Photocontrollable Proteins for Optoacoustic Imaging - American

Apr 1, 2019 - interference with the respective cells, tissue, or organism under observation. Together with a focused light source (laser or optical fi...
0 downloads 0 Views 939KB Size
Subscriber access provided by - Access paid by the | UCSB Libraries

Feature

Photo-Controllable Proteins for Optoacoustic Imaging Kanuj Mishra, Juan Pablo Fuenzalida Werner, Vasilis Ntziachristos, and Andre C Stiel Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.9b01048 • Publication Date (Web): 01 Apr 2019 Downloaded from http://pubs.acs.org on April 7, 2019

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

Photo-Controllable Proteins for Optoacoustic Imaging Kanuj Mishraa+, Juan Pablo Fuenzalida-Werner a+, Vasilis Ntziachristosa,b and Andre C. Stiela*

a) Institute of Biological and Medical Imaging (IBMI), Helmholtz Zentrum München, 85764 Neuherberg, Germany b) Chair of Biological Imaging and Center for Translational Cancer Research (TranslaTUM), Technische Universität München, 81675 Munich, Germany +) These authors contributed equally *) Correspondence should be addressed to A.C.S. ([email protected]) Abstract Photo-controllable proteins revolutionized life-science imaging due to their contribution to subdiffractionresolution optical microscopy. They might have yet another lasting impact on Photo- or Optoacoustic imaging (OA). OA combines optical contrast with ultrasound detection enabling high-resolution real-time in vivo imaging well-beyond the typical penetration depth of optical methods. While OA already showed numerous applications relying on endogenous contrast from blood hemoglobin or lipids its application in the life-science was limited by a lack of labels overcoming the strong signal from the aforementioned endogenous absorbers. Here, a number of recent studies showed that photo-controllable proteins provide the means to overcome this barrier eventually enabling OA to image small cell numbers in a complete organism in vivo. In this Feature article, we introduce the key photo-controllable proteins, explain the basic concepts and highlight achievements that have been already made. Introduction In several organic chromophores such as azobenzenes or diarylethenes, photoexcitation leads to a reversible chemical rearrangement, primarily isomerization. Such rearrangements can be exploited in photo-sensing materials, nanorobotics and other applications 1,2. Interestingly, nature utilizes similar photochemical transformations of chromophores in proteins to sense and react to light stimuli. In proteins like flavoproteins, phytochromes or opsins, light-induced rearrangements result in subsequent signaling cascades leading to immediate or long-term physiological responses in the respective organisms. For example, in mammals, isomerization of the retinal chromophore in rhodopsin is the first step in visual perception. Transgene technology allows us to use these photo-controllable proteins outside of their native hosts in organisms of interest and to harness their light-induced transformations as a way to control their function without direct (invasive) interference with the respective cells, tissue or organism under observation. Together with a focused light source (laser or optical fiber), this allows the manipulation and study of molecular processes with high spatiotemporal precision in vivo (optogenetics 3). For example ‘nerve impulses’ can be triggered by light to study neuronal functioning 4, or cellular programs can be activated by light to study developmental processes 5. Next to the light-control of molecular function the intrinsic photophysical characteristics of the chromophores of those proteins have heavily impacted optical imaging in the life sciences. Light control of photophysical characteristics has been a key to the success of super-resolution imaging (SR), a fluorescence microscopy method that allows the recording of images at sub-diffraction resolution, providing insight into the structure and function inside a cell in unprecedented detail 6,7. Recently, photo-controllable proteins have begun to become equally important for photo- or optoacoustic imaging (OA), a method that allows tomographic imaging in vivo at centimeter depths and relatively large fields of ACS Paragon Plus Environment

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

view far beyond the reach of purely optical methods. OA achieves this unique performance by combining optical excitation and ultrasound detection 8–10. We will begin this Feature article with a brief introduction on the two classes of photo-controllable proteins most relevant to imaging: photo-controllable members of the fluorescent protein (FP) family, and natively photo-controllable photo-receptors termed phytochromes. Broader overviews on photo-controllable proteins have recently been published 11,12. Here we focus on the applications of photocontrollable proteins in OA, since the application of these proteins to SR is already the focus of excellent reviews 13,14. Photo-control in fluorescent proteins and phytochromes As a fluorescence-imaging technique, SR relies primarily on photo-controllable FPs, while imaging photocontrollable proteins in OA relies on phytochromes, which are advantageous due to their near-infrared (NIR) absorption but show little to no fluorescence. Similar to other photo-controllable proteins, both families predominantly show a light-induced cis/trans isomerization of their chromophore as the keyelement of photo-control. This isomerization in context with the protein surroundings of the chromophore defines the photophysical characteristics of the proteins and thereby their applicability in different imaging contexts. With very few exceptions 15,16, photo-controllable FPs are engineered derivatives of non-photocontrollable FPs known from conventional fluorescence imaging 17. They contain a hydroxybenzylidene-imidazolidone chromophore in the center of a barrel-like structure (Figure 1A). The chromophore is autocatalytically formed from three amino acids of the protein itself. The entirely self-contained nature of the chromophore means that expression of the single transgene encoding the protein is sufficient, which helps explain the immense popularity of FPs for life-science imaging 18. The chromophore has two characteristic protonation states: a protonated form absorbing at lower wavelengths; and a deprotonated form absorbing at higher wavelengths. The deprotonated form is nearly always the more fluorescent form and, in most cases, predominant in equilibrium. Figure 1: Photo-controllable proteins: reversibly-switchable fluorescent proteins (RSFPs) and bacteriophytochromes (BphPs). (A) RSFPs host a hydroxybenzylidene-imidazolidone chromophore inside a barrel-like protein structure. The chromophore undergoes reversible, light-driven cis/trans isomerization at the methine bridge linking the rings. (B) BphPs are multi-domain proteins carrying a biliverdin chromophore in a central GAF domain. The chromophore undergoes lightdriven cis/trans isomerization at the methine bridge linking C and D ring.

Photo-control in FPs 19 can take the form of irreversible photo-activation (nonfluorescent → fluorescent) and photo-conversion (fluorescent color A → color B), or as reversible photo-switching (nonfluorescent ↔ fluorescent). In photo-activatable proteins, a glutamate in the vicinity of the chromophore, which stabilizes the protonated form, is decarboxylated by UV irradiation, which generates the fluorescent deprotonated form. In

ACS Paragon Plus Environment

Page 2 of 15

Page 3 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

photo-convertible proteins, β-elimination extends the chromophore's π-electron system, red-shifting the absorption of the deprotonated form. In reversible photoswitching proteins, which we refer to as reversibly-switchable fluorescent proteins (RSFPs) and which are the most relevant FPs for OA imaging, light induces the cis/trans isomerization of the methine bridge linking the hydroxybenzyl and imidazole rings (Figure 1A). The isomerization changes the chromophore position with respect to its protein environment, altering the interactions with surrounding amino acids. This leads to different protonation, quenching, stabilization and planarity of the chromophore. Thus, RSFPs undergo a reversible, light-induced change between forms with different photophysical characteristics (absorption spectra and deexcitation pathways).

Figure 2: General principles of photo-control. (A) The general concept assumes reversible light-driven transitions between a signal form and a no-signal form (e.g. fluorescence or OA). The signal form emits fluorescence and/or ultrasound (US) waves. (B) Simplified Jablonski diagram depicting the relevant transitions between forms A and B of a photo-controllable molecule. Abs = Absorption, Fluo = Fluorescence, NRD = Non-radiative decay, Vibr. = vibrational relaxation, ISC = Intersystem crossing. Other electronic states can occur but are not depicted. For OA a QYNRD >>> QYFluo is optimal (see thickness of transition arrows in Form A for example). (C) Symbolized changes of a bulk volume of photo-controllable molecules as it would appear in a cuvette or a cell, under illumination with two wavelengths. The curve depicts the exponential decay under green light illumination (green line) and subsequent recovery of the signal over time under UV illumination (purple arrowhead). A single switching curve is shown as inset together with a stylized cuvette showing the change of photo-controllable molecules in a bulk volume.

Phytochromes are multi-domain photoreceptor proteins in plants, fungi, cyanobacteria and other bacteria 20 (Figure 1B). Natively, they relay light-induced structural changes to subsequent effector cascades regulating molecular, cellular and developmental responses such as cell division. Their stronger absorption in farred and NIR regions stems from the extended π-electron system of their tetrapyrrole chromophores. Similar to RSFPs, the light-induced change is a cis/trans isomerization of a methine bridge, in this case the one between the C and D rings of the tetrapyrrole (Figure 1B). The result is interconversion between two forms with different absorption characteristics: most phytochromes exhibit a red-absorbing state (Pr; cis, 670 – 700 nm) and a far-red-absorbing state (Pfr; trans, 740 – 760 nm). The majority of phytochromes employ chromophores such as phytochromobilin (P𝚽B) and phycocyanobilin (PCB), which are not found in mammalian cells, hampering their

ACS Paragon Plus Environment ergoes reversible light driven cis / trans isomerization about the

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

application to in vivo imaging. The exception are bacteriophytochromes (BphPs), which utilize the tetrapyrrole biliverdin (BV) as a chromophore. BV is a product of heme catabolism and is ubiquitous in mammalian cells. BphPs and most other phytochromes share a three-domain architecture, with the chromophore covalently anchored in the central GAF domain, which is flanked by the PAS and PHY domains. The PHY domain is a C-terminal domain that partially shields the chromophore from the solvent and is mainly responsible for relaying the chromophore isomerization to changes in the overall protein structure, which regulate downstream signaling cascades in the cell. Fundamental photophysics of switching in RSFPs and phytochromes In RSFPs and phytochromes, the cis/trans isomerization induces a change in photophysical characteristics. In detail, these changes and the photophysical states involved are complex and differ from protein to protein. For reasons of simplification, we employ a model consisting of the protein and its chromophore being either in form A or B (Figure 2A). The two forms differ in the conformation of the chromophore and its position relative to residues in its vicinity. As a result, A and B differ in absorbance and emission spectra as well as in quantum yields (QY) and lifetimes of transitions. Effectively, this means a reversible lightcontrollable transition between a fluorescent (“on”), which is usually cis in FPs, and a non-fluorescent (“off”) form; alternatively, or in addition, this transition results in a red- or blue-shift in absorption (photochromism). These different absorption characteristics between A and B mean that light of different wavelengths can be used to stimulate forward (A → B) and reverse (B → A) transitions. The interconversion kinetics depend on the QY of the respective photophysical transitions relative to competing transitions, e.g. fluorescence, non-radiative decay or intersystem crossing (Figure 2B). A high QY for the cis/trans isomerization means a high likelihood that an absorbed photon will induce interconversion between A and B, rather than lead to some other transition. At the bulk level with millions of chromophoric proteins observed together in an imaging experiment, high QY for the transition between A and B translates to faster photo-controlled switching of the entire illuminated sample (Figure 2C). Consequently, the kinetics (koff and kon) also depend on the intensity of the light used, in other words, on the number of photons available for the chromophore to absorb and thereby induce the transition between A and B. A third conversion comes into play because A and B differ in absolute energy, resulting in a thermal relaxation of the chromophore in the dark (kdark). The kinetics of this transition strongly depend on the relative stabilities of A and B, and can be on the order of seconds to days. Photo-control in SR Presently, only the photo-switching of RSFPs has been employed for fluorescence SR because their onstate is strongly fluorescent. Fluorescent derivatives of the natively dark BphPs have been engineered by stabilizing the cis (Pr) state 21, but they do not photo-switch efficiently, precluding their widespread use in SR, although they have recently been used in SR schemes similar to stimulated emission depletion (STED)22. BphPs that photo-switch between highly fluorescent and non-fluorescent states would be powerful tools for SR due to their favorable NIR absorption. Several reviews exist on using photo-controllable FPs in different SR schemes to overcome the diffraction limit of optical resolution (~ 200 nm). Two major SR concepts relying on photo-controllable proteins exist to overcome this barrier. One is a purely physical strategy (dubbed RESOLFT), which relies on RSFPs. Here a diffraction limited excitation spot is overlaid by a second, ring-shaped diffraction-limited beam, which effectively transfers a large portion of the originally fluorescent RSFPs to an off-state that no longer contributes to fluorescence emission. The resulting “leftover” spot is diffraction-unlimited 6. In the second approach, which is typically performed with photo-activatable or -convertible proteins but can also be done with RSFPs 23, the sample is illuminated with low-intensity light that stochastically transfers a sparsely distributed sub-population of labels to the fluorescent state. The positions of those labels in the ‘on’ state ACS Paragon Plus Environment

Page 4 of 15

Page 5 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

can be determined at sub-diffraction accuracy using centroid analysis. Repeating this procedure and computationally combining the images allows the position of all labels to be determined, giving rise to a diffraction-unlimited image 7. General concepts in OA One of the exciting recent developments in the field of photo-controllable proteins is their application to optoacoustic imaging, which offers several advantages over many other imaging modalities. In addition to the resolution limit, optical imaging is limited by two other frontiers: penetration depth and field of view. Optical imaging is usually restricted to a depth of ~ 400 m due to strong light scattering and absorption in soft tissues. However, this is insufficient to provide a comprehensive understanding of many molecular processes in vivo, such as the functioning of the brain or immune system. Modalities that can provide such insights, such as magnetic resonance imaging (MRI) and positron emission tomography (PET), have highinfrastructure costs and often require very specialized contrast agents while ultrasound often shows relatively poor resolution. OA is much less expensive than MRI or PET, it can image tissues without exogenous contrast agents, and it provides better resolution than ultrasound. In OA, the sample is illuminated with short light pulses that are absorbed by chromophores, which show thermo-elastic expansion after non-radiative deexcitation, leading to the emission of transient acoustic waves 10,24 (Figure 3A), which are detected as pressure signals and reconstructed into an image using various inverse algorithms 25. Since OA detects ultrasound instead of light, it can penetrate to depths of several millimeters in tissue (Figure 3B), because tissue scatters sound much less than light. As a result, a complete mouse brain with a diameter of ̴1 cm can be imaged by OA but not by purely optical methods (Figure 3B). OA and its applications have been extensively reviewed 8,9 (Figure 3C).

Figure 3: Photo- or Optoacoustic (OA) imaging: (A) General principle of OA. (B) Relation of resolution and imaging depth for a number of OA and other imaging methods. AR, acoustic resolution; CFM, confocal fluorescence microscopy; OR, optical resolution; Adapted with permission from ref. 8. Copyright 2012 by AAAS. (C) OA application examples: tomography (e.g. multispectral OA tomography; MSOT, left), scanning acoustic focus mesoscopy (e.g. raster scanning OA mesoscopy; RSOM, middle) and OA microscopy (right). FOV = field-of-view. Coupling media is shown in blue (note: tomography is performed fully submerged).

OA based on endogenous contrast from hemoglobin or lipids is already established in preclinical and clinical research 9,26. However, its application to life science research is limited by the lack of appropriate labels, especially genetically encoded ones. This lack of labels is frustrating given that essentially any lightabsorbing molecule can function as an OA label. However, the signal strength is determined by the molar absorption as well as the QY and lifetime of non-radiative transitions that are on timescales detectable by transducers of common OA imaging systems (ns), this excludes contribution from very fast vibrational transitions (ps) as well as non-radiative transitions from triplet states (ms) 27 (Figure 2). Molecules that emit sufficiently strong acoustic signals after light absorption are hard to come by, partially because most efforts to develop labels have focused on labels for fluorescence imaging and so have tried to minimize the QY of non-radiative transitions. Genetically encoded labels 28 known from fluorescence imaging, such as EGFP and mCherry, have been used in OA, but their absorption is too blue-shifted to allow in vivo imaging of anything but transparent organisms such as zebrafish 29, due to

ACS Paragon Plus Environment

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

the overwhelming background signal from endogenous chromophores in the visible spectrum (e.g. hemoglobin) in mammals which hampers delineation of the label from other absorbers purely on the basis of spectral information. Another approach to generate OA labels is to express enzymes that catalyze reactions that generate light-absorbing products such as melanin 30, violacein 31 or galactopyranosides (e.g. X-Gal) 32. This approach has proven less effective because most products absorb in the visible range, too. Moreover, the product melanin emits a strong acoustic signal, but its production stresses cells and its absorption spectrum lacks features that can easily distinguish it from the background. To overcome these limitations to some extent, NIR-fluorescing phytochromes have been employed 33,34, but their signal is often too weak, and the concentration too low to give significant signal against the background of endogenous absorbers. Photo-control and signal unmixing in OA A more promising alternative for generating strong OA labels are proteins that, by virtue of their photo-switching, can generate a sufficiently strong signal over background even at lower, more physiological concentrations. Since the interconverting forms A and B differ in their QY and absorption, the excitation light can be used to modulate the strength of the OA signal, allowing it to be differentiated from non-modulating background absorption, such as from the abundant blood hemoglobin. To achieve this, the sample is repeatedly illuminated: first at a wavelength that switches the label to either an OAactive or -inactive state and subsequently with a second wavelength that induces the reverse transition (Figure 2C). Since the frequency at which the sample is illuminated with the second wavelength is known, OA signal modulation with the same frequency can be assigned as label and other signals as background (locked-in detection). This process is referred to as signal unmixing. To date this approach has been reported in five implementations: single 35 or dual differential imaging 14,15, temporal unmixing 38, multi-contrast temporal frequency lock-in photoacoustics reconstruction (LIR) 39 and difference-spectra demixing 40 (Figure 4). In single-wavelength differential imaging, the unmixing is done simply by subtracting the image acquired when the label is in the OA-active form (IA) from the image acquired after switching the label to the OA-inactive (IB) form with the appropriate wavelength (Figure 4A). (The OA-active and -inactive forms are named as depicted in Figure 2A.) Since only the label shows a change, it is readily distinguished from the background. The reversibility of switching allows for multiple repetitions, leading to robust enhancement of the contrast-to-noise ratio (CNR) 35. In the dual-wavelength differential approach, the concept of single-wavelength differential imaging is extended to include an intermediate state in which both OA-active and -inactive molecules (IA+B) are generated by simultaneously illuminating with both wavelengths. Difference images are obtained by subtracting the two single population images from the mixed one (Figure Figure 4: Principles of separating photo-controllable proteins from background signal: (A-C) depict the basic approaches: (A) Differential, (B) Double differential, (C) temporal unmixed and locked-in reconstruction (LIR). (D) Temporal multiplexing of two labels based on their characteristic photo-control kinetics. (E) Multiplexing based on difference spectra demixing. For all panels signal images are shown with background (red) and structure labeled with photo-controllable protein (black, blue, orange). Wavelengths of illumination are given as green and purple bars. The graphs depict idealized signal traces of the respective structure labeled with photo-controllable proteins. Basics calculation is depicted or indicated as VCA = vertical component analysis, for temporal unmixing and frequency space for LIR. Only the beginning of an image recording is shown in each case. Note, that the number of repetitions determines the CNR.

ACS Paragon Plus Environment

Page 6 of 15

Page 7 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

4B) 14,15. For example Märk and colleagues 37 converted the label BphP Agp1 sequentially from Pr to Pfr via an intermediate step (Pfr+r), and all three states could be differentiated based on time-resolved OA signals: Pfr absorbed primarily at 755 nm, the mixed population of Pfr and Pr showed peaks at 755 nm and 700 nm, and Pr showed a peak only at 700 nm. Subsequent differential imaging generates the unmixed image (SPfr,Pr - SPr - SPfr). One shortcoming of differential imaging is that it neglects the kinetics of the transition between OA-active and -inactive forms. Temporal unmixing and LIR take this kinetics into account, which can substantially improve the results. Temporal unmixing has been used with principal component analysis to extract modulation patterns from images, based on the known timing of illumination at different wavelengths 38 or by extracting the amplitudes of the harmonics of the pre-set photo-control frequency in LIR 39 (Figure 4C) . Another advantage of considering the kinetics of the transition between OA-active and -inactive forms is that the signals from multiple labels can be distinguished if their transition kinetics differ enough (Figure 4D). This allows the simultaneous imaging of several labels (multiplexing) while using only two wavelengths, thus reducing "spectral crowding" that normally limits how many labels can be used for a given set of wavelengths. An intermediate approach is difference-spectra demixing. Here two proteins that both absorb strongly at the photo-control wavelength but not at the second wavelength are imaged sequentially. The entire spectra of the proteins are recorded, and the final unmixed image is formed by taking advantage of the spectral differences between the two proteins. In this way, the crosstalk between the spectral overlap from the two reporter proteins can be minimized, facilitating multiplexing (Figure 4E) 40. It is interesting to note that similar concepts have already been applied in fluorescence imaging to separate modulated fluorescence signals from invariant background signal. These approaches include out-of-phase imaging after optical modulation 41, optical-locked-in-detection 42,43 and SAFIRe 44. However, invariant background noise in fluorescence imaging (autofluorescence) is usually relatively weak in biological samples, limiting the use of these methods. Photo-controllable proteins used in OA and their applications Conventional OA imaging relies on the signal of strong and abundant endogenous absorbers since most transgene labels tested for OA show too low CNR. In the future, employing photo-controllable labels and the unmixing strategies discussed above may provide the required robustness for efficient routine use of OA for the detection of small numbers of labeled cells, significantly expanding the possible uses of OA for life sciences. So far, a number of applications have showcased this potential, employing a number of photo-controllable proteins, most of them native BphPs. The conceptual basis and first experiments demonstrating the use of photo-control for OA were reported by Galanzha in 2013 45, albeit only using photo-convertible proteins. Since their transitions are irreversible (see above), the authors were able to observe only one differential signal. In vitro work using the RSFPs Dronpa and Dronpa-M159T 46 demonstrated the use of reversible photo-control and temporal unmixing of signals from blood. A subsequent study with a BphP from Rhodopseudomonas palustris reported the first in vivo work on OA photo-control 35. The authors visualized U87 cancer xenografts expressing BPhP1 in the liver despite strong intrinsic background from blood hemoglobin (Figure 5A). Two later studies based on the BphP Agp1 from Agrobacterium tumefaciens visualized subcutaneous HT29 tumors expressing AGP1 36,37 (Figure 5B). A drawback of native BphPs is that they are fairly large ( ̴80 kDa) and must dimerize to be functional 47,48. Consequently, the first attempts to engineer a BphP for OA have focused on creating a smaller, monomeric protein. Promising examples reported so far are a ~55-kDa monomeric protein from

ACS Paragon Plus Environment

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Deinococcus radiodurans 39 (DrBphP-PCM) and engineered monomeric cyanobacterial BphPs (~16 kDa) 40. Expressing smaller labels is likely to place a smaller metabolic burden on host cells. This expansion of photo-controllable proteins usable for in vivo OA imaging has already allowed the first examples of multiplexing using photo-control: Li et al. 39 injected U87 cells expressing RpBphP1 or DrBphP-PCM into the right rear or left front lobe of the brain. LIR was used to unmix the signals from the two probes based on the different transition kinetics. The same approach was used to resolve signals after injecting the two populations of cells into the kidney and liver (Figure 5C). Multiplexing has been used not only to image mammalian cells, but also to image bacteria invading a mammalian host. Chee at al.40 injected E. coli expressing cyanobacterial BphP, BphP1, and non-photo-controllable mIFP into the hind flank of a mouse and used difference-spectra demixing to separate the labels from background hemoglobin and from one another (Figure 5D). Detection of small numbers of bacteria in vivo in a whole organism is highly relevant to studying infection pathways and efficacy of treatment strategies, as well as following the effects of bacterial cancer therapies 49. Recently, the switching and photophysical characteristics of a range of RSFPs and BphPs have been compared spectroscopically 50. This work may facilitate the rational pairing of labels with appropriate imaging, switching and unmixing approaches. It may also help guide future engineering to optimize OA performance. Perspective Despite the number of promising studies using existing photo-controllable labels and unmixing algorithms, further work is needed to bring photo-control in OA to maturity and achieve the long-term goal of single-cell sensitivity in whole-animal studies. This will require advancement on several fronts: (i) more efficient transitions between the OA-active and -inactive forms to achieve more transitions in a given dwell-time (the time required to record an image), allowing robust unmixing; (ii) advanced illumination schemes and unmixing algorithms that allow extraction of as much differentiating information per illumination time as possible, and that compensate for movement and bleaching artifacts; and (iii) more labels with clearly distinguishable kinetics for each set of photo-control wavelengths in order to allow routine multiplexing in the time domain. Beyond GFP-like and BphPs it would be relevant to engineer other classes of chromophoric proteins, preferably with absorption in the NIR, to be photo-controllable, e.g. Phycobiliproteins. Analogously to the historical development of labels for fluorescence imaging, the next crucial step for developing photo-controllable OA labels is to create functional labels (sensors), that is, labels that provide information beyond the spatial position of the labeled structure or cell. The first such OA sensor can track protein-protein interactions in live cells using OA whole-animal tomography. Borrowing the complementation concept from fluorescence imaging 51, Li et al. expressed the DrPAS and DrGAF-PHY domains of DrBphP-PCM, and fused those individual domains to proteins that are known to interact. When the resulting fusion proteins are expressed and the binding partner come together, they reconstitute functional DrBphP-PCM 39 (Figure 5E). OA detection and unmixing of this label allowed visualization of a population as small as ~ 530 cells in tomographic images of an entire mouse in vivo. Along this road further sensors or indicator concepts known from fluorescence imaging can be translated to OA enabling further functional studies. For example, voltage-sensors with enhanced contrast through photo-control and temporal unmixing may enable the maturation of OA neuroimaging 52. Another interesting approach is to translate the way photo-controllable proteins are used in SR to OA. Yao and colleagues showed that a RESOLFT-like approach could achieve superior lateral resolution in comparison to conventional OA microscopy 35 (Figure 5F). Such "hybrid" approaches, which can combine ACS Paragon Plus Environment

Page 8 of 15

Page 9 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

the penetration depth of OA with the resolution enhancement of RESOLFT-like concepts, require adaptive optics to keep the quality of the photo-control light pattern through scattering tissue. Even if it proves impossible to achieve sub-diffraction resolution at centimeter depths, OA may still be able to mature from imaging only at the tissue level to imaging single cells at those depths if the resolution of whole-animal imaging can be increased to the few-micron level.

Figure 5: Examples of applications of photo-controllable proteins in OA: (A) Longitudinal OA tomography of cancer metastasis in a mouse liver using U87 cells expressing BphP1 and differential unmixing 35. (B) Volume-rendered 3D image of vascular morphology together with subcutaneous tumor of HT29 cells expressing AGP1 unmixed with the double differential strategy 37. (C) Multiplex detection (LIR) in the liver of HEK-293 cells expressing both DrBphP-PCM and RpBphP1 (left, blue) or U87 cells expressing DrBphP-PCM (right, red) 39. (D) Unmixing of bacteria expressing two photo-controllable proteins (BphP1 and sGPC2) and one strain expressing the invariant NIR label mIFP. All three populations were injected subcutaneously into a mouse. Unmixing was done by difference-spectra demixing 40. (E) Longitudinal imaging of protein-protein interactions during tumor growth using DrBphP-PCM and LIR unmixing 39 over more than one month. The increase in color tracks the increase in tumor growth visualized by interaction between two proteins, each one of which carries one half of the DrBphP-PCM label. Arrows indicate secondary tumors. (F) Bacteria expressing BphP1 were added to a coverslip and imaged using conventional OA (conv. PAM, left) or an approach similar to the RESOLFT concept (RS-PAM, right) 35. The RESOLFT-like approach improved lateral resolution. In order of appearance, images reproduced with permission from ref. 35, 37, 39, 40, 39 and 35. Copyright 2015, 2018, 2018, 2018, 2018 and 2015 by Nature Publishing Group, Nature Publishing Group, Nature Publishing Group, SPIE and Nature Publishing Group. All except 35 are reprinted under the Creative Commons Attribution 4.0 International License.

SUPPORTING INFORMATION No supporting information available AUTHOR INFORMATION Corresponding Author *E-mail: [email protected]. AUTHOR CONTRIBUTIONS

ACS Paragon Plus Environment

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

A.C.S. outlined and A.C.S. and K.M. wrote the manuscript. J.P.F-W. and V.N. contributed to the manuscript. V.N. is a shareholder of iThera Medical GmbH manufacturing OA imaging devices. All other authors declare no competing interests. ACKNOWLEDGMENTS The authors wish to thank A.C. Rodríguez, I. Weidenfeld, A. Chmyrov, M. Pleitez and A.L. Fuchs for discussions on the manuscript. K.M. receives funding from the Deutsche Forschungsgemeinschaft (STI656/1-1). BIOGRAPHIES Kanuj Mishra received his Diploma in Medical Biotechnology from the All India Institute of Medical Sciences (AIIMS), New Delhi, India. After a short stay at the Department for Neuroanatomy at the University of Saarland, Homburg, Germany he joined the Cell Engineering Group at the Institute for Biological and Medical Imaging (IBMI) at the Hemholtz Zentrum München, Germany, in 2017 as PhD student. Dr. rer. nat. Juan-Pablo Fuenzalida Werner studied pharmaceutical chemistry at the Universidad Austral de Chile, obtain his PhD in Biology from the University of Münster, Germany studying the interaction between polysaccharides and proteins. His first postdoctoral position at the University of Erlangen-Nürnberg was focused on the optimization of photosensitizer performance. Currently, he is a postdoctoral researcher in the Cell Engineering group at IBMI at the Helmholtz Zentrum München. Vasilis Ntziachristos, PhD, is Professor of Medicine, Professor of Electrical Engineering and Director of the Chair for Biological Imaging (CBI) at the Technical University of Munich, Director of the Institute for Biological and Medical Imaging (IBMI) at the Helmholtz Zentrum München and Director of Bioengineering at the Helmholtz Pioneering Campus. He has received the Diploma in Electrical Engineering and Computer Science from the Aristotle University of Thessaloniki, Greece and the M.Sc and PhD degrees in Bioengineering from the University of Pennsylvania in Philadelphia PA. Prior to his current appointment he was faculty at Harvard University and the Massachusetts General Hospital. Professor Ntziachristos is the Editor of the journal Photoacoustics, regularly Chairs in international meetings and councils and has received numerous awards and distinctions, including the Chaire Blaise Pascal (2019), the Gold Medal from the Society for Molecular Imaging (2015), the Gottfried Leibnitz prize from the German Research Foundation (2013), the Erwin Schrödinger Award (2012) and was named one of the world’s top innovators by the Massachusetts Institute of Technology (MIT) Technology Review in 2004. Dr. rer. nat. Andre C. Stiel is the head of the Cell Engineering group at IBMI at the Helmholtz Zentrum München focusing on the development of innovative transgene labels for Optoacoustics and other imaging methods. After receiving his Diploma in Biology from the Ruhr-Universität Bochum, Germany, he conducted his PhD studies at the Max Planck Institute for Biophysical Chemistry, Göttingen, in the group of Nobel Laureate Stefan Hell where he developed reversibly switchable fluorescent proteins for superresolution imaging. After receiving his PhD from the Ruprecht-Karls-Universität, Heidelberg, in 2008 he moved for a postdoctoral stay to the Max Planck Institute for Developmental Biology, Tübingen, where he worked on computer aided protein engineering in the group of Birte Höcker until he started his own group in Munich in 2015. REFERENCES

ACS Paragon Plus Environment

Page 10 of 15

Page 11 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

(1)

Beharry, A. A.; Woolley, G. A. Azobenzene Photoswitches for Biomolecules. Chem. Soc. Rev. 2011, 40 (8), 4422–4437. https://doi.org/10.1039/c1cs15023e.

(2)

Irie, M.; Fukaminato, T.; Matsuda, K.; Kobatake, S. Photochromism of Diarylethene Molecules and Crystals: Memories, Switches, and Actuators. Chem. Rev. 2014, 114 (24), 12174–12277. https://doi.org/10.1021/cr500249p.

(3)

O’Banion, C. P.; Lawrence, D. S. Optogenetics: A Primer for Chemists. Chembiochem 2018, 19 (12), 1201–1216. https://doi.org/10.1002/cbic.201800013.

(4)

Häusser, M. Optogenetics: The Age of Light. Nat. Methods 2014, 11 (10), 1012–1014. https://doi.org/10.1038/nmeth.3111.

(5)

Johnson, H. E.; Toettcher, J. E. Illuminating Developmental Biology with Cellular Optogenetics. Curr. Opin. Biotechnol. 2018, 52, 42–48. https://doi.org/10.1016/j.copbio.2018.02.003.

(6)

Eggeling, C.; Willig, K. I.; Sahl, S. J.; Hell, S. W. Lens-Based Fluorescence Nanoscopy. Q. Rev. Biophys. 2015, 48 (2), 178–243. https://doi.org/10.1017/S0033583514000146.

(7)

Sahl, S. J.; Moerner, W. Super-Resolution Fluorescence Imaging with Single Molecules. Curr. Opin. Struct. Biol. 2013, 23 (5), 778–787. https://doi.org/10.1016/j.sbi.2013.07.010.

(8)

Wang, L. V.; Hu, S. Photoacoustic Tomography: In Vivo Imaging from Organelles to Organs. Science. 2012, 335 (6075), 1458–1462. https://doi.org/10.1126/science.1216210.

(9)

Taruttis, A.; Ntziachristos, V. Advances in Real-Time Multispectral Optoacoustic Imaging and Its Applications. Nat Phot. 2015, 9 (4), 219–227. https://doi.org/10.1038/nphoton.2015.29.

(10)

Oraevsky, A. A.; Jacques, S. L.; Tittel, F. K. Measurement of Tissue Optical Properties by TimeResolved Detection of Laser-Induced Transient Stress. Appl. Opt. 1997, 36 (1), 402–415.

(11)

Shcherbakova, D. M.; Shemetov, A. a.; Kaberniuk, A. a.; Verkhusha, V. V. Natural Photoreceptors as a Source of Fluorescent Proteins, Biosensors, and Optogenetic Tools; 2014; Vol. 84. https://doi.org/10.1146/annurev-biochem-060614-034411.

(12)

Schmidt, D.; Cho, Y. K. Natural Photoreceptors and Their Application to Synthetic Biology. Trends Biotechnol. 2014, 1–12. https://doi.org/10.1016/j.tibtech.2014.10.007.

(13)

Shcherbakova, D. M.; Sengupta, P.; Lippincott-Schwartz, J.; Verkhusha, V. V. Photocontrollable Fluorescent Proteins for Superresolution Imaging. Annu. Rev. Biophys. 2014, 43, 303–329. https://doi.org/10.1146/annurev-biophys-051013-022836.

(14)

Nienhaus, K.; Ulrich Nienhaus, G. Fluorescent Proteins for Live-Cell Imaging with SuperResolution. Chem. Soc. Rev. 2014, 43 (4), 1088–1106. https://doi.org/10.1039/C3CS60171D.

(15)

Ando, R.; Mizuno, H.; Miyawaki, A. Regulated Fast Nucleocytoplasmic Shuttling Observed by Reversible Protein Highlighting. Science. 2004, 1370 (2004), 1–7. https://doi.org/10.1126/science.1102506.

(16)

Lukyanov, K. a; Fradkov, a F.; Gurskaya, N. G.; Matz, M. V; Labas, Y. a; Savitsky, a P.; Markelov, M. L.; Zaraisky, a G.; Zhao, X.; Fang, Y.; et al. Natural Animal Coloration Can Be Determined by a Nonfluorescent Green Fluorescent Protein Homolog. J. Biol. Chem. 2000, 275 (34), 25879–25882. https://doi.org/10.1074/jbc.C000338200.

(17)

Miyawaki, A.; Niino, Y. Molecular Spies for Bioimaging-Fluorescent Protein-Based Probes. Mol. Cell 2015, 58 (4), 632–643. https://doi.org/10.1016/j.molcel.2015.03.002.

(18)

Tsien, R. Y. Constructing and Exploiting the Fluorescent Protein Paintbox (Nobel Lecture). Angew. ACS Paragon Plus Environment

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Chemie Int. Ed. 2009, 48 (31), 5612–5626. https://doi.org/10.1002/anie.200901916. (19)

Shcherbakova, D. M.; Verkhusha, V. V. Chromophore Chemistry of Fluorescent Proteins Controlled by Light. Curr. Opin. Chem. Biol. 2014, 20, 60–68. https://doi.org/10.1016/j.cbpa.2014.04.010.

(20)

Rockwell, N. C.; Su, Y.-S.; Lagarias, J. C. Phytochrome Structure and Signaling Mechanisms. Annu. Rev. Plant Biol. is 2006, 57, 837–858. https://doi.org/10.1146/annurev.arplant.56.032604.144208.

(21)

Shcherbakova, D. M.; Baloban, M.; Verkhusha, V. V. Near-Infrared Fluorescent Proteins Engineered from Bacterial Phytochromes. Curr. Opin. Chem. Biol. 2015, 27, 52–63. https://doi.org/10.1016/j.cbpa.2015.06.005.

(22)

Kamper, M.; Ta, H.; Jensen, N. A.; Hell, S. W.; Jakobs, S. Near-Infrared STED Nanoscopy with an Engineered Bacterial Phytochrome. Nat. Commun. 2018, 9 (1), 4762. https://doi.org/10.1038/s41467-018-07246-2.

(23)

Stiel, A. C.; Andresen, M.; Bock, H.; Hilbert, M.; Schilde, J.; Schönle, A.; Eggeling, C.; Egner, A.; Hell, S. W.; Jakobs, S. Generation of Monomeric Reversibly Switchable Red Fluorescent Proteins for Far-Field Fluorescence Nanoscopy. Biophys. J. 2008, 95 (6), 2989–2997. https://doi.org/10.1529/biophysj.108.130146.

(24)

Rosencwaig, A. Photoacoustic Spectroscopy of Biological Materials. Science. 1973, 181 (4100), 657–658. https://doi.org/10.1126/science.181.4100.657.

(25)

Lutzweiler, C.; Razansky, D. Optoacoustic Imaging and Tomography: Reconstruction Approaches and Outstanding Challenges in Image Performance and Quantification. Sensors (Basel). 2013, 13 (6), 7345–7384. https://doi.org/10.3390/s130607345.

(26)

Wang, L. V; Gao, L. Photoacoustic Microscopy and Computed Tomography: From Bench to Bedside. Annu. Rev. Biomed. Eng. 2014, 16, 155–185. https://doi.org/10.1146/annurev-bioeng071813-104553.

(27)

Schaberle, F. A.; Rego Filho, F. de A. M. G.; Reis, L. A.; Arnaut, L. G. Assessment of Lifetime Resolution Limits in Time-Resolved Photoacoustic Calorimetry vs. Transducer Frequencies: Setting the Stage for Picosecond Resolution. Photochem. Photobiol. Sci. 2016, 15 (2), 204–210. https://doi.org/10.1039/c5pp00397k.

(28)

Brunker, J.; Yao, J.; Laufer, J.; Bohndiek, S. E. Photoacoustic Imaging Using Genetically Encoded Reporters: A Review. J. Biomed. Opt. 2017, 22 (7), 070901. https://doi.org/10.1117/1.JBO.22.7.070901.

(29)

Razansky, D.; Distel, M.; Vinegoni, C.; Ma, R.; Perrimon, N.; Köster, R. W.; Ntziachristos, V. Multispectral Opto-Acoustic Tomography of Deep-Seated Fluorescent Proteins in Vivo. Nat. Photonics 2009, 3 (7), 412–417. https://doi.org/10.1038/nphoton.2009.98.

(30)

Stritzker, J.; Kirscher, L.; Scadeng, M.; Deliolanis, N. C.; Morscher, S.; Symvoulidis, P.; Schaefer, K.; Zhang, Q.; Buckel, L.; Hess, M.; et al. Vaccinia Virus-Mediated Melanin Production Allows MR and Optoacoustic Deep Tissue Imaging and Laser-Induced Thermotherapy of Cancer. Proc. Natl. Acad. Sci. U. S. A. 2013, 110 (9), 3316–3320. https://doi.org/10.1073/pnas.1216916110.

(31)

Jiang, Y.; Sigmund, F.; Reber, J.; Luís Deán-Ben, X.; Glasl, S.; Kneipp, M.; Estrada, H.; Razansky, D.; Ntziachristos, V.; Westmeyer, G. G. Violacein as a Genetically-Controlled, Enzymatically Amplified and Photobleaching-Resistant Chromophore for Optoacoustic Bacterial Imaging. Sci. Rep. 2015, 5 (May), 11048. https://doi.org/10.1038/srep11048. ACS Paragon Plus Environment

Page 12 of 15

Page 13 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

(32)

Li, L.; Zemp, R. J.; Lungu, G.; Stoica, G.; Wang, L. V. Photoacoustic Imaging of LacZ Gene Expression in Vivo. J. Biomed. Opt. 2013, 12 (2), 020504. https://doi.org/10.1117/1.2717531.

(33)

Filonov, G. S.; Krumholz, A.; Xia, J.; Yao, J.; Wang, L. V.; Verkhusha, V. V. Deep-Tissue Photoacoustic Tomography of a Genetically Encoded near-Infrared Fluorescent Probe. Angew. Chem. Int. Ed. Engl. 2012, 51 (6), 1448–1451. https://doi.org/10.1002/anie.201107026.

(34)

Deliolanis, N. C.; Ale, A.; Morscher, S.; Burton, N. C.; Schaefer, K.; Radrich, K.; Razansky, D.; Ntziachristos, V. Deep-Tissue Reporter-Gene Imaging with Fluorescence and Optoacoustic Tomography: A Performance Overview. Mol. Imaging Biol. 2014, 16 (5), 652–660. https://doi.org/10.1007/s11307-014-0728-1.

(35)

Yao, J.; Kaberniuk, A. A.; Li, L.; Shcherbakova, D. M.; Zhang, R.; Wang, L.; Li, G.; Verkhusha, V. V; Wang, L. V. Multiscale Photoacoustic Tomography Using Reversibly Switchable Bacterial Phytochrome as a Near-Infrared Photochromic Probe. Nat. Methods 2015, No. November, 1–9. https://doi.org/10.1038/nmeth.3656.

(36)

Dortay, H.; Märk, J.; Wagener, A.; Zhang, E.; Grötzinger, C.; Hildebrandt, P.; Friedrich, T.; Laufer, J. Dual-Wavelength Photoacoustic Imaging of a Photoswitchable Reporter Protein; Oraevsky, A. A., Wang, L. V., Eds.; International Society for Optics and Photonics, 2016; Vol. 9708, p 970820. https://doi.org/10.1117/12.2208259.

(37)

Märk, J.; Dortay, H.; Wagener, A.; Zhang, E.; Buchmann, J.; Grötzinger, C.; Friedrich, T.; Laufer, J. Dual-Wavelength 3D Photoacoustic Imaging of Mammalian Cells Using a Photoswitchable Phytochrome Reporter Protein. Commun. Phys. 2018, 1 (1), 3. https://doi.org/10.1038/s42005017-0003-2.

(38)

Stiel, A. C.; Luís Deán-Ben, + X; Jiang, Y.; Ntziachristos, V.; Razansky, D.; Westmeyer, G. G. High Contrast Imaging of Reversibly Switchable Fluorescent Proteins via Temporally Unmixed Multispectral Optoacoustic Tomography (TuMSOT). Opt. Lett. 2015, 40 (20), 4691–4694. https://doi.org/10.1364/OL.40.004691.

(39)

Li, L.; Shemetov, A. A.; Baloban, M.; Hu, P.; Zhu, L.; Shcherbakova, D. M.; Zhang, R.; Shi, J.; Yao, J.; Wang, L. V.; et al. Small Near-Infrared Photochromic Protein for Photoacoustic Multi-Contrast Imaging and Detection of Protein Interactions in Vivo. Nat. Commun. 2018, 9 (1), 2734. https://doi.org/10.1038/s41467-018-05231-3.

(40)

Chee, R. K. W.; Li, Y.; Zhang, W.; Campbell, R. E.; Zemp, R. J. In Vivo Photoacoustic DifferenceSpectra Imaging of Bacteria Using Photoswitchable Chromoproteins. J. Biomed. Opt. 2018, 23 (10), 1–11. https://doi.org/10.1117/1.JBO.23.10.106006.

(41)

Quérard, J.; Zhang, R.; Kelemen, Z.; Plamont, M. A.; Xie, X.; Chouket, R.; Roemgens, I.; Korepina, Y.; Albright, S.; Ipendey, E.; et al. Resonant Out-of-Phase Fluorescence Microscopy and Remote Imaging Overcome Spectral Limitations. Nat. Commun. 2017, 8 (1), 1–8. https://doi.org/10.1038/s41467-017-00847-3.

(42)

Abbandonato, G.; Storti, B.; Signore, G.; Beltram, F.; Bizzarri, R. Quantitative Optical Lock-in Detection for Quantitative Imaging of Switchable and Non-Switchable Components. Microsc. Res. Tech. 2016, 79 (10), 929–937. https://doi.org/10.1002/jemt.22724.

(43)

Marriott, G.; Mao, S.; Sakata, T.; Ran, J.; Jackson, D. K.; Petchprayoon, C.; Gomez, T. J.; Warp, E.; Tulyathan, O.; Aaron, H. L.; et al. Optical Lock-in Detection Imaging Microscopy for ContrastEnhanced Imaging in Living Cells. Proc. Natl. Acad. Sci. U. S. A. 2008, 105 (46), 17789–17794. https://doi.org/10.1073/pnas.0808882105.

(44)

Hsiang, J.-C.; Jablonski, A. E.; Dickson, R. M. Optically Modulated Fluorescence Bioimaging: ACS Paragon Plus Environment

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Visualizing Obscured Fluorophores in High Background. Acc. Chem. Res. 2014, 47 (5), 1545–1554. https://doi.org/10.1021/ar400325y. (45)

Galanzha, E. E. I.; Nedosekin, D. a; Sarimollaoglu, M.; Orza, A. I.; Biris, A. S.; Verkhusha, V. V; Zharov, V. P. Photoacoustic and Photothermal Cytometry Using Photoswitchable Proteins and Nanoparticles with Ultrasharp Resonances. J. Biophotonics 2013, 13, 1–13. https://doi.org/10.1002/jbio.201300140.

(46)

Stiel, A. C.; Deán-Ben, X. L.; Jiang, Y.; Ntziachristos, V.; Razansky, D.; Westmeyer, G. G. HighContrast Imaging of Reversibly Switchable Fluorescent Proteins via Temporally Unmixed Multispectral Optoacoustic Tomography. Opt. Lett. 2015, 40 (3), 367–370. https://doi.org/10.1364/OL.40.000367.

(47)

Scheerer, P.; Michael, N.; Park, J. H.; Noack, S.; Förster, C.; Hammam, M. A. S.; Inomata, K.; Choe, H.-W.; Lamparter, T.; Krauss, N. Crystallization and Preliminary X-Ray Crystallographic Analysis of the N-Terminal Photosensory Module of Phytochrome Agp1, a Biliverdin-Binding Photoreceptor from Agrobacterium Tumefaciens. J. Struct. Biol. 2006, 153 (1), 97–102. https://doi.org/10.1016/j.jsb.2005.11.002.

(48)

Bellini, D.; Papiz, M. Z. Structure of a Bacteriophytochrome and Light-Stimulated Protomer Swapping with a Gene Repressor. Structure 2012, 20, 1436–1446. https://doi.org/10.1016/j.str.2012.06.002.

(49)

Zhou, S.; Gravekamp, C.; Bermudes, D.; Liu, K. Tumour-Targeting Bacteria Engineered to Fight Cancer. Nat. Rev. Cancer 2018, 18 (12), 727–743. https://doi.org/10.1038/s41568-018-0070-z.

(50)

Vetschera, P.; Mishra, kanuj; Fuenzalida Werner, J.-P.; Chmyrov, A.; Ntziachristos, V.; Stiel, A. C. Characterization of Reversibly Switchable Fluorescent Proteins (RsFPs) in Optoacoustic Imaging. Anal. Chem. 2018. https://doi.org/10.1021/acs.analchem.8b02599.

(51)

Shekhawat, S. S.; Ghosh, I. Split-Protein Systems: Beyond Binary Protein-Protein Interactions. Curr. Opin. Chem. Biol. 2011, 15 (6), 789–797. https://doi.org/10.1016/j.cbpa.2011.10.014.

(52)

Ovsepian, S. V; Olefir, I.; Westmeyer, G.; Razansky, D.; Ntziachristos, V. Pushing the Boundaries of Neuroimaging with Optoacoustics. Neuron 2017, 96 (5), 966–988. https://doi.org/10.1016/j.neuron.2017.10.022.

ACS Paragon Plus Environment

Page 14 of 15

Page 15 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

ACS Paragon Plus Environment