Friday, August 10, 2007

PS 72-22: T-RFLP approaches to nematode assemblage analysis

Suzanne Donn, Tim J Daniell, Roy Neilson, and Bryan S Griffiths. SCRI

Soil degradation is a global problem, threatening many ecosystems. One consequence is that sustainable agricultural production is under severe pressure in terms of monetary costs such as decreased crop yield and the need for increased fertiliser application. Furthermore loss of carbon from degraded soils to the atmosphere offsets reductions in CO2 emissions made elsewhere. Monitoring the state of soils (soil health) is therefore essential for their protection and in the European Union is a requirement of member countries. A number of indicators have been proposed, one such method is the use of biological indicators, for example profiling of soil nematode assemblages. Nematodes are considered a model indicator group being abundant and diverse in all soil systems, with a short generation time making them responsive to their surrounding environment. However, traditional characterisation of nematode assemblages is based on classical morphology which is both time consuming and problematical resulting in a low-throughput of samples.
Alternatively molecular approaches to classical characterisation of soil nematode assemblages can be applied. Here, we describe an alternative approach of Terminal Restriction Fragment Length Polymorphism (T-RFLP) of small subunit ribosomal DNA. Two approaches are described, the first entailing digestion of fluorescently labelled PCR product with a single enzyme, combined with multivariate analysis of the resulting fragment profile. Application of this method on agricultural sites under differing management regimes has revealed significant differences in nematode assemblage composition with addition of compost to barley plots. The second approach utilises a directed T-RFLP method where, from collected sequence information, a restriction digest has been designed to separate nematode taxa present at the study sites into terminal restriction profiles with fragments of known size.  We envisage that these resulting semi-quantitative profiles may be combined with existing biological diversity indices to provide a high-throughput robust ecological monitoring tool.