Single particle detection of protein molecules using dark-field microscopy to avoid signals from nonspecific adsorption

Detecting Attomolar Concentrations of Interleukin IL-17A via Pollen-Based Nanoplasmonic Biochips

Interleukins are involved in several diseases and cancers, and their detection and monitoring are of great interest. Their low abundance and short half-lives suggest the need to develop rapid, specific, and highly sensitive detection platforms, easily integrable in point-of-care (POC) systems. Among the other interleukins, interleukin IL-17A is associated with inflammations, neurodegenerative diseases, and cancers, and no biosensors have been previously reported for its detection. In this work, for the detection of IL-17A, a highly sensitive nanoplasmonic sensor based on natural nanostructures like pollen shells, covered by a gold film and a bio-receptor layer, is presented. Hybrid plasmonic modes are exploited to reach high sensitivity without using costly techniques to fabricate periodic nanostructures, such as electron beam lithography. A transparent amino-modified glass substrate is functionalized with carboxylic activated pollen via carbodiimide chemistry. Then, the pollen-based nanostructures are covered by a gold film and derivatized by an immuno-layer specific to IL-17A recognition. The developed IL-17A biosensor is monitored via a simple, small-sized, and low-cost experimental setup, demonstrating high selectivity, a fast response time of about five minutes, and sensitivity with a limit of detection in the ag/mL concentration range. The biosensor allows for the detection of IL-17A in complex solutions thanks to the possibility of high dilution, an advantageous aspect to POC systems.

Protein Corona of Nanoparticles: Isolation and Analysis

Nanoparticles entering biological systems or fluids inevitably adsorb biomolecules, such as protein, on their surfaces, forming a protein corona. Ensuing, the protein corona endows nanoparticles with a new biological identity and impacts the interaction between the nanoparticles and biological systems. Hence, the development of reliable techniques for protein corona isolation and analysis is key for understanding the biological behaviors of nanoparticles. First, this review systematically outlines the approach for isolating the protein corona, including centrifugation, magnetic separation, size exclusion chromatography, flow-field-flow fractionation, and other emerging methods. Next, we review the qualitative and quantitative characterization methods of the protein corona. Finally, we underscore the necessary steps to advance the efficiency and fidelity of protein corona isolation and characterization on nanoparticle surfaces. We anticipate that these insights into protein corona isolation and characterization methodologies will profoundly influence the development of technologies aimed at elucidating bionano interactions and the role of protein corona in various biomedical applications.

Simultaneous Detection of Biomarkers in Urine Using a Multicalibration Potentiometric Sensing Array Combined with a Portable Analyzer

Domestic monitoring devices make real-time and long-term health monitoring possible, allowing people to track their health status regularly. Uric acid (UA), creatinine, and urea in urine are three important biomarkers for various diseases, especially kidney diseases. This work proposed a 10-channel potentiometric sensing array containing a UA electrode group, a creatinine electrode group, a urea electrode group, a pH electrode group, and one pair of reference channels, which could be connected with a portable potentiometric analyzer, realizing the simultaneous detection of UA, creatinine, urea, and pH in urine. The prepared Pt/carbon nanotubes (CNTs)-uricase, creatinine deiminase, Au@urease, and polyaniline were employed as the sensing materials, showing responses to four targets with high sensitivity and selectivity. To improve the accuracy of domestic monitoring, a calibration channel was integrated into each electrode group to calibrate the basic potential of the sensing channels, and the influences of pH and temperature on the responses were investigated through the pH electrode group and an external temperature probe to calibrate the slope and intercept. With the preset of the deduced calibration parameters and computational formula for the four targets in the analyzer in Lab Mode, the concentrations of UA, creatinine, and urea and the pH of the human urine samples were directly displayed on the screen of the analyzer in Practical Mode. The agreement of these results with those obtained from commercial kits and pH meters reveals the high potential of these methods for developing domestic devices to facilitate health monitoring.

Ultra-stable and highly-bright CsPbBr3 perovskite/silica nanocomposites for miRNA detection based on digital single-nanoparticle counting

Single-nanoparticle counting (SNPC) based on fluorescent tag (FT) stands out for its capacity to achieve amplification-free and sensitive detection of biomarkers. The stability and luminescence of FT are important to the sensitivity and reliability of SPNC. In this work, we developed novel perovskite/silica nanocomposites by in-situ nanoconfined growth of CsPbBr3 nanocrystals inside mesoporous structure of silica nanoparticles. PbBr(OH) was formed in an alkaline-assisted reaction triggered by water on the surface of CsPbBr3 nanocrystals. The as-obtained nanocomposites, featuring dual protection from silica matrix and PbBr(OH), exhibited high absolute photoluminescence quantum yield (PLQY) of 86.5% and demonstrated outstanding PL stability confronting with water, heat, ultrasound and UV-irradiation, which is desired by SNPC-based biosensor. Thereafter, these nanocomposites were used to construct an operationally friendly SNPC assay for the amplification-free quantification of cancer-associated miRNA. Quantitative detection of miRNA could be accomplished by directly counting the number of nanocomposites using a flow cytometer in this assay. This strategy did not ask for multiple washing steps and demonstrated specific and sensitive detection of miRNA 21, which exhibited a dynamic range of 1-1000 pM and limit of detection of 79 amol. The employment of highly stable perovskite/silica nanocomposites improved the test reliability and stability of SNPC, revealing the vast potential of perovskites in biosensing.

Plasmonic Nanomaterials in Dark Field Sensing Systems

Plasma nanoparticles offer promise in data storage, biosensing, optical imaging, photoelectric integration, etc. This review highlights the local surface plasmon resonance (LSPR) excitation mechanism of plasmonic nanoprobes and its critical significance in the control of dark-field sensing, as well as three main sensing strategies based on plasmonic nanomaterial dielectric environment modification, electromagnetic coupling, and charge transfer. This review then describes the component materials of plasmonic nanoprobes based on gold, silver, and other noble metals, as well as their applications. According to this summary, researchers raised the LSPR performance of composite plasmonic nanomaterials by combining noble metals with other metals or oxides and using them in process analysis and quantitative detection.

Machine Learning Color Feature Analysis of a High Throughput Nanoparticle Conjugate Sensing Assay

Plasmonic nanoparticles are finding applications within the single molecule sensing field in a "dimer" format, where interaction of the target with hairpin DNA causes a decrease in the interparticle distance, leading to a localized surface plasmon resonance shift. While this shift may be detected using spectroscopy, achieving statistical relevance requires the measurement of thousands of nanoparticle dimers and the timescales required for spectroscopic analysis are incompatible with point-of-care devices. However, using dark-field imaging of the dimer structures, simultaneous digital analysis of the plasmonic resonance shift after target interaction of thousands of dimer structures may be achieved in minutes. The main challenge of this digital analysis on the single-molecule scale was the occurrence of false signals caused by non-specifically bound clusters of nanoparticles. This effect may be reduced by digitally separating dimers from other nanoconjugate types. Variation in image intensity was observed to have a discernible impact on the color analysis of the nanoconjugate constructs and thus the accuracy of the digital separation. Color spaces wherein intensity may be uncoupled from the color information (hue, saturation, and value (HSV) and luminance, a* vector, and b* vector (LAB) were contrasted to a color space which cannot uncouple intensity (RGB) to train a classifier algorithm. Each classifier algorithm was validated to determine which color space produced the most accurate digital separation of the nanoconjugate types. The LAB-based learning classifier demonstrated the highest accuracy for digitally separating nanoparticles. Using this classifier, nanoparticle conjugates were monitored for their plasmonic color shift after interaction with a synthetic RNA target, resulting in a platform with a highly accurate yes/no response with a true positive rate of 88% and a true negative rate of 100%. The sensor response of tested single stranded RNA (ssRNA) samples was well above control responses for target concentrations in the range of 10 aM-1 pM.

Single-Particle Optical Imaging for Ultrasensitive Bioanalysis

The quantitative detection of critical biomolecules and in particular low-abundance biomarkers in biofluids is crucial for early-stage diagnosis and management but remains a challenge largely owing to the insufficient sensitivity of existing ensemble-sensing methods. The single-particle imaging technique has emerged as an important tool to analyze ultralow-abundance biomolecules by engineering and exploiting the distinct physical and chemical property of individual luminescent particles. In this review, we focus and survey the latest advances in single-particle optical imaging (OSPI) for ultrasensitive bioanalysis pertaining to basic biological studies and clinical applications. We first introduce state-of-the-art OSPI techniques, including fluorescence, surface-enhanced Raman scattering, electrochemiluminescence, and dark-field scattering, with emphasis on the contributions of various metal and nonmetal nano-labels to the improvement of the signal-to-noise ratio. During the discussion of individual techniques, we also highlight their applications in spatial-temporal measurement of key biomarkers such as proteins, nucleic acids and extracellular vesicles with single-entity sensitivity. To that end, we discuss the current challenges and prospective trends of single-particle optical-imaging-based bioanalysis.

Extracellular Biomarkers of Inner Ear Disease and Their Potential for Point-of-Care Diagnostics

Rapid diagnostic testing has become a mainstay of patient care, using easily obtained samples such as blood or urine to facilitate sample analysis at the point-of-care. These tests rely on the detection of disease or organ-specific biomarkers that have been well characterized for a particular disorder. Currently, there is no rapid diagnostic test for hearing loss, which is one of the most prevalent sensory disorders in the world. In this review, potential biomarkers for inner ear-related disorders, their detection, and quantification in bodily fluids are described. The authors discuss lesion-specific changes in cell-free deoxyribonucleic acids (DNAs), micro-ribonucleic acids (microRNAs), proteins, and metabolites, in addition to recent biosensor advances that may facilitate rapid and precise detection of these molecules. Ultimately, these biomarkers may be used to provide accurate diagnostics regarding the site of damage in the inner ear, providing practical information for individualized therapy and assessment of treatment efficacy in the future.

Artificial intelligence-assisted enumeration of ultra-small viruses with dual dark-field plasmon resonance probes

Direct visual enumeration of viruses under dark-field microscope (DFM) using plasmon resonance probes (PRPs) is fast and convenient; however, it is greatly limited in the assay of real samples because of its inability to accurately identify false positives owing to non-specific adsorption. In this study, we propose an artificial intelligence (AI)-assisted DFM enumeration strategy for the accurate assay of Enterovirus A71 (an ultra-small human virus) using two PRPs; a 40 nm silver nanoparticle probe (SNP) that appears bright blue under DFM, and a 120 nm gold nanorod probe (GNP) that appears red under DFM. The capture chip was prepared by immobilizing the SNPs with antibodies on the glass to capture the target virus and to form dichromatic sandwich structures with the GNPs, followed by imaging under a dark field (DF). Subsequently, the DF images of the capture chip were subjected to a two-step screening: first, using image processing, and thereafter using the AI algorithm screening to eliminate false positive results and background noise. The results revealed that the data from the AI-assisted dual PRPs assay were highly consistent with those of quantitative PCR (qPCR), and that the sensitivity with a minimum detectable concentration of 3 copies/μL was 5 times higher than that of qPCR. The entire analysis was completed within 45 min. Therefore, our AI-assisted virus enumeration strategy with two DF PRPs holds great potential for ultra-sensitive and accurate quantification of viruses in real samples.

Zero-valent iron core-iron oxide shell nanoparticles coated with silica and gold with high saturation magnetization

A new type of gold-coated magnetic nanoparticle with strongly magnetic zero-valent iron core-iron oxide shell were synthesized. The small size of the magnetic cores and the zero-valent iron ensured superparamagnetic behaviour and high saturation magnetization of the overall nanoparticles. The nanoparticles showed stability against magnetic aggregation and good colloidal stability, which is important for many biomedical applications.

Impact of the Coverage of Aptamers on a Nanoparticle on the Binding Equilibrium and Kinetics between Aptamer and Protein

Knowledge of the interaction between aptamer and protein is integral to the design and development of aptamer-based biosensors. Nanoparticles functionalized with aptamers are commonly used in these kinds of sensors. As such, studies into how the number of aptamers on the nanoparticle surface influence both kinetics and thermodynamics of the binding interaction are required. In this study, aptamers specific for interferon gamma (IFN-γ) were immobilized on the surface of gold nanoparticles (AuNPs), and the effect of surface coverage of aptamer on the binding interaction with its target was investigated using fluorescence spectroscopy. The number of aptamers were adjusted from an average of 9.6 to 258 per particle. The binding isotherm between AuNPs-aptamer conjugate and protein was modeled with the Hill-Langmuir equation, and the determined equilibrium dissociation constant (K'_D) decreased 10-fold when increasing the coverage of aptamer. The kinetics of the reaction as a function of coverage of aptamer were also investigated, including the association rate constant (k_on) and the dissociation rate constant (k_off). The AuNPs-aptamer conjugate with 258 aptamers per particle had the highest k_on, while the k_off was similar for AuNPs-aptamer conjugates with different surface coverages. Therefore, the surface coverage of aptamers on AuNPs affects both the thermodynamics and the kinetics of the binding. The AuNPs-aptamer conjugate with the highest surface coverage is the most favorable in biosensors considering the limit of detection, sensitivity, and response time of the assay. These findings deepen our understanding of the interaction between aptamer and target protein on the particle surface, which is important to both improve the scientific design and increase the application of aptamer-nanoparticle based biosensor.