Characterization of Receptor Binding Affinity for Vascular Endothelial Growth Factor with Interferometric Imaging Sensor.

Wet Age-related macular degeneration (AMD) is the leading cause of vision loss in industrialized nations, often resulting in blindness. Biologics, therapeutic agents derived from biological sources, have been effective in AMD, albeit at a high cost. Due to the high cost of AMD treatment, it is critical to determine the binding affinity of biologics to ensure their efficacy and make quantitative comparisons between different drugs. This study evaluates the in vitro VEGF binding affinity of two drugs used for treating wet AMD, monoclonal antibody-based bevacizumab and fusion protein-based aflibercept, performing quantitative binding measurements on an Interferometric Reflectance Imaging Sensor (IRIS) system. Both biologics can inhibit Vascular Endothelial Growth Factor (VEGF). For comparison, the therapeutic molecules were immobilized on to the same support in a microarray format, and their real-time binding interactions with recombinant human VEGF (rhVEGF) were measured using an IRIS. The results indicated that aflibercept exhibited a higher binding affinity to VEGF than bevacizumab, consistent with previous studies using ELISA and SPR. The IRIS system's innovative and cost-effective features, such as silicon-based semiconductor chips for enhanced signal detection and multiplexed analysis capability, offer new prospects in sensor technologies. These attributes make IRISs a promising tool for future applications in the development of therapeutic agents, specifically biologics.

Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection.

Viral infections can pose a major threat to public health by causing serious illness, leading to pandemics, and burdening healthcare systems. The global spread of such infections causes disruptions to every aspect of life including business, education, and social life. Fast and accurate diagnosis of viral infections has significant implications for saving lives, preventing the spread of the diseases, and minimizing social and economic damages. Polymerase chain reaction (PCR)-based techniques are commonly used to detect viruses in the clinic. However, PCR has several drawbacks, as highlighted during the recent COVID-19 pandemic, such as long processing times and the requirement for sophisticated laboratory instruments. Therefore, there is an urgent need for fast and accurate techniques for virus detection. For this purpose, a variety of biosensor systems are being developed to provide rapid, sensitive, and high-throughput viral diagnostic platforms, enabling quick diagnosis and efficient control of the virus's spread. Optical devices, in particular, are of great interest due to their advantages such as high sensitivity and direct readout. The current review discusses solid-phase optical sensing techniques for virus detection, including fluorescence-based sensors, surface plasmon resonance (SPR), surface-enhanced Raman scattering (SERS), optical resonators, and interferometry-based platforms. Then, we focus on an interferometric biosensor developed by our group, the single-particle interferometric reflectance imaging sensor (SP-IRIS), which has the capability to visualize single nanoparticles, to demonstrate its application for digital virus detection.

Highly-Sensitive, Label-Free Detection of Microorganisms and Viruses via Interferometric Reflectance Imaging Sensor.

Pathogenic microorganisms and viruses can easily transfer from one host to another and cause disease in humans. The determination of these pathogens in a time- and cost-effective way is an extreme challenge for researchers. Rapid and label-free detection of pathogenic microorganisms and viruses is critical in ensuring rapid and appropriate treatment. Sensor technologies have shown considerable advancements in viral diagnostics, demonstrating their great potential for being fast and sensitive detection platforms. In this review, we present a summary of the use of an interferometric reflectance imaging sensor (IRIS) for the detection of microorganisms. We highlight low magnification modality of IRIS as an ensemble biomolecular mass measurement technique and high magnification modality for the digital detection of individual nanoparticles and viruses. We discuss the two different modalities of IRIS and their applications in the sensitive detection of microorganisms and viruses.

Attomolar sensitivity microRNA detection using real-time digital microarrays.

MicroRNAs (miRNAs) are a family of noncoding, functional RNAs. With recent developments in molecular biology, miRNA detection has attracted significant interest, as hundreds of miRNAs and their expression levels have shown to be linked to various diseases such as infections, cardiovascular disorders and cancers. A powerful and high throughput tool for nucleic acid detection is the DNA microarray technology. However, conventional methods do not meet the demands in sensitivity and specificity, presenting significant challenges for the adaptation of miRNA detection for diagnostic applications. In this study, we developed a highly sensitive and multiplexed digital microarray using plasmonic gold nanorods as labels. For proof of concept studies, we conducted experiments with two miRNAs, miRNA-451a (miR-451) and miRNA-223-3p (miR-223). We demonstrated improvements in sensitivity in comparison to traditional end-point assays that employ capture on solid phase support, by implementing real-time tracking of the target molecules on the sensor surface. Particle tracking overcomes the sensitivity limitations for detection of low-abundance biomarkers in the presence of low-affinity but high-abundance background molecules, where endpoint assays fall short. The absolute lowest measured concentration was 100 aM. The measured detection limit being well above the blank samples, we performed theoretical calculations for an extrapolated limit of detection (LOD). The dynamic tracking improved the extrapolated LODs from femtomolar range to [Formula: see text] 10 attomolar (less than 1300 copies in 0.2 ml of sample) for both miRNAs and the total incubation time was decreased from 5 h to 35 min.

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.

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.

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.