Genetically Encoded Fluorescent Indicators for Imaging Brain Chemistry

Abstract

Genetically encoded fluorescent indicators, combined with optical imaging, enable the detection of physiologically or behaviorally relevant neural activity with high spatiotemporal resolution. Recent developments in protein engineering and screening strategies have improved the dynamic range, kinetics, and spectral properties of genetically encoded fluorescence indicators of brain chemistry. Such indicators have detected neurotransmitter and calcium dynamics with high signal-to-noise ratio at multiple temporal and spatial scales in vitro and in vivo. This review summarizes the current trends in these genetically encoded fluorescent indicators of neurotransmitters and calcium, focusing on their key metrics and in vivo applications.

Encoding, transmission, decoding, and specificity of calcium signals in plants

“…A key property relating to signal encoding is the capacity of a calcium channel ( Eckford and Thomas, 2013 , 2018 ; Thomas and Eckford, 2016 ), which can reveal how much information can be captured within a given time. Recent progress in this area has led to mathematical models with the associated computational tools for answering such questions ( Farsad et al , 2016 ; Eckford and Thomas, 2018 ; Martins et al , 2019 ; Akyildiz et al , 2019 ; D. Bi et al , 2021 ). For instance, a framework for computing the channel capacity for a single ligand-activated channel has been derived ( Pagliara et al , 2014 ; Farsad et al , 2016 ; Thomas and Eckford, 2016 ; Ratti et al ., 2020 , 2021 ).…”

“…Upon calcium binding, conformational changes alter fluorescence intensity—due to CaM-induced modification of GFP ( Akerboom et al , 2012 ). Development of GCaMP1 in transgenic mouse models showed reduced background noise but unstable fluorescence ( X. Bi et al , 2021 ). Technological advances produced GCaMP2–3, GCaMP5–6, and jGCaMP7, exhibiting increased fluorescence, stability, signal-to-noise ratio, dynamic range, and responsiveness ( X. Bi et al , 2021 ).…”

“…How to achieve this is the goal of coding theory, which essentially devises algorithms for mapping the original messages onto signals whose distance between permissible code words increases (making the code words more robust to noise), often with built-in error-detection and error-correction features. Further background information can be found in Shannon (1948) and MacKay (2002) and for biological applications in D. Bi et al (2021) .…”

Letting the little light of mind shine: Advances and future directions in neurochemical detection

“…Single FP based indicators offer several appealing advantages for in vivo application, such as superior sensitivity, enhanced photostability, broader dynamic ranges and faster kinetics compared to FRET-based indicators. Tables comparing the properties of existing single FP and FRET neurotransmitter sensors have been generated in prior reviews (Bi et al, 2021;Leopold et al, 2019). They are relatively small, and are thus relatively easier to be targeted to sub-cellular locations, such as spines and axon terminals.…”

“…The first generation of GPCR-sensors were FRET-based and were mostly applied in cultured neurons to study receptor kinetics (Hoffmann et al, 2005;Jensen et al, 2009;Maier-Peuschel et al, 2010;Vilardaga et al, 2003). However, use of these sensors in vivo has been limited due to low dynamic range and sensitivity (Leopold et al, 2019;Bi et al, 2021). The iTango biosensor was developed to amplify the signal produced by ligand binding to induce gene expression via β-arrestin signaling, labeling cells that have undergone GPCR activation (Barnea et al, 2008;Smith et al, 2017).…”