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During aging, the cellular response to unfolded proteins is believed to decline, resulting in diminished proteostasis. In model organisms, such as Caenorhabditis elegans, proteostatic decline with age has been linked to proteome solubility shifts and the onset of protein aggregation. However, this correlation has not been extensively characterized in aging mammals. To uncover age-dependent changes in the insoluble portion of a mammalian proteome, we analyzed the detergent-insoluble fraction of mouse brain tissue by mass spectrometry. We identified a group of 171 proteins, including the small heat shock protein a-crystallin, that become enriched in the detergent-insoluble fraction obtained from old mice. To enhance our ability to detect features associated with proteins in that fraction, we complemented our data with a meta-analysis of studies reporting the detergent-insoluble proteins in various mouse models of aging and neurodegeneration. Strikingly, insoluble proteins from young and old mice are distinct in several features in our study and across the collected literature data. In younger mice, proteins are more likely to be disordered, part of membraneless organelles, and involved in RNA binding. These traits become less prominent with age, as an increased number of structured proteins enter the pellet fraction. This analysis suggests that age-related changes to proteome organization lead a group of proteins with specific features to become detergent-insoluble. Importantly, these features are not consistent with those associated with proteins driving membraneless organelle formation. We see no evidence in our system of a general increase of condensate proteins in the detergent-insoluble fraction with age. [ABSTRACT FROM AUTHOR]

Summary The comprehensive analysis of the proteome and its modulation by post-translational modification (PTM) is increasingly used in biological and biomedical studies. As a result, proteomics data analysis is ever more carried out by scientists with limited expertise in this type of data. While excellent software solutions for comprehensive and rigorous analysis of quantitative proteomic data exist, most are complex and not well suited for non-proteomics scientists. Integrative analysis of multi-level proteomics data on protein and diverse PTMs, like phosphorylation or proteolytic processing, remains particularly challenging and inaccessible to most biologists. To fill this void, we developed SQuAPP, an R-Shiny web-based analysis pipeline for the quantitative analysis of proteomic data. SQuAPP uses a streamlined workflow model to guide expert and novice users through quality control, data pre-processing, statistical analysis and visualization steps. Processing the protein, peptide and PTM datasets in parallel and their quantitative integration enable rapid identification of protein-level-independent modulation of protein modifications and intuitive interpretation of dynamic dependencies between different protein modifications. Availability and implementation SQuAPP is available at http://squapp.langelab.org/. The source code and local setup instructions can be accessed from https://github.com/LangeLab/SQuAPP. [ABSTRACT FROM AUTHOR]

Secreted and membrane tethered matrix metalloproteinases (MMPs) are key homeostatic proteases regulating the extracellular signaling and structural matrix environment of cells and tissues. For drug targeting of proteases, selectivity for individual molecules is highly desired and can be met by high yield active site specificity profiling. Using the high throughput Proteomic Identification of protease Cleavage Sites (PICS) method to simultaneously profile both the prime and non-prime sides of the cleavage sites of nine human MMPs, we identified more than 4300 cleavages from P6 to P6′ in biologically diverse human peptide libraries. MMP specificity and kinetic efficiency were mainly guided by aliphatic and aromatic residues in P1′ (with a ~ 32–93% preference for leucine depending on the MMP), and basic and small residues in P2′ and P3′, respectively. A wide differential preference for the hallmark P3 proline was found between MMPs ranging from 15 to 46%, yet when combined in the same peptide with the universally preferred P1′ leucine, an unexpected negative cooperativity emerged. This was not observed in previous studies, probably due to the paucity of approaches that profile both the prime and non-prime sides together, and the masking of subsite cooperativity effects by global heat maps and iceLogos. These caveats make it critical to check for these biologically highly important effects by fixing all 20 amino acids one-by-one in the respective subsites and thorough assessing of the inferred specificity logo changes. Indeed an analysis of bona fide MEROPS physiological substrate cleavage data revealed that of the 37 natural substrates with either a P3-Pro or a P1′-Leu only 5 shared both features, confirming the PICS data. Upon probing with several new quenched-fluorescent peptides, rationally designed on our specificity data, the negative cooperativity was explained by reduced non-prime side flexibility constraining accommodation of the rigidifying P3 proline with leucine locked in S1′. Similar negative cooperativity between P3 proline and the novel preference for asparagine in P1 cements our conclusion that non-prime side flexibility greatly impacts MMP binding affinity and cleavage efficiency. Thus, unexpected sequence cooperativity consequences were revealed by PICS that uniquely encompasses both the non-prime and prime sides flanking the proteomic-pinpointed scissile bond. [ABSTRACT FROM AUTHOR]