RNA sequencing of Isolated B cells from SM03 treatment on anti-IgM stimulated PBMC
Description
SM03, an anti-CD22 monoclonal antibody was previously proposed to induce specific interaction of CD22, facilitating the CD22-mediated ‘self-recognition’ of autologous cells, thereby attenuating autoreactive BCR signaling. To explore potential downstream mechanisms and effects. Healthy volunteer PBMCs were stimulated with anti-IgM to mimic B-cell activation and treated with SM03 or IgG1 Isotype Control. B cells were Isolated and RNA-seq analysis was conducted, mRNA was purified using polyT oligo-attached magnetic beads, fragmented, and converted to cDNA using random hexamer priming. After end repair, A-tailing, adaptor ligation, size selection, and PCR amplification, libraries were quantified and assessed by bioanalyzer. Cluster generation followed standard Illumina procedures, and paired-end sequencing was performed on an Illumina platform. Raw sequencing reads underwent quality control to remove adapter sequences, low‑quality reads, and reads containing poly‑N, generating high‑quality clean data for analysis. Clean paired‑end reads were aligned to the reference genome using HISAT2, and gene‑level counts were obtained with feature Counts. Gene expression levels were quantified as FPKM values, followed by differential expression analysis using DESeq2 to identify significantly regulated genes. Functional enrichment of differentially expressed genes (DEGs) was performed using GO, KEGG, Reactome, Disease Ontology, and DisGeNET pathway frameworks, and complementary Gene Set Enrichment Analysis (GSEA) was conducted to evaluate coordinated pathway shifts. SM03‑treated samples were compared against IgG1 controls to identify transcriptional changes associated with B‑cell modulation. This analysis revealed SM03‑specific DEGs linked to reduced BCR signaling, altered checkpoint regulation, and attenuated autoreactive responses. GSEA further demonstrated downregulation of B‑cell activation pathways and autoimmune signatures, supporting that SM03 modulates B‑cell activation and immune crosstalk distinct from IgG1. Together, DEG and GSEA results highlight transcriptomic differences that reflect the immunomodulatory effects of SM03 on B cells.
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Steps to reproduce
Total RNA was extracted from PBMCs and mRNA was purified using poly T oligo attached magnetic beads. Purified mRNA was fragmented and converted into first strand cDNA using random hexamer primers, followed by second strand synthesis using either dUTP for directional libraries or dTTP for non directional libraries. Libraries then underwent end repair, A tailing, adaptor ligation, size selection, PCR amplification, and purification. Library quality and size distribution were assessed using Qubit, real time PCR, and a bioanalyzer. Indexed libraries were pooled and sequenced on an Illumina platform using paired end reads following standard clustering and sequencing protocols. Raw FASTQ files were processed through in house scripts to remove adapters, low quality reads, and poly N content. Clean data quality was evaluated using Q20/Q30 scores and GC content metrics. Reads were aligned to the reference genome using HISAT2 (v2.0.5), which incorporates splice junction indexing for improved mapping accuracy. Gene level quantification was performed using featureCounts (v1.5.0 p3), and expression values were calculated as FPKM. Differential expression analysis was conducted using DESeq2 for biological replicates, applying negative binomial modeling and Benjamini–Hochberg multiple testing correction. Genes with adjusted p value ≤ 0.05 were considered differentially expressed. For datasets without biological replicates, edgeR normalization and statistical modeling were applied.