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Understanding the optical system of a flow cytometer may seem unnecessary for performing a typical experiment, but the more you know about your instrument, the better you will be at understanding your data, as well as troubleshooting potential issues. This article breaks down 4 elements of flow cytometer optics to provide a broad understanding on its impact on fluorescence.

Every experiment has the goal of ensuring consistent and reproducible data. This makes the proper use of controls to establish the boundaries of gates critical. With the exception of one controversial control discussed in this article, each one of these gating controls plays an important and specific role toward the goal of reproducibility. Using these gating controls in every experiment will reduce data variability within the experiment, as well as between labs and institutions.

Flow cytometry (FCM) datasets that are currently being generated will be two orders of magnitude larger than any that exist today. Reproducibility continues to be a critical area that all researchers need to be aware of and researchers need to keep up on best practices to stay relevant. One area that flow cytometry researchers should be focusing on is the emerging changes in the area of automated data analysis. This brief article explains why.

The last 40 years have seen significant advancements in cell sorting technology. Cell sorting is often the entry point for many experiments. Fluorescent Activated Cell Sorting (FACS) combines the traditional power of flow cytometry and couples it with the ability to isolate the cells of interest. Understanding the inner workings of the instruments and some rules for preparing samples will lead to more successful experiments. Here are 4 essential facts about FACS.

Multicolor sorting experiments can be complicated and if not setup properly, result in wasted time and suboptimal results. When setting up a multicolor experiment, the most saliently critical step is to set PMT voltages properly. In addition, using a viability dye and addressing doublet discrimination and setting the right sort regions and gates is important for any kind of flow cytometry experiment, but particularly for cell sorting. These tips help to ensure your setup is perfect to achieve results of the highest caliber.

When sitting down to perform a new analysis of flow cytometry data, the researcher is guided by very particular laws of nature and a very specific method of working through a biological hypothesis to avoid shaping the results to his or her whims. Following these 5 data analysis and gating strategies through the hierarchy described in this article, researchers are provided with several strategies for identifying and displaying the most relevant data from their flow cytometry experiments.

Implementing a system of quality assurance protocols lends confidence to the data collected, especially for those researchers performing longitudinal studies. Optimal instrument setting, cytometer sensitivity, and monitoring of day-to-day variability in measurement leads to improved assurance for those using this instrument to collect their critical data. QC programs will continue to be prudent measures for cytometrists to take as they align with the current emphasis on quality and reproducibility.

When preparing figures for publication, the scientific question and hypothesis that forms the basis of the paper must be central and all the figures must be in support of that. The flow cytometry data that forms the basis of the conclusions should be presented clearly and concisely. While it provides pretty pictures and colorful layouts, the meat of the data are the numbers ― percentages of populations, fluorescent intensity levels and the like ― are what will convince the reader that the hypothesis tested is valid and well thought out. Here’s how to choose the correct flow figure for presenting your data.

Cell sorters have become more sophisticated to rival the multicolor capabilities of analytical cytometers with cell sorting experiments becoming more complicated to match. While multicolor sorts are very feasible and can yield excellent results, success is always a product of very careful planning and optimization. From choosing optimal fluorophores to strategies to reducing spillover spreading, this comprehensive article is broken into two parts to give you all you need to play your experiments for advanced accuracy.

Cellular proliferation is a critical component in biological systems. While normal cell proliferation keeps the body functioning, abnormal proliferation (such as in cancer) can be a target for therapy. There are several critical components in developing, validating and optimizing an assay to make these measures using flow cytometry. Knowing the steps to optimize these assays and properly interpret the results will help ensure the best data and best opportunities are pursued.

Fluorochrome emission is the lifeblood of flow cytometry. The use of in silico tools, like spectral viewers, can save a lot of effort and missed opportunity by allowing for the modeling of excitation and emission profiles in the context of what filters a given instrument is equipped with. Using these tools, it is easy to identify where a new fluorochrome will be measured on an instrument, where a fluorochrome may cause issues with other fluorochromes, and what filters are best for detection. These tools can save a lot of troubleshooting at the beginning of an experiment, and also help provide understanding when issues appear.

Sorting efficiency, in fundamental terms, is a real-time measurement, generated by the instrument, of how successfully its sorting system is able to resolve cells that we want to sort (target events) from cells we do not want to sort (non-target events). In order for the instrument’s sort output be acceptable with respect to the researcher’s needs, it is not sufficient to simply tell the instrument WHAT to sort, but is also critical to tell the instrument HOW to sort the target population. The HOW is determined by the sort modes.