The epigenetic basis of cellular heterogeneity

Unraveling the genetic and epigenetic landscape governing intramuscular fat deposition in rabbits: Insights and implications

Intramuscular fat (IMF) content is a predominant factor recognized to affect rabbit meat quality, directly impacting flavor, juiciness, and consumer preference. Despite its significance, the major interplay of genetic and epigenetic factors regulating IMF in rabbits remains largely unexplored. This review sheds light on this critical knowledge gap, offering valuable insights and future directions. We delve into the potential role of established candidate genes from other livestock (e.g. PPARγ, FABP4, and SCD) in rabbits, while exploring the identified novel genes of IMF in rabbits. Furthermore, we explored the quantitative trait loci studies in rabbit IMF and genomic selection approaches for improving IMF content in rabbits. Beyond genetics, this review unveils the exciting realm of epigenetic mechanisms modulating IMF deposition. We explored the potential of DNA methylation patterns, histone modifications, and non-coding RNA-mediation as fingerprints for selecting rabbits with desirable IMF levels. Additionally, we explored the possibility of manipulating the epigenetic landscape through nutraceuticals interventions to promote favorable IMF depositions. By comprehensively deciphering the genomic and epigenetic terrain of rabbit intramuscular fat regulation, this study aims to assess the existing knowledge regarding the genetic and epigenetic factors that control the deposition of intramuscular fat in rabbits. By doing so, we identified gaps in the current research, and suggested potential areas for further investigation that would enhance the quality of rabbit meat. This can enable breeders to develop targeted breeding strategies, optimize nutrition, and create innovative interventions to enhance the quality of rabbit meat, meet consumer demands and increase market competitiveness.

Single-cell analysis with childhood and adult systemic lupus erythematosus

Patients with systemic lupus erythematosus (SLE), a heterogeneous and chronic autoimmune disease, exhibit unique changes in the complex composition and transcriptional signatures of peripheral blood mononuclear cells (PBMCs). While the mechanism of pathogenesis for both childhood-onset SLE (cSLE) and adult-onset SLE (aSLE) remains unclear, cSLE patients are considered more unpredictable and dangerous than aSLE patients. In this study, we analysed single-cell RNA sequencing data (scRNA-seq) to profile the PBMC clusters of cSLE/aSLE patients and matched healthy donors and compared the PBMC composition and transcriptional variations between the two groups. Our analysis revealed that the PBMC composition and transcriptional variations in cSLE patients were similar to those in aSLE patients. Comparative single-cell transcriptome analysis between healthy donors and SLE patients revealed IFITM3, ISG15, IFI16 and LY6E as potential therapeutic targets for both aSLE and cSLE patients. Additionally, we observed that the percentage of pre-B cells (CD34-) was increased in cSLE patients, while the percentage of neutrophil cells was upregulated in aSLE patients. Notably, we found decreased expression of TPM2 in cSLE patients, and similarly, TMEM150B, IQSEC2, CHN2, LRP8 and USP46 were significantly downregulated in neutrophil cells from aSLE patients. Overall, our study highlights the differences in complex PBMC composition and transcriptional profiles between cSLE and aSLE patients, providing potential biomarkers that could aid in diagnosing SLE.

Genetic and Epigenetic Alterations in Aging and Rejuvenation of Human

All the information essential for life is encoded within our genome and epigenome, which orchestrates diverse cellular states spatially and temporally. In particular, the epigenome interacts with internal and external stimuli, encoding and preserving cellular experiences, and it serves as the regulatory base of the transcriptome across diverse cell types. The emergence of single-cell transcriptomic and epigenomic data collection has revealed unique omics signatures in diverse tissues, highlighting cellular heterogeneity. Recent research has documented age-related epigenetic changes at the single-cell level, alongside the validation of cellular rejuvenation through partial reprogramming, which involves simultaneous epigenetic modifications. These dynamic shifts, primarily fueled by stem cell plasticity, have catalyzed significant interest and cross-disciplinary research endeavors. This review explores the genomic and epigenomic alterations with aging, elucidating their reciprocal interactions. Additionally, it seeks to discuss the evolving landscape of rejuvenation research, with a particular emphasis on dissecting stem cell behavior through the lens of single-cell analysis. Moreover, it proposes potential research methodologies for future studies.

Applications of single-cell analysis in immunotherapy for lung cancer: Current progress, new challenges and expectations

BACKGROUND

Lung cancer is a prevalent form of cancer worldwide, presenting a substantial risk to human well-being. Lung cancer is classified into two main types: non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). The advancement of tumor immunotherapy, specifically immune checkpoint inhibitors and adaptive T-cell therapy, has encountered substantial obstacles due to the rapid progression of SCLC and the metastasis, recurrence, and drug resistance of NSCLC. These challenges are believed to stem from the tumor heterogeneity of lung cancer within the tumor microenvironment.

AIM OF REVIEW

This review aims to comprehensively explore recent strides in single-cell analysis, a robust sequencing technology, concerning its application in the realm of tumor immunotherapy for lung cancer. It has been effectively integrated with transcriptomics, epigenomics, genomics, and proteomics for various applications. Specifically, these techniques have proven valuable in mapping the transcriptional activity of tumor-infiltrating lymphocytes in patients with NSCLC, identifying circulating tumor cells, and elucidating the heterogeneity of the tumor microenvironment.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The review emphasizes the paramount significance of single-cell analysis in mapping the immune cells within NSCLC patients, unveiling circulating tumor cells, and elucidating the tumor microenvironment heterogeneity. Notably, these advancements highlight the potential of single-cell analysis to revolutionize lung cancer immunotherapy by characterizing immune cell fates, improving therapeutic strategies, and identifying promising targets or prognostic biomarkers. It is potential to unravel the complexities within the tumor microenvironment and enhance treatment strategies marks a significant step towards more effective therapies and improved patient outcomes.

Best practices for differential accessibility analysis in single-cell epigenomics

Differential accessibility (DA) analysis of single-cell epigenomics data enables the discovery of regulatory programs that establish cell type identity and steer responses to physiological and pathophysiological perturbations. While many statistical methods to identify DA regions have been developed, the principles that determine the performance of these methods remain unclear. As a result, there is no consensus on the most appropriate statistical methods for DA analysis of single-cell epigenomics data. Here, we present a systematic evaluation of statistical methods that have been applied to identify DA regions in single-cell ATAC-seq (scATAC-seq) data. We leverage a compendium of scATAC-seq experiments with matching bulk ATAC-seq or scRNA-seq in order to assess the accuracy, bias, robustness, and scalability of each statistical method. The structure of our experiments also provides the opportunity to define best practices for the analysis of scATAC-seq data beyond DA itself. We leverage this understanding to develop an R package implementing these best practices.

Metabolic reprogramming tips vaccinia virus infection outcomes by stabilizing interferon-γ induced IRF1

Interferon (IFN) induced activities are critical, early determinants of immune responses and infection outcomes. A key facet of IFN responses is the upregulation of hundreds of mRNAs termed interferon-stimulated genes (ISGs) that activate intrinsic and cell-mediated defenses. While primary interferon signaling is well-delineated, other layers of regulation are less explored but implied by aberrant ISG expression signatures in many diseases in the absence of infection. Consistently, our examination of tonic ISG levels across uninfected human tissues and individuals revealed three ISG subclasses. As tissue identity and many comorbidities with increased virus susceptibility are characterized by differences in metabolism, we characterized ISG responses in cells grown in media known to favor either aerobic glycolysis (glucose) or oxidative phosphorylation (galactose supplementation). While these conditions over time had a varying impact on the expression of ISG RNAs, the differences were typically greater between treatments than between glucose/galactose. Interestingly, extended interferon-priming led to divergent expression of two ISG proteins: upregulation of IRF1 in IFN-γ/glucose and increased IFITM3 in galactose by IFN-α and IFN-γ. In agreement with a hardwired response, glucose/galactose regulation of interferon-γ induced IRF1 is conserved in unrelated mouse and cat cell types. In galactose conditions, proteasome inhibition restored interferon-γ induced IRF1 levels to that of glucose/interferon-γ. Glucose/interferon-γ decreased replication of the model poxvirus vaccinia at low MOI and high MOIs. Vaccinia replication was restored by IRF1 KO. In contrast, but consistent with differential regulation of IRF1 protein by glucose/galactose, WT and IRF1 KO cells in galactose media supported similar levels of vaccinia replication regardless of IFN-γ priming. Also associated with glucose/galactose is a seemingly second block at a very late stage in viral replication which results in reductions in herpes- and poxvirus titers but not viral protein expression. Collectively, these data illustrate a novel layer of regulation for the key ISG protein, IRF1, mediated by glucose/galactose and imply unappreciated subprograms embedded in the interferon response. In principle, such cellular circuitry could rapidly adapt immune responses by sensing changing metabolite levels consumed during viral replication and cell proliferation.

Identifying the "stripe" transcription factors and cooperative binding related to DNA methylation

DNA methylation plays a critical role in gene regulation by modulating the DNA binding of transcription factors (TFs). This study integrates TFs' ChIP-seq profiles with WGBS profiles to investigate how DNA methylation affects protein interactions. Statistical methods and a 5-letter DNA motif calling model have been developed to characterize DNA sequences bound by proteins, while considering the effects of DNA modifications. By employing these methods, 79 significant universal "stripe" TFs and cofactors (USFs), 2360 co-binding protein pairs, and distinct protein modules associated with various DNA methylation states have been identified. The USFs hint a regulatory hierarchy within these protein interactions. Proteins preferentially bind to non-CpG sites in methylated regions, indicating binding affinity is not solely CpG-dependent. Proteins involved in methylation-specific USFs and cobinding pairs play essential roles in promoting and sustaining DNA methylation through interacting with DNMTs or inhibiting TET binding. These findings underscore the interplay between protein binding and methylation, offering insights into epigenetic regulation in cellular biology.

Metabolic reprogramming tips vaccinia virus infection outcomes by stabilizing interferon-γ induced IRF1

Interferon (IFN) induced activities are critical, early determinants of immune responses and infection outcomes. A key facet of IFN responses is the upregulation of hundreds of mRNAs termed interferon-stimulated genes (ISGs) that activate intrinsic and cell-mediated defenses. While primary interferon signaling is well-delineated, other layers of regulation are less explored but implied by aberrant ISG expression signatures in many diseases in the absence of infection. Consistently, our examination of tonic ISG levels across uninfected human tissues and individuals revealed three ISG subclasses. As tissue identity and many comorbidities with increased virus susceptibility are characterized by differences in metabolism, we characterized ISG responses in cells grown in media known to favor either aerobic glycolysis (glucose) or oxidative phosphorylation (galactose supplementation). While these conditions over time had a varying impact on the expression of ISG RNAs, the differences were typically greater between treatments than between glucose/galactose. Interestingly, extended interferon-priming led to divergent expression of two ISG proteins: upregulation of IRF1 in IFN-γ/glucose and increased IFITM3 in galactose by IFN-α and IFN-γ. In agreement with a hardwired response, glucose/galactose regulation of interferon-γ induced IRF1 is conserved in unrelated mouse and cat cell types. In galactose conditions, proteasome inhibition restored interferon-γ induced IRF1 levels to that of glucose/interferon-γ. Glucose/interferon-γ decreased replication of the model poxvirus vaccinia at low MOI and high MOIs. Vaccinia replication was restored by IRF1 KO. In contrast, but consistent with differential regulation of IRF1 protein by glucose/galactose, WT and IRF1 KO cells in galactose media supported similar levels of vaccinia replication regardless of IFN-γ priming. Also associated with glucose/galactose is a seemingly second block at a very late stage in viral replication which results in reductions in herpes- and poxvirus titers but not viral protein expression. Collectively, these data illustrate a novel layer of regulation for the key ISG protein, IRF1, mediated by glucose/galactose and imply unappreciated subprograms embedded in the interferon response. In principle, such cellular circuitry could rapidly adapt immune responses by sensing changing metabolite levels consumed during viral replication and cell proliferation.

Single-cell transcriptome landscape of the kidney reveals potential innate immune regulation mechanisms in hybrid yellow catfish after Aeromonas hydrophila infection

Aeromonas hydrophila, the pathogen that is the causative agent of motile Aeromonas septicemia (MAS) disease, commonly attacks freshwater fishes, including yellow catfish (Pelteobagrus fulvidraco). Although the kidney is one of the most important organs involved in immunity in fish, its role in disease progression has not been fully elucidated. Understanding the cellular composition and innate immune regulation mechanisms of the kidney of yellow catfish is important for the treatment of MAS. In this study, single-cell RNA sequencing (scRNA-seq) was performed on the kidney of hybrid yellow catfish (Pelteobagrus fulvidraco ♀ × Pelteobagrus vachelli ♂) after A. hydrophila infection. Nine types of kidney cells were identified using marker genes, and a transcription module of marker genes in the main immune cells of hybrid yellow catfish kidney tissue was constructed using in-situ hybridization. In addition, the single-cell transcriptome data showed that the differentially expressed genes of macrophages were primarily enriched in the Toll-like receptor and Nod-like receptor signaling pathways. The expression levels of genes involved in these pathways were upregulated in macrophages following A. hydrophila infection. Transmission electron microscopy and TUNEL analysis revealed the cellular characteristics of macrophages before and after A. hydrophila infection. These data provide empirical support for in-depth research on the role of the kidney in the innate immune response of hybrid yellow catfish.

Utilization of Microfluidic Droplet-Based Methods in Diagnosis and Treatment Methods of Hepatocellular Carcinoma: A Review

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and is associated with high morbidity and mortality. One of the main challenges in the management of HCC is late clinical presentation and thus diagnosis of the disease, which results in poor survival. The pathogenesis of HCC is complex and involves chronic liver injury and genetic alterations. Diagnosis of HCC can be made either by biopsy or imaging; however, conventional tissue-based biopsy methods and serological biomarkers such as AFP have limited clinical applications. While hepatocellular carcinoma is associated with a range of molecular alterations, including the activation of oncogenic signaling pathways, such as Wnt-TGFβ, PI3K-AKT-mTOR, RAS-MAPK, MET, IGF, and Wnt-β-catenin and TP53 and TERT promoter mutations, microfluidic applications have been limited. Early diagnosis is crucial for advancing treatments that would address the heterogeneity of HCC. In this context, microfluidic droplet-based methods are crucial, as they enable comprehensive analysis of the genome and transcriptome of individual cells. Single-cell RNA sequencing (scRNA-seq) allows the examination of individual cell transcriptomes, identifying their heterogeneity and cellular evolutionary relationships. Other microfluidic methods, such as Drop-seq, InDrop, and ATAC-seq, are also employed for single-cell analysis. Here, we examine and compare these microfluidic droplet-based methods, exploring their advantages and limitations in liver cancer research. These technologies provide new opportunities to understand liver cancer biology, diagnosis, treatment, and prognosis, contributing to scientific efforts in combating this challenging disease.

A systematic framework for understanding the microbiome in human health and disease: from basic principles to clinical translation

The human microbiome is a complex and dynamic system that plays important roles in human health and disease. However, there remain limitations and theoretical gaps in our current understanding of the intricate relationship between microbes and humans. In this narrative review, we integrate the knowledge and insights from various fields, including anatomy, physiology, immunology, histology, genetics, and evolution, to propose a systematic framework. It introduces key concepts such as the 'innate and adaptive genomes', which enhance genetic and evolutionary comprehension of the human genome. The 'germ-free syndrome' challenges the traditional 'microbes as pathogens' view, advocating for the necessity of microbes for health. The 'slave tissue' concept underscores the symbiotic intricacies between human tissues and their microbial counterparts, highlighting the dynamic health implications of microbial interactions. 'Acquired microbial immunity' positions the microbiome as an adjunct to human immune systems, providing a rationale for probiotic therapies and prudent antibiotic use. The 'homeostatic reprogramming hypothesis' integrates the microbiome into the internal environment theory, potentially explaining the change in homeostatic indicators post-industrialization. The 'cell-microbe co-ecology model' elucidates the symbiotic regulation affecting cellular balance, while the 'meta-host model' broadens the host definition to include symbiotic microbes. The 'health-illness conversion model' encapsulates the innate and adaptive genomes' interplay and dysbiosis patterns. The aim here is to provide a more focused and coherent understanding of microbiome and highlight future research avenues that could lead to a more effective and efficient healthcare system.

Single-cell multi-modal chromatin profiles revealing epigenetic regulations of cells in hepatocellular carcinoma

BACKGROUND

Various epigenetic regulations systematically govern gene expression in cells involving various biological processes. Dysregulation of the epigenome leads to aberrant transcriptional programs and subsequently results in diseases, such as cancer. Therefore, comprehensive profiling epigenomics is essential for exploring the mechanisms underlying gene expression regulation during development and disease.

METHODS

In this study, we developed single-cell chromatin proteins and accessibility tagmentation (scCPA-Tag), a multi-modal single-cell epigenetic profile capturing technique based on barcoded Tn5 transposases and a droplet microfluidics platform. scCPA-Tag enables the simultaneous capture of DNA profiles of histone modification and chromatin accessibility in the same cell.

RESULTS

By applying scCPA-Tag to K562 cells and a hepatocellular carcinoma (HCC) sample, we found that the silence of several chromatin-accessible genes can be attributed to lysine-27-trimethylation of the histone H3 tail (H3K27me3) modification. We characterized the epigenetic features of the tumour cells and different immune cell types in the HCC tumour tissue by scCPA-Tag. Besides, a tumour cell subtype (C2) with more aggressive features was identified and characterized by high chromatin accessibility and a lower abundance of H3K27me3 on tumour-promoting genes.

CONCLUSIONS

Our multi-modal scCPA-Tag provides a comprehensive approach for exploring the epigenetic landscapes of heterogeneous cell types and revealing the mechanisms of gene expression regulation during developmental and pathological processes at the single-cell level.

HIGHLIGHTS

scCPA-Tag offers a highly efficient and high throughput technique to simultaneously profile histone modification and chromatin accessibility within a single cell. scCPA-Tag enables to uncover multiple epigenetic modification features of cellular compositions within tumor tissues. scCPA-Tag facilitates the exploration of the epigenetic landscapes of heterogeneous cell types and provides the mechanisms governing gene expression regulation.

Comprehensive review on single-cell RNA sequencing: A new frontier in Alzheimer's disease research

Alzheimer's disease (AD) is a multifaceted neurodegenerative condition marked by gradual cognitive deterioration and the loss of neurons. While conventional bulk RNA sequencing techniques have shed light on AD pathology, they frequently obscure the cellular diversity within brain tissues. The advent of single-cell RNA sequencing (scRNA-seq) has transformed our capability to analyze the cellular composition of AD, allowing for the detection of unique cell populations, rare cell types, and gene expression alterations at an individual cell level. This review examines the use of scRNA-seq in AD research, focusing on its contributions to understanding cellular diversity, disease progression, and potential therapeutic targets. We discuss key technological innovations, data analysis techniques, and challenges associated with scRNA-seq in studying AD. Furthermore, we highlight recent studies that have utilized scRNA-seq to identify novel biomarkers, uncover disease-associated pathways, and elucidate the role of non-neuronal cells, such as microglia and astrocytes, in AD pathogenesis. By providing a comprehensive overview of advancements in scRNA-seq for unraveling cellular heterogeneity in AD, this review highlights the transformative impact of scRNA-seq on our comprehension of disease mechanisms and the creation of targeted treatments.

NucMap 2.0: An Updated Database of Genome-wide Nucleosome Positioning Maps Across Species

Nucleosome dynamics plays important roles in many biological processes, such as DNA replication and gene expression. NucMap (https://ngdc.cncb.ac.cn/nucmap) is the first database of genome-wide nucleosome positioning maps across species. Here, we present an updated version, NucMap 2.0, by incorporating more species and MNase-seq samples. In addition, we integrate other related omics data for each MNase-seq sample to provide a comprehensive view of nucleosome positioning, such as gene expression, transcription factor binding sites, histone modifications and DNA methylation. In particular, NucMap 2.0 integrates and pre-analyzes RNA-seq data and ChIP-seq data of human-related samples, which facilitates the interpretation of nucleosome positioning in humans. All processed data are integrated into an in-built genome browser, and users can make comprehensive side-by-side analyses. In addition, more online analytical functions are developed, which allows researchers to identify differential nucleosome regions and explore potential gene regulatory regions. All resources are open access with a user-friendly web interface.

From Morphology to Molecules: Advances in the Distinction of Multiple Primary Lung Cancers From Intrapulmonary Metastases in Non-Small Cell Lung Cancer

The increasing incidence of multiple lung nodules underscores the need for precise differentiation between multiple primary lung cancers (MPLCs) and intrapulmonary metastases (IPMs). This distinction impacts patient prognosis and treatment strategies. The prevalence of multiple lung nodules, ranging from 19.7% to 55.5%, highlights the clinical significance of this challenge. Historically, the role of histopathology, particularly comprehensive histology assessment (CHA), has been pivotal in differentiating MPLCs and IPMs. However, CHA has significant limitations, resulting in a constant search for a better way to distinguish those lesions. The best strategy for delineating MPLCs from IPMs is a multidisciplinary approach combining clinical data, radiology, histology, and molecular methods. Histology provides architectural and cellular characteristics, radiology contributes anatomic context and lesion characterization, and molecular methods reveal molecular features critical for accurate differentiation. Incorporating clinical data further enhances diagnostic precision. This review presents current knowledge and current approaches to multiple lung tumors. It is clear that even with a combination of pathology, radiology, and molecular data, definitive classification of multifocal lung tumors is not always possible.

Label-free active single-cell encapsulation enabled by microvalve-based on-demand droplet generation and real-time image processing

Droplet microfluidics-based single-cell encapsulation is a critical technology that enables large-scale parallel single-cell analysis by capturing and processing thousands of individual cells. As the efficiency of passive single-cell encapsulation is limited by Poisson distribution, active single-cell encapsulation has been developed to theoretically ensure that each droplet contains one cell. However, existing active single-cell encapsulation technologies still face issues related to fluorescence labeling and low throughput. Here, we present an active single-cell encapsulation technique by using microvalve-based drop-on-demand technology and real-time image processing to encapsulate single cells with high throughput in a label-free manner. Our experiments demonstrated that the single-cell encapsulation system can encapsulate individual polystyrene beads with 96.3 % efficiency and HeLa cells with 94.9 % efficiency. The flow speed of cells in this system can reach 150 mm/s, resulting in a corresponding theoretical encapsulation throughput of 150 Hz. This technology has significant potential in various biomedical applications, including single-cell omics, secretion detection, and drug screening.

Rapid Screening of Biomarkers in KYSE-150 Cells Exposed to Polycyclic Aromatic Hydrocarbons via Inkjet Printing Single-Cell Mass Spectrometry

Single-cell analysis by mass spectrometry (MS) is emerging as a powerful tool that not only contributes to cellular heterogeneity but also offers an unprecedented opportunity to predict pathology onset and facilitates novel biomarker discovery. However, the development of single-cell MS analysis techniques with a focus on sample extraction, separation, and ionization methods for volume-limited samples and complexity of cellular samples are still a big challenge. In this study, we present a high-throughput approach to inkjet drop on demand printing single-cell MS for rapid screening of biomarkers of polycyclic aromatic hydrocarbon (PAH) exposure at the KYSE-150 cell, aiming to elucidate the pathogenesis of PAH-induced esophageal cancer. With an analytical bulk KYSE-150 cell throughput of up to 51 cells per minute, the method provides a new opportunity for simultaneous single-cell analysis of multiple biomarkers. We screened 930 characteristic ions from 3,683 detected peak signals and identified 91 distinctive molecules that exhibited significant differences under various concentrations of PAH exposure. These molecules have potential as clinical diagnostic biomarkers. Additionally, the current study identifies specific biomarkers that behave completely opposite in single-cell and multicell lipidomics as the concentration of PAH changes. These biomarkers potentially subdivide KYSE-150 cells into PAH-sensitive and PAH-insensitive types, providing a basis for revealing PAH toxicity and disease pathogenesis from the heterogeneity of cellular metabolism.

Distinct melanocyte subpopulations defined by stochastic expression of proliferation or maturation programs enable a rapid and sustainable pigmentation response

The ultraviolet (UV) radiation triggers a pigmentation response in human skin, wherein, melanocytes rapidly activate divergent maturation and proliferation programs. Using single-cell sequencing, we demonstrate that these 2 programs are segregated in distinct subpopulations in melanocytes of human and zebrafish skin. The coexistence of these 2 cell states in cultured melanocytes suggests possible cell autonomy. Luria-Delbrück fluctuation test reveals that the initial establishment of these states is stochastic. Tracking of pigmenting cells ascertains that the stochastically acquired state is faithfully propagated in the progeny. A systemic approach combining single-cell multi-omics (RNA+ATAC) coupled to enhancer mapping with H3K27 acetylation successfully identified state-specific transcriptional networks. This comprehensive analysis led to the construction of a gene regulatory network (GRN) that under the influence of noise, establishes a bistable system of pigmentation and proliferation at the population level. This GRN recapitulates melanocyte behaviour in response to external cues that reinforce either of the states. Our work highlights that inherent stochasticity within melanocytes establishes dedicated states, and the mature state is sustained by selective enhancers mark through histone acetylation. While the initial cue triggers a proliferation response, the continued signal activates and maintains the pigmenting subpopulation via epigenetic imprinting. Thereby our study provides the basis of coexistence of distinct populations which ensures effective pigmentation response while preserving the self-renewal capacity.

Cell Electrokinetic Fingerprint: A Novel Approach Based on Optically Induced Dielectrophoresis (ODEP) for In-Flow Identification of Single Cells

A novel optically induced dielectrophoresis (ODEP) system that can operate under flow conditions is designed for automatic trapping of cells and subsequent induction of 2D multi-frequency cell trajectories. Like in a "ping-pong" match, two virtual electrode barriers operate in an alternate mode with varying frequencies of the input voltage. The so-derived cell motions are characterized via time-lapse microscopy, cell tracking, and state-of-the-art machine learning algorithms, like the wavelet scattering transform (WST). As a cell-electrokinetic fingerprint, the dynamic of variation of the cell displacements happening, over time, is quantified in response to different frequency values of the induced electric field. When tested on two biological scenarios in the cancer domain, the proposed approach discriminates cellular dielectric phenotypes obtained, respectively, at different early phases of drug-induced apoptosis in prostate cancer (PC3) cells and for differential expression of the lectine-like oxidized low-density lipoprotein receptor-1 (LOX-1) transcript levels in human colorectal adenocarcinoma (DLD-1) cells. The results demonstrate increased discrimination of the proposed system and pose an additional basis for making ODEP-based assays addressing cancer heterogeneity for precision medicine and pharmacological research.

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding

Computational methods are desired for single-cell-resolution spatial transcriptomics (ST) data analysis to uncover spatial organization principles for how individual cells exert tissue-specific functions. Here, we present ST data analysis via interaction-aware cell embedding (SPACE), a deep-learning method for cell-type identification and tissue module discovery from single-cell-resolution ST data by learning a cell representation that captures its gene expression profile and interactions with its spatial neighbors. SPACE identified spatially informed cell subtypes defined by their special spatial distribution patterns and distinct proximal-interacting cell types. SPACE also automatically discovered "cell communities"-tissue modules with discernible boundaries and a uniform spatial distribution of constituent cell types. For each cell community, SPACE outputs a characteristic proximal cell-cell interaction network associated with physiological processes, which can be used to refine ligand-receptor-based intercellular signaling analyses. We envision that SPACE can be used in large-scale ST projects to understand how proximal cell-cell interactions contribute to emergent biological functions within cell communities. A record of this paper's transparent peer review process is included in the supplemental information.

A developmental constraint model of cancer cell states and tumor heterogeneity

Cancer is a disease that stems from a fundamental liability inherent to multicellular life forms in which an individual cell is capable of reneging on the interests of the collective organism. Although cancer is commonly described as an evolutionary process, a less appreciated aspect of tumorigenesis may be the constraints imposed by the organism's developmental programs. Recent work from single-cell transcriptomic analyses across a range of cancer types has revealed the recurrence, plasticity, and co-option of distinct cellular states among cancer cell populations. Here, we note that across diverse cancer types, the observed cell states are proximate within the developmental hierarchy of the cell of origin. We thus posit a model by which cancer cell states are directly constrained by the organism's "developmental map." According to this model, a population of cancer cells traverses the developmental map, thereby generating a heterogeneous set of states whose interactions underpin emergent tumor behavior.

Many Faces of Regulatory T Cells: Heterogeneity or Plasticity?

Regulatory T cells (Tregs) are essential for maintaining the immune balance in normal and pathological conditions. In autoimmune diseases and transplantation, they restrain the loss of self-tolerance and promote engraftment, whereas in cancer, an increase in Treg numbers is mostly associated with tumor growth and poor prognosis. Numerous markers and their combinations have been used to identify Treg subsets, demonstrating the phenotypic diversity of Tregs. The complexity of Treg identification can be hampered by the unstable expression of some markers, the decrease in the expression of a specific marker over time or the emergence of a new marker. It remains unclear whether such phenotypic shifts are due to new conditions or whether the observed changes are due to initially different populations. In the first case, cellular plasticity is observed, whereas in the second, cellular heterogeneity is observed. The difference between these terms in relation to Tregs is rather blurred. Considering the promising perspectives of Tregs in regenerative cell-based therapy, the existing confusing data on Treg phenotypes require further investigation and analysis. In our review, we introduce criteria that allow us to distinguish between the heterogeneity and plasticity of Tregs normally and pathologically, taking a closer look at their diversity and drawing the line between two terms.

Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases

Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.

DNMT1-targeting remodeling global DNA hypomethylation for enhanced tumor suppression and circumvented toxicity in oral squamous cell carcinoma

BACKGROUND

The faithful maintenance of DNA methylation homeostasis indispensably requires DNA methyltransferase 1 (DNMT1) in cancer progression. We previously identified DNMT1 as a potential candidate target for oral squamous cell carcinoma (OSCC). However, how the DNMT1- associated global DNA methylation is exploited to regulate OSCC remains unclear.

METHODS

The shRNA-specific DNMT1 knockdown was employed to target DNMT1 on oral cancer cells in vitro, as was the use of DNMT1 inhibitors. A xenografted OSCC mouse model was established to determine the effect on tumor suppression. High-throughput microarrays of DNA methylation, bulk and single-cell RNA sequencing analysis, multiplex immunohistochemistry, functional sphere formation and protein immunoblotting were utilized to explore the molecular mechanism involved. Analysis of human samples revealed associations between DNMT1 expression, global DNA methylation and collaborative molecular signaling with oral malignant transformation.

RESULTS

We investigated DNMT1 expression boosted steadily during oral malignant transformation in human samples, and its inhibition considerably minimized the tumorigenicity in vitro and in a xenografted OSCC model. DNMT1 overexpression was accompanied by the accumulation of cancer-specific DNA hypomethylation during oral carcinogenesis; conversely, DNMT1 knockdown caused atypically extensive genome-wide DNA hypomethylation in cancer cells and xenografted tumors. This novel DNMT1-remodeled DNA hypomethylation pattern hampered the dual activation of PI3K-AKT and CDK2-Rb and inactivated GSK3β collaboratively. When treating OSCC mice, targeting DNMT1 achieved greater anticancer efficacy than the PI3K inhibitor, and reduced the toxicity of blood glucose changes caused by the PI3K inhibitor or combination of PI3K and CDK inhibitors as well as adverse insulin feedback.

CONCLUSIONS

Targeting DNMT1 remodels a novel global DNA hypomethylation pattern to facilitate anticancer efficacy and minimize potential toxic effects via balanced signaling synergia. Our study suggests DNMT1 is a crucial gatekeeper regarding OSCC destiny and treatment outcome.

Epigenetic control of microglial immune responses

Microglia, the major population of brain-resident macrophages, are now recognized as a heterogeneous population comprising several cell subtypes with different (so far mostly supposed) functions in health and disease. A number of studies have performed molecular characterization of these different microglial activation states over the last years making use of "omics" technologies, that is transcriptomics, proteomics and, less frequently, epigenomics profiling. These approaches offer the possibility to identify disease mechanisms, discover novel diagnostic biomarkers, and develop new therapeutic strategies. Here, we focus on epigenetic profiling as a means to understand microglial immune responses beyond what other omics methods can offer, that is, revealing past and present molecular responses, gene regulatory networks and potential future response trajectories, and defining cell subtype-specific disease relevance through mapping non-coding genetic variants. We review the current knowledge in the field regarding epigenetic regulation of microglial identity and function, provide an exemplary analysis that demonstrates the advantages of performing joint transcriptomic and epigenomic profiling of single microglial cells and discuss how comprehensive epigenetic analyses may enhance our understanding of microglial pathophysiology.

The role of histone acetylation in transcriptional regulation and seed development

Histone acetylation is highly conserved across eukaryotes and has been linked to gene activation since its discovery nearly 60 years ago. Over the past decades, histone acetylation has been evidenced to play crucial roles in plant development and response to various environmental cues. Emerging data indicate that histone acetylation is one of the defining features of "open chromatin," while the role of histone acetylation in transcription remains controversial. In this review, we briefly describe the discovery of histone acetylation, the mechanism of histone acetylation regulating transcription in yeast and mammals, and summarize the research progress of plant histone acetylation. Furthermore, we also emphasize the effect of histone acetylation on seed development and its potential use in plant breeding. A comprehensive knowledge of histone acetylation might provide new and more flexible research perspectives to enhance crop yield and stress resistance.

EpiSegMix: a flexible distribution hidden Markov model with duration modeling for chromatin state discovery

MOTIVATION

Automated chromatin segmentation based on ChIP-seq (chromatin immunoprecipitation followed by sequencing) data reveals insights into the epigenetic regulation of chromatin accessibility. Existing segmentation methods are constrained by simplifying modeling assumptions, which may have a negative impact on the segmentation quality.

RESULTS

We introduce EpiSegMix, a novel segmentation method based on a hidden Markov model with flexible read count distribution types and state duration modeling, allowing for a more flexible modeling of both histone signals and segment lengths. In a comparison with existing tools, ChromHMM, Segway, and EpiCSeg, we show that EpiSegMix is more predictive of cell biology, such as gene expression. Its flexible framework enables it to fit an accurate probabilistic model, which has the potential to increase the biological interpretability of chromatin states.

AVAILABILITY AND IMPLEMENTATION

Source code: https://gitlab.com/rahmannlab/episegmix.

Beyond the tail: the consequence of context in histone post-translational modification and chromatin research

The role of histone post-translational modifications (PTMs) in chromatin structure and genome function has been the subject of intense debate for more than 60 years. Though complex, the discourse can be summarized in two distinct - and deceptively simple - questions: What is the function of histone PTMs? And how should they be studied? Decades of research show these queries are intricately linked and far from straightforward. Here we provide a historical perspective, highlighting how the arrival of new technologies shaped discovery and insight. Despite their limitations, the tools available at each period had a profound impact on chromatin research, and provided essential clues that advanced our understanding of histone PTM function. Finally, we discuss recent advances in the application of defined nucleosome substrates, the study of multivalent chromatin interactions, and new technologies driving the next era of histone PTM research.

Evaluating Riboglow-FLIM probes for RNA sensing

We recently developed Riboglow-FLIM, where we genetically tag and track RNA molecules in live cells through measuring the fluorescence lifetime of a small molecule probe that binds the RNA tag. Here, we systematically and quantitatively evaluated key elements of Riboglow-FLIM that may serve as the foundation for Riboglow-FLIM applications and further tool development efforts. Our investigation focused on measuring changes in fluorescence lifetime of representative Riboglow-FLIM probes with different linkers and fluorophores in different environments. In vitro measurements revealed distinct lifetime differences among the probe variants as a result of different linker designs and fluorophore selections. To expand on the platform's versatility, probes in a wide variety of mammalian cell types were examined using fluorescence lifetime imaging microscopy (FLIM), and possible effects on cell physiology were evaluated by metabolomics. The results demonstrated that variations in lifetime were dependent on both probe and cell type. Interestingly, distinct differences in lifetime values were observed between cell lines, while no overall change in cell health was measured. These findings underscore the importance of probe selection and cellular environment when employing Riboglow-FLIM for RNA detection, serving as a foundation for future tool development and applications across diverse fields and biological systems.

Single-cell RNA sequencing reveals the transcriptional heterogeneity of Tbx18-positive cardiac cells during heart development

The T-box family transcription factor 18 (Tbx18) has been found to play a critical role in regulating the development of the mammalian heart during the primary stages of embryonic development while the cellular heterogeneity and landscape of Tbx18-positive (Tbx18+) cardiac cells remain incompletely characterized. Here, we analyzed prior published single-cell RNA sequencing (scRNA-seq) mouse heart data to explore the heterogeneity of Tbx18+ cardiac cell subpopulations and provide a comprehensive transcriptional landscape of Tbx18+ cardiac cells during their development. Bioinformatic analysis methods were utilized to identify the heterogeneity between cell groups. Based on the gene expression characteristics, Tbx18+ cardiac cells can be classified into a minimum of two distinct cell populations, namely fibroblast-like cells and cardiomyocytes. In terms of temporal heterogeneity, these cells exhibit three developmental stages, namely the MEM stage, ML_P0 stage, and P stage Tbx18+ cardiac cells. Furthermore, Tbx18+ cardiac cells encompass several cell types, including cardiac progenitor-like cells, cardiomyocytes, and epicardial/stromal cells, as determined by specific transcriptional regulatory networks. The scRNA-seq results revealed the involvement of extracellular matrix (ECM) signals and epicardial epithelial-to-mesenchymal transition (EMT) in the development of Tbx18+ cardiac cells. The utilization of a lineage-tracing model served to validate the crucial function of Tbx18 in the differentiation of cardiac cells. Consequently, these findings offer a comprehensive depiction of the cellular heterogeneity within Tbx18+ cardiac cells.

Dynamics of cell-type transition mediated by epigenetic modifications

Maintaining tissue homeostasis requires appropriate regulation of stem cell differentiation. The Waddington landscape posits that gene circuits in a cell form a potential landscape of different cell types, wherein cells follow attractors of the probability landscape to develop into distinct cell types. However, how adult stem cells achieve a delicate balance between self-renewal and differentiation remains unclear. We propose that random inheritance of epigenetic states plays a pivotal role in stem cell differentiation and present a hybrid model of stem cell differentiation induced by epigenetic modifications. Our comprehensive model integrates gene regulation networks, epigenetic state inheritance, and cell regeneration, encompassing multi-scale dynamics ranging from transcription regulation to cell population. Through model simulations, we demonstrate that random inheritance of epigenetic states during cell divisions can spontaneously induce cell differentiation, dedifferentiation, and transdifferentiation. Furthermore, we investigate the influences of interfering with epigenetic modifications and introducing additional transcription factors on the probabilities of dedifferentiation and transdifferentiation, revealing the underlying mechanism of cell reprogramming. This in silico model provides valuable insights into the intricate mechanism governing stem cell differentiation and cell reprogramming and offers a promising path to enhance the field of regenerative medicine.

The chromatin landscape of healthy and injured cell types in the human kidney

There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. Comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measure dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We establish a spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we note distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3, KLF6, and KLF10 regulates the transition between health and injury, while in thick ascending limb cells this transition is regulated by NR2F1. Further, combined perturbation of ELF3, KLF6, and KLF10 distinguishes two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.

An omics review and perspective of researches on intrahepatic cholestasis of pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is one of the common pregnancy complications that may threaten the health of both pregnant women and their fetuses. Hence, it is of vital importance to identify key moleculars and the associated functional pathways of ICP, which will help us to better understand the pathological mechanisms as well as to develop precise clinical biomarkers. The emerging and developing of multiple omics approaches enable comprehensive studies of the genome, transcriptome, proteome and metabolome of clinical samples. The present review collected and summarized the omics based studies of ICP, aiming to provide an overview of the current progress, limitations and future directions. Briefly, these studies covered a broad range of research contents by the comparing of different experimental groups including ICP patients, ICP subtypes, ICP fetuses, ICP models and other complications. Correspondingly, the studied samples contain various types of clinical samples, in vitro cultured tissues, cell lines and the samples from animal models. According to the main research objectives, we further categorized these studies into two groups: pathogenesis and diagnosis analyses. The pathogenesis studies identified tens of functional pathways that may represent the key regulatory events for the occurrence, progression, treatment and fetal effects of ICP. On the other hand, the diagnosis studies tested more than 40 potential models for the early-prediction, diagnosis, grading, prognosis or differential diagnosis of ICP. Apart from these achievements, we also evaluated the limitations of current studies, and emphasized that many aspects of clinical characteristics, sample processing, and analytical method can greatly affect the reliability and repeatability of omics results. Finally, we also pointed out several new directions for the omics based analyses of ICP and other perinatal associated conditions in the future.

CellSTAR: a comprehensive resource for single-cell transcriptomic annotation

Large-scale studies of single-cell sequencing and biological experiments have successfully revealed expression patterns that distinguish different cell types in tissues, emphasizing the importance of studying cellular heterogeneity and accurately annotating cell types. Analysis of gene expression profiles in these experiments provides two essential types of data for cell type annotation: annotated references and canonical markers. In this study, the first comprehensive database of single-cell transcriptomic annotation resource (CellSTAR) was thus developed. It is unique in (a) offering the comprehensive expertly annotated reference data for annotating hundreds of cell types for the first time and (b) enabling the collective consideration of reference data and marker genes by incorporating tens of thousands of markers. Given its unique features, CellSTAR is expected to attract broad research interests from the technological innovations in single-cell transcriptomics, the studies of cellular heterogeneity & dynamics, and so on. It is now publicly accessible without any login requirement at: https://idrblab.org/cellstar.

CLIC3 interacts with NAT10 to inhibit N4-acetylcytidine modification of p21 mRNA and promote bladder cancer progression

Chromatin accessibility plays important roles in revealing the regulatory networks of gene expression, while its application in bladder cancer is yet to be fully elucidated. Chloride intracellular channel 3 (CLIC3) protein has been reported to be associated with the progression of some tumors, whereas the specific mechanism of CLIC3 in tumor remains unclear. Here, we screened for key genes in bladder cancer through the identification of transcription factor binding site clustered region (TFCR) on the basis of chromatin accessibility and TF motif. CLIC3 was identified by joint profiling of chromatin accessibility data with TCGA database. Clinically, CLIC3 expression was significantly elevated in bladder cancer and was negatively correlated with patient survival. CLIC3 promoted the proliferation of bladder cancer cells by reducing p21 expression in vitro and in vivo. Mechanistically, CLIC3 interacted with NAT10 and inhibited the function of NAT10, resulting in the downregulation of ac4C modification and stability of p21 mRNA. Overall, these findings uncover an novel mechanism of mRNA ac4C modification and CLIC3 may act as a potential therapeutic target for bladder cancer.

A review of innovative electrochemical strategies for bioactive molecule detection and cell imaging: Current advances and challenges

Cellular heterogeneity poses a major challenge for tumor theranostics, requiring high-resolution intercellular bioanalysis strategies. Over the past decades, the advantages of electrochemical analysis, such as high sensitivity, good spatio-temporal resolution, and ease of use, have made it the preferred method to uncover cellular differences. To inspire more creative research, herein, we highlight seminal works in electrochemical techniques for biomolecule analysis and bioimaging. Specifically, micro/nano-electrode-based electrochemical techniques enable real-time quantitative analysis of electroactive substances relevant to life processes in the micro-nanostructure of cells and tissues. Nanopore-based technique plays a vital role in biosensing by utilizing nanoscale pores to achieve high-precision detection and analysis of biomolecules with exceptional sensitivity and single-molecule resolution. Electrochemiluminescence (ECL) technology is utilized for real-time monitoring of the behavior and features of individual cancer cells, enabling observation of their dynamic processes due to its capability of providing high-resolution and highly sensitive bioimaging of cells. Particularly, scanning electrochemical microscopy (SECM) and scanning ion conductance microscopy (SICM) which are widely used in real-time observation of cell surface biological processes and three-dimensional imaging of micro-nano structures, such as metabolic activity, ion channel activity, and cell morphology are introduced in this review. Furthermore, the expansion of the scope of cellular electrochemistry research by innovative functionalized electrodes and electrochemical imaging models and strategies to address future challenges and potential applications is also discussed in this review.

Identification and validation of chromatin regulator-related signatures as a novel prognostic model for low-grade gliomas using translational bioinformatics

AIMS

The purpose of this study is to explore the potential biological role and prognostic significance of chromatin regulators (CRs) in low-grade gliomas (LGGs).

MAIN METHODS

CRs were obtained from the FACER database. Transcription profiles of LGG patients were collected from the TCGA and CGGA databases. Differentially expressed CRs (DECRs) between LGGs and normal controls were identified using DESeq2. The consensus clustering algorithm was employed to distinguish subtypes of LGGs based on prognosis-related DECRs. The differences in clinical and molecular characteristics between different subtypes were explored. R packages, GSVA, ssGSEA, and ESTIMATE were utilized to elucidate the tumor microenvironment and activated pathways in different subtypes. Subsequently, a CRs-related signature was developed using LASSO Cox regression. Its performance was evaluated by Kaplan-Meier curve and ROC curve analyses. In vitro experiments were performed to explore the function of JADE3 in LGGs, which predominantly expressed in glioma cells.

KEY FINDINGS

We identified 43 DECRs and two CRs-related subtypes of LGGs. The subtype characterized by shorter survival displayed significant enrichment for pathways associated with DNA damage response and repair, along with heightened immune cell infiltration. Furthermore, the CRs-based signature exhibited excellent prognostic performance in both the TCGA and CGGA databases. Knockdown of JADE3 significantly increased the invasion, migration, and proliferation abilities of Hs683.

SIGNIFICANCE

Our study reveals the aberrant expression and prognostic value of CRs in LGGs. It emphasizes the potential regulatory role of CRs in the microenvironment and DNA damage repair in LGGs. JADE3 could be a possible therapeutic target for LGGs.

Epigenetic modifications: Key players in cancer heterogeneity and drug resistance

Cancer heterogeneity and drug resistance remain pivotal obstacles in effective cancer treatment and management. One major contributor to these challenges is epigenetic modifications - gene regulation that does not involve changes to the DNA sequence itself but significantly impacts gene expression. As we elucidate these phenomena, we underscore the pivotal role of epigenetic modifications in regulating gene expression, contributing to cellular diversity, and driving adaptive changes that can instigate therapeutic resistance. This review dissects essential epigenetic modifications - DNA methylation, histone modifications, and chromatin remodeling - illustrating their significant yet complex contributions to cancer biology. While these changes offer potential avenues for therapeutic intervention due to their reversible nature, the interplay of epigenetic and genetic changes in cancer cells presents unique challenges that must be addressed to harness their full potential. By critically analyzing the current research landscape, we identify knowledge gaps and propose future research directions, exploring the potential of epigenetic therapies and discussing the obstacles in translating these concepts into effective treatments. This comprehensive review aims to stimulate further research and aid in developing innovative, patient-centered cancer therapies. Understanding the role of epigenetic modifications in cancer heterogeneity and drug resistance is critical for scientific advancement and paves the way towards improving patient outcomes in the fight against this formidable disease.

DNA Barcodes Using a Dual Nanopore Device

We report a novel method based on the current blockade (CB) characteristics obtained from a dual nanopore device that can determine DNA barcodes with near-perfect accuracy using a Brownian dynamics simulation strategy. The method supersedes our previously reported velocity correction algorithm (S. Seth and A. Bhattacharya, RSC Advances, 11:20781-20787, 2021), taking advantage of the better measurement of the time-of-flight (TOF) protocol offered by the dual nanopore setup. We demonstrate the efficacy of the method by comparing our simulation data from a coarse-grained model of a polymer chain consisting of 2048 excluded volume beads of diameter 𝜎 = 24 bp using with those obtained from experimental CB data from a 48,500 bp λ-phage DNA, providing a 48500 2400 ≅ 24 base pair resolution in simulation. The simulation time scale is compared to the experimental time scale by matching the simulated time-of-flight (TOF) velocity distributions with those obtained experimentally (Rand et al., ACS Nano, 16:5258-5273, 2022). We then use the evolving coordinates of the dsDNA and the molecular features to reconstruct the current blockade characteristics on the fly using a volumetric model based on the effective van der Waal radii of the species inside and in the immediate vicinity of the pore. Our BD simulation mimics the control-zoom-in-logic to understand the origin of the TOF distributions due to the relaxation of the out-of-equilibrium conformations followed by a reversal of the electric fields. The simulation algorithm is quite general and can be applied to differentiate DNA barcodes from different species.

The role of circRNAs in regulation of drug resistance in ovarian cancer

Ovarian cancer is one of the female reproductive system tumors. Chemotherapy is used for advanced ovarian cancer patients; however, drug resistance is a pivotal cause of chemotherapeutic failure. Hence, it is critical to explore the molecular mechanisms of drug resistance of ovarian cancer cells and to ameliorate chemoresistance. Noncoding RNAs (ncRNAs) have been identified to critically participate in drug sensitivity in a variety of human cancers, including ovarian cancer. Among ncRNAs, circRNAs sponge miRNAs and prevent miRNAs from regulation of their target mRNAs. CircRNAs can interact with DNA or proteins to modulate gene expression. In this review, we briefly describe the biological functions of circRNAs in the development and progression of ovarian cancer. Moreover, we discuss the underneath regulatory molecular mechanisms of circRNAs on governing drug resistance in ovarian cancer. Furthermore, we mention the novel strategies to overcome drug resistance via targeting circRNAs in ovarian cancer. Due to that circRNAs play a key role in modulation of drug resistance in ovarian cancer, targeting circRNAs could be a novel approach for attenuation of chemoresistance in ovarian cancer.

Geniposide alleviated hydrogen peroxide-induced apoptosis of human hepatocytes via altering DNA methylation

Geniposide (GP) is the homology of medicine and food with bioactive effects of antioxidation and resistance to apoptosis in the liver. It's of great significance to explore the biosafety exposure limits and action mechanisms of GP. This study detected the global DNA methylation microenvironment and the regulation of specific genes in GP against cellular apoptosis induced by hydrogen peroxide (H2O2) of human hepatocyte L-02 cells. The half inhibitory concentration (IC50) of GP on normal L-02 cells was 57.7 mg/mL. GP exerted new epigenetic activity, increased DNMT1, decreased TET1 and TET2 expression, and reversed the demethylation effect to some extent, thereby increasing the overall genomic DNA methylation level at the concentration of 900 μg/mL. GP pretreatment could also adjust the level of P53, Bcl-2 and AKT altered by H2O2, reducing their specific DNA methylation levels in the promoter regions of AKT and Bcl-2 to inhibit apoptosis. Taken together, GP regulates the global DNA methylation level and controls the expression changes of P53, Bcl-2 and AKT, jointly inhibiting the occurrence of apoptosis in human hepatocytes and providing the newly theoretical references for its safety evaluation.

Deciphering tumor-infiltrating dendritic cells in the single-cell era

Dendritic cells (DCs) serve as a pivotal link connecting innate and adaptive immunity by processing tumor-derived antigens and activating T cells. The advent of single-cell sequencing has revolutionized the categorization of DCs, enabling a high-resolution characterization of the previously unrecognized diversity of DC populations infiltrating the intricate tumor microenvironment (TME). The application of single-cell sequencing technologies has effectively elucidated the heterogeneity of DCs present in the tumor milieu, yielding invaluable insights into their subpopulation structures and functional diversity. This review provides a comprehensive summary of the current state of knowledge regarding DC subtypes in the TME, drawing from single-cell studies conducted across various human tumors. We focused on the categorization, functions, and interactions of distinct DC subsets, emphasizing their crucial roles in orchestrating tumor-related immune responses. Additionally, we delve into the potential implications of these findings for the identification of predictive biomarkers and therapeutic targets. Enhanced insight into the intricate interplay between DCs and the TME promises to advance our comprehension of tumor immunity and, in turn, pave the way for the development of more efficacious cancer immunotherapies.

Unveiling the growing significance of metabolism in modulating immune cell function: exploring mechanisms and implications; a review

Immunometabolism has emerged as a rapidly growing field of research, holding significant promise for personalised medicine and precision immunotherapy. This review explores the intricate relationship between immune function and metabolic processes, emphasising their profound impact on various immune-related disorders. Understanding how metabolic dysregulation contributes to the pathogenesis of these disorders remains a critical research gap. Therefore, this review aims to bridge that gap by examining the key metabolic pathways involved and their specific implications in immune cell function. Key metabolic pathways, including glycolysis, mitochondrial metabolism, fatty acid metabolism, and amino acid metabolism, are discussed in the context of immune cell function. Dysregulation of these pathways can disrupt immune cell activation, differentiation, and overall function, contributing to disease pathogenesis. Understanding these metabolic alterations' molecular mechanisms is essential for developing targeted therapeutic interventions. The review also emphasises the importance of personalised medicine in immune-related disorders. The unique metabolic profiles of individuals can influence treatment outcomes, highlighting the need for tailored approaches. Integrating metabolic profiling into clinical practice can enhance treatment efficacy and improve patient outcomes. Investigating the clinical significance of immunometabolism in diverse disease contexts will facilitate the translation of research findings into clinical practice. Moreover, refining treatment strategies based on individual metabolic profiles will contribute to advancing precision immunotherapy.

A live-cell platform to isolate phenotypically defined subpopulations for spatial multi-omic profiling

Numerous techniques have been employed to deconstruct the heterogeneity observed in normal and diseased cellular populations, including single cell RNA sequencing, in situ hybridization, and flow cytometry. While these approaches have revolutionized our understanding of heterogeneity, in isolation they cannot correlate phenotypic information within a physiologically relevant live-cell state with molecular profiles. This inability to integrate a live-cell phenotype-such as invasiveness, cell:cell interactions, and changes in spatial positioning-with multi-omic data creates a gap in understanding cellular heterogeneity. We sought to address this gap by employing lab technologies to design a detailed protocol, termed Spatiotemporal Genomic and Cellular Analysis (SaGA), for the precise imaging-based selection, isolation, and expansion of phenotypically distinct live cells. This protocol requires cells expressing a photoconvertible fluorescent protein and employs live cell confocal microscopy to photoconvert a user-defined single cell or set of cells displaying a phenotype of interest. The total population is then extracted from its microenvironment, and the optically highlighted cells are isolated using fluorescence activated cell sorting. SaGA-isolated cells can then be subjected to multi-omics analysis or cellular propagation for in vitro or in vivo studies. This protocol can be applied to a variety of conditions, creating protocol flexibility for user-specific research interests. The SaGA technique can be accomplished in one workday by non-specialists and results in a phenotypically defined cellular subpopulations for integration with multi-omics techniques. We envision this approach providing multi-dimensional datasets exploring the relationship between live cell phenotypes and multi-omic heterogeneity within normal and diseased cellular populations.

Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity

BACKGROUND

Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies.

RESULTS

The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development.

CONCLUSION

This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations.

Regulation of CTCF loop formation during pancreatic cell differentiation

Transcription reprogramming during cell differentiation involves targeting enhancers to genes responsible for establishment of cell fates. To understand the contribution of CTCF-mediated chromatin organization to cell lineage commitment, we analyzed 3D chromatin architecture during the differentiation of human embryonic stem cells into pancreatic islet organoids. We find that CTCF loops are formed and disassembled at different stages of the differentiation process by either recruitment of CTCF to new anchor sites or use of pre-existing sites not previously involved in loop formation. Recruitment of CTCF to new sites in the genome involves demethylation of H3K9me3 to H3K9me2, demethylation of DNA, recruitment of pioneer factors, and positioning of nucleosomes flanking the new CTCF sites. Existing CTCF sites not involved in loop formation become functional loop anchors via the establishment of new cohesin loading sites containing NIPBL and YY1 at sites between the new anchors. In both cases, formation of new CTCF loops leads to strengthening of enhancer promoter interactions and increased transcription of genes adjacent to loop anchors. These results suggest an important role for CTCF and cohesin in controlling gene expression during cell differentiation.

Cellular specificity is key to deciphering epigenetic changes underlying Alzheimer's disease

Different cell types in the brain play distinct roles in Alzheimer's disease (AD) progression. Late onset AD (LOAD) is a complex disease, with a large genetic component, but many risk loci fall in non-coding genome regions. Epigenetics implicates the non-coding genome with control of gene expression. The epigenome is highly cell-type specific and dynamically responds to the environment. Therefore, epigenetic mechanisms are well placed to explain genetic and environmental factors that are associated with AD. However, given this cellular specificity, purified cell populations or single cells need to be profiled to avoid effect masking. Here we review the current state of cell-type specific genome-wide profiling in LOAD, covering DNA methylation (CpG, CpH, and hydroxymethylation), histone modifications, and chromatin changes. To date, these data reveal that distinct cell types contribute and react differently to AD progression through epigenetic alterations. This review addresses the current gap in prior bulk-tissue derived work by spotlighting cell-specific changes that govern the complex interplay of cells throughout disease progression and are critical in understanding and developing effective treatments for AD.

scBridge embraces cell heterogeneity in single-cell RNA-seq and ATAC-seq data integration

Single-cell multi-omics data integration aims to reduce the omics difference while keeping the cell type difference. However, it is daunting to model and distinguish the two differences due to cell heterogeneity. Namely, even cells of the same omics and type would have various features, making the two differences less significant. In this work, we reveal that instead of being an interference, cell heterogeneity could be exploited to improve data integration. Specifically, we observe that the omics difference varies in cells, and cells with smaller omics differences are easier to be integrated. Hence, unlike most existing works that homogeneously treat and integrate all cells, we propose a multi-omics data integration method (dubbed scBridge) that integrates cells in a heterogeneous manner. In brief, scBridge iterates between i) identifying reliable scATAC-seq cells that have smaller omics differences, and ii) integrating reliable scATAC-seq cells with scRNA-seq data to narrow the omics gap, thus benefiting the integration for the rest cells. Extensive experiments on seven multi-omics datasets demonstrate the superiority of scBridge compared with six representative baselines.

Inferring chromatin accessibility during murine hematopoiesis through phylogenetic analysis

OBJECTIVE

Diversification of cell types and changes in epigenetic states during cell differentiation processes are important for understanding development. Recently, phylogenetic analysis using DNA methylation and histone modification information has been shown useful for inferring these processes. The purpose of this study was to examine whether chromatin accessibility data can help infer these processes in murine hematopoiesis.

RESULTS

Chromatin accessibility data could partially infer the hematopoietic differentiation hierarchy. Furthermore, based on the ancestral state estimation of internal nodes, the open/closed chromatin states of differentiating progenitor cells could be predicted with a specificity of 0.86-0.99 and sensitivity of 0.29-0.72. These results suggest that the phylogenetic analysis of chromatin accessibility could offer important information on cell differentiation, particularly for organisms from which progenitor cells are difficult to obtain.