Natural infection with Trypanosoma cruzi and feeding habits of Triatominae (Hemiptera: Reduviidae) from the state of Durango, Mexico

Abstract

Chagas disease is a chronic and systemic condition caused by the protozoan Trypanosoma cruzi, acquired via abrasions or wounds on the skin or mucous membranes, through contact with feces or urine of hematophagous bugs belonging to the family Reduviidae, subfamily Triatominae. Many regions in Mexico are endemic for Chagas disease, but entomological and parasitological data are still limited. This study identified the incidence of natural infection with T. cruzi, as well as the feeding habits of the different species of triatomines circulating in the state of Durango, in the north-central region of Mexico. One hundred and ninety triatomines were taxonomically identified between February 2023 and May 2024 and a sample of intestinal content was obtained to identify the presence of T. cruzi by using microscopy and endpoint PCR. In addition, a 382 bp product of vertebrate cytochrome B (CytB) was amplified and sequenced to obtain the profile of feeding habits of this triatomines. Of the specimens collected, 121 were adults and 69 nymphs ranging from stage I to stage V. Of the collected adults, 115 were identified as Triatoma longipennis and 6 as Triatoma recurva. The specimens were collected both indoors (116) and in the peridomicile (74) showing a high overall percentage of positivity to natural infection with T.cruzi (54.5 %). Considering the total number of specimens collected, the colonization index was 36.32 %. In 27 of the 190 samples (14.22 %) CytB was amplified, revealing humans as the main feeding source for the triatomines. Our findings reveal that both species of triatomines were infected and predominantly found indoors, with humans as their primary feeding source. Comprehensive knowledge of the behavior of triatomine species that transmit T. cruzi allows their integrated control and the implementation of molecular tools for precise identification that strengthens the algorithms for epidemiological surveillance.