A dichotomy in association of core transcription factors and gene regulation during the activated B-cell to plasmablast transition

Abstract

The activated B-cell (ABC) to plasmablast transition is the cusp of antibody secreting cell (ASC) differentiation but is incompletely defined. We apply expression time-courses, parsimonious gene correlation network analysis, and ChIP-seq to explore this in human cells. The transition initiates with input signal loss leading within hours from cell growth dominant programs to enhanced proliferation, accompanied from 24h by ER-stress response, secretory optimization and upregulation of ASC features. Clustering of genomic occupancy for ASC transcription factors (TFs) IRF4, BLIMP1 and XBP1 with CTCF and histone marks defines distinct patterns for each factor in plasmablasts. Integrating TF-associated clusters and modular gene expression identifies a dichotomy: XBP1 and IRF4 significantly link to gene modules induced in plasmablasts, but not to modules of repressed genes, while BLIMP1 links to modules of ABC genes repressed in plasmablasts but is not significantly associated with modules induced in plasmablasts. Pharmacological inhibition of the G9A (EHMT2) histone-methytransferase, a BLIMP1 co-factor that catalyzes repressive H3K9me2 marks, leaves functional ASC differentiation intact but de-represses ABC-state genes. Thus, in human plasmablasts IRF4 and XBP1 emerge as the dominant association with ASC gene expression, while BLIMP1 links to repressed modules with particular focus in repression of the B-cell activation state.

A neomorphic mutation in the interferon activation domain of IRF4 causes a dominant primary immunodeficiency

“…It has been reported that a shift in IRF4 binding from AICE sites to ISRE sites is associated with the IRF4 protein concentration and the pattern of B lymphocyte differentiation ( Cocco et al, 2019 Preprint ; Ochiai et al, 2013 ). To analyze IRF4’s binding to regulatory elements, we performed ChIP-Seq on both patient and healthy donor (control) B-EBV cell lines.…”

Network Approaches for Dissecting the Immune System

“…WGCNA was able to identify the co-expressed gene modules responsible for IFN stimulation in plasmablasts and construct gene regulatory network to define inflammatory regulatory circuits during plasma cell differentiation ( Care et al., 2016 ). Other gene correlation-based methods such as parsimonious gene correlation network analysis were also used to assess the gene regulatory network underlying the transition from activated B cells toward plasmablasts ( Cocco et al., 2019 ).…”