Time-resolved NMR studies of RNA folding

The application of real-time NMR experiments to the study of RNA folding, as reviewed in this article, is relatively new. For many RNA folding events, current investigations suggest that the time scales are in the second to minute regime. In addition, the initial investigations suggest that different folding rates are observed for one structural transition may be due to the hierarchical folding units of RNA. Many of the experiments developed in the field of NMR of protein folding cannot directly be transferred to RNA: hydrogen exchange experiments outside the spectrometer cannot be applied since the intrinsic exchange rates are too fast in RNA, relaxation dispersion experiments on the other require faster structural transitions than those observed in RNA. On the other hand, information derived from time-resolved NMR experiments, namely the acquisition of native chemical shifts, can be readily interpreted in light of formation of a single long-range hydrogen bonding interaction. Together with mutational data that can readily be obtained for RNA and new ligation technologies that enhance site resolution even further, time-resolved NMR may become a powerful tool to decipher RNA folding. Such understanding will be of importance to understand the functions of coding and non-coding RNAs in cells.     

Build-up mechanisms determining the topology of mutualistic networks

The frequency distribution of the number of interactions per species (i.e., degree distribution) within plant-animal mutualistic assemblages often decays as a power-law with an exponential truncation. Such a truncation suggests that there are ecological factors limiting the frequency of supergeneralist species. However, it is not clear whether these patterns can emerge from intrinsic features of the interacting assemblages, such as differences between plant and animal species richness (richness ratio). Here, we show that high richness ratios often characterize plant-animal mutualisms. Then, we demonstrate that exponential truncations are expected in bipartite networks generated by a simple model that incorporates build-up mechanisms that lead to a high richness ratio. Our results provide a simple interpretation for the truncations commonly observed in the degree distributions of mutualistic networks that complements previous ones based on biological effects.     

Dynamics and topology of idiotypic networks

Jerne's idiotypic network was previously modelled using simple proliferation dynamics and a homogeneous tree as a connection structure. The present paper studies analytically and numerically the genericity of the previous results when the network connection structure is randomized, e.g. with loops and varying connection intensities. The main feature of the dynamics is the existence of different localized attractors that can be interpreted in terms of vaccination and tolerance. This feature is preserved when loops are added to the network, with a few exceptions concerning some regular lattices. Localized attractors might be destroyed by the introduction of a continuous distribution of connection intensities. We conclude by discussing possible modifications of the elementary model that preserve localization of the attractors and functionality of the network.     

Gene essentiality and the topology of protein interaction networks

The mechanistic bases for gene essentiality and for cell mutational resistance have long been disputed. The recent availability of large protein interaction databases has fuelled the analysis of protein interaction networks and several authors have proposed that gene dispensability could be strongly related to some topological parameters of these networks. However, many results were based on protein interaction data whose biases were not taken into account. In this article, we show that the essentiality of a gene in yeast is poorly related to the number of interactants (or degree) of the corresponding protein and that the physiological consequences of gene deletions are unrelated to several other properties of proteins in the interaction networks, such as the average degrees of their nearest neighbours, their clustering coefficients or their relative distances. We also found that yeast protein interaction networks lack degree correlation, i.e. a propensity for their vertices to associate according to their degrees. Gene essentiality and more generally cell resistance against mutations thus seem largely unrelated to many parameters of protein network topology.     

The flow topology of chemical reaction networks

Analysis of the flow topology of dynamic systems modelling chemical reaction networks leads to the following conclusions: (1) a connected chemical system with a negative feedback circuit containing all except one of the internal species (phase determining intermediates) can exhibit chaotic oscillations; (2) a chemical system in which the only negative feedback circuit contains all of the internal species can exhibit periodic oscillations; (3) a chemical system containing no negative feedback circuits cannot exhibit oscillatory behavior but only multiple steady states. In this analysis a negative feedback circuit refers to a circuit containing an odd number of inhibitory relationships between internal species.     

The topology of metabolic isotope labeling networks

Background  

Metabolic Flux Analysis (MFA) based on isotope labeling experiments (ILEs) is a widely established tool for determining fluxes in metabolic pathways. Isotope labeling networks (ILNs) contain all essential information required to describe the flow of labeled material in an ILE. Whereas recent experimental progress paves the way for high-throughput MFA, large network investigations and exact statistical methods, these developments are still limited by the poor performance of computational routines used for the evaluation and design of ILEs. In this context, the global analysis of ILN topology turns out to be a clue for realizing large speedup factors in all required computational procedures.     

When metabolism meets topology: Reconciling metabolite and reaction networks

The search for a systems‐level picture of metabolism as a web of molecular interactions provides a paradigmatic example of how the methods used to characterize a system can bias the interpretation of its functional meaning. Metabolic maps have been analyzed using novel techniques from network theory, revealing some non‐trivial, functionally relevant properties. These include a small‐world structure and hierarchical modularity. However, as discussed here, some of these properties might actually result from an inappropriate way of defining network interactions. Starting from the so‐called bipartite organization of metabolism, where the two meaningful subsets (reactions and metabolites) are considered, most current works use only one of the subsets by means of so‐called graph projections. Unfortunately, projected graphs often ignore relevant biological and chemical constraints, thus leading to statistical artifacts. Some of these drawbacks and alternative approaches need to be properly addressed.     

Signal transduction networks: topology, response and biochemical processes

Conventionally, biological signal transduction networks are analysed using experimental and theoretical methods to describe specific protein components, interactions, and biochemical processes and to model network behavior under various conditions. While these studies provide crucial information on specific networks, this information is not easily converted to a broader understanding of signal transduction systems. Here, using a specific model of protein interaction we analyse small network topologies to understand their response and general properties. In particular, we catalogue the response for all possible topologies of a given network size to generate a response distribution, analyse the effects of specific biochemical processes on this distribution, and analyse the robustness and diversity of responses with respect to internal fluctuations or mutations in the network. The results show that even three- and four-protein networks are capable of creating diverse and biologically relevant responses, that the distribution of response types changes drastically as a function of biochemical processes at protein level, and that certain topologies strongly pre-dispose a specific response type while others allow for diverse types of responses. This study sheds light on the response types and properties that could be expected from signal transduction networks, provides possible explanations for the role of certain biochemical processes in signal transduction and suggests novel approaches to interfere with signaling pathways at the molecular level. Furthermore it shows that network topology plays a key role on determining response type and properties and that proper representation of network topology is crucial to discover and understand so-called building blocks of large networks.     

Beyond topology: coevolution of structure and flux in metabolic networks

Interactions between the structure of a metabolic network and its functional properties underlie its evolutionary diversification, but the mechanism by which such interactions arise remains elusive. Particularly unclear is whether metabolic fluxes that determine the concentrations of compounds produced by a metabolic network, are causally linked to a network's structure or emerge independently of it. A direct empirical study of populations where both structural and functional properties vary among individuals’ metabolic networks is required to establish whether changes in structure affect the distribution of metabolic flux. In a population of house finches (Haemorhous mexicanus), we reconstructed full carotenoid metabolic networks for 442 individuals and uncovered 11 structural variants of this network with different compounds and reactions. We examined the consequences of this structural diversity for the concentrations of plumage‐bound carotenoids produced by flux in these networks. We found that concentrations of metabolically derived, but not dietary carotenoids, depended on network structure. Flux was partitioned similarly among compounds in individuals of the same network structure: within each network, compound concentrations were closely correlated. The highest among‐individual variation in flux occurred in networks with the strongest among‐compound correlations, suggesting that changes in the magnitude, but not the distribution of flux, underlie individual differences in compound concentrations on a static network structure. These findings indicate that the distribution of flux in carotenoid metabolism closely follows network structure. Thus, evolutionary diversification and local adaptations in carotenoid metabolism may depend more on the gain or loss of enzymatic reactions than on changes in flux within a network structure.     

On the rate of convergence in topology preserving neural networks

A formal analysis of the neighborhood interaction function selection in the topology preserving unsupervised neural network is presented in this paper. The definition of the neighborhood interaction function is motivated by anatomical evidence as opposed to what is currently used, which is a uniform neighborhood interaction set. By selecting a neighborhood interaction function with a neighborhood amplitude of interaction which is decreasing in spatial domain the topological order is always enforced and the rate of self-organization to final equilibrium state is improved. Several simulations are carried out to show the improvement in rate between using a neighborhood interaction function vs. using a neighborhood interaction set. An error measure functional is further defined to compare the two approaches quantitatively.     

Three-dimensional structure topology of the calreticulin P-domain based on NMR assignment

Calreticulin (CRT) is an abundant molecular chaperone of the endoplasmic reticulum. Its central, proline-rich P-domain, comprising residues 189-288, contains three copies of each of two repeat sequences (types 1 and 2), which are arranged in a characteristic '111222' pattern. Here we show that the three-dimensional structure of CRT(189-288) contains a single hairpin fold formed by the entire polypeptide chain. The loop at the bottom of the hairpin consists of residues 227-247, and is closed by an anti-parallel beta-sheet of residues 224-226 and 248-250. Two additional beta-sheets contain residues 207-209 and 262-264, and 190-192 and 276-278. The 17-residue spacing of the beta-strands in the N-terminal part of the hairpin and the 14-residue spacing in the C-terminal part reflect the length of the type 1 and type 2 sequence repeats. As a consequence of this topology the peptide segments separating the beta-strands in the N-terminal part of the hairpin are likely to form bulges to accommodate the extra residues. These results are based on nearly complete sequence-specific NMR assignments for CRT(189-288), which were obtained using standard NMR techniques with the (13)C/(15)N-labeled protein, and collection of nuclear Overhauser enhancement upper distance constraints.     

BCL::Fold—Protein topology determination from limited NMR restraints

When experimental protein NMR data are too sparse to apply traditional structure determination techniques, de novo protein structure prediction methods can be leveraged. Here, we describe the incorporation of NMR restraints into the protein structure prediction algorithm BCL::Fold. The method assembles discreet secondary structure elements using a Monte Carlo sampling algorithm with a consensus knowledge‐based energy function. New components were introduced into the energy function to accommodate chemical shift, nuclear Overhauser effect, and residual dipolar coupling data. In particular, since side chains are not explicitly modeled during the minimization process, a knowledge based potential was created to relate experimental side chain proton–proton distances to C_β–C_β distances. In a benchmark test of 67 proteins of known structure with the incorporation of sparse NMR restraints, the correct topology was sampled in 65 cases, with an average best model RMSD100 of 3.4 ± 1.3 Å versus 6.0 ± 2.0 Å produced with the de novo method. Additionally, the correct topology is present in the best scoring 1% of models in 61 cases. The benchmark set includes both soluble and membrane proteins with up to 565 residues, indicating the method is robust and applicable to large and membrane proteins that are less likely to produce rich NMR datasets. Proteins 2014; 82:587–595. © 2013 Wiley Periodicals, Inc.     

NMR assignments of the binary hvDHFR1:folate complex

A better understanding of how salt affects enzyme activity can be gained via NMR studies of binary hvDHFR1:folate complex. Chemical shift assignments of the 17.9 kDa enzyme with bound substrate prepare the way for ongoing research of the effects of salt on enzyme flexibility through relaxation studies.     

Time-resolved fluorescence spectroscopy of human adenosine deaminase: effects of enzyme inhibitors on protein conformation

Adenosine deaminase, a purine salvage enzyme essential for immune competence, was studied by time-resolved fluorescence spectroscopy. The heterogeneous emission from this four-tryptophan protein was separated into three lifetime components: tau 1 = 1 ns and tau 2 = 2.2 ns an emission maximum at about 330 nm and tau 3 = 6.3 ns with emission maximum at about 340 nm. Solvent accessibility of the tryptophan emission was probed with polar and nonpolar fluorescence quenchers. Acrylamide, iodide, and trichloroethanol quenched emission from all three components. Acrylamide quenching caused a blue shift in the decay-associated spectrum of component 3. The ground-state analogue enzyme inhibitor purine riboside quenched emission associated with component 2 whereas the transition-state analogue inhibitor deoxycoformycin quenched emission from both components 2 and 3. The quenching due to inhibitor binding had no effect on the lifetimes or emission maxima of the decay-associated spectra. These observations can be explained by a simple model of four tryptophan environments. Quenching studies of the enzyme-inhibitor complexes indicate that adenosine deaminase undergoes different protein conformation changes upon binding of ground- and transition-state analogue inhibitors. The results are consistent with localized structural alterations in the enzyme.     

Lateral enzyme topology in the rough endoplasmic reticulum of rat liver

Summary Rough microsomes were subfractionated on the basis of different properties in order to investigate the nature and extent of the enzyme heterogeneity of these vesicles. A discontinuous gradient, containing monovalent cations allowed the separation of a ribosome-poor membrane fraction which was enriched in electron transport enzymes and relatively poor in phosphatases. Zonal centrifugation on a stabilizing gradient separated 3 fractions characterized by enrichment of electron transport enzymes, glucose-6-phosphatase and adenosinetriphosphatase, respectively. An essentially similar pattern was seen when ribosomes were removed with EDTA and the denuded vesicles subfractionated on a sucrose gradient. Rough microsomes from phenobarbitaltreated rats exhibited the same pattern both qualitatively and quantitatively. It appears that electron transport enzymes and two types of phosphatases are heterogeneously distributed among rough microsomal vesicles.This work has been supported by grants from the Swedish Medical Research Council. The authors wish to thank Mrs. Ulla-Britta Torndal for her valuable technical assistance     

Time-resolved fluorescence study during denaturation and renaturation of curcumin-myoglobin complex

Curcumin influences the transition point, the concentration of denaturant required to effect 50% of the total change, of myoglobin denaturation. Curcumin enhances absorbance of myoglobin at 280 nm with a binding constant K=3.0×10(4) M(-1) whereas fluorescence of curcumin is quenched by myoglobin with a Stern-Volmer association constant of 2.5×10(5) M(-1). Unfolding process of myoglobin-curcumin induces a recovery in fluorescence lifetime loss. The gain in time-resolved fluorescence lifetime during unfolding has been again lost during refolding of curcumin-myoglobin complex by dilution process suggesting partial reversibility of unfolding process for both myoglobin and curcumin-myoglobin complex.     

Effect of the topology and delayed interactions in neuronal networks synchronization

As important as the intrinsic properties of an individual nervous cell stands the network of neurons in which it is embedded and by virtue of which it acquires great part of its responsiveness and functionality. In this study we have explored how the topological properties and conduction delays of several classes of neural networks affect the capacity of their constituent cells to establish well-defined temporal relations among firing of their action potentials. This ability of a population of neurons to produce and maintain a millisecond-precise coordinated firing (either evoked by external stimuli or internally generated) is central to neural codes exploiting precise spike timing for the representation and communication of information. Our results, based on extensive simulations of conductance-based type of neurons in an oscillatory regime, indicate that only certain topologies of networks allow for a coordinated firing at a local and long-range scale simultaneously. Besides network architecture, axonal conduction delays are also observed to be another important factor in the generation of coherent spiking. We report that such communication latencies not only set the phase difference between the oscillatory activity of remote neural populations but determine whether the interconnected cells can set in any coherent firing at all. In this context, we have also investigated how the balance between the network synchronizing effects and the dispersive drift caused by inhomogeneities in natural firing frequencies across neurons is resolved. Finally, we show that the observed roles of conduction delays and frequency dispersion are not particular to canonical networks but experimentally measured anatomical networks such as the macaque cortical network can display the same type of behavior.     

The topology of chromatin-binding domains in the NuRD deacetylase complex

Class I histone deacetylase complexes play essential roles in many nuclear processes. Whilst they contain a common catalytic subunit, they have diverse modes of action determined by associated factors in the distinct complexes. The deacetylase module from the NuRD complex contains three protein domains that control the recruitment of chromatin to the deacetylase enzyme, HDAC1/2. Using biochemical approaches and cryo-electron microscopy, we have determined how three chromatin-binding domains (MTA1-BAH, MBD2/3 and RBBP4/7) are assembled in relation to the core complex so as to facilitate interaction of the complex with the genome. We observe a striking arrangement of the BAH domains suggesting a potential mechanism for binding to di-nucleosomes. We also find that the WD40 domains from RBBP4 are linked to the core with surprising flexibility that is likely important for chromatin engagement. A single MBD2 protein binds asymmetrically to the dimerisation interface of the complex. This symmetry mismatch explains the stoichiometry of the complex. Finally, our structures suggest how the holo-NuRD might assemble on a di-nucleosome substrate.