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EtBr cell

Figure 3.4. Illustration of using a single living cell as SM detection volume: (A) Sub-frame high-resolution optical image of single living bacterial cells, P. aeruginosa (WT), acquired using dark-field microscopy, showing the size of single cells. Solid-line and dash-line squares represent the selected pixel area for integrated fluorescence intensity analysis of EtBr in a single cell and in solution, respectively. (B) Schematic illustration of the selected detection volume containing a single EtBr molecule in the solution (left) and with a single live cell (right) in the microchannel. EtBr enters the cell using passive diffusion and is extruded out of the cell by MexAB-OprM. [Reprinted from Biochem Biophys Res Commun 305:941-949, with permission of Academic Press.] See insert for color representation of these figures.

and an equal sized pixel area that contains no cells (solution only) (dash-line square) in the same frame (Figure 3.4A) are selected. The integrated fluorescence intensity of area (dash-line square) where no cell is presence (EtBr in solution) is subtracted from that of the cell is presence (solid-line square) (EtBr in a single cell). Representative plots of subtracted integrated fluorescence intensity versus time Figure 3.5A clearly demonstrate that the change of fluorescence intensity of a single EtBr molecule with a single WT cell is above the fluctuation of background emission of a single cell and ICCD noise (baseline). Unlike eucaryote cells, the auto-fluorescence of the bacterial cells is not observed. This might be attributable to its tiny size (2 x 0.5 x 0.5 ^m).

As EtBr molecules enter the cell and intercalate with DNA, the fluorescence intensity of a single EtBr molecule in the cell increases over the intensity of EtBr in solution. Thus, the subtracted integrated intensity becomes positive. In contrast, as EtBr molecules are transported out of the cell, the fluorescence intensity of a single cell decreases below the intensity of EtBr in solution. Thus, the subtracted integrated intensity becomes negative. EtBr concentration in solution is higher than in a live cell. Thus, the molecule must be extruded out

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Figure 3.5. SMD of membrane pump efficiency of single living cells. Representative plots of (A) subtracted integrated fluorescence intensity of a single EtBr molecule in solution (dash-line square) from that in a single live cell (WT) (solid-line square) versus time (min) at 21.5000-21.9000 min; (B) seventeen sets of the 200 consecutive images are taken during 80 min. A zoom-in display of (B) at 21.5000-21.9000 min is shown in (A). Every set of 200 sequence images is taken with a 70-ms temporal resolution and 99.84-ms CCD exposure time. [Reprinted from Biochem Biophys Res Commun 305:941-949, with permission of Academic Press.]

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Figure 3.5. SMD of membrane pump efficiency of single living cells. Representative plots of (A) subtracted integrated fluorescence intensity of a single EtBr molecule in solution (dash-line square) from that in a single live cell (WT) (solid-line square) versus time (min) at 21.5000-21.9000 min; (B) seventeen sets of the 200 consecutive images are taken during 80 min. A zoom-in display of (B) at 21.5000-21.9000 min is shown in (A). Every set of 200 sequence images is taken with a 70-ms temporal resolution and 99.84-ms CCD exposure time. [Reprinted from Biochem Biophys Res Commun 305:941-949, with permission of Academic Press.]

of the cell through the active efflux mechanism. Taken together, the subtracted fluorescence intensity is positive or negative, representing the location of a single EtBr molecule, in or out of a single living cell, respectively. The frequency of change sign of the subtracted fluorescence intensity from negative to positive or from positive to negative represents the rates of influx and efflux of a single EtBr molecule by a single living cell. Seventeen sets of 200 sequence images recorded in Figure 3.5B demonstrates the stochastic influx and efflux rate of a single EtBr molecule with the average at (2.86 ± 0.12) s-1. The average of influx and efflux rate remains nearly constant over time, which is in an excellent agreement with the bulk measurement of accumulated EtBr in WT cells (Figure 3.2B).

The study of the dependence of efflux rate on temporal resolution, EtBr (substrate) concentration, and mutants indicates that the efflux rate of two mutants (nalB-1, AABM) in the presence of 0.2-0.4 nM EtBr at the temporal resolution of 60 ms and 70 ms is the same. The results suggest that the efflux rate is at least 10 ms, indicating that the influx and efflux rate at the single molecule level is indeed measured because the pump efficiency is independent on substrate concentration only at the single-molecule level and is dependent on substrate concentration at the multimolecule level (Kyriacou et al., 2002; Xu et al., 2003a,b). Furthermore, the result suggests that the influx and efflux rates of a singlesubstrate molecule (EtBr) are independent on number of pumps expressed per cell. This is consistent with the unique feature of single-molecule measurements. The observation of influx and efflux of EtBr by A ABM suggests that other pump proteins (e.g., MexCD-OprJ) with the low expression level in A ABM may be responsible, which is another distinguished feature of SMD, allowing rare phenomena to be observed at the SM level.

3.3.2. Sizing the Membrane Transport of Single Living Cells in Real Time

While fluorophors (e.g., EtBr) can be used to trace the influx and efflux rate of membrane pump, it does not provide the size information of membrane pores. It is very likely that membrane proteins can specifically recognize an array of structurally unrelated substrates (e.g., chemotoxics) and assemble membrane transporters optimized for the extrusion of specific encountered substrates. Such fascinating smart sensing and transport mechanisms occur at the nanoscale regime. Thus, studies of the mechanism and assembly of the efflux pump will offer new insights into the function of efflux pump and will provide new knowledge that is essential for the design of self-assembly of smart molecular pumps.

Currently, the sizes of membrane transporters are determined solely by x-ray crystallography measurements, which are limited by the difficulties of crystallization of membrane proteins. In addition, x-ray crystallography cannot be used to study real-time dynamics of self-assembly of pump proteins in living cells (Tate et al., 2001). Despite extensive study over decades (Poole et al., 1993; Nakae, 1995; Ryan et al., 2001; Li and Nikaido, 2004), the structure, mechanisms, and function of extrusion transport remain unclear.

To address some of these questions, our research group has developed a new tool that uses silver (Ag) nanoparticles as nanometer probes to determine the sizes of substrates that can be transported through the membrane of living microbial cells and to measure accumulation kinetics of the substrates in real time at single-cell resolution (Xu et al., 2002, 2004). The challenges of such a study include: (i) how to overcome the rapid motion of tiny bacterial cells with size of 2 x 0.5 x 0.5 ^m in suspension so that the living cells can be confined and continuously monitored in suspension for hours; (ii) how to simultaneously monitor a group of individual cells so that one can obtain statistical information of bulk cells at the single-cell resolution; and (iii) how to develop a new imaging tool that can measure the nanometer probes moving in and out of living cells for real-time monitoring change of membrane permeability and efflux kinetics at the nanometer (nm) resolution.

Our group has overcome these challenges by developing and utilizing a microchannel system to confine living bacterial cells in suspension with no need to immobilize them, which allows living bacterial cells to be continuously and simultaneously monitored and imaged at the single-cell resolution for hours using a CCD camera coupled with dark-field optical microscope (Kyriacou et al., 2002; Xu et al., 2003; Xu et al., 2004). Furthermore, Ag nanoparticles as nanometer probes are developed to directly image the changes of membrane pore sizes and permeability at the nanometer (nm) and millisecond (ms) resolution using optical microscopy (Xu et al., 2002; Kyriacou et al., 2004; Xu et al., 2004).

3.3.2.1. Surface Plasmon Resonance of Single Silver Nanoparticles

Optical properties, such as localized surface plasmon resonance spectra (LSPRS) of Ag nanoparticles, depend on size and shape of nanoparticles and dielectric constant of its embedded medium (Mie, 1908; Bohren and Huffman, 1983; Kreibig and Vollmer, 1995; Mulvaney, 1996; Lamprecht, 2000; Haynes and Van Duyne, 2001).

Unlike bulk material, individual nanoparticles have a much higher surface-to-volume ratio. The surface properties contribute significantly to optical properties of nanoparticles. Unlike the bulk plasmon, the surface plasmon of nanoparticles can be directly excited by propagating light waves (electromagnetic waves), leading to the selective absorption and scattering of particular wavelength of light.

When noble metal nanoparticles are illuminated by light (electromagnetic wave), due to the small size of nanoparticles, the electromagnetic field generates polarized charges on the nanoparticle surface, which creates a linear restoring force, leading to subsequent charges on the surface of nanoparticles (Raether, 1988; Bohren and Huffman, 1983; Lamprecht, 2000). Thus, the conduct electrons in a nanoparticle act as an oscillator system, leading to a resonance behavior of the electron plasmon oscillation, as illustrated in Figure 3.6. The frequency of oscillation (surface plasmon resonance spectra) depends upon the energy (wavelength) of light and geometry of nanoparticles. The phenomena of LSPR of nanoparticles have been described by Mie theory (Mie, 1908). With an assumption of quasi-static regime, nanoparticle radius (R) ^ x (wavelength of the light), the electromagnetic excitation field is assumed to be nearly constant for each location of the entire volume of a spherical nanoprticle. With such an assumption, the polarizability of nanoparticles shows the dependence of shape, aspect ratio and frequency-dependent dielectric function of nanopar-ticles, and dielectric constant of embedding medium of nanoparticles, as described in the following equation (Mie, 1908; Bohren and Huffman, 1983, Kreibig and Vollmer, 1995; Lamprecht, 2000):

sm + [e(rn) - sm]Li where ai (m), m, Li, V, e0, sm, and s(m) represent frequency-dependent electric polariz-ability, frequency, a geometrical depolarization factor (dependent on the shape and aspect ratio of nanoparticle), volume of a nanoparticle, dielectric constant of vacuum and of the embedding medium, and frequency-dependent dielectric function of the nanoparticle.

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Figure 3.6. Illustration of interaction of light (electromagnetic wave) with a noble metal nanoparticle, creating subsequent charges on the surface of a nanoparticle and thereby leading to a resonance behavior of the electron plasmon oscillation, a phenomenon known as localized surface plasmon resonance (LSPR) of a nanoparticle.

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