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<p>Metabolic Fluorescence Lifetime Imaging Microscopy (FLIM) algorithms have become invaluable tools for exploring deep into the complex dynamics of cellular metabolism. Monitoring subcellular parameters is of interest, particularly during photodynamic therapy (PDT), to enhance treatment efficacy. By joining together Metabolic FLIM with PLIM, it is possible to evaluate cellular metabolic states, such as oxygen consumption, redox states, pH levels, and energy production pathways. The aim of this work is to use NADH FLIM and PLIM techniques to distinguish different metabolic pattern signatures in tumor and normal cell lines using a PLIM pH sensitive complex from the family of phosphorescent [(N^C)<sub>2</sub>Ir(N^N)]<sup>+</sup> complexes. This investigation used a combination of 2-photon (2P) excited FLIM and PLIM techniques, coupled with time-correlated single-photon counting (TCSPC) detection. All the data were collected from living cells and were analyzed through exponential fitting. For the pattern segmentation we have used the phasor plot approach. By constructing a calibration curve and simultaneously acquiring NADH-FLIM and PLIM data from our pH sensor, we were able to identify metabolic regions and distinguished different pattern signatures in tumor and normal cell lines. This combined approach provides a comprehensive view of the tumor microenvironment, offering critical insights into parameters that influence photosensitizer localization, ROS generation, and therapeutic response. By identifying metabolic and pH heterogeneity at the single-cell level, this method contributes to improving the selectivity, precision, and overall efficacy of PDT treatments.</p>

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Combining NAD(P)H-FLIM and PLIM of Ir5 pH sensor to optimize photodynamic therapy through metabolic intracellular pattern segmentation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月3日

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  • D. dos Santos,
  • K. Reess,
  • N. Naskar,
  • I. S. Kritchenkov,
  • S. P. Tunik,
  • A. Rueck

摘要

Metabolic Fluorescence Lifetime Imaging Microscopy (FLIM) algorithms have become invaluable tools for exploring deep into the complex dynamics of cellular metabolism. Monitoring subcellular parameters is of interest, particularly during photodynamic therapy (PDT), to enhance treatment efficacy. By joining together Metabolic FLIM with PLIM, it is possible to evaluate cellular metabolic states, such as oxygen consumption, redox states, pH levels, and energy production pathways. The aim of this work is to use NADH FLIM and PLIM techniques to distinguish different metabolic pattern signatures in tumor and normal cell lines using a PLIM pH sensitive complex from the family of phosphorescent [(N^C)2Ir(N^N)]+ complexes. This investigation used a combination of 2-photon (2P) excited FLIM and PLIM techniques, coupled with time-correlated single-photon counting (TCSPC) detection. All the data were collected from living cells and were analyzed through exponential fitting. For the pattern segmentation we have used the phasor plot approach. By constructing a calibration curve and simultaneously acquiring NADH-FLIM and PLIM data from our pH sensor, we were able to identify metabolic regions and distinguished different pattern signatures in tumor and normal cell lines. This combined approach provides a comprehensive view of the tumor microenvironment, offering critical insights into parameters that influence photosensitizer localization, ROS generation, and therapeutic response. By identifying metabolic and pH heterogeneity at the single-cell level, this method contributes to improving the selectivity, precision, and overall efficacy of PDT treatments.