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. 2016 Aug 11;5:1949. [Version 1] doi: 10.12688/f1000research.9224.1

Rapid and high throughput molecular identification of diverse mosquito species by high resolution melting analysis

Yvonne Ukamaka Ajamma 1,2, Enock Mararo 1, David Omondi 1,3,4, Thomas Onchuru 1,5,6, Anne W T Muigai 2, Daniel Masiga 1, Jandouwe Villinger 1,a
PMCID: PMC5031131  PMID: 27703667

Abstract

Mosquitoes are a diverse group of invertebrates, with members that are among the most important vectors of diseases. The correct identification of mosquitoes is paramount to the control of the diseases that they transmit. However, morphological techniques depend on the quality of the specimen and often unavailable taxonomic expertise, which may still not be able to distinguish mosquitoes among species complexes (sibling and cryptic species). High resolution melting (HRM) analyses, a closed-tube, post-polymerase chain reaction (PCR) method used to identify variations in nucleic acid sequences, has been used to differentiate species within the Anopheles gambiae and Culex pipiens complexes. We validated the use of PCR-HRM analyses to differentiate species within Anopheles and within each of six genera of culicine mosquitoes, comparing primers targeting cytochrome b ( cyt b), NADH dehydrogenase subunit 1 (ND1), intergenic spacer region (IGS) and cytochrome c oxidase subunit 1 ( COI) gene regions. HRM analyses of amplicons from all the six primer pairs successfully differentiated two or more mosquito species within one or more genera ( Aedes ( Ae. vittatus from Ae. metallicus), Culex ( Cx. tenagius from Cx. antennatus, Cx. neavei from Cx. duttoni, cryptic Cx. pipiens species), Anopheles ( An. gambiae s.s. from An. arabiensis) and Mansonia ( Ma. africana from Ma. uniformis)) based on their HRM profiles. However, PCR-HRM could not distinguish between species within 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) genera using any of the primers. The IGS and COI barcode region primers gave the best and most definitive separation of mosquito species among anopheline and culicine mosquito genera, respectively, while the other markers may serve to confirm identifications of closely related sub-species. This approach can be employed for rapid identification of mosquitoes.

Keywords: High resolution melting analysis, molecular identification, mosquitoes, Aedes, Culex, Mansonia, Anopheles

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 animals 1. 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 transmission 2. The last and most comprehensive Afrotropical mosquito identification keys were published in 1941 for culicines 3 and in 1987 for anophelines 4. Molecular approaches that efficiently differentiate conspecific mosquitoes such as the barcode region 5 improve identification accuracy considerably 6, 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) analysis 7, 8. Indeed, PCR-HRM has been used to differentiate mosquito transmitted arboviruses 9– 11 and malaria Plasmodium 12, 13, vertebrate blood meals of mosquitoes 10, between two members of the Anopheles gambiae complex 14 and amongst three members of the Culex pipiens complex 15. 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 sizes 16, 17. Conventional detection of specific PCR products sequence relies on costly molecular probes and/or product sequencing 18. For species identification 16, only representative samples with distinct HRM profiles need to be sequenced, thereby reducing reagent and sample consumption costs 10– 11. Combining HRM analysis of barcode region sequences (Bar-HRM) has been successfully used to rapidly and accurately distinguish between closely related antelope species 19 and medicinal plants 20, 21 and to authenticate the source of vegetable oils 22.

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 complex 15. 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 Kenya 6. 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 study 6. Baringo County is a known hotspot for arbovirus outbreaks 23, while Homa Bay County is endemic to malaria and is located in a region with a history of arbovirus activity 10. 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.

Mosquito species N Logumgum
0.455 N, 36.078 E		 Sirata
0.462 N, 36.097 E		 Kampi ya Samaki
0.620 N, 36.028 E		 Nosuguro
0.605 N,
36.126 E
Ad. africana 4 4 (KU186980, KU186981,
KU186982, KU186985)
Ad. furfurea 4 4 (KU186979, KU186983,
KU186984, KU186986)
An. funestus 3 3 (KU187102, KU187103,
KU187105)
An. gambiae s.l. 3 1 2
Cq. aurites 2 2 (KU187114, KU187117)
Cq. chrysosoma 1 1 (KU187115)
Cq. fuscopennata 1 1 (KU187116)
Cq. metallica 2 2 (KU187112, KU187113)
Cx. antennatus 2 1 1 (KU187050)
Cx. perexiguus 4 4 (KU380423, KU380348,
KU380476, KU380382)
Cx. tenagius 1 1 (KU187054)
Ma. africana 4 2 (KU187124, KU187130) 2 (KU187127,
KU187128)
Ma. uniformis 3 2 (KU187170, KU187171) 1 (KU187164)
Total 34 8 16 6 4
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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 study 6.

Table 2. Number (N) of mosquito species (GenBank accessions) used for HRM analyses from Homa Bay County, Kenya.

Mosquito species N Mbita
0.432 S, 34.210 E		 Luanda
Nyamasare
0.478 S,
34.287 E		 Ngodhe
0.505 S,
34.363 E		 Ungoye
0.612 S,
34.098 E		 Mfangano Island
0.462 S, 33.999 E		 Rusinga Island
0.399 S, 34.193 E		 Chamaunga
Island
0.431 S,
34.228 E		 Takawiri
Island
0.472 S,
34.091 E
Ae. metallicus 3 1 (KU187014) 1
(KU187013)		 1
Ae. vittatus 8 6 (KU187004, KU187006,
KU187008-KU187011)		 2 (KU187005,
KU187007)
An. coustani s.l. 10 3
(KU187098,
KU187100,
KU187101)		 2 (KU187095,
KU187096)		 2 (KU187097, KU187099) 2 1
An. funestus 2 1 (KU187104) 1
An. gambiae s.l. 2 2 (KU187108, KU187109)
Cq. aurites 1 1 (KU187121)
Cq. microannulatus 2 1 1 (KU187118)
Cq. pseudoconopas 1 1
Cq. versicolor 2 2 (KU187119,
KU187120)
Cx. antennatus 4 4 (KU187037,
KU187038,
KU187048)
Cx. duttoni 6 1 (KU187075) 5 (KU187067, KU187068,
KU187070-KU187072)		 1
Cx. neavei 3 3 (KU187032, KU187040,
KU187046)
Cx. perexiguus 1 1 (KU380445)
Cx. pipiens 6 1 (KU187083) 5 (KU187077,
KU380366, KU380372,
KU380431, KU380444)
Culex sp. GPA 5 3 (KU380352,
KU380455,
KU380394)		 2 (KU380377,
KU380413)
Cx. univittatus 3 3 (KU187056,
KU187059,
KU187060)
Cx. watti 5 2 (KU187063,
KU187064)		 2 1
Ma. africana 2 1 1 (KU187153)
Ma. uniformis 3 1
(KU380460)		 1 1 (KU187175)
Mi. hispida 2 2
Mi. splendens 3 3 (KU187093,
KU187094)
Total 75 21 5 5 1 22 12 6 3
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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 study 6.

DNA extraction

From each mosquito, we extracted DNA according to the hot sodium hydroxide and Tris (HotSHOT) DNA extraction protocol 24 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 8.1.4 25 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 primer 26, 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 8.1.4 25 and queried against the GenBank nr database ( http://www.ncbi.nlm.nih.gov/) using the Basic Local Alignment Search Tool (BLAST N) version 2.3.0 27.

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
HCO2198R 26 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 BF 35 GGACAAATATCATTTTGAGGAGCAACAG L20934 10,821–10,848 470
CYT BR 35 ATTACTCCTCCTAGCTTATTAGGAATTG L20934 11,290–11,263
Ribosomal DNA IGS AgamUni F 2 GTGAAGCTTGGTGCGTGCT KT284724 126–174 169
AgamUni R 2 GCACGCCGACAAGCTCA KT284724 319–303
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F is forward primer direction; R is reverse primer direction.

Results

Raw Rotor-Gene Q HRM data files (.rex), viewable using Rotor-Gene Q software (Qiagen)

‘Contents.csv’ contains a description of the files.

Copyright: © 2016 Ajamma YU et al.

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).

Click here for additional data file. (1.6MB, tgz)

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 study 6 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.

Figure 1. HRM profiles of two Mansonia species.

Figure 1.

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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.

Figure 2.

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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.

Figure 3.

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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.

Figure 4.

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Polymorphic sites vary more between than within species.

Table 4. Differentiation of mosquito species using the six primer pairs amplifying four loci.

Mosquito genera COI cyt b ND1 IGS
COI-AnophF/HCO2198R Mos-CO1-JV Uni-Minibar-JV CYT B Mos-ND1 AgamUni
Anopheles DNS DNS DNS DNS DNS Separated
An. gambiae
from
An. arabiensis
Mansonia Separated Ma. africana
from Ma. uniformis 		Separated
Ma. africana
from
Ma. uniformis 		DNS Separated
Ma. africana
from
Ma. uniformis 		DNS DNS
Aedes Separated Ae. vittatus from
Ae. metallicus 		DNS DNS DNS DNS DNS
Culex Separated Cx. tenagius
from Cx. antennatus,
Separated Cx. pipiens from
Culex sp. GPA, Separated
Cx. neavei from Cx. duttoni 		DNS Separated
Cx. pipiens
from Culex
sp. GPA		 Separated
Cx. tenagius
from
Cx. antennatus 		Separated
Cx. tenagius from
Cx. antennatus,
Separated
Cx. pipiens from
Culex sp. GPA		 DNS
Aedeomyia DNS DNS DNS DNS DNS DNS
Mimomyia DNS DNS DNS DNS DNS DNS
Coquillettidia DNS DNS DNS DNS DNS DNS
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DNS means did not separate. COI means cytochrome c oxidase subunit 1. cyt b means cytochrome B. ND1 means NADH dehydrogenase subunit 1. IGS means intergenic spacer region.

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. GPA 6 (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 locus 28. 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.

Figure 5.

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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 sequences 6 were indeed first identified by HRM analysis of numerous samples 6. 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. gambiae 2 and is routinely used for distinguishing these sibling species by conventional PCR 29 and HRM analysis 14. In contrast, species complexes of An. coustani and An. funestus were not differentiated with any of the primers. The data suggest that COI 30, 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 variations 31.

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 species 32. 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 identification 2, 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 species 34. 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

The data referenced by this article are under copyright with the following copyright statement: Copyright: © 2016 Ajamma YU et al.

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). http://creativecommons.org/publicdomain/zero/1.0/

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.d130565 36

Acknowledgements

We thank Laban Njoroge of National Museums of Kenya for helping with morphological identifications of mosquitoes. We acknowledge John Tilion of Ruko Conservancy in Baringo County and Phillip Ojunju of Rusinga Island in Homa Bay County, for helping with mosquito sample collection in the two study areas respectively. We acknowledge the support of Milcah Gitau of icipe’s Insectary Unit in providing the Ae. aegypti, Cx. pipiens, An. gambiae s.s. and An. arabiensis controls. We also thank Esther Waweru of icipe’s Molecular Biology and Bioinformatics Unit (MBBU), Gerard Ronoh, Caroline Tigoi and Geoffrey Jagero of icipe’s ML-EID Laboratory, Lillian Igweta, Lisa Omondi and Margaret Ochanda icipe’s of Capacity Building & Institutional Development (CB&ID) Unit for assisting with logistics.

Funding Statement

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.

[version 1; referees: 2 approved]

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F1000Res. 2016 Sep 19. doi: 10.5256/f1000research.9928.r16385

Referee response for version 1

Hwa Chia Chai 1

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 seem to have clear directions or purpose. Did the authors want to come out with a pair of universal primers to differentiate all the clinically important mosquito species mentioned in the article? Or one specific primer pair for each genus of mosquitoes? Or there is other intention? Although the authors showed the ability of primer pairs to discern some mosquito species, for instance, COI-AnophF/HCO2198R could distinguish Mansonia spp., Aedes spp. and Culex spp., how about the species of the same genera that could not be discriminated? It would be more focused and directional if the primer pairs are genus-specific.

Methods:

  1. It would be great if the clinical importance of or disease transmitted by each mosquito genus/species is listed in Table 1 and Table 2 so that the readers understand the significance of discriminating the mosquito species.

  2. Please mention the T m for each primer in Table 3.

  3. Please elaborate more on the primer design: on what basis the authors design the primers and for what reason they want to amplify those regions with amplicon sizes mentioned in Table 3.

  4. What was the amount of DNA template used for HRM analyses?

 

Results:

  1. Please show the limitation of detection for each assay in the detection of each mosquito species.

  2. Was auto-calling mode used for clustering? What was the confidence interval? Please mention the mean T m for each species with standard deviation.

  3. Figure 2A, B, D: There was only one sample of C. tenagius included in the analysis. It is difficult to conclude the melting profile of this species if there was only one sample available.

  4. In Table 1, COI-AnophF/HCO2198R has been shown to be able to separate Cx. tenagius from Cx. antennatus, Cx. pipiens from Culex sp. GPA, and Cx. neavei from Cx. duttoni. Since I am not an expert in mosquitoes, is there any specific reason the authors wanted to report the separation between two species of Culex rather than reporting it as a separation between all species?   

  5. In Figure 2A, the melt curves of Cx. antennatus, Cx. neavei, Culex sp. GPA and Cx. pipiens looks closely apart and hard to differentiate. Was the clustering auto- or manually called? What was the confidence interval if it was auto-called? What is the possibility of all these species being present or analysed at the same time? It would be hard to differentiate them if all of them are present in a same run of HRM analysis.

  6. How do the melt curves of the unseparated species appear as compared to those in the same genus which could be differentiated? For instance, Cx. perexiguus vs.  Cx. tenagius, Cx. antennatus, Cx. pipiens, Culex sp. GPA, Cx. neavei and Cx. duttoni. And also melting curves of 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, which could not be differentiated in this study.

  7. In Figure 4, intraspecies variation in the target sequence is seen, for instance, in the four strains of Ma. africana. Although the authors did mention on Page 6 “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”. I am not sure how confident it is to employ these assays in the presence of intraspecies variations, plus the sample size may be too small to validate the assays. 

  8. Figure 5: please revise the figure legend.

 

Discussion:

  1. On page 8, 2 nd paragraph, the authors mentioned “Surprisingly, HRM analysis of PCR products from the COIAnophF/HCO2198R primers, which were designed for Anopheles, could not distinguish between these sibling species….” Can the authors explain the possible reason for this?

  2. Again, since I am not a mosquito expert, are the mosquitoes of the same genus morphologically identical? If the assays are successfully developed, are the mosquitoes going to be morphologically identified prior to subjecting them to HRM analysis? How are the authors going to decide which primer pairs to use later in the mosquito identification?

I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

F1000Res. 2016 Sep 12. doi: 10.5256/f1000research.9928.r15904

Referee response for version 1

Michael Zianni 1

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 to identify more species from multiple genera of mosquitoes.

The methodology is clear with sufficient details for it to be reproduced by listing all appropriate reagents, DNA primer sequences and real-time PCR instrumentation. I do recommend adding the criteria by which the melt curves were deemed to be sufficiently different to allow identification of the species as compared to the "Did Not Separate" state as reported in Table 4.

Figures 1 - 3 and 5 are clear and support the results summarized in table 4. I appreciate the authors efforts to repeat and report data from the previously published primers ("AgamUni") as a point of comparison. Appropriate controls were used with (1) water as a negative control for amplification and (2) samples from defined colonies and samples previously sequenced as positive controls. The most significant limitation is the number of replicates, and the diversity of sample collection points for each species.   The authors clearly acknowledge these limitations in the conclusion and clearly state the need for additional samples to asses the intra-specific variation which is critically important information to make this method highly useful.

In summary, the paper is clearly and concisely written with 1 minor recommendations for additional information on the method.  The goals of the research are clearly stated, and the results as well as the conclusions support the goals.  The researchers have achieved the goals by identifying and confirming at least one primer pair for each of 4 genera that identify various species that are difficult to identify by morphology alone.

I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Citations

    1. Ajamma YU, Mararo E, Omondi D, et al. : Dataset 1 in: Rapid and high throughput molecular identification of diverse mosquito species by high resolution melting analysis. F1000Research. 2016. Data Source [DOI] [PMC free article] [PubMed]

    Supplementary Materials

    Raw Rotor-Gene Q HRM data files (.rex), viewable using Rotor-Gene Q software (Qiagen)

    ‘Contents.csv’ contains a description of the files.

    Copyright: © 2016 Ajamma YU et al.

    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).

    Click here for additional data file. (1.6MB, tgz)

    Data Availability Statement

    The data referenced by this article are under copyright with the following copyright statement: Copyright: © 2016 Ajamma YU et al.

    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). http://creativecommons.org/publicdomain/zero/1.0/

    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.d130565 36

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