1H NMR-based serum metabolomics reveals erythromycin-induced liver toxicity in albino Wistar rats

摘要

Introduction: Erythromycin (ERY) is known to induce hepatic toxicity which mimics other liver diseases. Thus, ERY is often used to produce experimental models of drug-induced liver-toxicity. The serum metabolic profiles can be used to evaluate the liver-toxicity and to further improve the understanding of underlying mechanism. Objective: To establish the serum metabolic patterns of Erythromycin induced hepatotoxicity in albino wistar rats using 1H NMR based serum metabolomics. Experimental: Fourteen male rats were randomly divided into two groups ( n = 7 in each group): control and ERY treated. After 28 days of intervention, the metabolic profiles of sera obtained from ERY and control groups were analyzed using high-resolution 1D 1H CPMG and diffusion-edited nuclear magnetic resonance (NMR) spectra. The histopathological and SEM examinations were employed to evaluate the liver toxicity in ERY treated group. Results: The serum metabolic profiles of control and ERY treated rats were compared using multivariate statistical analysis and the metabolic patterns specific to ERY-induced liver toxicity were established. The toxic response of ERY was characterized with: (a) increased serum levels of Glucose, glutamine, dimethylamine, malonate, choline, phosphocholine and phospholipids and (b) decreased levels of isoleucine, leucine, valine, alanine, glutamate, citrate, glycerol, lactate, threonine, circulating lipoproteins, N-acetyl glycoproteins, and poly-unsaturated lipids. These metabolic alterations were found to be associated with (a) decreased TCA cycle activity and enhanced fatty acid oxidation, (b) dysfunction of lipid and amino acid metabolism and (c) oxidative stress. Conclusion and Recommendations: Erythromycin is often used to produce experimental models of liver toxicity; therefore, the established NMR-based metabolic patterns will form the basis for future studies aiming to evaluate the efficacy of anti-hepatotoxic agents or the hepatotoxicity of new drug-formulations. KEY WORDS: Erythromycin, metabolomics, multivariate data analysis, nuclear magnetic resonance, rats, liver-toxicity Erythromycin (ERY) belongs to a group of drugs called macrolide antibiotics and is widely used to treat or prevent different types of bacterial infections.[ 1 , 2 ] However, ERY has been found to induce certain side effects and may produce allergic reactions like hives, difficult breathing, swelling of face, lips, tongue, or throat. Further, the continuous use of ERY can also alter the gut flora;[ 3 ] thus additionally producing gastrointestinal disorders like abdominal pain, nausea, and diarrhea, but are rarely severe. However, the most adverse side-effect of frequent use of ERY have been linked to the instances of hepatotoxicity manifested as disturbances in liver function and jaundice.[ 4 , 5 ] ERY-induced hepatotoxicity likely arises from a combination of intrinsic hepatotoxic effects and the hypersensitivity reactions that characterize most cases with evidence of hepatocellular injury and cholestatic pattern of injury.[ 6 , 7 ] Such events of hepato-toxicity have been shown to cause significant metabolic perturbations in the sera of affected individuals. However, the serum metabolic patterns of ERY-induced liver toxicity have not been explored so far. To the best of our knowledge, this is the first study aiming to investigate the serum metabolic patterns specific to ERY-induced liver toxicity and to further improve the understanding of underlying mechanism. Metabolomics allows rapid identification of metabolic perturbations in biological systems and is routinely used to evaluate systemic responses from minimal amounts of biological material,[ 8 ] to any subtle pathophysiological stimuli or stress.[ 9 ] Over the years, it has increasingly been recognized as a valuable complementary approach to genomics, transcriptomics, and proteomics to achieve a complete understanding of the disease mechanism.[ 10 ] It also provides opportunities for developing diagnostic/prognostic biomarkers related to the disease and certain pathophysiological condition.[ 11 , 12 ] Practically, metabolomics approaches relies on multivariate statistical analysis of data collected with advanced analytical techniques-such as gas chromatography-mass spectrometry (GC-MS), liquid chromatography- mass spectrometry (LC-MS), and nuclear magnetic resonance (NMR) spectroscopy. Of them, NMR combined with multivariate analysis is an ideal platform and it has extensively been used in several metabolomic studies.[ 13 , 14 ] In comparison to any other analytical and biochemical method, NMR possesses various advantages. First, it is rapid, quantitative and offers the potential for high-throughput (analysis of >100 samples a day is attainable). Second, it requires virtually no sample preparation and can be used for studying variety of biological/clinical samples, tissue extracts, and even cell lines.[ 15 ] Third, it is nondestructive, noninvasi