Use of lux-marked rhizobacteria to investigate rhizosphere C-flow
The aim of this study was to develop a protocol for the use of a lux-marked pseudomonad for the investigation of rhizosphere C-fluxes, and then use this to examine a system experiencing change in C flow due to pollutant pressure. In this study a typical rhizobacterium, Pseudomonas fluorescens, was marked by the insertion of the lux gene cassette of Vibrio fischeri. Two constructs were produced, P. fluorescens pUCD607 (marked with the full lux gene cassette of CDABE) and P. fluorescens FAC510 (chromosomally marked with the lux AB genes), both with bioluminescence directly linked to metabolic activity. The bioluminescence response of C-starved suspensions of these constructs to typical rhizosphere C substrates, was determined by exposure of the cells to substrate over a 30 minute period. It was shown that P. fluorescens pUCD607 can distinguish between substrate type and concentration, in terms of bioluminescence. In terms of Michaelis-Menten kinetics, glucose had a Km of 30.4mMC, and a Vmax of 200 RLU's/mMC. However, an amino acid (glutamic acid) produced a Vmax of 23316 RLU's/mMC, and a Km of 1mMC. Succinic acid, an organic acid, caused a much lower Vmax in P. fluorescens pUCD607 of 240 RLU's/mMC, and a Km of 2.5mMC. Clearly, this reporter construct offers great potential for modelling rhizosphere C-flow, as indicated by the data shown. Following this, P. fluorescens pUCD607 was used to investigate the effects of pollutant stress on rhizosphere C-flow. Plantago lanceolata was treated with paraquat and sodium arsenate, two common soil pollutants. Both caused an increase in root exudate C from 20-350%, depending on application time and concentration. P. fluorescens pUCD607 was able to detect this change, with bioluminescence directly correlated to actual C concentration. This study demonstrates that P. fluorescens pUCD607 offers a valuable tool for the reliable investigation of rhizosphere C-flow, and that lux gene technology offers the potential to further model the rhizosphere. This novel technique opens up many possibilities for applications in monitoring of ecosystem health, organic agriculture and bioremediation.