Cluster Heat Map Research Articles

SingmiR: a single-cell miRNA alignment and analysis tool.

Single-cell RNA sequencing(RNA-seq) has revolutionized our understanding of cell biology, developmental and pathophysiological molecular processes, paving the way toward novel diagnostic and therapeutic approaches. However, most of the gene regulatory processes on the single-cell level are still unknown, including post-transcriptional control conferred by microRNAs (miRNAs). Like the established single-cell gene expression analysis, advanced computational expertise is required to comprehensively process newly emerging single-cell miRNA-seq datasets. A web server providing a workflow tailored for single-cell miRNA-seq data with a self-explanatory interface is currently not available. Here, we present SingmiR, enabling the rapid (pre-)processing and quantification of human miRNAs from noncoding single-cell samples. It performs read trimming for different library preparation protocols, generates automated quality control reports and provides feature-normalized count files. Numerous standard and advanced analyses such as dimension reduction, clustered feature heatmaps, sample correlation heatmaps and differential expression statistics are implemented. We aim to speed up the prototyping pipeline for biologists developing single-cell miRNA-seq protocols on small to medium-sized datasets. SingmiR is freely available to all users without the need for a login athttps://www.ccb.uni-saarland.de/singmir.

Aromatic Characterization of Graševina Wines from Slavonia and Podunavlje Sub-Regions

This study investigated the chemical aromatic profiles of 60 volatile organic compounds (VOCs), including 21 terpenes, 6 norisoprenoids, 6 volatile phenols, 4 C-6 alcohols, and 23 esters, in Graševina wines originating from Slavonia and Podunavlje sub-regions (Croatia). Headspace solid-phase microextraction gas chromatography coupled with mass spectrometric detection (HS-SPME-GCMS) was used to assess 60 VOCs, and a novel HS-SPME-GCMS method for the determination of terpenes and norisoprenoids was developed and validated. Statistical analysis found no significant differences between VOCs present in Graševina wines and others wines (Chardonnay and Pinot gris); nonetheless, comparison of VOC fingerprints between different wines from the same producer showed that four terpenes (α-terpinene, γ-terpinene, 1,4-cineol, and 4-terpineol) were present in higher amounts in Graševina wines when compared to other wines. By exclusively examining VOCs within Graševina wines through the utilization of a heatmap and hierarchical clustering, a distinct visualization of samples and VOCs emerged, highlighting the vintage effect. Simultaneously, a partial least squares discriminant analysis model was developed with a confidence interval of 95%, demonstrating a noticeable distinction between samples originating from the western and eastern regions. Furthermore, by employing the heatmap using only VOCs from the terpene and norisoprenoidic groups, a clear separation of samples into two groups was observed based on geographical origin; namely, higher concentrations of norisoprenoids and terpenes were observed in the Slavonia sub-region. These results suggest that terpenes and norisoprenoids to a lower extent may be valuable aromatic markers for the regional typicality of Graševina wines.

Chemometric Analysis Evidencing the Variability in the Composition of Essential Oils in 10 Salvia Species from Different Taxonomic Sections or Phylogenetic Clades.

Essential oil (EO) of Salvia spp. has been widely used for culinary purposes and in perfumery and cosmetics, as well as having beneficial effects on human health. The present study aimed to investigate the quantitative and qualitative variations in EOs in wild-growing and cultivated pairs of samples from members in four Salvia sections or three clades, namely S. argentea L. (Sect. Aethiopis; Clade I-C), S. ringens Sm. (Sect. Eusphace; Clade I-D), S. verticillata L. (Sect. Hemisphace; Clade I-B), S. amplexicaulis Lam., and S. pratensis L. (Sect. Plethiosphace; Clade I-C). Furthermore, the natural variability in EO composition due to different genotypes adapted in different geographical and environmental conditions was examined by employing members of three Salvia sections or two phylogenetic clades, namely S. sclarea L. (six samples; Sect. Aethiopis or Clade I-C), S. ringens (three samples; Sect. Eusphace or Clade I-D), and S. amplexicaulis (five samples; Sect. Plethiosphace or Clade I-C). We also investigated the EO composition of four wild-growing species of two Salvia sections, i.e., S. aethiopis L., S. candidissima Vahl, and S. teddii of Sect. Aethiopis, as well as the cultivated material of S. virgata Jacq. (Sect. Plethiosphace), all belonging to Clade I-C. The EO composition of the Greek endemic S. teddii is presented herein only for the first time. Taken together, the findings of previous studies are summarized and critically discussed with the obtained results. Chemometric analysis (PCA, HCA, and clustered heat map) was used to identify the sample relationships based on their chemical classes, resulting in the classification of two distinct groups. These can be further explored in assistance of classical or modern taxonomic Salvia studies.

How growing conditions are influential on the agronomic attributes and fiber-related quality parameters of flax (Linum usitatissimum L.) fibers: A seismomorphogenesis approach

Among industrial crops, flax (Linum usitatissimum L.) is a multi-purpose crop grown for production of stem fiber and seed oil. Through longterm domestication for these purposes, cultivated flax has diversified into two main types, namely fiber and oil or linseed types, as well as an intermediate type. This study was designed to investigate the effect of flax fibers of flax varieties (Antares, Dakota and Mures) in field and greenhouse cultivation on fiber mechanical performances, morphological properties and fatty acid composition in flaxseed was investigated. Additionally, plants can change their morphology and mechanical properties when exposed to stress, as is particularly the case when plants respond to wind, a phenomenon known as seismomorphogenesis. Greenhouse plants were found to be significantly lower than field grown plants, with an increase of 16.79cm in technical stem length and 56.02cm in technical stem height. In addition, the total plant height of flax grown in the field was 59.33 cm compared to 17.32 cm in the greenhouse. The Mures variety was found to be the highest both in the field (79.50-76.10cm) and in the greenhouse (18.36-17.47cm). Considering the fatty acid percentages, the highest α-linolenic acid was found in Dakota (29.23%) and the lowest in Antares (20.53%) in the field, while the highest was found in Dakota (19.25%) and the lowest in Mures (16.13%) in the greenhouse. In addition, the highest tensile strength was found in Dakota (704.6 Mpa) and the closest Antares (692.2 Mpa) under field conditions, while the lowest was found in Dakota (198.5 Mpa) and Mures varieties (288.8 Mpa) under greenhouse conditions. In order to reduce the dimension, correlate and visualize the measured parameters, the relevant data of the study were subjected to principal component analysis and heat-map clustering.

Impact of semolina-barley mixture on the volatolomic profile of dough and pasta: characterization by a multivariate chemometric approach.

Barley flour, known to be rich in various phytochemicals, has been demonstrated to improve the technological and nutritional properties of pasta; however, its volatile profile, on which its aromatic properties depend, also plays an important role in the acceptance of barley-enriched pasta. In the present work, volatile organic compounds (VOCs) of semolina doughs enriched with different percentages of barley and of the related pasta were characterized by solid phase micro-extraction (HS-SPME) coupled to gas-chromatography/mass spectrometry (GC-MS), and evaluated using a multivariate statistical approach, including principal component analysis (PCA), cluster heatmaps, Pearson's and Spearman's correlations, and partial least squares correlation (PLSC). The effects of single raw materials, and their interactions, were studied to establish their importance in the volatile profile of the samples, and the correlation between the dough VOCs and the processed product VOCs was assessed. The presence of barley flour markedly affected the volatile profile in comparison with the dough obtained with only durum wheat. For alcohols, esters, terpenes, and some aldehydes there was a clear correlation with the percentage of barley. For some of the VOCs, on the other hand, a strong dependence on the ingredients interaction effect due to the mixing stage has been demonstrated. The heatmaps allowed a good graphical visualization of the relationship between molecules and barley percentage, offering the possibility to select the best one according to the desired volatolomic footprint. Pasta with 40% of barley was demonstrated to give pasta with the most complex volatile profile. © 2024 Society of Chemical Industry.

Abstract 5507: High-resolution spatial atlas reveals insight into spatial landscape of lung cancer and chronic lung diseases

Abstract Background: Patients with lung cancer often have a high prevalence of severe comorbidities, primarily due to the significant correlation with cigarette smoking and the aging process. Dysregulations of the immune response are the cause of chronic inflammatory diseases such as chronic obstructive pulmonary disease (COPD), pulmonary arterial hypertension (PAH), pulmonary fibrosis (PF) and lung cancer. In addition, the lung microenvironment in these chronic inflammatory diseases has not yet been sufficiently investigated. Therefore, we aimed to investigate the spatio-temporal localization and cellular distribution in the lung microenvironment and to compare lung cancer with the concomitant diseases of lung cancer. Methods: FFPE lung sections, each 3µm in thickness, were collected from patients with diagnoses of lung cancer, COPD, PAH, PF, and from healthy donors, with three samples taken for each category. These sections were subsequently imaged using the PhenoCycler®-Fusion system, utilizing a comprehensive panel of 45 antibodies. including immune, epithelial, vascular, proliferation and apoptosis markers. The first step of the analysis workflow consists of cell segmentation using a fine-tuned deep learning model leading to a total of 5.2 million cells across the whole dataset. Protein expressions were then calculated from the segmented cells, and unsupervised clustering was performed based on the normalized expression values. The resulting clusters were manually annotated into 16 cell phenotypes based on their protein expression patterns as displayed on a hierarchical clustering heatmap. The percentages of cell phenotypes were then calculated for each sample and compared between disease groups. Furthermore, the spatial proximity and cellular neighborhood analyses were performed to study the spatial organization of the different cell phenotypes in the tissues. Results: Quantitative assessment revealed unique characteristics specific to each disease, identified by the varying abundance of different immune cell subtypes. Additionally, when comparing lungs from healthy donors with those affected by lung diseases, notable differences were observed in the spatial arrangement of immune cells and their proximity to lung blood vessels. Conclusions: This study presents the first architectural map of lung cancer, COPD, PAH, and PF linking various immune cell types to their spatial location within the tissue. Such in-depth spatial analyses will aid in comprehending the spatial and temporal interplay within the lung's microenvironment in diverse lung conditions, as well as in developing targeted therapies for specific cell types. Citation Format: Rajender Nandigama Nandigama, Bassem Ben Cheikh Cheikh, Jamal Nabhanizadeh, Friedrich Grimminger, Werner Seeger, Niyati Jhaveri, Soni Savai Pullamsetti, Rajkumar Savai. High-resolution spatial atlas reveals insight into spatial landscape of lung cancer and chronic lung diseases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5507.

Ability of Different Growth Indicators to Detect Salt Tolerance of Advanced Spring Wheat Lines Grown in Real Field Conditions

Plant growth indicators (GIs) are important for evaluating how different genotypes respond to normal and stress conditions separately. They consider both the morphological and physiological components of plants between two successive growth stages. Despite their significance, GIs are not commonly used as screening criteria for detecting salt tolerance of genotypes. In this study, 36 recombinant inbred lines (RILs) along with four genotypes differing in their salt tolerance were grown under normal and 150 mM NaCl in a two-year field trial. The performance and salt tolerance of these germplasms were assessed through various GIs. The analysis of variance showed highly significant variation between salinity levels, genotypes, and their interaction for all GIs and other traits in each year and combined data for two years, with a few exceptions. All traits and GIs were significantly reduced by salinity stress, except for relative growth rate (RGR), net assimilation rate (NAR), and specific leaf weight (SLW), which increased under salinity conditions. Traits and GIs were more correlated with each other under salinity than under normal conditions. Principal component analysis organized traits and GIs into three main groups under both conditions, with RGR, NAR, and specific leaf area (SLA) closely associated with grain yield (GY) and harvest index, while leaf area duration (LAD) was closely associated with green leaf area (GLA), plant dry weight (PDW), and leaf area index (LAI). A hierarchical clustering heatmap based on GIs and traits organized germplasms into three and four groups under normal and salinity conditions, respectively. Based on the values of traits and GIs for each group, the germplasms varied from high- to low-performing groups under normal conditions and from salt-tolerant to salt-sensitive groups under salinity conditions. RGR, NAR, and LAD were important factors determining genotypic variation in GY of high- and low-performing groups, while all GIs, except leaf area duration (LAR), were major factors describing genotypic variation in GY of salt-tolerant and salt-sensitive groups. In conclusion, different GIs that reveal the relationship between the morphological and physiological components of genotypes could serve as valuable selection criteria for evaluating the performance of genotypes under normal conditions and their salt tolerance under salinity stress conditions.

Effect of glabridin combined with bakuchiol on UVB-induced skin damage and its underlying mechanism: An experimental study.

Research has demonstrated the anti-photoaging properties of glabridin and bakuchiol. The impact of glabridin, glabridin + bakuchiol, and bakuchiol on the levels of tumor necrosis factor alpha (TNF-α) and interleukin-1 beta (IL-1β) in mice skin fibroblasts was observed. Furthermore, we investigated the potential roles of fibronectin (FN), interferon-γ (IFN-γ), interleukin-22 (IL-22), and transforming growth factor-β (TGF-β) in the tissues, and evaluated their impact on the enzymatic levels in the skin. In conjunction with transcriptomic analysis, metabolomic profiling, and network pharmacology, all samples underwent comprehensive metabolomic and principal component analysis. The Venny2.1 method was utilized to identify variances in shared metabolites between the treatment group and the UVB group, as well as between the UVB group and the control group. Subsequently, a cluster heat map was generated to forecast and analyze metabolic pathways and targets. The outcomes from the hematoxylin and eosin and toluidine blue staining revealed that glabridin and bakuchiol markedly decreased dermal thickness and suppressed mast cell infiltration in photoaged mice. Immunohistochemistry and Elisa analysis revealed that glabridin and bakuchiol effectively attenuated the levels of pro-inflammatory factors, including IL-1β, tumor necrosis factor-α, IL-22, and IFN-γ. Furthermore, an increase in the levels of anti-inflammatory factors such as FN and TGF-β was also observed. The determination of the contents of superoxide dismutase, hydroxypropyltransferase and malondialdehyde in mice dorsal skin revealed that glabridin and bakuchiol not only elevated the levels of superoxide dismutase and hydroxyproline, but also reduced malondialdehyde content. Due to the limited number of shared differential metabolites exclusively within Kyoto Encyclopedia of Genes and Genomes, comprehensive pathway enrichment analysis was not feasible. This study demonstrates that glabridin and bakuchiol effectively impede photoaging and alleviate skin inflammation in mice.

OralExplorer: a web server for exploring the mechanisms of oral inflammatory diseases.

Oral inflammatory diseases are localized infectious diseases primarily caused by oral pathogens with the potential for serious systemic complications. However, publicly available datasets for these diseases are underutilized. To address this issue, a web tool called OralExplorer was developed. This tool integrates the available data and provides comprehensive online bioinformatic analysis. Human oral inflammatory disease-related datasets were obtained from the GEO database and normalized using a standardized process. Transcriptome data were then subjected to differential gene expression analysis, immune infiltration analysis, correlation analysis, pathway enrichment analysis, and visualization. The single-cell sequencing data was visualized as cluster plot, feature plot, and heatmaps. The web platform was primarily built using Shiny. The biomarkers identified in OralExplorer were validated using local clinical samples through qPCR and IHC. A total of 35 human oral inflammatory disease-related datasets, covering 6 main disease types and 901 samples, were included in the study to identify potential molecular signatures of the mechanisms of oral diseases. OralExplorer consists of 5 main analysis modules (differential gene expression analysis, immune infiltration analysis, correlation analysis, pathway enrichment analysis and single-cell analysis), with multiple visualization options. The platform offers a simple and intuitive interface, high-quality images for visualization, and detailed analysis results tables for easy access by users. Six markers (IL1β, SRGN, CXCR1, FGR, ARHGEF2, and PTAFR) were identified by OralExplorer. qPCR- and IHC-based experimental validation showed significantly higher levels of these genes in the periodontitis group. OralExplorer is a comprehensive analytical platform for oral inflammatory diseases. It allows users to interactively explore the molecular mechanisms underlying the action and regression of these diseases. It also aids dental researchers in unlocking the potential value of transcriptomics data related to oral diseases. OralExplorer can be accessed at https://smuonco.shinyapps.io/OralExplorer/ (Alternate URL: http://robinl-lab.com/OralExplorer ).

Physiological, Agronomic, and Grain Quality Responses of Diverse Rice Genotypes to Various Irrigation Regimes under Aerobic Cultivation Conditions.

Aerobic rice cultivation represents an innovative approach to reduce water consumption and enhance water use efficiency compared to traditional transplanting methods. Simultaneously, cultivating drought-tolerant rice genotypes becomes crucial to ensure their sustainable production under abrupt climate fluctuations. Hence, this study aimed to explore the physiological, agronomic, and grain quality responses of ten diverse rice genotypes to various irrigation levels under aerobic cultivation conditions. A field experiment was performed for two summer seasons of 2019 and 2020 in an arid Mediterranean climate. The irrigation regimes were well watered (13,998 m3/ha), mild drought (10,446 m3/ha), moderate drought (7125 m3/ha), and severe drought (5657 m3/ha). The results revealed considerable variations among rice genotypes under tested irrigation regimes in all physiological, agronomic, and quality traits. According to drought response indices, rice genotypes were classified into three groups (A-C), varying from tolerant to sensitive genotypes. The identified drought-tolerant genotypes (Giza-179, Hybrid-1, Giza-178, and Line-9399) recorded higher yields and crop water productivity with reduced water usage compared to drought-sensitive genotypes. Thus, these genotypes are highly recommended for cultivation in water-scarce environments. Furthermore, their characteristics could be valuable in breeding programs to improve drought tolerance in rice, particularly under aerobic cultivation conditions. The PCA biplot, heatmap, and hierarchical clustering highlighted specific physiological parameters such as relative water content, chlorophyll content, proline content, peroxidase content, and catalase content exhibited robust associations with yield traits under water deficit conditions. These parameters offer valuable insights and could serve as rapid indicators for assessing drought tolerance in rice breeding programs in arid environments.

Effects of chronic cold stress on tissue structure, antioxidant response, and key gene expression in the warm-water bivalve Chlamys nobilis

As ectothermic invertebrates, mollusks are regarded as good environmental indicator species for determining the adverse effects of climate change on marine organisms. In the present study, the effects of cold stress on the tissue structure, antioxidant activity, and expression levels of genes were evaluated in the warm-water noble scallop Chlamys nobilis by simulating natural seawater cooled down during winter from 17 °C to 14 °C, 12 °C, 10 °C, and 9 °C. Firstly, the gill was severely damaged at 10 °C and 9 °C, indicating that it could be used as a visually indicative organ for monitoring cold stress. The methylenedioxyamphetamine (MDA) content significantly increased with the temperatures decreasing, meanwhile, the antioxidant enzyme activities superoxide dismutase (SOD) and catalase (CAT) showed a similar pattern, suggesting that the scallop made a positive response. More importantly, 6179 genes related to low temperatures were constructed in a module-gene clustering heat map including 10 modules. Furthermore, three gene modules about membrane lipid metabolism, amino acid metabolism, and molecular defense were identified. Finally, six key genes were verified, and HEATR1, HSP70B2, PI3K, and ATP6V1B were significantly upregulated, while WNT6 and SHMT were significantly downregulated under cold stress. This study provides a dynamic demonstration of the major gene pathways' response to various low-temperature stresses from a transcriptomic perspective. The findings shed light on how warm-water bivalves can tolerate cold stress and can help in breeding new strains of aquatic organisms with low-temperature resistance.

Genomic analysis reveals genes that encode the synthesis of volatile compounds by a Bacillus velezensis-based biofungicide used in the treatment of grapes to control Aspergillus carbonarius

Fungal control strategies based on the use of Bacillus have emerged in agriculture as eco-friendly alternatives to replace/reduce the use of synthetic pesticides. Bacillus sp. P1 was reported as a new promising strain for control of Aspergillus carbonarius, a known producer of ochratoxin A, categorized as possible human carcinogen with high nephrotoxic potential. Grape quality can be influenced by vineyard management practices, including the use of fungal control agents. The aim of this study was to evaluate, for the first time, the quality parameters of Chardonnay grapes exposed to an antifungal Bacillus-based strategy for control of A. carbonarius, supporting findings by genomic investigations. Furthermore, genomic tools were used to confirm that the strain P1 belongs to the non-pathogenic species Bacillus velezensis and also to certify its biosafety. The genome of B. velezensis P1 harbors genes that are putatively involved in the production of volatiles and hydrolytic enzymes, which are responsible for releasing the free form of aroma compounds. In addition to promote biocontrol of phytopathogenic fungi and ochratoxins, the treatment with B. velezensis P1 did not change the texture (hardness and firmness), color and pH of the grapes. Heat map and hierarchical clustering analysis (HCA) of volatiles evaluated by GC/MS revealed that Bacillus-treated grapes showed higher levels of compounds with a pleasant odor descriptions such as 3-hydroxy-2-butanone, 2,3-butanediol, 3-methyl-1-butanol, 3,4-dihydro-β-ionone, β-ionone, dihydroactinidiolide, linalool oxide, and β-terpineol. The results of this study indicate that B. velezensis P1 presents desirable properties to be used as a biocontrol agent.

Comprehensive quality evaluation of different types of Gardeniae Fructus (Zhizi) and Shuizhizi based on LC-MS/MS.

Gardeniae Fructus (Zhizi) serves as both a medicinal and edible substance and finds widespread use in various industries. There are often two kinds of medicinal materials in the market: Zhizi and Shuizhizi. Typically, Zhizi with small, round fruit is used for medicinal purposes, while Shuizhizi, characterized by large, elongated fruit, is employed for dyeing. Market surveys have revealed a diverse range of Zhizi types, and modern research indicates that Shuizhizi contains rich chemical components and pharmacological activities. In this study, we collected 25 batches of Zhizi and Shuizhizi samples, categorizing them based on appearance into obovate and round fruits, with seven length grades (A-G). Using the ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-QQQ-MS/MS) method, we simultaneously quantified 13 main chemical components in fruits of Gardenia species. In addition, we compared the weight percentage of the pericarp, flesh, and seeds parts of samples with different traits, and quantified 13 chemical components in different parts. Results indicated that, aside from a few instances of overlapping fruit size ranges, Shuizhizi generally exhibits larger and longer dimensions than Zhizi. The weight proportion of the Shuizhizi pericarp is often higher than that of the Zhizi pericarp. Quantitative results highlighted significant differences in the chemical component content between Zhizi and Shuizhizi, with Shuizhizi generally containing higher levels of iridoids. The PCA and OPLS-DA analysis distinctly divided Shuizhizi and Zhizi, among which three iridoids, two organic acids, and one flavonoid made significant contributions to their classification. Cluster heatmap analysis also demonstrated complete separation between Zhizi and Shuizhizi, with clear distinctions among Zhizi samples from different origins. The distribution of the 13 chemical components in different Zhizi and Shuizhizi parts remained consistent, with iridoids and pigments concentrated in the seeds and flesh, and two organic acids and one flavonoid enriched in the pericarp. In summary, this study contributes valuable insights for classifying Zhizi and offers guidance on the rational use of Shuizhizi and the different parts of Zhizi.

Rapid Determination of Different Ripening Stages of Occidental Pears (Pyrus communis L.) by Volatile Organic Compounds Using Proton-Transfer-Reaction Mass Spectrometry (PTR-MS).

Determination of Occidental pear (Pyrus communis) ripening is difficult because the appearance of Occidental pears does not change significantly during the ripening process. Occidental pears at different ripening stages release different volatile organic compounds (VOCs), which can be used to determine fruit ripeness non-destructively and rapidly. In this study, VOCs were detected using proton-transfer-reaction mass spectrometry (PTR-MS). Notably, data were acquired within 1 min. Occidental pears harvested at five separate times were divided into three ripening stages: unripe, ripe, and overripe. The results showed that the composition of VOCs differed depending on the ripening stage. In particular, the concentrations of esters and terpenes significantly increased during the overripe stage. Three ripening stages were clearly discriminated by heatmap clustering and principal component analysis (PCA). This study provided a rapid and non-destructive method to evaluate the ripening stages of Occidental pears. The result can help fruit farmers to decide the optimum harvest time and hence reduce their economic losses.

Revealing Medicinal Constituents of Bistorta vivipara Based on Non-Targeted Metabolomics and 16S rDNA Gene Sequencing Technology.

Bistorta vivipara is a medicinal plant with a long history, but there are few studies on the effects of its medicinal components and endophytic bacteria on the accumulation of secondary metabolites. Therefore, in this study, non-targeted metabolomics techniques and 16s rDNA techniques were used to study B. vivipara from different regions. A total of 1290 metabolites and 437 differential metabolites were identified from all samples. Among them, flavonoids, isoflavonoids, and benzopyrans are the main medicinal components of B. vivipara; these have potential anticancer, antiviral, and antioxidant properties, as well as potential applications for the treatment of atrial fibrillation. In addition, irigenin, an important medicinal component, was identified for the first time. The endophytic bacterial communities in the root tissues of B. vivipara from different regions were also different in composition and richness. Hierarchical clustering heat map analysis showed that Proteobacteria and Actinobacteriota bacteria significantly affected the accumulation of many medicinal components in the roots of B. vivipara.

DendroX: multi-level multi-cluster selection in dendrograms

BackgroundCluster heatmaps are widely used in biology and other fields to uncover clustering patterns in data matrices. Most cluster heatmap packages provide utility functions to divide the dendrograms at a certain level to obtain clusters, but it is often difficult to locate the appropriate cut in the dendrogram to obtain the clusters seen in the heatmap or computed by a statistical method. Multiple cuts are required if the clusters locate at different levels in the dendrogram.ResultsWe developed DendroX, a web app that provides interactive visualization of a dendrogram where users can divide the dendrogram at any level and in any number of clusters and pass the labels of the identified clusters for functional analysis. Helper functions are provided to extract linkage matrices from cluster heatmap objects in R or Python to serve as input to the app. A graphic user interface was also developed to help prepare input files for DendroX from data matrices stored in delimited text files. The app is scalable and has been tested on dendrograms with tens of thousands of leaf nodes. As a case study, we clustered the gene expression signatures of 297 bioactive chemical compounds in the LINCS L1000 dataset and visualized them in DendroX. Seventeen biologically meaningful clusters were identified based on the structure of the dendrogram and the expression patterns in the heatmap. We found that one of the clusters consisting of mostly naturally occurring compounds is not previously reported and has its members sharing broad anticancer, anti-inflammatory and antioxidant activities.ConclusionsDendroX solves the problem of matching visually and computationally determined clusters in a cluster heatmap and helps users navigate among different parts of a dendrogram. The identification of a cluster of naturally occurring compounds with shared bioactivities implicates a convergence of biological effects through divergent mechanisms.

Development and implementation of a prognostic model for clear cell renal cell carcinoma based on heterogeneous TLR4 expression

ObjectiveClear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cell carcinomas and has the worst prognosis, originating from renal tubular epithelial cells. Toll-like receptor 4 (TLR4) plays a crucial role in ccRCC proliferation, infiltration, and metastasis. The aim of this study was to construct a prognostic scoring model for ccRCC based on TLR4 expression heterogeneity and to explore its association with immune infiltration, thereby providing insights for the treatment and prognostic evaluation of ccRCC. MethodsUsing R software, a differential analysis was conducted on normal samples and ccRCC samples, and in conjunction with the KEGG database, a correlation analysis for the clear cell renal cell carcinoma pathway (hsa05211) was carried out. We observed the expression heterogeneity of TLR4 in the TCGA-KIRC cohort and identified its related differential genes (TRGs). Based on the expression levels of TRGs, consensus clustering was employed to identify TLR4-related subtypes, and further clustering heatmaps, principal component, and single-sample gene set enrichment analyses were conducted. Overlapping differential genes (ODEGs) between subtypes were analysed, and combined with survival data, univariate Cox regression, LASSO, and multivariate Cox regression were used to establish a prognostic risk model for ccRCC. This model was subsequently evaluated through ROC analysis, risk factor correlation analysis, independent prognostic factor analysis, and intergroup differential analysis. The ssGSEA model was employed to explore immune heterogeneity in ccRCC, and the performance of the model in predicting patient prognosis was evaluated using box plots and the oncoPredict software package. ResultsIn the TCGA-KIRC cohort, TLR4 expression was notably elevated in ccRCC samples compared to normal samples, correlating with improved survival in the high-expression group. The study identified distinct TLR4-related differential genes and categorized ccRCC into three subtypes with varied survival outcomes. A risk prognosis model based on overlapping differential genes was established, showing significant associations with immune cell infiltration and key immune checkpoints (PD-1, PD-L1, CTLA4). Additionally, drug sensitivity differences were observed between risk groups. ConclusionIn the TCGA-KIRC cohort, the expression of TLR4 in ccRCC samples exhibited significant heterogeneity. Through clustering analysis, we identified that the primary immune cells across subtypes are myeloid-derived suppressor cells, central memory CD4 T cells, and regulatory T cells. Furthermore, we successfully constructed a prognostic risk model for ccRCC composed of 17 genes. This model provides valuable references for the prognosis prediction and treatment of ccRCC patients.

Identifying genetic susceptibility to Aspergillus fumigatus infection using collaborative cross mice and RNA-Seq approach.

Aspergillus fumigatus (Af) is one of the most ubiquitous fungi and its infection potency is suggested to be strongly controlled by the host genetic background. The aim of this study was to search for candidate genes associated with host susceptibility to Aspergillus fumigatus (Af) using an RNAseq approach in CC lines and hepatic gene expression. We studied 31 male mice from 25 CC lines at 8 weeks old; the mice were infected with Af. Liver tissues were extracted from these mice 5 days post-infection, and next-generation RNA-sequencing (RNAseq) was performed. The GENE-E analysis platform was used to generate a clustered heat map matrix. Significant variation in body weight changes between CC lines was observed. Hepatic gene expression revealed 12 top prioritized candidate genes differentially expressed in resistant versus susceptible mice based on body weight changes. Interestingly, three candidate genes are located within genomic intervals of the previously mapped quantitative trait loci (QTL), including Gm16270 and Stox1 on chromosome 10 and Gm11033 on chromosome 8. Our findings emphasize the CC mouse model's power in fine mapping the genetic components underlying susceptibility towards Af. As a next step, eQTL analysis will be performed for our RNA-Seq data. Suggested candidate genes from our study will be further assessed with a human cohort with aspergillosis.

Fingerprint analysis of volatile flavor compounds in twenty varieties of Lentinula edodes based on GC-IMS

The fingerprint database of volatile components in 20 varieties of Lentinula edodes were built using the gas chromatography-ion mobility spectroscopy (GC-IMS). Based on fingerprint and partial least squares discriminant analysis (PLS-DA), the differences in volatile components among varied L. edodes were further analyzed by cluster heat maps. A total of 57 volatile components were identified from all the mushroom samples, including 17 esters, 13 alcohols, 6 ketones, 6 aldehydes, 5 sulfur compounds, 3 acids, 1 alkane, and 6 other compounds. The varieties of ZP51, YS37, YS8, ZP46, XG172 showed the highest contents of esters (19 %∼41 %), alcohols (6 %∼17 %), ketones (4 %∼12 %), aldehydes (21 %∼48 %), sulfur compounds (7 %∼13 %), acids (2 %∼6 %), respectively. Twenty-eight key volatile flavor compounds were selected as the main characteristic aroma of L. edodes. GC-IMS could effectively distinguish different varieties of L. edodes, and the differences in the volatile components were visualized with fingerprint and cluster heat maps. These results provide a method to rapid evaluate the flavor profiles of L. edodes.

Rational biodiesel production from oxidation stability perspective: Evaluation of lipid-soluble carbonyl compound formation in the seed oil and biodiesel with long-term storage

The exploration of appropriate feedstock and catalytic transesterification hinders the practical application of biodiesel. Here, we introduced rational biodiesel production from oxidation stability perspective and evaluated the lipid-soluble carbonyl-containing oxidation products in long-term stored biodiesel samples that prepared from different oil source, catalyst for production, and ester bond type. A stable isotope labeling method based on liquid chromatography-high resolution-mass spectrometry (SIL-LC-HRMS) detection is established using a pair of labeling reagents namely1-(2-hydrazinyl-2-oxoethyl)pyridin-1-ium chloride (GP) and [2H5]1-(2-Hydrazinyl-2-oxoethyl)pyridin-1-ium chloride ([2H5]GP) for lipid-soluble carbonyl-containing oxidation products, including aldehydes and ketones. The main benefits of SIL-LC-HRMS are its sensitivity, selectivity, and feature coverage towards carbonyl-containing compounds and realized their non-targeted screening and relative quantification from complex matrices. Using SIL-LC-HRMS analysis, it was estimated the distribution and formation of 131 carbonyl compounds in three different kinds of second-generation feedstock and biodiesels with one-year storage in the dark. Double bond equivalent (DBE)-number of carbon (nC) plots and hierarchical clustering heatmap analysis reveal the effect of the oil source, catalyst type, and alkyl ester bond type on the variance in carbonyl compound formation during long-term biodiesel storage, arguably the most crucial factor oxidation stability in rational biodiesel production. The carbonyl formation and their variations in biodiesel samples are also discussed by theoretically calculating the bond dissociation energy for the primary constituent of seed oil and biodiesel.