Integrated analysis of serum and liver metabonome in liver transplanted rats by gas chromatography coupled with mass spectrometry

An exploratory metabolomic study reveals the Dipsacus asper-Achyranthes bidentate herb pair against osteoarthritis by modulating imbalance in polyunsaturated fatty acids and energy metabolism

Osteoarthritis (OA) is a degenerative joint disease primarily affecting the cartilage. The therapeutic potential of the Dipsacus asper-Achyranthes bidentate herb pair for OA has been acknowledged, yet its precise mechanism remains elusive. In this study, we conducted a comprehensive analysis of metabolomic changes and therapeutic outcomes in osteoarthritic rats, employing a gas chromatography-mass spectrometry-based metabolomics approach in conjunction with histopathological and biochemical assessments. The rats were divided into six groups: control, model, positive control, Dipsacus asper treated, Achyranthes bidentata treated, and herb pair treated groups. Compared to the model group, significant reductions in levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), and iNOS were observed in the treated groups. Multivariate statistical analyses were employed to investigate metabolite profile changes in serum samples and identify potential biomarkers, revealing 45 differential biomarkers, with eighteen validated using standard substances. These analytes exhibited excellent linearity across a wide concentration range (R2>0.9990), with intra- and inter-day precision RSD values below 4.69% and 4.83%, respectively. Recoveries of the eighteen analytes ranged from 93.97% to 106.59%, with RSD values under 5.72%, underscoring the method's reliability. Treatment with the herbal pair effectively restored levels of unsaturated fatty acids such as linoleic acid and arachidonic acid, along with glucogenic amino acids. Additionally, levels of phosphoric acid and citric acid were reversed, indicating restoration of energy metabolism. Collectively, these findings highlight the utility of metabolomic analysis in evaluating therapeutic efficacy and elucidating the underlying molecular mechanisms of herb pairs in OA treatment.

Elevation of Lipid Metabolites in Deceased Liver Donors Reflects Graft Suffering

Liver transplantation can be performed with deceased or living donor allografts. Deceased liver grafts are donated from brain- or circulation-death patients, and they have usually suffered from a certain degree of damage. Post-transplant graft function and patient survival are closely related to liver allograft recovery. How to define the damage of liver grafts is unclear. A total of 47 liver donors, 23 deceased and 24 living, were enrolled in this study. All deceased donors had suffered from severe brain damage, and six of them had experienced cardio-pulmonary-cerebral resuscitation (CPR). The exploration of liver graft metabolomics was conducted by liquid chromatography coupled with mass spectrometry. Compared with living donor grafts, the deceased liver grafts expressed higher levels of various diacylglycerol, lysophosphatidylcholine, lysophosphatidylethanolamine, oleoylcarnitine and linoleylcarnitine; and lower levels of cardiolipin and phosphatidylcholine. The liver grafts from the donors with CPR had higher levels of cardiolipin, phosphatidic acid, phosphatidylcholine, phatidylethanolamine and amiodarone than the donors without CPR. When focusing on amino acids, the deceased livers had higher levels of histidine, taurine and tryptophan than the living donor livers. In conclusion, the deceased donors had suffered from cardio-circulation instability, and their lipid metabolites were increased. The elevation of lipid metabolites can be employed as an indicator of liver graft suffering.

Effects of Centella asiatica extract on antioxidant status and liver metabolome of rotenone-treated rats using GC-MS

Centella asiatica has been used as a culinary vegetable or medicinal herb. In this study, the hepatoprotective effect of the standardized extract of C. asiatica (ECa233) in rotenone-treated rats was examined using a GC-MS-based metabolomic approach. ECa233 contains >80% triterpenoids with a ratio of madecassoside to asiaticoside of 1.5(±0.5):1. Rats were randomly divided into three groups (with six rats/group): sham negative control, rotenone positive control and the ECa233 test group. Rats in the ECa233 group received 10 mg/kg ECa233 orally for 20 days, followed by 2.5 mg/kg intraperitoneal rotenone injection to induce toxicity before being sacrificed. Metabolomic analysis showed that supplementation of ECa233 protected rat liver against rotenone toxicity. Pipecolinic acid was one of the most important metabolites; its level was decreased in the rotenone group as compared with the control. Supplementation with ECa233 before administration of rotenone raised pipecolinic acid to levels intermediate between controls and rotenone alone. The metabolomics approach also helped discover a possible new genuine epimetabolite in the present work. Antioxidant tests revealed that ECa233 inhibited lipid peroxidation and increased catalase activities in liver tissue.

Global and untargeted metabolomics evidence of the protective effect of different extracts of Dipsacus asper Wall. ex C.B. Clarke on estrogen deficiency after ovariectomia in rats

ETHNOPHARMACOLOGICAL RELEVANCE

Dipsacus asper Wall. ex C.B. Clarke (DA) is an effectively traditional Chinese medicine for treating osteoporosis and bone fracture. Until now, studies on pharmacological mechanism of DA mostly centered on cell and gene level, little is known about its metabolic signatures. The aim of this study is to investigate the anti-osteoporosis effects of crude and wine-processed DA by global and untargeted metabolic profiling of rats serum, liver and kidney derived from sham, model and treated groups.

METHOD

A total of 25 female Wistar rats were divided into five groups: sham group, model group, E2, crude and wine-processed DA treated group. The treatment rats were orally administered 17β-estradiol, crude and wine-processed DA extract at a therapeutic dose once daily throughout the experimental period, while sham group and model group were orally gavaged approximately volume of saline solution. After 16 weeks, all serum, liver and kidney samples of five groups were collected and their metabolomic alterations were monitored by gas chromatography-mass spectrometry (GC-MS). The resulting dataset was analyzed by principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The identification of all potential biomarkers was performed using reference standard or NIST library. Moreover, clinical chemistry and biomechanical analysis were also performed to ensure the success of the osteoporosis model and to validate the anti-osteoporosis effect of crude and wine-processed DA.

RESULTS

Clear separation trend among sham, model and treatment group was observed in PCA score plot. The anti-osteoporosis effect of DA and wine-processed DA can be indicated in PLS-DA score plots. A total of 80 and 74 metabolite biomarkers were identified for DA and wine-processed DA treated groups, respectively. Pathway analysis revealed that phenylalanine, tyrosine and tryptophan biosynthesis, valine, leucine and isoleucine biosynthesis, methane metabolism, glycine, serine and threonine metabolism, galactose metabolism were the major intervened pathways. Compared with model group, levels of all biomarkers were gradually restored to normal after administration of DA and wine-processed DA.

CONCLUSION

The anti-osteoporosis effect of DA and wine-processed DA has been reliably confirmed by the metabolomics approach. The osteoporosis might be prevented by DA and wine-processed DA via intervening amino acid metabolism, carbohydrate metabolism and energy metabolism in vivo in rats.

Untargeted serum metabolomics reveals Fu-Zhu-Jiang-Tang tablet and its optimal combination improve an impaired glucose and lipid metabolism in type II diabetic rats

Fu-Zhu-Jiang-Tang tablet, a six-herb preparation, was proved to show beneficial effects on type II diabetes patients in clinical. This study aims to optimize the component proportion of the six-herb preparation and explore the serum metabolic signatures of type II diabetes rats after treatment with Fu-Zhu-Jiang-Tang tablet and its optimal combination. The component proportion of the preparation was optimized using uniform experimental design and machine learning techniques. Untargeted GC-MS metabolomic experiments were carried out with serum samples from model group and treatment groups. Data were normalized, multivariate and univariate statistical analysis performed and metabolites of interest putatively identified. 23 metabolites were significantly changed by Fu-Zhu-Jiang-Tang tablet treatment and the majority of these were decreased, including various carbohydrates (glucose, mannose, fructose, allose and gluconic acid), unsaturated fatty acids (palmitic acid, 9-octadecenoic acid, oleic acid, arachidonic acid), alanine, valine, propanoic acid, 3-hydroxybutyrate, along with pyrimidine and cholesterol. Increased concentrations of oxalic acid, leucine, glycine, serine, threonine, proline, lysine and citrate were observed. In the optimal combination-fed group, 21 metabolites were significantly affected and strikingly, the magnitudes of changes here were generally much greater than that of Fu-Zhu-Jiang-Tang tablet treated rats. 18 metabolites affected in both groups included various carbohydrates (mannose, glucose, allose, fructose and gluconic acid), unsaturated fatty acids (palmitic acid, 9-octadecenoic acid, oleic acid and arachidonic acid), short-chain fatty acids (oxalic acid, 3-hydroxybutyrate), and amino acids (alanine, valine, leucine, glycine, proline and lysine), as well as pyrimidine. Metabolites exclusively affected in optimal combination treated rat included succinic acid, cysteine and phenylalanine, whilst four metabolites (propanoic acid, citrate, serine and threonine) were only altered in Fu-Zhu-Jiang-Tang tablet treated rat. Our investigation demonstrated Fu-Zhu-Jiang-Tang tablet and its optimal combination treatments were able to ameliorate impaired glucose and lipid metabolism, down- regulate the high level of glucose to a lower level and reverse abnormal levels of metabolites in serum of type II diabetes rats. However, the optimal combination treatment was able to maximize the magnitudes of changes in some metabolites. These findings may be helpful in clarifying the anti-diabetic mechanism of FZJT tablet and its optimal combination.

Analytical protocols based on LC-MS, GC-MS and CE-MS for nontargeted metabolomics of biological tissues

Invasive, site-specific metabolite information could be better obtained from tissues. Hence, highly sensitive mass spectrometry-based metabolomics coupled with separation techniques are increasingly in demand in clinical research for tissue metabolomics application. Applying these techniques to nontargeted tissue metabolomics provides identification of distinct metabolites. These findings could help us to understand alterations at the molecular level, which can also be applied in clinical practice as screening markers for early disease diagnosis. However, tissues as solid and heterogeneous samples pose an additional analytical challenge that should be considered in obtaining broad, reproducible and representative analytical profiles. This manuscript summarizes the state of the art in tissue (human and animal) treatment (quenching, homogenization and extraction) for nontargeted metabolomics with mass spectrometry.

Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis

The aim of this study is to find the potential biomarkers from the rat hepatocellular carcinoma (HCC) disease model by using a non-target metabolomics method, and test their usefulness in early human HCC diagnosis. The serum metabolic profiling of the diethylnitrosamine-induced rat HCC model, which presents a stepwise histopathological progression that is similar to human HCC, was performed using liquid chromatography-mass spectrometry. Multivariate data analysis methods were utilized to identify the potential biomarkers. Three metabolites, taurocholic acid, lysophosphoethanolamine 16:0, and lysophosphatidylcholine 22:5, were defined as "marker metabolites," which can be used to distinguish the different stages of chemical hepatocarcinogenesis. These metabolites represented the abnormal metabolism during the progress of hepatocarcinogenesis, which could also be found in patients. To test their diagnosis potential 412 sera from 262 patients with HCC, 76 patients with cirrhosis and 74 patients with chronic hepatitis B were collected and studied, it was found that 3 marker metabolites were effective for the discrimination of small liver tumor (solitary nodules of less than 2 cm in diameter) patients, achieved a sensitivity of 80.5% and a specificity of 80.1%,which is better than those of α-fetoprotein (53 and 64%, respectively). Moreover, they were also effective for the discrimination of all HCCs and chronic liver disease patients, which could achieve a sensitivity of 87.5% and a specificity of 72.3%, better than those of α-fetoprotein (61.2 and 64%). These results indicate metabolomics method has the potential of finding biomarkers for the early diagnosis of HCC.

Method for liver tissue metabolic profiling study and its application in type 2 diabetic rats based on ultra performance liquid chromatography-mass spectrometry

A protocol for the metabolic profiling of rat liver was developed based on ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) to explore metabolic state directly. Methanol/water (4:1, v:v) was selected as the optimal extraction solvent. The established method was validated with a linearity over the 10-5000 ng/mL for internal standards (IS) and got an average correlation coefficient of 0.9986. The intra-day and inter-day RSD for most endogenous compounds were below 15%. And the absolute recovery of IS was from 84.8% to 109.1%. Liver tissues from diabetic and control rats were enrolled in the subsequent study to show the usefulness of the method. A clear classification between the control and model animals was achieved, some significant metabolites were successfully filtered. These metabolites reflected the abnormal metabolism of diabetic rats. This initial application indicated that the method is suitable and reliable for liver tissue metabolic profiling. It is expected this protocol could also be extended to metabonomic studies of other tissues.

High-resolution magic-angle-spinning NMR spectroscopy for metabolic profiling of intact tissues

Metabolic profiling, metabolomic and metabonomic studies require robust study protocols for any large-scale comparisons and evaluations. Detailed methods for solution-state NMR spectroscopy have been summarized in an earlier protocol. This protocol details the analysis of intact tissue samples by means of high-resolution magic-angle-spinning (HR-MAS) NMR spectroscopy and we provide a detailed description of sample collection, preparation and analysis. Described here are (1)H NMR spectroscopic techniques such as the standard one-dimensional, relaxation-edited, diffusion-edited and two-dimensional J-resolved pulse experiments, as well as one-dimensional (31)P NMR spectroscopy. These are used to monitor different groups of metabolites, e.g., sugars, amino acids and osmolytes as well as larger molecules such as lipids, non-invasively. Through the use of NMR-based diffusion coefficient and relaxation times measurements, information on molecular compartmentation and mobility can be gleaned. The NMR methods are often combined with statistical analysis for further metabonomics analysis and biomarker identification. The standard acquisition time per sample is 8-10 min for a simple one-dimensional (1)H NMR spectrum, giving access to metabolite information while retaining tissue integrity and hence allowing direct comparison with histopathology and MRI/MRS findings or the evaluation together with biofluid metabolic-profiling data.

Challenges in applying chemometrics to LC–MS-based global metabolite profile data

Metabolite profiling can provide insights into the metabolic status of complex living systems through the non-targeted analysis of metabolites in any biological sample. Metabolite profiling is complementary to genomics, transcriptomics and proteomics, and its applications span epidemiology, disease diagnosis, nutrition, pharmaceutical research, and toxicology. Metabolic phenotypes are a reflection of an organism’s environment, lifestyle, diet, gut microfloral composition and are also influenced by genetic factors, with important implications in genome-wide-association studies. Specialized analytical platforms, such as NMR spectroscopy and MS, are required to interrogate such metabolic complexity. The increased sophistication of such techniques has lead to a demand for improved data analysis approaches, including preprocessing and advanced chemometric techniques. This article discusses data generation, preprocessing, multivariate analysis and data interpretation for LC-MS-based metabolite profiling, focusing on challenges encountered and potential solutions.