ConspectusIn 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.

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 plateassay swarming communities. We found that PQS production was not a universal signaling response to antibiotics as tobramycin elicited an alkyl quinolone response while 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. The distribution of alkyl quinolones varied by several orders of magnitude within the same swarm. 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.

The mammalian dorsal root ganglia (DRG) are located on the dorsal roots of the spinal nerves and contain cell bodies of primary sensory neurons. DRG cells have been classified into subpopulations based on their size, morphology, intracellular markers, response to stimuli, and neuropeptides. To understand the connections between DRG chemical heterogeneity and cellular function, we performed optically guided, high-throughput single cell profiling using sequential matrix-assisted laser desorption/ionization mass spectrometry (MS) to detect lipids, peptides, and several proteins in individual DRG cells. Statistical analysis of the resulting mass spectra allows stratification of the DRG population according to cellular morphology and, presumably, major cell types. A subpopulation of small cells contained myelin proteins, which are abundant in Schwann cells, and mass spectra of several larger cells contained peaks matching neurofilament, vimentin, myelin basic protein S, and thymosin beta proteins. Of the over 1000 cells analyzed, approximately 78 % produced putative peptide-rich spectra, allowing the population to be classified into three distinct cell types. Two signals with m/z 4404 and 5487 were exclusively observed in a cell type, but could not be matched to results of our previous liquid chromatography-MS analyses.

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.

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.