MIFOBIO 2025 Workshop A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis

Xiaotong Yuan and Chiara Stringari Laboratory For Optics and Biosciences (LOB) Advanced Microscopies and Tissue Physiology École Polytechnique, Paris Saclay (France) October 15th 2025 A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis FLUTe –(F)luorescence (L)ifetime (U)ltima(T)e (E)xplorer a Python GUI for interactive phasor analysis of FLIM data Lien Ung Dale Gottlieb Bahar Asadipour I t Phase mapping Region Selection ab eModulation mapping cd fDistance mapping Custom written free software Open source code in Python user-friendly GUI large FLIM datasets Polina Kostina Open source code and Executable on GitHub https://github.com/LaboratoryOpticsBiosciences/FLUTE Gottlieb, D., Asadipour, B., Kostina, P., Ung, T., & Stringari, C. (2023). FLUTE: A Python GUI for interactive phasor analysis of FLIM data. Biological Imaging, 1-22. doi:10.1017/S2633903X23000211 FLIM data in Zenodo repository https://zenodo.org/records/8324901 Open source FLIM Analysis https://www.youtube.com/@I2KConference Xiaotong Yuan 1. General introduction (~15min ): Intro on FLIM and Phasor analysis and Metabolic imaging 2. Intro on FLUTE (15 min) FLUTE features 3. Calibration Procedures and number of photons (15 min) 4. Demonstration and examples/ HANDS ON (30 min) 5. Questions and discussions (15 min) Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis 1. General introduction (~15min )Intro on FLIM and Phasor analysis and Metabolic imaging 2. Intro on FLUTE (15 min) FLUTE features 3. Calibration Procedures and number of photons (15 min) 4. Demonstration and examples/ HANDS ON (30 min) 5. Questions and discussions (15 min) Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Problems: Heterogeneity, absorption, scattering background fluorescence η= Γ/ (Γ+k) Intensity ~ f(η) λ~ hc/(E1-E0) Spectra Problems: Spectral demixing, Overlapping absorption and emission spectra τ= 1/ (Γ+k) Lifetime Molecular identification (Γ): Intrinsic property (Fingerprint) of the fluorophore chemical structure Sensitive to molecular mico-environment (k) : binding, quenching, pH, viscosity, energy transfer… Independent on concentration, intensity heterogeneity and scattering, photobleaching Fluorescence Lifetime Becker et al. Microsc Res Tech. 2004 Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Datta et al JBO 2021 Analysis of FLIM data Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Analysis of FLIM Data I t (ns) FFT 𝐼 𝑡 = 𝛼 𝑒−𝑡 𝜏1+ 1 − 𝛼 𝑒−𝑡 𝜏2𝐷 𝜔 = 𝑓 1𝑅1𝜏1, 𝜔 + 𝑓2𝑅2𝜏2, 𝜔 2023-Gottlieb et al-In revision Phasor analysis Multi-exponential fitting Difficult interpretation of multi-exponential decay: high number of fitting parameters Dependence on initial conditions and hypothesis on the sample Limited number of components Slow Fit-free & unbiased representation Chemical species fingerprint Unlimited number components Ideal for high-throughput screening Straightforward interpretation of data Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis ω is the angular frequency of pulsed laser (80MHZ) Fourier Transform Time domain Frequency domain Digman et al. Biophysical J. 2008 Stringari et al. PNAS 2011          1 11 tan 1 2 m m      Phasor analysis of Fluorescence Lifetime Data LFD - Gratton Lab Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis •Multi-exponential lifetimes •All single exponential lifetimes lie on the “universal circle” Phasor lies on the straight line between the locations of the two single lifetime g s Digman et al. Biophys J. 2008 Phasor Properties Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Fluorescence Lifetime (FLIM) of NADH and FAD to probe environment (enzymatic binding) FAD Lifetime short lifetime: protein bound FAD Long lifetime: free FAD Protein-bound FAD is the very important for precancer discrimination NADH Lifetime Short lifetime (0.4 ns) : free NADH Long lifetime (2-3 ns) : protein-bound NADH Protein-bound NADH lifetime depends on enzymatic binding (NADH cycling through the energy production pathway) Glycolysis Oxidative Phosphorylation TCA Cycle glucose glucose pyruvate Acetyl CoA NAD+ NADH FAD FADH2 NADH lactate NAD+ ATP citrate Macromolecular biosynthesis H+ Fatty Acids Lipids O2 HO2 H+ ATP Skala et. al PNAS 2007 Free Bound NADH and FAD are the primary electron acceptor and electron donor in Oxidative Phosphorylation directly involved in ATP production and Redox stateof the cell Only NADH is involved in Glycolysis Walsh et al. Cancer Res; 2013 NADH and FAD are fluorescent while NAD+ and FADH2 are not 𝐅𝐀𝐃 𝐅𝐀𝐃 +𝐍𝐀𝐃𝐇 Optical Redox ratio: Glycolysis Oxidative phosphorylation Fatty Acid synthesis and oxidation Oxidative stress NAD(P)H and FAD: endogenous fluorophores for metabolic imaging Exc. Γ λem τ= 1/ (Γ+k) NADPH is mainly involved in the defense against ROS Lakowicz et al.. PNAS. 1992 Heikal at al. Biomark Med. 2010 Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Metabolic Imaging with intrinsic biomarker NADH and Fluorescence Lifetime Microscopy Protein-bound NADH Free NADH Time( ns) Intensity Glycolysis Oxidative Phosphorylation TCA Cycle glucose glucose pyruvate Acetyl CoA NAD+ NADH FAD FADH2 NADH lactate NAD+ ATP citrate Macromolecular biosynthesis H+ Fatty Acids Lipids O2 HO2 H+ ATP Nicotinamide adenine dinucleotide (NADH) Proliferating cell Glycolysis ++ Short NADH Lifetime Free NADH OxPhos ++ Long NADH Lifetime Bound NADH Resting cell Lakowicz et al.. PNAS. 1992 Heikal at al. Biomark Med. 2010 Bird et al Cancer Research 2005 Skala et al PNAS 2007 Stringari et al. PNAS. 2011 f2 f1 s fB NADH ∝𝒃𝒐𝒖𝒏𝒅 𝑵𝑨𝑫𝑯 𝒇𝒓𝒆𝒆 𝑵𝑨𝑫𝑯 ≈𝑵𝑨𝑫+ 𝑵𝑨𝑫𝑯 Stringari et al Sci Rep. 2017 Stringari . Phasor approach to fluorescence lifetime microscopy distinguishes different metabolic states of germ cells in a live tissue. PNAS 2011 Stringari et al. Metabolic trajectory of cellular differentiation in small intestine by Phasor Fluorescence Lifetime Microscopy of NADH. Sci Rep. 2012 Stringari et al. Multicolor two-photon imaging of endogenous fluorophores in living tissues by wavelength mixing. Sci Rep. 2017 Ung et al., Simultaneous NAD(P)H and FAD fluorescence lifetime microscopy of long UVA-induced metabolic stress in reconstructed human skin. Sci Rep. 2021 Sánchez-Ramírez, et al Coordinated metabolic transitions and gene expression by NAD+ during adipogenesis. Journal of Cell Biology 2022 Paillon et al. Label-free single-cell live imaging reveals fast metabolic switch in T lymphocytes. Mol Biol Cell. 2024 Sánchez-Ramírez, et al. Emerging Functional Connections Between Metabolism and Epigenetic Remodeling in Neural Differentiation. Mol Neurobiol (2024). Fraction of bound NADH NADH Intensity 0.65 0.4 20 µm Gottlieb, et al 2023 Biological Imaging •Label-free •non invasive •subcellular resolution (mitocondria, cytoplasm, nucleus) Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Metabolic Imaging with intrinsic biomarker NADH and Fluorescence Lifetime Microscopy Protein-bound NADH Free NADH Time( ns) Intensity Glycolysis Oxidative Phosphorylation TCA Cycle glucose glucose pyruvate Acetyl CoA NAD+ NADH FAD FADH2 NADH lactate NAD+ ATP citrate Macromolecular biosynthesis H+ Fatty Acids Lipids O2 HO2 H+ ATP Nicotinamide adenine dinucleotide (NADH) Proliferating cell Glycolysis ++ Short NADH Lifetime Free NADH OxPhos ++ Long NADH Lifetime Bound NADH Resting cell Lakowicz et al.. PNAS. 1992 Heikal at al. Biomark Med. 2010 Bird et al Cancer Research 2005 Skala et al PNAS 2007 Stringari et al. PNAS. 2011 f2 f1 s fB NADH ∝𝒃𝒐𝒖𝒏𝒅 𝑵𝑨𝑫𝑯 𝒇𝒓𝒆𝒆 𝑵𝑨𝑫𝑯 ≈𝑵𝑨𝑫+ 𝑵𝑨𝑫𝑯 Stringari et al Sci Rep. 2017 Stringari . Phasor approach to fluorescence lifetime microscopy distinguishes different metabolic states of germ cells in a live tissue. PNAS 2011 Stringari et al. Metabolic trajectory of cellular differentiation in small intestine by Phasor Fluorescence Lifetime Microscopy of NADH. Sci Rep. 2012 Stringari et al. Multicolor two-photon imaging of endogenous fluorophores in living tissues by wavelength mixing. Sci Rep. 2017 Ung et al., Simultaneous NAD(P)H and FAD fluorescence lifetime microscopy of long UVA-induced metabolic stress in reconstructed human skin. Sci Rep. 2021 Sánchez-Ramírez, et al Coordinated metabolic transitions and gene expression by NAD+ during adipogenesis. Journal of Cell Biology 2022 Paillon et al. Label-free single-cell live imaging reveals fast metabolic switch in T lymphocytes. Mol Biol Cell. 2024 Sánchez-Ramírez, et al. Emerging Functional Connections Between Metabolism and Epigenetic Remodeling in Neural Differentiation. Mol Neurobiol (2024). Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Bound NADH Stem Cells Differentiated cells Metabolic gradient z Free NADH Small Intestine Stringari et al. Sci Rep. 2012 •Label-free •non invasive •subcellular resolution (mitocondria, cytoplasm, nucleus) 800 1200 2PEF Excitation ~@750 nm NADH tdTomato 400 mCherry NAD(P)H Wavelength (nm) 1 0.6 0.2 600 500 NAD(P)H Intensity 0 250 [photons] LifeAct-mCherry Intensity 200 100 [photons] 20 µm 20 µm 600 Metabolic Imaging compatible with red staining Useful to simultaneously look at subcellular compartments or to identify a cell type in tissues Simultaneous two-photon excitation of NAD(P)H and a red fluorescence protein or dye Simultaneous collection of NAD(P)H fluorescence with a blue band pass filter and red fluorescence with red band pass filter Paillon et al. Label-free single-cell live imaging reveals fast metabolic switch in T lymphocytes. Mol Biol Cell. 2024 Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Metabolism Function Cancer (cell migration and metastasis) Immunometabolism (Immune cell activation) Stem cell differentiation (differentiation stage, lineage commitment) Development (lineage commitment, morphogenesis) Epigenetics (Chromatin dynamics and nuclear metabolism ) Neuroscience (neuron-glia coupling, neurodegeneration, brain activity, memory) Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis ~1 µm SCALE ~1-10 µm Intravital imaging In vivo diagnosis Single cell 500 µm-cm Mitochondria/Nucleus Patient derived spheroids and organoids Label-free metabolic imaging across scales: applications to Cancer 500 µm-1mm *non exhaustive bibliography Bird et al Cancer Research 2005 Walsh et al. Cancer Research 2015 van Horssen et al..Cell Mol Life Sci. 2013 Zhang et al. J Biophotonics. 2025 Trinh Cancers 2017 Wallrabe Sci.Rep 2018 Komorova Elife 2024 Shirshin PNAS 2022 Giacomarra et al in preparation, Cancer metabolic phenotype and heterogeneity, motility, migration, metastasis, tumor borders Morone et al. Sci Rep. 2020 Skala et al Pnas 2007 König K.. Methods Appl Fluoresc. 2020 Alfonso-Garcia et al J. Biophotonics et al. 2021 Suraci J. Biophotonics 2024 Hage J Biophotonics 2019 Pate K., Stringari C. et al. EMBO J. 2014 Walsh et al, Cancer Research 2014 Heatoe et al. Front Oncol. 2023 Davis, Nature Cell Biology 2020 Sohrabi et al Cell Report 2023 Surina et al Heliyon. 2023 Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis ~1 µm SCALE ~1-10 µm In vivo brain and ZF tail Single cell 500 µm-1mm Mitochondria/Nucleus Living tissue Engineered tissues Paillon, et al Mol Biol Cell. (2024) Alfonso-Garcia.Sci Rep.6, 25086. (2016) Smokelin, et al. J Biomed Opt. (2020). Sagar, et al. Neurophotonics. (2020) Walsh, et al Nat Biomed Eng (2021) Hu et al Biomedical Optics Express (2020) Pham et al. bioRxiv Datta et al. bioRxiv Asadipour et al, submitted Zhang et. al Sci Adv. 2024 Label-free metabolic imaging across scales: applications to immunometabolism 500 µm-1mm Bernier, et al..Nat Commun. (2020) Miskolci, et. (2022). Datta et al. bioRxiv Immune cell activation Cell classification Single cell heterogeneity (time and space) Immunoterapy (CAR T Cells) *non exhaustive bibliography Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis ~1 µm SCALE ~1-10 µm In vivo brain and spinal cord Single cell 500 µm-1mm Mitochondria/Nucleus Living tissue Engineered tissues Sánchez-Ramírez, et al In preparation Sánchez-Ramírez, et al.. Mol Neurobiol (2024) Stringari et al.. Plos One. 2012 Plotegher,et.FASEB (2012) Chakraborty et al. Sci Report (2016) Niederschweiberer et al. Front Mol Biosci.8, (2021) Asadipour et al, in preparation Zhang et. al Sci Adv. 2024 Bernier et al. Nat Commun. 2020 Chia. Opt Express. 2008 Cleland, J Neuroinflammation 2021 Bower at al. Optica 2018 Rishyashring, Optica 2024 Label-free metabolic imaging across scales: applications to the nervous system 500 µm-1mm Ung et al et al. in preparation Roussel et al. biorxiv Yaseen, e. a., Biomed Opt Express (2017) Gómez et al Neurophotonics. 2018 Kasischkle et al. Science 2004 neuron-glia coupling, neurodegeneration, brain activity, memory *non exhaustive bibliography Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Chiara Stringari Laboratory For Optics and Biosciences (LOB) Advanced Microscopies and Tissue Physiology École Polytechnique Institut Polytechnique Paris Fluorescence Lifetime Microscopy (FLIM) for label-free metabolic imaging of living tissues https://www.youtube.com/watch?v=WC1VOrVPWC4 Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Irene Georgakoudi Janet Sorrells Melissa Skala Stringari Chiara Ahmed Heikal Rupsa Datta Kevin Eliceiri Kayvan Samimi Kyle P Quinn .... Consensus Guidelines for Label-Free Optical Metabolic Imaging: Ensuring Accuracy and Reproducibility in Metabolic Profiling in press, JBO •Standardized protocols for label-free optical metabolic imaging using NAD(P)H and FAD FLIM measurement. •guidelines for calibration, normalization, and reproducible and accurate assessments of metabolic function in cells and tissues. •support translational applications in metabolic research, disease diagnostics, and therapeutic monitoring. FLIM analysis with opensource software: FLIMfit and FLUTE Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis FLIM Data Processing Processing times with a MacBook Air (M1, 2020, 8 GB Memory) for a phasor transformation of FLIM stacks are: ~0.7 s for a 256 x 256 images, ~1.1 s for a 512x512 images and ~3 s for a 1024 x 1024 images with 56 time beans each Data Processing b. Calibration with reference lifetime 𝑚𝑓= 𝑚𝑖∗ ∆𝑚 Δφ φf φimf mi 𝜑𝑓= 𝜑𝑖+ ∆𝜑 •Bin Width (ns): Duration of a single temporal bin of the time-domain FLIM acquisition •Laser Freq. (MHz): Laser repetition rate •Tau Ref. (ns): Known lifetime of the single-exponential reference sample •Harmonic:Integer multiple applied to calculate the Fourier transform Calibration with fluorophores with a known lifetime, e.g. Fluorescein (4 ns), Coumarin 6 (2.5 ns), Rodamine B (1.74 ns), or Rose Bengal (0.52 ns), or 0 ns lifetime of SHG signal from starch or KTP NPs Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis c. Median filter d. Intensity threshold A 3x3 convolutional median filter is applied n times to the phasor plot Changing the max and min of the intensity threshold Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Ranjit, S., et al., Fit-free analysis of fluorescence lifetime imaging data using the phasor approach. Nat Protoc, 2018. Median filter Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Saving results. Saved FLIM images and phasor plots (left) and applied filters (right) to create the mask and measurements of the average of g, s, TauPhase (TauP), TauModulation (TauM) and distance (right). Exporting results and batch processing Batch processing on multiple FLIM images Using the same parameters Typical processing times for the full analysis of one image (that includes phasor transformation, applications of filters, saving results, images and measurements) with a MacBook Air (M1, 2020, 8 GB Memory) are: ~1.8 s for a 256 x256 image ~2.5 s for a 512x512 image ~5.4 s for a 1024 x1024 image Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis a. Mapping of distance from mCherry in a 5-day post-fertilization (dpf) zebrafish embryo tail (H2B-mCherry line) in vivo. FLIM data in Zenodo repository https://zenodo.org/records/8324901 Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis b. FLIM analysis of NADH reveals intracellular metabolic heterogeneity in mesenchymal stromal cells. FLIM data in Zenodo repository https://zenodo.org/records/8324901 Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis c. Shift in the distance from free NADH in live cells upon metabolic treatment. Glycolysis Oxidative Phosphorylation TCA Cycle glucose glucose pyruvate Acetyl CoA NADH lactate NAD+ ATP citrate Macromolecular biosynthesis H+ Fatty Acids Lipids ATP Rotenone FLIM data in Zenodo repository https://zenodo.org/records/8324901 Future Developments 1. Direct import of the common FLIM file formats (.std, .fbd and .ptu) inside the Python code by using already available Python libraries and open-source codes 2. Integrate a fully automated calculation and mapping of fraction of molecules (with 2 known molecular species) 3. Add wavelet filter ( for low photon budget FLIM images) 4. Advanced features for metabolic imaging (global fit of phasor cloud; mitochondrial clustering) 5. Intermediary file format which encompasses matrices for Intensity, g and s coordinates. 6. Increase FLUTE speed 7. Adapt phasor analysis to typical time-gated sampling limitations 8. Advanced analysis tools such as, different filters, freehand cluster drawing, cluster analysis with Machine Learning, FRET trajectory estimation and calculation of absolute concentration of NADH. 9. Napari Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Acquisition time Acquisition time depends on: •Total number of photons and required lifetime accuracy, •number of pixels •Photon flux that can be obtained from the sample without photobleaching or photodamage. 10^6/s count rate (highly fluorescence samples) 10^4/s count rate (low fluorescence samples) Becker et al. Microsc Res Tech. 2004  N 1  320 x 320 ~10.000 pixels ~1000 photons: Acquisition time: ~ 10 -1000 sec Typical acquisition time for metabolic imaging of NADH: 100-200 µs per pixel 4. Adjust the average/accumulations/acquisition speed to reach the desired number of photons Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Phasor Plot N photons 100 500 1000 5000 SDV  t AetI  )( single exponential How many photons?  N 1  Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis     1 2 2 2 2 22 1 1 1 1 1                               r k r r k r r e k e ee e r k N  M. Kollner at al Chem Phys Letter 200, p199 (2000) σ2= variance of τ N= number of photon collected τ = lifetime of the fluorophore T= width of collection time window k= number of TCSPC bins within T r=T/ τ Error on TCSPC lifetime measurement  N 1  How many photons are necessary for fluorescence-lifetime measurements? Phasor Plot N photons 100 500 1000 5000 ns5.2 2  ns4.0 1  5.0 5.0 2 1     21 21 )(   tt eetI   double exponential )1( 10 5.2 4.0 12 1 2 1          ns ns Free Bound Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis 100 500 1000 5000 Photons 25.0 2  3.0 2  25.0 2  35.0 2  21 21 )(   tt eetI   double exponential How many photons? Δ=0.05 Δ=0.1 Free Bound 28th February: •Wavelength: 740nm •Laser Power: 4 and 10% (~4mW and ~10mW) •Accumulation: 20 •512 x 512 - 100 Hz (lines per second) •Total Dwell time (with accumulations): 115,2 μs Data collected during the GerBI FLIM Workshop 2024, 26.-29. Feb. 2024 https://zenodo.org/records/11371968 Hands on: FLIM metabolic data with different number of photons Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Bin width: 0.096 ns Laser freq: 80MHz ATTO488 lifetime: 4.18ns Calibration Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Power 4% Power 10% Power 4% Power 10% Mitochondria Nucleus Power 4% Power 10% Intensity Mitochondria Nucleus Intensity Intensity HeLa Cells Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Power 4% Power 10% Power 4% Power 10% Intensity HeLa Cells Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Power 4% Power 10% TauP (ns) HeLa Cells 1. General introduction (~15min )Intro on FLIM and Phasor analysis and Metabolic imaging 2. Intro on FLUTE (15 min) FLUTE features 3. Calibration Procedures and number of photons (15 min) 4. Demonstration and examples/ HANDS ON (30 min) 5. Questions and discussions (15 min) Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis Figure S5: Calibration of FLIM image (ZF-1100_noEF.tiff) using the SHG at 0 ns lifetime (starch SHG-IRF.tiff) as a calibration. Phasor transformation and plot are calculated at the first (A) and second (B) harmonic of the laser repetition rate. Multi harmonic phasor analysis with FLUTE Gottlieb et al (2023). FLUTE: A Python GUI for interactive phasor analysis of FLIM data. Biological Imaging, 1-22. Yuan and Stringari MiFOBIO 2025 : A-07 Analyzing FLIM data for metabolic imaging applications with Phasor Analysis