Fluorescence microscopy is a core biomedical imaging tool that provides high-resolution images of molecular contrast in living samples. Stokes coined the term “fluorescence” in 1852 for the “remarkable phenomena of light” observed in the materials that emitted light at a different color than the absorbed light.¹ At that time, refraction (or refrangibility), internal dispersion, circular dichroism, and other phenomena of light were well studied. Stokes examined flower petals, leaves, turmeric, calcium fluoride, and many other compounds. In the 20th century, fluorescence was redefined as a short-lived emission of photons caused by the incidence of higher energy photons and became a popular tool for studying molecular dynamics and characterizing compounds.

There is a growing interest in developing microphysiological systems that can be used to model both normal and pathological human organs in vitro. This “organs-on-chips” approach aims to capture key structural and physiological characteristics of the target tissue. Here we describe in vitro vascularized microtumors (VMTs). This “tumor-on-a-chip” platform incorporates human tumor and stromal cells that grow in a 3D extracellular matrix and that depend for survival on nutrient delivery through living, perfused microvessels. Both colorectal and breast cancer cells grow vigorously in the platform and respond to standard-of-care therapies, showing reduced growth and/or regression. Vascular-targeting agents with different mechanisms of action can also be distinguished, and we find that drugs targeting only VEGFRs (Apatinib and Vandetanib) are not effective, whereas drugs that target VEGFRs, PDGFR and Tie2 (Linifanib and Cabozantinib) do regress the vasculature. Tumors in the VMT show strong metabolic heterogeneity when imaged using NADH Fluorescent Lifetime Imaging Microscopy and, compared to their surrounding stroma, many show a higher free/bound NADH ratio consistent with their known preference for aerobic glycolysis. The VMT platform provides a unique model for studying vascularized solid tumors in vitro.

Presence of reactive oxygen species (ROS) in excess of normal physiological level results in oxidative stress. This can lead to a range of pathological conditions including inflammation, diabetes mellitus, cancer, cardiovascular and neurodegenerative disease. Biomarkers of oxidative stress play an important role in understanding the pathogenesis and treatment of these diseases. A number of fluorescent biomarkers exist. However, a non-invasive and label-free identification technique would be advantageous for in vivo measurements. In this work we establish a spectroscopic method to identify oxidative stress in cells and tissues by fluorescence lifetime imaging (FLIM). We identified an autofluorescent, endogenous species with a characteristic fluorescent lifetime distribution as a probe for oxidative stress. To corroborate our hypothesis that these species are products of lipid oxidation by ROS, we correlate the spectroscopic signals arising from lipid droplets by combining FLIM with THG and CARS microscopy which are established techniques for selective lipid body imaging. Further, we performed spontaneous Raman spectral analysis at single points of the sample which provided molecular vibration information characteristics of lipid droplets.

The majority of cancer cells have a unique metabolic requirement for methionine that is not observed in normal, non-tumorigenic cells. This phenotype is described as “methionine dependence” or “methionine stress sensitivity” in which cancer cells are unable to proliferate when methionine has been replaced with its metabolic precursor, homocysteine, in cell culture growth media. We focus on the metabolic response to methionine stress in the triple negative breast cancer cell line MDA-MB-468 and its methionine insensitive derivative cell line MDA-MB-468res-R8. Using a variety of techniques including fluorescence lifetime imaging microscopy (FLIM) and extracellular flux assays, we identified a metabolic down-regulation of oxidative phosphorylation in both MDA-MB-468 and MDA-MB-468res-R8 cell types when cultured in homocysteine media. Untargeted metabolomics was performed by way of gas chromatography/time-of-flight mass spectrometry on both cell types cultured in homocysteine media over a period of 2 to 24 h. We determined unique metabolic responses between the two cell lines in specific pathways including methionine salvage, purine/pyrimidine synthesis, and the tricarboxylic acid cycle. Stable isotope tracer studies using deuterium-labeled homocysteine indicated a redirection of homocysteine metabolism toward the transsulfuration pathway and glutathione synthesis. This data corroborates with increased glutathione levels concomitant with increased levels of oxidized glutathione. Redirection of homocysteine flux resulted in reduced generation of methionine from homocysteine particularly in MDA-MB-468 cells. Consequently, synthesis of the important one-carbon donor S-adenosylmethionine (SAM) was decreased, perturbing the SAM to S-adenosylhomocysteine ratio in MDA-MB-468 cells, which is an indicator of the cellular methylation potential. This study indicates a differential metabolic response between the methionine sensitive MDA-MB-468 cells and the methionine insensitive derivative cell line MDA-MB-468res-R8. Both cell lines appear to experience oxidative stress when methionine was replaced with its metabolic precursor homocysteine, forcing cells to redirect homocysteine metabolism toward the transsulfuration pathway to increase glutathione synthesis. The methionine stress resistant MDA-MB-468res-R8 cells responded to this cellular stress earlier than the methionine stress sensitive MDA-MB468 cells and coped better with metabolic demands. Additionally, it is evident that S-adenosylmethionine metabolism is dependent on methionine availability in cancer cells, which cannot be sufficiently supplied by homocysteine metabolism under these conditions.

Macrophages adopt a variety of phenotypes that are a reflection of the many functions they perform as part of the immune system. In particular, metabolism is a phenotypic trait that differs between classically activated, proinflammatory macrophages, and alternatively activated, prohealing macrophages. Inflammatory macrophages have a metabolism based on glycolysis while alternatively activated macrophages generally rely on oxidative phosphorylation to generate chemical energy. We employ this shift in metabolism as an endogenous marker to identify the phenotype of individual macrophages via live-cell fluorescence lifetime imaging microscopy (FLIM). We demonstrate that polarized macrophages can be readily discriminated with the aid of a phasor approach to FLIM, which provides a fast and model-free method for analyzing fluorescence lifetime images.

The fluorescence lifetime is the average time that a fluorophore remains in an excited state before returning to the ground state and emitting a photon. The fluorescence lifetime is sensitive to the environment of the fluorophore, including pH, temperature, viscosity, and binding state. Fluorescence lifetime imaging microscopy (FLIM) provides information on molecular interactions that are advantageous for biological and medical imaging. FLIM captures the decay time of fluorophores at each pixel of the image, and therefore, provides unique information compared to intensity (photon flux) or spectral (photon wavelength or energy) imaging of fluorescence. Unlike intensity-based measurements, lifetime is self-referenced and independent of the absolute number of photons. Therefore, FLIM is not corrupted by variations in intensity between pixels. Our previous review covered the fundamentals of FLIM instrumentation and analysis, along with applications to live cell and tissue imaging.¹ The goal of this perspective paper is to provide updates of innovations in FLIM which we, as experts in the field, found impactful within the last year. These new developments have been categorized into advances in instrumentation, new approaches to FLIM data analysis, and recent applications of FLIM in biology and medicine. The developments covered in this perspective are not exhaustive and innovations in FLIM instrumentation, analysis, and applications are ongoing. For a more comprehensive review on FLIM, readers are encouraged to refer to other publications.^{1 – 5}