Small Methods

The ability to encode and reliably read nanoscale information is increasingly important for multiplexed biomolecular detection and super-resolution imaging. DNA origami provides a uniquely programmable platform for arranging structural and functional elements with nanometer precision, enabling the creation of identifiable nanoscale patterns. In this context, DNA origami-based barcodes that incorporate gold nanoparticles (AuNPs) to encode either origami geometry or the identity of specific biological targets within defined nanoparticle patterns have been paired with transmission electron microscopy imaging for decoding. However, surface-bond AuNPs may detach during handling, purification, or biological incubation, leading to misidentification or decoding errors in barcode analysis. Here we report a rational design for the controlled encapsulation of AuNPs within DNA origami tubes to enhance nanoparticle retention and structural integrity. We engineered curvature-inducing modifications in a flat rectangular DNA origami scaffold to promote inward folding and confinement of AuNPs. These barcodes can be further functionalized on the outer surface with bioactive aptamers and/or fluorescence dyes, enabling targeted interactions with cells and optical readout. Programable dimerization further expands multiplexing capacity. This design provides a robust framework for structurally stable origami barcodes and advances the development of high-resolution, multiplexed labeling and diagnostic platforms. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=60 SRC="FIGDIR/small/725969v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@686c1aorg.highwire.dtl.DTLVardef@1914c4eorg.highwire.dtl.DTLVardef@28ad47org.highwire.dtl.DTLVardef@8847ca_HPS_FORMAT_FIGEXP M_FIG C_FIG

Double-stranded RNA (dsRNA) is a potent immunogenic impurity and its detection is a critical quality attribute in characterizing mRNA therapeutics. Standard analytical methods (e.g., sandwich ELISA) are only able to resolve the bulk presence of dsRNA and cannot characterize the different sub-species that may be present within a mRNA sample.. In this study, we use mass photometry (MP) as a single-molecule analytical platform for the simultaneous detection and characterization of dsRNA impurities in mRNA samples. We demonstrate how ionic strength can interfere with the stability of the mAb/dsRNA complex and measure the binding affinity (1 nM) under a set of parameters for reproducible characterization of the complex. We then leverage the J2 antibody to identify antibody/dsRNA complexes that then resolve dsRNA-positive species within an mRNA sample based on discrete molecular weight profiles. Furthermore, we introduce a novel MP assay that harnesses the repulsive surface chemistry of uncoated glass to exclude the bulk mRNA analyte to enable the use of higher loading concentrations to sensitively profile trace dsRNA impurities as antibody-bound species. This work establishes MP as a valuable next generation mRNA analytical tool for analyzing dsRNA byproducts within mRNA samples.

Extracellular vesicles (EVs) carry microRNAs (miRNAs) that mediate intercellular communication and have strong potential as disease biomarkers, yet the roles of miRNA isoforms (isomiRs) in EVs remain poorly understood. Here, we analyzed 96 human EV and corresponding source samples from nine public datasets. We found that EV samples consistently contained substantially higher proportions of isomiR reads than their corresponding source samples, indicating widespread isomiR enrichment in EVs. Although individual isomiRs showed limited reproducibility across biological replicates and limited sharing between EVs and their corresponding source samples, the parent miRNAs that generated these isomiRs remained highly reproducible across replicates and strongly shared between EV-source pairs. Despite extensive isomiR diversification, EV-source pairs retained highly correlated miRNA expression profiles. Using integrated miRNA- and isomiR-related features, we further developed a random forest model that successfully associated EV samples with their corresponding source samples, with improved performance when isomiR information was included. Together, our results demonstrate that EVs are enriched for biologically meaningful isomiRs while preserving source-associated miRNA landscapes, highlighting the importance of incorporating isomiRs into future EV studies.

The optimization of mRNA-lipid nanoparticles (mRNA-LNPs) for therapeutic applications is limited in part by the inadequate characterization of mRNA payload heterogeneity. One current challenge is accurately measuring the number of mRNA copies within individual LNPs, where the standard method of intensity-based mRNA number determination is sensitive to fluorescent dye-dye interactions and heterogeneity of mRNA labeling. Here we present a single-particle microscopy method that combines direct counting of the mRNA copies per LNP with LNP size measurements. While confined in microwells, individual mRNA-LNPs are lysed to release their cargo and stained with a dye such that the number of mRNA molecules in each well can be directly counted using fluorescence microscopy. Since the method stains the mRNA cargo in situ, it enables characterization of LNPs formulated with therapeutic grade (e.g., unlabeled) mRNA. We applied this approach to two Onpattro(R)-based LNP formulations prepared using different formulation buffers, where the two formulations had different average mRNA copy number, particle size, and fraction of LNPs lacking mRNA. The ability to directly count the number of mRNA molecules in LNPs establishes a complimentary method to intensity-based mRNA number determination and supports the characterization and screening of clinically relevant LNP formulations.

Apohas Liquid State Intelligence Platform (LSIP) records ellipsometric waveforms from injections depositing sub-microgram quantities of antibody drop-by-drop onto a liquid reservoir. We previously showed that a behavioural feature extracted from the waveforms, VIBE1, identified antibodies carrying multiple biophysical liabilities in an industrial dataset of 71 monoclonal antibodies, and enriched for clinical failure across a larger dataset of 235 therapeutic antibodies [1]. Here, we use an auxiliary coalescence-sensor channel to decode VIBE1 by separating the coalescence event from its propagation through the substrate. The pertitration drop-to-drop standard deviation of pinch-off time,{sigma}{tau} , explains most of VIBE1s variance across the dataset (R2 = 0.92, n = 1182). High-speed imaging at 10,000 frames per second reveals that all imaged drops initially thin at the same Newtonian capillary-inertial rate while the neck remains wide. In drops from certain antibodies, the thinning bridge then decelerates as internal strain builds in the narrowing neck. This elasto-capillary stiffening response has a timescale{lambda} that decreases as pinch-off time{tau} i increases across the imaged set.{sigma}{tau} is therefore a readout of the antibodys propensity to undergo a transient gel-like stiffening response during coalescence, and that variability is what VIBE1 captures. The signal is concentration dependent, and absent in bovine serum albumin (BSA) tested at up to an order of magnitude higher molarity than the antibodies, despite BSA being a strongly surface-active globular protein. The instrument is configured so that complex behaviours of this kind appear in its recorded waveforms; the gel-like coalescence response we identify here is one such phenomenon.

Paper-based diagnostics such as lateral flow assays (LFAs) and microfluidic paper-based analytical devices ({micro}PADs) have attracted considerable attention because of their low cost, portability, and ease of use. Currently, to enable fabrication of {micro}PADs and improve LFA performance, hydrophobic blocks are patterned on paper substrates. However, fabrication of high-resolution hydrophobic barriers remains a major challenge. In this work, we developed a novel silicone extrudable ink for the fabrication of hydrophobic features on paper substrates. The ink was formulated using a vinyl-terminated polydimethylsiloxane (vPDMS) and polymethylhydrosiloxane (PMHS) system crosslinked through platinum-catalyzed hydrosilylation, and its rheological properties were tailored by incorporating silica fillers, obtaining a shear-thinning gel suitable for extrusion. The resulting formulation provided tunable properties, controlled deposition, and stable feature formation, enabling simple, low-cost, rapid, and robust fabrication of high-resolution hydrophobic barriers. Using this approach, we demonstrated improved fluid confinement and pattern fidelity on paper substrates, fabricated high-resolution paper microfluidic devices down to 150 {micro}m channel width, and enhanced the sensitivity of an LFA for a malaria diagnostic test. These results highlight the potential of this silicone ink platform as a practical and scalable strategy for advancing high-performance paper-based diagnostic technologies.

Expanding genetic engineering beyond model microorganisms is critical to unlocking novel applications in biotechnology, yet the low efficiency of DNA delivery methods like conjugation, remains a major bottleneck in non-model and environmental microbes. Here, we present an automated, high-throughput droplet microfluidic platform that enhances conjugation by encapsulating donor and recipient microbes in picoliter-scale water-in-oil microdroplets, stabilizing cell-cell contact and DNA transfer. Optimization of incubation time, donor to recipient ratio, and plasmid type yielded over a 100-fold increase in conjugation efficiency compared to conventional methods and enabled delivery of complex DNA libraries in low reaction volumes, demonstrating scalability for pooled plasmid library delivery. We further utilized a synthetic biology circuit for donor removal within microdroplets without antibiotic selection, eliminating the need for host-specific selection markers or engineered auxotrophs. When applied to a soil microbial community, this platform improved community-level conjugation, preserving microbial diversity and enabling the identification of genetically accessible chassis. Collectively, this platform establishes a scalable, generalizable solution for high throughput DNA delivery in previously inaccessible microbial hosts. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=54 SRC="FIGDIR/small/721591v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@c7a8d4org.highwire.dtl.DTLVardef@1d1fbaorg.highwire.dtl.DTLVardef@e1faforg.highwire.dtl.DTLVardef@14234dc_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background and ObjectivesCardiovascular cells differentiated from human induced pluripotent stem cells (iPSCs), including cardiomyocytes, are valuable for evaluating human cardiac pharmacology and toxicity. Early assessment of cardiotoxicity, especially for novel drugs like anticancer agents, is essential for improving drug development efficiency and reducing costs. This study aimed to develop a highly sensitive bioassay system capable of evaluating the physiological function of human cardiac tissue in vitro. MethodsHuman iPSCs were differentiated into cardiovascular cell types (cardiomyocytes, vascular endothelial cells, and vascular mural cells) and assembled into a cardiac tissue model on aligned fiber device. This tissue was cultured dynamically to induce the formation of vascular network-like structure. By combining the fiber device with our previously developed heart-on-a-chip microdevice (HMD), we created a new model of HMD (Aligned Fiber-based HMD; AF-HMD) with improved throughput and stability. Pulsatile force changes induced by drug exposure were quantified by tracking the displacement of fluorescent microbeads within the microchannels. ResultsAF-HMD demonstrated functional responses to known cardiac agonists and toxicants, such as doxorubicin. The device also replicated clinically relevant cardiotoxic events, including the synergistic effects of trastuzumab and doxorubicin, showing marked reductions in contractile force and beat rate, mirroring clinical observations. ConclusionsThe AF-HMD system provides a sensitive and reproducible platform for evaluating cardiotoxicity in drug development. It offers a promising tool for preclinical screening, with potential applications in personalized medicine and predicting cardiotoxic risk in cancer therapy.

The cardiac autonomic nervous system is a key driver of various cardiac disorders and arrhythmias. However, investigating neuronal regulation of the human heart has proven difficult due to immitted and reliable experimental models. Here, we present a novel microphysiological system utilizing a compartmentalized microfluidic device (MFD) to integrate co-cultured human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (hiPSC-CMs) and sympathetic neurons (hiPSC-SNs). MFD is composed of two wide-open chambers separated by microfluidic microchannels. hiPSC-SNs were characterized by confocal imaging and RT-qPCR for the expression of peripherin, tyrosine hydroxylase, and {beta}-tubulin III, as well as high levels of dopamine {beta}-hydroxylase and nicotinic acetylcholine receptors. Furthermore, patch-clamp techniques confirmed their functional maturity, showing spontaneous action potentials and positive responses to nicotine (1{micro}M). Co-culturing hiPSC-CMs and hiPSC-SNs within the MFD facilitated axonal projection into the cardiomyocyte chamber, establishing a physical connection between the two cell types. After 10 days of co-culture, functional integration was confirmed by a significant increase in the action potential frequency and beating rate of hiPSC-CMs, as recorded by patch-clamp and video motion tracking, respectively. Notably, nicotine application in the neuronal chamber accelerated these rates in hiPSC-CMs chamber, whereas the administration of the {beta}-blocker, propranolol (5{micro}M), effectively decreased the beating rates. Collectively, these data demonstrate the feasibility of differentiating hiPSCs into functional sympathetic neurons and establishing a robust neuro-cardiac interface. This microphysiological system represents a powerful platform for investigating disorders characterized by impaired neuro-cardiac interactions, offering a valuable tool for both disease modeling and pharmacological screening.

Liposomes are self-assembled lipid vesicles capable of encapsulating both hydrophilic and hydrophobic therapeutics, making them versatile platforms in drug delivery and biomedical technology. In this study, the limitations of the classical thin-film hydration method were critically evaluated, and a sustainable, systematically optimized strategy was established for generating defined liposomal lamellar phases. Hydration conditions were optimized, and 4 mL of buffer per 10 mg of lipid was determined to be optimal for effective rehydration and improved statistical reliability of vesicle measurements. A refined probe-sonication protocol (20% amplitude, 5 s ON/55 s OFF pulse) enabled controlled transformation of multivesicular vesicles into stable multilamellar and unilamellar vesicles at net ON-times of 90 s and 185 s, respectively, without overheating or contamination. In addition, a Python-based machine-learning tool was developed for vesicle size characterization. Collectively, these optimizations provided a reproducible and sustainable framework for preparing liposomes across different lamellar phases.

Transport in complex biological tissues is governed by local rheological heterogeneity at the nanoscale, yet probing such environments deep inside living systems remains challenging. Here, we introduce an orientation-sensitive single-particle tracking (SPoT) approach that simultaneously resolves translational and rotational dynamics of individual carbon nanotubes deep within biological tissue. By exploiting the intrinsic dipole-like emission and shortwave infrared luminescence of carbon nanotubes enhanced through the incorporation of quantum color-centers our method enables long-duration tracking with high signal-to-noise ratio in optically dense environments. Crucially, the length of these nanotubes can be precisely shortened down to a few tens of nanometers to adapt to diffusion environmental dimensions, further optimizing the tracking applicability. SPoT of single carbon nanotubes provides access to relative changes in local viscosity, steric constraints, and environmental anisotropy. When applied to the brain extracellular space, SPoT demonstrates that local variations in the translational and rotational diffusion of tracers are heterogeneous and not systematically correlated. This allows to disentangle the local effects of viscosity and spatial tortuosity within the brain extracellular space, which are distinct features that would otherwise remain undetected through translational diffusion analysis alone. By enabling combined translational and rotational tracking of nano-emitters over unprecedented depths and timescales, this work establishes a new framework for probing nanoscale transport and rheological heterogeneity in intact biological tissues and more generally in complex diffusive environments.

Tissue phantoms that mimic microvasculature and perfusion are essential for modelling vascular function, guiding interventions, and calibrating imaging systems, which require faithful replication of vascular geometry and flow. Conventional fabrication strategies, including wire-based molding, lithographic micromachining, and additive manufacturing, offer useful capabilities but remain constrained by predefined designs, rectangular channel cross-sections, limited scalability, and high production costs. Reliance on predefined digital vascular models restricts design flexibility and limits the ability to capture the natural variability and complexity of real vascular systems. Here, we present a lithography-free, fractal-generating approach based on a modified Lifted Hele-Shaw Cell (LHSC) technique, in which vascular networks emerge spontaneously via interfacial fluid instabilities. Unlike pre-designed methods, these structures are governed by fluid properties and flow conditions, enabling adaptive, physiologically relevant geometries with smooth Gaussian cross-sections and natural diameter tapering. We demonstrate four phantom designs: a planar vascular tree, an anatomically guided cerebral network, a retinal vascular model, and a conformable curved substrate phantom. Validation using Laser Speckle Contrast Imaging confirms structural fidelity and physiologically relevant flow consistent with Murrays law. This platform uniquely integrates realistic vascular architecture with emergent, fractal driven formation, highlighting its potential as a reproducible and biologically relevant alternative to conventional vascular phantom fabrication. Furthermore, the availability of such realistic in vitro vascular models can reduce reliance on animal experiments and contribute towards more ethical and sustainable preclinical research.

Nanopore sequencing holds great potential for the direct detection of non-canonical DNA bases from electrical signals, yet current approaches remain limited to a few classical epigenetic marks. Here we present OpenBase, an open and universal framework that standardizes training-data generation and deep learning based-modeling for single-molecule identification of diverse non-canonical DNA bases. OpenBase transforms nanopore sequencing into a broadly accessible platform for exploring the chemical diversity of DNA.

Recent advances in plasmonic biosensing and imaging have enabled label-free analysis of single biological nanoparticles. We previously developed PlAsmonic NanOapeRture lAbel-free iMAging (PANORAMA) for isolation and purification-free, digital counting and precise localization of small extracellular vesicles (sEVs), with complementary fluorescence interrogation of surface and intravesicular biomarkers for quantitative molecular profiling. The fact that no isolation and purification or isolation is needed represents a crucial advantage because various specificity, efficiency, and time-consumption issues hinder quantitatively reproducible extraction of sEVs from biological fluids. PANORAMA achieves ultrahigh refractive-index sensitivity through arrayed gold nanodisks on invisible substrates (AGNIS) fabricated by nanosphere lithography (NSL). However, despite its simplicity and low cost, NSL is frequently constrained by poor large-area uniformity, which hinders scalable fabrication. Here, we introduce nanosphere settling lithography (NSSL) as an alternative to the gold-standard Langmuir-Blodgett trough (LBT) process, enabling highly uniform, large-area monolayers with reduced process stringency. AGNIS fabricated via NSSL exhibits high refractive-index sensitivity with low spatial variability across 60 mm x 24 mm substrates, sufficient for 60-well in standard 384-well plate format. The platform demonstrates exquisite sensitivity through PANORAMA digital counting and sizing of 25, 50, and 100 nm polystyrene beads, as well as single-vesicle characterization of sEVs derived from H460 lung cancer cells. For the first time, combined PANORAMA and fluorescence imaging enables quantitative analysis of microRNA-21 (miR-21) expression in sEVs to identify "cancer-suspicious" sub-population from liver cancer patient plasma in an unbiased fashion allowing both highly sensitive detection of individual sEVs and simultaneous molecular profiling. Collectively, NSSL enables uniform, high-performance plasmonic biosensing over large areas, providing a scalable and economical pathway for high-throughput, digital single-sEV analysis and translational liquid biopsy applications.

Spatiotemporal regulation of mRNA translation is central to gene expression. Over the past decade, translation has become directly observable in live cells at single-mRNA resolution by tagging nascent chains with tandem arrays of short epitope tags recognized by genetically encodable fluorescent intracellular antibodies (intrabodies). While this technology has revolutionized our understanding of translation regulation, the current toolbox of tagging systems remains limited. Here, we developed a novel and tight-binding intrabody against a short (11-amino acid) HIV protease epitope (named UTag). To ensure robust intracellular folding of the anti-UTag intrabody, we further engineered a cysteine-free variant that folds and functions independently of disulfide-bond formation, as validated by X-ray crystallography. The cysteine-free anti-UTag intrabody retains high binding affinity comparable to the parental intrabody while exhibiting significantly improved thermostability ([~]80 {degrees}C). Importantly, the cysteine-free UTag system enables real-time tracking of single-mRNA translation in live cells with performance on par with the parental UTag system as well as the established SunTag and ALFA-tag. Collectively, these results demonstrate that the newly developed UTag system expands the toolbox for live-cell translation tracking and provides complementary tools for multiplexed applications.

Dynamic FGF/ERK signaling plays key roles in development, regeneration, and disease. We recently developed a zebrafish-optimized optogenetic tool, bOpto-FGF, that enables reversible activation of FGF/ERK signaling in response to blue light ([~]455 nm) by fusing a zebrafish receptor tyrosine kinase domain to the blue light-dimerizing LOV domain. Previously, this tool was introduced into zebrafish embryos by mRNA injection. Here, we develop a novel transgenic zebrafish ubiquitously expressing bOpto-FGF, Tg(ubi:bOpto-FGF), to streamline experimental workflows. We demonstrate robust blue light-mediated activation of FGF/ERK signaling in gastrulation-stage Tg(ubi:bOpto-FGF) homozygous and heterozygous embryos. Light-mediated signaling activation is more spatially uniform in transgenics compared to embryos injected with bOpto-FGF mRNA. Tg(ubi:bOpto-FGF) heterozygotes are light-responsive from late blastula stages through at least 24 hours post-fertilization. Finally, ectopic signaling in response to continuous light exposure starting at late blastula stage is activated within 3 minutes and maintained for at least 75 minutes. This transgenic line provides a powerful and convenient new strategy for experimental manipulation of FGF/ERK signaling dynamics in the vertebrate zebrafish model.

The protein corona (PC) that forms on the surface of nanomaterials upon contact with biological fluids provides a molecular snapshot of the hosts physiological and pathological state. Here, we investigate two-dimensional (2D) titanium carbide (Ti3C2Tx) MXene nanosheets as nanobiointerfaces for capturing Alzheimers disease (AD)-associated plasma protein signatures. Ti3C2Tx MXene flakes were incubated with plasma from clinically diagnosed AD patients and age-matched healthy controls (HC), leading to the formation of Ti3C2Tx MXene-PC complexes. Physicochemical characterization using dynamic light scattering, zeta potential analysis, and transmission electron microscopy revealed disease-dependent changes in hydrodynamic size, surface charge, and PC profile. Proteomic analysis of the isolated PC layers quantified 1,611 proteins without prior fractionation, demonstrating effective enrichment of low-abundance plasma components. Principal component analysis (PCA) revealed consistent separation between AD- and HC-derived Ti3C2Tx MXene-PC proteomes despite inter-individual heterogeneity. Differential abundance analysis identified selective enrichment of heterogeneous nuclear ribonucleoproteins (hnRNPs), annexins, and inflammatory mediators in AD-derived PC, implicating dysregulated RNA metabolism, membrane stress responses, and immune activation, hallmark processes in AD pathology. Our findings demonstrate that Ti3C2Tx MXene-PC interfaces act as selective molecular filters that reshape the detectable plasma proteome, enabling disease-associated molecular phenotyping and establishing a versatile nanointerface-driven framework for uncovering AD-related plasma signatures, providing a foundation for future translational diagnostic development.

Conformationally responsive DNA nanoswitches have previously been developed and validated for a variety of biosensing applications including detection of DNA, microRNA, and viral RNA/DNA. Here we develop new methodology for enhancing the sensitivity of DNA-based sensing by recycling a fixed number of targets for repeated reuse. We achieved target-dependent enzymatic ligation of looped nanoswitches and showed that subsequent removal of target does not affect the ligated loop. Through cyclic annealing, ligation, and target removal, we can linearly control signal amplification up to hundreds of cycles. This method adds an important new capability for low abundance targets without the need for target amplification.

Refined single-molecule localization microscopy methods demonstrated superior localization precisions on isolated sample but remain limited by labeling density and imaging speed in cells. Here we combine expansion microscopy (ExM) with two-dye-imager (TDI)-DNA-PAINT to resolve fine molecular details of protein assemblies in [~]8-fold expanded cells with nanometer resolution. Using lattice light-sheet (LLS) microscopy, Ex-TDI-DNA-PAINT provides a robust platform for three-dimensional (3D) volumetric nanoscopy of the molecular organization of cells.

Lung adenocarcinoma (LUAD), a subtype of non-small cell lung cancer (NSCLC), is the most common primary lung cancer worldwide. Despite advancements in early detection and treatment, up to 39% of patients develop recurrent tumors following complete resection. Currently, no widely available models exist for reliably predicting early recurrence of LUAD, which is a significant prognostic factor of post-recurrence survival. Models leveraging deep learning (DL) techniques have demonstrated notable utility in cancer recurrence prediction, particularly when used in combination with both clinical and genomic data. We developed a DL-based model, Predicting Lung Adenocarcinoma recurrence via Selective Multimodal Attention (PLASMA), to predict early recurrence using clinical, mRNA expression, and mutation data from patients with primary stage I-III LUAD. Trained on The Cancer Genome Atlas (TCGA) dataset, PLASMA outperformed traditional machine learning models in predicting early recurrence in both the TCGA test set and an external validation set (TRACERx Lung), achieving area under the receiver operating characteristic curve (AUROC) scores of 85.0% and 76.5%, respectively. Our results support the potential of multimodal DL for early LUAD recurrence prediction and risk stratification.