We have observed reversible light-induced mechanical switching for individual organic molecules bound to a metal surface. Scanning tunneling microscopy (STM) was used to image the features of individual azobenzene molecules on Au(111) before and after reversibly cycling their mechanical structure between trans and cis states using light. Azobenzene molecules were engineered to increase their surface photomechanical activity by attaching varying numbers of tert-butyl (TB) ligands ("legs") to the azobenzene phenyl rings. STM images show that increasing the number of TB legs "lifts" the azobenzene molecules from the substrate, thereby increasing molecular photomechanical activity by decreasing molecule-surface coupling.

The relationship between protein three-dimensional structure and function is essential in determining mechanism. Unfortunately, most techniques do not provide a direct measurement of this relationship. Structural data are usually limited to static pictures and function must be inferred. Conversely, functional assays usually provide little information on structural conformation. We developed a single-molecule technique combining optical tweezers and fluorescence microscopy that allows for both measurements simultaneously. Here, we present measurements of UvrD, a DNA repair helicase, that directly and unambiguously reveal the connection between its structure and function. Our data reveal that UvrD exhibits two distinct types of unwinding activity regulated by its stoichiometry. Furthermore, two UvrD conformational states, termed ‘closed’ and ‘open’, correlate with movement toward or away from the DNA fork.

We present a single-molecule instrument that combines a timeshared ultra-high resolution dual optical trap interlaced with a confocal fluorescence microscope. In a demonstration experiment, individual single-fluorophore labeled DNA oligonucleotides were observed to bind and unbind to complementary DNA suspended between two trapped beads. Simultaneous with the single-fluorophore detection, coincident angstrom-scale changes in tether extension could be clearly observed. Fluorescence readout allowed us to determine the duplex melting rate as a function of force. The new instrument will enable the simultaneous measurement of angstrom-scale mechanical motion of individual DNA-binding proteins (e.g., single base pair stepping of DNA translocases) along with the detection of fluorescently labeled protein properties (e.g., internal configuration).

A method to determine the absolute orientation of molecules at liquid interfaces by sum frequency generation (SFG) is reported. It is based on measurements of the orientations of two nonparallel vibrationally active chromophores in the molecule of interest combined with a rotation matrix formulation to obtain the absolute molecular orientation. We chose m-tolunitrile, a planar molecule adsorbed to the air/water interface, as a proof-of-method experiment. Quantitative analysis of different polarization sum frequency intensities facilitate unique peak assignments of the methyl and nitrile groups of m-tolunitrile. The SFG analysis of the measurement yields a nitrile group tilting at 53°to the surface normal, and the C 3 axis of the methyl group is almost upright at 23°with respect to the surface normal. Using a rotation matrix formulation, we found that the angle between the surface plane and the m-tolunitrile molecular plane is 70°.

We have used single-molecule-resolved scanning tunneling microscopy to measure the photomechanical switching rates of azobenzene-derived molecules at a gold surface during exposure to UV and visible light. This enables the direct determination of both the forward and reverse photoswitching cross sections for surface-mounted molecules at different wavelengths. In a dramatic departure from molecular behavior in solution-based environments, visible light does not efficiently reverse the reaction for azobenzene-derived molecules at a gold surface.

Bayesian nonparametrics (BNPs) are poised to have a deep impact in the analysis of single molecule data as they provide posterior probabilities over entire models consistent with the supplied data, not just model parameters of one preferred model. Thus they provide an elegant and rigorous solution to the difficult problem encountered when selecting an appropriate candidate model. Nevertheless, BNPs' flexibility to learn models and their associated parameters from experimental data is a double-edged sword. Most importantly, BNPs are prone to increasing the complexity of the estimated models due to artifactual features present in time traces. Thus, because of experimental challenges unique to single molecule methods, naive application of available BNP tools is not possible. Here we consider traces with time correlations and, as a specific example, we deal with force spectroscopy traces collected at high acquisition rates. While high acquisition rates are required in order to capture dwells in short-lived molecular states, in this setup, a slow response of the optical trap instrumentation (i.e., trapped beads, ambient fluid, and tethering handles) distorts the molecular signals introducing time correlations into the data that may be misinterpreted as true states by naive BNPs. Our adaptation of BNP tools explicitly takes into consideration these response dynamics, in addition to drift and noise, and makes unsupervised time series analysis of correlated single molecule force spectroscopy measurements possible, even at acquisition rates similar to or below the trap's response times.

We demonstrate a new approach to laser control using binary phase shaping. We apply this method to the problem of spectrally narrowing multiphoton excitation using shaped laser pulses as required for selectivity in two-photon microscopy. The symmetry of the problem is analyzed from first principles and a rational solution is proposed. Successful experimental implementation and simulations are presented using 10 fs ultrashort pulses. The proposed solution is a factor of 6 better than the sinusoidal phase used previously by our group. An evolutionary learning algorithm was used to efficiently improve the solution by a further factor of 2.5 because of the greatly reduced search space afforded by binary phase shaping.

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