The peptide-centric local stability assay (PELSA) was developed to identify the protein targets and binding regions of diverse ligands at a proteome-wide scale. In this approach, the ligand is added to a cell lysate, and the proteins are digested for a short, defined time period using 0.5 mg ml-1 trypsin. Protein regions involved in ligand binding show less digestion, making it possible to identify binding sites and even quantify binding activity by dose-dependent analysis. In contrast to modification-based techniques that require chemical modification of ligands, the ligand modification-free property of the PELSA offers a key advantage by avoiding derivatization, thereby enabling proteome-wide identification of target proteins across diverse ligand types and biological contexts. The PELSA is broadly applicable for identifying protein targets of diverse ligands such as drugs and antibodies as well as endogenous metabolites and metal ions. However, performing PELSA experiments and subsequent data analysis to extract protein-ligand interaction details, including the binding protein, binding region and binding affinity, is not a trivial task. To address this, we present a detailed protocol for the experimental and computational PELSA workflow, including raw data processing and result visualization with the PELSA-Decipher software ( https://zenodo.org/records/18266507 ). Key points, such as selection of ligand concentrations, timing of trypsinization and quality control between different replicates, are discussed. Finally, we demonstrate the application of the protocol for identifying targets of staurosporine and 5-methyltetrahydrofolate, as well as for the dose-dependent PELSA analysis of inhibitors targeting the HSP90 family. The full PELSA protocol can be finished in 2 days, 1 day for sample preparation and 1 day for liquid chromatography-tandem mass spectrometry analysis and data processing. PELSA-Decipher can be downloaded from GitHub ( https://github.com/DICP-1809/ ).

Similar to proteins, many RNAs fold into three-dimensional (3D) structures to perform biological functions. Here we present the trRosettaRNA server, a web-based platform for automated RNA 3D structure prediction using deep learning. The primary input is the nucleotide sequence of a target RNA, with the option to upload custom multiple sequence alignments and secondary structures. The server uses an end-to-end neural network for automated 3D structure prediction, followed by an energy optimization step to resolve structural violations. As an automated server, trRosettaRNA is distinguished by its state-of-the-art modeling accuracy, flexible input options and comprehensive visualization of prediction results. trRosettaRNA has been successfully applied in various contexts, including predicting structures for Rfam families lacking known 3D structures, where representative cases of high-confidence structure predictions were found to align well with subsequent experimental observations. Utilizing up to 5 central processing unit (CPU) cores in parallel on our computer cluster, the server takes a median time of about 1 h to predict structures for RNA sequences with about 200 nucleotides. The standalone package for trRosettaRNA offers distinct advantages such as enhanced data privacy for sensitive sequences, the ability to bypass server queues and integration into high-throughput automated pipelines. Importantly, the open-source nature of the package empowers researchers to directly modify the codebase for specialized research needs or to develop derivative tools by fine-tuning the underlying neural network. The web server and standalone package of trRosettaRNA are available at https://yanglab.qd.sdu.edu.cn/trRosettaRNA/ and https://github.com/YangLab-SDU/trRosettaRNA2 , respectively.

Reprogrammable Adenosine Deaminase Acting on RNA (ADAR) Sensors (RADARS) control RNA translation in mammalian cells, allowing for noninvasive sensing or perturbation of specific cell types based on transcriptional signatures. Upon base-pairing between a target RNA and a sensor RNA, RADARS leverages ADAR to edit a premature stop codon upstream of a gene of interest, thereby releasing translation of the desired cargo. These design principles enable sequence programmability, allowing RADARS to adapt more easily to new contexts than existing tools for targeting cell types. We describe a detailed protocol for performing experiments with RADARS, including designing, cloning and validating RADARS constructs targeting a transcript of interest. RADARS guide sequences can be designed with an intuitive web interface and cloned into existing constructs for downstream applications including imaging, sorting and sequencing. We outline recommendations for cargo choice, sensor design and ADAR system selection, enabling users to choose the best workflow depending on the desired application. Beginning with sensor design, the selection of top-performing RADARS guides can be completed in ~2 weeks, followed by a desired use case. Convenient engineering and application of RADARS for various applications enable the design and execution of various cell-targeting experiments.

RNAs exhibit complex dynamics in cells, including expression, splicing, localization, translation and degradation, and these processes are highly coordinated and tightly regulated both spatially and temporally. To better understand the biological function of diverse RNAs, approaches that allow monitoring of RNA with high spatiotemporal resolution are essential. Fluorescent RNAs (FRs), fluorescent protein-like entities consisting of RNA aptamers and their cognate fluorogenic dyes, have emerged as a promising approach for imaging RNA dynamics in live cells. We recently reported the development of several high-performance FRs, named Pepper, Clivia and Okra, that show advantageous properties, including high cellular brightness and photostability, low ion dependence and/or large Stokes shifts, and have been used to image diverse RNA species in live cells. In this protocol, we provide easy, efficient and generalizable strategies for using FRs to visualize different RNA species in bacteria and mammalian cells by expressing the RNA of interest tagged with one or more copies of the aptamer. We also provide a detailed procedure for multiplexed RNA imaging using orthogonal FRs and the steps to perform super-resolution live imaging of RNAs. The protocol typically takes 5-7 d, including cloning, transfection of mammalian cells or transformation of bacteria, live imaging and results analysis. This protocol is applicable to the real-time monitoring of the localization and dynamics of RNAs of interest in live cells.

Lipid nanoparticles (LNPs) have garnered tremendous enthusiasm in preclinical and clinical settings for the delivery of nucleic acids such as mRNA. With applications in protein replacement therapies, vaccines and gene editing, mRNA LNPs have only recently been explored in the context of pregnancy disorders. There is a significant need for the design of novel therapeutic technologies such as mRNA LNPs to treat obstetric disorders like pre-eclampsia that are associated with placental pathology and detrimental effects on maternal and fetal health. Here, we present a step-by-step procedure for the preparation and evaluation of placenta-tropic mRNA LNPs for researchers from varied disciplines to explore their application in treating pregnancy disorders. In this Protocol, we describe steps for synthesizing and purifying the key ionizable lipid excipient of the placenta-tropic LNP formulation (4 d) before preparing mRNA LNPs using microfluidic mixing (1 d). Then, we detail in vitro mechanistic evaluations of the effect of protein adsorption on LNP-mediated mRNA transfection to placental trophoblasts (3 d). Finally, we outline methods for isolating reproductive tissues from time-dated pregnant mice to assess in vivo LNP biodistribution and mRNA transfection to the murine placenta (16 d). Compared to alternative LNP formulation procedures, this Protocol focuses on delivering mRNA LNPs to the placenta with a workflow that can be applied for a range of obstetric disorders. This Protocol seeks to increase interdisciplinary work at the interface of nanomedicine, gene modulation and reproductive health.

Single-cell epigenome and transcriptome profiling enables the dissection of gene regulatory networks, offering a powerful approach to characterize cellular heterogeneity and regulatory landscapes of cell states. Here we describe a single-cell ultra-high-throughput multiplexed sequencing (SUM-seq) assay for scalable and cost-effective simultaneous profiling of chromatin accessibility and gene expression in single nuclei. SUM-seq combines sample-specific accessible DNA and mRNA in situ barcoding with droplet-based microfluidic barcoding, introducing sample multiplexing and means to resolve multinucleated droplets for multiomic single-cell library preparation. In comparison with existing methods for multimodal profiling of chromatin accessibility and gene expression from the same cell, SUM-seq offers increased throughput and an unmatched multiplexing capability. This permits substantial scaling of the number of samples and nuclei assayed in one experiment, adhering to the needs of large-scale atlas projects, time-course experiments and perturbation screens while considerably reducing costs. We provide guidelines for experimental design and sample handling to accommodate various settings and sample types. Moreover, we discuss potential applications and provide guidelines for data processing. From sample collection to library preparation, the assay can be completed in 2-3 days, followed by sequencing and 1 day of data processing. Although the protocol can be implemented by researchers with general molecular biology skills, prior experience with single-cell assays is recommended.

High-throughput chemical synthesis plays a critical role in generating compound libraries and optimizing reaction conditions. Increasing adoption of robots and multiwell formats means that hundreds of reactions can be accessed with ease. However, conventional methods for quantitative detection of the product (for example, by liquid chromatography-mass spectrometry) create a bottleneck in the workflow because analyses need to be customized separately for each sample. Here we describe a tandem mass spectrometry approach where the samples are analyzed directly using acoustic ejection mass spectrometry. This approach features simple method development enabling accurate quantification for reactions where a characteristic neutral lost fragment is common to both the chemical starting material and the expected reaction products. Combining this precise fragmentation signature with acoustic ejection mass spectrometry allows whole 384-well plates of chemical reaction data to be collected at the same pace as two liquid chromatography-mass spectrometry samples, while maintaining the same levels of accuracy. To explain the principles involved in designing these experiments, we show four examples of common medicinal chemistry transformations for C-N and C-C bond formation that have been used in the synthesis of analogs of cereblon binding molecular glues, antifungals, antibiotics, and building blocks for automated small molecule synthesis. The whole procedure requires ~2 days of work to complete, including the 384-well plate reaction setup, analytical sample preparation, mass spectrometry data collection and analysis.

Microplastics (MPs) are persistent and widely distributed pollutants that have become an emerging environmental problem. When present in the environment, they are increasingly being incorporated into the carbon cycle and thus participate in the Earth's biochemical cycle alongside other pollutants. However, upon entering the environment (as primary or secondary MPs), various environmental factors collectively influence the physical and chemical characteristics of MPs, leading to changes in surface morphology, particle size and microstructure. These alterations can change their physical behavior and the effect that they have on living organisms. The aging processes of MPs are complex and influenced by multiple factors relating to both the size and composition of the MPs themselves and the environmental conditions. We developed a protocol for studying MP aging across different environmental settings (soil, water, air and organisms) over timescales from several weeks to months, applicable to common types of MPs. This protocol integrates modular aging experiments with an array of analytical techniques (for example, scanning electron microscopy, Fourier transform IR spectroscopy and pyrolysis-gas chromatography-mass spectrometry) to characterize MP aging according to micromorphology, chemical characteristics, dissolution characteristics and mass fraction. We have established a quantitative method for evaluating MP aging along with graded property assessment criteria for measuring the degree of aging-the composite aging index (CAI). This protocol takes approximately 4 days to 6 months, depending on the specific environmental aging conditions selected, the sample matrix and the suite of analytical techniques used. By implementing this protocol, we can gain mechanistic insights into MP aging processes, ultimately contributing to sustainable plastics development through strategic design that guides their fate and behavior.

Biomolecular condensates formed through liquid-liquid phase separation regulate cellular processes, and their dysregulation causes disease. Current methods for identifying endogenous phase-separating proteins have low throughput and cannot capture dynamic responses to stimuli. Here we present a protocol combining osmotic compression or transforming growth factor-β (TGF-β) treatment to induce condensation with sucrose density gradient centrifugation and quantitative mass spectrometry to enable systematic, high-throughput identification of endogenous condensates and phase-separating proteins. The method exploits the density changes that occur when phase-separating proteins undergo oligomerization during condensate formation. In H1975 cells, we identified over 1,500 phase-separating proteins under osmotic compression or TGF-β treatment; 538 of these candidates were not present in PhaSepDB, a database that compiles in vivo, in vitro and omics-derived proteins. The approach detects constitutive condensates and proteins that dynamically phase-separate in response to osmotic stress or TGF-β signaling. This protocol provides proteome-wide analysis of fractions of proteins having different densities and enables temporal resolution of phase-separation events. The procedure takes ~9 d and requires expertise in cell culture, biochemistry and mass spectrometry. This method enables systematic study of biomolecular condensates and disease-associated phase-separation mechanisms.

Molecular recording is an emerging paradigm for measuring biology over time. Enhancer-mediated genomic recording of activity in multiplex (ENGRAM) is a recently described synthetic biology circuit architecture that converts the transient activity of cis-regulatory elements (CREs) into stable genomic records that can be retrospectively recovered via DNA sequencing. Here we provide a step-by-step protocol for conducting ENGRAM experiments and analyzing the resulting data. We also describe key design considerations for ENGRAM recorders, summarize the strengths and limitations of ENGRAM, and highlight applications, including multiplex signal recording and high-throughput CRE screening. In contrast to other systems for DNA-based recording in mammalian systems, ENGRAM relies on prime editing-mediated insertions to record the activity of a given CRE, such that it is inherently multiplexable-for example, four-base-pair insertions can represent the activities of up to 256 distinct CREs. A further contrast lies with ENGRAM's compatibility with DNA Typewriter, which facilitates the capture of signal order. For users with basic skills in molecular biology, mammalian cell culture and DNA sequencing analysis, ENGRAM experiments can typically be completed within 5-6 weeks.