Biology subjects

Pear, W. S.

Publications and source records attributed to Pear, W. S..

3 recordsLinked to original sources

bioRxiv2023

The pseudokinase Trib1 regulates the transition of exhausted T cells to a KLR+ CD8+ effector state and its deletion improves checkpoint blockade

T cell exhaustion (TEX) impairs the ability of T cells to clear chronic infection or cancer. While exhausted T cells are hypofunctional, some exhausted T cells retain effector gene signatures, a feature that is associated with expression of KLRs (killer lectin-like receptors). Although KLR+ T cells may improve control of chronic antigen, the signaling molecules regulating this population are poorly understood. Using scRNA-seq, flow cytometry, RNA velocity, and scTCR-seq, we demonstrate that deleting the pseudokinase Trib1 shifts TEX towards CX3CR1+ intermediates (TINT) with robust enrichment of KLR+CD8+ T cells (TKLR) via clonal T cell expansion. These changes are associated with globally increased KLR gene expression throughout the exhaustion program. Further, Trib1 loss augments anti-PD-L1 blockade to improve viral clearance by expanding the TKLR population. Together, these data identify Trib1 as an important regulator of T cell exhaustion whose targeting enhances the KLR+ effector state and improves the response to checkpoint inhibitor therapy.

immunology↗

bioRxiv2019

Oncogenic Notch promotes long-range regulatory interactions within hyperconnected 3D cliques

Chromatin loops enable transcription factor-bound distal enhancers to interact with their target promoters to regulate transcriptional programs. Although developmental transcription factors, such as active forms of Notch, can directly stimulate transcription by activating enhancers, the effect of their oncogenic subversion on the 3-dimensional (3D) organization of the cancer genome is largely undetermined. By mapping chromatin looping genome-wide in Notch-dependent triple-negative breast cancer and B-cell lymphoma, we show that far beyond the well-characterized role of Notch as an activator of distal enhancers, Notch regulates its direct target genes through establishing new long-range regulatory interactions. Moreover, a large fraction of Notch-promoted regulatory loops forms highly interacting enhancer and promoter spatial clusters, termed "3D cliques". Loss-and gain-of-function experiments show that Notch preferentially targets hyperconnected 3D cliques that regulate the expression of crucial proto-oncogenes. Our observations suggest that oncogenic hijacking of developmental transcription factors can dysregulate transcription through widespread effects on the spatial organization of cancer genomes.

cancer biology↗

bioRxiv2019

TooManyCells identifies and visualizes relationships of single-cell clades

Transcriptional programs contribute to phenotypic and functional cell states. While elucidation of cell state heterogeneity and its role in biology and pathobiology has been advanced by studying single cell level measurements, the underlying assumptions of current analytical methods limit the identification and exploration of cell clades. Unlike other methods, which produce a single uni-layer partition of cells ignoring echelons of cell states, we present TooManyCells, a software consisting of a suite of graph-based tools for efficient, global, and unbiased identification and visualization of cell clades while maintaining and presenting the relationship between cell states. TooManyCells provides a set of tools based on a matrix-free efficient divisive hierarchical spectral clustering algorithm wholly different from the prevalent Louvain-based methods. BirchBeer, the visualization component of TooManyCells, introduces a new approach for single cell analysis that is built on a concept intentionally orthogonal to the widely used dimensionality reduction methods. Together, this suite of tools provide a paradigm shift in the analysis and interpretation of single cell data by enabling simultaneous comparisons of cell states at context-and application-dependent scales. A byproduct of this shift is the immediate detection and visualization of rare populations that outperforms previous algorithms as demonstrated by applying these tools to existing single cell RNA-seq data sets from various mouse organs.

bioinformatics↗