Interferometric Reflectance Imaging Sensor (IRIS)--A Platform Technology for Multiplexed Diagnostics and Digital Detection

Simultaneous Protein and RNA Analysis in Single Extracellular Vesicles, Including Viruses

The individual detection of human immunodeficiency virus (HIV) virions and resolution from extracellular vesicles (EVs) during analysis is a difficult challenge. Infectious enveloped virions and nonviral EVs are released simultaneously by HIV-infected host cells, in addition to hybrid viral EVs containing combinations of HIV and host components but lacking replicative ability. Complicating the issue, EVs and enveloped virions are both delimited by a lipid bilayer and share similar size and density. The feature that distinguishes infectious virions from host and hybrid EVs is the HIV genomic RNA (gRNA), which allows the virus to replicate. Single-particle analysis techniques, which provide snapshots of single biological nanoparticles, could resolve infectious virions from EVs. However, current single-particle analysis techniques focus mainly on protein detection, which fail to resolve hybrid EVs from infectious virions. A method to simultaneously detect viral protein and internal gRNA in the same particle would allow resolution of infectious HIV from EVs and noninfectious virions. Here, we introduce SPIRFISH, a high-throughput method for single-particle protein and RNA analysis, combining single particle interferometric reflectance imaging sensor with single-molecule fluorescence in situ hybridization. Using SPIRFISH, we detect HIV-1 envelope protein gp120 and genomic RNA within single infectious virions, allowing resolution against EV background and noninfectious virions. We further show that SPIRFISH can be used to detect specific RNAs within EVs. This may have major utility for EV therapeutics, which are increasingly focused on EV-mediated RNA delivery. SPIRFISH should enable single particle analysis of a broad class of RNA-containing nanoparticles.

Factors to consider before choosing EV labeling method for fluorescence-based techniques

A well-designed fluorescence-based analysis of extracellular vesicles (EV) can provide insights into the size, morphology, and biological function of EVs, which can be used in medical applications. Fluorescent nanoparticle tracking analysis with appropriate controls can provide reliable data for size and concentration measurements, while nanoscale flow cytometry is the most appropriate tool for characterizing molecular cargoes. Label selection is a crucial element in all fluorescence methods. The most comprehensive data can be obtained if several labeling approaches for a given marker are used, as they would provide complementary information about EV populations and interactions with the cells. In all EV-related experiments, the influence of lipoproteins and protein corona on the results should be considered. By reviewing and considering all the factors affecting EV labeling methods used in fluorescence-based techniques, we can assert that the data will provide as accurate as possible information about true EV biology and offer precise, clinically applicable information for future EV-based diagnostic or therapeutic applications.

Allergen Microarrays and New Physical Approaches to More Sensitive and Specific Detection of Allergen-Specific Antibodies

The prevalence of allergic diseases has increased tremendously in recent decades, which can be attributed to growing exposure to environmental triggers, changes in dietary habits, comorbidity, and the increased use of medications. In this context, the multiplexed diagnosis of sensitization to various allergens and the monitoring of the effectiveness of treatments for allergic diseases become particularly urgent issues. The detection of allergen-specific antibodies, in particular, sIgE and sIgG, is a modern alternative to skin tests due to the safety and efficiency of this method. The use of allergen microarrays to detect tens to hundreds of allergen-specific antibodies in less than 0.1 mL of blood serum enables the transition to a deeply personalized approach in the diagnosis of these diseases while reducing the invasiveness and increasing the informativeness of analysis. This review discusses the technological approaches underlying the development of allergen microarrays and other protein microarrays, including the methods of selection of the microarray substrates and matrices for protein molecule immobilization, the obtainment of allergens, and the use of different types of optical labels for increasing the sensitivity and specificity of the detection of allergen-specific antibodies.

Two-color interferometric scattering (iSCAT) microscopy reveals structural dynamics in discrete plasmonic molecules

Plasmonic molecules are discrete assemblies of noble metal nanoparticles (NPs) that are of interest as transducers in optical nanosensors. So far, NPs with diameters of ∼40 nm have been the preferred building blocks for plasmonic molecules intended as optical single molecule sensors due to difficulties associated with detecting smaller NPs through elastic scattering in conventional darkfield microscopy. Here, we apply 405 nm, 445 nm two-color interferometric scattering (iSCAT) microscopy to characterize polyethylene glycol (PEG) tethered dimers of 10 nm and 20 nm Ag NPs and their monomers. Dimers of both NP sizes can be discerned from their respective monomers through changes in the average iSCAT contrast. In the case of 20 nm Ag NPs, dimer formation induces a change in the sign of the iSCAT contrast, providing a characteristic signal for detecting binding events. 20 nm Ag NP dimers with 0.4 kDa and 3.4 kDa polyethylene glycol (PEG) spacers show iSCAT contrast distributions with significantly different averages on both wavelength channels. The iSCAT contrast measured for individual PEG-tethered 10 nm or 20 nm NP dimers as a function of time shows contrast fluctuations indicative of a rich structural dynamics in the assembled plasmonic molecules, which provides an additional metric to discern dimers from monomers and paves the path to a new class of interferometric plasmon rulers.

Understanding exosomes: Part 1-Characterization, quantification and isolation techniques

Exosomes are the smallest subset of extracellular signaling vesicles secreted by most cells with a diameter in the range of 30-150 nm. Their use has gained great momentum recently due to their ability to be utilized as diagnostic tools with a vast array of therapeutic applications. Over 5000 publications are currently being published yearly on this topic, and this number is only expected to dramatically increase as novel therapeutic strategies continue to be investigated. This review article first focuses on understanding exosomes, including their cellular origin, biogenesis, function, and characterization. Thereafter, overviews of the quantification methods and isolation techniques are given with discussion over their potential use as novel therapeutics in regenerative medicine.

Roadmap on Label-Free Super-Resolution Imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles which need to be overcome to break the classical diffraction limit of the LFSR imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability which are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.

Coherent Fourier scatterometry: a holistic tool for inspection of isolated particles or defects on gratings

Detecting defects on diffraction gratings is crucial for ensuring their performance and reliability. Practical detection of these defects poses challenges due to their subtle nature. We perform numerical investigations and demonstrate experimentally the capability of coherent Fourier scatterometry (CFS) to detect particles as small as 100 nm and also other irregularities that are encountered usually on diffraction gratings. Our findings indicate that CFS is a viable tool for inspection of diffraction gratings.

Extracellular Vesicles: Techniques and Biomedical Applications Related to Single Vesicle Analysis

Extracellular vesicles (EVs) are extensively dispersed lipid bilayer membrane vesicles involved in the delivery and transportation of molecular payloads to certain cell types to facilitate intercellular interactions. Their significant roles in physiological and pathological processes make EVs outstanding biomarkers for disease diagnosis and treatment monitoring as well as ideal candidates for drug delivery. Nevertheless, differences in the biogenesis processes among EV subpopulations have led to a diversity of biophysical characteristics and molecular cargos. Additionally, the prevalent heterogeneity of EVs has been found to substantially hamper the sensitivity and accuracy of disease diagnosis and therapeutic monitoring, thus impeding the advancement of clinical applications. In recent years, the evolution of single EV (SEV) analysis has enabled an in-depth comprehension of the physical properties, molecular composition, and biological roles of EVs at the individual vesicle level. This review examines the sample acquisition tactics prior to SEV analysis, i.e., EV isolation techniques, and outlines the current state-of-the-art label-free and label-based technologies for SEV identification. Furthermore, the challenges and prospects of biomedical applications based on SEV analysis are systematically discussed.

Two Decades of Arrayed Imaging Reflectometry for Sensitive, High-Throughput Biosensing

Arrayed imaging reflectometry (AIR), first introduced in 2004, is a thin-film interference sensor technique that optimizes optical properties (angle of incidence, polarization, substrate refractive index, and thickness) to create a condition of total destructive interference at the surface of a silicon substrate. The advantages of AIR are its sensitivity, dynamic range, multiplex capability, and high-throughput compatibility. AIR has been used for the detection of antibodies against coronaviruses, influenza viruses, Staphylococcus aureus, and human autoantigens. It has also shown utility in detection of cytokines, with sensitivity comparable to bead-based and ELISA assays. Not limited to antibodies or antigens, mixed aptamer and protein arrays as well as glycan arrays have been employed in AIR for differentiating influenza strains. Mixed arrays using direct and competitive inhibition assays have enabled simultaneous measurement of cytokines and small molecules. Finally, AIR has also been used to measure affinity constants, kinetic and at equilibrium. In this review, we give an overview of AIR biosensing technologies and present the latest AIR advances.

Optical Biosensors for the Diagnosis of COVID-19 and Other Viruses-A Review

The sudden outbreak of the COVID-19 pandemic led to a huge concern globally because of the astounding increase in mortality rates worldwide. The medical imaging computed tomography technique, whole-genome sequencing, and electron microscopy are the methods generally used for the screening and identification of the SARS-CoV-2 virus. The main aim of this review is to emphasize the capabilities of various optical techniques to facilitate not only the timely and effective diagnosis of the virus but also to apply its potential toward therapy in the field of virology. This review paper categorizes the potential optical biosensors into the three main categories, spectroscopic-, nanomaterial-, and interferometry-based approaches, used for detecting various types of viruses, including SARS-CoV-2. Various classifications of spectroscopic techniques such as Raman spectroscopy, near-infrared spectroscopy, and fluorescence spectroscopy are discussed in the first part. The second aspect highlights advances related to nanomaterial-based optical biosensors, while the third part describes various optical interferometric biosensors used for the detection of viruses. The tremendous progress made by lab-on-a-chip technology in conjunction with smartphones for improving the point-of-care and portability features of the optical biosensors is also discussed. Finally, the review discusses the emergence of artificial intelligence and its applications in the field of bio-photonics and medical imaging for the diagnosis of COVID-19. The review concludes by providing insights into the future perspectives of optical techniques in the effective diagnosis of viruses.

Two-Color iSCAT Imaging of Ag Nanoparticles Resolves Size and Ambient Refractive Index Changes

The ability to discern noble metal nanoparticles (NPs) with different sizes and in ambient media with different refractive indices has important applications in imaging and sensing. Here a two-color (405 nm, 445 nm) interferometric scattering (iSCAT) detection scheme is applied to characterize the wavelength-dependent iSCAT contrast of Ag NPs with nominal diameters of 10, 20, 40, and 60 nm and to distinguish between NPs of different sizes. The iSCAT contrast also depends on the ambient refractive index and the relative iSCAT contrast on both channels revealed a spectral red-shift for 40 and 60 nm Ag NPs when the ambient refractive index was increased from n = 1.3892 to n = 1.4328. With the selected wavelength channels, the spectral resolution of the two-color imaging strategy was, however, insufficient to resolve spectral shifts induced by refractive index changes for 10 and 20 nm Ag NPs.

A high-throughput single-particle imaging platform for antibody characterization and a novel competition assay for therapeutic antibodies

Monoclonal antibodies (mAbs) play an important role in diagnostics and therapy of infectious diseases. Here we utilize a single-particle interferometric reflectance imaging sensor (SP-IRIS) for screening 30 mAbs against Ebola, Sudan, and Lassa viruses (EBOV, SUDV, and LASV) to find out the ideal capture antibodies for whole virus detection using recombinant vesicular stomatitis virus (rVSV) models expressing surface glycoproteins (GPs) of EBOV, SUDV, and LASV. We also make use of the binding properties on SP-IRIS to develop a model for mapping the antibody epitopes on the GP structure. mAbs that bind to mucin-like domain or glycan cap of the EBOV surface GP show the highest signal on SP-IRIS, followed by mAbs that target the GP1-GP2 interface at the base domain. These antibodies were shown to be highly efficacious against EBOV infection in non-human primates in previous studies. For LASV detection, 8.9F antibody showed the best performance on SP-IRIS. This antibody binds to a unique region on the surface GP compared to other 15 mAbs tested. In addition, we demonstrate a novel antibody competition assay using SP-IRIS and rVSV-EBOV models to reveal the competition between mAbs in three successful therapeutic mAb cocktails against EBOV infection. We provide an explanation as to why ZMapp cocktail has higher efficacy compared to the other two cocktails by showing that three mAbs in this cocktail (13C6, 2G4, 4G7) do not compete with each other for binding to EBOV GP. In fact, the binding of 13C6 enhances the binding of 2G4 and 4G7 antibodies. Our results establish SP-IRIS as a versatile tool that can provide high-throughput screening of mAbs, multiplexed and sensitive detection of viruses, and evaluation of therapeutic antibody cocktails.

Prolonged Exposure to Simulated Microgravity Changes Release of Small Extracellular Vesicle in Breast Cancer Cells

Breast cancer is the leading cause of cancer incidence worldwide and among the five leading causes of cancer mortality. Despite major improvements in early detection and new treatment approaches, the need for better outcomes and quality of life for patients is still high. Extracellular vesicles play an important role in tumor biology, as they are able to transfer information between cells of different origins and locations. Their potential value as biomarkers or for targeted tumor therapy is apparent. In this study, we analyzed the supernatants of MCF-7 breast cancer cells, which were harvested following 5 or 10 days of simulated microgravity on a Random Positioning Machine (RPM). The primary results showed a substantial increase in released vesicles following incubation under simulated microgravity at both time points. The distribution of subpopulations regarding their surface protein expression is also altered; the minimal changes between the time points hint at an early adaption. This is the first step in gaining further insight into the mechanisms of tumor progression, metastasis, the education of the tumor microenvironments, and preparation of the metastatic niche. Additionally, this may lighten up the processes of the rapid cellular adaptions in the organisms of space travelers during spaceflights.

Small non-coding RNA landscape of extracellular vesicles from a post-traumatic model of equine osteoarthritis

Extracellular vesicles comprise an as yet inadequately investigated intercellular communication pathway in the field of early osteoarthritis. We hypothesised that the small non-coding RNA expression pattern in synovial fluid and plasma would change during progression of experimental osteoarthritis. In this study, we conducted small RNA sequencing to provide a comprehensive overview of the temporal expression profiles of small non-coding transcripts carried by extracellular vesicles derived from plasma and synovial fluid for the first time in a posttraumatic model of equine osteoarthritis. Additionally, we characterised synovial fluid and plasma-derived extracellular vesicles with respect to quantity, size, and surface markers. The different temporal expressions of seven microRNAs in plasma and synovial fluid-derived extracellular vesicles, eca-miR-451, eca-miR-25, eca-miR-215, eca-miR-92a, eca-miR-let-7c, eca-miR-486-5p, and eca-miR-23a, and four snoRNAs, U3, snord15, snord46, and snord58, represent potential biomarkers for early osteoarthritis. Bioinformatics analysis of the differentially expressed microRNAs in synovial fluid highlighted that in early osteoarthritis these related to the inhibition of cell cycle, cell cycle progression, DNA damage and cell proliferation as well as increased cell viability and differentiation of stem cells. Plasma and synovial fluid-derived extracellular vesicle small non-coding signatures have been established for the first time in a temporal model of osteoarthritis. These could serve as novel biomarkers for evaluation of osteoarthritis progression or act as potential therapeutic targets.

Recent advances in optical label-free characterization of extracellular vesicles

Extracellular vesicles (EVs) are complex biological nanoparticles endogenously secreted by all eukaryotic cells. EVs carry a specific molecular cargo of proteins, lipids, and nucleic acids derived from cells of origin and play a significant role in the physiology and pathology of cells, organs, and organisms. Upon release, they may be found in different body fluids that can be easily accessed via noninvasive methodologies. Due to the unique information encoded in their molecular cargo, they may reflect the state of the parent cell and therefore EVs are recognized as a rich source of biomarkers for early diagnostics involving liquid biopsy. However, body fluids contain a mixture of EVs released by different types of healthy and diseased cells, making the detection of the EVs of interest very challenging. Recent research efforts have been focused on the detection and characterization of diagnostically relevant subpopulations of EVs, with emphasis on label-free methods that simplify sample preparation and are free of interfering signals. Therefore, in this paper, we review the recent progress of the label-free optical methods employed for the detection, counting, and morphological and chemical characterization of EVs. We will first briefly discuss the biology and functions of EVs, and then introduce different optical label-free techniques for rapid, precise, and nondestructive characterization of EVs such as nanoparticle tracking analysis, dynamic light scattering, atomic force microscopy, surface plasmon resonance spectroscopy, Raman spectroscopy, and SERS spectroscopy. In the end, we will discuss their applications in the detection of neurodegenerative diseases and cancer and provide an outlook on the future impact and challenges of these technologies to the field of liquid biopsy via EVs.

The Effects of Three-Dimensional Ligand Immobilization on Kinetic Measurements in Biosensors

The field of biosensing is in constant evolution, propelled by the need for sensitive, reliable platforms that provide consistent results, especially in the drug development industry, where small molecule characterization is of uttermost relevance. Kinetic characterization of small biochemicals is particularly challenging, and has required sensor developers to find solutions to compensate for the lack of sensitivity of their instruments. In this regard, surface chemistry plays a crucial role. The ligands need to be efficiently immobilized on the sensor surface, and probe distribution, maintenance of their native structure and efficient diffusion of the analyte to the surface need to be optimized. In order to enhance the signal generated by low molecular weight targets, surface plasmon resonance sensors utilize a high density of probes on the surface by employing a thick dextran matrix, resulting in a three-dimensional, multilayer distribution of molecules. Despite increasing the binding signal, this method can generate artifacts, due to the diffusion dependence of surface binding, affecting the accuracy of measured affinity constants. On the other hand, when working with planar surface chemistries, an incredibly high sensitivity is required for low molecular weight analytes, and furthermore the standard method for immobilizing single layers of molecules based on self-assembled monolayers (SAM) of epoxysilane has been demonstrated to promote protein denaturation, thus being far from ideal. Here, we will give a concise overview of the impact of tridimensional immobilization of ligands on label-free biosensors, mostly focusing on the effect of diffusion on binding affinity constants measurements. We will comment on how multilayering of probes is certainly useful in terms of increasing the sensitivity of the sensor, but can cause steric hindrance, mass transport and other diffusion effects. On the other hand, probe monolayers on epoxysilane chemistries do not undergo diffusion effect but rather other artifacts can occur due to probe distortion. Finally, a combination of tridimensional polymeric chemistry and probe monolayer is presented and reviewed, showing advantages and disadvantages over the other two approaches.

Sensitive and real-time detection of IgG using interferometric reflecting imaging sensor system

Considering the limitations of well-known traditional detection techniques, innovative research studies have focused on the development of new sensors to offer label-free, highly sensitive, real-time, low-cost, and rapid detection for biomolecular interactions. In this study, we demonstrate immunoglobulin G (IgG) detection in aqueous solutions by using real-time and label-free kinetic measurements of the Interferometric Reflectance Imaging Sensor (IRIS) system. By performing kinetic characterization experiments, the sensor's performance is comprehensively evaluated and a high correlation coefficient value (>0.94) is obtained in the IgG concentration range of 1-50 μg/mL with a low detection limit (0.25 μg/mL or 1.67 nM). Moreover, the highly sensitive imaging system ensures accurate quantification and reliable validation of recorded binding events, offering new perspectives in terms of direct biomarker detection for clinical applications.

A bi-functional polymeric coating for the co-immobilization of proteins and peptides on microarray substrates

The analytical performance of the microarray technique in screening the affinity and reactivity of molecules towards a specific target, is highly affected by the coupling chemistry adopted to bind probes to the surface. However, the surface functionality limits the biomolecules that can be attached to the surface to a single type of molecule, thus forcing the execution of separate analyses to compare the performance of different species in recognizing their targets. Here we introduce a new N, N-dimethylacrylamide-based polymeric coating, bearing simultaneously different functionalities (N-acryloyloxysuccinimide and azide groups) to allow an easy and straightforward method to co-immobilize proteins and oriented peptides on the same substrate. The bi-functional copolymer has been obtained by partial post polymerization modification of the functional groups of a common precursor. A NMR characterization of the copolymer was conducted to quantify the percentage of NAS that has been transformed into azido groups. The polymer was used to coat surfaces onto which both native antibodies and alkyne modified peptides were immobilized, to perform the phenotype characterization of extracellular vesicles (EVs). This strategy represents a convenient method to reduce the number of analysis, thus possible systematic or random errors, besides offering a drastic shortage in time, reagents and costs.

Attomolar analyte sensing techniques (AttoSens): a review on a decade of progress on chemical and biosensing nanoplatforms

Detecting the ultra-low abundance of analytes in real-life samples, such as biological fluids, water, soil, and food, requires the design and development of high-performance biosensing modalities. The breakthrough efforts from the scientific community have led to the realization of sensing technologies that measure the analyte's ultra-trace level, with relevant sensitivity, selectivity, response time, and sampling efficiency, referred to as Attomolar Analyte Sensing Techniques (AttoSens) in this review. In an AttoSens platform, 1 aM detection corresponds to the quantification of 60 target analyte molecules in 100 μL of sample volume. Herein, we review the approaches listed for various sensor probe design, and their sensing strategies that paved the way for the detection of attomolar (aM: 10^-18 M) concentration of analytes. A summary of the technological advances made by the diverse AttoSens trends from the past decade is presented.

Changes in Exosomal miRNA Composition in Thyroid Cancer Cells after Prolonged Exposure to Real Microgravity in Space

As much as space travel and exploration have been a goal since humankind looked up to the stars, the challenges coming with it are manifold and difficult to overcome. Therefore, researching the changes the human organism undergoes following exposure to weightlessness, on a cellular or a physiological level, is imperative to reach the goal of exploring space and new planets. Building on the results of our CellBox-1 experiment, where thyroid cancer cells were flown to the International Space Station, we are now taking advantage of the newest technological opportunities to gain more insight into the changes in cell–cell communication of these cells. Analyzing the exosomal microRNA composition after several days of microgravity might elucidate some of the proteomic changes we have reported earlier. An array scan of a total of 754 miRNA targets revealed more than 100 differentially expressed miRNAs in our samples, many of which have been implicated in thyroid disease in other studies.

Scattering-based Light Microscopy: From Metal Nanoparticles to Single Proteins

Our ability to detect, image, and quantify nanoscopic objects and molecules with visible light has undergone dramatic improvements over the past few decades. While fluorescence has historically been the go-to contrast mechanism for ultrasensitive light microscopy due to its superior background suppression and specificity, recent developments based on light scattering have reached single-molecule sensitivity. They also have the advantages of universal applicability and the ability to obtain information about the species of interest beyond its presence and location. Many of the recent advances are driven by novel approaches to illumination, detection, and background suppression, all aimed at isolating and maximizing the signal of interest. Here, we review these developments grouped according to the basic principles used, namely darkfield imaging, interferometric detection, and surface plasmon resonance microscopy.

Tetraspanins are unevenly distributed across single extracellular vesicles and bias sensitivity to multiplexed cancer biomarkers

Background

Tetraspanin expression of extracellular vesicles (EVs) is often used as a surrogate for their detection and classification, a practice that typically assumes their consistent expression across EV sources.

Results

Here we demonstrate that there are distinct patterns in colocalization of tetraspanin expression of EVs enriched from a variety of in vitro and in vivo sources. We report an optimized method for the use of single particle antibody-capture and fluorescence detection to identify subpopulations according to tetraspanin expression and compare our findings with nanoscale flow cytometry. We found that tetraspanin profile is consistent from a given EV source regardless of isolation method, but that tetraspanin profiles are distinct across various sources. Tetraspanin profiles measured by flow cytometry do not totally agree, suggesting that limitations in subpopulation detection significantly impact apparent protein expression. We further analyzed tetraspanin expression of single EVs captured non-specifically, revealing that tetraspanin capture can bias the apparent multiplexed tetraspanin profile. Finally, we demonstrate that this bias can have significant impact on diagnostic sensitivity for tumor-associated EV surface markers.

Conclusion

Our findings may reveal key insights into protein expression heterogeneity of EVs that better inform EV capture and detection platforms for diagnostic or other downstream use.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-021-00987-1.

Cytokines: From Clinical Significance to Quantification

Cytokines are critical mediators that oversee and regulate immune and inflammatory responses via complex networks and serve as biomarkers for many diseases. Quantification of cytokines has significant value in both clinical medicine and biology as the levels provide insights into physiological and pathological processes and can be used to aid diagnosis and treatment. Cytokines and their clinical significance are introduced from the perspective of their pro- and anti-inflammatory effects. Factors affecting cytokines quantification in biological fluids, native levels in different body fluids, sample processing and storage conditions, sensitivity to freeze-thaw, and soluble cytokine receptors are discussed. In addition, recent advances in in vitro and in vivo assays, biosensors based on different signal outputs and intracellular to extracellular protein expression are summarized. Various quantification platforms for high-sensitivity and reliable measurement of cytokines in different scenarios are discussed, and commercially available cytokine assays are compared. A discussion of challenges in the development and advancement of technologies for cytokine quantification that aim to achieve real-time multiplex cytokine analysis for point-of-care situations applicable for both biomedical research and clinical practice are discussed.

A compact photonic resonator absorption microscope for point of care digital resolution nucleic acid molecular diagnostics

Rapid, sensitive, and selective detection of nucleic acid biomarkers for health diagnostic applications becomes feasible for point of care scenarios when the detection instrument is inexpensive, simple, and robust. Here, we report the design, implementation, and characterization of a point of care instrument for photonic resonator absorption microscopy (PRAM) that takes advantage of resonant optical coupling between plasmonic gold nanoparticle tags and a photonic crystal (PC) surface. Matching the PC resonant wavelength to the gold nanoparticle's surface plasmon wavelength generates localized and efficient quenching of the PC resonant reflection intensity, resulting in the ability to clearly detect and count individual gold nanoparticles when they are captured on the PC surface. Surface-captured nanoparticles are observed by illuminating the PC at normal incidence with polarized light from a low-intensity red LED, and recording of PC reflected intensity on an inexpensive CMOS image sensor. A contrast limited adaptive histogram equalization (CLAHE) image processing algorithm was applied to derive counts of captured nanoparticles. The instrument is utilized in the context of an activate capture + digital counting (AC + DC) assay for a specific miRNA sequence, using nucleic acid toehold probes applied to gold nano-urchin (AuNU) nanoparticles to achieve 160 aM detection limits in a 30 min. assay.

Separation, characterization, and standardization of extracellular vesicles for drug delivery applications

Extracellular vesicles (EVs) are membranous nanovesicles secreted from living cells, shuttling macromolecules in intercellular communication and potentially possessing intrinsic therapeutic activity. Due to their stability, low immunogenicity, and inherent interaction with recipient cells, EVs also hold great promise as drug delivery vehicles. Indeed, they have been used to deliver nucleic acids, proteins, and small molecules in preclinical investigations. Furthermore, EV-based drugs have entered early clinical trials for cancer or neurodegenerative diseases. Despite their appeal as delivery vectors, however, EV-based drug delivery progress has been hampered by heterogeneity of sample types and methods as well as a persistent lack of standardization, validation, and comprehensive reporting. This review highlights specific requirements for EVs in drug delivery and describes the most pertinent approaches for separation and characterization. Despite residual uncertainties related to pharmacodynamics, pharmacokinetics, and potential off-target effects, clinical-grade, high-potency EV drugs might be achievable through GMP-compliant workflows in a highly standardized environment.

Using single-vesicle technologies to unravel the heterogeneity of extracellular vesicles

Extracellular vesicles (EVs) are heterogeneous lipid containers with a complex molecular cargo comprising several populations with unique roles in biological processes. These vesicles are closely associated with specific physiological features, which makes them invaluable in the detection and monitoring of various diseases. EVs play a key role in pathophysiological processes by actively triggering genetic or metabolic responses. However, the heterogeneity of their structure and composition hinders their application in medical diagnosis and therapies. This diversity makes it difficult to establish their exact physiological roles, and the functions and composition of different EV (sub)populations. Ensemble averaging approaches currently employed for EV characterization, such as western blotting or 'omics' technologies, tend to obscure rather than reveal these heterogeneities. Recent developments in single-vesicle analysis have made it possible to overcome these limitations and have facilitated the development of practical clinical applications. In this review, we discuss the benefits and challenges inherent to the current methods for the analysis of single vesicles and review the contribution of these approaches to the understanding of EV biology. We describe the contributions of these recent technological advances to the characterization and phenotyping of EVs, examination of the role of EVs in cell-to-cell communication pathways and the identification and validation of EVs as disease biomarkers. Finally, we discuss the potential of innovative single-vesicle imaging and analysis methodologies using microfluidic devices, which promise to deliver rapid and effective basic and practical applications for minimally invasive prognosis systems.

Bond-selective imaging by optically sensing the mid-infrared photothermal effect

Mid-infrared (IR) spectroscopic imaging using inherent vibrational contrast has been broadly used as a powerful analytical tool for sample identification and characterization. However, the low spatial resolution and large water absorption associated with the long IR wavelengths hinder its applications to study subcellular features in living systems. Recently developed mid-infrared photothermal (MIP) microscopy overcomes these limitations by probing the IR absorption-induced photothermal effect using a visible light. MIP microscopy yields submicrometer spatial resolution with high spectral fidelity and reduced water background. In this review, we categorize different photothermal contrast mechanisms and discuss instrumentations for scanning and widefield MIP microscope configurations. We highlight a broad range of applications from life science to materials. We further provide future perspective and potential venues in MIP microscopy field.

Elucidating Methods for Isolation and Quantification of Exosomes: A Review

Exosomes are the smallest extracellular vesicles present in most of the biological fluids. They are found to play an important role in cell signaling, immune response, tumor metastasis, etc. Studies have shown that these vesicles also have diagnostic and therapeutic roles for which their accurate detection and quantification is essential. Due to the complexity in size and structure of exosomes, even the gold standard methods face challenges. This comprehensive review discusses the various standard methods such as ultracentrifugation, ultrafiltration, size-exclusion chromatography, precipitation, immunoaffinity, and microfluidic technologies for the isolation of exosomes. The principle of isolation of each method is described, as well as their specific advantages and disadvantages. Quantification of exosomes by nanoparticle tracking analysis, flow cytometry, tunable resistive pulse sensing, electron microscopy, dynamic light scattering, and microfluidic devices are also described, along with the applications of exosomes in various biomedical domains.

Single cell capture, isolation, and long-term in-situ imaging using quantitative self-interference spectroscopy

Single cell research with microfluidic chip is of vital importance in biomedical studies and clinical medicine. Simultaneous microfluidic cell manipulations and long-term cell monitoring needs further investigations due to the lack of label-free quantitative imaging techniques and systems. In this work, single cell capture, isolation and long-term in-situ monitoring was realized with a microfluidic cell chip, compact cell incubator and quantitative self-interference spectroscopy. The proposed imaging method could obtain quantitative and dynamic refractive index distribution in living cells. And the designed microfluidic chip could capture and isolate single cells. The customized incubator could support cell growth conditions when single cell was captured in microfluidic chip. According to the results, single cells could be trapped, transferred and pushed into the culture chamber with the microfluidic chip. The incubator could culture single cells in the chip for 120 h. The refractive index sensitivity of the proposed quantitative imaging method was 0.0282 and the relative error was merely 0.04%.

Changes in Exosome Release in Thyroid Cancer Cells after Prolonged Exposure to Real Microgravity in Space

Space travel has always been the man’s ultimate destination. With the ability of spaceflight though, came the realization that exposure to microgravity has lasting effects on the human body. To counteract these, many studies were and are undertaken, on multiple levels. Changes in cell growth, gene, and protein expression have been described in different models on Earth and in space. Extracellular vesicles, and in particular exosomes, are important cell-cell communicators, being secreted from almost all the cells and therefore, are a perfect target to further investigate the underlying reasons of the organism’s adaptations to microgravity. Here, we studied supernatants harvested from the CellBox-1 experiment, which featured human thyroid cancer cells flown to the International Space Station during the SpaceX CRS-3 cargo mission. The initial results show differences in the number of secreted exosomes, as well as in the distribution of subpopulations in regards to their surface protein expression. Notably, alteration of their population regarding the tetraspanin surface expression was observed. This is a promising step into a new area of microgravity research and will potentially lead to the discovery of new biomarkers and pathways of cellular cross-talk.

A Reliable, Label Free Quality Control Method for the Production of DNA Microarrays with Clinical Applications

The manufacture of a very high-quality microarray support is essential for the adoption of this assay format in clinical routine. In fact, poorly surface-bound probes can affect the diagnostic sensitivity or, in worst cases, lead to false negative results. Here we report on a reliable and easy quality control method for the evaluation of spotted probe properties in a microarray test, based on the Interferometric Reflectance Imaging Sensor (IRIS) system, a high-resolution label free technique able to evaluate the variation of the mass bound to a surface. In particular, we demonstrated that the IRIS analysis of microarray chips immediately after probe immobilization can detect the absence of probes, which recognizably causes a lack of signal when performing a test, with clinical relevance, using fluorescence detection. Moreover, the use of the IRIS technique allowed also to determine the optimal concentration of the probe, that has to be immobilized on the surface, to maximize the target recognition, thus the signal, but to avoid crowding effects. Finally, through this preliminary quality inspection it is possible to highlight differences in the immobilization chemistries. In particular, we have compared NHS ester versus click chemistry reactions using two different surface coatings, demonstrating that, in the diagnostic case used as an example (colorectal cancer) a higher probe density does not reflect a higher binding signal, probably because of a crowding effect.

Precise Nanosizing with High Dynamic Range Holography

Optical sensing is one of the key enablers of modern diagnostics. Especially label-free imaging modalities hold great promise as they eliminate labeling procedures prior to analysis. However, scattering signals of nanometric particles scale with their volume square. This unfavorable scaling makes it extremely difficult to quantitatively characterize intrinsically heterogeneous clinical samples, such as extracellular vesicles, as their signal variation easily exceeds the dynamic range of currently available cameras. Here, we introduce off-axis k-space holography that circumvents this limitation. By imaging the back-focal plane of our microscope, we project the scattering signal of all particles onto all camera pixels, thus dramatically boosting the achievable dynamic range to up to 110 dB. We validate our platform by detecting and quantitatively sizing metallic and dielectric particles over a 200 × 200 μm field of view and demonstrate that independently performed signal calibrations allow correctly sizing particles made from different materials. Finally, we present quantitative size distributions of extracellular vesicle samples.

Instrument-Free Protein Microarray Fabrication for Accurate Affinity Measurements

Protein microarrays have gained popularity as an attractive tool for various fields, including drug and biomarker development, and diagnostics. Thus, multiplexed binding affinity measurements in microarray format has become crucial. The preparation of microarray-based protein assays relies on precise dispensing of probe solutions to achieve efficient immobilization onto an active surface. The prohibitively high cost of equipment and the need for trained personnel to operate high complexity robotic spotters for microarray fabrication are significant detriments for researchers, especially for small laboratories with limited resources. Here, we present a low-cost, instrument-free dispensing technique by which users who are familiar with micropipetting can manually create multiplexed protein assays that show improved capture efficiency and noise level in comparison to that of the robotically spotted assays. In this study, we compare the efficiency of manually and robotically dispensed α-lactalbumin probe spots by analyzing the binding kinetics obtained from the interaction with anti-α-lactalbumin antibodies, using the interferometric reflectance imaging sensor platform. We show that the protein arrays prepared by micropipette manual spotting meet and exceed the performance of those prepared by state-of-the-art robotic spotters. These instrument-free protein assays have a higher binding signal (~4-fold improvement) and a ~3-fold better signal-to-noise ratio (SNR) in binding curves, when compared to the data acquired by averaging 75 robotic spots corresponding to the same effective sensor surface area. We demonstrate the potential of determining antigen-antibody binding coefficients in a 24-multiplexed chip format with less than 5% measurement error.

Characterizing Extracellular Vesicles and Their Diverse RNA Contents

Cells release nanometer-scale, lipid bilayer-enclosed biomolecular packages (extracellular vesicles; EVs) into their surrounding environment. EVs are hypothesized to be intercellular communication agents that regulate physiological states by transporting biomolecules between near and distant cells. The research community has consistently advocated for the importance of RNA contents in EVs by demonstrating that: (1) EV-related RNA contents can be detected in a liquid biopsy, (2) disease states significantly alter EV-related RNA contents, and (3) sensitive and specific liquid biopsies can be implemented in precision medicine settings by measuring EV-derived RNA contents. Furthermore, EVs have medical potential beyond diagnostics. Both natural and engineered EVs are being investigated for therapeutic applications such as regenerative medicine and as drug delivery agents. This review focuses specifically on EV characterization, analysis of their RNA content, and their functional implications. The NIH extracellular RNA communication (ERC) program has catapulted human EV research from an RNA profiling standpoint by standardizing the pipeline for working with EV transcriptomics data, and creating a centralized database for the scientific community. There are currently thousands of RNA-sequencing profiles hosted on the Extracellular RNA Atlas alone (Murillo et al., 2019), encompassing a variety of human biofluid types and health conditions. While a number of significant discoveries have been made through these studies individually, integrative analyses of these data have thus far been limited. A primary focus of the ERC program over the next five years is to bring higher resolution tools to the EV research community so that investigators can isolate and analyze EV sub-populations, and ultimately single EVs sourced from discrete cell types, tissues, and complex biofluids. Higher resolution techniques will be essential for evaluating the roles of circulating EVs at a level which impacts clinical decision making. We expect that advances in microfluidic technologies will drive near-term innovation and discoveries about the diverse RNA contents of EVs. Long-term translation of EV-based RNA profiling into a mainstay medical diagnostic tool will depend upon identifying robust patterns of circulating genetic material that correlate with a change in health status.

Multiplexed homogeneous digital immunoassay based on single-particle motion analysis

Homogeneous digital immunoassay is a powerful analytical method for highly sensitive protein biomarker detection with a simple protocol. However, it has not been multiplexed yet. In this study, we developed a multiplexed homogeneous digital immunoassay based on single-particle motion analysis (digital homogeneous non-enzyme-linked immunosorbent assay, digital Ho-Non ELISA). In this assay, multiple target antigen molecules react with the optical subpopulation of magnetic nanobeads labeled with fluorescent dyes and capture antigen-specific antibodies. Then, these beads are magnetically pulled into femtoliter-sized reactors. The surface of these reactors is modified with multiple detection antibodies specific to each antigen by molecular tethers. Each antigen on the particles reacts with the detection antibodies anchored to the surface of the reactors. Magnetic force enhances the efficiency of bead encapsulation in the reactors, and subsequent physical compartmentalization of beads enhances the binding efficiency of the antigen-antibody reaction. The tethered beads show characteristic Brownian motion distinct from free diffusion or non-specific binding of the antigen-free beads. The color of the beads is attributed to target-identification, and the number of tethered beads is attributed to the concentration of the specific target. We measured two biomarkers (PSA and IL6) as model targets by multiplexed digital Ho-Non ELISA. Our method showed higher sensitivity compared to previous digital Ho-Non ELISA and could detect multiple targets simultaneously with the same performance as in single-plex detection. This new strategy has the potential to open a new avenue for next-generation multiplexed immunoassays in in vitro diagnostics.

Ultrasensitive Surface Plasmon Resonance Biosensor Using Blue Phosphorus-Graphene Architecture

This study theoretically proposed a novel surface plasmon resonance biosensor by incorporating emerging two dimensional material blue phosphorus and graphene layers with plasmonic gold film. The excellent performances employed for biosensing can be realized by accurately tuning the thickness of gold film and the number of blue phosphorus interlayer. Our proposed plasmonic biosensor architecture designed by phase modulation is much superior to angular modulation, providing 4 orders of magnitude sensitivity enhancement. In addition, the optimized stacked configuration is 42 nm Au film/2-layer blue phosphorus /4-layer graphene, which can produce the sharpest differential phase of 176.7661 degrees and darkest minimum reflectivity as low as 5.3787 × 10-6. For a tiny variation in local refractive index of 0.0012 RIU (RIU, refractive index unit) due to the binding interactions of aromatic biomolecules, our proposed biosensor can provide an ultrahigh detection sensitivity up to 1.4731 × 105 °/RIU, highly promising for performing ultrasensitive biosensing application.

Highly sensitive and label-free digital detection of whole cell E. coli with Interferometric Reflectance Imaging

Bacterial infectious diseases are a major threat to human health. Timely and sensitive pathogenic bacteria detection is crucial in bacterial contaminations identification and preventing the spread of infectious diseases. Due to limitations of conventional bacteria detection techniques there have been concerted research efforts towards developing new biosensors. Biosensors offering label-free, whole bacteria detection are highly desirable over those relying on label-based or pathogenic molecular components detection. The major advantage is eliminating the additional time and cost required for labeling or extracting the desired bacterial components. Here, we demonstrate rapid, sensitive and label-free Escherichia coli (E. coli) detection utilizing interferometric reflectance imaging enhancement allowing visualizing individual pathogens captured on the surface. Enabled by our ability to count individual bacteria on a large sensor surface, we demonstrate an extrapolated limit of detection of 2.2 CFU/ml from experimental data in buffer solution with no sample preparation. To the best of our knowledge, this level of sensitivity for whole E. coli detection is unprecedented in label-free biosensing. The specificity of our biosensor is validated by comparing the response to target bacteria E. coli and non-target bacteria S. aureus, K. pneumonia and P. aeruginosa. The biosensor's performance in tap water proves that its detection capability is unaffected by the sample complexity. Furthermore, our sensor platform provides high optical magnification imaging and thus validation of recorded detection events as the target bacteria based on morphological characterization. Therefore, our sensitive and label-free detection method offers new perspectives for direct bacterial detection in real matrices and clinical samples.

Ultrafast chemical imaging by widefield photothermal sensing of infrared absorption

Infrared (IR) imaging has become a viable tool for visualizing various chemical bonds in a specimen. The performance, however, is limited in terms of spatial resolution and imaging speed. Here, instead of measuring the loss of the IR beam, we use a pulsed visible light for high-throughput, widefield sensing of the transient photothermal effect induced by absorption of single mid-IR pulses. To extract these transient signals, we built a virtual lock-in camera synchronized to the visible probe and IR light pulses with precisely controlled delays, allowing submicrosecond temporal resolution determined by the probe pulse width. Our widefield photothermal sensing microscope enabled chemical imaging at a speed up to 1250 frames/s, with high spectral fidelity, while offering submicrometer spatial resolution. With the capability of imaging living cells and nanometer-scale polymer films, widefield photothermal microscopy opens a new way for high-throughput characterization of biological and material specimens.

Label-free detection of nanoparticles using depth scanning correlation interferometric microscopy

Single particle level visualization of biological nanoparticles such as viruses and exosomes is challenging due to their small size and low dielectric contrast. Fluorescence based methods are highly preferred, however they require labelling which may perturb the functionality of the particle of interest. On the other hand, wide-field interferometric microscopy can be used to detect sub-diffraction limited nanoparticles without using any labels. Here we demonstrate that utilization of defocused images enhances the visibility of nanoparticles in interferometric microscopy and thus improves the detectable size limit. With the proposed method termed as Depth Scanning Correlation (DSC) Interferometric Microscopy, we experimentally demonstrate the detection of sub-35nm dielectric particles without using any labels. Furthermore, we demonstrate direct detection of single exosomes. This label-free and high throughput nanoparticle detection technique can be used to sense and characterize biological particles over a range between a few tens to a few hundred nanometers, where conventional methods are insufficient.

Label-free tomography of living cellular nanoarchitecture using hyperspectral self-interference microscopy

Quantitative phase imaging (QPI) is the most ideal method for achieving long-term cellular tomography because it is label free and quantitative. However, for current QPI instruments, interference signals from different layers overlay with each other and impede nanoscale optical sectioning. Integrated incubators and improved configurations also require further investigation for QPI instruments. In this work, hyperspectral self-reflectance microscopy is proposed to achieve label-free tomography of living cellular nanoarchitecture. The optical description and tomography reconstruction algorithm were proposed so that the quantitative morphological structure of the entire living cell can be acquired with 89.2 nm axial resolution and 1.91 nm optical path difference sensitivity. A cell incubator was integrated to culture living cells for in situ measurement and expensive precise optical components were not needed. The proposed system can reveal native and dynamic cellular nanoscale structure, providing an alternative approach for long-term monitoring and quantitative analysis of living cells.

Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing

We review some emerging trends in transduction, connectivity and data analytics for Point-of-Care Testing (POCT) of infectious and non-communicable diseases. The patient need for POCT is described along with developments in portable diagnostics, specifically in respect of Lab-on-chip and microfluidic systems. We describe some novel electrochemical and photonic systems and the use of mobile phones in terms of hardware components and device connectivity for POCT. Developments in data analytics that are applicable for POCT are described with an overview of data structures and recent AI/Machine learning trends. The most important methodologies of machine learning, including deep learning methods, are summarised. The potential value of trends within POCT systems for clinical diagnostics within Lower Middle Income Countries (LMICs) and the Least Developed Countries (LDCs) are highlighted.

An Antenna Proximity Sensor for Mobile Terminals Using Reflection Coefficient

This paper presents a new antenna proximity sensor for mobile terminals based on the measured reflection coefficient using a bidirectional coupler which is positioned between the main antenna and the front-end module. Using the coupled forward and reverse long-term evolution signals by the bidirectional coupler, the reflection coefficient looking into the antenna was calculated in the base-band processor. The measured reflection coefficients showed clear differences for both the types of objects, and the distances between the terminal and the objects. The proposed antenna proximity sensor showed a recognition distance that was approximately 5 mm longer than that of a conventional capacitive proximity sensor.

Resolution enhancement of wide-field interferometric microscopy by coupled deep autoencoders

Wide-field interferometric microscopy is a highly sensitive, label-free, and low-cost biosensing imaging technique capable of visualizing individual biological nanoparticles such as viral pathogens and exosomes. However, further resolution enhancement is necessary to increase detection and classification accuracy of subdiffraction-limited nanoparticles. In this study, we propose a deep-learning approach, based on coupled deep autoencoders, to improve resolution of images of L-shaped nanostructures. During training, our method utilizes microscope image patches and their corresponding manual truth image patches in order to learn the transformation between them. Following training, the designed network reconstructs denoised and resolution-enhanced image patches for unseen input.

Label-Free and High-Throughput Detection of Biomolecular Interactions Using a Flatbed Scanner Biosensor

Fluorescence based microarray detection systems provide sensitive measurements; however, variation of probe immobilization and poor repeatability negatively affect the final readout, and thus quantification capability of these systems. Here, we demonstrate a label-free and high-throughput optical biosensor that can be utilized for calibration of fluorescence microarrays. The sensor employs a commercial flatbed scanner, and we demonstrate transformation of this low cost (∼100 USD) system into an Interferometric Reflectance Imaging Sensor through hardware and software modifications. Using this sensor, we report detection of DNA hybridization and DNA directed antibody immobilization on label-free microarrays with a noise floor of ∼30 pg/mm², and a scan speed of 5 s (50 s for 10 frames averaged) for a 2 mm × 2 mm area. This novel system may be used as a standalone label-free sensor especially in low-resource settings, as well as for quality control and calibration of microarrays in existing fluorescence-based DNA and protein detection platforms.

Nanoparticle classification in wide-field interferometric microscopy by supervised learning from model

Interference-enhanced wide-field nanoparticle imaging is a highly sensitive technique that has found numerous applications in labeled and label-free subdiffraction-limited pathogen detection. It also provides unique opportunities for nanoparticle classification upon detection. More specifically, the nanoparticle defocus images result in a particle-specific response that can be of great utility for nanoparticle classification, particularly based on type and size. In this work, we combine a model-based supervised learning algorithm with a wide-field common-path interferometric microscopy method to achieve accurate nanoparticle classification. We verify our classification schemes experimentally by blindly detecting gold and polystyrene nanospheres, and then classifying them in terms of type and size.