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Journal articles on the topic 'Quantitative live-imaging'

Author: Grafiati

Published: 25 May 2024

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1

Tany, Ryosuke, Yuhei Goto, Yohei Kondo, and Kazuhiro Aoki. "Quantitative live-cell imaging of GPCR downstream signaling dynamics." Biochemical Journal 479, no. 8 (April 21, 2022): 883–900. http://dx.doi.org/10.1042/bcj20220021.

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G-protein-coupled receptors (GPCRs) play an important role in sensing various extracellular stimuli, such as neurotransmitters, hormones, and tastants, and transducing the input information into the cell. While the human genome encodes more than 800 GPCR genes, only four Gα-proteins (Gαs, Gαi/o, Gαq/11, and Gα12/13) are known to couple with GPCRs. It remains unclear how such divergent GPCR information is translated into the downstream G-protein signaling dynamics. To answer this question, we report a live-cell fluorescence imaging system for monitoring GPCR downstream signaling dynamics. Genetically encoded biosensors for cAMP, Ca2+, RhoA, and ERK were selected as markers for GPCR downstream signaling, and were stably expressed in HeLa cells. GPCR was further transiently overexpressed in the cells. As a proof-of-concept, we visualized GPCR signaling dynamics of five dopamine receptors and 12 serotonin receptors, and found heterogeneity between GPCRs and between cells. Even when the same Gα proteins were known to be coupled, the patterns of dynamics in GPCR downstream signaling, including the signal strength and duration, were substantially distinct among GPCRs. These results suggest the importance of dynamical encoding in GPCR signaling.

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2

Grossmann, Guido, Melanie Krebs, Alexis Maizel, Yvonne Stahl, Joop E. M. Vermeer, and Thomas Ott. "Green light for quantitative live-cell imaging in plants." Journal of Cell Science 131, no. 2 (December 20, 2017): jcs209270. http://dx.doi.org/10.1242/jcs.209270.

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3

Youn, Yeoan, Yongjae Lee, Gloria W. Lau, and Paul R. Selvin. "Quantitative DNA-paint imaging of AMPA receptors in live neurons." Biophysical Journal 121, no. 3 (February 2022): 141a. http://dx.doi.org/10.1016/j.bpj.2021.11.2028.

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4

Woehler, Andrew. "Simultaneous Quantitative Live Cell Imaging of Multiple FRET-Based Biosensors." PLoS ONE 8, no. 4 (April 16, 2013): e61096. http://dx.doi.org/10.1371/journal.pone.0061096.

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5

Lambert, Talley J., and Jennifer C. Waters. "Choosing a Fluorescence Microscopy Imaging Modality for Live Quantitative Experiments." Microscopy and Microanalysis 20, S3 (August 2014): 2122–23. http://dx.doi.org/10.1017/s1431927614012343.

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6

Trivedi, Vikas, Yuwei Li, Thai V. Truong, David Koos, Chuong Cheng-Ming, Rex Moats, and Scott E. Fraser. "How Embryonic Cartilage Grows: Insights Gained from Quantitative Live Imaging." Biophysical Journal 106, no. 2 (January 2014): 575a. http://dx.doi.org/10.1016/j.bpj.2013.11.3188.

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7

Burgess, Andrew, Thierry Lorca, and Anna Castro. "Quantitative Live Imaging of Endogenous DNA Replication in Mammalian Cells." PLoS ONE 7, no. 9 (September 20, 2012): e45726. http://dx.doi.org/10.1371/journal.pone.0045726.

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8

Rudkouskaya, Alena, Nattawut Sinsuebphon, Jamie Ward, Kate Tubbesing, Xavier Intes, and Margarida Barroso. "Quantitative imaging of receptor-ligand engagement in intact live animals." Journal of Controlled Release 286 (September 2018): 451–59. http://dx.doi.org/10.1016/j.jconrel.2018.07.032.

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9

Plant, Anne L., Michael Halter, and Jeffrey Stinson. "Probing pluripotency gene regulatory networks with quantitative live cell imaging." Computational and Structural Biotechnology Journal 18 (2020): 2733–43. http://dx.doi.org/10.1016/j.csbj.2020.09.025.

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10

Sengupta, Kheya, Eric Moyen, Magali Macé, Anne-Marie Benoliel, Anne Pierres, Frank Thibaudau, Laurence Masson, Laurent Limozin, Pierre Bongrand, and Margrit Hanbücken. "Large-Scale Ordered Plastic Nanopillars for Quantitative Live-Cell Imaging." Small 5, no. 4 (February 20, 2009): 449–53. http://dx.doi.org/10.1002/smll.200800836.

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11

Mullassery, Dhanya, Caroline A. Horton, Christopher D. Wood, and Michael R. H. White. "Single live-cell imaging for systems biology 9." Essays in Biochemistry 45 (September 30, 2008): 121–34. http://dx.doi.org/10.1042/bse0450121.

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Understanding how mammalian cells function requires a dynamic perspective. However, owing to the complexity of signalling networks, these non-linear systems can easily elude human intuition. The central aim of systems biology is to improve our understanding of the temporal complexity of cell signalling pathways, using a combination of experimental and computational approaches. Live-cell imaging and computational modelling are compatible techniques which allow quantitative analysis of cell signalling pathway dynamics. Non-invasive imaging techniques, based on the use of various luciferases and fluorescent proteins, trace cellular events such as gene expression, protein–protein interactions and protein localization in cells. By employing a number of markers in a single assay, multiple parameters can be measured simultaneously in the same cell. Following acquisition using specialized microscopy, analysis of multi-parameter time-lapse images facilitates the identification of important qualitative and quantitative relationships–linking intracellular signalling, gene expression and cell fate.

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12

Sung, Myong-Hee. "A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology." Cells 2, no. 2 (April 29, 2013): 284–93. http://dx.doi.org/10.3390/cells2020284.

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13

Baumgärtel, Viola, Barbara Müller, and Don C. Lamb. "Quantitative Live-Cell Imaging of Human Immunodeficiency Virus (HIV-1) Assembly." Viruses 4, no. 5 (May 4, 2012): 777–99. http://dx.doi.org/10.3390/v4050777.

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14

Lue, Niyom, Wonshik Choi, Gabriel Popescu, Takahiro Ikeda, Ramachandra R. Dasari, Kamran Badizadegan, and Michael S. Feld. "Quantitative phase imaging of live cells using fast Fourier phase microscopy." Applied Optics 46, no. 10 (March 13, 2007): 1836. http://dx.doi.org/10.1364/ao.46.001836.

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15

Shen, Yihui, Fang Xu, Lu Wei, Fanghao Hu, and Wei Min. "Live-Cell Quantitative Imaging of Proteome Degradation by Stimulated Raman Scattering." Angewandte Chemie 126, no. 22 (April 15, 2014): 5702–5. http://dx.doi.org/10.1002/ange.201310725.

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16

Shen, Yihui, Fang Xu, Lu Wei, Fanghao Hu, and Wei Min. "Live-Cell Quantitative Imaging of Proteome Degradation by Stimulated Raman Scattering." Angewandte Chemie International Edition 53, no. 22 (April 15, 2014): 5596–99. http://dx.doi.org/10.1002/anie.201310725.

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17

Olivier, Françios A. B., and Ana Traven. "Quantitative live-cell imaging of Candida albicans escape from immune phagocytes." STAR Protocols 4, no. 4 (December 2023): 102737. http://dx.doi.org/10.1016/j.xpro.2023.102737.

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18

Raarup, Merete Krog, and Jens Randel Nyengaard. "QUANTITATIVE CONFOCAL LASER SCANNING MICROSCOPY." Image Analysis & Stereology 25, no. 3 (May 3, 2011): 111. http://dx.doi.org/10.5566/ias.v25.p111-120.

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This paper discusses recent advances in confocal laser scanning microscopy (CLSM) for imaging of 3D structure as well as quantitative characterization of biomolecular interactions and diffusion behaviour by means of one- and two-photon excitation. The use of CLSM for improved stereological length estimation in thick (up to 0.5 mm) tissue is proposed. The techniques of FRET (Fluorescence Resonance Energy Transfer), FLIM (Fluorescence Lifetime Imaging Microscopy), FCS (Fluorescence Correlation Spectroscopy) and FRAP (Fluorescence Recovery After Photobleaching) are introduced and their applicability for quantitative imaging of biomolecular (co-)localization and trafficking in live cells described. The advantage of two-photon versus one-photon excitation in relation to these techniques is discussed.

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19

Mahen, Robert, Birgit Koch, Malte Wachsmuth, Antonio Z. Politi, Alexis Perez-Gonzalez, Julia Mergenthaler, Yin Cai, and Jan Ellenberg. "Comparative assessment of fluorescent transgene methods for quantitative imaging in human cells." Molecular Biology of the Cell 25, no. 22 (November 5, 2014): 3610–18. http://dx.doi.org/10.1091/mbc.e14-06-1091.

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Fluorescence tagging of proteins is a widely used tool to study protein function and dynamics in live cells. However, the extent to which different mammalian transgene methods faithfully report on the properties of endogenous proteins has not been studied comparatively. Here we use quantitative live-cell imaging and single-molecule spectroscopy to analyze how different transgene systems affect imaging of the functional properties of the mitotic kinase Aurora B. We show that the transgene method fundamentally influences level and variability of expression and can severely compromise the ability to report on endogenous binding and localization parameters, providing a guide for quantitative imaging studies in mammalian cells.

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20

Hamrang, Zahra, Yamini Arthanari, David Clarke, and Alain Pluen. "Quantitative Assessment of P-Glycoprotein Expression and Function Using Confocal Image Analysis." Microscopy and Microanalysis 20, no. 5 (August 27, 2014): 1329–39. http://dx.doi.org/10.1017/s1431927614013014.

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AbstractP-glycoprotein is implicated in clinical drug resistance; thus, rapid quantitative analysis of its expression and activity is of paramout importance to the design and success of novel therapeutics. The scope for the application of quantitative imaging and image analysis tools in this field is reported here at “proof of concept” level. P-glycoprotein expression was utilized as a model for quantitative immunofluorescence and subsequent spatial intensity distribution analysis (SpIDA). Following expression studies, p-glycoprotein inhibition as a function of verapamil concentration was assessed in two cell lines using live cell imaging of intracellular Calcein retention and a routine monolayer fluorescence assay. Intercellular and sub-cellular distributions in the expression of the p-glycoprotein transporter between parent and MDR1-transfected Madin–Derby Canine Kidney cell lines were examined. We have demonstrated that quantitative imaging can provide dose–response parameters while permitting direct microscopic analysis of intracellular fluorophore distributions in live and fixed samples. Analysis with SpIDA offers the ability to detect heterogeniety in the distribution of labeled species, and in conjunction with live cell imaging and immunofluorescence staining may be applied to the determination of pharmacological parameters or analysis of biopsies providing a rapid prognostic tool.

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21

Sarkar, Avik Ranjan, Cheol Ho Heo, Lei Xu, Hyo Won Lee, Ho Young Si, Ji Won Byun, and Hwan Myung Kim. "A ratiometric two-photon probe for quantitative imaging of mitochondrial pH values." Chemical Science 7, no. 1 (2016): 766–73. http://dx.doi.org/10.1039/c5sc03708e.

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22

Rambaud-Lavigne, Léa, and Angela Hay. "Floral organ development goes live." Journal of Experimental Botany 71, no. 9 (January 23, 2020): 2472–78. http://dx.doi.org/10.1093/jxb/eraa038.

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Abstract The chance to watch floral organs develop live is not to be missed! Here, we outline reasons why quantitative, live-cell imaging is an important approach to study floral morphogenesis, and provide a basic workflow of how to get started. We highlight key advances in morphodynamics of lateral organ development, and discuss recent work that uses live confocal imaging to address the regulation of floral organ number, its robustness, and patterning mechanisms that exploit stochasticity.

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23

Leary, Elizabeth, Claire Rhee, Benjamin T. Wilks, and Jeffrey R. Morgan. "Quantitative Live-Cell Confocal Imaging of 3D Spheroids in a High-Throughput Format." SLAS TECHNOLOGY: Translating Life Sciences Innovation 23, no. 3 (February 7, 2018): 231–42. http://dx.doi.org/10.1177/2472630318756058.

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Accurately predicting the human response to new compounds is critical to a wide variety of industries. Standard screening pipelines (including both in vitro and in vivo models) often lack predictive power. Three-dimensional (3D) culture systems of human cells, a more physiologically relevant platform, could provide a high-throughput, automated means to test the efficacy and/or toxicity of novel substances. However, the challenge of obtaining high-magnification, confocal z stacks of 3D spheroids and understanding their respective quantitative limitations must be overcome first. To address this challenge, we developed a method to form spheroids of reproducible size at precise spatial locations across a 96-well plate. Spheroids of variable radii were labeled with four different fluorescent dyes and imaged with a high-throughput confocal microscope. 3D renderings of the spheroid had a complex bowl-like appearance. We systematically analyzed these confocal z stacks to determine the depth of imaging and the effect of spheroid size and dyes on quantitation. Furthermore, we have shown that this loss of fluorescence can be addressed through the use of ratio imaging. Overall, understanding both the limitations of confocal imaging and the tools to correct for these limits is critical for developing accurate quantitative assays using 3D spheroids.

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24

Kasprowicz, Richard, Rakesh Suman, and Peter O’Toole. "Characterising live cell behaviour: Traditional label-free and quantitative phase imaging approaches." International Journal of Biochemistry & Cell Biology 84 (March 2017): 89–95. http://dx.doi.org/10.1016/j.biocel.2017.01.004.

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25

Lu, Shaoying, Yi Wang, He Huang, Yijia Pan, Eric J. Chaney, Stephen A. Boppart, Howard Ozer, Alex Y. Strongin, and Yingxiao Wang. "Quantitative FRET Imaging to Visualize the Invasiveness of Live Breast Cancer Cells." PLoS ONE 8, no. 3 (March 13, 2013): e58569. http://dx.doi.org/10.1371/journal.pone.0058569.

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26

Yao, Tatsuma, Jun Ueda, Tetsuya J. Kobayashi, Mayuko Hori, and Kazuo Yamagata. "Quantitative Assessment of Embryo Quality Based on a Live-Cell Imaging Technique." Journal of Mammalian Ova Research 32, no. 4 (October 2015): 149–57. http://dx.doi.org/10.1274/jmor.32.149.

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27

Kukhtevich, Igor V., Mariana Rivero-Romano, Namisha Rakesh, Poonam Bheda, Yagya Chadha, Paulina Rosales-Becerra, Stephan Hamperl, et al. "Quantitative RNA imaging in single live cells reveals age-dependent asymmetric inheritance." Cell Reports 41, no. 7 (November 2022): 111656. http://dx.doi.org/10.1016/j.celrep.2022.111656.

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28

Bourges, Anais C., Alexander Lazarev, Nathalie Declerck, Karyn L. Rogers, and Catherine A. Royer. "Quantitative High-Resolution Imaging of Live Microbial Cells at High Hydrostatic Pressure." Biophysical Journal 118, no. 11 (June 2020): 2670–79. http://dx.doi.org/10.1016/j.bpj.2020.04.017.

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29

Shen, Yihui, Fang Xu, and Wei Min. "Quantitative Imaging of Proteome Degradation in Live Cells by Stimulated Raman Scattering." Biophysical Journal 108, no. 2 (January 2015): 480a. http://dx.doi.org/10.1016/j.bpj.2014.11.2620.

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30

Raiola, Morena, Miquel Sendra, and Miguel Torres. "Imaging Approaches and the Quantitative Analysis of Heart Development." Journal of Cardiovascular Development and Disease 10, no. 4 (March 29, 2023): 145. http://dx.doi.org/10.3390/jcdd10040145.

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Heart morphogenesis is a complex and dynamic process that has captivated researchers for almost a century. This process involves three main stages, during which the heart undergoes growth and folding on itself to form its common chambered shape. However, imaging heart development presents significant challenges due to the rapid and dynamic changes in heart morphology. Researchers have used different model organisms and developed various imaging techniques to obtain high-resolution images of heart development. Advanced imaging techniques have allowed the integration of multiscale live imaging approaches with genetic labeling, enabling the quantitative analysis of cardiac morphogenesis. Here, we discuss the various imaging techniques used to obtain high-resolution images of whole-heart development. We also review the mathematical approaches used to quantify cardiac morphogenesis from 3D and 3D+time images and to model its dynamics at the tissue and cellular levels.

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31

NISHIYAMA, Koichi. "Understanding of angiogenic morphogenesis using in vitro timelapse live imaging and quantitative approaches." Japanese Journal of Thrombosis and Hemostasis 24, no. 6 (2013): 553–59. http://dx.doi.org/10.2491/jjsth.24.553.

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32

Corby, M. J., Michael R. Stoneman, Gabriel Biener, Joel D. Paprocki, Rajesh Kolli, Valerica Raicu, and David N. Frick. "Quantitative microspectroscopic imaging reveals viral and cellular RNA helicase interactions in live cells." Journal of Biological Chemistry 292, no. 27 (May 8, 2017): 11165–77. http://dx.doi.org/10.1074/jbc.m117.777045.

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33

Hundahl, Adam Coln, Arjen Weller, Jannik Bruun Larsen, Claudia U. Hjørringgaard, Morten B. Hansen, Ann-Kathrin Mündler, Astrid Knuhtsen, et al. "Quantitative live-cell imaging of lipidated peptide transport through an epithelial cell layer." Journal of Controlled Release 355 (March 2023): 122–34. http://dx.doi.org/10.1016/j.jconrel.2023.01.066.

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34

Henning, Alyssa L., Michael X. Jiang, Huseyin C. Yalcin, and Jonathan T. Butcher. "Quantitative three-dimensional imaging of live avian embryonic morphogenesis via micro-computed tomography." Developmental Dynamics 240, no. 8 (July 14, 2011): 1949–57. http://dx.doi.org/10.1002/dvdy.22694.

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35

Charrasse, Sophie, Victor Racine, Charlotte Saint-Omer, Titouan Poquillon, Loïc Lionnard, Marine Ledru, Christophe Gonindard, et al. "Quantitative imaging and semiotic phenotyping of mitochondrial network morphology in live human cells." PLOS ONE 19, no. 3 (March 28, 2024): e0301372. http://dx.doi.org/10.1371/journal.pone.0301372.

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The importance of mitochondria in tissue homeostasis, stress responses and human diseases, combined to their ability to transition between various structural and functional states, makes them excellent organelles for monitoring cell health. There is therefore a need for technologies to accurately analyze and quantify changes in mitochondrial organization in a variety of cells and cellular contexts. Here we present an innovative computerized method that enables accurate, multiscale, fast and cost-effective analysis of mitochondrial shape and network architecture from confocal fluorescence images by providing more than thirty features. In order to facilitate interpretation of the quantitative results, we introduced two innovations: the use of Kiviat-graphs (herein named MitoSpider plots) to present highly multidimensional data and visualization of the various mito-cellular configurations in the form of morphospace diagrams (called MitoSigils). We tested our fully automated image analysis tool on rich datasets gathered from live normal human skin cells cultured under basal conditions or exposed to specific stress including UVB irradiation and pesticide exposure. We demonstrated the ability of our proprietary software (named MitoTouch) to sensitively discriminate between control and stressed dermal fibroblasts, and between normal fibroblasts and other cell types (including cancer tissue-derived fibroblasts and primary keratinocytes), showing that our automated analysis captures subtle differences in morphology. Based on this novel algorithm, we report the identification of a protective natural ingredient that mitigates the deleterious impact of hydrogen peroxide (H2O2) on mitochondrial organization. Hence we conceived a novel wet-plus-dry pipeline combining cell cultures, quantitative imaging and semiotic analysis for exhaustive analysis of mitochondrial morphology in living adherent cells. Our tool has potential for broader applications in other research areas such as cell biology and medicine, high-throughput drug screening as well as predictive and environmental toxicology.

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36

Yin Ao, 尹傲, 翟士贤 Zhai Shixian, 孙晗 Sun Han, 刘智 Liu Zhi, 庄正飞 Zhuang Zhengfei, and 陈同生 Chen Tongsheng. "活细胞定量FRET成像方法鲁棒性评估." Chinese Journal of Lasers 48, no. 21 (2021): 2107001. http://dx.doi.org/10.3788/cjl202148.2107001.

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37

Inoue, S., V. Frank, M. Hörning, S. Kaufmann, H. Y. Yoshikawa, J. P. Madsen, A. L. Lewis, S. P. Armes, and M. Tanaka. "Live cell tracking of symmetry break in actin cytoskeleton triggered by abrupt changes in micromechanical environments." Biomaterials Science 3, no. 12 (2015): 1539–44. http://dx.doi.org/10.1039/c5bm00205b.

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38

Babakhanova, Greta, Stephen M. Zimmerman, Laura T. Pierce, Sumona Sarkar, Nicholas J. Schaub, and Carl G. Simon. "Quantitative, traceable determination of cell viability using absorbance microscopy." PLOS ONE 17, no. 1 (January 19, 2022): e0262119. http://dx.doi.org/10.1371/journal.pone.0262119.

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Cell viability, an essential measurement for cell therapy products, lacks traceability. One of the most common cell viability tests is trypan blue dye exclusion where blue-stained cells are counted via brightfield imaging. Typically, live and dead cells are classified based on their pixel intensities which may vary arbitrarily making it difficult to compare results. Herein, a traceable absorbance microscopy method to determine the intracellular uptake of trypan blue is demonstrated. The intensity pixels of the brightfield images are converted to absorbance images which are used to calculate moles of trypan blue per cell. Trypan blue cell viability measurements, where trypan blue content in each cell is quantified, enable traceable live-dead classifications. To implement the absorbance microscopy method, we developed an open-source AbsorbanceQ application that generates quantitative absorbance images. The validation of absorbance microscopy is demonstrated using neutral density filters. Results from four different microscopes demonstrate a mean absolute deviation of 3% from the expected optical density values. When assessing trypan blue-stained Jurkat cells, the difference in intracellular uptake of trypan blue in heat-shock-killed cells using two different microscopes is 3.8%. Cells killed with formaldehyde take up ~50% less trypan blue as compared to the heat-shock-killed cells, suggesting that the killing mechanism affects trypan blue uptake. In a test mixture of approximately 50% live and 50% dead cells, 53% of cells were identified as dead (±6% standard deviation). Finally, to mimic batches of low-viability cells that may be encountered during a cell manufacturing process, viability was assessed for cells that were 1) overgrown in the cell culture incubator for five days or 2) incubated in DPBS at room temperature for five days. Instead of making live-dead classifications using arbitrary intensity values, absorbance imaging yields traceable units of moles that can be compared, which is useful for assuring quality for biomanufacturing processes.

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39

Almassalha, Luay M., Greta M. Bauer, John E. Chandler, Scott Gladstein, Lusik Cherkezyan, Yolanda Stypula-Cyrus, Samuel Weinberg, et al. "Label-free imaging of the native, living cellular nanoarchitecture using partial-wave spectroscopic microscopy." Proceedings of the National Academy of Sciences 113, no. 42 (October 4, 2016): E6372—E6381. http://dx.doi.org/10.1073/pnas.1608198113.

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The organization of chromatin is a regulator of molecular processes including transcription, replication, and DNA repair. The structures within chromatin that regulate these processes span from the nucleosomal (10-nm) to the chromosomal (>200-nm) levels, with little known about the dynamics of chromatin structure between these scales due to a lack of quantitative imaging technique in live cells. Previous work using partial-wave spectroscopic (PWS) microscopy, a quantitative imaging technique with sensitivity to macromolecular organization between 20 and 200 nm, has shown that transformation of chromatin at these length scales is a fundamental event during carcinogenesis. As the dynamics of chromatin likely play a critical regulatory role in cellular function, it is critical to develop live-cell imaging techniques that can probe the real-time temporal behavior of the chromatin nanoarchitecture. Therefore, we developed a live-cell PWS technique that allows high-throughput, label-free study of the causal relationship between nanoscale organization and molecular function in real time. In this work, we use live-cell PWS to study the change in chromatin structure due to DNA damage and expand on the link between metabolic function and the structure of higher-order chromatin. In particular, we studied the temporal changes to chromatin during UV light exposure, show that live-cell DNA-binding dyes induce damage to chromatin within seconds, and demonstrate a direct link between higher-order chromatin structure and mitochondrial membrane potential. Because biological function is tightly paired with structure, live-cell PWS is a powerful tool to study the nanoscale structure–function relationship in live cells.

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40

Hu, Jun Jacob, Nai-Kei Wong, Ming-Yang Lu, Xingmiao Chen, Sen Ye, Angela Qian Zhao, Peng Gao, Richard Yi-Tsun Kao, Jiangang Shen, and Dan Yang. "HKOCl-3: a fluorescent hypochlorous acid probe for live-cell and in vivo imaging and quantitative application in flow cytometry and a 96-well microplate assay." Chemical Science 7, no. 3 (2016): 2094–99. http://dx.doi.org/10.1039/c5sc03855c.

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41

Gong, Sophie, Yuan Li, Wenji Su, Yu Ding, Jiaqi Lu, Kelly Dong, Steve Hood, Wandong Zhang, and Georg C. Terstappen. "Quantitative Algorithm-Based Paired Imaging Measurement for Antibody-Triggered Endocytosis in Cultured Cells." SLAS DISCOVERY: Advancing the Science of Drug Discovery 23, no. 8 (March 5, 2018): 832–41. http://dx.doi.org/10.1177/2472555218761355.

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Antibody-triggered endocytosis (ATE) is a biological mechanism on which many therapeutic strategies are grounded, such as delivery of antibody–drug conjugates (ADCs). Current methods monitoring ATE include confocal Z-stack analysis, acid wash, antibody quenching, and pH-sensitive dye labeling. However, those generate less quantifiable results with low throughput. Here we report a new method referred to as “paired imaging measurement” to analyze ATE using a quantitative algorithm in conjunction with high-content imaging. With two sequential measurements of cell surface antibody employing live cell staining and total antibody by immunostaining before and after cell permeabilization, intracellular antibody undergoing endocytosis can be quantified indirectly. Antibodies against CD98 and transferrin receptor were tested on hCMEC/D3 and hiPSC-derived endothelial cells. The maximal response and potency of endocytosed antibodies were generated with good assay robustness (Z′ > 0.6) and >5-fold signal/background ratio. Antibody endocytosis response ranking is consistent between batches ( R2 > 0.9). The obtained results were confirmed by other traditional methods. In conclusion, we have developed a novel method using a quantitative imaging algorithm in conjunction with live cell staining for high-throughput investigation of ATE.

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42

Van Valen, David A., Takamasa Kudo, Keara M. Lane, Derek N. Macklin, Nicolas T. Quach, Mialy M. DeFelice, Inbal Maayan, Yu Tanouchi, Euan A. Ashley, and Markus W. Covert. "Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments." PLOS Computational Biology 12, no. 11 (November 4, 2016): e1005177. http://dx.doi.org/10.1371/journal.pcbi.1005177.

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43

Gerlich, Daniel, Joël Beaudouin, Matthias Gebhard, Jan Ellenberg, and Roland Eils. "Four-dimensional imaging and quantitative reconstruction to analyse complex spatiotemporal processes in live cells." Nature Cell Biology 3, no. 9 (August 16, 2001): 852–55. http://dx.doi.org/10.1038/ncb0901-852.

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44

Holst, Mikkel R., and Lene N. Nejsum. "A versatile aquaporin-2 cell system for quantitative temporal expression and live cell imaging." American Journal of Physiology-Renal Physiology 317, no. 1 (July 1, 2019): F124—F132. http://dx.doi.org/10.1152/ajprenal.00150.2019.

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Aquaporin-2 (AQP2) fine tunes urine concentration in response to the antidiuretic hormone vasopressin. In addition, AQP2 has been suggested to promote cell migration and epithelial morphogenesis. A cell system allowing temporal and quantitative control of expression levels of AQP2 and phospho-mimicking mutants has been missing, as has a system allowing expression of fluorescently tagged AQP2 for time-lapse imaging. In the present study, we generated and validated a Flp-In T-REx Madin-Darby canine kidney cell system for temporal and quantitative control of AQP2 and phospho-mimicking mutants. We verified that expression levels can be temporally and quantitatively controlled and that AQP2 translocated to the plasma membrane in response to elevated cAMP, which also induced S256 phosphorylation. The phospho-mimicking mutants AQP2-S256A and AQP2-S256D localized as previously described, primarily intracellular and to the plasma membrane, respectively. Induction of AQP2 expression in combination with transient, low expression of enhanced green fluorescent protein-tagged AQP2 enabled expression without aggregation and correct translocation in response to elevated cAMP. Interestingly, time-lapse imaging revealed AQP2-containing tubulating endosomes and that tubulation significantly decreased 30 min after cAMP elevation. This was mirrored by the phospho-mimicking mutants AQP2-S256A and AQP2-S256D, where AQP2-S256A-containing endosomes tubulated, whereas AQP2-S256D-containing endosomes did not. Thus, this cell system enables a multitude of cell-based assays warranted to provide deeper insights into the mechanisms of AQP2 regulation and effects on cell migration and epithelial morphogenesis.

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Bradley, Josephine, Iestyn Pope, Francesco Masia, Randa Sanusi, Wolfgang Langbein, Karl Swann, and Paola Borri. "Quantitative imaging of lipids in live mouse oocytes and early embryos using CARS microscopy." Development 143, no. 12 (May 5, 2016): 2238–47. http://dx.doi.org/10.1242/dev.129908.

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SUNDD, PRITHU, EDGAR GUTIERREZ, BRIAN G. PETRICH, MARK H. GINSBERG, ALEX GROISMAN, and KLAUS LEY. "Live Cell Imaging of Paxillin in Rolling Neutrophils by Dual-Color Quantitative Dynamic Footprinting." Microcirculation 18, no. 5 (July 2011): 361–72. http://dx.doi.org/10.1111/j.1549-8719.2011.00090.x.

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Eils, Roland, and Chaitanya Athale. "Computational imaging in cell biology." Journal of Cell Biology 161, no. 3 (May 12, 2003): 477–81. http://dx.doi.org/10.1083/jcb.200302097.

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Microscopy of cells has changed dramatically since its early days in the mid-seventeenth century. Image analysis has concurrently evolved from measurements of hand drawings and still photographs to computational methods that (semi-) automatically quantify objects, distances, concentrations, and velocities of cells and subcellular structures. Today's imaging technologies generate a wealth of data that requires visualization and multi-dimensional and quantitative image analysis as prerequisites to turning qualitative data into quantitative values. Such quantitative data provide the basis for mathematical modeling of protein kinetics and biochemical signaling networks that, in turn, open the way toward a quantitative view of cell biology. Here, we will review technologies for analyzing and reconstructing dynamic structures and processes in the living cell. We will present live-cell studies that would have been impossible without computational imaging. These applications illustrate the potential of computational imaging to enhance our knowledge of the dynamics of cellular structures and processes.

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Ying, Zhan-Ming, Yue-Yan Yuan, Bin Tu, Li-Juan Tang, Ru-Qin Yu, and Jian-Hui Jiang. "A single promoter system co-expressing RNA sensor with fluorescent proteins for quantitative mRNA imaging in living tumor cells." Chemical Science 10, no. 18 (2019): 4828–33. http://dx.doi.org/10.1039/c9sc00458k.

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Kang, Jeon Woong, Freddy T. Nguyen, and Niyom Lue. "Temporal Imaging of Live Cells by High-Speed Confocal Raman Microscopy." Materials 14, no. 13 (July 3, 2021): 3732. http://dx.doi.org/10.3390/ma14133732.

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Label-free live cell imaging was performed using a custom-built high-speed confocal Raman microscopy system. For various cell types, cell-intrinsic Raman bands were monitored. The high-resolution temporal Raman images clearly delineated the intracellular distribution of biologically important molecules such as protein, lipid, and DNA. Furthermore, optical phase delay measured using quantitative phase microscopy shows similarity with the image reconstructed from the protein Raman peak. This reported work demonstrates that Raman imaging is a powerful label-free technique for studying various biomedical problems in vitro with minimal sample preparation and external perturbation to the cellular system.

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Bogorad, Max I., and Peter C. Searson. "Real-time imaging and quantitative analysis of doxorubicin transport in a perfusable microvessel platform." Integrative Biology 8, no. 9 (2016): 976–84. http://dx.doi.org/10.1039/c6ib00082g.

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The kinetics of solute transport across cell monolayers is complex, and often consists of multiple active transport processes in addition to passive diffusion. Here we demonstrate that mechanistic details of transport across biological barriers can be obtained from live cell imaging in a perfusable microvessel model with physiologically relevant geometry.

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