Analytics for assessing the efficacy of snakebite treatment at neutralizing venom toxins

This thesis describes recent research achievements in the field of snake venom bioactivity profiling and toxin identification, incorporating efficacy assessment of snakebite treatments in their capacity of neutralizing venom toxins. For this accomplishment, so-called nanofractionation analytics played a central role. Nanofractionation analytics embody a recently developed high-resolution and high-throughput format of bioassay-guided fractionation and represents a comprehensive analytical approach for the screening of bioactives in complex mixtures, such as in crude venoms. The approach encompasses both toxin identification and biochemical characterization in relatively rapid fashion. Nanofractionation analytics comprise modern liquid chromatography (LC), such as reversed-phase liquid chromatography (RPLC), with on-line UV absorbance (providing relative quantification of venom components) and high-resolution mass spectrometry (MS) detection (providing accurate molecular masses of individual toxins). In addition, a post-column split allows for high-resolution fractionation in parallel followed by bioassaying and optional proteomics analysis of collected fractions. For bioassaying, the low-volume fractions of the column effluent, collected in a high-density well plate (e.g. 384 well plates) at a typical frequency of 2 to 10 s per well, are vacuum-centrifuged to dryness. Subsequently, the content in the dried wells are submitted to a high-throughput screening (HTS) bioassay, or to a sample preparation fit for proteomics analysis. The nanofractionation platform thus makes it possible to hyphenate bioassays to LC separations in an at-line format. From the data obtained, bioactivity chromatograms can be constructed and correlated with the parallel obtained UV, MS, and proteomics data. Eventually, the approach allows toxin activities to be correlated to individual toxin identities. This thesis in particular focuses on investigating and understanding the neutralizing effects of antivenoms and small molecule inhibitors on individual snake venom toxins. To achieve this goal, analytical advances in the nanofractionation format had to be made and new bioassays had to be developed. The overarching objective was to gain new insights aiding the development and testing of (candidate) snakebite treatments. Snakebite results in over a hundred thousand deaths globally each year, and three to four times more cases of permanent morbidities. Snakebite has therefore been placed on the top list of Neglected Tropical Diseases (NTD) in 2017 by the World Health Organization (WHO). Venomous snakes exert their pathologies by their secreted venoms after envenoming of victims by defensive bites. Resulting major pathologies include neurotoxicity, hemotoxicity and cytotoxicity/mytotoxicity. Snake venoms are complex, largely protein-based secretions composed of numerous toxic enzymes and peptides, but also containing small organic molecules and inorganic components. Venom composition varies hugely between venomous snake species. Venom variation evolutionary and biologically can be related to natural selection pressure, to family, genus, species and individual characteristics, to geographical location, living habitat and available pray, to sex and age, and to venom gland morphology of species. Standard snakebite treatment currently is predominantly antivenom-based, next to adjunct treatment by ventilator-based life-support systems for counteracting paralysis of lung function by certain neurotoxic elapid snakebites. Snakebite treatment with antibodies is far away from providing adequate solution due to their limited availability, varying quality and specificity, and restricted utility to specific venoms. New generations of antivenoms or other therapeutic approaches are highly needed to increase the efficacy and affordability of snakebite treatment. For this, it is critical to understand which toxins from snake venoms can be neutralized or inhibited by therapeutic (candidates). The here presented thesis touches upon new analytics to address this issue.