Bacterial biofilms are known to withstand the effects of toxic metals better than planktonic cultures of the same species. This phenomenon has been attributed to many features of the sessile lifestyle not present in free-swimming populations, but the contribution of intracellular metabolism has not been previously examined. Here, we use a combined GC-MS and (1)H NMR metabolomic approach to quantify whole-cell metabolism in biofilm and planktonic cultures of the multimetal resistant bacterium Pseudomonas fluorescens exposed to copper ions. Metabolic changes in response to metal exposure were found to be significantly different in biofilms compared to planktonic cultures. Planktonic metabolism indicated an oxidative stress response that was characterized by changes to the TCA cycle, glycolysis, pyruvate and nicotinate and niacotinamide metabolism. Similar metabolic changes were not observed in biofilms, which were instead dominated by shifts in exopolysaccharide related metabolism suggesting that metal stress in biofilms induces a protective response rather than the reactive changes observed for the planktonic cells. From these results, we conclude that differential metabolic shifts play a role in biofilm-specific multimetal resistance and tolerance. An altered metabolic response to metal toxicity represents a novel addition to a growing list of biofilm-specific mechanisms to resist environmental stress.

Metabolomics experiments have become commonplace in a wide variety of disciplines. By identifying and quantifying metabolites researchers can achieve a systems level understanding of metabolism. These studies produce vast swaths of data which are often only lightly interpreted due to the overwhelmingly large amount of variables that are measured. Recently, a number of computational tools have been developed which enable much deeper analysis of metabolomics data. These data have been difficult to interpret as understanding the connections between dozens of altered metabolites has often relied on the biochemical knowledge of researchers and their speculations. Modern biochemical databases provide information about the interconnectivity of metabolism which can be automatically polled using metabolomics secondary analysis tools. Starting with lists of altered metabolites, there are two main types of analysis: enrichment analysis computes which metabolic pathways have been significantly altered whereas metabolite mapping contextualizes the abundances and significances of measured metabolites into network visualizations. Many different tools have been developed for one or both of these applications. In this review the functionality and use of these software is discussed. Together these novel secondary analysis tools will enable metabolomics researchers to plumb the depths of their data and produce farther reaching biological conclusions than ever before.

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Epidemic strains of Pseudomonas aeruginosa have been found worldwide among the cystic fibrosis (CF) patient population. Using pulse-field gel electrophoresis, the Prairie Epidemic Strain (PES) has recently been found in one-third of patients attending the Calgary Adult CF Clinic in Canada. Using multi-locus sequence typing, PES isolates from unrelated patients were found to consistently have ST192. Though most patients acquired PES prior to enrolling in the clinic, some patients were observed to experience strain replacement upon transitioning to the clinic whereby local non-epidemic P. aeruginosa isolates were displaced by PES. Here we genotypically and phenotypically compared PES to other P. aeruginosa epidemic strains (OES) found around the world as well as local non-epidemic CF P. aeruginosa isolates in order to characterize PES. Since some epidemic strains are associated with worse clinical outcomes, we assessed the pathogenic potential of PES to determine if these isolates are virulent, shared properties with OES, and if its phenotypic properties may offer a competitive advantage in displacing local non-epidemic isolates during strain replacement. As such, we conducted a comparative analysis using fourteen phenotypic traits, including virulence factor production, biofilm formation, planktonic growth, mucoidy, and antibiotic susceptibility to characterize PES, OES, and local non-epidemic isolates. We observed that PES and OES could be differentiated from local non-epidemic isolates based on biofilm growth with PES isolates being more mucoid. Pairwise comparisons indicated that PES produced significantly higher levels of proteases and formed better biofilms than OES but were more susceptible to antibiotic treatment. Amongst five patients experiencing strain replacement, we found that super-infecting PES produced lower levels of proteases and elastases but were more resistant to antibiotics compared to the displaced non-epidemic isolates. This comparative analysis is the first to be completed on a large scale between groups of epidemic and non-epidemic CF P. aeruginosa isolates.

Here we explain the omics approach of metabolomics and how it can be applied to study a physiological response to toxic metal exposure. This review aims to educate the metallomics field to the tool of metabolomics. Metabolomics is becoming an increasingly used tool to compare natural and challenged states of various organisms, from disease states in humans to toxin exposure to environmental systems. This approach is key to understanding and identifying the cellular or biochemical targets of metals and the underlying physiological response. Metabolomics steps are described and overviews of its application to metal toxicity to organisms are given. As this approach is very new there are yet only a small number of total studies and therefore only a brief overview of some metal metabolomics studies is described. A frank critical evaluation of the approach is given to provide newcomers to the method a clear idea of the challenges and the rewards of applying metabolomics to their research.