Podsumowanie

Quantifying Tissue-Specific Proteostatic Decline in Caenorhabditis elegans

Published: September 07, 2021
doi:

Podsumowanie

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.

Abstract

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’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.

Introduction

Protein homeostasis (proteostasis) is defined as the cellular ability to maintain proper function and folding of the proteome. The inherent challenge to proteostasis is ensuring all proteins are properly folded and maintained in a native conformation, which is further amplified by the varied nature of protein size, amino acid composition, structural conformation, stability, turnover, expression, sub-cellular compartmentalization, and modifications1. Proteostasis is maintained through the coordinated action of a large proteostatic network, consisting of approximately 2000 unique proteins, which regulate proper synthesis, folding, trafficking, and degradation within the proteome2,3. The workhorse components of the proteostatic network are nine major families of molecular chaperones4. Every tissue and cell type preferentially utilizes specific subsets of molecular chaperones, presumably in alignment with the differing demands of distinct proteomes5.

One hallmark of normal organismal aging is the progressive decline and collapse of cellular proteostasis, which is thought to be an underlying basis for the onset and progression of a growing number of age-associated diseases. For instance, Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and Amyotrophic Lateral Sclerosis (ALS) share a common characteristic: in each case manifestation of neurodegeneration is driven by genetic alterations that predisposes a mutant protein to aggregation (amyloid-β/Tau, α-synuclein, HTT, FUS/TBD-43/SOD-1, respectively)6,7,8,9,10. During aging, the integrity and inducibility of the proteostatic network declines, which results in the accumulation of proteotoxic aggregates that result in cellular dysfunction and neurodegeneration. Of note, protein conformational diseases are not unique to neurons, and occur across multiple tissues, as highlighted by type II diabetes, multiple myeloma, and cystic fibrosis11,12,13,14. Therefore, elucidating mechanisms capable of preserving proteostasis will facilitate the development of targeted interventions for the treatment of disease and to promote healthy aging.

The small soil nematode Caenorhabditis elegans (C. elegans) has been instrumental in discovering genes and elucidating pathways that alter proteostasis. Many components of the proteostatic network and the signal transduction pathways that regulate proteostasis are evolutionarily conserved. Furthermore, C. elegans has reduced complexity and redundancy relative to vertebrate systems, making it more amenable to genetic analysis and gene discovery. Additional advantages of C. elegans that have led to it being widely used as a model system to study proteostasis include: powerful genetic and functional genomics, a short life cycle (3 days) and lifespan (3 weeks), a compact and well-annotated genome, the availability of a wide assortment of genetic mutants, and the ease of visualizing tissue-specific changes in cell biology using fluorescent reporters.

The progressive decay of proteostasis during aging can be easily quantified in C. elegans. The Morimoto laboratory first demonstrated that a polyglutamine expansion fused to yellow fluorescent protein (polyQ::YFP) could be used to quantify proteostatic decline in C. elegans during aging15,16,17,18. YFP fusions to 35 glutamine repeats or more result in an age-associated formation of fluorescent foci along with signs of cellular pathology. Of note, this range of glutamine expansion mirrors the length of the polyglutamine tract of the Huntingtin protein at which Huntington’s Disease pathology begins to be observed in humans (typically >35 CAG repeats)19. Strains with expression of polyQ::YFP within muscle, intestinal, or neuronal cells have been utilized to confirm that the age-associated decline of proteostasis occurs across different cell and tissue types. Muscle-specific polyQ::YFP expression (i.e., unc-54p::Q35::YFP) has been the most widely used tissue-specific reporter, as accumulating fluorescent foci are easy to quantify over the first few days of adulthood using a simple fluorescent dissecting microscope (Figure 1A-1B). Additionally, animals become paralyzed during mid-life, as the proteome within the muscle collapses due to the proteotoxic effect of the reporter (Figure 1C). Similarly, the age-associated decline in neuronal proteostasis can be followed (rgef-1p::Q40::YFP) by directly quantifying foci/aggregate formation and age-associated declines in coordinated body-bends after placing animals into liquid (Figure 2).

Here, we present a detailed protocol on how to measure the age-dependent progression of protein aggregate accumulation and the associated proteotoxicity induced by the expression of polyglutamine repeats within neuronal and muscle tissue in C. elegans. We provide examples of typical results generated using these strains and methods. Further, we show how we have utilized these methods to study transcriptional regulation of the proteostatic network. We discuss additional ways these reporters can be easily integrated with other existing reagents or adapted for larger screens.

Protokół

1. Preparation of reagents Select genes of interest to be inactivated via feeding-based RNAi. Purchase stocks of HT115 E. coli containing the RNAi clone of interest20. Alternatively, subclone the cDNA of the gene of interest into the multicloning site of the L4440 plasmid. NOTE: To prevent degradation of dsRNA within the bacteria, use the HT115 strain. This is an RNase III-deficient E. coli strain with IPTG-inducible T7 polymerase activity. For proteostasis studies that do not use feeding-based RNAi, either HT115 or OP50 E. coli on standard NGM plates can be used. Prepare 5 x 6 cm plates per test condition. For experiments using RNAi, induce dsRNA production in transformed HT115 E. coli. For studies without RNAi, OP50 E. coli on standard NGM plates can be used (See Supplemental File 1 for standard NGM and RNAi plate recipes). NOTE: RNAi plates can be stored at 4 °C for several months before seeding with bacteria. Grow cultures of E. coli overnight (16-20 h) at 37 °C in a shaking incubator at 220 rpm. Grow HT115 E. coli in Luria Broth (LB) with ampicillin (50 μg/mL). NOTE: Standard OP50 E. coli is not antibiotic resistant, but streptomycin resistant variants are also available. Concentrate bacteria by centrifugation at 2,400 x g for 15-20 min in a benchtop centrifuge, aspirate the supernatant, and re-suspend the pellet in 1/10th the starting volume (i.e., 10x concentration) of LB with ampicillin for HT115, or LB without ampicillin for standard OP50. Aliquot 200 µL of concentrated 10x bacteria to each plate (3-4 replicates per test condition, with 2 extra backup plates, to be used in the event of contamination). Allow open plates to dry in a clean environment such as a laminar flow bench until all liquid has been absorbed or allow covered plates to dry on a lab bench overnight. For seeded RNAi plates dried in a hood, store dried plates within a worm box overnight (up to 24 hours) at room temperature. After 1 day at RT, plates can be stored at 4 °C for up to 2 weeks in a sealed bag (to prevent plates from drying out). Before use, allow plates stored at 4 °C to return to room temperature within the zip-lock bag to prevent condensation from introducing airborne fungal contaminates. When using feeding-based RNAi, leave seeded HT115 bacteria on RNAi plates at room temperature for at least 12 hours prior to adding C. elegans. RNAi plates contain IPTG, which induces dsRNA production. Alternatively, IPTG can be added to the liquid cultures at the end of step 1.3.1, 2 hours prior to seeding. Avoid long-term storage of seeded HT115 plates at room temperature (greater than a few days) to avoid cracking of the agar that will cause C. elegans to burrow into agar. 2. Synchronization of C. elegans NOTE: Choose whether to synchronize C. elegans by either alkaline hypochlorite treatment of gravid adults or egg lay. Synchronize animals by hypochlorite treatment of gravid adult animals to promote the release of embryos22. For hypochlorite treatment, wash gravid hermaphrodites 2 times with M9 buffer, then resuspend in 5 mL hypochlorite solution (3.25 mL of hypochlorite solution, 1 mL of M9 buffer and 0.75 mL of 5 M NaOH) for 5 min, shaking resuspended animals every minute. After 5 min, spin down animals and wash 3 times with M9 buffer. NOTE: Hypochlorite treatment has been posited to affect proteostasis21. After hypochlorite treatment, allow embryos to hatch overnight in 3 mL of M9 solution with rotation at 20 °C. Calculate the density of L1 animals (or alternatively, embryos) per µL by dropping 10 µL of L1 solution 3x onto a 6 cm plate and counting the number of L1 animals to calculate the average number of L1 animals per µL. L1 animals will settle over time. Therefore, periodically mix L1 solutions to avoid settling. Seed 50 L1 animals per plate, count and record the number seeded, and move plates to a 20 °C incubator. It is important to know the actual number of animals on each plate at the start of the assay. NOTE: Synchronizing L1 animals by overnight hatching in M9 is routinely used as it minimizes developmental heterogeneity after placing animals onto food. However, synchronization occurs through developmental arrest in response to starvation cues, which for some studies should be avoided (see23 for additional discussion). As an alternative, roughly synchronized animals can be obtained through an egg-lay, see 2.2. Freeze and store leftover L1 animals in liquid nitrogen or a -80 °C freezer. In this way, a sample of each strain at the time of the experimental setup is preserved, creating a valuable resource for future studies and improving reproducibility. NOTE: See Supplemental File 1 for hypochlorite and M9 solution recipes. To synchronize animals via egg lay, place 20 young gravid adult animals (day 1 of adulthood) onto each plate for 4-6 hours, and allow them to lay eggs until there are approximately 50 eggs per plate. Remove all gravid adults and move plates with eggs to a 20 °C incubator. NOTE: The gravid adult animals should be synchronized at the first day of adulthood. Older animals may lay eggs that have been retained in the uterus, causing the release of eggs that are in a more advanced developmental stage. 3. Progeny production NOTE: Steps must be taken to either prevent progeny production or to separate the synchronized starting population from their progeny. Preventing progeny production can be achieved chemically with addition of 5-Fluoro-2'-deoxyuridine (FUdR) to plates, which is described here. Some studies have reported that FUdR can alter proteostasis24,25. Alternative approaches to prevent progeny production are discussed below. Make a 1000x stock solution of FUdR by dissolving 1 g of FUdR into 10 mL of ultrapure H2O. Filter sterilize stock FUdR with a 0.2 μm filter and a 10 mL syringe. Aliquot 1 mL of stock into a sterile 1.5 mL tube. Freeze and store at -20 °C. Grow animals at 20 °C until the L4 stage. N2 animals raised from synchronized L1s from hypochlorite treatment require approximately 40 hours of growth at 20 °C to reach L4. Growth rates for other strains should be empirically tested prior to experimentation. For details on how to accurately stage C. elegans see26. To each 6 cm plate with L4 animals, add 100 µL of 80x FUdR. It is critical to add FUdR at the L4 stage. Return plates to a worm box and put the box in a zip-lock bag. Return to appropriate incubator. 4. Measuring the decline in proteostasis in muscle tissue by using polyglutamine-expressing animals NOTE: Two methods can be used to identify proteostasis decline in muscle cells: imaging the formation of protein aggregates during aging (4.1) and measuring the proteotoxicity these aggregates cause with age through the onset of paralysis (4.2). Imaging polyglutamine aggregate formation in the muscle during aging NOTE: The age-dependent progression of protein aggregation in the muscle cells is imaged using polyglutamine (polyQ) repeats fused to a yellow fluorescent protein (YFP). This protocol outlines use of strain AM140 rmIs132[unc-54p::Q35::YFP], but other polyglutamine variant strains can also be used. The polyQ::YFP transgene is expressed in the muscle using the unc-54 muscle-specific promoter. Synchronized unc-54p::polyQ::YFP expressing animals are visualized at Day 1, 2, 3 and 4 of adulthood. To visualize unc-54p::polyQ::YFP aggregates, use a compound microscope equipped for fluorescence or a fluorescent dissecting microscope. AM140 is available from the Caenorhabditis Genetics Center (CGC) at: https://cgc.umn.edu/strain/AM140. On imaging days (Day 1, 2, 3 and 4 of adulthood), pick 20 animals and mount on a microscope slide setup with a 3% agarose pad and a 5 μL drop of 10 mM sodium azide (diluted in M9 buffer). After all animals are immobilized by sodium azide (~ 5 minutes), image the whole bodies of the animals using a 10x magnification lens (Figure 1A). For imaging, use a FITC filter and the same exposure for every animal. Discard slides after imaging. NOTE: Alternatively, YFP foci can also be quantified directly on plates, but movement must be inhibited by applying a stream of carbon dioxide onto the plate while scoring. This alternative method is most appropriate when screening a large number of conditions (see discussion for more details). After acquisition of images, count the number of foci in the body wall muscles of the whole animal. Foci are brighter punctuated signals that can be differentiated from the dimmer soluble signal in the background. Plot the progression of YFP foci accumulation from days 1, 2, 3 and 4. Plot an XY graph where X represents days of adulthood and Y represents number of unc-54p::polyQ::YFP foci (Figure 1B). The number of foci in the experimental condition (e.g., gene downregulation or overexpression) is compared to control animals. Perform statistical analysis between the groups at each time point observed for each trial. When comparing foci counts for only two conditions, perform an independent sample t-test at each time point. When comparing foci counts for more than two conditions, perform an omnibus one-way ANOVA analysis for each time point, including the data for all the conditions at that time point. If the omnibus ANOVA yields a significant p-value (i.e., p < 0.005), perform a post-hoc analysis with pairwise independent sample t-tests to determine the specific conditions between which a significant difference in foci was detected (e.g., for groups A, B, and C compare A & B, A & C, and B & C). Measuring animal paralysis rates as a surrogate for polyglutamine toxicity in muscle cells NOTE: The age-dependent increase of polyQ aggregates in muscle causes the decline of muscular function that drives locomotion. This defect in locomotion can be determined by measuring the progressive rate of paralysis in polyQ-expressing animals. For the paralysis assay, synchronized unc-54p::polyQ::YFP expressing animals are scored at Day 3, 5, 7 and 9 of adulthood. Add additional time points, as needed to extend the scoring range, such that you can assess the effect of genetic perturbation. On scoring days (Day 3, 5, 7 and 9 of adulthood), look at the 6 cm plates containing 50 animals and record the number of paralyzed animals. Remove paralyzed animals from the plate. If animals have crawled off the plate, or have died, they should be censored; record the event so it can be accounted for in the analysis. NOTE: An animal is considered to be paralyzed when no movement is observed after exposing them to light or gentle touch stimuli. Pharyngeal pumping activity is used to determine whether nonmoving animals are alive or dead. At the completion of the experiment, calculate the paralysis rate for each condition. Do this at each time point by dividing the fraction of paralyzed animals by the total number of animals observed for that condition at that time. If observing multiple plates per condition per time point (i.e., replicate plates), calculate the ratio separately for each replicate. Plot the progression of paralysis rate in an XY graph (scatterplot). X represents days of adulthood and Y represents paralysis rates. The paralysis rate of unc-54p::polyQ::YFP animals is compared to control animals (Figure 1C). Perform statistical analysis between the groups; for multiple trials, treat trials independently. Use the Cox Proportional-Hazards Regression and the Wald test. Most data analysis tools that support survival analysis also support Cox modeling. Transform the data: each condition should have two columns, one for time, and another for “event”. At each time point observed, add a row with “0” for each paralyzed animal, and a “1” for each censored animal. The total number of rows should be equal to the number of starting animals on the plate for that condition. Perform Cox Proportional-Hazards modeling, followed by the Wald test, according to instructions for your statistical software. A univariate model will be appropriate for typical experiment designs. For more than two conditions, if a test with all conditions included indicates a significant result (i.e., p < 0.005), pairwise tests between conditions can be performed to determine the specific significant pair(s) of conditions. NOTE: The Cox model relies on an assumption that the test condition(s) modulate the probability of an event proportionally over time. This means, for example, that the Cox model would not be appropriate for comparing a condition under which most animals are paralyzed at day 1 to a condition under which most animals are paralyzed at day 9. Extensions of the Cox model, and other approaches for comparing proportions paralyzed at each time point, are available for cases where the proportional hazards assumption does not hold, see27,28,29,30. 5. Measuring the decline in proteostasis in neuronal tissue by using polyglutamine expressing animals. NOTE: Two complementary methods are used to assay proteostasis decline in neurons (1) by quantifying the formation of protein aggregates (fluorescent foci) during aging and (2) by measuring age-associated decline in the neuronal proteome via a movement-based assay. Imaging polyglutamine aggregate formation in the neurons during aging NOTE: Similar to the assay already discussed in muscle tissue, the age-dependent progression of protein aggregation in the neurons is imaged by expressing a polyQ::YFP fusion protein driven by the pan-neuronal tissue-specific promoter of rgef-1. Specifically we use AM101: rmIs110 [rgef-1p::Q40::YFP], a forty glutamine fusion to YFP16. To visualize rgef-1p::polyQ::YFP, use a compound microscope equipped for fluorescence with a 40x magnification lens. AM101 is available from the CGC at: https://cgc.umn.edu/strain/AM101. On imaging days (Day 4, 6, 8 and 10 of adulthood), pick 20 animals and mount on a microscope slide containing a 3% agarose pad with a 5 μL drop of 10 mM sodium azide (diluted in M9 buffer). After all animals are immobilized by sodium azide (~ 5 minutes), take z-stack images of the head of the animals using a 40x magnification lens (Figure 2A). Discard slides after imaging. After acquisition of images, process z-stacks to obtain the maximum projection and use to quantify the number of foci in neurons located on the nerve ring area. Foci are brighter punctuated signals that can be differentiated from the dimmer soluble signal in the background. NOTE: We specifically selected the nerve ring area to quantify rgef-1p::polyQ::YFP aggregates since this is the region where most neurons converge to make synaptic connections. However, in order to measure levels of aggregate formation in motor neurons, rgef-1p::polyQ::YFP aggregates located on the dorsal or ventral nerve cord can be quantified. Plot the progression of YFP foci accumulation from D4, D6, D8 and D10. Do this on an XY graph where X represents days of adulthood and Y represents number of rgef-1p::polyQ::YFP foci (Figure 2B). The number of foci in the experimental condition (e.g., gene downregulation or overexpression) is compared to control animals. Statistical analysis of foci counts for neurons is done in the same manner as for muscle polyQ foci; see steps 4.1.4 and the associated notes. Measuring body bends as a surrogate measure of polyglutamine proteotoxicity in neurons. NOTE: The proteotoxic stress induced from the progressive aggregate accumulation of neuronal polyQ is determined by looking at motor neuron defects through a thrashing assay. Quantify the number of body bends in a period of 30 seconds while suspended in M9 physiological buffer (Supplemental File 1). On Day 2 of adulthood, pick 10 synchronized animals from the plate and place on a 10 μL drop of M9 buffer on a microscope slide. Repeat this step at least four times to get a sample of 40 or more animals. Video record the movement of the 10 animals placed on the microscope slide with 10 μL of M9 buffer for a period of 30 s on a stereomicroscope with a video-capable camera. Repeat this step 4 times for a total sample number of 40. Zoom and position should be adjusted such that all the animals are visible in the frame for the full 30 seconds. Once all the videos with the animals to be analyzed are recorded, play the video and score the body bends of each animal. One body bend is defined as when the vulva of the animal goes from one side to the opposite and all the way back to the starting position. NOTE: We find wild type animals typically have 49 ± 0.79 body bends in 30 seconds. Plot the number of body bends for each animal in a column graph where each dot represents the number of body bends in 30 s (Y axis) with the different conditions tested on the X axis. The number of body bends of unc-54p::polyQ::YFP animals is compared to control animals (Figure 2C). Perform statistical analysis between the groups independently for each trial; if the assay is repeated at multiple time points, analyze the data independently for each time point. When considering only two conditions, perform an independent-sample t-test. When considering more than two conditions at once, first perform an omnibus one-way ANOVA analysis, including the data for all the conditions at that time trial/time point. If the omnibus ANOVA yields a significant p-value (i.e., p < 0.005), perform a post-hoc analysis with pairwise independent sample t-tests to determine the specific conditions between which a significant difference in body bend count was detected.

Representative Results

In C. elegans, the polyglutamine repeat model has been instrumental for the identification of genes that regulate the proteostatic network. For instance, we previously showed that the homeodomain interacting protein kinase (hpk-1), a transcriptional cofactor, influences proteostasis during aging by regulating expression of autophagy and molecular chaperones31. We found that loss of hpk-1, either by RNAi silencing or in hpk-1(pk1393) null mutant animals, increase…

Discussion

Aging is characterized by a gradual decline in proteostasis. Proteostasis is maintained by a complex system, the proteostatic network, for the coordinated, dynamic, stress-responsive control of protein folding, degradation, and translation. Why proteostasis fails in the course of aging is poorly understood, but a decaying epigenome, declining inducibility of stress responses, and loss of compensatory crosstalk all coincide with this breakdown. In C. elegans, the transcriptional inducibility of multiple forms of …

Ujawnienia

The authors have nothing to disclose.

Acknowledgements

We would like to thank past and present members of the Samuelson laboratory for their assistance in the refinement of this method and/or discussion that aided the development of this manuscript. Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Numbers RF1AG062593 and R21AG064519. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Materials

24 Well Culture Plates Greiner Bio-One #662102
2 mL 96-well plates Greiner Bio-One #780286
600 µL 96-well plates Greiner Bio-One #786261
96-pin plate replicator Nunc 250520
Air-permeable plate seal VWR 60941-086
bacteriological agar Affymetrix/USB 10906
bacto-peptone VWR 90000-368
C. elegans RNAi clone library in HT115 bacteria- Ahringer Source Bioscience C. elegans RNAi Collection (Ahringer) See also Kamath et. al, Nature 2003.
C. elegans RNAi clone library in HT115 bacteria- Vidal Source Bioscience C. elegans ORF-RNAi Resource (Vidal) See also Rual et. al, Genome Research 2004. This library is also available from Dharmacon.
FuDR (5-Fluoro-2'-deoxyuridine) Alfa Aesar L16497
Glass microscope cover slips VWR 48404-455
Glass microscope slides VWR 160004-422
IPTG (isopropyl beta-D-1-thigalactopyranoside) Gold Bio 12481C100
Retangular non-treated single-well plate, 128x86mm Thermo-Fisher 242811
Sodium Azide, CAS #26628-22-8 Sigma-Aldrich S2002
Zeiss Axio Imager M2m microscope with AxioVision v4.8.2.0 software Zeiss unknown
Zeiss StemiSV11 M2 Bio Quad microscope Zeiss unknown

Odniesienia

  1. Wolff, S., Weissman, J. S., Dillin, A. Differential scales of protein quality control. Cell. 157 (1), 52-64 (2014).
  2. Labbadia, J., Morimoto, R. I. The biology of proteostasis in aging and disease. Annual Review of Biochemistry. 84, 435-464 (2015).
  3. Powers, E. T., Morimoto, R. I., Dillin, A., Kelly, J. W., Balch, W. E. Biological and chemical approaches to diseases of proteostasis deficiency. Annual Review of Biochemistry. 78, 959-991 (2009).
  4. Brehme, M., et al. A chaperome subnetwork safeguards proteostasis in aging and neurodegenerative disease. Cell Reports. 9 (3), 1135-1150 (2014).
  5. Sala, A. J., Bott, L. C., Morimoto, R. I. Shaping proteostasis at the cellular, tissue, and organismal level. Journal of Cell Biology. 216 (5), 1231-1241 (2017).
  6. Braak, H., Braak, E., Strothjohann, M. Abnormally phosphorylated tau protein related to the formation of neurofibrillary tangles and neuropil threads in the cerebral cortex of sheep and goat. Neuroscience Letters. 171 (1-2), 1-4 (1994).
  7. Poirier, M. A., Jiang, H., Ross, C. A. A structure-based analysis of huntingtin mutant polyglutamine aggregation and toxicity: evidence for a compact beta-sheet structure. Human Molecular Genetics. 14 (6), 765-774 (2005).
  8. Vilchez, D., Saez, I., Dillin, A. The role of protein clearance mechanisms in organismal ageing and age-related diseases. Nature Communications. 5, 5659 (2014).
  9. Eftekharzadeh, B., Hyman, B. T., Wegmann, S. Structural studies on the mechanism of protein aggregation in age related neurodegenerative diseases. Mechanisms of Ageing and Development. 156, 1-13 (2016).
  10. Pokrishevsky, E., Grad, L. I., Cashman, N. R. TDP-43 or FUS-induced misfolded human wild-type SOD1 can propagate intercellularly in a prion-like fashion. Scientific Reports. 6, 22155 (2016).
  11. Mukherjee, A., Morales-Scheihing, D., Butler, P. C., Soto, C. Type 2 diabetes as a protein misfolding disease. Trends in Molecular Medicine. 21 (7), 439-449 (2015).
  12. Sikkink, L. A., Ramirez-Alvarado, M. Biochemical and aggregation analysis of Bence Jones proteins from different light chain diseases. Amyloid. 15 (1), 29-39 (2008).
  13. Qu, B. H., Strickland, E., Thomas, P. J. Cystic fibrosis: a disease of altered protein folding. Journal of Bioenergetics and Biomembranes. 29 (5), 483-490 (1997).
  14. Qu, B. H., Strickland, E. H., Thomas, P. J. Localization and suppression of a kinetic defect in cystic fibrosis transmembrane conductance regulator folding. Journal of Biological Chemistry. 272 (25), 15739-15744 (1997).
  15. Brignull, H. R., Moore, F. E., Tang, S. J., Morimoto, R. I. Polyglutamine proteins at the pathogenic threshold display neuron-specific aggregation in a pan-neuronal Caenorhabditis elegans model. Journal of Neuroscience. 26 (29), 7597-7606 (2006).
  16. Gidalevitz, T., Ben-Zvi, A., Ho, K. H., Brignull, H. R., Morimoto, R. I. Progressive disruption of cellular protein folding in models of polyglutamine diseases. Science. 311 (5766), 1471-1474 (2006).
  17. Morimoto, R. I. Stress, aging, and neurodegenerative disease. New England Journal of Medicine. 355 (21), 2254-2255 (2006).
  18. Morimoto, R. I. Proteotoxic stress and inducible chaperone networks in neurodegenerative disease and aging. Genes & Development. 22 (11), 1427-1438 (2008).
  19. Walker, F. O. Huntington’s disease. Lancet. 369 (9557), 218-228 (2007).
  20. Kamath, R. S., Martinez-Campos, M., Zipperlen, P., Fraser, A. G., Ahringer, J. Effectiveness of specific RNA-mediated interference through ingested double-stranded RNA in Caenorhabditis elegans. Genome Biology. 2 (1), 0002 (2001).
  21. Karady, I., et al. Using Caenorhabditis elegans as a model system to study protein homeostasis in a multicellular organism. Journal of Visualized Experiments. (82), e50840 (2013).
  22. Porta-de-la-Riva, M., Fontrodona, L., Villanueva, A., Ceron, J. Basic Caenorhabditis elegans methods: synchronization and observation. Journal of Visualized Experiments. (64), e4019 (2012).
  23. Cornwell, A. B., Llop, J. R., Salzman, P., Thakar, J., Samuelson, A. V. The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan. Journal of Visualized Experiments. (136), e57819 (2018).
  24. Angeli, S., et al. A DNA synthesis inhibitor is protective against proteotoxic stressors via modulation of fertility pathways in Caenorhabditis elegans. Aging (Albany NY). 5 (10), 759-769 (2013).
  25. Feldman, N., Kosolapov, L., Ben-Zvi, A. Fluorodeoxyuridine improves Caenorhabditis elegans proteostasis independent of reproduction onset. PLoS One. 9 (1), 85964 (2014).
  26. Byerly, L., Cassada, R. C., Russell, R. L. The life cycle of the nematode Caenorhabditis elegans. I. Wild-type growth and reproduction. Biologia Rozwoju. 51 (1), 23-33 (1976).
  27. Schemper, M. Cox Analysis of Survival Data with Non-Proportional Hazard Functions. Journal of the Royal Statistical Society. Series D (The Statistician). 41 (4), 455-465 (1992).
  28. Royston, P., Parmar, M. K. The use of restricted mean survival time to estimate the treatment effect in randomized clinical trials when the proportional hazards assumption is in doubt. Statistics in Medicine. 30 (19), 2409-2421 (2011).
  29. Campbell, I. Chi-squared and Fisher-Irwin tests of two-by-two tables with small sample recommendations. Statistics in Medicine. 26 (19), 3661-3675 (2007).
  30. Busing, F. M., Weaver, B., Dubois, S. 2 x 2 Tables: a note on Campbell’s recommendation. Statistics in Medicine. 35 (8), 1354-1358 (2016).
  31. Das, R., et al. The homeodomain-interacting protein kinase HPK-1 preserves protein homeostasis and longevity through master regulatory control of the HSF-1 chaperone network and TORC1-restricted autophagy in Caenorhabditis elegans. PLoS Genetics. 13 (10), 1007038 (2017).
  32. Garcia, S. M., Casanueva, M. O., Silva, M. C., Amaral, M. D., Morimoto, R. I. Neuronal signaling modulates protein homeostasis in Caenorhabditis elegans post-synaptic muscle cells. Genes & Development. 21 (22), 3006-3016 (2007).
  33. Morley, J. F., Brignull, H. R., Weyers, J. J., Morimoto, R. I. The threshold for polyglutamine-expansion protein aggregation and cellular toxicity is dynamic and influenced by aging in Caenorhabditis elegans. Proceedings of the National Academy of Sciences of the United States of America. 99 (16), 10417-10422 (2002).
  34. Labbadia, J., Morimoto, R. I. Repression of the Heat Shock Response Is a Programmed Event at the Onset of Reproduction. Molecular Cell. 59 (4), 639-650 (2015).
  35. Shemesh, N., Shai, N., Ben-Zvi, A. Germline stem cell arrest inhibits the collapse of somatic proteostasis early in Caenorhabditis elegans adulthood. Aging Cell. 12 (5), 814-822 (2013).
  36. Ben-Zvi, A., Miller, E. A., Morimoto, R. I. Collapse of proteostasis represents an early molecular event in Caenorhabditis elegans aging. Proceedings of the National Academy of Sciences of the United States of America. 106 (35), 14914-14919 (2009).
  37. Walther, D. M., et al. Widespread Proteome Remodeling and Aggregation in Aging C. elegans. Cell. 161 (4), 919-932 (2015).
  38. Cohen, E., Bieschke, J., Perciavalle, R. M., Kelly, J. W., Dillin, A. Opposing activities protect against age-onset proteotoxicity. Science. 313 (5793), 1604-1610 (2006).
  39. Silva, M. C., et al. A genetic screening strategy identifies novel regulators of the proteostasis network. PLoS Genetics. 7 (12), 1002438 (2011).
  40. Zhang, L., Ward, J. D., Cheng, Z., Dernburg, A. F. The auxin-inducible degradation (AID) system enables versatile conditional protein depletion in C. elegans. Development. 142 (24), 4374-4384 (2015).
  41. Hansen, M., Hsu, A. L., Dillin, A., Kenyon, C. New genes tied to endocrine, metabolic, and dietary regulation of lifespan from a Caenorhabditis elegans genomic RNAi screen. PLoS Genetics. 1 (1), 119-128 (2005).
  42. Nollen, E. A., et al. Genome-wide RNA interference screen identifies previously undescribed regulators of polyglutamine aggregation. Proceedings of the National Academy of Sciences of the United States of America. 101 (17), 6403-6408 (2004).
  43. Samuelson, A. V., Carr, C. E., Ruvkun, G. Gene activities that mediate increased life span of C. elegans insulin-like signaling mutants. Genes & Development. 21 (22), 2976-2994 (2007).
  44. Johnson, D. W., et al. The Caenorhabditis elegans Myc-Mondo/Mad complexes integrate diverse longevity signals. PLoS Genetics. 10 (4), 1004278 (2014).
  45. Wang, Z., Sherwood, D. R. Dissection of genetic pathways in C. elegans. Methods in Cell Biology. 106, 113-157 (2011).
  46. Jorgensen, E. M., Mango, S. E. The art and design of genetic screens: caenorhabditis elegans. Nature Reviews Genetics. 3 (5), 356-369 (2002).

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Lazaro-Pena, M. I., Cornwell, A. B., Samuelson, A. V. Quantifying Tissue-Specific Proteostatic Decline in Caenorhabditis elegans. J. Vis. Exp. (175), e61100, doi:10.3791/61100 (2021).

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