PubMed

Front Pharmacol. 2024 Dec 2;15:1402448. doi: 10.3389/fphar.2024.1402448. eCollection 2024.ABSTRACTINTRODUCTION: The Xihuang Pill (XHP), a venerated traditional Chinese medicine, has demonstrated significant anti-cancer capabilities. Despite its proven efficacy, the scarcity of comprehensive pharmacological studies limits the widespread application of XHP. This research endeavor seeks to demystify the therapeutic underpinnings of XHP, particularly in the realm of colorectal cancer (CRC) therapy.METHODS: In this study, mice harboring CT26 tumors were divided into four groups, each administered with either XHP monotherapy, 5-fluorouracil (5-FU), or a combination of both. The tumor growth trajectory was closely monitored to evaluate the effectiveness of these anti-neoplastic interventions. Advanced techniques, including 16S-rDNA gene sequencing and ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), were harnessed to scrutinize the gut microbiota and serum metabolite profiles. Immunohistochemical assays were employed to gauge the expression levels of CD4, CD8, and Foxp3, thereby providing insights into the dynamics of tumor-infiltrating lymphocytes within the tumor microenvironment.RESULTS: Our findings indicate that XHP effectively suppresses the initiation and progression of colorectal tumors. The combinatorial therapy of XHP with 5-FU exhibited an enhanced inhibitory effect on tumor growth. Metabolic profiling revealed that XHP induced notable metabolic shifts, particularly impacting pathways such as steroid hormone synthesis, arachidonic acid metabolism, purine biosynthesis, and renin secretion. Notably, 17α-ethinyl estradiol and α-ergocryptine were identified as serum metabolites with the most substantial increase following XHP administration. Analysis of the gut microbiome suggested that XHP promoted the expansion of specific bacterial taxa, including Lachnospiraceae_NK4A136_group, Clostridiales, Desulfovibrionaceae, and Anaerotignum_sp., while suppressing the proliferation of others such as Ligilactobacilus, Lactobacillus_taiwanensis, and Candidatus_saccharimonas. Immunohistochemical staining indicated an upregulation of CD4 and CD8 post-XHP treatment.CONCLUSION: This study delineates a potential mechanism by which XHP inhibits CRC tumorigenesis through modulating the gut microbiota, serum metabolites, and reshaping the tumor immune microenvironment in a murine CRC model. These findings contribute to a more profound understanding and potentially broaden the clinical utility of XHP in oncology.PMID:39687297 | PMC:PMC11646767 | DOI:10.3389/fphar.2024.1402448

Heliyon. 2024 Nov 28;10(23):e40768. doi: 10.1016/j.heliyon.2024.e40768. eCollection 2024 Dec 15.ABSTRACTThe tea moth pest, Agriophara rhombata is an economically important and highly damaging pest that drastically affects tea plant leaves. The chemical composition of its pheromone glands metabolites before and during calling period has not been reported yet. Therefore, the present study aimed at the metabolomic profiling of female moths' sex pheromones glands before and during calling period using gas chromatography time-of-flight mass spectrometry. A total of 114 significant differentially expressed metabolites were identified including 54 up- and 70 down-regulated metabolites in pheromone glands of the female moth. Two of the important previously recognized moth pheromones were identified including E,Z-5,7-dodecadien-1-ol acetate and Z-12-Octadecen-1-ol acetate, which were downregulated. The top ten up-regulated metabolites were "dodecanamide", "tetradecanamide", "2-propyn-1-amine, N,N-dimethyl", "cyclohexane, (1-methylethyl)", "tetradecane, 2-methyl", "1-cyclopentyleicosane", "cyclohexane, octyl", "1-decan-3-one", "cyclopentane, decyl" and "cyclopentadecane". In conclusion, while most of the identified compounds have not previously been identified as primary pheromones in moths, their differential expression in A. rhombata's pheromone glands during the calling period strongly suggests their supporting roles in the synthesis, stabilization, or release of the active pheromone components.PMID:39687108 | PMC:PMC11648114 | DOI:10.1016/j.heliyon.2024.e40768

Front Endocrinol (Lausanne). 2024 Dec 2;15:1481364. doi: 10.3389/fendo.2024.1481364. eCollection 2024.ABSTRACTBACKGROUND: Central precocious puberty (CPP) is characterized by the premature activation of the hypothalamic-pituitary-gonadal axis, resulting in early onset of sexual development. The incidence of CPP has been rising in recent years, with approximately 90% of cases lacking a clearly identifiable etiology. While an association between precocious puberty and gut microbiota has been observed, the precise causal pathways and underlying mechanisms remain poorly understood. The study aims to investigate the potential mechanisms through which gut microbiota imbalances may contribute to CPP.METHODS: In this study, clinical information and fecal samples were collected from 50 CPP patients and 50 healthy control subjects. The fecal samples were analyzed by 16S rDNA sequencing and UPLC-MS/MS metabolic analysis. Spearman correlation analysis was used to identify the relationships between gut microbiota and metabolites.RESULTS: The gut microbiota composition in CPP patients was significantly different from that in healthy controls, characterized by an increased abundance of Faecalibacterium and a decreased abundance of Anaerotruncus. Additionally, significant differences were observed in metabolite composition between the CPP and control groups. A total of 51 differentially expressed metabolites were identified, with 32 showing significant upregulation and 19 showing significant downregulation in the CPP group. Furthermore, Spearman correlation analysis indicated that gut microbiota dysbiosis may contribute to altered metabolic patterns in CPP, given its involvement in the regulation of several metabolic pathways, including phenylalanine and tyrosine biosynthesis and metabolism, the citrate cycle (TCA cycle), glyoxylate and dicarboxylate metabolism, and tryptophan metabolism.CONCLUSIONS: The study revealed the gut microbial and metabolite characteristics of CPP patients by integrating microbiome and metabolomics analyses. Moreover, several key metabolic pathways involved in the onset and progression of CPP were identified, which were regulated by gut microbiota. These findings broaden the current understanding of the complex interactions between gut microbial metabolites and CPP, and provide new insights into the pathogenesis and clinical management of CPP.PMID:39687078 | PMC:PMC11646730 | DOI:10.3389/fendo.2024.1481364

PeerJ. 2024 Dec 13;12:e18506. doi: 10.7717/peerj.18506. eCollection 2024.ABSTRACTOBJECTIVE: To characterize the bile acid metabolomic profiles of umbilical cord blood and meconium in healthy newborns.METHODS: Fifteen healthy newborns, which born in the Obstetrics Department of the Affiliated Hospital of Southwest Medical University between July 1 and August 31, 2023, were selected as study subjects. Umbilical cord blood and meconium samples were collected, and bile acid metabolomics were analyzed using ultra-high performance liquid chromatography-tandem mass spectrometry.RESULTS: The ratio of primary to secondary bile acids in cord blood was significantly higher than in meconium [2.64 (2.49, 5.70) vs. 0.99 (0.37, 1.58), Z = -3.80, P < 0.05]. The ratio of unconjugated to conjugated bile acids was notably higher in cord blood than in meconium [0.14 (0.07, 0.18) vs. 0.01 (0.01, 0.04), Z = -3.88, P < 0.05]. The ratio of cholic acid to chenodeoxycholic acid in conjugated primary bile acids was significantly lower in cord blood than in meconium [0.59 (0.19, 0.75) vs. 2.21 (1.34, 3.04), Z = -4.21, P < 0.05], but the ratio of cholic acid to chenodeoxycholic acid in secondary bile acids was significantly higher in cord blood than in meconium [0.42 (0.21, 0.63) vs. 0.03 (0.01, 0.05), Z = -4.54, P < 0.05]. Only three primary bile acids (taurochenodeoxycholic acid, glycochenodeoxycholic acid, and glycochenodeoxycholic acid 3-glucoside in umbilical cord blood) were correlated with their downstream metabolites in meconium (with hyodesoxycholic acid (r = -0.66, P = 0.01), tauro-ω-muricholic acid (r = 0.52, P = 0.048) and ursodeoxycholic acid-7S (r = -0.53, P = 0.04), respectively). In meconium, most of primary bile acids were correlated with their downstream metabolites (P all < 0.05): cholic acid was positively correlated with 3-dehydrocholic acid, taurocholic acid was positively correlated with taurodeoxycholic acid and 3-dehydrocholic acid, glycocholic acid was positively correlated with 3-dehydrocholic acid, chenodeoxycholic acid was positively correlated with glycoursodeoxycholic acid, taurolithocholic acid, and 7-keto lithocholic acid and negatively correlated with isolithocholic acid. Taurochenodeoxycholic acid was positively correlated with taurohyodeoxycholic acid, tauroursodeoxycholic acid, glycoursodeoxycholic acid, taurolithocholic acid, tauro-ω-muricholic acid, and glycohyodeoxycholic acid, while glycochenodeoxycholic acid was positively correlated with tauroursodeoxycholic acid, glycoursodeoxycholic acid, taurolithocholic acid, and glycohyodeoxycholic acid, and negatively correlated with isolithocholic acid.CONCLUSION: The bile acid metabolites in umbilical cord blood and meconium differ significantly, and the downstream bile acid metabolites in meconium are predominantly correlated with their upstream bile acids in meconium, but not those bile acids in umbilical cord blood. These findings contribute to a better understanding of bile acid metabolism in utero and lay the foundation for future research in this topic.PMID:39686994 | PMC:PMC11648689 | DOI:10.7717/peerj.18506

J Neurotrauma. 2024 Dec 17. doi: 10.1089/neu.2024.0385. Online ahead of print.ABSTRACTFollowing spinal cord injury (SCI), there is a short-lived recovery phase that ultimately plateaus. Understanding changes within the spinal cord over time may facilitate targeted approaches to prevent and/or reverse this plateau and allow for continued recovery. Untargeted metabolomics revealed distinct metabolic profiles within the injured cord during recovery (7 days postinjury [DPI]) and plateau (21 DPI) periods in a mouse model of severe contusion SCI. Alterations in lipid metabolites, particularly those involved in phospholipid (PL) metabolism, largely contributed to overall differences. PLs are hydrolyzed by phospholipases A2 (PLA2s), yielding lysophospholipids (LPLs) and fatty acids (FAs). PL metabolites decreased between 7 and 21 DPI, whereas LPLs increased at 21 DPI, suggesting amplified PL metabolism during the plateau phase. Expression of various PLA2s also differed between the two time points, further supporting dysregulation of PL metabolism during the two phases of injury. FAs, which can promote inflammation, mitochondrial dysfunction, and neuronal damage, were increased regardless of time point. Carnitine can bind with FAs to form acylcarnitines, lessening FA-induced toxicity. In contrast to FAs, carnitine and acylcarnitines were increased at 7 DPI, but decreased at 21 DPI, suggesting a loss of carnitine-mediated mitigation of FA toxicity at the later time point, which may contribute to the cessation of recovery post-SCI. Alterations in oxidative phosphorylation and tricarboxylic acid cycle metabolites were also observed, indicating persistent although dissimilar disruptions in mitochondrial function. These data aid in increasing our understanding of lipid metabolism following SCI and have the potential to lead to new biomarkers and/or therapeutic strategies.PMID:39686743 | DOI:10.1089/neu.2024.0385

Adv Sci (Weinh). 2024 Dec 16:e2410056. doi: 10.1002/advs.202410056. Online ahead of print.ABSTRACTIntraventricular hemorrhage in preterm neonates has become a major global health problem and is associated with a high risk of post-hemorrhagic hydrocephalus (PHH). Identifying diagnostic markers and therapeutic targets is a focal challenge in the PHH prevention and control. Here, this study applies multi-omics analyses to characterize the biochemical, proteomic, and metabolomic profiles of the cerebrospinal fluid (CSF) in clinical human cohorts to investigate disease development and recovery processes occurring due to PHH. Integrative multiomics analysis suggests that the over-representation of ferroptosis, calcium, calcium ion binding, and cell adhesion signaling pathways is associated with PHH. Bioinformatic analysis indicates that chondroitin sulfate proteoglycan 4 (CSPG4) is discovered as a CSF biomarker and positively correlated with the ventricular size and the rate of periventricular leukomalacia. Next, it is further demonstrated that these signaling pathways are dysregulated in the choroid plexus (ChP) in PHH by using in vitro cellular experiments and rat models of PHH, whereas CSPG4 silencing can suppress ferroptosis, cell adhesion function, and the intracellular flow of Ca2+. These findings broaden the understanding of the pathophysiological mechanisms of PHH and suggest that CSPG4 may be an effective therapeutic target for PHH.PMID:39686677 | DOI:10.1002/advs.202410056

J Food Sci. 2024 Dec 16. doi: 10.1111/1750-3841.17609. Online ahead of print.ABSTRACTOlive oil polyphenol hydroxytyrosol (HT) significantly repairs intestinal barrier function, but its absorption in the stomach and small intestine is limited. The metabolites of unabsorbed HT that reach the colon are crucial, yet their effects on colonic microbiota and intestinal barrier repair remain unclear. This study utilized in vitro simulated digestion and colonic fecal fermentation to investigate HT's digestion and fermentation. Results indicated that 79.25% of HT potentially reached the colon intact. Further 16S rDNA, targeted, and untargeted metabolomics analyses showed that HT can be decomposed by colonic microbiota, producing aromatic hydrocarbon metabolites and regulating gut microbiota structure. It promotes the growth of gut microbiota, such as Bacteroides, Faecalibacterium, Klebsiella, and Lachnospira, which degrade HT. Additionally, HT's intervention conversely affected the production of tryptophan-derived metabolites and short-chain fatty acids (SCFAs). Subsequently, computer-simulated molecular docking technology was used to simulate the binding affinity between HT metabolites and derived metabolites and the intestinal barrier repair-related receptor aryl hydrocarbon receptor (AhR). Indole-3-acetic acid, indole-3-acetaldehyde, skatole, kynurenine, and homovanillic acid could tightly bind to the amino acid residues of the AhR receptor, with binding energies all ˂-6.0 kcal/mol, suggesting that these metabolites may enhance the intestinal barrier function through the AhR signaling pathway.PMID:39686652 | DOI:10.1111/1750-3841.17609

J Clin Med. 2024 Dec 4;13(23):7390. doi: 10.3390/jcm13237390.ABSTRACTBackground/Objectives: Varicoceles are a common contributor to male infertility, significantly impacting male-factor infertility cases. Traditional diagnostic methods often lack the sensitivity to detect the molecular and cellular disruptions caused by varicoceles, limiting the development of effective, personalized treatments. This narrative review aims to explore the advancements in proteomics and metabolomics as innovative, non-invasive diagnostic tools for varicocele-associated male infertility and their potential in guiding personalized therapeutic strategies. Methods: A comprehensive literature search was conducted using databases such as PubMed, Scopus, and Web of Science up to October 2024. Studies focusing on the application of proteomic and metabolomic analyses in varicocele-associated male infertility were selected. The findings were critically analyzed to synthesize current knowledge and identify future research directions. Results: Proteomic analyses revealed differentially expressed proteins in the sperm and seminal plasma of varicocele patients, revealing disruptions in pathways related to oxidative stress, mitochondrial dysfunction, apoptosis, and energy metabolism. Key proteins such as heat shock proteins, mitochondrial enzymes, and apoptotic regulators were notably altered. Metabolomic profiling uncovered specific metabolites in seminal plasma-such as decreased levels of lysine, valine, and fructose-that correlate with impaired sperm function and fertility potential. The integration of proteomic and metabolomic data provides a comprehensive molecular fingerprint of varicocele-induced infertility, facilitating the identification of novel biomarkers for early diagnosis and the development of personalized therapeutic interventions. Conclusions: Advances in proteomics and metabolomics have significantly enhanced our understanding of the molecular mechanisms underlying varicocele-associated male infertility. These "omics" technologies hold great promise for improving diagnostic accuracy and personalizing treatment, ultimately leading to better outcomes for affected men. Future large-scale clinical trials and validations are essential to confirm these biomarkers and facilitate their integration into routine clinical practice.PMID:39685846 | DOI:10.3390/jcm13237390

Int J Mol Sci. 2024 Dec 8;25(23):13190. doi: 10.3390/ijms252313190.ABSTRACTMetabolomics has come to the fore as an efficient tool in the search for biomarkers that are critical for precision health approaches and improved diagnostics. This review will outline recent advances in biomarker discovery based on metabolomics, focusing on metabolomics biomarkers reported in cancer, neurodegenerative disorders, cardiovascular diseases, and metabolic health. In cancer, metabolomics provides evidence for unique oncometabolites that are important for early disease detection and monitoring of treatment responses. Metabolite profiling for conditions such as neurodegenerative and mental health disorders can offer early diagnosis and mechanisms into the disease especially in Alzheimer's and Parkinson's diseases. In addition to these, lipid biomarkers and other metabolites relating to cardiovascular and metabolic disorders are promising for patient stratification and personalized treatment. The gut microbiome and environmental exposure also feature among the influential factors in biomarker discovery because they sculpt individual metabolic profiles, impacting overall health. Further, we discuss technological advances in metabolomics, current clinical applications, and the challenges faced by metabolomics biomarker validation toward precision medicine. Finally, this review discusses future opportunities regarding the integration of metabolomics into routine healthcare to enable preventive and personalized approaches.PMID:39684900 | DOI:10.3390/ijms252313190

Int J Mol Sci. 2024 Dec 6;25(23):13115. doi: 10.3390/ijms252313115.ABSTRACTFollicular-patterned thyroid neoplasms comprise a diverse group of lesions that pose significant challenges in terms of differential diagnosis based solely on morphologic and genetic features. Thus, the identification of easily testable biomarkers complementing microscopic and genetic analyses is a highly anticipated advancement that could improve diagnostic accuracy, particularly for noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTPs). These tumors exhibit considerable morphological and molecular heterogeneity, which may complicate their distinction from structurally similar neoplasms, especially when genetic analyses reveal shared genomic alterations (e.g., RAS mutations). Here, we integrated next-generation sequencing (NGS) with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to perform a proteogenomic analysis on 85 NIFTPs (n = 30 RAS-mutant [RAS-mut] and n = 55 RAS-wild type [RAS-wt]), with the aim to detect putative biomarkers of RAS-mut lesions. Through this combined approach, we identified four proteins that were significantly underexpressed in RAS-mut as compared to RAS-wt NIFTPs. These proteins could serve as readily accessible markers in morphologically borderline cases showing RAS mutations. Additionally, our findings may provide insights into the distinct pathogenic pathways through which RAS-mut and RAS-wt NIFTPs arise, highlighting the pivotal role of constitutive RAS-mitogen-activated protein kinase (MAPK) pathway activation in the development and progression of RAS-mut tumors.PMID:39684824 | DOI:10.3390/ijms252313115

Int J Mol Sci. 2024 Dec 5;25(23):13077. doi: 10.3390/ijms252313077.ABSTRACTMass spectral identification (in particular, in metabolomics) can be refined by comparing the observed and predicted properties of molecules, such as chromatographic retention. Significant advancements have been made in predicting these values using machine learning and deep learning. Usually, model predictions do not contain any indication of the possible error (uncertainty) or only one criterion is used for this purpose. The spread of predictions of several models included in the ensemble, and the molecular similarity of the considered molecule and the most "similar" molecule from the training set, are values that allow us to estimate the uncertainty. The Euclidean distance between vectors, calculated based on real-valued molecular descriptors, can be used for the assessment of molecular similarity. Another factor indicating uncertainty is the molecule's belonging to one of the clusters (data set clustering). Together, all three factors can be used as features for the uncertainty assessment model. Classification models that predict whether a prediction belongs to the worst 15% were obtained. The area under the receiver operating curve value is in the range of 0.73-0.82 for the considered tasks: the prediction of retention indices in gas chromatography, retention times in liquid chromatography, and collision cross-sections in ion mobility spectroscopy.PMID:39684785 | DOI:10.3390/ijms252313077

Int J Mol Sci. 2024 Dec 5;25(23):13067. doi: 10.3390/ijms252313067.ABSTRACTMetabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is the most common chronic liver disorder in Western countries, encompassing a range of conditions from steatosis to Metabolic Dysfunction-Associated Steatohepatitis (MASH), which can potentially progress to cirrhosis. Lipidomics approaches have revealed significant alterations in the hepatic lipidome associated with both steatosis and steatohepatitis, with these changes correlating with disease manifestation. While the transition from steatosis to MASH remains poorly understood, recent research indicates that both the quantity and quality of deposited lipids play a pivotal role in MASLD progression. In our study, we utilized untargeted and targeted analyses to identify intact lipids and fatty acids in liver biopsies from healthy controls and MASLD patients, categorized based on their histological findings. In total, 447 lipid species were identified, with 215 subjected to further statistical analysis. Univariate and multivariate analyses revealed alterations in triglyceride species and fatty acids, including FA 16:0, FA 16:1, FA 18:3 n6, the sum of MUFA, and the Δ9-desaturase activity ratio. This research provides insights into the connection between dysregulated lipid metabolism in the progression of MASLD, supporting previous findings. Further studies on lipid metabolism could improve risk assessment methods, particularly given the current limited understanding of the transition from steatosis to MASH.PMID:39684777 | DOI:10.3390/ijms252313067

Int J Mol Sci. 2024 Dec 4;25(23):13029. doi: 10.3390/ijms252313029.ABSTRACTBreast cancer is a global concern as a leading cause of death for women. Early and precise diagnosis can be vital in handling the disease efficiently. Breast cancer subtyping based on estrogen receptor (ER) status is crucial for determining prognosis and treatment. This study uses metabolomics data from plasma samples to detect metabolite biomarkers that could distinguish ER-positive from ER-negative breast cancers in a non-invasive manner. The dataset includes demographic information, ER status, and metabolite levels from 188 breast cancer patients and 73 healthy controls. Recursive Feature Elimination (RFE) with a Random Forest (RF) classifier identified an optimal subset of 30 features-29 biomarkers and age-that achieved the highest area under the curve (AUC). To address the class imbalance, Gaussian noise-based augmentation and Adaptive Synthetic Oversampling (ADASYN) were applied, ensuring balanced representation during training. Four machine learning (ML) algorithms-Random Forest, Support Vector Classifier (SVC), XGBoost, and Logistic Regression (LR)-were evaluated using grid search. The Random Forest classifier emerged as the top performer, achieving an AUC of 0.95 and an accuracy of 93%. These results suggest that ML has great promise for identifying specific metabolites linked to ER expression, paving the development of a novel analytical tool that can minimize current challenges in identifying ER status, and improve the precision of breast cancer subtyping.PMID:39684741 | DOI:10.3390/ijms252313029

Int J Mol Sci. 2024 Nov 30;25(23):12905. doi: 10.3390/ijms252312905.ABSTRACTMetabolomic data often present challenges due to high dimensionality, collinearity, and variability in metabolite concentrations. Machine learning (ML) application in metabolomic analyses is enabling the extraction of meaningful information from complex data. Bringing together domain-specific knowledge from metabolomics with explainable ML methods can refine the predictive performance and interpretability of models used in atherosclerosis research. In this work, we aimed to identify the most impactful metabolites associated with the presence of atherosclerotic cardiovascular disease (ASCVD) in cross-sectional case-control studies using explainable ML methods integrated with metabolomics domain knowledge. For this, a subset from the FLEMENGHO cohort with metabolomic data available was used as the training cohort, including 63 patients with a history of ASCVD and 52 non-smoking controls matched by age, sex, and body mass index from the same population. First, Partial Least Squares Discriminant Analysis (PLS-DA) was applied for dimensionality reduction. The selected metabolites' correlations were analyzed by considering their chemical categorization. Then, eXtreme Gradient Boosting (XGBoost) was used to identify metabolites that characterize ASCVD. Next, the selected metabolites were evaluated in an external cohort to determine their effectiveness in distinguishing between cases and controls. A total of 56 metabolites were selected for ASCVD discrimination using PLS-DA. The primary identified metabolites' superclasses included lipids, organic acids, and organic oxygen compounds. Upon integrating these metabolites with the XGBoost model, the classification yielded a test area under the curve (AUC) of 0.75. SHAP analyses ranked cholesterol, 3-methylhistidine, and glucuronic acid among the most impactful features and showed the diversity of metabolites considered for building the ASCVD discriminator. Also using XGBoost, the selected metabolites achieved an AUC of 0.93 in an independent external validation cohort. In conclusion, the combination of different metabolites has the potential to build classifiers for ASCVD. Integrating metabolite categorization within the SHAP analysis further enhanced the interpretability of the model, offering insights into metabolite-specific contributions to ASCVD risk.PMID:39684618 | DOI:10.3390/ijms252312905

Int J Mol Sci. 2024 Nov 30;25(23):12910. doi: 10.3390/ijms252312910.ABSTRACTAutoimmune uveitis is a relapsing blind-causing ocular condition with complex pathogenesis that is not completely understood. There is a high demand for accurate animal models of experimental autoimmune uveitis (EAU) suitable for elucidating the molecular mechanisms of the disease and testing new therapeutic approaches. Here, we demonstrated that photoreceptor Ca2+/Zn2+-sensor protein recoverin is a uveoretinal antigen in albino rabbits provoking typical autoimmune chorioretinitis 2-4 weeks after immunization. The pathologic process in recoverin-induced EAU shared features with human disease and included lymphocytic infiltration of the retina, Dalen-Fuchs nodules and foci of subtotal or total retinal atrophy, manifested as a decrease in amplitude of the a-wave of the electroretinogram. In some cases, changes in the retinal vascular pattern and subretinal hemorrhages were also observed. These signs were accompanied by a gradual accumulation of serum antibodies against recoverin. Biochemical examination of the aqueous humor (AH) revealed typical characteristics of inflammation and oxidative stress, including increased levels of TNF-α and IL-6 and decreased levels of IL-10, as well as decreased total antioxidant activity, superoxide dismutase and glutathione peroxidase activities, and increased zinc concentration. Consistently, metabolomic and targeted lipidomic analysis of AH showed high lactate and low ascorbic acid levels in early EAU; increased levels of key pro-inflammatory signaling lipids such as PGE2, TXB2, 11-HETE and Lyso-PAF; and reduced levels of the anti-inflammatory fatty acid DHA in advanced stages of the disease. Uveitic AH became enriched with recoverin, confirming disruption of the blood-ocular barrier and photoreceptor damage. Notably, the application of mitochondria-targeted antioxidant therapy impeded EAU progression by maintaining local antioxidant activity and suppressing TNF-α, IL-6 and PGE2 signaling. Overall, our results demonstrate that recoverin-induced EAU in rabbits represents an accurate model of human autoimmune posterior uveitis and suggest new directions for its therapy that can be trialed using the developed model.PMID:39684616 | DOI:10.3390/ijms252312910

Int J Mol Sci. 2024 Nov 30;25(23):12901. doi: 10.3390/ijms252312901.ABSTRACTPuromycin (Puro) is a natural aminonucleoside antibiotic that inhibits protein synthesis by its incorporation into elongating peptide chains. The unique mechanism of Puro finds diverse applications in molecular biology, including the selection of genetically engineered cell lines, in situ protein synthesis monitoring, and studying ribosome functions. However, the key step of Puro biosynthesis remains enigmatic. In this work, pur6-guided genome mining is carried out to explore the natural diversity of Puro-like antibiotics. The diversity of biosynthetic gene cluster (BGC) architectures suggests the existence of distinct structural analogs of puromycin encoded by pur-like clusters. Moreover, the presence of tRNACys in some BGCs, i.e., cst-like clusters, leads us to the hypothesis that Pur6 utilizes aminoacylated tRNA as an activated peptidyl precursor, resulting in cysteine-based analogs. Detailed metabolomic analysis of Streptomyces sp. VKM Ac-502 containing cst-like BGC revealed the production of a cysteinyl-based analog of Puro-cystocin (Cst). Similar to puromycin, cystocin inhibits both prokaryotic and eukaryotic translation by the same mechanism. Aminonucleoside N-acetyltransferase CstC inactivated Cst, mediating antibiotic resistance in genetically modified bacteria and human cells. The substrate specificity of CstC originated from the steric hindrance of its active site. We believe that novel aminonucleosides and their inactivating enzymes can be developed through the directed evolution of the discovered biosynthetic machinery.PMID:39684615 | DOI:10.3390/ijms252312901

Int J Mol Sci. 2024 Nov 29;25(23):12884. doi: 10.3390/ijms252312884.ABSTRACTColored potatoes with red and purple skin or flesh possess significant nutritional value and health benefits due to their rich anthocyanin content. To investigate the genetic mechanisms underlying color formation, the high-anthocyanin-content purple-skinned and purple-fleshed potato line 15-12-16, and the white-skinned and white-fleshed Xiazhai 65 variety were used for ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS) analysis, which was conducted to identify and quantify anthocyanins. RNA sequencing was performed to analyze the transcriptome. The results indicated a significant upregulation of genes within the anthocyanidin biosynthesis pathway in the purple potato, while these genes were either downregulated or absent in the white potato. The bHLH, MYB, and WRKY gene families exhibited a greater number of regulatory members, suggesting their pivotal role in color formation. Integrated analysis of the transcriptional and metabolic revealed that 12 differentially expressed genes (DEGs) related to the anthocyanidin biosynthetic had a significant correlation with 18 anthocyanin metabolites. Notably, the key gene St5GT in the anthocyanidin biosynthesis pathway was markedly upregulated in the purple skin and flesh. Furthermore, the overexpression of St5GT (PGSC0003DMG400004573) in tobacco contributed to anthocyanin accumulation. The expression of 10 DEGs was validated through quantitative real-time PCR. In conclusion, these findings provide new insights into anthocyanin biosynthesis and accumulation in purple potatoes, offering valuable candidate genes for the future breeding of colored potatoes.PMID:39684596 | DOI:10.3390/ijms252312884

Int J Mol Sci. 2024 Nov 28;25(23):12809. doi: 10.3390/ijms252312809.ABSTRACTFrom a detailed review of 90 experimental and clinical metabolomic investigations of obesity and metabolic dysfunction-associated steatotic liver disease (MASLD), we have developed metabolomic hallmarks for both obesity and MASLD. Obesity studies were conducted in mice, rats, and humans, with consensus biomarker groups in plasma/serum being essential and nonessential amino acids, energy metabolites, gut microbiota metabolites, acylcarnitines and lysophosphatidylcholines (LPC), which formed the basis of the six metabolomic hallmarks of obesity. Additionally, mice and rats shared elevated cholesterol, humans and rats shared elevated fatty acids, and humans and mice shared elevated VLDL/LDL, bile acids and phosphatidylcholines (PC). MASLD metabolomic studies had been performed in mice, rats, hamsters, cows, geese, blunt snout breams, zebrafish, and humans, with the biomarker groups in agreement between experimental and clinical investigations being energy metabolites, essential and nonessential amino acids, fatty acids, and bile acids, which lay the foundation of the five metabolomic hallmarks of MASLD. Furthermore, the experimental group had higher LPC/PC and cholesteryl esters, and the clinical group had elevated acylcarnitines, lysophosphatidylethanolamines/phosphatidylethanolamines (LPE/PE), triglycerides/diglycerides, and gut microbiota metabolites. These metabolomic hallmarks aid in the understanding of the metabolic role played by obesity in MASLD development, inform mechanistic studies into underlying disease pathogenesis, and are critical for new metabolite-inspired therapies.PMID:39684520 | DOI:10.3390/ijms252312809

Int J Mol Sci. 2024 Nov 27;25(23):12770. doi: 10.3390/ijms252312770.ABSTRACTThe skin hydration level is a key factor that influences the physical and mechanical properties of the skin. The stratum corneum (SC), the outermost layer of the epidermis, is responsible for the skin's barrier function. In this study, we investigated the role of a unique composition of Viola yedoensis extract for its ability to activate CD44, a cell-surface receptor of hyaluronic acid, and aquaporin-3, a water-transporting protein, in human keratinocytes (HaCaT). An ELISA assay evaluating the protein expression levels of CD44, aquaporin-3 (AQP3), filaggrin, and keratin-10 revealed that V. yedoensis extract upregulated the levels of CD44 and AQP3 by 15% and 78%, respectively. Additionally, V. yedoensis extract demonstrated a comparative effect on water vapor flux in TEWL and lipid perturbation in DSC versus the reference, glycerin. In light of this new biological efficacy, a detailed phytochemical characterization was undertaken using an integrated LC-HRMS/MS-based metabolomics approach, which provided further insights on the chemistry of V. yedoensis. This led to the identification of 29 secondary metabolites, 14 of which are reported here for the first time, including esculetin, aesculin, apigenin and kaempferol C-glycosides, megastigmane glycosides, roseoside, platanionoside B, and an eriojaposide B isomer, along with the rare, calenduloside F and esculetin diglucoside, which are reported for the first time from the genus, Viola. Notably, two active components identified in the V. yedoensis extract, namely, aesculin and schaftoside, showed an upregulation of the protein expression of CD44 in HaCaT cells by 123% and 193% within 24 h of treatment, respectively, while aesculin increased AQP3 levels by 46%. Aesculin and schaftoside also significantly upregulated the expression of K-10 levels by 299% and 116%, which was considerably higher than sodium hyaluronate, the positive control. The rationale used to characterize the new structures is outlined along with the related biosynthetic pathways envisioned to generate roseoside and Eriojaposide B. These findings provide new molecular insights to deepen the understanding of how V. yedoensis extract, along with the biomarkers aesculin and schaftoside, restores the skin barrier and skin hydration benefits.PMID:39684479 | DOI:10.3390/ijms252312770

Int J Mol Sci. 2024 Nov 27;25(23):12744. doi: 10.3390/ijms252312744.ABSTRACTFungal infections pose a growing public health threat, creating an urgent clinical need for new antifungals. Natural products (NPs) from organisms in extreme environments are a promising source for novel drugs. Streptomyces albidoflavus CBMAI 1855 exhibited significant potential in this regard. This study aimed to (1) assess the antifungal spectrum of the CBMAI 1855 extract against key human pathogens, (2) elicit NP production through co-cultivation with fungi, correlating the metabolites with the biosynthetic gene clusters (BGCs), and (3) perform in silico toxicity predictions of the identified compounds to analyze their suitability for drug development. The crude extract of CBMAI 1855 exhibited broad-spectrum antifungal activity. The metabolomic analysis identified antifungal NPs such as antimycin A, fungimycin, surugamides, 9-(4-aminophenyl)-3,7-dihydroxy-2,4,6-trimethyl-9-oxo-nonoic acid, and ikarugamycin, with the latter two predicted to be the most suitable for drug development. Genome mining revealed three cryptic BGCs potentially encoding novel antifungals. These BGCs warrant a detailed investigation to elucidate their metabolic products and harness their potential. CBMAI 1855 is a prolific producer of multiple antifungal agents, offering a valuable source for drug discovery. This study highlights the importance of exploring microbial interactions to uncover therapeutics against fungal infections, with a detailed exploration of cryptic BGCs offering a pathway to novel antifungal compounds.PMID:39684453 | DOI:10.3390/ijms252312744