Methods

Summary/AbstractTelomere length has a significant impact on human health. Short telomeres cause age-related diseases, including pulmonary fibrosis, immunodeficiency, and bone marrow failure, while long telomeres predispose to cancer. Given the impact on human health, accurately measuring telomere length is important. A variety of methods have been developed over the past 40 years to measure telomere length. Many of these methods report only on the mean length of all of the telomere in the cell. Here, we describe the Telomere Profiling protocol using Oxford Nanopore Technologies (ONT) based on long read sequencing that can accurately measure chromosome specific telomere length.

BackgroundInvestigating the subcellular distribution of proteins is crucial for understanding complex cell behaviours and disease mechanisms, and fluorescence microscopy has become a key tool for visualising protein localisation. Endogenous protein tagging, where the sequence for a tag (typically a peptide or fluorescent protein) is integrated into the native genetic sequence encoding a protein of interest, enables proteins to be visualised without the need for antibodies against the target protein. ORANGE (Open Resource for the Application of Neuronal Genome Editing) is a CRISPR-Cas9-based endogenous protein tagging technique which relies on homology-independent targeted integration (HITI)-mediated gene editing. Utilising HITI as the DNA repair pathway of choice gives ORANGE the advantage of being more efficient than classical homology-directed repair (HDR)-based endogenous protein tagging techniques and additionally, means it can be used in post-mitotic cells. ResultsWe applied the ORANGE system to tag three proteins, CYFIP1, JAKMIP1, and STAT3, and confirmed that the expressed fusion proteins demonstrate expected subcellular localisations through fluorescence microscopy. Unexpectedly, the efficiency of ORANGE editing was less than 1% in HEK293 cells, despite high transfection efficiency. To improve the editing efficiency associated with ORANGE, we combined the ORANGE method with an established Sleeping Beauty transposase/CRISPR-Cas9 fusion technique, which has been shown to enhance HITI-mediated gene editing. Using this new method, which we term Sleeping ORANGE, we successfully tagged CYFIP1 with the fluorescent protein mNeonGreen. Importantly, quantitative analysis by fluorescence microscopy and flow cytometry demonstrated an increase in editing efficiency using Sleeping ORANGE, with an approximately 12.85-fold increase in the percentage of mNeonGreen-expressing cells at 72 hours post-transfection relative to populations of cells edited with the ORANGE method. ConclusionsWe have incorporated the DNA-binding domain of the Sleeping Beauty transposase to create a new system that improves the gene-editing efficiency of the ORANGE technique. With further developments to optimise CRISPR gRNA design and reduce off-target effects, the Sleeping ORANGE technique may form a valuable tool for researchers to better understand subcellular localisation and dynamics.

High content imaging is being applied to achieve quantitative fluorescence readouts in increasingly complex 3-dimensional (3D) cell culture models such as spheroids and organoids. Compared to conventional 2D assays, 3D assays better represent biological heterogeneity but require more complex sample preparation, 3D imaging and 3D image analysis that can affect the accuracy and precision of such assays. We used spheroids formed from the NRAS-activated melanoma cell line 19161 modified to express an ERK kinase translocation reporter (KTR) as an exemplar 3D phenotypic assay carried out in 96-well plates. The spheroids were treated with the ERK activator TPA and a range of concentrations of the MEK inhibitor Binimetinib. 3D live-cell imaging with sub-cellular spatial resolution was performed using a dual-view oblique plane microscope (dOPM) - a form of single-objective light-sheet microscope - and the experiment was performed separately at 4 different institutes. The results were analysed using an identical 3D analysis pipeline and parameters. We assessed the variation in assay readout using a linear mixed effects model. Random variance at the well level was negligible (SD = 0.0048 relative to range of KTR biosensor readout at reference site of 0.17), indicating low technical noise. Treatment effects were dose-dependent and highly statistically significant compared to DMSO control across all sites (Dunnett-corrected p < 0.001). The range in KTR readout between the minimum (3.5 M Binimetinib) and maximum (100 nM TPA) treatments varied between 59 to 96% relative to the reference site. Measured bias in KTR readout between sites was between 6 and 12% of the range of the reference site. This study quantifies the reproducibility of a 3D live spheroid-based assay employing a fluorescence biosensor requiring readout out at the per-cell level using the dOPM platform and discusses areas where experimental protocol could be improved in the future to further improve reproducibility.

We present a simple and efficient way to add cis dialdehydes, phosphoryl groups, or cis diols to the 3 prime end of oligonucleotides using periodate oxidized nucleotides (oNTPs) and terminal deoxynucleotidyl transferase (TdT). The 3 prime end cis dialdehyde-modified oligos are generated by incubating TdT with an oligo for several minutes followed by addition of a oNTP and incubated at 30 degrees C for 30 minutes to an hour. After allowing the addition of the cis dialdehydes, heating the reaction mixture at 90 to 95 degrees C for 10 minutes yields oligonucleotides with 3 prime phosphoryl groups. The 3 prime cis diol modified oligos are synthesized by starting with 3 prime cis diol nucleotides (HO-NTPs). The cis dialdehyde modified oligonucleotides and cis diols may then be used for a variety of investigations such as studying the interaction of proteins with the 3 prime end of DNA, and possibly RNA. As an example, we demonstrate the efficacy of using an oligonucleotide modified with oGMP at the 3 prime end as an affinity label for TdT and identified a peptide fragment that has been shown to contain two of three aspartate residues found to be in the TdT active site.

Bacterial sortases are widely used in sortase-mediated ligation (SML) experiments for various protein engineering applications. The power of these enzymes to bind and cleave a specific recognition motif, followed by ligation to another substrate using a ping-pong reaction mechanism has numerous applications in vaccine and antibody/nanobody drug conjugate development, as a diagnostic and therapeutic tool, in creating novel insulin derivatives, etc. The most widely used sortase for SML is the class A sortase (SrtA) from Staphylococcus aureus (saSrtA), and its engineered derivatives. Despite its utility, saSrtA and other endogenous sortases are relatively inefficient enzymes and use can be limited by the need for specific recognition of the Cell Wall Sorting Signal (CWSS), sequence Leu-Pro-X-Thr-Gly, where X=any amino acid. Therefore, there is a need to continue to identify new tools for SML and to develop screening assays towards these endeavors. Here, we present optimization procedures for a FRET-based assay utilizing the GFP derivatives mTurquoise2 and SYFP2 to directly monitor formation of ligation products generated via SML. Similar to related assays, our recombinant substrates can be easily manipulated to screen either the substrate recognition motif, second substrate nucleophile, and/or sortase variants themselves. We believe continued optimization of this assay for a variety of high throughput uses in sortase screening strategies is possible, providing a proof-of-concept approach for continued SML reagent development.

Living cells are highly dynamic and densely crowded environments in which organelles such as vesicles undergo continuous motion that is essential for cellular processes. Therefore, accurate tracking of individual organelles is crucial for understanding intercellular dynamics and functions. However, precise tracking of individual organelles in living cells remains challenging due to high organelle densities, frequent particle overlap, and the coexistence of stationary and motile organelles. In particular, stationary organelles can obscure the trajectories of moving organelles, leading to tracking errors and fragmented tracks. To overcome these challenges, we developed Multiple Particle Tracking via Velocity Filtering (MPT-vVF), an unbiased, semi-automated tracking framework that incorporates a mathematically derived velocity-filtering algorithm to selectively identify and track moving organelles with high accuracy in crowded intracellular environments. MPT-vVF integrates denoising, background subtraction, and a velocity-matching detection step that discriminates true particle motion from noise based on spatiotemporal continuity, followed by robust trajectory linking. We demonstrate that MPT-vVF can accurately resolve nanometer-scale displacements of immobilized beads, highlighting its high tracking precision. We also validate the robustness of MPT-vVF by quantifying the transport of brain-derived neurotrophic factor (BDNF)-mRFP-containing vesicles in living hippocampal neurons. Furthermore, MPT-vVF reveals that exposure to 50-nm nanoplastics impairs vesicular transport, reducing both travel length and speed of BDNF-containing vesicles in living neurons. These findings establish MPT-vVF as a powerful method for quantitative analysis of intracellular organelles in crowded living cells and suggest its broad application to biophysics, cell biology, and soft matter research.

BackgroundRecombinant expression of the SARS-CoV-2 receptor-binding domain (RBD) is essential for vaccine development, serological diagnostics, and mechanistic studies. Primary human fibroblasts offer physiologically relevant protein folding and post-translational modification, yet their short lifespan limits scalable production. We used an immortalized human splenic fibroblast cell line to stably express RBD-sfGFP for longitudinal characterization and downstream studies. MethodsImmortalized human primary splenic fibroblasts were transfected by electroporation with a plasmid encoding SARS-CoV-2 RBD fused to superfolder GFP (sfGFP), with a neomycin resistance cassette (neoR) for G418 selection. Four independent G418-resistant cultures (n=4), designated HPSF-IM-RBD-BHSKPU T1-T4, were established from distinct selection flasks. Based on previous screenings, two cultures (T1, T3) were monitored for 98 days (14 passages, P1-P14); two cultures (T2, T4) were monitored for 42 days (6 passages, P1-P6). RBD-sfGFP expression was assessed by fluorescence microscopy at 7-day intervals. For each timepoint, 2 fields were imaged and analyzed for relative fluorescence intensity (normalized to global maximum = 100%) and mean fluorescence intensity (MFI, normalized to global maximum = 100%). Coefficient of variation (CV), linear regression, and Pearson correlation were calculated. ResultsAll four cultures exhibited robust GFP fluorescence, confirming stable transgene retention. Expression ranking: T1 (93.1% +/- 3.6%) > T3 (89.2% +/- 3.4%) > T2 (84.2% +/- 3.2%) > T4 (79.7% +/- 3.9%). Long-term cultures T1 and T3 retained [~]100% of Day 7 signal at Day 98 (T1: 100.7%; T3: 100.0%). Expression exhibited passage-dependent oscillation rather than progressive silencing. CV increased over time in T1 (1.5% -> 8.5%), indicating growing inter-cellular heterogeneity. A strong positive correlation between fluorescence and MFI (Pearson r = 0.823, p = 7.44 x 10-11) suggested coherent population-level regulation. ConclusionsHPSF-IM-RBD-BHSKPU cells stably retain RBD-sfGFP expression for over 3 months, validating their utility as a recombinant protein production platform. However, oscillatory dynamics and increasing heterogeneity are consistent with position-effect variegation at distinct integration loci. Consequently, early passages (P1-P4) are optimal for applications requiring maximal uniformity. Ultimately, these cells provide a practical tool for RBD production and a valuable model for studying epigenetic regulation of transgene expression in human primary fibroblast backgrounds.

With the rapid development of modern biotechnology, DNA vectors have become fundamental tools for inserting, transferring, and expressing specific gene sequences in various fields such as gene cloning, gene expression, gene editing, and gene therapy. However, when dealing with complex structured DNA sequences, traditional vector construction methods face challenges with low connection efficiency. This study proposes a new method for constructing recombinant vectors by employing a strategy of high-temperature treatment followed immediately by placement on ice, effectively reducing the complexity of DNA structures and enhancing the efficiency of PCR product-vector connection, thereby improving the construction efficiency of recombinant vectors. This paper describes the technical details of the method, experimental validation, and applications in gene cloning, gene recombination editing, and the preparation of gene therapy drugs, providing a new efficient tool for molecular biology experiments.

Antisense oligonucleotides (ASO) are nucleotide polymers that hybridize to sense strands and have been successful in treating a variety of diseases. A wide range of strategies have been investigated to optimize and develop ASO for clinical studies. A key objective for this study was to provide an overview of the range of detailed data that get be obtained and provide an updated method review on how to design surface plasmon resonance (SPR) kinetic experiments for DNA oligonucleotide hybridization studies that can also be applied to other ASO including peptide nucleic acids (PNA). We describe many lessons learned from published literature and provide a state-of-the-art strategy and methods for generating not only kinetic but also thermodynamic characterizations of oligonucleotide hybridization. In this study we have performed an SPR kinetic and thermodynamic analysis for the hybridization of HIF1 antisense DNA strands to its immobilized Intron2-Exon3 splice site sense DNA strand to provide insight, in general, on the optimal length and insight into optimal design of DNA ASOs. We provide a process on how to design experiments to: 1.) obtain oligonucleotide-length dependent kinetics, 2.) analyze reactions to obtain association and dissociation rate kinetics (ka, kd), assess if hybridization follows a 2-state model and to obtain kinetic dissociation constants (Kd), 3.) perform temperature-dependent hybridization kinetics to obtain thermodynamic values ({Delta}H{degrees}, {Delta}S{degrees} and {Delta}G{degrees}) that can give insight into the molecular interactions driving hybridization, 4.) compare experimental thermodynamic values to values derived from nearest-neighbor prediction models to identify atypical reactions and importantly 5.) enable calculations to predict oligomer hybridization affinity at the physiological 37 {degrees}C temperature to asses if the design of the oligomer will have the required cellular activity for a therapeutic effect. The strategy and results presented throughout the paper are compared to previous SPR reports and suggestions made to optimize kinetic studies.

Precise quantification of myofilament protein phosphorylation is essential for understanding the regulation of cardiac contractility in health and disease. Although Phos-tag SDS-PAGE is widely used to resolve phosphorylated protein isoforms, its reproducibility and quantitative reliability are often limited by variability in the key experimental factors, including gel composition, electrophoretic conditions, protein loading, and sample preparation. Here, we present a standardized manganese (Mn2+)-Phos-tag SDS-PAGE workflow optimized for cardiac myofilament proteins, using myosin regulatory light chain 2 (MLC2) and cardiac troponin I (cTnI) as model targets. We systematically evaluated critical parameters - including Mn2+ and Phos-tag concentrations, acrylamide composition, electrophoretic regime, buffer chemistry, protein loading, and EDTA-mediated transfer - to define conditions that maximize phospho-species resolution while preserving quantitative fidelity. We further demonstrate that electrophoresis rate, sample loading, and extraction strategy significantly influence band morphology, signal intensity, and the apparent distribution of phospho-species. As a use case scenario, we compared Trichloroacetic acid (TCA) extracted mouse left ventricular homogenates with myofibrils prepared using a widely adopted Triton-X-100 tissue-demembranization protocol. Myofibril preparation was associated with profound MLC2 dephosphorylation at the earliest stages of preparation, whereas cTnI exhibited a marked reduction in higher-order, low-stoichiometry phosphoforms. Further evaluation of Myosin-binding protein C (MyBP-C) showed progressive loss of phosphorylation over the course of 24 hours. We submit that TCA-extracted heart standards in combination with Phos-tag gels can provide valuable quality control for the phosphorylation status of myofibril preparations, and that inclusion of a high-affinity PP2A and PP1 phosphatase inhibitor like okadaic acid may benefit future myofibril mechanics studies.

The bacterial three-hybrid (B3H) assay is a powerful genetic tool for detecting interactions between RNA and RNA-binding proteins (RBPs) and assessing the consequences of RBP mutations. This transcription-based system connects the strength of an RNA-protein interaction to the expression of a lacZ reporter gene in Escherichia coli cells. This in vivo approach allows researchers to dissect RNA-protein interactions within a cellular environment, bypassing the need for biochemical purification of RNAs or proteins. This chapter details a three-day protocol for generating quantitative B3H data. Since a significant challenge in B3H assays is RNA misfolding, we describe a recently optimized set of B3H constructs that mitigates this issue by isolating bait RNAs as discrete folding units.

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

An important step toward clinical implementation of (epi-)genomic assays on liquid biopsies is their validation on identical samples within and across laboratories. For these validation studies, there is a need for cell-free DNA (cfDNA) samples with defined tumor fractions and (epi-)genomic aberrations. However, the amount of circulating cfDNA isolated from patient samples is often limited, especially in pediatric cases. Additionally, patient samples contain a high degree of variability in cfDNA yield and tumor fraction. Several commercial artificial cfDNA products are available for validation studies, however their use is restricted to specific assays, aberrations and/or tumor entities. Alternatively, artificial cfDNA samples can be produced by fragmenting genomic DNA to mimic highly fragmented cfDNA derived from both tumor and healthy blood, followed by mixing artificial tumoral and healthy cfDNA at defined fractions. In this study, we compared native cfDNA with artificial cfDNA generated by three different fragmentation methods, including sonication and two enzymatic digestions using micrococcal nuclease and double-stranded deoxyribonuclease (dsDNase). We assessed fragment length profiles, end motifs and nucleosome occupancy patterns from shallow whole-genome sequencing data, as well as coverage profiles from targeted panel sequencing, together with a small-scale mixing experiment of tumor and healthy cell derived artificial cfDNA. Although sonication remains a convenient high-throughput approach to generate artificial cfDNA for certain downstream applications, enzymatic fragmentation, particularly the dsDNase-based method, more faithfully reproduced native cfDNA characteristics.

This paper presents and critically reviews the results of original and some literature based experimental studies conducted by the authors last years on the structural organization of DNA in dormant (starvation stress), anabiotic dormant (4 HR treatment) E. coli cells, as well as the K12 {Delta}dps strain, which lacks the Dps protein (Dps null E. coli). The experimental data includes small-angle synchrotron radiation diffraction (SAXS) and transmission electron microscopy (TEM) data. Synchrotron radiation diffraction experiments on K12{Delta}dps cells allowed us to conclude that peaks at 44.3, 22.1, and 14.8 angstrom resolutions are associated exclusively with ordered DNA organization. Peaks at 44.3, 22.1, and 14.8 angstrom resolutions are also observed for samples of dormant (starvation stress) cells and anabiotically dormant cells. Therefore, this ordered DNA organization also applies to samples of dormant and anabiotically dormant cells. A model is proposed that considers the ordered DNA organization in the cell as a cholesteric liquid crystal. The powder diffraction pattern calculated based on this model is compared with experimental small angle X ray scattering (SAXS) data obtained on Dps-null cell samples. The model completely reproduces the key features of the experimental diffraction pattern from Dps-null cell samples. Accordingly, the cholesteric liquid crystal model corresponds to DNA packaging in dormant and anabiotically dormant cells. Cholesteric liquid crystal ordering should be further considered in all models of cellular DNA packaging. To address the question of which structural organization of DNA predominates in the cell: the cholesteric liquid crystal or nanocrystalline or whether they coexist and fully manifest themselves under different external conditions, it is necessary to utilize the latest methodological advances in structural analysis.

The dCas9 system has rapidly been developed into many tools to explore different aspects of the human genome; the high binding specificity, coupled with the inactive nuclease enzyme, allows for precise recruitment of molecules to specific sequences of DNA. We sought to exploit these capabilities to create a tool for assessing the real-time proximity of two DNA sequences within a biological system. By incorporating aptamers into gRNAs, dCas9 molecules can be used to recruit the {beta}9 or {beta}10 strands of split-NanoLuc(R) to specific DNA sequences and quantify the proximity of those sequences based on their ability to complex with the luciferase fragment ({Delta}11S) and produce luminescence. While many tools exist to detect a single DNA sequence, this system is uniquely capable of assessing how two DNA sequences interact with each other. As expected, we found that the interaction of two dCas9 molecules was affected by their linear distance from each other on dsDNA. Surprisingly, we found that their interaction was also strongly influenced by rotational orientation, even for sequences that are close together in linear space. This finding indicates that dCas9 rotational alignment is an important consideration for designing dCas9 systems that target multiple DNA sequences simultaneously. Beyond the findings presented herein, we believe this DNA proximity detection tool has the potential to be adapted for applications involving the proximity and orientation of two DNA sequences.

Chromatin accessibility has long been used as a marker for regions of DNA with regulatory potential. Fiber-seq detects chromatin accessibility on individual DNA fibers, enabling analyses beyond the identification of the accessible chromatin regions (ACRs). By providing single molecule level high resolution, Fiber-seq provides unprecedented qualitative descriptions, including potential categorizations of ACRs, identification of internal transcription factor footprints and nucleosome positioning within individual DNA fibers. As with all tools, the power of this technique depends on careful experimental design and data analysis -- incorrect usage will result in incorrect conclusions. Here we offer guidelines and flag potential pitfalls when generating and analyzing Fiber-seq data, such as (1) the optimum levels of adenosine methylation per-fiber, (2) the power of per-fiber state inference, (3) the importance of controlling for read depth and methylation rates when comparing across samples, (4) the limitations of long-read sequence mapping, and (5) suggestions for identification of differentially accessible peaks across samples.

Isothermal nucleic acid amplification tests enable rapid and decentralized molecular diagnostics but often lack robust quantitative readouts compared to quantitative PCR. Here, we present a semi-quantitative nucleic acid measurement approach using machine learning to extract spatiotemporal features from real-time fluorescence imaging of rapid isothermal amplification reactions in microfluidic chips. A convolutional neural network was trained on multiple images sampled throughout a chip-based recombinase polymerase amplification reaction to classify samples into clinically relevant or logarithmically spaced concentration ranges spanning five orders of magnitude. The clinical classification model achieved 94.6% accuracy, and the logarithmic model achieved 92.7% accuracy, with most errors occurring between adjacent concentration categories. By learning spatiotemporal patterns of fluorescence development rather than relying on explicit feature extraction, the model remained accurate at both high and low nucleic acid concentration regimes where other quantitative isothermal molecular tests struggle. This approach enables automated interpretation of amplification reactions and extends the usable dynamic range of the assay. These results demonstrate that integrating machine learning with image-based amplification methods can support rapid semi-quantitative molecular testing and may facilitate broader deployment of nucleic acid diagnostics outside centralized laboratory settings. Author summaryMany rapid nucleic acid testing methods for infectious diseases are simple to run but struggle to measure how much genetic material is present, which limits their usefulness in clinical decision-making. In our work, we study a technique that produces visible fluorescent patterns during nucleic acid amplification reactions. Traditionally, the amount of nucleic acids present are measured by counting individual bright spots, but this becomes difficult when the target nucleic acid concentration is high and the spots merge together. We developed a machine learning approach that models how the fluorescence pattern changes over time. By analyzing a sequence of images from each reaction, our model can assign samples to concentration ranges across a wide span. This allows us to extract meaningful information even when traditional analysis methods break down. Because this approach works with simple imaging systems and does not require complex equipment, it could help support more informative and accessible diagnostic testing in point-of-care and low-resource settings.

Circular single-stranded DNA (cssDNA) is a versatile biomolecule with applications spanning genome editing, DNA nanotechnology, synthetic biology, molecular diagnostics, and aptamer development. Compared with linear single-stranded DNA, cssDNA offers enhanced structural stability, resistance to in-cellulo degradation by exonucleases and enables the generation of long, sequence-defined DNA molecules that are difficult to obtain through conventional chemical synthesis methods. Despite its growing utility, widespread adoption of cssDNA has been limited by the lack of accessible, scalable, and cost-effective production methods, with many existing workflows relying on specialised reagents, extensive optimisation, or commercially synthesised DNA. Here, we present a streamlined, end-to-end protocol for the laboratory-scale production of high-purity cssDNA using an M13 phagemid-based system and standard molecular biology laboratory infrastructure. The workflow encompasses bacterial culture, phage amplification, nuclease treatment, phage precipitation, anion-exchange purification, and quality control, with practical optimisations to improve yield, reproducibility, and scalability. Using this approach, yields range from 120-195 {micro}g of purified cssDNA from 300 mL of culture supernatant. The protocol provides detailed guidance on critical process parameters, troubleshooting, and quality assessment, enabling reliable production of cssDNA suitable for a wide range of downstream molecular biology and genome engineering applications.

Magnetic field effects (MFEs) in biological systems are typically small and experimentally challenging to measure reproducibly across large sample populations. Existing approaches to measure such effects often rely on low-throughput microscopy or custom-built magnetic stimulation systems that provide limited control over magnetic field geometry, synchronization, or experimental automation. Here, we present an open-source magnetofluorescence imaging platform designed for bacterial plate-scale screening of MFEs in live colonies. The instrument integrates a programmable three-axis vector electromagnet, synchronized fluorescence excitation and imaging, and integrated acquisition software with per-frame metadata logging on a hardware-synchronized data acquisition card. An extensive calibration procedure enables accurate generation of arbitrary magnetic field vectors, while synchronized triggering ensures deterministic alignment between field application, illumination, and image acquisition. The system images an entire 100 mm Petri dish in a single acquisition. Typical experiments monitor hundreds of bacterial colonies simultaneously over multi-hour acquisition sequences. Control software, calibration routines, mechanical design files, and acquisition workflows are provided openly to facilitate replication. Instrument performance is demonstrated through detection of magnetic field-dependent fluorescence changes in E. coli expressing the engineered magnetosensitive fluorescent protein MagLOV2. This instrument provides a flexible and scalable platform for high-throughput magnetobiology, synthetic biology, and quantum biology experiments.

Single-cell proteomics (SCP) generates protein abundance measurements across hundreds to thousands of individual cells, offering unprecedented resolution to study cellular heterogeneity. However, existing differential abundance (DA) methods are limited to detecting shifts in mean expression, leaving biologically relevant differences in shape undetected. Indeed, the specific power of SCP is to identify differences between individual cells in a population, which are typically only found as shape differences rather than in mean expression. We here therefore present gamdid (generalized additive models for differential distributions), a novel statistical framework and R package for differential distribution (DD) analysis in SCP data. gamdid is based on generalized additive models (GAMs) to flexibly model heterogeneous distributions, perform inference and provide interpretable visualizations. Through semi-synthetic benchmarking on two SCP datasets, gamdid demonstrates conservative false discovery rate control and substantially outperforms competing methods for differences in shape, while achieving comparable performance for mean shifts. A spike-in case study further demonstrates the utility of gamdid and its interpretable visualization. Uniquely among DD methods, gamdid supports omnibus testing across more than two groups, with post-hoc pairwise comparisons via stagewise testing, and is specifically tailored for proteomics abundance data.