Antibody-dye conjugates are an essential tool in biomedical research and are widely used in flow cytometry, immunofluorescence imaging, and ELISAs. The degree of labeling (DOL), often referred to as the F/P (fluorophore-to-protein) ratio, which is the number of dyes per antibody, is a fundamental characteristic of antibody-dye conjugates that impacts conjugate performance (emission intensity, affinity, solubility/aggregation) and the accuracy and reproducibility of results. Knowing the DOL of antibody-dye conjugates is essential for accurately quantifying target proteins and/or antigens in quantitative flow cytometry and quantitative immunofluorescence. In CAR-T cell therapy, the expression level of the chimeric antigen receptor (CAR) on T cells must be finely tuned to optimize treatment efficacy but cannot be calculated without the DOL of the anti-CAR antibody-dye conjugate. However, DOL cannot be easily measured (e.g., via absorption spectroscopy) for many widely used conjugates that contain protein-based or semiconducting polymer/nanoparticle dyes due to overlap in absorption cross-section between antibody and dye. Bulk analysis also cannot reveal the distribution of DOL values, which can impact conjugate performance and biomarker quantitation. Furthermore, quenching between dyes can reduce the conjugate emission. Herein, we demonstrate the use of a single-molecule-sensitive digital flow cytometer (dFC) with 100% single-fluorophore detection efficiency to measure the fluorescence emission distributions of conjugates and free dyes and perform deconvolution to obtain effective DOL values (the apparent number of dyes per conjugate based on fluorescence emission, useful for converting fluorescence intensity to antigens/cell) for antibodies conjugated with small-molecule, protein-based, and semiconducting polymer/nanoparticle dyes.

Digital assays such as digital PCR for nucleic acids and digital ELISA for proteins provide absolute quantitation and greater accuracy, sensitivity, and reproducibility than their analogue counterparts (real-time PCR and standard ELISA), but current digital assays involve amplification (e.g., DNA amplification in digital PCR and signal amplification in digital ELISA), which makes high multiplexing difficult, often requires complex and expensive sample compartmentalization, and adds reaction steps. We have developed a single-molecule sensitive flow cytometer, which we termed a digital flow cytometer (dFC). dFC optimizes the sensitivity and efficiency of single-molecule detection by using smaller, planar microfluidic channels, a smaller probe volume, and a shorter working distance/higher numerical aperture objective than used in current commercial high-sensitivity flow cytometers, allowing digital assays via direct single-molecule counting. This paper describes our characterization of the analytical performance of this system when detecting antibody-dye conjugates and demonstrates absolute concentration measurements of commercial antibody-dye conjugates. The dFC exhibited a single-molecule detection efficiency with which over 98% for antibodies conjugated with 18 different small-molecule, phycobiliprotein, and semiconducting polymer dyes were separated from noise, a low false-positive rate, a stable baseline signal, and accurate concentration measurements with a dynamic range spanning 4 orders of magnitude. This system can be used for authenticating antibody-dye conjugates used in flow cytometry and tissue imaging studies and in the development of multiplexed, amplification-free digital assays for nucleic acids and proteins.

Extracellular vesicles (EVs) play a crucial role in intercellular communication, signaling pathways, and disease pathogenesis by transporting biomolecules such as DNA, RNA, proteins, and lipids derived from their cells of origin, and they have demonstrated substantial potential in clinical applications. Their clinical significance underscores the need for sensitive methods to fully harness their diagnostic potential. In this comprehensive review, we explore EV heterogeneity related to biogenesis, structure, content, origin, sample type, and function roles; the use of EVs as disease biomarkers; and the evolving landscape of EV measurement for clinical diagnostics, highlighting the progression from bulk measurement to single vesicle analysis. This review covers emerging technologies such as single-particle tracking microscopy, single-vesicle RNA sequencing, and various nanopore-, nanoplasmonic-, immuno-digital droplet-, microfluidic-, and nanomaterial-based techniques. Unlike traditional bulk analysis methods, these methods contribute uniquely to EV characterization. Techniques like droplet-based single EV-counting enzyme-linked immunosorbent assays (ELISA), proximity-dependent barcoding assays, and surface-enhanced Raman spectroscopy further enhance our ability to precisely identify biomarkers, detect diseases earlier, and significantly improve clinical outcomes. These innovations provide access to intricate molecular details that expand our understanding of EV composition, with profound diagnostic implications. This review also examines key research challenges in the field, including the complexities of sample analysis, technique sensitivity and specificity, the level of detail provided by analytical methods, and practical applications, and we identify directions for future research. This review underscores the value of advanced EV analysis methods, which contribute to deep insights into EV-mediated pathological diversity and enhanced clinical diagnostics.

It is increasingly clear that intercellular communication is largely mediated by lipid-bilayer, membrane-bound extracellular vesicles (EVs) and amembranous, non-vesicular extracellular particles (NVEPs), including exomeres and the recently identified supermeres. To elucidate the cargo and functional roles of these carriers, we performed a comprehensive analysis of their lipid, protein and RNA content in the context of colorectal cancer and glioblastoma (GBM). Our results demonstrate that EVs exhibit distinct density profiles correlated with specific biomolecular signatures. Moreover, EVs and NVEPs display notable differences in their protein and RNA composition, which confer distinct functional attributes. Supermeres are notably enriched in components involved in extracellular matrix remodeling and possess the ability to cross the blood-brain barrier, a process dependent on their intact structure and RNA content. Once in the central nervous system (CNS), they preferentially engage with microglia and suppress TGFβ1 expression, suggesting a role in modulating microglial immune activity. Furthermore, systemically administered exogenous supermeres selectively accumulate in GBM tumors in vivo. Together, these findings highlight supermeres as a promising vehicle for delivering therapeutics to the CNS and brain tumors.

Current studies of biological tissues require visualizing diverse cell types and molecular interactions, creating a growing need for versatile techniques to simultaneously probe numerous targets. Traditional multiplexed imaging is limited to around five targets at once. Emerging methods using sequential rounds of staining, imaging, and signal removal can probe tens of targets but require specialized hardware and time-consuming workflows and face challenges with sample distortion and artifacts. We present a highly multiplexed fluorescence microscopy method using semiconducting polymer dots (Pdots) in a single round of staining and imaging. Pdots are small, bright, and photostable fluorescent probes with a wide range of tunable Stokes shifts (20 to 450 nanometers). Multiple series of Pdots with varying excitation wavelengths allow for fast (<1 minute) and single-round imaging of up to 21 targets in the brain and kidney. This method is based on a simple immunofluorescence workflow, efficient use of spectral space, standard hardware, and straightforward analysis, making it widely applicable for bioimaging laboratories.

High‐sensitivity flow cytometers have been developed for multi‐parameter characterization of single extracellular vesicles (EVs), but performance varies among instruments and calibration methods. Here we compare the characterization of identical (split) EV samples derived from human colorectal cancer (DiFi) cells by three high‐sensitivity flow cytometers, two commercial instruments, CytoFLEX/CellStream, and a custom single‐molecule flow cytometer (SMFC). DiFi EVs were stained with the membrane dye di‐8‐ANEPPS and with PE‐conjugated anti‐EGFR or anti‐tetraspanin (CD9/CD63/CD81) antibodies for estimation of EV size and surface protein copy numbers. The limits of detection (LODs) for immunofluorescence and vesicle size based on calibration using cross‐calibrated, hard‐dyed beads were ∼10 PE/∼80 nm EV diameter for CytoFLEX and ∼10 PEs/∼67 nm for CellStream. For the SMFC, the LOD for immunofluorescence was 1 PE and ≤ 35 nm for size. The population of EVs detected by each system (di‐8‐ANEPPS+/PE+ particles) differed widely depending on the LOD of the system; for example, CellStream/CytoFLEX detected only 5.7% and 1.5% of the tetraspanin‐labelled EVs detected by SMFC, respectively, and median EV diameter and antibody copy numbers were much larger for CellStream/CytoFLEX than for SMFC as measured and validated using super‐resolution/single‐molecule TIRF microscopy. To obtain a dataset representing a common EV population analysed by all three platforms, we filtered out SMFC and CellStream measurements for EVs below the CytoFLEX LODs as determined by bead calibration (10 PE/80 nm). The inter‐platform agreement using this filtered dataset was significantly better than for the unfiltered dataset, but even better concordance between results was obtained by applying higher cutoffs (21 PE/120 nm) determined by threshold analysis using the SMFC data. The results demonstrate the impact of specifying LODs to define the EV population analysed on inter‐instrument reproducibility in EV flow cytometry studies, and the utility of threshold analysis of SMFC data for providing semi‐quantitative LOD values for other flow cytometers.

With an evolving understanding and new discoveries in extracellular vesicle (EV) biology and their implications in health and disease, the significant diagnostic and therapeutic potential of EVs for vision research has gained recognition. In 2021, the National Eye Institute (NEI) unveiled its Strategic Plan titled 'Vision for the Future (2021-2025),' which listed EV research as a priority within the domain of Regenerative Medicine, a pivotal area outlined in the Plan. In alignment with this prioritization, NEI organized a workshop inviting twenty experts from within and beyond the visual system. The workshop aimed to review current knowledge in EV research and explore gaps, needs and opportunities for EV research in the eye, including EV biology and applications of EVs in diagnosis, therapy and prognosis within the visual system. This perspective encapsulates the workshop's deliberations, highlighting the current landscape and potential implications of EV research in advancing eye health and addressing visual diseases.

Single-cell analysis of cell phenotypic information such as surface protein expression and nucleic acid content is essential for understanding heterogeneity within cell populations. Here the design and use of a dielectrophoresis-assisted self-digitization (SD) microfluidics chip is described; it captures single cells in isolated microchambers with high efficiency for single-cell analysis. The self-digitization chip spontaneously partitions aqueous solution into microchambers through a combination of fluidic forces, interfacial tension, and channel geometry. Single cells are guided to and trapped at the entrances of microchambers by dielectrophoresis (DEP) due to local electric field maxima created by an externally applied AC voltage. Excess cells are flushed away, and trapped cells are released into the chambers and prepared for in situ analysis by turning off the external voltage, by running reaction buffer through the chip, and by sealing the chambers with a flow of an immiscible oil phase through the surrounding channels. The use of this device in single-cell analysis is demonstrated by performing single-cell nucleic acid quantitation based on loop-mediated isothermal amplification (LAMP). This platform provides a powerful new tool for single-cell research pertaining to drug discovery. For example, the single-cell genotyping of cancer-related mutant gene observed from the digital chip could be useful biomarker for targeted therapy.

Immunophenotyping of vesicles, such as extracellular vesicles (EVs), is essential to understanding their origin and biological role. We previously described a custom-built flow analyzer that utilizes a gravity-driven flow, high numerical aperture objective, and micrometer-sized flow channels to reach the sensitivity needed for fast multidimensional analysis of the surface proteins of EVs, even down to the smallest EVs (e.g., ∼30-40 nm). It is difficult to flow focus small EVs, and thus, the transiting EVs exhibit a distribution in particle velocities due to the laminar flow. This distribution of vesicle velocities leads to potentially incorrect results when immunophenotyping nanometer-sized vesicles using cross-correlation analysis (Xcorr), as the order of appearance of the vesicles might not be the same at different spatially offset laser excitation regions. Here, we describe an alternative cross-correlation analysis strategy (Scorr), which uses information on particle transit time across the laser excitation beam width to improve multicolor colocalization in single-vesicle immunoprofiling. We tested the performance of the algorithm for colocalization analysis of multicolor nanobeads and EVs experimentally and via simulations and found that Scorr improved both the efficiency and accuracy of colocalization versus Xcorr. As shown from Monte Carlo simulations, Scorr provided an ∼1.2-4.7-fold increase in the number of colocalized peaks and ensured negligible colocalization of peaks. In silico results were in good agreement with experimental data, which showed an increase in colocalized peaks of ∼1.3-2.5-fold and ∼1.2-2-fold for multicolor beads and EVs, respectively.

Single-molecule localization microscopy (SMLM) allows super-resolution imaging, mapping, counting, and sizing of biological nanostructures such as cell organelles and extracellular vesicles (EVs), but sizing structures smaller than ∼100 nm can be inaccurate due to single-molecule localization error caused by distortion of the point spread function and limited photon number. Here we demonstrate a method to correct localization error when sizing vesicles and other spherical nanoparticles with SMLM and compare sizing results using two vesicle labeling schemes. We use mean approximation theory to derive a simple equation using full width at half-maximum (FWHM) for correcting particle sizes measured by two-dimensional SMLM, validate the method by sizing streptavidin-coated polystyrene nanobeads with the SMLM technique dSTORM with and without error correction, using transmission electron microscopy (TEM) for comparison, and then apply the method to sizing small seminal EVs. Nanobead sizes measured by dSTORM became increasingly less accurate (larger than TEM values) for beads smaller than 50 nm. The error-correction method reduced the size difference versus TEM from 15% without error correction to 7% with error correction for 40 nm beads, from 44% to 9% for 30 nm beads, and from 66% to 15% for 20 nm beads. Seminal EVs were labeled with a lipophilic membrane dye (MemBright 700) and with an Alexa Fluor 488-anti-CD63 antibody conjugate, and were sized separately using both dyes by dSTORM. Error-corrected exosome diameters were smaller than uncorrected values: 72 nm vs 79 nm mean diameter with membrane dyes; 84 nm vs 97 nm with the antibody-conjugated dyes. The mean error-corrected diameter was 12 nm smaller when using the membrane dye than when using the antibody-conjugated dye likely due to the large size of the antibody. Thus, both the error-correction method and the compact membrane labeling scheme reduce overestimation of vesicle size by SMLM. This error-correction method has a low computational cost as it does not require correction of individual blinking events, and it is compatible with all SMLM techniques (e.g., PALM, STORM, and DNA-PAINT).

Semiconducting polymer dots (Pdots) with both narrow-band absorption and emission are desirable for multiplexed bioassay applications, but such Pdots with absorption peaks beyond 400 nm are difficult to achieve. Here we describe a donor-energy transfer unit-acceptor (D-ETU-A) design strategy to produce a BODIPY-based Pdot that exhibits simultaneously narrow absorption and emission bands. A green BODIPY (GBDP) unit was employed as the main building block of the polymer backbone, conferring a strong, narrow-band absorption around 551 nm. An NIR720 acceptor provides narrow-band NIR emission. The small Stokes shift of the GBDP donor allows introduction of a benzofurazan-based ETU, resulting in a ternary Pdot with a fluorescence quantum yield of 23.2%, the most efficient yellow-laser excitable Pdot. Due to the strong absorbance band centered at 551 nm and weak absorbance at 405 nm and 488 nm, the Pdot showed high single-particle brightness when excited by a 561 nm (yellow) laser, and selective yellow laser excitation when used to label MCF cells, with much greater brightness when excited at 561 nm than at 405 nm or 488 nm.

The spatial resolution of single-molecule localization microscopy is limited by the photon number of a single switching event because of the difficulty of correlating switching events dispersed in time. Here we overcome this limitation by developing a new class of photoswitching semiconducting polymer dots (Pdots) with structured and highly dispersed single-particle spectra. We imaged the Pdots at the first and the second vibronic emission peaks and used the ratio of peak intensities as a spectral coding. By correlating switching events using the spectral coding and performing 4-9 frame binning, we achieved a 2-3 fold experimental resolution improvement versus conventional superresolution imaging. We applied this method to count and map SV2 and proton ATPase proteins on synaptic vesicles (SVs). The results reveal that these proteins are trafficked and organized with high precision, showing unprecedented level of detail about the composition and structure of SVs.

Aberrant cerebral glucose metabolism is related to many brain diseases, especially brain tumor. However, it remains challenging to measure the dynamic changes in cerebral glucose. Here, we developed a near-infrared (NIR) optical transducer to sensitively monitor the glucose variations in cerebrospinal fluid in vivo. The transducer consists of an oxygen-sensitive nanoparticle combined with glucose oxidase (GOx), yielding highly sensitive NIR phosphorescence in response to blood glucose change. We demonstrated long-term continuous glucose monitoring by using the NIR transducer. After subcutaneous implantation, the glucose transducer provides a strong luminescence signal that can continuously monitor blood glucose fluctuations for weeks. By using the NIR emission of the transducer, we further observed abnormal dynamic changes in cerebrospinal fluid glucose and quantitatively assessed cerebral glucose uptake rates in transgenic mice bearing brain tumors. This study provides a promising method for the diagnosis of various metabolic diseases with altered glucose metabolism.

The extracellular RNA communication consortium (ERCC) is an NIH-funded program aiming to promote the development of new technologies, resources, and knowledge about exRNAs and their carriers. After Phase 1 (2013-2018), Phase 2 of the program (ERCC2, 2019-2023) aims to fill critical gaps in knowledge and technology to enable rigorous and reproducible methods for separation and characterization of both bulk populations of exRNA carriers and single EVs. ERCC2 investigators are also developing new bioinformatic pipelines to promote data integration through the exRNA atlas database. ERCC2 has established several Working Groups (Resource Sharing, Reagent Development, Data Analysis and Coordination, Technology Development, nomenclature, and Scientific Outreach) to promote collaboration between ERCC2 members and the broader scientific community. We expect that ERCC2's current and future achievements will significantly improve our understanding of exRNA biology and the development of accurate and efficient exRNA-based diagnostic, prognostic, and theranostic biomarker assays.

Hot embossing is a cost-effective and flexible fabrication technology with high replication accuracy for feature sizes as small as 50 nm. Here we develop a reinforced polydimethylsiloxane (PDMS) mold for hot embossing of cyclic olefin polymer (COP) sheets in the fabrication of microfluidic chips and demonstrate the method by fabricating chips for automated sample digitization in digital nucleic acid assays. The PDMS is hardened by adding an investment powder as a dopant and is constrained with an aluminum frame to prevent lateral expansion during hot pressing. The reinforced PDMS mold demonstrated excellent performance in hot embossing (180 °C, 103 kPa, 5 min) for micropatterning COP sheets, with highly reproducible features as small as 10 μm (width of draining channel). In contrast, the microscale features were inconsistent and distorted when omitting either the investment powder or frame from the PDMS mold. COP chips were assembled by thermally bonding patterned and unpatterned COP sheets. We tested the performance of the COP chip for automated sample digitization in a digital LAMP assay used to quantify human papillomavirus-18 (HPV-18) DNA. A mixture of nucleic acid amplification reagents was loaded into the main channel of the chip using a syringe pump, then the solution was spontaneously partitioned into chambers (∼0.6 nL), which were then isolated by flowing oil through the chip. The digital LAMP assay produced accurately absolute quantitation of DNA at concentrations ranging from 10 to 1000 copies per μL. The strategy presented here provides a simple, low-cost method to prepare molds for hot embossing, which facilitates rapid validation of microfluidic designs.

This report summarises the presentations and activities of the SELECTBIO Workshop on Rigor and Reproducibility in EV Research and Single EV Analysis held in San Diego, USA, in December 2021. The motivation for the session was the recognition that progress in the extracellular vesicle (EV) field is limited by the availability of rigorous and reproducible EV measurement tools. These tools are absolutely required for EVs to evolve from a research lab curiosity to something that will improve our ability to understand, diagnose, treat, and prevent disease. The program focused on guidelines for EV measurement and characterization as laid out in the recent MISEV2018 and MIFlowCyt-EV publications, their implementation in routine practice, and their continued evolution as new EV measurement technologies are introduced. The conclusion of the workshop was that more effort focused on pre-analytical issues and benchmarking of isolation methods is needed to strengthen collaborations and advance more effective biomarkers.

Semiconducting polymer dots (Pdots) are increasingly used in biomedical applications due to their extreme single-particle brightness, which results from their large absorption cross section (σ). However, the quantum yield (Φ) of Pdots is typically below 40% due to aggregation-induced self-quenching. One approach to reducing self-quenching is to use FRET between the donor (D) and acceptor (A) groups within a Pdot; however, Φ values of FRET-based Pdots remain low. Here, we demonstrate an approach to achieve ultrabright FRET-based Pdots with simultaneously high σ and Φ. The importance of self-quenching was revealed in a non-FRET Pdot: adding 30 mol % of a nonabsorbing polyphenyl to a poly(9,9-dioctylfluorene) (PFO) Pdot increased Φ from 13.4 to 71.2%, yielding an ultrabright blue-emitting Pdot. We optimized the brightness of FRET-based Pdots by exploring different D/A combinations and ratios with PFO and poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(1,4-phenylene)] (PFP) as donor polymers and poly[(9,9-dioctyl-2,7-divinylenefluorenylene)-alt-co-(1,4-phenylene)] (PFPV) and poly[(9,9-dioctylfluorenyl-2,7-diyl)-alt-co-(1,4-benzo-{2,1',3}-thiadiazole)] (PFBT) as acceptor polymers, with a fixed concentration of poly(styrene-co-maleic anhydride) as surfactant polymer. Ultrabright blue-emitting Pdots possessing high Φ (73.1%) and σ (σR = σabs/σall, 97.5%) were achieved using PFP/PFPV Pdots at a low acceptor content (A/[D + A], 2.5 mol %). PFP/PFPV Pdots were 1.8 times as bright as PFO/PFPV Pdots due to greater coverage of acceptor absorbance by donor emission─a factor often overlooked in D/A pair selection. Ultrabright green-emitting PFO Pdots (Φ = 76.0%, σR = 92.5%) were obtained by selecting an acceptor (PFBT) with greater spectral overlap with PFO. Ultrabright red-emitting Pdots (Φ = 64.2%, σR = 91.0%) were achieved by blending PFO, PFBT, and PFTBT to create a cascade FRET Pdot at a D:A1:A2 molar ratio of 61:5:1. These blue, green, and red Pdots are among the brightest Pdots reported. This approach of using a small, optimized amount of FRET acceptor polymer with a large donor-acceptor spectral overlap can be generalized to produce ultrabright Pdots with emissions that span the visible spectrum.

Optical sensors have attracted a great deal of interest for glucose detection. However, their practical applications for continuous glucose monitoring are still constrained by operational reliability in subcutaneous tissues. Here, we show an implantable hydrogel platform embedded with luminescent polymer dots (Pdots) for sensitive and long-term glucose monitoring. We use Pdot transducer in a polyacrylamide hydrogel matrix to construct an implantable platform. The hydrogel-Pdot transducer showed bright luminescence with ratiometric response to glucose changes. The in vitro and in vivo sensitivities of the hydrogel implant were enhanced by varying the enzyme concentration and injection volume. After implantation, the hydrogel with Pdot transducer remained at the implanted site without migration for 1 month and can be removed from the subcutaneous tissue for further analysis. Our results indicate that the hydrogel-Pdot platform maintains the intrinsic sensing property with excellent stability during 1 month implantation, while fibrous capsule formation on the implant in some cases needs to be solved for long-term continuous glucose monitoring.