Molecular Biology

Careful dissection of insect gut tissues is essential for microbiome studies to ensure accurate characterization of internal microbial communities and preservation of DNA integrity. Because insect-associated microbiomes are highly sensitive to contamination, effective removal of external microbes prior to dissection is critical to minimize bias in downstream analyses. While ethanol- and bleach-based surface sterilization methods are commonly used, standardized workflows integrating field collection, sterilization, and dissection remain limited. Here, we present a step-by-step protocol for the field collection, surface sterilization, and dissection of gut tissues from the agricultural pest Diaprepes abbreviatus (Coleoptera: Curculionidae), optimized for genomic DNA extraction and microbiome analyses. Using wild-caught specimens, this workflow incorporates a rigorous surface sterilization and dissection strategy that minimizes external contamination while preserving biologically relevant microbial signatures and DNA integrity for downstream microbiome analyses. The protocol provides a standardized framework for insect gut microbiome studies and can be broadly adapted to other wild-caught insect species requiring careful collection, disinfection, and sterile dissection prior to molecular analysis. The protocol integrates field collection and laboratory processing steps into a streamlined workflow that minimizes contamination while preserving tissue integrity for downstream applications.

UFMylation is an evolutionarily conserved ubiquitin-like modification that covalently conjugates UFM1 to lysine residues of substrates via a sequential E1-E2-E3 enzymatic cascade. UFMylation plays a pivotal role in maintaining cellular homeostasis, and its dysregulation is closely linked to multiple major diseases, including malignant tumors, hematopoietic defects, neurodegenerative disorders, and congenital developmental defects, highlighting its important biological significance. However, few substrates of UFMylation have been reported to date, limiting our deep understanding of the mechanistic functions of this modification. This major bottleneck stems from two major technical limitations: the overwhelming abundance of ribosomal protein L26 (RPL26)-UFM1 conjugates masks signals from low-abundance substrates, and conventional methods rely on cumbersome cotransfection of multiple pathway components with poor efficiency and specificity in UFMylated peptides enrichment. To address these challenges, we have developed an effective and specific experimental protocol for UFMylation detection and large-scale substrate identification. This protocol employs CRISPR-Cas9-mediated gene editing to generate UFSP1/UFSP2 double-knockout (UFSP1^KO/UFSP2^KO, DKO) HEK293T cells, which completely abrogate de-UFMylation and thus significantly elevate global protein UFMylation levels upon exogenous introduction of mature UFM1-ΔC2. In addition, exogenous co-expression of the E3 ligase core components UFL1 and DDRGK1 can further improve the sensitivity of substrate detection. This protocol enables large-scale identification of UFMylation substrates with modification sites via high-efficiency enrichment with the K-ε-VG antibody and LC-MS/MS analysis.

Transient transfection is commonly used for the commercial production of adeno-associated viral particles for gene therapy. In this process, packaging cells such as HEK293 cells are transfected with three plasmids, including the Rep/Cap plasmid, the Helper plasmid, and the gene-of-interest plasmid containing the transgene/gene therapy product. The combination of these plasmids allows for the robust production of recombinant adeno-associated viral particles. As a result, the concentration of these plasmids plays a critical role in viral production and must be accurately assessed. Typically, A₂₆₀/A₂₈₀ readings are utilized to measure plasmid titer; however, this approach lacks accuracy and specificity and is susceptible to matrix interference. To address these shortcomings, a digital droplet PCR method was developed to titer plasmids. This method uses a combined restriction digest/PCR protocol to linearize the plasmid template and evaluate copy numbers of a plasmid-specific gene. Qualification demonstrated that the method is highly accurate, specific to plasmid DNA, and impervious to matrix interference.

Determining the recruitment relationships of nuclear proteins is essential for understanding the mechanisms underlying nuclear complex assembly and gene regulation. A widely used method for studying recruitment is chromatin immunoprecipitation (ChIP), but it requires fixation, chromatin shearing, and specific antibodies and cannot easily resolve recruitment directionality. Other systems like lacO/LacI are restricted to a limited number of specialized cell lines containing this lacO array’s integration. To overcome these limitations, we developed a novel microscopy-based assay, CRISPR-PITA (protein interaction and telomere recruitment assay), to assess whether a nuclear protein can recruit other nuclear factors in living cells. The protein of interest is targeted to repetitive genomic loci (e.g., telomeres) using catalytically inactive Cas9 (dCas9) fused to a SunTag array, resulting in visible nuclear foci. Recruitment of endogenous proteins is evaluated by immunofluorescence. For proof-of-concept, we tested the Kaposi’s sarcoma herpesvirus (KSHV) latency-associated nuclear antigen (LANA). CRISPR-PITA revealed that LANA recruits known interactors, such as ORC2 and SIN3A, but not MeCP2. Conversely, MeCP2 recruits LANA, indicating a unidirectional recruitment relationship. Similarly, MeCP2 could recruit HDAC1, while HDAC1 could not recruit MeCP2, further supporting directional nuclear interactions. Here, we present an easy, straightforward protocol applicable to any transfectable cell line, enabling researchers to dissect recruitment dynamics at high spatial resolution. CRISPR-PITA provides a powerful, flexible, and accessible platform to interrogate recruitment directionality between nuclear proteins in their native cellular context.

In the last two decades, the field of molecular entomology has seen a shift toward next-generation sequencing techniques as a means of uncovering genetic and developmental processes. However, the standardization of methods is not well-established, and studies for insect–fungus consortia lack established protocols for advanced molecular techniques and downstream analysis compared to approaches applied in model systems involving insect–bacteria interactions. To investigate insect–microbe interactions, RNA sequencing and analysis is often used to identify genes involved in the symbiosis. But such protocols do not often consider insect–fungus systems, which vary significantly in community member abundance and/or fail to describe the details of the process from collection to data processing. This paper will introduce a comprehensive approach for RNA sequencing using two non-model insect–fungus consortia, which lack established, published protocols seen in model systems: the ambrosia beetle mutualism and cicada Massospora parasitism. The protocol includes a detailed TRIzol RNA extraction and quantification, RNA sequencing, and data processing using Nextflow pipeline software. Validation of a range of symbiotic interactions from mutualistic to parasitic is considered to justify this procedure to be utilized in a range of insect–fungus interactions with varied abundances and host interactions.

CRISPR/Cas9-based genome editing is a powerful approach for functional genomics and bioenergy research in woody plants. However, conventional single guide RNA (gRNA) strategies predominantly generate small insertions or deletions that may not fully disrupt gene function and often require extensive sequencing for mutation identification. Here, we present an optimized protocol for the efficient generation of large-fragment deletion mutants in Populus tremula × P. alba clone INRA 717-1B4 using a dual-gRNA CRISPR/Cas9 system. Co-expression of two gRNAs flanking the target region induces double-strand breaks at both sites, enabling the deletion of the intervening genomic fragment, typically larger than 50 bp. This protocol describes step-by-step procedures for gRNA design, vector construction, Agrobacterium-mediated transformation, plant regeneration, and molecular validation. Using the PtFBX230 gene as a representative target, large deletions are readily identified by conventional PCR and agarose gel electrophoresis, enabling rapid and cost-effective genotyping. This protocol can be readily adopted to other loci in poplar and related woody species and provides a robust framework for generating null alleles to support functional genomics and bioenergy-related trait engineering in woody plants.

Quantitative real-time PCR (qPCR) is widely used for the quantitative assessment of relative transcript abundance in biological and medical research. Rigorous interpretation of qPCR data requires appropriate correction and normalization workflows that account for both technical variability and experimental heterogeneity. Regarding the correction step, the most used qPCR analysis relies on the 2^-ΔΔCq method, which assumes identical and optimal amplification efficiencies across assays. Alternative strategies estimate amplification efficiencies using standard curves generated from serial dilutions, but these approaches require additional experimental work and may introduce serious dilution-related bias. Here, we describe a spreadsheet-based computational protocol for the correction of relative quantification of qPCR data that integrates amplification efficiencies derived directly from raw amplification curves using LinRegPCR. Cq values and per-reaction efficiency estimates are combined to calculate efficiency-corrected target quantities. Correction is then followed by normalization using the geometric mean of two reference genes. The workflow enables calculation of relative abundance fold-changes without the need for standard curves and produces output tables suitable for downstream statistical analysis. This protocol provides a transparent, dilution-free method for efficiency-corrected qPCR data analysis that can be implemented using commonly available software, facilitating reproducible and Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE)-compliant reporting of qPCR results.

RNA detection techniques have expanded into a diverse methodological landscape spanning hybridization, amplification, imaging, and sequencing. In this review, we provide a method‑centric synthesis of the major technologies that define this landscape, emphasizing how each method’s core principle, practical strengths, and sources of variability shape its reproducibility. Beginning with foundational approaches, we trace the development of isothermal amplification, quantitative and digital PCR, microarrays, single‑molecule imaging, multiplexed spatial methods, and amplification‑free digital quantification. We then examine the transformative impact of bulk, single‑cell, long‑read, direct‑RNA, and spatial transcriptomics, as well as CRISPR‑based detection and metabolic labeling for RNA dynamics. Across these technologies, we focus on reproducibility as a defining dimension of evaluation: mature methods benefit from established standards, whereas newer approaches remain pre‑standardization and require careful, experiment‑specific controls. Rigorous method selection must be guided by the biological question, required resolution, sample constraints, and the maturity of each method’s reproducibility framework. We conclude that RNA detection methods form interconnected methodological paths of problem‑solving rather than simple replacements.

The PrimeFlow^TM assay is a flow cytometry–based method for the co-detection of RNAs and proteins in cells. When combined with cell characterization by immunophenotyping, PrimeFlow^TM can be used to simultaneously detect RNA and proteins in a cell type–specific manner in complex heterogeneous samples, offering an advantage over bulk tissue analysis methods. Here, we describe the implementation of the PrimeFlow^TM assay protocol for the detection of transgene mRNA and protein expression in spleen samples from mice treated in vivo with luciferase mRNA-lipid nanoparticles (LNPs). This protocol involves spleen tissue dissociation for cell isolation, followed by cell fixation and permeabilization to allow immunolabeling of intracellular luciferase protein. The immunophenotyping strategy is based on immunolabeling with mouse CD marker antibodies for the identification of T cells, B cells, monocytes, granulocytes/macrophages, NK cells, and non-hematopoietic cells. The RNAs of luciferase and a housekeeping gene, β-actin, are detected with sequence-specific probe sets by employing sequential oligonucleotide annealing steps and fluorescent labeling using a branched DNA (bDNA) technology. Samples are analyzed by flow cytometry. Based on our analysis, we conclude it is feasible to apply the PrimeFlow^TM approach for evaluating successful drug targeting to the cell types of interest and any potential differences in the kinetics of RNA delivery and protein expression in various tissue cells, supporting the discovery and development of RNA therapeutics.

RNA alternative splicing (AS) is an essential process that expands transcriptomic and proteomic diversity in eukaryotic cells and contributes to cellular heterogeneity across physiological and pathological conditions in humans. With the advent of single-cell RNA sequencing (scRNA-seq), it has become possible to study AS at cellular resolution, although robust and standardized analytical workflows remain to be developed. Here, we present a stepwise protocol for analyzing AS in single cells from pediatric high-grade gliomas (pHGGs) harboring the histone H3.3 lysine 27-to-methionine (H3.3K27M) mutation using SMART-Seq2 scRNA-seq data. Starting from raw sequencing reads, the workflow includes read alignment, gene-level quantification, splice junction and intron quantification, and single-nucleotide variant-based mutation detection. Gene expression–based clustering and cell-type annotation are performed by using the Seurat R package. AS analysis in tumor cells is then conducted using the MARVEL R package in combination with customized scripts to calculate percent spliced-in (PSI) values, identify variable AS events, perform dimensionality reduction, cluster cells, conduct differential AS analysis, and visualize splicing patterns. This protocol provides a reproducible and comprehensive framework for dissecting AS dynamics at single-cell resolution. It is readily adaptable to other SMART-Seq2 datasets and facilitates systematic investigation of splicing heterogeneity in diverse biological contexts.