Development of heme protein based oxygen sensing indicators

Live Microscopy of Multicellular Spheroids with the Multimodal Near-Infrared Nanoparticles Reveals Differences in Oxygenation Gradients

Assessment of hypoxia, nutrients, metabolite gradients, and other hallmarks of the tumor microenvironment within 3D multicellular spheroid and organoid models represents a challenging analytical task. Here, we report red/near-infrared (NIR) emitting cell staining with O2-sensitive nanoparticles, which enable measurements of spheroid oxygenation on a conventional fluorescence microscope. Nanosensor probes, termed "MMIR" (multimodal infrared), incorporate an NIR O2-sensitive metalloporphyrin (PtTPTBPF) and deep red aza-BODIPY reference dyes within a biocompatible polymer shell, allowing for oxygen gradient quantification via fluorescence ratio and phosphorescence lifetime readouts. We optimized staining techniques and evaluated the nanosensor probe characteristics and cytotoxicity. Subsequently, we applied nanosensors to the live spheroid models based on HCT116, DPSCs, and SKOV3 cells, at rest, and treated with drugs affecting cell respiration. We found that the growth medium viscosity, spheroid size, and formation method influenced spheroid oxygenation. Some spheroids produced from HCT116 and dental pulp stem cells exhibited "inverted" oxygenation gradients, with higher core oxygen levels than the periphery. This contrasted with the frequently encountered "normal" gradient of hypoxia toward the core caused by diffusion. Further microscopy analysis of spheroids with an "inverted" gradient demonstrated metabolic stratification of cells within spheroids: thus, autofluorescence FLIM of NAD(P)H indicated the formation of a glycolytic core and localization of OxPhos-active cells at the periphery. Collectively, we demonstrate a strong potential of NIR-emitting ratiometric nanosensors for advanced microscopy studies targeting live and quantitative real-time monitoring of cell metabolism and hypoxia in complex 3D tissue models.

Genetically Encoded Biosensors for the Fluorescence Detection of O2 and Reactive O2 Species

The intracellular concentrations of oxygen and reactive oxygen species (ROS) in living cells represent critical information for investigating physiological and pathological conditions. Real-time measurement often relies on genetically encoded proteins that are responsive to fluctuations in either oxygen or ROS concentrations. The direct binding or chemical reactions that occur in their presence either directly alter the fluorescence properties of the binding protein or alter the fluorescence properties of fusion partners, mostly consisting of variants of the green fluorescent protein. Oxygen sensing takes advantage of several mechanisms, including (i) the oxygen-dependent hydroxylation of a domain of the hypoxia-inducible factor-1, which, in turn, promotes its cellular degradation along with fluorescent fusion partners; (ii) the naturally oxygen-dependent maturation of the fluorophore of green fluorescent protein variants; and (iii) direct oxygen binding by proteins, including heme proteins, expressed in fusion with fluorescent partners, resulting in changes in fluorescence due to conformational alterations or fluorescence resonance energy transfer. ROS encompass a group of highly reactive chemicals that can interconvert through various chemical reactions within biological systems, posing challenges for their selective detection through genetically encoded sensors. However, their general reactivity, and particularly that of the relatively stable oxygen peroxide, can be exploited for ROS sensing through different mechanisms, including (i) the ROS-induced formation of disulfide bonds in engineered fluorescent proteins or fusion partners of fluorescent proteins, ultimately leading to fluorescence changes; and (ii) conformational changes of naturally occurring ROS-sensing domains, affecting the fluorescence properties of fusion partners. In this review, we will offer an overview of these genetically encoded biosensors.

Ratiometric Oxygen Sensing with H-NOX Protein Conjugates

Ratiometric sensors are self-referencing constructs that are functional in cells and tissues, and the read-out is independent of sensor concentration. One strategy for ratiometric sensing is to utilize two-color emission, where one component possesses analyte-dependent emission and the other is independent of analyte concentration, serving as an internal standard. In this way, the intensity ratio of the two components is a quantitative measure of the analyte. In this study, protein-based ratiometric oxygen sensors are prepared using the heme nitric oxide/oxygen-binding protein (H-NOX) from the thermophilic bacterium Caldanaerobacter subterraneus. The native heme cofactor is replaced with a Pd(II) or Pt(II) porphyrin as the oxygen-responsive phosphor. Mutagenesis is performed to incorporate a cysteine residue on the protein surface for thiol/maleimide coupling of the oxygen-insensitive dye, which serves as a Förster resonance energy transfer (FRET) donor for the porphyrin. While both Pd(II)- and Pt(II)-based sensors are responsive over biologically relevant ranges, the Pd sensor exhibits greater sensitivity at lower oxygen concentrations. Together, these sensors represent a new class of protein-based ratiometric oxygen sensors, and the modular platform allows the oxygen sensitivity to be tailored for a specific application. This proof-of-principle study has identified the key considerations and optimal methodologies to develop and subsequently refine protein-based ratiometric oxygen sensors.

In Vivo Imaging of Plant Oxygen Levels

Oxygen is essential for multicellular aerobic life due to its central role in energy metabolism. The availability of oxygen can drop below the level to sustain oxidative phosphorylation when plants are flooded, posing a severe threat to survival. However, under non-stressful conditions, the internal oxygen concentration of most plant tissue is not in equilibrium with the environment, which is attributed to cellular respiration and diffusion constrains imposed by O2 barriers and bulky tissue. This is exemplified by the observations of steep oxygen gradients in roots, fruits, tubers, anthers and meristems. To adapt to a varying availability of oxygen, plants sense O2 via the conditional proteolysis of transcriptional regulators. This mechanism acts to switch oxidative metabolism to anaerobic fermentation, but it was also shown to play a role in plant development and pathogen defense. To investigate how dynamic and spatial distribution of O2 impacts on these processes, accurate mapping of its concentration in plants is essential. Physical oxygen sensors have been employed for decades to profile internal oxygen concentrations in plants, while genetically encoded oxygen biosensors have only recently started to see use. Driven by the critical role of hypoxia in human pathology and development, several novel oxygen-sensing devices have also been characterized in cell lines and animal model organisms. This review aims to provide an overview of available oxygen biosensors and to discuss their potential application to image oxygen levels in plants.

Synthetic biology of hypoxia

Synthetic biology can greatly aid the investigation of fundamental regulatory mechanisms and enable their direct deployment in the host organisms of choice. In the field of plant hypoxia physiology, a synthetic biology approach has recently been exploited to infer general properties of the plant oxygen sensing mechanism, by expression of plant-specific components in yeast. Moreover, genetic sensors have been devised to report cellular oxygen levels or physiological parameters associated with hypoxia, and orthogonal switches have been introduced in plants to trigger oxygen-specific responses. Upcoming applications are expected, such as genetic tailoring of oxygen-responsive traits, engineering of plant hypoxic metabolism and oxygen delivery to hypoxic tissues, and expansion of the repertoire of genetically encoded oxygen sensors.

Fluorescent Biosensors for Neuronal Metabolism and the Challenges of Quantitation

Over the past decade, genetically encoded fluorescent biosensors that report metabolic changes have become valuable tools for understanding brain metabolism. These sensors have been targeted to specific brain regions and cell types in different organisms to track multiple metabolic processes at single cell (and subcellular) resolution. Here, we review genetically encoded biosensors used to study metabolism in the brain. We particularly focus on the principles needed to use these sensors quantitatively while avoiding false inferences from variations in sensor fluorescence that arise from differences in expression level or environmental influences such as pH or temperature.

Genetically Encoded Tools for Research of Cell Signaling and Metabolism under Brain Hypoxia

Hypoxia is characterized by low oxygen content in the tissues. The central nervous system (CNS) is highly vulnerable to a lack of oxygen. Prolonged hypoxia leads to the death of brain cells, which underlies the development of many pathological conditions. Despite the relevance of the topic, different approaches used to study the molecular mechanisms of hypoxia have many limitations. One promising lead is the use of various genetically encoded tools that allow for the observation of intracellular parameters in living systems. In the first part of this review, we provide the classification of oxygen/hypoxia reporters as well as describe other genetically encoded reporters for various metabolic and redox parameters that could be implemented in hypoxia studies. In the second part, we discuss the advantages and disadvantages of the primary hypoxia model systems and highlight inspiring examples of research in which these experimental settings were combined with genetically encoded reporters.

Gas-Sensing Transcriptional Regulators

Gas molecules are ubiquitous in the environment and are used as nutrient and energy sources for living organisms. Many organisms, therefore, have developed gas-sensing systems to respond efficiently to changes in the atmospheric environment. In microorganisms and plants, two-component systems (TCSs) and transcription factors (TFs) are two primary mechanisms to sense gas molecules. In this review, gas-sensing transcriptional regulators, TCSs, and TFs, focusing on protein structures, mechanisms of gas molecule interaction, DNA binding regions of transcriptional regulators, signal transduction mechanisms, and gene expression regulation are discussed. At first, transcriptional regulators that directly sense gas molecules with the help of a prosthetic group is described and then gas-sensing systems that indirectly recognize the presence of gas molecules is explained. Overall, this review provides a comprehensive understanding of gas-sensing transcriptional regulators in microorganisms and plants, and proposes a future perspective on the use of gas-sensing transcriptional regulators.

Adaptation of the Alphaproteobacterium Rhodobacter sphaeroides to stationary phase

Exhaustion of nutritional resources stimulates bacterial populations to adapt their growth behaviour. General mechanisms are known to facilitate this adaptation by sensing the environmental change and coordinating gene expression. However, the existence of such mechanisms among the Alphaproteobacteria remains unclear. This study focusses on global changes in transcript levels during growth under carbon-limiting conditions in a model Alphaproteobacterium, Rhodobacter sphaeroides, a metabolically diverse organism capable of multiple modes of growth including aerobic and anaerobic respiration, anaerobic anoxygenic photosynthesis and fermentation. We identified genes that showed changed transcript levels independently of oxygen levels during the adaptation to stationary phase. We selected a subset of these genes and subjected them to mutational analysis, including genes predicted to be involved in manganese uptake, polyhydroxybutyrate production and quorum sensing and an alternative sigma factor. Although these genes have not been previously associated with the adaptation to stationary phase, we found that all were important to varying degrees. We conclude that while R. sphaeroides appears to lack a rpoS-like master regulator of stationary phase adaptation, this adaptation is nonetheless enabled through the impact of multiple genes, each responding to environmental conditions and contributing to the adaptation to stationary phase.

The Interplay between Salmonella enterica Serovar Typhimurium and the Intestinal Mucosa during Oral Infection

Bacterial infection results in a dynamic interplay between the pathogen and its host. The underlying interactions are multilayered, and the cellular responses are modulated by the local environment. The intestine is a particularly interesting tissue regarding host-pathogen interaction. It is densely colonized by commensal microbes and a portal of entry for ingested pathogens. This necessitates constant monitoring of microbial stimuli in order to maintain homeostasis during encounters with benign microbiota and to trigger immune defenses in response to bacterial pathogens. Homeostasis is maintained by physical barriers (the mucus layer and epithelium), chemical defenses (antimicrobial peptides), and innate immune responses (NLRC4 inflammasome), which keep the bacteria from reaching the sterile lamina propria. Intestinal pathogens represent potent experimental tools to probe these barriers and decipher how pathogens can circumvent them. The streptomycin mouse model of oral Salmonella enterica serovar Typhimurium infection provides a well-characterized, robust experimental system for such studies. Strikingly, each stage of the gut tissue infection poses a different set of challenges to the pathogen and requires tight control of virulence factor expression, host response modulation, and cooperation between phenotypic subpopulations. Therefore, successful infection of the intestinal tissue relies on a delicate and dynamic balance between responses of the pathogen and its host. These mechanisms can be deciphered to their full extent only in realistic in vivo infection models.