Borrelia burgdorferi membranes are the primary targets of reactive oxygen species

Spirochetes living in an oxygen-rich environment or when challenged by host immune cells are exposed to reactive oxygen species (ROS). These species can harm/destroy cysteinyl residues, iron-sulphur clusters, DNA and polyunsaturated lipids, leading to inhibition of growth or cell death. Because Borrelia burgdorferi contains no intracellular iron, DNA is most likely not a major target for ROS via Fenton reaction. In support of this, growth of B. burgdorferi in the presence of 5 mM H2O2 had no effect on the DNA mutation rate (spontaneous coumermycin A1 resistance), and cells treated with 10 mM t-butyl hydroperoxide or 10 mM H2O2 show no increase in DNA damage. Unlike most bacteria, B. burgdorferi incorporates ROS-susceptible polyunsaturated fatty acids from the environment into their membranes. Analysis of lipoxidase-treated B. burgdorferi cells by Electron Microscopy showed significant irregularities indicative of membrane damage. Fatty acid analysis of cells treated with lipoxidase indicated that host-derived linoleic acid had been dramatically reduced (50-fold) in these cells, with a corresponding increase in the levels of malondialdehyde by-product (fourfold). These data suggest that B. burgdorferi membrane lipids are targets for attack by ROS encountered in the various stages of the infective cycle

Nip1p associates with 40 S ribosomes and the Prt1p subunit of eukaryotic initiation factor 3 and is required for efficient translation initiation

Nip1p is an essential Saccharomyces cerevisiae protein that was identified in a screen for temperature conditional (ts) mutants exhibiting defects in nuclear transport. New results indicate that Nip1p has a primary role in translation initiation. Polysome profiles indicate that cells depleted of Nip1p and nip1-1 cells are defective in translation initiation, a conclusion that is supported by a reduced rate of protein synthesis in Nip1p- depleted cells. Nip1p cosediments with free 40 S ribosomal subunits and polysomal preinitiation complexes, but not with free or elongating 80 S ribosomes or 60 S subunits. Nip1p can be isolated in an about 670-kDa complex containing polyhistidine-tagged Prt1p, a subunit of translation initiation factor 3, by binding to Ni2+NTA-agarose beads in a manner completely dependent on the tagged form of Prt1p. The nip1-1 ts growth defect was suppressed by the deletion of the ribosomal protein, RPL46. Also, nip1-1 mutant cells are hypersensitive to paromomycin. These results suggest that Nip1p is a subunit of eukaryotic initiation factor 3 required for efficient translation initiation

RNA sensors: novel regulators of gene expression

RNA-mediated control can evolve far more rapidly than mechanisms that rely on proteins, creating selective advantages in adaptive gene regulation. Recently, evidence has emerged that messenger RNA is a source of cis-acting RNA elements that sense external signals and thereby regulate gene expression. With exquisite specificity, metabolite-sensing riboswitches control the formation or translation of prokaryotic mRNA. In eukaryotes, RNA sensors in human antiviral cytokine genes that encode tumour necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) have been shown to activate strongly the RNA-dependent protein kinase PKR, a stress kinase that is also activated by double-stranded RNA—a hallmark of viral infection. These cis-acting RNA elements in the TNF-α and IFN-γ transcripts function as sensors of intracellular PKR levels and regulate gene expression at the level of mRNA splicing and translation, respectively. Although RNA sensors in bacteria may be remnants of an ancient RNA world, it is likely that they form an integral part of higher eukaryotic genomes as well

Linking transcriptional regulation and high resolution metabolic fluxes in yeast modulated by the global regulator Gcn4p

Genome sequencing dramatically increased our ability to understand cellular response to perturbation. Integrating system-wide measurements such as gene expression with networks of protein protein interactions and transcription factor binding revealed critical insights into cellular behavior. However, the potential of systems biology approaches is limited by difficulties in integrating metabolic measurements across the functional levels of the cell despite their being most closely linked to cellular phenotype. To address this limitation, we developed a model-based approach to correlate mRNA and metabolic flux data that combines information from both interaction network models and flux determination models. We started by quantifying 5,764 mRNAs, 54 metabolites, and 83 experimental (13)C-based reaction fluxes in continuous cultures of yeast under stress in the absence or presence of global regulator Gcn4p. Although mRNA expression alone did not directly predict metabolic response, this correlation improved through incorporating a network-based model of amino acid biosynthesis (from r = 0.07 to 0.80 for mRNA-flux agreement). The model provides evidence of general biological principles: rewiring of metabolic flux (i.e., use of different reaction pathways) by transcriptional regulation and metabolite interaction density (i.e., level of pairwise metabolite-protein interactions) as a key biosynthetic control determinant. Furthermore, this model predicted flux rewiring in studies of follow-on transcriptional regulators that were experimentally validated with additional (13)C-based flux measurements. As a first step in linking metabolic control and genetic regulatory networks, this model underscores the importance of integrating diverse data types in large-scale cellular models. We anticipate that an integrated approach focusing on metabolic measurements will facilitate construction of more realistic models of cellular regulation for understanding diseases and constructing strains for industrial applications