Sphingolipids control dermal fibroblast heterogeneity.

Human cells produce thousands of lipids that change during cell differentiation and can vary across individual cells of the same type. However, we are only starting to characterize the function of these cell-to-cell differences in lipid composition. Here, we measured the lipidomes and transcriptomes of individual human dermal fibroblasts by coupling high-resolution mass spectrometry imaging with single-cell transcriptomics. We found that the cell-to-cell variations of specific lipid metabolic pathways contribute to the establishment of cell states involved in the organization of skin architecture. Sphingolipid composition is shown to define fibroblast subpopulations, with sphingolipid metabolic rewiring driving cell-state transitions. Therefore, cell-to-cell lipid heterogeneity affects the determination of cell states, adding a new regulatory component to the self-organization of multicellular systems.

Dysregulation of interaction between LOXhigh fibroblast and smooth muscle cells contributes to the pathogenesis of aortic dissection.

Rationale: While cell-cell interaction plays a critical role in physiology and disease, a comprehensive understanding of its dynamics in vascular homeostasis and diseases is yet absent. Methods: Here, by use of single-cell RNA-sequencing and multi-color staining, we delineate the cellular composition and spatial characterization of human aorta with or without aortic dissection (AD). Results: Scrutinization of cell subtype alterations revealed significantly changed fibroblast (FB)-smooth muscle cell (SMC) interactions in AD. Of these cellular interactions, LOXhigh fibroblast (fibroblast subtype 2, FB2) in diseased state exerted the most pronounced effects on pathological deterioration of SMCs in AD. In addition, pharmacologically targeting the BMP (bone morphogenetic protein) signaling pathway effectively suppressed FB2 state transition and reduced AD incidence in mice. Finally, COL5A1 (collagen type V alpha 1 chain), one of the secreted proteins released from FB2, was significantly higher in the plasma of AD patients than in control patients, suggesting its potential use as a biomarker for AD diagnosis. Conclusions: Our work not only identified a pivotal role of a specific FB subtype in AD progression, but also shed light on cell interaction dynamics in vascular diseases.

In vitro cytotoxicity assay of Fucoidan extracted from Turbinaria conoides against cancer cell lines MCF7, A549, and normal cell line L929

Abstract The main aim of the study is to quantify the cytotoxic property of the Fucoidan extracted from the Turbinaria conoides using the MTT assay with the standard fucose. Fucoidan was extracted using the soaked water method and it was determined using the HPLC procedure the obtained Test sample Fucoidan extracted from the Turbinaria conoides and standard fucose was subjected to the cytotoxicity assay against the MCF7 Human breast cancer cell line, A549 lung cancer cell line, and L929 normal mouse fibroblast cell line. From the results it was found that the Test sample showed good IC50 value for MCF7 cell line then A549 with an increasing concentration 24 hours incubation at 37°C The IC50 for MCF7 was 115.21 µg/ml and A549 396.46µg/ml and the Fucoidan extract was checked for its cytotoxicity against the normal mouse fibroblast cell line L929, Fucoidan was found non-lethal to the L929 mouse fibroblast normal cell line. Standard fucose also gave a significant result towards MCF7 and against the L929. This indicates that the Fucoidan extracted from Tubinaria conoides shows better anticancer potential in it. Hence its application can be further extended in the pharmacological fields.

Self-Organizing Maps for Cellular In Silico Staining and Cell Substate Classification.

Cellular composition and structural organization of cells in the tissue determine effective antitumor response and can predict patient outcome and therapy response. Here we present Seg-SOM, a method for dimensionality reduction of cell morphology in H&E-stained tissue images. Seg-SOM resolves cellular tissue heterogeneity and reveals complex tissue architecture. We leverage a self-organizing map (SOM) artificial neural network to group cells based on morphological features like shape and size. Seg-SOM allows for cell segmentation, systematic classification, and in silico cell labeling. We apply the Seg-SOM to a dataset of breast cancer progression images and find that clustering of SOM classes reveals groups of cells corresponding to fibroblasts, epithelial cells, and lymphocytes. We show that labeling the Lymphocyte SOM class on the breast tissue images accurately estimates lymphocytic infiltration. We further demonstrate how to use Seq-SOM in combination with non-negative matrix factorization to statistically describe the interaction of cell subtypes and use the interaction information as highly interpretable features for a histological classifier. Our work provides a framework for use of SOM in human pathology to resolve cellular composition of complex human tissues. We provide a python implementation and an easy-to-use docker deployment, enabling researchers to effortlessly featurize digitalized H&E-stained tissue.

Fibroblast pathology in inflammatory diseases.

Fibroblasts are important cells for the support of homeostatic tissue function. In inflammatory diseases such as rheumatoid arthritis and inflammatory bowel disease, fibroblasts take on different roles (a) as inflammatory cells themselves and (b) in recruiting leukocytes, driving angiogenesis, and enabling chronic inflammation in tissues. Recent advances in single-cell profiling techniques have transformed the ability to examine fibroblast states and populations in inflamed tissues, providing evidence of previously underappreciated heterogeneity and disease-associated fibroblast populations. These studies challenge the preconceived notion that fibroblasts are homogeneous and provide new insights into the role of fibroblasts in inflammatory pathology. In addition, new molecular insights into the mechanisms of fibroblast activation reveal powerful cell-intrinsic amplification loops that synergize with primary fibroblast stimuli to result in striking responses. In this Review, we focus on recent developments in our understanding of fibroblast heterogeneity and fibroblast pathology across tissues and diseases in rheumatoid arthritis and inflammatory bowel diseases. We highlight new approaches to, and applications of, single-cell profiling techniques and what they teach us about fibroblast biology. Finally, we address how these insights could lead to the development of novel therapeutic approaches to targeting fibroblasts in disease.

Cardiac Fibrosis and Fibroblasts.

Cardiac fibrosis is the excess deposition of extracellular matrix (ECM), such as collagen. Myofibroblasts are major players in the production of collagen, and are differentiated primarily from resident fibroblasts. Collagen can compensate for the dead cells produced by injury. The appropriate production of collagen is beneficial for preserving the structural integrity of the heart, and protects the heart from cardiac rupture. However, excessive deposition of collagen causes cardiac dysfunction. Recent studies have demonstrated that myofibroblasts can change their phenotypes. In addition, myofibroblasts are found to have functions other than ECM production. Myofibroblasts have macrophage-like functions, in which they engulf dead cells and secrete anti-inflammatory cytokines. Research into fibroblasts has been delayed due to the lack of selective markers for the identification of fibroblasts. In recent years, it has become possible to genetically label fibroblasts and perform sequencing at single-cell levels. Based on new technologies, the origins of fibroblasts and myofibroblasts, time-dependent changes in fibroblast states after injury, and fibroblast heterogeneity have been demonstrated. In this paper, recent advances in fibroblast and myofibroblast research are reviewed.

New Insights From Single-Cell Sequencing Data: Synovial Fibroblasts and Synovial Macrophages in Rheumatoid Arthritis.

Single-cell RNA sequencing (scRNA-seq) technology can analyze the transcriptome expression level of cells with high-throughput from the single cell level, fully show the heterogeneity of cells, and provide a new way for the study of multicellular biological heterogeneity. Synovitis is the pathological basis of rheumatoid arthritis (RA). Synovial fibroblasts (SFs) and synovial macrophages are the core target cells of RA, which results in the destruction of articular cartilage, as well as bone. Recent scRNA-seq technology has made breakthroughs in the differentiation and development of two types of synovial cells, identification of subsets, functional analysis, and new therapeutic targets, which will bring remarkable changes in RA treatment.

Cross-tissue organization of the fibroblast lineage.

Fibroblasts are non-haematopoietic structural cells that define the architecture of organs, support the homeostasis of tissue-resident cells and have key roles in fibrosis, cancer, autoimmunity and wound healing1. Recent studies have described fibroblast heterogeneity within individual tissues1. However, the field lacks a characterization of fibroblasts at single-cell resolution across tissues in healthy and diseased organs. Here we constructed fibroblast atlases by integrating single-cell transcriptomic data from about 230,000 fibroblasts across 17 tissues, 50 datasets, 11 disease states and 2 species. Mouse fibroblast atlases and a DptIRESCreERT2 knock-in mouse identified two universal fibroblast transcriptional subtypes across tissues. Our analysis suggests that these cells can serve as a reservoir that can yield specialized fibroblasts across a broad range of steady-state tissues and activated fibroblasts in disease. Comparison to an atlas of human fibroblasts from perturbed states showed that fibroblast transcriptional states are conserved between mice and humans, including universal fibroblasts and activated phenotypes associated with pathogenicity in human cancer, fibrosis, arthritis and inflammation. In summary, a cross-species and pan-tissue approach to transcriptomics at single-cell resolution has identified key organizing principles of the fibroblast lineage in health and disease.

Human Dermal Fibroblast Subpopulations Are Conserved across Single-Cell RNA Sequencing Studies.

On the basis of their differential location within the dermis and of discrete changes in gene and protein expression, two major fibroblast subtypes (papillary and reticular) have traditionally been distinguished. In the last 3 years, a number of research groups have begun to address transcriptomic heterogeneity of human skin cells at the single-cell level by determining mRNA levels of expressed genes through single-cell RNA sequencing technologies. However, the outcome of single-cell RNA sequencing studies is thus far confusing. Very little overlap was found in fibroblast subpopulations, which also varied in number and composition in each dataset. After a careful reappraisal of the transcriptomic data of 13,823 human adult dermal fibroblasts that have been sequenced to date, we show that fibroblasts may robustly be assigned to three major types (axes A‒C), which in turn are composed of 10 major subtypes (clusters), which we denominated A1‒A4, B1 and B2, and C1‒C4. These computationally determined axes and clusters represent the major fibroblast types and subtypes in adult healthy human skin across different datasets, accounting for 92.5% of the sequenced fibroblasts. They thus may provide the basis to improve our understanding of dermal homeostasis and cellular function at the transcriptomic level.

Progress and challenge for computational quantification of tissue immune cells.

Tissue immune cells have long been recognized as important regulators for the maintenance of balance in the body system. Quantification of the abundance of different immune cells will provide enhanced understanding of the correlation between immune cells and normal or abnormal situations. Currently, computational methods to predict tissue immune cell compositions from bulk transcriptomes have been largely developed. Therefore, summarizing the advantages and disadvantages is appropriate. In addition, an examination of the challenges and possible solutions for these computational models will assist the development of this field. The common hypothesis of these models is that the expression of signature genes for immune cell types might represent the proportion of immune cells that contribute to the tissue transcriptome. In general, we grouped all reported tools into three groups, including reference-free, reference-based scoring and reference-based deconvolution methods. In this review, a summary of all the currently reported computational immune cell quantification tools and their applications, limitations, and perspectives are presented. Furthermore, some critical problems are found that have limited the performance and application of these models, including inadequate immune cell type, the collinearity problem, the impact of the tissue environment on the immune cell expression level, and the deficiency of standard datasets for model validation. To address these issues, tissue specific training datasets that include all known immune cells, a hierarchical computational framework, and benchmark datasets including both tissue expression profiles and the abundances of all the immune cells are proposed to further promote the development of this field.

Distinct populations of crypt-associated fibroblasts act as signaling hubs to control colon homeostasis.

Despite recent progress in recognizing the importance of mesenchymal cells for the homeostasis of the intestinal system, the current picture of how these cells communicate with the associated epithelial layer remains unclear. To describe the relevant cell populations in an unbiased manner, we carried out a single-cell transcriptome analysis of the adult murine colon, producing a high-quality atlas of matched colonic epithelium and mesenchyme. We identify two crypt-associated colonic fibroblast populations that are demarcated by different strengths of platelet-derived growth factor receptor A (Pdgfra) expression. Crypt-bottom fibroblasts (CBFs), close to the intestinal stem cells, express low levels of Pdgfra and secrete canonical Wnt ligands, Wnt potentiators, and bone morphogenetic protein (Bmp) inhibitors. Crypt-top fibroblasts (CTFs) exhibit high Pdgfra levels and secrete noncanonical Wnts and Bmp ligands. While the Pdgfralow cells maintain intestinal stem cell proliferation, the Pdgfrahigh cells induce differentiation of the epithelial cells. Our findings enhance our understanding of the crosstalk between various colonic epithelial cells and their associated mesenchymal signaling hubs along the crypt axis-placing differential Pdgfra expression levels in the spotlight of intestinal fibroblast identity.

Cells of the adult human heart.

Cardiovascular disease is the leading cause of death worldwide. Advanced insights into disease mechanisms and therapeutic strategies require a deeper understanding of the molecular processes involved in the healthy heart. Knowledge of the full repertoire of cardiac cells and their gene expression profiles is a fundamental first step in this endeavour. Here, using state-of-the-art analyses of large-scale single-cell and single-nucleus transcriptomes, we characterize six anatomical adult heart regions. Our results highlight the cellular heterogeneity of cardiomyocytes, pericytes and fibroblasts, and reveal distinct atrial and ventricular subsets of cells with diverse developmental origins and specialized properties. We define the complexity of the cardiac vasculature and its changes along the arterio-venous axis. In the immune compartment, we identify cardiac-resident macrophages with inflammatory and protective transcriptional signatures. Furthermore, analyses of cell-to-cell interactions highlight different networks of macrophages, fibroblasts and cardiomyocytes between atria and ventricles that are distinct from those of skeletal muscle. Our human cardiac cell atlas improves our understanding of the human heart and provides a valuable reference for future studies.

Cardiac fibroblast activation during myocardial infarction wound healing: Fibroblast polarization after MI.

Cardiac wound healing after myocardial infarction (MI) evolves from pro-inflammatory to anti-inflammatory to reparative responses, and the cardiac fibroblast is a central player during the entire transition. The fibroblast mirrors changes seen in the left ventricle infarct by undergoing a continuum of polarization phenotypes that follow pro-inflammatory, anti-inflammatory, and pro-scar producing profiles. The development of each phenotype transition is contingent upon the MI environment into which the fibroblast enters. In this mini-review, we summarize our current knowledge regarding cardiac fibroblast activation during MI and highlight key areas where gaps remain.

Transcriptional and Cellular Diversity of the Human Heart.

BACKGROUND: The human heart requires a complex ensemble of specialized cell types to perform its essential function. A greater knowledge of the intricate cellular milieu of the heart is critical to increase our understanding of cardiac homeostasis and pathology. As recent advances in low-input RNA sequencing have allowed definitions of cellular transcriptomes at single-cell resolution at scale, we have applied these approaches to assess the cellular and transcriptional diversity of the nonfailing human heart. METHODS: Microfluidic encapsulation and barcoding was used to perform single nuclear RNA sequencing with samples from 7 human donors, selected for their absence of overt cardiac disease. Individual nuclear transcriptomes were then clustered based on transcriptional profiles of highly variable genes. These clusters were used as the basis for between-chamber and between-sex differential gene expression analyses and intersection with genetic and pharmacologic data. RESULTS: We sequenced the transcriptomes of 287 269 single cardiac nuclei, revealing 9 major cell types and 20 subclusters of cell types within the human heart. Cellular subclasses include 2 distinct groups of resident macrophages, 4 endothelial subtypes, and 2 fibroblast subsets. Comparisons of cellular transcriptomes by cardiac chamber or sex reveal diversity not only in cardiomyocyte transcriptional programs but also in subtypes involved in extracellular matrix remodeling and vascularization. Using genetic association data, we identified strong enrichment for the role of cell subtypes in cardiac traits and diseases. Intersection of our data set with genes on cardiac clinical testing panels and the druggable genome reveals striking patterns of cellular specificity. CONCLUSIONS: Using large-scale single nuclei RNA sequencing, we defined the transcriptional and cellular diversity in the normal human heart. Our identification of discrete cell subtypes and differentially expressed genes within the heart will ultimately facilitate the development of new therapeutics for cardiovascular diseases.

Cardiac Fibroblast Diversity.

Cardiac fibrosis is a pathological condition that occurs after injury and during aging. Currently, there are limited means to effectively reduce or reverse fibrosis. Key to identifying methods for curbing excess deposition of extracellular matrix is a better understanding of the cardiac fibroblast, the cell responsible for collagen production. In recent years, the diversity and functions of these enigmatic cells have been gradually revealed. In this review, I outline current approaches for identifying and classifying cardiac fibroblasts. An emphasis is placed on new insights into the heterogeneity of these cells as determined by lineage tracing and single-cell sequencing in development, adult, and disease states. These recent advances in our understanding of the fibroblast provide a platform for future development of novel therapeutics to combat cardiac fibrosis.

CD248 and integrin alpha-8 are candidate markers for differentiating lung fibroblast subtypes.

BACKGROUND: Lung fibrosis is a serious life-threatening condition whose manifestation varies according to the localization and characteristics of fibroblasts, which are considered heterogeneous. Therefore, to better understand the pathology and improve diagnosis and treatment of this disease, it is necessary to elucidate the nature of this heterogeneity and identify markers for the accurate classification of human lung fibroblast subtypes. METHODS: We characterized distinct mouse lung fibroblast subpopulations isolated by fluorescence-activated cell sorting (FACS) and performed microarray analysis to identify molecular markers that could be useful for human lung fibroblast classification. Based on the expression of these markers, we evaluated the fibroblast-like cell subtype localization in normal human lung samples and lung samples from patients with idiopathic pulmonary fibrosis (IPF). RESULTS: Mouse lung fibroblasts were classified into Sca-1high fibroblasts and Sca-1low fibroblasts by in vitro biological analyses. Through microarray analysis, we demonstrated CD248 and integrin alpha-8 (ITGA8) as cell surface markers for Sca-1high fibroblasts and Sca-1low fibroblasts, respectively. In mouse lungs, Sca-1high fibroblasts and Sca-1low fibroblasts were localized in the collagen fiber-rich connective tissue and elastic fiber-rich connective tissue, respectively. In normal human lungs and IPF lungs, two corresponding major fibroblast-like cell subtypes were identified: CD248highITGA8low fibroblast-like cells and CD248lowITGA8high fibroblast-like cells, localized in the collagen fiber-rich connective tissue and in the elastic fiber-rich connective tissue, respectively. CONCLUSION: CD248highITGA8low fibroblast-like cells and CD248lowITGA8high fibroblast-like cells were localized in an almost exclusive manner in human lung specimens. This human lung fibroblast classification using two cell surface markers may be helpful for further detailed investigations of the functions of lung fibroblast subtypes, which can provide new insights into lung development and the pathological processes underlying fibrotic lung diseases.

Protective Effects of Sesamin against UVB-Induced Skin Inflammation and Photodamage In Vitro and In Vivo.

Ultraviolet (UV) exposure has been demonstrated as the most critical factor causing extrinsic skin aging and inflammation. This study explored the protective effects and mechanisms of sesamin against skin photodamage. Sesamin reduced intracellular reactive oxygen species production after UVB irradiation in human dermal fibroblasts. The sesamin treatment attenuated mitogen-activated protein (MAP) kinase phosphorylation and matrix metalloproteinase (MMPs) overexpression induced by UVB exposure, and it significantly enhanced the tissue inhibitor of metalloproteinase-1 protein expression. Sesamin also elevated the total collagen content in human fibroblasts by inhibiting UVB-induced mothers against decapentaplegic homolog 7 (Smad7) protein expression. Sesamin reduced UVB-induced inducible nitric oxide synthase (i-NOS) and cyclooxygenase-2 (COX-2) overexpression and inhibited nuclear factor-kappa B (NF-κB) translocation. Moreover, sesamin may regulate the c-Jun N-terminal kinases (JNK) and p38 MAP kinase pathways, which inhibit COX-2 expression. Sesamin could reduce UVB-induced inflammation, epidermal hyperplasia, collagen degradation, and wrinkle formation in hairless mice. It also reduced MMP-1, interleukin (IL-1), i-NOS, and NF-κB in the mouse skin. These results demonstrate that sesamin had antiphotodamage and anti-inflammatory activities. Sesamin has potential for use as a skin protection agent in antiphotodamage and skin care products.

Distinct fibroblast subsets drive inflammation and damage in arthritis.

The identification of lymphocyte subsets with non-overlapping effector functions has been pivotal to the development of targeted therapies in immune-mediated inflammatory diseases (IMIDs)1,2. However, it remains unclear whether fibroblast subclasses with non-overlapping functions also exist and are responsible for the wide variety of tissue-driven processes observed in IMIDs, such as inflammation and damage3-5. Here we identify and describe the biology of distinct subsets of fibroblasts responsible for mediating either inflammation or tissue damage in arthritis. We show that deletion of fibroblast activation protein-α (FAPα)+ fibroblasts suppressed both inflammation and bone erosions in mouse models of resolving and persistent arthritis. Single-cell transcriptional analysis identified two distinct fibroblast subsets within the FAPα+ population: FAPα+THY1+ immune effector fibroblasts located in the synovial sub-lining, and FAPα+THY1- destructive fibroblasts restricted to the synovial lining layer. When adoptively transferred into the joint, FAPα+THY1- fibroblasts selectively mediate bone and cartilage damage with little effect on inflammation, whereas transfer of FAPα+ THY1+ fibroblasts resulted in a more severe and persistent inflammatory arthritis, with minimal effect on bone and cartilage. Our findings describing anatomically discrete, functionally distinct fibroblast subsets with non-overlapping functions have important implications for cell-based therapies aimed at modulating inflammation and tissue damage.

Diversity of dermal fibroblasts as major determinant of variability in cell reprogramming.

Induced pluripotent stem cells (iPSCs) are adult somatic cells genetically reprogrammed to an embryonic stem cell-like state. Notwithstanding their autologous origin and their potential to differentiate towards cells of all three germ layers, iPSC reprogramming is still affected by low efficiency. As dermal fibroblast is the most used human cell for reprogramming, we hypothesize that the variability in reprogramming is, at least partially, because of the skin fibroblasts used. Human dermal fibroblasts harvested from five different anatomical sites (neck, breast, arm, abdomen and thigh) were cultured and their morphology, proliferation, apoptotic rate, ability to migrate, expression of mesenchymal or epithelial markers, differentiation potential and production of growth factors were evaluated in vitro. Additionally, gene expression analysis was performed by real-time PCR including genes typically expressed by mesenchymal cells. Finally, fibroblasts isolated from different anatomic sites were reprogrammed to iPSCs by integration-free method. Intriguingly, while the morphology of fibroblasts derived from different anatomic sites differed only slightly, other features, known to affect cell reprogramming, varied greatly and in accordance with anatomic site of origin. Accordingly, difference also emerged in fibroblasts readiness to respond to reprogramming and ability to form colonies. Therefore, as fibroblasts derived from different anatomic sites preserve positional memory, it is of great importance to accurately evaluate and select dermal fibroblast population prior to induce reprogramming.

Gradient Photothermal Field for Precisely Directing Cell Sheet Detachment.

Due to the remaining intact intercellular interactions, cell sheets play increasing roles in biomedical fields. Recently, spatiotemporal control of cell sheets has become an urgent requirement in the context of precise surgery. Here, the development of a gradient photothermal biointerface for precisely directing cell sheet detachment through quantitatively regulating the dissociation rate of collagen is reported. This novel and facile method shows great potential for application in precise regenerative medicine.