分子生物学

Riboswitches are structured non-coding RNA elements that regulate gene expression in response to small molecules; they serve as valuable systems in both public health and biophysical research by elucidating principles around RNA–ligand interactions, structure, and cellular function. Traditional approaches to studying riboswitches have relied on low-throughput techniques such as reporter assays or gel electrophoresis analysis of transcriptional products, which are limited in scalability. In this study, we present a high-throughput protocol to characterize the transcriptional activity of nearly 2,000 natural variants of the fluoride riboswitch in in vitro transcription. Starting with bioinformatics, we compiled a comprehensive dataset of riboswitch variants and then employed massive parallel oligonucleotide synthesis to generate an oligo pool of the riboswitch library. This pool was transcribed in vitro, converted into an Illumina-compatible next-generation sequencing (NGS) library, and analyzed to identify transcriptionally active riboswitch candidates. The workflow integrates natural riboswitch bioinformatic acquisition into a quantitative readout in a single streamlined pipeline, enabling large-scale exploration of transcriptional riboswitch function. This protocol offers a scalable method for mapping genotype-to-function relationships across transcriptional riboswitch families, accelerating the identification of functional variants for desired applications.

RNA modifications and their “writer,” “eraser,” and “reader” proteins are emerging as key regulators of gene expression and DNA repair through dynamically regulating RNA:DNA hybrids, or R-loops, during transcription. Therefore, it is paramount to develop rigorous techniques for accurate analysis of R-loop modifications. A convenient method for analyzing RNA modifications within total RNA is by dot blot with specific RNA modification antibodies; however, analysis of the modification of the RNA moiety within R-loops presents specific challenges. Here, we provide a detailed protocol for the production or purification of DNA containing R-loops in vitro and from cells, and the analysis of the RNA moiety modifications by dot blot. The DNA containing R-loops is treated with either mock or RNase H, which specifically degrades the RNA within RNA:DNA hybrids, to control for the specificity of the signal as originating from R-loops. Known quantities of the mock or RNase H–treated DNA are then spotted on three membranes, each blotted with antibodies that recognize double-stranded DNA, RNA:DNA hybrids, or the specific RNA modification antibodies of interest, such as m⁶A or ac⁴C. Thus, this protocol is useful to both biochemists and cell biologists with scientific interests at the intersection of R-loops and epitranscriptomics.

Efficient protein synthesis in eukaryotic cells typically requires a 5′ cap structure on messenger RNAs (mRNAs). However, under stress conditions or in viral infection, translation can also occur independently of the cap via internal ribosomal entry sites (IRES). IRES elements are therefore key regulators of protein expression in both viral and cellular contexts. Here, we describe a cell-free protocol to quantitatively assess cap-independent translation using wheat germ extract (WGE) and a firefly luciferase (FLuc) reporter. The protocol includes template preparation, RNA synthesis, and luminescence measurement following in vitro translation in WGE. This method enables rapid and robust comparison of translation activity under controlled conditions and can additionally be applied to evaluate mRNA modifications designed to enhance translation efficiency.

RNA sequencing (RNA-seq) has revolutionized transcriptomics, ribosome footprinting, and polysome profiling, providing a wealth of data. Many RNA-based omics typically remove ribosomal RNA (rRNA) or select for messenger RNA (mRNA) prior to sequencing, thereby enriching reads that map to the translationally active part of the transcriptome. Prokaryotic mRNA lacks the 3′ polyadenylated tail, which excludes the use of poly(A)-based selection methods. While commercial rRNA depletion products exist for prokaryotes, their proprietary nature and potential inefficiency with non-model organisms are factors that may limit broad-scale application. To mitigate this issue, we designed DepStep, a consolidated workflow for one-step rRNA depletion using species-specific biotinylated antisense probes for selective hybridization and removal of the target rRNA molecules. As a proof-of-concept, RNA-seq libraries of the psychrophilic gram-negative bacterium Shewanella glacialimarina TZS-4_T were prepared using both DepStep and a commercial rRNA depletion kit for gram-negative bacteria, to which DepStep was benchmarked. DepStep compares favorably to the commercial depletion kit; it removes >98.6% of the rRNA content in the sample, resulting in sequencing libraries where the coding DNA sequence (CDS) reads account for >80% of the total read count. Importantly, DepStep’s cost-per-sample is three times lower than the commercial kit, establishing DepStep as a simple yet cost-effective alternative to commercial solutions.

Plant roots dynamically respond to environmental changes and serve as an ideal system for studying cell development and gene regulation. Recent advances in imaging-based spatial transcriptomics have enabled high-resolution mapping of gene expression while preserving spatial context. However, existing sample preparation techniques remain inadequate for handling rigid plant tissues such as crop roots. Here, we present a detailed and practical protocol for preparing rigid plant tissue samples for imaging-based spatial transcriptomics. The workflow ensures effective tissue handling while maintaining RNA integrity and spatial organization. Within approximately eight days, samples can be processed and mounted onto commercial slides, making them ready for subsequent probe hybridization and imaging. This protocol also includes an integrated sample attachment test performed to assess slide quality. It has been optimized to produce consistent and reliable results across experiments. Overall, our method provides a robust solution for spatial transcriptomic analysis in rigid plant tissues, facilitating broader application of these technologies in plant research.

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.

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.

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.

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.