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.

Two label-free molecular imaging techniques, confocal Raman microscopy (CRM) and secondary ion mass spectrometry (SIMS), are combined for in situ characterization of the spatiotemporal distributions of quinolone metabolites and signaling molecules in communities of the pathogenic bacterium Pseudomonas aeruginosa. Dramatic molecular differences are observed between planktonic and biofilm modes of growth for these bacteria. We observe patterned aggregation and a high abundance of N-oxide quinolines in early biofilms and swarm zones of P. aeruginosa, while the concentrations of these secreted components in planktonic cells and agar plate colonies are below CRM and SIMS detection limits. CRM, in conjunction with principal component analysis (PCA) is used to distinguish between the two co-localized isomeric analyte pairs 4-hydroxy-2-heptylquinoline-N-oxide (HQNO)/2-heptyl-3-hydroxyquinolone (PQS) and 4-hydroxy-2-nonylquinoline-N-oxide (NQNO)/2-nonyl-hydroxyquinolone (C9-PQS) based on differences in their vibrational fingerprints, illustrating how the technique can be used to guide tandem-MS and tandem-MS imaging analysis. Because N-oxide quinolines are ubiquitous and expressed early in biofilms, these analytes may be fundamentally important for early biofilm formation and the growth and organization of P. aeruginosa microbial communities. This study underscores the advantages of using multimodal molecular imaging to study complex biological systems.

We describe a hybrid MALDI/C(60)-SIMS Q-TOF mass spectrometer and corresponding sample preparation protocols to image intact biomolecules and their fragments in mammalian spinal cord, individual invertebrate neurons, and cultured neuronal networks. A lateral spatial resolution of 10 μm was demonstrated, with further improvement feasible to 1 μm, sufficient to resolve cell outgrowth and interconnections in neuronal networks. The high mass resolution (>13,000 FWHM) and tandem mass spectrometry capability of this hybrid instrument enabled the confident identification of cellular metabolites. Sublimation of a suitable matrix, 2,5-dihydroxybenzoic acid, significantly enhanced the ion signal intensity for intact glycerophospholipid ions from mammalian nervous tissue, facilitating the acquisition of high-quality ion images for low-abundance biomolecules. These results illustrate that the combination of C60-SIMS and MALDI mass spectrometry offers particular benefits for studies that require the imaging of intact biomolecules with high spatial and mass resolution, such as investigations of single cells, subcellular organelles, and communities of cells.

A high-throughput single cell profiling method has been developed for matrix-enhanced secondary ion mass spectrometry (ME-SIMS) to investigate the lipid profiles of neuronal cells. Populations of cells are dispersed onto the substrate, their locations determined using optical microscopy, and the cell locations used to guide the acquisition of SIMS spectra from the cells. Up to 2,000 cells can be assayed in one experiment at a rate of 6 s per cell. Multiple saturated and unsaturated phosphatidylcholines (PCs) and their fragments are detected and verified with tandem mass spectrometry from individual cells when ionic liquids are employed as a matrix. Optically guided single cell profiling with ME-SIMS is suitable for a range of cell sizes, from Aplysia californica neurons larger than 75 μm to 7-μm rat cerebellar neurons. ME-SIMS analysis followed by t-distributed stochastic neighbor embedding of peaks in the lipid molecular mass range (m/z 700–850) distinguishes several cell types from the rat central nervous system, largely based on the relative proportions of the four dominant lipids, PC(32:0), PC(34:1), PC(36:1), and PC(38:5). Furthermore, subpopulations within each cell type are tentatively classified consistent with their endogenous lipid ratios. The results illustrate the efficacy of a new approach to classify single cell populations and subpopulations using SIMS profiling of lipid and metabolite contents. These methods are broadly applicable for high throughput single cell chemical analyses.

Secondary ion mass spectrometry (SIMS) and confocal Raman microscopy (CRM) are combined to analyze the chemical composition of cultured Pseudomonas aeruginosa biofilms, providing complementary chemical information for multiple analytes within the sample. Precise spatial correlation between SIMS and CRM images is achieved by applying a chemical microdroplet array to the sample surface which is used to navigate the sample, relocate regions of interest, and align image data. CRM is then employed to nondestructively detect broad molecular constituent classes—including proteins, carbohydrates, and, for the first time, quinolone signaling molecules—in Pseudomonas-derived biofilms. Subsequent SIMS imaging at the same location detects quinolone distributions in excellent agreement with the CRM, discerns multiple quinolone species which differ slightly in mass, resolves subtle differences in their distributions, and resolves ambiguous compound assignments from CRM by determining specific molecular identities via in situ tandem MS.

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.

MALDI imaging of biofilms cultured on agar plates is challenging because of problems related to matrix deposition onto agar. We describe a one-step, spray-based application of a 2,5-dihydroxybenzoic acid solution for direct MALDI imaging of hydrated Bacillus subtilis biofilms on agar. Using both an optimized airbrush and a home-built automatic sprayer, region-specific distributions of signaling metabolites and cannibalistic factors were visualized from B. subtilis cells cultivated on biofilm-promoting medium. The approach provides a homogeneous, relatively dry coating on hydrated samples, improving spot to spot signal repeatability compared to sieved matrix application, and is easily adapted for imaging a range of agar-based biofilms.

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