PubMed

Nanomaterials (Basel). 2023 Jul 29;13(15):2204. doi: 10.3390/nano13152204.ABSTRACTAlthough chitosan-stabilized selenium nanoparticles (Ch-SeNPs) have emerged as a promising chemical form of selenium for anticancer purposes, gathering more profound knowledge related to molecular dysfunctions contributes significantly to the promotion of their evolution as a chemotherapeutic drug. In this sense, metabolites are the end products in the flow of gene expression and, thus, the most sensitive to changes in the physiological state of a biological system. Therefore, metabolomics provides a functional readout of the biochemical activity and cell state. In the present study, we evaluated alterations in the metabolomes of HepG2 cells after the exposure to Ch-SeNPs to elucidate the biomolecular mechanisms involved in their therapeutic effect. A targeted metabolomic approach was conducted to evaluate the levels of four of the main energy-related metabolites (adenosine triphosphate (ATP); adenosine diphosphate (ADP); nicotinamide adenine dinucleotide (NAD+); and 1,4-dihydronicotinamide adenine dinucleotide (NADH)), revealing alterations as a result of exposure to Ch-SeNPs related to a shortage in the energy supply system in the cell. In addition, an untargeted metabolomic experiment was performed, which allowed for the study of alterations in the global metabolic profile as a consequence of Ch-SeNP exposure. The results indicate that the TCA cycle and glycolytic pathways were impaired, while alternative pathways such as glutaminolysis and cysteine metabolism were upregulated. Additionally, increased fructose levels suggested the induction of hypoxia-like conditions. These findings highlight the potential of Ch-SeNPs to disrupt cancer cell metabolism and provide insights into the mechanisms underlying their antitumor effects.PMID:37570523 | DOI:10.3390/nano13152204

Animals (Basel). 2023 Aug 2;13(15):2494. doi: 10.3390/ani13152494.ABSTRACTThis study aimed to comprehensively evaluate the characteristics in the longissimus thoracis et lumborum (LTL) muscle of Chaka (CK) sheep and Tibetan (TB) sheep, and transcriptomics-metabolomics association analysis was used to find the possible genes, differential metabolites, and significant differential metabolic pathways that lead to meat quality differences. Based on the researched results, the nutritional quality of meat, including the contents of ether extract (11.95% vs. 10.56%), unsaturated fatty acid (51.20% vs. 47.69%), and polyunsaturated fatty acid (5.71% vs. 3.97%), were better in TB sheep than in CK sheep, while the CK sheep has better muscle fiber characteristics, such as the total number (62 vs. 45) and muscle fiber density (1426.54 mm2 vs. 1158.77 mm2) and flavor. Omics research has shown that the key differential metabolites and metabolic pathways were dominated by amino acid metabolism, particularly the glutathione metabolism, taurine and hypotaurine metabolism, and lipid metabolism-related pathways, such as glycerophospholipid metabolism and the sphingolipid signaling pathway. The intermediate metabolite sn-Glycerol 3-phosphoethanolamine played a key role in determining sheep meat quality, which was regulated by GPAT2, PLPP2, AGPAT1, PNPLA2, and GPAT4 and correlated with meat color, texture, and flavor. Overall, these results will provide effective information and more evidence to support further exploration of valuable biomarkers of meat quality.PMID:37570302 | DOI:10.3390/ani13152494

Int J Mol Sci. 2023 Aug 5;24(15):12470. doi: 10.3390/ijms241512470.ABSTRACTContinuous cropping (CC) is a common practice in agriculture, and usually causes serious economic losses due to soil degeneration, decreased crop yield and quality, and increased disease incidence, especially in medicinal plants. Continuous cropping obstacles (CCOs) are mainly due to changes in soil microbial communities, nutrient availability, and allelopathic effects. Recently, progressive studies have illustrated the molecular mechanisms of CCOs, and valid strategies to overcome them. Transcriptomic and metabolomics analyses revealed that identified DEGs (differently expressed genes) and metabolites involved in the response to CCOs are involved in various biological processes, including photosynthesis, carbon metabolism, secondary metabolite biosynthesis, and bioactive compounds. Soil improvement is an effective strategy to overcome this problem. Soil amendments can improve the microbial community by increasing the abundance of beneficial microorganisms, soil fertility, and nutrient availability. In this review, we sum up the recent status of the research on CCOs in medicinal plants, the combination of transcriptomic and metabolomics studies, and related control strategies, including uses of soil amendments, crop rotation, and intercropping. Finally, we propose future research trends for understanding CCOs, and strategies to overcome these obstacles and promote sustainable agriculture practices in medicinal plants.PMID:37569843 | DOI:10.3390/ijms241512470

Int J Mol Sci. 2023 Aug 5;24(15):12467. doi: 10.3390/ijms241512467.ABSTRACTType 2 diabetes mellitus (T2DM) is an expanding global health concern, closely associated with the epidemic of obesity. Individuals with diabetes are at high risk for microvascular and macrovascular complications, which include retinopathy, neuropathy, and cardiovascular comorbidities. Despite the availability of diagnostic tools for T2DM, approximately 30-60% of people with T2DM in developed countries are never diagnosed or detected. Therefore, there is a strong need for a simpler and more reliable technique for the early detection of T2DM. This study aimed to use a non-targeted metabolomic approach to systematically identify novel biomarkers from the serum samples of T2DM-induced Sprague Dawley (SD) rats using a comprehensive two-dimensional gas chromatography coupled with a time-of-flight mass spectrometry (GCxGC-TOF/MS). Fifty-four male Sprague Dawley rats weighing between 160-180 g were randomly assigned into two experimental groups, namely the type 2 diabetes mellitus group (T2DM) (n = 36) and the non-diabetic control group (n = 18). Results from this study showed that the metabolite signature of the diabetic rats was different from that of the non-diabetic control group. The most significantly upregulated metabolic pathway was aminoacyl-t-RNA biosynthesis. Metabolite changes observed between the diabetic and non-diabetic control group was attributed to the increase in amino acids, such as glycine, L-asparagine, and L-serine. Aromatic amino acids, including L-tyrosine, were associated with the risk of future hyperglycemia and overt diabetes. The identified potential biomarkers depicted a good predictive value of more than 0.8. It was concluded from the results that amino acids that were associated with impaired insulin secretion were prospectively related to an increase in glucose levels. Moreover, amino acids that were associated with impaired insulin secretion were prospectively related to an increase in glucose levels.PMID:37569840 | DOI:10.3390/ijms241512467

Int J Mol Sci. 2023 Aug 5;24(15):12466. doi: 10.3390/ijms241512466.ABSTRACTThe use of transcriptomic data to make inferences about plant metabolomes is a useful tool to help the discovery of important compounds in the available biodiversity. To unveil previously undiscovered metabolites of Coffea, of phytotherapeutic and economic value, we employed 24 RNAseq libraries. These libraries were sequenced from leaves exposed to a diverse range of environmental conditions. Subsequently, the data were meticulously processed to create models of putative metabolic networks, which shed light on the production of potential natural compounds of significant interest. Then, we selected one of the predicted compounds, the L-3,4-dihydroxyphenylalanine (L-DOPA), to be analyzed by LC-MS/MS using three biological replicates of flowers, leaves, and fruits from Coffea arabica and Coffea canephora. We were able to identify metabolic pathways responsible for producing several compounds of economic importance. One of the identified pathways involved in isoquinoline alkaloid biosynthesis was found to be active and producing L-DOPA, which is a common product of POLYPHENOL OXIDASES (PPOs, EC 1.14.18.1 and EC 1.10.3.1). We show that coffee plants are a natural source of L-DOPA, a widely used medicine for treatment of the human neurodegenerative condition called Parkinson's disease. In addition, dozens of other compounds with medicinal significance were predicted as potential natural coffee products. By further refining analytical chemistry techniques, it will be possible to enhance the characterization of coffee metabolites, enabling a deeper understanding of their properties and potential applications in medicine.PMID:37569839 | DOI:10.3390/ijms241512466

Int J Mol Sci. 2023 Aug 5;24(15):12458. doi: 10.3390/ijms241512458.ABSTRACTThe global prevalence of insulin resistance (IR) is increasing continuously, influencing metabolic parameters and fertility. The metabolic changes due to IR can alter the molecular composition of plasma and other body fluids. Follicular fluid (FF) is derived mainly from plasma, and it is a critical microenvironment for the developing oocytes. It contains various metabolites and amino acids, and the quality of the oocytes is linked at least partially to amino acid metabolism. Our goal was to quantitatively determine the amino acid (AA) profile of FF in IVF patients and to compare IR and non-insulin resistance (NIR) groups to investigate the AA changes in their FF. Using UHPLC-based methods, we quantified the main 20 amino acids from human FF samples in the IR and NIR groups. Several amino acids (aspartate, glycine, glutamate, and cysteine) differed significantly (p < 0.05 or less) between the two groups. The most significant alterations between the IR and NIR groups were related to the glutathione metabolic pathway involving glycine, serine, and threonine. Since insulin resistance alters the amino acid composition of the FF, the oocytes may undergo metabolism-induced changes resulting in poor oocyte quality and less fertility in the insulin resistance groups.PMID:37569834 | DOI:10.3390/ijms241512458

Int J Mol Sci. 2023 Aug 3;24(15):12387. doi: 10.3390/ijms241512387.ABSTRACTSaline-alkaline stress is one of the major damages that severely affects rice (Oryza sativa L.) growth and grain yield; however, the mechanism of the tolerance remains largely unknown in rice. Herein, we comparatively investigated the transcriptome and metabolome of two contrasting rice subspecies genotypes, Luohui 9 (abbreviation for Chao2R under study, O. sativa ssp. indica, saline-alkaline-sensitive) and RPY geng (O. sativa ssp. japonica, saline-alkaline-tolerant), to identify the main pathways and important factors related to saline-alkaline tolerance. Transcriptome analysis showed that 68 genes involved in fatty acid, amino acid (such as phenylalanine and tryptophan), phenylpropanoid biosynthesis, energy metabolism (such as Glycolysis and TCA cycle), as well as signal transduction (such as hormone and MAPK signaling) were identified to be specifically upregulated in RPY geng under saline-alkaline conditions, implying that a series of cascade changes from these genes promotes saline-alkaline stress tolerance. The transcriptome changes observed in RPY geng were in high accordance with the specifically accumulation of metabolites, consisting mainly of 14 phenolic acids, 8 alkaloids, and 19 lipids based on the combination analysis of transcriptome and metabolome. Moreover, some genes involved in signal transduction as hub genes, such as PR5, FLS2, BRI1, and NAC, may participate in the saline-alkaline stress response of RPY geng by modulating key genes involved in fatty acid, phenylpropanoid biosynthesis, amino acid metabolism, and glycolysis metabolic pathways based on the gene co-expression network analysis. The present research results not only provide important insights for understanding the mechanism underlying of rice saline-alkaline tolerance at the transcriptome and metabolome levels but also provide key candidate target genes for further enhancing rice saline-alkaline stress tolerance.PMID:37569762 | DOI:10.3390/ijms241512387

Int J Mol Sci. 2023 Aug 2;24(15):12340. doi: 10.3390/ijms241512340.ABSTRACTIn Antarctica, ice-free areas can be found along the coast, on mountain peaks, and in the McMurdo Dry Valleys, where microorganisms well-adapted to harsh conditions can survive and reproduce. Metabolic analyses can shed light on the survival mechanisms of Antarctic soil communities from both coastal sites, under different plant coverage stages, and inner sites where slow-growing or dormant microorganisms, low water availability, salt accumulation, and a limited number of primary producers make metabolomic profiling difficult. Here, we report, for the first time, an efficient protocol for the extraction and the metabolic profiling of Antarctic soils based on the combination of NMR spectroscopy and mass spectrometry (MS). This approach was set up on samples harvested along different localities of Victoria Land, in continental Antarctica, devoid of or covered by differently developed biological crusts. NMR allowed for the identification of thirty metabolites (mainly sugars, amino acids, and organic acids) and the quantification of just over twenty of them. UPLC-MS analysis identified more than twenty other metabolites, in particular flavonoids, medium- and long-chain fatty acids, benzoic acid derivatives, anthracenes, and quinones. Our results highlighted the complementarity of the two analytical techniques. Moreover, we demonstrated that their combined use represents the "gold standard" for the qualitative and quantitative analysis of little-explored samples, such as those collected from Antarctic soils.PMID:37569716 | DOI:10.3390/ijms241512340

Int J Mol Sci. 2023 Jul 31;24(15):12275. doi: 10.3390/ijms241512275.ABSTRACTMultiple myeloma (MM) is an incurable hematological cancer. It is preceded by monoclonal gammopathy of uncertain significance (MGUS)-an asymptomatic phase. It has been demonstrated that early detection increases the 5-year survival rate. However, blood-based biomarkers that enable early disease detection are lacking. Metabolomic and lipoprotein subfraction variable profiling is gaining traction to expand our understanding of disease states and, more specifically, for identifying diagnostic markers in patients with hematological cancers. This study aims to enhance our understanding of multiple myeloma (MM) and identify candidate metabolites, allowing for a more effective preventative treatment. Serum was collected from 25 healthy controls, 20 patients with MGUS, and 30 patients with MM. 1H-NMR (Nuclear Magnetic Resonance) spectroscopy was utilized to evaluate serum samples. The metabolite concentrations were examined using multivariate, univariate, and pathway analysis. Metabolic profiles of the MGUS patients revealed lower levels of alanine, lysine, leucine but higher levels of formic acid when compared to controls. However, metabolic profiling of MM patients, compared to controls, exhibited decreased levels of total Apolipoprotein-A1, HDL-4 Apolipoprotein-A1, HDL-4 Apolipoprotein-A2, HDL Free Cholesterol, HDL-3 Cholesterol and HDL-4 Cholesterol. Lastly, metabolic comparison between MGUS to MM patients primarily indicated alterations in lipoproteins levels: Total Cholesterol, HDL Cholesterol, HDL Free Cholesterol, Total Apolipoprotein-A1, HDL Apolipoprotein-A1, HDL-4 Apolipoprotein-A1 and HDL-4 Phospholipids. This study provides novel insights into the serum metabolic and lipoprotein subfraction changes in patients as they progress from a healthy state to MGUS to MM, which may allow for earlier clinical detection and treatment.PMID:37569650 | DOI:10.3390/ijms241512275

Int J Mol Sci. 2023 Jul 30;24(15):12214. doi: 10.3390/ijms241512214.ABSTRACTThe expression level of the progesterone receptor (PGR) plays a crucial role in determining the biological characteristics of serous ovarian carcinoma. Low PGR expression is associated with chemoresistance and a poorer outcome. In this study, our objective was to explore the relationship between tumor progesterone receptor levels and RNA profiles (miRNAs, piwiRNAs, and mRNAs) to understand their biological characteristics and behavior. To achieve this, we employed next-generation sequencing of small non-coding RNAs, quantitative RT-PCR, and immunohistochemistry to analyze both FFPE and frozen tumor samples, as well as blood plasma from patients with benign cystadenoma (BSC), serous borderline tumor (SBT), low-grade serous ovarian carcinoma (LGSOC), and high-grade serous ovarian carcinoma (HGSOC). Our findings revealed significant upregulation of MMP7 and MUC16, along with downregulation of PGR, in LGSOC and HGSOC compared to BSC. We observed significant correlations of PGR expression levels in tumor tissue with the contents of miR-199a-5p, miR-214-3p, miR-424-3p, miR-424-5p, and miR-125b-5p, which potentially target MUC16, MMP7, and MMP9, as well as with the tissue content of miR-16-5p, miR-17-5p, miR-20a-5p, and miR-93-5p, which are associated with the epithelial-mesenchymal transition (EMT) of cells. The levels of EMT-associated miRNAs were significantly correlated with the content of hsa_piR_022437, hsa_piR_009295, hsa_piR_020813, hsa_piR_004307, and hsa_piR_019914 in tumor tissues. We developed two optimal logistic regression models using the quantitation of hsa_piR_020813, miR-16-5p, and hsa_piR_022437 or hsa_piR_004307, hsa_piR_019914, and miR-93-5p in the tumor tissue, which exhibited a significant ability to diagnose the PGR-negative tumor phenotype with 93% sensitivity. Of particular interest, the blood plasma levels of miR-16-5p and hsa_piR_022437 could be used to diagnose the PGR-negative tumor phenotype with 86% sensitivity even before surgery and chemotherapy. This knowledge can help in choosing the most effective treatment strategy for this aggressive type of ovarian cancer, such as neoadjuvant chemotherapy followed by cytoreduction in combination with hyperthermic intraperitoneal chemotherapy and targeted therapy, thus enhancing the treatment's effectiveness and the patient's longevity.PMID:37569592 | DOI:10.3390/ijms241512214

Int J Mol Sci. 2023 Jul 30;24(15):12202. doi: 10.3390/ijms241512202.ABSTRACTParkinson's-disease (PD) is an incurable, age-related neurodegenerative disease, and its global prevalence of disability and death has increased exponentially. Although motor symptoms are the characteristic manifestations of PD, the clinical spectrum also contains a wide variety of non-motor symptoms, which are the main cause of disability and determinants of the decrease in a patient's quality of life. Noteworthy in this regard is the stress on the cardiac system that is often observed in the course of PD; however, its effects have not yet been adequately researched. Here, an untargeted metabolomics approach was used to assess changes in cardiac metabolism in the 6-hydroxydopamine model of PD. Beta-sitosterol, campesterol, cholesterol, monoacylglycerol, α-tocopherol, stearic acid, beta-glycerophosphoric acid, o-phosphoethanolamine, myo-inositol-1-phosphate, alanine, valine and allothreonine are the metabolites that significantly discriminate parkinsonian rats from sham counterparts. Upon analysis of the metabolic pathways with the aim of uncovering the main biological pathways involved in concentration patterns of cardiac metabolites, the biosynthesis of both phosphatidylethanolamine and phosphatidylcholine, the glucose-alanine cycle, glutathione metabolism and plasmalogen synthesis most adequately differentiated sham and parkinsonian rats. Our results reveal that both lipid and energy metabolism are particularly involved in changes in cardiac metabolism in PD. These results provide insight into cardiac metabolic signatures in PD and indicate potential targets for further investigation.PMID:37569578 | DOI:10.3390/ijms241512202

Int J Mol Sci. 2023 Jul 29;24(15):12190. doi: 10.3390/ijms241512190.ABSTRACTDrug combination therapy is a key approach in cancer treatments, aiming to improve therapeutic efficacy and overcome drug resistance. Evaluation of intracellular response in cancer cells to drug treatment may disclose the underlying mechanism of drug resistance. In this study, we aimed to investigate the effect of osimertinib, a tyrosine kinase inhibitor (TKI), and a curcumin derivative, 35d, on HCC827 cells and tumors by analyzing alterations in metabolome and related regulations. HCC827 tumor-bearing SCID mice and cultured HCC827 cells were separately examined. The treatment comprised four conditions: vehicle-only, 35d-only, osimertinib-only, and a combination of 35d and osimertinib. The treated tumors/cells were subsequently subjected to metabolomics profiling, fatty acyl analysis, mitochondrial potential measurement, and cell viability assay. Osimertinib induced changes in the ratio of short-chain (SC) to long-chain (LC) fatty acyls, particularly acylcarnitines (ACs), in both tumors and cells. Furthermore, 35d enhanced this effect by further lowering the SC/LC ratio of most ACs. Osimertinib and 35d also exerted detrimental effects on mitochondria through distinct mechanisms. Osimertinib upregulated the expression of carnitine palmitoyltransferase I (CPTI), while 35d induced the expression of heat shock protein 60 (HSP60). The alterations in ACs and CPTI were correlated with mitochondrial dysfunction and inhibited cell growth. Our results suggest that osimertinib and 35d disrupted the fatty acyl metabolism and induced mitochondrial stress in cancer cells. This study provides insights into the potential application of fatty acyl metabolism inhibitors, such as osimertinib or other TKIs, and mitochondrial stress inducers, such as curcumin derivatives, as combination therapy for cancer.PMID:37569564 | DOI:10.3390/ijms241512190

Int J Mol Sci. 2023 Jul 29;24(15):12147. doi: 10.3390/ijms241512147.ABSTRACTCucumber is an important vegetable crop, and grafts often affect the quality and wax loss in cucumber fruit and affect its value. However, their metabolites and molecular mechanisms of action remain unclear. Metabolome and transcriptome analyses were conducted on the fruit peels of self-rooted plants (SR) grafted with white seed pumpkin (WG). The results showed that there were 352 differential metabolites in the fruit peels of the SR and WG. The transcriptome analysis showed 1371 differentially expressed genes (DEGs) between the WG and SR. These differentially expressed genes were significantly enriched in plant hormone signal transduction, cutin, suberin, wax biosynthesis, phenylpropanoid biosynthesis, and zeatin biosynthesis. By analyzing the correlation between differential metabolites and differentially expressed genes, six candidate genes related to the synthesis of glycitein, kaempferol, and homoeriodictyol were identified as being potentially important. Key transcription factors belonging to the TCP and WRKY families may be the main drivers of transcriptional changes in the peel between the SR and WG. The results of this study have provided a basis for the biosynthesis and regulation of wax loss and quality in grafted cucumbers and represents an important step toward identifying the molecular mechanisms of grafting onto cucumber fruit.PMID:37569524 | DOI:10.3390/ijms241512147

Int J Mol Sci. 2023 Jul 28;24(15):12140. doi: 10.3390/ijms241512140.ABSTRACTPotassium humate is a widely used biostimulant known for its ability to enhance growth and improve tolerance to abiotic stress. However, the molecular mechanisms explaining its effects remain poorly understood. In this study, we investigated the mechanism of action of potassium humate using the model plant Arabidopsis thaliana. We demonstrated that a formulation of potassium humate effectively increased the fresh weight accumulation of Arabidopsis plants under normal conditions, salt stress (sodium or lithium chloride), and particularly under osmotic stress (mannitol). Interestingly, plants treated with potassium humate exhibited a reduced antioxidant response and lower proline accumulation, while maintaining photosynthetic activity under stress conditions. The observed sodium and osmotic tolerance induced by humate was not accompanied by increased potassium accumulation. Additionally, metabolomic analysis revealed that potassium humate increased maltose levels under control conditions but decreased levels of fructose. However, under stress, both maltose and glucose levels decreased, suggesting changes in starch utilization and an increase in glycolysis. Starch concentration measurements in leaves showed that plants treated with potassium humate accumulated less starch under control conditions, while under stress, they accumulated starch to levels similar to or higher than control plants. Taken together, our findings suggest that the molecular mechanism underlying the abiotic stress tolerance conferred by potassium humate involves its ability to alter starch content under normal growth conditions and under salt or osmotic stress.PMID:37569516 | DOI:10.3390/ijms241512140

Int J Mol Sci. 2023 Jul 27;24(15):12059. doi: 10.3390/ijms241512059.ABSTRACTImpaired redox homeostasis in the endoplasmic reticulum (ER) may contribute to proinsulin misfolding and thus to activate the unfolded protein response (UPR) and apoptotic pathways, culminating in pancreatic β-cell loss and type 2 diabetes (T2D). The present study was designed to identify differentially expressed genes (DEGs) encoding enzymes for glutathione metabolism and their impact on the expression levels of genes regulating protein folding and UPR in β-cells of T2D patients. The GEO transcriptome datasets of β-cells of diabetics and non-diabetics, GSE20966 and GSE81608, were analyzed for 142 genes of interest using limma and GREIN software, respectively. Diabetic β-cells showed dataset-specific patterns of DEGs (FDR ≤ 0.05) implicated in the regulation of glutathione metabolism (ANPEP, PGD, IDH2, and CTH), protein-folding (HSP90AB1, HSP90AA1, HSPA1B, HSPA8, BAG3, NDC1, NUP160, RLN1, and RPS19BP1), and unfolded protein response (CREB3L4, ERP27, and BID). The GCLC gene, encoding the catalytic subunit of glutamate-cysteine ligase, the first rate-limiting enzyme of glutathione biosynthesis, was moderately down-regulated in diabetic β-cells from both datasets (p ≤ 0.05). Regression analysis established that genes involved in the de novo synthesis of glutathione, GCLC, GCLM, and GSS affect the expression levels of genes encoding molecular chaperones and those involved in the UPR pathway. This study showed for the first time that diabetic β-cells exhibit alterations in the expression of genes regulating glutathione metabolism, protein-folding, and UPR and provided evidence for the molecular crosstalk between impaired redox homeostasis and abnormal protein folding, underlying ER stress in type 2 diabetes.PMID:37569434 | DOI:10.3390/ijms241512059

Int J Mol Sci. 2023 Jul 27;24(15):12053. doi: 10.3390/ijms241512053.ABSTRACTDiabetic retinopathy (DR) is a microvascular complication of diabetes mellitus (DM) which is the main cause of vision loss in the working-age population. Currently known risk factors such as age, disease duration, and hemoglobin A1c lack sufficient efficiency to distinguish patients with early stages of DR. A total of 194 plasma samples were collected from patients with type 2 DM and DR (moderate to proliferative (PDR) or control (no or mild DR) matched for age, gender, diabetes duration, HbA1c, and hypertension. Untargeted lipidomic and metabolomic approaches were performed. Partial-least square methods were used to analyze the datasets. Levels of 69 metabolites and 85 lipid species were found to be significantly different in the plasma of DR patients versus controls. Metabolite set enrichment analysis indicated that pathways such as metabolism of branched-chain amino acids (methylglutaryl carnitine p = 0.004), the kynurenine pathway (tryptophan p < 0.001), and microbiota metabolism (p-Cresol sulfate p = 0.004) were among the most enriched deregulated pathways in the DR group. Moreover, Glucose-6-phosphate (p = 0.001) and N-methyl-glutamate (p < 0.001) were upregulated in DR. Subgroup analyses identified a specific signature associated with PDR, macular oedema, and DR associated with chronic kidney disease. Phosphatidylcholines (PCs) were dysregulated, with an increase of alkyl-PCs (PC O-42:5 p < 0.001) in DR, while non-ether PCs (PC 14:0-16:1, p < 0.001; PC 18:2-14:0, p < 0.001) were decreased in the DR group. Through an unbiased multiomics approach, we identified metabolites and lipid species that interestingly discriminate patients with or without DR. These features could be a research basis to identify new potential plasma biomarkers to promote 3P medicine.PMID:37569425 | DOI:10.3390/ijms241512053

Int J Mol Sci. 2023 Jul 27;24(15):12021. doi: 10.3390/ijms241512021.ABSTRACTGraviola (Annona muricata) is a tropical plant with many traditional ethnobotanic uses and pharmacologic applications. A metabolomic study of both aqueous and DMSO extracts from Annona muricata leaves recently allowed us to identify dozens of bioactive compounds. In the present study, we use a proteomic approach to detect altered patterns in proteins on both conditioned media and extracts of HT-1080 fibrosarcoma cells under treatment conditions, revealing new potential bioactivities of Annona muricata extracts. Our results reveal the complete sets of deregulated proteins after treatment with aqueous and DMSO extracts from Annona muricata leaves. Functional enrichment analysis of proteomic data suggests deregulation of cell cycle and iron metabolism, which are experimentally validated in vitro. Additional experimental data reveal that DMSO extracts protect HT-1080 fibrosarcoma cells and HMEC-1 endothelial cells from ferroptosis. Data from our proteomic study are available via ProteomeXchange with identifier PXD042354.PMID:37569395 | DOI:10.3390/ijms241512021

Int J Mol Sci. 2023 Jul 26;24(15):12000. doi: 10.3390/ijms241512000.ABSTRACTCardiac complications are frequently found following a stroke in humans whose pathophysiological mechanism remains poorly understood. We used machine learning to analyse a large set of data from a metabolipidomic study assaying 630 metabolites in a rat stroke model to investigate metabolic changes affecting the heart within 72 h after a stroke. Twelve rats undergoing a stroke and 28 rats undergoing the sham procedure were investigated. A plasmatic signature consistent with the literature with notable lipid metabolism remodelling was identified. The post-stroke heart showed a discriminant metabolic signature, in comparison to the sham controls, involving increased collagen turnover, increased arginase activity with decreased nitric oxide synthase activity as well as an altered amino acid metabolism (including serine, asparagine, lysine and glycine). In conclusion, these results demonstrate that brain injury induces a metabolic remodelling in the heart potentially involved in the pathophysiology of stroke heart syndrome.PMID:37569376 | DOI:10.3390/ijms241512000

Foods. 2023 Jul 28;12(15):2878. doi: 10.3390/foods12152878.ABSTRACTThis study aimed to compare the in vitro fermentation characteristics of polysaccharides from Bergamot and Laoxianghuang (fermented 1, 3, and 5 years from bergamot) using the stable in vitro human gut fermentation model. Results showed that bergamot polysaccharide (BP) and Laoxianghuang polysaccharides (LPs) with different surface topographies were characterized as mannorhamnan (comprising Mannose and Rhamnose) and polygalacturonic acid (comprising Galacturonic acid and Galactose), respectively. The distinct effects on the gut microbiota and metabolome of BP and LPs may be due to their different monosaccharide compositions and surface morphologies. BP decreased harmful Fusobacterium and promoted beneficial Bifidobacterium, which was positively correlated with health-enhancing metabolites such as acetic acid, propionic acid, and pyridoxamine. Lactobacillus, increased by LPs, was positively correlated with 4-Hydroxybenzaldehyde, acetic acid, and butyric acid. Overall, this study elucidated gut microbiota and the metabolome regulatory discrepancies of BP and LPs, potentially contributing to their development as prebiotics in healthy foods.PMID:37569146 | DOI:10.3390/foods12152878

Cancers (Basel). 2023 Aug 7;15(15):4002. doi: 10.3390/cancers15154002.ABSTRACTBACKGROUND: Glioblastoma (GB) is a malignant brain tumour that is challenging to treat, often relapsing even after aggressive therapy. Evaluating therapy response relies on magnetic resonance imaging (MRI) following the Response Assessment in Neuro-Oncology (RANO) criteria. However, early assessment is hindered by phenomena such as pseudoprogression and pseudoresponse. Magnetic resonance spectroscopy (MRS/MRSI) provides metabolomics information but is underutilised due to a lack of familiarity and standardisation.METHODS: This study explores the potential of spectroscopic imaging (MRSI) in combination with several machine learning approaches, including one-dimensional convolutional neural networks (1D-CNNs), to improve therapy response assessment. Preclinical GB (GL261-bearing mice) were studied for method optimisation and validation.RESULTS: The proposed 1D-CNN models successfully identify different regions of tumours sampled by MRSI, i.e., normal brain (N), control/unresponsive tumour (T), and tumour responding to treatment (R). Class activation maps using Grad-CAM enabled the study of the key areas relevant to the models, providing model explainability. The generated colour-coded maps showing the N, T and R regions were highly accurate (according to Dice scores) when compared against ground truth and outperformed our previous method.CONCLUSIONS: The proposed methodology may provide new and better opportunities for therapy response assessment, potentially providing earlier hints of tumour relapsing stages.PMID:37568818 | DOI:10.3390/cancers15154002