Fluorescence lifetime imaging microscopy (FLIM) can probe the metabolic environment of living cells in a label-free and non-invasive manner. However, endogenous fluorophores have low absorption and quantum yields, which necessitates long integration times to acquire the high photon counts needed for accurate pixel-wise multi-exponential decay fitting. Here, we present a 'region-of-interest' photon pooling technique to expedite label-free, single cell FLIM acquisition and analysis. As a result, we achieved single-cell metabolic information at intervals as low as one second and acquired large FLIM mosaics 15 times faster than would be possible with conventional pixel-level analysis. This technique is computationally light, does not require machine learning algorithms, and has been integrated with commonly used analysis software and file types.

Significance:Human pluripotent stem-cell-derived cardiomyocytes (hPSC-CMs) are a powerful tool for drug discovery, and metabolic changes are associated with their long-term culture and maturation. However, the lack of technologies to monitor hPSC-derived cardiomyocyte metabolism during long-term culture presents a major technical bottleneck. Aim:Efforts to monitor in vitro metabolic maturation of hPSC-CMs are limited by traditional assessment methods, which are generally time-consuming, destructive to samples, and lack single-cell resolution. We report a rapid, noninvasive imaging-based method to monitor hPSC-CM metabolism throughout extended culture (90+ days). Approach:Label-free optical metabolic imaging (OMI) of autofluorescent metabolic coenzymes was performed at multiple time points during the extended culture maturation process. In addition, OMI monitored hPSC-CMs grown on substrates with varying stiffness and on cardiomyocytes derived from induced pluripotent stem cells associated with cardiac arrhythmia. OMI was paired with immunofluorescence to validate structural maturation. Results:Single-cell OMI can identify metabolic changes during cardiomyocyte maturation through extended in vitro culturing. It can also detect metabolic differences induced by substrates of varying stiffnesses, can distinguish diseased from normal cell lines, and is sensitive to patient-level metabolic heterogeneity. Conclusions:Our results demonstrate that label-free OMI can be used to monitor metabolic changes in hPSC-CMs under varying culture conditions in a rapid, non-destructive manner with single-cell resolution, providing insight into metabolic transitions arising from time in culture, culture conditions, or disease states.

Significance:Second-harmonic generation (SHG) analysis of collagen internal structure and overall organization in the tumor microenvironment may enhance current metastasis prediction methods, which do not prognosticate with the same accuracy for patients of different races. For these optical tools to be clinically available, a multicenter trial is needed. We investigate if SHG-based prognostic signals vary with patient race, providing insight for designing such a trial. Aim:SHG imaging was performed on colon adenocarcinoma (CRC) and invasive ductal carcinoma (IDC) patient samples to derive two prognostic indicators. We assessed the association between these indicators and patient race. Approach:SHG images were analyzed as previously described to determine the forward- to backward-SHG scattering ratio (F/B) and fiber angle variability (FAV). Both prognostic measurements were compared between Black and White patients. Results:In the IDC cohort, F/B from the tumor-stroma interface differed significantly between demographic groups. For the CRC cohort, a trend was observed in the tumor-stroma interface and tumor bulk. FAV did not vary by race in either cohort. Conclusions:F/B variation with patient race suggests the relationship between F/B and metastatic outcome may vary with patient race. These findings highlight the potential need for race-specific prognostic algorithms to improve metastasis prediction for all patients.

Induced pluripotent stem cells (iPSC) can be differentiated into cardiomyocytes (CM) for disease modeling and drug screening. Batch variability in differentiated cells frequently occurs due to heterogeneity in commercial culture substrates. We performed optical metabolic imaging (OMI) on synthetic hydrogels of varying stiffnesses and compositions and observed expected metabolic shifts as iPSCs differentiated. OMI revealed metabolic differences between cells cultured on heterogenous commercial substrates and synthetic hydrogels and can be used to monitor cell sensitivity to the microenvironment. These data demonstrate OMI is a powerful tool for identifying iPSC differentiation and maturation conditions, crucial in stem cell manufacturing.

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. IMPORTANCE This 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.

Significance:Heart disease is the leading cause of death in the United States, yet research is limited by the inability to culture primary cardiac cells. Cardiomyocytes (CMs) derived from human induced pluripotent stem cells (iPSCs) are a promising solution for drug screening and disease modeling. Aim:Induced pluripotent stem cell-derived CM (iPSC-CM) differentiation and maturation studies typically use heterogeneous substrates for growth and destructive verification methods. Reproducible, tunable substrates and touch-free monitoring are needed to identify ideal conditions to produce homogenous, functional CMs. Approach:We generated synthetic polyethylene glycol-based hydrogels for iPSC-CM differentiation and maturation. Peptide concentrations, combinations, and gel stiffness were tuned independently. Label-free optical redox imaging (ORI) was performed on a widefield microscope in a 96-well screen of gel formulations. We performed live-cell imaging throughout differentiation and early to late maturation to identify key metabolic shifts. Results:Label-free ORI confirmed the expected metabolic shifts toward oxidative phosphorylation throughout the differentiation and maturation processes of iPSC-CMs on synthetic hydrogels. Furthermore, ORI distinguished high and low differentiation efficiency cell batches in the cardiac progenitor stage. Conclusions:We established a workflow for medium throughput screening of synthetic hydrogel conditions with the ability to perform repeated live-cell measurements and confirm expected metabolic shifts. These methods have implications for reproducible iPSC-CM generation in biomanufacturing.

Single photon avalanche diode (SPAD) array sensors can increase the imaging speed for fluorescence lifetime imaging microscopy (FLIM) by transitioning from laser scanning to widefield geometries. While a SPAD camera in epi-fluorescence geometry enables widefield FLIM of fluorescently labeled samples, label-free imaging of single-cell autofluorescence is not feasible in an epi-fluorescence geometry because background fluorescence from out-of-focus features masks weak cell autofluorescence and biases lifetime measurements. Here, we address this problem by integrating the SPAD camera in a light sheet illumination geometry to achieve optical sectioning and limit out-of-focus contributions, enabling fast label-free FLIM of single-cell NAD(P)H autofluorescence. The feasibility of this NAD(P)H light sheet FLIM system was confirmed with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times, and in vivo NAD(P)H light sheet FLIM was demonstrated with live neutrophil imaging in a 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 30X to 6X frame rate advantage for the light sheet compared to the laser scanning geometry. This light sheet system provides faster frame rates for 3D NAD(P)H FLIM for live cell imaging applications such as monitoring single cell metabolism and immune cell migration throughout an entire living organism.

In the tumor microenvironment (TME), collagen fibers facilitate tumor cell migration through the extracellular matrix. Previous studies have focused on studying the responses of cells on uniformly aligned or randomly aligned collagen fibers. However, the in vivo environment also features spatial gradients in alignment, which arise from the local reorganization of the matrix architecture due to cell-induced traction forces. Although there has been extensive research on how cells respond to graded biophysical cues, such as stiffness, porosity, and ligand density, the cellular responses to physiological fiber alignment gradients have been largely unexplored. This is due, in part, to a lack of robust experimental techniques to create controlled alignment gradients in natural materials. In this study, we image tumor biopsy samples and characterize the alignment gradients present in the TME. To replicate physiological gradients, we introduce a first-of-its-kind biofabrication technique that utilizes a microfluidic channel with constricting and expanding geometry to engineer 3D collagen hydrogels with tunable fiber alignment gradients that range from sub-millimeter to millimeter length scales. Our modular approach allows easy access to the microengineered gradient gels, and we demonstrate that HUVECs migrate in response to the fiber architecture. We provide preliminary evidence suggesting that MDA-MB-231 cell aggregates, patterned onto a specific location on the alignment gradient, exhibit preferential migration towards increasing alignment. This finding suggests that alignment gradients could serve as an additional taxis cue in the ECM. Importantly, our study represents the first successful engineering of continuous gradients of fiber alignment in soft, natural materials. We anticipate that our user-friendly platform, which needs no specialized equipment, will offer new experimental capabilities to study the impact of fiber-based contact guidance on directed cell migration.

Regional metastasis of head and neck cancer (HNC) is prevalent (approximately 50% of patients at diagnosis), yet the underlying drivers and mechanisms of lymphatic spread remain unclear. The complex tumor microenvi-ronment (TME) of HNC plays a crucial role in disease maintenance and progression; however, the contribution of the lymphatics remains underexplored. We created a primary patient cell derived microphysiological system that incorporates cancer-associated-fibroblasts from patients with HNC alongside a HNC tumor spheroid and a lymphatic microvessel to create an in vitro TME platform to investigate metastasis. Screening of soluble factor signaling identified novel secretion of macrophage migration inhibitory factor (MIF) by lymphatic endothelial cells conditioned in the TME. Importantly, we also observed patient-to-patient heterogeneity in cancer cell migration similar to the heterogeneity observed in clinical disease. Optical metabolic imaging at the single cell level identified a distinct metabolic profile of migratory versus non-migratory HNC cells in a microenvironment dependent manner. Additionally, we report a unique role of MIF in increasing HNC reliance on glycolysis over oxidative phosphorylation. This multicellular, microfluidic platform expands the tools available to explore HNC biology in vitro through multiple orthogonal outputs and establishes a system with enough resolution to visualize and quantify patient-to-patient heterogeneity.

Breast cancer is the most common invasive cancer in women, with most deaths attributed to metastases. Neoadjuvant chemotherapy (NACT) may be prescribed prior to surgical removal of the tumor for subsets of breast cancer patients but can have diverse undesired and off-target effects, including the increased appearance of the 'tumor microenvironment of metastasis', image-based multicellular signatures that are prognostic of breast tumor metastasis. To assess whether NACT can induce changes in two other image-based prognostic/predictive signatures derived from tumor collagen, we quantified second-harmonic generation (SHG) directionality and fiber alignment in formalin-fixed, paraffin-embedded sections of core needle biopsies and primary tumor excisions from 22 human epidermal growth factor receptor 2-overexpressing (HER2+) and 22 triple-negative breast cancers. In both subtypes, we found that SHG directionality (i.e., the forward-to-backward scattering ratio, or F/B) is increased by NACT in the bulk of the tumor, but not the adjacent tumor-stroma interface. Overall collagen fiber alignment is increased by NACT in triple-negative but not HER2+ breast tumors. These results suggest that NACT impacts the collagenous extracellular matrix in a complex and subtype-specific manner, with some prognostic features being unchanged while others are altered in a manner suggestive of a more metastatic phenotype.

Human stem cells provide emerging methods for drug screening, disease modeling, and personalized patient therapies. To meet this growing demand for scale-up, stem cell manufacturing methods must be streamlined with continuous monitoring technologies and automated feedback to optimize growth conditions for high production and consistency. Label-free optical imaging and sensing, including multiphoton microscopy, Raman spectroscopy, and low-cost methods such as phase and transmitted light microscopy, can provide rapid, repeatable, and non-invasive monitoring of stem cells throughout cell differentiation and maturation. Machine learning algorithms trained on label-free optical imaging and sensing features could identify viable cells and predict optimal manufacturing conditions. These techniques have the potential to streamline stem cell manufacturing and accelerate their use in regenerative medicine.

Cancer treatment involves complex decision-making processes. A better understanding of recurrence risk at diagnosis, as well as prediction of treatment response (e.g., to choose the most cost-effective treatment path in an informed manner) are needed to produce the best possible outcomes at the patient level. Prior work shows that the forward/backward (F/B) ratio calculated from Second Harmonic Generation (SHG) imagery can be indicative of risk of recurrence if relevant tissue sub-regions are selected. The choice of which sub-regions to image is currently made by human experts, which is subjective and labor intensive. In this paper, we investigate machine learning methods to automatically identify tissue sub-regions that are most relevant to the prediction of breast cancer recurrence. We formulate the task as a multi-class classification problem and use support vector machine (SVM) classifiers as the inference engine. Given the limited amount of data available, we focus on exploring the feature extraction stage. To that end, we evaluate methods leveraging handcrafted features, deep features extracted from pre-trained models, as well as features extracted via transfer learning. The results show a steady trend of improvement on the classification accuracy as the features become more data-driven and customized to the task at hand. This is an indication that having larger amounts of labeled data could be beneficial for improving automated methods of classification. The best results achieved, using features learned via transfer learning from ResNet-101, correspond to 85% accuracy in a 3-class problem and 94% accuracy in a binary classification problem.

Noninvasive monitoring of vascularization can potentially diagnose impaired bone healing earlier than current radiographic methods. In this study, a noncontact diffuse correlation tomography (DCT) technique was employed to measure longitudinal blood flow changes during bone healing in a murine femoral fracture model. The three‐dimensional distribution of the relative blood flow was quantified from one day pre‐fracture to 48 days post‐fracture. For three mice, frequent DCT measurements were performed every other day for one week after fracture, and then weekly thereafter. A decrease in blood flow was observed in the bone fracture region at one day post‐fracture, followed by a monotonic increase in blood flow beyond the pre‐injury baseline until five to seven days post‐fracture. For the remaining 12 mice, only weekly DCT measurements were performed. Data collected on a weekly basis show the blood flow for most mice was elevated above baseline during the first two post‐fracture weeks, followed by a subsequent decrease. Torsional strength of the excised femurs was measured for all 15 mice after 7 weeks of healing. A metric based on the early blood flow changes shows a statistically significant difference between the high strength group and the low strength group.

Metastases are the leading cause of breast cancer-related deaths. The tumor microenvironment impacts cancer progression and metastatic ability. Fibrillar collagen, a major extracellular matrix component, can be studied using the light scattering phenomenon known as second-harmonic generation (SHG). The ratio of forward- to backward-scattered SHG photons (F/B) is sensitive to collagen fiber internal structure and has been shown to be an independent prognostic indicator of metastasis-free survival time (MFS). Here we assess the effects of heterogeneity in the tumor matrix on the possible use of F/B as a prognostic tool. SHG imaging was performed on sectioned primary tumor excisions from 95 untreated, estrogen receptor-positive, lymph node negative invasive ductal carcinoma patients. We identified two distinct regions whose collagen displayed different average F/B values, indicative of spatial heterogeneity: the cellular tumor bulk and surrounding tumor-stroma interface. To evaluate the impact of heterogeneity on F/B’s prognostic ability, we performed SHG imaging in the tumor bulk and tumor-stroma interface, calculated a 21-gene recurrence score (surrogate for OncotypeDX®, or S-ODX) for each patient and evaluated their combined prognostic ability. We found that F/B measured in tumor-stroma interface, but not tumor bulk, is prognostic of MFS using three methods to select pixels for analysis: an intensity threshold selected by a blinded observer, a histogram-based thresholding method, and an adaptive thresholding method. Using both regression trees and Random Survival Forests for MFS outcome, we obtained data-driven prediction rules that show F/B from tumor-stroma interface, but not tumor bulk, and S-ODX both contribute to predicting MFS in this patient cohort. We also separated patients into low-intermediate (S-ODX < 26) and high risk (S-ODX ≥26) groups. In the low-intermediate risk group, comprised of patients not typically recommended for adjuvant chemotherapy, we find that F/B from the tumor-stroma interface is prognostic of MFS and can identify a patient cohort with poor outcomes. These data demonstrate that intratumoral heterogeneity in F/B values can play an important role in its possible use as a prognostic marker, and that F/B from tumor-stroma interface of primary tumor excisions may provide useful information to stratify patients by metastatic risk.

Background Second harmonic generation (SHG) is an intrinsic optical property of fibrillar collagen. SHG directionality is quantified by F/B, the ratio of forward- to backward-propagating signal, which is affected by collagen fiber internal structure, specifically the diameter, spacing, and disorder of fibrils within a collagen fiber. We have previously shown that F/B of primary invasive ductal carcinoma sections is prognostic of metastatic outcome. One possible cause of this relationship was revealed by our observation that tumor cells’ motility on collagen I gels varied when collagen fiber internal structure in those gels was manipulated. The mechanism by which tumor cells sense changes in collagen fiber internal structure remains unknown: here we evaluate the role of elastic modulus in the relationship between collagen fiber internal structure (as reported by F/B) and tumor cell motility. Methods The 4T1 murine mammary adenocarcinoma, a model of metastatic triple negative breast cancer, (TNBC) and the 67NR line, a non-metastatic luminal phenotype, were introduced to a series of collagen-polyacrylamide mixed gels wherein collagen fiber internal structure and gel elastic modulus were independently controlled. F/B was measured with SHG, while elastic modulus was measured globally via rheometry and locally via atomic force microscopy (AFM). Tumor cell motility was quantified over three hours. Results The motility of both cell lines varied with F/B while elastic modulus was held constant, and did so at two physiological modulus values. Interestingly, 4T1 cell motility increased as F/B increased, while 67NR cell motility decreased. Conclusions Our results suggest that elastic modulus does not play a significant role in the observed relationship between collagen fiber internal structure (as reported by F/B) and tumor cell motility, for two cell lines that are models of TNBC and luminal-like breast cancer. Our observation that the two lines exhibit opposite motility trends as F/B increases is consistent with the trends in metastatic outcome versus F/B observed in our published clinical data for luminal versus basal cohorts, and suggests that a tumor’s subtype may play a role in their response to collagen fiber internal structure.

Neoadjuvant chemotherapy (NACT) is routinely administered to subsets of breast cancer patients, including triple negative (TN) or human epidermal growth factor receptor 2-positive (HER2+) cancers. After NACT and subsequent surgical resection, 5% to 30% of patients have no residual invasive carcinoma, termed pathological complete response. Unfortunately, many patients experience little-to-no response after NACT and unnecessarily suffer its side effects. Methods are needed to predict an individual patient’s response to NACT. Core needle biopsies, taken before NACT, consist of tumor cells and the surrounding extracellular matrix. We performed second-harmonic generation (SHG) imaging of fibrillar collagen in core needle biopsy sections as a possible predictor of response to NACT. The ratio of forward-to-backward scattering (F/B) SHG was assessed in the “tumor bulk” and “tumor–host interface” in HER2+ and TN core needle biopsy sections. Patient response was classified post-treatment using the Residual Cancer Burden (RCB) score. In HER2+ biopsies, RCB class was associated with F/B derived from the tumor–stromal interface, but not tumor bulk. F/B was not associated with RCB class in TN biopsies. These findings suggest that F/B from needle biopsy sections may be a useful predictor of which patients will respond favorably to NACT, with the potential to help reduce overtreatment.

Despite causing permanent hearing loss by damaging inner ear sensory cells, aminoglycosides (AGs) remain one of the most widely used classes of antibiotics in the world. Although the mechanisms of cochlear sensory cell damage are not fully known, reactive oxygen species (ROS) are clearly implicated. Mitochondrial-specific ROS formation was evaluated in acutely cultured murine cochlear explants exposed to gentamicin (GM), a representative ototoxic AG antibiotic. Superoxide (O-2(center dot-)) and hydrogen peroxide (H2O2) were measured using MitoSOX Red and Dihydrorhodamine 123, respectively, in sensory and supporting cells. A 1-h GM exposure significantly increased O-2(center dot-) formation in IHCs and increased H2O2 formation in all cell types. At the same time point, GM significantly increased manganese superoxide dismutase (MnSOD) levels while significantly decreasing copper/zinc superoxide dismutase (CuZnSOD) in cochlear sensory cells. This suggests (1) a rapid conversion of highly reactive O-2(center dot-) to H2O2 during the acute stage of ototoxic antibiotic exposure and (2) that the endogenous antioxidant system is significantly altered by AGs. Fluorescence intensity-based measurements of reduced nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] and mitochondrial membrane potential were measured to determine if increases in GM-induced ROS production were correlated with changes in mitochondrial metabolism. This project provides a basis for understanding the mechanisms of mitochondrial ROS production in cochlear cells exposed to ototoxic antibiotics. Understanding the nature of ototoxic antibiotic-induced changes in mitochondrial metabolism is critical for developing hearing loss treatment and prevention strategies. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.