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An interactive database for the investigation of high-density peptide microarray guided interaction patterns and antivenom cross-reactivity
- 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.
- Subjects :
- 0301 basic medicine
Computer science
Microarrays
Physiology
Data management
Antivenom
RC955-962
Snake Bites
computer.software_genre
Toxicology
Pathology and Laboratory Medicine
Biochemistry
Field (computer science)
Computer Applications
wa_20_5
Epitopes
0302 clinical medicine
Arctic medicine. Tropical medicine
Immune Physiology
Medicine and Health Sciences
Toxins
Snakebite
Post-Translational Modification
database
Data Management
qw_630
Immune System Proteins
Database
Antivenins
Eukaryota
Snakes
cross-recognition
Squamates
3. Good health
Infectious Diseases
Bioassays and Physiological Analysis
Vertebrates
Web-Based Applications
Peptide microarray
UniProt
DNA microarray
Public aspects of medicine
RA1-1270
Signal Peptides
wd_410
Research Article
Neglected Tropical Diseases
Snake Venoms
Computer and Information Sciences
030231 tropical medicine
Toxic Agents
Immunology
peptide microarray
Protein Array Analysis
Cross Reactions
Research and Analysis Methods
complex mixtures
Antibodies
Database normalization
03 medical and health sciences
SDG 3 - Good Health and Well-being
Web application
Animals
Humans
wd_400
antivenom
Binding Sites
business.industry
Venoms
Public Health, Environmental and Occupational Health
Organisms
Biology and Life Sciences
Proteins
Reptiles
Tropical Diseases
030104 developmental biology
Amniotes
Africa
business
Peptides
computer
Subjects
Details
- Language :
- English
- ISSN :
- 19352735 and 19352727
- Volume :
- 14
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- PLoS Neglected Tropical Diseases
- Accession number :
- edsair.doi.dedup.....7fc257a4702fea30841e8e1b8f1c7e5b