bioRxiv Science⌕ Search

Biology subjects

Kulis, M.

Publications and source records attributed to Kulis, M..

8 recordsLinked to original sources

Three-Dimensional Epigenome Roadmap of Human B-cell Differentiation Uncovers Mechanisms of Humoral Immunity and Oncogenesis

Human B-cell differentiation underlies humoral immunity, and its disruption leads to cancer, autoimmunity, and immunodeficiencies. However, the enhancer-based regulatory mechanisms governing this process remain poorly understood. To address this gap, we generated the first three-dimensional epigenomic roadmap of human B-cell differentiation in vivo. By profiling nine differentiation stages, we linked nearly half a million enhancers to their target genes through chromatin interactions, defined their activity states, and predicted bound transcription factors. We show that the acquisition of B-cell identity, distinct from common cellular processes, relies on large enhancer networks acting additively and synergistically to finely tune transcription. We further identify a 3D epigenetic priming mechanism underlying immune memory, whereby memory B cells retain primed DNA loops that enable faster responses to antigen re-exposure. Extending this roadmap to disease, we demonstrate that B-cell malignancies preserve enhancer signatures of their cell of origin while silencing distal tumor suppressor control. Finally, we uncover a previously unappreciated oncogenic mechanism in which intragenic deletions disrupt distal gene regulation via enhancer loss. Together, this resource provides a framework for understanding the genetic and epigenetic basis of humoral immunity and immune-related diseases.

genomics↗

A transcriptional map of human tonsil architecture:beyond the sum of (single cell) parts

The tonsil is a highly compartmentalized organ in which different microanatomical structures orchestrate designated (immune) functions. We use this already well-studied tissue to survey spatial molecular imaging data (CosMx SMI) for studying immune responses in native tissue context; and, to demonstrate the advantages of SMI for faithfully recapitulating cellular composition in direct comparison with single-cell RNA sequencing. While SMI data still poses many analytical challenges and lacks standardization, we established a versatile analysis pipeline focused on the profitable particularities of these data: considering organization (microenvironment), interactions (signaling), and function (higher-order structures) across scales. Specifically, we resolve ~ 2M cells into 52 subpopulations across immune and, in particular, structural compartments. Various spatial niches partition tonsillar tissue into architecturally and functionally distinct regions, which we characterize through cell-cell colocalization and communication analyses, while performing various non-standard analyses at the level of spatial features. These topological readouts may help elucidate where certain immunological processes occur (e.g., class switch recombination); and, where signaling pathways are active (e.g., TNF and galectin, which have been implicated in diverse lymphomas). In all, we provide an analytical framework for Spatial Immunology, and showcase alternative views that such techniques and concomitant computational approaches can bring on tissue composition and architecture.

immunology↗

KDM6A Regulates Immune Response Genes in Multiple Myeloma

The histone H3K27 demethylase KDM6A is a tumor suppressor in multiple cancers, including multiple myeloma (MM). We created isogenic MM cells disrupted for KDM6A and tagged the endogenous protein to facilitate genome wide studies. KDM6A binds genes associated with immune recognition and cytokine signaling. Most importantly, KDM6A binds and activates NLRC5 and CIITA encoding regulators of Major Histocompatibility Complex (MHC) genes. Patient data indicate that NLRC5 and CIITA, are downregulated in MM with low KDM6A expression. Chromatin analysis shows that KDM6A binds poised and active enhancers and KDM6A loss led to decreased H3K27ac at enhancers, increased H3K27me3 levels in body of genes bound by KDM6A and decreased gene expression. Reestablishing histone acetylation with an HDAC3 inhibitor leads to upregulation of MHC expression, offering a strategy to restore immunogenicity of KDM6A deficient tumors. Loss of Kdm6a in murine RAS-transformed fibroblasts led to increased growth in vivo associated with decreased T cell infiltration. Statement of significanceWe show that KDM6A participates in immune recognition of myeloma tumor cells by directly regulating the expression of the master regulators of MHC-I and II, NLRC5 and CIITA. The expression of these regulators can by rescued by the HDAC3 inhibitors in KDM6A-null cell lines.

cancer biology↗

An Atlas of Cells in the Human Tonsil

Palatine tonsils are secondary lymphoid organs representing the first line of immunological defense against inhaled or ingested pathogens. Here, we present a comprehensive census of cell types forming the human tonsil by applying single-cell transcriptome, epigenome, proteome and adaptive immune repertoire sequencing as well as spatial transcriptomics, resulting in an atlas of >357,000 cells. We provide a glossary of 121 annotated cell types and states, and disentangle gene regulatory mechanisms that drive cells through specialized lineage trajectories. Exemplarily, we stratify multiple tonsil-resident myeloid slancyte subtypes, establish a distant BCL6 superenhancer as locally active in both follicle-associated T and B cells, and describe SIX5 as a potentially novel transcriptional regulator of plasma cell maturation. Further, our atlas is a reference map to understand alterations observed in disease. Here, we discover immune-phenotype plasticity in tumoral cells and microenvironment shifts of mantle cell lymphomas (MCL). To facilitate such reference-based analysis, we develop HCATonsilData and SLOcatoR, a computational framework that provides programmatic and modular access to our dataset; and allows the straightforward annotation of future single-cell profiles from secondary lymphoid organs.

immunology↗

Content and performance of the MiniMUGA genotyping array, a new tool to improve rigor and reproducibility in mouse research

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well annotated genome, wealth of genetic resources and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost effective, informative and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole genome sequencing. Here we describe the content and performance of a new Mouse Universal Genotyping Array (MUGA). MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: 1) chromosomal sex determination, 2) discrimination between substrains from multiple commercial vendors, 3) diagnostic SNPs for popular laboratory strains, 4) detection of constructs used in genetically engineered mice, and 5) an easy to interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA we genotyped 6,899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived and recombinant inbred lines. Here we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, the extension of the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. There is preliminary but striking evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the main stock for a significant action of the genotyped inbred samples. We conclude that MiniMUGA is a valuable platform for genetic QC and important new tool to the increase rigor and reproducibility of mouse research.

genetics↗

The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome

We report a systematic analysis of the biological and clinical implications of DNA methylation variability in five categories of B-cell tumors derived from B cells spanning the entire maturation spectrum. We used 2056 primary samples including training and validation series and show that 88% of the human DNA methylome is dynamically modulated under normal and neoplastic conditions. B-cell tumors display both epigenetic imprints of their cellular origin and de novo, disease-specific epigenetic alterations that in part are related to differential transcription factor binding. These differential methylation patterns were used by a machine-learning approach to create a diagnostic algorithm that accurately classifies 14 B-cell tumor entities and subtypes with different clinical management. Beyond this, we identified extensive patient-specific epigenetic variability targeting constitutively silenced chromatin regions, a phenomenon we could relate to the proliferative history of normal and neoplastic B cells. We observed that, depending on the maturation stage of the tumor cell of origin, mitotic activity leaves different imprints into the DNA methylome. Subsequently, we constructed a novel DNA methylation-based mitotic clock called epiCMIT (epigenetically-determined Cumulative MIToses), whose lapse magnitude represents a strong independent prognostic variable within specific B-cell tumor subtypes and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracker of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of the outcome of the patients.

cancer biology↗

Sampling artifacts in single-cell genomics cohort studies

Robust protocols and automation now enable large-scale single-cell RNA and ATAC sequencing experiments and their application on biobank and clinical cohorts. However, technical biases introduced during sample acquisition can hinder solid, reproducible results and a systematic benchmarking is required before entering large-scale data production. Here, we report the existence and extent of gene expression and chromatin accessibility artifacts introduced during sampling and identify experimental and computational solutions for their prevention.

genomics↗

Chromatin activation as a unifying principle underlying pathogenic mechanisms in multiple myeloma

Multiple myeloma (MM) is a plasma cell neoplasm associated with a broad variety of genetic lesions. In spite of this genetic heterogeneity, MMs share a characteristic malignant phenotype whose underlying molecular basis remains poorly characterized. In the present study, we examined plasma cells from MM using a multi-epigenomics approach and demonstrated that when compared to normal B cells, malignant plasma cells showed an extensive activation of regulatory elements, in part affecting co-regulated adjacent genes. Among target genes upregulated by this process, we found members of the NOTCH, NFkB, mTOR1 signaling and p53 signaling pathways. Other activated genes included sets involved in osteoblast differentiation and response to oxidative stress, all of which have been shown to be associated with the MM phenotype and clinical behavior. We functionally characterized MM specific active distant enhancers controlling the expression of thioredoxin (TXN), a major regulator of cellular redox status, and in addition identified PRDM5 as a novel essential gene for MM. Collectively our data indicates that aberrant chromatin activation is a unifying feature underlying the malignant plasma cell phenotype.

cancer biology↗