Emerging Tools for Single-Cell Analysis

driven scanner with 500-Hz bandwidth (Cambridge Technology, Watertown, MA) correspondingly deflects the line-scanning beam along the y-axis. The spinning disc of the polygonal mirror comprises 50 aluminum-coated facets (2 2 mm) arranged contiguously around the disc’s perimeter. The facets repetitively deflect the laser beam over a specific angular range, correspondingly scanning a line 50 times per revolution. Rotation speeds of either 10,000, 15,000, 20,000, or 30,000 rpm are available.

The fluorescence is recorded by an intensified, frame transfer CCD camera (Pentamax; Princeton Instrument, Trenton, NJ). The 12-bit data of the 512 512 pixel CCD chip can be read out at 5 MHz. The maximum achievable image transfer rate is about 10 frames per second for 256 256 pixel images (2 2 pixel binning). Consequently, the polygonal mirror spinning speed is adjusted to 10,000 rpm, and the CCD exposure time is correspondingly set to 90 ms. In order to perform 3D volume scans, the objective is mounted on a computer-controlled piezoelectric objective translator (P-721.00, Physik Instrumente, Waldbronn, Germany).

A laser diode (1 mW at 632 nm; Thorlab, Newton, NJ) and a photodiode detector (Thorlab, Newton, NJ) are used to encode the polygonal mirror position and to generate a reference signal to synchronize the x, y scanners, the objective translator, and the CCD camera.

To demonstrate the acquisition of clinically relevant images using a video-rate two-photon microscope, we have studied the dermal structures in ex vivo human skin. The collagen/elastin fiber structures in the dermal layer were imaged (Fig. 10.6). One hundred images were taken at depths between 80 and 120 m below the skin surface. The frame rate was 90 ms and the entire stack of images was acquired in 9 s. The filamentous structures of the collagen/elastin fibers can be clearly resolved from the figure. Representative images of the fiber structures were shown in Figure 10.5. Due to the lower fluorescence intensity of the NAD(P)H components in the epidermal keratinocytes, they are more difficult to observe. The basal cells can be visualized; however, their high melanin content makes thermal damage due to one-photon absorption a major concern. Thermal damage to the basal layer was occasionally observed. We are investigating a method to mitigate this problem (Masters et al., submitted).

TWO-PHOTON FLUORESCENCE SPECTROSCOPY IN DEEP TISSUE

Importance of Spectroscopic Information in Deep-Tissue Imaging

In addition to structural information, two-photon fluorescence microscopy can be used to assess tissue functional state by spectroscopic study of the induced fluorescence. Information such as emission wavelength, fluorescence lifetime, and emission polarization can be used to monitor the tissue microenvironment. Fluorescence spectroscopic techniques can be applied in a number of ways. First, different structures in the tissue can be distinguished either by their endogenous spectroscopic properties or by extrinsic fluorophores labeling the tissue. Second, fluorescence spectroscopy can

mal keratocytes) with two-photon excitation at 730 nm are shown in Figure 10.7. These spectra show a peak in the region of 450 nm and an FWHM of about 100 nm. The shape and wavelengths of the emission spectra are consistent with those of the NAD(P)H fluorescence.

The maximum intensities of the fluorescence emission occur at 450 nm and show a large variation between the various cell layers. The highest fluorescent intensity was recorded for the basal epithelial cells (35,000 AU). The peak intensity recorded from the wing cells (3000 AU) was more than an order of magnitude less than that from the basal epithelial cell. The lowest fluorescent intensity (600 AU) was recorded from the stromal keratocytes. These results support the fact that the cells in the basal region are the most metabolically active.

CONCLUSION

Two-photon fluorescence microscopy is a powerful technique for studying deeptissue physiology. In this chapter, we discussed three recent complementary developments in the field with significant impacts in advancing two-photon, deep-tissue technology. We have shown that a blind deconvolution algorithm can not only further improve quality of two-photon images but also provide psf information in inhomogeneous specimen. The additional psf information can help to understand two-photon-induced photonic interaction in deep tissue. We have also seen the importance of video-rate microscopy in extending two-photon technology to potential clinical applications. In the section on video-rate, two-photon technology, we saw that video-rate, two-photon microscopy can provide fast structural information in deep tissue. Future development clearly will extend the faster imaging technique to clinical diagnosis of diseases. In addition to structural information, two-photon spectroscopic data can be acquired in conjunction with images. The biochemical information acquired can be complemented to structural images, providing a new dimension to the two-photon technique.

These developments represent significant advances in two-photon, deep-tissue microscopy. In the future, it can be envisioned that they will act in unison to address important physiological problems in deep-tissue studies.

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focusing and imaging systems but also counting photons, a process that implies important limitations on data rate and statistical accuracy.

The task of the confocal light microscope is to measure optical or fluorescent properties within a number of small, contiguous subvolumes of the specimen (Fig. 11.1; Pawley and Centonze, 1994). Because confocal microscopy is probably the most sensitive method for imaging living cells and because imaging such cells places the greatest demands on the instrumentation and technique, we will generally consider the specimen to be a living cell. The fundamental limits on this process are related to the quantitative accuracy with which these measurements can be made, a factor that depends on the number of photons that pass into, n1, and out of, n2, the subvolume; its size ( x, y, z); and its position (x, y, z). Additional limitations are imposed on the rate at which these measurements can be made by the effects of photodamage to the specimen, source brightness, and fluorescence saturation. Finally, limitations are imposed by the fact that the continuous specimen must be measured in terms of discrete volume elements called voxels (a voxel is the 3D equivalent of a pixel, which is the smallest element of a 2D image). Although, for simplicity in discussion, these factors are usually treated separately, in practical microscopy they almost always interact. The discussion that follows will often highlight the interactions.

This chapter will outline the factors that ultimately limit the accuracy with which these measurements can be made. Although most of the discussion should be applicable to any form of confocal microscope, we will assume that scanning is accomplished by moving a single beam of laser light.

The data recorded from a confocal laser scanning microscope (CLSM) are usually a set of intensity values matched to every pixel of a 2D optical section or to every voxel throughout a 3D volume in the specimen. Ideally, these values represent the concentration of fluorophore as a function of position. In fact, many other factors can produce unintended contrast. In fluorescence confocal microscopy, the rate at which data can be produced is limited by fluorescence saturation. As a result, the statistical quality of the data is often related inversely to the scanning speed, the instability of the fluorophore, and the size of the raster.

Counting Statistics: The Importance of n

The accuracy of any particular measurement involving fundamental, quantum interactions (such as counting photons) is limited by Poisson statistics, which ensure that the 1 error in a measurement of n photons is n. While similar considerations limit the performance of all types of microscopical measurements, they are more explicit in their effect on confocal microscopy, where peak signal levels often produce signal levels of only about 8 photons per 2- s pixel.

The uncertainty associated with counting quantum-mechanical events is the source of intrinsic statistical noise. Confocal data sets can also contain extrinsic noise introduced by detector dark current, electronic noise, or interference or produced by stray or out-of-focus light. Unlike intrinsic noise, extrinsic noise can be reduced by careful technique and technological improvements. Indeed, the first test of a confocal microscope should be to collect signal from a “blank field.” To do this, form an image

F i g . 11.1. Parameters related to the fundamental limitations of confocal microscopy.

of a nonfluorescent object such as pure water and set the PMT gain as you would for “normal” operation for a weak specimen and the dc offset so that the average recorded signal is about 10 digital units (assuming 8-bit, 256-level digitization). A statistical analysis of a single-scan data set should allow you to differentiate pixels with one dark count from those with none. A count rate of more than 10,000 “bright” pixels per 1-s scan should be a cause for concern. Perhaps the PMT photocathode is

being accidentally warmed by nearby equipment. Alternatively, you may have a light leak. To localize the problem, try comparing one detector channel with another, turning off the room lights, or obscuring the laser.

To check for “fixed-pattern” noise, accumulate data from a large number of dark frames by Kalman averaging. The appearance of any sort of pattern on the screen as more data are acquired may also indicate a problem. However, one must realize that fixed-pattern noise always exists at some level. It is only a problem if it is similar in size to the signal level, and even then its effect can sometimes be reduced by subtracting a “noise-only” pattern from a “signal-plus-noise” pattern.

In a well-designed CLSM, the major noise source is intrinsic noise. This fact highlights the importance of making sure that as many as possible of the available photons are recorded as part of the signal.

Specimen Response: Dye Saturation. In “normal microscopy” it is safe to assume that photons interact with the specimen in a manner that is independent of the intensity of the illumination and that output signal is always directly proportional to excitation. However, this linear response is not characteristic of any laser-based fluorescence confocal microscopes operated with 1 mW in a 0.5- m-diameter spot in the specimen. Not only may absorption in the specimen cause sufficient warming to produce damage or motion, but the electric field strength of the focused light may also become sufficient to produce a variety of nonlinear responses such as fluorescence saturation.

Saturation occurs when fluorescent molecules are excited by a flux of exciting illumination so intense that, at any instant, a significant fraction of the fluorescent molecules is in the excited state. As excited molecules no longer absorb light at the usual wavelength ( ), this has the effect of lowering the effective dye concentration. This saturation threshold can easily be reached at flux levels around 106 W/cm2. Saturation is related to absorption cross section and fluorescence lifetime. As can be seen from Equations (1) and (2), the problem is more severe when using dye molecules with long fluorescent decay times f:

I

(11.1) h

where is the excitation rate in reciprocal seconds at low intensity, is excitation cross section in centimeters squared, I is the excitation intensity in watts per centimeters squared, and h is the energy of the absorbed excitation photon. Then

where N1 is the fraction of dye molecules in the first singlet state, near saturation. With most dyes, singlet-state saturation occurs at power levels of about 1 mW if focused into a diffraction-limited spot by a numerical aperture (NA) 1.3 lens. As lower NA produces a larger spot area, an NA 0.65 would not saturate until about four times