Power and versatility make flow cytometry a cornerstone in modern vaccinology and immunology. One of the most powerful application of this platform is for evaluate drug and vaccine efficacy. Multiparameter flow cytometry relies on the use of fluid systems, fluorescent proteins, and optical systems to detect and collect fluorophore signals. When the technology first became available multiparameter meant 2 colors, today it can mean up to 32 colors. The availability of dyes and antibodies along with hardware and software improvements, make possible simultaneous analysis of a wide range of parameters. Researchers can probe a single cell for multiple markers, define the composition of a cell population or evaluate protein expression levels. However, with complex multiparameter experimental design come challenges to generating reproducible and publishable data.
Below are briefs on design, execution and analysis items to keep in mind when planning flow cytometry experiments.
One of its advantages is that cytometry can be used to generate a lot of data per cell basis. Researchers can probe a heterogeneous cell population derived from almost any solid tissue or body fluid. Regardless of the source, the cell processing protocol must be optimized to yield homogenous, single-cell suspension of viable cells. The protocol must therefore be optimized for pH, temperature and other conditions that will impact cell viability and/or produce autofluorescence. And, it must also yield sufficient numbers of quality cells for analysis. Sample quality directly correlates to data quality. As in every scientific experiments, technical skill and expertise is the only guarantee for experimental success.
Flow cytometry can be applied to almost any type of study if a fluorescent probe/marker is available for it. However, it requires the correct combination of fluorophores and antibody conjugates titrated to match the expression level for the marker(s) of interest. Titration is a simple but important control for minimizing nonspecific binding and optimizing signal detection to ensuring reducibility of experimental results. Each panel must also include appropriate controls specific to each experiment. Controls must include dyes to exclude signals from unwanted cell population and to differentiate signals from damaged or dying cells. While it may be possible to use up to 32 colors, more is not always better in flow cytometry. With increasing number of fluorochromes there is some loss of sensitivity due to background and spillover. The best way to compensate for this phenomenon is to design panels with the minimum number of markers needed to address specific research questions. And, of course to optimize the instrument to capture weak signals but exclude background noise. Instrument manufacturers will provide performance test certification. However, quality control beyond machine performance is a best practice for producing highest quality data.
Data acquisition & analysis:
Flow cytometry can be used to analyze population frequency and expression on the order of tens of thousands to millions of cells at a time. With simultaneous evaluation of several parameters, researchers can generate large volumes of data from a limited quantity of samples, fast. However, to be informative the data must capture relevant events and in sufficient numbers. This relies on gating strategies that effectively exclude coincidental and background noise. The large and complex data files flow cytometry yields can be both challenging and time consuming to analyze. Making sense of the seemingly random colored dots requires expert analysis and standardized statistical analysis methods.
Flow cytometry has evolved a great deal since its inception. It has become a powerful and versatile research tool. Reproducibility is the key to scientific discovery. Continued evaluation and optimization of flow cytometry best practices is key to generating publishable results.