Spatial-CUT&Tag: Spatially resolved chromatin modification profiling at the cellular level

Spatial biology of cancer evolution

The natural history of cancers can be understood through the lens of evolution given that the driving forces of cancer development are mutation and selection of fitter clones. Cancer growth and progression are spatial processes that involve the breakdown of normal tissue organization, invasion and metastasis. For these reasons, spatial patterns are an integral part of histological tumour grading and staging as they measure the progression from normal to malignant disease. Furthermore, tumour cells are part of an ecosystem of tumour cells and their surrounding tumour microenvironment. A range of new spatial genomic, transcriptomic and proteomic technologies offers new avenues for the study of cancer evolution with great molecular and spatial detail. These methods enable precise characterizations of the tumour microenvironment, cellular interactions therein and micro-anatomical structures. In conjunction with spatial genomics, it emerges that tumours and microenvironments co-evolve, which helps explain observable patterns of heterogeneity and offers new routes for therapeutic interventions.

Recent advances in high-throughput single-cell transcriptomics and spatial transcriptomics

Single-cell RNA sequencing (scRNA-seq) has been developed for characterizing the transcriptome of cells that are rare but of biological significance. With cell barcoding and microchip technologies, a suite of high-throughput scRNA-seq protocols enable transcriptome profiling in thousands of individual cells at single-cell resolution for classifying cell types, discovering novel cell populations, investigating cellular heterogeneity and elucidating lineage trajectories. Microchip technologies including microfluidics- and microwell-based platforms play a major role in high-throughput scRNA-seq. As the emerging technology, spatial transcriptomics integrates cellular transcriptomics with their spatial coordinates within tissues for spatially deciphering cellular composition, heterogeneity and cell-cell communications. Spatial transcriptomics has been increasingly recognized as one of the most powerful tools for discovering new biology and advancing precision medicine. Microfluidics as an enabling technology plays an increasingly important role in spatial transcriptomics. We review the technological spectrum and advances in high-throughput scRNA-seq and spatial transcriptomics, discuss their advantages and limitations, and pitch into new biology learned from these new tools.

Emergence of neuron types

Neuron types are the building blocks of the nervous system, and therefore, of functional circuits. Understanding the origin of neuronal diversity has always been an essential question in neuroscience and developmental biology. While knowledge on the molecular control of their diversification has largely increased during the last decades, it is now possible to reveal the dynamic mechanisms and the actual stepwise molecular changes occurring at single-cell level with the advent of single-cell omics technologies and analysis with high temporal resolution. Here, we focus on recent advances in the field and in technical and analytical tools that enable detailed insights into the emergence of neuron types in the central and peripheral nervous systems.

Omics goes spatial epigenomics

Spatial omics techniques generate spatially resolved, comprehensive data about molecules that define the identity and function of cells in tissues. Epigenetic multiplexing approaches such as Multiplexed Error-robust FISH (MERFISH), introduced by Lu et al.¹ in this issue of Cell, now allows researchers to study the epigenomic regulation of gene expression in a tissue-region specific manner.

Spatially resolved epigenomic profiling of single cells in complex tissues

The recent development of spatial omics methods has enabled single-cell profiling of the transcriptome and 3D genome organization with high spatial resolution. Expanding the repertoire of spatial omics tools, a spatially resolved single-cell epigenomics method will accelerate understanding of the spatial regulation of cell and tissue functions. Here, we report a method for spatially resolved epigenomic profiling of single cells using in situ tagmentation and transcription followed by multiplexed imaging. We demonstrated the ability to profile histone modifications marking active promoters, putative enhancers, and silent promoters in individual cells, and generated high-resolution spatial atlas of hundreds of active promoters and putative enhancers in embryonic and adult mouse brains. Our results suggested putative promoter-enhancer pairs and enhancer hubs regulating developmentally important genes. We envision this approach will be generally applicable to spatial profiling of epigenetic modifications and DNA-binding proteins, advancing our understanding of how gene expression is spatiotemporally regulated by the epigenome.

The industrial genomic revolution: A new era in neuroimmunology

Recent discoveries have highlighted the importance of understanding the complex interactions between the brain and immune systems in health and neurodegenerative disease. In this Primer, we outline single-cell multiomics approaches. Applied to patient samples with rich metadata, functional organoids, and animal models, single-cell studies will facilitate the next big leap in translational neuro-immune research. We believe this will pave the way for reshaping our understanding of the neuro-immune interplay: from descriptive to functional, from broad cell types to effective pathways, spatial organization, biomarkers, and targets, toward a comprehensive mechanistic understanding that will be the impetus for drug discovery and therapeutic breakthroughs. We envision that in the near future, single-cell multiomics technologies, along with the advances in immunotherapy development, will become a major driving force and fully integrated resource in the toolset for the development of therapeutic agents in neuroimmunology, which will revolutionize drug development for treating neurodegenerative diseases.

In situ tools for chromatin structural epigenomics

Technological progress over the past 15 years has fueled an explosion in genome-wide chromatin profiling tools that take advantage of low-cost short-read sequencing technologies to map particular chromatin features. Here, we survey the recent development of epigenomic tools that provide precise positions of chromatin proteins genome-wide in intact cells or nuclei. Some profiling tools are based on tethering Micrococcal Nuclease to chromatin proteins of interest in situ, whereas others similarly tether Tn5 transposase to integrate DNA sequencing adapters (tagmentation) and so eliminate the need for library preparation. These in situ cleavage and tagmentation tools have gained in popularity over the past few years, with many protocol enhancements and adaptations for single-cell and spatial chromatin profiling. The application of experimental and computational tools to address problems in gene regulation, eukaryotic development, and human disease are helping to define the emerging field of chromatin structural epigenomics.

Integrating Micro and Nano Technologies for Cell Engineering and Analysis: Toward the Next Generation of Cell Therapy Workflows

The emerging field of cell therapy offers the potential to treat and even cure a diverse array of diseases for which existing interventions are inadequate. Recent advances in micro and nanotechnology have added a multitude of single cell analysis methods to our research repertoire. At the same time, techniques have been developed for the precise engineering and manipulation of cells. Together, these methods have aided the understanding of disease pathophysiology, helped formulate corrective interventions at the cellular level, and expanded the spectrum of available cell therapeutic options. This review discusses how micro and nanotechnology have catalyzed the development of cell sorting, cellular engineering, and single cell analysis technologies, which have become essential workflow components in developing cell-based therapeutics. The review focuses on the technologies adopted in research studies and explores the opportunities and challenges in combining the various elements of cell engineering and single cell analysis into the next generation of integrated and automated platforms that can accelerate preclinical studies and translational research.

Clinical application of advanced multi-omics tumor profiling: Shaping precision oncology of the future

Next-generation DNA sequencing technology has dramatically advanced clinical oncology through the identification of therapeutic targets and molecular biomarkers, leading to the personalization of cancer treatment with significantly improved outcomes for many common and rare tumor entities. More recent developments in advanced tumor profiling now enable dissection of tumor molecular architecture and the functional phenotype at cellular and subcellular resolution. Clinical translation of high-resolution tumor profiling and integration of multi-omics data into precision treatment, however, pose significant challenges at the level of prospective validation and clinical implementation. In this review, we summarize the latest advances in multi-omics tumor profiling, focusing on spatial genomics and chromatin organization, spatial transcriptomics and proteomics, liquid biopsy, and ex vivo modeling of drug response. We analyze the current stages of translational validation of these technologies and discuss future perspectives for their integration into precision treatment.

Scalable and model-free detection of spatial patterns and colocalization

The expeditious growth in spatial omics technologies enables the profiling of genome-wide molecular events at molecular and single-cell resolution, highlighting a need for fast and reliable methods to characterize spatial patterns. We developed SpaGene, a model-free method to discover spatial patterns rapidly in large-scale spatial omics studies. Analyzing simulation and a variety of spatially resolved transcriptomics data showed that SpaGene is more powerful and scalable than existing methods. Spatial expression patterns identified by SpaGene reconstruct unobserved tissue structures. SpaGene also successfully discovers ligand-receptor interactions through their colocalization.

Spatial profiling of chromatin accessibility in mouse and human tissues

Cellular function in tissue is dependent on the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context1. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping2-5, but the ability to capture spatial epigenetic information of tissue at the cellular level and genome scale is lacking. Here we describe a method for spatially resolved chromatin accessibility profiling of tissue sections using next-generation sequencing (spatial-ATAC-seq) by combining in situ Tn5 transposition chemistry6 and microfluidic deterministic barcoding5. Profiling mouse embryos using spatial-ATAC-seq delineated tissue-region-specific epigenetic landscapes and identified gene regulators involved in the development of the central nervous system. Mapping the accessible genome in the mouse and human brain revealed the intricate arealization of brain regions. Applying spatial-ATAC-seq to tonsil tissue resolved the spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology progresses spatial biology by enabling spatially resolved chromatin accessibility profiling to improve our understanding of cell identity, cell state and cell fate decision in relation to epigenetic underpinnings in development and disease.

Histone post-translational modifications - cause and consequence of genome function

Much has been learned since the early 1960s about histone post-translational modifications (PTMs) and how they affect DNA-templated processes at the molecular level. This understanding has been bolstered in the past decade by the identification of new types of histone PTM, the advent of new genome-wide mapping approaches and methods to deposit or remove PTMs in a locally and temporally controlled manner. Now, with the availability of vast amounts of data across various biological systems, the functional role of PTMs in important processes (such as transcription, recombination, replication, DNA repair and the modulation of genomic architecture) is slowly emerging. This Review explores the contribution of histone PTMs to the regulation of genome function by discussing when these modifications play a causative (or instructive) role in DNA-templated processes and when they are deposited as a consequence of such processes, to reinforce and record the event. Important advances in the field showing that histone PTMs can exert both direct and indirect effects on genome function are also presented.

Multiplexed Single-Cell in Situ Protein Profiling

The ability to profile a large number of different proteins in individual cells in their native cellular locations is critical to accelerate our understanding of normal cell physiology and disease pathogenesis. Bulk cell protein quantification masks the cell heterogeneity in complex biological systems, while conventional immunofluorescence or immunohistochemistry are limited by their low multiplexing capacity. Recent technological advances in multiplexed protein imaging approaches allow many distinct proteins to be analyzed in single cells in situ. These methods will bring new insights into various biological and biomedical fields, such as cell type and subtype classification, signaling network regulation, tissue architecture, and disease diagnosis and prognosis, along with treatment monitoring. In this Review, we will describe the recent advances of multiplexed single-cell in situ protein profiling technologies, discuss their unique advantages and limitations, highlight their applications in biology and medicine, present the current challenges, and propose potential solutions.

Studying Chromatin Epigenetics with Fluorescence Microscopy

Epigenetic modifications of histones (methylation, acetylation, phosphorylation, etc.) are of great importance in determining the functional state of chromatin. Changes in epigenome underlay all basic biological processes, such as cell division, differentiation, aging, and cancerous transformation. Post-translational histone modifications are mainly studied by immunoprecipitation with high-throughput sequencing (ChIP-Seq). It enables an accurate profiling of target modifications along the genome, but suffers from the high cost of analysis and the inability to work with living cells. Fluorescence microscopy represents an attractive complementary approach to characterize epigenetics. It can be applied to both live and fixed cells, easily compatible with high-throughput screening, and provide access to rich spatial information down to the single cell level. In this review, we discuss various fluorescent probes for histone modification detection. Various types of live-cell imaging epigenetic sensors suitable for conventional as well as super-resolution fluorescence microscopy are described. We also focus on problems and future perspectives in the development of fluorescent probes for epigenetics.

The emerging landscape of spatial profiling technologies

Improved scale, multiplexing and resolution are establishing spatial nucleic acid and protein profiling methods as a major pillar for cellular atlas building of complex samples, from tissues to full organisms. Emerging methods yield omics measurements at resolutions covering the nano- to microscale, enabling the charting of cellular heterogeneity, complex tissue architectures and dynamic changes during development and disease. We present an overview of the developing landscape of in situ spatial genome, transcriptome and proteome technologies, exemplify their impact on cell biology and translational research, and discuss current challenges for their community-wide adoption. Among many transformative applications, we envision that spatial methods will map entire organs and enable next-generation pathology.

Identifying multicellular spatiotemporal organization of cells with SpaceFlow

One major challenge in analyzing spatial transcriptomic datasets is to simultaneously incorporate the cell transcriptome similarity and their spatial locations. Here, we introduce SpaceFlow, which generates spatially-consistent low-dimensional embeddings by incorporating both expression similarity and spatial information using spatially regularized deep graph networks. Based on the embedding, we introduce a pseudo-Spatiotemporal Map that integrates the pseudotime concept with spatial locations of the cells to unravel spatiotemporal patterns of cells. By comparing with multiple existing methods on several spatial transcriptomic datasets at both spot and single-cell resolutions, SpaceFlow is shown to produce a robust domain segmentation and identify biologically meaningful spatiotemporal patterns. Applications of SpaceFlow reveal evolving lineage in heart developmental data and tumor-immune interactions in human breast cancer data. Our study provides a flexible deep learning framework to incorporate spatiotemporal information in analyzing spatial transcriptomic data.

A critical task in spatial transcriptomics analysis is to understand inherently spatial relationships among cells. Here, the authors present a deep learning framework to integrate spatial and transcriptional information, spatially extending pseudotime and revealing spatiotemporal organization of cells.

Single-cell technologies: a new lens into epigenetic regulation in development

The totipotent zygote gives rise to diverse cell types through a series of well-orchestrated regulatory mechanisms. Epigenetic modifiers play an essential, though still poorly understood, role in the transition from pluripotency towards organogenesis. However, recent advances in single-cell technologies have enabled an unprecedented, high-resolution dissection of this crucial developmental window, highlighting more cell-type-specific functions of these ubiquitous regulators. In this review, we discuss and contextualize several recent studies that explore epigenetic regulation during mouse embryogenesis, emphasizing the opportunities presented by single-cell technologies, in vivo perturbation approaches as well as advanced in vitro models to characterize dynamic developmental transitions.

Single cell cancer epigenetics

Bulk sequencing methodologies have allowed us to make great progress in cancer research. Unfortunately, these techniques lack the resolution to fully unravel the epigenetic mechanisms that govern tumor heterogeneity. Consequently, many novel single cell-sequencing methodologies have been developed over the past decade, allowing us to explore the epigenetic components that regulate different aspects of cancer heterogeneity, namely: clonal heterogeneity, tumor microenvironment (TME), spatial organization, intratumoral differentiation programs, metastasis, and resistance mechanisms. In this review, we explore the different sequencing techniques that enable researchers to study different aspects of epigenetics (DNA methylation, chromatin accessibility, histone modifications, DNA-protein interactions, and chromatin 3D architecture) at the single cell level, their potential applications in cancer, and their current technical limitations.

Macrophage diversity in cancer revisited in the era of single-cell omics

Tumor-associated macrophages (TAMs) have multiple potent functions in cancer and, thus, represent important therapeutic targets. These diverse functions highlight the heterogenous nature of TAMs. Recent single cell omics technologies have significantly advanced our understanding of the molecular diversity of TAMs. However, a unifying nomenclature of TAM diversity and annotation of their molecular signatures is lacking. Here, we review recent major studies of single cell transcriptome, epigenome, metabolome, and spatial omics of cancer with a specific focus on TAMs. We also propose a consensus model of TAM diversity and present avenues for future research.

Unbiased spatial proteomics with single-cell resolution in tissues

Mass spectrometry (MS)-based proteomics has become a powerful technology to quantify the entire complement of proteins in cells or tissues. Here, we review challenges and recent advances in the LC-MS-based analysis of minute protein amounts, down to the level of single cells. Application of this technology revealed that single-cell transcriptomes are dominated by stochastic noise due to the very low number of transcripts per cell, whereas the single-cell proteome appears to be complete. The spatial organization of cells in tissues can be studied by emerging technologies, including multiplexed imaging and spatial transcriptomics, which can now be combined with ultra-sensitive proteomics. Combined with high-content imaging, artificial intelligence and single-cell laser microdissection, MS-based proteomics provides an unbiased molecular readout close to the functional level. Potential applications range from basic biological questions to precision medicine.

Single cell- and spatial 'Omics revolutionize physiology

Single cell multi- 'Omics and Spatial Transcriptomics are prominent technological highlights of recent years, and both fields still witness a ceaseless firework of novel approaches for high resolution profiling of additional omics layers. As all life processes in organs and organisms are based on the functions of their fundamental building blocks, the individual cells and their interactions, these methods are of utmost worth for the study of physiology in health and disease. Recent discoveries on embryonic development, tumor immunology, the detailed cellular composition and function of complex tissues like for example the kidney or the brain, different roles of the same cell type in different organs, the oncogenic program of individual tumor entities, or the architecture of immunopathology in infected tissue are based on single cell and spatial transcriptomics experiments. In this review, we will give a broad overview of technological concepts for single cell and spatial analysis, showing both advantages and limitations, and illustrate their impact with some particularly impressive case studies.

Large-Scale Chromatin Rearrangements in Cancer

Simple Summary

Cancers have many genetic mutations such as nucleotide changes, deletions, amplifications, and chromosome gains or losses. Some of these genetic alterations directly contribute to the initiation and progression of tumors. In parallel to these genetic changes, cancer cells acquire modifications to their chromatin landscape, i.e., to the marks that are carried by DNA and the histone proteins it is associated with. These “epimutations” have consequences for gene expression and genome stability, and also contribute to tumoral initiation and progression. Some of these chromatin changes are very local, affecting just one or a few genes. In contrast, some chromatin alterations observed in cancer are more widespread and affect a large part of the genome. In this review, we present different types of large-scale chromatin rearrangements in cancer, explain how they may occur, and why they are relevant for cancer diagnosis and treatment.

Abstract

Epigenetic abnormalities are extremely widespread in cancer. Some of them are mere consequences of transformation, but some actively contribute to cancer initiation and progression; they provide powerful new biological markers, as well as new targets for therapies. In this review, we examine the recent literature and focus on one particular aspect of epigenome deregulation: large-scale chromatin changes, causing global changes of DNA methylation or histone modifications. After a brief overview of the one-dimension (1D) and three-dimension (3D) epigenome in healthy cells and of its homeostasis mechanisms, we use selected examples to describe how many different events (mutations, changes in metabolism, and infections) can cause profound changes to the epigenome and fuel cancer. We then present the consequences for therapies and briefly discuss the role of single-cell approaches for the future progress of the field.

High-throughput single-сell sequencing in cancer research

With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to evaluate tumor progression, responses to environmental perturbations, heterogeneous composition of the tumor microenvironment, and complex intercellular interactions between these factors. Particularly, single-cell sequencing of T cell receptors, alone or in combination with single-cell RNA sequencing, is useful in the fields of tumor immunology and immunotherapy. Clinical insights obtained from single-cell analysis are critically important for exploring the biomarkers of disease progression or antitumor treatment, as well as for guiding precise clinical decision-making for patients with malignant tumors. In this review, we summarize the clinical applications of single-cell sequencing in the fields of tumor cell evolution, tumor immunology, and tumor immunotherapy. Additionally, we analyze the tumor cell response to antitumor treatment, heterogeneity of the tumor microenvironment, and response or resistance to immune checkpoint immunotherapy. The limitations of single-cell analysis in cancer research are also discussed.

One genome, many cell states: epigenetic control of innate immunity

A hallmark of the innate immune system is its ability to rapidly initiate short-lived or sustained transcriptional programs in a cell-specific and pathogen-specific manner that is dependent on dynamic chromatin states. Much of the epigenetic landscape is set during cellular differentiation; however, pathogens and other environmental cues also induce changes in chromatin that can either promote tolerance or 'train' innate immune cells for amplified secondary responses. We review chromatin processes that enable innate immune cell differentiation and functional transcriptional responses in naive or experienced cells, in concert with signal transduction and cellular metabolic shifts. We discuss how immune chromatin mechanisms are maladapted in disease and novel therapeutic approaches for cellular reprogramming.

Statistical and machine learning methods for spatially resolved transcriptomics data analysis

The recent advancement in spatial transcriptomics technology has enabled multiplexed profiling of cellular transcriptomes and spatial locations. As the capacity and efficiency of the experimental technologies continue to improve, there is an emerging need for the development of analytical approaches. Furthermore, with the continuous evolution of sequencing protocols, the underlying assumptions of current analytical methods need to be re-evaluated and adjusted to harness the increasing data complexity. To motivate and aid future model development, we herein review the recent development of statistical and machine learning methods in spatial transcriptomics, summarize useful resources, and highlight the challenges and opportunities ahead.