Metabolites as predictive biomarkers for Trypanosoma cruzi exposure in triatomine bugs

  • Trypanosoma cruzi, the causative agent of Chagas disease (American trypanosomiasis), colonizes the intestinal tract of triatomines. Triatomine bugs act as vectors in the life cycle of the parasite and transmit infective parasite stages to animals and humans. Contact of the vector with T. cruzi alters its intestinal microbial composition, which may also affect the associated metabolic patterns of the insect. Earlier studies suggest that the complexity of the triatomine fecal metabolome may play a role in vector competence for different T. cruzi strains. Using high-resolution mass spectrometry and supervised machine learning, we aimed to detect differences in the intestinal metabolome of the triatomine Rhodnius prolixus and predict whether the insect had been exposed to T. cruzi or not based solely upon their metabolic profile. We were able to predict the exposure status of R. prolixus to T. cruzi with accuracies of 93.6%, 94.2% and 91.8% using logistic regression, a random forest classifier and a gradient boosting machine model, respectively. We extracted the most important features in producing the models and identified the major metabolites which assist in positive classification. This work highlights the complex interactions between triatomine vector and parasite including effects on the metabolic signature of the insect.
Metadaten
Author:Fanny E. EberhardORCiDGND, Sven KlimpelORCiDGND, Alessandra Aparecida GuarneriORCiD, Nicholas J. TobiasORCiD
URN:urn:nbn:de:hebis:30:3-779569
DOI:https://doi.org/10.1016/j.csbj.2021.05.027
ISSN:2001-0370
Parent Title (English):Computational and structural biotechnology journal
Publisher:Research Network of Computational and Structural Biotechnology (RNCSB)
Place of publication:Gotenburg
Document Type:Article
Language:English
Date of Publication (online):2021/05/21
Date of first Publication:2021/05/21
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2024/01/08
Tag:Chagas disease; Host-parasite interaction; Metabolomics; Rhodnius prolixus; Supervised machine learning; Trypanosoma cruzi
Volume:19
Page Number:7
First Page:3051
Last Page:3057
Note:
This work was funded by the LOEWE-Centre TBG supported by the Hessen State Ministry of Higher Education, Research and the Arts (HMWK), Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG, CRA-APQ-00569-15 and CRA-PPM-00162-17), Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular (INCTEM/CNPq, 465678/2014-9) and the Vereinigung von Freunden und Förderern der Johann Wolfgang Goethe-Universität Frankfurt am Main, AAG was supported by CNPq productivity grants.
HeBIS-PPN:516371533
Institutes:Biowissenschaften
Fachübergreifende Einrichtungen / Biodiversität und Klima Forschungszentrum (BiK-F)
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International