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Molecularly imprinted polymers for continual, real-time sensing of dopamine for health monitoring

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By Andy Tay

A growing interest in monitoring key physiological signals such as blood composition has motivated researchers to develop biosensors making use of optical, chemical, and electrochemical readouts for health diagnosis and predictions. An important chemical to measure in the body is dopamine. Dopamine is a key neurotransmitter governing functions such as memory, pleasure, and motivation, and is implicated in multiple neurodegenerative diseases such as Alzheimer’s and Parkinson’s.

Unfortunately, most biosensors are not suitable for continual monitoring of health conditions as they offer one-time or limited-time use. The challenge is a trade-off between sensitivity and reversibility. If the sensors are sensitive enough to measure the minute concentrations of dopamine in the body, they offer one-time or limited-time use. This limitation has hindered commercialization of biosensors for measuring dopamine and other biochemicals and is motivating research to enhance biosensor performance.

In a recent paper published in ACS Nano, a team of researchers led by Professor Nicholas Melosh and Dr. Nofar Mintz Hemed in the Department of Materials Science and Engineering at Stanford University describe their innovative, dopamine-binding MIP that has a limit of detection in the sub-nanomolar range and does not require as complex a fabrication process.  With continued development of the sensor, it may be integrated with wireless electronics and used for long term monitoring of physiology.

A ground breaking technique

Molecularly imprinted polymer (MIP) is a material that is fabricated by polymerizing a monomer around an analyte of interest to form a selective recognition site within the polymer network. The synthesis process is straightforward and is analogous to making a clay mold. The monomer (clay) and target analyte (mold) are first polymerized. After which, the target analyte, used as a template molecule, is removed, leaving behind cavities that preserve the structure of the target analyte and molecular interactions critical for target recognition.

diagram of synthesis process for molecule dopamine
Credit: Dr. Nofar Mintz Hemed, Stanford U.

To ensure good performance of the MIP sensor, such as to lower the limits of detection, there should be high binding affinity between the analyte and MIP. This often comes at a cost - a sensor may not be able to release the dopamine (or other targeted analyte) and be used again.  The analyte might have slow release kinetics from MIP, and the binding might even be irreversible. This would make MIP sensors poorly suited for long-term, repeated use, especially for applications such as wearables and implants. 

headshot of Dr. Nofar Mintz Hemed
Dr. Nofar Mintz Hemed, Research Scientist, T. H. Geballe Laboratory for Advanced Materials, Stanford U.

“The motivation behind developing this kind of sensor lies in the quest for continuous, real-time health monitoring with high precision. Molecularly imprinted polymers (MIPs), known for their selectivity and sensitivity, are ideal candidates for biosensors. However, the challenge is to make them reversible, allowing for multiple uses. Our goal was to create a small-form-factor sensor capable of monitoring health conditions within complex biological environments to introduce a new era of seamless, precise diagnostics and monitoring,” says Dr. Hemed.

Sensor creation

The proof-of-concept sensor developed by the researchers consisted of a platinum-iridium microwire coated with an electrically conductive polymer and MIP particles for binding to dopamine. When the analyte of interest, i.e., dopamine, binds to the MIP recognition cavities, it impedes ion motion from the MIP to the electrode surface and increases electrical impedance - the higher the concentration of dopamine, the higher the impedance reading.

The sensor was tested to work across a wide range of dopamine concentrations (1 nM to 1 mM). The sensor performed well with little, unwanted spontaneous release of dopamine, and the concentration of dopamine shares a linear relationship with impedance, which is important for calibration and data interpretation. When the sensor was subjected to 30 cycles of dopamine binding and release, its performance was not affected.

Moving towards reversible sensing

Dopamine can be released from the MIP by applying a positive potential, which generates electrostatic repulsion forces, releasing dopamine from the MIP matrix. The team wanted to better understand how a mild electrical potential could cause the sensor to release dopamine and potentially be used again. The group tested different hypotheses. First, they determined electrochemical oxidation and local Joule heating were unlikely. Next, they turned to their observation that dopamine release is linearly proportional to the voltage applied, which fits well with the theoretical understanding of the linearized Poisson-Boltzmann equation. From this, the researchers concluded that electrostatic repulsion of dopamine is the primary release mechanism.

Measuring cell secreted dopamine

The researchers tested their dopamine sensor using actual neurons. The neurons used were PC-12 cells, a model cell line for neurons, that were cultured in a petri dish and electrically stimulated to induce the release of dopamine. Stimulation could increase dopamine levels and impedance measured at first, but beyond the third stimulation, impedance did not rise further. Researchers believe that repeated stimulation depletes the dopamine pool, which is consistent with the binding specificity of their sensor to dopamine. This finding has implications for neuroscience because it shows that repeated stimulation of neurons may not continue to produce cellular responses due to the limited storage of dopamine in neurons.

Mapping dopamine concentrations in the brain

In their ongoing research project, the team is utilizing a bundle of hundreds of microwires, each intricately functionalized with MIPs designed specifically for dopamine detection. Next steps include implanting the dopamine sensors in brains of living animals.

“This groundbreaking technique, in collaboration with Prof. Jun Ding in the Department of Neurosurgery and Neurology at Stanford U., empowers us to neurochemically map larger areas of mice brains, resulting in significantly improved spatial resolution for our neuroscientific investigations. As we look ahead, we anticipate that these developments will not only deepen our understanding of neural phenomena, but also unlock different opportunities for exploration and applications within the field of neuroscience and its related domains,” says Dr. Hemed.


Source article: Mintz Hemed, N., Leal-Ortiz, S., Zhao, E. T., & Melosh, N. A. (2023). On-Demand, Reversible, Ultrasensitive Polymer Membrane Based on Molecular Imprinting Polymer. ACS Nano, 17(6), 5632–5643.

Dr. Nofar Mintz Hemed is a Physical Science Research Scientist with the Geballe Laboratory for Advanced Materials at Stanford U. Other Stanford co-authors include Sergio Leal-Ortiz, formally of the Department of Psychiatry and Behavioral Sciences; Eric T. Zhao, Ph.D. candidate in Chemical Engineering; Nicholas A. Melosh is Professor of Materials Science and Engineering at Stanford University.

This research was supported by the Wu Tsai Institute Big Ideas program at Stanford U. Nofar Mintz Hemed was supported by the Schmidt Futures program, the Israeli Council for Higher Education, and Ben-Gurion University Postdoctoral Award Program for Advancing Women in Science. Part of this work was performed at the Stanford Nanofabrication Facility (SNF), supported by the National Science Foundation under award ECCS-2026822. 

The eWEAR-TCCI awards for science writing is a project commissioned by the Wearable Electronics Initiative (eWEAR) at Stanford University and made possible by funding through eWEAR industrial affiliates program member Shanda Group and the Tianqiao and Chrissy Chen Institute (TCCI®).