New discoveries and applications of mosquito fungal pathogens

Shen, Danyu; Nyawira, Karani T.; Xia, Ai

doi:10.1016/j.cois.2020.05.003

Cited by 17 publications

(22 citation statements)

References 45 publications

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“…Fungal diseases are common in insects, including mosquitoes. These entomopathogenic fungi have been extensively described elsewhere (e.g., Scholte et al, 2004 ; Kanzok and Jacobs-Lorena, 2006 ; Shen et al, 2020 ). However, it is not so clear that these organisms can be considered part of the normal microflora of the mosquito microbiome.…”

Section: A Path Forward: a Most Wanted List For Microbes In Gnotobiotic Studiesmentioning

confidence: 99%

The Axenic and Gnotobiotic Mosquito: Emerging Models for Microbiome Host Interactions

et al. 2021

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The increasing availability of modern research tools has enabled a revolution in studies of non-model organisms. Yet, one aspect that remains difficult or impossible to control in many model and most non-model organisms is the presence and composition of the host-associated microbiota or the microbiome. In this review, we explore the development of axenic (microbe-free) mosquito models and what these systems reveal about the role of the microbiome in mosquito biology. Additionally, the axenic host is a blank template on which a microbiome of known composition can be introduced, also known as a gnotobiotic organism. Finally, we identify a “most wanted” list of common mosquito microbiome members that show the greatest potential to influence host phenotypes. We propose that these are high-value targets to be employed in future gnotobiotic studies. The use of axenic and gnotobiotic organisms will transition the microbiome into another experimental variable that can be manipulated and controlled. Through these efforts, the mosquito will be a true model for examining host microbiome interactions.

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Section: A Path Forward: a Most Wanted List For Microbes In Gnotobiotic Studiesmentioning

confidence: 99%

The Axenic and Gnotobiotic Mosquito: Emerging Models for Microbiome Host Interactions

et al. 2021

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“…Twelve species of entomopathogenic Oomycota are known to exist within six genera: Lagenidium (L. giganteum), Leptolegnia (L. caudata and L, chapmanii), Pythium (P. carolinianum, P. sierrensis, and P. flevoense), Crypticola (C. clavulifera and C. entomophaga), Couchia (C. amphora, C. linnophila, and C. circumplexa), and Aphanomyces (A. laevis) (Araújo and Hughes 2016;Mendoza et al 2018). Most are facultative parasites of mosquito larvae belonging to the genera Anopheles, Culex, Aedes, Ochlerotatus, Culiseta, Orthopodomyia, Uranotaenia, Psorophora, and Mansonia (Frances et al 1989;Woodring et al 1995;Scholte et al 2004;Patwardhan et al 2005;Vyas et al 2007;Singh and Prakash 2012;Vilela et al 2018;Shen et al 2019;Vilela et al 2019;Shen et al 2020a). Some examples of infected insects are listed in Table 1.…”

Section: Oomycotamentioning

confidence: 99%

Fungi of entomopathogenic potential in Chytridiomycota and Blastocladiomycota, and in fungal allies of the Oomycota and Microsporidia

Kaczmarek

Boguś

2021

IMA Fungus

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The relationship between entomopathogenic fungi and their insect hosts is a classic example of the co-evolutionary arms race between pathogen and target host. The present review describes the entomopathogenic potential of Chytridiomycota and Blastocladiomycota fungi, and two groups of fungal allies: Oomycota and Microsporidia. The Oomycota (water moulds) are considered as a model biological control agent of mosquito larvae. Due to their shared ecological and morphological similarities, they had long been considered a part of the fungal kingdom; however, phylogenetic studies have since placed this group within the Straminipila. The Microsporidia are parasites of economically-important insects, including grasshoppers, lady beetles, bumblebees, colorado potato beetles and honeybees. They have been found to display some fungal characteristics, and phylogenetic studies suggest that they are related to fungi, either as a basal branch or sister group. The Blastocladiomycota and Chytridiomycota, named the lower fungi, historically were described together; however, molecular phylogenetic and ultrastructural research has classified them in their own phylum. They are considered parasites of ants, and of the larval stages of black flies, mosquitoes and scale insects.

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“…Simulation output will typically vary based on the value of the initial seed and this needs to be accounted for in the interpretation of the results. See Martinez-Moyano and Macal Results for Objective 1: Evaluating the Potential of LLA Insecticides LLA insecticides have been proposed as a potential method to delay the emergence of IR and to provide another tool for malaria control managers to reduce transmission by reducing the mosquito population [33][34][35][36][37][38][39]41]. It is argued that the delayed death of the mosquitoes after first exposure to the LLA insecticide can reduce the selective evolutionary pressures that result in IR by permitting the SS or SR genotypes time to return the susceptible allele to the population.…”

Section: Sensitivity To Random Generator Seedmentioning

confidence: 99%

“…One type of proposed LLA insecticide is based on using an entomopathogenic fungus -a biopesticide -which could provide the resistance delaying benefits of an LLA insecticide [33][34][35][36][37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

“…The application of these fungi has been evaluated in several field tests which have shown that the fungi can be applied effectively and work to kill mosquitoes in the field but have never been tried on a large enough scale to test their effect on malaria transmission [39,41]. Mosquitoes are frequently in natural contact with fungi and do have ways to adapt to them in nature.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Case Study: End User Development of an Agent-based Model of Malaria Transmission to Support the Design of Late-Life-Acting Insecticides for the Control of Malaria Transmission and Delay of the Evolution of Insecticide Resistance

2021

Preprint

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We describe an end-user developed agent-based simulation of malaria transmission. The simulation's development is a case study demonstrating an approach for non-technical investigators to easily develop useful simulations of complex public health problems. We focused on malaria transmission, a major global public health problem, and insecticide resistance (IR), a major problem affecting malaria control. Insecticides are used to reduce transmission of malaria caused by the Plasmodium parasite that is spread by the Anopheles mosquito. However, the emergence and spread of IR in a mosquito population can diminish the insecticide's effectiveness. IR results from mutations that produce behavioral changes or biochemical changes (such as detoxification enhancement, target site alterations) in the mosquito population that provide resistance to the insecticide. Evolutionary selection for the IR traits reduces the effectiveness of an insecticide favoring the resistant mosquito population. It has been suggested that biopesticides, and specifically those that are Late Life Acting (LLA), could address this problem. LLA insecticides exploit Plasmodium's approximate 10-day extrinsic incubation period in the mosquito vector, a delay that limits malaria transmission to older infected mosquitoes. Since the proposed LLA insecticide delays mosquito death until after the exposed mosquito has a chance to produce several broods of offspring, reducing the selective pressure for resistance, it delays IR and gives the insecticide longer effectivity. Such insecticides are designed to slow the evolution of IR thus maintaining their effectiveness for malaria control. For the IR problem, the simulation shows that an LLA insecticide could work as intended, but its operational characteristics are critical, primarily the mean-time-to-death after exposure and the associated standard deviation. We also demonstrate the simulation's extensibility to other malaria control measures, including larval source control and policies to mitigate the spread of IR. The simulation was developed using NetLogo as a case study of a simple but useful approach to public health research.

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New discoveries and applications of mosquito fungal pathogens

Cited by 17 publications

References 45 publications

The Axenic and Gnotobiotic Mosquito: Emerging Models for Microbiome Host Interactions

The Axenic and Gnotobiotic Mosquito: Emerging Models for Microbiome Host Interactions

Fungi of entomopathogenic potential in Chytridiomycota and Blastocladiomycota, and in fungal allies of the Oomycota and Microsporidia

Case Study: End User Development of an Agent-based Model of Malaria Transmission to Support the Design of Late-Life-Acting Insecticides for the Control of Malaria Transmission and Delay of the Evolution of Insecticide Resistance

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