Time-Resolved Metabolic Footprinting for Nonlinear Modeling of Bacterial Substrate Utilization

Abstract

ABSTRACT Untargeted profiling of small-molecule metabolites from microbial culture supernatants (metabolic footprinting) has great potential as a phenotyping tool. We used time-resolved metabolic footprinting to compare one Escherichia coli and three Pseudomonas aeruginosa strains growing on complex media and show that considering metabolite changes over the whole course of growth provides much more information than analyses based on data from a single time point. Most strikingly, there was pronounced selectivity in metabolite uptake, even when the bacteria were growing apparently exponentially, with certain groups of metabolites not taken up until others had been entirely depleted from the medium. In addition, metabolite excretion showed some complex patterns. Fitting nonlinear equations (four-parameter sigmoids) to individual metabolite data allowed us to model these changes for metabolite uptake and visualize them by back-projecting the curve-fit parameters onto the original growth curves. These “uptake window” plots clearly demonstrated strain differences, with the uptake of some compounds being reversed in order between different strains. Comparison of an undefined rich medium with a defined complex medium designed to mimic cystic fibrosis sputum showed many differences, both qualitative and quantitative, with a greater proportion of excreted to utilized metabolites in the defined medium. Extending the strain comparison to a more closely related set of isolates showed that it was possible to discriminate two species of the Burkholderia cepacia complex based on uptake dynamics alone. We believe time-resolved metabolic footprinting could be a valuable tool for many questions in bacteriology, including isolate comparisons, phenotyping deletion mutants, and as a functional complement to taxonomic classifications.