Biology subjects

Raposo, C.

Publications and source records attributed to Raposo, C..

3 recordsLinked to original sources

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↗

bioRxiv2021

A structured evaluation of cryopreservation in generating single cell transcriptomes from cerebrospinal fluid

ImportanceA robust cerebrospinal fluid (CSF) cell cryopreservation protocol using high resolution single-cell (sc) transcriptomic data would enable the deployment of this important modality in multi-center translational research studies and clinical trials in which many sites do not have the expertise or resources to produce data from fresh samples. It would also serve to reduce technical variability in larger projects. ObjectiveTo test a reliable cryopreservation protocol adapted for CSF cells, facilitating the characterization of these rare, fragile cells in moderate to large scale studies. DesignDiagnostic lumbar punctures were performed on twenty-one patients at two independent sites. Excess CSF was collected and cells were isolated. Each cell sample was split into two fractions for single cell analysis using one of two possible chemistries: 3 sc-RNA-Sequencing or 5sc-RNA-Sequencing. One cell fraction was processed fresh while the second sample was cryopreserved and profiled at a later time after thawing. SettingThe research protocol was deployed at two academic medical centers taking care of multiple sclerosis and other neurological conditions. Participants21 subjects (age 24 - 72) were recruited from individuals undergoing a diagnostic lumbar puncture for suspected neuroinflammatory disease or another neurologic illness; they donated excess CSF. FindingsOur comparison of fresh and cryopreserved data from the same individuals demonstrates highly efficient recovery of all known CSF cell types. The proportion of all cell types was similar between the fresh and the cryopreserved cells processed, and RNA expression was not significantly different. Results were comparable at both performance sites, and with different single cell sequencing chemistries. Cryopreservation also did not affect recovery of T and B cell clonotype diversity. Conclusion and relevanceOur cryopreservation protocol for CSF-cells provides an important alternative to fresh processing of fragile CSF cells: cryopreservation enables the involvement of sites with limited capacity for experimental manipulation and reduces technical variation by enabling batch processing and pooling of samples. Key pointsO_ST_ABSQuestionC_ST_ABSHow efficient is CSF cryopreservation for single-cell transcriptome analysis and can it be implemented in large multi-center translational and clinical trial settings? FindingsWe compared single-cell transcriptomes of paired fresh and cryopreserved CSF from 21 patients at two independent sites. We validate the efficacy of a simple and cost effective CSF cryopreservation method that preserves the composition and the transcriptomes of CSF cells stored for weeks-months. The protocol is deployed in a large multicenter Phase 4 MS clinical trial. MeaningA validated CSF cryopreservation method that would significantly advance basic science and biomarker research in neurological disorders by implementing single-cell transcriptome analyses in multi-center research and clinical trials.

genetics↗

bioRxiv2019

On the discovery of population-specific state transitions from multi-sample multi-condition single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) has quickly become an empowering technology to profile the transcriptomes of individual cells on a large scale. Many early analyses of differential expression have aimed at identifying differences between subpopulations, and thus are focused on finding subpopulation markers either in a single sample or across multiple samples. More generally, such methods can compare expression levels in multiple sets of cells, thus leading to cross-condition analyses. However, given the emergence of replicated multi-condition scRNA-seq datasets, an area of increasing focus is making sample-level inferences, termed here as differential state analysis. For example, one could investigate the condition-specific responses of cell subpopulations measured from patients from each condition; however, it is not clear which statistical framework best handles this situation. In this work, we surveyed the methods available to perform cross-condition differential state analyses, including cell-level mixed models and methods based on aggregated "pseudobulk" data. We developed a flexible simulation platform that mimics both single and multi-sample scRNA-seq data and provide robust tools for multi-condition analysis within the muscat R package.

bioinformatics↗