To flame-seal or not to flame-seal NMR tubes: The role of liquid-vapor equilibria on the accuracy of variable temperature experiments.

In NMR experiments, it is crucial to control the temperature of the sample, especially when measuring kinetic parameters. Usually, it takes 2 to 5 min for the temperature of the sample inside the NMR probe to stabilize at a fixed value set for the experiment. However, the NMR sample tubes are flame-sealed in some cases, such as when working with volatile solvents, atmosphere-sensitive samples, or calibration samples for long-term use. When these samples are placed inside the NMR probe, the spectrometer controls the lower portion (liquid phase) of the NMR sample tube with a gas flow at a fixed temperature, while the upper portion (vapor) is at ambient temperature. This probe design creates a unique temperature gradient across the sample, leading to vapor pressure build-up, particularly inside a sealed NMR tube. By analyzing the temperature-dependent spectral line shape changes of a chemical exchange process, we report that under standard experimental conditions, the sample temperature can take up to 2 to 3 h (instead of minutes) to stabilize. The time scale of the liquid-vapor equilibrium process is much slower, with a half-life exceeding 35 min, in contrast to the 2-min duration required to obtain each spectrum. This phenomenon is exclusively due to the liquid-vapor equilibrium process of the flame-sealed NMR tube and is not observable otherwise.

Enzyme kinetics by real-time quantitative NMR (qNMR) spectroscopy with progress curve analysis.

This review article summarizes how the experimental data obtained using quantitative nuclear magnetic resonance (qNMR) spectroscopy can be combined with progress curve analysis to determine enzyme kinetic parameters. The qNMR approach enables following the enzymatic conversion of the substrate to the product in real-time by a continuous collection of spectra. The Lambert-W function, a closed-form solution to the time-dependent substrate/product kinetics of the rate equation, can estimate the Michaelis-Menten constant (KM.) and the maximum velocity (Vmax) from a single experiment. This article highlights how the qNMR data is well suited for analysis using the Lambert-W function with three different applications. Results from studies on acetylcholinesterase (acetylcholine to acetic acid and choline), ß-Galactosidase (lactose to glucose and galactose), and invertase (sucrose to glucose and fructose) are presented. Furthermore, an additional example of how the progress curve analysis is applied to understand the inhibitory role of the artificial sweetener sucralose on sucrose's enzymatic conversion by invertase is discussed. With the wide availability of NMR spectrometers in academia and industries, including bench-top systems with permanent magnets, and the potential to enhance sensitivity using dynamic nuclear polarization in combination with ultrafast methods, the NMR-based enzyme kinetics could be considered a valuable tool for broader applications in the field of enzyme kinetics.

Identification of ligand binding sites in intrinsically disordered proteins with a differential binding score.

Screening ligands directly binding to an ensemble of intrinsically disordered proteins (IDP) to discover potential hits or leads for new drugs is an emerging but challenging area as IDPs lack well-defined and ordered 3D-protein structures. To explore a new IDP-based rational drug discovery strategy, a differential binding score (DIBS) is defined. The basis of DIBS is to quantitatively determine the binding preference of a ligand to an ensemble of conformations specified by IDP versus such preferences to an ensemble of random coil conformations of the same protein. Ensemble docking procedures performed on repeated sampling of conformations, and the results tested for statistical significance determine the preferential ligand binding sites of the IDP. The results of this approach closely reproduce the experimental data from recent literature on the binding of the ligand epigallocatechin gallate (EGCG) to the intrinsically disordered N-terminal domain of the tumor suppressor p53. Combining established approaches in developing a new method to screen ligands against IDPs could be valuable as a screening tool for IDP-based drug discovery.

Conformational Ensembles by NMR and MD Simulations in Model Heptapeptides with Select Tri-Peptide Motifs.

Both nuclear magnetic resonance (NMR) and molecular dynamics (MD) simulations are routinely used in understanding the conformational space sampled by peptides in the solution state. To investigate the role of single-residue change in the ensemble of conformations sampled by a set of heptapeptides, AEVXEVG with X = L, F, A, or G, comprehensive NMR, and MD simulations were performed. The rationale for selecting the particular model peptides is based on the high variability in the occurrence of tri-peptide E*L between the transmembrane ß-barrel (TMB) than in globular proteins. The ensemble of conformations sampled by E*L was compared between the three sets of ensembles derived from NMR spectroscopy, MD simulations with explicit solvent, and the random coil conformations. In addition to the estimation of global determinants such as the radius of gyration of a large sample of structures, the ensembles were analyzed using principal component analysis (PCA). In general, the results suggest that the -EVL- peptide indeed adopts a conformational preference that is distinctly different not only from a random distribution but also from other peptides studied here. The relatively straightforward approach presented herein could help understand the conformational preferences of small peptides in the solution state.

On the Differential Roles of Mg2+, Zn2+, and Cu2+ in the Equilibrium of ß-N-Methyl-Amino-L-Alanine (BMAA) and its Carbamates.

ß-N-methyl-amino-L-alanine (BMAA) in the presence of bicarbonate (HCO3-) undergoes structural modifications generating two carbamate species, α-carbamate and ß-carbamate forms of BMAA. The chemical structure of BMAA and BMAA-carbamate adducts strongly suggest they may interact with divalent metal ions. The ability of BMAA to cross the blood-brain barrier and possibly interact with divalent metal ions may augment the neurotoxicity of these molecules. To understand the effects of divalent metal ions (Mg2+, Zn2+, and Cu2+) on the overall dynamic equilibrium between BMAA and its carbamate adducts, a systematic study using nuclear magnetic resonance (NMR) is presented. The chemical equilibria between BMAA, its carbamate adducts, and each of the divalent ions were studied using two-dimensional chemical exchange spectroscopy (EXSY). The NMR results demonstrate that BMAA preferentially interacts with Zn2+ and Cu2+, causing an overall reduction in the production of carbamate species by altering the dynamic equilibria. The NMR-based spectral changes due to the BMAA interaction with Cu2+ is more drastic than with the Zn2+, under the same stoichiometric ratios of BMAA and the individual divalent ions. However, the presence of Mg2+ does not significantly alter the dynamic equilibria between BMAA and its carbamate adducts. The NMR-based results are further validated using circular dichroism (CD) spectroscopy, observing the n ➔ π interaction in the complex formation of BMAA and the divalent metal ions, with additional verification of the interaction with Cu2+ using UV-Vis spectroscopy. Our results demonstrate that BMAA differentially interacts with divalent metal ions (Mg2+ < Zn2+ < Cu2+), and thus alters the rate of formation of carbamate products. The equilibria between BMAA, the bicarbonate ions, and the divalent metal ions may alter the total population of a specific form of BMAA-ion complex at physiological conditions and, therefore, add a level of complexity of the mechanisms by which BMAA acts as a neurotoxin.

NMR based real-time enzyme kinetics on estimating the inhibitory effect of sucralose in the enzymatic conversion of sucrose.

Sucralose, one of the popular non-caloric artificial sweeteners, has been known to influence the enzymatic conversion of sucrose to glucose and fructose by invertase. In continuing the use of real-time NMR experiments and reaction progress curve analysis to measure enzyme kinetics, here we investigate the role of sucralose as an inhibitor. NMR based kinetic experiments were performed as a function of the substrate concentration for a range of sucralose concentrations, and the results were analyzed by fitting the progress curve to the Lambert-W function. The Michaelis-Menten parameters were then used to estimate the inhibitory constant of sucralose. To estimate the extent of sucralose inhibition on the enzymatic production of glucose, control experiments were performed with lactose as the inhibitor under similar experimental conditions. The results show that sucralose is a much more potent inhibitor than lactose, inhibiting the enzymatic conversion at least seven times more.

Chemistry and Chemical Equilibrium Dynamics of BMAA and Its Carbamate Adducts.

Beta-N-methylamino-L-alanine (BMAA) has been demonstrated to contribute to the onset of the ALS/Parkinsonism-dementia complex (ALS/PDC) and is implicated in the progression of other neurodegenerative diseases. While the role of BMAA in these diseases is still debated, one of the suggested mechanisms involves the activation of excitatory glutamate receptors. In particular, the excitatory effects of BMAA are shown to be dependent on the presence of bicarbonate ions, which in turn forms carbamate adducts in physiological conditions. The formation of carbamate adducts from BMAA and bicarbonate is similar to the formation of carbamate adducts from non-proteinogenic amino acids. Structural, chemical, and biological information related to non-proteinogenic amino acids provide insight into the formation of and possible neurological action of BMAA. This article reviews the carbamate formation of BMAA in the presence of bicarbonate ions, with a particular focus on how the chemical equilibrium of BMAA carbamate adducts may affect the molecular mechanism of its function. Highlights of nuclear magnetic resonance (NMR)-based studies on the equilibrium process between free BMAA and its adducts are presented. The role of divalent metals on the equilibrium process is also explored. The formation and the equilibrium process of carbamate adducts of BMAA may answer questions on their neuroactive potency and provide strong motivation for further investigations into other toxic mechanisms.

Effect of sucralose on the enzyme kinetics of invertase using real-time NMR spectroscopy and progress curve analysis.

Sucralose, a derivative of sucrose, is widely used in noncaloric artificial sweeteners (NAS). Contrary to the belief that sucralose is physiologically inert and a healthy alternative sweetener to natural sugar, emerging studies indicate that sucralose alters the host metabolism as well as the composition of the microbiome. In this manuscript, we use real-time nuclear magnetic resonance (NMR) spectroscopy to demonstrate that sucralose alters the enzymatic conversion of sucrose to glucose and fructose. The real-time NMR progress curve analysis suggests that sucralose has the characteristic of a competitive inhibitor on the kinetics of the enzymatic process. This affects the rate of glucose production, and thus indirectly affecting the mutarotation process of α-D-glucose to ß-D-glucose conversion. At a 1:2 M ratio of sucrose to sucralose, the results show that the catalytic efficiency of the enzyme is reduced by more than 50% in comparison to the measurements without sucralose. Altogether, as sucralose alters the rate of glucose production, sucralose cannot be considered inert to the metabolism as several downstream events in both prokaryotic and eukaryotic systems strongly depend on the rate of glucose metabolism.

Ensemble characterization of an intrinsically disordered FG-Nup peptide and its F>A mutant in DMSO-d6.

Intrinsically disordered proteins (IDP) lack a well-defined 3D-structure under physiological conditions, yet, the inherent disorder represented by an ensemble of conformation plays a critical role in many cellular and regulatory processes. Nucleoporins, or Nups, are the proteins found in the nuclear pore complex (NPC). The central pore of the NPC is occupied by Nups, which have phenylalanine-glycine domain repeats and are intrinsically disordered, and therefore are termed FG-Nups. These FG-domain repeats exhibit differing cohesiveness character and differ from least (FG) to most (GLFG) cohesive. The designed FG-Nup is a 25 AA model peptide containing a noncohesive FG-motif flanked by two cohesive GLFG-motifs (WT peptide). Complete NMR-based ensemble characterization of this peptide along with a control peptide with an F>A substitution (MU peptide) are discussed. Ensemble characterization of the NMR-determined models suggests that both the peptides do not have consistent secondary structures and continue to be disordered. Nonetheless, the role of cohesive elements mediated by the GLFG motifs is evident in the WT ensemble of structures that are more compact than the MU peptide. The approach presented here allows an alternate way to investigate the specific roles of distinct amino acid motifs that translate into the long-range organization of the ensemble of structures and in general on the nature of IDPs.

The interplay between immune maturation, age, chronic viral infection and environment.

BACKGROUND: The worldwide increase in life expectancy has been associated with an increase in age-related morbidities. The underlying mechanisms resulting in immunosenescence are only incompletely understood. Chronic viral infections, in particular infection with human cytomegalovirus (HCMV), have been suggested as a main driver in immunosenescence. Here, we propose that rhesus macaques could serve as a relevant model to define the impact of chronic viral infections on host immunity in the aging host. We evaluated whether chronic rhesus CMV (RhCMV) infection, similar to HCMV infection in humans, would modulate normal immunological changes in the aging individual by taking advantage of the unique resource of rhesus macaques that were bred and raised to be Specific Pathogen Free (SPF-2) for distinct viruses. RESULTS: Our results demonstrate that normal age-related immunological changes in frequencies, activation, maturation, and function of peripheral blood cell lymphocytes in humans occur in a similar manner over the lifespan of rhesus macaques. The comparative analysis of age-matched SPF-2 and non-SPF macaques that were housed under identical conditions revealed distinct differences in certain immune parameters suggesting that chronic pathogen exposure modulated host immune responses. All non-SPF macaques were infected with RhCMV, suggesting that chronic RhCMV infection was a major contributor to altered immune function in non-SPF macaques, although a causative relationship was not established and outside the scope of these studies. Further, we showed that immunological differences between SPF-2 and non-SPF macaques were already apparent in adolescent macaques, potentially predisposing RhCMV-infected animals to age-related pathologies. CONCLUSIONS: Our data validate rhesus macaques as a relevant animal model to study how chronic viral infections modulate host immunity and impact immunosenescence. Comparative studies in SPF-2 and non-SPF macaques could identify important mechanisms associated with inflammaging and thereby lead to new therapies promoting healthy aging in humans.

Application of data mining tools for classification of protein structural class from residue based averaged NMR chemical shifts.

The number of protein sequences deriving from genome sequencing projects is outpacing our knowledge about the function of these proteins. With the gap between experimentally characterized and uncharacterized proteins continuing to widen, it is necessary to develop new computational methods and tools for protein structural information that is directly related to function. Nuclear magnetic resonance (NMR) provides powerful means to determine three-dimensional structures of proteins in the solution state. However, translation of the NMR spectral parameters to even low-resolution structural information such as protein class requires multiple time consuming steps. In this paper, we present an unorthodox method to predict the protein structural class directly by using the residue's averaged chemical shifts (ACS) based on machine learning algorithms. Experimental chemical shift information from 1491 proteins obtained from Biological Magnetic Resonance Bank (BMRB) and their respective protein structural classes derived from structural classification of proteins (SCOP) were used to construct a data set with 119 attributes and 5 different classes. Twenty four different classification schemes were evaluated using several performance measures. Overall the residue based ACS values can predict the protein structural classes with 80% accuracy measured by Matthew correlation coefficient. Specifically protein classes defined by mixed αß or small proteins are classified with >90% correlation. Our results indicate that this NMR-based method can be utilized as a low-resolution tool for protein structural class identification without any prior chemical shift assignments.

Combining information from ancestors and personal experiences to predict individual differences in developmental trajectories.

A persistent question in biology is how information from ancestors combines with personal experiences over the lifetime to affect the developmental trajectories of phenotypic traits. We address this question by modeling individual differences in behavioral developmental trajectories on the basis of two assumptions: (1) differences among individuals in the behavior expressed at birth or hatching are based on information from their ancestors (via genes, epigenes, and prenatal maternal effects), and (2) information from ancestors is combined with information from personal experiences over ontogeny via Bayesian updating. The model predicts relationships between the means and the variability of the behavior expressed by neonates and the subsequent developmental trajectories of their behavior when every individual is reared under the same environmental conditions. Several predictions of the model are supported by data from previous studies of behavioral development, for example, that the temporal stability of personality will increase with age and that the intercepts and slopes of developmental trajectories for boldness will be negatively correlated across individuals or genotypes when subjects are raised in safe environments. We describe how other specific predictions of the model can be used to test the hypothesis that information from ancestors and information from personal experiences are combined via nonadditive, Bayesian-like processes.

Multiplexed measurements of immunomodulator levels in peripheral blood of healthy subjects: Effects of analytical variables based on anticoagulants, age, and gender.

Multiplex microbead immunoassay (MMIA) is a powerful technology for a wide range of biomedical and clinical applications. It is important to study the normal concentration ranges of immunomodulators under different sample preparation conditions and age groups of subjects in order to more precisely determine their reference values for use in assessing alterations of their levels in disease. The aim of this study was to determine the plasma concentrations of immunomodulators (cytokines, chemokines, and growth factors) in the peripheral blood from healthy subjects by the use of a large multiplex panel, and to determine the effects of different anticoagulants, age, and gender on the immunomodulator levels. In addition, the assay precision for these biomarker analytes was determined. Plasma samples from 107 healthy subjects, aged 18 to 85 years, were collected in three different anticoagulants (sodium citrate, EDTA, Heparin); corresponding serum samples were also obtained. Multiplex microbead immunoassays were performed for measuring a total of 23 analytes including chemokines, cytokines, and growth factors (IL-1ß, IL-1ra, IL-2, IL-6, IL-7, IL-8, IL-12 p70, IL-17, IFN-γ, IP-10, MCP-1, PDGF-BB, RANTES, TNF-α, IL-1a, IL-16, HGF, MIG, TNF-ß, PDGF-ABBB, EGF, Flt-3 Ligand, VEGF). For these analytes, our results showed that the anticoagulant affected the concentration measurements and the coefficients of variation. However, the relative levels of the analytes (profiles) of samples collected in a particular anticoagulant are consistent. The analytes IL-1ß, IL-7, Flt-3 Ligand, and IL-12p70 show the largest variation (up to fourfold) between the age groups. In addition, no statistically significant differences in the level of the analytes were found between the sexes.

NMR based solvent exchange experiments to understand the conformational preference of intrinsically disordered proteins using FG-nucleoporin peptide as a model.

The conformational preference of a peptide with three phenylalanine-glycine (FG) repeats from the intrinsically disordered domain of nucleoporin 159 (nup159) from the yeast nucleopore complex is studied. Conformational states of this FG-peptide in dimethyl sulfoxide (DMSO), a non-native solvent, are first studied. A solvent exchange scheme is designed and performed to understand how the conformational preferences of the peptide are altered as the solvent shifts from DMSO to water. An ensemble of structures of a 19-residue peptide is determined based on (13)Cα, (1)Hα, and (1)HN chemical shifts and with inter-proton distances. An experimental model is then presented where chemical shifts and amide-proton temperature dependence is probed at changing DMSO to water ratios. These co-solvent experiments provide evidence of a conformational change as the fraction of water increases by the stark change in the behavior of amide protons under varied temperature. This investigation provides a NMR based experimental method in the field of intrinsically disordered proteins to realize conformational transitions from a non-native set of structures (in DMSO) to a native set of disordered conformers (in water).

Genotypic differences in behavioural entropy: unpredictable genotypes are composed of unpredictable individuals.

Intra-genotypic variability (IGV) occurs when individuals with the same genotype, raised in the same environment and then tested under the same conditions, express different trait values. Game theoretical and bet-hedging models have suggested two ways that a single genotype might generate variable behaviour when behavioural variation is discrete rather than continuous: behavioural polyphenism (a genotype produces different types of individuals, each of which consistently expresses a different type of behaviour) or stochastic variability (a genotype produces one type of individual who randomly expresses different types of behaviour over time). We first demonstrated significant differences across 14 natural genotypes of male Drosophila melanogaster in the variability (as measured by entropy) of their microhabitat choice, in an experiment in which each fly was allowed free access to four different types of habitat. We then tested four hypotheses about ways that within-individual variability might contribute to differences across genotypes in the variability of microhabitat choice. There was no empirical support for three hypotheses (behavioural polymorphism, consistent choice, or time-based choice), nor could our results be attributed to genotypic differences in activity levels. The stochastic variability hypothesis accurately predicted the slope and the intercept of the relationship across genotypes between entropy at the individual level and entropy at the genotype level. However, our initial version of the stochastic model slightly but significantly overestimated the values of individual entropy for each genotype, pointing to specific assumptions of this model that might need to be adjusted in future studies of the IGV of microhabitat choice. This is among a handful of recent studies to document genotypic differences in behavioural IGV, and the first to explore ways that genotypic differences in within-individual variability might contribute to differences among genotypes in the predictability of their behaviour.

Modulations in restricted amide rotation by steric induced conformational trapping.

The rotation around the amide bond in N,N-diethyl-m-toluamide (m-DEET) has been studied extensively and often used in laboratory instructions to demonstrate the phenomenon of chemical exchange. Herein, we show that a simple modification to N,N-diethyl-o-toluamide (o-DEET) significantly alters the dynamics of the restricted rotation around the amide bond due to steric interactions between the ring methyl group and the two N-ethyl groups. This alters the classic two-site exchange due to restricted rotation around the amide bond, to a three-site exchange, with the third conformation trapped at a higher-energy state compared to the other two. This often overlooked phenomenon is elucidated using variable-temperature NMR, two-dimensional exchange spectroscopy and molecular modeling studies.

Low dose radiation response curves, networks and pathways in human lymphoblastoid cells exposed from 1 to 10cGy of acute gamma radiation.

We investigated the low dose dependency of the transcriptional response of human cells to characterize the shape and biological functions associated with the dose-response curve and to identify common and conserved functions of low dose expressed genes across cells and tissues. Human lymphoblastoid (HL) cells from two unrelated individuals were exposed to graded doses of radiation spanning the range of 1-10cGy were analyzed by transcriptome profiling, qPCR and bioinformatics, in comparison to sham irradiated samples. A set of ∼80 genes showed consistent responses in both cell lines; these genes were associated with homeostasis mechanisms (e.g., membrane signaling, molecule transport), subcellular locations (e.g., Golgi, and endoplasmic reticulum), and involved diverse signal transduction pathways. The majority of radiation-modulated genes had plateau-like responses across 1-10cGy, some with suggestive evidence that transcription was modulated at doses below 1cGy. MYC, FOS and TP53 were the major network nodes of the low-dose-response in HL cells. Comparison our low dose expression findings in HL cells with those of prior studies in mouse brain after whole body exposure, in human keratinocyte cultures, and in endothelial cells cultures, indicates that certain components of the low dose radiation response are broadly conserved across cell types and tissues, independent of proliferation status.

How different types of natal experience affect habitat preference.

In many animals, exposure to cues in a natal habitat increases disperser preferences for those cues (natal habitat preference induction [NHPI]), but the proximate and ultimate bases for this phenomenon are obscure. We developed a Bayesian model to study how different types of experience in the natal habitat and survival to the age/stage of dispersal interact to affect a disperser's estimate of the quality of new natal-type habitats. The model predicts that the types of experience a disperser had before leaving its natal habitat will affect the attractiveness of cues from new natal-type habitats and that favorable experiences will increase the level of preference for natal-type habitats more than unfavorable experiences will decrease it. An experimental study of NHPI in Drosophila melanogaster provided with "good" and "bad" experiences in their natal habitats supports these predictions while also indicating that the effects of different types of natal experience on NHPI vary across genotypes. If habitat preferences are modulated by an individual's experience before dispersal as described in this study, then NHPI may have stronger effects on sympatric speciation, metapopulation dynamics, conservation biology, and pest management than previously supposed.

A comparison of multiplex suspension array large-panel kits for profiling cytokines and chemokines in rheumatoid arthritis patients.

BACKGROUND: Multiplex analysis allows measurements of a large number of analytes simultaneously in each sample. On the basis of the Luminex multiplex technology (xMAP), kits for measuring multiple cytokines and chemokines (immunomodulators) are commercially available and are useful in investigations on inflammatory diseases. This study evaluated four multiplex kits (Bio-Plex, LINCOplex, Fluorokine, and Beadlyte) that contained 27, 29, 20, and 22 analytes each, respectively, for the analysis of immunomodulators in plasma of patients with rheumatoid arthritis (RA) who underwent treatment with antibody against CD20 (rituximab), a B-cell reductive therapy. METHODS: Multiplex kits were tested on serial plasma samples obtained from six RA patients at baseline and multiple time points (3, 6, and 9 months) post-treatment with rituximab. The RA patients included in this study had previously failed therapy with disease modifying anti-arthritis drugs (DMARD) and treatment with anti-TNFalpha antibody (infliximab). RESULTS: Computer modeling and hierarchical cluster analysis of the multiplex data allowed a comparison of the performance of multiplex assay kits and revealed profiles of immunomodulators in the RA patients. CONCLUSIONS: In plasma of RA patients who appeared to have benefited from the rituximab treatment, the profile of significantly elevated immunomodulators by at least two of the three kits (BioPlex, LINCOplex, Beadlyte) is as follows: IL-12p70, Eotaxin, IL-4, TNFalpha, Il-9, IL-1beta, IFNgamma, IL-10, IL-6, and IL-13. Immunomodulator profiling by multiplex analysis may provide useful plasma biomarkers for monitoring response to B-cell reductive therapy in RA patients.