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DOI 10.1080/14789450.2018.1500904

Медицинская библиотека · Expert review of proteomics · 2018

Snake venomics - from low-resolution toxin-pattern recognition to toxin-resolved venom proteomes with absolute quantification.

Calvete Juan J

СтатьяПоддержка исследования: вне правительства СШАОбзорПеревод в очереди

Аннотация

Venoms are integrated phenotypes used by a wide range of organisms for predatory and defensive purposes. The study of venoms is of great interest in diverse fields, such as evolutionary ecology and biotechnology. Omics technologies have contributed to understanding the evolutionary mechanisms that molded snake venoms to their present-day structural and functional variability landscape. Areas covered: This review article reflects on two recent implementations in venomics: absolute quantification of intact proteins by elemental mass spectrometry, and top-down molecular mass spectrometry. Expert commentary: Leveraging on a new way of polyatomic interference removal, a triple quadrupole inductively coupled plasma mass spectrometry configuration has proven feasible for the absolute quantification of venom toxins via sulfur detection. A major advantage of this approach over quantitative molecular mass spectrometry techniques is that only a generic S-standard is required to quantify all the chromatographically separated sulfur-containing fractions. Top-down venomics is in its infancy but, due to recent hardware and software developments, is gaining momentum. Proteoform-resolved venom proteomes are needed to understand the spatio-temporal variability landscape underlying the adaptations that drive intraspecific venom evolution. Integrating top-down venomics and absolute proteoform quantification into a novel elemental and molecular mass spectrometry configuration will represent a quantitative leap in the study of individual venoms.

Для цитирования: Calvete Juan J. Snake venomics - from low-resolution toxin-pattern recognition to toxin-resolved venom proteomes with absolute quantification.. Expert review of proteomics. 2018. DOI: 10.1080/14789450.2018.1500904.

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