Phasor analysis of fluorescence lifetime data and its application

Lin Dan-Ying; Niu Jing-Jing; Liu Xiong-Bo; Zhang Xiao; Zhang Jiao; Yu Bin; Qu Jun-Le

doi:10.7498/aps.69.20200554

Abstract

Fluorescence lifetime imaging microscopy (FLIM) is widely used in biomedical, materials and other fields. It not only has strong specificity and high sensitivity, but also has the capability of quantitative measurement because the fluorescence lifetime is not affected by the intensity of excitation, the concentration of fluorophores and photobleaching, and consequently is able to monitor the changes of microenvironment and reflecting the interaction between molecules. However, its application is limited to some extent by the complexity of data analysis. In order to make FLIM technology more suitable for fast analysis of high-throughput data, a variety of new algorithms for fluorescence lifetime analysis have emerged in recent years, such as phasor analysis, maximum likelihood estimation, first-order moment, Bayesian analysis, and compressed sensing. Among them, the phasor analysis (PA) method obtains the fluorescence lifetime by converting the fitting in the time domain to the direct calculation in the frequency domain. Compared with traditional least-square fitting method, it is not only simpler and faster, but also more suitable for the case of low photon counts. In addition, in the PA approach to FLIM, the fluorescence decay is directly converted into a phasor diagram by simple mathematics, where the phasor points originating from different pixels in the image are represented by the positions in the phasor plot, and thus the graphical representation obtained by PA method is convenient for data visualization and cluster analysis. Therefore, it has become a simple and powerful analysis method for FLIM, and is increasingly favored by researchers. In this paper, the basic principle of PA method and how we can use it are described in detail. And on this basis, the latest application research progress of the method in cell metabolism state measurement, protein interaction study, cell microenvironment measurement, auxiliary pathological diagnosis, and resolution improvement in super-resolution imaging are introduced and summarized. The advantages of PA method in these FLIM applications are focused on, providing useful reference for the research in related fields. Finally, the phasor analysis method for FLIM data analysis and the development trend of its application are prospected.

Keywords:

Authors and contacts

Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China

Corresponding author: Lin Dan-Ying, dylin@szu.edu.cn ; Qu Jun-Le, jlqu@szu.edu.cn

Funds: Project supported by the National Key R&D Program of China (Grant No. 2017YFA0700500), the National Natural Science Foundation of China (Grant Nos. 61775144, 61975131, 61620106016, 61525503, 61835009), the (Key) Project of Department of Education of Guangdong Province, China (Grant No. 2016KCXTD007), the Natural Science Foundation of Guangdong Province, China (Grant No. 2018A030313362), and the Shenzhen Basic Research Project, China (Grant Nos. JCYJ20170818144012025, JCYJ20170818141701667, JCYJ20170412105003520)

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References

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[42]	林丹樱, 屈军乐 2017 66 148703 Google Scholar Lin D Y, Qu J L 2017 Acta Phys. Sin. 66 148703 Google Scholar

Cited By

图 1 荧光寿命的测量方法及相量分析(PA)法示意图　(a)频域法测量原理示意图; (b)单指数衰减的寿命相量示例图; (c)双指数衰减的寿命相量示例图; (d)时间相关单光子计数(TCSPC)测量原理示意图

Figure 1. Schematic diagram of fluorescence lifetime measurement and phasor analysis (PA):(a) Frequency domain method; (b) lifetime phasor of single-exponential decay; (c) lifetime phasor of bi-exponential decay; (d) time-correlated single photon counting (TCSPC) method.

DownLoad: Full-Size Img PowerPoint

图 2 Phasor-FLIM的应用思路示意图　(a)包含未处理寿命信息的荧光强度图; (b)经PA法分析得到的寿命相量图; (c)对寿命相量直接进行分析; (d)通过相量聚类分析和伪彩色标记得到的荧光寿命图

Figure 2. Schematic diagram of phasor-FLIM application:(a) Fluorescence intensity image with untreated lifetime information; (b) lifetime phasor plot obtained by PA analysis; (c) direct analysis of lifetime phasors; (d) phasor-mapped FLIM image based on phasor clustering analysis and pseudo-color assignment.

DownLoad: Full-Size Img PowerPoint

图 3 Phasor-FLIM 的应用分类示意图

Figure 3. Application classification diagram of phasor-FLIM.

DownLoad: Full-Size Img PowerPoint

图 4 Phasor-FLIM用于分析细胞在缺氧和线粒体毒性药物氰化钾刺激下NADH/NAD+比例的变化, 研究代谢状态的转变^[27]

Figure 4. Phasor-FLIM was used to analyze the change of NADH/NAD+ ratio under the stimulation of hypoxia and mitochondrial toxic drug potassium cyanide, for studying the change of metabolic state of cells^[27].

DownLoad: Full-Size Img PowerPoint

图 5 Phasor-FLIM用于定量测量RhoA-kRas单链生物传感器的荧光共振能量转移(FRET)效率, 研究蛋白互作^[28]

Figure 5. Phasor-FLIM was used in quantitative FRET efficiency detection of a RhoA-kRas single chain biosensor, studying interaction between proteins^[28].

DownLoad: Full-Size Img PowerPoint

图 6 Phasor-FLIM用于分析细胞在正常(静止)状态和氧化应激状态下pH值的变化^[32]

Figure 6. Phasor-FLIM was used to analyze the changes of pH value of cells in normal state (at rest) and under oxidative stress^[32].

DownLoad: Full-Size Img PowerPoint

图 7 Phasor-FLIM聚类分析和伪彩色标记用于增强H&E染色基底细胞癌(BCC)切片病理学特征的可视化, 可辅助病理诊断^[36]

Figure 7. Phasor-FLIM clustering analysis and pseudo-color assignment was used to enhance visualization of pathological features of basal cell carcinoma (BCC) sections stained with H&E, assisting pathological diagnosis^[36].

DownLoad: Full-Size Img PowerPoint

图 8 Phasor-FLIM聚类分析用于滤除受激辐射耗尽(STED)成像中环形擦除光区域的光子, 可辅助提升超分辨成像分辨率^[39]

Figure 8. Phasor-FLIM cluster analysis was used to filter out the photons in the annular depletion region in stimulated radiation depletion (STED) imaging, improving the resolution of super-resolution imaging^[39].

DownLoad: Full-Size Img PowerPoint

map

[1]	刘雄波, 林丹樱, 吴茜茜, 严伟, 罗腾, 杨志刚, 屈军乐 2018 67 178701 Google Scholar Liu X B, Lin D Y, Wu Q Q, Yan W, Luo T, Yang Z G, Qu J L 2018 Acta Phys. Sin. 67 178701 Google Scholar
[2]	Levchenko S M, Pliss A, Qu J 2018 J. Innovative Opt. Health Sci. 11 1730009 Google Scholar
[3]	刘超, 周燕, 王新伟, 刘育梁 2011 激光与光电子学进展 48 111102 Google Scholar Liu C, Zhou Y, Wang X, Liu Y 2011 Laser Optoelectron. Prog. 48 111102 Google Scholar
[4]	Fitzgerald C, Hosny N A, Tong H, Seville P C, Gallimore P J, Davidson N M, Athanasiadis A, Botchway S W, Ward A D, Kalberer M, Kuimov M K, Pope F D 2016 Phys. Chem. Chem. Phys. 18 21710 Google Scholar
[5]	Gratton E, Breusegem S, Sutin J, Ruan Q, Barry N 2003 J. Biomed. Opt. 8 38190
[6]	Suman R, Leonel M, Jameson D M, Gratton E 2018 Nat. Protoc. 13 1979 Google Scholar
[7]	Chessel A, Waharte F, Salamero J, Kervrann C 2013 21st European Signal Processing Conference Marrakech, Morocco, September 9–13, 2013 p1
[8]	徐玲玲 2013 博士学位论文 (武汉: 华中科技大学) Xu L L 2013 Ph. D. Dissertation (Wuhan: Huazhong University of Science and Technology) (in Chinese)
[9]	Rowley M I, Coolen A C C, Vojnovic B, Barber P R 2016 PLoS One 11 e0158404 Google Scholar
[10]	Yang S, Lee J, Lee Y, Lee M, Lee B U 2015 J. Biomed. Opt. 20 096003 Google Scholar
[11]	Liu X, Lin D, Becker W, Niu J, Yu B, Liu L, Qu J 2019 J. Innovative. Opt. Health Sci. 12 1930003 Google Scholar
[12]	Stefl M, James N G, Ross J A, Jameson D M 2011 Anal. Biochem. 410 62 Google Scholar
[13]	Jameson D M, Gratton E, Hall R D 1984 Appl. Spectrosc. Rev. 20 55 Google Scholar
[14]	Weber G 1981 J. Phys. Chem. B 85 949 Google Scholar
[15]	Redford G I, Clegg R M 2005 J. Fluoresc. 15 805 Google Scholar
[16]	Digman M A, Caiolfa V R, Zamai M, Gratton E 2008 Biophys. J. 94 L14 Google Scholar
[17]	Bird D K, Yan L, Vrotsos K M, Eliceiri K W, Vaughan E M, Keely P J, White J G, Ramanujam N 2005 Cancer Res. 65 8766 Google Scholar
[18]	Stringari C, Cinquin A, Cinquin O, Digman M A, Donovan P J, Gratton E 2011 Proc. Natl. Acad. Sci. U.S.A. 108 13582 Google Scholar
[19]	Stringari C, Edwards R A, Pate K T, Waterman M L, Donovan P J, Gratton E 2012 Sci. Rep. 2 568 Google Scholar
[20]	Stringari C, Donovan P, Gratton E 2012 Proc. SPIE San Francisco, CA January 22–24, 2012 p9
[21]	Lee D H, Li X, Ma N, Digman M A, Lee A P 2018 Lab Chip 18 1349 Google Scholar
[22]	Romero-López M, Trinh A L, Sobrino A, Hatch M M S, Keating M T, Fimbres C, Lewis D E, Gershon P D, Botvinick E L, Digman M, Lowengrub J S, Hughes C C W 2016 Biomaterials 116 118
[23]	Sameni S, Syed A, Marsh J L, Digman M A 2016 Sci. Rep. 6 34755 Google Scholar
[24]	Dong Y, Sameni1 S, Digman M A, Brewer G J 2019 Sci. Rep. 9 11274 Google Scholar
[25]	Dong Y, Digman M A, Brewer G J 2019 GeroScience 41 51 Google Scholar
[26]	Hato T, Winfree S, Day R, Sandoval R M, Molitoris B A, Yoder M C, Wiggins R C, Zheng Y, Dunn K W, Dagher P C 2017 J. Am. Soc. Nephrol. 28 2420 Google Scholar
[27]	Datta R, Heylman C, George S C, Gratton E 2016 Biomed. Opt. Express 7 1690 Google Scholar
[28]	Hinde E, Digman M A, Hahn K M, Hahn K M, Gratton E 2012 Microsc. Res. Tech. 75 271 Google Scholar
[29]	Hinde E, Digman M A, Hahn K M, Gratton E 2013 Proc. Natl. Acad. Sci. U.S.A. 110 135 Google Scholar
[30]	Lou J Q, Scipioni L, Wright B K, Bartolec T K, Zhang J, Masamsetti V P, Gaus K, Gratton E, Cesare A J, Hinde E 2019 Proc. Natl. Acad. Sci. U.S.A. 116 7323 Google Scholar
[31]	Chen H, Ma N, Kagawa K, Kawahito S, Digman M, Gratton E 2018 J. Biophotonics 12 e201800223
[32]	Battisti A, Digman M A, Gratton E, Storti B, Beltram F, Bizzarri R 2012 Chem. Commun. 48 5127 Google Scholar
[33]	Zhou T, Luo T, Song J, Qu J 2018 Anal. Chem. 90 2170 Google Scholar
[34]	Ferri G, Nucara L, Biver T, Battisti A, Signore G, Bizzarri R 2016 Biophys. J. 110 163a Google Scholar
[35]	Luo T, Lu Y, Liu S, Lin D, Qu J 2017 Anal. Chem. 89 8104 Google Scholar
[36]	Luo T, Lu Y, Liu S, Lin D, Qu J 2017 Anal. Chem. 89 9224 Google Scholar
[37]	Ranjit S, Dvornikov A, Levi M, Furgeson S, Gratton E 2016 Biomed. Opt. Express 7 3519 Google Scholar
[38]	Lanzanò L, Hernandez I C, Castello M, Gratton E, Diaspro A, Vicidomini G 2015 Nat. Commun. 6 6701 Google Scholar
[39]	Wang L, Chen B, Yan W, Yang Z, Peng X, Lin D, Weng X, Ye T, Qu J 2018 Nanoscale 10 16252 Google Scholar
[40]	Tortarolo G, Sun Y, Teng K W, Ishitsuka Y, Lanzano L, Selvin P R, Barbieri B, Diaspro A, Vicidomini G 2019 Nanoscale 11 1754 Google Scholar
[41]	周宇会, 魏九峰, 李国东, 刘明 2017 国际肿瘤学杂志 44 762 Google Scholar Zhou Y, Wei J, Li G, Liu M 2017 J. Int. Oco. 44 762 Google Scholar
[42]	林丹樱, 屈军乐 2017 66 148703 Google Scholar Lin D Y, Qu J L 2017 Acta Phys. Sin. 66 148703 Google Scholar

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