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Toxoplasma gondii, the causative agent of toxoplasmosis, is an obligate intracellular parasite that infects warm-blooded vertebrates across the world. In humans, seropositivity rates of T. gondii range from 10% to 90% across communities. Despite its prevalence, few studies address how T. gondii infection changes the metabolism of host cells. In this study, we investigate how T. gondii manipulates the host cell metabolic environment by monitoring the metabolic response over time using noninvasive autofluorescence lifetime imaging of single cells, metabolite analysis, extracellular flux analysis, and reactive oxygen species (ROS) production. Autofluorescence lifetime imaging indicates that infected host cells become more oxidized and have an increased proportion of bound NAD(P)H compared to uninfected controls. Over time, infected cells also show decreases in levels of intracellular glucose and lactate, increases in oxygen consumption, and variability in ROS production. We further examined changes associated with the pre-invasion "kiss and spit" process using autofluorescence lifetime imaging, which also showed a more oxidized host cell with an increased proportion of bound NAD(P)H over 48 hours compared to uninfected controls, suggesting that metabolic changes in host cells are induced by T. gondii kiss and spit even without invasion.IMPORTANCEThis study sheds light on previously unexplored changes in host cell metabolism induced by T. gondii infection using noninvasive, label-free autofluorescence imaging. In this study, we use optical metabolic imaging (OMI) to measure the optical redox ratio (ORR) in conjunction with fluorescence lifetime imaging microscopy (FLIM) to noninvasively monitor single host cell response to T. gondii infection over 48 hours. Collectively, our results affirm the value of using autofluorescence lifetime imaging to noninvasively monitor metabolic changes in host cells over the time course of a microbial infection. Understanding this metabolic relationship between the host cell and the parasite could uncover new treatment and prevention options for T. gondii infections worldwide., Competing Interests: The authors declare no conflict of interest.

The function of a T cell depends on its subtype and activation state. Here, we show that imaging of the autofluorescence lifetime signals of quiescent and activated T cells can be used to classify the cells. T cells isolated from human peripheral blood and activated in culture using tetrameric antibodies against the surface ligands CD2, CD3 and CD28 showed specific activation-state-dependent patterns of autofluorescence lifetime. Logistic regression models and random forest models classified T cells according to activation state with 97-99% accuracy, and according to activation state (quiescent or activated) and subtype (CD3 + CD8 + or CD3 + CD4 + ) with 97% accuracy. Autofluorescence lifetime imaging can be used to non-destructively determine T-cell function.

Macrophages within the tumor microenvironment (TME) exhibit a spectrum of protumor and antitumor functions, yet it is unclear how the TME regulates this macrophage heterogeneity. Standard methods to measure macrophage heterogeneity require destructive processing, limiting spatiotemporal studies of function within the live, intact 3D TME. Here, we demonstrate two-photon autofluorescence imaging of NAD(P)H and FAD to nondestructively resolve spatiotemporal metabolic heterogeneity of individual macrophages within 3D microscale TME models. Fluorescence lifetimes and intensities of NAD(P)H and FAD were acquired at 24, 48, and 72 hours poststimulation for mouse macrophages (RAW264.7) stimulated with IFNγ or IL4 plus IL13 in 2D culture, confirming that autofluorescence measurements capture known metabolic phenotypes. To quantify metabolic dynamics of macrophages within the TME, mouse macrophages or human monocytes (RAW264.7 or THP-1) were cultured alone or with breast cancer cells (mouse polyoma-middle T virus or primary human IDC) in 3D microfluidic platforms. Human monocytes and mouse macrophages in tumor cocultures exhibited significantly different FAD mean lifetimes and greater migration than monocultures at 24, 48, and 72 hours postseeding. In cocultures with primary human cancer cells, actively migrating monocyte-derived macrophages had greater redox ratios [NAD(P)H/FAD intensity] compared with passively migrating monocytes at 24 and 48 hours postseeding, reflecting metabolic heterogeneity in this subpopulation of monocytes. Genetic analyses further confirmed this metabolic heterogeneity. These results establish label-free autofluorescence imaging to quantify dynamic metabolism, polarization, and migration of macrophages at single-cell resolution within 3D microscale models. This combined culture and imaging system provides unique insights into spatiotemporal tumor-immune cross-talk within the 3D TME. SIGNIFICANCE: Label-free metabolic imaging and microscale culture technologies enable monitoring of single-cell macrophage metabolism, migration, and function in the 3D tumor microenvironment., (©2020 American Association for Cancer Research.)

The goal of this study is to validate fluorescence intensity and lifetime imaging of metabolic co-enzymes NAD(P)H and FAD (optical metabolic imaging, or OMI) as a method to quantify cell-cycle status of tumor cells. Heterogeneity in tumor cell-cycle status (e. g. proliferation, quiescence, apoptosis) increases drug resistance and tumor recurrence. Cell-cycle status is closely linked to cellular metabolism. Thus, this study applies cell-level metabolic imaging to distinguish proliferating, quiescent, and apoptotic populations. Two-photon microscopy and time-correlated single photon counting are used to measure optical redox ratio (NAD(P)H fluorescence intensity divided by FAD intensity), NAD(P)H and FAD fluorescence lifetime parameters. Redox ratio, NAD(P)H and FAD lifetime parameters alone exhibit significant differences (p<0.05) between population means. To improve separation between populations, linear combination models derived from partial least squares - discriminant analysis (PLS-DA) are used to exploit all measurements together. Leave-one-out cross validation of the model yielded high classification accuracies (92.4 and 90.1 % for two and three populations, respectively). OMI and PLS-DA also identifies each sub-population within heterogeneous samples. These results establish single-cell analysis with OMI and PLS-DA as a label-free method to distinguish cell-cycle status within intact samples. This approach could be used to incorporate cell-level tumor heterogeneity in cancer drug development., (© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Primary tumor organoids are a robust model of individual human cancers and present a unique platform for patient-specific drug testing. Optical imaging is uniquely suited to assess organoid function and behavior because of its subcellular resolution, penetration depth through the entire organoid, and functional endpoints. Specifically, optical metabolic imaging (OMI) is highly sensitive to drug response in organoids, and OMI in tumor organoids correlates with primary tumor drug response. Therefore, an OMI organoid drug screen could enable accurate testing of drug response for individualized cancer treatment. The objective of this perspective is to introduce OMI and tumor organoids to a general audience in order to foster the adoption of these techniques in diverse clinical and laboratory settings., (© 2017 by the Society of Nuclear Medicine and Molecular Imaging.)

Head and neck cancer patients suffer from toxicities, morbidities, and mortalities, and these ailments could be minimized through improved therapies. Drug discovery is a long, expensive, and complex process, so optimized assays can improve the success rate of drug candidates. This study applies optical imaging of cell metabolism to three-dimensional in vitro cultures of head and neck cancer grown from primary tumor tissue (organoids). This technique is advantageous because it measures cell metabolism using intrinsic fluorescence from NAD(P)H and FAD on a single cell level for a three-dimensional in vitro model. Head and neck cancer organoids are characterized alone and after treatment with standard therapies, including an antibody therapy, a chemotherapy, and combination therapy. Additionally, organoid cellular heterogeneity is analyzed quantitatively and qualitatively. Gold standard measures of treatment response, including cell proliferation, cell death, and in vivo tumor volume, validate therapeutic efficacy for each treatment group in a parallel study. Results indicate that optical metabolic imaging is sensitive to therapeutic response in organoids after 1 day of treatment (p<0.05) and resolves cell subpopulations with distinct metabolic phenotypes. Ultimately, this platform could provide a sensitive high-throughput assay to streamline the drug discovery process for head and neck cancer., Competing Interests: The authors have declared that no competing interests exist.

Objectives: Three-dimensional organoids derived from primary pancreatic ductal adenocarcinomas are an attractive platform for testing potential anticancer drugs on patient-specific tissue. Optical metabolic imaging (OMI) is a novel tool used to assess drug-induced changes in cellular metabolism, and its quantitative end point, the OMI index, is evaluated as a biomarker of drug response in pancreatic cancer organoids., Methods: Optical metabolic imaging is used to assess both malignant cell and fibroblast drug response within primary murine and human pancreatic cancer organoids., Results: Anticancer drugs induce significant reductions in the OMI index of murine and human pancreatic cancer organoids. Subpopulation analysis of OMI data revealed heterogeneous drug response and elucidated responding and nonresponding cell populations for a 7-day time course. Optical metabolic imaging index significantly correlates with immunofluorescence detection of cell proliferation and cell death., Conclusions: Optical metabolic imaging of primary pancreatic ductal adenocarcinoma organoids is highly sensitive to drug-induced metabolic changes, provides a nondestructive method for monitoring dynamic drug response, and presents a novel platform for patient-specific drug testing and drug development.

There is a need for accurate, high-throughput, functional measures to gauge the efficacy of potential drugs in living cells. As an early marker of drug response in cells, cellular metabolism provides an attractive platform for high-throughput drug testing. Optical techniques can noninvasively monitor NADH and FAD, two autofluorescent metabolic coenzymes. The autofluorescent redox ratio, defined as the autofluorescence intensity of NADH divided by that of FAD, quantifies relative rates of cellular glycolysis and oxidative phosphorylation. However, current microscopy methods for redox ratio quantification are time-intensive and low-throughput, limiting their practicality in drug screening. Alternatively, high-throughput commercial microplate readers quickly measure fluorescence intensities for hundreds of wells. This study found that a commercial microplate reader can differentiate the receptor status of breast cancer cell lines (p < 0.05) based on redox ratio measurements without extrinsic contrast agents. Furthermore, microplate reader redox ratio measurements resolve response (p < 0.05) and lack of response (p > 0.05) in cell lines that are responsive and nonresponsive, respectively, to the breast cancer drug trastuzumab. These studies indicate that the microplate readers can be used to measure the redox ratio in a high-throughput manner and are sensitive enough to detect differences in cellular metabolism that are consistent with microscopy results.

Optical metabolic imaging measures fluorescence intensity and lifetimes from metabolic cofactors nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD). These molecular level measurements provide unique biomarkers for early cellular responses to cancer treatments. Head and neck squamous cell carcinoma (HNSCC) is an attractive target for optical imaging because of easy access to the site using fiber optic probes. Two HNSCC cell lines, SCC25 and SCC61, were treated with Cetuximab (anti-EGFR antibody), BGT226 (PI3K/mTOR inhibitor), or cisplatin (chemotherapy) for 24 hours. Results show increased redox ratio, NADH α1 (contribution from free NADH), and FAD α1 (contribution from protein-bound FAD) for malignant cells compared with the nonmalignant cell line OKF6 (p<0.05). In SCC25 and SCC61 cells, the redox ratio is unaffected by cetuximab treatment and decreases with BGT226 and cisplatin treatment (p<0.05), and these results agree with standard measurements of proliferation rates after treatment. For SCC25, NADH α1 is reduced with BGT226 and cisplatin treatment. For SCC61, NADH α1 is reduced with cetuximab, BGT226, and cisplatin treatment. Trends in NADH α1 are statistically similar to changes in standard measurements of glycolytic rates after treatment. FAD α1 is reduced with cisplatin treatment (p<0.05). These shifts in optical endpoints reflect early metabolic changes induced by drug treatment. Overall, these results indicate that optical metabolic imaging has potential to detect early response to cancer treatment in HNSCC, enabling optimal treatment regimens and improved patient outcomes.

Abnormal cellular metabolism is a hallmark of cancer, yet there is an absence of quantitative methods to dynamically image this powerful cellular function. Optical metabolic imaging (OMI) is a noninvasive, high-resolution, quantitative tool for monitoring cellular metabolism. OMI probes the fluorescence intensities and lifetimes of the autofluorescent metabolic coenzymes reduced NADH and flavin adenine dinucleotide. We confirm that OMI correlates with cellular glycolytic levels across a panel of human breast cell lines using standard assays of cellular rates of glucose uptake and lactate secretion (P < 0.05, r = 0.89). In addition, OMI resolves differences in the basal metabolic activity of untransformed from malignant breast cells (P < 0.05) and between breast cancer subtypes (P < 0.05), defined by estrogen receptor and/or HER2 expression or absence. In vivo OMI is sensitive to metabolic changes induced by inhibition of HER2 with the antibody trastuzumab (herceptin) in HER2-overexpressing human breast cancer xenografts in mice. This response was confirmed with tumor growth curves and stains for Ki67 and cleaved caspase-3. OMI resolved trastuzumab-induced changes in cellular metabolism in vivo as early as 48 hours posttreatment (P < 0.05), whereas fluorodeoxyglucose-positron emission tomography did not resolve any changes with trastuzumab up to 12 days posttreatment (P > 0.05). In addition, OMI resolved cellular subpopulations of differing response in vivo that are critical for investigating drug resistance mechanisms. Importantly, OMI endpoints remained unchanged with trastuzumab treatment in trastuzumab-resistant xenografts (P > 0.05). OMI has significant implications for rapid cellular-level assessment of metabolic response to molecular expression and drug action, which would greatly accelerate drug development studies., (©2013 AACR.)