Pre-equilibrium biosensors as an approach towards rapid and continuous molecular measurements

Aptamer-Antibody Chimera Sensors for Sensitive, Rapid, and Reversible Molecular Detection in Complex Samples

The development of receptors suitable for the continuous detection of analytes in complex, interferent-rich samples remains challenging. Antibodies are highly sensitive but difficult to engineer in order to introduce signaling functionality, while aptamer switches are easy to construct but often yield only a modest target sensitivity. We present here a programmable antibody and DNA aptamer switch (PANDAS), which combines the desirable properties of both receptors by using a nucleic acid tether to link an analyte-specific antibody to an internal strand-displacement (ISD)-based aptamer switch that recognizes the same target through different epitopes. The antibody increases PANDAS analyte binding due to its high affinity, and the effective concentration between the two receptors further enhances two-epitope binding and fluorescent aptamer signaling. We developed a PANDAS sensor for the clotting protein thrombin and show that a tuned design achieves a greater than 300-fold enhanced sensitivity compared to that of using an aptamer alone. This design also exhibits reversible binding, enabling repeated measurements with a temporal resolution of ∼10 min, and retains excellent sensitivity even in interferent-rich samples. With future development, this PANDAS approach could enable the adaptation of existing protein-binding aptamers with modest affinity to sensors that deliver excellent sensitivity and minute-scale resolution in minimally prepared biological specimens.

Real-Time Spatiotemporal Measurement of Extracellular Signaling Molecules Using an Aptamer Switch-Conjugated Hydrogel Matrix

Cells rely on secreted signaling molecules to coordinate essential biological functions including development, metabolism, and immunity. Unfortunately, such signaling processes remain difficult to measure with sufficient chemical specificity and temporal resolution. To address this need, an aptamer-conjugated hydrogel matrix that enables continuous fluorescent measurement of specific secreted analytes - in two dimensions, in real-time is developed. As a proof of concept, real-time imaging of inter-cellular cyclic adenosine 3',5'-monophosphate (cAMP) signals in Dictyostelium discoideum amoeba cells is performed. A set of aptamer switches that generate a rapid and reversible change in fluorescence in response to cAMP signals is engineered. By combining multiple switches with different dynamic ranges, measure cAMP concentrations spanning three orders of magnitude in a single experiment can be measured. These sensors are embedded within a biocompatible hydrogel on which cells are cultured and their cAMP secretions can be imaged using fluorescent microscopy. Using this aptamer-hydrogel material system, the first direct measurements of oscillatory cAMP signaling that correlate closely with previous indirect measurements are achieved. Using different aptamer switches, this approach can be generalized for measuring other secreted molecules to directly visualize diverse extracellular signaling processes and the biological effects that they trigger in recipient cells.

Wearing the Lab: Advances and Challenges in Skin-Interfaced Systems for Continuous Biochemical Sensing

Continuous, on-demand, and, most importantly, contextual data regarding individual biomarker concentrations exemplify the holy grail for personalized health and performance monitoring. This is well-illustrated for continuous glucose monitoring, which has drastically improved outcomes and quality of life for diabetic patients over the past 2 decades. Recent advances in wearable biosensing technologies (biorecognition elements, transduction mechanisms, materials, and integration schemes) have begun to make monitoring of other clinically relevant analytes a reality via minimally invasive skin-interfaced devices. However, several challenges concerning sensitivity, specificity, calibration, sensor longevity, and overall device lifetime must be addressed before these systems can be made commercially viable. In this chapter, a logical framework for developing a wearable skin-interfaced device for a desired application is proposed with careful consideration of the feasibility of monitoring certain analytes in sweat and interstitial fluid and the current development of the tools available to do so. Specifically, we focus on recent advancements in the engineering of biorecognition elements, the development of more robust signal transduction mechanisms, and novel integration schemes that allow for continuous quantitative analysis. Furthermore, we highlight the most compelling and promising prospects in the field of wearable biosensing and the challenges that remain in translating these technologies into useful products for disease management and for optimizing human performance.

Reduction of Biosensor False Responses and Time Delay Using Dynamic Response and Theory-Guided Machine Learning

Here, we provide a new methodology for reducing false results and time delay of biosensors, which are barriers to industrial, healthcare, military, and consumer applications. We show that integrating machine learning with domain knowledge in biosensing can complement and improve the biosensor accuracy and speed relative to the performance achieved by traditional regression analysis of a standard curve based on the biosensor steady-state response. The methodology was validated by rapid and accurate quantification of microRNA across the nanomolar to femtomolar range using the dynamic response of cantilever biosensors. Theory-guided feature engineering improved the performance and efficiency of several classification models relative to the performance achieved using traditional feature engineering methods (TSFRESH). In addition to the entire dynamic response, the technique enabled rapid and accurate quantification of the target analyte concentration and false-positive and false-negative results using the initial transient response, thereby reducing the required data acquisition time (i.e., time delay). We show that model explainability can be achieved by combining theory-guided feature engineering and feature importance analysis. The performance of multiple classifiers using both TSFRESH- and theory-based features from the biosensor's initial transient response was similar to that achieved using the entire dynamic response with data augmentation. We also show that the methodology can guide design of experiments for high-performance biosensing applications, specifically, the selection of data acquisition parameters (e.g., time) based on potential application-dependent performance thresholds. This work provides an example of the opportunities for improving biosensor performance, such as reducing biosensor false results and time delay, using explainable machine learning models supervised by domain knowledge in biosensing.

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.

An antibody-based molecular switch for continuous small-molecule biosensing

We present a generalizable approach for designing biosensors that can continuously detect small-molecule biomarkers in real time and without sample preparation. This is achieved by converting existing antibodies into target-responsive "antibody-switches" that enable continuous optical biosensing. To engineer these switches, antibodies are linked to a molecular competitor through a DNA scaffold, such that competitive target binding induces scaffold switching and fluorescent signaling of changing target concentrations. As a demonstration, we designed antibody-switches that achieve rapid, sample preparation-free sensing of digoxigenin and cortisol in undiluted plasma. We showed that, by substituting the molecular competitor, we can further modulate the sensitivity of our cortisol switch to achieve detection at concentrations spanning 3.3 nanomolar to 3.3 millimolar. Last, we integrated this switch with a fiber optic sensor to achieve continuous sensing of cortisol in a buffer and blood with <5-min time resolution. We believe that this modular sensor design can enable continuous biosensor development for many biomarkers.

Cortisol Monitoring Devices toward Implementation for Clinically Relevant Biosensing In Vivo

Cortisol is a steroid hormone that regulates energy metabolism, stress reactions, and immune response. Cortisol is produced in the kidneys' adrenal cortex. Its levels in the circulatory system are regulated by the neuroendocrine system with a negative feedback loop of the hypothalamic-pituitary-adrenal axis (HPA-axis) following circadian rhythm. Conditions associated with HPA-axis disruption cause deteriorative effects on human life quality in numerous ways. Psychiatric, cardiovascular, and metabolic disorders as well as a variety of inflammatory processes accompanying age-related, orphan, and many other conditions are associated with altered cortisol secretion rates and inadequate responses. Laboratory measurements of cortisol are well-developed and based mainly on the enzyme linked immunosorbent assay (ELISA). There is a great demand for a continuous real-time cortisol sensor that is yet to be developed. Recent advances in approaches that will eventually culminate in such sensors have been summarized in several reviews. This review compares different platforms for direct cortisol measurements in biological fluids. The ways to achieve continuous cortisol measurements are discussed. A cortisol monitoring device will be essential for personified pharmacological correction of the HPA-axis toward normal cortisol levels through a 24-h cycle.