Molecular and Biochemical Markers for Investigating the Vectorial Roles of Brazilian Sand Flies

Ready, P. D.; Vigoder, Felipe M.; Rangel, Elizabeth Ferreira

doi:10.1007/978-3-319-75544-1_3

“…The population structure and genetic variability within and among different sand fly populations were found to influence vectorial capacity [ 56 ]. Consequently, an array of molecular and biochemical markers have been explored to identify the genotypes underlying phenotypes of interest, such as vector competence, that should be considered during the planning and implementation of integrated control strategies for leishmaniasis [ 57 , 58 ].…”

Section: Discussionmentioning

confidence: 99%

Molecular signatures of sexual communication in the phlebotomine sand flies

Hickner

¹

,

Timoshevskaya

²

,

Nowling

³

et al. 2020

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Phlebotomine sand flies employ an elaborate system of pheromone communication wherein males produce pheromones that attract other males to leks (thus acting as an aggregation pheromone) and females to the lekking males (sex pheromone). In addition, the type of pheromone produced varies among populations. Despite the numerous studies on sand fly chemical communication, little is known of their chemosensory genome. Chemoreceptors interact with chemicals in an organism’s environment to elicit essential behaviors such as the identification of suitable mates and food sources. Thus, they play important roles during adaptation and speciation. Major chemoreceptor gene families, odorant receptors (ORs), gustatory receptors (GRs) and ionotropic receptors (IRs) together detect and discriminate the chemical landscape. Here, we annotated the chemoreceptor repertoire in the genomes of Lutzomyia longipalpis and Phlebotomus papatasi, major phlebotomine vectors in the New World and Old World, respectively. Comparison with other sequenced Diptera revealed a large and unique expansion where over 80% of the ~140 ORs belong to a single, taxonomically restricted clade. We next conducted a comprehensive analysis of the chemoreceptors in 63 L. longipalpis individuals from four different locations in Brazil representing allopatric and sympatric populations and three sex-aggregation pheromone types (chemotypes). Population structure based on single nucleotide polymorphisms (SNPs) and gene copy number in the chemoreceptors corresponded with their putative chemotypes, and corroborate previous studies that identified multiple populations. Our work provides genomic insights into the underlying behavioral evolution of sexual communication in the L. longipalpis species complex in Brazil, and highlights the importance of accounting for the ongoing speciation in central and South American Lutzomyia that could have important implications for vectorial capacity.

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“…From the literature we collected thirteen female morphological traits [30-33] including but not limited to wing length, width, and number of teeth (Table S1), as well as vector and infection status [26, 27, 29, 31, 34-38]. Most of the sandfly morphological traits and biting behavior were taken from Young & Duncan’s 1994 book [31], with additional biting behavior data taken from sandfly surveys using Disney and Shannon traps [25, 27, 38-81].…”

Section: Methodsmentioning

confidence: 99%

“…Our dataset comprised 512 documented sandfly species (sample size n = 512). Thirty-seven of these 512 are confirmed at the time of analysis as vectors of one or more species of Leishmania causing ACL, and 35 additional species are potential vectors [10,[25][26][27][28][29].…”

Section: Data Collectionmentioning

confidence: 99%

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Data-Driven Predictions of Potential Leishmania Vectors in Latin America

Vadmal

¹

,

Glidden

²

,

Han

³

et al. 2022

Preprint

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The incidence of vector-borne diseases is rising as deforestation, climate change, and globalization bring humans in contact with arthropods that can transmit pathogens. In particular, incidence of American Cutaneous Leishmaniasis (ACL), a parasitic disease transmitted by sandflies, is increasing as previously intact habitats are cleared for agriculture and urban areas, potentially bringing people into contact with vectors and reservoir hosts. Previous evidence has identified dozens of sandfly species that have been infected with and/or transmit Leishmania parasites. However, there is an incomplete understanding of which sandfly species transmit the parasite, complicating efforts to limit disease spread. Here, we apply machine learning models (boosted regression trees) to leverage biological and geographical traits of known sandfly vectors to predict potential vectors. Additionally, we generate trait profiles of confirmed vectors and identify important factors in transmission. Our model performed well with an average out of sample accuracy of 86%. The models predict that synanthropic sandflies living in areas with greater canopy height, less human modification, and within an optimal range of rainfall are more likely to be Leishmania vectors. We also observed that generalist sandflies that are able to inhabit many different ecoregions are more likely to transmit the parasite. Our results suggest that Psychodopygus amazonensis and Nyssomia antunesi are unidentified potential vectors, and should be the focus of sampling and research efforts. Overall, we found that our machine learning approach provides valuable information for Leishmania surveillance and management in an otherwise complex and data sparse system.Author SummaryAmerican Cutaneous Leishmaniasis (ACL) is a neglected parasitic disease transmitted by sandflies in Latin America. There is an incomplete understanding of which sandfly species transmit the parasite, complicating efforts to limit disease spread. In this study, the authors created a database of sandfly traits, then used predictive models to determine important factors in disease transmission and how different climate and environmental variables affect ACL transmission. The models suggest that transmission occurs at the interface between domestic habitats and well-preserved forests. The authors also generate predictions of which sandflies might be transmitting the parasite that are not known vectors at the time, specifically Psychodopygus amazonensis and Nyssomia antunesi. This new knowledge can lead to a better understanding of the system of transmission, and can point to possible hotspots of the disease. The analysis can also help direct researchers to areas of interest for sampling studies, as well as specific sandflies to focus their effort on.

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“…Our dataset comprised 512 documented sandfly species across the Americas (sample size n = 512). Thirty-seven of these 512 are confirmed at the time of analysis as vectors of one or more species of Leishmania causing ACL, and 35 additional species are potential vectors [10,[24][25][26][27][28].…”

Section: Data Collectionmentioning

confidence: 99%

Data-driven predictions of potential Leishmania vectors in the Americas

Vadmal¹,

Glidden²,

Han³

et al. 2023

PLoS Negl Trop Dis

2

0

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The incidence of vector-borne diseases is rising as deforestation, climate change, and globalization bring humans in contact with arthropods that can transmit pathogens. In particular, incidence of American Cutaneous Leishmaniasis (ACL), a disease caused by parasites transmitted by sandflies, is increasing as previously intact habitats are cleared for agriculture and urban areas, potentially bringing people into contact with vectors and reservoir hosts. Previous evidence has identified dozens of sandfly species that have been infected with and/or transmit Leishmania parasites. However, there is an incomplete understanding of which sandfly species transmit the parasite, complicating efforts to limit disease spread. Here, we apply machine learning models (boosted regression trees) to leverage biological and geographical traits of known sandfly vectors to predict potential vectors. Additionally, we generate trait profiles of confirmed vectors and identify important factors in transmission. Our model performed well with an average out of sample accuracy of 86%. The models predict that synanthropic sandflies living in areas with greater canopy height, less human modification, and within an optimal range of rainfall are more likely to be Leishmania vectors. We also observed that generalist sandflies that are able to inhabit many different ecoregions are more likely to transmit the parasites. Our results suggest that Psychodopygus amazonensis and Nyssomia antunesi are unidentified potential vectors, and should be the focus of sampling and research efforts. Overall, we found that our machine learning approach provides valuable information for Leishmania surveillance and management in an otherwise complex and data sparse system.

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Molecular and Biochemical Markers for Investigating the Vectorial Roles of Brazilian Sand Flies

Cited by 5 publications

References 169 publications

Molecular signatures of sexual communication in the phlebotomine sand flies

Molecular signatures of sexual communication in the phlebotomine sand flies

Data-Driven Predictions of Potential Leishmania Vectors in Latin America

Data-driven predictions of potential Leishmania vectors in the Americas

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