Methods

The precise regulation of chromatin composition is critical to gene expression and cellular identity, and thus a key component in development and disease. Robust assays to study chromatin features, including histone post-translational modifications (PTMs) and chromatin-associated proteins (e.g., transcription factors or PTM readers), are essential to understand their function and identify novel therapeutic strategies. To this end, Cleavage Under Targets and Release Using Nuclease (CUT&RUN) has emerged as a powerful tool for high-resolution epigenomic profiling. The approach has been successfully applied to numerous cell and tissue types, informing on target genomic distribution with unprecedented sensitivity and throughput. Here, we provide a detailed CUT&RUN protocol from sample collection through data analysis, including best practices and defined controls to ensure specific, efficient, and robust target profiling.

Micrococcal nuclease (MNase) digestion is widely used to profile chromatin accessibility and nucleosome footprinting. However, its application is often limited by sensitivity to reaction conditions, high cell input requirements, and the lack of standardized protocols across cell types. Here we developed a robust MNase workflow encompassing buffer composition, DNA purification chemistry, fixation and decrosslinking parameters, cell input scalability, and an in-house yeast spike-in for quantitative normalization. We validated this unified framework across human induced pluripotent stem cells (hiPSCs), hiPSC-derived cardiomyocytes at multiple differentiation stages, primary murine embryonic cardiac cells, and adult mouse cardiomyocytes, and demonstrated comparable digestion efficiencies and kinetics despite marked differences in cellular architecture and chromatin organization. Genome-wide MNase-seq in hiPSCs, combined with the nucMACC bioinformatic pipeline, resolved concentration-dependent nucleosomal occupancy and precise nucleosome positioning at pluripotency-related regulatory elements. This modular, end-to-end, and scalable workflow provides a standardized platform for reproducible MNase-based chromatin profiling across diverse in vitro and in vivo models. TEASERA unified, rapid, and scalable MNase-seq workflow for reproducible mononucleosomal and subnucleosomal profiling from stem cells to adult cardiomyocytes. HIGHLIGHTSO_LISystematic MNase optimization across buffer, DNA purification, and cell input variables C_LIO_LIUnified workflow validated in hiPSCs, hiPSC-CMs, embryonic, and adult cardiomyocytes C_LIO_LIFixed-cell protocol enables weeks of storage without loss of DNA quality C_LIO_LICost-effective yeast spike-in ensures quantitative normalization for MNase-seq C_LIO_LIGenome-wide analyses confirm robust and precise nucleosome positioning at regulatory elements C_LI

Recently a binary/digital scheme based on the superspecificity property of transfer RNAs (tRNAs) was proposed for the identification of single amino acids (AAs) from binary-valued measurements (Eur. Phys. J. E 45, 94, 2022). There are two formulations, they can be used to sequence short peptides and/or identify their parent proteins. In one of them an array of peptides is sequenced in 20 cycles by adding 20 different tRNAs carrying a fluorescent tag, optically recognizing the C-terminal residues, and cleaving the latter with a carboxypeptidase; the process is repeated over the peptides in parallel. Here this scheme is used to develop in theory a minimalist approach to protein identification that uses only two tRNAs and the carboxypeptidases A, B, and C. The latter form a complete and mutually exclusive set capable of cleaving all 20 AA types; this divides the 20 AAs into three classes. The sequences obtained are partial sequences in the reduced alphabet, their parent proteins can be obtained by search through a proteome database. The AA class of the terminal residue of every peptide in the array can be identified in a single cycle by using the three carboxypeptidases in the order C-B-A. With peptide lengths of [~]20 and a cycle time of [~]1 hour, the parent proteins of K peptides can be obtained in about 20 hours. This is independent of K (within the limits imposed by the imaging method used) and the dynamic range of a proteome; thus in theory a whole proteome can be processed in less than a day. Computational results suggest that the parent proteins of over 92% of peptides from the human proteome (Uniprot id UP000005640_9606) can be identified. The identification rate when residues are skipped due to carboxypeptidases cleaving the second and later residues in delayed reactions is about [~]90% with 1 or 2 skips. Full sequencing without skipped residues can be done by using all 20 tRNA types over 20 cycles in increasing order of cleavage time of the 20 AA types; a recursive procedure is given.

Measuring neurite length is crucial in neurobiology because it provides valuable insights into the growth, development, and function of neurons. In particular, neurite length is fundamental to study neuronal development and differentiation, neurons responses to drugs, neurodegenerative diseases and neuronal plasticity. Surprisingly, there is currently a lack of tools for high content neurite analysis. In this article, we present CABaNe, as an open source, high content, rule based Image J macro for cell analysis, including their neurite length. This macro possesses a graphical interface, metadata production, as well as verification means before and after analysis. Rule based and machine learning based programming have been tested for cell identification. After testing, we had better precision and adaptability using rule based cell identification. We challenged CABaNe with currently used techniques, which are manual or assisted. When tested on a small sample, CABaNe demonstrated a massive speed increase in capacity to treat dataset while maintaining or increasing precision when compared to manual measurement. When tested on a large data set, comparing different conditions, we successfully highlighted differences between conditions, in a fully automated manner. Therefore, CABaNe is viable as a high content option for cell analysis, for neurite length and other parameters. It is a base of code that can be used for other analysis or to train deep learning models. In the future, we expect this tool to be widely used in both basic and applied neurobiology research. Significance statementWhen studying neuronal cell differentiation, an important morphological parameter is neurite length. This parameter requires measuring the protrusions length of analysed cells. However, this analysis done manually can be long, as each individual cell must be measured independently. Currently, efficient single cell tools exist to assist the measurement, such as NeuronJ. However, there is currently no available automated tool for this analysis, and manual techniques suffer operator bias. In this paper, we present a macro to fully automatize neurite length and other parameters measurement, for each cell, in each image, in each condition.

A theoretical model is proposed for the identification of individual amino acids (AAs) in an unfolded whole proteins primary sequence. It is based in part on a recent report (Nat. Biotech. 41, 1130-1139, 2023) that describes the unfolding and translocation of whole proteins at constant speed through a biological nanopore (alpha-Hemolysin) of length 5 nm with a residue dwell time inside the pore of [~]10 s. Here current blockade levels in the pore due to the translocating protein are assumed to be measured with a limited precision of 70 nm3 and a bandwidth of 20 KHz for measurement with a low-bandwidth detector. Exclusion volumes in two pores of slightly different lengths are used as a computational proxy for the blockade signal; subsequence exclusion volume differences along the protein sequence are computed from the sampled translocation signals in the two pores relatively shifted multiple times. These are then converted into a system of linear inequalities that can be solved with linear programming and related methods; residues are coarsely identified as belonging to one of 4 subsets of the 20 standard AAs. To obtain the exact identity of a residue an artifice analogous to the use of base-specific tags for DNA sequencing with a nanopore (PNAS 113, 5233-5238, 2016) is used. Conjugates that add volume are attached to a given AA type, this biases the set of inequalities toward the volume of the conjugated AA, from this biased set the position of occurrence of every residue of the AA type in the whole sequence is extracted. By applying this step separately to each of the 20 standard AAs the full sequence can be obtained. The procedure is illustrated with a protein in the human proteome (Uniprot id UP000005640_9606).

Fluorescent reporters provide a useful tool for studying degron motifs. Fusing a degron of interest to a fluorescent protein allows to accurately track protein levels overtime to characterise the degradation kinetics of studied degrons. Here we describe a rapid and simple method to study degron peptides in Escherichia coli using plasmid-encoded eGFP-degron fusion constructs. The described methods provide an accessible workflow to evaluate degrons. We provide protocols for generation of pBAD plasmids encoding the studied constructs and two different methods for evaluating degrons - an end-point fluorescence measurement on agar plates and a kinetic measurement in liquid cultures in a 96-well format for high-throughput degron studies.

Biomolecular dynamics are often strikingly heterogeneous, with individual molecules sampling different states and kinetics--violating the "average molecule" assumption. Yet FRET analyses cannot resolve such variability or distinguish states differing mainly in kinetics, rather than FRET efficiency, as molecular configurations are projected onto 1D FRET signals. Here we introduce BNP-FRET-Bin, inferring state numbers and their kinetics directly from FRET data. In doing so, we eliminate user-specified parameters and expose molecule-to-molecule heterogeneity revealing new biologically relevant Holliday junction states with near identical FRET efficiencies.

The study of stoichiometry and supra-molecular organization of membrane (and membrane-associated) proteins plays a key role in understanding membrane structure and function. Single-molecule localization techniques (SML), besides providing imaging at unprecedented resolution, also offer quantitative tools such as stepwise photobleaching (SP) experiments and quantitative single-molecule localization (qSMLM). SML is becoming widely present in imaging core facilities but addressing biological problems by molecular counting experiments still remains not straightforward since experimental approaches for sample preparation require particular attention. We will focus on the experimental aspects that may prevent successful quantitative SML experiments of membrane-associated proteins. Depending on the specific experiment, to avoid artifacts and to miscount, fine-tuning of the expression levels and proper staining procedures are required, as well as optimized protocols and controls for counting. The work aims to highlight the crucial aspects that must be faced when quantitative single-molecule experiments are performed, helping to match the gap between sample preparation and the application of quantitative fluorescence microscopy techniques.

High throughput techniques that can massively produce in parallel, longer DNA sequences of interest can accelerate the decoding of gene functions. LASSO probes are a molecular biology tool that can enrich for DNA targets in a genomic sample via a multiplexed, single-pot reaction for downstream sequencing and/or cloning. Here we have explored aspects of process development and the design of the probes that relate to binding thermodynamics to determine impact on cloned library sequences. Control of ligase concentration, polymerase type, and melting temperature of probe are critical when translating the use of LASSO probes for homogeneous and high fidelity DNA capture.

This study presents a novel approach to understanding DNA movement dynamics through the development of a droplet-based, high-efficient chromatin conformation capture method, known as DropHiChew, and a new algorithm, loop velocity. DropHiChew, a user-friendly and cost-effective technique, employs the 10X single-cell systems allowing for easy experimental implementation. The loop velocity algorithm, on the other hand, enables the estimation of the speed and direction of cell development, providing a dynamic perspective on chromatin movement. Even with shallow sequencing, our loop velocity algorithm accurately gauges the trajectory of DNA motion and cellular states. The combined use of DropHiChew and loop velocity offers potential for a wide array of applications in future chromatin capture studies, including disease modeling, cellular differentiation studies, and developmental biology.

A method is proposed for the detection of post-translational modifications (PTMs) in single amino acids (AAs) for three types of PTMs (methylation, acetylation, and phosphorylation). It is preceded by a precursor step in which the terminal residue cleaved from a peptide is identified with a set of transfer RNAs (tRNAs) in a method proposed earlier (doi: 10.36227/techrxiv.19318145.v3). The identified AA (unmodified or modified) is separated from its cognate tRNA and translocated through a nanopore under electrophoresis. The resulting current blockade level (a proxy for analyte volume) and its width (a proxy for analyte translocation time) are measured and used to identify any PTM that might be present. The theoretical volumes of the 20 proteinogenic AAs and their PTMs are computed from crystallographic data and the ratio of the volume of a modified AA to that of an unmodified one obtained. The theoretical translocation time for the 20 AAs and their PTMs through a nanopore with a bilevel voltage profile is calculated with a Fokker-Planck drift-diffusion model. A 2-D scatter plot with these two quantities is generated for each AA type. Experimentally measured blockade levels and widths for an AA, modified or unmodified, can now be compared with the AAs scatter plot to assign a PTM for a modified AA. PTM assignment is horizontal across the PTMs for the AA because the latter has already been identified from its cognate tRNA in the precursor step, the other 19 AA types and their PTMs are not involved. Computational results are presented for 49 PTMs covering all 20 AAs and the three PTM types mentioned above.

Sequencing and quantification of whole proteins in a sample without separation, terminal residue cleavage, or proteolysis are modeled computationally. Similar to recent work on DNA sequencing (PNAS 113, 5233-5238, 2016), a high-volume conjugate is attached to every instance of amino acid (AA) type AAi, 1 [≤] i [≤] 20, in an unfolded whole protein, which is then translocated through a nanopore. From the volume excluded by 2L residues in a pore of length L nm (a proxy for the blockade current), a partial sequence containing AAi is obtained. Translocation is assumed to be unidirectional, with residues exiting the pore at a roughly constant rate of [~]1/s (Nature Biotechnology 41, 1130-1139, 2023). The blockade signal is sampled at intervals of 1 s and digitized with a step precision of 70 nm3; the positions of the AAis are obtained from the positions of well-defined quantum jumps in the signal. This procedure is applied to all 20 standard AA types, the resulting 20 partial sequences are merged to obtain the whole protein sequence. The complexity of subsequence computation is O(N) for a protein with N residues. The method is illustrated with a sample protein from the human proteome (Uniprot id UP000005640_9606). A mixture of M protein molecules (including multiple copies) can be sequenced by constructing an M x 20 array of partial sequences from which proteins occurring multiple times are first isolated and their sequences obtained separately. The remaining M singly-occurring molecules are detected from M disjoint paths through the 20 columns of the reduced M x 20 array. Detection complexity is O(M20), which is nominally in polynomial time but practical only for small M; to use this method a sample may be subdivided into subsamples down to this level. Quantification of proteins can be done by sorting their computed sequences on the sequence strings and counting the number of duplicates. The possibility of translating this procedure into practice and related implementation issues are discussed.

The formation of biomolecular condensates contributes to intracellular compartmentalization, and plays an important role in many cellular processes. The characterization of condensates is however challenging, requiring advanced biophysical or biochemical methods that are often less suitable for in vivo studies. A particular need for easily accessible yet thorough methods that enable the characterization of condensates across different experimental systems thus remains. To address this, we present PhaseMetrics, a semi-automated FIJI-based image analysis pipeline tailored for quantifying particle properties from microscopy data. Tested using the FG-domain of yeast nucleoporin Nup100, PhaseMetrics accurately assesses particle properties across diverse experimental setups, including in vitro, Xenopus egg extracts, and cellular systems. It reliably detects changes induced by various conditions such as the presence of polyethylene glycol, 1,6-hexanediol, a salt gradient, and the molecular chaperone DNAJB6b. By enabling the accurate representation of the variability within the population and the detection of subtle changes at the single particle level, the method complements conventional biochemical assays. Combined, PhaseMetrics is an easily accessible, customizable pipeline that enables imaging-based quantitative assessment of biomolecular condensates in vitro and in cells, providing a valuable addition to the current toolbox.

Transcription factors (TFs) are master regulators of gene expression and control a wide range of cellular functions including embryonic development, signaling pathways, immune response, and differentiation. A tight regulation of gene expression is crucial during all stages of life and changes in the TF function can lead to developmental abnormalities, diseases such as cancer, or resistance to treatment. Therefore, TFs are a promising class of drug targets, and the techniques that would contribute to the development of TF modulators are critical. Electrophoretic Mobility Shift Assay (EMSA) has been a primary tool to verify protein-DNA interactions, where a fluorescent, biotin, or isotope end-labelled DNA probe is used to quantify binding. Such labeling techniques, however, can be costly, time consuming, possess safety hazard risks and require capital equipment for imaging. Here, we optimized a label-free, staining-based EMSA to characterize a potential drug target, homeodomain (HD) TF Pre-B-cell leukemia homeobox-1 (Pbx1) and its binding partner Homeobox A9 (HoxA9). Staining the polyacrylamide EMSA gel with a DNA intercalating green cyanine dye - SYBR safe - allowed the visualization of Pbx1 homeodomain interactions with DNA at nanomolar concentrations and enabled quantitative determination of protein-DNA apparent binding affinity in the sub-micromolar range. Furthermore, a ternary complex of homeodomains of Pbx1 with HoxA9 and the DNA was also visible in the assay. We have shown that the staining-based EMSA can be used to evaluate inhibitors of Pbx1 that block the interaction with DNA. We have further validated the data from our assay with fluorophore labeling-based EMSA. Overall, using HD transcription factors Pbx1 and HoxA9 as a model, we have optimized a reliable and cost-effective staining-based EMSA that enables the high-sensitivity visualization and quantitative evaluation of transcription factor-DNA complexes without the need for end-labeled DNA probes. The streamlined workflow could be readily adapted to other DNA-binding proteins to study their interactions with the DNA, inhibitors, and other proteins.

SignificancePyruvate is a nodal intermediate in cellular metabolism, positioned at the crossroads between glycolysis and fermentative metabolism. It is exchanged between the intracellular and extracellular compartments through the proton-coupled monocarboxylate transporters and between the cytosol and mitochondria through the mitochondrial pyruvate carrier, where it serves as a primary carbon source for respiration. AimOur goal is to present a detailed protocol for quantifying cytosolic pyruvate concentration in neurons at single-cell resolution using a minimally invasive, two-point calibration approach with the FRET-based genetically-encoded fluorescent indicator Pyronic. ApproachThis protocol is based on a non-invasive pharmacological two-point calibration approach, where Pyronics dynamic range ({Delta}RMAX) is established by using trans-acceleration exchange to deplete intracellular pyruvate (RMIN), and by inducing Pyronic saturation (RMAX) through the combination of inhibition of pyruvate export, stimulation of its production, and blockade of its mitochondrial consumption. The protocol also incorporates the previously published KD values for Pyronic obtained from in vitro experiments. This procedure does not require the use of detergents to permeabilize the cells. ResultsImplementing this protocol enables the measurement of absolute cytosolic pyruvate concentrations. This quantitative parameter facilitates comparisons of pyruvate metabolism across different cells, samples and experimental batches, thereby enabling the comparison between a plethora of experimental conditions. ConclusionsThe FRET-based fluorescent indicator Pyronic can be reliably calibrated using a minimally invasive, pharmacology-based two-point calibration protocol in neurons, thus providing a robust and quantitative method to study pyruvate metabolism under various physiological and pathological scenarios.

The cellular environment is crowded with macromolecules and far from thermodynamic equilibrium. This active, crowded environment influences biochemical reactions and the formation of cellular structures such as membraneless organelles. These physical properties can change during normal physiology and in disease states such as neurodegenerative diseases and cancer, impacting cell behavior and function. Therefore, it is crucial to develop methods to characterize these properties. Microrheology is the inference of physical properties from the motion of tracer particles embedded within a material. This technique requires single particle tracking (SPT) and analysis of these tracks through the framework of soft-condensed matter physics. Analysis of SPT data can be challenging due to the lack of comprehensive user-friendly software tools. To address this, we introduce GEMspa, a software package implemented as a plugin for the open source image analysis platform, napari. GEMspa provides a GUI for a commonly used localization/tracking algorithm (via Trackpy), and a suite of methods to extract basic parameters describing particle motion. This platform aims to streamline the workflow of data analysis steps and allow researchers to visualize and optimize parameters for high-quality results, thereby making microrheology accessible to non-expert scientists.

A method to measure telomere length in S. cerevisiae was developed based on bioluminescence resonance energy transfer (BRET). The system uses energy transfer between a luciferase-Rif2 fusion protein and fluorescently tagged Rap1. The study demonstrates that the BRET ratio correlates with the Rap1/Rif2 complex at the telomeres and thus the availability of telomeric Rap1 binding sites. This enables the measurement of telomere length in living cells. The system was able to reproduce reported deviations in telomere length in mutants lacking telomere length regulators, cells treated with telomere length modifying compounds and strains expressing inducible telomerase. The BRET ratio linearly correlated with the average number of telomeric nucleotides derived from long-read sequencing data using a novel algorithm for telomere length calculation. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/711003v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1850c4dorg.highwire.dtl.DTLVardef@1ead295org.highwire.dtl.DTLVardef@1a76358org.highwire.dtl.DTLVardef@6b3183_HPS_FORMAT_FIGEXP M_FIG C_FIG

A label-free procedure to identify single amino acids (AAs) for protein sequencing is developed in theory and simulated in part. A terminal AA cleaved from a protein/peptide, a tRNA, its cognate amino-acyl tRNA synthetase (AARS), and adenosine triphosphate (ATP) are brought together in a container where tRNA, if cognate, gets charged with AA and adenosine monophosphate (AMP) is released. The released AMP (and any free AA and ATP molecules) filters into the cis chamber of an adjoining electrolytic cell (e-cell) from where they pass through a nanopore into the trans chamber. Addition of NaOH to the container deacylates the tRNA if it is charged. The resulting free AA passes into the cis chamber of the e-cell, translocates into trans, and causes a current blockade; AA is immediately known from the identity of the tRNA (the two are cognate). If the tRNA is not charged there is no AA bound to it so AA remains unidentified. In this approach there is no need to distinguish among the 20 AAs by blockade size; it suffices to distinguish blockades from noise: thus a high-precision analog measurement has been transformed into a low-precision binary one. Identification is accurate because of tRNA superspecificity (the tRNA charging error rate is < 1/350); parallel execution with 20 different tRNAs can identify AA in one cycle. This is a de novo method in which no prior information about the protein is used or needed.

Protein degradation mediated by the ubiquitin-proteasome pathway regulates signaling events in all eukaryotic cells, with implications in pathological conditions such as cancer and neurodegenerative diseases. Detection of protein degradation is an elementary need in basic and translational research. In vitro degradation assays, in particular, have been instrumental in the understanding of how cell proliferation and other fundamental cellular processes are regulated. These assays are direct, quantitative and highly informative but also laborious, typically relying on low-throughput polyacrylamide gel-electrophoresis followed by autoradiography or immunoblotting. We present protein degradation on chip (pDOC), a MITOMI-based integrated microfluidic device for discovery and analysis of ubiquitin-mediated proteolysis. The platform accommodates microchambers on which protein degradation is assayed quickly and simultaneously in physiologically relevant environments, using minute amount of reagents. Essentially, pDOC provides a multiplexed, sensitive and colorimetric alternative to the conventional degradation assays, with relevance to biomedical and translational research.

Chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) is a key technique for mapping the distribution and relative abundance of histone posttranslational modifications (PTMs) and chromatin-associated factors across genomes. There is a perceived challenge regarding the ability to quantitatively plot ChIP-seq data, and as such, approaches making use of exogenous additives, or \"spike-ins\" have recently been developed. Relying on the fact that the IP step of ChIP-seq is a competitive binding reaction, we present a quantitative framework for ChIP-seq analysis that circumvents the need to modify standard sample preparation pipelines with spike-in reagents. We also introduce a visualization technique that, when paired with our formal developments, produces a much more rich characterization of sequencing data.