The epigenetic basis of cellular heterogeneity

Multigenerational cell tracking of DNA replication and heritable DNA damage

Cell heterogeneity is a universal feature of life. Although biological processes affected by cell-to-cell variation are manifold, from developmental plasticity to tumour heterogeneity and differential drug responses, the sources of cell heterogeneity remain largely unclear1,2. Mutational and epigenetic signatures from cancer (epi)genomics are powerful for deducing processes that shaped cancer genome evolution3-5. However, retrospective analyses face difficulties in resolving how cellular heterogeneity emerges and is propagated to subsequent cell generations. Here, we used multigenerational single-cell tracking based on endogenously labelled proteins and custom-designed computational tools to elucidate how oncogenic perturbations induce sister cell asymmetry and phenotypic heterogeneity. Dual CRISPR-based genome editing enabled simultaneous tracking of DNA replication patterns and heritable endogenous DNA lesions. Cell lineage trees of up to four generations were tracked in asynchronously growing cells, and time-resolved lineage analyses were combined with end-point measurements of cell cycle and DNA damage markers through iterative staining. Besides revealing replication and repair dynamics, damage inheritance and emergence of sister cell heterogeneity across multiple cell generations, through combination with single-cell transcriptomics, we delineate how common oncogenic events trigger multiple routes towards polyploidization with distinct outcomes for genome integrity. Our study provides a framework to dissect phenotypic plasticity at the single-cell level and sheds light onto cellular processes that may resemble early events during cancer development.

The gene regulatory mechanisms shaping the heterogeneity of venom production in the Cape coral snake

BACKGROUND

Venoms and their associated glands and delivery structures have evolved numerous times among animals. Within these venom systems, the molecular, cellular, and morphological components interact and co-evolve to generate distinct, venom phenotypes that are increasingly recognized as models for studying adaptive evolution. However, toxins are often unevenly distributed across venom-producing tissues in patterns that are not necessarily adaptive but instead likely result from constraints associated with protein secretion.

RESULTS

We generate a high-quality draft genome of the Cape coral snake (Aspidelaps lubricus) and combine analyses of venom gland single-cell RNA-seq data with spatial venom gland in situ toxin distributions. Our results reveal that while different toxin families are produced by distinct populations of cells, toxin expression is fine-tuned by regulatory modules that result in further specialization of toxin production within each cell population. We also find that the evolution of regulatory elements closely mirrors the evolution of their associated toxin genes, resulting in spatial association of closely related and functionally similar toxins in the venom gland. While this compartmentalization is non-adaptive, the modularity of the underlying regulatory network likely facilitated the repeated evolution of defensive venom in spitting cobras.

CONCLUSIONS

Our results provide new insight into the variability of toxin regulation across snakes, reveal the molecular mechanisms underlying the heterogeneous toxin production in snake venom glands, and provide an example of how constraints can result in non-adaptive character states that appear to be adaptive, which may nevertheless facilitate evolutionary innovation and novelty.

Clonal dispersal is associated with tumor heterogeneity and poor prognosis in colorectal cancer

Clonal dispersal, resulting from the intermingling of tumor cell subpopulations, is thought to be a key driver of tumor heterogeneity. Despite advances in spatial modeling of cancer biology, quantification of clonal dispersal has been challenging. This study introduces a straightforward method, relying on fluorescent cell barcoding, to quantify clonal dispersal in various in vitro and in vivo models of colorectal cancer (CRC). Our approach allows for precise localization of clones and uncovering the degree of clonal mixing across different CRC models. Our findings suggest that clonal dispersal is correlated with the expression of genes involved in epithelial-mesenchymal transition and CMS4-related signaling pathways. We further identify a dispersal gene signature, associated with intratumor heterogeneity, which is a robust clinical predictor of poor prognosis and recurrence in CRC, highlighting its potential as a prognostic marker and a putative direction for therapeutic targeting.

RNA research for drug discovery: Recent advances and critical insight

The field of RNA research has experienced significant changes and is now at the forefront of contemporary drug development. This narrative overview explores the scientific developments and historical turning points in RNA research, emphasising the field's critical significance in the development of novel therapeutics. Important discoveries like antisense oligonucleotides (ASOs), mRNA therapies, and RNA interference (RNAi) have created novel treatment options that can be targeted, such as the ground-breaking mRNA vaccinations against COVID-19. Advances in high-throughput sequencing, single-cell RNA sequencing, and epitranscriptomics have further unravelled the complexity of RNA biology, shedding light on the intricacies of gene regulation and cellular diversity. The integration of computational tools and bioinformatics has propelled the identification of RNA-based biomarkers and the development of RNA therapeutics. Despite significant progress, challenges such as RNA stability, delivery, and off-target effects persist, necessitating continuous innovation and ethical considerations. This review provides a critical insight into the current state and prospects of RNA research, emphasising its transformative potential in drug discovery. By examining the interplay between technological advancements and therapeutic applications, we underscore the promising horizon for RNA-based interventions in treating a myriad of diseases, marking a new era in precision medicine.

scCompass: An Integrated Multi-Species scRNA-seq Database for AI-Ready

Emerging single-cell sequencing technology has generated large amounts of data, allowing analysis of cellular dynamics and gene regulation at the single-cell resolution. Advances in artificial intelligence enhance life sciences research by delivering critical insights and optimizing data analysis processes. However, inconsistent data processing quality and standards remain to be a major challenge. Here scCompass is proposed, which provides a comprehensive resource designed to build large-scale, multi-species, and model-friendly single-cell data collection. By applying standardized data pre-processing, scCompass integrates and curates transcriptomic data from nearly 105 million single cells across 13 species. Using this extensive dataset, it is able to identify stable expression genes (SEGs) and organ-specific expression genes (OSGs) in humans and mice. Different scalable datasets are provided that can be easily adapted for AI model training and the pretrained checkpoints with state-of-the-art single-cell foundation models. In summary, scCompass is highly efficient and scalable database for AI-ready, which combined with user-friendly data sharing, visualization, and online analysis, greatly simplifies data access and exploitation for researchers in single-cell biology (http://www.bdbe.cn/kun).

Insights into the role of histone lysine demethylases in bone homeostasis and skeletal diseases: A review

Histone lysine demethylases (KDMs), as important epigenetic regulators, are involved in various biological processes such as energy metabolism, apoptosis, and autophagy. Recent research shows that KDMs activate or silence downstream target genes by removing lysine residues from histone tails, and participate in the regulation of bone marrow mesenchymal stem cells (BM-MSCs), osteoblasts (OB), osteoclasts (OC), chondrocytes and other skeletal cell development, differentiation and formation. Moreover, several members of the KDM family affect the occurrence and development of bone diseases such as osteoporosis (OP), osteoarthritis (OA), osteosarcoma (OS), by regulating target genes. Specific regulation mechanisms of KDMs suggest new strategies for bone disease treatment and prevention. Despite the unique function and importance of KDMs in the skeletal system, previous studies have never systematically summarized their specific role, molecular mechanism, and clinical treatment in bone physiology and pathology. Therefore, this review summarises the expression pattern, intracellular signal transduction, and mechanism of action of the KDM family in several bone physiological and pathological conditions, aiming to highlight the important role of KDMs in bone diseases and provide a reference for the future treatment of bone diseases.

CRISPR/Cas-mediated macromolecular DNA methylation editing: Precision targeting of DNA methyltransferases in cancer therapy

Epigenetic modifications, particularly DNA methylation, play a pivotal role in gene regulation, influencing tumor suppressor silencing and oncogene activation in cancer. DNA methyltransferases (DNMTs), Ten-eleven translocation (TET) enzymes, and associated chromatin regulators are key biological macromolecules that mediate these epigenetic processes. Targeting aberrant DNA methylation holds great promise for cancer therapy, but traditional approaches lack precision and specificity. CRISPR/Cas-based epigenetic editing has emerged as a transformative tool for macromolecular DNA methylation reprogramming, offering targeted modifications without altering the genetic sequence. This review explores the role of DNMTs, TET enzymes, and chromatin-associated proteins in cancer epigenetics and discusses how CRISPR/dCas9 fused with DNMT3A or TET1 enables locus-specific DNA methylation editing. We highlight recent advances, including dCas9-DNMT3A for precise hypermethylation and dCas9-TET1 for targeted demethylation, and discuss their applications in reactivating tumor suppressor genes or silencing oncogenic pathways. Novel epigenetic editing systems, such as SunTag-based amplification, KRAB-MeCP2 repression, further enhance targeting efficiency and therapeutic potential. CRISPR/Cas-mediated macromolecular epigenetic editing represents a paradigm shift in cancer therapy, providing unprecedented control over DNA methylation and chromatin regulation. Despite challenges such as tumor heterogeneity and off-target effects, integrating CRISPR-based methylation reprogramming with precision oncology holds immense promise for future clinical applications.

The combination of BET and METTL3 inhibitors elicits synergistic antitumor effects in ovarian cancer cells via reducing SP1 and BCL-2 expression

Ovarian cancer (OC) remains a major health threat to woman despite treatment advances. New therapeutic strategies are demanded to persistently explored. In this study, we found that inhibitors of bromodomain and extra-Terminal domain (BET) and methyltransferase-like 3 (METTL3) exerted synergistic proliferative inhibition in different OC cell lines. In vitro synergism was translated into in vivo antitumor activity through the combination of BET inhibitor HJP-178 and METTL3 inhibitor STM2457. Mechanistically, this combination mainly enhanced apoptosis rather than affecting cell cycle arrest. Furthermore, it was revealed that HJP-178 decreased the transcription of Specificity protein 1 (SP1) while STM2457 lowered the N6-methyladenosine (m6A) levels of SP1 mRNA. Consequently, their combination synergistically reduces SP1 RNA and protein levels through both transcriptional and post-transcriptional modifications. Further exploration demonstrated that inhibiting SP1 directly downregulates the anti-apoptotic protein B-cell lymphoma-2 (BCL-2), activating the caspase-mediated apoptotic pathway and triggering programmed cell death. Importantly, SP1 overexpression significantly reducing the apoptosis induction and proliferation inhibition induced by the combination. Similarly, BCL-2 overexpression mimicked the effects of increased SP1. These results demonstrate the critical roles of SP1 and BCL-2 in the synergistic antitumor activity between BET and METTL3 inhibitors. Collectively, our findings broaden the potential applications of both drug types and present a promising therapeutic approach for OC, warranting further investigation in clinical settings.

The role of microheterogeneity in cell fate decisions in neural progenitors and neural crest

Neuroprogenitors must integrate a multitude of signals, including gradients of morphogens, transcriptional programs, and temporal cues to generate an astonishing diversity of cell types inhabiting the nervous system. How do these different layers of information come together to influence cell fate in progenitor cells in a coordinated way? Here we provide a nuanced perspective on cell fate selection in the nervous system and neural crest lineage, suggesting that it is not a straightforward, deterministic process governed by rigid on-off switches. Instead, the process involves probabilistic transitions influenced by small variations - termed "microheterogeneity" - within a progenitor cell population. These minuscule differences between individual neural progenitor cells can result in significantly different outcomes, making certain fates more probable for some cells than others. Here we discuss the diversity of such examples and the theory behind, also providing future perspectives.

The Temperature of the First Cleavage Impacts Preimplantation Development and Newborn Viability

At the early developmental stage, embryos are susceptible to environmental factors, which modulate development trajectories. In our study, we examined how different incubation temperatures (35 °C, 37 °C, and 39 °C) in vitro during the first embryonic cleavage affect the morphology, cell division rate, and DNA methylation in two-, four-, and eight-cell embryos and the viability of these two-cell embryos transferred to recipient females. Embryos kept at 35 °C for the first 24 h after in vitro fertilization in two- and four-cell embryos at 37 °C showed enhanced variability in the size of blastomeres and DNA 5mC level among blastomeres, as compared to the groups kept at 37 °C and 39 °C. This was associated with the highest rate of embryo death in four- and eight-cell embryos and the highest viability of newborns. In contrast, incubation at 39 °C did not significantly impact developmental dynamics and viability in vitro but led to a notably higher rate of gestation failure compared to other groups. The indicators of the 37 °C group fell within an intermediate range. Therefore, we conclude that a decrease in temperature during zygotic genome activation (ZGA) highlights the adaptive potential of embryos during their initial cleavages, while an increase in temperature does not show clear effects on their fate.

Regulatory element map of sheep reproductive tissues: functional annotation of tissue-specific strong active enhancers

Introduction

Comprehensive functional annotation of the genome is crucial for elucidating the molecular mechanisms underlying complex traits and diseases. Although functional annotation has been partially completed in sheep, a systematic annotation focused on reproductive tissues remains absent.

Methods

In this study, we integrated 60 transcriptomic and epigenomic datasets from five reproductive tissues. Using a multi-omics approach, we predicted 15 distinct chromatin states and conducted thorough functional annotation.

Results

We established the first regulatory element atlas for sheep reproductive tissues and examined the roles of these elements in reproductive traits and disease. In total, we annotated 1,680,172 regulatory elements, including 83,980 tissue-specific strong active enhancers (EnhAs).

Discussion

Enhancers were identified as critical drivers of tissue-specific functions, operating through sequence-specific transcription factor binding and direct regulation of target genes. Key transcription factors associated with reproductive function included INHBA (ovary), KITLG (oviduct), Snai2 (cervix), WNT7A (uterine horn), FOLR1 (uterine body), and SALL1 (shared uterine regions). Additionally, our findings support the potential of sheep as a promising model for investigating embryonic development and miscarriage. This work lays a theoretical foundation for future research into the molecular mechanisms of complex traits and diseases in sheep.

Diagnosing recipient- vs. donor-derived posttransplant myelodysplastic neoplasm via targeted single-cell mutational profiling

BACKGROUND

Distinguishing donor- vs. recipient-derived myelodysplastic neoplasm (MDS) after allogeneic hematopoietic stem cell transplantation (allo-HSCT) is challenging and has direct therapeutical implications.

METHODS

Here, we took a translational approach that we used in addition to conventional diagnostic techniques to resolve the origin of MDS in a 38-year-old patient with acquired aplastic anemia and evolving MDS after first allo-HSCT. Specifically, we used single-cell transcriptional profiling to differentiate between donor- and recipient-derived bone marrow cells and established a strategy that additionally allows identification of cells carrying the MDS-associated U2AF1S34Y variant.

RESULTS

The patient exhibited mixed donor chimerism combined with severely reduced erythropoiesis and dysplastic morphology within the granulocytic and megakaryocytic lineage along with the MDS-associated U2AF1S34Y mutation in the bone marrow. Single-cell transcriptional profiling together with targeted enrichment of the U2AF1S34Y-specific locus further revealed that, while the immune compartment was mainly populated by donor-derived cells, myelopoiesis was predominantly driven by the recipient. Additionally, concordant with recipient-derived MDS, we found that U2AF1S34Y-mutated cells were exclusively recipient derived with X but not Y chromosome-specific gene expression.

CONCLUSION

Our study highlights the clinical potential of integrating high-resolution single-cell techniques to resolve complex cases for personalized treatment decisions.

FUNDING

The study was funded by intramural resources of the Charité - Universitätsmedizin Berlin and the Berlin Institute of Health.

Stage-specific DNA methylation dynamics in mammalian heart development

Cardiac development is a precisely regulated process governed by both genetic and epigenetic mechanisms. Among these, DNA methylation is one mode of epigenetic regulation that plays a crucial role in controlling gene expression at various stages of heart development and maturation. Understanding stage-specific DNA methylation dynamics is critical for unraveling the molecular processes underlying heart development from specification of early progenitors, formation of a primitive and growing heart tube from heart fields, heart morphogenesis, organ function, and response to developmental and physiological signals. This review highlights research that has explored profiles of DNA methylation that are highly dynamic during cardiac development and maturation, exploring stage-specific roles and the key molecular players involved. By exploring recent insights into the changing methylation landscape, we aim to highlight the complex interplay between DNA methylation and stage-specific cardiac gene expression, differentiation, and maturation.

Examining cellular heterogeneity in human DNA methylation studies: Overview and recommendations

Intersample cellular heterogeneity (ISCH) is one of the largest contributors to DNA methylation (DNAme) variability. It is imperative to account for ISCH to accurately interpret analysis results in epigenome-wide association studies. We compiled this primer based on the current literature to guide researchers through the process of estimating and accounting for ISCH in DNA methylation studies. This primer outlines the procedure of bioinformatic ISCH prediction, including using reference-based and reference-free algorithms. It then follows with descriptions of several methods to account for ISCH in downstream analyses, including robust linear regression and principal-component-analysis-based adjustments. Finally, we outlined three methods for estimating differential DNAme signals in a cell-type-specific manner. Throughout the primer, we provided statistical and biological justification for our recommendations, as well as R code examples for ease of implementation.

CNV-mediated dysregulation of the ceRNA network mechanism revealed heterogeneity in diffuse and intestinal gastric cancers

BACKGROUND

Gastric cancer (GC) is a highly heterogeneous tumour with high morbidity. Approximately 95% of GC cases are gastric adenocarcinomas, which are further categorized into two predominant subtypes: diffuse gastric cancer (DGC) and intestinal gastric cancer (IGC). These subtypes exhibit distinct pathophysiological and molecular characteristics, reflecting their unique tumorigenic mechanisms.

METHOD

In this study, we employed a comprehensive approach to identify driver genes associated with DGC and IGC by focusing on copy number variation (CNV) genes within the competing endogenous RNA (ceRNA) network. The influence of driver CNV genes on the molecular, cellular, and clinical differences between DGC and IGC was subsequently analysed. Finally, therapeutic strategies for DGC and IGC were evaluated based on the status and functional pathways of the driver CNV genes.

RESULTS

A total of 17 and 22 driver CNV genes were identified in DGC and IGC, respectively. These genes drive subtype differences through the ceRNA network, resulting in alterations in the tumour microenvironment (TME). Based on these differences, personalized treatment strategies for DGC or IGC could be developed. Immune checkpoint inhibitors may be an effective treatment option in IGC. Additionally, DGC patients with homozygous deletion of PPIF might benefit from adjuvant chemotherapy, whereas those with high-level amplification of MTAP could respond to targeted therapy.

CONCLUSION

Driver CNV genes were identified to reveal the underlying cause of heterogeneity in DGC and IGC. Furthermore, specific driver CNV genes were identified as potential therapeutic targets, facilitating personalized treatment.

Integrated functional genomic analysis identifies regulatory variants underlying a major QTL for disease resistance in European sea bass

BACKGROUND

Viral nervous necrosis (VNN) is an important viral disease threatening global aquaculture sustainability and affecting over 50 farmed and ecologically important fish species. A major QTL for resistance to VNN has been previously detected in European sea bass, but the underlying causal gene(s) and mutation(s) remain unknown. To identify the mechanisms and genetic factors underpinning resistance to VNN in European sea bass, we employed integrative analyses of multiple functional genomics assays in European sea bass.

RESULTS

The estimated heritability of VNN resistance was high (h2 ~ 0.40), and a major QTL explaining up to 38% of the genetic variance of the trait was confirmed on chromosome 3, with individuals with the resistant QTL genotype showing a 90% survivability against a VNN outbreak. Whole-genome resequencing analyses narrowed the location of this QTL to a small region containing 4 copies of interferon alpha inducible protein 27-like 2A (IFI27L2A) genes, and one copy of the interferon alpha inducible protein 27-like 2 (IFI27L2) gene. RNA sequencing revealed a clear association between the QTL genotype and the expression of two of the IFI27L2A genes, and the IFI27L2 gene. Integration with chromatin accessibility and histone modification data pinpointed two SNPs in active regulatory regions of two of these genes (IFI27L2A and IFI27L2), and transcription factor binding site gains for the resistant alleles were predicted. These alleles, particularly the SNP variant CHR3:10,077,301, exhibited higher frequencies (0.55 to 0.77) in Eastern Mediterranean Sea bass populations, which show considerably higher levels of resistance to VNN, as compared to susceptible West Mediterranean and Atlantic populations (0.15-0.25).

CONCLUSIONS

The SNP variant CHR3:10,077,301, through modulation of IFI27L2 and IFI27L2A genes, is likely the causative mutation underlying resistance to VNN in European sea bass. This is one of the first causative mutations discovered for disease resistance traits in fish and paves the way for marker-assisted selection as well as biotechnological approaches to enhance resistance to VNN in European sea bass and other susceptible species.

Repurposing FDA-approved drugs to target G-quadruplexes in breast cancer

Breast cancer, a leading cause of cancer-related mortality in women, is characterized by genomic instability and aberrant gene expression, often influenced by noncanonical nucleic acid structures such as G-quadruplexes (G4s). These structures, commonly found in the promoter regions and 5'-untranslated RNA sequences of several oncogenes, play crucial roles in regulating transcription and translation. Stabilizing these G4 structures offers a promising therapeutic strategy for targeting key oncogenic pathways. In this study, we employed a drug repurposing approach to identify FDA-approved drugs capable of binding and stabilizing G4s in breast cancer-related genes. Using ligand-based virtual screening and biophysical methods, we identified several promising compounds, such as azelastine, belotecan, and irinotecan, as effective G4 binders, with significant antiproliferative effects in breast cancer cell lines. Notably, belotecan and irinotecan exhibited a synergistic mechanism, combining G4 stabilization with their established topoisomerase I inhibition activity to enhance cytotoxicity in cancer cells. Our findings support the therapeutic potential of G4 stabilization in breast cancer, validate drug repurposing as an efficient strategy to identify G4-targeting drugs, and highlight how combining G4 stabilization with other established drug activities may improve anticancer efficacy.

Linking DNA-packing density distribution and TAD boundary locations

DNA is heterogeneously packaged into chromatin, which is further organized into topologically associating domains (TADs) with sharp boundaries. These boundary locations are critical for genome regulation. Here, we explore how the distribution of DNA-packing density across chromatin affects the TAD boundary locations. We develop a polymer-physics-based model that utilizes DNA accessibility data to parameterize DNA-packing density along chromosomes, treating them as heteropolymers, and simulates the stochastic folding of these heteropolymers within a nucleus to yield a conformation ensemble. Such an ensemble reproduces a subset (over 60%) of TAD boundaries across the human genome, as confirmed by Hi-C data. Additionally, it reproduces the spatial distance matrices of 2-Mb genomic regions provided by FISH experiments. Furthermore, our model suggests that utilizing DNA accessibility data alone as input is sufficient to predict the emergence and disappearance of key TADs during early T cell differentiation. We show that stochastic folding of heteropolymers in a confined space can replicate both the prevalence of chromatin domain structures and the cell-to-cell variation in domain boundary positions observed in single-cell experiments. Furthermore, regions of lower DNA-packing density preferentially form domain boundaries, and this preference drives the emergence of TAD boundaries observed in ensemble-averaged Hi-C maps. The enrichment of TAD boundaries at CTCF binding sites can be attributed to the influence of CTCF binding on local DNA-packing density in our model. Collectively, our findings establish a strong link between TAD boundaries and regions of lower DNA-packing density, providing insights into the mechanisms underlying TAD formation.

Surface-Sensitive Waveguide Imaging for In Situ Analysis of Membrane Protein Binding Kinetics

Ligand binding to membrane proteins initiates numerous therapeutic processes. Surface plasmon resonance (SPR), a popular method for analyzing molecular interactions, has emerged as a promising tool for in situ determination of membrane protein binding kinetics owing to its label-free detection, high surface sensitivity, and resistance to intracellular interference. However, the excitation of SPR relies on noble metal films, typically gold, which are biologically incompatible and can cause fluorescence quenching. Here we present a surface-sensitive waveguide imaging technique that retains the advantages of SPR and can be easily integrated into standard SPR devices by depositing additional dielectric layers onto SPR sensor chips using conventional vacuum evaporation. This novel sensor provides a silica surface, a well-known biologically compatible surface, for cell attachment and produces a sharper resonance curve and a stronger surface electric field than SPR, leading to improved measurement precision. After incorporating amplitude modulation, this approach increases measurement precision by approximately eight times compared to traditional SPR with the same optical setup. This high-precision method enables in situ single-cell analysis, revealing cell-to-cell heterogeneity that provides fuel for drug resistance. We believe this technique provides a streamlined strategy to enhance SPR for expanding their applications in biochemical research and drug screening.

Epigene functional diversity: isoform usage, disordered domain content, and variable binding partners

BACKGROUND

Epigenes are defined as proteins that perform post-translational modification of histones or DNA, reading of post-translational modifications, form complexes with epigenetic factors or changing the general structure of chromatin. This specialized group of proteins is responsible for controlling the organization of genomic DNA in a cell-type specific fashion, controlling normal development in a spatial and temporal fashion. Moreover, mutations in epigenes have been implicated as causal in germline pediatric disorders and as driver mutations in cancer. Despite their importance to human disease, to date, there has not been a systematic analysis of the sources of functional diversity for epigenes at large. Epigenes' unique functions that require the assembly of pools within the nucleus suggest that their structure and amino acid composition would have been enriched for features that enable efficient assembly of chromatin and DNA for transcription, splicing, and post-translational modifications.

RESULTS

In this study, we assess the functional diversity stemming from gene structure, isoforms, protein domains, and multiprotein complex formation that drive the functions of established epigenes. We found that there are specific structural features that enable epigenes to perform their variable roles depending on the cellular and environmental context. First, epigenes are significantly larger and have more exons compared with non-epigenes which contributes to increased isoform diversity. Second epigenes participate in more multimeric complexes than non-epigenes. Thirdly, given their proposed importance in membraneless organelles, we show epigenes are enriched for substantially larger intrinsically disordered regions (IDRs). Additionally, we assessed the specificity of their expression profiles and showed epigenes are more ubiquitously expressed consistent with their enrichment in pediatric syndromes with intellectual disability, multiorgan dysfunction, and developmental delay. Finally, in the L1000 dataset, we identify drugs that can potentially be used to modulate expression of these genes.

CONCLUSIONS

Here we identify significant differences in isoform usage, disordered domain content, and variable binding partners between human epigenes and non-epigenes using various functional genomics datasets from Ensembl, ENCODE, GTEx, HPO, LINCS L1000, and BrainSpan. Our results contribute new knowledge to the growing field focused on developing targeted therapies for diseases caused by epigene mutations, such as chromatinopathies and cancers.

Leveraging epigenetic alterations in pancreatic ductal adenocarcinoma for clinical applications

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by late detection and poor prognosis. Recent research highlights the pivotal role of epigenetic alterations in driving PDAC development and progression. These changes, in conjunction with genetic mutations, contribute to the intricate molecular landscape of the disease. Specific modifications in DNA methylation, histone marks, and non-coding RNAs are emerging as robust predictors of disease progression and patient survival, offering the potential for more precise prognostic tools compared to conventional clinical staging. Moreover, the detection of epigenetic alterations in blood and other non-invasive samples holds promise for earlier diagnosis and improved management of PDAC. This review comprehensively summarises current epigenetic research in PDAC and identifies persisting challenges. These include the complex nature of epigenetic profiles, tumour heterogeneity, limited access to early-stage samples, and the need for highly sensitive liquid biopsy technologies. Addressing these challenges requires the standardisation of methodologies, integration of multi-omics data, and leveraging advanced computational tools such as machine learning and artificial intelligence. While resource-intensive, these efforts are essential for unravelling the functional consequences of epigenetic changes and translating this knowledge into clinical applications. By overcoming these hurdles, epigenetic research has the potential to revolutionise the management of PDAC and improve patient outcomes.

The yeast genome is globally accessible in living cells

Eukaryotic genomes are packaged into chromatin, which is composed of condensed filaments of regularly spaced nucleosomes, resembling beads on a string. The nucleosome contains ~147 bp of DNA wrapped almost twice around a central core histone octamer. The packaging of DNA into chromatin represents a challenge to transcription factors and other proteins requiring access to their binding sites. Consequently, control of DNA accessibility is thought to play a key role in gene regulation. Here we measure DNA accessibility genome wide in living budding yeast cells by inducible expression of DNA methyltransferases. We find that the genome is globally accessible in living cells, unlike in isolated nuclei, where DNA accessibility is severely restricted. Gene bodies are methylated at only slightly slower rates than promoters, indicating that yeast chromatin is highly dynamic in vivo. In contrast, silenced loci and centromeres are strongly protected. Global shifts in nucleosome positions occur in cells as they are depleted of ATP-dependent chromatin remodelers, suggesting that nucleosome dynamics result from competition among these enzymes. We conclude that chromatin is in a state of continuous flux in living cells, but static in nuclei, suggesting that DNA packaging in yeast is not generally repressive.

Cell-free epigenomes enhanced fragmentomics-based model for early detection of lung cancer

BACKGROUND

Lung cancer is a leading cause of cancer mortality, highlighting the need for innovative non-invasive early detection methods. Although cell-free DNA (cfDNA) analysis shows promise, its sensitivity in early-stage lung cancer patients remains a challenge. This study aimed to integrate insights from epigenetic modifications and fragmentomic features of cfDNA using machine learning to develop a more accurate lung cancer detection model.

METHODS

To address this issue, a multi-centre prospective cohort study was conducted, with participants harbouring suspicious malignant lung nodules and healthy volunteers recruited from two clinical centres. Plasma cfDNA was analysed for its epigenetic and fragmentomic profiles using chromatin immunoprecipitation sequencing, reduced representation bisulphite sequencing and low-pass whole-genome sequencing. Machine learning algorithms were then employed to integrate the multi-omics data, aiding in the development of a precise lung cancer detection model.

RESULTS

Cancer-related changes in cfDNA fragmentomics were significantly enriched in specific genes marked by cell-free epigenomes. A total of 609 genes were identified, and the corresponding cfDNA fragmentomic features were utilised to construct the ensemble model. This model achieved a sensitivity of 90.4% and a specificity of 83.1%, with an AUC of 0.94 in the independent validation set. Notably, the model demonstrated exceptional sensitivity for stage I lung cancer cases, achieving 95.1%. It also showed remarkable performance in detecting minimally invasive adenocarcinoma, with a sensitivity of 96.2%, highlighting its potential for early detection in clinical settings.

CONCLUSIONS

With feature selection guided by multiple epigenetic sequencing approaches, the cfDNA fragmentomics-based machine learning model demonstrated outstanding performance in the independent validation cohort. These findings highlight its potential as an effective non-invasive strategy for the early detection of lung cancer.

KEYPOINTS

Our study elucidated the regulatory relationships between epigenetic modifications and their effects on fragmentomic features. Identifying epigenetically regulated genes provided a critical foundation for developing the cfDNA fragmentomics-based machine learning model. The model demonstrated exceptional clinical performance, highlighting its substantial potential for translational application in clinical practice.

Heterogeneity in Cancer

Cancer heterogeneity is a major challenge in oncology, complicating diagnosis, prognostication, and treatment. The clinical heterogeneity of cancer, which leads to differential treatment outcomes between patients with histopathologically similar cancers, is attributable to molecular diversity manifesting through genetic, epigenetic, transcriptomic, microenvironmental, and host biology differences. Heterogeneity is observed between patients, individual metastases, and within individual lesions. This review discusses clinical implications of heterogeneity, emphasizing need for personalized approaches to overcome challenges posed by cancer's diverse presentations. Understanding of emerging molecular diagnostic and analytical techniques can provide a view into the multidimensional complexity of cancer heterogeneity. With over 90% of cancer-related deaths associated with metastasis, we additionally explore the role heterogeneity plays in treatment resistance and recurrence of metastatic lesions. Molecular insights from next-generation sequencing, single-cell transcriptomics, liquid biopsy technology, and artificial intelligence will facilitate the development of combination therapy regimens that can potentially induce lasting and even curative treatment outcomes.

Modeling non-genetic adaptation in tumor cells

Treatment resistance poses a significant challenge in the care of cancer patients. Hirsch et al. applied computational and genomic approaches, examining gene expression dynamics from a mouse model of melanoma at single-cell resolution to reveal that semi-heritable non-genetic alterations in tumor cell populations confer adaptive resistance to treatment.

Tissue-specific modulation of CRISPR activity by miRNA-sensing guide RNAs

Nucleic acid nanostructures offer unique opportunities for biomedical applications due to their sequence-programmable structures and functions, which enable the design of complex responses to molecular cues. Control of the biological activity of therapeutic cargoes based on endogenous molecular signatures holds the potential to overcome major hurdles in translational research: cell specificity and off-target effects. Endogenous microRNAs (miRNAs) can be used to profile cell type and cell state, and are ideal inputs for RNA nanodevices. Here, we present CRISPR MiRAGE (miRNA-activated genome editing), a tool comprising a dynamic single-guide RNA that senses miRNA complexed with Argonaute proteins and controls downstream CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) activity based on the detected miRNA signature. We study the operation of the miRNA-sensing single-guide RNA and attain muscle-specific activation of gene editing through CRISPR MiRAGE in models of Duchenne muscular dystrophy. By enabling RNA-controlled gene editing activity, this technology creates opportunities to advance tissue-specific CRISPR treatments for human diseases.

Enhancer Dynamics and Spatial Organization Drive Anatomically Restricted Cellular States in the Human Spinal Cord

Here, we report the spatial organization of RNA transcription and associated enhancer dynamics in the human spinal cord at single-cell and single-molecule resolution. We expand traditional multiomic measurements to reveal epigenetically poised and bivalent active transcriptional enhancer states that define cell type specification. Simultaneous detection of chromatin accessibility and histone modifications in spinal cord nuclei reveals previously unobserved cell-type specific cryptic enhancer activity, in which transcriptional activation is uncoupled from chromatin accessibility. Such cryptic enhancers define both stable cell type identity and transitions between cells undergoing differentiation. We also define glial cell gene regulatory networks that reorganize along the rostrocaudal axis, revealing anatomical differences in gene regulation. Finally, we identify the spatial organization of cells into distinct cellular organizations and address the functional significance of this observation in the context of paracrine signaling. We conclude that cellular diversity is best captured through the lens of enhancer state and intercellular interactions that drive transitions in cellular state. This study provides fundamental insights into the cellular organization of the healthy human spinal cord.

Adenosinergic Signalling in Cervical Cancer Microenvironment

Despite the emergence of the first human papillomavirus vaccine, the incidence of cervical cancer is still responsible for more than 350,000 deaths yearly. Over the past decade, ecto-5'-nucleotidase (CD73/5'-NT) and extracellular adenosine (ADO) signalling has been the subject of many investigations to target cancer progression. In general, the adenosinergic axis has been linked to tumourigenic effects. However, CD73 can play contradictory effects, probably dependent on the tumour type, tumour microenvironment and tumour stage, thus being in some circumstances, inversely related to tumour progression. We herein reviewed the pathophysiological function of CD73 in cervical cancer and performed in silico analysis of the main components of the adenosinergic signalling in human tissues of cervical cancer compared to non-tumour cervix tissue. Our data showed that the NT5E gene, that encoded CD73, is hypermethylated, leading to a decreased CD73 expression in cervical cancer cells compared to normal cells. Consequently, the high availability of ADO cytoplasmatic/extracellular leads to its conversion to AMP by ADK, culminating in global hypermethylation. Therefore, epigenetic modulation may reveal a new role for CD73 in cervical cancer.

Single-cell Technology in Stem Cell Research

Single-cell technology (SCT), which enables the examination of the fundamental units comprising biological organs, tissues, and cells, has emerged as a powerful tool, particularly in the field of biology, with a profound impact on stem cell research. This innovative technology opens new pathways for acquiring cell-specific data and gaining insights into the molecular pathways governing organ function and biology. SCT is not only frequently used to explore rare and diverse cell types, including stem cells, but it also unveils the intricacies of cellular diversity and dynamics. This perspective, crucial for advancing stem cell research, facilitates non-invasive analyses of molecular dynamics and cellular functions over time. Despite numerous investigations into potential stem cell therapies for genetic disorders, degenerative conditions, and severe injuries, the number of approved stem cell-based treatments remains limited. This limitation is attributed to the various heterogeneities present among stem cell sources, hindering their widespread clinical utilization. Furthermore, stem cell research is intimately connected with cutting-edge technologies, such as microfluidic organoids, CRISPR technology, and cell/tissue engineering. Each strategy developed to overcome the constraints of stem cell research has the potential to significantly impact advanced stem cell therapies. Drawing on the advantages and progress achieved through SCT-based approaches, this study aims to provide an overview of the advancements and concepts associated with the utilization of SCT in stem cell research and its related fields.

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.

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.

Divergent Contribution of Cytoplasmic Actins to Nuclear Structure of Lung Cancer Cells

A growing body of evidence suggests that actin plays a role in nuclear architecture, genome organisation, and regulation. Our study of human lung adenocarcinoma cells demonstrates that the equilibrium between actin isoforms affects the composition of the nuclear lamina, which in turn influences nuclear stiffness and cellular behaviour. The downregulation of β-actin resulted in an increase in nuclear area, accompanied by a decrease in A-type lamins and an enhancement in lamin B2. In contrast, the suppression of γ-actin led to upregulation of the lamin A/B ratio through an increase in A-type lamins. Histone H3 post-translational modifications display distinct patterns in response to decreased actin isoform expression. The level of dimethylated H3K9me2 declined while acetylated H3K9ac increased in β-actin-depleted A549 cells. In contrast, the inhibition of γ-actin expression resulted in a reduction in H3K9ac. Based on our observations, we propose that β-actin plays a role in chromatin compaction and deactivation, and is involved in the elevation of nuclear stiffness through the control of the lamins ratio. The non-muscle γ-actin is presumably responsible for chromatin decondensation and activation. The identification of novel functions for actin isoforms offers insights into the mechanisms through which they influence cell fate during development and cancer progression.

Chromatin accessibility: biological functions, molecular mechanisms and therapeutic application

The dynamic regulation of chromatin accessibility is one of the prominent characteristics of eukaryotic genome. The inaccessible regions are mainly located in heterochromatin, which is multilevel compressed and access restricted. The remaining accessible loci are generally located in the euchromatin, which have less nucleosome occupancy and higher regulatory activity. The opening of chromatin is the most important prerequisite for DNA transcription, replication, and damage repair, which is regulated by genetic, epigenetic, environmental, and other factors, playing a vital role in multiple biological progresses. Currently, based on the susceptibility difference of occupied or free DNA to enzymatic cleavage, solubility, methylation, and transposition, there are many methods to detect chromatin accessibility both in bulk and single-cell level. Through combining with high-throughput sequencing, the genome-wide chromatin accessibility landscape of many tissues and cells types also have been constructed. The chromatin accessibility feature is distinct in different tissues and biological states. Research on the regulation network of chromatin accessibility is crucial for uncovering the secret of various biological processes. In this review, we comprehensively introduced the major functions and mechanisms of chromatin accessibility variation in different physiological and pathological processes, meanwhile, the targeted therapies based on chromatin dynamics regulation are also summarized.

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.

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.

A versatile attention-based neural network for chemical perturbation analysis and its potential to aid surgical treatment: an experimental study

Deep learning models have emerged as rapid, accurate, and effective approaches for clinical decisions. Through a combination of drug screening and deep learning models, drugs that may benefit patients before and after surgery can be discovered to reduce the risk of complications or speed recovery. However, most existing drug prediction methods have high data requirements and lack interpretability, which has a limited role in adjuvant surgical treatment. To address these limitations, the authors propose the attention-based convolution transpositional interfusion network (ACTIN) for flexible and efficient drug discovery. ACTIN leverages the graph convolution and the transformer mechanism, utilizing drug and transcriptome data to assess the impact of chemical pharmacophores containing certain elements on gene expression. Remarkably, just with only 393 training instances, only one-tenth of the other models, ACTIN achieves state-of-the-art performance, demonstrating its effectiveness even with limited data. By incorporating chemical element embedding disparity and attention mechanism-based parameter analysis, it identifies the possible pharmacophore containing certain elements that could interfere with specific cell lines, which is particularly valuable for screening useful pharmacophores for new drugs tailored to adjuvant surgical treatment. To validate its reliability, the authors conducted comprehensive examinations by utilizing transcriptome data from the lung tissue of fatal COVID-19 patients as additional input for ACTIN, the authors generated novel lead chemicals that align with clinical evidence. In summary, ACTIN offers insights into the perturbation biases of elements within pharmacophore on gene expression, which holds the potential for guiding the development of new drugs that benefit surgical treatment.

Exploring Framework Nucleic Acids: A Perspective on Their Cellular Applications

Cells are fundamental units of life. The coordination of cellular functions and behaviors relies on a cascade of molecular networks. Technologies that enable exploration and manipulation of specific molecular events in living cells with high spatiotemporal precision would be critical for pathological study, disease diagnosis, and treatment. Framework nucleic acids (FNAs) represent a novel class of nucleic acid materials characterized by their monodisperse and rigid nanostructure. Leveraging their exceptional programmability, convenient modification property, and predictable atomic-level architecture, FNAs have attracted significant attention in diverse cellular applications such as cell recognition, imaging, manipulation, and therapeutic interventions. In this perspective, we will discuss the utilization of FNAs in living cell systems while critically assessing the opportunities and challenges presented in this burgeoning field.

M. Advances in nanomaterials for precision drug delivery: Insights into pharmacokinetics and toxicity

By integrating the cutting-edge principles of nanotechnology with medical science, nanomedicine offers unprecedented opportunities to develop advanced drug delivery systems that surpass the limitations of conventional therapies. These nanoscale systems are designed to enhance treatments' efficacy, specificity, and safety by optimizing pharmacokinetics and biodistribution, ensuring that therapeutic agents reach their intended targets with minimal side effects. The article provides an in-depth analysis of nanomaterials' pivotal role in overcoming challenges related to drug delivery, including the ability to bypass biological barriers, improve bioavailability, and achieve controlled release of drugs. Despite these promising advancements, the transition of nanomedicine from research to clinical practice faces significant hurdles. The review highlights key obstacles such as patient heterogeneity, physiological variability, and the complex ADME (Absorption, Distribution, Metabolism, Excretion) profiles of nanocarriers, which complicate treatment predictability and effectiveness. Moreover, the article addresses the issues of limited tissue penetration, variable patient responses, and the need for standardized protocols in nanomaterial characterization, all of which hinder the widespread clinical adoption of nanomedicine. Nevertheless, the potential of nanomedicine in revolutionizing personalized cancer therapy remains immense. The article advocates for increased translational research and international collaboration to overcome these challenges, paving the way for fully realizing nanomedicine's capabilities in precision oncology and beyond.

Metabolomics-driven approaches for identifying therapeutic targets in drug discovery

Identification of therapeutic targets can directly elucidate the mechanism and effect of drug therapy, which is a central step in drug development. The disconnect between protein targets and phenotypes under complex mechanisms hampers comprehensive target understanding. Metabolomics, as a systems biology tool that captures phenotypic changes induced by exogenous compounds, has emerged as a valuable approach for target identification. A comprehensive overview was provided in this review to illustrate the principles and advantages of metabolomics, delving into the application of metabolomics in target identification. This review outlines various metabolomics-based methods, such as dose-response metabolomics, stable isotope-resolved metabolomics, and multiomics, which identify key enzymes and metabolic pathways affected by exogenous substances through dose-dependent metabolite-drug interactions. Emerging techniques, including single-cell metabolomics, artificial intelligence, and mass spectrometry imaging, are also explored for their potential to enhance target discovery. The review emphasizes metabolomics' critical role in advancing our understanding of disease mechanisms and accelerating targeted drug development, while acknowledging current challenges in the field.

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.