Flight traits of dengue-infected Aedes aegypti mosquitoes.

Understanding the flight behaviour of dengue-infected mosquitoes can play a vital role in various contexts, including modelling disease risks and developing effective interventions against dengue. Studies on the locomotor activity of dengue-infected mosquitoes have often faced challenges in terms of methodology. Some studies used small tubes, which impacted the natural movement of the mosquitoes, while others that used cages did not capture the three-dimensional flights, despite mosquitoes naturally flying in three dimensions. In this study, we utilised Mask RCNN (Region-based Convolutional Neural Network) along with cubic spline interpolation to comprehensively track the three-dimensional flight behaviour of dengue-infected Aedes aegypti mosquitoes. This analysis considered a number of parameters as characteristics of mosquito flight, including flight duration, number of flights, Euclidean distance, flight speed, and the volume (space) covered during flights. The accuracy achieved for mosquito detection and tracking was 98.34% for flying mosquitoes and 100% for resting mosquitoes. Notably, the interpolated data accounted for only 0.31%, underscoring the reliability of the results. Flight traits results revealed that exposure to the dengue virus significantly increases the flight duration (p-value 0.0135 × 10-3) and volume (space) covered during flights (p-value 0.029) whilst decreasing the total number of flights compared to uninfected mosquitoes. The study did not observe any evident impact on the Euclidean distance (p-value 0.064) and speed (p-value 0.064) of Aedes aegypti. These results highlight the intricate relationship between dengue infection and the flight behaviour of Aedes aegypti, providing valuable insights into the virus transmission dynamics. This study focused on dengue-infected Aedes aegypti mosquitoes; future research can explore the impact of other arboviruses on mosquito flight behaviour.

Engineered Antiviral Sensor Targets Infected Mosquitoes.

Escalating vector disease burdens pose significant global health risks, as such innovative tools for targeting mosquitoes are critical. CRISPR-Cas technologies have played a crucial role in developing powerful tools for genome manipulation in various eukaryotic organisms. Although considerable efforts have focused on utilizing class II type II CRISPR-Cas9 systems for DNA targeting, these modalities are unable to target RNA molecules, limiting their utility against RNA viruses. Recently, the Cas13 family has emerged as an efficient tool for RNA targeting; however, the application of this technique in mosquitoes, particularly Aedes aegypti, has yet to be fully realized. In this study, we engineered an antiviral strategy termed REAPER (vRNA Expression Activates Poisonous Effector Ribonuclease) that leverages the programmable RNA-targeting capabilities of CRISPR-Cas13 and its potent collateral activity. REAPER remains concealed within the mosquito until an infectious blood meal is uptaken. Upon target viral RNA infection, REAPER activates, triggering programmed destruction of its target arbovirus such as chikungunya. Consequently, Cas13-mediated RNA targeting significantly reduces viral replication and viral prevalence of infection, and its promiscuous collateral activity can even kill infected mosquitoes within a few days. This innovative REAPER technology adds to an arsenal of effective molecular genetic tools to combat mosquito virus transmission.

EggCountAI: a convolutional neural network-based software for counting of Aedes aegypti mosquito eggs.

BACKGROUND: Mosquito-borne diseases exert a huge impact on both animal and human populations, posing substantial health risks. The behavioural and fitness traits of mosquitoes, such as locomotion and fecundity, are crucial factors that influence the spread of diseases. In existing egg-counting tools, each image requires separate processing with adjustments to various parameters such as intensity threshold and egg area size. Furthermore, accuracy decreases significantly when dealing with clustered or overlapping eggs. To overcome these issues, we have developed EggCountAI, a Mask Region-based Convolutional Neural Network (RCNN)-based free automatic egg-counting tool for Aedes aegypti mosquitoes. METHODS: The study design involves developing EggCountAI for counting mosquito eggs and comparing its performance with two commonly employed tools-ICount and MECVision-using 10 microscopic and 10 macroscopic images of eggs laid by females on a paper strip. The results were validated through manual egg counting on the strips using ImageJ software. Two different models were trained on macroscopic and microscopic images to enhance egg detection accuracy, achieving mean average precision, mean average recall, and F1-scores of 0.92, 0.90, and 0.91 for the microscopic model, and 0.91, 0.90, and 0.90 for the macroscopic model, respectively. EggCountAI automatically counts eggs in a folder containing egg strip images, offering adaptable filtration for handling impurities of varying sizes. RESULTS: The results obtained from EggCountAI highlight its remarkable performance, achieving overall accuracy of 98.88% for micro images and 96.06% for macro images. EggCountAI significantly outperformed ICount and MECVision, with ICount achieving 81.71% accuracy for micro images and 82.22% for macro images, while MECVision achieved 68.01% accuracy for micro images and 51.71% for macro images. EggCountAI also excelled in other statistical parameters, with mean absolute error of 1.90 eggs for micro, 74.30 eggs for macro, and a strong correlation and R-squared value (0.99) for both micro and macro. The superior performance of EggCountAI was most evident when handling overlapping or clustered eggs. CONCLUSION: Accurate detection and counting of mosquito eggs enables the identification of preferred egg-laying sites and facilitates optimal placement of oviposition traps, enhancing targeted vector control efforts and disease transmission prevention. In future research, the tool holds the potential to extend its application to monitor mosquito feeding preferences.

Flight behaviour monitoring and quantification of aedes aegypti using convolution neural network.

Mosquito-borne diseases cause a huge burden on public health worldwide. The viruses that cause these diseases impact the behavioural traits of mosquitoes, including locomotion and feeding. Understanding these traits can help in improving existing epidemiological models and developing effective mosquito traps. However, it is difficult to understand the flight behaviour of mosquitoes due to their small sizes, complicated poses, and seemingly random moving patterns. Currently, no open-source tool is available that can detect and track resting or flying mosquitoes. Our work presented in this paper provides a detection and trajectory estimation method using the Mask RCNN algorithm and spline interpolation, which can efficiently detect mosquitoes and track their trajectories with higher accuracy. The method does not require special equipment and works excellently even with low-resolution videos. Considering the mosquito size, the proposed method's detection performance is validated using a tracker error and a custom metric that considers the mean distance between positions (estimated and ground truth), pooled standard deviation, and average accuracy. The results showed that the proposed method could successfully detect and track the flying (≈ 96% accuracy) as well as resting (100% accuracy) mosquitoes. The performance can be impacted in the case of occlusions and background clutters. Overall, this research serves as an efficient open-source tool to facilitate further examination of mosquito behavioural traits.

Potent pan huACE2-dependent sarbecovirus neutralizing monoclonal antibodies isolated from a BNT162b2-vaccinated SARS survivor.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern such as Omicron hampered efforts in controlling the ongoing coronavirus disease 2019 pandemic due to their ability to escape neutralizing antibodies induced by vaccination or prior infection, highlighting the need to develop broad-spectrum vaccines and therapeutics. Most human monoclonal antibodies (mAbs) reported to date have not demonstrated true pan-sarbecovirus neutralizing breadth especially against animal sarbecoviruses. Here, we report the isolation and characterization of highly potent mAbs targeting the receptor binding domain (RBD) of huACE2-dependent sarbecovirus from a SARS-CoV survivor vaccinated with BNT162b2. Among the six mAbs identified, one (E7) showed better huACE2-dependent sarbecovirus neutralizing potency and breadth than any other mAbs reported to date. Mutagenesis and cryo-electron microscopy studies indicate that these mAbs have a unique RBD contact footprint and that E7 binds to a quaternary structure-dependent epitope.

Holobiont perspectives on tripartite interactions among microbiota, mosquitoes, and pathogens.

Mosquito-borne diseases like dengue and malaria cause a significant global health burden. Unfortunately, current insecticides and environmental control strategies aimed at the vectors of these diseases are only moderately effective in decreasing disease burden. Understanding and manipulating the interaction between the mosquito holobiont (i.e., mosquitoes and their resident microbiota) and the pathogens transmitted by these mosquitoes to humans and animals could help in developing new disease control strategies. Different microorganisms found in the mosquito's microbiota affect traits related to mosquito survival, development, and reproduction. Here, we review the physiological effects of essential microbes on their mosquito hosts; the interactions between the mosquito holobiont and mosquito-borne pathogen (MBP) infections, including microbiota-induced host immune activation and Wolbachia-mediated pathogen blocking (PB); and the effects of environmental factors and host regulation on the composition of the microbiota. Finally, we briefly overview future directions in holobiont studies, and how these may lead to new effective control strategies against mosquitoes and their transmitted diseases.

N-Terminomic Changes in Neurons During Excitotoxicity Reveal Proteolytic Events Associated With Synaptic Dysfunctions and Potential Targets for Neuroprotection.

Excitotoxicity, a neuronal death process in neurological disorders such as stroke, is initiated by the overstimulation of ionotropic glutamate receptors. Although dysregulation of proteolytic signaling networks is critical for excitotoxicity, the identity of affected proteins and mechanisms by which they induce neuronal cell death remain unclear. To address this, we used quantitative N-terminomics to identify proteins modified by proteolysis in neurons undergoing excitotoxic cell death. We found that most proteolytically processed proteins in excitotoxic neurons are likely substrates of calpains, including key synaptic regulatory proteins such as CRMP2, doublecortin-like kinase I, Src tyrosine kinase and calmodulin-dependent protein kinase IIß (CaMKIIß). Critically, calpain-catalyzed proteolytic processing of these proteins generates stable truncated fragments with altered activities that potentially contribute to neuronal death by perturbing synaptic organization and function. Blocking calpain-mediated proteolysis of one of these proteins, Src, protected against neuronal loss in a rat model of neurotoxicity. Extrapolation of our N-terminomic results led to the discovery that CaMKIIα, an isoform of CaMKIIß, undergoes differential processing in mouse brains under physiological conditions and during ischemic stroke. In summary, by identifying the neuronal proteins undergoing proteolysis during excitotoxicity, our findings offer new insights into excitotoxic neuronal death mechanisms and reveal potential neuroprotective targets for neurological disorders.

Engineered Antiviral Sensor Targets Infected Mosquitoes.

Escalating vector disease burdens pose significant global health risks, so innovative tools for targeting mosquitoes are critical. We engineered an antiviral strategy termed REAPER (vRNA Expression Activates Poisonous Effector Ribonuclease) that leverages the programmable RNA-targeting capabilities of CRISPR Cas13 and its potent collateral activity. Akin to a stealthy Trojan Horse hiding in stealth awaiting the presence of its enemy, REAPER remains concealed within the mosquito until an infectious blood meal is up taken. Upon target viral RNA infection, REAPER activates, triggering programmed destruction of its target arbovirus such as chikungunya. Consequently, Cas13 mediated RNA targeting significantly reduces viral replication and its promiscuous collateral activity can even kill infected mosquitoes. This innovative REAPER technology adds to an arsenal of effective molecular genetic tools to combat mosquito virus transmission.

Developing Wolbachia-based disease interventions for an extreme environment.

Aedes aegypti mosquitoes carrying self-spreading, virus-blocking Wolbachia bacteria are being deployed to suppress dengue transmission. However, there are challenges in applying this technology in extreme environments. We introduced two Wolbachia strains into Ae. aegypti from Saudi Arabia for a release program in the hot coastal city of Jeddah. Wolbachia reduced infection and dissemination of dengue virus (DENV2) in Saudi Arabian mosquitoes and showed complete maternal transmission and cytoplasmic incompatibility. Wolbachia reduced egg hatch under a range of environmental conditions, with the Wolbachia strains showing differential thermal stability. Wolbachia effects were similar across mosquito genetic backgrounds but we found evidence of local adaptation, with Saudi Arabian mosquitoes having lower egg viability but higher adult desiccation tolerance than Australian mosquitoes. Genetic background effects will influence Wolbachia invasion dynamics, reinforcing the need to use local genotypes for mosquito release programs, particularly in extreme environments like Jeddah. Our comprehensive characterization of Wolbachia strains provides a foundation for Wolbachia-based disease interventions in harsh climates.

Towards Integrated Management of Dengue in Mumbai.

With increasing urbanisation, the dengue disease burden is on the rise in India, especially in large cities such as Mumbai. Current dengue surveillance in Mumbai includes municipal corporation carrying out specific activities to reduce mosquito breeding sites and the use of insecticides to suppress the adult mosquito populations. Clinical cases remain either underreported or misreported due to the restriction to government clinics, missing the large private health care sector. There is a need for an integrated approach to manage dengue outbreaks in Mumbai. There are various novel strategies available for use that can be utilised to improve disease detection, mosquito surveillance, and control of mosquito-borne diseases. These novel technologies are discussed in this manuscript. Given the complex ecosystem of mosquito-borne diseases in Mumbai, integrating data obtained from these technologies would support the ongoing mosquito control measures in Mumbai.

Advances in Understanding Vector Behavioural Traits after Infection.

Vector behavioural traits, such as fitness, host-seeking, and host-feeding, are key determinants of vectorial capacity, pathogen transmission, and epidemiology of the vector-borne disease. Several studies have shown that infection with pathogens can alter these behavioural traits of the arthropod vector. Here, we review relevant publications to assess how pathogens modulate the behaviour of mosquitoes and ticks, major vectors for human diseases. The research has shown that infection with pathogens alter the mosquito's flight activity, mating, fecundity, host-seeking, blood-feeding, and adaptations to insecticide bed nets, and similarly modify the tick's locomotion, questing heights, vertical and horizontal walks, tendency to overcome obstacles, and host-seeking ability. Although some of these behavioural changes may theoretically increase transmission potential of the pathogens, their effect on the disease epidemiology remains to be verified. This study will not only help in understanding virus-vector interactions but will also benefit in establishing role of these behavioural changes in improved epidemiological models and in devising new vector management strategies.

In Vivo Inhibition of Marek's Disease Virus in Transgenic Chickens Expressing Cas9 and gRNA against ICP4.

Marek's disease (MD), caused by MD herpesvirus (MDV), is an economically important disease in chickens. The efficacy of the existing vaccines against evolving virulent stains may become limited and necessitates the development of novel antiviral strategies to protect poultry from MDV strains with increased virulence. The CRISPR/Cas9 system has emerged as a powerful genome editing tool providing an opportunity to develop antiviral strategies for the control of MDV infection. Here, we characterized Tol2 transposon constructs encoding Cas9 and guide RNAs (gRNAs) specific to the immediate early infected-cell polypeptide-4 (ICP4) of MDV. We generated transgenic chickens that constitutively express Cas9 and ICP4-gRNAs (gICP4) and challenged them via intraabdominal injection of MDV-1 Woodlands strain passage-19 (p19). Transgenic chickens expressing both gRNA/Cas9 had a significantly reduced replication of MDV in comparison to either transgenic Cas9-only or the wild-type (WT) chickens. We further confirmed that the designed gRNAs exhibited sequence-specific virus interference in transgenic chicken embryo fibroblast (CEF) expressing Cas9/gICP4 when infected with MDV but not with herpesvirus of turkeys (HVT). These results suggest that CRISPR/Cas9 can be used as an antiviral approach to control MDV infection in chickens, allowing HVT to be used as a vector for recombinant vaccines.

Superinfection Exclusion in Mosquitoes and Its Potential as an Arbovirus Control Strategy.

The continuing emergence of arbovirus disease outbreaks around the world, despite the use of vector control strategies, warrants the development of new strategies to reduce arbovirus transmission. Superinfection exclusion, a phenomenon whereby a primary virus infection prevents the replication of a second closely related virus, has potential to control arbovirus disease emergence and outbreaks. This phenomenon has been observed for many years in plants, insects and mammalian cells. In this review, we discuss the significance of identifying novel vector control strategies, summarize studies exploring arbovirus superinfection exclusion and consider the potential for this phenomenon to be the basis for novel arbovirus control strategies.

Correction: Broad dengue neutralization in mosquitoes expressing an engineered antibody.

[This corrects the article DOI: 10.1371/journal.ppat.1008103.].

Broad dengue neutralization in mosquitoes expressing an engineered antibody.

With dengue virus (DENV) becoming endemic in tropical and subtropical regions worldwide, there is a pressing global demand for effective strategies to control the mosquitoes that spread this disease. Recent advances in genetic engineering technologies have made it possible to create mosquitoes with reduced vector competence, limiting their ability to acquire and transmit pathogens. Here we describe the development of Aedes aegypti mosquitoes synthetically engineered to impede vector competence to DENV. These mosquitoes express a gene encoding an engineered single-chain variable fragment derived from a broadly neutralizing DENV human monoclonal antibody and have significantly reduced viral infection, dissemination, and transmission rates for all four major antigenically distinct DENV serotypes. Importantly, this is the first engineered approach that targets all DENV serotypes, which is crucial for effective disease suppression. These results provide a compelling route for developing effective genetic-based DENV control strategies, which could be extended to curtail other arboviruses.

Virology Downunder, a meeting commentary from the 2019 Lorne Infection and Immunity Conference, Australia.

The aim of this article is to summarise the virology content presented at the 9th Lorne Infection and Immunity Conference, Australia, in February 2019. The broad program included virology as a key theme, and the commentary herein highlights several key virology presentations at the meeting.

Whole Transcriptome Analysis of Aedes albopictus Mosquito Head and Thorax Post-Chikungunya Virus Infection.

Chikungunya virus (CHIKV) is transmitted by Aedes mosquitoes and causes prolonged arthralgia in patients. After crossing the mosquito midgut barrier, the virus disseminates to tissues including the head and salivary glands. To better understand the interaction between Aedes albopictus and CHIKV, we performed RNASeq analysis on pools of mosquito heads and parts of the thorax 8 days post infection, which identified 159 differentially expressed transcripts in infected mosquitos compared to uninfected controls. After validation using RT-qPCR (reverse transcriptase-quantitative polymerase chain reaction), inhibitor of Bruton's tyrosine kinase (BTKi), which has previously been shown to be anti-inflammatory in mammals after viral infection, was further evaluated for its functional significance. Knockdown of BTKi using double-stranded RNA in a mosquito cell line showed no significant difference in viral RNA or infectivity titer. However, BTKi gene knocked-down cells showed increased apoptosis 24 hours post-infection compared with control cells, suggesting involvement of BTKi in the mosquito response to viral infection. Since BTK in mammals promotes an inflammatory response and has been shown to be involved in osteoclastogenesis, a hallmark of CHIKV pathogenesis, our results suggest a possible conserved mechanism at play between mosquitoes and mammals. Taken together, these results will add to our understanding of Aedes Albopictus interactions with CHIKV.

RNASeq Analysis of Aedes albopictus Mosquito Midguts after Chikungunya Virus Infection.

Chikungunya virus (CHIKV) is an emerging pathogen around the world and causes significant morbidity in patients. A single amino acid mutation in the envelope protein of CHIKV has led to a shift in vector preference towards Aedesalbopictus. While mosquitoes are known to mount an antiviral immune response post-infection, molecular interactions during the course of infection at the tissue level remain largely uncharacterised. We performed whole transcriptome analysis on dissected midguts of Aedes albopictus infected with CHIKV to identify differentially expressed genes. For this, RNA was extracted at two days post-infection (2-dpi) from pooled midguts. We initially identified 25 differentially expressed genes (p-value < 0.05) when mapped to a reference transcriptome. Further, multiple differentially expressed genes were identified from a custom de novo transcriptome, which was assembled using the reads that did not align with the reference genome. Thirteen of the identified transcripts, possibly involved in immunity, were validated by qRT-PCR. Homologues of seven of these genes were also found to be significantly upregulated in Aedes aegypti midguts 2 dpi, indicating a conserved mechanism at play. These results will help us to characterise the molecular interaction between Aedes albopictus and CHIKV and can be utilised to reduce the impact of this viral infection.