Cell Separation Science and Technology - American Chemical Society

Chapter 2

High-Resolution Separation of Rare Cell Types 1

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James F. Leary , Steven P. Ellis , Scott R. McLaughlin , Mark A. Corio , Steven Hespelt , Janet G. Gram , and Stefan Burde 1

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Downloaded by UNIV OF ARIZONA on August 2, 2012 | http://pubs.acs.org Publication Date: June 10, 1991 | doi: 10.1021/bk-1991-0464.ch002

Department of Pathology and Laboratory Medicine and Division of Biostatistics, University of Rochester, Rochester, NY 14642

Isolation of cells by fluorescence-activated cell sorting, while useful, has been of only limited value. It is not a good isolation method for obtaining large numbers of cells. However, two recent developments, one in the technology of cell sorting and the other in the field of molecular biology make cell sorting extremely powerful for some applications. New high-speed (100,000 cells/sec) analysis and sorting of rare (0.01 percent) cell subpopulations allows more than 10,000-fold enrichments on the basis of multiple parameters, something not readily attainable by other cell separation technologies. Also, original frequency information important for studies in toxicology and genetics is not lost by this method. Second, application of new polymerase chain reaction (PCR) technologiesfrommolecular biology means that isolation of a single cell may be sufficient to provide necessary material for enzymatic expansion of cellular DNA or RNA to levels equivalent to 10 -10 cells. Thus a single sorted cell may provide preparative amounts of DNA or RNA for further characterization by standard molecular biology methodologies. 6

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Analysis and isolation of rare cell subpopulations are of interest to researchers and clinicians in many areas of biology and medicine including: (a) detection of somatic cell mutations (7) in mutagenized cells, (b) detection of human fetal cells in maternal blood for prenatal diagnosis of birth defects (2,3), (c) detection of CALLA+ cells (4), and (d) detection of minimal residual diseases (5). Conventional flow cytometer/cell sorters operating at rates below 10,000 cells/sec require many hours to analyze and/or isolate cell subpopulations of low frequencies (e.g. 10" -10" ). 5

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0097-6156/91/0464-0026$06.00/0 © 1991 American Chemical Society

In Cell Separation Science and Technology; Kompala, D., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1991.


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While analysis of rare cell subpopulations dates back to the 1970's, as for example in Herzenberg's early attempts to isolate fetal cells from maternal blood (3), rare-event analysis lacked the technology to make it a practical method for analysis and separation of rare cell subpopulations. There was an obvious need for faster cell processing speeds for analysis and sorting of rare cell subpopulations. Systems have been built to separate cells at rates of 15,000 - 25,000 cells/sec (6). While these systems employ newer methods and technological advances such as faster analog-to-digital converters and multi-stage buffering of incoming signals to achieve faster cell processing rates they retain the paradigm of the original flow cytometers/cell sorters, namely digitization and storage of information as correlated or uncorrelated data consisting of all signals from all cells. This paradigm, while important and necessary for some applications, particularly for processing of non-rare cell subpopulations, imposes severe and perhaps unnecessary restrictions on the analysis and sorting of rare cell subpopulations. A characteristic of "rare event analysis" is that most of the cells are not-of-interest. A simple but very important alternative paradigm is to classify signals as "of interest" or "not of interest" prior to digitization. It is then possible, using relatively simple circuitry, to count all cells for original frequency information but to only digitize information from cells "of interest" or from cells which cannot be reliably classified by this procedure. The benefits of such a paradigm are two-fold. First, the circuitry required to operate flow cytometers at rates of more than 100,000 cells/sec becomes simpler and less expensive and can be implemented on existing commercially available flow cytometers. Second, it reduces the problems of storing and analyzing data sets containing 10 - 1 0 cells by storing only data of interest or data about which the experimenter cannot be certain as to whether it must be stored for further analysis. Data classified by the system as "not of further interest" can be counted but not digitized and/or stored. This chapter describes a method and apparatus for the multiparameter highspeed measurement of a rare subpopulation of cells amidst a larger population of cells with differing characteristics. A multiparameter hardware/software system (U.S. patent pending) was developed which, when attached to a multiparameter flow cytometer/cell sorter and microcomputer, allowed multiparameter analysis of cells at rates in excess of 100,000 cells/sec. This system is an outboard module which can, with minor modifications, be attached to any commercially available or home-built flow cytometer. It allows analysis of 100,000,000 cells in less than 15 minutes as opposed to more than 6 hours on the same instrument without this module. The system provides for high speed counting, logic-gating, and countrate error-checking. Indirectly, by acting as a high-speed front-end filter of signals, the system can be used to control high-speed cell sorting. Actual instrument dead-time depends on the pulse widths of the signals as well as delay lines, if used. The actual through-put rate is limited not by the signal and software processing times, but rather by the in-excitation-beam cell 7

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coincidence caused by asynchronous cell arrival times in the cell sorter or similar type of device. Use of thresholds and logical gating from total and rare cell signals with other non-rare signals allows multiparameter rare-event listmode data (a record of all pulses for each rare cell and the total number of cells to obtain original frequency information vital to many applications) to be acquired reasonably both in terms of signal processing speeds and total amount of data to be stored by a conventional second-stage data acquisition system. Analysis of these multiparameter rare-event data also permit reduction or elimination of many "false positives", an important problem in the analysis and isolation of rare cell subpopulations (see Figure 1). This is achieved by further data processing techniques such as principal component/biplot analysis, provided by a second-stage out-board module. Some basic problems of rare cell sorting Specific labeling, no matter how it is defined, requires that the signal be greater than the "noise". The goal of specific labeling is then to improve the signal-tonoise (S/N) ratio to the point where it permits unequivocal identification of rare cells for cell sorting. In a study of Rh incompatibility (2) we previously demonstrated that indirect immunofluorescence labeling of Rh-positive cells could not be accomplished at the level of 0.1 percent rare cells due to an insufficient S/N ratio. However, using the same primary antibody but using a secondary antibody labeled with a fluorescent bead we were able to analyze and sort rare cells as low as .002 percent. Not only was the signal from the immunobead more than 200 times brighter than by normal indirect immunofluorescence, but the background "noise" non-specific binding was actually less, resulting in an outstanding S/N ratio for this application. This labeling approach was not as good for some other applications such as those involving cells which can phagocytize immunobeads. However, a multiparameter labeling approach can give even better results. Many false-positive cells can be eliminated by requiring the presence or absence of two or more fluorescent signals using either specific or non-specific antibodies labeled with different fluorescent colors. Addition of other intrinsic flow cytometric parameters such as cell size (by pulse width time-of-flight) or 90-degree light scatter, can significantly reduce the number of false-positive cells, thereby improving the overall S/N of the situation. To sort rare cells from a mixture requires "specific labeling" of these cells. Everyone hopes that the rare cells can be separated on the basis of a single parameter (e.g. immunofluorescence using a highly specific monoclonal antibody). However, this is not usually the case. Even the most highly specific monoclonal antibodies usually are insufficient for unequivocal identification of the rare cells. Quite often, the number of false-positives is several times that of the number of true-positives. However, if multiple labels are used the situation


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Figure 1: Special high-speed (HISPED) and principal component/biplot analysis and sorting system (BASS) modules shown on the right can be linked to existing commercial and home-built flow cytometer/cell sorters shown on the left. The DNA or RNA from rare sorted cells can be enzymatically amplified by polymerase chain reaction (PCR) to yield preparative amounts of DNA or RNA for Southern or Northern blotting analyses. is usually improved. Each label, while having some amount of non-specificity, adds new information. More importantly, true-positive cells differ from the false-positive cells when they are labeled according to combined parameters. Properly chosen combinations of specific labels correlate with each other with a positive correlation on the true-positive cells; but non-specific labels on falsepositive cells have little or no correlation with one another. This fact enabled us to use principal component/biplot sorting as described later in this chapter to separate true-positives from false-positives. A need for high speed signal processing electronics In the studies described in Cupp et al. (2), early experiments without the present high-speed system required nearly 6 hours to run a positive sample and another 6 hours to run the control sample. Use of special high-speed circuitry which allowed analysis at rates in excess of 100,000 cells/sec reduced the time per sample to approximately 15 minutes. In conventional cell sorters, the total instrument dead-time for processing each cell is on the order of 50-100 microseconds. These deadtimes cause most cells to be missed by the system



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when more than 20,000 cells/sec are processed. Our high-speed pre-processing circuitry, when acting as a front end-filter to a conventional flow cytometer/cell sorter, reduces this deadtime to 2 microseconds. This deadtime could be further improved by using one or more secondary buffering stages in the signal processing electronics. Few cells are missed by the system at rates in excess of 100,000 cells/sec. For example, at 150,000 cells/sec queuing theory based on random, Poisson arrival statistics predicts that only 1.9 percent of the cells will be missed due to instrument deadtime. Our experimental data agree well with that predicted by queuing theory, provided that the cells are not damaged and sticky and provided that the viscosity of the sample stream is equivalent to that of 0.25% bovine serum albumin in phosphate buffered saline. The actual deadtime of the system may vary to be slighdy more than this depending on the size of the cells and the laser beam width, but is typically less than 3 microseconds for all applications to date. The high-speed system attempts to classify cells as "positive/not sure", or "negative". Only "positive/not-sure" cells are passed on to the analog-to-digital converters to be digitized. For the application to Rh-incompatibility described in Cupp et al. (2), we were able to find fetal R h cells in maternal blood at frequencies as low as 10" . However, for other applications such as the isolation of fetal nucleated cells for subsequent genetic analysis the false-positive background from the maternal cells did not permit successful isolation of fetal cells on the basis of a single parameter. In fact, even multiparameter high-speed analysis of these fetal cells did not permit their successful isolation at very high purity. This led us to develop a second-stage system which looks at the correlations between multiple parameters on the "positives/not-sure" cells, not just their signal intensities as is done by conventional flow cytometry. This second-stage processing unit BASS (Biplot Acquisition and Sorting System) ( Figure 2) then attempts to correctly classify the "not-sure" cells into "true positives" and "false positives" so that only "true positives" are sorted. The joining of the high-speed and BASS systems is shown in more detail in Figure 3. +

Sorting speed versus purity Sorting of rare cells is limited by the number of droplets/sec. The problem is a straight-forward application of queuing theory. If cells arrive randomly, they are distributed among the subsequently-formed droplets according to a Poisson distribution. At typical sorting rates of 2000 cells/sec, the probability of two cells occurring inside the same droplet ("coincidence") is negligible. However, at higher rates the coincidence rate sharply increases. To sort cells of high purity (95%) at rates of 5000 cells/sec or greater requires "anti-coincidence" circuitry which rejects all cells which are close enough to be sorted in the same droplet or droplets (there may be more than one droplet in each sorting unit). At very high sorting rates (e.g. 100,000 cells/sec), there will be multiple cells in each sorted


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Photodetectors t Data Acquisition

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Droplet & Charge Control Hardware Downloaded by UNIV OF ARIZONA on August 2, 2012 | http://pubs.acs.org Publication Date: June 10, 1991 | doi: 10.1021/bk-1991-0464.ch002

PDP-11/73 Figure 2: The BASS (Biplot Acquisition and Sorting System) module provides for both real-time acquisition and transformation of data in principal component space so that subpopulations of cells as seen in projections of higher dimensional space can be visualized by human observers. Biplot analyses reveal "true-positive" and "false-positive" cell subpopulations so that the "true-positives" rare cells can be sorted at very high purity. High-Speed Multiparameter Rare Cell Analysis and Sorting > 100,000 CELLS/SEC ANALOG

BOOLEAN LOGIC

HIGH-SPEED MULTIPARAMETER! PRE-PROCESSING MODULE

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MICR0VAX II t = £ j COMPUTER FOR CALCULATION OF PRINCIPAL COM PONENT COEFFICIENTS AND BIPLOTS

1 GB 2.3 GB HARD * 8 mm DISK |

Cell Separation Science and Technology - American Chemical Society

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