Microbes on building materials--evaluation of DNA extraction protocols as common basis for molecular analysis.

The study of microbial life in building materials is an emerging topic concerning biodeterioration of materials as well as health risks in houses and at working places. Biodegradation and potential health implications associated with microbial growth in our residues claim for more precise methods for quantification and identification. To date, cultivation experiments are commonly used to gain insight into the microbial diversity. Nowadays, molecular techniques for the identification of microorganisms provide efficient methods that can be applied in this field. The efficiency of DNA extraction is decisive in order to perform a reliable and reproducible quantification of the microorganisms by qPCR or to characterize the structure of the microbial community. In this study we tested thirteen DNA extraction methods and evaluated their efficiency for identifying (1) the quantity of DNA, (2) the quality and purity of DNA and (3) the ability of the DNA to be amplified in a PCR reaction using three universal primer sets for the ITS region of fungi as well as one primer pair targeting the 16S rRNA of bacteria with three typical building materials - common plaster, red brick and gypsum cardboard. DNA concentration measurements showed strong variations among the tested methods and materials. Measurement of the DNA yield showed up to three orders of magnitude variation from the same samples, whereas A260/A280 ratios often prognosticated biases in the PCR amplifications. Visualization of the crude DNA extracts and the comparison of DGGE fingerprints showed additional drawbacks of some methods. The FastDNA Spin kit for soil showed to be the best DNA extraction method and could provide positive results for all tests with the three building materials. Therefore, we suggest this method as a gold standard for quantification of indoor fungi and bacteria in building materials.

Who is who in litter decomposition? Metaproteomics reveals major microbial players and their biogeochemical functions.

Leaf-litter decomposition is a central process in carbon cycling; however, our knowledge about the microbial regulation of this process is still scarce. Metaproteomics allows us to link the abundance and activity of enzymes during nutrient cycling to their phylogenetic origin based on proteins, the 'active building blocks' in the system. Moreover, we employed metaproteomics to investigate the influence of environmental factors and nutrients on the decomposer structure and function during beech litter decomposition. Litter was collected at forest sites in Austria with different litter nutrient content. Proteins were analyzed by 1-D-SDS-PAGE followed by liquid-chromatography and tandem mass-spectrometry. Mass spectra were assigned to phylogenetic and functional groups by a newly developed bioinformatics workflow, assignments being validated by complementary approaches. We provide evidence that the litter nutrient content and the stoichiometry of C:N:P affect the decomposer community structure and activity. Fungi were found to be the main producers of extracellular hydrolytic enzymes, with no bacterial hydrolases being detected by our metaproteomics approach. Detailed investigation of microbial succession suggests that it is influenced by litter nutrient content. Microbial activity was stimulated at higher litter nutrient contents via a higher abundance and activity of extracellular enzymes.

The effect of resource quantity and resource stoichiometry on microbial carbon-use-efficiency.

The carbon-use-efficiency (CUE) of microorganisms is an important parameter in determining ecosystem-level carbon (C) cycling; however, little is known about how variance in resources affects microbial CUE. To elucidate how resource quantity and resource stoichiometry affect microbial CUE, we cultured four microorganisms - two fungi (Aspergillus nidulans and Trichoderma harzianum) and two bacteria (Pectobacterium carotovorum and Verrucomicrobium spinosum) - under 12 unique C, nitrogen (N) and phosphorus (P) ratios. Whereas the CUE of A. nidulans was strongly affected by C, bacterial CUE was more strongly affected by mineral nutrients (N and P). Specifically, CUE in P. carotovorum was positively correlated with P, while CUE of V. spinosum primarily depended on N. This resulted in a positive relationship between fungal CUE and resource C : nutrient stoichiometry and a negative relationship between bacterial CUE and resource C : nutrient stoichiometry. The difference in the direction of the relationship between CUE and C : nutrient for fungi vs. bacteria was consistent with differences in biomass stoichiometry and suggested that fungi have a higher C demand than bacteria. These results suggest that the links between biomass stoichiometry, resource demand and CUE may provide a mechanism for commonly observed temporal and spatial patterns in microbial community structure and function in natural habitats.

Engineered bakers yeast as a sensitive bioassay indicator organism for the trichothecene toxin deoxynivalenol.

The aim of this study was to increase the sensitivity of Saccharomyces cerevisiae towards trichothecene toxins, in particular to deoxynivalenol (DON), in order to improve the utility of this yeast as a bioassay indicator organism. We report the construction of a strain with inactivated genes (PDR5, PDR10, PDR15) encoding ABC transporter proteins with specificity for the trichothecene deoxynivalenol, with inactivated AYT1 (encoding a trichothecene-3-O-acetyltransferase), and inactivated UBI4 and UBP6 genes. Inactivation of the stress inducible polyubiquitin gene UBI4 or the ubiquitin protease UBP6 increased DON sensitivity, the inactivation of both genes had a synergistic effect. The resulting pdr5 pdr10 pdr15 ayt1 ubp6 ubi4 mutant strain showed 50% growth inhibition at a DON concentration of 5 mg/l under optimal conditions. The development of a simple two step assay for microbial DON degradation in 96 well microtiter format and its testing with the DON detoxifying bacterium BBSH 797 is reported.