Anthocyanins are specialized flavonoid pigments that play critical roles in plant coloration, photoprotection, and responses to environmental stress. Arabidopsis thaliana serves as a valuable genetic model for dissecting anthocyanin biosynthesis and regulatory networks. Conventional methods for anthocyanin quantification, such as crude spectrophotometric assays, often compromise pigment integrity, yield inconsistent results, and provide limited information on compound composition. Here, we describe a simple, reproducible, and high-fidelity protocol for the induction, extraction, quantification, and chromatographic profiling of anthocyanins in Arabidopsis thaliana seedlings. The workflow employs well-defined anthocyanin-inductive conditions (AIC), methanol/formic acid extraction, lyophilization for dry-weight normalization, and dual quantification via spectrophotometry and High-performance liquid chromatography with diode-array detection (HPLC-DAD) analysis. This protocol enables accurate comparison between wild-type and mutant genotypes, facilitating both mutant screening and metabolic pathway analysis. The approach minimizes pigment degradation, enhances reproducibility across replicates, and offers a robust tool for research in plant metabolism, stress physiology, and flavonoid biochemistry.

Organelle abundance is a key microscopic readout of organelle formation and, in many cases, function. Quantification of organelle abundance using confocal microscopy requires estimating their area based on the fluorescence intensity of compartment-specific markers. This analysis usually depends on a user-defined intensity threshold to distinguish organelle regions from the surrounding cytoplasm, which introduces potential bias and variability. To address this issue, we present a machine learning–assisted algorithm that allows for the quantification of organelle density using the open-source Fiji platform and WEKA segmentation. Our method enables the automated quantification of organelle number, area, and density by learning from training data. This standardizes threshold selection and minimizes user intervention. We demonstrate the utility of this approach for both membrane and non-membrane organelles, such as peroxisomes, lipid droplets, and stress granules, in human cells and whole fish samples.

Amphibian retinas contain “green” rods, which are rod-shaped photoreceptors with a cone-type visual pigment. These rods are considered a potentially transitional photoreceptor type, but their phototransduction cascade’s molecular composition has remained uncertain. Here, we present a streamlined electrophysiology-molecular workflow that enables the rapid spectral identification, physical capture, and targeted single-cell reverse transcription-polymerase chain reaction (RT-PCR) of individual amphibian photoreceptors. After suction-pipette spectral screening under alternating red and green illumination, electrophysiologically identified cells are isolated and processed directly for reverse transcription and PCR. Coupling real-time functional phenotyping with sensitive molecular profiling provides a practical tool for resolving photoreceptor molecular heterogeneity and investigating evolutionary transitions between rod and cone phenotypes.

This protocol describes an easy, quick, cheap, and effective method for the purification and concentration of bacteriophages (phages) produced in rich culture media, meeting the quality criteria required for structural analyses. It is based on a tube dialysis system that replaces the classical but expensive and tedious density gradient ultracentrifugation step. We developed this protocol for the Oenococcus oeni bacteriophage OE33PA from its amplification to imaging by negative stain electron microscopy (NS-EM). The host bacterium, O. oeni, is a lactic acid bacterium that lives in harsh oenological ecosystems and grows only in rich and complex media such as Man–Rogosa–Sharpe (MRS) or fruit juice-based media in laboratory conditions. This raises experimental challenges in pure and concentrated phage preparations for further uses such as structure-function studies.

The deletion and mutation of Topoisomerase 3β (TOP3B) is linked to multiple neurological disorders and is the only known topoisomerase that is also catalytically active on RNA in vitro and in cells. Uniquely, TOP3B is primarily localized to the cytoplasm, binds to open reading frames of mRNA, and regulates mRNA stability and translation in a transcript-specific manner. A common approach for studying TOP3B activity in cells is immunodetection of TOP3B•RNA covalent intermediates after bulk RNA isolation. However, in this approach, the RNA species is unknown and is not selective for the major TOP3B substrate, mRNA. In this protocol, we describe a recently developed and optimized protocol for capturing TOP3B•mRNA covalent intermediates using oligo-dT isolation of mRNA under protein-denaturing conditions. Covalent intermediates are then detected by a dual membrane slot blotting strategy with nitrocellulose and positively charged nylon membranes. Nitrocellulose membrane-bound TOP3B•mRNA covalent intermediates are analyzed by immunodetection, and nylon membrane-bound free mRNA is stained with methylene blue. The protocol detailed below has been validated with wildtype and mutant 3xFLAG-tagged TOP3B expressed in Neuro2A cells, with additional optimization for slot blotting using recombinant EGFP.

ADGRL4 is an adhesion G protein–coupled receptor (aGPCR) implicated in multiple tumours. In our experience, conventional insect cell-based baculovirus expression systems have not yielded sufficient correctly folded ADGRL4 protein for purification and cryo-electron microscopy (cryo-EM) analysis. Here, we describe aGPCR-HEK, a six-week protocol that establishes stable tetracycline-inducible mammalian HEK293S GnTI- TetR cell lines expressing N-terminally HA- and GFP-tagged aGPCRs. The method comprises lentiviral production in Lenti-X 293T cells, transduction of target adherent HEK293S GnTI- TetR cells, flow cytometry enrichment of uninduced GFP-positive cells displaying leaky expression, adaptation to suspension culture, and large-scale tetracycline induction and harvesting of cells for downstream purification and cryo-EM. The system yields reproducible, milligram-scale quantities of folded aGPCR suitable for structural and biochemical studies.

Spatial proteomics enables the mapping of protein distribution within tissues, which is crucial for understanding cellular functions in their native context. While spatial transcriptomics has seen rapid advancement, spatial proteomics faces challenges due to protein non-amplifiability and mass spectrometry sensitivity limitations. This protocol describes a sparse sampling strategy for spatial proteomics (S4P) that combines multi-angle tissue strip microdissection with deep learning–based image reconstruction. The method achieves whole-tissue slice coverage with significantly reduced sampling requirements, enabling mapping of over 9,000 proteins in mouse brain tissue at 525 μm resolution within 200 h of mass spectrometry time. Key advantages include reduced sample processing time, deep proteome coverage, and applicability to centimeter-sized tissue samples.

Evaluating single-domain antibody cooperativity is essential for developing potent, escape-resistant antiviral biologics. Here, we present a protocol that reproducibly quantifies functional synergy between neutralizing nanobody pairs in standardized viral infectivity assays. Controlled automated liquid handling prepares two-dimensional concentration matrices, minimizing pipetting variance and systematic error. Neutralization data are fitted using quantitative models that independently estimate potency, cooperativity, and efficacy to distinguish additive, synergistic, and antagonistic effects between nanobody pairs. Replicated measurements enable statistically interpretable parameter estimates, supporting robust evaluation of combinatorial nanobody therapeutics with commonly available equipment and open-source analysis tools. This framework is broadly applicable to assessing cooperative effects among other classes of binding or inhibitory molecules, facilitating systematic discovery of synergistic combinations.

RNA-binding proteins (RBPs) have pleiotropic roles in modulating the physiology of both eukaryotic and prokaryotic cells, enabling them to adapt to environmental variations. The importance of RBPs has led to the development of a variety of methods aiming to identify them. However, most of these approaches have primarily been implemented and optimized in eukaryotic systems. To both uncover novel RBPs involved in Bacillus subtilis sporulation and capture their RNA-binding ability dynamically, we adapted the orthogonal organic phase separation technique (OOPS), which had previously been used in Escherichia coli to reveal its RNA-binding proteome (RBPome). We optimized the UV cross-linking process used to stabilize RNA–protein interactions in vivo and the bacterial lysis process to overcome the robust cell wall of Gram-positive sporulating cells. RNA–protein complexes are then recovered after phase separation steps using guanidinium thiocyanate–phenol–chloroform, and RNA-associated proteins are identified and label-free-quantified by liquid chromatography–mass spectrometry. Collecting samples at various time points during sporulation further enables tracking the dynamics of the RBPome. In addition to being applicable to bacteria and requiring minimal starting material, this method has provided a comprehensive map of the RBPome during sporulation, refining the roles of known factors and revealing new players.

Serial spatial omics technologies capture genome-wide gene expression patterns in thin tissue sections but lose spatial continuity along the third dimension. Reconstructing these two-dimensional measurements into coherent three-dimensional volumes is necessary to relate molecular domains, gradients, and tissue architecture within whole organs or embryos. sc3D is an open-source Python framework that registers consecutive spatial transcriptomic sections, interpolates bead coordinates in three dimensions, and stores the result in an AnnData object compatible with Scanpy. The workflow performs slice alignment, 3D reconstruction, optional downsampling, and interactive visualization in a napari-sc3D-viewer, enabling virtual in situ hybridization and spatial differential gene expression analysis. We tested sc3D on Slide-seq and Stereo-seq datasets, including E8.5 and E16.5 mouse embryos, recovering continuous tissue morphologies, cardiac anatomical markers, and the expected anterior–posterior gradients of Hox gene expression. These results show that sc3D allows reproducible reconstruction and analysis of volumetric spatial omics data across different samples and experimental platforms.

Endocytosis is an essential membrane transport mechanism that is indispensable for the maintenance of life. It is responsible for the selective internalization and subsequent degradation or recycling of specific extracellular proteins and nutrients, thereby facilitating cellular nutrient supply, modulation of receptor signaling, and clearance of foreign substances. However, methods for the quantitative analysis of lysosomal degradation of extracellular proteins via endocytosis remain limited. This protocol describes a method for purifying the protein-of-interest (POI)–red fluorescent protein (RFP)–green fluorescent protein (GFP) fusion protein, which is modified with specific mammalian cell glycans or other modifications, from the conditioned medium of mammalian cell cultures. Subsequently, the protocol details a quantitative approach for evaluating its internalization and lysosomal degradation within cells using the RFP–GFP tandem fluorescent reporter. Following the addition of POI-RFP-GFP to the medium, cells can be subjected to cell biological assays, such as flow cytometry, as well as biochemical analyses, such as immunoblotting. This protocol is broadly applicable to studies of the internalization of extracellular proteins.

The morphology of single-neuron axonal projections is critical for deciphering neural circuitry and information flow in the brain. Yet, manually reconstructing these complex, long-range projections from high-throughput whole-brain imaging data remains an exceptionally labor-intensive and time-consuming task. Here, we developed a points assignment-based method for axonal reconstruction, named PointTree. PointTree enables the precise identification of the individual axons from densely packed axonal population using a minimal information flow tree model to suppress the snowball effect of reconstruction errors. In this protocol, we have elaborated on how to configure the required environment for PointTree software, prepare suitable data for it, and run the software. This protocol can assist neuroscience researchers in more easily and rapidly obtaining the reconstruction results of neuronal axons.

Prostate carcinoma (PCa) progression is strongly influenced by the surrounding tumor microenvironment, where cancer-associated fibroblasts (CAFs) represent the most abundant and functionally relevant stromal population. Despite their importance, the lack of stable cell lines representing CAF phenotypes limits the study of stromal–tumor interactions. To address this limitation, we provide an optimized protocol for isolating CAFs from fresh human PCa biopsies based on a mechanical procedure exploiting the specific CAF ability to migrate out from the tumor explants. This approach preserves tissue architecture and maintains CAF viability and phenotype. The resulting ex vivo CAF cultures provide a suitable model to investigate CAF biology within the tumor microenvironment.

The deep learning revolution has accelerated discovery in cell biology by allowing researchers to outsource their microscopy analyses to a new class of tools called cell segmentation models. The performance of these models, however, is often constrained by the limited availability of annotated data for them to train on. This limitation is a consequence of the time cost associated with annotating training data by hand. To address this bottleneck, we developed Cell-APP (cellular annotation and perception pipeline), a tool that automates the annotation of high-quality training data for transmitted-light (TL) cell segmentation. Cell-APP uses two inputs—paired TL and fluorescence images—and operates in two main steps. First, it extracts each cell’s location from the fluorescence images. Then, it provides these locations to the promptable deep learning model μSAM, which generates cell masks in the TL images. Users may also employ Cell-APP to classify each annotated cell; in this case, Cell-APP extracts user-specified, single-cell features from the fluorescence images, which can then be used for unsupervised classification. These annotations and optional classifications comprise training data for cell segmentation model development. Here, we provide a step-by-step protocol for using Cell-APP to annotate training data and train custom cell segmentation models. This protocol has been used to train deep learning models that simultaneously segment and assign cell-cycle labels to HeLa, U2OS, HT1080, and RPE-1 cells.

Fluorescence in situ hybridization (FISH) can be employed to study the expression and subcellular localization of nucleic acids by using labeled antisense strands that hybridize with the target RNA or DNA molecules. Likewise, immunofluorescence antibody staining (IF) takes advantage of the specific interaction between a fluorophore-labeled antibody and its corresponding antigen. This protocol reports the combination of RNA-FISH and IF antibody staining for simultaneous detection of both RNA transcripts and proteins of interest in routine formalin-fixed paraffin-embedded (FFPE) bone marrow biopsy samples. Herein, we provide a detailed description of the methodology that we have developed and optimized to study the spatial expression of two transcripts—TGFB1 and PDGFA1—in human hematopoietic (CD45⁺) and non-hematopoietic (CD271⁺) cells in the bone marrow of patients with acute lymphoblastic leukemia (ALL).

RNA-binding protein (RBP)–RNA interactions are fundamental for gene regulation and cellular homeostasis. Ataxin-2 is an RBP that has been shown to play an instrumental role in pathophysiological processes by binding to mRNA. Methods such as RNA immunoprecipitation (RIP), cross-linking immunoprecipitation (CLIP), and their variants can be used to study the interactions between Ataxin-2 and its targets, although their high sample requirements and labor-intensive workflows can limit their widespread use. RNA editing-based approaches, such as targets of RBPs identified by editing (TRIBE), provide effective alternatives. TRIBE enables transcriptome-wide identification of RBP targets by inducing site-specific adenosine-to-inosine (A-to-I) editing, which is subsequently detected through high-throughput RNA sequencing in both in vivo and in vitro systems. Compared to in vivo models, cell lines offer a rapid and flexible experimental design. Drosophila S2 cells are a commonly used insect cell line to investigate RNA–protein dynamics and serve as a versatile platform for studying RBP function. Here, we describe a protocol used for identifying RNA targets of Ataxin-2, a versatile RBP involved in post-transcriptional and translational regulation, in S2 cells using TRIBE. This method allows rapid, efficient, and reliable identification of Ataxin-2-associated RNA targets and can be readily applied to other RBPs.

The cellular compartments of eukaryotic cells are defined by their specific protein compositions. Different strategies are used for the identification of the subcellular proteomes, such as fractionation by differential centrifugation of cellular extracts. The localization of mitochondrial proteins is particularly challenging, as mitochondria consist of two membranes of different protein composition and two aqueous subcompartments, the intermembrane space (IMS) and the matrix. Previous studies identified subcompartment-specific proteomes by using combinations of hypotonic swelling and protease digestion followed by mass spectrometry. Here, we present an alternative, more unbiased method to identify the proteomes of mitochondrial subcompartments by use of an improved ascorbate peroxidase (APEX2) that is targeted to the IMS and the matrix. This method allows the subcompartment-specific labeling of proteins in mitochondria isolated from cells of the baker’s yeast Saccharomyces cerevisiae, followed by their purification on streptavidin beads. With this method, the proteins located in the different mitochondrial subcompartments of yeast cells can be efficiently and comprehensively identified.

ADGRL4 is an adhesion G protein-coupled receptor (aGPCR) implicated in tumour progression in multiple malignancies. We recently determined the first cryo-EM structure of active-state ADGRL4, revealing its weak coupling to the heterotrimeric G protein G_q and providing insights into its activation mechanism. Here, we describe a complete modular workflow for purifying active-state ADGRL4 over 2–3 days using a multifunctional tagging strategy incorporating multiple orthogonal detection, purification, and cleavage tags at the N-terminus as well as a tethered mini-G_q at the C-terminus. This configuration enhanced receptor cell-surface expression and stability and allowed different purification strategies to be tested during the development of the purification protocol. Although developed and optimised for ADGRL4, this approach is readily transferable to other weakly coupling aGPCRs or GPCRs where complex stability is a limiting factor for structural analysis.

Obesity is a risk factor for many diseases. The 3T3-L1 cell line is often used to obtain mature adipocytes, but these lack the inflammatory phenotype observed in obesity. Using a cocktail of cytokines that mimics the secretome of macrophages found in the inflammatory adipose tissue, we developed a protocol for obtaining mature inflammatory adipocytes. This model was validated at gene (RT-qPCR) and protein levels (multiplex adipokine array) as we found a decrease of adipogenic markers (C/EBPα, PPARУ, adiponectin, and CD36) and an increase of pro-inflammatory cytokines (IL-6, IL-1β, CXCL1, CXCL10, TNF-α, ICAM-1, and lipocalin-2). We provide a relevant in vitro model for studying the impact of low-grade chronic inflammation caused by obesity and its downstream effects on metabolic disorders and tumor microenvironments.

Membrane-less organelles play essential roles in both physiological and pathological processes by compartmentalizing biomolecules through phase separation to form dynamic hubs. These hubs enable rapid responses to cellular stress and help maintain cellular homeostasis. However, a straightforward and efficient method for detecting and illustrating the distribution and diversity of RNA species within membrane-less organelles is still highly sought after. In this study, we present a detailed protocol for in situ profiling of RNA subcellular localization using Target Transcript Amplification and Sequencing (TATA-seq). Specifically, TATA-seq employs a primary antibody against a marker protein of the target organelle to recruit a secondary antibody conjugated with streptavidin, which binds an oligonucleotide containing a T7 promoter. This design enables targeted, in situ reverse transcription of RNAs with minimal background noise, a key advantage further refined during data analysis by subtracting signals obtained from a parallel IgG control experiment. The subsequent T7 RNA polymerase-mediated linear amplification ensures high-fidelity RNA amplification from low-input material, which directly contributes to optimized sequencing metrics, including a duplication rate of no more than 25% and a mapping ratio of approximately 90%. Furthermore, the modular design of TATA-seq provides broad compatibility with diverse organelles. While initially developed for membrane-less organelles, the protocol can be readily adapted to profile RNA in other subcellular compartments, such as nuclear speckles and paraspeckles, under both normal and pathogenic conditions, offering a versatile tool for spatial transcriptomics.

SLIT2 is a secreted glycoprotein implicated in axon guidance, immune modulation, and tumor biology, whose extracellular and glycosylated nature can complicate conventional biophysical screening workflows. Here, we provide a complete, step-by-step protocol for an orthogonal high-throughput discovery pipeline that integrates temperature-related intensity change (TRIC) as a solution-based primary binding screen with time-resolved Förster resonance energy transfer (TR-FRET, homogeneous time-resolved fluorescence format) as a functional assay for inhibition of the SLIT2–ROBO1 interaction. The workflow is designed to be fast and convenient, uses low reaction volumes and low nanomolar protein concentrations to minimize material use, and includes built-in quality control steps to support reproducible hit triage. In TRIC (NanoTemper Dianthus), binding is detected as temperature-dependent fluorescence intensity changes of a labeled target protein under an infrared (IR)-mediated thermal gradient, enabling immobilization-free detection of small-molecule interactions and instrument-assisted filtering of autofluorescent, quenching, or aggregating compounds. Candidate binders are advanced to multi-point TRIC/microscale thermophoresis (MST) measurements on Monolith X to determine binding affinity (Kd). In TR-FRET, disruption of SLIT2–ROBO1 association is quantified by changes in the ratiometric 665/620 nm emission readout, measured with a time delay to suppress short-lived background fluorescence, enabling concentration-response analysis and reporting of relative IC₅₀ values (including partial inhibition behavior where applicable). Although presented using the SLIT2–ROBO1 extracellular interaction as a representative model system, this orthogonal screening strategy is designed to be adaptable to other extracellular protein-protein interactions where minimizing immobilization artifacts and fluorescence interference is critical.

Mitophagy is a highly conserved process among eukaryotic cells, playing a primordial role in mitochondrial quality control and overall cellular homeostasis. In Saccharomyces cerevisiae, Atg32 is the only identified mitophagy receptor localized to the mitochondrial outer membrane, making this yeast a particularly powerful model for molecular studies of mitophagy that require the isolation of intact mitochondria. However, traditional methods for isolating mitochondria from yeast often rely on enzymatic cell wall digestion and homogenization, which can compromise the stability of mitochondrial surface proteins such as Atg32. In this protocol, we describe an optimized mechanical approach for yeast cell disruption using glass beads in a cold, protease-inhibited buffer to preserve mitochondrial integrity and facilitate the detection of Atg32. Subsequent differential centrifugation and washing steps yield mitochondrial fractions suitable for downstream biochemical analyses. This workflow eliminates enzymatic digestion steps, reduces sample variability, and allows parallel processing of multiple strains or experimental conditions. Overall, this method offers a rapid, low-cost, and reproducible alternative for crude mitochondrial isolation, ensuring excellent preservation of Atg32 and broad compatibility with quantitative and comparative studies.

Time-lapse into immunofluorescence (TL into IF) imaging combines the wealth of information acquired during live-cell imaging with ease of access for static immunofluorescence markers. In the field of mechanobiology, connecting live and static imaging to visualize cell biology dynamics is often troublesome. For instance, nuclear blebs are deformations of the nucleus that often rupture spontaneously, leading to changes in the molecular composition of the nucleus and the nuclear bleb. Current techniques to connect cellular dynamics and their downstream effects via live-cell imaging, followed by immunofluorescence, often require third-party analysis programs or stage position measurements to accurately track cells. This protocol simplifies the connection between live and static imaging by utilizing a gridded imaging dish. In our protocol, cells are plated on a dish with an engraved coordinate plane. Individual cells are then matched from when the time-lapse ends to the immunofluorescence images simply by their known coordinate location. Overall, TL into IF offers a straightforward method for connecting dynamic live-cell with static immunofluorescence imaging, in an easy and accessible tool for cell biologists.

In the Japanese rhinoceros beetle Trypoxylus dichotomus, gene function studies have relied mainly on systemic larval RNA interference (RNAi), as gain-of-function techniques remain underdeveloped and germline transgenesis is impractical given the species’ approximately one-year generation time. In addition, because larval RNAi is systemic, it has been difficult to analyze the function of lethal genes. Here, we present a simple and efficient protocol for the direct introduction of exogenous DNA into T. dichotomus larvae via in vivo electroporation. This protocol includes optimized procedures for adult breeding and egg collection, as well as a rigorously parameterized electroporation technique that delivers a piggyBac transposon vector into region-specific larval tissues. Within one day after electroporation, treated larvae exhibit mosaic expression of a reporter gene, enabling rapid tissue-specific functional analysis without the need to establish stable germline transgenic lines. Moreover, the key promoter used in this system (T. dichotomus actinA3 promoter) is effective across diverse insect species, indicating that the method can be readily adapted to other non-model insects. Overall, this electroporation-based approach provides a valuable gain-of-function tool for T. dichotomus and potentially many other insect species.

DNA epigenetic modifications play crucial roles in regulating gene expression and cellular function across diverse organisms. Among them, 5-glyceryl-methylcytosine (5gmC), a unique DNA modification first discovered in Chlamydomonas reinhardtii, represents a novel link between redox metabolism and epigenetic regulation. Accurate genome-wide detection of 5gmC is essential for investigating its biological functions, yet no streamlined method has been available. Here, we present deaminase-assisted sequencing (DEA-seq), a simple and robust approach for base-resolution mapping of 5gmC. DEA-seq employs a single DNA deaminase that efficiently converts unmodified cytosines (C) and 5-methylcytosine (5mC) into uracils or thymines, while leaving 5gmC intact. This selective resistance generates a clear sequence signature that enables precise identification of 5gmC sites across the genome. The method operates under mild reaction conditions and is compatible with low-input DNA, minimizing sample loss and improving detection sensitivity. Overall, DEA-seq provides an accessible, efficient, and highly accurate protocol for profiling 5gmC, offering clear advantages in workflow simplicity, DNA integrity, and analytical performance.

Breast cancer remains one of the most prevalent and deadly malignancies affecting women worldwide. Its progression and metastatic behavior are driven by complex mechanisms. To develop more effective therapeutic strategies, it is crucial to understand tumor growth, angiogenesis, and microenvironmental interactions. Although traditional in vivo models such as murine xenografts have long been used to study tumor biology, these approaches are often time-consuming, costly, and ethically constrained. In contrast, the chick embryo chorioallantoic membrane (CAM) assay offers a rapid, cost-effective, and ethically flexible alternative for evaluating tumor development and angiogenesis. This protocol describes an in ovo CAM-based xenograft model in which human breast cancer cells are implanted onto the vascularized CAM of chick embryos. This method enables real-time evaluation of tumor growth. Furthermore, the model allows for manipulation of experimental conditions, including pharmacological treatments or genetic modifications, to study specific molecular mechanisms involved in breast cancer progression. The major advantages of this protocol lie in its simplicity, reduced cost, and capacity for high-throughput screening, making it a valuable tool for translational cancer research.

Evaluating RNA–protein interactions is key to understanding post-transcriptional gene regulation. Electrophoretic mobility shift assays (EMSAs) remain a widely used technique to study these interactions, revealing information about binding affinities and binding modalities, including cooperativity and complex formation. Here, we detail, in a step-by-step protocol, how to perform EMSAs. We describe how to generate, purify, and quantitate ³²P-radiolabeled RNA by in vitro transcription, as well as the expression and purification of recombinant RNA-binding proteins in E. coli using ELAV as an example. We then describe how to set up binding reactions using serial dilutions in a microtiter plate format of recombinant ELAV and in vitro–transcribed RNA and how to perform EMSAs using native low-crosslinked acrylamide gels, with detailed graphically supported instructions and troubleshooting guides.

Understanding gene expression within defined neuronal populations is essential for dissecting the cellular and molecular diversity of the brain. mRNA assays provide a direct readout of gene expression, capturing transcriptional changes that may precede or occur independently of protein abundance, whereas protein assays reflect the cumulative effects of translation, modification, and degradation. Moreover, in histological analysis, immunohistochemical protein detection results in visually diffuse labeling, which makes it difficult to quantitatively assess levels and locations of expression at high resolution. Here, we present a protocol that allows for mRNA detection in single neuronal cell types with a high degree of sensitivity and anatomical resolution. This protocol combines fluorescent in situ hybridization (FISH) with immunohistochemistry (IHC) on the same tissue section. Briefly, FISH is carried out by ACDBio RNAscope^® fluorescent in situ hybridization technology, which involves processing the tissue sections, followed by signal amplification. This involves target retrieval, probe hybridization, and signal enhancement. Then, the tissue section is processed for IHC, which involves blocking nonspecific sites and incubation with primary antibodies, followed by development of a fluorescent signal with secondary antibodies. Typically, visual mRNA detection with FISH can be seen as individual puncta, whereas targeting the protein with an antibody results in filled cells or processes. The variation in staining pattern allows for the quantification of distinct mRNA transcripts within different neuronal populations, which renders co-localization analyses easy and efficient.

The genomes of RNA viruses can fold into dynamic structures that regulate their own infection and immune evasion processes. Proximity ligation methods (e.g., SPLASH) enable genome-wide interaction mapping but lack specificity when dealing with low-abundance targets in complex samples. Here, we describe HiCapR, a protocol integrating in vivo psoralen crosslinking, RNA fragmentation, proximity ligation, and hybridization capture to specifically enrich viral RNA–RNA interactions. Captured libraries are sequenced, and chimeric reads are analyzed via a customized computational pipeline to generate constrained secondary structures. HiCapR generates high-resolution RNA interaction maps for viral genomes. We applied it to resolve the in vivo structure of the complete HIV-1 RNA genome, identifying functional domains, homodimers, and long-range interactions. The protocol's robustness has been previously validated on the SARS-CoV-2 genome. HiCapR combines proximity ligation with targeted enrichment, providing an efficient and specific tool for studying RNA architecture in viruses, with broad applications in virology and antiviral development.

Functional enrichment analysis is essential for understanding the biological significance of differentially expressed genes. Commonly used tools such as g:Profiler, DAVID, and GOrilla are effective when applied to well-annotated model organisms. However, for non-model organisms, particularly for bacteria and other microorganisms, curated functional annotations are often scarce. In such cases, researchers often rely on homology-based approaches, using tools like BLAST to transfer annotations from closely related species. Although this strategy can yield some insights, it often introduces annotation errors and overlooks unique species-specific functions. To address this limitation, we present a user-friendly and adaptable method for creating custom annotation R packages using genomic data retrieved from NCBI. These packages can be directly imported as libraries into the R environment and are compatible with the clusterProfiler package, enabling effective gene ontology and pathway enrichment analysis. We demonstrate this approach by constructing an R annotation package for Mycobacterium tuberculosis H37Rv, as an example. The annotation package is then utilized to analyze differentially expressed genes from a subset of RNA-seq dataset (GSE292409), which investigates the transcriptional response of M. tuberculosis H37Rv to rifampicin treatment. The chosen dataset includes six samples, with three serving as untreated controls and three exposed to rifampicin for 1 h. Further, enrichment analysis was performed on genes to demonstrate changes in response to the treatment. This workflow provides a reliable and scalable solution for functional enrichment analysis in organisms with limited annotation resources. It also enhances the accuracy and biological relevance of gene expression interpretation in microbial genomics research.

RNA is now recognized as a highly diverse and dynamic class of molecules whose localization, processing, and turnover are central to cell function and disease. Live-cell RNA imaging is therefore essential for linking RNA behavior to mechanism. Existing approaches include quenched hybridization probes that directly target endogenous transcripts but face delivery and sequestration issues, protein-recruitment tags such as MS2/PP7 that add large payloads and can perturb localization or decay, and CRISPR–dCas13 imaging that requires substantial protein cargo and careful control of background and off-target effects. Here, we present a protocol for live-cell RNA imaging using the Spinach^TM family of fluorogenic RNA aptamers. The method details the design and cloning of Spinach^TM-tagged RNA constructs, selection and handling of cognate small-molecule fluorophores, expression in mammalian cell lines, dye loading, and image acquisition on standard fluorescence microscopes, followed by quantitative analysis of localization and dynamics. We include controls to verify aptamer expression and signal specificity, guidance for multiplexing with related variants (e.g., Broccoli, Corn, Squash, Beetroot), and troubleshooting for dye permeability and signal optimization. Application examples illustrate use in tracking cellular delivery of mRNA therapeutics, monitoring transcription and decay in response to perturbations, and the forming of toxic RNA aggregates. Compared with prior methods, Spinach^TM tags are compact, genetically encodable, and fluorogenic, providing high-contrast imaging in both the nucleus and cytoplasm with single-vector simplicity and multiplexing capability. The protocol standardizes key steps to improve robustness and reproducibility across cell types and laboratories.

RNA imaging techniques enable researchers to monitor RNA localization, dynamics, and regulation in live or fixed cells. While the MS2-MCP system—comprising the MS2 RNA hairpin and its binding partner, the MS2 coat protein (MCP)—remains the most widely used approach, it relies on a tag containing multiple fluorescent proteins and has several limitations, including the potential to perturb RNA function due to the tag’s large mass. Alternative methods using small-molecule binding aptamers have been developed to address these challenges. This protocol describes the synthesis and characterization of RNA-targeting probes incorporating a peptide nucleic acid (PNA)-based linker within the cobalamin (Cbl)-based probe of the Riboglow platform. Characterization in vitro involves a fluorescence turn-on assay to determine binding affinity (K_D) and selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) footprinting analysis to assess RNA-probe interactions at a single nucleotide resolution. To show the advancement of PNA probes in live cells, we present a detailed approach to perform both stress granule (SG) and U-body assays. By combining sequence-specific hybridization with structure-based recognition, our approach enhances probe affinity and specificity while minimizing disruption to native RNA behavior, offering a robust alternative to protein-based RNA imaging systems.

The CRISPR/Cas12a system has revolutionized molecular diagnostics; however, conventional Cas12a-based methods for RNA detection typically require transcription and pre-amplification steps. Our group has recently developed a diagnostic technique known as the SCas12a assay, which combines Cas12a with a split crRNA, achieving amplification-free detection of miRNA. However, this method still encounters challenges in accurately quantifying long RNA molecules with complex secondary structures. Here, we report an enhanced version termed SCas12aV2 (split-crRNA Cas12a version 2 system), which enables direct detection of RNA molecules without sequence limitation while demonstrating high specificity in single-nucleotide polymorphism (SNP) applications. We describe the general procedure for preparing the SCas12a system and its application in detecting RNA targets from clinical samples.