Continuous biomarker monitoring with single molecule resolution by measuring free particle motion

Towards continuous monitoring of TNF-α at picomolar concentrations using biosensing by particle motion

The ability to continuously monitor cytokines is desirable for fundamental research studies and healthcare applications. Cytokine release is characterized by picomolar circulating concentrations, short half-lives, and rapid peak times. Here, we describe the characteristics and feasibility of a particle-based biosensing technique for continuous monitoring of TNF-α at picomolar concentrations. The technique is based on the optical tracking of particle motion and uses an antibody sandwich configuration. Experimental results show how the analyte concentration influences the particle diffusivity and characteristic response time of the sensor, and how the sensitivity range depends on the antibody functionalization density. Furthermore, the data clarifies how antibodies supplemented in solution can shorten the characteristic response time. Finally, we demonstrate association rate-based sensing as a first step towards continuous monitoring of picomolar TNF-α concentrations, over a period of 2 h with delay times under 15 min. The insights from this research will enable the development of continuous monitoring sensors using high-affinity binders, providing the sensitivity and speed needed in applications like cytokine monitoring.

Continuous Monitoring Biosensing Mediated by Single-Molecule Plasmon-Enhanced Fluorescence in Complex Matrices

Continuous detection of critical markers directly at the point of interest and in undiluted biological fluids represents the next fundamental step in biosensing. The goal of realizing such a platform is utterly challenging because it requires a reversible biosensor that enables the tracking of pico- to nanomolar molecular concentrations over long time spans in a compact device. Here we describe a sensing method based on plasmon-enhanced fluorescence capable of single-molecule detection of unlabeled analyte by employing biofunctionalized gold nanoparticles. The very strong plasmon-enhanced fluorescence signals allow for single-molecule sensing in unaltered biological media, while the use of low-affinity interactions ensures the continuous tracking of increasing and decreasing analyte concentrations with picomolar sensitivity. We demonstrate the use of a sandwich assay for a DNA cancer marker with a limit of detection of picomolar and a time response of 10 min. The enhanced single-molecule signals will allow for miniaturization into a small and cheap platform with multiplexing capability for application in point-of-care diagnostics, monitoring of industrial processes, and safe keeping of the environment.

Fully Integrated Point-of-Care Platform for the Self-Monitoring of Phenylalanine in Finger-Prick Blood

Development of point-of-care platforms combining reliability and ease of use is a challenge for the evolution of sensing in healthcare technologies. Here, we report the development and testing of a fully integrated enzymatic colorimetric assay for the sensing of phenylalanine in blood samples from phenylketonuria patients. The platform works with a customized mobile app for data acquisition and visualization and comprises an electronic system and a disposable sensor. The sensing approach is based on specific enzymatic phenylalanine recognition, and the optical transduction method is based on in situ gold nanostructure formation. The phenylketonuria (PKU) smart sensor platform is conceived to perform self-monitoring on phenylalanine levels and real-time therapy tuning, thanks to the direct connection with clinicians. Validation of the technologies with a population of patients affected by PKU, together with the concurrent validation of the platform through centralized laboratories, has confirmed the good analytical performances in terms of sensitivity and specificity, robustness, and utility for phenylalanine sensing. The self-monitoring of phenylalanine for the daily identification of abnormal health conditions could facilitate rapid therapy tuning, improving the wellness of PKU patients.

Sandwich Immunosensor Based on Particle Motion: How Do Reactant Concentrations and Reaction Pathways Determine the Time-Dependent Response of the Sensor?

To control and optimize the speed of a molecular biosensor, it is crucial to quantify and understand the mechanisms that underlie the time-dependent response of the sensor. Here, we study how the kinetic properties of a particle-based sandwich immunosensor depend on underlying parameters, such as reactant concentrations and the size of the reaction chamber. The data of the measured sensor responses could be fitted with single-exponential curves, with characteristic response times that depend on the analyte concentration and the binder concentrations on the particle and substrate. By comparing characteristic response times at different incubation configurations, the data clarifies how two distinct reaction pathways play a role in the sandwich immunosensor, namely, analyte binding first to particles and thereafter to the substrate, and analyte binding first to the substrate and thereafter to a particle. For a concrete biosensor design, we found that the biosensor is dominated by the reaction pathway where analyte molecules bind first to the substrate and thereafter to a particle. Within this pathway, the binding of a particle to the substrate-bound analyte dominates the sensor response time. Thus, the probability of a particle interacting with the substrate was identified as the main direction to improve the speed of the biosensor while maintaining good sensitivity. We expect that the developed immunosensor and research methodology can be generally applied to understand the reaction mechanisms and optimize the kinetic properties of sandwich immunosensors with particle labels.

Real-time continuous monitoring of dynamic concentration profiles studied with biosensing by particle motion

Real-time monitoring-and-control of biological systems requires lab-on-a-chip sensors that are able to accurately measure concentration-time profiles with a well-defined time delay and accuracy using only small amounts of sampled fluid. Here, we study real-time continuous monitoring of dynamic concentration profiles in a microfluidic measurement chamber. Step functions and sinusoidal oscillations of concentrations were generated using two pumps and a herringbone mixer. Concentrations in the bulk of the measurement chamber were quantified using a solution with a dye and light absorbance measurements. Concentrations near the surface were measured using a reversible cortisol sensor based on particle motion. The experiments show how the total time delay of the real-time sensor has contributions from advection, diffusion, reaction kinetics at the surface and signal processing. The total time delay of the studied real-time cortisol sensor was ∼90 seconds for measuring 63% of the concentration change. Monitoring of sinusoidal cortisol concentration-time profiles showed that the sensor has a low-pass frequency response with a cutoff frequency of ∼4 mHz and a lag time of ∼60 seconds. The described experimental methodology paves the way for the development of monitoring-and-control in lab-on-a-chip systems and for further engineering of the analytical characteristics of real-time continuous biosensors.

Investigation of Limitations in the Detection of Antibody + Antigen Complexes Using the Silicon-on-Insulator Field-Effect Transistor Biosensor

The SOI-FET biosensor (silicon-on-insulator field-effect transistor) for virus detection is a promising device in the fields of medicine, virology, biotechnology, and the environment. However, the applications of modern biosensors face numerous problems and require improvement. Some of these problems can be attributed to sensor design, while others can be attributed to technological limitations. The aim of this work is to conduct a theoretical investigation of the "antibody + antigen" complex (AB + AG) detection processes of a SOI-FET biosensor, which may also solve some of the aforementioned problems. Our investigation concentrates on the analysis of the probability of AB + AG complex detection and evaluation. Poisson probability density distribution was used to estimate the probability of the adsorption of the target molecules on the biosensor's surface and, consequently, to obtain correct detection results. Many implicit and unexpected causes of error detection have been identified for AB + AG complexes using SOI-FET biosensors. We showed that accuracy and time of detection depend on the number of SOI-FET biosensors on a crystal.

High-Throughput Single-Molecule Sensors: How Can the Signals Be Analyzed in Real Time for Achieving Real-Time Continuous Biosensing?

Single-molecule sensors collect statistics of single-molecule interactions, and the resulting data can be used to determine concentrations of analyte molecules. The assays are generally end-point assays and are not designed for continuous biosensing. For continuous biosensing, a single-molecule sensor needs to be reversible, and the signals should be analyzed in real time in order to continuously report output signals, with a well-controlled time delay and measurement precision. Here, we describe a signal processing architecture for real-time continuous biosensing based on high-throughput single-molecule sensors. The key aspect of the architecture is the parallel computation of multiple measurement blocks that enables continuous measurements over an endless time span. Continuous biosensing is demonstrated for a single-molecule sensor with 10,000 individual particles that are tracked as a function of time. The continuous analysis includes particle identification, particle tracking, drift correction, and detection of the discrete timepoints where individual particles switch between bound and unbound states, yielding state transition statistics that relate to the analyte concentration in solution. The continuous real-time sensing and computation were studied for a reversible cortisol competitive immunosensor, showing how the precision and time delay of cortisol monitoring are controlled by the number of analyzed particles and the size of the measurement blocks. Finally, we discuss how the presented signal processing architecture can be applied to various single-molecule measurement methods, allowing these to be developed into continuous biosensors.

Real-Time Immunosensor for Small-Molecule Monitoring in Industrial Food Processes

Industrial food processes are monitored to ensure that food is being produced with good quality, yield, and productivity. For developing innovative real-time monitoring and control strategies, real-time sensors are needed that can continuously report chemical and biochemical data of the manufacturing process. Here, we describe a generalizable methodology to develop affinity-based biosensors for the continuous monitoring of small molecules in industrial food processes. Phage-display antibody fragments were developed for the measurement of small molecules, as exemplified with the measurement of glycoalkaloids (GAs) in potato fruit juice. The recombinant antibodies were selected for use in a competition-based biosensor with single-molecule resolution, called biosensing by particle motion, using assay architectures with free particles as well as tethered particles. The resulting sensor measures GAs in the micromolar range, is reversible, has a measurement response time below 5 min, and enables continuous monitoring of GAs in protein-rich solutions for more than 20 h with concentration measurement errors below 15%. The demonstrated biosensor gives the perspective to enable a variety of monitoring and control strategies based on continuous measurement of small molecules in industrial food processes.

Dynamic multispectral detection of bacteria with nanoplasmonic markers

Culture-based diagnosis of bacterial diseases is a time-consuming technique that can lead not only to antibiotic resistance or bacterial mutation but also to fast-spreading diseases. Such mutations contribute to the fast deterioration of the patient's health and in some cases the death depending on the complexity of the infection. There is great interest in developing widely available molecular-level diagnostics that provide accurate and rapid diagnosis at the individual level and that do not require sophisticated analysis or expensive equipment. Here, we present a promising analytical approach to detect the presence of pathogenic bacteria based on their dynamic properties enhanced with nanoplasmonic biomarkers. These markers have shown greater photostability and biocompatibility compared to fluorescent markers and quantum dots, and serve as both a selective marker and an amplifying agent in optical biomedical detection. We show that a simple dark-field side- illumination technique can provide sufficiently high-contrast dynamic images of individual plasmonic nanoparticles attached to Escherichia coli (E. coli) for multiplex biodetection. Combined with numerical dynamic filtering, our proposed system shows great potential for the deployment of portable commercial devices for rapid diagnostic tests available to physicians in emergency departments, clinics and public hospitals as point-of-care devices.

Single-Molecule Optical Biosensing: Recent Advances and Future Challenges

In recent years, the sensitivity and specificity of optical sensors has improved tremendously due to improvements in biochemical functionalization protocols and optical detection systems. As a result, single-molecule sensitivity has been reported in a range of biosensing assay formats. In this Perspective, we summarize optical sensors that achieve single-molecule sensitivity in direct label-free assays, sandwich assays, and competitive assays. We describe the advantages and disadvantages of single-molecule assays and summarize future challenges in the field including their optical miniaturization and integration, multimodal sensing capabilities, accessible time scales, and compatibility with real-life matrices such as biological fluids. We conclude by highlighting the possible application areas of optical single-molecule sensors that include not only healthcare but also the monitoring of the environment and industrial processes.