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High resolution melting analysis, molecular identification, mosquitoes, Aedes, Culex, Mansonia, Anopheles
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Ajamma YU, Mararo E, Omondi D et al. Rapid and high throughput molecular identification of diverse mosquito species by high resolution melting analysis [version 1; peer review: 2 approved]. F1000Research 2016, 5:1949 (https://doi.org/10.12688/f1000research.9224.1)
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Method Article
Rapid and high throughput molecular identification of diverse mosquito species by high resolution melting analysis
[version 1; peer review: 2 approved]
PUBLISHED 11 Aug 2016
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Abstract
Corresponding author:
Jandouwe Villinger
Competing interests:
No competing interests were disclosed.
Grant information:
We gratefully acknowledge the financial support for this research by the following organizations and agencies: Swedish International Development Cooperation Agency (SIDA), grant number 75000529 to YUA as an African Regional Postgraduate Programme in Insect Science (ARPPIS) student; Funds from Training Health Researchers into Vocational Excellence (THRiVE) in East Africa (grant number 087540) funded by Wellcome Trust to JV and DM supported part of the field sampling. We also acknowledge funding from UK’s Department for International Development (DFID); the Swiss Agency for Development and Cooperation (SDC); and the Kenyan Government.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Copyright:
© 2016 Ajamma YU et al.
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
How to cite: Ajamma YU, Mararo E, Omondi D et al. Rapid and high throughput molecular identification of diverse mosquito species by high resolution melting analysis [version 1; peer review: 2 approved]. F1000Research 2016, 5:1949 (https://doi.org/10.12688/f1000research.9224.1)
First published: 11 Aug 2016, 5:1949 (https://doi.org/10.12688/f1000research.9224.1)
Latest published: 11 Aug 2016, 5:1949 (https://doi.org/10.12688/f1000research.9224.1)
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Introduction
Mosquitoes are among the most important disease vectors, known to transmit and maintain the circulation of pathogens that cause both global and neglected tropical diseases in humans and animals1. The correct identification of different field-collected mosquito species, endemic to distinct ecologies, with high parasite and arthropod-borne virus (arbovirus) diversities is crucial to the planning of targeted vector control strategies to mitigate disease transmission2. The last and most comprehensive Afrotropical mosquito identification keys were published in 1941 for culicines3 and in 1987 for anophelines4. Molecular approaches that efficiently differentiate conspecific mosquitoes such as the barcode region5 improve identification accuracy considerably6, but are time consuming, expensive in terms of post-polymerase chain reaction (post-PCR) processing and depend heavily on DNA sequencing.
Recent approaches have taken advantage of the unique melting profiles generated by homologous PCR products with small sequence differences during high resolution melting (HRM) analysis7,8. Indeed, PCR-HRM has been used to differentiate mosquito transmitted arboviruses9–11 and malaria Plasmodium12,13, vertebrate blood meals of mosquitoes10, between two members of the Anopheles gambiae complex14 and amongst three members of the Culex pipiens complex15. HRM analysis has proven to offer higher resolution of PCR product based species identification on sequence variants than electrophoretic methods by revealing even single nucleotide polymorphisms (SNPs) in the simple sequence repeats (SSRs) among products of similar sizes16,17. Conventional detection of specific PCR products sequence relies on costly molecular probes and/or product sequencing18. For species identification16, only representative samples with distinct HRM profiles need to be sequenced, thereby reducing reagent and sample consumption costs10–11. Combining HRM analysis of barcode region sequences (Bar-HRM) has been successfully used to rapidly and accurately distinguish between closely related antelope species19 and medicinal plants20,21 and to authenticate the source of vegetable oils22.
Although HRM has been successfully used to differentiate between specific Anopheles and Culex mosquitoes, the approach’s broader applicability and most suitable markers have not been evaluated. Previously, only the ribosomal DNA was targeted for An. gambiae sensu lato (s.l.)14 and only the acetylcholinesterase gene was used in distinguishing the Cx. pipiens complex15. This study aimed at validating the use of HRM analysis for high throughput molecular culicine and anopheline mosquito identification and differentiation, comparing the utility of one ribosomal IGS (previously used to differentiate An. gambiae s.l.)14 and three mitochondrial (COI, ND1, cyt b) gene markers.
Methods
Sample collection and identification
We used 109 mosquitoes (Table 1 and Table 2) that were collected in 2012 during the rainy seasons near Lake Baringo from March 2–4, July 16–24 and October 12–21 and Lake Victoria from April 2–15, May 18–31 and November 12–29 during a mosquito diversity study around the islands and mainland shores of Lake Baringo in Baringo County (Table 1) and Lake Victoria in Homa Bay County (Table 2) in Kenya6. Before sampling, we obtained ethical clearance for the study from the Kenya Medical Research Institute (KEMRI) ethics review committee (Approval Ref: Non-SSC Protocol #310). These mosquitoes were morphologically identified during a previous study6. Baringo County is a known hotspot for arbovirus outbreaks23, while Homa Bay County is endemic to malaria and is located in a region with a history of arbovirus activity10. One sample each of Anopheles gambiae sensu stricto (s.s.) and An. arabiensis, Aedes aegypti and Culex pipiens from laboratory colonies maintained in the Insectary of the International Centre of Insect Physiology and Ecology (icipe), Nairobi, Kenya, were used as controls. Also, specimens with confirmed identity that have been previously sequenced and submitted to GenBank (Table 1 and Table 2) were used as both controls and samples.
Table 1. Number (N) of mosquito species (GenBank accessions) used for HRM analyses from Baringo County, Kenya.
GenBank accessions are provided only for samples with confirmed identity and from which the COI DNA sequences were obtained during a previously published mosquito diversity study6.
Table 2. Number (N) of mosquito species (GenBank accessions) used for HRM analyses from Homa Bay County, Kenya.
GenBank accessions are provided only for samples with confirmed identity and from which the COI DNA sequences were obtained during a previously published mosquito diversity study6.
DNA extraction
From each mosquito, we extracted DNA according to the hot sodium hydroxide and Tris (HotSHOT) DNA extraction protocol24 from a single mosquito leg that was detached from the rest of the body using a pair of forceps and dissecting pin. Without crushing, the mosquito leg was put in a 0.2 ml microcentrifuge tube containing 30 µl of Alkaline Lysis buffer (25 mM NaOH (Thermo Fisher Scientific, Pittsburgh, USA), 0.2 mM disodium EDTA (Thermo Fisher Scientific), pH 8.0) and incubated in a thermocycler at 95°C for 30 minutes and cooled at 4°C for 5 minutes. Then, 30 µl neutralising solution (40 mM Tris-HCl (Thermo Fisher Scientific)) was added. The resulting DNA was stored at -20°C until required as templates for PCR assays.
Primer design, PCR and HRM analyses
Based on multiple alignments using Geneious software version 8.1.425 of mitochondrial genomes of mosquitoes (GenBank accessions NC_015079, NC_028616, NC_028223, KR068634, NC_010241, NC_014574, EU352212, NC_008070, KT358413, KT382816, KU494979, JX040513, AY729979, KU494979), we designed four sets of primers from two mitochondrial gene regions: COI (COI-AnophF/HCO2108R; Uni-Minibar-JVF/Uni-Minibar-JVR; Mos-CO1-JVF/Mos-CO1-JVR) and ND1 (Mos-ND1F/Mos-ND1R) genes (Table 3). The COI AnophF primer was initially designed specifically for Anopheles mosquitoes to be used with the HCO2108R primer26, but tested on other species as well. Using samples of morphologically and molecularly identified Culex, Aedeomyia, Mimomyia, Coquillettidia, Mansonia, Aedes, and Anopheles mosquito species (Table 1 and Table 2), we amplified different gene regions of their genomes using six pairs of primers (Table 3) in three replicate runs of single-plex PCRs in a Rotor-Gene Q HRM real time PCR thermocycler (QIAGEN, Hannover, Germany). PCR grade water was used as negative control while mosquito species from Ae. aegypti, An. gambiae s.s., An. arabiensis and Cx. Pipiens quinquefasciatus colonies maintained in the International Centre of Insect Physiology and Ecology (icipe) Insectary Unit were used as positive controls. The PCR mix contained 5 µl of 5X Hot Firepol EvaGreen HRM Mix (Solis BioDyne, Tartu, Estonia), 0.5 µM of each primer, 1 µl of DNA template and distilled water in a final volume of 10 µl. The thermal cycling conditions involved an initial denaturation for 1 minute at 95°C, followed by 35 cycles of denaturation at 95°C for 30 seconds, annealing at 50°C for 20 seconds, and extension at 72°C for 30 seconds, and a final extension at 72°C for 7 minutes. Without stopping the reaction, the PCR amplicons were denatured at 95°C for 1 minute, held for another minute at 40°C and melted by gradually raising the temperature from 70°C to 95°C by 0.1°C in 2 second steps, waiting for 90 seconds of pre-melt conditioning on first step and 2 seconds in subsequent steps. The outcome was automatically plotted on a connected computer and visually observed and analysed using the Rotor-Gene Q Series software v2.1. Representative samples of differentiated mosquito species that had similar HRM curves were purified with ExoSAP-IT (USB Corporation, Cleveland, OH) and submitted for DNA sequencing at Macrogen (South Korea). To confirm the identity of PCR-HRM differentiated mosquitoes, DNA sequences were edited with Geneious version 8.1.425 and queried against the GenBank nr database (http://www.ncbi.nlm.nih.gov/) using the Basic Local Alignment Search Tool (BLAST N) version 2.3.027.
Table 3. Primers used for the amplification of gene fragments.
| Target gene | Primer name | Primer Sequence (5’ to 3’) | Reference genome | Primer coordinates | Amplicon size (bp) |
|---|---|---|---|---|---|
| Mitochondrial COI (within barcode region) | COI-AnophF | GCAGGAATTTCTTCTATTTTAGG | L20934 | 1,874–1,896 | 275 |
| HCO2198R26 | TAAACTTCAGGGTGACCAAAAAATCA | L20934 | 2,148–2,123 | ||
| Mitochondrial COI | Uni-Minibar-JVF | ACAAATCATAARGATATTGGAAC | L20934 | 1,445–1,467 | 173 |
| Uni-Minibar-JVR | AAAATTATAATAAAWGCATGAGC | L20934 | 1,617–1,55 | ||
| Mitochondrial COI | Mos-Co1-JVF | ATAGTWATACCTATYATAATTGG | L20934 | 1,622–1,644 | 299 |
| Mos-Co1-JVR | ACWGTAGTAATAAAATTTACTGC | L20934 | 1,920–1,898 | ||
| Mitochondrial ND1 | Mos-ND1F | TATGTCTTGAAAACATAAGAAAG | L20934 | 11,569–11,591 | 173 |
| Mos-ND1R | CGDTATGATAAATTAATGTAATTAG | L20934 | 11,717–11,741 | ||
| Mitochondrial cyt b | CYT BF35 | GGACAAATATCATTTTGAGGAGCAACAG | L20934 | 10,821–10,848 | 470 |
| CYT BR35 | ATTACTCCTCCTAGCTTATTAGGAATTG | L20934 | 11,290–11,263 | ||
| Ribosomal DNA IGS | AgamUni F2 | GTGAAGCTTGGTGCGTGCT | KT284724 | 126–174 | 169 |
| AgamUni R2 | GCACGCCGACAAGCTCA | KT284724 | 319–303 |
Results
Dataset 1.Raw Rotor-Gene Q HRM data files (.rex), viewable using Rotor-Gene Q software (Qiagen).
‘Contents.csv’ contains a description of the files.We differentiated 12 mosquito species in the Aedes (two), Anopheles (two), Culex (six), and Mansonia (two) genera by HRM analyses (Table 4). The COI sequences of some of the mosquito samples analyzed and differentiated were obtained during a previously published mosquito diversity study6 and their respective GenBank Accession numbers are listed in Table 1 and Table 2. Despite the fact that the COI-AnophF/HCO2198R primers were originally designed based on Anopheles mitochondria genome alignments, they were most efficient in differentiating among Mansonia (Ma. africana and Ma. uniformis (Figure 1A)), Culex (Cx. neavei and Cx. duttoni, Cx. tenagius and Cx. antennatus, and two genetic variants of Cx. pipiens (Figure 2A)), and Aedes (Ae. vittatus and Ae. metallicus (Figure 3)) mosquitoes (Table 4). Indeed, the DNA sequences flanked by the COI-AnophF/HCO2198R primers included multiple polymorphic sites in species within these genera (Figure 4). Although there are SNPs within species DNA that resulted to the slight changes observed in their HRM profiles, the SNPs across species were enough to distinguish between them.
Table 4. Differentiation of mosquito species using the six primer pairs amplifying four loci.
Figure 1. HRM profiles of two Mansonia species.
Mansonia uniformis and Ma. africana mosquitoes were differentiated by PCR-HRM using the (A) COI-AnophF/HCO2198R, (B) MOS-CO1 and (C) CYT B primer pairs.
Figure 2. HRM profiles of Culex species.
Culex species were differentiated by PCR-HRM using the (A) COI-AnophF/HCO2198R, (B) CYT B, (C) Uni-Minibar-JV, and (D) Mos-ND1 primer pairs.
Figure 3. HRM profiles of Aedes mosquitoes.
Aedes vittatus and Ae. metallicus were differentiated by PCR-HRM using the COI-AnophF/HCO2198R primer pair.
Figure 4. Single nucleotide polymorphisms (SNP) between mosquito species separated by the COI-AnophF/HCO2108R primer pair amplicons.
Polymorphic sites vary more between than within species.
Mansonia africana and Ma. uniformis could also be differentiated by Mos-COI-JV (Figure 1B) and CYT B (Figure 1C) PCR-HRM analysis. Some Culex species were similarly differentiated by HRM based on their CYT B, Uni-Minibar-JV and Mos-ND1 (Figure 2B–D) primer pair PCR products. The morphologically indistinguishable Cx. tenagius and Cx. antennatus were distinguished only by the COI-AnophF/HCO2198R, CYT B and ND1 primers (Figure 2A, B and D). Similarly, HRM analysis of only two of the COI (COI-AnophF/HCO2198R and Uni-Minibar JV) and the ND1 primer pairs grouped morphologically identical and difficult to differentiate Cx. pipiens into two distinct clades: one with Cx. pipiens voucher sequences from GenBank (KF919189) and those with a sequence that we identified as Culex sp. GPA6 (GenBank accessions KU380352, KU380455, KU380394) (Figure 2A, C and D; Table 4). However, unlike the COI HRM profiles (Figure 2A, B), the ND1 HRM profiles (Figure 2D) of Cx. pipiens amplicons showed a melting temperature shift of to the right (higher temperature) compared to the Culex sp. GPA amplicons, possibly due to greater GC richness of Cx. pipiens at this locus28. Similarly, the IGS primers (AgamUni) differentiated Anopheles gambiae s.s. from An. arabiensis (Figure 5). In addition, the COI-AnophF/HCO2198R primers were also used to separate Cx. neavei from Cx. duttoni (Figure 2A), which belong to the same subgenus of Culex mosquitoes.
Figure 5. HRM profiles of Anopheles mosquitoes.
Two sibling species of Anopheles gambiae s.l. were differentiated by PCR-HRM using the AgamUni primer pair.
HRM analysis of all the six primer pairs could not differentiate Aedeomyia (Ad. africana and Ad. furfurea), Mimomyia (Mi. hispida and Mi. splendens) and Coquillettidia (Cq. aurites, Cq. chrysosoma, Cq. fuscopennata, Cq. metallica, Cq. microannulatus, Cq. pseudoconopas and Cq. versicolor) species (Table 4) or among An. funestus and An. coustani species complexes.
Discussion
We compared six pairs of primers for their potential to differentiate at least two morphologically similar mosquito species within each of seven mosquito genera by PCR-HRM analysis and identified suitable markers for differentiating species within Anopheles, Aedes, Culex and Mansonia mosquitoes. However, none of the markers were suitable for HRM analysis to distinguish among species of Aedeomyia, Mimomyia or Coquillettidia genera mosquitoes. Also, Cx. watti, which can be misidentified morphologically as Cx. duttoni or Cx. pipiens, could not be differentiated by PCR-HRM analyses. Nonetheless, we were able to distinguish Ma. africana from Ma. uniformis, An. gambiae s.s. from An. arabiensis (sibling species of An. gambiae s.l.), Ae. vittatus from Ae. metallicus, as well as Cx. neavei from Cx. duttoni, Cx. tenagius from Cx. antennatus and two cryptic sympatric species of morphologically identical Cx. pipiens. Most notably, the two Cx. pipiens species with distinct COI barcode sequences6 were indeed first identified by HRM analysis of numerous samples6. Thus, the relative economy of HRM analysis compared to sequencing facilitates the rapid identification of cryptic species.
Surprisingly, HRM analysis of PCR products from the COI-AnophF/HCO2198R primers, which were designed for Anopheles, could not distinguish between these sibling species, yet were most effective in discriminating species within the Mansonia, Aedes and Culex genera, including between the cryptic Culex pipiens species. Anopheles gambiae and An. arabiensis were only distinguished using the IGS gene, which was also designed for An. gambiae2 and is routinely used for distinguishing these sibling species by conventional PCR29 and HRM analysis14. In contrast, species complexes of An. coustani and An. funestus were not differentiated with any of the primers. The data suggest that COI30, cyt b and ND1 loci may be unsuitable for distinguishing among Anopheles sibling species. Similarly, the Aedes species could only be differentiated by the COI-AnophF/HCO2198R primers. This could be as a result of more recent speciation, insufficient to allow for sibling species resolution at these markers. Such scenarios have been observed for recent or rapidly evolving groups, such as the Cichlid fishes of eastern Africa, where mitochondrial divergence is not concordant with morphological variations31.
In contrast, Ma. africana and Ma. uniformis were separated by the COI and cyt b loci, but not by the ND1 and IGS gene primers and Culex species were variably differentiable by all markers, except IGS. For both Mansonia and Culex, as with Aedes, the COI-AnophF/HCO2198R primers were most sensitive in discriminating morphologically indistinct species. This highlights the power of the COI barcode region for identifying diverse cryptic species32. The SNPs present in the COI genes of the ten mosquito species confirms that the COI gene is conserved and polymorphic enough to differentiate these species even in cases of morphological misidentification. The polymorphisms between species were enough to robustly separate them based on their HRM profiles, while sequence polymorphisms within species were too few to significantly alter their HRM profiles.
We, therefore, recommend the initial use of the COI-AnophF/HCO2198R primers Bar-HRM to differentiate Mansonia, Culex and Aedes mosquito species and the IGS primers for anopheline mosquito identification2,14,33 by HRM. The inability of all the six primer pairs to differentiate many mosquito species among all seven genera tested is an indication that the genetic diversity of many mosquito species is complicated and still poorly understood. Also, the number (sample size) of many of the analyzed mosquito species was small (<3) because these species were scarcely present in the study areas. More samples (≥3) should be used and more study areas should be sampled in subsequent studies to test genetic differentiation of mosquito species34. Additional polymorphic DNA loci should also be identified, tested and used in combination with existing ones for the identification of mosquito species, especially among species complexes and across genera.
Conclusions
This study shows that specific PCR markers can be used to distinguish closely related species of mosquitoes using HRM analysis. We distinguished two sibling species of An. gambiae s.l., two species each of Mansonia and Aedes, and six species, including cryptic species, of Culex using six pairs of primers targeting the mitochondrial and ribosomal genes. HRM is a low cost (<$1 per reaction), effective tool that enhances culicine and anopheline mosquito identification and may also reveal population differences in conserved mitochondrial sequences. This approach can improve vector surveillance associated with Plasmodium (malaria) or arbovirus transmission and inform targeted vector control strategies.
Data availability
All sequence data associated with this manuscript are freely available in GenBank. All relevant accession numbers are listed in Table 1 and Table 2.
F1000Research: Dataset 1. Raw Rotor-Gene Q HRM data files (.rex), viewable using Rotor-Gene Q software (Qiagen), 10.5256/f1000research.9224.d13056536
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how to cite this article
Ajamma YU, Mararo E, Omondi D et al. Rapid and high throughput molecular identification of diverse mosquito species by high resolution melting analysis [version 1; peer review: 2 approved]. F1000Research 2016, 5:1949 (https://doi.org/10.12688/f1000research.9224.1)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Chai HC. Reviewer Report For: Rapid and high throughput molecular identification of diverse mosquito species by high resolution melting analysis [version 1; peer review: 2 approved]. F1000Research 2016, 5:1949 (https://doi.org/10.5256/f1000research.9928.r16385)
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https://f1000research.com/articles/5-1949/v1#referee-response-16385
https://f1000research.com/articles/5-1949/v1#referee-response-16385
NOTE: it is important to ensure the information in square brackets after the title is included in this citation.
Reviewer Report 19 Sep 2016
Hwa Chia Chai, Department of Biomedical Science, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
Approved
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Overall, this is a well-written article on the development of HRM for identification of different species of mosquitoes. The authors also mentioned about the limitations of the study. However, the six pairs of primers used in this study did not
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HOW TO CITE THIS REPORT
Chai HC. Reviewer Report For: Rapid and high throughput molecular identification of diverse mosquito species by high resolution melting analysis [version 1; peer review: 2 approved]. F1000Research 2016, 5:1949 (https://doi.org/10.5256/f1000research.9928.r16385)
The direct URL for this report is:
https://f1000research.com/articles/5-1949/v1#referee-response-16385
https://f1000research.com/articles/5-1949/v1#referee-response-16385
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Zianni M. Reviewer Report For: Rapid and high throughput molecular identification of diverse mosquito species by high resolution melting analysis [version 1; peer review: 2 approved]. F1000Research 2016, 5:1949 (https://doi.org/10.5256/f1000research.9928.r15904)
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https://f1000research.com/articles/5-1949/v1#referee-response-15904
https://f1000research.com/articles/5-1949/v1#referee-response-15904
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Reviewer Report 12 Sep 2016
Michael Zianni, Thermo Fisher Scientific, Carlsbad, CA, USA
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Ajamma have an article on the use of the technique high resolution melt analysis towards the identification of morphologically indistinct species of mosquito. The specific goal is to expand the current set of primers in the research literature in order
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Zianni M. Reviewer Report For: Rapid and high throughput molecular identification of diverse mosquito species by high resolution melting analysis [version 1; peer review: 2 approved]. F1000Research 2016, 5:1949 (https://doi.org/10.5256/f1000research.9928.r15904)
The direct URL for this report is:
https://f1000research.com/articles/5-1949/v1#referee-response-15904
https://f1000research.com/articles/5-1949/v1#referee-response-15904
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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