Advanced DNA Amplification for Efficient Data Storage.

DNA amplification technologies have significantly advanced biotechnology, particularly in DNA storage. However, adaptation of these technologies to DNA storage poses substantial challenges. Key bottlenecks include achieving high throughput to manage large data sets, ensuring rapid and efficient DNA amplification, and minimizing bias to maintain data fidelity. This perspective begins with an overview of natural and artificial amplification strategies, such as polymerase chain reaction and isothermal amplification, highlighting their respective advantages and limitations. It then explores the prospective applications of these techniques in DNA storage, emphasizing the need to optimize protocols for scalability and robustness in handling diverse digital data. Concurrently, we identify promising avenues, including advancements in enzymatic processes and novel amplification methodologies, poised to mitigate existing constraints and propel the field forward. Ultimately, we provide insights into how to utilize advanced DNA amplification strategies poised to revolutionize the efficiency and feasibility of data storage, ushering in enhanced approaches to data retrieval in the digital age.

DMF-ChIP-seq for Highly Sensitive and Integrated Epigenomic Profiling of Low-Input Cells.

Mapping genome-wide DNA-protein interactions (DPIs) provides insights into the epigenetic landscape of complex biological systems and elucidates the mechanisms of epigenetic regulation in biological progress. However, current technologies in DPI profiling still suffer from high cell demands, low detection sensitivity, and large reagent consumption. To address these problems, we developed DMF-ChIP-seq that builds on digital microfluidic (DMF) technology to profile genome-wide DPIs in a highly efficient, cost-effective, and user-friendly way. The entire workflow including cell pretreatment, antibody recognition, pA-Tn5 tagmentation, fragment enrichment, and PCR amplification is programmatically manipulated on a single chip. Leveraging closed submicroliter reaction volumes and a superhydrophobic interface, DMF-ChIP-seq presented higher sensitivity in peak enrichment than other current methods, with high accuracy (Pearson Correlation Coefficient (PCC) > 0.86) and high repeatability (PCC > 0.92). Furthermore, DMF-ChIP-seq was capable of processing the samples with as few as 8 cells while maintaining a high signal-to-noise ratio. By applying DMF-ChIP-seq, H3K27ac histone modification of early embryonic cells during differentiation was profiled for the investigation of epigenomic landscape dynamics. With the benefits of high efficiency and sensitivity in DPI analysis, the system provides great promise in studying epigenetic regulation during various biological processes.

AMAR-seq: Automated Multimodal Sequencing of DNA Methylation, Chromatin Accessibility, and RNA Expression with Single-Cell Resolution.

Parallel single-cell multimodal sequencing is the most intuitive and precise tool for cellular status research. In this study, we propose AMAR-seq to automate methylation, chromatin accessibility, and RNA expression coanalysis with single-cell precision. We validated the accuracy and robustness of AMAR-seq in comparison with standard single-omics methods. The high gene detection rate and genome coverage of AMAR-seq enabled us to establish a genome-wide gene expression regulatory atlas and triple-omics landscape with single base resolution and implement single-cell copy number variation analysis. Applying AMAR-seq to investigate the process of mouse embryonic stem cell differentiation, we revealed the dynamic coupling of the epigenome and transcriptome, which may contribute to unraveling the molecular mechanisms of early embryonic development. Collectively, we propose AMAR-seq for the in-depth and accurate establishment of single-cell multiomics regulatory patterns in a cost-effective, efficient, and automated manner, paving the way for insightful dissection of complex life processes.

Fingerprint Profiling of Glycans on Extracellular Vesicles via Lectin-Induced Aggregation Strategy for Precise Cancer Diagnostics.

Extracellular vesicles (EVs) harbor abundant glycans that mediate various functions, such as intercellular communication and disease advancement, which play significant roles in disease progression. However, the presence of EV heterogeneity in body fluids and the complex nature of the glycan structures have posed challenges for the detection of EV glycans. In this study, we provide a streamlined method integrated, membrane-specific separation with lectin-induced aggregation strategy (MESSAGE), for multiplexed profiling of EV glycans. By leveraging a rationally designed lectin-induced aggregation strategy, the expression of EV glycans is converted to size-based signals. With the assistance learning machine algorithms, the MESSAGE strategy with high sensitivity, specificity, and simplicity can be used for early cancer diagnosis and classification, as well as monitoring cancer metastasis via 20 µL plasma sample within 2 h. Furthermore, our platform holds promise for advancing the field of EV-based liquid biopsy for clinical applications, opening new possibilities for the profiling of EV glycan signatures in various disease states.

DNA-DISK: Automated end-to-end data storage via enzymatic single-nucleotide DNA synthesis and sequencing on digital microfluidics.

In the age of information explosion, the exponential growth of digital data far exceeds the capacity of current mainstream storage media. DNA is emerging as a promising alternative due to its higher storage density, longer retention time, and lower power consumption. To date, commercially mature DNA synthesis and sequencing technologies allow for writing and reading of information on DNA with customization and convenience at the research level. However, under the disconnected and nonspecialized mode, DNA data storage encounters practical challenges, including susceptibility to errors, long storage latency, resource-intensive requirements, and elevated information security risks. Herein, we introduce a platform named DNA-DISK that seamlessly streamlined DNA synthesis, storage, and sequencing on digital microfluidics coupled with a tabletop device for automated end-to-end information storage. The single-nucleotide enzymatic DNA synthesis with biocapping strategy is utilized, offering an ecofriendly and cost-effective approach for data writing. A DNA encapsulation using thermo-responsive agarose is developed for on-chip solidification, not only eliminating data clutter but also preventing DNA degradation. Pyrosequencing is employed for in situ and accurate data reading. As a proof of concept, DNA-DISK successfully stored and retrieved a musical sheet file (228 bits) with lower write-to-read latency (4.4 min of latency per bit) as well as superior automation compared to other platforms, demonstrating its potential to evolve into a DNA Hard Disk Drive in the future.

Fast Isolation and Sensitive Multicolor Visual Detection of Small Extracellular Vesicles by Multifunctional Polydopamine Nanospheres.

Small extracellular vesicles (sEVs) assume pivotal roles as vital messengers in intercellular communication, boasting a plethora of biological functions and promising clinical applications. However, efficient isolation and sensitive detection of sEVs continue to present formidable challenges. In this study, we report a novel method for fast isolation and highly sensitive multicolor visual detection of sEVs using aptamer-functionalized polydopamine nanospheres (SIMPLE). In the SIMPLE strategy, aptamer-functionalized polydopamine nanospheres (Apt-PDANS) with 170 nm diameters were synthesized and exhibited a remarkable ability to selectively bind to specific proteins on the surface of sEVs. The binding between sEVs and Apt-PDANS engenders an increase in the overall size of the sEVs, allowing fast isolation of sEVs by filtration (a filter membrane with a pore size of 200 nm). The fast isolation strategy not only circumvents the interference posed by unbound proteins and excessive probes as well as the intricacies associated with conventional ultracentrifugation methods but also expedites the separation of sEVs. Concurrently, the incorporation of Fe3+-doped PDANS permits the multicolor visual detection of sEVs, enabling quantitative analysis by the discernment of visual cues. The proposed strategy achieves a detection limit of 3.2 × 104 sEV mL-1 within 1 h, devoid of any reliance on instrumental apparatus. Furthermore, we showcase the potential application of this methodology in epithelial-mesenchymal transition monitoring and cancer diagnosis, while also envisioning its widespread adoption as a straightforward, rapid, sensitive, and versatile platform for disease monitoring and functional exploration.

SERS Platform for Integrated Enrichment, Isolation, and Identification of Multiple Respiratory Viruses in a Single Assay Using 3D Stereoscopic SERS Tags and Flocked Swabs.

Influenza (flu) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibit similar clinical symptoms, complicating the diagnosis and clinical management of these critical respiratory infections. Thus, there is an urgent need for rapid on-site detection technologies that can simultaneously detect SARS-CoV-2 and influenza A viruses. Here, we have developed the first platform that combines in situ sampling with immune swabs and multichannel surface-enhanced Raman spectroscopy (SERS) for simultaneous screening of these two respiratory viruses in a single assay. A seed-mediated growth method was used to assemble a number of silver spheres on the surface of Fe3O4@SiO2 spheres, which not only creates extensive Raman hotspots but also provides numerous sites for Raman signaling molecules, enhancing the sensing sensitivity. Integrating two specific Raman signaling molecules into the nanospheres allows for the parallel detection of both viruses, improving the efficiency of SERS signal read-out. Rapid quantitative screening of both SARS-CoV-2 and H1N1 is achievable within 15 min, with detection limits of 7.76, and 8.13 pg·mL-1 for their respective target proteins. The platform demonstrated excellent performance in testing and analyzing 98 clinical samples (SARS-CoV-2:50; influenza A:48), achieving sensitivities of 88.00, and 95.83% for SARS-CoV-2 and influenza A, respectively. Pearson's correlation analysis revealed a significant correlation with the clinical CT values (P < 0.0001), underscoring the great potential of this platform for the early, rapid, and simultaneous diagnostic discrimination of multiple pathogens.

Spatial Engineering of Heterotypic Antigens on a DNA Framework for the Preparation of Mosaic Nanoparticle Vaccines with Enhanced Immune Activation against SARS-CoV-2 Variants.

Mosaic nanoparticle vaccines with heterotypic antigens exhibit broad-spectrum antiviral capabilities, but the impact of antigen proportions and distribution patterns on vaccine-induced immunity remains largely unexplored. Here, we present a DNA nanotechnology-based strategy for spatially assembling heterotypic antigens to guide the rational design of mosaic nanoparticle vaccines. By utilizing two aptamers with orthogonal selectivity for the original SARS-CoV-2 spike trimer and Omicron receptor-binding domain (RBD), along with a DNA soccer-ball framework, we precisely manipulate the spacing, stoichiometry, and overall distribution of heterotypic antigens to create mosaic nanoparticles with average, bipolar, and unipolar antigen distributions. Systematic in vitro and in vivo immunological investigations demonstrate that 30 heterotypic antigens in equivalent proportions, with an average distribution, leads to higher production of broad-spectrum neutralizing antibodies compared to the bipolar and unipolar distributions. Furthermore, the precise assembly utilizing our developed methodology reveals that a mere increment of five Omicron RBD antigens on a nanoparticle (from 15 to 20) not only diminishes neutralization against Omicron variant but also triggers excessive inflammation. This work provides a unique perspective on the rational design of mosaic vaccines by highlighting the significance of the spatial placement and proportion of heterotypic antigens in their structure-activity mechanisms.

Metabolic Labeling and Digital Microfluidic Single-Cell Sequencing for Single Bacterial Genotypic-Phenotypic Analysis.

Accurate assessment of phenotypic and genotypic characteristics of bacteria can facilitate comprehensive cataloguing of all the resistance factors for better understanding of antibiotic resistance. However, current methods primarily focus on individual phenotypic or genotypic profiles across different colonies. Here, a Digital microfluidic-based automated assay for whole-genome sequencing of single-antibiotic-resistant bacteria is reported, enabling Genotypic and Phenotypic Analysis of antibiotic-resistant strains (Digital-GPA). Digital-GPA can efficiently isolate and sequence antibiotic-resistant bacteria illuminated by fluorescent D-amino acid (FDAA)-labeling, producing high-quality single-cell amplified genomes (SAGs). This enables identifications of both minor and major mutations, pinpointing substrains with distinctive resistance mechanisms. Digital-GPA can directly process clinical samples to detect and sequence resistant pathogens without bacterial culture, subsequently provide genetic profiles of antibiotic susceptibility, promising to expedite the analysis of hard-to-culture or slow-growing bacteria. Overall, Digital-GPA opens a new avenue for antibiotic resistance analysis by providing accurate and comprehensive molecular profiles of antibiotic resistance at single-cell resolution.

DMF-DM-seq: Digital-Microfluidics Enabled Dual-Modality Sequencing of Single-Cell mRNA and microRNA with High Integration, Sensitivity, and Automation.

Multimodal measurement of single cells provides deep insights into the intricate relationships between individual molecular layers and the regulatory mechanisms underlying intercellular variations. Here, we reported DMF-DM-seq, a highly integrated, sensitive, and automated platform for single-cell mRNA and microRNA (miRNA) co-sequencing based on digital microfluidics. This platform first integrates the processes of single-cell isolation, lysis, component separation, and simultaneous sequencing library preparation of mRNA and miRNA within a single DMF device. Compared with the current half-cell measuring strategy, DMF-DM-seq enables complete separation of single-cell mRNA and miRNA via a magnetic field application, resulting in a higher miRNA detection ability. DMF-DM-seq revealed differential expression patterns of single cells of noncancerous breast cells and noninvasive and aggressive breast cancer cells at both mRNA and miRNA levels. The results demonstrated the anticorrelated relationship between miRNA and their mRNA targets. Further, we unravel the tumor growth and metastasis-associated biological processes enriched by miRNA-targeted genes, along with important miRNA-interaction networks involved in significant signaling pathways. We also deconstruct the miRNA regulatory mechanisms underlying different signaling pathways across different breast cell types. In summary, DMF-DM-seq offers a powerful tool for a comprehensive study of the expression heterogeneity of single-cell mRNA and miRNA, which will be widely applied in basic and clinical research.

Identification of new AAV vectors with enhanced blood-brain barrier penetration efficiency via organ-on-a-chip.

To overcome limitations in the generalizability and efficiency of current AAV vectors, in this current study, we constructed an AAV variant library by the insertion of random heptapeptide sequences in the receptor-binding domain of the AAV9 capsid gene. We then applied a recently developed organ-on-a-chip in vitro model of the human blood-brain barrier (BBB) to iteratively enrich for variants that efficiently cross the BBB and transduce astrocyte cells. Through multiple rounds of screening, we obtained two candidate AAV variants, AAV-M6 and AAV-M8, which showed significantly higher BBB penetration efficiency than AAV9 or AAV-PHP.eB. Quantitative PCR (qPCR) assay showed that AAV-M6 could accumulate to a 5 times higher titer, while AAV-M8 reached a 3 times higher titer, than AAV-PHP.eB in the neural chamber of the model. The transduction assay further verified that the AAV-M6 candidate vector was able to infect HA-1800 cells after crossing the BBB, suggesting it could potentially transduce brain parenchymal cells after crossing the hCMEC/D3 layer at higher efficiency than AAV-PHP.eB. Molecular simulations suggested that the human receptor proteins, LY6D and M6PR, could bind the AAV-M6 heptapeptide insertion with high affinity. This study provides two promising candidate AAV vectors and demonstrates the use of this in vitro BBB model for scalable, high-throughput screening of gene therapies. These tools can drive investigations of the mechanisms underlying BBB permeability and the cell-type specificity of virus vectors.

Au-Pt Coating Improved Catalytic Stability of Au@AuPt Nanoparticles for Pressure-Based Point-of-Care Detection of Escherichia coli O157:H7.

Point-of-care testing (POCT) technologies facilitate onsite detection of pathogens in minutes to hours. Among various POCT approaches, pressure-based sensors that utilize gas-generating reactions, particularly those catalyzed by nanozymes (e.g., platinum nanoparticles, PtNPs, or platinum-coated gold nanoparticles, and Au@PtNPs) have been shown to provide rapid and sensitive detection capabilities. The current study introduces Au-Pt alloy-coated gold nanoparticles (Au@AuPtNPs), an innovative nanozyme with enhanced catalytic activity and relatively high stability. For pathogen detection, Au@AuPtNPs are modified with H1 or H2 hairpin DNAs that can be triggered to undergo a hybridization chain reaction (HCR) that leads to their aggregation upon recognition by an initiator strand (Ini) with H1-/H2-complementary aptamers tethered to magnetic beads (MBs). Pathogen binding to the aptamer exposes Ini, which then binds Au@AuPtNPs and initiates a HCR, resulting in Au@AuPtNP aggregation on MBs. These Au@AuPtNP aggregates exhibit strong catalysis of O2 from the H2O2 substrate, which is measured by a pressure meter, enabling detection of Escherichia coli (E. coli) O157:H7 at concentrations as low as 3 CFU/mL with high specificity. Additionally, E. coli O157:H7 could also be detected in simulated water and tea samples. This method eliminates the need for costly, labor- and training-intensive instruments, supporting its further testing and validation for deployment as a rapid-response POCT application in the detection of bacterial contaminants.

Aptamer-RIBOTAC Strategy Enabling Tumor-Specific Targeted Degradation of MicroRNA for Precise Cancer Therapy.

MicroRNA (miRNA) molecules play crucial roles in a variety of diseases, making miRNA targeting a burgeoning field in medicinal chemistry. Ribonuclease targeting chimeras (RIBOTACs) present a compelling approach for RNA degradation. However, small molecule-based RIBOTAC requires an expensive and time-consuming screening process, and is difficult to directly target miRNA due to its short length lacking secondary structure. Antisense oligonucleotide (ASO)-based RIBOTAC is easy to design but with poor cell permeability. While both of them lack the specificity for tumor targeting. In this study, the first Aptamer-RIBOTAC (ARIBOTAC) chimera is designed based on ASO to achieve precise degradation of miRNA in a tumor cell-specific manner for precise cancer therapy. This chimera exhibits a remarkable ability to specifically identify and enter cancer cells, trigger localized activation of endogenous RNase L, and selectively cleave miRNAs that are complementary to ASO. The efficacy and universality of the ARIBOTAC strategy both in vitro and in vivo by degrading oncogenic miR-210-3p and miR-155-5p are validated. These findings underscore the potential of the ARIBOTAC strategy as a promising avenue for cancer therapy by precisely targeting cancer-associated miRNAs.

Next-Generation Sequencing-Based Spatial Transcriptomics: A Perspective from Barcoding Chemistry.

Gene expression profiling of tissue cells with spatial context is in high demand to reveal cell types, locations, and intercellular or molecular interactions for physiological and pathological studies. With rapid advances in barcoding chemistry and sequencing chemistry, spatially resolved transcriptome (SRT) techniques have emerged to quantify spatial gene expression in tissue samples by correlating transcripts with their spatial locations using diverse strategies. These techniques provide both physical tissue structure and molecular characteristics and are poised to revolutionize many fields, such as developmental biology, neuroscience, oncology, and histopathology. In this context, this Perspective focuses on next-generation sequencing-based SRT methods, particularly highlighting spatial barcoding chemistry. It delves into optically manipulated spatial indexing methods and DNA array-barcoded spatial indexing methods by exploring current advances, challenges, and future development directions in this nascent field.

Highly Multiplexing, Throughput and Efficient Single-Cell Protein Analysis with Digital Microfluidics.

Proteins as crucial components of cells are responsible for the majority of cellular processes. Sensitive and efficient protein detection enables a more accurate and comprehensive investigation of cellular phenotypes and life activities. Here, a protein sequencing method with high multiplexing, high throughput, high cell utilization, and integration based on digital microfluidics (DMF-Protein-seq) is proposed, which transforms protein information into DNA sequencing readout via DNA-tagged antibodies and labels single cells with unique cell barcodes. In a 184-electrode DMF-Protein-seq system, ≈1800 cells are simultaneously detected per experimental run. The digital microfluidics device harnessing low-adsorbed hydrophobic surface and contaminants-isolated reaction space supports high cell utilization (>90%) and high mapping reads (>90%) with the input cells ranging from 140 to 2000. This system leverages split&pool strategy on the DMF chip for the first time to overcome DMF platform restriction in cell analysis throughput and replace the traditionally tedious bench-top combinatorial barcoding. With the benefits of high efficiency and sensitivity in protein analysis, the system offers great potential for cell classification and drug monitoring based on protein expression at the single-cell level.

Well-Paired-Seq2: High-Throughput and High-Sensitivity Strategy for Characterizing Low RNA-Content Cell/Nucleus Transcriptomes.

Single-cell RNA sequencing (scRNA-seq) is a transformative technology that unravels the intricate cellular state heterogeneity. However, the Poisson-dependent cell capture and low sensitivity in scRNA-seq methods pose challenges for throughput and samples with a low RNA-content. Herein, to address these challenges, we present Well-Paired-Seq2 (WPS2), harnessing size-exclusion and quasi-static hydrodynamics for efficient cell capture. WPS2 exploits molecular crowding effect, tailing activity enhancement in reverse transcription, and homogeneous enzymatic reaction in the initial bead-based amplification to achieve 3116 genes and 8447 transcripts with an average of ∼20000 reads per cell. WPS2 detected 1420 more genes and 4864 more transcripts than our previous Well-Paired-Seq. It sensitively characterizes transcriptomes of low RNA-content single cells and nuclei, overcoming the Poisson limit for cell and barcoded bead capture. WPS2 also profiles transcriptomes from frozen clinical samples, revealing heterogeneous tumor copy number variations and intercellular crosstalk in clear cell renal cell carcinomas. Additionally, we provide the first single-cell-level characterization of rare metanephric adenoma (MA) and uncover potential specific markers. With the advantages of high sensitivity and high throughput, WPS2 holds promise for diverse basic and clinical research.

Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis.

Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.

In Situ Detection of Nucleic Acids in Extracellular Vesicles via Membrane Fusion.

Extracellular vesicles (EVs) carry diverse biomolecules (e. g., nucleic acids, proteins) for intercellular communication, serving as important markers for diseases. Analyzing nucleic acids derived from EVs enables non-invasive disease diagnosis and prognosis evaluation. Membrane fusion, a fundamental cellular process wherein two lipid membranes merge, facilitates cell communication and cargo transport. Building on this natural phenomenon, recent years have witnessed the emergence of membrane fusion-based strategies for the detection of nucleic acids within EVs. These strategies entail the encapsulation of detection probes within either artificial or natural vesicles, followed by the induction of membrane fusion with EVs to deliver probes. This innovative approach not only enables in situ detection of nucleic acids within EVs but also ensures the maintenance of structural integrity of EVs, thus preventing nucleic acid degradation and minimizing the interference from free nucleic acids. This concept categorizes approaches into universal and targeted membrane fusion strategies, and discusses their application potential, and challenges and future prospects.

Tumor Exosomal ENPP1 Hydrolyzes cGAMP to Inhibit cGAS-STING Signaling.

To evade immune surveillance, tumor cells express ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) on the surface of their membrane, which degrades extracellular cyclic GMP-AMP (cGAMP), thereby inhibiting the cyclic GMP-AMP synthase (cGAS) stimulator of interferon gene (STING) DNA-sensing pathway. To fully understand this tumor stealth mechanism, it is essential to determine whether other forms of ENPP1 with hydrolytic cGAMP activity also are present in the tumor microenvironment to regulate this innate immune pathway. Herein, it is reported that various tumor-derived exosomes carry ENPP1, and can hydrolyze synthetic 2'3'-cGAMP and endogenous 2'3'-cGAMP produced by cells to inhibit cGAS-STING pathway in immune cells. Moreover, tumor exosomal ENPP1 also can hydrolyze 2'3'-cGAMP bound to LL-37 (an effective transporter of 2'3'-cGAMP) to inhibit STING signaling. Furthermore, high expression of ENPP1 in exosomes is observed isolated from human breast and lung cancer tissue, and tumor exosomal ENPP1 inhibited the immune infiltration of CD8+ T cells and CD4+ T cells. The results elucidate the essential function of tumor exosomal ENPP1 in the cGAS-STING pathway, furthering understanding of the crosstalk between the tumor cells and immune system.