Trans-omic analysis reveals opposite metabolic dysregulation between feeding and fasting in liver associated with obesity.

Dysregulation of liver metabolism associated with obesity during feeding and fasting leads to the breakdown of metabolic homeostasis. However, the underlying mechanism remains unknown. Here, we measured multi-omics data in the liver of wild-type and leptin-deficient obese (ob/ob) mice at ad libitum feeding and constructed a differential regulatory trans-omic network of metabolic reactions. We compared the trans-omic network at feeding with that at 16 h fasting constructed in our previous study. Intermediate metabolites in glycolytic and nucleotide metabolism decreased in ob/ob mice at feeding but increased at fasting. Allosteric regulation reversely shifted between feeding and fasting, generally showing activation at feeding while inhibition at fasting in ob/ob mice. Transcriptional regulation was similar between feeding and fasting, generally showing inhibiting transcription factor regulations and activating enzyme protein regulations in ob/ob mice. The opposite metabolic dysregulation between feeding and fasting characterizes breakdown of metabolic homeostasis associated with obesity.

In-situ synthesis of ZIF-8 on magnetic pineapple leaf biochar as an efficient and reusable adsorbent for methylene blue removal from wastewater.

The presence of organic dyes in aquatic systems poses a significant threat to ecosystems and human well-being. Due to recycling challenges, traditional commercial activated carbon is not cost-effective. To address this, an imidazolate acid zeolite framework-8 (ZIF-8)-modified magnetic adsorbent (ZMPLB-800) was synthesized through the in-situ formation of ZIF-8 and subsequent carbonization at 800 °C, using magnetic pineapple leaf biochar (MPLB) as a carrier. The porous structure of ZMPLB-800 facilitates the rapid passage of dye molecules, enhancing adsorption performance. ZMPLB-800 exhibited remarkable adsorption capacity for methylene blue (MB) across a pH range of 3-13, with a maximum adsorption capacity of 455.98 mg g-1. Adsorption kinetics and thermodynamics followed the pseudo-second-order kinetic model and Langmuir isotherm model. Mechanisms of MB adsorption included pore filling, hydrogen bonding, electrostatic interactions, π-π interactions, and complexation through surface functional groups. Additionally, ZMPLB-800 demonstrated excellent regeneration performance, recording a removal efficiency exceeding 87% even after five adsorption/desorption cycles. This study provides a novel strategy for treating dye wastewater with MOF composites, laying the foundation for waste biomass utilization.

American Ginseng for the Treatment of Alzheimer's Disease: A Review.

Alzheimer's disease (AD) is a prevalent degenerative condition that is increasingly affecting populations globally. American ginseng (AG) has anti-AD bioactivity, and ginsenosides, as the main active components of AG, have shown strong anti-AD effects in both in vitro and in vivo studies. It has been reported that ginsenosides can inhibit amyloid ß-protein (Aß) production and deposition, tau phosphorylation, apoptosis and cytotoxicity, as well as possess anti-oxidant and anti-inflammatory properties, thus suppressing the progression of AD. In this review, we aim to provide a comprehensive overview of the pathogenesis of AD, the potential anti-AD effects of ginsenosides found in AG, and the underlying molecular mechanisms associated with these effects. Additionally, we will discuss the potential use of AG in the treatment of AD, and how ginsenosides in AG may exert more potent anti-AD effects in vivo may be a direction for further research.

Virus-like silica nanoparticles enhance macromolecule permeation in vivo.

Nanoparticle based permeation enhancers have the potential to improve the oral delivery of biologics. Recently, solid silica nanoparticles were discovered to improve the intestinal permeability of peptides and proteins via transient opening of the gut epithelium. In this study, we have developed small-sized (∼60 nm) virus-like silica nanoparticles (VSNP) as a reversible and next generation non-toxic permeation enhancer for oral delivery of biologics. Our results show that the anionic VSNP showed a better permeation-enhancing effect than the same sized spherical Stöber silica nanoparticles (∼60 nm) by enhancing the apparent insulin permeability by 1.3-fold in the Caco-2 monolayer model and by 1.2-fold in the Caco-2/MTX-HT-29 co-culture model. In vivo experiments in healthy mice demonstrated that anionic VSNP significantly enhanced the permeation of fluorescently labelled 4 kDa dextran after oral administration compared to Stöber nanoparticles and positively charged VSNP. The results indicated that the nanoscale surface roughness is an important consideration when designing nanoparticle-based permeation enhancers. Overall, our study shows for the first time that small-sized (∼60 nm) VSNP with nanoscale surface roughness can be used as a non-toxic permeation enhancer for oral delivery of therapeutic peptides and proteins.

In vivo transomic analyses of glucose-responsive metabolism in skeletal muscle reveal core differences between the healthy and obese states.

Metabolic regulation in skeletal muscle is essential for blood glucose homeostasis. Obesity causes insulin resistance in skeletal muscle, leading to hyperglycemia and type 2 diabetes. In this study, we performed multiomic analysis of the skeletal muscle of wild-type (WT) and leptin-deficient obese (ob/ob) mice, and constructed regulatory transomic networks for metabolism after oral glucose administration. Our network revealed that metabolic regulation by glucose-responsive metabolites had a major effect on WT mice, especially carbohydrate metabolic pathways. By contrast, in ob/ob mice, much of the metabolic regulation by glucose-responsive metabolites was lost and metabolic regulation by glucose-responsive genes was largely increased, especially in carbohydrate and lipid metabolic pathways. We present some characteristic metabolic regulatory pathways found in central carbon, branched amino acids, and ketone body metabolism. Our transomic analysis will provide insights into how skeletal muscle responds to changes in blood glucose and how it fails to respond in obesity.

Trans-omics analysis of insulin action reveals a cell growth subnetwork which co-regulates anabolic processes.

Insulin signaling promotes anabolic metabolism to regulate cell growth through multi-omic interactions. To obtain a comprehensive view of the cellular responses to insulin, we constructed a trans-omic network of insulin action in Drosophila cells that involves the integration of multi-omic data sets. In this network, 14 transcription factors, including Myc, coordinately upregulate the gene expression of anabolic processes such as nucleotide synthesis, transcription, and translation, consistent with decreases in metabolites such as nucleotide triphosphates and proteinogenic amino acids required for transcription and translation. Next, as cell growth is required for cell proliferation and insulin can stimulate proliferation in a context-dependent manner, we integrated the trans-omic network with results from a CRISPR functional screen for cell proliferation. This analysis validates the role of a Myc-mediated subnetwork that coordinates the activation of genes involved in anabolic processes required for cell growth.

MicroRNA-302s Might Regulate ARL4C-Mediated Gastric Cancer Progression via p53 Signaling: Bioinformatics Analysis and Experiments Validation.

BACKGROUND: Our previous studies demonstrate that ARL4C is the most critical clinical biomarker for gastric cancer (GC) patients among ARL family members (ARLs) and functions as an oncogene in GC. However, its underlying mechanisms in GC need to be further illustrated. In this study, we aim to explore the upstream and downstream molecular mechanisms of ARL4C in GC cells. METHODS: The genetic alteration of ARL4C in GC is analyzed by cBioPortal database. Potential ARL4C-targeted microRNAs (miRs) are predicted by three databases. The high-throughput RNA sequencing is performed to explore the underlying mechanisms of ARL4C in GC cells. The effects of predicted microRNAs on ARL4C, the RNA-sequencing results validation and the biological functions of ARL4C in GC cells are illustrated by in vitro experiments. RESULTS: Genetic analyses indicate that ARL4C is significantly upregulated in GC, which is not caused by gene amplification. MicroRNAs prediction shows the high relevance between ARL4C and miR-302 members. Moreover, miR-302c or miR-302d transfection reduces ARL4C protein expression in GC cells. Based on the high-throughput RNA sequencing of ARL4C-knockdown cells, enrichment analyses demonstrate that ARL4C is closely related to cell growth and involved in p53 signaling. Moreover, there are strong gene-gene interactions between ARL4C and genes in p53 signaling, and ARL4C downregulation could inhibit the protein expression of MDM2, a critical gene in p53 pathway. Further functional experiments demonstrate that ARL4C silencing leads to cell cycle arrest and increased cell apoptosis in AGS and MKN45 cells. CONCLUSION: Our data suggest that miR-302c and miR-302d may function as the upstream regulators of ARL4C. And, ARL4C might promote GC cell cycle progression via regulating p53 signaling. Our findings provide novel insights into the key role of ARL4C and the underlying mechanisms in GC progression, thus facilitating the development of ARL4C-targeted therapy.

Trans-omic analysis reveals obesity-associated dysregulation of inter-organ metabolic cycles between the liver and skeletal muscle.

Systemic metabolic homeostasis is regulated by inter-organ metabolic cycles involving multiple organs. Obesity impairs inter-organ metabolic cycles, resulting in metabolic diseases. The systemic landscape of dysregulated inter-organ metabolic cycles in obesity has yet to be explored. Here, we measured the transcriptome, proteome, and metabolome in the liver and skeletal muscle and the metabolome in blood of fasted wild-type and leptin-deficient obese (ob/ob) mice, identifying components with differential abundance and differential regulation in ob/ob mice. By constructing and evaluating the trans-omic network controlling the differences in metabolic reactions between fasted wild-type and ob/ob mice, we provided potential mechanisms of the obesity-associated dysfunctions of metabolic cycles between liver and skeletal muscle involving glucose-alanine, glucose-lactate, and ketone bodies. Our study revealed obesity-associated systemic pathological mechanisms of dysfunction of inter-organ metabolic cycles.

ARL4C might serve as a prognostic factor and a novel therapeutic target for gastric cancer: bioinformatics analyses and biological experiments.

The ADP-ribosylation factor-like proteins (ARLs) have been proved to regulate the malignant phenotypes of several cancers. However, the exact role of ARLs in gastric cancer (GC) remains elusive. In this study, we systematically investigate the expression status, interactive relations, potential pathways, genetic variations and clinical values of ARLs in GC. We find that ARLs are significantly dysregulated in GC and involved in various cancer-related pathways. Subsequently, machine learning models identify ARL4C as one of the two most significant clinical indicators among ARLs for GC. Furthermore, ARL4C silencing remarkably inhibits the growth and metastasis of GC cells both in vitro and in vivo. Moreover, enrichment analysis indicates that ARL4C is highly correlated with TGF-ß1 signalling. Correspondingly, TGF-ß1 treatment dramatically increases ARL4C expression and ARL4C knockdown inhibits the phosphorylation level of Smads, downstream factors of TGF-ß1. Meanwhile, the coexpression of ARL4C and TGF-ß1 worsens the prognosis of GC patients. Our work comprehensively demonstrates the crucial role of ARLs in the carcinogenesis of GC and the specific mechanisms underlying the GC-promoting effects of TGF-ß1. More importantly, we uncover the great promise of ARL4C-targeted therapy in improving the efficacy of TGF-ß1 inhibitors for GC patients.

Novel Metabolomics Serum Biomarkers for Pancreatic Ductal Adenocarcinoma by the Comparison of Pre-, Postoperative and Normal Samples.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive human malignancies. The metabolomic approaches are developed to discover the novel biomarkers of PDAC. Methods: 550 preoperative, postoperative PDAC and normal controls (NCs) serums were employed to characterize metabolic alterations in training and validation sets by LC-MS. Results: The results of PLS-DA analysis indicated that three groups could be distinguished clearly and the post-PDAC group is adjacent to a normal group as compared with pre-PDAC group. Further results showed that histidinyl-lysine significantly increased whereas docosahexaenoic acid and LysoPC (14:0) decreased in pre-PDAC patients as compared with NCs. And these three markers had a significant tendency to recover after tumor resection. The validation set results revealed that for CA19-9 negative patients, 92.3% (12/13) of them can be screened using these three metabolites. The combination of these markers could significantly improve the diagnostic performance for PDAC, with higher sensitivity (0.93), specificity (0.92) and AUC (0.97). Moreover, network and pathways analyses explored the latent relationship among differential metabolites. The glycerolipid metabolism and primary bile acid synthesis showed variation in network and pathway analysis. Conclusions: These three markers combined with CA199 displayed high sensitivity and specificity for detecting PDAC patients from NCs. The results indicated that these three metabolites could be regarded as potential biomarkers to distinguish PDAC from NCs.

SCIA: A Novel Gene Set Analysis Applicable to Data With Different Characteristics.

Gene set analysis is commonly used in functional enrichment and molecular pathway analyses. Most of the present methods are based on the competitive testing methods which assume each gene is independent of the others. However, the false discovery rates of competitive methods are amplified when they are applied to datasets with high inter-gene correlations. The self-contained testing methods could solve this problem, but there are other restrictions on data characteristics. Therefore, a statistically rigorous testing method applicable to different datasets with various complex characteristics is needed to obtain unbiased and comparable results. We propose a self-contained and competitive incorporated analysis (SCIA) to alleviate the bias caused by the limited application scope of existing gene set analysis methods. This is accomplished through a novel permutation strategy using a priori biological networks to selectively permute gene labels with different probabilities. In simulation studies, SCIA was compared with four representative analysis methods (GSEA, CAMERA, ROAST, and NES), and produced the best performance in both false discovery rate and sensitivity under most conditions with different parameter settings. Further, the KEGG pathway analysis on two real datasets of lung cancer showed that the results found by SCIA in both of the two datasets are much more than that of GSEA and most of them could be supported by literature. Overall, SCIA promisingly offers researchers more reliable and comparable results with different datasets.

Lipidomics characterization of the alterations of Trichoderma brevicompactum membrane glycerophospholipids during the fermentation phase.

The biological membrane lipid composition has been demonstrated to greatly influence the secretion of secondary metabolites. This study was conducted to investigate the periodical alterations of whole cellular lipids and their associations with secondary products in Trichoderma brevicompactum. An electrospray ionization-mass spectrometry-based lipidomics strategy was used to acquire the metabolic profiles of membrane lipids during fermentation. Univariate analyses showed that most fungi glycerophospholipids were significantly altered at the early phase compared with the late phase. In addition, correlation analyses showed high correlations between phosphatidylcholine alterations and fermentation duration. In addition, the fermentation-associated alterations of phosphatidylcholines were found to be in accordance with the degrees of unsaturation of acyl-chains. Harzianum A reached a maximum on the 12th day, while trichodermin and 6-pentyl-2H-pyran-2-one showed the highest abundances on the 9th day, both of which were inclined to correlate with the alterations of phosphatidylcholines and phosphatidylethanolamines, respectively. These findings demonstrated that the alterations of the membrane lipid species in Trichoderma spp. were associated with the fermentation phases and might influence the secretion of specific secondary products, which may be useful in studying the optimization of secondary products in Trichoderma spp.

Integrated Lipidomics and Transcriptomics Characterization upon Aging-Related Changes of Lipid Species and Pathways in Human Bone Marrow Mesenchymal Stem Cells.

Aberrant differentiations of bone mesenchymal stem cells (BMSCs) have proved to be associated with the occurrence of senile osteoporosis. However, mechanisms of this phenomenon relative to abnormal lipid metabolism remain unclear. This study was conducted to characterize the lipidomics alterations during BMSC passaging, aiming at uncovering the aging-related lipid metabolism that may play an important role in aberrant differentiations of BMSCs. Principal component analysis presented the sequential lipidomics alterations during BMSC passaging. The majority of glycerophospholipids, including phosphatidylcholines, phosphatidylethanolamines, phosphatidylglycerols, as well as sphingolipids, revealed significant elevations, whereas the others, including phosphatidic acids, phosphatidylinositols, and phosphatidylserines, presented decreases in aged cells. Double-bond equivalent versus carbon number plots demonstrated that the changing trends and significances of lipids during passaging were associated with the chain length and the degree of unsaturation. In the correlation networks, the scattering patterns of lipid categories suggested the category-related metabolic independence and potential conversion among phosphatidic acids, phosphatidylinositols, and phosphatidylserines. The lipid-enzyme integrated pathway analysis indicated the activated metabolic conversion from phosphatidic acids to CDP-diacylglycerol to phosphatidylinositols and from sphingosine to ceramides to sphingomyelins with BMSC passaging. The conversions among lipid species described the lipidomics responses that potentially induced the aberrant differentiations during BMSC aging.

Metabolic profiling analysis upon acylcarnitines in tissues of hepatocellular carcinoma revealed the inhibited carnitine shuttle system caused by the downregulated carnitine palmitoyltransferase 2.

The carnitine shuttle system (CSS) plays a crucial role in the transportation of fatty acyls during fatty acid ß-oxidation for energy supplementation, especially in cases of high energy demand, such as in cancer. In this study, to systematically characterize alterations of the CSS in hepatocellular carcinoma (HCC), acylcarnitine metabolic profiling was carried out on 80 pairs of HCC tissues and adjacent noncancerous tissues (ANTs) by using ultra-performance liquid chromatography coupled to mass spectrometry. Twenty-four acylcarnitines classified into five categories were identified and characterized between HCCs and ANTs. Notably, increased saturated long-chain acylcarnitines (LCACs) and decreased short- and medium-chain acylcarnitines (S/MCACs) were simultaneously observed in HCC samples. Subsequent correlation network and heatmap analysis indicated low correlations between LCACs and S/MCACs. The mRNA and protein expressions of carnitine palmitoyltransferase 2 (CPT2) was significantly downregulated in HCC samples, whereas CPT1A expression was not significantly changed. Correspondingly, the relative levels of S/MCACs were reduced and those of LCACs were increased in BEL-7402/CPT2-knockdown cells compared to negative controls. Both results suggested that decreased shuttling efficiency in HCC might be associated with downregulation of CPT2. In addition, decreases in the mRNA expression of acetyl-CoA acyltransferase 2 were also observed in HCC tissues and BEL-7402/CPT2-knockdown cells, suggesting potential low ß-oxidation efficiency, which was consistent with the increased expression of stearoyl-CoA desaturase 1 in both samples. The systematic strategy applied in our study illustrated decreased shuttling efficiency of the carnitine shuttle system in HCC and can provide biologists with an in-depth understanding of ß-oxidation in HCC.

Selection of small plasma peptides for the auxiliary diagnosis and prognosis of epithelial ovarian cancer by using UPLC/MS-based nontargeted and targeted analyses.

Epithelial ovarian cancer (EOC) is the leading cause of gynecologic cancer-related death due to its nonspecific characteristics compared to benign cases and poor prognosis after conventional therapies. Small peptides (SPs) demonstrated to have potential for diagnosis and prognosis were focused on in our study for the discovery of biomarkers that address these issues. Metabolic profiles of 15 SPs, including nine dipeptides and six tripeptides were acquired from plasma samples of 140 EOC and 158 benign ovarian tumor (BOT) patients. Partial least square discriminant analysis showed separations between EOC and BOT subjects of different age brackets. Hyp-Leu, Glu-Trp and Phe-Phe were selected as promising predictive SP-biomarkers for better EOC diagnosis compared to conventional biomarkers. Combined Hyp-Leu, Glu-Trp and CA125 presented an area under the curve (AUC) of 0.904, with a sensitivity and specificity of 0.804 and 0.944, respectively. This finding suggested that the combination of these biomarkers performed much better than CA125 alone. Hyp-Leu and Gly-Phe-Trp showed significantly improved performances in the log-rank tests and Kaplan-Meier curves demonstrating their prognostic potential. All SP-biomarkers proved to have excellent stabilities at room temperature. Correlation network analysis implied latent conversions among amino acids, dipeptides and tripeptides during EOC. In conclusion, the selected SPs in combination with CA125 show profound promise for discriminating EOCs from BOTs and for predicting the progression after surgery, which provides invaluable information for clinicians in the precision diagnosis and treatment of EOC.