ترغب بنشر مسار تعليمي؟ اضغط هنا

Zinc oxide induces the stringent response and major reorientations in the central metabolism of Bacillus subtilis

79   0   0.0 ( 0 )
 نشر من قبل Nathalie Gon
 تاريخ النشر 2018
  مجال البحث علم الأحياء
والبحث باللغة English
 تأليف Sylvie Luche




اسأل ChatGPT حول البحث

Microorganisms, such as bacteria, are one of the first targets of nanoparticles in the environment. In this study, we tested the effect of two nanoparticles, ZnO and TiO2, with the salt ZnSO4 as the control, on the Gram-positive bacterium Bacillus subtilis by 2D gel electrophoresis-based proteomics. Despite a significant effect on viability (LD50), TiO2 NPs had no detectable effect on the proteomic pattern, while ZnO NPs and ZnSO4 significantly modified B. subtilis metabolism. These results allowed us to conclude that the effects of ZnO observed in this work were mainly attributable to Zn dissolution in the culture media. Proteomic analysis highlighted twelve modulated proteins related to central metabolism: MetE and MccB (cysteine metabolism), OdhA, AspB, IolD, AnsB, PdhB and YtsJ (Krebs cycle) and XylA, YqjI, Drm and Tal (pentose phosphate pathway). Biochemical assays, such as free sulfhydryl, CoA-SH and malate dehydrogenase assays corroborated the observed central metabolism reorientation and showed that Zn stress induced oxidative stress, probably as a consequence of thiol chelation stress by Zn ions. The other patterns affected by ZnO and ZnSO4 were the stringent response and the general stress response. Nine proteins involved in or controlled by the stringent response showed a modified expression profile in the presence of ZnO NPs or ZnSO4: YwaC, SigH, YtxH, YtzB, TufA, RplJ, RpsB, PdhB and Mbl. An increase in the ppGpp concentration confirmed the involvement of the stringent response during a Zn stress. All these metabolic reorientations in response to Zn stress were probably the result of complex regulatory mechanisms including at least the stringent response via YwaC.



قيم البحث

اقرأ أيضاً

151 - Areejit Samal , Sanjay Jain 2007
Elucidating the architecture and dynamics of large scale genetic regulatory networks of cells is an important goal in systems biology. We study the system level dynamical properties of the genetic network of Escherichia coli that regulates its metabo lism, and show how its design leads to biologically useful cellular properties. Our study uses the database (Covert et al., Nature 2004) containing 583 genes and 96 external metabolites which describes not only the network connections but also the boolean rule at each gene node that controls the switching on or off of the gene as a function of its inputs. We have studied how the attractors of the boolean dynamical system constructed from this database depend on the initial condition of the genes and on various environmental conditions corresponding to buffered minimal media. We find that the system exhibits homeostasis in that its attractors, that turn out to be fixed points or low period cycles, are highly insensitive to initial conditions or perturbations of gene configurations for any given fixed environment. At the same time the attractors show a wide variation when external media are varied implying that the system mounts a highly flexible response to changed environmental conditions. The regulatory dynamics acts to enhance the cellular growth rate under changed media. Our study shows that the reconstructed genetic network regulating metabolism in {it E. coli} is hierarchical, modular, and largely acyclic, with environmental variables controlling the root of the hierarchy. This architecture makes the cell highly robust to perturbations of gene configurations as well as highly responsive to environmental changes. The twin properties of homeostasis and response flexibility are achieved by this dynamical system even though it is not close to the edge of chaos.
We generalize and systematize basic experimental data on optical and luminescence properties of ZnO single crystals, thin films, powders, ceramics, and nanocrystals. We consider and study mechanisms by which two main emission bands occur, a short-wav elength band near the fundamental absorption edge and a broad long-wavelength band, the maximum of which usually lies in the green spectral range. We determine a relationship between the two luminescence bands and study in detail the possibility of controlling the characteristics of ZnO by varying the maximum position of the short-wavelength band. We show that the optical and luminescence characteristics of ZnO largely depend on the choice of the corresponding impurity and the parameters of the synthesis and subsequent treatment of the sample. Prospects for using zinc oxide as a scintillator material are discussed. Additionally, we consider experimental results that are of principal interest for practice.
The wide bandgap semiconductor ZnO is interesting for spintronic applications because of its small spin-orbit coupling implying a large spin coherence length. Utilizing vertical spin valve devices with ferromagnetic electrodes (TiN/Co/ZnO/Ni/Au), we study the spin-polarized transport across ZnO in all-electrical experiments. The measured magnetoresistance agrees well with the prediction of a two spin channel model with spin-dependent interface resistance. Fitting the data yields spin diffusion lengths of 10.8nm (2K), 10.7nm (10K), and 6.2nm (200K) in ZnO, corresponding to spin lifetimes of 2.6ns (2K), 2.0ns (10K), and 31ps (200K).
Many organisms repartition their proteome in a circadian fashion in response to the daily nutrient changes in their environment. A striking example is provided by cyanobacteria, which perform photosynthesis during the day to fix carbon. These organis ms not only face the challenge of rewiring their proteome every 12 hours, but also the necessity of storing the fixed carbon in the form of glycogen to fuel processes during the night. In this manuscript, we extend the framework developed by Hwa and coworkers (Scott et al., Science 330, 1099 (2010)) for quantifying the relatinship between growth and proteome composition to circadian metabolism. We then apply this framework to investigate the circadian metabolism of the cyanobacterium Cyanothece, which not only fixes carbon during the day, but also nitrogen during the night, storing it in the polymer cyanophycin. Our analysis reveals that the need to store carbon and nitrogen tends to generate an extreme growth strategy, in which the cells predominantly grow during the day, as observed experimentally. This strategy maximizes the growth rate over 24 hours, and can be quantitatively understood by the bacterial growth laws. Our analysis also shows that the slow relaxation of the proteome, arising from the slow growth rate, puts a severe constraint on implementing this optimal strategy. Yet, the capacity to estimate the time of the day, enabled by the circadian clock, makes it possible to anticipate the daily changes in the environment and mount a response ahead of time. This significantly enhances the growth rate by counteracting the detrimental effects of the slow proteome relaxation.
Deciphering gene regulatory networks is a central problem in computational biology. Here, we explore the use of multi-modal neural networks to learn predictive models of gene expression that include cis and trans regulatory components. We learn model s of stress response in the budding yeast Saccharomyces cerevisiae. Our models achieve high performance and substantially outperform other state-of-the-art methods such as boosting algorithms that use pre-defined cis-regulatory features. Our model learns several cis and trans regulators including well-known master stress response regulators. We use our models to perform in-silico TF knock-out experiments and demonstrate that in-silico predictions of target gene changes correlate with the results of the corresponding TF knockout microarray experiment.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا