A naturally occurring variant of SHLP2 is a protective factor in Parkinson's disease.

Mitochondrial DNA single nucleotide polymorphisms (mtSNPs) have been associated with a reduced risk of developing Parkinson's disease (PD), yet the underlying mechanisms remain elusive. In this study, we investigate the functional role of a PD-associated mtSNP that impacts the mitochondrial-derived peptide (MDP) Small Humanin-like Peptide 2 (SHLP2). We identify m.2158 T > C, a mtSNP associated with reduced PD risk, within the small open reading frame encoding SHLP2. This mtSNP results in an alternative form of SHLP2 (lysine 4 replaced with arginine; K4R). Using targeted mass spectrometry, we detect specific tryptic fragments of SHLP2 in neuronal cells and demonstrate its binding to mitochondrial complex 1. Notably, we observe that the K4R variant, associated with reduced PD risk, exhibits increased stability compared to WT SHLP2. Additionally, both WT and K4R SHLP2 show enhanced protection against mitochondrial dysfunction in in vitro experiments and confer protection against a PD-inducing toxin, a mitochondrial complex 1 inhibitor, in a mouse model. This study sheds light on the functional consequences of the m.2158 T > C mtSNP on SHLP2 and provides insights into the potential mechanisms by which this mtSNP may reduce the risk of PD.

The CARM1 transcriptome and arginine methylproteome mediate skeletal muscle integrative biology.

OBJECTIVE: Coactivator-associated arginine methyltransferase 1 (CARM1) catalyzes the methylation of arginine residues on target proteins to regulate critical processes in health and disease. A mechanistic understanding of the role(s) of CARM1 in skeletal muscle biology is only gradually emerging. The purpose of this study was to elucidate the function of CARM1 in regulating the maintenance and plasticity of skeletal muscle. METHODS: We used transcriptomic, methylproteomic, molecular, functional, and integrative physiological approaches to determine the specific impact of CARM1 in muscle homeostasis. RESULTS: Our data defines the occurrence of arginine methylation in skeletal muscle and demonstrates that this mark occurs on par with phosphorylation and ubiquitination. CARM1 skeletal muscle-specific knockout (mKO) mice displayed altered transcriptomic and arginine methylproteomic signatures with molecular and functional outcomes confirming remodeled skeletal muscle contractile and neuromuscular junction characteristics, which presaged decreased exercise tolerance. Moreover, CARM1 regulates AMPK-PGC-1α signalling during acute conditions of activity-induced muscle plasticity. CONCLUSIONS: This study uncovers the broad impact of CARM1 in the maintenance and remodelling of skeletal muscle biology.

Identification of a Proteomic Signature of Senescence in Primary Human Mammary Epithelial Cells.

Senescence is a permanent cell cycle arrest that occurs in response to cellular stress and promotes age-related disease. Because senescence differs greatly depending on cell type and senescence inducer, continued progress in the characterization of senescent cells is needed. Here, we analyzed primary human mammary epithelial cells (HMECs), a model system for aging and cancer, using mass spectrometry-based proteomics. By integrating data from replicative senescence, immortalization by telomerase reactivation, and quiescence, we identified a robust proteomic signature of HMEC senescence consisting of 34 upregulated and 10 downregulated proteins. This approach identified known senescence biomarkers including ß-galactosidase (GLB1) as well as novel senescence biomarkers including catechol O-methyltransferase (COMT), synaptic vesicle membrane protein VAT-1 homolog (VAT1), and plastin-1/3 (PLS1/PLS3). Gene ontology enrichment analysis demonstrated that senescent HMECs upregulated lysosomal proteins and downregulated RNA metabolic processes. In addition, a classification model based on our proteomic signature successfully discriminated proliferating and senescent HMECs at the transcriptional level. Finally, we found that the HMEC senescence signature was positively and negatively correlated with proteomic alterations in HMEC aging and breast cancer, respectively. Taken together, our results demonstrate the power of proteomics to identify cell type-specific signatures of senescence and advance the understanding of senescence in HMECs.

Improved Discrimination of Asymmetric and Symmetric Arginine Dimethylation by Optimization of the Normalized Collision Energy in Liquid Chromatography-Mass Spectrometry Proteomics.

Protein arginine methylation regulates diverse biological processes including signaling, metabolism, splicing, and transcription. Despite its important biological roles, arginine dimethylation remains an understudied post-translational modification. Partly, this is because the two forms of arginine dimethylation, asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA), are isobaric and therefore indistinguishable by traditional mass spectrometry techniques. Thus, there exists a need for methods that can differentiate these two modifications. Recently, it has been shown that the ADMA and SDMA can be distinguished by the characteristic neutral loss (NL) of dimethylamine and methylamine, respectively. However, the utility of this method is limited because the vast majority of dimethylarginine peptides do not generate measurable NL ions. Here, we report that increasing the normalized collision energy (NCE) in a higher-energy collisional dissociation cell increases the generation of the characteristic NLs that distinguish ADMA and SDMA. By analyzing both synthetic and endogenous methyl-peptides, we identify an optimal NCE value that maximizes NL generation and simultaneously improves methyl-peptide identification. Using two orthogonal methyl-peptide enrichment strategies, high pH strong cation-exchange and immunoaffinity purification, we demonstrate that the optimal NCE improves NL-based ADMA and SDMA annotation and dimethyl-peptide identifications by 125% and 17%, respectively, compared to the standard NCE. This simple parameter change will greatly facilitate the identification and annotation of ADMA and SDMA in mass spectrometry-based methyl-proteomics to improve our understanding of how these modifications differentially regulate protein function. All raw data have been deposited in the PRIDE database with accession number PXD017193.

Deep Protein Methylation Profiling by Combined Chemical and Immunoaffinity Approaches Reveals Novel PRMT1 Targets.

Protein methylation has been implicated in many important biological contexts including signaling, metabolism, and transcriptional control. Despite the importance of this post-translational modification, the global analysis of protein methylation by mass spectrometry-based proteomics has not been extensively studied because of the lack of robust, well-characterized techniques for methyl peptide enrichment. Here, to better investigate protein methylation, we compared two methods for methyl peptide enrichment: immunoaffinity purification (IAP) and high pH strong cation exchange (SCX). Using both methods, we identified 1720 methylation sites on 778 proteins. Comparison of these methods revealed that they are largely orthogonal, suggesting that the usage of both techniques is required to provide a global view of protein methylation. Using both IAP and SCX, we then investigated changes in protein methylation downstream of protein arginine methyltransferase 1 (PRMT1). PRMT1 knockdown resulted in significant changes to 127 arginine methylation sites on 78 proteins. In contrast, only a single lysine methylation site was significantly changed upon PRMT1 knockdown. In PRMT1 knockdown cells, we found 114 MMA sites that were either significantly downregulated or upregulated on proteins enriched for mRNA metabolic processes. PRMT1 knockdown also induced significant changes in both asymmetric dimethyl arginine (ADMA) and symmetric dimethyl arginine (SDMA). Using characteristic neutral loss fragmentation ions, we annotated dimethylarginines as either ADMA or SDMA. Through integrative analysis of methyl forms, we identified 18 high confidence PRMT1 substrates and 12 methylation sites that are scavenged by other non-PRMT1 arginine methyltransferases in the absence of PRMT1 activity. We also identified one methylation site, HNRNPA1 R206, which switched from ADMA to SDMA upon PRMT1 knockdown. Taken together, our results suggest that deep protein methylation profiling by mass spectrometry requires orthogonal enrichment techniques to identify novel PRMT1 methylation targets and highlight the dynamic interplay between methyltransferases in mammalian cells.