Optical sensing

While the strength of electrochemical sensing lies in its high temporal resolution and the major drawback in the poor spatial resolution, the situation for optical sensing is reversed.

Optical sensing can be achieved by: (1) using fluorescent materials or molecules as building blocks for sensors, or (2) implementing genetically encoded fluorescent sensors into biological structures involved in neurotransmitter release.

One of the first examples of dopamine detection with a fluorescent nanoparticle was reported by Willner et al. [45]. They functionalized Cd-Se-ZnS quantum dots (QD) with a boronic acid derivate. This moiety is known for its ability to bind molecules with two adjacent hydroxy-groups. Thus, this principle can not only be applied to detection of catecholamines but also of sugars (e.g point-of-care glucose detectors for diabetes). In the first step, an organic fluorophore is conjugated to dopamine. Upon binding of dopamine-fluorophore con-jugate to the boronic acid moiety, there is a F¨orster resonance energy transfer (FRET) to the fluorophore and the fluorescence of the QD is decreased. When an unbound dopamine molecule from the solution replaces its dopamine-fluorophore counterpart on the QD, the fluorescence of the sensor is restored. An important disadvantage of this technique is the lack of reversibly in a biological setting. Once all dopamine-fluorophore conjugates are replaced on the GO, the sensor is saturated and cease to detect further molecules. Another nano-material used for dopamine detection is graphene oxide (GO). Emission of GO nanosheets is highly sensitive to binding of other molecules and is quenched by dopamine, probably via π - π stacking and photo-induced charge transfer [46]. This reaction allows to measure dopamine concentrations in urine samples down to 2.3µM, but the selectivity of such sensors is not sufficient to distinguish between various catecholamines or other small molecules with extendedπ-systems [47].

A reasonable approach to increase selectivity is to mimic existing molecular recognition units. Nature has already developed several receptors for such an important molecule class as neurotransmitters and one can integrate those natural neurotransmitter receptors into artificial sensors [48]. One of the first examples for such composition resulted in a genetically encoded fluorescent sensor for glutamate withK_d of 630 nM [49]. The sensor is a complex of a bacterial glutamate-binding protein (ybeJ) and two fluorescent proteins (YFP and CFP).

Conformational changes of the glutamate binding protein induce FRET and can be optically detected. By attaching a periplasmic binding sequence to the sensor, the sensor is connected to the membrane of the transfected cells. Docked on the surface of the cells the sensors can determine glutamate after electrical stimulation of hippocampal neurons. The novelty of this approach lies in the possibility to image the evolved neurotransmitter themselves and not only the related processes such as vesicle fusion. Despite the groundbreaking approach this technique still has several limitations: 1) both absorption and emission show width

spectra and make measuring an exact change difficult, 2) the conformational change of the binding protein is small, which results in a poor signal to noise ratio, 3) low photostability of fluorescent proteins (compared with more stable organic dyes or fluorescent nanomaterials without any bleaching at all) limits the applicability of the system, 4) conformational change upon binding of the neurotransmitter and its impact on the FRET signal is hard to foresee and tune beforehand. That makes a rational design of such sensors difficult.

To overcome some of the objections Johnsson et al. presented a semisynthetic approach.

Their biosensor is a complex of a self-labeling protein tag (SNAP-tag), an organic fluorophore and a metabolite-binding protein [50]. SNAP-tag is conjugated to a synthetic ligand (L) of the binding protein and a second fluorophor. In the absence of the analyte, the synthetic ligand (L) is bound to the metabolite-binding protein and the sensor protein is in closed conformation. Close proximity of both donor and acceptor fluorophores result in a high FRET efficiency. When the analyte is introduced into the system, it displaces the ligand from the binding protein. The sensor protein shifts from a closed to an open conformation.

This change can be measured by a ratiometric change in the fluorescence intensities of the two fluorophores. So far, this technique has been leading in the neurotransmitter dynamics research. Its modular approach and an existing library of available SNAP-tags and fluo-rophores allow adaptation to new biological systems. A drawback of this method is the need for cell transfection and manipulation. This can affect complex biological experiments and make in vivo measurements impossible.

A further development of this technique allowed to genetically encode the protein part of the sensor and produce it on the cell surface [50]. This development lead to a new acronym SNIFIT (SNAP-tag based indicator proteins with a fluorescent intramolecular tether) and allowed to measure the metabolite concentrations on the cell surface, as well as indirect measurements of glutamate, acetylcholine and γ-aminobutyric acid (GABA) concentrations [51], [52], [53]. Figure 7 illustrates this principle by showing a SNIFIT sensor for acetylcholine (ACh-SNIFIT).

Figure 5: Schematic of a semisynthetic SNIFIT based sensor for acetylcholine (ACh-SNIFIT). (a) A ACh-SNIFIT sensor contains: (i) acetylcholinesterase (AChE, green), (ii) a labeling protein tag (CLIP) used to introduce a FRET donor (Cy5, blue star), (iii) a self-labeling protein tag (SNAP) with a FRET acceptor (Cy3, red star), and (iv) a synthetic ligand for AChE (L, yellow triangle). When the analyte (ACh, violet) displaces the ligand (L), FRET efficiency changes. (b) Confocal images of HEK cells expressing ACh-SNIFIT, labeled with Cy3 and Cy5. Scale bars: 10 µm, (c) Titration of ACh-SNIFIT induced cells with various ACh concentrations, shown as the ratio of donor (Cy5) to acceptor (Cy5) emission. Adapted with permission from [52]

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As the metabolite-binding protein they use acetylcholinesterase (AChE) that hydrolyzes acetylcholine to choline. Cy5 and Cy3 serve as the FRET donor and acceptor, respectively.

This sensor has been anchored to the outer membrane of living cells and enable ACh detection (Fig. 7c). While this technique is currently leading in neurotransmitter release imaging, it has major drawbacks: (1) the opening and closing kinetics of the sensor protein are several orders of magnitude slower than the neurotransmitter release kinetics (seconds vs.

milliseconds), (2) the sensitivity of the sensors lies in the mM range. Combined those two specifics prevent detection of fast diffusing molecules.