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High morphological and genetic variabilities of Ochlerotatus scapularis, a potential vector of filarias and arboviruses
research-article
Publication date (Electronic):
26 February 2015
Journal:
Parasites & Vectors
Publisher:
BioMed Central
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Abstract
Background
Ochlerotatus scapularis is a potential vector of filarias and arboviruses in the Neotropics. This species was once typically associated with sylvatic environments; however, cases of synanthropy and urbanization of this species have been increasingly reported in southeast Brazil. Despite the medical relevance of Oc. scapularis, its populational variability is not yet known. To our knowledge, this is the first report describing the morphological and genetic variabilities of this species.
Methods
Population samples were characterized using the cytochrome oxidase subunit I (COI) mitochondrial gene and wing geometrics. Adult mosquitoes were collected from five sampling sites from remnants of the Atlantic forest embedded in the urban or rural areas of southeast Brazil.
Results
In the 130 individuals analyzed, 46 COI haplotypes were detected. Haplotype diversity was high and ranged from 0.66 to 0.97. Six haplotypes were present in 61% of the individuals, whereas the remaining haplotypes were less frequent (39%). Wing shape was also highly polymorphic. Differentiation of populations across sampling sites according to genetic distances (F st = −0.009 to 0.060) and morphological distances (Q st = 0.47) indicated that populations were not identical. No correlations were noted for phenetic and genetic diversities (p = 0.19) or for genetic or phenetic distances with geographical distances (p = 0.2 and p = 0.18, respectively).
Related collections
Most cited references41
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Morphometrics applied to medical entomology.
Jean-Claude Dujardin (2008)
Morphometrics underwent a revolution more than one decade ago. In the modern morphometrics, the estimate of size is now contained in a single variable reflecting variation in many directions, as many as there are landmarks under study, and shape is defined as their relative positions after correcting for size, position and orientation. With these informative data, and the corresponding software freely available to conduct complex analyses, significant biological and epidemiological features can be quantified more accurately. We discuss the evolutionary significance of the environmental impact on metric variability, mentioning the importance of concepts like genetic assimilation, genetic accommodation, and epigenetics. We provide examples of measuring the effect of selection on metric variation by comparing (unpublished) Qst values with corresponding (published) Fst. The primary needs of medical entomologists are to distinguish species, especially cryptic species, and to detect them where they are not expected. We explain how geometric morphometrics could apply to these questions, and where there are deficiencies preventing the approach from being utilized at its maximum potential. Medical entomologists in connection with control programs aim to identify isolated populations where the risk of reinfestation after treatment would be low ("biogeographical islands"). Identifying them can be obtained from estimating the number of migrants per generation. Direct assessment of movement remains the most valid approach, but it scores active movement only. Genetic methods estimating gene flow levels among interbreeding populations are commonly used, but gene flow does not necessarily mean the current flow of migrants. Methods using the morphometric variation are neither suited to evaluate gene flow, nor are they adapted to estimate the flow of migrants. They may provide, however, the information needed to create a preliminary map pointing to relevant areas where one could invest in using molecular machinery. In case of reinfesting specimens after treatment, the question relates to the likely source of reinfesting specimens: are they a residual sample not affected by the control measures, or are they individuals migrating from surrounding, untreated foci? We explain why the morphometric approach may be adapted to answer such question. Thus, we describe the differences between estimating the flow of migrants and identifying the source of reinfestation after treatment: although morphometrics is not suited to deal with the former, it may be an appropriate tool to address the latter.
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Tracing the Tiger: Population Genetics Provides Valuable Insights into the Aedes (Stegomyia) albopictus Invasion of the Australasian Region
Nigel Beebe, Luke Ambrose, Lydia Hill … (2013)
Introduction The Asian tiger mosquito Aedes (Stegomyia) albopictus, originally described by Skuse from Calcutta, India, in 1894, is considered native to the Southeast Asian region where the larvae are often found in forest tree holes – a characteristic that assists its current global expansion via rapid adaptation to human-made container habitats [1], [2], [3]. This global expansion is also driven by human behavior, often facilitated by the transport of used tyres that contain desiccation-resistant eggs or, in some cases, by the movement of the containers themselves [4], [5]. Prior to the 1980s, Ae. albopictus had spread to several islands in the Indian Ocean, as well as to the Hawaiian Islands in the Pacific [6]. It was discovered in Albania in Europe in 1979 [7], and has also established in both North [8] and South America [9], in Africa in 1992 [10], and in southern Europe [11]. It is currently expanding into over 20 European countries [2]. Alongside this species' global expansion, its status as a vector of human pathogens is also of increasing concern. As a laboratory vector of over 25 arboviruses, its role in arbovirus transmission cycles has mostly been secondary to other incriminated vectors [12], [13], [14]. In the absence of the primary dengue vector, Aedes (Stegomyia) aegypti, Ae. albopictus has been the epidemic vector of dengue viruses in Hawaii, Macao and China [14], [15], [16], [17]. In 2005, it was implicated as the epidemic vector during a resurgence of chikungunya (CHIKV), an alpha virus clinically similar to dengue, in the Indian Ocean and in Italy [17], [18], [19]. Subsequent studies revealed that Ae. albopictus is highly susceptible to the CHIKV, with the species not only responsible for these outbreaks but also able to transmit the virus after only two days [17], [20], [21]. In the Australasian region, Ae. albopictus was first detected in 1963 in Jayapura on the West Papua Province of Indonesia (see Fig. 1A). Subsequent surveys during the early 1970s confirmed its presence in northern Papua New Guinea (PNG) near Madang [22], [23]. By 1980 it had arrived in southern PNG's Port Moresby (PNG's capital), and moved eastwards into Bougainville Province and the Solomon Islands [24], [25]. Its detection in southern PNG's Western Province southern Fly River coastal fringe in 1988 (see Fig. 1B), combined with surveys in 1992 revealing it on Daru Island in the northern Torres Strait region and in Kiunga Port over 700 km up the Fly River, established beyond doubt that the species was extant just 150 km from mainland Australia's Cape York [24], [26]. Despite there being at least 28 collections of Ae. albopictus at six Australian seaports, this species has not yet established on Australia's mainland [27]. 10.1371/journal.pntd.0002361.g001 Figure 1 Map of the region under study and mosquito collection sites (Panel A). An expanded view of the region inhabited by the recently introduced Ae. albopictus population (red box) with collection sites indicated in Panel B. Colored triangles correspond to sample locations. In 2005, Ae. albopictus was detected on Masig Island in the central Torres Strait Islands and molecular identification of previously collected Ae. albopictus larvae [28] (which discriminated it from local Ae. scutellaris species), dated its arrival to 2004. Subsequent surveys in the Torres Strait revealed its presence on 10 of the 17 inhabited islands [29]. Considering the potential of both the human health and societal (nuisance) impacts of Ae. albopictus establishing on mainland Australia, the obvious question was why Ae. albopictus had only expanded into the Torres Strait Islands in 2004–05 when it was known to have been extant on Daru Island (northern Torres Strait) and in Kiunga in 1992 – 12 years earlier? A number of potential sociological and ecological factors may have contributed to the mosquitoes' proliferation and led to its dramatic expansion into the Torres Strait islands in the mid-2000s. For example, the increase in human-made water storage containers and sundry smaller discarded disposable containers may have served as potential larval habitats, leading to a population expansion. The discovery of Ae. albopictus in the Torres Strait in the mid 2000s led to the question of whether recent adaptation to climatic variability had played a role in its expansion – as we had suggested in earlier work on other container inhabiting Aedes species in this region [30]. The 1997–98 El Nino conditions contributed to the worst drought in PNG for 100 years: traditional groundwater supplies were greatly affected, either drying up or becoming contaminated [31]. As local springs and streams dried up, it became necessary for villages to store water in large containers including 220 L (44 gal) drums and rainwater tanks – both of which provide highly productive larval sites for container-inhabiting mosquito species [32]. As part of an international aid response, AusAID funded and transported 9,000 L polypropylene rainwater tanks and 200 L water containers to the southern Fly River region villages immediately adjacent to the Torres Strait in a project completed in 2002 [33], [34]. This human adaptation to climate variability may have provided abundant productive larval sources for the population of Ae. albopictus already present in PNG, leading to its rapid population expansion and a subsequent spillover into the Torres Strait Islands. Once Ae. albopictus was established on the islands, the continuous human ocean traffic would have rapidly shuttled mosquitoes through the region. Thus our working hypothesis was that climate variability driven by the 1997–98 El Nino resulted in water storage management changes in PNG's southern Fly River coastal villages and was indirectly responsible for the invasion of a local Ae. albopictus population through the Torres Strait Islands. In this study, we use extensive regional mosquito collections and population genetics methodologies to investigate the origins and dynamics of the introduction of Ae. albopictus into and through the Torres Strait islands, as well as the population structure of this species throughout PNG. The maternally inherited mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) is used as both a population genetics marker and a proxy for female movement between islands and southern PNG villages. The rationale here is that the DNA sequence of each female is (barring mutation) identical to that of her offspring, providing insights into the dynamics and diversity of the females' contribution to each population. This proxy would ultimately be an underestimate of movement as different females of the same sequence cannot be distinguished. Additionally, we developed and ran 13 microsatellites markers that permitted the evaluation of the nuclear background of these mosquitoes. Materials and Methods Mosquito samples Container-inhabiting mosquitoes were collected from throughout the Torres Strait and PNG's southern Fly River region villages by Queensland Health between 2004 and 2010 (Tables 1 and 2, and Figure 1). Populations of Ae. albopictus collected in 1992 from Daru Island (northeastern Torres Straits) and the Kiunga Port area in Western Province were provided by the Australian Defence Force. When samples were collected from private residences, permission was granted prior to entry. In most cases larvae were sampled from different containers at each location and preserved in 70% ethanol, and in some cases adults were collected. In many cases only a few individuals were collected at each location in order to reduce the chance of sampling siblings (as larvae in the same container). Larvae were initially identified as Ae. albopictus using the morphological keys of [35] and then by either real-time PCR assays [36] or by a PCR-restriction digest procedure [28] to distinguish them from endemic members of the Aedes (Stegomyia) scutellaris taxonomic group. 10.1371/journal.pntd.0002361.t001 Table 1 Summary of mtDNA COI study collection sites and haplotype distribution. Region Site Year Haplotypes 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Totals PNG Southern Fly Buzi 2007 1 1 2 Ber 2007 3 4 7 Sigabaduru 2007 7 1 8 Mabaduan 2007 7 6 7 2 22 Ture Ture 2007 5 1 6 Katatai 2007 3 2 1 6 Dorogori 2007 1 2 1 4 Parama 2007 5 3 4 12 Torres Strait Nth Eurb 2006 3 2 2 1 4 12 Ugar 2006 8 1 1 10 Masig 2006, 2007 4 4 2 4 14 Mer 2007 2 2 Torres Strait Central Poruma 2007 8 1 9 Mabuiag 2007 1 2 3 Badu 2007 2 1 4 1 8 Moa 2007 1 7 8 Warraber 2007 2 2 6 10 Torres Strait South Waiben 2010 4 3 7 Ngarupai 2010 1 16 1 6 1 2 27 Muralag 2010 2 1 3 Cape York New Marpoon 2010 2 2 PNG Daru 1992, 2008 29 1 1 2 1 1 35 PNG Kiunga 1992 34 1 3 38 PNG Port Moresby 1997, 1998 41 1 12 1 3 58 PNG Madang/Lae 2011/1996 29 10 39 Indonesia Timor Leste 2001 23 1 17 Indonesia Jakarta 2011 7 1 8 Totals 134 2 1 1 2 94 1 1 1 20 70 21 1 5 22 1 377 10.1371/journal.pntd.0002361.t002 Table 2 Mosquito sampling summary for microsatellite study. Region Site Year n PNG Southern Fly Kulalai 2007 2 Sigabaduru 2007 1 Katatai 2007 2 Mabudauan 2007 7 Torres Strait North Masig 2006/2007 21 Mer 2007 6 Torres Strait Central Mabuiag 2007 10 Warraber 2007 8 Torres Strait South Waiben 2010 3 Ngarupai 2010 7 Muralag 2010 5 PNG Daru 1992, 2008 26 Kiunga 1992 20 Port Moresby 1997, 1998 29 Madang/Lae 2011, 1996 33 Indonesian region Timor Leste 2001 10 Jakarta 2011 9 mtDNA sequencing and analyses Specimens identified as Ae. albopictus had genomic DNA extracted using a salt extraction method [37]. For PCR amplification of a 445 bp (final edited product size) region of the mtDNA cytochrome oxidase 1 (COI), the forward primer 5′ CAY CCT GGT ATA TTT ATT GG ′3 and reverse primer 5′AAT TAA AAT ATA AAC TTC TGG were modified from [38]. The reaction was carried out in 0.2 ml well PCR plates (Astral Scientific) using 25 µl final volume and oil overlay (single drop). Final PCR mixture contained 16.6 mM [NH4]2SO4, 67 mM Tris-HCl pH 8.8 (at 25°C), 0.45% Triton X-100, 0.2 mg/ml gelatin, 1.5 mM MgCl, 0.2 mM of each dNTP, 0.4 µM of each primer. One unit of Taq polymerase (Bioline) and 2–10 ng of purified genomic DNA (1 µl of gDNA) were used per reaction. Cycling (MJ research PTC200 or a BioRad C-1000 thermal cycler) was 94°C for 3 min followed by 30 cycles of 94°C for 1 min, 40°C for 1 min, and 72°C for 1 min using minimum transition times between steps. The PCR products were visualized on a 1% agarose gel containing 0.5 µg/ml ethidium bromide and visualized at 312 nm. PCR product purification was via QIAGEN (QIAquick) PCR purification columns using manufactures recommendations. All sequences were edited and aligned using the Geneious software [39]. To examine phylogeographic relationships, we constructed maximum parsimony haplotype networks in TCS 1.21 [40] under a 95% connection limit. Pair-wise F ST values were estimated in Arlequin version 3.5 (distance method) [41] to assess levels of differentiation between the regions for the COI locus: regions were designated Torres Strait Islands (excluding Daru Island), southern Fly region, Daru Island, Kiunga, Port Moresby, Madang/Lae Region, Timor Leste and Jakarta. The significance levels of F ST comparisons were assessed using permutation tests (1,023 permutations per comparison), also implemented in Arlequin. DnaSP 5 [42] was used to estimate haplotype diversity and nucleotide diversity within regions. We performed Tajima's D and Fu's Fs tests of neutrality for the COI data per population in the program Arlequin. Microsatellite development and population genetics analyses Candidate microsatellite markers were isolated from Roche GS FLX 454 sequencing data (1/16 plate - 25,000 reads at ∼400 bp length) generated from genomic DNA of Ae. albopictus and performed by Macrogen (Korea). To design primers for microsatellite loci, we ran the resultant data through the program msatcommander [43]. We used this program to find primers for dinucleotide, trinucleotide and tetranucleotide repeats, and allowed the program to design primers with a melting temperature in the range of 50–62°C with a GC content between 30 and 70 percent. Long polynucleotide repeats (>5 bp) within sequences to be amplified were avoided and duplicate markers (i.e. primers designed for sequence analogues) were excluded. Screening of candidate markers involved PCR amplification of a subset of samples using standard primers and visualization of products on 1% ethidium bromide stained agarose gels. Positive product primer sets were re-amplified with M13 labeled forward primers and dyes (VIC, FAM, PET and NED) and standard reverse primers. The final PCR mixture contained 1× Mytaq buffer (Bioline)(containing pre-optimized concentrations of MgCl and dNTPs), 0.4 µM of each primer, 0.5–1.0 unit of MyTaq polymerase (Bioline) and 5.0–10.0 ng of extracted genomic DNA (1 µl of extraction). The cycling involved an initial denaturation of 95°C for 3 min, then 13 cycles of 95°C for 30 s, 56°C for 40 s with a gradient decrease of 0.5°C/cycle, and 72°C for 30 s, followed by 25 cycles of 95°C for 30 s, 50°C for 40 s and 72°C for 30 s, and a final 72°C for 5 min using minimum transition times. M13 labeled products for 13 microsatellite markers (see Table 3 for details) that generated clean peaks and that amplified consistently were purified using ExoSap (Antarctic phosphatase and Exonuclease I-New England Biolab) and were sent to Macrogen (Macrogen, Geumchun-gu, Seoul, Korea) for genotyping. We attempted to genotype 199 individuals sampled from the Torres Strait Islands, New Guinea, Timor Leste and Jakarta (see Table 2 for sampling information). 10.1371/journal.pntd.0002361.t003 Table 3 Microsatellite primer and allelic information. #Alleles Size Range (bp) Forward Reverse Genbank Alb-di-4 14 166–200 TGGCGACCTATTATACCCGC CAACTCGTTCCTTGACCGTG KF146971 Alb-di-6 11 268–290 TCTTCATCTACGCTGTGCTC GACGCCAATCCGACAAAGTC KF146972 Alb-tri-3 9 123–153 AGATGTGTCGCAATGCTTCC GATTCGGTGATGTTGAGGCC KF146973 Alb-tri-6 17 164–219 AGCACGAGTACAGAATGTGC TGGCCTCCTACCGTTTATCTG KF146974 Alb-tri-18 10 250–280 ACACAATTGCCGTTCAGCTC CGTCTAATAGCTCCGGTCCC KF146975 Alb-tri-20 15 165–201 GTGCCGTTGATCATCCTGTC TCCAGCACCGTGAGTAATCC KF146976 Alb-tri-21 17 137–206 AGGGCTTCAATGGGTCTCTC TGGTTATTAATACGGCGAGGC KF146977 Alb-tri-25 8 257–278 CCAACCAACAACCCAGGAAC TACGATGCGCAACCATCATC KF146978 Alb-tri-33 11 137–182 GGCTGCTGTTGTTGGTACG CACGTTCAATCACCGGTTCC KF146979 Alb-tri-41 8 134–155 GATCGATTTGGGAGCTTCTG GAACCTCTTCTCGCTTGGCT KF146980 Alb-tri-44 10 173–212 CACTCGCGCGTGTTCTTC GACGCACCATCAGCATCATC KF146981 Alb-tri-45 9 120–150 TTTCAGCTCGGTGTTATGGC TGATGTTGATGATGATGACTACGA KF146982 Alb-tri-46 10 158–192 TTCACAACATACGGAATCGC GGTCCGGTGTAATAGCCTCC KF146983 Alleles for each marker were scored manually in the program GeneMarker [44]. We checked for the possible presence of null alleles for each marker at a population level (based on the regions: Torres Strait, Fly Region, Daru, Kiunga, Madang, Port Moresby, Timor Leste and Jakarta) using the program MICRO-CHECKER [45]. Using these same population definitions, we checked for HWE, as well as calculating observed (Ho) and expected (He) heterozygosity in the program GenAlEx, v6 [46] and the program GenoDive [47] was used to calculated Fis for each population (Table 4 contains details of Null Alleles, HWE, etc). 10.1371/journal.pntd.0002361.t004 Table 4 Characteristics of microsatellite markers per population. Torres Strait (n = 60) Fly Region PNG (n = 12) Daru (n = 26) Kiunga (n = 20) Locus HWE, Null, % missing [Na, Fis] (Ho, He) HWE, Null, % missing [Na, Fis] (Ho, He) HWE, Null, % missing [Na, Fis] (Ho, He) HWE, Null, % missing [Na, Fis] (Ho, He) DI-4 n, y, 0 [5, 0.505] (0.233, 0.465) n, y, 8 [5, 0.623] (0.182, 0.446) y, n, 4 [5, 0.110] (0.520, 0.571) n, y, 10 [3, 0.585] (0.222, 0.512) DI-6 n, y, 5 [8, 0.491] (0.368, 0.700) y, y, 0 [6, 0.675] (0.250, 0.715) n, y, 0 [7, 0.355] (0.385, 0.581) n, n, 5 [4, 0.324] (0.368, 0.526) TRI-3 n, y, 0 [7, 0.522] (0.300, 0.661) y, n, 0 [3, 0.267] (0.417, 0.538) y, n, 0 [5, 0.166] (0.538, 0.631) y, y, 0 [4, 0.575] (0.300, 0.679) TRI-6 n, n, 10 [12, 0.083] (0.630, 0.680) y, n, 8 [5, 0.200] (0.636, 0.752) n, y, 16 [6, 0.512] (0.364, 0.720) n, y, 30 [6, 0.644] (0.286, 0.755) TRI-18 n, y, 22 [6, 0.716] (0.213, 0.737) y, y, 50 [4, 0.792] (0.167, 0.681) y, n, 4 [6, 0.248] (0.520, 0.674) y, y, 35 [7, 0.544] (0.385, 0.793) TRI-20 n, y, 0 [13, 0.421] (0.483, 0.825) y, y, 8 [7, 0.459] (0.455, 0.785) y, n, 0 [8, 0.012] (0.769, 0.763) n, y, 10 [4, 0.812] (0.111, 0.562) TRI-21 n, y, 22 [9, 0.650] (0.277, 0.776) n, y, 17 [7, 0.744] (0.200, 0.805) n, y, 8 [5, 0.939] (0.042, 0.652) n, n, 30 [3, 0.235] (0.286, 0.357) TRI-25 y, n, 0 [5, 0.166] (0.517, 0.614) y, n, 8 [7, 0.221] (0.545, 0.661) y, y, 0 [5, 0.361] (0.500, 0.763) y, n, 75 [3, 0] (0.600, 0.540) TRI-33 y, n, 0 [7, 0.093] (0.683, 0.747) y, n, 8 [4, 0.277] (0.545, 0.711) n, n, 4 [7, 0.199] (0.560, 0.682) y, n, 5 [6, 0.238] (0.579, 0.735) TRI-41 n, y, 3 [6, 0.425] (0.345, 0.593) y, n, 8 [4, 0.469] (0.273, 0.479) y, n, 4 [2, 0.134] (0.440, 0.497) y, n, 5 [2, 0.345] (0.316, 0.465) TRI-44 n, y, 8 [7, 0.433] (0.436, 0.760) y, n, 17 [5, −0.091] (0.800, 0.700) y, n, 0 [5, −0.004] (0.654, 0.639) y, y, 5 [5, 0.396] (0.368, 0.587) TRI-45 y, n, 2 [6, 0.013] (0.542, 0.545) y, y, 8 [7, 0.394] (0.455, 0.702) y, n, 0 [6, −0.122] (0.846, 0.741) y, n, 0 [3, 0.150] (0.550, 0.629) TRI-46 y, n, 3 [6, 0.002] (0.621, 0.617) y, n, 8 [4, 0.161] (0.545, 0.616) n, y, 12 [3, 0.588] (0.261, 0.612) y, n, 30 [3, 0.444] (0.286, 0.487) Madang (n = 33) Port Moresby (n = 29) Timor Leste (n = 10) Jakarta (n = 9) Locus HWE, Null, % missing [Na, Fis] (Ho, He) HWE, Null, % missing [Na, Fis] (Ho, He) HWE, Null, % missing [Na, Fis] (Ho, He) HWE, Null, % missing [Na, Fis] (Ho, He) DI-4 n, y, 0 [7, 0.543] (0.273, 0.583) y, y, 4 [4, 0.475] (0.214, 0.397) y, n, 0 [4, 0.463] (0.200, 0.345) y, n, 0 [4, −0.247] (0.667, 0.512) DI-6 n, y, 0 [7, 0.291] (0.515, 0.712) y, y, 0 [4, 0.496] (0.345, 0.666) n, y, 0 [6, 0.755] (0.200, 0.745) y, n, 0 [3, −0.032] (0.222, 0.204) TRI-3 n, y, 0 [7, 0.277] (0.485, 0.657) y, y, 0 [5, 0.284] (0.552, 0.753) n, n, 0 [4, 0.550] (0.300, 0.615) y, y, 11 [4, 0.844] (0.125, 0.711) TRI-6 n, y, 0 [9, 0.469] (0.424, 0.781) y, y, 0 [9, 0.458] (0.448, 0.806) y, y, 10 [6, 0.484] (0.444, 0.790) y, y, 0 [7, 0.508] (0.444, 0.827) TRI-18 y, n, 0 [7, 0.144] (0.667, 0.765) y, n, 4 [8, 0.212] (0.643, 0.798) y, y, 0 [5, 0.628] (0.300, 0.740) y, y, 22 [4, 0.829] (0.143, 0.724) TRI-20 n, n, 0 [10, 0.171] (0.667, 0.790) n, n, 0 [8, 0.076] (0.655, 0.696) y, n, 0 [7, 0.027] (0.800, 0.780) y, n, 0 [5, −0.028] (0.778, 0.716) TRI-21 n, y, 3 [9, 0.581] (0.313, 0.728) n, y, 0 [6, 0.647] (0.276, 0.759) y, n, 40 [4, 0.592] (0.333, 0.708) y, n, 0 [3, 0.273] (0.333, 0.426) TRI-25 y, n, 0 [5, 0.153] (0.606, 0.703) n, n, 4 [6, 0.090] (0.679, 0.732) y, n, 0 [6, 0.176] (0.600, 0.685) y, n, 11 [5, 0.103] (0.625, 0.648) TRI-33 y, n, 0 [7, 0.070] (0.636, 0.673) y, n, 0 [5, 0.190] (0.552, 0.667) y, n, 0 [4, 0.069] (0.600, 0.610) y, n, 0 [5, −0.013] (0.556, 0.519) TRI-41 n, y, 0 [4, 0.501] (0.273, 0.534) n, y, 4 [6, 0.265] (0.500, 0.665) y, n, 10 [4, 0.489] (0.333, 0.599) y, n, 0 [5, 0.461] (0.333, 0.568) TRI-44 n, n, 0 [5, 0.098] (0.485, 0.528) n, n, 0 [6, 0.157] (0.448, 0.521) y, n, 0 [5, −0.008] (0.700, 0.660) y, n, 11 [3, −0.105] (0.375, 0.320) TRI-45 y, n, 0 [5, −0.120] (0.758, 0.668) y, n, 0 [5, 0.073] (0.724, 0.766) y, n, 0 [5, −0.220] (0.800, 0.630) y, n, 0 [3, −0.212] (0.556, 0.438) TRI-46 n, y, 0 [7, 0.445] (0.333, 0.587) n, y, 10 [5, 0.632] (0.269, 0.709) y, n, 0 [5, 0.085] (0.600, 0.620) y, n, 0 [4, 0] (0.778, 0.735) The Bayesian program STRUCTURE, v. 2.3.2 [48], [49], was used to infer the most likely number of genetically distinct groups (K) in the region sampled, based on the microsatellite data. STRUCTURE was run using the admixture model, and using sampling locations as priors. Including information on sampling locations in STRUCTURE analyses has been shown to be useful for detecting subtle genetic structure, without detecting structure that is not present [48]. Due to the potential presence of null alleles at a number of markers in some populations, we used a dominant marker model in STRUCTURE (as recommended in the user manual). STRUCTURE was run for five iterations of K = 2 to K = 8, for a total of 1 million generations per iteration with a burn-in of 200 000 iterations. STRUCTUREHARVESTER, a program that implements the Evanno et al. Delta K method [50], [51], was then used to infer the most likely value of K and CLUMPP v. 1.1.2 [52] was used to average the results of the replicates for K = 5 (the most likely value based on the Delta K method). We used the Greedy algorithm in CLUMPP with 1000 repeats. The output from CLUMPP was run through DISTRUCT [53], which provides more flexibility in generating figures than STRUCTURE. Additionally, the program GENETIX v. 4.05 [54] was used to perform a Factorial Correspondence Analysis (FCA). FSTAT v2.9.3 [55] was used to test for linkage disequilibrium between loci, and finally Arlequin v.3.5 [41] was used to estimate pair-wise F ST values between the eight populations defined above. Results Mitochondrial DNA A total of 16 mtDNA COI haplotypes were identified from 377 individuals (haplotype diversity Hd = 0.769) collected throughout the southern Fly River villages, the Torres Strait islands, north and south PNG, Timor Leste and Jakarta – 10 of these haplotypes were present in the Torres Strait Islands and southern Fly River region (see Table 1 and Fig. 1 for details on collections and mtDNA haplotype occurrence). All DNA sequences are available through GenBank (KC572145 - KC572496, KF042861-KF042885) and all tests of neutrality (Tajima's D and Fu's Fs) were non-significant. Haplotype diversity varied for each region with the Torres Strait Islands (122 individuals, 10 haplotypes, Hd = 0.801) and southern Fly River region (60 individuals, 6 haplotypes, Hd = 0.649) having substantially higher haplotype diversities than the PNG populations from Daru Island (35 individuals, 6 haplotypes, Hd = 316), Kiunga (38 individuals, 3 haplotypes, Hd = 0.198), Port Moresby (58 individuals, 5 haplotypes, Hd = 0.462) and Madang/Lae Region (39 individuals, 2 haplotypes, Hd = 0.391) as well as those from Timor Leste (17 individuals, 2 haplotypes, Hd = 0.118) and Jakarta (8 individuals, 2 haplotypes, Hd = 0.250). The COI haplotype network (Figure 2) suggests that there is some mitochondrial genetic structure between regions, with one of the most common haplotypes (H1) sampled found predominantly in the populations extant in PNG (the Madang/Lae region, Port Moresby, Kiunga and Daru Island – with Daru collections from both 1988 and 2008), and only being sampled once (in one individual) in the Torres Strait Islands. The other common PNG haplotype (H6) was sampled at relatively high frequency in the Torres Strait. Two other haplotypes (H11 and H12) that were sampled relatively commonly in both the Torres Strait and in the Fly Region of PNG were also sampled in Daru. Haplotype 11 was also the most predominant haplotype sampled in both of the Indonesian populations (Jakarta and Timor Leste), with Timor Leste also sharing H12 and Jakarta possessing one other private haplotype (H16). This suggests that there is a close affinity between Indonesian populations and those found in the Fly Region of PNG as well as those in the Torres Strait. Six private haplotypes were sampled in the Fly Region/Torres Strait (H7, H9, H10, H13, H14, H15), three of which were only found singly in Torres Strait (H7, H9, H13) and there were 5 private haplotypes sampled in PNG; H2, H4 and H5 found only in Daru; with H3 and H8 found only in Port Moresby. 10.1371/journal.pntd.0002361.g002 Figure 2 Mitochondrial COI haplotype network showing the 16 haplotypes identified throughout PNG and the Australian region. Haplotypes are colored by region and the size of their circle is proportional to number of individuals showing that haplotype sequence with each connection a single mutational step. Mitochondrial COI pair-wise F ST relationships and significance comparisons supported the presence of structure between populations (see Table 5). Again the PNG Southern Fly Region and Torres Strait populations appeared highly distinct from the PNG populations with high and significant F ST values between the populations (roughly between 0.4 to 0.5). The F ST value between Torres Strait and Fly Region populations is significant but small (0.043), and most comparisons between PNG populations are non-significant (all F ST<0.1). Indonesian populations are not significantly differentiated from each other but have significant F ST values in all other comparisons, with the Torres Strait populations being the most closely related to them, followed by the Fly Region and then by PNG populations. 10.1371/journal.pntd.0002361.t005 Table 5 Pairwise COI F ST values (bold = non-significant). Torres Strait Fly Region Daru Kiunga Port Moresby Madang Timor Leste Fly Region 0.04294 Daru 0.46207 0.46889 Kiunga 0.47707 0.50317 −0.00658 Port Moresby 0.44540 0.43966 0.02975 0.04464 Madang 0.46563 0.47669 0.03726 0.06915 −0.01029 Timor Leste 0.12338 0.30382 0.81124 0.86803 0.80658 0.89127 Jakarta 0.09859 0.26626 0.77880 0.84574 0.78493 0.87307 0.02812 Microsatellites A total of 199 individuals were genotyped for the 13 microsatellites (see Table 2 for mosquito sampling). Putative null alleles were found at some loci in some populations and tests for Hardy Weinberg equilibrium revealed that some loci did not meet the expectations of this model (see Table 4 for detailed information), but no evidence of linkage disequilibrium between loci was found. The overall number of alleles per locus ranged from 8 to 17 (Table 3). The inbreeding coefficients (FIS) of the majority of loci were positive, and observed heterozygosity was less than expected heterozygosity in most cases, indicating an excess of homozygote genotypes at most loci (see Table 4). Although F ST values are generally smaller for the microsatellite data than for the mitochondrial data (Tables 5 & 6), all microsatellite based pair-wise F ST values between populations were significant, with the exception of the Torres Strait – Fly Region comparison (F ST = 0.00421, Table 6). Low F ST values were found between PNG populations, as well as between Torres Strait/Fly Region populations and those from Indonesia, providing further evidence of close affinities between these populations. 10.1371/journal.pntd.0002361.t006 Table 6 Pairwise F ST msats: 13 loci (bold = non-significant). Torres Strait Fly Region Daru Kiunga Madang Port Moresby Timor Leste Fly Region 0.00421 Daru 0.15061 0.13217 Kiunga 0.14283 0.16632 0.07760 Madang 0.15134 0.13189 0.03805 0.07871 Port Moresby 0.12791 0.11830 0.09477 0.05612 0.08168 Timor Leste 0.10243 0.07446 0.15200 0.11821 0.15745 0.08435 Jakarta 0.13908 0.12848 0.25316 0.26416 0.24757 0.20855 0.11396 The most likely number of genetic clusters (K) inferred by STRUCTURE HARVESTER was K = 5 [50], [51]. The bar plot generated in STRUCTURE (Fig. 3) suggests five populations (Figure 3) with three historically extant populations within PNG that may have experienced various levels of admixture, and one distinct population encompassing the Torres Strait Islands and the southern Fly River region (purple). An additional population was found in Indonesia (pink), and bar-plots suggest some similarity of these populations to some individuals in the Torres Strait and Fly Region. The populations from Daru Island (collected in 1992 and 2008), which sits geographically adjacent to the southern Fly River coastal region, are clearly differentiated from the introduced populations, with all individuals from these regions being assigned with high probability to a single population (green). Samples from Kiunga are assigned with high probability to a distinct cluster (red) to which individuals from Port Moresby are also partially assigned, although these (Port Moresby) individuals are also assigned to another cluster (yellow) with higher probability. Individuals from Madang in northern PNG are assigned with highest probability to the green cluster (mostly found in Daru) and with a lower probability to the yellow cluster (mostly found in Port Moresby). 10.1371/journal.pntd.0002361.g003 Figure 3 Panel A: Microsatellite Bayesian Structure Plot for Ae. albopictus. Thirteen microsatellite markers were run on 199 Ae. albopictus individuals assuming five populations (K = 5). Each bar represents an individual with the color of the bar the probability of the individual belonging to a genetic population or cluster. Panel B: The structure plot results (K = 5) integrated into a map of the region with the locations of each population shown. The factorial correspondence analysis performed in GENETIX (Figure 4) supports the results of the STRUCTURE analysis. It clearly shows the close relationship between individuals from Daru Island and Madang, as well as between individuals from Port Moresby and Kiunga. Additionally, the introduced populations from the Torres Strait Islands and the southern Fly region are closely associated. The population with the greatest genetic affinities to the introduced population based on the FCA is Timor Leste, suggesting that the source of the introduction was more likely from the Indonesian region (where Ae. albopictus is common) than from the extant PNG populations, as had been previously hypothesized. The Jakarta population is relatively isolated on the FCA plot. 10.1371/journal.pntd.0002361.g004 Figure 4 Factorial Correspondence Analysis (FCA) of 199 Ae. albopictus individuals. Each point represents one individual assessed for 13 microsatellites with their relative proximity to each other on the graph representing genetic relatedness. Panels A and B represent two perspectives of the graph. Discussion Detection of Ae. albopictus in southern Papua New Guinea (PNG) in 1988 and 1992 placed it only 150 km across the Torres Strait from mainland Australia. In 2004–05 it appeared on the Torres Strait Islands and we initially suspected a range expansion from PNG potentially driven by human adaptation to climate variability. The AusAID funded drought-proofing expansion of rainwater tanks and 200 L water containers into the southern Fly River region villages immediately adjacent to the Torres Strait was completed in 2002 as a response to climate variability in the region [33], [34]. Thus it was reasonable to hypothesize that the population historically extant in PNG had undergone a range expansion, initially into the southern Fly River region and subsequently into the Torres Strait Islands. The introduction of the species into the Torres Strait Islands was traced back to 2004 [29], at a date that appeared to correlate with the change in water management which had occurred a few years earlier. Initially the mtCOI suggested that two genetically distinct populations were present in this region, providing the first piece of evidence that the invading population may not have originated from the population previously extant in PNG. Shared haplotypes between the southern Fly Region, the Torres Strait Islands and Indonesian populations provided the first clue as to where the invading population may have originated. Despite haplotype diversity being biased by the larval sampling method (which favors the collection of siblings of the same haplotype), the Torres Strait Island populations revealed four more haplotypes (a total of 10, Hd = 0.801) than the southern Fly River (6 haplotypes, Hd = 0.649). This difference in haplotype diversity may suggest that the initial introduction into the region started in the Torres Strait Islands from the Indonesian region, however more COI sequencing from the southern Fly region may be needed to clarify whether or not this is the case. Interestingly however, genetic diversity appears higher in the Torres Strait and Fly Region than in the Indonesian populations, possibly suggesting multiple introductions of closely related populations from different parts of Indonesia, or that the founding population was more genetically diverse than those sampled from the Indonesian region. The mitochondrial DNA was informative at another level with the discovery that multiple Ae. albopictus mtDNA haplotypes (representing different females contributing to the population) were moving between islands. This suggests that attempts to eradicate the species from individual islands would likely be unsuccessful given the high potential for re-introductions. Indeed, this information has assisted Queensland Health – the regional state health authority – in its decision to move from the island eradication program implemented in 2006 to a cordon sanitaire in 2008, whereby surveillance and control was focused on the inner Torres Strait islands of Waiben, Muralug and Ngurupai (Thursday, Prince of Wales and Horn islands) adjacent to mainland Australia. In particular, Muralug and Ngurupai act as the major regional transport hubs and are thus the most likely staging point for the species' introduction onto the Australian mainland. This cordon sanitaire was breached in 2009 and Ae. albopictus now exists on Waiben and Ngurupia, less than 30 km from Australia's Cape York Peninsula. In 2010, Aedes albopictus larvae were collected from New Marpoon on mainland Australia's Cape York although no other individuals have been collected in this area since. The 13 microsatellite loci reaffirmed the findings of the mitochondrial data that the introduced population was genetically distinct to the populations already present in PNG. As microsatellites evolve more rapidly than mitochondrial sequence data, they were more informative, resolving five genetically distinct populations in total with three historically extant populations in PNG that have experienced various levels of admixture and one distinct population encompassing the Torres Strait Islands and the southern Fly River region – the introduced population. Samples from Madang in northern PNG, as well as from Port Moresby on the southern Papuan Peninsula, appear to be admixtures, with individuals from Port Moresby being more similar to samples from Kiunga, and individuals from Madang more similar to the Daru Island population (Figures 3 and 4). Although Daru Island is proximal to the introduced population, material collected there on two separate occasions (1992 and 2008) was assigned with high probability to a separate population with close genetic affinities to the Madang material. Interestingly, the material collected from the Indonesian region (Timor Leste and Jakarta) forms a distinct population with apparent genetic affinities to the introduced population in the Torres Strait and southern Fly Region. Timor Leste revealed the highest genetic affinities in the FCA analysis and there are records of Ae. albopictus being present in Timor Leste dating to the 1920s [23]. Thus, our combined data strongly suggests that the introduction of Ae. albopictus into the Torres Strait and southern Fly River region came from the Indonesian region. Since it now appears highly unlikely that the introduced population originated from PNG but rather came from the Indonesian region (west of the Torres Strait), it is conceivable that the introduction was driven by foreign fishing vessels that travelled from the Indonesian region, harboring Ae. albopictus specimens which then infested the islands of the Torres Strait and/or the southern Fly region. Indonesian/Macassan visitations to the coastline of northern Australia have a long history predating European settlement, and Indonesian fishermen have been known to illegally enter Australian waters more recently to fish for shark fin (Walker, J. Pers. Com.). This activity is reported to have peaked between 2005–07, during which time several hundred landings occurred where fuel, water, shark fin, fishing nets and lines were often cached. Many of these landings were associated with well-established camps that received multiple visits. Uninhabited islands in the Torres Strait were one focus for these activities and evidence gathered from apprehended vessels indicates that most shark boats (Type III - highly mobile, motorized vessels) carried large open-topped water drums of which a significant proportion harboured Ae. aegypti and Ae. albopictus larvae. There have been documented collections of various Aedes (Stegomyia) species, including Ae. albopictus, from illegal fishing vessels that were intercepted at the port of Darwin in the Northern Territory that clearly indicate that the mosquitoes' survival in smaller vessels is possible [56], [57]. With regard to the expansion and movement of Ae. albopictus in this region, populations on Daru Island (which adjoins the Torres Strait) appear to have been unaffected by this exotic invasion up until 2008 and follow-up collections are now warranted to determine if the introduced population has established there since. Despite Daru Island sitting geographically adjacent to the southern Fly River coastal region, its Ae. albopictus population seems to be clearly isolated from the introduced population. The occurrence of two genetically distinct populations adjacent to each other in the northern Torres Strait/PNG region can be best explained by their different jurisdictions. While the Torres Strait operates as part of Australia, Daru Island is politically part of PNG and its function as the international customs clearance station into Western Province means that it encounters different incoming and outgoing transport movements. The movement of Ae. albopictus appears to be extensive in the Australasian region, particularly where the Torres Strait Islands' junction separates New Guinea and mainland Australia. With the maximum reported flight range of Ae. albopictus being 1 km [58], movement between the Torres Strait's islands has most likely taken place via human-mediated transport. Australia has an oceanic border with PNG and the Torres Straits, but unlike most other international countries, it has no clearly marked frontier with border policing or customs controls. Thus relatively free movement occurs between PNG and the Torres Straits with approximately 5,000 international shipping movements per year [59], and countless domestic movements that would likely shuttle Ae. albopictus between the islands and back and forth from the southern Fly region's villages. This movement is sanctioned under The Torres Strait Treaty (Miscellaneous Amendments) Act 1984 that allows for cross-border movement for trade, fishing, and family gatherings or for seeking medical attention without the need for customs protocols [60] –all of which may compromise quarantine in the region. The primary mode of transport between PNG villages and the Torres Strait Islands is via open-topped, outboard-motor-powered boats. In addition to sheltered harborage sites for adult mosquitoes, these vessels contain fresh water – both within drums for human consumption, and where rainwater has collected – which in turn provides oviposition sites and larval habitats for container-inhabiting species such as Ae. albopictus. Given its current location, its mobility and its phenotypic fondness for containers, Ae. albopictus is more than likely to arrive in a town or city on the Australian mainland via human transport. Due to the intrinsic ecological plasticity in both larval habitat (both natural and human-made) and host feeding patterns [3], it will likely be able to move between urban and sylvan habitat, and control will be extremely challenging once it enters the latter. Its effect on native virus vector systems in Australia represents an unknown risk both to humans and to native and domestic animals. However, its cool climate tolerant biology and plasticity will certainly present new risks for dengue and chikungunya transmission in summer throughout most of the Australian region [27], [30]. Aedes albopictus's particular biology permits its container inhabiting ecological niche to once again facilitate its global expansion. It is important to consider it's potential to rapidly exploit the outcomes of any socio-economic or policy-driven interventions, such as the recent and dramatic expansion of domestic rainwater tanks throughout Australian urban regions as a drought-proofing adaptation to observed and forecasted climate change [30]. Although this adaptation did not ultimately explain the range expansion of the species on Australia's northern doorstep, it will nonetheless provide a valuable niche in the landscape, which may augment this vector's existence across Australia's urban regions. In considering its eventual arrival, the public health risks associated with arboviruses meet the possibility of substantial daytime nuisance biting that will also negatively impact Australia's urban alfresco lifestyle.
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- Abstract: found
- Article: found
Genetic Structure of the Tiger Mosquito, Aedes albopictus, in Cameroon (Central Africa)
Basile Kamgang, Cecile Brengues, Didier Fontenille … (2011)
Background Aedes albopictus (Skuse, 1884) (Diptera: Culicidae), a mosquito native to Asia, has recently invaded all five continents. In Central Africa it was first reported in the early 2000s, and has since been implicated in the emergence of arboviruses such as dengue and chikungunya in this region. Recent genetic studies of invasive species have shown that multiple introductions are a key factor for successful expansion in new areas. As a result, phenotypic characters such as vector competence and insecticide susceptibility may vary within invasive pest species, potentially affecting vector efficiency and pest management. Here we assessed the genetic variability and population genetics of Ae. albopictus isolates in Cameroon (Central Africa), thereby deducing their likely geographic origin. Methods and Results Mosquitoes were sampled in 2007 in 12 localities in southern Cameroon and analyzed for polymorphism at six microsatellite loci and in two mitochondrial DNA regions (ND5 and COI). All the microsatellite markers were successfully amplified and were polymorphic, showing moderate genetic structureamong geographic populations (FST = 0.068, P<0.0001). Analysis of mtDNA sequences revealed four haplotypes each for the COI and ND5 genes, with a dominant haplotype shared by all Cameroonian samples. The weak genetic variation estimated from the mtDNA genes is consistent with the recent arrival of Ae. albopictus in Cameroon. Phylogeographic analysis based on COI polymorphism indicated that Ae. albopictus populations from Cameroon are related to tropical rather than temperate or subtropical outgroups. Conclusion The moderate genetic diversity observed among Cameroonian Ae. albopictus isolates is in keeping with recent introduction and spread in this country. The genetic structure of natural populations points to multiple introductions from tropical regions.
Author and article information
Contributors
Vivian Petersen: var_petersen@hotmail.com
Mariana Devicari: mdevicari@hotmail.com
Lincoln Suesdek: lincoln.suesdek@butantan.gov.br
Journal
Journal ID (nlm-ta): Parasit Vectors
Journal ID (iso-abbrev): Parasit Vectors
Title:
Parasites & Vectors
Publisher:
BioMed Central
(London
)
ISSN
(Electronic):
1756-3305
Publication date
(Electronic):
26
February
2015
Publication date PMC-release: 26
February
2015
Publication date Collection: 2015
Volume: 8
Electronic Location Identifier: 128
Affiliations
Article
Publisher ID: 740DOI: 10.1186/s13071-015-0740-6
PMC ID: 4357162
PubMed ID: 25561160
SO-VID: 6041b9ec-3e06-44e4-ac68-434234c00c1b
Copyright © © Petersen et al.; licensee BioMed Central. 2015
License:
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
History
Date
received
: 15
July
2014
Date
accepted
: 13
February
2015
Categories
Subject:
Research
Custom metadata
issue-copyright-statement © The Author(s) 2015
ScienceOpen disciplines: Parasitology
Data availability:
ScienceOpen disciplines: Parasitology