Single-cell mRNA quantification and differential analysis with Census

Single-cell RNA-Seq reveals the earliest lineage specification and X chromosome dosage compensation in bovine preimplantation embryos

Lineage specification and X chromosome dosage compensation are two crucial biological processes that occur during preimplantation embryonic development. Although extensively studied in mice, the timing and regulation of these processes remain elusive in other species, including humans. Previous studies have suggested conserved principles of human and bovine early development. This study aims to provide fundamental insights into these programs and the regulation using a bovine embryo model by employing single-cell transcriptomics and genome editing approaches. The study analyzes the transcriptomes of 286 individual cells and reveals that bovine trophectoderm/inner cell mass transcriptomes diverge at the early blastocyst stage, after cavitation but before blastocyst expansion. The study also identifies transcriptomic markers and provides the timing of lineage specification events in the bovine embryo. Importantly, we find that SOX2 is required for the first cell decision program in bovine embryos. Moreover, the study shows the occurrence of X chromosome dosage compensation from morula to late blastocyst and reveals that this compensation results from downregulation of X-linked genes in female embryonic cells. The transcriptional atlas generated by this study is expected to be widely useful in improving our understanding of mammalian early embryo development.

Integrative single-cell transcriptomic analyses reveal the cellular ontological and functional heterogeneities of primary and metastatic liver tumors

BACKGROUND

The global cellular landscape of the tumor microenvironment (TME) combining primary and metastatic liver tumors has not been comprehensively characterized.

METHODS

Based on the scRNA-seq and spatial transcriptomic data of non-tumor liver tissues (NTs), primary liver tumors (PTs) and metastatic liver tumors (MTs), we performed the tissue preference, trajectory reconstruction, transcription factor activity inference, cell-cell interaction and cellular deconvolution analyses to construct a comprehensive cellular landscape of liver tumors.

RESULTS

Our analyses depicted the heterogeneous cellular ecosystems in NTs, PTs and MTs. The activated memory B cells and effector T cells were shown to gradually shift to inhibitory B cells, regulatory or exhausted T cells in liver tumors, especially in MTs. Among them, we characterized a unique group of TCF7+ CD8+ memory T cells specifically enriched in MTs that could differentiate into exhausted T cells likely driven by the p38 MAPK signaling. With regard to myeloid cells, the liver-resident macrophages and inflammatory monocyte/macrophages were markedly replaced by tumor-associated macrophages (TAMs), with TREM2+ and UBE2C+ TAMs enriched in PTs, while SPP1+ and WDR45B+ TAMs in MTs. We further showed that the newly identified WDR45B+ TAMs exhibit an M2-like polarization and are associated with adverse prognosis in patients with liver metastases. Additionally, we addressed that endothelial cells display higher immune tolerance and angiogenesis capacity, and provided evidence for the source of the mesenchymal transformation of fibroblasts in tumors. Finally, the malignant hepatocytes and fibroblasts were prioritized as the pivotal cell populations in shaping the microenvironments of PTs and MTs, respectively. Notably, validation analyses by using spatial or bulk transcriptomic data in clinical cohorts concordantly emphasized the clinical significance of these findings.

CONCLUSIONS

This study defines the ontological and functional heterogeneities in cellular ecosystems of primary and metastatic liver tumors, providing a foundation for future investigation of the underlying cellular mechanisms.

Selective induction of human renal interstitial progenitor-like cell lineages from iPSCs reveals development of mesangial and EPO-producing cells

Recent regenerative studies using human pluripotent stem cells (hPSCs) have developed multiple kidney-lineage cells and organoids. However, to further form functional segments of the kidney, interactions of epithelial and interstitial cells are required. Here we describe a selective differentiation of renal interstitial progenitor-like cells (IPLCs) from human induced pluripotent stem cells (hiPSCs) by modifying our previous induction method for nephron progenitor cells (NPCs) and analyzing mouse embryonic interstitial progenitor cell (IPC) development. Our IPLCs combined with hiPSC-derived NPCs and nephric duct cells form nephrogenic niche- and mesangium-like structures in vitro. Furthermore, we successfully induce hiPSC-derived IPLCs to differentiate into mesangial and erythropoietin-producing cell lineages in vitro by screening differentiation-inducing factors and confirm that p38 MAPK, hypoxia, and VEGF signaling pathways are involved in the differentiation of mesangial-lineage cells. These findings indicate that our IPC-lineage induction method contributes to kidney regeneration and developmental research.

Characterizing CD8+ TEMRA Cells in CP/CPPS Patients: Insights from Targeted Single-Cell Transcriptomic and Functional Investigations

Background

The specific involvement of the CD8+ T effector memory RA (TEMRA) subset in patients with chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) has largely not been explored in the literature.

Methods

Targeted single-cell RNA sequencing (scRNA-seq) profiles were generated from peripheral blood mononuclear cells (PBMCs) obtained from two CP/CPPS patients and two healthy controls (HCs) in our recent study. Pseudotime series algorithms were used to reveal the differentiation trajectory, CellChat analysis was used to explore the communication between individual cells, and the SCENIC program was used to identify potential transcription factors (TFs). Based on the cosine similarity, clusters of differentially expressed genes (DEGs) were considered to be further enriched in different pathways. To confirm the functional role of the critical clusters, flow cytometry was employed.

Results

The results revealed the molecular landscape of these clusters, with TEMRA cells exhibiting pronounced cytokine-mediated signaling pathway enrichment. Pseudotime trajectory analysis further mapped the evolution from naïve T cells to that of TEMRA cells, elucidating the developmental pathways involved in the immune context. A significant finding from CellChat analysis was the differential expression of ligands and receptors, with CD8+ TEMRA cells showing enhanced signaling, particularly in the CP/CPPS context, compared to HCs. Flow cytometry confirmed these results, revealing a heightened proinflammatory cytokine profile in patients with chronic prostatitis-like symptoms (CP-LS), suggesting that TEMRA cells play a significant role in disease pathogenesis. TF profiling across the T-cell clusters identified key regulators of cellular identity, identifying novel therapeutic targets. Elevated TNF signaling activity in CD8+ TEMRA cells underscored the involvement of these cells in disease mechanisms.

Conclusion

This study elucidates the pivotal role of the CD8+ TEMRA cell subset in CP/CPPS, which is characterized by increased TNF signaling and proinflammatory factor expression, highlighting potential biomarkers and opening new avenues for therapeutic intervention.

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

Cellular hierarchy insights reveal leukemic stem-like cells and early death risk in acute promyelocytic leukemia

Acute promyelocytic leukemia (APL) represents a paradigm for targeted differentiation therapy, with a minority of patients experiencing treatment failure and even early death. We here report a comprehensive single-cell analysis of 16 APL patients, uncovering cellular compositions and their impact on all-trans retinoic acid (ATRA) response in vivo and early death. We unveil a cellular differentiation hierarchy within APL blasts, rooted in leukemic stem-like cells. The oncogenic PML/RARα fusion protein exerts branch-specific regulation in the APL trajectory, including stem-like cells. APL cohort analysis establishes an association of leukemic stemness with elevated white blood cell counts and FLT3-ITD mutations. Furthermore, we construct an APL-specific stemness score, which proves effective in assessing early death risk. Finally, we show that ATRA induces differentiation of primitive blasts and patients with early death exhibit distinct stemness-associated transcriptional programs. Our work provides a thorough survey of APL cellular hierarchies, offering insights into cellular dynamics during targeted therapy.

A comprehensive bioinformatics analysis identifies mitophagy biomarkers and potential Molecular mechanisms in hypertensive nephropathy

Mitophagy, the selective removal of damaged mitochondria, plays a critical role in kidney diseases, but its involvement in hypertensive nephropathy (HTN) is not well understood. To address this gap, we investigated mitophagy-related genes in HTN, identifying potential biomarkers for diagnosis and treatment. Transcriptome datasets from the Gene Expression Omnibus database were analyzed, resulting in the identification of seven mitophagy related differentially expressed genes (MR-DEGs), namely PINK1, ULK1, SQSTM1, ATG5, ATG12, MFN2, and UBA52. Further, we explored the correlation between MR-DEGs, immune cells, and inflammatory factors. The identified genes demonstrated a strong correlation with Mast cells, T-cells, TGFβ3, IL13, and CSF3. Machine learning techniques were employed to screen important genes, construct diagnostic models, and evaluate their accuracy. Consensus clustering divided the HTN patients into two mitophagy subgroups, with Subgroup 2 showing higher levels of immune cell infiltration and inflammatory factors. The functions of their proteins primarily involve complement, coagulation, lipids, and vascular smooth muscle contraction. Single-cell RNA sequencing revealed that mitophagy was most significant in proximal tubule cells (PTC) in HTN patients. Pseudotime analysis of PTC confirmed the expression changes observed in the transcriptome. Intercellular communication analysis suggested that mitophagy might regulate PTC's participation in intercellular crosstalk. Notably, specific transcription factors such as HNF4A, PPARA, and STAT3 showed strong correlations with mitophagy-related genes in PTC, indicating their potential role in modulating PTC function and influencing the onset and progression of HTN. This study offers a comprehensive analysis of mitophagy in HTN, enhancing our understanding of the pathogenesis, diagnosis, and treatment of HTN.Communicated by Ramaswamy H. Sarma.

Single-cell analysis of uterosacral ligament revealed cellular heterogeneity in women with pelvic organ prolapse

Pelvic organ prolapse (POP) markedly affects the quality of life of women, including significant financial burden. Using single-cell RNA sequencing, we constructed a transcriptional profile of 30,452 single cells of the uterosacral ligament in POP and control samples, which has never been constructed before. We identified 10 major cell types, including smooth muscle cells, endothelial cells, fibroblasts, neutrophils, macrophages, monocytes, mast cells, T cells, B cells, and dendritic cells. We performed subpopulation analysis and pseudo-time analysis of POP primary cells, and explored differentially expressed genes. We verified previous cell clusters of human neutrophils of uterosacral ligaments. We found a significant reduction in receptor-ligand pairs related to ECM and cell adhesion between fibroblasts and endothelial cells in POP. The transcription factors related to the extracellular matrix, development, and immunity were identified in USL. Here we provide insight into the molecular mechanisms of POP and valuable information for future research directions.

Aneuploid embryonic stem cells drive teratoma metastasis

Aneuploidy, a deviation of the chromosome number from euploidy, is one of the hallmarks of cancer. High levels of aneuploidy are generally correlated with metastasis and poor prognosis in cancer patients. However, the causality of aneuploidy in cancer metastasis remains to be explored. Here we demonstrate that teratomas derived from aneuploid murine embryonic stem cells (ESCs), but not from isogenic diploid ESCs, disseminated to multiple organs, for which no additional copy number variations were required. Notably, no cancer driver gene mutations were identified in any metastases. Aneuploid circulating teratoma cells were successfully isolated from peripheral blood and showed high capacities for migration and organ colonization. Single-cell RNA sequencing of aneuploid primary teratomas and metastases identified a unique cell population with high stemness that was absent in diploid ESCs-derived teratomas. Further investigation revealed that aneuploid cells displayed decreased proteasome activity and overactivated endoplasmic reticulum (ER) stress during differentiation, thereby restricting the degradation of proteins produced from extra chromosomes in the ESC state and causing differentiation deficiencies. Noticeably, both proteasome activator Oleuropein and ER stress inhibitor 4-PBA can effectively inhibit aneuploid teratoma metastasis.

CD38 promotes hematopoietic stem cell dormancy

A subpopulation of deeply quiescent, so-called dormant hematopoietic stem cells (dHSCs) resides at the top of the hematopoietic hierarchy and serves as a reserve pool for HSCs. The state of dormancy protects the HSC pool from exhaustion throughout life; however, excessive dormancy may prevent an efficient response to hematological stresses. Despite the significance of dHSCs, the mechanisms maintaining their dormancy remain elusive. Here, we identify CD38 as a novel and broadly applicable surface marker for the enrichment of murine dHSCs. We demonstrate that cyclic adenosine diphosphate ribose (cADPR), the product of CD38 cyclase activity, regulates the expression of the transcription factor c-Fos by increasing the release of Ca2+ from the endoplasmic reticulum (ER). Subsequently, we uncover that c-Fos induces the expression of the cell cycle inhibitor p57Kip2 to drive HSC dormancy. Moreover, we found that CD38 ecto-enzymatic activity at the neighboring CD38-positive cells can promote human HSC quiescence. Together, CD38/cADPR/Ca2+/c-Fos/p57Kip2 axis maintains HSC dormancy. Pharmacological manipulations of this pathway can provide new strategies to improve the success of stem cell transplantation and blood regeneration after injury or disease.

SPP1+ TAM subpopulations in tumor microenvironment promote intravasation and metastasis of head and neck squamous cell carcinoma

Macrophages are heterogeneous cells that play multifaceted roles in cancer progression and metastasis. However, the phenotypic diversity of tumor-associated macrophages (TAMs) in head and neck squamous carcinomas (HNSCC) remains poorly characterized. Here, we comprehensively analyzed the HNSCC single-cell transcriptomic dataset (GSE172577) and identified 5 subsets of myeloid-driven cells as TAMs using Seurat. Deciphering the lineage trajectory of TAMs, we revealed that FCN1+ TAMs could give rise to pro-angiogenesis SPP1+CCL18+ and SPP1+FOLR2+ populations through SPP1-CCL18+ and CXCL9+CXCL10+ TAMs. SPP1+CCL18+ and SPP1+FOLR2+ TAMs harbored pro-angiogenic and metastatic transcriptional programs and were correlated with poor survival of HNSCC patients. Our immunostaining examination revealed that infiltration of SPP1+ TAMs is associated with lymph node metastasis and poor prognosis in patients with HNSCC. Cell-cell communication analysis implied that SPP1+ TAM populations may employ SPP1 signaling to activate metastasis-related ECs. In vitro and in vivo studies, we demonstrated that SPP1hi TAMs enhanced tumor intravasation and metastasis in HNSCC in a manner dependent on the secretion of SPP1, CCL18, and CXCL8. Taken together, our study characterized the cellular heterogeneity of TAM populations and identified two SPP1+ TAM populations that play key roles in HNSCC intravasation and metastasis and serve as predictive markers for patients with HNSCC.

Analytical Workflows for Single-Cell Multiomic Data Using the BD Rhapsody Platform

The conversion of raw sequencing reads to biologically relevant data in high-throughput single-cell RNA sequencing experiments is a complex and involved process. Drawing meaning from thousands of individual cells to provide biological insight requires ensuring not only that the data are of the highest quality but also that the signal can be separated from noise. In this article, we describe a detailed analytical workflow, including six pipelines, that allows high-quality data analysis in single-cell multiomics. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Image analysis Basic Protocol 2: Sequencing quality control and generation of a gene expression matrix Basic Protocol 3: Gene expression matrix data pre-processing and analysis Basic Protocol 4: Advanced analysis Basic Protocol 5: Conversion to flow cytometry standard (FCS) format Basic Protocol 6: Visualization using graphical interfaces.

Transcriptome network analysis of inflammation and fibrosis in keloids

BACKGROUND

Keloid (KL) is a common benign skin tumor. KL is typically characterized by significant fibrosis and an intensive inflammatory response. Therefore, a comprehensive understanding of the interactions between cellular inflammation and fibrotic cells is essential to elucidate the mechanisms driving the progression of KL and to develop therapeutics.

OBJECTIVE

Investigate the transcriptome landscape of inflammation and fibrosis in keloid scars.

METHODS

In this paper, we performed transcriptome sequencing and microRNA (miRNA) sequencing on unselected live cells from six human keloid tissues and normal skin tissues to elucidate a comprehensive transcriptome landscape. In addition, we used single-cell RNA sequencing (scRNA-seq) analysis to analyze intercellular communication networks and enrich fibroblast populations in two additional keloid and normal skin samples to study fibroblast diversity.

RESULTS

By RNA sequencing and a miRNA-mRNA-PPI network analysis, we identified miR-615-5p and miR-122b-3p as possible miRNAs associated with keloids, as they differed most significantly in keloids. Similarly, COL3A1, COL1A2, THBS2, TNC, IGTA, THBS4, TGFB3 as genes with significant differences in keloid may be associated with keloid development. Using single-cell RNA sequencing data from 24,086 cells collected from normal or keloid, we report reconstructed intercellular signaling network analysis and aggregation to modules associated with specific cell subpopulations at the cellular level for keloid alterations.

CONCLUSIONS

Our multitranscriptomic dataset delineates inflammatory and fibro heterogeneity of human keloids, underlining the importance of intercellular crosstalk between inflammatory cells and fibro cells and revealing potential therapeutic targets.

A cell atlas of the larval Aedes aegypti ventral nerve cord

Mosquito-borne diseases account for nearly 1 million human deaths annually, yet we have a limited understanding of developmental events that influence host-seeking behavior and pathogen transmission in mosquitoes. Mosquito-borne pathogens are transmitted during blood meals, hence adult mosquito behavior and physiology have been intensely studied. However, events during larval development shape adult traits, larvae respond to many of the same sensory cues as adults, and larvae are susceptible to infection by many of the same disease-causing agents as adults. Hence, a better understanding of larval physiology will directly inform our understanding of physiological processes in adults. Here, we use single cell RNA sequencing (scRNA-seq) to provide a comprehensive view of cellular composition in the Aedes aegypti larval ventral nerve cord (VNC), a central hub of sensory inputs and motor outputs which additionally controls multiple aspects of larval physiology. We identify more than 35 VNC cell types defined in part by neurotransmitter and neuropeptide expression. We also explore diversity among monoaminergic and peptidergic neurons that likely control key elements of larval physiology and developmental timing, and identify neuroblasts and immature neurons, providing a view of neuronal differentiation in the VNC. Finally, we find that larval cell composition, number, and position are preserved in the adult abdominal VNC, suggesting studies of larval VNC form and function will likely directly inform our understanding adult mosquito physiology. Altogether, these studies provide a framework for targeted analysis of VNC development and neuronal function in Aedes aegypti larvae.

Preparation of hepatocellular carcinoma mRNA vaccines based on potential tumor targets and immunophenotypes

Background

With the development of messenger RNA (mRNA)-based therapeutics for malignant tumor, mRNA vaccines have shown considerable promise for tumor immunotherapy. Immunophenotypes can reflect the tumor microenvironment, which might have a significant influence on the effect of immunotherapy. This study seeks to discover and validate effective antigens that can be employed to develop mRNA vaccines for hepatocellular carcinoma (HCC) and to construct immunophenotypes and immune landscapes to identify potential beneficiaries.

Methods

RNA sequencing (RNASeq) data, mutation information, and clinical information were obtained from HCC patients and control cases from The Cancer Genome Atlas - Liver Hepatocellular Carcinoma (TCGA-LIHC), International Cancer Genome Consortium - Liver Cancer (ICGC-LIRI) and Gene Expression Omnibus (GEO) cohorts. Gene Expression Profiling Interactive Analysis (GEPIA2.0), cBioPortal for Cancer Genomics (cBioPortal), Tumor IMmune Estimation Resource (TIMER2.0), and immunohistochemistry (IHC) were employed to discover tumor antigens. ConsensusClusterPlus was employed to perform consistency matrix building and immunophenotypic clustering. Single sample gene set enrichment analysis (ssGSEA), ESTIMATE and monocle2 were employed to map immune cell distribution. Weighted correlation network analysis (WGCNA) was employed to identify potential gene modules that influence the efficacy of mRNA vaccines.

Results

Six antigen targets were discovered in the TCGA cohort, including AURKA, CDC25C, KPNA2, MCM3, NEK2 and TUBG1, which were associated with antigen-presenting cell infiltration and poor prognosis. IHC scores of AURKA, CDC25C and MCM3 were higher in tumor tissues, and high scores of AURKA and CDC25C indicated poor prognosis in the validation cohort. Five immunophenotypes derived from TCGA-LIHC and ICGC-LIRI cohorts were consistent. Furthermore, increased expression of blue and black modules may reduce vaccine responsiveness.

Conclusions

AURKA, CDC25C, KPNA2, MCM3, NEK2 and TUBG1 may be potential targets for mRNA vaccine development for HCC, especially AURKA and CDC25C. HCC patients with IS1 and IS5 subtypes perhaps present an autoimmunosuppressed state, then IS2 and IS3 subtypes perhaps the potential beneficiaries.

Single-cell RNA sequencing reveals cellular dynamics and therapeutic effects of astragaloside IV in slow transit constipation

The cellular characteristics of intestinal cells involved in the therapeutic effects of astragaloside IV (AS-IV) for treating slow transit constipation (STC) remain unclear. This study aimed to determine the dynamics of colon tissue cells in the STC model and investigate the effects of AS-IV treatment by single-cell RNA sequencing (scRNA-seq). STC mouse models were developed using loperamide, with subsequent treatment using AS-IV. Colon tissues and feces were collected for scRNA-seq and targeted short-chain fatty acid quantification. We integrated scRNA-seq data with network pharmacology to analyze the effect of AS-IV on constipation. AS-IV showed improvement in defecation for STC mice induced by loperamide. Notably, in STC mice, epithelial cells, T cells, B cells, and fibroblasts demonstrated alterations in cell proportions and aberrant functions, which AS-IV partially rectified. AS-IV has the potential to modulate the metabolic pathway of epithelial cells through its interaction with peroxisome proliferator-activated receptor gamma (PPARγ). AS-IV reinstated fecal butyrate levels and improved energy metabolism in epithelial cells. The proportion of naïve CD4+T cells is elevated in STC, and the differentiation of these cells into regulatory T cells (Treg) is regulated by B cells and fibroblasts through the interaction of ligand-receptor pairs. AS-IV treatment can partially alleviate this trend. The status of fibroblasts in STC undergoes alterations, and the FB_C4_Adamdec1 subset, associated with angiogenesis and the Wingless-related integration (Wnt) pathway, emerges. Our comprehensive analysis identifies perturbations of epithelial cells and tissue microenvironment cells in STC and elucidates mechanisms underlying the therapeutic efficacy of AS-IV.

Saa3 promotes pro-inflammatory macrophage differentiation and contributes to sepsis-induced AKI

Sepsis-induced acute kidney injury (SAKI) is a life-threatening condition with complex pathophysiology, often exacerbated by immune cell dysregulation. In this comprehensive study, we leverage publicly available single-cell RNA sequencing (scRNA-seq) datasets to unravel the intricate immune responses occurring during SAKI, shedding light on macrophages as critical players. Specifically, we identify Saa3, a gene primarily expressed in macrophages, as a potent pro-inflammatory cytokine in SAKI. Saa3hi Ccl2hi monocyte-derived infiltrated macrophages (IMs) emerge as a central effector subset, fostering inflammation, and directly engaging with renal cells. Our findings suggest that Saa3 may be a promising predictive marker of SAKI, although further exploration of human homologs is warranted.

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

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

Self-supervised deep learning of gene-gene interactions for improved gene expression recovery

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to gain biological insights at the cellular level. However, due to technical limitations of the existing sequencing technologies, low gene expression values are often omitted, leading to inaccurate gene counts. Existing methods, including advanced deep learning techniques, struggle to reliably impute gene expressions due to a lack of mechanisms that explicitly consider the underlying biological knowledge of the system. In reality, it has long been recognized that gene-gene interactions may serve as reflective indicators of underlying biology processes, presenting discriminative signatures of the cells. A genomic data analysis framework that is capable of leveraging the underlying gene-gene interactions is thus highly desirable and could allow for more reliable identification of distinctive patterns of the genomic data through extraction and integration of intricate biological characteristics of the genomic data. Here we tackle the problem in two steps to exploit the gene-gene interactions of the system. We first reposition the genes into a 2D grid such that their spatial configuration reflects their interactive relationships. To alleviate the need for labeled ground truth gene expression datasets, a self-supervised 2D convolutional neural network is employed to extract the contextual features of the interactions from the spatially configured genes and impute the omitted values. Extensive experiments with both simulated and experimental scRNA-seq datasets are carried out to demonstrate the superior performance of the proposed strategy against the existing imputation methods.

Effect of sodium stibogluconate in recruiting and awakening immune cells in the pleural fluid of pancreatic cancer: preparation for immunotherapy

Ascites and pleural effusion are recognized complications of pancreatic cancer. These diseases are accompanied by ascites and pleural effusion, and drug treatment is limited by high costs, long hospital stays, and failure rates. Immunotherapy may offer new option, but in most patients with late stages of cancer, immune cells may lose the ability to recognize tumor cells, how to activate their immune cells is a major problem, sodium glucosidate (SSG) is injected into ascites as a protein tyrosine phosphatase inhibitor to wake up immune cells and prepare for immunotherapy. We used single-cell RNA sequencing (scRNA-seq) to investigate whether and how SSG injected into ascites of pancreatic cancer elicits an immune response. Our study showed that the process of SSG fusion treatment of ascites and pleural effusion, the interaction between TandNK cells, MPs cells, monocytes and neutrophils was induced, and large numbers of genes were expressed, resulting in upregulation of immune response, which also approved that SSG is not only used as a protein tyrosine phosphatase inhibitor, but also it works as a protein tyrosine phosphatase inhibitor. It can also be used to regulate immune cell function, recruiting immune cells to the right place with the help of PD-1 or PD-L1 to fight cancer cells in ascites and pleural effusions in cancer patients.

VGLL1 cooperates with TEAD4 to control human trophectoderm lineage specification

In contrast to rodents, the mechanisms underlying human trophectoderm and early placenta specification are understudied due to ethical barriers and the scarcity of embryos. Recent reports have shown that human pluripotent stem cells (PSCs) can differentiate into trophectoderm (TE)-like cells (TELCs) and trophoblast stem cells (TSCs), offering a valuable in vitro model to study early placenta specification. Here, we demonstrate that the VGLL1 (vestigial-like family member 1), which is highly expressed during human and non-human primate TE specification in vivo but is negligibly expressed in mouse, is a critical regulator of cell fate determination and self-renewal in human TELCs and TSCs derived from naïve PSCs. Mechanistically, VGLL1 partners with the transcription factor TEAD4 (TEA domain transcription factor 4) to regulate chromatin accessibility at target gene loci through histone acetylation and acts in cooperation with GATA3 and TFAP2C. Our work is relevant to understand primate early embryogenesis and how it differs from other mammalian species.

Single-cell profiling of the microenvironment in human bone metastatic renal cell carcinoma

Bone metastasis is of common occurrence in renal cell carcinoma with poor prognosis, but no optimal treatment approach has been established for bone metastatic renal cell carcinoma. To explore the potential therapeutic targets for bone metastatic renal cell carcinoma, we profile single cell transcriptomes of 6 primary renal cell carcinoma and 9 bone metastatic renal cell carcinoma. We also include scRNA-seq data of early-stage renal cell carcinoma, late-stage renal cell carcinoma, normal kidneys and healthy bone marrow samples in the study to better understand the bone metastasis niche. The molecular properties and dynamic changes of major cell lineages in bone metastatic environment of renal cell carcinoma are characterized. Bone metastatic renal cell carcinoma is associated with multifaceted immune deficiency together with cancer-associated fibroblasts, specifically appearance of macrophages exhibiting malignant and pro-angiogenic features. We also reveal the dominance of immune inhibitory T cells in the bone metastatic renal cell carcinoma which can be partially restored by the treatment. Trajectory analysis showes that myeloid-derived suppressor cells are progenitors of macrophages in the bone metastatic renal cell carcinoma while monocytes are their progenitors in primary tumors and healthy bone marrows. Additionally, the infiltration of immune inhibitory CD47+ T cells is observed in bone metastatic tumors, which may be a result of reduced phagocytosis by SIRPA-expressing macrophages in the bone microenvironment. Together, our results provide a systematic view of various cell types in bone metastatic renal cell carcinoma and suggest avenues for therapeutic solutions.

Time-resolved single-cell transcriptomics defines immune trajectories in glioblastoma

Deciphering the cell-state transitions underlying immune adaptation across time is fundamental for advancing biology. Empirical in vivo genomic technologies that capture cellular dynamics are currently lacking. We present Zman-seq, a single-cell technology recording transcriptomic dynamics across time by introducing time stamps into circulating immune cells, tracking them in tissues for days. Applying Zman-seq resolved cell-state and molecular trajectories of the dysfunctional immune microenvironment in glioblastoma. Within 24 hours of tumor infiltration, cytotoxic natural killer cells transitioned to a dysfunctional program regulated by TGFB1 signaling. Infiltrating monocytes differentiated into immunosuppressive macrophages, characterized by the upregulation of suppressive myeloid checkpoints Trem2, Il18bp, and Arg1, over 36 to 48 hours. Treatment with an antagonistic anti-TREM2 antibody reshaped the tumor microenvironment by redirecting the monocyte trajectory toward pro-inflammatory macrophages. Zman-seq is a broadly applicable technology, enabling empirical measurements of differentiation trajectories, which can enhance the development of more efficacious immunotherapies.

Chemical immune conization of precancerous cervical lesions awakens immune cells and restores normal HPV negative and abnormal proliferation

Background

Cervical cancer is one of the most common and deadly cancers in women, which is closely linked to the persistent infection of high-risk human papillomavirus (HPV). Current treatment of cervical cancer involves radical hysterectomy, radiotherapy, and chemotherapy or a combination.

Objective

We investigated if hapten-enhanced intratumoral chemotherapy (HEIC) was effective in boosting immunity for effective treatment of precancerous cervical lesions and HPV infection.

Study design

We used single-cell RNA sequencing (scRNA-Seq) to obtain transcriptome profiles of 40,239 cells from biopsies of precancerous cervical lesions from the cervix directly from one patient before the start of HEIC and approximately 1 week after HEIC. The blood samples were taken at the same time as biopsies. We compared the expression characteristics of malignant epithelial cells and immune cells, including epithelial cells, endothelial cells (ECs), fibroblasts, mural cells, T cells, B cells, T and NK neutrophils, mast cells, microparticles (MPs), and platelets, as well as the dynamic changes in cell percentage and cell subtype heterogeneity.

Results

Intratumoral injection of chemotherapy drug plus hapten induces an acute immune response in precancerous cervical lesions with HPV and further awakens immune cells to prevent the abnormal proliferation of the precancerous cells.

Conclusion

HEIC provides a potential treatment method for cervical cancer and HPV infection tailored to each patient's condition.

Single-cell landscape of the cellular microenvironment in three different colonic polyp subtypes in children

BACKGROUND

The understanding of the heterogeneous cellular microenvironment of colonic polyps in paediatric patients with solitary juvenile polyps (SJPs), polyposis syndrome (PJS) and Peutz-Jeghers syndrome (PJS) remains limited.

METHODS

We conducted single-cell RNA sequencing and multiplexed immunohistochemistry (mIHC) analyses on both normal colonic tissue and different types of colonic polyps obtained from paediatric patients.

RESULTS

We identified both shared and disease-specific cell subsets and expression patterns that played important roles in shaping the unique cellular microenvironments observed in each polyp subtype. As such, increased myeloid, endothelial and epithelial cells were the most prominent features of SJP, JPS and PJS polyps, respectively. Noticeably, memory B cells were increased, and a cluster of epithelial-mesenchymal transition (EMT)-like colonocytes existed across all polyp subtypes. Abundant neutrophil infiltration was observed in SJP polyps, while CX3CR1hi CD8+ T cells and regulatory T cells (Tregs) were predominant in SJP and JPS polyps, while GZMAhi natural killer T cells were predominant in PJS polyps. Compared with normal colonic tissues, myeloid cells exhibited specific induction of genes involved in chemotaxis and interferon-related pathways in SJP polyps, whereas fibroblasts in JPS polyps had upregulation of myofiber-associated genes and epithelial cells in PJS polyps exhibited induction of a series of nutrient absorption-related genes. In addition, the TNF-α response was uniformly upregulated in most cell subsets across all polyp subtypes, while endothelial cells and fibroblasts separately showed upregulated cell adhesion and EMT signalling in SJP and JPS polyps. Cell-cell interaction network analysis showed markedly enhanced intercellular communication, such as TNF, VEGF, CXCL and collagen signalling networks, among most cell subsets in polyps, especially SJP and JPS polyps.

CONCLUSION

These findings strengthen our understanding of the heterogeneous cellular microenvironment of polyp subtypes and identify potential therapeutic approaches to reduce the recurrence of polyps in children.

Computational immunogenomic approaches to predict response to cancer immunotherapies

Cancer immunogenomics is an emerging field that bridges genomics and immunology. The establishment of large-scale genomic collaborative efforts along with the development of new single-cell transcriptomic techniques and multi-omics approaches have enabled characterization of the mutational and transcriptional profiles of many cancer types and helped to identify clinically actionable alterations as well as predictive and prognostic biomarkers. Researchers have developed computational approaches and machine learning algorithms to accurately obtain clinically useful information from genomic and transcriptomic sequencing data from bulk tissue or single cells and explore tumours and their microenvironment. The rapid growth in sequencing and computational approaches has resulted in the unmet need to understand their true potential and limitations in enabling improvements in the management of patients with cancer who are receiving immunotherapies. In this Review, we describe the computational approaches currently available to analyse bulk tissue and single-cell sequencing data from cancer, stromal and immune cells, as well as how best to select the most appropriate tool to address various clinical questions and, ultimately, improve patient outcomes.

Integration of single-cell and bulk RNA-sequencing to analyze the heterogeneity of hepatocellular carcinoma and establish a prognostic model

BACKGROUND

The highly heterogeneous nature of hepatocellular carcinoma (HCC) results in different responses and prognoses to the same treatment in patients with similar clinical stages.

AIMS

Thus, it is imperative to investigate the association between HCC tumor heterogeneity and treatment response and prognosis.

METHODS AND RESULTS

At first, we downloaded scRNA-seq, bulk RNA-seq, and clinical data from TCGA and GEO databases. We conducted quality control, normalization using SCTransform, dimensionality reduction using PCA, batch effect removal using Harmony, dimensionality reduction using UMAP, and cell annotation-based marker genes on the scRNA-seq data. We recognized tumor cells, identified tumor-related genes (TRGs), and performed cell communication analysis. Next, we developed a prognostic model using univariable Cox, LASSO, and multivariate Cox analyses. The signature was evaluated using survival analysis, ROC curves, C-index, and nomogram. Last, we studied the predictability of the signature in terms of prognosis and immunotherapeutic response for HCC, assessed a variety of drugs for clinical treatment, and used the qRT-PCR analysis to validate the mRNA expression levels of prognostic TRGs.

CONCLUSION

To conclude, this study expounded upon the influence of tumor cell heterogeneity on the prediction of treatment outcomes and prognosis in HCC. This, in turn, enhances the predictive ability of the TNM staging system and furnishes novel perspectives on the prognostic assessment and therapy of HCC.

The Deubiquitylase Otub1 Regulates the Chemotactic Response of Splenic B Cells by Modulating the Stability of the γ-Subunit Gng2

The ubiquitin proteasome system performs the covalent attachment of lysine 48-linked polyubiquitin chains to substrate proteins, thereby targeting them for degradation, while deubiquitylating enzymes (DUBs) reverse this process. This posttranslational modification regulates key features both of innate and adaptative immunity, including antigen presentation, protein homeostasis and signal transduction. Here we show that loss of one of the most highly expressed DUBs, Otub1, results in changes in murine splenic B cell subsets, leading to a significant increase in marginal zone and transitional B cells and a concomitant decrease in follicular B cells. We demonstrate that Otub1 interacts with the γ-subunit of the heterotrimeric G protein, Gng2, and modulates its ubiquitylation status, thereby controlling Gng2 stability. Proximal mapping of Gng2 revealed an enrichment in partners associated with chemokine signaling, actin cytoskeleton and cell migration. In line with these findings, we show that Otub1-deficient B cells exhibit greater Ca2+ mobilization, F-actin polymerization and chemotactic responsiveness to Cxcl12, Cxcl13 and S1P in vitro, which manifests in vivo as altered localization of B cells within the spleen. Together, our data establishes Otub1 as a novel regulator of G-protein coupled receptor signaling in B cells, regulating their differentiation and positioning in the spleen.

Single-cell sequencing of head and neck carcinoma: Transcriptional landscape and prognostic model based on malignant epithelial cell features

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide, and the development of novel therapeutic strategies for HNSCC requires a profound understanding of tumor cells and the tumor microenvironment (TME). Additionally, HNSCC has a poor prognosis, necessitating the use of genetic markers for predicting clinical outcomes in HNSCC. In this study, we performed single-cell sequencing analysis on tumor tissues from seven HNSCC patients, along with one adjacent normal tissue. Firstly, the analysis of epithelial cell clusters revealed two clusters of malignant epithelial cells, characterized by unique gene expression patterns and dysregulated signaling pathways compared to normal epithelial cells. Secondly, the examination of the TME unveiled extensive crosstalk between fibroblasts and malignant epithelial cells, potentially mediated through ligand-receptor interactions such as COL1A1-SDC1, COL1A1-CD44, and COL1A2-SDC1. Furthermore, transcriptional heterogeneity was observed in immune cells present in the TME, including macrophages and dendritic cells. Finally, leveraging the gene expression profiles of malignant epithelial cells, we developed a prognostic model comprising six genes, which we validated using two independent datasets. These findings shed light on the heterogeneity within HNSCC tumors and the intricate interplay between malignant cells and the TME. Importantly, the developed prognostic model demonstrates high efficacy in predicting the survival outcomes of HNSCC patients.

Lineage Tracing by Single-Cell Transcriptomics Decoding Dynamics of Lineage Commitment

Tracing the fate of individual cells and their progeny is necessary and significant for stem cell research and cancer research. Changes in lineage-specific transcription factor levels during lineage commitment are gradual and continuous. Development of single-cell sequencing technology allows many different states of cells to be sequenced at an unprecedented resolution, and it has been proved that single-cell transcriptomics meets lineage tracing. Here, we introduce a detailed protocol for the lineage tracing by single-cell transcriptomics to clarify the dynamics of lineage commitment.

YAP targetome reveals activation of SPEM in gastric pre-neoplastic progression and regeneration

Peptic ulcer disease caused by environmental factors increases the risk of developing gastric cancer (GC), one of the most common and deadly cancers in the world. However, the mechanisms underlying this association remain unclear. A major type of GC uniquely undergoes spasmolytic polypeptide-expressing metaplasia (SPEM) followed by intestinal metaplasia. Notably, intestinal-type GC patients with high levels of YAP signaling exhibit a lower survival rate and poor prognosis. YAP overexpression in gastric cells induces atrophy, metaplasia, and hyperproliferation, while its deletion in a Notch-activated gastric adenoma model suppresses them. By defining the YAP targetome genome-wide, we demonstrate that YAP binds to active chromatin elements of SPEM-related genes, which correlates with the activation of their expression in both metaplasia and ulcers. Single-cell analysis combined with our YAP signature reveals that YAP signaling is activated during SPEM, demonstrating YAP as a central regulator of SPEM in gastric neoplasia and regeneration.

Human iPSC-derived renal collecting duct organoid model cystogenesis in ADPKD

In autosomal dominant polycystic kidney disease (ADPKD), renal cyst lesions predominantly arise from collecting ducts (CDs). However, relevant CD cyst models using human cells are lacking. Although previous reports have generated in vitro renal tubule cyst models from human induced pluripotent stem cells (hiPSCs), therapeutic drug candidates for ADPKD have not been identified. Here, by establishing expansion cultures of hiPSC-derived ureteric bud tip cells, an embryonic precursor that gives rise to CDs, we succeed in advancing the developmental stage of CD organoids and show that all CD organoids derived from PKD1-/- hiPSCs spontaneously develop multiple cysts, clarifying the initiation mechanisms of cystogenesis. Moreover, we identify retinoic acid receptor (RAR) agonists as candidate drugs that suppress in vitro cystogenesis and confirm the therapeutic effects on an ADPKD mouse model in vivo. Therefore, our in vitro CD cyst model contributes to understanding disease mechanisms and drug discovery for ADPKD.

Systems immunology spanning tumors, lymph nodes, and periphery

The immune system defines a complex network of tissues and cell types that orchestrate responses across the body in a dynamic manner. The local and systemic interactions between immune and cancer cells contribute to disease progression. Lymphocytes are activated in lymph nodes, traffic through the periphery, and impact cancer progression through their interactions with tumor cells. As a result, therapeutic response and resistance are mediated across tissues, and a comprehensive understanding of lymphocyte dynamics requires a systems-level approach. In this review, we highlight experimental and computational methods that can leverage the study of leukocyte trafficking through an immunomics lens and reveal how adaptive immunity shapes cancer.

scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles

Many deep learning-based methods have been proposed to handle complex single-cell data. Deep learning approaches may also prove useful to jointly analyze single-cell RNA sequencing (scRNA-seq) and single-cell T cell receptor sequencing (scTCR-seq) data for novel discoveries. We developed scNAT, a deep learning method that integrates paired scRNA-seq and scTCR-seq data to represent data in a unified latent space for downstream analysis. We demonstrate that scNAT is capable of removing batch effects, and identifying cell clusters and a T cell migration trajectory from blood to cerebrospinal fluid in multiple sclerosis.

Lineage tracing of T cell differentiation from T-iPSC by 2D feeder-free culture and 3D organoid culture

Introduction

T cells induced from induced pluripotent stem cells(iPSCs) derived from antigen-specific T cells (T-iPS-T cells) are an attractive tool for T cell immunotherapy. The induction of cytotoxic T-iPS-T cells is well established in feeder-free condition for the aim of off-the-shelf production, however, the induction of helper T-iPS-T cells remains challenging.

Methods

We analyzed T-iPS-T cells matured in 3D organoid culture at different steps in the culture process at the single-cell level. T-iPS-T cell datasets were merged with an available human thymocyte dataset based in single-cell RNA sequencing (scRNA-seq). Particularly, we searched for genes crucial for generation CD4+ T-iPS-T cells by comparing T-iPS-T cells established in 2D feeder-free or 3D organoid culture.

Results

The scRNA-seq data indicated that T-iPS-T cells are similar to T cells transitioning to human thymocytes, with SELENOW, GIMAP4, 7, SATB1, SALMF1, IL7R, SYTL2, S100A11, STAT1, IFITM1, LZTFL1 and SOX4 identified as candidate genes for the 2D feeder-free induction of CD4+ T-iPS-T cells.

Discussion

This study provides single cell transcriptome datasets of iPS-T cells and leads to further analysis for CD4+ T cell generation from T-iPSCs.

Protocol for nuclear dissociation of the adult C. elegans for single-nucleus RNA sequencing and its application for mapping environmental responses

Caenorhabditis elegans is a valuable model to study organ, tissue, and cell-type responses to external cues. However, the nematode comprises multiple syncytial tissues with spatial coordinates corresponding to distinct nuclear transcriptomes. Here, we present a single-nucleus RNA sequencing (snRNA-seq) protocol that aims to overcome difficulties encountered with single-cell RNA sequencing in C. elegans. We describe steps for isolating C. elegans nuclei for downstream applications including snRNA-seq applied to the context of alcohol exposure. For complete details on the use and execution of this protocol, please refer to Truong et al. (2023).1.

Genomic alterations driving precancerous to cancerous lesions in esophageal cancer development

Esophageal squamous cell carcinoma (ESCC) develops through a series of increasingly abnormal precancerous lesions. Previous studies have revealed the striking differences between normal esophageal epithelium and ESCC in copy number alterations (CNAs) and mutations in genes driving clonal expansion. However, due to limited data on early precancerous lesions, the timing of these transitions and which among them are prerequisites for malignant transformation remained unclear. Here, we analyze 1,275 micro-biopsies from normal esophagus, early and late precancerous lesions, and esophageal cancers to decipher the genomic alterations at each stage. We show that the frequency of TP53 biallelic inactivation increases dramatically in early precancerous lesion stage while CNAs and APOBEC mutagenesis substantially increase at late stages. TP53 biallelic loss is the prerequisite for the development of CNAs of genes in cell cycle, DNA repair, and apoptosis pathways, suggesting it might be one of the earliest steps initiating malignant transformation.

Decoding aging-dependent regenerative decline across tissues at single-cell resolution

Regeneration across tissues and organs exhibits significant variation throughout the body and undergoes a progressive decline with age. To decode the relationships between aging and regenerative capacity, we conducted a comprehensive single-cell transcriptome analysis of regeneration in eight tissues from young and aged mice. We employed diverse analytical models to study tissue regeneration and unveiled the intricate cellular and molecular mechanisms underlying the attenuated regenerative processes observed in aged tissues. Specifically, we identified compromised stem cell mobility and inadequate angiogenesis as prominent contributors to this age-associated decline in regenerative capacity. Moreover, we discovered a unique subset of Arg1+ macrophages that were activated in young tissues but suppressed in aged regenerating tissues, suggesting their important role in age-related immune response disparities during regeneration. This study provides a comprehensive single-cell resource for identifying potential targets for interventions aimed at enhancing regenerative outcomes in the aging population.

SingleScan: a comprehensive resource for single-cell sequencing data processing and mining

Single-cell sequencing has shed light on previously inaccessible biological questions from different fields of research, including organism development, immune function, and disease progression. The number of single-cell-based studies increased dramatically over the past decade. Several new methods and tools have been continuously developed, making it extremely tricky to navigate this research landscape and develop an up-to-date workflow to analyze single-cell sequencing data, particularly for researchers seeking to enter this field without computational experience. Moreover, choosing appropriate tools and optimal parameters to meet the demands of researchers represents a major challenge in processing single-cell sequencing data. However, a specific resource for easy access to detailed information on single-cell sequencing methods and data processing pipelines is still lacking. In the present study, an online resource called SingleScan was developed to curate all up-to-date single-cell transcriptome/genome analyzing tools and pipelines. All the available tools were categorized according to their main tasks, and several typical workflows for single-cell data analysis were summarized. In addition, spatial transcriptomics, which is a breakthrough molecular analysis method that enables researchers to measure all gene activity in tissue samples and map the site of activity, was included along with a portion of single-cell and spatial analysis solutions. For each processing step, the available tools and specific parameters used in published articles are provided and how these parameters affect the results is shown in the resource. All information used in the resource was manually extracted from related literature. An interactive website was designed for data retrieval, visualization, and download. By analyzing the included tools and literature, users can gain insights into the trends of single-cell studies and easily grasp the specific usage of a specific tool. SingleScan will facilitate the analysis of single-cell sequencing data and promote the development of new tools to meet the growing and diverse needs of the research community. The SingleScan database is publicly accessible via the website at http://cailab.labshare.cn/SingleScan .

Myeloid cells interact with a subset of thyrocytes to promote their migration and follicle formation through NF-κB

The pathogenesis of thyroid dysgenesis (TD) is not well understood. Here, using a combination of single-cell RNA and spatial transcriptome sequencing, we identify a subgroup of NF-κB-activated thyrocytes located at the center of thyroid tissues in postnatal mice, which maintained a partially mesenchymal phenotype. These cells actively protruded out of the thyroid primordium and generated new follicles in zebrafish embryos through continuous tracing. Suppressing NF-κB signaling affected thyrocyte migration and follicle formation, leading to a TD-like phenotype in both mice and zebrafish. Interestingly, during thyroid folliculogenesis, myeloid cells played a crucial role in promoting thyrocyte migration by maintaining close contact and secreting TNF-α. We found that cebpa mutant zebrafish, in which all myeloid cells were depleted, exhibited thyrocyte migration defects. Taken together, our results suggest that myeloid-derived TNF-α-induced NF-κB activation plays a critical role in promoting the migration of vertebrate thyrocytes for follicle generation.

Host CD34+ cells are replacing donor endothelium of transplanted heart

BACKGROUND

Endothelium dysfunction is a central problem for early rejection due to the host alloimmune response and the late status of arteriosclerosis in heart transplantation. However, reliable pieces of evidence are still limited concerning the source of the regenerated endothelium within the transplanted heart.

METHODS

We analyzed single-cell RNA sequencing data and constructed an inducible lineage tracing mouse, combined heart transplantation with bone marrow transplantation and a parabiosis model, cellular components, and endothelial cell populations in cardiac graft lesions.

RESULTS

Our single-cell RNA sequencing analysis of a transplanted heart allowed for the establishment of an endothelial cell atlas with a heterogeneous population, including arterial, venous, capillary, and lymphatic endothelial cells. Along with genetic cell lineage tracing, we demonstrated that the donor cells were mostly replaced by recipient cells in the cardiac allograft, up to 83.29% 2 weeks after transplantation. Furthermore, recipient nonbone marrow CD34+ endothelial progenitors contributed significantly to extracellular matrix organization and immune regulation, with higher apoptotic ability in the transplanted hearts. Mechanistically, peripheral blood-derived human endothelial progenitor cells differentiate into endocardial cells via Vascular endothelial growth factor receptor-mediated pathways. Host circulating CD34+ endothelial progenitors could repair the damaged donor endothelium presumably through CCL3-CCR5 chemotaxis. Partial depletion of host CD34+ cells resulted in delayed endothelial regeneration.

CONCLUSIONS

We created an annotated fate map of endothelial cells in cardiac allografts, indicating how recipient CD34+ cells could replace the donor endothelium via chemokine CCL3-CCR5 interactions. The mechanisms we discovered could have a potential therapeutic effect on the long-term outcomes of heart transplantation.

Elucidating dynamic cell lineages and gene networks in time-course single cell differentiation

Single cell RNA sequencing (scRNA-seq) technologies provide researchers with an unprecedented opportunity to exploit cell heterogeneity. For example, the sequenced cells belong to various cell lineages, which may have different cell fates in stem and progenitor cells. Those cells may differentiate into various mature cell types in a cell differentiation process. To trace the behavior of cell differentiation, researchers reconstruct cell lineages and predict cell fates by ordering cells chronologically into a trajectory with a pseudo-time. However, in scRNA-seq experiments, there are no cell-to-cell correspondences along with the time to reconstruct the cell lineages, which creates a significant challenge for cell lineage tracing and cell fate prediction. Therefore, methods that can accurately reconstruct the dynamic cell lineages and predict cell fates are highly desirable. In this article, we develop an innovative machine-learning framework called Cell Smoothing Transformation (CellST) to elucidate the dynamic cell fate paths and construct gene networks in cell differentiation processes. Unlike the existing methods that construct one single bulk cell trajectory, CellST builds cell trajectories and tracks behaviors for each individual cell. Additionally, CellST can predict cell fates even for less frequent cell types. Based on the individual cell fate trajectories, CellST can further construct dynamic gene networks to model gene-gene relationships along the cell differentiation process and discover critical genes that potentially regulate cells into various mature cell types.

A global view of aging and Alzheimer's pathogenesis-associated cell population dynamics and molecular signatures in human and mouse brains

Conventional methods fall short in unraveling the dynamics of rare cell types related to aging and diseases. Here we introduce EasySci, an advanced single-cell combinatorial indexing strategy for exploring age-dependent cellular dynamics in the mammalian brain. Profiling approximately 1.5 million single-cell transcriptomes and 400,000 chromatin accessibility profiles across diverse mouse brains, we identified over 300 cell subtypes, uncovering their molecular characteristics and spatial locations. This comprehensive view elucidates rare cell types expanded or depleted upon aging. We also investigated cell-type-specific responses to genetic alterations linked to Alzheimer's disease, identifying associated rare cell types. Additionally, by profiling 118,240 human brain single-cell transcriptomes, we discerned cell- and region-specific transcriptomic changes tied to Alzheimer's pathogenesis. In conclusion, this research offers a valuable resource for probing cell-type-specific dynamics in both normal and pathological aging.

Single-cell RNA sequencing unveils Lrg1's role in cerebral ischemia‒reperfusion injury by modulating various cells

BACKGROUND AND PURPOSE

Cerebral ischemia‒reperfusion injury causes significant harm to human health and is a major contributor to stroke-related deaths worldwide. Current treatments are limited, and new, more effective prevention and treatment strategies that target multiple cell components are urgently needed. Leucine-rich alpha-2 glycoprotein 1 (Lrg1) appears to be associated with the progression of cerebral ischemia‒reperfusion injury, but the exact mechanism of it is unknown.

METHODS

Wild-type (WT) and Lrg1 knockout (Lrg1-/-) mice were used to investigate the role of Lrg1 after cerebral ischemia‒reperfusion injury. The effects of Lrg1 knockout on brain infarct volume, blood‒brain barrier permeability, and neurological score (based on 2,3,5-triphenyl tetrazolium chloride, evans blue dye, hematoxylin, and eosin staining) were assessed. Single-cell RNA sequencing (scRNA-seq), immunofluorescence, and microvascular albumin leakage tests were utilized to investigate alterations in various cell components in brain tissue after Lrg1 knockout.

RESULTS

Lrg1 expression was increased in various cell types of brain tissue after cerebral ischemia‒reperfusion injury. Lrg1 knockout reduced cerebral edema and infarct size and improved neurological function after cerebral ischemia‒reperfusion injury. Single-cell RNA sequencing analysis of WT and Lrg1-/- mouse brain tissues after cerebral ischemia‒reperfusion injury revealed that Lrg1 knockout enhances blood‒brain barrier (BBB) by upregulating claudin 11, integrin β5, protocadherin 9, and annexin A2. Lrg1 knockout also promoted an anti-inflammatory and tissue-repairing phenotype in microglia and macrophages while reducing neuron and oligodendrocyte cell death.

CONCLUSIONS

Our results has shown that Lrg1 mediates numerous pathological processes involved in cerebral ischemia‒reperfusion injury by altering the functional states of various cell types, thereby rendering it a promising therapeutic target for cerebral ischemia‒reperfusion injury.

Ginseng-derived nanoparticles reprogram macrophages to regulate arginase-1 release for ameliorating T cell exhaustion in tumor microenvironment

BACKGROUND

Lines of evidence indicated that, immune checkpoints (ICs) inhibitors enhanced T cell immune response to exert anti-tumor effects. However, T cell exhaustion has been so far a major obstacle to antitumor immunotherapy in colorectal cancer patients. Our previous studies showed that ginseng-derived nanoparticles (GDNPs) inhibited the growth of various tumors by reprograming tumor-associated macrophages (TAMs) and downregulated the ICs expression on T cells in tumor microenvironment (TME), but the underlying effector mechanisms remained unclear.

METHODS

The correlation between arginase-1 (ARG1) and T cells was computed based on the colorectal cancer patients in TCGA database. In vitro, we observed that GDNPs reprogrammed TAMs inhibited ARG1 release and ultimately ameliorated T cell exhaustion according to several techniques including WB, PCR, ELISA and flow cytometry. We also used an in vivo MC38 tumor-bearing model and administered GDNPs to assess their anti-tumor effects through multiple indices. The mechanism that GDNPs improved T cell exhaustion was further clarified using the bioinformatics tools and flow cytometry.

RESULTS

GDNPs reprogramed TAMs via reducing ARG1 production. Moreover, normalized arginine metabolism ameliorated T cell exhaustion through mTOR-T-bet axis, resulting in reduced ICs expression and enhanced CD8+ T cells expansion.

CONCLUSIONS

By regulating the mTOR-T-bet axis, GDNPs reprogramed macrophages to regulate ARG1 release, which further ameliorated T cell exhaustion in TME. These findings provided new insights into comprehending the mechanisms underlying the mitigation of T cell exhaustion, which may facilitate the development of innovative therapeutic strategies in the field of cancer treatment.

Single-cell RNA sequencing-guided fate-mapping toolkit delineates the contribution of yolk sac erythro-myeloid progenitors

Erythro-myeloid progenitors of the yolk sac that originates during early embryo development has been suggested to generate tissue-resident macrophage, mast cell, and even endothelial cell populations from fetal to adult stages. However, the heterogeneity of erythro-myeloid progenitors (EMPs) is not well characterized. Here, we adapt single-cell RNA sequencing to dissect the heterogeneity of EMPs and establish several fate-mapping tools for each EMP subset to trace the contributions of different EMP subsets. We identify two primitive and one definitive EMP subsets from the yolk sac. In addition, we find that primitive EMPs are decoupled from definitive EMPs. Furthermore, we confirm that primitive and definitive EMPs give rise to microglia and other tissue-resident macrophages, respectively. In contrast, only Kit+ Csf1r- primitive EMPs generate endothelial cells transiently during early embryo development. Overall, our results delineate the contribution of yolk sac EMPs more clearly based on the single-cell RNA sequencing (scRNA-seq)-guided fate-mapping toolkit.

Single-cell dissection, hdWGCNA and deep learning reveal the role of oxidatively stressed plasma cells in ulcerative colitis

Ulcerative colitis (UC) develops as a result of complex interactions between various cell types in the mucosal microenvironment. In this study, we aim to elucidate the pathogenesis of ulcerative colitis at the single-cell level and unveil its clinical significance. Using single-cell RNA sequencing and high-dimensional weighted gene co-expression network analysis, we identify a subpopulation of plasma cells (PCs) with significantly increased infiltration in UC colonic mucosa, characterized by pronounced oxidative stress. Combining 10 machine learning approaches, we find that the PC oxidative stress genes accurately distinguish diseased mucosa from normal mucosa (independent external testing AUC=0.991, sensitivity=0.986, specificity=0.909). Using MCPcounter and non-negative matrix factorization, we identify the association between PC oxidative stress genes and immune cell infiltration as well as patient heterogeneity. Spatial transcriptome data is used to verify the infiltration of oxidatively stressed PCs in colitis. Finally, we develop a gene-immune convolutional neural network deep learning model to diagnose UC mucosa in different cohorts (independent external testing AUC=0.984, sensitivity=95.9%, specificity=100%). Our work sheds light on the key pathogenic cell subpopulations in UC and is essential for the development of future clinical disease diagnostic tools.

Cytolytic circumsporozoite-specific memory CD4+ T cell clones are expanded during Plasmodium falciparum infection

Clinical immunity against Plasmodium falciparum infection develops in residents of malaria endemic regions, manifesting in reduced clinical symptoms during infection and in protection against severe disease but the mechanisms are not fully understood. Here, we compare the cellular and humoral immune response of clinically immune (0-1 episode over 18 months) and susceptible (at least 3 episodes) during a mild episode of Pf malaria infection in a malaria endemic region of Malawi, by analysing peripheral blood samples using high dimensional mass cytometry (CyTOF), spectral flow cytometry and single-cell transcriptomic analyses. In the clinically immune, we find increased proportions of circulating follicular helper T cells and classical monocytes, while the humoral immune response shows characteristic age-related differences in the protected. Presence of memory CD4+ T cell clones with a strong cytolytic ZEB2+ T helper 1 effector signature, sharing identical T cell receptor clonotypes and recognizing the Pf-derived circumsporozoite protein (CSP) antigen are found in the blood of the Pf-infected participants gaining protection. Moreover, in clinically protected participants, ZEB2+ memory CD4+ T cells express lower level of inhibitory and chemotactic receptors. We thus propose that clonally expanded ZEB2+ CSP-specific cytolytic memory CD4+ Th1 cells may contribute to clinical immunity against the sporozoite and liver-stage Pf malaria.

Low-dose radiotherapy combined with dual PD-L1 and VEGFA blockade elicits antitumor response in hepatocellular carcinoma mediated by activated intratumoral CD8+ exhausted-like T cells

Atezolizumab (anti-PD-L1) combined with bevacizumab (anti-VEGFA) is the first-line immunotherapy for advanced hepatocellular carcinoma (HCC), but the number of patients who benefit from this regimen remains limited. Here, we combine dual PD-L1 and VEGFA blockade (DPVB) with low-dose radiotherapy (LDRT), which rapidly inflames tumors, rendering them vulnerable to immunotherapy. The combinatorial therapy exhibits superior antitumor efficacy mediated by CD8+ T cells in various preclinical HCC models. Treatment efficacy relies upon mobilizing exhausted-like CD8+ T cells (CD8+ Tex) with effector function and cytolytic capacity. Mechanistically, LDRT sensitizes tumors to DPVB by recruiting stem-like CD8+ Tpex, the progenitor exhausted CD8+ T cells, from draining lymph nodes (dLNs) into the tumor via the CXCL10/CXCR3 axis. Together, these results further support the rationale for combining LDRT with atezolizumab and bevacizumab, and its clinical translation.

Single-cell epigenomics and spatiotemporal transcriptomics reveal human cerebellar development

Human cerebellar development is orchestrated by molecular regulatory networks to achieve cytoarchitecture and coordinate motor and cognitive functions. Here, we combined single-cell transcriptomics, spatial transcriptomics and single cell chromatin accessibility states to systematically depict an integrative spatiotemporal landscape of human fetal cerebellar development. We revealed that combinations of transcription factors and cis-regulatory elements (CREs) play roles in governing progenitor differentiation and cell fate determination along trajectories in a hierarchical manner, providing a gene expression regulatory map of cell fate and spatial information for these cells. We also illustrated that granule cells located in different regions of the cerebellar cortex showed distinct molecular signatures regulated by different signals during development. Finally, we mapped single-nucleotide polymorphisms (SNPs) of disorders related to cerebellar dysfunction and discovered that several disorder-associated genes showed spatiotemporal and cell type-specific expression patterns only in humans, indicating the cellular basis and possible mechanisms of the pathogenesis of neuropsychiatric disorders.