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 model's 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.

Inheritance of H3K9 methylation regulates genome architecture in Drosophila early embryos.

Constitutive heterochromatin is essential for transcriptional silencing and genome integrity. The establishment of constitutive heterochromatin in early embryos and its role in early fruitfly development are unknown. Lysine 9 trimethylation of histone H3 (H3K9me3) and recruitment of its epigenetic reader, heterochromatin protein 1a (HP1a), are hallmarks of constitutive heterochromatin. Here, we show that H3K9me3 is transmitted from the maternal germline to the next generation. Maternally inherited H3K9me3, and the histone methyltransferases (HMT) depositing it, are required for the organization of constitutive heterochromatin: early embryos lacking H3K9 methylation display de-condensation of pericentromeric regions, centromere-centromere de-clustering, mitotic defects, and nuclear shape irregularities, resulting in embryo lethality. Unexpectedly, quantitative CUT&Tag and 4D microscopy measurements of HP1a coupled with biophysical modeling revealed that H3K9me2/3 is largely dispensable for HP1a recruitment. Instead, the main function of H3K9me2/3 at this developmental stage is to drive HP1a clustering and subsequent heterochromatin compaction. Our results show that HP1a binding to constitutive heterochromatin in the absence of H3K9me2/3 is not sufficient to promote proper embryo development and heterochromatin formation. The loss of H3K9 HMTs and H3K9 methylation alters genome organization and hinders embryonic development.

HP1 drives de novo 3D genome reorganization in early Drosophila embryos.

Fundamental features of 3D genome organization are established de novo in the early embryo, including clustering of pericentromeric regions, the folding of chromosome arms and the segregation of chromosomes into active (A-) and inactive (B-) compartments. However, the molecular mechanisms that drive de novo organization remain unknown1,2. Here, by combining chromosome conformation capture (Hi-C), chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq), 3D DNA fluorescence in situ hybridization (3D DNA FISH) and polymer simulations, we show that heterochromatin protein 1a (HP1a) is essential for de novo 3D genome organization during Drosophila early development. The binding of HP1a at pericentromeric heterochromatin is required to establish clustering of pericentromeric regions. Moreover, HP1a binding within chromosome arms is responsible for overall chromosome folding and has an important role in the formation of B-compartment regions. However, depletion of HP1a does not affect the A-compartment, which suggests that a different molecular mechanism segregates active chromosome regions. Our work identifies HP1a as an epigenetic regulator that is involved in establishing the global structure of the genome in the early embryo.

The denatured state of HIV-1 protease under native conditions.

The denatured state of several proteins has been shown to display transient structures that are relevant for folding, stability, and aggregation. To detect them by nuclear magnetic resonance (NMR) spectroscopy, the denatured state must be stabilized by chemical agents or changes in temperature. This makes the environment different from that experienced in biologically relevant processes. Using high-resolution heteronuclear NMR spectroscopy, we have characterized several denatured states of a monomeric variant of HIV-1 protease, which is natively structured in water, induced by different concentrations of urea, guanidinium chloride, and acetic acid. We have extrapolated the chemical shifts and the relaxation parameters to the denaturant-free denatured state at native conditions, showing that they converge to the same values. Subsequently, we characterized the conformational properties of this biologically relevant denatured state under native conditions by advanced molecular dynamics simulations and validated the results by comparison to experimental data. We show that the denatured state of HIV-1 protease under native conditions displays rich patterns of transient native and non-native structures, which could be of relevance to its guidance through a complex folding process.

Assessing the accuracy of direct-coupling analysis for RNA contact prediction.

Many noncoding RNAs are known to play a role in the cell directly linked to their structure. Structure prediction based on the sole sequence is, however, a challenging task. On the other hand, thanks to the low cost of sequencing technologies, a very large number of homologous sequences are becoming available for many RNA families. In the protein community, the idea of exploiting the covariance of mutations within a family to predict the protein structure using the direct-coupling-analysis (DCA) method has emerged in the last decade. The application of DCA to RNA systems has been limited so far. We here perform an assessment of the DCA method on 17 riboswitch families, comparing it with the commonly used mutual information analysis and with state-of-the-art R-scape covariance method. We also compare different flavors of DCA, including mean-field, pseudolikelihood, and a proposed stochastic procedure (Boltzmann learning) for solving exactly the DCA inverse problem. Boltzmann learning outperforms the other methods in predicting contacts observed in high-resolution crystal structures.

Key interaction patterns in proteins revealed by cluster expansion of the partition function.

The native conformation of structured proteins is stabilized by a complex network of interactions. We analyzed the elementary patterns that constitute such network and ranked them according to their importance in shaping protein sequence design. To achieve this goal, we employed a cluster expansion of the partition function in the space of sequences and evaluated numerically the statistical importance of each cluster. An important feature of this procedure is that it is applied to a dense finite system. We found that patterns that contribute most to the partition function are cycles with even numbers of nodes, while cliques are typically detrimental. Each cluster also gives a contribute to the sequence entropy, which is a measure of the evolutionary designability of a fold. We compared the entropies associated with different interaction patterns to their abundances in the native structures of real proteins.

Managing Experimental 3D Structures in the Beyond-Rule-of-5 Chemical Space: The Case of Rifampicin.

The beyond-Rule-of-5 (bRo5) chemical space is a source of new oral drugs and includes large and flexible compounds. Because of their size and conformational variability, bRo5 molecules assume different privileged conformations in the compartments of human body, i. e., they can exhibit chameleonic properties. The elucidation of the ensemble of 3D structures explored by such molecules under different conditions is therefore critical to check the role played by chameleonicity to modulate cell permeability. Here we characterized the conformational ensembles of rifampicin, a bRo5 drug, in polar and nonpolar solvents and in the solid state. We performed NMR experiments, analyzed their results with a novel algorithm and set-up a pool of ad hoc in silico strategies to investigate crystallographic structures retrieved from the CSD. Moreover, a polarity descriptor often related to permeability (SA-3D-PSA) was calculated for all the conformers and its variation with the environment analyzed. Results showed that the conformational behavior of rifampicin in solution and in the solid state is not superposable. The identification of dynamic intramolecular hydrogen bonds can be assessed by NMR spectroscopy but not by X-ray structures. Moreover, SA-3D-PSA revealed that dynamic IMHBs do not provide rifampicin with chameleonic properties. Overall, this study highlights that the peculiarity of rifampicin, which is cell permeable probably because of the presence of static IMHBs but is devoid of any chameleonic behavior, can be assessed by a proper analysis of experimental 3D structures.

Evolution of frustrated and stabilising contacts in reconstructed ancient proteins.

Energetic properties of a protein are a major determinant of its evolutionary fitness. Using a reconstruction algorithm, dating the reconstructed proteins and calculating the interaction network between their amino acids through a coevolutionary approach, we studied how the interactions that stabilise 890 proteins, belonging to five families, evolved for billions of years. In particular, we focused our attention on the network of most strongly attractive contacts and on that of poorly optimised, frustrated contacts. Our results support the idea that the cluster of most attractive interactions extends its size along evolutionary time, but from the data, we cannot conclude that protein stability or that the degree of frustration tends always to decrease.

Reciprocal insulation analysis of Hi-C data shows that TADs represent a functionally but not structurally privileged scale in the hierarchical folding of chromosomes.

Understanding how regulatory sequences interact in the context of chromosomal architecture is a central challenge in biology. Chromosome conformation capture revealed that mammalian chromosomes possess a rich hierarchy of structural layers, from multi-megabase compartments to sub-megabase topologically associating domains (TADs) and sub-TAD contact domains. TADs appear to act as regulatory microenvironments by constraining and segregating regulatory interactions across discrete chromosomal regions. However, it is unclear whether other (or all) folding layers share similar properties, or rather TADs constitute a privileged folding scale with maximal impact on the organization of regulatory interactions. Here, we present a novel algorithm named CaTCH that identifies hierarchical trees of chromosomal domains in Hi-C maps, stratified through their reciprocal physical insulation, which is a single and biologically relevant parameter. By applying CaTCH to published Hi-C data sets, we show that previously reported folding layers appear at different insulation levels. We demonstrate that although no structurally privileged folding level exists, TADs emerge as a functionally privileged scale defined by maximal boundary enrichment in CTCF and maximal cell-type conservation. By measuring transcriptional output in embryonic stem cells and neural precursor cells, we show that the likelihood that genes in a domain are coregulated during differentiation is also maximized at the scale of TADs. Finally, we observe that regulatory sequences occur at genomic locations corresponding to optimized mutual interactions at the same scale. Our analysis suggests that the architectural functionality of TADs arises from the interplay between their ability to partition interactions and the specific genomic position of regulatory sequences.

Determination of Structural Ensembles of Flexible Molecules in Solution from NMR Data Undergoing Spin Diffusion.

Spin diffusion is a formidable problem when interpreting NMR data of chemical compounds. We developed a method to reconstruct the conformational ensemble of flexible molecules displaying spin diffusion, which minimizes the subjective bias in the interpretation of experimental data and which can be used routinely to obtain sets of structures with the correct thermodynamic weights. We showed in the case of a flexible molecule that the correct conformational ensemble is quite different from that obtained with standard methods.

A method for partitioning the information contained in a protein sequence between its structure and function.

Proteins employ the information stored in the genetic code and translated into their sequences to carry out well-defined functions in the cellular environment. The possibility to encode for such functions is controlled by the balance between the amount of information supplied by the sequence and that left after that the protein has folded into its structure. We study the amount of information necessary to specify the protein structure, providing an estimate that keeps into account the thermodynamic properties of protein folding. We thus show that the information remaining in the protein sequence after encoding for its structure (the 'information gap') is very close to what needed to encode for its function and interactions. Then, by predicting the information gap directly from the protein sequence, we show that it may be possible to use these insights from information theory to discriminate between ordered and disordered proteins, to identify unknown functions, and to optimize artificially-designed protein sequences.

Spontaneous domain formation in disordered copolymers as a mechanism for chromosome structuring.

Motivated by the problem of domain formation in chromosomes, we studied a co-polymer model where only a subset of the monomers feel attractive interactions. These monomers are displaced randomly from a regularly-spaced pattern, thus introducing some quenched disorder in the system. Previous work has shown that in the case of regularly-spaced interacting monomers this chain can fold into structures characterized by multiple distinct domains of consecutive segments. In each domain, attractive interactions are balanced by the entropy cost of forming loops. We show by advanced replica-exchange simulations that adding disorder in the position of the interacting monomers further stabilizes these domains. The model suggests that the partitioning of the chain into well-defined domains of consecutive monomers is a spontaneous property of heteropolymers. In the case of chromosomes, evolution could have acted on the spacing of interacting monomers to modulate in a simple way the underlying domains for functional reasons.

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.

An implementation of the maximum-caliber principle by replica-averaged time-resolved restrained simulations.

Inferential methods can be used to integrate experimental informations and molecular simulations. The maximum entropy principle provides a framework for using equilibrium experimental data, and it has been shown that replica-averaged simulations, restrained using a static potential, are a practical and powerful implementation of such a principle. Here we show that replica-averaged simulations restrained using a time-dependent potential are equivalent to the principle of maximum caliber, the dynamic version of the principle of maximum entropy, and thus may allow us to integrate time-resolved data in molecular dynamics simulations. We provide an analytical proof of the equivalence as well as a computational validation making use of simple models and synthetic data. Some limitations and possible solutions are also discussed.

FRET studies of various conformational states adopted by transthyretin.

Transthyretin (TTR) is an extracellular protein able to deposit into well-defined protein aggregates called amyloid, in pathological conditions known as senile systemic amyloidosis, familial amyloid polyneuropathy, familial amyloid cardiomyopathy and leptomeningeal amyloidosis. At least three distinct partially folded states have been described for TTR, including the widely studied amyloidogenic state at mildly acidic pH. Here, we have used fluorescence resonance energy transfer (FRET) experiments in a monomeric variant of TTR (M-TTR) and in its W41F and W79F mutants, taking advantage of the presence of a unique, solvent-exposed, cysteine residue at position 10, that we have labelled with a coumarin derivative (DACM, acceptor), and of the two natural tryptophan residues at positions 41 and 79 (donors). Trp41 is located in an ideal position as it is one of the residues of ß-strand C, whose degree of unfolding is debated. We found that the amyloidogenic state at low pH has the same FRET efficiency as the folded state at neutral pH in both M-TTR and W79F-M-TTR, indicating an unmodified Cys10-Trp41 distance. The partially folded state populated at low denaturant concentrations also has a similar FRET efficiency, but other spectroscopic probes indicate that it is distinct from the amyloidogenic state at acidic pH. By contrast, the off-pathway state accumulating transiently during refolding has a higher FRET efficiency, indicating non-native interactions that reduce the Cys10-Trp41 spatial distance, revealing a third distinct conformational state. Overall, our results clarify a negligible degree of unfolding of ß-strand C in the formation of the amyloidogenic state and establish the concept that TTR is a highly plastic protein able to populate at least three distinct conformational states.

A Combined NMR-Computational Study of the Interaction between Influenza Virus Hemagglutinin and Sialic Derivatives from Human and Avian Receptors on the Surface of Transfected Cells.

The development of small-molecule inhibitors of influenza virus Hemagglutinin could be relevant to the opposition of the diffusion of new pandemic viruses. In this work, we made use of Nuclear Magnetic Resonance (NMR) spectroscopy to study the interaction between two derivatives of sialic acid, Neu5Ac-α-(2,6)-Gal-β-(1⁻4)-GlcNAc and Neu5Ac-α-(2,3)-Gal-β-(1⁻4)-GlcNAc, and hemagglutinin directly expressed on the surface of recombinant human cells. We analyzed the interaction of these trisaccharides with 293T cells transfected with the H5 and H1 variants of hemagglutinin, which thus retain their native trimeric conformation in such a realistic environment. By exploiting the magnetization transfer between the protein and the ligand, we obtained evidence of the binding event, and identified the epitope. We analyzed the conformational features of the glycans with an approach combining NMR spectroscopy and data-driven molecular dynamics simulations, thus obtaining useful information for an efficient drug design.

Cold Denaturation of the HIV-1 Protease Monomer.

The human immunodeficiency virus-1 (HIV-1) protease is a complex protein that in its active form adopts a homodimer dominated by ß-sheet structures. We have discovered a cold-denatured state of the monomeric subunit of HIV-1 protease that is populated above 0 °C and therefore directly accessible to various spectroscopic approaches. Using nuclear magnetic resonance secondary chemical shifts, temperature coefficients, and protein dynamics, we suggest that the cold-denatured state populates a compact wet globule containing transient non-native-like α-helical elements. From the linearity of the temperature coefficients and the hydrodynamic radii, we propose that the overall architecture of the cold-denatured state is maintained over the temperature range studied.

SAGE: A Fast Computational Tool for Linear Epitope Grafting onto a Foreign Protein Scaffold.

Computational design is becoming a driving force of structural vaccinology, whereby protein antigens are engineered to generate new biomolecules with optimized immunological properties. In particular, the design of new proteins that contain multiple, different epitopes can potentially provide novel highly efficient vaccine candidates. In this context, epitope grafting, which entails the transplantation of an antibody recognition motif from one protein onto a different protein scaffold (possibly containing other immunoreactive sequences) holds great promise for the realization of superantigens. Herein, we present SAGE (strategy for alignment and grafting of epitopes), an automated computational tool for the implantation of immunogenic epitopes onto a given scaffold. It is based on the comparison between the expected secondary structures of the candidates to be grafted with all the secondary structures in the target scaffold. Evaluating the differences both in sequence and in structure between the epitope and the scaffold returns a ranking of most probable molecules containing the new antigenic sequence. We validate this approach identifying the grafting positions obtained in previous works by experimental and computational methods, proving an efficient, flexible, and fast tool to perform the initial scanning for epitope grafting. This approach is fully general and may be applied to any target antigen and candidate epitopes with known 3D structures.

How likely are oscillations in a genetic feedback loop with delay?

Some genetic control networks display temporal oscillations as a result of delays in their homeostatic control. A relevant question about these systems is whether the oscillating regime is a rare feature, or it corresponds to a sizeable volume of the space of parameters. The answer is not trivial mainly due to the large number of parameters controlling the rate equations which describe the network. We have developed an efficient sampling scheme of the parameter space, based on a Monte Carlo algorithm, and applied it to a two-node system with delay, characterised by a 8-dimension parameter space. The result is that the volume fraction of the parameter space associated with oscillations is small but not negligible, and it is weakly dependent on the duration of the delay. The most critical parameter to control oscillations is the coupling production rates, which must have opposite sign, giving rise to a negative feedback loop. The oscillating regions are connected except along the equilibrium constants between the two species, not allowing neutral evolution along this parameter.

Structural Fluctuations of the Chromatin Fiber within Topologically Associating Domains.

Experiments based on chromosome conformation capture have shown that mammalian genomes are partitioned into topologically associating domains (TADs), within which the chromatin fiber preferentially interacts. TADs may provide three-dimensional scaffolds allowing genes to contact their appropriate distal regulatory DNA sequences (e.g., enhancers) and thus to be properly regulated. Understanding the cell-to-cell and temporal variability of the chromatin fiber within TADs, and what determines them, is thus of great importance to better understand transcriptional regulation. We recently described an equilibrium polymer model that can accurately predict cell-to-cell variation of chromosome conformation within single TADs, from chromosome conformation capture-based data. Here we further analyze the conformational and energetic properties of our model. We show that the chromatin fiber within TADs can easily fluctuate between several conformational states, which are hierarchically organized and are not separated by important free energy barriers, and that this is facilitated by the fact that the chromatin fiber within TADs is close to the onset of the coil-globule transition. We further show that in this dynamic state the properties of the chromatin fiber, and its contact probabilities in particular, are determined in a nontrivial manner not only by site-specific interactions between strongly interacting loci along the fiber, but also by nonlocal correlations between pairs of contacts. Finally, we use live-cell experiments to measure the dynamics of the chromatin fiber in mouse embryonic stem cells, in combination with dynamical simulations, and predict that conformational changes within one TAD are likely to occur on timescales that are much shorter than the duration of one cell cycle. This suggests that genes and their regulatory elements may come together and disassociate several times during a cell cycle. These results have important implications for transcriptional regulation as they support the concept of highly dynamic interactions driven by a complex interplay between site-specific interactions and the intrinsic biophysical properties of the chromatin fiber.