Burkholderia cenocepacia Lipopolysaccharide Modification and Flagellin Glycosylation Affect Virulence but Not Innate Immune Recognition in Plants

Burkholderia cenocepacia causes opportunistic infections in plants, insects, animals, and humans, suggesting that “virulence” depends on the host and its innate susceptibility to infection. We hypothesized that modifications in key bacterial molecules recognized by the innate immune system modulate host responses to B. cenocepacia. Indeed, modification of lipo- polysaccharide (LPS) with 4-amino-4-deoxy-L-arabinose and flagellin glycosylation attenuates B. cenocepacia infection in Arabi- dopsis thaliana and Galleria mellonella insect larvae. However, B. cenocepacia LPS and flagellin triggered rapid bursts of nitric oxide and reactive oxygen species in A. thaliana leading to activation of the PR-1 defense gene. These responses were drastically reduced in plants with fls2 (flagellin FLS2 host receptor kinase), Atnoa1 (nitric oxide-associated protein 1), and dnd1-1 (reduced production of nitric oxide) null mutations. Together, our results indicate that LPS modification and flagellin glycosylation do not affect recognition by plant receptors but are required for bacteria to establish overt infection.

Uncertainty in the Cloud: An Angel-Daemon Approach to Modelling Performance

Uncertainty profiles are used to study the effects of contention within cloud and service-based environments. An uncertainty profile provides a qualitative description of an environment whose quality of service (QoS) may fluctuate unpredictably. Uncertain environments are modelled by strategic games with two agents; a daemon is used to represent overload and high resource contention; an angel is used to represent an idealised resource allocation situation with no underlying contention. Assessments of uncertainty profiles are useful in two ways: firstly, they provide a broad understanding of how environmental stress can effect an application’s performance (and reliability); secondly, they allow the effects of introducing redundancy into a computation to be assessed

ArnT proteins that catalyse the glycosylation of lipopolysaccharide share common features with bacterial N-oligosaccharyltransferases

ArnT is a glycosyltransferase that catalyses the addition of 4-amino-4-deoxy-L-arabinose (L-Ara4N) to the lipid A moiety of the lipopolysaccharide. This is a critical modification enabling bacteria to resist killing by antimicrobial peptides. ArnT is an integral inner membrane protein consisting of 13 predicted transmembrane helices and a large periplasmic C-terminal domain. We report here the identification of a functional motif with a canonical consensus sequence DEXRYAX(5)MX(3)GXWX(9)YFEKPX(4)W spanning the first periplasmic loop, which is highly conserved in all ArnT proteins examined. Site-directed mutagenesis demonstrated the contribution of this motif in ArnT function, suggesting that these proteins have a common mechanism. We also demonstrate that the Burkholderia cenocepacia and Salmonella enterica serovar Typhimurium ArnT C-terminal domain is required for polymyxin B resistance in vivo. Deletion of the C-terminal domain in B. cenocepacia ArnT resulted in a protein with significantly reduced in vitro binding to a lipid A fluorescent substrate and unable to catalyse lipid A modification with L-Ara4N. An in silico predicted structural model of ArnT strongly resembled the tertiary structure of Campylobacter lari PglB, a bacterial oligosaccharyltransferase involved in protein N-glycosylation. Therefore, distantly related oligosaccharyltransferases from ArnT and PglB families operating on lipid and polypeptide substrates, respectively, share unexpected structural similarity that could not be predicted from direct amino acid sequence comparisons. We propose that lipid A and protein glycosylation enzymes share a conserved catalytic mechanism despite their evolutionary divergence.

Tyrosine phosphorylation and dephosphorylation in Burkholderia cenocepacia affect biofilm formation, growth under nutritional deprivation, and pathogenicity

Burkholderia cenocepacia, a member of the B. cepacia complex (Bcc), is an opportunistic pathogen causing serious chronic infections in patients with cystic fibrosis. Tyrosine phosphorylation has emerged as an important post-translational modification modulating the physiology and pathogenicity of Bcc bacteria. Here, we investigated the predicted bacterial tyrosine kinases BCAM1331 and BceF, and the low molecular weight protein tyrosine phosphatases BCAM0208, BceD and BCAL2200 of B. cenocepacia K56-2. We show that BCAM1331, BceF, BCAM0208 and BceD contributed to biofilm formation, while BCAL2200 was required for growth in nutrient-limited conditions. Multiple deletions of either tyrosine kinase or low molecular weight protein tyrosine phosphatases genes resulted in attenuation of B. cenocepacia intramacrophage survival and reduced pathogenicity in the Galleria mellonella larvae infection model. Experimental evidence indicates that BCAM1331 displays a reduced
tyrosine autophosphorylation activity compared to BceF. Using the artificial substrate p-nitrophenyl phosphate, the phosphatase activity of the three low molecular weight protein tyrosine phosphatases demonstrated similar kinetic parameters. However, only BCAM0208 and BceD could dephosphorylate BceF. Further, BCAL2200 becomes tyrosine phosphorylated in vivo and catalyzes its auto-dephosphorylation. Together, our data suggest that despite having similar biochemical activities low molecular weight protein tyrosine phosphatases and tyrosine kinases have both overlapping and specific roles in the physiology of B. cenocepacia.

Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems

Real-space grids are a powerful alternative for the simulation of electronic systems. One of the main advantages of the approach is the flexibility and simplicity of working directly in real space where the different fields are discretized on a grid, combined with competitive numerical performance and great potential for parallelization. These properties constitute a great advantage at the time of implementing and testing new physical models. Based on our experience with the Octopus code, in this article we discuss how the real-space approach has allowed for the recent development of new ideas for the simulation of electronic systems. Among these applications are approaches to calculate response properties, modeling of photoemission, optimal control of quantum systems, simulation of plasmonic systems, and the exact solution of the Schrödinger equation for low-dimensionality systems.