Molecular analysis of fungal communities and laccase genes in decomposing litter reveals differences among forest types but no impact of nitrogen deposition

The fungal community of the forest floor was examined as the cause of previously reported increases in soil organic matter due to experimental N deposition in ecosystems producing predominantly high-lignin litter, and the opposite response in ecosystems producing low-lignin litter. The mechanism proposed to explain this phenomenon was that white-rot basidiomycetes are more important in the degradation of high-lignin litter than of low-lignin litter, and that their activity is suppressed by N deposition. We found that forest floor mass in the low-lignin sugar-maple dominated system decreased in October due to experimental N deposition, whereas forest floor mass of high-lignin oak-dominated ecosystems was unaffected by N deposition. Increased relative abundance of basidiomycetes in high-lignin forest floor was confirmed by denaturing gradient gel electrophoresis (DGGE) and sequencing. Abundance of basidiomycete laccase genes, encoding an enzyme used by white-rot basidiomycetes in the degradation of lignin, was 5-10 times greater in high-lignin forest floor than in low-lignin forest floor. While the differences between the fungal communities in different ecosystems were consistent with the proposed mechanism, no significant effects of N deposition were detected on DGGE profiles, laccase gene abundance, laccase length heterogeneity profiles, or phenol oxidase activity. Our observations indicate that the previously detected accumulation of soil organic matter in the high-lignin system may be driven by effects of N deposition on organisms in the mineral soil, rather than on organisms residing in the forest floor. However, studies of in situ gene expression and temporal and spatial variability within forest floor communities will be necessary to further relate the ecosystem dynamics of organic carbon to microbial communities and atmospheric N deposition.     

Evolutionary optimization of classifiers and features for single-trial EEG Discrimination

Background  

State-of-the-art signal processing methods are known to detect information in single-trial event-related EEG data, a crucial aspect in development of real-time applications such as brain computer interfaces. This paper investigates one such novel approach, evaluating how individual classifier and feature subset tailoring affects classification of single-trial EEG finger movements. The discrete wavelet transform was used to extract signal features that were classified using linear regression and non-linear neural network models, which were trained and architecturally optimized with evolutionary algorithms. The input feature subsets were also allowed to evolve, thus performing feature selection in a wrapper fashion. Filter approaches were implemented as well by limiting the degree of optimization.     

Classifying Life-Style Types of Phytoseiid Mites:Diagnostic Traits

Several traits are useful for identifying life-style types of predaceous phytoseiid mites when either 2 (diet generalist-specialist) or 4 (specialist I and II-generalist III and IV) type models [McMurtry J.A. and Croft B.A. 1997. Annu. Rev. Entomol. 42: 291-321] are considered. Traits useful for both models are developmental time and oviposition rates when feeding on several food types. Discriminating for the 2-types model are dorsal shield setae lengths, and intra- and inter-specific predation. Another trait useful for both models is feeding preferences of adult female phytoseiids on eggs versus larvae of Tetranychus urticae Koch. In this paper, we review established and other traits that need more study such as mouthpart types, other morphological features, spider mite webbing effects, distributions relative to prey-foods, plant-host relationships including domatia and sap feeding, density-dependent responses to prey and predator-prey ratios required for biological control. Uses of life-style data in biological control decision-making are discussed.     

Metabolic engineering through cofactor manipulation and its effects on metabolic flux redistribution in Escherichia coli

Applications of genetic engineering or metabolic engineering have increased in both academic and industrial institutions. Most current metabolic engineering studies have focused on enzyme levels and on the effect of the amplification, addition, or deletion of a particular pathway. Although it is generally known that cofactors play a major role in the production of different fermentation products, their role has not been thoroughly and systematically studied. It is conceivable that in cofactor-dependent production systems, cofactor availability and the proportion of cofactor in the active form may play an important role in dictating the overall process yield. Hence, the manipulation of these cofactor levels may be crucial in order to further increase production. We have demonstrated that manipulation of cofactors can be achieved by external and genetic means and these manipulations have the potential to be used as an additional tool to achieve desired metabolic goals. We have shown experimentally that the NADH/NAD(+) ratio can be altered by using carbon sources with different oxidation states. We have shown further that the metabolite distribution can be influenced by a change in the NADH/NAD(+) ratio as mediated by the oxidation state of the carbon source used. We have also demonstrated that the total NAD(H/(+)) levels can be increased by the overexpression of the pncB gene. The increase in the total NAD(H/(+)) levels can be achieved even in a complex medium, which is commonly used by most industrial processes. Finally, we have shown that manipulation of the CoA pool/flux can be used to increase the productivity of a model product, isoamyl acetate.     

Cultivable bacteria from ancient algal mats from the McMurdo Dry Valleys, Antarctica

The McMurdo Dry Valleys in Antarctica are a favorable location for preservation of dormant microbes due to their persistent cold and dry climate. In this study, we examined cultivable bacteria in a series of algal mat samples ranging from 8 to 26539 years old. Cultivable bacteria were found in all samples except one (12303 years old), but abundance and diversity of cultivable bacteria decreased with increasing sample age. Only members of the Actinobacteria, Bacteroidetes, and Firmicutes were found in the ancient samples, whereas bacteria in the 8-year-old sample also included Cyanobacteria, Proteobacteria, and Deinococcus-Thermus. Isolates of the Gram-positive spore-forming bacterium Sporosarcina were found in 5 of 8 samples. The growth of these isolates at different temperatures was related to the phylogenetic distance among genotypes measured by BOX-PCR. These findings suggest that adaptation to growth at different temperatures had occurred among Sporosarcina genotypes in the Dry Valleys, causing the existence of physiologically distinct but closely related genotypes. Additionally, fully psychrophilic isolates (that grew at 15°C, but not 25°C) were found in ancient samples, but not in the modern sample. The preservation of viable bacteria in the Dry Valleys could potentially represent a legacy of bacteria that impacts on current microbial communities of this environment.