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.

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.

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.

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.

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.

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.

Plaque assays remain the gold standard for bacteriophage quantification, but routine plaque counting is labor-intensive, time-consuming, and poorly suited to large experiments or automated workflows. Conventional plaque images also often provide insufficient contrast for simple software-based counting, especially when plaques are small, faint, or heterogeneous. Here we show that a membrane-impermeant nucleic acid dye can convert standard bacteriophage plaque assays into a high-contrast, machine-readable format compatible with simple automated counting. In a soft-agar overlay workflow, fluorescent labeling enabled plaque detection and automated enumeration using an open-source ImageJ pipeline based on Find Maxima, without phage engineering, machine learning, or custom software. Because the method improves the image contrast of the assay itself, it may also provide improved input for future machine-learning or other advanced automated counting workflows. The method was evaluated across diverse phage-host systems spanning dsDNA, ssRNA, filamentous, and enveloped phages, including T7, MS2, M13, and phi6. In lytic systems, fluorescent signal emerged prior to or alongside conventional plaque visibility and yielded automated counts that agreed closely with manual counting. M13 exhibited delayed fluorescence consistent with its chronic, nonlytic lifestyle, yet remained machine-countable at the conventional next-day endpoint. A Gram-positive Leo2-Bacillus safensis system revealed an important compatibility limit: dye incorporation at plating inhibited plaque formation, but a post-labeling workflow restored detectability and automated counting. Together, these results show that membrane-impermeant dye labeling can make plaque assays more computationally tractable while preserving the accessibility of standard phage methods. This approach provides a practical path toward higher-throughput, statistically rigorous phage biology in both low-resource and automation-oriented laboratories.

Quantitative analysis of single-molecule localisation microscopy (SMLM) data remains challenging because biologically diverse, well-annotated datasets are limited, whilst nanoscale protein organisation is heterogeneous and difficult to describe with hand-tuned metrics. We present SynthMLM, a framework that infers interpretable structural descriptors from experimental SMLM data and uses these descriptors to generate synthetic localisation datasets. We demonstrate SynthMLM by generating descriptor-matched synthetic datasets corresponding to diverse experimental SMLM datasets and evaluating their agreement with real data using descriptor-level and embedding-based measures. By enabling controlled generation of synthetic localisation data, SynthMLM provides a practical resource for benchmarking SMLM analysis methods, testing algorithm failure modes, and developing machine-learning workflows where large, labelled datasets are required.

BackgroundLamins are major regulators of the spatial and functional organization of chromatin. Lamins at the nuclear periphery form the lamina that anchors heterochromatin to the nuclear envelope. A subpool of A-type lamins localizes in the nuclear interior, where they also bind to euchromatic genomic regions. A-type lamin properties and chromatin association are regulated by lamin-associated polypeptide 2alpha (LAP2). Here we systematically analyze, how LAP2 depletion affects chromatin organization, accessibility and gene expression on a genome-wide level. ResultsLAP2 depletion in mouse dermal fibroblasts positively and negatively affects chromatin accessibility and gene expression throughout the genome, which correlates with changes in chromatin association of A-type lamins and the nucleosomal remodeler proteins BRG1 and CHD4. In particular, A-type lamins bind to open chromatin regions close to BRG1 and CHD4 binding sites and deregulated genes, but do not directly accumulate on genes and BRG1 and CHD4-enriched sites. Unsupervised clustering of the datasets on LAP2-bound genomic regions confirms spreading of A-type lamins to active chromatin regions containing deregulated genes and an enrichment of chromatin remodelers on a subset of these genomic regions. ConclusionsLAP2 depletion in fibroblasts leads to a gross rearrangement of chromatin. Genome-wide chromatin reorganization is linked to spreading of A-type lamins to active chromatin regions and accompanied by a restriction of chromatin remodelers to a subset of active genomic regions. These changes correlate with changes in chromatin accessibility and gene expression throughout the genome, particularly in regions where lamin binding is gained in LAP2 knockout versus wildtype cells.

Fundamental cellular decisions of life and death are governed by intricate and tightly regulated intracellular signalling pathways that determine whether cells proliferate, enter quiescence, or undergo programmed cell death (apoptosis). Live-cell fluorescence imaging enables these processes to be observed in real time at single-cell resolution, but two problems limit their study. First, existing biosensors do not allow apoptotic status and cell cycle progression to be resolved in tandem within the same cell. Second, interpreting live-cell imaging data is challenging even where multiplex reporters exist, as the biological meaning of fluorescent signals depends on their temporal ordering, and large-scale imaging experiments generate complex, multidimensional data that are difficult to analyse systematically and at scale. Here we address both problems. We present FluoroFate, a generalisable and user-friendly graphical interface-driven tool for time-resolved single-cell analysis of multiplex live-cell imaging datasets, which integrates existing, robust deep learning-based segmentation, cell tracking, and temporal classification methods to quantify fluorescent reporter dynamics in individual cells across time without the need for specialist computational expertise. Alongside FluoroFate, we develop tricistronic Fluorescent Ubiquitination-based Cell Cycle Indicator (Fucci) and apoptosis biosensors, enabling simultaneous monitoring of cell cycle progression and caspase activation within the same cell. Applying FluoroFate, we resolve apoptotic and non-apoptotic cell death at the single-cell level based on the temporal ordering of Annexin V and propidium iodide signals, identifying distinct kinetic and phenotypic cell death profiles in response to pharmacological perturbation. We highlight divergent temporal dynamics and modes of cell death between birinapant and cycloheximide treatment, reflecting differences in how TNF/TNFR1 signalling is disrupted by these agents. At the single-cell level, we uncover parallel, independently regulated death programmes, demonstrating that loss of RIPK1 selectively impairs apoptotic cell death whilst leaving non-apoptotic death largely unaffected. We then use FluoroFate to analyse timelapse images of our combined Fucci-apoptosis reporters, resolving cell cycle progression and caspase activation within the same cell over time. Together, FluoroFate and our new cell cycle and apoptosis biosensors represent a broadly applicable platform for extracting mechanistic insight from live-cell imaging data.

Three-dimensional live-cell fluorescence imaging of yeast cells is crucial for studying cell-cycle mechanics and regulation. However, extracting multi-channel phenotypes within dense cell clusters remains an image-processing bottleneck. Standard deep-learning models segment cells but fail to track mother-bud boundaries, mitotic spindle shapes and spindle-localizing proteins. Investigators rely on labour-intensive manual coordinate plotting, introducing observer bias and often exclude clustered cell data due to visual complexity. Here, we present an open-source Fiji pipeline for automated yeast cell image processing and deterministic classification of cell-cycle, spindle and protein dynamics. The workflow utilizes a dual-segmentation architecture via custom Cellpose models to capture the mother-bud cell boundaries. Extracted masks are integrated with multi-channel fluorescence data using a Difference-of-Gaussians framework to resolve SPB coordinates and localized protein kinetics, which a rule-based decision-tree maps to precise mitotic phenotypes. Validation demonstrates a 50-fold acceleration with ~6% deviation from manual analysis. Availability: Zenodo at https://doi.org/10.5281/zenodo.22083016.

Reliable delineation of the head and tail of swine spermatozoa supports automated assessment of boar semen quality, from morphometric measurement to the quality control of insemination doses. In practice this relies on fluorescent staining, which adds chemistry, cost, and delay to every acquisition and labels only the nucleus. Recent work coupling imaging flow cytometry with machine learning has advanced rapidly, yet the segmentation stage still depends on a stained channel at inference and resolves the head alone. We present a supervised encoder decoder network that segments boar spermatozoa from brightfield images acquired on an Amnis ImageStream Mark II with no stain at inference. Training labels derive from the Hoechst 33342 nuclear channel (Ch7), recorded in registration with brightfield (Ch1); the dye serves only as an annotation source, and the network sees Ch1 alone. The best semantic segmentation model reaches a Dice coefficient of 0.940 on held-out cells. For comparison we evaluate a classical morphological pipeline, four further semantic segmentation models spanning three decoder families and two ImageNet-pretrained backbones, and two zero-shot pipelines built on the Segment Anything Model 2 (SAM 2), prompted either by a dilated box around the predicted head mask or by head and tail boxes emitted by a Gemma 4 Vision Language Model (VLM). The zero-shot route scores 0.637 against Ch7 but labels the tail, which the fluorescence protocol cannot. Cells scoring worst under the supervised model proved to be mostly registration failures rather than segmentation failures, as Ch7 is displaced relative to Ch1. Manual screening for this drift is infeasible at dataset scale, so we propose a flagging system that marks any Dice below 0.792, two standard deviations below the mean, and pairs it with a zero-shot pipeline in which a VLM l and SAM 2 cross-check the flagged cell before human review.

Calcium transients encode cellular and neuronal activity across timescales ranging from milliseconds to hours, yet linking these transient signals to downstream molecular states remains a major challenge. We recently introduced Caprola, a calcium-dependent protein labeling tool that converts calcium transients into permanent fluorescent marks for later analysis. In this way, Caprola enables tracking of neuronal activities in animal models as well as retrospective identification of labeled cells for isolation and transcriptomic analysis. However, the relatively slow labeling kinetics of Caprola required high concentrations of fluorophore probe and relatively long labeling times, which limits its sensitivity and applicability, in particular in vivo. To address this limitation, we generated Caprola variants with up to 29-fold faster labeling rates than their predecessor. We demonstrate that our new Caprola variants record calcium transients in cells and in zebrafish larval brains under conditions where previous Caprola variants did not show labeling. We further expand the applicability of Caprola to activity-dependent marking of postsynaptic compartments, opening new avenues for coupling functional activity histories with downstream molecular and transcriptomic analyses.

The binding affinities of a chimeric analog of a riboflavin derivative linked to biotin, (6- (7,8-dimethyl-2,4-dioxo-3,4-dihydrobenzo[g]pteridin-10(2H)-yl)hexyl 5-((3aS,4S,6aR)-2- oxohexahydro-1H-thieno[3,4-d]imidazol-4-yl)pentanoate), referred to as C6-Rf-biotin-tag, to the riboflavin binding retain or streptavidin are in the M range, 1.29 {+/-} 0.277 and 3.00 {+/-} 0.459, respectively. These values suggest that C6-Rf-biotin-tag has potential applications in diagnostic assay and labelling target flavin binding proteins. The C6-Rf-biotin-tag which was characterized with respect to physical and biochemical properties retains UV/Vis spectroscopic and fluorescence behavior similar to riboflavin.

Endothelial cells (ECs) derived from human induced pluripotent stem cells (hiPSCs) are increasingly used to model vascular diseases and test therapeutic strategies. However, the efficiency and reproducibility of differentiation can vary depending on the culture medium and its supplemented factors and stages. Here, we directly compared two defined media, APEL and BPEL, for iPSC-to-ECs differentiation. iPSCs were differentiated over 10 days with sequential growth factor induction, followed by magnetic-activated cell sorting or flow cytometry for CD31+ cells. Both media produced ECs with similar morphology and marker expression, including CD31 and VE-cadherin. Functional assays demonstrated comparable tube formation, indicating equivalent endothelial functionality. Cost analysis indicated that APEL had a higher total reagent cost but generated a higher total cell yield, resulting in a comparable cost per 10 total cells, whereas BPEL was more cost-efficient for producing CD31/VE-cadherin endothelial-specific cells. Our results suggest that APEL and BPEL media are equally effective for generating iPSC-derived ECs, providing flexibility in method selection for vascular disease modeling and drug discovery applications.

Huntington's disease is caused by a CAG repeat tract expansion in the huntingtin gene, resulting in production of pathogenic N-terminal huntingtin protein fragments associated with disease pathology. Despite their central role, detection of these fragments has relied on a limited antibody repertoire with reproducibility concerns. Here, we describe the generation and characterization of recombinant rabbit monoclonal antibodies targeting two reciprocal neoepitopes flanking the huntingtin exon 1/exon 2 junction corresponding to amino acids P90 and K91. The P90 antibodies (clones 1B12, 11G2) demonstrate fragment-length-selective recognition of the C-terminal HTTexon1 P90 neoepitope with no detectable binding to full length huntingtin. A side-by-side comparison of the widely used monoclonal antibody MW8 from two different sources revealed measurable lot-to-lot drift in its fragment selectivity, whereas the recombinant P90 antibodies, expressed from a defined, sequenced clone, maintained consistent specificity, addressing this source-dependent variability. Whereas P90-positive fragments can arise through alternative splicing of the HTT1a transcript, generation of the reciprocal K91 N-terminal HTTexon2 neoepitope would require site-specific proteolytic cleavage, a mechanism that has not yet been directly tested for lack of a suitable reagent. The K91 antibody (clone 7G10) binds the N-terminal K91 neoepitope with high affinity and specificity over full length huntingtin and provides, for the first time, a tool capable of directly interrogating whether such cleavage occurs. Neoepitope specificity of these antibodies was orthogonally confirmed by protease digestion (Lys-N and Arg-C) coupled with intact mass spectrometry. As an additional outcome of the immunization and selection strategy, we discovered human-mouse cross-reactive antibodies (clones 27F5, 31C10) targeting the proline-rich domain of huntingtin that will facilitate mouse-human translational studies. All antibodies are recombinant, ensuring long-term reproducibility, and are being made available, along with their sequences, to the research community.