Explore the vast range of titles available.

The age structure and dynamics of mosquito populations are crucial for understanding their ability to spread diseases and assessing the effectiveness of anti-mosquito control measures. However, available methods to age-grade mosquito populations are labour-intensive and imprecise, particularly for Aedes species. We investigated the potential of Mid-Infrared Spectroscopy (MIRS) combined with Supervised Machine Learning (ML) to rapidly and accurately predict the age of adult females and males of the arbovirus vector, Aedes albopictus . First, we demonstrated the ability of MIRS-ML to age male and female mosquitoes reared under laboratory conditions. Second, we optimised the model with adults emerged from wild collected eggs reared under natural conditions in a semi-field facility, to expose them to more realistic ambient conditions. For each sex we developed three ML models based on the resolution of the predicted adult age class: low (grouping of the mosquitoes by age in 9-day interval), medium (6 days) and high resolution (3 days) from 1 to 15 or 33 days for males and females, respectively. The prediction accuracy decreased as the resolution increased. In males, the accuracy dropped from 99% (low resolution model) to 93% (medium resolution model) and 85.8% (high resolution model); in females the low and medium resolution models showed 89.4% and 78.5% accuracy, which decreased to 72.6% for the high resolution. In a simulated vector control intervention, the high-resolution models allowed to detect shifts in the age-structure of Ae. Albopictus populations with minimal sampling effort (< 100 specimens). Finally, we validated MIRS-ML on two unseen data and reconstructed plausible age structures in (1) laboratory-reared and (2) field-collected Ae. albopictus males and females. Overall, the results represent a first step towards the development of a sound and reproducible MIRS-ML approach for age-grading of Ae. albopictus populations in the wild.

Dengue (DENV) transmission is endemic throughout coastal Ecuador, showing heterogeneous incidence patterns in association with fine-scale variation in Aedes aegypti vector populations and other factors. Here, we investigated the impact of micro-climate and neighbourhood-level variation in urbanization on Aedes abundance, resting behaviour and associations with dengue incidence in two endemic areas. Aedes aegypti were collected in Quinindé and Portoviejo, two urban cantons with hyperendemic dengue transmission in coastal Ecuador. Aedes vectors were sampled in and around houses within urban and peri-urban neighbourhoods at four time periods. We tested for variation in vector abundance and resting behaviour in relation to neighbourhood urbanization level and microclimatic factors. Aedes abundance increased towards the end of the rainy season, was significantly higher in Portoviejo than in Quinindé, and in urban than in peri-urban neighbourhoods. Aedes vectors were more likely to rest inside houses in Portoviejo but had similar abundance in indoor and outdoor resting collections in Quinindé. Over the study period, DENV incidence was lower in Quinindé than in Portoviejo. Relationships between weekly Ae. aegypti abundance and DENV incidence were highly variable between trapping methods; with positive associations being detected only between BG-sentinel and outdoor Prokopack collections. Aedes aegypti abundance was significantly higher in urban than peri-urban neighbourhoods, and their resting behaviour varied between study sites. This fine-scale spatial heterogeneity in Ae. aegypti abundance and behaviour could generate site-specific variation in human exposure and the effectiveness of indoor-based interventions. The trap-dependent nature of associations between Aedes abundance and local DENV incidence indicates further work is needed to identify robust entomological indicators of infection risk.

Mid-infrared spectroscopy (MIRS) combined with machine learning analysis has shown potential for quick and efficient identification of mosquito species and age groups. However, current technology to collect spectra is destructive to the sample and does not allow targeting specific tissues of the mosquito, limiting the identification of other important biological traits such as insecticide resistance. Here, we assessed the use of a non-destructive approach of MIRS for vector surveillance, micro diffuse reflectance spectroscopy (µDRIFT) using mosquito legs to identify species, age and cuticular insecticide resistance within the Anopheles gambiae s.l. complex. These mosquitoes are the major vectors of malaria in Africa and the focus on surveillance in malaria control programs. Legs required significantly less scanning time and showed more spectral consistence compared to other mosquito tissues. Machine learning models were able to identify An. gambiae and An. coluzzii with an accuracy of 0.73, two ages groups (3 and 10 days old) with 0.77 accuracy and we obtained accuracy of 0.75 when identifying cuticular insecticide resistance. Our results highlight the potential of different mosquito tissues and µDRIFT as tools for biological trait identification on mosquitoes that transmit malaria. These results can guide new ways of identifying mosquito traits which can help the creation of innovative surveillance programs by adapting new technology into mosquito surveillance and control tools.

Background Entomological monitoring of Aedes vectors has largely relied on surveillance of larvae, pupae and non-host-seeking adults, which have been poorly correlated with human disease incidence. Exposure to mosquito-borne diseases can be more directly estimated using human landing catches (HLC), although this method is not recommended for Aedes- borne arboviruses. We evaluated a new method previously tested with malaria vectors, the mosquito electrocuting trap (MET) as an exposure-free alternative for measuring landing rates of Aedes mosquitoes on people. Aims were to (i) compare the MET to the BG-sentinel (BGS) trap gold standard approach for sampling host-seeking Aedes vectors; and (ii) characterize the diel activity of Aedes vectors and their association with microclimatic conditions. Methods The study was conducted over 12 days in Quinindé (Ecuador) in May 2017. Mosquito sampling stations were set up in the peridomestic area of four houses. On each day of sampling, each house was allocated either a MET or a BGS trap, which were rotated amongst the four houses daily in a Latin square design. Mosquito abundance and microclimatic conditions were recorded hourly at each sampling station between 7:00–19:00 h to assess variation between vector abundance, trapping methods, and environmental conditions. All Aedes aegypti females were tested for the presence of Zika (ZIKV), dengue (DENV) and chikungunya (CHIKV) viruses. Results A higher number of Ae. aegypti females were found in MET than in BGS collections, although no statistically significant differences in mean Ae. aegypti abundance between trapping methods were found. Both trapping methods indicated female Ae. aegypti had bimodal patterns of host-seeking, being highest during early morning and late afternoon hours. Mean Ae. aegypti daily abundance was negatively associated with daily temperature. No infection by ZIKV, DENV or CHIKV was detected in any Aedes mosquitoes caught by either trapping method. Conclusion We conclude the MET performs at least as well as the BGS standard and offers the additional advantage of direct measurement of per capita human-biting rates. If detection of arboviruses can be confirmed in MET-collected Aedes in future studies, this surveillance method could provide a valuable tool for surveillance and prediction on human arboviral exposure risk.

Although many theoretical models of sympatric speciation propose that genes responsible for assortative mating amongst incipient species should be associated with genomic regions protected from recombination, there are few data to support this theory. The malaria mosquito, Anopheles gambiae, is known for its sympatric cryptic species maintained by pre-mating reproductive isolation and its putative genomic islands of speciation, and is therefore an ideal model system for studying the genomic signature associated with incipient sympatric speciation. Here we selectively introgressed the island of divergence located in the pericentric region of the X chromosome of An. gambiae s.s. into its sister taxon An. coluzzii through 5 generations of backcrossing followed by two generations of crosses within the introgressed strains that resulted in An. coluzzii-like recombinant strains fixed for the M and S marker in the X chromosome island. The mating preference of recombinant strains was then tested by giving virgin recombinant individuals a choice of mates with X-islands matching and non-matching their own island type. We show through genetic analyses of transferred sperm that recombinant females consistently mated with matching island-type males thereby associating assortative mating genes with the X-island of divergence. Furthermore, full-genome sequencing confirmed that protein-coding differences between recombinant strains were limited to the experimentally swapped pericentromeric region. Finally, targeted-genome comparisons showed that a number of these unique differences were conserved in sympatric field populations, thereby revealing candidate speciation genes. The functional demonstration of a close association between speciation genes and the X-island of differentiation lends unprecedented support to island-of-speciation models of sympatric speciation facilitated by pericentric recombination suppression.

Tsetse are the insects responsible for transmitting African trypanosomes, which cause sleeping sickness in humans and animal trypanosomiasis in wildlife and livestock. Knowing the age of these flies is important when assessing the effectiveness of vector control programs and modelling disease risk. Current methods to assess fly age are, however, labour-intensive, slow, and often inaccurate as skilled personnel are in short supply. Mid-infrared spectroscopy (MIRS), a fast and cost-effective tool to accurately estimate several biological traits of insects, offers a promising alternative. This is achieved by characterising the biochemical composition of the insect cuticle using infrared light coupled with machine–learning (ML) algorithms to estimate the traits of interest. We tested the performance of MIRS in estimating tsetse sex and age for the first-time using spectra obtained from their cuticle. We used 541 insectary-reared Glossina m. morsitans of two different age groups for males (5 and 7 weeks) and three age groups for females (3 days, 5 weeks, and 7 weeks). Spectra were collected from the head, thorax, and abdomen of each sample. ML models differentiated between male and female flies with a 96% accuracy and predicted the age group with 94% and 87% accuracy for males and females, respectively. The key infrared regions important for discriminating sex and age classification were characteristic of lipid and protein content. Our results support the use of MIRS as a rapid and accurate way to identify tsetse sex and age with minimal pre-processing. Further validation using wild-caught tsetse could pave the way for this technique to be implemented as a routine surveillance tool in vector control programmes. Lay Summary Male and female tsetse transmit the parasites that cause sleeping sickness in humans and nagana in livestock. To control these diseases, knowing the age of these flies is important, as it helps evaluate the efficacy of control measures and assess disease risk. However, current age-grading methods are laborious, often unreliable, and in the case of male tsetse, highly inaccurate. This study explores a novel approach that uses mid-infrared spectroscopy (MIRS) to estimate the age of individual tsetse. Machine learning (ML) can detect signatures in MIRS for components of a fly's cuticle which differ between sexes and change as they age. We trained ML models that distinguished male from female flies with 96% accuracy and predicted the correct age group with 94% accuracy for males and 87% accuracy for females. MIRS offers a fast and reliable way to identify tsetse sex and age with minimal preparation. If this method is successfully validated with wild flies, it holds the potential to vastly increase the accuracy of the way we monitor and combat these disease-carrying insects, thus offering significant advantages in our efforts to control them.

Although many theoretical models of sympatric speciation propose that genes responsible for assortative mating amongst incipient species should be associated with genomic regions protected from recombination, there are few data to support this theory. The malaria mosquito, Anopheles gambiae, is known for its sympatric cryptic species maintained by pre-mating reproductive isolation and its putative genomic islands of speciation, and is therefore an ideal model system for studying the genomic signature associated with incipient sympatric speciation. Here we selectively introgressed the island of divergence located in the pericentric region of the X chromosome of An. gambiae s.s. into its sister taxon An. coluzzii through 5 generations of backcrossing followed by two generations of crosses within the introgressed strains that resulted in An. coluzzii-like recombinant strains fixed for the M and S marker in the X chromosome island. The mating preference of recombinant strains was then tested by giving virgin recombinant individuals a choice of mates with X-islands matching and non-matching their own island type. We show through genetic analyses of transferred sperm that recombinant females consistently mated with matching island-type males thereby associating assortative mating genes with the X-island of divergence. Furthermore, full-genome sequencing confirmed that protein-coding differences between recombinant strains were limited to the experimentally swapped pericentromeric region. Finally, targeted-genome comparisons showed that a number of these unique differences were conserved in sympatric field populations, thereby revealing candidate speciation genes. The functional demonstration of a close association between speciation genes and the X-island of differentiation lends unprecedented support to island-of-speciation models of sympatric speciation facilitated by pericentric recombination suppression.

Tsetse are the insects responsible for transmitting African trypanosomes, which cause sleeping sickness in humans and animal trypanosomiasis in wildlife and livestock. Knowing the age of these flies is important when assessing the effectiveness of vector control programs and modelling disease risk. However, current methods to assess fly age are labour-intensive, slow, and often inaccurate as skilled personnel are in short supply. Mid-infrared spectroscopy (MIRS), a fast and cost-effective tool to accurately estimate several biological traits of insects, offers a promising alternative. This is achieved by characterising the biochemical composition of the insect cuticle using infrared light coupled with machine learning algorithms to estimate the traits of interest. We tested the performance of MIRS in estimating tsetse sex and age for the first time using spectra obtained from their cuticle. We used 541 insectary-reared Glossina m. morsitans of two different age groups for males (5 and 7 weeks) and three age groups for females (3 days, 5 weeks, and 7 weeks). Spectra were collected from the head, thorax, and abdomen of each sample. Machine learning models differentiated between male and female flies with a 96% accuracy and predicted the age group with 94% and 87% accuracy for males and females, respectively. The key infrared regions important for discriminating sex and age classification were characteristic of lipid and protein content. Our results support the use of MIRS as a fast and accurate way to identify tsetse sex and age with minimal pre-processing. Further validation using wild-caught tsetse can pave the way for this technique to be implemented as a routine surveillance tool in vector control programmes.Competing Interest StatementThe authors have declared no competing interest.

Background: Entomological monitoring of Aedes vectors has largely relied on surveillance of larvae, pupae and non-host-seeking adults, which have been poorly correlated with human disease incidence. Exposure to mosquito-borne diseases can be more directly estimated using Human Landing Catches (HLC), although this method is not recommended for Aedes-borne arboviruses. We evaluated a new method previously tested with malaria vectors, the Mosquito Electrocuting Trap (MET) as an exposure-free alternative for measuring landing rates of Aedes mosquitoes on people. Aims were to 1) compare the MET to the BG-sentinel (BGS) trap gold standard approach for sampling host-seeking Aedes vectors; 2) characterize the diel activity of Aedes vectors and their association with microclimatic conditions. Methods: The study was conducted over 12 days in Quinindé – Ecuador in May 2017. Mosquito sampling stations were set up in the peridomestic area of four houses. On each day of sampling, each house was allocated either a MET or a BGS trap, which were rotated amongst the four houses daily in a Latin square design. Mosquito abundance and microclimatic conditions were recorded hourly at each sampling station between 07:00-19:00 hours to assess variation between vector abundance, trapping methods, and environmental conditions. All Aedes aegypti females were tested for the presence of Zika (ZIKV), dengue (DENV) and chikungunya (CHIKV) viruses. Results: A higher number of Ae. aegypti females were found in MET than in BGS collections, although no statistically significant differences in mean Ae. aegypti abundance between trapping methods were found. Both trapping methods indicated female Ae. aegypti had bimodal patterns of host seeking, being highest during early morning and late afternoon hours. Mean Ae. aegypti daily abundance was negatively associated with daily temperature. No infection by ZIKV, DENV or CHIKV was detected in any Aedes mosquitoes caught by either trapping method. Conclusion: We conclude the MET performs at least as well as the BGS standard, and offers the additional advantage of direct measurement of per capita human biting rates. If detection of arboviruses can be confirmed in MET-collected Aedes in future studies, this surveillance method could provide a valuable tool for surveillance and prediction on human arboviral exposure risk. Footnotes * https://osf.io/zwbs8