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    Figure 1.

    Collection sites for Triatoma brasiliensis specimens in the four localities (A, B, C, and S) in the state of Paraíba (PB), Brazil. Except for S (the sylvatic spot), each locality was divided into two sub-localities (1 and 2).

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    Figure 2.

    Maximum parsimony network showing the relationship among the 29 Triatoma brasiliensis haplotypes based on the cytochrome b mitochondrial gene. The left network (a) is coded in localities and the right one (b) in ecotopes. For an explanation of the localities, see Figure 1. The ecotopes are intradomiciliary (I), peridomiciliary (P), ruderal (R), and sylvatic (S).

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    Figure 3.

    Neighbor-joining tree derived from linear pairwise FST distances of Triatoma brasiliensis populations. The collection spots are shown in Figure 1. The suffix IP refers to samples collected for well reestablished intradomiciliary plus peridomiciliary infestations, and R to the ruderal ecotope. The code S refers to the sylvatic population. Suffix (i) indicates the samples collected within a short period (0.5 to 1.2 years) after insecticide spraying for A1IPi and simultaneous collections for ruderal (A1Ri). The values used to build the tree are shown in Table 3.

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    Figure 4.

    Each spot represents the genetic differentiation of one unique pair of Triatoma brasiliensis populations correlated with (Euclidean) distance. The left scale (gray diamonds) indicates the FST/(1−FST) values between populations from each locality (A, B, C, and S; see Figure 1). The same domiciliary sampling was used for the FST /(1−FST) values indicated on the right axis (black diamonds); ruderal samples were excluded from this analysis. Geographic distances were not log-transformed for circles, representing geographic and genetic correlation within localities.

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Inferring from the Cyt B Gene the Triatoma brasiliensis Neiva, 1911 (Hemiptera: Reduviidae: Triatominae) Genetic Structure and Domiciliary Infestation in the State of Paraíba, Brazil

Carlos Eduardo AlmeidaInstituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, RJ, Brazil; Universidade Federal do Rio Grande do Sul, Departamento de Genética, Porto Alegre, RS, Brazil; Institut de Recherche pour le Développement, UR072 en la Pontificia Universidad Católica del Ecuador, Laboratorio de Entomología, Quito, Ecuador; Division of Parasitic Diseases, Centers for Disease Control and Prevention, NCID, Chamblee, Georgia

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Raquel S. PachecoInstituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, RJ, Brazil; Universidade Federal do Rio Grande do Sul, Departamento de Genética, Porto Alegre, RS, Brazil; Institut de Recherche pour le Développement, UR072 en la Pontificia Universidad Católica del Ecuador, Laboratorio de Entomología, Quito, Ecuador; Division of Parasitic Diseases, Centers for Disease Control and Prevention, NCID, Chamblee, Georgia

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Karen HaagInstituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, RJ, Brazil; Universidade Federal do Rio Grande do Sul, Departamento de Genética, Porto Alegre, RS, Brazil; Institut de Recherche pour le Développement, UR072 en la Pontificia Universidad Católica del Ecuador, Laboratorio de Entomología, Quito, Ecuador; Division of Parasitic Diseases, Centers for Disease Control and Prevention, NCID, Chamblee, Georgia

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Stéphane DupasInstituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, RJ, Brazil; Universidade Federal do Rio Grande do Sul, Departamento de Genética, Porto Alegre, RS, Brazil; Institut de Recherche pour le Développement, UR072 en la Pontificia Universidad Católica del Ecuador, Laboratorio de Entomología, Quito, Ecuador; Division of Parasitic Diseases, Centers for Disease Control and Prevention, NCID, Chamblee, Georgia

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Ellen M. DotsonInstituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, RJ, Brazil; Universidade Federal do Rio Grande do Sul, Departamento de Genética, Porto Alegre, RS, Brazil; Institut de Recherche pour le Développement, UR072 en la Pontificia Universidad Católica del Ecuador, Laboratorio de Entomología, Quito, Ecuador; Division of Parasitic Diseases, Centers for Disease Control and Prevention, NCID, Chamblee, Georgia

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Jane CostaInstituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, RJ, Brazil; Universidade Federal do Rio Grande do Sul, Departamento de Genética, Porto Alegre, RS, Brazil; Institut de Recherche pour le Développement, UR072 en la Pontificia Universidad Católica del Ecuador, Laboratorio de Entomología, Quito, Ecuador; Division of Parasitic Diseases, Centers for Disease Control and Prevention, NCID, Chamblee, Georgia

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The Triatoma brasiliensis genetic structure was analyzed using the Cyt B gene in different geographic locations and ecotopes after a short and long period after insecticide treatment. Four different localities (16–40 km apart) in the state of Paraíba, Brazil, were sampled. Analysis of molecular variance (AMOVA) showed that grouping populations according to the geographic location or ecotope resulted in a higher variance among populations within groups (ΦSC ranging from 0.15 to 0.17) than among groups (ΦCT ranging from 0.04 to 0.07). The percentage of variation was reduced among populations within groups and increased among groups (ΦSC = 0.08, ΦCT = 0.16) by grouping 1) the domiciliary populations from each village and 2) all wild populations. These data indicated that T. brasiliensis is genetically structured both ecologically and at a smaller geographic scale for domiciliary populations. Re-infestations after insecticide treatment were composed of distinct populations, pointing to variable population sources for domiciliary infestations.

INTRODUCTION

Chagas disease is caused by a flagellate protozoan parasite, Trypanosoma cruzi, transmitted to humans mainly by bloodsucking bugs, the triatomines. Approximately 25% of the inhabitants of Latin America are at risk of contracting T. cruzi. Until now, no vaccine or drug has been developed to eliminate the infection by this parasite in the chronic phase of the disease. Most of the efforts against Chagas disease are focused on the interruption of its natural transmission by combating domiciliated vectors using pyrethroid insecticides, because vector transmission is still considered the main way to get infected in Brazil.15

The Brazilian National Health Foundation (Funasa) has used intense insecticide spraying since the 1990s. The most important achievement reached by this program has been the interruption of T. cruzi transmission by Triatoma infestans. However, after the successful vector control program for Tri. infestans, another vector, Triatoma brasiliensis, became the main vectorial threat in semi-arid areas of northeastern Brazil.6 This latter species exhibits remarkable chromatic variations observed across its geographic distribution. Multidisciplinary research based on morphology,7 biology,8,9 ecology,10 isoenzymes,11 and mitochondrial DNA variation12 showed that the four morphotypes of Tri. brasiliensis indeed constitute the Tri. brasiliensis species complex. A taxonomic review of this complex is in preparation, and the species of the complex are being described.13,14 The morphotype Tri. brasiliensis s.s. was considered the main concern in terms of Chagas disease transmission because this morphotype is the most widespread and has the highest rates of domiciliary captures and of natural infection by T. cruzi among the four members of the complex.15

The state of Paraíba, Brazil, was used as a model to estimate the time taken by Tri. brasiliensis to re-infest houses after insecticide treatment and the effect of house improvements (basically by replacing houses made of mud by houses built of concrete) on this process.16,17 These studies showed that the temporal pattern of triatomine re-infestation after insecticide spraying is highly heterogeneous. Usually, the reinfestation varies from 6 months to 2 years, probably depending on eco-geographic factors. It was suggested that genetic factors also contribute to such variation in re-infestation time. The difficulty of controlling Tri. brasiliensis has been attributed to its capacity to occupy the intradomiciliary, peridomiciliary, and wild environments. Hence, it has been stressed16,17 that accurate determination of the foci responsible for re-infestation is a crucial challenge to improving control measures implemented by Brazilian health authorities.

Dispersal within and among spatially or ecologically structured groups of populations can be compared through several kinds of neutral genetic markers, and elements of the landscape that limit dispersal can be identified using population genetics inferences. For triatomines, molecular and morphometric tools have both pointed out populations that invade and colonize domiciles and also helped to elucidate the dynamics between insects from domiciliary and sylvatic environments.1824

One of the main questions of population genetic studies on triatomines is whether ecotopic populations distant from each other would exchange migrants more often than physically close ones differing by ecotope, as has been proposed by some authors.18,19,23,24 The genetic structure of Tri. brasiliensis had been studied using cytochrome b mitochondrial gene (Cyt B) variation, an approach that clearly detected subpopulations separated by long distances (~500 km apart).12 However, the study referred to had not been designed to clarify important aspects regarding population structure over smaller distances, such as the gene flow between ecotopes.

This study was conducted in four sites (~16–40 km apart) in the state of Paraíba, Brazil, where only the morphotype Tri. brasiliensis s.s. is found, herein referred to as just Tri. brasiliensis. The study’s area is known to have high Tri. brasiliensis re-infestation pressure after insecticide treatment.16,17 Mitochondrial DNA variation and ecologic observations were used to address questions regarding to the population genetic structure and gene flow between sylvatic and domiciliary populations of Tri. brasiliensis. In addition, we tried to recognize the origin of populations that colonize domiciles after control activities.

MATERIALS AND METHODS

Captures.

The collection locations were between the coordinates 06°51′29.23″–07° 00′25.31″ W and 38°22′59.58″–38°00′49.08″ S, an area that is made up of the municipality of São José da Lagoa Tapada and bordering cities. All sampled spots were within the biogeographic zone known as Caatinga, a mosaic of xerophytic, deciduous, semi-arid thorn scrubs, and forest.25 Geographic locations and distances were obtained using GPS TrackMaker.26

Captures were performed from 2001 to 2004 with attention to the records of the Program to Control Chagas Disease in the State of Paraíba, northeastern Brazil. The process of reinfestation was estimated to begin ~6 months after insecticide treatment. This observation was based on a large study monitoring the process of re-infestation in the entire state of Paraíba, Brazil.16,17 Based on these studies, we also selected the location with one of the highest recorded pressures for re-infestation after insecticide spraying.

We herein define the population collected from 6 months to 1.2 years after domiciliary insecticide spraying as the populations sampled within a “short period” after house spraying. These domiciliary populations were considered to be in the process of infestation re-establishment.16,17 Furthermore, we sampled the same geographic area within 2.9–3.5 years after the insecticide treatment, at which time we also sampled domiciles that had not been treated during this period. We considered these insects as populations collected after a “long period” after insecticide spraying (or populations of well reestablished infestations).

Uninhabited (or wild) areas were sampled simultaneously with domiciliary collection. Although uninhabited environments are not treated with insecticide, these collections were also referred to as collected “within a short/long period after domiciliary insecticide spraying,” to link the term to the time of collection.

Spatial versus ecotopic and temporal genetic structures were analyzed independently. Because larger sample sizes were obtained after a long period had elapsed after insecticide spraying, only these samples were used to assess the general spatial versus ecotopic genetic structure.

Insects.

Samples were labeled by locality and ecotope (intradomiciliary, peridomiciliary, ruderal, and sylvatic). Intradomiciliary ecotopes (I) are the indoor space of domiciliary units or home-like environment where humans live and/or work. Triatomines were generally found in mud wall crevices or under beds. The peridomiciliary ecotopes (P) were considered within a radius of 50 m from the domiciles, where domesticated animals slept or were raised. In peridomiciles, most of the triatomines were captured in chicken coops and in goat and pig corrals.

We considered the beginning of ruderal ecotopes (R) to be 50 m past the peridomicile radius, usually ranging from 1 to 2 km from houses. We took one R unit per village sampled. In this environment, the native vegetation was substituted by new pastures or short-lived cropland. Local people, so-called “sertanejos,” hunt to eat and to protect the crop and domesticated animals. Therefore, domesticated animals (e.g., goats, horses, and cows) were easily observed in this environment, whereas wild homeothermic animals were seldom seen among rock piles where triatomines were collected. The sylvatic ecotope (S) is also an uninhabited area, starting at least 200 m from any house. This ecotope differs from the ruderal environment mainly because the sylvatic ecotope has not been transformed into either pasture or cropland. Wild animals were most often seen where triatomines were collected. A rodent closely related to the guinea pig (the rock cave or mocó, Kerodon rupestris) was the most representative homeothermic vertebrate seen among the rocks.27

Domiciliary captures were performed during the day, and dislodging (0.2% neopynamin) was used when needed. During the same period and with the same staff, we performed nocturnal and manual captures in uninhabited environments (R and S), where triatomines were captured in similar shelters (rock piles).

Only one sylvatic area was sampled, and except for this single sylvatic area, each locality was split into two sub-localities (or villages), referred to as 1 and 2 (Figure 1). We thus organized the samples according to the ecotope and sub-locality to define the sites. The sites were labeled by three characters: the first represents the locality label (A, B, or C), the second, the sub-locality (1 or 2), and the suffix, the ecotope (I, P, or R; Table 1). We used the suffix I when we merged intradomiciliary and peridomiciliary samples, also referred to as just domiciliary.

All immature triatomines collected were taken to the laboratory to be maintained under controlled temperature and humidity conditions (27 ± 2°C and 60 ± 3% RH) and fed on mice once a week until imaginal molt. The adult specimens were identified according to their taxonomic characteristics.13,14,28,29

DNA extraction and amplification.

Insects were stored at −20°C until processed. Each sample was quickly frozen in nitrogen liquid to individually grind the insects’ legs in an Eppendorf tube with a clean and sterile crusher. We used the Wizard Genomic Purification Kit (Promega, Madison, WI) for DNA extraction, following the manufacturer’s recommended protocol for animal tissue. Standard polymerase chain reaction (PCR) techniques were used to amplify the gene fragments. A 510-bp region of the Cyt B mitochondrial gene was amplified using primers CYTB7432F, 50-GGACG(AT)GG(AT)ATTTATTATGGATC, and CYTBR, 50-ATTACTCCTCCTAGCTTATTAGGAATTG,12,30,31 by running reactions in an Eppendorf Master Gradient Thermocycler (Brinkman Instruments, Westbury, NY). We used the following cycles: denaturation at 94°C for 5 minutes and then 35 cycles of denaturation at 94°C for 30 seconds, annealing at 47°C for 30 seconds, and extension at 72°C for 1 minute, followed by a 72°C extension for 7 minutes and holding at 4°C indefinitely. Amplified products were visualized on a 1.5% agarose gel stained with ethidium bromide. Purified PCR products were sequenced using a Big-Dye Terminator Cycle Sequencing Ready Reaction Kit (Applied Biosystems, Foster City, CA), according to the manufacturer’s recommended protocol. Both strands were sequenced directly in both directions with amplification primers, using an Applied Biosystem model 3100 automated DNA sequencer. The consensus sequences were edited and assembled using the SEQMAN program32 and aligned using Alignment Clustal available through Mega3.33

Neutrality and demography.

We tested the null hypothesis of neutrality using the Tajima D statistic,34 implemented by the software DNAsp 4.10.4.35 Because panmixy is a key assumption of Tajima D statistics, an initial test included all individuals sampled across the study area. The Tajima D was tested for all samples sorted by ecotope and after that by geographic location, which allowed more robust inferences based on multiple tests at finer scales. We also tested the hypothesis that geographic and ecotopic populations are not panmictic, further implementing neutrality tests on each proposed site individually. Values of the Tajima D are also used to assess evidence for demographic events.34

Genetic structure.

Variation among and within collections was partitioned by a hierarchical analysis of molecular (co)variance (AMOVA)36 using Arlequin version 3.01.37 Significance of the fixation indices was determined using a non-parametric approach.36 FST was calculated among all populations and between all pairs of populations. The significance of departures from zero of Φ statistics and genetic variance components were tested using 1,000 permutations.38 Nesting was imposed in the two ways because it has been hypothesized to limit the gene flow: physical distance and ecotopic barriers. First, we tested the null hypothesis that population genetic structure was not associated with ecotopes by grouping each site according to its geographic location. Second, we grouped sites according to ecotopes. Comparison between proportions of variance explained by each partition provides information on the relative role of geography versus ecology in Tri. brasiliensis population structure.

Localities A, B, and C are outside the probable flight range of triatomines. We tested the isolation by distance (IBD) by regressing pairwise FST on pairwise log-transformed geographic distances among populations and significance was determined by Mantel tests (1,000 permutations) using Arlequin. Additionally, we looked for evidence of IBD using matrices of pairwise linearized FST (FST/[1 − FST])3941 for the correlation by Euclidean distance. We assume the insects could actively fly throughout any two spots between sites within localities, and the same approach was applied to ecotopic populations within localities to detect evidence for ecotopic boundaries.

We constructed a haplotype network using the software TCS 1.2142 based on the statistical parsimony method.43 Reticulations were resolved according to common theoretical predictions about network structure.44,45 To visualize differences between geographic versus ecotopic groups, the network was coded in two ways, each depending on the structure of interest.

Influence of temporal factors and control activities on the genetic structure.

A second level of sampling was designed to study the temporal differences on the genetic structure of Tri. brasiliensis. We considered the population of insects collected within a short period after house spraying (from 0.5 to 1.2 years) “in the process of re-establishment.” The populations collected within 2.9–3.5 years after insecticide treatment (the populations used to make inferences on the overall genetic structure) were considered “well re-established” populations. Previous studies16,17 have shown that this last time frame was sufficient for the re-establishment of domiciliary infestations.

Haplotype diversity was measured for each population, and FST pairwise differences were calculated among all populations and between the pairs of populations collected in both periods after insecticide spraying. Taking into account signals of genetic variation, we nested combinations of groupings for an AMOVA using domiciliary and ruderal populations collected during both periods to access the spatio/ecotopic versus temporal variation on the genetic structure, in regard to vector control activities.

RESULTS

Captures.

Two hundred twenty-six samples collected in three inhabited localities (A, B, and C that were each divided into two, resulting in six sub-localities) and 37 samples from the single sylvatic (S) site (in the south) were available to analyze the general genetic structure. Furthermore, we collected 98 samples in A1 within a short period after insecticide spraying that were used to analyze the influence of temporal factors and control activities on the genetic structure.

Considering the material available to analyze the general genetic structure, we collected insects in the three ecotopes per sub-locality, allowing us to define a total of 18 sites with sample sizes ranging from seven to 18 individual sequences per site (Table 1). The sub-localities had a sample size ranging from 28 (C2) to 45 (B2). The totals analyzed per sub-locality in intradomiciliary and peridomiciliary ecotopes ranged from 9 to 18 and 7 to 16 samples, respectively. Ruderal sites were represented by 11–16 insects. We could not find any other spot exhibiting sylvatic characteristics among the A, B, and C localities (Figure 1). The sylvatic collection might herein correspond to a spatial and/or an ecotopic population.

In both R and S ecotopes, the triatomines captured during nocturnal fieldwork appeared to be searching for food or copulation outside rock piles. Despite the environmental similarity, bugs were easily collected in R sites in all localities, whereas approximately five times more effort (hour per captured bug) was required to obtain the same number of bugs in S as in R.

Thirty-one samples, all from the locality A1, were found in domiciliary ecotopes within a short period after insecticide spraying. On this same occasion and in the same sub-locality, 67 samples were collected in the ruderal environment (Table 1).

DNA sequences.

Twenty-nine haplotypes were identified across the sampling range. Polymorphic sites are shown in Table 2. We identified substitutions at 34 of the 510 nucleotide sites; of these, 32 were transitions, 2 were transversions, and 4 were non-synonymous substitutions. As commonly observed in insect mtDNA, nucleotide frequencies were AT-biased (frequencies of T = 0.31, C = 0.25, A = 0.31, and G = 0.13).

Neutrality and demography.

High average haplotype diversity (Hd) values were recorded in the four localities, ranging from 0.75 (overall B) to 0.93 (overall S). The sylvatic population showed the highest haplotype diversity of all populations at the levels of 1) total sample, 2) total for each locality, 3) ecotopic populations (overall I, P, and R), and 4) sites (Table 1).

Tajima D values for A, B, C, and S localities were −0.40, −0.66, −1.21, and −1.62, respectively. Except for the sylvatic and overall ruderal population (both P = 0.04), no significant deviation from neutrality (all P > 0.10) was identified among the sequences at any level (overall D = −1.28). Except for the B1I site (D = −1.43), high positive D values were associated with intradomiciliary ecotopes (overall D = 1.15). Overall intradomiciliary populations showed the following D values for each locality: A = 0.51, B = 0.01, and C = 1.73. Positive values were notably high for intradomiciliary populations in the sub-localities of B2, C2, and C1 (D = 1.56, 1.53, and 1.46, respectively). High negative D values were observed for ruderal sites ranging from −0.23 to −1.38 in A2R and C1R, respectively (all P > 0.10).

Genetic structure.

To examine the spatial versus ecotopic genetic structure, we used 263 samples exhibiting 29 haplotypes collected a long period after house spraying (Table 1, I–XXIX). The total number of sequences for well reestablished colonies from intradomicile, peridomicile, ruderal, and sylvatic environments were 68, 74, 84, and 37 samples, respectively. The intradomiciliary insects were represented by only eight haplotypes (ranging from I to VIII), being also found in peridomiciliary and ruderal environments. Haplotypes I–XIV were found in domiciliary and ruderal environments, and of these haplotypes, I and V were found in all ecotopes. Twenty-three and 16 haplotypes were identified in the ruderal and sylvatic environments, respectively. The haplotype XV was private for ruderal environment. Most of the private haplotypes in ecotopes were found in the sylvatic environment: three samples of haplotype XXIV and XXVI, two samples of haplotypes XXVII and XXVIII, and the two unique singletons found for haplotypes XXV and XXIX (Table 1).

The haplotype network was relatively superficial, with a maximum of seven mutational steps between haplotypes (Figure 2). We determined the frequency of each haplotype occurrence among localities (Figure 2a), as well as by ecotope (Figure 2b). Haplotype IV was found in all inhabited localities and the most frequent in intradomiciliary and peridomiciliary ecotopes, where this haplotype represented 38% and 25%, respectively, of the total sample collected in those environments (Table 1; Figure 2).

The lowest FST value among overall localities was between A and B (0.02), and the highest one (0.25) was observed between B and S (all P < 0.02). The highest FST values observed among the overall ecotopic populations were 0.29 and 0.20 (for I versus S and P versus S, respectively, both P < 0.0001). The FST values between ecotopic populations I versus P (0.02), P versus R (0.04), and R versus S (0.08) were lower (all P < 0.03).

The FST values between intradomiciliary and peridomiciliary sites indicated a low differentiation (all FST < 0.08, except for C2I versus C2P; FST = 0.2) in the same sub-locality. To improve the robustness of results, we repeated the FST calculations by merging the domiciliary sites (I and P) from each sub-locality. This allowed us to improve the statistical significance to make inferences about different domiciliary, ruderal, and sylvatic population sources for domiciliary colonization.

We constructed a neighbor-joining tree of pairwise FST distances (Figure 3), showing an association between the domiciliary populations from the sub-localities 1 and 2 within the localities A and C, however, without statistical significance (P = 0.9 and 0.36, respectively). We found that domiciliary populations B1IP and B2IP have been significantly differentiated (FST = 0.37, P < 0.0001), but B1IP was significantly related to the ruderal site within the sub-locality (FST = 0.28, P < 0.0001). Domiciliary populations from both B sub-localities were also significantly related to the domiciliary populations from A (all FST < 0.22, P < 0.01).

The only FST values > 0.1 among ruderal sites were observed for C2R with B2R and with C1R (0.17 and 0.11, P = 0.009 and 0.01, respectively). No correlation among ruderal populations could be observed taking into account the physical distances (Figure 3; Table 3).

Despite the low differentiation between domiciliary and ruderal populations within sub-localities (except for B1), no consistent pattern could be traced for this relationship, because domiciliary populations were, in most cases, associated with domiciliary or ruderal populations from other sub-localities (Figure 3).

AMOVA showed that grouping all sites according to geographic location resulted in a higher percentage of variance within localities (14%; ΦSC = 0.15, P < 0.0001) than among them (7%;ΦCT = 0.07, P = 0.02; Table 4). A similar pattern was obtained if we grouped sites by ecotope, regardless of the geographic location (ΦSC = 0.17, P < 0.0001; ΦCT = 0.04, P = 0.07; Table 4).

To test another AMOVA, we considered the indications (FST values) of population differentiation. Domiciliary populations (I and P) from the same sub-localities (or villages) were closely associated, and all populations from the ruderal environment seemed to not be differentiated from each other but did differ from the sylvatic population. We therefore nested the populations, taking into account the synanthropic level and spatial distribution of domiciliary sites as follows: 1) domiciliary (I plus P) sites from each village, 2) all ruderal sites across the sampling area, and 3) the sylvatic population. Grouping the samples in this manner showed that the percentage of variation among sites within groups decreased to 7% (ΦSC = 0.08, P < 0.0001) of total of variation further increased to 15% the magnitude of variation among groups (ΦCT = 0.16, P < 0.0001). The highest percentage of genetic variation was distributed within the sites (77.7%, P < 0.0001). Overall ΦST = was significant (P < 0.0001) and detected as high at 0.22 (Table 4).

Isolation by distance.

FST values > 0.15 might indicate great genetic differentiation.46 Pairwise differences showed a reasonable range of FST values, all statistically significant (ranging from 0.02 to 0.25, P = 0.01 and < 0.0001) for variation among overall sampling for the four geographic localities. Because the genetic structure indicated that ruderal populations are panmictic, we analyzed all samples excluding ruderal sites. At both scales, there were very low relationships between FST and geographic distances. The correlation between genetic and geographic distances within localities was also weak (Figure 4). A Mantel test confirmed that the matrixes had very weak correlation (all r < 33%, P > 0.24).

Influence of temporal factors and control activities on the genetic structure.

Because of the small sampling size for populations from intradomiciliary and peridomiciliary ecotopes within a short period after insecticide spraying (N = 31 samples from A1), we merged all the samples to define the A1IPi population. This approach allowed us to improve the robustness of the results. Ten samples exhibited haplotype III, and 15 and 2 insects represented haplotypes IV and VI, respectively. A total of four insects, one each representing haplotypes I, VII, XI, and XIII, were also collected. In addition, we sampled the ruderal environment (N = 67) in this same geographic location and period and identified 10 different haplotypes (Table 1).

Genetic diversity values for well re-established groups of domiciliary populations from A and C were high (0.67 < Hd < 0.93). Lower values (0.18 < Hd < 0.69) were obtained for well re-established groups from B and for the population collected within a short period after insecticide spraying (A1IPi). The FST values of A1IPi insects with well re-established groups from C (domiciliary populations) with all ruderal and sylvatic populations were significantly high (FST ranging from 0.15 to 0.35, all P < 0.0001). This A1IPi population exhibited the lowest differentiation observed for the well re-established B1IP population (FST = 0.18, P < 0.0001), and non-significant FST values (all FST < 0.04, P ranging from 0.13 to 0.19) with others also well re-established domiciliary populations from A and B localities collected a long period after insecticide spraying.

The low FST values (all < 0.07, P ranging from 0.04 to 0.69) between ruderal populations collected for the two different periods regarding short (A1Ri) and long (all others ruderal sites) periods after domiciliary insecticide spraying indicated a low influence of temporal factor (~2.5 years) in the genetic structure for this environment (Table 3).

AMOVA showed that when we nested one group with the domiciliary population collected within a short period after insecticide spraying (A1IPi) with the domiciliary A (AI1P and A2IP) and B (B1IP and B2IP) populations collected a long period after insecticide spraying, and further nested another group composed of all ruderal populations (including A1Ri) and well re-established domiciliary C populations (C1IP and C2IP), 15% of variation between these two groups was observed. In addition, only 8% of variation among populations within groups was detected (ΦSC = 0.15 and ΦSC= 0.09, for both P < 0.002). The overall ΦST was at 0.22 (P < 0.0001). The high variation within populations (78%) can be explained by the high haplotype diversity observed, particularly for the ruderal populations.

DISCUSSION

The data presented here showed that, within the area studied, Tri. brasiliensis is genetically structured both ecological and at a small geographic scale for the domiciliary populations. A reasonable degree of population fragmentation was also suggested by variation from uninhibited areas (ruderal and sylvatic). The pattern of re-colonization was analyzed by comparing Cyt B gene variation in ruderal and domiciliary populations and by comparing populations collected a short time and long time after insecticide spraying. Re-infestations after insecticide treatment are composed of distinct populations, indicating variable population sources from both ruderal and domiciliary sites.

Our results confirmed previous studies regarding the applicability of Cyt B sequence data for population genetics studies in Tri. brasiliensis and showed that this tool can be also used to obtain information regarding gene flow over smaller distances, such as ecotopic populations. Twenty-four haplotypes were previously recorded in a much wider geographic range (the states of Pernambuco, Paraba,í Rio Grande do Norte, and Piauí).12 In our study, only 14 haplotypes were recorded in the domiciliary environment, and of these, 6 had been previously described.12 A significant amount of haplotypes (N = 15) was herein identified in uninhabited environments (sylvatic and ruderal), where the sample sizes were extended in our study.

Based on ecologic niche modeling47 and nested clade analysis,12 it was assumed that the three morphotypes recorded for this species complex were a result of fragmentations and population expansions that had occurred in the past across the geographic distribution of the morphotype studied here. Here we recorded the same central haplotype in the network,12 which was also characterized by few mutational steps between haplotypes within this morphotype. Haplotype I was strongly supported to be the ancestral haplotype, because of its representation in a significant proportion of individuals in geographic and ecotopic populations and its central location in the network (Table 1; Figure 2).

Tajima D was significantly negative for the sylvatic population (D = −1.62) and overall ruderal (D = 1.29), suggesting that selection pushed the frequency spectrum of polymorphisms towards an excess of rare variants. However, in contrast to ruderal populations, we did not observe abundant colonies for the sylvatic population. Other authors23 have also described the abundance of wild populations of Tri. brasiliensis. Because a significant Tajima D could also originate from demographic events, such as population bottleneck or population expansion, our results can be interpreted as a signal of past demographic bottleneck eventually associated with natural selection on mitochondrial genes34,48 for these natural populations. Under a neutral model context (based on non-significant D values), most of the ruderal sites also exhibited high negative D values, in contrast to domiciliary populations (with the exception of B1I) that showed high positive D values. This may also indicate population fragmentation and distinct demographic events in wild and domiciliary populations.48

Genetic structure.

AMOVA indicated that, in the synanthropic populations within the sub-localities, the genetic structure was significantly associated with particular genetic profiles for domiciliary populations within each village. However, ruderal populations did not exhibit significant differentiation, allowing us to nest all populations in the same group. High haplotype diversity values were also recorded for the ruderal populations.

All haplotypes found in intradomiciles were also found in both the peridomiciliary and ruderal ecotopes, highlighting the role played by these environments as sources of invasive populations. Peridomiciliary environments do not usually include artificial lights that can attract bugs.49 On the other hand, in addition to proximity to the ruderal environment, weather may reduce the period of the insecticides’ residual effect.50 This might explain the higher haplotype diversity observed in peridomiciliary compared with intradomiciliary ecotopes.

The highest haplotype diversity recorded for Tri. infestans Cyt B was 0.67,51 which can be considered low if compared with the highest haplotype diversity of 0.93 found in this study. This can be considered significant in terms of vector control, given that higher variability has been associated with higher difficulty of controlling vectors.5153

Light traps were used49 to estimate that approximately one wild Tri. brasiliensis might be reaching houses every two nights attracted by artificial light in this same biogeographic zone (the Caatinga). Initial levels of founding genetic diversity are known to influence the likelihood that invasive populations become successful, because genetic diversity may also mediate population fitness and susceptibility to adversities,5456 such as treatments with insecticide.

The domiciliary populations from A and C that exhibited high genetic diversity also showed lowvalues with all ruderal populations (FST < 0.15, except for A domiciliary FST populations with C2R). On the contrary, the B domiciliary population that exhibited lower genetic diversity also showed high FST values with ruderal populations. This suggests that domiciliary populations A and C were mainly colonized by ruderal populations, whereas domiciliary B populations originally resulted from another population source, likely domiciliary ecotopes, because they were less genetically diverse.

We observed that intradomiciliary and peridomiciliary sites within villages were genetically related (all FST < 0.14). Similar results were obtained for this same species using random amplified polymorphic DNA (RAPD) and morphometric markers.23 Domiciliary versus ruderal populations within both of the C sub-localities, as well as A2, exhibited low FST values (< 0.12, all P < 0.05), suggesting significant gene flow between ecotopes within a sub-locality. All C populations also exhibited the lowest FST values (all < 0.19, P < 0.0001) with the sylvatic population, pointing toward a reasonable influence of this environment. For B sub-localities, however, domiciliary and ruderal populations were not significantly related within the sub-localities. For Triatoma dimidiata in the sylvatic and domiciliary environments in the Yucatan Peninsula of Mexico,52 variable patterns of relationship between domiciliary, peridomiliary, and wild ecotopes were also shown by microsatellite analysis.

Triatoma brasiliensis is phylogenetically related to Tri. infestans,57 which can fly 1.5–2 km from its source.58 The distances between our localities were likely longer than the possible flight range of Tri. brasiliensis. However, both the Euclidean distance and the Mantel test indicated that the genetic differentiation observed for domiciliary populations has no correlation with physical distance. The lack of correlation between genetic and geographical distances also within localities strengthens the role played by ecotopes to limit the gene flow mainly because domiciliary and ruderal populations are not always genetic associated, despite the physical proximity. On the other hand, domiciliary populations in the same locality are often genetically associated, despite the longer physical distance.

The higher genetic interchanging among ruderal populations might be explained by environmental observations in the field. First, except for the physical distance, no other possible barrier to gene flow was detected. Second, ruderal populations are not subject to drastic bottleneck events, such as insecticide treatment directed at vector control, which has been suggested to promote genetic drift.53 A similar panmictic pattern has also been postulated for wild populations of Triatoma sordida.20,21

Influence of temporal factors and control activities on the genetic structure.

A domiciliary population (B1IP) showed particularly high differentiation from all other populations, with all FST values significant and > 0.18. This differentiation was caused by the low genetic diversity exhibited for this population, because one haplotype (IV) represented 48% of the total sample. However, the only domiciliary population that could be found within a short period after house spraying (A1IPi, originating from the A1 locality) exhibited the lowest value observed for B1IP collected a long period after FST house spraying. In the event these two populations share a related origin, we assume that the B1IP genetic profile has likely been maintained by population expansion after a bottleneck event and less successful ruderal invasions.

Domiciliary well re-established populations from A and B, as well as the population collected within a short period after insecticide spraying (in the process of re-establishment of infestation), seemed to be genetically related. AMOVA indicated that these domiciliary populations (from the A and B localities) collected a long period after insecticide spraying could compose a robust group with the populations collected within a short period after insecticide spraying (A1IPi). Overall results led us to assume that there were connections between A and B domiciliary populations, maybe through persistent foci between these localities that were not eliminated. Analysis of mtDNA sequences of the 12S and 16S ribosomal RNA genes in different natural populations of Tri. infestans from Argentina also suggested that the recovered insecticide-treated populations in some localities originated from survivors in the same area.59 Because of the high variability for domiciliary populations in A a long period after insecticide spraying and the detection of positive captures in a short period after insecticide spraying, this locality might have acted as a source of founders for neighboring domiciliary populations. The dispersion between neighboring domiciles is a potential epidemiologic issue, because it might be the result (or increase the potential) of specialization to domiciliary environments.60

Vector control implications.

The combination of distinct geographic, ecologic, and temporal (or seasonal) patterns of domiciliary infestation represents a complex scenario for designing effective vector control strategies. This profile has been suggested for Tri. dimidiata in Mexico by morphometry and microsatellite markers.52 We identified different patterns of domiciliary colonization and dispersion, exhibiting different sources for re-infestations. Thus, we suggest that the heterogeneity observed in the genetic structure of Tri. brasiliensis must be taken into account for control measures. The only population found within a short period after insecticide spraying was genetically related to populations collected a long time after insecticide spraying in the same and other localities. Hence, we recommend particular attention to localities exhibiting a higher pressure of re-infestation. Ecologic studies are also required to identify factors favorable for domiciliary invasions, especially from ruderal foci.

A historical overview of the epidemiology of Chagas disease in northeastern Brazil indicates that two of the most important Chagas disease vectors (Tri. infestans and Panstrongylus megistus) became vulnerable to control after the event of domestication (adaptation to the domiciliary environment).6,61 There are also indications that this specialization allowed the enlargement of the vector’s geographical distribution. The Tri. brasiliensis morphotype studied here exhibits the widest geographical distribution among the four members of this species complex.15 Despite being the most domiciliated morphotype, it still shows strong persistence in infesting houses after the control activities.1517 Thus, modern molecular techniques can be useful tools for improving the control measures, monitoring vectorial, and understanding the events related to Chagas disease epidemiology.

Table 1

Sample size (N), haplotype diversity (Hd), and numbers of each haplotype (I-XXIX) found in each site

SitesA1IA1PA1RA2IA2PA2RB1IB1PB1RB2IB2PB2RC1IC1PC1RC2IC2PC2RS
The first eight and the following six lines represent the samples found for intradomiciles and peridomiciles, respectively. The values for samples collected within a short period (0.5–1.2 years) after insecticide treatment are in parentheses. Ruderal collections for this same period are in brackets. Shaded haplotypes were private for ruderal or sylvatic environment. The first letter (A, B, C, or S, see Figure 1) refers to the locality. The following number refers to the sub-locality and the last letter to the ecotope where the samples were collected: I, intradomiciliary; P, peridomiciliary; R, ruderal; S, sylvatic.
N16 (10)11 (21)15 [67]15121411181611141471014891137
Hd0.78 (0.62)0.84 (0.69)0.90 [0.85]0.770.800.920.180.400.880.690.580.910.670.930.880.680.810.840.93
    I4 [7]11221212
    II53 (1)16211
    III5 (2)(8)2 [10]41495
    IV4 (6)3 (9)1 [2]3411014452241
    V[7]11251
    VI1 (2)141134
    VII1(1)112331
    VIII221
    IX1[6]21211
    X22
    XI(1)11
    XII112
    XIII3 (1)1 [19]412413
    XIV12 [2]31
    XV[1]1
    XVI13
    XVII211
    XVIII3 [9]218
    XIX11
    XX11
    XXI12
    XXII[4]2123
    XXIII13
    XXIV3
    XXV1
    XXVI3
    XXVII2
    XXVIII2
    XXIX1
Table 2

Variable positions in the 510 bp of the Cyt B gene for the 29 haplotypes of T. brasiliensis collected in the study

2234677811112222222233333333444444
Haplotypes4766925116780244677902248899012579
........70101949136254723716840328
ITGCCTAAGCGTTCGATAATTTTCGTTTGTAATGC
II.....................C............
III.............A....C..C.......G....
IV.A...................C............
V.....................C..........T.
VI.......A..........................
VII.....G............................
VIII.....G............C...............
IX......G...................C.......
XC.T...G...................C.......
XI............T......C..............
XII.....................C.....A......
XIII...............C..................
XIV...............C.....C............
XV.........A........................
XVI........................C.........
XVII........................C...C.....
XVIII........................C........T
XIX....C...............G.............
XX.......................A.......C..
XXI.........A............T...........
XXII................G.............G...
XXIII...........C......................
XXIV..........C.......................
XXV.................G................
XXVI........T.........................
XXVII...T..............................
XXVIII..............G...................
XXIX.........................C........
Table 3

FST pairwise population comparisons for domiciliary, ruderal, and sylvatic populations from four localities (see Figure 1)

A1IPA2IPB1IPB2IPC1IPC2IPA1RA2RB1RB2RC1RC2RSA1IPiA1Ri
All values except those in bold were significant at α = 0.05. Shaded populations were collected within a short period after insecticide spraying. The first code (A, B, and C) followed by the number (1 or 2) refers to the village. The subsequent characters refer to the ecotope: IP, collections from well re-established intradomiciliary plus peridomiciliary colonies; R, ruderal; S, sylvatic collections. Suffix i (shaded populations) refers to collection within a short period (within 0.5–1.2 years) after insecticide spraying. Ruderal population collected for this same period was also shaded.
A1IP
A2IP0.036
B1IP0.2020.217
B2IP0.0980.1060.372
C1IP0.2160.2210.5030.313
C2IP0.1120.1130.4390.1700.005
A1R0.0610.0560.3850.1900.1120.054
A2R0.1150.1180.3900.2750.1310.1220.010
B1R0.0830.0840.2860.2540.1290.1230.0120.020
B2R0.0460.0500.3430.0140.1450.0460.0410.0890.085
C1R0.1190.1200.3870.2530.0830.0900.0370.0100.0340.085
C2R0.2240.2300.5440.3590.0570.0910.0570.0570.0550.1670.108
S0.2710.2650.4740.3800.1560.1770.0710.0720.1080.1950.1010.096
A1IPi0.0190.0240.1840.0340.2850.1620.1530.2320.1850.0610.2170.3110.349
A1Ri0.0950.0900.3170.2130.1160.0880.0170.0080.0220.0680.0340.0570.0940.190
Table 4

AMOVA variance components, percentage variation explained at each hierarchical spatial/ecotopic level, and fixation indices for sites grouped according to locality (Figure 1), sites grouped according to ecotopes (intradomiciciliary, peridomiciliary, ruderal, and sylvatic), and peridomiciliary and intradomiciliary sites grouped from each village, all ruderal populations, and the sylvatic population

Source of variationdfVariance componentsPercentage of variationFixation indicesP
ΦCT = Va/Vt; ΦSC = Vb/(Vb + Vc); ΦST = 1 − (Vc/Vt); NS, not significant; LS, low significance.
According to locality
    Among geographic populations30.10 Va7.10ΦCT = 0.070.02 (LS)
    Among ecotopic sites within localities150.21 Vb13.72ΦSC = 0.150.00
    Within sites2451.19 Vc79.18
    Total2631.50 VtΦST = 0.210.00
According to ecotopes
    Among ecotopic populations30.058 Va3.87ΦCT = 0.040.09 (NS)
    Among geographic sites within ecotopes150.24 Vb16.32ΦSC = 0.170.00
    Within sites2451.19 Vc79.77
    Total2631.49 VtΦST = 0.200.00
From each village, all ruderal populations, and the sylvatic population
    Among domiciliary sites from each village, all ruderal, and the sylvatic site70.24 Va15.54ΦCT = 0.160.00
    Among sites within groups110.10 Vb6.72ΦSC = 0.080.00
    Within sites2441.18 Vc77.74
    Total2621.52 VtΦST = 0.220.00
Figure 1.
Figure 1.

Collection sites for Triatoma brasiliensis specimens in the four localities (A, B, C, and S) in the state of Paraíba (PB), Brazil. Except for S (the sylvatic spot), each locality was divided into two sub-localities (1 and 2).

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 78, 5; 10.4269/ajtmh.2008.78.791

Figure 2.
Figure 2.

Maximum parsimony network showing the relationship among the 29 Triatoma brasiliensis haplotypes based on the cytochrome b mitochondrial gene. The left network (a) is coded in localities and the right one (b) in ecotopes. For an explanation of the localities, see Figure 1. The ecotopes are intradomiciliary (I), peridomiciliary (P), ruderal (R), and sylvatic (S).

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 78, 5; 10.4269/ajtmh.2008.78.791

Figure 3.
Figure 3.

Neighbor-joining tree derived from linear pairwise FST distances of Triatoma brasiliensis populations. The collection spots are shown in Figure 1. The suffix IP refers to samples collected for well reestablished intradomiciliary plus peridomiciliary infestations, and R to the ruderal ecotope. The code S refers to the sylvatic population. Suffix (i) indicates the samples collected within a short period (0.5 to 1.2 years) after insecticide spraying for A1IPi and simultaneous collections for ruderal (A1Ri). The values used to build the tree are shown in Table 3.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 78, 5; 10.4269/ajtmh.2008.78.791

Figure 4.
Figure 4.

Each spot represents the genetic differentiation of one unique pair of Triatoma brasiliensis populations correlated with (Euclidean) distance. The left scale (gray diamonds) indicates the FST/(1−FST) values between populations from each locality (A, B, C, and S; see Figure 1). The same domiciliary sampling was used for the FST /(1−FST) values indicated on the right axis (black diamonds); ruderal samples were excluded from this analysis. Geographic distances were not log-transformed for circles, representing geographic and genetic correlation within localities.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 78, 5; 10.4269/ajtmh.2008.78.791

*

Address correspondence to Carlos Eduardo Almeida, Pav. Mourisco 2° andar, s/211, Instituto Oswaldo Cruz/IOC/FIOCRUZ, Av. Brasil, 4365 Manguinhos, Rio de Janeiro 21040-900, Brazil. E-mail: almeidace@ioc.fiocruz.br

Authors’ addresses: Carlos Eduardo Almeida, Raquel S. Pacheco, and Jane Costa, Instituto Oswaldo Cruz, Fiocruz, Av. Brasil 4365, 21045-900 Rio de Janeiro, RJ, Brazil, Fax: 55212573-7276, E-mails: almeidace@ioc.fiocruz.br, rpacheco@ioc.fiocruz.br, and jcosta@ioc.fiocruz.br. Karen Haag, Departamento de Genética, Avenida Bento Gonçalves, 9500, 91501-970 Porto Alegre, RS, Brazil, E-mail: karen.haag@ufrgs.br. Stéphane Dupas, Institut de Recherche pour le Développement, UR072 en la Pontificia Universidad Católica del Ecuador, Departamento de Biología, Laboratorio de Entomología, 12 de Octubre 1076 y Roca, PO Box 17-12-184, Quito, E-mail: dupas@legs.cnrs-gif.fr. Ellen Dotson, Division of Parasitic Diseases, Centers for Disease Control and Prevention, NCID, 4770 Buford Highway, Chamblee, GA 30341-3717, E-mail: ebd6@cdc.gov.

Acknowledgments: We thank the technicians of Funasa for essential help in the field; Laura Ney for kindly arranging for all field work; LeeAnn Jones, Gena Groner, Audrey Lenhart, Lynn Y. Huynh, and Alberto D’Avila for help with the laboratory work and analysis of the data; Paula Marcet for helping with the molecular methods; Alexandre Peixoto, Pedro Cabello, and Marli M. Lima for valuable comments; and Márcio Felix, John Sved, Carine Brouat, and anonymous referees for kindly and carefully reviewing the manuscript. We appreciate the kindness shown to us by the people from the municipality of São José da Lagoa Tapada.

Financial support: This research was supported by the National Council for Scientific and Technological Development (CNPq), the Strategic Program of Research in Health (PAPES 3/Oswaldo Cruz Foundation), and the Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES).

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Author Notes

Reprint requests: Carlos Eduardo Almeida, Instituto Oswaldo Cruz, Fiocruz, Pav. Mourisco, s/211, Av. Brasil 4365, 21045-900 Rio de Janeiro, RJ, Brazil.
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