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Planning For Surface Staining Of Cells In Flow Cytometry

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Written by Tim Bushnell, Ph.D

One of the most common assays in flow cytometry is the surface labeling of cells with antibodies. Often termed “immunophenotyping”, it allows the researcher to identify, count, and isolate cells of interest in a mix of input cells. Every lab has their own favorite protocol, handed down from some hallowed, chemical-stained notebook, and followed as exactly as making a souffle.

The real questions are, which of those steps are critical, and (with changes in instruments and theory) what other factors should be considered when staining cells? This article will focus on staining immune cells, but the principles apply in general, and specific issues for a specific sample type can be optimized in a similar way.

Cell Preparation

A protocol usually starts with a list of equipment that is needed. After that, the next important component is obtaining and preparing a sample. A good, single-cell suspension is essential for quality flow cytometry.

The source of your primary tissue will guide you down a path for processing. For liquid samples like blood, bone marro ...

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2 Key SPADE Parameters To Adjust For Best Flow Cytometry Results

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Written by Tim Bushnell, Ph.D

Mass cytometry panels routinely include 30 or more markers, but traditional analysis methods like bivariate gating can’t adequately parse the resulting high-dimensional data.

Spanning-tree progression analysis of density-normalized events (SPADE) is one of the most commonly used computational tools for visualizing and interpreting data sets from mass cytometry and multidimensional fluorescence flow cytometry experiments.

There are two key parameters in SPADE that you can adjust in order get the best results possible: downsampling and target number of nodes, or k. Knowing how to properly set these values will enable you to enhance the quality of your analysis.

Downsampling

Imagine your data as a cloud of points in high dimensional space, where each dimension is one of the measured markers.

Cells that are similar to each other are close to one another in this cloud, just as similar cells fall together on a biaxial gating plot. This means that the cloud contains dense regions where there are groups of similar cells, and more sparsely populated regions wh ...

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3 Advantages Of Using The ZE5 Cell Analyzer

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Written by Tim Bushnell, Ph.D

Since the first laser was mounted to create the first flow cytometer, there has been a push for more – more lasers, more detectors, and more colors.

Why?

So researchers could ask more complicated questions to squeeze every iota of data out of rare events and precious samples, and so clinicians could expand the diagnostics capabilities of the technology. In addition, this trend has occurred so biotech companies could expand high-content screening for drug discovery.

Instrument manufacturers have brought to the table a plethora of different instruments, with capabilities to suit the needs of the researcher, at price points to make the accountants happy, with all improvements in hardware, software and automation to make the operator’s job easier. Often, these are based on an extension of the available equipment a vendor currently has.

Due to these improvements, the average researcher today has capabilities that were previously possible in only a very few specialized laboratories.

The Democratization of Flow Cytometry

What happens when an inst ...

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The Difference Between Linear And Log Displays In Flow Cytometry

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Written by Tim Bushnell, Ph.D

Data display is fundamental to flow cytometry and strongly influences the way that we interpret the underlying information.

One of the most important aspects of graphing flow cytometry data is the scale type. Flow cytometry data scales come in two flavors, linear and logarithmic (log), which dictate how data is organized on plots. Understanding these two scales is critical for data interpretation.

Let’s start at the beginning, where signal is generated, and trace its path all the way from the detector to the display.

Behind every flow cytometry data point is what we call a pulse. The pulse is the signal output of a detector generated as a particle transits the laser beam over time. As the cell passes through the laser beam, the intensity of the signal from the detector increases, reaches a maximum, and finally returns to baseline as the cell departs the laser beam. The entirety of this signal event is the pulse (see Figure 1).

Figure 1: The voltage pulse begins when a cell enters the laser, hits its maximum when the cell is maximally illuminated, the ...

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4 Ways To Achieve Reproducible Flow Cytometry Results

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Written by Tim Bushnell, Ph.D

Reproducibility is one of the hallmarks of the Scientific Method. One reason scientists publish their results is so that other labs can attempt to reproduce the results and extend the investigation into new areas.

From the Begley and Ellis commentary in Nature, to the development of the Rigor and Reproducibility initiative at NIH, to articles in the mainstream media, reproducibility is on everyone’s mind. This is not a bad thing, and following the best practices in flow cytometry provides investigators, peer reviewers, and colleagues with more confidence in your data.

There are several areas within the process of developing, implementing, and reporting a flow cytometry experiment where a little additional work, attention to proper controls, and careful planning will ensure reproducible data generation.

Instrumentation: Characterization, Optimization, and Quality Control.

The first line of defense for good, reproducible data is the instrument.

A properly maintained machine ensures that it is not introducing error in the data. A researcher needs to ...

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