Deleterious impact of a virulent bacteriophage on survival and biocontrol activity of Pseudomonas fluorescens strain CHAO in natural soil.

Many biotic and abiotic factors affect the persistence and activity of beneficial pseudomonads introduced into soil to suppress plant diseases. One such factor may be the presence of virulent bacteriophages that decimate the population of the introduced bacteria, thereby reducing their beneficial effect. We have isolated a lytic bacteriophage (phi)GP100) that specifically infects the biocontrol bacterium Pseudomonas fluorescens CHA0 and some closely related Pseudomonas strains. phiGP100 was found to be a double-stranded-DNA phage with an icosahedral head, a stubby tail, and a genome size of approximately 50 kb. Replication of phiGP100 was negatively affected at temperatures higher than 25 degrees C. phiGP100 had a negative impact on the population size and the biocontrol activity of P. fluorescens strain CHA0-Rif (a rifampicin-resistant variant of CHA0) in natural soil microcosms. In the presence of phiGP100, the population size of strain CHA0-Rif in soil and on cucumber roots was reduced more than 100-fold. As a consequence, the bacterium's capacity to protect cucumber against a root disease caused by the pathogenic oomycete Pythium ultimum was entirely abolished. In contrast, the phage affected neither root colonization and nor the disease suppressive effect of a phiDGP100-resistant variant of strain CHA0-Rif. To our knowledge, this study is the first to illustrate the potential of phages to impair biocontrol performance of beneficial bacteria released into the natural soil environment.

Diversity and structure of AMF communities as affected by tillage in a temperate soil.

Arbuscular mycorrhizal fungi (AMF) were studied in differently tilled soils from a long-term field experiment in Switzerland. Diversity and structure of AMF communities were surveyed either directly on spores isolated from the field soil or on spores isolated from trap cultures, planted with different host plants. Single-spore cultures were established from the AMF spores obtained from trap cultures. Identification of the AMF was made by observation of spore morphology and confirmed by sequencing of ITS rDNA. At least 17 recognised AMF species were identified in samples from field and/or trap cultures, belonging to five genera of AMF--Glomus, Gigaspora, Scutellospora, Acaulospora, and Entrophospora. Tillage had a significant influence on the sporulation of some species and non- Glomus AMF tended to be more abundant in the no-tilled soil. The community structure of AMF in the field soil was significantly affected by tillage treatment. However, no significant differences in AMF diversity were detected among different soil tillage treatments. AMF community composition in trap cultures was affected much more by the species of the trap plant than by the original tillage treatment of the field soil. The use of trap cultures for fungal diversity estimation in comparison with direct observation of field samples is discussed.

Mapping the Membrane Topology of Hepatitis C Virus Nonstructural Protein 4B

BACKGROUND: Nonstructural protein 4B (NS4B) plays an essential role in the formation of the hepatitis C virus (HCV) replication complex. It is an integral membrane protein that has only poorly been characterized to date. In particular, a precise membrane topology is thus far elusive. Here, we explored a novel strategy to map the membrane topology of HCV NS4B. METHODS: Selective permeabilization of the plasma membrane, maleimide-polyethyleneglycol (mPEG) labeling of natural or engineered cysteine residues and immunoblot analyses were combined to map the membrane topology of NS4B. Cysteine substitutions were introduced at carefully selected positions within NS4B and their impact on HCV RNA replication and infectious virus production analyzed in cell culture. RESULTS: We established a panel of viable HCV mutants with cysteine substitutions at strategic positions within NS4B. These mutants are infectious and replicate to high levels in cell culture. In parallel, we adapted and optimized the selective permeabilization and mPEG labeling techniques to Huh-7 human hepatocellular carcinoma cells which can support HCV infection and replication. CONCLUSIONS: The newly established experimental tools and techniques should allow us to refine the membrane topology of HCV NS4B in a physiological context. The expected results should enhance our understanding of the functional architecture of the HCV replication complex and may provide new opportunities for antiviral intervention in the future.

Contribution of the Global Regulator Gene gacA to Persistence and Dissemination of Pseudomonas fluorescens Biocontrol Strain CHA0 Introduced into Soil Microcosms.

Structural and regulatory genes involved in the synthesis of antimicrobial metabolites are essential for the biocontrol activity of fluorescent pseudomonads and, in principle, amenable to genetic engineering for strain improvement. An eventual large-scale release of such bacteria raises the question of whether such genes also contribute to the persistence and dissemination of the bacteria in soil ecosystems. Pseudomonas fluorescens wild-type strain CHA0 protects plants against a variety of fungal diseases and produces several antimicrobial metabolites. The regulatory gene gacA globally controls antibiotic production and is crucial for disease suppression in CHA0. This gene also regulates the production of extracellular protease and phospholipase. The contribution of gacA to survival and vertical translocation of CHA0 in soil microcosms of increasing complexity was studied in coinoculation experiments with the wild type and a gacA mutant which lacks antibiotics and some exoenzymes. Both strains were marked with spontaneous resistance to rifampin. In a closed system with sterile soil, strain CHA0 and the gacA mutant multiplied for several weeks, whereas these strains declined exponentially in nonsterile soil of different Swiss origins. The gacA mutant was less persistent in nonrhizosphere raw soil than was the wild type, but no competitive disadvantage when colonizing the rhizosphere and roots of wheat was found in the particular soil type and during the period studied. Vertical translocation was assessed after strains had been applied to undisturbed, long (60-cm) or short (20-cm) soil columns, both planted with wheat. A smaller number of cells of the gacA mutant than of the wild type were detected in the percolated water and in different depths of the soil column. Single-strain inoculation gave similar results in all microcosms tested. We conclude that mutation in a single regulatory gene involved in antibiotic and exoenzyme synthesis can affect the survival of P. fluorescens more profoundly in unplanted soil than in the rhizosphere.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.