scholarly journals Erratum: Robust high-throughput kinetic analysis of apoptosis with real-time high-content live-cell imaging

2017 ◽  
Vol 8 (5) ◽  
pp. e2758-e2758 ◽  
Author(s):  
Jesse D Gelles ◽  
Jerry Edward Chipuk
Keyword(s):  
Kinetic Analysis ◽  
Real Time ◽  
High Throughput ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell

scholarly journals Real-time integration of cell death mechanisms and proliferation kinetics at the single-cell and population-level using high-throughput live-cell imaging

2019 ◽  
Author(s):  
Jesse D. Gelles ◽  
Jarvier N. Mohammed ◽  
Luis C. Santos ◽  
Diana Legarda ◽  
Adrian T. Ting ◽  
...  
Keyword(s):  
Cell Death ◽  
Single Cell ◽  
Real Time ◽  
High Throughput ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Time Integration ◽  
Population Level ◽  
Live Cell ◽  
Cell Death Mechanisms

SummaryQuantifying cytostatic and cytotoxic outcomes are integral components of characterizing perturbagens used as research tools and/or in drug discovery pipelines. Furthermore, data-rich acquisition coupled with robust methods for analysis is required to properly assess the function and impact of these perturbagens. Here, we present a detailed and versatile method for Single-cell and Population-level Analyses using Real-time Kinetic Labeling (SPARKL). SPARKL integrates high-content live-cell imaging with automated detection and analysis of fluorescent reporters of cell death. We outline several examples of zero-handling, non-disruptive protocols for detailing cell death mechanisms and proliferation profiles. Additionally, we suggest several methods for mathematically analyzing these data to best utilize the collected kinetic data. Compared to traditional methods of detection and analysis, SPARKL is more sensitive, accurate, and high-throughput while substantially eliminating sample processing and providing richer data.

scholarly journals A high-throughput screening assay based on automated microscopy for monitoring antibiotic susceptibility of Mycobacterium tuberculosis phenotypes

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sadaf Kalsum ◽  
Blanka Andersson ◽  
Jyotirmoy Das ◽  
Thomas Schön ◽  
Maria Lerm
Keyword(s):  
Mycobacterium Tuberculosis ◽  
High Throughput ◽  
High Throughput Screening ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Imaging System ◽  
Aggregate Size ◽  
Live Cell ◽  
Screening Assay ◽  
High Throughput Screening Assay

Abstract Background Efficient high-throughput drug screening assays are necessary to enable the discovery of new anti-mycobacterial drugs. The purpose of our work was to develop and validate an assay based on live-cell imaging which can monitor the growth of two distinct phenotypes of Mycobacterium tuberculosis and to test their susceptibility to commonly used TB drugs. Results Both planktonic and cording phenotypes were successfully monitored as fluorescent objects using the live-cell imaging system IncuCyte S3, allowing collection of data describing distinct characteristics of aggregate size and growth. The quantification of changes in total area of aggregates was used to define IC50 and MIC values of selected TB drugs which revealed that the cording phenotype grew more rapidly and displayed a higher susceptibility to rifampicin. In checkerboard approach, testing pair-wise combinations of sub-inhibitory concentrations of drugs, rifampicin, linezolid and pretomanid demonstrated superior growth inhibition of cording phenotype. Conclusions Our results emphasize the efficiency of using automated live-cell imaging and its potential in high-throughput whole-cell screening to evaluate existing and search for novel antimycobacterial drugs.

scholarly journals mycelyso – high-throughput analysis of Streptomyces mycelium live cell imaging data

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Christian Carsten Sachs ◽  
Joachim Koepff ◽  
Wolfgang Wiechert ◽  
Alexander Grünberger ◽  
Katharina Nöh
Keyword(s):  
High Throughput ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell ◽  
Imaging Data ◽  
High Throughput Analysis ◽  
Throughput Analysis

scholarly journals CellCognition: time-resolved phenotype annotation in high-throughput live cell imaging

2010 ◽  
Vol 7 (9) ◽  
pp. 747-754 ◽  
Author(s):  
Michael Held ◽  
Michael H A Schmitz ◽  
Bernd Fischer ◽  
Thomas Walter ◽  
Beate Neumann ◽  
...  
Keyword(s):  
High Throughput ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell ◽  
Time Resolved ◽  
Phenotype Annotation

Real-time and quantitative fluorescent live-cell imaging with quadruplex-specific red-edge probe (G4-REP)

2017 ◽  
Vol 1861 (5) ◽  
pp. 1312-1320 ◽  
Author(s):  
Sunny Y. Yang ◽  
Souheila Amor ◽  
Aurélien Laguerre ◽  
Judy M.Y. Wong ◽  
David Monchaud
Keyword(s):  
Real Time ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell ◽  
Red Edge ◽  
Edge Probe

Single live cell imaging for real-time monitoring of resistance mechanism in Pseudomonas aeruginosa

2002 ◽  
Vol 7 (4) ◽  
pp. 576 ◽  
Author(s):  
Sophia V. Kyriacou ◽  
Michelle E. Nowak ◽  
William J. Brownlow ◽  
Xiao-Hong Nancy Xu
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Real Time ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Resistance Mechanism ◽  
Live Cell ◽  
Real Time Monitoring

High-throughput live-cell imaging reveals differential inhibition of tumor cell proliferation by human fibroblasts

2010 ◽  
Vol 128 (12) ◽  
pp. 2793-2802 ◽  
Author(s):  
Emilie Flaberg ◽  
Laszlo Markasz ◽  
Gabor Petranyi ◽  
Gyorgy Stuber ◽  
Ferenc Dicső ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Tumor Cell ◽  
High Throughput ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Human Fibroblasts ◽  
Live Cell ◽  
Tumor Cell Proliferation ◽  
Differential Inhibition

Engineering a Reversible Fluorescent Probe for Real-Time Live-Cell Imaging and Quantification of Mitochondrial ATP

2020 ◽  
Vol 92 (6) ◽  
pp. 4681-4688 ◽  
Author(s):  
Tian-Bing Ren ◽  
Si-Yu Wen ◽  
Lu Wang ◽  
Peng Lu ◽  
Bin Xiong ◽  
...  
Keyword(s):  
Real Time ◽  
Fluorescent Probe ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell

scholarly journals High-throughput formation and image-based analysis of basal-in mammary organoids in 384-well plates

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Soojung Lee ◽  
Jonathan Chang ◽  
Sung-Min Kang ◽  
Eric Parigoris ◽  
Ji-Hoon Lee ◽  
...  
Keyword(s):  
Growth Factor ◽  
High Throughput ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Automated Analysis ◽  
Time Lapse ◽  
Culture Conditions ◽  
Live Cell ◽  
Future Research ◽  
Heparin Binding

AbstractThis manuscript describes a new method for forming basal-in MCF10A organoids using commercial 384-well ultra-low attachment (ULA) microplates and the development of associated live-cell imaging and automated analysis protocols. The use of a commercial 384-well ULA platform makes this method more broadly accessible than previously reported hanging drop systems and enables in-incubator automated imaging. Therefore, time points can be captured on a more frequent basis to improve tracking of early organoid formation and growth. However, one major challenge of live-cell imaging in multi-well plates is the rapid accumulation of large numbers of images. In this paper, an automated MATLAB script to handle the increased image load is developed. This analysis protocol utilizes morphological image processing to identify cellular structures within each image and quantify their circularity and size. Using this script, time-lapse images of aggregating and non-aggregating culture conditions are analyzed to profile early changes in size and circularity. Moreover, this high-throughput platform is applied to widely screen concentration combinations of Matrigel and epidermal growth factor (EGF) or heparin-binding EGF-like growth factor (HB-EGF) for their impact on organoid formation. These results can serve as a practical resource, guiding future research with basal-in MCF10A organoids.

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