Real-time open-source FLIM analysis.

Fluorescence lifetime imaging microscopy (FLIM) provides valuable quantitative insights into fluorophores' chemical microenvironment. Due to long computation times and the lack of accessible, open-source real-time analysis toolkits, traditional analysis of FLIM data, particularly with the widely used time-correlated single-photon counting (TCSPC) approach, typically occurs after acquisition. As a result, uncertainties about the quality of FLIM data persist even after collection, frequently necessitating the extension of imaging sessions. Unfortunately, prolonged sessions not only risk missing important biological events but also cause photobleaching and photodamage. We present the first open-source program designed for real-time FLIM analysis during specimen scanning to address these challenges. Our approach combines acquisition with real-time computational and visualization capabilities, allowing us to assess FLIM data quality on the fly. Our open-source real-time FLIM viewer, integrated as a Napari plugin, displays phasor analysis and rapid lifetime determination (RLD) results computed from real-time data transmitted by acquisition software such as the open-source Micro-Manager-based OpenScan package. Our method facilitates early identification of FLIM signatures and data quality assessment by providing preliminary analysis during acquisition. This not only speeds up the imaging process, but it is especially useful when imaging sensitive live biological samples.

Light-sheet autofluorescence lifetime imaging with a single-photon avalanche diode array.

Significance: Fluorescence lifetime imaging microscopy (FLIM) of the metabolic co-enzyme nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] is a popular method to monitor single-cell metabolism within unperturbed, living 3D systems. However, FLIM of NAD(P)H has not been performed in a light-sheet geometry, which is advantageous for rapid imaging of cells within live 3D samples. Aim: We aim to design, validate, and demonstrate a proof-of-concept light-sheet system for NAD(P)H FLIM. Approach: A single-photon avalanche diode camera was integrated into a light-sheet microscope to achieve optical sectioning and limit out-of-focus contributions for NAD(P)H FLIM of single cells. Results: An NAD(P)H light-sheet FLIM system was built and validated with fluorescence lifetime standards and with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times. NAD(P)H light-sheet FLIM in vivo was demonstrated with live neutrophil imaging in a larval zebrafish tail wound also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light-sheet geometries, indicating a 30× to 6× acquisition speed advantage for the light sheet compared to the laser scanning geometry. Conclusions: FLIM of NAD(P)H is feasible in a light-sheet geometry and is attractive for 3D live cell imaging applications, such as monitoring immune cell metabolism and migration within an organism.

Metabolic response of microglia to amyloid deposition during Alzheimer's disease progression in a mouse model.

Alzheimer's disease (AD) drives metabolic changes in the central nervous system (CNS). In AD microglia are activated and proliferate in response to amyloid ß plaques. To further characterize the metabolic changes in microglia associated with plaque deposition in situ, we examined cortical tissue from 2, 4, and 8-month-old wild type and 5XFAD mice, a mouse model of plaque deposition. 5XFAD mice exhibited progressive microgliosis and plaque deposition as well as changes in microglial morphology and neuronal dystrophy. Multiphoton-based fluorescent lifetime imaging microscopy (FLIM) metabolic measurements showed that older mice had an increased amount of free NAD(P)H, indicative of a shift towards glycolysis. Interestingly in 5XFAD mice, we also found an abundant previously undescribed third fluorescence component that suggests an alternate NAD(P)H binding partner associated with pathology. This work demonstrates that FLIM in combination with other quantitative imaging methods, is a promising label-free tool for understanding the mechanisms of AD pathology.

CASPI: collaborative photon processing for active single-photon imaging.

Image sensors capable of capturing individual photons have made tremendous progress in recent years. However, this technology faces a major limitation. Because they capture scene information at the individual photon level, the raw data is sparse and noisy. Here we propose CASPI: Collaborative Photon Processing for Active Single-Photon Imaging, a technology-agnostic, application-agnostic, and training-free photon processing pipeline for emerging high-resolution single-photon cameras. By collaboratively exploiting both local and non-local correlations in the spatio-temporal photon data cubes, CASPI estimates scene properties reliably even under very challenging lighting conditions. We demonstrate the versatility of CASPI with two applications: LiDAR imaging over a wide range of photon flux levels, from a sub-photon to high ambient regimes, and live-cell autofluorescence FLIM in low photon count regimes. We envision CASPI as a basic building block of general-purpose photon processing units that will be implemented on-chip in future single-photon cameras.

Light sheet autofluorescence lifetime imaging with a single photon avalanche diode array.

Single photon avalanche diode (SPAD) array sensors can increase the imaging speed for fluorescence lifetime imaging microscopy (FLIM) by transitioning from laser scanning to widefield geometries. While a SPAD camera in epi-fluorescence geometry enables widefield FLIM of fluorescently labeled samples, label-free imaging of single-cell autofluorescence is not feasible in an epi-fluorescence geometry because background fluorescence from out-of-focus features masks weak cell autofluorescence and biases lifetime measurements. Here, we address this problem by integrating the SPAD camera in a light sheet illumination geometry to achieve optical sectioning and limit out-of-focus contributions, enabling fast label-free FLIM of single-cell NAD(P)H autofluorescence. The feasibility of this NAD(P)H light sheet FLIM system was confirmed with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times, and in vivo NAD(P)H light sheet FLIM was demonstrated with live neutrophil imaging in a zebrafish tail wound, also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light sheet geometries, indicating a 30X to 6X frame rate advantage for the light sheet compared to the laser scanning geometry. This light sheet system provides faster frame rates for 3D NAD(P)H FLIM for live cell imaging applications such as monitoring single cell metabolism and immune cell migration throughout an entire living organism.

Hardware-software co-design of an open-source automatic multimodal whole slide histopathology imaging system.

Significance: Advanced digital control of microscopes and programmable data acquisition workflows have become increasingly important for improving the throughput and reproducibility of optical imaging experiments. Combinations of imaging modalities have enabled a more comprehensive understanding of tissue biology and tumor microenvironments in histopathological studies. However, insufficient imaging throughput and complicated workflows still limit the scalability of multimodal histopathology imaging. Aim: We present a hardware-software co-design of a whole slide scanning system for high-throughput multimodal tissue imaging, including brightfield (BF) and laser scanning microscopy. Approach: The system can automatically detect regions of interest using deep neural networks in a low-magnification rapid BF scan of the tissue slide and then conduct high-resolution BF scanning and laser scanning imaging on targeted regions with deep learning-based run-time denoising and resolution enhancement. The acquisition workflow is built using Pycro-Manager, a Python package that bridges hardware control libraries of the Java-based open-source microscopy software Micro-Manager in a Python environment. Results: The system can achieve optimized imaging settings for both modalities with minimized human intervention and speed up the laser scanning by an order of magnitude with run-time image processing. Conclusions: The system integrates the acquisition pipeline and data analysis pipeline into a single workflow that improves the throughput and reproducibility of multimodal histopathological imaging.

Two-photon excitation fluorescent spectral and decay properties of retrograde neuronal tracer Fluoro-Gold.

Fluoro-Gold is a fluorescent neuronal tracer suitable for targeted deep imaging of the nervous system. Widefield fluorescence microscopy enables visualization of Fluoro-Gold, but lacks depth discrimination. Though scanning laser confocal microscopy yields volumetric data, imaging depth is limited, and optimal single-photon excitation of Fluoro-Gold requires an unconventional ultraviolet excitation line. Two-photon excitation microscopy employs ultrafast pulsed infrared lasers to image fluorophores at high-resolution at unparalleled depths in opaque tissue. Deep imaging of Fluoro-Gold-labeled neurons carries potential to advance understanding of the central and peripheral nervous systems, yet its two-photon spectral and temporal properties remain uncharacterized. Herein, we report the two-photon excitation spectrum of Fluoro-Gold between 720 and 990 nm, and its fluorescence decay rate in aqueous solution and murine brainstem tissue. We demonstrate unprecedented imaging depth of whole-mounted murine brainstem via two-photon excitation microscopy of Fluoro-Gold labeled facial motor nuclei. Optimal two-photon excitation of Fluoro-Gold within microscope tuning range occurred at 720 nm, while maximum lifetime contrast was observed at 760 nm with mean fluorescence lifetime of 1.4 ns. Whole-mount brainstem explants were readily imaged to depths in excess of 450 µm via immersion in refractive-index matching solution.

New Extensibility and Scripting Tools in the ImageJ Ecosystem.

ImageJ provides a framework for image processing across scientific domains while being fully open source. Over the years ImageJ has been substantially extended to support novel applications in scientific imaging as they emerge, particularly in the area of biological microscopy, with functionality made more accessible via the Fiji distribution of ImageJ. Within this software ecosystem, work has been done to extend the accessibility of ImageJ to utilize scripting, macros, and plugins in a variety of programming scenarios, e.g., from Groovy and Python and in Jupyter notebooks and cloud computing. We provide five protocols that demonstrate the extensibility of ImageJ for various workflows in image processing. We focus first on Fluorescence Lifetime Imaging Microscopy (FLIM) data, since this requires significant processing to provide quantitative insights into the microenvironments of cells. Second, we show how ImageJ can now be utilized for common image processing techniques, specifically image deconvolution and inversion, while highlighting the new, built-in features of ImageJ-particularly its capacity to run completely headless and the Ops matching feature that selects the optimal algorithm for a given function and data input, thereby enabling processing speedup. Collectively, these protocols can be used as a basis for automating biological image processing workflows. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Using PyImageJ for FLIM data processing Alternate Protocol: Groovy FLIMJ in Jupyter Notebooks Basic Protocol 2: Using ImageJ Ops for image deconvolution Support Protocol 1: Using ImageJ Ops matching feature for image inversion Support Protocol 2: Headless ImageJ deconvolution.

Hyperdimensional Imaging Contrast Using an Optical Fiber.

Fluorescence properties of a molecule can be used to study the structural and functional nature of biological processes. Physical properties, including fluorescence lifetime, emission spectrum, emission polarization, and others, help researchers probe a molecule, produce desired effects, and infer causes and consequences. Correlative imaging techniques such as hyperdimensional imaging microscopy (HDIM) combine the physical properties and biochemical states of a fluorophore. Here we present a fiber-based imaging system that can generate hyper-dimensional contrast by combining multiple fluorescence properties into a single fluorescence lifetime decay curve. Fluorescence lifetime imaging microscopy (FLIM) with controlled excitation polarization and temporally dispersed emission can generate a spectrally coded, polarization-filtered lifetime distribution for a pixel. This HDIM scheme generates a better contrast between different molecules than that from individual techniques. This setup uses only a single detector and is simpler to implement, modular, cost-efficient, and adaptable to any existing FLIM microscope. We present higher contrast data from Arabidopsis thaliana epidermal cells based on intrinsic anthocyanin emission properties under multiphoton excitation. This work lays the foundation for an alternative hyperdimensional imaging system and demonstrates that contrast-based imaging is useful to study cellular heterogeneity in biological samples.

FLIMJ: An open-source ImageJ toolkit for fluorescence lifetime image data analysis.

In the field of fluorescence microscopy, there is continued demand for dynamic technologies that can exploit the complete information from every pixel of an image. One imaging technique with proven ability for yielding additional information from fluorescence imaging is Fluorescence Lifetime Imaging Microscopy (FLIM). FLIM allows for the measurement of how long a fluorophore stays in an excited energy state, and this measurement is affected by changes in its chemical microenvironment, such as proximity to other fluorophores, pH, and hydrophobic regions. This ability to provide information about the microenvironment has made FLIM a powerful tool for cellular imaging studies ranging from metabolic measurement to measuring distances between proteins. The increased use of FLIM has necessitated the development of computational tools for integrating FLIM analysis with image and data processing. To address this need, we have created FLIMJ, an ImageJ plugin and toolkit that allows for easy use and development of extensible image analysis workflows with FLIM data. Built on the FLIMLib decay curve fitting library and the ImageJ Ops framework, FLIMJ offers FLIM fitting routines with seamless integration with many other ImageJ components, and the ability to be extended to create complex FLIM analysis workflows. Building on ImageJ Ops also enables FLIMJ's routines to be used with Jupyter notebooks and integrate naturally with science-friendly programming in, e.g., Python and Groovy. We show the extensibility of FLIMJ in two analysis scenarios: lifetime-based image segmentation and image colocalization. We also validate the fitting routines by comparing them against industry FLIM analysis standards.

Second Harmonic Generation Imaging of Collagen in Chronically Implantable Electrodes in Brain Tissue.

Advances in neural engineering have brought about a number of implantable devices for improved brain stimulation and recording. Unfortunately, many of these micro-implants have not been adopted due to issues of signal loss, deterioration, and host response to the device. While glial scar characterization is critical to better understand the mechanisms that affect device functionality or tissue viability, analysis is frequently hindered by immunohistochemical tissue processing methods that result in device shattering and tissue tearing artifacts. Devices are commonly removed prior to sectioning, which can itself disturb the quality of the study. In this methods implementation study, we use the label free, optical sectioning method of second harmonic generation (SHG) to examine brain slices of various implanted intracortical electrodes and demonstrate collagen fiber distribution not found in normal brain tissue. SHG can easily be used in conjunction with multiphoton microscopy to allow direct intrinsic visualization of collagen-containing glial scars on the surface of cortically implanted electrode probes without imposing the physical strain of tissue sectioning methods required for other high resolution light microscopy modalities. Identification and future measurements of these collagen fibers may be useful in predicting host immune response and device signal fidelity.

Optical imaging of collagen fiber damage to assess thermally injured human skin.

Surgery is the definitive treatment for burn patients who sustain full-thickness burn injuries. Visual assessment of burn depth is made by the clinician early after injury but is accurate only up to 70% of the time among experienced surgeons. Collagen undergoes denaturation as a result of thermal injury; however, the association of collagen denaturation and cellular death in response to thermal injury is unknown. While gene expression assays and histologic staining allow for ex vivo identification of collagen changes, these methods do not provide spatial or integrity information in vivo. Thermal effects on collagen and the role of collagen in wound repair have been understudied in human burn models due to a lack of methods to visualize both intact and denatured collagen. Hence, there is a critical need for a clinically applicable method to discriminate between damaged and intact collagen fibers in tissues. We present two complementary candidate methods for visualization of collagen structure in three dimensions. Second harmonic generation imaging offers a label-free, high-resolution method to identify intact collagen. Simultaneously, a fluorophore-tagged collagen-mimetic peptide can detect damaged collagen. Together, these methods enable the characterization of collagen damage in human skin biopsies from burn patients, as well as ex vivo thermally injured human skin samples. These combined methods could enhance the understanding of the role of collagen in human wound healing after thermal injury and potentially assist in clinical decision-making.

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.

Nonparametric empirical Bayesian framework for fluorescence-lifetime imaging microscopy.

Fluorescence lifetime imaging microscopy (FLIM) is a powerful imaging tool used to study the molecular environment of flurophores. In time domain FLIM, extracting lifetime from fluorophores signals entails fitting data to a decaying exponential distribution function. However, most existing techniques for this purpose need large amounts of photons at each pixel and a long computation time, thus making it difficult to obtain reliable inference in applications requiring either short acquisition or minimal computation time. In this work, we introduce a new nonparametric empirical Bayesian framework for FLIM data analysis (NEB-FLIM), leading to both improved pixel-wise lifetime estimation and a more robust and computationally efficient integral property inference. This framework is developed based on a newly proposed hierarchical statistical model for FLIM data and adopts a novel nonparametric maximum likelihood estimator to estimate the prior distribution. To demonstrate the merit of the proposed framework, we applied it on both simulated and real biological datasets and compared it with previous classical methods on these datasets.

Optimization of interstrand interactions enables burn detection with a collagen-mimetic peptide.

Collagen is an abundant component of the extracellular matrix and connective tissues. Some collagen-mimetic peptides (CMPs) that do not form homotrimers can anneal to damaged tissue. Here, through a computational screen, we identify (flpHypGly)7 as an optimal monomeric CMP for heterotrimer formation. We find that (flpHypGly)7 forms stable triple helices with (ProProGly)7 but not with itself. The nonnatural amino acid HflpOH, which is (2S,4S)-4-fluoroproline, is not toxic to human fibroblasts or keratinocytes. Conjugation of (flpHypGly)7 to a fluorescent dye enables the facile detection of burned collagenous tissue with high specificity. The ubiquity of collagen and the prevalence of injuries and diseases that disrupt endogenous collagen suggests widespread utility for this approach.

NAD(P)H fluorescence lifetime measurements in fixed biological tissues.

Autofluorescence based fluorescence lifetime imaging microscopy (AF-FLIM) techniques have come a long way from early studies on cancer characterization and have now been widely employed in several cellular and animal studies covering a wide range of diseases. The majority of research in autofluorescence imaging (AFI) study metabolic fluxes in live biological samples. However, tissues from clinical or scientific studies are often chemically fixed for preservation and stabilization of tissue morphology. Fixation is particularly crucial for enzymatic, functional, or histopathology studies. Interpretations of metabolic imaging such as optical redox intensity imaging and AF-FLIM, have often been viewed as potentially unreliable in a fixed sample due to lack of studies in this field. In this study, we carefully evaluate the possibility of extracting microenvironment information in fixed tissues using reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) endogenous fluorescence. The ability to distinguish changes such as metabolism and pH using intrinsic fluorescence in fixed tissues has great pathological value. In this work, we show that the lifetime based metabolic contrast in a sample is preserved after chemical fixation. The fluorescence lifetime of a sample increases with an additive fixative like formaldehyde; however, the fixed tissues retain metabolic signatures even after fixation. This study presents an opportunity to successfully image archived unstained histopathology tissues, and generate useful AF-FLIM signatures. We demonstrate the capability to draw metabolic interpretations in fixed tissues even after long periods of storage.

Autofluorescence lifetime imaging of cellular metabolism: Sensitivity toward cell density, pH, intracellular, and intercellular heterogeneity.

Autofluorescence imaging (AFI) has greatly accelerated in the last decade, way past its origins in detecting endogenous signals in biological tissues to identify differences between samples. There are many endogenous fluorescence sources of contrast but the most robust and widely utilized have been those associated with metabolism. The intrinsically fluorescent metabolic cofactors nicotinamide adenine dinucleotide (NAD+ /NADH) and flavin adenine dinucleotide (FAD/FADH2 ) have been utilized in a number of AFI applications including basic research, clinical, and pharmaceutical studies. Fluorescence lifetime imaging microscopy (FLIM) has emerged as one of the more powerful AFI tools for NADH and FAD characterization due to its unique ability to noninvasively detect metabolite bound and free states and quantitate cellular redox ratio. However, despite this widespread biological use, many standardization methods are still needed to extend FLIM-based AFI into a fully robust research and clinical diagnostic tools. FLIM is sensitive to a wide range of factors in the fluorophore microenvironment, and there are a number of analysis variables as well. To this end, there has been an emphasis on developing imaging standards and ways to make the image acquisition and analysis more consistent. However, biological conditions during FLIM-based AFI imaging are rarely considered as key sources of FLIM variability. Here, we present several experimental factors with supporting data of the cellular microenvironment such as confluency, pH, inter-/intracellular heterogeneity, and choice of cell line that need to be considered for accurate quantitative FLIM-based AFI measurement of cellular metabolism. © 2018 International Society for Advancement of Cytometry.

Feasibility study on mouse live imaging after spinal cord injury and poly(lactide-co-glycolide) bridge implantation.

Spinal cord injury (SCI) causes permanent paralysis below the damaged area. SCI is linked to neuronal death, demyelination, and limited ability of neuronal fibers to regenerate. Regeneration capacity is limited by the presence of many inhibitory factors in the spinal cord environment. The use of poly(lactide-co-glycolide) (PLG) bridges has demonstrated the ability to sustain long-term regeneration after SCI in a cervical hemisection mouse model. Critically, imaging of regenerating fibers and the myelination status of these neuronal filaments is a severe limitation to progress in SCI research. We used a transgenic mouse model that selectively expresses fluorescent reporters (eGFP) in the neuronal fibers of the spinal cord. We implanted a PLG bridge at C5 vertebra after hemisection and evaluated in live animals' neuronal fibers at the bridge interface and within the bridge 8 weeks postimplant. These in vivo observations were correlated with in situ evaluation 12 weeks postimplantation. We sectioned the spinal cords and performed fluorescent bioimaging on the sections to observe neuronal fibers going through the bridge. In parallel, to visualize myelination of regenerated axons, we exploited the characteristics of the third-harmonic generation arising from the myelin structure in these fixed sections.

Viral highway to nucleus exposed by image correlation analyses.

Parvoviral genome translocation from the plasma membrane into the nucleus is a coordinated multistep process mediated by capsid proteins. We used fast confocal microscopy line scan imaging combined with image correlation methods including auto-, pair- and cross-correlation, and number and brightness analysis, to study the parvovirus entry pathway at the single-particle level in living cells. Our results show that the endosome-associated movement of virus particles fluctuates from fast to slow. Fast transit of single cytoplasmic capsids to the nuclear envelope is followed by slow movement of capsids and fast diffusion of capsid fragments in the nucleoplasm. The unique combination of image analyses allowed us to follow the fate of intracellular single virus particles and their interactions with importin ß revealing previously unknown dynamics of the entry pathway.

Mechanoresponsive stem cells to target cancer metastases through biophysical cues.

Despite decades of effort, little progress has been made to improve the treatment of cancer metastases. To leverage the central role of the mechanoenvironment in cancer metastasis, we present a mechanoresponsive cell system (MRCS) to selectively identify and treat cancer metastases by targeting the specific biophysical cues in the tumor niche in vivo. Our MRCS uses mechanosensitive promoter-driven mesenchymal stem cell (MSC)-based vectors, which selectively home to and target cancer metastases in response to specific mechanical cues to deliver therapeutics to effectively kill cancer cells, as demonstrated in a metastatic breast cancer mouse model. Our data suggest a strong correlation between collagen cross-linking and increased tissue stiffness at the metastatic sites, where our MRCS is specifically activated by the specific cancer-associated mechano-cues. MRCS has markedly reduced deleterious effects compared to MSCs constitutively expressing therapeutics. MRCS indicates that biophysical cues, specifically matrix stiffness, are appealing targets for cancer treatment due to their long persistence in the body (measured in years), making them refractory to the development of resistance to treatment. Our MRCS can serve as a platform for future diagnostics and therapies targeting aberrant tissue stiffness in conditions such as cancer and fibrotic diseases, and it should help to elucidate mechanobiology and reveal what cells "feel" in the microenvironment in vivo.