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生物医学的图像处理,计算和显示

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ISSN 在线: 2162-3511

LABEL-FREE OPTICAL DETECTION OF OPTOGENETIC ACTIVATION OF CELLS USING PHASE-SENSITIVE FOURIER DOMAIN OPTICAL COHERENCE TOMOGRAPHY

Niloy Choudhury,1 Zhaoqiang Zhang,2 Feng Zhao,2 Ling Gu,3 & Samarendra Mohanty3

1Biophotonics Laboratory, Department of Biomedical Engineering, Michigan Technological University, 1400 Townsend Drive, Houghton, Michigan 49931-1295, USA

2Stem Cells and Engineered Tissue Laboratory, Department of Biomedical Engineering, Michigan Technological University, 1400 Townsend Drive, Houghton, Michigan 49931-1295, USA

3Biophysics and Physiology Laboratory, Department of Physics, University of Texas at Arlington, 500 UTA Blvd., Arlington, Texas 76019, USA

Abstract.

The existing methods for detection of neural activity during optogenetic stimulation are either mechanically intrusive or chemically invasive. Here, we report development of a label-free noninvasive optical readout method to monitor the changes in the cells resulting from optogenetic activation. Phase-sensitive Fourier domain optical coherence tomography (PSFD-OCT) was deployed to detect the activation of Channelrhodopsin-2 sensitized cells under the stimulation of blue light. A monolayer of transfected human embryonic kidney cells (HEK 293) in a cell culture dish was activated using a fiber-coupled laser diode that was modulated by a square wave (frequency 30 Hz with 50% duty cycle). Using the PSFD-OCT system, we demonstrate measurement of the optical path length change in the cell monolayer because of light-induced activation.

Keywords:

optogenetics, low coherence interferometry, phase-sensitive optical coherence tomography


1. Introduction

In optogenetic stimulation, chemically identical neurons can be activated by (blue) light with high temporal (typical relaxation time is of the order of a few milliseconds) and spatial resolution [1], by the introduction of light-activated molecular channels [2, 3] (e.g., Channelrhodopsin-2, ChR2), by genetic targeting [3, 4]. However, for detection of neural activity the usual methods used are either mechanically intrusive (e.g., use of microelectrodes) or chemically invasive (e.g., calcium imaging). In order to achieve complete noninvasiveness in optogenetic stimulation, there is a need to record cellular activation in addition to cell-specific gene delivery and light activation. A toolbox that can achieve cell-specific stimulation and simultaneous detection of neural activity will be of great importance for simultaneous input-output interrogation of excitable cells [5]. This will allow us to noninvasively investigate how a cell controls and converts information in diseased and normal states, and so on. The conventional method for cellular recording is mostly electrical in nature, where metallic microelectrodes or patch clamp pipettes are spatially localized in different regions of brain slices or the brain [6, 7]. While theses electrical methods are highly invasive in nature, there exist few all-optical methods for detecting cellular activity. These methods include the use of Ca2+ indicator dyes, genetically encoded Ca2+ indicators and voltage-sensitive dyes [8–10]. But all these optical methods require an additional step of sensitization and can be chemically invasive to the cells, thus limiting long-term studies.

In order to overcome the invasiveness (both mechanically and chemically) of the current techniques used to detect cell-specific activity, we have developed a phase-sensitive Fourier domain optical coherence tomography (PSFD-OCT) system to detect cellular activity. Optical coherence tomography (OCT) is rapidly gaining acceptance as one of the most promising in vivo imaging tools in biology and medicine [11–15]. Because of its high sensitivity and high speed, the Fourier-domain version (FD-OCT) is an excellent tool for obtaining 3D images of biological structures with resolution approaching that of conventional histology. Moreover, phase-sensitive Fourier domain optical coherence tomography (PSFD-OCT) is used to measure nano-motion [16–21] by analyzing the phase changes in the measured spectral interferograms. In FD-OCT, the interference signal is detected by a linear array of CCDs and then Fourier transformed to obtain the structural image (amplitude of the Fourier transformed signal). In PSFD-OCT the phase of the Fourier transformed signal is analyzed to detect nano-motion of cell membranes. Using PSFD-OCT, it is shown to be possible to measure subnanometer motion of the reflector, e.g., cells [17]. It has also been shown using a laser interferometer that it is possible to image the nanometer-level changes in human embryonic kidney (HEK 293) cells under electrical stimulation [22]. Because this interferometer uses a laser as a light source, which has meters of coherent length, the ability of using this technique to isolate and study the nano-changes of a cell in 3D volume of cells of the order of cubic mm is limited. On the other hand, PSFD-OCT is based on an interferometer that uses a broadband light source with less than 10 μm coherence length, and hence can isolate the signal from a cell in a 3D volume of tissue. Therefore, it will serve as an ideal tool for in vivo detection of optogenetic stimulation-induced nano-changes of cell volume, where a specific layer of cells is targeted for activation. While the present study deploys blue wavelength (470 nm) to excite ChR2, cells expressing red-shifted opsin such as VChR1 and C1V1, can be excited using green wavelengths (545 and 540 nm, respectively) [1]. Further, silencing of activity by excitation of Arch or Halorhodopsin expressing cells by yellow wavelengths (566 and 590 nm, respectively) may be monitored using our method.

2. MATERIALS AND METHODS

2.1. Cell Monolayer

Human embryonic kidney (HEK 293) cells were transfected with the ChR2 enhanced yellow fluorescent protein (EYFP) construct, cloned into pcDNA3.1 neo (Invitrogen). EYFP was fused in-frame to the C-terminus of ChR2 by polymerase chain reaction (PCR). Transgene-expressing cells were identified by visualizing the EYFP fluorescence under suitable illumination (514 nm). Stable clones were selected with 200 mg/L G418 and colonies were picked after 2 weeks and then expanded. Clones that showed the highest level of EYFP fluorescence were chosen for the optical activation experiments. For optical detection of the activation process, cells were incubated and maintained at 37°C, 5% CO2 in Dulbecco′s modified Eagle′s medium containing 10% fetal bovine serum. To generate light activation, cells were loaded with all-trans-retinal (ATR, 1 μM) for at least 6 h before stimulating with blue light.

2.2. PSFD-OCT System

PSFD-OCT is based on spectral domain implementation of the OCT system that was recently developed in the OCT research community [16–21], and analyzes the phase information contained in the OCT signals. Our PSFD-OCT system that is integrated with optogenetic stimulation is based on [21]. The schematic diagram of the PSFD-OCT system is shown in Fig. 1. It is a conventional Michelson interferometer system with a broadband super luminescent diode (SLED) as a light source (central wavelength is 1316 nm and bandwidth is 80 nm), which leads to an axial resolution of ~10 μm in air. The light from the SLED is connected to port 1 of a circulator, and port 2 of the circulator is coupled into an arm of a 2 × 2 coupler (90–10 split) as shown in Fig. 1.

Figure 1. Schematic diagram of the PSFD-OCT system. The light from the superluminescent diode is fed to a Michelson interferometer. The detection arm is fed to the input of a spectrometer, whose output is given by a line-scanning CCD. PC: polarization controller.

One of the outputs (10% output) of the coupler goes to the reference arm and the other (90% output) goes to the sample arm. The reference arm consists of a collimator, which collimates the light from the fiber and a lens that focuses the light onto a mirror. The sample arm consists of a collimator, followed by a x-y galvo-scanner and the objective lens (NA is 0.15, giving a transverse resolution of ~10.5 μm in air). The x-y scanners are used to scan the investigating light along the x-y directions of the sample. The reflected light from the reference arm and the sample arm go back to the 2 × 2 coupler and into port 2 of the circulator. Port 3 of the circulator is connected to the spectrometer. The spectrometer consists of another collimator that collimates the light emanating from the fiber, followed by a transmission grating to spectrally spread the signal. A lens is used to focus the dispersed signal to a line-scanning camera (1024 pixels). The camera output is the FD-OCT signal S(k) in k-space and is called an A-scan.

(1)

where we have ignored all the terms except the interference term. In Eq. (1), k = 2/λ, where λ is the wavelength of light, Ir and Is are light reflected back from the reference mirror and sample respectively, z is the depth location of the scattering sample, and Φ is some random phase noise. In order to obtain the FD-OCT image, I(z) Fourier transform (FT) of the signal S(k) is performed:

(2)

where Φ(z) is the phase of the interference signal. Since S(k) is not equally spaced in k-space, before taking FT, S(k) is usually resampled into equally spaced k-distribution, and also correction for any dispersion mismatch between sample and the reference arms is performed numerically. If a number of A-scans [S(k)] are taken at the same spatial location over time, then the phase term in Eq. (2) becomes

(3)

If at depth z = z0, there is a sample that is oscillating at frequency f0 with an amplitude a0, then

(4)

The phase difference between two consecutive time points (Δt = t2t1) is given by

(5)

where χ(t) is the phase noise caused by the system noises, including shot noise, thermal noise, and electrical noise. For the system described in Fig. 1, with a SNR of ~50 dB, the phase noise is ~3 mrad [23], but a motion of 1 nm gives a maximum phase difference of 10 mrad, making it difficult to measure motion below 1 nm, but by taking the Fourier transform of Eq. (5) one can increase the sensitivity of the measurement. As the Fourier transform is a coherent addition it increases the measured signal at f0 by √N/2 (N is the number of time points) and reduces χ(t) by √N, leading to a SNR improvement of √N/2. Taking the FT of Eq. (5) one gets

(6)

where A(f) gives the amplitude of motion of the sample at frequency f.

3. RESULTS

3.1. Calibration of PSFD-OCT System

In order to validate the system′s ability to measure subnanometer changes and to calibrate the measured PSFD-OCT signal, a series of experiments were performed. A piezo-stack that was driven by a sine wave generator at a frequency of 30 Hz with a driving voltage of 280 mVpp (this corresponds to a movement of ~2.8 nm) was imaged. The scan rate of the line-scan camera was set at 995 Hz (minimum scan rate available) and the sensitivity of the FD-OCT system was ~105 dB at a distance of 300 μm from zero delay. Figure 2 describes the algorithm of obtaining the PSFD-OCT signal. Figure 2(a) shows the signal in k-t space from a piezo-stack that is vibrating at a frequency of 30 Hz with an amplitude of ~2.8 nm. Then a fast Fourier transformation (FFT) is performed along the k-direction to obtain M(z, t) as described in Eq. (2). Then, the steps described in Eqs. (3)–(5) are performed to obtain ΔΦ(z, t) as shown in Fig. 2(b). Now if one takes the signal along the time dimension at z = z0 (indicated by the arrow) in Fig. 2(b), ΔΦ(z0, t) of Eq. (5) is obtained [shown in Fig. 2(c)]. Taking the fast Fourier transform (FFT) of ΔΦ(z0, t) the plot shown in Fig. 2(d) is obtained, which shows the piezo-stack vibrating at a frequency of 30 Hz. It can be seen from Fig. 2(d) that the signal to noise ratio of the vibration measurement is ~41, indicating a noise floor of less than 100 pm.

Figure 2. Algorithm for measuring nano-changes using PSFD-OCT. (a) The acquired k-t signal at a particular (x, y) location of the sample. (b) The calculated phase difference, ΔΦ, as a function of z-t, which is obtained after taking fast Fourier transform (FFT) along the k-axis of data shown in (a) [Eqs. (2)–(5)]. (b) Plots ΔΦ(z = z0,t), where z0 is the depth location of the pizeo-surface shown by the arrow in (b). (d) is obtained by taking FFT of ΔΦ(z = z0,t), showing the vibration response of the piezo with a peak at 30 Hz.

In order to calibrate the PSFD-OCT system’s measured response, so that A(f) in Eq. (6) can be given in nanometers, the piezo-stack was vibrated with a sinusoidal signal of 30 Hz frequency and various drive voltages. Since the piezo-stack was calibrated, i.e., it produced a known amount of displacement for a given drive voltage, drive voltages (V) can be easily converted into displacements (nm). Figure 3 shows the detected PSFD-OCT signal of the vibrating piezo-stack at 30 Hz for different amplitudes of motion. It can be seen that the response measured increases linearly with increasing drive voltage and the slope of the curve is the calibration constant, C. Dividing the measured PSFD-OCT signal by C the actual displacement can be measured. The PSFD-OCT response was measured when the piezo-stack was stationary, dividing the measured response by C, the noise floor was 80 pm at 30 Hz.

Figure 3. Measured PSFD-OCT signal as a function of different amplitudes of displacements for a piezo-stack vibrating at 30 Hz. The dashed line is the measurement from a stationary piezo-stack. Multiplying this measurement by C, the noise floor was found to be 80 pm at 30 Hz.

3.2. Monitoring of Cellular Activation Using PSFD-OCT System During Optogenetic Stimulation

A monolayer of transfected HEK293 cells was put in a cell culture dish and activated by a blue laser diode operating at 473 nm. The power output at the end of the lensed fiber was ~7 mW under CW operation. The blue light was modulated at a frequency of 30 Hz. Figure 4 shows the experimental setup. In this figure only the sample arm of the OCT system is shown. The blue light to activate the cells was delivered though the bottom of the cell culture dish to a spatially localized region.

Figure 4. The setup for measuring nano-changes from optogenetically activated cell(s). The 473-nm blue light for stimulating the cells was provided by a fiber-coupled laser beam. The lensed fiber delivered light to a stationary location within the whole FD-OCT scan volume.

In Fig. 5, the measured optogenetically stimulated cell response from HEK 293 cells is shown. Figure 5(a) shows the cross-sectional OCT image of the cell culture in a Petri dish. One can see the cell culture dish-medium interface and the cells lying on top of that interface. The arrow shows the location where the blue light was delivered. Figure 5(b) shows the PSFD-OCT signal obtained from the location indicated by the arrow in Fig. 5(a). Figure 5(b) also shows the PSFD-OCT signal when the blue light is turned off. Figure 5(c) shows the PSFD-OCT signal with light stimulation normalized by the PSFD-OCT signal without light stimulation. It is clear from the plot that the blue light activates ChR2-expressing HEK cells, and we were able to detect the nano-changes of the cell volume using PSFD-OCT.

(b)
(a) (c)

Figure 5. Schematic diagram of the PSFD-OCT system. The light from the superluminescent diode is fed to a Michelson interferometer. The detection arm is fed to the input of a spectrometer, whose output is given by a line-scanning CCD. PC: polarization controller.

4. CONCLUSIONS

Using a PSFD-OCT signal we were able to detect the nanoscale optical path length change due to optogenetic activation of ChR2-transfected HEK 293 cells. Use of PSFD-OCT system enables intrinsic detection of neural activity without addition of calcium dyes, thus mitigating the cytotoxicity issues. Further, it allows noninvasive recording unlike electrode-based approaches. In conclusion, this label-free noninvasive optical method for detection of neuronal activity in combination with light-assisted activation brings us a valuable approach to study and better understand the nervous system.

REFERENCES

1. Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G., and Deisseroth, K., Millisecond-timescale, genetically targeted optical control of neural activity, Nat. Neurosci., 8(9):1263-8, 2005.

2. Nagel, G., Szellas, T., Huhn, W., Kateriya, S., Adeishvili, N., Berthold, P., Ollig, D., Hegemann, P., and Bamberg, E., Channelrhodopsin-2, a directly light-gated cation-selective membrane channel, Proc. Natl. Acad. Sci., 100(24):13940-5, 2003.

3. Zhang, F., Wang, L. P., Boyden, E. S., and Deisseroth, K., Channelrhodopsin-2 and optical control of excitable cells, Nat. Methods, 3(10):785-92,2006.

4. Arenkiel, B. R., Peca, J., Davison, I. G., Feliciano, C., Deisseroth, K., Augustine, G. J., Ehlers, M. D., and Feng, G., In vivo light-induced activation of neural circuitry in transgenic mice expressing Channelrhodopsin-2, Neuron., 54(2):205-18, 2007.

5. Deisseroth, K., Optogenetics, Nat. Methods, 8(1):26-9, 2011.

6. Deisseroth, K., Feng, G., Majewska, A. K., Miesenböck, G., Ting, A., and Schnitzer, M. J., Next-generation optical technologies for illuminating genetically targeted brain circuits, J. Neurosci., 26(41):10380-6, 2006.

7. Petreanu, L., Huber, D., Sobczyk, A., and Svoboda, K., Channelrhodopsin-2-assisted circuit mapping of long-range callosal projections, Nat. Neurosci., 10(5):663-8, 2007.

8. Gu, L. and Mohanty, S. K., Targeted microinjection into cells and retina using optoporation, J. Biomed. Opt., 16(12):128003-6, 2011.

9. Mohanty, S. K., Reinscheid, R. K., Liu, X., Okamura, N., Krasieva, T. B., and Berns, M. W., In-depth activation of Channelrhodopsin 2-sensitized excitable cells with high spatial resolution using two-photon excitation with a near-infrared laser microbeam, Biophys. J., 95(8):3916-26, 2008.

10. Zhang, F., Wang, L.-P., Brauner, M., Liewald, J. F., Kay, K., Watzke, N., Wood, P. G., Bamberg, E., Nagel, G., Gottschalk, A., and Deisseroth, K., Multimodal fast optical interrogation of neural circuitry, Nature, 446(7136):633-9, 2007.

11. Bouma, B. E. and Tearney, G. J., Handbook of optical coherence tomography, New York: Informa Healthcare, 2001.

12. Brezinski, M., Optical coherence tomography: Principles and applications, London: Academic Press, 2006.

13. Fercher, A. F., Drexler, W., Hitzenberger, C. K., and Lasser, T., Optical coherence tomography—principles and applications, Rep. Prog. Phys., 66(2):239, 2003.

14. Hausler, G. and Lindner, M. W., “Coherence radar”' and “spectral radar”–New tools for dermatological diagnosis, J. Biomed. Opt., 3(1):21–31, 1998.

15. Tomlins, P. H. and Wang, R. K., Theory, developments and applications of optical coherence tomography, J. Phys. D: Appl. Phys., 38(15):2519, 2005.

16. Adler, D. C., Huber, R., and Fujimoto, J. G., Phase-sensitive optical coherence tomography at up to 370,000 lines per second using buffered Fourier domain mode-locked lasers, Opt. Lett., 32(6):626-8, 2007.

17. Choma, M. A., Ellerbee, A. K., Yang, C., Creazzo, T. L., and Izatt, J. A., Spectral-domain phase microscopy, Opt. Lett., 30(10):1162-4, 2005.

18. Joo, C., Akkin, T., Cense, B., Park, B. H., and de Boer, J. F., Spectral-domain optical coherence phase microscopy for quantitative phase-contrast imaging, Opt. Lett., 30(16):2131-3, 2005.

19. Joo, C., Kim, K. H., and de Boer, J. F., Spectral-domain optical coherence phase and multiphoton microscopy, Opt. Lett., 32(6):623-5, 2007.

20. Sarunic, M. V., Weinberg, S., and Izatt, J. A., Full-field swept-source phase microscopy, Opt. Lett., 31(10):1462-4, 2006.

21. Wang, R. K. and Nuttall, A. L., Phase-sensitive optical coherence tomography imaging of the tissue motion within the organ of Corti at a subnanometer scale: A preliminary study, J. Biomed. Opt., 15(5):056005-9, 2010.

22. Fang-Yen, C., Oh, S., Park, Y., Choi, W., Song, S., Seung, H. S., Dasari, R. R., and Feld, M. S., Imaging voltage-dependent cell motions with heterodyne Mach-Zehnder phase microscopy, Opt. Lett., 32(11):1572-4, 2007.

23. Vakoc, B., Yun, S., de Boer, J., Tearney, G., and Bouma, B., Phase-resolved optical frequency domain imaging, Opt. Express, 13(14):5483-93, 2005.

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