Single-molecule Biophysical Experiments Research Articles

Single-molecule biophysics experiments in silico: Toward a physical model of a replisome

SummaryThe interpretation of single-molecule experiments is frequently aided by computational modeling of biomolecular dynamics. The growth of computing power and ongoing validation of computational models suggest that it soon may be possible to replace some experiments outright with computational mimics. Here, we offer a blueprint for performing single-molecule studies in silico using a DNA-binding protein as a test bed. We demonstrate how atomistic simulations, typically limited to sub-millisecond durations and zeptoliter volumes, can guide development of a coarse-grained model for use in simulations that mimic single-molecule experiments. We apply the model to recapitulate, in silico, force-extension characterization of protein binding to single-stranded DNA and protein and DNA replacement assays, providing a detailed portrait of the underlying mechanics. Finally, we use the model to simulate the trombone loop of a replication fork, a large complex of proteins and DNA.

Progress toward Plug-and-Play Polymer Strings for Optical Tweezers Experiments: Concatenation of DNA Using Streptavidin Linkers.

Streptavidin is a tetrameric protein that is renowned for its strong binding to biotin. The robustness and strength of this noncovalent coupling has led to multitudinous applications of the pairing. Within the streptavidin tetramer, each protein monomer has the potential to specifically bind one biotin-bearing moiety. Herein, by separating various streptavidin species that have had differing numbers of their four potential binding sites blocked, several different types of “linking hub” were obtained, each with a different valency. The identification of these species and the study of the plugging process used to block sites during their preparation were carried out using capillary electrophoresis. Subsequently, a specific species, namely, a trans-divalent linker, in which the two open biotin-binding pockets are approximately opposite one another, was used to concatenate two ∼5 kb pieces of biotin-terminated double-stranded DNA. Following the incubation of this DNA with the prepared linker, a fraction of ∼10 kb strings was identified using gel electrophoresis. Finally, these concatenated DNA strings were stretched in an optical tweezer experiment, demonstrating the potential of the methodology for coupling and extending molecules for use in single-molecule biophysical experiments.

Increasing the Time Resolution of Single-Molecule Experiments with Bayesian Inference

Many time-resolved single-molecule biophysics experiments seek to characterize the kinetics of biomolecular systems exhibiting dynamics that challenge the time resolution of the given technique. Here, we present a general, computational approach to this problem that employs Bayesian inference to learn the underlying dynamics of such systems, even when they are much faster than the time resolution of the experimental technique being used. By accurately and precisely inferring rate constants, our Bayesian inference for the analysis of subtemporal resolution dynamics approach effectively enables the experimenter to super-resolve the poorly resolved dynamics that are present in their data.

Molecular Characterization of a Membrane-Associated Cytoskeletal Motor Family

Many large morphological changes in the plasma and intracellular membranes are powered by the actions of cytoskeletal motors. These motors include myosin-Is, which are the widely expressed members of the myosin superfamily that bind directly to membranes, linking them to the actin cytoskeleton. To better understand the molecular roles of myosin-I isoforms, and the mechanisms by which they modulate membrane dynamics, we performed a range of single-molecule biophysical, structural, biochemical, and cell biological experiments to determine force-generating, membrane-binding, and motile properties of these motors. We discovered that there is remarkable diversity among myosin-I isoforms in their ability to alter their ATPase activities in response to mechanical forces, and we are learning how structural features within the motor domain lead to chemomechanical tuning. We have also learned much about the biophysics of the attachment of myosin-I to membrane bilayers in the presence and absence of mechanical load. Our understanding of the biophysical properties of myosin-I isoforms has allowed us to further explore their roles in membrane dynamics via multi-motor in vitro assays that reconstitute membrane motility and tubulation. This work is supported by grants from NIH/NIGMS (GM057247 and GM087253).

Shuttling along DNA and directed processing of D-loops by RecQ helicase support quality control of homologous recombination

Cells must continuously repair inevitable DNA damage while avoiding the deleterious consequences of imprecise repair. Distinction between legitimate and illegitimate repair processes is thought to be achieved in part through differential recognition and processing of specific noncanonical DNA structures, although the mechanistic basis of discrimination remains poorly defined. Here, we show that Escherichia coli RecQ, a central DNA recombination and repair enzyme, exhibits differential processing of DNA substrates based on their geometry and structure. Through single-molecule and ensemble biophysical experiments, we elucidate how the conserved domain architecture of RecQ supports geometry-dependent shuttling and directed processing of recombination-intermediate [displacement loop (D-loop)] substrates. Our study shows that these activities together suppress illegitimate recombination in vivo, whereas unregulated duplex unwinding is detrimental for recombination precision. Based on these results, we propose a mechanism through which RecQ helicases achieve recombination precision and efficiency.

MEMLET: An Easy-to-Use Tool for Data Fitting and Model Comparison Using Maximum-Likelihood Estimation

We present MEMLET (MATLAB-enabled maximum-likelihood estimation tool), a simple-to-use and powerful program for utilizing maximum-likelihood estimation (MLE) for parameter estimation from data produced by single-molecule and other biophysical experiments. The program is written in MATLAB and includes a graphical user interface, making it simple to integrate into the existing workflows of many users without requiring programming knowledge. We give a comparison of MLE and other fitting techniques (e.g., histograms and cumulative frequency distributions), showing how MLE often outperforms other fitting methods. The program includes a variety of features. 1) MEMLET fits probability density functions (PDFs) for many common distributions (exponential, multiexponential, Gaussian, etc.), as well as user-specified PDFs without the need for binning. 2) It can take into account experimental limits on the size of the shortest or longest detectable event (i.e., instrument “dead time”) when fitting to PDFs. The proper modification of the PDFs occurs automatically in the program and greatly increases the accuracy of fitting the rates and relative amplitudes in multicomponent exponential fits. 3) MEMLET offers model testing (i.e., single-exponential versus double-exponential) using the log-likelihood ratio technique, which shows whether additional fitting parameters are statistically justifiable. 4) Global fitting can be used to fit data sets from multiple experiments to a common model. 5) Confidence intervals can be determined via bootstrapping utilizing parallel computation to increase performance. Easy-to-follow tutorials show how these features can be used. This program packages all of these techniques into a simple-to-use and well-documented interface to increase the accessibility of MLE fitting.

Dynamic fluctuations in single-molecule biophysics experiments: Comment on “Extracting physics of life at the molecular level: A review of single-molecule data analyses” by W. Colomb and S.K. Sarkar

Dynamic fluctuations in single-molecule biophysics experiments: Comment on “Extracting physics of life at the molecular level: A review of single-molecule data analyses” by W. Colomb and S.K. Sarkar

Single-molecule inhibition of human kinesin by adociasulfate-13 and -14 from the spongeCladocroce aculeata

Two merotriterpenoid hydroquinone sulfates designated adociasulfate-13 (1) and adociasulfate-14 (2) were purified from Cladocroce aculeata (Chalinidae) along with adociasulfate-8. All three compounds were found to inhibit microtubule-stimulated ATPase activity of kinesin at 15 µM by blocking both the binding of microtubules and the processive motion of kinesin along microtubules. These findings directly show that substitution of the 5'-sulfate in 1 for a glycolic acid moiety in 2 maintains kinesin inhibition. Nomarski imaging and bead diffusion assays in the presence of adociasulfates showed no signs of either free-floating or bead-bound adociasulfate aggregates. Single-molecule biophysical experiments also suggest that inhibition of kinesin activity does not involve adociasulfate aggregation. Furthermore, both mitotic and nonmitotic kinesins are inhibited by adociasulfates to a significantly different extent. We also report evidence that microtubule binding of nonkinesin microtubule binding domains may be affected by adociasulfates.

Back-scatter based whispering gallery mode sensing

Whispering gallery mode biosensors allow selective unlabelled detection of single proteins and, combined with quantum limited sensitivity, the possibility for noninvasive real-time observation of motor molecule motion. However, to date technical noise sources, most particularly low frequency laser noise, have constrained such applications. Here we introduce a new technique for whispering gallery mode sensing based on direct detection of back-scattered light. This experimentally straightforward technique is immune to frequency noise in principle, and further, acts to suppress thermorefractive noise. We demonstrate 27 dB of frequency noise suppression, eliminating frequency noise as a source of sensitivity degradation and allowing an absolute frequency shift sensitivity of 76 kHz. Our results open a new pathway towards single molecule biophysics experiments and ultrasensitive biosensors.

Molecular Traffic Jams on DNA

All aspects of DNA metabolism-including transcription, replication, and repair-involve motor enzymes that move along genomic DNA. These processes must all take place on chromosomes that are occupied by a large number of other proteins. However, very little is known regarding how nucleic acid motor proteins move along the crowded DNA substrates that are likely to exist in physiological settings. This review summarizes recent progress in understanding how DNA-binding motor proteins respond to the presence of other proteins that lie in their paths. We highlight recent single-molecule biophysical experiments aimed at addressing this question, with an emphasis placed on analyzing the single-molecule, ensemble biochemical, and in vivo data from a mechanistic perspective.

Correlation Analysis of Enzymatic Reaction of a Single Protein Molecule.

New advances in nano sciences open the door for scientists to study biological processes on a microscopic molecule-by-molecule basis. Recent single-molecule biophysical experiments on enzyme systems, in particular, reveal that enzyme molecules behave fundamentally differently from what classical model predicts. A stochastic network model was previously proposed to explain the experimental discovery. This paper conducts detailed theoretical and data analyses of the stochastic network model, focusing on the correlation structure of the successive reaction times of a single enzyme molecule. We investigate the correlation of experimental fluorescence intensity and the correlation of enzymatic reaction times, and examine the role of substrate concentration in enzymatic reactions. Our study shows that the stochastic network model is capable of explaining the experimental data in depth.

Two methods of temperature control for single-molecule measurements

Modern single-molecule biophysical experiments require high numerical aperture oil-immersion objectives in close contact with the sample. We introduce two methods of high numerical aperture temperature control which can be implemented on any microscope: objective temperature control using a ring-shaped Peltier device, and stage temperature control using a fluid flow cooling chip in close thermal contact with the sample. We demonstrate the efficacy of each system by showing the change in speed with temperature of two molecular motors, the bacterial flagellar motor and skeletal muscle myosin.

Nonparametric inference of doubly stochastic Poisson process data via the kernel method

Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure.

Deconvolution of dynamic mechanical networks

Time-resolved single-molecule biophysical experiments yield data that contain a wealth of dynamic information, in addition to the equilibrium distributions derived from histograms of the time series. In typical force spectroscopic setups the molecule is connected via linkers to a readout device, forming a mechanically coupled dynamic network. Deconvolution of equilibrium distributions, filtering out the influence of the linkers, is a straightforward and common practice. We have developed an analogous dynamic deconvolution theory for the more challenging task of extracting kinetic properties of individual components in networks of arbitrary complexity and topology. Our method determines the intrinsic linear response functions of a given object in the network, describing the power spectrum of conformational fluctuations. The practicality of our approach is demonstrated for the particular case of a protein linked via DNA handles to two optically trapped beads at constant stretching force, which we mimic through Brownian dynamics simulations. Each well in the protein free energy landscape (corresponding to folded, unfolded, or possibly intermediate states) will have its own characteristic equilibrium fluctuations. The associated linear response function is rich in physical content, because it depends both on the shape of the well and its diffusivity-a measure of the internal friction arising from such processes as the transient breaking and reformation of bonds in the protein structure. Starting from the autocorrelation functions of the equilibrium bead fluctuations measured in this force clamp setup, we show how an experimentalist can accurately extract the state-dependent protein diffusivity using a straightforward two-step procedure.

Versatile Control System for Automated Single-Molecule Optical Tweezers Investigations

AbstractWe present a versatile control system to automate single-molecule biophysics experiments. This method combines low-level controls into various functional, user-configurable modules, which can be scripted in a domain-specific instruction language. The ease with which the high-level parameters can be changed accelerates the development of a durable experiment for the perishable single-molecule samples. Once the experimental parameters are tuned, the control system can be used to repeatedly manipulate other single molecules in the same way, which is necessary to accumulate the statistics needed to report results from single-molecule studies. This system has been implemented for an optical tweezers instrument for single-molecule manipulations, with real-time point-by-point feedback at a loop rate of 10-20 kHz.

Reduced photobleaching of BODIPY-FL

We present a study of the photophysical properties of the BODIPY-FL fluorescent dye at the single molecule scale using total internal reflexion fluorescence microscopy. We characterized the saturation intensity and the maximum number of fluorescence photons for single BODIPY-FL in a usual buffer. We then studied the influence of the buffer depletion in oxygen and the addition of redox agents on the brightness and the lifetime before photobleaching of the BODIPY-FL. The great improvement of these two factors in such a medium allows the use of BODIPY-FL in single-molecule biophysics experiments.

A Novel Experimental Platform for DNA Mechanics Assays

Single-molecule biophysics experiments have been widely employed to characterize the mechanics and dynamics of DNA and the activity of DNA-binding proteins. In typical experiments requiring DNA tethering, a DNA molecule is conjugated to a coverslip and observed with a light microscope parallel to the optical axis, limiting the resolution of optical and magnetic trapping measurements and direct observation of interactions with DNA-binding proteins. Another assay technique, where two beads tethering DNA are optically trapped, orients the DNA perpendicular to the optical axis, but this assay is limited to manipulating one DNA molecule at a time. We developed a device to overcome the limitations of previous assays. A microfabricated cantilever platform exposes the edge of a 50 nm thin gold surface that runs along the length of the sidewalls of patterned microfluidic channels. This narrow gold surface, oriented orthogonal to the optical axis, serves as a substrate for the covalent attachment of an end-thiolated DNA molecule through well established gold-thiol chemistry. The microfabricated cantilever device provides complete optical access to the DNA, and allows a DNA-tethered bead to be optically or magnetically trapped perpendicular to the optical axis, the experimentally preferred orientation. This experimental set-up allows for efficient, parallelized investigation of multiple DNA molecules in a single assay format. As a proof-of-concept demonstration, we have tethered λ-DNA and shorter DNA molecules between the gold edge and polystyrene beads and verify the conjugation by quantifying the Brownian motion of the tethered beads. This experimental platform has the potential for studying the mechanics of DNA and DNA-protein interactions, such as histone binding and RNA polymerase transcription, in conjunction with tethered particle motion, optical and magnetic trapping, and fluorescence imaging techniques all within a single focal plane.

Stochastic Networks in Nanoscale Biophysics

Advances in nanotechnology enable scientists for the first time to study biological processes on a nanoscale molecule-by-molecule basis. A surprising discovery from recent nanoscale single-molecule biophysics experiments is that biological reactions involving enzymes behave fundamentally differently from what classical theory predicts. In this article we introduce a stochastic network model to explain the experimental puzzles (by modeling enzymatic reactions as a stochastic network connected by different enzyme conformations). Detailed analyses of the model, including analyses of the first-passage-time distributions and goodness of fit, show that the stochastic network model is capable of explaining the experimental surprises. The model is analytically tractable and closely fits experimental data. The biological/chemical meaning of the model is discussed.

Stochastic modeling in nanoscale biophysics: Subdiffusion within proteins

Advances in nanotechnology have allowed scientists to study biological processes on an unprecedented nanoscale molecule-by-molecule basis, opening the door to addressing many important biological problems. A phenomenon observed in recent nanoscale single-molecule biophysics experiments is subdiffusion, which largely departs from the classical Brownian diffusion theory. In this paper, by incorporating fractional Gaussian noise into the generalized Langevin equation, we formulate a model to describe subdiffusion. We conduct a detailed analysis of the model, including (i) a spectral analysis of the stochastic integro-differential equations introduced in the model and (ii) a microscopic derivation of the model from a system of interacting particles. In addition to its analytical tractability and clear physical underpinning, the model is capable of explaining data collected in fluorescence studies on single protein molecules. Excellent agreement between the model prediction and the single-molecule experimental data is seen.

Extending the absorbing boundary method to fit dwell-time distributions of molecular motors with complex kinetic pathways

Dwell-time distributions, waiting-time distributions, and distributions of pause durations are widely reported for molecular motors based on single-molecule biophysical experiments. These distributions provide important information concerning the functional mechanisms of enzymes and their underlying kinetic and mechanical processes. We have extended the absorbing boundary method to simulate dwell-time distributions of complex kinetic schemes, which include cyclic, branching, and reverse transitions typically observed in molecular motors. This extended absorbing boundary method allows global fitting of dwell-time distributions for enzymes subject to different experimental conditions. We applied the extended absorbing boundary method to experimental dwell-time distributions of single-headed myosin V, and were able to use a single kinetic scheme to fit dwell-time distributions observed under different ligand concentrations and different directions of optical trap forces. The ability to use a single kinetic scheme to fit dwell-time distributions arising from a variety of experimental conditions is important for identifying a mechanochemical model of a molecular motor. This efficient method can be used to study dwell-time distributions for a broad class of molecular motors, including kinesin, RNA polymerase, helicase, F(1) ATPase, and to examine conformational dynamics of other enzymes such as ion channels.