Filter Retardation Assay for Detecting and Quantifying Polyglutamine Aggregates Using Caenorhabditis elegans Lysates

Protein aggregation is a hallmark of several neurodegenerative diseases and is associated with impaired protein homeostasis. This imbalance is caused by the loss of the protein's native conformation, which ultimately results in its aggregation or abnormal localization within the cell. Using a C. elegans model of polyglutamine diseases, we describe in detail the filter retardation assay, a method that captures protein aggregates in a cellulose acetate membrane and allows its detection and quantification by immunoblotting

Nuclear/Cytoplasmic Fractionation of Proteins from Caenorhabditis elegans

C. elegans is widely used to investigate biological processes related to health and disease. To study protein localization, fluorescently-tagged proteins can be used in vivo or immunohistochemistry can be performed in whole worms. Here, we describe a technique to localize a protein of interest at a subcellular level in C. elegans lysates, which can give insight into the location, function and/or toxicity of proteinsNational Institutes of Health National Centre for Research Resources (NIH)European Research Council (ERC)USANIH National Center for Research Resources (NCRR)Japan National BioResource Projec

Identification of an RNA Polymerase III Regulator Linked to Disease-Associated Protein Aggregation.

Protein aggregation is associated with age-related neurodegenerative disorders, such as Alzheimer's and polyglutamine diseases. As a causal relationship between protein aggregation and neurodegeneration remains elusive, understanding the cellular mechanisms regulating protein aggregation will help develop future treatments. To identify such mechanisms, we conducted a forward genetic screen in a C. elegans model of polyglutamine aggregation and identified the protein MOAG-2/LIR-3 as a driver of protein aggregation. In the absence of polyglutamine, MOAG-2/LIR-3 regulates the RNA polymerase III-associated transcription of small non-coding RNAs. This regulation is lost in the presence of polyglutamine, which mislocalizes MOAG-2/LIR-3 from the nucleus to the cytosol. We then show biochemically that MOAG-2/LIR-3 can also catalyze the aggregation of polyglutamine-expanded huntingtin. These results suggest that polyglutamine can induce an aggregation-promoting activity of MOAG-2/LIR-3 in the cytosol. The concept that certain aggregation-prone proteins can convert other endogenous proteins into drivers of aggregation and toxicity adds to the understanding of how cellular homeostasis can be deteriorated in protein misfolding diseases

Comparative Studies in the A30P and A53T α-Synuclein C. elegans Strains to Investigate the Molecular Origins of Parkinson's Disease

The aggregation of α-synuclein is a hallmark of Parkinson's disease (PD) and a variety of related neurological disorders. A number of mutations in this protein, including A30P and A53T, are associated with familial forms of the disease. Patients carrying the A30P mutation typically exhibit a similar age of onset and symptoms as sporadic PD, while those carrying the A53T mutation generally have an earlier age of onset and an accelerated progression. We report two C. elegans models of PD (PDA30P and PDA53T), which express these mutational variants in the muscle cells, and probed their behavior relative to animals expressing the wild-type protein (PDWT). PDA30P worms showed a reduced speed of movement and an increased paralysis rate, control worms, but no change in the frequency of body bends. By contrast, in PDA53T worms both speed and frequency of body bends were significantly decreased, and paralysis rate was increased. α-Synuclein was also observed to be less well localized into aggregates in PDA30P worms compared to PDA53T and PDWT worms, and amyloid-like features were evident later in the life of the animals, despite comparable levels of expression of α-synuclein. Furthermore, squalamine, a natural product currently in clinical trials for treating symptomatic aspects of PD, was found to reduce significantly the aggregation of α-synuclein and its associated toxicity in PDA53T and PDWT worms, but had less marked effects in PDA30P. In addition, using an antibody that targets the N-terminal region of α-synuclein, we observed a suppression of toxicity in PDA30P, PDA53T and PDWT worms. These results illustrate the use of these two C. elegans models in fundamental and applied PD research

Discovery and functional prioritization of Parkinson's disease candidate genes from large-scale whole exome sequencing.

BACKGROUND: Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models. RESULTS: Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes-GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C-also showed evidence consistent with genetic replication. CONCLUSIONS: By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies

C. elegans as a Model for Synucleinopathies and Other Neurodegenerative Diseases: Tools and Techniques

Caenorhabditis elegans is widely used to investigate biological processes related to health and disease. Multiple C. elegans models for human neurodegenerative diseases do exist, including those expressing human α-synuclein. Even though these models do not feature all pathological and molecular hallmarks of the disease they mimic, they allow for the identification and dissection of molecular pathways that are involved. In line with this, genetic screens have yielded multiple modifiers of proteotoxicity in C. elegans models for neurodegenerative diseases. Here, we describe a set of common screening approaches and tools that can be used to study synucleinopathies and other neurodegenerative diseases in C. elegans. RNA interference and mutagenesis screens can be used to find genes that affect proteotoxicity, while relatively simple molecular, cellular (fractionation studies), metabolic (respiration studies), and behavioral (thrashing and crawling) readouts can be used to study the effects of disease proteins and modifiers more closely

Raw data for Figures in the publication "Assessing motor-related phenotypes of Caenorhabditis elegans with the wide field-of-view nematode tracking platform"

This dataset contains the raw data for the publication "Assessing motor-related phenotypes of Caenorhabditis elegans with the wide field-of-view nematode tracking platform". Here you can find the associated raw data from Figs. 3, 4, 5, 6, 7, 13 and 14 belonging to the Nature Protocols paper: ‘Assessing motor-related phenotypes of Caenorhabditis elegans with the wide field-of-view nematode tracking platform’. All data was generated with the WF-NTP software and not manipulated afterwards unless stated otherwise. For the figures the next data was used from each dataset: Figure 3: only the raw data for eccentricity and BPM (bends per minute) was used. Figure 4: only the raw data for BPM, average and maximum speed (mm/s) was used. Figure 5: only the raw data for maximum speed (mm/s) was used. Figure 6: this is a processed file, for both D1 and D8 old worms we compared the ‘detected’ number of worms per movie by the WF-NTP with the actual number of worms that was manually counted. Delta provides the difference. Also, the file contains several tabs in which the worm presence is annotated (How many frames was each worm present). The supplementary tables generated from this data are also included. Figure 7: only the raw data for average speed (mm/s) was used. Figure 13: only the raw data for BPM was used and compared with the manual counted data. Figure 14: only the raw data for BPM was used

Raw data for Figures in the publication "Assessing motor-related phenotypes of Caenorhabditis elegans with the wide field-of-view nematode tracking platform"

This dataset contains the raw data for the publication "Assessing motor-related phenotypes of Caenorhabditis elegans with the wide field-of-view nematode tracking platform". Here you can find the associated raw data from Figs. 3, 4, 5, 6, 7, 13 and 14 belonging to the Nature Protocols paper: ‘Assessing motor-related phenotypes of Caenorhabditis elegans with the wide field-of-view nematode tracking platform’. All data was generated with the WF-NTP software and not manipulated afterwards unless stated otherwise. For the figures the next data was used from each dataset: Figure 3: only the raw data for eccentricity and BPM (bends per minute) was used. Figure 4: only the raw data for BPM, average and maximum speed (mm/s) was used. Figure 5: only the raw data for maximum speed (mm/s) was used. Figure 6: this is a processed file, for both D1 and D8 old worms we compared the ‘detected’ number of worms per movie by the WF-NTP with the actual number of worms that was manually counted. Delta provides the difference. Also, the file contains several tabs in which the worm presence is annotated (How many frames was each worm present). The supplementary tables generated from this data are also included. Figure 7: only the raw data for average speed (mm/s) was used. Figure 13: only the raw data for BPM was used and compared with the manual counted data. Figure 14: only the raw data for BPM was used