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PubMed2025

Analytical Considerations for the Development of Plate-Based Proteomics Platforms Using Isobaric Labeling.

Mass spectrometer-based proteomics platforms have great potential to rapidly advance our systematic understanding of complex biological problems, enable drug discovery, decipher drug mechanisms of action, and discover novel biomarkers. As the demand for processing large sets of samples in an automatic manner is constantly increasing, the integration of automation platforms (nanoliter dispensers, liquid handlers, etc.) has become a routinary configuration paired with liquid chromatography-mass spectrometers. The functional integration of all of those instruments into a single unit is what we call a plate-based high-throughput proteomics platform (HT proteomics). The readout of the platform is the quantitative proteome data at the protein or peptide level. In this work, we developed a plate-based HT proteomics standard that we called the HT-sKO. The HT-sKO allows the evaluation of accuracy and the estimation of the relative limit of quantification when the target proteins vary up to 60-fold in abundance. The HT-sKO utilizes nonhuman recombinant proteins that can be spiked into the samples, allowing for sample acquisition and HT proteomics platform evaluation at the same time. We also showed the foundational role of a robust acquisition strategy for developing a stable HT proteomics platform and the value of using a tube-based method as an informant assay on data quality expectations for the platform. Using this new standard, we demonstrated that the intra- and inter-plate variance is around 4-6% for the protein level or around 10% for the peptide-level readout. We also showed that the HT-sKO standard is compatible with whole-proteome, phospho-proteome, and reactive cysteine profiling platforms.

Proteomics↗

PubMed2025

Boosting Quantification of N-Glycans by an Enhanced Isobaric Multiplex Reagents for Carbonyl-Containing Compound (SUGAR) Tagging Strategy.

Glycans are complex molecules composed of various monosaccharides and exhibit diverse, branched polymer structures. Extensive research has been conducted on mass spectrometry (MS)-based qualitative and quantitative glycan analysis due to their critical biological functions. However, traditional data-dependent acquisition (DDA) in MS analysis primarily selects a limited subset of abundant ions during MS1 scans for fragmentation in subsequent MS2 stages. In this study, we introduce an advanced isobaric labeling strategy that incorporates a large amount of content-relevant sample labeled with one isobaric tag channel as an additional boosting channel. This innovation enhances the efficiency of isobaric multiplex reagents for carbonyl-containing compound (SUGAR) tagging in quantitative glycomics. Notably, this approach significantly improves the characterization of low-abundance N-glycans and enables the detection of subtle quantitative differences in N-glycan profiling.

Polysaccharides↗

PubMed2026

High-throughput single-cell proteomics and transcriptomics from same cells with a nanoliter-scale, spin-transfer approach.

Single-cell multiomic platforms provide a comprehensive snapshot of cellular states and cell types by offering critical insights into the spatiotemporal regulation of biomolecular networks at a systems level, thereby defining the basis of multicellularity. Here, we introduce nanoSPINS, an advanced platform that enables high-throughput profiling and integrative analysis of the transcriptome and proteome from the same single cells using RNA sequencing and isobaric labeling LC-MS-based proteomics, respectively. NanoSPINS can efficiently transfer mRNA-containing droplets across two microarrays via a centrifugation-based approach, while proteins are retained on the initial platform. Benchmarking of nanoSPINS on two cell lines demonstrates its ability to generate global proteomic and transcriptomic profiles that align well with previously established methodologies/platforms. The incorporation of isobaric TMTpro labeling into this single-cell multiomics platform significantly enhances the throughput of single-cell proteomic analyses. Through the high-throughput quantification of the proteome and transcriptome, nanoSPINS not only facilitates the identification of molecular features at both mRNA and protein level but also provides larger sample sizes for improved statistical power in clustering and differential abundance. Given the broad applicability of single-cell multiomics in biological research and clinical settings, we believe nanoSPINS represents a powerful platform for the characterization of heterogeneous cell populations.

Single-Cell Analysis↗

PubMed2024

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 healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a 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 highest 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 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Proteome↗

PubMed2025

Spatiotemporally resolved GPCR interactome uncovers unique mediators of receptor agonism.

Cellular signaling by membrane G protein-coupled receptors (GPCRs) is governed by a complex and diverse array of mechanisms. The dynamics of a GPCR interactome, as it evolves over time and space in response to an agonist, provide a unique perspective on pleiotropic signaling decoding and functional selectivity at the cellular level. In this study, we utilized proximity-based APEX2 proteomics to investigate the interaction network of the luteinizing hormone receptor (LHR) on a minute-to-minute timescale. We developed an analytical approach that integrates quantitative multiplexed proteomics with temporal reference profiles, creating a platform to identify the proteomic environment of APEX2-tagged LHR at the nanometer scale. LHR activity is finely regulated spatially, leading to the identification of putative interactors, including the Ras-related GTPase RAP2B, which modulate both receptor signaling and post-endocytic trafficking. This work provides a valuable resource for spatiotemporal nanodomain mapping of LHR interactors across subcellular compartments.

Humans↗