Propylene glycol-specific dehydrogenases as functional biomarkers for monitoring biodegradation in sites contaminated by de-icing chemicals

The area under study at Gardermoen airport (Oslo, Norway) is a glacial contact formation with sand and gravels dominating near the ground surface. Due to the northern climate, every winter large amounts of de-icing chemicals, i.e. propylene glycol (PG) and potassium formate, are commonly used in the airport for the removal of snow and ice from airplanes and runways, respectively. Even though these contaminants are easily degradable by biotic or abiotic factors, they may still threaten groundwater, due to the system overloading. The present study, performed within the FPVII European research project: “SoilCAM - Soil Contamination: Advanced integrated characterisation and time-lapse Monitoring”, deals with the physic-chemical and microbiological characterization of the site and the development of suitable methods for monitoring PG biodegradation on site under reclamation. For this purpose, functional biomarkers were selected to evaluate their potential use in Real Time quantitative PCR (q-PCR) experiments directly on soil DNA. The soils are highly leached, with low biological and biochemical activities. Therefore, pollutant transfer to the groundwater occurs quickly and is virtually unhindered. Bacterial strains isolated from the soil were able to degrade PG in aerobic conditions at 4, 15 and 30 °C. The PG-degrading population was mainly composed by different species of Pseudomonas, as shown by denaturing gradient gel electrophoresis (DGGE) analysis on soil DNA. Gene probes for PG-specific alcohol dehydrogenase (ADH-IIG) detected the presence of such genes in the isolates. The deduced amino acid sequence of representative strains presented over 92% identities with PG-specific dehydrogenase-related proteins. ADH-IIG detected in soil DNA indicated that PG-degrading strains were present along the soil profile from 0 to 100 cm. The application of q-PCR analysis on DNA from soil mesocosm experiments will confirm the suitability of ADH-IIG as biomarker for monitoring PG biodegradation in soil systems

Different pioneer plant species select specific rhizosphere bacterial communities in a high mountain environment

The rhizobacterial communities of 29 pioneer plants belonging to 12 species were investigated in an alpine ecosystem to assess if plants from different species could select for specific rhizobacterial communities. Rhizospheres and unvegetated soils were collected from a floristic pioneer stage plot at 2,400 m a.s.l. in the forefield of Weisskugel Glacier (Matsch Valley, South Tyrol, Italy), after 160 years of glacier retreat. To allow for a culture-independent perspective, total environmental DNA was extracted from both rhizosphere and bare soil samples and analyzed by Automated Ribosomal Intergenic Spacer Analysis (ARISA) and Denaturing Gradient Gel Electrophoresis (DGGE). ARISA fingerprinting showed that rhizobacterial genetic structure was extremely different from bare soil bacterial communities while rhizobacterial communities clustered strictly together according to the plant species. Sequencing of DGGE bands showed that rhizobacterial communities were mainly composed of Acidobacteria and Proteobacteria whereas bare soil was colonized by Acidobacteria and Clostridia. UniFrac significance calculated on DGGE results confirmed the rhizosphere effect exerted by the 12 species and showed different bacterial communities (P < 0.05) associated with all the plant species. These results pointed out that specific rhizobacterial communities were selected by pioneer plants of different species in a high mountain ecosystem characterized by oligotrophic and harsh environmental conditions, during an early primary succession

Safe-site effects on rhizosphere bacterial communities in a high-altitude alpine environment

The rhizosphere effect on bacterial communities associated with three floristic communities (RW, FI, and M sites) which differed for the developmental stages was studied in a high-altitude alpine ecosystem. RW site was an early developmental stage, FI was an intermediate stage, M was a later more matured stage. The N and C contents in the soils confirmed a different developmental stage with a kind of gradient from the unvegetated bare soil (BS) site through RW, FI up to M site. The floristic communities were composed of 21 pioneer plants belonging to 14 species. Automated ribosomal intergenic spacer analysis showed different bacterial genetic structures per each floristic consortium which differed also from the BS site. When plants of the same species occurred within the same site, almost all their bacterial communities clustered together exhibiting a plant species effect. Unifrac significance value (P < 0.05) on 16S rRNA gene diversity revealed significant differences (P < 0.05) between BS site and the vegetated sites with a weak similarity to the RW site. The intermediate plant colonization stage FI did not differ significantly from the RW and the M vegetated sites. These results pointed out the effect of different floristic communities rhizospheres on their soil bacterial communities

Propylene glycol degrading bacteria and related functional biomarkers in Gardermoen airport contaminated soil

Gardermoen airport (Oslo) was built on the largest rain fed unconfined aquifer in Norway. The area is a glacial contact formation with sand and gravels dominating near the ground surface and the soil is highly leached, with low biological and biochemical activities. Every winter large amount of propylene glycol (PG) is used as de-icing compound for the removal of snow and ice on airplanes. Although this contaminant is easily degraded by biotic or abiotic factors along the soil profile, it may still threaten groundwater when the system is overloaded. The aim of the present study was the characterization of the indigenous bacterial communities affected by the PG spreading and the development of suitable genetic biomarkers for monitoring the biodegradation process. The selected functional probes were qgdA gene for PG alcohol dehydrogenase (ADH-IIG) and par gene for phenylacetaldehyde reductase (PAR), which react specifically with secondary alcohols. Primers for qgdA and par were designed and tested on bacterial isolates enriched from soils at different depths and which were able to use PG as sole carbon and energy source. Molecular identification through 16S rRNA gene sequence analyses revealed that microorganisms mostly belonged to different species of the genera Pseudomonas, and Rhodococcus, although representatives of the genera Streptomyces, Nocardia, Serratia and Ancylobacter were also found. The functional genes retrieved in Gammaproteobacteria and in Actinobacteria were highly homologous respectively to qgdA gene for ADH-IIG of P. putida strain HK5 (Toyama et al., 2005) and to par genes for PAR of Rhodococcus sp. strain ST-10 (Wang et al., 1999). Transcriptional analysis performed on representative strains highlighted the expression of qgdA and par genes when strains were grown in the presence of PG, thus confirming that both were specifically functional during in PG degradation. Our data allow to state that Gardermoen soil is characterized by a rich and well-established reservoir of bacteria potentially able to degrade PG in situ. This bacterial community is characterized by specific PG-degradative pathways based on the qdgA and par genes. These genes will be validated as biomarkers to quantitatively track the active PG-degrading bacterial populations in soil

A Three-Scale Analysis of Bacterial Communities Involved in Rocks Colonization and Soil Formation in High Mountain Environments

Alpha and beta diversities of the bacterial communities growing on rock surfaces, proto-soils, riparian sediments, lichen thalli, and water springs biofilms in a glacier foreland were studied. We used three molecular based techniques to allow a deeper investigation at different taxonomic resolutions: denaturing gradient gel electrophoresis, length heterogeneity-PCR, and automated ribosomal intergenic spacer analysis. Bacterial communities were mainly composed of Acidobacteria, Proteobacteria, and Cyanobacteria with distinct variations among sites. Proteobacteria were more represented in sediments, biofilms, and lichens; Acidobacteria were mostly found in proto-soils; and Cyanobacteria on rocks. Firmicutes and Bacteroidetes were mainly found in biofilms. UniFrac P values confirmed a significant difference among different matrices. Significant differences (P < 0.001) in beta diversity were observed among the different matrices at the genus-species level, except for lichens and rocks which shared a more similar community structure, while at deep taxonomic resolution two distinct bacterial communities between lichens and rocks were found

Statistical parameter identification of analog integrated circuit reverse models

We solve the manufacturing problem of identifying the model statistical parameters ensuring a satisfactory quality of analog circuits produced in a photolithographic process. We formalize it in a statistical framework as the problem of inverting the mapping from the population of the circuit production variables to the performances\u2019 population. Both variables and performances are random. From a sample of the joint population we want to identify the statistical features of the former producing a performance distribution that satisfies the design constraints with a good preassigned probability. The key idea of the solution method we propose consists of describing the above mapping in terms of a mixture of granular functions, where each is responsible for a fuzzy set within the input-output space, hence for a cluster therein. The way of synthesizing the whole space as a mixture of these clusters is learnt directly from the examples. As a result we have an analytical form both of the mapping approximating complex Spice models in terms of polynomials in the production variables, and of the distribution law of the induced performances that allows a relatively quick and easy management of the production variables\u2019 statistical parameters as a function of the probability with which we plan to satisfy the design constraint. We apply the method to case studies and real production data where our method outperforms current methods\u2019 running times and accuracies

Statistical parameter identification of analog integrated circuit reverse models

We solve the manufacturing problem of identifying the model statistical parameters ensuring a satisfactory quality of analog circuits produced in a photolithographic process. We formalize it in a statistical framework as the problem of inverting the mapping from the population of the circuit model parameters to the population of the performances. Both parameters and performances are random. From a sample of the latter population we want to identify the statistical features of the former that produce a performance distribution complying with production samples. The key artifact of the solution method we propose consists of describing the above mapping in terms of a mixture of granular functions, where each is responsible for a fuzzy set within the input-output space, hence for a cluster therein. The way of synthesizing the whole space as a mixture of these clusters is learnt directly from the examples. As a result, we have an analytical form of the mapping that approximates complex Spice models in terms of polynomials in the model parameters, and an implicit expression of the distribution law of the induced performances that allows a relatively quick and easy management of the model distribution statistical parameters. This flows into a semiautomatic procedure managing an adaptive composition of different granular modules to cope with the circuit peculiarities. We check the method both on real world manufacturing problems and on ad hoc benchmarks

Unraveling the role of ecosystem development in the shaping of soil bacterial communities

Microbial primary succession and plant biocoenosis establishment are key events in land reclamation, nevertheless the underlying mechanisms driving the succession are still poorly understood. Aim of the work was hence to determine the role of environmental factors and ecosystem development in shaping soil microbiota. The forefronts of receding glaciers are natural laboratories where to study microbial diversity in relation to geochemical factors and ecosystem development stage. Chronosequences can be identified on glacier moraines, where the increasing distance from the glacier edge corresponds to the increase of time of permanence out of ice, soil structuring and ecosystem development. We studied a first site on the moraines of the Lobuche glacier (Mount Everest area, Nepal), identifying several niches characterized by a different level of biotic colonization, from a bare mineral substrate to complex biological soil crust. Bacterial phylogenetic and functional diversity was studied by DNA-fingerprinting methods and a high variability was observed, demonstrating that the presence of spatially isolated microhabitats in soil matrices can strongly influence data interpretation. We then focused on a second site on the moraines of the Midtre Lov\ue9enbren glacier (Svalbard Islands, Norway) where a chronosequence was previously characterised (Hodkinson et al. 2003). The sequence was composed by 7 sites subjected to a primary succession process, exposed to the terrestrial habitat since 5 to 2000 years, thus not isolated by distance but by the age of ecosystem evolution, distinguished by increasing levels of nutrient availability, soil fertility and plant colonization. Together with environmental factors, plant cover and diversity have been demonstrated to strongly influence the structure of soil microbiota (Berg & Smalla 2009). To have the possibility to consider separately the role of plants and the role of soil development in the primary bacterial succession, we identified a vascular plant, namely Saxifraga oppositifolia, present along the whole Midtre-Love\ue9nbreen chronosequence and we analyzed the bacterial communities associated to the rhizosphere and the corresponding bulk soil. We demonstrated that soil development was the discriminating factor in the earlier successional stage, while the rhizosphere effect was significant only after 20 years out of ice covering. Rhizosphere communities showed higher similarity between 20 and 100 years of soil development, differentiating in the subsequenct successional stages. The results showed the presence of biogeographic patterns in rhizosphere microbiota, differently influenced by the interaction with the plant and by environmental factors related to different stages of ecosystem evolution. References: Hodkinsos ID, Coulson SJ, Webb NR (2003) Community assembly along proglacial chronosequences in the high Arctic: vegetation and soil development in north-west Svalbard. J Ecol 91:651\u2013663 Berg G & Smalla K (2009) Plant species and soil type cooperativelyshape the structure and function of microbial communities in the rhizosphere. FEMS Microbiol Ecol 68:1\u20131