Long-Range Modulation of Chain Motions within the Intrinsically Disordered Transactivation Domain of Tumor Suppressor p53

ABSTRACT: The tumor suppressor p53 is a hub protein with a multitude of binding partners, many of which target its intrinsically disordered N-terminal domain, p53-TAD. Partners, such as the N-terminal domain of MDM2, induce formation of local structure and leave the remainder of the domain apparently disordered. We investigated segmental chain motions in p53-TAD using fluorescence quenching of an extrinsic label by tryptophan in combination with fluorescence correlation spectroscopy (PET-FCS). We studied the loop closure kinetics of four consecutive segments within p53-TAD and their response to protein binding and phosphorylation. The kinetics was multiexponential, showing that the conformational ensemble of the domain deviates from random coil, in agreement with previous findings from NMR spectroscopy. Phosphorylations or binding of MDM2 changed the pattern of intrachain kinetics. Unexpectedly, we found that upon binding and phosphorylation chain motions were altered not only within the targeted segments but also in remote regions. Long-range interactions can be induced in an intrinsically disordered domain by partner proteins that induce apparently only local structure or by post-translational modification

Intrinsically Disordered Proteins Display No Preference for Chaperone Binding In Vivo

Intrinsically disordered/unstructured proteins (IDPs) are extremely sensitive to proteolysis in vitro, but show no enhanced degradation rates in vivo. Their existence and functioning may be explained if IDPs are preferentially associated with chaperones in the cell, which may offer protection against degradation by proteases. To test this inference, we took pairwise interaction data from high-throughput interaction studies and analyzed to see if predicted disorder correlates with the tendency of chaperone binding by proteins. Our major finding is that disorder predicted by the IUPred algorithm actually shows negative correlation with chaperone binding in E. coli, S. cerevisiae, and metazoa species. Since predicted disorder positively correlates with the tendency of partner binding in the interactome, the difference between the disorder of chaperone-binding and non-binding proteins is even more pronounced if normalized to their overall tendency to be involved in pairwise protein–protein interactions. We argue that chaperone binding is primarily required for folding of globular proteins, as reflected in an increased preference for chaperones of proteins in which at least one Pfam domain exists. In terms of the functional consequences of chaperone binding of mostly disordered proteins, we suggest that its primary reason is not the assistance of folding, but promotion of assembly with partners. In support of this conclusion, we show that IDPs that bind chaperones also tend to bind other proteins

Variability in school closure decisions in response to 2009 H1N1: a qualitative systems improvement analysis

<p>Abstract</p> <p>Background</p> <p>School closure was employed as a non-pharmaceutical intervention against pandemic 2009 H1N1, particularly during the first wave. More than 700 schools in the United States were closed. However, closure decisions reflected significant variation in rationales, decision triggers, and authority for closure. This variability presents the opportunity for improved efficiency and decision-making.</p> <p>Methods</p> <p>We identified media reports relating to school closure as a response to 2009 H1N1 by monitoring high-profile sources and searching Lexis-Nexis and Google news alerts, and reviewed reports for key themes. News stories were supplemented by observing conference calls and meetings with health department and school officials, and by discussions with decision-makers and community members.</p> <p>Results</p> <p>There was significant variation in the stated goal of closure decision, including limiting community spread of the virus, protecting particularly vulnerable students, and responding to staff shortages or student absenteeism. Because the goal of closure is relevant to its timing, nature, and duration, unclear rationales for closure can challenge its effectiveness. There was also significant variation in the decision-making authority to close schools in different jurisdictions, which, in some instances, was reflected in open disagreement between school and public health officials. Finally, decision-makers did not appear to expect the level of scientific uncertainty encountered early in the pandemic, and they often expressed significant frustration over changing CDC guidance.</p> <p>Conclusions</p> <p>The use of school closure as a public health response to epidemic disease can be improved by ensuring that officials clarify the goals of closure and tailor closure decisions to those goals. Additionally, authority to close schools should be clarified in advance, and decision-makers should expect to encounter uncertainty disease emergencies unfold and plan accordingly.</p

Disorder Predictors Also Predict Backbone Dynamics for a Family of Disordered Proteins

Several algorithms have been developed that use amino acid sequences to predict whether or not a protein or a region of a protein is disordered. These algorithms make accurate predictions for disordered regions that are 30 amino acids or longer, but it is unclear whether the predictions can be directly related to the backbone dynamics of individual amino acid residues. The nuclear Overhauser effect between the amide nitrogen and hydrogen (NHNOE) provides an unambiguous measure of backbone dynamics at single residue resolution and is an excellent tool for characterizing the dynamic behavior of disordered proteins. In this report, we show that the NHNOE values for several members of a family of disordered proteins are highly correlated with the output from three popular algorithms used to predict disordered regions from amino acid sequence. This is the first test between an experimental measure of residue specific backbone dynamics and disorder predictions. The results suggest that some disorder predictors can accurately estimate the backbone dynamics of individual amino acids in a long disordered region

A Network-Based Approach to Prioritize Results from Genome-Wide Association Studies

Genome-wide association studies (GWAS) are a valuable approach to understanding the genetic basis of complex traits. One of the challenges of GWAS is the translation of genetic association results into biological hypotheses suitable for further investigation in the laboratory. To address this challenge, we introduce Network Interface Miner for Multigenic Interactions (NIMMI), a network-based method that combines GWAS data with human protein-protein interaction data (PPI). NIMMI builds biological networks weighted by connectivity, which is estimated by use of a modification of the Google PageRank algorithm. These weights are then combined with genetic association p-values derived from GWAS, producing what we call ‘trait prioritized sub-networks.’ As a proof of principle, NIMMI was tested on three GWAS datasets previously analyzed for height, a classical polygenic trait. Despite differences in sample size and ancestry, NIMMI captured 95% of the known height associated genes within the top 20% of ranked sub-networks, far better than what could be achieved by a single-locus approach. The top 2% of NIMMI height-prioritized sub-networks were significantly enriched for genes involved in transcription, signal transduction, transport, and gene expression, as well as nucleic acid, phosphate, protein, and zinc metabolism. All of these sub-networks were ranked near the top across all three height GWAS datasets we tested. We also tested NIMMI on a categorical phenotype, Crohn’s disease. NIMMI prioritized sub-networks involved in B- and T-cell receptor, chemokine, interleukin, and other pathways consistent with the known autoimmune nature of Crohn’s disease. NIMMI is a simple, user-friendly, open-source software tool that efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses

Physical and functional interactions between human mitochondrial single-stranded DNA-binding protein and tumour suppressor p53

Single-stranded DNA-binding proteins (SSB) form a class of proteins that bind preferentially single-stranded DNA with high affinity. They are involved in DNA metabolism in all organisms and serve a vital role in replication, recombination and repair of DNA. In this report, we identify human mitochondrial SSB (HmtSSB) as a novel protein-binding partner of tumour suppressor p53, in mitochondria. It binds to the transactivation domain (residues 1–61) of p53 via an extended binding interface, with dissociation constant of 12.7 (± 0.7) μM. Unlike most binding partners reported to date, HmtSSB interacts with both TAD1 (residues 1–40) and TAD2 (residues 41–61) subdomains of p53. HmtSSB enhances intrinsic 3′-5′ exonuclease activity of p53, particularly in hydrolysing 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG) present at 3′-end of DNA. Taken together, our data suggest that p53 is involved in DNA repair within mitochondria during oxidative stress. In addition, we characterize HmtSSB binding to ssDNA and p53 N-terminal domain using various biophysical measurements and we propose binding models for both