Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-8686
Authors: Schmidt, Hanno
Mauer, Katharina
Glaser, Manuel
Sayyaf Dezfuli, Bahram
Hellmann, Sören Lukas
Silva Gomes, Ana Lúcia
Butter, Falk
Wade, Rebecca C.
Hankeln, Thomas
Herlyn, Holger
Title: Identification of antiparasitic drug targets using a multi-omics workflow in the acanthocephalan model
Online publication date: 3-Feb-2023
Year of first publication: 2022
Language: english
Abstract: Background With the expansion of animal production, parasitic helminths are gaining increasing economic importance. However, application of several established deworming agents can harm treated hosts and environment due to their low specificity. Furthermore, the number of parasite strains showing resistance is growing, while hardly any new anthelminthics are being developed. Here, we present a bioinformatics workflow designed to reduce the time and cost in the development of new strategies against parasites. The workflow includes quantitative transcriptomics and proteomics, 3D structure modeling, binding site prediction, and virtual ligand screening. Its use is demonstrated for Acanthocephala (thorny-headed worms) which are an emerging pest in fish aquaculture. We included three acanthocephalans (Pomphorhynchus laevis, Neoechinorhynchus agilis, Neoechinorhynchus buttnerae) from four fish species (common barbel, European eel, thinlip mullet, tambaqui). Results The workflow led to eleven highly specific candidate targets in acanthocephalans. The candidate targets showed constant and elevated transcript abundances across definitive and accidental hosts, suggestive of constitutive expression and functional importance. Hence, the impairment of the corresponding proteins should enable specific and effective killing of acanthocephalans. Candidate targets were also highly abundant in the acanthocephalan body wall, through which these gutless parasites take up nutrients. Thus, the candidate targets are likely to be accessible to compounds that are orally administered to fish. Virtual ligand screening led to ten compounds, of which five appeared to be especially promising according to ADMET, GHS, and RO5 criteria: tadalafil, pranazepide, piketoprofen, heliomycin, and the nematicide derquantel. Conclusions The combination of genomics, transcriptomics, and proteomics led to a broadly applicable procedure for the cost- and time-saving identification of candidate target proteins in parasites. The ligands predicted to bind can now be further evaluated for their suitability in the control of acanthocephalans. The workflow has been deposited at the Galaxy workflow server under the URL tinyurl.com/yx72rda7.
DDC: 610 Medizin
610 Medical sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 04 Medizin
Place: Mainz
ROR: https://ror.org/023b0x485
DOI: http://doi.org/10.25358/openscience-8686
Version: Published version
Publication type: Zeitschriftenaufsatz
Document type specification: Scientific article
License: CC BY
Information on rights of use: https://creativecommons.org/licenses/by/4.0/
Journal: BMC genomics
23
Pages or article number: 677
Publisher: BioMed Central
Publisher place: London
Issue date: 2022
ISSN: 1471-2164
Publisher DOI: 10.1186/s12864-022-08882-1
Appears in collections:DFG-491381577-G

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