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Technology advances in genomics, proteomics, and metabolomics largely expanded the pool of potential therapeutic targets. Compared with the in vitro setting, cell-based screening assays have been playing a key role in the processes of drug discovery and development. Besides the commonly used strategies based on colorimetric and cell viability, we reason that methods that capture the dynamic cellular events will facilitate optimal hit identification with high sensitivity and specificity. Herein, we propose a live-cell screening strategy using structured illumination microscopy (SIM) combined with an automated cell colocalization analysis software, CellprofilerTM, to screen and discover drugs for mitochondria and lysosomes interaction at a nanoscale resolution in living cells. This strategy quantitatively benchmarks the mitochondria-lysosome interactions such as mitochondria and lysosomes contact (MLC) and mitophagy. The automatic quantitative analysis also resolves fine changes of the mitochondria-lysosome interaction in response to genetic and pharmacological interventions. Super-resolution live-cell imaging on the basis of quantitative analysis opens up new avenues for drug screening and development by targeting dynamic organelle interactions at the nanoscale resolution, which could facilitate optimal hit identification and potentially shorten the cycle of drug discovery.


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Nanoscale monitoring of mitochondria and lysosome interactions for drug screening and discovery

Show Author's information Qixin Chen1,2,3Xintian Shao1,2,3Zhiqi Tian3Yang Chen3Payel Mondal4Fei Liu1,2Fengshan Wang1Peixue Ling1,2( )Weijiang He5( )Kai Zhang4Zijian Guo5Jiajie Diao3( )
School of Pharmaceutical Sciences,Shandong University,Jinan,250101,China;
Shandong Academy of Pharmaceutical Science,Key Laboratory of Biopharmaceuticals, Engineering Laboratory of Polysaccharide Drugs, National-Local Joint Engineering Laboratory of Polysaccharide Drugs,Jinan,250101,China;
Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
State Key Laboratory of Coordination Chemistry,Coordination Chemistry Institute, School of Chemistry and Chemical Engineering, Nanjing University,Nanjing,210093,China;

Abstract

Technology advances in genomics, proteomics, and metabolomics largely expanded the pool of potential therapeutic targets. Compared with the in vitro setting, cell-based screening assays have been playing a key role in the processes of drug discovery and development. Besides the commonly used strategies based on colorimetric and cell viability, we reason that methods that capture the dynamic cellular events will facilitate optimal hit identification with high sensitivity and specificity. Herein, we propose a live-cell screening strategy using structured illumination microscopy (SIM) combined with an automated cell colocalization analysis software, CellprofilerTM, to screen and discover drugs for mitochondria and lysosomes interaction at a nanoscale resolution in living cells. This strategy quantitatively benchmarks the mitochondria-lysosome interactions such as mitochondria and lysosomes contact (MLC) and mitophagy. The automatic quantitative analysis also resolves fine changes of the mitochondria-lysosome interaction in response to genetic and pharmacological interventions. Super-resolution live-cell imaging on the basis of quantitative analysis opens up new avenues for drug screening and development by targeting dynamic organelle interactions at the nanoscale resolution, which could facilitate optimal hit identification and potentially shorten the cycle of drug discovery.

Keywords: mitochondria, drug screening, lysosome, mitophagy, structured illumination microscopy

References(57)

1

Bialer, M.; White, H. S. Key factors in the discovery and development of new antiepileptic drugs. Nat. Rev. Drug Discov. 2010, 9, 68-82.

2

Chen, Q. X.; Shao, X. T.; Ling, P. X.; Liu, F.; Han, G. Y.; Wang, F. S. Recent advances in polysaccharides for osteoarthritis therapy. Eur. J. Med. Chem. 2017, 139, 926-935.

3

Prasad, V.; Mailankody, S. Research and development spending to bring a single cancer drug to market and revenues after approval. JAMA Intern. Med. 2017, 177, 1569-1575.

4

Schulze, K.; Imbeaud, S.; Letouzé, E.; Alexandrov, L. B.; Calderaro, J.; Rebouissou, S.; Couchy, G.; Meiller, C.; Shinde, J.; Soysouvanh, F. et al. Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets. Nat. Genet. 2015, 47, 505-511.

5

Xu, D. C.; Jin, T. J.; Zhu, H.; Chen, H. B.; Ofengeim, D.; Zou, C. Y.; Mifflin, L.; Pan, L. F.; Amin, P.; Li, W. J. et al. TBK1 suppresses RIPK1-driven apoptosis and inflammation during development and in aging. Cell 2018, 174, 1477-1491. E19.

6

Han, M. H.; Hwang, S. I.; Roy, D. B.; Lundgren, D. H.; Price, J. V.; Ousman, S. S.; Fernald, G. H.; Gerlitz, B.; Robinson, W. H.; Baranzini, S. E. et al. Proteomic analysis of active multiple sclerosis lesions reveals therapeutic targets. Nature 2008, 451, 1076-1081.

7

Wishart, D. S. Emerging applications of metabolomics in drug discovery and precision medicine. Nat. Rev. Drug Discov. 2016, 15, 473-484.

8

Vega-Avila, E.; Pugsley, M. K. An overview of colorimetric assay methods used to assess survival or proliferation of mammalian cells. Proc. West. Pharmacol. Soc. 2011, 54, 10-14.

9

Chen, Q. X.; Mei, X. F.; Han, G. Y.; Ling, P. X.; Guo, B.; Guo, Y. W.; Shao, H. R.; Wang, G.; Cui, Z.; Bai, Y. X. et al. Xanthan gum protects rabbit articular chondrocytes against sodium nitroprusside-induced apoptosis in vitro. Carbohydr. Polym. 2015, 131, 363-369.

10

Chen, Q. X.; Shao, X. T.; Ling, P. X.; Liu, F.; Shao, H. R.; Ma, A. B.; Wu, J. X.; Zhang, W.; Liu, F. Y.; Han, G. Y. et al. Low molecular weight xanthan gum suppresses oxidative stress-induced apoptosis in rabbit chondrocytes. Carbohydr. Polym. 2017, 169, 255-263.

11

Frankfurt, O. S.; Krishan, A. Enzyme-linked immunosorbent assay (ELISA) for the specific detection of apoptotic cells and its application to rapid drug screening. J. Immunol. Methods 2001, 253, 133-144.

12

Krutzik, P. O.; Nolan, G. P. Fluorescent cell barcoding in flow cytometry allows high-throughput drug screening and signaling profiling. Nat. Methods 2006, 3, 361-368.

13

Krutzik, P. O.; Crane, J. M.; Clutter, M. R.; Nolan, G. P. High-content single-cell drug screening with phosphospecific flow cytometry. Nat. Chem. Biol. 2008, 4, 132-142.

14

Rudin, M.; Weissleder, R. Molecular imaging in drug discovery and development. Nat. Rev. Drug Discov. 2003, 2, 123-131.

15

Neefjes, J.; Dantuma, N. P. Fluorescent probes for proteolysis: Tools for drug discovery. Nat. Rev. Drug Discov. 2004, 3, 58-69.

16

Willets, K. A. Super-resolution imaging of SERS hot spots. Chem. Soc. Rev. 2014, 43, 3854-3864.

17

Jia, S.; Vaughan, J. C.; Zhuang, X. W. Isotropic three-dimensional super-resolution imaging with a self-bending point spread function. Nat. Photonics 2014, 8, 302-306.

18

Boutros, M.; Heigwer, F.; Laufer, C. Microscopy-based high-content screening. Cell 2015, 163, 1314-1325.

19

Usaj, M. M.; Styles, E. B.; Verster, A. J.; Friesen, H.; Boone, C.; Andrews, B. J. High-content screening for quantitative cell biology. Trends Cell Biol. 2016, 26, 598-611.

20

Liu, Z.; Lavis, L. D.; Betzig, E. Imaging live-cell dynamics and structure at the single-molecule level. Mol. Cell 2015, 58, 644-659.

21

Chen, Q. X.; Jin, C. Z.; Shao, X. T.; Guan, R. L.; Tian, Z. Q.; Wang, C. R.; Liu, F.; Ling, P. X.; Guan, J. L.; Ji, L. N. et al. Super-resolution tracking of mitochondrial dynamics with an iridium(Ⅲ) luminophore. Small 2018, 14, 1802166.

22

Hanne, J.; Falk, H. J.; Görlitz, F.; Hoyer, P.; Engelhardt, J.; Sahl, S. J.; Hell, S. W. STED nanoscopy with fluorescent quantum dots. Nat. Commun. 2015, 6, 7127.

23

Tian, X. H.; Liu, T. Y.; Fang, B.; Wang, A. D.; Zhang, M. Z.; Hussain, S.; Luo, L.; Zhang, R. L.; Zhang, Q.; Wu, J. Y. et al. Neun-specific fluorescent probe revealing neuronal nuclei protein and nuclear acids association in living neurons under STED nanoscopy. ACS Appl. Mater. Interfaces 2018, 10, 31959-31964.

24

Huang, X. S.; Fan, J. C.; Li, L. J.; Liu, H. S.; Wu, R. L.; Wu, Y.; Wei, L. S.; Mao, H.; Lal, A.; Xi, P. et al. Fast, long-term, super-resolution imaging with Hessian structured illumination microscopy. Nat. Biotechnol. 2018, 36, 451-459.

25

Sigal, Y. M.; Zhou, R. B.; Zhuang, X. W. Visualizing and discovering cellular structures with super-resolution microscopy. Science 2018, 361, 880-887.

26

Huang, B.; Wang, W. Q.; Bates, M.; Zhuang, X. W. Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy. Science 2008, 319, 810-813.

27

Ha, T.; Tinnefeld, P. Photophysics of fluorescent probes for single-molecule biophysics and super-resolution imaging. Annu. Rev. Phys. Chem. 2012, 63, 595-617.

28

Fernández-Suárez, M.; Ting, A. Y. Fluorescent probes for super-resolution imaging in living cells. Nat. Rev. Mol. Cell Biol. 2008, 9, 929-943.

29

Onnis, A.; Cianfanelli, V.; Cassioli, C.; Samardzic, D.; Pelicci, P. G.; Cecconi, F.; Baldari, C. T. The pro-oxidant adaptor p66SHC promotes B cell mitophagy by disrupting mitochondrial integrity and recruiting LC3-Ⅱ. Autophagy 2018, 14, 2117-2138.

30

Wong, Y. C.; Ysselstein, D.; Krainc, D. Mitochondria-lysosome contacts regulate mitochondrial fission via RAB7 GTP hydrolysis. Nature 2018, 554, 382-386.

31

Burbulla, L. F.; Song, P. P.; Mazzulli, J. R.; Zampese, E.; Wong, Y. C.; Jeon, S.; Santos, D. P.; Blanz, J.; Obermaier, C. D.; Strojny, C. et al. Dopamine oxidation mediates mitochondrial and lysosomal dysfunction in Parkinson's disease. Science 2017, 357, 1255-1261.

32

Tian, Z. Q.; Gong, J. H.; Crowe, M.; Lei, M.; Li, D. C.; Ji, B. H.; Diao, J. J. Biochemical studies of membrane fusion at the single-particle level. Prog. Lipid Res. 2019, 73, 92-100.

33

Liu, K.; Lee, J.; Ou, J. H. J. Autophagy and mitophagy in hepatocarcinogenesis. Mol. Cell. Oncol. 2018, 5, e1405142.

34

Lamprecht, M. R.; Sabatini, D. M.; Carpenter, A. E. CellProfilerTM: Free, versatile software for automated biological image analysis. Biotechniques 2007, 42, 71-75.

35

Kamentsky, L.; Jones, T. R.; Fraser, A.; Bray, M. A.; Logan, D. J.; Madden, K. L.; Ljosa, V.; Rueden, C.; Eliceiri, K. W.; Carpenter, A. E. Improved structure, function and compatibility for CellProfiler: Modular high-throughput image analysis software. Bioinformatics 2011, 27, 1179-1180.

36

Kobayashi, S.; Liang, Q. R. Autophagy and mitophagy in diabetic cardiomyopathy. Biochim. Biophys. Acta 2015, 1852, 252-261.

37

Ryan, B. J.; Hoek, S.; Fon, E. A.; Wade-Martins, R. Mitochondrial dysfunction and mitophagy in Parkinson's: From familial to sporadic disease. Trends Biochem. Sci. 2015, 40, 200-210.

38

Burchell, V. S.; Nelson, D. E.; Sanchez-Martinez, A.; Delgado-Camprubi, M.; Ivatt, R. M.; Pogson, J. H.; Randle, S. J.; Wray, S.; Lewis, P. A.; Houlden, H. et al. The Parkinson's disease-linked proteins Fbxo7 and Parkin interact to mediate mitophagy. Nat. Neurosci. 2013, 16, 1257-1265.

39

Youle, R. J.; Narendra, D. P. Mechanisms of mitophagy. Nat. Rev. Mol. Cell Biol. 2011, 12, 9-14.

40

Li, H. Y.; Ham, A.; Ma, T. C.; Kuo, S. H.; Kanter, E.; Kim, D.; Ko, H. S.; Quan, Y.; Sardi, S. P.; Li, A. Q. Mitochondrial dysfunction and mitophagy defect triggered by heterozygous GBA mutations. Autophagy 2019, 15, 113-130.

41

Williams, J. A.; Ni, H. M.; Ding, W. X. Mitochondrial dynamics, mitophagy and mitochondrial spheroids in drug-induced liver injury. In Mitochondria in Liver Disease. Han, D.; Kaplowitz, N., Eds.; Apple Academic Press Inc. : Florida, 2015; pp 237.

42

Maldonado, E. N.; Gooz, M.; DeHart, D. N.; Lemasters, J. J. VDAC opening drugs to induce mitochondrial dysfunction and cell death. Biophys. J. 2015, 108, 369a.

43

Barutcu, S. A.; Girnius, N.; Vernia, S.; Davis, R. J. Role of the MAPK/ cJun NH2-terminal kinase signaling pathway in starvation-induced autophagy. Autophagy 2018, 14, 1586-1595.

44

Wallot-Hieke, N.; Verma, N.; Schlütermann, D.; Berleth, N.; Deitersen, J.; Böhler, P.; Stuhldreier, F.; Wu, W. X.; Seggewiß, S.; Peter, C. et al. Systematic analysis of ATG13 domain requirements for autophagy induction. Autophagy 2018, 14, 743-763.

45

Liu, F.; Guan, J. L. FIP200, an essential component of mammalian autophagy is indispensible for fetal hematopoiesis. Autophagy 2011, 7, 229-230.

46

Lazarou, M.; Sliter, D. A.; Kane, L. A.; Sarraf, S. A.; Wang, C. X.; Burman, J. L.; Sideris, D. P.; Fogel, A. I.; Youle, R. J. The ubiquitin kinase PINK1 recruits autophagy receptors to induce mitophagy. Nature 2015, 524, 309-314.

47

Li, F. X.; Xu, D. C.; Wang, Y. L.; Zhou, Z. X.; Liu, J. P.; Hu, S. C.; Gong, Y. K.; Yuan, J. Y.; Pan, L. F. Structural insights into the ubiquitin recognition by OPTN (optineurin) and its regulation by TBK1-mediated phosphorylation. Autophagy 2018, 14, 66-79.

48

Youle, R. J.; Van Der Bliek, A. M. Mitochondrial fission, fusion, and stress. Science 2012, 337, 1062-1065.

49

Novak, I. Mitophagy: A complex mechanism of mitochondrial removal. Antioxid. Redox Signal. 2012, 17, 794-802.

50

Vakifahmetoglu-Norberg, H.; Xia, H. G.; Yuan, J. Y. Pharmacologic agents targeting autophagy. J. Clin. Invest. 2015, 125, 5-13.

51

Xu, Y. Q.; Yuan, J. Y.; Lipinski, M. M. Live imaging and single-cell analysis reveal differential dynamics of autophagy and apoptosis. Autophagy 2013, 9, 1418-1430.

52

Cristofani, R.; Marelli, M. M.; Cicardi, M. E.; Fontana, F.; Marzagalli, M.; Limonta, P.; Poletti, A.; Moretti, R. M. Dual role of autophagy on docetaxel-sensitivity in prostate cancer cells. Cell Death Dis. 2018, 9, 889.

53

Mauthe, M.; Orhon, I.; Rocchi, C.; Zhou, X. D.; Luhr, M.; Hijlkema, K. J.; Coppes, R. P.; Engedal, N.; Mari, M.; Reggiori, F. Chloroquine inhibits autophagic flux by decreasing autophagosome-lysosome fusion. Autophagy 2018, 14, 1435-1455.

54

Quintana-Cabrera, R.; Quirin, C.; Glytsou, C.; Corrado, M.; Urbani, A.; Pellattiero, A.; Calvo, E.; Vázquez, J.; Enríquez, J. A.; Gerle, C. et al. The cristae modulator Optic atrophy 1 requires mitochondrial ATP synthase oligomers to safeguard mitochondrial function. Nat. Commun. 2018, 9, 3399.

55

Chen, Q. X.; Shao, X. T.; Hao, M. G.; Tian, Z. Q.; Wang, C. R.; Liu, F.; Zhang, K.; Wang, F. S.; Ling, P. X.; Guan, J. L. et al. Quantitative analysis of interactive behavior of mitochondria and lysosomes using structured illumination microscopy. 2018, bioRxiv: https://doi.org/10.1101/445841.

56

Zemanová, L.; Schenk, A.; Valler, M. J.; Nienhaus, G. U.; Heilker, R. Confocal optics microscopy for biochemical and cellular high-throughput screening. Drug Discov. Today 2003, 8, 1085-1093.

57

Simm, J.; Klambauer, G.; Arany, A.; Steijaert, M.; Wegner, J. K.; Gustin, E.; Chupakhin, V.; Chong, Y. T.; Vialard, J.; Buijnsters, P. et al. Repurposing high-throughput image assays enables biological activity prediction for drug discovery. Cell Chem. Biol. 2018, 25, 611-618. e3.

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Publication history
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Acknowledgements

Publication history

Received: 25 October 2018
Revised: 03 February 2019
Accepted: 04 February 2019
Published: 11 March 2019
Issue date: May 2019

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© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Acknowledgements

Acknowledgements

This research was supported by the National Basic Research Program of China (No. 2015CB856300), Natural Science Foundation of Shandong Province (Nos. ZR2017PH072, ZR2017BH051, and ZR2015QL007), and Key Research and Development Plan of Shandong Province (No. 2018GSF121033). K. Z. was supported by the University of Illinois at Urbana-Champaign. The Light Microscopy Imaging Center (LMIC) is supported in part with funds from Indiana University Office of the Vice Provost for Research. The 3D-SIM microscope was provided by NIH grant NIH1S10OD024988-01.

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