However, high-throughput analysis of these mosaic images requires use of other software platforms for quantification, such as: CellProfiler, ImageJ, or Matlab/Octave. The EVOS imaging system contains a scanning algorithm that screens culture plates and creates individual tiled images of each well. Because an entire well cannot fit into a single microscopic field, imaging multiple overlapping fields is required. In this case, cells occupy only a small fraction of the available growth area, so it’s essential the entire well be imaged to allow for an accurate count. For example, we frequently perform experiments where we deposit a limiting number of cells (e.g., 1,10, or 50) into individual wells of a 96-well culture plate. However, there are instances where using random fields for quantification may be confounding. Other common methods and endpoint assays of cell quantification in these types of experiments are possible e.g., MTT or ATP assays, but quantification afforded by imaging is non-destructive and allows an accurate and dynamic assessment of cell-division over the course of a month’s-long experiment.Ī common practice when scanning multi-well dishes is to image random fields, which produces results that are relative. The EVOS Automated Cell Imaging System (ThermoFisher Scientific) is such a device, and we frequently use our machine for high-throughput imaging applications and experiments that require quantifying absolute numbers of cells in multi-well dishes. Accessibility to these systems has increased the sheer volume of images that can be generated in short time, yielding densely layered data that becomes unwieldly without assistance of computational algorithms. Miniaturization of advanced microscopy equipment and automation of data collection now permit acquisition of high-quality fluorescent images within the confines of a typical cell laboratory. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. įunding: Research reported in this publication was supported by the University of New Mexico Cancer Center and an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number P20GM103451. Additional data and detailed instructions are available on our website. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: The data underlying the results presented in the study are available on Github. Received: FebruAccepted: JPublished: August 5, 2020Ĭopyright: © 2020 Klimaj et al. Mancini, Baylor College of Medicine, UNITED STATES We present development and optimization of this automated pipeline and submit it as an effective and facile tool for accurately counting cells from tiled images.Ĭitation: Klimaj SD, Licon Munoz Y, Del Toro K, Hines WC (2020) A high-throughput imaging and quantification pipeline for the EVOS imaging platform. We have since overcome these obstacles and have created a rigorous cell counting pipeline for analyzing images captured by the EVOS scan function. These included: high background, illumination and stitching artifacts, low contrast, noise, focus inconsistencies, and image distortion-all of which negatively impacted processing efficiency. Our initial attempts to quantify tiled images captured on an EVOS device was plagued by some expected-and other unforeseeable-issues that arose at nearly every stage of analysis. ![]() Automated batch analysis and quantification of these tiled images does however require off-loading files to other software platforms. The EVOS imaging system is such a device and is capable of scanning multi-well dishes and stitching together multiple adjacent fields to produce coherent individual images of each well. Many of these machines possess motorized stages and on-stage incubators that permit programmable imaging of live cells that make them a sensible tool for high-throughput applications. Self-contained imaging systems are versatile instruments that are becoming a staple in cell culture laboratories.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |