PubMed

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

Int J Mol Sci. 2024 Nov 26;25(23):12716. doi: 10.3390/ijms252312716.ABSTRACTElaeagnus angustifolia L. can attract adult Asian longhorned beetle (ALB), Anoplophora glabripennis (Motschulsky), and kill their offspring by gum secretion in oviposition scars. This plant has the potential to be used as a dead-end trap tree for ALB management. However, there is a limited understanding of the attraction ability and biochemical defense response of E. angustifolia to ALB. In this study, we conducted host selection experiments with ALB and then performed physiological and biochemical assays on twigs from different tree species before and after ALB feeding. We analyzed the differential metabolites using the liquid chromatograph-mass spectrometer method. The results showed that ALB's feeding preference was E. angustifolia > P.× xiaohei var. gansuensis > P. alba var. pyramidalis. After ALB feeding, the content of soluble sugars, soluble proteins, flavonoids, and tannins decreased significantly in all species. In three comparison groups, a total of 492 differential metabolites were identified (E. angustifolia:195, P.× xiaohei var. gansuensis:255, P. alba var. pyramidalis:244). Differential metabolites were divided into overlapping and specific metabolites for analysis. The overlapping differential metabolites 7-isojasmonic acid, zerumbone, and salicin in the twigs of three tree species showed upregulation after ALB feeding. The specific metabolites silibinin, catechin, and geniposide, in E. angustifolia, significantly increased after being damaged. Differential metabolites enriched in KEGG pathways indicated that ALB feeding activated tyrosine metabolism and the biosynthesis of phenylpropanoids in three tree species, with a particularly high enrichment of differential metabolites in the flavonoid biosynthesis pathway in E. angustifolia. This study provides the metabolic defense strategies of different tree species against ALB feeding and proposes candidate metabolites that can serve as metabolic biomarkers, potentially offering valuable insights into using E. angustifolia as a control measure against ALB.PMID:39684427 | DOI:10.3390/ijms252312716

Int J Mol Sci. 2024 Nov 26;25(23):12681. doi: 10.3390/ijms252312681.ABSTRACTPost-harvest storage loss in sugar beets due to root rot and respiration can cause >20% sugar loss. Breeding strategies focused on factors contributing to improved post-harvest storage quality are of great importance to prevent losses. Using 16S rRNA and ITS sequencing and sugar beet mutational breeding lines with high disease resistance (R), along with a susceptible (S) commercial cultivar, the role of root microbiome and metabolome in storage performance was investigated. The R lines in general showed higher abundances of bacterial phyla, Patescibacteria at the M time point, and Cyanobacteria and Desulfobacterota at the L time point. Amongst fungal phyla, Basidiomycota (including Athelia) and Ascomycota were predominant in diseased samples. Linear discriminant analysis Effect Size (LEfSe) identified bacterial taxa such as Micrococcales, Micrococcaceae, Bacilli, Glutamicibacter, Nesterenkonia, and Paenarthrobacter as putative biomarkers associated with resistance in the R lines. Further functional enrichment analysis showed a higher abundance of bacteria, such as those related to the super pathway of pyrimidine deoxyribonucleoside degradation, L-tryptophan biosynthesis at M and L, and fungi, such as those associated with the biosynthesis of L-iditol 2-dehydrogenase at L in the R lines. Metabolome analysis of the roots revealed higher enrichment of pathways associated with arginine, proline, alanine, aspartate, and glutamate metabolism at M, in addition to beta-alanine and butanoate metabolism at L in the R lines. Correlation analysis between the microbiome and metabolites indicated that the root's biochemical composition, such as the presence of nitrogen-containing secondary metabolites, may regulate relative abundances of key microbial candidates contributing to better post-harvest storage.PMID:39684393 | DOI:10.3390/ijms252312681

Int J Mol Sci. 2024 Nov 26;25(23):12667. doi: 10.3390/ijms252312667.ABSTRACTChronic stress is a key factor in the development of depression. It leads to hyperactivation of the hypothalamic-pituitary-adrenal (HPA) axis, which in turn increases the formation of glucocorticoids (GCs). Chronically elevated GC levels disrupt neuroplasticity and affect brain lipid metabolism, which may, ultimately, contribute to the development of depression. This study aimed to investigate the effects of the antidepressants St. John's Wort extract and escitalopram on lipid metabolism in vivo. Therefore, repeated corticosterone injections were used to induce depression-like behavior in rats. Male Sprague-Dawley rats were stressed with corticosterone injections (40 mg/kg, s.c.) over 22 consecutive days and were concomitantly treated with varying doses of the St. John's wort extract Ze 117 (30, 90 or 180 mg/kg, p.o.) or escitalopram (10 mg/kg, p.o.) and behavioral changes were evaluated using a modified forced swim test. The results indicate that repeated corticosterone injections significantly decreased the latency to first immobility. Furthermore, co-treatment of corticosterone with Ze 117 increased latency to first immobility significantly compared to rats treated with corticosterone alone. To further investigate the biochemical effects of corticosterone-induced stress, as well as the possible counter-regulation by antidepressants, the lipidomes of the plasma and hippocampus samples were analyzed by shotgun mass spectrometry. Corticosterone-induced stress significantly altered key lipid metabolites in the plasma but not in the hippocampal samples. In the hippocampus, however, specific glycerophospholipids such as lysophosphatidylethanolamines (LPEs) increased with escitalopram treatment and with Ze 117, both showing significant correlations with behavioral parameters. In summary, our study shows significant behavioral- and lipidome-altering processes with Ze 117 and escitalopram in rat plasma and hippocampal samples, thereby providing new targets and biomarker ideas for clinical diagnosis and antidepressant intervention.PMID:39684380 | DOI:10.3390/ijms252312667

Int J Mol Sci. 2024 Nov 26;25(23):12666. doi: 10.3390/ijms252312666.ABSTRACTHigh-altitude plants face extreme environments such as low temperature, low oxygen, low nutrient levels, and strong ultraviolet radiation, causing them to adopt complex adaptation mechanisms. Phenotypic variation is the core manifestation of ecological adaptation and evolution. Many plants have developed a series of adaptive strategies through long-term natural selection and evolution, enabling them to survive and reproduce under such harsh conditions. This article reviews the techniques and methods used in recent years to study the adaptive evolution of high-altitude plants, including transplantation techniques, genomics, transcriptomics, proteomics, and metabolomics techniques, and their applications in high-altitude plant adaptive evolution. Transplantation technology focuses on phenotypic variation, which refers to natural variations in morphological, physiological, and biochemical characteristics, exploring their key roles in nutrient utilization, photosynthesis optimization, and stress-resistance protection. Multiple omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have revealed genes, regulatory pathways, and metabolic networks associated with phenotypic variations at the genetic and molecular levels. At the same time, the limitations and deficiencies of current technologies used to study plant adaptation to high-altitude environments were discussed. In addition, we propose future improvements to existing technologies and advocate for the integration of different technologies at multiple levels to study the molecular mechanisms of plant adaptation to high-altitude environments, thus providing insights for future research in this field.PMID:39684378 | DOI:10.3390/ijms252312666

Int J Mol Sci. 2024 Nov 25;25(23):12638. doi: 10.3390/ijms252312638.ABSTRACTMicrogravity may profoundly impact the cardiovascular system, skeletal muscle system, and immune system of astronauts. At the cellular level, microgravity may also affect cell proliferation, differentiation, and growth, as well as lipid metabolism. In this work, we investigated lipid changes in Caco-2 cells cultured in a clinostat for 24 h under simulated microgravity conditions (SMC). Complex lipids were measured using a UHPLC-QTOF/MS platform, and the data were subjected to multivariate analysis. Under SMC, levels of ceramides Cer 18:0;O2/16:0, Cer 18:1;O2/16:0, Cer 18:1; O2/22:0, Cer 18:1;O2/24:0, and Cer 18:2;O2/24:0 were found to be upregulated, while sphingomyelins SM 16:1;O2/16:0, SM 16:1;O2/18:1, SM 18:1;O2/24:0, and SM 18:2;O2/24:0 were found to be downregulated. On the other hand, considering that sphingolipids are involved in the process of inflammation, we also treated Caco-2 cells with dextran sodium sulfate (DSS) to induce cell inflammation and lipopolysaccharide (LPS) to induce cell immune responses. As a result, we observed similar lipid dysregulation, indicating that SMC may exert a condition similar to inflammation. Our lipidomics strategy provides new insights into the altered metabolic pathway of ceramides and sphingomyelins of Caco-2 cells under SMC.PMID:39684348 | DOI:10.3390/ijms252312638

Int J Mol Sci. 2024 Nov 25;25(23):12629. doi: 10.3390/ijms252312629.ABSTRACTThe astringent selection criteria for milk-oriented traits in dairy cattle have rendered these animals prone to various metabolic disorders. Postpartum lactational peak and reduced feed intake lead to negative energy balance in cattle. As a compensatory mechanism, cattle start mobilizing fat reserves to meet the energy demand for vital body functions. Consequently, diminished glucose concentrations and elevated ketone body levels lead to poor ovarian function. The impaired follicular development and subpar oocyte quality diminish the conception rates, which poses significant economic repercussions. Follicular fluid is integral to the processes of follicular growth and oocyte development. Hence, the present study was performed to identify potential alterations in metabolites in the follicular fluid under in vitro culture conditions mimicking negative energy balance. Our results revealed nine distinct metabolites exhibiting differential expression in follicular fluid under negative energy balance. The differentially expressed metabolites were predominantly associated with pathways related to amino acid metabolism, lipid metabolism, signal transduction mechanisms, and membrane transport, alongside other biological processes. The identified signature metabolites may be further validated to determine oocyte fitness subjected to in vitro fertilization or embryo production from slaughterhouse source ovaries.PMID:39684341 | DOI:10.3390/ijms252312629

Int J Mol Sci. 2024 Nov 24;25(23):12610. doi: 10.3390/ijms252312610.ABSTRACTThe problem of marine noise pollution has a long history. Strong noise (>120 dB re 1 µPa) will affects the growth, development, physiological responses, and behaviors of fish, and also can induce the stress response, posing a mortal threat. Although many studies have reported that underwater noise may affect the survival of fish by disturbing their nervous system and endocrine system, the underlying causes of death due to noise stimulation remain unknown. Therefore, in this study, we used the underwater noise stress models to conduct underwater strong noise (50-125 dB re 1 µPa, 10-22,000 Hz) stress experiments on small yellow croaker for 10 min (short-term noise stress) and 6 days (long-term noise stress). A total of 150 fishes (body weight: 40-60 g; body length: 12-14 cm) were used in this study. Omics (metabolomics and transcriptomics) studies and quantitative analyses of important genes (HPA (hypothalamic-pituitary-adrenal)-axis functional genes) were performed to reveal genetic and metabolic changes in the important tissues associated with the HPA axis (brain, heart, and adrenal gland). Finally, we found that the strong noise pollution can significantly interfere with the expression of HPA-axis functional genes (including corticotropin releasing hormone (CRH), corticotropin releasing hormone receptor 2 (CRHR2), and arginine vasotocin (AVT)), and long-term stimulation can further induce metabolic disorders of the functional tissues (brain, heart, and adrenal gland), posing a lethal threat. Meanwhile, we also found that there were two kinds of death processes, direct death and chronic death, and both were closely related to the duration of stimulation and the regulation of the HPA axis.PMID:39684322 | DOI:10.3390/ijms252312610

Int J Mol Sci. 2024 Nov 23;25(23):12592. doi: 10.3390/ijms252312592.ABSTRACTElm (Ulmus) species are important components of forest resources with significant ecological and economic value. As tall hardwood trees that are drought-resistant, poor-soil-tolerant, and highly adaptable, Ulmus species are an excellent choice for ecologically protected forests and urban landscaping. Additionally, the bioactive substances identified in the fruits, leaves, bark, and roots of Ulmus have potential applications in the food and medical fields and as raw materials in industrial and cosmetic applications. However, the survival of Ulmus species in the natural environment has been threatened by recurrent outbreaks of Dutch elm disease, which have led to the death of large numbers of Ulmus trees. In addition, severe damage to the natural habitats of some Ulmus species is driving their populations to extinction. Omics technology has become an important tool for the collection, protection, and biological characteristic analysis of Ulmus species and their resources due to its recent advances. This article summarizes the current research and application status of omics technology in Ulmus. The remaining problems are noted, and future research directions are proposed. Our review is aimed at providing a reference for resource conservation of Ulmus and for scientific research into this genus.PMID:39684304 | DOI:10.3390/ijms252312592

Int J Mol Sci. 2024 Nov 22;25(23):12560. doi: 10.3390/ijms252312560.ABSTRACTAggressiveness is one of the personality traits of crustaceans, playing a crucial role in their growth, life history, and adaptability by influencing resource acquisition. However, the neuroregulatory mechanisms of aggressiveness in crustaceans remain poorly understood. The thoracic ganglion offers valuable insights into complementary aspects of aggression control. This study identified the aggressiveness of swimming crabs Portunus trituberculatus, conducted transcriptomic and metabolomic analyses of the thoracic ganglia, and confirmed the neural regulatory effects on aggressiveness. Behavioral analyses showed that highly aggressive individuals exhibited increased frequency and duration of chela extension, more frequent attacks, approaches and retreats, as well as extended movement distances. Omics analysis revealed 11 key candidate genes and three metabolites associated with aggressiveness, which were primarily enriched in pathways related to energy metabolism and neurodegeneration. Injection of an NMDAR activator significantly decreased aggressiveness in highly aggressive crabs, accompanied by a significant increase in NMDAR protein fluorescence intensity and downregulation of NR2B, CaMKII, and CREB genes. Conversely, when lowly aggressive crabs were injected with an NMDAR inhibitor, they showed increased aggressiveness alongside significantly decreased NMDAR protein fluorescence intensity, upregulated NR2B expression, and downregulated CaMKII and CREB genes. These results suggest that NMDAR within the thoracic ganglia serves as a key receptor in modulating aggressiveness in P. trituberculatus, potentially by influencing neural energy state via the NMDAR-CaMKII pathway, which in turn affects oxidative phosphorylation, cAMP, and FoxO pathways.PMID:39684272 | DOI:10.3390/ijms252312560

Int J Mol Sci. 2024 Nov 21;25(23):12515. doi: 10.3390/ijms252312515.ABSTRACTAutoimmune diseases represent a severe personal and healthcare problem that seeks novel therapeutic solutions. Mesenchymal stem cells (MSCs) are multipotent cells with interesting cell biology and promising therapeutic potential. The immunoregulatory effects of secretory factors produced by umbilical cord mesenchymal stem cells (UC-MSCs) were assessed on B lymphocytes from 17 patients with systemic lupus erythematosus (SLE), as defined by the 2019 European Alliance of Associations for Rheumatology (EULAR)/American College of Rheumatology (ACR) classification criteria for SLE, and 10 healthy volunteers (HVs). Peripheral blood mononuclear cells (PBMCs) from patients and HVs were cultured in a UC-MSC-conditioned medium (UC-MSCcm) and a control medium. Flow cytometry was used to detect the surface expression of CD80, CD86, BR3, CD40, PD-1, and HLA-DR on CD19+ B cells and assess the percentage of B cells in early and late apoptosis. An enzyme-linked immunosorbent assay (ELISA) quantified the production of BAFF, IDO, and PGE2 in PBMCs and UC-MSCs. Under UC-MSCcm influence, the percentage and mean fluorescence intensity (MFI) of CD19+BR3+ cells were reduced in both SLE patients and HVs. Regarding the effects of the MSC secretome on B cells in lupus patients, we observed a decrease in CD40 MFI and a reduced percentage of CD19+PD-1+ and CD19+HLA-DR+ cells. In contrast, in the B cells of healthy participants, we found an increased percentage of CD19+CD80+ cells and decreased CD80 MFI, along with a decrease in CD40 MFI and the percentage of CD19+PD-1+ cells. The UC-MSCcm had a minimal effect on B-cell apoptosis. The incubation of patients' PBMCs with the UC-MSCcm increased PGE2 levels compared to the control medium. This study provides new insights into the impact of the MSC secretome on the key molecules involved in B-cell activation and antigen presentation and survival, potentially guiding the development of future SLE treatments.PMID:39684227 | DOI:10.3390/ijms252312515