Spectral phasor analysis allows rapid and reliable unmixing of fluorescence microscopy spectral images

Automatic segmentation of lysosomes and analysis of intracellular pH with Radachlorin photosensitizer and FLIM

We report application of the fluorescence lifetime imaging microscopy (FLIM) for analysis of distributions of intracellular acidity using a chlorin-e6 based photosensitizer Radachlorin. An almost two-fold increase of the photosensitizer fluorescence lifetime in alkaline microenvironments as compared to acidic ones allowed for clear distinguishing between acidic and alkaline intracellular structures. Clusterization of a phasor plot calculated from fits of the FLIM raw data by two Gaussian distributions provided accurate automatic segmentation of lysosomes featuring acidic contents. The approach was validated in colocalization experiments with LysoTracker fluorescence in living cells of four established lines. The dependence of photosensitizer fluorescence lifetime on microenvironment acidity allowed for estimation of pH inside the cells, except for the nuclei, where photosensitizer does not penetrate. The developed method is promising for combined application of the photosensitizer for both photodynamic treatment and diagnostics.

Programmable hyperspectral coherent anti-Stokes Raman scattering microscopy

Hyperspectral coherent Raman scattering microscopy provides a significant improvement in acquisition time compared to spontaneous Raman scattering yet still suffers from the time required to sweep through individual wavenumbers. To address this, we present the use of a pulse shaper with a 2D spatial light modulator for phase- and amplitude-based shaping of the Stokes beam to create programmable spectrally tailored excitation envelopes. This enables collection of useful spectral information in a more rapid and efficient manner.

Spectral Phasor Applied to Spectrally-Resolved Single Molecule Localization Microscopy

Spectrally-resolved single-molecule localization microscopy (srSMLM) has emerged as a powerful tool for exploring the spectral properties of single emitters in localization microscopy. By simultaneously capturing the spatial positions and spectroscopic signatures of individual fluorescent molecules, srSMLM opens up the possibility of investigating an additional dimension in super-resolution imaging. However, appropriate and dedicated tools are required to fully capitalize on the spectral dimension. Here, we propose the application of the spectral phasor analysis as an effective method for summarizing and analyzing the spectral information obtained from srSMLM experiments. The spectral phasor condenses the complete spectrum of a single emitter into a two-dimensional space, preserving key spectral characteristics for single-molecule spectral exploration. We demonstrate the effectiveness of spectral phasor in efficiently classifying single Nile Red fluorescence emissions from largely overlapping cyanine fluorescence signals in dual-color PAINT experiments. Additionally, we employed spectral phasor with srSMLM to reveal subtle alterations occurring in the membrane of Gram-positive Enterococcus hirae in response to gramicidin exposure, a membrane-perturbing antibiotic treatment. Spectral phasor provides a robust, model-free analytic tool for the detailed analysis of the spectral component of srSMLM, enhancing the capabilities of multi-color spectrally-resolved single-molecule imaging.

Quantifying Fluorescence Lifetime Responsiveness of Environment-Sensitive Probes for Membrane Fluidity Measurements

The structural diversity of different lipid species within the membrane defines its biophysical properties such as membrane fluidity, phase transition, curvature, charge distribution, and tension. Environment-sensitive probes, which change their spectral properties in response to their surrounding milieu, have greatly contributed to our understanding of such biophysical properties. To realize the full potential of these probes and avoid misinterpretation of their spectral responses, a detailed investigation of their fluorescence characteristics in different environments is necessary. Here, we examined the fluorescence lifetime of two newly developed membrane order probes, NR12S and NR12A, in response to alterations in their environments such as the degree of lipid saturation, cholesterol content, double bond position and configuration, and phospholipid headgroup. As a comparison, we investigated the lifetime sensitivity of the membrane tension probe Flipper in these environments. Applying fluorescence lifetime imaging microscopy (FLIM) in both model membranes and biological membranes, all probes distinguished membrane phases by lifetime but exhibited different lifetime sensitivities to varying membrane biophysical properties (e.g., cholesterol). While the lifetime of Flipper is particularly sensitive to the membrane cholesterol content, the NR12S and NR12A lifetimes are moderately sensitive to both the cholesterol content and lipid acyl chains. Moreover, all of the probes exhibit longer lifetimes at longer emission wavelengths in membranes of any complexity. This emission wavelength dependency results in varying lifetime resolutions at different spectral regions, which are highly relevant for FLIM data acquisition. Our data provide valuable insights on how to perform FLIM with these probes and highlight both their potential and limitations.

Spectral Fluorescence Pathology of Protein Misfolding Disorders

Protein misfolding has been extensively studied in the context of neurodegenerative disorders and systemic amyloidoses. Due to misfolding and aggregation of proteins being highly heterogeneous and generating a variety of structures, a growing body of evidence illustrates numerous ways how the aggregates contribute to progression of diseases such as Alzheimer's disease, Parkinson's disease, and prion disorders. Different misfolded species of the same protein, commonly referred to as strains, appear to play a significant role in shaping the disease clinical phenotype and clinical progression. The distinct toxicity profiles of various misfolded proteins underscore their importance. Current diagnostics struggle to differentiate among these strains early in the disease course. This review explores the potential of spectral fluorescence approaches to illuminate the complexities of protein misfolding pathology and discusses the applications of advanced spectral methods in the detection and characterization of protein misfolding disorders. By examining spectrally variable probes, current data analysis approaches, and important considerations for the use of these techniques, this review aims to provide an overview of the progress made in this field and highlights directions for future research.

Curli Amyloid Fibers in Escherichia coli Biofilms: The Influence of Water Availability on their Structure and Functional Properties

Escherichia coli biofilms consist of bacteria embedded in a self-produced matrix mainly made of protein fibers and polysaccharides. The curli amyloid fibers found in the biofilm matrix are promising versatile building blocks to design sustainable bio-sourced materials. To exploit this potential, it is crucial to understand i) how environmental cues during biofilm growth influence the molecular structure of these amyloid fibers, and ii) how this translates at higher length scales. To explore these questions, the effect of water availability during biofilm growth on the conformation and functions of curli is studied. Microscopy and spectroscopy are used to characterize the amyloid fibers purified from biofilms grown on nutritive substrates with different water contents, and micro-indentation to measure the rigidity of the respective biofilms. The purified curli amyloid fibers present differences in the yield, structure, and functional properties upon biofilm growth conditions. Fiber packing and β-sheets content correlate with their hydrophobicity and chemical stability, and with the rigidity of the biofilms. This study highlights how E. coli biofilm growth conditions impact curli structure and functions contributing to macroscopic materials properties. These fundamental findings infer an alternative strategy to tune curli structure, which will ultimately benefit engineering hierarchical and functional curli-based materials.

Multiplexed imaging in live cells using pulsed interleaved excitation spectral FLIM

Multiplexed fluorescence detection has become increasingly important in the fields of biosensing and bioimaging. Although a variety of excitation/detection optical designs and fluorescence unmixing schemes have been proposed to allow for multiplexed imaging, rapid and reliable differentiation and quantification of multiple fluorescent species at each imaging pixel is still challenging. Here we present a pulsed interleaved excitation spectral fluorescence lifetime microscopic (PIE-sFLIM) system that can simultaneously image six fluorescent tags in live cells in a single hyperspectral snapshot. Using an alternating pulsed laser excitation scheme at two different wavelengths and a synchronized 16-channel time-resolved spectral detector, our PIE-sFLIM system can effectively excite multiple fluorophores and collect their emission over a broad spectrum for analysis. Combining our system with the advanced live-cell labeling techniques and the lifetime/spectral phasor analysis, our PIE-sFLIM approach can well unmix the fluorescence of six fluorophores acquired in a single measurement, thus improving the imaging speed in live-specimen investigation.

Spectral Analysis of Human Retinal Pigment Epithelium Cells in Healthy and AMD Eyes

Purpose

Retinal pigment epithelium (RPE) cells show strong autofluorescence (AF). Here, we characterize the AF spectra of individual RPE cells in healthy eyes and those affected by age-related macular degeneration (AMD) and investigate associations between AF spectral response and the number of intracellular AF granules per cell.

Methods

RPE-Bruch's membrane flatmounts of 22 human donor eyes, including seven AMD-affected eyes (early AMD, three; geographic atrophy, one; neovascular, three) and 15 unaffected macula (<51 years, eight; >80 years, seven), were imaged at the fovea, perifovea, and near-periphery using confocal AF microscopy (excitation 488 nm), and emission spectra were recorded (500-710 nm). RPE cells were manually segmented with computer assistance and stratified by disease status, and emission spectra were analyzed using cubic spline transforms. Intracellular granules were manually counted and classified. Linear mixed models were used to investigate associations between spectra and the number of intracellular granules.

Results

Spectra of 5549 RPE cells were recorded. The spectra of RPE cells in healthy eyes showed similar emission curves that peaked at 580 nm for fovea and perifovea and at 575 and 580 nm for near-periphery. RPE spectral curves in AMD eyes differed significantly, being blue shifted by 10 nm toward shorter wavelengths. No significant association coefficients were found between wavelengths and granule counts.

Conclusions

This large series of RPE cell emission spectra at precisely predefined retinal locations showed a hypsochromic spectral shift in AMD. Combining different microscopy techniques, our work has identified cellular RPE spectral AF and subcellular granule properties that will inform future in vivo investigations using single-cell imaging.

UVA Hyperspectral Light-Sheet Microscopy for Volumetric Metabolic Imaging: Application to Preimplantation Embryo Development

Cellular metabolism is a key regulator of energetics, cell growth, regeneration, and homeostasis. Spatially mapping the heterogeneity of cellular metabolic activity is of great importance for unraveling the overall cell and tissue health. In this regard, imaging the endogenous metabolic cofactors, nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavin adenine dinucleotide (FAD), with subcellular resolution and in a noninvasive manner would be useful to determine tissue and cell viability in a clinical environment, but practical use is limited by current imaging techniques. In this paper, we demonstrate the use of phasor-based hyperspectral light-sheet (HS-LS) microscopy using a single UVA excitation wavelength as a route to mapping metabolism in three dimensions. We show that excitation solely at a UVA wavelength of 375 nm can simultaneously excite NAD(P)H and FAD autofluorescence, while their relative contributions can be readily quantified using a hardware-based spectral phasor analysis. We demonstrate the potential of our HS-LS system by capturing dynamic changes in metabolic activity during preimplantation embryo development. To validate our approach, we delineate metabolic changes during preimplantation embryo development from volumetric maps of metabolic activity. Importantly, our approach overcomes the need for multiple excitation wavelengths, two-photon imaging, or significant postprocessing of data, paving the way toward clinical translation, such as in situ, noninvasive assessment of embryo viability.

Quantitative melanoma diagnosis using spectral phasor analysis of hyperspectral imaging from label-free slices

Introduction

Melanoma diagnosis traditionally relies on microscopic examination of hematoxylin and eosin (H&E) slides by dermatopathologists to search for specific architectural and cytological features. Unfortunately, no single molecular marker exists to reliably differentiate melanoma from benign lesions such as nevi. This study explored the potential of autofluorescent molecules within tissues to provide molecular fingerprints indicative of degenerated melanocytes in melanoma.

Methods

Using hyperspectral imaging (HSI) and spectral phasor analysis, we investigated autofluorescence patterns in melanoma compared to intradermal nevi. Using UV excitation and a commercial spectral confocal microscope, we acquired label-free HSI data from the whole-slice samples.

Results

Our findings revealed distinct spectral phasor distributions between melanoma and intradermal nevi, with melanoma displaying a broader phasor phase distribution, signifying a more heterogeneous autofluorescence pattern. Notably, longer wavelengths associated with larger phases correlated with regions identified as melanoma by expert dermatopathologists using H&E staining. Quantitative analysis of phase and modulation histograms within the phasor clusters of five melanomas (with Breslow thicknesses ranging from 0.5 mm to 6 mm) and five intradermal nevi consistently highlighted differences between the two groups. We further demonstrated the potential for the discrimination of several melanocytic lesions using center-of-mass comparisons of phase and modulation variables. Remarkably, modulation versus phase center of mass comparisons revealed strong statistical significance among the groups. Additionally, we identified the molecular endogenous markers responsible for tissue autofluorescence, including collagen, elastin, NADH, FAD, and melanin. In melanoma, autofluorescence is characterized by a higher phase contribution, indicating an increase in FAD and melanin in melanocyte nests. In contrast, NADH, elastin, and collagen dominate the autofluorescence of the nevus.

Discussion

This work underscores the potential of autofluorescence and HSI-phasor analysis as valuable tools for quantifying tissue molecular fingerprints, thereby supporting more effective and quantitative melanoma diagnosis.

Cells immersed in collagen matrices show a decrease in plasma membrane fluidity as the matrix stiffness increases

Cells are constantly adapting to maintain their identity in response to the surrounding media's temporal and spatial heterogeneity. The plasma membrane, which participates in the transduction of external signals, plays a crucial role in this adaptation. Studies suggest that nano and micrometer areas with different fluidities at the plasma membrane change their distribution in response to external mechanical signals. However, investigations linking fluidity domains with mechanical stimuli, specifically matrix stiffness, are still in progress. This report tests the hypothesis that the stiffness of the extracellular matrix can modify the equilibrium of areas with different order in the plasma membrane, resulting in changes in overall membrane fluidity distribution. We studied the effect of matrix stiffness on the distribution of membrane lipid domains in NIH-3 T3 cells immersed in matrices of varying concentrations of collagen type I, for 24 or 72 h. The stiffness and viscoelastic properties of the collagen matrices were characterized by rheometry, fiber sizes were measured by Scanning Electron Microscopy (SEM) and the volume occupied by the fibers by second harmonic generation imaging (SHG). Membrane fluidity was measured using the fluorescent dye LAURDAN and spectral phasor analysis. The results demonstrate that an increase in collagen stiffness alters the distribution of membrane fluidity, leading to an increasing amount of the LAURDAN fraction with a high degree of packing. These findings suggest that changes in the equilibrium of fluidity domains could represent a versatile and refined component of the signal transduction mechanism for cells to respond to the highly heterogeneous matrix structural composition. Overall, this study sheds light on the importance of the plasma membrane's role in adapting to the extracellular matrix's mechanical cues.

Particle-based phasor-FLIM-FRET resolves protein-protein interactions inside single viral particles

Fluorescence lifetime imaging microscopy (FLIM) is a popular modality to create additional contrast in fluorescence images. By carefully analyzing pixel-based nanosecond lifetime patterns, FLIM allows studying complex molecular populations. At the single-molecule or single-particle level, however, image series often suffer from low signal intensities per pixel, rendering it difficult to quantitatively disentangle different lifetime species, such as during Förster resonance energy transfer (FRET) analysis in the presence of a significant donor-only fraction. In this article we investigate whether an object localization strategy and the phasor approach to FLIM have beneficial effects when carrying out FRET analyses of single particles. Using simulations, we first showed that an average of ∼300 photons, spread over the different pixels encompassing single fluorescing particles and without background, is enough to determine a correct phasor signature (SD < 5% for a 4-ns lifetime). For immobilized single- or double-labeled dsDNA molecules, we next validated that particle-based phasor-FLIM-FRET readily allows estimating fluorescence lifetimes and FRET from single molecules. Thirdly, we applied particle-based phasor-FLIM-FRET to investigate protein-protein interactions in subdiffraction HIV-1 viral particles. To do this, we first quantitatively compared the fluorescence brightness, lifetime, and photostability of different popular fluorescent protein-based FRET probes when genetically fused to the HIV-1 integrase enzyme in viral particles, and conclude that eGFP, mTurquoise2, and mScarlet perform best. Finally, for viral particles coexpressing FRET-donor/acceptor-labeled IN, we determined the absolute FRET efficiency of IN oligomers. Available in a convenient open-source graphical user interface, we believe that particle-based phasor-FLIM-FRET is a promising tool to provide detailed insights in samples suffering from low overall signal intensities.

AutoUnmix: an autoencoder-based spectral unmixing method for multi-color fluorescence microscopy imaging

Multiplexed fluorescence microscopy imaging is widely used in biomedical applications. However, simultaneous imaging of multiple fluorophores can result in spectral leaks and overlapping, which greatly degrades image quality and subsequent analysis. Existing popular spectral unmixing methods are mainly based on computational intensive linear models, and the performance is heavily dependent on the reference spectra, which may greatly preclude its further applications. In this paper, we propose a deep learning-based blindly spectral unmixing method, termed AutoUnmix, to imitate the physical spectral mixing process. A transfer learning framework is further devised to allow our AutoUnmix to adapt to a variety of imaging systems without retraining the network. Our proposed method has demonstrated real-time unmixing capabilities, surpassing existing methods by up to 100-fold in terms of unmixing speed. We further validate the reconstruction performance on both synthetic datasets and biological samples. The unmixing results of AutoUnmix achieve the highest SSIM of 0.99 in both three- and four-color imaging, with nearly up to 20% higher than other popular unmixing methods. For experiments where spectral profiles and morphology are akin to simulated data, our method realizes the quantitative performance demonstrated above. Due to the desirable property of data independency and superior blind unmixing performance, we believe AutoUnmix is a powerful tool for studying the interaction process of different organelles labeled by multiple fluorophores.

Phasor Representation Approach for Rapid Exploratory Analysis of Large Infrared Spectroscopic Imaging Data Sets

Infrared (IR) spectroscopic imaging is potentially useful for digital histopathology as it provides spatially resolved molecular absorption spectra, which can subsequently yield useful information by powerful artificial intelligence methods. A typical analysis pipeline in using IR imaging data for chemical pathology often involves iterative processes of segmentation, evaluation, and analysis that necessitate rapid data exploration. Here, we present a fast, reliable, and intuitive method based on a phasor representation of spectra and discuss its unique applicability for IR imaging data. We simulate different features extant in IR spectra and discuss their influence on the phasor waveforms; similarly, we undertake IR image analysis in the transform space to understand spectral similarity and variance. We demonstrate the potential of phasor analysis for biomedical tissue imaging using a variety of samples, using fresh frozen surgical prostate resections and formalin-fixed paraffin-embedded breast cancer tissue microarray samples as model systems that span common histopathology practice. To demonstrate further generalizability of this approach, we apply the method to data from different experimental conditions─including standard (5.5 μm × 5.5 μm pixel size) and high-definition (1.1 μm × 1.1 μm pixel size) Fourier transform IR (FTIR) spectroscopic imaging using transmission and transflection modes. Quantitative segmentation results from our approach are compared to previous studies, showing good agreement and quick visualization. The presented method is rapid, easy to use, and highly capable of deciphering compositional differences, presenting a convenient tool for exploratory analysis of IR imaging data.

From the beginnings to multidimensional light and electron microscopy of virus morphogenesis

Individual functional viral morphogenesis events are often dynamic, short, and infrequent and might be obscured by other pathways and dead-end products. Volumetric live cell imaging has become an essential tool for studying viral morphogenesis events. It allows following entire dynamic processes while providing functional evidence that the imaged process is involved in viral production. Moreover, it allows to capture many individual events and allows quantitative analysis. Finally, the correlation of volumetric live-cell data with volumetric electron microscopy (EM) can provide crucial insights into the ultrastructure and mechanisms of viral morphogenesis events. Here, we provide an overview and discussion of suitable imaging methods for volumetric correlative imaging of viral morphogenesis and frame them in a historical summary of their development.

A single-shot hyperspectral phasor camera for fast, multi-color fluorescence microscopy

Hyperspectral fluorescence imaging improves multiplexed observations of biological samples by utilizing multiple color channels across the spectral range to compensate for spectral overlap between labels. Typically, spectral resolution comes at a cost of decreased detection efficiency, which both hampers imaging speed and increases photo-toxicity to the samples. Here, we present a high-speed, high-efficiency snapshot spectral acquisition method, based on optical compression of the fluorescence spectra via Fourier transform, that overcomes the challenges of discrete spectral sampling: single-shot hyperspectral phasor camera (SHy-Cam). SHy-Cam captures fluorescence spatial and spectral information in a single exposure with a standard scientific CMOS camera, with photon efficiency of over 80%, easily and with acquisition rates exceeding 30 datasets per second, making it a powerful tool for multi-color in vivo imaging. Its simple design, using readily available optical components, and its easy integration provide a low-cost solution for multi-color fluorescence imaging with increased efficiency and speed.

From mouse to human: Accessing the biochemistry of vision in vivo by two-photon excitation

The eye is an ideal organ for imaging by a multi-photon excitation approach, because ocular tissues such as the sclera, cornea, lens and neurosensory retina, are highly transparent to infrared (IR) light. The interface between the retina and the retinal pigment epithelium (RPE) is especially informative, because it reflects the health of the visual (retinoid) cycle and its changes in response to external stress, genetic manipulations, and drug treatments. Vitamin A-derived retinoids, like retinyl esters, are natural fluorophores that respond to multi-photon excitation with near IR light, bypassing the filter-like properties of the cornea, lens, and macular pigments. Also, during natural aging some retinoids form bisretinoids, like diretinoid-pyridiniumethanolamine (A2E), that are highly fluorescent. These bisretinoids appear to be elevated concurrently with aging. Vitamin A-derived retinoids and bisretinoidss are detected by two-photon ophthalmoscopy (2PO), using a new class of light sources with adjustable spatial, temporal, and spectral properties. Furthermore, the two-photon (2P) absorption of IR light by the visual pigments in rod and cone photoreceptors can initiate visual transduction by cis-trans isomerization of retinal, enabling parallel functional studies. Recently we overcame concerns about safety, data interpretation and complexity of the 2P-based instrumentation, the major roadblocks toward advancing this modality to the clinic. These imaging and retina-function assessment advancements have enabled us to conduct the first 2P studies with humans.

Spectral Phasor Analysis of Nile Red Identifies Membrane Microenvironment Changes in the Presence of Amyloid Peptides

The interaction of protein and peptide amyloid oligomers with membranes is thought to be one of the mechanisms contributing to cellular toxicity. However, techniques to study these interactions in the complex membrane environment of live cells are lacking. Spectral phasor analysis is a recently developed biophysical technique that can enable visualisation and analysis of membrane-associated fluorescent dyes. When the spectral profile of these dyes changes as a result of changes to the membrane microenvironment, spectral phasor analysis can localise those changes to discrete membrane regions. In this study, we investigated whether spectral phasor analysis could detect changes in the membrane microenvironment of live cells in the presence of fibrillar aggregates of the disease-related Aβ₄₂ peptide or the functional amyloid neurokinin B. Our results show that the fibrils cause distinct changes to the microenvironment of nile red associated with both the plasma and the nuclear membrane. We attribute these shifts in nile red spectral properties to changes in membrane fluidity. Results from this work suggest that cells have mechanisms to avoid or control membrane interactions arising from functional amyloids which have implications for how these peptides are stored in dense core vesicles. Furthermore, the work highlights the utility of spectral phasor analysis to monitor microenvironment changes to fluorescent probes in live cells.

Towards a New Biomarker for Diabetic Retinopathy: Exploring RBP3 Structure and Retinoids Binding for Functional Imaging of Eyes In Vivo

Diabetic retinopathy (DR) is a severe disease with a growing number of afflicted patients, which places a heavy burden on society, both socially and financially. While there are treatments available, they are not always effective and are usually administered when the disease is already at a developed stage with visible clinical manifestation. However, homeostasis at a molecular level is disrupted before visible signs of the disease are evident. Thus, there has been a constant search for effective biomarkers that could signal the onset of DR. There is evidence that early detection and prompt disease control are effective in preventing or slowing DR progression. Here, we review some of the molecular changes that occur before clinical manifestations are observable. As a possible new biomarker, we focus on retinol binding protein 3 (RBP3). We argue that it displays unique features that make it a very good biomarker for non-invasive, early-stage DR detection. Linking chemistry to biological function and focusing on new developments in eye imaging and two-photon technology, we describe a new potential diagnostic tool that would allow rapid and effective quantification of RBP3 in the retina. Moreover, this tool would also be useful in the future to monitor therapeutic effectiveness if levels of RBP3 are elevated by DR treatments.

SPLIT-PIN software enabling confocal and super-resolution imaging with a virtually closed pinhole

In point-scanning microscopy, optical sectioning is achieved using a small aperture placed in front of the detector, i.e. the detection pinhole, which rejects the out-of-focus background. The maximum level of optical sectioning is theoretically obtained for the minimum size of the pinhole aperture, but this is normally prevented by the dramatic reduction of the detected signal when the pinhole is closed, leading to a compromise between axial resolution and signal-to-noise ratio. We have recently demonstrated that, instead of closing the pinhole, one can reach a similar level of optical sectioning by tuning the pinhole size in a confocal microscope and by analyzing the resulting image series. The method, consisting in the application of the separation of photons by lifetime tuning (SPLIT) algorithm to series of images acquired with tunable pinhole size, is called SPLIT-pinhole (SPLIT-PIN). Here, we share and describe a SPLIT-PIN software for the processing of series of images acquired at tunable pinhole size, which generates images with reduced out-of-focus background. The software can be used on series of at least two images acquired on available commercial microscopes equipped with a tunable pinhole, including confocal and stimulated emission depletion (STED) microscopes. We demonstrate applicability on different types of imaging modalities: (1) confocal imaging of DNA in a non-adherent cell line; (2) removal of out-of-focus background in super-resolved STED microscopy; (3) imaging of live intestinal organoids stained with a membrane dye.

Detection and Typing of Renal Amyloidosis by Fluorescence Spectroscopy Using the Environmentally Sensitive Fluorophore K114

PURPOSE

To demonstrate that spectral analysis using the K114 fluorophore can detect and differentiate AL and AA renal amyloidosis.

PROCEDURES

Kidney biopsies from patients with AL amyloidosis, AA amyloidosis, and normal samples with no evident pathology were stained with Congo Red and K114. The specimens were imaged on a spectral confocal microscope.

RESULTS

Congo Red displayed homogeneous spectra across the three tissue types while K114 chromatically distinguished between normal tissue, AL amyloid, and AA amyloid. Additionally, Congo Red displayed an increased risk of false positive staining compared to K114. Spectral phasors computed from K114-stained tissue sections quantitatively differentiated the three tissue types. K114-stained amyloid deposits displayed a significantly greater increase in brightness after 50 images acquired in rapid succession compared to normal tissue. Quantitative analysis of intensity changes in the background of diseased tissue also differentiated AL and AA amyloid samples, suggesting widespread amyloid deposition. Both amyloid and the backgrounds of diseased samples red-shifted while normal tissue blue-shifted in response to repeated imaging, supporting this theory.

CONCLUSIONS

K114 staining of renal biopsies is a promising technique to detect and differentiate types of renal amyloidosis. Due to the advantages this method has over traditional Congo Red staining, the techniques presented here warrant further development for potential use in clinical settings.

Advanced Fluorescence Microscopy Methods to Study Dynamics of Fluorescent Proteins In Vivo

Fluorescent proteins are standard tools for addressing biological questions in a cell biology laboratory. The genetic tagging of protein of interest with fluorescent proteins opens the opportunity to follow them in vivo and to understand their interactions and dynamics. In addition, the latest advances in optical microscopy image acquisition and processing allow us to study many cellular processes in vivo. Techniques such as fluorescence lifetime microscopy and hyperspectral imaging provide valuable tools for understanding fluorescent protein interactions and their photophysics. Finally, fluorescence fluctuation analysis opens the possibility to address questions of molecular diffusion, protein-protein interactions, and oligomerization, among others, yielding quantitative information on the subject of study. This chapter will cover some of the more important advances in cutting-edge technologies and methods that, combined with fluorescent proteins, open new frontiers for biological studies.

HER2 classification in breast cancer cells: A new explainable machine learning application for immunohistochemistry

The immunohistochemical (IHC) evaluation of epidermal growth factor 2 (HER2) for the diagnosis of breast cancer is still qualitative with a high degree of inter-observer variability, and thus requires the incorporation of complementary techniques such as fluorescent in situ hybridization (FISH) to resolve the diagnosis. Implementing automatic algorithms to classify IHC biomarkers is crucial for typifying the tumor and deciding on therapy for each patient with better performance. The present study aims to demonstrate that, using an explainable Machine Learning (ML) model for the classification of HER2 photomicrographs, it is possible to determine criteria to improve the value of IHC analysis. We trained a logistic regression-based supervised ML model with 393 IHC microscopy images from 131 patients, to discriminate between upregulated and normal expression of the HER2 protein. Pathologists' diagnoses (IHC only) vs. the final diagnosis complemented with FISH (IHC + FISH) were used as training outputs. Basic performance metrics and receiver operating characteristic curve analysis were used together with an explainability algorithm based on Shapley Additive exPlanations (SHAP) values to understand training differences. The model could discriminate amplified IHC from normal expression with better performance when the training output was the IHC + FISH final diagnosis (IHC vs. IHC + FISH: area under the curve, 0.94 vs. 0.81). This may be explained by the increased analytical impact of the membrane distribution criteria over the global intensity of the signal, according to SHAP value interpretation. The classification model improved its performance when the training input was the final diagnosis, downplaying the weighting of the intensity of the IHC signal, suggesting that to improve pathological diagnosis before FISH consultation, it is necessary to emphasize subcellular patterns of staining.

Dual-probe fluorescence spectroscopy for sensitive quantitation of Alzheimer’s amyloid pathology

Protein misfolding is a prominent pathological hallmark of neurodegenerative disorders, including Alzheimer’s disease (AD). Studies have shown that the diversity of β sheet-rich protein deposits (such as amyloid β plaques and neurofibrillary tangles), present across different brain regions, might underlie different disease phenotypes and only certain types of aggregates might be associated with cognitive decline. Conformationally sensitive fluorescent amyloid probes have the ability to report different structures of protein aggregates by virtue of their shifting emission spectra. Here we defined the binding affinity of the fluorescent amyloid probes BSB and MCAAD to disease-relevant protein aggregates, and combined the two probes to examine formalin-fixed paraffin-embedded mouse and human brain samples. Coupled with quantitative spectral phasor analysis, the dual-probe staining approach revealed remarkable heterogeneity of protein aggregates across the samples. Distinct emission spectra were consistent with certain types of deposits present in the mouse and human brain sections. The sensitivity of this staining, imaging and analysis approach outperformed conventional immunohistochemistry with the detected spectral differences between the greater parenchyma of cognitively normal and AD cases indicating a subtle yet widespread proteopathy associated with disease. Our method offers more sensitive, objective, and quantitative examination of protein misfolding pathology using conventional tissue sections.

Denoising multiplexed microscopy images in n-dimensional spectral space

Hyperspectral fluorescence microscopy images of biological specimens frequently contain multiple observations of a sparse set of spectral features spread in space with varying intensity. Here, we introduce a spectral vector denoising algorithm that filters out noise without sacrificing spatial information by leveraging redundant observations of spectral signatures. The algorithm applies an n-dimensional Chebyshev or Fourier transform to cluster pixels based on spectral similarity independent of pixel intensity or location, and a denoising convolution filter is then applied in this spectral space. The denoised image may then undergo spectral decomposition analysis with enhanced accuracy. Tests utilizing both simulated and empirical microscopy data indicate that denoising in 3 to 5-dimensional (3D to 5D) spectral spaces decreases unmixing error by up to 70% without degrading spatial resolution.

Multiplexed bioluminescence microscopy via phasor analysis

Bioluminescence imaging with luciferase-luciferin pairs is a well-established technique for visualizing biological processes across tissues and whole organisms. Applications at the microscale, by contrast, have been hindered by a lack of detection platforms and easily resolved probes. We addressed this limitation by combining bioluminescence with phasor analysis, a method commonly used to distinguish spectrally similar fluorophores. We built a camera-based microscope equipped with special optical filters to directly assign phasor locations to unique luciferase-luciferin pairs. Six bioluminescent reporters were easily resolved in live cells, and the readouts were quantitative and instantaneous. Multiplexed imaging was also performed over extended time periods. Bioluminescent phasor further provided direct measures of resonance energy transfer in single cells, setting the stage for dynamic measures of cellular and molecular features. The merger of bioluminescence with phasor analysis fills a long-standing void in imaging capabilities, and will bolster future efforts to visualize biological events in real time and over multiple length scales.

A phasor-based approach to improve optical sectioning in any confocal microscope with a tunable pinhole

Confocal fluorescence microscopy is a well‐established imaging technique capable of generating thin optical sections of biological specimens. Optical sectioning in confocal microscopy is mainly determined by the size of the pinhole, a small aperture placed in front of a point detector. In principle, imaging with a closed pinhole provides the highest degree of optical sectioning. In practice, the dramatic reduction of signal‐to‐noise ratio (SNR) at smaller pinhole sizes makes challenging the use of pinhole sizes significantly smaller than 1 Airy Unit (AU). Here, we introduce a simple method to “virtually” perform confocal imaging at smaller pinhole sizes without the dramatic reduction of SNR. The method is based on the sequential acquisition of multiple confocal images acquired at different pinhole aperture sizes and image processing based on a phasor analysis. The implementation is conceptually similar to separation of photons by lifetime tuning (SPLIT), a technique that exploits the phasor analysis to achieve super‐resolution, and for this reason we call this method SPLIT‐pinhole (SPLIT‐PIN). We show with simulated data that the SPLIT‐PIN image can provide improved optical sectioning (i.e., virtually smaller pinhole size) but better SNR with respect to an image obtained with closed pinhole. For instance, two images acquired at 2 and 1 AU can be combined to obtain a SPLIT‐PIN image with a virtual pinhole size of 0.2 AU but with better SNR. As an example of application to biological imaging, we show that SPLIT‐PIN improves confocal imaging of the apical membrane in an in vitro model of the intestinal epithelium.

Discrimination of cancerous from benign pigmented skin lesions based on multispectral autofluorescence lifetime imaging dermoscopy and machine learning

SIGNIFICANCE

Accurate early diagnosis of malignant skin lesions is critical in providing adequate and timely treatment; unfortunately, initial clinical evaluation of similar-looking benign and malignant skin lesions can result in missed diagnosis of malignant lesions and unnecessary biopsy of benign ones.

AIM

To develop and validate a label-free and objective image-guided strategy for the clinical evaluation of suspicious pigmented skin lesions based on multispectral autofluorescence lifetime imaging (maFLIM) dermoscopy.

APPROACH

We tested the hypothesis that maFLIM-derived autofluorescence global features can be used in machine-learning (ML) models to discriminate malignant from benign pigmented skin lesions. Clinical widefield maFLIM dermoscopy imaging of 41 benign and 19 malignant pigmented skin lesions from 30 patients were acquired prior to tissue biopsy sampling. Three different pools of global image-level maFLIM features were extracted: multispectral intensity, time-domain biexponential, and frequency-domain phasor features. The classification potential of each feature pool to discriminate benign versus malignant pigmented skin lesions was evaluated by training quadratic discriminant analysis (QDA) classification models and applying a leave-one-patient-out cross-validation strategy.

RESULTS

Classification performance estimates obtained after unbiased feature selection were as follows: 68% sensitivity and 80% specificity with the phasor feature pool, 84% sensitivity, and 71% specificity with the biexponential feature pool, and 84% sensitivity and 32% specificity with the intensity feature pool. Ensemble combinations of QDA models trained with phasor and biexponential features yielded sensitivity of 84% and specificity of 90%, outperforming all other models considered.

CONCLUSIONS

Simple classification ML models based on time-resolved (biexponential and phasor) autofluorescence global features extracted from maFLIM dermoscopy images have the potential to provide objective discrimination of malignant from benign pigmented lesions. ML-assisted maFLIM dermoscopy could potentially assist with the clinical evaluation of suspicious lesions and the identification of those patients benefiting the most from biopsy examination.

Imaging approaches for monitoring three-dimensional cell and tissue culture systems

The past decade has seen an increasing demand for more complex, reproducible and physiologically relevant tissue cultures that can mimic the structural and biological features of living tissues. Monitoring the viability, development and responses of such tissues in real-time are challenging due to the complexities of cell culture physical characteristics and the environments in which these cultures need to be maintained in. Significant developments in optics, such as optical manipulation, improved detection and data analysis, have made optical imaging a preferred choice for many three-dimensional (3D) cell culture monitoring applications. The aim of this review is to discuss the challenges associated with imaging and monitoring 3D tissues and cell culture, and highlight topical label-free imaging tools that enable bioengineers and biophysicists to non-invasively characterise engineered living tissues.

Unsupervised super-resolution reconstruction of hyperspectral histology images for whole-slide imaging

SIGNIFICANCE

Hyperspectral imaging (HSI) provides rich spectral information for improved histopathological cancer detection. However, acquiring high-resolution HSI data for whole-slide imaging (WSI) can be time-consuming and requires a huge amount of storage space.

AIM

WSI using a color camera can be achieved with fast speed, high image resolution, and excellent image quality due to the established techniques. We aim to develop an RGB-guided unsupervised hyperspectral super-resolution reconstruction method that is hypothesized to improve image quality while maintaining the spectral characteristics.

APPROACH

High-resolution hyperspectral images of 32 histologic slides were obtained via automated WSI. High-resolution RGB histology images were registered to the hyperspectral images for RGB guidance. An unsupervised super-resolution network was trained to take the downsampled low-resolution hyperspectral patches (LR-HSI) and high-resolution RGB patches (HR-RGB) as inputs to reconstruct high-resolution hyperspectral patches (HR-HSI). Then, an Inception-based network was trained with the HR-RGB, original HR-HSI, and generated HR-HSI, respectively, for whole-slide histopathological cancer detection.

RESULTS

Our super-resolution reconstruction network generated high-resolution hyperspectral images with well-maintained spectral characteristics and improved image quality. Image classification using the original hyperspectral data outperformed RGB because of the extra spectral information. The generated hyperspectral image patches further improved the results.

CONCLUSIONS

The proposed method potentially reduces image acquisition time, saves storage space without compromising image quality, and improves the image classification performance.

In vivo macromolecular crowding is differentially modulated by aquaporin 0 in zebrafish lens: Insights from a nanoenvironment sensor and spectral imaging

Macromolecular crowding is crucial for cellular homeostasis. In vivo studies of macromolecular crowding and water dynamics are needed to understand their roles in cellular physiology and fate determination. Macromolecular crowding in the lens is essential for normal optics, and an understanding of its regulation will help prevent cataract and presbyopia. Here, we combine the use of the nanoenvironmental sensor [6-acetyl-2-dimethylaminonaphthalene (ACDAN)] to visualize lens macromolecular crowding with in vivo studies of aquaporin 0 zebrafish mutants that disrupt its regulation. Spectral phasor analysis of ACDAN fluorescence reveals water dipolar relaxation and demonstrates that mutations in two zebrafish aquaporin 0s, Aqp0a and Aqp0b, alter water state and macromolecular crowding in living lenses. Our results provide in vivo evidence that Aqp0a promotes fluid influx in the deeper lens cortex, whereas Aqp0b facilitates fluid efflux. This evidence reveals previously unidentified spatial regulation of macromolecular crowding and spatially distinct roles for Aqp0 in the lens.

Introducing the multi-dimensional spectral phasors: a tool for the analysis of fluorescence excitation-emission matrices

The use of phasors to analyze fluorescence data was first introduced for time-resolved studies for a simpler mathematical analysis of the fluorescence-decay curves. Recently, this approach was extended to steady-state experiments with the introduction of the spectral phasors (SP), derived from the Fourier transform of the fluorescence emission spectrum. In this work, we revise key mathematical aspects that lead to an interpretation of SP as the characteristic function of a probability distribution. This formalism allows us to introduce a new tool, called multi-dimensional spectral phasor (MdSP) that seize, not only the information from the emission spectrum, but from the full excitation-emission matrix (EEM). In addition, we developed a homemade open-source Java software to facilitate the MdSP data processing. Due to this mathematical conceptualization, we settled a mechanism for the use of MdSP as a tool to tackle spectral signal unmixing problems in a more accurate way than SP. As a proof of principle, with the use of MdSP we approach two important biophysical questions: protein conformational changes and protein-ligand interactions. Specifically, we experimentally measure the EEM changes upon denaturation of human serum albumin (HSA) or during its association with the fluorescence dye 1,8-anilinonaphtalene sulphate (ANS) detected via tryptophan-ANS Förster Resonance Energy Transfer (FRET). In this sense, MdSP allows us to obtain information of the system in a simpler and finer way than the traditional SP. Specifically, understanding a protein's EEM as a molecular fingerprint opens new doors for the use of MdSP as a tool to analyze and comprehend protein conformational changes and interactions.

Unsupervised Super Resolution Network for Hyperspectral Histologic Imaging

Hyperspectral imaging (HSI) has many advantages in microscopic applications, including high sensitivity and specificity for cancer detection on histological slides. However, acquiring hyperspectral images of a whole slide with a high image resolution and a high image quality can take a long scanning time and require a very large data storage. One potential solution is to acquire and save low-resolution hyperspectral images and reconstruct the high-resolution ones only when needed. The purpose of this study is to develop a simple yet effective unsupervised super resolution network for hyperspectral histologic imaging with the guidance of RGB digital histology images. High-resolution hyperspectral images of hemoxylin & eosin (H&E) stained slides were obtained at 10× magnification and down-sampled 2×, 4×, and 5× to generate low-resolution hyperspectral data. High-resolution digital histologic RGB images of the same field of view (FOV) were cropped and registered to the corresponding high-resolution hyperspectral images. A neural network based on a modified U-Net architecture, which takes the low-resolution hyperspectral images and high-resolution RGB images as inputs, was trained with unsupervised methods to output high-resolution hyperspectral data. The generated high-resolution hyperspectral images have similar spectral signatures and improved image contrast than the original high-resolution hyperspectral images, which indicates that the super resolution network with RGB guidance can improve the image quality. The proposed method can reduce the acquisition time and save storage space taken up by hyperspectral images without compromising image quality, which will potentially promote the use of hyperspectral imaging technology in digital pathology and many other clinical applications.

Phasor map analysis to investigate Hutchinson-Gilford progeria cell under polarization-resolved optical scanning microscopy

Polarized light scanning microscopy is a non-invasive and contrast-enhancing technique to investigate anisotropic specimens and chiral organizations. However, such arrangements suffer from insensitivity to confined blend of structures at sub-diffraction level. Here for the first time, we present that the pixel-by-pixel polarization modulation converted to an image phasor approach issues an insightful view of cells to distinguish anomalous subcellular organizations. To this target, we propose an innovative robust way for identifying changes in the chromatin compaction and distortion of nucleus morphology induced by the activation of the lamin-A gene from Hutchinson–Gilford progeria syndrome that induces a strong polarization response. The phasor mapping is evaluated based on the modulation and phase image acquired from a scanning microscope compared to a confocal fluorescence modality of normal cell opposed to the progeria. The method is validated by characterizing polarization response of starch crystalline granules. Additionally, we show that the conversion of the polarization-resolved images into the phasor could further utilized for segmenting specific structures presenting various optical properties under the polarized light. In summary, image phasor analysis offers a distinctly sensitive fast and easy representation of the polarimetric contrast that can pave the way for remote diagnosis of pathological tissues in real-time.

Linear Combination Properties of the Phasor Space in Fluorescence Imaging

The phasor approach to fluorescence lifetime imaging, and more recently hyperspectral fluorescence imaging, has increased the use of these techniques, and improved the ease and intuitiveness of the data analysis. The fit-free nature of the phasor plots increases the speed of the analysis and reduces the dimensionality, optimization of data handling and storage. The reciprocity principle between the real and imaginary space-where the phasor and the pixel that the phasor originated from are linked and can be converted from one another-has helped the expansion of this method. The phasor coordinates calculated from a pixel, where multiple fluorescent species are present, depends on the phasor positions of those components. The relative positions are governed by the linear combination properties of the phasor space. According to this principle, the phasor position of a pixel with multiple components lies inside the polygon whose vertices are occupied by the phasor positions of these individual components and the distance between the image phasor to any of the vertices is inversely proportional to the fractional intensity contribution of that component to the total fluorescence from that image pixel. The higher the fractional intensity contribution of a vertex, the closer is the resultant phasor. The linear additivity in the phasor space can be exploited to obtain the fractional intensity contribution from multiple species and quantify their contribution. This review details the various mathematical models that can be used to obtain two/three/four components from phasor space with known phasor signatures and then how to obtain both the fractional intensities and phasor positions without any prior knowledge of either, assuming they are mono-exponential in nature. We note that other than for blind components, there are no restrictions on the type of the decay or their phasor positions for linear combinations to be valid-and they are applicable to complicated fluorescence lifetime decays from components with intensity decays described by multi-exponentials.

Spatial transcriptomics using combinatorial fluorescence spectral and lifetime encoding, imaging and analysis

Multiplexed mRNA profiling in the spatial context provides new information enabling basic research and clinical applications. Unfortunately, existing spatial transcriptomics methods are limited due to either low multiplexing or complexity. Here, we introduce a spatialomics technology, termed Multi Omic Single-scan Assay with Integrated Combinatorial Analysis (MOSAICA), that integrates in situ labeling of mRNA and protein markers in cells or tissues with combinatorial fluorescence spectral and lifetime encoded probes, spectral and time-resolved fluorescence imaging, and machine learning-based decoding. We demonstrate MOSAICA's multiplexing scalability in detecting 10-plex targets in fixed colorectal cancer cells using combinatorial labeling of five fluorophores with facile error-detection and removal of autofluorescence. MOSAICA's analysis is strongly correlated with sequencing data (Pearson's r = 0.96) and was further benchmarked using RNAscopeTM and LGC StellarisTM. We further apply MOSAICA for multiplexed analysis of clinical melanoma Formalin-Fixed Paraffin-Embedded (FFPE) tissues. We finally demonstrate simultaneous co-detection of protein and mRNA in cancer cells.

Practical considerations for quantitative and reproducible measurements with stimulated Raman scattering microscopy

This tutorial review presents the most important practical considerations for sample preparation, instrument set-up, image acquisition and data analysis to obtain reproducible SRS measurements.

Fluorescence sensors for imaging membrane lipid domains and cholesterol

Lipid membrane domains are supramolecular lateral heterogeneities of biological membranes. Of nanoscopic dimensions, they constitute specialized hubs used by the cell as transient signaling platforms for a great variety of biologically important mechanisms. Their property to form and dissolve in the bulk lipid bilayer endow them with the ability to engage in highly dynamic processes, and temporarily recruit subpopulations of membrane proteins in reduced nanometric compartments that can coalesce to form larger mesoscale assemblies. Cholesterol is an essential component of these lipid domains; its unique molecular structure is suitable for interacting intricately with crevices and cavities of transmembrane protein surfaces through its rough β face while "talking" to fatty acid acyl chains of glycerophospholipids and sphingolipids via its smooth α face. Progress in the field of membrane domains has been closely associated with innovative improvements in fluorescence microscopy and new fluorescence sensors. These advances enabled the exploration of the biophysical properties of lipids and their supramolecular platforms. Here I review the rationale behind the use of biosensors over the last few decades and their contributions towards elucidation of the in-plane and transbilayer topography of cholesterol-enriched lipid domains and their molecular constituents. The challenges introduced by super-resolution optical microscopy are discussed, as well as possible scenarios for future developments in the field, including virtual ("no staining") staining.

Impact of macromolecular crowding on the mesomorphic behavior of lipid self-assemblies

Using LAURDAN fluorescence we observed that water dynamics measured at the interface of DOPC bilayers can be differentially regulated by the presence of crowded suspensions of different proteins (HSA, IgG, Gelatin) and PEG, under conditions where the polymers are not in direct molecular contact with the lipid interface. Specifically, we found that the decrease in water dipolar relaxation at the membrane interface correlates with an increased fraction of randomly oriented (or random coil) configurations in the polymers, as Gelatin > PEG > IgG > HSA. By using the same experimental strategy, we also demonstrated that structural transitions from globular to extended conformations in proteins can induce transitions between lamellar and non-lamellar phases in mixtures of DOPC and monoolein. Independent experiments using Raman spectroscopy showed that aqueous suspensions of polymers exhibiting high proportions of randomly oriented conformations display increased fractions of tetracoordinated water, a configuration that is dominant in ice. This indicates a greater capacity of this type of structure for polarizing water and consequently reducing its chemical activity. This effect is in line with one of the tenets of the Association Induction Hypothesis, which predicts a long-range dynamic structuring of water molecules via their interactions with proteins (or other polymers) showing extended conformations. Overall, our results suggest a crucial role of water in promoting couplings between structural changes in macromolecules and supramolecular arrangements of lipids. This mechanism may be of relevance to cell structure/function when the crowded nature of the intracellular milieu is considered.

Out-of-Phase Imaging after Optical Modulation (OPIOM) for Multiplexed Fluorescence Imaging Under Adverse Optical Conditions

Fluorescence imaging has become a powerful tool for observations in biology. Yet it has also encountered limitations to overcome optical interferences of ambient light, autofluorescence, and spectrally interfering fluorophores. In this account, we first examine the current approaches which address these limitations. Then we more specifically report on Out-of-Phase Imaging after Optical Modulation (OPIOM), which has proved attractive for highly selective multiplexed fluorescence imaging even under adverse optical conditions. After exposing the OPIOM principle, we detail the protocols for successful OPIOM implementation.

Cellular NADH and NADPH Conformation as a Real-Time Fluorescence-Based Metabolic Indicator under Pressurized Conditions

Cellular conformation of reduced pyridine nucleotides NADH and NADPH sensed using autofluorescence spectroscopy is presented as a real-time metabolic indicator under pressurized conditions. The approach provides information on the role of pressure in energy metabolism and antioxidant defense with applications in agriculture and food technologies. Here, we use spectral phasor analysis on UV-excited autofluorescence from Saccharomyces cerevisiae (baker's yeast) to assess the involvement of one or multiple NADH- or NADPH-linked pathways based on the presence of two-component spectral behavior during a metabolic response. To demonstrate metabolic monitoring under pressure, we first present the autofluorescence response to cyanide (a respiratory inhibitor) at 32 MPa. Although ambient and high-pressure responses remain similar, pressure itself also induces a response that is consistent with a change in cellular redox state and ROS production. Next, as an example of an autofluorescence response altered by pressurization, we investigate the response to ethanol at ambient, 12 MPa, and 30 MPa pressure. Ethanol (another respiratory inhibitor) and cyanide induce similar responses at ambient pressure. The onset of non-two-component spectral behavior upon pressurization suggests a change in the mechanism of ethanol action. Overall, results point to new avenues of investigation in piezophysiology by providing a way of visualizing metabolism and mitochondrial function under pressurized conditions.

Embedded nanometer position tracking based on enhanced phasor analysis

We present an embedded real-time 1D position tracking device at a nanometer precision. The embedded algorithm extracts the most appropriate region of the signal without manual intervention and estimates the position based on the phase shift from the signal's first Fourier harmonic. Using simulated datasets, we demonstrate that the proposed approach can achieve a similar precision to the state-of-the-art maximum likelihood fitting-based method while executing over four orders of magnitude faster. We further implemented this algorithm on a low-power microprocessor and developed a simple, compact, and low-cost embedded position tracking device. We demonstrate nanometer tracking precision in real-time drift tracking experiments.

Phasor approach of Mueller matrix optical scanning microscopy for biological tissue imaging

Mueller matrix microscopy is an advanced imaging technique providing a full characterization of the optical polarization fingerprint of a sample. The Lu-Chipman (LC) decomposition, a method based on the modeling of elementary polarimetric arrangements and matrix inversions, is the gold standard to extract each polarimetric component separately. However, this models the optical system as a small number of discrete optical elements and requires a priori knowledge of the order in which these elements occur. In stratified media or when the ordering is not known, the interpretation of the LC decomposition becomes difficult. In this work, we propose a new, to our knowledge, representation dedicated to the study of biological tissues that combines Mueller matrix microscopy with a phasor approach. We demonstrate that this method provides an easier and direct interpretation of the retardance images in any birefringent material without the use of mathematical assumptions regarding the structure of the sample and yields comparable contrast to the LC decomposition. By validating this approach through numerical simulations, we demonstrate that it is able to give access to localized structural information, resulting in a simple determination of the birefringent parameters at the microscopic level. We apply our novel, to our knowledge, method to typical biological tissues that are of interest in the field of biomedical diagnosis.

Method of transmission filters to measure emission spectra in strongly scattering media

We describe a method based on a pair of transmission filters placed in the emission path of a microscope to resolve the emission wavelength of every point in an image. The method can be applied to any type of imaging device that provides the light in the wavelength transmission range of the filters. Unique characteristics of the filter approach are that the light does not need to be collimated and the wavelength response does not depend on the scattering of the sample or tissue. The pair of filters are used to produce the spectral phasor of the transmitted light, which is sufficient to perform spectral deconvolution over a broad wavelength range. The method is sensitive enough to distinguish free and protein-bound NADH and can be used in metabolic studies.

Phasor-based hyperspectral snapshot microscopy allows fast imaging of live, three-dimensional tissues for biomedical applications

Hyperspectral imaging is highly sought after in many fields including mineralogy and geology, environment and agriculture, astronomy and, importantly, biomedical imaging and biological fluorescence. We developed ultrafast phasor-based hyperspectral snapshot microscopy based on sine/cosine interference filters for biomedical imaging not feasible with conventional hyperspectral detection methods. Current approaches rely on slow spatial or spectral scanning limiting their application in living biological tissues, while faster snapshot methods such as image mapping spectrometry and multispectral interferometry are limited in spatial and/or spectral resolution, are computationally demanding, and imaging devices are very expensive to manufacture. Leveraging light sheet microscopy, phasor-based hyperspectral snapshot microscopy improved imaging speed 10-100 fold which, combined with minimal light exposure and high detection efficiency, enabled hyperspectral metabolic imaging of live, three-dimensional mouse tissues not feasible with other methods. As a fit-free method that does not require any a priori information often unavailable in complex and evolving biological systems, the rule of linear combinations of the phasor could spectrally resolve subtle differences between cell types in the developing zebrafish retina and spectrally separate and track multiple organelles in 3D cultured cells over time. The sine/cosine snapshot method is adaptable to any microscope or imaging device thus making hyperspectral imaging and fit-free analysis based on linear combinations broadly available to researchers and the public.

Phasor-based image segmentation: machine learning clustering techniques

The phasor approach is a well-established method for data visualization and image analysis in spectral and lifetime fluorescence microscopy. Nevertheless, it is typically applied in a user-dependent manner by manually selecting regions of interest on the phasor space to find distinct regions in the fluorescence images. In this paper we present our work on using machine learning clustering techniques to establish an unsupervised and automatic method that can be used for identifying populations of fluorescent species in spectral and lifetime imaging. We demonstrate our method using both synthetic data, created by sampling photon arrival times and plotting the distributions on the phasor plot, and real live cells samples, by staining cellular organelles with a selection of commercial probes.

Identification of microplastics using 4-dimethylamino-4'-nitrostilbene solvatochromic fluorescence

In this work, we introduce the use of 4‐dimethylamino‐4′‐nitrostilbene (DANS) fluorescent dye for applications in the detection and analysis of microplastics, an impendent source of pollution made of synthetic organic polymers with a size varying from less than 5 mm to nanometer scale. The use of this dye revealed itself as a versatile, fast and sensitive tool for readily discriminate microplastics in water environment. The experimental evidences herein presented demonstrate that DANS efficiently absorbs into a variety of polymers constituting microplastics, and its solvatochromic properties lead to a positive shift of the fluorescence emission spectrum according to the polarity of the polymers. Therefore, under UV illumination, microplastics glow a specific emission spectrum from blue to red that allows for a straightforward polymer identification. In addition, we show that DANS staining gives access to different detection and analysis strategies based on fluorescence microscopy, from simple epifluorescence fragments visualization, to confocal microscopy and phasor approach for plastic components quantification.