Back

B Cell-Induced Lymph Node Stromal Remodeling Compromises Neutrophil Response to Secondary Staphylococcus aureus Infection

Xue, J.; Oo, D.; Rosin, N.; Biernaskie, J.; Huang, P.; Liao, S.

2025-11-03 immunology
10.1101/2025.10.31.681727 bioRxiv
Show abstract

The lymph node (LN) stromal cells create niches, regulate lymph drainage, and guide the migration, positioning, and activation of immune cells within the LN. Upon stimulation, the stromal cells respond dynamically to accommodate the massive expansion of immune cells in the LN. However, there is still a limited understanding of how niche-associated stromal cell subsets are remodeled and how this remodeling reshapes host immune protection. In an oxazolone (OX)-induced skin inflammation model, we found that LN remodeling weakened the neutrophil response to secondary Staphylococcus aureus (S. aureus) infection in the inflamed LN, whereas depleting B cells rescued the responses. To understand the mechanism, we used single-cell RNA sequencing (scRNAseq) to characterize alterations in fibroblastic reticular cell (FRC) subsets and identified a new FRC subset expressing an intermediate level of CXCL13 (Cxcl13int RCs) in the inflamed LN. Further studies revealed that Cxcl13int RCs replaced Ccl19lo FRCs in the interfollicular zones (IFZs) of the inflamed LN, leading to a compromised conduit network. Depleting B cells preserved the integrity and function of the FRC-conduit network within the IFZ. Finally, the induction of Cxcl13int RCs depended on the B cell-derived lymphotoxin signaling. The induced Cxcl13int RCs were transitional, creating a time window of comprised immune protection during the OX-inflammation. This study elucidated a mechanism underlying LN stromal remodeling and provides proof-of-principle evidence that B cell-stromal interactions may be a novel target to enhance host immunity in diseased conditions.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.