This work was supported by the National Institutes of Health (1RO3AG069056-01) and the Infectious Diseases Society of America funding to DMC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank the members of the Czyz Lab for proofreading the manuscript. Cartoon figures were generated using BioRender paid license.

<ol>
	<li>Soto, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unfolding+the+role+of+protein+misfolding+in+neurodegenerative+diseases.">Unfolding the role of protein misfolding in neurodegenerative diseases.</a> Nature Reviews Neuroscience. 4 (1), 49-60 (2003).</li><li>Fang, P., Kazmi, S. A., Jameson, K. G., Hsiao, E. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+microbiome+as+a+modifier+of+neurodegenerative+disease+risk.">The microbiome as a modifier of neurodegenerative disease risk.</a> Cell Host &amp; Microbe. 28 (2), 201-222 (2020).</li><li>Kundu, P., Blacher, E., Elinav, E., Pettersson, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Our+gut+microbiome:+The+evolving+inner+self.">Our gut microbiome: The evolving inner self.</a> Cell. 171 (7), 1481-1493 (2017).</li><li>Sherwin, E., Dinan, T. G., Cryan, J. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recent+developments+in+understanding+the+role+of+the+gut+microbiota+in+brain+health+and+disease.">Recent developments in understanding the role of the gut microbiota in brain health and disease.</a> Annals of the New York Academy of Sciences. 1420 (1), 5-25 (2018).</li><li>Mondal, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Large-scale+microfluidics+providing+high-resolution+and+high-throughput+screening+of+Caenorhabditis+elegans+poly-glutamine+aggregation+model.">Large-scale microfluidics providing high-resolution and high-throughput screening of Caenorhabditis elegans poly-glutamine aggregation model.</a> Nature Communications. 7 (1), 13023 (2016).</li><li>Guisbert, E., Czyz, D. M., Richter, K., McMullen, P. D., Morimoto, R. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+a+tissue-selective+heat+shock+response+regulatory+network.">Identification of a tissue-selective heat shock response regulatory network.</a> PLoS Genetics. 9 (4), 1003466 (2013).</li><li>Silva, M. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+genetic+screening+strategy+identifies+novel+regulators+of+the+proteostasis+network.">A genetic screening strategy identifies novel regulators of the proteostasis network.</a> PLoS Genetics. 7 (12), 1002438 (2011).</li><li>Nollen, E. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+RNA+interference+screen+identifies+previously+undescribed+regulators+of+polyglutamine+aggregation.">Genome-wide RNA interference screen identifies previously undescribed regulators of polyglutamine aggregation.</a> Proceedings of the National Academy of Sciences of the United States of America. 101 (17), 6403-6408 (2004).</li><li>Walker, A. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Colonization+of+the+Caenorhabditis+elegans+gut+with+human+enteric+bacterial+pathogens+leads+to+proteostasis+disruption+that+is+rescued+by+butyrate.">Colonization of the Caenorhabditis elegans gut with human enteric bacterial pathogens leads to proteostasis disruption that is rescued by butyrate.</a> PLOS Pathogens. 17 (5), 1009510 (2021).</li><li>Goya, M. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Probiotic+Bacillus+subtilis+protects+against+&#945;-Synuclein+aggregation+in+C.+elegans.">Probiotic Bacillus subtilis protects against &#945;-Synuclein aggregation in C. elegans.</a> Cell Reports. 30 (2), 367-380 (2020).</li><li>Kumsta, C., Chang, J. T., Schmalz, J., Hansen, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hormetic+heat+stress+and+HSF-1+induce+autophagy+to+improve+survival+and+proteostasis+in+C.+elegans.">Hormetic heat stress and HSF-1 induce autophagy to improve survival and proteostasis in C. elegans.</a> Nature Communications. 8, 14337 (2017).</li><li>Prahlad, V., Morimoto, R. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neuronal+circuitry+regulates+the+response+of+Caenorhabditis+elegans+to+misfolded+proteins.">Neuronal circuitry regulates the response of Caenorhabditis elegans to misfolded proteins.</a> Proceedings of the National Academy of Sciences of the United States of America. 108, 14204-14209 (2011).</li><li>Mohri-Shiomi, A., Garsin, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Insulin+signaling+and+the+heat+shock+response+modulate+protein+homeostasis+in+the+Caenorhabditis+elegans+intestine+during+infection.">Insulin signaling and the heat shock response modulate protein homeostasis in the Caenorhabditis elegans intestine during infection.</a> Journal of Biological Chemistry. 283 (1), 194-201 (2008).</li><li>Hakim, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=WorMachine:+machine+learning-based+phenotypic+analysis+tool+for+worms.">WorMachine: machine learning-based phenotypic analysis tool for worms.</a> BMC Biology. 16 (1), 8 (2018).</li><li>W&#228;hlby, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+image+analysis+toolbox+for+high-throughput+C.+elegans+assays.">An image analysis toolbox for high-throughput C. elegans assays.</a> Nature Methods. 9 (7), 714-716 (2012).</li><li>Jones, T. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CellProfiler+Analyst:+data+exploration+and+analysis+software+for+complex+image-based+screens.">CellProfiler Analyst: data exploration and analysis software for complex image-based screens.</a> BMC Bioinformatics. 9 (1), 482 (2008).</li><li>Held, K., Ramage, E., Jacobs, M., Gallagher, L., Manoil, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sequence-verified+two-allele+transposon+mutant+library+for+Pseudomona+aeruginosa+PA01.">Sequence-verified two-allele transposon mutant library for Pseudomona aeruginosa PA01.</a> Journal of Bacteriology. 194 (23), 6387-6389 (2012).</li><li>Schulenburg, H., Ewbank, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+genetics+of+pathogen+avoidance+in+Caenorhabditis+elegans.">The genetics of pathogen avoidance in Caenorhabditis elegans.</a> Molecular Microbiology. 66 (3), 563-570 (2007).</li><li>Feldman, N., Kosolapov, L., Ben-Zvi, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorodeoxyuridine+improves+Caenorhabditis+elegans+proteostasis+independent+of+reproduction+onset.">Fluorodeoxyuridine improves Caenorhabditis elegans proteostasis independent of reproduction onset.</a> PLoS One. 9 (1), 85964 (2014).</li><li>Van Raamsdonk, J. M., Hekimi, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FUdR+causes+a+twofold+increase+in+the+lifespan+of+the+mitochondrial+mutant+gas-1.">FUdR causes a twofold increase in the lifespan of the mitochondrial mutant gas-1.</a> Mechanisms of Ageing and Development. 132 (10), 519-521 (2011).</li><li>Haldimann, P., Muriset, M., V&#237;gh, L., Goloubinoff, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+novel+hydroxylamine+derivative+ng-094+suppresses+polyglutamine+protein+toxicity+in+Caenorhabditis+elegans.">The novel hydroxylamine derivative ng-094 suppresses polyglutamine protein toxicity in Caenorhabditis elegans.</a> Journal of Biological Chemistry. 286 (21), 18784-18794 (2011).</li><li>Shinn-Thomas, J. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wrapping+culture+plates+with+Parafilm+M&#174;+increases+Caenorhabditis+elegans+growth.">Wrapping culture plates with Parafilm M&#174; increases Caenorhabditis elegans growth.</a> BMC Research Notes. 12 (1), (2019).</li><li>Alexander-Floyd, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unexpected+cell+type-dependent+effects+of+autophagy+on+polyglutamine+aggregation+revealed+by+natural+genetic+variation+in+C.+elegans.">Unexpected cell type-dependent effects of autophagy on polyglutamine aggregation revealed by natural genetic variation in C. elegans.</a> BMC Biology. 18 (1), 18 (2020).</li><li>Moronetti Mazzeo, L. E., Dersh, D., Boccitto, M., Kalb, R. G., Lamitina, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stress+and+aging+induce+distinct+polyQ+protein+aggregation+states.">Stress and aging induce distinct polyQ protein aggregation states.</a> Proceedings of the National Academy of Sciences of the United States of America. 109 (26), 10587-10592 (2012).</li><li>Sink, R., Gobec, S., Pecar, S., Zega, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=False+positives+in+the+early+stages+of+drug+discovery.">False positives in the early stages of drug discovery.</a> Current Medicinal Chemistry. 17 (34), 4231-4255 (2010).</li></ol>

The authors have declared that no conflicts of interest exist.

The described protocol outlines procedures for C. elegans culturing, imaging, and image processing that incorporates CellProfiler, an open-source image analysis software. The representative results demonstrate reproducibility, reduction of bias, and scalability. This standardized procedure will improve screening strategies employed with large bacterial, genomic, or drug libraries. While other automated C. elegans methods of object detection exists, the described technique offers a standardized, higher-throughput pipeline that integrates culturing, image acquisition, and analysis.
Several variations of worm cultivation had to be tested to optimize the protocol described herein. Initially, worms were transferred to sample bacteria immediately post age-synchronization (L1 stage). However, such an approach resulted in a population of worms with variable sizes, even among worms within the same well. C. elegans are known for pathogen avoidance19, which could have contributed to the observed variability in size and ultimately affect downstream imaging-worm detection, in particular. To eliminate such variability, the entire NGM area in each well was covered with test bacteria. Furthermore, worms were fed E. coli OP50 and allowed to fully develop into young adults for 48 h at 25 &#176;C. Allowing worms to reach adulthood on E. coli OP50 prior to transferring them onto test bacteria resulted in more consistent body size. Additionally, overcrowding and rapid food depletion by progeny were eliminated by supplementing NGM agar with FUDR. The implementation of FUDR removed progeny and enhanced automated worm identification, which was obscured by progeny mixing in with the parental population. However, it is important to be cautious and use appropriate controls when utilizing FUDR, as the compound is known to affect C. elegans proteostasis and lifespan20,21. Under the conditions described in this protocol, FUDR did not affect intestinal polyQ aggregation (Supplemental Figure 5); therefore, its utilization was suitable and beneficial to the described method.
Freezing samples prior to imaging turned out to be a critical step in the successful employment of the pipeline. The aggregate counts prior to freezing were significantly higher than manual counts (Figure 3B). Keeping worms at -20 &#176;C for 18-48 h prior to imaging reduced background fluorescence and ultimately improved aggregate detection (Figure 3A). The effects of freezing on aggregate detection have only been investigated for polyQ and should not be generalized to other models without further investigation of such effects.
Despite all the conditions being kept the same, it was observed that the average number of aggregates per worm could vary between different runs, while the ratio between the number of aggregates in animals colonized with OP50 versus MPAO1 remained consistent (Figure 6, Supplemental Figure 2, Supplemental Figure 5). Therefore, it is essential to always include E. coli OP50 control, or any additional suitable reference controls, in every run. Such variability in aggregate counts between experiments could be influenced by environmental conditions (temperature, humidity)22,23 or genetic background8. In fact, it was observed that after prolonged culture, intestinal fluorescence drastically decreased or was completely lost, which required thawing a new strain from frozen stock. The observed decrease in fluorescence could be a result of genetic changes that suppress toxic transgenes, such as those expressing polyQ. Nonetheless, the exceptional reproducibility of the results observed between different experimenters (Supplemental Figure 2), between biological replicates (Figure 5), and within the same sample (Supplemental Figure 3) emphasize on the strength of this approach.
Numerous reports have employed intestinal polyQ to study proteostasis9,11,12,13,24,25. However, a direct comparison between results cannot be made due to variability between experimental approaches and readout methods. Nonetheless, a few results from previously published data are recapitulated by the automated quantification described herein, including bacterial induction of aggregation9,13 and a comparable number of aggregates11. Collectively, the described pipeline offers a valuable tool to study proteostasis.
The method described herein has some inherent challenges. For example, it requires sufficient time to master all components of this protocol, which is especially true for section 8 of the protocol, which requires familiarity with the assay to determine if the images acquired are appropriate for pipeline analysis. Deviations from the image acquisition settings used in this protocol are possible; however, modification of the settings and worm training set will likely be required. This pipeline can distinguish aggregates of various sizes and those that are touching, which limits the &#34;blending&#34; of aggregates and ultimately increases the detection sensitivity. However, issues may arise when attempting to identify large aggregates that exceed the accepted size range, as expanding the upper size threshold may lead to errors caused by poor identification, such as the inability to differentiate aggregates that are touching. A balance between accuracy, size, and intensity must be found prior to image analysis. The efficiency of aggregate identification could be further improved by incorporating machine learning to create a neural network capable of enhancing aggregate detection. Such improvements are currently being explored and will greatly assist in addressing current issues such as the detection of aggregates that lie on different focal planes or that have abnormal shapes.
One notable weakness of the described method is the variability in automated aggregate counts, as they are not always recapitulated by manual counts in worms fed different bacterial strains. For example, based on automated counts, worms fed P. aeruginosa mutant 53 (M53) had significantly fewer aggregates compared to the wild-type strain (MPAO1) (Figure 7); however, confirmation of the hit showed no significant difference (Supplemental Figure 4). In general, high-throughput drug screens have a high rate of false-positive hit detection, and the described method is no exception26. Thus, it is a critical part of the protocol to confirm all potential hits.
While this protocol was optimized to fit a screening strategy to identify bacteria that affect host proteostasis, each step can be further modified to test the effect of genomic RNAi libraries, small molecules, or other conditions. Additional modifications can be made at each step to suit the requirements of a specific screening strategy. Furthermore, this technique provides a level of flexibility that allows for the optimization of each step to suit a specific model. For example, this approach can be extended to polyQ aggregation in other tissues or extracting other features detected in images such as monitoring gene expression using inducible fluorescent reporters (e.g., heat shock genes), assessing subcellular localization of proteins (e.g., nuclear localization of DAF-16), studying aggregation in other disease models (A&#946;1-42, &#945;-synuclein, TDP-43, etc.) or assessing physiological phenotypes, such as worm size.

Age-dependent neurodegenerative protein conformational diseases (PCDs) such as Alzheimer&#39;s, Parkinson&#39;s, and Huntington&#39;s diseases, or amyotrophic lateral sclerosis, are characterized by protein misfolding that leads to aggregation, cell death, and tissue degeneration1. While protein misfolding is recognized as the culprit, the etiology of these diseases is not clear. As such, the development of effective therapies has been hindered by the lack of knowledge regarding the factors and conditions that contribute to disease onset and progression. Recent studies suggest that changes in the microbiome influence the onset, progression, and severity of PCDs2,3,4. However, the complexity of the human, or even murine, microbiome makes it difficult to conduct studies that would reveal the exact influence of microbes on their host. Therefore, simpler organisms, such as Caenorhabditis elegans, are often used as a discovery tool5,6,7,8. Recent studies have employed C. elegans to investigate the effect of bacteria on host proteostasis and disease pathogenesis9,10. Bacterial colonization, hormesis, and genomic changes are among exemplar conditions that affect the aggregation of polyglutamine (polyQ) tracts9,11,12. Additionally, these misfolded protein clusters exhibit polyQ length- and age-dependent accumulation within the host and are associated with impaired motility9,13. The relatively simple approach of quantifying fluorescently labeled puncta can generate important data on conditions, factors, or drugs that affect protein folding and aggregation.
Though quantification of fluorescent puncta has proven to be a reliable and relatively simple procedure, the challenge remains to develop a protocol that would facilitate large-scale screening of compounds, bacteria, or conditions that affect protein aggregation. The concept of automated C. elegans image processing and puncta quantification is not entirely novel, as a number of practical support tools have been developed14,15. However, the integration of culturing, image acquisition, and a processing pipeline are essential in eliminating variability in results and allowing for higher-throughput screens.
As such, the intent of this manuscript is to standardize the procedure used to quantify polyQ aggregation in C. elegans as a proxy to detect changes in proteostasis. This task was accomplished by employing CellProfiler, an open-source image analysis software16 capable of automated worm and aggregate identification, and is integrated into a larger protocol for culturing worms, acquiring images, and processing data.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1.7 mL Microtubes</td>
			<td>Olympus Plastics</td>
			<td>Cat#24-282</td>
			<td>Microcentrifuge tubes</td>
		</tr>
		<tr>
			<td>10 mL Serological Pipettes</td>
			<td>GenClone</td>
			<td>Cat#12-104</td>
			<td>Plastic pipettes</td>
		</tr>
		<tr>
			<td>15 mL Centrifuge Tubes, Racked</td>
			<td>Olympus Plastics</td>
			<td>Cat#28-101</td>
			<td>Conical tubes</td>
		</tr>
		<tr>
			<td>5-Fluoro-2&#8242;-deoxyuridine</td>
			<td>Fisher Scientific</td>
			<td>D2235100MG</td>
			<td>FUDR</td>
		</tr>
		<tr>
			<td>Accu-jet Pro Pipette Controller</td>
			<td>Genesee Scientific</td>
			<td>91-600RB</td>
			<td>Pipette gun</td>
		</tr>
		<tr>
			<td>Agar</td>
			<td>Fisher Scientific</td>
			<td>Cat#BP1423-2</td>
			<td>Granulated agar</td>
		</tr>
		<tr>
			<td>BioRender</td>
			<td>BioRender</td>
			<td></td>
			<td>Graphical figure generator</td>
		</tr>
		<tr>
			<td>Bleach (Regular)</td>
			<td>Clorox</td>
			<td>Bar# 044600324111, Splash-less Bleach</td>
			<td>4.5% sodium hypochlorite</td>
		</tr>
		<tr>
			<td>C. elegans: AM140: rmIs132 [unc-54p::q35::yfp]</td>
			<td>Morimoto Lab (Northwestern University)</td>
			<td>AM140, Q35::YFP</td>
			<td>Muscle polyQ</td>
		</tr>
		<tr>
			<td>C. elegans: AM738: rmIs297[vha-6p::q44::yfp; rol-6(su1006)]</td>
			<td>Morimoto Lab (Northwestern University)</td>
			<td>AM738, Q44::YFP</td>
			<td>Intestinal polyQ</td>
		</tr>
		<tr>
			<td>CaCl2&#183;2H2O</td>
			<td>Fisher Scientific</td>
			<td>Cat#C79-500</td>
			<td>Calcium chloride dihydrate</td>
		</tr>
		<tr>
			<td>CellProfiler</td>
			<td>Broad Institute</td>
			<td></td>
			<td>Image analysis software</td>
		</tr>
		<tr>
			<td>Cholesterol</td>
			<td>Fisher Scientific</td>
			<td>Cat#ICN10138201</td>
			<td>Cholesterol</td>
		</tr>
		<tr>
			<td>Circulating Water Bath Head</td>
			<td>Lauda</td>
			<td>26LE</td>
			<td>Lauda E 100</td>
		</tr>
		<tr>
			<td>CoolLED pE300lite 365 dir mount STEREO</td>
			<td>CoolLED</td>
			<td>8114931</td>
			<td>Fluorescent light control and emitter</td>
		</tr>
		<tr>
			<td>16 mL Culture Tubes</td>
			<td>Olympus Plastics</td>
			<td>21-129</td>
			<td>Culture tubes, 17 mm x 100 mm</td>
		</tr>
		<tr>
			<td>Escherichia coli OP50</td>
			<td>Caenorhabditis Genetics Center</td>
			<td>OP50</td>
			<td>E. coli control strain</td>
		</tr>
		<tr>
			<td>Ethanol, 200 Proof</td>
			<td>Decon Labs, Inc.</td>
			<td>2701</td>
			<td></td>
		</tr>
		<tr>
			<td>Eyepiece 10x/23B, adjustable, 3d gen</td>
			<td>Leica Microsystems</td>
			<td>10450910</td>
			<td>Eyepiece set</td>
		</tr>
		<tr>
			<td>Filter Set ET GFP - MZ10F</td>
			<td>Leica Microsystems</td>
			<td>10450588</td>
			<td>Filter cube</td>
		</tr>
		<tr>
			<td>GraphPad Prism v9.2.0</td>
			<td>GraphPad Software, Inc.</td>
			<td></td>
			<td>Statistical analysis tool</td>
		</tr>
		<tr>
			<td>Heratherm Incubator IMP180</td>
			<td>Thermo</td>
			<td>51031562</td>
			<td>Refrigerated incubator</td>
		</tr>
		<tr>
			<td>Innova 4000</td>
			<td>New Brunswick Scientific</td>
			<td>M1192-0000</td>
			<td>Shaking incubator</td>
		</tr>
		<tr>
			<td>K5 Camera</td>
			<td>Leica Microsystems</td>
			<td>11547112</td>
			<td>Stereomicroscope camera</td>
		</tr>
		<tr>
			<td>KH2P04</td>
			<td>Fisher Scientific</td>
			<td>Cat#P285-3</td>
			<td>Potassium phosphate monobasic</td>
		</tr>
		<tr>
			<td>LAS X Imaging Software</td>
			<td>Leica Microsystems</td>
			<td></td>
			<td>Microscope imaging software</td>
		</tr>
		<tr>
			<td>Leica MZ10 F Optics Carrier</td>
			<td>Leica Microsystems</td>
			<td>10450103</td>
			<td>Stereomicroscope</td>
		</tr>
		<tr>
			<td>Levamisole</td>
			<td>Fisher Scientific</td>
			<td>Cat#0215522805</td>
			<td>Levamisole hydrochloride</td>
		</tr>
		<tr>
			<td>Luria Broth (Lennox)</td>
			<td>Apex Bioresearch Products</td>
			<td>Cat#11-125</td>
			<td>LB</td>
		</tr>
		<tr>
			<td>Magnetic Stir Plate</td>
			<td>Fisher Scientific</td>
			<td>11-100-49S</td>
			<td>Stir plate</td>
		</tr>
		<tr>
			<td>MgSO4&#183;7H2O</td>
			<td>Alfa Aesar</td>
			<td>A14491</td>
			<td>Magnesium sulfate heptahydrate</td>
		</tr>
		<tr>
			<td>Microscope Slides</td>
			<td>Premiere</td>
			<td>8205</td>
			<td>Single frosted microscope slides</td>
		</tr>
		<tr>
			<td>Na2HPO4&#183;7H2O</td>
			<td>Fisher Scientific</td>
			<td>Cat#S373-500</td>
			<td>Sodium phosphate dibasic heptahydrate</td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>Fisher Scientific</td>
			<td>Cat#S671-500</td>
			<td>Sodium chloride</td>
		</tr>
		<tr>
			<td>NaOH</td>
			<td>Fisher Scientific</td>
			<td>Cat#S318-3</td>
			<td>Sodium hydroxide pellets</td>
		</tr>
		<tr>
			<td>Objective Achromat, f = 100 mm</td>
			<td>Leica Microsystems</td>
			<td>10411597</td>
			<td>Objective microscope lens</td>
		</tr>
		<tr>
			<td>Petri Dishes</td>
			<td>Genesee Scientific</td>
			<td>Cat#32-107G</td>
			<td>100 mm x 15 mm</td>
		</tr>
		<tr>
			<td>Pseudomonas aeruginosa Mutant Library</td>
			<td>Manoil Lab (University of Washington)</td>
			<td></td>
			<td>P. aeruginosa mutant library</td>
		</tr>
		<tr>
			<td>Suspension Culture Plate 24-Well, Flat Bottom</td>
			<td>Olympus Plastics</td>
			<td>25-102</td>
			<td>Used for worm growth and imaging</td>
		</tr>
		<tr>
			<td>Trinocular Tube 100% M-series</td>
			<td>Leica Microsystems</td>
			<td>10450043</td>
			<td></td>
		</tr>
		<tr>
			<td>Trypticase Peptone</td>
			<td>ThermoFisher, Difco</td>
			<td>Cat#211921</td>
			<td></td>
		</tr>
		<tr>
			<td>TX-400 Rotor</td>
			<td>Thermo Scientific</td>
			<td>Cat#75003181</td>
			<td>Swing bucket rotor</td>
		</tr>
		<tr>
			<td>Vacuum Driven Filter System</td>
			<td>GenClone</td>
			<td>Cat#25-227</td>
			<td>500 mL, PES Membrane, .22 &#181;m</td>
		</tr>
		<tr>
			<td>Video Objective with C-Mount</td>
			<td>Leica Microsystems</td>
			<td>10447367</td>
			<td>0.63x camera adapter tube</td>
		</tr>
	</tbody>
</table>

automating aggregate quantification in caenorhabditis elegans

A rise in the prevalence of neurodegenerative protein conformational diseases (PCDs) has fostered a great interest in this subject over the years. This increased attention has called for the diversification and improvement of animal models capable of reproducing disease phenotypes observed in humans with PCDs. Though murine models have proven invaluable, they are expensive and are associated with laborious, low-throughput methods. 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. Additionally, high conservation between the C. elegans and human genomes makes this model an invaluable discovery tool. Nematodes that express fluorescently tagged tissue-specific polyglutamine (polyQ) tracts exhibit age- and polyQ length-dependent aggregation characterized by fluorescent foci. Such reporters are often employed as proxies to monitor changes in proteostasis across tissues. Manual aggregate quantification is time-consuming, limiting experimental throughput. Furthermore, manual foci quantification can introduce bias, as aggregate identification can be highly subjective. Herein, a protocol consisting of worm culturing, image acquisition, and data processing was standardized to support high-throughput aggregate quantification using C. elegans that express intestine-specific polyQ. By implementing a C. 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. 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. It is anticipated that these methods can drastically simplify the screening process of large bacterial, genomic, or drug libraries using the C. elegans model.

Watch this Scientific Journal Video about Automating Aggregate Quantification in Caenorhabditis elegans at JoVE.com

Automating Aggregate Quantification in Caenorhabditis elegans

The following protocol describes the development and optimization of a high-throughput workflow for worm culturing, fluorescence imaging, and automated image processing to quantify polyglutamine aggregates as an assessment of changes in proteostasis.

Automating Aggregate Quantification in Caenorhabditis elegans

A rise in the prevalence of neurodegenerative protein conformational diseases (PCDs) has fostered a great interest in this subject over the years. This ...

automating-aggregate-quantification-in-caenorhabditis-elegans

Research

JoVE Journal

Biology

2.6K Views.  University of Florida. The following protocol describes the development and optimization of a high-throughput workflow for worm culturing, fluorescence imaging, and automated image processing to quantify polyglutamine aggregates as an assessment of changes in proteostasis. 

Video: Automating Aggregate Quantification in Caenorhabditis elegans

Isolation and In vitro Activation of Caenorhabditis elegans Sperm

Males and hermaphrodites are the two naturally found sexual forms in the nematode C. elegans. The amoeboid sperm are produced by both males and hermaphrodites. In the earlier phase of gametogenesis, the germ cells of hermaphrodites differentiate into limited number of sperm - around 300 - and are stored in a small 'bag' called the spermatheca. Later on, hermaphrodites continually produce oocytes1. In contrast, males produce exclusively sperm throughout their adulthood. The males produce so much sperm that it accounts for &gt;50% of the total cells in a typical adult worm2. Therefore, isolating sperm from males is easier than from that of hermaphrodites.
Only a small proportion of males are naturally generated due to spontaneous non-disjunction of X chromosome3. Crossing hermaphrodites with males or more conveniently, the introduction of mutations to give rise to Him (High Incidence of Males) phenotype are some of strategies through which one can enrich the male population3.
Males can be easily distinguished from hermaphrodites by observing the tail morphology4. Hermaphrodite's tail is pointed, whereas male tail is rounded with mating structures.
Cutting the tail releases vast number of spermatids stored inside the male reproductive tract. Dissection is performed under a stereo microscope using 27 gauge needles. Since spermatids are not physically connected with any other cells, hydraulic pressure expels internal contents of male body, including spermatids2.
Males are directly dissected on a small drop of 'Sperm Medium'. Spermatids are sensitive to alteration in the pH. Hence, HEPES, a compound with good buffering capacity is used in sperm media. Glucose and other salts present in sperm media help maintain osmotic pressure to maintain the integrity of sperm.
Post-meiotic differentiation of spermatids into spermatozoa is termed spermiogenesis or sperm activation. Shakes5, and Nelson6 previously showed that round spermatids can be induced to differentiate into spermatozoa by adding various activating compounds including Pronase E. Here we demonstrate in vitro spermiogenesis of C. elegans spermatids using Pronase E.
Successful spermiogenesis is pre-requisite for fertility and hence the mutants defective in spermiogenesis are sterile. Hitherto several mutants have been shown to be defective specifically in spermiogenesis process7. Abnormality found during in vitro activation of novel Spe (Spermatogenesis defective) mutants would help us discover additional players participating in this event.

Isolation and In vitro Activation of Caenorhabditis elegans Sperm

A protocol for isolating and activating spermatids from male C. elegans is described here. Cutting the posterior end of male releases spermatids. The spermatids can be activated by addition of protease.

Males and hermaphrodites are the two naturally found sexual forms in the nematode C. elegans. The amoeboid sperm are produced by both males and ...

Solid Plate-based Dietary Restriction in Caenorhabditis elegans

Reduction of food intake without malnutrition or starvation is known to increase lifespan and delay the onset of various age-related diseases in a wide range of species, including mammals. It also causes a decrease in body weight and fertility, as well as lower levels of plasma glucose, insulin, and IGF-1 in these animals. This treatment is often referred to as dietary restriction (DR) or caloric restriction (CR). The nematode Caenorhabditis elegans has emerged as an important model organism for studying the biology of aging. Both environmental and genetic manipulations have been used to model DR and have shown to extend lifespan in C. elegans. However, many of the reported DR studies in C. elegans were done by propagating animals in liquid media, while most of the genetic studies in the aging field were done on the standard solid agar in petri plates. Here we present a DR protocol using standard solid NGM agar-based plate with killed bacteria.

Solid Plate-based Dietary Restriction in Caenorhabditis elegans

Here we present a protocol for performing solid plate-based dietary restriction in C. elegans with killed bacteria.

Reduction of food intake without malnutrition or starvation is known to increase lifespan and delay the onset of various age-related diseases in a wide ...

Time-lapse Microscopy of Early Embryogenesis in Caenorhabditis elegans

Caenorhabditis elegans has often been used as a model system in studies of early developmental processes. The transparency of the 
embryos, the genetic resources, and the relative ease of transformation are qualities that make C. elegans an excellent model for early embryogenesis. Laser-based 
confocal microscopy and fluorescently labeled tags allow researchers to follow specific cellular structures and proteins in the developing embryo. For example, 
one can follow specific organelles, such as lysosomes or mitochondria, using fluorescently labeled dyes. These dyes can be delivered to the early embryo by means 
of microinjection into the adult gonad. Also, the localization of specific proteins can be followed using fluorescent protein tags. Examples are presented here 
demonstrating the use of a fluorescent lysosomal dye as well as fluorescently tagged histone and ubiquitin proteins. The labeled histone is used to visualize 
the DNA and thus identify the stage of the cell cycle. GFP-tagged ubiquitin reveals the dynamics of ubiquitinated vesicles in the early embryo. Observations 
of labeled lysosomes and GFP:: ubiquitin can be used to determine if there is colocalization between ubiquitinated vesicles and lysosomes. A technique for 
the microinjection of the lysosomal dye is presented. Techniques for generating transgenenic strains are presented elsewhere (1, 2). For imaging, embryos 
are cut out of adult hermaphrodite nematodes and mounted onto 2% agarose pads followed by time-lapse microscopy on a standard laser scanning confocal 
microscope or a spinning disk confocal microscope. This methodology provides for the high resolution visualization of early embryogenesis.

Time-lapse Microscopy of Early Embryogenesis in Caenorhabditis elegans

This article describes a technique for the visualization of the early events of embryogenesis in the nematode Caenorhabditis elegans.

Caenorhabditis elegans has often been used as a model system in studies of early developmental processes.  The transparency of the 
embryos, the genetic ...

Basic Caenorhabditis elegans Methods: Synchronization and Observation

Research into the molecular and developmental biology of the nematode Caenorhabditis elegans was begun in the early seventies by Sydney Brenner and it has since been used extensively as a model organism 1. C. elegans possesses key attributes such as simplicity, transparency and short life cycle that have made it a suitable experimental system for fundamental biological studies for many years 2. Discoveries in this nematode have broad implications because many cellular and molecular processes that control animal development are evolutionary conserved 3.
C. elegans life cycle goes through an embryonic stage and four larval stages before animals reach adulthood. Development can take 2 to 4 days depending on the temperature. In each of the stages several characteristic traits can be observed. The knowledge of its complete cell lineage 4,5 together with the deep annotation of its genome turn this nematode into a great model in fields as diverse as the neurobiology 6, aging 7,8, stem cell biology 9 and germ line biology 10. 
An additional feature that makes C. elegans an attractive model to work with is the possibility of obtaining populations of worms synchronized at a specific stage through a relatively easy protocol. The ease of maintaining and propagating this nematode added to the possibility of synchronization provide a powerful tool to obtain large amounts of worms, which can be used for a wide variety of small or high-throughput experiments such as RNAi screens, microarrays, massive sequencing, immunoblot or in situ hybridization, among others. 
Because of its transparency, C. elegans structures can be distinguished under the microscope using Differential Interference Contrast microscopy, also known as Nomarski microscopy. The use of a fluorescent DNA binder, DAPI (4',6-diamidino-2-phenylindole), for instance, can lead to the specific identification and localization of individual cells, as well as subcellular structures/defects associated to them.

Basic Caenorhabditis elegans Methods: Synchronization and Observation

The easiness of maintaining and propagating the nematode C. elegans make it a nice model organism to work with. The possibility of synchronizing worms allows the work with a significant amount of subjects at the same developmental stage, what facilitates the study of one particular process in many animals.

Research into the molecular and developmental biology of the nematode Caenorhabditis elegans was begun in the early seventies by Sydney Brenner and it has ...

Prostaglandin Extraction and Analysis in Caenorhabditis elegans

Caenorhabditis elegans is emerging as a powerful animal model to study the biology of lipids1-9. Prostaglandins are an important class of eicosanoids, which are lipid signals derived from polyunsaturated fatty acids (PUFAs)10-14. These signalling molecules are difficult to study because of their low abundance and reactive nature. The characteristic feature of prostaglandins is a cyclopentane ring structure located within the fatty acid backbone. In mammals, prostaglandins can be formed through cyclooxygenase enzyme-dependent and -independent pathways10,15. C. elegans synthesizes a wide array of prostaglandins independent of cyclooxygenases6,16,17. A large class of F-series prostaglandins has been identified, but the study of eicosanoids is at an early stage with ample room for new discoveries. Here we describe a procedure for extracting and analyzing prostaglandins and other eicosanoids. Charged lipids are extracted from mass worm cultures using a liquid-liquid extraction technique and analyzed by liquid chromatography coupled to electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS). The inclusion of deuterated analogs of prostaglandins, such as PGF2 &alpha;-d4 as an internal standard is recommended for quantitative analysis. Multiple reaction monitoring or MRM can be used to quantify and compare specific prostaglandin types between wild-type and mutant animals. Collision-induced decomposition or MS/MS can be used to obtain information on important structural features. Liquid chromatography mass spectrometry (LC-MS) survey scans of a selected mass range, such as m/z 315-360 can be used to evaluate global changes in prostaglandin levels. We provide examples of all three analyses. These methods will provide researchers with a toolset for discovering novel eicosanoids and delineating their metabolic pathways.

Prostaglandin Extraction and Analysis in Caenorhabditis elegans

In this paper, we describe an optimized procedure for extracting and analyzing prostaglandins and other eicosanoids from C. elegans using LC-MS/MS.

Caenorhabditis elegans is emerging as a powerful animal model to study the biology of lipids1-9. Prostaglandins are an important class of eicosanoids, ...

Observation and Quantification of Telomere and Repetitive Sequences Using Fluorescence In Situ Hybridization (FISH) with PNA Probes in Caenorhabditis elegans

Telomere is a ribonucleoprotein structure that protects chromosomal ends from aberrant fusion and degradation. Telomere length is maintained by telomerase or an alternative pathway, known as alternative lengthening of telomeres (ALT)1. Recently, C. elegans has emerged as a multicellular model organism for the study of telomere and ALT2. Visualization of repetitive sequences in the genome is critical in understanding the biology of telomeres. While telomere length can be measured by telomere restriction fragment assay or quantitative PCR, these methods only provide the averaged telomere length. On the contrary, fluorescence in situ hybridization (FISH) can provide the information of the individual telomeres in cells. Here, we provide protocols and representative results of the method to determine telomere length of C. elegans by fluorescent in situ hybridization. This method provides a simple, but powerful, in situ procedure that does not cause noticeable damage to morphology. By using fluorescently labeled peptide nucleic acid (PNA) and digoxigenin-dUTP-labeled probe, we were able to visualize two different repetitive sequences: telomere repeats and template of ALT (TALT) in C. elegans embryos and gonads.

Observation and Quantification of Telomere and Repetitive Sequences Using Fluorescence In Situ Hybridization FISH with PNA Probes in Caenorhabditis elegans

We report a concise procedure of fluorescence in situ hybridization (FISH) in the gonad and embryos of Caenorhabditis elegans for observing and quantifying repetitive sequences. We successfully observed and quantified two different repetitive sequences, telomere repeats and template of alternative lengthening of telomeres (TALT).

Telomere is a ribonucleoprotein structure that protects chromosomal ends from aberrant fusion and degradation. Telomere length is maintained by telomerase ...

Cultivation of Caenorhabditis elegans in Three Dimensions in the Laboratory

The use of genetic model organisms such as Caenorhabditis elegans has led to seminal discoveries in biology over the last five decades. Most of what we know about C. elegans is limited to laboratory cultivation of the nematodes that may not necessarily reflect the environments they normally inhabit in nature. Cultivation of C. elegans in a 3D habitat that is more similar to the 3D matrix that worms encounter in rotten fruits and vegetative compost in nature could reveal novel phenotypes and behaviors not observed in 2D. In addition, experiments in 3D can address how phenotypes we observe in 2D are relevant for the worm in nature. Here, a new method in which C. elegans grows and reproduces normally in three dimensions is presented. Cultivation of C. elegans in Nematode Growth Tube-3D (NGT-3D) can allow us to measure the reproductive fitness of C. elegans strains or different conditions in a 3D environment. We also present a novel method, termed Nematode Growth Bottle-3D (NGB-3D), to cultivate C. elegans in 3D for microscopic analysis. These methods allow scientists to study C. elegans biology in conditions that are more reflective of the environments they encounter in nature. These can help us to understand the overlying evolutionary relevance of the physiology and behavior of C. elegans we observe in the laboratory.

Cultivation of Caenorhabditis elegans in Three Dimensions in the Laboratory

We present a simple method to construct 3D nematode cultivation systems called NGT-3D and NGB-3D. These can be used to study nematode fitness and behaviors in habitats that are more similar to natural Caenorhabditis elegans habitats than the standard 2D laboratory C. elegans culture plates.

The use of genetic model organisms such as Caenorhabditis elegans has led to seminal discoveries in biology over the last five decades. Most of what we ...

Measurement of Oxygen Consumption Rates in Intact Caenorhabditis elegans

Optimal mitochondrial function is critical for healthy cellular activity, particularly in cells that have high energy demands like those in the nervous system and muscle. Consistent with this, mitochondrial dysfunction has been associated with a myriad of neurodegenerative diseases and aging in general. Caenorhabditis elegans have been a powerful model system for elucidating the many intricacies of mitochondrial function. Mitochondrial respiration is a strong indicator of mitochondrial function and recently developed respirometers offer a state-of-the-art platform to measure respiration in cells. In this protocol, we provide a technique to analyze live, intact C. elegans. This protocol spans a period of ~7 days and includes steps for (1) growing and synchronization of C. elegans, (2) preparation&#160;of compounds to be injected and hydration of probes, (3) drug loading and cartridge equilibration, (4) preparation of worm assay plate and assay run, and (5) post-experiment data analysis.

Measurement of Oxygen Consumption Rates in Intact Caenorhabditis elegans

Mitochondrial respiration is critical for organismal survival; therefore, oxygen consumption rate is an excellent indicator of mitochondrial health. In this protocol, we describe the use of a commercially available respirometer to measure basal and maximal oxygen consumption rates in live, intact, and freely-motile Caenorhabditis elegans.

Optimal mitochondrial function is critical for healthy cellular activity, particularly in cells that have high energy demands like those in the nervous ...

Quantifying Tissue-Specific Proteostatic Decline in Caenorhabditis elegans

The ability to maintain proper function and folding of the proteome (protein homeostasis) declines during normal aging, facilitating the onset of a growing number of age-associated diseases. For instance, proteins with polyglutamine expansions are prone to aggregation, as exemplified with the huntingtin protein and concomitant onset of Huntington&#8217;s disease. The age-associated deterioration of the proteome has been widely studied through the use of transgenic Caenorhabditis elegans expressing polyQ repeats fused to a yellow fluorescent protein (YFP). This polyQ::YFP transgenic animal model facilitates the direct quantification of the age-associated decline of the proteome through imaging the progressive formation of fluorescent foci (i.e., protein aggregates) and subsequent onset of locomotion defects that develop as a result of the collapse of the proteome. Further, the expression of the polyQ::YFP transgene can be driven by tissue-specific promoters, allowing the assessment of proteostasis across tissues in the context of an intact multicellular organism. This model is highly amenable to genetic analysis, thus providing an approach to quantify aging that is complementary to lifespan assays. We describe how to accurately measure polyQ::YFP foci formation within either neurons or body wall muscle during aging, and the subsequent onset of behavioral defects. Next, we highlight how these approaches can be adapted for higher throughput, and potential future applications using other emerging strategies for C. elegans genetic analysis.

Quantifying Tissue-Specific Proteostatic Decline in Caenorhabditis elegans

Proteostatic decline is a hallmark of aging, facilitating the onset of neurodegenerative diseases. We outline a protocol to quantifiably measure proteostasis in two different Caenorhabditis elegans tissues through heterologous expression of polyglutamine repeats fused to a fluorescent reporter. This model allows rapid in vivo genetic analysis of proteostasis.

The ability to maintain proper function and folding of the proteome (protein homeostasis) declines during normal aging, facilitating the onset of a ...

Modeling Age-Associated Neurodegenerative Diseases in Caenorhabditis elegans

Battling human neurodegenerative pathologies and managing their pervasive socioeconomic impact is becoming a global priority. Notwithstanding their detrimental effects on the human life quality and the healthcare system, the majority of human neurodegenerative disorders still remain incurable and non-preventable. Therefore, the development of novel therapeutic interventions against such maladies is becoming a pressing urgency. Age-associated deterioration of neuronal circuits and function is evolutionarily conserved in organisms as diverse as the lowly worm Caenorhabditis elegans and humans, signifying similarities in the underlying cellular and molecular mechanisms. C. elegans is a highly malleable genetic model, which offers a well-characterized nervous system, body transparency and a diverse repertoire of genetic and imaging techniques to assess neuronal activity and quality control during ageing. Here, we introduce and describe methodologies utilizing some versatile nematode models, including hyperactivated ion channel-induced necrosis (e.g., deg-3(d) and mec-4(d)) and protein aggregate (e.g., &#945;-syunclein and poly-glutamate)-induced neurotoxicity, to monitor and dissect the cellular and molecular underpinnings of age-related neuronal breakdown. A combination of these animal neurodegeneration models, together with genetic and pharmacological screens for cell death modulators will lead to an unprecedented understanding of age-related breakdown of neuronal function and will provide critical insights with broad relevance to human health and quality of life.

Modeling Age-Associated Neurodegenerative Diseases in Caenorhabditis elegans

Here, we introduce and describe widely accessible methodologies utilizing some versatile nematode models, including hyperactivated ion channel-induced necrosis and protein aggregate-induced neurotoxicity, to monitor and dissect the cellular and molecular underpinnings of age-associated neurodegenerative diseases.

Battling human neurodegenerative pathologies and managing their pervasive socioeconomic impact is becoming a global priority. Notwithstanding their ...