Slow Protein Dynamics Elicits New Enzymatic Functions by Means of Epistatic Interactions

Protein evolution depends on the adaptation of these molecules to different functional challenges. This occurs by tuning their biochemical, biophysical, and structural traits through the accumulation of mutations. While the role of protein dynamics in biochemistry is well recognized, there are limited examples providing experimental evidence of the optimization of protein dynamics during evolution. Here we report an NMR study of four variants of the CTX-M β-lactamases, in which the interplay of two mutations outside the active site enhances the activity against a cephalosporin substrate, ceftazidime. The crystal structures of these enzymes do not account for this activity enhancement. By using NMR, here we show that the combination of these two mutations increases the backbone dynamics in a slow timescale and the exposure to the solvent of an otherwise buried β-sheet. The two mutations located in this β-sheet trigger conformational changes in loops located at the opposite side of the active site. We postulate that the most active variant explores alternative conformations that enable binding of the more challenging substrate ceftazidime. The impact of the mutations in the dynamics is context-dependent, in line with the epistatic effect observed in the catalytic activity of the different variants. These results reveal the existence of a dynamic network in CTX-M β-lactamases that has been exploited in evolution to provide a net gain-of-function, highlighting the role of alternative conformations in protein evolution.Fil: Rossi, María Agustina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Palzkill, Timothy. Baylor College Of Medicine (baylor College Of Medicine);Fil: Almeida, Fabio C L. Universidade Federal do Rio de Janeiro; BrasilFil: Vila, Alejandro Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; Argentin

The Influence of Health Literacy on Reach, Retention, and Success in a Worksite Weight Loss Program

To examine if employee health literacy (HL) status moderated reach, retention, and weight outcomes in a worksite weight loss program

Who participates in internet-based worksite weight loss programs?

<p>Abstract</p> <p>Background</p> <p>The reach and representativeness are seldom examined in worksite weight loss studies. This paper describes and illustrates a method for directly assessing the reach and representativeness of a internet-based worksite weight loss program.</p> <p>Methods</p> <p>A brief health survey (BHS) was administered, between January 2008 and November 2009, to employees at 19 worksites in Southwest Virginia. The BHS included demographic, behavioral, and health questions. All employees were blinded to the existence of a future weight loss program until the completion of the BHS.</p> <p>Results</p> <p>The BHS has a participation rate of 66 percent and the subsequent weight loss program has a participation rate of 30 percent. Employees from higher income households, with higher education levels and health literacy proficiency were significantly more likely to participate in the program (p's < .01).</p> <p>Conclusions</p> <p>Worksite weight loss programs should include targeted marketing strategies to engage employees with lower income, education, and health literacy.</p

Peptide:lipid ratio and membrane surface charge determine the mechanism of action of the antimicrobial peptide BP100. Conformational and functional studies

The cecropin-melittin hybrid antimicrobial peptide BP100 (H-KKLFKKILKYL-NH2) is selective for Gram-negative bacteria, negatively charged membranes, and weakly hemolytic. We studied BP100 conformational and functional properties upon interaction with large unilamellar vesicles, LUVs, and giant unilamellar vesicles, GUVs, containing variable proportions of phosphatidylcholine (PC) and negatively charged phosphatidylglycerol (PG). CD and NMR spectra showed that upon binding to PG-containing LUVs BP100 acquires a-helical conformation, the helix spanning residues 3-11. Theoretical analyses indicated that the helix is amphipathic and surface-seeking. CD and dynamic light scattering data evinced peptide and/or vesicle aggregation, modulated by peptide: lipid ratio and PG content. BP100 decreased the absolute value of the zeta potential () of LUVs with low PG contents; for higher PG, binding was analyzed as an ion-exchange process. At high salt, BP100-induced LUVS leakage requires higher peptide concentration, indicating that both electrostatic and hydrophobic interactions contribute to peptide binding. While a gradual release took place at low peptide:lipid ratios, instantaneous loss occurred at high ratios, suggesting vesicle disruption. Optical microscopy of GUVs confirmed BP100-promoted disruption of negatively charged membranes. the mechanism of action of BP100 is determined by both peptide:lipid ratio and negatively charged lipid content While gradual release results from membrane perturbation by a small number of peptide molecules giving rise to changes in acyl chain packing, lipid clustering (leading to membrane defects), and/or membrane thinning, membrane disruption results from a sequence of events large-scale peptide and lipid clustering, giving rise to peptide-lipid patches that eventually would leave the membrane in a carpet-like mechanism. (C) 2014 Elsevier B.V. All rights reserved.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Institut Nacional de Ciencia e Tecnologia de fluidos complexos (INCTFCx)Nude de Apoio Pesquisa de Fluidos Complexos (NAPFCx)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Univ São Paulo, Inst Chem, Dept Biochem, BR-05513970 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Biophys, BR-04044020 São Paulo, BrazilUniv Fed Rio de Janeiro, Inst Med Biochem, Nucl Magnet Resonance Natl Ctr, Rio de Janeiro, BrazilEmbrapa Recursos Genet & Biotecnol, BR-70770917 Brasilia, DF, BrazilUniversidade Federal de São Paulo, Dept Biophys, BR-04044020 São Paulo, BrazilFAPESP: 2007/50970-5FAPESP: 2013/08166-5Web of Scienc

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients

Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions: The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.Fogarty/NIHFogarty/NIH [3 D43 TW000018-16S3, 5 U2R TW006883-02]CNPq [504162/2008-0, 308889/2007-0]CNP

Identification of Regions Involved in Substrate Binding and Dimer Stabilization within the Central Domains of Yeast Hsp40 Sis1

Protein folding, refolding and degradation are essential for cellular life and are regulated by protein homeostatic processes such those that involve the molecular chaperone DnaK/Hsp70 and its co-chaperone DnaJ. Hsp70 action is initiated when proteins from the DnaJ family bind an unfolded protein for delivery purposes. In eukaryotes, the DnaJ family can be divided into two main groups, Type I and Type II, represented by yeast cytosolic Ydj1 and Sis1, respectively. Although sharing some unique features both members of the DnaJ family, Ydj1 and Sis1 are structurally and functionally distinct as deemed by previous studies, including the observation that their central domains carry the structural and functional information even in switched chimeras. In this study, we combined several biophysical tools for evaluating the stability of Sis1 and mutants that had the central domains (named Gly/Met rich domain and C-terminal Domain I) deleted or switched to those of Ydj1 to gain insight into the role of these regions in the structure and function of Sis1. The mutants retained some functions similar to full length wild-type Sis1, however they were defective in others. We found that: 1) Sis1 unfolds in at least two steps as follows: folded dimer to partially folded monomer and then to an unfolded monomer. 2) The Gly/Met rich domain had intrinsically disordered characteristics and its deletion had no effect on the conformational stability of the protein. 3) The deletion of the C-terminal Domain I perturbed the stability of the dimer. 4) Exchanging the central domains perturbed the conformational stability of the protein. Altogether, our results suggest the existence of two similar subdomains in the C-terminal domain of DnaJ that could be important for stabilizing each other in order to maintain a folded substrate-binding site as well as the dimeric state of the protein.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Ministerio da Ciencia e Tecnologia/Conselho Nacional de Pesquisa e Desenvolvimento (MCT/CNPq

An Introspective Comparison of Random Forest-Based Classifiers for the Analysis of Cluster-Correlated Data by Way of RF++

Many mass spectrometry-based studies, as well as other biological experiments produce cluster-correlated data. Failure to account for correlation among observations may result in a classification algorithm overfitting the training data and producing overoptimistic estimated error rates and may make subsequent classifications unreliable. Current common practice for dealing with replicated data is to average each subject replicate sample set, reducing the dataset size and incurring loss of information. In this manuscript we compare three approaches to dealing with cluster-correlated data: unmodified Breiman's Random Forest (URF), forest grown using subject-level averages (SLA), and RF++ with subject-level bootstrapping (SLB). RF++, a novel Random Forest-based algorithm implemented in C++, handles cluster-correlated data through a modification of the original resampling algorithm and accommodates subject-level classification. Subject-level bootstrapping is an alternative sampling method that obviates the need to average or otherwise reduce each set of replicates to a single independent sample. Our experiments show nearly identical median classification and variable selection accuracy for SLB forests and URF forests when applied to both simulated and real datasets. However, the run-time estimated error rate was severely underestimated for URF forests. Predictably, SLA forests were found to be more severely affected by the reduction in sample size which led to poorer classification and variable selection accuracy. Perhaps most importantly our results suggest that it is reasonable to utilize URF for the analysis of cluster-correlated data. Two caveats should be noted: first, correct classification error rates must be obtained using a separate test dataset, and second, an additional post-processing step is required to obtain subject-level classifications. RF++ is shown to be an effective alternative for classifying both clustered and non-clustered data. Source code and stand-alone compiled versions of command-line and easy-to-use graphical user interface (GUI) versions of RF++ for Windows and Linux as well as a user manual (Supplementary File S2) are available for download at: http://sourceforge.org/projects/rfpp/ under the GNU public license