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Past Issue in 2025
Volume: 15, Issue: 9
Bioinformatics and Computational Biology
A Guide to Basic RNA Sequencing Data Processing and Transcriptomic Analysis
RNA sequencing (RNA-Seq) has transformed transcriptomic research, enabling researchers to perform large-scale inspection of mRNA levels in living cells. With the growing applicability of this technique to many scientific investigations, the analysis of next-generation sequencing (NGS) data becomes an important yet challenging task, especially for researchers without a bioinformatics background. This protocol offers a beginner-friendly step-by-step guide to analyze NGS data (starting from raw .fastq files), providing the required codes with an explanation of the different steps and software used. We outline a computational workflow that includes quality control, trimming of reads, read alignment to the genome, and gene quantification, ultimately enabling researchers to identify differentially expressed genes and gain insights on mRNA levels. Multiple approaches to visualize this data using statistical and graphical tools in R are also described, allowing the generation of heatmaps and volcano plots to represent genes and gene sets of interest.
Analysis of qRT-PCR Data to Identify the Most Stable Reference Gene Using gQuant
The accurate quantification of nucleic acid–based biomarkers, including long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), and microRNAs (miRNAs), is essential for disease diagnostics and risk assessment across the biological spectrum. Quantitative reverse transcription PCR (qRT-PCR) is the gold standard assay for the quantitative measurement of RNA expression levels, but its reliability depends on selecting stable reference targets for normalization. Yet, the lack of consensus on a universally accepted reference gene for a given sample type or species, despite being necessary for accurate quantification, presents a challenge to the broad application of such biomarkers. Various tools are currently being used to identify a stably expressed gene by using qRT-PCR data of a few potential normalizer genes. However, existing tools for normalizer gene selection are fraught with both statistical limitations and inadequate graphical user interfaces for data visualization. gQuant, the tool presented here, essentially overcomes these limitations. The tool is structured in two key components: the preprocessing component and the data analysis component. The preprocessing addresses missing values in the given dataset by the imputation strategies. After data preprocessing, normalizer genes are ranked using democratic strategies that integrate predictions from multiple statistical methods. The effectiveness of gQuant was validated through data available online as well as in-house data derived from urinary exosomal miRNA expression datasets. Comparative analysis against existing tools demonstrated that gQuant delivers more stable and consistent rankings of normalizer genes. With its promising performance, gQuant enhances the precision and reproducibility in the identification of normalizer genes across diverse research scenarios, addressing key limitations of RNA biomarker–based translational research.
ChIP-seq Data Processing and Relative and Quantitative Signal Normalization for Saccharomyces cerevisiae
Chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) is a widely used technique for genome-wide analyses of protein–DNA interactions. This protocol provides a guide to ChIP-seq data processing in Saccharomyces cerevisiae, with a focus on signal normalization to address data biases and enable meaningful comparisons within and between samples. Designed for researchers with minimal bioinformatics experience, it includes practical overviews and refers to scripting examples for key tasks, such as configuring computational environments, trimming and aligning reads, processing alignments, and visualizing signals. This protocol employs the sans-spike-in method for quantitative ChIP-seq (siQ-ChIP) and normalized coverage for absolute and relative comparisons of ChIP-seq data, respectively. While spike-in normalization, which is semiquantitative, is addressed for context, siQ-ChIP and normalized coverage are recommended as mathematically rigorous and reliable alternatives.
Applying LFQRatio Normalization in Quantitative Proteomic Analysis of Microbial Co-culture Systems
Quantitative proteomic analysis plays a crucial role in understanding microbial co-culture systems. Traditional techniques, such as label-free quantification (LFQ) and label-based proteomics, provide valuable insights into the interactions and metabolic exchanges of microbial species. However, the complexity of microbial co-culture systems often leads to challenges in data normalization, especially when dealing with comparative LFQ data where ratios of different organisms can vary across experiments. This protocol describes the application of LFQRatio normalization, a novel normalization method designed to improve the reliability and accuracy of quantitative proteomics data obtained from microbial co-cultures. The method was developed following the analysis of factors that affect both the identification of proteins and the quantitative accuracy of co-culture proteomics. These include peptide physicochemical characteristics such as isoelectric point (pI), molecular weight (MW), hydrophobicity, dynamic range, and proteome size, as well as shared peptides between species. We then created a normalization method based on LFQ intensity values named LFQRatio normalization. This approach was demonstrated by analysis of a synthetic co-culture of two bacteria, Synechococcus elongatus cscB/SPS and Azotobacter vinelandii ΔnifL. Results showed enhanced accuracy of differentially expressed proteins, allowing for more reliable biological interpretation. This protocol provides a reliable and effective tool with wider application to analyze other co-culture systems to study microbial interactions.
Reconstruction of Single-Neuron Projectomes in Mice
Reconstructing single-neuron projectomes is essential for mapping the mesoscopic connectome and eventually for understanding brain-wide connectivity and diverse brain functions. The combination of sparse labeling techniques and large-scale and high-resolution optical imaging technologies has been revolutionizing the brain-wide reconstruction of single-neuron morphologies, as exemplified by the dataset for over 10,100 single-neuron projectomes of hippocampal neurons. Here, we illustrate a comprehensive protocol for large-scale single-neuron reconstruction in the mouse brain. This includes key steps and examples in imaging data preprocessing, neurite tracing, and registration into a template brain. These procedures enable efficient and accurate large-scale morphological reconstruction of single neurons in the mouse brain.
Mapping the Simultaneously Accessible and ssDNA-Containing Genome With KAS-ATAC Sequencing
The KAS-ATAC assay provides a method to capture genomic DNA fragments that are simultaneously physically accessible and contain single-stranded DNA (ssDNA) bubbles. These are characteristic features of two of the key processes involved in regulating and expressing genes—on one hand, the activity of cis-regulatory elements (cREs), which are typically devoid of nucleosomes when active and occupied by transcription factors, and on the other, the association of RNA polymerases with DNA, which results in the presence of ssDNA structures. Here, we present a detailed protocol for carrying out KAS-ATAC as well as basic processing of KAS-ATAC datasets and discuss the key considerations for its successful application.
Cell Biology
A Cold-Active Protease Tissue Dissociation Protocol for the Preservation of the Tendon Fibroblast Transcriptome
Traditional tissue dissociation methods for bulk- and single-cell sequencing use various protease and/or collagenase combinations at temperatures ranging from 28 to 37 °C, which cause transcriptional cell stress that may alter data interpretation. Such artifacts can be reduced by dissociating cells in cold-active proteases, but few studies have shown that this improves cell-type specific transcription, particularly in tissues hypersensitive to mechanical integrity and extracellular matrix (ECM) interactions. To address this, we have dissociated zebrafish tendons and ligaments in subtilisin A at 4 °C and compared the results with 37 °C collagenase dissociation using bulk RNA sequencing. We find that high-temperature collagenase dissociation causes general cell stress in tendon fibroblasts (tenocytes) as reported in previous studies with other cell types, but also that high temperature specifically downregulates hallmark genes involved in tenocyte specification and ECM production in vivo. Our results suggest that cold-protease dissociation reduces transcriptional artifacts and increases the robustness of RNA-sequencing datasets such that they better reflect native in vivo tissue microenvironments.
TurboID Labeling and Analysis of Proteins in the Primary Cilium
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.
snPATHO-seq: A Detailed Protocol for Single Nucleus RNA Sequencing From FFPE
Formalin-fixed paraffin-embedded (FFPE) samples remain an underutilized resource in single-cell omics due to RNA degradation from formalin fixation. Here, we present snPATHO-seq, a robust and adaptable approach that enables the generation of high-quality single-nucleus (sn) transcriptomic data from FFPE tissues, utilizing advancements in single-cell genomic techniques. The snPATHO-seq workflow integrates optimized nuclei isolation with the 10× Genomics Flex assay, targeting short RNA fragments to mitigate FFPE-related RNA degradation. Benchmarking against standard 10× 3' and Flex assays for fresh/frozen tissues confirmed robust detection of transcriptomic signatures and cell types. snPATHO-seq demonstrated high performance across diverse FFPE samples, including diseased tissues like breast cancer. It seamlessly integrates with FFPE spatial transcriptomics (e.g., FFPE Visium) for multi-modal spatial and single-nucleus profiling. Compared to workflows like 10× Genomics’ snFFPE, snPATHO-seq delivers superior data quality by reducing tissue debris and preserving RNA integrity via nuclei isolation. This cost-effective workflow enables high-resolution transcriptomics of archival FFPE samples, advancing single-cell omics in translational and clinical research.
Developmental Biology
Measuring Anti-aging Effects in Drosophila
One of the major factors contributing to aging and age-related diseases is the well-understood decline in the function of adult stem cells. Quantifying the degree of aging in adult stem cells is essential for advancing anti-aging mechanisms and developing anti-aging agents. However, no systematic approach to this exists. In this study, we developed a method to quantitatively assess the degree of aging in adult intestinal stem cells using a Drosophila midgut model and two aging markers. First, aging was induced in Drosophila with the desired genotype, and the anti-aging agent was administered 7 days before dissection. Then, the levels of two intestinal stem cell aging markers found in Drosophila (PH3 and γ-tubulin) were measured using immunohistochemistry. Finally, fluorescence microscopy was employed to count the number of aging markers and take images, which were analyzed using image analysis software. Using this approach, we quantitatively analyzed the effects of anti-aging agents on the aging of adult intestinal stem cells. This methodology is expected to significantly expedite the development of anti-aging agents and substantially reduce the research costs associated with aging-related studies.
Environmental science
From Colonization to High Production and Plasmodium vivax Infection of Anopheles darlingi and Anopheles deaneorum: a Platform for Malaria Research
The mass rearing of anopheline mosquitoes under laboratory conditions is essential for advancing malaria research. It facilitates in-depth studies on mosquito biology, behavior, and genetics and their role in Plasmodium transmission. However, the colonization of Neotropical anophelines such as Anopheles darlingi—a primary malaria vector in the Amazon region—has proven particularly challenging due to its unique reproductive characteristics. Unlike other species that can initially be colonized using forced copulation methods and later adapt to natural mating, An. darlingi does not copulate under forced conditions. Recent breakthroughs in An. darlingi colonization have been achieved using flashlight induction techniques, which have enabled the establishment and maintenance of stable laboratory populations. These advancements have created new opportunities for vector control studies in Brazil, including the testing of innovative control methods and Plasmodium transmission-blocking strategies. This protocol offers a comprehensive, step-by-step guide for initiating and scaling up large laboratory colonies of An. darlingi and An. deaneorum, a secondary malaria vector. It details methods for copulation induction, colony management, and successful artificial infection of mosquitoes with Plasmodium vivax. The guide serves as a critical resource for establishing new Neotropical anopheline colonies from different populations, contributing to future malaria research and control efforts in the Amazon. Additionally, the establishment of Brazil’s first Malaria Vector Production and Infection Platform (Plataforma de Produção e Infecção de Vetores da Malária, PIVEM) has further supported the development of new control technologies and the study of P. vivax–Anopheles interaction, advancing efforts to combat malaria in the region.
Immunology
Standardized Flow Cytometry Method for Absolute Counting of Intraepithelial Lymphocytes in the Intestinal Mucosa Using TruCountTM Beads
In the intestinal epithelium, intraepithelial lymphocytes (IELs) coexist with intestinal epithelial cells (IECs). The IELs have an important role in defending the intestinal tract against pathogens and eliminating tumor cells. Anomalies in the absolute IEL count have been reported in various digestive diseases. IELs are typically counted using histologic techniques or under light microscopy after isolation of the epithelium. However, these techniques can introduce bias, which might account for the discrepancies in counts from one study to another. Here, we describe a flow cytometry assay for determining the absolute IEL count and the IEL/IEC ratio. We combined a conventional epithelial isolation method with a BD TruCountTM bead-based absolute counting technique to quantify IELs (CD45+ CD326/EpCAM- CD103+CD3+) and IECs (CD45- CD326/EpCAM+) in a C57BL/6 mouse model.
Plant Science
Assessing Metabolite Interactions With Chloroplastic Proteins via the PISA Assay
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.
Optimized Protocol for DNA Extraction in Three Theobroma Species
DNA extraction is a crucial step in molecular biology research, particularly for genetic and genomic analyses. These studies require a high concentration of high-quality DNA, which is often a challenge for underexplored species or when the available plant material consists of aged tissue. To address these challenges, the cetyltrimethylammonium bromide (CTAB)-based DNA extraction method has been optimized to improve efficiency and yield. The process begins with an overnight incubation of plant tissue macerated with liquid nitrogen in a solution containing a high concentration of CTAB (4%). Subsequently, the mixture undergoes two washes with chloroform: isoamyl alcohol. The nucleic acids are then precipitated using isopropanol, followed by a wash with 70% ethanol to ensure purity. Finally, the purified DNA is resuspended in ultrapure water. This optimized procedure produces high-quality DNA suitable for various downstream applications, including PCR and sequencing, even from older leaves of the three Theobroma species: T. cacao, T. bicolor, and T. grandiflorum. Additionally, this protocol significantly enhances throughput and allows for the parallel processing of a substantially larger number of samples compared to conventional techniques.
Image-Based Lignin Detection in Nematode-Induced Feeding Sites in Arabidopsis Roots
Cyst and root-knot nematodes are sedentary biotrophic parasites that infect a wide range of plant species, causing significant annual yield and economic losses. Cyst nematodes (genera Heterodera and Globodera) induce specialized feeding structures called syncytia in host plant roots, while root-knot nematodes (Meloidogyne spp.) form galls containing feeding cells known as giant cells. This protocol describes the visualization of lignin in Arabidopsis roots infected by beet cyst nematode H. schachtii and root-knot nematode M. incognita using histochemical staining. We present two distinct approaches for lignin detection: direct staining of root segments containing syncytia and galls and histopathological detection in thin longitudinal sections of the feeding sites.
Stem Cell
Human iPSC-Derived Neuron and Oligodendrocyte Co-culture as a Small-Molecule Screening Assay for Myelination
Neurons and oligodendrocytes are the building blocks of the brain. Neurons form synaptic connections and transmit signals, while oligodendrocytes, including oligodendrocyte precursor cells (OPCs) and their derivatives, are vital for central nervous system maintenance and myelination. The demand for human-specific neuron-oligodendrocyte model systems to study these interactions has grown, yet co-culture protocols remain limited. Recent advancements in the field provide methods for deriving co-cultures of neurons and OPCs from human induced pluripotent stem cells (hiPSC), each with distinct benefits and challenges. This study presents a time-efficient, reproducible method to derive neurons and O4-expressing oligodendrocytes, followed by a straightforward co-culture system that minimizes astrocyte differentiation and ensures robust neuron and oligodendrocyte populations.
A Cartilaginous Organoid System Derived From Human Expanded Pluripotent Stem Cells (hEPSCs)
The development of human organotypic models of cartilage provides essential insights into chondrogenesis and chondrocyte hypertrophy while enabling advanced applications in drug discovery, gene editing, and tissue regeneration. Here, we present a robust and efficient protocol for differentiating human expanded pluripotent stem cells (hEPSCs) into hypertrophic chondrocytes through a sclerotome intermediate. The protocol involves initial sclerotome induction, followed by 3D chondrogenic culture and subsequent hypertrophic maturation induced by bone morphogenetic protein-4 (BMP4), thyroid hormone (T3), and β-glycerophosphate. This protocol also allows for sensitive testing of the effects of various compounds on hypertrophic differentiation during the maturation process. Furthermore, we identify an α-adrenergic receptor antagonist, phentolamine, as an inhibitor of hypertrophic differentiation. This organoid system provides a practical platform for exploring cartilage hypertrophy mechanisms and testing therapeutic strategies for cartilage regeneration.
Systems Biology
Proteome Birthdating: A Single-Sample Approach for Measuring Global Turnover Dynamics and “Protein Age”
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.
