Metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy

Rapid Antibiotic Susceptibility Determination by Fluorescence Lifetime Tracking of Bacterial Metabolism

To combat the rise of antibiotic-resistance in bacteria and the resulting effects on healthcare worldwide, new technologies are needed that can perform rapid antibiotic susceptibility testing (AST). Conventional clinical methods for AST rely on growth-based assays, which typically require long incubation times to obtain quantitative results, representing a major bottleneck in the determination of the optimal antibiotic regimen to treat patients. Here, we demonstrate a rapid AST method based on the metabolic activity measured by fluorescence lifetime imaging microscopy (FLIM). Using lab strains and clinical isolates of Escherichia coli with tetracycline-susceptible and resistant phenotypes as models, we demonstrate that changes in metabolic state associated with antibiotic susceptibility can be quantitatively tracked by FLIM. Our results show that the magnitude of metabolic perturbation resulting from antibiotic activity correlates with susceptibility evaluated by conventional metrics. Moreover, susceptible and resistant phenotypes can be differentiated in as short as 10 min after antibiotic exposure. This FLIM-AST (FAST) method can be applied to other antibiotics and provides insights into the nature of metabolic perturbations inside bacterial cells resulting from antibiotic exposure with single cell resolution.

The use of fluorescence lifetime imaging (FLIM) for in situ microbial detection in complex mineral substrates

The utility of fluorescence lifetime imaging microscopy (FLIM) for identifying bacteria in complex mineral matrices was investigated. Baseline signals from unlabelled Bacillus subtilis and Euglena gracilis, and Bacillus subtilis labelled with SYTO 9 were obtained using two-photon excitation at 730, 750 and 800 nm, identifying characteristic lifetimes of photosynthetic pigments, unpigmented cellular autofluorescence, and SYTO 9. Labelled and unlabelled B. subtilis were seeded onto marble and gypsum samples containing endolithic photosynthetic cyanobacteria and the ability to distinguish cells from mineral autofluorescence and nonspecific dye staining was examined in parallel with ordinary multichannel confocal imaging. It was found that FLIM enabled discrimination of SYTO 9 labelled cells from background, but that the lifetime of SYTO 9 was shorter in cells on minerals than in pure culture under our conditions. Photosynthetic microorganisms were easily observed using both FLIM and confocal. Unlabelled, nonpigmented bacteria showed weak signals that were difficult to distinguish from background when minerals were present, though cellular autofluorescence consistent with NAD(P)H could be seen in pure cultures, and phasor analysis permitted detection on rocks. Gypsum and marble samples showed similar autofluorescence profiles, with little autofluorescence in the yellow-to-red range. Lifetime or time-gated imaging may prove a useful tool for environmental microbiology. LAY DESCRIPTION: The standard method of bacterial enumeration is to label the cells with a fluorescent dye and count them under high-power fluorescence microscopy. However, this can be difficult when the cells are embedded in soil and rock due to fluorescence from the surrounding minerals and dye binding to ambiguous features of the substrate. The use of fluorescence lifetime imaging (FLIM) can disambiguate these signals and allow for improved detection of bacteria in environmental samples.

Itaconic acid and dimethyl itaconate exert antibacterial activity in carbon-enriched environments through the TCA cycle

Itaconic acid (IA), a metabolite generated by the tricarboxylic acid (TCA) cycle in eukaryotic immune cells, and its derivative dimethyl itaconate (DI) exert antibacterial functions in intracellular environments. Previous studies suggested that IA and DI only inhibit bacterial growth in carbon-limited environments; however, whether IA and DI maintain antibacterial activity in carbon-enriched environments remains unknown. Here, IA and DI inhibited the bacteria with minimum inhibitory concentrations of 24.02 mM and 39.52 mM, respectively, in a carbon-enriched environment. The reduced bacterial pathogenicity was reflected in cell membrane integrity, motility, biofilm formation, AI-2/luxS, and virulence. Mechanistically, succinate dehydrogenase (SDH) activity and fumaric acid levels decreased in the IA and DI treatments, while isocitrate lyase (ICL) activity was upregulated. Inhibited TCA circulation was also observed through untargeted metabolomics. In addition, energy-related aspartate metabolism and lysine degradation were suppressed. In summary, these results indicated that IA and DI reduced bacterial pathogenicity while exerting antibacterial functions by inhibiting TCA circulation. This study enriches knowledge on the inhibition of bacteria by IA and DI in a carbon-mixed environment, suggesting an alternative method for treating bacterial infections by immune metabolites.

Antibacterial activity and mechanisms of α-terpineol against foodborne pathogenic bacteria

This study aimed to evaluate the antibacterial activities of α-terpineol against common foodborne pathogenic bacteria by agar well diffusion, broth microdilution, and colony counting assay. Propulsive research was conducted to reveal the antibacterial mechanisms, including morphology, infrared spectroscopy, membrane fluidity, membrane permeability, proton motive force, and oxidative phosphorylation. Results indicated that the antibacterial activity of α-terpineol decreased in the following order: Escherichia coli O157:H7, Salmonella typhimurium, Listeria monocytogenes, and Staphylococcus aureus. With an initial cell count of 8 log CFU/mL, α-terpineol at 0.8% (v/v) reduced E. coli O157:H7 and S. aureus by approximately 5.6 and 3.9 log CFU/mL within 1 h, respectively. Remarkable destruction in cell envelopes and intracellular organizations was observed. The hydroxyl of α-terpineol might form glycosidic bonds with carbohydrates and hydrogen bonds with PO2- and COO- via infrared spectroscopy analysis. Generalized polarization of Laurdan revealed that the polar head groups of phospholipids transformed into close packed. The anisotropy variations of trimethyl amino-diphenylhexatriene (TMA-DPH) and DPH suggested membrane fluidity decreased. The N-phenyl-1-naphthylamine intake assay indicated that α-terpineol impaired the cell wall. Propidium iodide staining was indicative of damaged plasma membranes. Electron transport in the cytoplasmic membrane was impaired, inducing reactive oxygen species accumulation. Both membrane electrical potential and membrane pH gradient collapsed. The disruption of proton motive force and the leakage of ATP resulted in a deficit of intracellular ATP. Our research revealed the interaction between the hydroxyl group of α-terpineol and bacteria affects membrane function contributing to the bacteria's death. KEY POINTS: • α-Terpineol hydroxy formed glycosidic bonds and hydrogen bonds with bacteria • α-Terpineol increased the membrane gelation and reduced the membrane fluidity • Proton motive force and oxidative phosphorylation were impaired.

Probing organoid metabolism using fluorescence lifetime imaging microscopy (FLIM): The next frontier of drug discovery and disease understanding

Organoid models have been used to address important questions in developmental and cancer biology, tissue repair, advanced modelling of disease and therapies, among other bioengineering applications. Such 3D microenvironmental models can investigate the regulation of cell metabolism, and provide key insights into the mechanisms at the basis of cell growth, differentiation, communication, interactions with the environment and cell death. Their accessibility and complexity, based on 3D spatial and temporal heterogeneity, make organoids suitable for the application of novel, dynamic imaging microscopy methods, such as fluorescence lifetime imaging microscopy (FLIM) and related decay time-assessing readouts. Several biomarkers and assays have been proposed to study cell metabolism by FLIM in various organoid models. Herein, we present an expert-opinion discussion on the principles of FLIM and PLIM, instrumentation and data collection and analysis protocols, and general and emerging biosensor-based approaches, to highlight the pioneering work being performed in this field.

Quantitative Spectroscopic Characterization of Near-UV/visible E. coli (pYAC4), B. subtilis (PY79), and Green Bread Mold Fungus Fluorescence for Diagnostic Applications

Ultraviolet (UV)-excited visible fluorescence is an attractive option for low-cost, low-complexity, rapid imaging of bacterial and fungal samples for imaging diagnostics in the biomedical community. While several studies have shown there is potential for identification of microbial samples, very little quantitative information is available in the literature for the purposes of diagnostic design. In this work, two non-pathogenic bacteria samples (E. coli pYAC4, and B. subtilis PY79) and a wild-cultivated green bread mold fungus sample are characterized spectroscopically for the purpose of diagnostic design. For each sample, fluorescence spectra excited with low-power near-UV continuous wave (CW) sources, and extinction and elastic scattering spectra are captured and compared. Absolute fluorescence intensity per cell excited at 340 nm is estimated from imaging measurements of aqueous samples. The results are used to estimate detection limits for a prototypical imaging experiment. It was found that fluorescence imaging is feasible for as few as 35 bacteria cells (or [Formula: see text]30 µm3 of bacteria) per pixel, and that the fluorescence intensity per unit volume is similar for the three samples tested here. A discussion and model of the mechanism of bacterial fluorescence in E. coli is provided.

Formation and emergent dynamics of spatially organized microbial systems

Spatial organization is the norm rather than the exception in the microbial world. While the study of microbial physiology has been dominated by studies in well-mixed cultures, there is now increasing interest in understanding the role of spatial organization in microbial physiology, coexistence and evolution. Where studied, spatial organization has been shown to influence all three of these aspects. In this mini review and perspective article, we emphasize that the dynamics within spatially organized microbial systems (SOMS) are governed by feedbacks between local physico-chemical conditions, cell physiology and movement, and evolution. These feedbacks can give rise to emergent dynamics, which need to be studied through a combination of spatio-temporal measurements and mathematical models. We highlight the initial formation of SOMS and their emergent dynamics as two open areas of investigation for future studies. These studies will benefit from the development of model systems that can mimic natural ones in terms of species composition and spatial structure.

Comprehensive Investigation of Parameters Influencing Fluorescence Lifetime Imaging Microscopy in Frequency- and Time-Domain Illustrated by Phasor Plot Analysis

Having access to fluorescence lifetime, researchers can reveal in-depth details about the microenvironment as well as the physico-chemical state of the molecule under investigation. However, the high number of influencing factors might be an explanation for the strongly deviating values of fluorescent lifetimes for the same fluorophore reported in the literature. This could be the reason for the impression that inconsistent results are obtained depending on which detection and excitation scheme is used. To clarify this controversy, the two most common techniques for measuring fluorescence lifetimes in the time-domain and in the frequency-domain were implemented in one single microscopy setup and applied to a variety of fluorophores under different environmental conditions such as pH-value, temperature, solvent polarity, etc., along with distinct state forms that depend, for example, on the concentration. From a vast amount of measurement results, both setup- and sample-dependent parameters were extracted and represented using a single display form, the phasor-plot. The measurements showed consistent results between the two techniques and revealed which of the tested parameters has the strongest influence on the fluorescence lifetime. In addition, quantitative guidance as to which technique is most suitable for which research task and how to perform the experiment properly to obtain consistent fluorescence lifetimes is discussed.

Rapid species identification of pathogenic bacteria from a minute quantity exploiting three-dimensional quantitative phase imaging and artificial neural network

The healthcare industry is in dire need of rapid microbial identification techniques for treating microbial infections. Microbial infections are a major healthcare issue worldwide, as these widespread diseases often develop into deadly symptoms. While studies have shown that an early appropriate antibiotic treatment significantly reduces the mortality of an infection, this effective treatment is difficult to practice. The main obstacle to early appropriate antibiotic treatments is the long turnaround time of the routine microbial identification, which includes time-consuming sample growth. Here, we propose a microscopy-based framework that identifies the pathogen from single to few cells. Our framework obtains and exploits the morphology of the limited sample by incorporating three-dimensional quantitative phase imaging and an artificial neural network. We demonstrate the identification of 19 bacterial species that cause bloodstream infections, achieving an accuracy of 82.5% from an individual bacterial cell or cluster. This performance, comparable to that of the gold standard mass spectroscopy under a sufficient amount of sample, underpins the effectiveness of our framework in clinical applications. Furthermore, our accuracy increases with multiple measurements, reaching 99.9% with seven different measurements of cells or clusters. We believe that our framework can serve as a beneficial advisory tool for clinicians during the initial treatment of infections.

Use of Flavin-Related Cellular Autofluorescence to Monitor Processes in Microbial Biotechnology

Cellular autofluorescence is usually considered to be a negative phenomenon because it can affect the sensitivity of fluorescence microscopic or flow cytometric assays by interfering with the signal of various fluorescent probes. Nevertheless, in our work, we adopted a different approach, and green autofluorescence induced by flavins was used as a tool to monitor fermentation employing the bacterium Cupriavidus necator. The autofluorescence was used to distinguish microbial cells from abiotic particles in flow cytometry assays, and it was also used for the determination of viability or metabolic characteristics of the microbial cells. The analyses using two complementary techniques, namely fluorescence microscopy and flow cytometry, are simple and do not require labor sample preparation. Flavins and their autofluorescence can also be used in a combination with other fluorophores when the need for multi-parametrical analyses arises, but it is wise to use dyes that do not emit a green light in order to not interfere with flavins' emission band (500-550 nm).

Toward absolute viability measurements for bacteria

We aim to develop a quantitative viability method that distinguishes individual quiescent from dead cells and is measured in time (ns) as a referenceable, comparable quantity. We demonstrate that fluorescence lifetime imaging of an anionic, fluorescent membrane voltage probe fulfills these requirements for Streptococcus mutans. A random forest machine-learning model assesses whether individual S. mutans can be correctly classified into their original populations: stationary phase (quiescent), heat killed and inactivated via chemical fixation. We compare the results to intensity using three models: lifetime variables (τ₁ , τ₂ and p₁ ), phasor variables (G, S) or all five variables, with the five variable models having the most accurate classification. This initial work affirms the potential for using fluorescence lifetime of a membrane voltage probe as a viability marker for quiescent bacteria, and future efforts on other bacterial species and fluorophores will help refine this approach.

Fluorescence Lifetime Imaging Microscopy of Porphyrins in Helicobacter pylori Biofilms

Bacterial biofilm constitutes a strong barrier against the penetration of drugs and against the action of the host immune system causing persistent infections hardly treatable by antibiotic therapy. Helicobacter pylori (Hp), the main causative agent for gastritis, peptic ulcer and gastric adenocarcinoma, can form a biofilm composed by an exopolysaccharide matrix layer covering the gastric surface where the bacterial cells become resistant and tolerant to the commonly used antibiotics clarithromycin, amoxicillin and metronidazole. Antimicrobial PhotoDynamic Therapy (aPDT) was proposed as an alternative treatment strategy for eradicating bacterial infections, particularly effective for Hp since this microorganism produces and stores up photosensitizing porphyrins. The knowledge of the photophysical characteristics of Hp porphyrins in their physiological biofilm microenvironment is crucial to implement and optimize the photodynamic treatment. Fluorescence lifetime imaging microscopy (FLIM) of intrinsic bacterial porphyrins was performed and data were analyzed by the 'fit-free' phasor approach in order to map the distribution of the different fluorescent species within Hp biofilm. Porphyrins inside bacteria were easily distinguished from those dispersed in the matrix suggesting FLIM-phasor technique as a sensitive and rapid tool to monitor the photosensitizer distribution inside bacterial biofilms and to better orientate the phototherapeutic strategy.

Roadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formation

Bacterial biofilms are communities of bacteria that exist as aggregates that can adhere to surfaces or be free-standing. This complex, social mode of cellular organization is fundamental to the physiology of microbes and often exhibits surprising behavior. Bacterial biofilms are more than the sum of their parts: single-cell behavior has a complex relation to collective community behavior, in a manner perhaps cognate to the complex relation between atomic physics and condensed matter physics. Biofilm microbiology is a relatively young field by biology standards, but it has already attracted intense attention from physicists. Sometimes, this attention takes the form of seeing biofilms as inspiration for new physics. In this roadmap, we highlight the work of those who have taken the opposite strategy: we highlight the work of physicists and physical scientists who use physics to engage fundamental concepts in bacterial biofilm microbiology, including adhesion, sensing, motility, signaling, memory, energy flow, community formation and cooperativity. These contributions are juxtaposed with microbiologists who have made recent important discoveries on bacterial biofilms using state-of-the-art physical methods. The contributions to this roadmap exemplify how well physics and biology can be combined to achieve a new synthesis, rather than just a division of labor.

Restructured Mitochondrial-Nuclear Interaction in Plasmodium falciparum Dormancy and Persister Survival after Artemisinin Exposure

Artemisinin and its semisynthetic derivatives (ART) are fast acting, potent antimalarials; however, their use in malaria treatment is frequently confounded by recrudescences from bloodstream Plasmodium parasites that enter into and later reactivate from a dormant persister state. Here, we provide evidence that the mitochondria of dihydroartemisinin (DHA)-exposed persisters are dramatically altered and enlarged relative to the mitochondria of young, actively replicating ring forms. Restructured mitochondrial-nuclear associations and an altered metabolic state are consistent with stress from reactive oxygen species. New contacts between the mitochondria and nuclei may support communication pathways of mitochondrial retrograde signaling, resulting in transcriptional changes in the nucleus as a survival response. Further characterization of the organelle communication and metabolic dependencies of persisters may suggest strategies to combat recrudescences of malaria after treatment.

Zinc limitation triggers anticipatory adaptations in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) has complex and dynamic interactions with the human host, and subpopulations of Mtb that emerge during infection can influence disease outcomes. This study implicates zinc ion (Zn2+) availability as a likely driver of bacterial phenotypic heterogeneity in vivo. Zn2+ sequestration is part of "nutritional immunity", where the immune system limits micronutrients to control pathogen growth, but this defense mechanism seems to be ineffective in controlling Mtb infection. Nonetheless, Zn2+-limitation is an environmental cue sensed by Mtb, as calprotectin triggers the zinc uptake regulator (Zur) regulon response in vitro and co-localizes with Zn2+-limited Mtb in vivo. Prolonged Zn2+ limitation leads to numerous physiological changes in vitro, including differential expression of certain antigens, alterations in lipid metabolism and distinct cell surface morphology. Furthermore, Mtb enduring limited Zn2+ employ defensive measures to fight oxidative stress, by increasing expression of proteins involved in DNA repair and antioxidant activity, including well described virulence factors KatG and AhpC, along with altered utilization of redox cofactors. Here, we propose a model in which prolonged Zn2+ limitation defines a population of Mtb with anticipatory adaptations against impending immune attack, based on the evidence that Zn2+-limited Mtb are more resistant to oxidative stress and exhibit increased survival and induce more severe pulmonary granulomas in mice. Considering that extracellular Mtb may transit through the Zn2+-limited caseum before infecting naïve immune cells or upon host-to-host transmission, the resulting phenotypic heterogeneity driven by varied Zn2+ availability likely plays a key role during early interactions with host cells.

FLIM data analysis based on Laguerre polynomial decomposition and machine-learning

SIGNIFICANCE

The potential of fluorescence lifetime imaging microscopy (FLIM) is recently being recognized, especially in biological studies. However, FLIM does not directly measure the lifetimes, rather it records the fluorescence decay traces. The lifetimes and/or abundances have to be estimated from these traces during the phase of data processing. To precisely estimate these parameters is challenging and requires a well-designed computer program. Conventionally employed methods, which are based on curve fitting, are computationally expensive and limited in performance especially for highly noisy FLIM data. The graphical analysis, while free of fit, requires calibration samples for a quantitative analysis.

AIM

We propose to extract the lifetimes and abundances directly from the decay traces through machine learning (ML).

APPROACH

The ML-based approach was verified with simulated testing data in which the lifetimes and abundances were known exactly. Thereafter, we compared its performance with the commercial software SPCImage based on datasets measured from biological samples on a time-correlated single photon counting system. We reconstructed the decay traces using the lifetime and abundance values estimated by ML and SPCImage methods and utilized the root-mean-squared-error (RMSE) as marker.

RESULTS

The RMSE, which represents the difference between the reconstructed and measured decay traces, was observed to be lower for ML than for SPCImage. In addition, we could demonstrate with a three-component analysis the high potential and flexibility of the ML method to deal with more than two lifetime components.

CONCLUSIONS

The ML-based approach shows great performance in FLIM data analysis.

Machine Learning Methods for Fluorescence Lifetime Imaging (FLIM) Based Label-Free Detection of Microglia

Automated computational analysis techniques utilizing machine learning have been demonstrated to be able to extract more data from different imaging modalities compared to traditional analysis techniques. One new approach is to use machine learning techniques to existing multiphoton imaging modalities to better interpret intrinsically fluorescent cellular signals to characterize different cell types. Fluorescence Lifetime Imaging Microscopy (FLIM) is a high-resolution quantitative imaging tool that can detect metabolic cellular signatures based on the lifetime variations of intrinsically fluorescent metabolic co-factors such as nicotinamide adenine dinucleotide [NAD(P)H]. NAD(P)H lifetime-based discrimination techniques have previously been used to develop metabolic cell signatures for diverse cell types including immune cells such as macrophages. However, FLIM could be even more effective in characterizing cell types if machine learning was used to classify cells by utilizing FLIM parameters for classification. Here, we demonstrate the potential for FLIM-based, label-free NAD(P)H imaging to distinguish different cell types using Artificial Neural Network (ANN)-based machine learning. For our biological use case, we used the challenge of differentiating microglia from other glia cell types in the brain. Microglia are the resident macrophages of the brain and spinal cord and play a critical role in maintaining the neural environment and responding to injury. Microglia are challenging to identify as most fluorescent labeling approaches cross-react with other immune cell types, are often insensitive to activation state, and require the use of multiple specialized antibody labels. Furthermore, the use of these extrinsic antibody labels prevents application in in vivo animal models and possible future clinical adaptations such as neurodegenerative pathologies. With the ANN-based NAD(P)H FLIM analysis approach, we found that microglia in cell culture mixed with other glial cells can be identified with more than 0.9 True Positive Rate (TPR). We also extended our approach to identify microglia in fixed brain tissue with a TPR of 0.79. In both cases the False Discovery Rate was around 30%. This method can be further extended to potentially study and better understand microglia’s role in neurodegenerative disease with improved detection accuracy.

Microglia activation visualization via fluorescence lifetime imaging microscopy of intrinsically fluorescent metabolic cofactors

Significance: A major obstacle to studying resident microglia has been their similarity to infiltrating immune cell types and the lack of unique protein markers for identifying the functional state. Given the role of microglia in all neural diseases and insults, accurate tools for detecting their function beyond morphologic alterations are necessary. Aims: We hypothesized that microglia would have unique metabolic fluxes in reduced nicotinamide adenine dinucleotide (NADH) that would be detectable by relative changes in fluorescence lifetime imaging microscopy (FLIM) parameters, allowing for identification of their activation status. Fluorescence lifetime of NADH has been previously demonstrated to show differences in metabolic fluxes. Approach: Here, we investigate the use of the label-free method of FLIM-based detection of the endogenous metabolic cofactor NADH to identify microglia and characterize their activation status. To test whether microglial activation would also confer a unique NADH lifetime signature, murine primary microglial cultures and adult mice were treated with lipopolysaccharide (LPS). Results: We found that LPS-induced microglia activation correlates with detected changes in NADH lifetime and its free-bound ratio. This indicates that NADH lifetime can be used to monitor microglia activation in a label-free fashion. Moreover, we found that there is an LPS dose-dependent change associated with reactive microglia lifetime fluxes, which is also replicated over time after LPS treatment. Conclusion: We have demonstrated a label-free way of monitoring microglia activation via quantifying lifetime of endogenous metabolic coenzyme NADH. Upon LPS-induced activation, there is a significant change in the fluorescence lifetime following activation. Together, these results indicate that NADH FLIM approaches can be used as a method to characterize microglia activation state, both in vitro and ex vivo.

Quantitative High-Resolution Imaging of Live Microbial Cells at High Hydrostatic Pressure

The majority of the Earth's microbial biomass exists in the deep biosphere, in the deep ocean, and within the Earth's crust. Although other physical parameters in these environments, such as temperature or pH, can differ substantially, they are all under high pressures. Beyond emerging genomic information, little is known about the molecular mechanisms underlying the ability of these organisms to survive and grow at pressures that can reach over 1000-fold the pressure on the Earth's surface. The mechanisms of pressure adaptation are also important in food safety, with the increasing use of high-pressure food processing. Advanced imaging represents an important tool for exploring microbial adaptation and response to environmental changes. Here, we describe implementation of a high-pressure sample chamber with a two-photon scanning microscope system, allowing for the first time, to our knowledge, quantitative high-resolution two-photon imaging at 100 MPa of living microbes from all three kingdoms of life. We adapted this setup for fluorescence lifetime imaging microscopy with phasor analysis (FLIM/Phasor) and investigated metabolic responses to pressure of live cells from mesophilic yeast and bacterial strains, as well as the piezophilic archaeon Archaeoglobus fulgidus. We also monitored by fluorescence intensity fluctuation-based methods (scanning number and brightness and raster scanning imaging correlation spectroscopy) the effect of pressure on the chromosome-associated protein HU and on the ParB partition protein in Escherichia coli, revealing partially reversible dissociation of ParB foci and concomitant nucleoid condensation. These results provide a proof of principle that quantitative, high-resolution imaging of live microbial cells can be carried out at pressures equivalent to those in the deepest ocean trenches.

A Shift in Central Metabolism Accompanies Virulence Activation in Pseudomonas aeruginosa

The availability of energy has significant impact on cell physiology. However, the role of cellular metabolism in bacterial pathogenesis is not understood. We investigated the dynamics of central metabolism during virulence induction by surface sensing and quorum sensing in early-stage biofilms of the multidrug-resistant bacterium Pseudomonas aeruginosa We established a metabolic profile for P. aeruginosa using fluorescence lifetime imaging microscopy (FLIM), which reports the activity of NADH in live cells. We identified a critical growth transition period during which virulence is activated. We performed FLIM measurements and direct measurements of NADH and NAD+ concentrations during this period. Here, planktonic (low-virulence) and surface-attached (virulence-activated) populations diverged into distinct metabolic states, with the surface-attached population exhibiting FLIM lifetimes that were associated with lower levels of enzyme-bound NADH and decreasing total NAD(H) production. We inhibited virulence by perturbing central metabolism using citrate and pyruvate, which further decreased the enzyme-bound NADH fraction and total NAD(H) production and suggested the involvement of the glyoxylate pathway in virulence activation in surface-attached populations. In addition, we induced virulence at an earlier time using the electron transport chain oxidase inhibitor antimycin A. Our results demonstrate the use of FLIM to noninvasively measure NADH dynamics in biofilms and suggest a model in which a metabolic rearrangement accompanies the virulence activation period.IMPORTANCE The rise of antibiotic resistance requires the development of new strategies to combat bacterial infection and pathogenesis. A major direction has been the development of drugs that broadly target virulence. However, few targets have been identified due to the species-specific nature of many virulence regulators. The lack of a virulence regulator that is conserved across species has presented a further challenge to the development of therapeutics. Here, we identify that NADH activity has an important role in the induction of virulence in the pathogen P. aeruginosa This finding, coupled with the ubiquity of NADH in bacterial pathogens, opens up the possibility of targeting enzymes that process NADH as a potential broad antivirulence approach.

Discriminating Bacterial Phenotypes at the Population and Single-Cell Level: A Comparison of Flow Cytometry and Raman Spectroscopy Fingerprinting

Investigating phenotypic heterogeneity can help to better understand and manage microbial communities. However, characterizing phenotypic heterogeneity remains a challenge, as there is no standardized analysis framework. Several optical tools are available, such as flow cytometry and Raman spectroscopy, which describe optical properties of the individual cell. In this work, we compare Raman spectroscopy and flow cytometry to study phenotypic heterogeneity in bacterial populations. The growth stages of three replicate Escherichia coli populations were characterized using both technologies. Our findings show that flow cytometry detects and quantifies shifts in phenotypic heterogeneity at the population level due to its high-throughput nature. Raman spectroscopy, on the other hand, offers a much higher resolution at the single-cell level (i.e., more biochemical information is recorded). Therefore, it can identify distinct phenotypic populations when coupled with analyses tailored toward single-cell data. In addition, it provides information about biomolecules that are present, which can be linked to cell functionality. We propose a computational workflow to distinguish between bacterial phenotypic populations using Raman spectroscopy and validated this approach with an external data set. We recommend using flow cytometry to quantify phenotypic heterogeneity at the population level, and Raman spectroscopy to perform a more in-depth analysis of heterogeneity at the single-cell level. © 2019 International Society for Advancement of Cytometry.

Intra- and Interspecies Variability of Single-Cell Innate Fluorescence Signature of Microbial Cell

A cell’s innate fluorescence signature is an assemblage of fluorescence signals emitted by diverse biomolecules within a cell. It is known that the innate fluoresce signature reflects various cellular properties and physiological statuses; thus, they can serve as a rich source of information in cell characterization as well as cell identification. However, conventional techniques focus on the analysis of the innate fluorescence signatures at the population level but not at the single-cell level and thus necessitate a clonal culture. In the present study, we developed a technique to analyze the innate fluorescence signature of a single microbial cell. Using this novel method, we found that even very similarly shaped cells differ noticeably in their autofluorescence features, and the innate fluorescence signature changes dynamically with growth phases. We also demonstrated that the different cell types can be classified accurately within a mixed population under a microscope at the resolution of a single cell, depending solely on the innate fluorescence signature information. We suggest that single-cell autofluoresce signature analysis is a promising tool to directly assess the taxonomic or physiological heterogeneity within a microbial population, without cell tagging.

Here we analyzed the innate fluorescence signature of the single microbial cell, within both clonal and mixed populations of microorganisms. We found that even very similarly shaped cells differ noticeably in their autofluorescence features and that the innate fluorescence signatures change dynamically with growth phases. We demonstrated that machine learning models can be trained with a data set of single-cell innate fluorescence signatures to annotate cells according to their phenotypes and physiological status, for example, distinguishing a wild-type Aspergillus nidulans cell from its nitrogen metabolism mutant counterpart and log-phase cells from stationary-phase cells of Pseudomonas putida. We developed a minimally invasive method (confocal reflection microscopy-assisted single-cell innate fluorescence [CRIF] analysis) to optically extract and catalog the innate cellular fluorescence signatures of each of the individual live microbial cells in a three-dimensional space. This technique represents a step forward from traditional techniques which analyze the innate fluorescence signatures at the population level and necessitate a clonal culture. Since the fluorescence signature is an innate property of a cell, our technique allows the prediction of the types or physiological status of intact and tag-free single cells, within a cell population distributed in a three-dimensional space. Our study presents a blueprint for a streamlined cell analysis where one can directly assess the potential phenotype of each single cell in a heterogenous population by its autofluorescence signature under a microscope, without cell tagging.

IMPORTANCE A cell’s innate fluorescence signature is an assemblage of fluorescence signals emitted by diverse biomolecules within a cell. It is known that the innate fluoresce signature reflects various cellular properties and physiological statuses; thus, they can serve as a rich source of information in cell characterization as well as cell identification. However, conventional techniques focus on the analysis of the innate fluorescence signatures at the population level but not at the single-cell level and thus necessitate a clonal culture. In the present study, we developed a technique to analyze the innate fluorescence signature of a single microbial cell. Using this novel method, we found that even very similarly shaped cells differ noticeably in their autofluorescence features, and the innate fluorescence signature changes dynamically with growth phases. We also demonstrated that the different cell types can be classified accurately within a mixed population under a microscope at the resolution of a single cell, depending solely on the innate fluorescence signature information. We suggest that single-cell autofluoresce signature analysis is a promising tool to directly assess the taxonomic or physiological heterogeneity within a microbial population, without cell tagging.

Quantitative imaging and spectroscopic technologies for microbiology

Light microscopy has enabled the observation of the structure and organisation of biofilms. Typically, the contrast in an image obtained from light microscopy is given by the time-averaged intensity that is effective in visualising the overall structure. Technological advancements in light microscopy have led to the creation of techniques that not only provide a static intensity image of the biofilm, but also enable one to quantify various dynamic physicochemical properties of biomolecules in microbial biofilms. Such light microscopy-based techniques can be grouped into two main classes, those that are based on luminescence and those that are based on scattering. Here, we review the fundamentals and applications of luminescence and scattering-based techniques, specifically, fluorescence lifetime imaging, Förster resonance energy transfer, fluorescence correlation spectroscopy, fluorescence recovery after photobleaching, single-particle tracking, transient state imaging, and Brillouin and Raman microscopy. These techniques provide information about the abundance, interactions and mobility of various molecules in the biofilms and also properties of the local microenvironment at optical resolution. Further, one could use any of these techniques to probe the real-time changes in these physical parameters upon the addition of external agents or at different stages during the growth of biofilms.

Understanding Real-Time Fluorescence Signals from Bacteria and Wound Tissues Observed with the MolecuLight i:XTM

The persistent presence of pathogenic bacteria is one of the main obstacles to wound healing. Detection of wound bacteria relies on sampling methods, which delay confirmation by several days. However, a novel handheld fluorescence imaging device has recently enabled real-time detection of bacteria in wounds based on their intrinsic fluorescence characteristics, which differ from those of background tissues. This device illuminates the wound with violet (405 nm) light, causing tissues and bacteria to produce endogenous, characteristic fluorescence signals that are filtered and displayed on the device screen in real-time. The resulting images allow for rapid assessment and documentation of the presence, location, and extent of fluorescent bacteria at moderate-to-heavy loads. This information has been shown to assist in wound assessment and guide patient-specific treatment plans. However, proper image interpretation is essential to assessing this information. To properly identify regions of bacterial fluorescence, users must understand: (1) Fluorescence signals from tissues (e.g., wound tissues, tendon, bone) and fluids (e.g., blood, pus); (2) fluorescence signals from bacteria (red or cyan); (3) the rationale for varying hues of both tissue and bacterial fluorescence; (4) image artifacts that can occur; and (5) some potentially confounding signals from non-biological materials (e.g., fluorescent cleansing solutions). Therefore, this tutorial provides clinicians with a rationale for identifying common wound fluorescence characteristics. Clinical examples are intended to help clinicians with image interpretation-with a focus on image artifacts and potential confounders of image interpretation-and suggestions of how to overcome such challenges when imaging wounds in clinical practice.

Unraveling the host's immune response to infection: Seeing is believing

It has long been appreciated that understanding the interactions between the host and the pathogens that make us sick is critical for the prevention and treatment of disease. As antibiotics become increasingly ineffective, targeting the host and specific bacterial evasion mechanisms are becoming novel therapeutic approaches. The technology used to understand host‐pathogen interactions has dramatically advanced over the last century. We have moved away from using simple in vitro assays focused on single‐cell events to technologies that allow us to observe complex multicellular interactions in real time in live animals. Specifically, intravital microscopy (IVM) has improved our understanding of infection, from viral to bacterial to parasitic, and how the host immune system responds to these infections. Yet, at the same time it has allowed us to appreciate just how complex these interactions are and that current experimental models still have a number of limitations. In this review, we will discuss the advances in vivo IVM has brought to the study of host‐pathogen interactions, focusing primarily on bacterial infections and innate immunity.

Visualizing Oxidative Cellular Stress Induced by Nanoparticles in the Subcytotoxic Range Using Fluorescence Lifetime Imaging

Nanoparticles hold a great promise in biomedical science. However, due to their unique physical and chemical properties they can lead to overproduction of intracellular reactive oxygen species (ROS). As an important mechanism of nanotoxicity, there is a great need for sensitive and high-throughput adaptable single-cell ROS detection methods. Here, fluorescence lifetime imaging microscopy (FLIM) is employed for single-cell ROS detection (FLIM-ROX) providing increased sensitivity and enabling high-throughput analysis in fixed and live cells. FLIM-ROX owes its sensitivity to the discrimination of autofluorescence from the unique fluorescence lifetime of the ROS reporter dye. The effect of subcytotoxic amounts of cationic gold nanoparticles in J774A.1 cells and primary human macrophages on ROS generation is investigated. FLIM-ROX measures very low ROS levels upon gold nanoparticle exposure, which is undetectable by the conventional method. It is demonstrated that cellular morphology changes, elevated senescence, and DNA damage link the resulting low-level oxidative stress to cellular adverse effects and thus nanotoxicity. Multiphoton FLIM-ROX enables the quantification of spatial ROS distribution in vivo, which is shown for skin tissue as a target for nanoparticle exposure. Thus, this innovative method allows identifying of low-level ROS in vitro and in vivo and, subsequently, promotes understanding of ROS-associated nanotoxicity.

Toward an Axial Nanoscale Ruler for Fluorescence Microscopy

In the discussion of resolution in optical microscopy, axial precision has often come second to its lateral counterpart. However, biological systems make no special arrangements for our preferred direction of imaging. The ability to measure axial distances, that is, the heights of fluorophores relative to a plane of reference, is thus of paramount importance and has been the subject of several recent advances. A novel method is to modify the fluorescence emission based on the height of the individual fluorophore, such that its z-position is encoded somehow in the detected signal. One such approach is metal-enhanced energy transfer, recently extended to multicolor distance measurements and applied to study the topography of the nuclear membrane. Here, the fluorescence lifetime is shortened due to the proximity of the fluorophores to a thin metallic surface. Fluorescence lifetime imaging can therefore be used as an axial ruler with nanometer precision.