Soil-Bacterium Compatibility Model as a Decision-Making Tool for Soil Bioremediation.

Bioremediation of organic pollutant contaminated soil involving bioaugmentation with dedicated bacteria specialized in degrading the pollutant is suggested as a green and economically sound alternative to physico-chemical treatment. However, intrinsic soil characteristics impact the success of bioaugmentation. The feasibility of using partial least-squares regression (PLSR) to predict the success of bioaugmentation in contaminated soil based on the intrinsic physico-chemical soil characteristics and, hence, to improve the success of bioaugmentation, was examined. As a proof of principle, PLSR was used to build soil-bacterium compatibility models to predict the bioaugmentation success of the phenanthrene-degrading Novosphingobium sp. LH128. The survival and biodegradation activity of strain LH128 were measured in 20 soils and correlated with the soil characteristics. PLSR was able to predict the strain's survival using 12 variables or less while the PAH-degrading activity of strain LH128 in soils that show survival was predicted using 9 variables. A three-step approach using the developed soil-bacterium compatibility models is proposed as a decision making tool and first estimation to select compatible soils and organisms and increase the chance of success of bioaugmentation.