Optimal analytical strategies for sensitive and quantitative phosphoproteomics using TMT-based multiplexing

O-linked glycosylations in human milk casein and major whey proteins during lactation

As glycosylations are difficult to analyze, their roles and effects are poorly understood. Glycosylations in human milk (HM) differ across lactation. Glycosylations can be involved in antimicrobial activities and may serve as food for beneficial microorganisms. This study aimed to identify and analyze O-linked glycans in HM by high-throughput mass spectrometry. 184 longitudinal HM samples from 66 donors from day 3 and months 1, 2, and 3 postpartum were subjected to a post-translational modification specific enrichment-based strategy using TiO2 and ZrO2 beads for O-linked glycopeptide enrichment. β-CN was found to be a major O-linked glycoprotein, additionally, αS1-CN, κ-CN, lactotransferrin, and albumin also contained O-linked glycans. As glycosyltransferases and glycosidases are involved in assembling the glycans including O-linked glycosylations, these were further investigated. Some glycosyltransferases and glycosidases were found to be significantly decreasing through lactation, including two O-linked glycan initiator enzymes (GLNT1 and GLNT2). Despite their decrease, the overall level of O-linked glycans remained stable in HM over lactation. Three different motifs for O-linked glycosylation were enriched in HM proteins: Gly-Xxx-Xxx-Gly-Ser/Thr, Arg-Ser/Thr and Lys-Ser/Thr. Further O-linked glycan motifs on β-CN were observed to differ between intact proteins and endogenous peptides in HM.

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in both normal and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 μm and the largest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in terms of identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables to identify protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Protocol for high-throughput semi-automated label-free- or TMT-based phosphoproteome profiling

Tandem mass tags data-dependent acquisition (TMT-DDA) as well as data-independent acquisition-based label-free quantification (LFQ-DIA) have become the leading workflows to achieve deep proteome and phosphoproteome profiles. We present a modular pipeline for TMT-DDA and LFQ-DIA that integrates steps to perform scalable phosphoproteome profiling, including protein lysate extraction, clean-up, digestion, phosphopeptide enrichment, and TMT-labeling. We also detail peptide and/or phosphopeptide fractionation and pre-mass spectrometry desalting and provide researchers guidance on choosing the best workflow based on sample number and input. For complete details on the use and execution of this protocol, please refer to Koenig et al.1 and Martínez-Val et al.2.

Recent progress in quantitative phosphoproteomics

INTRODUCTION

Protein phosphorylation is a critical post-translational modification involved in the regulation of numerous cellular processes from signal transduction to modulation of enzyme activities. Knowledge of dynamic changes of phosphorylation levels during biological processes, under various treatments or between healthy and disease models is fundamental for understanding the role of each phosphorylation event. Thereby, LC-MS/MS based technologies in combination with quantitative proteomics strategies evolved as a powerful strategy to investigate the function of individual protein phosphorylation events.

AREAS COVERED

State-of-the-art labeling techniques including stable isotope and isobaric labeling provide precise and accurate quantification of phosphorylation events. Here, we review the strengths and limitations of recent quantification methods and provide examples based on current studies, how quantitative phosphoproteomics can be further optimized for enhanced analytic depth, dynamic range, site localization, and data integrity. Specifically, reducing the input material demands is key to a broader implementation of quantitative phosphoproteomics, not least for clinical samples.

EXPERT OPINION

Despite quantitative phosphoproteomics is one of the most thriving fields in the proteomics world, many challenges still have to be overcome to facilitate even deeper and more comprehensive analyses as required in the current research, especially at single cell levels and in clinical diagnostics.

Hybrid-DIA: intelligent data acquisition integrates targeted and discovery proteomics to analyze phospho-signaling in single spheroids

Achieving sufficient coverage of regulatory phosphorylation sites by mass spectrometry (MS)-based phosphoproteomics for signaling pathway reconstitution is challenging, especially when analyzing tiny sample amounts. To address this, we present a hybrid data-independent acquisition (DIA) strategy (hybrid-DIA) that combines targeted and discovery proteomics through an Application Programming Interface (API) to dynamically intercalate DIA scans with accurate triggering of multiplexed tandem mass spectrometry (MSx) scans of predefined (phospho)peptide targets. By spiking-in heavy stable isotope labeled phosphopeptide standards covering seven major signaling pathways, we benchmark hybrid-DIA against state-of-the-art targeted MS methods (i.e., SureQuant) using EGF-stimulated HeLa cells and find the quantitative accuracy and sensitivity to be comparable while hybrid-DIA also profiles the global phosphoproteome. To demonstrate the robustness, sensitivity, and biomedical potential of hybrid-DIA, we profile chemotherapeutic agents in single colon carcinoma multicellular spheroids and evaluate the phospho-signaling difference of cancer cells in 2D vs 3D culture.

Recent advances in kinase signaling network profiling by mass spectrometry

Mass spectrometry-based phosphoproteomics is currently the leading methodology for the study of global kinase signaling. The scientific community is continuously releasing technological improvements for sensitive and fast identification of phosphopeptides, and their accurate quantification. To interpret large-scale phosphoproteomics data, numerous bioinformatic resources are available that help understanding kinase network functional role in biological systems upon perturbation. Some of these resources are databases of phosphorylation sites, protein kinases and phosphatases; others are bioinformatic algorithms to infer kinase activity, predict phosphosite functional relevance and visualize kinase signaling networks. In this review, we present the latest experimental and bioinformatic tools to profile protein kinase signaling networks and provide examples of their application in biomedicine.

Isobaric labeling: Expanding the breadth, accuracy, depth, and diversity of sample multiplexing

Isobaric labeling has rapidly become a predominant strategy for proteome-wide abundance measurements. Coupled to mass spectrometry, sample multiplexing techniques using isobaric labeling are unparalleled for profiling proteins and posttranslational modifications across multiple samples in a single experiment. Here, I highlight aspects of isobaric labeling in the context of expanding the breadth of multiplexing, improving quantitative accuracy and proteome depth, and developing a wide range of diverse applications. I underscore two facets that enhance quantitative accuracy and reproducibility, specifically the availability of quality control standards for isobaric labeling experiments and the evolution of data acquisition methods. I also emphasize the necessity for standardized methodologies, particularly for emerging high-throughput workflows. Future developments in sample multiplexing will further strengthen the importance of isobaric labeling for comprehensive proteome profiling.