Comprehensive profiling of amino acids and derivatives in biological samples: A robust UHPLC-MS/MS method for investigating acute lung injury.

The severe respiratory dysfunctions associated with acute lung injury (ALI) and its sequelae have a high morbidity and mortality rate, are multifactorial, and lack a viable treatment. Considering the critical function that amino acids and derivatives play in the genesis of illnesses and the regulation of metabolic processes, monitoring the levels of metabolites associated with amino acids in biological matrices is necessary and interesting to study their pathological mechanisms. Exploring the dynamics of amino acids and derivatives level and searching for biomarkers provides improved clinical ideas for the diagnosis and treatment of ALI. Therefore, we developed an ultra-high-performance liquid chromatography-electrospray tandem mass spectrometry (UHPLC-MS/MS) method that can simultaneously determine the amino acid and derivatives metabolic levels to study amino acid profiles in different biological samples to facilitate clinical research of ALI. In this study, 48 amino acids and derivatives, including neurotransmitters, polyamines, purines, and other types, were quantified simultaneously in a fast, high-throughput, sensitive, and reliable manner within a 15-minute run time without derivatization. No relevant studies have been reported to quantify these 48 amino acid metabolites in three biological samples simultaneously. Satisfactory linearity (R > 0.995), inter-day and intra-day accuracy (85.17-112.67 % and 85.29-111.60 %, respectively), inter-day and intra-day precision (RSD < 13.80 % and RSD < 12.01 %, respectively), matrix effects (81.00 %-118.00 %), recovery (85.09 %-114.65 %) and stability (RSD < 14.72 %) were all demonstrated by the optimized method's successful validation for all analytes. In addition, the suggested method was effectively implemented in plasma, urine, and lung tissue from normal mice and mice with ALI, with the aim of finding potential biomarkers associated with ALI. Potential biomarkers were screened through multivariate statistical analysis and volcanic map analysis, and the changes of markers in ALI were again identified through heat map analysis and correlation analysis with biochemical indicators, which provided ideas and references for subsequent mechanism studies. Here, the technique created in this work offers a quick and dependable way to perform an integrated analysis of amino acids in a variety of biological materials, which can provide research ideas for understanding the physiopathological state of various diseases.