Single amplified genomes of Pseudomonas veronii B560

A central question in microbial ecology is which member of a community performs a particular metabolism. Several sophisticated isotope labeling techniques are available for analyzing the metabolic function of populations and individual cells in a community. However, these methods are generally either insufficiently sensitive or throughput-limited, and thus have limited applicability for the study of complex environmental samples. Here we present a novel approach that combines highly sensitive radioisotope tracking, microfluidics, high-throughput sorting, and single-cell genomics to simultaneously detect and identify individual microbial cells based solely on their <i>in situ</i> metabolic activity, without prior information on community structure.