Free tryptophan pool and tryptophan biosynthetic enzymes in Saccharomyces cerevisiae

The free tryptophan pool and the levels of two enzymes of tryptophan biosynthesis (anthranilate synthase and indoleglycerolphosphate synthase) have been determined in a wild type strain of Saccharomyces cerevisiae and in mutants with altered regulatory properties.The tryptophan pool of wild type cells growing in minimal medium is 0.07 mole per g dry weight. Addition of anthranilate, indole or tryptophan to the medium produces a fifteen- to forty-fold increase in tryptophan pool, but causes no repression of the biosynthetic enzymes. Inclusion of 5-methyltryptophan in the growth medium causes a reduction in growth rate and a derepression of the biosynthetic enzymes, and this is shown here not to be correlated with a decrease in the free tryptophan pool.Mutants with an altered anthranilate synthase showing decreased sensitivity to inhibition by l-tryptophan or by the analogue dl-5-methyltryptophan have a tryptophan pool far higher than the wild type strain, but no repression of indoleglycerolphosphate synthase was observed. Mutants with an anthranilate synthase more sensitive to tryptophan inhibition show a slightly reduced tryptophan pool, but no derepression of indoleglycerolphosphate synthase was found.A mutant with constitutively derepressed levels of the biosynthetic enzymes shows a considerably increased tryptophan pool. Addition of 5-methyltryptophan to the growth medium of non-derepressible mutants causes a decrease in growth rate accompanied by a decrease in the tryptophan pool.Abbreviations CDRP 1-(o-carboxyphenylamino)-1-deoxyribulosephosphate - paba paraaminobenzoic acid - PRA N-(5-phosphoribosyl)-anthranilate - tRNA transfer ribonucleic acid; trp1 to trp5 refer to the structural genes for corresponding tryptophan biosynthetic enzymes     

Specific identification and molecular typing analysis of Lactobacillus johnsonii by using PCR-based methods and pulsed-field gel electrophoresis

A fast and reliable Multiplex-PCR assay was established to identify the species Lactobacillus johnsonii. Two opposing rRNA gene-targeted primers have been designed for this specific PCR detection. Specificity was verified with DNA samples isolated from different lactic acid bacteria. Out of 47 Lactobacillus strains isolated from different environments, 16 were identified as L. johnsonii by PCR. The same set of strains was investigated with five alternative molecular typing methods: enterobacterial repetitive intergenic consensus PCR (ERIC-PCR), repetitive extragenic palindromic PCR (REP-PCR), amplified fragment length polymorphism, single triplicate arbitrarily primed PCR, and pulsed-field gel electrophoresis in order to compare the discriminatory power of these methods. The reported data strongly support the highly significant heterogeneity among all L. johnsonii isolates, potentially linked to their origin of isolation. The use of species-specific primers as well as rapid and highly powerful PCR-based molecular typing tools (namely ERIC- and REP-PCR techniques) should be respectively envisaged for identifying, differentiating and monitoring L. johnsonii strains from various environmental samples, for product monitoring, for species tracing in clinical studies as well as bacterial profiling of various microecological or gastrointestinal environments.     

<Emphasis Type="Italic">Physcomitrella patens</Emphasis> is highly tolerant against drought,salt and osmotic stress

In order to determine the degree of tolerance of the moss Physcomitrella patens to different abiotic stress conditions, we examined its tolerance against salt, osmotic and dehydration stress. Compared to other plants like Arabidopsis thaliana, P. patens exhibits a high degree of abiotic stress tolerance, making it a valuable source for the identification of genes effecting the stress adaptation. Plants that had been treated with NaCl tolerated concentrations up to 350 mM. Treatments with sorbitol revealed that plants are able to survive concentrations up to 500 mM. Furthermore, plants that had lost 92% water on a fresh-weight basis were able to recover successfully. For molecular analyses, a P. patens expressed sequence tag (EST) database was searched for cDNA sequences showing homology to stress-associated genes of seed plants and bacteria. 45 novel P. patens genes were identified and subjected to cDNA macroarray analyses to define their expression pattern in response to water deficit. Among the selected cDNAs, we were able to identify a set of genes that is specifically up-regulated upon dehydration. These genes encode proteins exerting their function in maintaining the integrity of the plant cell as well as proteins that are known to be members of signaling networks. The identified genes will serve as molecular markers and potential targets for future functional analyses.     

Rapid alteration of the phosphoproteome in the moss Physcomitrella patens after cytokinin treatment

Cytokinin hormones are crucial regulators of a large number of processes in plant development. Recently, significant progress has been made toward the elucidation of the molecular details of cytokinin that has led to a model for signal transduction involving a phosphorylation cascade. However, the current knowledge of cytokinin action remains largely unknown and does not explain the different roles of this hormone. To gain further insights into this aspect of cytokinin action and the inducible phosphorelay, we have produced the first large-scale map of a phosphoproteome in the moss Physcomitrella patens. Using a protocol that we recently published (Heintz, D.; et al. Electrophoresis 2004, 25, 1149-1159) that combines IMAC, MALDI-TOF-MS, and LC-MS/MS, a total of 172 phosphopeptide sequences were obtained by a peptide de novo sequencing strategy. Specific P. patens EST and raw genomic databases were interrogated, and protein homology searches resulted in the identification of 112 proteins that were then classified into functional categories. In addition, the temporal dynamics of the phosphoproteome in response to cytokinin stimulation was studied at 2, 4, 6, and 15 min after hormone addition. We identified 13 proteins that were not previously known targets of cytokinin action. Among the responsive proteins, some were involved in metabolism, and several proteins of unknown function were also identified. We have mapped the time course of their activation in response to cytokinin and discussed their hypothetical biological significance. Deciphering these early induced phosphorylation events has shown that the cytokinin effect can be rapid (few minutes), and the duration of this effect can be variable. Also phosphorylation events can be differentially regulated. Taken together our proteomic study provides an enriched look of the multistep phosphorelay system mediating cytokinin response and suggests the existence of a multidirectional interaction between cytokinin and numerous other pathways.     

氨氧化古菌的生态学研究进展

上百年来细菌一直被认为是地球氨氧化过程的主要驱动者,2005年海洋中分离到迄今唯一的非极端环境泉古菌,发现其氧化氨态氮获得能源生长,是氨氧化古菌。氨氧化古菌和细菌对地球氨氧化过程的相对贡献率,是目前全球氮循环研究最重要的微生物生态学问题之一。已有的证据表明古菌在海洋氨氧化过程中发挥了重要作用,细菌则是土壤氨氧化过程的主要驱动者。本文重点探讨了原位自然环境下氨氧化古菌的生态学研究进展。     

Leaf chlorophyll content as a proxy for leaf photosynthetic capacity

Improving the accuracy of estimates of forest carbon exchange is a central priority for understanding ecosystem response to increased atmospheric CO₂ levels and improving carbon cycle modelling. However, the spatially continuous parameterization of photosynthetic capacity (Vcmax) at global scales and appropriate temporal intervals within terrestrial biosphere models (TBMs) remains unresolved. This research investigates the use of biochemical parameters for modelling leaf photosynthetic capacity within a deciduous forest. Particular attention is given to the impacts of seasonality on both leaf biophysical variables and physiological processes, and their interdependent relationships. Four deciduous tree species were sampled across three growing seasons (2013–2015), approximately every 10 days for leaf chlorophyll content (Chl_Leaf) and canopy structure. Leaf nitrogen (N_Area) was also measured during 2014. Leaf photosynthesis was measured during 2014–2015 using a Li‐6400 gas‐exchange system, with A‐Ci curves to model Vcmax. Results showed that seasonality and variations between species resulted in weak relationships between Vcmax normalized to 25°C () and N_Area (R² = 0.62, P < 0.001), whereas Chl_Leaf demonstrated a much stronger correlation with (R² = 0.78, P < 0.001). The relationship between Chl_Leaf and N_Area was also weak (R² = 0.47, P < 0.001), possibly due to the dynamic partitioning of nitrogen, between and within photosynthetic and nonphotosynthetic fractions. The spatial and temporal variability of was mapped using Landsat TM/ETM satellite data across the forest site, using physical models to derive Chl_Leaf. TBMs largely treat photosynthetic parameters as either fixed constants or varying according to leaf nitrogen content. This research challenges assumptions that simple N_Area– relationships can reliably be used to constrain photosynthetic capacity in TBMs, even within the same plant functional type. It is suggested that Chl_Leaf provides a more accurate, direct proxy for and is also more easily retrievable from satellite data. These results have important implications for carbon modelling within deciduous ecosystems.     

Methods to account for spatial autocorrelation in the analysis of species distributional data: a review

Species distributional or trait data based on range map (extent‐of‐occurrence) or atlas survey data often display spatial autocorrelation, i.e. locations close to each other exhibit more similar values than those further apart. If this pattern remains present in the residuals of a statistical model based on such data, one of the key assumptions of standard statistical analyses, that residuals are independent and identically distributed (i.i.d), is violated. The violation of the assumption of i.i.d. residuals may bias parameter estimates and can increase type I error rates (falsely rejecting the null hypothesis of no effect). While this is increasingly recognised by researchers analysing species distribution data, there is, to our knowledge, no comprehensive overview of the many available spatial statistical methods to take spatial autocorrelation into account in tests of statistical significance. Here, we describe six different statistical approaches to infer correlates of species’ distributions, for both presence/absence (binary response) and species abundance data (poisson or normally distributed response), while accounting for spatial autocorrelation in model residuals: autocovariate regression; spatial eigenvector mapping; generalised least squares; (conditional and simultaneous) autoregressive models and generalised estimating equations. A comprehensive comparison of the relative merits of these methods is beyond the scope of this paper. To demonstrate each method's implementation, however, we undertook preliminary tests based on simulated data. These preliminary tests verified that most of the spatial modeling techniques we examined showed good type I error control and precise parameter estimates, at least when confronted with simplistic simulated data containing spatial autocorrelation in the errors. However, we found that for presence/absence data the results and conclusions were very variable between the different methods. This is likely due to the low information content of binary maps. Also, in contrast with previous studies, we found that autocovariate methods consistently underestimated the effects of environmental controls of species distributions. Given their widespread use, in particular for the modelling of species presence/absence data (e.g. climate envelope models), we argue that this warrants further study and caution in their use. To aid other ecologists in making use of the methods described, code to implement them in freely available software is provided in an electronic appendix.