3 research outputs found
Massively parallel C. elegans tracking provides multi-dimensional fingerprints for phenotypic discovery.
BACKGROUND: The nematode worm C. elegans is a model organism widely used for studies of genetics and of human disease. The health and fitness of the worms can be quantified in different ways, such as by measuring their bending frequency, speed or lifespan. Manual assays, however, are time consuming and limited in their scope providing a strong motivation for automation. NEW METHOD: We describe the development and application of an advanced machine vision system for characterising the behaviour of C. elegans, the Wide Field-of-View Nematode Tracking Platform (WF-NTP), which enables massively parallel data acquisition and automated multi-parameter behavioural profiling of thousands of worms simultaneously. RESULTS: We screened more than a million worms from several established models of neurodegenerative disorders and characterised the effects of potential therapeutic molecules for Alzheimer's and Parkinson's diseases. By using very large numbers of animals we show that the sensitivity and reproducibility of behavioural assays is very greatly increased. The results reveal the ability of this platform to detect even subtle phenotypes. COMPARISON WITH EXISTING METHODS: The WF-NTP method has substantially greater capacity compared to current automated platforms that typically either focus on characterising single worms at high resolution or tracking the properties of populations of less than 50 animals. CONCLUSIONS: The WF-NTP extends significantly the power of existing automated platforms by combining enhanced optical imaging techniques with an advanced software platform. We anticipate that this approach will further extend the scope and utility of C. elegans as a model organism
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Core-Shell Spheroid-Laden Microgels Crosslinked under Biocompatible Conditions for Probing Cancer-Stromal Communication
Funder: H2020 European Research Council; Id: http://dx.doi.org/10.13039/100010663Funder: China ScholarshipFunder: College of Engineering, University of Canterbury; Id: http://dx.doi.org/10.13039/100014447Multicellular cancer spheroids (MCSs) have emerged as a promising in vitro model that recaptures many features of solid tumours in vivo. To generate cancer spheroids, cells are encapsulated in microgels with high throughput. While the biophysical properties of the cancer spheroid and biomaterial influence the function and behavior of the cells, characterization of these properties remains largely unexplored. In addition, many existing techniques lack control over cell positioning, resulting in the formation of spheroids with large variability. Herein, a versatile, microfluidic platform for generating biocompatible coreâshell microgels with uniform cancer spheroids is reported. In addition, an in situ micromechanics measuring device to determine the stiffness of individual artificial cancer niches is used. The power of the microfluidicsâbased method by making MCSâladen microgels to model the interactions of stromal cancer cells is demonstrated. Together with in vivo data, it is shown that tumor cell proliferation is promoted by cocultured fibroblasts
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Massively parallel C. elegans tracking provides multi-dimensional fingerprints for phenotypic discovery.
BACKGROUND: The nematode worm C. elegans is a model organism widely used for studies of genetics and of human disease. The health and fitness of the worms can be quantified in different ways, such as by measuring their bending frequency, speed or lifespan. Manual assays, however, are time consuming and limited in their scope providing a strong motivation for automation. NEW METHOD: We describe the development and application of an advanced machine vision system for characterising the behaviour of C. elegans, the Wide Field-of-View Nematode Tracking Platform (WF-NTP), which enables massively parallel data acquisition and automated multi-parameter behavioural profiling of thousands of worms simultaneously. RESULTS: We screened more than a million worms from several established models of neurodegenerative disorders and characterised the effects of potential therapeutic molecules for Alzheimer's and Parkinson's diseases. By using very large numbers of animals we show that the sensitivity and reproducibility of behavioural assays is very greatly increased. The results reveal the ability of this platform to detect even subtle phenotypes. COMPARISON WITH EXISTING METHODS: The WF-NTP method has substantially greater capacity compared to current automated platforms that typically either focus on characterising single worms at high resolution or tracking the properties of populations of less than 50 animals. CONCLUSIONS: The WF-NTP extends significantly the power of existing automated platforms by combining enhanced optical imaging techniques with an advanced software platform. We anticipate that this approach will further extend the scope and utility of C. elegans as a model organism