Analytical Applications
Single-species-level assays that would be Richard A. Keller W. Patrick Ambrose difficult or impossible with Angela A. Arias Hong Cai conventional bulk Steven R. Emory measurements can now be Peter M. Goodwin James H. Jett Los Alamos National Labo easurement capability is at the core of all physical investigations. New measurement capabilities have led to the discovery and understanding of many new physical phenomena. For analytical chemists, the ultimate goal of a measurement technique is single-molecule detection (SMD) and counting. Our group and others have developed the capability to detect and identify single fluorescent molecules as they pass through a tightly focused laser beam (1). In recent years, approximately two-dozen research groups worldwide have reported SMD and applications of single-molecule measurements. Single-molecule spectroscopy (SMS) enables the determination of properties of individual molecules that are often hidden in ensemble averages associated with bulk measurements. SMS techniques can now be used to quantitatively measure singlemolecule properties, such as fluorescence lifetime, fluorescence intensity, fluorescence resonance energy transfer (FRET) efficiency, spectral distribution, polarization anisotropy, and diffusional motion. Detection of single molecules labeled with ~100-fluorescein fluorophores was first reported by Hirschfeld in 1976 (2). We began our quest to detect single-fluorophore molecules in flow with Dovichi’s work in 1983 (3) and progressed until we detected them in 1990 (4). A description of our approach to SMD, as well as several review articles detailing progress in SMD, can be found elsewhere (1, 5–7 ). In this article, we describe the technol-
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ogy behind SMD in fluid solution and its applications in analytical chemistry. Applications to biophysics and molecular dynamics are summarized elsewhere (8). For the most part, we focus on the detection and spectroscopy of individual fluorophores. In a few cases, examples are given that involve species containing several fluorophores. Fluorescence correlation spectroscopy and related techniques, in which averages of single-molecule properties are acquired from measurements of many molecules at the single-molecule level, are not included.
Basics The signature of a single fluorophore is a burst of photons emitted as the molecule traverses a focused laser beam. In a laser beam tuned to the absorption frequency of a highly fluorescent molecule, the molecule is repeatedly cycled between its ground state and excited electronic states with the emission of a photon (fluorescence) on most cycles. Photobleaching limits the number of photons emitted by a highly fluorescent molecule to ~105. It is customary to work at an irradiance level such that 90% at a detection rate of ~100 molecules/s (17, 18).
Qualitative analysis
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Detection of single fluorescent molecules is only part of the story. An important component of analytical chemistry is identifying the analyte either alone or in a complex mixture. Fluorescence properties that have been used to identify single molecules are emission wavelength, fluorescence decay time, photon burst size, fluorescence emission polarization anisotropy, and photon burst duration, as well as various combinations of these properties. In 1992, Soper et al. used fluorescence emission spectra to distinguish between single molecules of rhodamine 6G (R6G) and Texas red (19). A hydrodynamically focused sample stream was illuminated with the output of a mode-locked, frequency-doubled Nd:YAG laser at 532 nm to excite R6G and a mode-locked dye laser tuned to 585 nm to excite Texas red. Fluorescence from the sample was collected with a high numerical aperture microscope objective, spectrally separated with a dichroic beam splitter, and impinged onto one of two microchannel plate photomultipliers. The cross talk between the two detection channels was small and the two
dyes were easily distinguished. The fluorescence lifetime can be measured at the single-molecule level (19, 20). In contrast to the fluorescence emission intensity (burst size), the fluorescence lifetime is an intrinsic prop-
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Burst size (PE) FIGURE 1.Detection of single-TRITC molecules in dilute aqueous buffer. TRITC was introduced electrokinetically from a drawn capillary with an i.d. of 1 µm at the tip. Conditions: excitation, 554-nm, mode-locked dye laser; average laser power, 20 mW; repetition rate, 82 MHz; beam waist, 15 µm (1/e2); transit time, ~2 ms; probe volume ~1 pL. Sample stream (a) on and (b) off. (c) Histogram of the burst sizes from (a) and (b). (Adapted with permission from Ref. 18.)
erty of the molecule and its environment; it does not depend upon the excitation intensity or the optical detection efficiency. However, the accuracy of the extracted lifetime, the confidence of identification, and the ability to distinguish between different molecules is a function of the number of photons detected for each molecule and the molecule’s fluorescence lifetime. Using fluorescence lifetime to distinguish among molecules is an attractive approach because it can be a one-laser, one-detector experiment, unlike emission spectra and fluorescence polarization anisotropy techniques. Extraction of the fluorescence lifetime from the limited data that is characteristic of SMD is a difficult problem for which several approaches have been developed. Enderlein and Sauer considered the problems of previous approaches and developed a sophisticated pattern matching procedure for the rapid analysis of single-molecule fluorescence decay curves (21). In a practical example, Sauer et al. used molecular identification by fluorescence decay to distinguish among three dyelabeled nucleotides (22).
time-resolved fluorescence polarization anisotropy to distinguish between rhodamine 123 (r = 0.01) and enhanced yellow fluorescent protein (EYFP) (r = 0.34) with a misclassification probability of ~1% (25). However, this is an extreme case with two components exhibiting nearly the maximum difference in fluorescence polarization anisotropies. To reduce the misidentification probability, simultaneous measurement of two or more parameters has been used. Van Orden and Werner were able to distinguish between R6G and TRITC by determining burst size and fluorescence decay rate, demonstrating greater confidence of identification than with one parameter alone (23, 24). Prummer and Herten combined fluorescence decay rate with spectral information to decrease molecular misidentification (26, 27). Unlike photon burst-size analysis, neither fluorescence spectra nor fluorescence decay are affected by photobleaching, the spatial dependence of the excitation, or the detection efficiencies. For example, Herten et al. distinguished among four fluorescently labeled nucleotides using two parame-
Using fluorescence lifetime to distin among molecules is an attractive approach because it can be a one-lase Fluorescence burst size can also be used to distinguish among single molecules. Burst size depends on the molecular absorption cross section at the excitation wavelength, fluorescence emission spectra, fluorescence quantum yield, and molecular photostability—all molecular properties that do not depend on the experimental configuration. Burst size also depends on the molecular environment (e.g., solvent), excitation intensity, and optical detection efficiency. Excitation intensity and optical detection efficiency are spatially dependent parameters. Again, this approach requires only a single excitation wavelength and a single detection channel. Using florescence burst size alone, Van Orden and Werner reported a 70–90% confidence level for distinguishing between R6G and TRITC (23, 24). A major contribution to the misidentification of R6G as TRITC resulted from the photobleaching of R6G. The fluorescence polarization anisotropy is related to the rotational relaxation time and is an intrinsic molecular property that depends on the size of the molecule, its environment, and its fluorescence lifetime. Polarized light is used to excite the molecule, and the intensity of the emission parallel (IZZ) and perpendicular (I⊥) to the excitation polarization is recorded. The polarization anisotropy r is defined by (IZZ – I⊥)/(IZZ + 2I⊥). For slowly rotating molecules, r = 0.4; for rapidly rotating molecules, the emission is depolarized and r = 0. The ratiometric measurement cancels out experimental variables and simplifies the data analysis. For example, Schaffer et al. used
ters. A scatter plot of the coordinated measurement of the fluorescence decay and two-channel spectra is shown in Figure 2. For the combined measurement, the lowest classification probability was 0.812 for four dyes and 0.994 for three dyes. Prummer used Monte Carlo simulations to generate lookup tables to estimate the probability of correctly identifying the dyes R6G (267), sulforhodamine B (647), dibenzanthranthene (102), and 1,1´-dioctadecyl-3,3,3´,3´-tetramethylindocarbocyanine perchlorate (724) by a combination of fluorescence decay rate and spectra as a function of the number of detected PE (26). The calculations are simple and can be done on-line. Prummer’s simulations show the number of detected PE that are needed to assign an observed single molecule to the correct species with a confidence level >99.9%. The number of PE required is indicated in parentheses in the list of dyes above. In all cases, the combination of determining spectral information and lifetime significantly improved the classification probability. Eggeling et al. used three parameters—intra-burst rate, fluorescence decay rate, and fluorescence polarization anisotropy— to reduce misidentification in a mixture of rhodamine 123 and EYFP (28). The low misidentification probability of 0.8% was primarily due to the large difference in rotational relaxation times between rhodamine 123 and EYFP. Similarly, Knemeyer et al. used a combination of burst size, fluorescence lifetime, and burst duration to distinguish between bound and free, fluorescently labeled, DNA hybridization probes (29).
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FIGURE 2.Identifying four mononucleotides. (a) Scatter plot of correlated spectrally resolved and time-resolved data and the regions used for identifying the four labeled mononucleotides, with darker shades of gray indicating increasing number of events. Histograms of the (b) fluorescence decay rate and (c) ratio of burst sizes detected at two spectral regions were constructed from one-dimensional measurements obtained from an experiment using a 1:1:1:1 mixture of the four mononucleotide conjugates. About 3000 fluorescence bursts with burst sizes ≥50 photon counts were detected. Average excitation power at the sample was 300 µW. F2 is the fractional intensity at Detector 2; kf is the fluorescence decay rate; SM is the fluorescence decay time. (Adapted with permission from Ref. 27.)
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Quantitative analysis Counting single molecules is an attractive way to do quantitative analysis. If the signal from each molecule is observable, the molecule count rate is a digital process and is a direct measure of the concentration of molecules. Knowing the photophysical properties of the molecule and experimental parameters is not necessary. Each molecule does not have to receive the same irradiance or have the same optical detection efficiency. This approach is particularly attractive for analyzing mixtures if the detected photon bursts can be identified with a molecular species. The probability of missing an analyte or obtaining a false
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positive caused by the background depend on the overlap of the burst-size distributions for the background and the analyte molecules and the value chosen for the threshold (decision point). In some cases, it is possible to operate the experiment with little photobleaching to obtain a peaked burst-size distribution (Figure 1c). A threshold is selected in the valley between the exponentially distributed background and the Gaussian-peaked signal to minimize the number of high background events above the threshold and include as many positive signals as possible. Alternatively, when the background and singlemolecule photocount statistics are characterized by Gaussian
Homogeneous assays—probe–target binding Typically, fluorescence probe–target binding assays require the removal of unbound fluorescent probes from the sample. Assays are termed homogenous when it is not necessary to separate the
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Separation chemistry Fister et al. were the first to demonstrate single-fluorophore analysis by CE (Figure 3). The separation and detection of single molecules of R6G and rhodamine B (RB) were performed in a micromachined electrophoresis channel using confocal techniques. Approximately 2% of the injected molecules were detected. For ultradilute samples and femtoliter detection volumes, the relative precision of the peak area, peak position, and peak standard deviation are dominated by the diffusion of the molecules into and out of the detection volume (14) and the inverse square root of the number of detected molecules (34). Concentration detection limits (>99% confidence) were reported to be 1.7 pM for R6G and 8.5 pM for RB. The separation time was 90% was demonstrated for TRITC molecules eluted from a ~1-µm-i.d. capillary tip into a focusing sheath flow (17 ) (Figure 1). A similar approach was used by Li and Davis who reported a molecular detection efficiency for sulforhodamine 101 of ~80% at a count rate of ~150 molecules/s (32). When confocal or total internal reflection techniques are used, special precautions are needed to ensure that a large fraction of the analyte molecules pass through the detection volume. Zander et al. reported counting molecules in a 10–11-M mixture of Cy5-dCTP and JA53-dUTP at the exit of a 0.5-µm-i.d. femtotip (33). Electrokinetic flow was used to move analyte molecules through the detection volume, and the molecular count rate was linear with applied voltage. Individual molecules were identified by their fluorescence decay rate. Lermer et al. reported counting R6G molecules dissolved in microdroplets with molecular detection efficiencies of ~80% at >99% confidence (30).
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FIGURE 3.Electrophoretic separation of R6G and RB. (a) Raw data from a 1.25-s gated injection of a solution containing 15 pM R6G and 30 pM RB. The solid horizontal line represents a molecular detection threshold of 7 photons/bin. (b) Histogram of the number of molecules detected in 100-ms-wide intervals. (Adapted from Ref. 14.)
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unbound probe from the sample. Thus, homogeneous assays are preferred because removing unbound probes requires a timeconsuming and potentially difficult chemical separation or washing step. In addition, removing unbound probe molecules disturbs the equilibrium of the probe–target binding. Molecular beacons are particularly attractive probes because the fluorescence quantum yield increases greatly when they bind to their target (36). The most common molecular beacon is a probe containing both a fluorescent energy transfer donor and a nonfluorescent, energy transfer acceptor. Initially, the donor and acceptor are in close proximity, and fluorescence from the probe is quenched. Upon binding to the target, the distance between the donor and acceptor increases, and the fluorescence quantum yield of the probe increases. Hence, only probe–target complexes fluoresce strongly. Knemeyer et al. developed an interesting molecular beacon DNA probe with a 25-mer single-stranded oligonucleotide containing an 18-base recognition sequence (29). It has a fluorescent energy donor (oxazine dye JA242) attached to a string of cytosines on one end. The other end has a string of energy quencher guanosines. In the absence of the DNA target, the cytosines and guanines bind, and the DNA probe forms a “hairpin” loop that brings the donor and quenchers into close proximity. In the presence of target DNA, the hairpin opens and the probe binds to the target at the complementary sequence, separating the donor from the quenchers, leading to strong emission from the donor. This probe was used to detect target DNA at a concentration
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(a) An expanded view of the square-bore capillary cell is depicted on the left, showing the two parallel laser beams focused through the cell. Fluorescence light, represented by two sets of arrows, is collected at right angles. (b) Fluorescence signal versus time for Detectors 1 and 2 for a 20-fM R6G aqueous solution. In this case, molecules travel toward the cathode, such that they are observed first in Detector 2 and then in Detector 1. Fluorescence bursts caused by the same molecule are labeled with the same number. The molecule marked X in Detector 2 either drifted away so that it missed the Detector 1 laser beam or photodegraded while in the first beam. Applied voltage, 100 V/cm. (c) A histogram of travel times extracted from (b). The distribution peak appears at negative times because the sign convention says that positive times indicate migration to the anode. (Adapted from Ref. 35.)
of 10–12 M. Spatial colocalization of two fluorescent tags forms the basis for single-molecule homogeneous assays for probe–target binding and molecule–molecule interactions. The assays are designed so that two different probes labeled with two different fluorescent dyes bind to the same target. The coincident detection of emission from both dyes denotes the presence of the target molecule. Castro developed a good example of a colocalization assay for detecting a specific sequence in DNA (Figure 5a) (37, 38). This approach was used to detect the presence of DNA in a large excess of salmon DNA (mass ratio 1:6 ⫻ 104), which provided a background of unrelated sequences. Two different fluorescently labeled peptide nucleic acid probes were designed to be specific for different sequences in DNA. Coincident bursts in both channels (Figures 5b and 5c) and a peak in the cross-correlation (Figure 5d) between the two channels indicated the presence of DNA in the sample. When the DNA was cleaved between the two binding sites, the coincident bursts and cross-correlation disappeared. This approach was also applied to the detection of an unamplified, single-copy gene in a transformed maize plant containing one transgene-per-haploid maize genome (3 ⫻ 109 base pairs) (37). A cross-correlation with a S/N of 60 was acquired in
