生物化学

Chromatin modifications regulate genome function by recruiting proteins that control transcription, genome organization, and DNA repair. Identifying the proteins associated with specific chromatin modifications is therefore essential for understanding how these regulatory processes operate. Traditional approaches, including chromatin immunoprecipitation and affinity purification coupled to mass spectrometry, have uncovered many chromatin-associated proteins. However, they often rely on crosslinking and chromatin fragmentation, which can disrupt native chromatin architecture and limit the detection of transient interactions. Here, we describe a proximity-labeling protocol for identifying the chromatin-dependent protein interactome associated with specific chromatin marks, termed ChromID. ChromID uses engineered chromatin readers (eCRs) fused to a promiscuous biotin ligase, which labels proteins in the immediate vicinity of the targeted chromatin mark. The protocol includes in vivo biotin labeling, nuclear extract preparation, streptavidin-based enrichment, and tryptic digestion for downstream LC-MS/MS analysis. The protocol has been validated across multiple cell types and chromatin contexts and can be extended to other chromatin-associated proteins, providing a versatile approach to profile chromatin-associated proteomes within their native cellular environment.

Actin filaments undergo dynamic growth and disassembly at their ends, regulated by many actin-binding proteins. However, structural analysis of filament end dynamics has been challenging due to the low abundance of filament ends in cryo-electron microscopy (cryo-EM) micrographs, their intrinsic polymorphisms, and the diversity and flexibility of end-binding proteins. Here, we describe a standardized cryo-EM protocol for determining actin filament end structures. First, short actin filaments are generated either biochemically using capping or severing proteins or mechanically through shearing. Filaments are then vitrified under conditions optimized for each specific end-binding protein. We describe data collection parameters using a 300 kV Titan Krios G3i microscope, including optimized grid preparation and imaging settings. Finally, we present a data processing pipeline for filament end structure determination based on machine learning–based particle picking, masking, and sorting strategies. This protocol has enabled the determination of multiple high-resolution structures of free, capped, elongating, and depolymerizing actin filament ends, and we further discuss considerations for extending this approach to other end-binding proteins.

Cyclic di-AMP is a bacterial second messenger nucleotide required for the regulation of numerous cellular functions, including potassium and osmolyte homeostasis, DNA repair, cell wall integrity, central metabolism, and stress adaptation. This second messenger is synthesized from two ATP molecules by diadenylate cyclases (DAC) and degraded by cytoplasmic and surface-associated phosphodiesterases (PDE) to phosphoadenylyl adenosine (5′ pApA), adenosine monophosphate (AMP), and, in some instances, adenosine and inorganic phosphate (Pi). Levels of c-di-AMP in bacteria can be determined using different methods, including liquid chromatography–mass spectrometry (LC-MS/MS), enzyme-linked immunosorbent assay (ELISA), and luminescent and fluorescent biosensors. Thin-layer chromatography (TLC) is another method routinely used to monitor c-di-AMP synthesis and degradation by purified DAC and PDE enzymes and is particularly useful for monitoring c-di-AMP degradation products. Here, we devised a TLC-based method to monitor extracellular c-di-AMP stability and degradation by intact bacterial cells using radiolabeled c-di-AMP. We show that bacterial strains of Enterococcus faecalis and Streptococcus agalactiae that possess surface-associated PDEs can rapidly degrade extracellular c-di-AMP. In addition, we demonstrate that this method can be used to indirectly identify alternative enzyme substrates through competition assays. We propose that this TLC-based assay is an efficient method to analyze bacterial-mediated degradation of c-di-AMP and is amenable to testing other radiolabeled nucleotides.

Efficient protein synthesis in eukaryotic cells typically requires a 5′ cap structure on messenger RNAs (mRNAs). However, under stress conditions or in viral infection, translation can also occur independently of the cap via internal ribosomal entry sites (IRES). IRES elements are therefore key regulators of protein expression in both viral and cellular contexts. Here, we describe a cell-free protocol to quantitatively assess cap-independent translation using wheat germ extract (WGE) and a firefly luciferase (FLuc) reporter. The protocol includes template preparation, RNA synthesis, and luminescence measurement following in vitro translation in WGE. This method enables rapid and robust comparison of translation activity under controlled conditions and can additionally be applied to evaluate mRNA modifications designed to enhance translation efficiency.

Estimation of model accuracy (EMA) is a critical step in protein structure prediction, enabling the ranking and selection of models in the absence of experimental structures. EMA methods aim to function independently of modeling approaches, ensuring broad applicability across diverse prediction workflows. Recent state-of-the-art EMA methods often improve estimation accuracy by incorporating consensus information from model pools, multiple sequence alignments (MSAs), structural templates, or protein language model representations. However, these strategies typically incur substantial computational cost or rely on information derived from the modeling process itself, which may introduce bias and compromise the independence of the assessment. This protocol describes the use of MViewEMA for global accuracy estimation of protein complex models from a single input structure. MViewEMA extracts residue–residue interaction features from complementary micro-, meso-, and macro-environmental perspectives and integrates multi-scale structural representations through a multi-view representation learning framework to predict global confidence scores. The protocol provides detailed procedures for input structure preparation, feature extraction, model inference, and global confidence score output, together with a tutorial for using the MViewEMA web server. The protocol provides a workflow based solely on structural information from the input model, achieving a balance between computational efficiency and estimation accuracy. It enables large-scale evaluation and selection of predicted models for protein structure prediction and downstream structural analysis applications.

Hepatitis E virus (HEV) is a zoonotic pathogen responsible for approximately 20 million infections annually worldwide. The lack of robust cell culture systems and the absence of approved antiviral therapies have hindered HEV research and drug development. A major technical challenge is the rapid loss of viral infectivity during freeze–thaw cycles following virus purification. Here, we describe a simple and reproducible method to preserve HEV infectivity during storage. We systematically evaluated the effects of salt, serum, and sucrose on viral stability under freezing conditions. We identified an optimized buffer containing 2% fetal bovine serum (FBS), 150 mM NaCl, and 7% sucrose, which significantly maintained the infectivity of non-enveloped HEV (nHEV) and quasi-enveloped HEV (eHEV) following freeze–thaw cycles based on immunofluorescence. The buffer also demonstrated good stability across three independent repeat infection experiments. This protocol provides a practical and scalable approach for maintaining HEV infectivity and will facilitate HEV-related virological studies.

Acid ceramidase (aCDase) is a lysosomal amidase that catalyzes the hydrolysis of sphingolipids (SphL), including ceramides and glucosylceramides. Altered expressions of aCDase are associated with several pathological conditions, such as cancer, inflammation, pain, and pulmonary disorders. aCDase activity is reduced in Farber disease, spinal muscular atrophy with progressive myoclonic epilepsy, diabetes, and cardiovascular disease. Recent reports suggest that aCDase inhibition may be an emerging strategy for treating several SphL-related neurodegenerative conditions, such as Krabbe, Gaucher, and Parkinson’s disease, due to its role in the accumulation of glycosphingolipids. Therefore, the development of a tissue-based aCDase activity assay has potential applications in clinical diagnostics and drug discovery, enabling the evaluation of the onset and progression of disease from biological samples of patients, drug-target engagement analysis, and identification of biomarkers. Here, we report a detailed protocol for detecting aCDase activity in tissue lysates, using Rbm14-12 as a specific fluorogenic substrate for aCDase. Assay protocol optimization, including a procedure for the preparation and storage of tissue lysates and the identification of optimal protein tissue lysate amounts and substrate concentrations based on kinetic enzymatic parameter analyses, is described.

Progressive neurodegeneration linked to the accumulation of misfolded proteins is a hallmark of several neurodegenerative disorders, including Parkinson’s disease, Huntington’s disease, and Alzheimer’s disease. Dysfunction in the protein homeostasis machinery correlates with pathology. The chaperone protein DNAJB6 is expressed in neurons and oligodendrocytes and has been shown to play a key role in preventing amyloid aggregation by binding to amyloidogenic proteins and facilitating their refolding or degradation, in cooperation with other chaperones. Here, we describe a simple and feasible assay that enables high-throughput screening for DNAJB6 activity in a plate reader format. We use genetically engineered HEK293 cells that stably express DNAJB6 fused to either CFP or YFP. These cells can be plated into multi-well plates, and the fluorescence resonance energy transfer (FRET) signal can be measured for analysis of DNAJB6 dimerization, which is linked to DNAJB6 activity. The protocol can be used for drug screening and to identify compounds that increase DNAJB6 dimerization, and can serve as a starting point for finding new medicines that act through modulating DNAJB6 activity.

Ribonucleoprotein (RNP) condensates are membraneless organelles that exist alongside many RNA-driven processes, such as transcription and splicing. Despite their ubiquity, the biological necessity of forming a condensed phase remains unclear, particularly because the same RNP components exist both within these organelles and in the surrounding dilute phase. Most current methods for studying biochemical interaction dynamics within condensates rely on in vitro reconstitution of minimal factors or low-throughput single-molecule studies. However, RNP condensates are complex organelles containing tens to hundreds of proteins and hundreds to thousands of different RNAs. Here, we describe a scalable, high-throughput fluorescence microscopy–based approach to analyze protein–protein interaction networks, allowing for the rigorous assessment of dynamic, process-critical interactions within RNP condensates from live cells. This method takes advantage of fluorescence lifetime imaging (FLIM) and phasor plot analysis to automate segmentation of condensate-localized fluorescence signals. Using suitable FLIM–Förster resonant energy transfer (FLIM-FRET) fluorescent pairs fused to proteins of interest, protein–protein interactions can be actively monitored throughout various conditions via changes in fluorescence lifetime. Results from this assay yield valuable insight into the organization and assembly of essential factors for different condensate-associated processes to infer the functional consequences of RNP granule partitioning. Although this protocol is tailored for studying protein interactions within condensates, the design and execution framework can be adapted to investigate protein–protein interactions across a wide variety of compartments within different biological systems.

Small ubiquitin-like modification (SUMOylation) is a crucial post-translational modification that modulates protein stability, localization, and interaction dynamics. Despite the identification of thousands of putative small ubiquitin-like modifier (SUMO) substrates, functional validation remains challenging due to the low abundance and highly dynamic nature of SUMOylated proteins. Here, we present a protocol for detecting protein SUMOylation, integrating bioinformatic site prediction, and rapid substrate screening via in vivo tobacco transient expression and in vitro E. coli assay, followed by precise validation using transgenic Arabidopsis lines. However, detection of low-abundance SUMOylated proteins may require coupling with mass spectrometry, and the in vitro system does not fully recapitulate the complex regulatory network in vivo. This workflow provides a useful tool for studying SUMOylation in plants.