*Confocal Laser Scanning Microscopy for Spectroscopic Studies of Living Photosynthetic Cells DOI: http://dx.doi.org/10.5772/intechopen.84825*

somehow during the time, the diffusion coefficient can be derived from these characteristic changes [48, 49]. Usually the component whose diffusion is to be observed must be tagged with a fluorophore, but, as it was mentioned above, the great advantage of photosynthetic membranes is that their protein complexes are naturally fluorescent, so their diffusion can be observed without any necessity for specific fluorophore binding or GFP gene fusions. The only requirements for quantitative FRAP are that the membrane geometry is known, and the membrane environment is uniform over an area considerably larger than the area of the bleach. Unfortunately, most green plant thylakoid membranes have an intricate, convoluted structure, and extensive lateral heterogeneity on small scales. On the other hand, some cyanobacterial species have the membrane systems located in the periphery of the cell and are uniform enough in small regions. Anyway, by means of FRAP technique, it is always possible to see if particular components are mobile or not, to make a rough estimation of time-scales and to investigate a number of factors that affect their diffusion coefficient.

In contrast to typical green plants, in most cyanobacterial strains, there is no thylakoid membrane stacking and no extensive lateral heterogeneity. The preferred model organism used in previously published papers [39, 48, 49] is the cyanobacterium Synechococcus sp. PCC7942, which has suitable membrane conformation and is also well-characterized and transformable. Its cells can be elongated up to 10–20 μm by means of some growth techniques to achieve lateral heterogeneity in relatively large region. But in this work, we demonstrate that reasonable results can be obtained even for spherical cells of Microcystis firma CALU 398.

It is well known that phycobilisomes diffuse rapidly on the surface of the thylakoid membrane, while PS II reaction centers are normally almost immobile. Here we used FRAP to measure the mobility of phycobilisomes in the intact cyanobacterial cells. These experiments indicate that phycobilisomes may frequently decouple from reaction centers and diffuse randomly before attaching to another reaction center.

FRAP measurements were carried out with a laser-scanning confocal microscope Leica TCS-SP5. During the measurement, a series of images of the cell is recorded, and it is important to keep the laser power low enough not to cause significant further bleaching of the cell during repeated imaging. The basic procedure for the measurement is to record an image of the sample cell before bleaching (**Figure 12(a)**(1). Then the laser power is increased by a factor of 8–10, and the confocal spot is scanned only over a restricted area of the sample (light-blue vertical rectangle) to bleach out most of the fluorescence in that area. The laser power is then reduced again, and a series of post-bleach images is recorded. The best timescale for the measurement depends on the rate of diffusion and has to be found by trial and error. In thylakoid membranes, the diffusion of both lipids and proteins is generally rather slow and a 1 s bleach, followed by a series of images recorded at 1.3 s intervals, was adequate to capture diffusion.

**Figure 12** summarizes the steps involved in recording and analyzing FRAP data. In the presented experiment, a one-dimensional diffusion of phycobilisomes was measured in a cell of the cyanobacterium Microcystis firma CALU 398. Confocal laser scanning microscope Leica TCS-SP5 with immersion objective HCX PL APO 63.0x1.30 GLYC 37°C UV was utilized in this investigation. The He-Ne laser (633 nm, 150 mW) was used for excitation in both bleaching and scanning modes, and the laser power was 25 and 2% correspondingly. The vertical (Z) resolution was 0.2 μm, and the resolution in the x-y plane was about 24.1 nm. Digital zoom was 20. The laser was scanned over the sample with oscillating mirrors. Scan speed was 400 Hz. Fluorescence from the sample was separated from the excitation light with a beamsplitter, passed through a 102.9 μm pinhole and detected with a photomultiplier with PMT voltage 1000 V. The emission band for recorded images was 673–678 nm.

*Color Detection*

**Figure 11.**

pigment-protein complexes begins. The intensity of Chl a and PC-APC fluorescence

*Time degradation of living cell of cyanobacterial strain Synechocystis CALU 1336 under high-light and heat stress. (a) Spectra recorded at the excitation wavelength 488 nm with the time-step 4 min. All spectra are shifted along x-axis for convenience of observation. (b) Time dependence of the fluorescence intensity at 656 nm* 

Two presented examples of CLSM lambda-scan application show the unique abilities of CLSM microscopic spectroscopy for investigation of physiological processes in cyanobacterial cells. More examples can be found in [3–5, 47].

A field of growing importance is the investigation of living specimens that show dynamic changes. Dynamic processes in living specimens can be recorded by means of time series implemented in modern CLSMs. Data once acquired can be analyzed "offline," that is, after image acquisition. Time series are defined by a start time and the time interval between two successive images. To analyze a time series, some option allows fluorescence intensity changes to be quantified in defined regions of interest (ROIs). Within a time series, the CLSM permits selective, point-accurate illumination of ROIs with laser light. This function is useful for generating a photobleaching routine, for example, within a FRAP experiment (fluorescence recovery after photobleaching), for analyzing dynamic processes. Complex time series experiments, with different images to be taken at different sites within a specimen according to a

Fluorescence recovery after photobleaching (FRAP) is a technique widely used in cell biology to observe the dynamics of biological systems. In photosynthetic organisms, it can be directly used, for example, for investigation of the dynamics of thylakoid membranes, including the diffusion of membrane components [39, 48–52]. Diffusion of membrane components is involved in a number of processes, for example, in investigation if the chromatic adaptation of light-harvesting apparatus, in describing of the electron transport in photosynthetic membranes and in studies of the biogenesis, turnover, and repair of the photosystems. Diffusion coefficients for certain thylakoid membrane components can also be estimated by indirect methods [53, 54], but FRAP and related optical techniques may be used for direct

The component whose diffusion is to be observed must be bleached by high laser power with the confocal spot scanning briefly over a small area of the sample. After bleaching, the laser power is decreased, and the whole sample is imaged. The bleached area of the sample will be seen as a dark, nonfluorescent patch on the image. Then the sample is repeatedly imaged, and if the bleaching will change

decreases, and maximum is shifted to shorter wavelengths.

*(PC-APC fluorescence) and at 682 nm (Chl a fluorescence).*

**3.4 Using fluorescence recovery after photobleaching (FRAP)**

defined time pattern, can be carried out by means of CLSM software.

observation of the diffusion in biological systems.

**54**

### **Figure 12.**

*Extracting data from a FRAP experiment on a cell of Microcystis CALU 398. (a) Fluorescence intensity images from FRAP-sequence, taken at −5, 0, 10.4, and 71.1 s, correspondingly. ROI 1 (light blue rectangular): bleaching area and ROI 2 (orange rectangular): the area for controlling fluorescence intensity profile across bleaching region. Scale bar = 1 μm. (b) Total fluorescence intensity of bleached area as a function of time. The recovery of the fluorescence is presented as open circles and exponential fitting function—solid line. (c) Pre-bleach and post-bleach fluorescence intensity profiles across bleaching region at t = 0, 1.3, 10.4, 22.1, and 71.1 s. (d) The subtracted postbleach and pre-bleach fluorescence intensity profiles and corresponding Gaussian fitting curves at five time-points indicated at (c). (d) A plot of C-function for one-dimensional diffusion versus time. The obtained diffusion coefficient is indicated on the plot.*

The first image (**Figure 12(a)**(1) was recorded prior to bleaching, by scanning the confocal spot in the XY mode. Excitation wavelength was at 633 nm, and the detection range was from 650 to 750 nm. The scan was then switched to another mode, the laser power was increased by a factor of 12, and the sample was bleached by scanning the laser repeatedly in one dimension across the cell for 1 s. Light-blue vertical rectangle indicates bleaching area. Then the laser power was reduced again to the initial value, the scan was switched back to the XY mode, and the cell was imaged by scanning over a square of 12.30 × 12.30 μm in the x-y plane (512 × 512 pixels) (**Figure 12(a)**(2–3). There was no detectable photobleaching during the recording of successive image scans. A series of 20 further images were recorded at time intervals 1.3 s and then another 10 images at time intervals 5 s. Images (a3) and (a4) show the state at 20th and 30th point (10.2 and 71.1 s, correspondingly). Within a few minutes, the bleaching profile spreads, becoming broader and shallower. This shows that phycobilisomes are diffusing, with unbleached phycobilisomes diffusing into the bleached area.

**57**

× 10–11 cm2

**4. Conclusion**

CLSM is well suited for this approach.

than has previously been possible.

*Confocal Laser Scanning Microscopy for Spectroscopic Studies of Living Photosynthetic Cells*

points were recorded with step 1.3 s and another 10 points with step 5 s.

Leica software (LAS AF Lite 2.6) was used to extract the fluorescence profiles across the bleaching area (orange rectangle) from the images, summing all the pixel values in the Y-direction for each X coordinate. And then MathCad 14 was used for

(**Figure 12(b)**) shows a typical time dependence of fluorescence recovery after photobleaching. The open circles denote the integrated signals over the bleached area, marked by the light-blue vertical rectangle in the fluorescence intensity images (a), and the line represents a fitting curve. First three points correspond to prebleaching images. Then goes a 1-s gap corresponds to bleaching period. The next 20

One pre-bleach and five post-bleach fluorescence profiles across the bleaching area (orange rectangle) at a series of time-points were aligned (**Figure 12(c)**). The post-bleach profiles (shown in thin lines) were corrected by subtracting the prebleach profile (shown in thick red line), and the Gaussian curves were then fitted to the corrected fluorescence profiles (**Figure 12(d)**). The fitted Gaussian curves were used to obtain corresponding depth (C) and the half-width (1/e2) (R) of the bleach. Note that the bleaching profile remains Gaussian, but becomes broader and shallower with time. The change in C and R with time and diffusion distance in one dimensional diffusion model can be described according to the equation given in [49]. Finally, a suitable function of C is plotted versus time in (**Figure 12(e)**) and the corresponding diffusion coefficient was obtained. Here, R0 and C0 are the values of R and C at time just after bleaching. For one-dimensional diffusion, the plot shown in (**Figure 12(e)**) should be linear with gradient equal to the diffusion coefficient. The calculations for the diffusion coefficient of phycobilisomes give a result of 6.8

/s, which is similar to those given in [49]. Together with the linearity of

the plot in **Figure 12(e)**, this indicates that this procedure can be applied to spherical

Light microscopy has been used for studying cells for many years and has advanced our understanding of key cellular processes. However, fixation involves nonphysiological procedures and only provides a snapshot view of cells at a single point in time. To truly understand cellular function, we need to extend our imaging capabilities in ways that enable us to follow sequential events in real time, monitor the kinetics of dynamic processes, and record sensitive or transient events. And CLSM gives such opportunity. In addition, CLSM technique allows the investigation

not only cultivable, but also the noncultivable phototrophic microorganisms.

This study presents simple and practical advices for performing special confocal microscopy applications. Our approach allows to study detailed mechanisms of photoprotection and stress reactions in different cyanobacterial species.

Fluorescence spectra of cyanobacterial photosynthetic pigments are easily recorded by spectral CLSM. The fluorescence shares of individual phycobiliproteins can be reliably determined by spectral unmixing, showing that the spectral resolution of

Finally, with the advent of live cell imaging and the development of high- and superresolution technologies, it is now possible to acquire data on viable cells in a biologically relevant context providing us with a greater insight of cellular function

Note here, that there are a lot of additional techniques already implemented in modern CLSMs, which open new perspectives for single-cell investigation, such as: white laser, which provides the ability to obtain not only fluorescence emission

cells also and that our measurement does not greatly perturb the system.

*DOI: http://dx.doi.org/10.5772/intechopen.84825*

curve fitting and further calculations.
