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.

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.

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.

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.

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.

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.

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.

Domain generalization enables general cancer cell annotation in single-cell and spatial transcriptomics.

Single-cell and spatial transcriptome sequencing, two recently optimized transcriptome sequencing methods, are increasingly used to study cancer and related diseases. Cell annotation, particularly for malignant cell annotation, is essential and crucial for in-depth analyses in these studies. However, current algorithms lack accuracy and generalization, making it difficult to consistently and rapidly infer malignant cells from pan-cancer data. To address this issue, we present Cancer-Finder, a domain generalization-based deep-learning algorithm that can rapidly identify malignant cells in single-cell data with an average accuracy of 95.16%. More importantly, by replacing the single-cell training data with spatial transcriptomic datasets, Cancer-Finder can accurately identify malignant spots on spatial slides. Applying Cancer-Finder to 5 clear cell renal cell carcinoma spatial transcriptomic samples, Cancer-Finder demonstrates a good ability to identify malignant spots and identifies a gene signature consisting of 10 genes that are significantly co-localized and enriched at the tumor-normal interface and have a strong correlation with the prognosis of clear cell renal cell carcinoma patients. In conclusion, Cancer-Finder is an efficient and extensible tool for malignant cell annotation.

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.

Characterization of the Nucleus Pulposus Progenitor Cells via Spatial Transcriptomics.

Loss of refreshment in nucleus pulposus (NP) cellularity leads to intervertebral disc (IVD) degeneration. Nevertheless, the cellular sequence of NP cell differentiation remains unclear, although an increasing body of literature has identified markers of NP progenitor cells (NPPCs). Notably, due to their fragility, the physical enrichment of NP-derived cells has limited conventional transcriptomic approaches in multiple studies. To overcome this limitation, a spatially resolved transcriptional atlas of the mouse IVD is generated via the 10x Genomics Visium platform dividing NP spots into two clusters. Based on this, most reported NPPC-markers, including Cathepsin K (Ctsk), are rare and predominantly located within the NP-outer subset. Cell lineage tracing further evidence that a small number of Ctsk-expressing cells generate the entire adult NP tissue. In contrast, Tie2, which has long suggested labeling NPPCs, is actually neither expressed in NP subsets nor labels NPPCs and their descendants in mouse models; consistent with this, an in situ sequencing (ISS) analysis validated the absence of Tie2 in NP tissue. Similarly, no Tie2-cre-mediated labeling of NPPCs is observed in an IVD degenerative mouse model. Altogether, in this study, the first spatial transcriptomic map of the IVD is established, thereby providing a public resource for bone biology.

Decoder-seq enhances mRNA capture efficiency in spatial RNA sequencing.

Spatial transcriptomics technologies with high resolution often lack high sensitivity in mRNA detection. Here we report a dendrimeric DNA coordinate barcoding design for spatial RNA sequencing (Decoder-seq), which offers both high sensitivity and high resolution. Decoder-seq combines dendrimeric nanosubstrates with microfluidic coordinate barcoding to generate spatial arrays with a DNA density approximately ten times higher than previously reported methods while maintaining flexibility in resolution. We show that the high RNA capture efficiency of Decoder-seq improved the detection of lowly expressed olfactory receptor (Olfr) genes in mouse olfactory bulbs and contributed to the discovery of a unique layer enrichment pattern for two Olfr genes. The near-cellular resolution provided by Decoder-seq has enabled the construction of a spatial single-cell atlas of the mouse hippocampus, revealing dendrite-enriched mRNAs in neurons. When applying Decoder-seq to human renal cell carcinomas, we dissected the heterogeneous tumor microenvironment across different cancer subtypes and identified spatial gradient-expressed genes related to epithelial-mesenchymal transition with the potential to predict tumor prognosis and progression.

Decoding Biomechanical Cues Based on DNA Sensors.

Biological systems perceive and respond to mechanical forces, generating mechanical cues to regulate life processes. Analyzing biomechanical forces has profound significance for understanding biological functions. Therefore, a series of molecular mechanical techniques have been developed, mainly including single-molecule force spectroscopy, traction force microscopy, and molecular tension sensor systems, which provide indispensable tools for advancing the field of mechanobiology. DNA molecules with a programmable structure and well-defined mechanical characteristics have attached much attention to molecular tension sensors as sensing elements, and are designed for the study of biomechanical forces to present biomechanical information with high sensitivity and resolution. In this work, a comprehensive overview of molecular mechanical technology is presented, with a particular focus on molecular tension sensor systems, specifically those based on DNA. Finally, the future development and challenges of DNA-based molecular tension sensor systems are looked upon.

Beyond single cells: microfluidics empowering multiomics analysis.

Single-cell multiomics technologies empower simultaneous measurement of multiple types of molecules within individual cells, providing a more profound comprehension compared with the analysis of discrete molecular layers from different cells. Microfluidic technology, on the other hand, has emerged as a pivotal facilitator for high-throughput single-cell analysis, offering precise control and manipulation of individual cells. The primary focus of this review encompasses an appraisal of cutting-edge microfluidic platforms employed in the realm of single-cell multiomics analysis. Furthermore, it discusses technological advancements in various single-cell omics such as genomics, transcriptomics, epigenomics, and proteomics, with their perspective applications. Finally, it provides future prospects of these integrated single-cell multiomics methodologies, shedding light on the possibilities for future biological research.

Highly Multiplexed, Efficient, and Automated Single-Cell MicroRNA Sequencing with Digital Microfluidics.

Single-cell microRNA (miRNA) sequencing has allowed for comprehensively studying the abundance and complex networks of miRNAs, which provides insights beyond single-cell heterogeneity into the dynamic regulation of cellular events. Current benchtop-based technologies for single-cell miRNA sequencing are low throughput, limited reaction efficiency, tedious manual operations, and high reagent costs. Here, a highly multiplexed, efficient, integrated, and automated sample preparation platform is introduced for single-cell miRNA sequencing based on digital microfluidics (DMF), named Hiper-seq. The platform integrates major steps and automates the iterative operations of miRNA sequencing library construction by digital control of addressable droplets on the DMF chip. Based on the design of hydrophilic micro-structures and the capability of handling droplets of DMF, multiple single cells can be selectively isolated and subject to sample processing in a highly parallel way, thus increasing the throughput and efficiency for single-cell miRNA measurement. The nanoliter reaction volume of this platform enables a much higher miRNA detection ability and lower reagent cost compared to benchtop methods. It is further applied Hiper-seq to explore miRNAs involved in the ossification of mouse skeletal stem cells after bone fracture and discovered unreported miRNAs that regulate bone repairing.

DIRECT: Digital Microfluidics for Isolation-Free Shared Library Construction of Single-Cell DNA Methylome and Transcriptome.

Simultaneous profiling of DNA methylation and gene expression within single cells is a powerful technology to dissect complex gene regulatory network of cells. However, existing methods are based on picking a single-cell in a tube and split single-cell lysate into two parts for transcriptome and methylome library construction, respectively, which is costly and cumbersome. Here, DIRECT is proposed, a digital microfluidics-based method for high-efficiency single-cell isolation and simultaneous analysis of the methylome and transcriptome in a single library construction. The accuracy of DIRECT is demonstrated in comparison with bulk and single-omics data, and the high CpG site coverage of DIRECT allows for precise analysis of copy number variation information, enabling expansion of single cell analysis from two- to three-omics. By applying DIRECT to monitor the dynamics of mouse embryonic stem cell differentiation, the relationship between DNA methylation and changes in gene expression during differentiation is revealed. DIRECT enables accurate, robust, and reproducible single-cell DNA methylation and gene expression co-analysis in a more cost-effective, simpler library preparation and automated manner, broadening the application scenarios of single-cell multi-omics analysis and revealing a more comprehensive and fine-grained map of cellular regulatory landscapes.

Aptamer-Assisted Blockade of the Immune Suppressor Sialic Acid-Binding Immunoglobulin-Like Lectin-15 for Cancer Immunotherapy.

The percentage of low response and adaptive resistance to current antibody-based immune checkpoint blockade (ICB) therapy requires the development of novel immunotherapy strategies. Here, we developed an aptamer-assisted immune checkpoint blockade (Ap-ICB) against sialic acid-binding immunoglobulin-like lectin-15 (Siglec-15), a novel immune suppressor broadly upregulated on cancer cells and tumor infiltrating myeloid cells, which is mutually exclusive of programmed cell death ligand 1 (PD-L1). Using protein aptamer selection, we identified WXY3 aptamer with high affinity against Siglec-15 protein/Siglec-15 positive cells. We demonstrated that WXY3 aptamer rescued antigen-specific T cell responses in vitro and in vivo. Importantly, the WXY3 Ap-ICB against Siglec-15 amplified anti-tumor immunity in the tumor microenvironment and inhibited tumor growth/metastasis in syngeneic mouse model, which may result from enhanced macrophage and T cell functionality. In addition, by using aptamer-based spherical nucleic acids, we developed a synergetic ICB strategy of multivalent binding and steric hindrance, which further improves the in vivo anti-tumor effect. Taken together, our results support Ap-ICB targeted Siglec-15 as a potential strategy for normalization cancer immunotherapy.