Two-Component Signal Transduction System SaeRS Positively Regulates Staphylococcus epidermidis

Staphylococcus epidermidis, which is a causative pathogen of nosocomial infection, expresses its virulent traits such as biofilm and autolysis regulated by two-component signal transduction system SaeRS. In this study, we performed a proteomic analysis of differences in expression between the S. epidermidis 1457 wild-type and saeRS mutant to identify candidates regulated by saeRS using two-dimensional gel electrophoresis (2-DE) combined with matrix-assisted laser desorption/lonization mass spectrometry (MALDI-TOF-MS). Of 55 identified proteins that significantly differed in expression between the two strains, 15 were upregulated and 40 were downregulated. The downregulated proteins included enzymes related to glycolysis and TCA cycle, suggesting that glucose is not properly utilized in S. epidermidis when saeRS was deleted. The study will be helpful for treatment of S. epidermidis infection from the viewpoint of metabolic modulation dependent on two-component signal transduction system SaeRS

Molecular and cellular mechanisms of neutral lipid accumulation in diatom following nitrogen deprivation

Abstract Background Nitrogen limitation can induce neutral lipid accumulation in microalgae, as well as inhibiting their growth. Therefore, to obtain cultures with both high biomass and high lipid contents, and explore the lipid accumulation mechanisms, we implemented nitrogen deprivation in a model diatom Phaeodactylum tricornutum at late exponential phase. Results Neutral lipid contents per cell subsequently increased 2.4-fold, both the number and total volume of oil bodies increased markedly, and cell density rose slightly. Transcriptional profile analyzed by RNA-Seq showed that expression levels of 1213 genes (including key carbon fixation, TCA cycle, glycerolipid metabolism and nitrogen assimilation genes) increased, with a false discovery rate cut-off of 0.001, under N deprivation. However, most light harvesting complex genes were down-regulated, extensive degradation of chloroplast membranes was observed under an electron microscope, and photosynthetic efficiency declined. Further identification of lipid classes showed that levels of MGDG and DGDG, the main lipid components of chloroplast membranes, dramatically decreased and triacylglycerol (TAG) levels significantly rose, indicating that intracellular membrane remodeling substantially contributed to the neutral lipid accumulation. Conclusions Our findings shed light on the molecular mechanisms of neutral lipid accumulation and the key genes involved in lipid metabolism in diatoms. They also provide indications of possible strategies for improving microalgal biodiesel production.http://deepblue.lib.umich.edu/bitstream/2027.42/112455/1/13068_2012_Article_291.pd

ApoE attenuates unresolvable inflammation by complex formation with activated C1q

Apolipoprotein-E (ApoE) has been implicated in Alzheimer's disease, atherosclerosis, and other unresolvable inflammatory conditions but a common mechanism of action remains elusive. We found in ApoE-deficient mice that oxidized lipids activated the classical complement cascade (CCC), resulting in leukocyte infiltration of the choroid plexus (ChP). All human ApoE iso-forms attenuated CCC activity via high-affinity binding to the activated CCC-initiating C1q protein (K-D similar to 140-580 pM) in vitro, and C1q-ApoE complexes emerged as markers for ongoing complement activity of diseased ChPs, A beta plaques, and atherosclerosis in vivo. C1q-ApoE complexes in human ChPs, A beta plaques, and arteries correlated with cognitive decline and atherosclerosis, respectively. Treatment with small interfering RNA (siRNA) against C5, which is formed by all complement pathways, attenuated murine ChP inflammation, A beta-associated microglia accumulation, and atherosclerosis. Thus, ApoE is a direct checkpoint inhibitor of unresolvable inflammation, and reducing C5 attenuates disease burden

Systematic Planning of Genome-Scale Experiments in Poorly Studied Species

Genome-scale datasets have been used extensively in model organisms to screen for specific candidates or to predict functions for uncharacterized genes. However, despite the availability of extensive knowledge in model organisms, the planning of genome-scale experiments in poorly studied species is still based on the intuition of experts or heuristic trials. We propose that computational and systematic approaches can be applied to drive the experiment planning process in poorly studied species based on available data and knowledge in closely related model organisms. In this paper, we suggest a computational strategy for recommending genome-scale experiments based on their capability to interrogate diverse biological processes to enable protein function assignment. To this end, we use the data-rich functional genomics compendium of the model organism to quantify the accuracy of each dataset in predicting each specific biological process and the overlap in such coverage between different datasets. Our approach uses an optimized combination of these quantifications to recommend an ordered list of experiments for accurately annotating most proteins in the poorly studied related organisms to most biological processes, as well as a set of experiments that target each specific biological process. The effectiveness of this experiment- planning system is demonstrated for two related yeast species: the model organism Saccharomyces cerevisiae and the comparatively poorly studied Saccharomyces bayanus. Our system recommended a set of S. bayanus experiments based on an S. cerevisiae microarray data compendium. In silico evaluations estimate that less than 10% of the experiments could achieve similar functional coverage to the whole microarray compendium. This estimation was confirmed by performing the recommended experiments in S. bayanus, therefore significantly reducing the labor devoted to characterize the poorly studied genome. This experiment-planning framework could readily be adapted to the design of other types of large-scale experiments as well as other groups of organisms