“Letting the little light of mind shine: Advances and future
directions in neurochemical detection”
Nikki Tjahjono
1
,
Yihan Jin
2
,
Alice Hsu
3
,
Michael Roukes
4
,
Lin Tian
5,†
1
Biomedical Engineering Graduate Group; University of California, Davis; Davis, CA 95616, USA
2
Neuroscience Graduate Group; University of California, Davis; Davis, CA 95618, USA
3
Division of Biology and Biological Engineering; California Institute of Technology; Pasadena, CA
91125
4
Department of Physics; California Institute of Technology; Pasadena, CA 91125
5
Department of Biochemistry and Molecular Medicine, School of Medicine; University of
California, Davis; Davis, CA 95616
Abstract
Synaptic transmission via neurochemical release is the fundamental process that integrates and
relays encoded information in the brain to regulate physiological function, cognition, and emotion.
To unravel the biochemical, biophysical, and computational mechanisms of signal processing,
one needs to precisely measure the neurochemical release dynamics with molecular and cell-type
specificity and high resolution. Here we reviewed the development of analytical, electrochemical,
and fluorescence imaging approaches to detect neurotransmitter and neuromodulator release. We
discussed the advantages and practicality in implementation of each technology for ease-of-use,
flexibility for multimodal studies, and challenges for future optimization. We hope this review
will provide a versatile guide for tool engineering and applications for recording neurochemical
release.
Introduction
Neuronal communication in the mammalian nervous system is governed by local and global
changes in brain chemistry. Dysfunction in the complex spatiotemporal regulation of brain
chemistry is associated with neurological diseases (
Sarter et al., 2007
). A comprehensive
understanding of chemical dynamics in the diseased and healthy brain would greatly
facilitate the discovery of targeted treatments that are safe and effective.
The tools available to neurobiologists to monitor chemical dynamics in the brain should
have desired properties in terms of molecular specificity, sensitivity, and resolution to reveal
the emergent properties of release. (Fig. 1). For example, high chemical selectivity and
specificity is needed to identify and monitor specific chemical species within the brain’s
complex chemical environment. A tool that can monitor a wide variety of spatial scales is
†
Corresponding author: lintian@ucdavis.edu.
HHS Public Access
Author manuscript
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Published in final edited form as:
Neurosci Res
. 2022 June ; 179: 65–78. doi:10.1016/j.neures.2021.11.012.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
ideal to gain cellular and subcellular resolution on neurotransmitter release and spillover as
well as population dynamics. Also, these tools should have temporal resolution that allows
for the measurement of the diverse timescales at play in chemical transmission. Considering
the limitations of diffusion and geometry in the extracellular space (
Pál, 2018
), tools with an
appropriate dynamic range that permit a low limit of detection and do not saturate at high
concentrations would be necessary. Finally, these tools should be minimally invasive and
permit chronic recording in a variety of brain regions.
Technology breakthrough in analytical chemistry, protein engineering, and optics has
led to the development of a toolkit of sensors and probes for real-time monitoring of
neurochemical release dynamics. Microdialysis involves implanting a probe that contains
a semi-permeable membrane over which dialysate is collected from the brain interstitial
space and chemically analyzed. Electrochemical detection via fast-scan cyclic voltammetry
(FSCV) is another significant advance in neurochemical monitoring that allows for sensitive
detection of electroactive compounds with high temporal resolution. The development
of fluorescent genetically-encoded or non-genetically encoded indicators in the past few
decades have been an important advance for measuring brain chemistry. Highly optimized
genetically encoded indicators such as calcium indicators (i.e.GCaMP and X-CaMPs
family), small molecule dyes, synthetic nanosensors, and protein-based neuromodulator
sensors have been widely used as non-invasive methods for measuring neural activity.
1. Analytic methods
1.1 Basic Principles and Advantages of microdialysis
Microdialysis is one of the most widely used methods for monitoring neurochemicals
in
vivo
. The concept of using dialysis to collect analytes from interstitial fluid in the brain was
first reported as early as 1966, where Bito et al. inserted dialysis bags into the cortices of
dogs to collect amino acids present in brain interstitial fluid (
Bito et al., 1966
). Since this
initial study, the development of dialysis probes for the active perfusion and collection of
dialysate has laid the ground work for modern-day microdialysis (
Ungerstedt and Pycock,
1974
). Microdialysis probes consist of a shaft housing inlet and outlet tubes that deliver
fluids to and from a semi-permeable membrane (Fig. 2). The inlet tube is connected to a
perfusion system that delivers perfusion fluid of physiological solute concentrations through
the probe, commonly artificial cerebrospinal fluid (aCSF) or Ringer’s solution, matching
the electrolyte concentration of the brain interstitial fluid (
Chen et al., 1997
;
Zapata et
al., 2009
). The perfusion fluid then flows through a semi-permeable membrane of defined
molecular weight cut-off across which extracellular analytes can diffuse. The dialysate
then flows through the outlet tube where fractions are collected for
post hoc
chemical
analysis. Chemical analysis of the dialysate is often done by electrochemical detection,
mass spectrometry (MS), high-performance liquid chromatography (HPLC), or enzymatic
detection (
Jin et al., 2008
;
Zestos and Kennedy, 2017
).
A critical advantage of microdialysis over the other techniques discussed in this review is its
ability to monitor many different analytes simultaneously with picomolar range sensitivity
in
vivo
(
Ballini et al., 2008
;
Reinhoud et al., 2013
;
Yang et al., 2013
). The collected samples
can be analyzed using HPLC or mass spectrometry, and up to 70 different neurochemical
Tjahjono et al.
Page 2
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
compounds can be detected in a single dialysate sample (
Wong et al., 2016
). As a direct
sampling method, it permits the measurement of basal concentrations of brain analytes
in addition to dynamic changes in neurochemical levels. The collection of analytes by
microdialysis is governed by passive diffusion (Fick’s first law) of extracellular solutes
through the dialysis membrane. At standard flow rates (0.3 to 3uL/min), microdialysis
probes do not achieve absolute equilibrium with the interstitial fluid. Therefore, 100%
recovery of solutes from the brain is rarely achieved, and calibration is needed to relate
experimental dialysate concentrations to absolute extracellular concentrations. Many factors
contribute to a microdialysis system’s efficiency of recovery (or relative recovery) for a
particular analyte of interest, including flow rate, membrane surface area, analyte diffusion
coefficients, and diffusion (penetration) distance (
Bungay et al., 1990
;
Chefer et al., 2009
).
However, improving many of these dialysate collection parameters come with trade-offs
in spatiotemporal resolution and invasiveness (brief discussion below). Probe membranes
generally have molecular weight cutoffs of 20 to 60 kilodaltons (kDa) (
Nandi and Lunte,
2009
), making microdialysis a well-established method for monitoring virtually any low
molecular weight analyte, such as amino acids or biogenic monoamines in the extracellular
space, with high sensitivity.
Microdialysis permits multimodal studies combining neural activity recording and
manipulation with sample collection and neurochemical detection. Retrodialysis is used in
neuropharmacological studies, where adding a pharmacological compound into the perfusate
allows for simultaneous steady-state drug delivery to the tissue and sample collection
from the extracellular fluid (
Höcht et al., 2007
). A single probe can further be used for
microdialysis in conjunction with other neural recording techniques such as single cell
recording or EEG (
Ludvig et al., 1994
;
Obrenovitch et al., 1993
). Quiroz and colleagues
demonstrated the utility of a novel optogenetic-microdialysis probe to optically stimulate
and measure glutamate and dopamine release in the posteromedial nuclear accumbens shell
(
Quiroz et al., 2016
). Al-Hasani and colleagues have also developed an opto-dialysis probe
to measure optically evoked, picomolar release of dynorphin and enkephalins in the nucleus
accumbens shell in awake, freely moving mice (
Al-Hasani et al., 2018
). The work that has
been done to allow for multimodal recording of brain activity with these new probes have
further modernized the use of microdialysis to answer emerging questions in neuroscience.
1.2 Limitations and optimization
Despite its many advantages, traditional microdialysis methods suffer from low
temporal and spatial resolution. While the release and uptake kinetics of many major
neurotransmitters occur on the subsecond timescale, the temporal resolution of detecting
small molecule neuromodulators using microdialysis is limited to the seconds to minutes
timescale compared to the subsecond resolution of FSCV or fluorescence imaging. It is
therefore not surprising that microdialysis is not well-suited for detecting fast changes
in neurotransmitter concentration, such as during synaptic transmission. The temporal
resolution of microdialysis comes hand-in-hand with the chemical sensitivity of the system.
For analytes with low physiological concentrations, such as neuropeptides, concentrations
in dialysate drops markedly due to fractional recovery rates and the dilution of analyte in
perfusate that naturally occurs during microdialysis. Furthermore, large molecular weight
Tjahjono et al.
Page 3
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
analytes like neuropeptides yield lower relative recovery rates than those of smaller analytes
(
Plock and Kloft, 2005
). Increased sampling times are needed for detection of high
molecular weight neurochemicals, or those present in the picomolar to nanomolar range
of concentrations, lending to a reduction of temporal resolution to the minutes timescale.
Work has been done to improve the temporal resolution of neurotransmitter detection
using microdialysis by improving chemical sensitivity (
Reinhoud et al., 2013
;
Zhang et
al., 2012
). Cyclodextrins and antibodies to capture neuropeptides have been used to reduce
sampling time for neuropeptide detection (
Fletcher and Stenken, 2008
). Schmerberg and Li
used antibody-coated magnetic nanoparticles to reduce the time needed (and obviate the
need for preconcentration) to detect 31 neuropeptides after a 30 min sample collection in
the Jonah crab (
Schmerberg and Li, 2013
). Given the release kinetics of neuropeptides,
more work is needed to improve the temporal resolution of neuropeptide detection with
microdialysis. Sensitivity and temporal resolution for detecting neuropeptides suffers further
due to its nature to “stick” to probe and sample tube surfaces. Therefore, work to reduce the
adsorption of neuropeptides has been done to aid in improved recovery and thus sensitivity
(
Maes et al., 2014
;
Zhou et al., 2015
).
In addition, dialysate analysis can occur offline after all samples are collected, or online,
where dialysate is immediately directed for separation and analytical processing, allowing
for “real-time” readout of neurochemical levels. Online microdialysis minimizes the
possibility for sample loss or degradation after collection that may happen during offline
microdialysis (
Nandi and Lunte, 2009
). The temporal resolution of online microdialysis
is thus limited by the time needed not only for sample collection, but also chemical
analysis. In the past decade, much work has been done to improve the temporal
resolution of online microdialysis to sub-minute resolution (
Ngo et al., 2017
;
Schultz and
Kennedy, 2008
;
Song et al., 2012
;
Yang et al., 2013
). Traditional microdialysis results in
temporal averaging of concentration data due to the “binning” of dialysate into collected
fractions (
Ngernsutivorakul et al., 2018a
). A strategy developed to combat this collects
samples in nanoliter sized droplets using segmented-flow microfluidics before chemical
analysis, resulting in further improvements in temporal resolution from minutes to seconds
(
Ngernsutivorakul et al., 2018a
;
Song et al., 2012
).
As mentioned previously, the surface area of the probe membrane can affect the relative
recovery of the probe. Although having a larger surface area can lead to improved recovery
and thus potentially improved chemical sensitivity, increased probe size decreases spatial
resolution. Commercial microdialysis probes can range from 200 μm in diameter and 0.5 to
4 mm long for commercially available probes to smaller microfabricated push-pull probes
that are around 70 μm thick and 85 μm wide at the tip (
Kennedy, 2013
). Traditional
probe diameters of 200 to 400 μm do not lend themselves to cellular or subcellular
resolution. Additionally, a large probe size increases tissue damage leading to ischemia,
gliosis, and cell death at the insertion site (
Jaquins-Gerstl and Michael, 2009
). Recent
efforts to miniaturize microdialysis probes have resulted in improved spatial resolution
and reduced tissue damage (
Lee et al., 2016
;
Ngernsutivorakul et al., 2018a
,
2018b
).
Low flow rates also results in higher relative recovery and lower invasiveness by reduced
non-specific depletion of solutes; however, at a cost to temporal resolution (
Chefer et al.,
Tjahjono et al.
Page 4
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
2009
). As an alternative to microdialysis, membrane-free low-flow push-pull perfusion
used with liquid chromatography-tandem mass spectrometry has been developed to yield
higher relative recovery of proteins and other larger molecules with higher spatial resolution
(
Raman et al., 2020
). Further work is needed to improve the analyte recovery, as well
as spatial and temporal resolution achieved by microdialysis. However, its flexibility for
multiplexed chemical detection, ability to quantify basal concentrations, and adaptability to
neuropharmacological studies lends to its popularity as a widely used tool for neurochemical
detection.
2. Electrochemical detection with Fast Scan Cyclic Voltammetry
2.1 Basic Principles and Advantages
Electrochemical detection of neurochemicals with fast scan cyclic voltammetry (FSCV) is
an important technique for monitoring the dynamics of many important neurochemicals
with high temporal resolution and sensitivity. Voltammetry is an analytical method by
which current at an electrode is measured in response to variations in applied potential.
In cyclic voltammetry, a sweep up and down a range of potentials results in currents
produced by the reduction and oxidation of analytes adsorbed to the electrode surface (Fig.
3). Analyte identity is commonly determined by matching traces with the characteristic
voltammogram shape and redox potentials for a given analyte. Carbon fiber microelectrodes
are commonly used in FSCV due to their low cost and wide potential window. The ability
to easily microfabricate miniaturized carbon microelectrodes to reduce its spatial footprint
compared to commercial microdialysis probes is another benefit. Carbon fiber electrodes are
typically 5–10 μm in diameter and 50–200 μm long, thus permitting higher spatial resolution
compared to that of commercial microdialysis probes (
Kennedy, 2013
;
Rodeberg et al.,
2017
).
To achieve millisecond “real-time” temporal resolution, FSCV utilizes fast scanning rates on
the order of hundreds of volts per second. FSCV was first reported by
Millar and colleagues
in 1985
, where they used a scan rate of 300 V/s to monitor dopamine release and uptake in
the rat striatum (
Millar et al., 1985
). Since then, FSCV has been frequently used to measure
dopamine and other catecholamines in the brains of awake and behaving animals. FSCV
is able to monitor phasic dopamine signaling with high sensitivity at a limit of detection
in vitro
of 8 nM (
Heien et al., 2005
,
2004
). In conjunction with carbon-fiber microsensors,
FSCV has even been used to monitor dopamine release in human Parkinson’s patients
during a decision making behavioral task (
Kishida et al., 2016
). In addition to dopamine,
FSCV has also been applied to detect serotonin in model animals as well as in human
patients (
Hashemi et al., 2009
;
Heien et al., 2004
;
Moran et al., 2018
). FSCV can also
detect other brain analytes such as other catecholamines, dopamine metabolites, adenosine,
guanosine, histamine, and oxygen (
Cryan and Ross, 2019
;
Heien et al., 2004
;
Park et al.,
2018
;
Samaranayake et al., 2015
;
Wang and Venton, 2017
).
Recent advances in electrode engineering have also pushed improvements in temporal
resolution and sensitivity. For example, the use of carbon nanotube fiber microelectrodes
increased the temporal resolution from the approximately 100 ms of standard FSCV for
dopamine detection to 2 ms (
Zestos and Venton, 2018
). Taylor and colleagues observed a
Tjahjono et al.
Page 5
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
marked increase in dopamine sensitivity as a result of applying a PEDOT graphene oxide
coating on microfiber electrodes (
Taylor et al., 2017
). Carbon nanotube yarn microelectrodes
allows for better analyte adsorption, resulting in increased sensitivity (
Mendoza et al., 2020
;
Zestos and Venton, 2018
). Dopamine trapping with cavity carbon nanopipette electrodes
have allowed for signal amplification without large reductions in temporal resolution and
high spatial resolution (
Yang et al., 2019
).
Furthermore, FSCV permits multimodal studies where neurochemical monitoring can be
coupled with electrical stimulation and electrophysiological measurements. To determine the
relationship between local electrical activity and changes in neurochemical concentrations,
probes for simultaneous FSCV and electrophysiological recording have been developed
(
Hobbs et al., 2017
;
Owesson-White et al., 2016
). Advances in voltammogram analysis,
alternate waveform development (other than the traditional triangle waveform, discussion
below), and specialized probes have allowed for simultaneous, multiplexed detection of
different neurochemicals (
Hersey et al., 2021
;
Rafi and Zestos, 2021a
;
Wang and Venton,
2017
).
2.2 Challenges and optimizations
One of the major limitations of FSCV is poor molecular specificity. The identity of
a chemical is determined by the shape of the resultant oxidation curve and redox
peak locations. Applying the traditional triangle waveform for detecting dopamine yields
similar voltammograms for dopamine and norepinephrine, making it difficult to distinguish
between changes in the two analytes (
Heien et al., 2003
). There is also similarity in the
voltammograms of dopamine metabolites DOPAC to 3-MT and L-DOPA, as well as similar
redox potentials between serotonin and dopamine or its metabolite 5-hydoxyindole acetic
acid (5-HIAA) (
Hashemi et al., 2009
;
Heien et al., 2004
;
Moran et al., 2018
).
There are several strategies that have been developed to improve chemical selectivity.
Principal components regression is the main method for FSCV data analysis, which is
used to identify distinct features of voltammograms and compare them against training
sets of voltammograms of known analyte identity and concentration (
Puthongkham and
Venton, 2020
). Several groups have developed supervised machine learning approaches
to discriminate between changes in serotonin and dopamine concentrations from their
FSCV recordings (
Bang et al., 2020
;
Moran et al., 2018
). Electrode coatings to reduce the
accumulation of metabolites and redox side products can also increase chemical selectivity
by preventing analytes with similar redox profiles from adsorbing to the electrode surface.
For example, Nafion coated electrodes have been used to prevent fouling of carbon fiber
electrodes by 5-HIAA whose similarities to serotonin would reduce recording specificity
and fidelity (
Hashemi et al., 2009
). Developments in using alternative waveforms other
than the traditional triangle waveform has been an inexpensive and easily implemented
method to get around chemical selectivity issues (
Puthongkham and Venton, 2020
;
Rafi and
Zestos, 2021b
). For example, using a square wave or staircase waveform can increase the
sensitivity and selectivity for detecting dopamine to differentiate from other catecholamines
(
Park et al., 2018
). Notably, the development of the “sawhorse” waveform has been used to
increase the selectivity of adenosine detection, and has been optimized to be used to detect
Tjahjono et al.
Page 6
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
neuropeptides leu and met-enkephalins with FSCV (
Calhoun et al., 2019
;
Ross and Venton,
2014
).
Another limitation of FSCV is that it can only directly measure electroactive
neurochemicals, limiting the range of chemicals that can be probed. However,
functionalization of electrodes has allowed for improvements in the breadth of chemicals
that can be detected via FSCV. For example, carbon fiber microelectrodes have been
enzyme-modified to contain convert glucose or L-lactate into the electroactive species H
2
O
2
that can be detected by FSCV (
Forderhase et al., 2020
;
Lugo-Morales et al., 2013
;
Smith et
al., 2017
).
FSCV requires the implantation of a large probe that is prone to biofouling, which can
reduce the fidelity of chronic recordings in freely moving animals. An additional challenge
is that the faradaic current resulting from the redox of analytes on the electrode is extracted
upon subtraction of the background current, which can be problematic for chronic recording
in brain regions where fluctuations in the background charging current itself is likely
to occur. Several factors can result in fluctuations in the background current, including
pH changes in the local environment and biofouling of the electrode due to non-specific
adsorption of redox by-products and metabolites to the electrode. Inflammation at the site of
implantation can result in immune cell encapsulation of microsensors, effectively increasing
the impedance of the electrode and also causing shifts in background current (
Kozai et
al., 2015
;
Seaton et al., 2020
). These factors reduce the sensitivity of FSCV over repeated
electrode use (
Bennet et al., 2016
;
Kozai et al., 2015
;
Takmakov et al., 2010
).
Several groups have been working on developing alternative electrode coatings and materials
to curb electrode fouling, thus improving compatibility with chronic recording. Bennet and
colleagues developed a diamond-based electrode for chronic FSCV in deep brain stimulation
devices for implantation in patients (
Bennet et al., 2016
). Polymeric coatings for electrodes
have been engineered to prevent nonspecific molecule adsorption to electrodes (
T. Feng
et al., 2019
;
Liu et al., 2017
;
Puthongkham et al., 2019
). Advances in FSCV protocols
have also been pursued to improve electrode sensitivity in chronic recordings. Seaton
and colleagues developed a three electrode system to combat increases in impedance over
prolonged electrode usage (
Seaton et al., 2020
). Waveforms to prevent fouling and renew
the electrode surface between scans have been used to prevent by-product accumulation and
increase sensitivity (
Cooper and Venton, 2009
;
Takmakov et al., 2010
).
An alternative electrochemical method of detection that yields higher temporal resolution
than FSCV is constant-potential amperometry. Rather than applying voltage sweeps,
constant-potential amperometry holds an electrode at an oxidizing potential to measure
the resulting current, thereby providing real-time measurements. However, because of low
chemical resolution, it requires chemical separation methods and preprocessing to gain
chemical information, making it difficult to implement
in vivo
(
Bucher and Wightman,
2015
). Meanwhile, both FSCV and microdialysis enables detection of a vast array of
analytes with high chemical resolution. Microdialysis enables quantification of analytes
independent of their electrochemical activity but has limitations for detecting larger analytes.
While microdialysis has high chemical resolution and sensitivity towards many analytes, it
Tjahjono et al.
Page 7
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
has limited temporal resolution. In contrast, FSCV has high temporal resolution (<100 ms)
and sensitivity, but limited chemical selectively that many recent efforts have been made to
ameliorate. Advances in probe engineering have resulted in reduced FSCV probe sizes and
reductions in biofouling. Future work will only further improve the applicability of both
FSCV and microdialysis for sensitive chronic recording applications.
3. Fluorescence imaging of neurotransmitter and neuromodulator release:
Synaptic transmission is a complex event that can be better accessed optically. Fluorescence
imaging with advanced microscopy and an array of synthetic and genetically encoded
sensors have become broadly utilized technology in modern neuroscience due to their
accessibility, high molecular and cell-type specificity, and high spatiotemporal resolution.
Here, we focus on discussing fluorescence sensors that can permit direct measurement of
neurotransmitters and neuromodulators in real-time.
3.1 Non-genetically encoded neurochemical probes
Chemical dyes and nanomaterials are rich resources for developing new fluorescence probes.
Fluorescent false neurotransmitters (FFN) are synthetic fluorescent neurotransmitter analogs
that can trace the accumulation and release of dopamine, norepinephrine, and serotonin with
single synapse resolution (
Dunn et al., 2018
;
Henke et al., 2018
;
Post and Sulzer, 2021
).
FFNs undergo vesicular loading and release with native neurotransmitters by binding to
specific neurotransmitter transporters, such as VMAT2, DAT, NET, and SERT (
Gubernator
et al., 2009
;
Henke et al., 2018
). FFNs can be especially valuable for analysis of the
heterogeneity of presynaptic sites. For example, FFN200 is a VMAT2 substrate that can
specifically label dopaminergic neurons (apart from serotonergic neurons) in the striatum,
and can report silent dopaminergic vesicle clusters when used in conjunction with endocytic
marker FM1-43 (
Pereira et al., 2016
). By tuning the pH sensitivity of FFNs, changes
in fluorescence of these small molecules can report exocytosis and thus neurotransmitter
release (
Dunn et al., 2018
;
Rodriguez et al., 2013
). FFNs are well suited for imaging
neurotransmitter dynamics at the scale of individual synapses in dissociated neuronal culture
and in brain slice, and have been used to image cortical norepinephrine dynamics
in vivo
(
Dunn et al., 2018
). It can also be used for high-throughput pharmacology bioassays to
identify new inhibitors for monoamine transporters (
Bernstein et al., 2012
).
Near infrared sensors based on carbon nanotubes are engineered by sonicating single wall
carbon nanotubes with oligonucleotides and can be evolved to specifically bind to analytes
of interest (
Jeong et al., 2019
;
Yang et al., 2021
). Near-IR catecholamine sensors (nIRCatS)
detect local dopamine release in striatal slices elicited by electrical stimuli (
Beyene et al.,
2019
;
Yang et al., 2021
). Near-infrared 5-HT probes (nIRHT) can detect exogenous 5-HT
in acute brain slices (
Jeong et al., 2019
). The near-IR spectrum provides flexibility for
simultaneous imaging with other dyes and sensors, as well as optogenetic tools in the visible
spectrum. Additionally, the nanosensors are compatible with both genetically tractable and
intractable organisms, making them easy to use and potentially compatible for human
applications. Some other advantages nIRCats offer over genetically-encoded fluorescent
indicators are they: 1) do not need viruses to express the sensor, 2) do not need time for
Tjahjono et al.
Page 8
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
cells to express the sensors, and 3) do not photobleach and are photo-stable (
O’Connell et
al., 2002
;
Yang et al., 2021
). However, these sensors are not able to distinguish between
dopamine and norepinephrine, and thus further optimization is needed to improve chemical
specificity. In addition, application
in vivo
has yet to be seen.
Though chemical probes allow for sensitive detection of synaptic neurochemical dynamics
and a broad range of potential applications in model animals and potential compatibility in
humans, they do not offer information about cell-type specificity and may thus require
post
hoc
immunostaining or parallel utilization of genetic labeling tools for increased specificity
(
Pereira et al., 2016
).
3.2 Genetically Encoded Fluorescent Indicators for Neurotransmitters and
Neuromodulators
In the past decade, the development and refinement of fluorescent genetically encoded
calcium and voltage indicators (
Abdelfattah et al., 2019
;
Baird et al., 1999
;
Carandini et
al., 2015
;
Chen et al., 2013
;
Dana et al., 2019
;
Miyawaki et al., 1997
;
Nakai et al., 2001
;
Piatkevich et al., 2019
;
Tian et al., 2009
;
Villette et al., 2019
;
Yang et al., 2018
;
Zhao
et al., 2011
) has advanced capabilities in sensor design, optimization, characterization,
and validation, as well as improved our understanding of how to apply these tools in
behaving animals. This know-how paved the way for the development of genetically
encoded indicators (GEIs) for neurotransmitters, neuromodulators, and neuropeptides (Table
1).
The basic design principle of fluorescent biosensors for neurochemical detection is to
couple ligand-induced conformational changes of a ligand binding domain to the fluorescent
intensity changes of the reporter domain, thus providing an optical readout of chemical
transients. The reporter element typically employs either a single fluorescent protein (FP)
or a FRET pair of donor and acceptor FPs. Upon ligand binding, conformational change in
the recognition element leads to changes in fluorescence intensity of a single FP or FRET
between two FPs. Genetically encoded indicators for glutamate, the predominant excitatory
neurotransmitter in the brain, are one of the earliest developed for imaging in the brain.
FLIPE is the first engineered glutamate sensor with an affinity (measured by K
d
) of 600 nM,
by fusing FRET pairs with bacterial glutamate periplasmic binding protein (PBP) YbeJ/GltI
(
Okumoto et al., 2005
). GltI was chosen as the molecular recognition domain of the sensor
for its “venus flytrap”-like conformational change in response to glutamate binding, where
two lobes of the protein come together. FRET pairs ECFP and Venus (YFP) were attached
on opposing sides of a lobe of GltI so that upon glutamate binding, GltI closure causes their
movement away from each other and a reduction in FRET efficiency (Fig. 4A). In 2008, the
FRET sensor superGluSnFr improved on existing FRET glutamate sensors with increased
response magnitude (changes in FRET efficiency upon glutamate binding) and operation at
a more physiological range of glutamate concentrations in neuronal culture (
Hires et al.,
2008a
).
Single FP sensors, utilizing the development of circularly permuted FPs (like those used in
the widely used calcium indicators GCaMP), offers many advantages compared to FRET
sensors. Thus far, the applicability of FRET sensors for imaging neurotransmitter release
Tjahjono et al.
Page 9
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
is limited to use in brain slice or in dissociated neuronal culture, primarily due to the
limited dynamic range of these ratiometric measurements (
Hires et al., 2008a
;
Okumoto
et al., 2005
). 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
preserved spectrum bandwidth of single-FP indicators can allow for multiplexed imaging or
use alongside optogenetic effectors such as channelrhodopsin. iGluSnFr is the first single
FP glutamate sensor, consisting of circularly permuted GFP (cpGFP) fused to YbeJ/GltI,
the PBP utilized in early FRET glutamate indicators (Fig. 4B) (
Marvin et al., 2013
).
iGluSnFr was engineered by rational design to determine the insertion location of cpGFP
into GltI near the hinge region of the protein that facilitates domain opening and closing
(venus flytrap-like motion). Marvin et al. also performed site-saturated mutagenesis and
high-throughput screening of the linker regions that connect cpGFP to GltI to achieve a
high dynamic range sensor that they validated in neuronal culture, brain slice, and
in vivo
in fish, mice, and
C. elegans
(
Marvin et al., 2013
). Recent engineering efforts have led
to the improvement of the brightness and affinity of iGluSnFr and expand available color
variants (SF-iGluSnFr) (
Marvin et al., 2018
). Helassa and colleagues have also pursued
improvements to the affinity and kinetics (iGlu
f
, iGlu
u
) of iGluSnFr to enable imaging of
high-frequency release in hippocampal slice (
Helassa et al., 2018
).
Microbial PBPs form a large protein superfamily that bind numerous classes of small
molecules and peptides. Ligand binding in PBPs induces a large venus flytrap-like
conformational change, which is highly conserved. These unique features have been
used to develop a toolkit of highly sensitive sensors for other neurochemicals, including
GABA(iGABASnFr), ATP (iATPSnFR), acetylcholine (iAchSnFR) and nicotine (iNicSnFr)
(
Borden et al., 2020
;
Lobas et al., 2019
;
Marvin et al., 2019
;
Shivange et al., 2019
).
However, there are several analytes for which bacterial PBPs do not exist. We recently
developed the PBP-based sensor iSeroSnFr for serotonin, which does not naturally have
any known associated PBPs. We used machine learning guided evolution of an existing
PBP-based sensor, iAchSnFr (
Borden et al., 2020
), to redesign its binding pocket to report
serotonin release at physiological concentrations (
Unger et al., 2020
). We utilized iSeroSnFr
to detect serotonin in cultured neurons, brain slice, and for detecting behaviorally triggered
serotonin release in mice using fiber photometry (
Unger et al., 2020
).
As an alternative to PBP-based sensors, recently, sensors for monoamine neurotransmitters
have been developed by fusing eukaryotic G-protein-coupled receptors (GPCRs) with
fluorescent reporters. As the endogenous receptors of neurochemicals, GPCRs have
the evolved affinity and specificity relevant to binding of neurochemicals released at
physiological ranges. 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
Tjahjono et al.
Page 10
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
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
). However, the
poor temporal resolution of an hour or more for signal amplification and expression and
the irreversible nature of this system necessitated GEIs that can capture the fast dynamics
of neurochemical release. To overcome these barriers, single-FP based GPCR sensors have
been recently developed.
GPCRs have seven transmembrane (TM) alpha helices, where the largest conformational
change upon activation is thought to occur for TM domains 5 to 7 (
Latorraca et al., 2017
).
Thus far, cpFPs have been inserted in the intracellular loop 3 (IL3) domain of GPCRs,
which bridges TM5 and TM6, to detect this conformational change upon ligand binding
(Fig. 4C). Using this versatile strategy, our lab developed the Light sensor family, consisting
of dopamine, norepinephrine and serotonin sensors by inserting cpGFP into human GPCRs,
including DRD1, 2, or 4,
β
2AR and 5-HT2A receptors (
Dong et al., 2021
;
Patriarchi et al.,
2018
). Through linker screening by site-directed mutagenesis we engineered high affinity,
fast indicators that were amenable to recording dopamine release in several brain regions
in
vivo
and
ex vivo
(
Patriarchi et al., 2018
). We also engineered other red-shifted color variants
of dLight1 for multiplexed neurochemical detection (
Patriarchi et al., 2020
). Parallel work
in dopamine GEI engineering has been carried out with the engineering of the GRAB-DA
sensors using DRD2 as the scaffold (
Sun et al., 2020
,
2018
). Jing and colleagues developed
the GACh family of sensors by inserting cpGFP in a chimeric muscarinic acetylcholine
receptor (M
3
R) with an IL3 domain derived from
β
2AR (
Jing et al., 2018
). Similar to the
Light series, GRAB sensors have also been expanded to norepinephrine, serotonin, and
adenosine, and implemented in culture, slice, and in behaving rodents (
Feng et al., 2019
;
Wan et al., 2021
;
Wu et al., 2020
).
Challenges for Neurochemical Monitoring with genetically encoded indicators
3.2.1 Mesoscopic and microscopic view of neurotransmitter and
neuromodulator release—
A major advantage of neurochemical monitoring using
genetically-encoded sensors is that it permits long-term recording where the same cells
can be revisited and imaged over the timescale of days to months (
Chen et al., 2012
).
The transgene that encodes the fluorescent indicator is typically delivered via targeted or
systemic injection of adeno-associated virus (AAV) and its derivatives (e.g. AAV-PHP.eB),
followed by a few weeks of expression before imaging. In addition, genetic tools like Cre/
loxP, Flp/FRT, and the Gal4/UAS system can be combined with sensors to permit cell-type
specific expression. Subcellular targeting of GEIs allow for specific localization of sensors
to cellular compartments of interest, such as the soma, cytosol, or the pre or post-synapse.
For example, we have tethered iSeroSnFr to full length neuroligin for post-synaptic targeting
and synaptic release measurements of serotonin (
Unger et al., 2020
). Using one-photon and
multiphoton (2p and 3p) imaging and the miniaturization of these microscopes, cells can be
imaged through a thinned skull or cranial window in head-fixed or freely-moving animals
(
Zong et al., 2017
). However, due to light scattering in deeper brain regions, a maximum
of about >1 mm from the surface of the brain can be imaged with multiphoton microscopy.
Fluorescence microendoscopy and fiber photometry, on the other hand, are compatible with
protein-based sensors and can be used to record release in deeper brain regions.
Tjahjono et al.
Page 11
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
The spatial resolution is determined, in part, by the resolution of the optical system
utilized for imaging. However, precise localization of analyte concentration changes
below the theoretical resolution of the optical system is possible. Dürst and colleagues
used fast spiral scanning of iGluSnFr to localize points of presynaptic glutamate release
(vesicle fusion) within single boutons in slice cultures (
Dürst et al., 2019
). Farsi and
colleagues demonstrated that single quantal vesicular release can be detected by iGluSnFr in
hippocampal boutons in neuronal culture (
Farsi et al., 2021
). In combination with other tools
such as cell type-specific optogenetic or chemogenetic actuators, these sensors allow us to
gain an understanding of circuit-specific mechanisms with unprecedented spatial resolution,
which is difficult to achieve with microdialysis or FSCV.
Besides recording local release, it is also critical to understand large-scale neuronal activity
in disease or behavior. Widefield imaging of glutamate dynamics through an intact skull
with iGluSnFr has been used to observe meso-scale cortical glutamate dynamics in rodents
(
Hefendehl et al., 2016
;
Xie et al., 2016
). For example, McGirr and colleagues performed
longitudinal widefield iGluSnFr imaging in mice to elucidate the effects of ketamine
in a social defeat behavioral paradigm (
McGirr et al., 2017
). Fast volumetric calcium
imaging with cellular resolution has become possible through innovations in multiphoton
microscopy, setting the stage for future potential applications for imaging neurotransmitter
GEIs. For example, Weisenburger et al. recorded the activity of over 10,000 GCaMP
expressing neurons with their volumetric hybrid 2p-3p calcium imaging setup (
Weisenburger
et al., 2019
). Optoacoustic imaging has allowed for fast whole-brain imaging of calcium
dynamics in GCaMP expressing mice with moderate 150 μm resolution (
Gottschalk et al.,
2019
). Creating brighter sensors with new spectral variants may aid in the translation of
these new high resolution volumetric calcium imaging modalities to neurotransmitter or
neuromodulator sensors in the near future. In contrast, microdialysis and FSCV are single
point recording techniques that do not permit ensemble recordings with high resolution or
specificity.
3.2.2 Optimizing the intrinsic properties of sensors—
Synaptic release and uptake
occur on the millisecond timescale whereas spillover and volume transmission occur at
longer time scales, necessitating sensors with kinetics at various physiological time scales.
Most single-FP GEIs for imaging neuromodulators have subsecond on- and off-rates
(
Sabatini and Tian, 2020
). As previously mentioned, ultrafast variants of iGluSnFr (
τ
on
of 460
μ
s,
τ
off
2.6 ms
μ
s for iGlu
u
) have been engineered to image the fast dynamics of
high frequency (100 Hz) glutamate release in organotypic slice culture (
Helassa et al., 2018
).
A limitation to further improving sensor kinetics is the nature of fluorescence generation
using cpFPs after ligand binding. Reconstitution of the fluorescent complex (may it be two
parts of a PBP sensor or bringing together GPCR strands) and subsequent conformational
change is first needed before fluorescence modulation (
Helassa et al., 2018
). The temporal
resolution for GEIs is thus limited by the timescale of ligand binding domain rearrangement
and transduction to the fluorescent reporter.
Although using natural receptors should allow for high sensitivity detection, to view single
quantal release with high SNR and lower the limit of detection of GEIs, further engineering
is often needed. The sensitivity of these sensors is determined by the dissociation rate
Tjahjono et al.
Page 12
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
and dynamic range, and can be altered by basal ligand concentrations. High SNR sensors,
however, may come at a cost to temporal resolution, as sensors with slow decay kinetics
allow for more time for photon detection. Engineering GEIs with large changes in
fluorescence in response to even low levels of an analyte of interest, often by linker
screening, is critical for low limits of detection for
in vivo
imaging. High affinity variants
of GltI, the PBP involved in iGluSnFr, have been screened and explored by several groups
in order to improve the detection limits of glutamate sensors (
Helassa et al., 2018
;
Hires
et al., 2008b
;
Marvin et al., 2018
). Creating high affinity sensors with slow off kinetics
and high expression, however, could result in ligand buffering effects and disruption of
endogenous activity. Negative physiological effects as a result of ligand buffering and
calcium dysregulation due to calcium GEI expression, including versions of GCaMP, have
been reported in several studies (
Gasterstädt et al., 2020
;
McMahon and Jackson, 2018
;
Steinmetz et al., 2017
;
Yang et al., 2018
). It has become more of the standard to express
GEIs under the relatively weak neuronal specific synapsin promoter to curb these potential
effects. Further efforts in sensor engineering will be needed to ensure minimal disruption
to host processes. For example, GCaMP-X was engineered based on the findings that
GCaMP was shown to disrupt endogenous voltage-gated calcium channel function by
causing calcium dysregulation (
Yang et al., 2018
). iGluSnFr has also been found to compete
with glutamate transporters and have buffering effects, so sensor engineering efforts must be
made to curb this disruption of endogenous activity (
Armbruster et al., 2020
).
The use of naturally occurring receptors or designed binding proteins as scaffolds affords for
high chemical selectivity; however, binding to off-target analytes, especially to structurally
related molecules can potentially complicate studies where multiple neurotransmitter release
mechanisms are expected (Table 1). Glutamate sensors like FLIPE and iGluSnFr can
respond to both glutamate and aspartate binding (
Marvin et al., 2013
;
Okumoto et al., 2005
).
iGABASnFr can respond to glycine and iAchSnFr can detect choline and nicotine (
Borden
et al., 2020
;
Marvin et al., 2019
). Previously, we discussed how FSCV can yield similar
voltammograms for dopamine and structurally similar norepinephrine and epinephrine.
Similarly, GRAB-DA and dLight can also respond to norepinephrine (
Patriarchi et al., 2018
;
Sun et al., 2020
), although with reduced affinity. For example, dLight has 70 fold and 40
fold lower affinity for norepinephrine and epinephrine, respectively, to dopamine (
Patriarchi
et al., 2018
). It is likely that for future sensors that are able to bind nonspecifically to
structurally related analytes, binding pocket engineering like that undergone to engineer
iSeroSnFr can reduce nonspecific binding affinity (
Unger et al., 2020
). A further limitation
for GPCR-based sensors is their ability to respond to drug modulation that may target that
specific receptor. While this may make this class of sensors difficult for studies that seek to
measure changes in drug-mediated changes in target concentration, it can also be an added
benefit. In our recent work, we demonstrated that psychLight has applications in not only
in vivo
detection of serotonin release, but also as a tool for predicting the hallucinogenic
potential of known and novel psychoplastogenic compounds
in vitro
(
Dong et al., 2021
).
Simultaneous detection of different neurochemicals with biosensors are relatively
challenging compared to microdialysis because of the need to avoid spectral overlap. The
majority of well-characterized single FP GEIs use GFP, though in the past few years, efforts
have been made to develop red-shifted versions of sensors that need further development
Tjahjono et al.
Page 13
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
for widespread
in vivo
use. Different color variants of fluorescent GEIs will allow for
flexibility with not only other sensors for simultaneous analyte detection, but also with other
optogenetic actuators. Beyond fluorescent protein based GEIs, hybrid far-red calcium and
voltage indicators based on the self-labeling protein HaloTag have been developed (
Deo et
al., 2021
). The development of orthogonal fluorescent GEIs with different mechanisms of
action, color variants, and targets will allow us the flexibility to answer an even broader
range of neuroscience questions.
A disadvantage of GEIs that is shared with FSCV is their inability to determine absolute
basal concentrations of an analyte of interest. While relative changes in concentration can
be calculated from changes in fluorescence by referring to dose-response curves, basal
concentrations cannot be estimated with intensity-based indicators, though it has been
attempted with FRET sensors, for example using the glycine sensor GlyFS (
Zhang et al.,
2018
). Perhaps the development of fluorescence lifetime-based indicators, such as a recent
calcium indicator released by van der Linden and colleagues, could allow for quantification
of basal analyte concentrations (
van der Linden et al., 2021
).
3.2.3 Challenges in image analysis—
Single FP sensors utilize the metric dF/F
0
,
where measurements of the change in fluorescence intensity are normalized by baseline
fluorescence intensity (F
0
) to quantify changes in analyte concentration. However, several
factors can interfere with accurately converting dF/F
0
to changes in concentration. For
example, sensor aggregation due to high sensor expression would invariably result in diluted
apparent dF/F
0
values. Furthermore, as fluorescence values are normalized by a “baseline”
fluorescence intensity for a period of time before the event of interest, drifts in conditions
that cause baseline fluorescence values to shift irrespective of analyte levels would interfere
with accurate quantification. Sample movement, photobleaching, and pH sensitivity can all
result in changing baseline levels throughout the course of an experiment. The consequences
of having a noisy F
0
and a suggestion for data quantification in light of this is discussed in a
recent work (
Sabatini and Tian, 2020
).
A further challenge for consistent reporting of neurochemical dynamics between different
studies is the lack of standardization in image processing and analysis techniques.
In
vivo
imaging with neurotransmitter sensors presents many challenges, including diffuse
membrane and neuropil expression, motion artifacts from imaging freely moving animals,
and high autofluorescence and low sensor signal with the use of minimal laser power to
minimize photodamage to the tissue and reporter bleaching. Multispectral imaging can
be used to unmix autofluorescence
in vivo
since the spectrum of objects contributing to
autofluorescent background are often broader than the fluorescent markers (
Mansfield et al.,
2005
). However this can be complicated by the many variable sources of autofluorescence
(from blood) in a tissue, which makes it difficult to determine the spectral properties of
all components in the sample required for accurate automated unmixing (
Mansfield et
al., 2005
). Additionally, uneven fluorescence illumination and detection across a field of
view makes it difficult to accurately and precisely quantify fluorescence (
Kozlowski and
Weimer, 2012
). Therefore, considerations for region of interest (ROI) selection, background
subtraction, and motion artifact correction are important. For example, different methods for
ROI determination for measuring mean fluorescence have been utilized for
in vivo
and
ex
Tjahjono et al.
Page 14
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
vivo
use of established neurotransmitter sensors, ranging from whole frame ROIs to ROIs
obtained by manual selection or automatic segmentation (
Marvin et al., 2013
;
Patriarchi
et al., 2018
;
Sun et al., 2018
). Each technique can result in different dF/F
0
results and
consistency issues when comparing results from different groups utilizing the same sensor.
The measured fluorescent changes from whole frame ROIs are diluted by background pixels
with no sensor expressed, thus making the magnitude of fluorescence changes dependent
on both noise from background and on sensor expression levels within a field of view.
Meanwhile, segmenting an image to restrict measurement to areas of sensor expression
can be a work-around for low SNR images and will minimize the “dilution” effect of
fluorescence changes when including background pixels where no sensor is expressed.
While much work has been done to develop open-source image analysis software for
in
vivo
calcium imaging (
Cantu et al., 2020
;
Giovannucci et al., 2019
;
Tegtmeier et al., 2018
),
the inherent differences between intracellular expressed calcium indicators and synaptic
and membrane targeted transmitter sensors may limit their translatability. Detecting and
quantifying neurochemical release at the level of individual synapses have been explored
(
Dürst et al., 2019
;
Farsi et al., 2021
), and perhaps recent advances in synapse detection
algorithms for fluorescent images may further improve the accessibility and accurate
quantification of synaptic release analysis using GEIs (
Feng et al., 2012
;
Kulikov et al.,
2019
;
Wang et al., 2019
). An open-source software suite (pMAT) for analysis of fiber
photometry data has been recently developed, allowing for implementation of a standardized
data analysis pipeline across groups (
Bruno et al., 2021
). As isosbestic points for various
sensors could vary, further development can be done to accommodate signal normalization
based on other spectra. Nonetheless, there is a need for new open-source tools for automated
analysis of longitudinal imaging with neurotransmitter GEIs with microscopic applications.
Outlook
We are in a new and exciting era of neurochemical recording. Emerging questions proposed
by neuroscientists and lessons learned in creating a variety of technologies will serve as
the nexus for the development of novel neurochemical probes. Besides techniques discussed
above, other chemical and cell-based approaches have also been developed to monitor
neurochemical dynamics. Though fluorescence imaging provides high spatiotemporal
resolution, it is not compatible with human applications. Positron emission tomography
(PET) and magnetic resonance imaging (MRI) using nuclear medicine or genetically
encoded probes provide information at the whole-brain level and have been broadly used
for diagnosis in humans, albeit with poor spatial and temporal resolution (
Finnema et
al., 2015
;
Li and Jasanoff, 2020
;
Shimojo et al., 2020
). The development of cell-based
neurotransmitter fluorescent engineered receptors (CNiFERs) is another detection method
for dopamine, norepinephrine and neuropeptides (
Muller et al., 2014
). CNiFERs are cells
that express GPCRs that are activated upon ligand binding, resulting in calcium influx and
a change in fluorescence in the FRET-based calcium reporter TN-XXL. This technique,
though, requires the invasive implantation of cells and lacks the cell-type or subcellular
specificity of genetically encoded indicators. Aptamers, single stranded oligonucleotides that
fold into 3D structures, have been engineered to bind neurochemicals with high sensitivity
and specificity (
Ellington and Szostak, 1990
;
Gold et al., 1995
). Aptamers have been used
Tjahjono et al.
Page 15
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
for electrochemical biosensors to detect the rearrangement of aptamer structure as a result of
ligand binding, and have potential for sensitive and specific neurochemical detection
in vivo
in the near future (
Nakatsuka et al., 2018
).
The type of neurochemical molecules is substantially diverse (e.g. more than 100 known
neurotransmitter/modulators) contributing to the myriad inputs signals to the circuit
(
Kovács, 2004
). Together with heterogeneity within cell types, it is a grand challenge to
elucidate circuit mechanisms and function. Fluorescence imaging permits cell-type specific
measurement of diverse signaling inputs and post-synaptic activity, as well as provides a
cellular map of neurochemical transients across the full-course of behavior, which is difficult
to achieve with analytic or electrochemical methods (Table 2). Combined with optogenetic
and chemogenetic actuators, we can specifically tease apart the input-output interactions
within neural circuits.
However, the breadth and range of chemicals that can be detected is limited by the
availability of engineered indicators. Spectral overlap between indicators also enforces
limitations on multiplexing. Microdialysis, on the other hand, can simultaneously detect
many compounds with sensitive chemical analysis methods. Its capability and flexibility for
temporal averaging can be useful for studies where monitoring short timescale dynamics
is not desired, such as to measure slow volume transmission of neuropeptides or signal
integration dynamics (Table 2).
Non-invasive or minimally invasive monitoring of neurochemical dynamics in freely-moving
animal models or even humans is still challenging. Probe implantation, may it be carbon
fiber microelectrodes, microdialysis probes, or fiber photometry probes, can result in
initiation of inflammatory processes and tissue damage. We have discussed several methods
by which these probes are being miniaturized and more biocompatible for chronic recording
applications. All the methods mentioned have been extensively implemented in model
animals, including non-human primates. Notably, the flexibility of FSCV for multimodal
study and its relatively low invasiveness has lended to its ability to measure neurochemicals
in the human brain (
Bennet et al., 2016
), which is likely not in the foreseeable future
for fluorescence imaging. Acute microdialysis studies have also been performed in the
human brain. Beyond the probe size itself, the chemical specificity of each method can
also contribute to its invasive properties. Compared to GEIs which are designed to bind
and recognize specific analytes, direct sampling with microdialysis or analyte adsorption
to FSCV probes are not as specific. Non-specific depletion of solutes around the probe
can result in repercussions given the tightly controlled chemical environment of the brain
(
Chefer et al., 2009
). Depleting a target of interest at a single region from FSCV or
microdialysis may have less of a disruption in endogenous processes compared to potentially
widespread ligand buffering effects of many cells expressing genetically encoded indicators.
This will continue to be an important consideration for sensor engineers moving forward.
Acknowledgements
We would like to thank our funding sources for supporting this work: NIH 5T32GM099608-10 (N.T.), NIA
R01AG054649-05(Y.H.), (A.H, M.R.), NIH U01NS113295, R01HD091325, U01NS120820, R21EY031858 (L.T.).
Tjahjono et al.
Page 16
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
References
Abdelfattah AS, Kawashima T, Singh A, Novak O, Liu H, Shuai Y, Huang YC, Campagnola L,
Seeman SC, Yu J, Zheng J, Grimm JB, Patel R, Friedrich J, Mensh BD, Paninski L, Macklin JJ,
Murphy GJ, Podgorski K, Lin BJ, Chen TW, Turner GC, Liu Z, Koyama M, Svoboda K, Ahrens
MB, Lavis LD, Schreiter ER, 2019. Bright and photostable chemigenetic indicators for extended in
vivo voltage imaging. Science (80-. ). 365, 699–704. 10.1126/science.aav6416
Al-Hasani R, Wong JMT, Mabrouk OS, McCall JG, Schmitz GP, Porter-Stransky KA, Aragona BJ,
Kennedy RT, Bruchas MR, 2018. In vivo detection of optically-evoked opioid peptide release. Elife
7, 1–13. 10.7554/eLife.36520
Armbruster M, Dulla CG, Diamond JS, 2020. Effects of fluorescent glutamate indicators on
neurotransmitter diffusion and uptake. Elife 9, 1–27. 10.7554/eLife.54441
Baird GS, Zacharias DA, Tsien RY, 1999. Circular permutation and receptor insertion within green
fluorescent proteins. Proc. Natl. Acad. Sci. U. S. A 96, 11241–11246. 10.1073/pnas.96.20.11241
[PubMed: 10500161]
Ballini C, Della Corte L, Pazzagli M, Colivicchi MA, Pepeu G, Tipton KF, Giovannini MG, 2008.
Extracellular levels of brain aspartate, glutamate and GABA during an inhibitory avoidance
response in the rat. J. Neurochem 106, 1035–1043. 10.1111/j.1471-4159.2008.05452.x [PubMed:
18466328]
Bang D, Kishida KT, Lohrenz T, White JP, Laxton AW, Tatter SB, Fleming SM, Montague PR, 2020.
Sub-second Dopamine and Serotonin Signaling in Human Striatum during Perceptual Decision-
Making. Neuron 108, 999–1010.e6. 10.1016/j.neuron.2020.09.015 [PubMed: 33049201]
Barnea G, Strapps W, Herrada G, Berman Y, Ong J, Kloss B, Axel R, Lee KJ, 2008. The genetic
design of signaling cascades to record receptor activation. Proc. Natl. Acad. Sci. U. S. A 105,
64–69. 10.1073/pnas.0710487105 [PubMed: 18165312]
Bennet KE, Tomshine JR, Min HK, Manciu FS, Marsh MP, Paek SB, Settell ML, Nicolai EN,
Blaha CD, Kouzani AZ, Chang SY, Lee KH, 2016. A diamond-based electrode for detection of
neurochemicals in the human brain. Front. Hum. Neurosci 10, 1–12. 10.3389/fnhum.2016.00102
[PubMed: 26858619]
Bernstein AI, Stout KA, Miller GW, 2012. A fluorescent-based assay for live cell, spatially resolved
assessment of vesicular monoamine transporter 2-mediated neurotransmitter transport. J. Neurosci.
Methods 209, 357–366. 10.1016/j.jneumeth.2012.06.002 [PubMed: 22698664]
Beyene AG, Delevich K, Del Bonis-O’Donnell JT, Piekarski DJ, Lin WC, Wren Thomas A, Yang SJ,
Kosillo P, Yang D, Prounis GS, Wilbrecht L, Landry MP, 2019. Imaging striatal dopamine release
using a nongenetically encoded near infrared fluorescent catecholamine nanosensor. Sci. Adv 5,
1–12. 10.1126/sciadv.aaw3108
Bi X, Beck C, Gong Y, 2021. Genetically encoded fluorescent indicators for imaging brain chemistry.
Biosensors 11. 10.3390/bios11040116
BITO L, Davson H, Levin E, Murray M, Snider N, 1966. the Concentrations of Free Amino Acids and
Other Electrolytes in Cerebrospinal Fluid, in Vivo Dialysate of Brain, and Blood Plasma of the
Dog. J. Neurochem 13, 1057–1067. 10.1111/j.1471-4159.1966.tb04265.x [PubMed: 5924657]
Borden PM, Zhang P, Shivange AV, Marvin JS, Cichon J, Dan C, Podgorski K, Figueiredo A, Novak
O, Tanimoto M, Shigetomi E, Lobas MA, Kim H, Zhu PK, Zhang Y, Zheng WS, Fan C, Wang
G, Xiang B, Gan L, Zhang G-X, Guo K, Lin L, Cai Y, Yee AG, Aggarwal A, Ford CP, Rees
DC, Dietrich D, Khakh BS, Dittman JS, Gan W-B, Koyama M, Jayaraman V, Cheer JF, Lester
HA, Zhu JJ, Looger LL, 2020. A fast genetically encoded fluorescent sensor for faithful in vivo
acetylcholine detection in mice, fish, worms and flies. Biorxiv 2020.02.07.939504.
Bruno CA, O’Brien C, Bryant S, Mejaes JI, Estrin DJ, Pizzano C, Barker DJ, 2021. pMAT: An
open-source software suite for the analysis of fiber photometry data. Pharmacol. Biochem. Behav
201, 173093. 10.1016/j.pbb.2020.173093 [PubMed: 33385438]
Bucher ES, Wightman RM, 2015. Electrochemical Analysis of Neurotransmitters. Annu. Rev. Anal.
Chem 8, 239–261. 10.1146/annurev-anchem-071114-040426
Tjahjono et al.
Page 17
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript
Bungay PM, Morrison PF, Dedrick RL, 1990. Peter M. Bungay, Paul F. Morrison, Robert L. Dedrick
Biomedical Engineering & Instrumentation Branch, Division of Research Services, National
Institutes of Health, Bethesda, MD 20892 USA. Life Sci 46, 105–119. [PubMed: 2299972]
Calhoun SE, Meunier CJ, Lee CA, McCarty GS, Sombers LA, 2019. Characterization of a Multiple-
Scan-Rate Voltammetric Waveform for Real-Time Detection of Met-Enkephalin. ACS Chem.
Neurosci 10, 2022–2032. 10.1021/acschemneuro.8b00351 [PubMed: 30571911]
Cantu DA, Wang B, Gongwer MW, He CX, Goel A, Suresh A, Kourdougli N, Arroyo ED, Zeiger
W, Portera-Cailliau C, 2020. EZcalcium: Open-Source Toolbox for Analysis of Calcium Imaging
Data. Front. Neural Circuits 14, 1–9. 10.3389/fncir.2020.00025 [PubMed: 32174815]
Carandini M, Shimaoka D, Rossi LF, Sato TK, Benucci A, Knopfel X, 2015. Imaging the awake
visual cortex with a genetically encoded voltage indicator. J. Neurosci 35, 53–63. 10.1523/
JNEUROSCI.0594-14.2015 [PubMed: 25568102]
Chefer VI, Thompson AC, Zapata A, Shippenberg TS, 2009. Overview of brain microdialysis. Curr.
Protoc. Neurosci 1–28. 10.1002/0471142301.ns0701s47
Chen NNH, Lai YJ, Pan WHT, 1997. Effects of different perfusion medium on the extracellular basal
concentration of dopamine in striatum and medial prefrontal cortex: A zero-net flux microdialysis
study. Neurosci. Lett 225, 197–200. 10.1016/S0304-3940(97)00222-X [PubMed: 9147404]
Chen Q, Cichon J, Wang W, Qiu L, Lee SJR, Campbell NR, DeStefino N, Goard MJ, Fu Z, Yasuda R,
Looger LL, Arenkiel BR, Gan WB, Feng G, 2012. Imaging Neural Activity Using Thy1-GCaMP
Transgenic Mice. Neuron 76, 297–308. 10.1016/j.neuron.2012.07.011 [PubMed: 23083733]
Chen TW, Wardill TJ, Sun Y, Pulver SR, Renninger SL, Baohan A, Schreiter ER, Kerr RA, Orger
MB, Jayaraman V, Looger LL, Svoboda K, Kim DS, 2013. Ultrasensitive fluorescent proteins for
imaging neuronal activity. Nature 499, 295–300. 10.1038/nature12354 [PubMed: 23868258]
Cooper SE, Venton BJ, 2009. Fast-scan cyclic voltammetry for the detection of tyramine
and octopamine. Anal. Bioanal. Chem 394, 329–336. 10.1007/s00216-009-2616-0 [PubMed:
19189084]
Cryan MT, Ross AE, 2019. Subsecond detection of guanosine using fast-scan cyclic voltammetry.
Analyst 144, 249–257. 10.1039/c8an01547c
Dana H, Sun Y, Mohar B, Hulse BK, Kerlin AM, Hasseman JP, Tsegaye G, Tsang A, Wong A,
Patel R, Macklin JJ, Chen Y, Konnerth A, Jayaraman V, Looger LL, Schreiter ER, Svoboda K,
Kim DS, 2019. High-performance calcium sensors for imaging activity in neuronal populations
and microcompartments. Nat. Methods 16, 649–657. 10.1038/s41592-019-0435-6 [PubMed:
31209382]
Deo C, Abdelfattah AS, Bhargava HK, Berro AJ, Falco N, Farrants H, Moeyaert B, Chupanova M,
Lavis LD, Schreiter ER, 2021. The HaloTag as a general scaffold for far-red tunable chemigenetic
indicators. Nat. Chem. Biol 17, 718–723. 10.1038/s41589-021-00775-w [PubMed: 33795886]
Deuschle K, Okumoto S, Fehr M, Looger LL, Kozhukh L, Frommer WB, 2005. Construction
and optimization of a family of genetically encoded metabolite sensors by semirational protein
engineering. Protein Sci 14, 2304–2314. 10.1110/ps.051508105 [PubMed: 16131659]
Dong C, Ly C, Dunlap LE, Vargas MV, Sun J, Hwang I-W, Azinfar A, Oh WC, Wetsel WC, Olson
DE, Tian L, 2021. Psychedelic-inspired drug discovery using an engineered biosensor. Cell 1–14.
10.1016/j.cell.2021.03.043 [PubMed: 33417857]
Dunn M, Henke A, Clark S, Kovalyova Y, Kempadoo KA, Karpowicz RJ, Kandel ER, Sulzer D,
Sames D, 2018. Designing a norepinephrine optical tracer for imaging individual noradrenergic
synapses and their activity in vivo. Nat. Commun 9, 1–13. 10.1038/s41467-018-05075-x [PubMed:
29317637]
Dürst CD, Wiegert JS, Helassa N, Kerruth S, Coates C, Schulze C, Geeves MA, Török K, Oertner TG,
2019. High-speed imaging of glutamate release with genetically encoded sensors. Nat. Protoc 14,
1401–1424. 10.1038/s41596-019-0143-9 [PubMed: 30988508]
Ellington AD, Szostak JW, 1990. In vitro selection of RNA molecules that bind specific ligands.
Nature 346, 818–822. 10.1038/346818a0 [PubMed: 1697402]
Farsi Z, Walde M, Klementowicz AE, Paraskevopoulou F, Woehler A, 2021. Single synapse glutamate
imaging reveals multiple levels of release mode regulation in mammalian synapses. iScience 24,
101909. 10.1016/j.isci.2020.101909 [PubMed: 33392479]
Tjahjono et al.
Page 18
Neurosci Res
. Author manuscript; available in PMC 2022 September 24.
Author Manuscript
Author Manuscript
Author Manuscript
Author Manuscript