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Genetic diversity, phylogeography and molecular clock of the Lutzomyia longipalpis complex (Diptera: Psychodidae)

  • Angélica Pech-May ,

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

    apechmay@gmail.com

    Affiliations Instituto Nacional de Medicina Tropical, Ministerio de Salud de la Nación, CONICET, Puerto Iguazú, Misiones, Argentina, Instituto Nacional de Salud Pública / Centro Regional de Investigación en Salud Pública, Tapachula, Chiapas, México

  • Janine M. Ramsey,

    Roles Conceptualization, Methodology, Supervision, Writing – review & editing

    Affiliation Instituto Nacional de Salud Pública / Centro Regional de Investigación en Salud Pública, Tapachula, Chiapas, México

  • Raúl E. González Ittig,

    Roles Formal analysis, Methodology, Writing – review & editing

    Affiliation Instituto de Diversidad y Ecología Animal (IDEA), CONICET-Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina

  • Magali Giuliani,

    Roles Methodology, Writing – review & editing

    Affiliation Instituto Nacional de Medicina Tropical, Ministerio de Salud de la Nación, CONICET, Puerto Iguazú, Misiones, Argentina

  • Pablo Berrozpe,

    Roles Methodology, Writing – review & editing

    Affiliation Instituto Nacional de Medicina Tropical, Ministerio de Salud de la Nación, CONICET, Puerto Iguazú, Misiones, Argentina

  • María G. Quintana,

    Roles Methodology, Writing – review & editing

    Affiliations Instituto Nacional de Medicina Tropical, Ministerio de Salud de la Nación, CONICET, Puerto Iguazú, Misiones, Argentina, Universidad Nacional de Tucumán- CONICET, Instituto Superior de Entomología, FCNeIML, San Miguel de Tucumán, Argentina

  • Oscar D. Salomón

    Roles Conceptualization, Funding acquisition, Resources, Supervision, Writing – review & editing

    Affiliation Instituto Nacional de Medicina Tropical, Ministerio de Salud de la Nación, CONICET, Puerto Iguazú, Misiones, Argentina

Abstract

Background

The Lutzomyia longipalpis complex has a wide but discontinuous distribution in Latin America, extending throughout the Neotropical realm between Mexico and northern Argentina and Uruguay. In the Americas, this sandfly is the main vector of Leishmania infantum, the parasite responsible for Visceral Leishmaniasis (VL). The Lu. longipalpis complex consists of at least four sibling species, however, there is no current consensus on the number of haplogroups, or on their divergence. Particularly in Argentina, there have been few genetic analyses of Lu. longipalpis, despite its southern expansion and recent colonization of urban environments. The aim of this study was to analyze the genetic diversity and structure of Lu. longipalpis from Argentina, and to integrate these data to re-evaluate the phylogeography of the Lu. longipalpis complex using mitochondrial markers at a Latin American scale.

Methodology/Principal findings

Genetic diversity was estimated from six sites in Argentina, using a fragment of the ND4 and the 3´ extreme of the cyt b genes. Greatest genetic diversity was found in Tartagal, Santo Tomé and San Ignacio. There was high genetic differentiation of Lu. longipalpis in Argentina using both markers: ND4 (FST = 0.452, p < 0.0001), cyt b (FST = 0.201, p < 0.0001). Genetic and spatial Geneland analyses reveal the existence of two primary genetic clusters in Argentina, cluster 1: Tartagal, Santo Tomé, and San Ignacio; cluster 2: Puerto Iguazú, Clorinda, and Corrientes city. Phylogeographic analyses using ND4 and cyt b gene sequences available in GenBank from diverse geographic sites suggest greater divergence than previously reported. At least eight haplogroups (three of these identified in Argentina), each separated by multiple mutational steps using the ND4, are differentiated across the Neotropical realm. The divergence of the Lu. longipalpis complex from its most recent common ancestor (MRCA) was estimated to have occurred 0.70 MYA (95% HPD interval = 0.48–0.99 MYA).

Conclusions/Significance

This study provides new evidence supporting two Lu. longipalpis genetic clusters and three of the total eight haplogroups circulating in Argentina. There was a high level of phylogeographic divergence among the eight haplogroups of the Lu. longipalpis complex across the Neotropical realm. These findings suggest the need to analyze vector competence, among other parameters intrinsic to a zoonosis, according to vector haplogroup, and to consider these in the design and surveillance of vector and transmission control strategies.

Author summary

The Lutzomyia longipalpis complex has a wide but discontinuous distribution in Latin America, extending throughout the Neotropical realm between Mexico and northern Argentina and Uruguay. In the Americas, this sandfly is the main vector of Leishmania infantum, the parasite responsible for Visceral Leishmaniasis (VL). The Lu. longipalpis complex is composed of at least four sibling species, although there is no current consensus on the number of haplogroups, or their divergence. In Argentina, little is known about the complex population structure. Therefore, the aim of this study was to analyze the diversity and genetic structure of Lu. longipalpis from Argentina and subsequently to analyze the complex phylogeography at a Latin American scale, using two mitochondrial markers. Greatest genetic diversity was found in Tartagal, Santo Tomé and San Ignacio. Two genetic clusters and three Lu. longipalpis haplogroups were identified from the six sites in Argentina. Phylogeographic analyzes using ND4 and cyt b gene sequences and those from across the Neotropical realm registered in GenBank, suggest greater divergence than previously reported. At least eight haplogroups are differentiated using the ND4, each separated by multiple mutational steps. Lu. longipalpis complex divergence from its most recent common ancestor (MRCA) was estimated at mid Pleistocene, 0.70 MYA (95% HPD interval = 0.48–0.99 MYA).

Introduction

Visceral leishmaniasis (VL) is a parasitic disease caused in the American continent, by Leishmania infantum (syn. Le. chagasi). VL has an estimated global incidence of 500,000 cases and 59,000 deaths per year [1]. Human cases of VL in Latin America are reported in 12 countries, while Argentina reports an expanding epidemiological scenario [2]. The first autochthonous VL cases in both humans and canines in Argentina were reported in 2006, in the city of Posadas, Misiones [3]. Currently, the country has reported 106 human cases of VL, with 7.7% mortality, between 2006 and 2016 [4]. Misiones is the province with most human VL cases; the age group with highest incidence is children 0–15 yrs [5]. In Argentina, the main vector of Le. infantum is Lutzomyia longipalpis (Lutz & Neiva) [3]. This phlebotomine was first reported in 1951 in Candelaria, and later in 2000, in Corpus, both in Misiones [6]; there were no VL cases reported at either time. The first autochthonous VL human cases with parasite presence confirmed were reported from Posadas, in 2006 [3]. At present, the vector has dispersed to southern Argentina while also expanding in the north. Currently, Lu. longipalpis is also reported in Corrientes, Entre Ríos, Chaco, Formosa, and Salta provinces [5, 710].

Lutzyomia longipalpis is currently considered a species complex, despite a broad yet discontinuous distribution within the Neotropical realm, from Mexico to the north of Argentina and Uruguay [9, 11]. Recent studies using ecological niche models report that anticipated distributional shifts of Lu. longipalpis vary by region, although greater projected landscape fragmentation and anthropic modifications will not significantly affect model projections [12, 13]. This sandfly is adapted to a variety of habitats in tropical regions, from rocky, arid, semi-arid, to very humid, and forested [11, 14]. Throughout the species´ distribution, different patterns of genetic divergence and evidence for cryptic species have been reported [1520]. Mangabeira [21] was the first to evidence ecological and morphological differences between populations of Lu. longipalpis collected in Pará and Ceará states, Brazil. These males had one pair of pale tergal spots on abdominal tergite IV (phenotype 1S), and another additional pair on tergite III (phenotype 2S). Other studies in Lu. longipalpis have reported sympatry of the differentiated phenotypes [22, 23], isoenzyme variability [19, 2326], differences in sex pheromones [2729], variation in the salivary peptide, maxadilan [30, 31], differences in male copulation songs [29], wing morphometric variation [24], and genetic variability and divergence using multiple genetic markers [16, 18, 19, 28, 29, 3234]. Mitochondrial genes are considered good tools for population genetics and phylogeography due to their abundance, little or no recombination and a haploid mode of inheritance [35]. Fragments of the nicotinamide dinucleotide dehydrogenase subunit 4 (ND4) and the 3' region of cytochrome b (cyt b) are highly variable at the inter and intra-specific level in phlebotomine sandflies [16, 3639]. They have been successfully used to analyze genetic diversity, population genetics, and phylogeography of Lu. longipalpis [16, 20, 37, 4042], as well as in other New World sandfly species e.g. Lu. cruciata (Coquillett) [43], Lu. anduzei (Rozeboom) [44], Lu. olmeca olmeca (Vargas & Díaz-Nájera) [45] and old world sandfly species e.g. Phlebotomus papatasi (Scopoli) [38, 39], Phlebotomus ariasi (Tonnoir) [46] and Sergentomyia (Sintonius) clydei (Sinton) [47]. Genetic diversity, genetic differentiation, and sandfly speciation have been associated with multiple factors, such as latitude or altitude, distance between populations, habitat modifications, anthropogenic landscape fragmentation, vegetation type, geographic barriers (rivers, mountains), host communities, and host species turnover. These factors reduce sandfly dispersal capacity thereby giving rise to isolated populations, loss of genetic diversity, and increasing differentiation among populations [20, 3941, 43, 44, 46, 4851].

There are few studies on the genetic status of Lu. longipalpis in Argentina, although it is clear that the species is expanding southward and is colonizing urban environments [52]. Salomón et al. [33] using the “per” gene, found high genetic differentiation between Lu. longipalpis from Posadas (Misiones province, Argentina) and the north and southeast regions of Brazil, suggesting they might represent another sibling species. In contrast, males from Argentina secrete the same male pheromone as those from Paraguay [53] and other populations from Brazil [27, 29, 54]. It is therefore important to be able to identify and differentiate haplogroups, since they may differ in importance as diseases vectors. Haplogroups may differ in terms of vector competence, vector capacity, or other epidemiological aspects [55], or the clinical expression of disease, based on maxadilan salivary content [31]. Although at least four sibling species have been proposed for the Lu. longipalpis complex [16, 18, 19, 56, 57], there is insufficient evidence currently for a general consensus on the exact number of haplogroups, or their divergence. The aim of this study was to analyze the genetic diversity and structure of Lu. longipalpis from Argentina, and to integrate these data to re-evaluate the phylogeography of the Lu. longipalpis complex using mitochondrial markers at a Latin America scale.

Methods

Study area and taxonomic identification

Lutzomyia longipalpis was collected in six sites in Argentina by the Leishmaniasis Research Network (REDILA). Four of these localities have reported human VL cases (Puerto Iguazú, San Ignacio, Santo Tomé, and Corrientes city), one has reported only canine cases (Clorinda), and one has not reported any VL cases to date (Tartagal) (Fig 1, S1 Table). Clorinda and Corrientes city are located in the humid Chaco ecoregion, which has a warm subtropical climate. Puerto Iguazú and San Ignacio are located in the Paranense forest ecoregion with a humid subtropical climate, and Santo Tomé is found in grassland and forest ecoregion also in a humid subtropical climate. Tartagal is located in the Yunga forest ecoregion with a subhumid warm climate [58]. Sandfly collections were carried out using REDILA-BL light traps [59], and specimens were preserved in 90% ethanol and transported to the laboratory. The last three segments of males were dissected for taxonomic identification, while the rest of the insects were used for molecular analyses. The dissected segments were clarified with lacto-phenol and mounted on slides, and identified using optical microscopy using the Galati taxonomic key [60].

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Fig 1. Geographic distribution of Lutzomyia longipalpis complex specimens analyzed.

Sampling sites for Argentinian specimens for which there are sequences for both gene fragments (triangles), for those sequences analyzed from GenBank for ND4 [16, 42] (circles), and those from GenBank for cyt b sequences [20, 37, 40, 41] (square). This map was generated using QGIS v.2.6.1 [61].

https://doi.org/10.1371/journal.pntd.0006614.g001

DNA extraction, amplification and sequencing

Genomic DNA was extracted from individual sandflies using DNA Puriprep-S kit Highway (Inbio, Argentina), according to manufacturer’s instructions. The ND4 fragment was amplified using primers reported by Soto et al. [16]. PCR reactions were carried out in 50 μl volumes, containing 25 μl of Gotaq green Master Mix (Promega, USA), 50 pmol/μl of each primer, 2.5 mM of MgCl2 and 50 ng of template DNA. Amplification conditions were: 95°C for 5 min, followed by 35 cycles of 95°C (30 sec), 48°C (45 sec), 72°C (1 min) and a final elongation step at 72°C for 10 min. The 3´end of the cyt b fragment was amplified using primers and amplification conditions reported by Hodgkinson et al. [40, 41] and the PCR was performed according to Pech May et al. [43]. PCR products were separated using 1.5% agarose gel electrophoresis, stained with 0.5 μg/ml Sybr Green (Invitrogen, USA), and visualized under UV light. PCR products were purified by HW DNA Puriprep-GP kit (Inbio, Argentina), and sequenced using both forward and reverse primers in a CEQ 2000XL automated sequencer (Beckman Coulter, USA).

Genetic analyses of Argentinian populations

Forward and reverse sequences from all samples were used to generate consensus sequences and were manually aligned and edited using MEGA v.7 [62]. All haplotypes were deposited in GenBank (accession numbers for the ND4 fragment: MH166358- MH166392; accession numbers for the cyt b fragment: MH166339- MH166356). Intra-population and global genetic diversity was analyzed using the number of mutations (η), the number of segregating sites (S), the number of unique sites (Su), the mean number of pairwise differences (k), haplotype number (Nh), haplotype diversity (Hd), nucleotide diversity (π), and the nucleotide polymorphism index (θ), using DnaSP v.5.10 [63]. Neutrality tests based on Tajima’s D and Fu’s Fs [64, 65] were calculated based on segregating sites, using the same software. In addition, the mismatch distribution test was also analyzed using ARLEQUIN v.3.5 [66]. The goodness-of-fit of the observed data to a simulated expansion model was tested using both Harpending’s raggedness index (r) [67] and the sum of squares deviations (SSD), using 10,000 replicates. Molecular variance (AMOVA) was used to evaluate population genetic differentiation, using 10,000 random permutations in ARLEQUIN v.3.5. The p values of pairwise FST were adjusted using the Holm-Bonferroni sequential correction “p´” [68, 69]. Association between genetic and geographic distance was analyzed using a Mantel test [70], implemented in a trial version of XLTAT (https://www.xlstat.com). Linear geographic distances between sites were estimated using QGIS v.2.6.1 [61].

ND4 and cyt b fragments were concatenated and analyzed using GENELAND package in R to infer the number of Lu. longipalpis genetic clusters among Argentinian sites [7174]. This program uses a spatial statistical model and Markov chain Monte Carlo sampling with GPS coordinates to estimate the number of populations or genetic clusters (K). Preliminarily, we estimated the number of K from 1 to 10, using 10 million MCMC iterations and 1,000 thinnings. Five independent runs with fixed “K” were run (to avoid ghost populations), assuming an uncorrelated allelic frequency and spatial model. For each run, the posterior probability (PP) of subpopulation membership was computed for each pixel of the spatial domain (100 x 100 pixels), using a burn-in of 1,000 iterations. Variation among and within populations of genetic clusters was analyzed using 10,000 random permutations for the AMOVA in ARLEQUIN v.3.5.

Phylogeographic analyses: Network haplotypes, phylogenetic inferences, and divergence times

Unique Lu. longipalpis haplotypes generated herein from Argentina, ND4 gene sequences from GenBank (AF293027—AF293054; AY870836—AY870863 [16, 42]), as well as cyt b gene sequences from GenBank (AF448542; AF468979—AF468999; AF480170—AF480181; EF107662—EF107666; HM030727 [20, 37, 40, 41]) were used in analyses (Fig 1, S1 Table). The relationship among haplotypes using ND4 and cyt b sequences was evaluated by constructing independent median-joining haplotype networks implemented in Network v.4.6 [75]. The jModeltest v.2 [76] was used to select the best-fitting model of evolution using the Bayesian Information Criterion (BIC). The Bayesian inference (BI) was generated using Mr. Bayes v.3.2 [77]. Posterior probabilities of phylogenetic trees were estimated using 10 million generations (sampled every 1,000 generations) and four Metropolis-coupled Markov chain Monte Carlo (MCMC) to allow adequate time and mixing for convergence. The first 25% of sampled trees were considered as burn in. The consensus tree was visualized using FigTree v.1.4. Sequences of Migonemyia migonei (access numbers, ND4: MH166393, cyt b: MH166357) and Phlebotomus papatasi (access number, ND4 and cyt b: KR349298) were used as outgroups.

Divergence times among haplogroups were estimated using BEAST v.1.8.4 [78]. We calibrated using the divergence rate reported by Esseghir et al. [36], and corrected as suggested by Ho et al. [79], assuming 0.105 substitution/site/million years. An uncorrelated lognormal relaxed-clock model was used to allow rate variation among branches and the coalescent exponential growth option. Convergence of the MCMC chains was checked using TRACER v.1.6, with 200 as the minimum effective sample size. The length of the runs were: a) 100 million generations for the ND4 fragment, and b) 500 million generations for the cyt b fragment; sampling was every 10,000 and 50,000 generations, respectively. The first 10% of the samples were discarded as burn-in and a maximum clade credibility tree, reflecting divergence times and their 95% highest posterior densities, was estimated using TreeAnotator of the BEAST package and visualized using FigTree v.1.4.

Nucleotide divergence (Da) for the haplogroups was estimated based on the number of net nucleotide substitutions, using the Jukes and Cantor (JC) correction [80, 81] with DnaSP v.5.1.0. The pairwise FST comparison between haplogroups was performed using 10,000 random permutations in ARLEQUIN v.3.5. The p values were adjusted using a Holm-Bonferroni sequential correction “p´” [68, 69]. The single sequence from Venezuela was not included in these latter analyses.

Results

Lu. longipalpis genetic diversity in Argentina using the ND4 fragment

Seventy-three specimens of Lu. longipalpis were sequenced from six Argentinian sites using a 618 bp fragment of the ND4 gene (Table 1A). This fragment had 68 polymorphic nucleotides (11%) and the A-T composition was 73.3%. A total of 35 haplotypes were identified, with a range of 4–14 haplotypes per site. Globally, haplotype diversity was high (Hd ± SD = 0.858 ± 0.039), while nucleotide diversity and polymorphism indices were low (π ± SD = 0.014 ± 0.001 and θ ± SD = 0.022 ± 0.002, respectively). Populations from San Ignacio, Santo Tomé, and Tartagal had highest genetic diversity (Table 1A). The global neutrality tests were, in general, not significant, except for Corrientes city, which was negative and significant for both tests (Tajima D = -1.897; Fs = -3.724), consistent with population expansion. This result agrees with the mismatch distributions which are unimodal (SSD = 0.0003, p = 0.979; r = 0.019, p = 0.992). Population expansion based on the mismatch distribution was also found in Puerto Iguazú (SSD = 0.02, p = 0.43; r = 0.089, p = 0.705) and San Ignacio (SSD = 0.098, p = 0.28; r = 0.217, p = 0.273). In the latter site, the distribution was multimodal, and hence few individuals shared each haplotype. In contrast, in Tartagal with no indication of population expansion (SSD = 0.038, p = 0.007; r = 0.062, p = 0.04), there was a multimodal distribution indicating demographic equilibrium. Analyses for Santo Tomé and Clorinda were inconclusive (SSD = 0.966, p = 0; r = 0.051, p = 1; SSD = 0.297, p = 0.049; r = 1.11, p = 0.057, respectively) (S1 Fig).

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Table 1. Genetic diversity indices for Lu. longipalpis populations from Argentina with the fragments ND4 and 3´cyt b.

https://doi.org/10.1371/journal.pntd.0006614.t001

The global genetic differentiation of Lu. longipalpis from Argentina using the ND4 fragment is high (FST = 0.452, p < 0.0001), although most of the genetic differentiation was within populations (54.8%). Greatest genetic difference was between San Ignacio and Corrientes city, with an FST of 0.86 (p < 0.0001) (Table 2). There was no evidence for genetic isolation associated with geographic distance (r = 0.24, p = 0.37).

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Table 2. Pairwise FST genetic comparisons between Lu. longipalpis populations from Argentina.

Below diagonal from ND4 fragment, above diagonal from 3´ cyt b fragment.

https://doi.org/10.1371/journal.pntd.0006614.t002

Lu. longipalpis genetic diversity in Argentina using the cyt b fragment

Seventy-six specimens of Lu. longipalpis were sequenced from all six sites in Argentina, using the 261 bp fragment of the cyt b gene (Table 1B). This fragment had 20 polymorphic nucleotides (7.66%), and the A-T composition was 76.3%. The cyt b fragment identified 18 haplotypes, ranging from 2 to 12 per site. Globally, haplotype diversity was high (Hd ± SD = 0.772 ± 0.036), similar to that for the ND4 fragment, as were low nucleotide diversity and nucleotide polymorphism index (π ± SD = 0.008 ± 0.0009 and θ ± SD = 0.015 ± 0.003, respectively). San Ignacio, Santo Tomé and Tartagal had highest cyt b diversity (Table 1B), although the global neutrality test was not significant. The Tajima test was significant for Corrientes city, but with a positive value (D = 2.083), probably due to the low number of haplotypes, suggesting bottleneck events. The mismatch analysis for this site was inconclusive (SSD = 0.196, p = 0.145, r = 0.767, p = 0.016). In contrast, in Tartagal, Fu’s Fs was negative and significant (Fs = -5.598; p < 0.0001), consistent with population expansion or selective sweep/hitch-hiking. This latter also agrees with the mismatch distribution analysis (SSD = 0.012, p = 0.481; r = 0.033, p = 0.761). Population expansions based on mismatch distributions were also present in Clorinda (SSD = 0.021, p = 0.655; r = 0.25, p = 0.93), San Ignacio (SSD = 0.089, p = 0.405; r = 0.204, p = 0.74), and Santo Tomé (SSD = 0.037, p = 0.302; r = 0.135, p = 0.228). Despite the previous for San Ignacio and Santo Tomé, they had multimodal distributions with pronounced peaks, suggesting that few individuals share each haplotype. There were inconclusive results from Puerto Iguazú (SSD = 0.202, p = 0.14; r = 0.783, p = 0.034) (S2 Fig). There was high genetic differentiation (FST = 0.201, p < 0.0001), principally within populations (79.84%). Greatest genetic difference was between San Ignacio and Corrientes city (FST = 0.605, p < 0.0001) (Table 2). Again, there was no evidence for genetic isolation associated with geographic distance (r = 0.49, p = 0.06).

Population clusters in Argentina

Geneland analysis (integrating genetic and spatial information) revealed two main genetic clusters (PP = 0.9, K = 2). Each cluster included three sites: Cluster 1 with Tartagal, Santo Tomé, and San Ignacio, and Cluster 2 with Puerto Iguazú, Clorinda, and Corrientes city (Fig 2). According to the AMOVA analysis, differences between the geographic clusters explained 30.16%, whereas inter- and intrapopulation differences explained 12.13% (p < 0.0009) and 57.72% (p < 0.0001) of the variation, respectively.

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Fig 2. Spatial distribution of Argentinian Lutzomyia longipalpis genetic clusters inferred with Geneland.

The highest membership values are in green (cluster 1) and blue (cluster 2) to a low PP (light green and light blue to white). Cluster 1: Tartagal (Tar), Santo Tomé (ST), and San Ignacio (SI); Cluster 2: Corrientes city (Corr), Clorinda (Clo) and Puerto Iguazú (Ig). This map was generated using QGIS v.2.6.1 [61].

https://doi.org/10.1371/journal.pntd.0006614.g002

Phylogeographic analysis using the ND4 fragment

A total of 91 haplotypes of Lu. longipalpis reported from seven Latin American countries were included in ND4 phylogeographic analyses (Guatemala, Honduras, Costa Rica, Venezuela, Colombia, Brazil and Argentina) (S1 Table). The Median-joining network identifies at least eight haplogroups, each separated by various mutational steps (BI results were also taken into account for the definition of these haplogroups, Figs 3 and 4). In the Ar1 haplogroup there are 12 haplotypes corresponding to San Ignacio, Santo Tomé and Tartagal specimens, which coincide with Cluster 1 from Geneland analyses. In the Ar-Bra haplogroup, H7 (from both Tartagal and Santo Tomé) and H22 (from Santo Tomé) are grouped with haplotypes from Jacobina and Lapinha in Brazil; there are at least two mutational steps between these haplotypes. The Ar2 haplogroup only includes haplotypes from Argentinian sites, H2 being the most prevalent and shared by all six sites from this study. Haplotypes H15, H20, and H30 are separated by at least 17 mutational steps from the Bra haplogroup. This latter haplogroup includes haplotypes exclusively from Sobral and Pernambuco, Brazil. The haplogroup from Central American (CA) (Honduras, Guatemala, and Costa Rica) is more related to the Bra haplogroup than to the two Colombian haplogroups (Col1 and Col2). The Ven haplogroup (only H53) is more related to haplotypes within the Col2 haplogroup. The two Colombian haplogroups (Col 1 with haplotypes from Giron and Col2 with haplotypes from Neiva and El Callejón) are separated by at least 71 mutational steps (Fig 3, for details of haplotypes see S1 Table).

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Fig 3. Median-joining haplotype network of the Lutzomyia longipalpis complex based on 618 nucleotides of the ND4 gene.

The circle size corresponds to the frequency of each haplotype. Missing haplotypes are shown as red circles. Each line connecting haplotypes represents one mutational step, whereas numbers along the lines are total number of mutational steps between haplotypes. Colours indicate: orange = Clorinda; fuchsia = Corrientes city; turquoise = Puerto Iguazú; grey = San Ignacio; pink = Santo Tomé; purple = Tartagal; blue = Honduras; white with red outline = Costa Rica; dark green = Guatemala; yellow = Colombia; white with blue outline = Venezuela; green = Brazil.

https://doi.org/10.1371/journal.pntd.0006614.g003

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Fig 4. Calibrated maximum-clade-credibility tree for the Lu. longipalpis complex using the ND4 fragment.

The HKY + G model was used for a 618 base pair dataset of the ND4 gene. Numbers above each branch represent PP obtained in the BI (≥ 0.95). M. migonei and P. papatasi were used as outgroup. The scale bar represents the line of time in million years ago (MYA) and the numbers indicated by arrows show the time estimate and the 95% HPD.

https://doi.org/10.1371/journal.pntd.0006614.g004

The BI for ND4 phylogeographic analysis was constructed using the HKY + G model as the most appropriate for the data (-lnL = 2913.8833; BIC = 7035.9464) with gamma of 0.1510. The tree revealed eight haplogroups with maximum support for two major clades (PP = 1.0; Fig 4). One of the major clades is composed of Ar1 (Argentina), Ar-Bra (Argentina-Brazil), Ar2 (Argentina), and Bra (Brazil) haplogroups. The other major clade includes haplogroups from CA (Guatemala, Honduras and Costa Rica), and the three northern South America haplogroups: Col1 (Colombia), Col2 (Colombia), and Ven (Venezuela). Divergence of the Lu. longipalpis complex from the most recent common ancestor (MRCA) was 0.70 MYA (95% HPD interval = 0.48–0.99 MYA). Divergence of the clade that includes Ar1, Ar-Bra, Ar2 and Bra haplogroups is estimated at 0.36 MYA (95% HPD interval = 0.23–0.53 MYA), and that of the other major clade that includes CA, Col1, Col2, and Ven, 0.58 MYA (95% HPD interval = 0.38–0.81 MYA. The MRCA of Argentinian populations is estimated at 0.22 MYA (95% HPD interval = 0.14–0.32 MYA). Net nucleotide substitutions (Da) between haplogroups ranged from 1.2% to 7.5%, while the pairwise FST between haplogroups was high, with genetic differentiation ranging from 0.468 to 0.966 (Table 3).

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Table 3. Nucleotide divergence (Da) of the ND4 fragment measured as the number of net nucleotide substitutions for Lu. longipalpis haplogroups (see Results) using the Jukes and Cantor correction (below diagonal), and pairwise FST comparisons between haplogroups (above diagonal).

https://doi.org/10.1371/journal.pntd.0006614.t003

Phylogeographic analysis using the cyt b fragment

Phylogeographic analyses using the cyt b fragment included 58 haplotypes of Lu. longipalpis from Venezuela, Brazil, and Argentina (S1 Table). The Median-joining network, had few mutational steps separating haplotypes, identifying five haplogroups (BI was also taken into account for haplogroup definition; Figs 5 and 6). The Bra haplogroup has a difference of two mutational steps with H46/Tartagal/Argentina (Ar1 haplogroup), while the Ar1 haplogroup has haplotypes only from Tartagal, Santo Tomé, and San Ignacio. The Ar2 haplogroup has cyt b haplotypes from all six Argentinian sites, the most frequent haplotype being H39 (present in five sites), although this has only a two mutational step difference with H5 (Brazil). The Ar-Bra haplogroup has haplotypes from Tartagal, Santo Tomé and from Juazeiro (Brazil). The single haplotype from Altagracia de Orituco, Venezuela, has a 9 mutational step difference with other frequent haplotypes shared with four Argentinian populations (H40) (Fig 5).

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Fig 5. Median-joining haplotype network of the Lu. longipalpis complex based on 261 nucleotides of the 3´ region of the cyt b gene.

The circle size corresponds to the frequency of each haplotype. Intermediary haplotypes (missing intermediate haplotypes) are shown as red circles. Each line connecting haplotypes represents one mutational step, whereas numbers along the lines are total number of mutational steps between haplotypes. Colours indicate: orange = Clorinda; fuchsia = Corrientes city; turquoise = Puerto Iguazú; grey = San Ignacio; pink = Santo Tome; purple = Tartagal; white with blue outline = Venezuela; green = Brazil.

https://doi.org/10.1371/journal.pntd.0006614.g005

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Fig 6. Calibrated maximum-clade-credibility tree for the Lu. longipalpis complex using the 3´ region of the cyt b gene.

The HKY + G model was used for a 261 base pair dataset. Numbers above each branch represent PP from the BI (≥ 0.95). M. migonei and P. papatasi were used as outgroup. The scale bar represents the line of time in million years ago (MYA) and the numbers indicated by arrows show the time estimate and the 95% HPD.

https://doi.org/10.1371/journal.pntd.0006614.g006

The BI from cyt b sequences was constructed using the HKY + G model as the most appropriate for the data (-lnL = 1073.7679; BIC = 2793.0201) with gamma 0.1910. Two major clades were identified, with PP ranging from 0.6 to 1.0: a) one with the Ar1, Ar2, Ar-Bra and Bra haplogroups, and b) the clade with the single haplotype from Venezuela. One haplotype from Juazeiro (H5/Brazil) grouped with Argentinian haplotypes into the Ar-Bra haplogroup (Fig 6). Divergence of the complete Lu. longipalpis complex from the MRCA was estimated at 0.45 MYA using the cyt b fragment (95% HPD interval = 0.22–0.83 MYA). The MRCA for the Argentinian and Brazilian haplogroups was estimated at 0.28 MYA (95% HPD interval = 0.15–0.45 MYA). Net nucleotide substitutions (Da) between haplogroups varied from 0.4%–4.7%, while the pairwise FST between haplogroups was high, genetic differentiation ranging from 0.381 to 0.521 (Table 4).

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Table 4. Nucleotide divergence (Da) from 3´ cyt b fragment measured as the number of net nucleotide substitutions between Lu. longipalpis haplogroups (see Results) using the Jukes and Cantor correction (below diagonal), and pairwise FST comparisons between Lu. longipalpis haplogroups (above diagonal).

https://doi.org/10.1371/journal.pntd.0006614.t004

Discussion

The two mitochondrial fragments from the ND4 and cyt b genes identified high overall haplotype diversity, but relatively low nucleotide diversity and nucleotide polymorphism for Lu. longipalpis in Argentinian populations. Similar indices for the ND4 gene were reported by Soto et al. [16] in Lu. longipalpis populations from Honduras, Central America (Honduras + Guatemala) and Colombia. Likewise, Coutinho-Abreu et al. [20] using the 3´ of the cyt b gene from nine Brazilian Lu. longipalpis populations reported similarly low nucleotide diversity, but higher haplotype diversity. Variability in Lu. longipalpis is similar to that within other species having wide distributions such as P. papatasi in the Old World using the ND4 gene [38]. A greater number of ND4 haplotypes were found (Nh = 35), than that for the 3´ of cyt b gene (Nh = 18) in the present study. The populations with highest genetic diversity, using both markers, were Tartagal, Santo Tomé, and San Ignacio. Previous studies have demonstrated that in general, older established populations have higher genetic diversity, which could be related in part to a relatively constant population size [82]. Neutrality indices were not significant for the three populations, which coincides with little change in population size. However, Tartagal had contradictory results, since the cyt b neutrality test (Fs = -5.598) and its mismatch distribution were consistent with an excess of low-frequency haplotypes, both characteristic of relatively recent population expansion, or of selective sweep/hitch-hiking [83]. In contrast, neutrality tests for the ND4 in Tartagal were not significant and the mismatch distribution was multimodal, which is consistent with demographic equilibrium [84]. Both fragment mismatch distributions from Santo Tomé and San Ignacio indicate that few individuals share each haplotype, which along with high haplotype diversity and a large number of unique haplotypes, may indicate that their populations were historically established.

In comparison, Corrientes city, Puerto Iguazú, and Clorinda had lower genetic diversity, which may be the result of a reduced effective population size and capacity for dispersal (causing loss of genetic diversity and increase of differentiation among the populations). These two features would favor genetic drift, as was proposed for Lu. cruciata [43], Lu. anduzei [44], and Lu. olmeca olmeca [45]. Additionally, populations with low haplotype and nucleotide diversity may have recently experienced prolonged or severe bottlenecks [85]. Results from both gene fragments are contradictory from Corrientes city, the neutrality test with cyt b suggesting an important population size reduction (D = 2.083, p < 0.05, and positive Fs), but the ND4 indicating population expansion (significant and negative Fs and unimodal mismatch distribution). A greater sampling effort will be required for Puerto Iguazú, Corrientes city, and Clorinda, from which too few haplotypes were identified for analyses and comparisons. These populations should be continuously monitored to analyze the impacts of environmental factors (abiotic, biotic, fragmentation) and healthcare or agricultural interventions (insecticides) over time. Landscape modification or fragmentation caused by anthropogenic actions (e.g. agricultural practices, deforestation) has been shown to be associated with the loss of genetic diversity in Lu. cruciata [43], Lu. gomezi [51], Lu. anduzei [44], and P. papatasi [39].

Argentinian Lu. longipalpis populations have high global genetic differentiation, with both markers, perhaps associated with the species´ reduced dispersal capacity. Sandfly dispersal depends on several factors, including average flight distance, wind speed and variation, and distance to resources [86]. It also depends on landscape heterogeneity (abiotic and biotic conditions), which influence female host, resting, mating, and egg laying site selection [87]. Phlebotomines are generally poor fliers, with movement restricted to short, flight-assisted hopping. Lu. longipalpis flight range is from 1 m to 500 m, but no more than 1,000 m around their breeding sites [86]. This flight range limitation would lead to rapid local population differentiation, due to genetic drift or to population fragmentation [43, 44, 51]. In Argentina, two specific Lu. longipalpis genetic clusters were identified. Given shared haplotypes in Tartagal and Santo Tomé, cluster 1 may have occurred via a colonization event from Brazil (Ar-Bra haplogroup) or from the Bolivia-Brazil-Paraguay Gran Chaco eco-region, which is associated with sporadic cases of rural human VL [6]. Curiously, there are no sequences of Lu. longipalpis from these latter countries in GenBank. In the case of Santo Tomé, the most likely route of entry to Argentina is São Borja, Brazil, where an outbreak of VL was reported in 2008 [88]. A similar situation could have occurred with rapid dispersal of Lu. longipalpis-VL and urban colonization in Campo Grande (Mato Grosso do Sul-Brazil). Subsequent colonization may have occurred via Paraguay and the Argentinian border areas of Clorinda and Posadas. In the present study, we detected genetic similarities among the populations of Clorinda, Corrientes city and Puerto Iguazú (these three populations share several haplotypes and low genetic differentiation), which is in agreement with rapid invasive scenarios of urban Lu. longipalpis-VL [52, 89].

Bayesian inference using the cyt b gene was not well supported, probably due to its low substitution rate [44]. However, too few haplogroups may have been analyzed (Argentinian, Brazilian and Venezuelan), and hence analysis of a larger sample set is recommended. The ND4 gene inference, in contrast, strongly supports monophyly for the Lu. longipalpis complex. Currently, the exact number of sibling species in the complex remains tentative, due to its broad distribution and absence of sufficient analyses. Soto et al. [16] identified four clades using the ND4 gene (Brazil, Central America, and laboratory colony population from Colombia and Venezuela), and similarly, Arrivillaga et al. [18, 19] using the COI gene also identified four clades (Laran: Venezuela; cis-Andean: Venezuela, Colombia, northern Brazil; trans-Andean: Venezuela, Colombia, Central America; and Brazilian: Brazil). Analyses of the ND4 sequences from the present study, in addition to those reported by Soto et al. [16] and Sonoda [42], identified eight haplogroups: Ar1 (Argentina), Ar2 (Argentina), Ar-Bra (Argentina, Brazil), Bra (Brazil), CA (Guatemala, Honduras, Costa Rica), Col1 (Colombia), Col2 (Colombia) and Ven (Venezuela). The latter haplogroup is interpreted with caution since only one sequence was analyzed despite the MRCA support with 1.0 PP. These eight haplogroups are highly distant by a minimum of several mutational steps, and they have high pairwise FST and nucleotide divergence, suggesting negligible gene exchange, similar to that suggested in a previous study [16]. This high genetic differentiation among haplogroups may potentially be due to vicariance, and/or climatic tolerance limits, in addition to low dispersal capacity. Geographic and/or climatic barriers have already been associated with diversification not just for Lu. longipalpis [16, 20, 42], but also for Lu. whitmani [48, 49], Lu. cruciata [43], Lu. gomezi [51], Lu. umbratillis [90], and P. papatasi [91].

The present study provides evidence that there are at least three Lu. longipalpis haplogroups in Argentina. Salomón et al. [33] were the first to provide evidence that Argentinian populations may be sibling species to those reported from the northeast and southeast of Brazil [29, 92, 93]. The present study documents significantly high genetic differentiation between the Argentinian and Brazilian haplogroups, despite the Ar-Bra haplogroup, which groups haplotypes from Argentina (Tartagal and Santo Tomé) and Brazil (Jacobina, Lapinha caves and Juazeiro). This genetic difference contrasts with similar complex-level compounds produced by Lu. longipalpis from Posadas, Argentina [33], Asunción, Paraguay [53], and many populations from Brazil including Lapinha [54].

Divergence of the Lu. longipalpis complex from its MRCA occurred approximately 0.70 MYA, and resulted in two principal clades, one located east and south of the Amazon basin, giving rise to the principal South American (SA) haplogroups (Brazil and Argentina), and another north from northern South America (NSA), through the Mesoamerican corridor (CA) to Mexico. These two clades are similar to those reported by Arrivillaga et al. [18, 19], although in contrast to those reported by Soto et al. [16]. Divergence times indicate that this latter cluster from Mesoamerica and NSA, was the first to diverge (0.58 MYA), significantly earlier than the cluster from east and south SA (0.36 MYA). Secondary divergence between the Col2 and the Ven haplogroups (0.25 MYA) and between Ar2 and Ar-Bra/Ar1 haplogroups (0.22 MYA), occurred on similar time scales. Diversification of all haplogroups occurred after the middle Pleistocene, probably during inter-glacial periods, when landscape fragmentation probably provoked diversification hotspots which conserved high diversity [13]. Extreme climate changes that occurred in the Pleistocene forced adaptation/selection of most biota, including phlebotomine sandflies, to resulting biotic and abiotic conditions [94]. Sandflies may have been subjected to local cycles of dry and cold periods, taking refuge and adapting to the more permanent humid resting fragments, which allowed these haplogroups and diversity to evolve [13, 95]. Indeed, plant species’ distribution shifts resulting from climate variation during the Pleistocene, have also been associated with changes in Lu. longipalpis complex diversification [18, 95, 96]. Arrivillaga et al., [18, 19] suggest that divergence was probably a result of vicariance events that occurred throughout the late Pliocene and Pleistocene (e.g. Andean orogeny). However, recent analyses indicate a highly conserved geographic coverage of the ecological niche of Lu. longipalpis from the Last Glacial Maximum (LGM) in northern Mesoamerica (88.1%), the species complex´ northern limit [13]. Hence, genetic diversity is highest in the most temporally conserved landscapes. This hypothesis can now be analyzed between and within the major Lu longipalpis haplogroup clades.

This is the first report on the genetic diversity of Lu. longipalpis from Argentinian populations, which has high genetic differentiation, two genetic clusters, and three haplogroups. Phylogeographic results provide evidence for a high level of divergence among the eight haplogroups identified for the Lu. longipalpis complex using ND4. Finally, the findings represent only the first stage of future studies required to include a more balanced sampling across Lu. longipalpis distributions and a greater number of samples not only within Argentina, but in all continental subregions. Multilocus genetic analyses will also be required in order to more completely understand evolutionary processes in this important vector species complex, and the impact of environmental change on vector transmission risk of VL. The understanding of the biological and evolutionary aspects of this species complex at the micro and macro-evolutionary levels are central to understanding the interplay between vector capacity, vectorial competence for different Leishmania parasites, urban colonization potential (micro-environment adaptation), demographic aspects of Leishmania transmission, and the clinical expression of disease [30, 55].

Supporting information

S1 Table. Origin of Lutzomyia longipalpis samples included in analyses.

https://doi.org/10.1371/journal.pntd.0006614.s001

(XLSX)

S1 Fig. Mismatch distributions based on 618 bp of the ND4 gene from six populations of Lu. longipalpis from Argentina.

The black lines are observed distribution, the dotted line indicates the distribution simulated under a sudden expansion model. The sum of squared deviations (SSD) and Harpending’s raggedness index (r) and corresponding p-values are shown.

https://doi.org/10.1371/journal.pntd.0006614.s002

(TIF)

S2 Fig. Mismatch distributions based on 261 nucleotides of the 3´ region of the cyt b gene from six populations of Lu. longipalpis from Argentina.

The black lines are observed distribution, the dotted line indicates the distribution simulated under a sudden expansion model. The sum of squared deviations (SSD) and Harpending’s raggedness index (r) and corresponding p-value are shown.

https://doi.org/10.1371/journal.pntd.0006614.s003

(TIF)

Acknowledgments

The first author (APM) dedicates this manuscript to her father Francisco Javier Pech Navarro in memoriam. The authors would like to thank Javier Liotta, Sergio Casertano, Juan Molina and Marcio Antúnez for their help in field and laboratory work. We thank Mundo Sano for the samples from Clorinda.

References

  1. 1. Alvar J, Velez ID, Bern C, Herrero M, Desjeux P, Cano J, et al. Leishmaniasis worldwide and global estimates of its incidence. PloS one. 2012;7(5):e35671. pmid:22693548
  2. 2. PAHO/WHO. Leishmaniasis: Epidemiological Report in the Americas: Washington: Pan American Health Organization. 2017; www.paho.org/leishmaniasis
  3. 3. Salomón O, Sinagra A, Nevot M, Barberian G, Paulin P, Estevez J, et al. First visceral leishmaniasis focus in Argentina. Memorias do Instituto Oswaldo Cruz. 2008;103(1):109–11. pmid:18368242
  4. 4. Ministerio de salud de la Nación Argentina. Enfermedades Infecciosas, leishmaniasis visceral. Guía para el equipo de salud Nro 5. 2010. p. 43
  5. 5. Gould IT, Perner MS, Santini MS, Saavedra SB, Bezzi G, Maglianese MI, et al. Visceral leishmaniasis in Argentina. Cases notification and distribution of vectors (2006–2012). Medicina. 2013;73(2):104–10. pmid:23570757
  6. 6. Salomón OD, Sosa Estani S, Rossi GC, Spinelli GR. Lutzomyia longipalpis and Leishmaniasis visceral in Argentina. Medicina. 2001;61(2):174–8. pmid:11374140
  7. 7. Salomón OD, Orellano PW. Lutzomyia longipalpis in Clorinda, Formosa province, an area of potential visceral leishmaniasis transmission in Argentina. Memorias do Instituto Oswaldo Cruz. 2005;100(5):475–6.
  8. 8. Salomón OD, Ramos LK, Quintana MG, Acardi SA, Santini MS, Schneider A. Distribution of vectors of visceral leishmaniasis in the Province of Corrientes, 2008. Medicina. 2009;69(6):625–30. pmid:20053601
  9. 9. Salomón OD, Basmajdian Y, Fernandez MS, Santini MS. Lutzomyia longipalpis in Uruguay: the first report and the potential of visceral leishmaniasis transmission. Memorias do Instituto Oswaldo Cruz. 2011;106(3):381–2. pmid:21655832
  10. 10. Bravo AG, Quintana MG, Abril M, Salomon OD. The first record of Lutzomyia longipalpis in the Argentine northwest. Memorias do Instituto Oswaldo Cruz. 2013;108(8):1071–3. pmid:24402160
  11. 11. Young DG, Duran MA. Guide to the Identification and geographic distribution of Lutzomyia sand flies in Mexico, the West Indies, Central and South America (Diptera: Psychodidae). Gainesville, Florida American Entomological Institute; 1994.
  12. 12. Peterson AT, Campbell LP, Moo-Llanes DA, Travi B, Gonzalez C, Ferro MC, et al. Influences of climate change on the potential distribution of Lutzomyia longipalpis sensu lato (Psychodidae: Phlebotominae). International Journal for Parasitology. 2017;47(10–11):667–74. pmid:28668326
  13. 13. Moo-Llanes D, Pech-May A, Ibarra-Cerdena CN, Rebollar-Tellez EA, Ramsey J. Inferring distributional shifts from Pleistocene to future scenarios of epidemiologically important North and Central American sand flies (Diptera: Psychodidae) Medical and Veterinary Entomology. 2018;in press.
  14. 14. González C, Cabrera OL, Munstermann LE, Ferro C. Distribución de los vectores de Leishmania infantum (Kinetoplastida: Trypanosomatidae) en Colombia. Biomedica. 2006;26:64–72.
  15. 15. Ward R.D., Phillips A., Burnet B, Marcondes C. The Lutzomyia longipalpis complex reproduction and distribution. In: Service, M.W. (Ed.), Biosystematics of Haematophagous Insects. Systematics Association, Special. 1988;37:257–69.
  16. 16. Soto SI, Lehmann T, Rowton ED, Velez BI, Porter CH. Speciation and population structure in the morphospecies Lutzomyia longipalpis (Lutz & Neiva) as derived from the mitochondrial ND4 gene. Molecular Phylogenetics and Evolution. 2001;18(1):84–93. pmid:11161745
  17. 17. Arrivillaga JC, Feliciangeli MD. Lutzomyia pseudolongipalpis: the first new species within the longipalpis (Diptera: Psychodidae: Phlebotominae) complex from La Rinconada, Curarigua, Lara State, Venezuela. Journal of Medical Entomology. 2001;38(6):783–90. pmid:11761375
  18. 18. Arrivillaga JC, Norris DE, Feliciangeli MD, Lanzaro GC. Phylogeography of the neotropical sand fly Lutzomyia longipalpis inferred from mitochondrial DNA sequences. Infection, Genetics and Evolution. 2002;2(2):83–95. pmid:12797984
  19. 19. Arrivillaga J, Mutebi JP, Pinango H, Norris D, Alexander B, Feliciangeli MD, et al. The taxonomic status of genetically divergent populations of Lutzomyia longipalpis (Diptera: Psychodidae) based on the distribution of mitochondrial and isozyme variation. Journal of Medical Entomology. 2003;40(5):615–27. pmid:14596274
  20. 20. Coutinho-Abreu IV, Sonoda IV, Fonseca JA, Melo MA, Balbino VQ, Ramalho-Ortigao M. Lutzomyia longipalpis s.l. in Brazil and the impact of the Sao Francisco River in the speciation of this sand fly vector. Parasites & Vectors. 2008;1(1):16.
  21. 21. Mangabeira O. Sobre a sistemática e biologia dos flebótomos do Ceará. Revista Brasileira De Malariologia E Doencas Tropicais. 1969;21:3–26.
  22. 22. Ward RD, Ribeiro AL, Ready PD, Murtagh A. Reproductive isolation between different forms of Lutzomyia longipalpis (Lutz & Neiva), (Diptera: Psychodidae), the vector of Leishmania donovani chagasi Cunha & Chagas and its significance to Kala-azar distribution on South America. Memorias do Instituto Oswaldo Cruz. 1983;78:269–80.
  23. 23. Lanzaro GC, Ostrovska K, Herrero MV, Lawyer PG, Warburg A. Lutzomyia longipalpis is a species complex: genetic divergence and interspecific hybrid sterility among three populations. The American Journal of Tropical Medicine and Hygiene. 1993;48(6):839–47. pmid:8333579
  24. 24. Dujardin JP, Torrez EM, Le Pont F, Hervas D, Sossa D. Isozymic and metric variation in the Lutzomyia longipalpis complex. Medical and Veterinary Entomology. 1997;11(4):394–400. pmid:9430121
  25. 25. Lanzaro GC, Alexander B, Mutebi JP, Montoya-Lerma J, Warburg A. Genetic variation among natural and laboratory colony populations of Lutzomyia longipalpis (Lutz & Neiva, 1912)(Diptera: Psychodidae) from Colombia. Memorias do Instituto Oswaldo Cruz. 1998;93(1):65–9. pmid:9698845
  26. 26. Lampo M, Torgerson D, Marquez LM, Rinaldi M, Garcia CZ, Arab A. Occurrence of sibling species of Lutzomyia longipalpis (Diptera: Psychodidae) in Venezuela: first evidence from reproductively isolated sympatric populations. The American Journal of Tropical Medicine and Hygiene. 1999;61(6):1004–9. pmid:10674686
  27. 27. Hamilton JG, Maingon RD, Alexander B, Ward RD, Brazil RP. Analysis of the sex pheromone extract of individual male Lutzomyia longipalpis sandflies from six regions in Brazil. Medical and Veterinary Entomology. 2005;19(4):480–8. pmid:16336313
  28. 28. Watts PC, Hamilton JG, Ward RD, Noyes HA, Souza NA, Kemp SJ, et al. Male sex pheromones and the phylogeographic structure of the Lutzomyia longipalpis species complex (Diptera: Psychodidae) from Brazil and Venezuela. The American Journal of Tropical Medicine and Hygiene. 2005;73(4):734–43. pmid:16222018
  29. 29. Araki AS, Vigoder FM, Bauzer LG, Ferreira GE, Souza NA, Araujo IB, et al. Molecular and behavioral differentiation among Brazilian populations of Lutzomyia longipalpis (Diptera: Psychodidae: Phlebotominae). PLoS Neglected Tropical Diseases. 2009;3(1):e365. pmid:19172187
  30. 30. Lanzaro GC, Lopes AH, Ribeiro JM, Shoemaker CB, Warburg A, Soares M, et al. Variation in the salivary peptide, maxadilan, from species in the Lutzomyia longipalpis complex. Insect Molecular Biology. 1999;8(2):267–75. pmid:10380110
  31. 31. Yin H, Norris DE, Lanzaro GC. Sibling species in the Llutzomyia longipalpis complex differ in levels of mRNA expression for the salivary peptide, maxadilan. Insect Molecular Biology. 2000;9(3):309–14. pmid:10886415
  32. 32. Lins RM, Souza NA, Peixoto AA. Genetic divergence between two sympatric species of the Lutzomyia longipalpis complex in the paralytic gene, a locus associated with insecticide resistance and lovesong production. Memorias do Instituto Oswaldo Cruz. 2008;103(7):736–40. pmid:19057828
  33. 33. Salomón OD, Araki AS, Hamilton JG, Acardi SA, Peixoto AA. Sex pheromone and period gene characterization of Lutzomyia longipalpis sensu lato (Lutz & Neiva) (Diptera: Psychodidae) from Posadas, Argentina. Memorias do Instituto Oswaldo Cruz. 2010;105(7):928–30. pmid:21120366
  34. 34. Araki AS, Ferreira GE, Mazzoni CJ, Souza NA, Machado RC, Bruno RV, et al. Multilocus analysis of divergence and introgression in sympatric and allopatric sibling species of the Lutzomyia longipalpis complex in Brazil. PLoS Neglected Tropical Diseases. 2013;7(10):e2495. pmid:24147172
  35. 35. Avise JC, Arnold J, Ball RM, Bermingham E, Lamb T, Neigel JE, et al. Intraspecific phylogeography: the mitochondrial DNA bridge between population genetics and systematics. Annual Review of Ecology and Systematics. 1987;18:489–522.
  36. 36. Esseghir S, Ready PD, Killick-Kendrick R, Ben-Ismail R. Mitochondrial haplotypes and phylogeography of Phlebotomus vectors of Leishmania major. Insect Molecular Biology. 1997;6(3):211–25. pmid:9272439
  37. 37. Torgerson DG, Lampo M, Velazquez Y, Woo PT. Genetic relationships among some species groups within the genus Lutzomyia (Diptera: Psychodidae). The American Journal of Tropical Medicine and Hygiene. 2003;69(5):484–93. pmid:14695085
  38. 38. Depaquit J, Lienard E, Verzeaux-Griffon A, Ferte H, Bounamous A, Gantier JC, et al. Molecular homogeneity in diverse geographical populations of Phlebotomus papatasi (Diptera, Psychodidae) inferred from ND4 mtDNA and ITS2 rDNA Epidemiological consequences. Infection, Genetics and Evolution. 2008;8(2):159–70. Epub 2008/02/05. pmid:18243814
  39. 39. Flanley CM, Ramalho-Ortigao M, Coutinho-Abreu IV, Mukbel R, Hanafi HA, El-Hossary SS, et al. Population genetics analysis of Phlebotomus papatasi sand flies from Egypt and Jordan based on mitochondrial cytochrome b haplotypes. Parasites & Vectors. 2018;11(1):214. Epub 2018/03/29.
  40. 40. Hodgkinson VH, Birungi J, Haghpanah M, Joshi S, Munstermann LE. Rapid identification of mitochondrial cytochrome B haplotypes by single strand conformation polymorphism in Lutzomyia longipalpis (Diptera: Psychodidae) populations. Journal of Medical Entomology. 2002;39(4):689–94. pmid:12144306
  41. 41. Hodgkinson VH, Birungi J, Quintana M, Dietze R, Munstermann LE. Mitochondrial cytochrome b variation in populations of the visceral leishmaniasis vector Lutzomyia longipalpis across eastern Brazil. The American Journal of Tropical Medicine and Hygiene. 2003;69(4):386–92. pmid:14640498
  42. 42. Sonoda IV. Variabilidade genética de populações naturais de Lutzomyia longipalpis (Diptera: Psychodidae) de Pernambuco [Tese de mestrado em Genética]. Recife: Universidade Federal de Pernambuco; 2005. p. 75.
  43. 43. Pech-May A, Marina CF, Vazquez-Dominguez E, Berzunza-Cruz M, Rebollar-Tellez EA, Narvaez-Zapata JA, et al. Genetic structure and divergence in populations of Lutzomyia cruciata, a phlebotomine sand fly (Diptera: Psychodidae) vector of Leishmania mexicana in southeastern Mexico. Infection, Genetics and Evolution. 2013;16:254–62. pmid:23416432
  44. 44. Scarpassa VM, Figueiredo Ada S, Alencar RB. Genetic diversity and population structure in the Leishmania guyanensis vector Lutzomyia anduzei (Diptera, Psychodidae) from the Brazilian Amazon. Infection, Genetics and Evolution. 2015;31:312–20. pmid:25701124
  45. 45. Pasos-Pinto P, Sánchez-García L, Sánchez-Montes S, Rebollar-Téllez EA, Pech-May A, Becker I. Genetic Diversity and Prevalence of Leishmania mexicana in Bichromomyia olmeca olmeca in an Endemic Area of Mexico. Southwestern Entomologist. 2017;42:983–94.
  46. 46. Franco FA, Morillas-Marquez F, Baron SD, Morales-Yuste M, Galvez R, Diaz V, et al. Genetic structure of Phlebotomus (Larroussius) ariasi populations, the vector of Leishmania infantum in the western Mediterranean: epidemiological implications. International Journal for Parasitology. 2010;40(11):1335–46. Epub 2010/05/11. pmid:20451525
  47. 47. Depaquit J, Randrianambinintsoa FJ, Jaouadi K, Payard J, Bounamous A, Augot D, et al. Molecular and morphological systematics of the sandfly Sergentomyia (Sintonius) clydei Sinton, 1928 and questions about its record in the Seychelles. Infection, Genetics and Evolution. 2014;21:41–53. Epub 2013/11/02. pmid:24177594
  48. 48. Ready PD, Day J, De Souza AA, Rangel EF, Davies CR. Mitochondrial DNA characterization of populations of Lutzomyia whitmani (Diptera: Psychodidae) incriminated in the peridomestic and sylvatic transmission of Leishmania species in Brazil. Bulletin of Entomological Research. 1997;87:187–95.
  49. 49. Ready PD, de Souza AA, Rebelo JM, Day JC, Silveira FT, Campbell-Lendrum D, et al. Phylogenetic species and domesticity of Lutzomyia whitmani at the southeast boundary of Amazonian Brazil. Transactions of the Royal Society of Tropical Medicine and Hygiene. 1998;92(2):159–60. pmid:9764319
  50. 50. Hamarsheh O, Presber W, Abdeen Z, Sawalha S, Al-Lahem A, Schonian G. Genetic structure of Mediterranean populations of the sandfly Phlebotomus papatasi by mitochondrial cytochrome b haplotype analysis. Medical and Veterinary Entomology. 2007;21(3):270–7. Epub 2007/09/28. pmid:17897368
  51. 51. Valderrama A, Tavares MG, Dilermando Andrade Filho J. Phylogeography of the Lutzomyia gomezi (Diptera: Phlebotominae) on the Panama Isthmus. Parasites & Vectors. 2014;7:9.
  52. 52. Salomón OD, Feliciangeli MD, Quintana MG, Afonso MM, Rangel EF. Lutzomyia longipalpis urbanisation and control. Memorias do Instituto Oswaldo Cruz. 2015;110(7):831–46. pmid:26517497
  53. 53. Brazil RP, Caballero NN, Hamilton JG. Identification of the sex pheromone of Lutzomyia longipalpis (Lutz & Neiva, 1912) (Diptera: Psychodidae) from Asuncion, Paraguay. Parasites & Vectors. 2009;2(1):51.
  54. 54. Hamilton JG, Dawson GW, Pickett JA. 9-Methylgermacrene-B; proposed structure for novel homosesquiterpene from the sex pheromone glands of Lutzomyia longipalpis (Diptera: Psychodidae) from Lapinha, Brazil. Journal of Chemical Ecology. 1996;22(8):1477–91. pmid:24226250
  55. 55. Lanzaro GC, Warburg A. Genetic variability in phlebotomine sand flies: possible implications for leishmaniasis epidemiology. Parasitology Today. 1995;11:151–4.
  56. 56. Bauzer LG, Souza NA, Maingon RD, Peixoto AA. Lutzomyia longipalpis in Brazil: a complex or a single species? A mini-review. Memorias do Instituto Oswaldo Cruz. 2007;102(1):1–12. pmid:17293992
  57. 57. Souza NA, Brazil RP, Araki AS. The current status of the Lutzomyia longipalpis (Diptera: Psychodidae: Phlebotominae) species complex. Memorias do Instituto Oswaldo Cruz. 2017;112(3):161–74. pmid:28225906
  58. 58. Burkart R, Bárbaro N.O., Sánchez R.O., D.A. G. Ecorregiones de la Argentina 1999. p. 42.
  59. 59. Fernandez MS, Martinez MF, Perez AA, Santini MS, Gould IT, Salomon OD. Performance of light-emitting diode traps for collecting sand flies in entomological surveys in Argentina. Journal of Vector Ecology. 2015;40(2):373–8. pmid:26611973
  60. 60. Galati EAB. Classificação de Phlebotominae. In Rangel EF, Lainson R. Flebotomíneos do Brasil. In: FIOCRUZ, editor. 2003. p. 53–175.
  61. 61. QGIS Development Team. QGIS 2.6.1 Brighton. Geographic Information System. Open Source Geospatial Foundation. 2015; http://www.qgis.org/it/site/.
  62. 62. Kumar S, Stecher G, Tamura K. MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets. Molecular Biology and Evolution. 2016;33(7):1870–4. pmid:27004904
  63. 63. Librado P, Rozas J. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009;25(11):1451–2. pmid:19346325
  64. 64. Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989;123(3):585–95. pmid:2513255
  65. 65. Fu YX. New statistical tests of neutrality for DNA samples from a population. Genetics. 1996;143(1):557–70. pmid:8722804
  66. 66. Excoffier L, Lischer HE. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources. 2010;10(3):564–7. pmid:21565059
  67. 67. Harpending HC. Signature of ancient population growth in a low-resolution mitochondrial DNA mismatch distribution. Human Biology. 1994;66(4):591–600. pmid:8088750
  68. 68. Holm S. A simple sequential rejective method procedure. Scandinavian Journal of Statistics 1979;6:65–70
  69. 69. Gaetano J. Holm-Bonferroni sequential correction: An Excel calculator (1.3) [Microsoft Excel workbook]. Retrieved from: https://www.researchgate.net/publication/322568540_Holm-Bonferroni_sequential_correction_An_Excel_calculator_13. 2018.
  70. 70. Mantel N. The detection of disease clustering and a generalized regression approach. Cancer Research. 1967;27(2):209–20. pmid:6018555
  71. 71. Guillot G, Estoup A, Mortier F, Cosson JF. A spatial statistical model for landscape genetics. Genetics. 2005;170(3):1261–80. pmid:15520263
  72. 72. Guillot G, Mortier F, Estoup A. Geneland: a computer package for landscape genetics. Molecular Ecology Notes. 2005;5:712–5.
  73. 73. Guillot G, Santos F, Estoup A. Analysing georeferenced population genetics data with Geneland: a new algorithm to deal with null alleles and a friendly graphical user interface. Bioinformatics. 2008;24(11):1406–7. pmid:18413327
  74. 74. R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2016.
  75. 75. Bandelt HJ, Forster P, Rohl A. Median-joining networks for inferring intraspecific phylogenies. Molecular Biology and Evolution. 1999;16(1):37–48. pmid:10331250
  76. 76. Darriba D, Taboada GL, Doallo R, Posada D. jModelTest 2: more models, new heuristics and parallel computing. Nature Methods. 2012;9(8):772.
  77. 77. Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Hohna S, et al. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Systematic Biology. 2012;61(3):539–42. pmid:22357727
  78. 78. Drummond AJ, Suchard MA, Xie D, Rambaut A. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Molecular Biology and Evolution. 2012;29(8):1969–73. pmid:22367748
  79. 79. Ho SY, Phillips MJ, Cooper A, Drummond AJ. Time dependency of molecular rate estimates and systematic overestimation of recent divergence times. Molecular Biology and Evolution. 2005;22(7):1561–8. pmid:15814826
  80. 80. Jukes TH, Cantor CR. Evolution of protein molecules. In: Munro H.N. (Ed.), Mammalian Protein Metabolism. Academic Press, New York1969.
  81. 81. Nei M. Molecular Evolutionary Genetics. New York: Columbia Univ Press; 1987. p. 512.
  82. 82. Mirabello L, Conn JE. Molecular population genetics of the malaria vector Anopheles darlingi in Central and South America. Heredity. 2006;96(4):311–21. pmid:16508661
  83. 83. Fu YX. Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics. 1997;147(2):915–25. pmid:9335623
  84. 84. Rogers AR, Harpending H. Population growth makes waves in the distribution of pairwise genetic differences. Molecular Biology and Evolution. 1992;9(3):552–69. pmid:1316531
  85. 85. Lowe A, Harris S, Ashton P. Ecological Genetics: Designs, Analysis, and Application. USA: Blackwell publishing 2004. p. 320.
  86. 86. Morrison AC, Ferro C, Morales A, Tesh RB, Wilson ML. Dispersal of the sand fly Lutzomyia longipalpis (Diptera: Psychodidae) at an endemic focus of visceral leishmaniasis in Colombia. Journal of Medical Entomology. 1993;30(2):427–35. pmid:8459421
  87. 87. Montes de Oca-Aguilar AC, Moo-Llanes DA, Rebollar-Téllez EA. Adult sand fly species form diurnal resting sites on the Peninsula of Yucatan, Mexico. Southwestern Entomologist. 2013;38:241–50.
  88. 88. Souza GD, Santos E, Andrade Filho JD. The first report of the main vector of visceral leishmaniasis in America, Lutzomyia longipalpis (Lutz & Neiva) (Diptera: Psychodidae: Phlebotominae), in the state of Rio Grande do Sul, Brazil. Memorias do Instituto Oswaldo Cruz. 2009;104(8):1181–2. pmid:20140381
  89. 89. Salomón OD, Mastrangelo AV, Santini MS, Liotta DJ, Yadon ZE. Retrospective eco-epidemiology as a tool for the surveillance of leishmaniasis in Misiones, Argentina, 1920–2014. Revista panamericana de salud publica. 2016;40(1):29–39. pmid:27706386
  90. 90. de Souza Freitas MT, Rios-Velasquez CM, Costa CR Jr., Figueiredo CA Jr., Aragao NC, da Silva LG, et al. Phenotypic and genotypic variations among three allopatric populations of Lutzomyia umbratilis, main vector of Leishmania guyanensis. Parasites & Vectors. 2015;8:448.
  91. 91. Hamarsheh O, Presber W, Yaghoobi-Ershadi MR, Amro A, Al-Jawabreh A, Sawalha S, et al. Population structure and geographical subdivision of the Leishmania major vector Phlebotomus papatasi as revealed by microsatellite variation. Medical and Veterinary Entomology. 2009;23(1):69–77. Epub 2009/02/26. pmid:19239616
  92. 92. Bauzer LG, Gesto JS, Souza NA, Ward RD, Hamilton JG, Kyriacou CP, et al. Molecular divergence in the period gene between two putative sympatric species of the Lutzomyia longipalpis complex. Molecular Biology and Evolution. 2002;19(9):1624–7. pmid:12200489
  93. 93. Bauzer LG, Souza NA, Ward RD, Kyriacou CP, Peixoto AA. The period gene and genetic differentiation between three Brazilian populations of Lutzomyia longipalpis. Insect Molecular Biology. 2002;11(4):315–23. pmid:12144696
  94. 94. Filho JD, Brazil RP. Relationships of new world phlebotomine sand flies (Diptera: Psychodidae) based on fossil evidence. Memorias do Instituto Oswaldo Cruz. 2003;98 Suppl 1:145–9.
  95. 95. Young DG. A review of the bloodsucking Psychodide flies of Colombia (Diptera: Phlebotominae and Sycoracinae). Gainesville, Florida,: Institute of Food and Agricultural Sciences, Agricultural Experiment Stations; 1979.
  96. 96. Conn JE, Mirabello L. The biogeography and population genetics of neotropical vector species. Heredity. 2007;99(3):245–56. pmid:17534382