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Bacterial biofilms are groups of bacteria that exist within a self-produced extracellular matrix, adhering to each other and usually to a surface. They grow on medical equipment and inserts such as catheters and are responsible for many persistent infections throughout the body, as they can have high resistance to many antimicrobials. Pseudomonas aeruginosa is an opportunistic pathogen that can cause both acute and chronic infections and is used as a model for research into biofilms. Direct biochemical methods of imaging of molecules in bacterial biofilms are of high value in gaining a better understanding of the fundamental biology of biofilms and biochemical gradients within them. Time of flight-secondary-ion mass spectrometry (TOF-SIMS) is one approach, which combines relatively high spatial resolution and sensitivity and can perform depth profiling analysis. It has been used to analyze bacterial biofilms but has not yet been used to study the distribution of antimicrobials (including antibiotics and the antimicrobial metal gallium) within biofilms. Here we compared two methods of imaging of the interior structure of P. aeruginosa in biological samples using TOF-SIMS, looking at both antimicrobials and endogenous biochemicals: cryosectioning of tissue samples and depth profiling to give pseudo-three-dimensional (pseudo-3D) images. The sample types included both simple biofilms grown on glass slides and bacteria growing in tissues in an ex vivo pig lung model. The two techniques for the 3D imaging of biofilms are potentially valuable complementary tools for analyzing bacterial infection. IMPORTANCE Modern analytical techniques are becoming increasingly important in the life sciences; imaging mass spectrometry offers the opportunity to gain unprecedented amounts of information on the distribution of chemicals in samples-both xenobiotics and endogenous compounds. In particular, simultaneous imaging of antibiotics (and other antimicrobial compounds) and bacterium-derived metabolites in complex biological samples could be very important in the future for helping to understand how sample matrices impact the survival of bacteria under antibiotic challenge. We have shown that an imaging mass spectrometric technique, TOF-SIMS, will be potentially extremely valuable for this kind of research in the future.

Unlabelled: Nitrogen regulation in Escherichia coli is a model system for gene regulation in bacteria. Growth on glutamine as a sole nitrogen source is assumed to be nitrogen limiting, inferred from slow growth and strong NtrB/NtrC-dependent gene activation. However, we show that under these conditions, the intracellular glutamine concentration is not limiting but 5.6-fold higher than in ammonium-replete conditions; in addition, α-ketoglutarate concentrations are elevated. We address this glutamine paradox from a systems perspective. We show that the dominant role of NtrC is to regulate glnA transcription and its own expression, indicating that the glutamine paradox is not due to NtrC-independent gene regulation. The absolute intracellular NtrC and GS concentrations reveal molecular control parameters, where NtrC-specific activities were highest in nitrogen-starved cells, while under glutamine growth, NtrC showed intermediate specific activity. We propose an in vivo model in which α-ketoglutarate can derepress nitrogen regulation despite nitrogen sufficiency., Importance: Nitrogen is the most important nutrient for cell growth after carbon, and its metabolism is coordinated at the metabolic, transcriptional, and protein levels. We show that growth on glutamine as a sole nitrogen source, commonly assumed to be nitrogen limiting and used as such as a model system for nitrogen limitation, is in fact nitrogen replete. Our integrative quantitative analysis of key molecules involved in nitrogen assimilation and regulation reveal that glutamine is not necessarily the dominant molecule signaling nitrogen sufficiency and that α-ketoglutarate may play a more important role in signaling nitrogen status. NtrB/NtrC integrates α-ketoglutarate and glutamine signaling--sensed by the UTase (glnD) and PII (glnB), respectively--and regulates the nitrogen response through self-regulated expression and phosphorylation-dependent activation of the nitrogen (ntr) regulon. Our findings support α-ketoglutarate acting as a global regulatory metabolite.

We grew Pseudomonas aeruginosa in LB and artificial sputum medium (ASM) (filtered and unfiltered) and quantified metabolite utilization and excretion by nuclear magnetic resonance (NMR) spectroscopy (metabolic footprinting or extracellular metabolomics). Utilization rates were similar between media, but there were differences in excretion-e.g., acetate was produced only in unfiltered ASM.

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.