20 research outputs found
<i>Staphylococcus aureus</i> CidC Is a Pyruvate:Menaquinone Oxidoreductase
Recent
studies have revealed an important role for the <i>Staphylococcus
aureus</i> CidC enzyme in cell death during the
stationary phase and in biofilm development and have contributed to
our understanding of the metabolic processes that are important in
the induction of bacterial programmed cell death (PCD). To gain more
insight into the characteristics of this enzyme, we performed an in-depth
biochemical and biophysical analysis of its catalytic properties. <i>In vitro</i> experiments show that this flavoprotein catalyzes
the oxidative decarboxylation of pyruvate to acetate and carbon dioxide.
CidC efficiently reduces menadione, but not CoenzymeQ<sub>0</sub>,
suggesting a specific role in the <i>S. aureus</i> respiratory
chain. CidC exists as a monomer under neutral-pH conditions but tends
to aggregate and bind to artificial lipid membranes at acidic pH,
resulting in enhanced enzymatic activity. Unlike its <i>Escherichia
coli</i> counterpart, PoxB, CidC does not appear to be activated
by other amphiphiles like Triton X-100 or octyl β-d-glucopyranoside. In addition, only reduced CidC is protected from
proteolytic cleavage by chymotrypsin, and unlike its homologues in
other bacteria, protease treatment does not increase CidC enzymatic
activity. Finally, CidC exhibits maximal activity at pH 5.5–5.8
and negligible activity at pH 7–8. The results of this study
are consistent with a model in which CidC functions as a pyruvate:menaquinone
oxidoreductase whose activity is induced at the cellular membrane
during cytoplasmic acidification, a process previously shown to be
important for the induction of bacterial PCD
Synergistic Effect of High Charge and Energy Particle Radiation and Chronological Age on Biomarkers of Oxidative Stress and Tissue Degeneration: A Ground-Based Study Using the Vertebrate Laboratory Model Organism <i>Oryzias latipes</i>
<div><p>High charge and energy (HZE) particles are a main hazard of the space radiation environment. Uncertainty regarding their health effects is a limiting factor in the design of human exploration-class space missions, that is, missions beyond low earth orbit. Previous work has shown that HZE exposure increases cancer risk and elicits other aging-like phenomena in animal models. Here, we investigate how a single exposure to HZE particle radiation, early in life, influences the subsequent age-dependent evolution of oxidative stress and appearance of degenerative tissue changes. Embryos of the laboratory model organism, <i>Oryzias latipes</i> (Japanese medaka fish), were exposed to HZE particle radiation at doses overlapping the range of anticipated human exposure. A separate cohort was exposed to reference γ-radiation. Survival was monitored for 750 days, well beyond the median lifespan. The population was also sampled at intervals and liver tissue was subjected to histological and molecular analysis. HZE particle radiation dose and aging contributed synergistically to accumulation of lipid peroxidation products, which are a marker of chronic oxidative stress. This was mirrored by a decline in PPARGC1A mRNA, which encodes a transcriptional co-activator required for expression of oxidative stress defense genes and for mitochondrial maintenance. Consistent with chronic oxidative stress, mitochondria had an elongated and enlarged ultrastructure. Livers also had distinctive, cystic lesions. Depending on the endpoint, effects of γ-rays in the same dose range were either lesser or not detected. Results provide a quantitative and qualitative framework for understanding relative contributions of HZE particle radiation exposure and aging to chronic oxidative stress and tissue degeneration.</p></div
Age and dose-dependent decline in PPARGC1A mRNA in liver tissue.
<p>A. Quantification of PPARGC1A mRNA. Box plot shows mean and interquartile ranges. Color denotes dose group. Values are normalized to 0 Gy, 250 day group. B. Plot showing correlation between actual and predicted PPARGC1A values. Each symbol represents one individual. Shape denotes age group, color denotes dose group using same values as in Panel A. Plot showing predicted PPARGC1A values as a function of age and HZE dose. Note that vertical axis shows relative mRNA amounts (i.e., back-transformed from ΔΔC<sub>t</sub> values). D, E, same as Panels B, C for γ-ray cohorts.</p
Necrotic cysts in livers of radiation-exposed individuals.
<p>A. Representative hematoxylin and eosin stained sections. The left panel shows normal liver, and the right panel shows a necrotic cyst. Insets show regions of each section at higher magnification. Scale bars are 20 µm. B. Stacked column graph showing the incidence of necrotic cysts, classified according to the percentage area of the liver that was affected. C. Pooled data showing incidence of necrotic cysts at different doses of HZE particle radiation. Lesions of different severity were combined and classified as abnormal. Different age groups were also combined. <i>P</i> values are shown based on ordinal logistic regression. D. Stacked column graph, as in Panel B but for γ-ray exposed groups. E. Pooled data showing incidence of necrotic cysts at different doses of γ-rays.</p
Age and dose dependence for 4-HNE.
a<p>Not significant.</p><p>Units for age are days; units for dose are Gy. Parameters are for ln-transformed data.</p><p>Age and dose dependence for 4-HNE.</p
Presentation_1_Negative Binomial Mixed Models for Analyzing Longitudinal Microbiome Data.PDF
<p>The metagenomics sequencing data provide valuable resources for investigating the associations between the microbiome and host environmental/clinical factors and the dynamic changes of microbial abundance over time. The distinct properties of microbiome measurements include varied total sequence reads across samples, over-dispersion and zero-inflation. Additionally, microbiome studies usually collect samples longitudinally, which introduces time-dependent and correlation structures among the samples and thus further complicates the analysis and interpretation of microbiome count data. In this article, we propose negative binomial mixed models (NBMMs) for longitudinal microbiome studies. The proposed NBMMs can efficiently handle over-dispersion and varying total reads, and can account for the dynamic trend and correlation among longitudinal samples. We develop an efficient and stable algorithm to fit the NBMMs. We evaluate and demonstrate the NBMMs method via extensive simulation studies and application to a longitudinal microbiome data. The results show that the proposed method has desirable properties and outperform the previously used methods in terms of flexible framework for modeling correlation structures and detecting dynamic effects. We have developed an R package NBZIMM to implement the proposed method, which is freely available from the public GitHub repository http://github.com//nyiuab//NBZIMM and provides a useful tool for analyzing longitudinal microbiome data.</p
Analysis of mitochondrial ultrastructure.
<p>Panels A–C show relatively normal mitochondria (triangles) from a non-irradiated individual and two examples of enlarged and elongate mitochondria (*) from HZE-exposed groups. D. Mitochondrial area as a function of HZE dose (left panel). Percent of elongated mitochondria as a function of dose (right panel).</p
Experimental design and radiation survival.
<p>A. Embryos were irradiated with 1 GeV/u <sup>56</sup>Fe ions or with γ-rays, reared, and scored for survival as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0111362#s2" target="_blank">Materials and Methods</a>. At the indicated times, male fish from each dose group were sacrificed and the livers analyzed. B, C. Kaplan-Meier survival curves for fish exposed as embryos to indicated doses and types of radiation.</p
Investigation of Selective Catalytic Reduction of N<sub>2</sub>O by NH<sub>3</sub> over an Fe–Mordenite Catalyst: Reaction Mechanism and O<sub>2</sub> Effect
We systematically investigated the reaction mechanism
and effect
of O<sub>2</sub> on N<sub>2</sub>O reduction by NH<sub>3</sub> over
an Fe–Mordenite (MOR) catalyst. O<sub>2</sub> has no inhibitory
effect on N<sub>2</sub>O reduction, and NH<sub>3</sub> selective catalytic
reduction (SCR) of N<sub>2</sub>O is superior to NH<sub>3</sub> oxidation
by O<sub>2</sub>. We found that the mechanism of NH<sub>3</sub> SCR
of N<sub>2</sub>O involves the redox cycle of FeÂ(III)–OH sites,
with FeÂ(III)–OH reduction by NH<sub>3</sub> as the first and
rate-determining step. Then N<sub>2</sub>O is activated at the reduced
FeÂ(II)–OH sites into NO/N or N<sub>2</sub>/O, reoxidizing the
FeÂ(II)–OH into FeÂ(III)–OH sites. Next, the NO formed
in situ reacts with adsorbed NH<sub>2</sub> to form NH<sub>2</sub>NO, which further decomposes to N<sub>2</sub> and water. In addition,
some NO may join with O to form NO<sub>2</sub>, which reacts with
NH<sub>4</sub><sup>+</sup> to produce NH<sub>4</sub>NO<sub>2</sub> and further decomposes to N<sub>2</sub> and water. It is possible
that under the steady state, N–NO breaking accounts for two-thirds
of N<sub>2</sub>O splitting. The formation of NO intermediates plays
a crucial role in this reaction. The structural arrangement of MOR
zeolites and the high content of Fe ions provides two proximal Fe
ions, that is, FeÂ(III)···FeÂ(III) pairs, as the active
sites for this N–NO breaking, resulting in the high activity
of Fe–MOR
Additional file 3: of Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression
Figure S2. Heatmap with Top 50 Significantly Probes with Drug response (Three Levels) in Terragna et al. [2]. (DOCX 72 kb