To more rapidly analyse catabolic gene diversity, but also diversity of expressed catabolic genes, molecular fingerprinting methods are necessary. We therefore established reliable PCR-SSCP (single stranded chain polymorphism) methods to sort catabolic genes (see Junca et al., 2003). New methods were needed to analyze the diversity of catabolic key genes involved in the degradation of phenoxyalkanoate herbicides.
Two kinds of genes are known to encode enzymes for 2,4-D transformation, termed tfdA encoding 2,4-D/a-ketoglutarate dioxygenase and cad encoding 2,4-D monooxygenases. Different primer combinations and phosphorylated derivatives were evaluated for tfdA genes to obtain fragment mixtures comprising only fragments of the target genes. Best results were obtained for primers termed tfdAa, which were capable to amplify both tfdA and tfdAa-genes.
Separation allowed distinguishing between highly similar gene variants, and successfully separated tfdA and tfdAa gene variants. Separation conditions were also evaluated for cad genes using fragments. The current method allows separating successfully different groups of cad genes, however, singling base differences cannot yet be evaluated. The current methods are of special use for evaluating the catabolic potential and diversity for phenoxyalkanoate degradation in diverse soil systems.
Bacterial community responses were assessed through T-RFLP (See Sanchez et al. 2004). To do so, bacterial community DNA was digested with MspI or HhaI restriction enzymes and the corresponding T-RFLP signals were plotted as relative abundance vs fragment length to obtain richness (number of bacteria or ribotypes in the sample) and diversity values that informed on the bacterial community structure. Two additional outputs from these T-RFLP plots could be obtained.
First, comparisons of the bacterial community structures under different conditions (presence/absence of herbicides or plants, time of incubation, type of soil, etc) were carried out, and were, usually, very informative of the effect of specific conditions on bacterial community structures (see below). Statistical significance of such comparisons was assessed by NMDS, PCA, and ANOSIM analyses. Second, taxonomic assignations, based on public databases such as the Ribosomal Database Project, were also possible.
This allowed distinction of the effect of different conditions at the level of phyla and some classes. The robustness of comparisons of soil bacteria taxonomic profiles obtained in this way was assessed by PCA, ANOSIM, and analysis of similarity of percentages (SIMPER).