Join 1 Million Scientists Who Use Our Advanced Technical Training In The Lab

The way you set your gates in flow cytometry is a key part of your experiment. You need to know that you can find the populations that you're interested in so you can extract the appropriate data. This is how you can do your secondary or statistical analysis confidently. Learn what gates you should be using and how to define them properly.

Cell death is a natural part of the lifecycle of a cell. In cases of development, it is critical for the shaping of fingers during human development. The processes of ordered cell death, or Apoptosis, are so important that in 2002, Sidney Brenner, Robert Horvitz, and John Sulston received the Nobel Prize in Medicine for their work on understanding this process. There are many different ways to measure cell death and flow cytometry is an ideal tool for this technique. Whether you are just assessing the viability of your cells or you are interested in the exact stage of cell death your sample is in, there are a variety of ways that you can measure cell death. Learn 3 ways you can use flow cytometry to measure cell death.

Controls are an integral part of all science. And the complexity of fluorescent microscopy makes including the right controls in your experiments paramount. You should be including these 5 controls in your experiments: an unlabeled sample, a non-specific binding control, a positive and negative control, an antibody titration curve, and blinded image capture. With those controls, you can be sure that your experiments are what you think they are and perform your imaging with confidence. So, happy imaging!

Reproducibility is a state of mind. It's not one simple thing that you do that will make all your data more reproducible, it a shift in the way one thinks about and perform experiments. With the emphasis on rigor and reproducibility in science, it's very important that researchers start putting into place everything they can do to help improve the quality and reproducibility of there data. Learn 3 action steps that can be taken to enhance experimental reproducibility.

Most people are familiar with coverslips being placed on slides to protect the sample, but that's not the only reasons that coverslips are important. They also affect the image quality. Coverslips function by working with your microscope to focus light to a single point and avoiding unnecessary noise in your image. Having the wrong type of coverslip will damage the quality of your images and the quality of the data you extract from those images.

There are so many downstream applications of cell sorting, but if you don’t take the time to do you cell sort the right way your downstream experiments won’t work. In order to have the most success with your cell sort be sure you consider these 3 things, size dictates almost everything you are going to do, sample preparation is key, and think about what type of tube you are collecting your cells in. If you account for those 3 things you will set yourself up for a successful cell sort and successful downstream applications.

Controls are an incredibly important part of your flow cytometry experiments. If not done correctly, poor controls will waste time and money. But with proper care, high-quality controls will result in high-quality data. Just be sure to ask yourself these key questions, should you be using isotype controls, do you have a quality control procedure in place, and are you following the 3 cardinal rules of compensation.

A lot of the troubleshooting is focused on fluidics issues. If you sit down and think about your workflow, and how you might want to add a couple of little tweaks here and there which will ultimately help you improve the quality of your data as well as aid you in identifying issues before they become problems your troubleshooting will be much smoother. Consider these three things, what do you before you start collecting data, ensure you have appropriate plots of time vs fluorescence for each of the lasers your using and apply appropriate gating procedures.

Cell sorting is a combination of a numbers game (Recovery), quality of output (Purity) and speed. For any experiment, the end goal is going to be measured by these three characteristics, and as soon as one of these measures is more heavily favored, the other two must be compromised in some manner. When designing a sorting experiment, start with the question of what will the cells be used for after sorting, and how many cells will you need for those experiments? That will set the minimum recovery that is needed. The second question is how pure do you need the cells? The requirements of the downstream assay will also dictate the purity needed. The cell type being used will, in part, dictate the speed of sorting. Smaller cells can be sorted faster because a smaller nozzle can be used. When you start a cell sort it’s important that you are aware of the downstream analysis and assays that you want to run. This will determine how you perform the sort and how you determine if your sort was successful or not. Successful cell sorting involves balancing recovery, yield and speed. What do these three terms mean and what influences each of these factors?

Cell sorting is a combination of a numbers game (Recovery), quality of output (Purity) and speed. For any experiment, the end goal is going to be measured by these three characteristics, and as soon as one of these measures is more heavily favored, the other two must be compromised in some manner. When designing a sorting experiment, start with the question of what will the cells be used for after sorting, and how many cells will you need for those experiments? That will set the minimum recovery that is needed. The second question is how pure do you need the cells? The requirements of the downstream assay will also dictate the purity needed. The cell type being used will, in part, dictate the speed of sorting. Smaller cells can be sorted faster because a smaller nozzle can be used. When you start a cell sort it’s important that you are aware of the downstream analysis and assays that you want to run. This will determine how you perform the sort and how you determine if your sort was successful or not. Successful cell sorting involves balancing recovery, yield and speed. What do these three terms mean and what influences each of these factors?

As a researcher, you want to achieve the best cell sorting possible. So, how can you achieve that? There are clear strategies you can use to achieve great cell sorting results, including finding your ideal sample concentration, using magnetic sorting to enrich your population, suspending cells in the right buffer to avoid cell clumps, changing your instrument settings when sorting small cells, and optimizing your sample preparation and instrument when sorting large cells.

Cell cycle seems like such a straightforward assay. At its heart, it is a one-color assay and should be a simple protocol to follow. However, as discussed before, fixation and dye concentrations are critical. Once those are optimized, it becomes important to run the cells low and slow in order to get the best quality histograms for analysis — the topic of another blog. Adding the critical CEN and TEN controls will help standardize the assay, and ensure consistency and reproducibility between runs while helping identify non-standard (aneuploid, polyploid) populations from normal ploidy. Trying to isolate and focus on specific components of the cell cycle can be done by addition of specific antibodies or using thymidine analogs. In the end, cell cycle analysis is a simple assay that has a great deal of potential. With work and optimization, a great deal of information about the life of a cell can be extracted.