Discovery and Identification of Arsenolipids Using a Precursor-Finder Strategy and Data-Independent Mass Spectrometry

Arsenolipids are a class of lipid-soluble arsenic species. They are present in seafoods and show high potentials of cytotoxicity and neurotoxicity. Hindered by traditional low-throughput analytical techniques, the characterization of arsenolipids is far from complete. Here, we report on a sensitive and high-throughput screening method for arsenolipids in krill oil, tuna fillets, hairtail heads, and kelp. We demonstrate the detection and identification of 23 arsenolipids, including novel arsenic-containing fatty acids (AsFAs), hydroxylated AsFAs, arsenic-containing hydrocarbons (AsHCs), hydroxylated AsHCs, thiolated trimethylarsinic acids, and arsenic-containing lysophosphatidylcholines not previously reported. The new method incorporated precursor ion scan (PIS) into data-independent acquisition. High-performance liquid chromatography (HPLC) electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-qToF-MS) was used to perform the sequential window acquisition of all theoretical spectra (SWATH). Comprehensive HPLC-MS and MS/MS data were further processed using a fragment-guided chromatographic computational program Precursorf inder developed here. Precursorf inder achieved efficient peak-picking, retention time comparison, hierarchical clustering, and wavelet coherence calculations to assemble fragment features with their target precursors. The identification of arsenolipids was supported by coeluting the HPLC-MS peaks detected with the characteristic fragments of arsenolipids. Method validation using available arsenic standards and the successful identification of previously unknown arsenolipids in seafood samples demonstrated the applicability of the method for environmental research.

Automated summary

Arsenolipids are a class of lipid-soluble arsenic species with high potentials of cytotoxicity and neurotoxicity. A new sensitive and high-throughput screening method was developed to detect and identify 23 arsenolipids in seafood samples, including novel ones not reported before. By incorporating precursor ion scan into data-independent acquisition and using HPLC-MS technique, efficient identification of arsenolipids in seafood samples was achieved, demonstrating the applicability of the method for environmental research.