Systems Biology

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.

Within a cell, proteins have distinct and highly variable half-lives. As a result, the molecular ages of proteins can range from seconds to years. How the age of a protein influences its environmental interactions is a largely unexplored area of biology. To facilitate such studies, we recently developed a technique termed “proteome birthdating” that differentially labels proteins based on their time of synthesis. Proteome birthdating enables analyses of age distributions of the proteome by tandem mass spectrometry (LC–MS/MS) and provides a methodology for investigating the protein age selectivity of diverse cellular pathways. Proteome birthdating can also provide measurements of protein turnover kinetics from single, sequentially labeled samples. Here, we provide a practical guide for conducting proteome birthdating in in vitro model systems. The outlined workflow covers cell culture, isotopic labeling, protein extraction, enzymatic digestion, peptide cleanup, mass spectrometry, data processing, and theoretical considerations for interpretation of the resulting data.

Plants rely on metabolite regulation of proteins to control their metabolism and adapt to environmental changes, but studying these complex interaction networks remains challenging. The proteome integral solubility alteration (PISA) assay, a high-throughput chemoproteomic technique, was originally developed for mammalian systems to investigate drug targets. PISA detects changes in protein stability upon interaction with small molecules, quantified through LC–MS. Here, we present an adapted PISA protocol for Arabidopsis thaliana chloroplasts to identify potential protein interactions with ascorbate. Chloroplasts are extracted using a linear Percoll gradient, treated with multiple ascorbate concentrations, and subjected to heat-induced protein denaturation. Soluble proteins are extracted via ultracentrifugation, and proteome-wide stability changes are quantified using multiplexed LC–MS. We provide instructions for deconvolution of LC–MS spectra and statistical analysis using freely available software. This protocol enables unbiased screening of protein regulation by small molecules in plants without requiring prior knowledge of interaction partners, chemical probe design, or genetic modifications.

Known as the cell’s antenna and signaling hub, the primary cilium is a hair-like organelle with a few micrometers in length and 200–300 nm in diameter. Due to the small size of the primary cilium, it is technically challenging to profile ciliary proteins from mammalian cells. Traditional methods, such as physical isolation of cilia, are susceptible to contamination from other cellular components. Other proximity-based labeling methods via APEX or BioID have been used to map ciliary proteins. However, these approaches have their inherent limitations, including the use of toxic reagents like H₂O₂ and prolonged labeling kinetics. Here, we show a new proximity-based labeling technique for primary cilia with TurboID. TurboID presents a distinct advantage over BioID and APEX2 due to its expedited labeling kinetics, taking minutes instead of hours, and its use of a non-toxic biotin substrate, which eliminates the need for H₂O₂. When targeted to the cilium, TurboID selectively labels ciliary proteins with biotin. The biotinylated proteins are then enriched with streptavidin beads and labeled with tandem mass tags (TMT), followed by mass spectrometry (MS) detection. This protocol eliminates the requirement of toxic labeling reagents and significantly reduces the labeling time, thus providing advantages in mapping signaling proteins with high temporal resolution in live cells.

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.