Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion

Decoding the mosaic of inflammatory bowel disease: Illuminating insights with single-cell RNA technology

Inflammatory bowel diseases (IBD), comprising ulcerative colitis (UC) and Crohn's disease (CD), are complex chronic inflammatory intestinal conditions with a multifaceted pathology, influenced by immune dysregulation and genetic susceptibility. The challenges in understanding IBD mechanisms and implementing precision medicine include deciphering the contributions of individual immune and non-immune cell populations, pinpointing specific dysregulated genes and pathways, developing predictive models for treatment response, and advancing molecular technologies. Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to address these challenges, offering comprehensive transcriptome profiles of various cell types at the individual cell level in IBD patients, overcoming limitations of bulk RNA sequencing. Additionally, single-cell proteomics analysis, T-cell receptor repertoire analysis, and epigenetic profiling provide a comprehensive view of IBD pathogenesis and personalized therapy. This review summarizes significant advancements in single-cell sequencing technologies for enhancing our understanding of IBD, covering pathogenesis, diagnosis, treatment, and prognosis. Furthermore, we discuss the challenges that persist in the context of IBD research, including the need for longitudinal studies, integration of multiple single-cell and spatial transcriptomics technologies, and the potential of microbial single-cell RNA-seq to shed light on the role of the gut microbiome in IBD.

scBlood: A comprehensive single-cell accessible chromatin database of blood cells

The advent of single cell transposase-accessible chromatin sequencing (scATAC-seq) technology enables us to explore the genomic characteristics and chromatin accessibility of blood cells at the single-cell level. To fully make sense of the roles and regulatory complexities of blood cells, it is critical to collect and analyze these rapidly accumulating scATAC-seq datasets at a system level. Here, we present scBlood (https://bio.liclab.net/scBlood/), a comprehensive single-cell accessible chromatin database of blood cells. The current version of scBlood catalogs 770,907 blood cells and 452,247 non-blood cells from ∼400 high-quality scATAC-seq samples covering 30 tissues and 21 disease types. All data hosted on scBlood have undergone preprocessing from raw fastq files and multiple standards of quality control. Furthermore, we conducted comprehensive downstream analyses, including multi-sample integration analysis, cell clustering and annotation, differential chromatin accessibility analysis, functional enrichment analysis, co-accessibility analysis, gene activity score calculation, and transcription factor (TF) enrichment analysis. In summary, scBlood provides a user-friendly interface for searching, browsing, analyzing, visualizing, and downloading scATAC-seq data of interest. This platform facilitates insights into the functions and regulatory mechanisms of blood cells, as well as their involvement in blood-related diseases.

Recruitment of homodimeric proneural factors by conserved CAT-CAT E-boxes drives major epigenetic reconfiguration in cortical neurogenesis

Proneural factors of the basic helix-loop-helix family coordinate neurogenesis and neurodifferentiation. Among them, NEUROG2 and NEUROD2 subsequently act to specify neurons of the glutamatergic lineage. Disruption of these factors, their target genes and binding DNA motifs has been linked to various neuropsychiatric disorders. Proneural factors bind to specific DNA motifs called E-boxes (hexanucleotides of the form CANNTG, composed of two CAN half sites on opposed strands). While corticogenesis heavily relies on E-box activity, the collaboration of proneural factors on different E-box types and their chromatin remodeling mechanisms remain largely unknown. Here, we conducted a comprehensive analysis using chromatin immunoprecipitation followed by sequencing (ChIP-seq) data for NEUROG2 and NEUROD2, along with time-matched single-cell RNA-seq, ATAC-seq and DNA methylation data from the developing mouse cortex. Our findings show that these factors are highly enriched in transiently active genomic regions during intermediate stages of neuronal differentiation. Although they primarily bind CAG-containing E-boxes, their binding in dynamic regions is notably enriched in CAT-CAT E-boxes (i.e. CATATG, denoted as 5'3' half sites for dimers), which undergo significant DNA demethylation and exhibit the highest levels of evolutionary constraint. Aided by HT-SELEX data reanalysis, structural modeling and DNA footprinting, we propose that these proneural factors exert maximal chromatin remodeling influence during intermediate stages of neurogenesis by binding as homodimers to CAT-CAT motifs. This study provides an in-depth integrative analysis of the dynamic regulation of E-boxes during neuronal development, enhancing our understanding of the mechanisms underlying the binding specificity of critical proneural factors.

CRISPR Screening of Transcribed Super-Enhancers Identifies Drivers of Triple-Negative Breast Cancer Progression

Triple-negative breast cancer (TNBC) is the most therapeutically recalcitrant form of breast cancer, which is due in part to the paucity of targeted therapies. A systematic analysis of regulatory elements that extend beyond protein-coding genes could uncover avenues for therapeutic intervention. To this end, we analyzed the regulatory mechanisms of TNBC-specific transcriptional enhancers together with their noncoding enhancer RNA (eRNA) transcripts. The functions of the top 30 eRNA-producing super-enhancers were systematically probed using high-throughput CRISPR-interference assays coupled to RNA sequencing that enabled unbiased detection of target genes genome-wide. Generation of high-resolution Hi-C chromatin interaction maps enabled annotation of the direct target genes for each super-enhancer, which highlighted their proclivity for genes that portend worse clinical outcomes in patients with TNBC. Illustrating the utility of this dataset, deletion of an identified super-enhancer controlling the nearby PODXL gene or specific degradation of its eRNAs led to profound inhibitory effects on target gene expression, cell proliferation, and migration. Furthermore, loss of this super-enhancer suppressed tumor growth and metastasis in TNBC mouse xenograft models. Single-cell RNA sequencing and assay for transposase-accessible chromatin with high-throughput sequencing analyses demonstrated the enhanced activity of this super-enhancer within the malignant cells of TNBC tumor specimens compared with nonmalignant cell types. Collectively, this work examines several fundamental questions about how regulatory information encoded into eRNA-producing super-enhancers drives gene expression networks that underlie the biology of TNBC. Significance: Integrative analysis of eRNA-producing super-enhancers defines molecular mechanisms controlling global patterns of gene expression that regulate clinical outcomes in breast cancer, highlighting the potential of enhancers as biomarkers and therapeutic targets.

The CCR6-CCL20 Axis Promotes Regulatory T-cell Glycolysis and Immunosuppression in Tumors

Regulatory T cells (Treg) are important players in the tumor microenvironment. However, the mechanisms behind their immunosuppressive effects are poorly understood. We found that CCR6-CCL20 activity in tumor-infiltrating Tregs is associated with greater glycolytic activity and ablation of Ccr6 reduced glycolysis and lactic acid production while increasing compensatory glutamine metabolism. Immunosuppressive activity toward CD8+ T cells was abrogated in Ccr6-/- Tregs due to reduction in activation-induced glycolysis. Furthermore, Ccr6-/- mice exhibited improved survival across multiple tumor models compared to wild-type mice and Treg and CD8+ T-cell depletion abrogated the improvement. In addition, Ccr6 ablation further promoted the efficacy of anti-PD-1 therapy in a preclinical glioma model. Follow-up knockdown of Ccl20 with siRNA also demonstrated improvement in antitumor efficacy. Our results unveil CCR6 as a marker and regulator of Treg-induced immunosuppression and identify approaches to target the metabolic determinants of Treg immunosuppressive activity.

SMARCA5-mediated chromatin remodeling is required for germinal center formation

The establishment of long-lasting immunity against pathogens is facilitated by the germinal center (GC) reaction, during which B cells increase their antibody affinity and differentiate into antibody-secreting cells (ASC) and memory cells. These events involve modifications in chromatin packaging that orchestrate the profound restructuring of gene expression networks that determine cell fate. While several chromatin remodelers were implicated in lymphocyte functions, less is known about SMARCA5. Here, using ribosomal pull-down for analyzing translated genes in GC B cells, coupled with functional experiments in mice, we identified SMARCA5 as a key chromatin remodeler in B cells. While the naive B cell compartment remained unaffected following conditional depletion of Smarca5, effective proliferation during B cell activation, immunoglobulin class switching, and as a result GC formation and ASC differentiation were impaired. Single-cell multiomic sequencing analyses revealed that SMARCA5 is crucial for facilitating the transcriptional modifications and genomic accessibility of genes that support B cell activation and differentiation. These findings offer novel insights into the functions of SMARCA5, which can be targeted in various human pathologies.

Single-cell sequencing: Current applications in various tuberculosis specimen types

Tuberculosis (TB) is a chronic disease caused by Mycobacterium tuberculosis (M.tb) and responsible for millions of deaths worldwide each year. It has a complex pathogenesis that primarily affects the lungs but can also impact systemic organs. In recent years, single-cell sequencing technology has been utilized to characterize the composition and proportion of immune cell subpopulations associated with the pathogenesis of TB disease since it has a high resolution that surpasses conventional techniques. This paper reviews the current use of single-cell sequencing technologies in TB research and their application in analysing specimens from various sources of TB, primarily peripheral blood and lung specimens. The focus is on how these technologies can reveal dynamic changes in immune cell subpopulations, genes and proteins during disease progression after M.tb infection. Based on the current findings, single-cell sequencing has significant potential clinical value in the field of TB research. Next, we will focus on the real-world applications of the potential targets identified through single-cell sequencing for diagnostics, therapeutics and the development of effective vaccines.

A molecular mechanism for bright color variation in parrots

Parrots produce stunning plumage colors through unique pigments called psittacofulvins. However, the mechanism underlying their ability to generate a spectrum of vibrant yellows, reds, and greens remains enigmatic. We uncover a unifying chemical basis for a wide range of parrot plumage colors, which result from the selective deposition of red aldehyde- and yellow carboxyl-containing psittacofulvin molecules in developing feathers. Through genetic mapping, biochemical assays, and single-cell genomics, we identified a critical player in this process, the aldehyde dehydrogenase ALDH3A2, which oxidizes aldehyde psittacofulvins into carboxyl forms in late-differentiating keratinocytes during feather development. The simplicity of the underlying molecular mechanism, in which a single enzyme influences the balance of red and yellow pigments, offers an explanation for the exceptional evolutionary lability of parrot coloration.

ChromaFold predicts the 3D contact map from single-cell chromatin accessibility

Identifying cell-type-specific 3D chromatin interactions between regulatory elements can help decipher gene regulation and interpret disease-associated non-coding variants. However, achieving this resolution with current 3D genomics technologies is often infeasible given limited input cell numbers. We therefore present ChromaFold, a deep learning model that predicts 3D contact maps, including regulatory interactions, from single-cell ATAC sequencing (scATAC-seq) data alone. ChromaFold uses pseudobulk chromatin accessibility, co-accessibility across metacells, and a CTCF motif track as inputs and employs a lightweight architecture to train on standard GPUs. Trained on paired scATAC-seq and Hi-C data in human samples, ChromaFold accurately predicts the 3D contact map and peak-level interactions across diverse human and mouse test cell types. Compared to leading contact map prediction models that use ATAC-seq and CTCF ChIP-seq, ChromaFold achieves state-of-the-art performance using only scATAC-seq. Finally, fine-tuning ChromaFold on paired scATAC-seq and Hi-C in a complex tissue enables deconvolution of chromatin interactions across cell subpopulations.

Spatial microniches of IL-2 combine with IL-10 to drive lung migratory TH2 cells in response to inhaled allergen

The mechanisms that guide T helper 2 (TH2) cell differentiation in barrier tissues are unclear. Here we describe the molecular pathways driving allergen-specific TH2 cells using temporal, spatial and single-cell transcriptomic tracking of house dust mite-specific T cells in mice. Differentiation and migration of lung allergen-specific TH2 cells requires early expression of the transcriptional repressor Blimp-1. Loss of Blimp-1 during priming in the lymph node ablated the formation of TH2 cells in the lung, indicating early Blimp-1 promotes TH2 cells with migratory capability. IL-2/STAT5 signals and autocrine/paracrine IL-10 from house dust mite-specific T cells were essential for Blimp-1 and subsequent GATA3 upregulation through repression of Bcl6 and Bach2. Spatial microniches of IL-2 in the lymph node supported the earliest Blimp-1+TH2 cells, demonstrating lymph node localization is a driver of TH2 initiation. Our findings identify an early requirement for IL-2-mediated spatial microniches that integrate with allergen-driven IL-10 from responding T cells to drive allergic asthma.

Single-nucleus transcriptional and chromatin accessibility analyses of maturing mouse Achilles tendon uncover the molecular landscape of tendon stem/progenitor cells

Tendons and ligaments are crucial connective tissues linking bones and muscles, yet achieving full functional recovery after injury remains challenging. We investigated the characteristics of tendon stem/progenitor cells (TSPCs) by focusing on the declining tendon repair capacity with growth. Using single-cell RNA sequencing on Achilles tendon cells from 2- and 6-week-old mice, we identified Cd55 and Cd248 as novel surface antigen markers for TSPCs. Combining single-nucleus ATAC and RNA sequencing analyses revealed that Cd55 and Cd248 positive fractions in tendon tissue are TSPCs, with this population decreasing at 1 weeks. We also identified candidate upstream transcription factors regulating these fractions. Functional analyses of isolated CD55/CD248 positive cells demonstrated high clonogenic potential and tendon differentiation capacity, forming functional tendon-like tissue in vitro . This study establishes CD55 and CD248 as novel TSPC surface antigens, potentially advancing tendon regenerative medicine and contributing to the development of new treatment strategies for tendon and ligament injuries.

Restriction of innate Tγδ17 cell plasticity by an AP-1 regulatory axis

IL-17-producing γδ T (Tγδ17) cells are innate-like mediators of intestinal barrier immunity. While Th17 cell and ILC3 plasticity have been extensively studied, the mechanisms governing Tγδ17 cell effector flexibility remain undefined. Here, we combined type 3 fate-mapping with single cell ATAC/RNA-seq multiome profiling to define the cellular features and regulatory networks underlying Tγδ17 cell plasticity. During homeostasis, Tγδ17 cell effector identity was stable across tissues, including for intestinal T-bet+ Tγδ17 cells that restrained IFNγ production. However, S. typhimurium infection induced intestinal Vγ6+ Tγδ17 cell conversion into type 1 effectors, with loss of IL-17A production and partial RORγt downregulation. Multiome analysis revealed a trajectory along Vγ6+ Tγδ17 effector conversion, with TIM-3 marking ex-Tγδ17 cells with enhanced type 1 functionality. Lastly, we characterized and validated a critical AP-1 regulatory axis centered around JunB and Fosl2 that controls Vγ6+ Tγδ17 cell plasticity by stabilizing type 3 identity and restricting type 1 effector conversion.

Epigenomic heterogeneity as a source of tumour evolution

In the past decade, remarkable progress in cancer medicine has been achieved by the development of treatments that target DNA sequence variants. However, a purely genetic approach to treatment selection is hampered by the fact that diverse cell states can emerge from the same genotype. In multicellular organisms, cell-state heterogeneity is driven by epigenetic processes that regulate DNA-based functions such as transcription; disruption of these processes is a hallmark of cancer that enables the emergence of defective cell states. Advances in single-cell technologies have unlocked our ability to quantify the epigenomic heterogeneity of tumours and understand its mechanisms, thereby transforming our appreciation of how epigenomic changes drive cancer evolution. This Review explores the idea that epigenomic heterogeneity and plasticity act as a reservoir of cell states and therefore as a source of tumour evolution. Best practices to quantify epigenomic heterogeneity and explore its various causes and consequences are discussed, including epigenomic reprogramming, stochastic changes and lasting memory. The design of new therapeutic approaches to restrict epigenomic heterogeneity, with the long-term objective of limiting cancer development and progression, is also addressed.

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.

Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data

Assay for Transposase-Accessible Chromatin sequencing (ATAC-Seq) is a widely used technique to explore gene regulatory mechanisms. For most ATAC-Seq data from healthy and diseased tissues such as tumors, chromatin accessibility measurement represents a mixed signal from multiple cell types. In this work, we derive reliable chromatin accessibility marker peaks and reference profiles for most non-malignant cell types frequently observed in the microenvironment of human tumors. We then integrate these data into the EPIC deconvolution framework (Racle et al., 2017) to quantify cell-type heterogeneity in bulk ATAC-Seq data. Our EPIC-ATAC tool accurately predicts non-malignant and malignant cell fractions in tumor samples. When applied to a human breast cancer cohort, EPIC-ATAC accurately infers the immune contexture of the main breast cancer subtypes.

Systems immunology approaches to study T cells in health and disease

T cells are dynamically regulated immune cells that are implicated in a variety of diseases ranging from infection, cancer and autoimmunity. Recent advancements in sequencing methods have provided valuable insights in the transcriptional and epigenetic regulation of T cells in various disease settings. In this review, we identify the key sequencing-based methods that have been applied to understand the transcriptomic and epigenomic regulation of T cells in diseases.

Evolution of plant cell-type-specific cis-regulatory elements

Cis-regulatory elements (CREs) are critical in regulating gene expression, and yet understanding of CRE evolution remains challenging. Here, we constructed a comprehensive single-cell atlas of chromatin accessibility in Oryza sativa, integrating data from 103,911 nuclei representing 126 discrete cell states across nine distinct organs. We used comparative genomics to compare cell-type resolved chromatin accessibility between O. sativa and 57,552 nuclei from four additional grass species (Zea mays, Sorghum bicolor, Panicum miliaceum, and Urochloa fusca). Accessible chromatin regions (ACRs) had different levels of conservation depending on the degree of cell-type specificity. We found a complex relationship between ACRs with conserved noncoding sequences, cell-type specificity, conservation, and tissue-specific switching. Additionally, we found that epidermal ACRs were less conserved compared to other cell types, potentially indicating that more rapid regulatory evolution has occurred in the L1-derived epidermal layer of these species. Finally, we identified and characterized a conserved subset of ACRs that overlapped the repressive histone modification H3K27me3, implicating them as potentially silencer-like CREs maintained by evolution. Collectively, this comparative genomics approach highlights the dynamics of plant cell-type-specific CRE evolution.

Midkine as a driver of age-related changes and increase in mammary tumorigenesis

Aging is a pivotal risk factor for cancer, yet the underlying mechanisms remain poorly defined. Here, we explore age-related changes in the rat mammary gland by single-cell multiomics. Our findings include increased epithelial proliferation, loss of luminal identity, and decreased naive B and T cells with age. We discover a luminal progenitor population unique to old rats with profiles reflecting precancerous changes and identify midkine (Mdk) as a gene upregulated with age and a regulator of age-related luminal progenitors. Midkine treatment of young rats mimics age-related changes via activating PI3K-AKT-SREBF1 pathway and promotes nitroso-N-methylurea-induced mammary tumorigenesis. Midkine levels increase with age in human blood and mammary epithelium, and higher MDK in normal breast tissue is associated with higher breast cancer risk in younger women. Our findings reveal a link between aging and susceptibility to tumor initiation and identify midkine as a mediator of age-dependent increase in breast tumorigenesis.

Single-nucleus multiomics reveals the gene-regulatory networks underlying sex determination of murine primordial germ cells

Accurate specification of female and male germ cells during embryonic development is critical for sexual reproduction. Primordial germ cells (PGCs) are the bipotential precursors of mature gametes that commit to an oogenic or spermatogenic fate in response to sex-determining cues from the fetal gonad. The critical processes required for PGCs to integrate and respond to signals from the somatic environment in gonads are not understood. In this study, we developed the first single-nucleus multiomics map of chromatin accessibility and gene expression during murine PGC development in both XX and XY embryos. Profiling of cell-type specific transcriptomes and regions of open chromatin from the same cell captured the molecular signatures and gene networks underlying PGC sex determination. Joint RNA and ATAC data for single PGCs resolved previously unreported PGC subpopulations and cataloged a multimodal reference atlas of differentiating PGC clusters. We discovered that regulatory element accessibility precedes gene expression during PGC development, suggesting that changes in chromatin accessibility may prime PGC lineage commitment prior to differentiation. Similarly, we found that sexual dimorphism in chromatin accessibility and gene expression increased temporally in PGCs. Combining single-nucleus sequencing data, we computationally mapped the cohort of transcription factors that regulate the expression of sexually dimorphic genes in PGCs. For example, the gene regulatory networks of XX PGCs are enriched for the transcription factors, TFAP2c, TCFL5, GATA2, MGA, NR6A1, TBX4, and ZFX. Sex-specific enrichment of the forkhead-box and POU6 families of transcription factors was also observed in XY PGCs. Finally, we determined the temporal expression patterns of WNT, BMP, and RA signaling during PGC sex determination, and our discovery analyses identified potentially new cell communication pathways between supporting cells and PGCs. Our results illustrate the diversity of factors involved in programming PGCs towards a sex-specific fate.

Regulatory mechanisms orchestrating cellular diversity of Cd36+ olfactory sensory neurons revealed by scRNA-seq and scATAC-seq analysis

Recent discoveries have revealed remarkable complexity within olfactory sensory neurons (OSNs), including the existence of two OSN populations based on the expression of Cd36. However, the regulatory mechanisms governing this cellular diversity in the same cell type remain elusive. Here, we show the preferential expression of 79 olfactory receptors in Cd36+ OSNs and the anterior projection characteristics of Cd36+ OSNs, indicating the non-randomness of Cd36 expression. The integrated analysis of single-cell RNA sequencing (scRNA-seq) and scATAC-seq reveals that the differences in Cd36+/- OSNs occur at the immature OSN stage, with Mef2a and Hdac9 being important regulators of developmental divergence. We hypothesize that the absence of Hdac9 may affect the activation of Mef2a, leading to the up-regulation of Mef2a target genes, including teashirt zinc finger family member 1 (Tshz1), in the Cd36+ OSN lineage. We validate that Tshz1 directly promotes Cd36 expression through enhancer bindings. Our study unravels the intricate regulatory landscape and principles governing cellular diversity in the olfactory system.

Acute and persistent responses after H5N1 vaccination in humans

To gain insight into how an adjuvant impacts vaccination responses, we use systems immunology to study human H5N1 influenza vaccination with or without the adjuvant AS03, longitudinally assessing 14 time points including multiple time points within the first day after prime and boost. We develop an unsupervised computational framework to discover high-dimensional response patterns, which uncover adjuvant- and immunogenicity-associated early response dynamics, including some that differ post prime versus boost. With or without adjuvant, some vaccine-induced transcriptional patterns persist to at least 100 days after initial vaccination. Single-cell profiling of surface proteins, transcriptomes, and chromatin accessibility implicates transcription factors in the erythroblast-transformation-specific (ETS) family as shaping these long-lasting signatures, primarily in classical monocytes but also in CD8+ naive-like T cells. These cell-type-specific signatures are elevated at baseline in high-antibody responders in an independent vaccination cohort, suggesting that antigen-agnostic baseline immune states can be modulated by vaccine antigens alone to enhance future responses.

Changes in conjunctival mononuclear phagocytes and suppressive activity of regulatory macrophages in desiccation induced dry eye

PURPOSE

To evaluate the effects of dry eye on conjunctival immune cell number and transcriptional profiles with attention to mononuclear phagocytes.

METHODS

Expression profiling was performed by single-cell RNA sequencing on sorted conjunctival immune cells from non-stressed and C57BL/6 mice subjected to desiccating stress (DS). Monocle 3 modeled cell trajectory, scATAC-seq assessed chromatin accessibility and IPA identified canonical pathways. Inflammation and goblet cells were measured after depletion of MRC1+ MΦs with mannosylated clodronate liposomes.

RESULTS

Mononuclear phagocytes (monocytes, MΦs, DCs) comprised 72 % of immune cells and showed the greatest changes with DS. Distinct DS induced gene expression patterns were seen in phagocytes classified by expression of Ccr2 and [Timd4, Lyve1, Folr2 (TLR)]. Expression of phagocytosis/efferocytosis genes increased in TLF+CCR2- MΦs. Monocytes showed the highest expression of Ace, Cx3cr1, Vegfa, Ifngr1,2, and Stat1 and TLF-CCR2+ cells expressed higher levels of inflammatory mediators (Il1a, Il1b, Il1rn, Nfkb1, Ccl5, MHCII, Cd80, Cxcl10, Icam1). A trajectory from monocyte precursors branched to terminate in regulatory MΦs or in mDCs via transitional MΦ and cDC clusters. Activated pathways in TLF+ cells include phagocytosis, PPAR/RXRα activation, IL-10 signaling, alternate MΦ activation, while inflammatory pathways were suppressed. Depletion of MRC1+ MΦs increased IL-17 and IFN-γ expression and cytokine-expressing T cells, reduced IL-10 and worsened goblet loss.

CONCLUSIONS

Dryness stimulates distinct gene expression patterns in conjunctival phagocytes, increasing expression of regulatory genes in TLF+ cells regulated in part by RXRα, and inflammatory genes in CCR2+ cells. Regulatory MΦs depletion worsens DS induced inflammation and goblet cell loss.

NR2F2 regulation of interstitial to fetal Leydig cell differentiation in the testis: insights into differences of sex development

Testicular fetal Leydig cells are a specialized cell type responsible for embryo masculinization. Fetal Leydig cells produce androgens, that induce the differentiation of male reproductive system and sexual characteristics. Deficiencies in Leydig cell differentiation leads to various disorders of sex development and male reproductive defects such as ambiguous genitalia, hypospadias, cryptorchidism, and infertility. Fetal Leydig cells are thought to originate from proliferating progenitor cells in the testis interstitium, marked by genes like Arx , Pdgfra , Tcf21 and Wnt5a . However, the precise mechanisms governing the transition from interstitial cells to fetal Leydig cells remain elusive. Through integrated approaches involving mouse models and single-nucleus multiomic analyses, we discovered that fetal Leydig cells originate from a Nr2f2 -positive non-steroidogenic interstitial cell population. Embryonic deletion of Nr2f2 in mouse testes resulted in disorders of sex development, including dysgenic testes, Leydig cell hypoplasia, cryptorchidism, and hypospadias. We found that NR2F2 promotes the progenitor cell fate while suppresses Leydig cell differentiation by directly and indirectly controlling a cohort of transcription factors and downstream genes. Bioinformatic analyses of single-nucleus ATAC-seq and NR2F2 ChIP-seq data revealed putative transcription factors co-regulating the process of interstitial to Leydig cell differentiation. Collectively, our findings not only highlight the critical role of Nr2f2 in orchestrating the transition from interstitial cells to fetal Leydig cells, but also provide molecular insight into the disorders of sex development as a result of Nr2f2 mutations.

Context-aware single-cell multiomics approach identifies cell-type-specific lung cancer susceptibility genes

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis-regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function.

Droplet-based single-cell sequencing: Strategies and applications

Notable advancements in single-cell omics technologies have not only addressed longstanding challenges but also enabled unprecedented studies of cellular heterogeneity with unprecedented resolution and scale. These strides have led to groundbreaking insights into complex biological systems, paving the way for a more profound comprehension of human biology and diseases. The droplet microfluidic technology has become a crucial component in many single-cell sequencing workflows in terms of throughput, cost-effectiveness, and automation. Utilizing a microfluidic chip to encapsulate and profile individual cells within droplets has significantly improved single-cell research. Therefore, this review aims to comprehensively elaborate the droplet microfluidics-assisted omics methods from a single-cell perspective. The strategies for using droplet microfluidics in the realms of genomics, epigenomics, transcriptomics, and proteomics analyses are first introduced. On this basis, the focus then turns to the latest applications of this technology in different sequencing patterns, including mono- and multi-omics. Finally, the challenges and further perspectives of droplet-based single-cell sequencing in both foundational research and commercial applications are discussed.

BCG vaccination alters the epigenetic landscape of progenitor cells in human bone marrow to influence innate immune responses

Although the Bacille-Calmette-Guérin (BCG) vaccine is used to prevent tuberculosis, it also offers protection against a diverse range of non-mycobacterial infections. However, the underlying protective mechanisms in humans are not yet fully understood. Here, we surveyed at single-cell resolution the gene expression and chromatin landscape of human bone marrow, aspirated before and 90 days after BCG vaccination or placebo. We showed that BCG alters both the gene expression and epigenetic profiles of human hematopoietic stem and progenitor cells (HSPCs). Changes in gene expression occurred primarily within uncommitted stem cells. By contrast, changes in chromatin accessibility were most prevalent within differentiated progenitor cells at sites influenced by Kruppel-like factor (KLF) and early growth response (EGR) transcription factors and were highly correlated (r > 0.8) with the interleukin (IL)-1β secretion capacity of paired peripheral blood mononuclear cells (PBMCs). Our findings shed light on BCG vaccination's profound and lasting effects on HSPCs and its influence on innate immune responses and trained immunity.

Single cell genome and epigenome co-profiling reveals hardwiring and plasticity in breast cancer

Understanding the impact of genetic alterations on epigenomic phenotypes during breast cancer progression is challenging with unimodal measurements. Here, we report wellDA-seq, the first high-genomic resolution, high-throughput method that can simultaneously measure the whole genome and chromatin accessibility profiles of thousands of single cells. Using wellDA-seq, we profiled 22,123 single cells from 2 normal and 9 tumors breast tissues. By directly mapping the epigenomic phenotypes to genetic lineages across cancer subclones, we found evidence of both genetic hardwiring and epigenetic plasticity. In 6 estrogen-receptor positive breast cancers, we directly identified the ancestral cancer cells, and found that their epithelial cell-of-origin was Luminal Hormone Responsive cells. We also identified cell types with copy number aberrations (CNA) in normal breast tissues and discovered non-epithelial cell types in the microenvironment with CNAs in breast cancers. These data provide insights into the complex relationship between genetic alterations and epigenomic phenotypes during breast tumor evolution.

Distinct epigenomic landscapes underlie tissue-specific memory T cell differentiation

The memory CD8+ T cell pool contains phenotypically and transcriptionally heterogeneous subsets with specialized functions and recirculation patterns. Here, we examined the epigenetic landscape of CD8+ T cells isolated from seven non-lymphoid organs across four distinct infection models, alongside their circulating T cell counterparts. Using single-cell transposase-accessible chromatin sequencing (scATAC-seq), we found that tissue-resident memory T (TRM) cells and circulating memory T (TCIRC) cells develop along distinct epigenetic trajectories. We identified organ-specific transcriptional regulators of TRM cell development, including FOSB, FOS, FOSL1, and BACH2, and defined an epigenetic signature common to TRM cells across organs. Finally, we found that although terminal TEX cells share accessible regulatory elements with TRM cells, they are defined by TEX-specific epigenetic features absent from TRM cells. Together, this comprehensive data resource shows that TRM cell development is accompanied by dynamic transcriptome alterations and chromatin accessibility changes that direct tissue-adapted and functionally distinct T cell states.

A primer on single-cell RNA-seq analysis using dendritic cells as a case study

Recent advances in single-cell (sc) transcriptomics have revolutionized our understanding of dendritic cells (DCs), pivotal players of the immune system. ScRNA-sequencing (scRNA-seq) has unraveled a previously unrecognized complexity and heterogeneity of DC subsets, shedding light on their ontogeny and specialized roles. However, navigating the rapid technological progress and computational methods can be daunting for researchers unfamiliar with the field. This review aims to provide immunologists with a comprehensive introduction to sc transcriptomic analysis, offering insights into recent developments in DC biology. Addressing common analytical queries, we guide readers through popular tools and methodologies, supplemented with references to benchmarks and tutorials for in-depth understanding. By examining findings from pioneering studies, we illustrate how computational techniques have expanded our knowledge of DC biology. Through this synthesis, we aim to equip researchers with the necessary tools and knowledge to navigate and leverage scRNA-seq for unraveling the intricacies of DC biology and advancing immunological research.

scConfluence: single-cell diagonal integration with regularized Inverse Optimal Transport on weakly connected features

The abundance of unpaired multimodal single-cell data has motivated a growing body of research into the development of diagonal integration methods. However, the state-of-the-art suffers from the loss of biological information due to feature conversion and struggles with modality-specific populations. To overcome these crucial limitations, we here introduce scConfluence, a method for single-cell diagonal integration. scConfluence combines uncoupled autoencoders on the complete set of features with regularized Inverse Optimal Transport on weakly connected features. We extensively benchmark scConfluence in several single-cell integration scenarios proving that it outperforms the state-of-the-art. We then demonstrate the biological relevance of scConfluence in three applications. We predict spatial patterns for Scgn, Synpr and Olah in scRNA-smFISH integration. We improve the classification of B cells and Monocytes in highly heterogeneous scRNA-scATAC-CyTOF integration. Finally, we reveal the joint contribution of Fezf2 and apical dendrite morphology in Intra Telencephalic neurons, based on morphological images and scRNA.

Decoding changes in tumor-infiltrating leukocytes through dynamic experimental models and single-cell technologies

The ability to characterize immune cells and explore the molecular interactions that govern their functions has never been greater, fueled in recent years by the revolutionary advance of single-cell analysis platforms. However, precisely how immune cells respond to different stimuli and where differentiation processes and effector functions operate remain incompletely understood. Inferring cellular fate within single-cell transcriptomic analyses is now omnipresent, despite the assumptions typically required in such analyses. Recently developed experimental models support dynamic analyses of the immune response, providing insights into the temporal changes that occur within cells and the tissues in which such transitions occur. Here we will review these approaches and discuss how these can be combined with single-cell technologies to develop a deeper understanding of the immune responses that should support the development of better therapeutic options for patients.

Immune system adaptation during gender-affirming testosterone treatment

Infectious, inflammatory and autoimmune conditions present differently in males and females. SARS-CoV-2 infection in naive males is associated with increased risk of death, whereas females are at increased risk of long COVID1, similar to observations in other infections2. Females respond more strongly to vaccines, and adverse reactions are more frequent3, like most autoimmune diseases4. Immunological sex differences stem from genetic, hormonal and behavioural factors5 but their relative importance is only partially understood6-8. In individuals assigned female sex at birth and undergoing gender-affirming testosterone therapy (trans men), hormone concentrations change markedly but the immunological consequences are poorly understood. Here we performed longitudinal systems-level analyses in 23 trans men and found that testosterone modulates a cross-regulated axis between type-I interferon and tumour necrosis factor. This is mediated by functional attenuation of type-I interferon responses in both plasmacytoid dendritic cells and monocytes. Conversely, testosterone potentiates monocyte responses leading to increased tumour necrosis factor, interleukin-6 and interleukin-15 production and downstream activation of nuclear factor kappa B-regulated genes and potentiation of interferon-γ responses, primarily in natural killer cells. These findings in trans men are corroborated by sex-divergent responses in public datasets and illustrate the dynamic regulation of human immunity by sex hormones, with implications for the health of individuals undergoing hormone therapy and our understanding of sex-divergent immune responses in cisgender individuals.

scATAcat: cell-type annotation for scATAC-seq data

Cells whose accessibility landscape has been profiled with scATAC-seq cannot readily be annotated to a particular cell type. In fact, annotating cell-types in scATAC-seq data is a challenging task since, unlike in scRNA-seq data, we lack knowledge of 'marker regions' which could be used for cell-type annotation. Current annotation methods typically translate accessibility to expression space and rely on gene expression patterns. We propose a novel approach, scATAcat, that leverages characterized bulk ATAC-seq data as prototypes to annotate scATAC-seq data. To mitigate the inherent sparsity of single-cell data, we aggregate cells that belong to the same cluster and create pseudobulk. To demonstrate the feasibility of our approach we collected a number of datasets with respective annotations to quantify the results and evaluate performance for scATAcat. scATAcat is available as a python package at https://github.com/aybugealtay/scATAcat.

Baf155 controls hematopoietic differentiation and regeneration through chromatin priming

Chromatin priming promotes cell-type-specific gene expression, lineage differentiation, and development. The mechanism of chromatin priming has not been fully understood. Here, we report that mouse hematopoietic stem and progenitor cells (HSPCs) lacking the Baf155 subunit of the BAF (BRG1/BRM-associated factor) chromatin remodeling complex produce a significantly reduced number of mature blood cells, leading to a failure of hematopoietic regeneration upon transplantation and 5-fluorouracil (5-FU) injury. Baf155-deficient HSPCs generate particularly fewer neutrophils, B cells, and CD8+ T cells at homeostasis, supporting a more immune-suppressive tumor microenvironment and enhanced tumor growth. Single-nucleus multiomics analysis reveals that Baf155-deficient HSPCs fail to establish accessible chromatin in selected regions that are enriched for putative enhancers and binding motifs of hematopoietic lineage transcription factors. Our study provides a fundamental mechanistic understanding of the role of Baf155 in hematopoietic lineage chromatin priming and the functional consequences of Baf155 deficiency in regeneration and tumor immunity.

Cell-free DNA from germline TP53 mutation carriers reflect cancer-like fragmentation patterns

Germline pathogenic TP53 variants predispose individuals to a high lifetime risk of developing multiple cancers and are the hallmark feature of Li-Fraumeni syndrome (LFS). Our group has previously shown that LFS patients harbor shorter plasma cell-free DNA fragmentation; independent of cancer status. To understand the functional underpinning of cfDNA fragmentation in LFS, we conducted a fragmentomic analysis of 199 cfDNA samples from 82 TP53 mutation carriers and 30 healthy TP53-wildtype controls. We find that LFS individuals exhibit an increased prevalence of A/T nucleotides at fragment ends, dysregulated nucleosome positioning at p53 binding sites, and loci-specific changes in chromatin accessibility at development-associated transcription factor binding sites and at cancer-associated open chromatin regions. Machine learning classification resulted in robust differentiation between TP53 mutant versus wildtype cfDNA samples (AUC-ROC = 0.710-1.000) and intra-patient longitudinal analysis of ctDNA fragmentation signal enabled early cancer detection. These results suggest that cfDNA fragmentation may be a useful diagnostic tool in LFS patients and provides an important baseline for cancer early detection.

FRA1 controls acinar cell plasticity during murine KrasG12D-induced pancreatic acinar to ductal metaplasia

Acinar cells have been proposed as a cell-of-origin for pancreatic ductal adenocarcinoma (PDAC) after undergoing acinar-to-ductal metaplasia (ADM). ADM can be triggered by pancreatitis, causing acinar cells to de-differentiate to a ductal-like state. We identify FRA1 (gene name Fosl1) as the most active transcription factor during KrasG12D acute pancreatitis-mediated injury, and we have elucidated a functional role of FRA1 by generating an acinar-specific Fosl1 knockout mouse expressing KrasG12D. Using a gene regulatory network and pseudotime trajectory inferred from single-nuclei ATAC-seq and bulk RNA sequencing (RNA-seq), we hypothesized a regulatory model of the acinar-ADM-pancreatic intraepithelial neoplasia (PanIN) continuum and experimentally validated that Fosl1 knockout mice are delayed in the onset of ADM and neoplastic transformation. Our study also identifies that pro-inflammatory cytokines, such as granulocyte colony stimulating factor (G-CSF), can regulate FRA1 activity to modulate ADM. Our findings identify that FRA1 is a mediator of acinar cell plasticity and is critical for acinar cell de-differentiation and transformation.

MOCHA's advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human cohorts

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is being increasingly used to study gene regulation. However, major analytical gaps limit its utility in studying gene regulatory programs in complex diseases. In response, MOCHA (Model-based single cell Open CHromatin Analysis) presents major advances over existing analysis tools, including: 1) improving identification of sample-specific open chromatin, 2) statistical modeling of technical drop-out with zero-inflated methods, 3) mitigation of false positives in single cell analysis, 4) identification of alternative transcription-starting-site regulation, and 5) modules for inferring temporal gene regulatory networks from longitudinal data. These advances, in addition to open chromatin analyses, provide a robust framework after quality control and cell labeling to study gene regulatory programs in human disease. We benchmark MOCHA with four state-of-the-art tools to demonstrate its advances. We also construct cross-sectional and longitudinal gene regulatory networks, identifying potential mechanisms of COVID-19 response. MOCHA provides researchers with a robust analytical tool for functional genomic inference from scATAC-seq data.

ClusterMatch aligns single-cell RNA-sequencing data at the multi-scale cluster level via stable matching

MOTIVATION

Unsupervised clustering of single-cell RNA sequencing (scRNA-seq) data holds the promise of characterizing known and novel cell type in various biological and clinical contexts. However, intrinsic multi-scale clustering resolutions poses challenges to deal with multiple sources of variability in the high-dimensional and noisy data.

RESULTS

We present ClusterMatch, a stable match optimization model to align scRNA-seq data at the cluster level. In one hand, ClusterMatch leverages the mutual correspondence by canonical correlation analysis and multi-scale Louvain clustering algorithms to identify cluster with optimized resolutions. In the other hand, it utilizes stable matching framework to align scRNA-seq data in the latent space while maintaining interpretability with overlapped marker gene set. Through extensive experiments, we demonstrate the efficacy of ClusterMatch in data integration, cell type annotation, and cross-species/timepoint alignment scenarios. Our results show ClusterMatch's ability to utilize both global and local information of scRNA-seq data, sets the appropriate resolution of multi-scale clustering, and offers interpretability by utilizing marker genes.

AVAILABILITY AND IMPLEMENTATION

The code of ClusterMatch software is freely available at https://github.com/AMSSwanglab/ClusterMatch.

A Cell Cycle-Aware Network for Data Integration and Label Transferring of Single-Cell RNA-Seq and ATAC-Seq

In recent years, the integration of single-cell multi-omics data has provided a more comprehensive understanding of cell functions and internal regulatory mechanisms from a non-single omics perspective, but it still suffers many challenges, such as omics-variance, sparsity, cell heterogeneity, and confounding factors. As it is known, the cell cycle is regarded as a confounder when analyzing other factors in single-cell RNA-seq data, but it is not clear how it will work on the integrated single-cell multi-omics data. Here, a cell cycle-aware network (CCAN) is developed to remove cell cycle effects from the integrated single-cell multi-omics data while keeping the cell type-specific variations. This is the first computational model to study the cell-cycle effects in the integration of single-cell multi-omics data. Validations on several benchmark datasets show the outstanding performance of CCAN in a variety of downstream analyses and applications, including removing cell cycle effects and batch effects of scRNA-seq datasets from different protocols, integrating paired and unpaired scRNA-seq and scATAC-seq data, accurately transferring cell type labels from scRNA-seq to scATAC-seq data, and characterizing the differentiation process from hematopoietic stem cells to different lineages in the integration of differentiation data.

Concepts and new developments in droplet-based single cell multi-omics

Single cell sequencing technologies have become a fixture in the molecular profiling of cells due to their ease, flexibility, and commercial availability. In particular, partitioning individual cells inside oil droplets via microfluidic reactions enables transcriptomic or multi-omic measurements for thousands of cells in parallel. Complementing the multitude of biological discoveries from genomics analyses, the past decade has brought new capabilities from assay baselines to enable a deeper understanding of the complex data from single cell multi-omics. Here, we highlight four innovations that have improved the reliability and understanding of droplet microfluidic assays. We emphasize new developments that further orient principles of technology development and guidelines for the design, benchmarking, and implementation of new droplet-based methodologies.

Single-nucleus atlas of the Artemia female reproductive system suggests germline repression of the Z chromosome

Our understanding of the molecular pathways that regulate oogenesis and define cellular identity in the Arthropod female reproductive system and the extent of their conservation is currently very limited. This is due to the focus on model systems, including Drosophila and Daphnia, which do not reflect the observed diversity of morphologies, reproductive modes, and sex chromosome systems. We use single-nucleus RNA and ATAC sequencing to produce a comprehensive single nucleus atlas of the adult Artemia franciscana female reproductive system. We map our data to the Fly Cell Atlas single-nucleus dataset of the Drosophila melanogaster ovary, shedding light on the conserved regulatory programs between the two distantly related Arthropod species. We identify the major cell types known to be present in the Artemia ovary, including germ cells, follicle cells, and ovarian muscle cells. Additionally, we use the germ cells to explore gene regulation and expression of the Z chromosome during meiosis, highlighting its unique regulatory dynamics and allowing us to explore the presence of meiotic sex chromosome silencing in this group.

scaDA: A novel statistical method for differential analysis of single-cell chromatin accessibility sequencing data

Single-cell ATAC-seq sequencing data (scATAC-seq) has been widely used to investigate chromatin accessibility on the single-cell level. One important application of scATAC-seq data analysis is differential chromatin accessibility (DA) analysis. However, the data characteristics of scATAC-seq such as excessive zeros and large variability of chromatin accessibility across cells impose a unique challenge for DA analysis. Existing statistical methods focus on detecting the mean difference of the chromatin accessible regions while overlooking the distribution difference. Motivated by real data exploration that distribution difference exists among cell types, we introduce a novel composite statistical test named "scaDA", which is based on zero-inflated negative binomial model (ZINB), for performing differential distribution analysis of chromatin accessibility by jointly testing the abundance, prevalence and dispersion simultaneously. Benefiting from both dispersion shrinkage and iterative refinement of mean and prevalence parameter estimates, scaDA demonstrates its superiority to both ZINB-based likelihood ratio tests and published methods by achieving the highest power and best FDR control in a comprehensive simulation study. In addition to demonstrating the highest power in three real sc-multiome data analyses, scaDA successfully identifies differentially accessible regions in microglia from sc-multiome data for an Alzheimer's disease (AD) study that are most enriched in GO terms related to neurogenesis and the clinical phenotype of AD, and AD-associated GWAS SNPs.

Cohesin prevents cross-domain gene coactivation

The contrast between the disruption of genome topology after cohesin loss and the lack of downstream gene expression changes instigates intense debates regarding the structure-function relationship between genome and gene regulation. Here, by analyzing transcriptome and chromatin accessibility at the single-cell level, we discover that, instead of dictating population-wide gene expression levels, cohesin supplies a general function to neutralize stochastic coexpression tendencies of cis-linked genes in single cells. Notably, cohesin loss induces widespread gene coactivation and chromatin co-opening tens of million bases apart in cis. Spatial genome and protein imaging reveals that cohesin prevents gene co-bursting along the chromosome and blocks spatial mixing of transcriptional hubs. Single-molecule imaging shows that cohesin confines the exploration of diverse enhancer and core promoter binding transcriptional regulators. Together, these results support that cohesin arranges nuclear topology to control gene coexpression in single cells.

Regression convolutional neural network models implicate peripheral immune regulatory variants in the predisposition to Alzheimer's disease

Alzheimer's disease (AD) involves aggregation of amyloid β and tau, neuron loss, cognitive decline, and neuroinflammatory responses. Both resident microglia and peripheral immune cells have been associated with the immune component of AD. However, the relative contribution of resident and peripheral immune cell types to AD predisposition has not been thoroughly explored due to their similarity in gene expression and function. To study the effects of AD-associated variants on cis-regulatory elements, we train convolutional neural network (CNN) regression models that link genome sequence to cell type-specific levels of open chromatin, a proxy for regulatory element activity. We then use in silico mutagenesis of regulatory sequences to predict the relative impact of candidate variants across these cell types. We develop and apply criteria for evaluating our models and refine our models using massively parallel reporter assay (MPRA) data. Our models identify multiple AD-associated variants with a greater predicted impact in peripheral cells relative to microglia or neurons. Our results support their use as models to study the effects of AD-associated variants and even suggest that peripheral immune cells themselves may mediate a component of AD predisposition. We make our library of CNN models and predictions available as a resource for the community to study immune and neurological disorders.

Single-cell profiling reveals altered immune landscape and impaired NK cell function in gastric cancer liver metastasis

Gastric cancer (GC) is a substantial global health concern, and the development of liver metastasis (LM) in GC represents a critical stage linked to unfavorable patient prognoses. In this study, we employed single-cell RNA sequencing (scRNA-seq) to investigate the immune landscape of GC liver metastasis, revealing several immuno-suppressive components within the tumor immune microenvironment (TIM). Our findings unveiled an increased presence of cancer-associated fibroblasts (CAFs), myeloid-derived suppressor cell (MDSC)-like macrophages, tumor-associated macrophage (TAM)-like macrophages, and naive T cells, while conventional dendritic cells (cDCs) and effector CD8 T cells declined in LM. Additionally, we identified two distinct natural killer (NK) cell clusters exhibiting differential cytotoxicity-related gene expression, with cytotoxic NK cells notably reduced in LM. Strikingly, TGFβ was identified as an inducer of NK cell dysfunction, potentially contributing to immune evasion and tumor metastasis. In preclinical LM models, the combined approach of inhibiting TGFβ and transferring NK cells exhibited a synergistic impact, resulting in a significant reduction in liver metastasis. This work highlights the importance of understanding the complex immune dynamics within GC liver metastasis and presents a promising strategy combining TGFβ inhibition and NK-based immunotherapy to improve patient outcomes.

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.

Microfluidic Biochips for Single-Cell Isolation and Single-Cell Analysis of Multiomics and Exosomes

Single-cell multiomic and exosome analyses are potent tools in various fields, such as cancer research, immunology, neuroscience, microbiology, and drug development. They facilitate the in-depth exploration of biological systems, providing insights into disease mechanisms and aiding in treatment. Single-cell isolation, which is crucial for single-cell analysis, ensures reliable cell isolation and quality control for further downstream analyses. Microfluidic chips are small lightweight systems that facilitate efficient and high-throughput single-cell isolation and real-time single-cell analysis on- or off-chip. Therefore, most current single-cell isolation and analysis technologies are based on the single-cell microfluidic technology. This review offers comprehensive guidance to researchers across different fields on the selection of appropriate microfluidic chip technologies for single-cell isolation and analysis. This review describes the design principles, separation mechanisms, chip characteristics, and cellular effects of various microfluidic chips available for single-cell isolation. Moreover, this review highlights the implications of using this technology for subsequent analyses, including single-cell multiomic and exosome analyses. Finally, the current challenges and future prospects of microfluidic chip technology are outlined for multiplex single-cell isolation and multiomic and exosome analyses.

CellMag-CARWash: A High Throughput Droplet Microfluidic Device for Live Cell Isolation and Single Cell Applications

The recent push toward understanding an individual cell's behavior and identifying cellular heterogeneity has created an unmet need for technologies that can probe live cells at the single-cell level. Cells within a population are known to exhibit heterogeneous responses to environmental cues. These differences can lead to varied cellular states, behavior, and responses to therapeutics. Techniques are needed that are not only capable of processing and analyzing cellular populations at the single cell level, but also have the ability to isolate specific cell populations from a complex sample at high throughputs. The new CellMag-Coalesce-Attract-Resegment Wash (CellMag-CARWash) system combines positive magnetic selection with droplet microfluidic devices to isolate cells of interest from a mixture with >93% purity and incorporate treatments within individual droplets to observe single cell biological responses. This workflow is shown to be capable of probing the single cell extracellular vesicle (EV) secretion of MCF7 GFP cells. This article reports the first measurement of β-Estradiol's effect on EV secretion from MCF7 cells at the single cell level. Single cell processing revealed that MCF7 GFP cells possess a heterogeneous response to β-Estradiol stimulation with a 1.8-fold increase relative to the control.

Harnessing HetHydrogel: A Universal Platform to Dropletize Single-Cell Multiomics

A universal platform is developed for dropletizing single cell plate-based multiomic assays, consisting of three main pillars: a miniaturized open Heterogeneous Hydrogel reactor (abbreviated HetHydrogel) for multi-step biochemistry, its tunable permeability that allows Tn5 tagmentation, and single cell droplet barcoding. Through optimizing the HetHydrogel manufacturing procedure, the chemical composition, and cell permeation conditions, simultaneous high-throughput mitochondrial DNA genotyping and chromatin profiling at the single-cell level are demonstrated using a mixed-species experiment. This platform offers a powerful way to investigate the genotype-phenotype relationships of various mtDNA mutations in biological processes. The HetHydrogel platform is believed to have the potential to democratize droplet technologies, upgrading a whole range of plate-based single cell assays to high throughput format.

Building and analyzing metacells in single-cell genomics data

The advent of high-throughput single-cell genomics technologies has fundamentally transformed biological sciences. Currently, millions of cells from complex biological tissues can be phenotypically profiled across multiple modalities. The scaling of computational methods to analyze and visualize such data is a constant challenge, and tools need to be regularly updated, if not redesigned, to cope with ever-growing numbers of cells. Over the last few years, metacells have been introduced to reduce the size and complexity of single-cell genomics data while preserving biologically relevant information and improving interpretability. Here, we review recent studies that capitalize on the concept of metacells-and the many variants in nomenclature that have been used. We further outline how and when metacells should (or should not) be used to analyze single-cell genomics data and what should be considered when analyzing such data at the metacell level. To facilitate the exploration of metacells, we provide a comprehensive tutorial on the construction and analysis of metacells from single-cell RNA-seq data ( https://github.com/GfellerLab/MetacellAnalysisTutorial ) as well as a fully integrated pipeline to rapidly build, visualize and evaluate metacells with different methods ( https://github.com/GfellerLab/MetacellAnalysisToolkit ).