Identification Of Mosquito Species Research Articles

Rapid identification of mosquito species and age by mass spectrometric analysis

BackgroundA rapid, accurate method to identify and to age-grade mosquito populations would be a major advance in predicting the risk of pathogen transmission and evaluating the public health impact of vector control interventions. Whilst other spectrometric or transcriptomic methods show promise, current approaches rely on challenging morphological techniques or simple binary classifications that cannot identify the subset of the population old enough to be infectious. In this study, the ability of rapid evaporative ionisation mass spectrometry (REIMS) to identify the species and age of mosquitoes reared in the laboratory and derived from the wild was investigated.ResultsThe accuracy of REIMS in identifying morphologically identical species of the Anopheles gambiae complex exceeded 97% using principal component/linear discriminant analysis (PC-LDA) and 84% based on random forest analysis. Age separation into 3 different age categories (1 day, 5–6 days, 14–15 days) was achieved with 99% (PC-LDA) and 91% (random forest) accuracy. When tested on wild mosquitoes from the UK, REIMS data could determine the species and age of the specimens with accuracies of 91 and 90% respectively.ConclusionsThe accuracy of REIMS to resolve the species and age of Anopheles mosquitoes is comparable to that achieved by infrared spectroscopy approaches. The processing time and ease of use represent significant advantages over current, dissection-based methods. Importantly, the accuracy was maintained when using wild mosquitoes reared under differing environmental conditions, and when mosquitoes were stored frozen or desiccated. This high throughput approach thus has potential to conduct rapid, real-time monitoring of vector populations, providing entomological evidence of the impact of alternative interventions.

Comparative performance of a multi‐locus barcoding approach to enhance taxonomic resolution of New Zealand mosquitoes (Diptera: Culicidae)

AbstractMosquitoes (Diptera: Culicidae) pose a serious threat to human health globally and the accurate identification of mosquito species is fundamental to entomological diagnostics and surveillance implementing effective vector control and management. However, cryptic species complexes, incomplete or damaged specimens, and juvenile life stages complicates the task. Molecular characterisation has shown the potential to identify the mosquito species accurately and overcomes the difficulties that morphological diagnosis face. Here, we assessed the effectiveness of a multi‐locus barcoding approach using cytochrome c oxidase subunit I (COI), internal transcribed spacer 1 (ITS1) and internal transcribed spacer 2 (ITS2) regions to identify the New Zealand mosquito species (n = 16) at the highest taxonomic resolution, which can make diagnosis more accurate and efficient. Our results show that most of the New Zealand mosquito species could be distinctly separated from each other as well as from other exotic species using either of these barcoding regions (i.e., COI, ITS1 and ITS2). The assessment of taxonomic discriminatory power of COI, ITS1 and ITS2 barcodes suggests that ITS2 can better distinguish the New Zealand closely‐related species. Two closely‐related endemic species from the Culex pervigilans species complex (Cx. rotoruae and Cx. pervigilans) were difficult to distinguish using COI and ITS1 regions. However, the ITS2 barcode could detect a greater genetic variation among individuals of those two species and demonstrate the potential to resolve the relationships among them to provide better resolution as a complementary to COI. Overall, this study provides a reference DNA barcode database of COI and ITS2 for New Zealand mosquito species, which will aid in their accurate identification at a higher taxonomic resolution and corroborate the traditional morphological approaches to perform better species discrimination among closely‐related species complex. The study also assessed the preliminary genetic diversity of the mosquito species from different regions of New Zealand, which can be used as a baseline for uncovering the environmental and geographical effect on genomic variations among New Zealand mosquito populations in the future.

DNA Barcoding of Morphologically Characterized Mosquitoes Belonging to the Genus Mansonia from the Atlantic Forest and Brazilian Savanna

The identification of mosquito species is necessary for determining the entomological components of disease transmission. However, identification can be difficult in species that are morphologically similar. The cytochrome c oxidase subunit I (COI) DNA barcode region is considered a valuable and reliable diagnostic tool for mosquito species recognition, including those that belong to species complexes. Mansonia mosquitoes are found in forests near swampy areas. They are nocturnal and are highly attracted to light. Hematophagous adult females exhibit aggressive biting behavior and can become infected with and transmit pathogens during their feeding, including some epizootic viruses and avian malaria. In Brazil, twelve Mansonia species have been reported. In a recent study from the São Paulo Zoo in Brazil, three morphologically distinct species were collected and identified, namely: Mansonia (Mansonia) indubitans, Ma. (Man.) pseudotitillans and Ma. (Man.) titillans. However, confirmation of these species by molecular identification was unsuccessful due to a lack of COI sequences in the GenBank database. Thus, this research aimed to describe the COI DNA barcode sequences of some morphologically characterized Mansonia (Man.) species from Brazil and to determine their utility in delimiting species collected from the Atlantic Forest and Brazilian Savanna. Accordingly, we provide tools for the genetic identification of species that play a significant role in pathogen transmission in wildlife and potentially humans. We show that the delimitation of Mansonia species via five different approaches based on COI DNA sequences (BI, NJ, ASAP, bPTP and GMYC) yield basically the same groups identified by traditional taxonomy, and we provide the identification of specimens that were previously identified only up to the subgenus level. We also provide COI sequences from two Mansonia species that were not previously available in sequence databases, Ma. wilsoni and Ma. pseudotitillans, and thus contribute to the ongoing global effort to standardize DNA barcoding as a molecular means of species identification.

Evaluation of Modern Techniques for Species Identification of Lutzia Mosquitoes (Diptera: Culicidae) in Thailand: Geometric Morphometrics and DNA Barcoding.

There are four species of Lutzia mosquitoes in Thailand, including Lutzia chiangmaiensis, Lt. fuscana, Lt. halifaxii, and Lt. vorax. The accurate species identification of adult Lutzia mosquitoes based on morphological features requires many body parts, including the abdominal terga and wing. However, species identification is difficult in the case of damaged specimens when some of their morphological character is missing due to transit or gathering in the field. Thus, we evaluated the efficacy of the landmark-based geometric morphometric (GM) approach for the discrimination of Lutzia species in Thailand. In addition, DNA barcoding was also used in parallel with the GM approach to identify the species. Larvae of Lutzia were collected, raised into adults, and identified based on their morphological characteristics. The validated reclassification test results clearly demonstrated that wing shape resulted in a high level of success in identification (correct identifications ranged from 92.50% to 100%); however, based on the DNA barcoding analyses, our results showed that it was poorly effective in identifying Lt. fuscana and Lt. halifaxii based on an overlap between the intraspecific and interspecific divergence. Moreover, our survey results provide updates on the distribution of Lt. chiangmaiensis and Lt. vorax in Thailand. This research will help medical entomologists more efficiently identify mosquitoes in the genus Lutzia, resulting in more effective mosquito control and surveillance.

Modification of the Folmer primers for the cytochrome c oxidase gene facilitates identification of mosquitoes

BackgroundAccurate identification of mosquito species is essential for the development and optimization of strategies to control mosquitoes and mosquito-borne diseases. Problems with the morphological identification of mosquito species have led to the use of molecular identification techniques, in particular the Folmer cytochrome c oxidase subunit I (COI) PCR system (FCOS), originally designed to identify a range of other invertebrates.MethodsAs there can be difficulties identifying mosquitoes using FCOS, we re-evaluated the FCOS primers and developed a new COI-based SYBR PCR (the Auburn COI system—AUCOS) to improve the molecular identification of mosquitoes. Sequence data in GenBank for 33 species from 10 genera of mosquitoes were used to develop our AUCOS primers. Two molecular assays (AUCOS, FCOS) and morphological identification were carried out on mosquitoes collected from the field in Auburn, Alabama (USA) and on Saint Kitts.ResultsWith a convenience sample of individual mosquitoes comprising 19 species from six genera in Saint Kitts (n = 77) and Auburn (n = 48), our AUCOS provided higher-quality sequence data than FCOS. It also proved more sensitive than FCOS, successfully amplifying 67.5% (85/126) as opposed to 16.7% (21/126) of the samples. The species determined by morphology, or genus with damaged samples, matched that as determined by AUCOS for 84.9% (62/73) of the samples. Morphological classification was confirmed by FCOS with 81.0% (17/21) of samples producing utilizable sequences. While both FCOS and AUCOS correctly identified all the Aedes, Anopheles, Deinocerites, and Uranotaenia species in the study, identification of Culex species was less successful with both methods: 50.0% (3/6) by FCOS and 35.7% (5/14) by AUCOS.ConclusionsThe AUCOS DNA barcoding system for mosquito species described in this study is superior to the existing FCOS for the identification of mosquito species. As AUCOS and FCOS amplify the same variable region of the COI, the large amount of existing data on GenBank can be used to identify mosquito species with sequences produced by either PCR.Graphical

A Swin Transformer-based model for mosquito species identification

Mosquito transmit numbers of parasites and pathogens resulting in fatal diseases. Species identification is a prerequisite for effective mosquito control. Existing morphological and molecular classification methods have evitable disadvantages. Here we introduced Deep learning techniques for mosquito species identification. A balanced, high-definition mosquito dataset with 9900 original images covering 17 species was constructed. After three rounds of screening and adjustment-testing (first round among 3 convolutional neural networks and 3 Transformer models, second round among 3 Swin Transformer variants, and third round between 2 images sizes), we proposed the first Swin Transformer-based mosquito species identification model (Swin MSI) with 99.04% accuracy and 99.16% F1-score. By visualizing the identification process, the morphological keys used in Swin MSI were similar but not the same as those used by humans. Swin MSI realized 100% subspecies-level identification in Culex pipiens Complex and 96.26% accuracy for novel species categorization. It presents a promising approach for mosquito identification and mosquito borne diseases control.

MALDI-TOF MS: An effective tool for a global surveillance of dengue vector species.

Dengue, Zika and chikungunya viruses cause significant human public health burdens in the world. These arboviruses are transmitted by vector mosquito species notably Aedes aegypti and Aedes albopictus. In the Pacific region, more vector species of arboviruses belonging to the Scutellaris Group are present. Due to the expansion of human travel and international trade, the threat of their dispersal in other world regions is on the rise. Strengthening of entomological surveillance ensuring rapid detection of introduced vector species is therefore required in order to avoid their establishment and the risk of arbovirus outbreaks. This surveillance relies on accurate species identification. The aim of this study was to assess the use of the Matrix-Assisted Laser Desorption Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) as a tool for an international identification and surveillance of these mosquito vectors of arboviruses. Field-mosquitoes belonging to 8 species (Ae. aegypti, Ae. albopictus, Aedes polynesiensis, Aedes scutellaris, Aedes pseudoscutellaris, Aedes malayensis, Aedes futunae and Culex quinquefasciatus) from 6 countries in the Pacific, Asian and Madagascar, were included in this study. Analysis provided evidence that a MALDI-TOF database created using mosquitoes from the Pacific region allowed suitable identification of mosquito species from the other regions. This technic was as efficient as the DNA sequencing method in identifying mosquito species. Indeed, with the exception of two Ae. pseudoscutellaris, an exact species identification was obtained for all individual mosquitoes. These findings highlight that the MALDI-TOF MS is a promising tool that could be used for a global comprehensive arbovirus vector surveillance.

Mitochondrial DNA barcoding of mosquito species (Diptera: Culicidae) in Thailand

The correct identification of mosquito species is important for effective mosquito vector control. However, the standard morphological identification of mosquito species based on the available keys is not easy with specimens in the field due to missing or damaged morphological features during mosquito collections, often leading to the misidentification of morphologically indistinguishable. To resolve this problem, we collected mosquito species across Thailand to gather genetic information, and evaluated the DNA barcoding efficacy for mosquito species identification in Thailand. A total of 310 mosquito samples, representing 73 mosquito species, were amplified using mitochondrial cytochrome c oxidase subunit I (COI) primers. The average maximum intraspecific genetic variation of the 73 mosquito species was 1% ranged from 0-5.7%. While, average minimum interspecific genetic variation (the distance to the nearest neighbour) of the 73 mosquito species was 7% ranged from 0.3-12.9%. The identification of success rates based on the "Best Match," "Best Close Match," and "All Species Barcodes" methods were 97.7%, 91.6%, and 81%, respectively. Phylogenetic analyses of Anopheles COI sequences demonstrated a clear separation between almost all species (except for those between An. baimaii and An. dirus), with high bootstrap support values (97%-99%). Furthermore, phylogenetic analyses revealed potential sibling species of An. annularis, An. tessellatus, and An. subpictus in Thailand. Our results indicated that DNA barcoding is an effective molecular approach for the accurate identification of mosquitoes in Thailand.

Mosquito larva distribution and natural Wolbachia infection in campus areas of Nakhon Ratchasima, Thailand

Objective: To determine the prevalence of mosquito larvae in campus areas and the infection rate of endosymbiotic bacteria, Wolbachia in mosquito larvae. Method: The mosquito larvae samples were collected in residential areas and academic buildings of Suranaree University of Technology located in Northeastern Thailand during 2017-2018. Mosquito species identification was performed using GLOBE mosquito protocols and Rattanarithikul & Panthusiri’s keys. The gene encoding for the surface protein of Wolbachia was amplified by PCR and confirmed by DNA sequencing. Results: Armigeres sp. is the highest proportion of mosquito larvae followed by Culex spp., Aedes albopictus, Aedes aegypti, and Toxorynchites spp., respectively. Aedes aegypti have breeding sites mostly in the containers found indoors, whereas the main breeding sites of Aedes albopictus were found in both outdoors and indoors. The House Index and Breteau Index for Aedes spp. was more than 5% and 20%, respectively, in both areas, indicating that these areas are dengue sensitive. The highest proportion of Wolbachia infection was found in the larvae of Culex spp. (86.21%), followed by Aedes albopictus (69.23%) and rarely detected in Aedes aegypti (9.09%). Conclusion: The present study reported the first natural infection of Wolbachia in mosquito larvae in Thailand. Our result suggested that the mosquito species containing higher proportion of Wolbachia are less likely to be vectors for dengue. Therefore, Wolbachia transfection in mosquito larvae could be applied as a biocontrol for dengue and other mosquito-borne disease prevention.

Enhanced procedures for mosquito identification by MALDI-TOF MS

BackgroundIn the last decade, an innovative approach has emerged for arthropod identification based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Increasing interest in applying the original technique for arthropod identification has led to the development of a variety of procedures for sample preparation and selection of body parts, among others. However, the absence of a consensual strategy hampers direct inter-study comparisons. Moreover, these different procedures are confusing to new users. Establishing optimized procedures and standardized protocols for mosquito identification by MALDI-TOF MS is therefore a necessity, and would notably enable the sharing of reference MS databases. Here, we assess the optimal conditions for mosquito identification using MALDI-TOF MS profiling.MethodsThree homogenization methods, two of which were manual and one automatic, were used on three distinct body parts (legs, thorax, head) of two mosquito laboratory strains, Anopheles coluzzii and Aedes aegypti, and the results evaluated. The reproducibility of MS profiles, identification rate with relevant scores and the suitability of procedures for high-throughput analyses were the main criteria for establishing optimized guidelines. Additionally, the consequences of blood-feeding and geographical origin were evaluated using both laboratory strains and field-collected mosquitoes.ResultsRelevant score values for mosquito identification were obtained for all the three body parts assayed using MALDI-TOF MS profiling; however, the thorax and legs were the most suitable specimens, independently of homogenization method or species. Although the manual homogenization methods were associated with a high rate of identification on the three body parts, this homogenization mode is not adaptable to the processing of a large number of samples. Therefore, the automatic homogenization procedure was selected as the reference homogenization method. Blood-feeding status did not hamper the identification of mosquito species, despite the presence of MS peaks from original blood in the MS profiles of the three body parts tested from both species. Finally, a significant improvement in identification scores was obtained for field-collected specimens when MS spectra of species from the same geographical area were added to the database.ConclusionThe results of the current study establish guidelines for the selection of mosquito anatomic parts and modality of sample preparation (e.g. homogenization) for future specimen identification by MALDI-TOF MS profiling. These standardized operational protocols could be used as references for creating an international MS database.

DNA Barcoding of Potential Mosquito Disease Vectors (Diptera, Culicidae) in Jazan Region, Saudi Arabia.

The conventional morphological characterization of mosquito species remains heavily used for species identification in Jazan, Saudi Arabia. It requires substantial expertise and time, as well as having difficulty in confirming identity of morphologically similar species. Therefore, to establish a reliable and accurate identification system that can be applied to understanding spatial distribution of local mosquito species from the Jazan region, DNA barcoding was explored as an integrated tool for mosquito species identification. In this study, 44 adult mosquito specimens were analyzed, which contain 16 species belong to three genera of potential mosquito disease vectors (Aedes, Anopheles, and Culex). The specimens were collected from the Jazan region located in southwest Saudi Arabia. These included old and preserved mosquito voucher specimens. In addition, we assessed the genetic distance based on the generated mitochondrial partial COI DNA barcodes to detect cryptic diversity across these taxa. Nine mosquito species belonging to three genera were successfully barcoded and submitted to GenBank, namely: Aedes aegypti, Aedes caspius, Aedes vexans, Aedes vittatus, Anopheles arabiensis, Culex pipiens, Culex quinquefasciatus, Culex sitiens, and Culex tritaeniorhynchus. Of these nine species, Aedes vexans, Aedes vittatus, Culex sitiens, and Culex tritaeniorhynchus were registered in GenBank for the first time from Saudi Arabia. The DNA barcodes generated a 100% match to known barcodes of these mosquito species, that also matched with the morphological identification. Ae. vexans was found to be either a case of cryptic species (subspecies) or a new species from the region. However, more research has to be conducted to prove the latter. This study directly contributes to the development of a molecular reference library of mosquito species from the Jazan region and Saudi Arabia. The library is essential for confirmation of species in support of existing mosquito surveillance and control programmes.

Myzorhynchus series of Anopheles mosquitoes as potential vectors of Plasmodium bubalis in Thailand

Ungulate malaria parasites and their vectors are among the least studied when compared to other medically important species. As a result, a thorough understanding of ungulate malaria parasites, hosts, and mosquito vectors has been lacking, necessitating additional research efforts. This study aimed to identify the vector(s) of Plasmodium bubalis. A total of 187 female mosquitoes (133 Anopheles spp., 24 Culex spp., 24 Aedes spp., and 6 Mansonia spp. collected from a buffalo farm in Thailand where concurrently collected water buffalo samples were examined and we found only Anopheles spp. samples were P. bubalis positive. Molecular identification of anopheline mosquito species was conducted by sequencing of the PCR products targeting cytochrome c oxidase subunit 1 (cox1), cytochrome c oxidase subunit 2 (cox2), and internal transcribed spacer 2 (ITS2) markers. We observed 5 distinct groups of anopheline mosquitoes: Barbirostris, Hyrcanus, Ludlowae, Funestus, and Jamesii groups. The Barbirostris group (Anopheles wejchoochotei or Anopheles campestris) and the Hyrcanus group (Anopheles peditaeniatus) were positive for P. bubalis. Thus, for the first time, our study implicated these anopheline mosquito species as probable vectors of P. bubalis in Thailand.

Rapid age-grading and species identification of natural mosquitoes for malaria surveillance

The malaria parasite, which is transmitted by several Anopheles mosquito species, requires more time to reach its human-transmissible stage than the average lifespan of mosquito vectors. Monitoring the species-specific age structure of mosquito populations is critical to evaluating the impact of vector control interventions on malaria risk. We present a rapid, cost-effective surveillance method based on deep learning of mid-infrared spectra of mosquito cuticle that simultaneously identifies the species and age class of three main malaria vectors in natural populations. Using spectra from over 40, 000 ecologically and genetically diverse An. gambiae, An. arabiensis, and An. coluzzii females, we develop a deep transfer learning model that learns and predicts the age of new wild populations in Tanzania and Burkina Faso with minimal sampling effort. Additionally, the model is able to detect the impact of simulated control interventions on mosquito populations, measured as a shift in their age structures. In the future, we anticipate our method can be applied to other arthropod vector-borne diseases.

A Barcoding and Morphological Identification of Mosquito Species of the Genus Aedes (Diptera: Culicidae) of the Russian Far East and Northern Vietnam

A Barcoding and Morphological Identification of Mosquito Species of the Genus Aedes (Diptera: Culicidae) of the Russian Far East and Northern Vietnam

Modified Mosquito Programs’ Surveillance Needs and An Image-Based Identification Tool to Address Them

Effective mosquito surveillance and control relies on rapid and accurate identification of mosquito vectors and confounding sympatric species. As adoption of modified mosquito (MM) control techniques has increased, the value of monitoring the success of interventions has gained recognition and has pushed the field away from traditional ‘spray and pray’ approaches. Field evaluation and monitoring of MM control techniques that target specific species require massive volumes of surveillance data involving species-level identifications. However, traditional surveillance methods remain time and labor-intensive, requiring highly trained, experienced personnel. Health districts often lack the resources needed to collect essential data, and conventional entomological species identification involves a significant learning curve to produce consistent high accuracy data. These needs led us to develop MosID: a device that allows for high-accuracy mosquito species identification to enhance capability and capacity of mosquito surveillance programs. The device features high-resolution optics and enables batch image capture and species identification of mosquito specimens using computer vision. While development is ongoing, we share an update on key metrics of the MosID system. The identification algorithm, tested internally across 16 species, achieved 98.4 ± 0.6% % macro F1-score on a dataset of known species, unknown species used in training, and species reserved for testing (species, specimens respectively: 12, 1302; 12, 603; 7, 222). Preliminary user testing showed specimens were processed with MosID at a rate ranging from 181-600 specimens per hour. We also discuss other metrics within technical scope, such as mosquito sex and fluorescence detection, that may further support MM programs.

Assessment of expertise in morphological identification of mosquito species (Diptera, Culicidae) using photomicrographs.

Accurate identification of insect species is an indispensable and challenging requirement for every entomologist, particularly if the species is involved in disease outbreaks. The European MediLabSecure project designed an identification (ID) exercise available to any willing participant with the aim of assessing and improving knowledge in mosquito taxonomy. The exercise was based on high-definition photomicrographs of mosquitoes (26 adult females and 12 larvae) collected from the western Palaearctic. Sixty-five responses from Europe, North Africa and the Middle East were usable. The study demonstrated that the responders were better at identifying females (82% correct responses) than larvae (63%). When the responders reported that they were sure of the accuracy of their ID, the success rate of ID increased (92% for females and 88% for larvae). The top three tools used for ID were MosKeyTool (72% of responders), the ID key following Becker et al. [2010. Mosquitoes and their control, 2nd edn. Berlin: Springer] (38%), and the CD-ROM of Schaffner et al. [2001. Les moustiques d’Europe: logiciel d’identification et d’enseignement – The mosquitoes of Europe: an identification and training programme. Montpellier: IRD; EID] (32%), while other tools were used by less than 10% of responders. Responders reporting the identification of mosquitoes using the MosKeyTool were significantly better (80% correct responses) than non-MosKeyTool users (69%). Most responders (63%) used more than one ID tool. The feedback from responders in this study was positive, with the exercise being perceived as halfway between educational training and a fun quiz. It raised the importance of further expanding training in mosquito ID for better preparedness of mosquito surveillance and control programmes.

Morphological and molecular characterization of Aedes aegypti variant collected from Tamil Nadu, India

Accurate mosquito species identification is the basis of entomological surveys and effective vector control. Mosquito identification is either done morphologically using diagnostic features mentioned in taxonomic keys or by molecular methods using cytochrome oxidase subunit 1 (coxI) and Internal transcribed spacer 2 (ITS2). We performed a larval survey for Aedes mosquitoes from eight different geographical regions in Tamil Nadu, India. The mosquitoes collected during the survey were characterized using both morphological and molecular markers. During an entomological survey from eight different geographical regions in Southern India, a morphological variety named Aedes aegypti var. luciensis was observed. The variant mosquitoes were characterized using both morphological and molecular markers. The variant mosquitoes differed only in the dark scaling of 5th segment of hind-tarsi. Around one third to two third of the 5th segment in variant mosquitoes was dark which has been described as white in identification keys. No other significant difference was observed in adults or immature stages. The variation was heritable and coexisting in the field with the type form mosquitoes. Comparison of the genetic profile of coxI and ITS2 were similar in variant and the type form indicating both of them to be conspecific. The morphological variant mosquitoes were found genetically similar to the Ae. aegypti type form. However, considering its high prevalence and coexistence with Ae. aegypti type form in different geographical regions, detailed studies on bionomics, ecology, genetics, behavior as well as its plausible role in disease transmission are warranted.

DNA Barcoding of Mosquitoes from the Pantanos de Centla Biosphere Reserve, Southeastern Mexico.

Accurate identification of mosquito species is essential to support programs that involve the study of distribution and mosquito control. Numerous mosquito species are difficult to identify based only on morphological characteristics, due to the morphological similarities in different life stages and large numbers of some species that are members of morphologically similar species complexes. In the present study, the mosquitoes collected in the Pantanos de Centla Biosphere Reserve, southeastern Mexico, were evaluated using a combination of morphological and molecular approaches (mitochondrial cytochrome c oxidase subunit I [COI] DNA barcode). A total of 1,576 specimens of 10 genera and 35 species, mostly adult stages, were collected. A total of 225 COI DNA barcode sequences were analyzed; most species formed well-supported groups in the neighbor joining, maximum likelihood, and Bayesian inference trees. The intraspecific Kimura 2-parameter (K2P) genetic distance averaged 1.52%. An intraspecific K2P distance of 6.20% was observed in Anopheles crucians s.l., while a deep split was identified in Culex erraticus and Cx. conspirator. This study showed that COI DNA barcodes offer a reliable approach to support mosquito species identification in Mexico.

Geometric morphometrics and machine learning as tools for the identification of sibling mosquito species of the Maculipennis complex (Anopheles).

Geometric morphometrics allows researchers to use the specific software to quantify and to visualize morphological differences between taxa from insect wings. Our objective was to assess wing geometry to distinguish four Anopheles sibling species of the Maculipennis complex, An. maculipennis s. s., An. daciae sp. inq., An. atroparvus and An. melanoon, found in Northern Italy. We combined the geometric morphometric approach with different machine learning alghorithms: support vector machine (SVM), random forest (RF), artificial neural network (ANN) and an ensemble model (EN). Centroid size was smaller in An. atroparvus than in An. maculipennis s. s. and An. daciae sp. inq. Principal component analysis (PCA) explained only 33% of the total variance and appeared not very useful to discriminate among species, and in particular between An. maculipennis s. s. and An. daciae sp. inq. The performance of four different machine learning alghorithms using procrustes coordinates of wing shape as predictors was evaluated. All models showed ROC-AUC and PRC-AUC values that were higher than the random classifier but the SVM algorithm maximized the most metrics on the test set. The SVM algorithm with radial basis function allowed the correct classification of 83% of An. maculipennis s. s. and 79% of An. daciae sp. inq. ROC-AUC analysis showed that three landmarks, 11, 16 and 15, were the most important procrustes coordinates in mean wing shape comparison between An. maculipennis s. s. and An. daciae sp. inq. The pattern in the three-dimensional space of the most important procrustes coordinates showed a clearer differentiation between the two species than the PCA. Our study demonstrated that machine learning algorithms could be a useful tool combined with the wing geometric morphometric approach.

A DNA barcode reference library of Portuguese mosquitoes.

Mosquitoes are important biological vectors of pathogens and species identification in all life stages is the first step for effective monitoring and control of mosquito-borne diseases. Molecular methods for species identification have been developed over the last years to overcome the limitations of the taxonomic identification based on morphology. DNA barcoding, using a fragment of the mitochondrial cytochrome oxidase I (COI) gene, can be used for species identification but a reliable and comprehensive reference database of verified sequences is required. In this study, we aimed to generate a DNA barcode reference library for the identification of mosquito species from Portuguese mosquito fauna, including most relevant vector species. Mosquitoes captured under the National Vector Surveillance Program (REVIVE) were processed for DNA extraction, COI gene fragment amplification and sequencing. Nighty-eight barcode sequences were obtained, representing 26 species and 6 genera. Sequences were submitted to GenBank and BOLD and were used for validation of phenetic classification. Barcode Index Number (BIN) assignment and Automatic Barcode Gap Discovery (ABGD) were used and clustered COI sequences into twenty-five molecular operational taxonomic units (MOTUs). This is the first comprehensive study that combines morphological and molecular identification of most mosquito species present in Portugal aiming to offer a reliable framework for mosquito species identification.