As the rate of data generation gradually exceeds the growth rate of the capabilities of traditional storage media, DNA storage, capable of storing information at the base pair level, emerges as a viable alternative. However, given the current precision of biotechnology, substantial error correction redundancy is necessary for the full recovery of data. We introduce a encoding method, the Random Interleaving Data Encoding (RIDE) method, to address this issue. RIDE can reduce the need for error correction redundancy while ensuring the encoded sequences comply with biochemical constraints, such as restrictions on homopolymers, minimum free energy requirements, and GC content limitations, by combining with conventional encoding methods such as fountain code, Reed-Solomon code, etc. Our DNA storage experiments demonstrate the application of the RIDE to internal and external RS code can generate more reliable data recovery results than conventional error correction coding methods. Experimental results indicate that the sequence information density using RIDE encoding can achieve at least 1.85 bits/nt, and the sequence recovery rate surpasses that of the Reed-Solomon code encoding method by approximately 4.5%. Furthermore, we highlight the potential applicability of RIDE for future long-sequence encoding through simulation experiments.

DNA has emerged as a promising medium for next-generation information storage due to its ultra-high storage density, long-term stability, and low energy consumption. With the rapid growth of global digital data, DNA storage provides a potential alternative to conventional electronic media. Dynamic random access, which allows selective retrieval of target information without reading the entire dataset, is essential for the practical application of DNA storage. Recent advances in PCR-based indexing, hybridization-assisted retrieval, and electrically controlled addressing have significantly improved access efficiency. However, challenges such as limited primer capacity, amplification bias, and molecular crosstalk still restrict large-scale implementation. This review highlights recent progress, current challenges, and future perspectives for achieving efficient and reliable large-scale DNA data storage systems.

Viral contamination poses significant risks in respiratory transmission, environmental exposure, and food safety. Accurate identification and quantification of viruses remain challenging, particularly in low-concentration and complex sample matrices. To address this, a high-efficiency and scalable electrophoretic microfluidic platform was developed for rapid enrichment and sensitive detection of negatively charged viral particles across diverse sample types. The device features a vertically layered microchannel design separated by a 0.8 mu m porous membrane, combined with a multi-electrode configuration to generate a precisely controlled electric field. Numerical simulations were employed to optimize electrode layout and field distribution, effectively guiding virus particles from the sample to the enrichment channel under electrophoretic force. Under optimal conditions (30 V, 200 mu L/h), the platform improved the RT-qPCR detection limits for H1N1 and SARS-CoV-2 by 2-3 orders of magnitude. The system demonstrated broad-spectrum compatibility, structural stability, and strong biocompatibility, with potential for seamless integration into automated workflows. This work provides a versatile and effective strategy for virus preconcentration and detection in complex environments such as exhaled breath, ambient air, and drinking water.

Rapid and sensitive detection of airborne respiratory viruses from exhaled breath is essential for early diagnosis and outbreak control, yet current strategies suffer from low capture efficiency and sample dilution. Here, we present a fully automated, noninvasive Phase-change Drywall Cyclone Sampler (PDC-sampler), which integrates phase-change condensation with a CFD-optimized cyclone gas-liquid separator. This design rapidly condenses viral aerosols─particularly those <5 μm─into microdroplets and directs them into a stable spiral liquid stream, thereby enhancing capture efficiency and producing a small-volume, high-concentration liquid sample. The collected condensate is directly coupled to a microfluidic RNA-release chip, enabling on-chip viral RNA lysis. From a single tidal exhalation (∼0.5 L), the system generates ∼20 μL of high-concentration RNA lysate in 10 s of on-device processing (sample-to-lysate), directly compatible with nucleic acid detection. Combined with ddPCR, it achieves detection limits as low as 5-9 copies per exhalation for pathogens including SARS-CoV-2 and H1N1 influenza. This ultrarapid, small-volume, sample-to-result workflow provides a scalable, field-deployable solution for point-of-care diagnosis and real-time respiratory virus surveillance.

Exhaled breath is a noninvasive and repeatable biological matrix offering new opportunities for respiratory microbiome analysis, yet its extremely low microbial biomass limits current high-throughput applications. Building on our previously developed phase-change drywall cyclone sampler (PDC-sampler), which integrates condensational growth with dry-wall cyclone separation, we established a validated workflow for efficient aerosol collection and multi-Omics sequencing of exhaled breath. Using this platform, exhaled breath from 15 febrile patients and 6 healthy volunteers was analyzed via shotgun metagenomic and 16 S rRNA sequencing to assess microbial composition, diversity, and functional features. The PDC-sampler significantly increased microbial DNA yield, enabling stable detection of bacterial taxa dominated byPseudomonadota, Bacillota, Bacteroidota, andActinomycetota. Functional annotations and diversity metrics revealed distinct microbial and metabolic patterns between individuals, confirming the platform's analytical sensitivity and biological representativeness. This work experimentally validates the feasibility of exhaled breath microbiome sequencing using the PDC-sampler, providing a practical and generalizable framework for noninvasive respiratory microecology studies and future diagnostic applications.

Staphylococcus aureus (S. aureus), one of the most prevalent foodborne pathogens, poses a persistent global threat to public health by causing severe infections and food poisoning. We present β-cyclodextrin/surfactant inclusion-mediated nucleic acid enrichment strategy synergized with a ratiometric electrochemical biosensor for the robust determination of S. aureus. Unlike commercial kits limited by dilution effects, our method utilizes cetyltrimethylammonium bromide (CTAB) to induce the condensation of nucleic acids from large-volume lysates, followed by a competitive inclusion reaction where β-cyclodextrin encapsulates the hydrophobic alkyl chains of CTAB. This mechanism triggers the efficient release of DNA into a micro-volume, achieving a 12-fold enrichment. The enriched target is subsequently quantified using a ratiometric electrochemical interface equipped with methylene blue (MB) and ferrocene (Fc), where the current ratio (IMB/IFc) serves as an intrinsic self-calibration parameter to eliminate the internal/external disturbances. Under optimized experimental conditions, the developed biosensor demonstrated a wide linear range spanning from 10¹ to 107 CFU/mL, with a low limit of detection of 8 CFU/mL. Moreover, the biosensor achieved reliable quantification of S. aureus in complex real samples, including peach juice and UHT skim milk, confirming its practical applicability. This work establishes a novel and cost-effective electrochemical sensing strategy that couples DNA enrichment and release with ratiometric signal, providing a feasible technical approach for rapid pathogen detection.

Accurate quantification of airborne pathogen transmission risks in indoor environments remains a major public health challenge. Existing airborne infection studies often lack empirical and biological validation under realistic conditions. Thus, this study develops a novel Aerosol-Scaled Quantitative Microbial Risk Assessment (AS-QMRA) framework using non-infectious viral aerosols as surrogates that complements conventional tracer gas and computational simulations methods. The framework quantitatively established a full-process risk quantification from aerosol generation to human exposure by defining the source emission ratio, transmission intensity ratio, and sampling-to-inhalation conversion factor, which extend the Wells-Riley model to an aerosol-scaled formulation. Under controlled chamber conditions, MS2 bacteriophage aerosols were released and collected using a condensation-enhanced cyclone sampler (PDC-sampler). The resulting concentration data were compared with theoretical predictions to calibrate and validate the AS-QMRA model. Results revealed that surrogates differ fundamentally from pathogen aerosols. The laboratory-generated aerosols exhibited 102-105 times higher emission rates than humans and showed 1.2-12 (near-field) and 1.4-1.5 (far-field) higher dilution intensity depend on particle size differences. Sampling results were consistent with theoretical expectations, demonstrating the model's reliability and scalability. This study provides a promising direction for more realistic and accurate indoor airborne infection risk assessment, supporting future applications in ventilation design, building engineering, and epidemic prevention.

Scleractinian corals are foundational to coral reefs, vital marine ecosystems under threat from climate change. Montipora, a widely distributed reef-building genus, contributes through continuous corallum mineralization, yet polyp budding and skeleton formation processes remain elusive. This study elucidates temporal and spatial dynamics of skeletal formation and polyp budding in Montipora capricornis using high-resolution micro-computed tomography (micro-CT). We demonstrate that skeleton-canal network formation precedes polyp budding at colony margins, identifying a "transit area" (volumes ~1 mm3, skeleton-to-void ratio 20%-35%) within tubular canals as a pathway for polyp migration to new calices. This feature serves as a morphological budding marker, enabling visualization of polyp trajectories and growth axes. The polyp-canal system undergoes dynamic changes, including concurrent skeleton formation and dissolution. These insights establish a structural framework for biomineralization regulation and colony expansion, contributing to the development of coral growth models, and informing environmental impacts on reef-building in M. capricornis.

Accurate quantification of on-site airborne transmission risk is critical for epidemic prevention and control. Environmental modeling study is hard for on-site monitoring of pathogens while instrument-based detection face barriers to evaluate potential risk directly. This study developed an aerosol sampling-based infection risk model (AS-IRM) that integrates the instruments, collection, and detection into the risk evaluation model. We demonstrated AS-IRM quantitatively evaluate potential transmission risk affected by interventions (exposure time, social distance, wearing mask) based on sampled pathogen. The study also introduced the aerosol-to-hydrosol enrichment rate (ERAH) as a standardized metric for describing the spatiotemporal risk assessment capability of monitoring systems. Specifically, an ERAH exceeding 3.02 × 10⁴ s-1 can achieve five-second temporal resolution for accurate quantification of infection risk in micro-scale spaces (0.002 m³). Comparative study shows that existing theoretical models may significantly misestimate infection risk at various stages of aerosol transmission. Our developed AS-IRM aims to bridging the gap between pathogen monitoring technologies and risk models, which can refer to effective public health decision-making and future epidemic control.

The need for long-term storage of medical images poses a challenge for healthcare organizations, and DNA is anticipated to offer a solution for it. This study proposes an effective DNA storage method (DPCM-DP-EN) for storing medical images, which comprises two key components: (i) In the compress stage, the redundancy between pixels is removed using the differential pulse code modulation (DPCM) method, followed by the use of the ZigZag and the dynamic programming (DP) for further compress; (ii) In the encode stage, a new encrypted (EN)) encode mapping method is proposed to satisfy the biological constraints while ensuring a short time and high density of encode. Tested on three distinct medical image datasets, the results indicate that the DPCM-DP-EN method achieves a compress rate of 40% and above, exceeding other methods by at least 30%. All sequences encoded by DPCM-DP-EN adhere to the GC content and homopolymer constraints, with an encode density of more than 3 bits/nt, significantly surpassing that of other encode methods, and without an impact on the processing time. Additionally, DPCM-DP-EN employs pixel coding, enabling to decode with information lossy at high error rates. In conclusion, the DPCM-DP-EN method provides a viable solution for large-scale storage of medical images (200).

Ocean acidification is becoming more prevalent and may contribute to coral reef degradation, yet our understanding of its role in global reef decline remains limited. Therefore, there is an urgent need to study the impact of reduced pH levels on the growth patterns of major reef-building corals. Here, we studied the skeleton-forming strategies of 4 widely distributed coral species in a simulated acidified habitat with a pH of 7.6 to 7.8. We reconstructed and visualized the skeleton-forming process, quantified elemental calcium loss, and determined gene expression changes. The results suggest that different reef-building corals have diverse growing strategies in lower pH conditions. A unique “cavity-like” forming process starts from the inside of the skeletons of Acropora muricata, which sacrifices skeletal density to protect its polyp–canal system. The forming patterns in Pocillopora damicornis, Montipora capricornis, and Montipora foliosa were characterized by “osteoporosis”, exhibiting disordered skeletal structures, insufficient synthesis of adhesion proteins, and low bone mass, correspondingly. In addition, we found that damage from acidification particularly affects pre-existing skeletal structures in the colony. These results enhance our understanding of skeleton-forming strategies in major coral species under lower pH conditions, providing a foundation for coral reef protection and restoration amidst increasing ocean acidification.

Bacterial infections are highly prevalent globally, and the health issues they induce often lead to numerous severe problems for human well-being, demanding timely and accurate detection strategies. Herein, We developed a universal electrochemical biosensor for pathogen screening, offering high sensitivity, specificity, rapidity, and multiplex detection. The platform integrates interdigitated electrodes for low-voltage pathogen lysis and nucleic acid release with asymmetric recombinase polymerase amplification (aRPA) to produce single-stranded DNA, simplifying extraction and reducing detection time. Screen-printed electrodes were carboxylated using diazonium salts to immobilize Fc-labeled hairpin DNA via amide bonds. Upon applying a positive voltage, amplified DNA hybridizes with the hairpin probes, distancing Fc molecules from the electrode surface and diminishing electrochemical signals, effectively eliminating false positives. Optimized conditions enabled detection sensitivities of 10 CFU/mL for Staphylococcus aureus and 5 CFU/mL for Acinetobacter baumannii. Additionally, Spiked testing in tap water, milk, and lake water demonstrated consistency with plate counting, validating the rapid system's accuracy and applicability. Remarkably, the assay time was reduced from 6 to 8 h to 25 min while maintaining pathogen specificity. This biosensor shows promise for foodborne pathogen surveillance, environmental monitoring, and point-of-care diagnostics, offering a streamlined platform for rapid, accurate pathogen identification.

IntroductionPocillopora damicornis, a key species of stony corals, has been the subject of considerable scientific study. However, the cellular composition of P. damicornis and the roles of these cells in endosymbiosis and biomineralization remain elusive. The development of single-cell technology has provided new opportunities for researching the cellular and molecular mechanisms underlying symbiosis and mineralization. Nevertheless, the stringent environmental requirements, the complexity of the cellular components, and the paucity of high-quality reference genomes of P. damicornis have posed significant challenges for single-cell transcriptome research.MethodsIn this study, we quantified the transcriptomic expression of P. damicornis by aligning its single-cell transcriptome (scRNA-seq) data to multiple species, including Stylophora pistillata, P. damicornis, and Pocillopora verrucosa. We determined the cell types of P. damicornis by comparing its cluster-specific genes with the published cell type-specific genes of S.pistillata and conducted gene function and enrichment analyses.ResultsUnsupervised clustering analysis yielded the identification of ten distinct cell populations, including epidermis cells, gastrodermis cells, algae-hosting cells, calicoblast, cnidocytes, and immune cells. In addition, we identified 53 genes that were highly similar to known sequences in the symbiotic zooxanthellae. These genes were mainly expressed in four different cell populations, corresponding to active symbiotic populations.ConclusionThis study identified cell types closely associated with symbiosis and calcification in P. damicornis, along with their marker genes, which are consistent with the findings in S. pistillata. These results offer insights into the cellular functions and symbiotic mechanisms of P. damicornis.

DNA storage is expected to tackle the dilemma faced by electronic information technology for the effective storage and management of massive amounts of data in the era of big data. Efficient and reliable data retrieval is crucial for DNA storage. However, it is still challenging to actualize DNA storage with fast and accurate readout capabilities, which play a key role in the practicality and reliability of DNA storage. In this study, an integrated system was constructed using homemade microfluidic PCR and DNA magnetic beads for fast and accurate DNA storage and reading with reproducibility. The homemade microfluidic PCR and DNA magnetic beads constructed for the random access of DNA storage have the advantages of short time and low bias named MMBP. The homemade DNA magnetic beads are low cost, stable, and reproducible. The integrated DNA storage and reading system integrated by MMBP can read information not only more accurately and quickly but also at a lower sequencing depth than traditional PCR. Overall, the MMBP-based DNA information storage system (MMBP-DIS) has the advantages of reducing the cost, decreasing the random access time to 10 min, and improving the reading accuracy and sensitivity. In the future, it can be integrated with DNA electrochemical synthesis to develop a fast and accurate portable microfluidic device for DNA synthesis-preservation-reading integration.

Limited by uncertain base errors in DNA storage, additional correction measures may introduce redundancy or even expand errors, resulting in poor reconstructed image. DNA-CTMF is proposed to reconstruct high quality images at high errors and indels. Firstly, Pixel-Base codebook and chaotic system ensure DNA sequences meet biological constraints. Then, codebook adjusts offset base-groups affected by indels to their original position. Finally, median filter removes salt-and-pepper noise caused by base errors. Simulated experiments show reconstructed images by DNA-CTMF exhibit high quality with minimal variation at different error compositions. Even at 5 % error rate and indels accounting for 2/3, DNA-CTMF reconstruct high quality images with PSNR approximately 23 and MS-SSIM exceeding 0.9. Tests on 4000 images demonstrate DNA-CTMF's superiority on multiple images. Wet experiments proves that DNA-CTMF can reconstruct images close to original at low error rate, which is consistent with the results of simulated experiments. Different from researches which adopted error correction codes, DNA-CTMF addresses base errors by image processing technology, providing a new interdisciplinary solution and perspective for storing images into DNA.

Traditional DNA storage technologies rely on passive filtering methods for error correction during synthesis and sequencing, which result in redundancy and inadequate error correction. Addressing this, the Low Quality Sequence Filter (LQSF) was introduced, an innovative method employing deep learning models to predict high-risk sequences. The LQSF approach leverages a classification model trained on error-prone sequences, enabling efficient pre-sequencing filtration of low-quality sequences and reducing time and resources in subsequent stages. Analysis has demonstrated a clear distinction between high and low-quality sequences, confirming the efficacy of the LQSF method. Extensive training and testing were conducted across various neural networks and test sets. The results showed all models achieving an AUC value above 0.91 on ROC curves and over 0.95 on PR curves across different datasets. Notably, models such as Alexnet, VGG16, and VGG19 achieved a perfect AUC of 1.0 on the Original dataset, highlighting their precision in classification. Further validation using Illumina sequencing data substantiated a strong correlation between model scores and sequence error-proneness, emphasizing the model’s applicability. The LQSF method marks a significant advancement in DNA storage technology, introducing active sequence filtering at the encoding stage. This pioneering approach holds substantial promise for future DNA storage research and applications.

Coral reef ecosystems face escalating threats from anthropogenic global climate challenges, leading to frequent bleaching events. A key issue in coral transplantation is the inability of fragments to rapidly grow to sizes that can resist environmental pressures. The observation of accelerated growth during the early stages of coral regeneration provides new insights for addressing this challenge. To investigate the underlying molecular mechanisms, we study the fast-growing stony coral Acropora muricata. Using single-cell RNA sequencing, bulk RNA sequencing, and high-resolution micro-computed tomography, we identify a critical regeneration phase around 2-4 weeks post-injury. Single-cell transcriptome analysis reveals 11 function-specific cell clusters. Pseudotime analysis indicates epidermal cell differentiation into calicoblasts. Bulk RNA-seq results highlight a temporal limitation in coral's rapid regeneration. Through integrated multi-omics analysis, this study emphasizes the importance of a comprehensive understanding of coral regeneration, providing insights beyond fundamental knowledge and offering potential protective strategies to promote coral growth.