Mass spectrometry imaging (MSI) is a versatile tool for visualizing molecular distributions in complex biological specimens, but locating microscopic chemical features of interest can be challenging in samples that lack a well-defined anatomy. To address this issue, we developed a correlated imaging approach that begins with performing matrix-assisted laser desorption/ionization (MALDI) MSI to obtain low-resolution molecular maps of a sample. The resulting maps are then used to direct subsequent microscopic secondary ion mass spectrometry (SIMS) imaging and tandem mass spectrometry (MS/MS) experiments to examine selected chemical regions of interest. By employing MALDI undersampling, the sample surface is left mostly unperturbed and available for the SIMS analysis, while also generating an ablation array that can be used for navigation in SIMS. We validated this MALDI-guided SIMS approach using cultured biofilms of the opportunistic pathogen Pseudomonas aeruginosa; bioactive secondary metabolites, including rhamnolipids and quinolones, were detected and visualized on both macro- and microscopic size scales. MSI mass assignments were confirmed with in situ MALDI MS/MS and capillary electrophoresis–electrospray ionization MS/MS analysis of biofilm extracts. Two strains of P. aeruginosa were compared, wild type and a quorum sensing mutant, and differences in metabolite abundance and distribution were observed.

Pseudomonas aeruginosa is a ubiquitous bacterium that survives in many environments, including as an acute and chronic pathogen in humans. Substantial evidence shows that P. aeruginosa behavior is affected by its motility, and appendages known as flagella and type IV pili (TFP) are known to confer such motility. The role these appendages play when not facilitating motility or attachment, however, is unclear. Here we discern a passive intercellular role of TFP during flagellar-mediated swarming of P. aeruginosa that does not require TFP extension or retraction. We studied swarming at the cellular level using a combination of laboratory experiments and computational simulations to explain the resultant patterns of cells imaged from in vitro swarms. Namely, we used a computational model to simulate swarming and to probe for individual cell behavior that cannot currently be otherwise measured. Our simulations showed that TFP of swarming P. aeruginosa should be distributed all over the cell and that TFP−TFP interactions between cells should be a dominant mechanism that promotes cell−cell interaction, limits lone cell movement, and slows swarm expansion. This predicted physical mechanism involving TFP was confirmed in vitro using pairwise mixtures of strains with and without TFP where cells without TFP separate from cells with TFP. While TFP slow swarm expansion, we show in vitro that TFP help alter collective motion to avoid toxic compounds such as the antibiotic carbenicillin. Thus, TFP physically affect P. aeruginosa swarming by actively promoting cell−cell association and directional collective motion within motile groups to aid their survival.he bacterium Pseudomonas aeruginosa is a ubiquitous organism that is a known opportunistic pathogen, causing both chronic and acute infections in susceptible populations, including individuals with cystic fibrosis or burn wounds, or Intensive Care Unit patients (1). Among questions that remain unanswered for nonobligate pathogens like P. aeruginosa is how these bacteria initiate infections after entering the host from the environment. Given that P. aeruginosa is among many bacteria that grow as a biofilm during infection, there is a need to understand how individual cells coordinate in space with each other to colonize new surfaces and subsequently transition to stationary biofilms.Many organisms coordinate their movement as a population, emerging as self-organized swarming groups. Even the untrained eye would note the coordinated swarming behavior of fish, birds, and insects. Many bacteria also exhibit collective motion by swarming over surfaces in a coordinated manner to move unimpeded at the same time (2-4). Our knowledge of the specific actions used by individual cells during collective motion is limited; the behavior of single cells within a dense population is difficult to discern experimentally. Previous attempts to study bacterial collective behavior have used computational models to test mechanisms hypothesized to influence collective motion, including directional r...

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.

Bacteria growing as surface attached biofilms differ significantly from planktonic cells in several important traits that are reflected in the spatiotemporal organization of the cells and the extracellular polymeric substances they secrete. The structural and chemical features that define these biofilms are explored here using a combination of matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) and confocal Raman microspectroscopies (CRM) to characterize and compare the composition and distribution of biomolecules found in biofilms and planktonic cells of the bacterium Pseudomonas aeruginosa. Three-day old P. aeruginosa biofilms show dramatic differences in molecular composition compared to planktonic cultures. CRM reveals that wild-type planktonic cell Raman spectra are characterized by bands linked to cellular constituents and are dominated by contributions from DNA- and RNA-related bands. In contrast, biofilm spectra are dominated by bands characteristic of glycolipids - rhamnolipids - polysaccharides and by secreted proteins. LDI MS was applied in turn to identify the rhamnolipids present in the biofilm. Experiments were also conducted using an acyl homoserine lactone quorum sensing-deficient mutant (ΔlasIΔrhlI), which is incapable of producing rhamnolipids. CRM and LDI MS analyses revealed that while molecular composition of the planktonic quorum sensing-deficient cells is similar to that of the wild-type planktonic cells, several compositional differences are observed in the mutant after biofilm growth, including complete absence of detectable rhamnolipids. CRM vibrational spectra of the mutant cells are very similar for planktonic and biofilm growth conditions, indicating that biofilm formation is greatly hindered in the absence of functioning quorum sensing machinery.

Correction for 'Spatial organization of Pseudomonas aeruginosa biofilms probed by combined matrixassisted laser desorption ionization mass spectrometry and confocal Raman microscopy' by Rachel N. Masyuko et al., Analyst, 2014, DOI: 10.1039 In the original study for the DOI detailed above, Masyuko et al. examined the Raman and mass spectrometric microspectra and images accompanying transition from planktonic cells to biolms in wild-type Pseudomonas aeruginosa and in a quorum sensing (QS)-decient mutant, DlasIDrhlI. In the course of follow-up studies, we became aware that some of the Raman spectra attributed to wild-type biolm could have arisen from a contaminant, microparticulate polystyrene (PS). Subsequently, a new series of wild-type Pseudomonas biolms were grown under rigorously PS-free conditions, and new spectra and images were acquired. For the new data shown in the gures below, Fig. 1 replaces the spectrum shown in Fig. 1(b) of the original and Fig. 3 replaces the images shown in Figs. 3(b) and S2 of the original. A detailed consideration of the bands and their assignments in the new biolm spectrum is given in the Supplemental Information (see below).While detailed analysis of the biolm spectrum, Fig. 1(b), and the image acquired, Fig. 3(b), differ from the corresponding data in the original, the major conclusions of the paper are unaffected. In particular:(1) the wild-type biolm spectra are markedly different than the corresponding wild-type planktonic cell spectra, cf. Fig. 1(b) vs. Fig. 1(a);(2) wild-type biolms produce spectra that are characteristic of rhamnolipids, secreted as part of the biolm formation process, and by a co-secreted protein/peptide component; and(3) these data are consistent with the formation of a thick (relative to the sampling depth of the CRM) biolm aer 72 h in the wild type cells, but not in the QS mutant. Supplemental InformationText in the original describing the Raman spectra ( Figs. 1(b) and 3(b) in the original) should be replaced with the following.Upon biolm formation, dramatic changes occur in the spectrum, Fig. 1(b). Biolms cultivated on bare Si exhibit a greatly reduced SiO 2 background (915-1015 cm À1 ), presumably because biolms at 72 h are much thicker than the <1 mm confocal depth of the CRM. In addition, the strong DNA/RNA-related bands at 747 (thymine), 1126 (cytosine), and 1310 cm À1 (adenine) are all diminished in relative intensity. The strong band at 1585 cm À1 is reduced in strength and a new band at 1606 cm À1 grows in. In addition, narrow bands with peaks centered at 1005 cm À1 and 1034 cm À1 appear as well as bands centered at 830 cm À1 , 1166 cm À1 , 1186 cm À1 , 1417 cm À1 , 1445 cm À1 and 1558 cm À1 . Most striking is the intense peak at 1005 cm À1 attributed to symmetric ring breathing vibrations in phenylalanine and tryptophan, indicative of proteins. 1 Other bands characteristic of proteins are at 830 cm À1 ring breathing vibrations in tyrosine (with a possible contribution from rhamnolipid), 1186 cm À1 arising from C-H in plane bend...