Combined molecular and elemental mass spectrometry approaches for absolute quantification of proteomes: application to the venomics characterization of the two species of desert black cobras, Walterinnesia aegyptia and Walterinnesia morgani

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We report a novel hybrid, molecular and elemental mass spectrometry (MS) setup for the absolute quantification of snake venom proteomes shown here for two desert black cobra species within the genus Walterinnesia, Walterinnesia aegyptia and Walterinnesia morgani. The experimental design includes the decomplexation of the venom samples by reverse-phase chromatography independently coupled to four mass spectrometry systems: the combined bottom-up and top-down molecular MS for protein identification and a parallel reverse-phase microbore high-performance liquid chromatograph (RP-μHPLC) on-line to inductively coupled plasma (ICP-MS/MS) elemental mass spectrometry and electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-QToF MS). This allows to continuously record the absolute sulfur concentration throughout the chromatogram and assign it to the parent venom proteins separated in the RP-μHPLC-ESI-QToF parallel run via mass profiling. The results provide a locus-resolved and quantitative insight into the three desert black cobra venom proteome samples. They also validate the units of measure of our snake venomics strategy for the relative quantification of snake venom proteomes as % of total venom peptide bonds as a proxy for the % by weight of the venom toxins/toxin families. In a more general context, our work may pave the way for broader applications of hybrid elemental/molecular MS setups in diverse areas of proteomics.
This paper was supported by PGC2018-098290-B-I00 (MCIU/AEI/FEDER,UE), Madrid, Spain. Research performed at IBV-CSIC and University of Oviedo was partially funded by grants BFU2017-89103-P and PID2019-109698GB-I00, respectively, from the Ministerio de Ciencia e Innovación, Madrid, Spain (J.J.C.). This work was also financed with funds from the Technische Universität Berlin by the Department of International Scientific Cooperation. Support by Agilent Technologies is also gratefully acknowledged.