Next-generation multiplexed targeted proteomics quantifies post-translational modifications in disease and compound-protein interactions with high throughput

A Scalable and Robust Workflow for Cost-Effective Post-Translational Modifications Profiling by Chemical Proteomics

Enhanced proteome relative quantification using refined quantotypic spectral libraries

Plasma proteomics is used for a variety of applications including biomarker discovery, disease monitoring, and drug development. Data-independent acquisition (DIA) has vastly improved the breadth of proteins that are identified from samples; however, given challenges in reproducibility and translation, it is critical that the quantitative performance of these methods is reliable. Analysis of global proteomics data typically incorporates information from all detected peptides. However, some peptides do not reflect their parent protein amount, due to irreproducible digestion, modification, analytical interferences or instability. We hypothesise that including these peptides impacts protein relative quantification, and thus, a refined spectral library containing only quantitatively representative peptides provides superior protein quantification. By analysing a defined multi-species spike-in model, we show that refining a plasma spectral library by removing precursors that fail to meet quality control metrics (25.4% of all identified precursors) reduces noise and variability, improving precision, accuracy and differential abundance analysis by up to ∼11%, with minimal identification losses and substantial reduction in computational demand. This demonstrates proof-of-concept that refining spectral libraries produces results that prioritize quantification quality over quantity. This approach could enable development of universal tissue-specific refined spectral libraries able to improve quantification quality with easy implementation and minimal processing time. Significance of the Study As DIA mass spectrometry proteome depth increases, the quality of the associated protein quantifications must be considered alongside identification breadth, particularly in complex matrices such as plasma, which presents additional technical challenges. The spectral library used for protein identification and quantification is a critical determinant of DIA performance, and its composition requires considerable consideration. This work illustrates an initial step toward improving protein quantification starting at the spectral library level by filtering precursors which are poor quantitative representatives of their parent proteins. In doing so, the resulting data is more reliable for downstream and biological interpretation, with fewer false differential abundance assignments and reduced quantitative noise. As such, this work represents a broader shift away from the habitual focus of MS workflows on maximising the number of protein and differential abundance identifications and instead prioritises the quality of quantification over quantity. These initial findings lay the groundwork for further development of spectral library refinement strategies, with the potential to continue improving the accuracy and precision of protein quantification in DIA-based proteomics.

STEP-PTMs: Sequential TMT-based Enrichment and Profiling of Post-Translational Modifications

A Derivatization-Free Parallel Reaction Monitoring-Based Proteomics Workflow for Quantitative, Site-Specific Analysis of Histone Post-Translational Modifications

Histone post-translational modifications (PTMs) are key regulators of chromatin architecture and gene expression. Although mass spectrometry (MS)-based data-independent acquisition (DIA) pipelines for histone PTM quantification are available, multiplexed targeted assays remain underdeveloped. Here, we present a derivatization-free parallel reaction monitoring (PRM) workflow for robust, quantitative, and site-specific analysis of major histone H3 and H4 PTMs. We employed highly efficient ArgC digestion to generate peptides of optimal length for liquid chromatography-tandem mass spectrometry (LC–MS/MS) while preserving endogenous PTMs, and we optimized chromatographic conditions to achieve isobaric separation and stable retention times. Co-eluting isobaric PTM species were confidently distinguished using site-specific fragment ions. The resulting PRM method enabled sensitive and reproducible detection of histone PTM isoforms across diverse biological systems. To illustrate its utility, we analyzed PTM dynamics in cells expressing histone H3.3 lysine-to-methionine substitutions and in cells treated with the histone deacetylase inhibitor entinostat, yielding results that correlated strongly with antibody-based readouts. This PRM platform provides a complementary, targeted approach to current chemical derivatization–based methods, enabling reliable validation of selected histone PTMs.

Nanoparticle-enriched mass spectrometry proteomics in British South Asians identifies links between genetic variants, plasma protein levels and disease risk

Understanding genetic variation associated with differences in plasma protein levels can elucidate human disease mechanisms. Here we demonstrate how untargeted nanoparticle-enriched mass spectrometry (MS)-based plasma proteomics delivers quantitatively and qualitatively different insights compared to two affinity-based assays in a sample of ~1,400 British South Asian individuals. We identify >1,200 significant locus–protein associations (P < 8.7 × 10−12; n = 895 cis-protein quantitative trait loci (pQTLs)), more than half of which have not been reported previously. Cross-platform comparison demonstrated that multiple platforms are required to capture the full spectrum of pQTLs of blood proteins. We combine proteogenomic results with evidence from multiple biological domains to suggest a potential role of 21 proteins in the pathology of 44 diseases, including a previously uncharacterized role of immunoglobulin λ variable 3-21 in the development of Graves’ disease. Our results demonstrate the potential of MS-based blood proteomics in non-European ancestries for pQTL discovery and the need to consolidate proteogenomic evidence to confidently assign proteins to disease pathology. This study reports genetic effects on mass spectrophotometry-based plasma proteomics in a cohort of ~1,400 British South Asians, accessing parts of the proteome missed by other proteomics platforms. The resulting protein quantitative trait loci are integrated with genome-wide association study data to find potential mechanisms of disease.

Emerging Trends in Mass Spectrometry-Based Quantitative Proteome and Phosphoproteome Profiling in Maize.

Maize (Zea mays) is both an agronomically important crop and a reference model organism that has enabled the dissection of the molecular basis of plant development and environmental responses. Mass spectrometry-based proteomics provides a powerful approach to identify and quantify proteins and their post-translational modifications, facilitating the discovery of molecular mechanisms underlying complex biological processes. Unlike the study of gene expression using transcriptomics, analysis of the proteome and phosphoproteome provides direct measurement of proteins, which are responsible for driving or regulating nearly all cellular processes, thus offering a more complete picture of the cell's functional state. Over the past two decades, advancements in mass spectrometry have enabled large-scale profiling of protein abundance and phosphorylation sites in maize, improving our understanding of various biological phenomena. Here, we briefly summarize some of the major biological insights gained from maize proteome and phosphoproteome studies, and provide an overview of mass spectrometry sample preparation and acquisition/analysis workflows for the quantitative and reproducible analysis of protein abundance and phosphorylation dynamics in maize.