Effects of transgenic Bt rice on the active rhizospheric methanogenic archaeal community as revealed by DNA-based stable isotope probing.

Abstract

This study aimed to investigate the influence of planting Cry1Ab/Cry1Ac gene expressing rice (Bt rice) on rhizospheric active methanogenic archaeal communities. The nontransgenic parental line was used as the control (Ck rice). DNA-based stable isotope probing (DNA-SIP) technology traced the rhizospheric active methanogens at the tillering stage. The results revealed significantly lower CH4 emission flux from Bt soil than that from Ck soil during the whole growth period. The active methanogenic community composition remained stable. The RC-I lineage (77·9-79·8%) and Methanosaetaceae (13·9-15·1%) were the predominant active methanogens in Bt and Ck rice rhizospheres. However, the abundance of functionally active methanogens in the Bt rice rhizosphere was significantly reduced. Lower levels of root exudates (that included carbohydrate and organic acids) from Bt rice were also detected at the tillering stage. This study found that the genetic modification of rice reduced the potential methanogenic substrates came from plant-derived root exudates, which represented an important factor in reducing CH4 generation and active methanogenic archaeal abundance in Bt rhizosphere soil. The effect of genetically modified (GM) insect-resistant crops on soil micro-organisms has become an issue of public concern, especially the indirect effect of plant metabolisms caused by the insertion of foreign genes. Methanogenesis, which is regarded as a critical ecological process in paddy soil, is influenced by plant root exudates; these are mainly derived from photosynthesis. The variations in root exudates across the Bt and Ck rice suggested the indirect influence of foreign gene insertion. DNA-SIP successfully traced the active methanogenic archaeal populations assimilating 13 C-labelled photosynthetic carbon and found a strong influence of planting Bt rice on active methanogens. As a consequence, we proposed that analysis of functionally active micro-organisms is more suitable for monitoring and predicting the environmental influence of GM plants.