Redox imaging using genetically encoded redox indicators in zebrafish and mice

Michael O. Breckwoldt, Christine Wittmann 3 , Thomas Misgeld, Martin Kerschensteiner and Clemens Grabher 3
  • 1 Department of Neuroradiology, University of Heidelberg, Im Neuenheimer Feld 400, D-69120 Heidelberg, Germany
  • 2 Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany
  • 3 Karlsruhe Institute für Technologie (KIT), Institut für Toxikologie und Genetik (ITG), Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen, Germany
  • 4 Institute for Neuronal Cell Biology, Technical University Munich, D-80802 Munich, Germany
  • 5 Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
  • 6 Center of Integrated Protein Sciences, Munich, Germany
  • 7 German Center for Neurodegenerative Diseases, Munich, Germany
  • 8 Institute of Clinical Neuroimmunology, Ludwig Maximilians University Munich, D-81377 Munich, Germany
Michael O. Breckwoldt, Christine Wittmann, Thomas Misgeld, Martin Kerschensteiner and Clemens Grabher

Abstract

Redox signals have emerged as important regulators of cellular physiology and pathology. The advent of redox imaging in vertebrate systems now provides the opportunity to dynamically visualize redox signaling during development and disease. In this review, we summarize recent advances in the generation of genetically encoded redox indicators (GERIs), introduce new redox imaging strategies, and highlight key publications in the field of vertebrate redox imaging. We also discuss the limitations and future potential of in vivo redox imaging in zebrafish and mice.

Introduction

Redox signals play a pivotal role in cellular physiology and pathology (Lin and Beal, 2006; D’Autréaux and Toledano, 2007; Murphy et al., 2011; Kaludercic et al., 2014). Redox sensitive GFP (roGFP) variants and circular permutated YFP (cpYFP) derivatives have been developed for ratiometric imaging of such signals. These fluorescent proteins have major advantages over conventional fluorescent redox dyes. First, they are genetically encoded and can thus be stably expressed in transgenic animals and targeted to the site of interest. Second, they provide superior photostability over common synthetic dyes and allow long-term investigations for days to months. Finally, in contrast to most synthetic redox dyes, roGFP and cpYFP are ratiometric indicators. Thus, signals are less dependent on sensor concentration or location, alleviating artifacts arising from sample movement or varying expression levels. Detailed information on the history, development, and properties of current GERIs is excellently compiled in recent reviews (Meyer and Dick, 2010; Tantama et al., 2012; Lukyanov and Belousov, 2013; Ezeriņa et al., 2014). We refer to additional publications for information on redox imaging in invertebrate systems (C. elegans and Drosophila; Albrecht et al., 2011; Barata and Dick, 2013; Lukyanov and Belousov, 2013; Wang et al., 2014).

roGFP and its variants

The field has come a long way since the first demonstrations of redox imaging using genetically encoded biosensors in vitro and in cell culture about a decade ago (Dooley et al., 2004; Hanson et al., 2004). Originally, the groups of Tsien and Remington developed redox sensitive GFP 1 and 2 (Dooley et al., 2004; Hanson et al., 2004) as the prototypical GERI. To render GFP redox sensitive, two thiol groups were genetically engineered into the ß-sheet backbone of GFP close to the chromophore. The oxidative formation of a disulfide bond dramatically changes the fluorescent properties of this new sensor, thus enabling absorption ratiometric measurements. A fundamental improvement came in 2008 when the lab of Dick coupled roGFP2 to the enzyme glutaredoxin 1 (Gutscher et al., 2008). This significantly improved the kinetics and specificity of the sensor, because glutaredoxin transfers the electron directly from oxidized glutathione (GSSG) to roGFP2, which allows for sensing the glutathione redox potential. Given that glutathione acts as an important cofactor for many redox reactions (Kumar et al., 2011), the ratio of GSSG:GSH is seen as a surrogate marker of ‘oxidative stress’. The strategy of enzyme-coupling roGFP2 was reemployed to fuse roGFP2 to Orp1, an H2O2-sensitive peroxidase from yeast. Orp1 reduces H2O2 and transfers the electron to roGFP2 (Gutscher et al., 2009); thus, roGFP2-Orp1 acts as a specific H2O2 sensor.

cpYFP and its variants

Additional redox sensitive fluorescent sensors include cpYFP and HyPer (Belousov et al., 2006; Wang et al., 2008; Bilan et al., 2013). cpYFPs were developed by the group of Miyawaki and serve as core structure of the genetically encoded calcium indicator Pericam (Nagai et al., 2001, 2002). Independently, the group of Lukyanov developed cpYFP as the basis for HyPer. In both cases, cpYFP bears the mutation Y203F, which renders the protonated form of the chromophore fluorescent (Nagai et al., 2001; Belousov et al., 2006). Thus, cpYFP exhibits two excitation peaks at 405 nm (protonated chromophore) and 490 nm (deprotonated chromophore) as well as a single emission peak at 515 nm. Therefore, cpYFP is ratiometric in excitation. HyPer was recently permutated into HyPer-3, resulting in an improved dynamic range (Bilan et al., 2013). Moreover, HyPerRed, a red-shifted H2O2 sensor, was recently engineered (Ermakova et al., 2014). HyPerRed is pH sensitive and non-ratiometric. Although HyPerRed has only been applied in cell culture so far, the red variant should facilitate co-imaging with other fluorescent reporters. cpYFP was also reported to be sensitive to superoxide (Wang et al., 2008). However, its reactivity towards superoxide is currently a matter of debate (Schwarzländer et al., 2014; Shen et al., 2014). For an overview of available sensors, see Table 1.

Table 1

Properties of GERIs applied in zebrafish and mice.

SensorSpecificityOne photon excitationTwo photon excitationEmissionpH sensitivityReferences
roGFP1Thiol/disulfide equlibrium405/475800/900505n.s.(Dooley et al., 2004; Hanson et al., 2004; Xie et al., 2013)
roGFP2Thiol/disulfide equlibrium400/490n.a.505n.s.
Grx1-roGFP22 GSH/GSSH400/490800/940505n.s.(Gutscher et al., 2008; Breckwoldt et al., 2014)
roGFP2-Orp1H2O2400/490n.a.505n.s.(Gutscher et al., 2009)
cpYFPpH/superoxide(?)405/490n.a.515Significant(Wang et al., 2008)
HyPer1H2O2420/500760/920515Significant(Belousov et al., 2006)
HyPer3H2O2420/500n.a.515Significant(Bilan et al., 2013)

n.a., not assessed; n.s., not significant; ?, the specificity of cpYPF is a matter of debate.

Imaging redox dynamics in mice and zebrafish

General considerations

Before getting started on redox imaging (in or ex vivo) using GERIs. The following three aspects have to be considered for the intended experiment:

  1. The anatomical site of imaging – Which imaging preparation enables the best visual access?
  2. The type of redox sensor – Which redox species is of interest and how will the sensor be expressed?
  3. The imaging approach – Which type of microscopy is suitable?

Choice of imaging site

With regards to the imaging site and preparation, most redox studies in vertebrates have so far taken advantage of mice or zebrafish. For redox imaging in mice, a number of applications have been established, especially in the field of neuroscience. These allow, e.g., the visualization of mitochondrial and cytoplasmic redox dynamics at different anatomical sites in the central and peripheral nervous system (Figure 1A). Approaches include ex vivo imaging of acute explants (e.g., cerebral slices, nerve-muscle explants, Carlson and Coulter, 2008; Kerschensteiner et al., 2008; Guzman et al., 2010) as well as in vivo imaging of the intact nervous system (cortex, spinal cord, peripheral nerve; Trachtenberg et al., 2002; Lichtman and Sanes, 2003; Brecht et al., 2004; Kerschensteiner et al., 2005; Misgeld and Kerschensteiner, 2006; Drew et al., 2010). So far, Investigations mainly focused on visualizing pathological redox signaling in neurological disease models. Studies of physiological redox signals that use, e.g., sensory stimuli or behavioral paradigms, have not yet been performed. All of the aforementioned approaches require a high level of imaging expertise to establish stable imaging conditions that do not disrupt physiological processes. Moreover, there are a number of challenging optical prerequisites (e.g., accessibility to deep tissue structures, excitation ratiometry for roGFP and cpYFP-based probes). These challenges probably explain why in vivo redox imaging using GERIs in mice has not yet been performed more extensively. Still, informative applications in other biomedical fields (e.g., cardiovascular, immunology, cancer) can be envisaged and are certainly underway.

Figure 1:
Figure 1:

Imaging physiological and pathological mitochondrial redox signals in mice.

Panel (A) indicates different imaging sites that are accessible to redox imaging in mice. Panel (B) illustrates multiparameter imaging in an axotomy paradigm. A spreading wave of permanent glutathione oxidation, mitochondrial acidification, and calcium elevation is induced upon axotomy. White dashed line indicates axotomy site by a pulsed laser. Panel (C) shows a spontaneous mitochondrial contraction under physiological conditions. These contractions go along with a transient oxidation of the glutathione pool and a temporary shortening of the organelle. Multiparameter imaging reveals a concomitant pH increase followed by long lasting matrix acidification (mito-SypHer). Calcium influx plays no major role in the contraction process (mito-RGECO-1). Experiments were performed in Thy1-Grx1-roGFP2 mice (B to C). (D) Scheme summarizes the two kinds of redox signals found under pathological (rounding/fragmentation) and physiological conditions (contraction). y-Axis labeling indicates the signal directions. The mitochondrial inner membrane potential (ψ) increases (indicated by a drop in TMRM fluorescence), whereas the matrix pH (measured by SypHer) shows a short matrix alkalization, followed by an acidification during mitochondrial rounding and contraction. ox: oxidized. Scale bars in (A), brain: 200 μm, spinal cord: 20 μm, peripheral nerve: 5 μm, retina: 25 μm, heart muscle: 20 μm; (B): 2 μm; (C): 5 μm. Images modified and reproduced with permission from Breckwoldt et al. (2014) and Wang et al. (2008). Grx1-roGFP2 retina image: M. Breckwoldt, unpublished.

Citation: Biological Chemistry 396, 5; 10.1515/hsz-2014-0294

For zebrafish, the situation is less complicated, as one of the major advantages of this model organism is its small size and optical transparency at the embryonic and early juvenile stages. In addition, several pigment mutant strains provide partially transparent fish even at adult stages (Rawls et al., 2001; White et al., 2008). The choice of imaging site is thus less confined by practical considerations than by the experimental question, for the majority of which microscopy solutions – including appropriate tools for analysis – are available. Nevertheless, redox imaging has rarely been performed before the arrival of ratiometric GERIs and has gained considerable attention since the study conducted by Niethammer et al. (2009).

Choice of the redox sensor

The decision as to which GERI to use depends critically on the redox species one aims to monitor. Unfused roGFPs, similar to Grx1-roGFP2, equilibrate with the glutathione redox pair indicating the glutathione redox potential. Thus, the equilibration depends on endogenous glutaredoxins. The advantage of Grx1-roGFP2 is that it provides improved kinetics when compared to unfused roGFPs through the direct coupling of the catalyst glutaredoxin 1 to roGFP2. How much a specific reactive species contributes to the roGFP signal ultimately depends on the circumvention of kinetic barriers through a specific catalyst. For example, H2O2 can be monitored by fusing the catalyst Orp1 to roGFP2 (roGFP2-Orp1). Alternatively, H2O2 may be measured by the cpYFP-based sensor HyPer (for additional sensor characteristics, see Table 2).

Table 2

Available mouse and zebrafish strains expressing GERIs.

Expressed GERICellular compartmentLocation of expressionReferences
Mouse line
Thy1-mito-Grx1-roGFP2Grx1-roGFP2MitochondriaNeurons in CNS and PNS(Breckwoldt et al., 2014)
 TH-mito-roGFP2roGFP2MitochondriaDopaminergic neurons(Guzman et al., 2010)
 CMV-mito-roGFP2roGFP2CytoplasmAll body cells(Guzman et al., 2010; Goldberg et al., 2012; Sena et al., 2013)
 α-MHC-mito-cpYFPcp-YFPCytoplasmCardiomyocytes, muscle(Wang et al., 2008)
Zebrafish line
 Tg(lyzC:HyPer)HyPerCytoplasmNeutrophils(Pase et al., 2012)
 Tg(myl7:HyPer)HyPerCytoplasmCardiac tissue(Han et al., 2014)
 Tg(actb2:HyPer3)HyPer3CytoplasmAll body cells(Bilan et al., 2013)
 Tg(actb1:Hsa.Grx1-roGFP)Grx1-roGFP2CytoplasmAll body cells(Seiler et al., 2012)
 Tg(actb2:roGFP2-Orp1)roGFP2-Orp1CytoplasmAll body cells(Grabher, unpub.)
 Tg(actb2:Grx1-roGFP2)Grx1-roGFP2CytoplasmAll body cells(Grabher, unpub.)

For expression of GERIs in vertebrate organisms, a range of options exists. In mice, viral labeling strategies, e.g., with adeno-associated virus particles (AAVs) or lentiviral constructs, have been successfully used to express fluorescent proteins as well as GERIs (Dittgen et al., 2004; Klugmann et al., 2005; Xie et al., 2013). Alternatively, first genetically modified mouse strains that stably express GERIs are now available (Table 2). In zebrafish, if uniform sensor expression is desired, the easiest way to administer GERIs is through mRNA injections into the one-cell stage. This approach allows transient analysis of redox events in embryos up to ∼5 days post fertilization. For mosaic sensor expression, the method of choice is injection of DNA. Given that DNA molecules are distributed randomly within the cells of a developing embryo, only individual cells will express the transgene (O’Donnell et al., 2013). Meanwhile, a few stable transgenic strains were established, which allow redox imaging at later stages and even in adults (Table 2). By choosing the appropriate imaging and labeling approaches, redox signals can be visualized in a variety of cellular locations (cytoplasm, mitochondria, endoplasmatic reticulum, nucleus) and cell types (neurons, glia, leukocytes, tumor cells) in both zebrafish and mice.

Choice of imaging approach

One central challenge for redox imaging is the establishment of suitable microscopy approaches. Excitation ratiometric imaging of roGFP variants or cpYFP-based probes can be performed using a range of microscopes and setups. Commonly, widefield microscopy is used to switch between two alternating wavelengths (mostly 408 nm and 488 nm). Other sensors in the higher wavelength spectrum (orange to red) can be incorporated into the experiment to measure additional parameters, such as the mitochondrial membrane potential (e.g., using TMRM, Chazotte, 2011) in addition to the redox state (Guzman et al., 2010; Breckwoldt et al., 2014). Zebrafish and murine explants (e.g., triangularis sterni preparation) or peripheral nerve preparations are often well accessible by widefield microscopy (Kerschensteiner et al., 2008; Rieger et al., 2011; Marinković et al., 2012; Weber and Köster, 2013). However, poor depth penetration due to light scattering limits the use of widefield microscopy in mice.

Fast multi-wavelengths imaging is also possible using confocal microscopy. Switching of the standard 405 nm and 488 nm laser lines can be performed with alternating line scans on the order of milliseconds (Breckwoldt et al., 2014). Confocal microscopy allows optical sectioning and acquisition of imaging stacks by means of using a point source of excitation and a conjugate pinhole in front of the detector (Lichtman and Conchello, 2005). One concern in ratiometric imaging is that the two wavelengths interact differently with optical components and tissue, which can interfere with obtaining accurate ratios. For example, the shorter wavelength 405 nm is absorbed and scattered to a higher degree in biological tissues than the longer wavelengths at 488 nm. The degree of light absorption and scatter can also dynamically change in different depths and with variable tissue compositions. Furthermore, properties of the optics themselves (e.g., lack of proper chromatic correction) can lead to variations of measured ratios, e.g., in different locations within the field of view. These factors can ultimately lead to artificial ‘redox’ ratios that can mimic redox changes and, therefore, require careful controls.

Two-photon microscopy (2PM) offers another imaging approach that is especially suitable for in vivo applications as it allows imaging deeper into tissues (500 μm to 1 mm in the CNS). This is due to the reduction of out-of focus emission (and, incidentally, phototoxicity), as well as the resilience to scatter afforded by the non-linearity of two-photon excitation and the near-infrared wavelengths employed (Helmchen and Denk, 2005; Kerr and Denk, 2008). Suitable 2PM wavelengths for Grx1-roGFP2 imaging are 800 nm and 940 nm (Breckwoldt et al., 2014). For roGFP1 imaging, 800 nm and 900 nm were described as optimal wavelengths (Xie et al., 2013). However, using 2PM for redox imaging is more challenging than single photon imaging. Constant tuning of the excitation laser between two wavelengths is necessary. Tuning the laser takes time (on the order of seconds in most laser systems) so that shifts in the imaging plane can occur. In general, excitation ratiometric imaging requires stable imaging conditions as motion can cause shifts in the imaging plane. Hence, small shifts in the μm range can prevent reliable measurements of small structures, such as cellular organelles. This is less critical when larger cellular compartments, such as the cytosol, are assessed. Possible solutions in 2PM include one-wavelength imaging with careful stabilization and calibration (Guzman et al., 2010). Such calibration of roGFP and its variants can, for example, be performed with reductants (e.g., dithiothreitol, DTT) and oxidants (e.g., H2O2, aldithriol, or diamide). The usage of relative change in fluorescence (ΔF/F) measurements is recommended when applying single wavelength imaging, which however, will markedly diminish the dynamic range of the sensor and render the measurements non ratiometric, thus making it difficult to compare absolute redox levels in different structures and sites. This is why two wavelength absorption ratiometric imaging is recommended whenever possible. Moreover, instead of tuning one laser, two 2-photon lasers can be employed, if available – a proposition that might become more realistic with single laser systems that emit two beams of differential wavelength or fixed-wavelength laser systems, which are more affordable than classical titanium: sapphire-based systems.

Insights from redox imaging in mice

First reports in mice studied redox changes in neurons using models of neurological disease with conventional roGFP2. In a landmark paper in 2010, the lab of Surmeier demonstrated that mitochondrial oxidative stress, quantified with roGFP2, occurred in dopaminergic neurons in a model of Parkinson’s disease (PD). The authors used acute brain slices of transgenic TH-mito-roGFP2 mice (tyrosin-hydroxylase, TH, a promoter active in dopamine-expressing neurons) to selectively express mitochondrial roGFP2 in dopaminergic circuits. ‘Oxidative stress’ was caused by a specific L-type calcium pacemaker current that led to permanent mitochondrial oxidation (Guzman et al., 2010). This finding is of particular interest because loss of dopaminergic neurons is a key feature of PD. In this model, mitochondrial oxidative stress was reduced by mild mitochondrial uncoupling via uncoupling proteins (UCPs). The gene DJ-1 increased the expression of UCP 4 and 5, thus lowering oxidative stress levels. Notably, mutations in the DJ-1 gene are responsible for a familial form of PD. Similar effects of calcium currents on mitochondrial oxidation were recently identified in other dopaminergic circuits (Goldberg et al., 2012; Sanchez-Padilla et al., 2014) affected in PD.

The first in vivo demonstration of roGFP1 imaging was performed in a model of Alzheimer’s disease (AD; Xie et al., 2013). Here, the authors investigated the role of oxidative stress in AD using a cranial window approach. roGFP1 was cytoplasmically expressed in neurons by AAV-mediated gene transfer. Using this approach, increased roGFP1 oxidation was found in neurons in the immediate vicinity (<20 μm) of amyloid-ß plaques. Interestingly, roGFP1 oxidation preceded neuronal apoptosis. The authors suggest that oxidative stress is first generated in neurites and subsequently spreads to the soma where it induces caspase-dependent apoptosis and neuronal loss.

More recently, newer genetically encoded redox indicators, such as Grx1-roGFP2, have been used for in vivo redox imaging. Here, transgenic mouse lines expressing Grx1-roGFP2 in neuronal mitochondria allowed the in vivo analysis of mitochondrial redox changes in different neurological disease models [spinal cord injury, SCI and amyotrophic laterals sclerosis (ALS; Breckwoldt et al., 2014)]. Imaging Thy1-mito-Grx1-roGFP2 mice and the establishment of ‘multi-parametric’ imaging using additional mitochondrially expressed biosensors allowed deciphering pathological redox dynamics and their mechanistic underpinnings. A model of spinal cord injury resulted in permanent mitochondrial glutathione oxidation, which spread from the transection site along axons at a speed of ∼2.4 μm/s (Figure 1B). Oxidation was followed by mitochondrial shortening and fragmentation (spread: ∼1.4 μm/s). Mechanistically, oxidation was initiated by an influx of extracellular calcium (measured with mito-RGECO1 and Thy1-TnXXL mice) and was mitigated by knockdown of cyclophilin D (Schinzel et al., 2005). A similar spread of mitochondrial oxidation upon acute lesion was found in the cerebral cortex and peripheral nerves. In Thy1-mito-Grx1-roGFP2 mice also allowed analysis of physiological redox dynamics. For example, spontaneous redox signals (‘mitochondrial contractions’) were observed in some mitochondria (Figure 1C), and might represent a ‘safety fuse’ to avoid mitochondrial over-activity. Contracting mitochondria showed a reversible oxidation of the glutathione pool accompanied by changes in mitochondrial pH (measured using mito-SypHer; Figure 1C) and membrane potential (TMRM). Contractions occurred in healthy neurons, but increased in frequency under oxidative and physiological ‘stress’ conditions (e.g., exogenous H2O2 application, increased electrical activity).

Apart from roGFP imaging in neurons, cpYFP imaging was also performed in transgenic mice (Wang et al., 2008). This study was the first demonstration of cpYFP imaging in the cardiovascular field. Cardiac myocytes were investigated under hypoxia-reperfusion conditions in α-MHC-mito-cpYFP mice ex vivo, as the heart is difficult to image in situ. Wang et al. described ‘superoxide flashes’ in single mitochondria that increased in frequency after reperfusion, and interpreted this phenomenon as quantal superoxide release. However, as cpYFP is highly pH-sensitive, another interpretation suggests that these flashes might represent mitochondrial pH spikes (Schwarzländer et al., 2011, 2012).

Insights from redox imaging in zebrafish

Redox imaging studies in zebrafish were mainly done by using the genetically encoded sensor HyPer to detect spatiotemporal changes in H2O2 concentrations. In recent years, HyPer has been employed to uncover a novel role of H2O2 as a mediator of acute inflammation responsible for leukocyte recruitment to sites of trauma.

The study of Niethammer et al. described, for the first time, that H2O2 was generated by wounded epithelium (Figure 2, Niethammer et al., 2009). Niethammer and colleagues introduced HyPer mRNA into zebrafish embryos inducing global transient cytoplasmic expression (Figure 2A). Transection of the caudal fin of 3 dpf zebrafish larvae resulted in a HyPer signal gradient extending approximately 100 μm to 200 μm from the wound margin, which was established within 10 min after wounding and dissipated 1 to 2 h later. Surprisingly, the establishment of the HyPer gradients preceded the arrival of leukocytes (Figures 2B to D). This finding led to a paradigm shift in sterile inflammation, since the prevailing view was that leukocytes were the major source of ROS production during inflammatory responses following blunt tissue injury. Instead, genetic and pharmacological experiments revealed that H2O2 was created by dual oxidase (Duox) in epithelial cells. Mechanistic insights into the dissipation of wound-induced hydrogen peroxide were later suggested by a study of Pase et al. (2012). In this study the authors observed that leukocyte arrival at sites of wounding actually caused a decline in H2O2 concentrations within wounded epithelium. Spatiotemporal dynamics of wound-induced H2O2 burst were simultaneously measured in fin tissue and within leukocytes. To this end, HyPer mRNA was injected into embryos of a new transgenic line expressing HyPer under the control of the leukocyte-specific promoter of the lysozyme C gene, thus allowing the simultaneous monitoring of neutrophil and tissue H2O2. This approach revealed that individual neutrophils arriving in wounded tails can act as sumps that lower can H2O2 concentrations locally.

Figure 2:
Figure 2:

Imaging wound margin H2O2 production in zebrafish larvae.

(A) Experimental procedure. (B) HyPer imaging in an injured zebrafish larva. [H2O2] is inferred from the YFP500/YFP420 excitation ratio of HyPer. Greyscale scaling is adjusted to improve contrast. (C) Temporal [H2O2] profile in a 10 μm to 30 μm broad region of interest along the wound margin. Arrival of first leukocyte at the wound site (solid red line)±SD (dashed red line) is shown. (D) [H2O2] line profile normalized to the wound margin. Scale bars: 100 μm in (B). Figure modified and reproduced with permission from Niethammer et al. (2009).

Citation: Biological Chemistry 396, 5; 10.1515/hsz-2014-0294

Yoo et al. reported a possible mechanism by which leukocytes sense and respond to wound-induced hydrogen peroxide gradients (Yoo et al., 2011). They identified the SRC family kinase (SFK) Lyn as a redox sensor in neutrophils responding to the guiding cue H2O2 emanating from wounds. Using the same experimental setup as Niethammer et al. and the imaging hydrogen peroxide gradients at the wound margin while using SFK inhibitors, they substantiated the role of Lyn as a neutrophilic redox sensor. SFK inhibition did not affect epithelial hydrogen peroxide gradients but significantly impaired early neutrophil accumulation.

In addition to its role as a chemoattractant for leukocytes, wound-produced hydrogen peroxide has recently been shown to prime the heart for regeneration. Spatiotemporal dynamics of H2O2 in the intact adult heart ex vivo during regeneration was visualized in a transgenic line expressing HyPer specifically in cardiac tissue (myl7:HyPer, Han et al., 2014). Hydrogen peroxide levels in the epicardium and adjacent myocardium at the resection site in injured adult zebrafish hearts were clearly elevated at 3 days post injury and during the entire course of active myocardial regeneration. After nearly full regeneration at 30 days post injury, H2O2 concentrations returned to basal levels. Ventricular resection-induced H2O2 gradients spanned 20 μm in depth from the epicardium to the myocardium, reaching a peak concentration of 30 μm. Elevated H2O2 concentrations were confirmed by imaging redox levels with the small-molecule redox potential sensor CC-1.

In 2013, a new GERI for intracellular hydrogen peroxide, HyPer-3, with improved performance was presented (Bilan et al., 2013). HyPer-3 has an expanded dynamic range compared to HyPer. Performance of HyPer and HyPer-3 was compared by in vivo imaging of wounded zebrafish tailfins. To this end, a new transgenic line expressing HyPer-3 under the control of a β-actin promoter was generated. The improved performance of HyPer-3 was demonstrated by a 1.5- to 2-fold expansion of the dynamic range compared to HyPer.

It is important to note that HyPer and HyPer-3 share the same permutated forms of YFP and, therefore, share the same pH-sensitivity. Niethammer et al. originally suggested that the changes in HyPer ratio upon tail wounding were not caused by pH variations using a pH sensitive dye. Their report initiated several follow-up studies boosting redox research in whole organisms. In the meantime, with the establishment of SypHer, it is recommended that for reliable results, application of the HyPer sensor for H2O2 measurements should include rigorous side-by-side pH recordings with SypHer to prevent misinterpretation and to identify potential simultaneous signal contributions of pH-related effects and true redox responses.

To date, roGFP2 has rarely been used in zebrafish. O’Donnell et al. applied roGFP2 targeted to the mitochondrial matrix to measure the role of mitochondrial ROS production upon axonal injury. Their observations elegantly demonstrated not only changes in the oxidation state of axonal mitochondria upon injury, but also that effects on mitochondrial oxidation state were functionally relevant to axon degeneration and protection (O’Donnell et al., 2013). One study measured epithelial ROS production using a newly generated transgenic line expressing the enzyme-coupled roGFP2 sensor Grx1-roGFP2 under the control of a β-actin promoter (Seiler et al., 2012). Here, Seiler et al. studied signals initiating epithelial cell invasion in the intestine of zebrafish to model cellular events during cancer metastasis. With this approach, an inducible signaling pathway sensitive to ROS signaling was revealed as a driving force in this process.

Potential, limitations, and outlook

Investigation of redox signaling and its analogy to calcium signaling

It is becoming increasingly clear that redox signaling – just as calcium or kinase mediated signaling – plays a key role in regulating cellular processes. The arrival of GERIs and the parallel advancement of in vivo microscopy techniques now allow the field of redox biology to enter the in vivo realm (Herrmann and Dick, 2012). A number of challenges remain to be tackled. However, similar challenges, such as small signal sizes and pH sensitivity, were also problems in the early days of calcium imaging. Over the last decade, concerted biochemical efforts have led to markedly improved versions of GCaMPs and other genetically encoded calcium indicators (GECIs). The calcium imaging community – in part driven by fundamental neuroscience questions – has developed efficient tools that now allow, e.g., following physiological ion fluxes resulting from neuronal activity, as well as recording pathological calcium accumulations in various nervous system disorders (Tian et al., 2009; Yamada and Mikoshiba, 2012; Thestrup et al., 2014). ‘RCaMPs’, for example, are a class of recently developed GECIs that combine several advantages: they are red-shifted, show increased signal amplitudes, and are less pH sensitive (Akerboom et al., 2013). Now the entire color palette of calcium indicators is available, thus allowing simultaneous measurements of calcium levels within different cellular compartments (Zhao et al., 2011; Grienberger and Konnerth, 2012).

Improved redox sensors and remaining ambiguities

Paralleling the efforts in the area of genetically-encoded calcium indicators, similar progress can now be expected in the emerging field of redox biology. While suitable in vivo tools to measure redox signals in situ have been missing for some time, this has now changed with the development of redox-sensitive GFP (Dooley et al., 2004; Hanson et al., 2004), the generation of enzyme-coupled roGFP variants (Gutscher et al., 2008, 2009), and the description of HyPer (Belousov et al., 2006; Bilan et al., 2013). These novel GERIs allow the investigation of defined redox pairs, overcoming many of the problems associated with redox-sensitive dyes that were often non-specific and less suitable for in vivo recordings (Meyer and Dick, 2010). Still, interpreting redox signals remains a challenge. Grx1-roGFP2, for example, senses the glutathione redox potential. However, this redox pair does not reflect the entire oxidative state of a given compartment because additional redox pairs exist, such as exposed cysteine residues within proteins. Under specific conditions, some redox systems are selectively modified without affecting others (Albrecht et al., 2011; Chouchani et al., 2013). Indeed, redox compartmentalization is increasingly recognized as an important factor in redox biology (Kaludercic et al., 2014). Thus, a signal measured with a specific GERI should not simply be interpreted as a global and uniform ‘redox signal’. Additionally, the equilibrium of the different redox pairs does not only depend on reactive species generated, but also on the concentration of the reducing enzymes and necessary cofactors like NADPH. This adds another layer of complexity to the investigation and interpretation of redox signals. Therefore, additional GERIs that will allow covering other redox pairs and reducing systems are clearly needed and will have to be employed in parallel.

Emission ratiometry for redox sensors

Until now, GERIs tend to be absorption ratiometric sensors. This might cause problems because switching excitation wavelengths can be time-consuming (2PM) and requires special precautions to avoid artifacts. Especially for in vivo imaging where absolute stability is not a given, emission ratiometric sensors have great advantages, as illustrated by the widespread use of emission-ratiometric fluorescence resonance energy transfer (FRET) sensors to detect calcium dynamics in vivo (Grienberger and Konnerth, 2012). An emission ratiometric sensor for redox imaging would require a different chemistry compared to roGFP, and first attempts have been performed in this direction. So far, however, these emission ratiometric sensors lack signal amplitude and are only suitable for oxidized compartments (Kolossov et al., 2008; Enyedi et al., 2013).

Improving the dynamic range, spectral palette, and coverage of redox sensors

It would also be desirable to develop redox sensors that have larger signal amplitudes and are tuned to variable ranges of redox potentials. On the one hand, this would facilitate in vivo imaging where signal to noise levels can be low. On the other hand, more sensitive probes are crucial to monitor physiological redox signals, which might be much smaller than pathological signals. Grx1-roGFP2 has a dynamic range of ∼2.5 to 6, depending on the system utilized (Gutscher et al., 2008; Albrecht et al., 2011), and attempts to generate ultra-sensitive Grx1-roGFP2 variants are underway. Recently, an improved version of HyPer, called HyPer-3 was published with increased kinetics and signal sizes (Bilan et al., 2013).

It is also necessary to expand the spectral palette of redox sensors to enable multiparametric imaging of different redox pairs to further facilitate the combination with other fluorescent indicators (Tantama et al., 2012). A first step in this direction was just published with a red-shifted version of HyPer (Ermakova et al., 2014).

Another aspect to improve GERIs involves the signals that can be monitored. H2O2 and the glutathione pool (assessed by HyPer and roGFP2 variants) are important parts of redox ‘circuits’. However, a number of additional important redox pairs and reactive species exist that cannot be sensed so far. Other relevant oxidative species that can serve as prime targets for potential new GERIs include O2-, OH- and ONOO-. These radicals are even more reactive than H2O2 and are probably responsible for most of the detrimental damage caused by ROS in vivo. Therefore, it is a fundamental challenge for biochemistry to identify novel design principles for new classes of GERIs that are able to sense these important targets. Such sensors would allow a true multi-parametric and quantitative assessment of a cell’s ‘redox state’ in conjunction with other important signaling molecules like calcium.

pH sensitivity

One important limitation of cpYFP is that the circular permutation results in distortions of the ß-barrel facilitating proton access to the chromophore. Consequently, cpYFP is very sensitive to pH and careful controls are needed when using this sensor (Schwarzländer et al., 2011; Wei-LaPierre et al., 2013). pH sensitivity is, unfortunately, a notorious problem for many sensor classes. Thus, attempts are necessary to eliminate this pH sensitivity by stepwise permutation of existing sensors.

Conclusion

As with GECIs, the 2nd generation of GERIs must address the aforementioned issues (pH-sensitivity, excitation ratiometry, signal size, color palette) to generate new sensors (GERIs 2.0) that can help us to understand the dynamics and complexity of redox reactions in living organisms.

Acknowledgments

M.O.B. acknowledges the support provided by a physician-scientist fellowship of the Medical Faculty, University of Heidelberg. C.W. was supported by a Helmholtz joint project initiative between KIT and DKFZ. C.G. was supported by a Marie Curie International Reintegration Grant within the 7th European Community Framework Program (PIRG07-GA-2010-267552). Further thanks go to Heidelberg-Karlsruhe Research Bridge (HeiKa) for the financial support given to C.G. within the synthetic biology platform. C.G., T.M., and M.K. are supported by the DFG Priority Program ‘Dynamics of thiol-based redox switches in cellular physiology’ (SPP1710).

References

  • Akerboom, J., Carreras Calderón, N., Tian, L., Wabnig, S., Prigge, M., Tolö, J., Gordus, A., Orger, M.B., Severi, K.E., Macklin, J.J., et al. (2013). Genetically encoded calcium indicators for multi-color neural activity imaging and combination with optogenetics. Front. Mol. Neurosci. 6, 1–29.

  • Albrecht, S.C., Barata, A.G., Großhans, J., Teleman, A.A., and Dick, T.P. (2011). In vivo mapping of hydrogen peroxide and oxidized glutathione reveals chemical and regional specificity of redox homeostasis. Cell Metab. 14, 819–829.

  • Barata, A.G., and Dick, T.P. (2013). In vivo imaging of H2O2 production in Drosophila. Meth. Enzymol. 526, 61–82.

  • Belousov, V.V., Fradkov, A.F., Lukyanov, K.A., Staroverov, D.B., Shakhbazov, K.S., Terskikh, A.V., and Lukyanov, S. (2006). Genetically encoded fluorescent indicator for intracellular hydrogen peroxide. Nat. Methods 3, 281–286.

  • Bilan, D.S., Pase, L., Joosen, L., Gorokhovatsky, A.Y., Ermakova, Y.G., Gadella, T.W.J., Grabher, C., Schultz, C., Lukyanov, S., and Belousov, V.V. (2013). HyPer-3: a genetically encoded H2O2 probe with improved performance for ratiometric and fluorescence lifetime imaging. ACS Chem. Biol. 8, 535–542.

  • Brecht, M., Fee, M.S., Garaschuk, O., Helmchen, F., Margrie, T.W., Svoboda, K., and Osten, P. (2004). Novel approaches to monitor and manipulate single neurons in vivo. J. Neurosci. 24, 9223–9227.

  • Breckwoldt, M.O., Pfister, F.M.J., Bradley, P.M., Marinković, P., Williams, P.R., Brill, M.S., Plomer, B., Schmalz, A., Clair, D.K.S., Naumann, R., et al. (2014). Multiparametric optical analysis of mitochondrial redox signals during neuronal physiology and pathology in vivo. Nat. Med. 20, 555–560.

  • Carlson, G.C., and Coulter, D.A. (2008). In vitro functional imaging in brain slices using fast voltage-sensitive dye imaging combined with whole-cell patch recording. Nat. Protoc. 3, 249–255.

  • Chazotte, B. (2011). Labeling mitochondria with TMRM or TMRE. Cold Spring Harb. Protoc. 2011, 895–897.

  • Chouchani, E.T., Methner, C., Nadtochiy, S.M., Logan, A., Pell, V.R., Ding, S., James, A.M., Cochemé, H.M., Reinhold, J., Lilley, K.S., et al. (2013). Cardioprotection by S-nitrosation of a cysteine switch on mitochondrial complex I. Nat. Med. 19, 753–759.

  • D’Autréaux, B., and Toledano, M.B. (2007). ROS as signalling molecules: mechanisms that generate specificity in ROS homeostasis. Nat. Rev. Mol. Cell Biol 8, 813–824.

  • Dittgen, T., Nimmerjahn, A., Komai, S., Licznerski, P., Waters, J., Margrie, T.W., Helmchen, F., Denk, W., Brecht, M., and Osten, P. (2004). Lentivirus-based genetic manipulations of cortical neurons and their optical and electrophysiological monitoring in vivo. Proc. Natl. Acad. Sci. USA 101, 18206–18211.

  • Dooley, C.T., Dore, T.M., Hanson, G.T., Jackson, W.C., Remington, S.J., and Tsien, R.Y. (2004). Imaging dynamic redox changes in mammalian cells with green fluorescent protein indicators. J. Biol. Chem. 279, 22284–22293.

  • Drew, P.J., Shih, A.Y., Driscoll, J.D., Knutsen, P.M., Blinder, P., Davalos, D., Akassoglou, K., Tsai, P.S., and Kleinfeld, D. (2010). Chronic optical access through a polished and reinforced thinned skull. Nat. Methods 7, 981–984.

  • Enyedi, B., Zana, M., Donkó, Á., and Geiszt, M. (2013). Spatial and temporal analysis of NADPH oxidase-generated hydrogen peroxide signals by novel fluorescent reporter proteins. Antioxidants Redox Signaling 19, 523–534.

  • Ermakova, Y.G., Bilan, D.S., Matlashov, M.E., Mishina, N.M., Markvicheva, K.N., Subach, O.M., Subach, F.V., Bogeski, I., Hoth, M., Enikolopov, G., et al. (2014). Red fluorescent genetically encoded indicator for intracellular hydrogen peroxide. Nat. Commun. 5, 5222.

  • Ezeriņa, D., Morgan, B., and Dick, T.P. (2014). Imaging dynamic redox processes with genetically encoded probes. J. Mol. Cell. Cardiol. 73, 43–49.

  • Goldberg, J.A., Guzman, J.N., Estep, C.M., Ilijic, E., Kondapalli, J., Sanchez-Padilla, J., and Surmeier, D.J. (2012). Calcium entry induces mitochondrial oxidant stress in vagal neurons at risk in Parkinson’s disease. Nat. Neurosci. 15, 1414–1421.

  • Grienberger, C., and Konnerth, A. (2012). Imaging calcium in neurons. Neuron 73, 862–885.

  • Gutscher, M., Pauleau, A.-L., Marty, L., Brach, T., Wabnitz, G.H., Samstag, Y., Meyer, A.J., and Dick, T.P. (2008). Real-time imaging of the intracellular glutathione redox potential. Nat. Meth. 5, 553–559.

  • Gutscher, M., Sobotta, M.C., Wabnitz, G.H., Ballikaya, S., Meyer, A.J., Samstag, Y., and Dick, T.P. (2009). Proximity-based protein thiol oxidation by H2O2-scavenging peroxidases. J. Biol. Chem. 284, 31532–31540.

  • Guzman, J.N., Sanchez-Padilla, J., Wokosin, D., Kondapalli, J., Ilijic, E., Schumacker, P.T., and Surmeier, D.J. (2010). Oxidant stress evoked by pacemaking in dopaminergic neurons is attenuated by DJ-1. Nature 468, 696–700.

  • Han, P., Zhou, X.-H., Chang, N., Xiao, C.-L., Yan, S., Ren, H., Yang, X.-Z., Zhang, M.-L., Wu, Q., Tang, B., et al. (2014). Hydrogen peroxide primes heart regeneration with a derepression mechanism. Cell. Res. 24, 1091–1107.

  • Hanson, G.T., Aggeler, R., Oglesbee, D., Cannon, M., Capaldi, R.A., Tsien, R.Y., and Remington, S.J. (2004). Investigating mitochondrial redox potential with redox-sensitive green fluorescent protein indicators. J. Biol. Chem. 279, 13044–13053.

  • Helmchen, F., and Denk, W. (2005). Deep tissue two-photon microscopy. Nat. Methods 2, 932–940.

  • Herrmann, J.M., and Dick, T.P. (2012). Redox biology on the rise. J. Biol. Chem. 393, 999–1004.

  • Kaludercic, N., Deshwal, S., and Di Lisa, F. (2014). Reactive oxygen species and redox compartmentalization. Front. Physiol. 5, 285.

  • Kerr, J.N.D., and Denk, W. (2008). Imaging in vivo: watching the brain in action. Nat. Rev. Neurosci. 9, 195–205.

  • Kerschensteiner, M., Schwab, M.E., Lichtman, J.W., and Misgeld, T. (2005). In vivo imaging of axonal degeneration and regeneration in the injured spinal cord. Nat. Med. 11, 572–577.

  • Kerschensteiner, M., Reuter, M.S., Lichtman, J.W., and Misgeld, T. (2008). Ex vivo imaging of motor axon dynamics in murine triangularis sterni explants. Nat. Protoc. 3, 1645–1653.

  • Klugmann, M., Symes, C.W., Leichtlein, C.B., Klaussner, B.K., Dunning, J., Fong, D., Young, D., and During, M.J. (2005). AAV-mediated hippocampal expression of short and long Homer 1 proteins differentially affect cognition and seizure activity in adult rats. Mol. Cell. Neurosci. 28, 347–360.

  • Kolossov, V.L., Spring, B.Q., Sokolowski, A., Conour, J.E., Clegg, R.M., Kenis, P.J.A., and Gaskins, H.R. (2008). Engineering redox-sensitive linkers for genetically encoded FRET-based biosensors. Exp. Biol. Med. 233, 238–248.

  • Kumar, C., Igbaria, A., D’Autréaux, B., Planson, A.-G., Junot, C., Godat, E., Bachhawat, A.K., Delaunay-Moisan, A., and Toledano, M.B. (2011). Glutathione revisited: a vital function in iron metabolism and ancillary role in thiol-redox control. EMBO J. 30, 2044–2056.

  • Lichtman, J.W., and Conchello, J.-A. (2005). Fluorescence microscopy. Nat. Methods 2, 910–919.

  • Lichtman, J.W., and Sanes, J.R. (2003). Watching the neuromuscular junction. J. Neurocytol. 32, 767–775.

  • Lin, M.T., and Beal, M.F. (2006). Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. Nature 443, 787–795.

  • Lukyanov, K.A., and Belousov, V.V. (2013). Genetically encoded fluorescent redox sensors. Biochim. Biophys. Acta. Gen. Subj. 1840, 745–756.

  • Marinković, P., Reuter, M.S., Brill, M.S., Godinho, L., Kerschensteiner, M., and Misgeld, T. (2012). Axonal transport deficits and degeneration can evolve independently in mouse models of amyotrophic lateral sclerosis. Proc. Natl. Acad. Sci. USA 109, 4296–4301.

  • Meyer, A.J., and Dick, T.P. (2010). Fluorescent protein-based redox probes. Antioxidants Redox Signaling 13, 621–650.

  • Misgeld, T., and Kerschensteiner, M. (2006). In vivo imaging of the diseased nervous system. Nat. Rev. Neurosci. 7, 449–463.

  • Murphy, M.P., Holmgren, A., Larsson, N.-G., Halliwell, B., Chang, C.J., Kalyanaraman, B., Rhee, S.G., Thornalley, P.J., Partridge, L., Gems, D., et al. (2011). Unraveling the biological roles of reactive oxygen species. Cell Metabolism 13, 361–366.

  • Nagai, T., Sawano, A., Park, E.S., and Miyawaki, A. (2001). Circularly permuted green fluorescent proteins engineered to sense Ca2+. Proc. Natl. Acad. Sci. USA 98, 3197–3202.

  • Nagai, T., Ibata, K., Park, E.S., Kubota, M., Mikoshiba, K., and Miyawaki, A. (2002). A variant of yellow fluorescent protein with fast and efficient maturation for cell-biological applications. Nat. Biotechnol. 20, 87–90.

  • Niethammer, P., Grabher, C., Look, A.T., and Mitchison, T.J. (2009). A tissue-scale gradient of hydrogen peroxide mediates rapid wound detection in zebrafish. Nature 459, 996–999.

  • O’Donnell, K.C., Vargas, M.E., and Sagasti, A. (2013). WldS and PGC-1 regulate mitochondrial transport and oxidation state after axonal injury. J. Neurosci. 33, 14778–14790.

  • Pase, L., Layton, J.E., Wittmann, C., Ellett, F., Nowell, C.J., Reyes-Aldasoro, C.C., Varma, S., Rogers, K.L., Hall, C.J., Keightley, M.C., et al. (2012). Neutrophil-delivered myeloperoxidase dampens the hydrogen peroxide burst after tissue wounding in zebrafish. Curr. Biol. 22, 1818–1824.

  • Rawls, J.F., Mellgren, E.M., and Johnson, S.L. (2001). How the zebrafish gets its stripes. Dev. Biol. 240, 301–314.

  • Rieger, S., Wang, F., and Sagasti, A. (2011). Time-lapse imaging of neural development: zebrafish lead the way into the fourth dimension. Genesis 49, 534–545.

  • Sanchez-Padilla, J., Guzman, J.N., Ilijic, E., Kondapalli, J., Galtieri, D.J., Ben Yang, Schieber, S., Oertel, W., Wokosin, D., Schumacker, P.T., et al. (2014). Mitochondrial oxidant stress in locus coeruleus is regulated by activity and nitric oxide synthase. Nat. Neurosci. 17, 832–840.

  • Schinzel, A.C., Takeuchi, O., Huang, Z., Fisher, J.K., Zhou, Z., Rubens, J., Hetz, C., Danial, N.N., Moskowitz, M.A., and Korsmeyer, S.J. (2005). Cyclophilin D is a component of mitochondrial permeability transition and mediates neuronal cell death after focal cerebral ischemia. Proc. Natl. Acad. Sci. USA 102, 12005–12010.

  • Schwarzländer, M., Logan, D.C., Fricker, M.D., and Sweetlove, L.J. (2011). The circularly permuted yellow fluorescent protein cpYFP that has been used as a superoxide probe is highly responsive to pH but not superoxide in mitochondria: implications for the existence of superoxide “flashes.” Biochem. J. 437, 381–387.

  • Schwarzländer, M., Murphy, M.P., Duchen, M.R., Logan, D.C., Fricker, M.D., Halestrap, A.P., Müller, F.L., Rizzuto, R., Dick, T.P., Meyer, A.J., et al. (2012). Mitochondrial “flashes”: a radical concept repHined. Trends. Cell. Biol. 22, 503–508.

  • Schwarzländer, M., Wagner, S., Ermakova, Y.G., Belousov, V.V., Radi, R., Beckman, J.S., Buettner, G.R., Demaurex, N., Duchen, M.R., Forman, H.J., et al. (2014). The “mitoflash” probe cpYFP does not respond to superoxide. Nature 514, E12–E14.

  • Seiler, C., Davuluri, G., Abrams, J., Byfield, F.J., Janmey, P.A., and Pack, M. (2012). Smooth muscle tension induces invasive remodeling of the zebrafish intestine. PLoS Biol. 10, e1001386.

  • Sena, L.A., Li, S., Jairaman, A., Prakriya, M., Ezponda, T., Hildeman, D.A., Wang, C.-R., Schumacker, P.T., Licht, J.D., Perlman, H., et al. (2013). Mitochondria are required for antigen-specific T cell activation through reactive oxygen species signaling. Immunity 38, 225–236.

  • Shen, E.-Z., Song, C.-Q., Lin, Y., Zhang, W.-H., Su, P.-F., Liu, W.-Y., Zhang, P., Xu, J., Lin, N., Zhan, C., et al. (2014). Mitoflash frequency in early adulthood predicts lifespan in Caenorhabditis elegans. Nature 508, 128–132.

  • Tantama, M., Hung, Y.P., and Yellen, G. (2012). Optogenetic reporters: fluorescent protein-based genetically-encoded indicators of signaling and metabolism in the brain. Progr. Brain. Res. 196, 235–263.

  • Thestrup, T., Litzlbauer, J., Bartholomäus, I., Mues, M., Russo, L., Dana, H., Kovalchuk, Y., Liang, Y., Kalamakis, G., Laukat, Y., et al. (2014). Optimized ratiometric calcium sensors for functional in vivo imaging of neurons and T lymphocytes. Nat. Methods 11, 175–182.

  • Tian, L., Hires, S.A., Mao, T., Huber, D., Chiappe, M.E., Chalasani, S.H., Petreanu, L., Akerboom, J., McKinney, S.A., Schreiter, E.R., et al. (2009). Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators. Nat. Methods 6, 875–881.

  • Trachtenberg, J.T., Chen, B.E., Knott, G.W., Feng, G., Sanes, J.R., Welker, E., and Svoboda, K. (2002). Long-term in vivo imaging of experience-dependent synaptic plasticity in adult cortex. Nature 420, 788–794.

  • Wang, W., Fang, H., Groom, L., Cheng, A., Zhang, W., Liu, J., Wang, X., Li, K., Han, P., and Zheng, M. (2008). Superoxide flashes in single mitochondria. Cell 134, 279–290.

  • Wang, H., Karadge, U., Humphries, W.H., IV, and Fisher, A.L. (2014). Analyzing cell physiology in C. elegans with fluorescent ratiometric reporters. Methods 68, 508–517.

  • Weber, T., and Köster, R. (2013). Genetic tools for multicolor imaging in zebrafish larvae. Methods 62, 279–291.

  • Wei-LaPierre, L., Gong, G., Gerstner, B.J., Ducreux, S., Yule, D.I., Pouvreau, S., Wang, X., Sheu, S.-S., Cheng, H., and Dirksen, R.T. (2013). Respective contribution of mitochondrial superoxide and pH to Mt-cpYFP flash activity. J. Biol. Chem. 288, 10567–10577.

  • White, R.M., Sessa, A., Burke, C., Bowman, T., LeBlanc, J., Ceol, C., Bourque, C., Dovey, M., Goessling, W., Burns, C.E., et al. (2008). Transparent adult zebrafish as a tool for in vivo transplantation analysis. Cell Stem Cell. 2, 183–189.

  • Xie, H., Hou, S., Jiang, J., Sekutowicz, M., Kelly, J., and Bacskai, B.J. (2013). Rapid cell death is preceded by amyloid plaque-mediated oxidative stress. Proc. Natl. Acad. Sci. USA 110, 7904–7909.

  • Yamada, Y., and Mikoshiba, K. (2012). Quantitative comparison of novel GCaMP-type genetically encoded calcium indicators in mammalian neurons. Front. Cell. Neurosci. 6, 41.

  • Yoo, S.K., Starnes, T.W., Deng, Q., and Huttenlocher, A. (2011). Lyn is a redox sensor that mediates leukocyte wound attraction in vivo. Nature 480, 109–112.

  • Zhao, Y., Araki, S., Wu, J., Teramoto, T., Chang, Y.F., Nakano, M., Abdelfattah, A.S., Fujiwara, M., Ishihara, T., Nagai, T., et al. (2011). An expanded palette of genetically encoded Ca2+ indicators. Science 333, 1888–1891.

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  • Akerboom, J., Carreras Calderón, N., Tian, L., Wabnig, S., Prigge, M., Tolö, J., Gordus, A., Orger, M.B., Severi, K.E., Macklin, J.J., et al. (2013). Genetically encoded calcium indicators for multi-color neural activity imaging and combination with optogenetics. Front. Mol. Neurosci. 6, 1–29.

  • Albrecht, S.C., Barata, A.G., Großhans, J., Teleman, A.A., and Dick, T.P. (2011). In vivo mapping of hydrogen peroxide and oxidized glutathione reveals chemical and regional specificity of redox homeostasis. Cell Metab. 14, 819–829.

  • Barata, A.G., and Dick, T.P. (2013). In vivo imaging of H2O2 production in Drosophila. Meth. Enzymol. 526, 61–82.

  • Belousov, V.V., Fradkov, A.F., Lukyanov, K.A., Staroverov, D.B., Shakhbazov, K.S., Terskikh, A.V., and Lukyanov, S. (2006). Genetically encoded fluorescent indicator for intracellular hydrogen peroxide. Nat. Methods 3, 281–286.

  • Bilan, D.S., Pase, L., Joosen, L., Gorokhovatsky, A.Y., Ermakova, Y.G., Gadella, T.W.J., Grabher, C., Schultz, C., Lukyanov, S., and Belousov, V.V. (2013). HyPer-3: a genetically encoded H2O2 probe with improved performance for ratiometric and fluorescence lifetime imaging. ACS Chem. Biol. 8, 535–542.

  • Brecht, M., Fee, M.S., Garaschuk, O., Helmchen, F., Margrie, T.W., Svoboda, K., and Osten, P. (2004). Novel approaches to monitor and manipulate single neurons in vivo. J. Neurosci. 24, 9223–9227.

  • Breckwoldt, M.O., Pfister, F.M.J., Bradley, P.M., Marinković, P., Williams, P.R., Brill, M.S., Plomer, B., Schmalz, A., Clair, D.K.S., Naumann, R., et al. (2014). Multiparametric optical analysis of mitochondrial redox signals during neuronal physiology and pathology in vivo. Nat. Med. 20, 555–560.

  • Carlson, G.C., and Coulter, D.A. (2008). In vitro functional imaging in brain slices using fast voltage-sensitive dye imaging combined with whole-cell patch recording. Nat. Protoc. 3, 249–255.

  • Chazotte, B. (2011). Labeling mitochondria with TMRM or TMRE. Cold Spring Harb. Protoc. 2011, 895–897.

  • Chouchani, E.T., Methner, C., Nadtochiy, S.M., Logan, A., Pell, V.R., Ding, S., James, A.M., Cochemé, H.M., Reinhold, J., Lilley, K.S., et al. (2013). Cardioprotection by S-nitrosation of a cysteine switch on mitochondrial complex I. Nat. Med. 19, 753–759.

  • D’Autréaux, B., and Toledano, M.B. (2007). ROS as signalling molecules: mechanisms that generate specificity in ROS homeostasis. Nat. Rev. Mol. Cell Biol 8, 813–824.

  • Dittgen, T., Nimmerjahn, A., Komai, S., Licznerski, P., Waters, J., Margrie, T.W., Helmchen, F., Denk, W., Brecht, M., and Osten, P. (2004). Lentivirus-based genetic manipulations of cortical neurons and their optical and electrophysiological monitoring in vivo. Proc. Natl. Acad. Sci. USA 101, 18206–18211.

  • Dooley, C.T., Dore, T.M., Hanson, G.T., Jackson, W.C., Remington, S.J., and Tsien, R.Y. (2004). Imaging dynamic redox changes in mammalian cells with green fluorescent protein indicators. J. Biol. Chem. 279, 22284–22293.

  • Drew, P.J., Shih, A.Y., Driscoll, J.D., Knutsen, P.M., Blinder, P., Davalos, D., Akassoglou, K., Tsai, P.S., and Kleinfeld, D. (2010). Chronic optical access through a polished and reinforced thinned skull. Nat. Methods 7, 981–984.

  • Enyedi, B., Zana, M., Donkó, Á., and Geiszt, M. (2013). Spatial and temporal analysis of NADPH oxidase-generated hydrogen peroxide signals by novel fluorescent reporter proteins. Antioxidants Redox Signaling 19, 523–534.

  • Ermakova, Y.G., Bilan, D.S., Matlashov, M.E., Mishina, N.M., Markvicheva, K.N., Subach, O.M., Subach, F.V., Bogeski, I., Hoth, M., Enikolopov, G., et al. (2014). Red fluorescent genetically encoded indicator for intracellular hydrogen peroxide. Nat. Commun. 5, 5222.

  • Ezeriņa, D., Morgan, B., and Dick, T.P. (2014). Imaging dynamic redox processes with genetically encoded probes. J. Mol. Cell. Cardiol. 73, 43–49.

  • Goldberg, J.A., Guzman, J.N., Estep, C.M., Ilijic, E., Kondapalli, J., Sanchez-Padilla, J., and Surmeier, D.J. (2012). Calcium entry induces mitochondrial oxidant stress in vagal neurons at risk in Parkinson’s disease. Nat. Neurosci. 15, 1414–1421.

  • Grienberger, C., and Konnerth, A. (2012). Imaging calcium in neurons. Neuron 73, 862–885.

  • Gutscher, M., Pauleau, A.-L., Marty, L., Brach, T., Wabnitz, G.H., Samstag, Y., Meyer, A.J., and Dick, T.P. (2008). Real-time imaging of the intracellular glutathione redox potential. Nat. Meth. 5, 553–559.

  • Gutscher, M., Sobotta, M.C., Wabnitz, G.H., Ballikaya, S., Meyer, A.J., Samstag, Y., and Dick, T.P. (2009). Proximity-based protein thiol oxidation by H2O2-scavenging peroxidases. J. Biol. Chem. 284, 31532–31540.

  • Guzman, J.N., Sanchez-Padilla, J., Wokosin, D., Kondapalli, J., Ilijic, E., Schumacker, P.T., and Surmeier, D.J. (2010). Oxidant stress evoked by pacemaking in dopaminergic neurons is attenuated by DJ-1. Nature 468, 696–700.

  • Han, P., Zhou, X.-H., Chang, N., Xiao, C.-L., Yan, S., Ren, H., Yang, X.-Z., Zhang, M.-L., Wu, Q., Tang, B., et al. (2014). Hydrogen peroxide primes heart regeneration with a derepression mechanism. Cell. Res. 24, 1091–1107.

  • Hanson, G.T., Aggeler, R., Oglesbee, D., Cannon, M., Capaldi, R.A., Tsien, R.Y., and Remington, S.J. (2004). Investigating mitochondrial redox potential with redox-sensitive green fluorescent protein indicators. J. Biol. Chem. 279, 13044–13053.

  • Helmchen, F., and Denk, W. (2005). Deep tissue two-photon microscopy. Nat. Methods 2, 932–940.

  • Herrmann, J.M., and Dick, T.P. (2012). Redox biology on the rise. J. Biol. Chem. 393, 999–1004.

  • Kaludercic, N., Deshwal, S., and Di Lisa, F. (2014). Reactive oxygen species and redox compartmentalization. Front. Physiol. 5, 285.

  • Kerr, J.N.D., and Denk, W. (2008). Imaging in vivo: watching the brain in action. Nat. Rev. Neurosci. 9, 195–205.

  • Kerschensteiner, M., Schwab, M.E., Lichtman, J.W., and Misgeld, T. (2005). In vivo imaging of axonal degeneration and regeneration in the injured spinal cord. Nat. Med. 11, 572–577.

  • Kerschensteiner, M., Reuter, M.S., Lichtman, J.W., and Misgeld, T. (2008). Ex vivo imaging of motor axon dynamics in murine triangularis sterni explants. Nat. Protoc. 3, 1645–1653.

  • Klugmann, M., Symes, C.W., Leichtlein, C.B., Klaussner, B.K., Dunning, J., Fong, D., Young, D., and During, M.J. (2005). AAV-mediated hippocampal expression of short and long Homer 1 proteins differentially affect cognition and seizure activity in adult rats. Mol. Cell. Neurosci. 28, 347–360.

  • Kolossov, V.L., Spring, B.Q., Sokolowski, A., Conour, J.E., Clegg, R.M., Kenis, P.J.A., and Gaskins, H.R. (2008). Engineering redox-sensitive linkers for genetically encoded FRET-based biosensors. Exp. Biol. Med. 233, 238–248.

  • Kumar, C., Igbaria, A., D’Autréaux, B., Planson, A.-G., Junot, C., Godat, E., Bachhawat, A.K., Delaunay-Moisan, A., and Toledano, M.B. (2011). Glutathione revisited: a vital function in iron metabolism and ancillary role in thiol-redox control. EMBO J. 30, 2044–2056.

  • Lichtman, J.W., and Conchello, J.-A. (2005). Fluorescence microscopy. Nat. Methods 2, 910–919.

  • Lichtman, J.W., and Sanes, J.R. (2003). Watching the neuromuscular junction. J. Neurocytol. 32, 767–775.

  • Lin, M.T., and Beal, M.F. (2006). Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. Nature 443, 787–795.

  • Lukyanov, K.A., and Belousov, V.V. (2013). Genetically encoded fluorescent redox sensors. Biochim. Biophys. Acta. Gen. Subj. 1840, 745–756.

  • Marinković, P., Reuter, M.S., Brill, M.S., Godinho, L., Kerschensteiner, M., and Misgeld, T. (2012). Axonal transport deficits and degeneration can evolve independently in mouse models of amyotrophic lateral sclerosis. Proc. Natl. Acad. Sci. USA 109, 4296–4301.

  • Meyer, A.J., and Dick, T.P. (2010). Fluorescent protein-based redox probes. Antioxidants Redox Signaling 13, 621–650.

  • Misgeld, T., and Kerschensteiner, M. (2006). In vivo imaging of the diseased nervous system. Nat. Rev. Neurosci. 7, 449–463.

  • Murphy, M.P., Holmgren, A., Larsson, N.-G., Halliwell, B., Chang, C.J., Kalyanaraman, B., Rhee, S.G., Thornalley, P.J., Partridge, L., Gems, D., et al. (2011). Unraveling the biological roles of reactive oxygen species. Cell Metabolism 13, 361–366.

  • Nagai, T., Sawano, A., Park, E.S., and Miyawaki, A. (2001). Circularly permuted green fluorescent proteins engineered to sense Ca2+. Proc. Natl. Acad. Sci. USA 98, 3197–3202.

  • Nagai, T., Ibata, K., Park, E.S., Kubota, M., Mikoshiba, K., and Miyawaki, A. (2002). A variant of yellow fluorescent protein with fast and efficient maturation for cell-biological applications. Nat. Biotechnol. 20, 87–90.

  • Niethammer, P., Grabher, C., Look, A.T., and Mitchison, T.J. (2009). A tissue-scale gradient of hydrogen peroxide mediates rapid wound detection in zebrafish. Nature 459, 996–999.

  • O’Donnell, K.C., Vargas, M.E., and Sagasti, A. (2013). WldS and PGC-1 regulate mitochondrial transport and oxidation state after axonal injury. J. Neurosci. 33, 14778–14790.

  • Pase, L., Layton, J.E., Wittmann, C., Ellett, F., Nowell, C.J., Reyes-Aldasoro, C.C., Varma, S., Rogers, K.L., Hall, C.J., Keightley, M.C., et al. (2012). Neutrophil-delivered myeloperoxidase dampens the hydrogen peroxide burst after tissue wounding in zebrafish. Curr. Biol. 22, 1818–1824.

  • Rawls, J.F., Mellgren, E.M., and Johnson, S.L. (2001). How the zebrafish gets its stripes. Dev. Biol. 240, 301–314.

  • Rieger, S., Wang, F., and Sagasti, A. (2011). Time-lapse imaging of neural development: zebrafish lead the way into the fourth dimension. Genesis 49, 534–545.

  • Sanchez-Padilla, J., Guzman, J.N., Ilijic, E., Kondapalli, J., Galtieri, D.J., Ben Yang, Schieber, S., Oertel, W., Wokosin, D., Schumacker, P.T., et al. (2014). Mitochondrial oxidant stress in locus coeruleus is regulated by activity and nitric oxide synthase. Nat. Neurosci. 17, 832–840.

  • Schinzel, A.C., Takeuchi, O., Huang, Z., Fisher, J.K., Zhou, Z., Rubens, J., Hetz, C., Danial, N.N., Moskowitz, M.A., and Korsmeyer, S.J. (2005). Cyclophilin D is a component of mitochondrial permeability transition and mediates neuronal cell death after focal cerebral ischemia. Proc. Natl. Acad. Sci. USA 102, 12005–12010.

  • Schwarzländer, M., Logan, D.C., Fricker, M.D., and Sweetlove, L.J. (2011). The circularly permuted yellow fluorescent protein cpYFP that has been used as a superoxide probe is highly responsive to pH but not superoxide in mitochondria: implications for the existence of superoxide “flashes.” Biochem. J. 437, 381–387.

  • Schwarzländer, M., Murphy, M.P., Duchen, M.R., Logan, D.C., Fricker, M.D., Halestrap, A.P., Müller, F.L., Rizzuto, R., Dick, T.P., Meyer, A.J., et al. (2012). Mitochondrial “flashes”: a radical concept repHined. Trends. Cell. Biol. 22, 503–508.

  • Schwarzländer, M., Wagner, S., Ermakova, Y.G., Belousov, V.V., Radi, R., Beckman, J.S., Buettner, G.R., Demaurex, N., Duchen, M.R., Forman, H.J., et al. (2014). The “mitoflash” probe cpYFP does not respond to superoxide. Nature 514, E12–E14.

  • Seiler, C., Davuluri, G., Abrams, J., Byfield, F.J., Janmey, P.A., and Pack, M. (2012). Smooth muscle tension induces invasive remodeling of the zebrafish intestine. PLoS Biol. 10, e1001386.

  • Sena, L.A., Li, S., Jairaman, A., Prakriya, M., Ezponda, T., Hildeman, D.A., Wang, C.-R., Schumacker, P.T., Licht, J.D., Perlman, H., et al. (2013). Mitochondria are required for antigen-specific T cell activation through reactive oxygen species signaling. Immunity 38, 225–236.

  • Shen, E.-Z., Song, C.-Q., Lin, Y., Zhang, W.-H., Su, P.-F., Liu, W.-Y., Zhang, P., Xu, J., Lin, N., Zhan, C., et al. (2014). Mitoflash frequency in early adulthood predicts lifespan in Caenorhabditis elegans. Nature 508, 128–132.

  • Tantama, M., Hung, Y.P., and Yellen, G. (2012). Optogenetic reporters: fluorescent protein-based genetically-encoded indicators of signaling and metabolism in the brain. Progr. Brain. Res. 196, 235–263.

  • Thestrup, T., Litzlbauer, J., Bartholomäus, I., Mues, M., Russo, L., Dana, H., Kovalchuk, Y., Liang, Y., Kalamakis, G., Laukat, Y., et al. (2014). Optimized ratiometric calcium sensors for functional in vivo imaging of neurons and T lymphocytes. Nat. Methods 11, 175–182.

  • Tian, L., Hires, S.A., Mao, T., Huber, D., Chiappe, M.E., Chalasani, S.H., Petreanu, L., Akerboom, J., McKinney, S.A., Schreiter, E.R., et al. (2009). Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators. Nat. Methods 6, 875–881.

  • Trachtenberg, J.T., Chen, B.E., Knott, G.W., Feng, G., Sanes, J.R., Welker, E., and Svoboda, K. (2002). Long-term in vivo imaging of experience-dependent synaptic plasticity in adult cortex. Nature 420, 788–794.

  • Wang, W., Fang, H., Groom, L., Cheng, A., Zhang, W., Liu, J., Wang, X., Li, K., Han, P., and Zheng, M. (2008). Superoxide flashes in single mitochondria. Cell 134, 279–290.

  • Wang, H., Karadge, U., Humphries, W.H., IV, and Fisher, A.L. (2014). Analyzing cell physiology in C. elegans with fluorescent ratiometric reporters. Methods 68, 508–517.

  • Weber, T., and Köster, R. (2013). Genetic tools for multicolor imaging in zebrafish larvae. Methods 62, 279–291.

  • Wei-LaPierre, L., Gong, G., Gerstner, B.J., Ducreux, S., Yule, D.I., Pouvreau, S., Wang, X., Sheu, S.-S., Cheng, H., and Dirksen, R.T. (2013). Respective contribution of mitochondrial superoxide and pH to Mt-cpYFP flash activity. J. Biol. Chem. 288, 10567–10577.

  • White, R.M., Sessa, A., Burke, C., Bowman, T., LeBlanc, J., Ceol, C., Bourque, C., Dovey, M., Goessling, W., Burns, C.E., et al. (2008). Transparent adult zebrafish as a tool for in vivo transplantation analysis. Cell Stem Cell. 2, 183–189.

  • Xie, H., Hou, S., Jiang, J., Sekutowicz, M., Kelly, J., and Bacskai, B.J. (2013). Rapid cell death is preceded by amyloid plaque-mediated oxidative stress. Proc. Natl. Acad. Sci. USA 110, 7904–7909.

  • Yamada, Y., and Mikoshiba, K. (2012). Quantitative comparison of novel GCaMP-type genetically encoded calcium indicators in mammalian neurons. Front. Cell. Neurosci. 6, 41.

  • Yoo, S.K., Starnes, T.W., Deng, Q., and Huttenlocher, A. (2011). Lyn is a redox sensor that mediates leukocyte wound attraction in vivo. Nature 480, 109–112.

  • Zhao, Y., Araki, S., Wu, J., Teramoto, T., Chang, Y.F., Nakano, M., Abdelfattah, A.S., Fujiwara, M., Ishihara, T., Nagai, T., et al. (2011). An expanded palette of genetically encoded Ca2+ indicators. Science 333, 1888–1891.

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    Imaging physiological and pathological mitochondrial redox signals in mice.

    Panel (A) indicates different imaging sites that are accessible to redox imaging in mice. Panel (B) illustrates multiparameter imaging in an axotomy paradigm. A spreading wave of permanent glutathione oxidation, mitochondrial acidification, and calcium elevation is induced upon axotomy. White dashed line indicates axotomy site by a pulsed laser. Panel (C) shows a spontaneous mitochondrial contraction under physiological conditions. These contractions go along with a transient oxidation of the glutathione pool and a temporary shortening of the organelle. Multiparameter imaging reveals a concomitant pH increase followed by long lasting matrix acidification (mito-SypHer). Calcium influx plays no major role in the contraction process (mito-RGECO-1). Experiments were performed in Thy1-Grx1-roGFP2 mice (B to C). (D) Scheme summarizes the two kinds of redox signals found under pathological (rounding/fragmentation) and physiological conditions (contraction). y-Axis labeling indicates the signal directions. The mitochondrial inner membrane potential (ψ) increases (indicated by a drop in TMRM fluorescence), whereas the matrix pH (measured by SypHer) shows a short matrix alkalization, followed by an acidification during mitochondrial rounding and contraction. ox: oxidized. Scale bars in (A), brain: 200 μm, spinal cord: 20 μm, peripheral nerve: 5 μm, retina: 25 μm, heart muscle: 20 μm; (B): 2 μm; (C): 5 μm. Images modified and reproduced with permission from Breckwoldt et al. (2014) and Wang et al. (2008). Grx1-roGFP2 retina image: M. Breckwoldt, unpublished.

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    Imaging wound margin H2O2 production in zebrafish larvae.

    (A) Experimental procedure. (B) HyPer imaging in an injured zebrafish larva. [H2O2] is inferred from the YFP500/YFP420 excitation ratio of HyPer. Greyscale scaling is adjusted to improve contrast. (C) Temporal [H2O2] profile in a 10 μm to 30 μm broad region of interest along the wound margin. Arrival of first leukocyte at the wound site (solid red line)±SD (dashed red line) is shown. (D) [H2O2] line profile normalized to the wound margin. Scale bars: 100 μm in (B). Figure modified and reproduced with permission from Niethammer et al. (2009).