Abstract

Background Performing accurate sample analyses during the culture of mammalian cells is vital in order to track the number and viability of cells present. This allows operators to recognise when reagents may need to be added to maximise yield, harvest cells appropriately and to identify when a targeted cell concentration has been reached. This is commonly performed via manual cell counts. Cell stains, such as Trypan blue are classically utilised for ‘dye exclusion’ assessment of viability, whereby dead cells are stained the colour of the dye and live cells remain colourless. However, this method is accompanied by many potential sources of human error and subjectivity as well as being a highly time consuming, labour-intensive mode of sample analysis. Various technologies introduced to the market in recent years automate this process in order to remove some human error and subjectivity associated with manual cell counts. However, the industry has not fully accepted these technologies, as the dye exclusion method is still the familiar and standard mode for assessing viability. This paper focuses on a new automated cell counter, the ‘Countstar’ as seen in figure 1, which uses brightfield image analysis and the trypan blue dye-exclusion method. This has the advantage of automating the process to remove human error and subjectivity, while retaining the standard trypan blue dye-exclusion method. The Countstar instrument uses individually packaged disposable plastic slides and associated software to analyse 20 μl samples. Each slide contains five separate chambers to lower costs and waste. Once a sample is loaded and the cells have settled, the instrument takes around 10 seconds to analyse an image. The Countstar requires no regular maintenance and will save vital time in the laboratory, while reducing human error associated with manual cell counts. The Countstar provides users with the live cell count, % viability and average cell size. It also offers aggregate and cell size histograms and a circularity index, which can be used as an estimation of cell population health. The software also saves all images taken automatically for future reference and allows users to manipulate previously recorded data if required. In this paper, an in depth assessment of the Countstar is carried out and * Correspondence: johnc@aberinstruments.com Aber Instruments Ltd., Aberystwyth, SY23 3AH, UK Figure 1 The Countstar automated cell counter and disposable slide. Carvell and Thomson BMC Proceedings 2015, 9(Suppl 9):P51 http://www.biomedcentral.com/1753-6561/9/S9/P51

Highlights

  • Performing accurate sample analyses during the culture of mammalian cells is vital in order to track the number and viability of cells present

  • This allows operators to recognise when reagents may need to be added to maximise yield, harvest cells appropriately and to identify when a targeted cell concentration has been reached. This is commonly performed via manual cell counts

  • Cell stains, such as Trypan blue are classically utilised for ‘dye exclusion’ assessment of viability, whereby dead cells are stained the colour of the dye and live cells remain colourless

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Summary

Introduction

Performing accurate sample analyses during the culture of mammalian cells is vital in order to track the number and viability of cells present This allows operators to recognise when reagents may need to be added to maximise yield, harvest cells appropriately and to identify when a targeted cell concentration has been reached. This is commonly performed via manual cell counts Cell stains, such as Trypan blue are classically utilised for ‘dye exclusion’ assessment of viability, whereby dead cells are stained the colour of the dye and live cells remain colourless. This method is accompanied by many potential sources of human error and subjectivity as well as being a highly time consuming, labour-intensive mode of sample analysis. The industry has not fully accepted these technologies, as the dye exclusion method is still the familiar and standard mode for assessing viability

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