Actions of Camptothecin Derivatives on Larvae and Adults of the Arboviral Vector Aedes aegypti

Mosquito-borne viruses including dengue, Zika, and Chikungunya viruses, and parasites such as malaria and Onchocerca volvulus endanger health and economic security around the globe, and emerging mosquito-borne pathogens have pandemic potential. However, the rapid spread of insecticide resistance threatens our ability to control mosquito vectors. Larvae of Aedes aegypti were screened with the Medicines for Malaria Venture Pandemic Response Box, an open-source compound library, using INVAPP, an invertebrate automated phenotyping platform suited to high-throughput chemical screening of larval motility. We identified rubitecan (a synthetic derivative of camptothecin) as a hit compound that reduced A. aegypti larval motility. Both rubitecan and camptothecin displayed concentration dependent reduction in larval motility with estimated EC50 of 25.5 ± 5.0 µM and 22.3 ± 5.4 µM, respectively. We extended our investigation to adult mosquitoes and found that camptothecin increased lethality when delivered in a blood meal to A. aegypti adults at 100 µM and 10 µM, and completely blocked egg laying when fed at 100 µM. Camptothecin and its derivatives are inhibitors of topoisomerase I, have known activity against several agricultural pests, and are also approved for the treatment of several cancers. Crucially, they can inhibit Zika virus replication in human cells, so there is potential for dual targeting of both the vector and an important arbovirus that it carries.

Actions of camptothecin derivatives on larvae and adults of the arboviral vector Aedes aegypti

Mosquito-borne viruses including dengue, Zika and Chikungunya viruses as well as parasites such as malaria and Onchocerca volvulus endanger health and economic security around the globe and emerging mosquito-borne pathogens have pandemic potential. However, the rapid spread of insecticide resistance threatens our ability to control mosquito vectors. Larvae of Aedes aegypti (New Orleans strain) were screened with the Medicines for Malaria Venture Pandemic Response Box, an open-source compound library, using INVAPP, an invertebrate automated phenotyping platform suited to high-throughput chemical screening of larval motility. Of the 400 compounds screened, we identified rubitecan (a synthetic derivative of camptothecin) as a hit compound that significantly reduced Ae. aegypti larval motility compared to DMSO controls. Both rubitecan and camptothecin displayed concentration dependent reduction in larval motility with estimated EC50s of 25.5 ± 5.0 μM and 22.3 ± 5.4 μM respectively. We extended our investigation to adult mosquitoes and found that camptothecin increased lethality when delivered in a blood meal to Ae. aegypti adults at 100 μM and 10 μM and completely blocked egg laying when fed at 100 μM. Camptothecin and its derivatives, inhibitors of topoisomerase I, have known activity against several agricultural pests and are also approved for the treatment of several cancers. Crucially, they can inhibit Zika virus replication in human cells, so there is potential for dual targeting of both the vector and an important arbovirus that it carries. Both humans and mosquitoes express the highly conserved topoisomerase I target, however, the design of derivatives with differing pharmacokinetic properties may offer a promising route towards the development of insect-specificity of this chemistry.

Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions

Controlled plant growth facilities provide the possibility to alter climate conditions affecting plant growth, such as humidity, temperature, and light, allowing a better understanding of plant responses to abiotic and biotic stresses. A bottleneck, however, is measuring various aspects of plant growth regularly and non-destructively. Although several high-throughput phenotyping facilities have been built worldwide, further development is required for smaller custom-made affordable systems for specific needs. Hence, the main objective of this study was to develop an affordable, standalone and automated phenotyping system called “Phenocave” for controlled growth facilities. The system can be equipped with consumer-grade digital cameras and multispectral cameras for imaging from the top view. The cameras are mounted on a gantry with two linear actuators enabling XY motion, thereby enabling imaging of the entire area of Phenocave. A blueprint for constructing such a system is presented and is evaluated with two case studies using wheat and sugar beet as model plants. The wheat plants were treated with different irrigation regimes or high nitrogen application at different developmental stages affecting their biomass accumulation and growth rate. A significant correlation was observed between conventional measurements and digital biomass at different time points. Post-harvest analysis of grain protein content and composition corresponded well with those of previous studies. The results from the sugar beet study revealed that seed treatment(s) before germination influences germination rates. Phenocave enables automated phenotyping of plants under controlled conditions, and the protocols and results from this study will allow others to build similar systems with dimensions suitable for their custom needs.

Automated phenotyping of mosquito larvae enables high-throughput screening for novel larvicides and offers potential for smartphone-based detection of larval insecticide resistance

Pyrethroid-impregnated nets have contributed significantly to halving the burden of malaria but resistance threatens their future efficacy and the pipeline of new insecticides is short. Here we report that an invertebrate automated phenotyping platform (INVAPP), combined with the algorithm Paragon, provides a robust system for measuring larval motility in Anopheles gambiae (and An. coluzzi) as well as Aedes aegypti with the capacity for high-throughput screening for new larvicides. By this means, we reliably quantified both time- and concentration-dependent actions of chemical insecticides faster than using the WHO standard larval assay. We illustrate the effectiveness of the system using an established larvicide (temephos) and demonstrate its capacity for library-scale chemical screening using the Medicines for Malaria Venture (MMV) Pathogen Box library. As a proof-of-principle, this library screen identified a compound, subsequently confirmed to be tolfenpyrad, as an effective larvicide. We have also used the INVAPP / Paragon system to compare responses in larvae derived from WHO classified deltamethrin resistant and sensitive mosquitoes. We show how this approach to monitoring larval response to insecticides can be adapted for use with a smartphone camera application and therefore has potential for further development as a simple portable field-assay with associated real-time, geo-located information to identify hotspots.

"Smart Tanks": An Intelligent High-Throughput Intervention Testing Platform in Daphnia

We present a novel platform for testing the effect of interventions on life- and health-span of a short-lived semi transparent freshwater organism, sensitive to drugs with complex behavior and physiology - the planktonic crustacean Daphnia magna. Within this platform, dozens of complex behavioural features of both routine motion and response to stimuli are continuously accurately quantified for large homogeneous cohorts via an automated phenotyping pipeline. We build predictive machine learning models calibrated using chronological age and extrapolate onto phenotypic age. We further apply the model to estimate the phenotypic age under pharmacological perturbation. Our platform provides a scalable framework for drug screening and characterization in both life-long and instant assays as illustrated using long term dose response profile of metformin and short term assay of such well-studied substances as caffeine and alcohol.

SPIRO-the automated Petri plate imaging platform designed by biologists, for biologists

The imaging of plant seedlings, fungal mycelia and bacterial colonies grown on Petri plates is commonly used in phenotyping assays, and is typically done manually despite the procedures being time-consuming and laborious. The main reason for this is the still limited availability of existing automated phenotyping tools and facilities. Additionally, constructing a custom-made automated solution is a daunting task for most research groups specializing in biology. Here, we describe SPIRO, the Smart Plate Imaging Robot, an automated platform that acquires time-lapse photos of up to four vertically oriented Petri plates in a single experiment. SPIRO was designed for biologists by biologists; thus its assembly does not require experience in engineering or programming and its operation is sufficiently intuitive to be done without training. SPIRO has a small footprint optimal to fit into standard incubators for plants and microbes and is equipped with an LED light source for imaging in the dark, thus allowing acquisition of photos under optimal growth conditions. SPIRO's web-based user interface allows setting up experiments and downloading data remotely, without interfering with samples growth. The robots' 8 MP camera provides excellent image quality suitable for automated image processing, which we demonstrate on the example of two semi-automated assays for analysis of commonly used phenotypic traits: seed germination and root growth. Moreover, the robot can be easily customized for a specific use, as all information about SPIRO, including the models for 3D-printed structural components, control software, and scripts for image analysis are released under permissive open source licenses.

Application of Phenotyping Methods in Detection of Drought and Salinity Stress in Basil (Ocimum basilicum L.)

Basil is one of the most widespread aromatic and medicinal plants, which is often grown in drought- and salinity-prone regions. Often co-occurrence of drought and salinity stresses in agroecosystems and similarities of symptoms which they cause on plants complicates the differentiation among them. Development of automated phenotyping techniques with integrative and simultaneous quantification of multiple morphological and physiological traits enables early detection and quantification of different stresses on a whole plant basis. In this study, we have used different phenotyping techniques including chlorophyll fluorescence imaging, multispectral imaging, and 3D multispectral scanning, aiming to quantify changes in basil phenotypic traits under early and prolonged drought and salinity stress and to determine traits which could differentiate among drought and salinity stressed basil plants. Ocimum basilicum “Genovese” was grown in a growth chamber under well-watered control [45–50% volumetric water content (VWC)], moderate salinity stress (100 mM NaCl), severe salinity stress (200 mM NaCl), moderate drought stress (25–30% VWC), and severe drought stress (15–20% VWC). Phenotypic traits were measured for 3 weeks in 7-day intervals. Automated phenotyping techniques were able to detect basil responses to early and prolonged salinity and drought stress. In addition, several phenotypic traits were able to differentiate among salinity and drought. At early stages, low anthocyanin index (ARI), chlorophyll index (CHI), and hue (HUE2D), and higher reflectance in red (RRed), reflectance in green (RGreen), and leaf inclination (LINC) indicated drought stress. At later stress stages, maximum fluorescence (Fm), HUE2D, normalized difference vegetation index (NDVI), and LINC contribute the most to the differentiation among drought and non-stressed as well as among drought and salinity stressed plants. ARI and electron transport rate (ETR) were best for differentiation of salinity stressed plants from non-stressed plants both at early and prolonged stress.

LAMA: automated image analysis for the developmental phenotyping of mouse embryos

ABSTRACTAdvanced 3D imaging modalities, such as micro-computed tomography (micro-CT), have been incorporated into the high-throughput embryo pipeline of the International Mouse Phenotyping Consortium (IMPC). This project generates large volumes of raw data that cannot be immediately exploited without significant resources of personnel and expertise. Thus, rapid automated annotation is crucial to ensure that 3D imaging data can be integrated with other multi-dimensional phenotyping data. We present an automated computational mouse embryo phenotyping pipeline that harnesses the large amount of wild-type control data available in the IMPC embryo pipeline in order to address issues of low mutant sample number as well as incomplete penetrance and variable expressivity. We also investigate the effect of developmental substage on automated phenotyping results. Designed primarily for developmental biologists, our software performs image pre-processing, registration, statistical analysis and segmentation of embryo images. We also present a novel anatomical E14.5 embryo atlas average and, using it with LAMA, show that we can uncover known and novel dysmorphology from two IMPC knockout lines.

Behavioral fingerprints predict insecticide and anthelmintic mode of action

Novel invertebrate-killing compounds are required in agriculture and medicine to overcome resistance to existing treatments. Because insecticides and anthelmintics are discovered in phenotypic screens, a crucial step in the discovery process is determining the mode of action of hits. Visible whole-organism symptoms are combined with molecular and physiological data to determine mode of action. However, manual symptomology is laborious and requires symptoms that are strong enough to see by eye. Here we use high-throughput imaging and quantitative phenotyping to measure C. elegans behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. We also classify compounds within each mode of action to discover pharmacological relationships that are not captured in broad mode of action labels. High-throughput imaging and automated phenotyping could therefore accelerate mode of action discovery in invertebrate-targeting compound development and help to refine mode of action categories.