Abstract

Accumulated evidences suggest that cardiolipins (CLs) and cardiolipin oxidation products (oxCLs) are a class of essential molecules that play critical roles in many physiological functions. Diversity of four acyl chains leads to high structure complexity for cardiolipin species including CLs, monolysocardiolipins (MLCLs) and their oxCLs. The ability to rapidly identify CL species can be implemented by the match of mass spectrometry (MS)-based in-silico spectral database. In this study, after optimizing the chromatography conditions and MS detection, an in-silico library containing 377,754 simulated tandem mass spectra deducing from 31,578 CLs to 52,160 of MLCLs was successfully augmented based on LipidBlast templates. For the construction of the oxCLs' library, twenty-five fatty acyls oxidation products relating to nine oxidation types were permuted and combined. A total of 42,180 oxCL spectra were predicted based on the experimental measurements of oxCLs forming by artificially oxidation. Applying the in-silico database to murine mitochondria and cell samples enabled the sensitive and comprehensive annotation of 86 MLCLs, 307 CLs and 112 oxCLs with high annotation confidence. Compared to the conventional method, our proposed in-silico database provides a more comprehensive interpretation for CL species’ characterization with high throughput and sensitivity in nontarget lipidomic study.

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