系统生物学

The cellular secretome is a rich source of biomarkers and extracellular signaling molecules, but proteomic profiling remains challenging, especially when processing culture volumes greater than 5 mL. Low protein abundance, high serum contamination, and sample loss during preparation limit reproducibility and sensitivity in mass spectrometry–based workflows. Here, we present an optimized and scalable protocol that integrates (i) 50 kDa molecular weight cutoff ultrafiltration, (ii) spin column depletion of abundant serum proteins, and (iii) acetone/TCA precipitation for protein recovery. This workflow enables balanced recovery of both low- and high-molecular-weight proteins while reducing background from serum albumin, thereby improving sensitivity, reproducibility, and dynamic range for LC–MS/MS analysis. Validated in human mesenchymal stromal cell cultures, the protocol is broadly applicable across diverse cell types and experimental designs, making it well-suited for biomarker discovery and extracellular proteomics.

Protein S-nitrosylation is a critical post-translational modification that regulates diverse cellular functions and signaling pathways. Although various biochemical methods have been developed to detect S-nitrosylated proteins, many suffer from limited specificity and sensitivity. Here, we describe a robust protocol that combines a modified biotin-switch technique (BST) with streptavidin-based affinity enrichment and quantitative mass spectrometry to detect and profile nitrosylated proteins in cultured cells. The method involves blocking free thiols, selective reduction of nitrosothiols, biotin labeling, enrichment of biotinylated proteins, and identification by tandem mass tag (TMT)-based quantitative mass spectrometry. Additionally, site-directed mutagenesis is employed to generate “non-nitrosylable” mutants for functional validation of specific nitrosylation sites. This protocol provides high specificity, quantitative capability, and versatility for both targeted and global analysis of protein nitrosylation.

In plants, the apoplast contains a diverse set of proteins that underpin mechanisms for maintaining cell homeostasis, cell wall remodeling, cell signaling, and pathogen defense. Apoplast protein composition is highly regulated, primarily through the control of secretory traffic in response to endogenous and environmental factors. Dynamic changes in apoplast proteome facilitate plant survival in a changing climate. Even so, the apoplast proteome profiles in plants remain poorly characterized due to technological limitations. Recent progress in quantitative proteomics has significantly advanced the resolution of proteomic profiling in mammalian systems and has the potential for application in plant systems. In this protocol, we provide a detailed and efficient protocol for tandem mass tag (TMT)-based quantitative analysis of Arabidopsis thaliana secretory proteome to resolve dynamic changes in leaf apoplast proteome profiles. The protocol employs apoplast flush collection followed by protein cleaning using filter-aided sample preparation (FASP), protein digestion, TMT-labeling of peptides, and mass spectrometry (MS) analysis. Subsequent data analysis for peptide detection and quantification uses Proteome Discoverer software (PD) 3.0. Additionally, we have incorporated in silico–generated spectral libraries using PD 3.0, which enables rapid and efficient analysis of proteomic data. Our optimized protocol offers a robust framework for quantitative secretory proteomic analysis in plants, with potential applications in functional proteomics and the study of trafficking systems that impact plant growth, survival, and health.

OtUBD is a high-affinity ubiquitin-binding domain (UBD) derived from a large protein produced by the microorganism Orientia tsutsugamushi. The following protocol describes a step-by-step process for the enrichment of ubiquitinated proteins from baker's yeast and mammalian cell lysates using OtUBD. The OtUBD affinity resin can strongly enrich both mono- and poly-ubiquitinated proteins from crude lysates. The protocol further describes the use of different buffer formulations to specifically enrich for proteins covalently modified by ubiquitin with or without proteins that associate with them. Combining different OtUBD-mediated enrichment protocols with liquid chromatography–tandem mass spectrometry (LC–MS/MS) helps distinguish the pool of covalently ubiquitinated proteins (the ubiquitinome) from ubiquitin- or ubiquitinated protein-interacting proteins (the ubiquitin interactome). The OtUBD tool described in the protocol has been used successfully with downstream applications such as immunoblotting and differential proteomics. It provides researchers with a versatile and economical tool for the study of ubiquitin biology.

Brain endothelial cells, which constitute the cerebrovasculature, form the first interface between the blood and brain and play essential roles in maintaining central nervous system (CNS) homeostasis. These cells exhibit strong apicobasal polarity, with distinct luminal and abluminal membrane compositions that crucially mediate compartmentalized functions of the vasculature. Existing transcriptomic and proteomic profiling techniques often lack the spatial resolution to discriminate between these membrane compartments, limiting insights into their distinct molecular compositions and functions. To overcome these limitations, we developed an in vivo proteomic strategy to selectively label and enrich luminal cerebrovascular proteins. In this approach, we perfuse a membrane-impermeable biotinylation reagent into the vasculature to covalently tag cell surface proteins exposed on the luminal side. This is followed by microvessel isolation and streptavidin-based enrichment of biotinylated proteins for downstream mass spectrometry analysis. Using this method, we robustly identified over 1,000 luminally localized proteins via standard liquid chromatography–tandem mass spectrometry (LC–MS/MS) techniques, achieving substantially improved enrichment of canonical luminal markers compared with conventional vascular proteomic approaches. Our method enables the generation of a high-confidence, compartment-resolved atlas of the luminal cerebrovascular proteome and offers a scalable platform for investigating endothelial surface biology in both healthy and disease contexts.

This manuscript details protocols for the ZnCl₂ precipitation-assisted sample preparation (ZASP) for proteomic analysis. By inducing protein precipitation with ZASP precipitation buffer (ZPB, final concentration of ZnCl ₂ at 100 mM and 50% methanol), ZASP depletes harsh detergents and impurities, such as sodium dodecyl sulfate (SDS), Triton X-100, and urea, at high concentrations in solution from protein solutions prior to trypsin digestion. It is a practical, robust, and cost-effective approach for proteomic sample preparation. It has been observed that 90.2% of the proteins can be recovered from lysates by incubating with an equal volume of ZPB at room temperature for 10 min. In 1 h of data-dependent acquisition (DDA) analysis on an Exploris 480, 4,037 proteins and 25,626 peptides were quantified from 1 μg of mouse small intestine proteins, reaching a peak of 4,500 proteins and up to 30,000 peptides with 5 μg of input. Additionally, ZASP outperformed other common sample preparation methods such as sodium deoxycholate (SDC)-based in-solution digestion, acetone precipitation, filter-aided sample preparation (FASP), and single-pot, solid-phase-enhanced sample preparation (SP3). It demonstrated superior performance in protein (4,456 proteins) and peptide identification (29,871 peptides), lower missing cleavage rates (16.3%), and high reproducibility (Pearson correlation coefficients of 0.96 between replicates) with similar protein distributions and cellular localization patterns. Significantly, the cost of ZASP per sample with 100 μg of protein as input is lower than 30 RMB, including the expense of trypsin.

Glioblastoma (GBM) is the most aggressive brain tumor, and different efforts have been employed in the search for new drugs and therapeutic protocols for GBM. A label-free, mass spectrometry–based quantitative proteomics has been developed to identify and characterize proteins that are differentially expressed in GBM to gain a better understanding of the interactions and functions that lead to the pathological state focusing on the extracellular matrix (ECM). The main challenge in GBM research has been to identify novel molecular therapeutic targets and accurate diagnostic/prognostic biomarkers. To better investigate the GBM secretome upon in vitro treatment with histone deacetylase inhibitor (iHDAC), we employed a high-throughput label-free methodology of protein identification and quantification based on mass spectrometry followed by in silico studies. Our analysis revealed significant changes in the ECM protein profile, particularly those associated with the angiogenic matrisome. Proteins such as decorin, ADAM10, ADAM12, and ADAM15 were differentially regulated upon in silico analysis. In contrast, key angiogenesis markers such as VEGF and ECM proteins like fibronectin and integrins did not display significant changes. These results suggest that iHDAC inhibitors may modulate or suppress tumor behavior growth by targeting ECM proteins’ secretion rather than directly inhibiting angiogenesis.

Proteomics analysis is crucial for understanding the molecular mechanisms underlying muscle adaptations to different types of exercise, such as concentric and eccentric training. Traditional methods like two-dimensional gel electrophoresis and standard mass spectrometry have been used to analyze muscle protein content and modifications. This protocol details the preparation of muscle samples for proteomics analysis using ultra-high-performance liquid chromatography (UHPLC). It includes steps for muscle biopsy collection, protein extraction, digestion, and UHPLC-based analysis. The UHPLC method offers high-resolution separation of complex protein mixtures, providing more detailed and accurate proteomic profiles compared to conventional techniques. This protocol significantly enhances sensitivity, reproducibility, and efficiency, making it ideal for comprehensive muscle proteomics studies.

The extracellular matrix (ECM) is a complex network of proteins that provides structural support and biochemical cues to cells within tissues. Characterizing ECM composition is critical for understanding this tissue component’s roles in development, homeostasis, and disease processes. This protocol describes an integrated pipeline for profiling both cellular and ECM proteins across varied tissue types using mass spectrometry–based proteomics. The workflow covers stepwise extraction of cellular and extracellular proteins, enzymatic digestion into peptides, peptide cleanup, mass spectrometry analysis, and bioinformatic data processing. The key advantages include unbiased coverage of cellular, ECM-associated, and core-ECM proteins, including the fraction of ECM that cannot be solubilized using strong chaotropic agents such as urea or guanidine hydrochloride. Additionally, the method has been optimized for reproducible ECM enrichment and quantification across diverse tissue samples. This protocol enables systematic mapping of the ECM at a proteome-wide scale.

Bottom-up proteomics utilizes sample preparation techniques to enzymatically digest proteins, thereby generating identifiable and quantifiable peptides. Proteomics integrates with other omics methodologies, such as genomics and transcriptomics, to elucidate biomarkers associated with diseases and responses to drug or biologics treatment. The methodologies employed for preparing proteomic samples for mass spectrometry analysis exhibit variability across several factors, including the composition of lysis buffer detergents, homogenization techniques, protein extraction and precipitation methodologies, alkylation strategies, and the selection of digestion enzymes. The general workflow for bottom-up proteomics consists of sample preparation, mass spectrometric data acquisition (LC-MS/MS analysis), and subsequent downstream data analysis including protein quantification and differential expression analysis. Sample preparation poses a persistent challenge due to issues such as low reproducibility and inherent procedure complexities. Herein, we have developed a validated chloroform/methanol sample preparation protocol to obtain reproducible peptide mixtures from both rodent tissue and human cell line samples for bottom-up proteomics analysis. The protocol we established may facilitate the standardization of bottom-up proteomics workflows, thereby enhancing the acquisition of reliable biologically and/or clinically relevant proteomic data.