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Biosensors for the detection of benzaldehyde and g-aminobutyric acid (GABA) are reported using aldehyde oxidoreductase PaoABC from Escherichia coli immobilized in a polymer containing bound low potential osmium redox complexes. The electrically connected enzyme already electrooxidizes benzaldehyde at potentials below −0.15 V (vs. Ag|AgCl, 1 M KCl). The pH-dependence of benzaldehyde oxidation can be strongly influenced by the ionic strength. The effect is similar with the soluble osmium redox complex and therefore indicates a clear electrostatic effect on the bioelectrocatalytic efficiency of PaoABC in the osmium containing redox polymer. At lower ionic strength, the pH-optimum is high and can be switched to low pH-values at high ionic strength. This offers biosensing at high and low pH-values. A “reagentless” biosensor has been formed with enzyme wired onto a screen-printed electrode in a flow cell device. The response time to addition of benzaldehyde is 30 s, and the measuring range is between 10–150 µM and the detection limit of 5 µM (signal to noise ratio 3:1) of benzaldehyde. The relative standard deviation in a series (n = 13) for 200 µM benzaldehyde is 1.9%. For the biosensor, a response to succinic semialdehyde was also identified. Based on this response and the ability to work at high pH a biosensor for GABA is proposed by coimmobilizing GABA-aminotransferase (GABA-T) and PaoABC in the osmium containing redox polymer.
Environmental change is likely to have a strong impact on biodiversity, and many species may shift their distribution in response. In this study, we aimed at projecting the availability of suitable habitat for an endangered amphibian species, the Fire-bellied toad Bombina bombina, in Brandenburg (north-eastern Germany). We modelled a potential habitat distribution map based on (1) a database with 10,581 presence records for Bombina from the years 1990 to 2009, (2) current estimates for ecogeographical variables (EGVs) and (3) the future projection of these EGVs according to the statistical regional model, respectively, the soil and water integrated model, applying the maximum entropy approach (Maxent). By comparing current and potential future distributions, we evaluated the projected change in distribution of suitable habitats and identified the environmental variables most associated with habitat suitability that turned out to be climatic variables related to the hydrological cycle. Under the applied scenario, our results indicate increasing habitat suitability in many areas and an extended range of suitable habitats. However, even if the environmental conditions in Brandenburg may change as predicted, it is questionable whether the Fire-bellied toad will truly benefit, as dispersal abilities of amphibian species are limited and strongly influenced by anthropogenic disturbances, that is, intensive agriculture, habitat destruction and fragmentation. Furthermore, agronomic pressure is likely to increase on productive areas with fertile soils and high water retention capacities, indeed those areas suitable for B. bombina. All these changes may affect temporary pond hydrology as well as the reproductive success and breeding phenology of toads.
Increasing attempts are made to understand the factors responsible for both the demographic and genetic depletion in amphibian populations. Landscape genetics aims at a spatially explicit correlation of genetic population parameters to landscape features. Using data from the endangered fire-bellied toad Bombina bombina in Brandenburg (Northeastern Germany), we performed an environmental niche factor analysis (ENFA), relating demographic (abundance) and genetic (diversity at 17 microsatellite loci and partial sequences of the mitochondrial control region in 434 individuals from 16 populations) parameters to ecological and anthropogenic variables such as temperature, precipitation, soil wetness, water runoff, vegetation density, and road/traffic impact. We found significant correlations between road disturbance and observed heterozygosity and between soil wetness and mitochondrial diversity. As the influences of the environmental variables can differ between different indicators for genetic diversity, population size and abundance data, our ENFA-based landscape genetics approach allows us to put various aspects of long- versus short term effective population size and genetic connectivity into an ecological and spatially explicit context, enabling potentially even forecast assessment under future environmental scenarios.