Single-cell chromatin immunocleavage sequencing (scChIC-seq) to profile histone modification

The evolving metabolic landscape of chromatin biology and epigenetics

Molecular inputs to chromatin via cellular metabolism are modifiers of the epigenome. These inputs - which include both nutrient availability as a result of diet and growth factor signalling - are implicated in linking the environment to the maintenance of cellular homeostasis and cell identity. Recent studies have demonstrated that these inputs are much broader than had previously been known, encompassing metabolism from a wide variety of sources, including alcohol and microbiotal metabolism. These factors modify DNA and histones and exert specific effects on cell biology, systemic physiology and pathology. In this Review, we discuss the nature of these molecular networks, highlight their role in mediating cellular responses and explore their modifiability through dietary and pharmacological interventions.

Asymmetric inheritance of epigenetic states in asymmetrically dividing stem cells

Asymmetric cell division produces two cells that are genetically identical but each have distinctly different cell fates. During this process, epigenetic mechanisms play an important role in allowing the two daughter cells to have unique gene expression profiles that lead to their specific cell identities. Although the process of duplicating and segregating the genetic information during the cell cycle has been well studied, the question of how epigenetic information is duplicated and partitioned still remains. In this review, we discuss recent advances in understanding how epigenetic states are established and inherited, with emphasis on the asymmetric inheritance patterns of histones, DNA methylation, nonhistone proteins, RNAs, and organelles. We also discuss how misregulation of these processes may lead to diseases such as cancer and tissue degeneration.

Unraveling the Complexity of the Cancer Microenvironment With Multidimensional Genomic and Cytometric Technologies

Cancers are characterized by extensive heterogeneity that occurs intratumorally, between lesions, and across patients. To study cancer as a complex biological system, multidimensional analyses of the tumor microenvironment are paramount. Single-cell technologies such as flow cytometry, mass cytometry, or single-cell RNA-sequencing have revolutionized our ability to characterize individual cells in great detail and, with that, shed light on the complexity of cancer microenvironments. However, a key limitation of these single-cell technologies is the lack of information on spatial context and multicellular interactions. Investigating spatial contexts of cells requires the incorporation of tissue-based techniques such as multiparameter immunofluorescence, imaging mass cytometry, or in situ detection of transcripts. In this Review, we describe the rise of multidimensional single-cell technologies and provide an overview of their strengths and weaknesses. In addition, we discuss the integration of transcriptomic, genomic, epigenomic, proteomic, and spatially-resolved data in the context of human cancers. Lastly, we will deliberate on how the integration of multi-omics data will help to shed light on the complex role of cell types present within the human tumor microenvironment, and how such system-wide approaches may pave the way toward more effective therapies for the treatment of cancer.

Design Approaches for Generating Organ Constructs

Organ constructs are organ-like structures grown in vitro or in vivo that harbor the components, architecture, and function of in vivo organs, in part or in toto. The convergence of stem cell biology, bioengineering, and gene editing tools have substantially broadened our ability to generate various types of organ constructs for regenerative medicine as well as to address pressing biomedical questions. In this Review, we highlight prevailing approaches for generating organ constructs, from organoids to chimeric organ engineering. We also discuss design principles of different approaches, their utility and limitations, and propose strategies to resolve existing hurdles.

Integration of single-cell multi-omics for gene regulatory network inference

The advancement of single-cell sequencing technology in recent years has provided an opportunity to reconstruct gene regulatory networks (GRNs) with the data from thousands of single cells in one sample. This uncovers regulatory interactions in cells and speeds up the discoveries of regulatory mechanisms in diseases and biological processes. Therefore, more methods have been proposed to reconstruct GRNs using single-cell sequencing data. In this review, we introduce technologies for sequencing single-cell genome, transcriptome, and epigenome. At the same time, we present an overview of current GRN reconstruction strategies utilizing different single-cell sequencing data. Bioinformatics tools were grouped by their input data type and mathematical principles for reader's convenience, and the fundamental mathematics inherent in each group will be discussed. Furthermore, the adaptabilities and limitations of these different methods will also be summarized and compared, with the hope to facilitate researchers recognizing the most suitable tools for them.

Simultaneous quantification of protein-DNA interactions and transcriptomes in single cells with scDam&T-seq

Protein-DNA interactions are essential for establishing cell type-specific chromatin architecture and gene expression. We recently developed scDam&T-seq, a multi-omics method that can simultaneously quantify protein-DNA interactions and the transcriptome in single cells. The method effectively combines two existing methods: DNA adenine methyltransferase identification (DamID) and CEL-Seq2. DamID works through the tethering of a protein of interest (POI) to the Escherichia coli DNA adenine methyltransferase (Dam). Upon expression of this fusion protein, DNA in proximity to the POI is methylated by Dam and can be selectively digested and amplified. CEL-Seq2, in contrast, makes use of poly-dT primers to reverse transcribe mRNA, followed by linear amplification through in vitro transcription. scDam&T-seq is the first technique capable of providing a combined readout of protein-DNA contact and transcription from single-cell samples. Once suitable cell lines have been established, the protocol can be completed in 5 d, with a throughput of hundreds to thousands of cells. The processing of raw sequencing data takes an additional 1-2 d. Our method can be used to understand the transcriptional changes a cell undergoes upon the DNA binding of a POI. It can be performed in any laboratory with access to FACS, robotic and high-throughput-sequencing facilities.

Improved mouse models and advanced genetic and genomic technologies for the study of neutrophils

Mice have been excellent surrogates for studying neutrophil biology and, furthermore, murine models of human disease have provided fundamental insights into the roles of human neutrophils in innate immunity. The emergence of novel humanized mice and high-diversity mouse populations offers the research community innovative and powerful platforms for better understanding, respectively, the mechanisms by which human neutrophils drive pathogenicity, and how genetic differences underpin the variation in neutrophil biology observed among humans. Here, we review key examples of these new resources. Additionally, we provide an overview of advanced genetic engineering tools available to further improve such murine model systems, of sophisticated neutrophil-profiling technologies, and of multifunctional nanoparticle (NP)-based neutrophil-targeting strategies.

Towards a comprehensive catalogue of validated and target-linked human enhancers

The human gene catalogue is essentially complete, but we lack an equivalently vetted inventory of bona fide human enhancers. Hundreds of thousands of candidate enhancers have been nominated via biochemical annotations; however, only a handful of these have been validated and confidently linked to their target genes. Here we review emerging technologies for discovering, characterizing and validating human enhancers at scale. We furthermore propose a new framework for operationally defining enhancers that accommodates the heterogeneous and complementary results that are emerging from reporter assays, biochemical measurements and CRISPR screens.

Loss of Kat2a enhances transcriptional noise and depletes acute myeloid leukemia stem-like cells

Acute Myeloid Leukemia (AML) is an aggressive hematological malignancy with abnormal progenitor self-renewal and defective white blood cell differentiation. Its pathogenesis comprises subversion of transcriptional regulation, through mutation and by hijacking normal chromatin regulation. Kat2a is a histone acetyltransferase central to promoter activity, that we recently associated with stability of pluripotency networks, and identified as a genetic vulnerability in AML. Through combined chromatin profiling and single-cell transcriptomics of a conditional knockout mouse, we demonstrate that Kat2a contributes to leukemia propagation through preservation of leukemia stem-like cells. Kat2a loss impacts transcription factor binding and reduces transcriptional burst frequency in a subset of gene promoters, generating enhanced variability of transcript levels. Destabilization of target programs shifts leukemia cell fate out of self-renewal into differentiation. We propose that control of transcriptional variability is central to leukemia stem-like cell propagation, and establish a paradigm exploitable in different tumors and distinct stages of cancer evolution.

The application of single-cell sequencing technology in the diagnosis and treatment of hepatocellular carcinoma

Single-cell sequencing technology refers to the sequencing of the genome, transcriptome and epigenome in one single cell. Comparing to traditional histology, single-cell sequencing can reveal the genetic heterogeneity among different cells. Due to the complex pathogenesis and various pathological types of hepatocellular carcinoma (HCC), studies on the heterogeneity of tumor cells confer improvement for its clinical diagnosis, treatment and prognosis. This article summarizes the principal basis and development of single-cell sequencing technology, as well as its increasing application in the field of HCC.

Single-cell sequencing and its applications in head and neck cancer

Head and neck squamous cell carcinoma (HNSCC), like many tumors, is characterized by significant intra-tumoral heterogeneity, namely transcriptional, genetic, and epigenetic differences that define distinct cellular subpopulations. While it has been established that intra-tumoral heterogeneity may have prognostic significance in HNSCC, we are only beginning to describe and define such heterogeneity at a cellular resolution. Recent advances in single-cell sequencing technologies have been critical in this regard, opening new avenues in our understanding of more nuanced tumor biology by identifying distinct cellular subpopulations, dissecting signaling within the tumor microenvironment, and characterizing cellular genomic mutations and copy number aberrations. The combined effect of these insights is likely to be robust and meaningful changes in existing diagnostic and treatment algorithms through the application of novel biomarkers as well as targeted therapeutics. Here, we review single-cell technological and computational advances at the genomic, transcriptomic, and epigenomic levels, and discuss their applications in cancer research and clinical practice, with a specific focus on HNSCC.

Genomic methods in profiling DNA accessibility and factor localization

Recent advancements in next-generation sequencing technologies and accompanying reductions in cost have led to an explosion of techniques to examine DNA accessibility and protein localization on chromatin genome-wide. Generally, accessible regions of chromatin are permissive for factor binding and are therefore hotspots for regulation of gene expression; conversely, genomic regions that are highly occupied by histone proteins are not permissive for factor binding and are less likely to be active regulatory regions. Identifying regions of differential accessibility can be useful to uncover putative gene regulatory regions, such as enhancers, promoters, and insulators. In addition, DNA-binding proteins, such as transcription factors that preferentially bind certain DNA sequences and histone proteins that form the core of the nucleosome, play essential roles in all DNA-templated processes. Determining the genomic localization of chromatin-bound proteins is therefore essential in determining functional roles, sequence motifs important for factor binding, and regulatory networks controlling gene expression. In this review, we discuss techniques for determining DNA accessibility and nucleosome positioning (DNase-seq, FAIRE-seq, MNase-seq, and ATAC-seq) and techniques for detecting and functionally characterizing chromatin-bound proteins (ChIP-seq, DamID, and CUT&RUN). These methods have been optimized to varying degrees of resolution, specificity, and ease of use. Here, we outline some advantages and disadvantages of these techniques, their general protocols, and a brief discussion of their development. Together, these complimentary approaches have provided an unparalleled view of chromatin architecture and functional gene regulation.

Genome-wide histone modification profiling of inner cell mass and trophectoderm of bovine blastocysts by RAT-ChIP

Chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-seq) has revolutionized our understanding of chromatin-related biological processes. The method, however, requires thousands of cells and has therefore limited applications in situations where cell numbers are limited. Here we describe a novel method called Restriction Assisted Tagmentation Chromatin Immunoprecipitation (RAT-ChIP) that enables global histone modification profiling from as few as 100 cells. The method is simple, cost-effective and takes a single day to complete. We demonstrate the sensitivity of the method by deriving the first genome-wide maps of histone H3K4me3 and H3K27me3 modifications of inner cell mass and trophectoderm of bovine blastocyst stage embryos.

Toward a Mechanistic Understanding of DNA Methylation Readout by Transcription Factors

Epigenetic DNA modification impacts gene expression, but the underlying molecular mechanisms are only partly understood. Adding a methyl group to a cytosine base locally modifies the structural features of DNA in multiple ways, which may change the interaction with DNA-binding transcription factors (TFs) and trigger a cascade of downstream molecular events. Cells can be probed using various functional genomics assays, but it is difficult to disentangle the confounded effects of DNA modification on TF binding, chromatin accessibility, intranuclear variation in local TF concentration, and rate of transcription. Here we discuss how high-throughput in vitro profiling of protein-DNA interactions has enabled comprehensive characterization and quantification of the methylation sensitivity of TFs. Despite the limited structural data for DNA containing methylated cytosine, automated analysis of structural information in the Protein Data Bank (PDB) shows how 5-methylcytosine (5mC) can be recognized in various ways by amino acid side chains. We discuss how a context-dependent effect of methylation on DNA groove geometry can affect DNA binding by homeodomain proteins and how principled modeling of ChIP-seq data can overcome the confounding that makes the interpretation of in vivo data challenging. The emerging picture is that epigenetic modifications affect TF binding in a highly context-specific manner, with a direction and effect size that depend critically on their position within the TF binding site and the amino acid sequence of the TF. With this improved mechanistic knowledge, we have come closer to understanding how cells use DNA modification to acquire, retain, and change their identity.

Human Germline Cell Development: from the Perspective of Single-Cell Sequencing

Germline cells are the beginning of new individuals in multicellular animals, including humans. Our understanding of these cell types is limited by the difficulty of analyzing the precious and heterogeneous germline tissue samples. The rapid development of single-cell sequencing technologies provides a chance for comprehensive profiling of the omics dynamics of human germline development. In this review, we discuss progress in analyzing the development of human germline cells, including preimplantation and implantation embryos, fetal germ cells (FGCs), and adult spermatogenesis by single-cell transcriptome and epigenome sequencing technologies.

Going low to reach high: Small-scale ChIP-seq maps new terrain

Chromatin immunoprecipitation (ChIP) enables mapping of specific histone modifications or chromatin-associated factors in the genome and represents a powerful tool in the study of chromatin and genome regulation. Importantly, recent technological advances that couple ChIP with whole-genome high-throughput sequencing (ChIP-seq) now allow the mapping of chromatin factors throughout the genome. However, the requirement for large amounts of ChIP-seq input material has long made it challenging to assess chromatin profiles of cell types only available in limited numbers. For many cell types, it is not feasible to reach high numbers when collecting them as homogeneous cell populations in vivo. Nonetheless, it is an advantage to work with pure cell populations to reach robust biological conclusions. Here, we review (a) how ChIP protocols have been scaled down for use with as little as a few hundred cells; (b) which considerations to be aware of when preparing small-scale ChIP-seq and analyzing data; and (c) the potential of small-scale ChIP-seq datasets for elucidating chromatin dynamics in various biological systems, including some examples such as oocyte maturation and preimplantation embryo development. This article is categorized under: Laboratory Methods and Technologies > Genetic/Genomic Methods Developmental Biology > Developmental Processes in Health and Disease Biological Mechanisms > Cell Fates.

The transcription factor TCF-1 enforces commitment to the innate lymphoid cell lineage

Innate lymphoid cells (ILCs) play important functions in immunity and tissue homeostasis, but their development is poorly understood. Through the use of single-cell approaches, we examined the transcriptional and functional heterogeneity of ILC progenitors, and studied the precursor-product relationships that link the subsets identified. This analysis identified two successive stages of ILC development within T cell factor 1-positive (TCF-1⁺) early innate lymphoid progenitors (EILPs), which we named 'specified EILPs' and 'committed EILPs'. Specified EILPs generated dendritic cells, whereas this potential was greatly decreased in committed EILPs. TCF-1 was dispensable for the generation of specified EILPs, but required for the generation of committed EILPs. TCF-1 used a pre-existing regulatory landscape established in upstream lymphoid precursors to bind chromatin in EILPs. Our results provide insight into the mechanisms by which TCF-1 promotes developmental progression of ILC precursors, while constraining their dendritic cell lineage potential and enforcing commitment to ILC fate.

Mapping chromatin modifications at the single cell level

Understanding chromatin regulation holds enormous promise for controlling gene regulation, predicting cellular identity, and developing diagnostics and cellular therapies. However, the dynamic nature of chromatin, together with cell-to-cell heterogeneity in its structure, limits our ability to extract its governing principles. Single cell mapping of chromatin modifications, in conjunction with expression measurements, could help overcome these limitations. Here, we review recent advances in single cell-based measurements of chromatin modifications, including optimization to reduce DNA loss, improved DNA sequencing, barcoding, and antibody engineering. We also highlight several applications of these techniques that have provided insights into cell-type classification, mapping modification co-occurrence and heterogeneity, and monitoring chromatin dynamics.

The Spatial and Genomic Hierarchy of Tumor Ecosystems Revealed by Single-Cell Technologies

Many malignancies display heterogeneous features that support cancer progression. Emerging high-resolution methods provide a view of heterogeneity that recognizes the influence of diverse cell types and cell states of the tumor microenvironment. Here we outline a hierarchical organization of tumor heterogeneity from a genomic perspective, summarize the origins of spatially patterned metabolic features, and review recent developments in single-cell and spatially resolved techniques for genome-wide study of multicellular tissues. We also discuss how integrating these approaches can yield new insights into human cancer and emerging immune therapies. Applying these technologies for the analysis of primary tumors, patient-derived xenografts, and in vitro systems holds great promise for understanding the hierarchical structure and environmental influences that underlie tumor ecosystems.