Trends In Gene Expression Research Articles

Blue Light Simultaneously Induces Peel Anthocyanin Biosynthesis and Flesh Carotenoid/Sucrose Biosynthesis in Mango Fruit.

Previous studies focused on the effects of light on fruit appearance, especially the peel color. However, the effect of light on fruit internal quality and the underlying mechanisms are unclear. In this study, we analyzed the effects of blue light on the appearance and internal quality of mango fruit (Mangifera indica L.). Blue light simultaneously induced peel anthocyanin and flesh sucrose/carotenoid biosynthesis in mango fruit. Analyses of co-expression networks and gene expression trends in mango fruit peel and flesh identified candidate genes, including transcription factor genes, involved in blue light-regulated anthocyanin, carotenoid, and sucrose biosynthesis pathways. Key blue light signaling-related genes (MiCRY and MiHY5) and blue light-triggered phytohormones were involved in these pathways. Additionally, there were common and tissue-specific pathways for the blue light-promoted accumulation of anthocyanins, carotenoids, and sucrose. Our results provide new insights into the regulatory effects of light on the appearance and internal quality of mango fruit.

Cross-Talk between Transcriptome Analysis and Dynamic Changes of Carbohydrates Identifies Stage-Specific Genes during the Flower Bud Differentiation Process of Chinese Cherry (Prunus pseudocerasus L.)

Flower bud differentiation is crucial to reproductive success in plants. In the present study, RNA-Seq and nutrients quantification were used to identify the stage-specific genes for flower bud differentiation with buds which characterize the marked change during flower bud formation from a widely grown Chinese cherry (Prunus pseudocerasus L.) cultivar 'Manaohong'. A KEGG enrichment analysis revealed that the sugar metabolism pathways dynamically changed. The gradually decreasing trend in the contents of total sugar, soluble sugar and protein implies that the differentiation was an energy-consuming process. Changes in the contents of D-glucose and sorbitol were conformed with the gene expression trends of bglX and SORD, respectively, which at least partially reflects a key role of the two substances in the transition from physiological to morphological differentiation. Further, the WRKY and SBP families were also significantly differentially expressed during the vegetative-to-reproductive transition. In addition, floral meristem identity genes, e.g., AP1, AP3, PI, AGL6, SEP1, LFY, and UFO demonstrate involvement in the specification of the petal and stamen primordia, and FPF1 might promote the onset of morphological differentiation. Conclusively, the available evidence justifies the involvement of sugar metabolism in the flower bud differentiation of Chinese cherry, and the uncovered candidate genes are beneficial to further elucidate flower bud differentiation in cherries.

Transcriptome analysis provides insights into lignin synthesis and MAPK signaling pathway that strengthen the resistance of bitter gourd (Momordica charantia) to Fusarium wilt

Fusarium wilt is a typical soil-borne disease caused by Fusarium oxysporum f. sp. momordicae (FOM) in bitter gourd. In this study, by comparing sequencing data at multiple time points and considering the difference between resistant (R) and susceptible (S) varieties, differentially expressed genes were screened out. Short time-series expression miner analysis revealed the upregulated expression trend of genes, which were enriched in phenylpropanoid biosynthesis, plant–pathogen interaction, and mitogen-activated protein kinase signaling pathway. Further, observation of the microstructure revealed that the R variety may form tyloses earlier than the S variety to prevent mycelium diffusion from the xylem vessel. After Fusarium wilt infection, the enzymatic activities of superoxide dismutase, peroxidase, phenylalanine ammonia lyase, and catalaseas well as levels of superoxide anion and malondialdehyde were increased in the R variety higher than those in the S variety. This study provides a reference to elucidate the disease resistance mechanism of bitter gourd.

Transcriptomic profiling implicates PAF1 in both active and repressive immune regulatory networks

BackgroundSitting at the interface of gene expression and host-pathogen interaction, polymerase associated factor 1 complex (PAF1C) is a rising player in the innate immune response. The complex localizes to the nucleus and associates with chromatin to modulate RNA polymerase II (RNAPII) elongation of gene transcripts. Performing this function at both proximal and distal regulatory elements, PAF1C interacts with many host factors across such sites, along with several microbial proteins during infection. Therefore, translating the ubiquity of PAF1C into specific impacts on immune gene expression remains especially relevant.ResultsAdvancing past work, we treat PAF1 knockout cells with a slate of immune stimuli to identify key trends in PAF1-dependent gene expression with broad analytical depth. From our transcriptomic data, we confirm PAF1 is an activator of traditional immune response pathways as well as other cellular pathways correlated with pathogen defense. With this model, we employ computational approaches to refine how PAF1 may contribute to both gene activation and suppression. Specifically focusing on transcriptional motifs and regulons, we predict gene regulatory elements strongly associated with PAF1, including those implicated in an immune response. Overall, our results suggest PAF1 is involved in innate immunity at several distinct axes of regulation.ConclusionsBy identifying PAF1-dependent gene expression across several pathogenic contexts, we confirm PAF1C to be a key mediator of innate immunity. Combining these transcriptomic profiles with potential regulatory networks corroborates the previously identified functions of PAF1C. With this, we foster new avenues for its study as a regulator of innate immunity, and our results will serve as a basis for targeted study of PAF1C in future validation studies.

Transcriptomic and metabolomic analyses reveal the antifungal mechanism of the compound phenazine-1-carboxamide on Rhizoctonia solani AG1IA.

To explore the molecular mechanisms of the antifungal compound phenazine-1-carboxamide (PCN) inhibits Rhizoctonia solani and discover potential targets of action, we performed an integrated analysis of transcriptome and metabolome in R. solani mycelium by whether PCN treating or not. A total of 511 differentially expressed genes (DEGs) were identified between the PCN treatment and control groups. The fluorescence-based quantitative PCR (qPCR) got the accordant results of the gene expression trends for ten randomly selected DEGs. The Gene Ontology (GO) enrichment analysis revealed that fatty acid metabolic process, fatty acid oxidation, and lipid oxidation were among the most enriched in the biological process category, while integral component of membrane, plasma membrane, and extracellular region were among the most enriched in the cellular component category and oxidoreductase activity, cofactor binding, and coenzyme binding were among the most enriched in the molecular function category. KEGG enrichment analysis revealed the most prominently enriched metabolic pathways included ATP-binding cassette (ABC) transporters, nitrogen metabolism, aminobenzoate degradation. The DEGs related functions of cellular structures, cell membrane functions, cellular nutrition, vacuole-mitochondrion membrane contact site and ATPase activity, pH, anti-oxidation, were downregulated. A total of 466 differential metabolites were found between the PCN treatment and control groups after PCN treatment. KEGG enrichment found purine, arachidonic acid, and phenylpropanoid biosynthesis pathways were mainly affected. Further results proved PCN decreased the mycelial biomass and protein content of R. solani, and superoxide dismutase (SOD) activity reduced while peroxidase (POD) and cytochrome P450 activities increased. The molecule docking indicted that NADPH nitrite reductase, ATP-binding cassette transporter, alpha/beta hydrolase family domain-containing protein, and NADPH-cytochrome P450 reductase maybe the particular target of PCN. In conclusion, the mechanisms via which PCN inhibits R. solani AG1IA may be related to cell wall damage, cell membrane impairment, intracellular nutrient imbalance, disturbed antioxidant system, and altered intracellular pH, which laid foundation for the further new compound designing to improve antifungal efficacy.

Strive or thrive: Trends in Phytophthora capsici gene expression in partially resistant pepper.

Partial resistance in plants generally exerts a low selective pressure on pathogens, and thus ensuring their durability in agrosystems. However, little is known about the effect of partial resistance on the molecular mechanisms of pathogenicity, a knowledge that could advance plant breeding for sustainable plant health. Here we investigate the gene expression of Phytophthora capsici during infection of pepper (Capsicum annuum L.), where only partial genetic resistance is reported, using Illumina RNA-seq. Comparison of transcriptomes of P. capsici infecting susceptible and partially resistant peppers identified a small number of genes that redirected its own resources into lipid biosynthesis to subsist on partially resistant plants. The adapted and non-adapted isolates of P. capsici differed in expression of genes involved in nucleic acid synthesis and transporters. Transient ectopic expression of the RxLR effector genes CUST_2407 and CUST_16519 in pepper lines differing in resistance levels revealed specific host-isolate interactions that either triggered local necrotic lesions (hypersensitive response or HR) or elicited leave abscission (extreme resistance or ER), preventing the spread of the pathogen to healthy tissue. Although these effectors did not unequivocally explain the quantitative host resistance, our findings highlight the importance of plant genes limiting nutrient resources to select pepper cultivars with sustainable resistance to P. capsici.

Understanding the Genome-Wide Transcription Response To Various cAMP Levels in Bacteria Using Phenomenological Models.

Attempts to understand gene regulation by global transcription factors have largely been limited to expression studies under binary conditions of presence and absence of the transcription factor. Studies addressing genome-wide transcriptional responses to changing transcription factor concentration at high resolution are lacking. Here, we create a data set containing the entire Escherichia coli transcriptome in Luria-Bertani (LB) broth as it responds to 10 different cAMP concentrations spanning the biological range. We use the Hill's model to accurately summarize individual gene responses into three intuitively understandable parameters, Emax, n, and k, reflecting the sensitivity, nonlinearity, and midpoint of the dynamic range. Our data show that most cAMP-regulated genes have an n of >2, with their k values centered around the wild-type concentration of cAMP. Additionally, cAMP receptor protein (CRP) affinity to a promoter is correlated with Emax but not k, hinting that a high-affinity CRP promoter need not ensure transcriptional activation at lower cAMP concentrations and instead affects the magnitude of the response. Finally, genes belonging to different functional classes are tuned to have different k, n, and Emax values. We demonstrate that phenomenological models are a better alternative for studying gene expression trends than classical clustering methods, with the phenomenological constants providing greater insights into how genes are tuned in a regulatory network. IMPORTANCE Different genes may follow different trends in response to various transcription factor concentrations. In this study, we ask two questions: (i) what are the trends that different genes follow in response to changing transcription factor concentrations and (ii) what methods can be used to extract information from the gene trends so obtained. We demonstrate a method to analyze transcription factor concentration-dependent genome-wide expression data using phenomenological models. Conventional clustering methods and principal-component analysis (PCA) can be used to summarize trends in data but have limited interpretability. The use of phenomenological models greatly enhances the interpretability and thus utility of conventional clustering. Transformation of dose-response data into phenomenological constants opens up avenues to ask and answer many different kinds of question. We show that the phenomenological constants obtained from the model fits can be used to generate insights about network topology and allows integration of other experimental data such as chromatin immunoprecipitation sequencing (ChIP-seq) to understand the system in greater detail.

Molecular Traits Underlying the Growth Promotion and Metabolite Accumulation in Rheum palmatum Inoculated with Endophytic Trichoderma citrinoviride HT-1

Trichoderma spp. are an important plant-growth-promoting fungi. Trichoderma citrinoviride HT-1 was isolated from Rheum palmatum root, which has beneficial effects on growth and metabolite accumulation. However, the improvement mechanisms for growth and metabolite accumulation of T. citrinoviride HT-1 are unclear. In this study, RNA sequencing (RNA-seq) and high-performance liquid chromatography (HPLC) were used to measure the effect of different concentrations of conidial suspension of the HT-1 strain on the growth promotion and metabolite accumulation of R. palmatum seedlings. The results showed that the highest biomass and metabolites of R. palmatum seedlings were obtained through treatment with the HT-1 strain at a final spore concentration of 107 spores/mL. RNA sequencing indicated that 1662 genes were upregulated and 2155 genes were downregulated after inoculation with 107 spores/mL of the HT-1 strain. This strain induced significant upregulation of related genes in the phenylpropanoid biosynthesis pathway, plant hormone signal transduction pathway, biosynthesis of secondary metabolites pathway, and plant-pathogen interaction pathway in R. palmatum. The gene expression trends were revealed through quantitative real-time polymerase chain reaction (qRT-PCR) and were consistent with those determined by RNA-seq. Our results will help us to understand the growth-promoting mechanisms of the HT-1 strain on R. palmatum and provide a theoretical basis for the application of T. citrinoviride HT-1 as a biological fertilizer.

The Analysis of Transcriptomes and Microorganisms Reveals Differences between the Intestinal Segments of Guinea Pigs

The intestine is a tubular organ with multiple functions such as digestion absorption and immunity, but the functions of each intestinal segments are different. Intestinal regionalization is necessary for normal physiological function, but it also means the research results obtained at specific sites may not be applicable to other intestinal segments. In order to comprehensively describe the functional changes in the intestine, different intestinal segments and their contents (duodenum, jejunum, ileum, cecum, colon, and rectum) of guinea pigs were collected for RNA seq and 16S rRNA seq, respectively. The results showed differential genes of each intestinal segment mainly involve mucosa, digestion, absorption, and immunity. The gene sets related to fat, bill salts, vitamins, aggregates, amino acids, and water absorption were highly expressed in the small intestine, and the gene sets related to metal ions, nucleotides, and SCFAs were highly expressed in the large intestine. In terms of immunity, the CD8+ T, Th1, eosinophils, pDCs, and natural killer (NK) T cells in the small intestine showed higher scores than those in the large intestine, while the pattern-recognition receptor signaling pathway-related genes are highly expressed in the large intestine. In terms of microbial composition, Proteobacteria and Actinobacteria are abundant in the small intestine, while Firmicutes and Spirochaete are abundant in large intestine. The correlation analysis showed a high correlation between intestinal microorganisms and gene modules related to digestion and absorption. In addition, cross-species analysis showed the SCFA metabolism gene expression trends in human and rodent intestine were different. In conclusion, we analyzed the changes in substance transport, immune and microbial composition between different intestinal segments of guinea pigs, and explored the relationship between intestinal transcriptome and microorganisms, our research will provides a reference for subsequent intestinal-related research.

ScRNA-sequencing uncovers metabolism and CD52 as new targets in ibrutinib-surviving mantle cell lymphoma cells

Ibrutinib improves the treatment of relapsed or refractory mantle cell lymphoma, amature Bcell neoplasm. However, relapses following treatment with this Bruton tyrosine kinase inhibitor occur frequently, and the outcome of affected patients is poor. Single-cell RNA sequencing (scRNA-seq) can track trends in gene expression of mantle cell lymphoma cells across ibrutinib treatment and new therapeutic targets can be defined based on the detected resistance mechanisms. The ibrutinib-sensitive mantle cell lymphoma cell line REC‑1 was treated with ibrutinib for6 h and48 h. Droplet-based scRNA-seq was performed to examine the transcriptomic alterations of surviving cells using the 10×Genomics platform. Extracellular flux analysis and flow cytometry were applied to further study the observed adaptations to ibrutinib treatment. REC‑1 harbored asubpopulation with potential for crosstalk with microenvironment and therefore greater risk for aggressiveness and drug resistance. Following ibrutinib treatment, NF-κB signaling was turned off. In contrast, the cells upregulated B-cell receptor genes and surface antigens such as CD52, and switched their metabolism to increased dependence on oxidative phosphorylation. Targeting oxidative phosphorylation or CD52 in combination with or as follow-up to ibrutinib might overcome resistance and provide improved prognosis for mantle cell lymphoma patients.

A novel metabolism-related prognostic gene development and validation in gastric cancer.

The importance of metabolism-related alterations in the development of gastric cancer (GC) is increasingly recognized. The present study aimed to identify metabolism-related genes to facilitate prognosis of GC patients. Gene expression datasets and clinical information of GC patients were downloaded from TCGA and GEO databases. We scored the enrichment of human metabolism-related pathways (n = 86) in GC samples by GSV, constructed prognostic risk models using LASSO algorithm and multivariate Cox regression analysis, combined with clinical information to construct a nomogram, and finally cis score algorithm to analyze the abundance of immune-related cells in different subtypes. We used Weka software to screen for prognosis-related marker genes and finally validated the expression of the selected genes in clinical cancer patient tissues. We identified that two GC metabolism-related signatures were strongly associated with OS and the levels of immune cell infiltration. Moreover, a survival prediction model for GC was established based on six GC metabolism-related genes. Time-dependent ROC analysis showed good stability of the risk prediction scoring model. The model was successfully validated in an independent ACRG cohort, and the expression trends of key genes were also verified in the GC tissues of patients. DLX1, LTBP2, FGFR1 and MMP2 were highly expressed in the cluster with poorer prognosis while SLC13A2 and SLCO1B3 were highly expressed in the cluster with better prognosis. We identified a risk predictive score model based on six metabolism-related genes related to survival, which may serve as prognostic indicators and potential therapeutic targets for GC.

WGCNA Identifies a Comprehensive and Dynamic Gene Co-Expression Network That Associates with Smut Resistance in Sugarcane.

Sugarcane smut is a major fungal disease caused by Sporisorium scitamineum, which seriously reduces the yield and quality of sugarcane. In this study, 36 transcriptome data were collected from two sugarcane genotypes, YT93-159 (resistant) and ROC22 (susceptible) upon S. scitamineum infection. Data analysis revealed 20,273 (12,659 up-regulated and 7614 down-regulated) and 11,897 (7806 up-regulated and 4091 down-regulated) differentially expressed genes (DEGs) in YT93-159 and ROC22, respectively. A co-expression network was then constructed by weighted gene co-expression network analysis (WGCNA), which identified 5010 DEGs in 15 co-expressed gene modules. Four of the 15 modules, namely, Skyblue, Salmon, Darkorange, and Grey60, were significantly associated with smut resistance. The GO and KEGG enrichment analyses indicated that the DEGs involving in these four modules could be enriched in stress-related metabolic pathways, such as MAPK and hormone signal transduction, plant-pathogen interaction, amino acid metabolism, glutathione metabolism, and flavonoid, and phenylpropanoid biosynthesis. In total, 38 hub genes, including six from the Skyblue module, four from the Salmon module, 12 from the Darkorange module, and 16 from the Grey60 module, were screened as candidate hub genes by calculating gene connectivity in the corresponding network. Only 30 hub genes were amplifiable with RT-qPCR, of which 27 were up-regulated upon S. scitamineum infection. The results were consistent with the trend of gene expression in RNA-Seq, suggesting their positive roles in smut resistance. Interestingly, the expression levels of AOX, Cyb5, and LAC were higher in ROC22 than in YT93-159, indicating these three genes may act as negative regulators in response to S. scitamineum infection. This study revealed the transcriptome dynamics in sugarcane challenged by S. scitamineum infection and provided gene targets for smut resistance breeding in sugarcane.

Identification of Seven Key Structural Genes in the Anthocyanin Biosynthesis Pathway in Sepals of Hydrangea macrophylla.

Under specific cultivation conditions, the sepal color of Hydrangea macrophylla (H. macrophylla) changes from red to blue due to the complexation of aluminum ions (Al3+), delphinidin 3-glucoside, and copigments. However, this phenomenon cannot occur in all cultivars despite the presence of sufficient Al3+ and copigments. To explore the mechanism of sepal bluing in H. macrophylla, there is an urgent need to study the molecular regulation of the anthocyanin biosynthesis pathway. However, the key structural genes, other than CHS, regulating anthocyanin biosynthesis in the sepals of H. macrophylla have not been identified. In this study, based on full-length transcriptome data from H. macrophylla ‘Bailmer’, the key structural genes regulating anthocyanin biosynthesis in the sepals of H. macrophylla were isolated and investigated. Ultimately, seven key structural genes, HmCHS1, HmCHI, HmF3H1, HmF3′H1, HmF3′5′H, HmDFR2, and HmANS3, were demonstrated to show high expression levels in colored sepals. The expression levels of these seven genes increased gradually with the development of sepals and were highest in the full-bloom stage. The trend of gene expression was consistent with the trend of anthocyanin contents. It was concluded that the seven selected genes were involved in anthocyanin biosynthesis in the sepals of H. macrophylla. The full-length sequence data have been deposited into the NCBI Sequence Read Archive (SRA) with accession number PRJNA849710. This study lays a good foundation for the further elucidation of the molecular mechanism of sepal coloration in H. macrophylla.

Transcriptional regulation mechanism of flavonoids biosynthesis gene during fruit development in astragalus membranaceus

Astragalus membranaceus, as an important medicinal plant, are an excellent source of flavonoids. Flavonoid compounds in A. membranaceus have been widely used in medicine and supplement, but known of the molecular mechanism of flavonoid biosynthesis is still very few. Here, we analyzed the association between flavonoid content and gene expression pattern during six different fruit developmental stages. Sixteen gene expression trends were significantly identified, involving 8,218 genes. The gene expression trend in profile 0 was positively correlated with flavonoid content, while the gene expression trend in profile 79 was negatively correlated with flavonoid content at six developmental stages. The expression level of genes involved in the general phenylpropane pathway was higher than that of genes involved in the flavonoid biosynthesis pathway. A total of 37 genes involved in flavonoid synthesis were identified in A. membranaceus. The expression pattern of flavonoid-related genes was highly correlated with flavonoid content. Our study deepened the understanding of the flavonoid synthesis mechanism and provided useful resources for future studies on the high flavonoid molecular breeding of A. membranaceus.

Fucose as a potential therapeutic molecule against the immune-mediated inflammation in IgA nepharopathy: An unrevealed link.

BackgroundIgA nephropathy (IgAN) is an autoimmune disease that affects people of any age and is an important cause of end-stage renal disease. However, the pathogenesis and pathophysiology of IgAN is not clear. This article aimed to explore the immune-mediated inflammation and genetic mechanisms in IgAN.MethodsThe transcriptome sequencing data of IgAN glomeruli in the Gene Expression Omnibus database were downloaded. Single-sample gene set enrichment analysis was used to estimate the immune microenvironment of the merged microarray data and GSE141295. IgAN samples were divided into two clusters by cluster analysis. “limma” and “DEseq2” package in R were used to identify differentially expressed genes (DEGs). The weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression modules related to inflammation in IgAN. R software package “clusterProfiler” was used for enrichment analysis, whereas Short Time-Series Expression Miner (STEM) analysis was used to identify the trend of gene expression. Machine-learn (ML) was performed using the shiny app. Finally, Drug Signatures Database (DSigDB) was used to identify potential molecules for treating IgAN.ResultsThe infiltration of macrophages in IgAN glomeruli was increased, whereas CD4+ T cells, especially inducedregulatory T cells (iTregs) were decreased. A total of 1,104 common DEGs were identified from the merged data and GSE141295. Brown module was identified to have the highest inflammatory correlation with IgAN using WGCNA, and 15 hub genes were screened from this module. Among these 15 hub genes, 14 increased with the severity of IgAN inflammation based on STEM analysis. Neural network (nnet) is considered as the best model to predict the severity of IgAN. Fucose identified from DSigDB has a potential biological activity to treat IgAN.ConclusionThe increase of macrophages and the decrease of iTregs in glomeruli represent the immune-mediated inflammation of IgAN, and fucose may be a potential therapeutic molecule against IgAN because it affects genes involved in the severe inflammation of IgAN.

Determining the Effects of Light on the Fruit Peel Quality of Photosensitive and Nonphotosensitive Eggplant.

With the development of facility agriculture, low-light stress is a prominent problem and a popular research topic currently. In this study, transcriptome analysis was used to analyze the genes in the fruit peel of photosensitive and nonphotosensitive eggplant and to explore the mechanism of changes in fruit color, texture, hormone content, aroma, and taste of these two different types of eggplant. We identified 51, 65, 66, and 66 genes involved in synthesizing anthocyanins, texture, hormone content, and aroma and flavor, respectively, in the two different types of eggplant based on the variation in gene expression trends in the fruit peel. These results provide a basis for further analysis of the molecular mechanism underlying the regulatory processes in eggplant fruits under low-light stress.

A deep learning framework for identifying essential proteins based on multiple biological information

BackgroundEssential Proteins are demonstrated to exert vital functions on cellular processes and are indispensable for the survival and reproduction of the organism. Traditional centrality methods perform poorly on complex protein–protein interaction (PPI) networks. Machine learning approaches based on high-throughput data lack the exploitation of the temporal and spatial dimensions of biological information.ResultsWe put forward a deep learning framework to predict essential proteins by integrating features obtained from the PPI network, subcellular localization, and gene expression profiles. In our model, the node2vec method is applied to learn continuous feature representations for proteins in the PPI network, which capture the diversity of connectivity patterns in the network. The concept of depthwise separable convolution is employed on gene expression profiles to extract properties and observe the trends of gene expression over time under different experimental conditions. Subcellular localization information is mapped into a long one-dimensional vector to capture its characteristics. Additionally, we use a sampling method to mitigate the impact of imbalanced learning when training the model. With experiments carried out on the data of Saccharomyces cerevisiae, results show that our model outperforms traditional centrality methods and machine learning methods. Likewise, the comparative experiments have manifested that our process of various biological information is preferable.ConclusionsOur proposed deep learning framework effectively identifies essential proteins by integrating multiple biological data, proving a broader selection of subcellular localization information significantly improves the results of prediction and depthwise separable convolution implemented on gene expression profiles enhances the performance.

Identifying biomarkers of response to progestin therapy in conservatively managed endometrial cancer and atypical hyperplasia/endometrioid intraepithelial neoplasia (266)

<b>Objectives:</b> The incidence of endometrial cancer (EC) and its precursor lesion, atypical hyperplasia/endometrioid intraepithelial neoplasia (AH/EIN), continues to increase among young women. In women desiring fertility, identifying clinical-pathologic markers predictive of response to progestin-based therapy (PT) is essential. Loss of AT-Rich Interactive Domain 1A (<i>ARID1A</i>) activates the PI3K/ AKT/mTOR signaling pathway leading to downregulation of progesterone receptor (PR) expression, resulting in primary progesterone resistance in EC cell lines. We propose that <i>ARID1A</i> deficient tumors, which will have relatively higher phosphorylated AKT (p-AKT) and lower PR expression than <i>ARID1A</i> proficient tumors, will have a lower response rate to PT. <b>Methods:</b> Patients with histologically proven AH/EIN or well-differentiated EC who were treated with PT at an academic center were retrospectively reviewed. Demographic and clinical data were abstracted from the medical record. For each patient, all endometrial biopsy specimens were evaluated, which included the initial diagnostic and any follow-up biopsy. A tissue microarray was constructed of all biopsy specimens, and immunohistochemical stains for <i>ARID1A</i>, <i>PTEN</i>, p-AKT, PR, estrogen receptor (ER), and mismatch repair protein expression were evaluated. Complete response (CR) to treatment was defined as resolution of EC or AH/EIN. Cox Proportional Hazards models were used to estimate the relative hazard (HR) of complete response to progestin by select patient characteristics. Kaplan-Meier survival curves were also estimated for patient characteristics of interest. Trends in gene expression over the follow-up time were assessed using linear regression fitted by generalized estimating equations. Analyses were conducted in R version 4.0.2. <b>Results:</b> A total of 42 women were treated with PT (12 EC and 30 EIN). The median age was 35 years, and the median BMI was 35.9 kg/m². The response rate was 81%. There were no clinical or pathological differences between responders and non-responders. In addition, time to response was not impacted by age, BMI, histology, or investigated immunohistochemical markers. There was no correlation between PR/ER (r_S = 0.29, p=0.09), <i>ARID1A</i>/ER (r_S = -0.26, p=0.13), and <i>ARID1A</i>/PR (r_S = 0.13, p=0.45) expression. On multivariable analysis, <i>ARID1A</i>, <i>PTEN</i>, ER, nor PR expression were associated with CR. However, age at diagnosis (HR: 0.84, p=0.02), obesity (HR: 0.15, p=0.02), and EC (HR: 0.17, p=0.01) were seen to have a reduced probability of response on multivariable analysis. Over time from diagnosis, ER and PR expression decreased, and <i>ARID1A</i> expression was lost in both responders and non-responders. Furthermore, the decrease over time for PR and <i>ARID1A</i> expression occurred at a faster rate for responders. <b>Conclusions:</b> In human endometrial samples taken at diagnosis, contrary to preclinical work, there were no potential biomarkers or clinical characteristics identified to be associated with improved response rate or time to respond.

FYN and CD247: Key Genes for Septic Shock Based on Bioinformatics and Meta-Analysis.

Septic shock is sepsis accompanied by hemodynamic instability and high clinical mortality. GSE95233, GSE57065, GSE131761 gene-expression profiles of healthy control subjects and septic shock patients were downloaded from the Gene-Expression Omnibus (GEO) database, and differences of expression profiles and their intersection were analysed using GEO2R. Function and pathway enrichment analysis was performed on common differentially expressed genes (DEG), and key genes for septic shock were screened using a protein-protein interaction network created with STRING. Also, data from the GEO database were used for survival analysis for key genes, and a meta-analysis was used to explore expression trends of core genes. Finally, high-throughput sequencing using the blood of a murine sepsis model was performed to analyse the expression of CD247 and FYN in mice. A total of 539 DEGs were obtained (p < 0.05). Gene ontology analysis showed that key genes were enriched in functions, such as immune response and T cell activity, and DEGs were enriched in signal pathways, such as T cell receptors. FYN and CD247 are in the centre of the protein-protein interaction network, and survival analysis found that they are positively correlated with survival from sepsis. Further, meta-analysis results showed that FYN could be useful for the prognosis of patients, and CD247 might distinguish between sepsis and systemic inflammatory response syndrome patients. Finally, RNA sequencing using a mouse septic shock model showed low expression of CD247 and FYN in this model. FYN and CD247 are expected to become new biomarkers of septic shock.

Identification of Respiratory Burst Oxidase Homolog (Rboh) Family Genes From Pyropia yezoensis and Their Correlation With Archeospore Release.

Reactive oxygen species (ROS) play important regulatory roles in plant growth and development, as well as in cell differentiation and stress responses. Respiratory burst oxidase homolog (RBOH) is the key enzyme in ROS production. So far, the Rboh family genes in Pyropia yezoensis have not been comprehensively characterized, and whether their function was involved in the formation of archeospores is still unknown. In this study, a total of 11 PyRboh genes were identified from the P. yezoensis genome by homology mining. Through phylogenetic analysis, it is suggested that the PyRboh genes were evolutionarily conserved among the lineages of red algae, but a few genes exhibited a species-specific manner. The treatment of P. yezoensis blades with NADPH oxidase inhibitor diphenylene iodonium (DPI) could significantly inhibit the formation of archeospores, suggesting that RBOH may be involved in the formation of archeospores. According to PyRboh gene expression analysis using the P. yezoensis strains with obvious differences in releasing archeospores, it is showed that the expression trends of most genes were consistent, with no significant difference between strains, whereas the expression pattern of the two P. yezoensis-specific genes (PyRbohJ and PyRbohK) was positively correlated with the amount of archeospores. Furthermore, as treatment of blades with allantoin resulted in a significant increase in the release of archeospores, the expression levels of PyRbohJ and PyRbohK were also consistently upregulated, further confirming the relationship between the two genes and archeospore formation. These findings provide insights into the molecular mechanism of P. yezoensis archeospore formation.