Single-cell ATAC Sequencing Research Articles

EPCO-51. A MULTI-OMIC ANALYSIS OF REGIONAL HETEROGENEITY IN GLIOBLASTOMA

Abstract Glioblastoma (GBM) is the most common malignant brain tumor in adults. A hallmark of GBM is its intratumoral heterogeneity as well as infiltration into the surrounding brain. The growing understanding of the cellular diversity and cellular state diversity within GBM necessitates a need for a more granular evaluation of the molecular landscape of this disease. This study aimed to investigate this using single cell RNA sequencing combined with single-cell ATAC sequencing and spatial transcriptomics in order to delineate cellular states and enriched pathways between malignant cells in different regions of GBM. The study cohort consisted of 15 patients with primary GBM. Tumor samples were taken at the time of surgical resection using intraoperative stereotactic navigation from three anatomically distinct locations: periphery – the cortex or white matter in the peri-tumoral region that is beyond contrast-enhancing tumor, border – the contrast-enhancing border of the tumor on T1-weighted MRI, and core - the hypointense core region on T1-weighted MRI. Samples underwent combined snRNA and ATAC sequencing (10x Multiome) as well as spatial transcriptomics (10x Visium). Single-nucleus RNA + ATAC sequencing captured a total of 37,547 neoplastic cells and 18,498 non-neoplastic cells within the tumor microenvironment. The majority of non-neoplastic cells were identified within the periphery alongside a distinct group of neoplastic cells that exhibited unique a unique distribution of malignant cellular state and differentially regulated genetic pathways compared to malignant cells within the tumor border and core. Gene regulatory analysis of the malignant cells in the periphery identified a previously undefined set of enriched transcription factors that are periphery-specific regulon drivers. Overall, this analysis sheds light on the genetic and epigenetic differences between malignant GBM cells based on their location and warrant further investigation into the biology and targetable aspects of the malignant cells that exist beyond the contrast-enhancing border of the tumor.

ChromaFold predicts the 3D contact map from single-cell chromatin accessibility

Identifying cell-type-specific 3D chromatin interactions between regulatory elements can help decipher gene regulation and interpret disease-associated non-coding variants. However, achieving this resolution with current 3D genomics technologies is often infeasible given limited input cell numbers. We therefore present ChromaFold, a deep learning model that predicts 3D contact maps, including regulatory interactions, from single-cell ATAC sequencing (scATAC-seq) data alone. ChromaFold uses pseudobulk chromatin accessibility, co-accessibility across metacells, and a CTCF motif track as inputs and employs a lightweight architecture to train on standard GPUs. Trained on paired scATAC-seq and Hi-C data in human samples, ChromaFold accurately predicts the 3D contact map and peak-level interactions across diverse human and mouse test cell types. Compared to leading contact map prediction models that use ATAC-seq and CTCF ChIP-seq, ChromaFold achieves state-of-the-art performance using only scATAC-seq. Finally, fine-tuning ChromaFold on paired scATAC-seq and Hi-C in a complex tissue enables deconvolution of chromatin interactions across cell subpopulations.

Abstract C077: Functional Dissection of the Highly Plastic Basal Cell State in Pancreatic Cancer

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a treatment-refractory malignancy with a dismal prognosis. Targeting cancer cell plasticity—the capacity to adapt to cell-extrinsic pressure via non-genetic mechanisms—is a promising therapeutic strategy, yet cell states within PDAC harboring high plasticity remain poorly understood. Using genetically engineered mouse models driven by oncogenic KrasG12D and loss of p53 (“KPC” model), we profiled primary PDAC tumors using single-cell RNA sequencing and single cell ATAC sequencing. We identified a cancer cell differentiation state that co-expresses both epithelial and mesenchymal programs and has a distinct epigenetic landscape with accessible chromatin across gene sets that mark cancer cell states with divergent phenotypes, suggesting that this cell state is primed for cell state switching. Notably, this high-plasticity cell state (HPCS) signature aligns with a "basal" signature in human PDAC, which associates with poor prognosis and chemoresistance. To functionally interrogate the HPCS in PDAC progression, we developed a novel lineage-tracing and ablation system. Lineage-tracing experiments revealed that the HPCS has a robust capacity for differentiation into epithelial and mesenchymal states, indicating that the HPCS is functionally plastic and acts as a source of fixed malignant states. Strikingly, targeted elimination of the HPCS over short time periods resulted in tumor collapse, underscoring a critical role in tumor maintenance. Further, we found that the HPCS is highly dependent on KRAS activity, with acute KRAS inhibitor treatment leading to a selective depletion of the HPCS. Taken together, our data indicates that PDAC harbors a striking dependency on the HPCS and encourages therapeutic approaches aimed at eradicating this critical subset of cancer cells. Citation Format: Anupriya Singhal, Hannah C. Styers, Jonathan Rub, Zhuxuan Li, Zeynep Tarcan, Jill Hallin, Olca Basturk, Rona Yaeger, James G. Christensen, Doron Betel, Yan Yan, Elisa de Stanchina, Tuomas Tammela. Functional Dissection of the Highly Plastic Basal Cell State in Pancreatic Cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C077.

Transcription Factor Activity Regulating Macrophage Heterogeneity during Skin Wound Healing.

Monocytes and macrophages (Mos/Mϕs) play diverse roles in wound healing by adopting a spectrum of functional phenotypes; however, the regulation of such heterogeneity remains poorly defined. We enhanced our previously published Bayesian inference TF activity model, incorporating both single-cell RNA sequencing and single-cell ATAC sequencing data to infer transcription factor (TF) activity in Mos/Mϕs during skin wound healing. We found that wound Mos/Mϕs clustered into early-stage Mos/Mϕs, late-stage Mϕs, and APCs, and that each cluster showed differential chromatin accessibility and differential predicted TF activity that did not always correlate with mRNA or protein expression. Network analysis revealed two highly connected large communities involving a total of 19 TFs, highlighting TF cooperation in regulating wound Mos/Mϕs. This analysis also revealed a small community populated by NR4A1 and NFKB1, supporting a proinflammatory link between these TFs. Importantly, we validated a proinflammatory role for NR4A1 activity during wound healing, showing that Nr4a1 knockout mice exhibit decreased inflammatory gene expression in early-stage wound Mos/Mϕs, along with delayed wound re-epithelialization and impaired granulation tissue formation. In summary, our study provides insight into TF activity that regulates Mo/Mϕ heterogeneity during wound healing and provides a rational basis for targeting Mo/Mϕ TF networks to alter phenotypes and improve healing.

Single-cell approaches define two groups of mammalian oligodendrocyte precursor cells and their evolution over developmental time

Here, we used single-cell RNA sequencing (scRNA-seq), single-cell ATAC sequencing (scATAC-seq), and single-cell spatial transcriptomics to characterize murine cortical OPCs throughout postnatal life. During development, we identified two groups of differentially localized PDGFRα+ OPCs that are transcriptionally and epigenetically distinct. One group (active, or actOPCs) is metabolically active and enriched in white matter. The second (homeostatic, or hOPCs) is less active, enriched in gray matter, and predicted to derive from actOPCs. In adulthood, these two groups are transcriptionally but not epigenetically distinct, and relative to developing OPCs are less active metabolically and have less open chromatin. When adult oligodendrogenesis is enhanced during experimentally induced remyelination, adult OPCs do not reacquire a developmental open chromatin state, and the oligodendrogenesis trajectory is distinct from that seen neonatally. These data suggest that there are two OPC groups subserving distinct postnatal functions and that neonatal and adult OPC-mediated oligodendrogenesis are fundamentally different.

HyGAnno: hybrid graph neural network-based cell type annotation for single-cell ATAC sequencing data.

Reliable cell type annotations are crucial for investigating cellular heterogeneity in single-cell omics data. Although various computational approaches have been proposed for single-cell RNA sequencing (scRNA-seq) annotation, high-quality cell labels are still lacking in single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) data, because of extreme sparsity and inconsistent chromatin accessibility between datasets. Here, we present a novel automated cell annotation method that transfers cell type information from a well-labeled scRNA-seq reference to an unlabeled scATAC-seq target, via a parallel graph neural network, in a semi-supervised manner. Unlike existing methods that utilize only gene expression or gene activity features, HyGAnno leverages genome-wide accessibility peak features to facilitate the training process. In addition, HyGAnno reconstructs a reference-target cell graph to detect cells with low prediction reliability, according to their specific graph connectivity patterns. HyGAnno was assessed across various datasets, showcasing its strengths in precise cell annotation, generating interpretable cell embeddings, robustness to noisy reference data and adaptability to tumor tissues.

Abstract 4943: Benchmarking unpaired single-cell RNA and single-cell ATAC integration

Abstract The integration of single-cell RNA-sequencing (scRNA-seq) and single-cell ATAC-sequencing (scATAC-seq) data offers a unique opportunity to gain a comprehensive view of cellular identity with defining features and to infer gene-regulatory relationships. Despite the emergence of technologies that simultaneously capture both the gene expression and chromatin accessibility of individual cells (paired data), the practical challenges of these approaches (e.g., the unavailability in previous samples and prohibitive cost) have led researchers to turn to the existing trove of single-modality data generated from independent biological samples (unpaired data). Various computational tools have been developed to integrate these unpaired single modality datasets. However, the comparative performance of these tools has not been comprehensively evaluated, and a standard benchmark pipeline is still lacking. To address these challenges, we used pseudo-unpaired scRNA-seq and scATAC-seq data derived from publicly available paired single-cell multi-omics datasets to benchmark 14 publicly available integration methods. The primary goal of unpaired single-cell multi-omics integration is to narrow the omics gap while preserving cell type diversity. We therefore focused on pair-wise cell distance and cluster performance in the joint latent space constructed by various integration tools in our benchmarking pipeline. To ensure the robustness of these computational approaches, we examined their stability across a variety of scenarios, including variations in cell number, cell types, and biological and technical batch effects. A number of the integration methods tested produced promising results. While the widely used Seurat package was recently reported to have the best performance (Lee et al., Genome Biology 2023), other computational tools such as scVI, Cobolt, scJoint, scglue and scBridge performed equally well or better in reducing omics differences and facilitating the identification of cell clusters. Notably, scglue and Cobolt demonstrated strong performance in aligning the same cell from different modalities, and discrete clusters emerged in the joint latent space using scJoint and scBridge. These findings suggest that it may not be strictly necessary to use paired multi-omics data to guide integration to achieve favorable results. Our freely available benchmarking pipeline will empower researchers to identify the optimal data integration methods for their specific data, facilitate the benchmarking of new methods, and contribute to future method development in the field. Citation Format: Jiani Chen, Wanzi Xiao, Eric Zhang, Xiang Chen. Benchmarking unpaired single-cell RNA and single-cell ATAC integration [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4943.

Cross-Omic Transcription Factor Analysis: An Insight on Transcription Factor Accessibility and Expression Correlation.

It is well known how sequencing technologies propelled cellular biology research in recent years, providing incredible insight into the basic mechanisms of cells. Single-cell RNA sequencing is at the front in this field, with single-cell ATAC sequencing supporting it and becoming more popular. In this regard, multi-modal technologies play a crucial role, allowing the possibility to simultaneously perform the mentioned sequencing modalities on the same cells. Yet, there still needs to be a clear and dedicated way to analyze these multi-modal data. One of the current methods is to calculate the Gene Activity Matrix (GAM), which summarizes the accessibility of the genes at the genomic level, to have a more direct link with the transcriptomic data. However, this concept is not well defined, and it is unclear how various accessible regions impact the expression of the genes. Moreover, the transcription process is highly regulated by the transcription factors that bind to the different DNA regions. Therefore, this work presents a continuation of the meta-analysis of Genomic-Annotated Gene Activity Matrix (GAGAM) contributions, aiming to investigate the correlation between the TF expression and motif information in the different functional genomic regions to understand the different Transcription Factors (TFs) dynamics involved in different cell types.

A distinct human cell type expressing MHCII and RORγt with dual characteristics of dendritic cells and type 3 innate lymphoid cells.

Recent studies have characterized various mouse antigen-presenting cells (APCs) expressing the lymphoid-lineage transcription factor RORγt (Retinoid-related orphan receptor gamma t), which exhibit distinct phenotypic features and are implicated in the induction of peripheral regulatory T cells (Tregs) and immune tolerance to microbiota and self-antigens. These APCs encompass Janus cells and Thetis cell subsets, some of which express the AutoImmune REgulator (AIRE). RORγt+ MHCII+ type 3 innate lymphoid cells (ILC3) have also been implicated in the instruction of microbiota-specific Tregs. While RORγt+ APCs have been actively investigated in mice, the identity and function of these cell subsets in humans remain elusive. Herein, we identify a rare subset of RORγt+ cells with dendritic cell (DC) features through integrated single-cell RNA sequencing and single-cell ATAC sequencing. These cells, which we term RORγt+ DC-like cells (R-DC-like), exhibit DC morphology, express the MHC class II machinery, and are distinct from all previously reported DC and ILC3 subsets, but share transcriptional and epigenetic similarities with DC2 and ILC3. We have developed procedures to isolate and expand them in vitro, enabling their functional characterization. R-DC-like cells proliferate in vitro, continue to express RORγt, and differentiate into CD1c+ DC2-like cells. They stimulate the proliferation of allogeneic T cells. The identification of human R-DC-like cells with proliferative potential and plasticity toward CD1c+ DC2-like cells will prompt further investigation into their impact on immune homeostasis, inflammation, and autoimmunity.

Single-cell sequencing highlights heterogeneity and malignant progression in actinic keratosis and cutaneous squamous cell carcinoma.

Cutaneous squamous cell carcinoma (cSCC) is the second most frequent of the keratinocyte-derived malignancies with actinic keratosis (AK) as a precancerous lesion. To comprehensively delineate the underlying mechanisms for the whole progression from normal skin to AK to invasive cSCC, we performed single-cell RNA sequencing (scRNA-seq) to acquire the transcriptomes of 138,982 cells from 13 samples of six patients including AK, squamous cell carcinoma in situ (SCCIS), cSCC, and their matched normal tissues, covering comprehensive clinical courses of cSCC. We identified diverse cell types, including important subtypes with different gene expression profiles and functions in major keratinocytes. In SCCIS, we discovered the malignant subtypes of basal cells with differential proliferative and migration potential. Differentially expressed genes (DEGs) analysis screened out multiple key driver genes including transcription factors along AK to cSCC progression. Immunohistochemistry (IHC)/immunofluorescence (IF) experiments and single-cell ATAC sequencing (scATAC-seq) data verified the expression changes of these genes. The functional experiments confirmed the important roles of these genes in regulating cell proliferation, apoptosis, migration, and invasion in cSCC tumor. Furthermore, we comprehensively described the tumor microenvironment (TME) landscape and potential keratinocyte-TME crosstalk in cSCC providing theoretical basis for immunotherapy. Together, our findings provide a valuable resource for deciphering the progression from AK to cSCC and identifying potential targets for anticancer treatment of cSCC.

Modeling fragment counts improves single-cell ATAC-seq analysis.

Single-cell ATAC sequencing coverage in regulatory regions is typically binarized as an indicator of open chromatin. Here we show that binarization is an unnecessary step that neither improves goodness of fit, clustering, cell type identification nor batch integration. Fragment counts, but not read counts, should instead be modeled, which preserves quantitative regulatory information. These results have immediate implications for single-cell ATAC sequencing analysis.

ASCL1 induces neurogenesis in human Müller glia

In mammals, loss of retinal cells due to disease or trauma is an irreversible process that can lead to blindness. Interestingly, regeneration of retinal neurons is a well established process in some non-mammalian vertebrates and is driven by the Müller glia (MG), which are able to re-enter the cell cycle and reprogram into neurogenic progenitors upon retinal injury or disease. Progress has been made to restore this mechanism in mammals to promote retinal regeneration: MG can be stimulated to generate new neurons invivo in the adult mouse retina after the over-expression of the pro-neural transcription factor Ascl1. In this study, we applied the same strategy to reprogram human MG derived from fetal retina and retinal organoids into neurons. Combining single cell RNA sequencing, single cell ATAC sequencing, immunofluorescence, and electrophysiology we demonstrate that human MG can be reprogrammed into neurogenic cells invitro.

A Longitudinal Single-Cell Atlas of Treatment Response in Pediatric AML

Introduction: Pediatric acute myeloid leukemia (pAML) is a heterogeneous disease in terms of driver alterations, treatment response and patient outcomes. Although approximately 90% of pAML patients respond to initial treatment, tumours relapse frequently. Despite large-scale genomic sequencing efforts, it remains elusive why tumors relapse. Previously, mutations have been identified that affect transcriptional regulation, indicating that epigenetic processes may contribute to treatment resistance in pAML. We therefore studied how tumor epigenetic patterns, transcriptional regulation and cell populations change over the course of treatment using single-cell ATAC sequencing (scATAC-seq) and single-cell RNA sequencing (scRNA-seq) in pediatric populations. Methods: We profiled 330,047 cells using scRNA-seq and 353,984 cells using scATAC-seq derived from 28 uniformly treated pAML patients, driven by either MLL fusions, CBFB fusions, RUNX1 fusions, FLT3-ITD or other aberrations (i.e. CEBPA mutations). All patients were enrolled in the AAML1031 trial (https://childrensoncologygroup.org/aaml1031), a randomized phase 3 clinical trial that investigated the addition of Bortezomib (BTZ) and Sorafenib to standard treatment modalities. Samples were obtained serially at diagnosis, at remission and at relapse and single-cell profiles were compared between these stages. Results: We identified malignant and non-malignant populations in the scATAC-seq and scRNA-seq data, showing that in all cases, malignant cells from patients at diagnosis were distinct from those taken at relapse. Major differences between diagnosis and relapse were associated with differentiation, and by inferring distinct cell populations we identified that relapsed cell populations appeared to shift towards a more primitive state. The extent of this shift was dependent on the genetic subtype and the effects were more pronounced in MLL-rearranged tumors. To identify the candidate mechanisms and transcription factors involved in this shift we studied the monocytic, lymphocytic and erythrocytic lineages in non-malignant cells and compared these to the tumor at diagnosis and relapse. Based on motif enrichment we found that across all different subgroups, transcription factors (TFs) that drive monocytic differentiation (i.e. CEBPA) have a lower activity while TFs driving erythrocytic and lymphocytic differentiation (i.e. TCF3) have a higher activity. Analysis of hematopoietic stem-like and progenitor-like cells (HSPC-like) confirmed this change, indicating that the “priming” towards other lineages is not only a result of shifts in cell populations but also a result of rewiring of early progenitors. To investigate this rewiring, we analysed regions of open chromatin that were enriched in malignant HSPCs compared to normal HSPCs across different subgroups. We found that those regions were highly specific to the driving alteration and were enriched for MEF2C binding sites in MLL-driven tumors and AP-1 binding sites in other tumors. Overall, upon relapse MEF2C expression and inferred TF activity appeared to increase, coinciding with an apparent increase in lymphoid priming and early lymphoid factors including LMO2, LYL1 and TCF3, among others. Two cases in the cohort appeared to switch lineage from a monocytic to lymphocytic phenotype and were enriched in CD19 and CD79A positive malignant cells upon relapse. Both cases shared the characteristic that MEF2C was upregulated upon relapse and showed upregulation of typical B-lymphoid transcription factors such as PAX5. Discussion: By generating a large dataset of pediatric AML patient samples collected at diagnosis, remission and relapse, we have identified changes in cellular hierarchies and transcriptional networks that occur upon relapse. Our study shows that shifts in cell populations readily occur upon treatment and are dependent on subgroup-defining alterations. Particularly MLL-rearranged tumors show a high level of plasticity that could explain the poor outcome of this group. Furthermore, we show that tumors appear to adapt their transcriptional programs towards a more “stem-like” state, with a likely higher propensity to differentiate towards other lineages such as the lymphoid lineage. We have identified MEF2C as a possible regulator of these processes, opening a new perspective to target the plasticity of these tumors.

Genome-wide profiling of transcription factor activity in primary liver cancer using single-cell ATAC sequencing

Primary liver cancer (PLC) consists of two main histological subtypes; hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). The role of transcription factors (TFs) in malignant hepatobiliary lineage commitment between HCC and iCCA remains underexplored. Here, we present genome-wide profiling of transcription regulatory elements of 16 PLC patients using single-cell assay for transposase accessible chromatin sequencing. Single-cell open chromatin profiles reflect the compositional diversity of liver cancer, identifying both malignant and microenvironment component cells. TF motif enrichment levels of 31 TFs strongly discriminate HCC from iCCA tumors. These TFs are members of the nuclear/retinoid receptor, POU, or ETS motif families. POU factors are associated with prognostic features in iCCA. Overall, nuclear receptors, ETS and POU TF motif families delineate transcription regulation between HCC and iCCA tumors, which may be relevant to development and selection of PLC subtype-specific therapeutics.

Single-cell ATAC sequencing illuminates the cis-regulatory differentiation of taxol biosynthesis between leaf mesophyll and leaf epidermal cells in Taxus mairei

Taxol is a widely used anticancer drug; however, its accumulation pattern can vary largely among leaf tissues. Taxol biosynthesis is driven by a series of transcription factors (TFs), but the extent of chromatin changes that functionally regulate gene expression associated with taxol biosynthesis remain poorly understood. To assess the effects of tissue heterogeneity on taxol biosynthesis, we applied single-cell transposase-accessible chromatin sequencing to Taxus mairei leaves and identified differentially accessible regions. We captured 9488 independent cells with 42,192 fragment reads per cell. In total, 66.64% were confidently mapped onto the T. mairei genome. Projection analysis divided all the cells into nine clusters, which suggests a high degree of cell heterogeneity in T. mairei leaves. Based on the cell type markers, Clusters 2 and 7 were annotated as leaf mesophyll cells, and Clusters 5 and 6 were annotated as leaf epidermal cells. A differential accessibility analysis identified 9600 and 8538 leaf mesophyll and epidermal, respectively, cell-specific open chromatin regions. We predicted the genomic features of the genes involved in different stages of taxol biosynthesis, and there was a close correlation between chromatin open peaks and the expression levels of several taxol biosynthesis-related genes. We further identified a number of cell type-specific TF motifs and reference TFs that appeared to be involved in taxol biosynthesis. The study of T. mairei leaves at a single-cell resolution provides a valuable resource for determining the basic principles of the cell type-specific regulation of taxol biosynthesis.

A scATAC-seq atlas of chromatin accessibility in axolotl brain regions

Axolotl (Ambystoma mexicanum) is an excellent model for investigating regeneration, the interaction between regenerative and developmental processes, comparative genomics, and evolution. The brain, which serves as the material basis of consciousness, learning, memory, and behavior, is the most complex and advanced organ in axolotl. The modulation of transcription factors is a crucial aspect in determining the function of diverse regions within the brain. There is, however, no comprehensive understanding of the gene regulatory network of axolotl brain regions. Here, we utilized single-cell ATAC sequencing to generate the chromatin accessibility landscapes of 81,199 cells from the olfactory bulb, telencephalon, diencephalon and mesencephalon, hypothalamus and pituitary, and the rhombencephalon. Based on these data, we identified key transcription factors specific to distinct cell types and compared cell type functions across brain regions. Our results provide a foundation for comprehensive analysis of gene regulatory programs, which are valuable for future studies of axolotl brain development, regeneration, and evolution, as well as on the mechanisms underlying cell-type diversity in vertebrate brains.

Sézary syndrome originates from heavily mutated hematopoietic progenitors

AbstractThe pathogenesis of cutaneous T-cell lymphoma (CTCL) remains unclear. Using single-cell RNA or T-cell receptor (TCR) sequencing of 32 619 CD3+CD4+ and CD26+/CD7+ and 29 932 CD3+CD4+ and CD26−/CD7− lymphocytes from the peripheral blood of 7 patients with CTCL, coupled to single-cell ATAC-sequencing of 26,411 CD3+CD4+ and CD26+/CD7+ and 33 841 CD3+CD4+ and CD26−/CD7− lymphocytes, we show that tumor cells in Sézary syndrome and mycosis fungoides (MF) exhibit different phenotypes and trajectories of differentiation. When compared to MF, Sézary cells exhibit narrower repertoires of TCRs and exhibit clonal enrichment. Surprisingly, we identified ≥200 mutations in hematopoietic stem cells from multiple patients with Sézary syndrome. Mutations in key oncogenes were also present in peripheral Sézary cells, which also showed the hallmarks of recent thymic egression. Together our data suggest that CTCL arises from mutated lymphocyte progenitors that acquire TCRs in the thymus, which complete their malignant transformation in the periphery.

Prmt5 deficiency inhibits CD4+ T-cell Klf2/S1pr1 expression and ameliorates EAE disease

BackgroundProtein arginine methyltransferase 5 (Prmt5) is the main type II methyltransferase, catalyzes protein arginine residue symmetric dimethylation, and modulates normal cellular physiology and disease progression. Prmt5 inhibition or deletion in CD4+ T cells has been reported to ameliorate experimental autoimmune encephalomyelitis (EAE), but the detailed molecular mechanisms have not yet been elucidated.MethodsEAE was induced by administration of myelin oligodendrocyte glycoprotein (MOG35–55) in T cells Prmt5 conditional knockout (CD4-cre-Prmt5fl/fl, Prmt5cko) and Prmt5fl/fl (WT) mice. Flow cytometry, single-cell RNA sequencing, ATAC sequencing and chromatin immunoprecipitation assay (ChIP) approaches were used to explore the detail mechanisms.ResultsWe find that Prmt5cko mice are resistant to EAE; infiltrating inflammatory CD4+ T cells in the central nervous system (CNS) are greatly reduced. However, in Prmt5cko mice, T cells in the spleen show much more proliferation and activation properties, the total number of CD4+ T cells in the spleen is not reduced, and the percentage of Rora+ CD4+ T cells is elevated. Also, CD4+ T cells express lower levels of S1pr1 and Klf2 than WT mice, which may influence pathogenic CD4+ T-cell egress from the spleen and migration to the CNS. Moreover, the single-cell ATAC sequence and ChIP assay reveal that the transcription factor Klf2 is enriched at the S1pr1 promoter and that Klf2 motif activity is reduced in Prmt5cko mice.ConclusionsOur study delineates the undiscovered role of Prmt5 in T-cell biology in which Prmt5 may inhibit Klf2-S1pr1 pathway to ameliorate EAE disease. Controlling T-cell Prmt5 expression may be helpful for the treatment of autoimmune diseases.

Multimodal single-cell analysis of non-random heteroplasmy distribution in human retinal mitochondrial disease.

Variants within the high copy number mitochondrial genome (mtDNA) can disrupt organelle function and lead to severe multi-system disease. The wide range of manifestations observed in mitochondrial disease patients results from varying fractions of abnormal mtDNA molecules in different cells and tissues, a phenomenon termed heteroplasmy. However, the landscape of heteroplasmy across cell types within tissues and its influence on phenotype expression in affected patients remains largely unexplored. Here, we identify non-random distribution of a pathogenic mtDNA variant across a complex tissue using single-cell RNA sequencing, mitochondrial single-cell ATAC sequencing, and multimodal single-cell sequencing. We profile the transcriptome, chromatin accessibility state, and heteroplasmy in cells from the eyes of a patient with mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MELAS) and healthy control donors. Utilizing the retina as a model for complex multi-lineage tissues, we found that the proportion of the pathogenic m.3243A>G allele was neither evenly nor randomly distributed across diverse cell types. All neuroectoderm-derived neural cells exhibited a high percentage of the mutant variant. However, a subset of mesoderm-derived lineage, namely the vasculature of the choroid, was near homoplasmic for the wildtype allele. Gene expression and chromatin accessibility profiles of cell types with high and low proportions of m.3243A>G implicate mTOR signaling in the cellular response to heteroplasmy. We further found by multimodal single-cell sequencing of retinal pigment epithelial cells that a high proportion of the pathogenic mtDNA variant was associated with transcriptionally and morphologically abnormal cells. Together, these findings show the non-random nature of mitochondrial variant partitioning in human mitochondrial disease and underscore its implications for mitochondrial disease pathogenesis and treatment.

Injury-induced hair growth response is promoted by tissue macrophages via insulin-like growth factor 1

Abstract Hair follicles (HFs) produce hair to mediate the first line of defense in mammals. HFs undergo cyclical production of hair (anagen), and while this process is unsynchronized during adulthood, external cues, including shaving, induce synchronized anagen and bolster the surface barrier. Herein, we show that macrophages were crucial in promoting anagen. Shaving triggered the accumulation of macrophages to the secondary hair germs (SHG), which underwent proliferation as early as Day3 post-induction. Constitutive ablation of macrophages markedly delayed anagen, and targeted ablation of macrophages at Day 3, but not at Day 0 or Day 6 post-shaving, impaired SHG activation with delayed anagen. Anagen entry was dependent on Folr2 +tissue macrophages, but not on CCR2 +monocyte-derived macrophages. Single-cell RNA-sequencing and cell-cell communication analyses revealed that Folr2 +macrophages communicated with the SHGs via Igf1 (encoding insulin-like growth factor 1 or IGF1). Ablation of macrophages and deletion of IGF1 from macrophages decreased AKT signaling in SHG and led to delayed anagen, both which were rescued via injection of recombinant IGF1 in vivo. Single-cell ATAC-sequencing revealed that the lack of IGF1-from macrophages resulted in alteration of transcription factor motif enrichment and decreased chromatin accessibility in various genes in SHGs, demonstrating that macrophages primed the SHGs to enter anagen by promoting IGF1R signaling. These results highlight the importance of immune-tissue crosstalk in facilitating hair growth and provide impetus for strategies to promote hair growth.