Research

NADH, NADPH, and FAD

Fig. 1: NADH, NADPH, and FAD are metabolic co-enzymes involved in hundreds of reactions in cells. The fluorescence of NADH and NADPH overlap and are collectively denoted as NAD(P)H. The fluorescence intensity and lifetimes of NAD(P)H and FAD provide insight into the redox ratio and enzyme binding activity across hundreds of reactions per cell, which reflect functional changes in cancer, immune cell behavior, and stem cell trajectory.

We develop label-free optical imaging technologies and quantitative analysis tools to study metabolic heterogeneity in cancer, stem cells, and immune cells. Optical metabolic imaging (OMI) uses two-photon fluorescence lifetime microscopy of metabolic co-enzymes NAD(P)H and FAD (Fig. 1) to quantify cell redox state and enzyme-binding activity. This approach is advantageous because autofluorescent molecules that are already present in the cells can be used to monitor metabolism with single-cell resolution. We integrate OMI with image analysis tools and population density models to quantify cellular heterogeneity within a range of complex biological samples including 2D cells, 3D organoids, microphysiological systems, and in vivo models. Ongoing projects require active collaborations and mentorship of trainees from diverse backgrounds in medicine, engineering, biochemistry, and biology.

  • Optical methods to monitor cell function, metabolism, and cellular diversity
    We specialize in label-free optical imaging techniques to monitor cellular metabolism in single cells. We have developed single cell segmentation and population density modeling to quantify metabolic diversity within intact samples, which we validated in breast cancer cell lines (Fig. 2A-B). Recently, we discovered that NAD(P)H lifetimes can robustly classify primary human T cells by activation state and function, which enables label-free monitoring of T cell function within intact samples and guidance of cell therapy manufacturing including CAR T cell therapy. We are investigating the same approach to monitor immune cell function across numerous cell types in human blood samples (Fig. 2C). Similarly, we found that autofluorescence lifetimes can predict stem cell differentiation efficiencies early in production. We have also developed higher-throughput technologies to assess single cell metabolism using label-free autofluorescence lifetime flow cytometry.

    Figure 2

    Fig. 2: (A-B) population density modeling of cellular heterogeneity in breast cancer cells with OMI. (C) OMI of primary human immune cells.

    Representative Publications

    • Pham DL, Cappabianca D, Forsberg MH, Weaver C, Mueller KP, Tommasi A, Vidugiriene J, Lauer A, Sylvester K, Lika J, Bugel M, Fan J, Capitini CM, Saha K*, Skala MC*. Label-free metabolic imaging monitors the fitness of chimeric antigen receptor T cells. Nat Biomed Eng. 2025 Sep 16. PMID: 40958004
    • Samimi K, Pasachhe O, Guzman EC, Riendeau J, Gillette AA, Pham DL, Wiech KJ, Moore DL, Skala MC*. Autofluorescence lifetime flow cytometry with time-correlated single photon counting. Cytometry A. 2024 Aug;105(8):607-620. PMID: 38943226
    • Walsh AJ*, Mueller KP, Tweed K, Jones I, Walsh CM, Piscopo NJ, Niemi NM, Pagliarini DJ, Saha K, Skala MC*. Classification of T-cell activation via autofluorescence lifetime imaging. Nat Biomed Eng. 2021; 5(1):77-88. PMCID: PMC7854821.
    • Qian T*, Heaster TM, Houghtaling AR, Sun K, Samimi K, Skala MC*. Label-free imaging for quality control of cardiomyocyte differentiation. Nat Commun. 2021 Jul 28;12(1):4580. PMCID: PMC8319125
  • Optical metabolic imaging of organoids for drug development and clinical treatment planning.
    Optical metabolic imaging of NAD(P)H and FAD intensities and lifetimes enables monitoring of cell metabolism within intact 3D primary tumor organoids. Primary tumor organoids are advantageous compared to traditional 2D culture because organoids retain multiple cell types from the original tumor in a 3D environment that maintains the cell-cell communication, genetic expression, and drug response of the original tumor. Primary tumor organoids also provide improved throughput compared to in vivo mouse models. Optical metabolic imaging provides a novel method to monitor cell metabolism within intact organoids so that changes in cell-cell metabolic interactions can be monitored over time. We have shown that optical metabolic imaging accurately predicts drug response in organoids with respect to standard in vivo tumor volume. We further defined metrics of metabolic heterogeneity in tumor organoids that predict drug response across breast, pancreatic, oral, neuroendocrine, and colon cancers (Fig. 3). Finally, we have developed higher-throughput wide-field optical redox imaging technologies and automated image analysis pipelines that can rapidly and automatically screen multi-well plates for drug response in 3D patient-derived cancer organoids. These wide-field technologies can identify driver mutations and track drug response over time within single organoids while using accessible hardware and software for non-specialists.

    Figure 3

    Fig. 3: Optical metabolic imaging of representative patient-derived tumor organoids.

    Representative Publications

    • Gillette A, Udgata S, Schmitz AE, Stoecker JN, Kratz JD, Deming DA, Skala MC*. Wide-Field Optical Redox Imaging with Leading-Edge Detection Enables Assessment of Treatment Response and Heterogeneity in Patient-Derived Cancer Organoids. Cancer Res. 2025 Sep 8. PMID: 40920506
    • Datta R, Sivanand S, Lau AN*, Florek LV, Barbeau AM, Wyckoff J, Skala MC*, Vander Heiden MG*. Interactions with stromal cells promote a more oxidized cancer cell redox state in pancreatic tumors. Sci Adv. 2022 Jan 21;8(3):eabg6383. PMCID: PMC8782446.
    • Heaster TM, Humayun M, Yu J, Beebe DJ, Skala MC*. Autofluorescence imaging of 3D tumor-macrophage microscale cultures resolves spatial and temporal dynamics of macrophage metabolism. Cancer Res. 2020;80(23):5408-23. PMCID: PMC7718391.
    • Sharick JT, Walsh CM, Sprackling CM, Pasch CA, Pham DL, Esbona K, Choudhary A, Garcia-Valera R, Burkard ME, McGregor SM, Matkowskyj KA, Parikh AA, Meszoely IM, Kelley MC, Tsai S, Deming DA, Skala MC*. Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment. Front Oncol. 2020;10:553. PMCID: PMC7242740.
  • In vivo optical metabolic imaging of single cells
    Animal models have provided critical in vivo context to validate optical metabolic imaging of cell metabolism. Optical metabolic imaging provides early (1-3 days post-treatment) measurements of drug response in vivo in mouse models (Fig. 4A) compared to standard tumor volume. Metabolic heterogeneity within immune cells, including T cells, neutrophils, and macrophages, can also be characterized in vivo in mouse models and in zebrafish models, revealing metabolic adaptations to tumor growth and treatment or changes in immune cell function with wound healing. Immune cell function can be monitored in the tumor microenvironment as well as systemically in tissues like the lymph node (Fig. 4B) and spleen (Fig. 4C). Additional studies used autofluorescence lifetimes to characterize single-cell neutrophil metabolism during activation using primary human neutrophils and in vivo imaging in zebrafish models. These studies provide unique insights into metabolism in vivo with single cell resolution, for both tumor cells and immune cells.

    Figure 4

    Fig. 4: (A) NAD(P)H mean lifetime of in vivo mouse mammary tumor. OMI of ex vivo mouse (B) tumor draining lymph node and (C) spleen where red is mCherry-expressing T cells and blue is NAD(P)H intensity.

    Representative Publications

    • Datta R*, Miskolci V, Gallego-López GM, Britt E, Gillette A, Kralovec A, Giese MA, Qian T, Votava J, Zhao W, Fan J, Huttenlocher A, Skala MC*. Single cell autofluorescence imaging reveals immediate metabolic shifts of neutrophils with activation across biological systems. Front Immunol. 2025 Aug 7;16:1617993. PMID: 40852713
    • Heaton AR, Rehani PR, Hoefges A, Lopez AF, Erbe AK, Sondel PM, Skala MC*. Single cell metabolic imaging of tumor and immune cells in vivo in melanoma bearing mice. Front Oncol. 2023 Mar 20;13:1110503. PMID: 37020875
    • Miskolci V, Tweed KE, Lasarev MR, Britt EC, Walsh AJ, Zimmerman LJ, McDougal CE, Cronan MR, Fan J, Sauer JD, Skala MC*, Huttenlocher A*. In vivo fluorescence lifetime imaging of macrophage intracellular metabolism during wound responses in zebrafish. Elife. 2022 Feb 24;11:e66080. PMCID: PMC8871371
    • Heaster TM, Heaton AR, Sondel PM, Skala MC*. Intravital Metabolic Autofluorescence Imaging Captures Macrophage Heterogeneity Across Normal and Cancerous Tissue. Front Bioeng Biotechnol. 2021 Apr 20;9:644648. PMCID: PMC8093439
  • Photothermal optical coherence tomography for molecular imaging
    Optical coherence tomography is a powerful 3D imaging tool that is routinely used in clinical ophthalmology. However, optical coherence tomography achieves poor molecular specificity. We developed a new technique, photothermal optical coherence tomography, which enables molecular contrast through microscopic thermoelastic expansions in vivo. Photothermal optical coherence tomography provides molecular contrast in a new spatial regime, between microscopy (poor penetration depth) and ultrasound (poor resolution). Our work focuses on technology development and in vivo applications in ophthalmology and cancer, using endogenous contrast agents such as melanin (Fig. 5) and exogenous contrast agents such as indocyanine green.

    Figure 5

    Fig. 5: Photothermal OCT of melanin in the zebrafish eye.

    Representative Publications

    • Lapierre-Landry M, Huckenpahler AL, Link BA, Collery RF, Carroll J*, Skala MC*. Imaging Melanin Distribution in the Zebrafish Retina Using Photothermal Optical Coherence Tomography. Transl Vis Sci Technol. 2018;7(5):4. PMCID: PMC6126953.
    • Lapierre-Landry M, Connor TB, Carroll J, Tao YK, Skala MC*. Photothermal optical coherence tomography of indocyanine green in ex vivo eyes. Opt Lett. 2018;43(11):2470-3. PMCID: PMC8148624
    • Lapierre–Landry M, Gordon AY, Penn JS, Skala MC*. In vivo photothermal optical coherence tomography of endogenous and exogenous contrast agents in the eye. Sci Rep. 2017;7(1):9228. PMCID: PMC5569082.
    • Tucker-Schwartz JM, Beavers KR, Sit WW, Shah AT, Duvall CL, Skala MC*. In vivo imaging of nanoparticle delivery and tumor microvasculature with multimodal optical coherence tomography. Biomed Opt Express. 2014;5(6):1731-43. PMCID: PMC4052907.
  • Collaborators