# Two-photon probes for in vivo multicolor microscopy of the structure and signals of brain cells

Clément Ricard, Erica D Arroyo, Cynthia X He, Carlos Portera-Cailliau, Gabriel Lepousez, Marco Canepari, Daniel Fiole

► To cite this version:

Clément Ricard, Erica D Arroyo, Cynthia X He, Carlos Portera-Cailliau, Gabriel Lepousez, et al. Two-photon probes for in vivo multicolor microscopy of the structure and signals of brain cells. Brain Structure and Function, 2018, 223 (7), pp.3011 - 3043. 10.1007/s00429-018-1678-1. hal-01872748

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1 **Two-photon probes for *in vivo* multicolor

2 **microscopy of the structure and signals of brain**

3 **cells.**

4 Clément Ricard<sup>1,2,3</sup>, Erica D. Arroyo<sup>4</sup>, Cynthia X. He<sup>4</sup>, Carlos Portera-Cailliau<sup>4,5</sup>,

5 Gabriel Lepousez<sup>6</sup>, Marco Canepari<sup>7,8,9</sup>, Daniel Fiole<sup>10,11,*</sup>

6

7 1) Brain Physiology Laboratory, CNRS UMR 8118, Paris, F-75006, France.

8 2) Faculté de Sciences Fondamentales et Biomédicales, Université Paris Descartes, PRES

9 Sorbonne Paris Cité, Paris, F-75006, France.

10 3) Fédération de Recherche en Neurosciences FR 3636, Paris, F-75006, France.

11 4) Department of Neurology, David Geffen School of Medicine, University of California, Los

12 Angeles, United States.

13 5) Department of Neurobiology, David Geffen School of Medicine, University of California, Los

14 Angeles, United States.

15 6) Unité Perception et Mémoire, Département de Neuroscience, Institut Pasteur, 25 rue du

16 Docteur Roux, F-75724 Paris Cedex 15, France.

17 7) Laboratory for Interdisciplinary Physics, UMR 5588 CNRS and Université Grenoble Alpes,

18 F-38402 Saint Martin d'Hères, France.

19 8) Laboratories of Excellence, Ion Channel Science and Therapeutics, France.

20 9) Institut National de la Santé et Recherche Médicale (INSERM), France.

21 10) Unité Biothérapies anti-Infectieuses et Immunité, Département des Maladies Infectieuses,

22 Institut de Recherche Biomédicale des Armées, BP 73, F-91223 Brétigny-sur-Orge cedex,

23 France.
24 11) Human Histopathology and Animal Models, Infection and Epidemiology department, Institut Pasteur, 28 rue du docteur Roux, F-75725 Paris Cedex 15, France.

26 * corresponding author: daniel.fiole@gmail.com.

27
28 Current address of DF: CREATIS, CNRS UMR 5220; Inserm U1044; Université de Lyon;
29 Université Lyon 1; INSA-Lyon, 69621 Villeurbanne, France, and: European Synchrotron
30 Radiation Facility, X-ray Imaging Group, 38043 Grenoble cedex, France. Current email
31 address: fiole@esrf.fr.

32
33 ORCID iD: CH 0000-0003-1236-3151; CPC 0000-0001-5735-6380; GL 0000-0002-9390-7749; DF 0000-0002-1072-6935.

35
36 [Keywords]

37 Two-photon cross section, calcium imaging, functional imaging, electroporation, intravital,
38 multicolor microscopy.

39
40

**Abstract**

41 Imaging the brain of living laboratory animals at a microscopic scale can be achieved by two-photon microscopy thanks to the high penetrability and low phototoxicity of the excitation 42 wavelengths used. However, knowledge of the two-photon spectral properties of the myriad 43 fluorescent probes is generally scarce and, for many, non-existent. Additionally, the use of 44 different measurement units in published reports further hinders the design of a 45 comprehensive imaging experiment. 46

47 In this review, we compile and homogenize the two-photon spectral properties of more than 48 280 fluorescent probes. We provide practical data, including the wavelengths for optimal two- 49 photon excitation, the peak values of two-photon action cross-section or molecular brightness, 50 and the emission ranges. Beyond the spectroscopic description of these fluorophores, we 51 discuss their binding to biological targets. This specificity allows *in vivo* imaging of cells, 52 their processes, and even organelles and other subcellular structures in the brain. In addition 53 to probes that monitor endogenous cell metabolism, studies of healthy and diseased brain 54 benefit from the specific binding of certain probes to pathology-specific features, ranging 55 from amyloid-β plaques to the autofluorescence of certain antibiotics. A special focus is 56 placed on functional *in vivo* imaging using two-photon probes that sense specific ions or 57 membrane potential, and that may be combined with optogenetic actuators. Being closely 58 linked to their use, we examine the different routes of intravital delivery of these fluorescent 59 probes according to the target. Finally, we discuss different approaches, strategies, and 60 prerequisites for two-photon multicolor experiments in the brains of living laboratory animals.
61

# Introduction

Two-photon excitation fluorescence microscopy, or two-photon microscopy (TPM), became a standard and powerful method of investigation in biology due to its excellent penetrability in living tissues and high spatiotemporal resolution, while inducing low phototoxicity and photobleaching compared to other optical techniques (Denk et al. 1990; So et al. 2000; Zipfel et al. 2003b; Helmchen and Denk 2005). In this review, we focus on neuroscience because the functional and physiological properties of the brain makes it a particularly fecund field for the application of TPM (Svoboda and Yasuda 2006; Mostany et al. 2015).

The sophistication of intravital TPM is currently expanding through three axes: 1. Hardware; 2. Sample preparation and new genetic tools; 3. Fluorescent probes (Crowe and Ellis-Davies 2014). First, as far as hardware there have been improvements and new developments in excitation sources, scanning, and detection. The popularization of optical parametric oscillators (OPO), which allow excitation far beyond the traditional Titanium:Sapphire lasers, helps improve the depth of imaging up to 1.6 mm (Kobat et al. 2011). Deep scattering tissues can be efficiently observed by wavefront optimization thanks to adaptive optics (Ji et al. 2010; Wang et al. 2015). New kinds of detectors like GaAsP photomultipliers or hybrid avalanche photodiodes allow detection of dimmer signals. Also, promising advances in the miniaturization of two-photon microscopes are enabling simultaneous recordings of neural circuit activity in freely moving animals (Yu et al. 2015; Zong et al. 2017) while avoiding the side effects associated with the use of anesthetics (Tran and Gordon 2015; Santisakultarm et al. 2016).

Second, refinements in sample preparation beyond the original glass-covered cranial windows (Holtmaat et al. 2009) and skull thinning (Yang et al. 2010) now permit chronic live imaging below the superficial layers of neocortex. For example, a substantial increase in resolution can be achieved by replacing the single coverslip with a pair of coverslips separated by a thin
layer of air, which minimizes the effects of spherical aberration (Estrada et al. 2015). Also, surgical GRIN lens implantation can be combined with head-mounted miniscopes (Resendez et al. 2016) or standard two-photon microscopes for imaging of deep brain structures such as hippocampus (Crowe and Ellis-Davies 2014).

*In vivo* TPM imaging also benefits from the use of genetic tools that can target fluorochrome expression to different brain cells, including promoters for specific cell types (e.g., Thy1 mice for Layer 5B neurons (Feng et al. 2000), CX3CR1 mice for microglia (Jung et al. 2000)). Cre-Lox recombination can be fruitfully used to target any fluorescent protein in spatially restricted patterns, such as different cell types, cortical layers, or brain regions, thanks to the existence of a number of Cre driver lines. Other genetic strategies (e.g., Cre-ER<sup>T2</sup>) can temporally restrict expression (Kristianto et al. 2017). Different fluorochromes can be simultaneously expressed on different cells of the same lineage thus (e.g., the Brainbow construct (Livet et al. 2007)) or on different cell types by breeding together mice of different phenotypes (e.g., Thy1-CFP/LysM-GFP/CD11c-EYFP (Fenrich et al. 2013)).

Designing new transgenic animal models has been recently made less arduous than previously by CRISPR/Cas9 (Wang and Qi 2016) and PiggyBac (Woodard and Wilson 2015) technologies, but remains a time-consuming task that can be overcome by the administration of exogenous fluorescent probes. Depending on the target and on physical and chemical properties of the probe, methods of administration can range from intravenous dye injection to *in utero* electroporation and viral protein transduction.

Third, the availability of increasing numbers of two-photon-suitable synthetic dyes or genetically encoded probes with extended properties has brought new perspectives to the use of TPM in neuroscience. One of these perspectives consists of two-photon functional imaging, which makes possible to witness brain cells 'at work' thanks to voltage-sensitive
110 dyes, probes that monitor levels of various ions (e.g., Cl⁻, Ca²⁺) (Helmchen 2009), or caged
111 neurotransmitters that can be photoreleased with TPM (Hess et al. 2014).

112 Beyond the prolific engineering of new fluorescent proteins that unquestionably and fruitfully
113 expands the biological applications of TPM (Pak et al. 2015), its routine use is hindered by
114 the need for a more extensive characterization of spectral properties of existing fluorescent
115 probes. Recent developments in far-red two-photon excitation make the need for an update of
116 the spectral characteristics of fluorescent probes even more acute (Herz et al. 2010; Mojzisova
117 and Vermot 2011). While commercial and academic databases of one-photon absorption
118 spectra are well documented, the two-photon specifications of most probes are only scarcely
119 documented, despite a small number of helpful initiatives (Bestvater et al. 2002; Cahalan et al.
120 2002; Drobizhev et al. 2011; Mütze et al. 2012; Romanelli et al. 2013; Lim and Cho 2013).

121 In this review, we provide a comprehensive list of two-photon-related spectral and biological
122 properties of more than 280 fluorescent probes, and discuss different routes of delivery of
123 such probes into laboratory animals, as well as their actual or prospective relevance to in vivo
124 multicolor TPM of cells, structures, and functions, in the healthy and diseased brain.

125

126

127

# 1) Reaching the target

128

## 1.1 Intravenous route

129

130 Blood vessels transport oxygen and nutriments in the whole organism and can be used to
131 deliver fluorescent dyes into the tiniest parts of an organ (cf. Table 1).

132 Blood vessel labeling requires only the intravenous delivery of a fluorescent dye to efficiently
133 stain an entire organ's vascular tree, which can then be observed *in vivo* with TPM by a z-
stack acquisition (Tozer et al. 2005; Ricard et al. 2013b). Common dyes such as **fluorescein** or **rhodamine** (cf. Table 2) can be used; these are harmless to the animal and cleared from the circulation after a few hours. As capillaries can be permeable to small molecules, these dyes are usually conjugated with a large molecular weight dextran that is too large to leak into the tissue. The molecular weight of the resulting dye can thus be chosen depending on the permeability of the targeted type of vessel. Neocortical arteries and arterioles can be specifically labeled using **Alexa Fluor 633** (cf. Table 3), which binds to elastin fibres (Shen et al. 2012). However, when multicolor labeling is required, green or red channels are frequently chosen through the use of other fluorophores or fluorescent proteins (e.g., **EGFP** or **DsRed**).

Blue-emitting dyes such as **Cascade Blue** have been successfully used in intravital studies and can efficiently be excited by TPM (Ricard and Debarbieux 2014; Ricard et al. 2016b). It must be considered, however, that in living tissues the maximum imaging depth is a function of the wavelengths of both the excitation and fluorescence beam. In the TPM range, high-energy photons are quickly absorbed by the tissue, resulting in a reduced imaging depth (König 2000). Such a parameter has to be taken into account in the design of the experiment.

Moreover, fluorescent dyes conjugated to dextrans can be captured by phagocytes resulting in a long-lasting labeling of these cells (Fenrich et al. 2012; Fiole et al. 2014). Such labeling is observed in the brain and spinal cord dura mater for several days after a single intravenous injection and can impede the correct segmentation of blood vessels during image processing.

**Quantum dots** were introduced as an alternative to classic fluorescent dyes. They present low toxicity, are not engulfed by macrophages, have reduced photobleaching, and can fluoresce in the red and deep-red range, making them particularly suitable for multicolor imaging (Mashinchian et al. 2014). It was also demonstrated that excitation of quantum dots using an optical parametric oscillator can improve imaging depth of vasculature in the brain and the spinal cord (Kobat et al. 2009, 2011; Ricard et al. 2016a). The fluorescence intermittency of
quantum dots (Frantsuzov et al. 2013) should however be taken into consideration especially for single-particle tracking, unless their nonblinking properties are established (Marchuk et al. 2012; Lane et al. 2014).

Intravenous injections of fluorescent dyes have also been used to label other structures. **Sulforhodamine 101** and **Sulforhodamine B** were reported to leak out of the vasculature and to stain specifically astrocytes (cf. Table 1 and Table 3) without showing adverse reactions on astrocytic calcium signals or electroencephalographic recording *in vivo* (Appaix et al. 2012; Vérant et al. 2013). **Sulforhodamine B** was also demonstrated to stain elastic fibers in blood vessel walls, as well as in muscles after a single intravenous injection (Ricard et al. 2007).

Intravenous injection of fluorescent probes can also be used to determine the acidity of tissues using pH indicators (cf. Table 4), or to measure physiological parameters such as cerebral blood flow (Chaigneau et al. 2003) and blood-brain-barrier permeability (Ricard et al. 2009) in different pathologies, including vascular occlusion (Schaffer et al. 2006) and brain tumors (Ricard et al. 2013b, 2016b). Investigating the properties of the blood vessel tree enables the assessment of side effects of treatments in preclinical trials (Ricard et al. 2013a). For instance, the blood vessel density of glioblastoma-animals injected with **Rhodamine B** dextran was recorded over time. Experiments conducted in untreated conditions and after the administration of bevacizumab, an anti-angiogenic compound, revealed a lack of correlation between tumor growth and blood vessel density (Ricard et al. 2013b).

As an alternative but comparable route to intravenous delivery, intraperitoneal administration (cf. Table 1) of fluorochromes can also be performed to stain structures in the diseased brain (cf. Table 5). For example, in Alzheimer's disease research, amyloid-β plaques can be specifically stained by intraperitoneal administration of **SAD1** (Heo et al. 2013) or **Methoxy-X04** (Klunk et al. 2002), revealing the kinetics of amyloid-β plaques growing over months (Burgold et al. 2011).
184

185

## 1.2 Whole-cell and bulk loading

186

187

188

189

190

191

192

193

A large population of neurons can be bulk-loaded with a cell membrane-permeable acetoxymethyl (AM) ester-conjugated indicator form (e.g., **Fura-2-AM** or **Fluo-4-AM**) (Garaschuk et al. 2006; Brenowitz and Regehr 2014) or dextran-conjugated form, enabling readout of activity across a network (Yuste et al. 2011; Reeves et al. 2011). Bulk-loading of ion indicators may be spatially restricted to the soma and most proximal processes of neural cells. However, Reeves *et al.* have shown that performing morphological reconstructions after bulk-loading of astrocytes in the CA1 region of the hippocampus from rats can help detecting calcium transients in distal astrocyte processes (Reeves et al. 2011).

194

195

196

197

198

199

Alternatively, chemical ion indicators can be typically delivered into single cells via micropipettes (enabling electrophysiology) or electroporation (Liu and Haas 2011; Grienberger and Konnerth 2012). While the chemical indicators have high sensitivity and fast on-off kinetics allowing for precise temporal resolution of action potentials, they are typically used in acute experimental preparations (a few hours at most), and they are not amenable for labeling of specific cell populations (Grienberger and Konnerth 2012).

200

201

## 1.3 Viral transduction

202

203

204

205

In order to allow expression of new genes coding for fluorescent proteins in spatially-restricted and genetically-defined neurons, researchers have developed a versatile toolbox of replication-incompetent recombinant viral vectors (cf. Table 1) that are devoid of most of their natural genetic material and loaded with engineered constructs (Nassi et al. 2015). The
206 diversity of available vectors reflects the different specifications of each viral vectors in terms
207 of:

208 1) tropism for cell type, compartment (axonal vs. somato-dendritic), and animal species. This
209 tropism is directly influenced by the nature of the glycoprotein of the envelope (which defines
210 the serotype) and the expression of receptors for envelope glycoprotein on targeted cells
211 leading to vector internalization;

212 2) transduction and expression efficiency, speed of expression after infection, and stability for
213 long term expression;

214 3) vector genome size and maximum insert size, ease of manipulating the genome and
215 producing high-titer solutions, and integration into the host genome;

216 4) and immunogenicity, cell toxicity and safety.

217 Here we list the main viral vectors used in the neuroscience field and their general features:

218 - retroviruses are integrative vectors with an insert size up to 8-9 kB, providing a stable
219 long-term expression. They exclusively transduce dividing cells and show moderate
220 immunogeneticity.

221 - lentiviruses are integrative vectors with an insert size up to 8-9 kb, good for stable
222 long-term expression. They have a large tropism and can transduce most CNS cells
223 (astrocytes, neurons, and oligodendrocytes) and show moderate immunogeneticity.

224 - adeno-associated viruses (AAV) are currently the most commonly used vector for
225 gene delivery. They are non-integrative vectors with an insert size up to 4-5 kb.
226 Because of their small size and high titer production, a single injection can infect a
227 large volume of tissue. They are also favored over other vectors for their mild
228 immunogenicity and a dominant neuronal tropism. To enlarge their tropism, envelope
229 proteins have been engineered using directed evolution to target specific cell types
230 (e.g., oligodendrocytes (Büning et al. 2015; Powell et al. 2016)) or to target specific
231 neuronal compartments (e.g., axonal domain for retrograde labeling of neurons (Tervo
232 et al. 2016)).

233 - Herpes Simplex Virus (HSV-1) is a non-integrative vector with an insert size up to
234 100 kb. Although its complex genome is not easy to manipulate, HSV-1s transduce
235 mainly neurons with a dominant axonal tropism, making them an interesting tool for
236 retrograde labeling of neurons. Importantly, they show significant immunogenicity
237 and cell toxicity.

238 - Canine Adenovirus (CAV-2) is a non-integrative vector with a smaller insert size up to
239 30 kb (Junyent and Kremer 2015). CAV-2s transduce mainly neurons with a dominant
240 axonal tropism, making them an interesting tool for retrograde labeling of neurons.
241 The main receptor for the internalization of the virus is the coxsackievirus and
242 adenovirus receptor (CAR). They also show a significant immunogenicity and cell
243 toxicity.

244 - Rabies virus (RABV) is a non-integrative vector with an insert size of 4-5 kb. RABVs
245 are neurotropic and are classically used as replication-conditional pseudotyped viruses
246 for retrograde tracing of mono-synaptic inputs onto genetically-defined cell
247 populations (Wickersham et al. 2007). Rabies virus is pseudotyped with the EnVA
248 glycoprotein to ensure that the virus exclusively infects cells expressing the EnvA
249 receptor (TVA). The virus also lacks the envelope glycoprotein and expresses the gene
250 of interest. Complementation of the modified rabies virus with the envelope
251 glycoprotein in the TVA-expressing cells allows the generation of infectious particles,
252 which trans-synaptically infect presynaptic neurons. Importantly, rabies virus shows
253 strong neurotoxicity with longer-term infection (>15 days).

254
256

## 1.4 *In utero* electroporation

257 *In utero* electroporation (IUE) is a technique that enables researchers to express genes of
258 interest within specific neuronal populations (cf. Table 1) by targeting plasmid DNA
259 constructs directly to the embryonic brain of rodents (Fukuchi-Shimogori and Grove 2001;
260 Saito and Nakatsuji 2001; Takahashi et al. 2002; Wang and Mei 2013). Although this section
261 focuses on cerebral cortex, IUE can be used for gene transfer in other brain regions
262 (Takiguchi-Hayashi et al. 2004; Borrell et al. 2005; Nakahira et al. 2006; Navarro-Quiroga et
263 al. 2007; Bonnin et al. 2007). For cortical labeling, IUE takes advantage of one of the most
264 reliable and tightly regulated processes that occurs during brain development: the sequential
265 inside-out laminar organization of the cortex, whereby neurons in deeper layers are generated
266 before those in more superficial layers (Angevine and Sidman 1961; Rakic 1974). IUE is
267 performed at the gestational age that coincides with the generation of pyramidal precursor
268 cells at the subventricular zone along the lateral ventricles. These newborn neurons eventually
269 migrate to and incorporate into their appropriate cortical layer (Caviness and Takahashi 1995;
270 Tabata and Nakajima 2001). For instance, to label layer 2/3 excitatory pyramidal neurons,
271 IUE is performed at embryonic day (E)15-16 (Saito and Nakatsuji 2001).

272 Although IUE can be used to over-express essentially any protein of interest, it is perhaps
273 most often used to express fluorescent proteins that make it possible to image neuronal
274 structure with confocal or two-photon microscopy. Because IUE can provide sparse labeling
275 in neurons, it is particularly well-suited for high-resolution imaging of the finest detail of
276 neuronal structure, such as dendritic spines. Another major advantage of IUE over traditional
277 fluorescence labeling techniques such as transgenic mouse lines, is that it enables researchers
278 to conduct early postnatal imaging. This is due to the fact that expression of fluorescent
279 proteins (e.g., **GFP**, **YFP**) in transgenic mouse lines is often driven by promoters that initiate
transcription after synaptogenesis has already been completed in neocortex; for example, cortical expression of **YFP** in Thyl-eYFP-H mice occurs around postnatal day (P) 21 (Feng et al. 2000; Porrero et al. 2010)). IUE can also achieve potent transduction of fluorescent proteins through the use of constitutively active promoters such as pCAG or other CMV variations (Saito and Nakatsuji 2001); this is particularly useful for deep tissue imaging with *in vivo* TPM. Following IUE, mice can be imaged from perinatal development through adulthood (Cruz-Martin et al. 2010). Another problem with transgenic lines is that layer specificity is limited by the fidelity of the promoter itself and specific Cre lines are not yet available for desired cell types or brain regions, or they may have off target expression. In contrast, IUE at different embryonic stages can be used to target different cortical layers in different locations. Furthermore, tailoring DNA plasmid constructs to a particular experimental design is less expensive and less time-consuming than generating new mouse lines. Additionally, co-labeling cells with multiple fluorophores using IUE can easily be achieved by co-injecting multiple plasmids or by using bi-cistronic promoters (e.g., P2A (Kim et al. 2011)). It is also possible to design plasmids to express opsins or DREADD constructs, to genetically manipulate subpopulations of neurons both constitutively and conditionally (Takahashi et al. 2002; Matsuda and Cepko 2004, 2007; Yasuda et al. 2006; Huber et al. 2008; Manent et al. 2009). IUE also affords significant flexibility because the level of expression can be controlled by varying the voltage delivery, concentration of the plasmid, and the volume injected. Of note, IUE may not be compatible with the expression of fluorescent calcium indicators (GCaMP6) as anecdotal reports suggest that few if any neurons survive postnatally, presumably due to some toxicity from calcium buffering.

In conclusion, IUE is a powerful method for the expression of proteins in the early postnatal brain and into adulthood, especially for layer-specific cortical neurons.

304
## 2) Interrogating neural signals

### 2.1 Calcium imaging

The ability to measure changes in ion levels in living tissues with fluorescent microscopy offers many possibilities for scientific investigations (cf. Table 6). Across cell types and within multiple intracellular compartments, calcium ions ($Ca^{2+}$) play a variety of important roles, including cell cycle regulation, gene transcription modulation, intracellular signaling, muscle contraction and neurotransmission (Grienberger and Konnerth 2012). Action potentials in neurons result in massive influxes of $Ca^{2+}$ through voltage-gated channels, as well as the release of $Ca^{2+}$ from intracellular stores (Kandel et al. 2000), and fluctuations in free $Ca^{2+}$ in the presynaptic and postsynaptic compartments contribute to activity-dependent plasticity (Grienberger and Konnerth 2012). Because changes in the level of intracellular $Ca^{2+}$ are a robust indicator of action potential firing in neurons, fluorescent $Ca^{2+}$ indicators have become powerful tools for recording neural activity with excellent spatial and temporal resolution. Additionally, different types of $Ca^{2+}$ signaling events have been studied in astrocytes (Srinivasan et al. 2015) and in cardiomyocytes (Herron et al. 2012).

In general, $Ca^{2+}$ imaging relies on a fluorescent sensor compound that is introduced into neurons (or other cells) and that, when bound to $Ca^{2+}$, changes its fluorescent properties. The two primary classes of $Ca^{2+}$ indicators are the synthetic chemical indicators and the genetically encoded indicators. The chemical calcium indicators (e.g., **Fura-2**, **Indo-1**, **Fluo-4**, **Oregon Green BAPTA-1**) were pioneered by Roger Tsien's group and utilize a synthetic $Ca^{2+}$ chelator combined with a fluorophore (Grynkiewicz et al. 1985; Tsien et al. 1985; Brain and Bennett 1997; Gee et al. 2000). When $Ca^{2+}$ binds to the chelator site, the molecule undergoes a conformational change that alters the spectrum of emitted fluorescence
(Grienberger and Konnerth 2012). **Fura-2** is excited by ultraviolet wavelengths, produces peak fluorescence at 505-520 nm, and has relatively fast kinetics (Tsien et al. 1985). Under two-photon excitation, **Fura-2** fluorescence decreases as [Ca²⁺] increases, producing decreases in fluorescence intensity during neuronal activity. In contrast, the fluorescence emitted by **Fluo-4** and **Oregon Green BAPTA-1** increases above its baseline as [Ca²⁺] increases during action potential firing.

The genetically encoded Ca²⁺ indicators (GECIs) use a Ca²⁺ binding protein, such as calmodulin or troponin, instead of a chelator like BAPTA. Since the discovery of the green fluorescent protein, scientists have generated an array of sensors combining **GFP** variants with Ca²⁺-binding proteins. The GECI subcategory of cameleons (Miyawaki et al. 1997), is perhaps the most popular amongst GECIs, but other varieties exist based on troponin-C as the Ca²⁺-binding protein (Mank et al. 2008). Yellow Cameleon (Nagai et al. 2004) utilizes Förster resonance energy transfer (FRET) between two different fluorescent proteins, linked by calmodulin and calmodulin binding peptide M13. Upon calmodulin binding to Ca²⁺, the conformational change brings the two fluorophores – one **ECFP** and one **Venus-YFP** – close enough to result in activation of the yellow, resulting in a measurable change in the cyan:yellow fluorescence ratio (Nagai et al. 2004; Grienberger et al. 2014).

For *in vivo* two-photon Ca²⁺ imaging, the most frequently used GECI is the cameleon-based **GCaMP** variety, which utilizes a single circularly permuted green fluorophore (GFP) attached to calmodulin and the M13 peptide, and is maintained in a low fluorescence state when Ca²⁺ is not bound (Nakai et al. 2001). Ca²⁺ binding to calmodulin causes a conformational shift that changes the solvent exposure of the **GFP** and allows a fluorescence increase (Chen et al. 2013). Earlier versions of **GCaMP** indicators had relatively low slow on-off kinetics and signal-to-noise ratio, which could however be improved by 3D Block-Matching filtering (Danielyan et al. 2014). More recently, the development of the
353 "ultrasensitive" **GCaMP6** has improved neuronal event detection capability to single-spike
354 resolution, though the off-kinetics remain somewhat slow (Chen et al. 2013). Typical
355 expression methods for GECIs include viral transduction (Chen et al. 2013), with the
356 associated limitation of eventual cytotoxicity caused by long-term calcium sequestration; and
357 transgenic mice expressing **GCaMP** (Zariwala et al. 2012; Chen et al. 2012; Dana et al.
358 2014). Finally, it is important to note that continual improvements have also been made in
359 red-shifted GECIs (Looger and Griesbeck 2011), with the most recent iterations being
360 **jRCaMP1a**, **jRCaMP1b**, and **jRGECO1a** (Dana et al. 2016). Further developments in these
361 latter GECIs will allow neuroscientists to record from even deeper brain structures, due to the
362 reduced scattering of longer-wavelength excitation light.
363

363

364 2.2 Sodium imaging

365 Another important ion that can be measured intracellularly is Na⁺. In contrast to Ca²⁺
366 indicators, Na⁺ indicators are designed to measure Na⁺ concentration in millimolar ranges and
367 therefore these dyes have significantly lower affinity. A commonly used indicator is **SBFI**
368 that is excitable in the UV range and has ratiometric properties similar to **Fura** indicators.
369 This indicator has been used to measure Na⁺ in neurons (Myoga et al. 2009) and astrocytes
370 (Langer and Rose 2009). An alternative indicator excitable with blue light is **Sodium Green**
371 that was also used to measure Na⁺ in neurons (Senatorov et al. 2000). More recently, a greater
372 sensitivity for fast Na⁺ changes in neuronal axons was found for the green excitable indicator
373 **ANG-2** (Miyazaki and Ross 2015).
374

374

375 2.3 Voltage-sensitive dyes
One problem with Ca²⁺ imaging is that the kinetics of the dyes, on the order of hundreds of milliseconds or seconds, are orders of magnitude slower than the duration of typical action potentials. As a result, one cannot record neural activity with precise temporal resolution, which is critical for phenomena like spike timing dependent plasticity. Ideally, one would want to record changes in membrane potential (Vₘ), using either organic (cf. Table 6) or genetically encoded voltage sensors (GEVS), which have exquisite temporal resolution. *In vivo* voltage-sensitive dye (VSD) imaging from large cell populations in the anesthetized mammalian brain was developed in the nineties (Shoham et al. 1999; Petersen et al. 2003; Grinvald and Hildesheim 2004). This approach is sometimes coupled with intracortical microstimulation and electrode recordings, and requires either injection or topical application (Murphy et al. 2008) of oxonol VSDs, such as **RH-1692**. These have been designed to absorb light in the red region and are therefore outside the absorption band of haemoglobin (which causes pulsation and hemodynamic noise in brain recordings). More recently, styryl VSDs with similar spectral properties were developed (Zhou et al. 2007). The techniques of *in vivo* VSD imaging from large cell populations, using oxonols dyes, further progressed until enabling recordings from the barrel cortex of awake head-fixed mice (Poulet and Petersen 2008) or from freely moving animals (Ferezou et al. 2006).

Among the other *in vivo* applications of VSD imaging, it is important to mention the studies on embryonic developing nervous systems (Kamino et al. 1989). For this application, absorption VSDs such as NK2429 (Fujii et al. 1981) are typically used, since the high translucency of embryonic tissue allows high-sensitivity absorption measurements (Momose-Sato et al. 2001). To achieve *in vivo* Vₘ imaging with cellular or subcellular resolution, two-photon excitation can be used. To this purpose, the two-photon cross-sections of several styryl VSDs were measured (Fisher et al. 2005). Action potentials from mammalian nerve terminals were then recorded in an *ex vivo* preparation, the neurohypophysis (*pars nervosa*), using the
401 VSD **di-3-ANEPPDHQ** (Fisher et al. 2008). More recently, some novel fluorinated VSDs
402 (Yan et al. 2012) that appear to be more photostable when excited by two photon were
403 developed, and have been used to resolve action potentials from dendritic spines in brain
404 slices (Acker et al. 2011).

405 In many cases, *in vivo* two-photon V<sub>m</sub> imaging requires the topical application of two-photon
406 suitable VSD (cf. Table 1) after either craniotomy (Murphy et al. 2008). This challenging
407 approach is highly rewarding as it allows V<sub>m</sub> imaging during wakefulness after topical
408 administration of **ANNINE-6** (Kuhn et al. 2008), opening the door for simultaneous V<sub>m</sub>
409 imaging and behavioral tests.

410 In summary, *in vivo* V<sub>m</sub> imaging using organic indicators has several practical limitations
411 associated with dye loading, access to small structures, and stability of recordings. In terms of
412 future prospective, most of these limitations can be overcome by replacing organic indicators
413 with GEVS that can be expressed *in vivo* by viral transduction (Marshall et al. 2016). The first
414 generation of GEVS was developed by mutating the *Drosophila* Shaker potassium channel
415 and fusing it to a **GFP** protein (Siegel and Isacoff 1997). While good optical responses to V<sub>m</sub>
416 changes could be obtained by expressing the sensor in oocytes, the protein could not be
417 expressed in the plasma membrane of mammalian neurons and therefore a second generation
418 of GEVS was developed (Dimitrov et al. 2007). These GEVSs, now expressed in neuronal
419 outer membranes, were based on the voltage-sensitive phosphatase from the sea squirt, *Ciona
420 intestinalis*, fused to a **CFP** and **YFP** FRET pair (Lundby et al. 2008). From these pioneering
421 works, new GEVS based either on single FRET pairs (Jin et al. 2012) or on **GFP** probes (St-
422 Pierre et al. 2014) have been more recently developed with faster responses and enhanced
423 sensitivity, opening the gate to future explorations of activity in the living brain.
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## 2.4 Optogenetics actuators

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Optogenetic technology has become an essential tool to study the structure and the function of the neural circuits underlying behavior and cognition. Using photosensitive microbial opsin genes expressed into genetically defined neurons, optogenetics provides millisecond-precision control —activation or inhibition— of defined circuit elements in intact organisms with light (reviewed by Deisseroth (Deisseroth 2015)). Recent developments have provided a large diversity of excitatory and inhibitory opsins that are sensitive to different wavelengths. For instance, red-light-activated opsins (such as C1V1, ChRimson) allow simultaneous activation of neurons and imaging of neuronal activity with the green genetic probe GCaMP.

Optogenetic tools have been upgraded to achieve two-photon manipulation of neuronal populations at the single-cell resolution. The red-light-activated C1V1 opsin allows the robust generation of precise and fast spike trains using 1,040-nm light and standard raster-scanning light delivery (Prakash et al. 2012). This tool can also be used in combination with two-photon imaging of GCaMP probe using 920-nm light (Rickgauer et al. 2014; Packer et al. 2015). Inhibitory opsins such as eNpHR3.0 have also proven to be efficient for neuronal inhibition using 1,040 nm light (Prakash et al. 2012). New illumination methods now exist to improve opsin activation, such as spiral scanning, temporal focusing and holography-based patterned light illumination (Papagiakoumou et al. 2013). Thus, combining optogenetics with imaging technologies opens new avenues to all-optical interrogation of neuronal circuits with closed-loop manipulation of neurons in real time (Emiliani et al. 2015).
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## 2.5 Spectral properties of endogenous molecules

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Utilizing the intrinsic spectral properties of the target tissue, when possible, places the experimenter in a very favorable situation by avoiding the complicated, invasive, and/or possibly bias-inducing administration and binding of exogenous fluorescent probes.

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Many, if not all endogenous molecules display a certain capacity of two-photon excitation, though this excitation is generally rather inefficient. What appears in most cases to produce an annoying background noise does carry some meaningful information. The two-photon action cross-section spectra of several intrinsic molecules (among which **NADH**, **riboflavin**, **folic acid**, **cholecalciferol**, **pyridoxine**, and **retinol**) has been assessed in the early 2000s by the laboratory of Watt W. Webb at Cornell (Zipfel et al. 2003a), facilitating the two-photon- based analysis of metabolism (cf. Table 7). Investigating cell dysfunction in a number of pathologies is made possible through the measurement of the fluorescence decay using fluorescence lifetime imaging (FLIM) of metabolites. For instance, **NADH** FLIM- experiments allowed a better characterization of tumor-associated microglia phenotypes (Bayerl et al. 2016), unveiled the role of astrocytes in chronic neuroinflammation-related neuronal death (Mossakowski et al. 2015; Radbruch et al. 2016), and provided a label-free and non-invasive mean to identify neuron- or glial- biased progenitors (Stringari et al. 2012).

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Moreover, simultaneous FLIM-based detection of several metabolites like **NADH** and **FAD** with SHG can be achieved through wavelength mixing (Stringari et al. 2017) (for more details, see section *Designing a microscopy setup for intravital multicolor TPM*).

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Although not endogenous, it is worth mentioning the very few instances of therapeutic agents whose two-photon spectral characteristics are known: the fluoroquinolone antibiotics

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**gatifloxacin** and **moxifloxacin** (Lee et al. 2016) (cf. Table 5), and **quinacrine** (Bestvater et al. 2002) which stains nucleic acids (cf. Table 8) while having several therapeutic indications (Wallace 1989; Eriksson et al. 2015; Lippes 2015).

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3) Combining fluorescent probes for multicolor TPM

475

3.1 Designing a multicolor animal model

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The first point to consider when designing an intravital multicolor TPM experiment is the co-
labeling of multiple targets in the biological sample. Such labeling can result from crossing
transgenic mice that express fluorescent proteins in different cells or structures of interest. For
instance, triple transgenic fluorescent mice were described and successfully involved in
intravital multicolor TPM experiments (Fenrich et al. 2013; Ricard and Debarbieux 2014).

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However, producing such animals requires many crossings that considerably delay their use
and increase the cost of the experiment. Another approach to multicolor imaging is the
Brainbow transgenic mouse, which takes advantage of Cre/lox recombination to stochastically
express different fluorescent proteins in a cell population. As a consequence, each cell
randomly express a combination of fluorescent proteins and thus can be followed individually
(Livet et al. 2007; Weissman and Pan 2015). Different probes can be used to highlight
structures and/or functions (e.g., VSD or calcium-sensitive dyes) (Akemann et al. 2013;
Shigetomi et al. 2013, 2016; Xu et al. 2017).

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Taking advantage of the intrinsic properties of endogenous molecules is an elegant way to
investigate biological tissues without the drawbacks associated with the administration,
binding and possibly metabolize of exogenous molecules. Second-harmonic generation
(SHG) can be used to visualize not only the meninges via type-I or -III collagen imaging
(Williams et al. 2005; Ricard et al. 2007; Keikhosravi et al. 2014; Ricard and Debarbieux
2014), but also membrane potential (Rama et al. 2010; Loew and Lewis 2015). Third-
harmonic generation (THG) highlights water-lipids and water-proteins interfaces (Débarre et
al. 2006; Weigelin et al. 2016) and was successfully tested in vivo to image neurons, white-
matter structures, and blood vessels simultaneously (Witte et al. 2011). Both SHG and THG

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require no staining at all and are observed at half or one-third of the excitation wavelength respectively. Beside the respective specificity of SHG and THG, they have been fruitfully used to record morphological landmarks and help data registration during longitudinal *in vivo* imaging of neural zebrafish stem cells (Dray et al. 2015). Autofluorescence does arise from molecules and structures under specific excitation wavelengths (Zipfel et al. 2003a; Ricard et al. 2012). At best autofluorescence may carry relevant information, and at worst, being aware of it may help achieve higher contrast between the background and structures of interest by choosing fluorophores accordingly. It must be noted that autofluorescence signals are not very bright in intravital conditions (cf. Table 7) and were mainly described in explants or tissue slices. Due to the low intensity of endogenous signals, one could be tempted to increase the laser power. However, this usually causes artifacts to appear, whose monitoring can help in evaluating photodamage induced during the experiment (Galli et al. 2014).

The preparation of a biological sample for intravital multicolor TPM often requires combining different approaches to label a maximal number of structures of interest involved in a complex process. For example, using Thy1-CFP/LysM-GFP/CD11c-EYFP triple transgenic mice intravenously injected with **Rhodamine B** dextran or Quantum-dots 655, Fenrich *et al.* have revealed a differential spatiotemporal recruitment of myelomonocytic cells after a spinal cord injury (Fenrich *et al.* 2013). Recently, Ricard *et al.* have described the combination of a LysM-EGFP/CD11c-EYFP mouse implanted with **DsRed**-expressing glioblastoma cells and intravenously injected with **Cascade Blue** dextran in order to study the recruitment of immune cells during glioblastoma progression (Ricard *et al.* 2016b).

The development of the co-staining protocol of a biological sample to be used for intravital multicolor TPM must follow some guidelines:

1) Spectral overlap of the emission spectra of all of the utilized fluorophores must be minimal,
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2) Utilized fluorophores must not bias physiological and biological properties of the sample nor the pathological condition that is observed,

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3) As multiple-fluorophore-expressing animals are difficult to produce, the experimental design should take into account the risk of a downsized animal cohort.

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The next point to consider, when multicolor TPM is required for an experiment, is the microscopy setup (cf. Figure 1). Excitation spectra of the fluorophores are the first elements to take into account. The majority of blue-, green- and red-emitting fluorophores can be excited with a Ti:Sapphire femtosecond laser, as its emission wavelength is generally tunable in between 700 and 1,040 nm. When possible, it is advisable to use a single excitation wavelength and tune precisely the gain of detectors associated with each fluorophore. The laser power should be kept as low as possible and the experiment duration as short as possible, to limit photobleaching and phototoxicity. This is essential for multicolor timelapse experiments (Fenrich et al. 2013; Ricard et al. 2016b), in which the same region is scanned over and over, at the risk of exposing the tissue to an energy that would threaten its health and/or integrity. When different excitation wavelengths are required (for example, when both Cascade Blue with $\lambda_{ex} = 800$ nm and eGFP with $\lambda_{ex} = 940$ nm are present in the same biological sample), a sequential acquisition or the simultaneous use of two Ti:Sapphire femtosecond lasers is required. Continuous sequential acquisition (for example, for calcium imaging recordings) increases the total acquisition time of the images, which is of concern as far as preventing photodamage and prolonged exposure of the animal to anesthetics (if applicable), or depending on the characteristic time of the studied phenomenon.

Deep-red fluorophores require higher excitation wavelengths that cannot be delivered by Ti:Sapphire femtosecond lasers alone. Typically, they are excited by Ytterbium lasers (1,040 nm) but the addition of an OPO (Herz et al. 2010) pumped by a Ti:Sapphire femtosecond laser can enable excitation wavelengths ranging from 1,050 to 1,300 nm when pumped at 800 nm. Simultaneous utilization of both a Ti:Sapphire femtosecond laser and an OPO is achievable. Interestingly, it enables the simultaneous two-photon excitation of three fluorophores with distinct absorption spectra insofar as the pulses of the laser and OPO are
synchronized. The excitation of the three fluorophores is done by the femtosecond laser, the OPO and by their spatiotemporal overlap that produces a third two-photon excitation. With such a wavelength mixing, **CFP**, **YFP** and **tdTomato** – having distinct two-photon absorption spectra – can be simultaneously excited. Biological phenomena such as cell movements in embryonic tissues were thereby monitored over time using Brainbow constructs (Mahou et al. 2012). Endogenous metabolites such as **NADH** and **FAD** can also be detected by FLIM, simultaneously with the SHG of surrounding tissues, using a wavelength mixing approach (Stringari et al. 2017). In this case, two-photon excitations are produced by the synchronization of two excitation beams at 760 nm (**NADH** and **FAD**) and 1041 nm that creates a third (virtual) wavelength at 879 nm (**FAD**) (cf. Figure 2).

More recently, the efficient detection of up to 7 tissue compartments (five fluorophores, SHG from collagen, and autofluorescence) has been reported using wavelength mixing combined with both a broad set of fluorophores (cf. Figure 3) and a dedicated spectral unmixing algorithm (Rakhymzhan et al. 2017) (for more details, see section *Image processing*).

The next element to consider is the fluorescence collection. Fluorescence photons are nearly always collected in non-descanned mode in intravital TPM, i.e., without passing back through the scanning mirrors. They are instead reflected on a dichroic mirror situated between the objective and scanning mirrors, and are directed towards photomultiplier tubes (PMT), also known as non-descanned detectors (NDDs). In multicolor TPM, a number of NDDs is used. Fluorescence photons are discriminated according to their wavelengths using dichroic mirrors and filters. With such a setup, fluorescence arising from different fluorophores can be simultaneously collected on distinct detectors. Fluorescence intensity varies between the different used fluorophores according to parameters such as their quantity, their two-photon absorption cross-section ($\sigma_2$) and quantum yield ($\phi$), the product of which defining the two-photon action cross-section ($\sigma_2\phi$) listed in Tables 2-8. The emission wavelength of a
578 fluorophore is another parameter influencing the collected intensity when put into perspective
579 with the NDD response curve, high-energy blue photons being more absorbed than low-
580 energy red photons in biological tissues (König 2000). When a single excitation is used, the
581 laser intensity delivered to each of the fluorophores at the same observation depth will be
582 identical. NDD gain should be adjusted accordingly for each of the fluorophores in order to
583 enhance the signal over noise ratio, while avoiding saturating the detectors. When one expects
584 a specific fluorescence signal to be low, more efficient PMTs such as Gallium Arsenide
585 Phosphide (GaAsP) detectors should be considered (Becker et al. 2011).

586 Multicolor intravital TPM can benefit from the use of spectral chips, composed of an array of
587 PMTs and a prism or diffraction grating to separate the fluorescence photons (Im et al. 2010;
588 Shi et al. 2012, 2015; Zimmermann et al. 2014). Spectral segmentation of the wavelengths
589 arising for the different fluorophores will be thereby both more accurate and easier to achieve.
590 Although such chips are already available on commercial confocal microscopes, they are
591 positioned on the descanned path that is less suitable for intravital applications. Spectral chips
592 in a non-descanned mode are required, and recent advances in non-descanned collection of
593 fluorescence photons by optical fibers may help develop this approach (Ducros et al. 2011).

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## 3.3 Image processing

597

Multicolor intravital timelapse TPM generates large amounts of data. The aim of the post-processing steps is to extract quantitative data and relevant characterization of the phenomenon of interest from multicolor acquisition.

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When required, the first step is to perform spectral unmixing (Zimmermann et al. 2002; Neher and Neher 2004; Ducros et al. 2009). Even though the emission spectra of all of the fluorophores used in the experiment do not peak at the same wavelengths, there is generally a certain overlap of the spectra. As a consequence, the signal collected on one NDD contains a major contribution from one fluorophore and minor contributions from the others. It is possible to overcome this problem and to clean the image to retain only the contribution of the major fluorophore. To perform this spectral unmixing (a.k.a., spectral deconvolution), the contribution of each of the fluorophores used in the experiment in each of the NDD must be measured. Then, using dedicated algorithms based on maximum-likelihood unmixing (Davis and Shen 2007), each image from each NDD can be spectrally unmixed and then analyzed (Thaler and Vogel 2006; Brenner et al. 2013; Zimmermann et al. 2014). As an example of the crucial importance of spectral unmixing, Ducros et al. have used it to detect small spectral variations of odor-evoked FRET transients up to 250 µm in the olfactory bulb of living mice (Ducros et al. 2009).

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In another instance of multicolor intravital TPM experiment, Ricard et al. have recently proposed the 6-color intravital TPM of brain tumors (Ricard and Debarbieux 2014). They designed a triple transgenic Connexin43-CFP/Thyl-GFP/CD11c-YFP mouse model enabling the simultaneous observation of astrocytes, neurons, and microglia/dendritic cells, respectively. Mice were grafted under a chronic cranial window with glioblastoma cells expressing DsRed. Blood vessels were highlighted by an intravenous delivery of Cascade Blue dextran. Meninges were observed using SHG. Images were acquired on a microscope
equipped with 5 NDDs under a sequential excitation at 800 and 940 nm. This sequential
acquisition allows a discrimination of **CFP** and **Cascade Blue** signals as their two-photon
excitation spectra are different, even though their emission spectra strongly overlap. After
spectral unmixing, analysis revealed in particular significant alterations of cell motility in the
peritumoral area.

The usefulness of spectral unmixing algorithms has become even clearer with the successful
attempt to simultaneously detect up to 7 tissue compartments using two two-photon excitation
sources and 6 NDDs (Rakhymzhan et al. 2017). In order to do this, the authors of this work
developed a dedicated pixel-based algorithm based both on similarity measurements between
overlapping fluorophores and on the spectral fingerprints of the individual fluorophores. As a
result, the ‘SIMI’ algorithm enables the separation of more fluorophores than available
channels (cf. Figure 4). This protocol has been used in murine lymph nodes to simultaneously
detect *in vivo* lymphocytes labelled with **Hoechst**, **CFP**, hrGFP, **YFP**, or **DsRed**, plus SHG
and autofluorescence from macrophages.
635 **Conclusion**

636 Intravital TPM is a powerful tool to visualize biological phenomena with a subcellular
637 resolution in a physiological environment. Multicolor TPM experiments make the most of the
638 presence of all the actors – known or yet unknown – exhaustively involved in the complex
639 processes that characterize brain functions. The design of intravital multicolor TPM
640 experiments is, however, hindered at different stages following the identification of the
641 biological targets of interest: choice of suitable fluorophores, choice of appropriate routes of
642 delivery of these fluorophores, and design of the setup allowing simultaneous detection of
643 various fluorophores.

644 This review was intended to reduce these hurdles by providing a comprehensive list of two-
645 photon-suitable probes along with their spectral properties and biological specificities (cf.
646 Tables 2 to 8), a description of different routes of *in vivo* delivery of these fluorophores (cf.
647 Table 1), recommendations for the design of intravital multicolor TPM microscope setups,
648 and a discussion about strategies of data post-processing. Taken together, this database and set
649 of recommendations will help scientists design intravital TPM experiments focusing
650 simultaneously on biological targets of diverse natures, ranging from cells (e.g., neurons,
651 astrocytes) and sub-cellular structures (e.g., DNA, organelles) to functional processes – whose
652 exploration greatly benefits from the optogenetics technology – (e.g., ion transport, membrane
653 potential), and through chemical or environmental parameters (e.g., mechanical strains, pH)
654 or even potentially connectomics (Nemoto et al. 2015).

655 Extending beyond the current trends in neuroscience, this comprehensive two-photon probe
656 database, as well as the resources related to intravital multicolor TPM, is intended to broaden
657 the use of TPM not only in neuroscience, but also to other fields of biology in which the full
658 extent of this technology's capabilities has not yet been revealed.
Figures 659

660

**Fig. 1** Optical setup for multicolor two-photon microscopy

DC: dichroic mirror; NDD: non-descanned detector; OPO: optical parametric oscillator.

¹: Dichroic mirror used to collect fluorescent photons on five non-descanned detectors.

664
Excitatory infrared photons pass through the mirror whereas fluorescence photons are
665
reflected. This mirror must be removed to collect photons in descanned mode.

666
²: Dichroic mirror used to collect fluorescent photons on a spectral chip in descanned mode.

667
Modified from (Ricard and Debarbieux 2014).

668

669 **Fig. 2** Wavelength mixing–fluorescence lifetime imaging of endogenous fluorophores

670 When the excitation beams λ₁ = 760 nm and λ₂ = 1041 nm are synchronized (Δt = 0), a third
671 virtual wavelength for two-photon excitation λᵥ = 879 nm is created by wavelength mixing. A
672 time-correlated single photon counting system (TCSPC) is used to perform FLIM.

673
Originally published in *Scientific reports* (Stringari et al. 2017) under a Creative Commons
674
Attribution 4.0 International License [http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/).

675

676 **Fig. 3** Wavelength-mixing optimal combination of two sets of fluorophores

677 Two-photon excitation and emission spectra of two sets of fluorophores that can be efficiently
678
excited by wavelength mixing with λ₁ = 850 nm and λ₂ = 1230 nm (full arrows), resulting in
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λᵥ = 1005 nm (dashed arrow). (a) **CFP**, **eGFP**, **mOrange2**, **mKate2**, **eqFP670**. (b) **Hoechst**,
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**eGFP**, **Kusabira Orange**, **CMTPX Red**, **Alexa 647**, **Atto 680**.

681
Originally published in *Scientific reports* (Rakhymzhan et al. 2017) under a Creative

682
Commons Attribution 4.0 International License [http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/).
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**Fig. 4** Example of similarity unmixing of more fluorochromes than available channels

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(a) Images of cells labelled with several fluorophores, showing crosstalk in two detection

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channel. (b) Extraction of a relative signal distribution in the two channels pixels by pixel,

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corresponding to . (c) The algorithm calculates similarities between the known fingerprints of

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each fluorophore and the signature of undefined fluorophores extracted during step (b). (d)

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Color separation based on the ratios between the fluorophore fingerprints.

690

Originally published in *Scientific reports* (Rakhymzhan et al. 2017) under a Creative

691

Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

692
**Table 1** Routes of administration of fluorochromes for intravital two-photon microscopy of

brain cells, structures, and functions.

<table><thead><tr><th>Technique</th><th>Target</th><th>Probe</th></tr></thead><tbody><tr><td>Single-cell electroporation</td><td>Diverse (e.g. neurons (Liu and Haas 2011))</td><td>Diverse</td></tr><tr><td>In utero electroporation (Wang and Mei 2013)</td><td>e.g. layer 2/3 cortical neurons (Saito and Nakatsuji 2001)</td><td>e.g. eGFP</td></tr><tr><td>Intraperitoneal administration</td><td>Amyloid-β plaques</td><td>e.g. SAD1 (Heo et al. 2013)</td></tr><tr><td rowspan="4">Intravenous administration</td><td>Astrocytes</td><td>Sulforhodamine 101 (Nimmerjahn et al. 2004), sulforhodamine B (Vérant et al. 2013)</td></tr><tr><td>Blood vessels</td><td>e.g. Rhodamine B dextran, quantum-dots (Ricard et al. 2016a)</td></tr><tr><td>Arteries</td><td>Alexa Fluor 633 (Shen et al. 2012)</td></tr><tr><td>Amyloid-β plaques</td><td>e.g. DCIP-1 (Zhu et al. 2017)</td></tr><tr><td rowspan="4">Viral transduction (Nassi et al. 2015)</td><td>Spatially-restricted (e.g. axonal domain of neurons (Tervo et al. 2016)) and genetically-defined cells (e.g. oligodendrocytes (Powell et al. 2016))</td><td>Diverse</td></tr><tr><td>Calcium activity</td><td>Genetically encoded Ca<sup>2+</sup> indicators (GECIs)</td></tr><tr><td>Membrane potential (V<sub>m</sub>)</td><td>Genetically encoded voltage sensors (GEVs)</td></tr><tr><td>Ion activity (neurons, astrocytes (Reeves et al. 2011))</td><td>Ion indicators (e.g. Fura-2-AM, Fluo-4-AM, Oregon Green BAPTA-1 (Garaschuk et al. 2006))</td></tr><tr><td rowspan="2">Whole-cell and bulk loading</td><td>Membrane potential (V<sub>m</sub>)</td><td>Voltage-sensitive dyes (e.g. ANNINE-6 (Kuhn et al. 2008), RH-1692 (Murphy et al. 2008))</td></tr><tr><td></td><td></td></tr></tbody></table>
**Table 2** Biophysical properties of two-photon-suitable non-specific probes: peak wavelength of two-photon action cross-section ($\lambda_{2PA}$); peak two-photon action cross-section ($\sigma_2\phi$); peak wavelength of molecular brightness ($\lambda_{\epsilon_{max}}$); peak molecular brightness ($\epsilon_{max}$); fluorescence wavelength ($\lambda_{fluo}$). Probes discussed in the text are in bold.

702 (1): calculated from the $\sigma_2$ and $\phi$ values

703 (2): data from commercial provider

704 *: data from http://www.drbio.cornell.edu/cross sections.html (accessed 10/24/2017)

<table><thead><tr><th>Probe</th><th>λ<sub>2PA</sub> [nm]</th><th>σ<sub>2</sub>φ [GM]</th><th>λ<sub>ε_m</sub> ax [nm]</th><th>ε<sub>max</sub> [kcps m]</th><th>λ<sub>fluo</sub> [nm]</th><th>Comment</th><th>Reference</th></tr></thead><tbody><tr><td>— Pond 2002 Derivative 1</td><td>830</td><td>1207 (1)</td><td></td><td></td><td>536</td><td>Hydrophobic</td><td>Figure 3(1) in (Pond et al. 2002)</td></tr><tr><td>— Pond 2002 Derivative 2</td><td>830</td><td>1427 (1)</td><td></td><td></td><td>528</td><td>Hydrophobic</td><td>Figure 3(2) in (Pond et al. 2002)</td></tr><tr><td>— Pond 2002 Derivative 3</td><td>790</td><td>2.67 (1)</td><td></td><td></td><td>504</td><td>Hydrophobic</td><td>Figure 3(3) in (Pond et al. 2002)</td></tr><tr><td>— Pond 2002 Derivative 4</td><td>825</td><td>11 (1)</td><td></td><td></td><td>510</td><td>Hydrophobic</td><td>Figure 3(4) in (Pond et al. 2002)</td></tr><tr><td>— Sadowski 2017 Derivative 4a</td><td>740</td><td>112</td><td></td><td></td><td>671</td><td></td><td>Figure 3 in (Sadowski et al. 2017)</td></tr><tr><td>— Sadowski 2017 Derivative 4b</td><td>820</td><td>83</td><td></td><td></td><td>699</td><td></td><td>Figure 3 in (Sadowski et al. 2017)</td></tr><tr><td>— Sadowski 2017 Derivative 4c</td><td>740</td><td>70</td><td></td><td></td><td>662</td><td></td><td>Figure 3 in (Sadowski et al. 2017)</td></tr><tr><td>— Sadowski 2017 Derivative 5a (7a)</td><td>720</td><td>1450</td><td></td><td></td><td>633</td><td></td><td>Figure 3 in (Sadowski et al. 2017)</td></tr><tr><td>— Sadowski 2017 Derivative 5b (7c)</td><td>720</td><td>500</td><td></td><td></td><td>643</td><td></td><td>Figure 3 in (Sadowski et al. 2017)</td></tr><tr><td>— Sadowski 2017 Derivative 5c (7d)</td><td>860</td><td>340</td><td></td><td></td><td>736</td><td></td><td>Figure 3 in (Sadowski et al. 2017)</td></tr><tr><td>5C-TMR</td><td>830</td><td>135</td><td>850</td><td>31.5</td><td>580 (2)</td><td></td><td>Figure 5 in (Mütze et al. 2012)</td></tr><tr><td>7-amino-4-</td><td>703 &lt;</td><td></td><td></td><td></td><td>439 (2)</td><td></td><td>Figure 3 in</td></tr></tbody></table>
<table><tr><td>methylcoumarin</td><td>722 &gt;&gt; 863</td><td></td><td></td><td></td><td></td><td>(Bestvater et al. 2002)</td></tr><tr><td>Alexa Fluor 350</td><td>~715</td><td></td><td></td><td></td><td>442 (2)</td><td>Figure 5C in (Trägårdh et al. 2015)</td></tr><tr><td>Alexa Fluor 430</td><td>870</td><td>11.6</td><td>910</td><td>16</td><td>541 (2)</td><td>Figure 2 in (Mütze et al. 2012)</td></tr><tr><td>Alexa Fluor 488</td><td>940</td><td>~30</td><td></td><td></td><td>519 (2)</td><td>Figure 2 in (Anderson and Webb 2011)</td></tr><tr><td>Alexa Fluor 514</td><td></td><td></td><td>790, 960</td><td>~32, ~25</td><td>542 (2)</td><td>Figure 2 in (Mütze et al. 2012)</td></tr><tr><td>Alexa Fluor 546</td><td></td><td></td><td>820</td><td>58</td><td>573 (2)</td><td>Figure 2 in (Mütze et al. 2012)</td></tr><tr><td>Alexa Fluor 568</td><td></td><td></td><td>780</td><td>~25</td><td>603 (2)</td><td>Figure 2 in (Mütze et al. 2012)</td></tr><tr><td>Alexa Fluor 594</td><td></td><td></td><td>800</td><td>~32</td><td>617 (2)</td><td>Figure 2 in (Mütze et al. 2012)</td></tr><tr><td>Alexa Fluor 610</td><td></td><td></td><td>820</td><td>~28</td><td>628 (2)</td><td>Figure 2 in (Mütze et al. 2012)</td></tr><tr><td>Alexa Fluor 633</td><td></td><td></td><td>820</td><td>~24</td><td>647 (2)</td><td>Arteries (Shen et al. 2012)</td></tr><tr><td>Alexa Fluor 647</td><td>1240</td><td>~45</td><td></td><td></td><td>665 (2)</td><td>Figure 7 in (Kobat et al. 2009)</td></tr><tr><td>Alexa Fluor 680</td><td>1280</td><td>~75</td><td></td><td></td><td>702 (2)</td><td>Figure 7 in (Kobat et al. 2009)</td></tr><tr><td>Alexa Fluor 700</td><td>1300</td><td>~52</td><td></td><td></td><td>723 (2)</td><td>Figure 7 in (Kobat et al. 2009)</td></tr><tr><td>Aminomethyl coumarin acetate</td><td>700</td><td></td><td></td><td></td><td>445 (2)</td><td>– (Bok et al. 2015)</td></tr><tr><td>Ant-PHEA (in water)</td><td>800</td><td>2480</td><td></td><td></td><td>575 (2)</td><td>Figure 6 in (Mettra et al. 2016)</td></tr><tr><td>ATTO 590</td><td>790</td><td>~250 (NHS ester)</td><td></td><td></td><td>624 (2)</td><td>STED-compatible</td></tr><tr><td>ATTO 594</td><td>800</td><td>~220 (NHS ester), ~140 (antibodies)</td><td></td><td></td><td>627 (2)</td><td>STED-compatible</td></tr><tr><td>ATTO 647N</td><td>840</td><td>~270</td><td></td><td></td><td>669 (2)</td><td>STED-</td></tr></table>
<table><thead><tr><th></th><th></th><th>(NHS ester), ~120 (streptavidin)</th><th></th><th></th><th>compatibl e</th><th>(Velasco et al. 2015)</th></tr></thead><tbody><tr><td>ATTO 680</td><td>~1260</td><td></td><td></td><td>695 (2)</td><td>OPO-friendly</td><td>Figure 2D in (Rakhymzha n et al. 2017)</td></tr><tr><td>BODIPY (in water)</td><td>920</td><td>17.12</td><td></td><td>Variable</td><td></td><td>*</td></tr><tr><td>BODIPY 492/515 (in water)</td><td>920</td><td>14.3</td><td>920</td><td>47.4</td><td>515</td><td>Figure 5 in (Mütze et al. 2012)</td></tr><tr><td>BODIPY-FL (in DMSO)</td><td>920 &lt;&lt; 972</td><td></td><td></td><td></td><td>512 (2)</td><td>Figure 3 in (Bestvater et al. 2002)</td></tr><tr><td>BODIPY-TR</td><td>1080</td><td>242</td><td>1060</td><td>15.2</td><td>618 (2)</td><td>Figure 5 in (Mütze et al. 2012)</td></tr><tr><td>Brilliant Violet 421</td><td>710-1000</td><td></td><td></td><td></td><td>421</td><td>– (Figure 6) (Chattopadh yay et al. 2012)</td></tr><tr><td>Cascade Blue</td><td>740, 800</td><td>2.1 (at 750 nm)</td><td></td><td></td><td>420 (2)</td><td>Figure 7 in (Xu and Webb 1996)</td></tr><tr><td>CellTracker Blue</td><td>780</td><td></td><td></td><td></td><td>466 (2)</td><td>– (Zinselmeye r et al. 2009)</td></tr><tr><td>CellTracker Orange</td><td>820</td><td></td><td></td><td></td><td>565 (2)</td><td>– (Miller et al. 2002)</td></tr><tr><td>CellTracker Red</td><td>~1080</td><td></td><td></td><td></td><td>602 (2)</td><td>Figure 2D in (Rakhymzha n et al. 2017)</td></tr><tr><td>CFP</td><td>840</td><td>~180</td><td></td><td></td><td>485 (2)</td><td>Figure 3B in (Zipfel et al. 2003b)</td></tr><tr><td>CFSE</td><td>780</td><td></td><td></td><td></td><td>521 (2)</td><td>– (Miller et al. 2002)</td></tr><tr><td>Citrine</td><td>968</td><td>6.7</td><td></td><td></td><td>529 (Griesbec k et al. 2001)</td><td>Figure 1 in (Drobizhev et al. 2011)</td></tr><tr><td>Coumarin 307</td><td>800</td><td>15.3</td><td></td><td></td><td>490 (in ethanol) (2)</td><td>*</td></tr><tr><td>Cy2-IgG</td><td>837 &lt; 905 &gt; 981</td><td></td><td></td><td></td><td>505 (2)</td><td>Figure 4 in (Bestvater et al. 2002)</td></tr><tr><td>Cy3-IgG</td><td>1032</td><td></td><td></td><td></td><td>565 (2)</td><td>Figure 4 in (Bestvater et al. 2002)</td></tr></tbody></table>
<table><tr><td>Cy5.5</td><td>1280</td><td>~60</td><td></td><td>702 (2)</td><td>OPO-friendly</td><td>Figure 7 in (Kobat et al. 2009)</td></tr><tr><td>Dronpa-3</td><td>920</td><td></td><td></td><td>515</td><td>Reversible switchable</td><td>– (Ando et al. 2007; Kao et al. 2012)</td></tr><tr><td>dsRed</td><td>&gt; 990</td><td>108</td><td></td><td>583 (Shaner et al. 2008)</td><td></td><td>*</td></tr><tr><td>dsRed2</td><td>1050</td><td>73</td><td></td><td>587</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>E2-Crimson</td><td>1138</td><td>1.8</td><td></td><td>643</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>EBFP2.0</td><td>750</td><td>9.2</td><td></td><td>446</td><td></td><td>Figure 1 in (Drobizhev et al. 2011)</td></tr><tr><td>eCFP</td><td>857</td><td>12</td><td></td><td>476</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>eGFP (pH 8)</td><td>927</td><td>30</td><td></td><td>510</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>eqFP650</td><td>1112</td><td>8.5</td><td></td><td>646</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>eqFP670</td><td>1120</td><td>1.3</td><td></td><td>661</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>Evans Blue</td><td>850</td><td></td><td></td><td>680 (Saria and Lundberg 1983)</td><td></td><td>– (Bennewitz et al. 2014)</td></tr><tr><td>eYFP</td><td>960</td><td>25</td><td></td><td>527 (Merzlyak et al. 2007)</td><td></td><td>– (Table 2) (Blab et al. 2001)</td></tr><tr><td>Fluorescein (in water, pH = 11)</td><td>770</td><td>39</td><td>800</td><td>18.4</td><td>520 (Zhu et al. 2005)</td><td>Figure 5 in (Mütze et al. 2012)</td></tr><tr><td>Fluorescein isothiocyanate (FITC)</td><td>800</td><td></td><td></td><td></td><td>525 (2)</td><td>Figure 3B in (Wang and Yeh 2012)</td></tr><tr><td>GFP</td><td>800</td><td>6.5</td><td></td><td></td><td>504 (Chattoraj et al. 1996)</td><td>*</td></tr><tr><td>Hilyte Fluor 488</td><td>~815, 960</td><td>~55, ~30</td><td></td><td></td><td>525 (2)</td><td>Figure 2 in (Anderson and Webb 2011)</td></tr><tr><td>Katushka</td><td>1080</td><td>23</td><td></td><td></td><td>635</td><td>Figure S1 in</td></tr></table>
<table><tr><td></td><td></td><td></td><td></td><td>(Shcherbo et al. 2007)</td><td></td><td>(Drobizhev et al. 2011)</td></tr><tr><td>Katushka2</td><td>1140</td><td>27</td><td></td><td>633 (2)</td><td>OPO-friendly</td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>Kusabira Orange</td><td>~1110</td><td></td><td></td><td>561 (Karasawa et al. 2004)</td><td></td><td>Figure 2D in (Rakhymzha n et al. 2017)</td></tr><tr><td>Lissamine rhodamine</td><td>837 >> 1116</td><td></td><td></td><td>~580 (2)</td><td></td><td>Figure 4 in (Bestvater et al. 2002)</td></tr><tr><td>LSS-mKate1</td><td>920</td><td>~40</td><td></td><td>624</td><td></td><td>Figure 1E in (Piatkevich et al. 2010)</td></tr><tr><td>LSS-mKate2</td><td>920</td><td>~90</td><td></td><td>605</td><td></td><td>Figure 1E in (Piatkevich et al. 2010)</td></tr><tr><td>Lucifer Yellow</td><td>840</td><td>1.4</td><td></td><td>540 (2)</td><td></td><td>*</td></tr><tr><td>mAmetrine</td><td>809</td><td>40</td><td></td><td>526 (Ai et al. 2008)</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mBanana</td><td>1070</td><td>44</td><td></td><td>553 (Shaner et al. 2004)</td><td>OPO-friendly</td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mCardinal</td><td>>1080</td><td></td><td></td><td>659</td><td>OPO-friendly</td><td>Figure S3 in (Chu et al. 2014)</td></tr><tr><td>mCerulean</td><td>840</td><td>~75</td><td></td><td>475-503 (Ai et al. 2006)</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mCFP</td><td>840</td><td>187</td><td></td><td>475 (Shaner et al. 2005)</td><td></td><td>*</td></tr><tr><td>mCherry</td><td>1080 (Drobizhev et al. 2011), 1160 (Vadakk an et al. 2009)</td><td>6.4 (at 1080 nm)</td><td></td><td>610 (Shaner et al. 2008)</td><td>OPO-friendly</td><td>Figure S1 in (Drobizhev et al. 2011) and Figure 8 in (Vadakkan et al. 2009)</td></tr><tr><td>mCitrene</td><td>960</td><td>~320</td><td></td><td></td><td></td><td>Figure 3C in (Rizzo et al. 2006)</td></tr><tr><td>mCitrine (pH 8)</td><td>950</td><td>7.6</td><td></td><td>527</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mEGFP</td><td>960</td><td>~300</td><td></td><td>507 (Shaner et al. 2005)</td><td></td><td>Figure 3B in (Rizzo et al. 2006)</td></tr><tr><td>mGrape3</td><td>1140</td><td>1.6</td><td></td><td>645</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr></table>
<table><tr><td>mKate (pH 8)</td><td>1118</td><td>14</td><td></td><td>635 (Shcherbo et al. 2007)</td><td>OPO-friendly</td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mKate2</td><td>1140</td><td>30</td><td></td><td>633 (Shcherbo et al. 2009)</td><td>OPO-friendly</td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mKeima</td><td>~880</td><td>~70</td><td></td><td>620</td><td></td><td>Figure 1E in (Piatkevich et al. 2010)</td></tr><tr><td>mNeptune</td><td>1104</td><td>12</td><td></td><td>651 (Chu et al. 2014)</td><td>OPO-friendly</td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mOrange</td><td>1080</td><td>47</td><td></td><td>565</td><td>OPO-friendly</td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mOrange2</td><td>~1080</td><td></td><td></td><td>565 (Shaner et al. 2008)</td><td></td><td>Figure 2B in (Rakhymzha n et al. 2017)</td></tr><tr><td>mPlum</td><td>1105</td><td>2.9</td><td></td><td>644</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mRaspberry</td><td>1118</td><td>5.8</td><td></td><td>625 (Shcherbo et al. 2007)</td><td>OPO-friendly</td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mRFP</td><td>1080</td><td>13</td><td></td><td>611</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mStrawberry</td><td>1070</td><td>6.8</td><td></td><td>596 (Shaner et al. 2004)</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>mTangerine</td><td>1055</td><td>3.3</td><td></td><td>584</td><td></td><td>Figure S1 in (Drobizhev et al. 2009, 2011)</td></tr><tr><td>mVenus</td><td>960</td><td>~200</td><td></td><td>525 (Sarkar et al. 2009)</td><td></td><td>Figure 3C in (Rizzo et al. 2006)</td></tr><tr><td>mWasabi</td><td>927</td><td>7.3</td><td></td><td>508</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>Near-iRFP</td><td>1260</td><td></td><td></td><td>713</td><td>OPO-friendly</td><td>Figure S5 in (Filonov et al. 2011)</td></tr><tr><td>Neptune</td><td>1120</td><td>16</td><td></td><td>647</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>Pacific Blue</td><td>780</td><td></td><td></td><td>455 (2)</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr></table>
<table><tr><td>Peridinin<br>chlorophyll</td><td>850</td><td></td><td></td><td>678</td><td></td><td>– (Bok et al.<br>2015)</td></tr><tr><td>Phycoerythrin</td><td>1064</td><td>322</td><td></td><td>576 (2)</td><td></td><td>– (Chen et<br>al. 1997; So<br>et al. 2000)</td></tr><tr><td>QD550 (organic)</td><td>700-<br>1000</td><td>~2000</td><td></td><td>550</td><td>Broad<br>absorption<br>spectrum</td><td>Figure 1A in<br>(Larson et<br>al. 2003)</td></tr><tr><td>QD550 (water-<br>soluble)</td><td>700-<br>1000</td><td>~2000</td><td></td><td>550</td><td>Broad<br>absorption<br>spectrum</td><td>Figure 1A in<br>(Larson et<br>al. 2003)</td></tr><tr><td>QD567 (water-<br>soluble)</td><td>700-<br>1000</td><td>~10000</td><td></td><td>567</td><td>Broad<br>absorption<br>spectrum</td><td>Figure 1A in<br>(Larson et<br>al. 2003)</td></tr><tr><td>QD605 (water-<br>soluble)</td><td>700-<br>1000</td><td>47000</td><td></td><td>605</td><td>Broad<br>absorption<br>spectrum</td><td>Figure 1A in<br>(Larson et<br>al. 2003)</td></tr><tr><td>QD630 (organic)</td><td>700-<br>1000</td><td>~2000</td><td></td><td>630</td><td>Broad<br>absorption<br>spectrum</td><td>Figure 1A in<br>(Larson et<br>al. 2003)</td></tr><tr><td>Resorufin</td><td>1040</td><td>9</td><td>106<br>0</td><td>33.9</td><td>585 (2)</td><td>Figure 5 in<br>(Mütze et al.<br>2012)</td></tr><tr><td>Rhodamine 110</td><td>790</td><td>48</td><td>800</td><td>30.9</td><td>521 (2)</td><td>Figure 5 in<br>(Mütze et al.<br>2012)</td></tr><tr><td>Rhodamine 6G</td><td>700,<br>~820</td><td>~150, ~40</td><td></td><td></td><td>~570<br>(Zehentba<br>uer et al.<br>2014)</td><td>Figure 1C in<br>(Albota et<br>al. 1998)</td></tr><tr><td>Rhodamine B</td><td>830</td><td>204</td><td></td><td></td><td>590 (2)</td><td>*</td></tr><tr><td>Rhodamine Green</td><td>850</td><td></td><td></td><td></td><td>527 (2)</td><td>Figure 3 in<br>(Heinze et<br>al. 2000)</td></tr><tr><td>Sapphire</td><td>810</td><td>40</td><td></td><td></td><td>511<br>(Zapata-<br>Hommer<br>and<br>Griesbeck<br>2003)</td><td>*</td></tr><tr><td>SeTa-632</td><td>820</td><td>200</td><td></td><td></td><td>641 (2)</td><td>Broad<br>absorption<br>spectrum</td><td>Figure 1B in<br>(Podgorski<br>et al. 2012)</td></tr><tr><td>SeTa-646</td><td>840</td><td>500</td><td></td><td></td><td>656 (2)</td><td>Broad<br>absorption<br>spectrum</td><td>Figure 1B in<br>(Podgorski<br>et al. 2012)</td></tr><tr><td>SeTa-660</td><td>840</td><td>1500</td><td></td><td></td><td>672 (2)</td><td>Broad<br>absorption<br>spectrum</td><td>Figure 1B in<br>(Podgorski<br>et al. 2012)</td></tr><tr><td>SeTa-670</td><td>840</td><td>2000</td><td></td><td></td><td>688 (2)</td><td>Broad<br>absorption<br>spectrum</td><td>Figure 1B in<br>(Podgorski<br>et al. 2012)</td></tr><tr><td>SeTa-700</td><td>900</td><td>200</td><td></td><td></td><td>703 (2)</td><td>Broad<br>absorption</td><td>Figure 1B in<br>(Podgorski</td></tr></table>
<table><thead><tr><th></th><th></th><th></th><th></th><th></th><th>spectrum</th><th>et al. 2012)</th></tr></thead><tbody><tr><td>SeTau-647</td><td>920</td><td>3000</td><td></td><td>694 (2)</td><td>Broad absorption spectrum</td><td>Figure 2A in (Podgorski et al. 2012)</td></tr><tr><td>SeTau-665</td><td>900</td><td>9000</td><td></td><td>712 (2)</td><td>Broad absorption spectrum</td><td>Figure 1B in (Podgorski et al. 2012)</td></tr><tr><td>Silicon Rhodamine</td><td>830</td><td>~140 (antibodies)</td><td></td><td>~670</td><td>STED-compatible</td><td>Figure 2B in (Velasco et al. 2015)</td></tr><tr><td>STAR 635P</td><td>820</td><td>~110 (NHS carbonate)</td><td></td><td>651 (2)</td><td>STED-compatible</td><td>Figure 2C in (Velasco et al. 2015)</td></tr><tr><td>TagGFP2</td><td>896</td><td>27</td><td></td><td>506 (2)</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>TagRFP</td><td>1050</td><td>42</td><td></td><td>584 (Shaner et al. 2008)</td><td></td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>tdKatushka2</td><td>1100</td><td>63</td><td></td><td>633 (Shcherbo et al. 2009)</td><td>OPO-friendly</td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>tdRFP</td><td>1110</td><td>13.7 (1)</td><td></td><td>579</td><td>OPO-friendly</td><td>Figure 2B in (Herz et al. 2010)</td></tr><tr><td>tdTomato</td><td>1050</td><td>200</td><td></td><td>581 (Shaner et al. 2008)</td><td>OPO-friendly</td><td>Figure S1 in (Drobizhev et al. 2011)</td></tr><tr><td>Tetramethylrhodamine (TRITC)</td><td>840</td><td></td><td></td><td>576 (2)</td><td></td><td>Figure 3C in (Wang and Yeh 2012)</td></tr><tr><td>Texas Red</td><td>780</td><td></td><td></td><td>615 (Cahalan et al. 2002)</td><td></td><td>Figure 3 in (Heinze et al. 2000)</td></tr><tr><td>Venus</td><td>~965, ~1015</td><td>~19, ~15</td><td></td><td>528 (Nagai et al. 2002)</td><td></td><td>Figure 7B in (Hashimoto et al. 2010)</td></tr><tr><td>VivoTag 680</td><td>820</td><td></td><td></td><td>688</td><td></td><td>– (Swirski et al. 2007)</td></tr><tr><td>YFP</td><td>960</td><td>228</td><td></td><td>527</td><td></td><td>*</td></tr></tbody></table>
707 **Table 3** Biophysical properties of two-photon-suitable probes specific of brain cells and structures: peak wavelength of two-photon action cross-section ($\lambda_{2PA}$); peak two-photon action cross-section ($\sigma_2\phi$); peak wavelength of molecular brightness ($\lambda_{\epsilon_{max}}$); peak molecular brightness ($\epsilon_{max}$); fluorescence wavelength ($\lambda_{fluo}$). Probes discussed in the text are in bold.

711 (1) : calculated from the $\sigma_2$ and $\phi$ values

712 (2) : data from commercial provider

<table><thead><tr><th>Probe</th><th>λ<sub>2PA</sub><br>[nm]</th><th>σ<sub>2</sub>φ<br>[GM]</th><th>λ<sub>ε max</sub><br>[nm]</th><th>ε<sub>max</sub><br>[kcpsm]</th><th>λ<sub>fluo</sub><br>[nm]</th><th>Comment</th><th>Reference</th></tr></thead><tbody><tr><td>Alexa Fluor 633</td><td></td><td></td><td>820</td><td>~24</td><td>647 (2)</td><td>Arteries<br>(Shen et al.<br>2012)</td><td>Figure 2 in<br>(Mütze et<br>al. 2012)</td></tr><tr><td>Ant2-PHEA (in<br>water)</td><td>800</td><td>490</td><td></td><td></td><td>654</td><td>Endothelium</td><td>Figure 6 in<br>(Mettra et<br>al. 2016)</td></tr><tr><td>Sulforhodamine<br>101</td><td>910</td><td>118</td><td>900</td><td>38.4</td><td>~605<br>(2)</td><td>Astroglia<br>(Nimmerjahn<br>et al. 2004)</td><td>Figure 5 in<br>(Mütze et<br>al. 2012)</td></tr><tr><td>Sulforhodamine<br>B</td><td>810</td><td></td><td></td><td></td><td>~586<br>(2)</td><td>Astroglia</td><td>Figure 2A<br>in (Appaix<br>et al. 2012)</td></tr></tbody></table>

713
714
715 **Table 4** Biophysical properties of two-photon-suitable environment sensing probes: peak
716 wavelength of two-photon action cross-section ($\lambda_{2PA}$); peak two-photon action cross-section
717 ($\sigma_2\phi$); fluorescence wavelength ($\lambda_{fluo}$). Probes discussed in the text are in bold.

718 (1) : calculated from the $\sigma_2$ and $\phi$ values

719 (2) : data from commercial provider

<table><thead><tr><td>Probe</td><td>λ<sub>2PA</sub> [nm]</td><td>σ<sub>2φ</sub> [GM]</td><td>λ<sub>fluo</sub> [nm]</td><td>Comment</td><td>Reference</td></tr></thead><tbody><tr><td>— Chen 2017 Probe L1 (pH 6.73 / pH 4.33)</td><td>710</td><td>135 / 68 (1)</td><td>460 / 580</td><td>Ratiometric pH indicator</td><td>Figure 6A in (Chen et al. 2017)</td></tr><tr><td>— Chen 2017 Probe L2 (pH 5.53 / pH 2.99)</td><td>700</td><td>67 / 110 (1)</td><td>465 / 540</td><td>Ratiometric pH indicator</td><td>Figure 6B in (Chen et al. 2017)</td></tr><tr><td>C-Laurdan (in EtOH)</td><td>780 (820)</td><td>64.5 (1)</td><td>487</td><td>Mechanical strain in the cell membrane</td><td>Figure S7 in (Kim et al. 2007)</td></tr><tr><td>Laurdan (in EtOH)</td><td>780</td><td>60 (1)</td><td>494</td><td>Mechanical strain in the cell membrane</td><td>Figure S7 in (Kim et al. 2007)</td></tr><tr><td>NP1 (in DMF)</td><td>740</td><td>155</td><td>400-500 / 600-750</td><td>Ratiometric pH indicator</td><td>Figure S4 in (Park et al. 2012)</td></tr><tr><td>SNARF-1</td><td>&lt; 837</td><td></td><td>580-640 (2)</td><td>pH indicator between pH 7 and pH 8</td><td>Figure 3 in (Bestvater et al. 2002)</td></tr><tr><td>Thiophene DiHemiCyanine</td><td>740</td><td>~1.4 (with high-viscosity)</td><td>~590</td><td>Viscosity-sensitive dye</td><td>Figure 5A in (Baek et al. 2016)</td></tr></tbody></table>
Table 5 Biophysical properties of two-photon-suitable probes in the diseased brain: peak wavelength of two-photon action cross-section ($\lambda_{2PA}$); peak two-photon action cross-section ($\sigma_2\phi$); fluorescence wavelength ($\lambda_{fluo}$). Probes discussed in the text are in bold.

(1) : calculated from the $\sigma_2$ and $\phi$ values

(2) : data from commercial provider

<table><thead><tr><td>Probe</td><td>λ<sub>2PA</sub> [nm]</td><td>σ<sub>2φ</sub> [GM]</td><td>λ<sub>fluo</sub> [nm]</td><td>Comment</td><td>Reference</td></tr></thead><tbody><tr><td>Calcofluor White</td><td>590</td><td></td><td>430 (2)</td><td>Cellulose and chitin binding (identification of fungi and yeast)</td><td>Figure 5B in (Trägårdh et al. 2015)</td></tr><tr><td>DCIP-1 (in PBS / bound to amyloid-β aggregates)</td><td>900</td><td>118</td><td>675 / 635</td><td>Amyloid-β plaques, penetrates BBB</td><td>Figure S7 in (Zhu et al. 2017)</td></tr><tr><td>Gatifloxacin</td><td>700</td><td></td><td>~510</td><td>Fluoroquinolone antibiotics</td><td>Figure 1A in (Lee et al. 2016)</td></tr><tr><td>MeO-X04 (in PBS / EtOH)</td><td>720</td><td>10 / 75</td><td>452 / 444</td><td>Amyloid-β plaques (Klunk et al. 2002)</td><td>– (Table S1) (Heo et al. 2013)</td></tr><tr><td>MNAH</td><td>820</td><td></td><td>536</td><td>Imaging of mitochondrial singlet oxygen</td><td>– (Liu et al. 2016)</td></tr><tr><td>Moxifloxacin</td><td>700</td><td></td><td>~530</td><td>Fluoroquinolone antibiotics</td><td>Figure 1A in (Lee et al. 2016)</td></tr><tr><td>PIB (in PBS / EtOH)</td><td>740</td><td>45 / 40</td><td>431 / 417</td><td>Amyloid-β plaques</td><td>– (Table S1) (Heo et al. 2013)</td></tr><tr><td>SAD1 (in PBS / EtOH)</td><td>750</td><td>10 / 170</td><td>497 / 465</td><td>Amyloid-β plaques</td><td>– (Table S1) (Heo et al. 2013)</td></tr></tbody></table>
Table 6 Biophysical properties of two-photon-suitable functional probes : peak wavelength of two-photon action cross-section ($\lambda_{2PA}$) ; peak two-photon action cross-section ($\sigma_2\phi$) ; peak wavelength of molecular brightness ($\lambda_{\epsilon_{max}}$) ; peak molecular brightness ($\epsilon_{max}$) ; fluorescence wavelength ($\lambda_{fluo}$). Probes discussed in the text are in bold.

(1) : calculated from the $\sigma_2$ and $\phi$ values

(2) : data from commercial provider

* : data from http://www.drbio.cornell.edu/cross sections.html (accessed 10/24/2017)

# : data from https://www.janelia.org/lab/harris-lab-apig/research/photophysics/two-photon-fluorescent-probes (accessed 10/24/2017)

<table><thead><tr><th>Probe</th><th>λ<sub>2PA</sub> [nm]</th><th>σ<sub>2</sub>φ [GM]</th><th>λ<sub>ε_max</sub> [nm]</th><th>ε<sub>max</sub> [kcpsm]</th><th>λ<sub>fluo</sub> [nm]</th><th>Comment</th><th>Reference</th></tr></thead><tbody><tr><td colspan="8"><strong>Calcium indicators</strong></td></tr><tr><td>ACa1 (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>- / 780</td><td>- / 110</td><td></td><td></td><td>498 / 498</td><td></td><td>Figure 2A in (Kim et al. 2008a)</td></tr><tr><td>ACa2 (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>- / 780</td><td>- / 90</td><td></td><td></td><td>495 / 495</td><td></td><td>Figure 2A in (Kim et al. 2008a)</td></tr><tr><td>ACa3 (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>- / 780</td><td>- / 95</td><td></td><td></td><td>500 / 517</td><td></td><td>Figure 2A in (Kim et al. 2008a)</td></tr><tr><td>ACaL (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>- / 780</td><td>- / 90</td><td></td><td></td><td>500 / 502</td><td></td><td>Figure 1B in (Mohan et al. 2009)</td></tr><tr><td>ACaLN (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>- / 750</td><td>- / 20</td><td></td><td></td><td>494 / 497</td><td></td><td>- (Table 1) (Lim et al. 2011a)</td></tr><tr><td>BCaM (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>- / 780</td><td>- / 150</td><td></td><td></td><td>470 / 470</td><td></td><td>Figure 1C in (Kim et al. 2010a)</td></tr><tr><td>Cal-590</td><td>1050</td><td></td><td></td><td></td><td>590</td><td></td><td>Figure 1B in (Tischbirek et al. 2015)</td></tr><tr><td>Calcium Crimson (+Ca<sup>2+</sup>)</td><td>870</td><td>95</td><td></td><td></td><td>615 (2)</td><td></td><td>*</td></tr><tr><td>Calcium Green (+Ca<sup>2+</sup>)</td><td>820, 960</td><td>46, 57</td><td></td><td></td><td>531 (2)</td><td></td><td>*</td></tr><tr><td>Calcium Orange (+Ca<sup>2+</sup>)</td><td>820</td><td>60</td><td></td><td></td><td>576 (2)</td><td></td><td>*</td></tr></tbody></table>
<table><tr><td>CaRuby-Cl</td><td>912</td><td></td><td></td><td>604</td><td>Figure 5 in (Collot et al. 2012)</td></tr><tr><td>CaRuby-F</td><td>917</td><td></td><td></td><td>604</td><td>Figure 5 in (Collot et al. 2012)</td></tr><tr><td>CaRuby-Me</td><td>917</td><td></td><td></td><td>604</td><td>Figure 5 in (Collot et al. 2012)</td></tr><tr><td>Fluo-3</td><td>810</td><td>13</td><td></td><td>520-530 (Svoboda and Yasuda 2006)</td><td>*</td></tr><tr><td>Fluo-4</td><td>810</td><td></td><td>800, 930</td><td>~6, ~6</td><td>520-530 (Yasuda et al. 2004)</td></tr><tr><td>Fluo-4FF</td><td>810</td><td></td><td></td><td>516 (2)</td><td>– (Yasuda et al. 2004)</td></tr><tr><td>Fluo-5F</td><td>810</td><td></td><td></td><td>516 (2)</td><td>– (Sabatini et al. 2002)</td></tr><tr><td>Fluo-8</td><td></td><td></td><td>930, 1000</td><td>~4</td><td>514 (2)</td></tr><tr><td>Fura-2 +Ca<sup>2+</sup>)</td><td>780</td><td>~35</td><td></td><td>505 (Cahalan et al. 2002)</td><td>Figure 4 in (Mütze et al. 2012)</td></tr><tr><td>GCaMP2</td><td></td><td></td><td>950</td><td>~6</td><td>511 (Tallini et al. 2006)</td></tr><tr><td>GCaMP3 (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>980</td><td>0.126 / 0.33 *</td><td></td><td>515 (Chen et al. 2013)</td><td>Figure 4I in (Helassa et al. 2015)</td></tr><tr><td>GCaMP3bright (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>950</td><td>0.02 / 0.7 *</td><td></td><td>~515</td><td>high fluorescence dynamic range</td></tr><tr><td>GCaMP3fast (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>990</td><td>0.014 / 0.2 *</td><td></td><td>~515</td><td>fast Ca2+ response times</td></tr><tr><td>GCaMP5A (pH 9.5)</td><td>~940</td><td></td><td>9.9</td><td>~515</td><td>– (Table 3) (Akerboom et al. 2012)</td></tr><tr><td>GCaMP5D (pH 9.5)</td><td>~940</td><td></td><td>9.0</td><td>~515</td><td>– (Table 3) (Akerboom et al. 2012)</td></tr><tr><td>GCaMP5G (pH 9.5)</td><td>~940</td><td></td><td>9.3</td><td>515 (Chen et al. 2013)</td><td>Figure 1D in (Akerboom et al. 2012)</td></tr><tr><td>GCaMP6f</td><td>~940</td><td>~35</td><td></td><td>515 (Chen et al. 2013)</td><td>#</td></tr><tr><td>GCaMP6s</td><td>940</td><td>20</td><td></td><td>515</td><td>Figure 5A in</td></tr></table>
<table><thead><tr><th></th><th></th><th></th><th></th><th>(Chen et al. 2013)</th><th></th><th>(Dana et al. 2016)</th></tr></thead><tbody><tr><td>iGluSnFR</td><td>~940</td><td></td><td></td><td>~515</td><td>Glutamate release</td><td>Figure S13 in (Marvin et al. 2013)</td></tr><tr><td>Indo-1</td><td>730</td><td></td><td></td><td>490 / 405 (Cahalan et al. 2002)</td><td></td><td>* and Figure 3A in (Wang and Yeh 2012)</td></tr><tr><td>jRCaMP1a</td><td>~1070</td><td>~8</td><td></td><td>~593</td><td>OPO-friendly</td><td>Figure 2S1B in (Dana et al. 2016)</td></tr><tr><td>jRCaMP1b</td><td>~1080</td><td>~11</td><td></td><td>~593</td><td>OPO-friendly</td><td>Figure 2S1B in (Dana et al. 2016)</td></tr><tr><td>jRGECO1a</td><td>~1070</td><td>~7</td><td></td><td>~593</td><td>OPO-friendly</td><td>Figure 2S1B in (Dana et al. 2016)</td></tr><tr><td>K-GECO1 (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>~1100</td><td>~10</td><td></td><td>594 / 590</td><td></td><td>Figure 2C in (Shen et al. 2018)</td></tr><tr><td>mApple</td><td>1070</td><td></td><td>7.0</td><td>592</td><td></td><td>– (Table 3) (Akerboom et al. 2013)</td></tr><tr><td>mRuby</td><td>1060</td><td></td><td>4.0</td><td>590</td><td></td><td>– (Table 3) (Akerboom et al. 2013)</td></tr><tr><td>Oregon Green BAPTA-1</td><td>800</td><td>24</td><td></td><td>523</td><td></td><td>Figure 2A in (Kim et al. 2008a)</td></tr><tr><td>RCaMP1a (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>1070 / 1070</td><td></td><td>– / 5.9</td><td>594 / 595</td><td></td><td>– (Table 3) (Akerboom et al. 2013)</td></tr><tr><td>RCaMP1c (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>1070 / 1070</td><td></td><td>– / 7.3</td><td>597 / 595</td><td></td><td>– (Table 3) (Akerboom et al. 2013)</td></tr><tr><td>RCaMP1d (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>1070 / 1070</td><td></td><td>– / 7.7</td><td>597.5 / 592.5</td><td></td><td>– (Table 3) (Akerboom et al. 2013)</td></tr><tr><td>RCaMP1f (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>1070 / 1070</td><td></td><td>– / 8.2</td><td>597 / 591.5</td><td></td><td>Figure 2F in (Akerboom et al. 2013)</td></tr><tr><td>RCaMP1h</td><td>~1070</td><td>~27</td><td></td><td>595</td><td></td><td>#</td></tr><tr><td>R-GECO1 (-Ca<sup>2+</sup> / +Ca<sup>2+</sup>)</td><td>1065 / 1065</td><td></td><td>– / 3.8</td><td>598 / 588</td><td></td><td>– (Table 3) (Akerboom et al. 2013)</td></tr><tr><td colspan="7">Other ions</td></tr><tr><td>6-CO2H-ZAP4 (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>&lt;700, &gt;1000</td><td>– / 86</td><td></td><td>527 / 523</td><td>Zinc</td><td>Figure 2B in (Khan et al. 2014)</td></tr><tr><td>ANa1 (+Na<sup>+</sup>)</td><td>780</td><td>95</td><td></td><td>500</td><td>Sodium</td><td>Figure 1C in (Kim et al.</td></tr></tbody></table>
<table><thead><tr><th></th><th></th><th></th><th></th><th></th><th></th><th>2010b)</th></tr></thead><tbody><tr><td>Asante NaTRIUM Green-2 (ANG-2) (-Na<sup>+</sup> / +Na<sup>+</sup>)</td><td>780</td><td>0.84 / 5.7</td><td></td><td>542</td><td>Sodium</td><td>Figure 2 in (Roder and Hille 2014)</td></tr><tr><td>AZn1 (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>- / 780</td><td>- / 95</td><td></td><td>496 / 498</td><td>Zinc</td><td>Figure 1B in (Kim et al. 2008b)</td></tr><tr><td>AZn2 (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>- / 780</td><td>- / 110</td><td></td><td>494 / 499</td><td>Zinc</td><td>Figure 1B in (Kim et al. 2008b)</td></tr><tr><td>AZnE1 (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>- / 780</td><td>- / 86</td><td></td><td>502 / 503</td><td>Zinc</td><td>Figure 2A in (Danish et al. 2011)</td></tr><tr><td>AZnE2 (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>- / 780</td><td>- / 86</td><td></td><td>503 / 504</td><td>Zinc</td><td>Figure 2A in (Danish et al. 2011)</td></tr><tr><td>AZnM1 (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>- / 780</td><td>- / 88</td><td></td><td>501 / 504</td><td>Zinc</td><td>Figure 2A in (Danish et al. 2011)</td></tr><tr><td>AZnM2 (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>- / 780</td><td>- / 86</td><td></td><td>504 / 504</td><td>Zinc</td><td>Figure 2A in (Danish et al. 2011)</td></tr><tr><td>AZnN (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>- / 780</td><td>- / 89</td><td></td><td>500 / 502</td><td>Zinc</td><td>Figure 2A in (Danish et al. 2011)</td></tr><tr><td>FMg1 (-Mg<sup>2+</sup> / +Mg<sup>2+</sup>)</td><td>- / 740</td><td>- / 87</td><td></td><td>540 / 540</td><td>Magnesium</td><td>Figure 1C in (Dong et al. 2012)</td></tr><tr><td>FMg2 (-Mg<sup>2+</sup> / +Mg<sup>2+</sup>)</td><td>- / 740</td><td>- / 76</td><td></td><td>555 / 555</td><td>Magnesium</td><td>Figure 1C in (Dong et al. 2012)</td></tr><tr><td>NC7</td><td>860</td><td>77 (1)</td><td></td><td>520</td><td>Magnesium</td><td>Figure 4 in (Yin et al. 2015)</td></tr><tr><td>OC7</td><td>740</td><td>71 (1)</td><td></td><td>500</td><td>Magnesium</td><td>Figure 4 in (Yin et al. 2015)</td></tr><tr><td>PhenGreen-FL</td><td>1074</td><td></td><td></td><td>517 (Petrat et al. 1999)</td><td>Heavy metals</td><td>Figure 3 in (Bestvater et al. 2002)</td></tr><tr><td>P-Zn (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>700 / 700</td><td>304 / 565 (1)</td><td></td><td>465 / 550</td><td>Zinc</td><td>Figure 1A in (Li et al. 2017)</td></tr><tr><td>SBFI (+Na<sup>+</sup>)</td><td>780</td><td>20</td><td></td><td>539</td><td>Sodium</td><td>Figure 1C in (Kim et al. 2010b)</td></tr><tr><td>Sodium Green(+Na<sup>+</sup>)</td><td>800</td><td>30</td><td></td><td>532</td><td>Sodium</td><td>Figure 1C in (Kim et al. 2010b)</td></tr><tr><td>SZn-Mito (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>- / 760</td><td>- / 75</td><td></td><td>500 / 493</td><td>Zinc</td><td>Figure 1B in (Masanta et al. 2011)</td></tr><tr><td>SZn2-Mito (-</td><td>- / -</td><td>-</td><td></td><td>536 / 536</td><td>Zinc</td><td>Figure 1B in</td></tr></tbody></table>
<table><tr><td>Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>750</td><td>155</td><td></td><td></td><td>(Baek et al. 2012)</td></tr><tr><td>SZnC (-Zn<sup>2+</sup> / +Zn<sup>2+</sup>)</td><td>750 / 750</td><td>16 / 92</td><td></td><td>499 / 499</td><td>Zinc (Golgi-localized)</td><td>Figure 2D in (Singh et al. 2015)</td></tr><tr><td>— Schwarze 2015 Probe 1 (DMSO / K<sup>+</sup> / Na<sup>+</sup>)</td><td>860</td><td>3.1 / 9.4 / 3.4</td><td></td><td>511</td><td>Potassium / Sodium</td><td>Figure 2B in (Schwarze et al. 2015)</td></tr><tr><td>— Schwarze 2015 Probe 2 (DMSO / K<sup>+</sup>)</td><td>840</td><td>5.7 / 16.1</td><td></td><td>493</td><td>Potassium</td><td>– (Table 1) (Schwarze et al. 2015)</td></tr></table>

Voltage-sensitive dyes

<table><tr><td>ANNINE-6</td><td>1020</td><td></td><td></td><td>560-660 (Frey et al. 2006)</td><td>– (Kuhn et al. 2008)</td></tr><tr><td>ANNINE-6plus</td><td>1060</td><td></td><td></td><td>560-660</td><td>– (Kuhn et al. 2004)</td></tr><tr><td>ArcLight A242</td><td>950</td><td></td><td></td><td>&lt;775</td><td>– (Table 1) (Brinks et al. 2015)</td></tr><tr><td>ASAP1</td><td>950</td><td></td><td></td><td>&lt;775</td><td>– (Table 1) (Brinks et al. 2015)</td></tr><tr><td>BP6</td><td>740</td><td>100</td><td></td><td>545</td><td>Mitochondrial membrane potential</td><td>Figure 7 in (Moritomo et al. 2014)</td></tr><tr><td>CAESR</td><td>968</td><td></td><td></td><td>&lt;775</td><td></td><td>– (Table 1) (Brinks et al. 2015)</td></tr><tr><td>di-2- ANEP(F)PTEA</td><td>1060</td><td></td><td></td><td>632 (bound to lipids)</td><td></td><td>– (Yan et al. 2012)</td></tr><tr><td>di-3- ANEPPDHQ</td><td>850</td><td></td><td></td><td>&gt;560</td><td></td><td>Figure 5A in (Fisher et al. 2008)</td></tr><tr><td>Di-4-ANEPPS</td><td>940</td><td>5</td><td></td><td>635 (in ethanol) (2)</td><td>*</td><td></td></tr><tr><td>Di-8- ANEPPDHQ</td><td>~900-950</td><td>~20</td><td></td><td>620 (in octanol)</td><td></td><td>Figure 3 in (Fisher et al. 2005)</td></tr><tr><td>Di-8-ANEPPS</td><td>940</td><td>10</td><td></td><td>625 (in octanol)</td><td></td><td>* and Figure 5 in (Fisher et al. 2005)</td></tr><tr><td>FlicR1</td><td>1120</td><td></td><td></td><td>597</td><td>OPO-friendly</td><td>– (Abdelfattah et al. 2016)</td></tr><tr><td>Merocyanine 540</td><td>&gt;950</td><td>4.4 (at 960 nm)</td><td></td><td>615 (in octanol)</td><td></td><td>Figure 3 in (Fisher et al. 2005)</td></tr></table>
<table><tr><td>Nile Blue A</td><td>&lt;800</td><td>0.6 (at 800 nm)</td><td>660 (in octanol)</td><td>Figure 3 in (Fisher et al. 2005)</td></tr><tr><td>QuasAr1</td><td>1200</td><td></td><td>660-775</td><td>– (Table 1) (Brinks et al. 2015)</td></tr><tr><td>QuasAr2</td><td>1200</td><td></td><td>660-775</td><td>Figure S3 in (Brinks et al. 2015)</td></tr><tr><td>RH-1692</td><td>~800-850</td><td>1.5 (at 800 nm)</td><td>680 (in octanol)</td><td>Figure 3 in (Fisher et al. 2005)</td></tr><tr><td>RH-237</td><td>&lt;800, &gt;960</td><td>8.9 (at 800 nm)</td><td>676 (in octanol)</td><td>Figure 3 in (Fisher et al. 2005)</td></tr><tr><td>RH-414</td><td>~950</td><td>12 (at 960 nm)</td><td>636 (in octanol)</td><td>Figure 3 in (Fisher et al. 2005)</td></tr><tr><td>RH-421</td><td>~950</td><td>16 (at 960 nm)</td><td>648 (in octanol)</td><td>Figure 3 in (Fisher et al. 2005)</td></tr><tr><td>RH-795</td><td>~950</td><td>10 (at 960 nm)</td><td>640 (in octanol)</td><td>Figure 3 in (Fisher et al. 2005)</td></tr></table>
**Table 7** Biophysical two-photon properties of intrinsic fluorophores: peak wavelength of two-photon action cross-section ($\lambda_{2PA}$); peak two-photon action cross-section ($\sigma_2\phi$); peak wavelength of molecular brightness ($\lambda_{\epsilon_{max}}$); peak molecular brightness ($\epsilon_{max}$); fluorescence wavelength ($\lambda_{fluo}$). Probes discussed in the text are in bold.

<table><thead><tr><td>Probe</td><td>λ<sub>2PA</sub> [nm]</td><td>σ<sub>2φ</sub> [GM]</td><td>λ<sub>fluo</sub> [nm]</td><td>Comment</td><td>Reference</td></tr></thead><tbody><tr><td>Cholecalciferol</td><td>&lt;700, 820, 980</td><td>0.0006 (at 700 nm)</td><td>460</td><td>Vitamin D3</td><td>Figure 1A in (Zipfel et al. 2003a)</td></tr><tr><td>FAD</td><td>~880</td><td>&lt;1</td><td>~530</td><td></td><td>Figure 1B in (Stringari et al. 2017)</td></tr><tr><td>Folic acid</td><td>&lt;700</td><td>0.007 (at 700 nm)</td><td>~445</td><td>Vitamin B9</td><td>Figure 1A in (Zipfel et al. 2003a)</td></tr><tr><td>NADH</td><td>700</td><td>0.09 (at 700 nm)</td><td>~470</td><td></td><td>Figure 1A in (Zipfel et al. 2003a)</td></tr><tr><td>Pyridoxine</td><td>&lt;700</td><td>0.008 (at 700 nm)</td><td>~390</td><td></td><td>Figure 1A in (Zipfel et al. 2003a)</td></tr><tr><td>Retinol</td><td>&lt;700</td><td>0.07 (at 700 nm)</td><td>~490</td><td></td><td>Figure 1A in (Zipfel et al. 2003a)</td></tr><tr><td>Riboflavin</td><td>&lt;700</td><td>0.8 (at 700 nm)</td><td>~530</td><td></td><td>Figure 1A in (Zipfel et al. 2003a)</td></tr></tbody></table>

744
745
**Table 8** Biophysical properties of two-photon-suitable probes specific of sub-cellular structures : peak wavelength of two-photon action cross-section ($\lambda_{2PA}$); peak two-photon action cross-section ($\sigma_2\phi$); peak wavelength of molecular brightness ($\lambda_{e\_max}$); peak molecular brightness ($\epsilon_{max}$); fluorescence wavelength ($\lambda_{fluo}$). Probes discussed in the text are in bold.

(1) : calculated from the $\sigma_2$ and $\phi$ values

(2) : data from commercial provider

*: data from http://www.drbio.cornell.edu/cross sections.html (accessed 10/24/2017)

<table><thead><tr><td>Probe</td><td>λ<sub>2PA</sub> [nm]</td><td>σ<sub>2φ</sub> [GM]</td><td>λ<sub>fluo</sub> [nm]</td><td>Comment</td><td>Reference</td></tr></thead><tbody><tr><td>Acridine Orange</td><td>837 &gt; 882 &gt;&gt; 981</td><td></td><td>526 (DNA), 650 (RNA) (2)</td><td>Nucleic acids</td><td>Figure 3 in (Bestvater et al. 2002)</td></tr><tr><td>ANO1</td><td>750</td><td>170</td><td>502</td><td>Nitric oxide</td><td>Figure 3 in (Seo et al. 2012)</td></tr><tr><td>AS1</td><td>780</td><td>85</td><td>498</td><td>Glucose</td><td>Figure S6A in (Lim et al. 2012)</td></tr><tr><td>ASiR1 (in CH<sub>3</sub>CN)</td><td>750</td><td>258</td><td>593</td><td>Lysosomes</td><td>Figure S2 in (Zhang et al. 2018)</td></tr><tr><td>ASiR2 (in CH<sub>3</sub>CN)</td><td>760</td><td>237</td><td>601</td><td>Lysosomes</td><td>Figure S2 in (Zhang et al. 2018)</td></tr><tr><td>ASiR3 (in CH<sub>3</sub>CN)</td><td>760</td><td>160</td><td>606</td><td>Lysosomes</td><td>Figure S2 in (Zhang et al. 2018)</td></tr><tr><td>ASiR4 (in CH<sub>3</sub>CN)</td><td>760</td><td>179</td><td>608</td><td>Lysosomes</td><td>Figure S2 in (Zhang et al. 2018)</td></tr><tr><td>ASiR5 (in CH<sub>3</sub>CN)</td><td>750</td><td>189</td><td>609</td><td>Lysosomes</td><td>Figure S2 in (Zhang et al. 2018)</td></tr><tr><td>ASiR6 (in CH<sub>3</sub>CN)</td><td>750</td><td>193</td><td>601</td><td>Lysosomes</td><td>Figure S2 in (Zhang et al. 2018)</td></tr><tr><td>ASS (H<sub>2</sub>O / 2-AET)</td><td>780</td><td>11 / 113</td><td>457 / ~505</td><td>Thiols</td><td>Figure 1D in (Lee et al. 2010)</td></tr><tr><td>BLT-blue</td><td>750</td><td>160</td><td>451</td><td>Lysosomes</td><td>Figure 1B in (Han et al. 2012)</td></tr><tr><td>CAEI</td><td>850</td><td>152</td><td>550</td><td>Mitochondria</td><td>Figure 1B in (Miao et al. 2014)</td></tr></tbody></table>
<table><tr><td>CAI</td><td>860</td><td>328</td><td>562</td><td>Mitochondria</td><td>Figure 1B in (Miao et al. 2014)</td></tr><tr><td>CLT-blue</td><td>750</td><td>50</td><td>471</td><td>Lysosomes</td><td>Figure 1B in (Son et al. 2011)</td></tr><tr><td>CLT-yellow</td><td>850</td><td>47</td><td>549</td><td>Lysosomes</td><td>Figure 1B in (Son et al. 2011)</td></tr><tr><td>C-Laurdan (in EtOH)</td><td>780</td><td>64.5 (1)</td><td>487</td><td>Lipid rafts</td><td>Figure S7 in (Kim et al. 2007)</td></tr><tr><td>DAPI</td><td>580 >> 685</td><td></td><td>461 (2)</td><td>Nucleic acids</td><td>Figure 2A in (Trägårdh et al. 2015)</td></tr><tr><td>DCF2 (H<sub>2</sub>DCFDA) (in DMSO)</td><td>1065</td><td></td><td>538 (Yi et al. 2009)</td><td>Organelle tracker</td><td>Figure 3 in (Bestvater et al. 2002)</td></tr><tr><td>DiA</td><td>880 (study limited to [830-920 nm])</td><td></td><td>590</td><td>Lipophilic Tracer</td><td>– (Table 1) (Ruthazer and Cline 2002)</td></tr><tr><td>DiD</td><td>830</td><td></td><td>665</td><td>Lipophilic Tracer</td><td>– (Table 1) (Ruthazer and Cline 2002)</td></tr><tr><td>DiI</td><td>&lt;700, 1020</td><td>96, 10</td><td>565 (Cahalan et al. 2002)</td><td>Lipophilic Tracer, organelles</td><td>*</td></tr><tr><td>DiO</td><td>880 (study limited to [830-920 nm])</td><td></td><td>501</td><td>Lipophilic Tracer</td><td>– (Table 1) (Ruthazer and Cline 2002)</td></tr><tr><td>ER-Tracker white/blue</td><td>728</td><td></td><td>430-640 (2)</td><td>Endoplasmic Reticulum (environmentally-sensitive)</td><td>Figure 5 in (Bestvater et al. 2002)</td></tr><tr><td>FMT-green</td><td>750</td><td>175</td><td>523</td><td>Mitochondria</td><td>Figure 1B in (Han et al. 2012)</td></tr><tr><td>Hoechst 33258</td><td>560 >> 717</td><td></td><td>461 (2)</td><td>Nucleic acids</td><td>Figure 5A in (Trägårdh et al. 2015)</td></tr><tr><td>Hoechst 33342</td><td>660 &gt; 715</td><td></td><td>461 (2)</td><td>Nucleic acids</td><td>Figure 3A in (Bestvater et al. 2002)</td></tr><tr><td>Laurdan (in EtOH)</td><td>780</td><td>60 (1)</td><td>494</td><td>Lipid rafts</td><td>Figure S7 in (Kim et al. 2007)</td></tr><tr><td>LysoTracker Red</td><td>1010 &lt; 1100</td><td></td><td>590 (2)</td><td>Organelle tracker</td><td>Figure 5 in (Bestvater et al. 2002)</td></tr><tr><td>LysoTracker Yellow</td><td>972</td><td></td><td>535 (2)</td><td>Organelle tracker</td><td>Figure 5 in (Bestvater et al. 2002)</td></tr></table>
<table><tr><td>MitoTracker Red</td><td>860, 1133</td><td>3.12 (at 860 nm)</td><td>599 (2)</td><td>Organelle tracker</td><td>Figure 5 in (Bestvater et al. 2002)</td></tr><tr><td>PKH26</td><td>950</td><td></td><td>567 (2)</td><td>Membrane labelling</td><td>– (Takaki et al. 2015)</td></tr><tr><td>PKH67</td><td>870, 850</td><td></td><td>502 (2)</td><td>Membrane labelling</td><td>– (Morelli et al. 2003; Kuwashima et al. 2005)</td></tr><tr><td>Propidium iodide</td><td>989 &gt; 1015 &gt;&gt; 1099</td><td></td><td>617 (2)</td><td>Nucleic acids (dead cells)</td><td>Figure 3 in (Bestvater et al. 2002)</td></tr><tr><td>Quinacrine</td><td>678 &gt; 697</td><td></td><td>525 (2)</td><td>Nucleic acids, therapeutic effect</td><td>Figure 3 in (Bestvater et al. 2002)</td></tr><tr><td>SL2 (in EtOH / THF)</td><td>800</td><td>40 / 185</td><td>576 / 495</td><td>Lipid rafts, turn-on</td><td>Figure 1B in (Lim et al. 2011b)</td></tr><tr><td>Rhodamine 123</td><td>913 &gt; 1090</td><td></td><td>527 (2)</td><td>Mitochondria</td><td>Figure 3 in (Bestvater et al. 2002)</td></tr><tr><td>SYBR Gold</td><td>~820</td><td></td><td>~537 (2)</td><td>Nucleic acids</td><td>Figure 3 in (Neu et al. 2002)</td></tr><tr><td>SYBR Green</td><td>~820</td><td></td><td>520 (2)</td><td>Nucleic acids</td><td>Figure 3 in (Neu et al. 2002)</td></tr><tr><td>Syto 13</td><td>~780-800</td><td></td><td>509 (DNA), 514 (RNA) (2)</td><td>Nucleic acids</td><td>Figure 2 in (Neu et al. 2002)</td></tr><tr><td>Syto 40</td><td>900</td><td></td><td>441 (2)</td><td>Nucleic acids</td><td>Figure 2 in (Neu et al. 2002)</td></tr><tr><td>Syto 9</td><td>&lt;800</td><td></td><td>503 (2)</td><td>Nucleic acids</td><td>Figure 2 in (Neu et al. 2002)</td></tr><tr><td>Sytox Blue</td><td>&lt;800</td><td></td><td>480 (2)</td><td>Nucleic acids</td><td>Figure 3 in (Neu et al. 2002)</td></tr><tr><td>Sytox Green</td><td>~715</td><td></td><td>523 (2)</td><td>Nucleic acids</td><td>Figure 5C in (Trägårdh et al. 2015)</td></tr><tr><td>TO-PRO-3</td><td>1110</td><td></td><td>661 (2)</td><td>Nucleic acids, OPO-friendly</td><td>– (Smith et al. 2012)</td></tr></table>
754 **Table S1** Biophysical properties of two-photon-suitable probes in alphabetical order: peak
755 wavelength of two-photon action cross-section ($\lambda_{2PA}$) ; peak two-photon action cross-section
756 ($\sigma_2\phi$) ; peak wavelength of molecular brightness ($\lambda_{\epsilon_{max}}$) ; peak molecular brightness ($\epsilon_{max}$) ;
757 fluorescence wavelength ($\lambda_{fluo}$).

758 (1) : calculated from the $\sigma_2$ and $\phi$ values

759 (2) : data from commercial provider

760

761
762 Compliance with Ethical Standards

763 **Funding:** CH is supported by a F30 Fellowship (NS093719 from NIH NINDS), as well as the
764 UCLA Medical Scientist Training Program (NIH NIGMS training grant GM08042). CP-C is
765 supported by W81XWH-14-1-0433 (USAMRMC, DOD), a Developmental Disabilities
766 Translational Research Program grant (#20160969 from John Merck), SFARI Awards 295438
767 and 513155CP (Simons Foundation) and 5R01HD054453 (NICHD/NIH). GL is supported by
768 the Agence Nationale de la Recherche (ANR-15-CE37-0004 "SmellBrain" & ANR-15-
769 NEUC-0004 "Circuit_OPL").

770 **Conflict of Interest:** GL is supported by the life insurance company AG2R-La-Mondiale
771 ("Vivons vélo pour l'Institut Pasteur").

772 **Ethical approval:** All procedures performed in studies involving animals were in accordance
773 with the ethical standards of the institution at which the studies were conducted. This article
774 does not contain any studies with human participants performed by any of the authors.

775
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