Effect of Micro-Patterned Mucin on Quinolone and Rhamnolipid Profiles of Mucoid Pseudomonas aeruginosa under Antibiotic Stress.

Pseudomonas aeruginosa (P. aeruginosa) is commonly implicated in hospital-acquired infections where its capacity to form biofilms on a variety of surfaces and the resulting enhanced antibiotic resistance seriously limit treatment choices. Because surface attachment sensitizes P. aeruginosa to quorum sensing (QS) and induces virulence through both chemical and mechanical cues, we investigate the effect of surface properties through spatially patterned mucin, combined with sub-inhibitory concentrations of tobramycin on QS and virulence factors in both mucoid and non-mucoid P. aeruginosa strains using multi-modal chemical imaging combining confocal Raman microscopy and matrix-assisted laser desorption/ionization-mass spectrometry. Samples comprise surface-adherent static biofilms at a solid-water interface, supernatant liquid, and pellicle biofilms at an air-water interface at various time points. Although the presence of a sub-inhibitory concentration of tobramycin in the supernatant retards growth and development of static biofilms independent of strain and surface mucin patterning, we observe clear differences in the behavior of mucoid and non-mucoid strains. Quinolone signals in a non-mucoid strain are induced earlier and are influenced by mucin surface patterning to a degree not exhibited in the mucoid strain. Additionally, phenazine virulence factors, such as pyocyanin, are observed in the pellicle biofilms of both mucoid and non-mucoid strains but are not detected in the static biofilms from either strain, highlighting the differences in stress response between pellicle and static biofilms. Differences between mucoid and non-mucoid strains are consistent with their strain-specific phenology, in which the mucoid strain develops highly protected biofilms.

Biopolymer Patterning-Directed Secretion in Mucoid and Nonmucoid Strains of Pseudomonas aeruginosa Revealed by Multimodal Chemical Imaging.

Quinolone, pyocyanin, and rhamnolipid production were studied in Pseudomonas aeruginosa by spatially patterning mucin, a glycoprotein important to infection of lung epithelia. Mass spectrometric imaging and confocal Raman microscopy are combined to probe P. aeruginosa biofilms from mucoid and nonmucoid strains grown on lithographically defined patterns. Quinolone signatures from biofilms on patterned vs unpatterned and mucin vs mercaptoundecanoic acid (MUA) surfaces were compared. Microbial attachment is accompanied by secretion of 2-alkyl-4-quinolones as well as rhamnolipids from the mucoid and nonmucoid strains. Pyocyanin was also detected both in the biofilm and in the supernatant in the mucoid strain only. Significant differences in the spatiotemporal distributions of secreted factors are observed between strains and among different surface patterning conditions. The mucoid strain is sensitive to composition and patterning while the nonmucoid strain is not, and in promoting community development in the mucoid strain, nonpatterned surfaces are better than patterned, and mucin is better than MUA. Also, the mucoid strain secretes the virulence factor pyocyanin in a way that correlates with distress. A change in the relative abundance for two rhamnolipids is observed in the mucoid strain during exposure to mucin, whereas minimal variation is observed in the nonmucoid strain. Differences between mucoid and nonmucoid strains are consistent with their strain-specific phenology, in which the mucoid strain develops highly protected and withdrawn biofilms that achieve Pseudomonas quinolone signal production under limited conditions.

Lipid Analysis of 30 000 Individual Rodent Cerebellar Cells Using High-Resolution Mass Spectrometry.

Single-cell measurements aid our understanding of chemically heterogeneous systems such as the brain. Lipids are one of the least studied chemical classes, and their cell-to-cell heterogeneity remains largely unexplored. We adapted microscopy-guided single-cell profiling using matrix-assisted laser desorption/ionization ion cyclotron resonance mass spectrometry to profile the lipid composition of over 30 000 individual rat cerebellar cells. We detected 520 lipid features, many of which were found in subsets of cells; Louvain clustering identified 101 distinct groups that can be correlated to neuronal and astrocytic classifications and lipid classes. Overall, the two most common lipids found were [PC(32:0)+H]+ and [PC(34:1)+H]+, which were present within 98.9 and 89.5% of cells, respectively; lipid signals present in <1% of cells were also detected, including [PC(34:1)+K]+ and [PG(40:2(OH))+Na]+. These results illustrate the vast lipid heterogeneity found within rodent cerebellar cells and hint at the distinct functional consequences of this heterogeneity.

A Versatile Strategy for Characterization and Imaging of Drip Flow Microbial Biofilms.

The inherent architectural and chemical complexities of microbial biofilms mask our understanding of how these communities form, survive, propagate, and influence their surrounding environment. Here we describe a simple and versatile workflow for the cultivation and characterization of model flow-cell-based microbial ecosystems. A customized low-shear drip flow reactor was designed and employed to cultivate single and coculture flow-cell biofilms at the air-liquid interface of several metal surfaces. Pseudomonas putida F1 and Shewanella oneidensis MR-1 were selected as model organisms for this study. The utility and versatility of this platform was demonstrated via the application of several chemical and morphological imaging techniques-including matrix-assisted laser desorption/ionization mass spectrometry imaging, secondary ion mass spectrometry imaging, and scanning electron microscopy-and through the examination of model systems grown on iron substrates of varying compositions. Implementation of these techniques in combination with tandem mass spectrometry and a two-step imaging principal component analysis strategy resulted in the identification and characterization of 23 lipids and 3 oligosaccharides in P. putida F1 biofilms, the discovery of interaction-specific analytes, and the observation of several variations in cell and substrate morphology present during microbially influenced corrosion. The presented workflow is well-suited for examination of both single and multispecies drip flow biofilms and offers a platform for fundamental inquiries into biofilm formation, microbe-microbe interactions, and microbially influenced corrosion.

Quantitative SIMS Imaging of Agar-Based Microbial Communities.

After several decades of widespread use for mapping elemental ions and small molecular fragments in surface science, secondary ion mass spectrometry (SIMS) has emerged as a powerful analytical tool for molecular imaging in biology. Biomolecular SIMS imaging has primarily been used as a qualitative technique; although the distribution of a single analyte can be accurately determined, it is difficult to map the absolute quantity of a compound or even to compare the relative abundance of one molecular species to that of another. We describe a method for quantitative SIMS imaging of small molecules in agar-based microbial communities. The microbes are cultivated on a thin film of agar, dried under nitrogen, and imaged directly with SIMS. By use of optical microscopy, we show that the area of the agar is reduced by 26 ± 2% (standard deviation) during dehydration, but the overall biofilm morphology and analyte distribution are largely retained. We detail a quantitative imaging methodology, in which the ion intensity of each analyte is (1) normalized to an external quadratic regression curve, (2) corrected for isomeric interference, and (3) filtered for sample-specific noise and lower and upper limits of quantitation. The end result is a two-dimensional surface density image for each analyte. The sample preparation and quantitation methods are validated by quantitatively imaging four alkyl-quinolone and alkyl-quinoline N-oxide signaling molecules (including Pseudomonas quinolone signal) in Pseudomonas aeruginosa colony biofilms. We show that the relative surface densities of the target biomolecules are substantially different from values inferred through direct intensity comparison and that the developed methodologies can be used to quantitatively compare as many ions as there are available standards.

Spatially dependent alkyl quinolone signaling responses to antibiotics in Pseudomonas aeruginosa swarms.

There is a general lack of understanding about how communities of bacteria respond to exogenous toxins such as antibiotics. Most of our understanding of community-level stress responses comes from the study of stationary biofilm communities. Although several community behaviors and production of specific biomolecules affecting biofilm development and associated behavior have been described for Pseudomonas aeruginosa and other bacteria, we have little appreciation for the production and dispersal of secreted metabolites within the 2D and 3D spaces they occupy as they colonize, spread, and grow on surfaces. Here we specifically studied the phenotypic responses and spatial variability of alkyl quinolones, including the Pseudomonas quinolone signal (PQS) and members of the alkyl hydroxyquinoline (AQNO) subclass, in P. aeruginosa plate-assay swarming communities. We found that PQS production was not a universal signaling response to antibiotics, as tobramycin elicited an alkyl quinolone response, whereas carbenicillin did not. We also found that PQS and AQNO profiles in response to tobramycin were markedly distinct and influenced these swarms on different spatial scales. At some tobramycin exposures, P. aeruginosa swarms produced alkyl quinolones in the range of 150 µm PQS and 400 µm AQNO that accumulated as aggregates. Our collective findings show that the distribution of alkyl quinolones can vary by several orders of magnitude within the same swarming community. More notably, our results suggest that multiple intercellular signals acting on different spatial scales can be triggered by one common cue.

Mass Spectrometry Imaging of Complex Microbial Communities.

In the two decades since mass spectrometry imaging (MSI) was first applied to visualize the distribution of peptides across biological tissues and cells, the technique has become increasingly effective and reliable. MSI excels at providing complementary information to existing methods for molecular analysis-such as genomics, transcriptomics, and metabolomics-and stands apart from other chemical imaging modalities through its capability to generate information that is simultaneously multiplexed and chemically specific. Today a diverse family of MSI approaches are applied throughout the scientific community to study the distribution of proteins, peptides, and small-molecule metabolites across many biological models. The inherent strengths of MSI make the technique valuable for studying microbial systems. Many microbes reside in surface-attached multicellular and multispecies communities, such as biofilms and motile colonies, where they work together to harness surrounding nutrients, fend off hostile organisms, and shield one another from adverse environmental conditions. These processes, as well as many others essential for microbial survival, are mediated through the production and utilization of a diverse assortment of chemicals. Although bacterial cells are generally only a few microns in diameter, the ecologies they influence can encompass entire ecosystems, and the chemical changes that they bring about can occur over time scales ranging from milliseconds to decades. Because of their incredible complexity, our understanding of and influence over microbial systems requires detailed scientific evaluations that yield both chemical and spatial information. MSI is well-positioned to fulfill these requirements. With small adaptations to existing methods, the technique can be applied to study a wide variety of chemical interactions, including those that occur inside single-species microbial communities, between cohabitating microbes, and between microbes and their hosts. In recognition of this potential for scientific advancement, researchers have adapted MSI methodologies for the specific needs of the microbiology research community. As a result, workflows exist for imaging microbial systems with many of the common MSI ionization methods. Despite this progress, there is substantial room for improvements in instrumentation, sample preparation, and data interpretation. This Account provides a brief overview of the state of technology in microbial MSI, illuminates selected applications that demonstrate the potential of the technique, and highlights a series of development challenges that are needed to move the field forward. In the coming years, as microbial MSI becomes easier to use and more universally applicable, the technique will evolve into a fundamental tool widely applied throughout many divisions of science, medicine, and industry.