Poskanzer, K. E. | bioRxiv Science

bioRxiv2019

Reversible silencing of endogenous receptors in intact brain tissue using two-photon pharmacology

The physiological activity of proteins is often studied with loss-of-function genetic approaches, but the corresponding phenotypes develop slowly and can be confounding. Photopharmacology allows direct, fast and reversible control of endogenous protein activity, with spatiotemporal resolution set by the illumination method. Here, we combine a photoswitchable allosteric modulator (alloswitch) and two-photon excitation (2PE) using pulsed near-infrared lasers to reversibly silence mGlu5 receptor activity in intact brain tissue. Endogenous receptors can be photoactivated in neurons and astrocytes with pharmacological selectivity and with an axial resolution between 5 and 10 m. Thus, two-photon pharmacology (2PP) using alloswitch allows investigating mGlu5-dependent processes in wild type animals, including synaptic formation and plasticity, and signaling pathways from intracellular organelles.

pharmacology and toxicology↗

bioRxiv2018

An event-based paradigm for analyzing fluorescent astrocyte activity uncovers novel single-cell and population-level physiology

Recent work examining astrocytic physiology centers on fluorescence imaging approaches, due to development of sensitive fluorescent indicators and observation of spatiotemporally complex calcium and glutamate activity. However, the field remains hindered in fully characterizing these dynamics, both within single cells and at the population-level, because of the insufficiency of current region-of-interest-based approaches to describe activity that is often spatially unfixed, size-varying, and propagative. Here, we present a paradigm-shifting analytical framework that releases astrocyte biologists from ROI-based tools. Astrocyte Quantitative Analysis (AQuA) software enables users to take an event-based approach to accurately capture and quantify the irregular activity observed in astrocyte imaging datasets. We apply AQuA to a range of ex vivo and in vivo imaging data, and uncover previously undescribed physiological phenomena in each. Since AQuA is data-driven and based on machine learning principles, it can be applied across model organisms, fluorescent indicators, experimental modes, and imaging resolutions and speeds, enabling researchers to elucidate fundamental astrocyte physiology.

neuroscience↗