Perspectives on label-free microscopy of heterogeneous and dynamic biological systems.

Significance: Advancements in label-free microscopy could provide real-time, non-invasive imaging with unique sources of contrast and automated standardized analysis to characterize heterogeneous and dynamic biological processes. These tools would overcome challenges with widely used methods that are destructive (e.g., histology, flow cytometry) or lack cellular resolution (e.g., plate-based assays, whole animal bioluminescence imaging). Aim: This perspective aims to (1) justify the need for label-free microscopy to track heterogeneous cellular functions over time and space within unperturbed systems and (2) recommend improvements regarding instrumentation, image analysis, and image interpretation to address these needs. Approach: Three key research areas (cancer research, autoimmune disease, and tissue and cell engineering) are considered to support the need for label-free microscopy to characterize heterogeneity and dynamics within biological systems. Based on the strengths (e.g., multiple sources of molecular contrast, non-invasive monitoring) and weaknesses (e.g., imaging depth, image interpretation) of several label-free microscopy modalities, improvements for future imaging systems are recommended. Conclusion: Improvements in instrumentation including strategies that increase resolution and imaging speed, standardization and centralization of image analysis tools, and robust data validation and interpretation will expand the applications of label-free microscopy to study heterogeneous and dynamic biological systems.

Touch-free optical technologies to streamline the production of T cell therapies.

Currently approved adoptive T cell therapy relies on autologous (obtained from the same patient) T cells, which often suffer from poor quality that diminishes treatment efficacy. Due to the heterogeneous nature of T cell quality between and within patients, significant efforts are aimed at optimizing cell manipulation and growth conditions for potent T cell products. We believe that touch-free imaging and sensing technologies are critical to monitor single-cell features during T cell manufacturing to ensure consistent and optimally timed methods for cell manipulation and growth. Here, we discuss emerging label-free optical imaging and sensing methods, along with machine learning techniques that could enable in-line feedback to optimize T cell quality at multiple stages during manufacturing. These methods have the potential to streamline current workflow, accelerate the manufacture of safe high-quality T cell therapies, and improve our understanding of the dynamic, heterogeneous processes of T cell manufacturing.

Development and characterization of phasor-based analysis for FLIM to evaluate the metabolic and epigenetic impact of HER2 inhibition on squamous cell carcinoma cultures.

SIGNIFICANCE: Deranged metabolism and dysregulated growth factor signaling are closely associated with abnormal levels of proliferation, a recognized hallmark in tumorigenesis. Fluorescence lifetime imaging microscopy (FLIM) of endogenous nicotinamide adenine dinucleotide (NADH), a key metabolic coenzyme, offers a non-invasive, diagnostic indicator of disease progression, and treatment response. The model-independent phasor analysis approach leverages FLIM to rapidly evaluate cancer metabolism in response to targeted therapy. AIM: We combined lifetime and phasor FLIM analysis to evaluate the influence of human epidermal growth factor receptor 2 (HER2) inhibition, a prevalent cancer biomarker, on both nuclear and cytoplasmic NAD(P)H of two squamous cell carcinoma (SCC) cultures. While better established, the standard lifetime analysis approach is relatively slow and potentially subject to intrinsic fitting errors and model assumptions. Phasor FLIM analysis offers a rapid, model-independent alternative, but the sensitivity of the bound NAD(P)H fraction to growth factor signaling must also be firmly established. APPROACH: Two SCC cultures with low- and high-HER2 expression, were imaged using multiphoton-excited NAD(P)H FLIM, with and without treatment of the HER2 inhibitor AG825. Cells were challenged with mitochondrial inhibition and uncoupling to investigate AG825's impact on the overall metabolic capacity. Phasor FLIM and lifetime fitting analyses were compared within nuclear and cytoplasmic compartments to investigate epigenetic and metabolic impacts of HER2 inhibition. RESULTS: NAD(P)H fluorescence lifetime and bound fraction consistently decreased following HER2 inhibition in both cell lines. High-HER2 SCC74B cells displayed a more significant response than low-HER2 SCC74A in both techniques. HER2 inhibition induced greater changes in nuclear than cytoplasmic compartments, leading to an increase in NAD(P)H intensity and concentration. CONCLUSIONS: The use of both, complementary FLIM analysis techniques together with quantitative fluorescence intensity revealed consistent, quantitative changes in NAD(P)H metabolism associated with inhibition of growth factor signaling in SCC cell lines. HER2 inhibition promoted increased reliance on oxidative phosphorylation in both cell lines.

Time-domain single photon-excited autofluorescence lifetime for label-free detection of T cell activation.

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique, capable of label-free assessment of the metabolic state and function within single cells. The FLIM measurements of autofluorescence were recently shown to be sensitive to the functional state and subtype of T cells. Therefore, autofluorescence FLIM could improve cell manufacturing technologies for adoptive immunotherapy, which currently require a time-intensive process of cell labeling with fluorescent antibodies. However, current autofluorescence FLIM implementations are typically too slow, bulky, and prohibitively expensive for use in cell manufacturing pipelines. Here we report a single photon-excited confocal whole-cell autofluorescence system that uses fast field-programmable gate array-based time tagging electronics to achieve time-correlated single photon counting (TCSPC) of single-cell autofluorescence. The system includes simultaneous near-infrared bright-field imaging and is sensitive to variations in the fluorescence decay profile of the metabolic coenzyme NAD(P)H in human T cells due to the activation state. The classification of activated and quiescent T cells achieved high accuracy and precision (area under the receiver operating characteristic curve, AUC = 0.92). The lower-cost, higher acquisition speed, and resistance to pile-up effects at high photon flux compared to traditional multiphoton-excited FLIM and TCSPC implementations with similar SNR make this system attractive for integration into flow cytometry, sorting, and quality control in cell manufacturing.

Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment.

New tools are needed to match cancer patients with effective treatments. Patient-derived organoids offer a high-throughput platform to personalize treatments and discover novel therapies. Currently, methods to evaluate drug response in organoids are limited because they overlook cellular heterogeneity. In this study, non-invasive optical metabolic imaging (OMI) of cellular heterogeneity was characterized in breast cancer (BC) and pancreatic cancer (PC) patient-derived organoids. Baseline heterogeneity was analyzed for each patient, demonstrating that single-cell techniques, such as OMI, are required to capture the complete picture of heterogeneity present in a sample. Treatment-induced changes in heterogeneity were also analyzed, further demonstrating that these measurements greatly complement current techniques that only gauge average cellular response. Finally, OMI of cellular heterogeneity in organoids was evaluated as a predictor of clinical treatment response for the first time. Organoids were treated with the same drugs as the patient's prescribed regimen, and OMI measurements of heterogeneity were compared to patient outcome. OMI distinguished subpopulations of cells with divergent and dynamic responses to treatment in living organoids without the use of labels or dyes. OMI of organoids agreed with long-term therapeutic response in patients. With these capabilities, OMI could serve as a sensitive high-throughput tool to identify optimal therapies for individual patients, and to develop new effective therapies that address cellular heterogeneity in cancer.