Specific Pathways Research Articles

Effect of glyphosate on renal function: A study integrating epidemiological and experimental evidence.

Glyphosate, a widely used herbicide globally, has prompted concerns regarding its potential health impacts. This study aimed to explore the link between glyphosate exposure and renal function by combining NHANES, a zebrafish model, and metabolomics. A cross-sectional analysis of 2013-2014 NHANES data investigated the relationship between glyphosate exposure and renal function [albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR)]. A subsequent zebrafish experiment was conducted to verify this association. Embryos (0.75 hpf-96 hpf) were exposed to different glyphosate concentrations dissolved in water (0, 30, 60, 90, 120 μg/mL). The underlying mechanism of the association between glyphosate and renal function was explored by the real-time quantitative polymerase chain reaction (RT-qPCR) and non-targeted metabolomics analysis [embryos (0.75 hpf-96 hpf) were exposed to 90 μg/mL glyphosate]. 1170 participants were enrolled in the NHANES study. The NHANES-based study found a positive association between glyphosate and ACR [0.07 (0.01, 0.13)]. Higher urinary glyphosate levels, particularly in the third quartile group, were negatively linked to eGFR [-3.72 (-5.98, -1.46)]. Further zebrafish experiments indicated that zebrafish exposed to 90 μg/mL glyphosate exhibited increased mortality rates, higher fluorescence intensity, up-regulated the havcr1 expression level, and cystic dilatation of the kidney. Non-targeted metabolomics analysis identified differential metabolites (e.g., 5-Hydroxyindole acetic acid) and pathways (e.g., ABC transporters) influenced by glyphosate. Glyphosate exposure is negatively associated with renal function in community adults. The damage to the kidneys caused by glyphosate may be mediated through the regulation of metabolic pathways, and the specific mechanisms require further experimental investigation.

Differential cell death pathways in normal and cancerous breast cells response to direct X-ray irradiation and bystander effects

Differential cell death pathways in normal and cancerous breast cells response to direct X-ray irradiation and bystander effects

Identification of pain-related long non-coding RNAs for pulpitis prediction.

We investigated the recently generated RNA-sequencing dataset of pulpitis to identify the potential pain-related lncRNAs for pulpitis prediction. Differential analysis was performed on the gene expression profile between normal and pulpitis samples to obtain pulpitis-related genes. The co-expressed gene modules were identified by weighted gene coexpression network analysis (WGCNA). Then the hypergeometric test was utilized to screen pain-related core modules. The functional enrichment analysis was performed on the up- and down-regulated genes in the core module of pulpitis pain to explore the underlying mechanisms. A pain-related lncRNA-based classification model was constructed using LASSO. Consensus clustering and gene set variation analysis (GSVA) on the infiltrating immunocytes was used for pulpitis subtyping. miRanda predicts miRNA-target relationship, which was filtered by expression correlation. Hallmark pathway and enrichment analysis was performed to investigate the candidate target pathways of the lncRNAs. A total of 1830 differential RNAs were identified in pulpitis. WGCNA explored seven co-expressed modules, among which the turquoise module is pain-related with hypergeometric test. The up-regulated genes were significantly enriched in immune response related pathways. Down-regulated genes were significantly enriched in differentiation pathways. Eight lncRNAs in the pain-related module were related to inflammation. Among them, MIR181A2HG was downregulated while other seven lncRNAs were upregulated in pulpitis. The LASSO classification model revealed that MIR181A2HG and LINC00426 achieved outstanding predictive performances with perfect ROC-AUC score (AUC = 1). We differentiated the pulpitis samples into two progression subtypes and MIR181A2HG is a progressive marker for pulpitis. The miRNA-mRNA-lncRNA regulatory network of pulpitis pain was constructed, with GATA3 as a key transcription factor. NF-kappa B signaling pathway is a candidate pathway impacted by these lncRNAs. PCED1B-AS1, MIAT, MIR181A2HG, LINC00926, LINC00861, LINC00528, LINC00426 and ITGB2-AS1 may be potential markers of pulpitis pain. A two-lncRNA signature of LINC00426 and MIR181A2HG can accurately predict pulpitis, which could facilitate the molecular diagnosis of pulpitis. GATA3 might regulate these lncRNAs and downstream NF-kappa B signaling pathway. This study identified potential pain-related lncRNAs with underlying molecular mechanism analysis for the prediction of pulpitis. The classification model based on lncRNAs will facilitate the early diagnosis of pulpitis.

Clinical and genetic diagnosis of first cohort of differences of sexual development in the Iranian population.

Differences of sex development (DSD) refer to various congenital conditions affecting the urogenital and hormonal systems. Accurate diagnosis and personalized management are crucial for supporting patients through complex decisions, such as those related to gender identity. This study represents the first comprehensive investigation into DSD inIran, analyzing patient's clinical and genetic data between 1991 and 2020. Karyotype analysis was performed on 69 patients without a molecular diagnosis, with sex chromosome DSD excluded. Presence of SRY gene evaluated in all sex reversal patients. Whole exome sequencing (WES) was used for 26 undiagnosed patients, revealing pathogenic variants in WT1, NR5A1, DHX37, AR, CYP17A1, and LHCGR genes. The most common diagnosis was testicular TDSD, identified in 42 patients (60.86 %), with the SRY gene being the primary cause in 36 of these patients. The study highlights the importance of genetic analysis in identifying novel and rare gene variants, particularly within the steroid hormone and gonad differentiation pathways, for both 46, XY and 46, XX DSD. These findings emphasize the need for genetic analysis in providing personalized patient care and tailored counseling to help individuals navigate complex decisions, including those involving gender identity.

Comparative metabolomic analysis of Haematococcus pluvialis during hyperaccumulation of astaxanthin under the high salinity and nitrogen deficiency conditions.

Revealing the differences of metabolite profiles of H. pluvialis during hyperaccumulation of astaxanthin under the high salinity and nitrogen deficiency conditions was the key issues of the present study. To investigate the optimum NaCl and NaNO3 concentration and the corresponding metabolic characteristic related to the astaxanthin accumulation in H. pluvialis, a batch culture experiment was conducted. The results indicated that 7.5g·L- 1 and 0g·L- 1 (nitrogen deficiency) were the optimum NaCl and NaNO3 levels for the astaxanthin accumulation respectively, under which the highest astaxanthin contents reached up to 7.51mg·L- 1 and 5.60mg·L- 1. A total of 132 metabolites were identified using LC-MS/MS technique, among which 30 differential metabolites with statistical significance were highlighted. Subsequently, 18 and 10 differential metabolic pathways in the high salinity (HS) and nitrogen-deficient (ND) treatments were extracted and annotated respectively. The values of Fv/Fm, Yield and NPQ were all at the highest level in the ND group during the experiment. The levels of the metabolites in the ND group were almost lower than those both in the control (CK) and HS group, while which in the HS group were substantially at the higher or close levels compared to the CK group. Finally, 7 metabolic markers related to the astaxanthin accumulation were highlighted in the HS and ND group respectively. L-Proline, L-Aspartate, Uridine 5'-monophosphate (UMP), Succinate, L-2-Hydroxygluterate, L-Valine and Inosine 5'-monophosphate (IMP) were identified as the metabolic markers in the HS group, whose fold change were 0.85, 4.14, 0.31, 0.66, 3.10, 1.32 and 0.30. Otherwise, the metabolic markers were Glyceric acid, Thymine, sn-Glycerol 3-phosphate, Glycine, Allantoic acid, L-Valine and IMP in the ND group, with the fold change 0.23, 2.11, 0.38, 0.41, 0.50 and 2.96 respectively. The results provided the comparative metabolomic view of astaxanthin accumulation in H. pluvialis under the different cultivation conditions, moreover showed a novel insights into the astaxanthin production.

Machine Learning and Multi-Omics Integration to Reveal Biomarkers and Microbial Community Assembly Differences in Abnormal Stacking Fermentation of Sauce-Flavor Baijiu.

Stacking fermentation is critical in sauce-flavor Baijiu production, but winter production often sees abnormal fermentations, like Waistline and Sub-Temp fermentation, affecting yield and quality. This study used three machine learning models (Logistic Regression, KNN, and Random Forest) combined with multi-omics (metagenomics and flavoromics) to develop a classification model for abnormal fermentation. SHAP analysis identified 13 Sub-Temp Fermentation and 9 Waistline microbial biomarkers, along with 9 Sub-Temp Fermentation and 12 Waistline flavor biomarkers. Komagataeibacter and Gluconacetobacter are key for normal fermentation, while Ligilactobacillus and Lactobacillus are critical in abnormal cases. Excessive acid and ester markers caused unbalanced aromas in abnormal fermentations. Additionally, ecological models reveal the bacterial community assembly in abnormal fermentations was influenced by stochastic factors, while the fungal community assembly was influenced by deterministic factors. RDA analysis shows that moisture significantly drove Sub-Temp fermentation. Differential gene analysis and KEGG pathway enrichment identify metabolic pathways for flavor markers. This study provides a theoretical basis for regulating stacking fermentation and ensuring Baijiu quality.

Amantadine modulates novel macrophage phenotypes to enhance neural repair following spinal cord injury

BackgroundSpinal cord injury (SCI) triggers a complex inflammatory response that impedes neural repair and functional recovery. The modulation of macrophage phenotypes is thus considered a promising therapeutic strategy to mitigate inflammation and promote regeneration.MethodsWe employed microarray and single-cell RNA sequencing (scRNA-seq) to investigate gene expression changes and immune cell dynamics in mice following crush injury at 3 and 7 days post-injury (dpi). High-dimensional gene co-expression network analysis (hdWGCNA) and slingshot trajectory analysis were employed to identify key gene modules and macrophage differentiation pathways. Subsequently, immunofluorescence staining, flow cytometry, and western blotting were performed to validate the identified effects of amantadine on macrophage differentiation and inflammation.ResultsTo elucidate the molecular mechanisms underlying the injury response at the transcriptional level, we performed a microarray analysis followed by gene set enrichment analysis (GSEA). The results revealed that pathways related to phagocytosis and macrophage activation are significantly involved post-injury, shedding light on the regulatory role of macrophages in SCI repair. To further investigate macrophage dynamics within the injured spinal cord, we conducted scRNA-Seq, identifying three distinct macrophage subtypes: border-associated macrophages (BAMs), inflammatory macrophages (IMs), and chemotaxis-inducing macrophages (CIMs). Trajectory analysis suggested a differentiation pathway from Il-1b+ IMs to Mrc1+ BAMs, and subsequently to Arg1+ CIMs, indicating a potential maturation process. Given the importance of these pathways in the injury response, we utilized molecular docking to hypothesize that amantadine might modulate this process. Subsequent in vitro and in vivo experiments demonstrated that amantadine reduces Il-1b+ IMs and facilitates the transition to Mrc1+ BAMs and Arg1+ CIMs, likely through modulation of the HIF-1α and NF-κB pathways. This modulation promotes neural regeneration and enhances functional recovery following SCI.ConclusionsAmantadine modulates macrophage phenotypes following SCI, reduces early inflammatory responses, and enhances neural function recovery. These findings highlight the therapeutic potential of amantadine as a treatment for SCI, and provide a foundation for future translational research into its clinical applications.

Investigation of the Molecular Mechanism of Asthma in Meishan Pigs Using Multi-Omics Analysis.

Asthma has been extensively studied in humans and animals, but the molecular mechanisms underlying asthma in Meishan pigs, a breed with distinct genetic and physiological characteristics, remain elusive. Understanding these mechanisms could provide insights into veterinary medicine and human asthma research. We investigated asthma pathogenesis in Meishan pigs through transcriptomic and metabolomic analyses of blood samples taken during autumn and winter. Asthma in Meishan pigs is related to inflammation, mitochondrial oxidative phosphorylation, and tricarboxylic acid (TCA) cycle disorders. Related genes include CXCL10, CCL8, CCL22, CCL21, OLR1, and ACKR1, while metabolites include succinic acid, riboflavin-5-phosphate, and fumaric acid. Transcriptomic sequencing was performed on panting and normal Meishan pigs, and differentially expressed genes underwent functional enrichment screening. Metabolomic analysis revealed differential metabolites and pathways between groups. Combined analyses indicated that lung inflammation is influenced by genetic, allergenic, and environmental factors disrupting oxidative phosphorylation in lung mitochondria, affecting the TCA cycle. Mitochondrial reactive oxygen species, glutathione S-transferases, arginase 1 and RORC in immune regulation, the Notch pathway, YPEL4 in cell proliferation, and MARCKS in airway mucus secretion play roles in asthma pathogenesis. This study highlights that many cytokines and signaling pathways contribute to asthma. Further studies are needed to elucidate their complex interactions.

Gene Expression Profiles Reveal Distinct Mechanisms Driving Chronic Obstructive Pulmonary Disease Exacerbations.

Chronic obstructive pulmonary disease (COPD) exacerbations are major contributors to morbidity and mortality, highlighting the need to better understand their molecular mechanisms to improve prevention, diagnosis, and treatment. This study investigated differential gene expression profiles and key biological processes in COPD exacerbations categorized based on sputum microbiome profiling. An observational study was performed on a cohort of 16 COPD patients, who provided blood and sputum samples during exacerbations, along with five stable-state samples as controls. Exacerbations were classified using 16S rRNA sequencing to analyze the sputum microbiota and multiplex PCR to detect respiratory viruses. Blood transcriptomic profiling was conducted using Oxford Nanopore technology, followed by differential gene expression and pathway enrichment analyses. A total of 768 regulated genes were identified across the exacerbation groups, with 35 shared genes associated with neutrophil activation. Bacterial exacerbations activated pathways related to phagocytosis and toll-like receptor signaling, while viral exacerbations were linked to pro-inflammatory responses and mitochondrial damage. Exacerbations of unknown origin showed activation of pathways involved in protozoan defense and neutrophilic asthma. Biomarkers such as IFITM3 and ISG15 for bacterial exacerbations, DEFA3 for viral, and CD47 for unknown-origin exacerbations were identified. These findings highlight distinct transcriptomic profiles and biological pathways in COPD exacerbations, emphasizing the central role of neutrophil-driven inflammation and identifying potential biomarkers for improved differential diagnosis and personalized management.

Integrating Metabolomics and Genomics to Uncover the Impact of Fermented Total Mixed Ration on Heifer Growth Performance Through Host-Dependent Metabolic Pathways.

With the increasing demand for enhancing livestock production performance and optimizing feed efficiency, this study aimed to investigate the effects of fermented total mixed ration (FTMR) containing different proportions of rice straw and sheath and leaves of Zizania latifolia on systemic nutrient metabolism and oxidative metabolism under host genetic regulation and on growth performance of heifers. A total of 157 heifers aged 7-8 months were selected, and their hair was collected for whole-genome sequencing. They were randomly assigned into four groups of 18 to 21 cattle each and fed FTMR containing varying levels of rice straw (21% in LSF, 28% in MSF, 35% in HSF) or 31% sheath and leaves of Zizania latifolia (ZF) for a two-month period. At the end of trial, blood and urine samples were collected to measure biochemical indexes and metabolomics. The results showed that high rice straw content and ZF diets could increase blood glucose and non-protein nitrogen in heifers, that is, blood glucose and urea nitrogen levels in HSF and ZF groups were higher than those in LSF and MSF groups (p < 0.05). Meanwhile, the two diets could improve the antioxidant level of heifers. Urine metabolomics analysis between the groups identified three differential metabolic pathways, including 11 metabolites. Among them, l-homoserine and o-acetylserine had significant SNPs associated with them, which promoted glutathione metabolism. Although there was no significant effect of diet on heifers' average daily gain (ADG) in body weight (p > 0.05), there was substantial inter-individual variation in metabolites among all animals, as further correlation analyses illustrated. Twenty-eight metabolites were significantly associated with ADG (R > 0.3, p < 0.05). Four of them were identified as biomarkers, primarily regulating energy metabolism and oxidative balance. In conclusion, feeding HSF and ZF FTMR enhances glutathione metabolism and antioxidant capacity in heifers, positioning key metabolites as candidates for ADG markers. This integrative omics approach underscores the potential for enhancing livestock productivity and promoting sustainable agricultural practices.

Leveraging computational approaches in identifying novel HER-2 + breast cancer potential therapeutics: integrating virtual screening and molecular dynamics simulation

BackgroundBreast cancer, particularly the human epidermal growth factor receptor 2 positive subtype, presents a significant global health challenge due to its high prevalence and mortality rates. This study delves into the molecular intricacies of HER-2 positive breast cancer, with an emphasis on the role of the HER-2 oncoprotein and its associated signaling pathways in cell growth, differentiation, and survival. In our pursuit of overcoming the limitations of one of the leading therapeutic options, Lapatinib, such as its inhibition of hERG, we embarked on a comprehensive research journey.ResultThis study involved dual-stage molecular docking, initially with a library of PubChem-curated compounds, revealing Compound 90196902 as the best of the set. This was followed by the docking of DataWarrior-generated structural analogs of Compound 90196902, using various docking protocols such as standard precision, extra precision, and induced fit docking. Through this rigorous screening protocol, three promising drug candidates (Compound_56, Compound_81, and Compound_339) were identified, showing excellent interaction with the target. Additionally, binding free energy calculations, ADME and toxicity profiling, and molecular dynamics simulations presented these compounds as lead-like.ConclusionCompound_56 showed the most promising pharmacodynamic and pharmacokinetic properties, coupled with substantial structural stability. While immensely promising, further optimization and pre-clinical investigation are imperative to validate this compound as a viable alternative to existing therapies for HER-2 positive breast cancer.Graphical abstract

Deciphering glioblastoma pathogenesis: Insights from mitophagy dysregulation and SNX7 as a therapeutic target.

Glioblastoma is a highly aggressive and invasive brain tumor with an extremely poor prognosis. The aims of the present study are to investigate the pathogenesis of glioblastoma and identify potential therapeutic targets. We performed a systematic analysis of gene expression data from multiple datasets, including GEO and TCGA, to identify hub genes and pathways associated with glioblastoma progression. Bioinformatics tools were utilized to analyze differential gene expression, pathway enrichment and survival prognosis. Both in vitro and in vivo functional experiments were conducted to validate biological roles of SNX7. Pathway analysis revealed significant enrichment of the mitophagy pathway in glioblastoma, indicating its critical role in tumor development. We identified 12 hub genes associated with glioblastoma prognosis, with high-risk patients having worse survival outcomes. Among the hub gene set, sorting nexin 7 (SNX7) was found to be the most significant regulator of glioblastoma progression. Our results also demonstrated that SNX7 expression is associated with tumor ferroptosis and genomic variations, representing potential biomarkers for clinical diagnosis and treatment. Furthermore, functional experiments confirmed that SNX7 promotes glioblastoma cell proliferation, invasion and survival by inhibiting protective mitophagy. Our results highlight the importance of mitophagy dysregulation in the pathogenesis of glioblastoma and identify SNX7 as a novel therapeutic target. Further research is needed to elucidate the underlying mechanisms of SNX7 in glioblastoma and validate its clinical significance. These findings may facilitate the development of personalized treatment strategies and improve outcomes for glioblastoma patients.

Comparative Metabolomics in Liver Reveals Eggshell Translucency Formation Using LC-MS Analysis

Eggshell translucency is the common problem on eggshell that become more severe with age. They are important because it influence consumer preferences and the economic value of eggs. The reason for the eggshell translucency is currently believed to be the eggshell membrane (ESM). In this study, we screened translucency eggs and normal eggs and used metabolomics to study liver metabolism in different eggshell translucency and discuss important liver lipids and phosphatidyl metabolites. Liver samples were taken for Liquid Chromatograph Mass Spectrometer (LC-MS) during the formation of eggshell membranes in hens, that is, when eggs form eggshell membranes in the oviduct isthmus. The results showed that we identified two essential metabolic pathways through differential metabolite pathway analysis, which were glycine, serine, and threonine metabolism related to amino acids metabolism and the PPAR metabolic pathway related to lipid metabolism. Furthermore, this study helps us understand the process of translucency egg production in poultry. This laid the foundation for in-depth research on eggshell translucency. These results may and provide support for future breeding.

Polysaccharides from Yupingfeng granules ameliorated cyclophosphamide-induced immune injury by protecting intestinal barrier.

Immune injury is the main side effect caused by cyclophosphamide and the disruption of the intestinal barrier may be an important cause. Yupingfeng granules have been reported to have immunomodulatory effects and polysaccharides are important components of them. This study aimed to investigate the ameliorative effect of polysaccharides from Yupingfeng granules (YPFP) on cyclophosphamide induced immune injury and reveal their potential mechanisms based on its protective effect on the intestine. YPFP were isolated and preliminarily characterized. Pharmacodynamic evaluation revealed that YPFP treatment could effectively mitigate lesions of immune organs, ameliorate white blood cells and downregulate IL-10 level. Further, the protective effect of intestinal barrier on the basis of intestinal tight junctions, MUC-2, microflora, endogenous metabolites, pathways and immune cells was discussed to outline mechanisms. The results showed that YPFP repaired the integrity of intestinal epithelium, enhanced the abundance of Muribaculaceae_unclassified, Bacteroide and Muribaculum, downgraded the abundance of Lachnospiraceae_NK4A136_group, improved the excretion of lipids and bile acids especially 3-oxo-LCA, increased the content of SCFAs in feces and inhibited the expression of key proteins of PI3K-AKT and MAPK-JUN pathways. More importantly, Th17 and Treg balance was remodeled after YPFP administration, which might be related to certain differential metabolites and pathways enriched by metabolomics. This study provides a rich understanding of YPFP and lays a foundation for further development of Yupingfeng granules. It was shown for the first time that the immunomodulatory effect of YPFP might be involved in multiple mechanisms of intestinal homeostasis. YPFP could be regarded as an immunomodulator to alleviate immune damage caused by cyclophosphamide.

Microbiota dynamics and metabolic mechanisms in fermented sausages inoculated with Lactiplantibacillus plantarum and Staphylococcus xylosus.

Lactiplantibacillus plantarum and Staphylococcus xylosus are common starters for fermented sausages. Several studies have demonstrated the impact of these two strains on the quality of fermented sausages. However, the mechanism underlying the effects of these two microorganisms on co-cultivation in sausages remains unclear. This study aimed to investigate the effects of inoculation with various combinations of starters on the microbial communities and metabolic profiles of fermented sausages. High-throughput sequencing revealed that, during sausage fermentation, Firmicutes was the dominant bacterial phylum, and the primary microorganisms were Lactococcus, Staphylococcus, Lactobacillus, and Pseudomonas. On the last day of fermentation, the highest abundance of Staphylococcus was observed in the co-inoculation group. Furthermore, inoculated fermentation effectively inhibited the growth of pathogenic and spoilage bacteria. Metabolomic analysis of the four groups of samples identified 208 metabolites in positive ion mode and 109 in negative ion mode. A total of 31 differential metabolites were identified (P<0.05, variable importance in the projection >1.5), primarily benzene and substituted derivatives, carboxylic acids and derivatives, and fatty acyls. Five crucial differential metabolites (subaphylline, naringenin, 1-hexadecanol, beta-alanyl-L-lysine, and 3'-AMP) were identified as potential biomarkers for fermented sausages. Key differential metabolite metabolic pathways indicated that L. plantarum YR07 dominated in metabolite regulation during sausage fermentation, and S. xylosus Y-18 downregulated the fatty acid degradation pathway, which also affected the metabolism of fermented sausages. Co-cultivation of the two bacteria exhibited a synergistic effect on the metabolism of the fermented sausages. This study offers further insights into improving the quality of fermented sausages, thereby establishing a theoretical foundation for the production of excellent fermenters.

Proteomics and transcriptomic analyses provide new insights into the pectin polysaccharide biosynthesis in Premna puberula Pamp

Premna puberula Pamp. is a plant with similarities to both food and medicine, which has attracted the attention of researchers because of the rich pectin in its leaves. However, the mechanism of efficient pectin accumulation remains unclear. Through transcriptomic and proteomic analyses, this study investigated the differentially expressed genes and proteins associated with pectin during various developmental stages of P. puberula. The combined omics approach revealed that the majority of differential genes are mainly involved in the anabolic metabolism of primary and secondary metabolites. Notable differential pathways include starch and sucrose metabolism, amino acid sugar metabolism, and nucleotide sugar metabolism. The SWEET gene family was identified and analyzed, leading to the cloning of PpSWEET15 and subcellular localization. Overexpression of PpSWEET15 resulted in a significant decrease in sucrose content in leaves from 134.44 μg·g−1 to <10 μg·g−1. Glucose content decreased from 407.75 μg·g−1 to 318.38 μg·g−1, while fructose levels showed no significant difference between the two groups of leaves. This comprehensive transcriptomic and proteomic analysis provides valuable insights into the molecular mechanisms underlying the efficient accumulation of pectin in P. puberula.

High-selenium exposure is associated with modulation of serum lipid metabolism.

At present, there is no consensus on the relationship between selenium (Se) exposure and human serum lipid metabolism. The etiological role of high-Se exposure in lipid markers, dyslipidemia, and nonalcoholic fatty liver (NAFLD) remains unclear. We used serum untargeted metabolomics analysis to evaluate whether high-Se exposure is cross-sectionally associated with lipid metabolism in adults from high-Se exposure area (n = 112) and control area (n = 101) in Hubei Province, China. An untargeted liquid chromatography/mass spectrometry (LC/MS)-based metabolomic analysis identified 144 differential pathways and yielded 204 differentially abundant metabolites, including 32 lipid metabolites associated with lipids profiles. To further explore the correlation between Se exposure and serum lipid metabolism, we measured serum levels of lipid profiles among all the people, including serum cholesterol (CHOL), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and apolipoprotein B (APOB). The average serum Se level of the high-Se exposure group was 537.18 μg/L, significantly higher than 72.98 μg/L in the control group (p < 0.0001). The measurement levels of serum TG, LDL-C, HDL-C, and APOB in the high-Se exposure group were 1.03 (0.76, 1.34) mmol/L, 2.25 ± 0.48 mmol/L, 1.12 ± 0.24 mmol/L, and 0.77 ± 0.15 g/L, respectively, while the control group were 1.13 (0.84, 1.80) mmol/L, 2.56 ± 0.61 mmol/L, 1.02 ± 0.22 mmol/L, and 0.83 ± 0.16 g/L, respectively (all p values <0.05). Correlation analysis showed a significant negative correlation between serum Se and CHOL (r = -0.201, p < 0.01), serum Se is also associated with metabolomics markers, the negative correlation includes glyceric acid and ect., the positive correlation includes phosphorylcholine and ect. Our study suggests that high-Se exposure is negatively associated with serum lipid profiles and decreases the risk of high-TC and HDL-C dyslipidemia.

The phospholipid kinase PIKFYVE is essential for Th17 differentiation.

T helper 17 (Th17) cells are effector cells that mediate inflammatory responses to bacterial and fungal pathogens. While the cytokine signaling inputs required to generate Th17s are established, less is known about intracellular pathways that drive Th17 differentiation. Our previously published phosphoproteomic screen identifies that PIKFYVE, a lipid kinase that generates the phosphatidylinositol PtdIns(3,5)P2, is activated during Th17 differentiation. Herein, we discovered that PIKFYVE regulates kinase and transcription factor networks to promote Th17 differentiation. As a specific example, PtdIns(3,5)P2 directly stimulates mTORC1 kinase activity to promote cell division and differentiation pathways. Furthermore, PIKFYVE promotes STAT3 phosphorylation, which is required for Th17 differentiation. Chemical inhibition or CD4-specific deletion of PIKFYVE reduces Th17 differentiation and autoimmune pathology in the experimental autoimmune encephalomyelitis murine model of multiple sclerosis. Our findings identify molecular mechanisms by which PIKFYVE promotes Th17 differentiation and suggest that PIKFYVE is a potential therapeutic target in Th17-driven autoimmune diseases.

Exploitation of Key Regulatory Modules and Genes for High-Salt Adaptation in Schizothoracine by Weighted Gene Co-Expression Network Analysis

Schizothoracine fishes in saltwater lakes of the Tibetan Plateau are important models for studying the evolution and uplift of the Tibetan Plateau. Examining their adaptation to the high-salt environment is interesting. In this study, we first assembled the RNA-Seq data of each tissue of G. przewalskii, G. selincuoensis, and G. namensis from Qinghai Lake, Selincuo Lake, and Namtso Lake, respectively, obtained by the group previously. After obtaining reliable results, the adaptation of the gills, kidneys, and livers of the three species to the high-salinity environment was assessed by weighted gene co-expression network analysis (WGCNA). Using module eigengenes (ME), 21, 22, and 22 gene modules were identified for G. przewalskii, G. selincuoensis, and G. nemesis, respectively. Functional clustering analysis of genes in the significant association module identified several genes associated with osmolarity-regulated potential KEGG pathways in the gills of three species of Schizothoracine fish. Th17 cell differentiation pathway was up-regulated in the gills of all three species; histocompatibility class 2 II antigen and E alpha (h2-ea) were up-regulated genes in this pathway. Functional clustering analysis of genes in apparently related modules in the kidney unveiled several differential KEGG pathways. The pentose phosphate pathway was up-regulated in the three Schizothoracine fishes, and glucose-6-phosphate dehydrogenase (g6pd) was an up-regulated gene in this pathway. In the livers of the three Schizothorax species, the propanoate metabolism pathway was up-regulated, and succinate-CoA ligase GDP-forming subunit beta (suclg2) was an up-regulated gene in this pathway. The above analyses provide reference data for the adaptation of Schizothorax to high-salt environments and lay the foundation for future studies on the adaptive mechanism of Schizothorax in the plateau. These results partly fill the void in the knowledge gap in the survival adaptations of Schizothoracine fishes to highland saline lakes.

Untargeted metabolite profiling reveals metabolic disorders in livers of rats with mepiquat exposure.

Mepiquat is a contaminant produced in thermal-processed food. It can induce spleen and liver injury. However, the mechanism that mepiquat induced hepatotoxicity remains unclear. In this study, a ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS)-based metabolomic analysis of livers in rats was performed to explore metabolic alterations. Our results demonstrated that there were 36 differential metabolites. Eleven major disordered metabolic pathways were found. Network analysis of differential metabolites and metabolic pathways indicated that glutamic acid was a possible key upregulated metabolite. It participated in nine metabolic networks. Glutathione and l-proline may be key downregulated metabolites. They were involved in eight and seven metabolic pathways, respectively. Compared with the control group, serum concentrations of alanine aminotransferase, aspartate aminotransferase, and total bile acid in high dosage group increased significantly. In addition, histopathological analysis showed liver injury in rats with mepiquat exposure. These data were consistent with results of metabolomics. Our results offered new insights for molecular mechanism of liver toxicity induced by mepiquat. PRACTICAL APPLICATION: Mepiquat is a contaminant formed in thermal-processed food. It can induce spleen and liver injury. Our results offered new insights for molecular mechanism of liver toxicity induced by mepiquat. It will provide important information for official limits of mepiquat in foods.