DNA Methylation-Based Assessment of Cell Composition in Human Pancreas and Islets.

Assessment of pancreas cell type composition is crucial to the understanding of the genesis of diabetes. Current approaches use immunodetection of protein markers, for example, insulin as a marker of ß-cells. A major limitation of these methods is that protein content varies in physiological and pathological conditions, complicating the extrapolation to actual cell number. Here, we demonstrate the use of cell type-specific DNA methylation markers for determining the fraction of specific cell types in human islet and pancreas specimens. We identified genomic loci that are uniquely demethylated in specific pancreatic cell types and applied targeted PCR to assess the methylation status of these loci in tissue samples, enabling inference of cell type composition. In islet preparations, normalization of insulin secretion to ß-cell DNA revealed similar ß-cell function in pre-type 1 diabetes (T1D), T1D, and type 2 diabetes (T2D), which was significantly lower than in donors without diabetes. In histological pancreas specimens from recent-onset T1D, this assay showed ß-cell fraction within the normal range, suggesting a significant contribution of ß-cell dysfunction. In T2D pancreata, we observed increased α-cell fraction and normal ß-cell fraction. Methylation-based analysis provides an accurate molecular alternative to immune detection of cell types in the human pancreas, with utility in the interpretation of insulin secretion assays and the assessment of pancreas cell composition in health and disease.

Toxinome-the bacterial protein toxin database.

IMPORTANCE: Microbes use protein toxins as important tools to attack neighboring cells, microbial or eukaryotic, and for self-killing when attacked by viruses. These toxins work through different mechanisms to inhibit cell growth or kill cells. Microbes also use antitoxin proteins to neutralize the toxin activities. Here, we developed a comprehensive database called Toxinome of nearly two million toxins and antitoxins that are encoded in 59,475 bacterial genomes. We described the distribution of bacterial toxins and identified that they are depleted by bacteria that live in hot and cold temperatures. We found 5,161 cases in which toxins and antitoxins are densely clustered in bacterial genomes and termed these areas "Toxin Islands." The Toxinome database is a useful resource for anyone interested in toxin biology and evolution, and it can guide the discovery of new toxins.

Accurate age prediction from blood using a small set of DNA methylation sites and a cohort-based machine learning algorithm.

Chronological age prediction from DNA methylation sheds light on human aging, health, and lifespan. Current clocks are mostly based on linear models and rely upon hundreds of sites across the genome. Here, we present GP-age, an epigenetic non-linear cohort-based clock for blood, based upon 11,910 methylomes. Using 30 CpG sites alone, GP-age outperforms state-of-the-art models, with a median accuracy of ∼2 years on held-out blood samples, for both array and sequencing-based data. We show that aging-related changes occur at multiple neighboring CpGs, with implications for using fragment-level analysis of sequencing data in aging research. By training three independent clocks, we show enrichment of donors with consistent deviation between predicted and actual age, suggesting individual rates of biological aging. Overall, we provide a compact yet accurate alternative to array-based clocks for blood, with applications in longitudinal aging research, forensic profiling, and monitoring epigenetic processes in transplantation medicine and cancer.

Elevated cfDNA after exercise is derived primarily from mature polymorphonuclear neutrophils, with a minor contribution of cardiomyocytes.

Strenuous physical exercise causes a massive elevation in the concentration of circulating cell-free DNA (cfDNA), which correlates with effort intensity and duration. The cellular sources and physiological drivers of this phenomenon are unknown. Using methylation patterns of cfDNA and associated histones, we show that cfDNA in exercise originates mostly in extramedullary polymorphonuclear neutrophils. Strikingly, cardiomyocyte cfDNA concentration increases after a marathon, consistent with elevated troponin levels and indicating low-level, delayed cardiac cell death. Physical impact, low oxygen levels, and elevated core body temperature contribute to neutrophil cfDNA release, while muscle contraction, increased heart rate, ß-adrenergic signaling, or steroid treatment fail to cause elevation of cfDNA. Physical training reduces neutrophil cfDNA release after a standard exercise, revealing an inverse relationship between exercise-induced cfDNA release and training level. We speculate that the release of cfDNA from neutrophils in exercise relates to the activation of neutrophils in the context of exercise-induced muscle damage.

Circulating cell-free methylated DNA reveals tissue-specific, cellular damage from radiation treatment.

Radiation therapy is an effective cancer treatment, although damage to healthy tissues is common. Here we analyzed cell-free, methylated DNA released from dying cells into the circulation to evaluate radiation-induced cellular damage in different tissues. To map the circulating DNA fragments to human and mouse tissues, we established sequencing-based, cell-type-specific reference DNA methylation atlases. We found that cell-type-specific DNA blocks were mostly hypomethylated and located within signature genes of cellular identity. Cell-free DNA fragments were captured from serum samples by hybridization to CpG-rich DNA panels and mapped to the DNA methylation atlases. In a mouse model, thoracic radiation-induced tissue damage was reflected by dose-dependent increases in lung endothelial and cardiomyocyte methylated DNA in serum. The analysis of serum samples from patients with breast cancer undergoing radiation treatment revealed distinct dose-dependent and tissue-specific epithelial and endothelial responses to radiation across multiple organs. Strikingly, patients treated for right-sided breast cancers also showed increased hepatocyte and liver endothelial DNA in the circulation, indicating the impact on liver tissues. Thus, changes in cell-free methylated DNA can uncover cell-type-specific effects of radiation and provide a readout of the biologically effective radiation dose received by healthy tissues.

The DNA methylome of human vascular endothelium and its use in liquid biopsies.

BACKGROUND: Vascular endothelial cells (VECs) are an essential component of each tissue, contribute to multiple pathologies, and are targeted by important drugs. Yet, there is a shortage of biomarkers to assess VEC turnover. METHODS: To develop DNA methylation-based liquid biopsies for VECs, we determined the methylome of VECs isolated from freshly dissociated human tissues. FINDINGS: A comparison with a human cell-type methylome atlas yielded thousands of loci that are uniquely unmethylated in VECs. These sites are typically gene enhancers, often residing adjacent to VEC-specific genes. We also identified hundreds of genomic loci that are differentially methylated in organotypic VECs, indicating that VECs feeding specific organs are distinct cell types with a stable epigenetic identity. We established universal and lung-specific VEC markers and evaluated their presence in circulating cell-free DNA (cfDNA). Nearly 2.5% of cfDNA in the plasma of healthy individuals originates from VECs. Sepsis, graft versus host disease, and cardiac catheterization are associated with elevated levels of VEC-derived cfDNA, indicative of vascular damage. Lung-specific VEC cfDNA is selectively elevated in patients with chronic obstructive pulmonary disease (COPD) or lung cancer, revealing tissue-specific vascular turnover. CONCLUSIONS: VEC cfDNA biomarkers inform vascular dynamics in health and disease, potentially contributing to early diagnosis and monitoring of pathologies, and assessment of drug activity. FUNDING: This work was supported by the Beutler Research Program, Helmsley Charitable Trust, JDRF, Grail and the DON Foundation (to Y.D.). Y.D holds the Walter & Greta Stiel Chair in heart studies. B.G., R.S., J.M., D.N., T.K., and Y.D. filed patents on cfDNA analysis.

Predicting gene knockout effects from expression data.

BACKGROUND: The study of gene essentiality, which measures the importance of a gene for cell division and survival, is used for the identification of cancer drug targets and understanding of tissue-specific manifestation of genetic conditions. In this work, we analyze essentiality and gene expression data from over 900 cancer lines from the DepMap project to create predictive models of gene essentiality. METHODS: We developed machine learning algorithms to identify those genes whose essentiality levels are explained by the expression of a small set of "modifier genes". To identify these gene sets, we developed an ensemble of statistical tests capturing linear and non-linear dependencies. We trained several regression models predicting the essentiality of each target gene, and used an automated model selection procedure to identify the optimal model and hyperparameters. Overall, we examined linear models, gradient boosted trees, Gaussian process regression models, and deep learning networks. RESULTS: We identified nearly 3000 genes for which we accurately predict essentiality using gene expression data of a small set of modifier genes. We show that both in the number of genes we successfully make predictions for, as well as in the prediction accuracy, our model outperforms current state-of-the-art works. CONCLUSIONS: Our modeling framework avoids overfitting by identifying the small set of modifier genes, which are of clinical and genetic importance, and ignores the expression of noisy and irrelevant genes. Doing so improves the accuracy of essentiality prediction in various conditions and provides interpretable models. Overall, we present an accurate computational approach, as well as interpretable modeling of essentiality in a wide range of cellular conditions, thus contributing to a better understanding of the molecular mechanisms that govern tissue-specific effects of genetic disease and cancer.

A DNA methylation atlas of normal human cell types.

DNA methylation is a fundamental epigenetic mark that governs gene expression and chromatin organization, thus providing a window into cellular identity and developmental processes1. Current datasets typically include only a fraction of methylation sites and are often based either on cell lines that underwent massive changes in culture or on tissues containing unspecified mixtures of cells2-5. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing, allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell type are more than 99.5% identical, demonstrating the robustness of cell identity programmes to environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny and identifies methylation patterns retained since embryonic development. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hypermethylated loci are rare and are enriched for CpG islands, Polycomb targets and CTCF binding sites, suggesting a new role in shaping cell-type-specific chromatin looping. The atlas provides an essential resource for study of gene regulation and disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.

Comparative parallel multi-omics analysis during the induction of pluripotent and trophectoderm states.

Following fertilization, it is only at the 32-64-cell stage when a clear segregation between cells of the inner cell mass and trophectoderm is observed, suggesting a 'T'-shaped model of specification. Here, we examine whether the acquisition of these two states in vitro, by nuclear reprogramming, share similar dynamics/trajectories. Using a comparative parallel multi-omics analysis (i.e., bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, RRBS and CNVs) on cells undergoing reprogramming to pluripotency and TSC state we show that each reprogramming system exhibits specific trajectories from the onset of the process, suggesting 'V'-shaped model. We describe in detail the various trajectories toward the two states and illuminate reprogramming stage-specific markers, blockers, facilitators and TSC subpopulations. Finally, we show that while the acquisition of the TSC state involves the silencing of embryonic programs by DNA methylation, during the acquisition of pluripotency these regions are initially defined but retain inactive by the elimination of H3K27ac.

Ep300 sequestration to functionally distinct glucocorticoid receptor binding loci underlie rapid gene activation and repression.

The rapid transcriptional response to the transcription factor, glucocorticoid receptor (GR), including gene activation or repression, is mediated by the spatial association of genes with multiple GR binding sites (GBSs) over large genomic distances. However, only a minority of the GBSs have independent GR-mediated activating capacity, and GBSs with independent repressive activity were rarely reported. To understand the positive and negative effects of GR we mapped the regulatory environment of its gene targets. We show that the chromatin interaction networks of GR-activated and repressed genes are spatially separated and vary in the features and configuration of their GBS and other non-GBS regulatory elements. The convergence of the KLF4 pathway in GR-activated domains and the STAT6 pathway in GR-repressed domains, impose opposite transcriptional effects to GR, independent of hormone application. Moreover, the ROR and Rev-erb transcription factors serve as positive and negative regulators, respectively, of GR-mediated gene activation. We found that the spatial crosstalk between GBSs and non-GBSs provides a physical platform for sequestering the Ep300 co-activator from non-GR regulatory loci in both GR-activated and -repressed gene compartments. While this allows rapid gene repression, Ep300 recruitment to GBSs is productive specifically in the activated compartments, thus providing the basis for gene induction.

Universal lung epithelium DNA methylation markers for detection of lung damage in liquid biopsies.

BACKGROUND: Circulating biomarkers for lung damage are lacking. Lung epithelium-specific DNA methylation patterns can potentially report the presence of lung-derived cell-free DNA (cfDNA) in blood, as an indication of lung cell death. METHODS: We sorted human lung alveolar and bronchial epithelial cells from surgical specimens, and obtained their methylomes using whole-genome bisulfite sequencing. We developed a PCR sequencing assay determining the methylation status of 17 loci with lung-specific methylation patterns, and used it to assess lung-derived cfDNA in the plasma of healthy volunteers and patients with lung disease. RESULTS: Loci that are uniquely unmethylated in alveolar or bronchial epithelial cells are enriched for enhancers controlling lung-specific genes. Methylation markers extracted from these methylomes revealed that normal lung cell turnover probably releases cfDNA into the air spaces, rather than to blood. People with advanced lung cancer show a massive elevation of lung cfDNA concentration in blood. Among individuals undergoing bronchoscopy, lung-derived cfDNA is observed in the plasma of those later diagnosed with lung cancer, and to a lesser extent in those diagnosed with other lung diseases. Lung cfDNA is also elevated in patients with acute exacerbation of COPD compared with patients with stable disease, and is associated with future exacerbation and mortality in these patients. CONCLUSIONS: Universal cfDNA methylation markers of normal lung epithelium allow for mutation-independent, sensitive and specific detection of lung-derived cfDNA, reporting on ongoing lung injury. Such markers can find broad utility in the study of normal and pathologic human lung dynamics.

Liquid biopsy reveals collateral tissue damage in cancer.

Cancer inflicts damage to surrounding normal tissues, which can culminate in fatal organ failure. Here, we demonstrate that cell death in organs affected by cancer can be detected by tissue-specific methylation patterns of circulating cell-free DNA (cfDNA). We detected elevated levels of hepatocyte-derived cfDNA in the plasma of patients with liver metastases originating from different primary tumors, compared with cancer patients without liver metastases. In addition, patients with localized pancreatic or colon cancer showed elevated hepatocyte cfDNA, suggesting liver damage inflicted by micrometastatic disease, by primary pancreatic tumor pressing the bile duct, or by a systemic response to the primary tumor. We also identified elevated neuron-, oligodendrocyte-, and astrocyte-derived cfDNA in a subpopulation of patients with brain metastases compared with cancer patients without brain metastasis. Cell type-specific cfDNA methylation markers enabled the identification of collateral tissue damage in cancer, revealing the presence of metastases in specific locations and potentially assisting in early cancer detection.

Remote immune processes revealed by immune-derived circulating cell-free DNA.

Blood cell counts often fail to report on immune processes occurring in remote tissues. Here, we use immune cell type-specific methylation patterns in circulating cell-free DNA (cfDNA) for studying human immune cell dynamics. We characterized cfDNA released from specific immune cell types in healthy individuals (N = 242), cross sectionally and longitudinally. Immune cfDNA levels had no individual steady state as opposed to blood cell counts, suggesting that cfDNA concentration reflects adjustment of cell survival to maintain homeostatic cell numbers. We also observed selective elevation of immune-derived cfDNA upon perturbations of immune homeostasis. Following influenza vaccination (N = 92), B-cell-derived cfDNA levels increased prior to elevated B-cell counts and predicted efficacy of antibody production. Patients with eosinophilic esophagitis (N = 21) and B-cell lymphoma (N = 27) showed selective elevation of eosinophil and B-cell cfDNA, respectively, which were undetectable by cell counts in blood. Immune-derived cfDNA provides a novel biomarker for monitoring immune responses to physiological and pathological processes that are not accessible using conventional methods.

Detection of Cell Types Contributing to Cancer From Circulating, Cell-Free Methylated DNA.

Detection of cellular changes in tissue biopsies has been the basis for cancer diagnostics. However, tissue biopsies are invasive and limited by inaccuracies due to sampling locations, restricted sampling frequency, and poor representation of tissue heterogeneity. Liquid biopsies are emerging as a complementary approach to traditional tissue biopsies to detect dynamic changes in specific cell populations. Cell-free DNA (cfDNA) fragments released into the circulation from dying cells can be traced back to the tissues and cell types they originated from using DNA methylation, an epigenetic regulatory mechanism that is highly cell-type specific. Decoding changes in the cellular origins of cfDNA over time can reveal altered host tissue homeostasis due to local cancer invasion and metastatic spread to distant organs as well as treatment responses. In addition to host-derived cfDNA, changes in cancer cells can be detected from cell-free, circulating tumor DNA (ctDNA) by monitoring DNA mutations carried by cancer cells. Here, we will discuss computational approaches to identify and validate robust biomarkers of changed tissue homeostasis using cell-free, methylated DNA in the circulation. We highlight studies performing genome-wide profiling of cfDNA methylation and those that combine genetic and epigenetic markers to further identify cell-type specific signatures. Finally, we discuss opportunities and current limitations of these approaches for implementation in clinical oncology.

ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells of origin.

Cell-free DNA (cfDNA) in human plasma provides access to molecular information about the pathological processes in the organs or tumors from which it originates. These DNA fragments are derived from fragmented chromatin in dying cells and retain some of the cell-of-origin histone modifications. In this study, we applied chromatin immunoprecipitation of cell-free nucleosomes carrying active chromatin modifications followed by sequencing (cfChIP-seq) to 268 human samples. In healthy donors, we identified bone marrow megakaryocytes, but not erythroblasts, as major contributors to the cfDNA pool. In patients with a range of liver diseases, we showed that we can identify pathology-related changes in hepatocyte transcriptional programs. In patients with metastatic colorectal carcinoma, we detected clinically relevant and patient-specific information, including transcriptionally active human epidermal growth factor receptor 2 (HER2) amplifications. Altogether, cfChIP-seq, using low sequencing depth, provides systemic and genome-wide information and can inform diagnosis and facilitate interrogation of physiological and pathological processes using blood samples.

Genomic retargeting of p53 and CTCF is associated with transcriptional changes during oncogenic HRas-induced transformation.

Gene transcription is regulated by distant regulatory elements via combinatorial binding of transcription factors. It is increasingly recognized that alterations in chromatin state and transcription factor binding in these distant regulatory elements may have key roles in cancer development. Here we focused on the first stages of oncogene-induced carcinogenic transformation, and characterized the regulatory network underlying transcriptional changes associated with this process. Using Hi-C data, we observe spatial coupling between differentially expressed genes and their differentially accessible regulatory elements and reveal two candidate transcription factors, p53 and CTCF, as determinants of transcriptional alterations at the early stages of oncogenic HRas-induced transformation in human mammary epithelial cells. Strikingly, the malignant transcriptional reprograming is promoted by redistribution of chromatin binding of these factors without major variation in their expression level. Our results demonstrate that alterations in the regulatory landscape have a major role in driving oncogene-induced transcriptional reprogramming.

Disease-associated astrocytes in Alzheimer's disease and aging.

The role of non-neuronal cells in Alzheimer's disease progression has not been fully elucidated. Using single-nucleus RNA sequencing, we identified a population of disease-associated astrocytes in an Alzheimer's disease mouse model. These disease-associated astrocytes appeared at early disease stages and increased in abundance with disease progression. We discovered that similar astrocytes appeared in aged wild-type mice and in aging human brains, suggesting their linkage to genetic and age-related factors.

Triangular correlation (TrC) between cancer aggressiveness, cell uptake capability, and cell deformability.

The malignancy potential is correlated with the mechanical deformability of the cancer cells. However, mechanical tests for clinical applications are limited. We present here a Triangular Correlation (TrC) between cell deformability, phagocytic capacity, and cancer aggressiveness, suggesting that phagocytic measurements can be a mechanical surrogate marker of malignancy. The TrC was proved in human prostate cancer cells with different malignancy potential, and in human bladder cancer and melanoma cells that were sorted into subpopulations based solely on their phagocytic capacity. The more phagocytic subpopulations showed elevated aggressiveness ex vivo and in vivo. The uptake potential was preserved, and differences in gene expression and in epigenetic signature were detected. In all cases, enhanced phagocytic and aggressiveness phenotypes were correlated with greater cell deformability and predicted by a computational model. Our multidisciplinary study provides the proof of concept that phagocytic measurements can be applied for cancer diagnostics and precision medicine.