Arid1a-dependent canonical BAF complex suppresses inflammatory programs to drive efficient germinal center B cell responses.

The mammalian Brg1/Brm-associated factor (BAF) complexes are major regulators of nucleosomal remodeling that are commonly mutated in several cancers, including germinal center (GC)-derived B cell lymphomas. However, the specific roles of different BAF complexes in GC B cell biology are not well understood. Here we show that the AT-rich interaction domain 1a (Arid1a) containing canonical BAF (cBAF) complex is required for maintenance of GCs and high-affinity antibody responses. While Arid1a-deficient B cells undergo initial activation, they fail to sustain the GC program. Arid1a establishes permissive chromatin landscapes for B cell activation and is concomitantly required to suppress inflammatory gene programs. The inflammatory signatures instigated by Arid1a deficiency promoted the recruitment of neutrophils and inflammatory monocytes. Dampening of inflammatory cues through interleukin-1ß blockade or glucocorticoid receptor agonist partially rescued Arid1a-deficient GCs, highlighting a critical role for inflammation in impeding GCs. Our work reveals essential functions of Arid1a-dependent cBAF in promoting efficient GC responses.

Autofluorescence lifetime imaging classifies human lymphocyte activation and subtype.

New non-destructive tools are needed to reliably assess lymphocyte function for immune profiling and adoptive cell therapy. Optical metabolic imaging (OMI) is a label-free method that measures the autofluorescence intensity and lifetime of metabolic cofactors NAD(P)H and FAD to quantify metabolism at a single-cell level. Here, we investigate whether OMI can resolve metabolic changes between human quiescent versus IL4/CD40 activated B cells and IL12/IL15/IL18 activated memory-like NK cells. We found that quiescent B and NK cells were more oxidized compared to activated cells. Additionally, the NAD(P)H mean fluorescence lifetime decreased and the fraction of unbound NAD(P)H increased in the activated B and NK cells compared to quiescent cells. Machine learning classified B cells and NK cells according to activation state (CD69+) based on OMI parameters with up to 93.4% and 92.6% accuracy, respectively. Leveraging our previously published OMI data from activated and quiescent T cells, we found that the NAD(P)H mean fluorescence lifetime increased in NK cells compared to T cells, and further increased in B cells compared to NK cells. Random forest models based on OMI classified lymphocytes according to subtype (B, NK, T cell) with 97.8% accuracy, and according to activation state (quiescent or activated) and subtype (B, NK, T cell) with 90.0% accuracy. Our results show that autofluorescence lifetime imaging can accurately assess lymphocyte activation and subtype in a label-free, non-destructive manner.