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Single-tube nested PCR (STnPCR) is a technique that improves nested PCR, reducing potential contamination and false-positive results, enhancing the amplification sensitivity. Despite being commonly used for the detection of microorganisms, STnPCR can be a valuable tool for bovine genotyping, encompassing essential targets as ROSA26 and TSPY, pivotal in the fields of animal reproduction, genetic improvement, and transgenic research. The objective of this study was to improve and innovate STnPCR for gene detection in cattle. We aimed to detect the ROSA26 and TSPY genes using low-concentration DNA samples, including single cells, small cell groups (one to five cells), in vitro-produced embryos, and bovine tissue samples. Moreover, we refined STnPCR for gene detection in up to single cells by conducting sensitivity testing with different concentration ratios of internal and external primers. Successful amplification of the ROSA26 and TSPY genes was achieved across all tested primer concentrations, even in single cells, with more consistent results observed at lower primer concentrations. Additionally, simultaneous gene amplification was achieved through STnPCR multiplexing, representing the first study of multiplex STnPCR in cattle. These outcomes not only confirm its effectiveness in detecting genetic markers for animal genetic improvement and transgenic elements but also pave the way for its widespread adoption in reproductive studies in bovines.
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Técnicas de Genotipagem , Reação em Cadeia da Polimerase , Animais , Bovinos/genética , Reação em Cadeia da Polimerase/métodos , Técnicas de Genotipagem/métodos , Embrião de Mamíferos , Análise de Célula Única/métodos , GenótipoRESUMO
BACKGROUND: To investigate the impact of the tumor microenvironment (TME) on the responsiveness to chemotherapy in ovarian cancer (OV). METHODS: We integrated single cell RNA-seq datasets of OV containing chemo-response information, and characterize their clusters based on different TME sections. We focus on analyzing cell-cell communication to elaborate on the mechanisms by which different components of the TME directly influence the chemo-response of tumor cells. RESULTS: scRNA-seq datasets were annotated according to specific markers for different cell types. Differential analysis of malignant epithelial cells revealed that chemoresistance was associated with the TME. Notably, distinct TME components exhibited varying effects on chemoresistance. Enriched SPP1+ tumor-associated macrophages in chemo-resistant patients could promote chemoresistance through SPP1 binding to CD44 on tumor cells. Additionally, the overexpression of THBS2 in stromal cells could promote chemoresistance through binding with CD47 on tumor cells. In contrast, GZMA in the lymphocytes could downregulate the expression of PARD3 through direct interaction with PARD3, thereby attenuating chemoresistance in tumor cells. CONCLUSION: Our study indicates that the non-tumor cell components of the TME (e.g. SPP1+ TAMs, stromal cells and lymphocytes) can directly impact the chemo-response of OV and targeting the TME was potentially crucial in chemotherapy of OV.
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Here, we performed single-cell RNA sequencing of S1 and receptor binding domain protein-specific B cells from convalescent COVID-19 patients with different clinical manifestations. This study aimed to evaluate the role and developmental pathway of atypical memory B cells (MBCs) in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The results revealed a proinflammatory signature across B cell subsets associated with disease severity, as evidenced by the upregulation of genes such as GADD45B, MAP3K8, and NFKBIA in critical and severe individuals. Furthermore, the analysis of atypical MBCs suggested a developmental pathway similar to that of conventional MBCs through germinal centers, as indicated by the expression of several genes involved in germinal center processes, including CXCR4, CXCR5, BCL2, and MYC. Additionally, the upregulation of genes characteristic of the immune response in COVID-19, such as ZFP36 and DUSP1, suggested that the differentiation and activation of atypical MBCs may be influenced by exposure to SARS-CoV-2 and that these genes may contribute to the immune response for COVID-19 recovery. Our study contributes to a better understanding of atypical MBCs in COVID-19 and the role of other B cell subsets across different clinical manifestations.
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COVID-19 , Células B de Memória , SARS-CoV-2 , Análise de Célula Única , Humanos , COVID-19/imunologia , COVID-19/virologia , COVID-19/genética , SARS-CoV-2/imunologia , SARS-CoV-2/genética , Células B de Memória/imunologia , Masculino , Adulto , Feminino , Pessoa de Meia-Idade , Perfilação da Expressão Gênica , Transcriptoma , Centro Germinativo/imunologia , Linfócitos B/imunologia , IdosoRESUMO
PURPOSE: Breast cancer (BRCA) is characterized by a unique metastatic pattern, often presenting with bone metastasis (BoM), posing significant clinical challenges. Through the study of the immune microenvironment in BRCA BoM offer perspectives for therapeutic interventions targeting this specific metastatic manifestation of BRCA. METHODS: This study employs single-cell RNA sequencing and TCGA data analysis to comprehensively compare primary tumors (PT), lymph node metastasis (LN), and BoM. RESULTS AND CONCLUSIONS: Our investigation identifies a metastatic niche in BoM marked by an increased abundance of cancer-associated fibroblasts (CAFs) and reduced immune cell presence. A distinct subtype (State 1) of BRCA BoM cells associated with adverse prognosis is identified. State 1, displaying heightened stemness traits, may represent an initiation phase for BoM in BRCA. Complex cell communications involving tumor, stromal, and immune cells are revealed. Interactions of FN1, SPP1, and MDK correlate with elevated immune cells in BoM. CD46, MDK, and PTN interactions drive myofibroblast activation and proliferation, contributing to tissue remodeling. Additionally, MDK, PTN, and FN1 interactions influence FAP+ CAF activation, impacting cell adhesion and migration in BoM. These insights deepen our understanding of the metastatic niche in breast cancer BoM.
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The aging of mammalian ovary is accompanied by an increase in tissue fibrosis and heightened inflammation. Myeloid cells, including macrophages, monocytes, dendritic cells, and neutrophils, play pivotal roles in shaping the ovarian tissue microenvironment and regulating inflammatory responses. However, a comprehensive understanding of the roles of these cells in the ovarian aging process is lacking. To bridge this knowledge gap, we utilized single-cell RNA sequencing (scRNAseq) and flow cytometry analysis to functionally characterize CD45+ CD11b+ myeloid cell populations in young (3 months old) and aged (14-17 months old) murine ovaries. Our dataset unveiled the presence of five ovarian macrophage subsets, including a Cx3cr1 low Cd81 hi subset unique to the aged murine ovary. Most notably, our data revealed significant alterations in ANNEXIN and TGFß signaling within aged ovarian myeloid cells, which suggest a novel mechanism contributing to the onset and progression of aging-associated inflammation and fibrosis in the ovarian tissue.
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BACKGROUND: Pulmonary hypertension (PH) is a common complication of systemic sclerosis (SSc) and a leading cause of mortality among patients with this disease. PH can also occur as an idiopathic condition (idiopathic pulmonary arterial hypertension). Investigation of transcriptomic alterations in vascular populations is critical to elucidating cellular mechanisms underlying pathobiology of SSc-associated and idiopathic PH. METHODS: We analyzed single-cell RNA sequencing profiles of endothelial and perivascular mesenchymal populations from explanted lung tissue of patients with SSc-associated PH (n=16), idiopathic pulmonary arterial hypertension (n=3), and healthy controls (n=15). Findings were validated by immunofluorescence staining of explanted human lung tissue. RESULTS: Three disease-associated endothelial populations emerged. Two angiogenic endothelial cell (EC) subtypes markedly expanded in SSc-associated PH lungs: tip ECs expressing canonical tip markers PGF and APLN and phalanx ECs expressing genes associated with vascular development, endothelial barrier integrity, and Notch signaling. Gene regulatory network analysis suggested enrichment of Smad1 (SMAD family member 1) and PPAR-γ (peroxisome proliferator-activated receptor-γ) regulon activities in these 2 populations, respectively. Mapping of potential ligand-receptor interactions highlighted Notch, apelin-APJ (apelin receptor), and angiopoietin-Tie (tyrosine kinase with immunoglobulin-like and EGF-like domains 1) signaling pathways between angiogenic ECs and perivascular cells. Transitional cells, expressing both endothelial and pericyte/smooth muscle cell markers, provided evidence for the presence of endothelial-to-mesenchymal transition. Transcriptional programs associated with arterial endothelial dysfunction implicated VEGF-A (vascular endothelial growth factor-A), TGF-ß1 (transforming growth factor beta-1), angiotensin, and TNFSF12 (tumor necrosis factor ligand superfamily member 12)/TWEAK (TNF-related weak inducer of apoptosis) in the injury/remodeling phenotype of PH arterial ECs. CONCLUSIONS: These data provide high-resolution insights into the complexity and plasticity of the pulmonary endothelium in SSc-associated PH and idiopathic pulmonary arterial hypertension and provide direct molecular insights into soluble mediators and transcription factors driving PH vasculopathy.
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Neovascularização Patológica , Escleroderma Sistêmico , Remodelação Vascular , Humanos , Escleroderma Sistêmico/genética , Escleroderma Sistêmico/patologia , Escleroderma Sistêmico/metabolismo , Escleroderma Sistêmico/complicações , Masculino , Feminino , Pessoa de Meia-Idade , Hipertensão Pulmonar Primária Familiar/metabolismo , Hipertensão Pulmonar Primária Familiar/genética , Hipertensão Pulmonar Primária Familiar/fisiopatologia , Hipertensão Pulmonar Primária Familiar/patologia , Estudos de Casos e Controles , Células Endoteliais/metabolismo , Células Endoteliais/patologia , Artéria Pulmonar/metabolismo , Artéria Pulmonar/patologia , Artéria Pulmonar/fisiopatologia , Transcriptoma , Transdução de Sinais , Adulto , Análise de Célula Única , Pulmão/metabolismo , Pulmão/irrigação sanguínea , Pulmão/patologia , Redes Reguladoras de Genes , AngiogêneseRESUMO
Advancements in long-read transcriptome sequencing (long-RNA-seq) technology have revolutionized the study of isoform diversity. These full-length transcripts enhance the detection of various transcriptome structural variations, including novel isoforms, alternative splicing events, and fusion transcripts. By shifting the open reading frame or altering gene expressions, studies have proved that these transcript alterations can serve as crucial biomarkers for disease diagnosis and therapeutic targets. In this project, we proposed IFDlong, a bioinformatics and biostatistics tool to detect isoform and fusion transcripts using bulk or single-cell long-RNA-seq data. Specifically, the software performed gene and isoform annotation for each long-read, defined novel isoforms, quantified isoform expression by a novel expectation-maximization algorithm, and profiled the fusion transcripts. For evaluation, IFDlong pipeline achieved overall the best performance when compared with several existing tools in large-scale simulation studies. In both isoform and fusion transcript quantification, IFDlong is able to reach more than 0.8 Spearman's correlation with the truth, and more than 0.9 cosine similarity when distinguishing multiple alternative splicing events. In novel isoform simulation, IFDlong can successfully balance the sensitivity (higher than 90%) and specificity (higher than 90%). Furthermore, IFDlong has proved its accuracy and robustness in diverse in-house and public datasets on healthy tissues, cell lines and multiple types of diseases. Besides bulk long-RNA-seq, IFDlong pipeline has proved its compatibility to single-cell long-RNA-seq data. This new software may hold promise for significant impact on long-read transcriptome analysis. The IFDlong software is available at https://github.com/wenjiaking/IFDlong.
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Glioblastoma Multiforme is a brain tumor distinguished by its aggressiveness. We suggested that this aggressiveness leads single-cell RNA-sequence data (scRNA-seq) to span a representative portion of the cancer attractors domain. This conjecture allowed us to interpret the scRNA-seq heterogeneity as reflecting a representative trajectory within the attractor's domain. We considered factors such as genomic instability to characterize the cancer dynamics through stochastic fixed points. The fixed points were derived from centroids obtained through various clustering methods to verify our method sensitivity. This methodological foundation is based upon sample and time average equivalence, assigning an interpretative value to the data cluster centroids and supporting parameters estimation. We used stochastic simulations to reproduce the dynamics, and our results showed an alignment between experimental and simulated dataset centroids. We also computed the Waddington landscape, which provided a visual framework for validating the centroids and standard deviations as characterizations of cancer attractors. Additionally, we examined the stability and transitions between attractors and revealed a potential interplay between subtypes. These transitions might be related to cancer recurrence and progression, connecting the molecular mechanisms of cancer heterogeneity with statistical properties of gene expression dynamics. Our work advances the modeling of gene expression dynamics and paves the way for personalized therapeutic interventions.
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Neoplasias Encefálicas , Glioblastoma , Análise de Célula Única , Glioblastoma/genética , Glioblastoma/patologia , Glioblastoma/metabolismo , Humanos , Análise de Célula Única/métodos , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patologia , Neoplasias Encefálicas/metabolismo , Regulação Neoplásica da Expressão Gênica , Heterogeneidade Genética , Perfilação da Expressão Gênica/métodos , Instabilidade Genômica , Análise de Sequência de RNA/métodos , Análise por ConglomeradosRESUMO
BACKGROUND: Normalization is a critical step in the analysis of single-cell RNA-sequencing (scRNA-seq) datasets. Its main goal is to make gene counts comparable within and between cells. To do so, normalization methods must account for technical and biological variability. Numerous normalization methods have been developed addressing different sources of dispersion and making specific assumptions about the count data. MAIN BODY: The selection of a normalization method has a direct impact on downstream analysis, for example differential gene expression and cluster identification. Thus, the objective of this review is to guide the reader in making an informed decision on the most appropriate normalization method to use. To this aim, we first give an overview of the different single cell sequencing platforms and methods commonly used including isolation and library preparation protocols. Next, we discuss the inherent sources of variability of scRNA-seq datasets. We describe the categories of normalization methods and include examples of each. We also delineate imputation and batch-effect correction methods. Furthermore, we describe data-driven metrics commonly used to evaluate the performance of normalization methods. We also discuss common scRNA-seq methods and toolkits used for integrated data analysis. CONCLUSIONS: According to the correction performed, normalization methods can be broadly classified as within and between-sample algorithms. Moreover, with respect to the mathematical model used, normalization methods can further be classified into: global scaling methods, generalized linear models, mixed methods, and machine learning-based methods. Each of these methods depict pros and cons and make different statistical assumptions. However, there is no better performing normalization method. Instead, metrics such as silhouette width, K-nearest neighbor batch-effect test, or Highly Variable Genes are recommended to assess the performance of normalization methods.
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Análise de Célula Única , Animais , Humanos , Algoritmos , Perfilação da Expressão Gênica/métodos , Perfilação da Expressão Gênica/normas , RNA-Seq/métodos , RNA-Seq/normas , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Transcriptoma , Conjuntos de Dados como AssuntoRESUMO
The marine subsurface is a long-term sink of atmospheric carbon dioxide with significant implications for climate on geologic timescales. Subsurface microbial cells can either enhance or reduce carbon sequestration in the subsurface, depending on their metabolic lifestyle. However, the activity of subsurface microbes is rarely measured. Here, we used nanoscale secondary ion mass spectrometry (nanoSIMS) to quantify anabolic activity in 3,203 individual cells from the thermally altered deep subsurface in the Guaymas Basin, Mexico (3-75 m below the seafloor, 0-14°C). We observed that a large majority of cells were active (83%-100%), although the rates of biomass generation were low, suggesting cellular maintenance rather than doubling. Mean single-cell activity decreased with increasing sediment depth and temperature and was most strongly correlated with porewater sulfate concentrations. Intracommunity heterogeneity in microbial activity decreased with increasing sediment depth and age. Using a dual-isotope labeling approach, we determined that all active cells analyzed were heterotrophic, deriving the majority of their cellular carbon from organic sources. However, we also detected inorganic carbon assimilation in these heterotrophic cells, likely via processes such as anaplerosis, and determined that inorganic carbon contributes at least 5% of the total biomass carbon in heterotrophs in this community. Our results demonstrate that the deep marine biosphere at Guaymas Basin is largely active and contributes to subsurface carbon cycling primarily by not only assimilating organic carbon but also fixing inorganic carbon. Heterotrophic assimilation of inorganic carbon may be a small yet significant and widespread underappreciated source of labile carbon in the global subsurface. IMPORTANCE: The global subsurface is the largest reservoir of microbial life on the planet yet remains poorly characterized. The activity of life in this realm has implications for long-term elemental cycling, particularly of carbon, as well as how life survives in extreme environments. Here, we recovered cells from the deep subsurface of the Guaymas Basin and investigated the level and distribution of microbial activity, the physicochemical drivers of activity, and the relative significance of organic versus inorganic carbon to subsurface biomass. Using a sensitive single-cell assay, we found that the majority of cells are active, that activity is likely driven by the availability of energy, and that although heterotrophy is the dominant metabolism, both organic and inorganic carbon are used to generate biomass. Using a new approach, we quantified inorganic carbon assimilation by heterotrophs and highlighted the importance of this often-overlooked mode of carbon assimilation in the subsurface and beyond.
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Bactérias , Ciclo do Carbono , Sedimentos Geológicos , Processos Heterotróficos , Microbiota , Análise de Célula Única , Sedimentos Geológicos/microbiologia , Sedimentos Geológicos/química , Bactérias/metabolismo , Bactérias/classificação , México , Água do Mar/microbiologia , Água do Mar/química , Carbono/metabolismoRESUMO
Bladder cancer (BC) is the 10th most common cancer worldwide, with about 0.5 million reported new cases and about 0.2 million deaths per year. In this scoping review, we summarize the current evidence regarding the clinical implications of single-cell sequencing for bladder cancer based on PRISMA guidelines. We searched PubMed, CENTRAL, Embase, and supplemented with manual searches through the Scopus, and Web of Science for published studies until February 2023. We included original studies that used at least one single-cell technology to study bladder cancer. Forty-one publications were included in the review. Twenty-nine studies showed that this technology can identify cell subtypes in the tumor microenvironment that may predict prognosis or response to immune checkpoint inhibition therapy. Two studies were able to diagnose BC by identifying neoplastic cells through single-cell sequencing urine samples. The remaining studies were mainly a preclinical exploration of tumor microenvironment at single cell level. Single-cell sequencing technology can discriminate heterogeneity in bladder tumor cells and determine the key molecular properties that can lead to the discovery of novel perspectives on cancer management. This nascent tool can advance the early diagnosis, prognosis judgment, and targeted therapy of bladder cancer.
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Carcinoma de Células de Transição , Neoplasias da Bexiga Urinária , Humanos , Carcinoma de Células de Transição/tratamento farmacológico , Carcinoma de Células de Transição/patologia , Neoplasias da Bexiga Urinária/diagnóstico , Neoplasias da Bexiga Urinária/genética , Neoplasias da Bexiga Urinária/terapia , Prognóstico , Microambiente Tumoral/genéticaRESUMO
BACKGROUND: Neoadjuvant immunotherapy has evolved as an effective option to treat non-small cell lung cancer (NSCLC). B cells play essential roles in the immune system as well as cancer progression. However, the repertoire of B cells and its association with clinical outcomes remains unclear in NSCLC patients receiving neoadjuvant immunotherapy. METHODS: Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data for LUAD samples were accessed from the TCGA and GEO databases. LUAD-related B cell marker genes were confirmed based on comprehensive analysis of scRNA-seq data. We then constructed the B cell marker gene signature (BCMGS) and validated it. In addition, we evaluated the association of BCGMS with tumor immune microenvironment (TIME) characteristics. Furthermore, we validated the efficacy of BCGMS in a cohort of NSCLC patients receiving neoadjuvant immunotherapy. RESULTS: A BCMGS was constructed based on the TCGA cohort and further validated in three independent GSE cohorts. In addition, the BCMGS was proven to be significantly associated with TIME characteristics. Moreover, a relatively higher risk score indicated poor clinical outcomes and a worse immune response among NSCLC patients receiving neoadjuvant immunotherapy. CONCLUSIONS: We constructed an 18-gene prognostic signature derived from B cell marker genes based on scRNA-seq data, which had the potential to predict the prognosis and immune response of NSCLC patients receiving neoadjuvant immunotherapy.
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Carcinoma Pulmonar de Células não Pequenas , Imunoterapia , Neoplasias Pulmonares , Terapia Neoadjuvante , Análise de Sequência de RNA , Análise de Célula Única , Microambiente Tumoral , Humanos , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/terapia , Carcinoma Pulmonar de Células não Pequenas/patologia , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/terapia , Neoplasias Pulmonares/patologia , Prognóstico , Imunoterapia/métodos , Microambiente Tumoral/genética , Microambiente Tumoral/imunologia , Feminino , Masculino , Biomarcadores Tumorais/genética , Linfócitos B/imunologia , Pessoa de Meia-Idade , IdosoRESUMO
Telocytes (TCs) are CD34-positive interstitial cells that have long cytoplasmic projections, called telopodes; they have been identified in several organs and in various species. These cells establish a complex communication network between different stromal and epithelial cell types, and there is growing evidence that they play a key role in physiology and pathology. In many tissues, TC network impairment has been implicated in the onset and progression of pathological conditions, which makes the study of TCs of great interest for the development of novel therapies. In this review, we summarise the main methods involved in the characterisation of these cells as well as their inherent difficulties and then discuss the functional assays that are used to uncover the role of TCs in normal and pathological conditions, from the most traditional to the most recent. Furthermore, we provide future perspectives in the study of TCs, especially regarding the establishment of more precise markers, commercial lineages and means for drug delivery and genetic editing that directly target TCs.
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Telócitos , Telócitos/citologia , Telócitos/metabolismo , Humanos , AnimaisRESUMO
Gene editing tools have triggered a revolutionary transformation in the realms of cellular and molecular physiology, serving as a fundamental cornerstone for the evolution of disease models and assays in cell culture reactions, marked by various enhancements. Concurrently, microfluidics has emerged over recent decades as a versatile technology capable of elevating performance and reducing costs in daily experiments across diverse scientific disciplines, with a pronounced impact on cell biology. The amalgamation of these groundbreaking techniques holds the potential to amplify the generation of stable cell lines and the production of extracellular matrix hydrogels. These hydrogels, assuming a pivotal role in isolating cells at the single-cell level, facilitate a myriad of analyses. This study presents a novel method that seamlessly integrates CRISPR-Cas9 gene editing techniques with single-cell isolation methods in induced pluripotent stem cell (hiPSC) lines, utilizing the combined power of droplets and hydrogels. This innovative approach is designed to optimize clonal selection, thereby concurrently reducing costs and the time required for generating a stable genetically modified cell line. By bridging the advancements in gene editing and microfluidic technologies, our approach not only holds significant promise for the development of disease models and assays but also addresses the crucial need for efficient single-cell isolation. This integration contributes to streamlining processes, making it a transformative method with implications for enhancing the efficiency and cost-effectiveness of stable cell line generation. As we navigate the intersection of gene editing and microfluidics, our study marks a significant stride toward innovative methodologies in the dynamic landscape of cellular and molecular physiology research.
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Glioblastomas are known for their poor clinical prognosis, with recurrent tumors often exhibiting greater invasiveness and faster growth rates compared to primary tumors. To understand the intratumoral changes driving this phenomenon, we employed single-cell sequencing to analyze the differences between two pairs of primary and recurrent glioblastomas. Our findings revealed an upregulation of ferroptosis in endothelial cells within recurrent tumors, identified by the significant overexpression of the NOX4 gene. Further analysis indicated that knocking down NOX4 in endothelial cells reduced the activity of the ferroptosis pathway. Utilizing conditioned media from endothelial cells with lower ferroptosis activity, we observed a decrease in the growth rate of glioblastoma cells. These results highlighted the complex role of ferroptosis within tumors and suggested that targeting ferroptosis in the treatment of glioblastomas requires careful consideration of its effects on endothelial cells, as it may otherwise produce counterproductive outcomes.
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The key role of CFTR in secretory epithelia has been extensively documented. Additionally, CFTR plays a significant role in ion absorption in exocrine glands, including salivary and sweat glands. Most of the knowledge about CFTR expression comes from animal models such as the mouse or the rat, but there is limited information about CFTR expression in human tissues. In the present study, we assessed the expression of CFTR in human submandibular and parotid glands. Consistent with findings in rodent salivary glands, our immunolocalization studies show that CFTR is expressed in duct cells. However, CFTR expression in human salivary glands differs from that in rodents, as immunolocalization and single-cell RNA sequencing analysis from a previous study performed in the human parotid gland revealed the presence of CFTR protein and transcripts within a distinct cell cluster. Based on cell marker expression, this cluster corresponds to acinar cells. To obtain functional evidence supporting CFTR expression, we isolated human parotid acinar cells through collagenase digestion. Acinar cells displayed an anion conductance that was activated in response to cAMP-increasing agents and was effectively blocked by CFTRInh172, a known CFTR blocker. This study provides novel evidence of CFTR expression within acinar cells of human salivary glands. This finding challenges the established model positioning CFTR exclusively in duct cells from exocrine glands.NEW & NOTEWORTHY This study addresses the uncertainty about the impact of CFTR on human salivary gland function. We found CFTR transcripts in a subset of duct cells known as ionocytes, as well as in acinar cells. Isolated human parotid acinar cells exhibited Cl- conductance consistent with CFTR activity. This marks the first documented evidence of functional CFTR expression in human salivary gland acinar cells.
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Células Acinares , Regulador de Condutância Transmembrana em Fibrose Cística , Humanos , Ratos , Camundongos , Animais , Regulador de Condutância Transmembrana em Fibrose Cística/genética , Regulador de Condutância Transmembrana em Fibrose Cística/metabolismo , Glândulas Salivares/metabolismo , Glândula Submandibular/metabolismo , Glândula Parótida/metabolismoRESUMO
BACKGROUND: Protein phosphatase 1 regulatory subunit 14B (PPP1R14B) is an oncogenic gene found in a variety of tumors, but its role in the prognosis and development of kidney renal clear cell carcinoma (KIRC) remains unknown. Our study aimed to determine whether PPP1R14B could be a prognostic biomarker for KIRC and its role in the development of KIRC. METHODS: In this work, we used The Cancer Genome Atlas (TCGA) database to explore the expression of PPP1R14B in tumor tissues, its relationship with the prognosis of tumor patients, and its role in tumor occurrence and development. We validated our findings using the International Cancer Genome Consortium (ICGC) cohort, our clinical samples, and in vitro experiments. RESULTS: PPP1R14B was upregulated in KIRC compared to adjacent normal tissue. Moreover, multivariate analysis revealed that upregulated PPP1R14B expression was an independent risk factor for KIRC progression. High-PPP1R14B groups had shorter overall survival (OS) and disease-free survival (DFS) in TCGA and ICGC cohorts. We used Cell Counting Kit-8 (CCK8) and scratch wound healing assay to explore the proliferation and migration of KIRC cells following PPP1R14B knockdown. Our results indicated that PPP1R14B knockdown significantly reduced the proliferation and migration of KIRC cells in vitro. We also explored the possible cellular mechanisms of PPP1R14B through the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene ontology (GO) analysis, and TISIDB analysis. The function enrich analysis revealed that PPP1R14B-related genes were mainly enriched in purine metabolism and the macromolecule catabolic process. PPP1R14B expression was associated with tumor-infiltrating immune cells (TIICs) in the TCGA cohort, and the results of single-cell RNA-seq (scRNA) further demonstrated that PPP1R14B expression was associated with the enhanced infiltration of CD8 + T lymphocytes. CONCLUSION: PPP1R14B may serve as a prognostic biomarker in KIRC, affect purine metabolism, activate immune infiltration, and promote KIRC cell migration.
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Carcinoma de Células Renais , Neoplasias Renais , Humanos , Biomarcadores , Carcinoma de Células Renais/genética , Rim , Neoplasias Renais/genética , Prognóstico , Proteína Fosfatase 1 , PurinasRESUMO
BACKGROUND: Cancer-associated fibroblasts (CAFs) play a significant role in regulating the clinical outcome and radiotherapy prognosis of prostate cancer (PCa). The aim of this study is to identify CAFs-related genes (CAFsRGs) using single-cell analysis and evaluate their potential for predicting the prognosis and radiotherapy prognosis in PCa. METHODS: We acquire transcriptome and single-cell RNA sequencing (scRNA-seq) results of PCa and normal adjacent tissues from The GEO and TCGA databases. The "MCPcounter" and "EPIC" R packages were used to assess the infiltration level of CAFs and examine their correlation with PCa prognosis. ScRNA-seq and differential gene expression analyses were used to extract CAFsRGs. We also applied COX and LASSO analysis to further construct a risk score (CAFsRS) to assess biochemical recurrence-free survival (BRFS) and radiotherapy prognosis of PCa. The predictive efficacy of CAFsRS was evaluated by ROC curves and subgroup analysis. Finally, we integrated the CAFsRS gene signature with relevant clinical features to develop a nomogram, enhancing the predictive accuracy. RESULTS: The abundance of CAFs is associated with a poor prognosis of PCa patients. ScRNA-seq and differential gene expression analysis revealed 323 CAFsRGs. After COX and LASSO analysis, we obtained seven CAFsRGs with prognostic significance (PTGS2, FKBP10, ENG, CDH11, COL5A1, COL5A2, and SRD5A2). Additionally, we established a risk score model based on the training set (n = 257). The ROC curve was used to confirm the performance of CAFsRS (The AUC values for 1, 3 and 5-year survival were determined to be 0.732, 0.773, and 0.775, respectively.). The testing set (n = 129), GSE70770 set (n = 199) and GSE116918 set (n = 248) revealed that the model exhibited exceptional predictive performance. This was also confirmed by clinical subgroup analysis. The violin plot demonstrated a statistically significant disparity in the CAFs infiltrations between the high-risk and low-risk groups of CAFsRS. Further analysis confirmed that both CAFsRS and T stage were independent prognostic factors for PCa. The nomogram was then established and its excellent predictive performance was demonstrated through calibration and ROC curves. Finally, we developed an online prognostic prediction app ( https://sysu-symh-cafsnomogram.streamlit.app/ ) to facilitate the practical application of the nomogram. CONCLUSIONS: The prognostic prediction risk score model we constructed could accurately predict BRFS and radiotherapy prognosis PCa, which can provide new ideas for clinicians to develop personalized PCa treatment and follow-up programs.
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Coffee is a crop of significant socioeconomic importance, and the reuse of agri-food by-products and biowaste has great potential across several industries. Coffee wastewater (CWW) is a valuable resource containing essential nutrients that can be utilized by Candida sorboxylosa for single-cell protein (SCP) production. This utilization contributes to mitigating the negative impacts of agro-industrial waste. The optimization of culture conditions using the design of experiments (DoE) technique is crucial in understanding the environmental factors influencing metabolite production. In our study, the DoE technique was employed to analyze culture conditions, including room temperature, pH 8.4, agitation at 200 rpm, a headspace of 60% (v/v), and an inoculum of 0.75 DO600nm over 28-h period. This approach resulted in a remarkable SCP yield of 64.4% and dry cell weight (DCW) of 2.26 g/L. It is noteworthy that there is no literature reporting SCP production under alkaline pH conditions in yeast. Interestingly, our work demonstrated that an alkaline pH of 8.4 significantly influenced SCP production by C. sorboxylosa. The DoE technique proved to be an efficient statistical tool for optimizing culture conditions, offering several advantages, such as: (i) conducting cultures at room temperature to minimize unnecessary energy consumption; (ii) reducing the incubation time from 46 to 28 h, thereby enhancing overall productivity; (iii) achieving 1.7-fold increase in SCP yield compared to previous basal production levels.
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Candida , Coffea , Águas Residuárias , Café , Saccharomyces cerevisiaeRESUMO
Deep transfer learning improves the inference of gene regulatory networks in human cells, reveals disease-associated genes, and identifies network-based druggable targets in human heart disease.