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Voltage sensitive fluorescent dyes (VSDs) are important tools for probing signal transduction in neurons and other excitable cells. These sensors, rendered highly lipophilic to anchor the conjugated pi-wire molecular framework in the membrane, offer several favorable functional parameters including fast response kinetics and high sensitivity to membrane potential changes. The impact of VSDs has, however, been limited due to the lack of cell-specific targeting methods in brain tissue or living animals. We address this key challenge by introducing a non-genetic molecular platform for cell- and molecule-specific targeting of synthetic voltage sensitive dyes in the brain. We employ a dextran polymer particle to overcome the inherent lipophilicity of voltage sensitive dyes by dynamic encapsulation, and high-affinity ligands to target the construct to specific neuronal cells utilizing only native components of the neurotransmission machinery at physiological expression levels. Dichloropane, a monoamine transporter ligand, enables targeting of dense dopaminergic axons in the mouse striatum and sparse noradrenergic axons in the mouse cortex in acute brain slices. PFQX in conjunction with ligand-directed acyl imidazole chemistry enables covalent labeling of AMPA-type glutamate receptors in the same brain regions. Probe variants bearing either a classical electrochromic ANEP dye or state-of-the-art VoltageFluor-type dye respond to membrane potential changes in a similar manner to the parent dyes, as shown by whole-cell patch recording. We demonstrate the feasibility of optical voltage recording with our probes in brain tissue with one-photon and two-photon fluorescence microscopy and define the signal limits of optical voltage imaging with synthetic sensors under a low photon budget determined by the native expression levels of the target proteins. We envision that modularity of our platform will enable its application to a variety of molecular targets and sensors, as well as lipophilic drugs and signaling modulators. This work demonstrates the feasibility of a chemical targeting approach and expands the possibilities of cell-specific imaging and pharmacology.

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Abstract-We present a novel and relatively simple method for clustering pixels into homogeneous patches using a directed graph of edges between neighboring pixels. For a 2D image, the mean and variance of image intensity is computed within a circular region centered at each pixel. Each pixel stores its circle's mean and variance, and forms the node in a graph, with possible edges to its 4 immediate neighbors. If at least one of those neighbors has a lower variance than itself, a directed edge is formed, pointing to the neighbor with the lowest variance. Local minima in variance thus form the roots of disjoint trees, representing patches of relative homogeneity. The method works in n-dimensions and requires only a single parameter: the radius of the circular (spherical, or hyperspherical) regions used to compute variance around each pixel. Setting the intensity of all pixels within a given patch to the mean at its root pixel significantly reduces image noise while preserving anatomical structure, including location of boundaries. The patches may themselves be clustered using techniques that would be computationally too expensive if applied to the raw pixels. We demonstrate such clustering to identify fascicles in the median nerve in high-resolution 2D ultrasound images, as well as white matter hyperintensities in 3D magnetic resonance images.

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