Data from: RAC2 gain of function variants causing inborn error of immunity drive NLRP3 inflammasome activation
Data files
Aug 08, 2024 version files 55.12 MB
Abstract
A growing number of patients presenting severe combined immunodeficiencies attributed to monoallelic RAC2 variants have been identified. The expression of the RHO GTPase RAC2 is restricted to the hematopoietic lineage. RAC2 variants have been described to cause immunodeficiencies associated with high frequency of infection, leukopenia, and autoinflammatory features. Here we show that RAC2 activating mutations induce the NLRP3 inflammasome leading to the secretion of IL-1 and IL-18 from macrophages. This induction depends on the RAC2 mutation and in particular their activation state. This suggests that inhibiting the RAC2-PAK1-NLRP3 inflammasome pathway might be considered as a potential treatment for these patients.
To investigate in depth the impact of the activating variant RAC2 A59S we performed a single cell RNAseq analysis of blood circulating cells. This analysis showed increased numbers of both classical and non classical monocytes as well as myeloid dendritic cells when compared to a healthy control. In addition, and supporting our hypothesis, NLRP3 and IL-1b expression levels were increased in both monocytes and myeloid dendritic cells, while their expression in lymphocytes was not affected in our analysis.
To further confirm our data, we compared monocytes isolated from PBMCs of patients harboring the RAC2 A59S with monocytes isolated from RAC2 E62K mutation. In both cases, the PBMCs were collected and frozen using the same protocol and PBMCs from patients and control healthy donors were processed in parallel.
In general, the results of this study identified the RAC2 A59S mutation as a gain of function variant activating NLRP3.
README: Data from: RAC2 gain of function variants causing inborn error of immunity drive NLRP3 inflammasome activation.
https://doi.org/10.5061/dryad.p8cz8w9zx
Single cell on blood samples were processed for Chromium Single Cell Gene Expression Flex analysis according to manufacturer protocol. Whole blood cells from control (n= 8078 cells) and RAC2 A59S patient (n= 14524 cells) were analyzed. Raw sequencing data were processed using the 10× Chromium CellRanger "multi" analysis pipeline (version 7.0.0). Reads were aligned to the human reference genome (GRCh38-3.0.0) (10x Genomics).
Description of the data and file structure
The study includes data from a patient carrying the A59S mutation and a representative control. The processed data for these subjects are stored in two separate folders: filesample_filtered_feature_bc_matrix_A59S for the patient and filesample_filtered_feature_bc_matrix_Control for the control. Containing matrix, features and barcodes files for single cell analysis.
Generally, all single-cell RNA-seq datasets, regardless of technology or pipeline, will contain three files:
- a file with the gene IDs, representing all genes quantified
- a file with the cell IDs, representing all cells quantified
- a matrix of counts per gene for every cell
We can explore these files by clicking on the filesample_filtered_feature_bc_matrix folder:
matrix.mtx: a matrix of count values, where rows are associated with the gene IDs above and columns correspond to the cellular barcodes.
features.tsv: IDs of quantified genes
barcodes.tsv: text file which contains all cellular barcodes present for that sample. Barcodes are listed in the order of data presented in the matrix file (i.e. these are the column names).
Further information on the study design, sampling method, software used, and the statistical analysis calculation is given in the associated manuscript.
Sharing/Access information
The data used in this study were published in the Journal of Experimental Medicine under the title "RAC2 gain of function variants causing inborn error of immunity drive NLRP3 inflammasome activation." DOI: 10.1084/jem.20231562.
Methods
Blood samples were processed for Chromium Single Cell Gene Expression Flex analysis according to manufacturer protocol. Whole blood cells from control (n= 8078 cells) and RAC2 A59S patient (n= 14524 cells) were analyzed. Raw sequencing data were processed using the 10× Chromium CellRanger "multi" analysis pipeline (version 7.0.0). Reads were aligned to the human reference genome (GRCh38-3.0.0) (10x Genomics).