Continuous Biosensor Based on Particle Motion: How Does the Concentration Measurement Precision Depend on Time Scale?

Continuous biosensors measure concentration-time profiles of biomolecular substances in order to allow for comparisons of measurement data over long periods of time. To make meaningful comparisons of time-dependent data, it is essential to understand how measurement imprecision depends on the time interval between two evaluation points, as the applicable imprecision determines the significance of measured concentration differences. Here, we define a set of measurement imprecisions that relate to different sources of variation and different time scales, ranging from minutes to weeks, and study these using statistical analyses of measurement data. The methodology is exemplified for Biosensing by Particle Motion (BPM), a continuous, affinity-based sensing technology with single-particle and single-molecule resolution. The studied BPM sensor measures specific small molecules (glycoalkaloids) in an industrial food matrix (potato fruit juice). Measurements were performed over several months at two different locations, on nearly 50 sensor cartridges with in total more than 1000 fluid injections. Statistical analyses of the measured signals and concentrations show that the relative residuals are normally distributed, allowing extraction and comparisons of the proposed imprecision parameters. The results indicate that sensor noise is the most important source of variation followed by sample pretreatment. Variations caused by fluidic transport, changes of the sensor during use (drift), and variations due to different sensor cartridges and cartridge replacements appear to be small. The imprecision due to sensor noise is recorded over few-minute time scales and is attributed to stochastic fluctuations of the single-molecule measurement principle, false-positive signals in the signal processing, and nonspecific interactions. The developed methodology elucidates both time-dependent and time-independent factors in the measurement imprecision, providing essential knowledge for interpreting concentration-time profiles as well as for further development of continuous biosensing technologies.

Oriented Antibody Coupling to an Antifouling Polymer Using Glycan Remodeling for Biosensing by Particle Motion.

Biosensors based on immobilized antibodies require molecular strategies that (i) couple the antibodies in a stable fashion while maintaining the conformation and functionality, (ii) give outward orientation of the paratope regions of the antibodies for good accessibility to analyte molecules in the biofluid, and (iii) surround the antibodies by antibiofouling molecules. Here, we demonstrate a method to achieve oriented coupling of antibodies to an antifouling poly(l-lysine)-grafted-poly(ethylene glycol) (PLL-g-PEG) substrate, using glycan remodeling to create antibody-DNA conjugates. The coupling, orientation, and functionality of the antibodies were studied using two analysis methods with single-molecule resolution, namely single-molecule localization microscopy and continuous biosensing by particle motion. The biosensing functionality of the glycan-remodeled antibodies was demonstrated in a sandwich immunosensor for procalcitonin. The results show that glycan-remodeled antibodies enable oriented immobilization and biosensing functionality with low nonspecific binding on antifouling polymer substrates.

Molecular Origins of Long-Term Changes in a Competitive Continuous Biosensor with Single-Molecule Resolution.

Biosensing by particle motion is a biosensing technology that relies on single-molecule interactions and enables the continuous monitoring of analytes from picomolar to micromolar concentration levels. However, during sensor operation, the signals are observed to change gradually. Here, we present a comprehensive methodology to elucidate the molecular origins of long-term changes in a particle motion sensor, focusing on a competitive sensor design under conditions without flow. Experiments were performed wherein only the particles or only the surfaces were aged in order to clarify how each individual component changes over time. Furthermore, distributions of particle motion patterns and switching activity were studied to reveal how particle populations change over timespans of several days. For a cortisol sensor with anticortisol antibodies on the particles and cortisol analogues on the sensing surface, the leading hypotheses for the long-term changes are (i) that the particles lose antibodies and develop nonspecific interactions and (ii) that analogue molecules dissociate from the sensing surface. The developed methodologies and the acquired insights pave a way for realizing sensors that can operate over long timespans.

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.

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.

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.

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.

Reversible Immunosensor for the Continuous Monitoring of Cortisol in Blood Plasma Sampled with Microdialysis.

Cortisol is a steroid hormone involved in a wide range of medical conditions. The level of the hormone fluctuates over time, but with traditional laboratory-based assays, such dynamics cannot be monitored in real time. Here, a reversible cortisol sensor is reported that allows continuous monitoring of cortisol in blood plasma using sampling by microdialysis. The sensor is based on measuring single-molecule binding and unbinding events of tethered particles. The particles are functionalized with antibodies and the substrate with cortisol-analogues, causing binding and unbinding events to occur between particles and substrate. The frequency of binding events is reduced when cortisol is present in the solution as it blocks the binding sites of the antibodies. The sensor responds to cortisol in the high nanomolar to low micromolar range and can monitor cortisol concentrations over multiple hours. Results are shown for cortisol monitoring in filtered and in microdialysis-sampled human blood plasma.

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

There is a need for sensing technologies that can continuously monitor concentration levels of critical biomolecules in applications such as patient care, fundamental biological research, biotechnology and food industry, as well as the environment. However, it is fundamentally difficult to develop measurement technologies that are not only sensitive and specific, but also allow monitoring over a broad concentration range and over long timespans. Here we describe a continuous biomolecular sensing methodology based on the free diffusion of biofunctionalized particles hovering over a sensor surface. The method records digital events due to single-molecule interactions and enables biomarker monitoring at picomolar to micromolar concentrations without consuming any reagents. We demonstrate the affinity-based sensing methodology for DNA-based sandwich and competition assays, and for an antibody-based cortisol assay. Additionally, the sensor can be dried, facilitating storage over weeks while maintaining its sensitivity. We foresee that this will enable the development of continuous monitoring sensors for applications in fundamental research, for studies on organs on a chip, for the monitoring of patients in critical care, and for the monitoring of industrial processes and bioreactors as well as ecological systems.

Real-Time Monitoring of Biomolecules: Dynamic Response Limits of Affinity-Based Sensors.

Sensors for monitoring biomolecular dynamics in biological systems and biotechnological processes in real time, need to accurately and precisely reconstruct concentration-time profiles. This requirement becomes challenging when transport processes and biochemical kinetics are important, as is typically the case for biomarkers at low concentrations. Here, we present a comprehensive methodology to study the concentration-time profiles generated by affinity-based sensors that continuously interact with a biological system of interest. Simulations are performed for sensors with diffusion-based sampling (e.g., a sensor patch on the skin) and advection-based sampling (e.g., a sensor connected to a catheter). The simulations clarify how transport processes and molecular binding kinetics result in concentration gradients and time delays in the sensor system. Using these simulations, measured and true concentration-time profiles of insulin were compared as a function of sensor design parameters. The results lead to guidelines on how biomolecular monitoring sensors can be designed for optimal bioanalytical performance in terms of concentration and time properties.

Sensing Methodology for the Rapid Monitoring of Biomolecules at Low Concentrations over Long Time Spans.

Studies on the dynamics of biological systems and biotechnological processes require measurement techniques that can reveal time dependencies of concentrations of specific biomolecules, preferably with small time delays, short time intervals between subsequent measurements, and the possibility to record over long time spans. For low-concentration biomolecules, these requirements are very challenging since low-concentration assays are typically slow and require new reagents in every assay. Here, we present a sensing methodology that enables rapid monitoring of picomolar and sub-picomolar concentrations in a reversible affinity-based assay, studied using simulations. We demonstrate that low-concentration biomolecules can be monitored with small time delays, short time intervals, and in principle over an endless time span.

Real-Time Detection of State Transitions in Stochastic Signals from Biological Systems.

Robust analysis of signals from stochastic biomolecular processes is critical for understanding the dynamics of biological systems. Measured signals typically show multiple states with heterogeneities and a wide range of state lifetimes. Here, we present an algorithm for robust detection of state transitions in experimental time traces where the properties of the underlying states are a priori unknown. The method implements a maximum-likelihood approach to fit models in neighboring windows of data points. Multiple windows are combined to achieve a high sensitivity for state transitions with a wide range of lifetimes. The proposed maximum-likelihood multiple-windows change point detection (MM-CPD) algorithm is computationally extremely efficient and enables real-time signal analysis. By analyzing both simulated and experimental data, we demonstrate that the algorithm provides accurate change point detection in time traces with multiple heterogeneous states that are a priori unknown. A high sensitivity for a wide range of state lifetimes is achieved.

Click-Coupling to Electrostatically Grafted Polymers Greatly Improves the Stability of a Continuous Monitoring Sensor with Single-Molecule Resolution.

Sensing technologies for the real-time monitoring of biomolecules will allow studies of dynamic changes in biological systems and the development of control strategies based on measured responses. Here, we describe a molecular architecture and coupling process that allow continuous measurements of low-concentration biomolecules over long durations in a sensing technology with single-molecule resolution. The sensor is based on measuring temporal changes of the motion of particles upon binding and unbinding of analyte molecules. The biofunctionalization involves covalent coupling by click chemistry to PLL-g-PEG bottlebrush polymers. The polymer is grafted to a surface by multivalent electrostatic interactions, while the poly(ethylene glycol) suppresses nonspecific binding of biomolecules. With this biofunctionalization strategy, we demonstrate the continuous monitoring of single-stranded DNA and a medically relevant small-molecule analyte (creatinine), in sandwich and competitive assays, in buffer and in filtered blood plasma, with picomolar, nanomolar, and micromolar analyte concentrations, and with continuous sensor operation over 10 h.

How Reactivity Variability of Biofunctionalized Particles Is Determined by Superpositional Heterogeneities.

The biofunctionalization of particles with specific targeting moieties forms the foundation for molecular recognition in biomedical applications such as targeted nanomedicine and particle-based biosensing. To achieve a high precision of targeting for nanomedicine and high precision of sensing for biosensing, it is important to understand the consequences of heterogeneities of particle properties. Here, we present a comprehensive methodology to study with experiments and simulations the collective consequences of particle heterogeneities on multiple length scales, called superpositional heterogeneities, in generating reactivity variability per particle. Single-molecule techniques are used to quantify stochastic, interparticle, and intraparticle variabilities, in order to show how these variabilities collectively contribute to reactivity variability per particle, and how the influence of each contributor changes as a function of the system parameters such as particle interaction area, the particle size, the targeting moiety density, and the number of particles. The results give insights into the consequences of superpositional heterogeneities for the reactivity variability in biomedical applications and give guidelines on how the precision can be optimized in the presence of multiple independent sources of variability.

Continuous Small-Molecule Monitoring with a Digital Single-Particle Switch.

The ability to continuously measure concentrations of small molecules is important for biomedical, environmental, and industrial monitoring. However, because of their low molecular mass, it is difficult to quantify concentrations of such molecules, particularly at low concentrations. Here, we describe a small-molecule sensor that is generalizable, sensitive, specific, reversible, and suited for continuous monitoring over long durations. The sensor consists of particles attached to a sensing surface via a double-stranded DNA tether. The particles transiently bind to the sensing surface via single-molecular affinity interactions, and the transient binding is optically detected as digital binding events via the Brownian motion of the particles. The rate of binding events decreases with increasing analyte concentration because analyte molecules inhibit binding of the tethered particle to the surface. The sensor enables continuous measurements of analyte concentrations because of the reversibility of the intermolecular bonds and digital read-out of particle motion. We show results for the monitoring of short single-stranded DNA sequences and creatinine, a small-molecule biomarker (113 Da) for kidney function, demonstrating a temporal resolution of a few minutes. The precision of the sensor is determined by the statistics of the digital switching events, which means that the precision is tunable by the number of particles and the measurement time.

Multiplexed Continuous Biosensing by Single-Molecule Encoded Nanoswitches.

Single-molecule techniques have become impactful in bioanalytical sciences, though the advantages for continuous biosensing are yet to be discovered. Here we present a multiplexed, continuous biosensing method, enabled by an analyte-sensitive, single-molecular nanoswitch with a particle as a reporter. The nanoswitch opens and closes under the influence of single target molecules. This reversible switching yields binary transitions between two highly reproducible states, enabling reliable quantification of the single-molecule kinetics. The multiplexing functionality is encoded per particle via the dissociation characteristics of the nanoswitch, while the target concentration is revealed by the association characteristics. We demonstrate by experiments and simulations the multiplexed, continuous monitoring of oligonucleotide targets, at picomolar concentrations in buffer and in filtered human blood plasma.

Conformation switching of single native proteins revealed by nanomechanical probing without a pulling force.

Protein conformational changes are essential to biological function, and the heterogeneous nature of the corresponding protein states provokes an interest to measure conformational changes at the single molecule level. Here we demonstrate that conformational changes in single native proteins can be revealed by non-covalent antibody-targeting of specific domains within the protein, using nanomechanical probing without an applied pulling force. The protein of interest was captured between a particle and a substrate and three properties were quantified: the twist amplitude related to an applied torque, torsional compliance related to rotational Brownian motion, and translational Brownian displacement. Calcium-dependent conformation switching was studied in native human cardiac troponin, a heterotrimer protein complex that regulates the contraction and relaxation of heart muscle cells and is also a key biomarker for diagnosing myocardial infarction. The data reveal a change in mechanical properties upon conformation switching from the non-saturated to the calcium-saturated state, which in cardiomyocytes gives myosin motor proteins access to actin filaments. A clear increase was observed in the molecular stiffness for the calcium-saturated protein conformation. Using libraries of monoclonal antibodies, the nanomechanical probing of conformation by antibody targeting opens avenues for characterizing single native protein complexes for research as well as for diagnostic applications.

Continuous biomarker monitoring by particle mobility sensing with single molecule resolution.

Healthcare is in demand of technologies for real-time sensing in order to continuously guard the state of patients. Here we present biomarker-monitoring based on the sensing of particle mobility, a concept wherein particles are coupled to a substrate via a flexible molecular tether, with both the particles and substrate provided with affinity molecules for effectuating specific and reversible interactions. Single-molecular binding and unbinding events modulate the Brownian particle motion and the state changes are recorded using optical scattering microscopy. The technology is demonstrated with DNA and protein as model biomarkers, in buffer and in blood plasma, showing sensitivity to picomolar and nanomolar concentrations. The sensing principle is direct and self-contained, without consuming or producing any reactants. With its basis in reversible interactions and single-molecule resolution, we envisage that the presented technology will enable biosensors for continuous biomarker monitoring with high sensitivity, specificity, and accuracy.

Nanoscale Interparticle Distance within Dimers in Solution Measured by Light Scattering.

We demonstrate a novel approach to quantify the interparticle distance in colloidal dimers using Mie scattering. The interparticle distance is varied in a controlled way by changing the ionic strength of the solution and the magnetic attraction between the particles. The measured scaling behavior is interpreted using an energy-distance model that includes the repulsive electrostatic and attractive magnetic interactions. The center-to-center distances of particles with a 525 nm radius can be determined with a root-mean-square accuracy of 12 nm. The data show that the center-to-center distance is larger by 83 nm compared to perfect spheres. The underlying distance offset can be attributed to repulsion by charged protrusions caused by particle surface roughness. The measurement method accurately quantifies interparticle distances that can be used to study cluster formation and colloid aggregation in complex systems, e.g., in biosensing applications.