Guido Tiana

Predictive Polymer Modeling Reveals Coupled Fluctuations in Chromosome Conformation and Transcription

A new level of chromosome organization, topologically associating domains (TADs), was recently uncovered by chromosome conformation capture (3C) techniques. To explore TAD structure and function, we developed a polymer model that can extract the full repertoire of chromatin conformations within TADs from population-based 3C data. This model predicts actual physical distances and to what extent chromosomal contacts vary between cells. It also identifies interactions within single TADs that stabilize boundaries between TADs and allows us to identify and genetically validate key structural elements within TADs. Combining the models predictions with high-resolution DNA FISH and quantitative RNA FISH for TADs within the X-inactivation center (Xic), we dissect the relationship between transcription and spatial proximity to cis-regulatory elements. We demonstrate that contacts between potential regulatory elements occur in the context of fluctuating structures rather than stable loops and propose that such fluctuations may contribute to asymmetric expression in the Xic during X inactivation.

Sustained oscillations and time delays in gene expression of protein Hes1

A number of genes change their expression pattern dynamically by displaying oscillations. In a few important cases these oscillations are sustained and can work as molecular clocks, as in the well-known cases of the circadian clock [1] and the cell cycle [2]. In other cases the oscillations in protein expression are connected with the response to external stimuli, as reported for protein p53 after induction by DNA damage [3] or as reported in association to speci¢city in gene expression [4]. Recently oscillations have been observed for the Hes1 system studied in the very interesting paper [5]. The Hes1 system is particularly interesting because it is connected with cell di¡erentiation, and the temporal oscillations of the Hes1 system may thus be associated with the formation of spatial patterns in development. Oscillations may be obtained by a closed loop of inhibitory couplings, provided that there are at least three di¡erent elements [5,6]. Alternatively, it was noted in the study of the p53 network [7] that a time delay in one of the components can give rise to oscillations also in a system composed of only two species (in this case, p53 and mdm2). We suggest that time delay can be a general mechanism which produces oscillatory responses in a more economical way than three-species inhibitory networks do. A delay in a biological system can typically be related to transcription and translation times, and to transport between cellular compartments. An example is the Hes1 system recently examined in [5]. In this system the protein Hes1 represses the transcription of its own mRNA, and the system displays oscillations in both the concentration of the protein and of its mRNA. To explain this behavior, the authors of [5] suggest a third, hidden factor which would complete a three-species inhibitory network of the kind discussed in [6]. There is however no direct evidence for such a factor. Furthermore, since there is a non-negligible time for transport between the cell nucleus, where the protein controls mRNA transcription, and the cytoplasm, where mRNA is translated into the protein, we feel compelled to suggest a simpler scenario. We want to test the hypothesis that Hes1 and its mRNA are su⁄cient ingredients to produce oscillations in the system. The equations for the concentrations [mRNA] and [Hes1] read

Noncooperative Interactions between Transcription Factors and Clustered DNA Binding Sites Enable Graded Transcriptional Responses to Environmental Inputs

A paradigm in transcriptional regulation is that graded increases in transcription factor (TF) concentration are translated into on/off transcriptional responses by cooperative TF binding to adjacent sites. Digital transcriptional responses underlie the definition of anatomical boundaries during development. Here we show that NF-kappaB, a TF controlling inflammation and immunity, is conversely an analog transcriptional regulator that uses clustered binding sites noncooperatively. We observed that increasing concentrations of NF-kappaB are translated into gradual increments in gene transcription. We provide a thermodynamic interpretation of the experimental observations by combining quantitative measurements and a minimal physical model of an NF-kappaB-dependent promoter. We demonstrate that NF-kappaB binds independently to adjacent sites to promote additive RNA Pol II recruitment and graded transcriptional outputs. These findings reveal an alternative mode of operation of clustered TF binding sites, which might function in biological conditions where the transcriptional output is proportional to the strength of an environmental input.

Time delay as a key to apoptosis induction in the p53 network

Abstract:A feedback mechanism that involves the proteins p53 and mdm2, induces cell death as a controlled response to severe DNA damage. A minimal model for this mechanism demonstrates that the response may be dynamic and connected with the time needed to translate the mdm2 protein. The response takes place if the dissociation constant k between p53 and mdm2 varies from its normal value. Although it is widely believed that it is an increase in k that triggers the response, we show that the experimental behaviour is better described by a decrease in the dissociation constant. The response is quite robust upon changes in the parameters of the system, as required by any control mechanism, except for few weak points, which could be connected with the onset of cancer.

Urea and Guanidinium Chloride Denature Protein L in Different Ways in Molecular Dynamics Simulations

In performing protein-denaturation experiments, it is common to employ different kinds of denaturants interchangeably. We make use of molecular dynamics simulations of Protein L in water, in urea, and in guanidinium chloride (GdmCl) to ascertain if there are any structural differences in the associated unfolding processes. The simulation of proteins in solutions of GdmCl is complicated by the large number of charges involved, making it difficult to set up a realistic force field. Furthermore, at high concentrations of this denaturant, the motion of the solvent slows considerably. The simulations show that the unfolding mechanism depends on the denaturing agent: in urea the beta-sheet is destabilized first, whereas in GdmCl, it is the alpha-helix. Moreover, whereas urea interacts with the protein accumulating in the first solvation shell, GdmCl displays a longer-range electrostatic effect that does not perturb the structure of the solvent close to the protein.

β‐Hairpin conformation of fibrillogenic peptides: Structure and α‐β transition mechanism revealed by molecular dynamics simulations

Understanding the conformational transitions that trigger the aggregation and amyloidogenesis of otherwise soluble peptides at atomic resolution is of fundamental relevance for the design of effective therapeutic agents against amyloid‐related disorders. In the present study the transition from ideal α‐helical to β‐hairpin conformations is revealed by long timescale molecular dynamics simulations in explicit water solvent, for two well‐known amyloidogenic peptides: the H1 peptide from prion protein and the Aβ(12–28) fragment from the Aβ(1–42) peptide responsible for Alzheimers disease. The simulations highlight the unfolding of α‐helices, followed by the formation of bent conformations and a final convergence to ordered in register β‐hairpin conformations. The β‐hairpins observed, despite different sequences, exhibit a common dynamic behavior and the presence of a peculiar pattern of the hydrophobic side‐chains, in particular in the region of the turns. These observations hint at a possible common aggregation mechanism for the onset of different amyloid diseases and a common mechanism in the transition to the β‐hairpin structures. Furthermore the simulations presented herein evidence the stabilization of the α‐helical conformations induced by the presence of an organic fluorinated cosolvent. The results of MD simulation in 2,2,2‐trifluoroethanol (TFE)/water mixture provide further evidence that the peptide coating effect of TFE molecules is responsible for the stabilization of the soluble helical conformation. Proteins 2004.

Folding and aggregation of designed proteins

Protein aggregation is studied by following the simultaneous folding of two designed identical 20-letter amino acid chains within the framework of a lattice model and using Monte Carlo simulations. It is found that protein aggregation is determined by elementary structures (partially folded intermediates) controlled by local contacts among some of the most strongly interacting amino acids and formed at an early stage in the folding process.

Understanding the determinants of stability and folding of small globular proteins from their energetics

The results of minimal model calculations indicate that the stability and the kinetic accessibility of the native state of small globular proteins are controlled by few “hot” sites. By means of molecular dynamics simulations around the native conformation, which describe the protein and the surrounding solvent at the all‐atom level, an accurate and compact energetic map of the native state of the protein is generated. This map is further simplified by means of an eigenvalue decomposition. The components of the eigenvector associated with the lowest eigenvalue indicate which hot sites are likely to be responsible for the stability and for the rapid folding of the protein. The comparison of the results of the model with the findings of mutagenesis experiments performed for four small proteins show that the eigenvalue decomposition method is able to identify between 60% and 80% of these (hot) sites.

Exploring the protein G helix free-energy surface by solute tempering metadynamics.

The free‐energy landscape of the α‐helix of protein G is studied by means of metadynamics coupled with a solute tempering algorithm. Metadynamics allows to overcome large energy barriers, whereas solute tempering improves the sampling with an affordable computational effort. From the sampled free‐energy surface we are able to reproduce a number of experimental observations, such as the fact that the lowest minimum corresponds to a globular conformation displaying some degree of β‐structure, that the helical state is metastable and involves only 65% of the chain. The calculations also show that the system populates consistently a π‐helix state and that the hydrophobic staple motif is present only in the free‐energy minimum associated with the helices, and contributes to their stabilization. The use of metadynamics coupled with solute tempering results then particularly suitable to provide the thermodynamics of a short peptide, and its computational efficiency is promising to deal with larger proteins. Proteins 2008.

Use of the Metropolis algorithm to simulate the dynamics of protein chains

The Metropolis implementation of the Monte Carlo algorithm has been developed to study the equilibrium thermodynamics of many-body systems. Choosing small trial moves, the trajectories obtained applying this algorithm agree with those obtained by Langevins dynamics. Applying this procedure to a simplified protein model, it is possible to show that setting a threshold of 1∘ on the movement of the dihedrals of the protein backbone in a single Monte Carlo step, the mean quantities associated with the off-equilibrium dynamics (e.g., energy, RMSD, etc.) are well reproduced, while the good description of higher moments requires smaller moves. An important result is that the time duration of a Monte Carlo step depends linearly on the temperature, something which should be accounted for when doing simulations at different temperatures.