Mitochondrial single-cell ATAC-seq for high-throughput multi-omic detection of mitochondrial genotypes and chromatin accessibility

Single-cell lineage tracing techniques in hematology: unraveling the cellular narrative

Lineage tracing is a valuable technique that has greatly facilitated the exploration of cell origins and behavior. With the continuous development of single-cell sequencing technology, lineage tracing technology based on the single-cell level has become an important method to study biological development. Single-cell Lineage tracing technology plays an important role in the hematological system. It can help to answer many important questions, such as the heterogeneity of hematopoietic stem cell function and structure, and the heterogeneity of malignant tumor cells in the hematological system. Many studies have been conducted to explore the field of hematology by applying this technology. This review focuses on the superiority of the emerging single-cell lineage tracing technologies of Integration barcodes, CRISPR barcoding, and base editors, and summarizes their applications in the hematology system. These studies have suggested the vast potential in unraveling complex cellular behaviors and lineage dynamics in both normal and pathological contexts.

Reducing batch effects in single cell chromatin accessibility measurements by pooled transposition with MULTI-ATAC

Large-scale scATAC-seq experiments are challenging because of their costs, lengthy protocols, and confounding batch effects. Several sample multiplexing technologies aim to address these challenges, but do not remove batch effects introduced when performing transposition reactions in parallel. We demonstrate that sample-to-sample variability in nuclei-to-Tn5 ratios is a major cause of batch effects and develop MULTI-ATAC, a multiplexing method that pools samples prior to transposition, as a solution. MULTI-ATAC provides high accuracy in sample classification and doublet detection while eliminating batch effects associated with variable nucleus-to-Tn5 ratio. We illustrate the power of MULTI-ATAC by performing a 96-plex multiomic drug assay targeting epigenetic remodelers in a model of primary immune cell activation, uncovering tens of thousands of drug-responsive chromatin regions, cell-type specific effects, and potent differences between matched inhibitors and degraders. MULTI-ATAC therefore enables batch-free and scalable scATAC-seq workflows, providing deeper insights into complex biological processes and potential therapeutic targets.

A pathogenic subpopulation of human glioma associated macrophages linked to glioma progression

Malignant gliomas follow two distinct natural histories: de novo high grade tumors such as glioblastoma, or lower grade tumors with a propensity to transform into high grade disease. Despite differences in tumor genotype, both entities converge on a common histologically aggressive phenotype, and the basis for this progression is unknown. Glioma associated macrophages (GAM) have been implicated in this process, however GAMs are ontologically and transcriptionally diverse, rendering isolation of pathogenic subpopulations challenging. Since macrophage contextual gene programs are orchestrated by transcription factors acting on cis -acting promoters and enhancers in gene regulatory networks (GRN), we hypothesized that functional populations of GAMs can be resolved through GRN inference. Here we show via parallel single cell RNA and ATAC sequencing that a subpopulation of human GAMs can be defined by a GRN centered around the Activator Protein-1 transcription factor FOSL2 preferentially enriched in high grade tumors. Using this GRN we nominate ANXA1 and HMOX1 as surrogate cell surface markers for activation, thus permitting prospective isolation and functional validation in human GAMs. These cells, termed malignancy associated GAMs (mGAMs) are pro-invasive, pro-angiogenic, pro-proliferative, possess intact antigen presentation but skew T-cells towards a CD4+FOXP3+ phenotype under hypoxia. Ontologically, mGAMs share somatic mitochondrial mutations with peripheral blood monocytes, and their presence correlates with high grade disease irrespective of underlying tumor mutation status. Furthermore, spatio-temporally mGAMs occupy distinct metabolic niches; mGAMs directly induce proliferation and mesenchymal transition of low grade glioma cells and accelerate tumor growth in vivo upon co-culture. Finally mGAMs are preferentially enriched in patients with newly transformed regions in human gliomas, supporting the view that mGAMs play a pivotal role in glioma progression and may represent a plausible therapeutic target in human high-grade glioma.

Single-cell atlas reveals multi-faced responses of losartan on tubular mitochondria in diabetic kidney disease

BACKGROUND AND OBJECTIVE

Mitochondria are crucial to the function of renal tubular cells, and their dynamic perturbation in many aspects is an important mechanism of diabetic kidney disease (DKD). Single-nucleus RNA sequencing (snRNA-seq) technology is a high-throughput sequencing analysis technique for RNA at the level of a single cell nucleus. Here, our DKD mouse kidney single-cell RNA sequencing conveys a more comprehensive mitochondrial profile, which helps us further understand the therapeutic response of this unique organelle family to drugs.

METHODS

After high fat diet (HFD), mice were intraperitoneally injected with streptozotocin (STZ) to induce DKD, and then divided into three subsets: CON (healthy) subset, DKD (vehicle) subset, and LST (losartan; 25 mg/kg/day) subset. Divide HK-2 cell into LG (low glucose; 5 mM) and HG (high glucose; 30 mM) and HG + LST (losartan; 1 µ M) subsets. snRNA-seq was performed on the renal tissues of LST and DKD subset mice. To reveal the effects of losartan on gene function and pathway changes in renal tubular mitochondria, Gene Ontology (GO) enrichment analysis and GSEA/GSVA scoring were performed to analyze the specific response of proximal tubular (PT) cell mitochondria to losartan treatment, including key events in mitochondrial homeostasis such as mitochondrial morphology, dynamics, mitophagy, autophagic flux, mitochondrial respiratory chain, apoptosis, and ROS generation. Preliminary validation through in vitro and in vivo experiments, including observation of changes in mitochondrial morphology and dynamics using probes such as Mitotracker Red, and evaluation of the effect of losartan on key events of mitochondrial homeostasis perturbation using electron microscopy, laser confocal microscopy, immunofluorescence, and Western blotting. Detection of autophagic flux in cells by transfecting Ad-mCherry-GFP-LC3B dual fluorescence labeled adenovirus. Various fluorescent probes and energy detector are used to detect mitochondrial apoptosis, ROS, and respiration of mitochondrion.

RESULTS

Through the single-cell atlas of DKD mouse kidneys, it was found that losartan treatment significantly increased the percentage of PT cells. Gene Ontology (GO) enrichment analysis of differentially expressed genes showed enrichment of autophagy of mitochondrion pathway. Further GSEA analysis and GSVA scoring revealed that mitophagy and other key mitochondrial perturbation events, such as ROS production, apoptosis, membrane potential, adenosine triphosphate (ATP) synthesis, and mitochondrial dynamics, were involved in the protective mechanism of losartan on PT cells, thereby improving mitochondrial homeostasis. Consistent results were also obtained in mice and cellular experiments. In addition, we highlighted a specific renal tubular subpopulation with mitophagy phenotype found in single-cell data, and preliminarily validated it with co-localization and increased expression of Pink1 and Gclc in kidney specimens of DKD patients treated with losartan.

CONCLUSIONS

Our research suggests that scRNA-seq can reflect the multifaceted mitochondrial landscape of DKD renal tubular cells after drug treatment, and these findings may provide new targets for DKD therapy at the organelle level.

Advances and applications in single-cell and spatial genomics

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

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.

Applying single-cell and single-nucleus genomics to studies of cellular heterogeneity and cell fate transitions in the nervous system

Single-cell and single-nucleus genomic approaches can provide unbiased and multimodal insights. Here, we discuss what constitutes a molecular cell atlas and how to leverage single-cell omics data to generate hypotheses and gain insights into cell transitions in development and disease of the nervous system. We share points of reflection on what to consider during study design and implementation as well as limitations and pitfalls.

Transfer of mitochondrial DNA into the nuclear genome during induced DNA breaks

Mitochondria serve as the cellular powerhouse, and their distinct DNA makes them a prospective target for gene editing to treat genetic disorders. However, the impact of genome editing on mitochondrial DNA (mtDNA) stability remains a mystery. Our study reveals previously unknown risks of genome editing that both nuclear and mitochondrial editing cause discernible transfer of mitochondrial DNA segments into the nuclear genome in various cell types including human cell lines, primary T cells, and mouse embryos. Furthermore, drug-induced mitochondrial stresses and mtDNA breaks exacerbate this transfer of mtDNA into the nuclear genome. Notably, we observe that mitochondrial editors, including mitoTALEN and recently developed base editor DdCBE, can also enhance crosstalk between mtDNA and the nuclear genome. Moreover, we provide a practical solution by co-expressing TREX1 or TREX2 exonucleases during DdCBE editing. These findings imply genome instability of mitochondria during induced DNA breaks and explain the origins of mitochondrial-nuclear DNA segments.

Tracking Rare Single Donor and Recipient Immune and Leukemia Cells after Allogeneic Hematopoietic Cell Transplantation Using Mitochondrial DNA Mutations

Combined tracking of clonal evolution and chimeric cell phenotypes could enable detection of the key cellular populations associated with response following therapy, including after allogeneic hematopoietic stem cell transplantation (HSCT). We demonstrate that mitochondrial DNA (mtDNA) mutations coevolve with somatic nuclear DNA mutations at relapse post-HSCT and provide a sensitive means to monitor these cellular populations. Furthermore, detection of mtDNA mutations via single-cell assay for transposase-accessible chromatin with select antigen profiling by sequencing (ASAP-seq) simultaneously determines not only donor and recipient cells but also their phenotype at frequencies of 0.1% to 1%. Finally, integration of mtDNA mutations, surface markers, and chromatin accessibility profiles enables the phenotypic resolution of leukemic populations from normal immune cells, thereby providing fresh insights into residual donor-derived engraftment and short-term clonal evolution following therapy for post-transplant leukemia relapse. As throughput evolves, we envision future development of single-cell sequencing-based post-transplant monitoring as a powerful approach for guiding clinical decision-making. Significance: mtDNA mutations enable single-cell tracking of leukemic clonal evolution and donor-recipient origin following allogeneic HSCT. This provides unprecedented insight into chimeric cellular phenotypes of early immune reconstitution, incipient relapse, and quality of donor engraftment with immediate translational potential for future clinical post-transplant monitoring and decision-making.

DMF-Bimol: Counting mRNA and Protein Molecules in Single Cells with Digital Microfluidics

Analyzing single-cell protein and mRNA levels yields invaluable insights into cellular functions and the intricacies of biologically heterogeneous systems. Current joint mRNAs and protein analysis methodologies suffer from relative quantification, low sensitivity, possible background interference, and tedious manual manipulation. Therefore, we propose DMF-Bimol that leverages addressable digital microfluidics to automate digital counting of single-cell mRNA and protein based on proximity ligation assay (PLA) and one-step RT-droplet digital PCR (RT-ddPCR). Through an engineered hydrophilic-hydrophobic interface, DMF-Bimol enables efficient single-cell isolation and lossless protein and nucleic acid processing. The closed droplet reaction system enhances the protein concentration and isolates exogenous contaminants, thereby dramatically improving the efficiency of the PLA reaction. The limit of detection of this approach achieves 3313 protein copies, marking a significant 17-fold enhancement in sensitivity over traditional benchtop PLA. This heightened sensitivity also uncovers a lower correlation between mRNA and protein levels in individual cells (Spearman r = 0.255) than bulk results, reflecting the complex relationship in heterogeneous cells. Using DMF-Bimol, we observed a significant upsurge of CD147 protein in CD138+ myeloma cells but consistent levels of CD147 mRNAs compared with normal leukocytes. This discovery indicates a possible consequence of CD147 oncogenic activation that tends to harness protein translation to bolster tumor cell survival and enhance invasiveness, highlighting the potential of DMF-Bimol in unveiling intricate dynamics in translation processes at the single-cell level.

Engineering mtDNA Deletions by Reconstituting End-Joining in Human Mitochondria

Recent breakthroughs in the genetic manipulation of mitochondrial DNA (mtDNA) have enabled the precise introduction of base substitutions and the effective removal of genomes carrying harmful mutations. However, the reconstitution of mtDNA deletions responsible for severe mitochondrial myopathies and age-related diseases has not yet been achieved in human cells. Here, we developed a method to engineer specific mtDNA deletions in human cells by co-expressing end-joining (EJ) machinery and targeted endonucleases. As a proof-of-concept, we used mito-EJ and mito-ScaI to generate a panel of clonal cell lines harboring a ∼3.5 kb mtDNA deletion with the full spectrum of heteroplasmy. Investigating these isogenic cells revealed a critical threshold of ∼75% deleted genomes, beyond which cells exhibited depletion of OXPHOS proteins, severe metabolic disruption, and impaired growth in galactose-containing media. Single-cell multiomic analysis revealed two distinct patterns of nuclear gene deregulation in response to mtDNA deletion accumulation; one triggered at the deletion threshold and another progressively responding to increasing heteroplasmy. In summary, the co-expression of mito-EJ and programable nucleases provides a powerful tool to model disease-associated mtDNA deletions in different cell types. Establishing a panel of cell lines with a large-scale deletion at varying levels of heteroplasmy is a valuable resource for understanding the impact of mtDNA deletions on diseases and guiding the development of potential therapeutic strategies.

Highlights

Combining prokaryotic end-joining with targeted endonucleases generates specific mtDNA deletions in human cellsEngineering a panel of cell lines with a large-scale deletion that spans the full spectrum of heteroplasmy75% heteroplasmy is the threshold that triggers mitochondrial and cellular dysfunctionTwo distinct nuclear transcriptional programs in response to mtDNA deletions: threshold-triggered and heteroplasmy-sensing.

Mitochondrial genetic variations in leukemia: a comprehensive overview

Leukemias are a group of heterogeneous hematological malignancies driven by diverse genetic variations, and the advent of genomic sequencing technologies facilitates the investigation of genetic abnormalities in leukemia. However, these sequencing-based studies mainly focus on nuclear DNAs. Increasing evidence indicates that mitochondrial dysfunction is an important mechanism of leukemia pathogenesis, which is closely related to the mitochondrial genome variations. Here, we provide an overview of current research progress concerning mitochondrial genetic variations in leukemia, encompassing gene mutations and copy number variations. We also summarize currently accessible mitochondrial DNA (mtDNA) sequencing methods. Notably, somatic mtDNA mutations may serve as natural genetic barcodes for lineage tracing and longitudinal assessment of clonal dynamics. Collectively, these findings enhance our understanding of leukemia pathogenesis and foster the identification of novel therapeutic targets and interventions.

Mechanisms and therapeutic target of anti-tumour treatment-related Ferroptosis: How to improve cancer therapy?

Recently, increased attention has been focused on the regulatory mechanism and potential clinical application of ferroptosis in cancer cells, especially therapy-related ferroptosis. However, the mechanism of treatment-related ferroptosis and the application prospects and strategies for future treatment still require further clarification. This review highlights the molecular relationships between different clinical antitumour drugs, including commonly used chemotherapy drugs, radiation therapy and vitamins, and ferroptosis. This review also proposes strategies for future treatments that involve ferroptosis, with an aim to develop a new strategy for the transformative potential of the emerging field of ferroptosis to improve cancer therapy.

Unveiling aging dynamics in the hematopoietic system insights from single-cell technologies

As the demographic structure shifts towards an aging society, strategies aimed at slowing down or reversing the aging process become increasingly essential. Aging is a major predisposing factor for many chronic diseases in humans. The hematopoietic system, comprising blood cells and their associated bone marrow microenvironment, intricately participates in hematopoiesis, coagulation, immune regulation and other physiological phenomena. The aging process triggers various alterations within the hematopoietic system, serving as a spectrum of risk factors for hematopoietic disorders, including clonal hematopoiesis, immune senescence, myeloproliferative neoplasms and leukemia. The emerging single-cell technologies provide novel insights into age-related changes in the hematopoietic system. In this review, we summarize recent studies dissecting hematopoietic system aging using single-cell technologies. We discuss cellular changes occurring during aging in the hematopoietic system at the levels of the genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial multi-omics. Finally, we contemplate the future prospects of single-cell technologies, emphasizing the impact they may bring to the field of hematopoietic system aging research.

DOGMA-seq and multimodal, single-cell analysis in acute myeloid leukemia

Acute myeloid leukemia (AML) is a complex cancer, yet advances in recent years from integrated genomics methods have helped improve diagnosis, treatment, and means of patient stratification. A recent example of a powerful, multimodal method is DOGMA-seq, which can measure chromatin accessibility, gene expression, and cell-surface protein levels from the same individual cell simultaneously. Previous bimodal single-cell techniques, such as CITE-seq (Cellular indexing of transcriptomes and epitopes), have only permitted the transcriptome and cell-surface protein expression measurement. DOGMA-seq, however, builds on this foundation and has implications for examining epigenomic, transcriptomic, and proteomic interactions between various cell types. This technique has the potential to be particularly useful in the study of cancers such as AML. This is because the cellular mechanisms that drive AML are rather heterogeneous and require a more complete understanding of the interplay between the genetic mutations, disruptions in RNA transcription and translation, and surface protein expression that cause these cancers to develop and evolve. This technique will hopefully contribute to a more clear and complete understanding of the growth and progression of complex cancers.

Mitochondrial DNA mosaicism in normal human somatic cells

Somatic cells accumulate genomic alterations with age; however, our understanding of mitochondrial DNA (mtDNA) mosaicism remains limited. Here we investigated the genomes of 2,096 clones derived from three cell types across 31 donors, identifying 6,451 mtDNA variants with heteroplasmy levels of ≳0.3%. While the majority of these variants were unique to individual clones, suggesting stochastic acquisition with age, 409 variants (6%) were shared across multiple embryonic lineages, indicating their origin from heteroplasmy in fertilized eggs. The mutational spectrum exhibited replication-strand bias, implicating mtDNA replication as a major mutational process. We evaluated the mtDNA mutation rate (5.0 × 10-8 per base pair) and a turnover frequency of 10-20 per year, which are fundamental components shaping the landscape of mtDNA mosaicism over a lifetime. The expansion of mtDNA-truncating mutations toward homoplasmy was substantially suppressed. Our findings provide comprehensive insights into the origins, dynamics and functional consequences of mtDNA mosaicism in human somatic cells.

Mitochondrial genetics through the lens of single-cell multi-omics

Mitochondria carry their own genetic information encoding for a subset of protein-coding genes and translational machinery essential for cellular respiration and metabolism. Despite its small size, the mitochondrial genome, its natural genetic variation and molecular phenotypes have been challenging to study using bulk sequencing approaches, due to its variation in cellular copy number, non-Mendelian modes of inheritance and propensity for mutations. Here we highlight emerging strategies designed to capture mitochondrial genetic variation across individual cells for lineage tracing and studying mitochondrial genetics in primary human cells and clinical specimens. We review recent advances surrounding single-cell mitochondrial genome sequencing and its integration with functional genomic readouts, including leveraging somatic mitochondrial DNA mutations as clonal markers that can resolve cellular population dynamics in complex human tissues. Finally, we discuss how single-cell whole mitochondrial genome sequencing approaches can be utilized to investigate mitochondrial genetics and its contribution to cellular heterogeneity and disease.

New tools to study renal fibrogenesis

PURPOSE OF REVIEW

Kidney fibrosis is a key pathological aspect and outcome of chronic kidney disease (CKD). The advent of multiomic analyses using human kidney tissue, enabled by technological advances, marks a new chapter of discovery in fibrosis research of the kidney. This review highlights the rapid advancements of single-cell and spatial multiomic techniques that offer new avenues for exploring research questions related to human kidney fibrosis development.

RECENT FINDINGS

We recently focused on understanding the origin and transition of myofibroblasts in kidney fibrosis using single-cell RNA sequencing (scRNA-seq) [1] . We analysed cells from healthy human kidneys and compared them to patient samples with CKD. We identified PDGFRα+/PDGFRβ+ mesenchymal cells as the primary cellular source of extracellular matrix (ECM) in human kidney fibrosis. We found several commonly shared cell states of fibroblasts and myofibroblasts and provided insights into molecular regulators. Novel single-cell and spatial multiomics tools are now available to shed light on cell lineages, the plasticity of kidney cells and cell-cell communication in fibrosis.

SUMMARY

As further single-cell and spatial multiomic approaches are being developed, opportunities to apply these methods to human kidney tissues expand similarly. Careful design and optimisation of the multiomic experiments are needed to answer questions related to cell lineages, plasticity and cell-cell communication in kidney fibrosis.

Joint inference of cell lineage and mitochondrial evolution from single-cell sequencing data

MOTIVATION

Eukaryotic cells contain organelles called mitochondria that have their own genome. Most cells contain thousands of mitochondria which replicate, even in nondividing cells, by means of a relatively error-prone process resulting in somatic mutations in their genome. Because of the higher mutation rate compared to the nuclear genome, mitochondrial mutations have been used to track cellular lineage, particularly using single-cell sequencing that measures mitochondrial mutations in individual cells. However, existing methods to infer the cell lineage tree from mitochondrial mutations do not model "heteroplasmy," which is the presence of multiple mitochondrial clones with distinct sets of mutations in an individual cell. Single-cell sequencing data thus provide a mixture of the mitochondrial clones in individual cells, with the ancestral relationships between these clones described by a mitochondrial clone tree. While deconvolution of somatic mutations from a mixture of evolutionarily related genomes has been extensively studied in the context of bulk sequencing of cancer tumor samples, the problem of mitochondrial deconvolution has the additional constraint that the mitochondrial clone tree must be concordant with the cell lineage tree.

RESULTS

We formalize the problem of inferring a concordant pair of a mitochondrial clone tree and a cell lineage tree from single-cell sequencing data as the Nested Perfect Phylogeny Mixture (NPPM) problem. We derive a combinatorial characterization of the solutions to the NPPM problem, and formulate an algorithm, MERLIN, to solve this problem exactly using a mixed integer linear program. We show on simulated data that MERLIN outperforms existing methods that do not model mitochondrial heteroplasmy nor the concordance between the mitochondrial clone tree and the cell lineage tree. We use MERLIN to analyze single-cell whole-genome sequencing data of 5220 cells of a gastric cancer cell line and show that MERLIN infers a more biologically plausible cell lineage tree and mitochondrial clone tree compared to existing methods.

AVAILABILITY AND IMPLEMENTATION

https://github.com/raphael-group/MERLIN.

Approaches and challenges in identifying, quantifying, and manipulating dynamic mitochondrial genome variations

Mitochondria, the cellular powerhouses, possess their own unique genetic system, including replication, transcription, and translation. Studying these processes is crucial for comprehending mitochondrial disorders, energy production, and their related diseases. Over the past decades, various approaches have been applied in detecting and quantifying mitochondrial genome variations with also the purpose of manipulation of mitochondria or mitochondrial genome for therapeutics. Understanding the scope and limitations of above strategies is not only fundamental to the understanding of basic biology but also critical for exploring disease-related novel target(s), as well to develop innovative therapies. Here, this review provides an overview of different tools and techniques for accurate mitochondrial genome variations identification, quantification, and discuss novel strategies for the manipulation of mitochondria to develop innovative therapeutic interventions, through combining the insights gained from the study of mitochondrial genetics with ongoing single cell omics combined with advanced single molecular tools.

Integration of single-cell transcriptome and chromatin accessibility and its application on tumor investigation

The advent of single-cell sequencing techniques has not only revolutionized the investigation of biological processes but also significantly contributed to unraveling cellular heterogeneity at unprecedented levels. Among the various methods, single-cell transcriptome sequencing stands out as the best established, and has been employed in exploring many physiological and pathological activities. The recently developed single-cell epigenetic sequencing techniques, especially chromatin accessibility sequencing, have further deepened our understanding of gene regulatory networks. In this review, we summarize the recent breakthroughs in single-cell transcriptome and chromatin accessibility sequencing methodologies. Additionally, we describe current bioinformatic strategies to integrate data obtained through these single-cell sequencing methods and highlight the application of this analysis strategy on a deeper understanding of tumorigenesis and tumor progression. Finally, we also discuss the challenges and anticipated developments in this field.

Single-nucleoid architecture reveals heterogeneous packaging of mitochondrial DNA

Cellular metabolism relies on the regulation and maintenance of mitochondrial DNA (mtDNA). Hundreds to thousands of copies of mtDNA exist in each cell, yet because mitochondria lack histones or other machinery important for nuclear genome compaction, it remains unresolved how mtDNA is packaged into individual nucleoids. In this study, we used long-read single-molecule accessibility mapping to measure the compaction of individual full-length mtDNA molecules at near single-nucleotide resolution. We found that, unlike the nuclear genome, human mtDNA largely undergoes all-or-none global compaction, with most nucleoids existing in an inaccessible, inactive state. Highly accessible mitochondrial nucleoids are co-occupied by transcription and replication components and selectively form a triple-stranded displacement loop structure. In addition, we showed that the primary nucleoid-associated protein TFAM directly modulates the fraction of inaccessible nucleoids both in vivo and in vitro, acting consistently with a nucleation-and-spreading mechanism to coat and compact mitochondrial nucleoids. Together, these findings reveal the primary architecture of mtDNA packaging and regulation in human cells.

Cofea: correlation-based feature selection for single-cell chromatin accessibility data

Single-cell chromatin accessibility sequencing (scCAS) technologies have enabled characterizing the epigenomic heterogeneity of individual cells. However, the identification of features of scCAS data that are relevant to underlying biological processes remains a significant gap. Here, we introduce a novel method Cofea, to fill this gap. Through comprehensive experiments on 5 simulated and 54 real datasets, Cofea demonstrates its superiority in capturing cellular heterogeneity and facilitating downstream analysis. Applying this method to identification of cell type-specific peaks and candidate enhancers, as well as pathway enrichment analysis and partitioned heritability analysis, we illustrate the potential of Cofea to uncover functional biological process.

Comprehensive Identification of Mitochondrial Pseudogenes (NUMTs) in the Human Telomere-to-Telomere Reference Genome

Practices related to mitochondrial research have long been hindered by the presence of mitochondrial pseudogenes within the nuclear genome (NUMTs). Even though partially assembled human reference genomes like hg38 have included NUMTs compilation, the exhaustive NUMTs within the only complete reference genome (T2T-CHR13) remain unknown. Here, we comprehensively identified the fixed NUMTs within the reference genome using human pan-mitogenome (HPMT) from GeneBank. The inclusion of HPMT serves the purpose of establishing an authentic mitochondrial DNA (mtDNA) mutational spectrum for the identification of NUMTs, distinguishing it from the polymorphic variations found in NUMTs. Using HPMT, we identified approximately 10% of additional NUMTs in three human reference genomes under stricter thresholds. And we also observed an approximate 6% increase in NUMTs in T2T-CHR13 compared to hg38, including NUMTs on the short arms of chromosomes 13, 14, and 15 that were not assembled previously. Furthermore, alignments based on 20-mer from mtDNA suggested the presence of more mtDNA-like short segments within the nuclear genome, which should be avoided for short amplicon or cell free mtDNA detection. Finally, through the assay of transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) on cell lines before and after mtDNA elimination, we concluded that NUMTs have a minimal impact on bulk ATAC-seq, even though 16% of sequencing data originated from mtDNA.

Single cell RNA sequencing sheds light on infiltrating T cells in idiopathic inflammatory myopathies

Idiopathic inflammatory myopathies (IIM), also referred to as "myositis," are a group of heterogeneous autoimmune disorders characterised by muscle weakness, atrophy and progressive reduced mobility (Lundberg et al, 2021). IIM represent a significant health burden in adult populations, affecting individuals at a mean age of 50 with an estimated prevalence of 2.9-34 per 100,000 (Dobloug et al, 2015; Svensson et al, 2017). IIM encompass several subtypes including dermatomyositis, immune-mediated necrotising myopathy, inclusion-body myositis, antisynthetase syndrome and polymyositis, which are characterised by specific clinical features, histopathological findings and autoantibody status (Pinal-Fernandez et al, 2020).

Systematic investigation of mitochondrial transfer between cancer cells and T cells at single-cell resolution

Mitochondria (MT) participate in most metabolic activities of mammalian cells. A near-unidirectional mitochondrial transfer from T cells to cancer cells was recently observed to "metabolically empower" cancer cells while "depleting immune cells," providing new insights into tumor-T cell interaction and immune evasion. Here, we leverage single-cell RNA-seq technology and introduce MERCI, a statistical deconvolution method for tracing and quantifying mitochondrial trafficking between cancer and T cells. Through rigorous benchmarking and validation, MERCI accurately predicts the recipient cells and their relative mitochondrial compositions. Application of MERCI to human cancer samples identifies a reproducible MT transfer phenotype, with its signature genes involved in cytoskeleton remodeling, energy production, and TNF-α signaling pathways. Moreover, MT transfer is associated with increased cell cycle activity and poor clinical outcome across different cancer types. In summary, MERCI enables systematic investigation of an understudied aspect of tumor-T cell interactions that may lead to the development of therapeutic opportunities.

The Mycoplasma hyorhinis genome displays differential chromatin accessibility

Whilst the regulation of chromatin accessibility and its effect on gene expression have been well studied in eukaryotic species, the role of chromatin dynamics and 3D organisation in genome reduced bacteria remains poorly understood [1,2]. In this study we profiled the accessibility of the Mycoplasma hyorhinis genome, these data were collected fortuitously as part of an experiment where ATAC-Seq was conducted on mycoplasma, contaminated mammalian cells. We found a differential and highly reproducible chromatin accessibility landscape, with regions of increased accessibility corresponding to genes important for the bacteria's life cycle and infectivity. Furthermore, accessibility in general correlated with transcriptionally active genes as profiled by RNA-Seq, but peaks of high accessibility were also seen in non-coding and intergenic regions, which could contribute to the topological organisation of the genome. However, changes in transcription induced by starvation or application of the RNA polymerase inhibitor rifampicin did not themselves change the accessibility profile, which confirms that the differential accessibility is inherently a property of the genome, and not a consequence of its function. These results together show that differential chromatin accessibility is a key feature of the regulation of gene expression in bacteria.