FLIMPA: A versatile software for Fluorescence Lifetime Imaging Microscopy Phasor Analysis
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Abstract
Fluorescence lifetime imaging microscopy (FLIM) is an advanced microscopy technique capable of providing a deeper understanding of the molecular environment of a fluorophore. While FLIM data were traditionally analysed through the exponential fitting of the fluorophores’ emission decays, the use of phasor plots is increasingly becoming the preferred standard. This is due to their ability to visualise the distribution of fluorescent lifetimes within a sample, offering insights into molecular interactions in the sample without the need for model assumptions regarding the exponential decay behaviour of the fluorophores. However, so far most researchers have had to rely on commercial phasor plot software packages, which are closed-source and rely on proprietary data formats. In this paper, we introduce FLIMPA, an opensource, stand-alone software for phasor plot analysis that provides many of the features found in commercial software, and more. FLIMPA is fully developed in Python and offers advanced tools for data analysis and visualisation. It enhances FLIM data comparison by integrating phasor points from multiple trials and experimental conditions into a single plot, while also providing the possibility to explore detailed, localised insights within individual samples. We apply FLIMPA to introduce a cell-based assay for the quantification of microtubule depolymerisation, measured through fluorescence lifetime changes of SiR-tubulin, in response to various concentrations of Nocodazole, a microtubule depolymerising drug relevant to anti-cancer treatment.
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indicating that 10 µM Nocodazole is enough to completely destabilise the microtubules
I understand the logic, but how can you be sure that a plateau in the increase in fluorescence lifetime means that the microtubules have completely depolymerized?
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FLIMPA’s GitHub repository.
Could you please provide a link to the GitHub repository? Is it publicly available yet?
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Figure 6
This is a very cool visualization! The choice of the colormap is, however, not the most intuitive, especially given that the same color is used to represent different concentrations in different panels.
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individual identity masks
What is meant by "identity" masks? I understand these masks to be based on either the lifetime or the number of photons per pixel, what does identity mean in this context?
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This is the first application of FLIM for building a cell-based assay for measuring drug-induced microtubule destabilisation.
This seems like a great case study for showcasing your software! But if you are going to make this claim, could you explain how or why reference [35] is not the first? Given that you also say:
Changes in the fluorescence lifetime of SiR-tubulin following the addition of Nocodazole have been used to quantify the degree of microtubule depolymerisation [35].
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Recently, the open-source Python-based software, FLUTE [28], a Napari-Live-FLIM plugin [29], and Phasor identifier [30] have been published
While I don't think it has been published yet, there is also PhasorPy, which is an open-source, Python-based library for doing phasor analysis.
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