Ectopic Tcf1 expression instills a stem-like program in exhausted CD8^(+) T cells to enhance viral and tumor immunity

Exhausted CD8^(+)T(Tex)cells are dysfunctional due to persistent antigen exposure in chronic viral infection and tumor contexts.A stem cell-like Tex(Tex-stem)subset can self-renew and differentiate into terminally exhausted(Tex-term)cells.Here,we show that ectopic Tcf1 expression potently promoted the generation of Tex-stem cells in both a chronic viral infection and preclinical tumor models.Tcf1 overexpression diminished coinhibitory receptor expression and enhanced polycytokine-producing capacity while retaining a heightened responses to checkpoint blockade,leading to enhanced viral and tumor control.Mechanistically,ectopically expressed Tcf1 exploited existing and novel chromatin accessible sites as transcriptional enhancers or repressors and modulated the transcriptome by enforcing pre-existing expression patterns in Tex-stem cells,such as enhanced suppression of Blimp1 and Bim and acquisition of new downstream genes,including Mx1,Tox2,and Runx3.These findings reveal a pronounced impact of ectopic Tcf1 expression on Tex functional restoration and highlight the therapeutic potential of harnessing Tcf1-enforced transcriptional programs.

RECOGNICER:A coarse-graining approach for identifying broad domains from ChIP-seq data

Background:Histone modifications are major factors that define chromatin states and have functions in regulating gene expression in eukaryotic cells.Chromatin immunoprecipitation coupled with high-throughput sequencing(ChIP-seq)technique has been widely used for profiling the genome-wide distribution of chromatin-associating protein factors.Some histone modifications,such as H3K27me3 and H3K9me3,usually mark broad domains in the genome ranging from kilobases(kb)to megabases(Mb)long,resulting in diffuse patterns in the ChIP-seq data that are challenging for signal separation.While most existing ChIP-seq peak-calling algorithms are based on local statistical models without account of multi-scale features,a principled method to identify scale-free board domains has been lacking.Methods:Here we present RECOGNICER(Recursive coarse-graining identification for ChIP-seq enriched regions),a computational method for identifying ChIP-seq enriched domains on a large range of scales.The algorithm is based on a coarse-graining approach,which uses recursive block transformations to determine spatial clustering of local enriched elements across multiple length scales.Results:We apply RECOGNICER to call H3K27me3 domains from ChIP-seq data,and validate the results based on H3K27me3's association with repressive gene expression.We show that RECOGNICER outperforms existing ChIP-seq broad domain calling tools in identifying more whole domains than separated pieces.Conclusion:RECOGNICER can be a useful bioinformatics tool for next-generation sequencing data analysis in epigenomics research.