NAR Molecular Medicine

RNA-targeting CRISPR-Cas systems enable modulation of gene expression without permanent genome modification, making them useful for sensitive cell types such as neurons. While CRISPR-Cas technologies have been most extensively applied and validated in primary hippocampal and cortical neurons, their use in sensory neurons remains largely unexplored. Sensory neurons are an established cellular model for studying axon growth and regeneration, pain mechanisms, sensory transduction, and neuron-environment interactions. Here, we evaluated the performance of compact RNA-targeting CRISPR-Cas effectors Cas7-11S, hfCas13X, and hfCas13d in primary rat sensory neurons in culture. Using an endogenous mRNA as the target, we compared knockdown efficiency and assessed the effects of CRISPR-Cas expression on neuronal health. The systems showed distinct differences in performance, with Cas7-11S inducing toxicity, hfCas13X showing minimal knockdown, and hfCas13d providing robust gene silencing with minimal adverse effects on neuronal health. These findings identify hfCas13d as an effective and well-tolerated RNA-targeting CRISPR-Cas tool for sensory neurons and provide important insight into its suitability for neuroscience research and potential therapeutic applications.

ObjectiveTransfer RNA-derived fragments (tRFs) belong to an emerging class of small non-coding RNAs that dynamically respond to metabolic stressors and drive different pathological processes, yet their role in osteoarthritis (OA) remains poorly explored. We aimed to define the tRF landscape in OA and investigate the function of 3tRFAsp(GTC) in chondrocyte stress adaptation and translational control. MethodsEx vivo, cartilage specimens from OA patients (n=6) and healthy donors (n=7) were analyzed by small RNA sequencing to define disease-associated tRF signatures. In vitro, primary chondrocytes derived from OA patients were treated with lipopolysaccharide (LPS) to mimic inflammatory environment of OA, used for small RNA sequencing (n=3) and validation analysis (n=6). Functional studies in C28/I2 chondrocytes included antisense oligonucleotide-mediated 3tRFAsp(GTC) inhibition, AGO2-RNA immunoprecipitation (RIP), polysome profiling, stress granule (SG) immunofluorescence, and differential protein analysis. Computational target prediction and pathway enrichment were used to explore tRF-mediated regulatory networks. ResultsBoth OA cartilage and LPS-treated chondrocytes displayed upregulation of 3tRFAsp(GTC) and 5tRFGlu(CTC), indicating a shared inflammatory tRF signature. Predicted targets of upregulated tRFs were enriched in stress-adaptive, proteostasis, and translational control pathways, whereas downregulated tRFs modulated mitochondrial processes. Silencing 3tRFAsp(GTC) inhibited LPS-induced COX2 and MMP13 expression, prevented ER stress, and blocked SG assembly. RIP confirmed selective recruitment of 3tRFAsp(GTC) into AGO2 complexes. Polysome profiling revealed association with 40S ribosomal subunit, mediating translational arrest and influencing selective mRNA expression. Conclusion3tRFAsp(GTC) emerges as a regulator linking inflammation to translational control and SG dynamics in OA. tRFs thus could represent novel therapeutic targets in OA disease.

BackgroundThe transport of transfer RNAs (tRNAs) from the nucleus to the cytoplasm is a crucial step in the regulation of gene expression and protein synthesis. This process is mediated by specialized export molecules, among which XPOT (Exportin-t, XPO3) plays a central role by recognizing and transporting mature tRNAs through the nuclear pore complex. XPOT is not essential in RNA trafficking in the simple organisms, however the potential impact of XPOT deficiency in human health remains unresolved. MethodsWe identified eight patients from five unrelated families with rare biallelic germline variants in XPOT resulting in putative loss-of-function. Functional analyses were carried out in patient-derived fibroblasts, lymphoblastoid cells and zebrafish models. Ex vivo immunohistochemical stainings for Xpot were performed in the mouse cochlea. xpot knockout zebrafish models were generated to assess the morphology and hearing ability. ResultsAll patients presented with a uniform clinical phenotype that included increased susceptibility to infection, bronchiectasis, severe sensorineural hearing loss, developmental delay, and growth retardation. We demonstrated a complete absence of XPOT protein expression in three patient-derived cell lines. XPOT deficiency leads to disruptions in protein synthesis of the cytokine TNF pathway upon cellular stimulation. Additional XPO1 inhibition in XPOT deficient cells had little effect on cellular functions, suggesting alternative tRNA nuclear transporter pathways. Increased XPOT immunoreactivity was observed in type I spiral ganglion neurons and hair cells of the mouse cochlea, with enrichment in stereocilia. xpot knockout zebrafish model showed dysmorphic features, and reduced hearing, recapitulating key patient phenotypes. ConclusionsOur findings establish a direct connection between impaired XPOT-dependent tRNA export and human pathology. It illustrates that perturbations in nuclear export pathways lead to disease. It also raises the possibility that other nuclear transport receptors may play similarly underappreciated roles in human health and disease. The identification of XPOT as a disease-associated gene opens up new research directions and potential targets for therapeutic intervention.

--Alzheimers disease (AD) is a complex neurodegenerative disorder characterized by widespread dysregulation of gene expression and regulatory pathways. MicroRNAs (miRNAs) act as key post-transcriptional regulators by modulating messenger RNAs (mRNAs), and their disruption can influence synaptic function, neuroinflammation, and neuronal survival. In this study, we present an integrative transcriptome-driven framework to identify AD-associated miRNA-mRNA regulatory signatures and potential biomarkers. Transcriptomic and clinical data were obtained from the Alzheimers Disease Neuroimaging Initiative (ADNI) and the GEO dataset GSE48552. Differential expression analysis (Welchs t-test with FDR correction) identified 148 significantly dysregulated genes (35 up-regulated, 113 down-regulated) between AD and cognitively normal controls. Experimentally validated and predicted miRNA-target interactions were integrated using miRTarBase and additional target resources, yielding 1,669,089 miRNA-gene interactions involving 3,055 unique miRNAs, with strong enrichment toward down-regulated gene targeting. Functional enrichment analysis revealed convergence of miRNA-regulated genes on synaptic signaling, neuronal communication, intracellular transport, apoptosis, oxidative stress, and PI3K-Akt/MAPK-related pathways. A bipartite miRNA-mRNA regulatory network (2,343 nodes; 14,603 edges) was constructed and analyzed using centrality metrics, highlighting key hub regulators including PBX1 and SLC7A5. Finally, supervised machine learning models trained on selected molecular features achieved strong performance, with ensemble approaches (XGBoost/LightGBM) demonstrating robust discrimination of AD from controls.

CAG repeat expansions in ATXN2 are implicated as risk factors for neurological diseases, including amyotrophic lateral sclerosis (ALS) when 27-33 CAG (intermediate) repeats are present. However, how haplotypes around the repeats and CAA interruptions within the repeats are associated with diseases remains poorly understood. Here, we used long-read sequencing on the Oxford Nanopore technologies (ONT) platform to simultaneously infer haplotypes around ATXN2, the number of CAG repeats, and the number of CAA interruptions. We found that haplotypes around ATXN2 and the number of interruptions show ethnicity-specific and ALS-specific distribution. Three CAA interruptions are present at low prevalence ([~]1%) in control populations in multiple ancestry groups, but high prevalence ([~]55%) in ALS individuals with intermediate repeats. Furthermore, we examined 159 individuals with ALS ([~]90% European ancestry) with intermediate ATXN2 repeats and found a unique haplotype in ALS individuals with three CAA interruptions, which can be tagged by an SNV, rs148019457. We further sequenced 41 individuals (EUR = 39) with neurological diseases with intermediate repeats by ONT, and validated that the rs148019457-G allele is only present in haplotypes with three CAA interruptions. Our study shows that 3 CAA interruptions are rare in healthy controls but are common in individuals with intermediate ATXN2 CAG repeats and neurological disorders, and that rs148019457 tags a specific haplotype with 3 CAA interruptions in individuals of European ancestry. These results have implications for the development of precision genomic medicine for neurological disorders, and the tag SNV may help identify those with interruptions from existing microarray genotyping data.

We present a novel integrative analysis of transposable elements (TEs) in 4 single cell RNA-seq (scRNA-seq) datasets of postmortem substantia nigra pars compacta samples of Parkinson Disease (PD) patients matched healthy controls, with the objective of building a cell-type specific trustworthy atlas of TEs that may clarify the role of TEs in sex differences in PD. We have used the soloTE tool to evaluate the TEs expression changes across all snRNA-seq studies identified in our previous systematic review, and then integrated the results using meta-analysis techniques. Finally, we evaluated the possible associations between TEs and protein coding genes by integrating our previous results in this matter with the information of TEs obtained, in order to propose the possible action mechanism by which some of the TEs contribute to PD.

Long non-coding RNAs (lncRNAs) account for a major proportion of the transcriptional output in complex organismal genomes. Their emergence as auxiliary regulators of gene expression as well as their roles in metastasis and cancer progression has put them in the limelight. LncRNAs perform multitudes of functions and often moonlight as regulators, scaffolds and guides. Most lncRNAs are cell and tissue specific and can act as markers for diseases as well as targets for therapeutic interventions. LncRNAs are also known to make use of higher order structures such as G-quadruplexes (G4) to facilitate complex functions and interactions. THAP9-antisense1 (AS1) is a lncRNA coding gene (recently annotated by Ensembl) that codes for 12 lncRNA transcripts and has been implicated in many disease pathologies like gastric cancer, spontaneous neutrophil apoptosis, hepatocellular carcinoma, and the progression of oesophageal cancer. It is the antisense gene pair of the THAP9 gene ( a transposase derived gene) with which it shares a promoter. THAP9-AS1 has been reported to be dysregulated during stress and several cancers. However, the exact role of the lncRNA is not well understood. Bioinformatics driven strategies are used to identify putative quadruplex forming sequences (PQSs) within the lncRNA THAP9-AS1. The identified PQSs are further validated using biophysical, spectroscopic and molecular biology driven techniques. The importance of each G-tract in the formation of a particular RNA G-quadruplex (rG4) is studied via the investigation of several deletion mutants. The findings demonstrate the rG4 forming potential of the identified PQSs within THAP9-AS1.

The KRAS oncogene, central to cellular signaling via MAPK and PI3K-AKT pathways, is a notorious cancer driver frequently activated in pancreatic, colorectal, and lung carcinomas. Regulation of human KRAS oncogene expression is important due to its capital role in cell growth, proliferation, and survival. Misregulation of its expression contributes directly to the development and progression of multiple types of cancer. In previous studies, the role of G-quadruplexes elements in both the promoter and 5 UTR regions have shown to play important roles in KRAS expression, particularly when these G4s elements interact with regulatory protein hnRNPA1. In this study, we reveal that KRAS expression is also modulated at the post-transcriptional level through the formation of RNA G-quadruplexes (rG4s) situated at the 5 untranslated region (5UTR) of the mRNA. Biophysical and binding studies were carried out to probe the interaction. Through isothermal titration calorimetry (ITC), we quantified a strong binding affinity between the UP1 domain of hnRNPA1 and short-nucleotide RNA segments capable of adopting different G-quadruplex fold. The binding interaction is characterized by a favorable Gibbs free energy change in the range of {Delta}G {approx} -32 to -34 kJ/mol, suggesting a specific and energetically favorable association. One-dimensional and two-dimensional 1H-15N HSQC NMR spectroscopy revealed pronounced chemical shift changes in residues of both RNA recognition motifs (RRMs) of UP1, signifying direct contact with the rG4 structure.

Huntingtons disease (HD) is a repeat-associated neurodegenerative disorder traditionally characterized by toxic protein pathology resulting from expanded CAG repeats in the huntingtin (HTT) gene. In recent years, however, studies have identified repeat expansion-driven RNA pathology as an additional and potentially independent contributor to disease. In particular, mutant HTT transcripts containing expanded CAG repeats accumulate in the nucleus and form discrete RNA clusters, a feature shared with several other repeat-associated disorders. While protein aggregation and its downstream consequences have been extensively studied, our current understanding of the composition, organization, and dynamics of these nuclear mRNA clusters remains limited. Progress in this area has been constrained in part by the lack of robust methods to detect and quantify expanded HTT transcripts at single-molecule resolution within intact tissue. As a result, the contribution of RNA clustering to disease mechanisms, its relationship to repeat length, and its interaction with other pathological features of HD remain poorly defined. Here we present a high-throughput RNAscope pipeline that combines automated confocal imaging with rigorous microscope characterization to quantify both single mRNA molecules and multi-transcript clusters in fixed mouse brain tissue. Using 3D Gaussian point-spread function (PSF) fitting calibrated on 200 nm fluorescent beads and pointilistic image features from tissue data, we establish per-slide intensity thresholds from negative controls and normalize experimental signals to single-molecule reference intensities. The critical validation of our approach operates at two scales: for single molecules, the linear relationship between spot size and intensity (r2 > 0.90) reflects variable probe binding along transcripts; for clusters, the linear scaling between cluster volume and mRNA content (R2 > 0.98) confirms uniform probe accessibility and enables quantitative conversion of fluorescence intensity to absolute mRNA counts. Applied to HttQ111+/- knock-in mice across multiple ages, we analyzed thousands of fields of view (FOVs), detecting >900,000 single mRNA molecules and segmenting >1.9 million mRNA clusters using two probes targeting mouse huntingtin (Htt): one detecting the spliced transcript that uses early cryptic polyadenylation sites in intron 1 (HTT1a), and one detecting full-length Htt (fl-HTT). Our analysis reveals considerable heterogeneity in mRNA accumulation: 16-63% of Q111 FOVs are classified as "extreme" (exceeding the 95th percentile of wildtype clustered mRNA levels), with striatum showing higher prevalence than cortex for both probes (HTT1a: 63% striatum, 31% cortex; fl-HTT: 44% striatum, 16%cortex). Extreme FOVs are characterized by elevated cluster numbers (2-6x more clusters per nucleus) and higher cluster density (1.3-1.7x more mRNA per {micro}m3). Cluster localization shows nuclear bias ([~]68%) in normal FOVs, but extreme FOVs exhibit a shift toward cytoplasmic localization, particularly for fl-HTT (48% nuclear vs 68% in normal FOVs), though the interpretation of this shift requires further investigation. Despite the large dataset at the cellular level, our study included only 11 mice (9 Q111, 2 wildtype), and this limited sample size precluded robust statistical inference at the animal level. Nevertheless, these quantitative metrics provide a framework for investigating disease mechanisms and evaluating therapeutic interventions using RNAscope in future studies with larger cohorts.

BackgroundIdentifying safe and broad-spectrum antiviral and anti-inflammatory agents remains an urgent need in infectious and inflammatory diseases. Here, we demonstrated that MNS (NSC170724), a small-molecule nitrovinyl benzodioxole, enhanced antiviral defense while limiting excessive inflammation. MethodsThe antiviral activity of MNS was evaluated in multiple cell lines and mouse infection models across DNA and RNA viruses. Virus-induced and LPS-induced inflammatory responses were assessed using RT-qPCR, ELISA and western blotting. Bulk RNA-seq and ATAC-seq were performed to define transcriptional and epigenetic mechanisms. ResultsMNS significantly suppressed viral infection in vitro and improved survival in four lethal viral infection models, accompanied by reduced viral loads and attenuated tissue injury. MNS also diminished virus-triggered and LPS-triggered inflammatory cytokine production in macrophages and multiple mouse organs, and protected mice from LPS-induced endotoxic lethality. Multi-omics profiling showed that MNS broadly repressed LPS-induced inflammatory transcriptional programs and reversed chromatin accessibility gains across promoters and transcription start sites. Joint analysis of RNA-seq and ATAC-seq data demonstrated consistent downregulation of pivotal inflammatory pathways, such as NF-{kappa}B, Toll-like receptor, and TNF signaling. ConclusionsWith potent activity against viral replication and inflammation in cellular and animal models, MNS emerges as a promising candidate for the treatment of viral infections and hyperinflammatory conditions.

Spinal muscular atrophy (SMA) is a neuromuscular disorder primarily caused by mutations in the Survival of Motor Neuron 1 (SMN1) gene. SMN1 is ubiquitously expressed and encodes a protein essential for the assembly of small nuclear ribonucleoproteins (snRNPs), key components of pre-mRNA splicing. Beyond this canonical role, SMN participates in several other fundamental cellular processes, including RNA transport, regulation of actin dynamics, transcription, and translation. While multiple hypotheses have been put forward to explain selective motor neuron (MN) vulnerability to SMN deficiency, the precise mechanisms involved remain incompletely understood. In this study, we used a simple and tractable C. elegans model to investigate the molecular mechanisms underlying neuronal degeneration in SMA. Silencing of the smn-1 in targeted neurons resulted in defects in the birth and development of both motor neurons and touch receptor neurons (TRNs). In TRNs SMN-1 depletion caused distinct defects in neuronal process morphology. Our results provide evidence that key aspects of SMA pathology are conserved in C. elegans, which may offer new opportunities to elucidate the molecular mechanisms underlying neuronal degeneration in SMA.

The role of the epigenome in age-related neurodegenerative disorders remains understudied. Here, we analyzed circulating cell-free DNA (cfDNA) from blood to detect methylation changes as a liquid-biopsy for Amyotrophic Lateral Sclerosis (ALS). Our study included 20 patients with sporadic ALS, 10 patients with C9orf72-associated ALS, 10 asymptomatic carriers of the C9orf72 repeat expansion mutation, and 21 non-disease controls. Following targeted enzymatic methyl-sequencing (EM-seq) of [~]4 million CpG sites, we detected numerous differentially methylated genes, including several implicated in ALS disease risk and pathogenesis. By integrating multiple epigenetic features, we delineated a distinct epigenetic signature, which achieved an average area under the curve (AUC) of 0.91 {+/-} 0.10 upon receiver operator characteristic (ROC) analysis, which enabled detection of [~]70% of ALS patients with close to 100% specificity. Furthermore, we also identified a set of genes whose methylation status significantly correlated with clinical disease progression and cerebrospinal fluid (CSF) neurofilament levels. Our results reveal the potential of cfDNA-based biomarkers to accurately diagnose ALS and potentially predict disease progression.

BackgroundSmall non-coding RNAs (sncRNAs) play central roles in post-transcriptional gene regulation. In addition to canonical microRNAs (miRNAs), fragments derived from vault RNAs (vtRNAs), called small vault RNAs (svtRNAs), have been reported in human cells. However, the absence of a standardized annotation framework has hindered their systematic detection, quantification, and comparison across small RNA sequencing (small RNA-seq) studies. MethodsWe developed an expression-based annotation strategy to identify svtRNAs from human small RNA-seq datasets. Using FlaiMapper followed by structure and expression-based filtering, we generated two annotation sets: a stringent "miRNA-like" set enriched in Argonaute-associated datasets, and (ii) a broader "Total" set derived from total small RNA-seq libraries under relaxed structural constraints. We explored the expression of the annotated svtRNAs across the different datasets analyzed: multiple normal and tumor-derived human cell lines, including Argonaute immunoprecipitation datasets. ResultsWe identified a repertoire of svtRNAs that are detected across independent datasets and, in several cases, reach abundance levels comparable to canonical miRNAs. Several highly abundant svtRNAs correspond to molecules with experimental validation from prior studies, supporting the robustness of our annotation strategy. Importantly, the same "dominant" (in terms of gene expression) svtRNAs emerged independently from Argonaute-associated and total small RNA datasets, supporting the idea of enzymatically consistent, reproducible svtRNA processing. We further identified svtRNAs derived from distinct vtRNA precursors that could share identical seed sequences, suggesting the possibility of svtRNA families with potential miRNA-like regulatory properties. We provide a standardized annotation that enables reproducible svtRNA quantification. ConclusionsOur study establishes a comprehensive expression-based annotation resource for human svtRNAs. By enabling their systematic detection and reproducible quantification, we show that svtRNAs appear to represent an abundant component of the human small RNA landscape.

Spinal muscular atrophy (SMA) is caused by loss of SMN protein and is increasingly recognized as a multisystem disorder involving molecular pathology beyond motor neurons. Recently, we identified NRF2-KEAP1 signaling as dysregulated in SMA mice. Because NRF2 coordinates transcriptional programs that maintain cellular redox homeostasis and adaptive stress responses, we investigated whether NRF2 signaling is similarly altered in SMA type I patient-derived fibroblasts and whether it can be pharmacologically engaged. Compared with control fibroblasts, SMA fibroblasts displayed reduced basal expression of NRF2 target proteins, including NQO1 and xCT (SLC7A11), along with decreased levels of PGC1. Omaveloxolone (OMAV), a pharmacological NRF2 activator approved for the treatment of Friedreichs ataxia, increased cell viability and upregulated NRF2 target proteins in both control and SMA fibroblasts. Notably, OMAV produced a modest increase in SMN protein abundance and PGC1 levels selectively in SMA cells. Together, these findings support diminished NRF2 pathway output as a feature of SMA fibroblasts and demonstrate that OMAV induces NRF2 target proteins in this human SMA cellular model, consistent with enhanced cytoprotective signaling. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/712434v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1904bfeorg.highwire.dtl.DTLVardef@6d20e2org.highwire.dtl.DTLVardef@89f365org.highwire.dtl.DTLVardef@ca9638_HPS_FORMAT_FIGEXP M_FIG C_FIG

Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system affecting 2.8 million people worldwide. Both genetic and environmental factors contribute to MS risk, with Epstein-Barr virus (EBV) infection being an important environmental factor. To better clarify the role of EBV in MS, we examined its impact on gene expression, chromatin accessibility, and transcription factor binding in primary B cells and EBV-transformed B cells derived from patients with MS and healthy controls. RNA-seq and ATAC-seq analyses revealed extensive MS-dependent gene expression and chromatin accessibility differences in EBV-transformed, but not in primary B cells. These changes are largely accounted for by the expression levels of EBNA2, an EBV-encoded transcriptional regulator previously implicated in MS. ChIP-seq analysis revealed that EBNA2 binding with its interacting human partners RBPJ, EBF1, and PU.1 is highly enriched at MS genetic risk loci, with extensive EBNA2 allelic binding and increased enrichment at MS genetic risk loci in MS-derived cells. Our findings demonstrate that enhanced EBNA2 activity in MS alters human gene expression, chromatin accessibility, and transcription factor binding in an MS-dependent manner. Collectively, this study provides new insights into the molecular mechanisms through which EBV, particularly EBNA2, interacts with host genetic risk to contribute to MS pathogenesis.

Long-read RNA sequencing (lrRNA-seq) provides advantages for transcript discovery and quantification through the sequencing of full-length transcripts. Although recent benchmarks have evaluated long-read technologies and quantification tools, to the best of our knowledge, no study to date has jointly compared sequencing technology, quantification choice, and depth across both bulk and single-cell platforms. Here, we generate a matched dataset using NGN2-induced neurons derived from Fragile X syndrome and isogenic rescue lines, profiled with bulk and single-cell Illumina, Oxford Nanopore Technologies (ONT), and Pacific Biosciences (PB) Kinnex technologies. All platforms and technologies capture the expected FMR1 reactivation signal. We find that PB bulk under-detects and under-quantifies short transcripts (less than 1.25 kb), ONT bulk under-detects and under-quantifies long transcripts (greater than 5 kb), and single-cell long-read technologies a large number of single-cell specific transcripts associated with truncations. Across six bulk and four single-cell long-read quantification tools, Isosceles, Miniquant, and Oarfish provide the best compromise between computational efficiency and performance in terms of quantification accuracy as measured by spike-ins, comparisons to Illumina, and on consensus based down-stream tasks such as differential transcript expression (DTE). Depth-equivalency analyses reveal that PB single-cell sequencing requires approximately three- to four-fold greater depth than bulk to reach comparable power for transcript discovery and differential transcript expression. Our work aims to offer practical guidance for study design, including the choice of technology, sequencing depth, and quantification method. In addition, we hope our data may serve a reference dataset to evaluate emerging long-read transcriptomic protocols and methods as well as more closely investigate FMR1 biology.

Accurate detection of RNA splice variants is often hindered when transcripts lack large distinguishable exonic regions, making conventional PCR strategies challenging. We developed a simple melting temperature (Tm)-guided exon-exon junction (EEJ) RT-PCR method to enable variant-specific detection under these conditions. Uni-directional primers spanning exon-exon junctions were designed so that approximately each half anneals to adjacent exons. The Tm of each half-site was set >7{degrees}C below the annealing temperature, preventing stable binding to individual exons and enforcing junction-dependent amplification. The method was evaluated using HTRA1-AS1 long noncoding RNA variants that share overlapping exon sequences but differ in splice connectivity. HTRA1-AS1 comprises five variants, only one with a large distinguishable exon. Tm-guided EEJ primers robustly discriminated the remaining four variants. After optimization, amplification yielded sharp, single bands with minimal cross-reactivity. Compared with conventional designs, this approach reduced heteroduplex and heteroquadruplex formation, improving band clarity. Sanger sequencing confirmed junction specificity, and the method performed well in multiplex settings. Overall, Tm-guided EEJ RT-PCR is a cost-effective, high-resolution approach for detecting RNA variants lacking easily distinguishable exonic regions, readily compatible with standard RT-PCR and qPCR workflows.

The CRISPR-Cas9 system has revolutionized genome engineering, yet its full therapeutic potential remains constrained by challenges in precisely modulating its activity and specificity. Here we report a fully computational end-to-end pipeline for the de novo design of a single-domain VHH nanobody (NbSpCas9-v1) targeting a structurally conserved, non-catalytic epitope at the PAM-interacting (PI) and RuvC-III interface of Streptococcus pyogenes Cas9 (SpCas9; PDB: 4UN3). Nanobody sequences were generated using BoltzGen, a generative diffusion binder design framework, and co-folded with SpCas9 using Boltz-2 to evaluate structural confidence and binding affinity. The top-ranked model (SpCas9_4UN3_Bivalent_Hub_v1) achieved a complex pLDDT of 0.8406, an aggregate score of 0.8016, and an ipTM of >0.8, indicating high confidence in the nanobody-antigen interface. The designed 1,616-residue quaternary complex (SpCas9 + sgRNA + DNA + nanobody) was subjected to 10 ns of all-atom molecular dynamics (MD) simulation using the AMBER14SB force field within the GROMACS/OpenMM framework. The complex stabilized at RMSD [~]6 [A] with a radius of gyration of 39-44 [A], confirming thermodynamic stability under physiological conditions (310 K, 0.15 M NaCl). A conserved 96.3 [A] inter-molecular distance between the nanobody centroid and the HNH catalytic residue H840 establishes NbSpCas9-v1 as a distal, non-inhibitory binder -- ideally suited for a Bivalent Hub architecture recruiting secondary effectors to the Cas9 ribonucleoprotein (RNP). The nanobody-Cas9 interface is stabilized by 8 hydrogen bonds, 4 salt bridges, and [~]1,850 [A]2 of buried solvent-accessible surface area. These results provide a rigorous structural and dynamic foundation for experimental validation of VHH-based CRISPR-Cas9 enhancers and modulators. GRAPHICAL ABSTRACTThe computational workflow proceeds from SpCas9 crystal structure acquisition (PDB: 4UN3) through BoltzGen nanobody design, Boltz-2 structural co-folding, 10 ns explicit-solvent MD validation, and Bivalent Hub functional characterization. The PyMOL rendering below shows the full quaternary complex at atomistic resolution.

Global quantification of DNA cytosine modifications, including 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC), is important for understanding cancer biology, though established methods require multi-step workflows and costly instrumentation. Here we show that attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy combined with regression modelling enables rapid, label-free, and non-destructive quantification of both modifications from DNA samples. Using Adenomatous Polyposis Coli (APC) promoter DNA standards spanning 0-100% modification, we identified modification-sensitive spectral features and observed that 5-hmC produces greater spectral changes than 5-mC. A univariate peak-ratio approach yielded strong linearity for both modifications (R2 = 0.97), while partial least squares regression (PLSR) improved quantification accuracy to R2 = 0.99 (RMSE = 2.6%) for 5-hmC and R2 = 0.97 (RMSE = 5.7%) for 5-mC. In composite mixtures containing all three cytosine states, 5-hmC remained highly quantifiable (R2 = 0.97; RMSE = 5.1%), while 5-mC accuracy decreased (R2 = 0.90; RMSE = 9.6%), consistent with the greater spectral distinctiveness secondary to the hydroxymethyl group. Transferability was assessed using circulating tumour DNA (ctDNA), short cell-free DNA fragments shed from tumour cells into the bloodstream, comprising multiplexed reference material spanning seven genomic regions and a polydisperse fragment-length distribution (155-220 bp). After domain adaptation between synthetic and ctDNA spectra, we obtained a quantitative methylation calibration with R2 = 0.98 and RMSE = 5.2% under cross-validation. These results support ATR-FTIR spectroscopy as a viable platform for global cytosine modification quantification and establish proof-of-concept applicability to ctDNA analysis.

DNA length analysis is essential for genomic workflows including next-generation sequencing and fragmentomics based diagnostics. Conventional approaches typically require large, expensive instrumentation and sample-destructive protocols with long processing times. Here we present a rapid, label-free approach integrating vibrational spectroscopy with deep learning to quantify DNA fragment length distributions. We demonstrate that ATR-FTIR and Raman spectroscopy capture length-dependent spectral features arising from phosphate backbone, nucleobase, and structural vibrations. Machine learning models trained on spectra acquired from purified monodisperse DNA (50-300 bp) predicted DNA length with high accuracy (R2=0.92-0.94), with multimodal fusion improving performance to R2=0.96. A convolutional neural network trained on 35 DNA mixtures comprising molecules of different lengths also successfully deconvoluted their fragment length profile. Transfer learning enabled adaptation to biological samples, achieving low prediction error (RMSE=0.3-7.2%, {Delta}=12 bp). Importantly, the method requires only 4 L sample and 15 minutes passive drying, with no consumables beyond cleaning materials, and allows full sample recovery. This establishes vibrational spectroscopy as a scalable alternative for DNA length quantification.