DNA-based molecular classifiers have emerged as a promising strategy for precise cancer diagnosis, offering a superior alternative to invasive biopsy detection. However, current DNA-computation-dependent molecular classifiers remain limited by complex pathways and cumbersome weight assignment procedures. To address this, we developed weight-controllable biobarcode probes (WBPs) that enable programmable signal amplification via precise stoichiometric regulation of barcode strands versus nonbarcode strands. These probes demonstrated robust performance in the weighted molecular computation. Using these WBPs, we performed fluorescence-based analog-to-digital signal conversion, enabling the representation of 128 combinations across up to seven targets. By integrating three miRNA inputs trained in silico machine learning, we constructed a WBP-based molecular classifier that can distinguish breast cancer patients from healthy individuals, achieving an accuracy of 84.00% on clinical serum samples. This work expands the scope of biobarcode technology from single-target detection to logical analysis of multiple targets, establishing a scalable and noninvasive platform for precision cancer diagnosis.

Revealing the protein-protein interactions (PPIs) of membrane proteins is as challenging as their structural reconstruction, primarily because the molecular structures and related PPIs of membrane proteins are highly dependent on the bio-membrane where they are situated. DNA origami offers a platform for manipulating molecules with nanoscale precision. Herein, we used a square-like DNA origami, refer to as DNA origami rubbing, to map the two-dimensional distribution of membrane proteins in situ. Through artificial models and cell studies, we correlated the efficiency of barcode recording of DNA origami rubbings with the distance between adjacent proteins, and we observed that the frequency of adjacent proteins mapped by DNA origami rubbings was correlated to the abundance of the bait protein. We demonstrated that the DNA origami rubbing was able to reflect the distribution change of adjacent proteins caused by adding the ligand of bait protein. Our results suggested that the DNA origami rubbing can serve as a powerful tool in the field of protein interactomics.

Bladder cancer (BCa) holds a critical position among urological malignancies worldwide, characterized by its significant impact on public health. Current detection methods are often constrained by invasiveness, high costs, or limited sensitivity, impeding early and rapid diagnosis and prediction of reoccurrence. Here, we present a detection method combining loop-mediated isothermal amplification (LAMP) with lateral flow dipsticks (LFD) for the identification of methylated TWIST1 and PENK genes in urine samples. This approach aims to provide a rapid, convenient, and point-of-care (POC) tool for BCa detection, particularly in resource-limited settings. Featuring an optimized sample preprocessing protocol, a robust LAMP system, and intuitive visual readout via LFD, the LAMP-LFD method achieved 100% accuracy in both diagnostic (25/25) and prognostic (3/3) cohorts, which demonstrates significant potential for DNA methylation-based diagnostics and prognosis monitor. With further refinement, we anticipate that this method will play a crucial role in improving diagnosis and prognostic recurrence surveillance for BCa, facilitating earlier intervention and improved patient outcomes.

Tumor progression remains a significant challenge due to the complexity of oncogenesis and the prevalence of undruggable protein targets. Strategies such as targeted protein degradation (TPD) and RNA interference (RNAi) have emerged as complementary approaches to eliminate disease-driving proteins at the protein and transcript levels, respectively. However, the integration of these mechanisms within a single-molecule construct has not been realized. Here, we report a Dicer-activatable aptamer-adamantane/siRNA (AptHyT-siRNA) chimera that combines hydrophobic tagging-induced proteasomal degradation with siRNA-mediated gene silencing. Upon cleavage inside cells, the chimera releases both a functional AptHyT degrader and a siRNA duplex. As a proof of concept, we chose the androgen receptor (AR) in castration-resistant prostate cancer (CRPC) as a target to demonstrate synergistic AR degradation and mRNA knockdown. This resulted in robust antiproliferative and antitumor activities in vitro and in vivo. Our findings establish a versatile platform for dual-mechanism oligonucleotide therapeutics with potential for broad application in precision oncology.

[This corrects the article DOI: 10.1016/j.fmre.2023.06.015.].

The approach of tailoring ligands on the surface of extracellular vesicle (EV)-based drugs has been pivotal in achieving an effective EV-based therapeutic delivery. However, indiscriminate modifications to the membranes can diminish efficacy due to uncontrollable binding affinities and disruptions in the EV membrane functionality, often caused by disordered ligand coverage. In this study, we present an approach for affinity-tunable and receptor-interference-free extracellular vesicle mimetic (EVM) functionalization. We employ a soft wireframe DNA origami-based "cobweb" to achieve a customized spatial distribution of targeting ligands on the EVM surface, allowing for precise control over the cellular affinity and subsequent EVM uptake. Moreover, by utilizing the hollow structure of the DNA origami cobweb, we are able to program EVM without compromising the native functions of their membrane proteins such as CD47-mediated immune evasion. We believe that our strategy will provide a versatile platform for the targeted delivery of EVM-based drugs with high efficiency.

Functional nucleic acids (FNAs) are essential elements for designing advanced molecular tools, yet their de novo design faces challenges due to the vast sequence space and inefficiency of experimental screening methods. Nucleic acid large language models (NA-LLMs) offer new opportunities for FNA design, but their generative capability remains underexplored. Here we introduce InstructNA, a framework leveraging NA-LLMs and high-throughput systematic evolution of ligands by exponential enrichment (HT-SELEX) to guide de novo design of FNAs without relying on structural information. InstructNA encodes semantically rich FNA representations and robustly decodes FNA sequences, enabling the generation of various types of FNA such as transcription factor-binding DNA and protein-binding aptamers with enhanced functionality and high sequence diversity. Compared with the traditional HT-SELEX, InstructNA generates 100% and 200% more strong aptamer binders for two protein targets, with a sequence similarity to the original HT-SELEX aptamers as low as 38%. These results underscore the efficacy and robustness of InstructNA, demonstrating its potential for FNA design.

Biomolecular condensates regulate essential biological processes relevant to health and disease. However, the mechanisms driving pathogenic condensate formation and their therapeutic targeting have not been fully elucidated. In amyotrophic lateral sclerosis and frontotemporal dementia caused by C9orf72 GGGGCC repeat expansions (c9ALS/FTD), the expanded repeat RNA and repeat-associated non-AUG translation products are key pathogenic factors. Here, we show that the GGGGCC-repeat RNA and poly(GR) form cocondensates in vitro and in cellulo. The G-quadruplex and hairpin structures of GGGGCC-repeat RNA act as scaffolds to accelerate liquid-to-solid phase transition and aggregation of poly(GR), with the hairpin structure promoting amorphous solid-like condensates in vitro and reducing poly(GR) mobility. The cocondensation of GGGGCC-repeat RNA and poly(GR) exacerbates nucleolar stress and cellular toxicity. Targeting both G-quadruplex and hairpin structures of GGGGCC-repeat RNA with small molecules diminishes poly(GR) aggregation and ameliorates cellular dysfunction. These findings expand our understanding of poly(GR) aggregation in c9ALS/FTD, highlight the importance of RNA structure in regulating protein aggregation and suggest that targeting the RNA scaffold may expand the druggable space of pathogenic condensates.

The rapid expansion of the information era necessitates molecular information encoding systems that simultaneously offer high capacity and robust security. DNA, characterized by its ultra-high information density, outstanding chemical stability, and inherent programmability, stands out as a promising medium for molecular data storage. Nevertheless, traditional DNA sequence-based information encoding strategy remains intrinsically static, restricting real-time and dynamic manipulation of stored information, and thereby limiting its practical utility in adaptive data processing and dynamic encryption. To overcome these limitations, we present a programmable data encoding and dynamic encryption platform leveraging DNA Temporal Barcodes (DTBs). DTBs consist of DNA strands designed with distinct retention times during high-performance liquid chromatography (HPLC) separation. Through systematic programming of chemical modifications and DNA sequences, we constructed a versatile DTB library capable of encoding a broad diversity of information states. HPLC, while providing time-resolved readout for DTBs, also allows for their efficient recovery and subsequent reuse in information encoding. Notably, to further reinforce data security, we introduce a key-triggered DNA ligation mechanism that generates reconfigurable DTBs, facilitating dynamic encryption at the molecular level. This work establishes a versatile strategy for constructing programmable, high-capacity, and dynamically adaptable molecular information security systems.

The clustered regularly interspaced short palindromic repeat (CRISPR)-associated system has displayed promise in visualizing the dynamics of target loci in living cells, which is important for studying genome regulation. However, developing a cell-friendly and rapid transfection method for achieving dynamic and long-term genomic imaging in living cells with high specificity and accuracy is still challenging. Herein, a robust and versatile method is presented that employs a barrel-shaped DNA nanostructure (TUBE) modified with aptamers for loading, protecting, and delivering CRISPR-Cas9 to visualize specific genomic loci in living cells. This approach enables dynamic tracking of target genomic regions (Chr3q29, a repetitive region of chromosome 3) throughout the mitotic process and captures variations in their spatial distribution and quantity accurately. Distinct dynamic behaviors between the Chr3q29 and telomeres are observed, which are linked to their unique chromosomal positions and levels of mobility. High-resolution multicolor labeling of the target genes is achieved, with a high degree of colocalization between the enhanced green fluorescent protein and cyanine-5 channels, facilitating precise imaging of target loci. This method not only supports dynamic genomic imaging but also enables multiplexed tracking, providing a powerful visualization tool for studying cellular processes and genetic interactions in real time within living cells.

DNA computing has emerged as a transformative paradigm for tackling computational problems at the molecular level, yet existing approaches remain constrained in algorithmic interpretability, efficiency, and scalability. Here we present a DNA-based decision tree system that modularly embeds classification rules into DNA strand displacement reaction cascades for interpretable decision-making across various configurations. It supports cascaded networks exceeding 10 layers, parallel computation of 13 decision trees in a Random Forest involving 333 strands, and multimode operation (linear/nonlinear, binary/multi-class, single/tandem trees), while maintaining low leakage, rapid signal propagation, and minimal computational elements. Coupled with a DNA-methylation sensing module, it translates biomarker profiles into molecular instructions for tree traversal, reproduces in-silico predictions and enables accurate disease subtype classification. The decision tree system represents an interpretable, scalable, and memory-efficient DNA computing approach and will open new avenues for programming intelligent molecular machines with broad applicability.

Solid-phase synthesis has revolutionized the programmable preparation of oligonucleotides (ONs), enabling precise gene expression modulation and expanding their applications in therapeutic and material sciences. To further enhance ON functionality, this study introduces a novel adamantane-based phosphoramidite for oligonucleotide modification. Adamantane, known for its hydrophobicity and stability, was incorporated into nucleic acid aptamers using automated synthesis. Two aptamers─Sgc8 and AS1411─were functionalized with one or two adamantane units, and the products were purified and validated using high-performance liquid chromatography and mass spectrometry. The incorporation of adamantane significantly altered the aptamers' polarity and facilitated their self-assembly with poly-β-cyclodextrin, forming stable supramolecular complexes, as demonstrated by polyacrylamide gel electrophoresis. Additionally, adamantane-modified AS1411 exhibited enhanced degradation of its target protein, nucleolin, in MCF-7 cells, suggesting potential utility in targeted protein regulation. These findings establish a versatile platform for functionalizing ONs, broadening their potential for biomedical and nanotechnological applications.

DNA aptamers that bind small molecules with high affinity have revolutionized the fields of biosensing and bioimaging. Recently, a DNA aptamer named 1301b has been identified as the most potent DNA aptamer for the binding of adenosine triphosphate (ATP) with a dissociation constant (KD) of ~2.7 µM. However, the structural basis and recognition mechanism remain unclear, hindering further development of this DNA aptamer. In this study, we first design a shortened DNA aptamer namely 1301b_v1 that retains a good affinity for ATP and then determine the tertiary structure of 1:1 1301b_v1-ATP binding complex using solution NMR spectroscopy. The overall complex structure shows an "L" shape architecture with the binding pocket formed by two internal loops. The ATP intercalates into the binding pocket through forming hydrogen bond with G14 and stacking with T8·A28 and G9. We also reveal an adaptive binding mechanism where the DNA aptamer switches from a semifolded state to a stable tertiary structure upon ATP binding. Based on the structure-function relationship, we introduce 2'-O-methyl modification to residues in the central junction and obtain a DNA aptamer named 9/10/16OMe with a KD of ~0.7 µM for the binding of ATP. These results underscore the ability of DNA molecules to form intricate three-dimensional folds with sophisticated functionality, opening up avenues for designing novel DNA-based molecular tools.

In this study, we present a systematic approach for the rational design of synthetic allosteric DNA aptamers. This methodology enables precise control over the allosteric ON-OFF transition in fluorescent DNA aptamers, allowing for the engineering of aptamers with highly tunable fluorescent properties. When combined with toehold-mediated strand displacement, we have developed a series of allosteric aptamers in which the target sequence functions as a specific allosteric modulator. Furthermore, these aptamers have been applied in synthetic DNA computing and in the construction of responsive nanostructures that light up upon activation. ### Competing Interest Statement The authors have declared no competing interest.

The ability of cytokine receptors to mediate the internalization of targets in lysosomes positions them as specific and effective effectors for protein degradation strategies. However, challenges remain, including the potential unintended activation of cell-proliferation-related cytokine receptors, as well as limitations in programmability and structural flexibility of protein degradators. In this work, a CXCR7-targeting chimera (AP-CRTAC) that functions as a CXCR7 inducer by covalently linking a membrane protein-targeting aptamer with a mutant-CXCL12 mimic peptide is developed. This peptide selectively binds to CXCR7 without activating CXCR4. The AP-CRTAC, which incorporates various aptamer forms from DNA, RNA, or even bispecific aptamers, has shown significant efficacy in degrading one or more proteins or protein mutants on the cell surface. Moreover, the AP-CRTAC constructed with a 2' F-pyrimidine-modified RNA aptamer targeting EGFR effectively degrades various EGFR activating mutations. Notably, AP-CRTAC enhances the sensitivity of the L858R/T790M/C797S triple mutant lung cancer cells, which are resistant to current EGFR-targeted therapies, to the third-generation EGFR inhibitor osimertinib in both in vitro and in vivo settings. This research introduces an engineered CXCR7 inducer with high specificity and programmability for the targeted degradation of cell surface proteins, while minimizing unwanted side effects.

Capitalizing on the superior programmability of RNA for the precise targeting of diverse targets, fluorogenic RNA aptamer (FRAP)-based biosensors have become powerful tools for synthetic biology. By engineering FRAPs with recognition systems, these biosensors achieve remarkable specificity and sensitivity across detection targets spanning small molecules, proteins, and RNAs. Their unique capacity for real-time visualization of biomolecular dynamics renders them indispensable for living cell imaging applications. In this review, we discuss the generation process of FRAP-based biosensors, propose standardized methods for in vitro performance characterization, and provide a comprehensive analysis of their progress in living cell applications. Additionally, we analyzed strategies for improving biosensor performance in cellular environments. This review provides insights to accelerate the creation of FRAP-based biosensors, targeting diverse molecules, ultimately inspiring dynamic monitoring capabilities in living cell systems for decoding complex cellular responses.

Cell-free RNA (cfRNA) circulating in biofluids comprises RNA molecules originating from diverse tissues and cell types, providing a dynamic and real-time snapshot of the body that can be harnessed for early disease detection, differential diagnosis, and longitudinal monitoring. Nevertheless, clinical translation of cfRNA analysis is hindered by pronounced variability arising from diverse pre-analytical conditions, as well as the immaturity and limited standardization of subsequent analytical pipelines. Recent advances in sequencing technologies, together with optimized library preparation protocols and computational frameworks, have substantially improved the sensitivity, reproducibility, and interpretability of cfRNA profiling, thereby paving the way for its broader diagnostic and biomedical applications. In this Review, we highlight the critical impact of pre-analytical workflows on cfRNA studies, provide a summary of current technologies from low-plex assays to high-throughput sequencing, explore the promising potential of cfRNA in clinical applications, and conclude with a discussion of current challenges and future directions.

Molecular diagnosis of biliary tract cancer (BTC) remains a significant clinical challenge due to the lack of sensitive and specific diagnostic tools. Although large panels based on multi-biomarkers have demonstrated potential in enhancing diagnostic accuracy, their clinical application is hindered by complexity and high costs. To overcome these limitations, we have developed a DNA-based molecular computation system that integrates the detection of plasma circular RNAs (circRNAs) with molecular computation, enabling intelligent and rapid diagnosis of BTC. By identifying and validating a specific and small set of circRNA biomarkers that are differentially expressed in BTC patients, we designed a DNA computation framework that directly translates biomarker levels into diagnostic outcomes without the need of external analysis and interpretation. In a validation cohort of 70 individuals, our approach achieved a diagnostic accuracy of 83%, demonstrating its potential as a cost-effective and efficient tool for rapid diagnosis of BTC. This work highlights the potential of molecular computation in enhancing integrated and rapid cancer diagnostics, paving the way for clinical implementation.

Biomolecular condensation lays the foundation of forming biologically important membraneless organelles, but abnormal condensation processes are often associated with human diseases. Ribonucleic acid (RNA) plays a critical role in the formation of biomolecular condensates by mediating the phase transition through its interactions with proteins and other RNAs. However, the physicochemical principles governing RNA phase transitions, especially for short RNAs, remain inadequately understood. Here, we report that small CAG repeat (sCAG) RNAs composed of six to seven CAG repeats, which are pathogenic factors in Huntington's disease, undergo phase transition in vitro and in cells. Leveraging solution nuclear magnetic resonance spectroscopy and advanced coarse-grained molecular dynamic simulations, we reveal that sCAG RNAs form duplex structures with 3 '-sticky ends, where the GC stickers initiate intermolecular crosslinking and promote the formation of RNA condensates. Furthermore, we demonstrate that sCAG RNAs can form cellular condensates within nuclear speckles. Our work suggests that the RNA phase transition can be promoted by specific structural motifs, reducing the reliance on sequence length and multivalence. This opens avenues for exploring new functions of RNA in biomolecular condensates and designing novel biomaterials based on RNA condensation.