Autofluorescence Imaging of 3D Tumor-Macrophage Microscale Cultures Resolves Spatial and Temporal Dynamics of Macrophage Metabolism

Endogenous mitochondrial NAD(P)H fluorescence can predict lifespan

Many aging clocks have recently been developed to predict health outcomes and deconvolve heterogeneity in aging. However, existing clocks are limited by technical constraints, such as low spatial resolution, long processing time, sample destruction, and a bias towards specific aging phenotypes. Therefore, here we present a non-destructive, label-free and subcellular resolution approach for quantifying aging through optically resolving age-dependent changes to the biophysical properties of NAD(P)H in mitochondria through fluorescence lifetime imaging (FLIM) of endogenous NAD(P)H fluorescence. We uncover age-dependent changes to mitochondrial NAD(P)H across tissues in C. elegans that are associated with a decline in physiological function and construct non-destructive, label-free and cellular resolution models for prediction of age, which we refer to as "mito-NAD(P)H age clocks." Mito-NAD(P)H age clocks can resolve heterogeneity in the rate of aging across individuals and predict remaining lifespan. Moreover, we spatiotemporally resolve age-dependent changes to mitochondria across and within tissues, revealing multiple modes of asynchrony in aging and show that longevity is associated with a ubiquitous attenuation of these changes. Our data present a high-resolution view of mitochondrial NAD(P)H across aging, providing insights that broaden our understanding of how mitochondria change during aging and approaches which expand the toolkit to quantify aging.

Surface Molecularly Engineered Mitochondria Conduct Immunophenotype Repolarization of Tumor-Associated Macrophages to Potentiate Cancer Immunotherapy

Reprogramming tumor-associated macrophages (TAMs) to an inflammatory phenotype effectively increases the potential of immune checkpoint blockade (ICB) therapy. Artificial mitochondrial transplantation, an emerging and safe strategy, has made brilliant achievements in regulating the function of recipient cells in preclinic and clinic, but its performance in reprogramming the immunophenotype of TAMs has not been reported. Here, the metabolism of M2 TAMs is proposed resetting from oxidative phosphorylation (OXPHOS) to glycolysis for polarizing M1 TAMs through targeted transplantation of mannosylated mitochondria (mPEI/M1mt). Mitochondria isolated from M1 macrophages are coated with mannosylated polyethyleneimine (mPEI) through electrostatic interaction to form mPEI/M1mt, which can be targeted uptake by M2 macrophages expressed a high level of mannose receptors. Mechanistically, mPEI/M1mt accelerates phosphorylation of NF-κB p65, MAPK p38 and JNK by glycolysis-mediated elevation of intracellular ROS, thus prompting M1 macrophage polarization. In vivo, the transplantation of mPEI/M1mt excellently potentiates therapeutic effects of anti-PD-L1 by resetting an antitumor proinflammatory tumor microenvironment and stimulating CD8 and CD4 T cells dependent immune response. Altogether, this work provides a novel platform for improving cancer immunotherapy, meanwhile, broadens the scope of mitochondrial transplantation technology in clinics in the future.

The Use of Patient-Derived Organoids in the Study of Molecular Metabolic Adaptation in Breast Cancer

Around 13% of women will likely develop breast cancer during their lifetime. Advances in cancer metabolism research have identified a range of metabolic reprogramming events, such as altered glucose and amino acid uptake, increased reliance on glycolysis, and interactions with the tumor microenvironment (TME), all of which present new opportunities for targeted therapies. However, studying these metabolic networks is challenging in traditional 2D cell cultures, which often fail to replicate the three-dimensional architecture and dynamic interactions of real tumors. To address this, organoid models have emerged as powerful tools. Tumor organoids are 3D cultures, often derived from patient tissue, that more accurately mimic the structural and functional properties of actual tumor tissues in vivo, offering a more realistic model for investigating cancer metabolism. This review explores the unique metabolic adaptations of breast cancer and discusses how organoid models can provide deeper insights into these processes. We evaluate the most advanced tools for studying cancer metabolism in three-dimensional culture models, including optical metabolic imaging (OMI), matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), and recent advances in conventional techniques applied to 3D cultures. Finally, we explore the progress made in identifying and targeting potential therapeutic targets in breast cancer metabolism.

Evaluation of Cellpose segmentation with sequential thresholding for instance segmentation of cytoplasms within autofluorescence images

BACKGROUND

Autofluorescence imaging of the coenzyme, reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H), provides a label-free technique to assess cellular metabolism. Because NAD(P)H is localized in the cytosol and mitochondria, instance segmentation of cell cytoplasms from NAD(P)H images allows quantification of metabolism with cellular resolution. However, accurate cytoplasmic segmentation of autofluorescence images is difficult due to irregular cell shapes and cell clusters.

METHOD

Here, a cytoplasm segmentation method is presented and tested. First, autofluorescence images are segmented into cells via either hand-segmentation or Cellpose, a deep learning-based segmentation method. Then, a cytoplasmic post-processing algorithm (CPPA) is applied for cytoplasmic segmentation. CPPA uses a binarized segmentation image to remove non-segmented pixels from the NAD(P)H image and then applies an intensity-based threshold to identify nuclei regions. Errors at cell edges are removed using a distance transform algorithm. The nucleus mask is then subtracted from the cell segmented image to yield the cytoplasm mask image. CPPA was tested on five NAD(P)H images of three different cell samples, quiescent T cells, activated T cells, and MCF7 cells.

RESULTS

Using POSEA, an evaluation method tailored for instance segmentation, the CPPA yielded F-measure values of 0.89, 0.87, and 0.94 for quiescent T cells, activated T cells, and MCF7 cells, respectively, for cytoplasm identification of hand-segmented cells. CPPA achieved F-measure values of 0.84, 0.74, and 0.72 for Cellpose segmented cells.

CONCLUSION

These results exceed the F-measure value of a comparative cell segmentation method (CellProfiler, ∼0.50-0.60) and support the use of artificial intelligence and post-processing techniques for accurate segmentation of autofluorescence images for single-cell metabolic analyses.

Imaging immunometabolism in situ in live animals

Immunometabolism is a rapidly developing field that holds great promise for diagnostic and therapeutic benefits to human diseases. The field has emerged based on seminal findings from in vitro and ex vivo studies that established the fundamental role of metabolism in immune cell effector functions. Currently, the field is acknowledging the necessity of investigating cellular metabolism within the natural context of biological processes. Examining cells in their native microenvironment is essential not only to reveal cell-intrinsic mechanisms but also to understand how cross-talk between neighboring cells regulates metabolism at the tissue level in a local niche. This necessity is driving innovation and advancement in multiple imaging-based technologies to enable analysis of dynamic intracellular metabolism at the single-cell level, with spatial and temporal resolution. In this review, we tally the currently available imaging-based technologies and explore the emerging methods of Raman and autofluorescence lifetime imaging microscopy, which hold significant potential and offer broad applications in the field of immunometabolism.

Quantitative Optical Redox Imaging of Melanoma Xenografts with Different Metastatic Potentials

To develop imaging biomarkers for tumors aggressiveness, our previous optical redox imaging (ORI) studies of the reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavoproteins (Fp, containing flavin adenine dinucleotide, i.e., FAD) in tumor xenografts of human melanoma associated the high optical redox ratio (ORR = Fp/(Fp + NADH)) and its heterogeneity to the high invasive/metastatic potential, without having reported quantitative results for NADH and Fp. Here, we implemented a calibration procedure to facilitate imaging the nominal concentrations of tissue NADH and Fp in the mouse xenografts of two human melanoma lines, an indolent less metastatic A375P and a more metastatic C8161. Images of the redox indices (NADH, Fp, ORR) revealed the existence of more oxidized areas (OAs) and more reduced areas (RAs) within individual tumors. ORR was found to be higher and NADH lower in C8161 compared to that of A375P xenografts, both globally for the whole tumors and locally in OAs. The ORR in the OA can differentiate xenografts with a higher statistical significance than the global averaged ORR. H&E staining of the tumors indicated that the redox differences we identified were more likely due to intrinsically different cell metabolism, rather than variations in cell density.

Autofluorescence is a biomarker of neural stem cell activation state

Neural stem cells (NSCs) must exit quiescence to produce neurons; however, our understanding of this process remains constrained by the technical limitations of current technologies. Fluorescence lifetime imaging (FLIM) of autofluorescent metabolic cofactors has been used in other cell types to study shifts in cell states driven by metabolic remodeling that change the optical properties of these endogenous fluorophores. Using this non-destructive, live-cell, and label-free strategy, we found that quiescent NSCs (qNSCs) and activated NSCs (aNSCs) have unique autofluorescence profiles. Specifically, qNSCs display an enrichment of autofluorescence localizing to a subset of lysosomes, which can be used as a graded marker of NSC quiescence to predict cell behavior at single-cell resolution. Coupling autofluorescence imaging with single-cell RNA sequencing, we provide resources revealing transcriptional features linked to deep quiescence and rapid NSC activation. Together, we describe an approach for tracking mouse NSC activation state and expand our understanding of adult neurogenesis.

Live-Cell Imaging Quantifies Changes in Function and Metabolic NADH Autofluorescence During Macrophage-Mediated Phagocytosis of Tumor Cells

BACKGROUND

The immune system has evolved to detect foreign antigens and deliver coordinated responses, while minimizing "friendly fire." Until recently, studies investigating the behavior of immune cells were limited to static in vitro measurements. Although static measurements allow for real-time imaging, results are often difficult to translate to an in vivo setting. Multiphoton microscopy is an emerging method to capture spatial information on subcellular events and characterize the local microenvironment. Previous studies have shown that multiphoton microscopy can monitor changes in single-cell macrophage heterogeneity during differentiation. Therefore, there is a need to use multiphoton microscopy to monitor molecular interactions during immunological activities like phagocytosis. Here we investigate the correlation between phagocytic function and changes in endogenous optical reporters during phagocytosis.

METHODS

In vitro autofluorescence imaging of nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) was used to detect metabolic changes in macrophages during phagocytosis. More specifically, optical redox ratio, mean NADH fluorescence lifetime and ratio of free to protein-bound NADH were used to quantify changes in metabolism.

RESULTS

Results show that IFN-γ (M1) macrophages showed decreased optical redox ratios and mean NADH lifetime while phagocytosing immunogenic cancer cells compared to metastatic cells. To validate phagocytic function, a fluorescence microscopy-based protocol using a pH-sensitive fluorescent probe was used. Results indicate that M0 and M1 macrophages show similar trends in phagocytic potential.

CONCLUSION

Overall, this work demonstrates that in vitro multiphoton imaging can be used to longitudinally track changes in phagocytosis and endogenous metabolic cofactors.

Extracellular vesicles associated microRNAs: Their biology and clinical significance as biomarkers in gastrointestinal cancers

Gastrointestinal (GI) cancers, including colorectal, gastric, esophageal, pancreatic, and liver, are associated with high mortality and morbidity rates worldwide. One of the underlying reasons for the poor survival outcomes in patients with these malignancies is late disease detection, typically when the tumor has already advanced and potentially spread to distant organs. Increasing evidence indicates that earlier detection of these cancers is associated with improved survival outcomes and, in some cases, allows curative treatments. Consequently, there is a growing interest in the development of molecular biomarkers that offer promise for screening, diagnosis, treatment selection, response assessment, and predicting the prognosis of these cancers. Extracellular vesicles (EVs) are membranous vesicles released from cells containing a repertoire of biological molecules, including nucleic acids, proteins, lipids, and carbohydrates. MicroRNAs (miRNAs) are the most extensively studied non-coding RNAs, and the deregulation of miRNA levels is a feature of cancer cells. EVs miRNAs can serve as messengers for facilitating interactions between tumor cells and the cellular milieu, including immune cells, endothelial cells, and other tumor cells. Furthermore, recent years have witnessed considerable technological advances that have permitted in-depth sequence profiling of these small non-coding RNAs within EVs for their development as promising cancer biomarkers -particularly non-invasive, liquid biopsy markers in various cancers, including GI cancers. Herein, we summarize and discuss the roles of EV-associated miRNAs as they play a seminal role in GI cancer progression, as well as their promising translational and clinical potential as cancer biomarkers as we usher into the area of precision oncology.

3D Coculture between Cancer Cells and Macrophages: From Conception to Experimentation

A tumor is a complex cluster with many types of cells in the microenvironment that help it grow. Macrophages, immune cells whose main role is to maintain body homeostasis, represent in the majority of cancers the most important cell population. In this context, they are called tumor-associated macrophages (TAMs) because of their phenotype, which contributes to tumor growth. In order to limit the use of animals, there is a real demand for the creation of in vitro models able to represent more specifically the complexity of the tumor microenvironment (TME) in order to characterize it and evaluate new treatments. However, the two-dimensional (2D) culture, which has been used for a long time, has shown many limitations, especially in terms of tumor representation. The three-dimensional (3D) models, developed over the last 20 years, have made it possible to get closer to what happens in vivo in terms of phenotypic and functional characteristics. Due to their architectural similarity to in vivo tissues, they provide a more physiologically relevant in vitro system. Most recently, it is the development of 3D coculture models in which two or three cell lines are cultured together that has allowed a better representation of TME with cell-cell interactions. Unfortunately, there is no clear direction for the design of these models at this time. In this Review on the coculture between cancer cells and TAMs, an in-depth analysis is performed to answer multiple questions on the conception of these models: Which models to use, and with which material and cancer lineage? Which monocyte or macrophage lines should be added to the coculture? And how can these models be exploited?

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.

Perfusability and immunogenicity of implantable pre-vascularized tissues recapitulating features of native capillary network

Vascularization is a key pre-requisite to engineered anatomical scale three dimensional (3-D) constructs to ensure their nutrient and oxygen supply upon implantation. Presently, engineered pre-vascularized 3-D tissues are limited to only micro-scale hydrogels, which meet neither the anatomical scale needs nor the complexity of natural extracellular matrix (ECM) environments. Anatomical scale perfusable constructs are critically needed for translational applications. To overcome this challenge, we previously developed pre-vascularized ECM sheets with long and oriented dense microvascular networks. The present study further evaluated the patency, perfusability and innate immune response toward these pre-vascularized constructs. Macrophage-co-cultured pre-vascularized constructs were evaluated in vitro to confirm micro-vessel patency and perturbations in macrophage metabolism. Subcutaneously implanted pre-vascularized constructs remained viable and formed a functional anastomosis with host vasculature within 3 days of implantation. This completely biological pre-vascularized construct holds great potential as a building block to engineer perfusable anatomical scale tissues.

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.

Comparison of phasor analysis and biexponential decay curve fitting of autofluorescence lifetime imaging data for machine learning prediction of cellular phenotypes

Introduction: Autofluorescence imaging of the coenzymes reduced nicotinamide (phosphate) dinucleotide (NAD(P)H) and oxidized flavin adenine dinucleotide (FAD) provides a label-free method to detect cellular metabolism and phenotypes. Time-domain fluorescence lifetime data can be analyzed by exponential decay fitting to extract fluorescence lifetimes or by a fit-free phasor transformation to compute phasor coordinates. Methods: Here, fluorescence lifetime data analysis by biexponential decay curve fitting is compared with phasor coordinate analysis as input data to machine learning models to predict cell phenotypes. Glycolysis and oxidative phosphorylation of MCF7 breast cancer cells were chemically inhibited with 2-deoxy-d-glucose and sodium cyanide, respectively; and fluorescence lifetime images of NAD(P)H and FAD were obtained using a multiphoton microscope. Results: Machine learning algorithms built from either the extracted lifetime values or phasor coordinates predict MCF7 metabolism with a high accuracy (∼88%). Similarly, fluorescence lifetime images of M0, M1, and M2 macrophages were acquired and analyzed by decay fitting and phasor analysis. Machine learning models trained with features from curve fitting discriminate different macrophage phenotypes with improved performance over models trained using only phasor coordinates. Discussion: Altogether, the results demonstrate that both curve fitting and phasor analysis of autofluorescence lifetime images can be used in machine learning models for classification of cell phenotype from the lifetime data.

Label-free optical metabolic imaging of adipose tissues for prediabetes diagnosis

Rationale: Prediabetes can be reversed through lifestyle intervention, but its main pathologic hallmark, insulin resistance (IR), cannot be detected as conveniently as blood glucose testing. In consequence, the diagnosis of prediabetes is often delayed until patients have hyperglycemia. Therefore, developing a less invasive diagnostic method for rapid IR evaluation will contribute to the prognosis of prediabetes. Adipose tissue is an endocrine organ that plays a crucial role in the development and progression of prediabetes. Label-free visualizing the prediabetic microenvironment of adipose tissues provides a less invasive alternative for the characterization of IR and inflammatory pathology. Methods: Here, we successfully identified the differentiable features of prediabetic adipose tissues by employing the metabolic imaging of three endogenous fluorophores NAD(P)H, FAD, and lipofuscin-like pigments. Results: We discovered that 1040-nm excited lipofuscin-like autofluorescence could mark the location of macrophages. This unique feature helps separate the metabolic fluorescence signals of macrophages from those of adipocytes. In prediabetes fat tissues with IR, we found only adipocytes exhibited a low redox ratio of metabolic fluorescence and high free NAD(P)H fraction a₁. This differential signature disappears for mice who quit the high-fat diet or high-fat-high-sucrose diet and recover from IR. When mice have diabetic hyperglycemia and inflamed fat tissues, both adipocytes and macrophages possess this kind of metabolic change. As confirmed with RNA-seq analysis and histopathology evidence, the change in adipocyte's metabolic fluorescence could be an indicator or risk factor of prediabetic IR. Conclusion: Our study provides an innovative approach to diagnosing prediabetes, which sheds light on the strategy for diabetes prevention.

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

Significance

Fluorescence lifetime imaging microscopy (FLIM) of the metabolic co-enzyme nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] is a popular method to monitor single-cell metabolism within unperturbed, living 3D systems. However, FLIM of NAD(P)H has not been performed in a light-sheet geometry, which is advantageous for rapid imaging of cells within live 3D samples.

Aim

We aim to design, validate, and demonstrate a proof-of-concept light-sheet system for NAD(P)H FLIM.

Approach

A single-photon avalanche diode camera was integrated into a light-sheet microscope to achieve optical sectioning and limit out-of-focus contributions for NAD(P)H FLIM of single cells.

Results

An NAD(P)H light-sheet FLIM system was built and validated with fluorescence lifetime standards and with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times. NAD(P)H light-sheet FLIM in vivo was demonstrated with live neutrophil imaging in a larval zebrafish tail wound also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light-sheet geometries, indicating a 30 × to 6 × acquisition speed advantage for the light sheet compared to the laser scanning geometry.

Conclusions

FLIM of NAD(P)H is feasible in a light-sheet geometry and is attractive for 3D live cell imaging applications, such as monitoring immune cell metabolism and migration within an organism.

Fluorescence Lifetime Imaging of NAD(P)H T Cells Autofluorescence in the Lymphatic Nodes to Assess the Effectiveness of Anti-CTLA-4 Immunotherapy

The main problem in the field of tumor immunotherapy is the lack of reliable biomarkers that allow pre-determining the susceptibility of individual patients to treatment, as well as insufficient knowledge about the resistance mechanisms. Biomarkers based on the autofluorescence of metabolic coenzymes in immune cells can become a powerful new predictor of early tumor response to treatment, whereas the optical FLIM method can be a tool to predict the effectiveness of immunotherapy, which allows preserving the spatial structure of the sample and obtaining results on the metabolic status of immune cells in real time. The aim of the study is to conduct a metabolic autofluorescence imaging study of the NAD(P)H metabolic coenzyme in immune cells of freshly isolated lymph nodes as a potential marker for assessing the effectiveness of an early response to immunotherapy.

Materials and Methods

The study was carried out on C57Bl/6 FoxP3-EGFP mice with B16F0 melanoma implanted near the inguinal lymph node. The mice were injected with antibodies to CTLA-4 (Bio X Cell, USA) (250 μg per mouse, intraperitoneally on days 7, 8, 11, and 12 of the tumor growth). FLIM images in the nicotinamide adenine dinucleotide (phosphate) coenzyme (NAD(P)H) channel (excitation - 375 nm, reception - 435-485 nm) were received using an LSM 880 fluorescent confocal laser scanning microscope (Carl Zeiss, Germany) equipped with a FLIM Simple-Tau module 152 TCSPC (Becker & Hickl GmbH, Germany). Flow cytometry was conducted using a BD FACSAria III cell sorter (BD Biosciences, USA).

Results

Immunotherapy with checkpoint inhibitors resulted in marked metabolic rearrangements in T cells of freshly isolated lymph nodes in responder mice, with inhibition of the tumor growth. Fluorescence lifetime imaging data on NAD(P)H indicated an increase in the free fraction of NADH α1, a form associated with glycolysis to meet high demands of the activated T cells and pro-inflammatory cytokine synthesis. In contrast, non-responder mice with advanced tumors showed low values of the ratio of free fraction to bound α1/α2, which may be related to mechanisms of resistance to therapy.The response to immunotherapy was verified by data on the expression of activation and proliferation markers by means of flow cytometry. The authors observed an increase in the production of the pro-inflammatory cytokine IFN-γ in effector T cells in responder mice compared to untreated controls and non-responders. In addition, an increase in the expression of the surface activation markers CD25 and CD69 was registered compared to untreated controls.

Conclusion

Use of the FLIM method allowed to demonstrate that autofluorescence of the NAD(P)H coenzyme is sensitive to the response to checkpoint immunotherapy and can be used as a reliable marker of the effectiveness of response to treatment.

Label-free optical imaging of cell function and collagen structure for cell-based therapies

Cell-based therapies harness functional cells or tissues to mediate healing and treat disease. Assessment of cellular therapeutics requires methods that are non-destructive to ensure therapies remain viable and uncontaminated for use in patients. Optical imaging of endogenous collagen, by second-harmonic generation, and the metabolic coenzymes NADH and FAD, by autofluorescence microscopy, provides tissue structure and cellular information. Here, we review applications of label-free nonlinear optical imaging of cellular metabolism and collagen second-harmonic generation for assessing cell-based therapies. Additionally, we discuss the potential of label-free imaging for quality control of cell-based therapies, as well as the current limitations and potential future directions of label-free imaging technologies.

FLIM of NAD(P)H in Lymphatic Nodes Resolves T-Cell Immune Response to the Tumor

Assessment of T-cell response to the tumor is important for diagnosis of the disease and monitoring of therapeutic efficacy. For this, new non-destructive label-free methods are required. Fluorescence lifetime imaging (FLIM) of metabolic coenzymes is a promising innovative technology for the assessment of the functional status of cells. The purpose of this work was to test whether FLIM can resolve metabolic alterations that accompany T-cell reactivation to the tumors. The study was carried out on C57Bl/6 FoxP3-EGFP mice bearing B16F0 melanoma. Autofluorescence of the immune cells in fresh lymphatic nodes (LNs) was investigated. It was found that fluorescence lifetime parameters of nicotinamide adenine dinucleotide (phosphate) NAD(P)H are sensitive to tumor development. Effector T-cells in the LNs displayed higher contribution of free NADH, the form associated with glycolysis, in all tumors and the presence of protein-bound NADPH, associated with biosynthetic processes, in the tumors of large size. Flow cytometry showed that the changes in the NADH fraction of the effector T-cells correlated with their activation, while changes in NADPH correlated with cell proliferation. In conclusion, FLIM of NAD(P)H in fresh lymphoid tissue is a powerful tool for assessing the immune response to tumor development.

Interactions with stromal cells promote a more oxidized cancer cell redox state in pancreatic tumors

Access to electron acceptors supports oxidized biomass synthesis and can be limiting for cancer cell proliferation, but how cancer cells overcome this limitation in tumors is incompletely understood. Nontransformed cells in tumors can help cancer cells overcome metabolic limitations, particularly in pancreatic cancer, where pancreatic stellate cells (PSCs) promote cancer cell proliferation and tumor growth. However, whether PSCs affect the redox state of cancer cells is not known. By taking advantage of the endogenous fluorescence properties of reduced nicotinamide adenine dinucleotide and oxidized flavin adenine dinucleotide cofactors we use optical imaging to assess the redox state of pancreatic cancer cells and PSCs and find that direct interactions between PSCs and cancer cells promote a more oxidized state in cancer cells. This suggests that metabolic interaction between cancer cells and PSCs is a mechanism to overcome the redox limitations of cell proliferation in pancreatic cancer.

Metabolic Regulation of Inflammation and Its Resolution: Current Status, Clinical Needs, Challenges, and Opportunities

Metabolism and inflammation have been viewed as two separate processes with distinct but critical functions for our survival: metabolism regulates the utilization of nutrients, and inflammation is responsible for defense and repair. Both respond to an organism's stressors to restore homeostasis. The interplay between metabolic status and immune response (immunometabolism) plays an important role in maintaining health or promoting disease development. Understanding these interactions is critical in developing tools for facilitating novel preventative and therapeutic approaches for diseases, including cancer. This trans-National Institutes of Health workshop brought together basic scientists, technology developers, and clinicians to discuss state-of-the-art, innovative approaches, challenges, and opportunities to understand and harness immunometabolism in modulating inflammation and its resolution.

The Oncogenic Role and Immune Infiltration for CARM1 Identified by Pancancer Analysis

Chromatin-modifying enzymes, especially protein arginine methyltransferases (PRMTs), have been identified as candidate targets for cancer. Cellular or animal-based evidence has suggested an association between coactivator-linked arginine methyltransferase 1 (CARM1) and cancer progression. However, the relationship between CARM1 and patient prognosis and immune infiltration in pancancer patients is unknown. On the basis of the GEO and TCGA databases, we first investigated the possible oncogenic functions of CARM1 in thirty-three tumor types. CARM1 expression was elevated in many types of tumors. In addition, there was a significant association between CARM1 expression and the survival rate of tumor patients. Uterine corpus endometrial carcinoma (UCES) samples had the highest CARM1 mutation frequency of all cancer types. In head and neck squamous cell carcinoma (HNSC) and lung squamous cell carcinoma (LUSC), CARM1 expression was associated with the level of CD8+ T cell infiltration, and cancer-associated fibroblast infiltration was also observed in other tumors including kidney renal papillary cell carcinoma (KIRC) and prostate adenocarcinoma (PRAD). CARM1 was involved in immune modulation and played an important role in the tumor microenvironment (TME). Furthermore, activities associated with RNA transport and its metabolism were included in the possible mechanisms of CARM1. Herein, our first pancancer research explores the oncogenic role of CARM1 in various tumors. CARM1 is associated with immune infiltrates and can be employed as a predictive biomarker in pancancer.

Luminescence lifetime imaging of three-dimensional biological objects

A major focus of current biological studies is to fill the knowledge gaps between cell, tissue and organism scales. To this end, a wide array of contemporary optical analytical tools enable multiparameter quantitative imaging of live and fixed cells, three-dimensional (3D) systems, tissues, organs and organisms in the context of their complex spatiotemporal biological and molecular features. In particular, the modalities of luminescence lifetime imaging, comprising fluorescence lifetime imaging (FLI) and phosphorescence lifetime imaging microscopy (PLIM), in synergy with Förster resonance energy transfer (FRET) assays, provide a wealth of information. On the application side, the luminescence lifetime of endogenous molecules inside cells and tissues, overexpressed fluorescent protein fusion biosensor constructs or probes delivered externally provide molecular insights at multiple scales into protein-protein interaction networks, cellular metabolism, dynamics of molecular oxygen and hypoxia, physiologically important ions, and other physical and physiological parameters. Luminescence lifetime imaging offers a unique window into the physiological and structural environment of cells and tissues, enabling a new level of functional and molecular analysis in addition to providing 3D spatially resolved and longitudinal measurements that can range from microscopic to macroscopic scale. We provide an overview of luminescence lifetime imaging and summarize key biological applications from cells and tissues to organisms.

Intravital Metabolic Autofluorescence Imaging Captures Macrophage Heterogeneity Across Normal and Cancerous Tissue

Macrophages are dynamic immune cells that govern both normal tissue function and disease progression. However, standard methods to measure heterogeneity in macrophage function within tissues require tissue excision and fixation, which limits our understanding of diverse macrophage function in vivo. Two-photon microscopy of the endogenous metabolic co-enzymes NAD(P)H and flavin adenine dinucleotide (FAD) (metabolic autofluorescence imaging) enables dynamic imaging of mouse models in vivo. Here, we demonstrate metabolic autofluorescence imaging to assess cell-level macrophage heterogeneity in response to normal and cancerous tissue microenvironments in vivo. NAD(P)H and FAD fluorescence intensities and lifetimes were measured for both tissue-resident macrophages in mouse ear dermis and tumor-associated macrophages in pancreatic flank tumors. Metabolic and spatial organization of macrophages were determined by performing metabolic autofluorescence imaging and single macrophage segmentation in mice engineered for macrophage-specific fluorescent protein expression. Tumor-associated macrophages exhibited decreased optical redox ratio [NAD(P)H divided by FAD intensity] compared to dermal macrophages, indicating that tumor-associated macrophages are more oxidized than dermal macrophages. The mean fluorescence lifetimes of NAD(P)H and FAD were longer in dermal macrophages than in tumor-associated macrophages, which reflects changes in NAD(P)H and FAD protein-binding activities. Dermal macrophages had greater heterogeneity in optical redox ratio, NAD(P)H mean lifetime, and FAD mean lifetime compared to tumor-associated macrophages. Similarly, standard markers of macrophage phenotype (CD206 and CD86) assessed by immunofluorescence revealed greater heterogeneity in dermal macrophages compared to tumor-associated macrophages. Ultimately, metabolic autofluorescence imaging provides a novel tool to assess tissue-specific macrophage behavior and cell-level heterogeneity in vivo in animal models.

Breast cancer immunotherapy: current biomarkers and the potential of in vitro assays

Breakthroughs in metastatic breast cancer care require new model systems that can identify the unique features and vulnerabilities of each cancer. Primary tumor cultures are proposed to efficiently screen multiple treatment options in a patient-specific strategy to maximize therapeutic benefit, minimize toxicity, and enable mechanistic insights that inspire future biomarkers for patient selection. To realize the potential of patient-specific cultures, new tools are needed to capture cell-by-cell variability in behavior and dynamic response to treatments in living 3D specimens. Potential bioengineering tools that can achieve this include optical microscopy to image single-cell dynamics and microphysiological in vitro systems to evaluate cell-cell interactions and immunotherapies.

A bioengineered organotypic prostate model for the study of tumor microenvironment-induced immune cell activation

The prostate tumor microenvironment (TME) is strongly immunosuppressive; it is largely driven by alteration in cell phenotypes (i.e. tumor-associated macrophages and exhausted cytotoxic T cells) that result in pro-tumorigenic conditions and tumor growth. A greater understanding into how these altered immune cell phenotypes are developed and could potentially be reversed would provide important insights into improved treatment efficacy for prostate cancer. Here, we report a microfluidic model of the prostate TME that mimics prostate ducts across various stages of prostate cancer progression, with associated stroma and immune cells. Using this platform, we exposed immune cells to a benign prostate TME or a metastatic prostate TME and investigated their metabolism, gene and cytokine expression. Immune cells exposed to the metastatic TME showed metabolic differences with a higher redox ratio indicating a switch to a more glycolytic metabolic profile. These cells also increased expression of pro-tumor response cytokines that have been shown to increase cell migration and angiogenesis such as Interleukin-1 (IL-1) a and Granulocyte-macrophage colony-stimulating factor (GM-CSF). Lastly, we observed decreased TLR, STAT signaling and TRAIL expression, suggesting that phenotypes derived from exposure to the metastatic TME could have an impaired anti-tumor response. This platform could provide a valuable tool for studying immune cell phenotypes in in vitro tumor microenvironments.

Sex and SP-A2 Dependent NAD(H) Redox Alterations in Mouse Alveolar Macrophages in Response to Ozone Exposure: Potential Implications for COVID-19

Co-enzyme nicotinamide adenine dinucleotide (NAD(H)) redox plays a key role in macrophage function. Surfactant protein (SP-) A modulates the functions of alveolar macrophages (AM) and ozone (O₃) exposure in the presence or absence of SP-A and reduces mouse survival in a sex-dependent manner. It is unclear whether and how NAD(H) redox status plays a role in the innate immune response in a sex-dependent manner. We investigated the NAD(H) redox status of AM from SP-A2 and SP-A knockout (KO) mice in response to O₃ or filtered air (control) exposure using optical redox imaging technique. We found: (i) In SP-A2 mice, the redox alteration of AM in response to O₃ showed sex-dependence with AM from males being significantly more oxidized and having a higher level of mitochondrial reactive oxygen species than females; (ii) AM from KO mice were more oxidized after O₃ exposure and showed no sex differences; (iii) AM from female KO mice were more oxidized than female SP-A2 mice; and (iv) Two distinct subpopulations characterized by size and redox status were observed in a mouse AM sample. In conclusions, the NAD(H) redox balance in AM responds to O₃ in a sex-dependent manner and the innate immune molecule, SP-A2, contributes to this observed sex-specific redox response.