Marker Genes Research Articles

Machine Learning-enhanced Signature of Metastasis-related T Cell Marker Genes for Predicting Overall Survival in Malignant Melanoma.

In this study, we aimed to investigate disparities in the tumor immune microenvironment (TME) between primary and metastatic malignant melanoma (MM) using single-cell RNA sequencing (scRNA-seq) and to identify metastasis-related T cell marker genes (MRTMGs) for predicting patient survival using machine learning techniques. We identified 6 distinct T cell clusters in 10×scRNA-seq data utilizing the Uniform Manifold Approximation and Projection (UMAP) algorithm. Four machine learning algorithms highlighted SRGN, PMEL, GPR143, EIF4A2, and DSP as pivotal MRTMGs, forming the foundation of the MRTMGs signature. A high MRTMGs signature was found to be correlated with poorer overall survival (OS) and suppression of antitumor immunity in MM patients. We developed a nomogram that combines the MRTMGs signature with the T stage and N stage, which accurately predicts 1-year, 3-year, and 5-year OS probabilities. Furthermore, in an immunotherapy cohort, a high MRTMG signature was associated with an unfavorable response to anti-programmed death 1 (PD-1) therapy. In conclusion, primary and metastatic MM display distinct TME landscapes with different T cell subsets playing crucial roles in metastasis. The MRTMGs signature, established through machine learning, holds potential as a valuable biomarker for predicting the survival of MM patients and their response to anti-PD-1 therapy.

Palmitic Acid Induced a Dedifferentiation Profile at the Transcriptome Level: A Collagen Synthesis but no Triglyceride Accumulation in Hepatocyte-Like Cells Derived From Human-Induced Pluripotent Stem Cells Cultivated Inside Organ on a Chip.

Nonalcoholic fatty liver disease (NAFLD) is one of the main causes of critical liver diseases leading to steatosis, steatohepatitis, fibrosis, and ultimately to liver cirrhosis and hepatic carcinoma. In this study, the effect of palmitic acid (PA), one of the most abundant dietary fatty acids, was investigated using an organ-on-a-chip (OoC) technology on hepatocyte-like cells derived from human-induced pluripotent stem cells (hiPSCs). After 1 week of hepatic maturation, followed by 1 week of exposure, the transcriptomic analysis showed lower liver transcription factor activity. It also revealed that 318 genes were differentially expressed between the control and 0.5-mM PA conditions. The 0.5-mM PA conditions were characterized by the downregulation of hepatic markers (liver transcription factors, phase I and phase II metabolism genes) of lipidic genes (metabolism and transport). In parallel, the 0.5-mM PA treatment upregulated several extracellular matrix genes (such as collagen genes). The physiopathological staining demonstrated no lipid accumulation in our model and confirmed the secretion of collagen in the 0.5-mM PA conditions. However, the production of albumin, the metabolic biotransformation by the cytochrome P450 enzymes, and the biliary acid concentrations were not altered by the PA treatments. Overall, our data illustrated the response to PA characterized by an early stage of dedifferentiation observed at the transcriptomic levels associated with a modification of the collagenic profile but without lipid accumulation. We believe that our model provides new insight of the onset of palmitic lipotoxicity in the early stage of NAFLD.

Overview on Current Selectable Marker Systems and Novel Marker Free Approaches in Fruit Tree Genetic Engineering

Selectable marker genes are useful for recognizing which cells have integrated specific sequences in their genome after genetic transformation processes. They are especially important for fruit trees genetic transformation to individuate putatively genetically modified events, because most of the protocols used to genetic engineer these species are often unsuccessful or with low efficiency. Traditional selectable marker genes, mainly of bacterial origin, confer antibiotics/herbicides-resistance or metabolic advantages to transformed cells. Genes that allow the visual recognition of engineered tissues without using any selective agent, such as morphogenic regulators and reporter genes, are also used as selection tools to in vitro identify genetically modified regenerated lines. As final step, genetic engineered plants should be tested in field conditions, where selectable marker genes are no longer necessary, and strongly unpopular especially for the commercial development of the new products. Thus, different approaches, mainly based on the use of site-specific recombinases and/or editing nucleases, are being now used to recover marker-free fruit crops. This review describes and comments the most used and suitable selection tools of interest, particularly for fruit tree genetic engineering. Lastly, a spotlight highlights the biosafety aspects related to the use of selectable marker genes exploited for fruit species genetic engineering.

A visible seedling-stage screening system for the Brassica napus hybrid breeding by a novel hypocotyl length-regulated gene BnHL.

Rapeseed (Brassica napus) is a globally significant oilseed crop with strong heterosis performance. Recessive genic male sterility (RGMS) is one of the key approaches for utilizing heterosis in B. napus. However, this method faces the inherent challenge of being time-consuming and labour-intensive for removing fertile plants during seed production. Here, we report a hypocotyl length-regulated gene, BnHL, which is closely linked to a known fertility gene, BnMs2, serving as a seedling morphology marker. This marker could be used to identify fertile plants in the breeding of RGMS lines based on hypocotyl traits. By targeting the BnHL gene, both homozygous and heterozygous edited mutants exhibited significantly longer hypocotyls than the wild type (WT). Furthermore, germination experiments revealed that 7 days after seed germination, the difference in hypocotyl length between the mutant and the WT seedlings reached its maximum, effectively distinguishing fertile plants under both white (W) and red/far-red (R/FR) light. Mutations in BnHL did not result in significant changes in main agronomic traits. Thus, this study provides a comprehensive strategy for screening and identifying a new morphological marker gene for early screening in RGMS hybrid breeding with completely non-transgene during the whole production.

Utilizing the apical-out enteroids in vitro model to investigate intestinal glucose transport, barrier function, oxidative stress, and inflammatory responses in broiler chickens

IntroductionConventional 2D intestinal epithelial cell lines have been widely used in investigating intestinal functions, yet with limitations in recapitulating the in vivo gut physiology of chickens. A recently established chicken enteroid model with apical-out nature and the presence of leukocyte components represents intestinal mucosal functions. The objectives of this study were to 1) evaluate basic gut nutrient transport and barrier functions in this model and 2) identify the model’s effectiveness in studying inflammation and oxidative stress responses.MethodsEnteroids were generated from individual villus units isolated from the small intestine of Cobb500 broiler embryos. Enteroid viability, morphology, and epithelial cell markers were monitored; barrier function was evaluated based on the permeability to fluorescein isothiocyanate–dextran (FD4) with or without EDTA and lipopolysaccharide (LPS) challenges; nutrient transport was evaluated by fluorescence-labeled glucose (2NBD-G) with or without transporter blockade; the oxidative status was indicated by reactive oxygen species (ROS). Inflammatory and oxidative challenges were induced by LPS and menadione treatment, respectively. Selected marker gene expressions, including tight junction proteins (CLDN-1, CLDN-2, ZO-1, and OCCL), epithelial cell markers (Lgr-5, LYZ, and MUC-2), cytokines (IL-1β, IL-6, IL-8, IL-10, TNF-α, and INF-γ), and antioxidant enzymes (Nrf-2, catalase, and SOD), were determined by using RT-qPCR. Data were analyzed by one-way ANOVA among treatment groups.ResultsEnteroid cell activity was stable from day (d) 2 to d 6 and declined at d 7. Epithelial cell marker and cytokine expressions were stable from d 4 to d 6. FD4 permeability was increased after the EDTA treatment (P ≤ 0.05). Transporter-mediated 2NBD-G absorption was observed, which was reduced with glucose transporter blockade (P ≤ 0.05). Enteroids showed classic responses to LPS challenges, including upregulated gene expressions of IL-1β and IL-6, downregulated gene expressions of ZO-1 and OCCL, and increased FD4 permeability (P ≤ 0.05). Enteroids showed increased ROS generation (P ≤ 0.05) in response to oxidative stress.DiscussionIn conclusion, this apical-out enteroid model is a stable alternative in vitro model that exhibits intestinal barrier, nutrient transport, oxidation, and inflammation functions. With this enteroid model, we developed two challenge protocols for evaluating intestinal functions under oxidative stress and inflammation conditions.

KIF1A promotes neuroendocrine differentiation in prostate cancer by regulating the OGT-mediated O-GlcNAcylation.

Neuroendocrine prostate cancer (NEPC) arises from prostate adenocarcinoma after endocrine treatment failure and implies lethality and limited therapeutic options. Deciphering the molecular mechanisms underlying transdifferentiation from adenocarcinoma to NEPC may provide valuable therapeutic strategies. We performed a pan-cancer differential mRNA abundance analysis and identified that Kinesin-like protein (KIF1A) was highly expressed in NEPC. KIF1A knockdown impaired neuroendocrine(NE) features, including NE marker gene expression, stemness, and epithelial-mesenchymal transition (EMT), whereas KIF1A overexpression promoted these processes. Targeting KIF1A inhibited the growth of NE differentiated prostate cancer (PCa) cells in vitro and in vivo. Mechanistically, KIF1A bound with O-linked N-acetylglucosamine transferase (OGT) and regulated its protein expression and activity. Nuclear accumulation of OGT induced by KIF1A overexpression promoted intranuclear O-GlcNAcylation of β-catenin and OCT4 in nucleus. More importantly, our data revealed that OGT was critical for KIF1A induced NE differentiation and aggressive tumor growth. An OGT inhibitor, OSMI-1, can significantly inhibited NE differentiated PCa cell proliferation in vitro and tumor growth in vivo. Our findings showed that KIF1A promotes NE differentiation to NEPC by regulating the OGT-mediated O-GlcNAcylation. Targeting O-GlcNAcylation may impede the development of NEPC for a group of PCa patients with elevated KIF1A expression.

BreCML: identifying breast cancer cell state in scRNA-seq via machine learning

Breast cancer is a prevalent malignancy and one of the leading causes of cancer-related mortality among women worldwide. This disease typically manifests through the abnormal proliferation and dissemination of malignant cells within breast tissue. Current diagnostic and therapeutic strategies face significant challenges in accurately identifying and localizing specific subtypes of breast cancer. In this study, we developed a novel machine learning-based predictor, BreCML, designed to accurately classify subpopulations of breast cancer cells and their associated marker genes. BreCML exhibits outstanding predictive performance, achieving an accuracy of 98.92% on the training dataset. Utilizing the XGBoost algorithm, BreCML demonstrates superior accuracy (98.67%), precision (99.15%), recall (99.49%), and F1-score (99.79%) on the test dataset. Through the application of machine learning and feature selection techniques, BreCML successfully identified new key genes. This predictor not only serves as a powerful tool for assessing breast cancer cellular status but also offers a rapid and efficient means to uncover potential biomarkers, providing critical insights for precision medicine and therapeutic strategies.

Xanthomonas protegens sp. nov., a novel rice seed-associated bacterium, provides in vivo protection against X. oryzae pv. oryzae, the bacterial leaf blight pathogen.

Historically, Xanthomonas species are primarily known for their pathogenicity against plants, but recently, there have been more findings of non-pathogenic xanthomonads. In the present study, we report isolates from healthy rice seeds that belong to a new species, X. protegens, a protector of the rice plants against a serious pathogenic counterpart, i.e. X. oryzae pv. oryzae upon leaf clip co-inoculation. The new member species is non-pathogenic to rice and lacks a type III secretion system. The pangenome investigation revealed a large number of unique genes, including a novel lipopolysaccharide biosynthetic gene cluster, that might be important in its adaptation. The phylo-taxonogenomic analysis revealed that X. protegens is a taxonomic outlier species of X. sontii, a core, vertically transmitted rice seed endophyte with numerous probiotic properties. Interestingly, X. sontii is also reported as a keystone species of healthy rice seed microbiome. The findings and resources will help in the development of unique gene markers and evolutionary studies of X. sontii as a successful symbiont and X. oryzae as a serious pathogen. Here, we propose X. protegens sp. nov. as a novel species of the genus Xanthomonas with PPL118=MTCC 13396=CFBP 9164=ICMP 25181 as the type strain. PPL117, PPL124, PPL125 and PPL126 are other strains of the species.

Discovery of optimal cell type classification marker genes from single cell RNA sequencing data

BackgroundThe use of single cell/nucleus RNA sequencing (scRNA-seq) technologies that quantitively describe cell transcriptional phenotypes is revolutionizing our understanding of cell biology, leading to new insights in cell type identification, disease mechanisms, and drug development. The tremendous growth in scRNA-seq data has posed new challenges in efficiently characterizing data-driven cell types and identifying quantifiable marker genes for cell type classification. The use of machine learning and explainable artificial intelligence has emerged as an effective approach to study large-scale scRNA-seq data.MethodsNS-Forest is a random forest machine learning-based algorithm that aims to provide a scalable data-driven solution to identify minimum combinations of necessary and sufficient marker genes that capture cell type identity with maximum classification accuracy. Here, we describe the latest version, NS-Forest version 4.0 and its companion Python package (https://github.com/JCVenterInstitute/NSForest), with several enhancements to select marker gene combinations that exhibit highly selective expression patterns among closely related cell types and more efficiently perform marker gene selection for large-scale scRNA-seq data atlases with millions of cells.ResultsBy modularizing the final decision tree step, NS-Forest v4.0 can be used to compare the performance of user-defined marker genes with the NS-Forest computationally-derived marker genes based on the decision tree classifiers. To quantify how well the identified markers exhibit the desired pattern of being exclusively expressed at high levels within their target cell types, we introduce the On-Target Fraction metric that ranges from 0 to 1, with a metric of 1 assigned to markers that are only expressed within their target cell types and not in cells of any other cell types. NS-Forest v4.0 outperforms previous versions in simulation studies and on its ability to identify markers with higher On-Target Fraction values for closely related cell types in real data, and outperforms other marker gene selection approaches for cell type classification with significantly higher F-beta scores when applied to datasets from three human organs—brain, kidney, and lung.DiscussionFinally, we discuss potential use cases of the NS-Forest marker genes, including for designing spatial transcriptomics gene panels and semantic representation of cell types in biomedical ontologies, for the broad user community.

Effect of NR1D1 on the proliferation and differentiation of yak skeletal muscle satellite cells

The severe conditions at high altitudes, where yaks inhabit, contribute to delayed muscular growth and compromised tenderness of their muscle tissue. Myosatellite cells are responsible for the growth and regeneration of skeletal muscle after birth and have the potential to proliferate and differentiate, its development is closely related to meat quality, and the nuclear receptor gene NR1D1 is involved in muscle formation and skeletal muscle regulation. Therefore, in order to understand the effect of NR1D1 on muscle satellite cells, we identified the mRNA expression levels of marker genes specifically expressed in muscle satellite cells at different stages to determine the type of cells isolated. Eventually, we successfully constructed a primary cell line of yak muscle satellite cells. Then we constructed NR1D1 overexpression vector and interference RNA, and introduced them into isolated yak skeletal muscle satellite cells. We performed qPCR, CCK8, and fluorescence-specific to detect the expression of genes or abundance of proteins as markers of cell proliferation and differentiation. Compared with those in the control group, the expression levels of proliferation marker genes KI-67, CYCLIND1, and CYCLINA were significantly inhibited after NR1D1 overexpression, which was also supported by the CCK-8 test, whereas differentiation marker genes MYOD, MYOG, and MYF5 were significantly inhibited. Fluorescence-specific staining showed that KI-67 protein abundance and the number of microfilaments both decreased, while the opposite trend was observed after NR1D1 interference. In conclusion, we confirmed that NR1D1 inhibited the proliferation and differentiation of yak skeletal muscle satellite cells, which provides a theoretical basis for further research on the effect of NR1D1 on improving meat quality traits and meat production performance of yaks.

Alterations in the transcriptome and microRNAs of adipose-derived mesenchymal stem cells from different sites in rats during aging.

Aging is an intricate and gradual process characterized by tissue and cellular dysfunction. Adipose-derived mesenchymal stem cells (ADMSCs) experience a functional decline as part of systemic aging. However, the alterations in ADMSCs across various anatomical sites throughout an individual's lifespan remain unclear. To shed light on these changes, we collected white adipose tissue and brown adipose tissue samples from the epididymis, perirenal, inguinal, and scapular regions of young, adult, and aged rats and subsequently isolated ADMSCs for RNA sequencing. As aging progressed, we observed a reduction in the number of ADMSCs at all anatomical sites. Marker genes of ADMSCs from different sites were identified. Aging triggered notable activation of inflammatory and immune responses while diminishing the ADMSC differentiation capacity and ability to maintain normal tissue morphology. Furthermore, miR-195-5p and miR-497-3p, which promoted cell senescence and apoptosis while inhibiting proliferation and differentiation, were positively correlated with aging. These findings increase our understanding of ADMSC senescence and underscore the unique physiological changes and functions of ADMSCs across different anatomical sites during aging.

The study of Alzheimer's disease risk diagnosis based on natural killer cell marker genes in the multi-omics data.

Alzheimer's disease (AD) is a common neurodegenerative disorder, currently lacking effective early diagnostic methods. However, natural killer (NK) cells may play a potential role in AD pathogenesis. This study aims to identify AD-related feature genes from NK cell markers to construct a diagnostic model and explore their potential biological mechanisms in AD. Single-cell RNA sequencing data was used to identify NK cell markers. A novel feature selection algorithm, adaptive dynamic graph convolutional network (ADGCN), was proposed to extract AD-related feature genes and construct a diagnostic model. Differential, correlation and enrichment analyses were performed to understand the biological mechanisms of these genes. Immune infiltration analysis compared the immune microenvironment between AD and controls. Two regulatory networks explored interactions between feature genes, transcription factors and microRNAs. The association between SNPs and feature genes' expression was examined through expression quantitative trait loci analysis. Differential CpG sites were identified to analyze their association with the NK cell markers' expression. We developed an optimal diagnostic model (ADGCN-XGBoost) with 17 feature genes, demonstrating high diagnostic effectiveness across datasets. These genes were primarily related to macromolecule biosynthesis, cytoplasmic translation biological processes and ribosome pathway, and potentially modulated immune infiltration of AD patients. We predicted 27 target miRNAs and 21 transcription factors influencing these genes. Multimodal analysis identified 57 significant SNP-gene associations and seven CpG-gene pairs. This study proposed a novel feature selection algorithm and developed a diagnostic model based on 17 feature genes, providing new potential biomarkers for AD diagnosis.

Does Fusobacterium in Colorectal Cancer Sites Originate From the Oral Cavity? A Pilot Study.

Fusobacterium can contribute to oral diseases, but also pose as a systemic risk factor. This genus, and especially F. nucleatum, can be found in colorectal cancer (CRC) tissue and is involved in multiple aspects of this type of cancer. Previous studies indicated a possible oral origin of these bacteria; however, stronger evidence is needed to reach a definitive conclusion. This pilot study aimed to establish a method to successfully compare, at the strain level, fusobacteria from the oral cavity and CRC resection material for future cohort studies of CRC patients. In a first cohort of eight periodontitis patients, gingival crevicular fluid and saliva were collected. Fusobacterium was isolated on two different media. In a second cohort, saliva and CRC resection material were collected from ten CRC patients. These samples were used for screening of Fusobacterium with culturing, 16S rRNA gene profiling and a PCR-based approach. In the first cohort, different Fusobacterium species were identified in GCF and saliva samples. However, as the total yield of Fusobacterium seemed slightly higher in saliva samples, it was therefore preferred for subsequent sample collection. Thus, in the second cohort, patient-matched saliva and CRC resection material were screened for Fusobacterium and this showed that nine patients were culture-positive in the saliva samples; however, no Fusobacterium could be isolated from the resection material. On the other hand, 16S rRNA gene profiling of the resection material indicated that eight CRC patients were positive for Fusobacterium. All eight of these patients carried Fusobacterium in their saliva, indicated by both marker gene PCR and culture-based screening. These pilot results are compatible with data from previous studies, indicating a possible link between oral and CRC-associated Fusobacterium, and a more in-depth analysis of specific strains and their characteristics in a larger cohort is justified. The protocol was registered at clinicaltrials.gov (NCT05945082).

Integrated Genetic and Statolith Shape Analysis Reveals the Population Structure of Loliolus (Nipponololigo) uyii (Cephalopoda: Loliginidae) in the Coastal Waters of China

Understanding population structure is a priority for evaluating population dynamics of commercially fished cephalopods under fishing pressure and environmental changes. This study employed a multidisciplinary approach to clarify the population structure of Loliolus (Nipponololigo) uyii, a common squid in inshore fisheries. Sampling was conducted multiple times to cover the distribution range across the East China Sea and South China Sea. High haplotype diversity was revealed by three gene markers (COI, 16S and ODH). Two geographical clades with significant genetic differentiation were divided through phylogenetic trees and haplotype networks. The boundary between the two clades is delineated by the Dongshan population in the southern East China Sea. Furthermore, the neutrality tests and mismatch analysis suggested that L. (N.) uyii populations may have undergone population expansion. Correspondingly, statolith differences in lateral dome and posterior indentation, along with high classification success, further supported the genetic division. The overall difference in statolith shape also efficiently identified seasonal groups in the Beibu Gulf lacking genetic differentiation. This result offers new insights into the influence of genetic and environmental factors on statolith shape. The integrated results provide a comprehensive understanding of the population structure of L. (N.) uyii, laying the foundation for resource development and the conservation of the species.

ГЕНЕТИЧЕСКИЙ СКРИНИНГ ПЕРСПЕКТИВНЫХ ГИБРИДОВ КАРТОФЕЛЯ РЕСПУБЛИКИ КОМИ

The studies were conducted with the aim of genetic screening of promising selection hybrids of potatoes to identify genotypes resistant to a complex of phytopathogens. The study was carried out at A.V.Zhuravskiy Institute of Agrobiotechnology of Komi Scientific Center of the Ural Branch of the Russian Academy of Sciences and Sintol company (Moscow) using the GenExpert reagent kit “Markers of potato resistance genes” (“Syntol”). For the study, 10 markers of genes encoding resistance to potato cancer, golden potato cyst nematode, pale potato cyst nematode, X-virus and Y-virus were selected (genes H1, Gro1-4 were detected using markers TG-689, 57R, N195 and Gro1-4-1, gene Sen1 – using marker NL25, gene Gpa2 – Gpa2-2). The objects of the study were leaves of plants of five potato hybrids undergoing selection testing in breeding nurseries: 2341-265 (Amur × Gala), 2339-8 (Oksania × Gala), 2339-9 (Oksania × Gala), 1992-14 (Udacha × Elmundo), 2000-60 (Colette × FZ 1867). The maximum number of markers (five in each) linked to resistance genes was revealed in samples 2339-8 and 1992-14: TG-689, 57R, N195 and NL25 in both hybrids; Gro1-4-1 marker in 2339-8 and Gpa2-2 in 1992-14. Only the marker of potato wart resistance gene, NL25, was noted in selection number 2341-265. Sample 2339-8 was characterized as a valuable source of R-genes, having in its genome the genes of resistance to golden potato cyst nematode (H1, Gro1-4) and potato wart (Sen1). The genotype of the 1992-14 hybrid, carrying the Gpa2 gene, is recommended for breeding new potato varieties resistant to various types of nematodes.

BMSCs-derived exosomes carrying miR-668-3p promote progression of osteoblasts in osteonecrosis of the femoral head: Expression of proteins CD63 and CD9

Recently, exosomes that are derived from bone marrow mesenchymal stem cells (BMSCs) have garnered considerable interest due to their significant roles in the processes of bone regeneration and repair. Among the various molecular components present within these exosomes, miR-668-3p has emerged as a pivotal microRNA that may be instrumental in modulating the function and proliferation of osteoblasts, the cells responsible for bone formation. The primary objective of this research was to examine the enhancing effects of BMSC-derived exosomes that are enriched with miR-668-3p on the advancement of osteoblasts in the context of osteonecrosis of the femoral head. Furthermore, the study aimed to analyze how the expression of specific exosomal proteins, namely CD63 and CD9, influences this biological process. To conduct the investigation, BMSCs were isolated from healthy rat models, followed by the extraction of their secreted exosomes. The subsequent phase of the study involved assessing the proliferation and differentiation of osteoblasts by introducing the exosomes enriched with miR-668-3p into an experimental setup representing osteonecrosis of the femoral head. The findings revealed that exosomes derived from BMSCs, which contained miR-668-3p, significantly enhanced the proliferation of osteoblasts as well as the expression of key osteogenic marker genes. Notably, the levels of CD63 and CD9 proteins were markedly increased in the treated groups, indicating that the mechanisms underlying this promotion might involve cell adhesion and the endocytic uptake of exosomes.

Development of a TBXT-EGFP iPS Cell Model for Screening the Early Developmental Toxicity of Typical Environmental Pollutants

In our daily lives, we are inevitably exposed to a variety of environmental pollutants in numerous ways. Fortunately, recent years have witnessed significant advancements in the field of stem cell toxicology, which have provided new opportunities for research in environmental toxicology. Applying stem cell technology to environmental toxicology, overcomes some of the limitations of traditional screening methods and we can more accurately predict the toxicity of environmental pollutants. However, there are still several aspects of stem cell toxicology models that require improvement, such as increasing the throughput of detection and simplifying detection methods. Consequently, we developed an environmental pollutant toxicity detection model based on TBXT-EGFP iPS cells and screened the developmental toxicity of 38 typical environmental pollutants. Our results indicate that TBBPA-BDBPE, TBBPA-BHEE, DG, and AO2246 may interfere with the expression of TBXT, a critical marker gene for early human embryo development, implying that these environmental pollutants could lead to developmental abnormalities.

Methyl jasmonate mitigates Fusarium graminearum infection in wheat by inhibiting deoxynivalenol synthesis.

Methyl jasmonate (MeJA), a plant growth regulator, coordinates a diverse array of physiological responses, including the inhibition of seed germination, modulation of secondary metabolite biosynthesis, and activation of defence responses. The external application of MeJA has been demonstrated to effectively diminish the severity of fungal diseases. Here, we unveil a novel mechanism through which exogenous MeJA alleviates Fusarium head blight (FHB) by inhibiting the synthesis of deoxynivalenol (DON) in Fusarium graminearum, rather than by enhancing the wheat resistance response. MeJA treatment reduced the infection by wild-type F. graminearum in wheat coleoptiles, but exhibited no significant influence on that of the DON-deficient mutant strain (∆Tri5). The production of DON in F. graminearum was significantly inhibited both in vitro and in planta. MeJA affected the expression of genes related to DON biosynthesis, without influencing the formation of toxisomes as observed under microscopic analysis. Exogenous MeJA demonstrated a limited impact on the early genes of plant jasmonic acid signalling pathway, in contrast to the wild-type pathogen strain, which induced the upregulation of these genes. The expression levels of defence marker genes induced by MeJA were notably lower compared to those induced by the pathogen. This study elucidates the molecular mechanisms of MeJA in modulating the wheat-F. graminearum interaction, providing new insights into the development of environmentally friendly strategies against fungi.

Decoding marker genes and immune landscape of unstable carotid plaques from cellular senescence

Recently, cellular senescence-induced unstable carotid plaques have gained increasing attention. In this study, we utilized bioinformatics and machine learning methods to investigate the correlation between cellular senescence and the pathological mechanisms of unstable carotid plaques. Our aim was to elucidate the causes of unstable carotid plaque progression and identify new therapeutic strategies. First, differential expression analysis was performed on the test set GSE43292 to identify differentially expressed genes (DEGs) between the unstable plaque group and the control group. These DEGs were intersected with cellular senescence-associated genes to obtain 40 cellular senescence-associated DEGs. Subsequently, key genes were then identified through weighted gene co-expression network analysis, random forest, Recursive Feature Elimination for Support Vector Machines algorithm and cytoHubba plugin. The intersection yielded 3 CSA-signature genes, which were validated in the external validation set GSE163154. Additionally, we assessed the relationship between these CSA-signature genes and the immune landscape of the unstable plaque group. This study suggests that cellular senescence may play an important role in the progression mechanism of unstable plaques and is closely related to the influence of the immune microenvironment. Our research lays the foundation for studying the progression mechanism of unstable carotid plaques and provides some reference for targeted therapy.

Identify novel therapeutic targets for type II diabetes and periodontitis: insights from single-cell analysis and Mendelian randomization analysis

BackgroundPeriodontitis is a common complication of type II diabetes (T2D). However, the existing research cannot fully elucidate the association between them, let alone identify therapeutic targets for precise treatment of diabetic periodontitis. Therefore, we employed integrated genetic approaches such as single-cell analysis, Mendelian randomization (MR) analysis and colocalization analysis to uncover novel therapeutic targets for T2D and periodontitis.MethodsThis study integrated single-cell analysis, MR analysis, colocalization analysis, phenotype scanning, cell-cell communication analysis and metabolic pathway activity analysis to unveil novel therapeutic targets for periodontitis and T2D. We firstly identified core cell clusters of T2D and periodontitis, and important marker genes were selected. The causal associations between these genes and the two diseases were evaluated through MR analysis. Reverse MR analysis, colocalization analysis, additional validation and phenotype scanning further supported our findings. Finally, cell-cell communication analysis and metabolic pathway activity analysis were employed to preliminarily investigate the mechanisms of the observed causal associations.ResultsThrough analysis of scRNA-seq data, we identified classical monocytes and intermediate monocytes as core cell subclusters. Differential analysis identified 221 differentially expressed genes (DEGs). MR analysis identified 13 genes exhibiting causal associations with T2D, and 11 causal genes with periodontitis. Colocalization analysis, reverse MR analysis, additional validation and phenotype scanning further enhanced the robustness of our results. Finally, we identified NCF1 as the core therapeutic target for T2D (OR = 1.09, 95% CI: 1.03-1.14, p = 1.85 ×10−3) and LRRC25 for T2D (OR = 0.96, 95% CI: 0.93-0.99, p = 3.44 ×10−2) and periodontitis (OR = 0.92, 95% CI: 0.84-0.99, p = 4.45 ×10−2). At last, cell-cell communication analysis indicated significant differences in functions and metabolic pathway activity between monocytes expressing or not expressing the core causal genes, which preliminarily interpreted the observed causal associations.ConclusionThis study integrated single-cell analysis, MR analysis and colocalization analysis to identified novel therapeutic targets for T2D and periodontitis. 13 causal genes were identified for T2D, and 11 for periodontitis. Among them, NCF1 and LRRC25 were regarded as core therapeutic targets. Our findings bridge the gap in the understanding of the association between T2D and periodontitis, and pave the way for targeted therapy of the two diseases.