PhoR/PhoP two component regulatory system affects biocontrol capability of Bacillus subtilis NCD-2

The Bacillus subtilis strain NCD-2 is an important biocontrol agent against cotton verticillium wilt and cotton sore shin in the field, which are caused by Verticillium dahliae Kleb and Rhizoctonia solani Kuhn, respectively. A mutant of strain NCD-2, designated M216, with decreased antagonism to V. dahliae and R. solani, was selected by mini-Tn10 mutagenesis and in vitro virulence screening. The inserted gene in the mutant was cloned and identified as the phoR gene, which encodes a sensor kinase in the PhoP/PhoR two-component system. Compared to the wild-type strain, the APase activities of the mutant was decreased significantly when cultured in low phosphate medium, but no obvious difference was observed when cultured in high phosphate medium. The mutant also grew more slowly on organic phosphate agar and lost its phosphatidylcholine-solubilizing ability. The suppression of cotton seedling damping-off in vivo and colonization of the rhizosphere of cotton also decreased in the mutant strain when compared with the wild type strain. All of these characteristics could be partially restored by complementation of the phoR gene in the M216 mutant

Problems with Using the Normal Distribution – and Ways to Improve Quality and Efficiency of Data Analysis

Background: The Gaussian or normal distribution is the most established model to characterize quantitative variation of original data. Accordingly, data are summarized using the arithmetic mean and the standard deviation, by x 6 SD, or with the standard error of the mean, x 6 SEM. This, together with corresponding bars in graphical displays has become the standard to characterize variation. Methodology/Principal Findings: Here we question the adequacy of this characterization, and of the model. The published literature provides numerous examples for which such descriptions appear inappropriate because, based on the ‘‘95 % range check’’, their distributions are obviously skewed. In these cases, the symmetric characterization is a poor description and may trigger wrong conclusions. To solve the problem, it is enlightening to regard causes of variation. Multiplicative causes are by far more important than additive ones, in general, and benefit from a multiplicative (or log-) normal approach. Fortunately, quite similar to the normal, the log-normal distribution can now be handled easily and characterized at the level of the original data with the help of both, a new sign, x /, times-divide, and notation. Analogous to x 6 SD, it connects the multiplicative (or geometric) mean x * and the multiplicative standard deviation s * in the form x * x /s*, that is advantageous and recommended. Conclusions/Significance: The corresponding shift from the symmetric to the asymmetric view will substantially increas

Biocontrol Potential of Forest Tree Endophytes

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