Novel Approach for Lifetime-Proportional Luminescence Imaging Using Frame Straddling.

Optode-based chemical imaging is a rapidly evolving field that has substantially enhanced our understanding of the role of microenvironments and chemical gradients in biogeochemistry, microbial ecology, and biomedical sciences. Progress in sensor chemistry has resulted in a broadened spectrum of analytes, alongside enhancements in sensor performance (e.g., sensitivity, brightness, and photostability). However, existing imaging techniques are often costly, challenging to implement, and limited in their recording speed. Here we use the "frame-straddling" technique, originally developed for particle image velocimetry for imaging the O2-dependent, integrated luminescence decay of optical O2 sensor materials. The method synchronizes short excitation pulses and camera exposures to capture two frames at varying brightness, where the first excitation pulse occurs at the end of the exposure of the first frame and the second excitation pulse at the beginning of the second frame. Here the first frame truncates the luminescence decay, whereas the second frame fully captures it. The difference between the frames quantifies the integral of the luminescence decay curve, which is proportional to the luminescence lifetime, at time scales below one millisecond. Short excitation pulses avoid depopulation of the ground state of luminophores, resulting in a linear Stern-Volmer response with increasing concentrations of the quencher (O2), which can be predicted through a simple model. This methodology is compatible with a wide range of camera systems, making it a versatile tool for various optode based chemical imaging applications. We showcase the utility of frame straddling in measuring O2 dynamics around algae and by observing O2 scavenging sodium dithionite particles sinking through oxygenated water.

Simultaneous Imaging of Temperature and Oxygen by Utilizing Thermally Activated Delayed Fluorescence and Phosphorescence of a Single Indicator.

Chemical gradients are essential in biological systems, affecting processes like microbial activity in soils and nutrient cycling. Traditional tools, such as microsensors, offer high-resolution data but are limited to one-dimensional measurements. Planar optodes allow for two-dimensional (2D) and three-dimensional (3D) chemical imaging but are often sensitive to temperature changes. This study presents an advanced dual-emission optical sensor that simultaneously measures temperature and oxygen using a modified platinum(II) meso-tetrakis(3,5-ditert-butylphenyl)-tetra(2-tert-butyl-1,4-naphthoquinono)porphyrin. The ratio between thermally activated delayed fluorescence and phosphorescence was optimized by modifying platinum(II) naphthoquinonoporphyrin with tert-butyl groups which simultaneously improved solubility in apolar solvents and polymer matrix (polystyrene). This dual-function sensor enables two-parameter chemical imaging with a consumer-grade RGB camera or a hyperspectral camera. We demonstrated 2D visualization of temperature and oxygen distribution in a model soil system. The RGB camera provided rapid and cost-effective imaging, while the hyperspectral camera offered more detailed spectral information despite some limitations. Our findings revealed the formation of a stable temperature gradient and oxygen depletion, driven by water content and temperature-sensitive microbial activity. This dual O2/T sensor, with further potential improvements, shows considerable promise for advanced multiparameter sensing in complex biological and environmental studies, providing deeper insights into dynamic microenvironments.

SlipO2Chip - single-cell respiration under tuneable environments.

In disciplines like toxicology and pharmacology, oxygen (O2) respiration is a universal metric for evaluating the effects of chemicals across various model systems, including mammalian and microalgal cells. However, for these cells the common practice is to segregate populations into control and exposure groups, which assumes direct equivalence in their responses and does not take into account heterogeneity among individual cells. This lack of resolution impedes our ability to precisely investigate differences among experimental groups with small or limited sample sizes. To overcome this barrier, we introduce SlipO2Chip, an innovative glass microfluidic platform for precisely quantifying single-cell O2 respiration in the coordinated absence and presence of chemical solutes. SlipO2Chip comprises a wet-etched fused silica channel plate on the top and a dry-etched borosilicate microwell plate at the bottom. The microwells are coated with Pt(II) meso-tetra(pentafluorophenyl)porphine (PtTFPP), an O2 sensing optode material and an O2-independent reference dye. A custom 3D-printed holder facilitates the controlled horizontal movement ('slipping') of the channel plate over the microwell plate, thereby establishing or disrupting the fluid path over microwells. Collectively, these design elements enable the immobilization of single-cells in microwells, their exposure to controlled fluid flows, the coordinated opening and closing of microwells and repeated measurements of single-cell O2 respiration. Uniquely, by sequentially executing opening and closing it becomes possible to measure single-cell respiration prior to and after exposure to chemical solutes. In a proof-of-concept application, we utilized SlipO2Chip to measure the impact of increasing exposures of the marine bacterial signal 2-heptyl-4-quinolone (HHQ) on the dark respiration of the diatom Ditylum brightwellii at single-cell resolution. Results revealed a concentration-dependent decrease in per-cell O2 dark respiration, with a maximum reduction of 40.2% observed at HHQ concentrations exceeding 35.5 µM, and a half-maximal effective concentration (EC50) of 5.8 µM, consistent with that obtained via conventional bulk respiration methods. The ability of SlipO2Chip to sequentially assess the effects of chemical substances on single-cell O2 metabolism is advantageous for research where sample volumes are limited, such as clinical biopsies, studies involving rare microbial isolates, and toxicological studies aiming to address exposure effects while accounting for cell-to-cell variability.

Exploiting the pH-Cross Sensitivity of Ion-Selective Optodes to Broaden Their Response Range.

While the pH cross-sensitivity of chromoionophore-based ion-selective optodes (ISOs) has often been regarded as a significant limitation, this paper demonstrates how this apparent drawback can be transformed into a beneficial feature. The response range of chromoionophore-based ISOs shifts proportionally with changes in the sample pH. Thus, integrating them with a stable pH gradient across the optode surface, such as those provided by immobilized pH gradient (IPG) gels, allows for significant enhancement of the effective measuring range of chromoionophore-based ISOs while preserving their maximum sensitivity. We show that the measuring range of sodium-selective chromoionophore-based optodes can be increased up to 2.5 log units when used with commercially available IPG gels. This improvement in measuring range is directly correlated with the pH difference in the pH gradient across the optode, suggesting that even greater enhancements are possible with more substantial pH gradients. Furthermore, this approach is not confined to sodium-selective optodes but can be readily adapted to other ion-selective chromoionophore-based optodes, broadening their potential applications and impact in the field of chemical sensing. This work paves the way for the development of more versatile and highly sensitive optodes across a broad range of analytes, leveraging the pH cross-sensitivity as a tool for enhanced performance.

Size-related variability of oxygen consumption rates in individual human hepatic cells.

Accurate descriptions of the variability in single-cell oxygen consumption and its size-dependency are key to establishing more robust tissue models. By combining microfabricated devices with multiparameter identification algorithms, we demonstrate that single human hepatocytes exhibit an oxygen level-dependent consumption rate and that their maximal oxygen consumption rate is significantly lower than that of typical hepatic cell cultures. Moreover, we found that clusters of two or more cells competing for a limited oxygen supply reduced their maximal consumption rate, highlighting their ability to adapt to local resource availability and the presence of nearby cells. We used our approach to characterize the covariance of size and oxygen consumption rate within a cell population, showing that size matters, since oxygen metabolism covaries lognormally with cell size. Our study paves the way for linking the metabolic activity of single human hepatocytes to their tissue- or organ-level metabolism and describing its size-related variability through scaling laws.

Considerations on the use of microsensors to profile dissolved H2 concentrations in microbial electrochemical reactors.

Measuring the distribution and dynamics of H2 in microbial electrochemical reactors is valuable to gain insights into the processes behind novel bioelectrochemical technologies, such as microbial electrosynthesis. Here, a microsensor method to measure and profile dissolved H2 concentrations in standard H-cell reactors is described. Graphite cathodes were oriented horizontally to enable the use of a motorized microprofiling system and a stereomicroscope was used to place the H2 microsensor precisely on the cathode surface. Profiling was performed towards the gas-liquid interface, while preserving the electric connections and flushing the headspace (to maintain anoxic conditions) and under strict temperature control (to overcome the temperature sensitivity of the microsensors). This method was tested by profiling six reactors, with and without inoculation of the acetogen Sporomusa ovata, at three different time points. H2 accumulated over time in the abiotic controls, while S. ovata maintained low H2 concentrations throughout the liquid phase (< 4 µM) during the whole experimental period. These results demonstrate that this setup generated insightful H2 profiles. However, various limitations of this microsensor method were identified, as headspace flushing lowered the dissolved H2 concentrations over time. Moreover, microsensors can likely not accurately measure H2 in the immediate vicinity of the solid cathode, because the solids cathode surface obstructs H2 diffusion into the microsensor. Finally, the reactors had to be discarded after microsensor profiling. Interested users should bear these considerations in mind when applying microsensors to characterize microbial electrochemical reactors.

Cable Bacteria Skeletons as Catalytically Active Electrodes.

Cable bacteria are multicellular, filamentous bacteria that use internal conductive fibers to transfer electrons over centimeter distances from donors within anoxic sediment layers to oxygen at the surface. We extracted the fibers and used them as free-standing bio-based electrodes to investigate their electrocatalytic behavior. The fibers catalyzed the reversible interconversion of oxygen and water, and an electric current was running through the fibers even when the potential difference was generated solely by a gradient of oxygen concentration. Oxygen reduction as well as oxygen evolution were confirmed by optical measurements. Within living cable bacteria, oxygen reduction by direct electrocatalysis on the fibers and not by membrane-bound proteins readily explains exceptionally high cell-specific oxygen consumption rates observed in the oxic zone, while electrocatalytic water oxidation may provide oxygen to cells in the anoxic zone.

Optical sensors (optodes) for multiparameter chemical imaging: classification, challenges, and prospects.

Chemical gradients and uneven distribution of analytes are common in natural and artificial systems. As a result, the ability to visualize chemical distributions in two or more dimensions has gained significant importance in recent years. This has led to the integration of chemical imaging techniques into all domains of analytical chemistry. In this review, we focus on the use of optical sensors, so-called optodes, to obtain real-time and multidimensional images of two or more parameters simultaneously. It is important to emphasize that multiparameter imaging in this context is not confined solely to multiple chemical parameters (analytes) but also encompasses physical (e.g., temperature or flow) or biological (e.g., metabolic activity) parameters. First, we discuss the technological milestones that have paved the way for chemical imaging using optodes. Later, we delve into various strategies that can be taken to enable multiparameter imaging. The latter spans from developing novel receptors that enable the recognition of multiple parameters to chemometrics and machine learning-based techniques for data analysis. We also explore ongoing trends, challenges, and prospects for future developments in this field. Optode-based multiparameter imaging is a rapidly expanding field that is being fueled by cutting-edge technologies. Chemical imaging possesses the potential to provide novel insights into complex samples, bridging not only across various scientific disciplines but also between research and society.

Timing matters: the overlooked issue of response time mismatch in pH-dependent analyte sensing using multiple sensors.

Accurate measurement of pH-dependent analytes is crucial for a wide range of applications, including environmental monitoring, industrial processes, and healthcare diagnostics. In multi-sensor systems, combining data from multiple sensors offers the potential for more comprehensive analysis, yet it is important to be aware of the limitations of this approach. In this paper, we investigate the often-overlooked issue of response time mismatch among sensors, which can introduce significant errors in calculated sum parameters. We present a model and software application (SensinSilico) that allows predicting the error arising from a mismatch of sensor response times. The model was compared and validated using experimental results from calculations of total dissolved sulphide (TDS). These calculations were based on data from concurrent sensor measurements of hydrogen sulfide (H2S) and pH, which had different response times. We believe that SensinSilico has the potential to be a powerful tool for researchers, professionals, and end-users, enabling them to estimate and minimize errors arising from response time mismatches, enhancing the accuracy and reliability of their results.

Differential impacts of sewage sludge and biochar on phosphorus-related processes: An imaging study of the rhizosphere.

Recycling of phosphorus (P) from waste streams in agriculture is essential to reduce the negative environmental effects of surplus P and the unsustainable mining of geological P resources. Sewage sludge (SS) is an important P source; however, several issues are associated with the handling and application of SS in agriculture. Thus, post-treatments such as pyrolysis of SS into biochar (BC) could address some of these issues. Here we elucidate how patches of SS in soil interact with the living roots of wheat and affect important P-related rhizosphere processes compared to their BC counterparts. Wheat plants were grown in rhizoboxes with sandy loam soil, and 1 cm Ø patches with either SS or BC placed 10 cm below the seed. A negative control (CK) was included. Planar optode pH sensors were used to visualize spatiotemporal pH changes during 40 days of plant growth, diffusive gradients in thin films (DGT) were applied to map labile P, and zymography was used to visualize the spatial distribution of acid (ACP) and alkaline (ALP) phosphatase activity. In addition, bulk soil measurements of available P, pH, and ACP activity were conducted. Finally, the relative abundance of bacterial P-cycling genes (phoD, phoX, phnK) was determined in the patch area rhizosphere. Labile P was only observed in the area of the SS patches, and SS further triggered root proliferation and increased the activity of ACP and ALP in interaction with the roots. In contrast, BC seemed to be inert, had no visible effect on root growth, and even reduced ACP and ALP activity in the patch area. Furthermore, there was a lower relative abundance of phoD and phnK genes in the BC rhizosphere compared to the CK. Hence, optimization of BC properties is needed to increase the short-term efficiency of BC from SS as a P fertilizer.

Let's Talk about Slime; or Why Biofouling Needs More Attention in Sensor Science.

Although there is a growing demand for new sensors for environmental monitoring, biofouling continues to plague current sensors and sensing networks. As soon as a sensor is placed in water, the formation of a biofilm begins. Once a biofilm is established, reliable measurements are often no longer possible. Although current biofouling mitigation strategies can slow the biofouling process, a biofilm will eventually develop on or near the sensing surface. While antibiofouling strategies are being continuously developed, the complexity of the biofilm community structure and the surrounding environment means that there is unlikely to be a single solution that will minimize biofilms on all environmental sensors. Thus, antibiofouling research often focuses on optimizing a specific biofilm mitigation approach for a given sensor, application, and environmental condition. While this is practical from the standpoint of a sensor developer, it makes the comparison of different mitigation strategies difficult. In this Perspective, we discuss the application of different biofouling mitigation strategies to sensing and then explore the need for the sensor community to adopt standard protocols to increase the comparability of the biofouling mitigation approaches and help sensor developers identify the most appropriate strategy for their system.

Imaging of CO2 and Dissolved Inorganic Carbon via Electrochemical Acidification-Optode Tandem.

Dissolved inorganic carbon (DIC) is a key component of the global carbon cycle and plays a critical role in ocean acidification and proliferation of phototrophs. Its quantification at a high spatial resolution is essential for understanding various biogeochemical processes. We present an analytical method for 2D chemical imaging of DIC by combining a conventional CO2 optode with localized electrochemical acidification from a polyaniline (PANI)-coated stainless-steel mesh electrode. Initially, the optode response is governed by local concentrations of free CO2 in the sample, corresponding to the established carbonate equilibrium at the (unmodified) sample pH. Upon applying a mild potential-based polarization to the PANI mesh, protons are released into the sample, shifting the carbonate equilibrium toward CO2 conversion (>99%), which corresponds to the sample DIC. It is herein demonstrated that the CO2 optode-PANI tandem enables the mapping of free CO2 (before PANI activation) and DIC (after PANI activation) in complex samples, providing high 2D spatial resolution (approx. 400 µm). The significance of this method was proven by inspecting the carbonate chemistry of complex environmental systems, including the freshwater plant Vallisneria spiralis and lime-amended waterlogged soil. This work is expected to pave the way for new analytical strategies that combine chemical imaging with electrochemical actuators, aiming to enhance classical sensing approaches via in situ (and reagentless) sample treatment. Such tools may provide a better understanding of environmentally relevant pH-dependent analytes related to the carbon, nitrogen, and sulfur cycles.

Reducing biofouling on optical oxygen sensors; a simple modification enabling sensor cleaning via water splitting.

Biofouling is a major challenge in environmental sensing. Current mitigation strategies are often expensive, energy consuming or require toxic chemicals. In this contribution electrochemical biofouling control is evaluated as an alternative approach to reduce biofouling on an optical O2 sensor (optode). By using the outer stainless-steel sleeve of the optode as an electrode, water splitting increases the local pH and forms H2 bubbles close to the optode surface. As seen in a biofouling assay, the combination of those processes leads to biofilm removal when compared to a non-modified optode. The findings suggest that electrochemical biofouling control can be an attractive, low-cost alternative to current biofouling mitigation strategies and that this approach may not be limited to O2 optodes.

Machine learning for optical chemical multi-analyte imaging : Why we should dare and why it's not without risks.

Simultaneous sensing of metabolic analytes such as pH and O2 is critical in complex and heterogeneous biological environments where analytes often are interrelated. However, measuring all target analytes at the same time and position is often challenging. A major challenge preventing further progress occurs when sensor signals cannot be directly correlated to analyte concentrations due to additional effects, overshadowing and complicating the actual correlations. In fields related to optical sensing, machine learning has already shown its potential to overcome these challenges by solving nested and multidimensional correlations. Hence, we want to apply machine learning models to fluorescence-based optical chemical sensors to facilitate simultaneous imaging of multiple analytes in 2D. We present a proof-of-concept approach for simultaneous imaging of pH and dissolved O2 using an optical chemical sensor, a hyperspectral camera for image acquisition, and a multi-layered machine learning model based on a decision tree algorithm (XGBoost) for data analysis. Our model predicts dissolved O2 and pH with a mean absolute error of < 4.50·10-2 and < 1.96·10-1, respectively, and a root mean square error of < 2.12·10-1 and < 4.42·10-1, respectively. Besides the model-building process, we discuss the potentials of machine learning for optical chemical sensing, especially regarding multi-analyte imaging, and highlight risks of bias that can arise in machine learning-based data analysis.

Microsensor for total dissolved sulfide (TDS).

Total Dissolved Sulfide (TDS) concentrations can either be derived from simultaneous measurement of pH and one of the sulfide species or determined indirectly in samples following an acidification step. Here we report a microsensor that allows for direct measurement of TDS in aquatic media without the need for pH monitoring. An acidic chamber placed in front of a commercial, amperometric H2S microsensor allows for the in-situ conversion of dissolved ionic sulfide species to H2S, which in turn is oxidized at the transducer anode. A typical sensor had a tip opening of 30 µm, a response time of <50 s and linear range between 0.5 and 650 µM. The sensor performance can be largely tuned by altering the geometry of the chamber. Sensors of different sensitivity (0.04-2.93 pA/µM) showed no noticeable change in zero current and sensitivity during continuous polarization over 7 weeks. The sensor was successfully applied to resolve microscale TDS gradients in freshwater and marine sediments. Other avenues of application include the online monitoring of industrial and urban sewers.

Optode-based chemical imaging of laboratory burned soil reveals millimeter-scale heterogeneous biogeochemical responses.

Soil spatial responses to fire are unclear. Using optical chemical sensing with planar 'optodes', pH and dissolved O2 concentration were tracked spatially with a resolution of 360 µm per pixel for 72 h after burning soil in the laboratory with a butane torch (∼1300 °C) and then sprinkling water to simulate a postfire moisture event. Imaging data from planar optodes correlated with microbial activity (quantified via RNA transcripts). Post-fire and post-wetting, soil pH increased throughout the entire ∼13 cm × 17 cm × 20 cm rectangular cuboid of sandy loam soil. Dissolved O2 concentrations were not impacted until the application of water postfire. pH and dissolved O2 both negatively correlated (p < 0.05) with relative transcript expression for galactose metabolism, the degradation of aromatic compounds, sulfur metabolism, and narH. Additionally, dissolved O2 negatively correlated (p < 0.05) with the relative activity of carbon fixation pathways in Bacteria and Archaea, amoA/amoB, narG, nirK, and nosZ. nifH was not detected in any samples. Only amoB and amoC correlated with depth in soil (p < 0.05). Results demonstrate that postfire soils are spatially complex on a mm scale and that using optode-based chemical imaging as a chemical navigator for RNA transcript sampling is effective.

Imaging Sample Acidification Triggered by Electrochemically Activated Polyaniline.

In this letter, we demonstrate 2D acidification of samples at environmental and physiological pH with an electrochemically activated polyaniline (PANI) mesh. A novel sensor-actuator concept is conceived for such a purpose. The sample is sandwiched between the PANI (actuator) and a planar pH optode (sensor) placed at a very close distance (∼0.50 mm). Upon application of a mild potential to the mesh, in contrast to previously reported acidification approaches, PANI releases a significant number of protons, causing an acid-base titration in the sample. This process is monitored in time and space by the pH optode, providing chemical imaging of the pH decrease along the dynamic titration via photographic acquisition. Acidification of samples at varying buffer capacity has been investigated: the higher the buffer capacity, the more time (and therefore proton charge) was needed to reach a pH of 4.5 or even lower. Also, the ability to map spatial differences in buffer capacity within a sample during the acid-base titration was unprecedentedly proven. The sensor-actuator concept could be used for monitoring certain analytes in samples that specifically require acidification pretreatment. Particularly, in combination with different optodes, dynamic mapping of concentration gradients will be accessible in complex environmental samples ranging from roots and sediments to bacterial aggregates.

Ciliary flows in corals ventilate target areas of high photosynthetic oxygen production.

Most tropical corals live in symbiosis with Symbiodiniaceae algae whose photosynthetic production of oxygen (O2) may lead to excess O2 in the diffusive boundary layer (DBL) above the coral surface. When flow is low, cilia-induced mixing of the coral DBL is vital to remove excess O2 and prevent oxidative stress that may lead to coral bleaching and mortality. Here, we combined particle image velocimetry using O2-sensitive nanoparticles (sensPIV) with chlorophyll (Chla)-sensitive hyperspectral imaging to visualize the microscale distribution and dynamics of ciliary flows and O2 in the coral DBL in relation to the distribution of Symbiodiniaceae Chla in the tissue of the reef building coral, Porites lutea. Curiously, we found an inverse relation between O2 in the DBL and Chla in the underlying tissue, with patches of high O2 in the DBL above low Chla in the underlying tissue surrounding the polyp mouth areas and pockets of low O2 concentrations in the DBL above high Chla in the coenosarc tissue connecting neighboring polyps. The spatial segregation of Chla and O2 is related to ciliary-induced flows, causing a lateral redistribution of O2 in the DBL. In a 2D transport-reaction model of the coral DBL, we show that the enhanced O2 transport allocates parts of the O2 surplus to areas containing less chla, which minimizes oxidative stress. Cilary flows thus confer a spatially complex mass transfer in the coral DBL, which may play an important role in mitigating oxidative stress and bleaching in corals.

Simultaneous visualization of flow fields and oxygen concentrations to unravel transport and metabolic processes in biological systems.

From individual cells to whole organisms, O2 transport unfolds across micrometer- to millimeter-length scales and can change within milliseconds in response to fluid flows and organismal behavior. The spatiotemporal complexity of these processes makes the accurate assessment of O2 dynamics via currently available methods difficult or unreliable. Here, we present "sensPIV," a method to simultaneously measure O2 concentrations and flow fields. By tracking O2-sensitive microparticles in flow using imaging technologies that allow for instantaneous referencing, we measured O2 transport within (1) microfluidic devices, (2) sinking model aggregates, and (3) complex colony-forming corals. Through the use of sensPIV, we find that corals use ciliary movement to link zones of photosynthetic O2 production to zones of O2 consumption. SensPIV can potentially be extendable to study flow-organism interactions across many life-science and engineering applications.

Noise versus Resolution in Optical Chemical Imaging-How Reliable Are Our Measurements?

Optical chemical imaging has established itself as a valuable technique for visualizing analyte distributions in 2D, notably in medical, biological, and environmental applications. In particular for image acquisitions on small scales between few millimeter to the micrometer range, as well as in heterogeneous samples with steep analyte gradients, image resolution is essential. When individual pixels are inspected, however, image noise becomes a metric as relevant as image accuracy and precision, and denoising filters are applied to preserve relevant information. While denoising filters smooth the image noise, they can also lead to a loss of spatial resolution and thus to a loss of relevant information about analyte distributions. To investigate the trade-off between image resolution and noise reduction for information preservation, we studied the impact of random camera noise and noise due to incorrect camera settings on oxygen optodes using the ratiometric imaging technique. First, we estimated the noise amplification across the calibration process using a Monte Carlo simulation for nonlinear fit models. We demonstrated how initially marginal random camera noise results in a significant standard deviation (SD) for oxygen concentration of up to 2.73% air under anoxic conditions, although the measurement was conducted under ideal conditions and over 270 thousand sample pixels were considered during calibration. Second, we studied the effect of the Gaussian denoising filter on a steep oxygen gradient and investigated the impact when the smoothing filter is applied during data processing. Finally, we demonstrated the effectiveness of a Savitzky-Golay filter compared to the well-established Gaussian filter.