bioRxivImmunologyPreprint
Germinal center BCR maturation in appendicitis reveals a role for antigen-specific adaptive immune responses during disease
E. Stewart, Z. Taghvaei, C. Leon, J. Shapiro, L. Zhu, L. Alpert, K. Turaga, R. Roy Chowdhury
Abstract
Appendicitis is one of the most common abdominal emergencies globally, yet little is understood about the inflammatory mechanisms or potential drivers of disease. Neutrophil inflammation and increased cytokine expression such as IL-6 and IL-8 are hallmarks of appendicitis inflammation. However, early histological studies identified increased T and B cell infiltration during appendicitis, providing support for adaptive immune activation as well, although this has never been investigated in depth. We hypothesized that antigen-dependent activation of the adaptive immune response contributes to appendicitis pathology, in addition to the known innate-mediated processes. Via a series of transcriptomic approaches and lymphocyte repertoire analysis in human appendiceal tissue, we identified evidence of antigen-dependent B cell activation. Increased somatic hypermutation in the germinal center and plasma cell compartment was comprised of presumed high-affinity IgG and IgA B cells. We propose that the appendiceal microbiome acts as a source of antigen, as significant microbial dysbiosis was observed during appendicitis. This dysbiosis was characterized by outgrowth of pathobionts such as Parvimonas and oral biofilm-formers such as Fretibacterium and Fusobacterium, in line with previous reports. We also identified potential loss of epithelial barrier integrity via spatial transcriptomic analysis of the appendiceal epithelium, supporting the possibility of microbial invasion into the tissue during appendicitis. This study provides insight into the inflammatory mechanisms of a common disease and helps to define the immune and microbial compartment of an often-ignored organ, the appendix.
- organism: human
- assay: bulk RNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
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