Structural insights into the DNA recognition mechanism by the bacterial transcription factor PdxR

This is the final version. Available from Oxford University Press via the DOI in this record.Atomic coordinates and structure factors for the reported apo-PdxR crystal structure have been deposited with the RCSB Protein Data Bank (PDB) under accession number 7PQ9. The cryo-EM maps of the holo-PdxR–DNA complex in the open, half-closed, and closed (C1 and C2 symmetry) conformation and the relative coordinates generated and analysed in the current study have been deposited in the Electron Microscopy Data Bank (EMDB) and in the PDB under accession code EMD-14960 (PDB 7ZTH), EMD-14778 (PDB 7ZLA), EMD-14852 (PDB 7ZPA) and EMD-14801 (PDB 7ZN5), respectively.Specificity in protein-DNA recognition arises from the synergy of several factors that stem from the structural and chemical signatures encoded within the targeted DNA molecule. Here, we deciphered the nature of the interactions driving DNA recognition and binding by the bacterial transcription factor PdxR, a member of the MocR family responsible for the regulation of pyridoxal 5'-phosphate (PLP) biosynthesis. Single particle cryo-EM performed on the PLP-PdxR bound to its target DNA enabled the isolation of three conformers of the complex, which may be considered as snapshots of the binding process. Moreover, the resolution of an apo-PdxR crystallographic structure provided a detailed description of the transition of the effector domain to the holo-PdxR form triggered by the binding of the PLP effector molecule. Binding analyses of mutated DNA sequences using both wild type and PdxR variants revealed a central role of electrostatic interactions and of the intrinsic asymmetric bending of the DNA in allosterically guiding the holo-PdxR-DNA recognition process, from the first encounter through the fully bound state. Our results detail the structure and dynamics of the PdxR-DNA complex, clarifying the mechanism governing the DNA-binding mode of the holo-PdxR and the regulation features of the MocR family of transcription factors.Italian MIUR-PRIN 2020POR FESR Lazio 2014–2020Sapienza University of RomeDefence Science and Technology Laboratory (DSTL)Istituto Pasteur Italia – Fondazione Cenci Bolognett

Accumulo di rame su foglie e grappoli: il rame apportato con i trattamenti raggiunge l’interno del grappolo?

A parità di superficie trattata il rame si accumula maggiormente sulle foglie rispetto a rachidi e bacche interne e non espost

Neuroglobin, clues to function and mechanism

Neuroglobin is expressed in vertebrate brain and belongs to a branch of the globin family that diverged early in evolution. Sequence conservation and presence in nervous cells of several taxa suggests a relevant role in the nervous system, with tight structural restraints. Twenty years after its discovery, a rich scientific literature provides convincing evidence of the involvement of neuroglobin in sustaining neuron viability in physiological and pathological conditions however, a full and conclusive picture of its specific function, or set of functions is still lacking. The difficulty of unambiguously assigning a precise mechanism and biochemical role to neuroglobin might arise from the participation to one or more cell mechanism that redundantly guarantee the functioning of the highly specialized and metabolically demanding central nervous system of vertebrates. Here we collect findings and hypotheses arising from recent biochemical, biophysical, structural, in cell and in vivo experimental work on neuroglobin, aiming at providing an overview of the most recent literature. Proteins are said to have jobs and hobbies, it is possible that, in the case of neuroglobin, evolution has selected for it more than one job, and support to cover for its occasional failings. Disentangling the mechanisms and roles of neuroglobin is thus a challenging task that might be achieved by considering data from different disciplines and experimental approaches

Uncertainty quantification and sensitivity analysis of COVID-19 exit strategies in an individual-based transmission model

Many countries are currently dealing with the COVID-19 epidemic and are searching for an exit strategy such that life in society can return to normal. To support this search, computational models are used to predict the spread of the virus and to assess the efficacy of policy measures before actual implementation. The model output has to be interpreted carefully though, as computational models are subject to uncertainties. These can stem from, e.g., limited knowledge about input parameters values or from the intrinsic stochastic nature of some computational models. They lead to uncertainties in the model predictions, raising the question what distribution of values the model produces for key indicators of the severity of the epidemic. Here we show how to tackle this question using techniques for uncertainty quantification and sensitivity analysis. We assess the uncertainties and sensitivities of four exit strategies implemented in an agent-based transmission model with geographical stratification. The exit strategies are termed Flattening the Curve, Contact Tracing, Intermittent Lockdown and Phased Opening. We consider two key indicators of the ability of exit strategies to avoid catastrophic health care overload: the maximum number of prevalent cases in intensive care (IC), and the total number of IC patient-days in excess of IC bed capacity. Our results show that uncertainties not directly related to the exit strategies are secondary, although they should still be considered in comprehensive analysis intended to inform policy makers. The sensitivity analysis discloses the crucial role of the intervention uptake by the population and of the capability to trace infected individuals. Finally, we explore the existence of a safe operating space. For Intermittent Lockdown we find only a small region in the model parameter space where the key indicators of the model stay within safe bounds, whereas this region is larger for the other exit strategies

Spatial Covariance Modeling for Stochastic Subgrid‐Scale Parameterizations Using Dynamic Mode Decomposition

Stochastic parameterizations are increasingly being used in climate modeling to represent subgrid‐scale processes. While different parameterizations are being developed considering different aspects of the physical phenomena, less attention is given to technical and numerical aspects. In particular,empirical orthogonal functions (EOFs) are employed when a spatial structure is required. Here, we provide evidence they might not be the most suitable choice. By applying an energy‐consistent parameterization to the two‐layer quasi‐geostrophic (QG) model, we investigate the model sensitivity to apriori assumptions made on the parameterization. In particular, we consider here two methods to prescribe the spatial covariance of the noise:first, by using climatological variability patterns provided by EOFs,and second, by using time‐varying dynamics‐adapted Koopman modes, approximated by dynamic mode decomposition (DMD). The performance of the two methods are analyzed through numerical simulations of the stochastic system on a coarse spatial resolution and the outcomes compared to a high‐resolution simulation of the original deterministic system. The comparison reveals that the DMD‐based noise covariance scheme outperforms the EOF‐based one. The use of EOFs leads to a significant increase of the ensemble spread and to a meridional misplacement of the bimodal eddy kinetic energy (EKE) distribution.Conversely, using DMDs, the ensemble spread is confined, the meridional propagation of the zonal jet stream is accurately captured, and the total variance of the system is improved. Our results highlight the importance of the systematic design of stochastic parameterizations with dynamically adapted spatial correlations, rather than relying on statistical spatial patterns

Point mutations at a key site alter the cytochrome P450 oleP structural dynamics

Substrate binding to the cytochrome P450 OleP is coupled to a large open-to-closed transition that remodels the active site, minimizing its exposure to the external solvent. When the aglycone substrate binds, a small empty cavity is formed between the I and G helices, the BC loop, and the substrate itself, where solvent molecules accumulate mediating substrate-enzyme interactions. Herein, we analyzed the role of this cavity in substrate binding to OleP by producing three mutants (E89Y, G92W, and S240Y) to decrease its volume. The crystal structures of the OleP mutants in the closed state bound to the aglycone 6DEB showed that G92W and S240Y occupied the cavity, providing additional contact points with the substrate. Conversely, mutation E89Y induces a flipped-out conformation of this amino acid side chain, that points towards the bulk, increasing the empty volume. Equilibrium titrations and molecular dynamic simulations indicate that the presence of a bulky residue within the cavity impacts the binding properties of the enzyme, perturbing the conformational space explored by the complexes. Our data highlight the relevance of this region in OleP substrate binding and suggest that it represents a key substrate-protein contact site to consider in the perspective of redirecting its activity towards alternative compounds