Biology subjects

Belk, J. A.

Publications and source records attributed to Belk, J. A..

14 recordsLinked to original sources

bioRxiv2026

Isolation of postnatal human neural stem cells

While it was once thought that neurogenesis is complete by birth, it is now apparent that the human brain continues to generate new neurons postnatally, at least into childhood. While much attention has been focused on postnatally-born neurons, their presumed progenitor - the postnatal neural stem cell (NSC) - remains poorly characterized. Using index sorting, we identify and prospectively isolate two subsets of NSCs from the postnatal human brain, and describe their differentiation dynamics using clonal barcoding and in vivo xenotransplantation. We demonstrate an A2B5+EGFR+ population biased towards interneuron and oligodendrocyte fates (NINO), and an A2B5-EGFRhi population biased towards an astrocyte fate (NAC). Profiling of human brains across lifespan shows that the frequency of NSCs declined exponentially across the first two decades of life, but stabilized thereafter, still present in the brains of donors as old as 90 years. Our study provides a framework for the functional study of postnatal human NSCs and their potential roles in development, aging, and disease.

neuroscience↗

bioRxiv2025

Genetic elements promote retention of extrachromosomal DNA in cancer cells

Extrachromosomal DNA (ecDNA) is a prevalent and devastating form of oncogene amplification in cancer1,2. Circular megabase-sized ecDNAs lack centromeres and segregate stochastically during cell division3-6 yet persist over many generations. EcDNAs were first observed to hitchhike on mitotic chromosomes into daughter cell nuclei over 40 years ago with unknown mechanism3,7. Here we identify a family of human genomic elements, termed retention elements, that tether episomes to mitotic chromosomes to increase ecDNA transmission to daughter cells. We develop Retain-seq, a genome-scale assay that reveals thousands of human retention elements conferring generational persistence to heterologous episomes. Retention elements comprise a select set of CpG-rich gene promoters and act additively. Live-cell imaging and chromatin conformation capture show that retention elements physically interact with mitotic chromosomes at regions which are mitotically bookmarked by transcription factors and chromatin proteins, intermolecularly recapitulating promoter-enhancer interactions. Multiple retention elements are co-amplified with oncogenes on individual ecDNAs in human cancers and shape their sizes and structures. CpG-rich retention elements are focally hypomethylated; targeted cytosine methylation abrogates retention activity and leads to ecDNA loss, suggesting that methylation-sensitive interactions modulate episomal DNA retention. These results highlight the DNA elements and regulatory logic of mitotic ecDNA retention. Amplifications of retention elements promote the maintenance of oncogenic ecDNA across generations of cancer cells, revealing the principles of episome immortality intrinsic to the human genome.

cancer biology↗

bioRxiv2025

EcDNA-borne PVT1 fusion stabilizes oncogenic mRNAs

Extrachromosomal DNA (ecDNA) amplifications are prevalent drivers of human cancers. We show that ecDNAs exhibit elevated structural variants leading to gene fusions that produce oncogene fusion transcripts. The long noncoding RNA (lncRNA) gene PVT1 is the most recurrent structural variant across cancer genomes, with PVT1-MYC fusions arising most frequently on ecDNA. PVT1 exon 1 is the predominant 5 partner fused to MYC or other oncogenes on the 3 end. Mechanistic studies demonstrate that PVT1 exon 1 confers enhanced RNA stability for fusion transcripts, which requires PVT1 exon 1 interaction with SRSF1 protein. Genetic rescue of MYC-addicted cancer models and isoform-specific single-cell RNA sequencing of tumors reveal that PVT1-MYC better supports MYC dependency and better activates MYC target genes in vivo. Thus, the mutagenic landscape of ecDNA contributes to genome instability and generates chimeric fusions of lncRNA and mRNA genes, selecting PVT1 5 region as a stabilizer of oncogene mRNAs.

cancer biology↗

bioRxiv2024

Deciphering regulation of FOXP3 expression in human conventional T cells

FOXP3 is a lineage-defining transcription factor (TF) for immune-suppressive regulatory T cells (Tregs). While mice exclusively express FOXP3 in Tregs, humans also transiently express FOXP3 in stimulated conventional CD4+ T cells (Tconvs). Mechanisms governing these distinct expression patterns remain unknown. Here, we performed CRISPR screens tiling the FOXP3 locus and targeting TFs in human Tregs and Tconvs to discover cis-regulatory elements (CREs) and trans-regulators of FOXP3. Tconv FOXP3 expression depended on a subset of Treg CREs and Tconv-selective positive (TcNS+) and negative (TcNS-) CREs. The CREs are occupied and regulated by TFs we identified as critical regulators of FOXP3. Finally, mutagenesis of murine TcNS- revealed that it is critical for restriction of FOXP3 expression to Tregs. We discover CRE and TF circuitry controlling FOXP3 expression and reveal evolution of mechanisms regulating a gene indispensable to immune homeostasis. HighlightsO_LIComprehensive CRISPR maps of CREs and TFs controlling FOXP3 in human Tregs and Tconvs C_LIO_LIKey TFs that control FOXP3 directly occupy and regulate CREs forming TF-CRE circuits C_LIO_LIA previously unknown negative CRE stringently restricts FOXP3 to Tregs in mice C_LI

immunology↗

bioRxiv2023

Coordinated inheritance of extrachromosomal DNA species in human cancer cells

The chromosomal theory of inheritance has dominated human genetics, including cancer genetics. Genes on the same chromosome segregate together while genes on different chromosomes assort independently, providing a fundamental tenet of Mendelian inheritance. Extrachromosomal DNA (ecDNA) is a frequent event in cancer that drives oncogene amplification, dysregulated gene expression and intratumoral heterogeneity, including through random segregation during cell division. Distinct ecDNA sequences, herein termed ecDNA species, can co-exist to facilitate intermolecular cooperation in cancer cells. However, how multiple ecDNA species within a tumor cell are assorted and maintained across somatic cell generations to drive cancer cell evolution is not known. Here we show that cooperative ecDNA species can be coordinately inherited through mitotic co-segregation. Imaging and single-cell analyses show that multiple ecDNAs encoding distinct oncogenes co-occur and are correlated in copy number in human cancer cells. EcDNA species are coordinately segregated asymmetrically during mitosis, resulting in daughter cells with simultaneous copy number gains in multiple ecDNA species prior to any selection. Computational modeling reveals the quantitative principles of ecDNA co-segregation and co-selection, predicting their observed distributions in cancer cells. Finally, we show that coordinated inheritance of ecDNAs enables co-amplification of specialized ecDNAs containing only enhancer elements and guides therapeutic strategies to jointly deplete cooperating ecDNA oncogenes. Coordinated inheritance of ecDNAs confers stability to oncogene cooperation and novel gene regulatory circuits, allowing winning combinations of epigenetic states to be transmitted across cell generations.

cancer biology↗

bioRxiv2022

XIST ribonucleoproteins promote female sex-biased autoimmunity

Autoimmune diseases disproportionately affect females more than males. The XX sex chromosome complement is strongly associated with susceptibility to autoimmunity. Xist long noncoding RNA (lncRNA) is expressed only in females to randomly inactivate one of the two X chromosomes to achieve gene dosage compensation. Here, we show that the Xist ribonucleoprotein (RNP) complex, comprised of numerous autoantigenic components, is an important driver of sex-biased autoimmunity. Inducible transgenic expression of a non-silencing form of Xist in male mice introduced Xist RNP complexes and sufficed to produce autoantibodies. Male SJL/J mice expressing transgenic Xist developed more severe multiorgan pathology in pristane-induced model of lupus than wild-type males. Xist expression in males reprogrammed T and B cell population and chromatin states to more resemble wild type females. Human patients with autoimmune diseases displayed significant autoantibodies to multiple components of XIST RNP. Thus, a sex-specific lncRNA scaffolds ubiquitous RNP components to drive sex-biased immunity. HIGHLIGHTSO_LITransgenic mouse models inducibly express Xist in male animals. C_LIO_LIXist expression in males induce autoantibodies and autoimmune pathology. C_LIO_LIXist in males reprograms T and B cell populations to female-like patterns. C_LIO_LIAutoantibodies to Xist RNP characterize female-biased autoimmune diseases. C_LI

molecular biology↗

bioRxiv2022

Enhanced Effector Activity of Mediator Kinase Module Deficient CAR-T Cells

Adoptive T cell immune therapies mediate impressive clinical benefit in a fraction of patients, but anti-tumor effects are often limited by inadequate T cell potency. To identify genes limiting T cell effector function, we conducted genome-wide CRISPR knock-out screens in human primary CAR-T cells. The top hits were MED12 and CCNC, components of the cyclin-dependent kinase (CDK) module of the Mediator complex, an evolutionarily conserved regulator of gene transcription. MED12 or CCNC deficient CAR-T cells manifest increased expansion, cytokine production, metabolic fitness, effector function, anti-tumor activity and reduced terminal effector differentiation. Chemical inhibition of CDK8/19 kinase activity recapitulated some features of genetic loss of MED12, including increased T cell expansion. MED12 deficient CAR-T cells showed widespread but selective increases in chromatin accessibility, MED1 chromatin occupancy, and H3K27 acetylation at enhancers used by transcription factors playing a critical role in T cell fate, including several STAT and AP1 family members. The most pronounced enhancement was observed for STAT5 which manifested as increased sensitivity to IL-2 in MED12 deficient T cells. These results link Mediator induced transcriptional coactivation with T cell effector programming and identify the CDK module as a target for enhancing the potency of anti-tumor T cell responses. One Sentence SummaryThe Mediator kinase module is a primary regulator of T cell differentiation, and genetic or small molecule-based inhibition of this module enhances effector T cell potency.

immunology↗

bioRxiv2022

A unique epigenomic landscape defines CD8+ tissue-resident memory T cells

Memory T cells provide rapid and long-term protection against infection and tumors. The memory CD8+ T cell repertoire contains phenotypically and transcriptionally heterogeneous subsets with specialized functions and recirculation patterns. While these T cell populations have been well characterized in terms of differentiation potential and function, the epigenetic changes underlying memory T cell fate determination and tissue-residency remain largely unexplored. Here, we examined the single-cell chromatin landscape of CD8+ T cells over the course of acute viral infection. We reveal an early bifurcation of memory precursors displaying distinct chromatin accessibility and define epigenetic trajectories that lead to a circulating (TCIRC) or tissue-resident memory T (TRM) cell fate. While TRM cells displayed a conserved epigenetic signature across organs, we demonstrate that these cells exhibit tissue-specific signatures and identify transcription factors that regulate TRM cell populations in a site-specific manner. Moreover, we demonstrate that TRM cells and exhausted T (TEX) cells are distinct epigenetic lineages that are distinguishable early in their differentiation. Together, these findings show that TRM cell development is accompanied by dynamic alterations in chromatin accessibility that direct a unique transcriptional program resulting in a tissue-adapted and functionally distinct T cell state. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/490680v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@b03f1corg.highwire.dtl.DTLVardef@ff6871org.highwire.dtl.DTLVardef@220db2org.highwire.dtl.DTLVardef@1b15166_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIscATAC atlas reveals the epigenetic variance of memory CD8+ T cell subsets over the course of acute infection C_LIO_LIEarly bifurcation of memory precursors leads to circulating versus tissue-resident cell fates C_LIO_LIIntegrating transcriptional and epigenetic analyses identified organ-specific TRM cell regulators including HIC1 and BACH2 C_LIO_LIEpigenetic distinction of TRM cells and TEX cell subsets C_LI

immunology↗

bioRxiv2021

Systematic discovery of receptor-ligand biology by engineered cell entry and single-cell genomics

Cells communicate with each other via receptor-ligand interactions on the cell surface. Here we describe a technology for lentiviral-mediated cell entry by engineered receptor-ligand interaction (ENTER) to decode receptor specificity. Engineered lentiviral particles displaying specific ligands deliver fluorescent proteins into target cells upon cognate receptor-ligand interaction, without genome integration or transgene transcription. We optimize ENTER to decode interactions between T cell receptor (TCR)-MHC peptides, antibody-antigen, and other receptor-ligand pairs. We develop an effective presentation strategy to capture interactions between B cell receptor (BCR) and intracellular antigen epitopes. Single-cell readout of ENTER by RNA sequencing (ENTER-seq) enables multiplexed enumeration of TCR-antigen specificities, clonality, cell type, and cell states of individual T cells. ENTER-seq of patient blood samples after CMV infection reveals the viral epitopes that drive human effector memory T cell differentiation and inter-clonal phenotypic diversity that targets the same epitope. ENTER enables systematic discovery of receptor specificity, linkage to cell fates, and cell-specific delivery of gene or protein payloads. HIGHLIGHTSO_LIENTER displays ligands, deliver cargos, and records receptor specificity. C_LIO_LIENTER deorphanizes antigen recognition of TCR and BCR. C_LIO_LIENTER-seq maps TCR specificity, clonality and cell state in single cells. C_LIO_LIENTER-seq of patient sample decodes antiviral T cell memory. C_LI

genomics↗

bioRxiv2021

Clonal hematopoiesis is driven by aberrant activation of TCL1A

A diverse set of driver genes, such as regulators of DNA methylation, RNA splicing, and chromatin remodeling, have been associated with pre-malignant clonal expansion of hematopoietic stem cells (HSCs). The factors mediating expansion of these mutant clones remain largely unknown, partially due to a paucity of large cohorts with longitudinal blood sampling. To circumvent this limitation, we developed and validated a method to infer clonal expansion rate from single timepoint data called PACER (passenger-approximated clonal expansion rate). Applying PACER to 5,071 persons with clonal hematopoiesis accurately recapitulated the known fitness effects due to different driver mutations. A genome-wide association study of PACER revealed that a common inherited polymorphism in the TCL1A promoter was associated with slower clonal expansion. Those carrying two copies of this protective allele had up to 80% reduced odds of having driver mutations in TET2, ASXL1, SF3B1, SRSF2, and JAK2, but not DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 by CRISPR editing led to aberrant expression of TCL1A and expansion of HSCs in vitro. These effects were abrogated in HSCs from donors carrying the protective TCL1A allele. Our results indicate that the fitness advantage of multiple common driver genes in clonal hematopoiesis is mediated through TCL1A activation. PACER is an approach that can be widely applied to uncover genetic and environmental determinants of pre-malignant clonal expansion in blood and other tissues.

genetics↗

bioRxiv2021

TCR-BERT: learning the grammar of T-cell receptors for flexible antigen-binding analyses

The T-cell receptor (TCR) allows T-cells to recognize and respond to antigens presented by infected and diseased cells. However, due to TCRs staggering diversity and the complex binding dynamics underlying TCR antigen recognition, it is challenging to predict which antigens a given TCR may bind to. Here, we present TCR-BERT, a deep learning model that applies self-supervised transfer learning to this problem. TCR-BERT leverages unlabeled TCR sequences to learn a general, versatile representation of TCR sequences, enabling numerous downstream applications. We demonstrate that TCR-BERT can be used to build state-of-the-art TCR-antigen binding predictors with improved generalizability compared to prior methods. TCR-BERT simultaneously facilitates clustering sequences likely to share antigen specificities. It also facilitates computational approaches to challenging, unsolved problems such as designing novel TCR sequences with engineered binding affinities. Importantly, TCR-BERT enables all these advances by focusing on residues with known biological significance. TCR-BERT can be a useful tool for T-cell scientists, enabling greater understanding and more diverse applications, and provides a conceptual framework for leveraging unlabeled data to improve machine learning on biological sequences.

bioinformatics↗

bioRxiv2021

Macrophage inflammatory and regenerative response periodicity is programmed by cell cycle and chromatin state

Cell cycle (CC) is a fundamental biological process with robust, cyclical gene expression programs to facilitate cell division. In the immune system, a productive immune response requires the expansion of pathogen-responsive cell types, but whether CC also confers unique gene expression programs that inform the subsequent immunological response remains unclear. Here we demonstrate that single macrophages adopt different plasticity states in CC, which is a major source of heterogeneity in response to polarizing cytokines. Specifically, macrophage plasticity to interferon gamma (IFNG) is substantially reduced, while interleukin 4 (IL-4) can induce S-G2/M-biased gene expression. Additionally, IL-4 polarization shifts the CC-phase distribution of the population towards G2/M phase, providing a mechanism for reduced IFNG-induced repolarization. Finally, we show that macrophages express tissue remodeling genes in the S-G2/M-phases of CC, that can be also detected in vivo during muscle regeneration. Therefore, macrophage inflammatory and regenerative responses are gated by CC in a cyclical phase-dependent manner. HighlightsO_LISingle-cell chromatin maps reveal heterogeneous macrophage polarization states C_LIO_LICell cycle coincides with heterogeneity and alters macrophage plasticity to polarizing cytokines C_LIO_LIMacrophage polarization is a cell cycle phase-dependent immunological process C_LIO_LIS-G2/M-biased gene expression is linked to tissue remodeling and detected in proliferating macrophages during muscle regeneration C_LI

immunology↗

bioRxiv2020

Systematic discovery and functional interrogation of SARS-CoV-2 viral RNA-host protein interactions during infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a pandemic with growing global mortality. There is an urgent need to understand the molecular pathways required for host infection and anti-viral immunity. Using comprehensive identification of RNA-binding proteins by mass spectrometry (ChIRP-MS), we identified 309 host proteins that bind the SARS-CoV-2 RNA during active infection. Integration of this data with viral ChIRP-MS data from three other positive-sense RNA viruses defined pan-viral and SARS-CoV-2-specific host interactions. Functional interrogation of these factors with a genome-wide CRISPR screen revealed that the vast majority of viral RNA-binding proteins protect the host from virus-induced cell death, and we identified known and novel anti-viral proteins that regulate SARS-CoV-2 pathogenicity. Finally, our RNA-centric approach demonstrated a physical connection between SARS-CoV-2 RNA and host mitochondria, which we validated with functional and electron microscopy data, providing new insights into a more general virus-specific protein logic for mitochondrial interactions. Altogether, these data provide a comprehensive catalogue of SARS-CoV-2 RNA-host protein interactions, which may inform future studies to understand the mechanisms of viral pathogenesis, as well as nominate host pathways that could be targeted for therapeutic benefit. Highlights{middle dot} ChIRP-MS of SARS-CoV-2 RNA identifies a comprehensive viral RNA-host protein interaction network during infection across two species {middle dot} Comparison to RNA-protein interaction networks with Zika virus, dengue virus, and rhinovirus identify SARS-CoV-2-specific and pan-viral RNA protein complexes and highlights distinct intracellular trafficking pathways {middle dot} Intersection of ChIRP-MS and genome-wide CRISPR screens identify novel SARS-CoV-2-binding proteins with pro- and anti-viral function {middle dot} Viral RNA-RNA and RNA-protein interactions reveal specific SARS-CoV-2-mediated mitochondrial dysfunction during infection

microbiology↗

bioRxiv2020

Leveraging non-structural data to predict structures of protein-ligand complexes

Over the past fifty years, tremendous effort has been devoted to computational methods for predicting properties of ligands that bind macromolecular targets, a problem critical to rational drug design. Such methods generally fall into two categories: physics-based methods, which directly model ligand interactions with the target given the targets three-dimensional (3D) structure, and ligand-based methods, which predict ligand properties given experimental measurements for similar ligands. Here we present a rigorous statistical framework to combine these two sources of information. We develop a method to predict a ligands pose--the 3D structure of the ligand bound to its protein target--that leverages a widely available source of information: a list of other ligands that are known to bind the same target but for which no 3D structure is available. This combination of physics-based and ligand-based modeling improves upon state-of-the-art pose prediction accuracy across all major families of drug targets. As an illustrative application, we predict binding poses of antipsychotics and validate the results experimentally. Our statistical framework and results suggest broad opportunities to predict diverse ligand properties using machine learning methods that draw on physical modeling and ligand data simultaneously.

biophysics↗