Flow-through imaging and automated analysis of oil-exposed early stage Atlantic cod (Gadus morhua)

Toxicology studies in early fish life stages serve an important function in measuring the impact of potentially harmful substances, such as crude oil, on marine life. Morphometric analysis of larvae can reveal the effects of such substances in retarding growth and development. These studies are labor intensive and time consuming, typically resulting in only a small number of samples being considered. An automated system for imaging and measurement of experimental animals, using flow-through imaging and an artificial neural network to allow faster sampling of more individuals, has been described previously and used in toxicity experiments. This study compares the performance of the automated imaging and analysis system with traditional microscopy techniques in measuring biologically relevant endpoints using two oil treatments as positive controls. We demonstrate that while the automated system typically underestimates morphometric measurements relative to analysis of manual microscopy images, it shows similar statistical results to the manual method when comparing treatments across most endpoints. It allows for many more individual specimens to be sampled in a shorter time period, reducing labor requirements and improving statistical power in such studies, and is noninvasive allowing for repeated sampling of the same population.

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

Phenotyping of model organisms grown on Petri plates is often carried out manually, despite the procedures being time-consuming and laborious. The main reason for this is the limited availability of automated phenotyping facilities, whereas constructing a custom automated solution can be a daunting task for biologists. Here, we describe SPIRO, the Smart Plate Imaging Robot, an automated platform that acquires time-lapse photographs of up to four vertically oriented Petri plates in a single experiment, corresponding to 192 seedlings for a typical root growth assay and up to 2500 seeds for a germination assay. SPIRO is catered specifically to biologists' needs, requiring no engineering or programming expertise for assembly and operation. Its small footprint is optimized for standard incubators, the inbuilt green LED enables imaging under dark conditions, and remote control provides access to the data without interfering with sample growth. SPIRO's excellent image quality is suitable for automated image processing, which we demonstrate on the example of seed germination and root growth assays. Furthermore, the robot can be easily customized for specific uses, as all information about SPIRO is released under open-source licenses. Importantly, uninterrupted imaging allows considerably more precise assessment of seed germination parameters and root growth rates compared with manual assays. Moreover, SPIRO enables previously technically challenging assays such as phenotyping in the dark. We illustrate the benefits of SPIRO in proof-of-concept experiments which yielded a novel insight on the interplay between autophagy, nitrogen sensing, and photoblastic response.

A Low-Cost Method for Phenotyping Wilting and Recovery of Wheat Leaves under Heat Stress Using Semi-Automated Image Analysis

Leaf wilting is the most common symptom of dehydration stress. Methods to analyze this phenomenon are particularly relevant to evaluate crop agronomic performance, to genetically dissect out the wilting process, and for functional analysis of genetically modified plants. In this study, a low-cost, semi-automated method to quantify leaf folding of wilting plants is described that can replace visual analysis. Standardized heat-stress conditions were applied with a thermostatic drier, on plantlets or excised leaves from three wheat genotypes (Trinakria, Cappelli, and a Water-mutant of Trinakria). The best time–temperature binomial to record both the leaf wilting and recovery phases was identified using a free time-lapse application, by a smartphone camera. The quantitative description of the wilting phenomenon was obtained through the Kinovea software, which automatically tracked the leaf angle changes over time, computed various kinematic data (angular velocity, centripetal acceleration, total degrees of displacement) and constructed the graphs. The possibility of applying standardized heat-stress conditions and quantitatively describe the leaf folding kinematics means that this instrumentation and its use represents a very low cost tool for objective phenotyping of the degree of the heat-stress tolerance of wheat and of morphologically similar species.

A Multiparametric Assay Platform for Simultaneous In Vivo Assessment of Pronephric Morphology, Renal Function and Heart Rate in Larval Zebrafish

Automated high-throughput workflows allow for chemical toxicity testing and drug discovery in zebrafish disease models. Due to its conserved structural and functional properties, the zebrafish pronephros offers a unique model to study renal development and disease at larger scale. Ideally, scoring of pronephric phenotypes includes morphological and functional assessments within the same larva. However, to efficiently upscale such assays, refinement of existing methods is required. Here, we describe the development of a multiparametric in vivo screening pipeline for parallel assessment of pronephric morphology, kidney function and heart rate within the same larva on a single imaging platform. To this end, we developed a novel 3D-printed orientation tool enabling multiple consistent orientations of larvae in agarose-filled microplates. Dorsal pronephros imaging was followed by assessing renal clearance and heart rates upon fluorescein isothiocyanate (FITC)-inulin microinjection using automated time-lapse imaging of laterally positioned larvae. The pipeline was benchmarked using a set of drugs known to induce developmental nephrotoxicity in humans and zebrafish. Drug-induced reductions in renal clearance and heart rate alterations were detected even in larvae exhibiting minor pronephric phenotypes. In conclusion, the developed workflow enables rapid and semi-automated in vivo assessment of multiple morphological and functional parameters.

Application of automated electron microscopy imaging and machine learning to characterise and quantify nanoparticle dispersion in aqueous media

For many nanoparticle applications it is important to understand dispersion in liquids. For nanomedicinal and nanotoxicological research this is complicated by the often complex nature of the biological dispersant and ultimately this leads to severe limitations in the analysis of the nanoparticle dispersion by light scattering techniques. Here we present an alternative analysis and associated workflow which utilises electron microscopy. The need to collect large, statistically relevant datasets by imaging vacuum dried, plunge frozen aliquots of suspension was accomplished by developing an automated STEM imaging protocol implemented in an SEM fitted with a transmission detector. Automated analysis of images of agglomerates was achieved by machine learning using two free open‐source software tools: CellProfiler and ilastik. The specific results and overall workflow described enable accurate nanoparticle agglomerate analysis of particles suspended in aqueous media containing other potential confounding components such as salts, vitamins and proteins.

Lay Description

In order to further advance studies in both nanomedicine and nanotoxicology, we need to continue to understand the dispersion of nanoparticles in biological fluids. These biological environments often contain a number of components such as salts, vitamins and proteins which can lead to difficulties when using traditional techniques to monitor dispersion. Here we present an alternative analysis which utilises electron microscopy. In order to use this approach statistically relevant large image datasets were collected from appropriately prepared samples of nanoparticle suspensions by implementing an automated imaging protocol. Automated analysis of these images was achieved through machine learning using two readily accessible freeware; CellProfiler and ilastik. The workflow presented enables accurate nanoparticle dispersion analysis of particles suspended in more complex biological media.

On hormonal regulation of the dynamic apical hook development

Contents Summary 1230 I. Introduction 1230 II. Apical hook development is a spatio-temporally dynamic process orchestrated by a complex signaling network 1231 III. Central players of apical hook development: auxin and HOOKLESS1 1232 IV. Towards a cellular-based understanding of hormonal regulation of apical hook development with cutting-edge toolboxes 1232 V. Conclusions 1233 Acknowledgements 1233 References 1233 SUMMARY: To deal with the ever-changing environment, sessile plants adapt diverse and plastic organ structures during postembryonic development. Among these, the apical hook forms shortly after seed germination of most dicots, and protects the delicate shoot meristem from mechanical damage during soil emergence. For decades, this structure has been taken as an excellent model for the investigation of the mechanisms underlying the differential growth of plant tissues. Here, we summarize recent advances in the investigation of the hormonal regulation of apical hook development, focusing on the convergence to auxin and a central regulator HOOKLESS1 (HLS1). We propose the revisitation of hook curvature kinematics at suborgan and single-cell resolution, and further pursuance of the mechanistics of apical hook development through combinatorial approaches of automated imaging and multidimensional modeling.

A Smart Imaging Workflow for Organ-Specific Screening in a Cystic Kidney Zebrafish Disease Model

The zebrafish is being increasingly used in biomedical research and drug discovery to conduct large-scale compound screening. However, there is a lack of accessible methodologies to enable automated imaging and scoring of tissue-specific phenotypes at enhanced resolution. Here, we present the development of an automated imaging pipeline to identify chemical modifiers of glomerular cyst formation in a zebrafish model for human cystic kidney disease. Morpholino-mediated knockdown of intraflagellar transport protein Ift172 in Tg(wt1b:EGFP) embryos was used to induce large glomerular cysts representing a robustly scorable phenotypic readout. Compound-treated embryos were consistently aligned within the cavities of agarose-filled microplates. By interfacing feature detection algorithms with automated microscopy, a smart imaging workflow for detection, centring and zooming in on regions of interests was established, which enabled the automated capturing of standardised higher resolution datasets of pronephric areas. High-content screening datasets were processed and analysed using custom-developed heuristic algorithms implemented in common open-source image analysis software. The workflow enables highly efficient profiling of entire compound libraries and scoring of kidney-specific morphological phenotypes in thousands of zebrafish embryos. The demonstrated toolset covers all the aspects of a complex whole organism screening assay and can be adapted to other organs, specimens or applications.

Multimodal Hierarchical Imaging of Serial Sections for Finding Specific Cellular Targets within Large Volumes

Targeting specific cells at ultrastructural resolution within a mixed cell population or a tissue can be achieved by hierarchical imaging using a combination of light and electron microscopy. Samples embedded in resin are sectioned into arrays consisting of ribbons of hundreds of ultrathin sections and deposited on pieces of silicon wafer or conductively coated coverslips. Arrays are imaged at low resolution using a digital consumer like smartphone camera or light microscope (LM) for a rapid large area overview, or a wide field fluorescence microscope (fluorescence light microscopy (FLM)) after labeling with fluorophores. After post-staining with heavy metals, arrays are imaged in a scanning electron microscope (SEM). Selection of targets is possible from 3D reconstructions generated by FLM or from 3D reconstructions made from the SEM image stacks at intermediate resolution if no fluorescent markers are available. For ultrastructural analysis, selected targets are finally recorded in the SEM at high-resolution (a few nanometer image pixels). A ribbon-handling tool that can be retrofitted to any ultramicrotome is demonstrated. It helps with array production and substrate removal from the sectioning knife boat. A software platform that allows automated imaging of arrays in the SEM is discussed. Compared to other methods generating large volume EM data, such as serial block-face SEM (SBF-SEM) or focused ion beam SEM (FIB-SEM), this approach has two major advantages: (1) The resin-embedded sample is conserved, albeit in a sliced-up version. It can be stained in different ways and imaged with different resolutions. (2) As the sections can be post-stained, it is not necessary to use samples strongly block-stained with heavy metals to introduce contrast for SEM imaging or render the tissue blocks conductive. This makes the method applicable to a wide variety of materials and biological questions. Particularly prefixed materials e.g., from biopsy banks and pathology labs, can directly be embedded and reconstructed in 3D.

Developmental toxicity assay using high content screening of zebrafish embryos

Typically, time-consuming standard toxicological assays using the zebrafish (Danio rerio) embryo model evaluate mortality and teratogenicity after exposure during the first 2 days post-fertilization. Here we describe an automated image-based high content screening (HCS) assay to identify the teratogenic/embryotoxic potential of compounds in zebrafish embryos in vivo. Automated image acquisition was performed using a high content microscope system. Further automated analysis of embryo length, as a statistically quantifiable endpoint of toxicity, was performed on images post-acquisition. The biological effects of ethanol, nicotine, ketamine, caffeine, dimethyl sulfoxide and temperature on zebrafish embryos were assessed. This automated developmental toxicity assay, based on a growth-retardation endpoint should be suitable for evaluating the effects of potential teratogens and developmental toxicants in a high throughput manner. This approach can significantly expedite the screening of potential teratogens and developmental toxicants, thereby improving the current risk assessment process by decreasing analysis time and required resources.

The RootScope: a simple high-throughput screening system for quantitating gene expression dynamics in plant roots

BACKGROUND

High temperature stress responses are vital for plant survival. The mechanisms that plants use to sense high temperatures are only partially understood and involve multiple sensing and signaling pathways. Here we describe the development of the RootScope, an automated microscopy system for quantitating heat shock responses in plant roots.

RESULTS

The promoter of Hsp17.6 was used to build a Hsp17.6p:GFP transcriptional reporter that is induced by heat shock in Arabidopsis. An automated fluorescence microscopy system which enables multiple roots to be imaged in rapid succession was used to quantitate Hsp17.6p:GFP response dynamics. Hsp17.6p:GFP signal increased with temperature increases from 28°C to 37°C. At 40°C the kinetics and localization of the response are markedly different from those at 37°C. This suggests that different mechanisms mediate heat shock responses above and below 37°C. Finally, we demonstrate that Hsp17.6p:GFP expression exhibits wave like dynamics in growing roots.

CONCLUSIONS

The RootScope system is a simple and powerful platform for investigating the heat shock response in plants.