Fluorescence lifetime imaging - techniques and applications

Enhanced quantification of chlorophyll a and its degradation products in olive oil using time-resolved laser-induced fluorescence fingerprint analysis

Potential errors in the fluorescence analysis of chlorophylls and their degradation products, primarily due to spectral overlap and inner filter, are widely acknowledged. This study aimed to devise a sensitivity-enhanced technique for the concurrent quantification of chlorophyll a and its degradation products while minimizing effects from type-B chlorophylls. Initially, a time-resolved laser-induced fluorescence spectroscopic system was designed and tested on stardard chlorophyll samples. The origins, implications, and mitigation strategies of spectral overlap and the inner filter effect on the measured fluorescence intensity were thoroughly examined. Then, this methodology was proved to be efficacious within complex liquid matrices derived from olive oil. The experimental outcomes not only shed additional light on the mechanisms of chlorophyll fluorescence overlap and the inner filter effect, but also establish a general framework for developing spectrally and timely resolved fluorescence fingerprint analysis for the simultaneous quantification of chlorophylls and their degradation products at high concentrations.

Light-field tomographic fluorescence lifetime imaging microscopy

Fluorescence lifetime imaging microscopy (FLIM) is a powerful imaging technique that enables the visualization of biological samples at the molecular level by measuring the fluorescence decay rate of fluorescent probes. This provides critical information about molecular interactions, environmental changes, and localization within biological systems. However, creating high-resolution lifetime maps using conventional FLIM systems can be challenging, as it often requires extensive scanning that can significantly lengthen acquisition times. This issue is further compounded in three-dimensional (3D) imaging because it demands additional scanning along the depth axis. To tackle this challenge, we developed a computational imaging technique called light-field tomographic FLIM (LIFT-FLIM). Our approach allows for the acquisition of volumetric fluorescence lifetime images in a highly data-efficient manner, significantly reducing the number of scanning steps required compared to conventional point-scanning or line-scanning FLIM imagers. Moreover, LIFT-FLIM enables the measurement of high-dimensional data using low-dimensional detectors, which are typically low cost and feature a higher temporal bandwidth. We demonstrated LIFT-FLIM using a linear single-photon avalanche diode array on various biological systems, showcasing unparalleled single-photon detection sensitivity. Additionally, we expanded the functionality of our method to spectral FLIM and demonstrated its application in high-content multiplexed imaging of lung organoids. LIFT-FLIM has the potential to open up broad avenues in both basic and translational biomedical research.

Facile One Pot Synthesis of Hybrid Core-Shell Silica-Based Sensors for Live Imaging of Dissolved Oxygen and Hypoxia Mapping in 3D Cell Models

Fluorescence imaging allows for noninvasively visualizing and measuring key physiological parameters like pH and dissolved oxygen. In our work, we created two ratiometric fluorescent microsensors designed for accurately tracking dissolved oxygen levels in 3D cell cultures. We developed a simple and cost-effective method to produce hybrid core-shell silica microparticles that are biocompatible and versatile. These sensors incorporate oxygen-sensitive probes (Ru(dpp) or PtOEP) and reference dyes (RBITC or A647 NHS-Ester). SEM analysis confirmed the efficient loading and distribution of the sensing dye on the outer shell. Fluorimetric and CLSM tests demonstrated the sensors' reversibility and high sensitivity to oxygen, even when integrated into 3D scaffolds. Aging and bleaching experiments validated the stability of our hybrid core-shell silica microsensors for 3D monitoring. The Ru(dpp)-RBITC microparticles showed the most promising performance, especially in a pancreatic cancer model using alginate microgels. By employing computational segmentation, we generated 3D oxygen maps during live cell imaging, revealing oxygen gradients in the extracellular matrix and indicating a significant decrease in oxygen level characteristics of solid tumors. Notably, after 12 h, the oxygen concentration dropped to a hypoxic level of PO2 2.7 ± 0.1%.

The promise and peril of comparing fluorescence lifetime in biology revealed by simulations

Signaling dynamics are crucial in biological systems, and biosensor-based real-time imaging has revolutionized their analysis. Fluorescence lifetime imaging microscopy (FLIM) excels over the widely used fluorescence intensity imaging by allowing the measurement of absolute signal levels, independent of sensor concentration. This capability enables the comparison of signaling dynamics across different animals, body regions, and timeframes. However, FLIM's advantage can be compromised by factors like autofluorescence in biological experiments. To address this, we introduce FLiSimBA, a flexible computational framework for realistic F luorescence Li fetime Sim ulation for B iological A pplications. Through simulations, we analyze the signal-to-noise ratios of fluorescence lifetime data, determining measurement uncertainty and providing necessary error bars for lifetime measurements. Furthermore, we challenge the belief that fluorescence lifetime is unaffected by sensor expression and establish quantitative limits to this insensitivity in biological applications. Additionally, we propose innovations, notably multiplexed dynamic imaging that combines fluorescence intensity and lifetime measurements. This innovation can transform the number of signals that can be simultaneously monitored, thereby enabling a systems approach in studying signaling dynamics. Thus, by incorporating diverse factors into our simulation framework, we uncover surprises, identify limitations, and propose advancements for fluorescence lifetime imaging in biology. This quantitative framework supports rigorous experimental design, facilitates accurate data interpretation, and paves the way for technological advancements in fluorescence lifetime imaging.

Micro blood analysis technology (μBAT): multiplexed analysis of neutrophil phenotype and function from microliter whole blood samples

There is an ongoing need to do more with less and provide highly multiplexed analysis from limited sample volumes. Improved "sample sparing" assays would have a broad impact across pediatric and other rare sample type studies in addition to enabling sequential sampling. This capability would advance both clinical and basic research applications. Here we report the micro blood analysis technology (μBAT), a microfluidic platform that supports multiplexed analysis of neutrophils from a single drop of blood. We demonstrate the multiplexed orthogonal capabilities of μBAT including functional assays (phagocytosis, neutrophil extracellular traps, optical metabolic imaging) and molecular assays (gene expression, cytokine secretion). Importantly we validate our microscale platform using a macroscale benchmark assay. μBAT is compatible with lancet puncture or microdraw devices, and its design facilitates rapid operations without the need for specialized equipment. μBAT offers a new method for investigating neutrophil function in populations with restricted sample amounts.

Drosophila melanogaster sperm turn more oxidative in the female

Males and females of many species store sperm for extended periods. During storage, sperm are predicted to undergo cellular and functional changes, especially towards glycolytic energy metabolism because oxygen radicals derived from oxidative phosphorylation can affect sperm motility and fertilisation ability. However, not all species can use both major energy metabolism pathways. Here, we examined the fruit fly Drosophila melanogaster and asked whether sperm metabolism can be fuelled by both glycolysis and oxidative phosphorylation, and to what extent metabolism changes during storage. Inhibiting glycolysis in vitro led to a more oxidative state of sperm; inhibiting oxidative phosphorylation increased the glycolytic component, assessed by multi-photon autofluorescence lifetime imaging (FLIM) of NAD(P)H. We further examined sperm in male and female sperm storage organs using FLIM of NAD(P)H and FAD. In intact storage organs, we found that, unexpectedly, (i) sperm were more oxidative in females than in males, and (ii) oxidative phosphorylation increased with storage duration in females. Our observation that the relative contribution of the two major energy metabolic pathways in D. melanogaster sperm differs in males and females and over storage time has important evolutionary implications.

Increasing the Dye Payload of Cetuximab-IRDye800CW Enables Photodynamic Therapy

Cetuximab (Cet)-IRDye800CW, among other antibody-IRDye800CW conjugates, is a potentially effective tool for delineating tumor margins during fluorescence image-guided surgery (IGS). However, residual disease often leads to recurrence. Photodynamic therapy (PDT) following IGS is proposed as an approach to eliminate residual disease but suffers from a lack of molecular specificity for cancer cells. Antibody-targeted PDT offers a potential solution for this specificity problem. In this study, we show, for the first time, that Cet-IRDye800CW is capable of antibody-targeted PDT in vitro when the payload of dye molecules is increased from 2 (clinical version) to 11 per antibody. Cet-IRDye800CW (1:11) produces singlet oxygen, hydroxyl radicals, and peroxynitrite upon activation with 810 nm light. In vitro assays on FaDu head and neck cancer cells confirm that Cet-IRDye800CW (1:11) maintains cancer cell binding specificity and is capable of inducing up to ∼90% phototoxicity in FaDu cancer cells. The phototoxicity of Cet-IRDye800CW conjugates using 810 nm light follows a dye payload-dependent trend. Cet-IRDye800CW (1:11) is also found to be more phototoxic to FaDu cancer cells and less toxic in the dark than the approved chromophore indocyanine green, which can also act as a PDT agent. We propose that antibody-targeted PDT using high-payload Cet-IRDye800CW (1:11) could hold potential for eliminating residual disease postoperatively when using sustained illumination devices, such as fiber optic patches and implantable surgical bed balloon applicators. This approach could also potentially be applicable to a wide variety of resectable cancers that are amenable to IGS-PDT, using their respective approved full-length antibodies as a template for high-payload IRDye800CW conjugation.

Metabolic imaging of human cumulus cells reveals associations with pregnancy and live birth

STUDY QUESTION

Can fluorescence lifetime imaging microscopy (FLIM) detect associations between the metabolic state of cumulus cell (CC) samples and the clinical outcome of the corresponding embryos?

SUMMARY ANSWER

FLIM can detect significant variations in the metabolism of CC associated with the corresponding embryos that resulted in a clinical pregnancy versus those that did not.

WHAT IS KNOWN ALREADY

CC and oocyte metabolic cooperativity are known to be necessary for the acquisition of developmental competence. However, reliable CC biomarkers that reflect oocyte viability and embryo developmental competency have yet to be established. Quantitative measures of CC metabolism could be used to aid in the evaluation of oocyte and embryo quality in ART.

STUDY DESIGN, SIZE, DURATION

A prospective observational study was carried out. In total, 223 patients undergoing IVF with either conventional insemination or ICSI at a tertiary care center from February 2018 to May 2020 were included, with no exclusion criteria applied.

PARTICIPANTS/MATERIALS, SETTING, METHODS

This cohort had a mean maternal age of 36.5 ± 4.4 years and an average oocyte yield of 16.9 (range 1-50). One to four CC clusters from each patient were collected after oocyte retrieval and vitrified. CC metabolic state was assessed using FLIM to measure the autofluorescence of the molecules NAD(P)H and FAD+, which are essential for multiple metabolic pathways. CC clusters were tracked with their corresponding oocytes and associated embryos. Patient age, Day 3 and Day 5/6 embryo morphological grades, and clinical outcomes of embryos with traceable fate were recorded. Nine FLIM quantitative parameters were obtained for each CC cluster. We investigated associations between the FLIM parameters and patient maternal age, embryo morphological rank, ploidy, and clinical outcome, where false discovery rate P-values of <0.05 were considered statistically significant.

MAIN RESULTS AND THE ROLE OF CHANCE

A total of 851 CC clusters from 851 cumulus-oocyte complexes from 223 patients were collected. Of these CC clusters, 623 were imaged using FLIM. None of the measured CC FLIM parameters were correlated with Day 3 morphological rank or ploidy of the corresponding embryos, but FAD+ FLIM parameters were significantly associated with morphological rank of blastocysts. There were significant differences for FAD+ FLIM parameters (FAD+ fraction engaged and short lifetime) from CC clusters linked with embryos resulting in a clinical pregnancy compared with those that did not, as well as for CC clusters associated with embryos that resulted in a live birth compared those that did not.

LIMITATIONS, REASONS FOR CAUTION

Our data are based on a relatively low number of traceable embryos from an older patient population. Additionally, we only assessed CCs from 1 to 4 oocytes from each patient. Future work in a younger patient population with a larger number of traceable embryos, as well as measuring the metabolic state of CCs from all oocytes from each patient, would provide a better understanding of the potential utility of this technology for oocyte/embryo selection.

WIDER IMPLICATIONS OF THE FINDINGS

Metabolic imaging via FLIM is able to detect CC metabolic associations with maternal age and detects variations in the metabolism of CCs associated with oocytes leading to embryos that result in a clinical pregnancy and a live birth versus those that do not. Our findings suggest that FLIM of CCs may be used as a new approach to aid in the assessment of oocyte and embryo developmental competence in clinical ART.

STUDY FUNDING/COMPETING INTEREST(S)

National Institutes of Health grant NIH R01HD092550-03 (to C.R., and D.J.N.). Becker and Hickl GmbH and Boston Electronics sponsored research with the loaning of equipment for FLIM. D.J.N. and C.R. are inventors on patent US20170039415A1.

TRIAL REGISTRATION NUMBER

N/A.

Advancements in fluorescence lifetime imaging microscopy Instrumentation: Towards high speed and 3D

Fluorescence lifetime imaging microscopy (FLIM) is a powerful imaging tool offering molecular specific insights into samples through the measurement of fluorescence decay time, with promising applications in diverse research fields. However, to acquire two-dimensional lifetime images, conventional FLIM relies on extensive scanning in both the spatial and temporal domain, resulting in much slower acquisition rates compared to intensity-based approaches. This problem is further magnified in three-dimensional imaging, as it necessitates additional scanning along the depth axis. Recent advancements have aimed to enhance the speed and three-dimensional imaging capabilities of FLIM. This review explores the progress made in addressing these challenges and discusses potential directions for future developments in FLIM instrumentation.

Effect of time post warming to embryo transfer on human blastocyst metabolism and pregnancy outcome

PURPOSE

This study is aiming to test whether variation in post warming culture time impacts blastocyst metabolism or pregnancy outcome.

METHODS

In this single center retrospective cohort study, outcomes of 11,520 single frozen embryo transfer (FET) cycles were analyzed from January 2015 to December 2020. Patient treatments included both natural and programmed cycles. Time categories were determined using the time between blastocyst warming and embryo transfer: 0 (0- <1h), 1 (1-<2h), 2 (2-<3h), 3(3-<4h), 4 (4-<5), 5 (5-<6), 6 (6-<7) and 7 (7-8h). Non-invasive metabolic imaging of discarded human blastocysts for up to 10h was also performed using Fluorescence lifetime imaging microscopy (FLIM) to examine for metabolic perturbations during culture.

RESULTS

The mean age of patients across all time categories were comparable (35.6 ± 3.9). Live birth rates (38-52%) and miscarriage rate (5-11%) were not statistically different across post-warming culture time. When assessing pregnancy outcomes based on the use of PGT-A, miscarriage and live birth rates were not statistically different across culture hours in both PGT-A and non-PGT cycles. Further metabolic analysis of blastocysts for the duration of 10h of culture post warming, revealed minimal metabolic changes of embryos in culture.

CONCLUSION

Overall, our results show that differences in the time of post warming culture have no significant impact on miscarriage or live birth rate for frozen embryo transfers. This information can be beneficial for clinical practices with either minimal staffing or a high number of patient cases.

Fluorescence in depth: integration of spectroscopy and imaging with Raman, IR, and CD for advanced research

Fluorescence spectroscopy serves as a vital technique for studying the interaction between light and fluorescent molecules. It encompasses a range of methods, each presenting unique advantages and applications. This technique finds utility in various chemical studies. This review discusses Fluorescence spectroscopy, its branches such as Time-Resolved Fluorescence Spectroscopy (TRFS) and Fluorescence Lifetime Imaging Microscopy (FLIM), and their integration with other spectroscopic methods, including Raman, Infrared (IR), and Circular Dichroism (CD) spectroscopies. By delving into these methods, we aim to provide a comprehensive understanding of the capabilities and significance of fluorescence spectroscopy in scientific research, highlighting its diverse applications and the enhanced understanding it brings when combined with other spectroscopic methods. This review looks at each technique's unique features and applications. It discusses the prospects of their combined use in advancing scientific understanding and applications across various domains.

A Review of Image Sensors Used in Near-Infrared and Shortwave Infrared Fluorescence Imaging

To translate near-infrared (NIR) and shortwave infrared (SWIR) fluorescence imaging into the clinic, the paired imaging device needs to detect trace doses of fluorescent imaging agents. Except for the filtration scheme and excitation light source, the image sensor used will finally determine the detection limitations of NIR and SWIR fluorescence imaging systems. In this review, we investigate the current state-of-the-art image sensors used in NIR and SWIR fluorescence imaging systems and discuss the advantages and limitations of their characteristics, such as readout architecture and noise factors. Finally, the imaging performance of these image sensors is evaluated and compared.

Label-Free Assessment of Key Biological Autofluorophores: Material Characteristics and Opportunities for Clinical Applications

Autofluorophores are endogenous fluorescent compounds that naturally occur in the intra and extracellular spaces of all tissues and organs. Most have vital biological functions - like the metabolic cofactors NAD(P)H and FAD+, as well as the structural protein collagen. Others are considered to be waste products - like lipofuscin and advanced glycation end products - which accumulate with age and are associated with cellular dysfunction. Due to their natural fluorescence, these materials have great utility for enabling non-invasive, label-free assays with direct ties to biological function. Numerous technologies, with different advantages and drawbacks, are applied to their assessment, including fluorescence lifetime imaging microscopy, hyperspectral microscopy, and flow cytometry. Here, the applications of label-free autofluorophore assessment are reviewed for clinical and health-research applications, with specific attention to biomaterials, disease detection, surgical guidance, treatment monitoring, and tissue assessment - fields that greatly benefit from non-invasive methodologies capable of continuous, in vivo characterization.

Two-photon autofluorescence lifetime assay of rabbit photoreceptors and retinal pigment epithelium during light-dark visual cycles in rabbit retina

Two-photon excited fluorescence (TPEF) is a powerful technique that enables the examination of intrinsic retinal fluorophores involved in cellular metabolism and the visual cycle. Although previous intensity-based TPEF studies in non-human primates have successfully imaged several classes of retinal cells and elucidated aspects of both rod and cone photoreceptor function, fluorescence lifetime imaging (FLIM) of the retinal cells under light-dark visual cycle has yet to be fully exploited. Here we demonstrate a FLIM assay of photoreceptors and retinal pigment epithelium (RPE) that reveals key insights into retinal physiology and adaptation. We found that photoreceptor fluorescence lifetimes increase and decrease in sync with light and dark exposure, respectively. This is likely due to changes in all-trans-retinol and all-trans-retinal levels in the outer segments, mediated by phototransduction and visual cycle activity. During light exposure, RPE fluorescence lifetime was observed to increase steadily over time, as a result of all-trans-retinol accumulation during the visual cycle and decreasing metabolism caused by the lack of normal perfusion of the sample. Our system can measure the fluorescence lifetime of intrinsic retinal fluorophores on a cellular scale, revealing differences in lifetime between retinal cell classes under different conditions of light and dark exposure.

Fluorescent Protein-Based Sensors for Detecting Essential Metal Ions across the Tree of Life

Genetically encoded fluorescent metal ion sensors are powerful tools for elucidating metal dynamics in living systems. Over the last 25 years since the first examples of genetically encoded fluorescent protein-based calcium indicators, this toolbox of probes has expanded to include other essential and non-essential metal ions. Collectively, these tools have illuminated fundamental aspects of metal homeostasis and trafficking that are crucial to fields ranging from neurobiology to human nutrition. Despite these advances, much of the application of metal ion sensors remains limited to mammalian cells and tissues and a limited number of essential metals. Applications beyond mammalian systems and in vivo applications in living organisms have primarily used genetically encoded calcium ion sensors. The aim of this Perspective is to provide, with the support of historical and recent literature, an updated and critical view of the design and use of fluorescent protein-based sensors for detecting essential metal ions in various organisms. We highlight the historical progress and achievements with calcium sensors and discuss more recent advances and opportunities for the detection of other essential metal ions. We also discuss outstanding challenges in the field and directions for future studies, including detecting a wider variety of metal ions, developing and implementing a broader spectral range of sensors for multiplexing experiments, and applying sensors to a wider range of single- and multi-species biological systems.

Implementation of FRET Spectrometry Using Temporally Resolved Fluorescence: A Feasibility Study

Förster resonance energy transfer (FRET) spectrometry is a method for determining the quaternary structure of protein oligomers from distributions of FRET efficiencies that are drawn from pixels of fluorescence images of cells expressing the proteins of interest. FRET spectrometry protocols currently rely on obtaining spectrally resolved fluorescence data from intensity-based experiments. Another imaging method, fluorescence lifetime imaging microscopy (FLIM), is a widely used alternative to compute FRET efficiencies for each pixel in an image from the reduction of the fluorescence lifetime of the donors caused by FRET. In FLIM studies of oligomers with different proportions of donors and acceptors, the donor lifetimes may be obtained by fitting the temporally resolved fluorescence decay data with a predetermined number of exponential decay curves. However, this requires knowledge of the number and the relative arrangement of the fluorescent proteins in the sample, which is precisely the goal of FRET spectrometry, thus creating a conundrum that has prevented users of FLIM instruments from performing FRET spectrometry. Here, we describe an attempt to implement FRET spectrometry on temporally resolved fluorescence microscopes by using an integration-based method of computing the FRET efficiency from fluorescence decay curves. This method, which we dubbed time-integrated FRET (or tiFRET), was tested on oligomeric fluorescent protein constructs expressed in the cytoplasm of living cells. The present results show that tiFRET is a promising way of implementing FRET spectrometry and suggest potential instrument adjustments for increasing accuracy and resolution in this kind of study.

A practical guide to time-resolved fluorescence microscopy and spectroscopy

Time-correlated single photon counting (TCSPC) coupled with confocal microscopy is a versatile biophysical tool that enables real-time monitoring of biomolecular dynamics across many timescales. With TCSPC, Fluorescence correlation spectroscopy (FCS) and pulsed interleaved excitation-Förster resonance energy transfer (PIE-FRET) are collected simultaneously on diffusing molecules to extract diffusion characteristics and proximity information. This article is a guide to calibrating FCS and PIE-FRET measurements with several biological samples including liposomes, streptavidin-coated quantum dots, proteins, and nucleic acids for reliable determination of diffusion coefficients and FRET efficiency. The FRET efficiency results are also compared to surface-attached single molecules using fluorescence lifetime imaging microscopy (FLIM-FRET). Combining the methods is a powerful approach to revealing mechanistic details of biological processes and pathways.

More than double the fun with two-photon excitation microscopy

For generations researchers have been observing the dynamic processes of life through the lens of a microscope. This has offered tremendous insights into biological phenomena that span multiple orders of time- and length-scales ranging from the pure magic of molecular reorganization at the membrane of immune cells, to cell migration and differentiation during development or wound healing. Standard fluorescence microscopy techniques offer glimpses at such processes in vitro, however, when applied in intact systems, they are challenged by reduced signal strengths and signal-to-noise ratios that result from deeper imaging. As a remedy, two-photon excitation (TPE) microscopy takes a special place, because it allows us to investigate processes in vivo, in their natural environment, even in a living animal. Here, we review the fundamental principles underlying TPE aimed at basic and advanced microscopy users interested in adopting TPE for intravital imaging. We focus on applications in neurobiology, present current trends towards faster, wider and deeper imaging, discuss the combination with photon counting technologies for metabolic imaging and spectroscopy, as well as highlight outstanding issues and drawbacks in development and application of these methodologies.

Live-cell biosensors based on the fluorescence lifetime of environment-sensing dyes

In this work, we examine the use of environment-sensitive fluorescent dyes in fluorescence lifetime imaging microscopy (FLIM) biosensors. We screened merocyanine dyes to find an optimal combination of environment-induced lifetime changes, photostability, and brightness at wavelengths suitable for live-cell imaging. FLIM was used to monitor a biosensor reporting conformational changes of endogenous Cdc42 in living cells. The ability to quantify activity using phasor analysis of a single fluorophore (e.g., rather than ratio imaging) eliminated potential artifacts. We leveraged these properties to determine specific concentrations of activated Cdc42 across the cell.

Time-Resolved Spectroscopy for Dynamic Investigation of Photoresponsive Metal-Organic Frameworks

Photoresponsive MOFs with precise and adjustable reticular structures are attractive for light conversion applications. Uncovering the photoinduced carrier dynamics lays the essential foundation for the further development and optimization of the MOF material. With the application of time-resolved spectroscopy, photophysical processes including excimer formation, energy transfer/migration, and charge transfer/separation have been widely investigated. However, the identification of distinct photophysical processes in real experimental MOF spectra still remains difficult due to the spectral and dynamic complexity of MOFs. In this Perspective, we summarize the typical spectral features of these photophysical processes and the related analysis methods for dynamic studies performed by time-resolved photoluminescence (TR-PL) and transient absorption (TA) spectroscopy. Based on the recent understanding of excited-state properties of photoresponsive MOFs and the discussion of challenges and future outlooks, this Perspective aims to provide convenience for MOF kinetic analysis and contribute to the further development of photoresponsive MOF material.

Endomembrane-biased dimerization of ABCG16 and ABCG25 transporters determines their substrate selectivity in ABA-regulated plant growth and stress responses

ATP-binding cassette (ABC) transporters are integral membrane proteins that have evolved diverse functions fulfilled via the transport of various substrates. In Arabidopsis, the G subfamily of ABC proteins is particularly abundant and participates in multiple signaling pathways during plant development and stress responses. In this study, we revealed that two Arabidopsis ABCG transporters, ABCG16 and ABCG25, engage in ABA-mediated stress responses and early plant growth through endomembrane-specific dimerization-coupled transport of ABA and ABA-glucosyl ester (ABA-GE), respectively. We first revealed that ABCG16 contributes to osmotic stress tolerance via ABA signaling. More specifically, ABCG16 induces cellular ABA efflux in both yeast and plant cells. Using FRET analysis, we showed that ABCG16 forms obligatory homodimers for ABA export activity and that the plasma membrane-resident ABCG16 homodimers specifically respond to ABA, undergoing notable conformational changes. Furthermore, we demonstrated that ABCG16 heterodimerizes with ABCG25 at the endoplasmic reticulum (ER) membrane and facilitates the ER entry of ABA-GE in both Arabidopsis and tobacco cells. The specific responsiveness of the ABCG16-ABCG25 heterodimer to ABA-GE and the superior growth of their double mutant support an inhibitory role of these two ABCGs in early seedling establishment via regulation of ABA-GE translocation across the ER membrane. Our endomembrane-specific analysis of the FRET signals derived from the homo- or heterodimerized ABCG complexes allowed us to link endomembrane-biased dimerization to the translocation of distinct substrates by ABCG transporters, providing a prototypic framework for understanding the omnipotence of ABCG transporters in plant development and stress responses.

3D convolutional neural networks predict cellular metabolic pathway use from fluorescence lifetime decay data

Fluorescence lifetime imaging of the co-enzyme reduced nicotinamide adenine dinucleotide (NADH) offers a label-free approach for detecting cellular metabolic perturbations. However, the relationships between variations in NADH lifetime and metabolic pathway changes are complex, preventing robust interpretation of NADH lifetime data relative to metabolic phenotypes. Here, a three-dimensional convolutional neural network (3D CNN) trained at the cell level with 3D NAD(P)H lifetime decay images (two spatial dimensions and one time dimension) was developed to identify metabolic pathway usage by cancer cells. NADH fluorescence lifetime images of MCF7 breast cancer cells with three isolated metabolic pathways, glycolysis, oxidative phosphorylation, and glutaminolysis were obtained by a multiphoton fluorescence lifetime microscope and then segmented into individual cells as the input data for the classification models. The 3D CNN models achieved over 90% accuracy in identifying cancer cells reliant on glycolysis, oxidative phosphorylation, or glutaminolysis. Furthermore, the model trained with human breast cancer cell data successfully predicted the differences in metabolic phenotypes of macrophages from control and POLG-mutated mice. These results suggest that the integration of autofluorescence lifetime imaging with 3D CNNs enables intracellular spatial patterns of NADH intensity and temporal dynamics of the lifetime decay to discriminate multiple metabolic phenotypes. Furthermore, the use of 3D CNNs to identify metabolic phenotypes from NADH fluorescence lifetime decay images eliminates the need for time- and expertise-demanding exponential decay fitting procedures. In summary, metabolic-prediction CNNs will enable live-cell and in vivo metabolic measurements with single-cell resolution, filling a current gap in metabolic measurement technologies.

Phasor-FLIM analysis of cellulose paper ageing mechanism with carbotrace 680 dye

Ageing of paper is a complex process of great relevance for application purposes because of its widespread use as support for information storage in books and documents, and as common low-cost and green packaging material, to name a few. A key factor in paper ageing is the oxidation of cellulose, a macromolecule of natural origin that constitutes the main chemical component of paper. Such a complex process results in changes in the cellulose polymeric chains in chemical and structural properties. The scope of this work is to explore the effects of oxidation of cellulose as one of the principal mechanisms of ageing of paper using a fluorescence-based approach. To this aim, fluorescence-lifetime imaging microscopy (FLIM) measurements on pure cellulose samples stained using Carbotrace 680 dye were performed, and data were analyzed by phasor approach. The comparison with results from conventional techniques allowed to map paper microstructure as a function of the sample oxidation degree correlating the fluorescence-lifetime changes to cellulose oxidation. A two-step oxidation kinetics that produced specific modification in paper organization was highlighted indicating that FLIM measurements using Carbotrace 680 dye may provide a simple tool to obtain information on the oxidation process also adding spatial information at sub-micrometric scale.

Artificial Intelligence in Fluorescence Lifetime Imaging Ophthalmoscopy (FLIO) Data Analysis-Toward Retinal Metabolic Diagnostics

The purpose of this study was to investigate the possibility of implementing an artificial intelligence (AI) approach for the analysis of fluorescence lifetime imaging ophthalmoscopy (FLIO) data even with small data. FLIO data, including the fluorescence intensity and mean fluorescence lifetime (τm) of two spectral channels, as well as OCT-A data from 26 non-smokers and 28 smokers without systemic and ocular diseases were used. The analysis was performed with support vector machines (SVMs), a well-known AI method for small datasets, and compared with the results of convolutional neural networks (CNNs) and autoencoder networks. The SVM was the only tested AI method, which was able to distinguish τm between non-smokers and heavy smokers. The accuracy was about 80%. OCT-A data did not show significant differences. The feasibility and usefulness of the AI in analyzing FLIO and OCT-A data without any apparent retinal diseases were demonstrated. Although further studies with larger datasets are necessary to validate the results, the results greatly suggest that AI could be useful in analyzing FLIO-data even from healthy subjects without retinal disease and even with small datasets. AI-assisted FLIO is expected to greatly advance early retinal diagnosis.

Unravelling molecular dynamics in living cells: Fluorescent protein biosensors for cell biology

Genetically encoded, fluorescent protein (FP)-based Förster resonance energy transfer (FRET) biosensors are microscopy imaging tools tailored for the precise monitoring and detection of molecular dynamics within subcellular microenvironments. They are characterised by their ability to provide an outstanding combination of spatial and temporal resolutions in live-cell microscopy. In this review, we begin by tracing back on the historical development of genetically encoded FP labelling for detection in live cells, which lead us to the development of early biosensors and finally to the engineering of single-chain FRET-based biosensors that have become the state-of-the-art today. Ultimately, this review delves into the fundamental principles of FRET and the design strategies underpinning FRET-based biosensors, discusses their diverse applications and addresses the distinct challenges associated with their implementation. We place particular emphasis on single-chain FRET biosensors for the Rho family of guanosine triphosphate hydrolases (GTPases), pointing to their historical role in driving our understanding of the molecular dynamics of this important class of signalling proteins and revealing the intricate relationships and regulatory mechanisms that comprise Rho GTPase biology in living cells.

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, and robustness. Inspired by the concept of Edge Artificial Intelligence (Edge AI), we propose a robust approach that enables fast FLI with no degradation of accuracy. This approach couples a recurrent neural network (RNN), which is trained to estimate the fluorescence lifetime directly from raw timestamps without building histograms, to SPAD TCSPC systems, thereby drastically reducing transfer data volumes and hardware resource utilization, and enabling real-time FLI acquisition. We train two variants of the RNN on a synthetic dataset and compare the results to those obtained using center-of-mass method (CMM) and least squares fitting (LS fitting). Results demonstrate that two RNN variants, gated recurrent unit (GRU) and long short-term memory (LSTM), are comparable to CMM and LS fitting in terms of accuracy, while outperforming them in the presence of background noise by a large margin. To explore the ultimate limits of the approach, we derive the Cramer-Rao lower bound of the measurement, showing that RNN yields lifetime estimations with near-optimal precision. To demonstrate real-time operation, we build a FLI microscope based on an existing SPAD TCSPC system comprising a 32[Formula: see text]32 SPAD sensor named Piccolo. Four quantized GRU cores, capable of processing up to 4 million photons per second, are deployed on the Xilinx Kintex-7 FPGA that controls the Piccolo. Powered by the GRU, the FLI setup can retrieve real-time fluorescence lifetime images at up to 10 frames per second. The proposed FLI system is promising and ideally suited for biomedical applications, including biological imaging, biomedical diagnostics, and fluorescence-assisted surgery, etc.

Applications of machine learning in time-domain fluorescence lifetime imaging: a review

Many medical imaging modalities have benefited from recent advances in Machine Learning (ML), specifically in deep learning, such as neural networks. Computers can be trained to investigate and enhance medical imaging methods without using valuable human resources. In recent years, Fluorescence Lifetime Imaging (FLIm) has received increasing attention from the ML community. FLIm goes beyond conventional spectral imaging, providing additional lifetime information, and could lead to optical histopathology supporting real-time diagnostics. However, most current studies do not use the full potential of machine/deep learning models. As a developing image modality, FLIm data are not easily obtainable, which, coupled with an absence of standardisation, is pushing back the research to develop models which could advance automated diagnosis and help promote FLIm. In this paper, we describe recent developments that improve FLIm image quality, specifically time-domain systems, and we summarise sensing, signal-to-noise analysis and the advances in registration and low-level tracking. We review the two main applications of ML for FLIm: lifetime estimation and image analysis through classification and segmentation. We suggest a course of action to improve the quality of ML studies applied to FLIm. Our final goal is to promote FLIm and attract more ML practitioners to explore the potential of lifetime imaging.

Fibre-optic based exploration of lung cancer autofluorescence using spectral fluorescence lifetime

Fibre-optic based time-resolved fluorescence spectroscopy (TRFS) is an advanced spectroscopy technique that generates sample-specific spectral-temporal signature, characterising variations in fluorescence in real-time. As such, it can be used to interrogate tissue autofluorescence. Recent advancements in TRFS technology, including the development of devices that simultaneously measure high-resolution spectral and temporal fluorescence, paired with novel analysis methods extracting information from these multidimensional measurements effectively, provide additional insight into the underlying autofluorescence features of a sample. This study demonstrates, using both simulated data and endogenous fluorophores measured bench-side, that the shape of the spectral fluorescence lifetime, or fluorescence lifetimes estimated over high-resolution spectral channels across a broad range, is influenced by the relative abundance of underlying fluorophores in mixed systems and their respective environment. This study, furthermore, explores the properties of the spectral fluorescence lifetime in paired lung tissue deemed either abnormal or normal by pathologists. We observe that, on average, the shape of the spectral fluorescence lifetime at multiple locations sampled on 14 abnormal lung tissue, compared to multiple locations sampled on the respective paired normal lung tissue, shows more variability; and, while not statistically significant, the average spectral fluorescence lifetime in abnormal tissue is consistently lower over every wavelength than the normal tissue.

Two-photon excited-state dynamics of mEGFP-linker-mScarlet-I crowding biosensor in controlled environments

Macromolecular crowding affects many cellular processes such as diffusion, biochemical reaction kinetics, protein-protein interactions, and protein folding. Mapping the heterogeneous, dynamic crowding in living cells or tissues requires genetically encoded, site-specific, crowding sensors that are compatible with quantitative, noninvasive fluorescence micro-spectroscopy. Here, we carried out time-resolved 2P-fluorescence measurements of a new mEGFP-linker-mScarlet-I macromolecular crowding construct (GE2.3) to characterize its environmental sensitivity in biomimetic crowded solutions (Ficoll-70, 0-300 g L-1) via Förster resonance energy transfer (FRET) analysis. The 2P-fluorescence lifetime of the donor (mEGFP) was measured under magic-angle polarization, in the presence (intact) and absence (enzymatically cleaved) of the acceptor (mScarlet-I), as a function of the Ficoll-70 concentration. The FRET efficiency was used to quantify the sensitivity of GE2.3 to macromolecular crowding and to determine the environmental dependence of the mEGFP-mScarlet-I distance. We also carried out time-resolved 2P-fluorescence depolarization anisotropy to examine both macromolecular crowding and linker flexibility effects on GE2.3 rotational dynamics within the context of the Stokes-Einstein model as compared with theoretical predictions based on its molecular weight. These time-resolved 2P-fluorescence depolarization measurements and conformational population analyses of GE2.3 were also used to estimate the free energy gain upon the structural collapse in crowded environment. Our results further the development of a rational engineering design for bioenvironmental sensors without the interference of cellular autofluorescence. Additionally, these results in well-defined environments will inform our future in vivo studies of genetically encoded GE2.3 towards the mapping of the crowded intracellular environment under different physiological conditions.

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.

Label-free single-cell live imaging reveals fast metabolic switch in T lymphocytes

T-cell activation induces a metabolic switch generating energy for proliferation, survival, and functions. We used noninvasive label-free two-photon fluorescence lifetime microscopy (2P-FLIM) to map the spatial and temporal dynamics of the metabolic NAD(P)H co-enzyme during T lymphocyte activation. This provides a readout of the OXPHOS and glycolysis rates at a single-cell level. Analyzes were performed in the CD4+ leukemic T cell line Jurkat, and in human CD4+ primary T cells. Cells were activated on glass surfaces coated with activating antibodies mimicking immune synapse formation. Comparing the fraction of bound NAD(P)H between resting and activated T cells, we show that T-cell activation induces a rapid switch toward glycolysis. This occurs after 10 min and remains stable for one hour. Three-dimensional analyzes revealed that the intracellular distribution of fraction of bound NAD(P)H increases at the immune synapse in activated cells. Finally, we show that fraction of bound NAD(P)H tends to negatively correlate with spreading of activated T cells, suggesting a link between actin remodeling and metabolic changes. This study highlights that 2P-FLIM measurement of fraction of bound NAD(P)H is well suited to follow a fast metabolic switch in three dimensions, in single T lymphocytes with subcellular resolution.

Review of optical methods for noninvasive imaging of skin fibroblasts-From in vitro to ex vivo and in vivo visualization

Fibroblasts are among the most common cell types in the stroma responsible for creating and maintaining the structural organization of the extracellular matrix in the dermis, skin regeneration, and a range of immune responses. Until now, the processes of fibroblast adaptation and functioning in a varying environment have not been fully understood. Modern laser microscopes are capable of studying fibroblasts in vitro and ex vivo. One-photon- and two-photon-excited fluorescence microscopy, Raman spectroscopy/microspectroscopy are well-suited noninvasive optical methods for fibroblast imaging in vitro and ex vivo. In vivo staining-free fibroblast imaging is not still implemented. The exception is fibroblast imaging in tattooed skin. Although in vivo noninvasive staining-free imaging of fibroblasts in the skin has not yet been implemented, it is expected in the future. This review summarizes the state-of-the-art in fibroblast visualization using optical methods and discusses the advantages, limitations, and prospects for future noninvasive imaging.

Fluorescence Lifetime Measurements and Analyses: Protocols Using Flow Cytometry and High-Throughput Microscopy

This chapter focuses on applications and protocols that involve the measurement of the fluorescence lifetime as an informative cytometric parameter. The timing of fluorescence decay has been well-studied for cell counting, sorting, and imaging. Therefore, provided herein is an overview of the techniques used, how they enhance cytometry protocols, and the modern techniques used for lifetime analysis. The background and theory behind fluorescence decay kinetic measurements in cells is first discussed followed by the history of the development of time-resolved flow cytometry. These sections are followed by a review of applications that benefit from the quantitative nature of fluorescence lifetimes as a photophysical trait. Lastly, perspectives on the modern ways in which the fluorescence lifetime is scanned at high throughputs which include high-speed microscopy and machine learning are provided.

Molecularly Engineered Room-Temperature Phosphorescence for Biomedical Application: From the Visible toward Second Near-Infrared Window

Phosphorescence, characterized by luminescent lifetimes significantly longer than that of biological autofluorescence under ambient environment, is of great value for biomedical applications. Academic evidence of fluorescence imaging indicates that virtually all imaging metrics (sensitivity, resolution, and penetration depths) are improved when progressing into longer wavelength regions, especially the recently reported second near-infrared (NIR-II, 1000-1700 nm) window. Although the emission wavelength of probes does matter, it is not clear whether the guideline of "the longer the wavelength, the better the imaging effect" is still suitable for developing phosphorescent probes. For tissue-specific bioimaging, long-lived probes, even if they emit visible phosphorescence, enable accurate visualization of large deep tissues. For studies dealing with bioimaging of tiny biological architectures or dynamic physiopathological activities, the prerequisite is rigorous planning of long-wavelength phosphorescence, being aware of the cooperative contribution of long wavelengths and long lifetimes for improving the spatiotemporal resolution, penetration depth, and sensitivity of bioimaging. In this Review, emerging molecular engineering methods of room-temperature phosphorescence are discussed through the lens of photophysical mechanisms. We highlight the roles of phosphorescence with emission from visible to NIR-II windows toward bioapplications. To appreciate such advances, challenges and prospects in rapidly growing studies of room-temperature phosphorescence are described.

Single-photon microscopy to study biomolecular condensates

Biomolecular condensates serve as membrane-less compartments within cells, concentrating proteins and nucleic acids to facilitate precise spatial and temporal orchestration of various biological processes. The diversity of these processes and the substantial variability in condensate characteristics present a formidable challenge for quantifying their molecular dynamics, surpassing the capabilities of conventional microscopy. Here, we show that our single-photon microscope provides a comprehensive live-cell spectroscopy and imaging framework for investigating biomolecular condensation. Leveraging a single-photon detector array, single-photon microscopy enhances the potential of quantitative confocal microscopy by providing access to fluorescence signals at the single-photon level. Our platform incorporates photon spatiotemporal tagging, which allowed us to perform time-lapse super-resolved imaging for molecular sub-diffraction environment organization with simultaneous monitoring of molecular mobility, interactions, and nano-environment properties through fluorescence lifetime fluctuation spectroscopy. This integrated correlative study reveals the dynamics and interactions of RNA-binding proteins involved in forming stress granules, a specific type of biomolecular condensates, across a wide range of spatial and temporal scales. Our versatile framework opens up avenues for exploring a broad spectrum of biomolecular processes beyond the formation of membrane-less organelles.

Label-free spatially maintained measurements of metabolic phenotypes in cells

Metabolic reprogramming at a cellular level contributes to many diseases including cancer, yet few assays are capable of measuring metabolic pathway usage by individual cells within living samples. Here, autofluorescence lifetime imaging is combined with single-cell segmentation and machine-learning models to predict the metabolic pathway usage of cancer cells. The metabolic activities of MCF7 breast cancer cells and HepG2 liver cancer cells were controlled by growing the cells in culture media with specific substrates and metabolic inhibitors. Fluorescence lifetime images of two endogenous metabolic coenzymes, reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavin adenine dinucleotide (FAD), were acquired by a multi-photon fluorescence lifetime microscope and analyzed at the cellular level. Quantitative changes of NADH and FAD lifetime components were observed for cells using glycolysis, oxidative phosphorylation, and glutaminolysis. Conventional machine learning models trained with the autofluorescence features classified cells as dependent on glycolytic or oxidative metabolism with 90%-92% accuracy. Furthermore, adapting convolutional neural networks to predict cancer cell metabolic perturbations from the autofluorescence lifetime images provided improved performance, 95% accuracy, over traditional models trained via extracted features. Additionally, the model trained with the lifetime features of cancer cells could be transferred to autofluorescence lifetime images of T cells, with a prediction that 80% of activated T cells were glycolytic, and 97% of quiescent T cells were oxidative. In summary, autofluorescence lifetime imaging combined with machine learning models can detect metabolic perturbations between glycolysis and oxidative metabolism of living samples at a cellular level, providing a label-free technology to study cellular metabolism and metabolic heterogeneity.

Aggregation-induced emission (AIE)-active metallacycles with near-infrared emission for photodynamic therapy

Multifunctional metallacycles with solid-state emission are highly important in cancer therapy. Here, an aggregation-induced emission (AIE)-active metallacycle of DTPABT-MC-R is developed with efficient emission in the NIR region in the solid state (PLQYs = 4.92%). DTPABT-MC-R-based nanoparticles also display excellent photo-stability, and impressive photosensitive characteristics (ROS efficiency = 10.74%), finally leading to applications in cellular imaging and photodynamic therapy (PDT).

Fluorescence-readout as a powerful macromolecular characterisation tool

The last few decades have witnessed significant progress in synthetic macromolecular chemistry, which can provide access to diverse macromolecules with varying structural complexities, topology and functionalities, bringing us closer to the aim of controlling soft matter material properties with molecular precision. To reach this goal, the development of advanced analytical techniques, allowing for micro-, molecular level and real-time investigation, is essential. Due to their appealing features, including high sensitivity, large contrast, fast and real-time response, as well as non-invasive characteristics, fluorescence-based techniques have emerged as a powerful tool for macromolecular characterisation to provide detailed information and give new and deep insights beyond those offered by commonly applied analytical methods. Herein, we critically examine how fluorescence phenomena, principles and techniques can be effectively exploited to characterise macromolecules and soft matter materials and to further unravel their constitution, by highlighting representative examples of recent advances across major areas of polymer and materials science, ranging from polymer molecular weight and conversion, architecture, conformation to polymer self-assembly to surfaces, gels and 3D printing. Finally, we discuss the opportunities for fluorescence-readout to further advance the development of macromolecules, leading to the design of polymers and soft matter materials with pre-determined and adaptable properties.

FLUTE: A Python GUI for interactive phasor analysis of FLIM data

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique used to probe the local environment of fluorophores. The fit-free phasor approach to FLIM data is increasingly being used due to its ease of interpretation. To date, no open-source graphical user interface (GUI) for phasor analysis of FLIM data is available in Python, thus limiting the widespread use of phasor analysis in biomedical research. Here, we present Fluorescence Lifetime Ultimate Explorer (FLUTE), a Python GUI that is designed to fill this gap. FLUTE simplifies and automates many aspects of the analysis of FLIM data acquired in the time domain, such as calibrating the FLIM data, performing interactive exploration of the phasor plot, displaying phasor plots and FLIM images with different lifetime contrasts simultaneously, and calculating the distance from known molecular species. After applying desired filters and thresholds, the final edited datasets can be exported for further user-specific analysis. FLUTE has been tested using several FLIM datasets including autofluorescence of zebrafish embryos and in vitro cells. In summary, our user-friendly GUI extends the advantages of phasor plotting by making the data visualization and analysis easy and interactive, allows for analysis of large FLIM datasets, and accelerates FLIM analysis for non-specialized labs.

The structure of NAD+ consuming protein Acinetobacter baumannii TIR domain shows unique kinetics and conformations

Toll-like and interleukin-1/18 receptor/resistance (TIR) domain-containing proteins function as important signaling and immune regulatory molecules. TIR domain-containing proteins identified in eukaryotic and prokaryotic species also exhibit NAD+ hydrolase activity in select bacteria, plants, and mammalian cells. We report the crystal structure of the Acinetobacter baumannii TIR domain protein (AbTir-TIR) with confirmed NAD+ hydrolysis and map the conformational effects of its interaction with NAD+ using hydrogen-deuterium exchange-mass spectrometry. NAD+ results in mild decreases in deuterium uptake at the dimeric interface. In addition, AbTir-TIR exhibits EX1 kinetics indicative of large cooperative conformational changes, which are slowed down upon substrate binding. Additionally, we have developed label-free imaging using the minimally invasive spectroscopic method 2-photon excitation with fluorescence lifetime imaging, which shows differences in bacteria expressing native and mutant NAD+ hydrolase-inactivated AbTir-TIRE208A protein. Our observations are consistent with substrate-induced conformational changes reported in other TIR model systems with NAD+ hydrolase activity. These studies provide further insight into bacterial TIR protein mechanisms and their varying roles in biology.

Genetically encoded fluorescence lifetime biosensors: overview, advances, and opportunities

Genetically encoded biosensors based on fluorescent proteins (FPs) are powerful tools for tracking analytes and cellular events with high spatial and temporal resolution in living cells and organisms. Compared with intensiometric readout and ratiometric readout, fluorescence lifetime readout provides absolute measurements, independent of the biosensor expression level and instruments. Thus, genetically encoded fluorescence lifetime biosensors play a vital role in facilitating accurate quantitative assessments within intricate biological systems. In this review, we first provide a concise description of the categorization and working mechanism of genetically encoded fluorescence lifetime biosensors. Subsequently, we elaborate on the combination of the fluorescence lifetime imaging technique and lifetime analysis methods with fluorescence lifetime biosensors, followed by their application in monitoring the dynamics of environment parameters, analytes and cellular events. Finally, we discuss worthwhile considerations for the design, optimization and development of fluorescence lifetime-based biosensors from three representative cases.

A Series of Planar Phosphorescent Cyclometalated Platinum(II) Complexes as New Anticancer Theranostic Agents That Induce Oncosis

Herein, four planar cyclometalated platinum(II) complexes with a main ligand of enlarged aromatic rings have been assessed as effective anticancer theranostic agents for the first time. With an increased number of aromatic rings in the N∧N ligand, 1a-1d exhibit increased lipophilicity and cytotoxicity selectivity. The intensity of the Pt-Pt interaction of each complex can be indicated by an enhanced near-infrared (NIR) emission in phosphate-buffered saline (PBS), their binding activity with biomolecules of bovine serum albumin (BSA) is accompanied by a vivid turn-on green emission, and the intensity gradually decreased from 1a to 1d, which is consistent with the docking of two complexes with BSA. Both "turn-on" NIR and green emission of 1d can be mainly observed in nuclei of living cell within 24 h, while two phosphorescence traces of 1b were recorded in lysosomes by confocal imaging. Moreover, 1d shows the highest efficiency in inducing oncosis of Hela cells, and the relative process was investigated.

Kernelizing: A way to increase accuracy in trilinear decomposition analysis of multiexponential signals

The unmixing of multiexponential decay signals into monoexponential components using soft modelling approaches is a challenging task due to the strong correlation and complete window overlap of the profiles. To solve this problem, slicing methodologies, such as PowerSlicing, tensorize the original data matrix into a three-way data array that can be decomposed based on trilinear models providing unique solutions. Satisfactory results have been reported for different types of data, e.g., nuclear magnetic resonance or time-resolved fluorescence spectra. However, when decay signals are described by only a few sampling (time) points, a significant degradation of the results can be observed in terms of accuracy and precision of the recovered profiles. In this work, we propose a methodology called Kernelizing that provides a more efficient way to tensorize data matrices of multiexponential decays. Kernelizing relies on the invariance of exponential decays, i.e., when convolving a monoexponential decaying function with any positive function of finite width (hereafter called "kernel"), the shape of the decay (determined by the characteristic decay constant) remains unchanged and only the preexponential factor varies. The way preexponential factors are affected across the sample and time modes is linear, and it only depends on the kernel used. Thus, using kernels of different shapes, a set of convolved curves can be obtained for every sample, and a three-way data array generated, for which the modes are sample, time and kernelizing effect. This three-way array can be afterwards analyzed by a trilinear decomposition method, such as PARAFAC-ALS, to resolve the underlying monoexponential profiles. To validate this new approach and assess its performance, we applied Kernelizing to simulated datasets, real time-resolved fluorescence spectra collected on mixtures of fluorophores and fluorescence-lifetime imaging microscopy data. When the measured multiexponential decays feature few sampling points (down to fifteen), more accurate trilinear model estimates are obtained than when using slicing methodologies.

Trends in Single-Molecule Total Internal Reflection Fluorescence Imaging and Their Biological Applications with Lab-on-a-Chip Technology

Single-molecule imaging technologies, especially those based on fluorescence, have been developed to probe both the equilibrium and dynamic properties of biomolecules at the single-molecular and quantitative levels. In this review, we provide an overview of the state-of-the-art advancements in single-molecule fluorescence imaging techniques. We systematically explore the advanced implementations of in vitro single-molecule imaging techniques using total internal reflection fluorescence (TIRF) microscopy, which is widely accessible. This includes discussions on sample preparation, passivation techniques, data collection and analysis, and biological applications. Furthermore, we delve into the compatibility of microfluidic technology for single-molecule fluorescence imaging, highlighting its potential benefits and challenges. Finally, we summarize the current challenges and prospects of fluorescence-based single-molecule imaging techniques, paving the way for further advancements in this rapidly evolving field.

Identification of the SNARE complex that mediates the fusion of multivesicular bodies with the plasma membrane in exosome secretion

Exosomes play crucial roles in local and distant cellular communication and are involved in various physiological and pathological processes. Tumour-derived exosomes are pivotal to tumorigenesis, but the precise mechanisms underlying their secretion remain elusive. In particular, the SNARE proteins that mediate the fusion of multivesicular bodies (MVBs) with the plasma membrane (PM) in tumour cells are subject to debate. In this study, we identified syntaxin-4, SNAP-23, and VAMP-7 as the SNAREs responsible for exosome secretion in MCF-7 breast cancer cells and found that a SNARE complex consisting of these SNAREs can drive membrane fusion in vitro. Deletion of any of these SNAREs in MCF-7 cells did not affect MVB biogenesis and transportation, indicating their specific involvement in MVB-PM fusion. In addition, syntaxin-4, SNAP-23, and VAMP-7 play equivalent roles in exosome secretion in both HeLa cervical cancer cells and A375 melanoma cells, suggesting their conserved function in exosome secretion. Furthermore, deletion of VAMP-7 in 4T1 mammary carcinoma cells efficiently inhibited exosome secretion and led to significant attenuation of tumour growth and lung metastasis in mouse models, implying that VAMP-7 may hold promise as a novel therapeutic target for breast cancer.

Two-photon fluorescence lifetime imaging microscopy of NADH metabolism in HIV-1 infected cells and tissues

Rapid detection of microbial-induced cellular changes during the course of an infection is critical to understanding pathogenesis and immunological homeostasis. In the last two decades, fluorescence imaging has received significant attention for its ability to help characterize microbial induced cellular and tissue changes in in vitro and in vivo settings. However, most of these methods rely on the covalent conjugation of large exogenous probes and detection methods based on intensity-based imaging. Here, we report a quantitative, intrinsic, label-free, and minimally invasive method based on two-photon fluorescence lifetime (FLT) imaging microscopy (2p-FLIM) for imaging 1,4-dihydro-nicotinamide adenine dinucleotide (NADH) metabolism of virally infected cells and tissue sections. To better understand virally induced cellular and tissue changes in metabolism we have used 2p-FLIM to study differences in NADH intensity and fluorescence lifetimes in HIV-1 infected cells and tissues. Differences in NADH fluorescence lifetimes are associated with cellular changes in metabolism and changes in cellular metabolism are associated with HIV-1 infection. NADH is a critical co-enzyme and redox regulator and an essential biomarker in the metabolic processes. Label-free 2p-FLIM application and detection of NADH fluorescence using viral infection systems are in their infancy. In this study, the application of the 2p-FLIM assay and quantitative analyses of HIV-1 infected cells and tissue sections reveal increased fluorescence lifetime and higher enzyme-bound NADH fraction suggesting oxidative phosphorylation (OxPhos) compared to uninfected cells and tissues. 2p-FLIM measurements improve signal to background, fluorescence specificity, provide spatial and temporal resolution of intracellular structures, and thus, are suitable for quantitative studies of cellular functions and tissue morphology. Furthermore, 2p-FLIM allows distinguishing free and bound populations of NADH by their different fluorescence lifetimes within single infected cells. Accordingly, NADH fluorescence measurements of individual single cells should provide necessary insight into the heterogeneity of metabolic activity of infected cells. Implementing 2p-FLIM to viral infection systems measuring NADH fluorescence at the single or subcellular level within a tissue can provide visual evidence, localization, and information in a real-time diagnostic or therapeutic metabolic workflow.

Label-free fluorescence microscopy: revisiting the opportunities with autofluorescent molecules and harmonic generations as biosensors and biomarkers for quantitative biology

Over the past decade, the utilization of advanced fluorescence microscopy technologies has presented numerous opportunities to study or re-investigate autofluorescent molecules and harmonic generation signals as molecular biomarkers and biosensors for in vivo cell and tissue studies. The label-free approaches benefit from the endogenous fluorescent molecules within the cell and take advantage of their spectroscopy properties to address biological questions. Harmonic generation can be used as a tool to identify the occurrence of fibrillar or lipid deposits in tissues, by using second and third-harmonic generation microscopy. Combining autofluorescence with novel techniques and tools such as fluorescence lifetime imaging microscopy (FLIM) and hyperspectral imaging (HSI) with model-free analysis of phasor plots has revolutionized the understanding of molecular processes such as cellular metabolism. These tools provide quantitative information that is often hidden under classical intensity-based microscopy. In this short review, we aim to illustrate how some of these technologies and techniques may enable investigation without the need to add a foreign fluorescence molecule that can modify or affect the results. We address some of the most important autofluorescence molecules and their spectroscopic properties to illustrate the potential of these combined tools. We discuss using them as biomarkers and biosensors and, under the lens of this new technology, identify some of the challenges and potentials for future advances in the field.

Impact of cigarette smoking on fluorescence lifetime of ocular fundus

Cigarette smoking is known to adversely affect cellular metabolism and is a risk factor for various retinal diseases. Fluorescence lifetime imaging ophthalmoscopy (FLIO) has the potential to detect metabolic changes in the ocular fundus. Aim of this study was to analyze the influence of cigarette smoking on fluorescence lifetime (FLT) of healthy eyes using FLIO. Twenty-six non-smokers and 28 smokers aged between 20 and 37 years without systemic and ocular diseases were investigated by FLIO (excitation: 473 nm, emission: short spectral channel (SSC) 498-560 nm, long spectral channel (LSC) 560-720 nm). The FLT at the ETDRS grid regions were analyzed and compared. In SSC, the mean FLT (τ_m) of smokers was significantly longer in the ETDRS inner ring region, whereas the τ_m in LSC was significantly shorter in the outer ring. For the long component (τ₂), smokers with pack year < 7.11 showed significantly shorter τ₂ in SSC than non-smokers and the smokers with pack year ≥ 7.11. There were no significant differences in retinal thickness. The lack of obvious structural differences implies that the observed FLT changes are likely related to smoking-induced metabolic changes. These results suggest that FLIO may be useful in assessing retinal conditions related to lifestyle and systemic metabolic status.

Past, present, and future of tools for dopamine detection

Dopamine (DA) is a critical neuromodulator involved in various brain functions. To understand how DA regulates neural circuits and behaviors in the physiological and pathological conditions, it is essential to have tools that enable the direct detection of DA dynamics in vivo. Recently, genetically encoded DA sensors based on G protein-coupled receptors revolutionized this field, as it allows us to track in vivo DA dynamic with unprecedented spatial-temporal resolution, high molecular specificity, and sub-second kinetics. In this review, we first summarize traditional DA detection methods. Then we focus on the development of genetically encoded DA sensors and feature its significance to understanding dopaminergic neuromodulation across diverse behaviors and species. Finally, we present our perspectives about the future direction of the next-generation DA sensors and extend their potential applications. Overall, this review offers a comprehensive perspective on the past, present, and future of DA detection tools, with important implications for the study of DA functions in health and disease.

Comparison of denoising tools for the reconstruction of nonlinear multimodal images

Biophotonic multimodal imaging techniques provide deep insights into biological samples such as cells or tissues. However, the measurement time increases dramatically when high-resolution multimodal images (MM) are required. To address this challenge, mathematical methods can be used to shorten the acquisition time for such high-quality images. In this research, we compared standard methods, e.g., the median filter method and the phase retrieval method via the Gerchberg-Saxton algorithm with artificial intelligence (AI) based methods using MM images of head and neck tissues. The AI methods include two approaches: the first one is a transfer learning-based technique that uses the pre-trained network DnCNN. The second approach is the training of networks using augmented head and neck MM images. In this manner, we compared the Noise2Noise network, the MIRNet network, and our deep learning network namely incSRCNN, which is derived from the super-resolution convolutional neural network and inspired by the inception network. These methods reconstruct improved images using measured low-quality (LQ) images, which were measured in approximately 2 seconds. The evaluation was performed on artificial LQ images generated by degrading high-quality (HQ) images measured in 8 seconds using Poisson noise. The results showed the potential of using deep learning on these multimodal images to improve the data quality and reduce the acquisition time. Our proposed network has the advantage of having a simple architecture compared with similar-performing but highly parametrized networks DnCNN, MIRNet, and Noise2Noise.