Search Results (102)

Although numerous quantitative trait loci (QTLs) and candidate genes have been implicated in litter size in certain pig breeds, the genetic basis underlying the pronounced differences in reproductive capacity among breeds remains incompletely understood. To elucidate the underlying mechanisms responsible for the heterogeneity in reproductive capacity, we performed integrated transcriptomic and metabolomic analyses on ovarian tissues from two pig breeds with contrasting litter sizes: Diannan Small-ear (DSE) pigs and Yorkshire (YK) pigs. YK pigs exhibited significantly higher total born piglets. Transcriptome analysis revealed that upregulated DEGs in YK ovaries were enriched in ovarian steroidogenesis, retinol metabolism, vitamin digestion/absorption, and folate biosynthesis. In contrast, DSE pigs showed enrichment in inflammatory and immune-related pathways. Furthermore, integrative transcriptomic and metabolomic analysis revealed that upregulated DEGs in YK pigs, such as STAR and COL3A1, and concurrently elevated metabolites (e.g., L-threonine, L-asparagine, L-proline, L-methionine, arachidonic acid, and progesterone) were jointly enriched in three key pathways: protein digestion and absorption, mineral absorption, and aldosterone synthesis and secretion. These genes and metabolites are implicated in granulosa cell and oocyte proliferation, maturation, and protection against oxidative damage. Our findings provide a theoretical foundation for future strategies aimed at improving reproductive performance through targeted modulation of key genes and metabolites. Full article

Background: High-throughput metabolomics studies have promoted the discovery of candidate biomarkers linked to atherosclerosis (AS). This narrative systematic review summarises metabolomics studies conducted in (1) individuals with subclinical AS (assessed by imaging techniques such as carotid intimal media thickness, IMT, and coronary artery calcium, CAC), (2) patients with established atherosclerotic plaques, and (3) individuals with AS risk factors. Methods: The systematic search was conducted in the PubMed database according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. The inclusion criteria were as follows: (i) publication date between 2009 and 2024; (ii) identification of potential biomarkers for AS in subjects with a diagnosis of AS or with one or more traits characteristic of the disease (i.e., CAC or IMT); (iii) identification of potential AS biomarkers in subjects with atherogenic clinical conditions (i.e., Down’s syndrome, DS, polycystic ovarian syndrome, PCOS, and systemic lupus erythematosus, SLE); (iv) metabolomic studies; and (iv) studies in human samples. Exclusion criteria comprised the following: (i) studies on lipid metabolic diseases unrelated to AS, (ii) “omics” results not derived from metabolomics, (iii) reviews and studies in animal models or cell cultures, and (iv) systematic reviews and meta-analyses. Of 90 eligible studies screened, 24 met the inclusion criteria. Results: Across subclinical and overt AS, consistent disturbances were observed in amino acid, lipid, and carbohydrate metabolism. Altered profiles included branched-chain amino acids (BCAAs), aromatic amino acids (AACs) and derivatives (e.g., kynurenine–tryptophan pathway), bile acids (BAs), androgenic steroids, short-chain fatty acids (FAs)/ketone intermediates (e.g., acetate, 3-hydroxybutyrate, 3-HB), and Krebs cycle intermediates (e.g., citrate). Several metabolites (e.g., glutamine, lactate, 3-HB, phosphatidylcholines, PCs/lysophosphatidylcholines, lyso-PCs) showed reproducible associations with vascular phenotypes (IMT/CAC) and/or clinical AS. Conclusions: The identification of low-weight metabolites altered in both subclinical and overt AS suggests their potential as candidate biomarkers for early AS diagnosis. Given the steady increase in deaths from cardiovascular disease, a manifestation of advanced AS, this finding could have significant clinical relevance. Full article

The cryopreservation and transplantation of germline stem cells (GSCs) have become the key to conserving fish genetic resources and safeguarding species diversity. This study aimed to investigate the effects of post-mortem temperature and time on the preservation of oogonial stem cells (OSCs) in the marine fish Paralichthys olivaceus. OSCs remained viable after fish death, and they remained viable and could be cultured after storage at 19 °C for 15 h and at 4 °C for 24 h. Combined transcriptomic and metabolomic analysis was used to identify the pathways leading to OSC death. Several genes were differentially expressed in the ovarian tissue post-mortem, with the most enriched pathways being ferroptosis, fatty acid metabolism/biosynthesis, glutathione metabolism, citric acid cycle (TCA cycle), and arachidonic acid metabolism signaling pathways. Genes related to ferroptosis, such as vdac2, p53, and slc7a11, as well as metabolites such as adrenic acid and arachidic acid, can serve as reliable biomarkers for evaluating the viability of post-mortem OSCs. These findings provide valuable insights and theoretical support for the effective use of post-mortem GSCs and enhance strategies for germplasm resource conservation in fish. Full article

Ovarian follicular fluid (FF) is a metabolically active and biomarker-rich medium that mirrors the oocyte microenvironment. Its analysis is increasingly recognized in infertility diagnostics and assisted reproductive technologies (ART) for assessing oocyte competence, understanding reproductive disorders, and guiding personalized treatment. However, FF’s high viscosity, complex composition, and biochemical variability challenge reproducibility in sample preparation and molecular profiling. Sonication-based extraction has emerged as an effective approach to address these issues. By exploiting acoustic cavitation, sonication improves protein solubilization, metabolite release, and lipid recovery, while reducing solvent use and processing time. This review synthesizes recent advances in sonication-assisted FF analysis across proteomics, metabolomics, and lipidomics, emphasizing parameter optimization, integration with advanced mass spectrometry workflows, and emerging applications in microfluidics, automation, and point-of-care devices. Clinical implications are discussed in the context of enhanced biomarker discovery pipelines, real-time oocyte selection, and ART outcome prediction. Key challenges, such as preventing biomolecule degradation, standardizing protocols, and achieving inter-laboratory reproducibility, are addressed alongside regulatory considerations. Future directions highlight the potential of combining sonication with multi-omics strategies and AI-driven analytics, paving the way for high-throughput, standardized, and clinically actionable FF analysis to advance precision reproductive medicine. Full article

Sea cucumber ovum are high-value compounds that remain after the processing of sea cucumbers, and their optimal utilization has long posed a challenge. In this research, we systematically examined the therapeutic effects of sea cucumber ovum hydrolysate (SCH) on premature ovarian failure (POF) and its underlying mechanism. We utilized a model of ICR mice induced with 100 mg/kg cyclophosphamide (CP) to evaluate the therapeutic influence of SCH on ovarian performance. The ovarian and uterine indices were significantly decreased in the POF group compared to the control group; however, these trends were notably reversed following SCH intervention. The therapeutic effects of SCH were positively reflected by the alterations induced by CP in levels of estradiol (E2), follicle-stimulating hormone (FSH), testosterone (T), luteinizing hormone (LH), and anti-Müllerian hormone (AMH). Regarding oxidative stress, SCH was found to enhance superoxide dismutase (SOD) activity and decrease malondialdehyde (MDA) levels, while also alleviating apoptosis in ovarian granulosa cells. Metabolomics analysis revealed hypoxanthine, mannitol, neocnidilide, tryptophan, palmitoleic acid, and protoporphyrinogen IX as potential biomarkers. In conclusion, SCH effectively improves POF induced by CP, thereby reinforcing the potential application of SCH in the domain of functional foods. Full article

Background: Premature ovarian insufficiency (POI) poses a significant challenge for women. The effects of Cucumaria frondosa tentacles hydrolysates (CFTH) on POI remain to be fully elucidated. Purpose: This study aimed to determine whether CFTH exerts a beneficial effect on ovarian function using a POI mouse model and to investigate the underlying mechanisms of action. Methods: In this study, we characterized the amino acid composition and physicochemical properties of CFTH. The POI model was established by administering 100 mg/kg of cyclophosphamide (CP). We assessed the regulation of the estrous cycle, hormone levels, ovarian cell apoptosis, and oxidative stress markers in POI mice. Differences in ovarian and uterine morphology among the different groups were observed. Furthermore, metabolomics analysis was employed to explore potential mechanisms. Results: CFTH treatment reversed the dysregulation of the estrous cycle and hormone levels. TUNEL analysis revealed that CFTH treatment significantly reduced apoptosis in granulosa cells and altered the expression levels of apoptosis-related genes at the mRNA level. Additionally, CFTH significantly increased superoxide dismutase activity and decreased malondialdehyde levels, thereby mitigating oxidative stress. Metabolomics analysis suggested that CFTH may ameliorate ovarian dysfunction by regulating steroid biosynthesis and the cGMP-PKG signaling pathway. Conclusions: These findings suggest that CFTH may serve as an effective strategy for alleviating POI. Further research is warranted to verify the long-term safety and effectiveness of CFTH in humans. Full article

The aim of this study was to evaluate the effects of Flos lonicerae and Baikal skullcap extracts (PE) on laying performance, antioxidant capacity, immune function, follicular development, estrogen secretion, ovarian metabolomics, and cecal microbiota in aged laying hens. The total number of 70-week-old XinYang Black-Feathered laying hens was 240. These hens were randomly divided into two groups, with each group consisting of six replicates of 20 birds. Control (CON) group was fed a basal diet, whereas the PE group received the same basal diet supplemented with 500 mg/kg of PE. The duration of the experiment was 10 weeks. The findings indicated that the supplementation of PE improved laying performance, antioxidant capacity, and immune function. This was reflected by significant increases (p < 0.05) in laying rate, feed conversion ratio, antioxidant indicators (such as glutathione peroxidase, total antioxidant capacity, and catalase), and immunoglobulin levels. Additionally, there were notable decreases (p < 0.05) in the malondialdehyde levels and pro-inflammatory markers. Moreover, the PE group exhibited a greater number of large yellow and white follicles, as well as higher serum estrogen levels, compared to the CON group (p < 0.05). 16S rRNA sequencing revealed that PE supplementation altered the composition of the cecal microbiota by increasing Ruminococcus_torques_group, Butyricoccus and Christensenellaceae_R-7_group abundances and decreasing Bacteroides, Prevotellaceae_UCG-001 and Megamonas abundances (at genus level), which are primarily associated with short-chain fatty acid production. Ovarian metabolomic analysis showed that the major metabolites altered by PE supplementation were mainly involved in follicular development, estrogen biosynthesis, anti-inflammatory and antioxidant properties. Moreover, changes in both the cecal microbiota (at genus level) and ovarian metabolites were strongly correlated with laying performance, antioxidant status, and immune function. In conclusion, PE supplementation improved laying performance in aged hens by enhancing antioxidant, immune, and ovarian functions, promoting follicular development and estrogen secretion, and modulating the gut microbiota and ovarian metabolites. These findings will offer novel insights into the mechanisms that underlie egg production in the ovaries of aged poultry. Full article

Nucleus accumbens-associated protein 1 (NAC1), a cancer-related transcriptional regulator, is overexpressed in several malignancies, including ovarian cancer. However, its role in ovarian carcinogenesis remains unclear. We aimed to investigate whether NAC1 contributes to metabolic adaptation in endometriosis-related ovarian neoplasms (ERONs) and elucidate its regulatory mechanisms. The clinical relationship between NAC1 and its potential downstream target, phosphoenolpyruvate carboxykinase isoform 2 (PCK2), was examined using immunohistochemical analysis of ovarian cancer specimens. A cell viability assay was performed to clarify the impact of PCK2 on ovarian cancer cell viability. Reporter and chromatin immunoprecipitation (ChIP) assays were conducted to evaluate transcriptional regulation by NAC1. Metabolomic profiling was performed to assess the functional impact of the NAC1–PCK2 axis. A positive correlation between NAC1 and PCK2 expression was observed, and co-expression was associated with poor long-term survival. Knockdown of PCK2 led to a significant reduction in cell viability, indicating that PCK2 is required for maintaining cell survival. Reporter and ChIP assays confirmed that NAC1 directly binds to the PCK2 promoter via the CATG motif. The metabolomic analysis demonstrated that NAC1 promotes truncated gluconeogenesis and de novo serine synthesis through PCK2 upregulation. These findings suggest that NAC1 contributes to ovarian cancer progression by promoting metabolic adaptation, highlighting the NAC1–PCK2 axis as a potential therapeutic target for ERONs. Full article

This review article focuses on the role of choline in ovarian follicular development, regulated by nutrient–epigenetic interactions. Choline, a key feed additive, participates in DNA methylation and steroid hormone synthesis via its methyl donor function. However, its role in follicular hierarchy and maturation is unclear. Research lacks an understanding of species-specific choline metabolism, follicular fluid methylation dynamics, and toxicity thresholds. This study combines animal nutrition, epigenetics, and reproductive endocrinology. Using in vitro follicle culture models, metabolomics analysis, and cytochrome P450 family 19 subfamily A member 1 (CYP19a1) methylation site screening, it reveals that choline regulates follicle hierarchy through the betaine-S-adenosylmethionine (SAM) pathway. Proper dietary choline reduces homocysteine (HCY) and boosts CYP19a1 demethylation, enhancing theca cell estradiol (E₂) production and accelerating follicle maturation. In contrast, inadequate or excessive choline causes mesoderm-specific transcript (MEST) gene methylation abnormalities or trimethylamine N-oxide (TMAO)-mediated β-oxidation inhibition, increasing follicle atresia. A phenomenon of steroidogenic factor 1 (SF-1) methylation has been observed in poultry, showing that choline affects offspring egg-laying persistence by altering the adrenal–ovarian axis DNA methylation imprint. Future research should establish a precise choline supply system based on the HCY/TMAO ratio in follicular fluid and the CYP19a1 methylation map to improve animal reproduction. Full article

Fish reproduction requires suitable salinity and temperature, as well as sufficient energy. This study investigated temperature and salinity effects on ovarian development of Lateolabrax maculatus and energy metabolism differences between reproduction and growth. Two salinities (4‰ and 30‰) and temperatures (18 ± 1 °C and 30 ± 1 °C) formed four treatments: SWNT (30‰, 30 ± 1 °C), SWLT (30‰, 18 ± 1 °C), FWLT (4‰, 18 ± 1 °C), and FWNT (4‰, 30 ± 1 °C). GSI and sex hormones (FSH, LH, E2, and 17α,20β-DHP) were measured. Transcriptome analysis explored how temperature and salinity regulate ovarian development in L. maculatus, while integrated transcriptomic and targeted energy metabolomic analyses revealed energy metabolism differences between ovary and muscle during this process. The results showed that low salinity (4‰) and low temperature (18 ± 1 °C) synergistically promoted ovarian development in the FWLT group, as indicated by a significant increase in GSI and elevated levels of key sex hormones (FSH, LH, E2, and 17α,20β-DHP). Transcriptome analysis showed that low temperature activated pathways involved in steroidogenesis, oocyte maturation, and meiosis, and genes such as ADCY6, PRKACB, CPEB4, FZD7-A, and CCND2 were significantly upregulated. Salinity changes mainly affected amino acid metabolism, cholesterol metabolism, and the insulin signaling pathway. Genes such as PCSK9 and CKM may regulate ovarian development by regulating hormone synthesis and energy metabolism. Comprehensive transcriptome and metabolome analyses show that glycolysis is downregulated and oxidative phosphorylation is upregulated in the ovary, suggesting that ovarian oogenesis tends to be energized by aerobic metabolism. The TCA cycle may be used more for providing biosynthetic precursors and facilitating the transport of substrates between the mitochondrion and the cytoplasm rather than just as a source of ATP. Muscle tissue relies primarily on glycolysis for rapid energy production and may redistribute energy to the gonads, prioritizing the energy needs of the ovaries and contributing to the dynamic balance between reproduction and growth. This study provides insights into the molecular mechanisms of how environmental factors regulate fish reproduction, providing a theoretical basis and potential molecular targets for the regulation of reproduction and optimization of aquaculture environments. Full article

Background/Objectives: The breast cancer susceptibility gene 1 (BRCA1) is a tumor suppressor gene whose mutations are associated with increased susceptibility to develop breast or ovarian cancer. BRCA1 mainly exerts its protective effects through DNA double-strand break repair. Although not itself a transcriptional factor, BRCA1, through its multiple protein interaction domains, exerts transcriptional coregulation. In addition, BRCA1 expression alters cellular metabolism including inhibition of de novo fatty acid synthesis, changes in cellular bioenergetics, and activation of antioxidant defenses. Some of these actions may contribute to its global oncosuppressive effects. However, the breadth of metabolic pathways reprogrammed by BRCA1 is not fully elucidated. Methods: Breast cancer cells expressing BRCA1 were investigated by multiplatform metabolomics, metabolism-related transcriptomics, and joint metabolomics/transcriptomics data processing techniques, namely two-way orthogonal partial least squares and pathway analysis. Results: Joint analyses revealed the most important metabolites, genes, and pathways of metabolic reprogramming in BRCA1-expressing breast cancer cells. The breadth of metabolic reprogramming included fatty acid synthesis, bioenergetics, HIF-1 signaling pathway, antioxidation, nucleic acid synthesis, and other pathways. Among them, rewiring of glycerophospholipid (including phosphatidylcholine, -serine and -inositol) metabolism and increased arginine metabolism have not been reported yet. Conclusions: Rewired glycerophospholipid and arginine metabolism were identified as components of BRCA1-induced metabolic reprogramming in breast cancer cells. The study helps to identify metabolites that are candidate biomarkers of the BRCA1 genotype and metabolic pathways that can be exploited in targeted therapies. Full article

Cancer metabolic reprogramming plays a critical role in tumor progression and therapeutic resistance, underscoring the need for advanced analytical strategies. Metabolomics, leveraging mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, offers a comprehensive and functional readout of tumor biochemistry. By enabling both targeted metabolite quantification and untargeted profiling, metabolomics captures the dynamic metabolic alterations associated with cancer. The integration of metabolomics with machine learning (ML) approaches further enhances the interpretation of these complex, high-dimensional datasets, providing powerful insights into cancer biology from biomarker discovery to therapeutic targeting. This review systematically examines the transformative role of ML in cancer metabolomics. We discuss how various ML methodologies—including supervised algorithms (e.g., Support Vector Machine, Random Forest), unsupervised techniques (e.g., Principal Component Analysis, t-SNE), and deep learning frameworks—are advancing cancer research. Specifically, we highlight three major applications of ML–metabolomics integration: (1) cancer subtyping, exemplified by the use of Similarity Network Fusion (SNF) and LASSO regression to classify triple-negative breast cancer into subtypes with distinct survival outcomes; (2) biomarker discovery, where Random Forest and Partial Least Squares Discriminant Analysis (PLS-DA) models have achieved >90% accuracy in detecting breast and colorectal cancers through biofluid metabolomics; and (3) prognostic modeling, demonstrated by the identification of race-specific metabolic signatures in breast cancer and the prediction of clinical outcomes in lung and ovarian cancers. Beyond these areas, we explore applications across prostate, thyroid, and pancreatic cancers, where ML-driven metabolomics is contributing to earlier detection, improved risk stratification, and personalized treatment planning. We also address critical challenges, including issues of data quality (e.g., batch effects, missing values), model interpretability, and barriers to clinical translation. Emerging solutions, such as explainable artificial intelligence (XAI) approaches and standardized multi-omics integration pipelines, are discussed as pathways to overcome these hurdles. By synthesizing recent advances, this review illustrates how ML-enhanced metabolomics bridges the gap between fundamental cancer metabolism research and clinical application, offering new avenues for precision oncology through improved diagnosis, prognosis, and tailored therapeutic strategies. Full article

Curcumin is a natural polyphenolic compound known to alleviate follicular developmental abnormalities associated with ovarian dysfunction. However, its precise molecular mechanisms remain to be fully elucidated. In this study, we systematically investigated the regulatory effects of curcumin on bovine ovarian granulosa cells through integrated transcriptomic and metabolomic analyses. A total of 503 and 200 significantly altered metabolites were identified in the positive and negative ion modes, respectively, with enrichment in key pathways such as glutathione metabolism, fatty acid biosynthesis, and the phosphatidylinositol signaling pathway. Transcriptomic profiling revealed 1168 differentially expressed genes (582 upregulated and 586 downregulated) which were significantly enriched in pathways related to glutathione metabolism and cellular senescence. Joint multi-omics analysis further demonstrated that curcumin significantly influenced pathways related to glutathione metabolism, cysteine, and methionine metabolism, as well as multiple forms of programmed cell death, including apoptosis, necroptosis, and ferroptosis. Collectively, these findings suggest that curcumin may enhance the antioxidant capacity and survival of granulosa cells by maintaining redox homeostasis and modulating cell fate. This work provides new insights into the potential cellular mechanisms underlying the protective effects of curcumin on granulosa cell function. Full article

Ovarian cancer (OC), the third most common gynecologic malignancy, exhibits distinct metabolic alterations that could enable early detection via liquid biopsy. We developed an advanced machine learning pipeline integrating lipidomics (HPLC-MS, positive/negative ion modes) and NMR-based metabolomics to analyze plasma samples from 229 subjects, including 103 serous OC patients, 107 benign cases, and 19 healthy controls. By systematically evaluating feature selection methods and machine learning architectures, we identified optimal biomarker combinations for OC detection. Convolutional Neural Network (CNN) model based on Mann–Whitney-selected features demonstrated strong discriminatory power (81% accuracy) in distinguishing malignant from benign cases, while Extreme Gradient Boosting (XGBoost) combined with Support Vector Machine-Recursive Feature Elimination (SVM-RFE) achieved exceptional performance (96% accuracy) in differentiating benign from control samples. For multiclass classification, XGBoost with Kruskal–Wallis-selected features achieved 77% accuracy, while one-versus-one CNN models utilizing Mann–Whitney-selected features attained 78% accuracy, demonstrating optimal performance among tested approaches. The complementary strengths of deep learning and ensemble methods underscore their potential for tailored diagnostic applications. While clinical implementation requires further standardization, these findings provide both a methodological framework for metabolic biomarker discovery and biological insights into OC pathophysiology, paving the way for integrated multi-omics approaches in gynecologic oncology. Full article

Granulosa cells (GCs) are essential for follicular growth and development, and their functional state critically impacts folliculogenesis. TAp73α, a transcriptionally active isoform of the p73 gene, is crucial for maintaining follicular integrity. In this study, we demonstrate that TAp73α overexpression promotes ferroptosis in bovine GCs by downregulating SLC7A11, depleting intracellular glutathione (GSH), and enhancing lipid peroxidation, particularly under Erastin treatment. By contrast, TAp73α knockdown restores antioxidant capacity, elevates GSH levels, and attenuates ferroptosis. To elucidate the underlying mechanism, untargeted metabolomic profiling revealed that TAp73α overexpression significantly altered the metabolic landscape of GCs, with marked enrichment in the glutathione metabolism pathway. Notably, betaine—a metabolite closely linked to redox homeostasis—was markedly downregulated. Functional assays confirmed that exogenous betaine supplementation restored SLC7A11 expression, increased GSH levels, and alleviated oxidative damage induced by either H₂O₂ or TAp73α overexpression. Moreover, betaine co-treatment effectively reversed lipid peroxide accumulation and mitigated TAp73α-induced ferroptosis. Collectively, our findings identify a novel mechanism by which TAp73α promotes ferroptosis in granulosa cells through the suppression of betaine and glutathione metabolism, highlighting betaine as a key metabolic modulator with promising protective potential. Full article