Development of a rechargeable optical hydrogen peroxide sensor – sensor design and biological application

Abstract

Hydrogen peroxide (H₂O₂) is an important member of the reactive oxygen species (ROS) family. Among ROS, H₂O₂ is considered the most long-lived and can accumulate inside and outside of cells, where it is involved in both vital (signaling) and deadly (toxic) reactions depending on its concentration. Quantifying H₂O₂ within biological samples is challenging and often not possible. Here we present a quasi-reversible fiber-optic sensor capable of measuring H₂O₂ concentrations ranging from 1–100 μM within different biological samples. Based on a Prussian blue/white redox cycle and a simple sensor recharging and readout strategy, H₂O₂ can be measured with high spatial (∼500 μm) and temporal (∼30 s) resolution. The sensor has a broad applicability both in complex environmental and biomedical systems, as demonstrated by (i) H₂O₂ concentration profile measurements in natural photosynthetic biofilms under light stress reaching H₂O₂ concentrations as high as 15 μM, and (ii) the quantification of the transient increase of the extracellular concentration of H₂O₂ during stimulation of neutrophils.

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1. Introduction

Hydrogen peroxide (H₂O₂) has two important roles in living organisms;¹ on the one hand H₂O₂ is associated with cell death, dysfunction and ageing,^2,3 on the other hand H₂O₂ is also involved in vital processes like cell signaling⁴ and combatting microbial intruders.⁵ As a reactive oxygen species (ROS), H₂O₂ is involved in a variety of redox processes within organisms.⁶ In contrast to less stable and more reactive ROS such as superoxide anion or hydroxyl radical, H₂O₂ exhibits a longer lifetime and a higher steady state concentration and can thus accumulate within a cell and even diffuse out.⁷

Maintaining ROS levels below certain threshold concentrations is essential for cellular survival,² but despite of the development of new fluorescent^8–10 and genetically encoded probes,¹¹ quantification of ROS concentrations remains challenging and is often not conducted in biomedical studies due to a lack of suitable methods.^12,13 While several probes (with varying specificity) enable visualization of the localization and relative differences of certain ROS,^14,15 the lack of quantitative data is recognized as a main bottle neck in understanding redox processes within cells or tissues.¹⁶

A possible alternative to fluorescent probes could be the use of mini- or microsensors. Optical¹⁷ as well as electrochemical¹⁸ microsensors have been used in a variety of biological systems and revealed quantitative information on small molecules like O₂,¹⁹ H⁺(pH),²⁰ H₂S,²¹ N₂O²² or NO.²³ Microsensors with tip diameters well below 100 μm are now commercially available and facilitate scientist to measure a variety of analytes at high spatio-temporal resolution. As those sensors are still bigger or at best in the same size range as individual cells, the most promising member of the ROS family to measure with microsensors is H₂O₂ as it is most likely to be found outside cells. Several electrochemical H₂O₂ sensor concepts exist^24,25 including some strategies towards intracellular measurements using nanoelectrodes.^26–28 Researchers within the field are very active in terms of modifying the used electrodes in order to reduce the overpotential and improve electrode kinetics.²⁹ One of the most important materials used to modify electrodes is Prussian blue (PB),^30,31i.e., ferric hexacyanoferrate. By modifying electrodes with PB, the sensitivity and selectivity of electrochemical H₂O₂ sensors can be drastically improved.³¹ PB is often considered an “artificial peroxidase” due to its rather specific catalytic activity towards H₂O₂.³² In terms of (reversible) optical H₂O₂ sensors only a few sensing principles³³ have been reported, but they failed to be applicable in biological systems due to lack of specificity.

Recently, the potential of exploiting the redox reaction induced change in the optical properties of PB has been realized.^34,35 It was shown that upon exposure to a reducing agent, PB can be reduced to colorless Prussian white (PW) than can be oxidized back to PB by H₂O₂. Regeneration of the sensor was possible, but the kinetics were rather slow and the reduction and oxidation steps were separated in space compromising real-time sensing.³⁴

In this study, we present a new quasi-reversible luminescence-based optical H₂O₂ sensor using PB as sensing element with fast kinetics and high stability. Recharging can be accomplished in close proximity to the sample using a “recharger gel” (containing ascorbic acid donating electrons to PB oxidized by H₂O₂). By using a differential readout scheme, we measured the rate of oxidation which is directly linked to the H₂O₂ concentration. We describe the sensor design and fabrication along with its measuring characteristics and demonstrate its application for quantitative H₂O₂ measurements in environmental and biomedical science.

2. Experimental section

Chromium(III)-Activated Yttrium Aluminum Borate (Cr-YAB) was synthesized and characterized as reported elsewhere.³⁶ Polyurethane hydrogel (Hydromed D4) was obtained from AdvanSource Biomaterials (http://www.advbiomaterials.com). Multimode low OH fibers with a core diameter of 400 μm, 30 μm cladding and equipped with ST connectors were purchased from Laser Components Nordic. The protective plastic coating was removed using standard stripping tools from RS Components. Micromanipulator with a motorized z-axis, optical O₂ microsensors (50 μm tip diameter) and the fiber optical phase fluorimeter FirestingII were obtained from Pyro Science (Aachen, Germany, pyro-science.com).

2.1. Sensor preparation

2.2 mg of Prussian blue (PB) and 140 mg of Cr-YAB were dispersed in 1 g of a 10% w/w D4 in ethanol/water (9/1) and the flat-cut end of an optical fiber was dip-coated with this dispersion. In detail, a small drop of the dispersion was placed on the tip of a flat spatula. The flat-cut fiber tip was slowly dipped into the drop until the entire tip was covered with the dispersion (as judged by naked eye or with a magnification glass). After slow retraction of the fiber from the dispersion, the sensor was dried at ambient air for half an hour and was ready to use thereafter.

2.2. Recharging gel

To recharge/regenerate the sensor a 1% agarose gel containing 0.05 M of ascorbic acid in PBS (phosphate-buffered saline) adjusted to pH 7.4 was used. The ascorbic acid was dissolved in PBS, the buffer adjusted and subsequently the agar was added and dissolved at elevated temperatures. Around 3 ml of the hot solution was filled in 15 ml centrifugation tubes (vwr.com). After hardening the recharging gels could be stored in the fridge for several weeks.

2.3. Measurement setup

The coated optical fiber was fixed in a Pasteur pipet using a rubber stopper and the pipet was mounted on a motorized micromanipulator controlled by the manufacturer's profiling software (Profix, Pyroscience GmbH, Germany). This allowed for rapid and reproducible vertical positioning of the sensor tip. A tube with the recharging gel was fixed below the sensor, the bottom of the tube was cut open, and the sensor was lowered through the gel in the tube. Calibration solutions or samples were placed underneath the tube opening and it was ensured that the recharging gel was in contact with the sample (no air between); see Fig. 2 and S10.† In general the following settings were used: the sensor was charged in the gel for 17 seconds and was lowered with a speed of 2 mm s⁻¹ into the sample, where it was left for 5 seconds and then retracted into the gel. Measuring signals were recorded using the logger software of the fiber-optic phase fluorimeter (FirestingII, PyroScience GmbH, Germany). The modulation frequency of the meter was set to 470 Hz, the LED intensity and amplification were set to maximum levels, and the measurement time 1 data point each 0.75 s. The experimental setup is shown in Fig. 2. If not stated otherwise the measurements were performed at room temperature (22 °C) and checked with a digital thermometer. Every sensor was calibrated prior to and after the measurement.

2.4. Biofilm measurements

Sediment samples covered with a well-developed brownish-green photosynthetic biofilm of diatoms and cyanobacteria were collected at a brackish seawater site at Løgstør Bredning, Limfjorden near the city of Aggersund, Denmark (57°00′ 02.15 N, 9°17′ 12.89 E). The samples were mounted in a flow chamber and flushed with a constant flow of aerated seawater from a seawater reservoir. The temperature of the seawater was kept constant with the help of an aquarium heater and was checked constantly with an electric thermometer (testo 110; http://www.testo.de). The biofilm was illuminated with a fiber-optic tungsten halogen lamp equipped with a collimating lens (KL-2500, Schott GmbH, Germany). The scalar irradiance at the biofilm surface was determined with an underwater quantum irradiance meter (ULM-500, WALZ, walz.com). The position of the microsensor measuring tips relative to the biofilm-surface were determined using an USB microscope (Dino-lite digital microscope, dino-light.eu). O₂ concentration profiles were measured with a commercial fiber-optic O₂ microsensor with 50 μm tip diameter (Pyro Science) that were calibrated according to the manufacturer.

2.5. PMN measurements

Experimental details on the PMN measurements can be found in the ESI.†

2.6. Data analysis

All data was analyzed using OriginPro 9 (Microcal, USA). As the sensor is based on a kinetic measuring principle, the change of signal over time correlates to the analyte concentration (see Fig. 3 and S12†). The intensity traces generated by the measurement device were imported and the first derivative was taken in order to obtain ΔS/Δt traces. As the change from PW to PB results in a decrease of the signal over time, −ΔS/Δt were extracted from the differential plot and correlated to the known H₂O₂ concentrations in case of calibrations. For the real measurements, measured −ΔS/Δt values were then converted into H₂O₂ concentrations with the help of the previously generated calibration curve that showed a linear correlation between −ΔS/Δt and [H₂O₂].

3. Results

3.1. Sensor principle and design

The optical H₂O₂ sensor employs the pigment Prussian blue (PB) as sensing element undergoing a H₂O₂-dependent redox cycle. Prussian blue, i.e., ferric hexacyanoferrate, is one of the first discovered synthetic pigments³⁷ and can be easily reduced to its uncolored form Prussian white (PW),³⁸ that reacts rather specifically with H₂O₂ restoring the oxidized and deep blue-colored form (PB) and thus coupling the color change to H₂O₂ concentration (Fig. 1A). To enable a fast redox-cycling, i.e., reconditioning of PB to PW after H₂O₂ exposure, we constructed a recharger gel, containing ascorbic acid as a reductant that could be placed in close proximity to the sample.

Fig. 1 Prussian blue (PB) based optical H₂O₂ sensor concept. (A) Redox chemistry involved in the presented sensor. PB gets reduced when in the recharging gel, and reduced PW can be oxidized by H₂O₂ when the sensor is immersed into the sample. (B) Spectral properties of the indicator (PB/PW) and the coupled emitter Cr-YAB. Orange and blue curves show absorption spectra of PW and PB, respectively. Cr-YAB excitation (solid line) and luminescence emission spectra (dashed line) are shown in green.

In order to produce a miniaturized optical fiber-based sensor, the H₂O₂ – induced color change of PB was coupled to a change in luminescence from chromium(III)-Activated Yttrium Aluminum Borate (Cr-YAB), a highly (photo)stable luminescent crystal.³⁶ The excitation and emission spectra of Cr-YAB overlap with the broad absorption spectrum of PB (Fig. 1B), where oxidized PB will reduce the emission of Cr-YAB significantly due to the inner-filter effect, while colorless PW will not cause signal reduction. The spectral characteristics of the combined PB/Cr-YAB indicator immobilized on the tip of an optical fiber are compatible with a commercial fiber-optic meter for luminescence amplitude and lifetime measurements (FireStingII, Pyro Science GmbH, Germany). This instrument uses a 625 nm LED as excitation source and collects luminescence above 700 nm (RG9 glass filter) and enables flexible use with different types of optical fibers connected via a standard ST connector. An additional benefit of the emitter is that Cr-YAB is not susceptible to photobleaching and only shows cross-sensitivity to temperature (as every sensor) while being insensitive to other analytes like O₂ or pH.³⁶

The optical fiber tip with the immobilized PB/Cr-YAB indicator can be moved through the recharger gel with the help of a motorized micromanipulator. This enables fast measurements, as the sensor can be dipped in the sample for a few seconds and recharged directly thereafter by retracting it into the gel (Fig. 2). One measurement and recharging cycle takes ∼30 seconds, which is fast enough to follow many relevant biological processes involving H₂O₂. In terms of spatial resolution the size of the fiber tip (in this case 400 μm) and the diffusibility of H₂O₂ have to be considered. The diffusion coefficient of H₂O₂ in water, D(H₂O₂) at room temperature is ∼1.4 × 10⁻⁵ cm² s⁻¹.³⁹ Within a t = 5 s measuring period, peroxide can thus diffuse a distance of ∼(2Dt)^1/2 = 118 μm. As the sensor tip is larger than diffusive distance of H₂O₂ we conclude that a spatial resolution of <500 μm can be achieved.

Fig. 2 Schematic drawing of the H₂O₂ sensor measurement setup. The optical fiber sensor is fixed on a motorized micromanipulator that moves the sensor tip in and out of the recharging gel and the sample. The photographs show the fiber tip with immobilized PB/Cr-YAB in its oxidized and reduced state.

As the reaction of PW with H₂O₂ is responsible for the change in signal intensity, a differential readout mode was chosen. By using the first derivative of the luminescence signal intensity, a more robust sensor readout was obtained. Even in cases when the recharging was not fully completed, the measured decline in signal intensity upon H₂O₂ exposure could be quantitatively correlated to the analyte concentration. By using differential signal readout, the sensor is less affected by optical interferences such as ambient light as long as light intensity does not change dramatically within the measurement cycle. The readout principle is shown in Fig. 3, where an example of the luminescence signal dynamics, its first derivative, and the obtained calibration curve for different H₂O₂ concentrations are shown. From the calibration curve of this sensor a detection limit of 0.4 μM and a limit of quantification of 1.3 μM was determined. This makes the reported sensor suitable for measurements in the range between 1 and 100 μM. We stress that the novel H₂O₂ sensor is not equilibrium based, in contrast to e.g. optical O₂ sensors. The new sensor is based on the H₂O₂-dependent kinetics of the optical indicator redox status. This means that it is not necessary to await equilibrium and enables fast data acquisition; <30 s between measurement points. The kinetics based sensor concept also has implications for sensor stability and sensitivity.

Fig. 3 (A) Raw sensor luminescence intensity trace during calibration in eight different H₂O₂ containing solutions (pH = 7.4). (B) Differentiated sensor signal trace showing a higher reproducibility than the original raw signal data. (C) Calibration curve obtained from the differential readout (mean ± SD; n = 3).

3.2. Cross-sensitivities and limitations

As the H₂O₂-catalyzed conversion of PW to PB is responsible for the change in signal, all factors either stabilizing or destabilizing PW lead to cross-sensitivities. Obviously, temperature is affecting the sensitivity and therefore has to be kept as constant as possible. Additionally, we found that increased O₂ levels lead to an increase in sensor sensitivity. When calibrations were conducted in O₂ free and O₂ saturated water the sensitivity increased by ∼18% with rising oxygenation (see ESI Fig. S6†). Also the effect of pH on the sensor performance has to be taken into account. Increased pH leads to a decreased sensitivity (see ESI Fig. S5†). The calibration obtained at pH 9 exhibited a slope ∼20% less steep than a calibration curve obtained at pH 4. In contrast, calibration curves measured at pH 4 and 7.4 only showed a 7% difference in sensitivity. This can be explained by PW being less stable at increased pH. It was observed that only the PW form is prone to cause sensor instability and changes in sensitivity. The PB state was stable even at pH 9 for over 17 hours without showing any indicator leakage or decomposition that would lead to a signal increase (see ESI Fig. S1†). Obviously, the PB/PW redox couple is strongly affected by reducing agents. As ascorbic acid is used within the recharging gel, the sensor will be strongly responding to ascorbic acid. This ultimately limits the applicability in systems with high ascorbic acid concentrations. On the contrary, hydrogen sulfide (H₂S) and glutathione (GSH) did not affect the sensor signal (data not shown). The sensor response to other types of ROS was evaluated (see Fig. S7†) and no cross-sensitivity towards any of the tested ROS was found. An apparent response to superoxide could be attributed to H₂O₂ produced from dismutation. A technical aspect regarding cross-sensitivity is that ascorbic acid may diffuse out of the gel or H₂O₂ into the gel. We tried to reduce this effect by using a minimal contact area between the gel and the sample (diameter <5 mm). Obviously by using a 3 dimensional (xyz) micromanipulator recharging could be achieved more remote from the sample and would overcome this limitation. Further information on the sensor performance can be found in the ESI.†

3.3. Sensor stability

As every sensor is unique due to the fiber tip coating process, calibration before use is essential. It was observed that sensor sensitivity to H₂O₂ could vary quite dramatically; between −0.05 and −0.005 ΔS/Δt μM⁻¹. Therefore, a short (at least 4 point) calibration was obtained prior to every measurement series. Calibrations were obtained by diluting a fresh H₂O₂ solution in the respective medium (buffer). All calibrations showed high linearity, and recalibration after the measurement yielded identical calibration curves; recalibration was done to test for sensor drift throughout the measurement. The repeatability of the sensor reading was tested and showed a RSD of ≤5% (see Fig. S4†). The same sensor could be used for multiple subsequent measurements over several days. The main limitation in terms of sensor stability was the mechanical stability of the sensor coating. Typically before any other degradation was observed, the sensor chemistry detached from the optical fiber and a more stable immobilization of the sensor chemistry is under investigation.

3.4. Biological H₂O₂ measurements

We tested the new optical H₂O₂ sensor in several biological applications spanning from measurements in defined enzyme systems, over concentration profiling in a complex natural biofilm to quantification of H₂O₂ concentration dynamics in activated neutrophils.

3.4.1. Enzymatic reactions. We measured O₂ and H₂O₂ concentrations simultaneously in a buffered glucose solution upon addition of enzymes (Fig. 4A). Addition of glucose oxidase (GOX) caused a decline in O₂ concentration and a concomitant increase in H₂O₂ concentration. The decline in O₂ concentration within the first 600 s corresponded well to the increased concentration of H₂O₂ (−55 μM O₂, +59 μM H₂O₂) as expected from the enzymatic reaction scheme. Addition of catalase led to a decline in H₂O₂ concentration and a reduced O₂ consumption. Simultaneous addition of GOX and glucose lead to a second intermittent peak in H₂O₂ levels before the sample became anoxic and catalase activity extinguished the produced H₂O₂.

Fig. 4 (A) Dynamics of O₂ and H₂O₂ concentrations measured simultaneously with an O₂ micro-optode and the new H₂O₂ sensor in a buffered glucose solution (1 mM) upon addition of glucose oxidase (GOX) and catalase at the marked time points. The insert shows the chemical reactions involved. (B) Micro profiling of O₂ (solid line) and H₂O₂ (stars) concentrations in a natural photosynthetic biofilm under high irradiance (2000 μM photons m⁻² s⁻¹; red lines and symbols) and in the dark (black lines and symbols). The H₂O₂ profile shows the average of 3 measurements ± SD; for O₂ only one of the three measured and highly similar profiles is plotted. (C) Respiratory burst in activated neutrophils as shown by O₂ and H₂O₂ concentration dynamics in a PMN suspension (5 × 10⁶ cells per mL in Krebs–Ringer buffer at 37 °C) upon addition of an external stimuli (PMA) as indicated by an arrow. The insert shows a simplified version of the processes leading to H₂O₂ buildup.

3.4.2. Depth profiling of H₂O₂ concentration in a natural biofilm. The new sensor was used for measuring H₂O₂ concentration profiles in a complex natural biofilm from a coastal marine environment along with O₂ concentration profiles measured with an O₂ microsensor (Fig. 4B). The obtained O₂ profiles are in good agreement with published data.⁴⁰ The measured H₂O₂ concentration profiles showed distinct differences between high light and darkness. Under high irradiance, i.e., high light stress, H₂O₂ concentrations increased up to 15 μM within the biofilm zone of maximal oxygenic photosynthesis as indicated by the peak in O₂ concentration.

Obviously the cross-sensitivity towards O₂ and pH has to be considered when analyzing the data. It is well known that due to photosynthesis not only the O₂ levels but also the pH increases.⁴⁰ Luckily those effects were found to counteract on the sensor sensitivity and therefore minimize the cross-effects in the light; nevertheless leading to uncertainty. In the dark and also in the bulk water no H₂O₂ was measured, albeit some offset in the zero response of the new H₂O₂ sensor was observed with depth in the biofilm³⁸ (see Discussion).

3.4.3. H₂O₂ concentration dynamics in activated neutrophils. Stimulation of phagocytosis in polymorphonuclear leukocytes (PMNs) involves increased O₂ consumption⁴¹ and increased production of superoxide (O₂⁻) resulting from the reduction of O₂ by their NADPH-oxidase,⁴² which successively leads to the increased production of H₂O₂.⁴³ PMNs were exposed to 10 μM phorbol-12-myristate-13-acetate (PMA) which stimulates the respiratory burst of PMNs⁴⁴ resulting in increased extracellular pools of H₂O₂ ⁴⁵ and accelerated O₂ consumption.⁴⁶ Simultaneous measurements of O₂ and H₂O₂ concentration dynamics in isolated neutrophils activated with PMA confirmed the expected changes (Fig. 4C). About 2 minutes after PMN stimulation by PMA, an increased O₂ consumption and H₂O₂ production was observed. The extracellular H₂O₂ concentration peaked at ∼10 μM after 7 min. When extracellular O₂ levels started to stabilize, extracellular H₂O₂ disappeared, presumably due to activity of catalase and myeloperoxidase.⁴⁷ A replicate of the experimental data in Fig. 4C can be found in the ESI (Fig. 8†).

4. Discussion

Hydrogen peroxide (H₂O₂) is a key analyte in environmental and biomedical research. Quantification of this reactive analyte enables the study of the current redox status of cells and tissues. Hitherto, optical H₂O₂ detection has focused on the use of cell permeable dyes selective to H₂O₂. Despite their high spatial resolution, the application of such indicators mainly yields qualitative information on the presence/absence of H₂O₂ and is difficult, if not impossible, to extract quantitative measures of H₂O₂ concentration from such probes.

Here we present a fiber-optic H₂O₂ sensor for H₂O₂ concentration measurements with a spatial resolution of ∼500 μm and a time resolution of ∼30 seconds. The system is based on the PB induced reduction of the emission of a secondary emitter. In order to provide the highest possible photostability, an inorganic emitter, namely Cr-YAB was chosen. Although this crystalline material was previously used for temperature sensing, it has to be noted that mainly the luminescence decay time is sensitive to temperature, while the intensity is much less affected.³⁶

A crucial step of applying the new H₂O₂ sensor for biological measurements is the possibility of rapid regenerating. This was achieved by producing a recharger gel and using automated approach and retract protocols of a computer controlled micromanipulator. It was possible to position the recharger gel in close proximity to the sample; e.g. 5 mm above the biofilm or in the calibration solution (see Fig. 2 and ESI†). This is a major advancement in comparison to irreversible H₂O₂ probes. While irreversible probes are superior for localizing H₂O₂ especially within cells or tissues,⁸ this sensor enables H₂O₂ quantification over a long time. Computer controlled positioning into the sample and retraction of the sensor into the recharging gel facilitates easy handling.

Monitoring an enzyme reaction using the proposed sensor showed that it is possible to follow the evolution of H₂O₂ over time. With intervals between measurement points of around 30 seconds, the sensor system is able to follow H₂O₂ dynamics during relatively fast reactions. The obtained H₂O₂ concentration traces are in very good agreement with the simultaneously measured O₂ dynamics.

To the best of our knowledge this is the first quantification of H₂O₂ in a natural biofilm with an optical H₂O₂ sensor. Previously, scanning electrochemical analysis was used to measure H₂O₂ concentration in a photosynthetic biofilm⁴⁸ or amperometric microsensors were used to study the effect of externally added H₂O₂ (>50 mM)^49,50 on a lab-grown biofilm. In the presented data it is remarkable that the H₂O₂ profile follows the O₂ profile indicating that increased photosynthetic O₂ production leads to an increase of ROS. This is in good agreement with previous observations^51,52 suggesting that H₂O₂ production is associated with photosynthesis under high light stress.⁵³ ROS are important potential byproducts in the photosynthesis pathway and can be produced at Photosystem I⁵⁴ and II⁵¹via a variety of reactions. Our measurements thus clearly demonstrate that H₂O₂ production is tightly linked to the local O₂ concentration and that H₂O₂ can accumulate in biofilms as a reaction to light stress.⁵⁵

We note that the standard deviation of the measured H₂O₂ concentration profiles is rather high and that the observed cross-sensitivities to pH and O₂ are to be taken into account as photosynthetic biofilms show pronounced O₂ and pH dynamics.⁴⁰ A quantification of O₂ and pH interference on H₂O₂ sensor calibration can be found in the ESI.† The fact that the measured H₂O₂ levels in the dark apparently became negative might be due to the reductive environment that builds up when O₂ is gone leading to stabilization of PW. The cross-sensitivity to pH and reductants that will stabilize the PW form are the current limitations of the sensor. Nevertheless, the measured profile gives valuable information on the buildup of H₂O₂ and the new H₂O₂ sensor is an important new tool for studies investigating how environmental conditions affect in situ ROS production in natural aquatic systems.

As an example of biomedical application the respiratory burst of neutrophils was investigated. The H₂O₂ is produced by neutrophils as a response to bacterial infections⁵ by converting O₂ to first superoxide (O₂⁻) and subsequently H₂O₂ (see insert in Fig. 4C). This process is facilitated using the plasma membrane-associated NADPH oxidase that gets activated upon contact with bacteria or due to stimulation (e.g. by PMA). So far H₂O₂ generation in this highly important immune response has been monitored using electrochemical systems.^45,47 Here we showed that the rechargeable optical H₂O₂ sensor is capable of measuring H₂O₂ generation in this bio-medically relevant system. The obtained O₂ and H₂O₂ time traces follow each other and lead to the conclusion that the consumed O₂ is rapidly converted into superoxide and subsequently H₂O₂. The obtained results are in good agreement with previous findings⁴⁵ regarding the extracellular H₂O₂ concentration.

5. Conclusion

We developed a versatile rechargeable fiber-optic H₂O₂ sensor for fast, spatially resolved and quantitative measurement of extracellular H₂O₂ concentration in complex media. While electrochemical H₂O₂ quantification has seen a lot of development over the years,²⁹ this paper presents the first fiber-optic H₂O₂ sensor enabling quantitative concentration measurements in environmental and biomedical applications. As H₂O₂ often reacts irreversibly with optical indicators,⁹ the possibility of recharging the sensor makes this sensing principle very promising for a wide range of applications. By bringing the recharging process in close proximity to the sample and by applying differential readout, a fast and robust measurement scheme was developed that is applicable in a wide range of complex environmental and even some biomedical samples. Future development should try to decrease current cross-sensitivities, lower the detection limit and go towards further miniaturization to also enable less invasive measurement in tissues.

Acknowledgements

Sofie L. Jakobsen is thanked for technical assistance and for collecting the biofilm sample. Prof. Ingo Klimant and Dr Sergey M. Borisov from the Graz University of Technology are thanked for fruitful discussions throughout the development of this sensor and for kindly providing the Cr-YAB used in this study. Dr Roland Thar, CEO of Pyro Science, is thanked for his help and advice. Dr Mette Kolpen, Rigshospitalet Copenhagen, is thanked for helping isolate the neutrophil cells. This study was supported by a grant from the Villum Foundation, a Sapere-Aude Advanced grant from the Danish Research Council for Independent Research, and a grant by the Danish Research Council for Independent Research | Technical and Production Sciences.

References

1. D. R. Gough and T. G. Cotter, Cell Death Dis., 2011, 2, e213.
2. T. Finkel and N. J. Holbrook, Nature, 2000, 408, 239–247.
3. B. Halliwell and J. Gutteridge, Free Radicals in Biology and Medicine, Oxdord Univerity Press, Oxford, 2007.
4. M. P. Murphy, A. Holmgren, N.-G. Larsson, B. Halliwell, C. J. Chang, B. Kalyanaraman, S. G. Rhee, P. J. Thornalley, L. Partridge, D. Gems, T. Nyström, V. Belousov, P. T. Schumacker and C. C. Winterbourn, Cell Metab., 2011, 13, 361–366.
5. W. M. Nauseef, Immunol. Rev., 2007, 219, 88–102.
6. C. C. Winterbourn, Methods Enzymol., 2013, 528, 3–25.
7. C. C. Winterbourn, Nat. Chem. Biol., 2008, 4, 278–286.
8. J. Chan, S. C. Dodani and C. J. Chang, Nat. Chem., 2012, 4, 973–984.
9. A. R. Lippert, G. C. Van de Bittner and C. J. Chang, Acc. Chem. Res., 2011, 44, 793–804.
10. X. Chen, X. Tian, I. Shin and J. Yoon, Chem. Soc. Rev., 2011, 40, 4783–4804.
11. V. V. Belousov, A. F. Fradkov, K. A. Lukyanov, D. B. Staroverov, K. S. Shakhbazov, A. V. Terskikh and S. Lukyanov, Nat. Methods, 2006, 3, 281–286.
12. M. B. Grisham, Comp. Biochem. Physiol., Part A: Mol. Integr. Physiol., 2013, 165, 429–438.
13. C. C. Winterbourn, Biochim. Biophys. Acta, 2014, 1840, 730–738.
14. B. C. Dickinson, C. Huynh and C. J. Chang, J. Am. Chem. Soc., 2010, 132, 5906–5915.
15. J. F. Woolley, J. Stanicka and T. G. Cotter, Trends Biochem. Sci., 2013, 38, 556–565.
16. M. M. Tarpey and I. Fridovich, Circ. Res., 2001, 89, 224–236.
17. M. Kühl, Methods Enzymol., 2005, 397, 166–199.
18. N. P. Revsbech, Methods Enzymol., 2005, 397, 147–166.
19. I. Klimant, V. Meyer and M. Kühl, Limnol. Oceanogr., 1995, 40, 1159–1165.
20. M. Kühl, Y. Cohen, T. Dalsgaard, B. B. Jørgensen and N. P. Revsbech, Mar. Ecol.: Prog. Ser., 1995, 117, 159–172.
21. P. Jeroschewski, C. Steuckart and M. Kühl, Anal. Chem., 1996, 68, 4351–4357.
22. M. Kolpen, M. Kühl, T. Bjarnsholt, C. Moser, C. R. Hansen, L. Liengaard, A. Kharazmi, T. Pressler, N. Høiby and P. Ø. Jensen, PLoS One, 2014, 9, e84353.
23. T. Malinski and Z. Taha, Nature, 1992, 358, 676–678.
24. C. Calas-Blanchard, G. Catanante and T. Noguer, Electroanalysis, 2014, 26, 1277–1286.
25. N. V. Kulagina and A. C. Michael, Anal. Chem., 2003, 75, 4875–4881.
26. D. W. M. Arrigan, Analyst, 2004, 129, 1157–1165.
27. M. Delvaux, A. Walcarius and S. Demoustier-Champagne, Anal. Chim. Acta, 2004, 525, 221–230.
28. Y. Wang, J.-M. Noël, J. Velmurugan, W. Nogala, M. V. Mirkin, C. Lu, M. Guille Collignon, F. Lemaître and C. Amatore, Proc. Natl. Acad. Sci. U. S. A., 2012, 109, 11534–11539.
29. W. Chen, S. Cai, Q.-Q. Ren, W. Wen and Y.-D. Zhao, Analyst, 2012, 137, 49–58.
30. F. Ricci and G. Palleschi, Biosens. Bioelectron., 2005, 21, 389–407.
31. A. A. Karyakin, Electroanalysis, 2001, 13, 813–819.
32. A. A. Karyakin and E. E. Karyakina, Sens. Actuators, B, 1999, 57, 268–273.
33. O. S. Wolfbeis, A. Dürkop, M. Wu and Z. Lin, Angew. Chem., Int. Ed., 2002, 41, 4495–4498.
34. J. F. Botero-Cadavid, A. G. Brolo, P. Wild and N. Djilali, Sens. Actuators, B, 2013, 185, 166–173.
35. H. A. Khorami, J. F. Botero-Cadavid, P. Wild and N. Djilali, Electrochim. Acta, 2014, 115, 416–424.
36. S. M. Borisov, K. Gatterer, B. Bitschnau and I. Klimant, J. Phys. Chem. C, 2010, 114, 9118–9124.
37. J. Brown, Philos. Trans. R. Soc. London, 1724, 33, 17–24.
38. R. Koncki, T. Lenarczuk and S. Głąb, Anal. Chim. Acta, 2000, 424, 27–35.
39. S. A. M. van Stroe-Biezen, F. M. Everaerts, L. J. J. Janssen and R. A. Tacken, Anal. Chim. Acta, 1993, 273, 553–560.
40. M. Nielsen, L. H. Larsen, L. D. M. Ottosen and N. P. Revsbech, Sens. Actuators, B, 2015, 215, 1–8.
41. C. W. Baldridge and R. W. Gerard, Am. J. Physiol., 1932, 103, 235–236.
42. B. M. Babior, R. S. Kipnes and J. T. Curnutte, J. Clin. Invest., 1973, 52, 741–744.
43. G. Y. N. Iyer, M. F. Islam and J. H. Quastel, Nature, 1961, 192, 535–541.
44. L. R. DeChatelet, P. S. Shirley and R. B. Johnston, Blood, 1976, 47, 545–554.
45. S. T. Test and S. J. Weisst, Biol. Chem., 1984, 259, 399–405.
46. J. E. Repine, J. G. White, C. C. Clawson and B. M. Holmes, J. Clin. Invest., 1974, 54, 83–90.
47. A. J. Kettle and C. C. Winterbourn, Biochemistry, 2001, 40, 10204–10212.
48. X. Liu, M. M. Ramsey, X. Chen, D. Koley, M. Whiteley and A. J. Bard, Proc. Natl. Acad. Sci. U. S. A., 2011, 108, 2668–2673.
49. X. Lu, F. Roe, A. Jesaitis, Z. Lewandowski and X. Liu, Biotechnol. Bioeng., 1998, 59, 156–162.
50. P. S. Stewart, F. Roe, J. Rayner, J. G. Elkins, Z. Lewandowski, U. A. Ochsner and D. J. Hassett, Appl. Environ. Microbiol., 2000, 66, 836–838.
51. P. Pospísil, Biochim. Biophys. Acta, 2009, 1787, 1151–1160.
52. M. P. Lesser, Annu. Rev. Physiol., 2006, 68, 253–278.
53. A. Latifi, M. Ruiz and C. C. Zhang, FEMS Microbiol. Rev., 2009, 33, 258–278.
54. K. Apel and H. Hirt, Annu. Rev. Plant Biol., 2004, 55, 373–399.
55. J. Collen, M. J. Del Rio, G. Garcia-Reina and M. Pedersen, Planta, 1995, 196, 225–230.

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Footnote

† Electronic supplementary information (ESI) available. See DOI: 10.1039/c6an00864j

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