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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.