Retro-proteomics to identify misfolded proteins from the ER and their quality control pathways

Yale University, New Haven CT

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Abstract

Project Summary Protein aggregation is the common defining feature in many age-related neurodegenerative diseases such as Alzheimer's and Parkinson's disease as well as systemic amyloidosis. Protein aggregates do not accumulate in normal healthy cells because of the existence of sophisticated cellular quality control pathways, the activity of which is progressively impaired during aging. While the core components of protein quality control pathways in virtually all cellular organelles have been identified, the fundamental question of how these pathways recognize their specific endogenous misfolded substrates remains elusive. A major bottleneck in addressing this question is that the endogenous misfolded proteins remain unidentified since there are no suitable tools to selectively separate them from the sea of abundant folded proteins. To approach this problem, we propose to develop innovative approaches to identify the endogenous misfolded proteins and their quality control components from the endoplasmic reticulum (ER). The misfolded secretory and membrane proteins in the ER are recognized by multiple ER-associated degradation (ERAD) pathways, which add ubiquitin to them and retrotranslocate them into the cytosol for the proteasomal degradation. These retrotranslocated misfolded proteins can be trapped as full-length proteins in the cytosol upon transiently inhibiting the proteasome. In the Aim 1, we will take advantage of this retrotranslocation process and develop novel retro-proteomic approaches to selectively purify retrotranslocated proteins from the cytosol using either through their ER-specific modifications or their association with the cytosolic chaperone Bag6. The purified proteins will be identified by quantitative mass spectrometry, which we term retro-proteomics. Furthermore, we will use the retro-proteomics to identify, for the first time, ER proteins that are prone to misfolding during oxidative stress, which has been associated with the aging process. In the Aim 2, we describe a highly innovative strategy to combine our retro- proteomics with CRISPR/Cas9 method to identify endogenous misfolded substrates for ER quality control components, particularly for E3 ligases. Our preliminary studies indicate that using this technique we can successfully identify numerous novel substrate candidates for the conserved Hrd1 E3 ligase. We will validate the misfolded proteins and their associated quality control pathways using protein turnover assays and metabolic labeling combined with quantitative mass spectrometry. We believe that the ability to catalog ER misfolded proteins and their quality control pathways will help us to understand how cells selectively recognize various types of misfolded proteins for degradation and why they poorly recognize them during aging. Answers to these questions may help with the development of targeted small molecules to improve protein folding during stress and aging.