Systematic identification of cell-fate regulatory programs using a single-cell atlas of mouse development

Functional mapping of epigenetic regulators uncovers coordinated tumor suppression by the HBO1 and MLL1 complexes

Epigenetic dysregulation is widespread in cancer. However, the specific epigenetic regulators and the processes they control to drive cancer phenotypes are poorly understood. Here, we employed a novel, scalable and high-throughput in vivo method to perform iterative functional screens of over 250 epigenetic regulatory genes within autochthonous oncogenic KRAS-driven lung tumors. We identified multiple novel epigenetic tumor suppressor and tumor dependency genes. We show that a specific HBO1 complex and the MLL1 complex are among the most impactful tumor suppressive epigenetic regulators in lung. The histone modifications generated by the HBO1 complex are frequently absent or reduced in human lung adenocarcinomas. The HBO1 and MLL1 complexes regulate chromatin accessibility of shared genomic regions, lineage fidelity and the expression of canonical tumor suppressor genes. The HBO1 and MLL1 complexes are epistatic during lung tumorigenesis, and their functional correlation is conserved in human cancer cell lines. Together, these results demonstrate the value of quantitative methods to generate a phenotypic roadmap of epigenetic regulatory genes in tumorigenesis in vivo .

Age-dependent functional development pattern in neonatal brain: An fMRI-based brain entropy study

The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5-43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the 'S-A' axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.

aKNNO: single-cell and spatial transcriptomics clustering with an optimized adaptive k-nearest neighbor graph

Typical clustering methods for single-cell and spatial transcriptomics struggle to identify rare cell types, while approaches tailored to detect rare cell types gain this ability at the cost of poorer performance for grouping abundant ones. Here, we develop aKNNO to simultaneously identify abundant and rare cell types based on an adaptive k-nearest neighbor graph with optimization. Benchmarking on 38 simulated and 20 single-cell and spatial transcriptomics datasets demonstrates that aKNNO identifies both abundant and rare cell types more accurately than general and specialized methods. Using only gene expression aKNNO maps abundant and rare cells more precisely compared to integrative approaches.

Spatial transcriptomic profiling of isolated microregions in tissue sections utilizing laser-induced forward transfer

Profiling gene expression while preserving cell locations aids in the comprehensive understanding of cell fates in multicellular organisms. However, simple and flexible isolation of microregions of interest (mROIs) for spatial transcriptomics is still challenging. We present a laser-induced forward transfer (LIFT)-based method combined with a full-length mRNA-sequencing protocol (LIFT-seq) for profiling region-specific tissues. LIFT-seq demonstrated that mROIs from two adjacent sections could reliably and sensitively detect and display gene expression. In addition, LIFT-seq can identify region-specific mROIs in the mouse cortex and hippocampus. Finally, LIFT-seq identified marker genes in different layers of the cortex with very similar expression patterns. These genes were then validated using in situ hybridization (ISH) results. Therefore, LIFT-seq will be a valuable and efficient technique for profiling the spatial transcriptome in various tissues.

TagP, a PAAR-domain containing protein, plays roles in the fitness and virulence of Acinetobacter baumannii

Background

Type VI secretion system (T6SS) is widely present in Gram-negative bacteria and directly mediates antagonistic prokaryote interactions. PAAR (proline-alanine-alanine-arginine repeats) proteins have been proven essential for T6SS-mediated secretion and target cell killing. Although PAAR proteins are commonly found in A. baumannii, their biological functions are not fully disclosed yet. In this study, we investigated the functions of a PAAR protein termed TagP (T6SS-associated-gene PAAR), encoded by the gene ACX60_RS09070 outside the core T6SS locus of A. baumannii strain ATCC 17978.

Methods

In this study, tagP null and complement A. baumannii ATCC 17978 strains were constructed. The influence of TagP on T6SS function was investigated through Hcp detection and bacterial competition assay; the influence on environmental fitness was studied through in vitro growth, biofilm formation assay, surface motility assay, survivability in various simulated environmental conditions; the influence on pathogenicity was explored through cell adhesion and invasion assays, intramacrophage survival assay, serum survival assay, and G. melonella Killing assays. Quantitative transcriptomic and proteomic analyses were utilized to observe the global impact of TagP on bacterial status.

Results

Compared with the wildtype strain, the tagP null mutant was impaired in several tested phenotypes such as surface motility, biofilm formation, tolerance to adverse environments, adherence to eukaryotic cells, endurance to serum complement killing, and virulence to Galleria melonella. Notably, although RNA-Seq and proteomics analysis revealed that many genes were significantly down-regulated in the tagP null mutant compared to the wildtype strain, there is no significant difference in their antagonistic abilities. We also found that Histone-like nucleoid structuring protein (H-NS) was significantly upregulated in the tagP null mutant at both mRNA and protein levels.

Conclusions

This study enriches our understanding of the biofunction of PAAR proteins in A. baumannii. The results indicates that TagP involved in a unique modulation of fitness and virulence control in A. baumannii, it is more than a classic PAAR protein involved in T6SS, while how TagP play roles in the fitness and virulence of A. baumannii needs further investigation to clarify.

A single-cell atlas of chromatin accessibility in mouse organogenesis

Organogenesis is a highly complex and precisely regulated process. Here we profiled the chromatin accessibility in >350,000 cells derived from 13 mouse embryos at four developmental stages from embryonic day (E) 10.5 to E13.5 by SPATAC-seq in a single experiment. The resulting atlas revealed the status of 830,873 candidate cis-regulatory elements in 43 major cell types. By integrating the chromatin accessibility atlas with the previous transcriptomic dataset, we characterized cis-regulatory sequences and transcription factors associated with cell fate commitment, such as Nr5a2 in the development of gastrointestinal tract, which was preliminarily supported by the in vivo experiment in zebrafish. Finally, we integrated this atlas with the previous single-cell chromatin accessibility dataset from 13 adult mouse tissues to delineate the developmental stage-specific gene regulatory programmes within and across different cell types and identify potential molecular switches throughout lineage development. This comprehensive dataset provides a foundation for exploring transcriptional regulation in organogenesis.

Systems Genetics Analyses Reveals Key Genes Related to Behavioral Traits in the Striatum of CFW Mice

The striatum plays a central role in directing many complex behaviors ranging from motor control to action choice and reward learning. In our study, we used 55 male CFW mice with rapid decay linkage disequilibrium to systematically mine the striatum-related behavioral functional genes by analyzing their striatal transcriptomes and 79 measured behavioral phenotypic data. By constructing a gene coexpression network, we clustered the genes into 13 modules, with most of them being positively correlated with motor traits. Based on functional annotations as well as Fisher's exact and hypergeometric distribution tests, brown and magenta modules were identified as core modules. They were significantly enriched for striatal-related functional genes. Subsequent Mendelian randomization analysis verified the causal relationship between the core modules and dyskinesia. Through the intramodular gene connectivity analysis, Adcy5 and Kcnma1 were identified as brown and magenta module hub genes, respectively. Knock outs of both Adcy5 and Kcnma1 lead to motor dysfunction in mice, and KCNMA1 acts as a risk gene for schizophrenia and smoking addiction in humans. We also evaluated the cellular composition of each module and identified oligodendrocytes in the striatum to have a positive role in motor regulation.

Computational single-cell methods for predicting cancer risk

Despite recent biotechnological breakthroughs, cancer risk prediction remains a formidable computational and experimental challenge. Addressing it is critical in order to improve prevention, early detection and survival rates. Here, I briefly summarize some key emerging theoretical and computational challenges as well as recent computational advances that promise to help realize the goals of cancer-risk prediction. The focus is on computational strategies based on single-cell data, in particular on bottom-up network modeling approaches that aim to estimate cancer stemness and dedifferentiation at single-cell resolution from a systems-biological perspective. I will describe two promising methods, a tissue and cell-lineage independent one based on the concept of diffusion network entropy, and a tissue and cell-lineage specific one that uses transcription factor regulons. Application of these tools to single-cell and single-nucleus RNA-seq data from stages prior to invasive cancer reveal that they can successfully delineate the heterogeneous inter-cellular cancer-risk landscape, identifying those cells that are more likely to turn cancerous. Bottom-up systems biological modeling of single-cell omic data is a novel computational analysis paradigm that promises to facilitate the development of preventive, early detection and cancer-risk prediction strategies.

Precision Nanomedicine with Bio-Inspired Nanosystems: Recent Trends and Challenges in Mesenchymal Stem Cells Membrane-Coated Bioengineered Nanocarriers in Targeted Nanotherapeutics

In the recent past, the formulation and development of nanocarriers has been elaborated into the broader fields and opened various avenues in their preclinical and clinical applications. In particular, the cellular membrane-based nanoformulations have been formulated to surpass and surmount the limitations and restrictions associated with naïve or free forms of therapeutic compounds and circumvent various physicochemical and immunological barriers including but not limited to systemic barriers, microenvironmental roadblocks, and other cellular or subcellular hinderances-which are quite heterogeneous throughout the diseases and patient cohorts. These limitations in drug delivery have been overcome through mesenchymal cells membrane-based precision therapeutics, where these interventions have led to the significant enhancements in therapeutic efficacies. However, the formulation and development of nanocarriers still focuses on optimization of drug delivery paradigms with a one-size-fits-all resolutions. As mesenchymal stem cell membrane-based nanocarriers have been engineered in highly diversified fashions, these are being optimized for delivering the drug payloads in more and better personalized modes, entering the arena of precision as well as personalized nanomedicine. In this Review, we have included some of the advanced nanocarriers which have been designed and been utilized in both the non-personalized as well as precision applicability which can be employed for the improvements in precision nanotherapeutics. In the present report, authors have focused on various other aspects of the advancements in stem cells membrane-based nanoparticle conceptions which can surmount several roadblocks and barriers in drug delivery and nanomedicine. It has been suggested that well-informed designing of these nanocarriers will lead to appreciable improvements in the therapeutic efficacy in therapeutic payload delivery applications. These approaches will also enable the tailored and customized designs of MSC-based nanocarriers for personalized therapeutic applications, and finally amending the patient outcomes.

Periportal macrophages protect against commensal-driven liver inflammation

The liver is the main gateway from the gut, and the unidirectional sinusoidal flow from portal to central veins constitutes heterogenous zones, including the periportal vein (PV) and the pericentral vein zones1-5. However, functional differences in the immune system in each zone remain poorly understood. Here intravital imaging revealed that inflammatory responses are suppressed in PV zones. Zone-specific single-cell transcriptomics detected a subset of immunosuppressive macrophages enriched in PV zones that express high levels of interleukin-10 and Marco, a scavenger receptor that sequesters pro-inflammatory pathogen-associated molecular patterns and damage-associated molecular patterns, and consequently suppress immune responses. Induction of Marco+ immunosuppressive macrophages depended on gut microbiota. In particular, a specific bacterial family, Odoribacteraceae, was identified to induce this macrophage subset through its postbiotic isoallolithocholic acid. Intestinal barrier leakage resulted in inflammation in PV zones, which was markedly augmented in Marco-deficient conditions. Chronic liver inflammatory diseases such as primary sclerosing cholangitis (PSC) and non-alcoholic steatohepatitis (NASH) showed decreased numbers of Marco+ macrophages. Functional ablation of Marco+ macrophages led to PSC-like inflammatory phenotypes related to colitis and exacerbated steatosis in NASH in animal experimental models. Collectively, commensal bacteria induce Marco+ immunosuppressive macrophages, which consequently limit excessive inflammation at the gateway of the liver. Failure of this self-limiting system promotes hepatic inflammatory disorders such as PSC and NASH.

Transcription factor PBX4 regulates limb development and haematopoiesis in mice

The mammalian Pre-B cell leukaemia transcription factors 1-4 (PBX1-4) constitutes the PBC class of the homeodomain (HD)-containing proteins, which play important roles in diverse developmental processes. The functions and the underlying molecular mechanisms of PBX1-3 but not PBX4 have been extensively studied, and they have been reported to direct essential morphogenetic processes and organogenesis. In the present study, we generated knockin mice of FLAG-tagged PBX4 and the Pbx4 knockout (KO) mice and carried out in-depth characterisation of PBX4 expression and function. PBX4 was initially detected only in the testis among several organs of the adult mice and was expressed in spermatocytes and spermatids. However, no abnormality in spermatogenesis, but growth retardation and premature death after birth were observed in most adult Pbx4 KO mice. These animals were inactive and had shorter hindlimbs and lower numbers of reticulocytes and lymphocytes, probably caused by abnormalities at earlier developmental stages. Pbx4 mRNAs were indeed detected in several embryonic cell types related to limb development by in situ hybridisation and single-cell RNA-sequencing analysis. Pbx4 protein was also detected in the bone marrow of adult mice with a lower level compared with that in the testis. PBX4 preferentially binds to the promoters of a large number of genes including those for other HD-containing proteins and ribosomal proteins whose mutations are related to anaemia. PBX4-binding sites are enriched in motifs similar to those of other HD-containing proteins such as PKNOX1 indicating that PBX4 may also act as a co-transcription factor like other PBC proteins. Together, these results show that PBX4 participates in limb development and haematopoiesis while its function in spermatogenesis has not been revealed by gene KO probably due to the complementary effects of other genes.

PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes

Single-cell RNA sequencing (scRNA-seq) is a powerful approach for studying cellular differentiation, but accurately tracking cell fate transitions can be challenging, especially in disease conditions. Here we introduce PhyloVelo, a computational framework that estimates the velocity of transcriptomic dynamics by using monotonically expressed genes (MEGs) or genes with expression patterns that either increase or decrease, but do not cycle, through phylogenetic time. Through integration of scRNA-seq data with lineage information, PhyloVelo identifies MEGs and reconstructs a transcriptomic velocity field. We validate PhyloVelo using simulated data and Caenorhabditis elegans ground truth data, successfully recovering linear, bifurcated and convergent differentiations. Applying PhyloVelo to seven lineage-traced scRNA-seq datasets, generated using CRISPR-Cas9 editing, lentiviral barcoding or immune repertoire profiling, demonstrates its high accuracy and robustness in inferring complex lineage trajectories while outperforming RNA velocity. Additionally, we discovered that MEGs across tissues and organisms share similar functions in translation and ribosome biogenesis.

Xbp1 promotes odontoblastic differentiation through modulating mitochondrial homeostasis

Odontoblast differentiation depends on the orderly recruitment of transcriptional factors (TFs) in the transcriptional regulatory network. The depletion of crucial TFs disturbs dynamic alteration of the chromatin landscape and gene expression profile, leading to developmental defects. Our previous studies have revealed that the basic leucine zipper (bZIP) TF family is crucial in odontoblastic differentiation, but the function of bZIP TF family member XBP1 is still unknown. Here, we showed the stage-specific expression patterns of the spliced form Xbp1s during tooth development. Elevated Xbp1 expression and nuclear translocation of XBP1S in mesenchymal stem cells (MSCs) were induced by differentiation medium in vitro. Diminution of Xbp1 expression impaired the odontogenic differentiation potential of MSCs. The further integration of ATAC-seq and RNA-seq identified Hspa9 as a direct downstream target, an essential mitochondrial chaperonin gene that modulated mitochondrial homeostasis. The amelioration of mitochondrial dysfunction rescued the impaired odontogenic differentiation potential of MSCs caused by the diminution of Xbp1. Furthermore, the overexpression of Hspa9 rescued Xbp1-deficient defects in odontoblastic differentiation. Our study illustrates the crucial role of Xbp1 in odontoblastic differentiation via modulating mitochondrial homeostasis and brings evidence to the therapy of mitochondrial diseases caused by genetic defects.

Bioluminescence imaging of Cyp1a1-luciferase reporter mice demonstrates prolonged activation of the aryl hydrocarbon receptor in the lung

Aryl hydrocarbon receptor (AHR) signalling integrates biological processes that sense and respond to environmental, dietary, and metabolic challenges to ensure tissue homeostasis. AHR is a transcription factor that is inactive in the cytosol but upon encounter with ligand translocates to the nucleus and drives the expression of AHR targets, including genes of the cytochrome P4501 family of enzymes such as Cyp1a1. To dynamically visualise AHR activity in vivo, we generated reporter mice in which firefly luciferase (Fluc) was non-disruptively targeted into the endogenous Cyp1a1 locus. Exposure of these animals to FICZ, 3-MC or to dietary I3C induced strong bioluminescence signal and Cyp1a1 expression in many organs including liver, lung and intestine. Longitudinal studies revealed that AHR activity was surprisingly long-lived in the lung, with sustained Cyp1a1 expression evident in discrete populations of cells including columnar epithelia around bronchioles. Our data link diet to lung physiology and also reveal the power of bespoke Cyp1a1-Fluc reporters to longitudinally monitor AHR activity in vivo.

Construction of single-cell cross-species chromatin accessibility landscapes with combinatorial-hybridization-based ATAC-seq

Despite recent advances in single-cell genomics, the lack of maps for single-cell candidate cis-regulatory elements (cCREs) in non-mammal species has limited our exploration of conserved regulatory programs across vertebrates and invertebrates. Here, we developed a combinatorial-hybridization-based method for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) named CH-ATAC-seq, enabling the construction of single-cell accessible chromatin landscapes for zebrafish, Drosophila, and earthworms (Eisenia andrei). By integrating scATAC censuses of humans, monkeys, and mice, we systematically identified 152 distinct main cell types and around 0.8 million cell-type-specific cCREs. Our analysis provided insights into the conservation of neural, muscle, and immune lineages across species, while epithelial cells exhibited a higher organ-origin heterogeneity. Additionally, a large-scale gene regulatory network (GRN) was constructed in four vertebrates by integrating scRNA-seq censuses. Overall, our study provides a valuable resource for comparative epigenomics, identifying the evolutionary conservation and divergence of gene regulation across different species.

Cell-free genomics: transcription factor interactions in reconstituted naïve embryonic chromatin

Extracts from Drosophila preblastoderm embryos (DREX) form the basis of a powerful in vitro chromatin reconstitution system that assembles entire genomes into complex chromatin with physiological nucleosome spacing and polymer condensation. As the zygotic genome has not yet been activated in preblastoderm embryos, the reconstitution extract lacks endogenous transcription factors (TFs) and the RNA polymerase machinery. At the same time, it contains high levels of ATP-dependent nucleosome sliding enzymes that render the reconstituted chromatin dynamic. The naïve chromatin can be used to determine the intrinsic DNA binding properties of exogenous, usually recombinant TFs (or DNA binding proteins in general) in a complex chromatin context. Recent applications of the system include the description of cooperation and competition of Drosophila pioneer TFs for composite binding sites, and the characterization of nucleosome interactions of mammalian pioneer TFs in the heterologous system.

Mapping Cell Atlases at the Single-Cell Level

Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.

Distinct mast cell subpopulations within and around lymphatic vessels regulate lymph flow and progression of inflammatory-erosive arthritis in TNF-transgenic mice

Objective

Inflammatory-erosive arthritis is exacerbated by dysfunction of joint-draining popliteal lymphatic vessels (PLVs). Synovial mast cells are known to be pro-inflammatory in rheumatoid arthritis (RA). In other settings they have anti-inflammatory and tissue reparative effects. Herein, we elucidate the role of mast cells on PLV function and inflammatory-erosive arthritis in tumor necrosis factor transgenic (TNF-tg) mice that exhibit defects in PLVs commensurate with disease progression.

Methods

Whole mount immunofluorescent microscopy, toluidine blue stained histology, scanning electron microscopy, and in silico bioinformatics were performed to phenotype and quantify PLV mast cells. Ankle bone volumes were assessed by μCT, while corresponding histology quantified synovitis and osteoclasts. Near-infrared indocyanine green imaging measured lymphatic clearance as an outcome of PLV draining function. Effects of genetic MC depletion were assessed via comparison of 4.5-month-old WT, TNF-tg, MC deficient KitW-sh/W-sh (cKit-/-), and TNF-tg x cKit-/- mice. Pharmacological inhibition of mast cells was assessed by treating TNF-tg mice with placebo or cromolyn sodium (3.15mg/kg/day) for 3-weeks.

Results

PLVs are surrounded by MCT+/MCPT1+/MCPT4+ mast cells whose numbers are increased 2.8-fold in TNF-tg mice. The percentage of peri-vascular degranulating mast cells was inversely correlated with ICG clearance. A population of MCT+/MCPT1-/MCPT4- mast cells were embedded within the PLV structure. In silico single-cell RNA-seq (scRNAseq) analyses identified a population of PLV-associated mast cells (marker genes: Mcpt4, Cma1, Cpa3, Tpsb2, Kit, Fcer1a & Gata2) with enhanced TGFβ-related signaling that are phenotypically distinct from known MC subsets in the Mouse Cell Atlas. cKit-/- mice have greater lymphatic defects than TNF-tg mice with exacerbation of lymphatic dysfunction and inflammatory-erosive arthritis in TNF-tg x cKit-/- vs. TNF-Tg mice. Cromolyn sodium therapy stabilized PLV mast cells, increased TNF-induced bone loss, synovitis, and osteoclasts, and decreased ICG clearance.

Conclusions

Mast cells are required for normal lymphatic function. Genetic ablation and pharmacological inhibition of mast cells exacerbates TNF-induced inflammatory-erosive arthritis with decreased lymphatic clearance. Together, these findings support an inflammatory role of activated/degranulated peri-PLV mast cells during arthritic progression, and a homeostatic role of intra-PLV mast cells, in which loss of the latter dominantly exacerbates arthritis secondary to defects in joint-draining lymphatics, warranting investigation into specific cellular mechanisms.

Characterization of human pluripotent stem cell differentiation by single-cell dual-omics analyses

In vivo differentiation of human pluripotent stem cells (hPSCs) has unique advantages, such as multilineage differentiation, angiogenesis, and close cell-cell interactions. To systematically investigate multilineage differentiation mechanisms of hPSCs, we constructed the in vivo hPSC differentiation landscape containing 239,670 cells using teratoma models. We identified 43 cell types, inferred 18 cell differentiation trajectories, and characterized common and specific gene regulation patterns during hPSC differentiation at both transcriptional and epigenetic levels. Additionally, we developed the developmental single-cell Basic Local Alignment Search Tool (dscBLAST), an R-based cell identification tool, to simplify the identification processes of developmental cells. Using dscBLAST, we aligned cells in multiple differentiation models to normally developing cells to further understand their differentiation states. Overall, our study offers new insights into stem cell differentiation and human embryonic development; dscBLAST shows favorable cell identification performance, providing a powerful identification tool for developmental cells.

Single-cell and Spatial Transcriptomics Clustering with an Optimized Adaptive K-Nearest Neighbor Graph

Single-cell and spatial transcriptomics have been widely used to characterize cellular landscape in complex tissues. To understand cellular heterogeneity, one essential step is to define cell types through unsupervised clustering. While typical clustering methods have difficulty in identifying rare cell types, approaches specifically tailored to detect rare cell types gain their ability at the cost of poorer performance for grouping abundant ones. Here, we developed aKNNO, a method to identify abundant and rare cell types simultaneously based on an adaptive k-nearest neighbor graph with optimization. Benchmarked on 38 simulated and 20 single-cell and spatial transcriptomics datasets, aKNNO identified both abundant and rare cell types accurately. Without sacrificing performance for clustering abundant cell types, aKNNO discovered known and novel rare cell types that those typical and even specifically tailored methods failed to detect. aKNNO, using transcriptome alone, stereotyped fine-grained anatomical structures more precisely than those integrative approaches combining expression with spatial locations and histology image.

Dual-GCN-based deep clustering with triplet contrast for ScRNA-seq data analysis

Single-cell RNA sequencing (ScRNA-seq) technology reveals gene expression information at the cellular level. The critical tasks in ScRNA-seq data analysis are clustering and dimensionality reduction. Recent deep clustering algorithms are used to optimize the two tasks jointly, and their variations, graph-based deep clustering algorithms, are used to capture and preserve topological information in the process. However, the existing graph-based deep clustering algorithms ignore the distribution information of nodes when constructing cell graphs which leads to incomplete information in the embedding representation; and graph convolutional networks (GCN), which are most commonly used, often suffer from over-smoothing that leads to high sample similarity in the embedding representation and then poor clustering performance. Here, the dual-GCN-based deep clustering with Triplet contrast (scDGDC) is proposed for dimensionality reduction and clustering of scRNA-seq data. Two critical components are dual-GCN-based encoder for capturing more comprehensive topological information and triplet contrast for reducing GCN over-smoothing. The two components improve the dimensionality reduction and clustering performance of scDGDC in terms of information acquisition and model optimization, respectively. The experiments on eight real ScRNA-seq datasets showed that scDGDC achieves excellent performance for both clustering and dimensionality reduction tasks and is high robustness to parameters.

Entry receptor LDLRAD3 is required for Venezuelan equine encephalitis virus peripheral infection and neurotropism leading to pathogenesis in mice

Venezuelan equine encephalitis virus (VEEV) is an encephalitic alphavirus responsible for epidemics of neurological disease across the Americas. Low-density lipoprotein receptor class A domain-containing 3 (LDLRAD3) is a recently reported entry receptor for VEEV. Here, using wild-type and Ldlrad3-deficient mice, we define a critical role for LDLRAD3 in controlling steps in VEEV infection, pathogenesis, and neurotropism. Our analysis shows that LDLRAD3 is required for efficient VEEV infection and pathogenesis prior to and after central nervous system invasion. Ldlrad3-deficient mice survive intranasal and intracranial VEEV inoculation and show reduced infection of neurons in different brain regions. As LDLRAD3 is a determinant of pathogenesis and an entry receptor required for VEEV infection of neurons of the brain, receptor-targeted therapies may hold promise as countermeasures.

NF-kB's contribution to B cell fate decisions

NF-κB signaling is essential to an effective innate and adaptive immune response. Many immune-specific functional and developmental outcomes depend in large on NF-κB. The formidable task of sorting out the mechanisms behind the regulation and outcome of NF-κB signaling remains an important area of immunology research. Here we briefly discuss the role of NF-κB in regulating cell fate decisions at various times in the path of B cell development, activation, and the generation of long-term humoral immunity.

LY6D is crucial for lipid accumulation and inflammation in nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is a serious metabolic disorder characterized by excess fat accumulation in the liver. Over the past decade, NAFLD prevalence and incidence have risen globally. There are currently no effective licensed drugs for its treatment. Thus, further study is required to identify new targets for NAFLD prevention and treatment. In this study, we fed C57BL6/J mice one of three diets, a standard chow diet, high-sucrose diet, or high-fat diet, and then characterized them. The mice fed a high-sucrose diet had more severely compacted macrovesicular and microvesicular lipid droplets than those in the other groups. Mouse liver transcriptome analysis identified lymphocyte antigen 6 family member D (Ly6d) as a key regulator of hepatic steatosis and the inflammatory response. Data from the Genotype-Tissue Expression project database showed that individuals with high liver Ly6d expression had more severe NAFLD histology than those with low liver Ly6d expression. In AML12 mouse hepatocytes, Ly6d overexpression increased lipid accumulation, while Ly6d knockdown decreased lipid accumulation. Inhibition of Ly6d ameliorated hepatic steatosis in a diet-induced NAFLD mouse model. Western blot analysis showed that Ly6d phosphorylated and activated ATP citrate lyase, which is a key enzyme in de novo lipogenesis. In addition, RNA- and ATAC-sequencing analyses revealed that Ly6d drives NAFLD progression by causing genetic and epigenetic changes. In conclusion, Ly6d is responsible for the regulation of lipid metabolism, and inhibiting Ly6d can prevent diet-induced steatosis in the liver. These findings highlight Ly6d as a novel therapeutic target for NAFLD.

Single-cell and spatiotemporal transcriptomic analyses reveal the effects of microorganisms on immunity and metabolism in the mouse liver

The gut-liver axis is a complex bidirectional communication pathway between the intestine and the liver in which microorganisms and their metabolites flow from the intestine through the portal vein to the liver and influence liver function. In a sterile environment, the phenotype or function of the liver is altered, but few studies have investigated the specific cellular and molecular effects of microorganisms on the liver. To this end, we constructed single-cell and spatial transcriptomic (ST) profiles of germ-free (GF) and specific-pathogen-free (SPF) mouse livers. Single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq) revealed that the ratio of most immune cells was altered in the liver of GF mice; in particular, natural killer T (NKT) cells, IgA plasma cells (IgAs) and Kupffer cells (KCs) were significantly reduced in GF mice. Spatial enhanced resolution omics sequencing (Stereo-seq) confirmed that microorganisms mediated the accumulation of Kupffer cells in the periportal zone. Unexpectedly, IgA plasma cells were more numerous and concentrated in the periportal vein in liver sections from SPF mice but less numerous and scattered in GF mice. ST technology also enables the precise zonation of liver lobules into eight layers and three patterns based on the gene expression level in each layer, allowing us to further investigate the effects of microbes on gene zonation patterns and functions. Furthermore, untargeted metabolism experiments of the liver revealed that the propionic acid levels were significantly lower in GF mice, and this reduction may be related to the control of genes involved in bile acid and fatty acid metabolism. In conclusion, the combination of sc/snRNA-seq, Stereo-seq, and untargeted metabolomics revealed immune system defects as well as altered bile acid and lipid metabolic processes at the single-cell and spatial levels in the livers of GF mice. This study will be of great value for understanding host-microbiota interactions.

The increased cfRNA of TNFSF4 in peripheral blood at late gestation and preterm labor: its implication as a noninvasive biomarker for premature delivery

Introduction

Given the important roles of immune tolerance and inflammation in both preterm and term labor, some inflammation-related genes could be related to the initiation of labor, even preterm labor. Inspection of cell-free RNA (cfRNA) engaged in inflammation in maternal blood may represent the varied gestational age and may have significant implications for the development of noninvasive diagnostics for preterm birth.

Methods

To identify potential biomarkers of preterm birth, we investigated the cfRNA and exosomal miRNA in the peripheral blood of pregnant women at different gestational ages that undergo term labor or preterm labor. 17 inflammatory initiation-related cfRNAs were screened by overlapping with the targets of decreasing miRNAs during gestation and highly expressed cfRNAs at late gestation in maternal blood. To reveal the origins and mechanisms of these screened cfRNAs, the datasets of single-cell RNA sequencing from peripheral blood mononuclear cells of pregnant women, the fetal lung, and the placenta across different gestational ages were analyzed.

Results

During late gestation, TNFSF4 expression increased exclusively in pro-inflammatory macrophages of maternal blood, whereas its receptor, TNFRSF4, increased expression in T cells from the decidua, which suggested the potential cell-cell communication of maternally-originated pro-inflammatory macrophages with the decidual T cells and contributed to the initiation of labor. Additionally, the cfRNA of TNFSF4 was also increased in preterm labor compared to term labor in the validation cohorts. The EIF2AK2 and TLR4 transcripts were increased in pro-inflammatory macrophages from both fetal lung and placenta but not in those from maternal mononuclear cells at late gestation, suggesting these cfRNAs are possibly derived from fetal tissues exclusively. Moreover, EIF2AK2 and TLR4 transcripts were found highly expressed in the pro-inflammatory macrophages from decidua as well, which suggested these specific fetal-origin macrophages may function at the maternal-fetal interface to stimulate uterine contractions, which have been implicated as the trigger of parturition and preterm labor.

Discussion

Taken together, our findings not only revealed the potential of peripheral TNFSF4 as a novel cfRNA biomarker for noninvasive testing of preterm labor but further illustrated how maternal and fetal signals coordinately modulate the inflammatory process at the maternal-fetal interface, causing the initiation of term or preterm labor.

Lacking ARHGAP25 mitigates the symptoms of autoantibody-induced arthritis in mice

Objective

Despite intensive research on rheumatoid arthritis, the pathomechanism of the disease is still not fully understood and the treatment has not been completely resolved. Previously we demonstrated that the GTPase-activating protein, ARHGAP25 has a crucial role in the regulation of basic phagocyte functions. Here we investigate the role of ARHGAP25 in the complex inflammatory process of autoantibody-induced arthritis.

Methods

Wild-type and ARHGAP25 deficient (KO) mice on a C57BL/6 background, as well as bone marrow chimeric mice, were treated i.p. with the K/BxN arthritogenic or control serum, and the severity of inflammation and pain-related behavior was measured. Histology was prepared, leukocyte infiltration, cytokine production, myeloperoxidase activity, and superoxide production were determined, and comprehensive western blot analysis was conducted.

Results

In the absence of ARHGAP25, the severity of inflammation, joint destruction, and mechanical hyperalgesia significantly decreased, similarly to phagocyte infiltration, IL-1β, and MIP-2 levels in the tibiotarsal joint, whereas superoxide production or myeloperoxidase activity was unchanged. We observed a significantly mitigated phenotype in KO bone marrow chimeras as well. In addition, fibroblast-like synoviocytes showed comparable expression of ARHGAP25 to neutrophils. Significantly reduced ERK1/2, MAPK, and I-κB protein signals were detected in the arthritic KO mouse ankles.

Conclusion

Our findings suggest that ARHGAP25 has a key role in the pathomechanism of autoantibody-induced arthritis in which it regulates inflammation via the I-κB/NF-κB/IL-1β axis with the involvement of both immune cells and fibroblast-like synoviocytes.

Zebrafish as outgroup model to study evolution of scavenger receptor class B type I functions

BACKGROUND AND AIMS

Scavenger receptor class B1 (SCARB1) - also known as the high-density lipoprotein (HDL) receptor - is a multi-ligand scavenger receptor that is primarily expressed in liver and steroidogenic organs. This receptor is known for its function in reverse cholesterol transport (RCT) in mammals and hence disruption leads to a massive increase in HDL cholesterol in these species. The extracellular domain of SCARB1 - which is important for cholesterol handling - is highly conserved across multiple vertebrates, except in zebrafish.

METHODS

To examine the functional conservation of SCARB1 among vertebrates, two stable scarb1 knockout zebrafish lines, scarb1 715delA (scarb1 -1 nt) and scarb1 715_716insGG (scarb1 +2 nt), were created using CRISPR-Cas9 technology.

RESULTS

We demonstrate that, in zebrafish, SCARB1 deficiency leads to disruption of carotenoid-based pigmentation, reduced fertility, and a decreased larvae survival rate, whereas steroidogenesis was unaltered. The observed reduced fertility is driven by defects in female fertility (-50 %, p < 0.001). Importantly, these alterations were independent of changes in free (wild-type 2.4 ± 0.2 μg/μl versus scarb1^-/- 2.0 ± 0.1 μg/μl) as well as total (wild-type 4.2 ± 0.4 μg/μl versus scarb1^-/- 4.0 ± 0.3 μg/μl) plasma cholesterol levels. Uptake of HDL in the liver of scarb1^-/- zebrafish larvae was reduced (-86.7 %, p < 0.001), but this coincided with reduced perfusion of the liver. No effect was observed on lipoprotein uptake in the caudal vein. SCARB1 deficient canaries, which also lack carotenoids in their plumage, similarly as scarb1^-/- zebrafish, failed to show an increase in plasma free- and total cholesterol levels.

CONCLUSION

Our findings suggest that the specific function of SCARB1 in maintaining plasma cholesterol could be an evolutionary novelty that became prominent in mammals, while other known functions were already present earlier during vertebrate evolution.

Construction of a cross-species cell landscape at single-cell level

Individual cells are basic units of life. Despite extensive efforts to characterize the cellular heterogeneity of different organisms, cross-species comparisons of landscape dynamics have not been achieved. Here, we applied single-cell RNA sequencing (scRNA-seq) to map organism-level cell landscapes at multiple life stages for mice, zebrafish and Drosophila. By integrating the comprehensive dataset of > 2.6 million single cells, we constructed a cross-species cell landscape and identified signatures and common pathways that changed throughout the life span. We identified structural inflammation and mitochondrial dysfunction as the most common hallmarks of organism aging, and found that pharmacological activation of mitochondrial metabolism alleviated aging phenotypes in mice. The cross-species cell landscape with other published datasets were stored in an integrated online portal-Cell Landscape. Our work provides a valuable resource for studying lineage development, maturation and aging.

Multi-omics profiling visualizes dynamics of cardiac development and functions

Cardiogenesis is a tightly regulated dynamic process through a continuum of differentiation and proliferation events. Key factors and pathways governing this process remain incompletely understood. Here, we investigate mice hearts from embryonic day 10.5 to postnatal week 8 and dissect developmental changes in phosphoproteome-, proteome-, metabolome-, and transcriptome-encompassing cardiogenesis and cardiac maturation. We identify mitogen-activated protein kinases as core kinases involved in transcriptional regulation by mediating the phosphorylation of chromatin remodeling proteins during early cardiogenesis. We construct the reciprocal regulatory network of transcription factors (TFs) and identify a series of TFs controlling early cardiogenesis involved in cycling-dependent proliferation. After birth, we identify cardiac resident macrophages with high arachidonic acid metabolism activities likely involved in the clearance of injured apoptotic cardiomyocytes. Together, our comprehensive multi-omics data offer a panoramic view of cardiac development and maturation that provides a resource for further in-depth functional exploration.

Multi-Transcriptomic Analysis Reveals the Heterogeneity and Tumor-Promoting Role of SPP1/CD44-Mediated Intratumoral Crosstalk in Gastric Cancer

GC is a fatal disease with high heterogeneity and invasiveness. Recently, SPP1 has been reported to be involved in the tumor progression of multiple human cancers; however, the role of SPP1 in GC heterogeneity and whether it is associated with the invasiveness and mortality of GC remain unclear. Here, we combined multiple RNA sequencing approaches to evaluate the impact of SPP1 on GC. Through bulk RNA sequencing (bulk RNA-seq) and immunohistochemistry (IHC), we found that SPP1 was highly expressed in GC, and high levels of SPP1 were associated with macrophage infiltration, an advanced tumor stage, and higher mortality for advanced GC patients. Furthermore, through simultaneous single-cell and spatial analysis, we demonstrated that SPP1⁺ macrophages are tumor-specific macrophages unique to cancer and enriched in the deep layer of GC tissue. Cell-cell communication analysis revealed that SPP1/CD44 interactions between SPP1⁺ macrophages and their localized tumor epithelial cells could activate downstream target genes in epithelial cells to promote dynamic changes in intratumor heterogeneity. Moreover, these activated genes were found to be closely associated with poor clinical GC outcomes and with cancer-related pathways that promote GC progression, as shown by survival analysis and enrichment analysis, respectively. Collectively, our study reveals that tumor-specific SPP1⁺ macrophages drive the architecture of intratumor heterogeneity to evolve with tumor progression and that SPP1 may serve as a prognostic marker for advanced GC patients, as well as a potential therapeutic target for GC.

Secuer: Ultrafast, scalable and accurate clustering of single-cell RNA-seq data

Identifying cell clusters is a critical step for single-cell transcriptomics study. Despite the numerous clustering tools developed recently, the rapid growth of scRNA-seq volumes prompts for a more (computationally) efficient clustering method. Here, we introduce Secuer, a Scalable and Efficient speCtral clUstERing algorithm for scRNA-seq data. By employing an anchor-based bipartite graph representation algorithm, Secuer enjoys reduced runtime and memory usage over one order of magnitude for datasets with more than 1 million cells. Meanwhile, Secuer also achieves better or comparable accuracy than competing methods in small and moderate benchmark datasets. Furthermore, we showcase that Secuer can also serve as a building block for a new consensus clustering method, Secuer-consensus, which again improves the runtime and scalability of state-of-the-art consensus clustering methods while also maintaining the accuracy. Overall, Secuer is a versatile, accurate, and scalable clustering framework suitable for small to ultra-large single-cell clustering tasks.

Determination of the nanoparticle- and cell-specific toxicological mechanisms in 3D liver spheroids using scRNAseq analysis

Engineered nanomaterials (ENMs) are commonly used in consumer products, allowing exposure to target organs such as the lung, liver, and skin that could lead to adverse health effects in humans. To better reflect on toxicological effects in liver cells, it is important to consider the contribution of hepatocyte morphology, function, and intercellular interactions in a dynamic 3D microenvironment. Herein, we used a 3D liver spheroid model containing hepatocyte and Kupffer cells (KCs) to study the effects of three different material compositions, namely vanadium pentoxide (V2O5), titanium dioxide (TiO2), or graphene oxide (GO). Additionally, we used single-cell RNA sequencing (scRNAseq) to determine the nanoparticle (NP) and cell-specific toxicological responses. A general finding was that hepatocytes exhibit more variation in gene expression and adaptation of signaling pathways than KCs. TNF-α production tied to the NF-κB pathway was a commonly affected pathway by all NPs while impacts on the metabolic function of hepatocytes were unique to V2O5. V2O5 NPs also showed the largest number of differentially expressed genes in both cell types, many of which are related to pro-inflammatory and apoptotic response pathways. There was also evidence of mitochondrial ROS generation and caspase-1 activation after GO and V2O5 treatment, in association with cytokine production. All considered, this study provides insight into the impact of nanoparticles on gene responses in key liver cell types, providing us with a scRNAseq platform that can be used for high-content screening of nanomaterial impact on the liver, for use in biosafety and biomedical applications.

TEDD: a database of temporal gene expression patterns during multiple developmental periods in human and model organisms

Characterization of the specific expression and chromatin profiles of genes enables understanding how they contribute to tissue/organ development and the mechanisms leading to diseases. Whilst the number of single-cell sequencing studies is increasing dramatically; however, data mining and reanalysis remains challenging. Herein, we systematically curated the up-to-date and most comprehensive datasets of sequencing data originating from 2760 bulk samples and over 5.1 million single-cells from multiple developmental periods from humans and multiple model organisms. With unified and systematic analysis, we profiled the gene expression and chromatin accessibility among 481 cell-types, 79 tissue-types and 92 timepoints, and pinpointed cells with the co-expression of target genes. We also enabled the detection of gene(s) with a temporal and cell-type specific expression profile that is similar to or distinct from that of a target gene. Additionally, we illustrated the potential upstream and downstream gene-gene regulation interactions, particularly under the same biological process(es) or KEGG pathway(s). Thus, TEDD (Temporal Expression during Development Database), a value-added database with a user-friendly interface, not only enables researchers to identify cell-type/tissue-type specific and temporal gene expression and chromatin profiles but also facilitates the association of genes with undefined biological functions in development and diseases. The database URL is https://TEDD.obg.cuhk.edu.hk/.

Lineage Landscape: a comprehensive database that records lineage commitment across species

Commitment to specific cell lineages is critical for mammalian embryonic development. Lineage determination, differentiation, maintenance, and organogenesis result in diverse life forms composed of multiple cell types. To understand the formation and maintenance of living individuals, including human beings, a comprehensive database that integrates multi-omic information underlying lineage differentiation across multiple species is urgently needed. Here, we construct Lineage Landscape, a database that compiles, analyzes and visualizes transcriptomic and epigenomic information related to lineage development in a collection of species. This landscape draws together datasets that capture the ongoing changes in cell lineages from classic model organisms to human beings throughout embryonic, fetal, adult, and aged stages, providing comprehensive, open-access information that is useful to researchers of a broad spectrum of life science disciplines. Lineage Landscape contains single-cell gene expression and bulk transcriptomic, DNA methylation, histone modifications, and chromatin accessibility profiles. Using this database, users can explore genes of interest that exhibit dynamic expression patterns at the transcriptional or epigenetic levels at different stages of lineage development. Lineage Landscape currently includes over 6.6 million cells, 15 million differentially expressed genes and 36 million data entries across 10 species and 34 organs. Lineage Landscape is free to access, browse, search, and download at http://data.iscr.ac.cn/lineage/#/home.

Single-cell transcriptomics to understand the cellular heterogeneity in toxicology

Background

Identification of molecular signatures from omics studies is widely applied in toxicological studies, and the evaluation of potential toxic effects provides novel insights into molecular resolution.

Objective

The prediction of toxic effects and drug tolerance provides important clues regarding the mode of action of target compounds. However, heterogeneity within samples makes toxicology studies challenging because the purity of the target cell in the samples remains unknown until their actual utilization.

Result

Single-cell resolution studies have been suggested in toxicogenomics, and several studies have explained toxic effects and drug tolerance using heterogeneous cells in both in vivo and in vitro conditions. In this review, we presented an understanding of single-cell transcriptomes and their applications in toxicogenomics.

Conclusion

The most toxicological mechanism in organisms occurs through intramolecular combinations, and heterogeneity issues have reached a surmountable level. We hope this review provides insights to successfully conduct future studies on toxicology.

Purpose of the review

Toxicogenomics is an interdisciplinary field between toxicology and genomics that was successfully applied to construct molecular profiles in a broad spectrum of toxicology. However, heterogeneity within samples makes toxicology studies challenging because the purity of target cell in the samples remains unknown until their actual utilisation. In this review, we presented an understanding of single-cell transcriptomes and their applications in toxicogenomics.

Recent findings

A high-throughput techniques have been used to understand cellular heterogeneity and molecular mechanisms at toxicogenomics. Single-cell resolution analysis is required to identify biomarkers of explain toxic effect and in order to understand drug tolerance.