Molecular & Cellular Proteomics最新文献

Acute kidney injury (AKI), characterized by a rapid decline in renal function, has high mortality rates and frequently progresses to chronic kidney disease (CKD). A major contributor to AKI is ischemia-reperfusion injury (IRI). However, the global molecular changes underlying the AKI-to-CKD transition post-IRI remain to be fully elucidated. Using 4D label-free proteomic and phosphoproteomic analyses in a murine unilateral IRI model at 1 hour, 1 day, 3 days, 7 days, and 28 days post-injury, we systematically identified dysregulated proteins, phosphoproteins, and signaling pathways involved in the progression from AKI to CKD. Critically, these analyses consistently revealed the enrichment and sustained activation of NF-κB signaling, a key pathway driving inflammatory and fibrotic responses, across multiple time points. In addition, we identified significant impairment of fatty acid β-oxidation (FAO). Notably, our omics analysis specifically identified the dedicator of cytokinesis (Dock) protein family, with Dock2 emerging as a prime candidate due to its known immune regulatory functions. Dock2 expression showed significant upregulation post-IRI and was found predominantly localized to injured tubular epithelial cells (TECs). Functional validation demonstrated that Dock2 knockdown attenuated pro-inflammatory responses in TECs by inhibiting IKKβ-mediated NF-κB activation in vitro. Consistently, pharmacological inhibition of Dock2 by CPYPP ameliorated renal tubular injury, inflammation, and fibrosis in vivo. To our knowledge, this is the first study to reveal the role and mechanism of Dock2 in the AKI-to-CKD progression post-IRI. In conclusion, our findings delineate molecular mechanisms underpinning the transition from AKI to CKD and nominate Dock2 as a promising therapeutic target for mitigating this process.

High-throughput proteomics is critical for understanding biological processes, enabling large-scale studies such as biomarker discovery and systems biology. However, current mass spectrometry technologies face limitations in speed, sensitivity, and scalability for analyzing large sample cohorts. The Thermo Scientific™ Orbitrap™ Astral™ Zoom mass spectrometer (MS) was developed to address these limitations by improving acquisition speed, ion utilization, and spectral processing, which are all essential for advancing proteome depth in high-throughput proteomics. The Orbitrap Astral Zoom MS achieves ultra-fast MS/MS scan rates of up to 270 Hz with enhanced ion utilization through pre-accumulation, enabling the identification of ∼100,000 unique peptides and >8,400 proteins in a single 300 samples-per-day (SPD) analysis of human cell lysate. The optimized system reduces analysis time by 40%, achieves near-complete proteome coverage (>12,000 proteins) in 2.7 hours, and enables ultra-high-throughput workflows, identifying >7,000 proteins in a 500 SPD method with exceptional reproducibility (Pairwise Pearson correlations >0.99). These advancements establish the Orbitrap Astral Zoom MS among the fastest and most sensitive instruments under the tested conditions, significantly enhancing speed, sensitivity, and scalability, paving the way for routine large-scale proteomics with applications in clinical research and systems biology.

Small extracellular vesicles (sEVs), lipid-bilayer delimited particles (50-200 nm) released by cells, are emerging as a promising class of liquid biopsy biomarkers for elusive cancers such as high-grade serous ovarian cancer (HGSOC). HGSOC originates from the fallopian tube (FT), progressing from p53 signatures to a precursor lesion known as serous tubal intraepithelial carcinoma (STIC). We hypothesize that sEVs contribute to ovarian cancer pathogenesis, carry cargo reflective of their site of origin, and serve as diagnostic biomarkers for early detection. To test this, we established a case-control cohort using archival plasma samples from 30 HGSOC patients (10 early-stage and 20 late-stage) and 40 healthy controls (HC). sEVs were enriched by size exclusion chromatography and profiled by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Across all samples, 1,078 EV-associated proteins (exo-proteins) were identified, including 52 upregulated in early-stage HGSOC vs HC, and 59 upregulated in late-stage HGSOC vs healthy controls (HC) (log₂FC>1, p-value<0.05). Upregulated EV-proteins were prioritized based on FT origin and tissue expression in STIC lesions. Seven candidate biomarkers (MYL6, GSTP1, TTYH3, PRDX6, MUC1, MYH14, and PTGS1) were validated by immunohistochemistry in FT tissue harboring STIC lesions and in HGSOC tissues, as well as by western blotting in FT/HGSOC cell-derived EVs. These findings suggest that circulating exo-proteins upregulated in early-stage cancer disease reflect precursor lesions. A four-protein combinatorial panel (MUC1, MYL6, TTYH3, GSTP1), selected using Akaike Information Criterion (AIC), yielded an AUC of 0.975 and 90% sensitivity at 95% specificity for distinguishing early-stage HGSOC vs HC. Additionally, increased MUC1 levels in circulating sEVs were confirmed by immunoassay (AUC = 0.840 for early-stage HGSOC vs HC; AUC = 0.860 for late-stage HGSOC vs HC, p-value<0.05). In summary, our sEV proteomic analysis of early-stage HGSOC reveals exo-biomarkers associated with early FT lesions, offering a promising avenue for detecting disease while it remains confined to the fallopian tube.

Extracellular vesicles (EVs) have gained increasing attention with their intriguing biological functions and their molecular cargoes serving as potential biomarkers for various diseases, including cancers. A relatively lower abundance of EV proteins compared to cellular counterparts necessitates sensitive and accurate quantitative proteomic strategies. Multiplexed proteomics combined with data-independent acquisition (mDIA) has shown promise for improving sensitivity and quantification over traditional DDA and label-free methods. Despite this, mDIA pipelines that utilize various types of spectral libraries and search software suites have not been thoroughly evaluated with EV proteome samples. In this study, we aim to establish a robust mDIA pipeline based on dimethyl labeling for quantitative proteomics of EVs. EVs were isolated using the extracellular vesicle total recovery and purification (EVtrap) technique and processed directly through an on-bead one-pot sample preparation workflow to obtain digested peptides. We evaluated different mDIA pipelines, including library-free and library-based DIA on the timsTOF HT platform. Results showed that library-based DIA, with project-specific spectral libraries generated from StageTip-based fractionation, outperformed other pipelines in protein identification and quantification. We demonstrated for the first time EV proteome landscape changes caused by the IDH1 mutation and inhibitor treatment in intrahepatic cholangiocarcinoma, highlighting the utility of mDIA in EV-based biomarker discovery.

The development of targeted assays that monitor biomedically relevant proteins is an important step in bridging discovery experiments to large scale clinical studies. Targeted assays are currently unable to scale to hundreds or thousands of targets. We demonstrate the generation of large-scale assays using a novel hybrid nominal mass instrument. The scale of these assays is achievable with the Stellar^TM mass spectrometer through the accommodation of shifting retention times by real-time alignment, while being sensitive and fast enough to handle many concurrent targets. Assays were constructed using precursor information from gas-phase fractionated (GPF) data-independent acquisition (DIA). We demonstrate the ability to schedule methods from orbitrap and linear ion trap acquired GPF DIA library, and compare the quantification of a matrix-matched calibration curve from orbitrap DIA and linear ion trap parallel reaction monitoring (PRM). Two applications of these proposed workflows are shown with a cerebrospinal fluid (CSF) neurodegenerative disease protein PRM assay and with a Mag-Net enriched plasma extracellular vesicle (EV) protein survey PRM assay. In CSF, our assay targets proteins discovered previously to be associated with Alzheimer's disease in a small independent sample set. For the Mag-Net enriched plasma survey assay, we observe that proteins selected based on their measurement robustness are still able to capture differences in abundance across disease groups in a small sample set. These highlight the application of highly multiplex, targeted protein assays in clinical research.

Malaria transmission from humans to mosquitoes is essential to the parasite life cycle. In the human malaria parasite, Plasmodium falciparum, the rate of commitment to produce the sexual transmission stages, or gametocytes varies and is governed by genetic, epigenetic and environmental factors. The sexually committed parasite has so far remained elusive due to the lack of markers to efficiently isolate these parasites for subsequent functional studies including proteomic analysis of the isolated population. Here, we demonstrate that MSRP1 is a highly specific sexual commitment marker. Using this marker, we generated and validated reporter parasite lines for subsequent FACS-based isolation of sexually and asexually committed parasites. Proteomics of isolated parasites defined distinct protein signatures, including several merozoite surface proteins, indicating functional differences between the two parasite populations. This study provides a blueprint for systematic characterisation of the parasite stage at this crucial juncture in the life cycle.

Although the plasma membrane (PM) is among the most biologically important and therapeutically targeted cellular compartments, it is among the most challenging to faithfully capture using proteomic approaches. The quality of quantitative surfaceomics data depends heavily on the effectiveness of the cell surface enrichment used during sample preparation. Enrichment improves sensitivity for low abundance PM proteins and ensures that the changes detected reflect PM expression changes rather than whole cell changes. Cell surface biotinylation with PM-impermeable, amine-reactive reagents is a facile, accessible, and unbiased approach to enrich PM proteins. However, it results in unexpectedly high contamination with intracellular proteins, reducing its utility. We report that biotinylating human cells with amine-reactive reagents intracellularly labels a small but reproducible population of non-viable cells. Although these dead cells represent only 5±2% of the total, we find that in T cell preparations the dead cells account for 90% of labelled proteins. Depleting Annexin V positive dead T cells post-labelling removes ∼99% of the intracellularly labelled cells, resulting in markedly improved PM identifications, peptide counts, and iBAQ intensities. Correspondingly, we found substantial depletion of intracellular proteins, particularly of nuclear origin. Overall, the cumulative intensity of PM proteins increased from 4% to 55.8% with dead cell depletion. Finally, we demonstrate that immature ER/Golgi glycoforms of CD11a and CD18 are selectively removed by dead-cell depletion. We conclude that high intracellular labelling of non-viable cells is the major source of intracellular protein contaminants in amine-reactive surface enrichment methods and can be reduced by dead-cell depletion post-labelling, improving both the sensitivity and accuracy of plasma membrane proteomics.

Post-translational modifications (PTMs) play a central role in cellular regulation and are implicated in numerous diseases. Database searching remains the standard for identifying modified peptides from tandem mass spectra, but is hindered by the combinatorial expansion of modification types and sites. De novo peptide sequencing offers an attractive alternative, yet existing methods remain limited to unmodified peptides or a narrow set of PTMs. Here, we curated a large dataset of spectra from endogenous and synthetic peptides from ProteomeTools spanning 19 biologically relevant amino acid-PTM combinations, covering phosphorylation, acetylation, and ubiquitination. We used this dataset to develop Modanovo, an extension of the Casanovo transformer architecture for de novo peptide sequencing. Modanovo achieved robust performance across these amino acid-PTM combinations (median area under the precision-coverage curve 0.92), while maintaining performance on unmodified peptides (0.93), nearly identical to Casanovo (0.94). The model outperformed π-PrimeNovo-PTM and InstaNovo-P and showed increased precision and complementarity to the database search tool MSFragger. Robustness was confirmed across independent datasets, particularly at peptide lengths frequently represented in the curated dataset. Applied to a phosphoproteomics dataset from monkeypox virus-infected cells, Modanovo recovered numerous confident peptides not reported by database search, including new viral phosphosites supported by spectral evidence, thereby demonstrating its complementarity to database-driven identification approaches. These results establish Modanovo as a broadly applicable model for comprehensive de novo sequencing of both modified and unmodified peptides.