Studying DNA histone modifications as determinant for infection susceptibility

Cleavage under targets and release using nuclease (CUT & RUN)

To comprehensively understand the contributions of histone modifications to transcript regulation, we generated data on three CVID patients (5000026, 5001414, and 5000291) and three controls (FR124, FR135, and FR145). We performed Cleavage under targets and release using nuclease (CUT & RUN) to analyze histone modifications of active (H3K27ac) and repressive chromatin (H3K27me3) derived from stimulated naïve B cells.

Materials and methods

Sample preparation. Peripheral Blood Mononuclear Cells (PBMCs) were isolated from EDTA blood by Ficoll density centrifugation following standard protocols. A total of three patient and three control PBMC samples were sorted into naïve B cells (CD19+, IgD, CD27-) and stimulated for 24 hours. Three patient and three control PBMC samples were sorted into naïve B cells (CD19+, IgD-, CD27-) and stimulated for 24 hours. Cells were sorted on a MoFlo Astrios Cell sorter (Beckman Coulter, Brea, CA, USA).

Cell stimulation. Naïve B lymphocytes were stimulated with 1µg/ml CD40L (provided by Pascal Schneider, Lausanne, Switzerland) and 50ng/ml IL21 and incubated for 24 hours at 37ºC, 5 % CO2. After stimulation, cell numbers were determined with a Neubauer chamber. A total of 5,000-50,000 cells were used for CUT&RUN processing. B cell activation (CD69 APC, CD80 Brilliant Violet 421, CD86 PerCP-Cy5.5, CD95 Brilliant Violet 650, HLA-DR PE-Cy7) was measured on a LSR Fortessa from Becton Dickinson (BD Biosciences, San Jose, CA).

CUT&RUN protocol. Samples were processed according to a modified protocol and available on protocols.io (1). Antibodies used included H3K27ac (Abcam, 4729), H3K27me3 (Cell Signalling, 9733), and IgG (Cell Signaling, 2729). Samples from three CVID patients and three controls were used for each antibody. CUT&RUN library preparation and sequencing was performed by Novogene (Cambridge, UK), using the HiSeq (Illumina) in paired-end mode with reads of 150bp length.

Bioinformatics analysis. Detailed bioinformatics analysis workflows with command line examples for illumina sequences are available on protocols io (2). Data preprocessing was performed on the Galaxy web platform and the public server usegalaxy.eu. Briefly, trimmed fastq files were aligned to the hg38 reference genome using Bowtie 2. Aligned reads were extracted and converted to a sorted bam file using SAM tools. Scaled bigwig files were generated using Deeptools, and peaks were called using Macs2. Further analysis was performed in R v4.2.0 using a custom R script. For annotation, BED files of the identified peaks were loaded and harmonized using the GenomicRanges and rtracklayer packages in R. Default chromosome names (chr1-chr22, chrX, chrY) were used. Feature counts for the identified peaks were generated using the featureCounts function from the Rsubread package. Count matrices were generated and normalized for subsequent analysis. Differential binding analysis was performed using the DESeq2 package in R. Count data were normalized and differential peaks between CVID patients and controls were identified. Genomic annotation bar plots and pie charts were generated using the plotAnnoBar and plotAnnoPie functions of the ChIPseeker package. These plots showed the distribution of peaks across genomic features such as promoters, exons, introns, 5′ UTR, 3′ UTR, downstream regions, and intergenic regions. Significantly differentially bound regions were identified and annotated. Their potential regulatory roles were inferred based on their genomic locations and annotations.

Results

We investigated the differential binding patterns of two key histone modifications, H3K27ac and H3K27me3, in CVID patients compared to controls. H3K27ac is associated with active enhancers and promoters, indicating regions of active transcription, while H3K27me3 is associated with gene repression, indicating silenced regions of the genome. A total of 18 samples were sent for sequencing One control sample failed library sequencing (FR135), resulting in the analysis of fifteen stimulated naïve B cell samples.

H3K27ac binding patterns

The comparative analysis of the genomic distribution of H3K27ac binding sites between healthy controls and CVID patients showed significant differences (Figure 1a). In healthy controls, the majority of H3K27ac binding sites are located in distal intergenic regions (85.73 %), suggesting a dominant role for distal enhancers in regulating gene expression. In contrast, CVID patients show a reduced proportion of binding sites in distal intergenic regions (50.82 %) and an increased proportion in promoter regions (<=3kb) and introns. Specifically, CVID patients have more binding sites in promoter regions (3.86 % for <=1kb, 3.42 % for 1-2kb, and 4.46 % for 2-3kb) and in introns (11.89 % for 1st intron and 22.29 % for other introns). These differences suggest a shift in the regulatory landscape in CVID patients. On the differential analysis, we found 27 significant differential binding regions (Figure 1b). Specifically, NUP88, involved in nucleocytoplasmic transport, and DUSP8, a regulator of MAPK signaling pathways, showed reduced binding (log2 fold change ~ -4 and -3.5, respectively). On the other hand, BMI1, part of the Polycomb Repressive Complex 1 (PRC1) involved in gene silencing showed decreased H3K27ac binding in CVID patients (log2 fold change ~ -2.7). These changes suggest a significant impact on enhancer and promoter activity, which may lead to dysregulated gene expression and impaired immune responses in CVID patients.