New biosensors detect light deep inside the brain

Abstract

In recent years, the field of biosensors has seen significant advances in the development of fluorescent sensors, including quantum dots,¹ upconversion nanoparticles,² and fluorescent proteins,³ to monitor the generation of information in living systems. The fluorescence of these sensors can be observed by shining a laser at them. However, conventional fluorescent sensors are limited in their ability to image signals in deep tissues because most of the light is absorbed or scattered as it penetrates the tissue. To address this challenge, a team led by Jasanoff developed a novel sensor that converts light into a magnetic signal that is unaffected by absorption or scattering. This allows the response of the light detector to be visualized using magnetic resonance imaging (MRI; Figure 1).⁴ The development of this sensor has significant potential to improve our understanding of information processing in deep tissues.

To fabricate the photosensitive MRI probe, magnetic particles were encapsulated in light-responsive azobenzene-conjugated liposomes (called Light-LisNRs).⁵ By adjusting the composition and proportion of the lipid bilayer molecules, these liposome nanoparticles can switch from being permeable to being impenetrable, depending on the type of light exposure. This property allowed modulation of the MRI contrast of the Light-LisNRs and facilitated the optimization of the switchable longitudinal relaxation time (T1). Specifically, upon exposure to ultraviolet (UV) light, the Light-LisNRs became more permeable to water, resulting in a strong interaction between the magnetic particles and water and thereby producing strong MRI signals. Conversely, exposure to blue light caused the Light-LisNRs to become impermeable to water, resulting in the lack of a detectable MRI signal.

The optimized Light-LisNRs could potentially be used to map light distribution in live animals. When these nanoparticles were injected into the living rat brain, they effectively diffused through the brain by convection, as evidenced by changes in the magnetic resonance signal. The probes exhibited exceptional light sensitivity, which could be demonstrated by changes in magnetic relaxation under blue and UV irradiation. Relative to the initial baseline, the probes showed significant differences in the mean MRI signals in response to UV and blue light, and the temporal characteristics of the light response observed during repeated photoperiods were consistent.

The steady performance of Light-LisNRs in the rat brain suggests that they are suitable for the quantitative measurement of the light intensity distribution in tissues. In addition, the researchers used a hybrid model consisting of a beam spreading function combined with a homogeneous photon diffusion term to fit the experimental data and produced a quantitative map of the distribution of light emitted by the optical fiber implanted near the brain's striatum. These results highlight the potential of the optimized Light-LisNRs in mapping the distribution of light in living animals.

In summary, this study describes the design of a novel sensor and its application elucidating light propagation in optically opaque environments. The sensor exploits the photomodulation of liposomal permeability to enhance the contrast produced by contrast agent molecules, leading to improved visualization in MRI. The results of this work demonstrate the potential of Light-LisNRs as a versatile tool for photon detection and highlight opportunities for further optimization through adjustments to action spectra, absorption cross sections, and contrast agent packaging parameters. The sensing approach outlined here holds promise for the future development of MRI probes capable of detecting stimuli beyond light, such as neurochemicals or other molecular species in the brain. In addition, the sensor may serve as a valuable tool for monitoring patients undergoing light-based therapies, including photodynamic therapy, which uses lasers to ablate cancer cells.

Lei Luo: Conceptualization, Visualization, Writing - Original draft; Dandan Yang: Writing - Reviewing & Editing; Yu Yang: Conceptualization, Funding Acquisition, Writing - Reviewing & Editing.

The authors declare no conflicts of interest.