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Research

Areas of Focus

Protein Conformational Dynamics Background

Once the protein has obtained its proper three-dimensional structure it may undergo further structural changes that are associated with its function.  Many enzymes and ligand-binding proteins must undergo large conformational changes during their function.

Single molecule protein/peptide conformational dynamics

We are interested in understanding the mechanisms of protein...

Information theory and hidden Markov models

We are using information theory and hidden Markov models...

Amyloid aggregation mechanisms

The study of amyloid structure and growth has been...

Single molecule Methods development

We are developing new approaches to single molecule measurements...

Highlights of Recent Research

HMM Analysis

The measurement of fluorescence from single protein molecules has become an important new tool in the study of dynamic processes, allowing for the direct visualization of the motions experienced by individual proteins and macromolecular complexes. The data from such single-molecule experiments are in the form of photon trajectories, consisting of arrival times and wavelength information on individual photons. The analysis of photon trajectories can be difficult, particularly if the motions are occurring at rates comparable to the photon arrival rate. In Andrec \emph{et al.} (2003) we introduced the use of HMMs for the analysis of photon trajectory data that operate using the photon data directly, without the need for ensemble averaging of the data as implied by correlation function analysis.

Preprint - Markov processes in single molecule fluorescence

Protein Free Energy Landscapes Remodeled by Ligand Binding

Glucose/galactose binding protein (GGBP) functions in two different larger systems of proteins used by enteric bacteria for molecular recognition and signaling. Here we report on the thermodynamics of conformational equilibrium distributions of GGBP. Three fluorescence components appear at zero glucose concentration and systematically transition to three compo- nents at high glucose concentration. Fluorescence anisotropy correlations, fluorescent lifetimes, thermodynamics, computational structure minimization, and literature work were used to assign the three components as open, closed, and twisted conformations of the protein. The existence of three states at all glucose concentrations indicates that the protein continuously fluctuates about its conformational state space via thermally driven state transitions; glucose biases the populations by reorganizing the free energy profile. These results and their implications are discussed in terms of the two types of specific and nonspecific interactions GGBP has with cytoplasmic membrane proteins.

β-Lactoglobulin Calyx Dynamics

β-Lactoglobulin Calyx Dynamics
The formation of a hydrophobic core provides a large part of the driving force for protein folding.
We are investigating amyloid formation from β-lactoglobulin and are therefore interested in understanding how the dynamics of core stability are influenced by solution conditions.
We have exploited the presence of a large hydrophobic binding pocket in β-lactoglobulin to encapsulate coumarin 153 (C153).
Steady state spectroscopy reveals a very blue-shifted spectrum consistent with an environment similar to a combination of hexane and toluene.
Time resolved fluorescence Stokes shift measurements reflect the dynamics of the hydrophobic core of β-lactoglobulin.
A transition in the dynamics of the hydrophobic core occurs at a lower temperature than does the melting of the protein as measured by circular dichroism suggesting a partitioning of  the enthalpy and entropy balance between the core structure and secondary structure.

Solid-state nanopore measurements of amyloid formation

In collaboration with the group of Jiali Li at the University of Arkansas Department of Physics we have begun making solid state nanopore electrical measurements on the aggregates that form during assembly of amyloid from ß-lactoglobulin. Our preliminary assessment of the data suggests that the solid state nanopore can distinguish between different classes of amyloid species.

HMM for Langevin dynamics

(a) Potential of mean force used to describe the protein dynamics dictate by the FRET pair (donor and acceptor) distance attached to a protein.
(b) Probability distribution function in (a).
(c) Simulated photon trajectories recorded by donor (red) and acceptor (blue) channels. Microtime (the time lag between the laser pulse and the arrival of the photon) for each photon recorded in donor channel (d) and acceptor channel (e).
(f) Reconstructed donor-acceptor distance trajectory using hidden Markov model (HMM) with evenly spaced 21 states across the donor-acceptor distance.
(g) “True” donor-acceptor distance trajectory, generated by Langevin dynamics simulation on (a), used to simulate the photon trajectory in (c).

Hidden Markov Model Analysis of Multichromophore Photobleaching

The interpretation of single-molecule measurements is greatly complicated by the presence of multiple fluorescent labels. However, many molecular systems of interest consist of multiple interacting components. We address this issue using multiply-labeled dextran polymers that we intentionally photobleach to the background on a single molecule basis. Hidden Markov models allow unsupervised analysis of the data to determine the number of fluorescent subunits involved in the fluorescence intermittency of the 6-carboxy-tetramethylrhodamine labels by counting the discrete steps in fluorescence intensity. The Bayes information criterion allows us to distinguish between hidden Markov models that differ by number of states, i.e., number of fluorescent molecules. We determine information-theoretical limits and show via Monte Carlo simulations that the hidden Markov model analysis approaches these theoretical limits. This technique has resolving power of one fluorescing unit up to as many as 30 fluorescent dyes with the appropriate choice of dye and adequate detection capability. We discuss the general utility of this method for determining aggregation-state distributions as could appear in many biologically important systems and its adaptability to general photometric experiments.

Information theoretical approach to single molecule experimental design and interpretation

We use Shannon’s definition of information to develop a theory to predict the ability of a photon-counting-based single molecule experiment to result in the measurement of a desired property. We treat several phenomena that are commonly measured on single molecules. We treat spectral fluctuations of a solvatochromic dye. We treat assignment of the azimuthal dipole angle. We treat determination of a distance by fluorescence resonant energy transfer using Förster’s theory. We consider the effect of background and other “imperfections” on the measurement through the decrease in information. We have implemented the information theoretical results in cross-platform commercial analysis programs and have made them available for download at http://www.singlemolecule.net.

Beta-lactoglobulin aggregation visualized by AFM

This is an image of ß-Amyloid fibrils derived from ß-lactoglobulin taken using tapping-mode AFM in air on a piece of mica that has been chemically modified to bind our sample. Note the great diversity of size, shape, and height of the species present. Many different types of aggregates are visible in this image including filaments, fibrils, and small aggregates of various sizes.

Hidden Markov Models for Diffusive Processes

The top panel (a) shows a Monte Carlo simulated trajectory of a molecule diffusing through a spherically symmetric Gaussian collection volume. The next panel (b) shows the reciprocal of the inter-photon time. The delay between excitation and emission of the photon is the lifetime and is shown in panel (c). Panels (b) and (c) are used with three dimensional diffusion of the molecule through the focus of the instrument as the hidden Markov model to reconstruct the Brownian motion trajectory in panel (d). The trajectory was reconstructed by using Monte Carlo sampling of the HMM parameters to maximize the likelihood of the data in (b) and (c).

Production of a microfluidic mixer in PDMS

This multi-channel sorting mixer was produced from a negative mold of photoresist on silicon. The mold creates an embedded design in PDMS. Subsequent bonding of the PDMS to a glass slide makes a liquid-tight seal. These fluidic devices are being used to confine bio-molecules to an observable volume by confocal microscopy so that we may watch the bio-molecules as they perform their function in real time.

Overview of amyloid assembly mechanisms

Amyloid – any fibril, plaque, seed, or aggregate that has the characteristic cross-ß sheet structure.
Amyloidogenic precursor – a protein or peptide that upon incubation under appropriate conditions will form amyloid fibrils or plaques.
Amyloid fibril – long ribbons of amyloid ~10nm in diameter and >100nm in length. Most often observed in vitro.
Amyloid plaque – the form of amyloid most often found in vivo – often comprised of aggregated amyloid fibrils.
Amyloid protofibril/filament – a species of amyloid smaller in diameter (3-6nm) and length(<100nm) than typical for amyloid fibrils, thought to be a possible direct precursor to amyloid fibrils perhaps through lateral aggregation.
Amyloid seed (or template) – a species of a critical size or structure that rapidly elongates to form larger amyloid species possibly by providing a proper scaffold for amyloid assembly
Amyloidogenic oligomer – A small aggregate of precursor that is smaller than the critical “seed” size but still may have some of the structural characteristics of amyloid.
Amyloidogenic fold – a structure of the precursor that must be accessed prior to amyloidogenic aggregation, thought to retain substantial secondary structure possibly including some of the native fold. It could be related to a misfolded or molten globule structure.
Folded state – The native (functional) state of the precursor.
Folding intermediate – A partially folded or misfolded structure of the precursor. These partially folded structures are potentially the same as or precursors to amyloidogenic folds.
Denatured state – The unfolded state of the precursor.
Unstructured aggregate – Completely or partially denatured proteins tend to aggregate non-specifically without forming a particular structural motif

Amyloid Assembly Background

Medical Relevance
Aggregation of soluble polypeptides or proteins into insoluble amyloid fibrils with cross-ß structural motif has been observed in the progression of a great variety of diseases. Over 20 diseases1 have been linked to excessive deposits of amyloid fibrils or plaques derived from different precursor proteins. Amyloidogenic diseases include Alzheimer’s disease, Parkinson’s disease, type II diabetes, and spongiform encephalopathies. The human health impact of these diseases has motivated intensive study and numerous reviews of the structure and growth of amyloid fibrils.1-19
A mechanistic understanding of the amyloid-assembly process will provide new handles and probes for the physiological interactions that cause amyloidosis. This will allow better approaches to the prevention of amyloid formation and new diagnostics for early detection of amyloid-related diseases. A popular hypothesis is that blocking and/or reversing amyloid formation will be an effective treatment for diseases involving organ failure due to amyloidosis. To adequately test this hypothesis, rational strategies must be based on interrupting or reversing amyloid aggregation at various points in amyloid assembly. This requires detailed knowledge of the mechanisms of amyloid growth and the factors that influence the (dis)aggregation rates at all stages of amyloid assembly.20
Of particular interest is the participation of the difficult-to-detect-and-quantify species present during the lag phase of amyloid assembly. Recent evidence has shifted some of the focus from amyloid fibrils to these prefibrillar amyloidogenic aggregates as the cause of Alzheimer’s disease symptoms.2 Development of vaccines targeting small amyloidogenic aggregates 6,7,12,13,21 would benefit from understanding how the concentrations of amyloidogenic species will be influenced by the induced immunological response to and clearing of particular amyloid species. A species that is too small to seed further amyloid assembly could, in principle, be “deactivated” if it is known what structural part of these species is required for further aggregation to the critical size for nucleation of amyloid fibrils. This structural part could be tested as a chimeric vaccine to induce immunological clearing of that particular amyoidogenic species with a lower likelihood of inducing further amyloid plaque deposition from the introduction of an actual amyloidogenic species.

Structural Features of Amyloid
Amyloid deposits derived from diverse precursors share many structural features.
Core structure:  Experiments suggest that amyloid fibrils share a common core filament structure, irrespective of the nature of their precursor proteins. X-ray²²  and electron diffraction^9,23-27 studies of amyloid fibrils have confirmed the generality of the cross-ß helical structure present in amyloid with ß-Strands separated by 4.7Å18 and ß-sheets separated by 9.8Å. The ß-sheet structure has the strands perpendicular to the long axis of the fibril and hydrogen bonded along the axis of the fibril.^22,28-31 Filaments typically have two or more ß-sheets that are stacked normal to the helical axis and extend along it. Fibrils are composed of two or more filaments.^25,32-35  Histological staining of various amyloid deposits exhibits a common behavior. Congo red shows green birefringence and thioflavin T (ThT) shows a new profluorescent absorption band^36-38 that that are both thought to be related to the common cross-ß core structure. Recently, linear birefringence and dichroism of Congo red has been used to determine the relative orientation of fibrils within amyloid plaques in situ.³⁹ This type of non-covalent labeling is sensitive to the presence of the quaternary interactions specific to fully-formed amyloid.
NMR has also been used to determine the residue-level participation in the core structure of amyloid fibrils using H/D exchange^40-44 and relaxation measurements.45-50 These results show that the segments of ß-stands that comprise the core of the fibrils is are protected from access to water and are more rigidly held than the loops or ends that are not part of the core.²²

Conformational changes are typically observed during amyloid assembly. In their native state, the precursor proteins may not, in general, contain the secondary structural elements present in the final amyloid assembly. The amide I infrared absorption or Raman band is typically observed to lose intensity associated with the native state and gain intensity associated with cross-ß.^51-59 Circular dichroism of the peptide backbone absorption band is also sensitive to secondary structure and gives similar results.^23,60-63 Fluorescence spectroscopy can also be used to detect conformational changes either by non-covalent labeling with dyes like ANS that are specific for exposed hydrophobic patches^64-70 or through covalent attachment of fluorescent dyes.^71-74 Infrared absorption and Raman suffer from solvent interferences and are often performed on powders. We use circular dichroism to confirm the correlation of covalent and non-covalent fluorescent labeling schemes with secondary structural changes.

Direct Determination of Kinetic Rates from Single-Molecule Photon Arrival Trajectories Using Hidden Markov Models

The measurement of fluorescence from single protein molecules has become an important new tool in the study of dynamic processes, allowing for the direct visualization of the motions experienced by individual proteins and macromolecular complexes. The data from such single-molecule experiments are in the form of photon trajectories, consisting of arrival times and wavelength information on individual photons. The analysis of photon trajectories can be difficult, particularly if the motions are occurring at rates comparable to the photon arrival rate or in the presence of noise. In this paper, we introduce the use of hidden Markov models (HMMs) for the analysis of photon trajectory data that operate using the photon data directly, without the need for ensemble averaging of the data as implied by correlation function analysis. Using a simple kinetic model, we examine the relationship between the uncertainty in the estimates of the motional rate and the photon detection rate. Remarkably, we obtain relative uncertainties in the rate constants of as little as 3% even when the interconversion rate is equal to the photon detection rate, and the uncertainty increases to only 10% when the interconversion rate is 10 times the photon detection rate. This suggests that useful information can be obtained for much faster kinetic regimes than have typically been studied. We also examine the impact of background photons on the determination of the rate and demonstrate that the HMM-based approach is robust, displaying small uncertainties for background photon arrival rates approaching that of the signal. These results not only are relevant in establishing the theoretical limits on precision, but are also useful in the context of experimental design. Finally, to demonstrate how the methodology can be extended to more complex kinetic models and how it can allow one to make use of the full power of statistics for purposes of model evaluation and selection, we consider a four-state kinetic model for protein conformational transitions previously studied by Schenter et al. (J. Phys. Chem. A 1999, 103, 10477). We show how an HMM can be used as an alternative to higher-order correlation function analysis for the detection of “conformational memory” and apparent non-Markovian dynamics arising from such temporally inhomogeneous kinetic schemes.

Single Molecule Dynamics Associated with Protein Folding and Deformations of Light-Harvesting Complexes.

Two new applications of single molecule methods in biology are described. In one, single assemblies of the intact light harvesting complex LH2 from Rhodopseudomonas acidophila were bound to mica surfaces at 300K and examined by observing their fluorescence after polarized light excitation. They mostly behaved as electrically elliptic absorbers whose ellipticity fluctuates, showing that there is a mobile structural deformation. The other application involves the folding and unfolding of a coiled coil GCN4-P1 peptides. By following the trajectory of individual members of a folding ensemble we are able to evaluate and distributions of properties not available from bulk studies.

Symmetry and Local Mode Coupling in Absorption and Raman Spectroscopy of Intervalence Electronic Transitions

Intervalence electron transfer spectra in mixed-valence molecules are frequently modeled by an interacting pair of adiabatic potential energy surfaces. The presence or absence of a double minimum in the lower surface is correlated with trapped or delocalized charges, respectively. The coordinate involved in this interpretation is the asymmetric normal coordinate representing the nuclear motions taking the molecule from one extreme to the other. In this paper, a model is developed involving both a symmetric and an asymmetric coordinate on an equal footing. The time dependent theory of electronic spectroscopy is used to calculate both absorption and resonance Raman spectra. The model uses physically meaningful interactions in the mixed-valence molecule including the electronic coupling, vibrational coupling, vibrational force constants, and bond length changes as a result of the electron transfer. The effect of these interactions on the relative intensities of symmetric and asymmetric modes in both the absorption and resonance Raman spectra are examined. The quantitative calculations are discussed in parallel with the physical meaning. The calculations show how the spectra can smoothly go from domination by one type of mode to the other. The most important effects are caused by the bond length changes, the electronic coupling, and the force constant changes.

Dynamics and folding of single two-stranded coiled-coil peptides studied by fluorescent energy transfer confocal microscopy

We report single-molecule measurements on the folding and unfolding conformational equilibrium distributions and dynamics of a disulfide crosslinked version of the two-stranded coiled coil from GCN4. The peptide has a fluorescent donor and acceptor at the N termini of its two chains and a Cys disulfide near its C terminus. Thus, folding brings the two N termini of the two chains close together, resulting in an enhancement of fluorescent resonant energy transfer. End-to-end distance distributions have thus been characterized under conditions where the peptide is nearly fully folded (0 M urea), unfolded (7.4 M urea), and in dynamic exchange between folded and unfolded states (3.0 M urea). The distributions have been compared for the peptide freely diffusing in solution and deposited onto aminopropyl silanized glass. As the urea concentration is increased, the mean end-to-end distance shifts to longer distances both in free solution and on the modified surface. The widths of these distributions indicate that the molecules are undergoing millisecond conformational fluctuations. Under all three conditions, these fluctuations gave nonexponential correlations on 1- to 100-ms time scale. A component of the correlation decay that was sensitive to the concentration of urea corresponded to that measured by bulk relaxation kinetics. The trajectories provided effective intramolecular diffusion coefficients as a function of the end-to-end distances for the folded and unfolded states. Single-molecule folding studies provide information concerning the distributions of conformational states in the folded, unfolded, and dynamically interconverting states.

Copyright © 2001-2006 David Talaga  All rights reserved.