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An interactive database for the investigation of high-density peptide microarray guided interaction patterns and antivenom cross-reactivity

Authors :
Julián Fernández
Andreas Hougaard Laustsen
José María Gutiérrez
Timothy P. Jenkins
Nicholas R. Casewell
Kamille Elvstrøm Krause
Carina Skaarup
Mikael Engmark
Stuart Ainsworth
Bruno Lomonte
Ole Lund
Source :
PLoS Neglected Tropical Diseases, PLoS Neglected Tropical Diseases (2020) 14, e0008366., Kérwá, Universidad de Costa Rica, instacron:UCR, PLoS Neglected Tropical Diseases, Vol 14, Iss 6, p e0008366 (2020), Krause, K E, Jenkins, T P, Skaarup, C, Engmark, M, Casewell, N R, Ainsworth, S, Lomonte, B, Fernández, J, Gutiérrez, J M, Lund, O & Laustsen, A H 2020, ' An interactive database for the investigation of high-density peptide microarray guided interaction patterns and antivenom cross-reactivity ', PLOS Neglected Tropical Diseases, vol. 14, no. 6, e0008366 . https://doi.org/10.1371/journal.pntd.0008366, PLOS Neglected Tropical Diseases
Publication Year :
2020
Publisher :
Public Library of Science, 2020.

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.<br />Author summary Millions of people are bitten by venomous snakes each year, resulting in over 100,000 deaths. Currently, such envenomings are treated with animal derived antivenoms that contain undefined antibodies against snake venom toxins that have been raised by the production animal’s immune system. To date, our understanding of these antibody toxin interactions is sparse, but with the help of high-density peptide microarray (hdpm) technology this is starting to change. Whilst this technology is very powerful, analysis of the output data is complex and requires expert training. Therefore, in this study, we developed a user-friendly, and high-throughput web application named “Snake Toxin and Antivenom Binding Profiles” (STAB Profiles). Furthermore, we ensured our tool was functional and able to handle large amounts of data by creating an entirely novel and larger than ever hdpm dataset based on all African snake toxin proteins together with eight commercial antivenoms. With these data and our tool, we were able to further our understanding on toxin-antivenom interactions and were able to differentiate the ability of different antivenoms to interact with certain toxins of interest. Ideally, these and future insights can help guide the improvement and optimization of current antivenoms, as well as aid the informed development of next-generation antivenoms.

Details

Language :
English
ISSN :
19352735 and 19352727
Volume :
14
Issue :
6
Database :
OpenAIRE
Journal :
PLoS Neglected Tropical Diseases
Accession number :
edsair.doi.dedup.....7fc257a4702fea30841e8e1b8f1c7e5b