Nature Protocols

Small molecules targeting RNA can be valuable chemical probes and potential therapeutics. The interactions between small molecules, particularly fragments, and RNA, however, can be difficult to detect due to their modest affinities and short residence times. Here, we describe the procedures for mapping the molecular fingerprints of small molecules in vitro and throughout the human transcriptome in live cells, identifying both the targets bound by the small molecule and the sites of binding therein. For complete details on the use and execution of this protocol, please refer to 1.

Tyrosine kinases control a wide range of cell signaling pathways that are central to human physiology, and they are dysregulated in a variety of human diseases, most notably cancers. Our understanding of tyrosine kinase biology hinges upon a clear delineation of their protein substrates. Thus, much effort has been invested into defining the substrate specificities of tyrosine kinases, which is partly driven by recognition of the amino acid sequences surrounding the phospho-acceptor tyrosine residues. Numerous methods have been developed to profile tyrosine kinase sequence recognition, and these approaches have collectively demonstrated that different tyrosine kinases have distinct substrate sequence preferences. Here, we describe one such method that combines bacterial peptide display and deep sequencing to study tyrosine kinase substrate preferences. Our approach enables rapid measurement of relative phosphorylation efficiencies for thousands of peptides simultaneously. The genetically-encoded nature of the peptide libraries used with this method allows for facile and cheap construction of libraries tailored to answer a variety questions. Notably, our approach is compatible with genetic code expansion via Amber codon suppression, which allows for the construction and screening of libraries containing non-canonical amino acids. Importantly, results from this assay correlate strongly with quantitative measurements of enzyme kinetics, they corroborate previously reported tyrosine kinase substrate preferences, and they can reveal new insights into tyrosine kinase substrate specificity.

Recent advances in molecular and cell biology and imaging have unprecedentedly enabled multi-scale structure-functional studies of entire metabolic pathways from atomic to micrometer resolution, and the visualization of macromolecular complexes in situ, especially if these molecules are expressed with appropriately-engineered and easily-detectable tags. However, genome editing in eukaryotic cells is challenging when generating stable cell lines loaded with large DNA cargoes. To address this limitation, here, we have conceived biGMamAct, a system that allows the straightforward assembly of a multitude of genetic modules and their subsequent integration in the genome at the ACTB locus with high efficacy, through standardized cloning steps. Our technology encompasses a set of modular plasmids for mammalian expression, which can be efficiently docked into the genome in tandem with a validated Cas9/sgRNA pair through homologous-independent targeted insertion (HITI). As a proof of concept, we have generated a stable cell line loaded with an 18.3-kilobase-long DNA cargo to express 6 fluorescently-tagged proteins and simultaneously visualize 5 different subcellular compartments. Our protocol leads from the in-silico design to the genetic and functional characterization of single clones within 6 weeks and can be implemented by any researcher with familiarity with molecular biology and access to mammalian cell culturing infrastructure.

Papain-like protease (PLpro) from SARS-CoV-2 is a high-priority target for COVID-19 antiviral drug development. We present protocols for PLpro production in Escherichia coli. PLpro expressed as a fusion with the Saccharomyces cerevisiae Smt3 protein (SUMO), is purified and obtained in its native form upon hydrolysis, with yields as high as 38 mg L-1. The protocol also provides isotope-enriched samples suitable for NMR studies. Protocols are also presented for PLpro characterization by mass spectrometry, 1D 19F-NMR and 2D heteronuclear NMR, and a fluorescence-based enzyme assay. HighlightsO_LIProduction, purification, and biochemical analysis of native N- and C-termini PLpro C_LIO_LIHigh yields in E. coli, up to 38 mg L-1 using lysogeny broth. C_LIO_LISupports labeled samples for inhibitor interaction studies. C_LIO_LI19F NMR and fluorescence assays for inhibitor screening and IC50 determination. C_LI eTOC BlurbSARS-CoV-2 PLpro is a key cysteine protease involved in viral replication and immune evasion, making it an important target for antiviral drug development. This study presents a detailed protocol for PLpro production, purification, and biochemical analysis, achieving high yields in E. coli. The workflow includes fusion expression with a His-SUMO tag, isotope labeling for inhibitor studies, and assays for screening and quantifying inhibitors. This comprehensive guide facilitates large-scale production of active PLpro for drug discovery and structural studies.

Trans-neuronal viruses that spread between synaptically connected neurons have become invaluable tools in neuroscience, enabling circuit mapping and targeted delivery of genetic material to cells within defined pathways. Although most available trans-neuronal viral tracers propagate retrogradely, an anterograde trans-neuronal virus that spread from presynaptic to postsynaptic neurons would substantially expand experimental capabilities. We previously demonstrated that YFV-17D--a live attenuated yellow fever vaccine used clinically for decades--spreads anterogradely along neuronal circuits. We further developed a suite of recombinant YFV-17D-based vectors for diverse applications, including tracing monosynaptic projectome of defined neuronal cell types, multiplex mapping of parallel pathways, and trans-neuronal genetic manipulation with minimal neurotoxicity. We have now tested and optimized procedures for vector production and application. Based on these optimizations, here, we present a two-part guide for preparing and deploying this viral vector system to map brain connectivity. The first part describes the molecular biology and cell culture workflows required to generate high-quality viral vectors, yielding titers of [~]1 x 10^10 to 5 x 10^11 genomic copies per milliliter within approximately two weeks. The second part outlines optimized animal procedures, including intracranial injections, perioperative care, and experimental considerations tailored to specific aims and vector variants. Depending on the application, efficient trans-neuronal tracing can be achieved within 1-4 weeks following delivery.

1Life continues to shock and amaze us, reminding us that truth is far stranger than fiction. http://Euplotid.io is a quantized geometric model of the eukaryotic cell, an attempt at quantifying the incredible complexity that gives rise to a living cell by beginning from the smallest unit, a quanta. Starting from the very bottom we are able to build the pieces which when hierarchically and combinatorially combined produce the emergent complex behavior that even a single celled organism can show. Euplotid is composed of a set of quantized geometric 3D building blocks and constantly evolving dockerized bioinformatic pipelines enabling a user to build and interact with the local regulatory architecture of every gene starting from DNA-interactions, chromatin accessibility, and RNA-sequencing. Reads are quantified using the latest computational tools and the results are normalized, quality-checked, and stored. The local regulatory architecture of each gene is built using a Louvain based graph partitioning algorithm parameterized by the chromatin extrusion model and CTCF-CTCF interactions. Cis-Regulatory Elements are defined using chromatin accessibility peaks which are mapped to Transcriptional Start Sites based on inclusion within the same neighborhood. Deep Neural Networks are trained in order to provide a statistical model mimicking transcription factor binding, giving the ability to identify all Transcription Factors within a given chromatin accessibility peak. By in-silico mutating and re-applying the neural network we are able to gauge the impact of a transition mutation on the binding of any transcription factor. The annotated output can be visualized in a variety of 1D, 2D, 3D and 4D ways overlaid with existing bodies of knowledge such as GWAS results or PDB structures. Once a particular CRE of interest has been identified a Base Editor mediated transition mutation can then be performed in a relevant model for further study. O_FIG O_LINKSMALLFIG WIDTH=182 HEIGHT=200 SRC="FIGDIR/small/170159v15_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1a55a1borg.highwire.dtl.DTLVardef@bebb0dorg.highwire.dtl.DTLVardef@1ea5b11org.highwire.dtl.DTLVardef@100e735_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 0.1:C_FLOATNO Graphical Abstract C_FIG

Nuclei isolation from myelin-rich adult mouse brain regions remains challenging for single-nucleus RNA sequencing because myelin and debris can reduce nuclei quality. We describe an optimized protocol for mouse hippocampi and cerebella using tube-and-pestle homogenization and low-volume sucrose-gradient pelleting with a standard benchtop centrifuge, with optional magnetic enrichment of nuclei to reduce debris/non-nuclear carryover. Under the tested conditions, the workflow produces intact, debris-reduced nuclei and supports downstream 10x Genomics Flex and PARSE WT library preparation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/716374v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@ccbd87org.highwire.dtl.DTLVardef@1aef4bcorg.highwire.dtl.DTLVardef@14569a8org.highwire.dtl.DTLVardef@1bc261_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIBenchtop sucrose-gradient pelleting enables rapid nuclei purification from myelin-rich adult mouse brain C_LIO_LIScales across tissue inputs (e.g., hippocampus [~]15-20 mg; cerebellum [~]50-70 mg) without ultracentrifugation or 15 mL gradients C_LIO_LIMagnetic enrichment as the recommended final cleanup step further reduces myelin/debris carryover and is compatible with 10x Flex and PARSE WT workflows. C_LI

Since its inception, single molecule localization microscopy (SMLM) has enabled imaging scientists to visualize biological structures with unprecedented resolution. Particularly powerful implementations capable of 3D, multi-color and high-throughput imaging have yielded key biological insights although widespread access to such technologies has been limited. The purpose of this protocol is to provide a guide for interested researchers to establish high-end SMLM in their laboratories. We detail the initial configuration and subsequent assembly of the SMLM, including instructions for alignment of all optical pathways, software/hardware integration and operation of the instrument. We describe validation steps including the preparation and imaging of test- and biological samples with structures of well-defined geometry and assist the user in troubleshooting and benchmarking performance. Additionally, we provide a walkthrough of the reconstruction of a super-resolved dataset from acquired raw images using the Super-resolution Microscopy Analysis Platform (SMAP). Depending on the instrument configuration, the cost of components is in the range $80,000 - 160,000, a fraction of the cost of a commercial instrument. A builder with some experience of optical systems is expected to require 3 - 6 months from the start of system construction to attain high-quality 3D and multi-color biological images.

Advances in theoretical understanding are frequently unlocked by access to large, diverse experimental datasets. Olfactory neuroscience and psychophysics remain years behind the other senses in part because rich datasets linking olfactory stimuli with their corresponding percepts, behaviors, and neural pathways underlying this transformation, remain scarce. Here we present a concerted effort to unlock and unify dozens of stimulus-linked olfactory datasets across species and modalities under a unified framework called Pyrfume. We present examples of how researchers might use Pyrfume to conduct novel analyses uncovering new principles, introduce trainees to the field, or construct benchmarks for machine olfaction.

Small molecule-protein interactions underpin many biological functions and play an integral role in the treatment and prevention of several human diseases. These interactions can be key to understanding the mechanism of action of these compounds. Previous methods of determining protein-protein or protein-antibody interactions have been well established; however, the use of BLI in antiviral discovery is a promising and relatively new avenue. The high-throughput nature of this method in tandem with its pM sensitivity allows for quick and seamless identification of hit compounds. Here we discuss ways to overcome common pitfalls that can occur while using BLI such as nonspecific binding (NSB) and ligand drift while offering possible solutions. Characterizing small molecule-protein interactions is not trivial and optimizing the experimental conditions is imperative. To address this gap in knowledge, we present optimized BLI protocols for the study of three cases of protein-small molecule interactions: PF74 or Lenacapavir (LEN) with HIV-1 capsid protein (CA), and Nirmatrelvir (NIR) with SARS-CoV-2 Mpro. LEN and NIR are of particular interest because they are clinically relevant, and PF74, a well-studied control, was the first compound reported to target the LEN binding site. We demonstrate that BLI can be a powerful and effective tool in calculating the binding affinities between a protein and small molecule. These newly designed methods enabled calculation of KD values, the affinity between ligand and analyte, ranging from the micro to the sub-nanomolar range for CA binding events and confirmed the covalent interaction between NIR and Mpro. These protocols will facilitate efficient testing of new antivirals or derivatives in a high- throughput format. SummaryBio-Layer Interferometry (BLI) is a multifunctional technology that is used to determine valuable information on real-time kinetics including association and dissociation. Optimizing experimental conditions to acquire data about protein-ligand interactions can be challenging. We provide three example methods of collecting binding data that characterize how viral proteins interact with antivirals.

The isolation of specific cell types of the brain is essential to study cell-type-specific differences in complex neurological diseases such as Alzheimers disease. This protocol isolates oligodendrocytes, microglia, endothelial cells, astrocytes, and neurons from a single mouse brain. The process involves gentle tissue homogenization, debris removal, and sequential sorting of five distinct cell types. We validate cell purity and viability using flow cytometry and RT-qPCR. This protocol is well-suited for a range of downstream applications, including genomics, transcriptomics, and proteomics. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/666877v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@1426b97org.highwire.dtl.DTLVardef@1a5bb77org.highwire.dtl.DTLVardef@1b69f32org.highwire.dtl.DTLVardef@8da416_HPS_FORMAT_FIGEXP M_FIG C_FIG

Despite advances in automated liquid handling and microfluidics, preparing samples for RNA sequencing at scale generally requires expensive equipment, which is beyond the reach of many academic labs. Manual sample preparation remains a slow, expensive, and error-prone process. Here, we describe a low-cost, semi-automated pipeline to extract cell-free RNA (cfRNA) that like many RNA isolation protocols, can be decomposed into three subparts - RNA extraction, DNA digestion, and RNA cleaning and concentration. RT-qPCR data using a synthetic spike-in confirms comparable RNA quality as compared to manual sample processing, the gold-standard used in our prior work. The semi-automated pipeline also shows striking improvement in sample throughput (+12x), time spent (-11x), cost (-3x), and biohazardous waste produced (-4x) as compared to its manual counterpart. In total, this protocol enables cfRNA extraction from 96 samples simultaneously in 4.5 hours; in practice, this dramatically improves time to results as demonstrated in our recent work [1] where it was used to process 404 samples in 27 hours. Importantly, any lab already has most of the parts required (manual pipette, corresponding tips and kits) to build a semi-automated sample processing pipeline of their own and would only need to purchase or 3D-print a few extra parts ($5.5K total). This pipeline is also generalizable for many nucleic acid extraction applications, thereby increasing the scale of studies, which can be performed in small research labs.

For single-molecule studies requiring surface anchoring of biomolecules, a poorly passivated surface can result in alterations of biomolecule structure and function that can result in artifacts. This protocol describes surface passivation and sample chamber preparation for mechanical manipulation of chromatin fibers and characterization of topoisomerase II activity in physiological buffer conditions. The method employs enhanced surface hydrophobicity and purified blocking proteins to reduce non-specific surface adsorption. This method is accessible, cost-effective, and potentially widely applicable to other biomolecules. For a complete list of publications that employ this protocol, see the paper references. B. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/614989v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@d52b73org.highwire.dtl.DTLVardef@117bfc3org.highwire.dtl.DTLVardef@2eb670org.highwire.dtl.DTLVardef@cb88b2_HPS_FORMAT_FIGEXP M_FIG C_FIG

Bioluminescence resonance energy transfer (BRET) allows to quantitate protein interactions in intact cells. Here we provide a step-by-step protocol for measuring BRET due to transient interactions of oncogenic K-RasG12V in plasma membrane nanoclusters of HEK293-EBNA cells. We describe how to seed, transfect and replate cells, followed by their preparation for BRET-measurements on a microplate reader and detailed data analysis steps. For details on how to apply this protocol, please refer to Steffen et al., 2024 1. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/602189v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@152e8c2org.highwire.dtl.DTLVardef@2f2aacorg.highwire.dtl.DTLVardef@9a8e9borg.highwire.dtl.DTLVardef@108833f_HPS_FORMAT_FIGEXP M_FIG C_FIG

ImmCellFie is a user-friendly, web-based platform for comprehensive analysis of metabolic functions inferred from transcriptomic or proteomic data. It enables researchers to leverage the powerful mechanistic insight provided by complex genome-scale metabolic models with little to no bioinformatics training required. The platform has been integrated with a series of useful tools and richly annotated scientific visualizations for interactive exploration by the user. ImmCellFie pushes beyond simple statistical enrichment and incorporates complex biological mechanisms to quantify cell activity. Graphical abstract

AMP-activated protein kinase (AMPK) has evolved to detect a critical increase in cellular AMP/ATP and ADP/ATP concentration ratios as a signal for limiting energy supply. Such energy stress then leads to AMPK activation and downstream events that maintain cellular energy homeostasis. AMPK activation by AMP, ADP or pharmacological activators involves a conformational switch within the AMPK heterotrimeric complex. We have engineered an AMPK-based sensor, AMPfret, which translates the activating conformational switch into a fluorescence signal, based on increased fluorescence resonance energy transfer (FRET) between donor and acceptor fluorophores. Here we describe how this sensor can be used to analyze direct AMPK activation by small molecules in vitro using a fluorimeter, or to estimate changes in the energy state of cells using standard fluorescence or confocal microscopy.

Numerous techniques have been employed to deconstruct the heterogeneity observed in normal and diseased cellular populations, including single cell RNA sequencing, in situ hybridization, and flow cytometry. While these approaches have revolutionized our understanding of heterogeneity, in isolation they cannot correlate phenotypic information within a physiologically relevant live-cell state, with molecular profiles. This inability to integrate a historical live-cell phenotype, such as invasiveness, cell:cell interactions, and changes in spatial positioning, with multi-omic data, creates a gap in understanding cellular heterogeneity. We sought to address this gap by employing lab technologies to design a detailed protocol, termed Spatiotemporal Genomics and Cellular Analysis (SaGA), for the precise imaging-based selection, isolation, and expansion of phenotypically distinct live-cells. We begin with cells stably expressing a photoconvertible fluorescent protein and employ live cell confocal microscopy to photoconvert a user-defined single cell or set of cells displaying a phenotype of interest. The total population is then extracted from its microenvironment, and the optically highlighted cells are isolated using fluorescence activated cell sorting. SaGA-isolated cells can then be subjected to multi-omics analysis or cellular propagation for in vitro or in vivo studies. This protocol can be applied to a variety of conditions, creating protocol flexibility for user-specific research interests. The SaGA technique can be accomplished in one workday by non-specialists and results in a phenotypically defined cellular subpopulation for integration with multi-omics techniques. We envision this approach providing multi-dimensional datasets exploring the relationship between live-cell phenotype and multi-omic heterogeneity within normal and diseased cellular populations.

Oligodendrocyte precursor cells (OPCs) sculpt neural circuits through the phagocytic engulfment of synapses during development and in adulthood. However, precise techniques for analyzing synapse engulfment by OPCs are limited. Here, we describe a two-pronged cell biological approach for quantifying synapse engulfment by OPCs which merges low-and high-throughput methodologies. In the first method, an adeno-associated virus encoding a pH-sensitive, fluorescently-tagged synaptic marker is expressed in neurons in vivo. This construct allows for the differential labeling of presynaptic inputs that are contained outside of and within acidic phagolysosomal compartments. When followed by immunostaining for markers of OPCs and synapses in lightly fixed tissue, this approach enables the quantification of synapses engulfed by around 30-50 OPCs within a given experiment. In the second method, OPCs isolated from dissociated brain tissue are fixed, incubated with fluorescent antibodies against presynaptic proteins, and then analyzed by flow cytometry. This approach enables the quantification of presynaptic material within tens of thousands of OPCs in less than one week. These methods extend beyond the current imaging-based engulfment assays designed to quantify synaptic phagocytosis by brain-resident immune cells, microglia. Through the integration of these methods, the engulfment of synapses by OPCs can be rigorously quantified at both the individual and populational levels. With minor modifications, these approaches can be adapted to study synaptic phagocytosis by numerous glial cell types in the brain.

Metabolomics is the comprehensive study of small molecules that provides a snapshot of an organisms physiological state. Reflecting phenotype more closely than genes or proteins, metabolites reveal changes linked to diseases, mutations, genetic interventions, and environmental stimuli. Recent technological advancements in metabolomics analysis through the application of ion mobility mass spectrometry have enhanced the comprehensive analysis of complex metabolic mixtures. However, pre-analytical bottlenecks in throughput and consistent extraction persist. We developed an automated, sample-agnostic metabolite extraction workflow for diverse liquid samples using an Agilent Bravo liquid handling platform. Here, we provide device, protocol, and form files for efficient sample processing to extract metabolites for global metabolomics analysis using liquid chromatography - mass spectrometry techniques.

One obvious feature of life is that it is highly dynamic. The dynamics can be captured by movies that are made by acquiring images at regular time intervals, a method that is also known as timelapse imaging. Looking at movies is a great way to learn more about the dynamics in cells, tissue and organisms. However, science is different from Netflix, in that it aims for a quantitative understanding of the dynamics. The quantification is important for the comparison of dynamics and to study effects of perturbations. Here, we provide detailed processing and analysis methods that we commonly use to analyze and visualize our timelapse imaging data. All methods use freely available open-source software and use example data that is available from an online data repository. The step-by-step guides together with example data allow for fully reproducible workflows that can be modified and adjusted to visualize and quantify other data from timelapse imaging experiments. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/432684v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@d04086org.highwire.dtl.DTLVardef@3c304borg.highwire.dtl.DTLVardef@186bf56org.highwire.dtl.DTLVardef@17bbd6d_HPS_FORMAT_FIGEXP M_FIG C_FIG