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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 β-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.

Nanomaterial contamination in the environment poses severe threats to public health and wellness. Understanding interactions between nanoparticles and biomembranes is pivotal to understanding the physiological effects of nanomaterials. The prevailing understanding is that a protein corona forms around nanoparticles upon their entering biological systems. The effect of the protein corona on the membrane–nanoparticle interaction has not been comprehensively investigated. Here, we report a systematic study to better understand the effects of the protein corona on nanoparticle–biomembrane interactions with both plasma membranes (293T cell line) and biomimetic membranes. Giant plasma membrane vesicles (GPMVs) and giant unilamellar vesicles (GUVs) fabricated from organ lipid extracts (brain, heart, and liver) served as biomimetic models in our study. Reduced charged-nanoparticle adhesion to both plasma and biomimetic membranes with the presence of the protein corona suggests that the protein corona interferes with the electrostatic interaction between nanoparticles and biomembranes. These similar trends of nanoparticle adhesion among the membranes indicated that model membranes can capture this electrostatic interaction with similar responses as plasma membranes. However, the membrane integrity subsequent to the interaction was different between the two systems, indicating the limitations of model membranes in recreating the complexity and dynamics of plasma membranes. As the first systematic study correlating nanoparticle interactions with cell membranes, isolated cell membranes, and synthetic vesicles from natural lipid extracts, we demonstrated that biomimetic membranes can serve as excellent analogues to cell membranes in providing fundamental insights regarding the electrostatic interaction between nanoparticles and biomembranes.

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 due to the lack of robust, well-characterized techniques for methyl peptide enrichment. Here, to better investigate protein methylation, we optimized and compared two methods for methyl peptide enrichment: immunoaffinity purification (IAP) and high pH strong cation exchange (SCX). Comparison of these methods revealed that they are largely orthogonal for monomethyl arginine (MMA), suggesting that the usage of both techniques is required to provide a global view of protein methylation. Using both IAP and SCX, we investigated changes in protein methylation downstream of protein arginine methyltransferase 1 (PRMT1) and quantified ∼1,000 methylation sites on 407 proteins. Of these methylation sites, PRMT1 knockdown resulted in significant changes to 97 arginine methylation sites on 59 proteins. In contrast, zero lysine methylation sites were significantly changed upon PRMT1 knockdown. In PRMT1 knockdown cells, 84 MMA sites were either significantly downregulated or upregulated. PRMT1 knockdown also induced significant changes in both asymmetric dimethyl arginine (ADMA) and symmetric dimethyl arginine (SDMA), suggesting that loss of PRMT1 activity allows scavenging of PRMT1 substrates by other PRMTs. Using neutral loss fragmentation ions unique to ADMA and SDMA, we annotated dimethylarginines as either ADMA or SDMA. Through integrative analysis of methyl forms, we identified 12 high confidence PRMT1 substrates, 43 putative PRMT1 substrates, and 17 methylation sites that are scavenged by other non-PRMT1 arginine methyltransferases in the absence of PRMT1 activity. 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.

Background Disrupted in schizophrenia 1 (DISC1) has been implicated in a number of psychiatric diseases along with neurodevelopmental phenotypes such as the proliferation and differentiation of neural progenitor cells. While there has been significant effort directed toward understanding the function of DISC1 through the determination of its protein-protein interactions within an in vitro setting, endogenous interactions involving DISC1 within a cell type–specific setting relevant to neural development remain unclear. Methods Using CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9) genome engineering technology, we inserted an endogenous 3X-FLAG tag at the C-terminus of the canonical DISC1 gene in human induced pluripotent stem cells (iPSCs). We further differentiated these cells and used affinity purification to determine protein-protein interactions involving DISC1 in iPSC-derived neural progenitor cells and astrocytes. Results We were able to determine 151 novel cell type–specific proteins present in DISC1 endogenous interactomes. The DISC1 interactomes can be clustered into several subcomplexes that suggest novel DISC1 cell-specific functions. In addition, the DISC1 interactome in iPSC-derived neural progenitor cells associates in a connected network containing proteins found to harbor de novo mutations in patients affected by schizophrenia and contains a subset of novel interactions that are known to harbor syndromic mutations in neurodevelopmental disorders. Conclusions Endogenous DISC1 interactomes within iPSC-derived human neural progenitor cells and astrocytes are able to provide context to DISC1 function in a cell type–specific setting relevant to neural development and enables the integration of psychiatric disease risk factors within a set of defined molecular functions.

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.

Protein arginine methylation regulates diverse biological processes including signaling, metabolism, splicing, and transcription. Despite its important biological roles, arginine methylation 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 (HCD) cell increases the generation of the characteristic NL 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 (SCX) and immunoaffinity purification (IAP), we demonstrate that the optimal NCE increases improves NL-based ADMA and SDMA annotation and methyl 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.

SummarySynGAP-α1 is a splice variant of the neurodevelopmental disorder risk gene, SYNGAP1/Syngap1. α1 encodes the C-terminal PDZ binding motif (PBM) that promotes liquid-liquid phase separation, a candidate process for postsynaptic density organization within excitatory synapses. However, it remains unknown how the endogenous SynGAP PBM regulates synapse properties and related cognitive functions. We found that a major PBM function in mice is to limit the mobility of SynGAP-α1 in response to NMDA receptor activation. Genetic disruption of the PBM increased SynGAP-α1 mobility to levels consistent with other non-PBM-containing C-terminal isoforms. This resulted in a lowering of the threshold for NMDA receptor-dependent signaling required for plasticity, leading to aberrant strengthening of excitatory synapses in spontaneously active neurons. PBM-deficient animals also exhibited a lower seizure threshold, disrupted LTP, and impaired cognition. Thus, the PBM enables isoform-specific SynGAP gating of NMDA receptor function, a mechanism linking synaptic signaling dynamics to network excitability and cognition.