Molecular & Cellular Proteomics最新文献

Since its first appearance, severe acute respiratory syndrome coronavirus 2 quickly spread around the world and the lack of adequate PCR testing capacities, especially during the early pandemic, led the scientific community to explore new approaches such as mass spectrometry (MS). We developed a proteomics workflow to target several tryptic peptides of the nucleocapsid protein. A highly selective multiple reaction monitoring-cubed (MRM³) strategy provided a sensitivity increase in comparison to conventional MRM acquisition. Our MRM³ approach was first tested on an Amsterdam public health cohort (alpha-variant, 760 participants) detecting viral nucleocapsid protein peptides from nasopharyngeal swabs samples presenting a cycle threshold value down to 35 with sensitivity and specificity of 94.2% and 100.0%, without immunopurification. A second iteration of the MS-diagnostic test, able to analyze more than 400 samples per day, was clinically validated on a Leiden-Rijswijk public health cohort (delta-variant, 2536 participants) achieving 99.9% specificity and 93.1% sensitivity for patients with cycle threshold values up to 35. In this manuscript, we also developed and brought the first proof of the concept of viral variant monitoring in a complex matrix using targeted MS.

At the molecular scale, adaptive advantages during plant growth and development rely on modulation of gene expression, primarily provided by epigenetic machinery. One crucial part of this machinery is histone posttranslational modifications, which form a flexible system, driving transient changes in chromatin, and defining particular epigenetic states. Posttranslational modifications work in concert with replication-independent histone variants further adapted for transcriptional regulation and chromatin repair. However, little is known about how such complex regulatory pathways are orchestrated and interconnected in cells. In this work, we demonstrate the utility of mass spectrometry-based approaches to explore how different epigenetic layers interact in Arabidopsis mutants lacking certain histone chaperones. We show that defects in histone chaperone function (e.g., chromatin assembly factor-1 or nucleosome assembly protein 1 mutations) translate into an altered epigenetic landscape, which aids the plant in mitigating internal instability. We observe changes in both the levels and distribution of H2A.W.7, altogether with partial repurposing of H3.3 and changes in the key repressive (H3K27me1/2) or euchromatic marks (H3K36me1/2). These shifts in the epigenetic profile serve as a compensatory mechanism in response to impaired integration of the H3.1 histone in the fas1 mutants. Altogether, our findings suggest that maintaining genome stability involves a two-tiered approach. The first relies on flexible adjustments in histone marks, while the second level requires the assistance of chaperones for histone variant replacement.

Protein identification and quantification is an important tool for biomarker discovery. With the increased sensitivity and speed of modern mass spectrometers, sample preparation remains a bottleneck for studying large cohorts. To address this issue, we prepared and evaluated a simple and efficient workflow on the Opentrons OT-2 robot that combines sample digestion, cleanup, and loading on Evotips in a fully automated manner, allowing the processing of up to 192 samples in 6 h. Analysis of 192 automated HeLa cell sample preparations consistently identified ∼8000 protein groups and ∼130,000 peptide precursors with an 11.5 min active liquid chromatography gradient with the Evosep One and narrow-window data-independent acquisition (nDIA) with the Orbitrap Astral mass spectrometer providing a throughput of 100 samples per day. Our results demonstrate a highly sensitive workflow yielding both reproducibility and stability at low sample inputs. The workflow is optimized for minimal sample starting amount to reduce the costs for reagents needed for sample preparation, which is critical when analyzing large biological cohorts. Building on the digesting workflow, we incorporated an automated phosphopeptide enrichment step using magnetic titanium-immobilized metal ion affinity chromatography beads. This allows for a fully automated proteome and phosphoproteome sample preparation in a single step with high sensitivity. Using the integrated digestion and Evotip loading workflow, we evaluated the effects of cancer immune therapy on the plasma proteome in metastatic melanoma patients.

Human extracellular 6-O-endosulfatases Sulf-1 and Sulf-2 are the only enzymes that post-synthetically alter the 6-O sulfation of heparan sulfate proteoglycans (HSPG), which regulates interactions of HSPG with many proteins. Oncogenicity of Sulf-2 in different cancers has been documented, and we have shown that Sulf-2 is associated with poor survival outcomes in head and neck squamous cell carcinoma (HNSCC). Despite its importance, limited information is available on direct protein-protein interactions of the Sulf-2 protein in the tumor microenvironment. In this study, we used monoclonal antibody (mAb) affinity purification and mass spectrometry to identify galectin-3-binding protein (LG3BP) as a highly specific binding partner of Sulf-2 in the conditioned media of HNSCC cell lines. We validated their direct interaction in vitro using recombinant proteins and have shown that the chondroitin sulfate (CS) covalently bound to the Sulf-2 influences the binding to LG3BP. We confirmed the importance of the CS chain for the interaction by generating a mutant Sulf-2 protein that lacks the CS. Importantly, we have shown that the LG3BP inhibits Sulf-2 activity in vitro in a concentration-dependent manner. As a consequence, the addition of LG3BP to a spheroid cell culture inhibited the invasion of the HNSCC cells into Matrigel. Thus, Sulf-2 interaction with LG3BP may regulate the physiological activity of the Sulf-2 enzyme as well as its activity in the tumor microenvironment.

High myopia is a leading cause of blindness worldwide, among which pathologic myopia, characterized by typical myopic macular degeneration, is the most detrimental. However, its pathogenesis remains largely unknown. Here, using a HuProt array, we first initiated a serological autoantibody profiling of high myopia and identified 18 potential autoantibodies, of which anti-LIMS1 autoantibody was validated by a customized focused microarray. Further subgroup analysis revealed its actual relevance to pathologic myopia, rather than simple high myopia without myopic macular degeneration. Mechanistically, anti-LIMS1 autoantibody predominantly belonged to IgG1/IgG2/IgG3 subclasses. Serum IgG obtained from patients with pathologic myopia could disrupt the barrier function of retinal pigment epithelial cells via cytoskeleton disorganization and tight junction component reduction, and also trigger a pro-inflammatory mediator cascade in retinal pigment epithelial cells, which were all attenuated by depletion of anti-LIMS1 autoantibody. Together, these data uncover a previously unrecognized autoimmune etiology of myopic macular degeneration in pathologic myopia.

Positional proteomics methodologies have transformed protease research, and have brought mass spectrometry (MS)-based degradomics studies to the forefront of protease characterization and system-wide interrogation of protease signaling. Considerable advancements in both sensitivity and throughput of liquid chromatography (LC)-MS/MS instrumentation enable the generation of enormous positional proteomics datasets of natural and protein termini and neo-termini of cleaved protease substrates. However, concomitant progress has not been observed to the same extent in data analysis and post-processing steps, arguably constituting the largest bottleneck in positional proteomics workflows. Here, we present a computational tool, CLIPPER 2.0, that builds on prior algorithms developed for MS-based protein termini analysis, facilitating peptide-level annotation and data analysis. CLIPPER 2.0 can be used with several sample preparation workflows and proteomics search algorithms and enables fast and automated database information retrieval, statistical and network analysis, as well as visualization of terminomic datasets. We demonstrate the applicability of our tool by analyzing GluC and MMP9 cleavages in HeLa lysates. CLIPPER 2.0 is available at https://github.com/UadKLab/CLIPPER-2.0.

Colorectal cancer (CRC) is characterized by high morbidity, high mortality, and limited response to immunotherapies. The peripheral immune system is an important component of tumor immunity, and enhancements of peripheral immunity help to suppress tumor progression. However, the functional alterations of the peripheral immune system in CRC are unclear. Here, we used mass spectrometry-based quantitative proteomics to establish a protein expression atlas for the peripheral immune system in CRC, including plasma and five types of immune cells (CD4⁺ T cells, CD8⁺ T cells, monocytes, natural killer cells, and B cells). Synthesizing the results of the multidimensional analysis, we observed an enhanced inflammatory phenotype in CRC, including elevated expression of plasma inflammatory proteins, activation of the inflammatory pathway in monocytes, and increased inflammation-related ligand-receptor interactions. Notably, we observed tumor effects on peripheral T cells, including altered cell subpopulation ratios and suppression of cell function. Suppression of CD4⁺ T cell function is mainly mediated by high expression levels of protein tyrosine phosphatases. Among them, the expression of protein tyrosine phosphatase receptor type J (PTPRJ) gradually increased with CRC progression; knockdown of PTPRJ in vitro could promote T cell activation, thereby enhancing peripheral immunity. We also found that the combination of leucine-rich α-2 glycoprotein 1 (LRG1) and apolipoprotein A4 (APOA4) had the best predictive ability for colorectal cancer and has the potential to be a biomarker. Overall, this study provides a comprehensive understanding of the peripheral immune system in CRC. It also offers insights regarding the potential clinical utilities of these peripheral immune characteristics as diagnostic indicators and therapeutic targets.

The understanding of dynamic plasma proteome features in hybrid immunity and breakthrough infection is limited. A deeper understanding of the immune differences between heterologous and homologous immunization could assist in the future establishment of vaccination strategies. In this study, 40 participants who received a third dose of either a homologous BBIBP-CorV or a heterologous ZF2001 protein subunit vaccine following two doses of inactivated coronavirus disease 2019 vaccines and 12 patients with BA2.2 breakthrough infections were enrolled. Serum samples were collected at days 0, 28, and 180 following the boosting vaccination and breakthrough and then analyzed using neutralizing antibody tests and mass spectrometer-based proteomics. Mass cytometry of peripheral blood mononuclear cell samples was also performed in this cohort. The chemokine signaling pathway and humoral response markers (IgG2 and IgG3) associated with infection were found to be upregulated in breakthrough infections compared to vaccination-induced immunity. Elevated expression of IGKV, IGHV, IL-17 signaling, and the phagocytosis pathway, along with lower expression of FGL2, were correlated with higher antibody levels in the boosting vaccination groups. The MAPK signaling pathway and Fc gamma R-mediated phagocytosis were more enriched in the heterologous immunization groups than in the homologous immunization groups. Breakthrough infections can trigger more intensive inflammatory chemokine responses than vaccination. T-cell and innate immune activation have been shown to be closely related to enhanced antibody levels after vaccination and therefore might be potential targets for vaccine adjuvant design.

Signaling networks are critical for virtually all cell functions. Our current knowledge of cell signaling has been summarized in signaling pathway databases, which, while useful, are highly biased toward well-studied processes, and do not capture context specific network wiring or pathway cross-talk. Mass spectrometry-based phosphoproteomics data can provide a more unbiased view of active cell signaling processes in a given context, however, it suffers from low signal-to-noise ratio and poor reproducibility across experiments. While progress in methods to extract active signaling signatures from such data has been made, there are still limitations with respect to balancing bias and interpretability. Here we present phuEGO, which combines up-to-three-layer network propagation with ego network decomposition to provide small networks comprising active functional signaling modules. PhuEGO boosts the signal-to-noise ratio from global phosphoproteomics datasets, enriches the resulting networks for functional phosphosites and allows the improved comparison and integration across datasets. We applied phuEGO to five phosphoproteomics data sets from cell lines collected upon infection with SARS CoV2. PhuEGO was better able to identify common active functions across datasets and to point to a subnetwork enriched for known COVID-19 targets. Overall, phuEGO provides a flexible tool to the community for the improved functional interpretation of global phosphoproteomics datasets.

Trilaciclib, a cyclin-dependent kinase 4/6 inhibitor, was approved as a myeloprotective agent for protecting bone marrow from chemotherapy-induced damage in extensive-stage small cell lung cancer. This is achieved through the induction of a temporary halt in the cell cycle of bone marrow cells. While it has been studied in various cancer types, its potential in hematological cancers remains unexplored. This research aimed to investigate the efficacy of trilaciclib in hematological cancers. Utilizing mass spectrometry-based proteomics, we examined the alterations induced by trilaciclib in the chronic myeloid leukemia cell line, K562. Interestingly, trilaciclib promoted senescence in these cells rather than cell death, as observed in acute myeloid leukemia, acute lymphoblastic leukemia, and myeloma cells. In K562 cells, trilaciclib hindered cell cycle progression and proliferation by stabilizing cyclin-dependent kinase 4/6 and downregulating cell cycle-related proteins, along with the concomitant activation of autophagy pathways. Additionally, trilaciclib-induced senescence was also observed in the nonsmall cell lung carcinoma cell line, A549. These findings highlight trilaciclib's potential as a therapeutic option for hematological cancers and underscore the need to carefully balance senescence induction and autophagy modulation in chronic myeloid leukemia treatment, as well as in nonsmall cell lung carcinoma cell line.