Co-reporter:Xun Sun, Thomas E. Morrell, and Haw Yang
The Journal of Physical Chemistry B 2016 Volume 120(Issue 40) pp:10469-10482
Publication Date(Web):September 19, 2016
DOI:10.1021/acs.jpcb.6b07767
Protein conformational changes are known to play important roles in assorted biochemical and biological processes. Driven by thermal motions of surrounding solvent molecules, such a structural remodeling often occurs stochastically. Yet, regardless of how random the conformational reconfiguration may appear, it could in principle be described by a linear combination of a set of orthogonal modes which, in turn, are contained in the intramolecular distance distributions. The central challenge is how to obtain the distribution. This contribution proposes a Bayesian data-augmentation scheme to extract the predominant modes from only few distance distributions, be they from computational sampling or directly from experiments such as single-molecule Förster-type resonance energy transfer (smFRET). The inference of the complete protein structure from insufficient data was recognized as isomorphic to the missing-data problem in Bayesian statistical learning. Using smFRET data as an example, the missing coordinates were deduced, given protein structural constraints and multiple but limited number of smFRET distances; the Boltzmann weighing of each inferred protein structure was then evaluated using computational modeling to numerically construct the posterior density for the global protein conformation. The conformational modes were then determined from the iteratively converged overall conformational distribution using principal component analysis. Two examples were presented to illustrate these basic ideas as well as their practical implementation. The scheme described herein was based on the theory behind the powerful Tanner–Wang algorithm that guarantees convergence to the true posterior density. However, instead of assuming a mathematical model to calculate the likelihood as in conventional statistical inference, here the protein structure was treated as a statistical parameter and was imputed from the numerical likelihood function based on structural information, a probability model-free method. The framework put forth here is anticipated to be generally applicable, offering a new way to articulate protein conformational changes in a quantifiable manner.
Co-reporter:Kevin Welsher; Simon A. McManus; Chih-Hao Hsia; Shuhui Yin
Journal of the American Chemical Society 2015 Volume 137(Issue 2) pp:580-583
Publication Date(Web):January 5, 2015
DOI:10.1021/ja511297d
The seemingly inevitable protein corona appears to be an insurmountable obstacle to wider application of functional nanomaterials in biotechnology. The accumulation of serum proteins can block targeting functionalities and alter the in vivo fate of these nanomaterials. Here we demonstrate a method to generate non-stick, robustly passivated functional nanoparticles (NPs) using a tailored silica coating. We apply agarose gel electrophoresis to sensitively evaluate protein binding to NPs with different surface chemistry. Using gel banding and retardation as a read-out for protein adsorption, we optimize the surface chemistry to yield a mixed charge surface which displays remarkable binding resistance to a wide range of serum proteins and nucleic acids. The hard silica shell also protects the functional NP core in harsh environments (down to pH 1) while still showing the ability to be targeted for cellular uptake with little or no non-specific binding.
Co-reporter:Nyssa T. Emerson, Chih-Hao Hsia, Ilona U. Rafalska-Metcalf and Haw Yang
Nanoscale 2014 vol. 6(Issue 9) pp:4538-4543
Publication Date(Web):21 Feb 2014
DOI:10.1039/C3NR06468A
Nanotechnology has opened up the opportunity to probe, sense, and manipulate the chemical environment of biological systems with an unprecedented level of spatiotemporal control. A major obstacle to the full realization of these novel technologies is the lack of a general, robust, and simple method for the delivery of arbitrary nanostructures to the cytoplasm of intact live cells. Here, we identify a new delivery modality, based on mechanical disruption of the plasma membrane, which efficiently mediates the delivery of nanoparticles to the cytoplasm of mammalian cells. We use two distinct execution modes, two adherent cell lines, and three sizes of semiconducting nanocrystals, or quantum dots, to demonstrate its applicability and effectiveness. As the underlying mechanism is purely physical, we anticipate that such “mechanodelivery” can be generalized to other modes of execution as well as to the cytoplasmic introduction of a structurally diverse array of functional nanomaterials.
Co-reporter:Xun Sun, Daniel Montiel, Hao Li, and Haw Yang
Bioconjugate Chemistry 2014 Volume 25(Issue 8) pp:1375
Publication Date(Web):July 31, 2014
DOI:10.1021/bc500296p
The streptavidin–biotin set is one of the most widely utilized conjugation pairs in biotechnological applications. The tetravalent nature of streptavidin and its homologues, however, tends to result in such undesirable complications as cross-linking or ill-defined stoichiometry. Here, we describe a mutagenesis-free strategy to manipulate the valencies of wild-type streptavidin that only requires commercially available reagents. The basic idea is simple: one obtains the desired streptavidin valency by blocking off unwanted binding sites using ancillary biotin (“plug”); this way, the extraordinary fM-biotin-binding affinity is fully retained for the remaining sites in streptavidin. In the present implementation, the ancillary biotin is attached to an auxiliary separation handle, negatively charged DNA or His-tagged protein, via a photochemically or enzymatically cleavable linker. Mixing streptavidin with the ancillary biotin construct produces a distribution of streptavidin valencies. The subsequent chromatographic separation readily isolates the construct of desired streptavidin valency, and the auxiliary handles are easily removed afterward (“go”). We demonstrate how this “plug-and-go” strategy allows a precise control for the compositions of streptavidin–biotin conjugates at the single-molecule level. This low-entry-barrier protocol could further expand the application scope of the streptavidin technology.
Co-reporter:Xun Sun, Hao Li, Jonas Alfermann, Henning D. Mootz, and Haw Yang
Biochemistry 2014 Volume 53(Issue 50) pp:
Publication Date(Web):December 1, 2014
DOI:10.1021/bi501156m
Nonribosomal peptide synthetases (NRPS) incorporate assorted amino acid substrates into complex natural products. The substrate is activated via the formation of a reactive aminoacyl adenylate and is subsequently attached to the protein template via a thioester bond. The reactive nature of such intermediates, however, leads to side reactions that also break down the high-energy anhydride bond. The off-pathway kinetics or their relative weights compared to that of the on-pathway counterpart remains generally elusive. Here, we introduce multiplatform kinetics profiling to quantify the relative weights of on- and off-pathway reactions. Using the well-defined stoichiometry of thioester formation, we integrate a mass spectrometry (MS) kinetics assay, a high-performance liquid chromatography (HPLC) assay, and an ATP–pyrophosphate (PPi) exchange assay to map out a highly efficient on-pathway kinetics profile of the substrate activation and intermediate uploading (>98% relative weight) for wide-type gramicidin S synthetase A (GrsA) and a 87% rate profile for a cysteine-free GrsA mutant. Our kinetics profiling approach complements the existing enzyme-coupled byproduct-release assays, unraveling new mechanistic insights of substrate activation/channeling in NRPS enzymes.
Co-reporter:Kevin R. Haas, Haw Yang, and Jhih-Wei Chu
The Journal of Physical Chemistry B 2014 Volume 118(Issue 28) pp:8099-8107
Publication Date(Web):April 29, 2014
DOI:10.1021/jp501133w
The analytical expression for the trajectory entropy of the overdamped Langevin equation is derived via two approaches. The first route goes through the Fokker–Planck equation that governs the propagation of the conditional probability density, while the second method goes through the path integral of the Onsager–Machlup action. The agreement of these two approaches in the continuum limit underscores the equivalence between the partial differential equation and the path integral formulations for stochastic processes in the context of trajectory entropy. The values obtained using the analytical expression are also compared with those calculated with numerical solutions for arbitrary time resolutions of the trajectory. Quantitative agreement is clearly observed consistently across different models as the time interval between snapshots in the trajectories decreases. Furthermore, analysis of different scenarios illustrates how the deterministic and stochastic forces in the Langevin equation contribute to the variation in dynamics measured by the trajectory entropy.
Co-reporter:Kevin R. Haas, Haw Yang, and Jhih-Wei Chu
The Journal of Physical Chemistry Letters 2014 Volume 5(Issue 6) pp:999-1003
Publication Date(Web):March 3, 2014
DOI:10.1021/jz500111p
We propose to quantify the trajectory entropy of a dynamic system as the information content in excess of a free-diffusion reference model. The space–time trajectory is now the dynamic variable, and its path probability is given by the Onsager–Machlup action. For the time propagation of the overdamped Langevin equation, we solved the action path integral in the continuum limit and arrived at an exact analytical expression that emerged as a simple functional of the deterministic mean force and the stochastic diffusion. This work may have direct implications in chemical and phase equilibria, bond isomerization, and conformational changes in biological macromolecules as well transport problems in general.Keywords: overdamped Langevin dynamics; trajectory entropy; trajectory path integral;
Co-reporter:Bian Qian, Daniel Montiel, Andreas Bregulla, Frank Cichos and Haw Yang
Chemical Science 2013 vol. 4(Issue 4) pp:1420-1429
Publication Date(Web):10 Jan 2013
DOI:10.1039/C2SC21263C
A simple scheme is presented for remotely maneuvering individual microscopic swimmers by means of on-demand photo-induced actuation, where a laser gently and intermittently pushed the swimmer along its body axis (photon nudging) through a combination of radiation-pressure force and photophoretic pull. The proposed strategy utilized rotational random walks to reorient the micro-swimmer and turned on its propulsion only when the swimmer was aligned with the target location (adaptive control). A Langevin-type equation of motion was formulated, integrating these two ideas to describe the dynamics of the stochastically controlled swimmer. The strategy was examined using computer simulations and illustrated in a proof-of-principle experiment steering a gold-coated Janus micro-sphere moving in three dimensions. The physical parameters relevant to the two actuating forces under the experimental conditions were investigated theoretically and experimentally, revealing that a ∼7 K temperature differential on the micro-swimmer surface could generate a propelling photophoretic strength of ∼0.1 pN. The controllability and positioning error were discussed using both experimental data and Langevin dynamics simulations, where the latter was further used to identify two key unitless control parameters for manipulation accuracy and efficiency; they were the number of random-walk turns the swimmer experienced on the experimental timescale (the revolution number) and the photon-nudge distance within the rotational diffusion time (the propulsion number). A comparison of simulation and experiment indicated that a near-optimal micron-precision motion control was achieved.
Co-reporter:Kevin R. Haas, Haw Yang, and Jhih-Wei Chu
The Journal of Physical Chemistry B 2013 Volume 117(Issue 49) pp:15591-15605
Publication Date(Web):August 12, 2013
DOI:10.1021/jp405983d
The dynamics of a protein along a well-defined coordinate can be formally projected onto the form of an overdamped Lagevin equation. Here, we present a comprehensive statistical-learning framework for simultaneously quantifying the deterministic force (the potential of mean force, PMF) and the stochastic force (characterized by the diffusion coefficient, D) from single-molecule Förster-type resonance energy transfer (smFRET) experiments. The likelihood functional of the Langevin parameters, PMF and D, is expressed by a path integral of the latent smFRET distance that follows Langevin dynamics and realized by the donor and the acceptor photon emissions. The solution is made possible by an eigen decomposition of the time-symmetrized form of the corresponding Fokker–Planck equation coupled with photon statistics. To extract the Langevin parameters from photon arrival time data, we advance the expectation-maximization algorithm in statistical learning, originally developed for and mostly used in discrete-state systems, to a general form in the continuous space that allows for a variational calculus on the continuous PMF function. We also introduce the regularization of the solution space in this Bayesian inference based on a maximum trajectory-entropy principle. We use a highly nontrivial example with realistically simulated smFRET data to illustrate the application of this new method.
Co-reporter:Jeffrey A. Hanson, Jason Brokaw, Carl C. Hayden, Jhih-Wei Chu, Haw Yang
Chemical Physics 2012 Volume 396() pp:61-71
Publication Date(Web):2 March 2012
DOI:10.1016/j.chemphys.2011.06.014
Abstract
A mechanical view provides an attractive alternative for predicting the behavior of complex systems since it circumvents the resource-intensive requirements of atomistic models; however, it remains extremely challenging to characterize the mechanical responses of a system at the molecular level. Here, the structural distribution is proposed to be an effective means to extracting the molecular mechanical properties. End-to-end distance distributions for a series of short poly-l-proline peptides with the sequence PnCG3K-biotin (n = 8, 12, 15 and 24) were used to experimentally illustrate this new approach. High-resolution single-molecule Förster-type resonance energy transfer (FRET) experiments were carried out and the conformation-resolving power was characterized and discussed in the context of the conventional constant-time binning procedure for FRET data analysis. It was shown that the commonly adopted theoretical polymer models—including the worm-like chain, the freely jointed chain, and the self-avoiding chain—could not be distinguished by the averaged end-to-end distances, but could be ruled out using the molecular details gained by conformational distribution analysis because similar polymers of different sizes could respond to external forces differently. Specifically, by fitting the molecular conformational distribution to a semi-flexible polymer model, the effective persistence lengths for the series of short poly-l-proline peptides were found to be size-dependent with values of ∼190 Å, ∼67 Å, ∼51 Å, and ∼76 Å for n = 8, 12, 15, and 24, respectively. A comprehensive computational modeling was carried out to gain further insights for this surprising discovery. It was found that P8 exists as the extended all-trans isomaer whereas P12 and P15 predominantly contained one proline residue in the cis conformation. P24 exists as a mixture of one-cis (75%) and two-cis (25%) isomers where each isomer contributes to an experimentally resolvable conformational mode. This work demonstrates the resolving power of the distribution-based approach, and the capacity of integrating high-resolution single-molecule FRET experiments with molecular modeling to reveal detailed structural information about the conformation of molecules on the length scales relevant to the study of biological molecules.
Co-reporter:Yan-Wen Tan and Haw Yang
Physical Chemistry Chemical Physics 2011 vol. 13(Issue 5) pp:1709-1721
Publication Date(Web):23 Dec 2010
DOI:10.1039/C0CP02412K
Enzymes are remarkable molecular machines that make many difficult biochemical reactions possible under mild biological conditions with incredible precision and efficiency. Our understanding of the working principles of enzymes, however, has not reached the level where one can readily deduce the mechanism and the catalytic rates from an enzyme's structure. Resolving the dynamics that relate the three-dimensional structure of an enzyme to its function has been identified as a key issue. While still challenging to implement, single-molecule techniques have emerged as one of the most useful methods for studying enzymes. We review enzymes studied using single-molecule fluorescent methods but placing them in the context of results from other complementary experimental work done on bulk samples. This review primarily covers three enzyme systems—flavoenzymes, dehydrofolate reductase, and adenylate kinase—with additional enzymes mentioned where appropriate. When the single-molecule experiments are discussed together with other methods aiming at the same scientific question, the weakness, strength, and unique contributions become clear.
Co-reporter:Jui-Ming Yang, Haw Yang, and Liwei Lin
ACS Nano 2011 Volume 5(Issue 6) pp:5067
Publication Date(Web):May 16, 2011
DOI:10.1021/nn201142f
The local temperature response inside single living cells upon external chemical and physical stimuli was characterized using quantum dots as nano thermometers. The photoluminescence spectral shifts from endocytosed quantum dots were used to map intracellular heat generation in NIH/3T3 cells following Ca2+ stress and cold shock. The direct observation of inhomogeneous intracellular temperature progression raises interesting new possibilities, including further innovations in nanomaterials for sensing local responses, as well as the concept of subcellular temperature gradient for signaling and regulation in cells.Keywords: intracellular temperature; nanobio; single-cell analysis; spectral imaging; thermal signaling
Co-reporter:Chih-Hao Hsia, Anna Wuttig, and Haw Yang
ACS Nano 2011 Volume 5(Issue 12) pp:9511
Publication Date(Web):October 28, 2011
DOI:10.1021/nn2025622
A new synthetic scheme allowing structural modifications to temperature-sensitive and water-soluble d-penicillamine-passivated Mn2+-doped (CdSSe)ZnS (core)shell nanocrystals (MnQDs) was reported using air-stable chemicals. The temperature-dependent optical properties of the nanocrystals were tuned by changing their structure and composition—the ZnS shell thickness and the Mn2+-dopant concentration. Thick ZnS shells significantly reduce the interference of nonradiative transitions on ratiometric emission intensities. High-dopant concentration affords consistent temperature sensitivity. In addition to the new base structure for quantum dot ratiometric temperature sensing via flexible, glovebox-free routes, the results also underscore the generalizability of the emission intensity ratio scheme for temperature sensing, originally proposed for rare-earth-doped materials.Keywords: air stable; green chemistry; nanothermometer; quantum dot; temperature-dependent lifetime
Co-reporter:E. Megan Flynn ; Jeffrey A. Hanson ; Tom Alber
Journal of the American Chemical Society 2010 Volume 132(Issue 13) pp:4772-4780
Publication Date(Web):March 15, 2010
DOI:10.1021/ja909968n
The Mycobacterium tuberculosis protein tyrosine phosphatase PtpB shows resistance to the oxidative conditions that prevail within an infected host macrophage, but the mechanism of this molecular adaptation is unknown. Crystal structures of PtpB revealed previously that a closed, two-helix lid covers the active site. By measuring single-molecule Förster-type resonance energy transfer to probe the dynamics of two helices that constitute the lid, we obtained direct evidence for large, spontaneous opening transitions of PtpB with the closed form of both helices favored ∼3:1. Despite similar populations of conformers, the two helices move asynchronously as demonstrated by different opening and closing rates under our experimental conditions. Assuming that lid closure excludes oxidant, the rates of opening and closing quantitatively accounted for the slow observed rate of oxidative inactivation. Increasing solvent viscosity using glycerol but not PEG8000 resulted in higher rates of oxidative inactivation due to an increase in the population of open conformers. These results establish that the rapid conformational gating of the PtpB lid constitutes a reversible physical blockade that transiently masks the active site and retards oxidative inactivation.
Co-reporter:Yan-Wen Tan and Haw Yang
Physical Chemistry Chemical Physics 2011 - vol. 13(Issue 5) pp:NaN1721-1721
Publication Date(Web):2010/12/23
DOI:10.1039/C0CP02412K
Enzymes are remarkable molecular machines that make many difficult biochemical reactions possible under mild biological conditions with incredible precision and efficiency. Our understanding of the working principles of enzymes, however, has not reached the level where one can readily deduce the mechanism and the catalytic rates from an enzyme's structure. Resolving the dynamics that relate the three-dimensional structure of an enzyme to its function has been identified as a key issue. While still challenging to implement, single-molecule techniques have emerged as one of the most useful methods for studying enzymes. We review enzymes studied using single-molecule fluorescent methods but placing them in the context of results from other complementary experimental work done on bulk samples. This review primarily covers three enzyme systems—flavoenzymes, dehydrofolate reductase, and adenylate kinase—with additional enzymes mentioned where appropriate. When the single-molecule experiments are discussed together with other methods aiming at the same scientific question, the weakness, strength, and unique contributions become clear.
Co-reporter:Bian Qian, Daniel Montiel, Andreas Bregulla, Frank Cichos and Haw Yang
Chemical Science (2010-Present) 2013 - vol. 4(Issue 4) pp:NaN1429-1429
Publication Date(Web):2013/01/10
DOI:10.1039/C2SC21263C
A simple scheme is presented for remotely maneuvering individual microscopic swimmers by means of on-demand photo-induced actuation, where a laser gently and intermittently pushed the swimmer along its body axis (photon nudging) through a combination of radiation-pressure force and photophoretic pull. The proposed strategy utilized rotational random walks to reorient the micro-swimmer and turned on its propulsion only when the swimmer was aligned with the target location (adaptive control). A Langevin-type equation of motion was formulated, integrating these two ideas to describe the dynamics of the stochastically controlled swimmer. The strategy was examined using computer simulations and illustrated in a proof-of-principle experiment steering a gold-coated Janus micro-sphere moving in three dimensions. The physical parameters relevant to the two actuating forces under the experimental conditions were investigated theoretically and experimentally, revealing that a ∼7 K temperature differential on the micro-swimmer surface could generate a propelling photophoretic strength of ∼0.1 pN. The controllability and positioning error were discussed using both experimental data and Langevin dynamics simulations, where the latter was further used to identify two key unitless control parameters for manipulation accuracy and efficiency; they were the number of random-walk turns the swimmer experienced on the experimental timescale (the revolution number) and the photon-nudge distance within the rotational diffusion time (the propulsion number). A comparison of simulation and experiment indicated that a near-optimal micron-precision motion control was achieved.
