Proteomics最新文献

Targeted proteomics, which includes parallel reaction monitoring (PRM), is typically utilized for more precise detection and quantitation of key proteins and/or pathways derived from complex discovery proteomics datasets. Initial discovery-based analysis using data independent acquisition (DIA) can obtain deep proteome coverage with low data missingness while targeted PRM assays can provide additional benefits in further eliminating missing data and optimizing measurement precision. However, PRM method development from bioinformatic predictions can be tedious and time-consuming because of the DIA output complexity. We address this limitation with a Python script that rapidly generates a PRM method for the TIMS-TOF platform using DIA data and a user-defined target list. To evaluate the script, DIA data obtained from HeLa cell lysate (200 ng, 45-min gradient method) as well as canonical pathway information from Ingenuity Pathway Analysis was utilized to generate a pathway-driven PRM method. Subsequent PRM analysis of targets within the example pathway, regulation of apoptosis, resulted in improved chromatographic data and enhanced quantitation precision (100% peptides below 10% CV with a median CV of 2.9%, n = 3 technical replicates). The script is freely available at https://github.com/StevensOmicsLab/PRM-script and provides a framework that can be adapted to multiple DDA/DIA data outputs and instrument-specific PRM method types.

Adeno-associated viruses (AAVs) are common vectors for emerging gene therapies due to their lack of pathogenicity in humans. Here, we present our investigation of the viral proteins (i.e., VP1, VP2, and VP3) of the capsid of AAVs via top-down mass spectrometry (MS). These proteins, ranging from 59 to 81 kDa, were chromatographically separated using hydrophilic interaction liquid chromatography and characterized in the gas-phase by high-resolution Orbitrap Fourier transform MS. Complementary ion dissociation methods were utilized to improve the overall sequence coverage. By reducing the overlap of product ion signals via proton transfer charge reduction on the Orbitrap Ascend BioPharma Tribrid mass spectrometer, the sequence coverage of each VP was significantly increased, reaching up to ∼40% in the case of VP3. These results showcase the improvements in the sequencing of proteins >30 kDa that can be achieved by manipulating product ions via gas-phase reactions to obtain easy-to-interpret fragmentation mass spectra.

The protein corona, a layer of biomolecules forming around nanoparticles in biological environments, critically influences nanoparticle interactions with biosystems, affecting pharmacokinetics and biological outcomes. Initially, the protein corona presented challenges for nanomedicine and nanotoxicology, such as nutrient depletion in cell cultures and masking of nanoparticle-targeting species. However, recent advancements have highlighted its potential in environmental toxicity, proteomics, and immunology. This viewpoint focuses on leveraging the protein corona to enhance the depth of plasma proteome analysis, addressing challenges posed by the high dynamic range of protein concentrations in plasma. The protein corona simplifies sample preparation, enriches low-abundance proteins, and improves proteome coverage. Innovations include using diverse nanoparticles and spiking small molecules to increase the number of quantified proteins. Reproducibility issues across core facilities necessitate standardized protocols. Moreover, top-down proteomics enables proteoform-specific measurements, providing deeper insights into protein corona composition. Future research should aim at improving top-down proteomics techniques and integrating protein corona studies and proteomics for personalized medicine and advanced diagnostics.

Plasma proteomics offers high potential for biomarker discovery, as plasma is collected through a minimally invasive procedure and constitutes the most complex human-derived proteome. However, the wide dynamic range poses a significant challenge. Here, we propose a semi-automated method based on the use of multiple single chain variable fragment antibodies, each enriching for peptides found in up to a few hundred proteins. This approach allows for the analysis of a complementary fraction compared to full proteome analysis. Proteins from pooled plasma were extracted and digested before testing the performance of 29 different antibodies with the aim of reproducibly maximizing peptide enrichment. Our results demonstrate the enrichment of 3662 peptides not detected in neat plasma or negative controls. Moreover, most antibodies were able to enrich for at least 155 peptides across different levels of abundance in plasma. To further reduce analysis time, a combination of antibodies was used in a multiplexed setting. Repeated sample analyses showed low coefficients of variation, and the method is flexible in terms of affinity binders. It does not impose drastic increases in instrument time, thus showing excellent potential for usage in large scale discovery projects.