生物化学

Palmitoylation is a crucial post-translational modification, and bioorthogonal chemistry based on azide-alkyne cycloaddition is typically used to verify protein palmitoylation. Traditional copper-catalyzed click chemistry (CuAAC) proceeds with fast kinetics and is widely used, but it requires a copper catalyst and suffers from copper-induced toxicity and nonspecific labeling. By contrast, strain-promoted click chemistry (SPAAC) has slower kinetics but is catalyst-free, offering high specificity, low cytotoxicity, and simple operation. However, SPAAC is mostly applied to live-cell labeling and imaging of known palmitoylated proteins in the field of palmitoylation, and its use in identifying novel palmitoylated proteins is still limited. Here, we present a SPAAC-based method for detecting endogenous protein palmitoylation. Compared with CuAAC, this method eliminates the need for copper catalysts and reducing agents, thereby simplifying the procedure and reducing reagent usage.

Memory is a fundamental process, regulated by protein–protein interactions within neuronal proteome networks. Learning-dependent changes in specific brain regions important for memory have been detected by mass spectrometry, by comparing proteins from animals trained to learn with mock-trained controls. Detection through this method relies on relative protein abundance; brain dissection is readily available for macroscopic animals to spatially control protein identification by mass spectrometry. In the nematode C. elegans, however, such spatial control is limited due to its microscopic size, hindering its utilization in proteomics. A protocol to address this limitation would strengthen an already excellent model to study memory, given that many proteins for learning are evolutionarily conserved in the worm and single-cell expression is uniquely defined across all 302 neurons. We modified existing protocols to enable (i) proximity labeling detection of neuronal proteins in C. elegans and (ii) high-throughput enrichment of these proteins from >3,000 whole worm bodies simultaneously, to assess trained vs. mock-trained proteomes. This involved the biotin ligase enzyme TurboID, which promiscuously labels nearby proteins with its substrate biotin. Enzyme expression was transgenically restricted to the nervous system, and biotin supplementation was limited to the training (or mock training) period in a classical (gustatory) conditioning paradigm. Labeled proteins were enriched by pull-down using streptavidin, which has a high binding affinity to biotin, and then processed for mass spectrometry runs and qualitative data analysis. This protocol is uniquely advantageous in that it minimizes proteins present before a temporal window of interest (training/mock training), improving the detection of lowly abundant proteins from a specific tissue in the worm (neurons). We have demonstrated that the protocol can sufficiently detect novel learning regulators, thus providing a useful framework to interrogate proteomes in microscopic brains.

The transient receptor mucolipin subtype 1 (TRPML1) is a ubiquitously expressed ion channel involved in lysosomal homeostasis. Recent pharmaceutical interest in developing agonist ligands has emerged due to beneficial effects in neurodegenerative diseases. The major high-throughput screening techniques to investigate this ion channel involve fluorescent calcium imaging and electrophysiology. Despite their high capacity for screening compounds, it is well known that both methods face hurdles, such as the need for expensive, specialized equipment. Here, we present a novel technique to screen for ligands of TRPML1 using a bioluminescence resonance energy transfer (BRET) assay. This assay consists of a target engagement assay in live cells, which permits the determination of binding constants between ligands and the target of interest in equilibrium or time-dependently. We employ a full-length TRPML1 C-terminally tagged with the small bioluminescent protein nanoluciferase. This ensures the correct localization of the ion channel in the lysosomal membrane and an optimal placement of the luciferase in the cytoplasm. We also developed a cell- and lysosome-permeable fluorescent BRET tracer that gives a BRET signal only when bound to the ion channel. This new protocol allows researchers worldwide to screen compounds that would interact with TRPML1 by using any plate reader with luminescent and fluorescence filters.

ADP ribosylation (ADPr) is a crucial post-translational modification that plays a vital role in DNA damage repair. Catalyzed by ADP ribose polymerases using NAD⁺ as a substrate, ADPr activates DNA repair pathways rapidly, thereby maintaining genomic integrity. The involvement of ADP ribose hydrolases in this process is significant, as they hydrolyze PAR chains, facilitating the release of ADPr-modified proteins from DNA or other proteins, which is essential for subsequent DNA repair steps. This protocol outlines a high-throughput screening method for identifying inhibitors of ADP ribose hydrolases, utilizing His-Tb-conjugated and ADPr-modified His-ADP ribose polymerase as the signal donor, and GST-d2-conjugated GST-XRCC1 as the signal receptor. The detection of time-resolved fluorescence signals enables efficient evaluation of compounds with potential therapeutic activity against cancer.

Nucleases are key tools in molecular biology, enabling controlled nucleic acid digestion for applications such as ribosome profiling. Micrococcal nuclease (MNase) from Staphylococcus aureus is widely used as a tool in molecular biology and biochemistry, but its reduced activity under high-salt conditions necessitates higher enzyme input to achieve efficient digestion, increasing costs in studies of halophilic organisms. Here, we present an optimized protocol for the heterologous expression and purification of the recombinant staphylococcal MNase. The procedure enables reproducible production of a highly active, stable enzyme and incorporates an enzymatic activity assay to standardize batches to minimize variability. The resulting MNase exhibits robust activity in high-salt environments and remains stable during storage, providing a cost-effective and reliable alternative to commercial nucleases for ribosome profiling and related applications.

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.