A Randomization-Based, Model-Free Approach to Functional Neuroimaging: A Proof of Concept.

Functional neuroimaging analysis takes noisy multidimensional measurements as input and produces statistical inferences regarding the functional properties of brain regions as output. Such inferences are most commonly model-based, in that they assume a model of how neural activity translates to the measured signal (blood oxygenation level-dependent signal in the case of functional MRI). The use of models increases statistical sensitivity and makes it possible to ask fine-grained theoretical questions. However, this comes at the cost of making theoretical assumptions about the underlying data-generating process. An advantage of model-free approaches is that they can be used in cases where model assumptions are known not to hold. To this end, we introduce a randomization-based, model-free approach to functional neuroimaging. TWISTER randomization makes it possible to infer functional selectivity from correlations between experimental runs. We provide a proof of concept in the form of a visuomotor mapping experiment and discuss the possible strengths and limitations of this new approach in light of our empirical results.

Analysis of electromagnetic response of cells and lipid membranes using a model-free method.

Electromagnetic radiation (EMR) is omnipresent on earth and may interact with the biological systems in diverse manners. But the scope and nature of such interactions remain poorly understood. In this study, we have measured the permittivity of cells and lipid membranes over the EMR frequency range of 20 Hz to 4.35 × 1010 Hz. To identify EMR frequencies that display physically intuitive permittivity features, we have developed a model-free method that relies on a potassium chloride reference solution of direct-current (DC) conductivity equal to that of the target sample. The dielectric constant, which reflects the capacity to store energy, displays a characteristic peak at 105-106 Hz. The dielectric loss factor, which represents EMR absorption, is markedly enhanced at 107-109 Hz. The fine characteristic features are influenced by the size and composition of these membraned structures. Mechanical disruption results in abrogation of these characteristic features. Enhanced energy storage at 105-106 Hz and energy absorption at 107-109 Hz may affect certain membrane activity relevant to cellular function.

Helical Molecular Springs with Varying Spring Constants.

We report a general synthetic route toward helical ladder polymers with varying spring constants, built with chirality-assisted synthesis (CAS). Under tension and compression, these shape-persistent structures do not unfold, but rather stretch and compress akin classical Hookean springs. Our synthesis is adaptable to helices with different pitch and diameter, which allowed us to investigate how molecular flexibility in solution depends on the exact geometry of the ladder polymers. Specifically, we showed with molecular dynamic simulations and by measuring the longitudinal 1 H NMR relaxation times (T1 ) for our polymers at different Larmor frequencies, that increasing the helix diameter leads to increased flexibility. Our results present initial design rules for tuning the mechanical properties of intrinsically helical ladder polymers in solution, which will help inspire a new class of robust, spring-like molecular materials with varying mechanical properties.

Model-Free or Not?

Relaxation in nuclear magnetic resonance is a powerful method for obtaining spatially resolved, timescale-specific dynamics information about molecular systems. However, dynamics in biomolecular systems are generally too complex to be fully characterized based on NMR data alone. This is a familiar problem, addressed by the Lipari-Szabo model-free analysis, a method that captures the full information content of NMR relaxation data in case all internal motion of a molecule in solution is sufficiently fast. We investigate model-free analysis, as well as several other approaches, and find that model-free, spectral density mapping, LeMaster's approach, and our detector analysis form a class of analysis methods, for which behavior of the fitted parameters has a well-defined relationship to the distribution of correlation times of motion, independent of the specific form of that distribution. In a sense, they are all "model-free." Of these methods, only detectors are generally applicable to solid-state NMR relaxation data. We further discuss how detectors may be used for comparison of experimental data to data extracted from molecular dynamics simulation, and how simulation may be used to extract details of the dynamics that are not accessible via NMR, where detector analysis can be used to connect those details to experiments. We expect that combined methodology can eventually provide enough insight into complex dynamics to provide highly accurate models of motion, thus lending deeper insight into the nature of biomolecular dynamics.

Altered brain network function during attention-modulated visual processing in multiple sclerosis.

BACKGROUND: Multiple sclerosis may damage cognitive performance in several domains, including attention. Although attention network deficits were described during rest, studies that investigate their function during task performance are scarce. OBJECTIVE: To investigate connectivity within and between task-related networks in multiple sclerosis during a visual attention task as a function of cognitive performance. METHODS: A total of 23 relapsing-remitting multiple sclerosis (RRMS) patients and 29 healthy controls underwent task-functional magnetic resonance imaging (fMRI) scans using a visual attention paradigm on a 3T scanner. Scans were analysed using tensor-independent component analysis (TICA). Functional connectivity was calculated within and between components. We assessed cognitive function with the Brief International Cognitive Assessment for MS (BICAMS) battery. RESULTS: TICA extracted components related to visual processing, attention, executive function and the default-mode network. Subject scores of visual/attention-related and executive components were greater in healthy controls (p < 0.032, p < 0.023). Connectivity between visual/attention-related and default-mode components was higher in patients (p < 0.043), correlating with Brief Visuospatial Memory Test-Revised (BVMT-R) scores (R = -0.48, p < 0.036). Patients showed reduced connectivity between the right intraparietal sulcus (rIPS) and frontal eye field (rFEF), and bilateral frontal eye fields (p < 0.012, p < 0.003). Reduced rIPS-rFEF connectivity came with lower Symbol Digit Modalities Test (SDMT)/BVMT-R scores in patients (R = 0.53, p < 0.02, R = 0.46, p < 0.049). CONCLUSION: Attention-related networks show altered connectivity during task performance in RRMS patients, scaling with cognitive disability.

Direct Measure of the Local Concentration of Pyrenyl Groups in Pyrene-Labeled Dendrons Derived from the Rate of Fluorescence Collisional Quenching.

The model-free analysis (MFA) was applied to measure the average rate constant () for pyrene excimer formation (PEF) in a series of pyrene-labeled dendrons referred to as Pyx-G(N), where x (= 2N) is the number of pyrenyl labels born by a dendron of generation N ranging from 1 to 6. was measured in four different solvents, namely tetrahydrofuran (THF), toluene, N,N-dimethylformamide (DMF), and dimethylsulfoxide (DMSO). was found to increase linearly with increasing local pyrene concentration ([Py]loc), where [Py]loc had been determined mathematically for the Pyx-G(N) dendrons. The slope of each straight line changed with the nature of the solvent and represented kdiff, the bimolecular rate constant for PEF. kdiff depended on the solvent viscosity (η) and the probability (p) for PEF upon encounter between an excited and a ground-state pyrene. In a same solvent, kdiff for the Pyx-G(N) dendrons was about 360 ± 30 times smaller than kdiff obtained for ethyl 4-(1-pyrene)butyrate (PyBE), a pyrene model compound similar to the pyrene derivative used to label the dendrons. The massive decrease in kdiff observed for the Pyx-G(N) samples reflected the massive loss in mobility experienced by the pyrenyl labels after being covalently attached onto a macromolecule compared to freely diffusing PyBE. Interestingly, the kdiff values obtained for the Pyx-G(N) dendrons and the PyBE model compound followed similar trends as a function of solvent, indicating that the difference in behavior between the kdiff values obtained in different solvents were merely due to the changes in the η and p values between the solvents. Normalizing the values obtained with the Pyx-G(N) dendrons by the kdiff values obtained for PyBE in the same solvents accounted for changes in η and p, resulting in a master curve upon plotting /(fdiff × kdiff) as a function of [Py]loc, where fdiff was introduced to account for some pyrene aggregation in the higher generation dendron (Py64-G(6)). This result demonstrates that represents a direct measure of [Py]loc in pyrene-labeled macromolecules.

NMR characterization of conformational fluctuations and noncovalent interactions of SUMO protein from Drosophila melanogaster (dSmt3).

Structural heterogeneity in the native-state ensemble of dSmt3, the only small ubiquitin-like modifier (SUMO) in Drosophila melanogaster, was investigated and compared with its human homologue SUMO1. Temperature dependence of amide proton's chemical shift was studied to identify amino acids possessing alternative structural conformations in the native state. Effect of small concentration of denaturant (1M urea) on this population was also monitored to assess the ruggedness of near-native energy landscape. Owing to presence of many such amino acids, especially in the ß2 -loop-α region, the native state of dSmt3 seems more flexible in comparison to SUMO1. Information about backbone dynamics in ns-ps timescale was quantified from the measurement of 15 N-relaxation experiments. Furthermore, the noncovalent interaction of dSmt3 and SUMO1 with Daxx12 (Daxx729 DPEEIIVLSDSD740 ), a [V/I]-X-[V/I]-[V/I]-based SUMO interaction motif, was characterized using Bio-layer Interferometery and NMR spectroscopy. Daxx12 fits itself in the groove formed by ß2 -loop-α structural region in both dSmt3 and SUMO1, but the binding is stronger with the former. Flexibility of ß2 -loop-α region in dSmt3 is suspected to assist its interaction with Daxx12. Our results highlight the role of native-state flexibility in assisting noncovalent interactions of SUMO proteins especially in organisms where a single SUMO isoform has to tackle multiple substrates single handedly.

Characterization of Internal Protein Dynamics and Conformational Entropy by NMR Relaxation.

Recent studies suggest that the fast timescale motion of methyl-bearing side chains may play an important role in mediating protein activity. These motions have been shown to encapsulate the residual conformational entropy of the folded state that can potentially contribute to the energetics of protein function. Here, we provide an overview of how to characterize these motions using nuclear magnetic resonance (NMR) spin relaxation methods. The strengths and limitations of several techniques are highlighted in order to assist with experimental design. Particular emphasis is placed on the practical aspects of sample preparation, data collection, data fitting, and statistical analysis. Additionally, discussion of the recently refined "entropy meter" is presented and its use in converting NMR observables to conformational entropy is illustrated. Taken together, these methods should yield new insights into the complex interplay between structure and dynamics in protein function.

Dynamics of dehaloperoxidase-hemoglobin A derived from NMR relaxation spectroscopy and molecular dynamics simulation.

Dehaloperoxidase-hemoglobin is the first hemoglobin identified with biologically-relevant oxidative functions, which include peroxidase, peroxygenase and oxidase activities. Herein we report a study of the protein backbone dynamics of DHP using heteronuclear NMR relaxation methods and molecular dynamics (MD) simulations to address the role of protein dynamics in switching from one function to another. The results show that DHP's backbone helical regions and turns have average order parameters of S2 = 0.87 ±â€¯0.03 and S2 = 0.76 ±â€¯0.08, respectively. Furthermore, DHP is primarily a monomer in solution based on the overall tumbling correlation time τm is 9.49 ±â€¯1.65 ns calculated using the prolate diffusion tensor model in the program relax. A number of amino acid residues have significant Rex using the Lipari-Szabo model-free formalism. These include Lys3, Ile6, Leu13, Gln18, Arg32, Ser48, Met49, Thr56, Phe60, Arg69, Thr71 Cys73, Ala77, Asn81, Gly95, Arg109, Phe115, Leu127 and Met136, which may experience slow conformational motions on the microseconds-milliseconds time scale according to the model. Caution should be used when the model contains >4 fitting parameters. The program caver3.0 was used to identify tunnels inside DHP obtained from MD simulation snapshots that are consistent with the importance of the Xe binding site, which is located at the central intersection of the tunnels. These tunnels provide diffusion pathways for small ligands such as O2, H2O and H2O2 to enter the distal pocket independently of the trajectory of substrates and inhibitors, both of which are aromatic molecules.

Towards Tunable Consensus Clustering for Studying Functional Brain Connectivity During Affective Processing.

In the past decades, neuroimaging of humans has gained a position of status within neuroscience, and data-driven approaches and functional connectivity analyses of functional magnetic resonance imaging (fMRI) data are increasingly favored to depict the complex architecture of human brains. However, the reliability of these findings is jeopardized by too many analysis methods and sometimes too few samples used, which leads to discord among researchers. We propose a tunable consensus clustering paradigm that aims at overcoming the clustering methods selection problem as well as reliability issues in neuroimaging by means of first applying several analysis methods (three in this study) on multiple datasets and then integrating the clustering results. To validate the method, we applied it to a complex fMRI experiment involving affective processing of hundreds of music clips. We found that brain structures related to visual, reward, and auditory processing have intrinsic spatial patterns of coherent neuroactivity during affective processing. The comparisons between the results obtained from our method and those from each individual clustering algorithm demonstrate that our paradigm has notable advantages over traditional single clustering algorithms in being able to evidence robust connectivity patterns even with complex neuroimaging data involving a variety of stimuli and affective evaluations of them. The consensus clustering method is implemented in the R package "UNCLES" available on http://cran.r-project.org/web/packages/UNCLES/index.html .

Rapid Determination of Fast Protein Dynamics from NMR Chemical Exchange Saturation Transfer Data.

Functional motions of (15)N-labeled proteins can be monitored by solution NMR spin relaxation experiments over a broad range of timescales. These experiments however typically take of the order of several days to a week per protein. Recently, NMR chemical exchange saturation transfer (CEST) experiments have emerged to probe slow millisecond motions complementing R1ρ and CPMG-type experiments. CEST also simultaneously reports on site-specific R1 and R2 parameters. It is shown here how CEST-derived R1 and R2 relaxation parameters can be measured within a few hours at an accuracy comparable to traditional relaxation experiments. Using a "lean" version of the model-free approach S(2) order parameters can be determined that match those from the standard model-free approach applied to (15)N R1, R2 , and {(1)H}-(15)N NOE data. The new methodology, which is demonstrated for ubiquitin and arginine kinase (42 kDa), should serve as an effective screening tool of protein dynamics from picosecond-to-millisecond timescales.

Solution NMR studies reveal no global flexibility in the catalytic domain of CDC25B.

The CDC25B phosphatase is a critical regulator of the cell cycle and has been validated as an important therapeutic target in cancer. Previous studies using molecular dynamics simulations have concluded that the catalytic domain of CDC25B may experience a significant degree of dynamics or be partially disordered in solution, a finding that has a pronounced impact on the structure-based development of CDC25B inhibitors. We have probed the backbone dynamics of the CDC25B catalytic domain in solution using NMR relaxation experiments and found that the core of the protein is relatively rigid and does not experience any large-scale dynamics over a broad range of time scales. Furthermore, based on residual dipolar coupling measurements we have concluded that the conformation in solution is very similar to that observed in the crystal form. Importantly, these findings rationalize the application of the CDC25B crystal structure in structure-based drug development.

Solution structure and backbone dynamics of human Raf-1 kinase inhibitor protein.

Human Raf-1 kinase inhibitor protein (hRKIP) is a small multi-functional protein of 187 residues. It contains a conserved pocket, which binds a wide range of ligands from various small molecules to distinct proteins. To provide a structural basis for the ligand diversity of RKIP, we herein determined the solution structure of hRKIP, and analyzed its structural dynamics. In solution, hRKIP mainly comprises two antiparallel ß sheets, two α helices and two 310 helices. NMR dynamic analysis reveals that the overall structure of hRKIP is rigid, but its C-terminal helix which is close to the ligand-binding site is mobile. In addition, residues around the ligand-binding pocket exhibit significant conformational exchange on the µs-ms timescale. Conformational flexibility may allow the ligand-binding pocket and the C-terminal helix to adopt various conformations to interact with different substrates. This work may shed light on the underlying molecular mechanisms of how hRKIP recognizes and binds diverse substrate ligands.