Modern Flow Cytometry: A Practical Approach

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The demonstration that CD T-cell counts can be used to monitor HIV disease progression opened the way to the first clinical application for fluorescence activated cell sorting (FACS) technology. Modern FACS methodologies such multicolor staining and sorting has opened the way to new and constructive therapeutic and clinical applications. This article outlines approaches in which current users can use to improve the quality of their FACS work without undue effort. FACS technology development and the emergence of new software support for this technology are cooperating in this effort.

Section snippets

Collecting fluorescence-activated cell sorting data

FACS instruments measure the amount of light emitted by fluorescent molecules associated with individual cells. Lasers are used to excite the fluorescent molecules, which are excited at one range of wavelengths and emit at a second range. Filters in front of each of a series of detectors restrict the light that reaches the detector to only a small range of wavelengths. Newer FACS instruments have up to four lasers and 18 or more detectors, commonly referred to as channels [9]. Older FACS

Fluorescence compensation

Most FACS instruments have fluorescence compensation hardware that can be set to correct for spillover. This utility, which enables real-time visualization of subsets in the format that approximates (or is) the way they usually are viewed, is crucial for setting gates for cell sorting. It also has been used for many years to generate FACS data sets to which compensation corrections already are applied, and it still is used by many laboratories.

In early versions, these hardware compensation

Logicle versus logarithmic visualization

Logarithmic scales have been used for years to visualize FACS data for data collection and data analysis. Because logarithmic scales are asymptotic to zero, however, they cannot be used to correctly represent values for cells whose fluorescence values fall at or below zero. They are the result of background subtraction and fluorescence compensation. This always has caused a problem because negative values for FACS data points are real. Therefore, a display method that provides an accurate place

Roadmap

The sections that follow summarize procedures that the authors have established or adopted to make the collection and analysis of FACS data easier and more accurate. Examples are presented of high-dimensional FACS analyses of human peripheral blood cells stained with reagent sets that reveal typical leukocyte and lymphocyte subsets of interest in the clinical world. Finally, in closing is a brief discussion of new software support for experiment planning, data annotation, and data archiving.

Staining peripheral blood cells: proper controls and more colors result in better subset resolution

Properly staining cells with fluorochrome-conjugated antibodies, fluorescent compounds, or substrates clearly is the key to successful FACS analyses. Following are suggestions.

Set the instrument up correctly

The hardware design for FACS instruments has progressed much in the past few years. With the incorporation of digital detection, linear data collection, and software-computed compensation matrix and overlay, the data quality collected in these digital instruments has increased dramatically compared with the data acquired using the analog FACS instruments. The new digital instruments correctly record data points that fall at or below zero after the instrument background is subtracted.

Logicle

Compute the fluorescence compensation matrix and apply it to the data

Choose a data analysis program that has a compensation utility. Import the data into the program and use the utility provided to specify the data sets collected for the singly compensation controls that are to be used to compensate the experiment data for each stain set (staining combination). After the matrices are computed, apply each to the data for the appropriate samples. The authors use the FlowJo data analysis package for this purpose [21].

Data for compensation controls always should be

Summary

Considering the amount of time, effort, money, and patient sample material that goes into FACS studies every year, it is surprising that FACS studies for so long have relied on methodology developed in what might reasonably be termed, “the dark ages of FACS.” This discussion has attempted to outline ways in which current FACS users can get more from their FACS work without undue effort. Fortunately, FACS technology development and the emergence of new software support for various aspects of

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