01. ConclusionWe present the first robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.

genetics↗

bioRxiv2020

In silico integration of thousands of epigenetic datasets into 707 cell type regulatory annotations improves the trans-ethnic portability of polygenic risk scores

Poor trans-ethnic portability of polygenic risk score (PRS) models is a critical issue that may be partially due to limited knowledge of causal variants shared among populations. Hence, leveraging noncoding regulatory annotations that capture genetic variation across populations has the potential to enhance the trans-ethnic portability of PRS. To this end, we constructed a unique resource of 707 cell-type-specific IMPACT regulatory annotations by aggregating 5,345 public epigenetic datasets to predict binding patterns of 142 cell-type-regulating transcription factors across 245 cell types. With this resource, we partitioned the common SNP heritability of diverse polygenic traits and diseases from 111 GWAS summary statistics of European (EUR, average N=180K) and East Asian (EAS, average N=157K) origin. For 95 traits, we were able to identify a single IMPACT annotation most strongly enriched for trait heritability. Across traits, these annotations captured an average of 43.3% of heritability (se = 13.8%) with the top 5% of SNPs. Strikingly, we observed highly concordant polygenic trait regulation between populations: the same regulatory annotations captured statistically indistinguishable SNP heritability (fitted slope = 0.98, se = 0.04). Since IMPACT annotations capture both large and consistent proportions of heritability across populations, prioritizing variants in IMPACT regulatory elements may improve the trans-ethnic portability of PRS. Indeed, we observed that EUR PRS models more accurately predicted 21 tested phenotypes of EAS individuals when variants were prioritized by key IMPACT tracks (49.9% mean relative increase in R2). Notably, the improvement afforded by IMPACT was greater in the trans-ethnic EUR-to-EAS PRS application than in the EAS-to-EAS application (47.3% vs 20.9%, P < 1.7e-4). Overall, our study identifies a crucial role for functional annotations such as IMPACT to improve the trans-ethnic portability of genetic data, and this has important implications for future risk prediction models that work across populations.

genetics↗