Dissecting Redox Biology Using Fluorescent Protein Sensors.

ANTIOXIDANTS & REDOX SIGNALING Volume 24, Number 13, 2016 ª Mary Ann Liebert, Inc. DOI: 10.1089/ars.2015.6266

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FORUM REVIEW ARTICLE

Dissecting Redox Biology Using Fluorescent Protein Sensors Markus Schwarzla¨nder,1 Tobias P. Dick,2 Andreas J. Meyer,3 and Bruce Morgan 2,4

Abstract

Significance: Fluorescent protein sensors have revitalized the field of redox biology by revolutionizing the study of redox processes in living cells and organisms. Recent Advances: Within one decade, a set of fundamental new insights has been gained, driven by the rapid technical development of in vivo redox sensing. Redox-sensitive yellow and green fluorescent protein variants (rxYFP and roGFPs) have been the central players. Critical Issues: Although widely used as an established standard tool, important questions remain surrounding their meaningful use in vivo. We review the growing range of thiol redox sensor variants and their application in different cells, tissues, and organisms. We highlight five key findings where in vivo sensing has been instrumental in changing our understanding of redox biology, critically assess the interpretation of in vivo redox data, and discuss technical and biological limitations of current redox sensors and sensing approaches. Future Directions: We explore how novel sensor variants may further add to the current momentum toward a novel mechanistic and integrated understanding of redox biology in vivo. Antioxid. Redox Signal. 24, 680–712.

Fluorescent Protein Sensors Transforming Thiol Redox Biology

R

edox reactions lie at the heart of all life. Nonetheless, a sufficiently detailed understanding of redox biochemistry inside living cells remains surprisingly elusive in many instances. Reductionist approaches, which have shaped our understanding of biology, have limited power when it comes to redox biology: The physiological electron fluxes that give rise to the steady states of the various cellular redox couples depend on the completeness and intactness of the cellular redox machinery, together with a meaningful thermodynamic driving force and strict spatial organization. These factors allow for kinetic competition and, in turn, specificity, which it is difficult to replicate in vitro. In the few cases where in vivo measurements are possible, for example through the electromagnetic properties of endogenous redox active metals and the spectral behavior of endogenous redoxresponsive pigments, fundamental discoveries have been made, such as chemiosmotic energy transformation by res-

piration and photosynthesis. However, those techniques are only applicable to specific niches of redox biology. The redox biology of thiols has been particularly hard to investigate. Cysteinyl thiol-based oxidative modifications are suspected to play central and diverse roles in cellular regulation, protection, and signaling (62, 96, 171). Such ‘‘thiol switches’’ may respond, either directly or indirectly, to changes in the redox potential of other cellular redox couples as well as to levels of reactive oxygen species (ROS) and reactive nitrogen species (RNS). However, until recently, no reporters that monitor the in vivo status and dynamics of a given thiol redox couple (i.e., the two species of a particular half-reaction, for example, GSSG/2GSH) or ROS/RNS were available. In vitro experiments have not delivered the required advances; on the contrary, they have often added artifacts and cemented problematic interpretations that are unlikely to hold true in vivo. As a result, our understanding of the sophisticated workings of thiol redox dynamics in cells and organisms has remained superficial, a shortcoming that is widely camouflaged by collective and unspecific terms such

1

Plant Energy Biology Lab, Department Chemical Signalling, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany. 2 Division of Redox Regulation, German Cancer Research Center (DKFZ), DKFZ-ZMBH Alliance, Heidelberg, Germany. 3 Department Chemical Signalling, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany. 4 Cellular Biochemistry, Department of Biology, University of Kaiserslautern, Kaiserslautern, Germany.

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FLUORESCENT REDOX SENSORS IN VIVO

as ‘‘cellular redox status’’ or ‘‘oxidative stress.’’ In most cases, the best we have been able to achieve is the measurement of defined redox couples in whole cell lysates. By analogy, this situation is comparable to trying to understand calcium and kinase signaling by measuring the total calcium and phosphate levels of a cell. Hence, new techniques are required, which can monitor the redox state of a specific redox couple, or level of a defined ROS/RNS, with appropriate spatiotemporal resolution, and that ideally do not significantly impact the measured redox species. Recently developed sensors, based on redox-sensitive yellow fluorescent protein (rxYFP) (160) and green fluorescent proteins (roGFPs) (65, 91), now allow real-time monitoring of thiol redox dynamics, combined with the option of precise genetic targeting to any specific subcellular location. This technical advance has already been exploited and refined in a substantial body of studies. However, limitations and misunderstandings remain and the currently available work appears to constitute just the beginning of a new era in redox biology research. Here, we will review how the opportunities that redoxsensitive protein probes offer (Fig. 1) have been harnessed to understand redox biology. For the purpose of this review, we define measurements in any intact living cell or whole organism as in vivo as opposed to cell free systems, which are specified as in vitro. We focus on the in vivo application of rxYFP- and redox-sensitive GFP (roGFP)-based probes in thiol redox and H2O2 sensing to date. The molecular and biophysical principles by which those sensors work have already been thoroughly reviewed (43, 143) and other classes of fluorescent protein-based redox sensors, including the HyPer family, are covered elsewhere (e.g., 128, 159, 253). Sensor Specificities and Fusions

RxYFP and the roGFPs were developed by the rational engineering of YFP (rxYFP), wild-type GFP (roGFP1), and

FIG. 1. Key properties of fluorescent protein redox sensors opening new opportunities for the study of redox biology in vivo. Important strengths of genetically encoded redox sensors include (A) the possibility to make ratiometric measurements that are independent of the level of probe expression (applicable only to roGFPs, not rxYFP). (B) Redox species specificity can be achieved via coupling to specific redox enzymes combined with the option of targeting to (C) defined subcellular locations via genetic fusion to appropriate targeting peptides and proteins. (D) Probe oxidation is fully reversible, permitting dynamic, real-time measurements. To see this illustration in color, the reader is referred to the web version of this article at www.liebertpub.com/ars

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enhanced GFP (roGFP2) to contain two cysteines residues that are present in adjacent b-strands on the surface of the protein b-barrel. The cysteine residues are positioned in close proximity to the chromophore and are readily capable of forming a disulfide bond, leading to small structural changes that influence protein fluorescence. This allows a real-time read out of the redox state of the fluorescent protein thioldisulfide pair. The exact biophysical mechanism by which fluorescence changes occur is slightly different for each fluorescent protein (143), but to illustrate the general biophysical principle we briefly describe next the example of wild-type GFP. Biophysical basis of roGFP-based measurements

The chromophore of wild-type GFP consists of three amino acids, Ser65, Tyr66, and Gly67. These amino acids undergo a post-translational cyclization reaction, followed by dehydration and oxidation steps, leading to formation of the mature chromophore. The phenolic oxygen in the chromophore can exist in either a neutral (protonated) state or an anionic (deprotonated) state, which is reflected by two clear excitation maxima at 395 nm (neutral) and 475 nm (anionic). The proton is reversibly translocated between Tyr66 and Glu222 through a proton-wire involving Ser205 (38). Importantly, minor structural changes in the vicinity of this proton wire lead to significant changes in protonation of Tyr66, which consequently leads to opposing shifts in the relative intensities of the two excitation maxima. These properties were exploited to develop the redox-sensitive YFP (rxYFP) and GFPs (roGFPs). The formation of a disulfide bond between the two engineered cysteine residues triggers small structural changes that are sufficient to significantly affect the protonation state of the chromophore. Thus, the redox state of the engineered dithiol/disulfide pair is coupled to the relative intensity of the two fluorescence excitation maxima. The presence of two excitation maxima with inverse

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intensity shifts permits ratiometric measurements, independent of probe concentration. Of note, the chromophore of all roGFPs is solvent inaccessible and the protonation state is not influenced by ambient pH changes in the physiological range.


Mechanism of the rxYFP and roGFP2 probes

Soon after the development of the rxYFP and roGFP sensors, it became clear that they equilibrate predominantly, if not exclusively, with the glutathione redox couple (GSSG/ 2GSH) when expressed in vivo (142, 161, 198). However, this equilibration is dependent on the presence of glutaredoxins (Grxs), which act as catalysts for thiol-disulfide exchange between the glutathione pool and the redox-sensitive protein (161). Experiments clearly showed that Grx catalyzes equilibration between the glutathione and probe redox couples, and the reaction conforms to the expected Nernstian relationship (86, 161). Thus, upon an increase in EGSH, leading to a disequilibrium EGSH > Eprobe, Grx catalyzes probe oxidation to reestablish equilibrium (Eprobe = EGSH). Likewise, upon a decrease in EGSH, leading to a disequilibrium EGSH < Eprobe, Grx catalyzes probe reduction to re-establish equilibrium (Eprobe = EGSH). Traditionally, Grx is considered an enzyme catalyzing the reduction of S-glutathionylated proteins. Indeed, if EGSH < Eprobe, probe reduction is catalyzed by the expected monothiol mechanism, in a three-step process (32, 142): (i) GSH attacks the roGFP/rxYFP disulfide. (ii) The S-glutathionylated roGFP/rxYFP is then rapidly de-glutathionylated by Grx. (iii) A second GSH de-glutathionylates Grx, yielding GSSG. Although Grx is not typically considered a catalyst for protein oxidation, the probe oxidizing reaction is an exact reversal of the reduction mechanism: (i) GSSG reacts with Grx to yield S-glutathionylated Grx. (ii) The S-glutathionylated Grx is then deglutathionylated by roGFP/rxYFP. (iii) The S-glutathionylated roGFP/rxYFP forms the disulfide bond, releasing GSH. Indeed, the kinetics of roGFP/ rxYFP disulfide bond formation is insignificant in the absence of Grx and dramatically enhanced in the presence of Grx (e.g., 86). Again, a Grx with a single thiol (only capable of supporting the monothiol mechanism) is fully sufficient, if not superior, in catalyzing roGFP/rxYFP oxidation (32). The fact that Grx efficiently operates ‘‘in reverse’’ to rapidly facilitate roGFP/rxYFP oxidation may seem surprising at first glance, because roGFP/rxYFP glutathionylation is expected to be unfavorable as compared with roGFP/rxYFP deglutathionylation. However, it is important to realize that glutathionylation of roGFP/rxYFP is just an intermediate step toward formation of a highly favored (low energy) disulfide bond (E’ = - 280 mV for roGFP2; 143). Thus, it is the thermodynamic coupling between Sglutathionylation (unfavorable) and disulfide bond formation (favorable) that allows Grx to act as an efficient catalyst of roGFP/rxYFP disulfide bond formation. Accordingly, as confirmed experimentally, the whole system is only driven by the potential difference (DE) between the glutathione and probe (disulfide/dithiol) redox couples. Thermodynamically, the intermediary glutathionylation/

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deglutathionylation steps are inconsequential. Kinetically, they are hugely important. rxYFP-yGrx1 and Grx1-roGFP2

The use of rxYFP and roGFPs to monitor EGSH in vivo is restricted to subcellular compartments that harbor appropriate glutaredoxin activity to mediate the equilibration between the probe and the glutathione redox couple. The possibility that glutaredoxin availability may influence measurements thus raises concerns about making comparisons between different subcellular compartments, cell types, and organisms and makes it impossible to make measurements in compartments lacking glutaredoxin activity. The first steps to address these problems were taken by the group of Jakob Winther. They constructed the first ‘‘fusion probe,’’ by genetically coupling yeast Grx1 (yGrx1) to rxYFP using a short linker peptide (32). The rxYFP-yGrx1 probe is effectively independent of the availability of endogenous glutaredoxins, and, thus, measurements can be made in—and become comparable between—different subcellular compartments, different cell types, and different organisms. The genetic fusion of yGrx1 also increases the effective local Grx concentration ‘‘seen’’ by the rxYFP by around 3000-fold, which affords two further advantages compared with unfused rxYFP. First, the kinetics of the equilibration between the analyte and the rxYFP is dramatically increased (by around 4000-fold in vitro), which, in turn, leads to a further increase in the specificity of rxYFP to the glutathione redox couple (32). Thus, in principle, the rxYFP-yGrx1 fusion probe permits real-time, highly specific EGSH measurements in vivo. However, it has not been applied for such measurements to date, because rxYFP is not ratiometric (160). The next probe to be developed was a specific EGSH sensor based on a fusion of human Grx1 (hGrx1) to roGFP2 (86). RoGFP2 holds two key advantages compared with rxYFP when the fluorescent properties of the sensor are exploited. First, it lends itself to ratiometric fluorescence excitation imaging, making measurements independent of sensor concentration, that is, expression level. Second, the ratiometric readout is largely unaffected by pH changes within the physiological range (pH 5.5–8.5), whereas rxYFP fluorescence emission is pH sensitive (86, 161, 198). The resultant Grx1-roGFP2 sensor (if not specified otherwise, Grx1 in all fusion sensors described in this review represents hGrx1) currently remains the best characterized sensor for monitoring real-time changes in EGSH, with subcellular compartment specificity in intact living cells. RoGFP variants such as roGFP1-iE or roGFP1-iL and roGFP2-iL have been developed, each of which harbor a thiol/disulfide pair with a less reducing midpoint potential than roGFP1 and 2 (4, 125). These have been fused to hGrx1 and used to monitor EGSH in the endoplasmic reticulum (ER; 30) and in the cytosol of severely glutathione-depleted Arabidopsis seedlings (4), respectively. Subsequent to the development of the Grx1-roGFP2 and rxYFP-yGrx1 sensors, it was recognized that when coupled directly to other redox enzymes, rxYFP and the roGFPs can respond to other redox species. These observations triggered attempts to genetically fuse these enzymes, predominantly to roGFP variants, to generate in vivo redox sensors with


specificity toward a number of different redox species. This ‘‘modular’’ approach to probe design, that is, combining specific redox enzymes with selected fluorescent redox sensors, allows the development of probes specifically tailored to the redox species, subcellular compartment, and cell type of interest (Fig. 2).


roGFP2-Orp1

Shortly after the development of the Grx1-roGFP2 and rxYFP-yGrx1 probes, roGFPs were also employed to develop probes for hydrogen peroxide (H2O2). The mechanistic principle underlying these probes is borrowed from a concept found in nature, where redox relays exist between thiol peroxidases and specific target proteins (57, 208). Thiol peroxidases react extremely sensitively with H2O2, resulting in the formation of a sulfenic acid group and, subsequently, a disulfide bond. The oxidation from either of these groups can then be transferred, by means of a thiol-disulfide exchange reaction, either to dedicated reductive systems, such as thioredoxins (Trxs) or Grxs, or to specific target proteins. This mechanistic principle was used to develop the roGFP2Orp1 H2O2 sensor (87), in which close proximity between a peroxidase (Orp1) and an artificial target protein (roGFP2) is established by genetic fusion. This ensures that oxidation is passed efficiently from Orp1 to roGFP2, in preference to endogenous Orp1 reductants such as Trxs or the transcription factor Yap1 (if expressed in yeast). The roGFP2-Orp1 probe is readily oxidized by H2O2. This reaction per se is irreversible under physiological conditions; nevertheless, the oxidized probe is reduced in vivo, thereby

FIG. 2. Fusion sensors and specificities. An illustration of the rxYFP and roGFP-based constructs that have been used in vivo (see also Table 1). yGrx1 and yGrx2 represent yeast Grx1 and Grx2, respectively. To see this illustration in color, the reader is referred to the web version of this article at www.liebertpub.com/ars

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permitting dynamic measurements. Clearly, the probe reduction must be mediated by other cellular redox couples. The most likely candidates are the Grx system, which, as discussed earlier, can interact directly with the roGFP, and the Trx system, which can directly reduce the Orp1 moiety. The relative importance of each of these systems for roGFP2Orp1 reduction remains unclear and likely varies between subcellular compartments, cell types, and organisms. Consequently, it is possible that due to differences in reductive efficiency, the sensitivity of the roGFP2-Orp1 probe to H2O2 may vary depending on the context. The redox state of the roGFP2-Orp1 probe is therefore not only influenced by the oxidant (H2O2), but also by the reductants GSH and thioredoxin. The same is true for the HyPer family of H2O2sensing probes (21, 28, 71, 72, 131). In that sensor family, the OxyR protein from Escherichia coli forms an intramolecular disulfide upon oxidation by H2O2, modifying the spectroscopic properties of a fused circularly permuted fluorescent protein. Reduction of oxidized HyPer is assumed to occur via the endogenous glutathione/Grx system in vivo, although this has not been established in full detail and may depend on the specific intracellular context. While the integration of oxidizing (H2O2) and reducing (Trx/GSH) influences may be considered a disadvantage of roGFP2-Orp1 and the HyPer probes, they are reflective of how the redox state of endogenous H2O2-reactive thiols is regulated, that is, determined by both a per se irreversible reaction with H2O2 and subsequent reduction by alternative systems. The ER harbors numerous protein disulfide isomerase (PDI) homologs. While roGFP oxidation can indeed be catalyzed by PDIs in principle (10), their relative contributions

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in vivo are unknown and their interaction properties with Orp1 have not been tested. Furthermore, the ER maintains an active disulfide-generating machinery as well as a glutathione pool that is too oxidized to reduce roGFP2-Orp1 probes. Given these considerations, particular care and appropriate controls should be implemented when employing any currently available genetically encoded probe in the ER, or other compartments in which the interactions of the probes are poorly understood, to be sure of what the probe is actually measuring. Mrx1-roGFP2

Glutathione is not ubiquitously present in all organisms. Functional homologs of glutathione in other organisms include trypanothione, bacillithiol, and mycothiol. Recently, the group of Amit Singh developed a probe for measuring the mycothiol redox potential EMSH (25). The development of this probe was made possible by the identification of mycothiol-specific Grx homologs in Mycobacterium species (222). When genetically fused to roGFP2, these oxidoreductases perform the functionally homologous reaction to Grxs, mediating the equilibration of roGFP2 with the intracellular mycothiol redox couple. roGFP2 fusion to p47phox

Recently, roGFP2 was fused to the NADPH oxidase 2 (NOX2) complex organizer protein p47phox (162–164). In analogy to the discovery of calcium microdomains by targeting calcium sensors to defined subcellular locations, this is the first example of localizing redox sensors in the direct vicinity of sources of oxidant production and it has the potential to lead to valuable new insights into the redox properties of cellular micro-compartments. However, caution should be taken with the interpretation of results obtained with such novel fusions. Despite sometimes ambiguous claims in the literature, roGFP1 and 2 are not ‘‘ROS sensors.’’ The rate of direct roGFP2 oxidation by H2O2 is very slow when compared with the rate of reduction by equilibration with the glutathione pool via cytosolic Grxs, and it is unlikely to play any significant role under most in vivo situations. While sensor responses were observed with the p47phox-roGFP2 fusion probe, indicating that the sensor does indeed indicate NOX2 activity, it is unclear which redox species is actually driving roGFP2 oxidation; GSSG is the most likely candidate, although at present it cannot be ruled out that other redox enzymes are localized to the p47phox microdomain and could play a role in roGFP2 oxidation. An additional consideration is that p47phox and thus the fused roGFP2 is actually located on the cytosolic side of the plasma membrane, in contrast to the site of superoxide release from the NOX2 complex, which is directed toward the extracellular space. Superoxide is rapidly dismutated to H2O2, which may, subsequently, be able to enter the cell, potentially by specific aquaporin channels (27). However, the advantage of genetically linking an roGFP2 with an accessory protein of an H2O2-producing protein complex remains unclear when the sensor is separated from the H2O2 production site by a membrane and re-entry of H2O2 into the cell may occur at a different location in the plasma membrane. To decide whether redox changes are specifically localized to the site of the p47phox microdomain or even the inner surface of the plasma


membrane in general, an unfused roGFP2 control (i.e., freely diffusible in the cytosol) would be required for comparison. Nevertheless, it appears likely that p47phox-roGFP2 fusion constructs can yield valuable insights into how protein oxidation actually occurs in microdomains of oxidant production. This is especially true because many endogenous redox regulated proteins suffer from the same issue as roGFPs, that is, they are intrinsically unreactive toward H2O2, and likely require enzyme catalysts to mediate their oxidation. To understand the actual oxidation processes at the molecular level it will thus be particularly interesting to localize redox species-specific probes, that is, roGFP2-Orp1 and Grx1-roGFP2 to specific sites of oxidant production such as p47phox. Perhaps then, when used in combination with probes localized to various other appropriate subcellular locations, we can begin to understand the spatio-temporal dynamics of the various cellular redox species. Subunit orientation is important for organelle targeting in some organisms

At least in the case of the Grx1-roGFP2 the domain order appears to be irrelevant to the function of the sensor (3, 151). In vitro and in vivo measurements made with Grx1-roGFP2 and roGFP2-Grx1 probes are very similar, with the exception that the kinetics of reduction and oxidation may be slightly quicker for roGFP2-Grx1 than for Grx1-roGFP2 (3). However, these new domain order probe variants are particularly useful for organellar targeting of the probe in some organisms. While Grx1-roGFP2 can be efficiently targeted to the mitochondrial matrix (MM) in mammalian cells, this is not the case in both Arabidopsis and Drosophila. However, efficient targeting can be achieved with roGFP2-Grx1. Due to its superior targeting properties, roGFP2-Grx1, therefore, represents the sensor of choice for EGSH measurements in the MM in a broad range of organisms. Redox Sensors in Different Organisms, Tissues, and Compartments

Yeast was the first in vivo system to be analyzed with rxYFP (161), while the roGFPs were initially applied in mammalian cell lines (65, 91). In this early work, roGFPs were already targeted to several subcellular compartments, including the cytosol, the MM, the plasma membrane, and the nucleus (65), demonstrating their potential for location-specific analysis of redox phenomena. Since then, most work with the roGFPs has been carried out in mammalian cell lines, with additional subcellular locations analyzed, including the mitochondrial intermembrane space (IMS), the peroxisomes, endosomes, lysosomes, and the ER. Table 1 and Fig. 3 provide an overview of the systems, the specific sensor variants, and subcellular locations covered by published work, the body of which is rapidly growing (Fig. 3A). Mammalian cell lines were followed by plants for which a combination of transient expression in tobacco leaves and stable Arabidopsis lines for global expression of roGFP1 and 2 were established for the cytosol, the MM, the plastid stroma, the peroxisomes, and the ER (104, 142, 198) (Fig. 3B). On the basis of those genetic resources, the different roGFP variants have been extensively used in a variety of photosynthetic (e.g., leaves, hypocotyl) and nonphotosynthetic plant tissues (e.g., roots) and allow the investigation of the

685

rxYFP rxYFP roGFP1

roGFP1 roGFP1

roGFP1 roGFP1 roGFP1

roGFP1 roGFP1 roGFP1-iE roGFP1-iL roGFP1-R12 roGFP2

roGFP2 roGFP2

roGFP2 roGFP2 roTurbo roGFPx

roGFPx roGFPx

Grx1-roGFP1-iE Grx1-roGFP1-iL

Human Human

Human Human Human

Human Human Human Human Human Human

Human Human

Human Human Human Human

Human Human

Human Human

rxYFP

Sensor variant

Human Human Human

Human Human

System

ER ER

ER MM

PM PX C C

ER MM

N PM ER ER MM C

IMS LY MM

EN ER

MM N C

C

Cell compartment Embryonic kidney cells 293T Phoenix, HeLa cells, epidermal keratinocytes HEK001 HeLa cells, epidermal keratinocytes HEK001 HeLa cells, epidermal keratinocytes HEK001 HeLa cells, promyelocytic leukemia cells HL60, embryonic kidney cells HEK293, U937 macrophage cells, airway epithelial cells JME/CF15, dopaminergic neuroblastoma SK-N-SH cells, CFTR-CFB41o cells, prostate cancer cells DU145 Prostatic cancer cells PC3 Airway epithelial cells JME/CF15, prostatic cancer cells PC3, embryonic kidney HEK 293 cells Dopaminergic neuroblastoma cells SK-N-SH Prostatic cancer cells PC3 HeLa cells, A431 cells, airway epithelial cells JME/CF15, prostatic cancer PC3 cells, dopaminergic neuroblastoma cells SK-N-SH HeLa cells Airway epithelial cells JME/CF15 HeLa cells, embryonic kidney HEK 293 cells, Flp-in Trex cells 293 Fibroblastic HT1080 cells, HeLa cells, Flp-in Trex 293 cells, SHSY-SY cells Bladder cancer cells 253J, 253J B-V Promyelocytic leukemia cells HL60, embryonic kidney cells HEK293 cells, HeLa cells, liver cells AML12, osteosarcomal cells 143B, airway epithelial cells, endothelial cells ECV304, airway epithelial cells BEAS-2B, primary fibroblasts, lung cancer cells A549 HeLa cells, Flp-in Trex 293 cells Endothelial ECV304 cells, airway epithelial cells BEAS-2B, HeLa cells, primary fibroblasts, malignant mesothelioma cells HMESO1 & H2373, mesenchymal stem cells, retinal pigment epithelial cells ARPE19 HeLa cells Primary fibroblasts Neuroblastoma SH-SY5Y cells Primary lung fibroblasts, dopaminergic neuroblastoma cells SK-N-SH, airway epithelial cells JME/CF15, nonsmall-cell lung cancer cells A549, hepatoma cells Hep3B, alveolar epithelium-derived tumor cells A549, osteosarcoma cells 143B Airway epithelial cells JME/CF15 Dopaminergic neuroblastoma cells SK-N-SH, HeLa cells, nonsmall lung carcinoma cells H520, airway epithelial cells JME/CF15, primary lung fibroblasts, lung embryonic fibroblasts WI-38 HeLa cells, Flp-in Trex 293 cells HeLa cells, Flp-in Trex 293 cells

Tissue type/cell line

Table 1. In Vivo Application of rxYFP, roGFPs, and Their Variants References

30, 31 30 (continued)

195, 197 5, 103, 113, 165, 205, 242

65 102 66 5, 20, 81, 89, 103, 113, 195

30, 221 49, 52, 53, 65, 102, 122, 168, 228, 251

173 9 9, 50, 56, 91, 173, 181, 196, 232, 241 65 196 10, 30, 31 30, 163, 223 94 48, 49, 52, 65, 80, 86, 90, 102, 155, 157, 168, 170, 228

9 9, 109, 196, 232

17 16, 17 65, 109, 140, 173, 193, 194, 196, 201, 232, 241

17, 137


686

roGFP1-iE roGFP1-iL roGFP1-R12 roGFP2

roGFP2

roGFP2 roGFPx

roGFPx roGFPx

Mouse Mouse Mouse Mouse

Mouse

Mouse Mouse

Mouse Mouse

IMS MM

PX C

MM

ER ER C C

MM

C ER C MM C C C

roGFP1 roGFP1-iL roGFP2 roGFP2 Grx1-roGFP2 rxYFP roGFP1

roGFP1

C C MM

roGFP2 roGFPx roGFPx

Mouse

ER

roGFP1-iE

C C/PM

roGFP2-Orp1

Human

ER MM

C C

Cell compartment

p47-roGFP2

Grx1-roGFP2 Grx1-roGFP2

Human Human

Human Monkey Monkey Cloven-hoofed Sheep Sheep Sheep Rodent Hamster Hamster Hamster Hamster Hamster Mouse Mouse

roGFP2-Grx1 Grx1-roGFP2

Sensor variant

Human Human

System

Ovarian CHO cells Ovarian CHO cells Ovarian CHO cells Ovarian CHO cells Ovarian CHO cells B16F10 mouse melanoma cells Transgenic mouse line (EF1a), skin epidermal keratinocytes, P388D1 cells, NR6 cells, neurocortical neurons, hippocampal neurons Transgenic mouse line (EF1a), skin epidermal keratinocytes, flexor digitorum brevis Embryonic fibroblasts 3T3-L1 fibroblasts Alveolar macrophages MHS NR6 cells, P388D1 cells, erythrocytes, lung epithelial cells C10, mouse embryonic fibroblasts Lung epithelial cells C10, mouse embryonic fibroblasts, thymic lymphoma cells WEHI7.2 Embryonic fibroblasts Lung slices, pulmonary arterial smooth muscle cells, mesostriatal co-cultures, lung vascular cells Pulmonary arterial smooth muscle cells Transgenic mouse line (TH & CMV), monoaminergic neurons, dopaminergic circuits, brain slices, pulmonary arterial smooth muscle cells, mesostriatal cocultures, DMV neurons, noradrenergic locus coeruleus neurons, embryonic fibroblasts

Pulmonary arterial smooth muscle cells Fetal pulmonary artery smooth muscle cells Fetal pulmonary artery smooth muscle cells

Kidney cells COS-7

HeLa cells HeLa cells, airway epithelial cells,T-lymphocytic J1.1 cells, Jurkat cells, monocytic U1 & U937 cells, U251MG-L106 spheroid-forming glioblastoma cells, embryonic kidney cells HEK 293, SHSY-SY cells HeLa cells, Flp-in Trex 293 cells Monocytic U1 & U937 cells, U251MG-L106 spheroid-forming glioblastoma cells, embryonic kidney HEK 293 cells T-cells, HeLa cells, embryonic kidney cells HEK293, nonsmall-cell lung cancer cells A549 SHSY-SY cells


Table 1. (Continued) References

(continued)

234 67, 82, 88, 188, 234, 236

102 63, 67, 183, 234

54, 102, 220

254 189 100 19, 54, 65, 102, 245

145, 243

129 117 116 129 116 136 65, 84, 148, 243, 244

203 74, 167, 235 74, 167

10

163

81, 87, 207

30 26, 71, 240

3 3, 26, 75, 80, 86, 163, 212, 221, 240


687

C ER MM MM C C, MM C MM

roGFP1-R12 roGFP2 roGFP2 roGFP2-Grx1 Grx1-roGFP2 roGFP2-Orp1

roGFP1-R12 roGFPx

N IMS MM

MM C

roGFPx roGFP2 roGFP2

Rat Rat Rat

IMS MM

roGFP2 Grx1-roGFP2

roGFPx roGFPx

Rat Rat

C

C MM

roGFPx

Rat

ER C

roGFPx roGFPx

roGFP1-iE roGFP2

Rat Rat

ER MM

ER C MM

roGFP1 roGFP1

Rat Rat

MM C/PM C

C

Cell compartment

Grx1-roGFP1-iE Grx1-roGFP2 Grx1-roGFP2

Grx1-roGFP2 p47-roGFP2 roGFP1

Mouse Mouse Rat

Rat Rat Rat Avian Chicken Chicken Fish Zebrafish Zebrafish Insect Drosophila Drosophila Drosophila Drosophila Drosophila Drosophila Nematode C. elegans C. elegans

Grx1-roGFP2

Sensor variant

Mouse

System

Global Transgenic worm line (Pmyo-3), ventral cord neuritis neurons

Transgenic fly line (GAL4/UAS), primary neuronal cells Schneider cells Transgenic fly line (GAL4/UAS), primary neuronal cells Global, Schneider cells Global Global

Peripheral sensory neurons Intestinal epithelium

Cardiomyocytes Cardiomyocytes

Macrophagal cells RAW264.7, stromal bone marrow cells ST-2, cortical neurons, flexor digitorum brevis Transgenic mouse line (Thy1), neurons, oocytes Flexor digitorum brevis PC12 cells, ventricular myocytes, hippocampal slices & neurons, pancreatic INS1 832/13 b-cells Pancreatic INS-1 832/13 b-cells Pancreatic islets, pancreatic b-cells, insulinoma cells INS-1E, hippocampal neurons Pancreatic cells AR42j PC12 cells, pulmonary microvascular epithelial cells, lung slices, alveolar epithelial type 2 cells, pulmonary arterial smooth muscle cells, small airway smooth muscle cells, cerebellar granule neurons Pulmonary arterial endothelial cells, pulmonary arterial smooth muscle cells, pulmonary arterial epithelial cells, embryonic myocardial cells H9C2 Pulmonary arterial smooth muscle cells Embryonic myocardial cells H9C2, pulmonary arterial smooth muscle cells, hippocampal neurons Pulmonary artery endothelial cells Pulmonary arterial smooth muscle cells, small airway smooth muscle cells Lung slices, alveolar epithelial type 2 cells, pulmonary arterial smooth muscle cells, small airway smooth muscle cells McA-RH7777 hepatoma cells Pancreatic islets, neonatal cardiomyocytes H9c2 Pancreatic islets



176 79, 106, 107

124 187 44, 124 2, 3 2 2

158 202

127, 172 126, 127

231 210, 216 216

1 233 6, 24, 233

184 29, 184, 250

1, 51, 184, 250

10 6, 24, 65, 112, 226, 233

109 64, 69, 78, 174, 175

37, 219 162, 164 65, 77, 109, 229, 243

46, 86, 92, 164


(continued)

688

C MM PX C ER MM PL MM C

roGFP1 roGFP1 roGFP1 roGFP2 roGFP2 roGFP2 roGFP2 roGFP2-Grx1 Grx1-roGFP2

plant plant plant plant plant plant plant plant plant

line line line line line line line line line

(35S/UBQ10) (35S/UBQ10) (35S/UBQ10) (35S/UBQ10) (35S/UBQ10) (35S/UBQ10) (35S/UBQ10) (35S/UBQ10) (35S/UBQ10)

Global—transgenic fungus line (OliC) Global—transgenic fungus line (RP27)

C C

Global

Global—transgenic fungus line (OliC)

C

C

Pollen, leaf epidermis Leaf epidermis Leaf epidermis Leaf epidermis Leaf epidermis Leaf epidermis Leaf epidermis Pollen—transgenic plant line (LAT52) Protoplasts

Global Global Global Global Global Global

Global

Global—transgenic plant line (35S/UBQ10) Global—transgenic plant line (35S/UBQ10) Global—transgenic plant line (35S/UBQ10) Protoplasts

Global—transgenic Global—transgenic Global—transgenic Global—transgenic Global—transgenic Global—transgenic Global—transgenic Global—transgenic Global—transgenic

Global (rpl-17) Global (myo-3)


MM N PL MM N PL C MM C ER PL PX C C C

C

PL PX C PL

C MM

Cell compartment

Grx1-roGFP2 Grx1-roGFP2

Sensor variant

Arabidopsis Grx1-roGFP2 Arabidopsis Grx1-roGFP2 Arabidopsis Grx1-roGFP2-iL Bienertia roGFP2 sinuspersici Phaeodactylum roGFP2 tricornutum P. tricornutum roGFP2 P. tricornutum roGFP2 P. tricornutum roGFP2 P. tricornutum roGFPx P. tricornutum roGFPx P. tricornutum roGFPx Tobacco roGFP1 Tobacco roGFP1 Tobacco roGFP2 Tobacco roGFP2 Tobacco roGFP2 Tobacco roGFP2 Tobacco Grx1-roGFP2 Tomato roGFP1 Maize roGFP1 Eukaryotic pathogen Botrytis roGFP2 cinerea B. cinerea Grx1-roGFP2 Magnaporthe Grx1-roGFP2 oryzae Plasmodium Grx1-roGFP2 falciparum

C. elegans C. elegans Plant Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis Arabidopsis

System


110

93, 192 185

93

(continued)

83 83 83 177 177 177 99, 211, 239 211 35, 119, 142, 198, 209, 230 35, 119, 142, 198, 209, 230 211 198 134 99 123

83

8, 39, 104, 108, 152, 178, 198 104, 152, 178, 179, 198, 199a, 214 178 22, 35, 121, 135, 142, 191, 198, 199 35 121, 179, 198, 199 121, 135, 178, 179, 198, 199 3, 190 4, 68, 118, 133, 166, 179, 190, 238, 247 118, 166, 247 179 4 180

14 98


689

C ER C ER C ER C IMS MM N MM C C ER IMS MM PX MM C C IMS MM PX C C C C C C C C C C S

rxYFP rxYFP rxYFP roGFP1 roGFP1-R12 roGFP2 roGFP2 roGFP2 roGFP2 roGFP2 roGFPx roGFP1-iL-Grx1 Grx1-roGFP2 Grx1-roGFP2 Grx1-roGFP2 Grx1-roGFP2 roGFP2-Grx1 roGFP2-yGrx1 roGFP2-yGrx2 roGFP2-Orp1

roGFP2

rxYFP

roGFP2 roGFP1-R12

roGFP1-R12

Mrx1-roGFP2 roGFP2

Cell compartment

roGFP1 roGFP1 roGFP1-iE roGFP1-iE roGFP1-iL roGFP1-iL rxYFP

Sensor variant

Global Global

Global

Global Global

Global

Global

Global Global Global Global Global Global Global Global Global Global Global Global Global Global Global Global Global Global Global Global

Global Global Global Global Global Global Global


26 206

15

7 47

160

232

97 97 55 95, 138, 139, 227 246 11–13, 115, 151 141 115 11–13, 115 11, 12 224 151 36, 70, 85, 114, 115, 151 114, 115 70, 114, 115 70 151 151 151 33

58–60 59, 60 59, 60 58–60 59, 60 59, 60 55, 97, 161

References

Expression of rxYFP, roGFPs, and derived variants in organisms, tissues, cells, and subcellular compartments. roGFPx, sensor version not specified or ambiguous in the corresponding report; C, cytosol; EN, endosomes; ER, endoplasmic reticulum; IMS, mitochondrial intermembrane space; LY, lysosomes; MM, mitochondrial matrix; N, nucleus; PL, plastid; PM, plasma membrane; PX, peroxisome; S, cell surface. Grx1 represents human Grx1; yGrx1 and yGrx2 represent yeast Grx1 and Grx2, respectively. No claim of comprehensiveness is made.

Yeast Pichia pastoris P. pastoris P. pastoris P. pastoris P. pastoris P. pastoris Saccharomyces cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae S. cerevisiae Eubacteria Chlamydia trachomatis Escherichia coli E. coli Lactococcus lactis Mycobacterium tuberculosis M. tuberculosis Shewanella oneidensis

System

Table 1. (Continued)



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FIG. 3. In vivo systems exploiting fluorescent protein redox sensors. (A) Number of published articles, exploiting rxYFP (introduced in 2001) and roGFP sensors (introduced in 2004) in vivo, as estimated by our survey of the literature (Table 1). (B) Subcellular compartments targeted for sensor expression in animal, plant, yeast, and bacterial systems so far; C, cytosol; EN, endosomes; ER, endoplasmic reticulum; IMS, mitochondrial intermembrane space; LY, lysosomes; MM, mitochondrial matrix; N, nucleus; PL, plastid; PM, plasma membrane; PX, peroxisome; S, cell surface (see Table 1 for details). impact of a sessile, photo-autotrophic lifestyle on cellular thiol redox dynamics. Recently, roGFP2 was introduced into the diatom Phaeodactylum tricornutum (177), opening the chance for a comparative analysis of thiol redox dynamics across photosynthetic organisms, although important systems such as mosses are currently missing. Furthermore, a tomato expressing roGFP1 in the cytosol of pollen (99) is currently the only crop plant line available featuring stable redox sensor expression, although global expression would be desirable, and cereal systems such as rice make obvious additional candidates. In yeast, the pioneering work using rxYFP in the cytosol (161) was followed by a major study employing roGFP2 in the ER (141). Expression of different sensor variants in the cytosol, the MM, the IMS, the peroxisomes, and the ER have since been used to address several fundamental and mechanistic questions of eukaryotic redox biology (36, 114, 151) (Fig. 3B and Table 1). Studies in yeast have benefited from the medium to high-throughput possibilities afforded by plate-reader-based measurements. Although the same is, in principle, also true for many prokaryotes—and most work on the in vitro characterization of all sensor variants has relied on harnessing overexpression in E. coli—in vivo studies are still under-represented for eubacteria and unavailable for archaea. Stable lines for cytosolic Grx1-roGFP2 expression in three eukaryotic parasites have been generated. Both the necrotrophic fungus Botrytis cinera (the ‘‘noble rot’’ of grapes and ‘‘gray mold’’ on other crops) and the rice blast fungus Magnaporthe oryzae are plant pathogens of eminent agricultural relevance (93, 185). Recently, a sensor line has also been made for the malaria-causing parasite, Plasmodium falciparum (110), allowing in vivo redox imaging of the intracellular pathogen within their host cells (mammalian red blood cells; r.b.c.). Despite the central, yet largely elusive,

role of thiol and free radical redox dynamics during infection and immune responses Mycobacterium tuberculosis and Chlamydia trachomatis are the only bacterial pathogens that have been equipped with redox sensors so far (15, 25, 232) (Fig. 3B and Table 1). The availability of sensor systems for both pathogen and host may turn out to be a particularly powerful tool for dissecting the redox interplay of their interaction. More complex, nonplant and nonmammalian eukaryotes are currently covered by expression of roGFP variants in the fly model Drosophila, the nematode model Caenorhabditis elegans and zebrafish (Table 1). Different roGFP derivatives have been targeted to the cytosol and the MM, while other cellular compartments are not yet available. Those systems allow the analysis of redox dynamics in an entire multicellular organism, that is, across tissues and developmental stages, including sexual reproduction and aging. Recently, the first mouse models of the redox sensors have been introduced. Mouse lines expressing a roGFP variant in the MM (82, 88) were generated for the study of Parkinson’s disease, followed by cytosolic and MM roGFP1 lines that have been used for the in vivo analysis of redox dynamics in the skin (243). Independently, a model expressing the Grx1roGFP2 sensor in the MM of neurons was established and exploited for the study of redox physiology and pathology in axonal mitochondria in living animals (37). With the availability of whole mammalian models, translation of insights on the subcellular redox dynamics gained from cell lines, especially under pathology, into a bona fide in vivo context can commence. The subcellular targeting of the redox sensors is similar across eukaryotic systems. In most studies, redox sensors are expressed in the cytosol (C) and/or the MM, but seven distinct compartments have been targeted with soluble sensors



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so far, covering the IMS, the nucleus (N), the peroxisome (PX), the ER, and the plastids of plants (PL). In addition, four membrane systems have been targeted, the plasma membrane (PM), membranes of recycling and late endosomes (EN), lysosomes (LY), and the ER membrane, where the sensor has been attached to the membrane facing the cytosol or the ER lumen (9, 35, 65, 162). Making a distinction between nuclear and cytosolic redox analysis is questionable, since even if sensor expression is limited to one of those locations most interacting molecules are below the size exclusion limit of the nuclear pores and fully diffusible between both compartments. Like any genetically encoded probe, the fluorescent protein redox sensors lend themselves to targeting to sub-compartmental structures, complexes, or microdomains to provide a readout of the local physiological conditions. Such an approach has allowed the observation of calcium micro-domains, but has thus far only been actively attempted by fusing roGFP2 to p47phox, a subunit of the NOX complex (162). Opening the Door to Novel Biology Highly reduced plasmatic glutathione pools

Genetically encoded probes revolutionized our ability to investigate cellular glutathione homeostasis. Before such probes became available, the options for making measurements of the glutathione pool were, barring a few exceptions (144), limited to biochemical analyses of whole cell lysates (169). Unavoidably, these analyses destroy all sub-cellular compartment-specific information; they have limited temporal resolution and are prone to postlysis artifacts. While specific measurements of the cytosolic glutathione pool were not previously possible, the whole cell GSH:GSSG ratio, which is around 50:1 depending on the cell type, was, and often still is, commonly assumed to be broadly representative of the cytosolic glutathione pool. The advent of genetically encoded redox probes allowed direct, real-time imaging of EGSH, with subcellular compartment specificity, inside intact, living cells. The initial application of rxYFP in yeast led to the highly surprising observation that the GSH:GSSG ratio is in the order of 3000:1, implying that cytosolic GSSG levels are much lower than previously assumed (161). Simultaneosuly, the development of the first roGFP sensors was reported. When applied to the MM (91) and cytosol (65) of HeLa cells, these probes too reported highly reduced ‘‘cytosolic redox potentials.’’ Subsequently, roGFPs were shown to equilibrate predominantly with the glutathione redox couple (142). These roGFP-based studies implied that cytosolic EGSH is even more reducing (* - 320 mV) than originally measured with rxYFP. Remarkably, for a total glutathione concentration range of 1–10 mM, this indicates a GSH:GSSG ratio of between 50,000:1 (10 mM total glutathione concentration) and 500,000:1 (1 mM total glutathione concentration) (Fig. 4). This equates to only 60–6000 GSSG molecules in the entire cytosol, assuming a cytosolic volume of 50 lm3, which is typical for a yeast cell. At those GSH:GSSG ratios, EGSH is far from the ‘‘buffered’’ range (E0’GSH = - 240 mV): Very small (nanomolar to micromolar) changes in GSSG concentration lead to large changes in EGSH. Hence, the cytosolic glutathione pool itself is not able to ‘‘buffer’’ EGSH. Instead, EGSH can only be kept at a steady state if any accumulation of

FIG. 4. Fundamental insights into in vivo thiol redox biology gained through in vivo imaging of fluorescent redox sensors. The application of rxYFP and roGFP-based sensors have already greatly deepened our understanding of cellular redox biology. Novel insights include (i) the discovery of highly reduced plasmatic glutathione pools GSH:GSSH &50,000:1, (ii) the identification of GSSG transport between subcellular compartments such as the cytosol and vacuole, (iii) the realization that glutathione homeostasis can be independently regulated in different subcellular compartments, for example, the cytosol and mitochondrial matrix, and (iv) the observation that changes in H2O2 levels and EGSH can occur independently from another in a given compartment and are not always firmly linked. Furthermore, (v) roGFPs have been established as a tool to investigate the topology of membrane proteins by harnessing EGSH gradients (ReTA: redox-based topology analysis).

GSSG is prevented. It is also worth noting that a value of - 320 mV may be regarded as a conservative estimate: roGFP2-based sensors are almost completely reduced in the cytosol and operate at their sensitivity limit, leaving open the possibility that even more negative glutathione redox potentials may occur. Subsequent measurements with the Grx1roGFP2 fusion protein reported similar EGSH values in the cytosol of mammalian cells (86). Since then, very similar cytosolic EGSH values have been reported for all organisms in which roGFP measurements have been performed, including bacteria, yeast, eukaryotic parasites, worms, flies, zebrafish, multiple mammalian cell lines, plants, and mice (Table 1). Interestingly, assessment of the mycothiol pool in the prokaryote M. tuberculosis (25) also indicates a strongly reducing mycothiol redox potential (EMSH) in the cytosol. Reconciling probe-based measurements with whole cell data

The highly reduced cytosolic EGSH values reported by the roGFP-based probes raise the question of how to reconcile these with the much more oxidized EGSH typically measured in whole cell lysates, which are in the range of - 210 to


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-240 mV and are frequently claimed to be representative of the cytosolic glutathione pool, for example (111). To address this question, we performed a simple set of calculations to ask what EGSH value we can expect to measure in a cell lysate prepared from cells in which the cytosolic EGSH is fixed at - 320 mV (Fig. 5A). For simplicity, only two separate subcellular glutathione pools (cytosolic, ER) are assumed. While that is not strictly correct, a separation into more reducing compartments (cytosol, nucleus, mitochondria, peroxisomes and chloroplasts, here represented as ‘‘cytosol’’) and more oxidizing compartments (ER, Golgi, other secretory compartments and vacuole, here represented as ‘‘ER’’) is justified. Since empirical data vary between studies, the assumptions on which we base our calculations are selected conservatively. We assume a total glutathione concentration of 10 mM throughout the cell, although there is evidence for higher total glutathione concentrations in the ER as compared with the cytosol (149). We also assume perfect lysate prep-

FIG. 5. Whole-cell lysate EGSH offers no information on cytosolic EGSH. (A) Calculating the EGSH of lysates prepared from idealized cells with a cytosolic EGSH of - 320 mV demonstrates that the contribution of GSSG from another cellular compartment with a more oxidized glutathione pool, even if that compartment occupies only a very small percentage of the total cell volume, results in a lysate EGSH that is considerably more oxidized than the cytosolic EGSH. (B) Calculating the EGSH of lysates prepared from idealized cells with variable cytosolic EGSH (from - 209 mV [GSH:GSSG = 10:1] to - 329 mV [GSH:GSSG = 100,000:1]) reveals that the contribution of GSSG from a compartment with a more oxidized glutathione pool produces a very similar lysate EGSH, irrespective of the initial cytosolic EGSH. These results clearly demonstrate that measurements of wholecell lysate EGSH and probe-based cytosol-specific measurements are fundamentally different. Measurement of one cannot be used to draw a conclusion regarding the state of the other.


aration, free from any postlysis oxidation artifacts. We then use the EGSH values of - 320 mV and - 210 mV determined for the cytosol and the ER, respectively, by the fluorescent sensors, to calculate the expected EGSH of the lysate as a function of the ER volume (expressed as a percentage of total cell volume). Even based on our conservatively chosen criteria, it is clear that even small ER volumes (*5%) are sufficient to significantly increase the expected lysate EGSH as compared with the cytosolic value. In fact, across the full range of realistic ER volumes, the calculated lysate EGSH values after cytosol and ER mixing are remarkably consistent with those widely reported in the literature. This demonstrates that EGSH values around - 230 mV measured in lysates and highly reducing cytosolic EGSH values around - 320 mV measured in vivo do not mutually contradict another but are consistent with the unavoidable mixing of glutathione pools of different subcellular compartments that occurs during cell lysis. As an alternative approach (Fig. 5B), we assumed a fixed ER volume (10% of the total cell volume), with an EGSH of - 210 mV and 10 mM total glutathione concentration and asked what the impact of mixing of this compartment with a 10 mM total cytosolic glutathione pool (90% of total cell volume) would be over a range of cytosolic EGSH values, from - 330 mV to - 208 mV (Fig. 5B). Interestingly, we found that the lysate EGSH is always between - 242 mV and - 208 mV, even for the most reducing cytosol values. This clearly demonstrates that irrespective of what the cytosolic EGSH actually is, it can be expected that a similar lysate EGSH will always be measured. Thus, it can be concluded that lysate EGSH offers no information on cytosolic EGSH and the very different values for cytosol and lysate EGSH are not incompatible. The calculations detailed earlier illustrate that the impact of mixing different subcellular glutathione pools is sufficient to account for the apparent discrepancy between EGSH measured in lysate and in the cytosol in vivo. However, the example of r.b.c., which have no significant subcellular structures, appears to contradict this argument: Conventionally measured EGSH in r.b.c. lysates is often even more oxidizing than lysates from other cell types (& –193 mV; 186). It was therefore even suggested that r.b.c. may deliver better estimates of cytosolic EGSH than cell types harboring organelles (111). Nonetheless, a roGFP2 probe expressed in r.b.c. still indicates a cytosolic EGSH & –320 mV, consistent with other cell types (245) and also consistent with the presence of glutathione reductase in r.b.c. (45). The apparent discrepancy may be explained by the particular sensitivity of GSH/GSSG extraction from r.b.c. to lysis-induced artifacts (120). Several of the measures routinely employed to prevent lysis-induced oxidation can actually increase GSSG production in the special case of r.b.c lysis. For example, acidification of samples causes acidinduced denaturation of oxyhemoglobin, leading to the production of O2 - and, subsequently, H2O2 (120). Optimized extraction procedures for r.b.c. yield lysates with an EGSH & –260 mV, thus containing only low lM GSSG (120). In our opinion, this remaining ‘‘extra’’ GSSG (as compared with that suggested by probe measurements) is most likely an unavoidable oxidation artifact of even the most careful r.b.c lysis procedure.



Highly reduced glutathione pools have been measured in a number of other subcellular compartments, including the MM (65, 104, 178, 196, 198), peroxisome (70, 198), plastid (177, 178, 198), IMS (114), and nucleus (177). For mitochondria, peroxisomes, and light-exposed chloroplasts, the apparent EGSH value is even more negative (up to - 380 mV) due to the assumption of a more alkaline pH for the calculation (decrease of EGSH by 59 mV per 1 unit increase in pH). Previously reported more oxidized redox potentials may be the result of limited equilibration between the sensor and glutathione pool, inappropriate in vivo probe calibration, or spectroscopic artifacts (104, 178). Cytosolic glutathione redox homeostasis is actively and robustly maintained

Considering that most organisms are exposed to an oxidizing environment, the maintenance of such a highly reduced glutathione pool (or the respective corresponding small thiol pool in prokaryotes) in the cytosol presumably requires robust mechanisms to ensure that the oxidized species (e.g., GSSG or MSSM) is efficiently eliminated, either chemically by re-reduction or by transport. Nonetheless, measurements of GSSG in whole cell lysates clearly show that whole cell GSSG levels can change considerably, for example after an oxidative challenge or genetic manipulation (154). It was typically assumed that much of this GSSG accumulates in the cytosol, at least transiently. Therefore, a clear discrepancy existed between whole cell measurements and recent probe-based measurements that indicate an extremely reduced and robustly regulated cytosolic glutathione pool. This discrepancy was recently resolved by a study in yeast (151). It was found that changes in whole cell GSSG levels are almost completely dependent on the activity of an ABC-C transporter, Ycf1 (the yeast homolog of the human multidrug transporter protein MRP1), which transports GSSG from the cytosol to the vacuole (Fig. 4). Thus, changes in whole cell GSSG content can be almost exclusively ascribed to changes in the amount of GSSG stored in the vacuole (which lacks GSSG reductive activity) and do not inform about the capacity of the cytosolic glutathione pool to resist perturbation (151). Interestingly, deletion of Ycf1 leads to a dramatic decrease in whole cell GSSG content. Furthermore, without Ycf1, whole cell GSSG levels are extremely resistant to genetic and chemical-induced perturbation. Therefore, deletion of Ycf1, by eliminating confounding GSSG-transport dependent changes, allows the use of whole cell GSSG measurements as an alternative to probe-based measurements, to assess the actual robustness of the cytosolic glutathione pool to oxidative challenge. In this scenario, it appears that the cytosolic glutathione pool is extremely robustly regulated and can easily reduce almost all the GSSG formed (when transport to the vacuole is prevented), even under conditions of severe oxidative challenge (150, 151), which is consistent with the probe-based observations. In summary, application of the Grx1-roGFP2 sensors facilitated the identification of a GSSG-transport activity and allowed us to develop our understanding of subcellular GSSG distribution. This enabled us to understand the true extent of the robustness inherent in cytosolic glutathione regulation,

693

which, in turn, further supports and validates the probebased measurements. The observation of highly reduced cytosolic glutathione pools in all organisms tested so far, together with the similarly reduced mycothiol pool in M. tuberculosis, indicates that the physiological redox potential is independent of the chemical identity of the small thiol molecule employed by an organism. Potentials around - 320 mV (or lower) are observed across the prokaryotic/eukaryotic divide and may be a common feature of all life. This could suggest that a highly reduced redox potential of the dominating cytosolic thiol pool was already present early in evolution. Potential reasons are intriguing yet speculative: (i) Maintaining a glutathione pool so far from its midpoint potential means that even very small changes in GSSG are translated into large changes in EGSH (143, 176). Perhaps this allows the glutathione pool to serve as a signaling platform, regulating protein oxidation and thus function in response to small changes in GSSG production, which may occur due to a diverse range of exogenous and endogenous changes (176). Indeed, mechanistically, the Grx1-roGFP2 probe depends on the fact that Grxs rapidly translate changes in EGSH into changes in roGFP2 oxidation. It will be interesting to examine whether changes in EGSH also elicit changes in the redox state of endogenous cellular proteins, including altered protein S-glutathionylation (146, 182). (ii) The first cells may have arisen in reducing environments, meaning that the early cellular machinery had evolved to operate under the ambient redox potential. This ambient redox potential may even have already been dominated by sulfur-containing inorganic compounds that may have driven evolution to the incorporation of reducing cysteine into proteins. After evolution of oxygenic photosynthesis and the required protection against ROS, evolving active maintenance of the intracellular redox potential may have been more easily achieved than adaptation of the entire cell machinery. As a result, the redox conditions of the primordial environment may have been ‘‘frozen’’ and conserved in the glutathione redox potential of modern cells. While also highly reduced, the glutathione pools of the MM and peroxisomes seem less resistant to perturbation of redox potential (70, 199). This may be due to a combination of reasons, including a lower capacity for GSSG reduction and export as compared with the cytosol. In addition, kinetic constraints in the uptake of newly synthesized, reduced glutathione may contribute to increased susceptibility in a situation where redox control is dominated by GSSG turnover and replacement by newly synthesized GSH. Another major difference may lie in the individual ability of each compartment to regenerate NADPH, which is the ultimate source of reducing equivalents for the different systems of EGSH maintenance, the relative contribution of which may vary between organisms, tissues, and cell types. Active control rather than passive equilibration of subcellular glutathione pools

In many organisms, the cytosol is the sole site of glutathione synthesis, although in plants both the cytosol and



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plastid share and coordinate this task. Nonetheless, in all organisms, glutathione is present in multiple subcellular compartments, which necessitates transport across membranes. However, the glutathione pools of most subcellular compartments appear largely isolated from each other. For example, by expressing GR solely in the MM or solely in the cytosol, stable glutathione redox gradients between the two locations can be established (97, 114, and [Marty, et al., unpublished data]). Furthermore, the recovery of different subcellular compartments from oxidation can follow very different kinetics (199). Both results indicate that the cytosolic and MM glutathione pools are regulated relatively independently of each other, exchange between the two pools is usually slow, and changes in glutathione redox potential can occur in a compartmentspecific manner (Fig. 4). The degree of linkage between the peroxisomal and the cytosolic glutathione pools remains unclear. In plant and yeast cells, the peroxisomal glutathione pool has been observed to be highly reduced, similar to the cytosol (70, 178, 198). Although that may seem surprising in an organelle of high H2O2 production, it emphasizes the clear separation between glutathione and H2O2 under physiological conditions, with kinetics, rather than thermodynamics, governing their interaction. Opt2, a homolog of the yeast plasma membrane glutathione transporter Opt1, was recently observed to be localized to the peroxisome and was suggested to transport either GSH or GSSG (70), although its mechanistic link with glutathione remains to be further dissected. RoGFP2-based probes targeted to the ER have supported the long-held conception that the glutathione pool in the ER is considerably more oxidized than in the cytosol (30, 142). However, given that no glutaredoxins are known to exist within the ER, it was unclear whether an unfused roGFP2 really reports EGSH in the ER. Steps toward addressing this issue were recently taken, with the expression of Grx1roGFP1-iE and iL probes in the ER (30). This study also clearly indicates a highly oxidized glutathione pool in the ER compared with the cytosol. Furthermore, evidence for a considerably higher glutathione concentration ( > 15 mM) in the ER than in the cytosol was reported by employing a combination of an ER-targeted Grx1-roGFP1-iE sensor for monitoring ER EGSH (i.e., [GSH]2:[GSSG]) and a sCGrx1p sensor of the GSH:GSSG ratio, suggesting that both EGSH and glutathione concentration are actively regulated at the subcellular compartment level (149). Heterogeneous distribution of glutathione concentration between various cell compartments has also been suggested based on immunological evidence (248, 249), but it remains to be followed up by in vivo sensing. While large differences in glutathione concentration as well as redox potential can arise across intracellular membranes, similar gradients are harder to rationalize for the nucleus, where there is currently no convincing evidence for the nuclear pores limiting the equilibration of cytosolic and nucleoplasmic glutathione pools by diffusion. The redox sensors themselves also diffuse efficiently between the cytosol and nucleus when expressed without nuclear exclusion or localization signals (NES/NLS), leading to equilibration of the readout even if there were EGSH differences. In accordance, no significant differences in EGSH between the cytosol and the nucleus were found in Arabidopsis root cells (191) and this also remained true under glutathione deficiency (4).

H2O2 levels and glutathione oxidation do not necessarily correlate

Recently, four transgenic Drosophila lines were generated, which express Grx1-roGFP2 or roGFP2-Orp1 probes in either the cytosol or the MM (2). This permitted the intriguing observation that both EGSH and H2O2 can vary in a subcellular compartment, cell- and tissue-specific manner. Furthermore, dependent on subcellular compartment and cell type, changes in H2O2 were observed to occur independently of changes in EGSH and vice versa. For example, high levels of H2O2 were observed in the MM of adult adipose tissue but this was not accompanied by an increase in EGSH relative to that observed in the mitochondria of other cell and tissues types. These observations indicate that changes in different parameters of cellular redox homeostasis, including EGSH and H2O2, are likely due to different biological changes, convey different biological information, and have different impacts on cellular physiology. These observations further reinforce the importance of considering different biological redox species separately and suggest that we are only just beginning to understand their relationship to cellular function. Membrane protein topology

As a technical innovation, roGFPs have been applied in the determination of membrane protein topology, especially those of the secretory pathway (35). This method is based on the fact that roGFP2 is almost fully reduced in the cytosol but almost fully oxidized in the ER (Fig. 4). Therefore, by genetically inserting roGFP2 into the polypeptide chain of interest at positions in putative extra-membrane loops, it is, in principle, possible to determine the topology of an entire multi-spanning membrane protein (35). Based on genetically engineered EGSH gradients across other membranes, for example, by knocking out GR activity in the cytosol but not in the peroxisome, this experimental approach can be flexibly adapted to proteins residing in other internal membranes. How Solid Is the Conclusion That Cytosolic EGSH & - 320 mV?

The previous section discussed the discovery of very low cytosolic EGSH. As already explained, this finding is not in contradiction with conventional whole-cell-lysate measurements and indeed makes sense in the light of many other observations. Nevertheless, questions have been raised occasionally to challenge the conclusion that cytosolic EGSH is indeed as low as reported by roGFP based measurements. In this section we further address these questions. Do the Grx1-roGFP-based probes specifically and accurately measure EGSH?

Although it is clear that whole cell measurements cannot and should not be used to make conclusions regarding the state of the cytosolic glutathione pool, this fact per se does not prove that the Grx1-roGFP-based measurements are accurate. How certain are we that the probes specifically and accurately report EGSH? Regarding the specificity of the probe, one important observation is that roGFPs are nonresponsive to the other major



thiol-reducing system, the thioredoxin system (thioredoxin/ thioredoxin reductase/NADPH). Even when genetically fused to roGFP2, thioredoxin is unable to drive any redox changes in roGFP2 either in vitro or in vivo (86). The mechanistic basis for the lack of reactivity between Trx and roGFP is likely due to steric hindrance preventing the roGFP2 and Trx thiols from aligning in the correct orientation to enable the disulfide exchange reaction (143). Another relevant observation comes from in vitro experiments, namely that the direct (uncatalyzed) reaction between roGFP2 and a number of tested small cellular redox compounds is either very slow or unmeasurable (including glutathione, cysteine, ascorbate, and NADPH). Thus in vivo, a reaction with such redox compounds is very unlikely to occur at a physiologically meaningful rate and is therefore very unlikely to contribute to establishing the probe redox state. Glutaredoxins (endogenous or genetically fused) selectively accelerate the reaction of an roGFP with GSSG/GSH, but not with other thiol and nonthiol compounds (86). Thus, an important means of testing the in vivo specificity of roGFPs would be the deletion of glutaredoxins from cells. If glutaredoxins are indeed the dominant kinetic drivers of roGFP reduction and oxidation in vivo, then their absence should alter the basal roGFP oxidation state and also prevent roGFP responses to glutathione oxidation. Indeed, an unfused roGFP2 probe expressed in the cytosol of yeast cells deleted for both dithiol glutaredoxins (yGrx1 and yGrx2) is about 50% oxidized at steady state and unresponsive to treatment with exogenous oxidants such as H2O2, which usually trigger a rapid probe oxidation followed by a recovery back to baseline (151). If instead the roGFP2-Grx1 fusion probe is expressed in the same cells (Dgrx1Dgrx2), the basal probe redox state and responsiveness is again identical to wild-type cells (151). Therefore, it is apparent that glutaredoxin catalysis is necessary and sufficient both for the extremely low (*5%) probe oxidation that is observed in the cytosol (corresponding to EGSH & - 320 mV) and for driving dynamic probe responses to redox perturbations. Further evidence for a specificity toward glutathione comes from applying the probe in glutathione reductasedeleted cells, where a higher steady-state probe oxidation is observed as well as a greater sensitivity to exogenous oxidant (151). Consistent observations have been made in plants. Absence of the cytosolic GR in Arabidopsis leads to a marked oxidation of cytosolic Grx1-roGFP2 sensor and strongly elevated responsiveness to H2O2 treatments (133). Arabidopsis mutants impaired in glutathione biosynthesis with decreased glutathione levels also show marked oxidation of the roGFP2 and Grx1-roGFP2 probes (4, 142). This demonstrates a dominating role of EGSH on the redox sensors that cannot be compensated for by any other redox system in vivo. In conclusion, all the existing evidence strongly supports the notion that the highly reduced state of roGFP2 in the cytosol is indeed caused by the exclusive or near-exclusive equilibration with the GSSG/2GSH redox couple, in a Grxdependent manner. Given the dependency on Grx, the wellstudied specificity of Grx for glutathione, and the observed influence of glutathione biosynthetic and reducing systems, it seems highly unlikely that an additional redox couple dom-

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inantly acting on roGFP2 is actually responsible for bringing about its highly reduced state. Is there any evidence for a highly reduced cytosolic glutathione pool that is independent of fluorescent protein redox sensing?

It was recently shown that the redox state of the disulfide bond in human SOD1 is predominantly determined by an interaction with endogenous glutaredoxins when human SOD1 is expressed in yeast cells lacking the SOD1 oxidizing factor Ccs1 (34). Therefore, as with rxYFP and roGFP probes, the redox state of the human SOD1 thiol pair is expected to equilibrate with EGSH. In fact, in Dccs1 cells, about 25% of human SOD1 contains a disulfide bond, which given the midpoint potential of the thiol pair (- 300 mV) implies a cytosolic EGSH value of - 320 mV. Thus, protein thiol-disulfide equilibration with GSH/GSSG generally indicates a very low EGSH. Is glutathione reductase capable of maintaining an EGSH of - 320 mV?

Another question is whether the maintenance of glutathione pools at such a low EGSH is achievable by the known GSSG reductive systems, principally GR in most organisms. There are two independent lines of evidence that support the conclusion that such low GSSG levels are indeed achievable through GR-mediated reduction. First, the glutathione reduction pathway can be reconstituted in an assay including NADPH, GR, and GSSG or GSH/GSSG mixtures as substrate. When using the Grx1-roGFP2 sensor (or Grx and roGFP2 separately) as a readout of the glutathione redox state in these assays, the probe indicates an EGSH of around the value of - 320 mV, equivalent to the cytosolic EGSH value (86, 142). This indicates that the GR system alone, in the absence of any other cellular redox system, is indeed capable of establishing a highly reduced EGSH value. In contrast, incubation of the sensor with low concentrations of GSSG, or with commercial GSH preparations, which unavoidably contain trace amounts of GSSG, in the absence of NADPH/GR, leads to rapid probe oxidation (3, 86). These observations fit theoretical expectations. The second-order rate constant for the reduction of GSSG by GR is in the range of *4.85 · 106 M - 1s - 1 (40). Thus, GSSG reduction should always proceed with high efficiency assuming that NADPH does not become limiting. Based solely on such theoretical considerations, as early as 1969, Hans Krebs’ group calculated that cytosolic GSSG should be present only in very low nanomolar amounts (225), in agreement with what is now measured. A major point of persistent confusion is that the Km value of glutathione reductase, which is typically reported to be between 50 and 100 lM, dependent on the species, might appear too high for GR to reduce GSSG down to nanomolar levels. However, it is important here to clarify that Km values for GR are usually determined using high fixed NADPH concentrations, which are orders of magnitude higher than free NADPH levels estimated in vivo (*100 lM vs. *2 lM; 41). Given that GR operates with ping-pong kinetics, decreasing the concentration of one substrate will decrease the


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apparent Km for the second substrate. A reassessment of the Km for pea glutathione reductase revealed an apparent Km for GSSG of 1 lM (61, 130). Such a Km is compatible with reducing GSSG concentrations down to nanomolar levels, and consistent with the in vitro assays of GR-mediated glutathione reduction.


Is there really a simple thermodynamic equilibration between roGFP and GSSG/2GSH in vivo?

One remaining issue is the question whether the straightforward thermodynamic equilibration between the roGFP and glutathione redox couples indeed applies to the in vivo situation. Perhaps the best evidence in support of a simple thermodynamic equilibration in vivo is from the use of roGFPs with very different standard midpoint potentials, for example, roGFP2 ( - 280 mV) and roGFP1-iL ( - 230 mV) or roGFP2-iL ( - 238 mV). When both a Grx1-roGFP2 and Grx1-roGFP1-iL probe were used to monitor the response of the cytosolic glutathione pool in Dglr1 yeast cells to a bolus of H2O2, both probes showed very different OxD values over the whole time course of the assay. Nonetheless, when EGSH was calculated based on the known standard midpoint potentials of the different roGFP variants and the degree of probe oxidation, it was found that both reported almost identical EGSH (151). The same was observed for the combination of Grx1-(4). Both examples provide strong evidence for the existence of a Nernst-equilibrium between sensor and glutathione in vivo.

the ratiometric principle. In other words, the same cytosolic EGSH is reported over the whole range of achievable probe expression levels (from very dim to extremely bright). This observation does not seem to be compatible with the idea of probe expression causing EGSH perturbations. In summary, low cytosolic EGSH values are fully compatible with conventional whole-cell EGSH measurements, supported by probe-independent observations, and can be explained by GR activity alone on both empirical and theoretical grounds. Furthermore, all previous observations strongly indicate, to our knowledge without exception, that in vivo probe measurements follow the same basic principles established in vitro, are highly specific to glutathione, and do not alter endogenous EGSH. We find it surprising that it is sometimes assumed that whole-cell EGSH is a good estimate of cytosolic EGSH (111). We cannot see any scientific reasons for doing so. Limits of In Vivo Redox Sensing

A large range of biological questions has been addressed using the redox sensors, resulting in fundamental advances in our understanding of redox biology. However, there are clear conceptual and technical limits as to what currently available sensors can tell us. Considering those limitations is critical if we are to avoid misinterpretation and misunderstanding and draw solid and meaningful biological insights from sensor data. Here, we will exemplify several areas where sensors currently reach their limits:

Does the probe itself influence EGSH?

It may be asked whether the Grx1 moiety of the roGFP2Grx1 probe would potentially influence intracellular EGSH, thus generating the very low EGSH that the probe is reporting. Indeed, Grxs have been suggested to play a role in GSSG reduction by drawing electrons from other sources, for example the thioredoxin system (105, 151, 215). Nonetheless, both unfused roGFP2 (which equilibrates with the glutathione pool in the cytosol via the action of endogenous glutaredoxins) and Grx1-roGFP2 report the same steady-state EGSH value (133, 142, 198). Thus, the addition of extra glutaredoxin activity, at least in the context of the cytosol where Grx is not limiting, makes no apparent difference to the EGSH reported by roGFP2. Importantly, there is one observation that more generally speaks against the idea that any of the discussed probes (fused or unfused) is altering endogenous EGSH. In many probe transfection experiments, in particular when using transient transfection, cell populations with a wide distribution of probe expression levels are created. While in some cells probe expression is barely detectable, other cells strongly overexpress, and the whole range of intermediate expression levels between these extremes is represented as well. Analysis of the fluorescence intensities (405 and 488 nm excitation) from such (otherwise homogenous) cell populations, either pixel-by-pixel from confocal images or from single-cell flow cytometry readings, reveals that the 405/ 488 nm ratio (i.e., the measured probe redox state) is indeed independent of the expression level of the probe inside cells. Thus, scatter plots of paired fluorescence intensities (I405 vs. I488) reveal straight lines (12, 25), matching quantitative theoretical considerations (18) and confirming

Measuring out of range

Every probe has a specific measuring range, and the EGSH sensors are no exception. While oxidation of the glutathione pool in plasmatic compartments, even by only a few mV, can be measured with high confidence using roGFP1- or roGFP2-based sensors, the same does not apply for reductive shifts. Even roGFP1, which has the most negative reported standard midpoint potential ( - 291 mV; 143) of the current actively used in vivo sensors, is strongly reduced in most plasmatic compartments, especially the cytosol (*90%) (196, 198) (Fig. 6). This means that shifts of EGSH toward a more reduced state are not reliably detectable. This is even more applicable to roGFP2-based glutathione measurements, where the less negative standard midpoint potential ( - 280 mV) causes an even earlier cut-off. Hence, caution must be taken when interpreting shifts in fluorescent ratio, indicating further reduction, for example, in the chloroplast stroma or the MM (166, 177). An exception from this rule are situations in which steady-state plasmatic EGSH is shifted toward more oxidizing potentials and into the measurement range of the sensor [e.g., in mutants of glutathione biosynthesis or glutathione reduction (4, 151)]. At the other end of the scale, the same applies for oxidative shifts in extra-plasmatic compartments, such as the ER, where the currently available sensors (roGFP1-iE, roGFP1iL, roGFP2-iL) are almost fully oxidized. While reductive shifts can be measured with high sensitivity, only a limited range is available for further oxidation. Critical interpretation of data while considering the technical sensor properties in relation to the biology is therefore required for each measurement.



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FIG. 6. Measuring ranges of the different redox sensors that have been used in vivo. Reported standard midpoint potentials of the sensors as determined by redox titration are given next to each sensor name; consensus midpoint potentials are shown for roGFP1 and 2 for which different values have been determined (4, 42, 65, 66, 91, 125, 143, 160). roGFP3 and 4 are shown in gray, since, like several other roGFP1-iX (125) and roGFP1-RX variants (42) that are not shown, they have not been used in vivo. Reliable measurement ranges (i.e., between 10% and 90% of sensor oxidation) cover about – 30 mV from the standard midpoint potential and are plotted in relation to the in vivo EGSH values in the ER and the cytosol as estimated experimentally using the sensors (30, 91, 142). To see this illustration in color, the reader is referred to the web version of this article at www.liebertpub.com/ars Measuring ‘‘cellular redox state’’ and ‘‘ROS’’

Specificities when endogenous Grx activity is limiting

One of the major strengths of the roGFP and rxYFP sensors is their well-documented specificity toward the glutathione pool. Furthermore, the reaction mechanism is reasonably well understood. Considering this, it is surprising therefore that the free (unfused to any redox enzyme) roGFP1, roGFP2, and rxYFP sensors have been widely described and interpreted as indicators of ‘‘cellular redox state’’ or ‘‘ROS.’’ At face value, such an interpretation can be misleading and should—in our view—be avoided. Measurement of a general ‘‘cellular redox state’’ relies on the assumption that a general cellular redox state actually exists. This is not supported by experimental data or theoretical considerations. On the contrary, kinetic control of individual redox couples appears to be the dominating principle of redox regulation. That still leaves open the theoretical possibility that the sensor thiols react with several different redox couples. While in the complex intracellular environment this cannot be completely ruled out, all available in vitro and in vivo evidence points to clear sensor specificity for the Grx/glutathione system. No evidence for equilibration with any other major cellular redox systems, including the Trx systems, or the NAD and NADP pools, has been found so far. Even if multiple redox couples were to interact with the sensor thiols, kinetic control of the reaction means that the couple that is most efficient in interaction will dominate the measurement. Sensing of ‘‘ROS,’’ most importantly H2O2, by the free roGFPs is unlikely, given the very low reactivity of the sensor thiols as compared with competing endogenous thiols of specialized H2O2-detoxifying enzymes (e.g., from peroxidases). In the case of the roGFP2-Orp1 sensor, the efficient reactivity of the Orp1 peroxidatic cysteine thiol with H2O2 was exploited to drive a roGFP response: Without the presence of Orp1 to provide catalysis and specificity, no relevant impact of H2O2 (as compared with the equilibration with the glutathione pool) can be expected in vivo.

The equilibration of roGFPs with the glutathione redox pair is strictly dependent upon the presence of suitable Grxs. This raises the question of what is measured by a roGFP (unfused to any redox enzyme) when expressed in a compartment that lacks endogenous Grxs or in which Grx activity is limiting. Examples of such compartments include the peroxisome (for which no Grx activity has been reported in yeast) or the IMS, which was recently demonstrated to have highly limited Grx activity (115). When an unfused roGFP2 or rxYFP was expressed in the peroxisome (11) and IMS (97) respectively, they were observed to be much more oxidized compared to the cytosol. In contrast, other studies employing Grx1-roGFP2 probes found the glutathione redox state in these compartments to be comparable to the cytosol (70, 114). The most likely explanation for these differences is that the unfused probes no longer equilibrate with the glutathione redox couple when no Grx is available. This interpretation is supported by the fact that an unfused roGFP2 expressed in the cytosol of yeast cells deleted for both endogenous dithiol yGrxs (Dgrx1Dgrx2) reports a redox potential similar to that reported by the unfused sensors in the peroxisome and IMS. Furthermore, in the Dgrx1Dgrx2 background an unfused cytosolic roGFP2 is poorly responsive to exogenously applied H2O2—which usually leads to a transient deflection of EGSH—consistent with the conclusion that the probe does not efficiently equilibrate with the glutathione redox couple. It is unknown what redox couple drives roGFP/rxYFP oxidation in the absence of Grxs. Presumably in the absence of any Grx activity the unfused roGFPs and rxYFP will equilibrate with whatever redox couple is most kinetically favored: this cannot automatically be assumed to be the glutathione redox couple and may vary from compartment to compartment. In any case, the equilibration with these other redox pairs is very slow compared to Grx-catalyzed equilibration with the glutathione redox couple and is extremely unlikely to influence the probe redox state when Grxs are available (151).

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Potential side effects of expressing additional redox activities

Ambiguity arising from potentially limiting endogenous Grx capacity can be overcome by using an hGrx1-fusion probe. Then, the possibility needs to be considered that the introduction of an hGrx1-containing sensor, particularly into a compartment in which endogenous Grx activity is limiting, may artificially perturb the system to be measured. Interference may arise by different mechanisms. First, Grxs were suggested to have a role in GSSG reduction (151). It is plausible that in compartments with absent or limiting endogenous Grx activity the glutathione redox potential is genuinely more oxidized, and that introduction of an hGrx1-containing sensor artificially reduces the glutathione pool. Although we consider this scenario unlikely, it cannot be definitely ruled out and at present it is unclear how this could be tested, as some Grx activity is essential to ensure probe equilibration with the glutathione pool. Along these lines, it is worth mentioning that whole-cell GSSG levels were found to be indistinguishable between yeast cells expressing roGFP2 alone and those expressing Grx1-roGFP2, although in the absence of endogenous glutaredoxins small differences in GSSG levels were observed between roGFP2and Grx1-roGFP2-expressing cells (151). This suggests that the Grx1-roGFP2 probe may be able to compensate for the lack of endogenous Grxs, but that the extra Grx activity introduced by the Grx1-roGFP2 probe has no effect on GSSG levels when endogenous Grxs are present. Second, the introduction of an hGrx1-containing sensor may change the oxidation state of endogenous proteins in that compartment (Fig. 7). For example, it was recently shown that the level of yGrx2 in the IMS impacts upon the redox state of the redox-active thiol pair in Mia40, presumably by controlling the rate of equilibration with the glutathione pool (115). This should not come as a surprise given the impact of Grx availability on the sensor redox state in this compartment. It is unclear what other proteins may be affected by introducing additional Grx activity and what the impact of these changes may be. In principle, H2O2 sensors, such as Orp1 fusions with roGFP1 or 2, may also interfere with physiology, as they introduce additional peroxidase activity. However, the relative rate constant for H2O2 metabolism by Orp1 is slower than that of many endogenous H2O2 scavengers, including most typical 2-cys peroxiredoxins and glutathione peroxidases. Nonetheless, Orp1 is able to support H2O2 turnover and drain electrons from the endogenous Trx and/or glutathione/Grx


systems. It is conceivable, although not likely, that endogenous H2O2 dynamics are altered and the dynamics of thiol redox systems may be modified by Orp1-based sensor expression. The degree to which this may occur in vivo depends on the individual biological context and includes H2O2 production rates, endogenous peroxidase activities, including their active concentration ranges and electron flux rates through the thiol redox machinery. In simple biological systems, such as yeast, the impact of the sensor may be quantitatively validated and H2O2 turnover can be assessed after genetic removal of all endogenous peroxidase activities (which, however, will then itself modify the status of the thiol redox systems). In most cases, the effects of the sensor are probably minor as compared with the endogenous mechanisms. Nonetheless, interference should be considered, especially if an obvious phenotype occurs. Measurement of ‘‘mixed’’ potentials

Since roGFPs and rxYFPs equilibrate efficiently with the glutathione pool in the presence of endogenous Grxs, without any further information it should be assumed that they are unlikely to stop doing so after fusion with a specificity factor for a redox couple other than glutathione, such as Orp1. Orp1fusion sensors are able to interact with at least three in vivo redox systems, including H2O2 and two reducing systems, the Trx system, and the Grx/glutathione system. The relative contribution of each system to the sensor redox state will depend on the specific redox potentials and interaction kinetics of the biological milieu in which the sensor is expressed (Fig. 8). Interaction with the reducing systems comes with the benefit of efficient re-reduction of the sensor after oxidation by H2O2, thereby allowing dynamic measurements. Specific measurements of H2O2 dynamics are possible under the assumption that the rate of interaction with the other systems does not change during the measurement. This possibility should be considered and potentially be controlled for. The same applies for the H2O2 sensors of the HyPer family (21, 28, 131), but alternative interpretations of measurements (e.g., changes in the rate of reduction by the endogenous Grx system) are rarely discussed. Biological and Technical Considerations

When using the sensors, there are a number of biological and technical considerations to be aware of that are rarely

FIG. 7. Potential interference with redox physiology by expression of redox sensors. (A) Redox equilibration mechanism of Grx1-roGFP2 between the glutathione pool and roGFP2, and (B) a potential mechanism of interference with the redox state of endogenous thiol proteins through the Grx activity introduced with the sensor. This may be particularly relevant when endogenous Grx activity is limiting. Endo protein: endogenous thiol protein. To see this illustration in color, the reader is referred to the web version of this article at www.liebertpub.com/ars



Clarifying the issue of probe pH sensitivity

A number of different (mis-)interpretations regarding the pH sensitivity of thiol redox sensors are to be found in the published literature. The probes, including roGFP1, roGFP2, roGFP1-iE, roGFP1-iL, roGFP2-iL, and their fusions and rxYFP, show a significant response to pH when assessed at a single wavelength, with quantum yield increasing with rising pH. Potential pH effects need to be carefully controlled for if rxYFP is to be used for in vivo redox measurements based on single-wavelength fluorescence excitation (160, 161). Readout of rxYFP redox state by gel-shift assays, as usually employed so far instead of

fluorescence measurements, circumvents this issue (55, 161). When using roGFP1, roGFP2, roGFP1-iE, roGFP1iL, roGFP2-iL, and their fusions in a ratiometric manner, pH sensitivity is negligible across the physiological pH range (2, 4, 86, 125, 198, 243). This is due to the fact that the pH-dependent intensity change occurs in a proportional manner for both wavelengths and is therefore normalized out. In the initial report on the roGFPs, roGFP2 was described as pH-sensitive and roGFP1 as pH inert (91). This appears to have caused confusion and in several studies it is reasoned that roGFP1 has been chosen over roGFP2 due to pH considerations (e.g., 241, 243). However, the fluorescence excitation ratio of both the reduced and oxidized roGFP2 is insensitive to pH changes between 5.5 and 8.5 (86, 198). Indeed, insensitivity of all roGFPs to pH is a critical advantage of roGFP-based sensors and can be the decisive criterion to choose a roGFP-Orp1 fusion sensor for H2O2 measurements compared with a sensor of the HyPer family where pH sensitivity, also for the ratiometric readout, is dramatic and needs strict control to avoid artifacts (200, 237). The importance of precisely specifying sensor variants

Although their sensing principle is the same, different sensor variants, such as roGFP1 and roGFP2, have fundamentally different physico-chemical properties, including their midpoint potential that determines what a measured change actually means in terms of redox potential shift. That makes information about the employed sensor variant essential for data interpretation. Nevertheless, in many cases, simply the use of ‘‘roGFP’’ is reported or ambiguous references on the used roGFP variant are provided (Table 1, referred to as roGFPx), which at first glance is merely a semantic or formal inaccuracy but can

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specifically mentioned. Here, we discuss selected examples of practical importance.

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FIG. 8. Sensing ‘‘mixed’’ inputs exemplified for the roGFP2-Orp1 sensor. (A) roGFP-Orp1-fusion sensors are able to interact with three in vivo redox systems, H2O2, the Trx system, and the Grx/glutathione system. The relative contribution of oxidant and reductive pressures setting sensor redox state depends on the specific redox potentials and interaction kinetics of the local biological sensor milieu in vivo, as illustrated in a simplified hydraulic model (B). The balance of electron flux into and out of the sensor pool sets the sensor redox state and its readout in turn. A given readout can be achieved in several different ways, determined by the specific local redox environment. Sensor oxidation can occur by an increase in H2O2 concentration (C) increasing ‘‘electron pull’’ (indicated by a red arrow), while re-reduction from the Trx and Grx systems is kinetically limited (indicated by a ‘‘bottleneck’’ between the columns) despite sufficient thermodynamic ‘‘electron push’’ (indicated by a blue arrow). In an alternative scenario (D), sensor oxidation can be caused by less reducing regeneration systems decreasing ‘‘electron push’’ under unchanged H2O2 concentrations. It should be noted that Grx and Trx systems can interact with the sensor independently by distinct mechanisms on distinct sites and their relative contributions vary depending on organism, tissue, and cell type. This is not considered in this simple model. To see this illustration in color, the reader is referred to the web version of this article at www.liebertpub.com/ars

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introduce unnecessary ambiguity and complicate reproducibility of the data.


Commercial kits for genetically encoded probe expression

Recently, ‘‘kits’’ that use roGFP1-based redox sensors have become commercially available (e.g., Premo Cellular Redox Sensor, Grx-1-roGFP, and Premo Cellular hydrogen peroxide (H2O2) Sensor, Orp1-roGFP; Life Technologies). Those kits mainly justify themselves by the combination with a standardized transfection protocol for mammalian cells. However, an overly reductionist manual that does not inform about the limits of applying the sensors nor the processing and interpretion of data may foster the illusion of a simple ‘‘instant’’ method. This comes with the high risk that ‘‘ROS’’ or ‘‘redox’’ measurements will be performed with questionable reflection and mechanistic rigor. It should also be mentioned that while the probe provided with the kit is roGFP1-Orp1 (a bona fide H2O2 sensor), it is marketed as Orp1-roGFP1. The importance of this is that in our hands, Orp1-roGFP1/2, with Orp1 located at the N-terminus, is nonfunctional as an H2O2 sensor. This highlights the need to be clear on the actual domain order of the probe used, particularly if novel probe variants are being employed. Phenotypes related to probe expression

No systematic information exists about sensor expressionrelated phenotypes. In most cases, stably transformed yeast and plant lines do not show any obvious developmental phenotypes. Nonetheless, expressing very high levels of roGFP in yeast MM, irrespective of whether it is fused to a redox catalyst or not, leads to a slow growth phenotype. Likewise, we have observed a range of phenotypes when expressing the sensors in plant mitochondria. This range goes from a wild type-like appearance to heavily stunted plants with curly, early senescing leaves and also appears to correlate with expression strength of the sensor. The occurrence of the phenotype is independent of roGFP variant or sensor fusion and has not been observed on expression in any compartment other than the mitochondria. While no such effect has been observed for native GFP, very similar phenotypes can arise from the expression of fluorescent protein sensors that detect parameters other than thiol redox potentials too. This makes it hard to interpret the observed phenotypic changes mechanistically and suggests that, in principle, interference with physiology can occur and may need accounting for. It is usually possible, however, to screen for lines with wild type-like phenotype to avoid obvious pleiotropic effects. Problems associated with probe silencing

Sensor silencing in certain cells, tissue areas, or indeed whole individual organisms has been apparent by a lack of fluorescence signal in several different systems. In particular, this applies to stable lines, where time allows progression of silencing. The reason for this has not been specifically addressed, but it is likely to involve the general gene silencing mechanisms. It is also assumed that similar silencing effects may arise in many overexpression approaches. In the case of the sensors, imaging can resolve their spatial expression


pattern (certain tissue areas are silenced, while others still overexpress), although the effect may go unnoticed by methods such as immunoblotting that ‘‘average’’ over cells and tissues. In stable sensor lines of the model plant Arabidopsis, silencing has been observed to increase over generations, leading to a patchy appearance of fluorescent tissue areas expressing the sensor. Use of different promoters has not been found to overcome the issue. Instead, using the expressing areas of partially silenced specimens or going back to earlier generations of the line often allows the desired measurements to be performed. Background signal, auto-fluorescence, and other spectroscopic issues in vivo

For reliable quantitative measurements, a high signal-tonoise ratio is critical. Hence, the fluorescent sensor signal needs to be high as compared with background and structured auto-fluorescence. While for most biological systems this is the case for the longer excitation wavelengths (typically 488 nm), cellular constituents (such as NAD(P)H or phenolic compounds) often interfere with the shorter wavelength (typically 405 nm), which can skew measurements and limit the spectroscopic range of the sensor. Therefore, the contribution of background and auto-fluorescence to the measured signal needs to be assessed and, if necessary, suitable corrections need to be applied (76, 121). In case of novel and surprising observations, particular attention should be focussed on assessment of the data for spectroscopic artifacts. For instance, a report of ‘‘patches’’ that appear to differ strongly in EGSH from other cytosolic areas of the same cell (134) appears to contradict general biophysical constraints of diffusion, and imaging artifacts may provide a more parsimonious explanation. In general, signal-to-noise ratios increase with probe expression levels; hence, bright fluorescence can improve the technical quality of the data, while dim in vivo signals require particular caution. Moreover, the quantum yield (‘‘brightness’’) of different sensors at the specific wavelengths in question is a decisive factor. For example, while roGFP2 has a higher quantum yield than roGFP1 at excitation in most parts of the spectrum, roGFP1 shows a higher yield at low wavelengths (around 405 nm), that is, in the range where auto-fluorescence preferentially occurs and a high signal-tonoise ratio particularly matters. Recently, fluorescence lifetime imaging (FLIM) has been used for roGFP2 and roGFP1iE as an attractive alternative to the ratiometric analysis and has the potential to circumvent issues of low quantum yield (10, 238). In contrast to roGFP2, roGFP1 is sensitive to photo-conversion on exposure to high intensity and/or extended excitation, resulting in ratio levels that suggest a reduced state (198). While this requires attention and optimization for the individual measurement setup, suitable controls and excitation regimes can avoid artifacts. An issue that is less well understood is the observation that the experimental spectroscopic dynamic range of roGFP2-based sensors can be much smaller in vivo as compared with in vitro and also differs between studies, biological systems, and subcellular compartments. While the ratio range between the fully oxidized and the fully reduced situation gets close to the in vitro value (*10 for the 405/488 nm ratio) in many reports, it is often smaller, for example, in the MM (e.g., 65, 198). Potential explanations may include systematic errors


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from the in vivo signal-to-noise ratio. Compartment-specific over-oxidation of a fraction of the sensor population may provide an alternative explanation. Although the effect has been observed across the published work employing roGFP2, its cause has not been systematically assessed. Artifacts may be minimized not only by careful selection of the biological material, sensor expression levels, and correction routines but also by the well thought-out sensor selection and imaging technique. New Sensors for New Answers

Development of several key sensor features may further boost the power of redox sensing and the promise of new biological insights (Fig. 9). Probes with new midpoint potentials

The midpoint potential of the cysteine pair of the sensor determines the range of redox potentials in which quantitative measurements are possible. To allow for truly dynamic measurements, the sensor must be able to respond in either direction, that is, starting from its steady state it must be able to become both more oxidized and more reduced. This requirement is best fulfilled if the midpoint potential of the sensor and the steady-state redox potential of the redox couple of interest are similar, implying that sensors with midpoint potentials of * - 320 mV and * - 210 mV (30) would be best suited for the glutathione pools in the cytosol and the ER, respectively (Fig. 9A). Neither midpoint potential is currently available (Fig. 6). RoGFP1 and roGFP2 are almost fully reduced in the cytosol, which makes it extremely difficult to confidently and quantitatively resolve reductive shifts in redox potential. For instance, transient ‘‘overreduction’’ of the glutathione pool, and the transcriptional co-regulator NPR1 in turn, is believed to regulate pathogen responses in plants (153). It would be desirable to determine the redox dynamics of this event that is only vaguely understood at cell level. If we are to explore such reductive changes in plasmatic glutathione pools, sensors with more negative standard midpoint potentials will be necessary. One possibility may be to develop the roGFP3 sensor, which was originally generated alongside roGFP 1 and 2 but has not been further developed for in vivo use ever since. Its standard midpoint potential was reported to be more negative than that of roGFP1 by *10 mV ( - 299 mV; 91). To generate novel sensor variants with modified standard midpoint potential, rational engineering strategies have been used (4, 42, 125), but the quantitative impact of targeted mutagenesis on midpoint potential is still largely unpredictable. Hence, strategies combining rational protein engineering with medium throughput screening will be required to adjust midpoints potentials while maintaining other characteristics such as spectroscopic dynamic range and lack of pH sensitivity. With a collection of sensors covering the entire physiological thiol redox range, it will be possible to select the most suitable sensor to match the biological question. Probes with new colors

In vivo redox sensing has so far mostly been performed by expressing a single redox sensor in one compartment at a time. However, this strategy can be limiting, as it does not

FIG. 9. Future perspectives for engineering new redox sensors. (A) Midpoint potentials of sensors to match in vivo conditions, allowing dynamic measurements with oxidative and reductive shifts; (B) sensor color to allow simultaneous readout of several sensors in different subcellular locations or for different redox couples; (C) specificity for additional biologically important redox couples through fusion with novel specificity factors; and (D) the sensing principle by generating ‘‘unreactive’’ sensors, to measure the concentration of redox species through a mechanism of reversible binding of (rather than reaction with) the redox compound to be sensed. To see this illustration in color, the reader is referred to the web version of this article at www.liebertpub .com/ars


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allow the simultaneous measurement of the same redox couple in more than one compartment, or of different redox couples and/or other physiological parameters, such as pH, calcium, or ATP levels. Side-by-side measurements in the same sample will be necessary if we are to dissect the interconnectivity and dynamics between different subcellular redox pools as well as the crosstalk between different redox species and other physico-chemical equilibria. For example, in the case of a measured oxidation of the glutathione pool in the MM, it may be of interest to determine whether there are simultaneous cytosolic changes, for example, to ascertain whether the oxidation is compartment specific or, more generally, affects the whole cell. In such a case, measurements cannot currently be performed in the same sample, because the sensor readouts cannot be quantitatively separated (although some degree of qualitative separation may be possible by resolving separate subcellular compartments spatially by microscopy; [Marty, et al., unpublished data]). Instead, measurements in different subcellular compartments or of different redox species have typically been made using different probes expressed in separate samples, which are treated under identical conditions, for example (2, 199). In a few cases, ‘‘multiplexing’’ of different sensor signals in a single sample has been performed with redox sensors, by relying on separate monitoring of another sensor based on its different color, (37, 185). RxYFP and roGFP thiol redox sensors rely on excitation in the blue/green area of the spectrum to fluoresce in green/yellow. This leaves a wide range of the visible spectrum unexploited, which can only be used if probes are developed that fluoresce in these colors. Since most probes (e.g., for calcium, pH, ATP, or NADH) are based on green or yellow fluorescent proteins, it is not possible to make simultaneous measurements in different subcellular compartments or of different cellular parameters. A first generation of sensors with distinct spectral properties has recently been engineered for specific parameters such as calcium, pH, and H2O2 (71, 204, 217, 252) and also first examples of blue and red fluorescent redox sensors have become available (73, 213). Increasing the color range of redox probes would cater for the required flexibility to select sensor combinations for multiplexing (Fig. 9B). Red fluorescent redox sensors appear particularly suitable to be combined with existing green and yellow variants and may be generated by using analogous strategies to those used to develop the rxYFP- and roGFP-based probes.


catalyze the relay between substrate redox status and the fluorescent protein thiols. As an example, a GR or an NADPH-dependent thioredoxin reductase catalyzing the transfer of electrons between NADPH and thiols may be considered a candidate for building an NADPH/NADP redox sensor. For an ascorbate sensor, monodehydroascorbate reductase (MDHAR; catalyzing the transfer of electrons between thiols and ascorbate) may be suitable. In either case, it is critical to use a sensor variant with a midpoint potential that matches the expected potential of the new parameter (i.e., highly reducing for a NADPH/NADP sensor and more oxidizing for an ascorbate sensor). Whether or not a functional redox relay can be established and proceed with high efficiency depends to a large degree on steric considerations as well as on the kinetics of the interaction, particularly in comparison to the kinetics of potential competing (unspecific) reactions. Although engineering new specificities will necessitate much empirical testing and optimization, such novel sensors hold the potential to make completely new areas of biology accessible. Alternatively, the fusion of as-yet uncharacterized redox proteins to roGFPs might allow for their in vivo specificities to be dissected. This will be important, as most knowledge on key redox proteins, if available at all, relies heavily on in vitro characterization. In vivo, multiple redox pathways compete, giving rise to kinetic (rather than thermodynamic) control, and effective specificities can deviate strongly from those derived from reductionist in vitro systems. For instance, the biological roles of the different Grxs are not clear and are likely to cover diverse functions and specificities within a cell. An example is yGrx8; when fused to roGFP2 (roGFP2yGrx8), the sensor is almost fully oxidized in vivo in cells deleted for endogenous Grxs (which dominate over the genetically fused yGrx8 and mediate equilibration of the roGFP2 with the glutathione pool; Morgan et al., unpublished data). In contrast in the same background, roGFP2 fused to yGrx1 or yGrx2 is almost fully reduced, indicating equilibration with the glutathione pool (151). Clearly, yGrx8 is interacting with one or more alternative redox systems. A redox couple of less negative potential is a likely in vivo interactor that can be systematically addressed either using in vitro reconstitution of candidate redox systems (e.g., 142) or in vivo using yeast strains with appropriate genetic manipulations to selectively disrupt different redox components. These approaches may deliver valuable new insights into yet unknown physiological redox interactions.

Probes with new specificities

While H2O2 and glutathione redox dynamics can now be monitored in vivo, similar measurements are currently not possible for other central redox couples, including NADPH/ NADP, ascorbate, Trx-systems, other ROS/RNS, or speciesspecific glutathione substitutes such as the low-molecularweight thiols, that is, bacillithiol in Bacillus or trypoanothione in trypanosomes. Nonetheless, it is likely possible that thiolbased redox sensors can be engineered to become a specific sensor for many of these redox species by genetic fusion to appropriate redox enzymes (Fig. 9C). To build such a new sensor, a functional thiol relay between the redox-sensitive protein and the specificity domain has to be established and carefully validated. As a specificity domain, a natural protein or a functional part thereof needs to be selected that can

Probe based on new sensing principles

The thiol redox sensors that currently exist interact with their analyte by a redox reaction. This sensing principle will inevitably add artificial redox activity into the cell with the potential to interfere with the system. Even expression of the free sensor, without fusion to any redox enzyme, increases the electron ‘‘storage’’ capacity of the glutathione pool by a very small degree via the equilibration through endogenous Grxs (sensor expression is in the lM range, while glutathione pool size is in the low mM range). The overall impact can usually be assumed to be small, given the small ratio between added and endogenous redox activity, but ultimately depends on the rate of electron flux through the sensor system, as compared with the endogenous systems. Residual interference



with redox physiology cannot be completely ruled out. A related limitation is that the current redox-sensing principle can measure redox potentials, but not absolute pool size. An oxidation of the glutathione pool may be due a decrease of the GSH:GSSG ratio or result from depletion of the pool. The sensor cannot distinguish between these two options. Similarly, H2O2 measurements by a peroxidase-fusion sensor integrate the rate of sensor oxidation by H2O2 versus reduction by endogenous thiol systems. The resulting readout represents the steady state between both rates, while it is impossible to calculate the steady-state concentration of H2O2 in vivo. These limits may be addressed by applying ‘‘unreactive’’ sensors to redox biology. Those sensors reversibly bind their substrate without undergoing any redox reaction, analogous to the sensing principle of existing calcium and co-factor sensors. To design an unreactive GSH sensor, a GSH-specific binding domain that does not bind GSSG will need to be selected or generated by mutagenesis. This domain needs to undergo a conformational change on binding, but it does not catalyze any reaction of GSH with another redox couple. The conformational change could then be exploited in a circularly permuted fluorescent protein, analogous to Pericam or Perceval sensors (23, 156, 218) or a FRET-based approach, analogous to Cameleon or ATeam sensors (101, 147). Reversible binding is conceivable for molecules such as GSH or GSSG, but it may be also feasible for more reactive yet selective molecules such as H2O2 (Fig. 9D). Such a sensor concept would make a valuable addition to the existing ‘‘reactive’’ redox-sensing strategy. Potential interference with endogenous redox systems by introducing ‘‘bypasses’’ or ‘‘sinks’’ for electrons would be minimized, while the absolute pool size of redoxactive compounds, including GSH, GSSG, and perhaps even H2O2, could be quantified in vivo. The field of redox biology has been re-invigorated by the new in vivo sensing possibilities. This exciting development is far from having reached maturity, and there are critical hurdles that remain to be overcome. Rapid progress can be expected for the next decade, based on the dedicated yet careful exploitation of the sensing possibilities that are already available to address some of the most pressing open questions of redox biology. In parallel, the integration of the sensing approaches in high-throughput screening and routine testing platforms appears to be a logical next step, holding promise to advance related fields, such as biotechnology or pharmacology. Additional momentum is likely to come from novel sensors and sensing approaches, tailored to explore new biological ground. Much rigor will be required, but the promise of bridging redox chemistry, physiology, and cell biology in vivo should justify those efforts and open the door to an integrated understanding and biomedical targeting of redox biology. Acknowledgments

The authors would like to thank Isabel Aller and Thomas Nietzel (University of Bonn, Germany) for important discussions and a critical reading of this article. They are also grateful for stimulating exchange with Marcel Deponte (University of Heidelberg, Germany) on redox catalysis. They apologize to all their colleagues whose work could not be covered or cited due to space restrictions. They are grateful for support provided by the Deutsche For-

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schungsgemeinschaft, Germany through the framework of the Priority Program SPP1710 and through the Emmy Noether Program (SCHW1719/1-1). References

1. Al-Mehdi AB, Pastukh VM, Swiger BM, Reed DJ, Patel MR, Bardwell GC, Pastukh VV, Alexeyev MF, and Gillespie MN. Perinuclear mitochondrial clustering creates an oxidant-rich nuclear domain required for hypoxiainduced transcription. Sci Signal 5: ra47, 2012. 2. Albrecht SC, Barata AG, Grosshans J, Teleman AA, and Dick TP. In vivo mapping of hydrogen peroxide and oxidized glutathione reveals chemical and regional specificity of redox homeostasis. Cell Metab 14: 819–829, 2011. 3. Albrecht SC, Sobotta MC, Bausewein D, Aller I, Hell R, Dick TP, and Meyer AJ. Redesign of genetically encoded biosensors for monitoring mitochondrial redox status in a broad range of model eukaryotes. J Biomol Screen 19: 379–386, 2014. 4. Aller I, Rouhier N, and Meyer AJ. Development of roGFP2-derived redox probes for measurement of the glutathione redox potential in the cytosol of severely glutathione-deficient rml1 seedlings. Front Plant Sci 4: 506, 2013. 5. Anandhan A, Rodriguez-Rocha H, Bohovych I, Griggs AM, Zavala-Flores L, Reyes-Reyes EM, Seravalli J, Stanciu LA, Lee J, Rochet JC, Khalimonchuk O, and Franco R. Overexpression of a-synuclein at non-toxic levels increases dopaminergic cell death induced by copper exposure via modulation of protein degradation pathways. Neurobiol Dis 2014 [Epub ahead of print]; DOI: 10.1016/j.nbd.2014.11.018. 6. Archer SL, Marsboom G, Kim GH, Zhang HJ, Toth PT, Svensson EC, Dyck JR, Gomberg-Maitland M, Thebaud B, Husain AN, Cipriani N, and Rehman J. Epigenetic attenuation of mitochondrial superoxide dismutase 2 in pulmonary arterial hypertension: a basis for excessive cell proliferation and a new therapeutic target. Circulation 121: 2661–2671, 2010. 7. Arias-Barreiro CR, Okazaki K, Koutsaftis A, InayatHussain SH, Tani A, Katsuhara M, Kimbara K, and Mori IC. A bacterial biosensor for oxidative stress using the constitutively expressed redox-sensitive protein roGFP2. Sensors (Basel) 10: 6290–6306, 2010. 8. Au KK, Perez-Gomez J, Neto H, Mu¨ller C, Meyer AJ, Fricker MD, and Moore I. A perturbation in glutathione biosynthesis disrupts endoplasmic reticulum morphology and secretory membrane traffic in Arabidopsis thaliana. Plant J 71: 881–894, 2012. 9. Austin CD, Wen X, Gazzard L, Nelson C, Scheller RH, and Scales SJ. Oxidizing potential of endosomes and lysosomes limits intracellular cleavage of disulfide-based antibody-drug conjugates. Proc Natl Acad Sci U S A 102: 17987–17992, 2005. 10. Avezov E, Cross BC, Kaminski Schierle GS, Winters M, Harding HP, Melo EP, Kaminski CF, and Ron D. Lifetime imaging of a fluorescent protein sensor reveals surprising stability of ER thiol redox. J Cell Biol 201: 337–349, 2013. 11. Ayer A, Fellermeier S, Fife C, Li SS, Smits G, Meyer AJ, Dawes IW, and Perrone GG. A genome-wide screen in yeast identifies specific oxidative stress genes required for the maintenance of sub-cellular redox homeostasis. PLoS One 7: e44278, 2012.


704

12. Ayer A, Sanwald J, Pillay BA, Meyer AJ, Perrone GG, and Dawes IW. Distinct redox regulation in sub-cellular compartments in response to various stress conditions in Saccharomyces cerevisiae. PLoS One 8: e65240, 2013. 13. Ayer A, Tan SX, Grant CM, Meyer AJ, Dawes IW, and Perrone GG. The critical role of glutathione in maintenance of the mitochondrial genome. Free Radic Biol Med 49: 1956–1968, 2010. 14. Back P, De Vos WH, Depuydt GG, Matthijssens F, Vanfleteren JR, and Braeckman BP. Exploring real-time in vivo redox biology of developing and aging Caenorhabditis elegans. Free Radic Biol Med 52: 850–859, 2012. 15. Baker JJ, Johnson BK, and Abramovitch RB. Slow growth of Mycobacterium tuberculosis at acidic pH is regulated by phoPR and host-associated carbon sources. Mol Microbiol 94: 56–69, 2014. 16. Banach-Latapy A, Dardalhon M, and Huang ME. A redox-sensitive yellow fluorescent protein sensor for monitoring nuclear glutathione redox dynamics. Methods Mol Biol 1228: 159–169, 2015. 17. Banach-Latapy A, He T, Dardalhon M, Vernis L, Chanet R, and Huang ME. Redox-sensitive YFP sensors for monitoring dynamic compartment-specific glutathione redox state. Free Radic Biol Med 65: 436–445, 2013. 18. Barata AG and Dick TP. In vivo imaging of H2O2 production in Drosophila. Methods Enzymol 526: 61–82, 2013. 19. Barlow CA, Kitiphongspattana K, Siddiqui N, Roe MW, Mossman BT, and Lounsbury KM. Protein kinase Amediated CREB phosphorylation is an oxidant-induced survival pathway in alveolar type II cells. Apoptosis 13: 681–692, 2008. 20. Bell EL, Klimova TA, Eisenbart J, Schumacker PT, and Chandel NS. Mitochondrial reactive oxygen species trigger hypoxia-inducible factor-dependent extension of the replicative life span during hypoxia. Mol Cell Biol 27: 5737–5745, 2007. 21. Belousov VV, Fradkov AF, Lukyanov KA, Staroverov DB, Shakhbazov KS, Terskikh AV, and Lukyanov S. Genetically encoded fluorescent indicator for intracellular hydrogen peroxide. Nat Methods 3: 281–286, 2006. 22. Beneloujaephajri E, Costa A, L’Haridon F, Metraux JP, and Binda M. Production of reactive oxygen species and wound-induced resistance in Arabidopsis thaliana against Botrytis cinerea are preceded and depend on a burst of calcium. BMC Plant Biol 13: 160, 2013. 23. Berg J, Hung YP, and Yellen G. A genetically encoded fluorescent reporter of ATP:ADP ratio. Nat Methods 6: 161–166, 2009. 24. Berkelhamer SK, Kim GA, Radder JE, Wedgwood S, Czech L, Steinhorn RH, and Schumacker PT. Developmental differences in hyperoxia-induced oxidative stress and cellular responses in the murine lung. Free Radic Biol Med 61C: 51–60, 2013. 25. Bhaskar A, Chawla M, Mehta M, Parikh P, Chandra P, Bhave D, Kumar D, Carroll KS, and Singh A. Reengineering redox sensitive GFP to measure mycothiol redox potential of Mycobacterium tuberculosis during infection. PLoS Pathog 10: e1003902, 2014. 26. Bhaskar A, Munshi M, Khan SZ, Fatima S, Arya R, Jameel S, and Singh A. Measuring glutathione redox potential of HIV-1 infected macrophages. J Biol Chem 290: 1020–1038, 2015.


27. Bienert GP, Moller AL, Kristiansen KA, Schulz A, Moller IM, Schjoerring JK, and Jahn TP. Specific aquaporins facilitate the diffusion of hydrogen peroxide across membranes. J Biol Chem 282: 1183–1192, 2007. 28. Bilan DS, Pase L, Joosen L, Gorokhovatsky AY, Ermakova YG, Gadella TW, Grabher C, Schultz C, Lukyanov S, and Belousov VV. HyPer-3: a genetically encoded H2O2 probe with improved performance for ratiometric and fluorescence lifetime imaging. ACS Chem Biol 8: 535–542, 2013. 29. Bingol B, Tea JS, Phu L, Reichelt M, Bakalarski CE, Song Q, Foreman O, Kirkpatrick DS, and Sheng M. The mitochondrial deubiquitinase USP30 opposes parkin-mediated mitophagy. Nature 510: 370–375, 2014. 30. Birk J, Meyer M, Aller I, Hansen HG, Odermatt A, Dick TP, Meyer AJ, and Appenzeller-Herzog C. Endoplasmic reticulum: reduced and oxidized glutathione revisited. J Cell Sci 126: 1604–1617, 2013. 31. Birk J, Ramming T, Odermatt A, and Appenzeller-Herzog C. Green fluorescent protein-based monitoring of endoplasmic reticulum redox poise. Front Genet 4: 108, 2013. 32. Bjo¨rnberg O, Østergaard H, and Winther JR. Mechanistic insight provided by glutaredoxin within a fusion to redoxsensitive yellow fluorescent protein. Biochemistry 45: 2362–2371, 2006. 33. Bode M, Longen S, Morgan B, Peleh V, Dick TP, Bihlmaier K, and Herrmann JM. Inaccurately assembled cytochrome c oxidase can lead to oxidative stress-induced growth arrest. Antioxid Redox Signal 18: 1597–1612, 2013. 34. Bouldin SD, Darch MA, Hart PJ, and Outten CE. Redox properties of the disulfide bond of human Cu,Zn superoxide dismutase and the effects of human glutaredoxin 1. Biochem J 446: 59–67, 2012. 35. Brach T, Soyk S, Mu¨ller C, Hinz G, Hell R, Brandizzi F, and Meyer AJ. Non-invasive topology analysis of membrane proteins in the secretory pathway. Plant J 57: 534–541, 2009. 36. Braun NA, Morgan B, Dick TP, and Schwappach B. The yeast CLC protein counteracts vesicular acidification during iron starvation. J Cell Sci 123: 2342–2350, 2010. 37. Breckwoldt MO, Pfister FM, Bradley PM, Marinkovic P, Williams PR, Brill MS, Plomer B, Schmalz A, St Clair DK, Naumann R, Griesbeck O, Schwarzla¨nder M, Godinho L, Bareyre FM, Dick TP, Kerschensteiner M, and Misgeld T. Multiparametric optical analysis of mitochondrial redox signals during neuronal physiology and pathology in vivo. Nat Med 20: 555–560, 2014. 38. Brejc K, Sixma TK, Kitts PA, Kain SR, Tsien RY, Ormo M, and Remington SJ. Structural basis for dual excitation and photoisomerization of the Aequorea victoria green fluorescent protein. Proc Natl Acad Sci U S A 94: 2306– 2311, 1997. 39. Brossa R, Pinto-Marijuan M, Jiang K, Alegre L, and Feldman LJ. Assessing the regulation of leaf redox status under water stress conditions in Arabidopsis thaliana: Col-0 ecotype (wild-type and vtc-2), expressing mitochondrial and cytosolic roGFP1. Plant Signal Behav 8: e24781, 2013. 40. Can B, Kulaksiz Erkmen G, Dalmizrak O, Ogus IH, and Ozer N. Purification and characterisation of rat kidney glutathione reductase. Protein J 29: 250–256, 2010. 41. Canepa L, Ferraris AM, Miglino M, and Gaetani GF. Bound and unbound pyridine dinucleotides in normal and


42. 43.


44.

45. 46.

47.

48.

49. 50.

51.

52.

53.

54.

55.

56.

glucose-6-phosphate dehydrogenase-deficient erythrocytes. Biochim Biophys Acta 1074: 101–104, 1991. Cannon MB and Remington SJ. Re-engineering redoxsensitive green fluorescent protein for improved response rate. Protein Sci 15: 45–57, 2006. Cannon MB and Remington SJ. Redox-sensitive green fluorescent protein: probes for dynamic intracellular redox responses. A review. Methods Mol Biol 476: 51–65, 2008. Celotto AM, Liu Z, Vandemark AP, and Palladino MJ. A novel Drosophila SOD2 mutant demonstrates a role for mitochondrial ROS in neurodevelopment and disease. Brain Behav 2: 424–434, 2012. Chang JC, van der Hoeven LH, and Haddox CH. Glutathione reductase in the red blood cells. Ann Clin Lab Sci 8: 23–29, 1978. Chartoumpekis DV, Ziros PG, Sykiotis GP, Zaravinos A, Psyrogiannis AI, Kyriazopoulou VE, Spandidos DA, and Habeos IG. Nrf2 activation diminishes during adipocyte differentiation of ST2 cells. Int J Mol Med 28: 823–828, 2011. Chen J, Shen J, Solem C, and Jensen PR. Oxidative stress at high temperatures in Lactococcus lactis due to an insufficient supply of riboflavin. Appl Environ Microbiol 79: 6140–6147, 2013. Cheng WY, Currier J, Bromberg PA, Silbajoris R, Simmons SO, and Samet JM. Linking oxidative events to inflammatory and adaptive gene expression induced by exposure to an organic particulate matter component. Environ Health Perspect 120: 267–274, 2012. Cheng WY, Larson JM, and Samet JM. Monitoring intracellular oxidative events using dynamic spectral unmixing microscopy. Methods 66: 345–352, 2014. Cheng WY, Tong H, Miller EW, Chang CJ, Remington J, Zucker RM, Bromberg PA, Samet JM, and Hofer TP. An integrated imaging approach to the study of oxidative stress generation by mitochondrial dysfunction in living cells. Environ Health Perspect 118: 902–908, 2010. Chi AY, Waypa GB, Mungai PT, and Schumacker PT. Prolonged hypoxia increases ROS signaling and RhoA activation in pulmonary artery smooth muscle and endothelial cells. Antioxid Redox Signal 12: 603–610, 2010. Cossu A, Posadino AM, Giordo R, Emanueli C, Sanguinetti AM, Piscopo A, Poiana M, Capobianco G, Piga A, and Pintus G. Apricot melanoidins prevent oxidative endothelial cell death by counteracting mitochondrial oxidation and membrane depolarization. PLoS One 7: e48817, 2012. Cunniff B, Benson K, Stumpff J, Newick K, Held P, Taatjes D, Joseph J, Kalyanaraman B, and Heintz NH. Mitochondrial-targeted nitroxides disrupt mitochondrial architecture and inhibit expression of peroxiredoxin 3 and FOXM1 in malignant mesothelioma cells. J Cell Physiol 228: 835–845, 2013. Cunniff B, Snider GW, Fredette N, Stumpff J, Hondal RJ, and Heintz NH. Resolution of oxidative stress by thioredoxin reductase: Cysteine versus selenocysteine. Redox Biol 2: 475–484, 2014. Dardalhon M, Kumar C, Iraqui I, Vernis L, Kienda G, Banach-Latapy A, He T, Chanet R, Faye G, Outten CE, and Huang ME. Redox-sensitive YFP sensors monitor dynamic nuclear and cytosolic glutathione redox changes. Free Radic Biol Med 52: 2254–2265, 2012. De Marchi U, Santo-Domingo J, Castelbou C, Sekler I, Wiederkehr A, and Demaurex N. NCLX protein, but not

705

57. 58.

59. 60.

61. 62. 63.

64.

65.

66. 67.

68.

69.

70.

71.

LETM1, mediates mitochondrial Ca2 + extrusion, thereby limiting Ca2 + -induced NAD(P)H production and modulating matrix redox state. J Biol Chem 289: 20377–20385, 2014. Delaunay A, Pflieger D, Barrault MB, Vinh J, and Toledano MB. A thiol peroxidase is an H2O2 receptor and redoxtransducer in gene activation. Cell 111: 471–481, 2002. Delic M, Graf AB, Koellensperger G, Haberhauer-Troyer C, Hann S, Mattanovich D, and Gasser B. Overexpression of the transcription factor Yap1 modifies intracellular redox conditions and enhances recombinant protein secretion. Microbial Cell 1: 376–386, 2014. Delic M, Mattanovich D, and Gasser B. Monitoring intracellular redox conditions in the endoplasmic reticulum of living yeasts. FEMS Microbiol Lett 306: 61–66, 2010. Delic M, Rebnegger C, Wanka F, Puxbaum V, Haberhauer-Troyer C, Hann S, Kollensperger G, Mattanovich D, and Gasser B. Oxidative protein folding and unfolded protein response elicit differing redox regulation in endoplasmic reticulum and cytosol of yeast. Free Radic Biol Med 52: 2000–2012, 2012. Deponte M. Glutathione catalysis and the reaction mechanisms of glutathione-dependent enzymes. Biochim Biophys Acta 1830: 3217–3266, 2013. Deponte M and Lillig CH. Enzymatic control of cysteinyl thiol switches in proteins. Biol Chem 396: 401–413, 2015. Desireddi JR, Farrow KN, Marks JD, Waypa GB, and Schumacker PT. Hypoxia increases ROS signaling and cytosolic Ca2 + in pulmonary artery smooth muscle cells of mouse lungs slices. Antioxid Redox Signal 12: 595–602, 2010. Dlaskova A, Spacek T, Santorova J, Plecita-Hlavata L, Berkova Z, Saudek F, Lessard M, Bewersdorf J, and Jezek P. 4Pi microscopy reveals an impaired three-dimensional mitochondrial network of pancreatic islet b-cells, an experimental model of type-2 diabetes. Biochim Biophys Acta 1797: 1327–1341, 2010. Dooley CT, Dore TM, Hanson GT, Jackson WC, Remington SJ, and Tsien RY. Imaging dynamic redox changes in mammalian cells with green fluorescent protein indicators. J Biol Chem 279: 22284–22293, 2004. Dooley CT, Li L, Misler JA, and Thompson JH. Toxicity of 6-hydroxydopamine: live cell imaging of cytoplasmic redox flux. Cell Biol Toxicol 28: 89–101, 2012. Dryanovski DI, Guzman JN, Xie Z, Galteri DJ, VolpicelliDaley LA, Lee VM, Miller RJ, Schumacker PT, and Surmeier DJ. Calcium entry and a-synuclein inclusions elevate dendritic mitochondrial oxidant stress in dopaminergic neurons. J Neurosci 33: 10154–10164, 2013. Dubreuil-Maurizi C, Vitecek J, Marty L, Branciard L, Frettinger P, Wendehenne D, Meyer AJ, Mauch F, and Poinssot B. Glutathione deficiency of the Arabidopsis mutant pad2-1 affects oxidative stress-related events, defense gene expression, and the hypersensitive response. Plant Physiol 157: 2000–2012, 2011. Duprez J, Roma LP, Close AF, and Jonas JC. Protective antioxidant and antiapoptotic effects of ZnCl2 in rat pancreatic islets cultured in low and high glucose concentrations. PLoS One 7: e46831, 2012. Elbaz-Alon Y, Morgan B, Clancy A, Amoako TN, Zalckvar E, Dick TP, Schwappach B, and Schuldiner M. The yeast oligo-peptide transporter Opt2 is localized to peroxisomes and affects glutathione redox homeostasis. FEMS Yeast Res 14: 1055–1067, 2014. Ermakova YG, Bilan DS, Matlashov ME, Mishina NM, Markvicheva KN, Subach OM, Subach FV, Bogeski I,


706

72. 73.


74.

75.

76. 77.

78.

79.

80.

81.

82.

83.

84.

85.

86.

Hoth M, Enikolopov G, and Belousov VV. Red fluorescent genetically encoded indicator for intracellular hydrogen peroxide. Nat Commun 5: 5222, 2014. Ezerina D, Morgan B, and Dick TP. Imaging dynamic redox processes with genetically encoded probes. J Mol Cell Cardiol 73: 43–49, 2014. Fan Y, Chen Z, and Ai HW. Monitoring redox dynamics in living cells with a redox-sensitive red fluorescent protein. Anal Chem 87: 2802–2810, 2015. Farrow KN, Lee KJ, Perez M, and Schriewer JM, Wedgwood S, Lakshminrusimha S, Smith CL, Steinhorn RH, and Schumacker PT. Brief hyperoxia increases mitochondrial oxidation and increases phosphodiesterase 5 activity in fetal pulmonary artery smooth muscle cells. Antioxid Redox Signal 17: 460–470, 2012. Fischer M, Horn S, Belkacemi A, Kojer K, Petrungaro C, Habich M, Ali M, Kuttner V, Bien M, Kauff F, Dengjel J, Herrmann JM, and Riemer J. Protein import and oxidative folding in the mitochondrial intermembrane space of intact mammalian cells. Mol Biol Cell 24: 2160–2170, 2013. Fricker MD. Quantitative Redox Imaging Software. Antioxid Redox Signal 24: 752–762. Funke F, Gerich FJ, and Mu¨ller M. Dynamic, semiquantitative imaging of intracellular ROS levels and redox status in rat hippocampal neurons. Neuroimage 54: 2590– 2602, 2011. Gerencser AA and Nicholls DG. Measurement of instantaneous velocity vectors of organelle transport: mitochondrial transport and bioenergetics in hippocampal neurons. Biophys J 95: 3079–3099, 2008. Ghose P, Park EC, Tabakin A, Salazar-Vasquez N, and Rongo C. Anoxia-reoxygenation regulates mitochondrial dynamics through the hypoxia response pathway, SKN-1/ Nrf, and stomatin-like protein STL-1/SLP-2. PLoS Genet 9: e1004063, 2013. Gibbs-Flournoy EA, Simmons SO, Bromberg PA, Dick TP, and Samet JM. Monitoring intracellular redox changes in ozone-exposed airway epithelial cells. Environ Health Perspect 121: 312–317, 2013. Glasauer A, Sena LA, Diebold LP, Mazar AP, and Chandel NS. Targeting SOD1 reduces experimental non-small-cell lung cancer. J Clin Invest 124: 117–128, 2014. Goldberg JA, Guzman JN, Estep CM, Ilijic E, Kondapalli J, Sanchez-Padilla J, and Surmeier DJ. Calcium entry induces mitochondrial oxidant stress in vagal neurons at risk in Parkinson’s disease. Nat Neurosci 15: 1414–1421, 2012. Graff van Creveld S, Rosenwasser S, Schatz D, Koren I, and Vardi A. Early perturbation in mitochondria redox homeostasis in response to environmental stress predicts cell fate in diatoms. ISME J 9: 385–395, 2015. Grosser E, Hirt U, Janc OA, Menzfeld C, Fischer M, Kempkes B, Vogelgesang S, Manzke TU, Opitz L, Salinas-Riester G, and Muller M. Oxidative burden and mitochondrial dysfunction in a mouse model of Rett syndrome. Neurobiol Dis 48: 102–114, 2012. Gruhlke MC, Portz D, Stitz M, Anwar A, Schneider T, Jacob C, Schlaich NL, and Slusarenko AJ. Allicin disrupts the cell’s electrochemical potential and induces apoptosis in yeast. Free Radic Biol Med 49: 1916–1924, 2010. Gutscher M, Pauleau AL, Marty L, Brach T, Wabnitz GH, Samstag Y, Meyer AJ, and Dick TP. Real-time imaging of the intracellular glutathione redox potential. Nat Methods 5: 553–559, 2008.

87. Gutscher M, Sobotta MC, Wabnitz GH, Ballikaya S, Meyer AJ, Samstag Y, and Dick TP. Proximity-based protein thiol oxidation by H2O2-scavenging peroxidases. J Biol Chem 284: 31532–31540, 2009. 88. Guzman JN, Sanchez-Padilla J, Wokosin D, Kondapalli J, Ilijic E, Schumacker PT, and Surmeier DJ. Oxidant stress evoked by pacemaking in dopaminergic neurons is attenuated by DJ-1. Nature 468: 696–700, 2010. 89. Guzy RD, Sharma B, Bell E, Chandel NS, and Schumacker PT. Loss of the SdhB, but Not the SdhA, subunit of complex II triggers reactive oxygen species-dependent hypoxia-inducible factor activation and tumorigenesis. Mol Cell Biol 28: 718–731, 2008. 90. Haga S, Remington SJ, Morita N, Terui K, and Ozaki M. Hepatic ischemia induced immediate oxidative stress after reperfusion and determined the severity of the reperfusion-induced damage. Antioxid Redox Signal 11: 2563– 2572, 2009. 91. Hanson GT, Aggeler R, Oglesbee D, Cannon M, Capaldi RA, Tsien RY, and Remington SJ. Investigating mitochondrial redox potential with redox-sensitive green fluorescent protein indicators. J Biol Chem 279: 13044– 13053, 2004. 92. Hasel P, McKay S, Qiu J, and Hardingham GE. Selective dendritic susceptibility to bioenergetic and redox perturbations in cortical neurons. Biochim Biophys Acta 2014 [Epub ahead of print]; DOI: 10.1016/j.bbamcr.2014.12.021. 93. Heller J, Meyer AJ, and Tudzynski P. Redox-sensitive GFP2: use of the genetically encoded biosensor of the redox status in the filamentous fungus Botrytis cinerea. Mol Plant Pathol 13: 935–947, 2012. 94. Hempel N, Ye H, Abessi B, Mian B, and Melendez JA. Altered redox status accompanies progression to metastatic human bladder cancer. Free Radic Biol Med 46: 42–50, 2009. 95. Higuchi R, Vevea JD, Swayne TC, Chojnowski R, Hill V, Boldogh IR, and Pon LA. Actin dynamics affect mitochondrial quality control and aging in budding yeast. Curr Biol 23: 2417–2422, 2013. 96. Hildebrandt T, Knuesting J, Berndt C, Morgan B, and Scheibe R. Cytosolic thiol switches regulating basic cellular functions: GAPDH as an information hub? Biol Chem 396: 523–537, 2015. 97. Hu J, Dong L, and Outten CE. The redox environment in the mitochondrial intermembrane space is maintained separately from the cytosol and matrix. J Biol Chem 283: 29126–29134, 2008. 98. Hu M, Xu T, and Chang C. Evaluation of the mitochondrial redox status in Caenorhabditis elegans: an assay based on the COPAS Biosort Flow Cytometer Acta Biophys Sin 30: 110–116, 2014. 99. Huang WJ, Liu HK, McCormick S, and Tang WH. Tomato pistil factor STIG1 promotes in vivo pollen tube growth by binding to phosphatidylinositol 3-phosphate and the extracellular domain of the pollen receptor kinase LePRK2. Plant Cell 26: 2505–2523, 2014. 100. Hynes WF, Doty NJ, Zarembinski TI, Schwartz MP, Toepke MW, Murphy WL, Atzet SK, Clark R, Melendez JA, and Cady NC. Micropatterning of 3D microenvironments for living biosensor applications. Biosensors (Basel) 4: 28–44, 2014. 101. Imamura H, Nhat KP, Togawa H, Saito K, Iino R, KatoYamada Y, Nagai T, and Noji H. Visualization of ATP levels inside single living cells with fluorescence resonance


102.


103.

104.

105.

106.

107. 108.

109.

110.

111.

112.

113.

114.

115.

116.

energy transfer-based genetically encoded indicators. Proc Natl Acad Sci U S A 106: 15651–15656, 2009. Ivashchenko O, Van Veldhoven PP, Brees C, Ho YS, Terlecky SR, and Fransen M. Intraperoxisomal redox balance in mammalian cells: oxidative stress and interorganellar cross-talk. Mol Biol Cell 22: 1440–1451, 2011. Jain M, Rivera S, Monclus EA, Synenki L, Zirk A, Eisenbart J, Feghali-Bostwick C, Mutlu GM, Budinger GR, and Chandel NS. Mitochondrial reactive oxygen species regulate transforming growth factor-b signaling. J Biol Chem 288: 770–777, 2013. Jiang K, Schwarzer C, Lally E, Zhang S, Ruzin S, Machen T, Remington SJ, and Feldman L. Expression and characterization of a redox-sensing green fluorescent protein (reduction-oxidation-sensitive green fluorescent protein) in Arabidopsis. Plant Physiol 141: 397–403, 2006. Johansson C, Lillig CH, and Holmgren A. Human mitochondrial glutaredoxin reduces S-glutathionylated proteins with high affinity accepting electrons from either glutathione or thioredoxin reductase. J Biol Chem 279: 7537–7543, 2004. Johnson D, Allman E, and Nehrke K. Regulation of acidbase transporters by reactive oxygen species following mitochondrial fragmentation. Am J Physiol Cell Physiol 302: C1045–C1054, 2012. Johnson D and Nehrke K. Mitochondrial fragmentation leads to intracellular acidification in Caenorhabditis elegans and mammalian cells. Mol Biol Cell 21: 2191–2201, 2010. Jubany-Mari T, Alegre-Batlle L, Jiang K, and Feldman LJ. Use of a redox-sensing GFP (c-roGFP1) for real-time monitoring of cytosol redox status in Arabidopsis thaliana water-stressed plants. FEBS Lett 584: 889–897, 2010. Kanekura K, Ishigaki S, Merksamer PI, Papa FR, and Urano F. Establishment of a system for monitoring endoplasmic reticulum redox state in mammalian cells. Lab Invest 93: 1254–1258, 2013. Kasozi D, Mohring F, Rahlfs S, Meyer AJ, and Becker K. Real-time imaging of the intracellular glutathione redox potential in the malaria parasite Plasmodium falciparum. PLoS Pathog 9: e1003782, 2013. Kemp M, Go YM, and Jones DP. Nonequilibrium thermodynamics of thiol/disulfide redox systems: a perspective on redox systems biology. Free Radic Biol Med 44: 921–937, 2008. Khader H, Solodushko V, Al-Mehdi AB, Audia J, and Fouty B. Overlap of doxycycline fluorescence with that of the redox-sensitive intracellular reporter roGFP. J Fluoresc 24: 305–311, 2014. Klimova TA, Bell EL, Shroff EH, Weinberg FD, Snyder CM, Dimri GP, Schumacker PT, Budinger GR, and Chandel NS. Hyperoxia-induced premature senescence requires p53 and pRb, but not mitochondrial matrix ROS. FASEB J 23: 783–794, 2009. Kojer K, Bien M, Gangel H, Morgan B, Dick TP, and Riemer J. Glutathione redox potential in the mitochondrial intermembrane space is linked to the cytosol and impacts the Mia40 redox state. EMBO J 31: 3169–3182, 2012. Kojer K, Peleh V, Calabrese G, Herrmann JM, and Riemer J. Kinetic control by limiting glutaredoxin amounts enables thiol oxidation in the reducing mitochondrial IMS. Mol Biol Cell 26: 195–204, 2015. Kolossov VL, Beaudoin JN, Hanafin WP, DiLiberto SJ, Kenis PJ, and Gaskins HR. Transient light-induced in-

707

117.

118.

119.

120.

121.

122.

123.

124.

125.

126.

127.

128. 129.

130. 131.

tracellular oxidation revealed by redox biosensor. Biochem Biophys Res Commun 439: 517–521, 2013. Kolossov VL, Leslie MT, Chatterjee A, Sheehan BM, Kenis PJ, and Gaskins HR. Forster resonance energy transfer-based sensor targeting endoplasmic reticulum reveals highly oxidative environment. Exp Biol Med (Maywood) 237: 652–662, 2012. Ko¨nig K, Galliardt H, Moore M, Treffon P, Seidel T, and Dietz KJ. Assessing redox state and reactive oxygen species in circadian rhythmicity. Methods Mol Biol 1158: 239–271, 2014. Kriechbaumer V, Wang P, Hawes C, and Abell BM. Alternative splicing of the auxin biosynthesis gene YUCCA4 determines its subcellular compartmentation. Plant J 70: 292–302, 2012. Lee R and Britz-McKibbin P. Differential rates of glutathione oxidation for assessment of cellular redox status and antioxidant capacity by capillary electrophoresis-mass spectrometry: an elusive biomarker of oxidative stress. Anal Chem 81: 7047–7056, 2009. Lehmann M, Schwarzla¨nder M, Obata T, Sirikantaramas S, Burow M, Olsen CE, Tohge T, Fricker MD, Moller BL, Fernie AR, Sweetlove LJ, and Laxa M. The metabolic response of Arabidopsis roots to oxidative stress is distinct from that of heterotrophic cells in culture and highlights a complex relationship between the levels of transcripts, metabolites, and flux. Mol Plant 2: 390–406, 2009. Lei H and Kazlauskas A. A reactive oxygen speciesmediated, self-perpetuating loop persistently activates platelet-derived growth factor receptor a. Mol Cell Biol 34: 110–122, 2014. Liu X, Wu J, Liu H, Zong N, and Zhao J. RoGFP1 is a quantitative biosensor in maize cells for cellular redox changes caused by environmental and endogenous stimuli. Biochem Biophys Res Commun 452: 503–508, 2014. Liu Z, Celotto AM, Romero G, Wipf P, and Palladino MJ. Genetically encoded redox sensor identifies the role of ROS in degenerative and mitochondrial disease pathogenesis. Neurobiol Dis 45: 362–368, 2012. Lohman JR and Remington SJ. Development of a family of redox-sensitive green fluorescent protein indicators for use in relatively oxidizing subcellular environments. Biochemistry 47: 8678–8688, 2008. Loor G, Kondapalli J, Iwase H, Chandel NS, Waypa GB, Guzy RD, Vanden Hoek TL, and Schumacker PT. Mitochondrial oxidant stress triggers cell death in simulated ischemia-reperfusion. Biochim Biophys Acta 1813: 1382– 1394, 2011. Loor G, Kondapalli J, Schriewer JM, Chandel NS, Vanden Hoek TL, and Schumacker PT. Menadione triggers cell death through ROS-dependent mechanisms involving PARP activation without requiring apoptosis. Free Radic Biol Med 49: 1925–1936, 2010. Lukyanov KA and Belousov VV. Genetically encoded fluorescent redox sensors. Biochim Biophys Acta 1840: 745–756, 2014. Maharjan S, Oku M, Tsuda M, Hoseki J, and Sakai Y. Mitochondrial impairment triggers cytosolic oxidative stress and cell death following proteasome inhibition. Sci Rep 4: 5896, 2014. Mapson LW and Isherwood FA. Glutathione reductase from germinated peas. Biochem J 86: 173–191, 1963. Markvicheva KN, Bilan DS, Mishina NM, Gorokhovatsky AY, Vinokurov LM, Lukyanov S, and Be-


708

132. 133.


134.

135.

136.

137.

138.

139.

140.

141.

142.

143. 144. 145.

lousov VV. A genetically encoded sensor for H2O2 with expanded dynamic range. Bioorg Med Chem 19: 1079– 1084, 2011. This reference has been deleted. Marty L, Siala W, Schwarzla¨nder M, Fricker MD, Wirtz M, Sweetlove LJ, Meyer Y, Meyer AJ, Reichheld JP, and Hell R. The NADPH-dependent thioredoxin system constitutes a functional backup for cytosolic glutathione reductase in Arabidopsis. Proc Natl Acad Sci U S A 106: 9109–9114, 2009. Matern S, Peskan-Berghoefer T, Gromes R, Vazquez Kiesel R, and Rausch T. Imposed glutathione-mediated redox switch modulates tobacco SIPK/WIPK activation state and impacts on defense against Pseudomonas syringae. J Exp Bot 66: 1935–1950, 2015. Maughan SC, Pasternak M, Cairns N, Kiddle G, Brach T, Jarvis R, Haas F, Nieuwland J, Lim B, Mu¨ller C, SalcedoSora E, Kruse C, Orsel M, Hell R, Miller AJ, Bray P, Foyer CH, Murray JA, Meyer AJ, and Cobbett CS. Plant homologs of the Plasmodium falciparum chloroquine-resistance transporter, PfCRT, are required for glutathione homeostasis and stress responses. Proc Natl Acad Sci U S A 107: 2331–2336, 2010. Maulucci G, Labate V, Mele M, Panieri E, Arcovito G, Galeotti T, Østergaard H, Winther JR, De Spirito M, and Pani G. High-resolution imaging of redox signaling in live cells through an oxidation-sensitive yellow fluorescent protein. Sci Signal 1: pl3, 2008. Maulucci G, Pani G, Labate V, Mele M, Panieri E, Papi M, Arcovito G, Galeotti T, and De Spirito M. Investigation of the spatial distribution of glutathione redoxbalance in live cells by using Fluorescence Ratio Imaging Microscopy. Biosens Bioelectron 25: 682–687, 2009. McFaline-Figueroa JR, Vevea J, Swayne TC, Zhou C, Liu C, Leung G, Boldogh IR, and Pon LA. Mitochondrial quality control during inheritance is associated with lifespan and mother-daughter age asymmetry in budding yeast. Aging Cell 10: 885–895, 2011. McInnes J, Rehders M, McFaline-Figueroa JR, Brix K, Pon LA, and Nevoigt E. Defects in mitochondrial distribution during the prolonged lag phase of Saccharomyces cerevisiae preceding growth in glycerol as the sole source of carbon. FEMS Yeast Res 13: 706–710, 2013. Melillo AA, Bakshi CS, and Melendez JA. Francisella tularensis antioxidants harness reactive oxygen species to restrict macrophage signaling and cytokine production. J Biol Chem 285: 27553–27560, 2010. Merksamer PI, Trusina A, and Papa FR. Real-time redox measurements during endoplasmic reticulum stress reveal interlinked protein folding functions. Cell 135: 933–947, 2008. Meyer AJ, Brach T, Marty L, Kreye S, Rouhier N, Jacquot JP, and Hell R. Redox-sensitive GFP in Arabidopsis thaliana is a quantitative biosensor for the redox potential of the cellular glutathione redox buffer. Plant J 52: 973– 986, 2007. Meyer AJ and Dick TP. Fluorescent protein-based redox probes. Antioxid Redox Signal 13: 621–650, 2010. Meyer AJ, May MJ, and Fricker M. Quantitative in vivo measurement of glutathione in Arabidopsis cells. Plant J 27: 67–78, 2001. Michaelson LP, Shi G, Ward CW, and Rodney GG. Mitochondrial redox potential during contraction in single intact muscle fibers. Muscle Nerve 42: 522–529, 2010.

146. Michelet L, Zaffagnini M, Marchand C, Collin V, Decottignies P, Tsan P, Lancelin JM, Trost P, MiginiacMaslow M, Noctor G, and Lemaire SD. Glutathionylation of chloroplast thioredoxin f is a redox signaling mechanism in plants. Proc Natl Acad Sci U S A 102: 16478– 16483, 2005. 147. Miyawaki A, Llopis J, Heim R, McCaffery JM, Adams JA, Ikura M, and Tsien RY. Fluorescent indicators for Ca2 + based on green fluorescent proteins and calmodulin. Nature 388: 882–887, 1997. 148. Mollajew R, Toloe J, and Mironov SL. Single KATP channel opening in response to stimulation of AMPA/ kainate receptors is mediated by Na + accumulation and submembrane ATP and ADP changes. J Physiol 591: 2593–2609, 2013. 149. Montero D, Tachibana C, Rahr Winther J, and AppenzellerHerzog C. Intracellular glutathione pools are heterogeneously concentrated. Redox Biol 1: 508–513, 2013. 150. Morgan B. Reassessing cellular glutathione homoeostasis: novel insights revealed by genetically encoded redox probes. Biochem Soc Trans 42: 979–984, 2014. 151. Morgan B, Ezerina D, Amoako TN, Riemer J, Seedorf M, and Dick TP. Multiple glutathione disulfide removal pathways mediate cytosolic redox homeostasis. Nat Chem Biol 9: 119–125, 2013. 152. Morgan MJ, Lehmann M, Schwarzla¨nder M, Baxter CJ, Sienkiewicz-Porzucek A, Williams TC, Schauer N, Fernie AR, Fricker MD, Ratcliffe RG, Sweetlove LJ, and Finkemeier I. Decrease in manganese superoxide dismutase leads to reduced root growth and affects tricarboxylic acid cycle flux and mitochondrial redox homeostasis. Plant Physiol 147: 101–114, 2008. 153. Mou Z, Fan W, and Dong X. Inducers of plant systemic acquired resistance regulate NPR1 function through redox changes. Cell 113: 935–944, 2003. 154. Muller EG. A glutathione reductase mutant of yeast accumulates high levels of oxidized glutathione and requires thioredoxin for growth. Mol Biol Cell 7: 1805– 1813, 1996. 155. Mungai PT, Waypa GB, Jairaman A, Prakriya M, Dokic D, Ball MK, and Schumacker PT. Hypoxia triggers AMPK activation through reactive oxygen species-mediated activation of calcium release-activated calcium channels. Mol Cell Biol 31: 3531–3545, 2011. 156. Nagai T, Sawano A, Park ES, and Miyawaki A. Circularly permuted green fluorescent proteins engineered to sense Ca2 + . Proc Natl Acad Sci U S A 98: 3197–3202, 2001. 157. Nøstbakken OJ, Bredal IL, Olsvik PA, Huang TS, and Torstensen BE. Effect of marine omega 3 fatty acids on methylmercury-induced toxicity in fish and mammalian cells in vitro. J Biomed Biotechnol 2012: 417652, 2012. 158. O’Donnell KC, Vargas ME, and Sagasti A. WldS and PGC1a regulate mitochondrial transport and oxidation state after axonal injury. J Neurosci 33: 14778–14790, 2013. 159. Oku M and Sakai Y. Assessment of physiological redox state with novel FRET protein probes. Antioxid Redox Signal 16: 698–704, 2012. 160. Østergaard H, Henriksen A, Hansen FG, and Winther JR. Shedding light on disulfide bond formation: engineering a redox switch in green fluorescent protein. EMBO J 20: 5853–5862, 2001. 161. Østergaard H, Tachibana C, and Winther JR. Monitoring disulfide bond formation in the eukaryotic cytosol. J Cell Biol 166: 337–345, 2004.



162. Pal R, Basu Thakur P, Li S, Minard C, and Rodney GG. Real-time imaging of NADPH oxidase activity in living cells using a novel fluorescent protein reporter. PLoS One 8: e63989, 2013. 163. Pal R, Monroe TO, Palmieri M, Sardiello M, and Rodney GG. Rotenone induces neurotoxicity through Rac1-dependent activation of NADPH oxidase in SHSY-5Y cells. FEBS Lett 588: 472–481, 2014. 164. Pal R, Palmieri M, Loehr JA, Li S, Abo-Zahrah R, Monroe TO, Thakur PB, Sardiello M, and Rodney GG. Src-dependent impairment of autophagy by oxidative stress in a mouse model of Duchenne muscular dystrophy. Nat Commun 5: 4425, 2014. 165. Pan J, Zhang Q, Liu Q, Komas SM, Kalyanaraman B, Lubet RA, Wang Y, and You M. Honokiol inhibits lung tumorigenesis through inhibition of mitochondrial function. Cancer Prev Res (Phila) 7: 1149–1159, 2014. 166. Park SW, Li W, Viehhauser A, He B, Kim S, Nilsson AK, Andersson MX, Kittle JD, Ambavaram MM, Luan S, Esker AR, Tholl D, Cimini D, Ellerstrom M, Coaker G, Mitchell TK, Pereira A, Dietz KJ, and Lawrence CB. Cyclophilin 20–23 relays a 12-oxo-phytodienoic acid signal during stress responsive regulation of cellular redox homeostasis. Proc Natl Acad Sci U S A 110: 9559–9564, 2013. 167. Perez M, Wedgwood S, Lakshminrusimha S, Farrow KN, and Steinhorn RH. Hydrocortisone normalizes phosphodiesterase-5 activity in pulmonary artery smooth muscle cells from lambs with persistent pulmonary hypertension of the newborn. Pulm Circ 4: 71–81, 2014. 168. Posadino AM, Cossu A, Piga A, Madrau MA, Del Caro A, Colombino M, Paglietti B, Rubino S, Iaccarino C, Crosio C, Sanna B, and Pintus G. Prune melanoidins protect against oxidative stress and endothelial cell death. Front Biosci (Elite Ed) 3: 1034–1041, 2011. 169. Queval G and Noctor G. A plate reader method for the measurement of NAD, NADP, glutathione, and ascorbate in tissue extracts: Application to redox profiling during Arabidopsis rosette development. Anal Biochem 363: 58– 69, 2007. 170. Rehman J, Zhang HJ, Toth PT, Zhang Y, Marsboom G, Hong Z, Salgia R, Husain AN, Wietholt C, and Archer SL. Inhibition of mitochondrial fission prevents cell cycle progression in lung cancer. FASEB J 26: 2175–2186, 2012. 171. Riemer J, Schwarzlander M, Conrad M, and Herrmann JM. Thiol switches in mitochondria: operation and physiological relevance. Biol Chem 396: 465–482, 2015. 172. Robin E, Guzy RD, Loor G, Iwase H, Waypa GB, Marks JD, Hoek TL, and Schumacker PT. Oxidant stress during simulated ischemia primes cardiomyocytes for cell death during reperfusion. J Biol Chem 282: 19133–19143, 2007. 173. Rodriguez-Rocha H, Garcia-Garcia A, Pickett C, Li S, Jones J, Chen H, Webb B, Choi J, Zhou Y, Zimmerman MC, and Franco R. Compartmentalized oxidative stress in dopaminergic cell death induced by pesticides and complex I inhibitors: Distinct roles of superoxide anion and superoxide dismutases. Free Radic Biol Med 61C: 370– 383, 2013. 174. Roma LP, Duprez J, Takahashi HK, Gilon P, Wiederkehr A, and Jonas JC. Dynamic measurements of mitochondrial hydrogen peroxide concentration and glutathione redox state in rat pancreatic b-cells using ratiometric fluorescent proteins: confounding effects of pH with HyPer but not roGFP1. Biochem J 441: 971–978, 2012.

709

175. Roma LP, Pascal SM, Duprez J, and Jonas JC. Mitochondrial oxidative stress contributes differently to rat pancreatic islet cell apoptosis and insulin secretory defects after prolonged culture in a low non-stimulating glucose concentration. Diabetologia 55: 2226–2237, 2012. 176. Romero-Aristizabal C, Marks DS, Fontana W, and Apfeld J. Regulated spatial organization and sensitivity of cytosolic protein oxidation in Caenorhabditis elegans. Nat Commun 5: 5020, 2014. 177. Rosenwasser S, Graff van Creveld S, Schatz D, Malitsky S, Tzfadia O, Aharoni A, Levin Y, Gabashvili A, Feldmesser E, and Vardi A. Mapping the diatom redox-sensitive proteome provides insight into response to nitrogen stress in the marine environment. Proc Natl Acad Sci U S A 111: 2740–2745, 2014. 178. Rosenwasser S, Rot I, Meyer AJ, Feldman L, Jiang K, and Friedman H. A fluorometer-based method for monitoring oxidation of redox-sensitive GFP (roGFP) during development and extended dark stress. Physiol Plant 138: 493– 502, 2010. 179. Rosenwasser S, Rot I, Sollner E, Meyer AJ, Smith Y, Leviatan N, Fluhr R, and Friedman H. Organelles contribute differentially to reactive oxygen species-related events during extended darkness. Plant Physiol 156: 185–201, 2011. 180. Rosnow J, Yerramsetty P, Berry JO, Okita TW, and Edwards GE. Exploring mechanisms linked to differentiation and function of dimorphic chloroplasts in the single cell C4 species Bienertia sinuspersici. BMC Plant Biol 14: 34, 2014. 181. Rossignol R, Gilkerson R, Aggeler R, Yamagata K, Remington SJ, and Capaldi RA. Energy substrate modulates mitochondrial structure and oxidative capacity in cancer cells. Cancer Res 64: 985–993, 2004. 182. Rouhier N, Lemaire SD, and Jacquot JP. The role of glutathione in photosynthetic organisms: emerging functions for glutaredoxins and glutathionylation. Annu Rev Plant Biol 59: 143–166, 2008. 183. Rowlands DJ, Islam MN, Das SR, Huertas A, Quadri SK, Horiuchi K, Inamdar N, Emin MT, Lindert J, Ten VS, Bhattacharya S, and Bhattacharya J. Activation of TNFR1 ectodomain shedding by mitochondrial Ca2 + determines the severity of inflammation in mouse lung microvessels. J Clin Invest 121: 1986–1999, 2011. 184. Sabharwal SS, Waypa GB, Marks JD, and Schumacker PT. Peroxiredoxin-5 targeted to the mitochondrial intermembrane space attenuates hypoxia-induced reactive oxygen species signalling. Biochem J 456: 337–346, 2013. 185. Samalova M, Meyer AJ, Gurr SJ, and Fricker MD. Robust anti-oxidant defences in the rice blast fungus Magnaporthe oryzae confer tolerance to the host oxidative burst. New Phytol 201: 556–573, 2014. 186. Samiec PS, Drews-Botsch C, Flagg EW, Kurtz JC, Sternberg P, Jr., Reed RL, and Jones DP. Glutathione in human plasma: decline in association with aging, agerelated macular degeneration, and diabetes. Free Radic Biol Med 24: 699–704, 1998. 187. Sanchez-Alvarez M, Finger F, Arias-Garcia Mdel M, Bousgouni V, Pascual-Vargas P, and Bakal C. Signaling networks converge on TORC1-SREBP activity to promote endoplasmic reticulum homeostasis. PLoS One 9: e101164, 2014. 188. Sanchez-Padilla J, Guzman JN, Ilijic E, Kondapalli J, Galtieri DJ, Yang B, Schieber S, Oertel W, Wokosin D, Schumacker PT, and Surmeier DJ. Mitochondrial oxidant


710

189.


190.

191.

192.

193.

194.

195.

196.

197.

198.

199.

199a.

200.

stress in locus coeruleus is regulated by activity and nitric oxide synthase. Nat Neurosci 17: 832–840, 2014. Sarkar DD, Edwards SK, Mauser JA, Suarez AM, Serowoky MA, Hudok NL, Hudok PL, Nunez M, Weber CS, Lynch RM, Miyashita O, and Tsao TS. Increased redoxsensitive green fluorescent protein reduction potential in the endoplasmic reticulum following glutathione-mediated dimerization. Biochemistry 52: 3332–3345, 2013. Schaedler TA, Thornton JD, Kruse I, Schwarzla¨nder M, Meyer AJ, van Veen HW, and Balk J. A conserved mitochondrial ATP-binding cassette transporter exports glutathione polysulfide for cytosolic metal cofactor assembly. J Biol Chem 289: 23264–23274, 2014. Schnaubelt D, Queval G, Dong Y, Diaz-Vivancos P, Makgopa ME, Howell G, De Simone A, Bai J, Hannah MA, and Foyer CH. Low glutathione regulates gene expression and the redox potentials of the nucleus and cytosol in Arabidopsis thaliana. Plant Cell Environ 38: 266– 279, 2015. Schumacher J, Simon A, Cohrs KC, Viaud M, and Tudzynski P. The transcription factor BcLTF1 regulates virulence and light responses in the necrotrophic plant pathogen Botrytis cinerea. PLoS Genet 10: e1004040, 2014. Schwarzer C, Fischer H, Kim EJ, Barber KJ, Mills AD, Kurth MJ, Gruenert DC, Suh JH, Machen TE, and Illek B. Oxidative stress caused by pyocyanin impairs CFTR Cltransport in human bronchial epithelial cells. Free Radic Biol Med 45: 1653–1662, 2008. Schwarzer C, Fu Z, Fischer H, and Machen TE. Redoxindependent activation of NF-jB by Pseudomonas aeruginosa pyocyanin in a cystic fibrosis airway epithelial cell line. J Biol Chem 283: 27144–27153, 2008. Schwarzer C, Fu Z, Patanwala M, Hum L, Lopez-Guzman M, Illek B, Kong W, Lynch SV, and Machen TE. Pseudomonas aeruginosa biofilm-associated homoserine lactone C12 rapidly activates apoptosis in airway epithelia. Cell Microbiol 14: 698–709, 2012. Schwarzer C, Illek B, Suh JH, Remington SJ, Fischer H, and Machen TE. Organelle redox of CF and CFTR-corrected airway epithelia. Free Radic Biol Med 43: 300– 316, 2007. Schwarzer C, Ravishankar B, Patanwala M, Shuai S, Fu Z, Illek B, Fischer H, and Machen TE. Thapsigargin blocks Pseudomonas aeruginosa homoserine lactone-induced apoptosis in airway epithelia. Am J Physiol Cell Physiol 306: C844–C855, 2014. Schwarzla¨nder M, Fricker MD, Mu¨ller C, Marty L, Brach T, Novak J, Sweetlove LJ, Hell R, and Meyer AJ. Confocal imaging of glutathione redox potential in living plant cells. J Microsc 231: 299–316, 2008. Schwarzla¨nder M, Fricker MD, and Sweetlove LJ. Monitoring the in vivo redox state of plant mitochondria: effect of respiratory inhibitors, abiotic stress and assessment of recovery from oxidative challenge. Biochim Biophys Acta 1787: 468–475, 2009. Schwarzla¨nder M, Logan DC, Johnston IG, Jones NS, Meyer AJ, Fricker MD, and Sweetlove LJ. Pulsing of membrane potential in individual mitochondria: a stressinduced mechanism to regulate respiratory bioenergetics in Arabidopsis. Plant Cell 24: 1188–1201, 2012. Schwarzla¨nder M, Wagner S, Ermakova YG, Belousov VV, Radi R, Beckman JS, Buettner GR, Demaurex N, Duchen MR, Forman HJ, Fricker MD, Gems D, Halestrap AP, Halliwell B, Jakob U, Johnston IG, Jones NS, Logan DC,

201. 202.

203.

204. 205.

206.

207.

208.

209.

210.

211.

212.

213.

214.

215.

Morgan B, Muller FL, Nicholls DG, Remington SJ, Schumacker PT, Winterbourn CC, Sweetlove LJ, Meyer AJ, Dick TP, and Murphy MP. The ‘mitoflash’ probe cpYFP does not respond to superoxide. Nature 514: E12–E14, 2014. Searle JS, Li B, and Du W. Targeting Rb mutant cancers by inactivating TSC2. Oncotarget 1: 228–232, 2010. Seiler C, Davuluri G, Abrams J, Byfield FJ, Janmey PA, and Pack M. Smooth muscle tension induces invasive remodeling of the zebrafish intestine. PLoS Biol 10: e1001386, 2012. Shah MR, Wedgwood S, Czech L, Kim GA, Lakshminrusimha S, Schumacker PT, Steinhorn RH, and Farrow KN. Cyclic stretch induces inducible nitric oxide synthase and soluble guanylate cyclase in pulmonary artery smooth muscle cells. Int J Mol Sci 14: 4334–4348, 2013. Shen Y, Rosendale M, Campbell RE, and Perrais D. pHuji, a pH-sensitive red fluorescent protein for imaging of exo- and endocytosis. J Cell Biol 207: 419–432, 2014. Shimi T, Butin-Israeli V, Adam SA, Hamanaka RB, Goldman AE, Lucas CA, Shumaker DK, Kosak ST, Chandel NS, and Goldman RD. The role of nuclear lamin B1 in cell proliferation and senescence. Genes Dev 25: 2579–2593, 2011. Sivakumar K, Mukherjee M, Hsin IC, Yingdan Z, Ji L, and Cao B. Surface display of roGFP for monitoring redox status of extracellular microenvironments in Shewanella oneidensis biofilms. Biotechnol Bioeng 112: 512–520, 2015. Sobotta MC, Barata AG, Schmidt U, Mueller S, Millonig G, and Dick TP. Exposing cells to H2O2: a quantitative comparison between continuous low-dose and one-time highdose treatments. Free Radic Biol Med 60: 325–335, 2013. Sobotta MC, Liou W, Stocker S, Talwar D, Oehler M, Ruppert T, Scharf AN, and Dick TP. Peroxiredoxin-2 and STAT3 form a redox relay for H2O2 signaling. Nat Chem Biol 11: 64–70, 2015. Sparkes I, Tolley N, Aller I, Svozil J, Osterrieder A, Botchway S, Mu¨ller C, Frigerio L, and Hawes C. Five Arabidopsis reticulon isoforms share endoplasmic reticulum location, topology, and membrane-shaping properties. Plant Cell 22: 1333–1343, 2010. Squires S, Christians E, Riedel M, Timothy D, Rodesch CK, Marvin J, and Benjamin I. Effects of redox state on the efficient uptake of cell permeable peptide in mammalian cells. Open Biochem J 7: 54–65, 2013. Stonebloom S, Brunkard JO, Cheung AC, Jiang K, Feldman L, and Zambryski P. Redox states of plastids and mitochondria differentially regulate intercellular transport via plasmodesmata. Plant Physiol 158: 190– 199, 2012. Su T, Zhang Z, and Luo Q. Ratiometric fluorescence imaging of dual bio-molecular events in single living cells using a new FRET pair mVenus/mKOkappa-based biosensor and a single fluorescent protein biosensor. Biosens Bioelectron 31: 292–298, 2012. Sugiura K, Nagai T, Nakano M, Ichinose H, Nakabayashi T, Ohta N, and Hisabori T. Redox sensor proteins for highly sensitive direct imaging of intracellular redox state. Biochem Biophys Res Commun 457: 242–248, 2015. Sun A, Nie S, and Xing D. Nitric oxide-mediated maintenance of redox homeostasis contributes to NPR1-dependent plant innate immunity triggered by lipopolysaccharides. Plant Physiol 160: 1081–1096, 2012. Sun QA, Su D, Novoselov SV, Carlson BA, Hatfield DL, and Gladyshev VN. Reaction mechanism and regulation


216.

217.


218.

219.

220.

221.

222.

223. 224.

225. 226.

227.

228.

229.

230.

of mammalian thioredoxin/glutathione reductase. Biochemistry 44: 14528–14537, 2005. Takahashi HK, Santos LR, Roma LP, Duprez J, Broca C, Wojtusciszyn A, and Jonas JC. Acute nutrient regulation of the mitochondrial glutathione redox state in pancreatic b-cells. Biochem J 460: 411–423, 2014. Tantama M, Hung YP, and Yellen G. Imaging intracellular pH in live cells with a genetically encoded red fluorescent protein sensor. J Am Chem Soc 133: 10034–10037, 2011. Tantama M, Martinez-Francois JR, Mongeon R, and Yellen G. Imaging energy status in live cells with a fluorescent biosensor of the intracellular ATP-to-ADP ratio. Nat Commun 4: 2550, 2013. Tatone C, Heizenrieder T, Di Emidio G, Treffon P, Amicarelli F, Seidel T, and Eichenlaub-Ritter U. Evidence that carbonyl stress by methylglyoxal exposure induces DNA damage and spindle aberrations, affects mitochondrial integrity in mammalian oocytes and contributes to oocyte ageing. Hum Reprod 26: 1843–1859, 2011. Tome ME, Lee K, Jaramillo MC, and Briehl MM. Mitochondria are the primary source of the H2O2 signal for glucocorticoid-induced apoptosis of lymphoma cells. Exp Ther Med 4: 237–242, 2012. Tsunoda S, Avezov E, Zyryanova A, Konno T, MendesSilva L, Pinho Melo E, Harding HP, and Ron D. Intact protein folding in the glutathione-depleted endoplasmic reticulum implicates alternative protein thiol reductants. Elife 3: e03421, 2014. Van Laer K, Buts L, Foloppe N, Vertommen D, Van Belle K, Wahni K, Roos G, Nilsson L, Mateos LM, Rawat M, van Nuland NA, and Messens J. Mycoredoxin-1 is one of the missing links in the oxidative stress defence mechanism of Mycobacteria. Mol Microbiol 86: 787–804, 2012. van Lith M, Tiwari S, Pediani J, Milligan G, and Bulleid NJ. Real-time monitoring of redox changes in the mammalian endoplasmic reticulum. J Cell Sci 124: 2349–2356, 2011. Van Vranken JG, Bricker DK, Dephoure N, Gygi SP, Cox JE, Thummel CS, and Rutter J. SDHAF4 promotes mitochondrial succinate dehydrogenase activity and prevents neurodegeneration. Cell Metab 20: 241–252, 2014. Veech RL, Eggleston LV, and Krebs HA. The redox state of free nicotinamide-adenine dinucleotide phosphate in the cytoplasm of rat liver. Biochem J 115: 609–619, 1969. Vesce S, Jekabsons MB, Johnson-Cadwell LI, and Nicholls DG. Acute glutathione depletion restricts mitochondrial ATP export in cerebellar granule neurons. J Biol Chem 280: 38720–38728, 2005. Vevea JD, Wolken DM, Swayne TC, White AB, and Pon LA. Ratiometric biosensors that measure mitochondrial redox state and ATP in living yeast cells. J Vis Exp 2013 DOI: 10.3791/5063. Wages PA, Silbajoris R, Speen A, Brighton L, Henriquez A, Tong H, Bromberg PA, Simmons SO, and Samet JM. Role of H2O2 in the oxidative effects of zinc exposure in human airway epithelial cells. Redox Biol 3: 47–55, 2014. Wagner S, Dantz C, Flebbe H, Azizian A, Sag CM, Engels S, Mollencamp J, Dybkova N, Islam T, Shah AM, and Maier LS. NADPH oxidase 2 mediates angiotensin IIdependent cellular arrhythmias via PKA and CaMKII. J Mol Cell Cardiol 75: 206–215, 2014. Wang P, Hummel E, Osterrieder A, Meyer AJ, Frigerio L, Sparkes I, and Hawes C. KMS1 and KMS2, two plant endoplasmic reticulum proteins involved in the early secretory pathway. Plant J 66: 613–628, 2011.

711

231. Wang S, Park S, Kodali VK, Han J, Yip T, Chen Z, Davidson NO, and Kaufman RJ. Identification of protein disulfide isomerase 1 as a key isomerase for disulfide bond formation in apolipoprotein B100. Mol Biol Cell 26: 594– 604, 2014. 232. Wang X, Schwarzer C, Hybiske K, Machen TE, and Stephens RS. Developmental stage oxidoreductive states of Chlamydia and infected host cells. MBio 5: e01924, 2014. 233. Waypa GB, Marks JD, Guzy R, Mungai PT, Schriewer J, Dokic D, and Schumacker PT. Hypoxia triggers subcellular compartmental redox signaling in vascular smooth muscle cells. Circ Res 106: 526–535, 2010. 234. Waypa GB, Osborne SW, Marks JD, Berkelhamer SK, Kondapalli J, and Schumacker PT. Sirtuin 3 deficiency does not augment hypoxia-induced pulmonary hypertension. Am J Respir Cell Mol Biol 49: 885–891, 2013. 235. Wedgwood S, Lakshminrusimha S, Fukai T, Russell JA, Schumacker PT, and Steinhorn RH. Hydrogen peroxide regulates extracellular superoxide dismutase activity and expression in neonatal pulmonary hypertension. Antioxid Redox Signal 15: 1497–1506, 2011. 236. Weinberg F, Hamanaka R, Wheaton WW, Weinberg S, Joseph J, Lopez M, Kalyanaraman B, Mutlu GM, Budinger GR, and Chandel NS. Mitochondrial metabolism and ROS generation are essential for Kras-mediated tumorigenicity. Proc Natl Acad Sci U S A 107: 8788–8793, 2010. 237. Weller J, Kizina KM, Can K, Bao G, and Mu¨ller M. Response properties of the genetically encoded optical H2O2 sensor HyPer. Free Radic Biol Med 76: 227–241, 2014. 238. Wierer S, Peter S, Elgass K, Mack HG, Bieker S, Meixner AJ, Zentgraf U, and Schleifenbaum F. Determination of the in vivo redox potential by one-wavelength spectro-microscopy of roGFP. Anal Bioanal Chem 403: 737–744, 2012. 239. Williams B, Kabbage M, Kim HJ, Britt R, and Dickman MB. Tipping the balance: Sclerotinia sclerotiorum secreted oxalic acid suppresses host defenses by manipulating the host redox environment. PLoS Pathog 7: e1002107, 2011. 240. Wittig R, Richter V, Wittig-Blaich S, Weber P, Strauss WS, Bruns T, Dick TP, and Schneckenburger H. Biosensor-expressing spheroid cultures for imaging of druginduced effects in three dimensions. J Biomol Screen 18: 736–743, 2013. 241. Wolf AM, Asoh S, Hiranuma H, Ohsawa I, Iio K, Satou A, Ishikura M, and Ohta S. Astaxanthin protects mitochondrial redox state and functional integrity against oxidative stress. J Nutr Biochem 21: 381–389, 2010. 242. Wolf AM, Asoh S, Ohsawa I, and Ohta S. Imaging mitochondrial redox environment and oxidative stress using a redox-sensitive fluorescent protein. J Nippon Med Sch 75: 66–67, 2008. 243. Wolf AM, Nishimaki K, Kamimura N, and Ohta S. Realtime monitoring of oxidative stress in live mouse skin. J Invest Dermatol 134: 1701–1709, 2014. 244. Xie H, Hou S, Jiang J, Sekutowicz M, Kelly J, and Bacskai BJ. Rapid cell death is preceded by amyloid plaque-mediated oxidative stress. Proc Natl Acad Sci U S A 110: 7904–7909, 2013. 245. Xu X, von Lohneysen K, Soldau K, Noack D, Vu A, and Friedman JS. A novel approach for in vivo measurement of mouse red cell redox status. Blood 118: 3694–3697, 2011. 246. Yu S, Qin W, Zhuang G, Zhang X, Chen G, and Liu W. Monitoring oxidative stress and DNA damage induced by


712

247.


248.

249.

250.

251. 252.

253. 254.

heavy metals in yeast expressing a redox-sensitive green fluorescent protein. Curr Microbiol 58: 504–510, 2009. Yu X, Pasternak T, Eiblmeier M, Ditengou F, Kochersperger P, Sun J, Wang H, Rennenberg H, Teale W, Paponov I, Zhou W, Li C, Li X, and Palme K. Plastidlocalized glutathione reductase2-regulated glutathione redox status is essential for Arabidopsis root apical meristem maintenance. Plant Cell 25: 4451–4468, 2013. Zechmann B, Liou LC, Koffler BE, Horvat L, Tomasic A, Fulgosi H, and Zhang Z. Subcellular distribution of glutathione and its dynamic changes under oxidative stress in the yeast Saccharomyces cerevisiae. FEMS Yeast Res 11: 631–642, 2011. Zechmann B, Mauch F, Sticher L, and Mu¨ller M. Subcellular immunocytochemical analysis detects the highest concentrations of glutathione in mitochondria and not in plastids. J Exp Bot 59: 4017–4027, 2008. Zhang H, Limphong P, Pieper J, Liu Q, Rodesch CK, Christians E, and Benjamin IJ. Glutathione-dependent reductive stress triggers mitochondrial oxidation and cytotoxicity. FASEB J 26: 1442–1451, 2012. Zhang Y, Marsboom G, Toth PT, and Rehman J. Mitochondrial respiration regulates adipogenic differentiation of human mesenchymal stem cells. PLoS One 8: e77077, 2013. Zhao Y, Araki S, Wu J, Teramoto T, Chang YF, Nakano M, Abdelfattah AS, Fujiwara M, Ishihara T, Nagai T, and Campbell RE. An expanded palette of genetically encoded Ca2 + indicators. Science 333: 1888–1891, 2011. Zhao Y and Yang Y. Profiling metabolic states with genetically encoded fluorescent biosensors for NADH. Curr Opin Biotechnol 31C: 86–92, 2014. ˚ , Neubert TA, and Ron Zito E, Melo EP, Yang Y, Wahlander A D. Oxidative protein folding by an endoplasmic reticulumlocalized peroxiredoxin. Mol Cell 40: 787–797, 2010.

Address correspondence to: Dr. Markus Schwarzla¨nder Plant Energy Biology Lab Department Chemical Signalling Institute of Crop Science and Resource Conservation (INRES) University of Bonn Friedrich-Ebert-Allee 144 Bonn 53113 Germany E-mail: [email protected]

Dr. Bruce Morgan Cellular Biochemistry University of Kaiserslautern Erwin-Schro¨dinger-Strasse 13 Kaiserslautern 67663 Germany E-mail: [email protected] Date of first submission to ARS Central, January 23, 2015; date of final revised submission, March 19, 2015; date of acceptance, April 9, 2015.

Abbreviations Used E ¼ redox potential EGSH ¼ glutathione redox potential EMSH ¼ mycothiol redox potential ER ¼ endoplasmic reticulum FLIM ¼ fluorescence lifetime imaging FP ¼ fluorescent protein FRET ¼ Fo¨rster resonance energy transfer GR ¼ glutathione reductase Grx ¼ glutaredoxin hGrx ¼ human glutaredoxin yGrx ¼ yeast glutaredoxin GSH ¼ glutathione (reduced) GSSG ¼ glutathione disulfide (oxidized) H2 O2 ¼ hydrogen peroxide IMS ¼ mitochondrial intermembrane space Mrx ¼ mycoredoxin MSH ¼ mycothiol (reduced) MSSM ¼ mycothiol (oxidized) NOX ¼ NADPH oxidase NPR1 ¼ nonexpresser of PR (pathogen response) genes 1 Orp1 ¼ oxidant receptor protein 1 (glutathione peroxidase 3 from S. cerevisiae) PDI ¼ protein disulfide isomerase r.b.c. ¼ red blood cells RNS ¼ reactive nitrogen species roGFP ¼ redox-sensitive green fluorescent protein ROS ¼ reactive oxygen species rxYFP ¼ redox-sensitive yellow fluorescent protein Trx ¼ thioredoxin

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