Fast fluorescence lifetime imaging techniques: A review on challenge and development

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.

Artificial intelligence (AI)/machine-learning (ML) algorithms have been heavily used in data processing in various biological and clinical applications. Sensitive biological signaling can be monitored using two-photon fluorescence lifetime imaging microscopy (FLIM). Lifetime fitting, processing, and analyzing FLIM data of biological specimens can be a challenging and time-consuming affair. The recently developed Fluorescence Lifetime Redox Ratio (FLIRR) focuses on tracking metabolic changes ‘before-and-after-treatment’ in live cells using only two lifetime parameters. FLIM data produces many data parameters which are all associated with drug response in living cells. To predict drug cellular responses, we have chosen the Becker & Hickl SPCImage software to fit the lifetime images and the resultant data was used in ML analysis. With the objective of achieving even more robust statistical power predicting earliest drug effects, we developed Python software and autoencoder (AE) models to analyze the multiple biophysical FLIM parameters acquired in 2p-FLIM images of drug response in cervical cancer cells. The use of systematic hyperparameter (HP) tuning shows the variation in performance across the different models, enabling the selection of the highest performing model and HPs for repetition. Our results show that our optimized multi-parameter trained AE models can statistically outperform single FLIRR time-course analysis in discriminating earliest metabolic changes following drug treatment.

Metabolism is a complex phenomenon in the biological systems, falling into one of two general categories: catabolic and anabolic reactions, or the processes of breaking down and building up, respectively. Changes in cell or tissue metabolic states respond to changes in physiological demands or the onset of pathological conditions. Auto-fluorescent endogenous biomolecules associated with metabolism such as coenzymes nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) are key players in the production of adenosine triphosphate (ATP)—the energy currency of life. Thus, changes in the abundance of NADH and FAD can serve as noninvasive biomarkers in cells and tissues. There are other auto-fluorescent endogenous molecules, but none as thoroughly investigated as NADH and FAD by advancements in technology such as intensity and lifetime microscopy. The importance of the coenzymes NADH and FAD in metabolism was fully recognized to the scientific world by the great innovator, the late Prof. Britton Chance (1913–2010). He demonstrated cellular NADH auto-fluorescence in 1958 by fluorescence spectrophotometry 1. He developed a fiber optics based fluorimeter to monitor by NADH, the mitochondrial metabolic state of awake rat brains during 1962 2. He has published over 1,500 research articles. Prof. Chance's passion was in translational research and mentoring diverse student populations—regardless of their gender, ethnicity, nationality, religion, or social status—to influence research communities all over the world. Prof. Chance students regarded him as a role model, great mentor, and dear friend. Prof. Chance has tirelessly promoted scientific cooperation and academic exchanges between East and West 3. The ability to make these visible the endogenous biomarkers introduced by Prof. Chance led to their characterization and pathways. During glycolysis, two molecules of ATP are produced in the cytoplasm. Cytoplasmic NADH is transported to mitochondria by malate–aspartate shuttle 4 where, NADH is oxidized to NAD+ producing malate; malate is transported to mitochondrial matrix, mitochondrial NAD+ is reduced to NADH which is in turn is oxidized to NAD+ by the electron transport chain (ETC) in the respiratory chain in the mitochondrial matrix 4, 5. Mitochondrial NADH is produced by citric acid cycle or Kreb's cycle based on several substrates. The energy stored in mitochondrial NADH is transferred to an electrochemical proton gradient that is essential to drive phosphorylation of ADP to ATP by F0F1 ATP synthase, to produce approximately 30 units of ATP, the energy currency of the cell (see Fig. 1 reproduced from the review by Schaefer et al. [in this issue, 34]). The coenzymes FMN/FAD are derived from riboflavin (vitamin B 2) and are covalently bound to flavoproteins in enzymatic reactions of the Kreb's cycle and ETC which takes place in the mitochondria 4. The ETC complex II of succinate dehydrogenase contains bound FAD cofactor which is reduced to FADH2. FADH2 is then oxidized to FAD by Coenzyme Q 4, 5. Only the oxidized form of the flavins, FpOx (FAD or FMN) are fluorescent whereas, the reduced forms Fp (FADH2 or FMNH2), are nonfluorescent. On the other hand, NAD(P)H is fluorescent whereas, the oxidized form NAD(P)+ is nonfluorescent 5, 6. Three out of the 20 amino acids, Tyrosine (Try or Y), Phenylalanine (Phe or F), and Tryptophan (Trp or W), all aromatic, are autofluorescent absorbing and emitting in the UV region. Tryptophan (Trp), an essential amino acid is of particular interest in the biomedical sciences, their fluorescence intensity and lifetime providing information on protein abundance and is dysregulated in cancer 7, 8. Trp is moderately fluorescent with a quantum yield of 0.1–0.5 and has the highest absorption coefficient of the 3 amino acids, and therefore the highest brightness and the longest emission wavelength of 350 nm 8. Alterations in the tryptophan metabolism are suggested to be a common pathological pathway for clinically distinct neurodegenerative disorders, like Parkinson's, Huntington's, and Alzheimer's diseases 9. Modern technologies such as fluorescence lifetime imaging (FLIM) produce endogenous fluorophore data as readouts of mitochondrial function in their natural environment for investigators in the biological and clinical sciences. The unique characteristics of lifetime are that it is sensitive to environmental changes and insensitive to change in fluorophore concentration or excitation intensity. Lifetime helps investigators to fingerprint the molecular functions under various conditions 10. Lifetime techniques have been used for measuring NADH decays since 1967 by spectrofluorometry 11. FLIM provides both spatial and temporal information of molecules and discriminates the bound from free NADH (ref) and NADH from NAD(P)H 12. In this special Cytometry A issue on Metabolism, 10 well-established authors used multiple imaging techniques to explore metabolism in various directions, by: different cell types in 2D and 3D, single cell analyses and their intra- and inter-cell heterogeneities, response to treatment. While imaging the auto-fluorescent NADH and FAD molecules have come a long way to provide insights into the metabolic states of cells and tissue, Schaefer et al. (in this issue, 34) in their very thorough review discuss the “confounding factors” and potential pitfalls—and how to mitigate them. Lukina et al. (in this issue, 47) and Cao et al. (in this issue, 100) discuss additional correlative biomarkers to NADH in second harmonic generation (SHG) of collagen and the putative FRET interaction of Tryptophan (Trp) and NADH, respectively, both in tumors. Lukina et al. (in this issue, 47) investigated the cellular metabolism collagen in colorectal cancer model. Their results demonstrates that the changes in cellular metabolism and fibrotic stroma organization precede morphological alterations and tumor size reduction, and that indicates that NAD(P)H and collagen can be considered as intrinsic indicators of the response to colorectal cancer treatment. Cao et al. (in this issue, 110) presents data in HeLa cervical cancer cells upon treatment with doxorubicin to show the correlations of Trp-NADH energy transfer (E%) of putative Trp residues on enzymes interacting with NADH during NADH to NAD+ transition to a novel, entirely FLIM-based redox ratio – FLIRR 13. In addition, the NADPH/NADH ratio as per Blacker 12 is established suggesting the changing balance between catabolism and anabolism/ROS defense. Cong et al. (in this issue, 80) applied 2-photon FLIM to characterize the critical factors such as physical and chemical microenvironmental signaling in in vitro 3-dimensional tumor models. Ramanujan (in this issue, 101) used a flow cytometry assay to monitor NAD(p)H oxidation kinetics and metabolic status in human breast cancer cells. He also investigated tumor cell heterogeneity in primary tumor epithelial cells isolated from preclinical animal models. Ma et al. (in this issue, 93) sorted out the leukemia cell lines based on their metabolic state differences between proliferation and quiescent cells using the droplet microfluidic technology and phasor FLIM. This approach may be useful to upstream phenotypic platform to correlate with genomic statistics. Chorvatova et al. (in this issue, 13) provided a detailed analysis of endogenous flavins fluorescence photobleaching arising in living cardiac cells during spectrally resolved confocal imaging. This investigation led to significant modifications of the cell responsiveness to metabolic modulators and its contractility, suggesting functional metabolic alterations in the recorded cells. FLIM based AFI imaging is a sensitive way to monitor the cellular metabolism but there are many issues involved in the complex biological system and that may influence the variability in the lifetime values. Chacko and Eliceiri (in this issue, 56) described in this article that it is important to consider the cellular microenvironment such as confluency, pH, inter-/intra-cellular heterogeneity, and choice of cell line for accurate quantitative FLIM based AFI measurement of cellular metabolism. Altarkistany et al. (in this issue, 70) monitored the shift in the fluorescence decay of NAD(P)H and correlate this shift to changes in metabolism that cells undergo during apoptosis using cytometry based FLIM acquisition with phasor analysis. They have demonstrated free to bound ratios as the ratio of “short-to-long” (S/L) fluorescence lifetime, where S/L was found to consistently decrease with an increase in apoptosis. This special issue on metabolism highlights the challenges involved in the investigation using biomarkers but also provides great opportunities to advance research by using the advanced technologies such as FLIM and data analysis at single cells for tissue/in vivo metabolism mapping using biomarkers such as FLIRR, Tryptophan and SHG for changes in collagen. We would like to thank Dr. Attila Tarnok, Editor-in-Chief and Steven Perez, Associate Managing Editor for their valuable guidance and help during this administration of this special issue.

Cadmium zinc telluride (CZT) is the material of choice for high-energy room-temperature X-ray and γ-ray detectors. However, the performance of pixelated detectors is greatly influenced by the quality of CZT. Crystal defects and impurities are one source of shallow and deep level traps for charge carriers. Fluorescence lifetime of the recombination of optically excited charges may indicate the presence and type of defects and impurities in CZT. Fluorescence lifetime imaging microscopy (FLIM) is used to examine the excited-state lifetime in CZT fabricated by different growth methods and conditions. The FLIM set-up analyzes luminescence emitted from the sample following photo excitation. Samples were optically excited above band gap with a pulsed laser (590 nm) for raster scanning a 220 × 165 µm2 sample area. In-situ room-temperature photoluminescence (PL) and FLIM were recorded simultaneously. In order to analyze the FLIM data, two dominant charge carrier decay processes (τ1, τ2) were identified. The luminescence signal decays with a rapid lifetime of τ1 ≈ 50–200 ps, and a large variety of long-lifetime components τ2 were found in the range of 225–900 ps. CZT grown by multi-tube physical vapor transport (MTPVT) showed extremely long-lived recombination decay times up to 3.5 ns in the vicinity of the interface at growth start. Further away from this interface, the recombination lifetime was in the typical range of fast transitions similar to those found in detector-grade CZT fabricated by travelling heater method. Crystalline material quality strongly influences FLIM lifetime. Time-resolved transients of MTPVT-grown CZT compared with industry-leading detector grade CZT (dots: measured data; lines: fitted exponential decay curves).

A quantitative assessment of wound status in a murine model was developed using phasor plot presentation of fluorescence lifetime imaging microscopy (FLIM) data. The quantitative assessment is based on calculating Bhattacharyya distance between g coordinates of FLIM data phasor plot density distributions of wound and healthy skin. The approach was validated for both diabetic and non-diabetic mice wounds, including during low-dose photodynamic therapy (LDPDT). Analysis revealed a shift in the FLIM data phasor plot g coordinates, suggesting altered metabolic processes involved in wound healing. Bhattacharyya distances in the LDPDT groups were closer to zero compared to the control group, which was not treated by LDPDT. Bhattacharyya distances in the non-diabetic LDPDT groups were closer to zero compared to the diabetic LDPDT groups that is consistent with the literature regarding the positive role of LDPDT in accelerating wound healing and the role of diabetes mellitus in impairing wound healing.

Fluorescence lifetime imaging microscopy (FLIM) has been widely used in the field of biological research because of its high specificity, sensitivity, and quantitative ability in the sensing cellular microenvironment. The most commonly used FLIM technology is based on time-correlated single photon counting (TCSPC). Although the TCSPC method has the highest temporal resolution, the data acquisition time is usually long, and the imaging speed is slow. In this work, we proposed a fast FLIM technology for fluorescence lifetime tracking and imaging of single moving particles, named single particle tracking FLIM (SPT-FLIM). We used feedback-controlled addressing scanning and Mosaic FLIM mode imaging to reduce the number of scanned pixels and the data readout time, respectively. Moreover, we developed a compressed sensing analysis algorithm based on alternating descent conditional gradient (ADCG) for low-photon-count data. We applied the ADCG-FLIM algorithm on both simulated and experimental datasets to evaluate its performance. The results showed that ADCG-FLIM could achieve reliable lifetime estimation with high accuracy and precision in the case of a photon count less than 100. By reducing the photon count requirement for each pixel from, typically, 1000 to 100, the acquisition time for a single frame lifetime image could be significantly shortened, and the imaging speed could be improved to a great extent. On this basis, we obtained lifetime trajectories of moving fluorescent beads using the SPT-FLIM technique. Overall, our work offers a powerful tool for fluorescence lifetime tracking and imaging of single moving particles, which will promote the application of TCSPC-FLIM in biological research.

Fluorescence lifetime imaging microscopy (FLIM) techniques are widely used in auto-fluorescence imaging to investigate dynamic metabolic states of the cells. Traditional FLIM imaging requires the cells to adhere to the coverslip to collect enough photons for FLIM data processing. Such conditions pose challenges to non-adherent cells, such as acute myeloid leukemia (AML) cells, because of cell motility. We developed a proto-type micro cell trapping array (MCTA) to immobilize cells in picoliter-size wells with location references. The array keeps non-adherent cells in referenced well locations, allows treatment on stage and re-imaging after time for ultimate cell segmentation analysis. Individual wells are analyzed by a pixel-based region-of-interest (ROI) to analyze cellular redox states. This single well trapping and analysis method allows to isolate treatment responses of a small number of cells, compare their range and predict early effect, which may have clinical applications in the context of cancer aggressiveness and treatment outcomes. We expanded the common intensity-based assay for cellular redox state by a Fluorescence Lifetime measurement, NAD(P)H-a2%, serving as an alternative metric. The new assay is flexible and can be applied to other non-adherent cell lines, expanding FLIM applications in both research and the clinic.

Cancer metastasis involves complex cell behavior and interaction with the extracellular matrix by metabolically active cells. To observe invasion and metastasis with sub-cellular resolution in vivo, multiphoton microscopy (MPM) allows imaging more deeply into tissues with less toxicity, compared with other optical imaging methods. MPM can be combined with second harmonic generation (SHG), fluorescent lifetime imaging microscopy (FLIM), and spectral-lifetime imaging microscopy (SLIM). SHG facilitates imaging of stromal collagen and tumor-stroma interactions, including the architecture and remodeling of the tumor microenvironment. FLIM allows characterization of exogenous and endogenous fluorophores, such as the metabolites FAD and NADH to score for metabolic state and provide optical biomarkers. SLIM permits additional identification and separation of endogenous and exogenous fluorophores by simultaneously collecting their spectra and lifetime, producing an optical molecular "fingerprint". Both FLIM and SLIM also serve as an improved method for the assessment of Förster (or fluorescence) resonance energy transfer (FRET). Hence, the use and further development of these approaches strongly enhances the visualization and quantification of tumor progression, invasion, and metastasis. Herein, we review recent developments of multiphoton FLIM and SLIM to study 2D and 3D cell migration, invasion into the tumor microenvironment, and metastasis.

Fluorescence lifetime imaging microscopy (FLIM) of reduced nicotinamide adenine dinucleotide and reduced nicotinamide adenine dinucleotide phosphate, together termed NAD(P)H, is often used to analyze and characterize the metabolic state of biological samples. The use of photon counting in FLIM of NAD(P)H often leads to long accumulation times which average out sub-second dynamics. This challenge is overcome with the presented two-photon fast FLIM system that uses an analog detection system and fast digitizer, enabling imaging up to 20 frames per second. Furthermore, GPU processing is used for real-time phasor analysis and visualization of collected data.

A Multifocal Multiphoton Volumetric Imaging Technique for High Speed Time-Resolved FRET Imaging in vivo

Intravital imaging is now widely performed using wide-field microscopy, endoscopy, and state-of-the-art multiphoton microscopy for research and clinical assessment applications. Fluorescence lifetime imaging is increasingly being used as a complementary technology to greatly enhance the specificity and sensitivity in the analysis of the various fluorophores present within an intravital image. The fluorescence lifetime of a fluorophore. The fluorescence lifetime distribution for a fluorophore is an intrinsic property, arising from the emission of photons of light in the decaying to its original energy state after its molecules are excited by a specific wavelength of light and remain in an excited state for a range of times. This behavior for individual autofluorescent fluorophores, dyes, drugs, fluorescent proteins and antibodies is most frequently summarized in terms of their average fluorescence lifetime. Fluorescence lifetime differences are then used to identify and discriminate between molecules in various applications, including the assessment of drug distribution and metabolism, and in quantifying cell responses for toxicology. Fluorescence lifetime imaging microscopy (FLIM) and tomography involves the spatial representation of the fluorescent lifetimes of all molecules within image collected over a specified time period and resolution. Autofluorescence lifetime differences between normal and cancerous tissues have been used to define surgical margins during intraoperative surgery. Recent advances have enabled the rapid and robust collection of fluorescence lifetime information from tissues with high-resolution at video-rate speeds using endoscopic probes. Fluorescence lifetime imaging, combined with multi-spectral and anisotropic analysis, yields detailed redox state data from within a cell, arising from its metabolic state and enables intravital analysis of the transport and metabolism of fluorescent probes in cells. Intravital fluorescence lifetime imaging is becoming an indispensable diagnostic approach with broad therapeutic and clinical applications.

High resolution fluorescence lifetime maps from minimal photon counts

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique for studying biological processes. There exists a growing interest in developing strategies to enhance throughput and reduce acquisition time of FLIM systems, which commonly employ laser scanning excitation and time-correlated single-photon counting (TCSPC) detection. In this work, we propose a wide-field FLIM microscope based on compressive sensing and high photon rate detection (beyond pile-up limit) based on a high-efficiency silicon photomultiplier detector as a single-pixel camera. We experimentally validate the capabilities of this design achieving 20 frames per second FLIM images on free-moving green algae sample.

Fluorescence lifetime imaging microscopy (FLIM) is now routinely used for dynamic measurements of signaling events inside living cells, including detection of protein-protein interactions. An understanding of the basic physics of fluorescence lifetime measurements is required to use this technique. In this protocol, we describe both the time-correlated single photon counting and the frequency-domain methods for FLIM data acquisition and analysis. We describe calibration of both FLIM systems, and demonstrate how they are used to measure the quenched donor fluorescence lifetime that results from Förster resonance energy transfer (FRET). We then show how the FLIM-FRET methods are used to detect the dimerization of the transcription factor CCAAT/enhancer binding protein-α in live mouse pituitary cell nuclei. Notably, the factors required for accurate determination and reproducibility of lifetime measurements are described. With either method, the entire protocol including specimen preparation, imaging and data analysis takes ∼2 d.

This study assesses the metabolic status of rat diabetic cardiomyopathy (DCM) models. Echocardiography is used to detect the diastolic dysfunction in type 2 diabetic rats, and a lower threshold for inducible atrial fibrillation is found in type 2 diabetic rats with diastolic dysfunction compared to the control. Metabolic abnormalities are detected by status changes of reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H), which is an essential coenzyme in cells or tissues. Fluorescence lifetime imaging microscopy (FLIM) is used to monitor changes in NAD(P)H in both myocardial tissues and blood. FLIM reveals that the protein-bound proportion of NAD(P)H in rat myocardium in the DCM group is smaller than the control group, which indicates the oxidative phosphorylation rate of the DCM group decreased. Similar results are found for blood plasma of DCM rats by the FLIM study. FLIM exhibits high potential for screening DCM as a label-free, sensitive, and noninvasive method.