Historically, monitoring nematode movement and mortality in response to various potential nematicide treatments usually involved tedious manual microscopic analysis. High-content analysis instrumentation enables rapid and high-throughput collection of experimental data points on large numbers of individual worms simultaneously. The high-throughput platform outlined here should accelerate discovery of unique classes and types of promising lead molecules and sample types to control these plant pests. Also, the ability to automate the data analysis pipeline rather than relying on manual scoring reduces a potential source of data variance. Here we describe a high-throughput process based on high-content imaging. We demonstrate the use of time-lapse image acquisition to measure movement, and viability staining to confirm nematode mortality (versus paralysis) in targeted plant-pathogenic nematodes. We present screening results from a microbial-exudate library generated from approximately 2,300 microbial fermentations that demonstrate the robustness of this high-throughput process. The described methods should be applicable to other relevant nematode parasites with human, crop, or animal hosts.
High Content Analysis (HCA) has become a cornerstone of cellular analysis within the drug discovery industry. To expand the capabilities of HCA, we have applied the same analysis methods, validated in numerous mammalian cell models, to microbiology methodology. Image acquisition and analysis of various microbial samples, ranging from pure cultures to culture mixtures containing up to three different bacterial species, were quantified and identified using various machine learning processes. These HCA techniques allow for faster cell enumeration than standard agar-plating methods, identification of “viable but not plate culturable” microbe phenotype, classification of antibiotic treatment effects, and identification of individual microbial strains in mixed cultures. These methods greatly expand the utility of HCA methods and automate tedious and low-throughput standard microbiological methods.
Monitoring nematode parasite movement and mortality in response to various treatment samples usually involves tedious manual microscopic analysis. High Content Analysis instrumentation enables rapid and high throughput collecting of large numbers of treatment data on huge numbers of individual worms. These large sample sizes and increased sample diversity result in robust, reliable results with increased statistical significance. These methods would be applicable to relevant human, crop, or animal worm parasites.
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