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Integrating Proteome-Wide Association Studies and Single-Cell Transcriptomics Identifies GSTT2B as a Causal Mediator and Prioritizes COL4A1 in Diabetic Retinopathy.
Diabetic retinopathy (DR) is a leading cause of vision loss, yet its systemic proteomic mediators remain largely elusive. This study aimed to identify causal plasma proteins, map their cell-type-specific localization in the retina, and experimentally validate their expression under disease-relevant stress. We conducted a proteome-wide association study (PWAS) integrating UK Biobank plasma pQTL data (N = 53,022) with DR GWAS summary statistics. Causal relationships were inferred utilizing summary-data-based Mendelian randomization (SMR) and Bayesian colocalization. Prioritized candidates were mapped to the Human and Mouse Retina Cell Atlases via single-nucleus RNA sequencing (snRNA-seq). Finally, to substantiate the computational findings, in vitro validation of COL4A1 was performed in ARPE-19 cells cultured under hyperglycemic conditions utilizing quantitative real-time PCR (qPCR) and transcriptomic dataset re-analysis. The PWAS identified 26 proteins significantly associated with DR. Subsequent causal inference prioritized 12 high-confidence candidates, including GSTT2B, COL4A1, PAM, and GALNT3. Notably, GSTT2B emerged as a Tier-1 protective causal protein (Z = -3.609; PSMR = 1.22 × 10-4). snRNA-seq mapping revealed that GSTT2B is robustly expressed in Müller glia and the retinal pigment epithelium (RPE), whereas COL4A1 is prominently enriched in vascular compartments. These specific expression signatures exhibited partial conservation across species with notable cell-type specific variations. Crucially, in vitro validation confirmed that COL4A1 mRNA expression is significantly upregulated under high-glucose stress. Furthermore, druggability analysis highlighted actionable targets, identifying GSTT2B as a highly probable causal mediator and COL4A1 as a prioritized candidate for structural intervention. This study provides robust genetic, single-cell, and experimental evidence implicating specific plasma proteins in DR pathogenesis. The identification of GSTT2B-mediated protective pathways and the hyperglycemia-induced upregulation of COL4A1 offer a high-resolution molecular atlas to guide drug repositioning and precision therapeutic strategies.
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Utilising Single Cell Analysis and Spatial Transcriptomics to Elucidate Molecular Mechanisms of Wound Healing: A Literature Review.
The use of single-cell RNA sequencing and spatial transcriptomics has recently challenged and refined concepts in the field of wound healing by enabling detailed characterisation of cellular heterogeneity while providing spatial context. Previously used separately, these methods are now increasingly applied together due to the advent of newer platforms, enabling delineation of discrete subpopulations of cutaneous cells, including epidermal basal stem cells, fibroblasts, neutrophils, macrophages, and T cells. Detailed transcriptional profiling of these subpopulations has revealed upregulation of either pro-regenerative or pro-fibrotic pathways. For example, fibroblast heterogeneity significantly influences wound healing outcomes, with Lef1+ and Trps1+ fibroblasts promoting regeneration through Wnt and Hedgehog pathway activation, whereas fibroblasts isolated from scars show upregulation of genes that promote excessive fibroblast activation, such as the YAP mechanotransduction pathway. Despite these insights, clinical translation can be challenging due to platform variability, computational demands, and biological heterogeneity inherent to models of wound healing. Ultimately, integration of multiomic data and public databases such as the Human Skin Atlas is necessary to increase biomarker reliability and mechanistic clarity. As these technologies become more accessible and standardised, they hold great potential for personalised wound care management by enabling molecular risk stratification and targeted therapeutic interventions. This literature review aimed to elucidate the latest advancements in gene expression analysis, with particular focus on the use of scRNA-seq and ST in the context of wound healing. The goal is to summarise previous efforts that contribute to the understanding of the cellular mechanisms of wound healing and reflect on how these insights could influence future therapeutic development.
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Single-cell transcriptomics of chicken ovarian cancer identifying immune subsets with prognostic implications.
Ovarian cancer (OC) is a lethal gynecological malignancy with a low 5-year survival rate. The lack of preclinical models accurately capturing OC's early pathogenesis contributes to this poor prognosis. The domestic laying hen uniquely develops spontaneous OC, but its single-cell-level insights for pathogenesis have been lacking. Here, we present the first single-cell transcriptomic atlas of ovarian tissues from 110-week-old laying hens with or without OC. We annotated 12 core cellular lineages and characterized tumor-associated changes, including increased CD4+ and CD8+ T cells and reduced macrophages in OC samples. T cells sub-clustering revealed conserved cell subtype-specific pH homeostasis regulation profiles across species. Notably, gene signatures from the two dominant Cyto_CD8+ subsets exhibited opposing prognostic roles when validated against human OC datasets (GSE18520, GSE26712, GSE49997). This study confirms the laying hen as a valuable OC model by demonstrating cross-species conservation in cellular heterogeneity and oncogenic pathways, advancing it from a pathologically analogous system to a molecularly traceable tool.
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Single-cell transcriptomic profiling of the chicken spleen reveals cell-type-specific immune responses to Salmonella infection.
Although the spleen is a key immune organ, the dynamic remodeling of its cellular landscape during development and the heterogeneous immune responses of these cells to avian Salmonella infection remain to be elucidated. In this study, we reanalyzed publicly available datasets comprising 116,791 single-cell transcriptomes from the chicken spleen. We annotated a total of 40 distinct cell types, systematically delineating the cellular composition and dynamic changes from embryonic to adult stages. Moreover, single-cell comparisons before and after Salmonella infection revealed markedly strengthened intercellular crosstalk within the lymphoid lineage and between lymphoid and myeloid lineages. Transcriptional analysis demonstrated that naive T cells, NK2 cells, and B cells underwent the most extensive transcriptional remodeling, implying their pivotal roles in the antibacterial immune response. Of note, the responses of different immune cell subsets displayed both subset-specific patterns and shared features. Furthermore, notable differences were detected in cellular interaction networks, as well as in the gene expression profiles of NK2 cells and activated T cells between different chicken breeds, which may serve as potential molecular mechanisms underlying the divergent disease resistance phenotypes among chicken breeds. Collectively, these findings provide a comprehensive temporal atlas of chicken splenic development and immunity, offering valuable insights into the molecular basis of disease resistance and laying a theoretical foundation for poultry breeding strategies.
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Single-cell transcriptomics reveals the regulation of bco1 and bco2 genes in the carotenoid metabolism of koi carp.
The koi carp is a highly valued ornamental fish with a variety of skin color patterns that play an important role in survival and reproduction, but the molecular basis of these conspicuous colors remains obscure. Here, we generated a single-cell atlas of the red and white skin of Kohaku koi. We found that the skin tissue could be divided into 10 cell types, of which epithelial cells, endothelial cells, fibroblasts and xanthophores were present in higher proportions. Interestingly, pseudotime analysis revealed that pigment cells developed from white to red skin, and genes related to the uptake and degradation of carotenoids were significantly upregulated in red skin. Functional studies using TEM, HPLC, ISH, immunofluorescence, RNAi, cell culture, gene editing, RNA-seq and gene family analysis showed that k-bco2 could access more substrates than k-bco1, and that the two genes do not interact directly but may act synergistically via the calcium-ion signaling pathway. These insights enhance our understanding of pigment cell development and differentiation in fish, and the scRNA-seq transcriptome profiles offer valuable implications for future molecular breeding strategies.
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Single-Cell Transcriptomic Profiling of Ectopic ACTH-Secreting Pheochromocytoma Reveals the Chromaffin Cell Origin of Ectopic Hormone Production.
Ectopic ACTH-secreting pheochromocytomas are rare and life-threatening endocrine tumors responsible for hypertension, paroxysmal symptoms, and Cushing's syndrome. The cellular origin of ACTH and the tumor's molecular characteristics remain poorly understood. Single-cell RNA sequencing was performed on tumor specimens and adjacent adrenal tissues from three patients with ectopic ACTH-secreting pheochromocytomas. Integrated bioinformatic analyses, including differential expression, functional enrichment, cell-cell communication, and pseudotemporal trajectory inference, were conducted. Key findings were supported by immunofluorescence and immunohistochemical staining. Our study integrated single-cell transcriptomic profiling with detailed clinical characterization of three cases of ectopic ACTH-secreting pheochromocytomas. All patients presented classic Cushing's features and variable catecholamine secretory patterns. Hormone levels improved after surgical resection. Single-cell analysis revealed a complex tumor microenvironment comprising 11 distinct cell populations. Chromaffin cells expressing the ACTH precursor gene POMC were identified within the tumor cell population, suggesting that these cells may represent the source of ectopic ACTH production. This finding was further supported by immunofluorescence and immunohistochemical staining demonstrating ACTH expression in CHGA-positive chromaffin tumor cells and absence of staining for the adrenocortical marker α-inhibin. These tumor cells exhibited metabolic reprogramming characterized by upregulation of oxidative phosphorylation pathways and downregulation of adaptive immune responses. Cell-cell communication analysis suggested interactions between POMC-expressing chromaffin cells and cytotoxic immune cells. Pseudotemporal trajectory analysis further suggested that these chromaffin cells did not transition toward a steroidogenic fate. This study provided a single-cell atlas of ectopic ACTH-secreting pheochromocytomas. Our integrated analysis suggested POMC-expressing chromaffin cells may represent the cellular source of ectopic ACTH production and revealed a transcriptional signature involving metabolic activation and immune modulation that might contribute to tumor progression. These findings offered new insights into the pathophysiology of this rare disease and provided a framework for future investigations into the molecular mechanisms underlying ectopic ACTH production.
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Building consensus: construction of a juvenile and adult scRNA-seq meta-atlas for dataset comparisons and harmonizing transcriptomic definitions of enteric neuron subtypes.
BACKGROUND: The enteric nervous system (ENS) is a complex network of interconnected ganglia within the gastrointestinal (GI) tract. Among its diverse functions, the ENS detects bowel luminal contents and coordinates the passing of stool. ENS defects predispose to GI motility disorders. Previously, distinct enteric neuron types were cataloged by dye-filling techniques, immunohistochemistry, retrograde labeling, and electrophysiology. Recent technical advances in single cell RNA-sequencing (scRNA-seq) have enabled transcriptional profiling of hundreds to millions of individual cells from the intestine. These data allow cell types to be resolved and compared using their transcriptional profiles (“clusters”) rather than relying on antibody labeling. As a result, greater diversity of enteric neuron types has been appreciated. Because each scRNA-seq study has relied on different methods for cell isolation and library generation, numbers of neuron clusters and cell types detected differ between analyses. Cell counts in each dataset are particularly important for characterization of rare cell types since small numbers of profiled cells may not sample rare cell types. Importantly, each dataset, depending on the isolation methods, may contain different proportions of cells that are not detected in other datasets. Aggregation of datasets can effectively increase the total number of cells being analyzed and can be helpful for confirming the presence of low-abundance neuron types that might be absent or observed infrequently in any single dataset. RESULTS: Here we briefly systematically review each Mus musculus single cell or single nucleus RNA-sequencing (snRNA-seq) ENS dataset. We then reprocess and computationally integrate these select independent scRNA-seq enteric neuron datasets from the myenteric plexus with the aim to identify new cell types, shared marker genes across juvenile to adult ages, dataset differences, and achieve some consensus on transcriptomic definitions of enteric neuronal subtypes. CONCLUSIONS: Data aggregation generates a consensus view of enteric neuron types and improves resolution of rare neuron classes. This meta-atlas offers a deeper understanding of enteric neuron diversity and may prove useful to investigators aiming to define alterations among enteric neurons in disease states. Future studies face the challenge of connecting these deep transcriptional profiles for enteric neurons with historical classification systems.
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ANLN: A New Hub in Glutamine Metabolism of Lung Adenocarcinoma by scRNA-Seq and Machine Learning.
OBJECTIVES: Lung adenocarcinoma (LUAD) has a poor prognosis, and effective metabolic biomarkers are still few. Glutamine metabolism is one of the central features of tumor metabolic reprogramming, but the cellular heterogeneity and clinical significance of glutamine metabolism in the LUAD tumor microenvironment (TME) remain unknown. The goal of this paper was to define glutamine metabolism on a single-cell basis and determine major regulators that have predictive value. METHODS: A single-cell RNA sequencing dataset (GSE149655) was combined with The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) and Gene Expression Omnibus (GEO) datasets in order to evaluate the metabolic activity and intercellular communication. The prognostic model was constructed on weighted gene co-expression network analysis (WGCNA), machine learning-based approaches, and least absolute shrinkage and selection operator (LASSO)-Cox regression to examine the characteristics of the immune system and sensitivity to drugs. Carried out CRISPR/Cas9 knockout experiments to prove the function of ANLN. RESULTS: Glutamine metabolism activity and increased cell-cell communication were observed in mast cells. A gene signature of 4 genes (ANLN, CIP2A, MEST, WDR76) divided the patients into high-risk and low-risk groups; the survival of these two groups, immunosuppressant features of TME, and susceptibility to dasatinib were different. ANLN was also determined to be an essential prognostic driver, and downregulating it inhibited glutamine metabolism and the invasion properties of LUAD cells. CONCLUSIONS: Mast cells are metabolic centers of LUAD, whereas ANLN is a mediator of the association between glutamine metabolism and the development of tumors, which offers possible treatment options to achieve precise prognostication and treatment goals.
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POSTN+ cancer-associated fibroblasts promote bladder cancer progression via angiogenesis and immune modulation: an analysis based on single-cell Transcriptomics.
BACKGROUND: Bladder cancer (BCa) progression is driven by the tumor microenvironment, with cancer-associated fibroblasts (CAFs) playing a pivotal role. Periostin (POSTN), secreted by CAFs, is linked to tumor malignancy, but its specific role in BCa remains unclear. METHODS: This study is a secondary analysis of publicly available single-cell and bulk transcriptomic data. Single-cell RNA sequencing (scRNA-seq) data from four BCa and four control samples were analyzed to construct a transcriptomic atlas. CAFs and monocytes were subclustered, and POSTN+ CAFs were characterized using differential gene expression, GSVA, and KEGG analyses. CellChat and NicheNet assessed cell-cell communication. TCGA data were used to validate POSTN's prognostic significance. Additionally, POSTN expression was detected in transfected CAF cell lines, and scratch and invasion assays were performed using the co-culture system of CAFs and bladder cancer cells (T24). RESULTS: Nine cell clusters were identified, with monocytes and CAFs enriched in BCa. POSTN+ CAFs, significantly increased in BCa, promoted angiogenesis, migration, and invasion. CellChat revealed enhanced CAF-monocyte communication via the IL1B/IL1R1 axis, contributing to an immunosuppressive microenvironment. KLRC1+ monocytes were enriched in BCa, regulating cell cycle and angiogenesis. Pseudotime analysis showed CAFs' differentiation toward pro-tumorigenic states. TCGA analysis confirmed POSTN's upregulation and association with poor prognosis (P < 0.05). Functional assays revealed CAFs markedly enhanced T24 migration and invasion, and POSTN knockdown suppressed this CAF-induced effect (P < 0.01). CONCLUSION: POSTN+ CAFs drive BCa progression by enhancing angiogenesis, migration, and immune suppression, mediated partly by the IL1B/IL1R1 axis.
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Canine mesenteric lymph nodes (MLNs) characterization by sc-RNAseq: insights compared to human and mouse MLNs.
In the human and veterinary fields, oral vaccines generate considerable interest. In dogs, these vaccines are newly developed, and understanding their mechanisms is crucial. Mesenteric lymph nodes (MLNs) and Peyer's patches (PPs) are important sites for gastrointestinal mucosal induction, yet canine MLNs lack sufficient information. To address this, we collected MLN samples from healthy dogs, performed flow cytometry to characterize immune cells, and conducted single-cell RNA sequencing (scRNA-seq) to explore subpopulations, particularly B and T lymphocytes. This effort enabled the characterization of canine MLN's main cell populations and the construction of a predictive atlas, as well as the identification of particularities of this area.