Molecular & Cellular Proteomics最新文献

Usher syndrome is the leading cause of inherited deaf-blindness, with type 2 (USH2) being the most common form. USH2A, ADGRV1, and WHRN are the three known USH2 causative genes, which are also linked to isolated retinal degeneration and hearing loss. These genes encode usherin, ADGRV1, and whirlin, respectively, collectively called USH2 proteins. These proteins form a multiprotein complex (USH2 complex) at the periciliary membrane in retinal photoreceptors and at the stereociliary ankle link in inner ear hair cells. The molecular function of the USH2 complex and its disease mechanisms are poorly understood. Currently, there is no cure for diseases caused by mutations in the three USH2 genes. In this study, we employed multiple affinity purification methods combined with mass spectrometry to systematically identify the interaction partners of USH2 proteins in the retina. The ADGRV1 intracellular bait pulled down proteins involved in actin-based cell projections, the chaperone-containing TCP-1 complex, and the Bardet-Biedl syndrome complex. The extracellular domains of ADGRV1 and usherin pulled down proteins related to peptidase regulation, collagen biosynthesis and modification, and elastic fiber formation. The EAR/EPTP repeats of ADGRV1 specifically pulled down TGFβ signaling proteins. Further immunoprecipitation experiments identified, with high confidence, Gαi and Gαq as ADGRV1-interacting proteins, and retinal degeneration and ciliary proteins as interaction partners of USH2 proteins. We also demonstrated that the usherin extracellular domains interact with each other and with ADGRV1. Overall, these findings suggest that the USH2 complex connects the extracellular matrix (ECM) to the intracellular actin network, signals through Gαi and Gαq, and participates in ECM remodeling, TGFβ signaling, cell adhesion, and ciliary function in photoreceptors.

Extracellular vesicles (EVs) are central to intercellular communication and have gained attention as rich sources of molecular information in cancer research, but their molecular composition remains incompletely characterized. Protein glycosylation is a frequent post-translational modification; however, most EV studies focus on proteomics, while mapping glycosylation changes of proteins are still underrepresented. To address this gap, we analyzed the proteomic, N-glycoproteomic, and chondroitin/dermatan sulfate (CS/DS) glycosaminoglycan (GAG) profiles of small EVs (sEVs) derived from A549 lung adenocarcinoma and BEAS-2B non-tumorigenic epithelial cells. Principal component analysis and hierarchical clustering revealed that all three profiles strongly reflect sEV origin. Comparative proteomic analysis showed enrichment of proteins associated with cell cycle regulation, deoxyribonucleic acid repair, metabolism, and protein synthesis in A549 sEVs, while immune-related processes were enriched in BEAS-2B sEVs. Five differentially expressed CS proteoglycans were identified, highlighting the value of complementary GAG-level analysis. N-glycoproteomics revealed a shift from oligomannose to complex N-glycans in A549 sEVs. Prominent glycoproteins with multiple glycosylation sites included versican, galectin-3-binding protein and laminins. CS/DS content increased 3.4-fold in A549 sEVs, while the ratio of the two monosulfated disaccharides changed 2-fold. These findings demonstrate the utility of N-glycoproteomics and GAG profiling for sensitively characterizing molecular differences between sEVs derived from different cell culture models, thereby providing a foundation for future EV biomarker studies.

Targeted mass spectrometry enables precise peptide quantification by identifying high-quality chromatographic peaks for area integration. Automated peak identification remains challenging, particularly for low-abundance targets, due to interference and noise. Existing approaches typically rely on two supervised learning models, one for selecting peak regions and the other for performing downstream quality control in a separate post-processing step. However, deferring quality assessment to a separate stage may limit the ability to refine peak boundaries in pursuit of improved quality, as the initial selection is performed without explicit awareness of quality-related criteria. In this study, we present MsTargetPeaker, a quality-aware search procedure for identifying peak regions in targeted proteomics data. The method employs a reinforcement learning agent to guide Monte Carlo tree search to efficiently explore chromatograms and localize target peaks while minimizing interference. Peak quality is dynamically assessed during the search via a custom-designed reward function, which prioritizes regions with desirable peak characteristics and enables accurate and robust boundary determination. The reward function further incorporates cross-sample consensus profiles of candidate boundaries to improve the identification of low-quality or ambiguous signals. These innovations support fine-grained peak identification, enhancing both peak quality and quantification precision. Additionally, the transparent reward calculation allows MsTargetPeaker to generate interpretable diagnostic quality reports, providing comprehensive metrics across transitions, peak groups, and sample replicates. This facilitates efficient detection of problematic cases for manual curation. Collectively, MsTargetPeaker offers a practical advancement toward robust and automated peak identification in targeted proteomics.

High-throughput proteomic profiling provides a comprehensive analysis of systemic cancer effects and tumor microenvironment interactions. Characterizing soluble proteins driving inflammation in acute myeloid leukemia (AML) offers insight into inflammatory diseases like differentiation syndrome (DS) related to AML therapies like menin inhibitors. We present our application of NUcleic acid-Linked Immuno-Sandwich Assay (NULISA), a novel technology leveraging next-generation sequencing (NGS) for high-throughput, ultra-sensitive characterization of secreted inflammatory proteins in plasma or serum. Here we report its use to identify dynamic soluble protein changes during treatment and at the time of suspected DS in pediatric AML patients treated with the menin inhibitor revumenib (NCT04065399, NCT05360160).

The spatial organization of the cellular proteome is vital for cellular physiology, as protein localization is closely linked to post-translational modifications, subcellular trafficking, and protein-protein interactions. Systematic profiling of these spatial features can greatly enhance our understanding of protein functions. Recent advances in enzyme-mediated proximity labeling (PL) techniques, such as TurboID and APEX2, have improved our ability to map subcellular proteomes in living cells. This review discusses emerging trends in PL methods, which now offer subcellular precision with multi-dimensional protein features, including post-translational modifications, trafficking, turnover, and interaction with other biomolecules. Additionally, new techniques such as photoactivatable PL (optoPL) and antibody-targeted PL (immunoPL) provide enhanced spatiotemporal control and allow for detailed subcellular proteome mapping without genetic manipulation.

The Hevea brasiliensis is the only commercial source of natural rubber. In natural rubber production, exogenous ethylene is widely used as a stimulant for increasing rubber latex yield. To reveal the potential regulation mechanisms for ethylene stimulation of natural rubber production in H. brasiliensis, we performed an integrative analysis of transcriptomics and proteomics for ethylene-stimulated rubber latex. A total of 35,306 genes and 3,620 proteins were successfully identified from the different latex samples upon ethylene stimulation. Gene ontology analysis revealed these genes are mainly involved in cytoplasm, cytoplasmic and catalytic activity. Kyoto encyclopedia of genes and genomes analysis demonstrated their pathways are mainly enriched in alanine and glutamate metabolism, carbon metabolism, and carbon fixation. Ethylene stimulation played a key regulatory role at the translation/post-translation modification level to promote nature rubber synthesis. Notably, 64 genes and 35 proteins are directly involved in natural rubber biosynthesis. Among them, several family members of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR), small rubber particle protein (SRPP) and cis-prenyl transferase (CPT) are ethylene-responsive ones. It is noteworthy that accumulation of CPT7 was significantly increased after ethylene application. Overexpression of HbCPT7 in a rubber-producing model plant, Taraxacum Kok-saghyz (TKS), resulted in a significant increase for rubber content in the transgenic TKS roots.

Interchanging canonical histone H2A with variant H2A.Z in chromatin complexes is vital for the proper regulation of transcription, DNA damage repair, and centromere maintenance. However, the physical mechanisms underlying functional differences between H2A and H2A.Z complexes are unclear. Human H2A and H2A.Z exhibit high sequence and structural conservation, with subtle differences in the H2A DNA-binding loops. In this study, we employ hydrogen-deuterium exchange coupled with mass spectrometry and molecular dynamics simulation to investigate the differences in solution behavior between human H2A-H2B and H2A.Z-H2B. We demonstrate that replacing H2A with H2A.Z enhances the dynamics of the refolded histone heterodimer, whether it is in nucleosomes, in complex with H3-H4, or alone in solution. In all situations, enhanced dynamics are observed for H2B, suggesting altered interaction with H2A.Z and DNA. Parallel comparisons of H2A-H2B orthologs between humans and frogs reveal fewer differences in dynamics. Our findings provide mechanistic insights into the function of histone variants and reveal how differences in dynamics may underlie functional differences between structurally similar proteins.

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) has become an indispensable tool for structural biology, yet conventional microflow configurations limit its application to readily expressible proteins available in microgram quantities. Here, we present nano-scaled HDX (nHDX), a nanoflow implementation on a commercial automated HDX platform that overcomes these limitations. We demonstrate that rapid, online microflow digestion and trapping can be effectively coupled with nanoflow separation at low temperatures to achieve unprecedented sensitivity. By integrating narrower bore tubing, optimized valve configurations, and appropriate columns, we achieved a >20-fold reduction in gradient delay volume while enhancing sensitivity by over 100-fold, maintaining equivalent performance while using just 10 ng versus 1 μg of of peptide mix per injection. We demonstrate exceptional system robustness with chromatographic reproducibility below 1.5% CV for peptides, retention time shifts averaging 0.035 minutes, deuterium (D)-uptake measurements with standard deviations of 0.1 Da and improved D-retention compared to conventional microflow HDX. The drastic reduction in the amounts of protein required enabled characterization of challenging macromolecular complexes previously inaccessible to conventional HDX-MS. Using 250 fmol of the 320 kDa Polycomb Repressive Complex 2 (PRC2) per injection, we achieved sequence coverage exceeding 86%, while the 0.9 MDa RNA Editing Catalytic Complex 2 (RECC2), generated following one-step purification, yielded 77% coverage with 600 fmol of RECC2 per injection. The nHDX configuration reduces sample requirements to the sub-pmol range per injection without compromising performance relative to conventional HDX-MS, enabling the analysis of previously intractable protein systems with limited sample availability or those available only from rapid, low-yield purification protocols. Our straightforward implementation on a commercial platform eliminates the need for extensive method development, making this enhancement readily accessible and scalable to the broader structural biology community.

Tumor stiffening plays a pivotal role in cancer progression. Increased tumor stiffness, resulting from interactions between cancer cells and their surrounding microenvironment, alters the tumor's mechanical properties and significantly impacts cancer growth and metastasis, the primary cause of cancer-related death. Despite the importance of tumor stiffness, systematic studies exploring its effect on protein dysregulation are limited. In this study, focused on colorectal cancer, we show by in-depth proteomics that matrix stiffness significantly alters the expression of secreted proteins, while intracellular protein levels remain largely unaffected. Functional assays reveal that the changes observed by proteomics in the secretome, driven by matrix stiffness, enhance cell migration, angiogenesis, and matrix remodeling, which collectively would contribute to a more aggressive cancer phenotype in a real scenario. Our findings emphasize the critical role of matrix stiffness in driving colorectal cancer progression through changes in the secretome, offering valuable insights for the development of biomechanical cancer therapies.

Chronic myeloid leukemia (CML) resistance to BCR-ABL tyrosine kinase inhibitors (TKIs) can arise from ABL kinase domain mutations, BCR-ABL fusion gene amplification, or kinase-independent mechanisms. To investigate imatinib-resistance, we performed quantitative mass spectrometry comparing the proteome and phosphoproteome of K562 cells (a standard CML model) and ImR cells, an imatinib-resistant K562 derivative that also exhibits cross-resistance to second- and third-generation BCR-ABL TKIs. In addition to revealing global proteome and phosphoproteome changes associated with drug resistance, we identified LIN28A-a multi-functional RNA-binding protein-as a critical mediator of imatinib resistance. LIN28A was significantly overexpressed and hyperphosphorylated in ImR cells. Depleting LIN28A via shRNA restored imatinib sensitivity, while its ectopic expression in parental K562 cells induced imatinib resistance. Mechanistically, LIN28A coordinates an extensive kinase-substrate network regulating proliferation, survival, and metabolism to drive resistance. Notably, pharmacological inhibition of LIN28A-dependent kinases (PKC, AKT, SGK1, and RPS6K) suppressed ImR proliferation. Midostaurin, a clinical PKC/FLT3 inhibitor used in FLT3-ITD-positive AML, potently re-sensitized ImR cells to imatinib. Our findings suggest that targeting LIN28A and its downstream effectors, particularly PKC, could overcome resistance to imatinib and next-generation BCR-ABL inhibitors.