Cell-cell Communication Networks Research Articles

Analysis of matrisome expression patterns in murine and human dorsal root ganglia.

The extracellular matrix (ECM) is a dynamic structure of molecules that can be divided into six different categories and are collectively called the matrisome. The ECM plays pivotal roles in physiological processes in many tissues, including the nervous system. Intriguingly, alterations in ECM molecules/pathways are associated with painful human conditions and murine pain models. Nevertheless, mechanistic insight into the interplay of normal or defective ECM and pain is largely lacking. The goal of this study was to integrate bulk, single-cell, and spatial RNA sequencing (RNAseq) datasets to investigate the expression and cellular origin of matrisome genes in male and female murine and human dorsal root ganglia (DRG). Bulk RNAseq showed that about 65% of all matrisome genes were expressed in both murine and human DRG, with proportionally more core matrisome genes (glycoproteins, collagens, and proteoglycans) expressed compared to matrisome-associated genes (ECM-affiliated genes, ECM regulators, and secreted factors). Single cell RNAseq on male murine DRG revealed the cellular origin of matrisome expression. Core matrisome genes, especially collagens, were expressed by fibroblasts whereas matrisome-associated genes were primarily expressed by neurons. Cell-cell communication network analysis with CellChat software predicted an important role for collagen signaling pathways in connecting vascular cell types and nociceptors in murine tissue, which we confirmed by analysis of spatial transcriptomic data from human DRG. RNAscope in situ hybridization and immunohistochemistry demonstrated expression of collagens in fibroblasts surrounding nociceptors in male and female human DRG. Finally, comparing human neuropathic pain samples with non-pain samples also showed differential expression of matrisome genes produced by both fibroblasts and by nociceptors. This study supports the idea that the DRG matrisome may contribute to neuronal signaling in both mouse and human, and that dysregulation of matrisome genes is associated with neuropathic pain.

Single-cell RNA transcriptome landscape of murine liver following systemic administration of mesoporous silica nanoparticles

Due to the unique physicochemical properties, mesoporous silica nanoparticles (MONs) have been widely utilized in biomedical fields for drug delivery, gene therapy, disease diagnosis and imaging. With the extensive applications and large-scale production of MONs, the potential effects of MONs on human health are gaining increased attention. To better understand the cellular and molecular mechanisms underlying the effects of MONs on the mouse liver, we profiled the transcriptome of 63,783 single cells from mouse livers following weekly intravenous administration of MONs for 2 weeks. The results showed that the proportion of endothelial cells and CD4+ T cells was increased, whereas that of Kupffer cells was decreased, in a dose-dependent manner after MONs treatment in the mouse liver. We also observed that the proportion of inflammation-related Kupffer cell subtype and wound healing-related hepatocyte subtype were elevated, but the number of hepatocytes with detoxification characteristics was reduced after MONs treatment. The cell-cell communication network revealed that there was more crosstalk between cholangiocytes and Kupffer cells, liver capsular macrophages, hepatic stellate cells, and endothelial cells following MONs treatment. Furthermore, we identified key ligand-receptor pairs between crucial subtypes after MONs treatment that are known to promote liver fibrosis. Collectively, our study explored the effects of MONs on mouse liver at a single-cell level and provides comprehensive information on the potential hepatotoxicity of MONs.

Uncovering the Heterogeneity of Cardiac Lin-KIT+ Cells: A scRNA-seq Study on the Identification of Subpopulations.

The reparative potential of cardiac Lin-KIT+ (KIT) cells is influenced by their population, but identifying their markers is challenging due to changes in phenotype during in vitro culture. Resolving this issue requires uncovering cell heterogeneity and discovering new subpopulations. Single-cell RNA sequencing (scRNA-seq) can identify KIT cell subpopulations, their markers, and signaling pathways. We used 10× genomic scRNA-seq to analyze cardiac-derived cells from adult mice and found 3 primary KIT cell populations: KIT1, characterized by high-KIT expression (KITHI), represents a population of cardiac endothelial cells; KIT2, which has low-KIT expression (KITLO), expresses transcription factors such as KLF4, MYC, and GATA6, as well as genes involved in the regulation of angiogenic cytokines; KIT3, with moderate KIT expression (KITMOD), expresses the cardiac transcription factor MEF2C and mesenchymal cell markers such as ENG. Cell-cell communication network analysis predicted the presence of the 3 KIT clusters as signal senders and receivers, including VEGF, CXCL, and BMP signaling. Metabolic analysis showed that KIT1 has the low activity of glycolysis and oxidative phosphorylation (OXPHOS), KIT2 has high glycolytic activity, and KIT3 has high OXPHOS and fatty acid degradation activity, indicating distinct metabolic adaptations of the 3 KIT populations. Through the systemic infusion of KIT1 cells in a mouse model of myocardial infarction, we observed their involvement in promoting the formation of new micro-vessels. In addition, in vitro spheroid culture experiments demonstrated the cardiac differentiation capacity of KIT2 cells.

Abstract P1016: Single Cell Transcriptomic Analysis Of Tafazzin Knockout Mice For Pathway And Therapeutic Discovery In Barth Syndrome

Barth Syndrome, a rare X-linked disorder affecting 1:300,000 live births, results from defects in Tafazzin, an acyltransferase that remodels cardiolipin and is essential for mitochondrial respiration. Barth Syndrome patients develop cardiomyopathy, muscular hypotonia and cyclic neutropenia during childhood, rarely surviving to middle age. At present, no effective therapy exists and downstream transcriptional effects of Tafazzin dysfunction are incompletely understood. To identify novel, cell-specific pathological pathways downstream of Tafazzin that mediate heart dysfunction, we performed snRNA-seq on mouse hearts deficient in Tafazzin. We generated libraries from four WT and four KO mouse hearts (10X Genomics Chromium) and performed next generation sequencing (Illumina NovaSeq S4), demultiplexing (CellRanger), doublet reduction (DoubletFinder), ambient RNA removal (SoupX), sample integration (Harmony), optimal clustering (ChooseR/Seurat), determined differentially expressed genes (DEGs; DESEQ2), and inferred a predicted cell-cell communication network (scLR). Surprisingly, DEGs were distributed heterogeneously, with cardiomyocytes, adipocytes, endothelial cells, fibroblasts and macrophages exhibiting the greatest number of DEGs between each genotype, while lymphocytes, lymphatic endothelium, pericytes, smooth muscle cells and mesothelial cells were mostly unaffected. Gene Ontology analysis showed cell specific effects such as altered amino acid and carbohydrate metabolism plus altered ion channel function in cardiomyocytes and common metabolic perturbations across all affected cell types. Analysis of Ligand-Receptor pair expression, to infer intercellular communication patterns, revealed WT adipocytes form the densest intercellular communication network, followed by WT cardiomyocytes. In the Tafazzin KO hearts, adipocyte significant intercellullar communication ceases, primarily through loss of PDGFRB interactions, while cardiomyocytes remain largely unperturbed. These findings suggest that adipocyte mitochondria may be most sensitive to mitochondrial Tafazzin deficiency and rescuing adipocyte mitochondrial dysfunction may provide therapeutic benefit in Barth Syndrome patients.

Single-cell transcriptomics reveals the drivers and therapeutic targets of lymph node metastasis in lung adenocarcinoma.

Lymph node metastasis (LNM) is usually the most common metastatic pathway in lung adenocarcinoma (LUAD) and is associated with a poorer prognosis and higher possibility of recurrence. Therefore, discovering the drivers and therapeutic targets of LNM is important for early and non-invasive detection of patients with a high risk of LNM and guiding individualized therapy. Various cell constitutions of the primary tumor and lymph node microenvironment was characterized based on scRNA-seq data. The copy number variation (CNV) analysis was performed to probe clonal structures and origins of metastatic lymph nodes, and found 6q loss and 20q gain may drive LNM in LUAD. Then a LNM-related cell subset, named Scissor+ cells, was identified using the Scissor algorithm. And cell-cell communication network among Scissor+ cells and microenvironment was further analyzed. Besides, a pro-LNM signature was subsequently constructed based on 27 genes using pseudotime trajectory analysis and gene set variation analysis. The pro-LNM signature showed a significant correlation with N stage and a good predictive ability of LUAD survival. At last, we identified that erastin and gefitinib could potentially inhibit LNM by targeting Scissor+ cells based on the drug sensitivity data of the cancer cell lines, which provided new insights for LUAD therapy.

Single Cell Transcriptomic Analysis in a Mouse Model of Barth Syndrome Reveals Cell-Specific Alterations in Gene Expression and Intercellular Communication.

Barth Syndrome, a rare X-linked disorder affecting 1:300,000 live births, results from defects in Tafazzin, an acyltransferase that remodels cardiolipin and is essential for mitochondrial respiration. Barth Syndrome patients develop cardiomyopathy, muscular hypotonia and cyclic neutropenia during childhood, rarely surviving to middle age. At present, no effective therapy exists, and downstream transcriptional effects of Tafazzin dysfunction are incompletely understood. To identify novel, cell-specific, pathological pathways that mediate heart dysfunction, we performed single-nucleus RNA-sequencing (snRNA-seq) on wild-type (WT) and Tafazzin-knockout (Taz-KO) mouse hearts. We determined differentially expressed genes (DEGs) and inferred predicted cell-cell communication networks from these data. Surprisingly, DEGs were distributed heterogeneously across the cell types, with fibroblasts, cardiomyocytes, endothelial cells, macrophages, adipocytes and pericytes exhibiting the greatest number of DEGs between genotypes. One differentially expressed gene was detected for the lymphatic endothelial and mesothelial cell types, while no significant DEGs were found in the lymphocytes. A Gene Ontology (GO) analysis of these DEGs showed cell-specific effects on biological processes such as fatty acid metabolism in adipocytes and cardiomyocytes, increased translation in cardiomyocytes, endothelial cells and fibroblasts, in addition to other cell-specific processes. Analysis of ligand-receptor pair expression, to infer intercellular communication patterns, revealed the strongest dysregulated communication involved adipocytes and cardiomyocytes. For the knockout hearts, there was a strong loss of ligand-receptor pair expression involving adipocytes, and cardiomyocyte expression of ligand-receptor pairs underwent reorganization. These findings suggest that adipocyte and cardiomyocyte mitochondria may be most sensitive to mitochondrial Tafazzin deficiency and that rescuing adipocyte mitochondrial dysfunction, in addition to cardiomyocyte mitochondrial dysfunction, may provide therapeutic benefit in Barth Syndrome patients.

Integrative analysis of bulk and single-cell RNA sequencing data reveals distinct subtypes of MAFLD based on N1-methyladenosine regulator expression

BackgroundMetabolic dysfunction-associated fatty liver disease (MAFLD) is now the most prevalent chronic liver disease worldwide, with an increasing incidence rate. MAFLD is a heterogeneous disease that can have a low or high-risk profile for developing severe liver disease in its natural course. Recent evidence has highlighted the critical role of RNA methylation modification in the pathogenesis of various liver diseases. However, it remains unclear whether the RNA N1-methyladenosine (m1A) modification of immune cells could potentially contribute to the pathogenesis and heterogeneity of MAFLD. Materials and methodsTo address this issue, we conducted an integrated bioinformatics analysis of MAFLD bulk and single-cell RNA sequencing (scRNA-seq) data to pinpoint m1A regulators in the network. This was followed by a description of the immune landscape, pathway enrichment analysis, and molecular subtyping. ResultsThe expression patterns of m1A regulatory genes stratify MAFLD into two molecular subtypes, Cluster 1 and Cluster 2. These subtypes demonstrate different immune cell infiltration with distinct inflammation characteristics, which suggest different immune-inflammatory responses in the liver. Notably, Cluster 2 is associated with pro-inflammation and may be more likely to lead to progressive stages of MAFLD. Through intersection analysis of weighted gene co-expression network analysis (WGCNA) and m1A regulatory genes, three true hub genes (ALKBH1, YTHDC1, and YTHDF3) were identified, all of which were strongly correlated with infiltrating immune cells. The specific signaling pathways involved in the three core genes were derived from genomic variation analysis. Furthermore, scRNA-seq data from 33,168 cells from six liver samples identified 26 cell clusters and eight cell types, with endothelial cells, macrophages, and monocytes showing the most significant differences between MAFLD and normal controls. The cell-cell communication network between immune cells and non-parenchymal cells was extremely sophisticated and changed significantly in MAFLD. ConclusionsIn summary, these findings demonstrate the involvement of m1A in MAFLD heterogeneity and emphasize the crucial role of m1A modulation of immune cells in regulating inflammation in MAFLD. These results may suggest potential therapeutic strategies for MAFLD.

Dictionary of immune responses to 86 cytokines in vivoat single-cell resolution

Abstract Cytokines mediate cell-cell communication in the immune system and represent important therapeutic targets. A myriad of studies have underscored their central role in immune function, yet we lack a global view of the cellular responses of each immune cell type to each cytokine. To address this gap we created the Immune Dictionary – a compendium of single-cell transcriptomic profiles of over 20 cell types in response to each of 86 cytokines in murine lymph nodes in vivo, representing over 1,500 cytokine-cell type combinations. A cytokine-centric view of the dictionary revealed that most cytokines induced highly cell type-specific responses. For example, the inflammatory cytokine IL-1β induced distinct gene programs in almost every cell type. A cell type-centric view of the dictionary identified multiple cytokine-driven cellular polarization states in each immune cell type, including previously uncharacterized states such as an IL-18-induced polyfunctional NK cell state. Based on the dictionary, we developed companion software, Immune Response Enrichment Analysis (IREA), for assessing cytokine activities and immune cell polarization from gene expression data, and applied it to reveal cytokine networks in tumors following immune checkpoint blockade therapy. Our dictionary generates new hypotheses for cytokine functions, illuminates pleiotropic effects of cytokines, expands our knowledge of activation states of each immune cell type, and provides a framework to deduce the roles of specific cytokines and cell-cell communication networks in any immune response. This work was supported by the NIH Grant RM1HG006193 and an Adelson Medical Research Foundation Grant to N.H. This work was also supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) Doctoral Fellowship, Whitaker Health Sciences Fund Fellowship, and Wellington and Irene Loh Fund Fellowship to A.C., and NCI Research Specialist Award (R50CA251956) to S.L.

Evaluating the transcriptional landscape and cell-cell communication networks in chronically irradiated parotid glands

Understanding the transcriptional landscape that results in chronic salivary hypofunction after irradiation will help identify injury mechanisms and develop regenerative therapies. We present scRNA-seq analysis from control and irradiated murine parotid glands collected 10months after irradiation. We identify a population of secretory cells defined by specific expression of Etv1, which may be an acinar cell precursor. Acinar and Etv1+ secretory express Ntrk2 and Erbb3, respectively while the ligands for these receptors are expressed in myoepithelial and stromal cells. Furthermore, our data suggests that secretory cells and CD4+CD8+T-cells are the most transcriptionally affected during chronic injury with radiation, suggesting active immune involvement. Lastly, evaluation of cell-cell communication networks predicts that neurotrophin, neuregulin, ECM, and immune signaling are dysregulated after irradiation, and thus may play a role in the lack of repair. This resource will be helpful to understand cell-specific pathways that may be targeted to repair chronic damage in irradiated glands.

Phenotypic plasticity: The role of a phosphatase family Rap in the genetic regulation of Bacilli.

In the last two decades, an increasing number of bacterial species have been recognized that are able to generate a phenotypically diverse population that shares an identical genotype. This ability is dependent on a complex genetic regulatory network that includes cellular and environmental signals, as well as stochastic elements. Among Bacilli, a broadly distributed family of Rap (Response-regulator aspartyl phosphate) phosphatases is known to modulate the function of the main phenotypic heterogeneity regulators by controlling their phosphorylation. Even more, their related extracellular Phr (Phosphatase regulator) peptides function as signals, creating a cell-cell communication network that regulates the phenotypic development of the entire population. In this review, we examine the role that the Rap phosphatases and their Phr peptides play in the regulation of Bacillus subtilis phenotypic differentiation, and in other members of the Bacillus genus. We also highlight the contribution of these regulatory elements to the fitness of bacterial cells and mobile genetic elements, for example, prophages and conjugative vectors.

Abstract 5445: Segmentation-free analysis of multiplexed images with unbiased spatial analytics and explainable AI for predicting disease outcomes

Abstract Background: The spatial intratumor heterogeneity (ITH) is widely acknowledged as driving therapeutic response and providing fuel for drug resistance. Currently, patient selection for immunotherapy is driven mostly by PD-1/PD-L1 based IHC tests and mutational analysis. These oversimplified approaches fail to predict the risk of recurrence, therapeutic response and drug resistance with high accuracy. We hypothesize that functional responses of heterogeneous non-random spatial arrangements of tumor, stromal and immune cells in the tumor microenvironment are determined by distinct combinations of their internal states and spatial interactions within neighborhoods. The interactions generate distinct cell-cell communication networks forming functional spatial configurations of cells, termed microdomains, as organizational units of spatial ITH. Deriving the spatial networks within each microdomain with unbiased spatial analytics and the underlying network biology through explainable AI, is key to understanding tumor initiation, tumor progression, and response to therapy. Problem: There has been an explosion of spatial imaging technologies using immunofluorescence and/or mass spectrometry for intact tissues measuring protein expressions, DNA and RNA probes. To extract high-value knowledge from these multiplexed datasets, a key first step is to segment cells accurately. Despite decades of research, this step remains elusive due to imaging artifacts arising from issues with tile stitching, incorrect registration, signal oversaturation, non-uniform illumination, poor or high-background nuclei signal, defocus, varying cell and nuclear shapes, fluorescence emission efficiency variation, overlapping and/or superimposed nuclei and low resolution (e.g., mass cytometry). Those artifacts may lead to incorrect cell phenotypes, incomplete cell phenotype atlases, and missing rare cell, fusion cell or transition cell types. Solution: We present TumorMapr™, a segmentation-free, unbiased spatial analytics and explainable AI platform that extracts information and creates knowledge from patient disease pathology samples imaged with any technology including fluorescence, mass spectrometry etc. Results: We apply TumorMapr on hyperplexed immunofluorescence dataset of colorectal cancer and hyperplexed imaging mass cytometry dataset of triple negative breast cancer to discover functional cell prototypes involving spatial collections of neighboring pixels highly predictive of disease progression and response to therapy, tumor promoting and tumor restraining microdomains and microdomain-specific network biology predictive of disease outcomes. We further compare these results with segmentation-based approaches to showcase the discovery of novel cell prototypes. Citation Format: Filippo Pullara, Brian Falkenstein, Bruce Campbell, Samantha Panakkal, Akif Burak Tosun, Jeffrey Fine, S. Chakra Chennubhotla. Segmentation-free analysis of multiplexed images with unbiased spatial analytics and explainable AI for predicting disease outcomes. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5445.

Integrated single-cell RNA-seq analysis reveals the vital cell types and dynamic development signature of atherosclerosis.

Introduction: In the development of atherosclerosis, the remodeling of blood vessels is a key process involving plaque formation and rupture. So far, most reports mainly believe that macrophages, smooth muscle cells, and endothelial cells located at the intima and media of artery play the key role in this process. Few studies had focused on whether fibroblasts located at adventitia are involved in regulating disease process. Methods and results: In this study, we conducted in-depth analysis of single-cell RNA-seq data of the total of 18 samples from healthy and atherosclerotic arteries. This study combines several analysis methods including transcription regulator network, cell-cell communication network, pseudotime trajectory, gene set enrichment analysis, and differential expression analysis. We found that SERPINF1 is highly expressed in fibroblasts and is involved in the regulation of various signaling pathways. Conclusion: Our research reveals a potential mechanism of atherosclerosis, SERPINF1 regulates the formation and rupture of plaques through the Jak-STAT signaling pathway, which may provide new insights into the pathological study of disease. Moreover, we suggest that SRGN and IGKC as potential biomarkers for unstable arterial plaques.

Integrated Immune Cell-Cell Communication Networks Underpinning Rheumatoid Arthritis Pathogenesis

Rheumatoid Arthritis (RA) is a chronic, systemic auto-inflammatory disease that targets peripheral joints causing bone erosion, worsened mobility, and lower quality of life. RA is a complex autoimmune disease that develops through the combined actions of many cell types. In particular, monocytes, fibroblasts, and T cells play critical roles within the arthritic joint driving disease pathogenesis. These cells communicate with each other via ligand-receptor interactions orchestrating inflammatory responses ultimately leading to joint destruction. However, it remains unclear how the combined efforts of these different cells form an integrated network of immune responses which ultimately lead to disease development. Therefore, we hypothesized that an integrated communication network between the different immune cells found within RA joints functions to promote inflammation and drive RA disease pathogenesis. I utilized predictive assessment of cell-cell communication networks through single-cell RNA-sequencing to determine how immune cell interactions differ between autoimmune and non-autoimmune joint destruction. These studies identified a novel cell-cell communication network in which monocytes, fibroblasts and T cells cooperate to promote cell-cell interactions, immune activation, and induction of pro-inflammatory gene networks. Together, these results identify numerous potential therapeutic targets for the intervention of RA disease.

Spectrin-Based Regulation of Cardiac Fibroblast Cell-Cell Communication.

Cardiac fibroblasts (CFs) maintain the fibrous extracellular matrix (ECM) that supports proper cardiac function. Cardiac injury induces a transition in the activity of CFs to promote cardiac fibrosis. CFs play a critical role in sensing local injury signals and coordinating the organ level response through paracrine communication to distal cells. However, the mechanisms by which CFs engage cell-cell communication networks in response to stress remain unknown. We tested a role for the action-associated cytoskeletal protein βIV-spectrin in regulating CF paracrine signaling. Conditioned culture media (CCM) was collected from WT and βIV-spectrin deficient (qv4J) CFs. WT CFs treated with qv4J CCM showed increased proliferation and collagen gel compaction compared to control. Consistent with the functional measurements, qv4J CCM contained higher levels of pro-inflammatory and pro-fibrotic cytokines and increased concentration of small extracellular vesicles (30-150 nm diameter, exosomes). Treatment of WT CFs with exosomes isolated from qv4J CCM induced a similar phenotypic change as that observed with complete CCM. Treatment of qv4J CFs with an inhibitor of the βIV-spectrin-associated transcription factor, STAT3, decreased the levels of both cytokines and exosomes in conditioned media. This study expands the role of the βIV-spectrin/STAT3 complex in stress-induced regulation of CF paracrine signaling.

Improved in situ sequencing for high-resolution targeted spatial transcriptomic analysis in tissue sections

Spatial transcriptomics enables the study of localization-indexed gene expression activity in tissues, providing the transcriptional landscape that in turn indicates the potential regulatory networks of gene expression. In situ sequencing (ISS) is a targeted spatial transcriptomic technique, based on padlock probe and rolling circle amplification combined with next-generation sequencing chemistry, for highly multiplexed in situ gene expression profiling. Here, we present improved in situ sequencing (IISS) that exploits a new probing and barcoding approach, combined with advanced image analysis pipelines for high-resolution targeted spatial gene expression profiling. We develop an improved combinatorial probe anchor ligation chemistry using a 2-base encoding strategy for barcode interrogation. The new encoding strategy results in higher signal intensity as well as improved specificity for in situ sequencing, while maintaining a streamlined analysis pipeline for targeted spatial transcriptomics. We show that IISS can be applied to both fresh frozen tissue and formalin-fixed paraffin-embedded tissue sections for single-cell level spatial gene expression analysis, based on which the developmental trajectory and cell-cell communication networks can also be constructed.

Single-cell analysis reveals melanocytes may promote inflammation in chronic wounds through cathepsin G.

During acute wound (AW) healing, a series of proper communications will occur between different epidermal cells at precise temporal stages to restore the integrity of the skin. However, it is still unclear what variation happened in epidermal cell interaction in the chronic wound environment. To provide new insights into chronic wound healing, we reconstructed the variations in the epidermal cell-cell communication network that occur in chronic wound healing via single-cell RNA-seq (scRNA-seq) data analysis. We found that the intricate cellular and molecular interactions increased in pressure ulcer (PU) compared to AW, especially the PARs signaling pathways were significantly upregulated. It shows that the PARs signaling pathways' main source was melanocytes and the CTSG-F2RL1 ligand-receptor pairs were its main contributor. Cathepsin G (CatG or CTSG) is a serine protease mainly with trypsin- and chymotrypsin-like specificity. It is synthesized and secreted by some immune or non-immune cells. Whereas, it has not been reported that melanocytes can synthesize and secrete the CTSG. F2R Like Trypsin Receptor 1 (F2RL1) is a member of proteinase-activated receptors (PARs) that are irreversibly activated by proteolytic cleavage and its stimulation can promote inflammation and inflammatory cell infiltration. In this study, we found that melanocytes increased in pressure ulcers, melanocytes can synthesize and secrete the CTSG and may promote inflammation in chronic wounds through CTSG-F2RL1 pairs, which may be a novel potential target and a therapeutic strategy in the treatment of chronic wounds.

A novel enterocyte-related 4-gene signature for predicting prognosis in colon adenocarcinoma.

Colon adenocarcinoma (COAD) is a fatal disease, and its cases are constantly increasing worldwide. Further, the therapeutic and management strategies for patients with COAD are still unsatisfactory due to the lack of accurate patient classification and prognostic models. Therefore, our study aims to identify prognostic markers in patients with COAD and construct a cell subtype-specific prognostic model with high accuracy and robustness. Single-cell transcriptomic data of six samples were retrieved from the Gene expression omnibus (GEO) database. The cluster annotation and cell-cell communication analysis identified enterocytes as a key player mediating signal communication networks. A four-gene signature prognostic model was constructed based on the enterocyte-related differentially expressed genes (ERDEGs) in patients with COAD of the Cancer Genome Atlas cohort. The prognostic model was validated on three external validation cohorts from the GEO database. The correlation between immune cell infiltration, immunotherapy response, drug sensitivity, and the four-gene signature prognostic model was investigated. Finally, immunohistochemistry (IHC) was performed to determine the expression of the four genes. We found that the proportion of epithelial cells was obviously large in COAD samples. Further analysis of epithelial cells showed that the activity of the enterocytes was highest in the cell-cell communication network. Based on enterocyte data, 30 ERDEGs were identified and a 4-gene prognostic model including CPM, CLCA4, ELOVL6, and ATP2A3 was developed and validated. The risk score derived from this model was considered as an independent variable factor to predict overall survival. The patients were divided into high- and low-risk groups based on the median riskscore value. The correlation between immune cell infiltration, immunotherapy response, immune status, clinical characteristics, drug sensitivity, and risk score was analyzed. IHC confirmed the expression of signature genes in tissues from normal individuals, patients with polyps, and COAD. In this study, we constructed and validated a novel four-gene signature prognostic model, which could effectively predict the response to immunotherapy and overall survival in patients with COAD. More importantly, this model provides useful insight into the management of colon cancer patients and aids in designing personalized therapy.

Remarkable sex-specific differences at single-cell resolution in neonatal hyperoxic lung injury.

Exposure to supraphysiological concentrations of oxygen (hyperoxia) predisposes to bronchopulmonary dysplasia (BPD), which is characterized by abnormal alveolarization and pulmonary vascular development, in preterm neonates. Neonatal hyperoxia exposure is used to recapitulate the phenotype of human BPD in murine models. Male sex is considered an independent predictor for the development of BPD, but the main mechanisms underlying sexually dimorphic outcomes are unknown. Our objective was to investigate sex-specific and cell-type specific transcriptional changes that drive injury in the neonatal lung exposed to hyperoxia at single-cell resolution and delineate the changes in cell-cell communication networks in the developing lung. We used single-cell RNA sequencing (scRNAseq) to generate transcriptional profiles of >35,000 cells isolated from the lungs of neonatal male and female C57BL/6 mice exposed to 95% [Formula: see text] between PND1-5 (saccular stage of lung development) or normoxia and euthanized at PND7 (alveolar stage of lung development). ScRNAseq identified 22 cell clusters with distinct populations of endothelial, epithelial, mesenchymal, and immune cells. Our data identified that the distal lung vascular endothelium (composed of aerocytes and general capillary endothelial cells) is exquisitely sensitive to hyperoxia exposure with the emergence of an intermediate capillary endothelial population with both general capillaries (gCap) and aerocytes or alveolar capillaries (aCap) markers. We also identified a myeloid-derived suppressor cell population from the lung neutrophils. Sex-specific differences were evident in all lung cell subpopulations but were striking among the lung immune cells. Finally, we identified that the specific intercellular communication networks and the ligand-receptor pairs that are impacted by neonatal hyperoxia exposure.

Research strategies for single-cell transcriptome analysis in plant leaves.

The recent and continuous improvement in single-cell RNA sequencing (scRNA-seq) technology has led to its emergence as an efficient experimental approach in plant research. However, compared with single-cell research in animals and humans, the application of scRNA-seq in plant research is limited by several challenges, including cell separation, cell type annotation, cellular function analysis, and cell-cell communication networks. In addition, the unavailability of corresponding reliable and stable analysis methods and standards has resulted in the relative decentralization of plant single-cell research. Considering these shortcomings, this review summarizes the research progress in plant leaf using scRNA-seq. In addition, it describes the corresponding feasible analytical methods and associated difficulties and problems encountered in the current research. In the end, we provide a speculative overview of the development of plant single-cell transcriptome research in the future.

Single-cell and spatial mapping Identify cell types and signaling Networks in the human ureter.

Tissue engineering offers a promising treatment strategy for ureteral strictures, but its success requires an in-depth understanding of the architecture, cellular heterogeneity, and signaling pathways underlying tissue regeneration. Here, we define and spatially map cell populations within the human ureter using single-cell RNA sequencing, spatial gene expression, and immunofluorescence approaches. We focus on the stromal and urothelial cell populations to enumerate the distinct cell types composing the human ureter and infer potential cell-cell communication networks underpinning the bi-directional crosstalk between these compartments. Furthermore, we analyze and experimentally validate the importance of the sonic hedgehog (SHH) signaling pathway in adult progenitor cell maintenance. The SHH-expressing basal cells support organoid generation invitro and accurately predict the differentiation trajectory from basal progenitor cells to terminally differentiated umbrella cells. Our results highlight the essential processes involved in adult ureter tissue homeostasis and provide a blueprint for guiding ureter tissue engineering.