- Biowissenschaften (2) (remove)
- The Janthinobacterium sp. HH01 genome encodes a homologue of the V. cholerae CqsA and L. pneumophila LqsA autoinducer synthases (2013)
- Janthinobacteria commonly form biofilms on eukaryotic hosts and are known to synthesize antibacterial and antifungal compounds. Janthinobacterium sp. HH01 was recently isolated from an aquatic environment and its genome sequence was established. The genome consists of a single chromosome and reveals a size of 7.10 Mb, being the largest janthinobacterial genome so far known. Approximately 80% of the 5,980 coding sequences (CDSs) present in the HH01 genome could be assigned putative functions. The genome encodes a wealth of secretory functions and several large clusters for polyketide biosynthesis. HH01 also encodes a remarkable number of proteins involved in resistance to drugs or heavy metals. Interestingly, the genome of HH01 apparently lacks the N-acylhomoserine lactone (AHL)-dependent signaling system and the AI-2-dependent quorum sensing regulatory circuit. Instead it encodes a homologue of the Legionella- and Vibrio-like autoinducer (lqsA/cqsA) synthase gene which we designated jqsA. The jqsA gene is linked to a cognate sensor kinase (jqsS) which is flanked by the response regulator jqsR. Here we show that a jqsA deletion has strong impact on the violacein biosynthesis in Janthinobacterium sp. HH01 and that a jqsA deletion mutant can be functionally complemented with the V. cholerae cqsA and the L. pneumophila lqsA genes.
- The estimation of aboveground biomass and nutrient pools of understorey plants in closed Norway spruce forests and on clearcuts (2010)
- The estimation model PhytoCalc allows a non-destructive quantification of dry weight and nutrient pools of understorey plants in forests by using the relationship between species biomass, cover and mean shoot length. The model has been validated with independent samples in several German forest types and can be a useful tool in forest monitoring. However, in open areas within forests (e.g. clearcuts), the current model version underestimates biomass and produces unreliable nutrient pool estimations. Thus, tissue density, as approximated by leaf dry matter content (LDMC), is systematically higher under high light compared to low light conditions. We demonstrate that the ratio of LDMC under clearcut conditions to LDMC under forest conditions can be used to adjust the PhytoCalc model to clearcut conditions. We investigated the LDMC ratio of five exemplary species commonly occurring on clearcuts. Integrating the square of the ratio as a correction factor improved estimates of biomass to more than 70% fit between observations and predictions. Results also suggest this ratio can be used to correct nutrient concentrations modelled in PhytoCalc, which tend to be overestimated in clearcuts. As morphological groups of plant species exhibit significantly different ratios, we advise using group-specific correction factors for clearcut adjustments in the future.