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. 2009 Jun 30;3(6):e468. doi: 10.1371/journal.pntd.0000468

The Neovolcanic Axis Is a Barrier to Gene Flow among Aedes aegypti Populations in Mexico That Differ in Vector Competence for Dengue 2 Virus

Saul Lozano-Fuentes 1, Ildefonso Fernandez-Salas 2, Maria de Lourdes Munoz 3, Julian Garcia-Rejon 4, Ken E Olson 1, Barry J Beaty 1,*, William C Black IV 1
Editor: Duane Gubler5
PMCID: PMC2697380  PMID: 19564909

Abstract

Background

Aedes aegypti is the main mosquito vector of the four serotypes of dengue virus (DENV). Previous population genetic and vector competence studies have demonstrated substantial genetic structure and major differences in the ability to transmit dengue viruses in Ae. aegypti populations in Mexico.

Methodology/Principal Findings

Population genetic studies revealed that the intersection of the Neovolcanic axis (NVA) with the Gulf of Mexico coast in the state of Veracruz acts as a discrete barrier to gene flow among Ae. aegypti populations north and south of the NVA. The mosquito populations north and south of the NVA also differed in their vector competence (VC) for dengue serotype 2 virus (DENV2). The average VC rate for Ae. aegypti mosquitoes from populations from north of the NVA was 0.55; in contrast the average VC rate for mosquitoes from populations from south of the NVA was 0.20. Most of this variation was attributable to a midgut infection and escape barriers. In Ae. aegypti north of the NVA 21.5% failed to develop midgut infections and 30.3% of those with an infected midgut failed to develop a disseminated infection. In contrast, south of the NVA 45.2% failed to develop midgut infections and 62.8% of those with an infected midgut failed to develop a disseminated infection.

Conclusions

Barriers to gene flow in vector populations may also impact the frequency of genes that condition continuous and epidemiologically relevant traits such as vector competence. Further studies are warranted to determine why the NVA is a barrier to gene flow and to determine whether the differences in vector competence seen north and south of the NVA are stable and epidemiologically significant.

Author Summary

The Neovolcanic axis (NVA) traverses Mexico at the 19th parallel and is considered to be a geographic barrier to many species. We have demonstrated that the intersection of the NVA with the coast in Veracruz state is a barrier to gene flow in Ae. aegypti. This was unexpected because the intersection of the NVA with the Pacific Coast is not a barrier to gene flow. Further studies to identify the actual mechanism(s) that is(are) contributing to the lack of gene flow will provide important information on the trafficking potential of Ae. aegypti, which will be of great value to Ae. aegypti control programs. There are significant differences in vector competence for dengue virus between mosquitoes north and south of the NVA, but the epidemiological significance of these finding remains to be determined. Future studies will determine if, for example, the genes that condition midgut infection and vector competence of Ae. aegypti populations provide biomarkers for risk of dengue transmission. Such biomarkers could be of great value to control programs in resource limited environments by allowing targeting of vector control efforts to areas at most risk for epidemic dengue and dengue hemorrhagic fever.

Introduction

The mosquito Aedes aegypti is the main vector of the four serotypes of Dengue virus (DENV1-4). There are 50–100 million DENV infections each year [1],[2] and while most of these are mild or asymptomatic, the numbers of severe infections with shock and hemorrhage have increased dramatically in many parts of the world [3],[4]. Aedes aegypti populations exhibit a large amount of genetic variation in their ability to become infected with, propagate, and eventually transmit flaviviruses [5][8], including DENV1–4. Vector competence for flaviviruses is thought to be controlled by at least two physiological mechanisms, a midgut infection barrier (MIB) and a midgut escape barrier (MEB) [9],[10] with environmental factors contributing up to 60% of variation [9]. Our genetic studies suggested that infection rates among natural populations of Ae. aegypti may be due to segregation of alleles at up to 8 loci [11][14].

We previously conducted studies to determine the breeding structure and vector competence of Ae. aegypti populations in Mexico [15],[16]. For the population genetic studies, Ae. aegypti were collected from throughout the coastal regions of Mexico, and 25 haplotypes of the Nicotinamide Adenine dinucleotide dehydrogenase subunit 4 mitochondrial (ND4) gene were detected by SSCP analysis. These studies revealed that northeastern Mexican Ae. aegypti were genetically differentiated from the Yucatan and Pacific Coast mosquitoes. FST values revealed extensive gene flow along the Pacific Coast, but not in the Yucatan Peninsula and northeastern Mexico. These studies also revealed a barrier to gene flow somewhere along the Gulf of Mexico between Tuxpan and Moloacan/Minatitlan in northern and southern Veracruz State, respectively. Ae. aegypti collected for the population genetic studies were also phenotyped for vector competence for DENV2, which revealed considerable variation in vector competence for DENV2 in Mexico [8]. Interestingly, the Ae. aegypti collections from southern Veracruz Coastal Plain differed significantly in vector competence; mosquitoes from Merida, Chetumal, and Cancun in the Yucatan were the most vector competent and those from Nuevo Laredo and Houston, the least vector competent [8]. Unfortunately, in both the population genetic and vector competence studies, no sites were sampled in Veracruz state (∼750 km from north to south). This prevented us from identifying the specific barriers to gene flow.

This also prevented us from examining vector competence in Veracruz. This is of special interest because a 1986 serological survey conducted by the Secretaria de Salud of Mexico [17] revealed major differences in dengue seroprevalence rates in cities and towns in Veracruz state. The dengue seroprevalence rate was 58% (29/50) in people from Martinez de la Torre (in northern Veracruz) versus 0% (0/50) in samples from Moloacan (southern Veracruz).

The present study is therefore an attempt to define more precisely the geographic barrier to gene flow previously observed between the northern [16] and southern Gulf of Mexico Coastal Plain [15] and to characterize more thoroughly the vector competence of mosquitoes separated in southern Veracruz. We obtained 10 Ae. aegypti collections between Tuxpan in the north to Minatitlan in the south (Figure 1). Nine of these same 10 sites were resampled in 2004 to test the consistency of our 2003 results. These collections were analyzed with the same mitochondrial ND4 marker gene as in earlier studies [15],[16]. The same mosquitoes were assessed for VC and midgut infection and escape barriers using established protocols [8].

Figure 1. Map of the coastal plain of Veracruz indicating the locations of the 10 Aedes aegypti sampling sites relative to the Neovolcanic Axis.

Figure 1

Pie charts indicate the proportion of mosquitoes that were vector competent (black), midgut negative (red) and head negative (green). The VC rates were interpolated by Inverse Distance Weighting and geographic areas are colored from yellow to red according to predicted vector competence rates. R2 = 0.66 and root mean square error = 9.6.

Methods

Mosquito collection

Mosquitoes were collected as larvae from the cities listed in Table 1. In each city multiple locations were visited (Figure 1) and at each location at least 3 separate breeding sites separated by at least 500 meters were sampled. These larvae were returned to the laboratory and emerged adults were individually examined to confirm that they were Ae aegypti. The 2003 collection was processed for analysis of vector competence and mtDNA markers; the 2004 collection only for mtDNA analyses. All experiments used F1–F4 mosquitoes to minimize effects of colonization and inbreeding.

Table 1. Locations, dates of collections, coordinate, and sample sizes of Aedes aegypti collections in Mexico.

State City/Region Date(s) m/y Latitude Longitude n
Nuevo Leon Monterrey North 7/96 N25°40′00.12″ W100°18′00.00″ 57
South 7/96 N25°28′00.12″ W100°10′01.20″ 58
West 7/96 N25°30′00.00″ W100°04′58.80″ 58
East 7/96 N25°40′59.88″ W100°22′01.20″ 58
Tamaulipas Ciudad Victoria 8/96 N23°40′00.12″ W099°15′00.00″ 59
Miguel Aleman 6/98 N26°23′30.00″ W099°03′39.00″ 50
Matamoros 7/96 N26°15′00.00″ W097°28′00.12″ 59
Nuevo Laredo 8/97 N27°30′00.00″ W099°28′00.12″ 48
Reynosa 7/97 N26°10′00.12″ W098°10′00.12″ 59
Tampico 8/96 N23°40′00.12″ W097°49′59.88″ 59
Veracruz* Panuco 08/03, 08/04 N22°03′12.47″ W098°11′11.78″ 141
Tantoyuca 08/03, 08/04 N21°20′30.33″ W098°13′39.88″ 118
Poza Rica 08/03, 08/04 N20°32′37.18″ W097°28′14.83″ 105
Martinez de la Torre 08/03, 08/04 N20°02′59.97″ W097°02′19.77″ 102
Acayucan 08/03, 08/04 N17°57′43.07″ W094°24′45.17″ 138
Alvarado 08/03, 08/04 N18°46′27.19″ W095°45′48.80″ 116
Coatzacoalcos 08/03, 08/04 N18°08′26.91″ W094°24′47.15″ 120
Cosoleacaque 08/03 N17°57′43.07″ W094°32′09.79″ 63
Minatitlan 9/96, 08/03, 08/04 N17°58′47.00″ W094°32′27.00″ 161
Moloacan 9/98 N17°59′09.00″ W094°20′46.00″ 55
Tuxpan 8/96 N21°10′00.12″ W097°25′00.12″ 59
Zempoala 08/03, 08/04 N19°26′41.60″ W096°24′23.31″ 105
Tabasco Villahermosa 9/98 N17°59′59.99″ W092°54′00.00″ 58
Campeche Campeche 8/98 N19°53′59.99″ W090°36′00.01″ 53
Cd. del Carmen 8/98 N18°35′59.99″ W091°47′59.99″ 52
Yucatan Merida 7/99 N20°57′00.01″ W089°38′23.99″ 57
North 7/99 N21°00′44.64″ W089°37′51.60″ 49
South 7/99 N20°57′06.84″ W089°38′26.88″ 35
Central 7/99 N20°57′58.68″ W089°39′57.24″ 46
East 7/99 N20°59′28.32″ W089°35′00.60″ 53
West 7/99 N20°58′39.00″ W089°39′28.80″ 60
Quintana Roo Cancun Central 6/99 N21°08′24.01″ W086°52′47.99″ 32
North 6/99 N21°09′03.61″ W086°52′38.97″ 53
Chetumal Central 6/99 N18°29′59.99″ W088°18′00.00″ 38
North 6/99 N18°30′29.31″ W088°17′49.97″ 54
Total 2488

Vector competence

The DENV2 strain used was dengue 2 JAM1409, which was isolated in 1983 in Jamaica and belongs to the American Asian genotype [18],[19]. Procedures for growing virus in 14 day cell culture, quantifying the virus and infecting mosquitoes with membrane feeders covered with sterile hog gut membranes are published [8]. A highly DENV2 susceptible Aedes aegypti colony called D2S3 [20] served as an internal control in each experimental feed to test for consistency in the titer and infectiousness of the DENV2 meal preparation. Undiluted virus titers ranged from 7.5–8.5 log10 infectious virus/ml, which resulted in infection of 100% of the D2S3 mosquitoes in each feeding experiment.

Fully engorged mosquitoes were removed from the feeding carton and held for 14-days at a constant 27°C and 80% relative humidity in an insectary with a 12-hour photoperiod. Mosquitoes were frozen at −70°C until processed. Heads and abdomen were assayed for infections by immunofluorescence assay (IFA) using a mouse derived primary monoclonal antibody directed against a flavivirus E gene epitope [21],[22]. DNA was then extracted from the thorax [23] for population genetic studies.

For IFA, detection of DENV antigen in head tissues revealed a disseminated infection; these mosquitoes were scored as head positive (H+). The H+ mosquitoes were considered to be vector competent (VC), because salivary glands become infected in disseminated DENV infections and the H+ mosquitoes are presumably capable of transmitting the virus [24]. If no viral antigen was detected in the head tissues, the mosquito was scored as head negative (H−) and vector incompetent (VIC). To determine the anatomic basis for VIC, the H− mosquitoes were then examined to determine if the midgut was infected. H− mosquitoes with no detectable antigen in the midgut were scored as having a midgut infection barrier (MIB). H− mosquitoes with detectable viral antigen in the midgut were scored as having a midgut escape barrier (MEB). Because mosquitoes with a MIB could not be phenotyped for a MEB, we also determined the overall head negative rate (H-R) = H−/N.

The 95% confidence interval around VC, MIB, MEB and H-R was calculated as the Wald interval:

graphic file with name pntd.0000468.e001.jpg

where Inline graphic VC, MIB, MEB and H-R. Estimates are either adjusted by adding half of the squared Z-critical value (1.96) to the numerator and the entire squared critical value to the denominator before computing the interval [25].

Population structure

Primers used to amplify the ND4 and all the polymerase chain reaction (PCR) and Single Strand Conformation Polymorphism (SSCP) conditions were reported earlier [15],[16]. The ND4 PCR products from mosquitoes containing each of the 9 haplotypes were sequenced at least once along both strands using an ABI sequencer (Davis Sequencing, Davis, California). Products from at least two mosquitoes representing each haplotype were sequenced. These 20 sequences were compared to sequences reported previously and assigned the same numeric labels [15],[16]. Phylogenetic relationships among haplotypes have been previously described [15],[16].

Statistical analysis of mitochondrial haplotype frequencies

Variation in haplotype frequencies within and among collection sites and regions was examined using Molecular Analysis of Variance (AMOVA) [26]. Arlequin3 estimated pairwise Slatkin's “linearized FST” [FST/(1−FST)] [27] among collections and computed the significance of the variance components associated with each level of genetic structure by a nonparametric permutation test with 100,000 pseudoreplicates [26]. A distance matrix containing linearized FST values was collapsed to construct a dendrogram using unweighted pair-group method with arithmetic averaging analysis [28] in the NEIGHBOR procedure in PHYLIP3.5C [29].

Spatial analysis of vector competence

Inverse Distance Weighting interpolations are based on the assumption that the interpolating surface should be influenced most by the nearby points and less by the more distant points [30],[31]. The transformed VC values (arcsin√VC) were interpolated and the resulting surface was then back transformed. The maximum search area considered was 2.5° with no anisotropy (i.e. circular search area); the search was continued until five geographically most proximate collections (neighbors) were identified.

Results

Gene flow

The ND4 was amplified and surveyed for variation by SSCP analysis [32],[33] among 654 mosquitoes in 19 collections (Table 1). These were 10 collections obtained in 2003 and 9 obtained in 2004 (no mosquitoes were collected in Cosoleacaque). Nine different ND4 haplotypes were detected with SSCP. The ND4 gene was sequenced in 20 mosquitoes. All the sequenced haplotypes were compared to those previously reported (GenBank accession numbers AF334841–AF334865), and no novel haplotypes were detected. Accordingly all haplotypes in this study retain the same numerical designations as those in GenBank. As reported in previous studies [15],[16], sequences of mosquitoes with identical SSCP patterns were identical within each haplotype, and SSCP patterns differed among mosquitoes with one or a few nucleotide differences.

Figure 2 is a UPGMA cluster analysis of pairwise linearized FST values [27] among 46 collections including 19 from the present study, 12 from previous studies north of Panuco in 1996–1997 [16] and 15 from south and east of Minatitlan in 1998–1999 [15]. With the single exception of Nuevo Laredo, all collections in northern Veracruz fall within a single cluster. The genetic distinctness of Nuevo Laredo Ae. aegypti was previously reported for both RAPD and mtDNA markers [16]. Northern collections cluster independently of collection year. Figure 3 indicates that most mosquitoes in northern Veracruz have haplotypes 1–9 and that haplotypes 10–18 are absent.

Figure 2. An UPGMA cluster analysis of pairwise linearized FST values among 46 collections including 19 from the present study, 12 from previous studies north of Panuco in 1996–1997 [22] and 15 from south and east of Minatitlan in 1998–1999 [21].

Figure 2

Figure 3. Relative frequencies of the 24 mitochondrial ND4 haplotypes in the 46 collections north (top) and south (bottom) of the Neovolcanic Axis.

Figure 3

Haplotype number designations correspond to those in GenBank accessions AF334841–AF334865.

With the exceptions of Minatitlan 1996, Moloacan 1998, and Zempoala 2003, all collections in southern Veracruz fall into a cluster that is distinct from the northern cluster (Figure 2). Figure 3 indicates that most mosquitoes in southern Veracruz have haplotypes 10–18, 19 and 24. In 2003 Zempoala (Figure 1) mosquitoes (indicated with an arrow in Figure 2) clustered with the northern collections and were most similar to Martinez de la Torre (Figure 3), the collection site just north of Zempoala. But in 2004, Zempoala mosquitoes clustered with the southern collections. In contrast to northern mosquitoes, southern collections cluster according to collection year with 1998–1999 collections clustering independently of the 2003–2004 collections. Figure 2 indicates that the Minatitlan 1996 and Moloacan 1998 collections are similar to one another but genetically very distinct from Minatitlan 2003–2004. Moloacan and Minatitlan are in close geographic proximity to one another, yet they are also close to Cosoleacaque, Acayucan, and Coatzacoalcos.

Nested analysis of haplotype frequencies

AMOVA [26] was used to compare haplotype frequencies 1) among all 46 collections in northern and southern Veracruz, 2) among the nineteen 2003 and 2004 collections in northern and southern Veracruz, and 3) in 2003 vs. 2004 collections (Table 2). When analyzing all 46 collections, a significant 16% of the variation in haplotype frequencies arose between collections in northern and southern Veracruz (Table 2) and an additional 20% arose among collections made either in northern or southern Veracruz. A similar pattern was detected when analyzing the 2003 and 2004 collections alone. However a greater percentage of the variation (24.5%) arose between collections in northern and southern Veracruz and, probably because we eliminated variation arising from the 1996–1998 collections, less variation (13%) arose among collections in northern and southern Veracruz. Whether collections were made in 2003 or 2004 made no difference. A negative and non-significant percentage of the variation arose between years.

Table 2. Molecular Analysis of Variance [26] of haplotype frequencies between the 46 collections north and south of the NVA, the nineteen 2003 and 2004 collections north and south of the NVA and between 2003 and 2004 collections.

Source of variation d.f. S.S. Var. comp. (F) %
All 46 Collections
Collections N vs. S of the NVA 1 103.80 0.079 (FNVA = 0.162)*** 16.3
Among collections N or S of NVA 44 249.87 0.099 (FCollections(NVA) = 0.243) *** 20.4
Within collections 2435 756.33 0.308 (F(Mosquitoes(Collections) = 0.366)*** 63.4
Total 2498 1109.91 0.487
19 collections from 2003-4
Collections N vs. S of the NVA 1 65.30 0.118 (FNVA = 0.245)*** 24.5
Among collections N or S of NVA 17 64.45 0.062 (FCollections(NVA) = 0.172) *** 13.0
Within collections 1055 315.52 0.299(F(Mosquitoes(Collections) = 0.375)*** 62.5
Total 1073 445.26 0.479
2003 vs. 2004 collections
Between 2003 vs. 2004 collections 1 1.92 −0.011 (FYear = −0.026) −2.7
Among collections within years 17 127.82 0.128 (FCollections(Year) = 0.300)*** 30.8
Within collections 1055 315.52 0.299 (F(Mosquitoes(Collections)  = 0.282)*** 71.9
Total 1073 445.26 0.416

***: p-value ≤ 0.0001

Analysis of vector competence

Table 3 provides the results of the vector competence studies for DENV2 of mosquitoes from the 2003 collections. In each site we report the proportion of mosquitoes with virus in the head tissues (H+) or not (H−), and for H− individuals the presence of virus in the midgut (M+) or not (M−). The VC (H+/N), VIC (H−/N), MIB (M−/N) and MEB (H−/M+) rates were calculated for each population (Table 3). The VC and VIC rates as well as the MIB rate for each of the 10 populations are presented in pie charts in Figure 1.

Table 3. Vector competence in the 2003 Veracruz Collections.

Collection N 1M+ 2M- 3H+ 4H- 5VC 695CI 7MIB 695CI 8H-R 695CI 9MEB 695CI
Panuco 60 39 21 23 16 0.383 (0.264–0.503) 0.350 (0.232–0.468) 0.267 (0.156–0.377) 0.410 (0.263–0.558)
Tantoyuca 77 60 17 45 15 0.584 (0.477–0.692) 0.221 (0.128–0.313) 0.195 (0.106–0.284) 0.250 (0.142–0.358)
Poza Rica 47 41 6 35 6 0.745 (0.622–0.867) 0.128 (0.028–0.227) 0.128 (0.028–0.227) 0.146 (0.035–0.258)
Martinez* 72 61 11 37 24 0.514 (0.401–0.626) 0.153 (0.068–0.237) 0.333 (0.227–0.440) 0.393 (0.274–0.513)
256 201 55 140 61 0.547 (0.486–0.607) 0.215 (0.165–0.265) 0.238 (0.186–0.290) 0.303 (0.240–0.367)
Zempoala 75 55 20 25 30 0.333 (0.229–0.438) 0.267 (0.168–0.366) 0.400 (0.292–0.508) 0.545 (0.418–0.673)
Alvarado 56 20 36 6 14 0.107 (0.021–0.193) 0.643 (0.521–0.765) 0.250 (0.138–0.362) 0.700 (0.511–0.890)
Cosoleacaque 63 33 30 8 25 0.127 (0.042–0.212) 0.476 (0.356–0.596) 0.397 (0.279–0.514) 0.758 (0.614–0.901)
Minatitlan 60 29 31 12 17 0.200 (0.099–0.301) 0.517 (0.394–0.639) 0.283 (0.171–0.395) 0.586 (0.417–0.755)
Acayucacan 73 35 38 8 27 0.110 (0.035–0.185) 0.521 (0.409–0.632) 0.370 (0.262–0.478) 0.771 (0.634–0.909)
Coatzasacoalcos 71 46 25 22 24 0.310 (0.204–0.415) 0.352 (0.243–0.461) 0.338 (0.230–0.446) 0.522 (0.383–0.660)
398 218 180 81 137 0.204 (0.164–0.243) 0.452 (0.404–0.501) 0.344 (0.298–0.391) 0.628 (0.565–0.692)
P(Wilcoxon Test) 0.0095 0.0191 0.0667 0.0095

* = Martinez de la Torre, 1 Midgut Positive, 2 Midgut Negative, 3 Head Positive, 4 Head Negative, 5 Vector Competence (VC) = H+/N, 6 Wald 95% Confidence interval (95CI), 7 Midgut Infection Barrier (MIB) = M−/N, 8 Head Negative Rate (H-R) = H−/N, 9 Midgut Escape Barrier (MEB) = H−/M+

In northern Veracruz, the VC rate ranged from 0.38–0.75 with an average of 0.55, while VC among mosquitoes in southern Veracruz ranged from 0.11–0.33 and averaged 0.20. These differences were significant (Wilcoxon tests for unpaired samples, p = 0.0095). This variation was attributable to the greater proportion of mosquitoes with both MIBs and MEBs in southern Veracruz. Mosquitoes with uninfected guts constituted 21.5% of collections in northern Veracruz while 45.2% of mosquitoes in southern Veracruz had a MIB. This 23.7% difference in MIB rate was significant (Wilcoxon tests for unpaired samples, p = 0.0191). MEB rate varied by 32.5% between northern MEB% = 30.3%) and southern (MEB% = 62.8%) collections ((Wilcoxon tests for unpaired samples, p = 0.0095).

The VC rates among the 10 Veracruz sites were interpolated by Inverse Distance Weighting (IDW) [30],[31] with (arcsin√VC)/100 using ArcInfo 9.1. The model derived by jackknifing over the 10 sites using the “leave-one-out” procedure had a R2 = 0.66 and a root mean square error of 9.6. The interpolated predicted values appear in colors from red (susceptible) to yellow (refractory) in Figure 1.

Both the original measurements of VC (pie charts) and the predicted values from IDW interpolation suggest that VC declines precipitously south of the intersection of the Neovolcanic axis (NVA) with the Gulf of Mexico coast (Figure 1). The overall pattern in VC among 34 collections of Ae. aegypti made over an 8 year period throughout Mexico and two sites in the southern United States (Figure 4) demonstrates that the VC of mosquitoes from Alvarado, Acayucan, Coatzacoalcos and Cosoleacaque is among the lowest in Mexico.

Figure 4. Map of Mexico and southern United States indicating the locations of the 34 collections of Aedes aegypti, 24 from a previous study [8] and 10 from the present study made over an 8 year period.

Figure 4

The bars represent mosquito susceptibility to DENV2 (Jam1409). The number next to the city name is the mosquito susceptibility ((H+/N)×100).

Discussion

Our results are consistent with an hypothesis that the intersection of the NVA with the Gulf of Mexico coast is the barrier to gene flow previously observed between Ae. aegypti collections north [16] and south on coastal plain along the Gulf of Mexico [15]. The Transverse Volcanic Belt of Mexico [34] divides the state of Veracruz into northern and southern Coastal Plains. This belt began to develop during the Oligocene and then later, during the Pliocene–Pleistocene, intense orogenic activity raised the Neovolcanic axis. The NVA extends from near the Pacific Coast east to the Gulf of Mexico and intersects the Atlantic coast in the state of Veracruz. The NVA favored a warm and dry climate in the south of Mexico, and promoted the establishment of tropical deciduous forests [35],[36]. Near the NVA, the onset of rainfall is earlier than in the semiarid highlands. Mexico's six highest mountains are part of the NVA, which constitutes the largest east west mountain range on the North American continent and have played an enormous role in vicariance and allopatric speciation events in a large number of plant and animal species [37][39]. We observed a local change in mitochondrial haplotype frequencies in Zempoala from a northern type of pattern (very similar to Martinez de la Torre) in 2003 to a more southern type of pattern (high frequency of haplotype 14) in 2004 (Figure 3). This suggests that local gene flow can occur across the NVA intersection. However, the overall pattern among collections made over an 8 year period (Figure 2) argues strongly that the narrow corridor between the NVA and the Atlantic Ocean restricts gene flow in the long term.

It isn't clear why the NVA acts as a barrier to gene flow in Ae. aegypti. We examined differences in climatic factors such as solar radiation, precipitation, and land use as potential barriers to gene flow in the Veracruz Coastal Plain, but there were no obvious consistent differences in these factors north and south of the NVA [40]. The NVA could serve as physical barrier to gene flow because the distribution of Ae. aegypti in Mexico is largely limited to elevations < 610 m (∼2,000 feet) above sea level [41]. However, elevations also exceed this limit where the NVA intersects the Pacific Ocean and mosquitoes from Tapachula north to Tucson Arizona appeared to represent a single panmictic population [15].

One major difference between the Pacific and Atlantic coasts of Mexico is the amount of movement of people and commerce. Aedes aegypti is generally considered to have low mobility via flight [42],[43], but is facilely moved about locally and globally through human transportation and commerce [14], [44][47]. In comparison with the Pacific Coast of Mexico, where there are major roads and railways (albeit not always on the edge of the coastal plain), the corridor between the Atlantic Ocean and the NVA contains only a single, two lane road that is used only for local travel. Most automobile and truck traffic between northern and southern Mexico goes through Mexico city [40]. The Pacific Coast also has robust maritime and cruise ship activity which may traffic Ae. aegypti along the coast. In contrast, there is little such activity between cities on the Gulf of Mexico, which could also limit gene flow [40]. Overall these considerations suggest that the principal barrier is human trafficking and commerce, but further investigations will be required to determine if this is true.

Unexpectedly the NVA is also associated with significantly different VC phenotypes. Figure 4 shows the overall pattern in vector competence of Ae. aegypti in Mexico and the southern United States and demonstrates that the low vector competence of mosquitoes from sites just south of the NVA is unusual. The reasons for this remain to be determined. The genetic mechanisms conditioning the differences in VC remain to be determined. Association mapping studies to determine if the early trypsin and late trypsin genes conditioned VC revealed no consistent associations between segregating sites in the genes and VC for DENV2 [48]. Importantly the DNA from each of the mosquitoes phenotyped for DENV2 VC has been archived and as new candidate genes for VC are identified, the potential role of the genes in VC can be rapidly tested using these materials. It is also important to note that these studies have been done with only one dengue virus serotype/genotype. It will be important to confirm these results with additional dengue serotypes and genotypes that are circulating in Mexico and Latin America [19].

The temporal stability of the VC patterns north and south of the NVA is of interest. VC for DENV2 appears to be a quantitative genetic trait with up to 60% of the variation in VC being associated with random, or uncontrolled environmental effects [9],[12]. QTL mapping of genome regions conditioning MIB and MEB have identified 8 different genome regions [11],[13],[14] three associated with a MEB, and five associated with an MIB and three of these mapping families originated from northeastern Mexico [11],[13],[14]. An ongoing reevaluation of VC in mosquitoes collected north and south of the NVA in 2005 indicates that the reduced VC south of the NVA is stable (S. Bernhardt, personal communication).

An interesting alternative hypothesis is that the patterns that we are detecting may have little to do with environmental and ecological factors and may instead represent the introduction of Ae aegypti formosus south of the NVA [46],[49]. The two subspecies are sympatric in Senegal [50] and other parts of West Africa, and could have been introduced independently and multiple times into the New World. We recently discovered chromosomal inversions in Senegalese Ae. aegypti formosus [51]. Such inversions might also act as barriers to gene flow if they condition prezygotic reproductive isolating mechanisms. If mating does occur then inversions might cause excess chromosome breakage following crossing over during meiosis in hybrids yielding aneuploid gametes. Aedes aegypti aegypti and Ae aegypti formosus differ dramatically in their vector competence for yellow fever virus [5],[7] and DENV [50]. Provocatively, the Ae. aegypti populations north and south of the NVA also differed significantly in VC for DENV2. However a focal distribution of Ae. aegypti formosus in southern Veracruz would not explain why no barriers to gene flow were detected between southern Veracruz collections and collections in the Yucatan Peninsula.

A major goal of our dengue research program in Mexico is to determine if mosquito VC is correlated with dengue incidence. If so, identification of genes that are biomarkers of VC could permit targeting of control efforts to areas at greatest risk for dengue epidemics. In this regard, it is intriguing that the Ae. aegypti south of the NVA exhibited low VC and some cities, for example, in Moloacan, the seroprevalence rate was zero [17]. This historical data, which is 20 years old, may not reflect current conditions in southern Veracruz. The epidemiology of dengue in Mexico has changed dramatically in the last two decades, and dengue is now hyperendemic in Coastal Plains of Mexico. A serosurvey for dengue antibodies conducted in Jatilpan, Veracruz, which is in the same region as Moloacan, revealed a seroprevalence rate of 80% [52]. However, in the Secretaria de Salud report there were cities/towns in southern Veracruz that had similar seroprevalence rates in 1986. Clearly this is a complex situation, and conducting prospective VC studies and seroprevalence surveys in cities and towns in this unique region. Such studies would provide important information on the importance of VC in dengue incidence.

Supporting Information

Alternative Language Abstract S1

Translation of the Abstract into Spanish by Saul Lozano-Fuentes

(0.03 MB DOC)

Acknowledgments

We gratefully acknowledge the support of vector control programs in Veracruz State for assistance in collection of Ae. aegypti eggs. We also thank Cindy Meredith and staff of the Arthropod-Borne and Infectious Disease Laboratory for their assistance in Ae. aegypti population colonization and maintenance.

Footnotes

The authors declare that there are no competing interests.

This study was supported by grants AI-49256 and AI-45430 from the National Institutes of Health and in part by the Innovative Vector Control Consortium. SLF was supported by NIH Fogarty Center Training Grant AI-46753. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Gubler DJ. The global emergence/resurgence of arboviral diseases as public health problems. Arch Med Res. 2002;33:330–342. doi: 10.1016/s0188-4409(02)00378-8. [DOI] [PubMed] [Google Scholar]
  • 2.Monath TP. Dengue: the risk to developed and developing countries. Proc Natl Acad Sci U S A. 1994;91:2395–2400. doi: 10.1073/pnas.91.7.2395. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Gubler DJ. Epidemic dengue/dengue hemorrhagic fever as a public health, social and economic problem in the 21st century. Trends Microbiol. 2002;10:100–103. doi: 10.1016/s0966-842x(01)02288-0. [DOI] [PubMed] [Google Scholar]
  • 4.Organization PAH. Dengue and Dengue Hemorrhagic Fever in the Americas: Guidelines for Prevention and Control. Washington, D.C: 1994. [Google Scholar]
  • 5.Aitken TH, Downs WG, Shope RE. Aedes aegypti strain fitness for yellow fever virus transmission. Am J Trop Med Hyg. 1977;26:985–989. doi: 10.4269/ajtmh.1977.26.985. [DOI] [PubMed] [Google Scholar]
  • 6.Rosen L, Roseboom LE, Gubler DJ, Lien JC, Chaniotis BN. Comparative susceptibility of mosquito species and strains to oral and parenteral infection with dengue and Japanese encephalitis viruses. Am J Trop Med Hyg. 1985;34:603–615. doi: 10.4269/ajtmh.1985.34.603. [DOI] [PubMed] [Google Scholar]
  • 7.Tabachnick WJ, Wallis GP, Aitken TH, Miller BR, Amato GD, et al. Oral infection of Aedes aegypti with yellow fever virus: geographic variation and genetic considerations. Am J Trop Med Hyg. 1985;34:1219–1224. doi: 10.4269/ajtmh.1985.34.1219. [DOI] [PubMed] [Google Scholar]
  • 8.Bennett KE, Olson KE, Munoz Mde L, Fernandez-Salas I, Farfan-Ale JA, et al. Variation in vector competence for dengue 2 virus among 24 collections of Aedes aegypti from Mexico and the United States. Am J Trop Med Hyg. 2002;67:85–92. doi: 10.4269/ajtmh.2002.67.85. [DOI] [PubMed] [Google Scholar]
  • 9.Bosio CF, Beaty BJ, Black WC. Quantitative genetics of vector competence for dengue-2 virus in Aedes aegypti. Am J Trop Med Hyg. 1998;59:965–970. doi: 10.4269/ajtmh.1998.59.965. [DOI] [PubMed] [Google Scholar]
  • 10.Miller BR, Mitchell CJ. Genetic selection of a flavivirus-refractory strain of the yellow fever mosquito Aedes aegypti. Am J Trop Med Hyg. 1991;45:399–407. doi: 10.4269/ajtmh.1991.45.399. [DOI] [PubMed] [Google Scholar]
  • 11.Bennett KE, Flick D, Fleming KH, Jochim R, Beaty BJ, et al. Quantitative trait loci that control dengue-2 virus dissemination in the mosquito Aedes aegypti. Genetics. 2005;170:185–194. doi: 10.1534/genetics.104.035634. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Black WC, Bennett KE, Gorrochotegui-Escalante N, Barillas-Mury CV, Fernandez-Salas I, et al. Flavivirus susceptibility in Aedes aegypti. Arch Med Res. 2002;33:379–388. doi: 10.1016/s0188-4409(02)00373-9. [DOI] [PubMed] [Google Scholar]
  • 13.Bosio CF, Fulton RE, Salasek ML, Beaty BJ, Black WC. Quantitative trait loci that control vector competence for dengue-2 virus in the mosquito Aedes aegypti. Genetics. 2000;156:687–698. doi: 10.1093/genetics/156.2.687. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Gomez-Machorro C, Bennett KE, del Lourdes Munoz M, Black WC IV. Quantitative trait loci affecting dengue midgut infection barriers in an advanced intercross line of Aedes aegypti. Insect Mol Biol. 2004;13:637–648. doi: 10.1111/j.0962-1075.2004.00522.x. [DOI] [PubMed] [Google Scholar]
  • 15.Gorrochotegui-Escalante N, Gomez-Machorro C, Lozano-Fuentes S, Fernandez-Salas L, De Lourdes Munoz M, et al. Breeding structure of Aedes aegypti populations in Mexico varies by region. Am J Trop Med Hyg. 2002;66:213–222. doi: 10.4269/ajtmh.2002.66.213. [DOI] [PubMed] [Google Scholar]
  • 16.Gorrochotegui-Escalante N, Munoz ML, Fernandez-Salas I, Beaty BJ, Black WC. Genetic isolation by distance among Aedes aegypti populations along the northeastern coast of Mexico. Am J Trop Med Hyg. 2000;62:200–209. doi: 10.4269/ajtmh.2000.62.200. [DOI] [PubMed] [Google Scholar]
  • 17.Gomez H. Monografia sobre la epidemiologia del dengue [Monograph] Distrito Federal, Mexico: Secretaria de Salud; 1992. pp. 11–59. [Google Scholar]
  • 18.Deubel V, Kinney RM, Trent DW. Nucleotide sequence and deduced amino acid sequence of the structural proteins of dengue type 2 virus, Jamaica genotype. Virology. 1986;155:365–377. doi: 10.1016/0042-6822(86)90200-x. [DOI] [PubMed] [Google Scholar]
  • 19.Diaz FJ, Black WC, Farfan-Ale JA, Lorono-Pino MA, Olson KE, et al. Dengue virus circulation and evolution in Mexico: A phylogenetic perspective. Arch Med Res. 2006;37:760–773. doi: 10.1016/j.arcmed.2006.02.004. [DOI] [PubMed] [Google Scholar]
  • 20.Bennett KE, Beaty BJ, Black WC. Selection of D2S3, an Aedes aegypti (Diptera: Culicidae) strain with high oral susceptibility to Dengue 2 virus and D2MEB, a strain with a midgut barrier to Dengue 2 escape. J Med Entomol. 2005;42:110–119. doi: 10.1603/0022-2585(2005)042[0110:SODAAA]2.0.CO;2. [DOI] [PubMed] [Google Scholar]
  • 21.Gould EA, Buckley A, Cammack N. Use of the biotin-streptavidin interaction to improve flavivirus detection by immunofluorescence and ELISA tests. J Virol Methods. 1985;11:41–48. doi: 10.1016/0166-0934(85)90123-5. [DOI] [PubMed] [Google Scholar]
  • 22.Gould EA, Buckley A, Cammack N, Barrett AD, Clegg JC, et al. Examination of the immunological relationships between flaviviruses using yellow fever virus monoclonal antibodies. J Gen Virol. 1985;66(Pt 7):1369–1382. doi: 10.1099/0022-1317-66-7-1369. [DOI] [PubMed] [Google Scholar]
  • 23.Black WC, DuTeau NM. RAPD-PCR and SSCP analysis for insect population genetic studies. In: Crampton J, Beard CB, Louis C, editors. The Molecular Biology of Insect Disease Vectors: A Methods Manual. New York: Chapman and Hall; 1997. pp. 361–373. [Google Scholar]
  • 24.Salazar MI, Richardson J, Sanchez-Vargas I, Olson K, Beaty B. Dengue virus type 2: replication and tropisms in orally infected Aedes aegypti mosquitoes. BMC Microbiol. 2007;7:9. doi: 10.1186/1471-2180-7-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Agresti A, Coull BA. Approximate is better than “exact” for interval estimation of binomial proportions. Am Stat. 1998;52:119–126. [Google Scholar]
  • 26.Excoffier L, Smouse PE, Quattro JM. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics. 1992;131:479–491. doi: 10.1093/genetics/131.2.479. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Slatkin M. Isolation by distance in equilibrium and nonequilibrium populations. Evolution. 1993;47:264–279. doi: 10.1111/j.1558-5646.1993.tb01215.x. [DOI] [PubMed] [Google Scholar]
  • 28.Sokal RR, Sneath PHA. Principles of Numerical Taxonomy. San Francisco: Freeman; 1963. [Google Scholar]
  • 29.Felsenstein J. Phylogeny Inference Package. Version 3.66 ed. Seattle, WA: University of Washington; 2006. [Google Scholar]
  • 30.Shepard D. A two-dimensional interpolation function for irregularly-spaced data. ACM; 1968. pp. 517–524. [Google Scholar]
  • 31.Wartenberg D, Uchrin C, Coogan P. Estimating exposure using kriging: a simulation study. Environ Health Perspect. 1991;94:75–82. doi: 10.1289/ehp.94-1567973. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Hayashi K. PCR-SSCP: a simple and sensitive method for detection of mutations in the genomic DNA. PCR Methods Appl. 1991;1:34–38. doi: 10.1101/gr.1.1.34. [DOI] [PubMed] [Google Scholar]
  • 33.Orita M, Iwahana H, Kanazawa H, Hayashi K, Sekiya T. Detection of polymorphisms of human DNA by gel electrophoresis as single-strand conformation polymorphisms. Proc Natl Acad Sci U S A. 1989;86:2766–2770. doi: 10.1073/pnas.86.8.2766. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Alaniz-Alvarez SA, Nieto-Samaniego AF, Ferrari L. Effect of strain rate in the distribution of monogenetic and polygenetic volcanism in the Transmexican volcanic belt. Geology. 1998;26:591–594. [Google Scholar]
  • 35.Lozano-Garcia S, Sosa-Najera S, Sugiura Y, Caballero M. 23,000 yr of vegetation history of the Upper Lerma, a tropical high-altitude basin in Central Mexico. Quat Res. 2005;64:70–82. [Google Scholar]
  • 36.Metcalfe SE, O'Hara SL, Caballero M, Davies SJ. Records of Late Pleistocene-Holocene climatic change in Mexico - a review. Quat Sci Rev. 2000;19:699–721. [Google Scholar]
  • 37.Fa JE. Conservation-motivated analysis of mammalian biogeography in the Trans-Mexican Neovolcanic Belt. Natl Geogr Res. 1989;5:296–316. [Google Scholar]
  • 38.Halffter G. Biogeography of the Montane Entomofauna of Mexico and Central-America. Annu Rev Entomol. 1987;32:95–114. [Google Scholar]
  • 39.Huidobro L, Morrone JJ, Villalobos JL, Alvarez F. Distributional patterns of freshwater taxa (fishes, crustaceans and plants) from the Mexican Transition Zone. J Biogeogr. 2006;33:731–741. [Google Scholar]
  • 40.Lozano-Fuentes S. Aedes aegypti vector competence and gene flow in Mexico. Association mapping software for testing candidates genes associated with a phenotype. [Dissertation] Fort Collins, Colorado: Colorado State University; 2004. [Google Scholar]
  • 41.Ibanez-Bernal S, Gomez-Dantes H. Vectors of dengue in Mexico: a critical review). Salud Publica Mex. 1995;37(Suppl):S53–S63. [PubMed] [Google Scholar]
  • 42.Edman JD, Scott TW, Costero A, Morrison AC, Harrington LC, et al. Aedes aegypti (Diptera : Culicidae) movement influenced by availability of oviposition sites. J Med Entomol. 1998;35:578–583. doi: 10.1093/jmedent/35.4.578. [DOI] [PubMed] [Google Scholar]
  • 43.Harrington LC, Scott TW, Lerdthusnee K, Coleman RC, Costero A, et al. Dispersal of the dengue vector Aedes aegypti within and between rural communities. Am J Trop Med Hyg. 2005;72:209–220. [PubMed] [Google Scholar]
  • 44.Huber K, Le Loan L, Chantha N, Failloux AB. Human transportation influences Aedes aegypti gene flow in Southeast Asia. Acta Trop. 2004;90:23–29. doi: 10.1016/j.actatropica.2003.09.012. [DOI] [PubMed] [Google Scholar]
  • 45.Lounibos LP. Invasions by insect vectors of human disease. Annu Rev Entomol. 2002;47:233–266. doi: 10.1146/annurev.ento.47.091201.145206. [DOI] [PubMed] [Google Scholar]
  • 46.Tabachnick WJ. The yellow fever mosquito: evolutionary genetics and arthropod-borne disease. Am Entomol. 1991;37:14–24. [Google Scholar]
  • 47.Tabachnick WJ, Powell JR. A world-wide survey of genetic variation in the yellow fever mosquito, Aedes aegypti. Genet Res. 1979;34:215–229. doi: 10.1017/s0016672300019467. [DOI] [PubMed] [Google Scholar]
  • 48.Gorrochotegui-Escalante N, Lozano-Fuentes S, Bennett KE, Molina-Cruz A, Beaty BJ, et al. Association mapping of segregating sites in the early trypsin gene and susceptibility to dengue-2 virus in the mosquito Aedes aegypti. Insect Biochem Mol Biol. 2005;35:771–788. doi: 10.1016/j.ibmb.2005.02.015. [DOI] [PubMed] [Google Scholar]
  • 49.Powell JR, Tabachnick WJ, Arnold J. Genetics and the origin of a vector population: Aedes aegypti, a case study. Science. 1980;208:1385–1387. doi: 10.1126/science.7375945. [DOI] [PubMed] [Google Scholar]
  • 50.Sylla M, Bosio C, Urdaneta-Marquez L, Ndiaye M, Black WC IV. Gene flow, subspecies composition, and dengue virus-2 susceptibility among Aedes aegypti collections in Senegal. PLoS Negl Trop Dis. 2009;3:e408. doi: 10.1371/journal.pntd.0000408. doi:10.1371/journal.pntd.0000408. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Scott A, Bernhardt CB, Sylla M, Bosio C, Black WC., IV Evidence of multiple chromosomal inversions in Aedes aegypti formosus from Senegal. Insect Mol Biol. 2009 doi: 10.1111/j.1365-2583.2009.00895.x. In press. [DOI] [PubMed] [Google Scholar]
  • 52.Navarrete-Espinosa J, Acevedo-Vales JA, Huerta-Hernández E, Torres-Barranca J, Gavaldón-Rosas DG. Prevalencia de anticuerpos contra dengue y leptospira en la población de Jáltipan, Veracruz. Salud Publica Mex. 2006;48:220–228. doi: 10.1590/s0036-36342006000300006. [DOI] [PubMed] [Google Scholar]

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Supplementary Materials

Alternative Language Abstract S1

Translation of the Abstract into Spanish by Saul Lozano-Fuentes

(0.03 MB DOC)


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