Label-free imaging of intracellular motility by low ... - OSA Publishing

Label-free imaging of intracellular motility by low-coherent quantitative phase microscopy Toyohiko Yamauchi,* Hidenao Iwai, and Yutaka Yamashita Hamamatsu Photonics K. K., 5000, Hirakuchi, Hamamatsu City, Shizuoka Pref., 434-8601, Japan * [email protected]

Abstract: The subject study demonstrates the imaging of cell activity by quantitatively assessing the motion of intracellular organelles and cell plasma membranes without any contrast agent. The low-coherent interferometric technique and phase-referenced phase shifting technique were integrated to reveal the depth-resolved distribution of intracellular motility. The transversal and vertical spatial resolutions were 0.56 μm and 0.93 μm, respectively, and the mechanical stability of the system was 1.2 nm. The motility of the cell was assessed by mean squared displacement (MSD) and we have compensated for the MSD by applying statistical noise analysis. Thus we show the significant change of intracellular motility after paraformaldehyde treatment in non-labeled cells. ©2011 Optical Society of America OCIS codes: (180.3170) Interference microscopy; (170.1530) Cell analysis; (240.6648) Surface dynamics.

References and links 1. 2. 3. 4. 5. 6. 7.

8.

9.

10. 11.

12. 13.

14.

A. W. Partin, J. S. Schoeniger, J. L. Mohler, and D. S. Coffey, “Fourier analysis of cell motility: correlation of motility with metastatic potential,” Proc. Natl. Acad. Sci. U.S.A. 86(4), 1254–1258 (1989). P. C. Zhang, A. M. Keleshian, and F. Sachs, “Voltage-induced membrane movement,” Nature 413(6854), 428– 432 (2001). S. Suresh, “Biomechanics and biophysics of cancer cells,” Acta Biomater. 3(4), 413–438 (2007). T. Ikeda, G. Popescu, R. R. Dasari, and M. S. Feld, “Hilbert phase microscopy for investigating fast dynamics in transparent systems,” Opt. Lett. 30(10), 1165–1167 (2005). G. Popescu, T. Ikeda, C. A. Best, K. Badizadegan, R. R. Dasari, and M. S. Feld, “Erythrocyte structure and dynamics quantified by Hilbert phase microscopy,” J. Biomed. Opt. 10(6), 060503 (2005). G. Popescu, T. Ikeda, K. Goda, C. A. Best-Popescu, M. Laposata, S. Manley, R. R. Dasari, K. Badizadegan, and M. S. Feld, “Optical measurement of cell membrane tension,” Phys. Rev. Lett. 97(21), 218101 (2006). X. Li, T. Yamauchi, H. Iwai, Y. Yamashita, H. Zhang, and T. Hiruma, “Full-field quantitative phase imaging by white-light interferometry with active phase stabilization and its application to biological samples,” Opt. Lett. 31(12), 1830–1832 (2006). P. Marquet, B. Rappaz, P. J. Magistretti, E. Cuche, Y. Emery, T. Colomb, and C. Depeursinge, “Digital holographic microscopy: a noninvasive contrast imaging technique allowing quantitative visualization of living cells with subwavelength axial accuracy,” Opt. Lett. 30(5), 468–470 (2005). B. Rappaz, P. Marquet, E. Cuche, Y. Emery, C. Depeursinge, and P. Magistretti, “Measurement of the integral refractive index and dynamic cell morphometry of living cells with digital holographic microscopy,” Opt. Express 13(23), 9361–9373 (2005). W. Drexler, U. Morgner, F. X. Kärtner, C. Pitris, S. A. Boppart, X. D. Li, E. P. Ippen, and J. G. Fujimoto, “In vivo ultrahigh-resolution optical coherence tomography,” Opt. Lett. 24(17), 1221–1223 (1999). S. Makita, T. Fabritius, and Y. Yasuno, “Full-range, high-speed, high-resolution 1 microm spectral-domain optical coherence tomography using BM-scan for volumetric imaging of the human posterior eye,” Opt. Express 16(12), 8406–8420 (2008). A. Dubois, K. Grieve, G. Moneron, R. Lecaque, L. Vabre, and C. Boccara, “Ultrahigh-resolution full-field optical coherence tomography,” Appl. Opt. 43(14), 2874–2883 (2004). C. Yang, A. Wax, M. S. Hahn, K. Badizadegan, R. R. Dasari, and M. S. Feld, “Phase-referenced interferometer with subwavelength and subhertz sensitivity applied to the study of cell membrane dynamics,” Opt. Lett. 26(16), 1271–1273 (2001). J. Kühn, T. Colomb, F. Montfort, F. Charrière, Y. Emery, E. Cuche, P. Marquet, and C. Depeursinge, “Real-time dual-wavelength digital holographic microscopy with a single hologram acquisition,” Opt. Express 15(12), 7231– 7242 (2007).

#142012 - $15.00 USD

(C) 2011 OSA

Received 31 Jan 2011; revised 28 Feb 2011; accepted 28 Feb 2011; published 9 Mar 2011

14 March 2011 / Vol. 19, No. 6 / OPTICS EXPRESS 5536

15. C. Fang-Yen, M. C. Chu, H. S. Seung, R. R. Dasari, and M. S. Feld, “Noncontact measurement of nerve displacement during action potential with a dual-beam low-coherence interferometer,” Opt. Lett. 29(17), 2028– 2030 (2004). 16. T. Akkin, D. Davé, T. Milner, and H. Rylander Iii, “Detection of neural activity using phase-sensitive optical low-coherence reflectometry,” Opt. Express 12(11), 2377–2386 (2004). 17. K. Jeong, J. J. Turek, and D. D. Nolte, “Fourier-domain digital holographic optical coherence imaging of living tissue,” Appl. Opt. 46(22), 4999–5008 (2007). 18. K. Jeong, J. J. Turek, and D. D. Nolte, “Volumetric motility-contrast imaging of tissue response to cytoskeletal anti-cancer drugs,” Opt. Express 15(21), 14057–14064 (2007). 19. A. K. Ellerbee, T. L. Creazzo, and J. A. Izatt, “Investigating nanoscale cellular dynamics with cross-sectional spectral domain phase microscopy,” Opt. Express 15(13), 8115–8124 (2007). 20. D. C. Adler, R. Huber, and J. G. Fujimoto, “Phase-sensitive optical coherence tomography at up to 370,000 lines per second using buffered Fourier domain mode-locked lasers,” Opt. Lett. 32(6), 626–628 (2007). 21. D. C. Adler, S. W. Huang, R. Huber, and J. G. Fujimoto, “Photothermal detection of gold nanoparticles using phase-sensitive optical coherence tomography,” Opt. Express 16(7), 4376–4393 (2008). 22. J. Oh, M. D. Feldman, J. Kim, H. W. Kang, P. Sanghi, and T. E. Milner, “Magneto-motive detection of tissuebased macrophages by differential phase optical coherence tomography,” Lasers Surg. Med. 39(3), 266–272 (2007). 23. T. Yamauchi, H. Iwai, M. Miwa, and Y. Yamashita, “Low-coherent quantitative phase microscope for nanometer-scale measurement of living cells morphology,” Opt. Express 16(16), 12227–12238 (2008). 24. A. Dubois, J. Selb, L. Vabre, and A. C. Boccara, “Phase measurements with wide-aperture interferometers,” Appl. Opt. 39(14), 2326–2331 (2000). 25. K. Creath, “V Phase-Measurement Interferometry Techniques,” in Progress in Optics, E. Wolf, ed. (Elsevier, 1988), pp. 349–393. 26. K. Hibino, B. F. Oreb, D. I. Farrant, and K. G. Larkin, “Phase shifting for nonsinusoidal waveforms with phaseshift errors,” J. Opt. Soc. Am. A 12(4), 761–768 (1995). 27. M. H. Gail, and C. W. Boone, “The locomotion of mouse fibroblasts in tissue culture,” Biophys. J. 10(10), 980– 993 (1970). 28. H. Qian, M. P. Sheetz, and E. L. Elson, “Single particle tracking. Analysis of diffusion and flow in twodimensional systems,” Biophys. J. 60(4), 910–921 (1991). 29. G. Popescu, Y. Park, N. Lue, C. Best-Popescu, L. Deflores, R. R. Dasari, M. S. Feld, and K. Badizadegan, “Optical imaging of cell mass and growth dynamics,” Am. J. Physiol. Cell Physiol. 295(2), C538–C544 (2008). 30. N. T. Shaked, L. L. Satterwhite, N. Bursac, and A. Wax, “Whole-cell-analysis of live cardiomyocytes using wide-field interferometric phase microscopy,” Biomed Opt. Express 1(2), 706–719 (2010). 31. J. A. Hessler, A. Budor, K. Putchakayala, A. Mecke, D. Rieger, M. M. Banaszak Holl, B. G. Orr, A. Bielinska, J. Beals, and J. Baker, Jr., “Atomic force microscopy study of early morphological changes during apoptosis,” Langmuir 21(20), 9280–9286 (2005). 32. C. P. Brophy, “Effect of intensity error correlation on the computed phase of phase-shifting interferometry,” J. Opt. Soc. Am. A 7(4), 537–541 (1990).

1. Introduction The measurement of cell motility is important for the study of living cells sampled from biological tissues. For example, the motility of cancer cells correlates with their metastatic potentials [1]. As for nanometer-scale measurements, the voltage-induced cell membrane motion was examined by applying atomic force microscopy (AFM), and its relationship to the charge density of the cell surface was demonstrated [2]. In recent years, the biophysical properties of cancer cells have been investigated by AFMs in nanometer scale [3]. Considering the intactness of the cell samples, it is desirable to use a non-invasive labelfree technique to image the dynamic morphology of the cells. In this regard we expect that an optical technique that uses interferometry would be ideal. There are two optical schemes available to measure the cell morphology. One is quantitative phase microscopy (QPM), which allows the measurement of the phase of optical fields in the sub-wavelength resolution. So far, Hilbert Phase Microscopy (HPM) [4–6], Quantitative Phase Microscopy by white-light interferometry [7], and Digital Holographic Microscopy (DHM) [8,9] have been used for the imaging of living cells. The other is Optical Coherence Tomography (OCT), which allows the acquisition of weak light reflected from spatially localized regions [10–12]. The key technique of QPM is to compensate the phase drifts and phase noise associated with the measurement system by monitoring the phase-referenced signals [4,13]. HPM and the DHM have the nanometer-scale resolution of the optical path [6,8]. However, they do not allow the discrimination of multiple reflection surfaces [4,9,14]. OCT, on the other hand, #142012 - $15.00 USD

(C) 2011 OSA



allows the discrimination of reflection signals attributed to multiple surfaces in a sample. However, many cases of conventional OCT have omitted the phase information of reflected light for obtaining the distribution of the amplitude of reflectance [10,12]. Increasing numbers of researchers in recent years have integrated the advantages of the quantitative-phase imaging technique with OCT in order to measure the dynamic morphology of a particular surface with sub-cellular resolution. Yang et al. developed a phase-referenced interferometer with a low-coherence light source in order to observe the phase fluctuation associated with cell surface motion [13]. Moreover, they employed the phase-referenced lowcoherence technique to measure nerve displacement during action potential [15,16]. Concerning the OCT approach, Jeong et al. developed Fourier Domain Digital Holographic OCT (FD-DHOCT) to quantify the degree of cell motility by an intensity-based statistical technique [17,18], and Ellerbee et al. were able to capture an image of the phase fluctuation of chick embryos by applying Multi-Dimensional Spectral Domain Phase Microscopy (MDSDPM) [19]. To distinguish a particular cell surface, some researchers used nanoparticles to enhance the reflection signals of cells by OCT [20–22]. These studies showed nanometerscale motions of cells. However, in a label-free state the reflected light from the cell surface was not sufficiently distinguished from that of other boundaries, including the glass surface or the membrane of intracellular organelles, and when the researchers needed to take the signal from the membranes only, it was necessary to use contrast agents. This paper shows the three-dimensional distribution of quantitatively assessed phase fluctuation caused by the motion of multiple surfaces in cultured cells. We used highnumerical-aperture (NA) illumination with a low-coherence light source while controlling the phase-referenced optical path difference at the nanometer scale [23]. The longitudinal spatial resolution (FWHM (Full Width at Half Maximum) of the interference fringe) of the imaging system was 0.93 μm, while the transversal resolution was 0.56 μm (diffraction limit). The results quantitatively revealed the depth-resolved fluctuations of the intracellular surfaces, allowing us to measure the plasma membrane, the reflecting surfaces in cytoplasmic region and the surface of the substrate independently. 2. Methods Figure 1(a) depicts the experimental setup of Low-Coherent QPM based on a Linnik configuration. Light emitted from a halogen lamp (Nikon, LV-UEPI 50W) passed through a Linnik interferometer equipped with two identical water-immersion objective lenses (Nikon, CFI Fluor 60 × W, NA = 1.0). The reflected wavefronts from the sample and the reference mirror were focused onto the 12-bit CCD camera (Hamamatsu, C9300-201) in order to obtain interference images. The cells under testing were cultured on a glass slide to which both an AR coating for the bandwidth of 550-950 nm and a reflection enhancement coating for 1.3 μm were applied. The AR coating was necessary because the light reflected from the cell membrane and intracellular membranes was so weak that the reflection from the glass surface would easily overwhelm the cell reflection even if coherence gating was used. The reflection enhancement coating caused the glass surface to work as a reference plane for the feedback control of optical path difference (OPD).

#142012 - $15.00 USD

(C) 2011 OSA



Fig. 1. Schematic illustration of the experimental Setup. (a): Whole setup, (b): Interference fringe observed on the CCD camera while moving the PZT2, (c): Detail of the sample arm. IR-LD: Infrared laser diode, PZT: Piezoelectric transducer, PD: Photo detector, ND: Neutral density filter, M: Mirror, L: Lenses, BS: Beam splitter, DM: Dichroic mirror (cutoff: 900nm).

The emission light from the halogen lamp was spectrally filtered by a glass long-pass filter having a cutoff wavelength of 695 nm (Shott, RG695), in order to match the AR coatings of the optical components. Figure 1(b) shows the one-point interferogram measured on a single pixel of the CCD camera while linearly translating the mirror by PZT2. The fringe spacing Λ was 327 nm per fringe, and the FWHM of the envelope of the interference fringe was estimated to be 0.93 μm. As Dubois et al. reported, in the case of focusing illumination, the fringe spacing Λ became β times more than the estimated in the case of plane waves: Λ     2nmedium  where β related to the numerical aperture NA through the equation

  2 1  cossin 1 NA n  [12,24]. We measured the factor β to be 1.13 using a narrow

band-pass optical filter to transmit the wavelength of 780 ± 5 nm (FWHM) in front of the lamp. With the measured value of β, we estimated the effective numerical aperture of the entire system to be 0.85 and the original center wavelength λc of the incident imaging light to be 773 nm. The resultant diffraction limited lateral resolution d was 0.61 × λ /NA = 0.56 μm. The feedback control system of the OPD consists of an infrared laser diode (IR-LD) (PDLD Inc., PL13H0101), an infrared photodetector (PD) (New Focus, MODEL 2053), a piezoelectric transducer (PZT1) (NEC TOKIN, AE0505D08F) to translate the reference mirror longitudinally, and a long-working-distance piezoelectric transducer (PZT2) (Physik Instrumente, P-611.ZS) to translate the sample dish. The optical path of the IR light is adjusted so that it is reflected by the glass surface in the vicinity of the cell (see Fig. 1(c)). The details of this feedback system have been described in our previous publications [7,23]. The PZT1 adjusts the OPD fast (~500 Hz) with a small stroke (