Two novel antibiotic resistance genes, tet(44) and ant(6)-Ib, are located within a transferable pathogenicity island in Campylobacter fetus subsp. fetus

New tetracycline and streptomycin resistance genes, tet(44) and ant(6)-Ib, were identified in Campylobacter fetus subsp. fetus within a transferable pathogenicity island that is typically unique to Campylobacter fetus subsp. venerealis. The 640-amino-acid tetracycline resistance determinant, Tet 44, belongs to a class of proteins that confers resistance to tetracycline and minocycline by ribosomal protection. The 286-amino-acid streptomycin resistance determinant, ANT(6)-Ib, belongs to a family of aminoglycoside nucleotidyltransferases. The resistance phenotypes were demonstrated by gene inactivation and expression.

Learning Paradigms Exemplified by Virtual Experiments with Honey Bees

Learning is based on rules that can be elucidated by behavioural experiments. This article focuses on virtual experiments, in which non-associative learning (habituation, sensitization) and principles of associative learning (contiguity, inhibitory learning, generalization, overshadowing, positive and negative patterning) can be examined using 'virtual' honey bees in PER (Proboscis Reaction Extension) conditioning experiments. Users can develop experimental designs, simulate and document the experiments and find explanations and suggestions for the analysis of the learning experiments. The virtual experiments are based on video sequences and data from actual learning experiments. The bees' responses are determined by probability-based learning profiles.

Sequenzierung mit Ant-Colony-Systemen am Beispiel Querverteil-Wagen

Dieser Beitrag zeigt die Anwendung des Ant-Colony-System (ACS) Algorithmus auf die Sequenzierung von Querverteil-Wagen in einem Lager. Wir erweitern den Basisalgorithmus der Ant-Colony-Optimierung (ACO) für die Minimierung der Bearbeitungszeit einer Menge von Fahraufträgen für die Querverteil-Wagen. Im Vergleich zu dem Greedy-Algorithmus ist der ACO-Algorithmus wettbewerbsfähig und schnell. In vielen Lagerverwaltungssystemen werden die Fahraufträge nach dem FIFO-Prinzip (First-in-First-out) ausgeführt. In diesem Beitrag wird der ACO-Algorithmus genutzt, um eine optimale Sequenz der Fahraufträge zu bilden.

Clinical signs of deformed wing virus infection are predictive markers for honey bee colony losses.

The ectoparasitic mite Varroa destructor acting as a virus vector constitutes a central mechanism for losses of managed honey bee, Apis mellifera, colonies. This creates demand for an easy, accurate and cheap diagnostic tool to estimate the impact of viruliferous mites in the field. Here we evaluated whether the clinical signs of the ubiquitous and mite-transmitted deformed wing virus (DWV) can be predictive markers of winter losses. In fall and winter 2007/2008, A.m. carnica workers with apparent wing deformities were counted daily in traps installed on 29 queenright colonies. The data show that colonies which later died had a significantly higher proportion of workers with wing deformities than did those which survived. There was a significant positive correlation between V. destructor infestation levels and the number of workers displaying DWV clinical signs, further supporting the mite's impact on virus infections at the colony level. A logistic regression model suggests that colony size, the number of workers with wing deformities and V. destructor infestation levels constitute predictive markers for winter colony losses in this order of importance and ease of evaluation.

Sugar concentration influences decision making in <i>Apis mellifera</i> L. workers during early-stage honey storage behaviour

Decision making in honeybees is based on in- formation which is acquired and processed in order to make choices between two or more al- ternatives. These choices lead to the expression of optimal behaviour strategies such as floral constancy. Optimal foraging strategies such as floral constancy improve a colony’s chances of survival, however to our knowledge, there has been no research on decision making based on optimal storage strategies. Here we show, using diagnostic radioentomology, that decision mak- ing in storer bees is influenced by nectar sugar concentrations and that, within 48 hours of col- lection, honeybees workers store carbohydrates in groups of cells with similar sugar concentra- tions in a nonrandom way. This behaviour, as evidenced by patchy spatial cell distributions, would help to hasten the ripening process by reducing the distance between cells of similar sugar concentrations. Thus, colonies which ex- hibit optimal storage strategies such as these would have an evolutionary advantage and im- prove colony survival expectations over less efficient colonies and it should be plausible to select colonies that exhibit these preferred traits.

Wild pollinators enhance fruit set of crops regardless of honey bee abundance.

The diversity and abundance of wild insect pollinators have declined in many agricultural landscapes. Whether such declines reduce crop yields, or are mitigated by managed pollinators such as honey bees, is unclear. We found universally positive associations of fruit set with flower visitation by wild insects in 41 crop systems worldwide. In contrast, fruit set increased significantly with flower visitation by honey bees in only 14% of the systems surveyed. Overall, wild insects pollinated crops more effectively; an increase in wild insect visitation enhanced fruit set by twice as much as an equivalent increase in honey bee visitation. Visitation by wild insects and honey bees promoted fruit set independently, so pollination by managed honey bees supplemented, rather than substituted for, pollination by wild insects. Our results suggest that new practices for integrated management of both honey bees and diverse wild insect assemblages will enhance global crop yields.