Downregulation of the motA gene delays the escape of the obligate predator Bdellovibrio bacteriovorus 109J from bdelloplasts of bacterial prey cells

Bdellovibrio bacteriovorus is a Gram-negative bacterium that preys on other Gram-negative bacteria. The lifecycle of B. bacteriovorus alternates between an extracellular flagellated and highly motile non-replicative attack-phase cell and a periplasmic non-flagellated growth-phase cell. The prey bacterium containing periplasmic bdellovibrios becomes spherical but osmotically stable, forming a structure known as the bdelloplast. After completing the growth phase, newly formed bdellovibrios regain their flagellum and escape the bdelloplast into the environment, where they encounter more prey bacteria. The obligate predatory nature of B. bacteriovorus imposes a major difficulty to introducing mutations in genes directly involved in predation, since these mutants could be non-viable. This work reports the cloning of the B. bacteriovorus 109J motAB operon, encoding proteins from the flagellar motor complex, and a genetic approach based on the expression of a motA antisense RNA fragment to downregulate motility. Periplasmic bdellovibrios carrying the plasmid expressing antisense RNA displayed a marked delay in escaping from bdelloplasts, while the released attack-phase cells showed altered motility. These observations suggest that a functionally intact flagellar motor is required for the predatory lifecycle of B. bacteriovorus. Also, the use of antisense RNA expression may be a useful genetic tool to study the Bdellovibrio developmental cycle.

Random Regret Minimization: Exploration of a New Choice Model for Environmental and Resource Economics

This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the dominant choice-modelling paradigm based on Random Utility Maximization-theory (RUM-theory). We highlight how RRM-based models provide closed form, logit-type formulations for choice probabilities that allow for capturing semi-compensatory behaviour and choice set-composition effects while being equally parsimonious as their utilitarian counterparts. Using data from a Stated Choice-experiment aimed at identifying valuations of characteristics of nature parks, we compare RRM-based models and RUM-based models in terms of parameter estimates, goodness of fit, elasticities and consequential policy implications.

Exploring Scale Effects of Best/Worst Rank Ordered Choice Data to Estimate Benefits of Tourism in Alpine Grazing Commons

In many environmental valuation applications standard sample sizes for choice modelling surveys are impractical to achieve. One can improve data quality using more in-depth surveys administered to fewer respondents. We report on a study using high quality rank-ordered data elicited with the best-worst approach. The resulting "exploded logit" choice model, estimated on 64 responses per person, was used to study the willingness to pay for external benefits by visitors for policies which maintain the cultural heritage of alpine grazing commons. We find evidence supporting this approach and reasonable estimates of mean WTP, which appear theoretically valid and policy informative. © The Author (2011).