Optically Measuring Single Cell Mass

Femtogram Sensitivity and Cycle Dependent Growth

  • Fig. 1: Quantitative dry mass density map of a pair of human osteosarcoma cells acquired using Spatial Light Interference Microscopy (SLIM). SLIM is a non-invasive optical method which may be used to measure the dry mass of single cells with femtogram accuracy. In conjunction with fluorescence microscopy, SLIM can be used to study how a single cells growth rate changes depending on its age and current cell cycle stage.Fig. 1: Quantitative dry mass density map of a pair of human osteosarcoma cells acquired using Spatial Light Interference Microscopy (SLIM). SLIM is a non-invasive optical method which may be used to measure the dry mass of single cells with femtogram accuracy. In conjunction with fluorescence microscopy, SLIM can be used to study how a single cells growth rate changes depending on its age and current cell cycle stage.
  • Fig. 1: Quantitative dry mass density map of a pair of human osteosarcoma cells acquired using Spatial Light Interference Microscopy (SLIM). SLIM is a non-invasive optical method which may be used to measure the dry mass of single cells with femtogram accuracy. In conjunction with fluorescence microscopy, SLIM can be used to study how a single cells growth rate changes depending on its age and current cell cycle stage.
  • Fig. 2: Schematic of a SLIM system. SLIM is designed to attach to the imaging port (IP) of a commercial phase contrast microscope (Zeiss Axio Observer Z1 shown). The microscope is fitted with an incubator allowing cells to be measured continuously for weeks. The SLIM module itself consist of a 4f lens system (L1 and L2) a beam splitter (BS), liquid crystal phase modulator (LCPM) to modulate the phase and an imaging CCD. The light path is indicated by the red arrows. By scanning and stitching it is possible to cover millimeter scale samples with sub-micron resolution, the image shows a culture of U2OS cells measured in such a manner, the colors in the image correspond to the dry mass density at each pixel.
  • Fig. 3: Not just an exponential: U2OS cells exhibit cell cycle dependent growth.
  • Fig. 4: Imaging a System: SLIM provides the ability to measure biological systems at a wide range of temporal and spatial scales providing insight on several fundamental biological phenomena.

The ability to measure single cell growth is of fundamental importance to our understanding of biological systems. Despite several major efforts, studying this phenomenon has remained largely intangible due to the simple fact that cells are small and only double their mass during their lifetime. In order to draw conclusions on growth trends and gain insight on growth regulatory systems, the required sensitivity to mass is in the order of femtograms.


The question of how single cells regulate their growth has been described as "one of the last big unsolved problems in cell biology" [1]. The major question has been whether cells grow at a constant (linear) rate or proportional to their size (exponential). This question is essential to understating how a constant cell size distribution (homeostasis) is maintained. If the growth is exponential, any small difference in the size of two daughter cells at the time of division would be compounded with each generation. Thus, a growth trend which is proportional to the cell size requires a robust, intrinsic regulatory system to maintain homeostasis. On the other hand, if the growth is constant no such special mechanism is necessary. It has been calculated that measuring the difference between these two trends requires sensitivities of less than 6% of the cells size. For single cells this translates to a required sensitivity on the order of femtograms.

Until recently, the only reliable method to address this problem has been to measure cell size distributions using an impedance counter and apply statistical analysis to draw conclusions on growth rates [2]. Such approaches assume that measuring volume is analogous to measuring mass and furthermore limit understanding of the inherent cell to cell variability present in any population. Over the last two years several new methods that utilize Microelectromechanical systems (MEMS) technology have been introduced which are capable of measuring single cell mass with the required accuracy [3, 4]. However, these methods have their own limitations: they are either capable of measuring non-adherent cells with high throughput but no lifecycle information at the single cell level, or measuring adherent cells, but one at a time.

In light of these efforts, it is clear that the ideal method for measuring cell growth should have the ability to follow single cells throughout their life-cycle, be compatible with many cell types (adherent/non-adherent, prokaryotes, eukaryotes, etc.), be non-invasive and also work on spatial scales ranging from the population level (millimeters) down to subcellular (microns). Here we show that Spatial Light Interference Microscopy approaches this ideal. SLIM can be used to quantitatively measure dry mass with femotogram accuracy for a variety of cell types, over several cell cycles and at spatial scales ranging from millimeters to sub-micron.

Optical Measurement of Cell Mass

In the 1950's, soon after the invention of phase contrast microscopy, it was shown that the refractive index of a solution is linearly related to the concentration of the solute by a quantity known as the refractive increment [5]. Furthermore, it was also shown that for biological samples this quantity varies insignificantly, such that it is reasonable to consider one average value for all cellular contents. Following this demonstration, which was largely due to experiments in immersion refractometry, it was realized that if one measured the optical path length difference produced by an object using interference microscopy, it is possible to calculate the objects dry mass per unit area [5]. For the case of living cells, which are heterogeneous objects, the dry mass per unit area may then simply be integrated over the entire projected area of the cell.

Although the idea of using interference microscopy to measure cell mas is old, the applications have been limited due to two major reasons. Firstly, the spatial resolution and contrast are limited due to the speckle generated by coherent laser sources. Secondly, the experimental setups required for interference microscopy are traditionally very complicated and are too unstable for long term biological imaging. In recent years these limitations have been overcome through the advent of common path interferometry, to address the issue of stability and broadband phase measurements, to address the issue of speckle [6].

Spatial Light Interference Microscopy (SLIM)

SLIM is a new technique that is both common path and broadband [7]. SLIM combines two classical ideas in optical imaging, Zernike's Phase Contrast microscopy, which provides high contrast images of phase objects and Gabor's holography which gives quantitative phase information about the objects. In short SLIM operates by measuring the intensity of the image at four different phase shifts between light scattered by the object and the un-scattered light (fig. 2). From the four intensity measurements a unique quantitative phase map may be determined [7]. Since SLIM uses white light (short coherence length) illumination it provides speckle free imaging. Due to the illumination and common path geometry, the temporal and spatial noise in optical path length has been measured to be 0.029 nm and 0.28 nm respectively. When translated to dry mass the spatial and temporal sensitivities are 1.5 and 0.15 femtograms/µm2 respectively. Furthermore, since SLIM is designed to be an add-on module to a commercial microscope (fig. 2) it is possible to utilize other commonly used modalities such as fluorescence, which is essential for biological studies. The high demand for long term biological imaging has also pushed several companies to develop microscope top incubation systems which enable SLIM to measure living biological samples for weeks at rates of several Hertz, providing a large temporal range. By scanning and stitching it is possible to image an entire microscope slide with subcellular resolution, thus providing information on both the growth of the entire cell population and single cells simultaneously. Due to its sensitivity, multi-modal capabilities, flexibility in spatial and temporal scales, and non-invasive nature, SLIM approaches the ideals for measuring cell growth that were laid out earlier.

Is Cell Growth Exponential, Linear, or Something Else?

To test the single cell growth measurement capabilities of SLIM, we started off by measuring a culture of E. coli cells [8]. Since E. coli cells are relatively simple, with short generation times and have been extensively studied, they are a natural choice before moving on to a more complicated system. In E. coli we found that single cells grow exponentially throughout their life cycle, which is in agreement with previous studies [3]. Since the cells also have a regular and well defined cylindrical shape, it is also possible to estimate their volume from measurements on the width and length of the cells. Combining the mass and morphology information we found that E. coli cells also maintain a constant volumetric density, meaning that for these cells it is valid to use size as a surrogate for mass. Convinced of the mass measurement capabilities of SLIM, we proceeded to measure a human osteosarcoma cell line (U2OS) with the goal of deciphering the single cell growth characteristics at different stages of the cell cycle. To differentiate between the cell cycle stages we used a fluorescence marker (YFP-PCNA) which distinctly indicates the beginning and end of the DNA synthesis or S phase. Using this information and the clear changes in morphology at the onset of we were able to divide our growth curves according to cell cycle stage. From this data we found that U2OS cells exhibit fast exponential growth during G2 and slower rates during G1 and S (fig. 3). This is contrary to previous measurements on synchronized populations performed using impedance counters which showed that for the case of lymphoblasts, there is continuous exponential growth throughout the cell cycle [2].


To summarize, SLIM provides unprecedented insight into cycle dependent cell growth with femtogram accuracy to dry mass. In addition to measuring growth, SLIM may also be used to acquire information using fluorescence channels, has the ability to quantify mass transport [9], measure cell dynamics, perform tomographic measurements and provide information on scattering parameters [10]. Thus SLIM provides the ability to truly measure and characterize a system, (fig. 4) at a wide range of spatial and temporal scales, providing information on a variety of fundamental biological phenomena.

We would like to thank our collaborators for providing cells, fluorescence probes and invaluable insight: Zhen Shen, Michael Bednarz, Rashid Bashir, Ido Golding and Supriya G. Prasanth. This work was supported by National Science Foundation (NSF) Grants CBET 08-46660 CAREER (to G.P.), CBET-0939511 (to G.P. and R.B.), and 0843604 and the Grainger Foundation (G.P.). Work in the I.G. laboratory is supported by National Institutes of Health Grant R01GM082837, Human Frontier Science Program Grant RGY 70/2008, and NSF Grant 082265 (Physics Frontiers Center: Center for the Physics of Living Cells).

[1] Weitzman J.B.: J. Biol. 2 (2003)
[2] Tzur A. et al.: Science 325 (2009)
[3] Godin M. et al.: Nature Methods 7 (2010)
[4] Park K. et al.: Proc. Natl. Acad. Sci. USA, 107 (2010)
[5] Barer R.: Interference microscopy and mass determination. Nature 169, (1952)
[6] Popescu G.: Quantitative Phase Imaging of Cells and Tissues, McGraw-Hill, 2011
[7] Wang Z. et al.: Optics Express, 19 (2011)
[8] Mir M. and Wang Z. et al.: Proc. Natl. Acad. Sci. USA, 108 (2011)
[9] Wang R. et al.: J. Phys. Cond. Matt., 23, (2011)
[10] Wang Z. et al.: Opt. Lett., 36, (2011)


Prof. Gabriel Popescu
Dr. Mustafa Mir
Dr. Zhuo Wang

Quantitative Light Imaging Laboratory
Department of Electrical and Computer Engineering
Beckman Institute for Advanced Science and ­Technology
University of Illinois at Urbana-Champaign
Urbana, IL, USA



University of Illinois
Department of Electrical & Computer Engineering
61801 Urbana, IL

You may also be interested in

Register now!

The latest information directly via newsletter.

To prevent automated spam submissions leave this field empty.