Biology subjects

Yost, K. E.

Publications and source records attributed to Yost, K. E..

18 recordsLinked to original sources

bioRxiv2026

The diverse functions of viral microproteins

A large fraction of the uncharacterized proteome consists of microproteins. Viruses, rich in microproteins with potent activities, provide a unique system for exploring their functions and evolution. Here, we systematically annotate viral microproteins through a phenotype-first approach: construction of a >50,000-element small ORF library spanning the microprotein-coding potential of human-infecting viruses, followed by broad screens that enrich candidates for high-resolution profiling by Perturb-seq, mass spectrometry, AI-guided structure prediction, and mechanistic studies. This atlas identified >2,000 active microproteins that modulate host pathways through diverse mechanisms, including molecular mimicry, hijacking of key regulators, and altering subcellular localization. We further show the oncogenic potential of BNLF2b, an uncharacterized Epstein-Barr virus microprotein linked to nasopharyngeal carcinoma. Three principles emerge: viral microproteins are diverse and often multifunctional, show widespread convergence toward shared functions, and serve as reservoirs of evolutionary innovation. These findings elucidate how viral microproteins occupy a large functional landscape, establish them as versatile tools for host manipulation, and provide a framework for functional annotation of uncharacterized proteins, contributing toward predictive systems virology.

systems biology↗

bioRxiv2025

High-resolution spatial mapping of cell state and lineage dynamics in vivo with PEtracer

Charting the spatiotemporal dynamics of cell fate determination in development and disease is a long-standing objective in biology. Here we present the design, development, and extensive validation of PEtracer, a prime editing-based, evolving lineage tracing technology compatible with both single-cell sequencing and multimodal imaging methodologies to jointly profile cell state and lineage in dissociated cells or while preserving cellular context in tissues with high spatial resolution. Using PEtracer coupled with MERFISH spatial transcriptomic profiling in a syngeneic mouse model of tumor metastasis, we reconstruct the growth of individually-seeded tumors in vivo and uncover distinct modules of cell-intrinsic and cell-extrinsic factors that coordinate tumor growth. More generally, PEtracer enables systematic characterization of cell state and lineage relationships in intact tissues over biologically-relevant temporal and spatial scales.

molecular biology↗

bioRxiv2024

Spatiotemporal lineage tracing reveals the dynamic spatial architecture of tumor growth and metastasis

Tumour progression is driven by dynamic interactions between cancer cells and their surrounding microenvironment. Investigating the spatiotemporal evolution of tumours can provide crucial insights into how intrinsic changes within cancer cells and extrinsic alterations in the microenvironment cooperate to drive different stages of tumour progression. Here, we integrate high-resolution spatial transcriptomics and evolving lineage tracing technologies to elucidate how tumour expansion, plasticity, and metastasis co-evolve with microenvironmental remodelling in a Kras;p53-driven mouse model of lung adenocarcinoma. We find that rapid subclonal expansion contributes to a hypoxic, immunosuppressive, and fibrotic microenvironment that is associated with the emergence of pro-metastatic cancer cell states. Furthermore, metastases arise from spatially-confined subclones of primary tumours and remodel the distant metastatic niche into a fibrotic, collagen-rich microenvironment. Together, we present a comprehensive dataset integrating spatial assays and lineage tracing to elucidate how sequential changes in cancer cell state and microenvironmental structures cooperate to promote tumour progression.

cancer biology↗

bioRxiv2024

Regulation of immune signal integration and memory by inflammation-induced chromosome conformation

3-dimensional (3D) genome conformation is central to gene expression regulation, yet our understanding of its contribution to rapid transcriptional responses, signal integration, and memory in immune cells is limited. Here, we study the molecular regulation of the inflammatory response in primary macrophages using integrated transcriptomic, epigenomic, and chromosome conformation data, including base pair-resolution Micro-Capture C. We demonstrate that interleukin-4 (IL-4) primes the inflammatory response in macrophages by stably rewiring 3D genome conformation, juxtaposing endotoxin-, interferon-gamma-, and dexamethasone-responsive enhancers in close proximity to their cognate gene promoters. CRISPR-based perturbations of enhancer-promoter contacts or CCCTC-binding factor (CTCF) boundary elements demonstrated that IL-4-driven conformation changes are indispensable for enhanced and synergistic endotoxin-induced transcriptional responses, as well as transcriptional memory following stimulus removal. Moreover, transcriptional memory mediated by changes in chromosome conformation often occurred in the absence of changes in chromatin accessibility or histone modifications. Collectively, these findings demonstrate that rapid and memory transcriptional responses to immunological stimuli are encoded in the 3D genome.

genomics↗

bioRxiv2023

Disparate pathways for extrachromosomal DNA biogenesis and genomic DNA repair

Oncogene amplification on extrachromosomal DNA (ecDNA) is a pervasive driver event in cancer, yet our understanding of how ecDNA forms is limited. Here, we couple a CRISPR-based method for induction of ecDNA with extensive characterization of newly formed ecDNA to examine ecDNA biogenesis. We find that DNA circularization is efficient, irrespective of 3D genome context, with formation of a 1 Mb and 1.8 Mb ecDNA both reaching 15%. We show non-homologous end joining and microhomology mediated end joining both contribute to ecDNA formation, while inhibition of DNA-PKcs and ATM have opposing impacts on ecDNA formation. EcDNA and the corresponding chromosomal excision scar form at significantly different rates and respond differently to DNA-PKcs and ATM inhibition. Taken together, our results support a model of ecDNA formation in which double strand break ends dissociate from their legitimate ligation partners prior to joining of illegitimate ends to form the ecDNA and excision scar. SIGNIFICANCEOur study harnesses a CRISPR-based method to examine ecDNA biogenesis, uncovering efficient circularization between DSBs. ecDNAs and their corresponding chromosomal scars can form via NHEJ or MMEJ, but the ecDNA and scar formation processes are distinct. Based on our findings, we establish a mechanistic model of excisional ecDNA formation.

cancer biology↗

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

Divergent clonal differentiation trajectories of T cell exhaustion

T cells activated by chronic antigen exposure in the setting of viral infections or cancer can adopt an exhausted T cell (Tex) state, characterized by reduced effector function and proliferative capacity, and the upregulation of inhibitory receptors. However, whether all antigen-specific T cell clones follow the same molecular and cellular Tex differentiation trajectory remains unclear. Here, we generate a single-cell multi-omic atlas of T cell exhaustion that redefines the phenotypic diversity and molecular regulation of Tex phenotypes. Longitudinal analysis during chronic viral infection identifies an early effector phenotype that is epigenetically primed for Tex differentiation and two late-stage Tex cell states with either a terminal exhaustion or a killer cell lectin-like receptor (KLR)-expressing cytotoxic gene signature. We define clonal trajectories of antigen-specific T cells using paired single-cell RNA and T cell receptor sequencing and reveal distinct differentiation trajectories resulting in terminal Tex-biased, KLR Tex-biased, or divergent clones that differentiate into both phenotypes. Comparison of Tex phenotypes among shared T cell clones that traffic to multiple organs reveals that clonal differentiation trajectories are maintained across tissues. Finally, we show that differences in clonal differentiation trajectory are driven by TCR signal strength, whereby high-affinity T cell clones preferentially adopt a terminal Tex fate, while low-affinity clones adopt an effector-like KLR Tex fate that is detectable long-term but depleted in high antigen settings. These findings reveal clonal heterogeneity in the T cell response to chronic antigen and genomic programs that underlie Tex fates and persistence. HighlightsO_LIA single-cell atlas of T cell exhaustion identifies novel early effector and KLR Tex states. C_LIO_LIClonal T cell analysis defines divergent differentiation trajectories during chronic viral infection leading to terminal and KLR Tex fates. C_LIO_LIThe heterogeneity of the Tex pool arises from three primary differentiation patterns and are differentially persistent in the setting of high antigen. C_LIO_LIClonal Tex differentiation patterns are conserved across organ sites and driven by TCR signal strength. 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

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

Principles of ecDNA random inheritance drive rapid genome change and therapy resistance in human cancers

The foundational principles of Darwinian evolution are variation, selection, and identity by descent. Oncogene amplification on extrachromosomal DNA (ecDNA) is a common event, driving aggressive tumour growth, drug resistance, and shorter survival in patients1-4. Currently, the impact of non-chromosomal oncogene inheritance--random identity by descent--is not well understood. Neither is the impact of ecDNA on variation and selection. Here, integrating mathematical modeling, unbiased image analysis, CRISPR-based ecDNA tagging, and live-cell imaging, we identify a set of basic "rules" for how random ecDNA inheritance drives oncogene copy number and distribution, resulting in extensive intratumoural ecDNA copy number heterogeneity and rapid adaptation to metabolic stress and targeted cancer treatment. Observed ecDNAs obligatorily benefit host cell survival or growth and can change within a single cell cycle. In studies ranging from well-curated, patient-derived cancer cell cultures to clinical tumour samples from patients with glioblastoma and neuroblastoma treated with oncogene-targeted drugs, we show how these ecDNA inheritance "rules" can predict, a priori, some of the aggressive features of ecDNA-containing cancers. These properties are entailed by their ability to rapidly change their genomes in a way that is not possible for cancers driven by chromosomal oncogene amplification. These results shed new light on how the non-chromosomal random inheritance pattern of ecDNA underlies poor outcomes for cancer patients.

cancer biology↗

bioRxiv2021

Integrated spatial multi-omics reveals fibroblast fate during tissue repair

In the skin, tissue injury results in fibrosis in the form of scars composed of dense extracellular matrix deposited by fibroblasts. The therapeutic goal of regenerative wound healing has remained elusive in part because principles of fibroblast programming and adaptive response to injury remain incompletely understood. Here, we present a multimodal -omics platform for the comprehensive study of cell populations in complex tissue, which has allowed us to characterize the cells involved in wound healing across both time and space. We employ a stented wound model that recapitulates human tissue repair kinetics and multiple Rainbow transgenic lines to precisely track fibroblast fate during the physiologic response to injury. Through integrated analysis of single cell chromatin landscapes and gene expression states, coupled with spatial transcriptomic profiling, we are able to impute fibroblast epigenomes with temporospatial resolution. This has allowed us to define the mechanisms controlling cell fate during migration, proliferation, and differentiation following tissue injury and thereby reexamine the canonical phases of wound healing. These findings have broad implications for the study of tissue repair in complex organ systems.

bioinformatics↗

bioRxiv2020

EcDNA hubs drive cooperative intermolecular oncogene expression

Extrachromosomal DNAs (ecDNAs) are prevalent in human cancers and mediate high oncogene expression through elevated copy number and altered gene regulation1. Gene expression typically involves distal enhancer DNA elements that contact and activate genes on the same chromosome2,3. Here we show that ecDNA hubs, comprised of ~10-100 ecDNAs clustered in the nucleus of interphase cells, drive intermolecular enhancer input for amplified oncogene expression. Single-molecule sequencing, single-cell multiome, and 3D enhancer connectome reveal subspecies of MYC-PVT1 ecDNAs lacking enhancers that access intermolecular and ectopic enhancer-promoter interactions in ecDNA hubs. ecDNA hubs persist without transcription and are tethered by BET protein BRD4. BET inhibitor JQ1 disperses ecDNA hubs, preferentially inhibits ecDNA oncogene transcription, and kills ecDNA+ cancer cells. Two amplified oncogenes MYC and FGFR2 intermix in ecDNA hubs, engage in intermolecular enhancer-promoter interactions, and transcription is uniformly sensitive to JQ1. Thus, ecDNA hubs are nuclear bodies of many ecDNAs tethered by proteins and platforms for cooperative transcription, leveraging the power of oncogene diversification and combinatorial DNA interactions. We suggest ecDNA hubs, rather than individual ecDNAs, as units of oncogene function, cooperative evolution, and new targets for cancer therapy.

cancer biology↗

bioRxiv2020

BABEL enables cross-modality translation between multi-omic profiles at single-cell resolution

Simultaneous profiling of multi-omic modalities within a single cell is a grand challenge for single-cell biology. While there have been impressive technical innovations demonstrating feasibility - for example generating paired measurements of scRNA-seq and scATAC-seq - wide-spread application of joint profiling is challenging due to the experimental complexity, noise, and cost. Here we introduce BABEL, a deep learning method that translates between the transcriptome and chromatin profiles of a single cell. Leveraging a novel interoperable neural network model, BABEL can generate scRNA-seq directly from a cells scATAC-seq, and vice versa. This makes it possible to computationally synthesize paired multi-omic measurements when only one modality is experimentally available. Across several paired scRNA-seq and scATAC-seq datasets in human and mouse, we validate that BABEL accurately translates between these modalities for individual cells. BABEL also generalizes well to new biological contexts not seen during training. For example, starting from scATAC-seq of patient derived basal cell carcinoma (BCC), BABEL generated scRNA-seq that enabled fine-grained classification of complex cell states, despite having never seen BCC data. These predictions are comparable to analyses of the experimental BCC scRNA-seq data. We further show that BABEL can incorporate additional single-cell data modalities, such as CITE-seq, thus enabling translation across chromatin, RNA, and protein. BABEL offers a powerful approach for data exploration and hypothesis generation.

bioinformatics↗

bioRxiv2020

Polycomb-mediated Genome Architecture Enables Long-range Spreading of H3K27 methylation

Polycomb-group proteins play critical roles in gene silencing through the deposition of histone H3 lysine 27 trimethylation (H3K27me3) and chromatin compaction1-5. This process is essential for embryonic stem cell (ESCs) pluripotency, differentiation, and development. Polycomb repressive complex 2 (PRC2) can both read and write H3K27me3, enabling progressive spread of H3K27me3 on the linear genome6. Long-range Polycomb-associated DNA contacts have also been described, but their regulation and role in gene silencing remains unclear7-10. Here, we apply H3K27me3 HiChIP11-13, a protein-directed chromosome conformation method, and optical reconstruction of chromatin architecture14 to profile long-range Polycomb-associated DNA loops that span tens to hundreds of megabases across multiple topological associated domains in mouse ESCs and human induced pluripotent stem cells7-10. We find that H3K27me3 loop anchors are enriched for Polycomb nucleation points and coincide with key developmental genes, such as Hmx1, Wnt6 and Hoxa. Genetic deletion of H3K27me3 loop anchors revealed a coupling of Polycomb-associated genome architecture and H3K27me3 deposition evidenced by disruption of spatial contact between distant loci and altered H3K27me3 in cis, both locally and megabases away on the same chromosome. Further, we find that global alterations in PRC2 occupancy resulting from an EZH2 mutant15 selectively deficient in RNA binding is accompanied by loss of Polycomb-associated DNA looping. Together, these results suggest PRC2 acts as a "genomic wormhole", using RNA binding to enhance long range chromosome folding and H3K27me3 spreading. Additionally, developmental gene loci have novel roles in Polycomb spreading, emerging as important architectural elements of the epigenome.

genetics↗

bioRxiv2020

Latent Plasticity of Effector-like Exhausted CD8 T cells contributes to memory responses

Persistent antigen induces a dysfunctional CD8 T cell state known as T cell "exhaustion" characterized by expression of PD-1 and decreased effector functions. Nevertheless, dysfunctional CD8 T cells can mediate control of antigen burden which is long-lasting. While heterogeneity of exhausted CD8 T cells has been described, the cells which actively proliferate and exert viral control have remained elusive. Here, we define subsets of PD-1+ CD8 T cells during chronic infection marked by expression of CX3CR1 with substantial in situ proliferation and high expression of granzyme B. Moreover, these cells maintain the effector pool through self-renewal independently of previously defined stem-like cells. Unexpectedly, CX3CR1+ CD8 T cells retain plasticity to be reprogrammed to memory cells through expression of TCF-1 and re-gain polyfunctionality. Thus, we define a subset of effector-like exhausted CD8 T cells with capacity to contribute to the memory pool, offering a prime target for novel immunotherapies.

immunology↗

bioRxiv2019

Spen links RNA-mediated endogenous retrovirus silencing and X chromosome inactivation

Dosage compensation between the sexes has emerged independently multiple times during evolution, often harnessing long noncoding RNAs (lncRNAs) to alter gene expression on the sex chromosomes. In eutherian mammals, X chromosome inactivation (XCI) in females proceeds via the lncRNA Xist, which coats one of the two X chromosomes and recruits repressive proteins to epigenetically silence gene expression in cis1,2. How Xist evolved new functional RNA domains to recruit ancient, pleiotropic protein partners is of great interest. Here we show that Spen, an Xist-binding repressor protein essential for XCI3-7, binds to ancient retroviral RNA, performing a surveillance role to recruit chromatin silencing machinery to these parasitic loci. Spen inactivation leads to de-repression of a subset of endogenous retroviral (ERV) elements in embryonic stem cells, with gain of chromatin accessibility, active histone modifications, and ERV RNA transcription. Spen binds directly to ERV RNAs that show structural similarity to the A-repeat of Xist, a region critical for Xist-mediated gene silencing8-9. ERV RNA and Xist A-repeat bind the RRM3 domain of Spen in a competitive manner. Insertion of an ERV into an A-repeat deficient Xist rescues binding of Xist RNA to Spen and results in local gene silencing in cis. These results suggest that insertion of an ERV element into proto-Xist may have been a critical evolutionary event, which allowed Xist to coopt transposable element RNA-protein interactions to repurpose powerful antiviral chromatin silencing machinery for sex chromosome dosage compensation.

genomics↗

bioRxiv2019

Clonal replacement of tumor-specific T cells following PD-1 blockade

Immunotherapies that block inhibitory checkpoint receptors on T cells have transformed the clinical care of cancer patients. However, which tumor-specific T cells are mobilized following checkpoint blockade remains unclear. Here, we performed paired single-cell RNA- and T cell receptor (TCR)-sequencing on 79,046 cells from site-matched tumors from patients with basal cell carcinoma (BCC) or squamous cell carcinoma (SCC) pre- and post-anti-PD-1 therapy. Tracking TCR clones and transcriptional phenotypes revealed a coupling of tumor-recognition, clonal expansion, and T cell dysfunction: the T cell response to treatment was accompanied by clonal expansions of CD8+CD39+ T cells, which co-expressed markers of chronic T cell activation and exhaustion. However, this expansion did not derive from pre-existing tumor infiltrating T cell clones; rather, it comprised novel clonotypes, which were not previously observed in the same tumor. Clonal replacement of T cells was preferentially observed in exhausted CD8+ T cells, compared to other distinct T cell phenotypes, and was evident in BCC and SCC patients. These results, enabled by single-cell multi-omic profiling of clinical samples, demonstrate that pre-existing tumor-specific T cells may be limited in their capacity for re-invigoration, and that the T cell response to checkpoint blockade relies on the expansion of a distinct repertoire of T cell clones that may have just recently entered the tumor.

immunology↗

bioRxiv2019

Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion

Understanding complex tissues requires single-cell deconstruction of gene regulation with precision and scale. Here we present a massively parallel droplet-based platform for mapping transposase-accessible chromatin in tens of thousands of single cells per sample (scATAC-seq). We obtain and analyze chromatin profiles of over 200,000 single cells in two primary human systems. In blood, scATAC-seq allows marker-free identification of cell type-specific cis- and trans-regulatory elements, mapping of disease-associated enhancer activity, and reconstruction of trajectories of differentiation from progenitors to diverse and rare immune cell types. In basal cell carcinoma, scATAC-seq reveals regulatory landscapes of malignant, stromal, and immune cell types in the tumor microenvironment. Moreover, scATAC-seq of serial tumor biopsies before and after PD-1 blockade allows identification of chromatin regulators and differentiation trajectories of therapy-responsive intratumoral T cell subsets, revealing a shared regulatory program driving CD8+ T cell exhaustion and CD4+ T follicular helper cell development. We anticipate that droplet-based single-cell chromatin accessibility will provide a broadly applicable means of identifying regulatory factors and elements that underlie cell type and function.

genomics↗