Biospectroscopy Combined with Multivariate Analysis as Tools for Identifying Trypanosoma cruzi Discrete Typing Units in Triatoma brasiliensis (Hemiptera: Reduviidae: Triatominae).

Epidemiological surveillance of Chagas disease with determination of Trypanosoma cruzi (T. cruzi) positivity and genotyping is important for the adoption of control measures. The association of biospectroscopy with chemometric models can be used as an alternative tool to determine T. cruzi positivity and genotyping directly on the insect, with laser incidence, without damage to the insects, and without parasite isolation and growing. In this study, infrared spectroscopy (ATR-FTIR) combined with classification and authentication models was used for the identification of the experimental infection of Triatoma brasiliensis (T. brasiliensis) by different discrete typing units of T. cruzi. T. brasiliensis fourth and fifth instars were experimentally infected with 40,000 parasites (TcI, TcII, TcIII, or mixed infection) per milliliter of blood, and 1, 15, and 30 days after infection, infrared spectra were collected from the abdomen of each insect. The classification models, genetic algorithm linear discriminant analysis (GA-LDA) and successive projections algorithm linear discriminant analysis, achieved 100% sensitivity and specificity for TcII, the mixed infection, and control across all infection periods. For TcI and TCII, GA-LDA performed best in 15 days with 75% sensitivity and 94% specificity. The data-driven soft independent modeling of the class analogy model correctly classified most infected samples within the limits of both the training set and the test set, excluding the uninfected samples of the acceptance region, and achieving sensitivity and specificity close to 100%. Spectral differences, primarily attributed to proteins (amide III band, 1247-1307 cm-1) and nucleic acids (phosphate stretching vibrations, 1048-1085 cm-1), allowed for consistent discrimination between infected and uninfected insects. The polymerase chain reaction of kDNA analysis confirmed 92.5% (37/40) of infections in all triatomines submitted to experimental infection. Thus, the integration of ATR-FTIR, classification tools, and authentication models has been shown to be a rapid, noninvasive, and promising approach for the diagnosis and entomological surveillance of Chagas disease.