Histone H1 protects telomeric repeats from H3K27me3 invasion in Arabidopsis.

While the pivotal role of linker histone H1 in shaping nucleosome organization is well established, its functional interplays with chromatin factors along the epigenome are just starting to emerge. Here we show that, in Arabidopsis, as in mammals, H1 occupies Polycomb Repressive Complex 2 (PRC2) target genes where it favors chromatin condensation and H3K27me3 deposition. We further show that, contrasting with its conserved function in PRC2 activation at genes, H1 selectively prevents H3K27me3 accumulation at telomeres and large pericentromeric interstitial telomeric repeat (ITR) domains by restricting DNA accessibility to Telomere Repeat Binding (TRB) proteins, a group of H1-related Myb factors mediating PRC2 cis recruitment. This study provides a mechanistic framework by which H1 avoids the formation of gigantic H3K27me3-rich domains at telomeric sequences and contributes to safeguard nucleus architecture.

LEVELNET to visualize, explore, and compare protein-protein interaction networks.

Physical interactions between proteins are central to all biological processes. Yet, the current knowledge of who interacts with whom in the cell and in what manner relies on partial, noisy, and highly heterogeneous data. Thus, there is a need for methods comprehensively describing and organizing such data. LEVELNET is a versatile and interactive tool for visualizing, exploring, and comparing protein-protein interaction (PPI) networks inferred from different types of evidence. LEVELNET helps to break down the complexity of PPI networks by representing them as multi-layered graphs and by facilitating the direct comparison of their subnetworks toward biological interpretation. It focuses primarily on the protein chains whose 3D structures are available in the Protein Data Bank. We showcase some potential applications, such as investigating the structural evidence supporting PPIs associated to specific biological processes, assessing the co-localization of interaction partners, comparing the PPI networks obtained through computational experiments versus homology transfer, and creating PPI benchmarks with desired properties.

Deep Local Analysis deconstructs protein-protein interfaces and accurately estimates binding affinity changes upon mutation.

MOTIVATION: The spectacular recent advances in protein and protein complex structure prediction hold promise for reconstructing interactomes at large-scale and residue resolution. Beyond determining the 3D arrangement of interacting partners, modeling approaches should be able to unravel the impact of sequence variations on the strength of the association. RESULTS: In this work, we report on Deep Local Analysis, a novel and efficient deep learning framework that relies on a strikingly simple deconstruction of protein interfaces into small locally oriented residue-centered cubes and on 3D convolutions recognizing patterns within cubes. Merely based on the two cubes associated with the wild-type and the mutant residues, DLA accurately estimates the binding affinity change for the associated complexes. It achieves a Pearson correlation coefficient of 0.735 on about 400 mutations on unseen complexes. Its generalization capability on blind datasets of complexes is higher than the state-of-the-art methods. We show that taking into account the evolutionary constraints on residues contributes to predictions. We also discuss the influence of conformational variability on performance. Beyond the predictive power on the effects of mutations, DLA is a general framework for transferring the knowledge gained from the available non-redundant set of complex protein structures to various tasks. For instance, given a single partially masked cube, it recovers the identity and physicochemical class of the central residue. Given an ensemble of cubes representing an interface, it predicts the function of the complex. AVAILABILITY AND IMPLEMENTATION: Source code and models are available at http://gitlab.lcqb.upmc.fr/DLA/DLA.git.

Investigation of Fumasep® FAA3-50 Membranes in Alkaline Direct Methanol Fuel Cells.

This paper describes the use of a commercial Fumasep® FAA3-50 membrane as an anion exchange membrane (AEM) in alkaline direct methanol fuel cells (ADMFCs). The membrane, supplied in bromide form, is first exchanged in chloride and successively in the hydroxide form. Anionic conductivity measurements are carried out in both a KOH aqueous solution and in a KOH/methanol mixture. AEM-DMFC tests are performed by feeding 1 M methanol, with or without 1 M KOH as a supporting electrolyte. A maximum power density of 5.2 mW cm-2 at 60 °C and 33.2 mW cm-2 at 80 °C is reached in KOH-free feeding and in the alkaline mixture, respectively. These values are in good agreement with some results in the literature obtained with similar experimental conditions but with different anion exchange membranes (AEMs). Finally, methanol crossover is investigated and corresponds to a maximum value of 1.45 × 10-8 mol s-1 cm-2 at 50 °C in a 1 M KOH methanol solution, thus indicating that the Fumasep® FAA3-50 membrane in OH form is a good candidate for ADMFC application.

Soft disorder modulates the assembly path of protein complexes.

The relationship between interactions, flexibility and disorder in proteins has been explored from many angles over the years: folding upon binding, flexibility of the core relative to the periphery, entropy changes, etc. In this work, we provide statistical evidence for the involvement of highly mobile and disordered regions in complex assembly. We ordered the entire set of X-ray crystallographic structures in the Protein Data Bank into hierarchies of progressive interactions involving identical or very similar protein chains, yielding 40205 hierarchies of protein complexes with increasing numbers of partners. We then examine them as proxies for the assembly pathways. Using this database, we show that upon oligomerisation, the new interfaces tend to be observed at residues that were characterised as softly disordered (flexible, amorphous or missing residues) in the complexes preceding them in the hierarchy. We also rule out the possibility that this correlation is just a surface effect by restricting the analysis to residues on the surface of the complexes. Interestingly, we find that the location of soft disordered residues in the sequence changes as the number of partners increases. Our results show that there is a general mechanism for protein assembly that involves soft disorder and modulates the way protein complexes are assembled. This work highlights the difficulty of predicting the structure of large protein complexes from sequence and emphasises the importance of linking predictors of soft disorder to the next generation of predictors of complex structure. Finally, we investigate the relationship between the Alphafold2's confidence metric pLDDT for structure prediction in unbound versus bound structures, and soft disorder. We show a strong correlation between Alphafold2 low confidence residues and the union of all regions of soft disorder observed in the hierarchy. This paves the way for using the pLDDT metric as a proxy for predicting interfaces and assembly paths.

Deep Local Analysis evaluates protein docking conformations with locally oriented cubes.

MOTIVATION: With the recent advances in protein 3D structure prediction, protein interactions are becoming more central than ever before. Here, we address the problem of determining how proteins interact with one another. More specifically, we investigate the possibility of discriminating near-native protein complex conformations from incorrect ones by exploiting local environments around interfacial residues. RESULTS: Deep Local Analysis (DLA)-Ranker is a deep learning framework applying 3D convolutions to a set of locally oriented cubes representing the protein interface. It explicitly considers the local geometry of the interfacial residues along with their neighboring atoms and the regions of the interface with different solvent accessibility. We assessed its performance on three docking benchmarks made of half a million acceptable and incorrect conformations. We show that DLA-Ranker successfully identifies near-native conformations from ensembles generated by molecular docking. It surpasses or competes with other deep learning-based scoring functions. We also showcase its usefulness to discover alternative interfaces. AVAILABILITY AND IMPLEMENTATION: http://gitlab.lcqb.upmc.fr/dla-ranker/DLA-Ranker.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

iBIS2Analyzer: a web server for a phylogeny-driven coevolution analysis of protein families.

Residue coevolution within and between proteins is used as a marker of physical interaction and/or residue functional cooperation. Pairs or groups of coevolving residues are extracted from multiple sequence alignments based on a variety of computational approaches. However, coevolution signals emerging in subsets of sequences might be lost if the full alignment is considered. iBIS2Analyzer is a web server dedicated to a phylogeny-driven coevolution analysis of protein families with different evolutionary pressure. It is based on the iterative version, iBIS2, of the coevolution analysis method BIS, Blocks in Sequences. iBIS2 is designed to iteratively select and analyse subtrees in phylogenetic trees, possibly large and comprising thousands of sequences. With iBIS2Analyzer, openly accessible at http://ibis2analyzer.lcqb.upmc.fr/, the user visualizes, compares and inspects clusters of coevolving residues by mapping them onto sequences, alignments or structures of choice, greatly simplifying downstream analysis steps. A rich and interactive graphic interface facilitates the biological interpretation of the results.

Crystal structure of chloroplast fructose-1,6-bisphosphate aldolase from the green alga Chlamydomonas reinhardtii.

The Calvin-Benson cycle fixes carbon dioxide into organic triosephosphates through the collective action of eleven conserved enzymes. Regeneration of ribulose-1,5-bisphosphate, the substrate of Rubisco-mediated carboxylation, requires two lyase reactions catalyzed by fructose-1,6-bisphosphate aldolase (FBA). While cytoplasmic FBA has been extensively studied in non-photosynthetic organisms, functional and structural details are limited for chloroplast FBA encoded by oxygenic phototrophs. Here we determined the crystal structure of plastidial FBA from the unicellular green alga Chlamydomonas reinhardtii (Cr). We confirm that CrFBA folds as a TIM barrel, describe its catalytic pocket and homo-tetrameric state. Multiple sequence profiling classified the photosynthetic paralogs of FBA in a distinct group from non-photosynthetic paralogs. We mapped the sites of thiol- and phospho-based post-translational modifications known from photosynthetic organisms and predict their effects on enzyme catalysis.

From complete cross-docking to partners identification and binding sites predictions.

Proteins ensure their biological functions by interacting with each other. Hence, characterising protein interactions is fundamental for our understanding of the cellular machinery, and for improving medicine and bioengineering. Over the past years, a large body of experimental data has been accumulated on who interacts with whom and in what manner. However, these data are highly heterogeneous and sometimes contradictory, noisy, and biased. Ab initio methods provide a means to a "blind" protein-protein interaction network reconstruction. Here, we report on a molecular cross-docking-based approach for the identification of protein partners. The docking algorithm uses a coarse-grained representation of the protein structures and treats them as rigid bodies. We applied the approach to a few hundred of proteins, in the unbound conformations, and we systematically investigated the influence of several key ingredients, such as the size and quality of the interfaces, and the scoring function. We achieved some significant improvement compared to previous works, and a very high discriminative power on some specific functional classes. We provide a readout of the contributions of shape and physico-chemical complementarity, interface matching, and specificity, in the predictions. In addition, we assessed the ability of the approach to account for protein surface multiple usages, and we compared it with a sequence-based deep learning method. This work may contribute to guiding the exploitation of the large amounts of protein structural models now available toward the discovery of unexpected partners and their complex structure characterisation.

Influence of Ionomer Content in the Catalytic Layer of MEAs Based on Aquivion® Ionomer.

Perfluorinated sulfonic acid (PFSA) polymers such as Nafion® are widely used for both electrolyte membranes and ionomers in the catalytic layer of membrane-electrode assemblies (MEAs) because of their high protonic conductivity, σH, as well as chemical and thermal stability. The use of PFSA polymers with shorter side chains and lower equivalent weight (EW) than Nafion®, such as Aquivion® PFSA ionomers, is a valid approach to improve fuel cell performance and stability under drastic operative conditions such as those related to automotive applications. In this context, it is necessary to optimize the composition of the catalytic ink, according to the different ionomer characteristics. In this work, the influence of the ionomer amount in the catalytic layer was studied, considering the dispersing agent used to prepare the electrode (water or ethanol). Electrochemical studies were carried out in a single cell in the presence of H2-air, at intermediate temperatures (80-95 °C), low pressure, and reduced humidity ((50% RH). %). The best fuel cell performance was found for 26 wt.% Aquivion® at the electrodes using ethanol for the ink preparation, associated to a maximum catalyst utilization.

Polydopamine Coated CeO2 as Radical Scavenger Filler for Aquivion Membranes with High Proton Conductivity.

CeO2 nanoparticles were coated with polydopamine (PDA) by dopamine polymerization in water dispersions of CeO2 and characterized by Infrared and Near Edge X-ray Absorption Fine Structure spectroscopy, Transmission Electron Microscopy, Thermogravimetric analysis and X-ray diffraction. The resulting materials (PDAx@CeO2, with x = PDA wt% = 10, 25, 50) were employed as fillers of composite proton exchange membranes with Aquivion 830 as ionomer, to reduce the ionomer chemical degradation due to hydroxyl and hydroperoxyl radicals. Membranes, loaded with 3 and 5 wt% PDAx@CeO2, were prepared by solution casting and characterized by conductivity measurements at 80 and 110 °C, with relative humidity ranging from 50 to 90%, by accelerated ex situ degradation tests with the Fenton reagent, as well as by in situ open circuit voltage stress tests. In comparison with bare CeO2, the PDA coated filler mitigates the conductivity drop occurring at increasing CeO2 loading especially at 110 °C and 50% relative humidity but does not alter the radical scavenger efficiency of bare CeO2 for loadings up to 4 wt%. Fluoride emission rate data arising from the composite membrane degradation are in agreement with the corresponding changes in membrane mass and conductivity.

A fusion peptide in preS1 and the human protein disulfide isomerase ERp57 are involved in hepatitis B virus membrane fusion process.

Cell entry of enveloped viruses relies on the fusion between the viral and plasma or endosomal membranes, through a mechanism that is triggered by a cellular signal. Here we used a combination of computational and experimental approaches to unravel the main determinants of hepatitis B virus (HBV) membrane fusion process. We discovered that ERp57 is a host factor critically involved in triggering HBV fusion and infection. Then, through modeling approaches, we uncovered a putative allosteric cross-strand disulfide (CSD) bond in the HBV S glycoprotein and we demonstrate that its stabilization could prevent membrane fusion. Finally, we identified and characterized a potential fusion peptide in the preS1 domain of the HBV L glycoprotein. These results underscore a membrane fusion mechanism that could be triggered by ERp57, allowing a thiol/disulfide exchange reaction to occur and regulate isomerization of a critical CSD, which ultimately leads to the exposition of the fusion peptide.

MyCLADE: a multi-source domain annotation server for sequence functional exploration.

The ever-increasing number of genomic and metagenomic sequences accumulating in our databases requires accurate approaches to explore their content against specific domain targets. MyCLADE is a user-friendly webserver designed for targeted functional profiling of genomic and metagenomic sequences based on a database of a few million probabilistic models of Pfam domains. It uses the MetaCLADE multi-source domain annotation strategy, modelling domains based on multiple probabilistic profiles. MyCLADE takes a list of protein sequences and possibly a target set of domains/clans as input and, for each sequence, it provides a domain architecture built from the targeted domains or from all Pfam domains. It is linked to the Pfam and QuickGO databases in multiple ways for easy retrieval of domain and clan information. E-value, bit-score, domain-dependent probability scores and logos representing the match of the model with the sequence are provided to help the user to assess the quality of each annotation. Availability and implementation: MyCLADE is freely available at http://www.lcqb.upmc.fr/myclade.

The complexity of protein interactions unravelled from structural disorder.

The importance of unstructured biology has quickly grown during the last decades accompanying the explosion of the number of experimentally resolved protein structures. The idea that structural disorder might be a novel mechanism of protein interaction is widespread in the literature, although the number of statistically significant structural studies supporting this idea is surprisingly low. At variance with previous works, our conclusions rely exclusively on a large-scale analysis of all the 134337 X-ray crystallographic structures of the Protein Data Bank averaged over clusters of almost identical protein sequences. In this work, we explore the complexity of the organisation of all the interaction interfaces observed when a protein lies in alternative complexes, showing that interfaces progressively add up in a hierarchical way, which is reflected in a logarithmic law for the size of the union of the interface regions on the number of distinct interfaces. We further investigate the connection of this complexity with different measures of structural disorder: the standard missing residues and a new definition, called "soft disorder", that covers all the flexible and structurally amorphous residues of a protein. We show evidences that both the interaction interfaces and the soft disordered regions tend to involve roughly the same amino-acids of the protein, and preliminary results suggesting that soft disorder spots those surface regions where new interfaces are progressively accommodated by complex formation. In fact, our results suggest that structurally disordered regions not only carry crucial information about the location of alternative interfaces within complexes, but also about the order of the assembly. We verify these hypotheses in several examples, such as the DNA binding domains of P53 and P73, the C3 exoenzyme, and two known biological orders of assembly. We finally compare our measures of structural disorder with several disorder bioinformatics predictors, showing that these latter are optimised to predict the residues that are missing in all the alternative structures of a protein and they are not able to catch the progressive evolution of the disordered regions upon complex formation. Yet, the predicted residues, when not missing, tend to be characterised as soft disordered regions.

Anionic Exchange Membrane for Photo-Electrolysis Application.

Tandem photo-electro-chemical cells composed of an assembly of a solid electrolyte membrane and two low-cost photoelectrodes have been developed to generate green solar fuel from water-splitting. In this regard, an anion-exchange polymer-electrolyte membrane, able to separate H2 evolved at the photocathode from O2 at the photoanode, was investigated in terms of ionic conductivity, corrosion mitigation, and light transmission for a tandem photo-electro-chemical configuration. The designed anionic membranes, based on polysulfone polymer, contained positive fixed functionalities on the side chains of the polymeric network, particularly quaternary ammonium species counterbalanced by hydroxide anions. The membrane was first investigated in alkaline solution, KOH or NaOH at different concentrations, to optimize the ion-exchange process. Exchange in 1M KOH solution provided high conversion of the groups, a high ion-exchange capacity (IEC) value of 1.59 meq/g and a hydroxide conductivity of 25 mS/cm at 60 °C for anionic membrane. Another important characteristic, verified for hydroxide membrane, was its transparency above 600 nm, thus making it a good candidate for tandem cell applications in which the illuminated photoanode absorbs the highest-energy photons (< 600 nm), and photocathode absorbs the lowest-energy photons. Furthermore, hydrogen crossover tests showed a permeation of H2 through the membrane of less than 0.1%. Finally, low-cost tandem photo-electro-chemical cells, formed by titanium-doped hematite and ionomer at the photoanode and cupric oxide and ionomer at the photocathode, separated by a solid membrane in OH form, were assembled to optimize the influence of ionomer-loading dispersion. Maximum enthalpy (1.7%), throughput (2.9%), and Gibbs energy efficiencies (1.3%) were reached by using n-propanol/ethanol (1:1 wt.) as solvent for ionomer dispersion and with a 25 µL cm-2 ionomer loading for both the photoanode and the photocathode.

Predicting substitutions to modulate disorder and stability in coiled-coils.

BACKGROUND: Coiled-coils are described as stable structural motifs, where two or more helices wind around each other. However, coiled-coils are associated with local mobility and intrinsic disorder. Intrinsically disordered regions in proteins are characterized by lack of stable secondary and tertiary structure under physiological conditions in vitro. They are increasingly recognized as important for protein function. However, characterizing their behaviour in solution and determining precisely the extent of disorder of a protein region remains challenging, both experimentally and computationally. RESULTS: In this work, we propose a computational framework to quantify the extent of disorder within a coiled-coil in solution and to help design substitutions modulating such disorder. Our method relies on the analysis of conformational ensembles generated by relatively short all-atom Molecular Dynamics (MD) simulations. We apply it to the phosphoprotein multimerisation domains (PMD) of Measles virus (MeV) and Nipah virus (NiV), both forming tetrameric left-handed coiled-coils. We show that our method can help quantify the extent of disorder of the C-terminus region of MeV and NiV PMDs from MD simulations of a few tens of nanoseconds, and without requiring an extensive exploration of the conformational space. Moreover, this study provided a conceptual framework for the rational design of substitutions aimed at modulating the stability of the coiled-coils. By assessing the impact of four substitutions known to destabilize coiled-coils, we derive a set of rules to control MeV PMD structural stability and cohesiveness. We therefore design two contrasting substitutions, one increasing the stability of the tetramer and the other increasing its flexibility. CONCLUSIONS: Our method can be considered as a platform to reason about how to design substitutions aimed at regulating flexibility and stability.

Effects of the Chemical Treatment on the Physical-Chemical and Electrochemical Properties of the Commercial Nafion™ NR212 Membrane.

Polymer Electrolyte Fuel Cells (PEFCs) are one of the most promising power generation systems. The main component of a PEFC is the proton exchange membrane (PEM), object of intense research to improve the efficiency of the cell. The most commonly and commercially successful used PEMs are Nafion™ perfluorosulfonic acid (PFSA) membranes, taken as a reference for the development of innovative and alternative membranes. Usually, these membranes undergo different pre-treatments to enhance their characteristics. With the aim of understanding the utility and the effects of such pre-treatments, in this study, a commercial Nafion™ NR212 membrane was subjected to two different chemical pre-treatments, before usage. HNO3 or H2O2 were selected as chemical agents because the most widely used ones in the procedure protocols in order to prepare the membrane in a well-defined reference state. The pre-treated membranes properties were compared to an untreated membrane, used as-received. The investigation has showed that the pre-treatments enhance the hydrophilicity and increase the water molecules coordinated to the sulphonic groups in the membrane structure, on the other hand the swelling of the membranes also increases. As a consequence, the untreated membrane shows a better mechanical resistance, a good electrochemical performance and durability in fuel cell operations, orienting toward the use of the NR212 membrane without any chemical pre-treatment.

Novel Polymeric Composite TPPS/s-PEEK Membranes for Low Relative Humidity PEFC.

Composite membranes based on different wt percentages of meso-tetrakis-(4-sulfonatophenyl)porphyrin (TPPS) embedded in a medium sulfonation degree (50%) sulfonated poly(etheretherketone) (s-PEEK) were investigated. The successful introduction of porphyrin into the membranes and the characterization of its different species into the membrane ionic domains were carried out by spectroscopic techniques. Moreover, the effect of TPPS arrangement was investigated in terms of water retention, proton conductivity and fuel cell performance at low relative humidity (RH). It was found that the introduction of this porphyrin induces a variation of the chemical-physical parameters, such as ion exchange capacity (IEC), water up-take (Wup %) λ and proton concentration ([H+]), attributable to the interactions that occur between the sulfonic groups of the polymer and the nitrogen sites of TPPS. The TPPS, in its J-aggregated form, actively participates in the proton conduction mechanism, also maintaining the adequate water content in more drastic conditions (80 °C and 50% RH). A maximum power density value of 462 mW cm-2 was obtained for the s-PEEK membrane, with a 0.77 wt % content of TPPS. This evidence suggests that the presence of J-aggregates in the proton conduction channels maintains a good hydration, even if a drastic reduction of the RH of the reactant gases occurs, preventing the membrane from a dry-out effect.

COVTree: Coevolution in OVerlapped sequences by Tree analysis server.

Overlapping genes are commonplace in viruses and play an important role in their function and evolution. For these genes, molecular coevolution may be seen as a mechanism to decrease the evolutionary constraints of amino acid positions in the overlapping regions and to tolerate or compensate unfavorable mutations. Tracing these mutational sites, could help to gain insight on the direct or indirect effect of the mutations in the corresponding overlapping proteins. In the past, coevolution analysis has been used to identify residue pairs and coevolutionary signatures within or between proteins that served as markers of physical interactions and/or functional relationships. Coevolution in OVerlapped sequences by Tree analysis (COVTree) is a web server providing the online analysis of coevolving amino-acid pairs in overlapping genes, where residues might be located inside or outside the overlapping region. COVTree is designed to handle protein families with various characteristics, among which those that typically display a small number of highly conserved sequences. It is based on BIS2, a fast version of the coevolution analysis tool Blocks in Sequences (BIS). COVTree provides a rich and interactive graphical interface to ease biological interpretation of the results and it is openly accessible at http://www.lcqb.upmc.fr/COVTree/.

Phylogenetic Reconstruction Based on Synteny Block and Gene Adjacencies.

Gene order can be used as an informative character to reconstruct phylogenetic relationships between species independently from the local information present in gene/protein sequences. PhyChro is a reconstruction method based on chromosomal rearrangements, applicable to a wide range of eukaryotic genomes with different gene contents and levels of synteny conservation. For each synteny breakpoint issued from pairwise genome comparisons, the algorithm defines two disjoint sets of genomes, named partial splits, respectively, supporting the two block adjacencies defining the breakpoint. Considering all partial splits issued from all pairwise comparisons, a distance between two genomes is computed from the number of partial splits separating them. Tree reconstruction is achieved through a bottom-up approach by iteratively grouping sister genomes minimizing genome distances. PhyChro estimates branch lengths based on the number of synteny breakpoints and provides confidence scores for the branches. PhyChro performance is evaluated on two data sets of 13 vertebrates and 21 yeast genomes by using up to 130,000 and 179,000 breakpoints, respectively, a scale of genomic markers that has been out of reach until now. PhyChro reconstructs very accurate tree topologies even at known problematic branching positions. Its robustness has been benchmarked for different synteny block reconstruction methods. On simulated data PhyChro reconstructs phylogenies perfectly in almost all cases, and shows the highest accuracy compared with other existing tools. PhyChro is very fast, reconstructing the vertebrate and yeast phylogenies in <15 min.