Our experiments addressed systemic metabolic effects in above-ground plant tissue as part of the plant's response to the arbuscular mycorrhizal (AM) interaction. Due to the physiology of this interaction, we expected effects in the areas of plant mineral nutrition, carbon allocation and stress-related metabolism, but also a notable dependence of respective metabolic changes on environmental conditions and on plant developmental programs. To assess these issues, we analyzed metabolite profiles from mycorrhizal and non-mycorrhizal Lotus japonicus grown under greenhouse conditions at three different time points in the growing season in three different above-ground organs (flowers, sink leaves and source leaves). Statistical analysis of our data revealed a number of significant changes in individual experiments with little overlap between these experiments, indicating the expected impact of external conditions on the plant's response to AM colonization. Partial least square-discriminant analysis (PLS-DA) nevertheless revealed considerable similarities between the datasets, and loading analysis of the component separating mycorrhizal and non-mycorrhizal plants allowed the defining of a core set of metabolites responsible for this separation. This core set was observed in experiments with and without mycorrhiza-induced growth effects. It corroborated trends already indicated by the significant changes from individual experiments and suggested a negative systemic impact of AM colonization on central catabolic metabolism as well as on amino acid metabolism. In addition, metabolic signals for an increase in stress experienced by plant tissue were recorded in flowers and source leaves.

Biogas is an important renewable energy carrier. It is a product of stepwise anaerobic degradation of organic materials by highly diverse microbial communities forming complex interlinking metabolic networks. Knowledge about the microbial background of long-term stable process performance in full-scale reactors is crucial for rationally improving the efficiency and reliability of biogas plants. To generate such knowledge, in the present study three parallel mesophilic full-scale reactors fed exclusively with energy crops were sampled weekly over one year. Physicochemical process parameters were determined and the microbial communities were analysed by terminal restriction fragment length polymorphism (T-RFLP) fingerprinting and 454-amplicon sequencing. For investigating the methanogenic community, a high-resolution T-RFLP approach based on the mcrA gene was developed by selecting restriction enzymes with improved taxonomic resolution compared to previous studies. Interestingly, no Methanosarcina-related generalists, but rather specialized hydrogenotrophic and acetoclastic methanogenic taxa were detected. In general, the microbial communities in the non-connected reactors were remarkably stable and highly similar indicating that identical environmental and process parameters resulted in identical microbial assemblages and dynamics. Practical implications such as flexible operation schemes comprising controlled variations of process parameters for an efficient microbial resource management under fluctuating process conditions are discussed.

Two-phasic anaerobic digestion processes (hydrolysis/acidogenesis separated from acetogenesis/methanogenesis) can be used for biogas production on demand or a combined chemicals/bioenergy production. For an effective process control, detailed knowledge about the microbial catalysts and their correlation to process conditions is crucial. In this study, maize silage was digested in a two-phase process and interrelationships between process parameters and microbial communities were revealed. In the first-phase reactor, alternating metabolic periods were observed which emerged independently from the feeding frequency. During the L-period, up to 11.8 g L(-1) lactic acid was produced which significantly correlated to lactic acid bacteria of the genus Lactobacillus as the most abundant community members. During the alternating G-period, the production of volatile fatty acids (up to 5.3, 4.0 and 3.1 g L(-1) for propionic, n-butyric and n-caproic acid, respectively) dominated accompanied by a high gas production containing up to 28 % hydrogen. The relative abundance of various Clostridiales increased during this metabolic period. In the second-phase reactor, the metabolic fluctuations of the first phase were smoothed out resulting in a stable biogas production as well as stable bacterial and methanogenic communities. However, the biogas composition followed the metabolic dynamics of the first phase: the hydrogen content increased during the L-period whereas highest CH4/CO2 ratios (up to 2.8) were reached during the G-period. Aceticlastic Methanosaeta as well as hydrogenotrophic Methanoculleus and Methanobacteriaceae were identified as dominant methanogens. Consequently, a directed control of the first-phase stabilizing desired metabolic states can lead to an enhanced productivity regarding chemicals and bioenergy.

In times of global change and intensified resource exploitation, advanced knowledge of ecophysiological processes in natural and engineered systems driven by complex microbial communities is crucial for both safeguarding environmental processes and optimising rational control of biotechnological processes. To gain such knowledge, high-throughput molecular techniques are routinely employed to investigate microbial community composition and dynamics within a wide range of natural or engineered environments. However, for molecular dataset analyses no consensus about a generally applicable alpha diversity concept and no appropriate benchmarking of corresponding statistical indices exist yet. To overcome this, we listed criteria for the appropriateness of an index for such analyses and systematically scrutinised commonly employed ecological indices describing diversity, evenness and richness based on artificial and real molecular datasets. We identified appropriate indices warranting interstudy comparability and intuitive interpretability. The unified diversity concept based on 'effective numbers of types' provides the mathematical framework for describing community composition. Additionally, the Bray-Curtis dissimilarity as a beta-diversity index was found to reflect compositional changes. The employed statistical procedure is presented comprising commented R-scripts and example datasets for user-friendly trial application.

SUMMARYThree methods have been used to investigate the effects of a number of commercial herbicides on the growth of certain soil fungi: measurements of hyphal extension across agar plates; measurements of hyphal extension along sterilized plant material; and manometric techniques. Three points, in particular, emerged from these studies. First, that there was no stimulation of fungal growth. Herbicide interference in growth included suppression of spore germination, inhibition of the rate of linear extension of the mycelia, and abnormalities in growth habit and in patterns of spore production. Secondly, that some herbicides (e.g. linuron and paraquat) were more fungitoxic than others (e.g. MCPA and simazine) to a range of organisms. Thirdly, that there were differences between fungi in their sensitivity to individual herbicides. All three methods have shown consistent differences between fungi in their ability to tolerate paraquat. Trichoderma viride, in particular, has been found to be sensitive to paraquat. The inhibitory effects were observed at concentrations well within the range likely to be experienced in the field.