Molecular & Cellular Proteomics最新文献

O-GlcNAcylation was identified in the 1980s by Torres and Hart and modifies thousands of cellular proteins, yet the regulatory role of O-GlcNAc is still poorly understood compared to the abundance of mechanistic information known for other cycling post-translational modifications like phosphorylation. Many challenges are associated with studying O-GlcNAcylation and are tied to the technical hurdles with analysis by mass spectrometry. Over the years, many research groups have developed important methods to study O-GlcNAcylation revealing its role in the cell, and this perspective aims to review the challenges and innovations around O-GlcNAc research and chronicle the work by Donald F. Hunt and his laboratory, particularly in development of ETD and its application to this field of research.

At the plasma membrane, in response to biotic and abiotic cues, specific ligands initiate the formation of receptor kinase heterodimers, which regulate the activities of plasma membrane proteins and initiate signaling cascades to the nucleus. In this study, we utilized affinity enrichment mass spectrometry to investigate the stimulus-dependent interactomes of LRR receptor kinases in response to their respective ligands, with an emphasis on exploring structural influences and potential cross-talk events at the plasma membrane. BRI1 and SIRK1 were chosen as receptor kinases with distinct coreceptor preference. By using interactome characteristic of domain-swap chimera following a gradient boosting learning algorithm trained on SIRK1 and BRI1 interactomes, we attribute contributions of extracellular domain, transmembrane domain, juxtamembrane domain, and kinase domain of respective ligand-binding receptors to their interaction with their coreceptors and substrates. Our results revealed juxtamembrane domain as major structural element defining the specific substrate recruitment for BRI1 and extracellular domain for SIRK1. Furthermore, the learning algorithm enabled us to predict the phenotypic outcomes of chimeric receptors based on different domain combinations, which was verified by dedicated experiments. As a result, our work reveals a tightly controlled balance of signaling cascade activation dependent on ligand-binding receptors domains and the internal ligand status of the plant. Moreover, our study shows the robust utility of machine learning classification as a quantitative metric for studying dynamic interactomes, dissecting the contribution of specific domains and predicting their phenotypic outcome.

Neutrophils are indispensable for defense against pathogens. Injured tissue-infiltrated neutrophils can establish a niche of chronic inflammation and promote degeneration. Studies investigated transcriptome of single-infiltrated neutrophils which could misinterpret molecular states of these post mitotic cells. However, neutrophil proteome characterization has been challenging due to low harvests from affected tissues. Here, we present a workflow to obtain proteome of 1000 murine and human tissue-infiltrated neutrophils. We generated spectral libraries containing ∼6200 mouse and ∼5300 human proteins from circulating neutrophils. 4800 mouse and 3400 human proteins were recovered from 1000 cells with 10²-10⁸ copies/cell. Neutrophils from stroke-affected mouse brains adapted to the glucose-deprived environment with increased mitochondrial activity and ROS-production, while cells invading inflamed human oral cavities increased phagocytosis and granule release. We provide an extensive protein repository for resting human and mouse neutrophils, identify proteins lost in low input samples, thus enabling the proteomic characterization of limited tissue-infiltrated neutrophils.

Inherited retinal degenerations (IRDs) are a leading cause of blindness among the population of young people in the developed world. Approximately half of IRDs initially manifest as gradual loss of night vision and visual fields, characteristic of retinitis pigmentosa (RP). Due to challenges in genetic testing, and the large heterogeneity of mutations underlying RP, targeted gene therapies are an impractical largescale solution in the foreseeable future. For this reason, identifying key pathophysiological pathways in IRDs that could be targets for mutation-agnostic and disease-modifying therapies (DMTs) is warranted. In this study, we investigated the retinal proteome of three distinct IRD mouse models, in comparison to sex- and age-matched wild-type mice. Specifically, we used the Pde6β^Rd10 (rd10) and Rho^P23H/WT (P23H) mouse models of autosomal recessive and autosomal dominant RP, respectively, as well as the Rpe65^-/- mouse model of Leber's congenital amaurosis type 2 (LCA2). The mice were housed at two distinct institutions and analyzed using LC-MS in three separate facilities/instruments following data-dependent and data-independent acquisition modes. This cross-institutional and multi-methodological approach signifies the reliability and reproducibility of the results. The large-scale profiling of the retinal proteome, coupled with in vivo electroretinography recordings, provided us with a reliable basis for comparing the disease phenotypes and severity. Despite evident inflammation, cellular stress, and downscaled phototransduction observed consistently across all three models, the underlying pathologies of RP and LCA2 displayed many differences, sharing only four general KEGG pathways. The opposite is true for the two RP models in which we identify remarkable convergence in proteomic phenotype even though the mechanism of primary rod death in rd10 and P23H mice is different. Our data highlights the cAMP and cGMP second-messenger signaling pathways as potential targets for therapeutic intervention. The proteomic data is curated and made publicly available, facilitating the discovery of universal therapeutic targets for RP.

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) probes dynamic motions of proteins by monitoring the kinetics of backbone amide deuteration. Dynamic regions exhibit rapid HDX, while rigid segments are more protected. Current data readouts focus on qualitative comparative observations (such as "residues X to Y become more protected after protein exposure to ligand Z"). At present, it is not possible to decode HDX protection patterns in an atomistic fashion. In other words, the exact range of protein motions under a given set of conditions cannot be uncovered, leaving space for speculative interpretations. Amide back exchange is an under-appreciated problem, as the widely used (m-m₀)/(m₁₀₀-m₀) correction method can distort HDX kinetic profiles. Future data analysis strategies require a better fundamental understanding of HDX events, going beyond the classical Linderstrøm-Lang model. Combined with experiments that offer enhanced spatial resolution and suppressed back exchange, it should become possible to uncover the exact range of motions exhibited by a protein under a given set of conditions. Such advances would provide a greatly improved understanding of protein behavior in health and disease.

Understanding the integrated regulation of cellular processes during viral infection is crucial for developing host-targeted approaches. We have previously reported that an optimal in vitro infection by influenza A virus (IAV) requires three components of Cullin 4-RING E3 ubiquitin ligases (CRL4) complexes, namely the DDB1 adaptor and two substrate recognition factors, DCAF11 and DCAF12L1, which mediate non-degradative poly-ubiquitination of the PB2 subunit of the viral polymerase. However, the impact of IAV infection on the CRL4 interactome remains elusive. Here, using Affinity Purification coupled with Mass Spectrometry (AP-MS) approaches, we identified cellular proteins interacting with these CRL4 components in IAV-infected and non-infected contexts. IAV infection induces significant modulations in protein interactions, resulting in a global loss of DDB1 and DCAF11 interactions, and an increase in DCAF12L1-associated proteins. The distinct rewiring of CRL4's associations upon infection impacted cellular proteins involved in protein folding, ubiquitination, translation, splicing, and stress responses. Using a split-nanoluciferase-based assay, we identified direct partners of CRL4 components and via siRNA-mediated silencing validated their role in IAV infection, representing potential substrates or regulators of CRL4 complexes. Our findings unravel the dynamic remodeling of the proteomic landscape of CRL4's E3 ubiquitin ligases during IAV infection, likely involved in shaping a cellular environment conducive to viral replication and offer potential for the exploration of future host-targeted antiviral therapeutic strategies.

Ubiquitin carboxyl-terminal hydrolase 19 (USP19) is a unique deubiquitinase (DUB), characterized by multiple variants generated by alternative splicing. Several variants bear a C-terminal transmembrane domain that anchors them to the endoplasmic reticulum (ER). Other than regulating protein stability by preventing proteasome degradation, USP19 has been reported to rescue substrates from ER-associated protein degradation (ERAD) in a catalytic-independent manner, promote autophagy and address proteins to lysosomal degradation via endosomal microautophagy. USP19 has recently emerged as the protein responsible for the unconventional secretion of misfolded proteins including Parkinson's disease-associated protein α-synuclein. Despite mounting evidence that USP19 plays crucial roles in several biological processes, the underlying mechanisms are unclear due to lack of information on the physiological substrates of USP19. Herein, we used high-resolution quantitative proteomics to analyze changes in the secretome and cell proteome induced by loss of USP19 to identify proteins whose secretion or turnover is regulated by USP19. We found that ablation of USP19 induced significant proteomic alterations both in and out of the cell. Loss of USP19 impaired the release of several lysosomal proteins, including legumain (LGMN) and several cathepsins. In order to understand the underlaying mechanism, we dissected the USP19-regulated secretion of LGMN in several cell types. We found that LGMN was not a DUB substrate of USP19 and that its USP19-dependent release did not require their direct interaction. LGMN secretion occurred by a mechanism that involved the Golgi apparatus, autophagosome formation and lysosome function. This mechanism resembled the recently described "lysosomal exocytosis", by which lysosomal hydrolases are secreted, when ubiquitination of p62 is increased in cells lacking deubiquitinases such as USP15 and USP17. In conclusion, our proteomic characterization of USP19 has identified a collection of proteins in the secretome and within the cell that are regulated by USP19, which link USP19 to secretion of lysosomal proteins, including LGMN.

Ubiquitination is crucial for maintaining protein homeostasis and plays a vital role in diverse biological processes. Ubiquitinome profiling and quantification are of great scientific significance. Artificial ubiquitin-binding domains (UBDs) have been widely employed to capture ubiquitinated proteins. The success of this enrichment relies on recognizing native spatial structures of ubiquitin and ubiquitin chains by UBDs under native conditions. However, the use of native lysis conditions presents significant challenges, including insufficient protein extraction, heightened activity of deubiquitinating enzymes and proteasomes in removing the ubiquitin signal, and purification of a substantial number of contaminant proteins, all of which undermine the robustness and reproducibility of ubiquitinomics. In this study, we introduced a novel approach that combines denatured-refolded ubiquitinated sample preparation (DRUSP) with a tandem hybrid UBD for ubiquitinomic analysis. The samples were effectively extracted using strongly denatured buffers and subsequently refolded using filters. DRUSP yielded a significantly stronger ubiquitin signal, nearly three times greater than that of the Control method. Then, eight types of ubiquitin chains were quickly and accurately restored; therefore, they were recognized and enriched by tandem hybrid UBD with high efficiency and no biases. Compared with the Control method, DRUSP showed extremely high efficiency in enriching ubiquitinated proteins, improving overall ubiquitin signal enrichment by approximately 10-fold. Moreover, when combined with ubiquitin chain-specific UBDs, DRUSP had also been proven to be a versatile approach. This new method significantly enhanced the stability and reproducibility of ubiquitinomics research. Finally, DRUSP was successfully applied to deep ubiquitinome profiling of early mouse liver fibrosis with increased accuracy, revealing novel insights for liver fibrosis research.

The bacillus Calmette-Guérin BCG vaccine (Mycobacterium bovis) is primarily used to prevent tuberculosis (TB) infections but has wide-ranging immunogenic effects. One of its most notable properties is its ability to induce trained immunity, a memory-like response in innate immune cells such as macrophages. Through targeted analyses of well-established histone marks, prior research has shown that these changes are generated through epigenetic modification. Mass spectrometry-based proteomic approaches provide a way to globally profile various aspects of the proteome, providing data to further identify unexplored mechanisms of BCG-mediated immunomodulation. Here we use multi-level proteomics (total, histone, and phospho to identify networks and potential mechanisms that mediate BCG-induced immunomodulation in macrophages. Histone-focused proteomics and total proteomics were performed at the University of Cape Town (data available via ProteomeXchange with identifier PXD051187), while phosphoproteomics data was retrieved from the ProteomeXchange Repository (identifier PXD013171). We identify several epigenetic mechanisms that may drive BCG-induced training phenotypes. Evidence across the proteomics and histone-focused proteomics data set pair 6 epigenetic effectors (NuA4, NuRD, NSL, Sin3A, SIRT2, SIRT6) and their substrates.

Dopaminergic neurons participate in fundamental physiological processes and are the cell type primarily affected in Parkinson's disease. Their analysis is challenging due to the intricate nature of their function, involvement in diverse neurological processes, and heterogeneity and localization in deep brain regions. Consequently, most of the research on the protein dynamics of dopaminergic neurons has been performed in animal cells ex vivo. Here we use iPSC-derived human mid-brain-specific dopaminergic neurons to study general features of their proteome biology and provide datasets for protein turnover and dynamics, including a human axonal translatome. We cover the proteome to a depth of 9409 proteins and use dynamic SILAC to measure the half-life of more than 4300 proteins. We report uniform turnover rates of conserved cytosolic protein complexes such as the proteasome and map the variable rates of turnover of the respiratory chain complexes in these cells. We use differential dynamic SILAC labeling in combination with microfluidic devices to analyze local protein synthesis and transport between axons and soma. We report 105 potentially novel axonal markers and detect translocation of 269 proteins between axons and the soma in the time frame of our analysis (120 h). Importantly, we provide evidence for local synthesis of 154 proteins in the axon and their retrograde transport to the soma, among them several proteins involved in RNA editing such as ADAR1 and the RNA helicase DHX30, involved in the assembly of mitochondrial ribosomes. Our study provides a workflow and resource for the future applications of quantitative proteomics in iPSC-derived human neurons.