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Impact of Folded-State Protein Filaments on the Yeast Proteome

ABSTRACT: The formation of large polymeric structures without protein unfolding and aggregation, such as cytoskeletal and enzyme filaments, is crucial for normal cellular function. We term this type of assembly agglomeration in contrast to protein aggregation caused by protein misfolding. Several agglomeration-associated diseases, such as sickle cell disease, are caused by hemoglobin agglomeration. Nevertheless, it is still unknown whether there is a specific machinery to recognize protein agglomeration and how agglomeration affects cell – is it as harmful as aggregation or relatively neutral? To address this question, we performed shotgun proteomics of wild-type dihedral homomeric proteins and their mutated counterparts prone to aggregation or agglomeration in yeasts. We identified lower expression of both the exogenous construct and YFP in the misfolded variants of all three constructs when compared to their wild type and agglomerate counterparts (Fig. 4A-B, Sup Fig. 9D-E). Surprisingly, they were the only differentially expressed proteins in both 1POK variants and 1M3U variants. On the contrary, in 2VYC there were many differentially expressed proteins between its variants (Fig. 4C-D). In the misfolded variant, we detected the decrease in 2VYC and YFP expression was coupled with an increase in chaperone proteins (HSP104/HSP78/HSP42/SSA4/STI1, Fig 4C, Sup Fig. 10). GO-SLIM analysis showed enrichment in the upregulated genes for four categories; ‘protein-folding’ (P.value < 0.0002), ‘response to heat’ (P.value < 0.0016), ‘response to oxidative stress’ (P.value < 0.0352) and ‘oligosaccharide metabolic process’ (P.value < 0.0445). Looking at the agglomerate, we focused on proteins that are differentially expressed uniquely in the agglomerate mutant but don’t change in the misfolded mutant. We detected several cell wall related proteins that were upregulated (DCW1/GAS1/GAS3/NPP1) [71–73] as well as proteins localized to the bud neck (PAL1/RAX2) [74,75]. We also detected an increase in the prion progenitor RNQ1. In the down regulated proteins, we identified several metabolic enzymes and among them CYS4 which forms filaments [10]. Other down regulated proteins relate to cell polarity and especially actin polarization (CDC42/LST8/PHO85/RHO4) [76–79]. We detected three protein categories that were enriched in the upregulated genes; ‘cell budding’ (P.value < 0.0334), ‘cell wall organization or biogenesis’ (P.value < 0.0396) and ‘chromatin organization’ (P.value < 0.0441). In the downregulated genes three categories were also enriched; ‘carbohydrate metabolic process’ (P.value < 0.00363), ‘generation of precursor metabolites and energy’ (P.value < 0.0154) and ‘monocarboxylic acid metabolic process’ (P.value < 0.0427)

INSTRUMENT(S):

ORGANISM(S): Saccharomyces Cerevisiae (baker's Yeast)

SUBMITTER: Arseniy Lobov

LAB HEAD: Emmanuel Levy

PROVIDER: PXD052597 | Pride | 2025-08-21

REPOSITORIES: Pride

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			Action	DRS
	EL_19152_HFX_DDA_070124.xlsx	Xlsx
	HFX_19152_EL_298-1_DDA_191223-calib.mzID.gz	Mzid
	HFX_19152_EL_298-1_DDA_191223-calib.mzML	Mzml
	HFX_19152_EL_298-1_DDA_191223.raw	Raw
	HFX_19152_EL_298-2_DDA_191223-calib.mzID.gz	Mzid

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Project description:Proctor2007 - Age related decline of proteolysis, ubiquitin-proteome system This is a stochastic model of the ubiquitin-proteasome system for a generic pool of native proteins (NatP), which have a half-life of about 10 hours under normal conditions. It is assumed that these proteins are only degraded after they have lost their native structure due to a damage event. This is represented in the model by the misfolding reaction which depends on the level of reactive oxygen species (ROS) in the cell. Misfolded proteins (MisP) are first bound by an E3 ubiquitin ligase. Ubiquitin (Ub) is activated by E1 (ubiquitin-activating enzyme) and then passed to E2 (ubiquitin-conjugating enzyme). The E2 enzyme then passes the ubiquitin molecule to the E3/MisP complex with the net effect that the misfolded protein is monoubiquitinated and both E2 and E3 are released. Further ubiquitin molecules are added in a step-wise manner. When the chain of ubiquitin molecules is of length 4 or more, the polyubiquitinated misfolded protein may bind to the proteasome. The model also includes de-ubiquitinating enzymes (DUB) which cleave ubiquitin molecules from the chain in a step-wise manner. They work on chains attached to misfolded proteins both unbound and bound to the proteasomes. Misfolded proteins bound to the proteasome may be degraded releasing ubiquitin. Misfolded proteins including ubiquitinated proteins may also aggregate. Aggregates (AggP) may be sequestered (Seq_AggP) which takes them out of harm's way or they may bind to the proteasome (AggP_Proteasome). Proteasomes bound by aggregates are no longer available for protein degradation. Figure 2 and Figure 3 has been simulated using Gillespie2. This model is described in the article: An in silico model of the ubiquitin-proteasome system that incorporates normal homeostasis and age-related decline. Proctor CJ, Tsirigotis M, Gray DA. BMC Syst Biol 2007; 1: 17 Abstract: BACKGROUND: The ubiquitin-proteasome system is responsible for homeostatic degradation of intact protein substrates as well as the elimination of damaged or misfolded proteins that might otherwise aggregate. During ageing there is a decline in proteasome activity and an increase in aggregated proteins. Many neurodegenerative diseases are characterised by the presence of distinctive ubiquitin-positive inclusion bodies in affected regions of the brain. These inclusions consist of insoluble, unfolded, ubiquitinated polypeptides that fail to be targeted and degraded by the proteasome. We are using a systems biology approach to try and determine the primary event in the decline in proteolytic capacity with age and whether there is in fact a vicious cycle of inhibition, with accumulating aggregates further inhibiting proteolysis, prompting accumulation of aggregates and so on. A stochastic model of the ubiquitin-proteasome system has been developed using the Systems Biology Mark-up Language (SBML). Simulations are carried out on the BASIS (Biology of Ageing e-Science Integration and Simulation) system and the model output is compared to experimental data wherein levels of ubiquitin and ubiquitinated substrates are monitored in cultured cells under various conditions. The model can be used to predict the effects of different experimental procedures such as inhibition of the proteasome or shutting down the enzyme cascade responsible for ubiquitin conjugation. RESULTS: The model output shows good agreement with experimental data under a number of different conditions. However, our model predicts that monomeric ubiquitin pools are always depleted under conditions of proteasome inhibition, whereas experimental data show that monomeric pools were depleted in IMR-90 cells but not in ts20 cells, suggesting that cell lines vary in their ability to replenish ubiquitin pools and there is the need to incorporate ubiquitin turnover into the model. Sensitivity analysis of the model revealed which parameters have an important effect on protein turnover and aggregation kinetics. CONCLUSION: We have developed a model of the ubiquitin-proteasome system using an iterative approach of model building and validation against experimental data. Using SBML to encode the model ensures that it can be easily modified and extended as more data become available. Important aspects to be included in subsequent models are details of ubiquitin turnover, models of autophagy, the inclusion of a pool of short-lived proteins and further details of the aggregation process. This model is hosted on BioModels Database and identified by: BIOMD0000000105. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:In preliminary experiments, the absence of anthrose in our genetic Sterne knockout was found to decrease pagA expression in BHI broth containing glucose (Fig 5A and B). This contrasted with the large spike in pagA expression when the Sterne antC mutant is grown in protein rich HIB media which does not contain sugars. When exogenous anthrose was added during growth in BHI broth, expression from PpagA increased in both WT (purple line in Fig 5A) and antC Sterne (purple line in Fig 5B). Many bacteria respond to levels of metabolic intermediates and modulate gene expression accordingly. We hypothesized intracellular or extracellular anthrose levels could impact the vegetative cells through modification of gene expression during vegetative growth. Wildtype B. anthracis Sterne was grown in the presence and absence of exogenously added pure anthrose to avoid any possibility of confounding data in a deletion mutant. Bacteria were harvested at two timepoints post-addition of anthrose, 30 min and 2 h, and compared to diluent only treated cultures (Fig 5C). After 30 min treatment, there were 6 genes significantly upregulated more than two-fold while 17 genes were downregulated (Fig 5D). These genes were mainly involved in generating metabolic intermediates such as pyruvate and trehalose. The most upregulated gene was a putative membrane protein (log2FC=10.98) followed by a gene encoding a GerPF homologue at a log2FC of 10.98. Mutation of GerPF family proteins have been linked to a super-dormant spore phenotype[10]. The gene experiencing the highest downregulation was a putative lipoprotein (log2FC = -20.02). No genes located on pXO1 were detected at 30 min. A subset of differentially transcribed genes from the 30 min timepoint are listed in Fig 5F. After 2 h of anthrose treatment, 52 genes experienced significant up regulation, 18 of which were hypothetical proteins (Fig 5E). Forty-five genes experienced significant down regulation across replicates, 13 of which were hypothetical proteins.

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Impact of Folded-State Protein Filaments on the Yeast Proteome

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