Sequences of the cytochrome c oxidase subunit I (COI) mitochondrial gene from adults
of 22 Culex ( Culex ) species from Argentina and
Brazil were employed to assess species identification and to test the usefulness of
COI for barcoding using the best close match (BCM) algorithm. A pairwise Kimura
two-parameter distance matrix including the mean intra and interspecific distances
for 71 COI barcode sequences was constructed. Of the 12 COI lineages recovered in the
Neighbour-joining topology, five confirmed recognised morphological species (
Cx. acharistus , Cx. chidesteri , Cx.
dolosus , Cx. lygrus and Cx.
saltanensis ) with intraspecific divergences lower than 1.75%.
Cx. bilineatus is formally resurrected from the synonymy of
Cx. dolosus . Cx. maxi , Cx.
surinamensis and the Coronator group species included were clustered into
an unresolved lineage. The intraspecific distance of Cx. pipiens
(3%) was almost twice the interspecific between it and Cx.
quinquefasciatus (1.6%). Regarding the BCM criteria, the COI barcode
successfully identified 69% of all species. The rest of the sequences, approximately
10%, 18% and 3%, remained as ambiguously, mis and unidentified, respectively. The COI
barcode does not contain enough information to distinguish Culex (
Cux. ) species.
Twenty-six years after it was last detected, Saint Louis encephalitis virus (SLEV) genotype III reemerged in 2005 in Córdoba, Argentina, where it caused an outbreak. Two genotype III SLEV strains were isolated from Culex quinquefasciatus. A 71.43% prevalence for neutralizing antibodies was found in domestic fowl in the homestead of a patient with encephalitis.
In order to classify mosquito immature stage habitats, samples were taken in 42 localities of Córdoba Province, Argentina, representing the phytogeographic regions of Chaco, Espinal and Pampa. Immature stage habitats were described and classified according to the following criteria: natural or artificial; size; location related to light and neighboring houses; vegetation; water; permanence, movement, turbidity and pH. Four groups of species were associated based on the habitat similarity by means of cluster analysis: Aedes albifasciatus, Culex saltanensis, Cx. mollis, Cx. brethesi, Psorophora ciliata, Anopheles albitarsis, and Uranotaenia lowii (Group A); Cx. acharistus, Cx. quinquefasciatus, Cx. bidens, Cx. dolosus, Cx. maxi and Cx. apicinus (Group B); Cx. coronator, Cx. chidesteri, Mansonia titillans and Ps. ferox (Group C); Ae. fluviatilis and Ae. milleri (Group D). The principal component analysis (ordination method) pointed out that the different types of habitats, their nature (natural or artificial), plant species, water movement and depth are the main characters explaining the observed variation among the mosquito species. The distribution of mosquito species by phytogeographic region did not affect the species groups, since species belonging to different groups were collected in the same region.
The use of content from this health information product for all non-commercial education, training and information purposes is encouraged, including translation, quotation and reproduction, in any medium, but the content must not be changed and full acknowledgement of the source must be clearly stated. A copy of any resulting product with such content should be sent to TDR,
Aedes aegypti (Diptera: Culicidae) is an urban mosquito involved in the transmission of numerous viruses, including dengue, chikungunya and Zika. In Argentina, Ae. aegypti is the main vector of dengue virus and has been involved in several outbreaks in regions ranging from northern to central Argentina since 2009. In order to evaluate areas of potential vector-borne disease transmission in the city of Córdoba, Argentina, the present study aimed to identify the environmental, socioeconomic and demographic factors driving the distribution of Ae. aegypti larvae through spatial analysis in the form of species distribution models (SDMs). These models elucidate relationships between known occurrences of a species and environmental data in order to identify areas with suitable habitats for that species and the consequent risk for disease transmission. The maximum entropy species distribution model was able to fit the training data well, with an average area under the receiver operating characteristic curve (AUC) of > 0.8, and produced models with fair extrapolation capacity (average test AUC: > 0.75). Human population density, distance to vegetation and water channels were the main variables predictive of the vector suitability of an area. The results of this work will be used to target surveillance and prevention measures, as well as in mosquito management.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.