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Updated: Nov 2, 2025
Chemical Cartography Approaches to Study Trypanosomatid Infection
Published on: January 21, 2022
Metabolites as predictive biomarkers for Trypanosoma cruzi exposure in triatomine bugs
Fanny E Eberhard1, Sven Klimpel1,2,3, Alessandra A Guarneri4
1Institute for Ecology, Evolution and Diversity, Goethe University Frankfurt, Frankfurt/Main, Germany.
Abstract:
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.
Insights
Detecting Trypanosoma cruzi (the parasite causing Chagas disease) in triatomine bugs is possible by analyzing their gut
Area of Science:
- Vector-borne diseases
- Parasitology
- Metabolomics
Background:
- Chagas disease is transmitted by triatomine bugs, which harbor the parasite Trypanosoma cruzi.
- T. cruzi infection alters the gut microbiome and metabolic profile of triatomine vectors.
- The triatomine fecal metabolome may influence vector competence for T. cruzi.
Purpose of the Study:
- To detect differences in the intestinal metabolome of Rhodnius prolixus exposed to T. cruzi.
- To predict T. cruzi exposure in R. prolixus based on metabolic profiles.
- To identify key metabolites associated with T. cruzi infection in triatomines.
Main Methods:
- High-resolution mass spectrometry was used to analyze the metabolome of R. prolixus.
- Supervised machine learning models (logistic regression, random forest, gradient boosting) were employed for classification.
- Feature extraction identified important metabolites for predicting T. cruzi exposure.
Main Results:
- Machine learning models accurately predicted T. cruzi exposure in R. prolixus (91.8%–94.2% accuracy).
- Specific metabolites were identified as key indicators of T. cruzi infection.
- The study revealed significant alterations in the insect's metabolic signature post-infection.
Conclusions:
- Metabolic profiling is a viable method for detecting T. cruzi in its vector.
- Understanding host-parasite metabolic interactions is crucial for vector control strategies.
- This approach offers a novel way to assess vector exposure to T. cruzi.
