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Biology

Using Caenorhabditis elegans to Screen for Tissue-Specific Chaperone Interactions

doi: 10.3791/61140 Published: June 7, 2020
Shiran Dror1, Tomer D. Meidan1, Ido Karady1, Anat Ben-Zvi1

Abstract

Correct folding and assembly of proteins and protein complexes are essential for cellular function. Cells employ quality control pathways that correct, sequester or eliminate damaged proteins to maintain a healthy proteome, thus ensuring cellular proteostasis and preventing further protein damage. Because of redundant functions within the proteostasis network, screening for detectable phenotypes using knockdown or mutations in chaperone-encoding genes in the multicellular organism Caenorhabditis elegans results in the detection of minor or no phenotypes in most cases. We have developed a targeted screening strategy to identify chaperones required for a specific function and thus bridge the gap between phenotype and function. Specifically, we monitor novel chaperone interactions using RNAi synthetic interaction screens, knocking-down chaperone expression, one chaperone at a time, in animals carrying a mutation in a chaperone-encoding gene or over-expressing a chaperone of interest. By disrupting two chaperones that individually present no gross phenotype, we can identify chaperones that aggravate or expose a specific phenotype when both perturbed. We demonstrate that this approach can identify specific sets of chaperones that function together to modulate the folding of a protein or protein complexes associated with a given phenotype.

Introduction

Cells cope with protein damage by employing quality control machineries that repair, sequester or remove any damaged proteins1,2. Folding and assembly of protein complexes are supported by molecular chaperones, a diverse group of highly conserved proteins that can repair or sequester damaged proteins3,4,5,6,7. The removal of damaged proteins is mediated by the ubiquitin-proteasome system (UPS)8 or by the autophagy machinery9 in collaboration with chaperones10,11,12. Protein homeostasis (proteostasis) is, therefore, maintained by quality control networks composed of folding and degradation machineries3,13. However, understanding the interactions between the various components of the proteostasis network in vivo is a major challenge. While protein-protein interaction screens contribute important information on physical interactions and chaperone complexes14,15, understanding the organization and compensatory mechanisms within tissue-specific chaperone networks in vivo is lacking.

Genetic interactions are often used as a powerful tool to examine relationship between pairs of genes that are involved in common or compensatory biological pathways16,17,18. Such relationships can be measured by combining pairs of mutations and quantifying the impact of a mutation in one gene on the phenotypic severity caused by a mutation in the second gene16. While most such combinations do not show any effect in terms of phenotype, some genetic interactions can either aggravate or alleviate the severity of the measured phenotype. Aggravating mutations are observed when the phenotype of the double deletion mutant is more severe than the expected phenotype seen upon combining the single deletion mutants, implying that the two genes function in parallel pathways, together affecting a given function. In contrast, alleviating mutations are observed when the phenotype of the double deletion mutant is less severe than the phenotype seen with the single deletion mutants, implying that the two genes act together as a complex or participate in the same pathway16,18. Accordingly, diverse phenotypes that can be quantified, including broad phenotypes, such as lethality, growth rates and brood size, as well as specific phenotypes, such as transcriptional reporters, have been used to identify genetic interactions. For example, Jonikas et al. relied on an ER stress reporter to examine interactions of the Saccharomyces cerevisiae ER unfolded protein response proteostasis network using pairwise gene deletion analyses19.

Genetic interaction screens involve systematically crossing pairwise deletion mutations to generate a comprehensive set of double mutants20. However, in animal models, and specifically in C. elegans, this large-scale approach is not feasible. Instead, mutant strains can be tested for their genetic interaction patterns by down-regulating gene expression using RNA interference (RNAi)21. C. elegans is a powerful system for screens based on RNAi22,23. In C. elegans, double-stranded RNA (dsRNA) delivery is achieved by bacterial feeding, leading to the spread of dsRNA molecules to numerous tissues. In this manner, the introduced dsRNA molecules impact the animal via a rapid and simple procedure21. A genetic interaction screen using RNAi can, therefore, reveal the impact of down-regulating a set of genes or most C. elegans coding genes using RNAi libraries24. In such a screen, hits that impact the behavior of the mutant of interest but not the wild type strain are potential modifiers of the phenotype being monitored25. Here, we apply a combination of mutations and RNAi screening to systematically map tissue-specific chaperone interactions in C. elegans.

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Protocol

1. Preparation of nematode growth media plates for RNAi

  1. To a 1 L bottle, add 3 g of NaCl, 2.5 g of Bacto-Peptone, 17 g of agar and distilled water up to 1 L and autoclave.
  2. Cool bottle to 55 °C.
  3. Add 25 mL of 1 M KH2PO4, pH 6.0, 1 mL of 1 M CaCl2, 1 mL of 1 M MgSO4, and 1 mL of cholesterol solution (Table 1) to make nematode growth media (NGM).
  4. Add 1 mL of ampicillin (100 mg/mL) and 0.5 mL of 1 M IPTG (Table 1) to make NGM-RNAi solution.
    NOTE: Commonly used HT115(DE3) E. coli bacteria contain an IPTG-inducible T7 DNA polymerase used for expressing the dsRNA-encoding plasmids. These plasmids also encode for ampicillin resistance.
  5. Mix the warm solution by swirling the bottle.
  6. In the hood or using sterile procedures, pour the NGM solution into plates or using a peristaltic pump, dispense the solution into plates. Use 6-well, 12-well, 40 mm or 60 mm plates for this screen. Agar should fill about 2/3 of the plate depth.
  7. Let the plates dry overnight on the bench at room temperature, keeping the plates covered. NGM plates for RNAi can be stored at 4 °C for up to a month.

2. Growing RNAi bacteria and seeding the plates

  1. In the hood or using sterile procedures, add 1 mL of ampicillin (100 mg/mL) and 2.5 mL of tetracycline (5 mg/mL) (Table 1) to a pre-autoclaved 1 L of LB solution and mix.
    NOTE: Commonly used HT115(DE3) E. coli bacteria are tetracycline-resistant.
  2. In the hood or using sterile procedures, add 600 µL of LB solution to each well in 2 mL-deep 96-well sterile plates. It is best to use a multichannel pipet for dispensing the media.
  3. Using sterile procedures, inoculate wells with HT115(DE3) E. coli bacteria transformed with a dsRNA-encoding plasmid targeting a gene of interest or an empty plasmid, as a control. Cover the plates and incubate at 37 °C overnight. Libraries that consist of bacterial clones expressing dsRNA, corresponding to ~94% of predicted C. elegans genes were previously constructed22,23 and are commercially available. The chaperone library used here was constructed by Dr. Richard Morimoto laboratory26.
  4. Using sterile procedures, seed 75, 150 or 250 µL of bacteria onto the 12-well, 40 mm and 6-well or 60 mm NGM RNAi plates, respectively. Clearly mark the name of the target gene on the plate. Bacteria should cover 30-50% of the agar surface and should not touch the edges of the plate.
  5. Allow plates to dry for at least 2 days on the bench at room temperature, keeping the plates covered.
    NOTE: Plates can be incubated at 37 °C overnight. Make sure the inner wells are dry before using or storing the plates. For all long-term purposes (i.e., drying or storage) keep the plates in the dark. Dried, seeded plates can be stored at 4 °C for up to a month.

3. Non-stressful synchronization of embryos

  1. Use a worm pick to move about 100 eggs from an unsynchronized worm plate to a newly seeded NGM plate.
  2. Cultivate animals for 5 days at 15 °C, 3.5 days at 20 °C or 2.5 days at 25 °C. Animals should reach the first day of egg laying.
    NOTE: Worms are commonly cultivated at 20 °C. However, different chaperone mutant strains may require specific cultivation temperatures. For example, many temperature-sensitive strains are cultivated at 15 °C but shifted to 25 °C to expose their phenotype.
  3. Add 1 mL of M9 buffer (Table 1) slowly and away from the bacterial lawn. Rotate the plate so that the buffer completely covers the plate. Then tilt it to one side and remove the liquid from the plate and wash the animals off the plate.
    NOTE: When using temperature-sensitive animals or chaperone mutants, it is best to maintain the buffers used in the protocol at the animals’ cultivation temperature.
  4. Repeat step 3.3 three times or until all the animals are washed off the plate.
  5. Using a standard plastic tip, cut a square of agar from the washed plate where eggs are concentrated and place the piece of agar onto a newly seeded NGM plate.
    NOTE: ~200 eggs are required to produce enough egg-laying animals; too many animals consume the bacteria too quickly. Low food levels can impact proteostasis27.
  6. Cultivate the animals for 5 days at 15 °C, 3.5 days at 20 °C or 2.5 days at 25 °C. At this point, the plates should be covered with synchronized eggs.
    NOTE: Animals can be shifted to a new plate for a short duration for a more stringent synchronization. However, it is important to only use adults at the early stages of egg-laying as animals can retain eggs in their uterus impacting synchronization.
  7. Add 1 mL of M9 buffer slowly and away from the bacterial lawn.
  8. Rotate the plate so that the buffer completely covers the plate. Then tilt it to one side and remove the liquid from the plate and wash the animals off the plate.
  9. Repeat step 3.7 three times or until all animals are washed off the plate.
  10. Add 1 mL of M9 buffer and use a cell scraper to release the eggs from the plate.
  11. Collect the M9 buffer containing the eggs from the plates.
  12. Centrifuge the M9 buffer containing the eggs at 3,000 x g for 2 min.
  13. Remove the supernatant and add M9 buffer to reach a volume of 1 mL.
  14. Resuspend the eggs to disrupt any chunks of eggs and bacteria.
  15. Repeat the washing procedure described in steps 3.11-3.13 five times. The egg pellet should appear white. If it is still yellow/brown, repeat the wash until a white pellet is attained.
    NOTE: Bacteria that remain on the eggs can contaminate the dsRNA-expressing bacteria.
  16. Remove most of the supernatant, leaving about 200 µL. Synchronized eggs can be used for RNAi screens.

4. Common phenotypic assays

  1. Cultivation of animals during experiments
    1. Place a drop of ~30 eggs close to the bacterial lawn in each RNAi-seeded plate. For reference, also place ~30 eggs on plates seeded with empty vector-containing (L4440) bacteria.
    2. Cultivate age-synchronized animals on NGM RNAi-seeded plates. The duration of the experiment will depend on the stage at which the animals are to be monitored and the temperature of cultivation. Adjust the cultivation temperature when using temperature-sensitive mutant animals. Adjust the cultivation duration when using developmentally delayed mutant animals.
      NOTE: While timing can vary, once animals reach adulthood, egg laying (and the resulting rapid food consumption), as well as age-dependent proteostsis collapse28, could impact the results. It is thus recommended to score animals before the onset of egg laying (day 1 of adulthood). Wild type animals reach this stage after 4.5 days at 15 °C, 3 days at 20 °C or 2 days at 25 °C.
    3. The number of repeats used will depend on the size of the gene set examined. For the chaperone library (97 genes), repeat experiments at least four times. The size of the population depends on the assay used. In the behavioral assays discussed here, score >15 animals per experimental condition in each repeat. Data and statistical analyses also strongly depend on the type of assay used. Data in the assays discussed here can be presented as means ± SEM.
    4. Compare the RNAi- and empty vector control-treated animals as independent populations. P values can be calculated using one-way or two-way ANOVA, depending on the changes examined, namely aggravating or alleviating alone or both. When examining a single RNAi treatment vs. control, P values can be calculated using one-way or two-way Mann-Whitney rank sum test. Other than statistical significance, consider a threshold for hits based on the degree of impact on the phenotype.
  2. Developmental arrest/delay
    1. Cultivate age-synchronized animals as in step 4.1 until animals grown on empty vector-containing control bacteria reach adulthood but before egg laying starts.
    2. Monitor animals using a stereomicroscope and count the number of larvae and adults to score the percent of developmentally delayed animals. For reference, compare to mutant animals grown on empty vector-containing control bacteria. hsp-1 or hsp-90 RNAi treatment results in developmental arrest of wild type animals and can be used as a positive control.
    3. To score the percent of developmentally delayed animals over time, repeat step 4.2.2.
      NOTE: If there are egg-laying adults on the plate, transfer the developmentally delayed animals to a new NGM-RNAi plate labeled for the same target gene to avoid confusion with progeny.
  3. Sterility or egg laying defects
    1. Cultivate age-synchronized animals as in step 4.1 until animals grown on empty vector-control bacteria begin to lay eggs.
    2. Monitor animals using a stereomicroscope and score the percent of animals with no visible eggs in their uterus. For reference, compare to mutant animals grown on empty vector-control bacteria.
    3. Alternately, monitor animals using a stereomicroscope and score the percent of animals with a uterus full of eggs, defined as EGg Laying defective (Egl-d) phenotype29.
  4. Embryonic lethality
    1. Cultivate age-synchronized animals as in step 4.1 until the animals begin to lay eggs.
    2. Transfer ~100 eggs to an empty plate. Spread the eggs in rows to simplify counting.
    3. Score the percent of unhatched eggs on the plate after 24-48 hours. For reference, compare to eggs of animals treated with empty vector-control bacteria.
  5. Paralysis assay
    1. For day 1 adults, cultivate age-synchronized animals as in step 4.1 until animals grown on empty vector-control bacteria reach adulthood but before egg laying starts.
    2. Draw a line on the back of a regular NGM agar plate using a fine marker.
    3. Place 5-10 animals on the marked line.
    4. Set a timer and wait for 10 min.
    5. Score the percent of animals remaining on the line as paralyzed worms. For reference, compare to mutant animals grown on empty vector-control bacteria. Wild type animals treated with unc-45 RNAi show severe paralysis phenotype and can be used as a positive control.
      NOTE: This assay highlights animals showing medium to severe paralysis. Such animals usually lie straight on the plate, rather than presenting the common curved shape. Moreover, a patch cleared of bacteria is visible around the heads of paralyzed worms.
  6. Thrashing assay
    1. Cultivate age-synchronized animals as in step 4.1 until animals grown on empty vector-control bacteria reach adulthood but before egg laying starts.
    2. Pipet 100 µL of M9 buffer at the animals’ cultivation temperature into a 96-well plate.
    3. Place ~15 worms, one per well, into the M9 buffer-containing wells.
    4. Let the animals adjust for 5 min.
    5. Examine each animal under the stereomicroscope, start a timer counting down 15 s, and count the number of body bends each animal performs in that timespan. The values counted can be normalized to body bends per min. For reference, compare to mutant animals grown on empty vector-control bacteria.
      NOTE: This motility assay is very sensitive and can detect very mild differences between treatments. However, motility in liquid and motility on agar can differ.

5. Validation of protein knockdown

  1. Place 250-300 synchronized eggs onto a 60 mm NGM-RNAi plate seeded with the relevant dsRNA-expressing or empty vector-containing (L4440) bacteria.
    NOTE: RNAi knockdown could result in aberrant accumulation of embryos, in a lack of embryos or in developmental arrest that could impact gene expression. This should be considered when determining the age of the animals to be examined.
  2. For day 1 adults, cultivate animals for 4.5 days at 15 °C, 3 days at 20 °C or 2 days at 25 °C.
  3. Pick and transfer a total of 200 young adult animals into the cap of a 1.5 mL tube fill with 200 µL of PBS-T.
    NOTE: When using temperature-sensitive animals or chaperone mutants, it is best to maintain the buffers used in the protocol at the animals’ cultivation temperature.
  4. Close the cap carefully and centrifuge at 1,000 x g for 1 min.
  5. Add 800 µL of PBS-T (Table 1) and centrifuge at 1,000 x g for 1 min.
  6. Carefully remove the top 900 µL.
  7. Repeat steps 5.4-5.6 three times.
  8. Remove 900 µL, leaving 100 µL of solution containing the 200 worms.
  9. Add 25 µL of 5x sample buffer (Table 1).
  10. Heat the samples for 10 min at 92°C while shaking at 1000 rpm. Samples can then be frozen and kept at -20 °C.
  11. Load 20 µL of each sample and run on an SDS-PAGE gel.
  12. Perform western blot analysis using appropriate antibodies to determine the relative stability of the protein.
  13. Determine the intensity of the bands using densitometric software, such as the freely available ImageJ gel module. Normalize all values to those measured in the control sample(s).
    NOTE: The aim of RNAi knockdown in our screens is to lower protein levels of a specific chaperone/co-chaperone. Thus, the best way to assess the efficiency of the RNAi knockdown is by western blot analysis. This requires specific antibodies. Alternately, qPCR can be used to quantify mRNA levels.

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Representative Results

Using temperature-sensitive mutations in UNC-45 to screen for aggravating or alleviating interactions under permissive or restrictive conditions, respectively
Muscle assembly and maintenance offer an effective system to study tissue-specific chaperone interactions. The functional unit of contractile muscles, the sarcomere, presents a crystalline-like arrangement of structural and regulatory proteins. The stability of the motor protein myosin and its incorporation into the thick filaments of contractile muscle sarcomeres depends on cooperation of chaperones and UPS components30. An example of one such chaperone is the conserved and specialized myosin chaperone UNC-45 that is mainly expressed in body wall muscle31,32,33,34,35. Mutations in UNC-45 have been shown to induce myosin disorganization and severe motility defects in C. elegans31,36. UNC-45 tandem modules assemble into a multi-site docking platform37 that enforces collaboration between UNC-45, HSP-90 and HSP-1 and likely other chaperones and co-chaperones in myosin filament assembly25,36,37,38. To confirm known UNC-45 interactions and identify novel genetic interactions in muscle proteostasis, we established a strategy using C. elegans temperature-sensitive unc-45 mutations as a sensitized genetic background for tissue-specific chaperone interaction screening19,25.

Single amino acid substitutions in C. elegans UNC-45 (L822F and E781K, corresponding to the e286 and m94 alleles, respectively; unc-45(ts)) are responsible for temperature-dependent motility defects and myosin disorganization phenotypes when affected animals are grown under restrictive conditions (>22 °C). In contrast, these unc-45(ts) mutants show no movement or myosin organization defects at the permissive temperature (15 °C)31. In the proposed approach, age-synchronized unc-45(e286) animals at the first larval stage (L1) were depleted of different molecular chaperones by RNAi (97 genes) and then monitored for motility defects under permissive conditions (15 °C) (Figure 1). We confirmed the known interaction of UNC-45 and HSP-90 proteins in our genetic interactions screen and identified three hsp-90 co-chaperones, sti-1, ahsa-1, and daf-41, as specifically causing a synthetic movement defect in unc-45(ts) mutant animals but not in wild-type animals25. We went on to examine whether sti-1-, ahsa-1- or daf-41-associated synthetic phenotypes were caused by myosin disorganization by monitoring the subcellular arrangement of myosin heavy chain A (MYO-3), using established immuno-staining techniques39. Whereas treatment of wild type animals with sti-1, ahsa-1 or daf-41 RNAi did not affect myofilament organization, depletion of these genes in unc-45(e286) mutant animals resulted in complete disruption of sarcomeric structures and MYO-3 mislocalization, even under permissive conditions (15 °C). This effect was comparable to what was seen with unc-45(e286) single mutants grown at the restrictive temperature (25 °C)25. These results were confirmed using another unc-45(ts)-allele, namely unc-45(m94) mutant animals25.

To identify chaperones that destabilize UNC-45, we next screened for chaperones that improved the motility of unc-45(286) animals at 25 °C, relying on gene knockdown by RNAi. While unc-45(e286) mutant animals displayed severe movement defects at 25 °C, the motility of animals treated with RNAi against genes encoding four of the 97 chaperones screened was significantly improved. Here too, the results were confirmed using unc-45(m94) mutant animals. Thus, the use of temperature-sensitive mutations allows for establishing both aggravating and alleviating screens, depending on the temperature at which the screen is conducted.

Using tissue-specific over-expression of a chaperone to screen for aggravating interactions
We next utilized tissue-specific over-expression of a single chaperone as a mild perturbation of the muscle chaperone network for screening purposes. Specifically, we utilized animals over-expressing wild type dnj-24, encoding the C. elegans homolog of the Hsp40 protein DNAJB6 in the C. elegans body wall muscle (DNJ-24M). As above, L1 DNJ-24M animals were treated with RNAi for different chaperones and monitored for motility defects (20 °C) (Figure 1). While DNJ-24M animals showed no notable motility defects, three genes (of the 48 chaperone-encoding genes examined; 6%), namely hsp-1, rme-8, and dnj-8, specifically affected the motility of DNJ-24M-expressing animals but not wild type animals. It is of note that testing the specificity of the hits using animals over-expressing a different chaperone, namely HSP-90, in muscle (HSP90M), showed no effect on HSP90M motility upon hsp-1, rme-8, or dnj-8 RNAi treatment40. Taken together, the screening platform, employing mild perturbation to the chaperone network, such as the expression of metastable mutant proteins or tissue-specific over-expression, resulted in a highly specific hit rate (normally ~5%).

Using tissue-specific RNAi to screen for tissue-specific genetic interactions
Tissue-specific RNAi-sensitive strains allow for tissue-specific knockdown of genes while still using bacterial feeding for dsRNA delivery. These strains are mutant for the RDE-1 argonaute protein, a major component in the RNAi pathway required for effective gene silencing21. However, expressing wild type RDE-1 under the control of a tissue-specific promoter led to effective tissue-specific gene knockdown41,42. This tool thus allows for genetic interaction screens without using tissue-specific chaperones, such as UNC-45 or DNAJ-24M. For example, hsp-6 (mortalin) knockdown in wild type animals during development resulted in a strong developmental arrest (96±1% of the RNAi-treated animals). At the same time, hsp-6 knockdown in a strain expressing wild type RDE-1 in muscle did not cause developmental arrest, whereas expressing wild type RDE-1 in intestinal cells resulted in a strong developmental arrest phenotype (90±3%; Figure 2). Thus, HSP-6 function in intestinal cells is required for normal development. A mutation in hsp-6(mg585) that causes a mild growth delay can, therefore, be used to screen for aggravating or alleviating chaperone interactions by crossing that mutated gene into an intestinal-specific RNAi strain and screening the chaperone RNAi library.

Monitoring age-dependent changes in the folding environment using genetic interactions
Animals show an age-dependent decline in motility that is associated with sarcomeric disorganization43,44,45. Changes in protein folding capacity coincide with altered regulation and composition of the cellular proteostasis machinery28, including altered levels of UNC-45, CHN-1, and UFD-2, proteins of the muscle quality control machinery46. In agreement, myosin folding and degradation are affected by alterations in proteostatic capacity at the transition to adulthood47. We, therefore, asked whether such changes could impact chaperone interactions. For example, we monitored the impact of sti-1, ahsa-1 and daf-41 knockdown on motility over time. We found that although sti-1-, ahsa-1- and daf-41-RNAi treated animals showed reduced motility during larval development, motility strongly declined in unc-45(ts) adult worms. Moreover, MYO-3 organization in unc-45(ts) mutant animals treated with sti-1, ahsa-1 or daf-41 RNAi was similar to that of wild type worms at the fourth larval stage (L4), although the mutants exhibited disrupted sarcomeres after the animals reached adulthood (Figure 3). In contrast, both unc-45(ts) mutant animals treated with an empty vector control and wild type animals remained unaffected (Figure 3). Thus, proteostasis dynamics as a function of age or environmental conditions27,45,46,48,49 could critically impact chaperone interactions.

Figure 1
Figure 1: Setup of RNAi synthetic interaction screens using C. elegans carrying a mutation in a gene encoding a chaperone of interest. (A) Schematic representation of the basic setup of targeted chaperone interaction screens. (B) Hit validation requires confirmation of the genetic interaction using another chaperone mutant, as well as validating the specify of RNAi knockdown. (C-D) Simple readouts, such as motility defects, can be quantified to determine aggravating or alleviating interactions, using paralysis or thrashing assays, respectively. Please click here to view a larger version of this figure.

Figure 2
Figure 2: Tissue-specific RNAi of the mitochondrial chaperone hsp-6 can be used to examine genetic interactions in one tissue. Wild type intestine- and muscle-specific RNAi strains were treated with hsp-6 RNAi and (A) developmental delay was scored or (B) images were taken on the first day of adulthood. Data are mean ± SEM, N=6. Scale bar is 1 mm. Please click here to view a larger version of this figure.

Figure 3
Figure 3: Age-dependent effects of RNAi. (A) Motility with age. Wild type or unc-45(e286) embryos were placed on sti-1, ahsa-1 or daf-41 RNAi-seeded plates at 15 °C and scored for motility using a thrashing assay at each developmental stage, L1-L4, young adult and day 1 of adulthood. Data are mean ± SEM, N=15. (B) Confocal images of body wall muscle. Animals were treated as in A and fixed at the L4, young adult and day 1 of adulthood stages and immuno-stained with anti-MYO-3 antibodies. Scale bar is 10 µm. Please click here to view a larger version of this figure.

Solution Preparation instructions Storage
1 M CaCl2 (1 L) Add 147.01 g CaCl2·2H2O Store at RT
Add dH2O to 1 L
Autoclave or filter (0.22 µm)
1 M KH2PO4, pH 6.0 (1 L) Add 136.09 g KH2PO4 Store at RT
Add 800 mL dH2O
Mix using magnetic stirrer until dissolved
Titrate pH using KOH
Add dH2O to 1 L
Autoclave or filter (0.22 µm)
1 M MgSO4 (1 L) Add 248.58 g MgSO4·7H2O Store at RT
Add dH2O to 1 L
Autoclave or filter (0.22 µm)
Cholesterol solution (50 mL) Add 250 mg cholesterol to a 50 mL Falcon tube Store at -20 °C
Completely dissolve in 40 mL ethanol
Add ethanol to 50 mL
1 M IPTG (50 mL) Add 11.9 g IPTG (isopropyl-β-D-thiogalactopyranoside) to a 50 mL Falcon tube Store in the dark at -20 °C
Completely dissolve in 40 mL dH2O
Add dH2O to 50 mL
Filter (0.22 µm), aliquot 1mL tubes
Ampicillin stock (50 mL) Add 5 g ampicillin to a 50 mL Falcon tube Store at -20 °C
Completely dissolve in 40 mL dH2O
Add dH2O to 50 mL
Filter (0.22 µm), distribute 1 mL aliquot into Eppendorf tubes
Tetracycline stock (50 mL) Add 250 mg tetracycline to a 50 mL Falcon tube Store at -20 °C
Completely dissolve in 40 mL ethanol
Add ethanol to 50 mL
Aliquot 1 mL tubes
M9 buffer (1 L) Add 5.8 g Na2HPO4·7H2O Store at RT
Add 3 g KH2PO4
Add 5 g NaCl
Add 0.25 g MgSO4·7H2O
Add dH2O to 1 L
Filter (0.22 µm)
1X PBS-T (pH 7.4) ( 1 L) Add 8 g of NaCl Store at RT
Add 200 mg of KCl
Add 1.44 g Na2HPO4·7H2O
Add 240 mg KH2PO4
Completely dissolve in 800 mL dH2O
Titrate pH using KOH tp pH 7.4
Add 500 µL Tween-20
Add dH2O to 1 L
5x sample buffer Add 6.8 mL dH2O Store at -20 °C
Add 2 mL 0.5M Tris pH 6.8
Add 3.2 mL Glycerol
Add 1.6 mL 20% SDS
Add 0.8 mL ß-mercaptoethanol
1% bromophenol blue

Table 1: Solution Recipes

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Discussion

An integrated picture of the proteostasis network reflecting how it is organized and functions in different metazoan cells and tissues remains lacking. To address this shortcoming, specific information on the interactions of various components of this network, such as molecular chaperones, in specific tissues during the course of development and aging is required. Here, we showed how the use of tissue-specific perturbations enabled us to examine the chaperone network in a given tissue. To explore tissue-specific chaperone genetic interactions, three different approaches were considered. In the first approach, UNC-45, a chaperone that is highly expressed in muscle cells, was used to screen for chaperone interactions via feeding-RNAi25. While the use of a specialized chaperone allows for discerning tissue-specificity, it can only report on that highly focused sub-network to which it contributes. Note that most C. elegans neurons are resistant to feeding-based RNAi delivery50 and thus using this approach to identify genetic interactions in neuronal cells requires crossing the mutant chaperone examined with an RNAi-enhanced strain51. In a second approach, a tissue-specific promoter was used to drive over-expression of a chaperone in muscle and thus specifically affect the muscle folding environment40. However, over-expressing a single chaperone could be generally beneficial to the folding environment and thus mask disruption caused by the two chaperones together. The third approach relied on tissue-specific RNAi knockdown to examine chaperone interactions in a given a tissue41. One advantage of this approach is that it allows for targeting neuronal cells that are resistant to RNAi delivery via feeding42. Still, this approach requires the use of a mild mutant (although not specialized), as well as that this mutant be crossed into a rde-1 null mutant carrying a tissue-specific rde-1 rescue gene. Importantly, these approaches can be combined so as to potentially modulate chaperone function in a single tissue or even a single cell.

The quality control machinery can impact the function of many gene products by perturbing proteostasis. This is a major challenge when using genetic interactions to explore the quality control network18. For example, chronic expression of aggregation-prone proteins or proteostasis collapse in aging resulted in phenotypic aggravation of many unrelated metastable proteins in C. elegans and yeast45,52,53. Moreover, clathrin-mediated endocytosis in mammalian cells was inhibited upon functional sequestration of Hsc70 to protein aggregates. Yet, it was shown that endocytosis could be rescued by Hsc70 over-expression, while aggregation could not54,55. Likewise, a genetic screen in Drosophila designed to uncover regulators of the heat shock response identified a missense mutation in flight muscle actin that constitutively activated the heat shock response56. Taken together, perturbation of the proteostasis network can expose metastable proteins or induce stress that can impact result specificity. Nonetheless, analyzing genetic interactions can yield highly specific and functional insight. For example, epistatic analyses of yeast genes required for folding in the endoplasmic reticulum identified specific genetic interactions between molecular chaperones that were subsequently validated19. Likewise, an aggravating screen for chaperones that enhance the toxicity of two aggregation-prone models (as measured by motility) identified a specific subset of 18 chaperones, orthologs of which impacted Huntingtin aggregation in human cells26. Here, we showed that various perturbations of the proteostasis network can uncover specific and functional chaperone interactions.

The main advantage of using RNAi feeding-based genetic interaction screens is the relative simplicity of the method. Even employing a general behavioral output, such as motility, can reveal novel genetic interactions (Figure 3). However, variability and partial effects of expression knockdown can limit the robustness and specificity of the results57. Moreover, genetic interactions are not indicative of physical interactions and the relationship between two genes could thus be indirect. Exploring the nature of the interactions and discarding non-specific interactions can be time consuming57,58,59. This is a concern that needs to be addressed in the screen setup and validation. For example, using null alleles in genetic screening allows for determining whether these genes function in the same or distinct pathways in a given biological process. However, using partial loss of gene function, hypomorphic alleles, such as temperature-sensitive alleles, or RNAi-dependent down-regulation of expression, results in residual activities that can yield aggravating or alleviating phenotypes, regardless of whether the genes act in the same or in parallel pathways59. Thus, the nature of any interaction requires further analysis. However, using hypomorphic alleles and RNAi could identify a broad range of interactors, including genes in the same protein complex or pathway or in a redundant pathway59. While this larger scope of possible interactions can yield more hits in a genetic screen, it can also lead to non-specific interactions, such as, for example, the non-specific exposure of temperature-sensitive alleles in proteostasis collapse45,53.

Hit validation and non-specific interactions can be examined in several ways. The number of hits should be low. For example, down-regulation of chaperone expression in an unc-45 mutant background resulted in a small percentage of hits (4%), with most chaperone gene down-regulation not showing any effect on motility. A similar rate was observed when DNJ-24M was over-expressed (6%). As noted above, a screen for chaperone interactions with aggregation-prone proteins identified 18 chaperones of 219 screened (8%).

Several mutant alleles, over-expression lines or disease models should be used. The use of different mutant alleles that have different impacts on chaperone function, as well as different strains with different genetic backgrounds, can support the specificity of any screen hits. Alternatively, using mutation or over-expression of a different chaperone that does not lead to similar perturbation can serve as a negative control. For example, both unc-45(e286) and unc-45(m94) showed aggravating behavior when sti-1, ahsa-1 or daf-41 were down-regulated. Moreover, a similar interaction was observed when animals carrying the ahsa-1(ok3501) deletion mutant were treated with hsp-90 RNAi25.

The identity of the chaperone hits and their known interactions should be examined. For example, chaperones identified in a unc-45 aggravating screen are a highly specific set of chaperones required for the HSP-90 ATPase cycle, including those encoding a client recruiter (STI-1), a remodeling co-chaperone (AHSA-1), and a client maturation co-chaperone (DAF-41). In fact, this set of co-chaperones forms a complete HSP-90 folding cycle60. Likewise, a DNJ-24M screen identified HSP-1, the main chaperone partner of Hsp40s40.

Changes in interactions over the lifespan of the animal should also be examined. For example, chaperones identified in unc-45 aggravating screen strongly impacted motility and myosin organization in adulthood but had a milder effect during development. This could be due to changes in the proteostasis network in adulthood28 or to changes in myosin folding requirements between myo-fiber folding and maintenance.

Use complementary biochemical approaches to directly examine interactions between the proteins, as well as their localization in the cell. For example, the HSP-90 co-chaperones, STI-1, AHSA-1 and DAF-41, are localized to the sarcomere where they interact with myosin25.

C. elegans is a well-established metazoan model for monitoring quality control. It is often used to monitor cellular and organismal proteostasis using a variable toolkit of cell biology, biochemical and genetic approaches. Here, we employed genetic screening approaches and available tools57,58,59, such as a mutant bank, available RNAi libraries22,23 and tissue-specific RNAi strains41,42, to monitor chaperone interactions in a living animal during development and aging. The use of simple behavioral assays, such as motility, simplify the screen of many possible gene pairs to explore novel genetic interactions. This can then serve as a platform to further explore chaperone localization and physical interactions using biochemical tools to mechanistically study their potential interactions in vivo and in vitro. The protocol described here has been successfully used to identify novel chaperone interactions in C. elegans body wall muscle25,40.

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Disclosures

The authors have nothing to disclose.

Acknowledgments

We thank the Caenorhabditis Genetics Center, funded by the NIH National Center for Research Resources (NCRR), for some of the nematode strains. Monoclonal antibodies developed by H.F. Epstein were obtained from the Developmental Studies Hybridoma Bank developed under the auspices of the NICHD and maintained by the Department of Biology, University of Iowa. This research was supported by a grant from the Israel Science Foundation (grant No. 278/18) and by a grant from the Israel Ministry of Science & Technology, and the Ministry of Foreign Affairs and International Cooperation, General Directorate for Country Promotion, Italian Republic (grant No. 3-14337). We thank members of the Ben-Zvi laboratory for help in preparing this manuscript.

Materials

Name Company Catalog Number Comments
12-well-plates SPL BA3D16B
40 mm plates Greiner Bio-one 627160
60 mm plates Greiner Bio-one 628102
6-well plates Thermo Scientific 140675
96 well 2 mL 128.0/85mm Greiner Bio-one 780278
Agar Formedium AGA03
Ampicillin Formedium 69-52-3
bromophenol blue Sigma BO126-25G
CaCl2 Merck 1.02382.0500
Camera Qimaging q30548
Cholesterol Amresco 0433-250G
Confocal Leica DM5500
Filter (0.22 µm) Sigma SCGPUO2RE
Fluorescent stereomicroscope Leica MZ165FC
Glycerol Frutarom 2355519000024
IPTG Formedium 367-93-1
KCl Merck 104936
KH2PO4 Merck 1.04873.1000
KOH Bio-Lab 001649029100
MgSO4 Fisher 22189-08-8 Gift from the Morimoto laboratory
Myosin MHC A (MYO-3) antibody Hybridoma Bank 5-6
Na2HPO4·7H2O Sigma s-0751
NaCl Bio-Lab 001903029100
Peptone Merck 61930705001730
Plate pouring pump Integra does it p920
RNAi Chaperone library NA NA
SDS VWR Life Science 0837-500
ß-mercaptoethanol Bio world 41300000-1
stereomicroscope Leica MZ6
Tetracycline Duchefa Biochemie 64-75-5
Tris Bio-Lab 002009239100
Tween-20 Fisher BP337-500

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References

  1. Gomez-Pastor, R., Burchfiel, E. T., Thiele, D. J. Regulation of heat shock transcription factors and their roles in physiology and disease. Nature Reviews Molecular Cell Biology. 19, (1), 4-19 (2018).
  2. Dubnikov, T., Ben-Gedalya, T., Cohen, E. Protein quality control in health and disease. Cold Spring Harbor Perspectives in Biology. 9, (3), (2017).
  3. Bar-Lavan, Y., Shemesh, N., Ben-Zvi, A. Chaperone families and interactions in metazoa. Essays in Biochemistry. 60, (2), 237-253 (2016).
  4. Schopf, F. H., Biebl, M. M., Buchner, J. The HSP90 chaperone machinery. Nature Reviews Molecular Cell Biology. 18, (6), 345-360 (2017).
  5. Carra, S., et al. The growing world of small heat shock proteins: from structure to functions. Cell Stress Chaperones. 22, (4), 601-611 (2017).
  6. Rosenzweig, R., Nillegoda, N. B., Mayer, M. P., Bukau, B. The Hsp70 chaperone network. Nature Reviews Molecular Cell Biology. (2019).
  7. Gestaut, D., Limatola, A., Joachimiak, L., Frydman, J. The ATP-powered gymnastics of TRiC/CCT: an asymmetric protein folding machine with a symmetric origin story. Current Opinion in Structural Biology. 55, 50-58 (2019).
  8. Bett, J. S. Proteostasis regulation by the ubiquitin system. Essays in Biochemistry. 60, (2), 143-151 (2016).
  9. Jackson, M. P., Hewitt, E. W. Cellular proteostasis: degradation of misfolded proteins by lysosomes. Essays in Biochemistry. 60, (2), 173-180 (2016).
  10. Kettern, N., Dreiseidler, M., Tawo, R., Hohfeld, J. Chaperone-assisted degradation: multiple paths to destruction. Biological Chemistry. 391, (5), 481-489 (2010).
  11. Cuervo, A. M., Wong, E. Chaperone-mediated autophagy: roles in disease and aging. Cell Research. 24, (1), 92-104 (2014).
  12. Kevei, E., Pokrzywa, W., Hoppe, T. Repair or destruction-an intimate liaison between ubiquitin ligases and molecular chaperones in proteostasis. FEBS Letters. 591, (17), 2616-2635 (2017).
  13. O'Brien, D., van Oosten-Hawle, P. Regulation of cell-non-autonomous proteostasis in metazoans. Essays in Biochemistry. 60, (2), 133-142 (2016).
  14. Taipale, M., et al. Quantitative analysis of HSP90-client interactions reveals principles of substrate recognition. Cell. 150, (5), 987-1001 (2012).
  15. Taipale, M., et al. A quantitative chaperone interaction network reveals the architecture of cellular protein homeostasis pathways. Cell. 158, (2), 434-448 (2014).
  16. Baryshnikova, A., Costanzo, M., Myers, C. L., Andrews, B., Boone, C. Genetic interaction networks: toward an understanding of heritability. Annual Review of Genomics and Human Genetics. 14, 111-133 (2013).
  17. Costanzo, M., et al. Global Genetic Networks and the Genotype-to-Phenotype Relationship. Cell. 177, (1), 85-100 (2019).
  18. Domingo, J., Baeza-Centurion, P., Lehner, B. The Causes and Consequences of Genetic Interactions (Epistasis). Annual Review of Genomics and Human Genetics. 20, 433-460 (2019).
  19. Jonikas, M. C., et al. Comprehensive characterization of genes required for protein folding in the endoplasmic reticulum. Science. 323, (5922), 1693-1697 (2009).
  20. Schuldiner, M., et al. Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell. 123, (3), 507-519 (2005).
  21. Billi, A. C., Fischer, S. E., Kim, J. K. Endogenous RNAi pathways in C. elegans. WormBook. 1-49 (2014).
  22. Kamath, R. S., et al. Systematic functional analysis of the Caenorhabditis elegans genome using RNAi. Nature. 421, (6920), 231-237 (2003).
  23. Rual, J. F., et al. Toward improving Caenorhabditis elegans phenome mapping with an ORFeome-based RNAi library. Genome Research. 14, (10), 2162-2168 (2004).
  24. Lehner, B., Crombie, C., Tischler, J., Fortunato, A., Fraser, A. G. Systematic mapping of genetic interactions in Caenorhabditis elegans identifies common modifiers of diverse signaling pathways. Nature Genetics. 38, (8), 896-903 (2006).
  25. Frumkin, A., et al. Challenging muscle homeostasis uncovers novel chaperone interactions in Caenorhabditis elegans. Frontiers in Molecular Biosciences. 1, 21 (2014).
  26. Brehme, M., et al. A chaperome subnetwork safeguards proteostasis in aging and neurodegenerative disease. Cell Reports. 9, (3), 1135-1150 (2014).
  27. Shpigel, N., Shemesh, N., Kishner, M., Ben-Zvi, A. Dietary restriction and gonadal signaling differentially regulate post-development quality control functions in Caenorhabditis elegans. Aging Cell. 18, (2), 12891 (2019).
  28. Shai, N., Shemesh, N., Ben-Zvi, A. Remodeling of proteostasis upon transition to adulthood is linked to reproduction onset. Current Genomics. 15, (2), 122-129 (2014).
  29. Trent, C., Tsuing, N., Horvitz, H. R. Egg-laying defective mutants of the nematode Caenorhabditis elegans. Genetics. 104, (4), 619-647 (1983).
  30. Pokrzywa, W., Hoppe, T. Chaperoning myosin assembly in muscle formation and aging. Worm. 2, (3), 25644 (2013).
  31. Barral, J. M., Bauer, C. C., Ortiz, I., Epstein, H. F. Unc-45 mutations in Caenorhabditis elegans implicate a CRO1/She4p-like domain in myosin assembly. Journal of Cell Biology. 143, (5), 1215-1225 (1998).
  32. Venolia, L., Ao, W., Kim, S., Kim, C., Pilgrim, D. unc-45 gene of Caenorhabditis elegans encodes a muscle-specific tetratricopeptide repeat-containing protein. Cell Motility and the Cytoskeleton. 42, (3), 163-177 (1999).
  33. Hoppe, T., et al. Regulation of the myosin-directed chaperone UNC-45 by a novel E3/E4-multiubiquitylation complex in C. elegans. Cell. 118, (3), 337-349 (2004).
  34. Etard, C., et al. The UCS factor Steif/Unc-45b interacts with the heat shock protein Hsp90a during myofibrillogenesis. Developmental Biology. 308, (1), 133-143 (2007).
  35. Wohlgemuth, S. L., Crawford, B. D., Pilgrim, D. B. The myosin co-chaperone UNC-45 is required for skeletal and cardiac muscle function in zebrafish. Developmental Biology. 303, (2), 483-492 (2007).
  36. Barral, J. M., Hutagalung, A. H., Brinker, A., Hartl, F. U., Epstein, H. F. Role of the myosin assembly protein UNC-45 as a molecular chaperone for myosin. Science. 295, (5555), 669-671 (2002).
  37. Gazda, L., et al. The myosin chaperone UNC-45 is organized in tandem modules to support myofilament formation in C. elegans. Cell. 152, (1-2), 183-195 (2013).
  38. Gaiser, A. M., Kaiser, C. J., Haslbeck, V., Richter, K. Downregulation of the Hsp90 system causes defects in muscle cells of Caenorhabditis elegans. PLoS One. 6, (9), 25485 (2011).
  39. 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).
  40. Bar-Lavan, Y., et al. A Differentiation Transcription Factor Establishes Muscle-Specific Proteostasis in Caenorhabditis elegans. PLoS Genetics. 12, (12), 1006531 (2016).
  41. Qadota, H., et al. Establishment of a tissue-specific RNAi system in C. elegans. Gene. 400, (1-2), 166-173 (2007).
  42. Firnhaber, C., Hammarlund, M. Neuron-specific feeding RNAi in C. elegans and its use in a screen for essential genes required for GABA neuron function. PLoS Genet. 9, (11), 1003921 (2013).
  43. Fisher, A. L. Of worms and women: sarcopenia and its role in disability and mortality. Journal of the American Geriatrics Society. 52, (7), 1185-1190 (2004).
  44. Herndon, L. A., et al. Stochastic and genetic factors influence tissue-specific decline in ageing C. elegans. Nature. 419, (6909), 808-814 (2002).
  45. 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).
  46. Janiesch, P. C., et al. The ubiquitin-selective chaperone CDC-48/p97 links myosin assembly to human myopathy. Nature Cell Biology. 9, (4), 379-390 (2007).
  47. 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).
  48. Vilchez, D., et al. RPN-6 determines C. elegans longevity under proteotoxic stress conditions. Nature. 489, (7415), 263-268 (2012).
  49. Liu, G., Rogers, J., Murphy, C. T., Rongo, C. EGF signalling activates the ubiquitin proteasome system to modulate C. elegans lifespan. EMBO Journal. 30, (15), 2990-3003 (2011).
  50. Asikainen, S., Vartiainen, S., Lakso, M., Nass, R., Wong, G. Selective sensitivity of Caenorhabditis elegans neurons to RNA interference. Neuroreport. 16, (18), 1995-1999 (2005).
  51. Calixto, A., Chelur, D., Topalidou, I., Chen, X., Chalfie, M. Enhanced neuronal RNAi in C. elegans using SID-1. Nature Methods. 7, (7), 554-559 (2010).
  52. Eremenko, E., Ben-Zvi, A., Morozova-Roche, L. A., Raveh, D. Aggregation of human S100A8 and S100A9 amyloidogenic proteins perturbs proteostasis in a yeast model. PLoS One. 8, (3), 58218 (2013).
  53. 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).
  54. Yu, A., et al. Tau protein aggregates inhibit the protein-folding and vesicular trafficking arms of the cellular proteostasis network. Journal of Biological Chemistry. (2019).
  55. Yu, A., et al. Protein aggregation can inhibit clathrin-mediated endocytosis by chaperone competition. Proceedings of the National Academy of Sciences of the United States of America. 111, (15), 1481-1490 (2014).
  56. Parker-Thornburg, J., Bonner, J. J. Mutations that induce the heat shock response of Drosophila. Cell. 51, (5), 763-772 (1987).
  57. Boutros, M., Ahringer, J. The art and design of genetic screens: RNA interference. Nature Reviews Genetics. 9, (7), 554-566 (2008).
  58. Jorgensen, E. M., Mango, S. E. The art and design of genetic screens: caenorhabditis elegans. Nature Reviews Genetics. 3, (5), 356-369 (2002).
  59. Wang, Z., Sherwood, D. R. Dissection of genetic pathways in C. elegans. Methods in Cell Biology. 106, 113-157 (2011).
  60. Rohl, A., Rohrberg, J., Buchner, J. The chaperone Hsp90: changing partners for demanding clients. Trends in Biochemical Sciences. 38, (5), 253-262 (2013).
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Dror, S., Meidan, T. D., Karady, I., Ben-Zvi, A. Using Caenorhabditis elegans to Screen for Tissue-Specific Chaperone Interactions. J. Vis. Exp. (160), e61140, doi:10.3791/61140 (2020).More

Dror, S., Meidan, T. D., Karady, I., Ben-Zvi, A. Using Caenorhabditis elegans to Screen for Tissue-Specific Chaperone Interactions. J. Vis. Exp. (160), e61140, doi:10.3791/61140 (2020).

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