Biology subjects

Sumida, T. S.

Publications and source records attributed to Sumida, T. S..

8 recordsLinked to original sources

bioRxiv2025

Inflamed Microglia like Macrophages in the Central Nervous System of Prodromal Parkinson's Disease

We hypothesized that prodromal Parkinsons Disease (PD), characterized by REM Sleep Behavior Disorder and hyposmia, is an inflammatory disorder initiated in the gut that evolves into a neurodegenerative process manifest as classical PD. To test this hypothesis, we performed single-cell RNAseq analysis of cerebrospinal fluid (CSF) and blood from 118 individuals, comparing healthy subjects with prodromal PD and manifest PD to patients with the central nervous system (CNS) autoimmune disease, multiple sclerosis (MS). Surprisingly, we identified increased numbers of immune cells in the CSF of patients with prodromal PD. Single-cell RNA sequencing revealed increases in CSF-specific microglia-like macrophages with enhanced JAK-STAT and TNF signaling signatures in prodromal PD. CSF macrophages exhibited similar transcriptional profiles to dural macrophages and gut muscularis macrophages from -synuclein-expressing PD model mice. Finally, shared memory T cell clones were found in humans between gut and CSF T cells. These findings uncover a myeloid-mediated TNF inflammatory process in the CNS of patients with prodromal PD, with an immunological linkage between the gut and the CNS.

immunology↗

bioRxiv2024

A Nerve-Fibroblast Axis in Mammalian Lung Fibrosis

Fibrosis contributes to incurable pathologies in vital organs including the lung. Myofibroblasts are fibrogenic effector cells that accumulate via incompletely understood mechanisms. We discovered that 1-adrenoreceptor expressing myofibroblasts receive sympathetic nerve-derived noradrenergic inputs in fibrotic mouse and human lungs. We combined optical clearing, whole lung imaging, cell-specific gene deletion in sympathetic nerves and myofibroblasts, pharmacologic interventions, sympathetic nerve co-culture and precision-cut lung slices, with analysis of bronchoalveolar lavage fluid, lung tissues, single-cell RNA sequencing datasets, and isolated lung fibroblasts from patients with diverse forms of pulmonary fibrosis to characterize a fibrogenic unit comprised of aberrantly patterned sympathetic nerves and 1-adrenoreceptor subtype D expressing myofibroblasts. The discovery of this previously undefined nerve-fibroblast axis that is conserved across species demonstrates the pivotal contribution of nerves to tissue remodeling and heralds a novel paradigm in fibrosis research.

cell biology↗

bioRxiv2024

A highly scalable approach to topic modelling in single-cell data by approximate pseudobulk projection

Probabilistic topic modelling has become essential in many types of single-cell data analysis. Based on probabilistic topic assignments in each cell, we identify the latent representation of cellular states, and topic-specific gene frequency vectors provide interpretable bases to be compared with known cell-type-specific marker genes. However, fitting a topic model on a large number of cells would require heavy computational resources-specialized computing units, computing time and memory. Here, we present a scalable approximation method customized for single-cell RNA-seq data analysis, termed ASAP, short for Annotating Single-cell data by Approximate Pseudobulk estimation. Our approach is more accurate than existing methods but requires orders of magnitude less computing time, leaving much lower memory consumption. We also show that our approach is widely applicable for atlas-scale data analysis; our method seamlessly integrates single-cell and bulk data in joint analysis, not requiring additional preprocessing or feature selection steps.

bioinformatics↗

bioRxiv2024

Systematic Analysis of Immune Changes after B-cell Depletion in Autoimmune Multiple Sclerosis

Multiple sclerosis (MS) is a complex genetically mediated autoimmune disease of the central nervous system where anti-CD20-mediated B cell depletion is remarkably effective in the treatment of early disease. While previous studies investigated the effect of B cell depletion on select immune cell subsets using flow cytometry-based methods, the therapeutic impact on patient immune landscape is unknown. In this study, we explored how a therapy-driven "in vivo perturbation" modulates the diverse immune landscape by measuring transcriptomic granularity with single-cell RNA sequencing (scRNAseq). We demonstrate that B cell depletion leads to cell type-specific changes in the abundance and function of CSF macrophages and peripheral blood monocytes. Specifically, a CSF-specific macrophage population with an anti-inflammatory transcriptomic signature and peripheral CD16+ monocytes increased in frequency post-B cell depletion. This was accompanied by increases in TNF messenger RNA and protein in monocytes post-B cell depletion, consistent with the finding that anti-TNF treatment exacerbates autoimmune activity in MS. In parallel, B cell depletion induced changes in peripheral CD4+ T cell populations, including increases in the frequency of TIGIT+ regulatory T cells and marked decreases in the frequency of myelin peptide loaded-tetramer binding CD4+ T cells. Collectively, this study provides an exhaustive transcriptomic map of immunological changes, revealing different mechanisms of action contributing to the high efficacy in B cell depletion treatment of MS.

immunology↗

bioRxiv2023

Peripheral Blood Single-Cell Sequencing Uncovers Common and Specific Immune Aberrations in Fibrotic Lung Diseases

Rationale and ObjectivesThe extent and commonality of peripheral blood immune aberrations in fibrotic interstitial lung diseases are not well characterized. In this study, we aimed to identify common and distinct immune aberrations in patients with idiopathic pulmonary fibrosis (IPF) and fibrotic hypersensitivity pneumonitis (FHP) using cutting-edge single-cell profiling technologies. MethodsSingle-cell RNA sequencing was performed on patients and healthy controls peripheral blood and bronchoalveolar lavage samples using 10X Genomics 5 gene expression and V(D)J profiling. Cell type composition, transcriptional profiles, cellular trajectories and signaling, and T and B cell receptor repertoires were studied. The standard Seurat R pipeline was followed for cell type composition and differential gene expression analyses. Transcription factor activity was imputed using the DoRothEA-VIPER algorithm. Pseudotime analyses were conducted using Monocle3, while RNA velocity analyses were performed with Velocyto, scVelo, and CellRank. Cell-cell connectomics were assessed using the Connectome R package. V(D)J analyses were conducted using CellRanger and Immcantation frameworks. Across all analyses, disease group differences were assessed using the Wilcoxon rank-sum test. Measurements and Main Results327,990 cells from 83 samples were profiled. Overall, changes in monocytes were common to IPF and FHP, whereas lymphocytes exhibited disease-specific aberrations. Both diseases displayed enrichment of CCL3hi/CCL4hi CD14+ monocytes (p<2.2e-16) and S100Ahi CD14+ monocytes (p<2.2e-16) versus controls. Trajectory and RNA velocity analysis suggested that pro-fibrotic macrophages observed in BAL originated from peripheral blood monocytes. Lymphocytes exhibited disease-specific aberrations, with CD8+ GZMKhi T cells and activated B cells primarily enriched in FHP patients. V(D)J analyses revealed unique T and B cell receptor complementarity-determining region 3 (CDR3) amino acid compositions (p<0.05) in FHP and significant IgA enrichment in IPF (p<5.2e-7). ConclusionsWe identified common and disease-specific immune mechanisms in IPF and FHP; S100Ahi monocytes and SPP1hi macrophages are common to IPF and FHP, whereas GMZKhi T lymphocytes and T and B cell receptor repertoires were unique in FHP. Our findings open novel strategies for the diagnosis and treatment of IPF and FHP.

genomics↗

bioRxiv2022

An Autoimmune Transcriptional Circuit Driving Foxp3+ Regulatory T cell Dysfunction

Autoimmune diseases, among the most common disorders of young adults, are mediated by genetic and environmental factors. While CD4+Foxp3+ regulatory T cells (Tregs) play a central role in preventing autoimmunity, the molecular mechanism underlying their dysfunction is unknown. Here, we performed comprehensive transcriptomic and epigenomic profiling of Tregs in the autoimmune disease multiple sclerosis (MS) to identify central transcriptional programs regulating human autoimmunity. We discovered that upregulation of a primate-specific short PRDM1 isoform (PRDM1-S) induces SGK1 independent from evolutionally conserved long PRDM1, leading to destabilization of Foxp3 and Treg dysfunction. This aberrant PRDM1-S/SGK1 axis is shared among other autoimmune diseases. Furthermore, by chromatin landscape profiling in MS Tregs we identified a PRDM1-S specific cis-regulatory element associated with enriched binding of AP-1/IRF transcription factors. Our study identifies evolutionally emerged PRDM1-S and epigenetic priming of AP-1/IRF as key drivers of pathogenic Treg programs leading to human autoimmune disease.

immunology↗

bioRxiv2021

ProtAnno, an Automated Cell Type Annotation Tool for Single Cell Proteomics Data that Integrates Information from Multiple Reference Sources

Compared with sequencing-based global genomic profiling, cytometry labels targeted surface markers on millions of cells in parallel either by conjugated rare earth metal particles or Unique Molecular Identifier (UMI) barcodes. Correct annotation of these cells to specific cell types is a key step in the analysis of these data. However, there is no computational tool that automatically annotates single cell proteomics data for cell type inference. In this manuscript, we propose an automated single cell proteomics data annotation approach called ProtAnno to facilitate cell type assignments without laborious manual gating. ProtAnno is designed to incorporate information from annotated single cell RNA-seq (scRNA-seq), CITE-seq, and prior data knowledge (which can be imprecise) on biomarkers for different cell types. We have performed extensive simulations to demonstrate the accuracy and robustness of ProtAnno. For several single cell proteomics datasets that have been manually labeled, ProtAnno was able to correctly label most single cells. In summary, ProtAnno offers an accurate and robust tool to automate cell type annotations for large single cell proteomics datasets, and the analysis of such annotated cell types can offer valuable biological insights.

bioinformatics↗

bioRxiv2020

Type I Interferon Transcriptional Network Regulates Expression of Coinhibitory Receptors in Human T cells

While inhibition of T cell co-inhibitory receptors has revolutionized cancer therapy, the mechanisms governing their expression on human T cells have not been elucidated. Type 1 interferon (IFN-I) modulates T cell immunity in viral infection, autoimmunity, and cancer, and may facilitate induction of T cell exhaustion in chronic viral infection1,2. Here we show that IFN-I regulates co-inhibitory receptors expression on human T cells, inducing PD-1/TIM-3/LAG-3 while surprisingly inhibiting TIGIT expression. High-temporal-resolution mRNA profiling of IFN-I responses enabled the construction of dynamic transcriptional regulatory networks uncovering three temporal transcriptional waves. Perturbation of key transcription factors on human primary T cells revealed both canonical and non-canonical IFN-I transcriptional regulators, and identified unique regulators that control expression of co-inhibitory receptors. To provide direct in vivo evidence for the role of IFN-I on co-inhibitory receptors, we then performed single cell RNA-sequencing in subjects infected with SARS-CoV-2, where viral load was strongly associated with T cell IFN-I signatures. We found that the dynamic IFN-I response in vitro closely mirrored T cell features with acute IFN-I linked viral infection, with high LAG3 and decreased TIGIT expression. Finally, our gene regulatory network identified SP140 as a key regulator for differential LAG3 and TIGIT expression. The construction of co-inhibitory regulatory networks induced by IFN-I with identification of unique transcription factors controlling their expression may provide targets for enhancement of immunotherapy in cancer, infectious diseases, and autoimmunity.

immunology↗