Rapid Detection and Enumeration of Exoelectrogenic Bacteria in Lake Sediments and a Wastewater Treatment Plant Using a Coupled WO3 Nanoclusters and Most Probable Number Method

Abstract

Exoelectrogenic bacteria (EEB) play important roles in biogeochemical cycling, environmental remediation, wastewater treatment, and bioenergy recovery. Methods for effectively and rapidly probing the abundance of EEB in environments are highly desirable. In this work, a novel approach that couples WO3 nanoclusters and the most probable number (MPN) method for rapid detection and enumeration of EEB was developed. This WO3–MPN approach allowed rapid and reliable estimation of the population size of two typical EEB, Shewanella oneidensis MR-1 and Geobacter sulfurreducens DL-1. In addition, it was successfully applied to detect and count EEB in environmental samples from the sediments of a freshwater lake (9.9 × 104 to 4.1 × 106 cells/g of dry sediment) and engineered samples of a municipal wastewater treatment plant (1.0 × 103 to 7.5 × 105 cells/mL). This work may facilitate better identification and practical applications of EEB in natural and engineered environments.