General Surveillance of the soil ecosystem: An approach to monitoring unexpected adverse effects of GMO's

The commercial cultivation of genetically modified (GM) crops in the European Union (EU) necessitates, according to EU legislation, the setting up of a General Surveillance (GS) system that should be able to detect unanticipated effects of GM crops on the environment. Although the applicant is responsible for setting up GS as well as for reporting the results, EU Member States may implement additional supporting surveillance programmes. Devising a GS system to detect unanticipated effects is not straightforward and requires clearly defined protection goals, suitable indicators that are linked to measurable parameters and an objective system for assessing the data. This paper describes a number of recommendations for the development of a General Surveillance system of the soil ecosystem specifically focussed on the situation in the Netherlands. The overarching protection goal of General Surveillance is ‘soil quality’, which is translated into more practical terms of ecosystem services that are relevant for soil quality, and that can be used to select measurable parameters and thus make a link with actual measurements.Ultimately, if and when effects on ecosystem services are detected, decision makers will have to decide whether these effects are acceptable or not. As a support for these decision-making processes, this paper discusses the modalities for the development of a stakeholder participation model. The model involves three groups of persons: the land users, the soil scientists and the decision makers.For reasons of cost effectiveness, a GS system of the soil ecosystem will have to make use of existing networks. The Dutch Soil Quality Network (DSQN) offers an existing infrastructure for soil sampling for GS. Finally, the GS system may be extended to contain data from the Dutch Ecological Monitoring Network, earth observation systems as well as other data resources such as farmers questionnaires or reports form organisations involved in nature conservation. Ideally these data are compiled by a Central Reporting Office (CRO) and maintained in a Geographic Information System (GIS) based database.     

Repeated Introduction of Genetically Modified Pseudomonas putida WCS358r without Intensified Effects on the Indigenous Microflora of Field-Grown Wheat

To investigate the impact of genetically modified, antibiotic-producing rhizobacteria on the indigenous microbial community, Pseudomonas putida WCS358r and two transgenic derivatives were introduced as a seed coating into the rhizosphere of wheat in two consecutive years (1999 and 2000) in the same field plots. The two genetically modified microorganisms (GMMs), WCS358r::phz and WCS358r::phl, constitutively produced phenazine-1-carboxylic acid (PCA) and 2,4-diacetylphloroglucinol (DAPG), respectively. The level of introduced bacteria in all treatments decreased from 10⁷ CFU per g of roots soon after sowing to less than 10² CFU per g after harvest 132 days after sowing. The phz and phl genes remained stable in the chromosome of WCS358r. The amount of PCA produced in the wheat rhizosphere by WCS358r::phz was about 40 ng/g of roots after the first application in 1999. The DAPG-producing GMMs caused a transient shift in the indigenous bacterial and fungal microflora in 1999, as determined by amplified ribosomal DNA restriction analysis. However, after the second application of the GMMs in 2000, no shifts in the bacterial or fungal microflora were detected. To evaluate the importance of the effects induced by the GMMs, these effects were compared with those induced by crop rotation by planting wheat in 1999 followed by potatoes in 2000. No effect of rotation on the microbial community structure was detected. In 2000 all bacteria had a positive effect on plant growth, supposedly due to suppression of deleterious microorganisms. Our research suggests that the natural variability of microbial communities can surpass the effects of GMMs.     

Analysis of fungal diversity in the wheat rhizosphere by sequencing of cloned PCR-amplified genes encoding 18S rRNA and temperature gradient gel electrophoresis.

Like bacteria, fungi play an important role in the soil ecosystem. As only a small fraction of the fungi present in soil can be cultured, conventional microbiological techniques yield only limited information on the composition and dynamics of fungal communities in soil. DNA-based methods do not depend on the culturability of microorganisms, and therefore they offer an attractive alternative for the study of complex fungal community structures. For this purpose, we designed various PCR primers that allow the specific amplification of fungal 18S-ribosomal-DNA (rDNA) sequences, even in the presence of nonfungal 18S rDNA. DNA was extracted from the wheat rhizosphere, and 18S rDNA gene banks were constructed in Escherichia coli by cloning PCR products generated with primer pairs EF4-EF3 (1. 4 kb) and EF4-fung5 (0.5 kb). Fragments of 0.5 kb from the cloned inserts were sequenced and compared to known rDNA sequences. Sequences from all major fungal taxa were amplified by using both primer pairs. As predicted by computer analysis, primer pair EF4-EF3 appeared slightly biased to amplify Basidiomycota and Zygomycota, whereas EF4-fung5 amplified mainly Ascomycota. The 61 clones that were sequenced matched the sequences of 24 different species in the Ribosomal Database Project (RDP) database. Similarity values ranged from 0.676 to 1. Temperature gradient gel electrophoresis (TGGE) analysis of the fungal community in the wheat rhizosphere of a microcosm experiment was carried out after amplification of total DNA with both primer pairs. This resulted in reproducible, distinctive fingerprints, confirming the difference in amplification specificity. Clear banding patterns were obtained with soil and rhizosphere samples by using both primer sets in combination. By comparing the electrophoretic mobility of community fingerprint bands to that of the bands obtained with separate clones, some could be tentatively identified. While 18S-rDNA sequences do not always provide the taxonomic resolution to identify fungal species and strains, they do provide information on the diversity and dynamics of groups of related species in environmental samples with sufficient resolution to produce discrete bands which can be separated by TGGE. This combination of 18S-rDNA PCR amplification and TGGE community analysis should allow study of the diversity, composition, and dynamics of the fungal community in bulk soil and in the rhizosphere.