Key role and diversity of EcR/USP and other nuclear receptors in selected Arthropoda species

The nuclear receptors (NRs), an important protein superfamily of transcription factors found in all animals, regulate the expression of genes in a large array of biological processes. Their involvement in moulting and metamorphosis, embryonic development, cell differentiation and reproduction of arthropods is well documented. Especially the two NRs that form the functional ecdysteroid receptor and which are at the base of the ecdysteroid signalling cascade regulating moulting and metamorphosis, EcR and USP, have been researched intensively. During evolution, gene duplication and gene loss events have created a broad diversity of these NRs between different groups in the animal kingdom. However, in 2008, at the time this PhD research started, the information that was available on arthropod NRs was mainly restricted to holometabolic insects. Complete sets of NRs for other groups, including Crustacea, Chelicerata or more basal insects were unavailable. Over the last few years, the number of genome sequencing projects that are carried out for Arthropoda is rapidly increasing. This gave us the opportunity to investigate the NRs in a number of other arthropods and compare the sets of NRs between some of these groups. We chose three species, the hemimetabolic pea aphid Acyrthosiphon pisum, the holometabolic buff-tailed bumblebee Bombus terrestris and the chelicerate two-spotted spidermite Tetranychus urticae as representatives of their respective clades. The main research questions that were addressed in the PhD thesis were: (1) Do holometabolic, hemimetabolic and non-insect arthropods exhibit important differences in their sets of nuclear receptors?, (2) What are the consequences towards the ecdysteroid signalling cascade and can any differences be found there?, and (3) Can RNAi be used to add functional information to the fundamental data that these genome annotation analyses have delivered

RNAi efficiency, systemic properties, and novel delivery methods for pest insect control : what we know so far

In recent years, the research on the potential of using RNA interference (RNAi) to suppress crop pests has made an outstanding growth. However, given the variability of RNAi efficiency that is observed in many insects, the development of novel approaches toward insect pest management using RNAi requires first to unravel factors behind the efficiency of dsRNA-mediated gene silencing. In this review, we explore essential implications and possibilities to increase RNAi efficiency by delivery of dsRNA through non-transformative methods. We discuss factors influencing the RNAi mechanism in insects and systemic properties of dsRNA. Finally, novel strategies to deliver dsRNA are discussed, including delivery by symbionts, plant viruses, trunk injections, root soaking, and transplastomic plants

Vortex Image Processing (VIP) package for high-contrast direct imaging

VIP is a Python instrument-agnostic toolbox featuring a flexible framework for reproducible and robust data reduction. VIP currently supports three high-contrast imaging observational techniques: angular, reference-star and multi-spectral differential imaging. The code can be downloaded from our git repository on Github: http://github.com/vortex-exoplanet/VI

RNA interference : a promising biopesticide strategy against the African sweetpotato weevil Cylas brunneus

The African sweetpotato weevil Cylas brunneus is one of the most devastating pests affecting the production of sweetpotatoes, an important staple food in Sub-Saharan Africa. Current available control methods against this coleopteran pest are limited. In this study, we analyzed the potential of RNA interference as a novel crop protection strategy against this insect pest. First, the C. brunneus transcriptome was sequenced and RNAi functionality was confirmed by successfully silencing the laccase2 gene. Next, 24 potential target genes were chosen, based on their critical role in vital biological processes. A first screening via injection of gene-specific dsRNAs showed that the dsRNAs were highly toxic for C. brunneus. Injected doses of 200ng/mg body weight led to mortality rates of 90% or higher for 14 of the 24 tested genes after 14 days. The three best performing dsRNAs, targeting pros alpha 2, rps13 and the homolog of Diabrotica virgifera snf7, were then used in further feeding trials to investigate RNAi by oral delivery. Different concentrations of dsRNAs mixed with artificial diet were tested and concentrations as low as 1 mu g dsRNA/mL diet led to significant mortality rates higher than 50%. These results proved that dsRNAs targeting essential genes show great potential to control C. brunneus

Double-Stranded RNA Technology to Control Insect Pests: Current Status and Challenges

Exploiting the RNA interference (RNAi) gene mechanism to silence essential genes in pest insects, leading to toxic effects, has surfaced as a promising new control strategy in the past decade. While the first commercial RNAi-based products are currently coming to market, the application against a wide range of insect species is still hindered by a number of challenges. In this review, we discuss the current status of these RNAi- based products and the different delivery strategies by which insects can be targeted by the RNAi-triggering double-stranded RNA (dsRNA) molecules. Furthermore, this review also addresses a number of physiological and cellular barriers, which can lead to decreased RNAi efficacy in insects. Finally, novel non-transgenic delivery technologies, such as polymer or liposomic nanoparticles, peptide-based delivery vehicles and viral- like particles, are also discussed, as these could overcome these barriers and lead to effective RNAi-based pest control

Double-stranded RNA technology to control insect pests : current status and challenges

Exploiting the RNA interference (RNAi) gene mechanism to silence essential genes in pest insects, leading to toxic effects, has surfaced as a promising new control strategy in the past decade. While the first commercial RNAi-based products are currently coming to market, the application against a wide range of insect species is still hindered by a number of challenges. In this review, we discuss the current status of these RNAi-based products and the different delivery strategies by which insects can be targeted by the RNAi-triggering double-stranded RNA (dsRNA) molecules. Furthermore, this review also addresses a number of physiological and cellular barriers, which can lead to decreased RNAi efficacy in insects. Finally, novel non-transgenic delivery technologies, such as polymer or liposomic nanoparticles, peptide-based delivery vehicles and viral-like particles, are also discussed, as these could overcome these barriers and lead to effective RNAi-based pest control

Double-stranded RNA technology to control insect pests : current status and challenges

Exploiting the RNA interference (RNAi) gene mechanism to silence essential genes in pest insects, leading to toxic effects, has surfaced as a promising new control strategy in the past decade. While the first commercial RNAi-based products are currently coming to market, the application against a wide range of insect species is still hindered by a number of challenges. In this review, we discuss the current status of these RNAi-based products and the different delivery strategies by which insects can be targeted by the RNAi-triggering double-stranded RNA (dsRNA) molecules. Furthermore, this review also addresses a number of physiological and cellular barriers, which can lead to decreased RNAi efficacy in insects. Finally, novel non-transgenic delivery technologies, such as polymer or liposomic nanoparticles, peptide-based delivery vehicles and viral-like particles, are also discussed, as these could overcome these barriers and lead to effective RNAi-based pest control

Silencing of double-stranded ribonuclease improves oral RNAi efficacy in southern green stinkbug Nezara viridula

Simple summary: RNAi interference (RNAi) is a conserved mechanism found in all eukaryotes. This mechanism is initiated by the presence of double-stranded RNA in the cells and leads to the blockage of protein synthesis of a target gene. This technique is being explored to develop species-selective biopesticides, where insect-specific double-stranded RNA would be delivered to an insect via the oral route. However, orally delivered double-stranded RNA leads to a variable RNAi-interference efficacy in different insect orders. Previous studies have shown rapid degradation of double-stranded RNA in the saliva of the southern green stinkbug. In this study, we identified and characterized the protein associated with double-stranded RNA degradation and provided evidence of the involvement of this protein in limiting RNAi efficacy in this pest. Our results revealed that one protein, a double-stranded RNA nuclease, is associated with double-stranded RNA degradation. Further, the blockage of double-stranded RNA nuclease synthesis by RNAi-interference significantly enhances the death-rate in the southern green stinkbug. These findings will be useful in the development of RNAi-interference-based pest control strategies. Abstract : Variability in RNA-interference (RNAi) efficacy among different insect orders poses a big hurdle in the development of RNAi-based pest control strategies. The activity of double-stranded ribonucleases (dsRNases) in the digestive canal of insects can be one of the critical factors affecting oral RNAi efficacy. Here, the involvement of these dsRNases in the southern green stinkbug Nezara viridula was investigated. First, the full sequence of the only dsRNase (NvdsRNase) in the transcriptome of N. viridula was obtained, followed by an oral feeding bioassay to evaluate the effect of NvdsRNase-silencing on oral RNAi efficacy. The NvdsRNase was first silenced in nymphs by NvdsRNase-dsRNA injections, followed by exposure to an artificial diet containing a lethal alpha Cop-specific dsRNA. A significantly higher mortality was observed in the NvdsRNase-silenced nymphs when placed on the ds alpha Cop-containing diet (65%) than in the dsGFP injected and ds alpha Cop fed control (46.67%). Additionally, an ex vivo dsRNA degradation assay showed a higher stability of dsRNA in the saliva and midgut juice of NvdsRNase-silenced adults. These results provide evidence for the involvement of NvdsRNase in the reduction of oral RNAi efficacy in N. viridula. This information will be useful in further improving potential RNAi-based strategies to control this pest

Improving direct exoplanet detections using both spatial and spectral data through ML

Advances in observing methods and the advent of instruments such as SINFONI, GPI etc allow to simultaneously produce high contrast images (HCI) and extract high resolution spectra (HRS) of exoplanet targets. This has produced multispectral images of the targets making it possible to simultaneously use the image and spectral dimensions of such data. Such data has been used in detection and characterization of multiple systems such as PDS70 (Haffert et al 2020., Christiaens 2020 etc.), HD142527 (Christiaens 2019) etc. Advanced data science techniques have been proposed to improve the current detection limit taking advantage of the large feature set provided by multispectral imaging. Machine learning (ML) has had a particularly high success rate in the imaging domain (e.g Dahlquist et al 2021, Gomez Gonzales et al 2018). However ML has proven ineffective when using spectra alone (e.g Fisher et al 2020) owing to the a large number of spectral channels that do not contribute discriminatory features from the star. Therefore, dimensionality reduction have been suggested in order to effectively harness HRS data. Consequently, this project investigates if after reducing the dimensionality of HRS, will the spatial diversity provided by the HCI improve the detection limit. We use SDI cubes from SINFONI. This consist of the HD142527 data cube and an empty data cube with injected companions. We implement dimensionality reduction by replacing the spectral dimension with a relative velocity dimension and the pixel values with cross correlation (CCF) values This produces a spatial CCF map consisting of correlated and uncorrelated pixels. Naturally, pixels which contain spectra closer to the template that it is correlated with have a higher value. However, this map is still contaminated by noise correlations and field rotation. It has been proven that the application of derotation and STIM algorithms with appropriate thresholding (Pairet et al 2019) to a standard ADI cube produces a reliable detection map. In our case we replace the ADI cube with a CCF cube and apply derotation+STIM. Choice of an appropriate threshold converts this STIM map into a detection map The thresholding in the STIM map has been shown to be somewhat noise dependent. In order to now harness the power of ML to our project we will replace the STIM+thresholding with an appropriate noise independent ML algorithm and summarize the improvement in detectability

Increased RNAi efficacy in Spodoptera exigua via the formulation of dsRNA with guanylated polymers

Lepidoptera comprise some of the most devastating herbivorous pest insects worldwide. One of the most promising novel pest control strategies is exploiting the RNA interference (RNAi) mechanism to target essential genes for knockdown and incite toxic effects in the target species without harming other organisms in the ecosystem. However, many insects are refractory to oral RNAi, often due to rapid degradation of ingested dsRNA in their digestive system. This is the case for many lepidopteran insects, including the beet armyworm Spodoptera exigua, which is characterized by a very alkaline gut environment (pH > 9.0) and a strong intestinal nucleolytic activity. In this research, guanidine-containing polymers were developed to protect dsRNA against nucleolytic degradation, specifically in high pH environments. First, their ability to protect dsRNA against nucleolytic degradation in gut juice of the beet armyworm S. exigua was investigated ex vivo. Polymers with high guanidine content provided a strong protection against nucleolytic degradation at pH 11, protecting the dsRNA for up to 30 h. Next, cellular uptake of the dsRNA and the polyplexes in lepidopteran CF203 midgut cells was investigated by confocal microscopy, showing that the polymer also enhanced cellular uptake of the dsRNA. Finally, in vivo feeding RNAi bioassays demonstrated that using these guanidine-containing polymer nanoparticles led to an increased RNAi efficiency in S. exigua. Targeting the essential gene chitin synthase B, we observed that the mortality increased to 53% in the polymer-protected dsRNA treatment compared to only 16% with the naked dsRNA and found that polymer-protected dsRNA completely halted the development of the caterpillars. These results show that using guanylated polymers as a formulation strategy can prevent degradation of dsRNA in the alkaline and strongly nucleolytic gut of lepidopteran insects. Furthermore, the polymer also enhances cellular uptake in lepidopteran midgut cells. This new delivery strategy could be of great use in further fundamental research in lepidopterans, using RNAi as a research tool, and could lead to future applications for RNAi-based pest control of lepidopteran insects