We have a shelf in our family kitchen that is filled with beautiful books that have more than a few stains and singed pages – badges of honor for any respectable cookbook. Sadly, we only have one chef in my house and I am most certainly not it. Fortunately for all of us though, my wife loves to cook and is a master of culinary improvisation. In this way, our well-loved cookbooks act more as guides than sets of strict instructions to follow.
Often my enthusiasm (if not my skill) is called upon to assist in the preparation of ingredients. I will frequently ask the chef, “How much of this do you want?” and “Should I add more?” My questions are met with casual replies like “a bit more” or “that looks good.” As much as I admire the freewheeling nature of this process, as a scientist, I pine for precise, defined quantities – and the tools to measure them!
In the applications lab at BioTek, we design cell-based assays to run on our life science instruments, including the Cytation™ and Lionheart™ automated imaging systems. These powerful tools enable robust and reproducible measurements for a broad range of applications. One important variable in cell-based assays is the number of cells contributing to a signal of interest. Many factors can lead to variations in cell number across conditions, including pipetting errors and treatment-induced effects. Lacking a reliable method to quantify and adjust for these variations can generate misleading results.
Counting cells directly using automated image acquisition and analysis is the most straightforward and accurate method for measuring the size of a cell population. Coupled with powerful Gen5™ software, the Cytation and Lionheart systems deliver intuitive and accurate cell counts using both label-free and fluorescent label-based techniques. Cell counts provide a sensitive metric for cell proliferation and viability assays, as well as a powerful method for normalizing results across conditions and replicates.
There are a number of similarities between cooking a great meal and conducting a successful assay. Both require thoughtful selection of ingredients, access to the right tools, and recognition of the diverse factors that influence how these components come together. In science, accurate measurements – and adjusting for the variables that can affect them – are crucial for interpreting results correctly and the ability to reproduce them. And while preparing a delicious meal may not require precise measurements, appreciating all the elements that contributed to its creation certainly adds to the experience of those who get to sit down and enjoy it.
Below are just a few examples of how cell counting can be used to add accuracy and reproducibility to your cell-based assays…we hope you enjoy.
Quantitative Evaluation of Cell Proliferation Using Label-Free Direct Cell Counting
Label-free methods of measuring cell growth kinetics are preferable over the use of stains that can influence proliferation rates. Although confluence level can be used for some applications, cell counting is the most direct quantitative measure of cell proliferation over a broad range of cell population densities. |
| High contrast brightfield cell counts over time relative to confluence. A comparison of NIH3T3 direct cell counts and percent confluence over time demonstrate the different characteristics of the two cell growth metrics. Label free cell counts indicate robust logarithmic cell growth up to full confluence (dashed line). |
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| Profiles from 5 drug concentrations demonstrate a cell type-dependent differential dose response. NIH3T3, HeLa and HCT116 cell proliferation profiles enable quantitative analysis of drug response. Cell counts per mm2 were calculated every 2 hours for 5 days or until cells reached full confluence. |
Related Application Note: Kinetic Proliferation Assay Using Label-Free Cell Counting
Evaluation of relative levels of apoptosis and necrosis in a population using cell counting
The use of apoptosis and necrosis fluorescent probes were used in combination with automated kinetic imaging to quantitatively assess the effects of known inducers of cell death in multiple cell lines. Label-free high contrast brightfield imaging is used to assess the total number of cells in the population, and fluorescent probes to quantify early stage apoptosis at the level of plasma membrane inversion of phosphatidyl serine, and plasma membrane rupture associated with necrosis. This allows for accurate determination of percent apoptosis and necrosis in each cell population throughout the experiment. |
| Image analysis of apoptotic and necrotic cells. HT1080 cells were treated with camptothecin in order to determine the effect of the drug on the apoptotic and necrotic response of HT1080 cells. The first row (A-C) shows pre-processed high contrast brightfield images along with GFP and PI at 0 (A), 12 (B), and 24 (C) hours after treatment. The next row of images (D-F) shows the primary mask surrounding each individual cell as delineated by the pre-processed high contrast bright field image. Row G-I shows the expanded mask which captures more of the cell area and encompasses the GFP and PI signal. Row J-L shows the apoptotic cells highlighted in blue. Row M-O indicates necrotic cells highlighted in blue. |
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| HT1080 cells treated with Camptothecin. Apoptosis and necrosis increase in a dose dependent manner as demonstrated by time course (A,B) and dose response (C,D). |
Data Normalization for cellular metabolism analysis
The real-time measurement of oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) using the Agilent Seahorse XF analyzer are widely accepted as the industry standard for obtaining in vitro cellular metabolic parameters. The metabolic rate difference caused by cell amount variation can be eliminated by cell count-based normalization. Here counts of cells stained with Hoechst 33342 are automatically determined and integrated into the data reduction pathway using a Cytation Cell Imaging Multi-Mode Reader. |
| Example of Seahorse XF data normalization using in situ nuclear staining and in situ cell counting. (A) Raw OCR and ECAR change with serial injections of oligomycin/FCCP (green arrow) and Hoechst 33342 (red arrow) before normalization. (B) Representative images of nuclei fluorescently labeled by Hoechst 33342 injection (upper panel) and nuclei identified and outlined by Gen5 software (lower panel). (C) OCR and ECAR normalized by in situ cell counts using Cytation Cell Imaging Multi-Mode Reader. |
By: BioTek Instruments, Joe Clayton, PhD., Principal Scientist
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