Immunity, host physiology, and behaviour in infected vectors

Arbovirus impact on mosquito behavior: the jury is still out

Parasites can manipulate host behavior to enhance transmission, but our understanding of arbovirus-induced changes in mosquito behavior is limited. Here, we explore current knowledge on such behavioral alterations in mosquito vectors, focusing on host-seeking and blood-feeding behaviors. Reviewing studies on dengue, Zika, La Crosse, Sindbis, and West Nile viruses in Aedes or Culex mosquitoes reveals subtle yet potentially significant effects. However, assay heterogeneity and limited sample sizes challenge definitive conclusions. To enhance robustness, we propose using deep-learning tools for automated behavior quantification and stress the need for standardized assays. Additionally, conducting longitudinal studies across the extrinsic incubation period and integrating diverse traits into modeling frameworks are crucial for understanding the nuanced implications of arbovirus-induced behavioral changes for virus transmission dynamics.

Barley Yellow Dwarf Virus Influences Its Vector's Endosymbionts but Not Its Thermotolerance

The barley yellow dwarf virus (BYDV) of cereals is thought to substantially increase the high-temperature tolerance of its aphid vector, Rhopalosiphum padi, which may enhance its transmission efficiency. This is based on experiments with North American strains of BYDV and R. padi. Here, we independently test these by measuring the temperature tolerance, via Critical Thermal Maximum (CTmax) and knockdown time, of Australian R. padi infected with a local BYDV isolate. We further consider the interaction between BYDV transmission, the primary endosymbiont of R. padi (Buchnera aphidicola), and a transinfected secondary endosymbiont (Rickettsiella viridis) which reduces the thermotolerance of other aphid species. We failed to find an increase in tolerance to high temperatures in BYDV-infected aphids or an impact of Rickettsiella on thermotolerance. However, BYDV interacted with R. padi endosymbionts in unexpected ways, suppressing the density of Buchnera and Rickettsiella. BYDV density was also fourfold higher in Rickettsiella-infected aphids. Our findings indicate that BYDV does not necessarily increase the temperature tolerance of the aphid transmission vector to increase its transmission potential, at least for the genotype combinations tested here. The interactions between BYDV and Rickettsiella suggest new ways in which aphid endosymbionts may influence how BYDV spreads, which needs further testing in a field context.

Aphrophoridae Role in Xylella fastidiosa subsp. pauca ST53 Invasion in Southern Italy

The Philaenus spumarius L. (Hemiptera Aphrophoridae) is a xylem-sap feeder vector that acquires Xylella fastidiosa subsp. pauca ST53 during feeding on infected plants. The bacterium is the plant pathogen responsible for olive quick decline syndrome that has decimated olive trees in Southern Italy. Damage originates mainly from the insect vector attitude that multiplies the pathogen potentialities propagating Xf in time and space. The principal action to manage insect-borne pathogens and to contain the disease spread consists in vector and transmission control. The analysis of an innovative and sustainable integrated pest management quantitative strategy that targets the vector and the infection by combining chemical and physical control means demonstrates that it is possible to stop the Xylella invasion. This review updates the available topics addressing vectors' identification, bionomics, infection management, and induced disease by Xylella invasion to discuss major available tools to mitigate the damage consequent to the disease.

Tonic Immobility Is Influenced by Starvation, Life Stage, and Body Mass in Ixodid Ticks

The ability to escape predation modulates predator-prey interactions and represents a crucial aspect of organismal life history, influencing feeding, mating success, and survival. Thanatosis, also known as death feigning or tonic immobility (TI), is taxonomically widespread, but understudied in blood-feeding vectors. Hematophagous arthropods, such as ticks, are unique among animals as their predators (birds, mice, lizards, frogs, and other invertebrates) may also be their source of food. Therefore, the trade-off between predator avoidance and host-seeking may shift as the time since the last bloodmeal increases. Because ticks are slow-moving and unable to fly, or otherwise escape, we predicted that they may use TI to avoid predation, but that TI would be influenced by time since the last bloodmeal (starvation). We therefore aimed to quantify this relationship, examining the effect of starvation, body mass, and ontogeny on TI for two tick species: Dermacentor variabilis (Say) (Acari: Ixodidae) and Rhipicephalus sanguineus (Latreille) (Acari: Ixodidae). As we predicted, the duration and use of TI decreased with time since feeding and emergence across species and life stages. Therefore, ticks may become more aggressive in their search for a bloodmeal as they continue to starve, opting to treat potential predators as hosts, rather than avoiding predation by feigning death. Antipredator behaviors such as TI may influence the intensity and amount of time ticks spend searching for hosts, driving patterns of tick-borne pathogen transmission. This identification and quantification of a novel antipredation strategy add a new component to our understanding of tick life history.

The Role of Vector Trait Variation in Vector-Borne Disease Dynamics

Many important endemic and emerging diseases are transmitted by vectors that are biting arthropods. The functional traits of vectors can affect pathogen transmission rates directly and also through their effect on vector population dynamics. Increasing empirical evidence shows that vector traits vary significantly across individuals, populations, and environmental conditions, and at time scales relevant to disease transmission dynamics. Here, we review empirical evidence for variation in vector traits and how this trait variation is currently incorporated into mathematical models of vector-borne disease transmission. We argue that mechanistically incorporating trait variation into these models, by explicitly capturing its effects on vector fitness and abundance, can improve the reliability of their predictions in a changing world. We provide a conceptual framework for incorporating trait variation into vector-borne disease transmission models, and highlight key empirical and theoretical challenges. This framework provides a means to conceptualize how traits can be incorporated in vector borne disease systems, and identifies key areas in which trait variation can be explored. Determining when and to what extent it is important to incorporate trait variation into vector borne disease models remains an important, outstanding question.

Assessment of vector-host-pathogen relationships using data mining and machine learning

Infectious diseases, including vector-borne diseases transmitted by arthropods, are a leading cause of morbidity and mortality worldwide. In the era of big data, addressing broad-scale, fundamental questions regarding the complex dynamics of these diseases will increasingly require the integration of diverse datasets to produce new biological knowledge. This review provides a current snapshot of the systematic assessment of the relationships between microbial pathogens, arthropod vectors and mammalian hosts using data mining and machine learning. We employ PRISMA to identify 32 key papers relevant to this topic. Our analysis shows an increasing use of data mining and machine learning tasks and techniques, including prediction, classification, clustering, association rules mining, and deep learning, over the last decade. However, it also reveals a number of critical challenges in applying these to the study of vector-host-pathogen interactions at various systems biology levels. Here, relevant studies, current limitations and future directions are discussed. Furthermore, the quality of data in relevant papers was assessed using the FAIR (Findable, Accessible, Interoperable, Reusable) compliance criteria to evaluate and encourage reproducibility and shareability of research outcomes. Although shortcomings in their application remain, data mining and machine learning have significant potential to break new ground in understanding fundamental aspects of vector-host-pathogen relationships and their application in this field should be encouraged. In particular, while predictive modeling, feature engineering and supervised machine learning are already being used in the field, other data mining and machine learning methods such as deep learning and association rules analysis lag behind and should be implemented in combination with established methods to accelerate hypothesis and knowledge generation in the domain.

Maternal host responses to poly(I:C) during pregnancy leads to both dysfunctional immune profiles and altered behaviour in the offspring

PROBLEM

Autism spectrum disorder (ASD)-like phenotypes in murine models are linked to elevated pro-inflammatory cytokine profiles caused by maternal immune activation (MIA), but whether MIA alters the immune response in the offspring remains unclear.

METHOD OF STUDY

Polyinosinic:polycytidylic acid (poly:[IC]) was used to induce MIA in immunocompetent and control TLR3-deficient pregnant mice, and cytokine levels were measured in maternal and foetal organs. Furthermore, cytokines and behaviour responses were tested after challenge with lipopolysaccharide in 7-day-old and adult mice.

RESULTS

MIA induced on E12 resulted in changes in the cytokine expression profile in maternal and foetal organs and correlated with TNFα and IL-18 dysregulation in immune organs and brains from neonatal mice born to MIA-induced dams. Such changes further correlated with altered behavioural responses in adulthood.

CONCLUSION

MIA induced by pathogens during pregnancy can interfere with the development of the foetal immune and nervous systems leading to dysfunctional immune responses and behaviour in offspring.

Manipulating Mosquito Tolerance for Arbovirus Control

The inexorable emergence of mosquito-borne arboviruses and the failure of traditional vector control methods to prevent their transmission have triggered the development of alternative entomological interventions to render mosquito populations incapable of carrying arboviruses. Here, we use a theoretical framework to argue that decreasing mosquito tolerance to arbovirus infection could be a more evolutionarily sustainable disease control strategy than increasing mosquito resistance. Increasing resistance is predicted to select for mutant arboviruses escaping resistance, whereas reducing tolerance should lead to the death of infected vectors and thus select for mosquito-attenuated arbovirus variants that are less transmissible.

Mosquito adaptations to hematophagia impact pathogen transmission

Mosquito-borne diseases such as Dengue fever, Chikungunya, and Malaria are critical threats to public health in many parts of the world. Female mosquitoes have evolved multiple adaptive mechanisms to hematophagy, including the ability to efficiently draw and digest blood, as well as the ability to eliminate excess fluids and toxic by-products of blood digestion. Pathogenic agents enter the mosquito digestive tract with the blood meal and need to travel through the midgut and into the hemocele in order to reach the salivary glands and infect a new host. Pathogens need to adjust to these hostile gut, hemocele, and salivary gland environments, and when possible influence the physiology and behavior of their hosts to enhance transmission.

Estimating the effects of variation in viremia on mosquito susceptibility, infectiousness, and R0 of Zika in Aedes aegypti

Zika virus (ZIKV) is an arbovirus primarily transmitted by Aedes mosquitoes. Like most viral infections, ZIKV viremia varies over several orders of magnitude, with unknown consequences for transmission. To determine the effect of viral concentration on ZIKV transmission risk, we exposed field-derived Ae. aegypti mosquitoes to four doses (10³, 10⁴, 10⁵, 10⁶ PFU/mL) representative of potential variation in the field. We demonstrate that increasing ZIKV dose in the blood-meal significantly increases the probability of mosquitoes becoming infected, and consequently disseminating virus and becoming infectious. Additionally, we observed significant interactions between dose and days post-infection on dissemination and overall transmission efficiency, suggesting that variation in ZIKV dose affects the rates of midgut escape and salivary gland invasion. We did not find significant effects of dose on mosquito mortality. We also demonstrate that detecting virus using RT-qPCR approaches rather than plaque assays potentially over-estimates key transmission parameters, including the time at which mosquitoes become infectious and viral burden. Finally, using these data to parameterize an R₀ model, we showed that increasing viremia from 10⁴ to 10⁶ PFU/mL increased relative R₀ 3.8-fold, demonstrating that variation in viremia substantially affects transmission risk.

The number of people at risk for contracting Zika virus (ZIKV) is difficult to estimate accurately because most infected hosts are asymptomatic and the relationship between variation in host viremia and transmission to local mosquitoes is unclear. Controlling ZIKV transmission remains a major challenge due to lack of basic information on transmission mechanisms and gaps in mechanistic models. Therefore, our study highlights the importance of variation in viral concentration that current modeling efforts ignore, which will enhance our ability to predict the number of people at risk for arbovirus infection, overall disease transmission, and the efficacy of current and future intervention strategies. We demonstrated that increased concentration of ZIKV in the blood significantly increases the probability and the rate at which mosquitoes become infectious, which increases the risk of ZIKV transmission.

Management of arthropod vector data - Social and ecological dynamics facing the One Health perspective

Emerging infectious diseases (EIDs) are spread by direct and/or indirect contacts between a pathogen or parasite and their hosts. Arthropod vectors have evolved as excellent bloodsuckers, providing an elegant transportation mode for a wide number of infectious agents. The nature of pathogen and parasite transfer and the models used to predict how a disease might spread are magnified in complexity when an arthropod vector is part of the disease cycle. One Health is a worldwide strategy for expanding interdisciplinary collaborations and communications in all aspects of health care for humans, animals and the environment. It would benefit from a structured analysis to address vectoring of arthropod-borne diseases as a dynamic transactional process. This review focused on how arthropod vector data can be used to better model and predict zoonotic disease outbreaks. With enhanced knowledge to describe arthropod vector disease transfer, researchers will have a better understanding about how to model disease outbreaks. As public health research evolves to include more social-ecological systems, the roles of society, ecology, epidemiology, pathogen/parasite evolution and animal behavior can be better captured in the research design. Overall, because of more collaborative data collection processes on arthropod vectors, disease modeling can better predict conditions where EIDs will occur.

Global Transcriptome Analysis of Aedes aegypti Mosquitoes in Response to Zika Virus Infection

Vector-borne viruses pose great risks to human health. Zika virus has recently emerged as a global threat, rapidly expanding its distribution. Understanding the interactions of the virus with mosquito vectors at the molecular level is vital for devising new approaches in inhibiting virus transmission. In this study, we embarked on analyzing the transcriptional response of Aedes aegypti mosquitoes to Zika virus infection. Results showed large changes in both coding and long noncoding RNAs. Analysis of these genes showed similarities with other flaviviruses, including dengue virus, which is transmitted by the same mosquito vector. The outcomes provide a global picture of changes in the mosquito vector in response to Zika virus infection.

Zika virus (ZIKV) of the Flaviviridae family is a recently emerged mosquito-borne virus that has been implicated in the surge of the number of microcephaly instances in South America. The recent rapid spread of the virus led to its declaration as a global health emergency by the World Health Organization. The virus is transmitted mainly by the mosquito Aedes aegypti, which is also the vector of dengue virus; however, little is known about the interactions of the virus with the mosquito vector. In this study, we investigated the transcriptome profiles of whole A. aegypti mosquitoes in response to ZIKV infection at 2, 7, and 14 days postinfection using transcriptome sequencing. Results showed changes in the abundance of a large number of transcripts at each time point following infection, with 18 transcripts commonly changed among the three time points. Gene ontology analysis revealed that most of the altered genes are involved in metabolic processes, cellular processes, and proteolysis. In addition, 486 long intergenic noncoding RNAs that were altered upon ZIKV infection were identified. Further, we found changes of a number of potential mRNA target genes correlating with those of altered host microRNAs. The outcomes provide a basic understanding of A. aegypti responses to ZIKV and help to determine host factors involved in replication or mosquito host antiviral response against the virus.

IMPORTANCE Vector-borne viruses pose great risks to human health. Zika virus has recently emerged as a global threat, rapidly expanding its distribution. Understanding the interactions of the virus with mosquito vectors at the molecular level is vital for devising new approaches in inhibiting virus transmission. In this study, we embarked on analyzing the transcriptional response of Aedes aegypti mosquitoes to Zika virus infection. Results showed large changes in both coding and long noncoding RNAs. Analysis of these genes showed similarities with other flaviviruses, including dengue virus, which is transmitted by the same mosquito vector. The outcomes provide a global picture of changes in the mosquito vector in response to Zika virus infection.