Metabolomic analysis to discover candidate therapeutic agents against acute pancreatitis

Multi-dimensional metabolomic profiling reveals dysregulated ornithine metabolism hallmarks associated with a severe acute pancreatitis phenotype

To reveal dysregulated metabolism hallmark that was associated with a severe acute pancreatitis (SAP) phenotype. In this study, LC-MS/MS-based targeted metabolomics was used to analyze plasma samples from 106 acute pancreatitis (AP) patients (34 mild, 38 moderate, and 34 severe) admitted within 48 hours from abdominal pain onset and 41 healthy controls. Temporal metabolic profiling was performed on days 1, 3, and 7 after admission. A random forest (RF) was performed to significantly determine metabolite differences between SAP and non-SAP (NSAP) groups. Mass spectrometry imaging (MSI) and immunohistochemistry were conducted for the examination of pancreatic metabolite and metabolic enzyme alterations, respectively, on necrosis and paracancerous tissues. Simultaneously determination of serum and pancreatic tissue metabolic alterations using an L-ornithine-induced AP model to discover metabolic commonalities. Twenty-two significant differential metabolites screened by RF were selected to build an accurate model for the prediction of SAP from NSAP (AUC = 0.955). Six of 22 markers were found by MSI with significant alterations in pancreatic lesions, reduced ornithine-related metabolites were also identified. The abnormally expressed arginase2 and ornithine transcarboxylase were further discovered in combination with time-course metabolic profiling in the SAP animal models, the decreased ornithine catabolites were found at a late stage of inflammation, but ornithine-associated metabolic enzymes were activated during the inflammatory process. The plasma metabolome of AP patients is distinctive, which shows promise for early SAP diagnosis. AP aggravation is linked to the activated ornithine metabolic pathway and its inadequate levels of catabolites in in-situ lesion.

Study on the acute toxicity of sodium taurocholate via zebrafish mortality, behavioral response, and NMR-metabolomics analysis

Sodium taurocholate (NaT) is a hydrophobic bile salt that exhibits varying toxicity and antimicrobial activity. The accumulation of BSs during their entero-hepatic cycle causes cytotoxicity in the liver and intestine and could also alter the intestinal microbiome leading to various diseases. In this research, the acute toxicity of sodium taurocholate in different concentrations (3000 mg/L, 1500 mg/L, 750 mg/L, 375 mg/L, and 0 mg/L) was investigated on four months old zebrafish by immersion in water for 96 h. The results were determined based on the fish mortality, behavioral response, and NMR metabolomics analysis which revealed LC50 of 1760.32 mg/L and 1050.42 mg/L after 72 and 96 h treatment, respectively. However, the non-lethal NaT concentrations of 750 mg/L and 375 mg/L at 96 h exposure significantly (p ≤ 0.05) decreased the total distance traveled and the activity duration, also caused surface respiration on the zebrafish. Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) revealed that the metabolome of the fish treated with 750 mg/L was discriminated from that of the control by PC1. Major significantly downregulated metabolites by NaT-induction include valine, isoleucine, 2-hydroxyvalerate, glycine, glycerol, choline, glucose, pyruvate, anserine, threonine, carnitine and homoserine. On the contrary, taurine, creatine, lactate, acetate and 3-hydroxybutyrate were upregulated suggesting cellular consumption of lipids, glucose and amino acids for adenosine triphosphate (ATP) generation during immune and inflammatory response. whereby these metabolites were released in the process. In conclusion, the research revealed the toxic effect of NaT and its potential to trigger changes in zebrafish metabolism.

Unraveling the Metabolic Changes in Acute Pancreatitis: A Metabolomics-Based Approach for Etiological Differentiation and Acute Biomarker Discovery

Acute pancreatitis (AP) remains a challenging medical condition, where a deeper metabolic insight could pave the way for innovative treatments. This research harnessed serum metabolomics to discern potential diagnostic markers for AP and distinguish between its biliary (BAP) and alcohol-induced (AAP) forms. Leveraging high-performance liquid chromatography coupled with mass spectrometry, the metabolic signatures of 34 AP patients were contrasted against 26 healthy participants, and then between different etiologies of AP. The results identified metabolites primarily from glycerophospholipids, glycerolipids, fatty acyls, sterol lipids, and pteridines and derivative classes, with the Human Metabolome Database aiding in classification. Notably, these metabolites differentiated AP from healthy states with high AUROC values above 0.8. Another set of metabolites revealed differences between BAP and AAP, but these results were not as marked as the former. This lipidomic analysis provides an introduction to the metabolic landscape of acute pancreatitis, revealing changes in multiple lipid classes and metabolites and identifying these metabolites. Future research could add and discover new diagnostic biomarkers and therapeutic strategies enhancing the management of acute pancreatitis.

Metabolic profiling of induced acute pancreatitis and pancreatic cancer progression in a mutant Kras mouse model

Untargeted Nuclear Magnetic Resonance (NMR) metabolomics of polar extracts from the pancreata of a caerulin-induced mouse model of pancreatitis (Pt) and of a transgenic mouse model of pancreatic cancer (PCa) were used to find metabolic markers of Pt and to characterize the metabolic changes accompanying PCa progression. Using multivariate analysis a 10-metabolite metabolic signature specific to Pt tissue was found to distinguish the benign condition from both normal tissue and precancerous tissue (low grade pancreatic intraepithelial neoplasia, PanIN, lesions). The mice pancreata showed significant changes in the progression from normal tissue, through low-grade and high-grade PanIN lesions to pancreatic ductal adenocarcinoma (PDA). These included increased lactate production, amino acid changes consistent with enhanced anaplerosis, decreased concentrations of intermediates in membrane biosynthesis (phosphocholine and phosphoethanolamine) and decreased glycosylated uridine phosphates, reflecting activation of the hexosamine biosynthesis pathway and protein glycosylation.

Estrogen-Related Receptor γ Maintains Pancreatic Acinar Cell Function and Identity by Regulating Cellular Metabolism

BACKGROUND & AIMS

Mitochondrial dysfunction disrupts the synthesis and secretion of digestive enzymes in pancreatic acinar cells and plays a primary role in the etiology of exocrine pancreas disorders. However, the transcriptional mechanisms that regulate mitochondrial function to support acinar cell physiology are poorly understood. Here, we aim to elucidate the function of estrogen-related receptor γ (ERRγ) in pancreatic acinar cell mitochondrial homeostasis and energy production.

METHODS

Two models of ERRγ inhibition, GSK5182-treated wild-type mice and ERRγ conditional knock-out (cKO) mice, were established to investigate ERRγ function in the exocrine pancreas. To identify the functional role of ERRγ in pancreatic acinar cells, we performed histologic and transcriptome analysis with the pancreas isolated from ERRγ cKO mice. To determine the relevance of these findings for human disease, we analyzed transcriptome data from multiple independent human cohorts and conducted genetic association studies for ESRRG variants in 2 distinct human pancreatitis cohorts.

RESULTS

Blocking ERRγ function in mice by genetic deletion or inverse agonist treatment results in striking pancreatitis-like phenotypes accompanied by inflammation, fibrosis, and cell death. Mechanistically, loss of ERRγ in primary acini abrogates messenger RNA expression and protein levels of mitochondrial oxidative phosphorylation complex genes, resulting in defective acinar cell energetics. Mitochondrial dysfunction due to ERRγ deletion further triggers autophagy dysfunction, endoplasmic reticulum stress, and production of reactive oxygen species, ultimately leading to cell death. Interestingly, ERRγ-deficient acinar cells that escape cell death acquire ductal cell characteristics, indicating a role for ERRγ in acinar-to-ductal metaplasia. Consistent with our findings in ERRγ cKO mice, ERRγ expression was significantly reduced in patients with chronic pancreatitis compared with normal subjects. Furthermore, candidate locus region genetic association studies revealed multiple single nucleotide variants for ERRγ that are associated with chronic pancreatitis.

CONCLUSIONS

Collectively, our findings highlight an essential role for ERRγ in maintaining the transcriptional program that supports acinar cell mitochondrial function and organellar homeostasis and provide a novel molecular link between ERRγ and exocrine pancreas disorders.

Temporal metabolic trajectory analyzed by LC-MS/MS based targeted metabolomics in acute pancreatitis pathogenesis and Chaiqin Chengqi decoction therapy

BACKGROUND

Acute pancreatitis (AP) is an inflammatory disorder of pancreas that lacks effective specific drugs as well as gold standard laboratory tests for diagnosis and severity assessment. Chaiqin chengqi decoction (CQCQD) has been proven to alleviate the severity and mortality of AP, but its underlying mechanisms remain incompletely understood.

PURPOSE

To investigate the correlation between metabolic trajectories of the serum and pancreas, the metabolic pathways with respect to the onset and progression of AP, and investigate the effect of CQCQD in modulating the dysregulated pancreatic metabolism of AP.

METHODS

Serum and pancreas samples from cerulein-induced AP mice were collected for pathology, biochemical index assessment, LC-MS/MS based metabolomics and functional validation over the course of 1 - 24 h. The temporal trends of pancreatic and serum metabolites in AP were analyzed using Mfuzz clustering algorithm, and their associations were revealed by Pearson correlation analysis. The metabolic trajectories and pathways across multi-timepoints were analyzed by univariate and multivariate statistical analyses, and the AP-related metabolic pathways were further screened by metabolite correlation and network interaction analyses. Finally, the changes in metabolite levels and metabolic trajectory after CQCQD therapy were identified, and the altered expression of related metabolic enzymes was verified by RT-qPCR, western blotting, and immunohistochemistry.

RESULTS

Amino acid metabolism was significantly altered in the pancreas and serum of AP, but with different trends. The unsynchronized "open" and "closed" metabolic trajectories in pancreas and serumrevealed that metabolic processes occur earlier in peripheral rather than local tissue, with the most obvious changes occuring at 12 h in the pancreas which were also consistent with the inflammation score results. Several amino acid intermediates showed strong positive correlation between serum and pancreas, and therein serum cystathionine was positively correlated to 33 pancreatic metabolites. In particular, the correlations between the levels of pancreatic cystathionine and methionine, serine, and glutathione (GSH) emphasized the importance of trans-sulfuration to GSH metabolism for AP progression. CQCQD treatment reversed the metabolic trajectory of the pancreas, and also restored the levels of cystathionine and glutathione synthase.

CONCLUSION

Our results have defined a unique time-course metabolic trajectory for AP progression in both the serum and pancreas; it has also revealed a key role of CQCQD in reversing AP-associated metabolic alterations, thus providing new metabolic targets for the treatment and prognosis of AP.

Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis

BACKGROUND

Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP.

METHODS

Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP).

RESULTS

A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets.

CONCLUSIONS

Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis.

Metabolomic-based clinical studies and murine models for acute pancreatitis disease: A review

Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.

Clinical Application of Metabolomics in Pancreatic Diseases: A Mini-Review

Metabolomics is a powerful new analytical method to describe the set of metabolites within cellular tissue and bodily fluids. Metabolomics can uncover detailed information about metabolic changes in organisms. The morphology of these metabolites represents the metabolic processes that occur in cells, such as anabolism, catabolism, inhomogeneous natural absorption and metabolism, detoxification, and metabolism of biomass energy. Because the metabolites of different diseases are different, the specificity of the changes can be found by metabolomics testing, which provides a new source of biomarkers for the early identification of diseases and the difference between benign and malignant states. Metabolomics has a wide application potential in pancreatic diseases, including early detection, diagnosis, and identification of pancreatic diseases. However, there are few studies on metabolomics in pancreatic diseases in the literature. This article reviews the application of metabolomics in the diagnosis, prognosis, treatment, and evaluation of pancreatic diseases.

GC-MS based metabolomics strategy to distinguish three types of acute pancreatitis

Acute pancreatitis (AP) is a progressive systemic inflammatory response with high morbidity and high mortality, which is mainly caused by alcohol, bulimia, gallstones and hyperlipidemia. The early diagnosis of different types of AP and further explore potential pathophysiological mechanism of each type of AP is beneficial for optimized treatment strategies and better patient's care. In this study, a metabolomics approach based on gas chromatography-mass spectrometry (GC-MS), and random forests algorithm was established to distinguish biliary acute pancreatitis (BAP), Hyperlipidemia acute pancreatitis (HLAP), and alcoholic acute pancreatitis (AAP), from healthy controls. The classification accuracies for BAP, HLAP, and AAP patients compared with healthy control, were 0.886, 0.906 and 0.857, respectively, by using 5-fold cross-validation method. And some special metabolites for each type of AP were discovered, such as l-Lactic acid, (R)-3-Hydroxybutyric acid, Phosphoric acid, Glycine, Erythronic acid, l-Phenylalanine, d-Galactose, l-Tyrosine, Arachidonic acid, Glycerol 1-hexadecanoate. Furthermore, associations between these metabolites with the metabolism of amino acids, fatty acids were identified. Our studies have illuminated the biomarkers and physiological mechanism of disease in a clinical setting, which suggested that metabolomics is a valuable tool for identifying the molecular mechanisms that are involved in the etiology of BAP, AAP, HLAP and thus novel therapeutic targets.

Identification of potential diagnostic biomarkers of acute pancreatitis by serum metabolomic profiles

Acute pancreatitis (AP) is defined as an acute inflammation of pancreas that may cause damage to other tissues and organs depending upon the severity of symptoms. The diagnosis of AP is usually made by detection of raised circulating pancreatic enzyme levels, but there are occasional false positive and false negative diagnoses and such tests are often normal in delayed presentations. More accurate biomarkers would help in such situations. In this study, the global metabolites' changes of AP patients (APP) were profiled by using gas chromatography-mass spectrometry (GC-MS). Multivariate pattern recognition techniques were used to establish the classification models to distinguish APP from healthy participants (HP). Some significant metabolites including 3-hydroxybutyric acid, phosphoric acid, glycerol, citric acid, d-galactose, d-mannose, d-glucose, hexadecanoic acid and serotonin were selected as potential biomarkers for helping clinical diagnosis of AP. Furthermore, the metabolite changes in APP with severe and mild symptoms were also analyzed. Based on the selected biomarkers, some relevant pathways were also identified. Our results suggested that GC-MS based serum metabolomics method can be used in the clinical diagnosis of AP by profiling potential biomarkers.

Stereotypical Metabolic Response to Endoscopic Retrograde Cholangiopancreatography Show Alterations in Pancreatic Function Regardless of Post-Procedure Pancreatitis

OBJECTIVES:

Metabolomics-based diagnosis or prediction of risk may improve patient outcomes and improve understanding of the pathogenesis of acute pancreatitis (AP). Endoscopic retrograde cholangiopancreatography (ERCP) is a risk factor for developing AP. This pilot study examined metabolomes of patients before and after ERCP, hypothesizing that metabolomics could differentiate between patients who did and did not develop post-ERCP pancreatitis, and that biomarkers associated with development of AP could be identified.

METHODS:

Patients at high risk for developing post-ERCP pancreatitis were prospectively enrolled at the University of Minnesota from October 2012 to February 2014. Urine and serum samples were collected before ERCP, 2 h after ERCP, and daily thereafter if patients were admitted to the hospital with AP. Pancreatitis severity was calculated with Bedside Index for Severity in Acute Pancreatitis (BISAP) and Modified Glasgow scores. Patients who developed AP (n=9) were matched to patients who did not develop AP (n=18) by age and gender. Urine and serum metabolites were profiled with nuclear magnetic resonance spectroscopy. Partial least squares discriminant analysis (PLS-DA) was performed to detect changes in metabolic profiles associated with development of pancreatitis. Metabolic networks were constructed to probe functional relationships among metabolites.

RESULTS:

Of the 113 enrolled patients, 9 developed mild AP according to BISAP and modified Glasglow scores. PLS-DA showed common differences between pre- and post-ERCP metabolic profiles in urine and serum regardless of AP status, characterized by increases in serum and urine ketones and serum glucose. Pre-ERCP lipase levels were somewhat elevated in those who went on to develop AP, though this did not reach statistical significance. Metabolic networks differed between patients with AP and those without after ERCP; however, metabolomics did not identify specific prognostic or diagnostic markers of ERCP-induced AP. Aspartate and asparagine were identified as well-connected hubs in post-ERCP serum networks of cases and were correlated with aspartate transaminase (AST) and white blood cell count levels. These features were not evident in controls. Serum aspartate was elevated in AP patients relative to those without AP after ERCP (P=0.03).

CONCLUSIONS:

In this pilot study, ERCP was found to induce global changes in urine and serum metabolomes indicative of alterations in pancreatic function and insulin resistance. This should be taken into consideration in future research on this topic. Post-ERCP serum metabolic networks indicate functional differences surrounding aspartate metabolism between patients with AP and those without. Further study must be done in larger patient populations to test elevated lipase as a prognostic biomarker associated with risk of developing AP and to examine active metabolic mechanisms at work.

Multi-dimensional, comprehensive sample extraction combined with LC-GC/MS analysis for complex biological samples: application in the metabolomics study of acute pancreatitis

Multi-dimensional sample extraction and optimal LC-GC/MS were combined to obtain as much sample information as possible for metabolomics applications.

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.

New insights into the methodology of L-arginine-induced acute pancreatitis

Animal models are ideal to study the pathomechanism and therapy of acute pancreatitis (AP). The use of L-arginine-induced AP model is nowadays becoming increasingly popular in mice. However, carefully looking through the literature, marked differences in disease severity could be observed. In fact, while setting up the L-arginine (2×4 g/kg i.p.)-induced AP model in BALB/c mice, we found a relatively low rate (around 15%) of pancreatic necrosis, whereas others have detected much higher rates (up to 55%). We suspected that this may be due to differences between mouse strains. We administered various concentrations (5–30%, pH = 7.4) and doses (2×4, 3×3, or 4×2.5 g/kg) of L-arginine-HCl in BALB/c, FVB/n and C57BL/6 mice. The potential gender-specific effect of L-arginine was investigated in C57BL/6 mice. The fate of mice in response to the i.p. injections of L arginine followed one of three courses. Some mice (1) developed severe AP or (2) remained AP-free by 72 h, whereas others (3) had to be euthanized (to avoid their death, which was caused by the high dose of L-arginine and not AP) within 12 h., In FVB/n and C57BL/6 mice, the pancreatic necrosis rate (about 50%) was significantly higher than that observed in BALB/c mice using 2×4 g/kg 10% L–arginine, but euthanasia was necessary in a large proportion of animals, The i.p. injection of lower L-arginine concentrations (e.g. 5–8%) in case of the 2×4 g/kg dose, or other L-arginine doses (3×3 or 4×2.5 g/kg, 10%) were better for inducing AP. We could not detect any significant differences between the AP severity of male and female mice. Taken together, when setting up the L-arginine-induced AP model, there are several important factors that are worth consideration such as the dose and concentration of the administered L arginine-HCl solution and also the strain of mice.

1HNMR-based metabolomic profile of rats with experimental acute pancreatitis

Background

Acute pancreatitis (AP) is a common inflammatory disease of the pancreas accompanied by serious metabolic disturbances. Nevertheless, the specific metabolic process of this disease is still unclear. Characterization of the metabolome may help identify biomarkers for AP. To identify potential biomarkers, this study therefore investigated the 1H-nuclear magnetic resonance (NMR)-based metabolomic profile of AP.

Methods

Fourteen male adult Sprague–Dawley rats were randomized into two groups: the AP group, in which AP was induced by retrograde ductal infusion of 3.5% sodium taurocholate; and the sham operation group (SO), in which rats were infused with 0.9% saline. Blood samples were obtained 12 hours later and a 600 MHz superconducting NMR spectrometer was used to detect plasma metabolites. Principal components analysis (PCA) and partial least squares-discriminant analysis after orthogonal signal correction (OSC-PLS-DA) were used to analyze both longitudinal Eddy-delay (LED) and Carr–Purcell–Meiboom–Gill (CPMG) spectra.

Results

Differences in plasma metabolites between the two groups were detected by PCA and PLS-DA of 1HNMR spectra. Compared with the SO group, plasma levels of lactate (δ 1.3, 1.34, 4.1), valine (δ 0.98, 1.02), succinic acid (δ 2.38), 3-hydroxybutyric acid (3-HB, δ 1.18), high density lipoprotein (HDL, δ 0.8), and unsaturated fatty acid (UFA, δ 2.78, 5.3) were elevated in the AP group, while levels of glycerol (δ 3.58, 3.66), choline (δ 3.22), trimethylamine oxide (TMAO, δ 3.26), glucose (δ 3–4), glycine (δ 3.54), very low density lipoprotein (VLDL, δ 1.34) and phosphatidylcholine (Ptd, δ 2.78) were decreased.

Conclusions

AP has a characteristic metabolic profile. Lactate, valine, succinic acid, 3-HB, HDL, UFA, glycerol, choline, TMAO, glucose, glycine, VLDL, and Ptd may be potential biomarkers of early stage AP.

Metabolomics-based search for therapeutic agents for non-alcoholic steatohepatitis

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is the commonest form of chronic liver disease in developed countries. Non-alcoholic steatohepatitis (NASH), which represents advanced stage NAFLD, is increasingly being recognized as a major cause of liver-related morbidity and mortality. However, no effective drugs against NASH have yet been developed. Therefore, we searched for candidate therapeutic agents based on the changes in levels of hepatic metabolites via gas chromatography mass spectrometry (GC/MS)-based metabolome analysis of livers from methionine-choline deficient (MCD) diet-fed mice, a mouse model of NASH.

METHODS

The metabolites were extracted from the livers of the MCD diet-fed mice and then analyzed using GC/MS. Subsequently, the MCD diet-fed mice were supplemented with hypotaurine, and the therapeutic effects of hypotaurine against steatohepatitis were evaluated.

RESULTS

Ninety-nine metabolites were detected in the livers of the MCD diet-induced steatohepatitis model mice. Among these metabolites, hypotaurine exhibited the greatest decrease in its concentration in the mice. Supplementation with 2 mmol/kgBW hypotaurine attenuated liver injuries and fat accumulation caused by the MCD diet-induced steatohepatitis. Furthermore, 10 mmol/kgBW hypotaurine supplementation ameliorated fibrosis and oxidative stress induced by the MCD diet.

CONCLUSION

The present metabolome analysis-based study demonstrated that hypotaurine is a novel candidate therapeutic agent for NASH.

Recent advances in the investigation of pancreatic inflammation induced by large doses of basic amino acids in rodents

It has been known for approximately 30 years that large doses of the semi-essential basic amino acid L-arginine induce severe pancreatic inflammation in rats. Recently, it has been demonstrated that L-arginine can also induce pancreatitis in mice. Moreover, other basic amino acids like L-ornithine and L-lysine can cause exocrine pancreatic damage without affecting the endocrine parenchyma and the ducts in rats. The utilization of these noninvasive severe basic amino acid-induced pancreatitis models is becoming increasingly popular and appreciated as these models nicely reproduce most laboratory and morphological features of human pancreatitis. Consequently, the investigation of basic amino acid-induced pancreatitis may offer us a better understanding of the pathogenesis and possible treatment options of the human disease.