From genetic mosaicism to tumorigenesis through indirect genetic effects.

Genetic mosaicism has long been linked to aging, and several hypotheses have been proposed to explain the potential connections between mosaicism and susceptibility to cancer. It has been proposed that mosaicism may disrupt tissue homeostasis by affecting intercellular communications and releasing microenvironmental constraints within tissues. The underlying mechanisms driving these tissue-level influences remain unidentified, however. Here, we present an evolutionary perspective on the interplay between mosaicism and cancer, suggesting that the tissue-level impacts of genetic mosaicism can be attributed to Indirect Genetic Effects (IGEs). IGEs can increase the level of cellular stochasticity and phenotypic instability among adjacent cells, thereby elevating the risk of cancer development within the tissue. Moreover, as cells experience phenotypic changes in response to challenging microenvironmental conditions, these changes can initiate a cascade of nongenetic alterations, referred to as Indirect non-Genetic Effects (InGEs), which in turn catalyze IGEs among surrounding cells. We argue that incorporating both InGEs and IGEs into our understanding of the process of oncogenic transformation could trigger a major paradigm shift in cancer research with far-reaching implications for practical applications.

Single-cell analysis of human prepuce reveals dynamic changes in gene regulation and cellular communications.

BACKGROUND: The cellular and molecular dynamics of human prepuce are crucial for understanding its biological and physiological functions, as well as the prevention of related genital diseases. However, the cellular compositions and heterogeneity of human prepuce at single-cell resolution are still largely unknown. Here we systematically dissected the prepuce of children and adults based on the single-cell RNA-seq data of 90,770 qualified cells. RESULTS: We identified 15 prepuce cell subtypes, including fibroblast, smooth muscle cells, T/natural killer cells, macrophages, vascular endothelial cells, and dendritic cells. The proportions of these cell types varied among different individuals as well as between children and adults. Moreover, we detected cell-type-specific gene regulatory networks (GRNs), which could contribute to the unique functions of related cell types. The GRNs were also highly dynamic between the prepuce cells of children and adults. Our cell-cell communication network analysis among different cell types revealed a set of child-specific (e.g., CD96, EPO, IFN-1, and WNT signaling pathways) and adult-specific (e.g., BMP10, NEGR, ncWNT, and NPR1 signaling pathways) signaling pathways. The variations of GRNs and cellular communications could be closely associated with prepuce development in children and prepuce maintenance in adults. CONCLUSIONS: Collectively, we systematically analyzed the cellular variations and molecular changes of the human prepuce at single-cell resolution. Our results gained insights into the heterogeneity of prepuce cells and shed light on the underlying molecular mechanisms of prepuce development and maintenance.

Cell-cell communications shape tumor microenvironment and predict clinical outcomes in clear cell renal carcinoma.

BACKGROUND: Cell-cell communications of various cell populations within tumor microenvironment play an essential role in primary tumor growth, metastasis evolution, and immune escape. Nevertheless, comprehensive investigation of cell-cell communications in the ccRCC (Clear cell renal carcinoma) microenvironment and how this interplay affects prognosis still remains limited. METHODS: Intercellular communications were characterized by single-cell data. Firstly, we employed "CellChat" package to characterize intercellular communications across all types of cells in microenvironment in VHL mutated and non-mutated samples from 8 patients, respectively. And pseudotime trajectory analyses were performed with monocle analyses. Finally clinical prognosis and immunotherapy efficacy with different landscapes of intercellular interplay are evaluated by TCGA-KIRC and immunotherapy cohort. RESULTS: Firstly, the VHL phenotype may be related to the intercellular communication landscape. And trajectory analysis reveals the potential relationship of cell-cell communication molecules with T cells and Myeloid cells differentiation. Furthermore, those molecules also correlate with the infiltration of T cells and Myeloid cells. A tumor cluster with highly expressed ligands was defined by quantitative analysis and transcription factor enrichment analysis, which was identified to be pivotal for intercellular communications in tumor microenvironment. Finally, bulk data indicates bulk that different clusters with different intercellular communications have significant predictive value for prognosis and distinguished immunotherapy efficiency. CONCLUSIONS: The intercellular communication landscapes of VHL wild and VHL mutant ccRCC vary. Intercellular communications within the tumor microenvironment also influence T cell and myeloid cell development and infiltration, as well as predict clinical prognosis and immunotherapy efficacy in ccRCC.

Defining Specific Cell States of MPTP-Induced Parkinson's Disease by Single-Nucleus RNA Sequencing.

Parkinson's disease (PD) is a neurodegenerative disease with an impairment of movement execution that is related to age and genetic and environmental factors. 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is a neurotoxin widely used to induce PD models, but the effect of MPTP on the cells and genes of PD has not been fully elucidated. By single-nucleus RNA sequencing, we uncovered the PD-specific cells and revealed the changes in their cellular states, including astrocytosis and endothelial cells' absence, as well as a cluster of medium spiny neuron cells unique to PD. Furthermore, trajectory analysis of astrocyte and endothelial cell populations predicted candidate target gene sets that might be associated with PD. Notably, the detailed regulatory roles of astrocyte-specific transcription factors Dbx2 and Sox13 in PD were revealed in our work. Finally, we characterized the cell-cell communications of PD-specific cells and found that the overall communication strength was enhanced in PD compared with a matched control, especially the signaling pathways of NRXN and NEGR. Our work provides an overview of the changes in cellular states of the MPTP-induced mouse brain.

Friend or foe? The tumour microenvironment dilemma in colorectal cancer.

The network of bidirectional homotypic and heterotypic interactions established among parenchymal tumour cells and surrounding mesenchymal stromal cells generates the tumour microenvironment (TME). These intricate crosstalks elicit both beneficial and adverse effects on tumour initiation and progression unbalancing the signals and responses from the neighbouring cells. Here, we highlight the structure, activities and evolution of TME cells considering a novel colorectal cancer (CRC) classification based on differential stromal composition and gene expression profiles. In this scenario, we scrutinise the molecular pathways that either change or become corrupted during CRC development and their relative prognostic value. Finally, we survey the therapeutic molecules directed against TME components currently available in clinical trials as well as those with stronger potential in preclinical studies. Elucidation of dynamic variations in the CRC TME cell composition and their relative contribution could provide novel diagnostic or prognostic biomarkers and allow more personalised therapeutic strategies.

Single-cell transcriptomics reveals tumor microenvironment remodeling in hepatocellular carcinoma with varying tumor subclonal complexity.

Introduction: The complexity of tumor cell subclonal structure has been extensively investigated in hepatocellular carcinoma. However, the role of subclonal complexity in reshaping the tumor microenvironment (TME) remains poorly understood. Methods: We integrated single-cell transcriptome sequencing data from four independent HCC cohorts, involving 30 samples, to decode the associations between tumor subclonal complexity and the TME. We proposed a robust metric to accurately quantify the degree of subclonal complexity for each sample based on discrete copy number variations (CNVs) profiles. Results: We found that tumor cells in the high-complexity group originated from the cell lineage with FGB overexpression and exhibited high levels of transcription factors associated with poor survival. In contrast, tumor cells in low-complexity patients showed activation of more hallmark signaling pathways, more active cell-cell communications within the TME and a higher immune activation status. Additionally, cytokines signaling activity analysis suggested a link between HMGB1 expressed by a specific endothelial subtype and T cell proliferation. Discussion: Our study sheds light on the intricate relationship between the complexity of subclonal structure and the TME, offering novel insights into potential therapeutic targets for HCC.

Single-cell sequencing of the substantia nigra reveals microglial activation in a model of MPTP.

Background: N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is a neurotoxin widely used to induce PD models, but the effect of MPTP on the cells and genes of PD has not been fully elucidated. Methods: Single-nucleus RNA sequencing was performed in the Substantia Nigra (SN) of MPTP mice. UMAP analysis was used for the dimensionality reduction visualization of the SN in the MPTP mice. Known marker genes highly expressed genes in each cluster were used to annotate most clusters. Specific Differentially Expressed Genes (DEGs) and PD risk genes analysis were used to find MPTP-associated cells. GO, KEGG, PPI network, GSEA and CellChat analysis were used to reveal cell type-specific functional alterations and disruption of cell-cell communication networks. Subset reconstruction and pseudotime analysis were used to reveal the activation status of the cells, and to find the transcription factors with trajectory characterized. Results: Initially, we observed specific DEGs and PD risk genes enrichment in microglia. Next, We obtained the functional phenotype changes in microglia and found that IGF, AGRN and PTN pathways were reduced in MPTP mice. Finally, we analyzed the activation state of microglia and revealed a pro-inflammatory trajectory characterized by transcription factors Nfe2l2 and Runx1. Conclusion: Our work revealed alterations in microglia function, signaling pathways and key genes in the SN of MPTP mice.

Single-cell RNA sequencing reveals special basal cells and fibroblasts in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is the most predominant type of idiopathic interstitial pneumonia and has an increasing incidence, poor prognosis, and unclear pathogenesis. In order to investigate the molecular mechanisms underlying IPF further, we performed single-cell RNA sequencing analysis on three healthy controls and five IPF lung tissue samples. The results revealed a significant shift in epithelial cells (ECs) phenotypes in IPF, which may be attributed to the differentiation of alveolar type 2 cells to basal cells. In addition, several previously unrecognized basal cell subtypes were preliminarily identified, including extracellular matrix basal cells, which were increased in the IPF group. We identified a special population of fibroblasts that highly expressed extracellular matrix-related genes, POSTN, CTHRC1, COL3A1, COL5A2, and COL12A1. We propose that the close interaction between ECs and fibroblasts through ligand-receptor pairs may have a critical function in IPF development. Collectively, these outcomes provide innovative perspectives on the complexity and diversity of basal cells and fibroblasts in IPF and contribute to the understanding of possible mechanisms in pathological lung fibrosis.

Responsiveness to Vedolizumab Therapy in Ulcerative Colitis is Associated With Alterations in Immune Cell-Cell Communications.

BACKGROUND: Ulcerative colitis (UC) and Crohn's disease are 2 types of inflammatory bowel disease (IBD), a group of chronic digestive disorders caused by aberrant immune responses to intestinal microbes. Although changes in the composition of immune cell subsets in the context of IBD have been previously described, the interactions and communication among cells are less well understood. Moreover, the precise mechanisms of action underlying many biologic therapies, including the anti-α4ß7 integrin antagonist vedolizumab, remain incompletely understood. Our study aimed to explore possible additional mechanisms through which vedolizumab acts. METHODS: We performed cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) on peripheral blood and colon immune cells derived from patients with ulcerative colitis treated with the anti-α4ß7 integrin antagonist vedolizumab. We applied a previously published computational approach, NicheNet, to predict immune cell-cell interactions, revealing putative ligand-receptor pairs and key transcriptional changes downstream of these cell-cell communications (CCC). RESULTS: We observed decreased proportions of T helper 17 (TH17) cells in UC patients who responded to vedolizumab and therefore focused the study on identifying cell-cell communications and signals of TH17 cells with other immune cells. For example, we observed that colon TH17 cells from vedolizumab nonresponders were predicted to have a greater degree of interactions with classical monocytes compared with responders, whereas colon TH17 cells from vedolizumab responders exhibited more interactions with myeloid dendritic cells compared with nonresponders. CONCLUSIONS: Overall, our results indicate that efforts to elucidate cell-cell communications among immune and nonimmune cell types may increase the mechanistic understanding of current and investigational therapies for IBD.

Compared to ulcerative patients unresponsive to vedolizumab, immune cell networks of ulcerative colitis patients responsive to vedolizumab have decreased proportion of TH17 and less pro-inflammatory signaling in the gut. Decreased pro-TH17 and interleukin (IL)-1 signaling from classical monocytes and innate immunocytes may mediate this phenotype.

Large-Scale Integration of Single-Cell RNA-Seq Data Reveals Astrocyte Diversity and Transcriptomic Modules across Six Central Nervous System Disorders.

The dysfunction of astrocytes in response to environmental factors contributes to many neurological diseases by impacting neuroinflammation responses, glutamate and ion homeostasis, and cholesterol and sphingolipid metabolism, which calls for comprehensive and high-resolution analysis. However, single-cell transcriptome analyses of astrocytes have been hampered by the sparseness of human brain specimens. Here, we demonstrate how large-scale integration of multi-omics data, including single-cell and spatial transcriptomic and proteomic data, overcomes these limitations. We created a single-cell transcriptomic dataset of human brains by integration, consensus annotation, and analyzing 302 publicly available single-cell RNA-sequencing (scRNA-seq) datasets, highlighting the power to resolve previously unidentifiable astrocyte subpopulations. The resulting dataset includes nearly one million cells that span a wide variety of diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), multiple sclerosis (MS), epilepsy (Epi), and chronic traumatic encephalopathy (CTE). We profiled the astrocytes at three levels, subtype compositions, regulatory modules, and cell-cell communications, and comprehensively depicted the heterogeneity of pathological astrocytes. We constructed seven transcriptomic modules that are involved in the onset and progress of disease development, such as the M2 ECM and M4 stress modules. We validated that the M2 ECM module could furnish potential markers for AD early diagnosis at both the transcriptome and protein levels. In order to accomplish a high-resolution, local identification of astrocyte subtypes, we also carried out a spatial transcriptome analysis of mouse brains using the integrated dataset as a reference. We found that astrocyte subtypes are regionally heterogeneous. We identified dynamic cell-cell interactions in different disorders and found that astrocytes participate in key signaling pathways, such as NRG3-ERBB4, in epilepsy. Our work supports the utility of large-scale integration of single-cell transcriptomic data, which offers new insights into underlying multiple CNS disease mechanisms where astrocytes are involved.

Neuronal guidance genes in health and diseases.

Neurons migrate from their birthplaces to the destinations, and extending axons navigate to their synaptic targets by sensing various extracellular cues in spatiotemporally controlled manners. These evolutionally conserved guidance cues and their receptors regulate multiple aspects of neural development to establish the highly complex nervous system by mediating both short- and long-range cell-cell communications. Neuronal guidance genes (encoding cues, receptors, or downstream signal transducers) are critical not only for development of the nervous system but also for synaptic maintenance, remodeling, and function in the adult brain. One emerging theme is the combinatorial and complementary functions of relatively limited classes of neuronal guidance genes in multiple processes, including neuronal migration, axonal guidance, synaptogenesis, and circuit formation. Importantly, neuronal guidance genes also regulate cell migration and cell-cell communications outside the nervous system. We are just beginning to understand how cells integrate multiple guidance and adhesion signaling inputs to determine overall cellular/subcellular behavior and how aberrant guidance signaling in various cell types contributes to diverse human diseases, ranging from developmental, neuropsychiatric, and neurodegenerative disorders to cancer metastasis. We review classic studies and recent advances in understanding signaling mechanisms of the guidance genes as well as their roles in human diseases. Furthermore, we discuss the remaining challenges and therapeutic potentials of modulating neuronal guidance pathways in neural repair.

Highlighting In Vitro the Role of Brain-like Endothelial Cells on the Maturation and Metabolism of Brain Pericytes by SWATH Proteomics.

Within the neurovascular unit, brain pericytes (BPs) are of major importance for the induction and maintenance of the properties of the blood-brain barrier (BBB) carried by the brain microvessel endothelial cells (ECs). Throughout barriergenesis, ECs take advantage of soluble elements or contact with BPs to maintain BBB integrity and the regulation of their cellular homeostasis. However, very few studies have focused on the role of ECs in the maturation of BPs. The aim of this study is to shed light on the proteome of BPs solocultured (hBP-solo) or cocultured with ECs (hBP-coc) to model the human BBB in a non-contact manner. We first generated protein libraries for each condition and identified 2233 proteins in hBP-solo versus 2492 in hBP-coc and 2035 common proteins. We performed a quantification of the enriched proteins in each condition by sequential window acquisition of all theoretical mass spectra (SWATH) analysis. We found 51 proteins enriched in hBP-solo related to cell proliferation, contractility, adhesion and extracellular matrix element production, a protein pattern related to an immature cell. In contrast, 90 proteins are enriched in hBP-coc associated with a reduction in contractile activities as observed in vivo in 'mature' BPs, and a significant gain in different metabolic functions, particularly related to mitochondrial activities and sterol metabolism. This study highlights that BPs take advantage of ECs during barriergenesis to make a metabolic switch in favor of BBB homeostasis in vitro.

dsCellNet: A new computational tool to infer cell-cell communication networks in the developing and aging brain.

Cell-cell interactions mediated by ligand-receptor complexes are critical to coordinating organismal development and functions. Majority of studies focus on the key time point, the mediator cell types or the critical genes during organismal development or diseases. However, most existing methods are specifically designed for stationary paired samples, there hasn't been a repository to deal with inferring cell-cell communications in developmental series RNA-seq data, which usually contains multiple developmental stages. Here we present a cell-cell interaction networks inference method and its application for developmental series RNA-seq data (termed dsCellNet) from the developing and aging brain. dsCellNet is implemented as an open-access R package on GitHub. It identifies interactions according to protein localizations and reinforces them via dynamic time warping within each time point and between adjacent time points, respectively. Then, fuzzy clustering of those interactions helps us refine key time points and connections. Compared to other published methods, our methods display high accuracy and high tolerance based on both simulated data and real data. Moreover, our methods can help identify the most active cell type and genes, which may provide a powerful tool to uncover the mechanisms underlying the organismal development and disease.

Dissecting the single-cell transcriptomeunderlying chronic liver injury.

Chronic liver disease (CLD) is currently a major health problem worldwide, which is accompanied by chronic liver injury and lack of clinically effective treatment; however, systematic characterization of chronic liver injury procedures at single-cell resolution is lacking. In the present study, we established chronic liver injury mouse models and conducted single-cell RNA sequencing (scRNA-seq), including choline-deficient, ethionine-supplemented (CDE) and 3,5-diethoxycarbonyl 1,4-dihydrocollidinen (DDC) mouse models. We captured in total 16,389 high-quality cells and identified 12 main cell types in scRNA-seq data. Macrophages and endothelial cells are the largest cell populations in our dataset. Transcriptional trajectory analysis revealed different expression patterns of cells between CDE and DDC models and identified potential liver injury markers, such as Ets1, Gda, Itgam, and Sparc. Differential analysis identified 25 and 152 differentially expressed genes in CDE and DDC macrophages, respectively. In addition, 413 genes were detected to exclusively express in specific pseudotime states of macrophages. These genes were found to participate in immune-related biological processes. Further cell-cell communication analysis found extensive receding of cell-cell interactions between different cell types in the liver injury process, especially in the DDC model. Our study characterized the single-cell transcriptional landscape in the process of chronic liver injury, promoting the understanding of the underlying molecular mechanisms and providing candidate clinical strategy for effective intervention of chronic liver diseases.

Statistical and machine learning methods for spatially resolved transcriptomics with histology.

Recent developments in spatially resolved transcriptomics (SRT) technologies have enabled scientists to get an integrated understanding of cells in their morphological context. Applications of these technologies in diverse tissues and diseases have transformed our views of transcriptional complexity. Most published studies utilized tools developed for single-cell RNA sequencing (scRNA-seq) for data analysis. However, SRT data exhibit different properties from scRNA-seq. To take full advantage of the added dimension on spatial location information in such data, new methods that are tailored for SRT are needed. Additionally, SRT data often have companion high-resolution histology information available. Incorporating histological features in gene expression analysis is an underexplored area. In this review, we will focus on the statistical and machine learning aspects for SRT data analysis and discuss how spatial location and histology information can be integrated with gene expression to advance our understanding of the transcriptional complexity. We also point out open problems and future research directions in this field.

LR Hunting: A Random Forest Based Cell-Cell Interaction Discovery Method for Single-Cell Gene Expression Data.

Cell-cell interactions (CCIs) and cell-cell communication (CCC) are critical for maintaining complex biological systems. The availability of single-cell RNA sequencing (scRNA-seq) data opens new avenues for deciphering CCIs and CCCs through identifying ligand-receptor (LR) gene interactions between cells. However, most methods were developed to examine the LR interactions of individual pairs of genes. Here, we propose a novel approach named LR hunting which first uses random forests (RFs)-based data imputation technique to link the data between different cell types. To guarantee the robustness of the data imputation procedure, we repeat the computation procedures multiple times to generate aggregated imputed minimal depth index (IMDI). Next, we identify significant LR interactions among all combinations of LR pairs simultaneously using unsupervised RFs. We demonstrated LR hunting can recover biological meaningful CCIs using a mouse cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) dataset and a triple-negative breast cancer scRNA-seq dataset.

Topographical control of cell-cell interaction in C6 glioma by nanodot arrays.

Nanotopography modulates the physiological behavior of cells and cell-cell interactions, but the manner of communication remains unclear. Cell networking (syncytium) of astroglia provides the optimal microenvironment for communication of the nervous system. C6 glioma cells were seeded on nanodot arrays with dot diameters ranging from 10 to 200 nm. Cell viability, morphology, cytoskeleton, and adhesion showed optimal cell growth on 50-nm nanodots if sufficient incubation was allowed. In particular, the astrocytic syncytium level maximized at 50 nm. The gap junction protein Cx43 showed size-dependent and time-dependent transport from the nucleus to the cell membrane. The transport efficiency was greatly enhanced by incubation on 50-nm nanodots. In summary, nanotopography is capable of modulating cell behavior and influencing the cell-cell interactions of astrocytes. By fine-tuning the nanoenvironment, it may be possible to regulate cell-cell communications and optimize the biocompatibility of neural implants.

Bone cell senescence: mechanisms and perspectives.

Age-related bone loss is in large part the consequence of senescence mechanisms that impact bone cell number and function. In recent years, progress has been made in the understanding of the molecular mechanisms underlying bone cell senescence that contributes to the alteration of skeletal integrity during aging. These mechanisms can be classified as intrinsic senescence processes, alterations in endogenous anabolic factors, and changes in local support. Intrinsic senescence mechanisms cause cellular dysfunctions that are not tissue specific and include telomere shortening, accumulation of oxidative damage, impaired DNA repair, and altered epigenetic mechanisms regulating gene transcription. Aging mechanisms that are more relevant to the bone microenvironment include alterations in the expression and signaling of local growth factors and altered intercellular communications. This review provides an integrated overview of the current concepts and interacting mechanisms underlying bone cell senescence during aging and how they could be targeted to reduce the negative impact of senescence in the aging skeleton.

Membrane tubulovesicular extensions (cytonemes): secretory and adhesive cellular organelles.

In this review, we summarized data on the formation and structure of the long and highly adhesive membrane tubulovesicular extensions (TVEs, membrane tethers or cytonemes) observed in human neutrophils and other mammalian cells, protozoan parasites and bacteria. We determined that TVEs are membrane protrusions characterized by a uniform diameter (130-250 nm for eukaryotic cells and 60-90 nm for bacteria) along the entire length, an outstanding length and high rate of development and a high degree of flexibility and capacity for shedding from the cells. This review represents TVEs as protrusions of the cellular secretory process, serving as intercellular adhesive organelles in eukaryotic cells and bacteria. An analysis of the physical and chemical approaches to induce TVEs formation revealed that disrupting the actin cytoskeleton and inhibiting glucose metabolism or vacuolar-type ATPase induces TVE formation in eukaryotic cells. Nitric oxide is represented as a physiological regulator of TVE formation.