Structure and mechanism of PhnP, a phosphodiesterase of the carbon-phosphorus lyase pathway

PhnP is a phosphodiesterase that plays an important role within the bacterial carbon-phosphorus lyase (CP-lyase) pathway by recycling a "dead-end" intermediate, 5-phospho-α-d-ribosyl 1,2-cyclic phosphate, that is formed during organophosphonate catabolism. As a member of the metallo-β-lactamase superfamily, PhnP is most homologous in sequence and structure to tRNase Z phosphodiesterases. X-ray structural analysis of PhnP complexed with orthovanadate to 1.5 ? resolution revealed this inhibitor bound in a tetrahedral geometry by the two catalytic manganese ions and the putative general acid residue H200. Guided by this structure, we probed the contributions of first- and second-sphere active site residues to catalysis and metal ion binding by site-directed mutagenesis, kinetic analysis, and ICP-MS. Alteration of H200 to alanine resulted in a 6-33-fold decrease in k(cat)/K(M) with substituted methyl phenylphosphate diesters with leaving group pK(a) values ranging from 4 to 8.4. With bis(p-nitrophenyl)phosphate as a substrate, there was a 10-fold decrease in k(cat)/K(M), primarily the result of a large increase in K(M). Moreover, the nickel ion-activated H200A PhnP displayed a bell-shaped pH dependence for k(cat)/K(M) with pK(a) values (pK(a1) = 6.3; pK(a2) = 7.8) that were comparable to those of the wild-type enzyme (pK(a1) = 6.5; pK(a2) = 7.8). Such modest effects are counter to what is expected for a general acid catalyst and suggest an alternate role for H200 in this enzyme. A Br?nsted analysis of the PhnP reaction with a series of substituted phenyl methyl phosphate esters yielded a linear correlation, a β(lg) of -1.06 ± 0.1, and a Leffler α value of 0.61, consistent with a synchronous transition state for phosphoryl transfer. On the basis of these data, we propose a mechanism for PhnP.     

Protein Partitioning into Ordered Membrane Domains: Insights from Simulations

Cellular membranes are laterally organized into domains of distinct structures and compositions by the differential interaction affinities between various membrane lipids and proteins. A prominent example of such structures are lipid rafts, which are ordered, tightly packed domains that have been widely implicated in cellular processes. The functionality of raft domains is driven by their selective recruitment of specific membrane proteins to regulate their interactions and functions; however, there have been few general insights into the factors that determine the partitioning of membrane proteins between coexisting liquid domains. In this work, we used extensive coarse-grained and atomistic molecular dynamics simulations, potential of mean force calculations, and conceptual models to describe the partitioning dynamics and energetics of a model transmembrane domain from the linker of activation of T cells. We find that partitioning between domains is determined by an interplay between protein-lipid interactions and differential lipid packing between raft and nonraft domains. Specifically, we show that partitioning into ordered domains is promoted by preferential interactions between peptides and ordered lipids, mediated in large part by modification of the peptides by saturated fatty acids (i.e., palmitoylation). Ordered phase affinity is also promoted by elastic effects, specifically hydrophobic matching between the membrane and the peptide. Conversely, ordered domain partitioning is disfavored by the tight molecular packing of the lipids therein. The balance of these dominant drivers determines partitioning. In the case of the wild-type linker of activation of T cells transmembrane domain, these factors combine to yield enrichment of the peptide at L_o/L_d interfaces. These results define some of the general principles governing protein partitioning between coexisting membrane domains and potentially explain previous disparities among experiments and simulations across model systems.     

Enzymatic Activity versus Structural Dynamics: The Case of Acetylcholinesterase Tetramer

The function of many proteins, such as enzymes, is modulated by structural fluctuations. This is especially the case in gated diffusion-controlled reactions (where the rates of the initial diffusional encounter and of structural fluctuations determine the overall rate of the reaction) and in oligomeric proteins (where function often requires a coordinated movement of individual subunits). A classic example of a diffusion-controlled biological reaction catalyzed by an oligomeric enzyme is the hydrolysis of synaptic acetylcholine (ACh) by tetrameric acetylcholinesterase (AChEt). Despite decades of efforts, the extent to which enzymatic efficiency of AChEt (or any other enzyme) is modulated by flexibility is not fully determined. This article attempts to determine the correlation between the dynamics of AChEt and the rate of reaction between AChEt and ACh. We employed equilibrium and nonequilibrium electro-diffusion models to compute rate coefficients for an ensemble of structures generated by molecular dynamics simulation. We found that, for the static initial model, the average reaction rate per active site is ∼22-30% slower in the tetramer than in the monomer. However, this effect of tetramerization is modulated by the intersubunit motions in the tetramer such that a complex interplay of steric and electrostatic effects either guides or blocks the substrate into or from each of the four active sites. As a result, the rate per active site calculated for some of the tetramer structures is only ∼15% smaller than the rate in the monomer. We conclude that structural dynamics minimizes the adverse effect of tetramerization, allowing the enzyme to maintain similar enzymatic efficiency in different oligomerization states.     

Segregation of negatively charged phospholipids by the polycationic and farnesylated membrane anchor of Kras

The Kras protein, a member of the Ras family of bio-switches that are frequently mutated in cancer and developmental disorders, becomes functional when anchored to the inner surface of the plasma membrane. It is well known that membrane attachment involves the farnesylated and poylcationic C-terminus of the protein. However, little is known about the structure of the complex and the specific protein-lipid interactions that are responsible for the binding. On the basis of data from extensive (>0.55 μs) molecular dynamics simulations of multiple Kras anchors in bilayers of POPC/POPG lipids (4:1 ratio), we show that, as expected, Kras is tethered to the bilayer surface by specific lysine-POPG salt bridges and by nonspecific farnesyl-phospholipid van der Waals interactions. Unexpectedly, however, only the C-terminal five of the eight Kras Lys side chains were found to directly interact with the bilayer, with the N-terminal ones staying in water. Furthermore, the positively charged Kras anchors pull the negatively charged POPG lipids together, leading to the clustering of the POPG lipids around the proteins. This selective Kras-POPG interaction is directly related to the specific geometry of the backbone, which exists in two major conformational states: 1), a stable native-like ensemble of structures characterized by an extended geometry with a pseudohelical turn; and 2), less stable nonnative ensembles of conformers characterized by severely bent geometries. Finally, although the interface-bound anchor has little effect on the overall structure of the bilayer, it induces local thinning within a persistence length of ∼12 Å. Our results thus go beyond documenting how Kras attaches to a mixed bilayer of charged and neutral lipids; they highlight a fascinating process of protein-induced lipid sorting coupled with the (re)shaping of a surface-bound protein by the host lipids.     

Heavy Metal Concentration in the Urban Environment of Addis Ababa,Ethiopia

This work assesses the issue of whether the measured concentrations of heavy metals in soil, rocks, surface and ground waters in Addis Ababa can be related to anthropogenic contamination or natural weathering of rocks. Heavy metal analyses of rocks, soils, streams, springs and boreholes have been carried out to identify the presence of potentially harmful solutes. The maximum concentration of total chromium measured is 269 ppm in the northern, industry-free zone of Addis Ababa in the B ₂-horizon of soil profile (cambisol). The Ni/Cr ratio in the rocks is higher than soils, which could indicate the presence of high concentrations of Cr in soils is from weathering processes. A comparative study of different samples collected from various parts of the city indicates that the chemical composition of the hydrothermally affected volcanic rocks plays an important role in increasing heavy metal concentration in the study area. The fresh country rocks contain relatively low concentrations of heavy metals, as shown by background values. The statistical evaluation indicates that the hydrothermally altered rocks contain far higher mean heavy metal concentrations than the fresh acidic rocks (background values). Consequently, soils derived from altered rocks are enriched with respect to heavy metals. From this study it was possible to observe that the rock and soil outcrops of Addis Ababa are anomalously rich in heavy metals derived from hydrothermal activity. Therefore, heavy metal concentrations in the surrounding rocks and soils are related to geogenic sources whereas anthropogenic contribution as a cause of these concentrations is minor.     

Disruption of the<Emphasis Type="Italic">RAD51</Emphasis> gene sensitizes<Emphasis Type="Italic">S. cerevisiae</Emphasis> cells to the toxic and mutagenic effects of hydrogen peroxide

The RAD51 gene was disrupted in three different parental wild-type strains to yield three rad51 null strains with different genetic background. The rad51 mutation sensitizes yeast cells to the toxic and mutagenic effects of H2O2, suggesting that Rad51-mediated repair, similarly to that of RecA-mediated, is relevant to the repair of oxidative damage in S. cerevisiae. Moreover, pulsed-field gel electrophoresis analysis demonstrated that increased sensitivity of the rad51 mutant to H2O2 is accompanied by its decreased ability to repair double-strand breaks induced by this agent. Our results show that ScRad51 protects yeast cells from H2O2-induced DNA double-strand breakage.     

Remote sensing-based time series models for malaria early warning in the highlands of Ethiopia

ABSTRACT: BACKGROUND: Malaria is one of the leading public health problems in most of sub-Saharan Africa, particularly in Ethiopia. Almost all demographic groups are at risk of malaria because of seasonal and unstable transmission of the disease. Therefore, there is a need to develop malaria early-warning systems to enhance public health decision making for control and prevention of malaria epidemics. Data from orbiting earth-observing sensors can monitor environmental risk factors that trigger malaria epidemics. Remotely sensed environmental indicators were used to examine the influences of climatic and environmental variability on temporal patterns of malaria cases in the Amhara region of Ethiopia. METHODS: In this study seasonal auto regressive integrated moving average (SARIMA) models were used to quantify the relationship between malaria cases and remotely sensed environmental variables, including rainfall, land-surface temperature (LST), vegetation indices (NDVI and EVI), and actual evapotranspiration (ETa) with lags ranging from one to three months. Predictions from the best model with environmental variables were compared to the actual observations from the last 12 months of the time series. RESULTS: Malaria cases exhibited positive associations with LST at a lag of one month and positive associations with indicators of moisture (rainfall, EVI and ETa) at lags from one to three months. SARIMA models that included these environmental covariates had better fits and more accurate predictions, as evidenced by lower AIC and RMSE values, than models without environmental covariates. CONCLUSIONS: Malaria risk indicators such as satellite-based rainfall estimates, LST, EVI, and ETa exhibited significant lagged associations with malaria cases in the Amhara region and improved model fit and prediction accuracy. These variables can be monitored frequently and extensively across large geographic areas using data from earth-observing sensors to support public health decisions.     

CD4 Cell Count Trends after Commencement of Antiretroviral Therapy among HIV-Infected Patients in Tigray,Northern Ethiopia: A Retrospective Cross-Sectional Study

Background

The rate and extent of CD4 cell recovery varies widely among HIV-infected patients with different baseline CD4 cell count strata. The objective of the study was to assess trends in CD4 cell counts in HIV-infected patients after initiation of antiretroviral therapy in Tigray, Northern Ethiopia.

Methods

A retrospective cross-sectional study was conducted by reviewing medical records of HIV patients who received antiretroviral treatment at twenty health centers in Tigray region during 2008–2012. Multi-stage cluster sampling technique was employed to collect data, and the data were analyzed using SPSS version 20.0 software.

Results

The median change from baseline to the most recent CD4 cell count was +292 cells/μl. By 5 years, the overall median (inter-quartile range, IQR) CD4 cell count was 444(263-557) cells/μl while the median (IQR) CD4 cell count was 342(246-580) cells/μl among patients with baseline CD4 cell counts ≤200 cells/μl, 500(241-557) cells/μl among those with baseline CD4 cell counts of 201–350 cells/μl, and 652(537-767) cells/μl among those with baseline CD4 cell counts >350 cells/μl. Higher baseline CD4 cell counts and being male were independently associated with the risk of immunological non-response at 12 months. Furthermore, it was also investigated that these factors were significant predictors of subsequent CD4 cell recovery.

Conclusions

Patients with higher baseline CD4 cell stratum returned to normal CD4 Cell counts though they had an increased risk of immunological non-response at 12 months compared to those with the least baseline CD4 cell stratum. The findings suggest that consideration be given to initiation of HAART at a CD4 cell count >350 cells/μl to achieve better immune recovery, and to HIV-infected male patients to improve their health seeking behavior.     

Magnitude and Predictors of Anti-Retroviral Treatment (ART) Failure in Private Health Facilities in Addis Ababa,Ethiopia

BackgroundThe public health approach to antiretroviral treatment management encourages the public private partnership in resource limited countries like Ethiopia. As a result, some private health facilities are accredited to provide antiretroviral treatment free services. Evidence on magnitude and predictors of treatment failure are crucial for timely actions. However, there are few studies in this regard.ObjectiveTo assess the magnitude and predictors of ART failure in private health facilities in Addis Ababa, Ethiopia.MethodsThe study followed retrospective cohort design, with 525 adult antiretroviral treatment clients who started the treatment since October 2009 and have at least six months follow up until December 31, 2013. Kaplan Meier survival analysis and Cox proportional hazard model were used for analysis.ResultsTreatment failure, using the three WHO antiretroviral treatment failure criteria, was 19.8%. The immunologic, clinical, and virologic failures were 15%, 6.3% and 1.3% respectively. The mean and median survival times in months were 41.17 with 95% Confidence Interval (CI) [39.69, 42.64] and 49.00, 95% CI [47.71, 50.29] respectively. The multivariate cox regression analysis showed years since HIV diagnosis (Adjusted Hazard Ratio (AHR)=13.87 with 95% CI [6.65, 28.92]), disclosure (AHR=0.59, 95% CI [0.36, 0.96]), WHO stage at start (AHR=1.84, 95% CI [1.16, 2.93]), weight at baseline (AHR=0.58, 95% CI [0.38, 0.89]), and functionality status at last visit (AHR=2.57, 95% CI [1.59, 4.15]) were independent predictors of treatment failure.ConclusionThe study showed that the treatment failure is high among the study subjects. The predictors for antiretroviral treatment failure were years since HIV diagnosis, weight at start, WHO stage at start, status at last visit and disclosure.RecommendationsFacilities need to monitor antiretroviral treatment clients to avoid disease progression and drug resistance.