The ALS-Linked Gene TDP-43 Regulates IFNβIFN\beta Expression through a Novel Mechanism of 3' UTR-Mediated Promoter cis-Regulation

The TAR DNA-binding protein (TDP-43) is a heterogeneous nuclear ribonucleprotein that is involved in multiple stages of RNA processing. Mutations in the TDP-43 gene and mislocalization of TDP-43 protein have been implicated in a growing number of neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). Here, we show that TDP-43 negatively regulates innate immune gene expression in response to RNA virus sensing. Perturbation of TDP-43 protein expression leads to an increase in antiviral gene expression in a variety of human and mouse cells. Crosslinked RNA immunoprecipitation (CLIP) experiments revealed that TDP-43 binds to type I interferon (IFN) and interferon stimulated gene (ISGs) transcripts. Using massively parallel 3’ UTR reporter assays coupled with high throughput sequencing (MPRA-seq), we identified polyadenylation signal sequences in the 3' UTRs of innate immune genes to be specifically regulated by TDP-43. Surprisingly, IFN and ISG mRNA decay rates are faster in TDP-43-perturbed cells. Using a metabolic labeling approach to measure nascent transcript generation, we found that perturbation of TDP-43 expression leads to an increase in antiviral gene transcription rates. Additionally, RNA polymerase II (pol II) chromatin immunoprecipitation (ChIP) confirmed that there is greater pol II occupancy on innate immune genes when TDP-43 is depleted. Although TDP-43 perturbation has no effect on an isolated $IFN\beta$ promoter reporter, we found that TDP-43 inhibits $IFN\beta$ promoter activity when the $IFN\beta$ 3' UTR sequence is inserted downstream of the $IFN\beta$ promoter element, suggesting a novel mechanism of 3' UTR-mediated promoter cis-regulation

Musashi-2 controls cell fate, lineage bias, and TGF-β signaling in HSCs

Hematopoietic stem cells (HSCs) are maintained through the regulation of symmetric and asymmetric cell division. We report that conditional ablation of the RNA-binding protein Msi2 results in a failure of HSC maintenance and engraftment caused by a loss of quiescence and increased commitment divisions. Contrary to previous studies, we found that these phenotypes were independent of Numb. Global transcriptome profiling and RNA target analysis uncovered Msi2 interactions at multiple nodes within pathways that govern RNA translation, stem cell function, and TGF-β signaling. Msi2-null HSCs are insensitive to TGF-β–mediated expansion and have decreased signaling output, resulting in a loss of myeloid-restricted HSCs and myeloid reconstitution. Thus, Msi2 is an important regulator of the HSC translatome and balances HSC homeostasis and lineage bias

The Msi Family of RNA-Binding Proteins Function Redundantly as Intestinal Oncoproteins

Members of the Msi family of RNA-binding proteins have recently emerged as potent oncoproteins in a range of malignancies. MSI2 is highly expressed in hematopoietic cancers, where it is required for disease maintenance. In contrast to the hematopoietic system, colorectal cancers can express both Msi family members, MSI1 and MSI2. Here, we demonstrate that, in the intestinal epithelium, Msi1 and Msi2 have analogous oncogenic effects. Further, comparison of Msi1/2-induced gene expression programs and transcriptome-wide analyses of Msi1/2-RNA-binding targets reveal significant functional overlap, including induction of the PDK-Akt-mTORC1 axis. Ultimately, we demonstrate that concomitant loss of function of both MSI family members is sufficient to abrogate the growth of human colorectal cancer cells, and Msi gene deletion inhibits tumorigenesis in several mouse models of intestinal cancer. Our findings demonstrate that MSI1 and MSI2 act as functionally redundant oncoproteins required for the ontogeny of intestinal cancers

A framework for highly multiplexed dextramer mapping and prediction of T cell receptor sequences to antigen specificity.

T cell receptor (TCR) antigen-specific recognition is essential for the adaptive immune system. However, building a TCR-antigen interaction map has been challenging due to the staggering diversity of TCRs and antigens. Accordingly, highly multiplexed dextramer-TCR binding assays have been recently developed, but the utility of the ensuing large datasets is limited by the lack of robust computational methods for normalization and interpretation. Here, we present a computational framework comprising a novel method, ICON (Integrative COntext-specific Normalization), for identifying reliable TCR-pMHC (peptide-major histocompatibility complex) interactions and a neural network-based classifier TCRAI that outperforms other state-of-the-art methods for TCR-antigen specificity prediction. We further demonstrated that by combining ICON and TCRAI, we are able to discover novel subgroups of TCRs that bind to a given pMHC via different mechanisms. Our framework facilitates the identification and understanding of TCR-antigen-specific interactions for basic immunological research and clinical immune monitoring

Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses

Models of mammalian regulatory networks controlling gene expression have been inferred from genomic data but have largely not been validated. We present an unbiased strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We applied this approach to derive regulatory networks that control the transcriptional response of mouse primary dendritic cells to pathogens. Our approach revealed the regulatory functions of 125 transcription factors, chromatin modifiers, and RNA binding proteins, which enabled the construction of a network model consisting of 24 core regulators and 76 fine-tuners that help to explain how pathogen-sensing pathways achieve specificity. This study establishes a broadly applicable, comprehensive, and unbiased approach to reveal the wiring and functions of a regulatory network controlling a major transcriptional response in primary mammalian cells

Rapid TCR:Epitope Ranker (RAPTER): a primary human T cell reactivity screening assay pairing epitope and TCR at single cell resolution

Abstract Identifying epitopes that T cells respond to is critical for understanding T cell-mediated immunity. Traditional multimer and other single cell assays often require large blood volumes and/or expensive HLA-specific reagents and provide limited phenotypic and functional information. Here, we present the Rapid TCR:Epitope Ranker (RAPTER) assay, a single cell RNA sequencing (scRNA-SEQ) method that uses primary human T cells and antigen presenting cells (APCs) to assess functional T cell reactivity. Using hash-tag oligonucleotide (HTO) coding and T cell activation-induced markers (AIM), RAPTER defines paired epitope specificity and TCR sequence and can include RNA- and protein-level T cell phenotype information. We demonstrate that RAPTER identified specific reactivities to viral and tumor antigens at sensitivities as low as 0.15% of total CD8+ T cells, and deconvoluted low-frequency circulating HPV16-specific T cell clones from a cervical cancer patient. The specificities of TCRs identified by RAPTER for MART1, EBV, and influenza epitopes were functionally confirmed in vitro. In summary, RAPTER identifies low-frequency T cell reactivities using primary cells from low blood volumes, and the resulting paired TCR:ligand information can directly enable immunogenic antigen selection from limited patient samples for vaccine epitope inclusion, antigen-specific TCR tracking, and TCR cloning for further therapeutic development