Inhibitory effect of dihydroxyacetone onGluconobacter oxydans: Kinetic aspects and expression by mathematical equations

Summary Microbial conversion of glycerol into dihydroxyacetone (DHA) byGluconobacter oxydans was subjected to inhibition by excess substrate. Comparison of cultures containing increasing initial DHA contents (0 to 100 g l^–1) demonstrated that DHA also inhibited this fermentation process. The first effect was on bacterial growth (cellular development stopped when DHA concentration reached 67 gl^–1), and then on oxidation of glycerol (DHA synthesis only occurred when the DHA concentration in the culture medium was lower than 85 g l^–1). Productivity, specific rates and, to a lesser extent, conversion yields decreased as initial concentrations of DHA increased. The changes in the specific parameters according to increasing initial DHA contents were described by general equations. These formulae satisfactorily express the concave aspect of the curves and the reduction in biological activity when the cells were in contact with DHA concentrations of up to 96 g l^–1.Abbreviations X, S, P biomass, substrate, product concentrations - r _x,r _s,r _p rates of growth, consumption and production - ,q _s,q _p specific rates of growth, glycerol consumption and DHA production - Y _x/s, Y_p/s conversion yields of substrate into biomass and product - K _s constant of affinity of cells to the substrate - K _ip product inhibition constant - P _m threshold concentration of DHA in substrate     

SSB蛋白的高效表达及其与ssDNA的相互作用

大肠杆菌单链结合蛋白SSB在DNA复制、重组和修复中起着重要作用。为研究单链结合蛋白SSB的体外生物功能构建了融合蛋白SSB的表达载体并使其高效表达及易于纯化。ssb基因片段是以E.coli K-12基因组为模板经PCR扩增获得,并通过基因的体外拼接成功构建了表达载体pQE30-ssb。重组菌株M15/ pQE30-ssb经过IPTG的诱导表达了蛋白SSB。收集菌体细胞、超声波破碎后离心取上清进行SDS-PAGE分析,结果表明有一与预期分子量（20.6 kD）相应的诱导表达条带出现,其表达量约占全细胞蛋白的30％且以可溶形式存在。利用固定化金属离子（Ni2+）配体亲和层析柱纯化融合蛋白SSB,其纯度达到90％。通过凝胶层析和等离子共振技术对SSB的生物功能进行了系统研究分析。结果表明,SSB蛋白以四聚体形式与单链DNA分子结合,其亲和力常数（KD）为4.79×10-7 M。     

Modelling biomass of mountainous grasslands by including a species composition map

High mountain grasslands offer multiple goods and services to society but are severely threatened by improper land use practices such as abandonment or rapid intensification. In order to reduce abandonment and strengthen the common extensive agricultural practice a sustainable land use management of high mountain grasslands is needed. A spatially detailed yield assessment helps to identify possible meadows or, on the contrary, areas with a low carrying capacity in a region, making it easier to manage these sites. Such assessments are rarely available for remote and inaccessible areas. Remotely sensed vegetation indices are able to provide valuable information on grassland properties. These indices tend, however, to saturate for high biomass. This affects their applicability to assessments of high-yield grasslands.The main aim of this study was to model a spatially explicit grassland yield map and to test whether saturation issues can be tackled by consideration of plant species composition in the modelling process. The high mountain grassland of the subalpine belt (1800 – 2500 m a.s.l.) in the Kazbegi region, Greater Caucasus, Georgia, was chosen as test site for its strong species composition and yield gradients.We first modelled the species composition of the grassland described as metrically scaled gradients in the form of ordination axes by random forest regression. We then derived vegetation indices from Rapid Eye imagery, and topographic variables from a digital elevation model, which we used together with the multispectral bands as predictive variables. For comparison, we performed two yield models, one excluding the species composition maps and one including the species composition map as predictors. Moreover, we performed a third individual model, with species composition as predictors and a split dataset, to produce the final yield map.Three main grassland types were found in the vegetation analysis: Hordeum violaceum-meadows, Gentianella caucasea-grassland and Astragalus captiosus-grassland. The three random forest regression models for the ordination axes explained 64%, 33% and 46% of the variance in species composition. Independent validation of modelled ordination scores against a validation data set resulted in an R² of 0.64, 0.32 and 0.46 for the first, second and third axes, respectively. The model based on species composition resulted in a R² = 0.55, whereas the benchmark model showed weaker relationships between yield and the multispectral reflectance, vegetation indices, and topographical parameters (R² = 0.42). The final random forest yield model used to derive the yield map resulted in 62% variance explained and an R² = 0.64 between predicted and observed biomass. The results further indicate that high yields are generally difficult to predict with both models.The benefit of including a species composition map as a predictor variable for grassland yield lies in the preservation of ecologically meaningful features, especially the occurrence of high yielding vegetation type of Hordeum violaceum meadows is depicted accurately in the map. Even though we used a gradient based design, sharp boundaries or immediate changes in productivity were visible, especially in small structures such as arable fields or roads (Fig. 6b), making it a valuable tool for sustainable land use management. The saturation effect however, was mitigated by using species composition as predictor variables but is still present at high yields.     

Degree-day Models for Predicting Egg Hatch and Population Increase of Criconemella xenoplax

A degree-day model was derived to predict egg hatch for Criconemella xenoplax. Eggs collected from gravid females were incubated in distilled water at constant temperatures of 10-35 C. Sixty-six percent of all eggs hatched between 13 and 32 C, and 42% hatched at 10 C. All eggs aborted above 32.5 C. Between 25 and 32 C, 8.5 ± 0.5 days were required for egg hatch. Degree-day requirement for egg hatch at 10-30 C was estimated to be 154 ± 5 with a base of 9.03 ± 0.04 C. This base of 9 C was adopted in studies of the relationship between degree-days and nematode population increase on Prunus seedlings grown 9-11 weeks in a greenhouse. Degree-day accumulations were based upon daily averages from maximum and minimum air temperatures. Ratios of final to initial population densities exhibited an exponential pattern in relation to degree-day accumulations with proportionate doubling increment of 0.100 ± 0.049 every 139 ± 8 degree-days. These results provide a means of predicting nematode population increase under greenhouse conditions and a basis for choosing sampling intervals when evaluating nematode multiplication.     

Specific allowance for antibody bivalence in the determination of dissociation constants by kinetic exclusion assay

Theory that takes rigorous account of antibody bivalence in the characterization of immunospecific reactions by kinetic exclusion assay is presented. In addition to reinforcing the basic correctness of quantitative expressions currently being used for the determination of dissociation constants (K_d) by this method, the current study highlights a requirement for conformity of the system with critical assumptions/approximations therein. Published results for the interaction between the extracellular domain of human insulin-like growth factor (hIGFR) and anti-hIGFR are used to illustrate aspects of the theoretical predictions for a system to which those assumptions/approximations may well apply; and those for a cadmium–ethylenediaminetetraacetic acid (Cd–EDTA) antibody interaction to emphasize the consequences of adopting the same analytical procedure in a situation where one of those assumptions does not apply. The major weakness of current protocols for the characterization of antigen–antibody interactions by kinetic exclusion assay is an absence of any check on the likely magnitude of the probability of antibody capture by the affinity beads—a parameter that needs to be 5% or lower for validity of the quantitative expression on which the analysis is based.     

Molecular characterization and expression analysis of a gene encoding mannose-binding lectin from bulb of Zephyranthes grandiflora

In this paper we report on the molecular cloning, sequencing and partially characterisation of a lectin from bulb of the Chinese medicinal plant Zephyranthes grandiflora. The full-length cDNA of Z. grandiflora bulb lectin (ZGBL) consisted of 986 bp and contained a 576 bp ORF encoding a 191 amino acid protein. Bioinformatics analysis results clearly indicate that ZGBL belongs to the monocot mannose-binding lectin family, which contains 3 putative mannose-binding sites per subunit. RT-PCR analysis results indicate that ZGBL is constitutively expressed in all the tested tissue types including root, bulb, leaf and flower. Interestingly, ZGBL is more closely related to the Orchidaceae rather than the Amaryllidaceae family on molecular evolution.     

昆虫种群动态非线性建模理论与应用

本文以非线性动力学为基础,对自然界中昆虫种群动态的复杂性、不确定性进行了建模方法的探讨,在讨论了昆虫种群动态的混沌与非线性时间序列预测方法的前提下,以山东省玉米螟等种群动态资料进行了实例分析。     

Macroecology meets macroevolution: evolutionary niche dynamics in the seaweed Halimeda

Aim Because of their broad distribution in geographical and ecological dimensions, seaweeds (marine macroalgae) offer great potential as models for marine biogeographical inquiry and exploration of the interface between macroecology and macroevolution. This study aims to characterize evolutionary niche dynamics in the common green seaweed genus Halimeda, use the observed insights to gain understanding of the biogeographical history of the genus and predict habitats that can be targeted for the discovery of species of special biogeographical interest. Location Tropical and subtropical coastal waters. Methods The evolutionary history of the genus is characterized using molecular phylogenetics and relaxed molecular clock analysis. Niche modelling is carried out with maximum entropy techniques and uses macroecological data derived from global satellite imagery. Evolutionary niche dynamics are inferred through application of ancestral character state estimation. Results A nearly comprehensive molecular phylogeny of the genus was inferred from a six‐locus dataset. Macroecological niche models showed that species distribution ranges are considerably smaller than their potential ranges. We show strong phylogenetic signal in various macroecological niche features. Main conclusions The evolution of Halimeda is characterized by conservatism for tropical, nutrient‐depleted habitats, yet one section of the genus managed to invade colder habitats multiple times independently. Niche models indicate that the restricted geographical ranges of Halimeda species are not due to habitat unsuitability, strengthening the case for dispersal limitation. Niche models identified hotspots of habitat suitability of Caribbean species in the eastern Pacific Ocean. We propose that these hotspots be targeted for discovery of new species separated from their Caribbean siblings since the Pliocene rise of the Central American Isthmus.     

The why,what, where,when and how of goal-directed choice: neuronal and computational principles

The central problems that goal-directed animals must solve are: ‘What do I need and Why, Where and When can this be obtained, and How do I get it?'' or the H4W problem. Here, we elucidate the principles underlying the neuronal solutions to H4W using a combination of neurobiological and neurorobotic approaches. First, we analyse H4W from a system-level perspective by mapping its objectives onto the Distributed Adaptive Control embodied cognitive architecture which sees the generation of adaptive action in the real world as the primary task of the brain rather than optimally solving abstract problems. We next map this functional decomposition to the architecture of the rodent brain to test its consistency. Following this approach, we propose that the mammalian brain solves the H4W problem on the basis of multiple kinds of outcome predictions, integrating central representations of needs and drives (e.g. hypothalamus), valence (e.g. amygdala), world, self and task state spaces (e.g. neocortex, hippocampus and prefrontal cortex, respectively) combined with multi-modal selection (e.g. basal ganglia). In our analysis, goal-directed behaviour results from a well-structured architecture in which goals are bootstrapped on the basis of predefined needs, valence and multiple learning, memory and planning mechanisms rather than being generated by a singular computation.