Advanced Proteomics Techniques and Applications

The paper develops a method for high-throughput structural analysis of endogenous protein complexes using native top-down proteomics.

The paper develops a high-throughput single-cell proteomics pipeline for tumor analysis, identifying over 1,800 proteins per cell in murine lung metastasis models.

This paper develops a method to perform single-cell proteomics on preserved tissues, expanding its applicability by overcoming sample preservation challenges.

This paper presents a simplified method to comprehensively capture the Staphylococcus aureus proteome, identifying 2,231 proteins and revealing changes in metabolic and stress-response processes during growth.

This paper enhances the Comet search engine with fragment-ion indexing, improving peptide spectral matching speeds by up to 94% while maintaining accuracy in proteomics applications.

This paper evaluates FDR control in mass spectrometry proteomics tools, finding that none consistently control FDR at the peptide level in DIA data, especially for single-cell datasets.

moPepGen identifies non-canonical peptides from genetic and transcriptomic data across species and technologies by generating them in linear time.

This paper improves HCP identification in monoclonal antibodies by combining FASP and native digestion with shotgun proteomics, achieving higher sensitivity and broader molecular weight coverage.

This study evaluates the Platinum sequencer's ability to detect proteoform-informative peptides, distinguishing TPM1/TPM2 paralogs, spliceforms, and PTMs.

The paper uses diaPASEF proteomics to analyze zebrafish lens regions, achieving higher peptide and protein identifications compared to standard DIA methods.

UniScore integrates and standardizes outputs from multiple search engines in proteomics, outperforming single search engines in large-scale data analysis.

This paper introduces Pairwise Attention, a modified transformer encoder for de novo peptide sequencing from MS2 spectra, improving precision by 12.7% on a nine-species benchmark.

EPSD 2.0 updates the eukaryotic phosphorylation site database with 2.7 million experimentally identified p-sites across 223 species, integrating new data and annotations from multiple sources.

The paper introduces msqrob2TMT, a mixed model-based workflow for differential protein abundance analysis in labelled proteomics, showing improved performance over existing tools.

TopLib is a software package for building and searching top-down mass spectral libraries, offering faster and more reproducible proteoform identification than conventional methods.

The paper develops an automated SP3-TMT sample preparation workflow for proteomics, showing it matches manual methods in performance while improving throughput, cost, and error reduction.

Machine learning integration of over 25,000 mass spectrometry experiments yields 15,326 human protein complexes covering 13,769 proteins, plus 511 AlphaFold-derived mutually exclusive subunit pairs.

The paper introduces SPIED-DIA, a phosphoproteomics method, to identify synergistic signaling responses in colon cancer cells to MEK inhibition and growth factor stimulation.

This paper evaluates kinase activity inference methods using phosphoproteomics data and benchmarking approaches, finding that curated kinase-substrate libraries significantly impact results.

This study uses Orbitrap Astral mass spectrometry with TMT to analyze proteomic changes in mouse brain and kidney tissues across age and sex, revealing tissue-specific and non-linear age-related protein dynamics.

This paper evaluates six plasma proteomic technologies, finding that Seer Proteograph XT provides the highest proteomic depth and quantification, while Olink Explore HT shows comparable LOD but worse LOQ.

ProteoPlotter is a visualization tool for proteomics data that complements Perseus, offering enhanced features for data analysis and interpretation.

Pfly predicts peptide detectability in mass spectrometry using a deep learning model trained on synthetic and biological data, offering customizable classification for different experimental conditions.

This study evaluates the use of FAIMS with Orbitrap Ascend Tribrid Mass Spectrometer to enhance AP-MS analysis of SAP25 protein complexes, showing improved sensitivity and reduced contaminants.

The paper demonstrates using data-independent acquisition (DIA) to select peptides for targeted proteomics assays, achieving comparable quantitative precision to existing methods.

The paper identifies a signature for protein leakage in single-cell proteomics and develops a classifier to detect damaged cells across species and cell types.

This study evaluates the Orbitrap Astral MS's sensitivity for single-cell proteomics, showing improved proteome coverage and quantitative accuracy in low-input samples.

This paper introduces a simple one-step vial-based pretreatment method for deep single-cell proteomics and applies it to study oocyte aging, identifying age-related protein markers.

The paper introduces SPARCE, a method for multiplexed phosphoproteomic analysis of low cell numbers, demonstrating its effectiveness in quantifying phosphosite changes from 1,000 FACS-sorted cells.

CHIMERYS deconvolves chimeric spectra in proteomic data, enabling unified analysis across DDA, DIA, and PRM experiments by accurately identifying and quantifying multiple peptides per spectrum.