Statistical Evaluation of Single Nano‐Object Fluorescence

Lippitz, Markus; Kulzer, Florian; Orrit, Michel

doi:10.1002/cphc.200400560

Cited by 129 publications

(135 citation statements)

References 201 publications

(235 reference statements)

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“…Individual fluorescent molecules can now be detected routinely (43); yet, to realize the full potential of single-molecule spectroscopy and imaging, it is important to go beyond simple visualization when analyzing and interpreting data from these experiments (44). This report represents the application of several recent developments in fluorescence single-molecule techniques based on information theory that use the information carried by each detected photon in an unbiased way (31,32,45).…”

Section: Discussionmentioning

confidence: 99%

Illuminating the mechanistic roles of enzyme conformational dynamics

Hanson

Duderstadt

Watkins

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

280

430

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Many enzymes mold their structures to enclose substrates in their active sites such that conformational remodeling may be required during each catalytic cycle. In adenylate kinase (AK), this involves a large-amplitude rearrangement of the enzyme's lid domain. Using our method of high-resolution single-molecule FRET, we directly followed AK's domain movements on its catalytic time scale. To quantitatively measure the enzyme's entire conformational distribution, we have applied maximum entropy-based methods to remove photon-counting noise from single-molecule data. This analysis shows unambiguously that AK is capable of dynamically sampling two distinct states, which correlate well with those observed by x-ray crystallography. Unexpectedly, the equilibrium favors the closed, active-site-forming configurations even in the absence of substrates. Our experiments further showed that interaction with substrates, rather than locking the enzyme into a compact state, restricts the spatial extent of conformational fluctuations and shifts the enzyme's conformational equilibrium toward the closed form by increasing the closing rate of the lid. Integrating these microscopic dynamics into macroscopic kinetics allows us to model lid opening-coupled product release as the enzyme's rate-limiting step.conformational equilibrium ͉ rate-limiting step ͉ single-molecule FRET ͉ adenylate kinase P roteins such as enzymes are flexible with a range of motions spanning from picoseconds for localized vibrations to seconds for concerted global conformational rearrangements (1). Despite their randomly fluctuating environment, in which stochastic collisions with solvent molecules drive changes in tertiary structure, enzymes have evolved to catalyze reactions efficiently and specifically. Indeed, conformational transitions have been postulated to play a central role in enzyme functions in a wide variety of ways, including direct contribution to catalysis (2), allosteric regulation (3), and large-scale conformational changes in response to ligand binding (4). Most of our current understanding of structural motions in solution comes from NMR experiments (5) as well as from molecular dynamics simulations (6), approaches that are best suited to study dynamics in the picoto millisecond time scales. Because catalysis in enzymes frequently occurs in the submillisecond to minute time regime, our current understanding of the relationship between enzyme function and conformational dynamics comes from NMR experiments involving relatively localized motions of active site forming loops on the submillisecond time scale (7-10). However, many enzymes contain active sites located in between domains in which large-amplitude, low-frequency domain motions are required to complete their Michaelis-Menten enzyme-substrate complexes. Even simple questions regarding these transitions remain generally unanswered: What is the number and range of conformational states accessible to enzymes during their catalytic cycle? How does the enzyme's conformation respond to interac...

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Section: Discussionmentioning

confidence: 99%

Illuminating the mechanistic roles of enzyme conformational dynamics

Hanson

Duderstadt

Watkins

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

280

430

View full text Add to dashboard Cite

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“…Considering the various analysis methods (Lippitz et al 2005) yielding often different types of information, an obvious question arises: is a particular method analysing the data efficiently, and what is the limit on the amount of information that can be extracted from given data with certain noise level? The answers are being sought using the concepts of information theory, such as Shannon information, entropy, mutual information or Fisher information (Watkins & Yang 2004;Talaga 2006).…”

Section: Single-point Measurementsmentioning

confidence: 99%

Fluctuations as a source of information in fluorescence microscopy

Petrášek

Schwille

2008

J. R. Soc. Interface.

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Fluctuations in fluorescence spectroscopy and microscopy have traditionally been regarded as noise-they lower the resolution and contrast and do not permit high acquisition rates. However, fluctuations can also be used to gain additional information about a system. This fact has been exploited in single-point microscopic techniques, such as fluorescence correlation spectroscopy and analysis of single molecule trajectories, and also in the imaging field, e.g. in spatio-temporal image correlation spectroscopy. Here, we discuss how fluctuations are used to obtain more quantitative information from the data than that given by average values, while minimizing the effects of noise due to stochastic photon detection.

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“…While autocorrelation has the advantages of allowing information to be extracted at relatively low signal-to-noise ratios, real-time autocorrelation traditionally has required dedicated, relatively expensive hardware. In addition, there is the assumption that the process is stationary (Krichevsky, 2002;Lippitz, 2005). A third method involves plotting the distribution of delays (Lippitz, 2005), alternatively denoted as the photo arrival time histogram (PART) (Fore, 2005), obtained from timecorrelated single-photon counting (TCSPC).…”

Section: Introductionmentioning

confidence: 99%

“…In addition, there is the assumption that the process is stationary (Krichevsky, 2002;Lippitz, 2005). A third method involves plotting the distribution of delays (Lippitz, 2005), alternatively denoted as the photo arrival time histogram (PART) (Fore, 2005), obtained from timecorrelated single-photon counting (TCSPC). While powerful, this technique requires expensive hardware designed explicitly for TCSPC.…”

Section: Introductionmentioning

confidence: 99%

Real‐time data acquisition incorporating high‐speed software correlator for single‐molecule spectroscopy

Yang

Lee

Wang

et al. 2009

Journal of Microscopy

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SummarySingle-molecule spectroscopy and detection are powerful techniques for the study of single fluorescent particles and their interaction with their environment. We present a lowcost system for simultaneous real-time acquisition, storage of inter-photon arrival times and the calculation and display of the fluorescence time trace, autocorrelation function and distribution of delays histogram for single-molecule experiments. From a hardware perspective, in addition to a multi-core computer, only a standard low-cost counting board is required as processing is software-based. Software is written in a parallel programming environment with time crucial operations coded in ANSI-C. Crucial to system performance is a simple and efficient real-time autocorrelation algorithm (acf) optimized for the count rates (approximately 10 4 cps) encountered in single-molecule experiments. The algorithm's time complexity is independent of temporal resolution, which is maintained at all time delays. The system and algorithm's performance was validated by duplicating the signal from the photon detector and sending it to both the ordinary counter board and a commercial correlator simultaneously. The data acquisition system's robustness under typical single-molecule experimental conditions was tested by observing the diffusion of Rhodamine 6G molecules in deionized water.

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Statistical Evaluation of Single Nano‐Object Fluorescence

Cited by 129 publications

References 201 publications

Illuminating the mechanistic roles of enzyme conformational dynamics

Illuminating the mechanistic roles of enzyme conformational dynamics

Fluctuations as a source of information in fluorescence microscopy

Real‐time data acquisition incorporating high‐speed software correlator for single‐molecule spectroscopy

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