CellProfiler Analyst is a data exploration package for helping users to explore and extract information from large datasets, including (but not limited to) those produced by CellProfiler pipelines ( Jones et al., 2008). Spreadsheet programs are familiar but lack features and integration with source images that biologists often need. Free software packages such as ImageJ ( Schneider et al., 2012) and CellProfiler ( McQuin et al., 2018) allow users to extract hundreds or thousands of numerical measurements from their image data, but it is ultimately on the user to determine which of these features are relevant to the biological problem being investigated. This necessitates automated computational analysis to efficiently derive biological insights from the raw data. elegans model.With the increasing adoption of high-throughput microscopy, scientists have been able to generate large datasets containing thousands of individual images. It is anticipated that these methods can drastically simplify the screening process of large bacterial, genomic, or drug libraries using the C. Though the concept of automation is not entirely unique, the need to standardize such procedures for reproducibility, elimination of bias from manual counting, and increase throughput is high. elegans-based image processing pipeline using CellProfiler, an image analysis software, this method has been optimized to separate and identify individual worms and enumerate their respective aggregates. elegans that express intestine-specific polyQ. Herein, a protocol consisting of worm culturing, image acquisition, and data processing was standardized to support high-throughput aggregate quantification using C. Furthermore, manual foci quantification can introduce bias, as aggregate identification can be highly subjective. Manual aggregate quantification is time-consuming, limiting experimental throughput. Such reporters are often employed as proxies to monitor changes in proteostasis across tissues. Nematodes that express fluorescently tagged tissue-specific polyglutamine (polyQ) tracts exhibit age- and polyQ length-dependent aggregation characterized by fluorescent foci. elegans and human genomes makes this model an invaluable discovery tool. Additionally, high conservation between the C. Use of the Caenorhabditis elegans nematode model to study PCDs has been justified by its relative ease of maintenance, low cost, and rapid generation time, which allow for high-throughput applications. Though murine models have proven invaluable, they are expensive and are associated with laborious, low-throughput methods. This increased attention has called for the diversification and improvement of animal models capable of reproducing disease phenotypes observed in humans with PCDs. e62997 ISSN: 1940-087X Subject: Caenorhabditis elegans, automation, computer software, drugs, fluorescence, genome, genomics, humans, image analysis, mice, models, protocols Abstract: A rise in the prevalence of neurodegenerative protein conformational diseases (PCDs) has fostered a great interest in this subject over the years. Source: Journal of visualized experiments 2021 no.176 pp. Automating aggregate quantification in Caenorhabditis elegans Author: Vaziriyan-Sani Alfonso S., Handy Robert D., Walker Alyssa C., Pagolu Carol Navya, Enslow Samantha M., Czyż Daniel M.
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