Metabolic mechanism analysis of abdominal aortic aneurysm tissues by internal extractive electrospray ionization mass spectrometry with minimal sample size.

Abdominal aortic aneurysm (AAA) is a major clinical challenge, with a mortality rate of over 80% if rupture. Metabolic imbalance is a critical factor in the progression of AAA. Therefore, using modern analytical techniques to study the tissue metabolic characteristics of AAA is crucial for elucidating the pathological mechanisms and identifying novel drug targets. However, existing methodologies often require large sample sizes and involve complex experimental procedures, which limit their applicability in studies with limited sample availability, especially when rodent AAA models are used. Herein, we established an analytical platform based on internal extractive electrospray ionization mass spectrometry (iEESI-MS) to analyze the metabolic characteristics of AAA tissue, which only requires 0.1 mg of tissue (representing a sample reduction of over 99% compared to conventional methods). Using iEESI-MS, we detected significant changes in metabolite profiles between normal aorta and aneurysmal samples from Angiotensin II induced AAA, with 121 ions showing significantly increased signal intensities and 99 ions showing decreased intensities in AAA tissues. These ions clearly distinguished normal group samples from AAA samples. Notably, Anemoside B4 (AB4), a compound known to inhibit AAA progression, significantly reversed the signal intensities of 116 of these ions, effectively distinguishing the AB4-treated group from the untreated AAA group. Subsequently, Collision induced dissociation (CID) identification was performed on the top 40 differential ions with the most significant changes in signal intensity, leading to the identification of 22 metabolites. Moreover, we conducted quantitative analysis on five significantly altered metabolites, including l-cysteine and protoporphyrin IX. They were directly quantified in the range of 1.0 × 103-1.0 × 108 ng/kg (R2 ≥ 0.9908), with limits of detection of 4.73-16.44 ng/kg, limits of quantification of 14.33-49.81 ng/kg, recovery rate of 91.45%-109.41%, and relative standard deviation of repeatability (n = 9) of 1.26%-7.01%, respectively. These 22 metabolites are primarily involved in the pathways of glutathione and porphyrin metabolism. Taken together, these studies establish a plausible approach for examining metabolic alterations in AAA development, which may aid in drug development.