Autofluorescence spectroscopy in redox monitoring across cell confluencies
Autoři:
Derrick Yong aff001; Ahmad Amirul Abdul Rahim aff001; Chaw Su Thwin aff001; Sixun Chen aff001; Weichao Zhai aff001; May Win Naing aff001
Působiště autorů:
Bio-Manufacturing Group, Singapore Institute of Manufacturing Technology, Singapore, Singapore
aff001
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0226757
Souhrn
Patient-specific therapies require that cells be manufactured in multiple batches of small volumes, making it a challenge for conventional modes of quality control. The added complexity of inherent variability (even within batches) necessitates constant monitoring to ensure comparable end products. Hence, it is critical that new non-destructive modalities of cell monitoring be developed. Here, we study, for the first time, the use of optical spectroscopy in the determination of cellular redox across cell confluencies by exploiting the autofluorescence properties of molecules found natively within cells. This was achieved through a simple retrofitting of a standard inverted fluorescence microscope with a spectrometer output and an appropriate fluorescence filter cube. Through spectral decomposition on the acquired autofluorescence spectra, we are able to further discern the relative contributions of the different molecules, namely flavin adenine dinucleotide (FAD) and reduced nicotinamide adenine dinucleotide (NADH). This is then quantifiable as redox ratios (RR) that represent the extent of oxidation to reduction based upon the optically measured quantities of FAD and NADH. Results show that RR decreases with increasing cell confluency, which we attribute to several inter-related cellular processes. We validated the relationship between RR, metabolism and cell confluency through bio-chemical and viability assays. Live-dead and DNA damage studies were further conducted to substantiate that our measurement process had negligible effects on the cells. In this study, we demonstrate that autofluorescence spectroscopy-derived RR can serve as a rapid, non-destructive and label-free surrogate to cell metabolism measurements. This was further used to establish a relationship between cell metabolism and cellular redox across cell confluencies, and could potentially be employed as an indicator of quality in cell therapy manufacturing.
Klíčová slova:
Cell metabolism – Cell viability testing – DNA damage – Fluorescence – Fluorescence microscopy – Glucose metabolism – Oxidation-reduction reactions – Silicones
Zdroje
1. Buzhor E, Leshansky L, Blumenthal J, Barash H, Warshawsky D, Mazor Y, et al. Cell-based therapy approaches: the hope for incurable diseases. Regenerative Medicine. 2014;9(5):649–672. doi: 10.2217/rme.14.35 25372080
2. Lipsitz YY, Timmins NE, Zandstra PW. Quality cell therapy manufacturing by design. Nature Biotechnology. 2016;34(4):393–400. doi: 10.1038/nbt.3525 27054995
3. Roh KH, Nerem RM, Roy K. Biomanufacturing of Therapeutic Cells: State of the Art, Current Challenges, and Future Perspectives. Annual Review of Chemical and Biomolecular Engineering. 2016;7(1):455–478. doi: 10.1146/annurev-chembioeng-080615-033559 27276552
4. Heathman TRJ, Rafiq QA, Chan AKC, Coopman K, Nienow AW, Kara B, et al. Characterization of human mesenchymal stem cells from multiple donors and the implications for large scale bioprocess development. Biochemical Engineering Journal. 2016;108:14–23. doi: 10.1016/j.bej.2015.06.018
5. Food U, Administration D. FDA Guidance for Industry: PAT—A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance. Rockville, MD: US Food and Drug Administration; 2004.
6. Wu YY, Yong D, Win Naing M. Automated Cell Expansion: Trends & Outlook of Critical Technologies. Cell Gene Therapy Insights. 2018;4(9):843–863. doi: 10.18609/cgti.2018.087
7. Teixeira AP, Oliveira R, Alves PM, Carrondo MJT. Advances in on-line monitoring and control of mammalian cell cultures: Supporting the PAT initiative. Biotechnology Advances. 2009;27(6):726–732. doi: 10.1016/j.biotechadv.2009.05.003 19450676
8. Claßen J, Aupert F, Reardon KF, Solle D, Scheper T. Spectroscopic sensors for in-line bioprocess monitoring in research and pharmaceutical industrial application. Analytical and Bioanalytical Chemistry. 2017;409(3):651–666. doi: 10.1007/s00216-016-0068-x 27900421
9. Butler HJ, Ashton L, Bird B, Cinque G, Curtis K, Dorney J, et al. Using Raman spectroscopy to characterize biological materials. Nature Protocols. 2016;11(4):664–687. doi: 10.1038/nprot.2016.036 26963630
10. Croce AC, Bottiroli G. Autofluorescence Spectroscopy for Monitoring Metabolism in Animal Cells and Tissues. In: Pellicciari C, Biggiogera M, editors. Histochemistry of Single Molecules: Methods and Protocols. New York, NY: Springer New York; 2017. p. 15–43.
11. Ghukasyan VV, Heikal AA, editors. Natural Biomarkers for Cellular Metabolism: Biology, Techniques, and Applications. Series in Cellular and Clinical Imaging. CRC Press; 2014.
12. Chance B, Cohen P, Jobsis F, Schoener B. Intracellular oxidation-reduction states in vivo. Science. 1962;137(3529):499–508. doi: 10.1126/science.137.3529.499 13878016
13. Croce AC, Bottiroli G. Autofluorescence Spectroscopy and Imaging: A Tool for Biomedical Research and Diagnosis. European Journal of Histochemistry: EJH. 2014;58(4):2461. doi: 10.4081/ejh.2014.2461 25578980
14. Rice WL, Kaplan DL, Georgakoudi I. Two-Photon Microscopy for Non-Invasive, Quantitative Monitoring of Stem Cell Differentiation. PLOS ONE. 2010;5(4):e10075. doi: 10.1371/journal.pone.0010075 20419124
15. Quinn KP, Sridharan GV, Hayden RS, Kaplan DL, Lee K, Georgakoudi I. Quantitative metabolic imaging using endogenous fluorescence to detect stem cell differentiation. Scientific Reports. 2013;3:3432. doi: 10.1038/srep03432 24305550
16. Skala MC, Riching KM, Gendron-Fitzpatrick A, Eickhoff J, Eliceiri KW, White JG, et al. In vivo multiphoton microscopy of NADH and FAD redox states, fluorescence lifetimes, and cellular morphology in precancerous epithelia. Proceedings of the National Academy of Sciences. 2007;104(49):19494–19499. doi: 10.1073/pnas.0708425104
17. Miller JP, Habimana-Griffin L, Edwards TS, Achilefu S. Multimodal fluorescence molecular imaging for in vivo characterization of skin cancer using endogenous and exogenous fluorophores. Journal of Biomedical Optics. 2017;22:7. doi: 10.1117/1.JBO.22.6.066007
18. Shi L, Lu L, Harvey G, Harvey T, Rodríguez-Contreras A, Alfano RR. Label-Free Fluorescence Spectroscopy for Detecting Key Biomolecules in Brain Tissue from a Mouse Model of Alzheimer’s Disease. Scientific Reports. 2017;7(1):2599. doi: 10.1038/s41598-017-02673-5 28572632
19. Huang S, Heikal AA, Webb WW. Two-Photon Fluorescence Spectroscopy and Microscopy of NAD(P)H and Flavoprotein. Biophysical Journal. 2002;82(5):2811–2825. doi: 10.1016/S0006-3495(02)75621-X 11964266
20. Lakowicz JR, Szmacinski H, Nowaczyk K, Johnson ML. Fluorescence lifetime imaging of free and protein-bound NADH. Proceedings of the National Academy of Sciences of the United States of America. 1992;89(4):1271–1275. doi: 10.1073/pnas.89.4.1271 1741380
21. Blacker TS, Mann ZF, Gale JE, Ziegler M, Bain AJ, Szabadkai G, et al. Separating NADH and NADPH fluorescence in live cells and tissues using FLIM. Nature Communications. 2014;5. doi: 10.1038/ncomms4936 24874098
22. Gosnell ME, Anwer AG, Mahbub SB, Menon Perinchery S, Inglis DW, Adhikary PP, et al. Quantitative non-invasive cell characterisation and discrimination based on multispectral autofluorescence features. Scientific Reports. 2016;6:23453. doi: 10.1038/srep23453 27029742
23. Croce AC, Spano A, Locatelli D, Barni S, Sciola L, Bottiroli G. Dependence of Fibroblast Autofluorescence Properties on Normal and Transformed Conditions. Role of the Metabolic Activity. Photochemistry and Photobiology. 1999;69(3):364–374. doi: 10.1562/0031-8655(1999)069<0364:dofapo>2.3.co;2 10089830
24. Heikal AA. Intracellular coenzymes as natural biomarkers for metabolic activities and mitochondrial anomalies. Biomarkers in Medicine. 2010;4(2):241–263. doi: 10.2217/bmm.10.1 20406068
25. Georgakoudi I, Quinn KP. Optical Imaging Using Endogenous Contrast to Assess Metabolic State. Annual Review of Biomedical Engineering. 2012;14(1):351–367. doi: 10.1146/annurev-bioeng-071811-150108 22607264
26. Paull TT, Rogakou EP, Yamazaki V, Kirchgessner CU, Gellert M, Bonner WM. A critical role for histone H2AX in recruitment of repair factors to nuclear foci after DNA damage. Current Biology. 2000;10(15):886–895. doi: 10.1016/s0960-9822(00)00610-2 10959836
27. Aw TY. Cellular Redox: A Modulator of Intestinal Epithelial Cell Proliferation. Physiology. 2003;18(5):201–204. doi: 10.1152/nips.01448.2003
28. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation. Science. 2009;324(5930):1029–1033. doi: 10.1126/science.1160809 19460998
29. Quinn KP, Bellas E, Fourligas N, Lee K, Kaplan DL, Georgakoudi I. Characterization of metabolic changes associated with the functional development of 3D engineered tissues by non-invasive, dynamic measurement of individual cellular redox ratios. Biomaterials. 2012;33(21):5341–5348. doi: 10.1016/j.biomaterials.2012.04.024 22560200
30. Folmes CDL, Nelson TJ, Dzeja PP, Terzic A. Energy metabolism plasticity enables stemness programs. Annals of the New York Academy of Sciences. 2012;1254(1):82–89. doi: 10.1111/j.1749-6632.2012.06487.x 22548573
31. Jones DP. Extracellular Redox State: Refining the Definition of Oxidative Stress in Aging. Rejuvenation Research. 2006;9(2):169–181. doi: 10.1089/rej.2006.9.169 16706639
32. Friedman JR, Nunnari J. Mitochondrial form and function. Nature. 2014;505(7483):335–343. doi: 10.1038/nature12985 24429632
33. Westermann B. Bioenergetic role of mitochondrial fusion and fission. Biochimica et Biophysica Acta (BBA)—Bioenergetics. 2012;1817(10):1833–1838. doi: 10.1016/j.bbabio.2012.02.033
34. Picard M, Turnbull DM. Linking the Metabolic State and Mitochondrial DNA in Chronic Disease, Health, and Aging. Diabetes. 2013;62(3):672. doi: 10.2337/db12-1203 23431006
35. Menon SG, Sarsour EH, Spitz DR, Higashikubo R, Sturm M, Zhang H, et al. Redox Regulation of the G1 to S Phase Transition in the Mouse Embryo Fibroblast Cell Cycle. Cancer Research. 2003;63(9):2109–2117. 12727827
36. Sonnaert M, Papantoniou I, Luyten FP, Schrooten JI. Quantitative Validation of the Presto Blue Metabolic Assay for Online Monitoring of Cell Proliferation in a 3D Perfusion Bioreactor System. Tissue Engineering Part C: Methods. 2015;21(6):519–529. doi: 10.1089/ten.tec.2014.0255
37. Hervera A, Santos CX, De Virgiliis F, Shah AM, Di Giovanni S. Paracrine Mechanisms of Redox Signalling for Postmitotic Cell and Tissue Regeneration. Trends in Cell Biology. 2019;29(6):514–530. doi: 10.1016/j.tcb.2019.01.006 30795898
38. Rastogi RP, Richa Kumar A, Tyagi MB, Sinha RP. Molecular mechanisms of ultraviolet radiation-induced DNA damage and repair. Journal of nucleic acids. 2010;2010:592980–592980. doi: 10.4061/2010/592980 21209706
39. Rösner J, Liotta A, Angamo EA, Spies C, Heinemann U, Kovács R. Minimizing photodecomposition of flavin adenine dinucleotide fluorescence by the use of pulsed LEDs. Journal of Microscopy. 2016;264(2):215–223. doi: 10.1111/jmi.12436 27368071
40. Young EWK, Berthier E, Beebe DJ. Assessment of enhanced autofluorescence and impact on cell microscopy for microfabricated thermoplastic devices. Analytical chemistry. 2013;85(1):44–49. doi: 10.1021/ac3034773 23249264
41. Zipfel WR, Williams RM, Webb WW. Nonlinear magic: multiphoton microscopy in the biosciences. Nature Biotechnology. 2003;21(11):1369–1377. doi: 10.1038/nbt899 14595365
42. Duveneck GL, Bopp MA, Ehrat M, Balet LP, Haiml M, Keller U, et al. Two-photon fluorescence excitation of macroscopic areas on planar waveguides. Biosensors and Bioelectronics. 2003;18(5):503–510. doi: 10.1016/s0956-5663(03)00006-x 12706556
43. Trachootham D, Lu W, Ogasawara MA, Nilsa RDV, Huang P. Redox regulation of cell survival. Antioxidants & redox signaling. 2008;10(8):1343–1374. doi: 10.1089/ars.2007.1957
44. Jeong EM, Yoon JH, Lim J, Shin JW, Cho AY, Heo J, et al. Real-Time Monitoring of Glutathione in Living Cells Reveals that High Glutathione Levels Are Required to Maintain Stem Cell Function. Stem Cell Reports. 2018;10(2):600–614. doi: 10.1016/j.stemcr.2017.12.007 29307581
45. Rosa V, Eva JG, Gaia S, Paolo M. Oxidative Stress in Mesenchymal Stem Cell Senescence: Regulation by Coding and Noncoding RNAs. Antioxidants & Redox Signaling. 2018;29(9):864–879. doi: 10.1089/ars.2017.7294
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