Comprehensive Metabolomic Analysis Research Articles

Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is known for its aggressive nature, lack of effective diagnostic tools and treatments, and generally poor prognosis. The objective of this study was to investigate metabolic changes in TNBC using metabolomics approaches and explore the underlying mechanisms through integrated analysis with transcriptomics. In this study, serum untargeted metabolic profiles were first examined between 18 TNBC patients and 21 healthy control (HC) subjects using liquid chromatography-mass spectrometry (LC-MS), identifying a total of 22 significantly differential metabolites (DMs). Subsequently, receiver operating characteristic analysis revealed that 7-methylguanine could serve as a potential biomarker for TNBC in both the discovery and validation sets. Additionally, transcriptomic datasets were retrieved from the GEO database to identify differentially expressed genes (DEGs) between TNBC and normal tissues. An integrative analysis of the DMs and DEGs was conducted, uncovering potential molecular mechanisms underlying TNBC. Notably, three pathways-tyrosine metabolism, phenylalanine metabolism, and glycolysis/gluconeogenesis-were enriched, providing insight into the energy metabolism disorders in TNBC. Within these pathways, two DMs (4-hydroxyphenylacetaldehyde and oxaloacetic acid) and six DEGs (MAOA, ADH1B, ADH1C, AOC3, TAT, and PCK1) were identified as key components. In summary, this study highlights metabolic biomarkers that could potentially be used for the diagnosis and screening of TNBC. The comprehensive analysis of metabolomics and transcriptomics data offers a validated and in-depth understanding of TNBC metabolism.

Co-Colorectal cancer stem cells employ the FADS1/DDA axis to evade NK cell-mediated immunosuppression after co-cultured with NK cells under hypoxia

Colorectal cancer (CRC) ranks as China’s second most common cancer and fifth top cancer death cause. The study highlights the role of Natural Killer (NK) cells in targeting cancer stem cells (CSCs) that evade immune responses in CRC. Colorectal cancer stem cells (CCSCs) were stem from HT-29 cells and co-cultured with NK cells under normoxic or hypoxic conditions. The impact of this co-culture was evaluated using CCK8 assays for NK cell viability, ELISA for cytokine level changes, and flow cytometry for assessing NK cell apoptosis and activation. Comprehensive metabolomic and transcriptomic analyses were also performed to identify key genes and metabolites involved in the interaction between CCSCs and NK cells Co-culture of CCSCs with NK cells under hypoxia reduced NK cytotoxicity, increased NK apoptosis, and altered cytokine secretion by decreasing IFN-γ and TNF-α levels while increasing IL-6. Transcriptomic and metabolomic analysis identified 4 genes (FADS1, ALDH3A2, GCSH, MTCL1) and 3 metabolites (glyoxylic acid, spermine, DDA) as significant. Interfering with FADS1 counteracted the suppression of IFN-γ and TNF-α induced by CSC cells. Curiously, this inhibition caused by si-FADS1 could be neutralized by the addition of exogenous DDA. Co-culturing with NK cells notably increased spermine levels. Exogenous spermine resulted in a significant reduction in HT-29 cell death rates at 32 µM, 64 µM, and 128 µM, compared to NK cells without spermine. Our research explored CCSCs employed the FADS1/DDA axis to evade NK cell-mediated immunosuppression after co-cultured with NK cells under hypoxia.

Serum metabolomics signature of maternally inherited diabetes and deafness by gas chromatography-time of flight mass spectrometry.

The aim of this study was to identify a metabolic signature of MIDD as compared to healthy controls and other types of diabetes. We performed a comprehensive serum metabolomic analysis using gas chromatography-time of flight mass spectrometry (GC-TOFMS) in participants diagnosed with MIDD (n = 14), latent autoimmune diabetes in adults (LADA) (n = 14), type 2 diabetes mellitus (n = 14), and healthy controls (n = 14). Each group was matched for gender and age. There were significant metabolic differences among MIDD and other diabetic and control groups. Compared with control, MIDD patients had high levels of carbohydrates (glucose, galactose, mannose, sorbose, and maltose), fatty acids (2-Hydroxybutyric acid, eicosapentaenoic acid, and octadecanoic acid), and other metabolites (alanine, threonic acid, cholesterol, lactic acid, and gluconic acid), but low level of threonine. Compared with LADA, MIDD patients had high levels of threonic acid and some amino acids (alanine, tryptophan, histidine, proline, glutamine, and creatine) but low levels of serine. Compared with type 2 diabetes mellitus, MIDD patients had high levels of citrulline, creatine, 3-Amino-2-piperidone, but low levels of ornithine, fatty acids (arachidonic acid and octadecanoic acid), and intermediates of the tricarboxylic acid cycle (malic acid and succinic acid). Our study identified a specific metabolic profile related to glycolysis and the tricarboxylic acid cycle in MIDD that differs from healthy controls and other types of diabetes. This unique metabolic signature provides new perspectives for understanding the pathophysiology and underlying mechanisms of MIDD.

Leveraging ML for profiling lipidomic alterations in breast cancer tissues: a methodological perspective

In this study, a comprehensive methodology combining machine learning and statistical analysis was employed to investigate alterations in the metabolite profiles, including lipids, of breast cancer tissues and their subtypes. By integrating biological and machine learning feature selection techniques, along with univariate and multivariate analyses, a notable lipid signature was identified in breast cancer tissues. The results revealed elevated levels of saturated and monounsaturated phospholipids in breast cancer tissues, consistent with external validation findings. Additionally, lipidomics analysis in both the original and validation datasets indicated lower levels of most triacylglycerols compared to non-cancerous tissues, suggesting potential alterations in lipid storage and metabolism within cancer cells. Analysis of cancer subtypes revealed that levels of PC 30:0 were relatively reduced in HER2(−) samples that were ER(+) and PR(+) compared to those that were ER(−) and PR(−). Conversely, HER2(+) tumors, which were ER(−) and PR(−), exhibited increased concentrations of PC 30:0. This increase could potentially be linked to the role of Stearoyl-CoA-Desaturase 1 in breast cancer. Comprehensive metabolomic analyses of breast cancer can offer crucial insights into cancer development, aiding in early detection and treatment evaluation of this devastating disease.

Comparative analysis of features extraction protocols for LC-HRMS untargeted metabolomics in mountain cheese ‘identitation’

This study presents a comprehensive metabolomic analysis of Parmigiano Reggiano samples to differentiate between those designated as Mountain Quality Certification (QC) and conventional Protected Designation of Origin (PDO). Despite following the same production protocol, these cheese varieties differ in the cows’ feeding regimes and milk stable locations, with mountain-certified samples adhering to specific requirements regarding milk origin and feed composition. An untargeted approach with Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) was proposed to characterize the cheese metabolome. High-resolution LC-MS data can generate gigabyte-sized files, making data compression essential for manageable multivariate analysis and noise reduction. This study employs the Region of Interest-Multivariate Curve Resolution (ROI-MCR) protocol to achieve effective data compression and chromatographic resolution, thereby extracting the most informative features. This method was compared with a classical approach for feature extraction from chromatographic data, namely Compound Discoverer (CD) software. The features extracted by both methods were analysed through Principal Component Analysis (PCA) and ASCA (ANOVA Simultaneous Component Analysis). The comparison of ROI-MCR and CD approaches demonstrated that while both methods yielded similar overall conclusions, ROI-MCR provided a more streamlined and manageable dataset, facilitating easier interpretation of the metabolic differences. Both approaches indicated that amino acids, fatty acids, and bacterial activity-related compounds played significant roles in distinguishing between the two sample types.

Investigation of the preharvest arginine spraying mechanism on antioxidant system in postharvest broccoli via transcriptomics and metabolomics

According to our previous study, preharvest spraying of arginine for 1 day enhanced the antioxidant capacity of postharvest broccoli, but the underlying molecular mechanisms remain unclear. We here performed a comprehensive transcriptome and metabolome analysis to investigate the effects of arginine sprayed 1 day before harvest on the antioxidant capacity and yellowing of broccoli as well as the related action mechanisms. In total, 67 differentially expressed genes and 12 key differentially accumulated metabolites were identified in broccoli at 4 and 8 days during storage. Herein, the gene expression of superoxide dismutase, catalase, and the corresponding peroxisome protein Mpv17 (MPV17) was upregulated, consequently enhancing the scavenging of reactive oxygen species. Genes encoding glucosinolate synthesis- and metabolism-related enzymes were upregulated, and among them, the gene ST5b_c was upregulated by 8.23-fold, which promoted the accumulation of its metabolites. Expression of lignin- and flavonoid biosynthesis-related genes (CAD, POD, CHI, and CHS) was elevated. Flavonoid and lignin accumulation was promoted, with a greater antioxidant capacity at 4 and 8 days, respectively, in the arginine-sprayed broccoli. Additionally, the ascorbate–glutathione cycle was promoted in broccoli at 4 days, GLCAK and APX genes were upregulated by more than 2-fold, and broccoli exhibited a higher tolerance level because of the notably stimulated ascorbic acid and glutathione accumulation. This study offers new insights into the mechanisms through which preharvest spraying of arginine regulates the antioxidant capacity of postharvest broccoli.

Bacteroides vesicles promote functional alterations in the gut microbiota composition.

Inflammatory bowel diseases are characterized by chronic intestinal inflammation and alterations in the gut microbiota composition. Bacteroides fragilis, which secretes outer membrane vesicles (OMVs) with polysaccharide A (PSA), can moderate the inflammatory response and possibly alter the microbiota composition. In this study, we created a murine model of chronic sodium dextran sulfate (DSS)-induced intestinal colitis and treated it with B. fragilis OMVs. We monitored the efficiency of OMV therapy by determining the disease activity index (DAI) and performing histological examination (HE) of the intestine before and after vesicle exposure. We also analyzed the microbiota composition using 16S rRNA gene sequencing. Finally, we evaluated the volatile compound composition in the animals' stools by HS-GC/MS to assess the functional activity of the microbiota. We observed more effective intestinal repair after OMV treatment according to the DAI and HE. A metabolomic study also revealed changes in the functional activity of the microbiota, with a predominance of phenol and pentanoic acid in the control group compared to the group treated with DSS and the group treated with OMVs (DSS OMVs). We also observed a positive correlation of these metabolites with Saccharibacteria and Acetivibrio in the control group, whereas in the DSS group, there was a negative correlation of phenol and pentanoic acid with Lactococcus and Romboutsia. According to the metabolome and sequencing data, the microbiota composition of the DSS-treated OMV group was intermediate between that of the control and DSS groups. OMVs not only have an anti-inflammatory effect but also contribute to the recovery of the microbiota composition.IMPORTANCEBacteroides fragilis vesicles contain superficially localized polysaccharide A (PSA), which has unique immune-modulating properties. Isolated PSA can prevent chemically induced colitis in a murine model. Outer membrane vesicles (OMVs) also contain digestive enzymes and volatile metabolites that can complement the anti-inflammatory properties of PSA. OMVs showed high therapeutic activity against sodium dextran sulfate-induced colitis, as confirmed by histological assays. 16S rRNA sequencing of fecal samples from different inflammatory stages, supplemented with comprehensive metabolome analysis of volatile compounds conducted by HS-GC/MS, revealed structural and functional alterations in the microbiota composition under the influence of OMVs. Correlation analysis of the OMV-treated and untreated experimental animal groups revealed associations of phenol and pentanoic acid with Lactococcus, Romboutsia, Saccharibacteria, and Acetivibrio.

Optimized high-throughput protocols for comprehensive metabolomic and lipidomic profiling of brain sample

Establishing direct causal and functional links between genotype and phenotype requires thoroughly analyzing metabolites and lipids in systems biology. Tissue samples, which provide localized and direct information and contain unique compounds, play a significant role in objectively classifying diseases, predicting prognosis, and deciding personalized therapeutic strategies. Comprehensive metabolomic and lipidomic analyses in tissue samples need efficient sample preparation steps, optimized analysis conditions, and the integration of orthogonal analytical platforms because of the physicochemical diversities of biomolecules. Here, we propose simple, rapid, and robust high-throughput analytical protocols based on the design of experiment (DoE) strategies, with the various parameters systematically tested for comprehensively analyzing the heterogeneous brain samples. The suggested protocols present a systematically DoE-based strategy for performing the most comprehensive analysis for integrated GC-MS and LC-qTOF-MS from brain samples. The five different DoE models, including D-optimal, full factorial, fractional, and Box-Behnken, were applied to increase extraction efficiency for metabolites and lipids and optimize instrumental parameters, including sample preparation and chromatographic parameters. The superior simultaneous extraction of metabolites and lipids from brain samples was achieved by the methanol-water-dichloromethane (2:1:3, v/v/v) mixture. For GC-MS based metabolomics analysis, incubation time, temperature, and methoxyamine concentration (10 mg/mL) affected metabolite coverage significantly. For LC-qTOF-MS based metabolomics analysis, the extraction solvent (methanol-water; 2:1, v/v) and the reconstitution solvent (%0.1 FA in acetonitrile) were superior on the metabolite coverage. On the other hand, the ionic strength and column temperature were critical and significant parameters for high throughput metabolomics and lipidomics studies using LC-qTOF-MS. In conclusion, DoE-based optimization strategies for a three-in-one single-step extraction enabled rapid, comprehensive, high-throughput, and simultaneous analysis of metabolites, lipids, and even proteins from a 10 mg brain sample. Under optimized conditions, 475 lipids and 158 metabolites were identified in brain samples.

Arabidopsis hydathodes are sites of auxin accumulation and nutrient scavenging.

Hydathodes are small organs found on the leaf margins of vascular plants which release excess xylem sap through a process called guttation. While previous studies have hinted at additional functions of hydathode in metabolite transport or auxin metabolism, experimental support is limited. We conducted comprehensive transcriptomic, metabolomic and physiological analyses of mature Arabidopsis hydathodes. This study identified 1460 genes differentially expressed in hydathodes compared to leaf blades, indicating higher expression of most genes associated with auxin metabolism, metabolite transport, stress response, DNA, RNA or microRNA processes, plant cell wall dynamics and wax metabolism. Notably, we observed differential expression of genes encoding auxin-related transcriptional regulators, biosynthetic processes, transport and vacuolar storage supported by the measured accumulation of free and conjugated auxin in hydathodes. We also showed that 78% of the total content of 52 xylem metabolites was removed from guttation fluid at hydathodes. We demonstrate that NRT2.1 and PHT1;4 transporters capture nitrate and inorganic phosphate in guttation fluid, respectively, thus limiting the loss of nutrients during this process. Our transcriptomic and metabolomic analyses unveil an organ with its specific physiological and biological identity.

Mitochondrial reprogramming by activating OXPHOS via glutamine metabolism in African American patients with bladder cancer.

Bladder cancer (BLCA) mortality is higher in African American (AA) patients compared with European American (EA) patients, but the molecular mechanism underlying race-specific differences are unknown. To address this gap, we conducted comprehensive RNA-Seq, proteomics, and metabolomics analysis of BLCA tumors from AA and EA. Our findings reveal a distinct metabolic phenotype in AA BLCA characterized by elevated mitochondrial oxidative phosphorylation (OXPHOS), particularly through the activation of complex I. The results provide insight into the complex I activation-driven higher OXPHOS activity resulting in glutamine-mediated metabolic rewiring and increased disease progression, which was also confirmed by [U]13C-glutamine tracing. Mechanistic studies further demonstrate that knockdown of NDUFB8, one of the components of complex I in AA BLCA cells, resulted in reduced basal respiration, ATP production, GLS1 expression, and proliferation. Moreover, preclinical studies demonstrate the therapeutic potential of targeting complex I, as evidenced by decreased tumor growth in NDUFB8-depleted AA BLCA tumors. Additionally, genetic and pharmacological inhibition of GLS1 attenuated mitochondrial respiration rates and tumor growth potential in AA BLCA. Taken together, these findings provide insight into BLCA disparity for targeting GLS1-Complex I for future therapy.

Integration of deep neutral network modeling and LC-MS-based pseudo-targeted metabolomics to discriminate easily confused ginseng species

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus and P. japonicus var. major, containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM, and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

BZIP transcription factor responds to changes in light quality and affects saponins synthesis in Eleutherococcus senticosus

Light quality considerably influences plant secondary metabolism, yet the precise mechanism underlying its impact on Eleutherococcus senticosus remains elusive. Comprehensive metabolomic and transcriptomic analyses revealed that varying light quality alters the biosynthesis of triterpene saponins by modulating the expression of genes involved in the process in E. senticosus. Through correlation analysis of gene expression and saponin biosynthesis, we identified four light-responsive transcription factors, namely EsbZIP1, EsbZIP2, EsbZIP4, and EsbZIP5. EsbZIP transcription factors function in the nucleus, with light quality-dependent promoter activity. Except for EsbZIP2, the other EsbZIP transcription factors exhibit transcriptional self-activation. Furthermore, EsbZIP can bind to the promoter areas of genes that encode important enzymes (EsFPS, EsSS, and EsSE) involved in triterpene saponin biosynthesis, thereby regulating their expression. Overexpression of EsbZIP resultes in significant down-regulation of most downstream target genes，which leads to a decrease in saponin content. Overall, varying light quality enhances the content of triterpene saponins by suppressing the expression of EsbZIP. This study thus elucidates the molecular mechanism by which E. senticosus adjusts triterpene saponin levels in response to changes in light quality.

Comprehensive biomarker analysis of metabolomics in different syndromes in traditional Chinese medical for prediabetes mellitus

BackgroundPrediabetes mellitus (PreDM) is a high-risk state for developing type 2 diabetes mellitus (T2DM) and often goes undiagnosed, which is closely associated with obesity and characterized by insulin resistance that urgently needs to be treated.PurposeTo obtain a better understanding of the biological processes associated with both "spleen-dampness" syndrome individuals and those with dysglycaemic control at its earliest stages, we performed a detailed metabolomic analysis of individuals with various early impairments in glycaemic control, the results can facilitate clinicians’ decision making and benefit individuals at risk.MethodsAccording to the diagnostic criteria of TCM patterns and PreDM, patients were divided into 4 groups with 20 cases, patients with syndrome of spleen deficiency with dampness encumbrance and PreDM (PDMPXSK group), patients with syndrome of dampness-heat in the spleen and PreDM (PDMSRYP group), patients with syndrome of spleen deficiency with dampness encumbrance and normal blood glucose (NDMPXSK group), and patients with syndrome of dampness-heat in the spleen and normal blood glucose (NDMSRYP group). Plasma samples from patients were collected for clinical index assessment and untargeted metabolomics using liquid chromatography-mass spectrometry.ResultsAmong patients with the syndrome of spleen deficiency with dampness encumbrance (PXSK), those with PreDM (PDMPXSK group) had elevated levels of 2-hour post-load blood glucose (2-h PG), glycosylated hemoglobin (HbA1c), high-density lipoprotein cholesterol (HDL-C), and systolic blood pressure (SBP) than those in the normal blood glucose group (NDMPXSK group, P < 0.01). Among patients with the syndrome of dampness-heat in the spleen (SRYP), the levels of body mass index (BMI), fasting blood glucose (FBG), 2-h PG, HbA1c, and fasting insulin (FINS) were higher in the PreDM group (PDMSRYP group) than those in the normal blood glucose group (NDMSRYP group, P < 0.05). In both TCM syndromes, the plasma metabolomic profiles of PreDM patients were mainly discriminatory from the normal blood glucose controls of the same syndrome in the levels of lipid species, with the PXSK syndrome showing a more pronounced and broader spectrum of alterations than the SRYP syndrome. Changes associated with PreDM common to both syndromes included elevations in the levels of 27 metabolites which were mainly lipid species encompassing glycerophospholipids (GPs), diglycerides (DGs) and triglycerides (TGs), cholesterol and derivatives, and decreases in 5 metabolites consisting 1 DG, 1 TG, 2 N,N-dimethyl phosphatidylethanolamine (PE-NMe2) and iminoacetic acid. Correlation analysis identified significant positive correlations of 3α,7α,12α,25-Tetrahydroxy-5β-cholestane-24-one with more than one glycaemia-related indicators, whereas DG (20:4/20:5) and PC (20:3/14:0) were positively and PC (18:1/14:0) was inversely correlated with more than one lipid profile-related indicators. Based on the value of correlation coefficient, the top three correlative pairs were TG with PC (18:1/14:0) (r = − 0.528), TG with TG (14:0/22:4/22:5) (r = 0.521) and FINS with PE-NMe (15:0/22:4) (r = 0.52).ConclusionOur results revealed PreDM patients with different TCM syndromes were characterized by different clinical profiles. Common metabolite markers associated with PreDM shared by the two TCM syndromes were mainly lipid species encompassing GP, GL, cholesterol and derivatives. Our findings were in line with the current view that altered lipid metabolism is a conserved and early event of dysglycaemia. Our study also implied the possible involvement of perturbed bile acid homeostasis and dysregulated PE methylation during development of dysglycaemia.

Comprehensive Analysis of Microbiomes and Metabolomics Reveals the Mechanism of Adaptation to Cadmium Stress in Rhizosphere Soil of Rhododendron decorum subsp. Diaprepes

The toxicity of cadmium (Cd) not only affects the growth and development of plants but also has an impact on human health. In this study, high-throughput sequencing and LC-MS were conducted to analyze the effect of CdCl2 treatment on the microbial community and soil metabolomics of rhizosphere soil in Rhododendron decorum subsp. diaprepes. The results showed that CdCl2 treatment reduced the quality of the rhizosphere soil by significantly decreasing the soil organic carbon (SOC) content, urease, and invertase activities, increasing the percentage of the exchangeable Cd fraction. CdCl2 treatment did not significantly change the Chao1 and Shannon indices of bacterial and fungal communities in the rhizosphere soil. R. decorum was more likely to recruit Cd-resistant bacteria (e.g., Proteobacteria, Chloroflexi) and increase the abundance of Cd-resistant fungi (e.g., Basidiomycota, Rozellomycota). Moreover, CdCl2 treatment decreased the content of secondary metabolites associated with plants’ resistance to Cd. Rhizosphere soil urease, invertase activities, alkaline phosphatase (ALP), SOC, total potassium (TK), Cd, and nitrate nitrogen (NN) were the main drivers of the composition of rhizosphere bacterial and fungal communities. CdCl2 treatment weakened the relationships among bacterial/fungi, differential metabolites, and physicochemical properties in rhizosphere soil.

Epithelial‑derived head and neck squamous tumourigenesis (Review).

Head and neck squamous cell carcinomas (HNSCCs), a heterogeneous group of cancers that arise from the mucosal epithelia cells in the head and neck areas, present great challenges in diagnosis, treatment and prognosis due to their complex aetiology and various clinical manifestations. Several factors, including smoking, alcohol consumption, oncogenic genes, growth factors, Epstein‑Barr virus and human papillomavirus infections can contribute to HNSCC development. The unpredictable tumour microenvironment adds to the complexity of managing HNSCC. Despite significant advances in therapies, the prediction of outcome after treatment for patients with HNSCC remains poor, and the 5‑year overall survival rate is low due to late diagnosis. Early detection greatly increases the chances of successful treatment. The present review aimed to bring together the latest findings related to the molecular mechanisms of HNSCC carcinogenesis and progression. Comprehensive genomic, transcriptomic, metabolomic, microbiome and proteomic analyses allow researchers to identify important biological markers such as genetic alterations, gene expression signatures and protein markers that drive HNSCC tumours. These biomarkers associated with the stages of initiation, progression and metastasis of cancer are useful in the management of patients with cancer in order to improve their life expectancy and quality of life.

Exploring the Flavonoid Biosynthesis Pathway of Two Ecotypes of Leymus chinensis Using Transcriptomic and Metabolomic Analysis

This research investigates the flavonoid biosynthesis pathways of two ecotypes of Leymus chinensis, distinguished by their gray-green (GG) and yellow-green (YG) leaf colors, to uncover the molecular bases of their adaptability to different environmental conditions. By integrating comprehensive transcriptomic and metabolomic analyses, we identified 338 metabolites, with 161 showing differential expression—124 upregulated and 37 downregulated. The transcriptomic data revealed substantial variation, with 50,065 genes differentially expressed between the ecotypes, suggesting complex genetic regulation of the flavonoid biosynthesis pathways involving 20 enzyme-coding genes. KEGG pathway enrichment analysis further highlighted the involvement of 26 genes in the synthesis of four distinct types of flavonoid metabolites, indicating the sophisticated modulation of these pathways. Our results demonstrate that the GG and YG ecotypes of Leymus chinensis exhibit distinct flavonoid profiles and gene expression patterns, with the GG ecotype showing a higher accumulation of quercetin and kaempferol (increased by 25% and 33%, respectively, compared to YG), suggesting enhanced antioxidant capacity. Conversely, the YG ecotype displayed a broader spectrum of flavonoid metabolites, possibly indicating an adaptive strategy favoring diverse ecological interactions. Our results show that the GG and YG ecotypes of Leymus chinensis exhibit distinct flavonoid profiles and gene expression patterns, suggesting divergent adaptive strategies to environmental stress. This study highlights the crucial role of flavonoid metabolites in plant adaptation strategies, enhancing our understanding of plant resilience and adaptability. The distinct metabolic profiles observed suggest that the GG ecotype may be better equipped to handle oxidative stress, while the YG ecotype could be predisposed to broader ecological interactions. This emphasizes the value of applying machine learning in predicting plant adaptability, providing a new perspective for the future exploration of how plants adapt to environmental challenges. Meanwhile, the information gleaned from this nuanced study offers a foundation for future investigations into the genetic and environmental factors involved in plant adaptation.

The cap-binding complex modulates ABA-responsive transcript splicing during germination in barley (Hordeum vulgare)

To decipher the molecular bases governing seed germination, this study presents the pivotal role of the cap-binding complex (CBC), comprising CBP20 and CBP80, in modulating the inhibitory effects of abscisic acid (ABA) in barley. Using both single and double barley mutants in genes encoding the CBC, we revealed that the double mutant hvcbp20.ab/hvcbp80.b displays ABA insensitivity, in stark contrast to the hypersensitivity observed in single mutants during germination. Our comprehensive transcriptome and metabolome analysis not only identified significant alterations in gene expression and splicing patterns but also underscored the regulatory nexus among CBC, ABA, and brassinosteroid (BR) signaling pathways.

Integrating Transcriptome and Metabolome Analysis Unveils the Browning Mechanism of Leaf Response to High Temperature Stress in Nicotiana tabacum

During the process of flue-curing and processing, leaves from cash crops such as tea and tobacco frequently undergo a phenomenon of browning, leading to reduced quality and significant economic losses. Despite a variety of approaches developed to suppress browning, little is known about the role that flue-curing of postharvest leaves with stems plays in delaying browning. This study investigated the impact of leaf-with-stem (LWS) flue-curing on the browning of tobacco and its underlying mechanisms. Physiological results indicated that LWS flue-curing effectively delayed browning by enhancing antioxidant capacity and maintaining reactive oxygen species (ROS) levels during the yellowing stage. Comprehensive transcriptome and metabolome analyses showed that LWS flue-curing significantly influenced various metabolic pathways. Specifically, 196, 218, and 402 metabolites, and 65, 131, and 718 genes exhibited significant changes at the 38 °C, 40 °C, and 42 °C stages, respectively, inhibiting membrane lipid degradation and enhancing the supply of reducing hydrogen through the oxidative pentose-phosphate pathway. Additionally, hormone signaling pathways were found to be associated with LWS flue-curing. These findings highlight the complex interplay of metabolic pathways and signaling networks in attenuating browning, providing valuable insights for minimizing postharvest leaf browning during flue-curing and processing.

Metabolome and Transcriptome Unveil the Correlated Metabolites and Transcripts with 2-acetyl-1-pyrroline in Fragrant Rice.

Fragrance is a valuable trait in rice varieties, with its aroma significantly influencing consumer preference. In this study, we conducted comprehensive metabolome and transcriptome analyses to elucidate the genetic and biochemical basis of fragrance in the Shangsixiangnuo (SSXN) variety, a fragrant indica rice cultivated in Guangxi, China. Through sensory evaluation and genetic analysis, we confirmed SSXN as strongly fragrant, with an 806 bp deletion in the BADH2 gene associated with fragrance production. In the metabolome analysis, a total of 238, 233, 105 and 60 metabolic compounds exhibited significant changes at the seedling (S), reproductive (R), filling (F), and maturation (M) stages, respectively. We identified four compounds that exhibited significant changes in SSXN across all four development stages. Our analyses revealed a significant upregulation of 2-acetyl-1-pyrroline (2AP), the well-studied aromatic compound, in SSXN compared to the non-fragrant variety. Additionally, correlation analysis identified several metabolites strongly associated with 2AP, including ethanone, 1-(1H-pyrrol-2-yl)-, 1H-pyrrole, and pyrrole. Furthermore, Weighted Gene Co-expression Network Analysis (WGCNA) analysis highlighted the magenta and yellow modules as particularly enriched in aroma-related metabolites, providing insights into the complex aromatic compounds underlying the fragrance of rice. In the transcriptome analysis, a total of 5582, 5506, 4965, and 4599 differential expressed genes (DEGs) were identified across the four developmental stages, with a notable enrichment of the common pathway amino sugar and nucleotide sugar metabolism in all stages. In our correlation analysis between metabolome and transcriptome data, the top three connected metabolites, phenol-, 3-amino-, and 2AP, along with ethanone, 1-(1H-pyrrol-2-yl)-, exhibited strong associations with transcripts, highlighting their potential roles in fragrance biosynthesis. Additionally, the downregulated expression of the P4H4 gene, encoding a procollagen-proline dioxygenase that specifically targets proline, in SSXN suggests its involvement in proline metabolism and potentially in aroma formation pathways. Overall, our study provides comprehensive insights into the genetic and biochemical mechanisms underlying fragrance production in rice, laying the foundation for further research aimed at enhancing fragrance quality in rice breeding programs.

Antibacterial characteristics and mechanistic insights of combined tea polyphenols, Nisin, and epsilon-polylysine against feline oral pathogens: a comprehensive transcriptomic and metabolomic analysis.

This study evaluates the antibacterial characteristics and mechanisms of combined tea polyphenols (TPs), Nisin, and ε-polylysine (PL) against Streptococcus canis, Streptococcus minor, Streptococcus mutans, and Actinomyces oris, common zoonotic pathogens in companion animals. Pathogenic strains were isolated from feline oral cavities and assessed using minimum inhibitory concentration (MIC) tests, inhibition zone assays, growth kinetics, and biofilm inhibition studies. Among single agents, PL exhibited the lowest MIC values against all four pathogens. TP showed significant resistance against S. minor, and Nisin against S. mutans. The combination treatment (Comb) of TP, Nisin, and PL in a ratio of 13:5:1 demonstrated broad-spectrum antibacterial activity, maintaining low MIC values, forming large inhibition zones, prolonging the bacterial lag phase, reducing growth rates, and inhibiting biofilm formation. RNA sequencing and metabolomic analysis indicated that TP, Nisin, and PL inhibited various membrane-bound carbohydrate-specific transferases through the phosphoenolpyruvate-dependent phosphotransferase system in S. canis, disrupting carbohydrate uptake. They also downregulated glycolysis and the citric acid cycle, inhibiting cellular energy metabolism. Additionally, they modulated the activities of peptidoglycan glycosyltransferases and d-alanyl-d-alanine carboxypeptidase, interfering with peptidoglycan cross-linking and bacterial cell wall stability. The Comb therapy significantly enhances antibacterial efficacy by targeting multiple bacterial pathways, offering potential applications in food and pharmaceutical antimicrobials.