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Slit Scanning of Saccharomyces cerevisiae Cells: Quantification of Asymmetric Cell Division and Cell Cycle Progression in Asynchronous Culture David E. Block, Philip D. Eitzman, Jeffrey D. Wangensteen, and Friedrich Srienc* Department of Chemical Engineering and Materials Science and Institute for Advanced Studies in Biological Process Technology, University of Minnesota, St. Paul, Minnesota 55108

Slit scanning flow cytometry has been applied to the analysis of the cell cycle and cellcycle-dependent events in Saccharomyces cerevisiae, yielding information on the lowresolution spatial distribution of cellular components in single cells of unperturbed cell populations. Because this process is rapid, large numbers of cells can be analyzed t o give distributions of parameters in a given population. T o study asymmetric cell division and cell cycle progression, forward-angle light scattering (FALS) signals together with fluorescence signals from acriflavine-stained nuclei have been measured in cells from exponentially growing yeast populations. An algorithm has been developed that assigns the position of the bud neck in the FALS signals so that both FALS and DNA signals can be analyzed in terms of the contributions from the mother cell and the cell bud. The data indicate t h a t mother cell FALS, on average, remains constant while FALS due to the cell bud increases as a cell progresses through the cell cycle. By identifying mitotic cells and measuring their properties, we have found that the coefficient of variation for the distribution of FALS is smallest within the dividing cell population and largest within the newborn cell population, in accordance with the critical size control mechanism of yeast cell growth. The use of this experimental approach to provide data for statistical population models is discussed.

Introduction In Saccharomyces cerevisiae, asexual reproduction occurs by budding and asymmetric cell division (Wheals, 1987; Pringle and Hartwell, 1981). Typically, the resulting daughter cell is smaller than the corresponding mother cell as both cells enter the GI cell cycle phase. The amount of time that each of these cells remains in GI phase, however, depends on its size. The larger mother cell enters the DNA replication period within a shorter time after cell division than the corresponding smaller daughter cell, thus indicating the presence of a proliferation control mechanism prior to the initiation of DNA synthesis. The point in the cell cycle where this control acts has been termed "start" and has been shown to be related to critical concentrations of certain intracellular factors (Mendenhall, 1987; Hadwiger, 1989; Richardson, 1989). The segregation of cellular material a t cell division and progression through the cell cycle, especially at major control points, are important features of the S. cereuisiae cell cycle. A temporal and functional map of the cell cycle has been established on the basis of a variety of morphological and biochemical landmarks that occur during the cell cycle of S. cereuisiae. These landmarks include events such as initiation of DNA synthesis, chitin ring formation, bud emergence, spindle elongation, and nuclear migration prior to mitosis (Wheals, 1987;Pringle and Hartwell, 1981;Hanes et al., 1986). These specific cell cycle events and cell division have traditionally been studied either with microscopic analysis of single cells (Hereford and Hartwell, 1974; Hartwell, 1967; Hartwell et al., 1970) or with cell populations synchronized through treatments such as temperature shift (Hereford and Hartwell, 1974) or

* To whom correspondence should be addressed.

addition of mating pheromone (Mendenhall et al., 1987). While microscopic procedures can usually be applied only to a limited number of cells on a solid support, induction of culture synchrony requires perturbation of normal cell growth. A method that has been used extensively to observe morphological and low-resolution spatial features of mammalian cells and mammalian cell mitotic chromosomes is slit scanning in conjunction with flow cytometry (Wheeless, 1973; Wheeless et al., 1979; Robinson et al., 1989; Cram et al., 1985; Gray et al., 1979). We have adapted this method to the study of asynchronous populations of yeast cells (see Figure 3) and show in this work that slit scanning is feasible with microbial cells. This type of measurement is particularly useful in connection with budding yeast since the measurement yields information on the spatial distribution of specific cell components in individual cells. This is of interest with regard to the distribution of specific components in the mother cell and the emerging cell bud during the cell cycle. We show that it is possible to obtain quantitative information on the sizes of mother cells and cell buds at various points in the cell cycle. Furthermore, mitotic and postmitotic cells can be identified with this technique and the degree of asymmetry a t cell division can be estimated. In this study, we detail the optimization and verification of our slit scanning and data analysis system. By using this methodology, distributions of cellular and subcellular characteristics in exponentially growing S. cerevisiae populations have been determined.

Materials and Methods Strains and Growth Conditions. The tetraploid S. cerevisiae strain DB4212 (MATa MATa MATa MATa

8756-7938/90/3006-0504$02.50/00 1990 American Chemical Society and American Institute of Chemical Engineers

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ade2-101 his3 lys2-801 met regl-501) used in this study was constructed from derivatives of D603i (Srienc et al., 1986) by using mating with nutritional markers. Cells were grown in YPD medium containing 1%Bacto Yeast Extract (Difco, Detroit, MI), 2 % Bacto-Peptone (Difco), and 2% glucose (Sherman et al., 1979). To ensure that cells were harvested in exponential growth phase, 50 mL of YPD in a 250-mL Erlenmeyer flask was inoculated with approximately 1mL from a 5-mL overnight culture and incubated a t 30 "C in a shaking incubator for a t least 4 h. Cell Staining. The nucleotide-specific fluorescent strain acriflavine (Sigma, St. Louis, MO) was used to stain DNA in cells (Crissman et al., 1975; Doran and Bailey, 1986). Exponential cells (1.5 mL) were harvested a t a concentration of approximately 5 X 106cells/mL. Samples were centrifuged at 14 000 rpm for 3 s in an Eppendorf centrifuge 5415 (Brinkmann Instruments, Westbury, NY), and the pellet was resuspended in 0.3 mL of cold (4 "C) distilled water. Next, 0.7 mL of 95% ethanol was added and the cells were fixed on ice for 20 min. After fixation, the cells were centrifuged and resuspended in 0.7 mL of 4 N HC1 for 20 min a t room temperature. Addition of HC1 accomplishes removal of purines from the DNA by acid hydrolysis, a necessary step in acriflavine staining, and also hydrolyzes cellular RNA (Crissman et al., 1975). Cells were centrifuged and the supernatant was decanted. Then, 0.7 mL of acriflavine staining solution (100 mL of distilled water, 20 mg of acriflavine, 10 mL of 0.5 N HC1, and 500 mg of KzSzOb) was added to the cells and the mixture was allowed t o incubate for 20 min a t room temperature. Finally, cells were recovered and washed three times with 0.7 mL of an acid alcohol solution (1mL of concentrated HC1+ 99 mL of 70 70 ethanol) and then suspended in 0.7 mL of distilled water. Stained cells were stored a t 4 "C until analyzed. Cells could be analyzed for a t least 1week subsequent to staining without loss of the quality of the DNA distributions. Flow Cytometry. An Ortho Cytofluorograf 11s flow cytometer (Ortho Diagnostics Systems, Westwood, MA) was used in conjunction with a n Ortho 2151 d a t a acquisition system ( O r t h o Diagnostic Systems). Measurements were carried out in the standard nonsorting analytical flow cell. Illumination was accomplished with a Coherent Innova 90-5 argon ion laser (Coherent, Palo Alto, CA) at a wavelength of 488 nm with a power output of 200 mW. Stained cells were analyzed by measuring forward-angle light scatter (FALS) simultaneously with the acriflavine (DNA) fluorescence by using a yellow long-pass filter (OG-530,Rolyn, Covina, CA). DNA signals were processed in area and peak mode, and the data were stored in list mode for later analysis. Slit Scanning. Slit scanning was performed with an Iwatsu DS-6121 dual-trace digitizing oscilloscope (Iwatsu Electric Company, Japan) with a sampling rate of 20 MHz per channel interfaced with an IBM Model 30 microcomputer (IBM Corp., New York) with a math coprocessor through an IEEE 488 general-purpose interface bus (GPIB). The preamplified signals of the flow cytometer photomultiplier tubes were used as input for the oscilloscope. Data acquisition was controlled by the microcomputer running routines in the Asyst programming language (MacMillan Publishing Co., Rochester, NY) and was triggered by a signal from the discriminator of the flow cytometer. Controls on the discriminator allowed the selective acquisition of waveforms from cells with defined properties. As many as 200 pairs of waveforms were acquired consecutively and stored for later data analysis. In this configuration, one acquisition cycle took less than

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Figure 1. Peak reflect algorithm for locating bud neck position. First, the peak of the original smoothed waveform is found and marked as point A. The mother cell portion of the waveform is then reflected around this point to give the symmetric curve 1. Next, curve 1 is subtracted from the original waveform to give curve 2. The position of the peak in curve 2 (point C) is then located, and used for reflection of the bud portion of the original waveform to give curve 3. The intersection of curves 1 and 3 locates point B, which we have defined as the position of the bud neck.

5 s, and therefore many cells could be analyzed in a relatively short period of time. Data Analysis. The objective of the waveform analysis was to estimate the location of the bud neck from the single cell waveforms so that contributions to the signal by mother cell and cell bud could be evaluated. The empirical algorithm developed for this purpose assumes that the FALS signal obtained is proportional to the crosssectional area of the illuminated cell. The algorithm consists of three parts. First, a pair of raw waveforms (FALS and DNA fluorescence) was prepared for analysis by digital filtering by using a Blackman window (Blackman and Tukey, 1958) to minimize the effect of noise in the signals. At the same time, the smoothed waveforms were deconvolved to reduce the broadening of the peaks contributed by the finite width of the illuminating laser beam slit (Norgren et al., 1982). Second, after the waveforms were prepared in this manner, the number and location of peaks in the FALS signal were found by using a point-to-point comparison method. If more than two peaks were present in this signal, the pair of waveforms was assumed to be a signal from multiple cells and was skipped. The third and final step was to analyze the pairs of waveforms that exhibited two peaks in the FALS signal. To do this, the skewness of the FALS waveform was first used to indicate whether the bud portion of the cell was positioned on the right or the left of the waveform. After the position of the bud was established, a peak reflect algorithm was applied to the FALS signal to identify the location of the bud neck between the contributions of the mother cell and bud to the total cell (Barlogie et al., 1976). This analysis is illustrated for a typical waveform in Figure 1. After the position of the bud neck was estimated, the portions of the FALS waveform on either side of the estimated bud neck position were integrated to give mother cell size and bud size along with total cell size. Similarly, total DNA content and DNA peak height were determined from the DNA fluorescence waveform. In addition, nuclear position was derived from the distance between the location of the bud neck in the FALS signal and the peak DNA content location for each evident nucleus. Data from all cells in the waveform file were automatically stored in a spreadsheet file for further analysis of whole cell populations. This algorithm takes approximately 4-6 s on a microcomputer (IBM PS2/50 with a math coprocessor) for each pair of waveforms.

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Figure 2. Verification of the analysis algorithm using simulated cell waveforms. Simulated cell waveforms, approximated by touching spheres of various bud-to-mother size ratios and convolved with a Simulated laser beam, were analyzed by using our algorithm and the ratios compared with the actual ones. These simulated cells were also rotated to various angles in relation to the direction of flow, and the resulting waveforms analyzed for bud-to-mothersize ratios. Good agreement is seen until at least 35’. (A),waveforms with a bud-to-mother ratio of 1.0; (A),0.7; (a),0.5; and (o),0.3. Algorithm Verification. In order to verify the validity of the developed algorithm, simulated waveforms were generated with specified bud-to-mother size ratios. The budding cell was assumed to be represented by two touching spheres of different diameter. This simulated “image” of a cell was mathematically convolved with a simulated Gaussian-shaped laser beam to yield a simulation of a signal obtained with the slit scanning procedure. These waveforms, along with simulated waveforms of cells oriented at varying angles to the simulated laser beam, were then analyzed with the developed algorithm. Good agreement between calculated and actual size ratios was found for ratios above 0.1 a t angles less than 40’ from the axis perpendicular to the laser beam (Figure 2). This observation demonstrates the necessity of keeping cells oriented correctly, although slight deviations from a perfect orientation, even up to 40°,will not significantly affect the result of the analysis.

Results The general principle of slit scanning is shown in Figure 3. As cells travel through the light beam that is focused to a narrow slit, they generate a time-dependent light signal that corresponds to a scan of a particular cell along its axis that is parallel to the flow. In cases where the measured light can be related to a biological quantity, the obtained waveform shows how the biological quantity is spatially distributed along the scanning axis of a cell. To increase the resolution of the measured signals, dictated by the finite dimension of the light beam, we have used a tetraploid strain of S. cerevisiae that is proportionally larger than its isogenic versions of lower ploidy (Murray, 1987; D. E. B., unpublished data). These cells are therefore larger in relation to the laser beam, and obtained signals were expected to have a more detailed substructure than in the case of smaller haploid or diploid cells. Measured waveforms included simultaneous detection of the forwardangle light scattering (FALS) signal, as an indicator of cell size (Salzman e t al., 1990), and a fluorescence signal, reflecting cellular DNA content after staining with the nucleic acid specific stain acriflavine (Crissman et al., 1975). The acriflavine stain is excited a t a wavelength of 488 nm and is detected at wavelengths greater than 530 nm. The choice of the FALS signal as an indicator for cell size was mainly dictated by experimental restrictions. One of the

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Figure 3. Slit scanning of individual yeast cells. Onedimensional, low-resolution,spatial distributions of both FALS and DNA fluorescence are generated as a cell passes through the highly focused laser beam.

main reasons for this choice was that measured DNA distributions based on the acriflavine-stained DNA gave consistently better results than after staining with propidium iodide. For detection in a single-laser flow cytometer, the latter DNA stain could be combined with a total protein stain, which in turn would represent a better defined measure for cell size (Crissman et al., 1985). While ethanol fixation prior to staining may change the scatter properties of the yeast cells, measurements on fixed cells should be valid, since all of the cells in the population undergo the same treatment and all measurements are on a relative basis. Orientation of Cells during Measurements. One of the factors that affects the interpretation of slit scanning data is the orientation of the scanned object as it passes through the laser beam. In fact, the value of slit scanning data would be restricted if one did not know the scanning axis of the object. Lucas and Pinkel (1986) have shown that a region exists in the flow cell of a flow cytometer in which the fluid flow is extensional, and in this region of accelerating fluid, objects with an aspect ratio greater than unity tend to align their longitudinal axis with the direction of flow. As the flow becomes fully developed, objects have a tendency t o tumble a n d t h u s take on a random orientation. In order to find the region of extensional flow in our system, fluorescent 6-pm beads (Polysciences, Warrington, PA) were analyzed as described. Bead doublets were selected with the discriminator by using a twodimensional frequency distribution function, or cytogram, correlating FALS and fluorescence intensities. Waveform pairs were collected with the laser beam a t various distances from the inlet of the flow cell. Three types of waveforms were observed. The first type of signal consisted of a unimodal signal that has been attributed to particles that are not oriented along their longitudinal axis. The second type of signal was a bimodal waveform characterized by the presence of a minimum between the two modes or by a shoulder with zero slope (Lucas and Pinkel, 1986). This type of signal is apparently due to doublets that are closely oriented along their longitudinal axis, and the fraction of bead doublets with this orientation was evaluated. The third type of signal consisted of two unimodal, well-separated peaks, most likely generated by doublets that separated shortly before the signals were acquired. Waveforms from bead doublets that had separated were not included in these calculations. From the data in Figure 4, it can be seen that the extensional flow region for our system extends at least 1.2

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Figure 4. Fraction of correctly oriented bead doublets as a function of distance from the flow cell inlet. Waveforms of

fluorescent bead doublets were collected with the laser positioned at various distances from the flow cell inlet. Fluorescent signals with two distinct peaks or a shoulder with zero slope were scored as doublets with correct orientation (see text). mm from the inlet of the flow cell. When the laser beam is positioned within this region, 80%-90% of the bead doublets are correctly oriented. This maximum percentage is consistent with that determined for other instruments (Lucas and Pinkel, 1986). Farther from the inlet, the orientation becomes random, giving a relatively constant fraction of correctly oriented doublets of about 50 % . All further experiments with yeast cells were performed with the laser beam positioned within 1mm of the flow cell inlet. Cell Cycle Position Determination and Sample Waveforms. After fixation of cells from an exponentially growing population and staining of the DNA with acriflavine, whole cell characteristics were examined by using conventional flow cytometry. A cytogram correlating the FALS intensity with fluorescence intensity based on the DNA content is shown in Figure 5A. One can clearly identify the cell fractions in the GI and in the G2 + M cell cycle periods. In addition one can see that with increasing cell cycle progression the FALS signal increases, as is expected if FALS is a reasonable measure of cell size. In Figure 5B, the integral of the measured fluorescence signals is plotted versus the peak height of the fluorescence signals. This representation of the data has the advantage that cells undergoing mitosis as well as binucleate cells can be identified. These cells generate a fluorescence signal the integral of which corresponds to a DNA content of cells after DNA replication; however, the peak height of the fluorescence signal is lower because the DNA in these cells is partitioned into two nuclei. This cell population presumably does not represent cell doublets since mild sonication and sample dilution did not decrease the magnitude of this fraction of cells, which was approximately 19%. As calculated from the age distribution according to the mixed mother-daughter cell cycle model (Slater, 19771, this fraction indicates that cells spend a period of 28 min in this cell cycle phase out of a total doubling time of 112 min. With this type of peak versus area fluorescence cytogram, cells in a particular cell cycle phase can be selected by using the discriminator of the flow cytometer and their slit scanning signals acquired as described. Typical waveforms obtained with this procedure are shown in Figure 6. In Figure 6A, signals from a GI phase cell are displayed. The FALS signal is symmetric, indicating that the cell apparently is unbudded. The corresponding fluorescence peak reflects the DNA content in the nucleus. Because the two signals were acquired a t the same time, the relative occurrence of the DNA signal with respect to the FALS

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Figure 5. Cytograms of acriflavine-staned yeast populations. The DNA of ethanol-fixed yeast cells was stained with the fluorescent stain acriflavine as described and analyzed by using standard flow cytometry. A cytogram of DNA fluorescence in area mode versus FALS (A) allows differentiation of the subpopulation of cells in GI phase and cells in G2 + M phases with S-phase cells between. When DNA fluorescence in area mode is plotted versus the DNA fluorescence in peak mode (B),the Gz and M phase cells can also be differentiated since M-phase dividing nuclei have the same total DNA but approximately half the peak fluorescence as mononucleated G2 cells.

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Figure 6. Typical pairs of waveforms obtained through slit scanning of S. cereuisiae cells in various stages of the cell cycle. FALS and DNA waveforms were acquired simultaneously from

the various regions of the DNA area versus peak fluorescence cytogram as described in the text and represent (A) an unbudded G1-phase cell, (B)a G2-phase cell, and cells in early (C)and late (D) mitosis. signal indicates the position of the nucleus within the cell. One can recognize that the nucleus is located in the center of the cell, since the positions of the peaks in the FALS and DNA signals coincide. Figure 6B shows the signal pair of a cell in the G2 cell cycle phase. The FALS signal shows a distinct asymmetry due to a second peak or shoulder that most likely reflects the growing cell bud. As the bud continues to grow, this peak becomes larger and more distinct. In addition, the area under the corresponding DNA signal is twice as large as the signal for the GIphase cell, indicating that DNA replication has been completed. As cells move into mitosis, two peaks appear as the nucleus begins to divide (Figure 6C). Cells in later stages of mitosis can be recognized by the presence of two more widely separated DNA peaks, indicating that nuclear division is completed and that the nuclei are spatially separated (Figure 6D). The peaks of the DNA waveform are symmetric, as is expected for correct segregation of the nuclear material, while the peaks of the FALS waveform have different magnitudes, reflecting the asymmetric nature of cell growth in budding yeast. Cell Growth during the Cell Cycle. A characteristic of S. cerevisiae cells is that, after the initiation of S phase,

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DNA Content Figure 7. Mother cell and bud size as a function of DNA content. The upper figure is a contour plot of relative mother cell size as a function of DNA content. The mean mother cell size increases slightly during GI phase and then remains relatively constant throughout the cell cycle. The lower figure is a contour plot of the relative bud size as a function of DNA content on the same axes. Here, bud size is seen to grow continuously from late GI phase into Gz phase.

de novo cell wall synthesis, and therefore size increase, occurs almost exclusively in the cell bud (Streiblova, 1984; Cabib and Roberts, 1982). With the assumption that the area of the measured FALS signals reasonably reflects the size of individual cells, one should anticipate that mother cell sizes, on average, should be constant while the size of the cell bud should increase as cells progress through the cell cycle. To test this and to investigate the distribution of measured single-cell properties, slit scanning data were acquired and analyzed for a large number of cells. In a typical experiment using fixed cells from an exponential culture with acriflavine-stained nuclei, 800 pairs of waveforms from the total cell population were acquired and analyzed in terms of mother cell contribution and cell bud contribution to the overall signal. Also, 600 additional pairs of waveforms were acquired from the mitotic and dividing cell subpopulation by using the peak versus area fluorescence cytogram and gating technique described previously. The signals were analyzed with the described algorithm, and the contributions to the FALS signal by the mother portion and by the bud portion of individual cells were calculated. The data are plotted in Figure 7 as a function of DNA content to indicate the cell cycle position of the individual cells. If FALS is assumed to be an indicator of cell size, the data indicate that the size of the mother cell remains almost constant throughout the cell cycle while the size of the cell bud increases throughout the cell cycle. When the mean FALS is calculated for each class of cells with a given DNA content, mother cell size appears to increase slightly during the GI phase, while for the remainder of the cycle, this mean size remains relatively constant. It can also be seen in this plot that growth in the bud portion of the cell commences after GI phase and continues through the rest of the cell cycle. In addition,

even though these cells are in exponential growth, bud size does not quite reach the mother cell size at the end of the cell cycle, indicating the asymmetric nature of cell division in this yeast. The nonzero bud size at the GI peak in this figure is due to a threshold level for bud detection in the analysis algorithm. This level was implemented to avoid artifacts that could arise due to false buds found in signal noise. The level of this threshold is set to optimize the observation of true buds while avoiding detection of artifacts. Quantification of Asymmetric Cell Division. The partitioning of cell material at cell division has a major influence on the behavior of a growing cell population, since this partitioning determines the properties of individual cells a t birth. However, little data is available on this aspect of cell growth, presumably because of the lack of methods that can (i) identify dividing cells and (ii) quantify the properties of dividing cells. The type of analysis described here permits evaluation of the population of dividing cells as identified by the occurrence of a double peak in the DNA signal. The calculated contributions of the mother cell and the cell bud should reflect their relative sizes at cell division. Furthermore, this calculation should permit the prediction of the properties of the newborn cell population. T h e FALS signals of the dividing cell population and of the predicted newborn cell population in relation to the distribution of FALS signals in the total cell population are shown in Figure 8A. Because the mother cell is presumably larger at cell division than the corresponding daughter cell, it is possible to identify newborn mother and daughter cells within the total population of newborn cells (Figure 8B). The distribution of newborn daughter cell size and the distribution of their corresponding parent cells have a different mean value. The distributions, however, are wide enough so that their tails overlap, i.e., large daughter cells are as big as small mother cells. The displayed distributions of newborn cells do not reveal the relationship between the size of a daughter cell and its associated parent cell. A better representation of the partitioning process is given by the so-called partitioning function (Ramkrishna, 1979),which is the joint frequency distribution function of the observed cell property in the dividing cell population and in the resulting daughter or parent cell population. This partitioning function describing cell division as obtained with slit scanning is shown in Figure 9. One can see from this contour plot that newborn mother cell size is correlated with cell size at division. Linear regression on the data yields a correlation coefficient ( R )of 0.8 for a straight line with slope 0.58 and intercept 0. One should note that the slope of this line represents a measure of the asymmetry of cell division. In the case of symmetric division, the slope of this line would be 0.5. Table I summarizes the features of FALS distributions before and after cell division. Of particular interest is the coefficient of variation (CV) that provides a means of expressing the variability in the cell population. The coefficient of variation of the distribution of FALS signals of dividing cells in Figure 8A is 12.6% while the CV of the distribution of all newborn cells is 23.4%, nearly twice the value for dividing cells. Because of the asymmetric cell division, this larger variation in the total newborn cell population should be expected. The CV for the calculated newborn daughter cell distribution is 16.4% and for the newborn mother cells 18.2 74, which are also larger than the values obtained for the dividing cell population. The variability of the cell population must therefore decrease during the cell cycle, and it is conceivable that this decrease

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Figure 8. Distribution of sizes in subpopulations of a n exponentially growing yeast population. Distributions in the size of newborn cells were calculated from the mother (open bars) and bud (solid bars) sizes of cells undergoing division (A). Added together,these distributionsgive the distribution of total newborns in the populations (- - -). (B) The size distribution of the dividing cells (- -) was calculated by using the total integrated area under the FALS signal for the same population used for the newborn distribution (- - - -). The distribution for total cells (open bars) was derived from data for cells from all stages of the cell cycle. The distributions in (B) have been normalized to give a total area of 1.

occurs at start, the key control point in the cell cycle of S. cereuisiae. The data are therefore consistent with the size control mechanism of cell cycle progression that equalizes initial differences in cell size a t the entry into the S cell cycle phase. This type of critical size control has been studied in S. cereuisiae by Johnston et al. (1977) and others (Hartwell and Unger, 1977; Carter and Jagadish, 1978) and has also been observed to a lesser extent in mammalian cells (Darzynkiewicz et al., 1982). Estimation of the Position of the Nucleus. Microscopically observable events that occur during the cell cycle have provided specific landmarks that are characteristic of the status of cell cycle progression. The migration of the nucleus to the bud neck is one such event that can be easily observed in the microscope. With the slit scanning procedure, t h e position of t h e nucleus along t h e longitudinal cell axis as a function of cell cycle position can be readily determined and quantified in combination with the determination of the DNA content. Data obtained from 1400 cells from an exponentially growing culture are summarized in Figure 10. Here the position of the nucleus is expressed as relative distance between the identified bud neck (position 0) and the center of the mother cell (position 1). The position of a nucleus in the daughter cell portion of a binucleate cell is indicated by a negative distance in this plot. Distance data are plotted versus the measured DNA content of cells to indicate the position of particular

Figure 9. Mother cell contribution of FALS plotted versus total cell FALS at cell division. The mother cell contribution was estimated as described and should indicate its size after division is completed, Le., in its newborn state. Note that the demonstrated correlation allows the prediction of the sizes of newborn cells from the sizes of dividing cells. The five contours shown represent20%,40%,60%,80%,and 100% ofthemaximumcell frequency. Table I. Statistical Properties of Size Distributions meana standard deviation CV, 7% distribution newborns mother cells daughter cells total newborns dividing cells total population

39.07 28.46 33.77 67.20 51.56

6.42 5.18 7.89 8.46 12.45

16.4 18.2 23.4 12.6 24.1

Expressed in relative units. cells within the cell cycle. As can be seen from the graph, the nuclei, on average, are positioned approximately in the center of the mother cell at the beginning of S phase. The nucleus is then seen to migrate gradually to the bud neck during the S and GP phases of the cell cycle. It can also be observed, though, that the nuclei do not actually migrate all of the distance to the bud neck but stop while still at a normalized distance of 0.4 on the mother cell side of the bud neck. Light and electron microscope observations corroborate this evidence in that they show that the nucleus moves toward the bud neck a t some point after bud emergence. The nucleus then extends a process into the bud that becomes the new nucleus after the completion of process elongation (King and Hyams, 1982; Byers and Goetsch, 1973, 1975). Therefore, the centroid of the nucleus, when plotted versus cell cycle position, should and does move completely to the bud neck as the two nuclei become even in size during mitosis (data not shown). After mitosis, the two nuclei are again seen to be located in the centers of their respective newly formed GI-phase cells.

Discussion Slit scanning flow cytometry is a measurement technique that has been applied in numerous investigations of mammalian cell systems. In this procedure, the speed of flow cytometric analysis, which normally yields information only on the total composition of a cell, is combined with elements of image analysis to provide rapid access to onedimensional spatial information on individual cells. We

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Figure 10. Migration of the nucleus during the cell cycle of S. cereuisiae cells. Migration of nuclei is followed by calculating the distance between the peak of the DNA fluorescence signal and the position of the bud neck. All values are normalized by the distance from the peak of the mother cell FALS signal to the bud neck. In this contour plot, the thin lines represent data for cells in S and Gz phase, where a definite movement from a location of 1 (center of the mother cell) toward a position of 0 at the bud neck is evident. The contours with thicker lines represent the mitotic cells with two nuclei. Nuclei in cells derived from the bud portion of the mitotic cell are assigned a negative position for clarity.

have demonstrated in this paper that slit scanning flow cytometry is feasible with microbial systems and that it yields particularly useful information in the case of the budding yeast S. cereuisiae. Because of the formation of the cell bud, the cell morphology has a spatial orientation that can serve as a reference to localize and to identify specific cell structures and compartments. Moreover, because budding cells have an aspect ratio greater than 1, they become oriented in the flow channel of the flow cytometer due to hydrodynamic forces. This provides the basis for the slit scanning measurement and the interpretation of the obtained signals in terms of a spatial distribution of specific cell characteristics along this longitudinal axis. The interpretation of the measured data from yeast cells is based on the algorithm developed to identify the location of the bud neck on a cell. The localization of the bud neck permits quantification of the mother cell portion and bud portion of a single cell. Several arguments can be made that indicate that the estimation of the bud neck location within a cell is reasonably approximated by the algorithm. First, computed images of touching spheres of various sizes that simulate budding cells are accurately analyzed and correctly decomposed into contributing sphere sizes. The orientation studies have shown that a deviation in the orientation of particle doublets of up to 40' relative to the direction of flow does not significantly affect the performance of the algorithm. Therefore, it can be anticipated

that real measurements, in which some variation in cell orientation occurs, will yield correct results. Second, the result that mother cell sizes, on average, are almost invariant during the cell cycle strongly supports, although in an indirect manner, the correct performance of the algorithm, since several other studies have shown that, after bud emergence,cell growth is concentrated in the emerging cell bud (Wheals, 1987). The expected behavior of growing yeast cells is therefore confirmed with the data obtained. The main advantage of using this type of slit scanning configuration in the study of yeast cell cycle progression is that it enables large numbers of cells from unperturbed populations to be analyzed quickly. Because this method can be used to examine subcellular characteristics and intracellular distributions of cellular components, it is possible to quantify the occurrence of morphological landmarks during the cell cycle. Slit scanning would therefore provide an attractive way to rapidly characterize genes that are essential in cell cycle progression and control, including those that affect processes such as nuclear migration and those that have been closely associated with proliferation control, such as the cyclin genes (Hadwiger et al., 1989; Richardson et al., 1989). These latter types of genes are often present in multiple copies and thus require a more subtle quantification of phenotypic traits, since conventional microscopic analysis relies on singlegene mutations that cause an absolute arrest at some cell cycle landmark. In order to study the influence of partitioning of cellular material a t cell division on the characteristics of normal cell growth, it is necessary to be able to identify both dividing and newborn cells. In our analysis of the asymmetric division of cell mass, we have made two assumptions. First, we have made the assumption that the population of cells that are about to divide can be approximated by all mitotic and postmitotic cells. Second, we have assumed that the characteristics of the mother cell and bud portions of this dividing cell population represent a good approximation of the characteristics of the population of newborn cells that will arise from them. These assumptions are necessary in this approach, in that it is impossible to observe the characteristics of dividing cells instantaneously as cell division occurs. As stated previously, the population of mitotic and postmitotic cells used for these calculations represents about 20% of the total population, and 28 min of a 112-mincell cycle, though a more accurate depiction of the dividing and newborn populations would result from the exclusion of cells that have just begun mitosis. This could be accomplished by using a critical distance between peaks in the DNA fluorescence signal as the criterion for placing cells at a stage of mitosis or, alternatively, by choosing a smaller population from which to acquire waveforms in the DNA peak versus area cytogram shown in Figure 5B. One should note that the data have been obtained with a commercially available instrument without any specific modification. With a more efficient data transfer system and an oscilloscope capable of acquiring three to four waveforms, slit scanning will become an even more powerful tool for finding low-resolution spatial distributions of cellular components. In addition, specific fluorescent probes (Eitzman et al., 1989) in conjunction with this technique should allow for studies of segregation patterns of proteins and other suborganellar material that have proved to be important in the control of cellular proliferation. A possible immediate application of these slit scanning measurements is the examination of relative bud size at cell division as an indicator of growth rate. Since

Biotechnol. Prog., 1990, Vol. 6, No. 6

relative bud size can be correlated with the growth rate of individual cells, factors that affect the distribution of growth rates in a population, such as the distribution of plasmid copy number, could be investigated by using this method. Furthermore, this analysis, in conjunction with standard cell sorting technology, could provide a basis for isolating cells according to growth rate, provided the speed of data analysis could be increased. Sorting of mammalian chromosomes on the basis of centromeric index as determined from slit scanning data has been demonstrated (van Oven and Aten, 1990; Bartholdi et al., 1990). Because of the speed of the measurement, properties of many cells can be evaluated and their distribution within a cell population can be determined. Such data form the basis for a statistical description of population behavior. The theoretical framework of statistical population models was established over two decades ago (Collins and Richmond, 1962; Bell and Anderson, 1967; Harvey et al., 1967; Ramkrishna, 1979). However, their application has been limited by the lack of accessibility t o critical experimental data needed to make them useful. These data include population characteristics a t particular transition stages during the cell cycle such as at cell division or at cell birth. The slit scanning procedure described here provides access to this type of data. Therefore, it is anticipated that in combination with statistical population models, the developed methodology will provide a useful tool in the study of fundamental biological questions from a different perspective, as well as a novel approach to biochemical engineering problems related to the dynamics of cell growth.

Acknowledgment This work was made possible through support by the National Science Foundation (Grants BCS-8619399 and BCS-8819747) and by the Graduate School of the University of Minnesota. J.D.W. was partially supported by the REU program of NSF and the Undergraduate Research Opportunity Program of the University of Minnesota. We thank J. W. Gray for helpful discussions and for making a waveform recorder available to us. Literature Cited Barlogie, B.; Drewinko, B.; Johnston, D. A.; Buchner, T.; Hauss, W. H.; Freireich, E. J. Pulse Cytophotometric Analysis of Synchronized Cells in Vitro. Cancer Res. 1976, 36, 11761181. Bartholdi, M. F.; Parson, J. D.; Albright, K. A.; Cram, L. S. System for Flow Sorting Chromosomes on the Basis of Pulse Shape. Cytometry 1990, 11, 165-172. Bell, G. I.; Anderson, E. C. Cell Growth and Division I. A Mathematical Model with Applications t o Cell Volume Distributions in Mammalian Suspension Cultures. Biophys. J. 1967, 7,329-351. Blackman, R. B.; Tukey, J. W. The Measurement of Power Spectra; Dover: New York, 1958; pp 95-100. Byers, B.; Goetsch, L. Duplication of Spindle Plaques and Integration of the Yeast Cell Cycle. Cold Spring Harbor Symp. Quant. Biol. 1973,38, 123-131. Byers, B.; Goetsch, L. Behavior of Spindles and Spindle Plaques in the Cell Cycle and Conjugation of Saccharomyces cerevisiae. J . Bacteriol. 1975, 124, 511-523. Cabib, E.; Roberts, R. Synthesis of the Yeast Cell Wall and Its Regulation. Annu. Rev. Biochem. 1982, 51, 763-793. Carter, B. L. A.; Jagadish, M. N. The Relationship between Cell Size and Cell Division in the Yeast Saccharomyces cereuisiae. Exp. Cell Res. 1978, 112, 15-24. Collins, J. F.; Richmond, M. H. Rate of Growth of Bacillus cereus Between Divisions. J . Gen. Microbiol. 1962, 28, 15-33. Cram, L. S.; Bartholdi, M. F.; Wheeless, L. L.; Gray, J. W. In Flow Cytometry: Instrumentation and Data Analysis; Van Dilla,

511

M. A., Dean, P. N., Laerum, 0. D., Melamed, M. R., Eds.; Academic Press: Orlando, FL, 1985; pp 163-194. Crissman, H. A.; Mullaney, P. F.; Steinkamp, J. A. In Methods in Cell Biology, Vol. 9; Prescott, D. M., Ed.; Academic Press: New York, 1975; pp 179-246. Crissman, H. A.; Darzynkiewicz, Z.; Tobey, R. A.; Steinkamp, J. A. Correlated Measurements of DNA, RNA, and Protein in Individual Cells by Flow Cytometry. Science 1985,228,13211324. Darzynkiewicz, Z.; Crissman, H.; Traganos, F.; Steinkamp, J. Cell Heterogeneity During the Cell Cycle. J. Cell. Physiol. 1982, 113,465-474. Doran, P. M.; Bailey, J. E. Effects of Immobilization on Growth, Fermentation Properties, and Macromolecular Composition of Saccharomyces cerevisiae Attached to Gelatin. Biotechnol. Bioeng. 1986,28, 73-87. Eitzman, P. D.; Hendrick, J. L.; Srienc, F. Quantitative Immunofluorescence in Single Saccharomyces cerevisiae Cells. Cytometry 1989, 10,475-483. Gray, J. W.; Peters, D.; Merrill, J. T.; Martin, R.; Van Dilla, M. A. Slit-Scan Flow Cytometry of Mammalian Chromosomes. J. Histochem. Cytochem. 1979,27,441-444. Hadwiger, J. A.; Wittenberg, C.; Richardson, H. E.; de Barros Lopes, M.; Reed, S. I. A Family of Cyclin Homologs t h a t Control the GI Phase in Yeast. Proc. Natl. Acad. Sci. U.S.A. 1989,86, 6255-6259. Hanes, S. D.; Koren, R.; Bostian, K. A. Control of Cell Growth and Division in Saccharomyces cerevisiae. CRC Crit. Rev. Biochem. 1986,21, 153-223. Hartwell, L. H. Macromolecule Synthesis in Temperaturesensitive Mutants of Yeast. J. Bacteriol. 1967, 93, 16621670. Hartwell, L. H.; Unger, M. W. Unequal Division in Saccharomyces cereuisiae and Its Implications for the Control of Cell Division. J. Cell Biol. 1977, 75, 422-435. Hartwell, L. H.; Culotti, J.; Reid, B. Genetic Control of the CellDivision Cycle in Yeast, I. Detection of Mutants. Proc. Natl. Acad. Sci. U.S.A. 1970, 66, 352-359. Harvey, R. J.; Marr, A. G.; Painter, P. R. Kinetics of Growth of Individual Cells of Escherichia coli and Azotobacter agilis. J . Bacteriol. 1967, 93, 605-617. Hereford, L. M.; Hartwell, L. H. Sequential Gene Function in the Initiation of Saccharomyces cerevisiae DNA Synthesis. J. Mol. Biol. 1974, 84, 445-462. Huffaker, T. C.; Thomas, J. H.; Botstein, D. Diverse Effects of 0-Tubulin Mutations on Microtubule Formation and Function. J. Cell Biol. 1988, 106, 1997-2010. Johnston, G. C.; Pringle, J. R.; Hartwell, L. H. Coordination of Growth with Cell Division in the Yeast Saccharomyces cereuisiae. Exp. Cell Res. 1977, 105, 79-98. King, S.M.; Hyams, J. S. The Mitotic Spindle of Saccharomyces cereuisiae: Assembly, Structure, and Function. Micron 1982, 13, 93-117. Lucas, J. N.; Pinkel, D. Orientation Measurements of Microsphere Doublets and Metaphase Chromosomes in Flow. Cytometry 1986, 7, 575-581. Mendenhall, M. D.; Jones, C. A,; Reed, S.I. Dual Regulation of the Yeast CDC28-p40 Protein Kinase Complex: Cell Cycle, Pheromone, and Nutrient Limitation Effects. Cell 1987,50, 927-935. Murray, L. E.; Veinot-Drebot, L. M.; Hanic-Joyce, P. J.; Singer, R. A.; Johnston, G. C. Effect of Ploidy on the Critical Size for Cell Proliferation of the Yeast Saccharomyces cerevisiae. Curr. Genet. 1987,11,591-594. Norgren, R. M.; Gray, J. W.; Young, I. T. Restoration of Profiles from Slit-Scan Flow Cytometry. IEEE Trans. Biomed. Eng. 1982, BME-29, 101-105. Pringle, J. R.; Hartwell, L. H. In The Molecular Biology of the Yeast Saccharomyces: Life Cycle and Inheritance; Strathern, J. N., Jones, E. W., Broach, J. R., Eds.; Cold Spring Harbor Laboratory: Cold Spring Harbor, NY, 1981; pp 97-142. Ramkrishna, D. In Advances in Biochemical Engineering, Vol. 11; Ghose, T. K., Fiechter, A., Blakebrough, N., Eds.; SpringerVerlag: Berlin, 1979; pp 1-47.

512

Richardson, H. E.; Wittenberg, C.; Cross, F.; Reed, S. I. An Essential GI Function for Cyclin-likeProteins in Yeast. Cell 1989,59,1127-1133. Robinson, R. D.; Reeder, J. E.; Wheeless, L. L. Technique for Cellular Fluorescence Distribution Analysis. Cytometry 1989, 10,402-409. Salzman, G. C.; Brito Singham, S.; Johnston, R. G.; Bohren, C. F. In Flow Cytometry and Sorting, 2nd ed.; Melamed, M. R., Lindmo, T., Mendelsohn, M. L., Eds.; Wiley-Liss: New York, 1990;pp 81-107. Sherman, F.; Fink, G. R.; Hicks, J. Methods in Yeast Genetics; Cold Spring Harbor Laboratory: Cold Spring Harbor, NY, 1979; p 61. Slater, M. L.; Sharrow, S. 0.; Gart, J. J. Cell Cycle of Saccharomyces cereuisiae in Populations Growing at Different Rates. Proc. Natl. Acad. Sei. U.S.A.1977,74, 3850-3854.

Biorechnol. Pmg., 1990, Vol. 6,No. 6

Srienc,F.; Campbell, J. L.; Bailey, J. E. Flow Cytometry Analysis of Recombinant Saccharomyces cereuisiae Populations. Cytometry 1986,7, 132-141. Streiblova,E. In The Microbial Cell Cycle; Nurse, P., Streiblova, E., Eds.; CRC Press: Boca Raton, FL, 1984;pp 127-141. van Oven, C.; Aten, J. A. Instrument for Real-Time PulseShape Analysis of Slit-Scan Flow Cytometry Signals. Cytometry 1990,11,630-635. Wheals, A. E. In The Yeasts, Vol. 1; Rose, A. H., Harrison, J. S., Eds.; Academic Press: Orlando, FL, 1987;pp 283-390. Wheeless, L. L. Slit-Scan Cytofluorometry. Acta Cytol. 1973, 19,333-339. Wheeless, L. L.;Hardy, J. A.; Bdasubramanian, N. Slit-ScanFlow System for Automated Cytopathology. Acta Cytol. 1979,19, 45-52. Accepted September 21,1990.

Slit scanning of Saccharomyces cerevisiae cells: quantification of asymmetric cell division and cell cycle progression in asynchronous culture.

Slit scanning flow cytometry has been applied to the analysis of the cell cycle and cell-cycle-dependent events in Saccharomyces cerevisiae, yielding ...
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