Fluorescence fluctuation data

A related method has been used to demonstrate that lifetimes as ort as 200 ps can be measured usii the mode noise in a free-running a on-ion laser to produce variations in the excited state population of a fluorophore . Meaairement of the rf power spectmm of the resilting fluctuations then reveals the excited state lifetime. Mode noise contains very high frequency fluctuations which the excited state population cannot follow because of its finite lifetime, and thus these hi frequency components are absent from the rf spectrum of the fluorescence fluctuations. The fluorescence process thus acts like a low pass exponential filter, and comparison of the fluorescence power spectmm with that of the source provides the decay time data, as demonstrated below. 

One limitation, however, is that only a limited number of spots can be measured simultaneously. A compromise between the temporal analysis of FCS and fluorescence fluctuation analysis in the spatial domain [39] can be obtained by exploiting the time structure of sample/laser scanning confocal microscope images [40,41]. Thereby, spatial correlation analysis of the emitted fluorescence is combined with temporal characterization of the fluorescence emission from the serial data stream of subsequently scanned pixels. This... 

Section 7.3.1 describes the experimental apparatus for collecting and analyzing fluorescence lifetime data vs temperature. Section 7.3.2 presents the results of lifetime measurements of polyproline peptides and MD simulations to (a) relate fluorescence quenching rates to specific conformational fluctuations, and (b) calculate the implications of intramolecular electrostatic interactions for the quenching mechanism. 

Brownian diffusion and internal motions of a macromolecule cause the intensity of quasielastically scattered hght to fluctuate with time, and the autocorrelation function of the scattering provides information on the dynamics of these motions as we discussed in Sect. 5.11 for fluorescence fluctuations. Berne and Pecora [13], Schurr [113, 114], Chu [112] and Brown [115] give expressions for the autocorrelation functions that apply to various models for proteins and nucleic acids, along with further information on data collection and analysis. If the autocorrelation function decays with a single exponential time constant t, the molecule s diffusion... 

B) FRET efficiency as a function of Mg2+ ion concentration for the SB and BC vectors. The data have been fitted to a two-state ion binding model. Fluorescence emission spectra were recorded at 4 °C using an SLM-Aminco 8100 fluorimeter with modernized Phoenix electronics (ISS Inc., Champaign, IL, USA). Spectra were corrected for xenon lamp fluctuations and instrumental variations, and polarization artifacts were avoided by crossing excitation and emission polarizers at 54.7°. 

Figure 11.2 The image in the upper left panel shows a snapshot of several individual protein molecules immobilized in a gel. Each protein undergoes conformational fluctuations that can be monitored by a fluorescent probe. The fluorescent signal from a single protein molecule, as a function of time, is recorded in the time trace shown in the lower left panel. On the right, the experimental situation and the fluorescent time trace are idealized as a two-state conformational transition process as given in Equation (11.5), with A representing the darker state and B representing the brighter state. Image and data in left panel obtained from Lu et al. [133], Reprinted with permission from AAAS.

Figure 17.4 Principle of fluorescence correlation spectroscopy the fluorescence intensity temporal fluctuations originating from a well-defined volume are recorded and correlated to estimate the average number of molecules observed and the characteristic fluctuation time. This data is used to compute the average detected fluorescence rate per molecule in the observation volume.

Fig. 24.2. Single-molecule recording of T4 lysozyme conformational motions and enzymatic reaction turnovers of hydrolysis of an E. coli B cell wall in real time, (a) This panel shows a pair of trajectories from a fluorescence donor tetramethyl-rhodamine blue) and acceptor Texas Red (red) pair in a single-T4 lysozyme in the presence of E. coli cells of 2.5mg/mL at pH 7.2 buffer. Anticorrelated fluctuation features are evident. (b) The correlation functions (C (t)) of donor ( A/a (0) Aid (f)), blue), acceptor ((A/a (0) A/a (t)), red), and donor-acceptor cross-correlation function ((A/d (0) A/d (t)), black), deduced from the single-molecule trajectories in (a). They are fitted with the same decay rate constant of 180 40s. A long decay component of 10 2s is also evident in each autocorrelation function. The first data point (not shown) of each correlation function contains the contribution from the measurement noise and fluctuations faster than the time resolution. The correlation functions are normalized, and the (A/a (0) A/a (t)) is presented with a shift on the y axis to enhance the view, (c) A pair of fluorescence trajectories from a donor (blue) and acceptor (red) pair in a T4 lysozyme protein without substrates present. The acceptor was photo-bleached at about 8.5 s. (d) The correlation functions (C(t)) of donor ((A/d (0) A/d (t)), blue), acceptor ((A/a (0) A/a (t)), red) derived from the trajectories in (c). The autocorrelation function only shows a spike at t = 0 and drops to zero at t > 0, which indicates that only uncorrelated measurement noise and fluctuation faster than the time resolution recorded (Adapted with permission from [12]. Copyright 2003 American Chemical Society)...

Common to most fluorescence-based single-molecule methods, photobleaching limits the observation time window using the fluorescence quenching via energy transfer approach. In addition, this approach only obtains the fluorescence intensity from one probe thus, fluorescence intensity fluctuations due to probe photophysics, such as fluorescence blinking, can complicate the results and data analyses. Triplet quenchers such as Trolox 95 can reduce fluorescence blinking. Careful control experiments are in any case necessary. 

The explanations most often invoked are i) temperature fluctuations, ii) incorrect atomic data, iii) fluorescent excitation, iv) upward bias in the measurement of weak line intensities, v) blending with other lines, vi) abundance inhomogeneities. None of them is completely satisfactory, some are now definitely abandoned. 

From the point of view of field insfrumentation for measuring pressure inside fhe combustion chamber, it is possible to use either a glass U-tube manometer filled with fluorescent liquid or an industrial manometer for local measurements and an electronic pressure sensor for remote measurements and collection of data. Reliability and ability to dampen the pressure fluctuation inside the combustion chamber are the advantages of the U-tube and robust industrial manometers. 

---