Causal dynamical modelling predicts novel regulatory genes of FOXP3 in human regulatory T cells

Abstract

Regulatory T cells (Tregs), characterized as a CD4+CD25+FOXP3+ subset of T cells, are vital to the induction of immune tolerance and the maintenance of immune homeostasis. While target genes of Treg master regulator FOXP3 have been identified, the upstream regulatory machinery of FOXP3 still remains largely unknown. Here we dynamically model causal relationships among genes from available time-series genome-scale datasets, to predict direct or indirect regulatory genes of FOXP3 in human primary Tregs. From the whole genome, we selected five top ranked candidates for further experimental validation. Following knockdown, three out of the five candidates indeed showed significant effects on the mRNA expression of FOXP3. Further experiments showed that one out of these three predicted candidates, namely nuclear receptor binding factor 2 (NRBF2), also affected FOXP3 protein expression. These results open new doors to identify potential new mechanisms of immune related diseases.