Paracoccus and Achromobacter bacteria contribute to rapid biodegradation of imidacloprid in soils

Neonicotinoids are among the most widely used insecticides worldwide, and as such, have garnered increasing attention from the scientific community in regards to their potentially negative environmental impacts. Recently, the degradability of neonicotinoid in soil has gained more attentions. However, what role soil microbes play in this degradation remains vastly underexplored. In this study, we compared the capacity of soil microbes sampled from different geographic regions and fields to degrade the neonicotinoid insecticide imidacloprid. Additionally, the composition of microbiota having low, middle, and high degradation activity was analyzed via high throughput sequencing. Correlations between microbiota composition and degradation activities were analyzed and reconfirmed. The results showed that the composition of soil microbiota and their degradation activity (ranged from zero to 96.25%) varied significantly between soil samples from different geographic locations. Correlation analysis showed that Paracoccus and Achromobacter bacteria were positively correlated with high degradation activity. Imidacloprid degradation experiments using these bacteria showed that Achromobacter sp. alone exhibited degradation activity reaching and sustaining 100% by day 20 while Paracoccus sp. did not. However, combining these bacteria resulted in increased degradation activity which reached 100% at day 15 relative to that achieved by Achromobacter sp. alone. This study demonstrated the capacity of soil microbes to degrade imidacloprid, and identified two promising bacterial candidates that could be potentially used in future to reduce imidacloprid accumulation in soils.

Automated summary

This study revealed significant variation in the ability of soil microbes from different geographic locations to degrade neonicotinoid insecticide imidacloprid, and identified two promising bacterial candidates, Paracoccus and Achromobacter, through high throughput sequencing.