Neutrophil trapping and nexocytosis, mast cell-mediated processes for inflammatory signal relay.

Neutrophils are sentinel immune cells with essential roles for antimicrobial defense. Most of our knowledge on neutrophil tissue navigation derived from wounding and infection models, whereas allergic conditions remained largely neglected. Here, we analyzed allergen-challenged mouse tissues and discovered that degranulating mast cells (MCs) trap living neutrophils inside them. MCs release the attractant leukotriene B4 to re-route neutrophils toward them, thus exploiting a chemotactic system that neutrophils normally use for intercellular communication. After MC intracellular trap (MIT) formation, neutrophils die, but their undigested material remains inside MC vacuoles over days. MCs benefit from MIT formation, increasing their functional and metabolic fitness. Additionally, they are more pro-inflammatory and can exocytose active neutrophilic compounds with a time delay (nexocytosis), eliciting a type 1 interferon response in surrounding macrophages. Together, our study highlights neutrophil trapping and nexocytosis as MC-mediated processes, which may relay neutrophilic features over the course of chronic allergic inflammation.

COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas.

A dysfunctional immune response in coronavirus disease 2019 (COVID-19) patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells. The large dataset enabled us to identify that different peripheral immune subtype changes are associated with distinct clinical features, including age, sex, severity, and disease stages of COVID-19. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was found in diverse epithelial and immune cell types, accompanied by dramatic transcriptomic changes within virus-positive cells. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis of and developing effective therapeutic strategies for COVID-19.

Detecting Tumor Antigen-Specific T Cells via Interaction-Dependent Fucosyl-Biotinylation.

Re-activation and clonal expansion of tumor-specific antigen (TSA)-reactive T cells are critical to the success of checkpoint blockade and adoptive transfer of tumor-infiltrating lymphocyte (TIL)-based therapies. There are no reliable markers to specifically identify the repertoire of TSA-reactive T cells due to their heterogeneous composition. We introduce FucoID as a general platform to detect endogenous antigen-specific T cells for studying their biology. Through this interaction-dependent labeling approach, intratumoral TSA-reactive CD4+, CD8+ T cells, and TSA-suppressive CD4+ T cells can be detected and separated from bystander T cells based on their cell-surface enzymatic fucosyl-biotinylation. Compared to bystander TILs, TSA-reactive TILs possess a distinct T cell receptor (TCR) repertoire and unique gene features. Although exhibiting a dysfunctional phenotype, TSA-reactive CD8+ TILs possess substantial capabilities of proliferation and tumor-specific killing. Featuring genetic manipulation-free procedures and a quick turnover cycle, FucoID should have the potential of accelerating the pace of personalized cancer treatment.

Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer.

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for defining cellular diversity in tumors, but its application toward dissecting mechanisms underlying immune-modulating therapies is scarce. We performed scRNA-seq analyses on immune and stromal populations from colorectal cancer patients, identifying specific macrophage and conventional dendritic cell (cDC) subsets as key mediators of cellular cross-talk in the tumor microenvironment. Defining comparable myeloid populations in mouse tumors enabled characterization of their response to myeloid-targeted immunotherapy. Treatment with anti-CSF1R preferentially depleted macrophages with an inflammatory signature but spared macrophage populations that in mouse and human expresses pro-angiogenic/tumorigenic genes. Treatment with a CD40 agonist antibody preferentially activated a cDC population and increased Bhlhe40+ Th1-like cells and CD8+ memory T cells. Our comprehensive analysis of key myeloid subsets in human and mouse identifies critical cellular interactions regulating tumor immunity and defines mechanisms underlying myeloid-targeted immunotherapies currently undergoing clinical testing.

SEGCECO: Subgraph Embedding of Gene expression matrix for prediction of CEll-cell COmmunication.

Recent advances in single-cell RNA sequencing technology have eased analyses of signaling networks of cells. Recently, cell-cell interaction has been studied based on various link prediction approaches on graph-structured data. These approaches have assumptions about the likelihood of node interaction, thus showing high performance for only some specific networks. Subgraph-based methods have solved this problem and outperformed other approaches by extracting local subgraphs from a given network. In this work, we present a novel method, called Subgraph Embedding of Gene expression matrix for prediction of CEll-cell COmmunication (SEGCECO), which uses an attributed graph convolutional neural network to predict cell-cell communication from single-cell RNA-seq data. SEGCECO captures the latent and explicit attributes of undirected, attributed graphs constructed from the gene expression profile of individual cells. High-dimensional and sparse single-cell RNA-seq data make converting the data into a graphical format a daunting task. We successfully overcome this limitation by applying SoptSC, a similarity-based optimization method in which the cell-cell communication network is built using a cell-cell similarity matrix which is learned from gene expression data. We performed experiments on six datasets extracted from the human and mouse pancreas tissue. Our comparative analysis shows that SEGCECO outperforms latent feature-based approaches, and the state-of-the-art method for link prediction, WLNM, with 0.99 ROC and 99% prediction accuracy. The datasets can be found at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84133 and the code is publicly available at Github https://github.com/sheenahora/SEGCECO and Code Ocean https://codeocean.com/capsule/8244724/tree.

Big-Data Glycomics: Tools to Connect Glycan Biosynthesis to Extracellular Communication.

Characteristically, cells must sense and respond to environmental cues. Despite the importance of cell-cell communication, our understanding remains limited and often lacks glycans. Glycans decorate proteins and cell membranes at the cell-environment interface, and modulate intercellular communication, from development to pathogenesis. Providing further challenges, glycan biosynthesis and cellular behavior are co-regulating systems. Here, we discuss how glycosylation contributes to extracellular responses and signaling. We further organize approaches for disentangling the roles of glycans in multicellular interactions using newly available datasets and tools, including glycan biosynthesis models, omics datasets, and systems-level analyses. Thus, emerging tools in big data analytics and systems biology are facilitating novel insights on glycans and their relationship with multicellular behavior.

Identifying phenotype-associated subpopulations through LP_SGL.

Single-cell RNA sequencing (scRNA-seq) enables the resolution of cellular heterogeneity in diseases and facilitates the identification of novel cell types and subtypes. However, the grouping effects caused by cell-cell interactions are often overlooked in the development of tools for identifying subpopulations. We proposed LP_SGL which incorporates cell group structure to identify phenotype-associated subpopulations by integrating scRNA-seq, bulk expression and bulk phenotype data. Cell groups from scRNA-seq data were obtained by the Leiden algorithm, which facilitates the identification of subpopulations and improves model robustness. LP_SGL identified a higher percentage of cancer cells, T cells and tumor-associated cells than Scissor and scAB on lung adenocarcinoma diagnosis, melanoma drug response and liver cancer survival datasets, respectively. Biological analysis on three original datasets and four independent external validation sets demonstrated that the signaling genes of this cell subset can predict cancer, immunotherapy and survival.

Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs).

Cell-cell interactions are important to numerous biological systems, including tissue microenvironments, the immune system, and cancer. However, current methods for studying cell combinations and interactions are limited in scalability, allowing just hundreds to thousands of multicell assays per experiment; this limited throughput makes it difficult to characterize interactions at biologically relevant scales. Here, we describe a paradigm in cell interaction profiling that allows accurate grouping of cells and characterization of their interactions for tens to hundreds of thousands of combinations. Our approach leverages high-throughput droplet microfluidics to construct multicellular combinations in a deterministic process that allows inclusion of programmed reagent mixtures and beads. The combination droplets are compatible with common manipulation and measurement techniques, including imaging, barcode-based genomics, and sorting. We demonstrate the approach by using it to enrich for chimeric antigen receptor (CAR)-T cells that activate upon incubation with target cells, a bottleneck in the therapeutic T cell engineering pipeline. The speed and control of our approach should enable valuable cell interaction studies.

Phenotypic analysis with trans-recombination-based genetic mosaic models.

Mosaicism refers to the presence of genetically distinct cell populations in an individual derived from a single zygote, which occurs during the process of development, aging, and genetic diseases. To date, a variety of genetically engineered mosaic analysis models have been established and widely used in studying gene function at exceptional cellular and spatiotemporal resolution, leading to many ground-breaking discoveries. Mosaic analysis with a repressible cellular marker and mosaic analysis with double markers are genetic mosaic analysis models based on trans-recombination. These models can generate sibling cells of distinct genotypes in the same animal and simultaneously label them with different colors. As a result, they offer a powerful approach for lineage tracing and studying the behavior of individual mutant cells in a wildtype environment, which is particularly useful for determining whether gene function is cell autonomous or nonautonomous. Here, we present a comprehensive review on the establishment and applications of mosaic analysis with a repressible cellular marker and mosaic analysis with double marker systems. Leveraging the capabilities of these mosaic models for phenotypic analysis will facilitate new discoveries on the cellular and molecular mechanisms of development and disease.

T cell and airway smooth muscle interaction: a key driver of asthmatic airway inflammation and remodeling.

Cross talk between T cells and airway smooth muscle (ASM) may play a role in modulating asthmatic airway inflammation and remodeling. Infiltrating T cells have been observed within the ASM bundles of asthmatics, and a wide range of direct and indirect interactions between T cells and ASM has been demonstrated using various in vitro and in vivo model systems. Contact-dependent mechanisms such as ligation and activation of cellular adhesion and costimulatory molecules, as well as the formation of lymphocyte-derived membrane conduits, facilitate the adhesion, bidirectional communication, and transfer of materials between T and ASM cells. T cell-derived cytokines, particularly of the Th1, Th2, and Th17 subsets, modulate the secretome, proliferation, and contractility of ASM cells. This review summarizes the mechanisms governing T cell-ASM cross talk in the context of asthma. Understanding the underlying mechanistic basis is important for directing future research and developing therapeutic interventions targeted toward this complex interaction.

Ischemia-reperfusion responses in human lung transplants at the single-cell resolution.

Ischemia-reperfusion is an unavoidable step of organ transplantation. Development of therapeutics for lung injury during transplantation has proved challenging; understanding lung injury from human data at the single-cell resolution is required to accelerate the development of therapeutics. Donor lung biopsies from 6 human lung transplant cases were collected at the end of cold preservation and 2-hour reperfusion and underwent single-cell RNA sequencing. Donor and recipient origin of cells from the reperfusion timepoint were deconvolved. Gene expression profiles were: (1) compared between each donor cell type between timepoints and (2) compared between donor and recipient cells. Inflammatory responses from donor lung macrophages were found after reperfusion with upregulation of multiple cytokines and chemokines, especially IL-1ß and IL-1α. Significant inflammatory responses were found in alveolar epithelial cells (featured by CXCL8) and lung endothelial cells (featured by IL-6 upregulation). Different inflammatory responses were noted between donor and recipient monocytes and CD8+ T cells. The inflammatory signals and differences between donor and recipient cells observed provide insight into the cellular and molecular mechanisms of ischemia-reperfusion induced lung injury. Further investigations may lead to the development of novel targeted therapeutics.

Intratumor transforming growth factor-ß signaling with extracellular matrix-related gene regulation marks chemotherapy-resistant gastric cancer.

Drug-tolerant persister (DTP) cells remain following chemotherapy and can cause cancer relapse. However, it is unclear when acquired resistance to chemotherapy emerges. Here, we compared the gene expression profiles of gastric cancer patient-derived cells (GC PDCs) and their respective xenograft tumors with different sensitivities to 5-fluorouracil (5-FU) by using immunodeficient female BALB/c-nu mice. RNA sequencing analysis of 5-FU-treated PDCs demonstrated that DNA replication/cell cycle-related genes were transiently induced in the earlier phase of DTP cell emergence, while extracellular matrix (ECM)-related genes were sustainably upregulated during long-term cell survival in 5-FU-resistant residual tumors. NicheNet analysis, which uncovers cell-cell signal interactions, indicated the transforming growth factor-ß (TGF-ß) pathway as the upstream regulator in response to 5-FU treatment. This induced ECM-related gene expression in the 5-FU-resistant tumor model. In the 5-FU-resistant residual tumors, there was a marked upregulation of cancer cell-derived TGF-ß1 expression and increased phosphorylation of SMAD3, a downstream regulator of the TGF-ß receptor. By contrast, these responses were not observed in a 5-FU-sensitive tumor model. We further found that TGF-ß-related upregulation of ECM genes was preferentially observed in non-responders to chemotherapy with 5-FU and/or oxaliplatin among 22 patient-derived xenograft tumors. These observations suggest that chemotherapy-induced activation of the TGF-ß1/SMAD3/ECM-related gene axis is a potential biomarker for the emergence of drug resistance in GCs.

A new integrative analysis of histopathology and single cell RNA-seq reveals the CCL5 mediated T and NK cell interaction with vascular cells in idiopathic pulmonary arterial hypertension.

BACKGROUND: Inflammation and dysregulated immunity play vital roles in idiopathic pulmonary arterial hypertension (IPAH), while the mechanisms that initiate and promote these processes are unclear. METHODS: Transcriptomic data of lung tissues from IPAH patients and controls were obtained from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA), differential expression analysis, protein-protein interaction (PPI) and functional enrichment analysis were combined with a hemodynamically-related histopathological score to identify inflammation-associated hub genes in IPAH. The monocrotaline-induced rat model of pulmonary hypertension was utilized to confirm the expression pattern of these hub genes. Single-cell RNA-sequencing (scRNA-seq) data were used to identify the hub gene-expressing cell types and their intercellular interactions. RESULTS: Through an extensive bioinformatics analysis, CXCL9, CCL5, GZMA and GZMK were identified as hub genes that distinguished IPAH patients from controls. Among these genes, pulmonary expression levels of Cxcl9, Ccl5 and Gzma were elevated in monocrotaline-exposed rats. Further investigation revealed that only CCL5 and GZMA were highly expressed in T and NK cells, where CCL5 mediated T and NK cell interaction with endothelial cells, smooth muscle cells, and fibroblasts through multiple receptors. CONCLUSIONS: Our study identified a new inflammatory pathway in IPAH, where T and NK cells drove heightened inflammation predominantly via the upregulation of CCL5, providing groundwork for the development of targeted therapeutics.

Invasion of the stigma by oomycete pathogenic hyphae or pollen tubes: striking similarities and differences.

Both the pollen tube and hyphae of filamentous pathogens penetrate the outer layer of the host and then grow within host tissues. Early epidermal responses are decisive for the outcome of these two-cell interaction processes. We identified a single cell type, the papilla in the stigma of Arabidospis, as a tool to conduct a comprehensive comparative analysis on how an epidermal cell responds to the invasion of an unwanted pathogen or a welcome pollen tube. We showed that Phytophtora parasitica, a root oomycete, effectively breaches the stigmatic cell wall and develops as a biotroph within the papilla cytoplasm. These invasive features resemble the behaviour exhibited by the pathogen within its natural host cell, but diverge from the manner in which the pollen tube progresses, being engulfed within the papilla cell wall. Quantitative analysis revealed that both invaders trigger reorganization of the stigmatic endomembrane system and the actin cytoskeleton. While some remodelling processes are shared between the two interactions, others appear more specific towards the respective invader. These findings underscore the remarkable ability of an epidermal cell to differentiate between two types of invaders, thereby enabling it to trigger the most suitable response during the onset of invasion.

Revealing the pathogenesis of keloids based on the status: Active vs inactive.

Recently, the pathomechanisms of keloids have been extensively researched using transcriptomic analysis, but most studies did not consider the activity of keloids. We aimed to profile the transcriptomics of keloids according to their clinical activity and location within the keloid lesion, compared with normal and mature scars. Tissue samples were collected (keloid based on its activity (active and inactive), mature scar from keloid patients and normal scar (NS) from non-keloid patients). To reduce possible bias, all keloids assessed in this study had no treatment history and their location was limited to the upper chest or back. Multiomics assessment was performed by using single-cell RNA sequencing and multiplex immunofluorescence. Increased mesenchymal fibroblasts (FBs) was the main feature in keloid patients. Noticeably, the proportion of pro-inflammatory FBs was significantly increased in active keloids compared to inactive ones. To explore the nature of proinflammatory FBs, trajectory analysis was conducted and CCN family associated with mechanical stretch exhibited higher expression in active keloids. For vascular endothelial cells (VECs), the proportion of tip and immature cells increased in keloids compared to NS, especially at the periphery of active keloids. Also, keloid VECs highly expressed genes with characteristics of mesenchymal activation compared to NS, especially those from the active keloid center. Multiomics analysis demonstrated the distinct expression profile of active keloids. Clinically, these findings may provide the future appropriate directions for development of treatment modalities of keloids. Prevention of keloids could be possible by the suppression of mesenchymal activation between FBs and VECs and modulation of proinflammatory FBs may be the key to the control of active keloids.

Transcriptomic signatures of individual cell types in cerebral cavernous malformation.

Cerebral cavernous malformation (CCM) is a hemorrhagic neurovascular disease with no currently available therapeutics. Prior evidence suggests that different cell types may play a role in CCM pathogenesis. The contribution of each cell type to the dysfunctional cellular crosstalk remains unclear. Herein, RNA-seq was performed on fluorescence-activated cell sorted endothelial cells (ECs), pericytes, and neuroglia from CCM lesions and non-lesional brain tissue controls. Differentially Expressed Gene (DEG), pathway and Ligand-Receptor (LR) analyses were performed to characterize the dysfunctional genes of respective cell types within CCMs. Common DEGs among all three cell types were related to inflammation and endothelial-to-mesenchymal transition (EndMT). DEG and pathway analyses supported a role of lesional ECs in dysregulated angiogenesis and increased permeability. VEGFA was particularly upregulated in pericytes. Further pathway and LR analyses identified vascular endothelial growth factor A/ vascular endothelial growth factor receptor 2 signaling in lesional ECs and pericytes that would result in increased angiogenesis. Moreover, lesional pericytes and neuroglia predominantly showed DEGs and pathways mediating the immune response. Further analyses of cell specific gene alterations in CCM endorsed potential contribution to EndMT, coagulation, and a hypoxic microenvironment. Taken together, these findings motivate mechanistic hypotheses regarding non-endothelial contributions to lesion pathobiology and may lead to novel therapeutic targets. Video Abstract.

Minimal cellular automaton model with heterogeneous cell sizes predicts epithelial colony growth.

Regulation of cell proliferation is a crucial aspect of tissue development and homeostasis and plays a major role in morphogenesis, wound healing, and tumor invasion. A phenomenon of such regulation is contact inhibition, which describes the dramatic slowing of proliferation, cell migration and individual cell growth when multiple cells are in contact with each other. While many physiological, molecular and genetic factors are known, the mechanism of contact inhibition is still not fully understood. In particular, the relevance of cellular signaling due to interfacial contact for contact inhibition is still debated. Cellular automata (CA) have been employed in the past as numerically efficient mathematical models to study the dynamics of cell ensembles, but they are not suitable to explore the origins of contact inhibition as such agent-based models assume fixed cell sizes. We develop a minimal, data-driven model to simulate the dynamics of planar cell cultures by extending a probabilistic CA to incorporate size changes of individual cells during growth and cell division. We successfully apply this model to previous in-vitro experiments on contact inhibition in epithelial tissue: After a systematic calibration of the model parameters to measurements of single-cell dynamics, our CA model quantitatively reproduces independent measurements of emergent, culture-wide features, like colony size, cell density and collective cell migration. In particular, the dynamics of the CA model also exhibit the transition from a low-density confluent regime to a stationary postconfluent regime with a rapid decrease in cell size and motion. This implies that the volume exclusion principle, a mechanical constraint which is the only inter-cellular interaction incorporated in the model, paired with a size-dependent proliferation rate is sufficient to generate the observed contact inhibition. We discuss how our approach enables the introduction of effective bio-mechanical interactions in a CA framework for future studies.

Exploring coaggregation mechanisms involved in biofilm formation in drinking water through a proteomic-based approach.

AIM: Coaggregation, a highly specific cell-cell interaction mechanism, plays a pivotal role in multispecies biofilm formation. While it has been mostly studied in oral environments, its occurrence in aquatic systems is also acknowledged. Considering biofilm formation's economic and health-related implications in engineered water systems, it is crucial to understand its mechanisms. Here, we hypothesized that traceable differences at the proteome level might determine coaggregation ability. METHODS AND RESULTS: Two strains of Delftia acidovorans, isolated from drinking water were studied. First, in vitro motility assays indicated more swarming and twitching motility for the coaggregating strain (C+) than non-coaggregating strain (C-). By transmission electronic microscopy, we confirmed the presence of flagella for both strains. By proteomics, we detected a significantly higher expression of type IV pilus twitching motility proteins in C+, in line with the motility assays. Moreover, flagellum ring proteins were more abundant in C+, while those involved in the formation of the flagellar hook (FlE and FilG) were only detected in C-. All the results combined suggested structural and conformational differences between stains in their cell appendages. CONCLUSION: This study presents an alternative approach for identifying protein biomarkers to detect coaggregation abilities in uncharacterized strains.

Fibroblast regulates angiogenesis in assembled oral cancer organoid: A possible role of NNMT.

OBJECTIVE: Tumour angiogenesis is affected by various cell types in the tumour microenvironment (TME), including cancer cells and cancer-associated fibroblasts (CAFs). Here, an assembled organoid model was generated to investigate the mechanism by which the TME regulates angiogenesis in oral squamous cell carcinoma (OSCC). MATERIALS AND METHODS: Secretion of vascular endothelial growth factor-A (VEGFA) was analysed to compare the proangiogenic properties of OSCC cells and corresponding CAFs. Cell aggregates consisting of endothelial cells (ECs), CAFs and cancer cells were generated to construct assembled organoids. Nicotinamide N-methyltransferase (NNMT) was pharmacologically or genetically inhibited to block the activation of CAFs. ATAC-seq was employed to test the transcriptional network of fibroblasts overexpressing NNMT. RESULTS: Compared with cancer cells, CAFs secreted more VEGFA. Coculture with CAFs more effectively promoted the sprouting of ECs. Blockade of CAF activation via inhibition of NNMT drastically reduced the expression of CD31 in the assembled organoids. Overexpression of NNMT enhanced the transcription of genes related to angiogenesis in fibroblasts. Specifically, NNMT orchestrated the enrichment of the transcription factor JUNB at the promoter of VEGFA. CONCLUSIONS: We clarify that stromal NNMT enables the steady reproduction of angiogenesis in assembled oral cancer organoids, providing a novel target for exploiting antiangiogenic therapy.

Structure of cell-cell adhesion mediated by the Down syndrome cell adhesion molecule.

The Down syndrome cell adhesion molecule (DSCAM) belongs to the immunoglobulin superfamily (IgSF) and plays important roles in neural development. It has a large ectodomain, including 10 Ig-like domains and 6 fibronectin III (FnIII) domains. Previous data have shown that DSCAM can mediate cell adhesion by forming homophilic dimers between cells and contributes to self-avoidance of neurites or neuronal tiling, which is important for neural network formation. However, the organization and assembly of DSCAM at cell adhesion interfaces has not been fully understood. Here we combine electron microscopy and other biophysical methods to characterize the structure of the DSCAM-mediated cell adhesion and generate three-dimensional views of the adhesion interfaces of DSCAM by electron tomography. The results show that mouse DSCAM forms a regular pattern at the adhesion interfaces. The Ig-like domains contribute to both trans homophilic interactions and cis assembly of the pattern, and the FnIII domains are crucial for the cis pattern formation as well as the interaction with the cell membrane. By contrast, no obvious assembly pattern is observed at the adhesion interfaces mediated by mouse DSCAML1 or Drosophila DSCAMs, suggesting the different structural roles and mechanisms of DSCAMs in mediating cell adhesion and neural network formation.