Cell Growth

Posted on February 28, 2011 by admin

M. Mir, Z. Wang, Z. Shen, M. Bednarz, R. Bashir, I. Golding, S. Prasanth and G.Popescu, Optical Measurement of cycle-dependent growth , Proc. Natl. Acad. Sci., 108 (32), (2011).

Determining the growth patterns of single cells offers answers to some of the most elusive questions in contemporary cell biology: how cell growth is regulated and how cell size distributions are maintained. For example, a linear growth in time implies that there is no regulation required to maintain homeostasis; an exponential pattern indicates the opposite. Recently, there has been great effort to measure single cells using microelectromechanical systems technology, and several important questions have been explored. However, a unified, easy-to-use methodology to measure the growth rate of individual adherent cells of various sizes has been lacking. We have demonstrated that SLIM can measure the cell dry mass of many individual adherent cells with femotrgram accuracy in various conditions, over spatial scales from micrometers to millimeters, temporal scales ranging from seconds to days, and cell types ranging from bacteria to mammalian cells. We found evidence of exponential growth in Escherichia coli, which agrees very well with other recent reports. Perhaps most importantly, combining spatial light interference microscopy with fluorescence imaging provides a unique method for studying cell cycle-dependent growth. Thus, by using a fluorescent reporter for the S phase, we measured single cell growth over each phase of the cell cycle in human osteosarcoma U2OS cells and found that the G2 phase exhibits the highest growth rate, which is massdependent and can be approximated by an exponential.

Figure 1 here shows SLIM measurements of E. coli growth. (A) Dry mass vs. time for a cell family. Growth curves for each cell are indicated by the colored circles on the images. Images show single cell dry mass density maps at the indicated time points (in minutes). (Scale bar: 2 ìm.) (Inset) Histogram of the dry mass noiseassociated with the background of the same projected area as the averagecell (SD ó = 1.9 fg is shown). The blue line is a fixed cell measurement, with SD of 19.6 fg. Markers indicate raw data, and solid lines indicate averageddata. (B) Growth rate vs. mass of 20 cells measured in the same manner. Faint circles indicate single data points from individual cell growth curves, dark squares show the average, and the dashed line is a linear fit through the averaged data; the slope of this line, 0.011 min.1, is a measure of the average growth constant for this population. The linear relationship between the growth rate and mass indicates that, on average, E. coli cells exhibit exponential growth behavior.

Figure 2 here shows a SLIM measurement of U2OS growth over 2 days. This is the first time to our knowledge that cycle dependent growth is measured at the single cell level. (A) Dry mass density maps of a single U2OS cell over its entire cycle at the times indicated. (Scale bar: 25 μm.) Color bar indicates dry mass density in pg/μm2. (B) Simultaneously acquired GFP fluorescence images indicating PCNA activity; the distinct GFP signal during S phase and the morphological changes during mitosis allow for determination of the cell cycle phase. (C) Dry mass vs. time for a cell family (i.e., 1→2→4 cells). The two different daughter cell lineages are differentiated by the filled and open markers; only one daughter cell from each parent is shown for clarity. Different colors indicate the cell cycle as reported by the GFP–PCNA fluorescence. The dotted black line shows measurements from a fixed cell, which has SD of 1.02 pg.

Although population-level measurements on various cell types reveal exponential or linear growth patterns, we can expect large variability in results from different cell types. Our experiments on E. coli show that, on average, the cells follow an exponential pattern, although there is large variation among single cells in the same population. These types of variations are expected from a biological system and are of scientific interest in themselves; by studying the variations in the growth patterns of single cells under varying conditions, we may help elucidate some of the underlying regulatory processes. Because SLIM is an imaging technique, we may also simultaneously calculate the volume of regularly shaped cells such as E. coli. This ability allows us to explore questions of cell density and morphology and their roles in mass regulation. For E. coli, we found that the density is relatively constant, which is consistent with the exponential growth model for this organism. SLIM is also a powerful tool for studying the relationship of cell cycle stage, growth, and mass measurement in complex mammalian cells.

By taking advantage of the ability of SLIM to be implemented as an add-on to a commercial microscope, we can use all other available imaging channels. By combining SLIM with fluorescence, it is possible to combine the quantitative nature of interferometry with the specificity provided by fluorescent molecular probes. In conclusion, the results presented here establish that SLIM provides a number of advances with respect to existing methods for quantifying cell growth: (i) SLIM can perform parallel growth measurements on an ensemble of individual cells simultaneously; (ii) spatial and temporal correlations, such as cell–cell interactions, can be explored on large scales; (iii) in combination with fluorescence, specific chemical processes may be probed simultaneously; (iv) the environment is fully biocompatible and identical to widely used equipment; (v) the imaging nature of SLIM offers the ability to directly monitor cells and their surroundings, elucidating the nature of any artifacts and providing morphological information simultaneously; (vi) a lineage study is possible, i.e., a cell and its progeny may be followed; and (vii) measurements can be performed on cells ranging from bacteria to mammalian cells.