A Comprehensive Enumeration of the Human Proteostasis Network. 2. Components of the Autophagy-Lysosome Pathway

Abstract

The condition of having a healthy, functional proteome is known as protein homeostasis, or proteostasis. Establishing and maintaining proteostasis is the province of the proteostasis network, approximately 2,700 components that regulate protein synthesis, folding, localization, and degradation. The proteostasis network is a fundamental entity in biology that is essential for cellular health and has direct relevance to many diseases of protein conformation. However, it is not well defined or annotated, which hinders its functional characterization in health and disease. In this series of manuscripts, we aim to operationally define the human proteostasis network by providing a comprehensive, annotated list of its components. We provided in a previous manuscript a list of chaperones and folding enzymes as well as the components that make up the machineries for protein synthesis, protein trafficking into and out of organelles, and organelle-specific degradation pathways. Here, we provide a curated list of 838 unique high-confidence components of the autophagy-lysosome pathway, one of the two major protein degradation systems in human cells.

Mapping stress-responsive signaling pathways induced by mitochondrial proteostasis perturbations

“…Thus, we wanted to demonstrate that our gene sets similarly show selective UPR activation induced by ER proteostasis perturbations. We monitored the expression of stress pathway target genes in K562 cells CRISPRi-depleted of the 215 enumerated proteins comprising discrete ER proteostasis pathways including ER chaperones/folding enzymes, glycoproteostasis factors, protein degradation pathways, and protein targeting/trafficking pathways ( Proteostasis Consortium et al. , 2022 ).…”

“…Here, we sought to probe the activation of these stress-responsive signaling pathways in K562 cells CRISPRi-depleted of individual mitochondrial proteostasis factors. The mitochondrial proteostasis network comprises 94 chaperones/folding enzymes, proteases, and import factors ( Proteostasis Consortium et al. , 2022 ), 82 of which were included in the published Perturb-seq dataset ( Replogle et al.…”

“…, 2016 ), confirming our ability to identify stress-responsive signaling pathways preferentially activated by organelle-selective proteostasis disruptions. We then used this profiling strategy to monitor activation of stress pathway gene sets in cells CRISPRi-depleted of known mitochondrial proteostasis factors ( Proteostasis Consortium et al. , 2022 ).…”

An mTOR-independent Macroautophagy Activator Ameliorates Tauopathy and Prionopathy Neurodegeneration Phenotypes

“…127 To scrutinize whether the induced nuclear localization of TFEB by CCT020312 in HeLa cells is consistent with its transcriptional activation, we conducted RNA-Seq analysis of the same batch of cells treated with CCT020312 (2.5µM) for 20 h. RNA-Seq analysis revealed that CCT020312 treatment (2.5µM) significantly (adjusted p-value < 0.05) upregulated 1039 genes and downregulated 1177 genes (Supplemental Table 1), including 152 associated with the autophagy-lysosomal pathway (Figure 3C). 128 To discern which genes are specifically modulated by the TFEB transcriptional program, we cross-referenced our findings with TFEB transcriptional program gene sets from previous studies, 125–127,129 identifying 172 genes significantly altered by CCT020312 treatment (Supplemental Table 1, Figures 3C, 3D, S3L). These genes, including lysosomal acid hydrolases and selective autophagy receptors exhibited significant upregulation relative to vehicle-treated samples, establishing a link between CCT020312-induced gene expression changes and autophagy-lysosomal pathway regulation (NEU1: 2.1x DMSO, CTSL: 1.5x DMSO, ASAH1: 1.4x DMSO, LIPA: 1.4x DMSO, CTSD: 1.3x DMSO, CTSF: 1.3x DMSO, SQSTM1: 1.6x DMSO, CALCOCO2: 1.4x DMSO).…”

Functional and multi-omic aging rejuvenation with GLP-1R agonism

“…Pathway enrichment was done with ClusterProfiler (v4.6.2) against the Gene Ontology 91 and KEGG 92 databases, and custom gene sets of functional pathways related to aging [93][94][95][96][97][98][99] . For each tissue, all genes that underwent differential expression analysis were used as the background gene set.…”