Abstract
Snakebite envenoming is a major neglected tropical disease that affects millions of people every year. The only effective treatment against snakebite envenoming consists of unspecified cocktails of polyclonal antibodies purified from the plasma of immunized production animals. Currently, little data exists on the molecular interactions between venom-toxin epitopes and antivenom-antibody paratopes. To address this issue, high-density peptide microarray (hdpm) technology has recently been adapted to the field of toxinology. However, analysis of such valuable datasets requires expert understanding and, thus, complicates its broad application within the field. In the present study, we developed a user-friendly, and high-throughput web application named “Snake Toxin and Antivenom Binding Profiles” (STAB Profiles), to allow straight-forward analysis of hdpm datasets. To test our tool and evaluate its performance with a large dataset, we conducted hdpm assays using all African snake toxin protein sequences available in the UniProt database at the time of study design, together with eight commercial antivenoms in clinical use in Africa, thus representing the largest venom-antivenom dataset to date. Furthermore, we introduced a novel method for evaluating raw signals from a peptide microarray experiment and a data normalization protocol enabling intra-microarray and even inter-microarray chip comparisons. Finally, these data, alongside all the data from previous similar studies by Engmark et al., were preprocessed according to our newly developed protocol and made publicly available for download through the STAB Profiles web application (http://tropicalpharmacology.com/tools/stab-profiles/). With these data and our tool, we were able to gain key insights into toxin-antivenom interactions and were able to differentiate the ability of different antivenoms to interact with certain toxins of interest.The data, as well as the web application, we present in this article should be of significant value to the venom-antivenom research community. Knowledge gained from our current and future analyses of this dataset carry the potential to guide the improvement and optimization of current antivenoms for maximum patient benefit, as well as aid the development of next-generation antivenoms.
Highlights
An urgent demand exists for addressing the global public health burden of snakebite envenoming, a neglected tropical disease that each year exacts a death toll of more than 100,000 and leaves many more disfigured for life [1, 2]
We discovered that 3FTxs were the most bound toxin family out of all tested dominant toxins, with peptide interaction signals for phospholipase A2s (PLA2s) and metalloproteases (SVMPs) being markedly lower
We found that the majority of these toxins were very poorly recognized or not recognized at all, which is in line with reports from previous toxicovenomic studies that suggest poor neutralization of these types of toxins [19,20,21, 27]
Summary
An urgent demand exists for addressing the global public health burden of snakebite envenoming, a neglected tropical disease that each year exacts a death toll of more than 100,000 and leaves many more disfigured for life [1, 2]. Toxicovenomics needs to be combined with complementary analytical approaches, such as animal-based neutralization assays, immunochemical studies [3], and antivenomics [10]; these, together, can provide an in-depth view into the molecular reactivity and potential neutralization of these medically relevant toxins [11, 12]. All of these approaches fail to provide information about the specific binding interactions between venom toxin epitopes and antivenom antibody paratopes [11]. Such molecular interaction information is key towards developing a better understanding of the nature of antivenom cross-reactivity and para-specificity and, the development of improved and broadly neutralizing antivenoms [11, 12]
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