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Volume:16 Issue: 21 | Bio-protocol
Current Issue in 2026
Volume: 16, Issue: 21
Biochemistry
In-Gel Tryptic Digestion and HCD/EThcD LC-MS/MS for Mapping Autophosphorylation Sites
This protocol describes a targeted workflow for identifying and quantitatively comparing kinase autophosphorylation sites, using in-gel proteolytic digestion, LC-MS/MS analysis, phosphosite localisation, and extracted ion chromatogram (XIC) analysis. The detailed protocol begins with an excised SDS-PAGE gel band containing the immunoprecipitated kinase of interest. Standard cell culture, expression, immunoprecipitation, and SDS-PAGE procedures can be used to generate this starting material according to the experimental system under investigation; the specific conditions used for NEK1 are described in our associated research article. Here, the protocol is applied to characterise phosphorylation sites on NEK1—a serine/threonine kinase implicated in amyotrophic lateral sclerosis (ALS)—using a homozygous NEK1 knockout cell background in which GFP-tagged wild-type or kinase-dead NEK1 constructs are re-expressed. This experimental system enables accurate assessment of kinase-dependent phosphorylation events in the absence of endogenous NEK1. A key methodological feature of the workflow is the use of two parallel MS2 fragmentation strategies: higher energy collisional dissociation (HCD) and electron-transfer/HCD (EThcD). EThcD generates complementary b/y and c/z ion series, providing superior localisation confidence for labile phosphorylation events that are difficult to resolve using HCD alone. Relative phosphopeptide abundance across conditions can be assessed using extracted ion chromatograms generated in FreeStyle, or using Skyline software with normalisation to the total ion current (TIC), as performed in the associated NEK1 study. Although demonstrated here using NEK1, the protocol is readily adaptable to other kinases amenable to immunoprecipitation and will be of interest to researchers studying kinase signalling, post-translational modification biology, and disease-associated phosphorylation events.
Bioinformatics and Computational Biology
A Python-Based Workflow for Image-Based Single-Cell Phenotypic Profiling From Fluorescence Microscopy Images
While advances in omics technologies have greatly improved our understanding of cellular heterogeneity, there is an increasing need for complementary approaches that capture the spatial organization and structural dynamics of cells. Image-based single-cell phenotypic profiling provides quantitative information on cell morphology and organelle organization, offering valuable insights into cellular function and regulation. Although numerous image analysis tools are available, establishing a complete analysis workflow, from image preprocessing and segmentation to feature extraction and multivariate analysis, often requires substantial computational expertise and software integration. Here, we describe a Python-based workflow for image-based single-cell phenotypic profiling from immunofluorescence microscopy images and provide a detailed protocol for its implementation. Using synchronized HeLa cells with drug-induced mitotic spindle defects as an example, the workflow covers image loading, cell segmentation, quantitative feature extraction, profile integration, dimensionality reduction, clustering, and data visualization. The protocol is accompanied by example datasets, annotated Jupyter Notebooks, and instructions for execution in either a local Python environment or Google Colab, facilitating straightforward implementation and customization. By integrating the entire analysis pipeline within a single coding environment, this workflow enables reproducible and accessible single-cell morphological profiling without requiring specialized imaging equipment or extensive programming expertise. The workflow therefore provides a practical platform for studying cell morphology, organelle organization, and cellular dynamics across a broad range of biological applications.
A Batch-Processing Pipeline for RNA-seq Gene Abundance Estimation
RNA sequencing (RNA-seq) datasets provide valuable opportunities to investigate gene and transcript abundance across species, tissues, developmental stages, and experimental conditions. However, processing multiple datasets consistently remains challenging because sequencing runs may differ in library layout, read length, sequencing depth, metadata quality, and analytical settings. Existing RNA-seq workflows often depend on dedicated workflow managers, substantial computational infrastructure, or advanced bioinformatics expertise, which may limit their accessibility for routine analyses. We present a modular Bash- and Python-based batch-processing pipeline for estimating gene and isoform abundance and generating expression matrices from multiple RNA-seq runs. Using an SRA RunTable, a reference genome, and its corresponding gene annotation, the workflow automates reference preparation, sequencing-data retrieval, quality assessment, read preprocessing, alignment, abundance estimation, and post-processing. It produces gene-level TPM and FPKM matrices, individual gene- and isoform-level RSEM outputs, quality-control summaries, and integrated MultiQC reports. Configurable computational resources, sample-level status tracking, automatic download retries, selective reprocessing of failed samples, and controlled removal of intermediate files allow interrupted analyses to resume without repeating completed runs while reducing storage requirements. By combining batch processing, transparent configuration, and restartable execution in a lightweight workflow, this protocol provides an accessible approach for standardized RNA-seq abundance estimation.
Computational Approach for the Reliable Inference of Task States Encoded by Neurons Using Calcium Imaging
Calcium imaging has become a widely used technique for measuring the activity of identified neurons during behavior. A key goal in such investigations is to determine whether, and to what extent, neurons preferentially encode one task-relevant state over another—a property referred to as neuronal selectivity. Despite the widespread use of calcium imaging for this purpose, no consensus exists on the parameter choices required to assess neuronal selectivity reliably: choices regarding neural data representation, behavioral position tracking, temporal binning, data balancing, and statistical shuffling all vary substantially across published studies. We recently developed a systematic computational approach to address this gap. Here, we describe the step-by-step protocol for implementing this computational pipeline. Starting from preprocessed calcium imaging data, the protocol guides users through all stages of the analysis: loading and aligning neural and behavioral data, deriving four metrics of neural activity, computing a selectivity index (SI), generating null distributions using four shuffling strategies, and assigning selectivity labels to individual neurons. The protocol introduces a principled, data-driven framework for evaluating the quality of any combination of parameter choices using quantitative metrics of accuracy and robustness and for identifying the optimal combination. The framework is validated using bootstrap resampling and hold-out cross-validation, and its generality is demonstrated by application to a different, regression-based approach for assessing selectivity of individual neurons. Finally, we describe the natural extension of this framework to inferences about task states encoded by populations of neurons. Thus, our protocol provides a reusable, extensible approach to identify optimal parameter settings for reliably characterizing neural encoding of two discrete task states.
Cancer Biology
Mouse Intratongue Injection With Cancer Cells—An Orthotopic Model for Head and Neck Squamous Cell Carcinoma
Syngeneic and orthotopic injection of cancer cells in mice is a gold standard model in pre-clinical cancer research. Herein, we detail a protocol of orthotopic intratongue injection as a model for upper respiratory tract cancer studies. This model recapitulates tumor growth and invasion in an orthotopic site, the oral cavity mucosa. It can be experimentally designed in a syngeneic context or used to study patient-derived cells in immunocompromised animals. Procedurally, mice are anesthetized and injected with a small volume of cancer cell suspension near the lateral border of the tongue, right under the mucous membrane. Post-injection, animal welfare is carefully attended to by appropriate analgesia, while providing soft food for the duration of the experiment to ensure the ability of the mice to eat ad libitum. Tongues and potential metastatic organs are dissected and can be sampled and analyzed using relevant state-of-the-art methods, including -omics and imaging approaches. We describe a broad range of distinct tumor profiling and analysis methods applicable to this model. These include physical measurements of elasticity with atomic force microscopy on fresh tissue, hematoxylin-eosin staining and standard immunohistochemistry, and confocal microscopy applied to paraffin-embedded tongue sections. This model is orthotopic, accessible without surgery, easy to monitor, and rapid to perform.
Quantification of Asymmetric Division in Cancer Cells via a Flow Cytometry and Cell Sorting–Based Protocol
Asymmetric partitioning of cellular components during division contributes to generating phenotypic heterogeneity and plasticity in genetically identical cells, like bacteria or cancer cells. Traditionally, this partitioning noise has been investigated using live-cell time-lapse confocal microscopy; however, while imaging offers high spatial resolution, it suffers from low statistical throughput and labor-intensive cell tracking. To overcome these limitations, we present a protocol that combines high-throughput flow cytometry and sorting with a theoretical model to precisely quantify partitioning noise during cell division. This method details the experimental setup for measuring cellular components in dividing populations, the data acquisition pipeline, and the implementation of the mathematical framework to extract inheritance parameters. Applicable to both suspension and adherent cells, we have validated our approach against live-cell imaging of adherent colon cancer cells. Hence, this flow cytometry–based approach offers a highly scalable, accessible, and statistically robust alternative to traditional imaging. It is widely applicable across diverse cell lines and biological systems, significantly advancing our capacity to study partitioning-driven phenotypic heterogeneity.
Cell Biology
Suspension-Based Intracellular Immunofluorescence Staining Coupled With Genome-Wide CRISPR-Cas9 Screening to Identify Regulators of O-GlcNAcylation
Protein O-GlcNAcylation is a dynamic and reversible post-translational modification that regulates diverse cellular processes, including transcription, signal transduction, metabolism, and cell fate determination. Systematic identification of genes that modulate global O-GlcNAc levels remains technically challenging at the genome scale. Here, we describe a pooled CRISPR-Cas9 screening protocol that combines the human genome-scale CRISPR knockout (GeCKO) v2 knockout library with intracellular immunofluorescence staining using the anti-O-GlcNAc antibody RL2 and fluorescence-activated cell sorting (FACS). In this workflow, HEK293T cells are transduced with the GeCKO v2 lentiviral library at a low multiplicity of infection to ensure predominantly single-sgRNA integration. Following puromycin selection, cells are fixed, permeabilized, and stained in suspension with RL2. The top 5% of cells with the highest intracellular RL2 fluorescence are collected as the RL2-high population, while a corresponding unsorted/input sample is retained as the reference for downstream sgRNA enrichment analysis. Genomic DNA is recovered from the RL2-high and unsorted/input samples, and integrated sgRNA cassettes are amplified through a two-step PCR and library-preparation workflow for Illumina sequencing. This protocol enables the identification of candidate genes whose knockout is associated with increased intracellular RL2 fluorescence.
Monitoring Protein Secretion in Living Cells With a HiBiT-Integrated RUSH System
The cellular secretory pathway is a fundamental physiological process; however, precise, efficient, and quantitative methods for monitoring this process remain rarely explored. Although several classic approaches have been developed to investigate secretory trafficking, the RUSH (Retention Using Selective Hooks) system currently represents the most advanced technique. Here, we introduce a method termed the HiBiT-integrated RUSH system and provide a detailed protocol for its application. This approach enables real-time monitoring of the secretion of cell membrane receptors such as ACE2, PDL1, NTCP, and CD209. By converting the cellular secretion process into a quantitative curve, our method offers an objective means for result interpretation. The HiBiT-integrated RUSH system is particularly effective for studying the transport dynamics of various cell membrane receptors, thereby facilitating the identification of both common and specific regulators of the cellular secretory pathway.
Establishment and Cryopreservation of Primary Fibroblast Cultures From Livestock Ear-Tissue Explants
Primary fibroblast cell culture is widely used in livestock research as a renewable genetic source for applications such as cell banking, molecular analyses, and functional studies [1]. Establishing high-quality primary culture requires careful tissue collection, aseptic processing, and optimized cell culture conditions to maximize growth and minimize contamination [2]. This protocol describes a standardized method for establishing primary fibroblast cultures from livestock species, representing multiple breeds, including cattle, swine, sheep, and goats. Although the ear is the primary tissue source described due to its easy accessibility and minimal invasiveness, this protocol may also be used with similar skin or tissue types if needed. Procedures for tissue collection, sample preparation, explant culture, routine maintenance, passaging, and cryopreservation are detailed to support the generation and proliferation of healthy fibroblast cultures suitable for downstream research applications.
Immunology
Long-Term Neutrophil Depletion and Flow Cytometric Analysis of Brain Neutrophils in the 5xFAD Mouse Model
Neutrophils are the most abundant circulating leukocytes in human blood and have been implicated in the progression of Alzheimer’s disease (AD). Elevated neutrophil numbers have been observed in the blood and brain parenchyma of AD patients and mouse models, yet their precise pathological role remains poorly understood. A major barrier to progress is the lack of validated protocols for long-term neutrophil depletion and reliable recovery of brain-infiltrating neutrophils for characterization. Here, we describe a step-by-step protocol for sustained neutrophil depletion in the 5xFAD mouse model using intraperitoneal injection of an anti-Ly6G antibody for six weeks. We used a dose-escalation strategy to maintain depletion efficiency, as neutrophil regeneration increases over time. We also applied a previously established flow cytometry method to monitor neutrophil depletion in peripheral blood, using an antibody panel designed to avoid interference from the depleting anti-Ly6G clone. Furthermore, we present an optimized brain tissue processing workflow that combines mechanical dissociation with Percoll density gradient centrifugation to collect brain-infiltrating neutrophils for downstream flow cytometric analysis. Here, this workflow was applied and validated in the 5xFAD mouse model but is not specific to AD brain tissue and may be applicable to other mouse models.
Molecular Biology
Transcriptomic Signature-Guided EGFP Labeling of Alveolar Epithelial Cells via RNA Sensing in Mouse Lungs In Vivo and Human Idiopathic Pulmonary Fibrosis Lung Slices Ex Vivo
Single-cell RNA sequencing has revealed transient and disease-associated alveolar epithelial states that are difficult to access with conventional transgenic approaches. Here, we describe a programmable RNA-sensing workflow based on CellREADR [cell access through RNA sensing by endogenous adenosine deaminases acting on RNA (ADAR)] to couple a selected cellular RNA signature to enhanced green fluorescent protein (EGFP) translation. The protocol covers sequence-encoded sensing RNA (sesRNA) design and cloning, in vitro validation of sesRNA-dependent EGFP expression in HEK293T cells, production and heparin-column purification of adeno-associated virus variant 6.2FF (AAV6.2FF), delivery to mouse lungs, and application to human idiopathic pulmonary fibrosis (IPF) precision-cut lung slices (PCLS). Sensors targeting Sftpc, Pdpn, or Sprr1a can be used to label alveolar type 2, alveolar type 1, and injury-induced Krt8+ alveolar differentiation intermediate cells in mice and KRT17+KRT5- aberrant basaloid cells in humans, respectively. Because cell specificity is programmed by the sensor sequence rather than a cell type–specific promoter or newly generated mouse line, this approach can be rapidly adapted to emerging transcriptomic targets in both experimental mouse models and human lung tissues, enabling cross-species validation and translational investigation of disease-associated epithelial states.
Plant Science
Anther Dissection and Confocal Imaging of Developing and Mature Pollen in Arabidopsis
Pollen development is a fundamental process underlying plant fertility that involves a series of coordinated cellular transitions from microspore mother cells (MMCs) to mature pollen grains. Conventional approaches for studying this process often require tissue sectioning, extensive sample preparation, and specialized instrumentation operated by trained personnel, making them labor-intensive, time-consuming, costly, and poorly suited for high-throughput analysis. Here, we describe simpler protocols for preparing and imaging both developing pollen lineage cells and mature pollen grains from Arabidopsis. By combining targeted anther dissection with gentle extrusion of pollen cells from anthers, fluorescent staining, and confocal microscopy, our protocol makes pollen cells at different developmental stages accessible for high-resolution imaging, enabling visualization of cellular morphology and protein localization, as well as fluorescence-based protein quantification. We also describe a complementary workflow for imaging mature pollen grains that provides a rapid alternative to scanning electron microscopy (SEM) for examining pollen surface structures and patterns. Together, these protocols offer practical approaches for investigating the cellular and molecular processes underlying pollen development and for characterizing the surface morphology of mature pollen.
Stem Cell
Myoclone Assay: Clonogenic Expansion of Activating Muscle Stem Cells
Muscle regeneration depends on the function of adult muscle stem cells (MuSCs). During homeostasis, MuSCs reside in a quiescent state of prolonged reversible cell cycle exit. Upon muscle injury, MuSCs exit the quiescent state and activate to enter the cell cycle. Subsequently, they undergo rounds of clonogenic expansion before differentiating to form new muscle fibers. Any impairment to the MuSCs’ ability to switch between these cell states can impair muscle regeneration. To study MuSC function, it is therefore important to quantitatively assess MuSCs’ capacity to switch between cell states. Numerous robust methods have been developed that assess the activation and proliferation capacity of MuSCs. However, these methods often require thousands of cells, and MuSCs are rare. Here, we present a protocol to assess MuSC activation using only 60 cells per sample by monitoring the parallel clonogenic expansion of single MuSCs. Single primary MuSCs are seeded into 96-well half-area microplates at a 1-cell-per-well density, which takes as little as 2 min per sample. The cells are then incubated for 8 days in the presence of growth factors, stained with Hoechst, and imaged by inverse fluorescence microscopy. We demonstrate that relative clonogenic expansion data provide results that are similar to published data obtained using other methods, such as cumulative EdU incorporation assays. This myoclone protocol enables the quantitative assessment of MuSC activation using only 60 cells, in a time-efficient and cost-effective manner, and thereby can provide new insights into MuSC function.