Metabolic Effects of Clenbuterol and Salbutamol on Pork Meat Studied Using Internal Extractive Electrospray Ionization Mass Spectrometry.
Haiyan LuHua ZhangTenggao ZhuYipo XiaoShaoxian XieHaiwei GuMeng CuiLiping LuoPublished in: Scientific reports (2017)
Direct mass spectrometry analysis of metabolic effects of clenbuterol and salbutamol on pork quality at the molecular level is incredibly beneficial for food regulations, public health and the development of new anti-obesity drugs. With internal extractive electrospray ionization mass spectrometry (iEESI-MS), nutrients including creatine, amino acids, L-carnitine, vitamin B6, carnosine and phosphatidylcholines in pork tissue were identified, without sample pretreatment, using collision-induced dissociation (CID) experiments and by comparison with authentic compounds. Furthermore, normal pork samples were clearly differentiated from pork samples with clenbuterol and salbutamol via principal component analysis (PCA). Correlation analysis performed on the spectral data revealed that the above-mentioned nutrients strongly correlated with pork quality, and the absolute intensity of phosphatidylcholines in normal pork was much higher than pork contaminated by clenbuterol and salbutamol. Our findings suggested that clenbuterol and salbutamol may render effects on the activity of carnitine acyltransferase I, hence the process that L-carnitine transports long-chain fatty acids into mitochondria and the formation of phosphatidylcholines might be affected. However, the underlying metabolic mechanisms of clenbuterol and salbutamol on carnitine acyltransferase I requires more comprehensive studies in future work.
Keyphrases
- mass spectrometry
- public health
- liquid chromatography
- heavy metals
- high performance liquid chromatography
- capillary electrophoresis
- high resolution
- fatty acid
- type diabetes
- gas chromatography
- insulin resistance
- electronic health record
- weight loss
- multiple sclerosis
- optical coherence tomography
- amino acid
- cell death
- computed tomography
- magnetic resonance
- drinking water
- climate change
- deep learning
- single molecule
- diabetic rats
- big data
- human health
- artificial intelligence
- skeletal muscle
- solid state