Colormap adjustment iterations.

<p>In this example, the viridis colormap is taken through each stage of our pipeline. From top to bottom, the image plotted is the colormap (i) as it was input, (ii) overlaid on the test image discussed by Peter Kovesi [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0199239#pone.0199239.ref021" target="_blank">21</a>], and (iii-v) based on the method presented by the Smith group [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0199239#pone.0199239.ref001" target="_blank">1</a>], these show the values of this colormap in CIECAM02-UCS space, with (iii) comparing individual values J′ (black), a′ (blue), and b′ (red) across the map, (iv) showing the perceptual deltas between each point on the map, calculated as the Euclidean distance between each point, and (v) providing a three dimensional view of the colormap in this space.</p

Our optimal colormap, cividis.

<p>Colormap shown overlaid onto a a) NanoSIMS image and b) fluid velocity map from COMSOL. Below is each corresponding CDPS plot for data along the white lines.</p

Script pipeline.

<p>Schematic of our script and how it optimizes colormaps for CVD. The colorspace, either sRGB or CIECAM02-UCS, where each operation takes place is shown along with the Python packages specifically required for each step.</p

Constant-Distance Mode Nanospray Desorption Electrospray Ionization Mass Spectrometry Imaging of Biological Samples with Complex Topography

A new approach for constant-distance mode mass spectrometry imaging (MSI) of biological samples using nanospray desorption electrospray ionization (nano-DESI) was developed by integrating a shear-force probe with the nano-DESI probe. The technical concept and basic instrumental setup, as well as the general operation of the system are described. Mechanical dampening of resonant oscillations due to the presence of shear forces between the probe and the sample surface enabled the constant-distance imaging mode via a computer-controlled closed-feedback loop. The capability of simultaneous chemical and topographic imaging of complex biological samples is demonstrated using living Bacillus subtilis ATCC 49760 colonies on agar plates. The constant-distance mode nano-DESI MSI enabled imaging of many metabolites, including nonribosomal peptides (surfactin, plipastatin, and iturin) on the surface of living bacterial colonies, ranging in diameter from 10 to 13 mm, with height variations up to 0.8 mm above the agar plate. Co-registration of ion images to topographic images provided higher-contrast images. Based on this effort, constant-mode nano-DESI MSI proved to be ideally suited for imaging biological samples of complex topography in their native states

Expanded Coverage of Phytocompounds by Mass Spectrometry Imaging Using On-Tissue Chemical Derivatization by 4‑APEBA

Probing the entirety of any species metabolome is an analytical grand challenge, especially on a cellular scale. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a common spatial metabolomics assay, but this technique has limited molecular coverage for several reasons. To expand the application space of spatial metabolomics, we developed an on-tissue chemical derivatization (OTCD) workflow using 4-APEBA for the confident identification of several dozen elusive phytocompounds. Overall, this new OTCD method enabled the annotation of roughly 280 metabolites, with only a 10% overlap in metabolic coverage when compared to analog negative ion mode MALDI-MSI on serial sections. We demonstrate that 4-APEBA outperforms other derivatization agents by providing: (1) broad specificity toward carbonyls, (2) low background, and (3) introduction of bromine isotopes. Notably, the latter two attributes also facilitate more confidence in our bioinformatics for data processing. The workflow detailed here trailblazes a path toward spatial hormonomics within plant samples, enhancing the detection of carboxylates, aldehydes, and plausibly other carbonyls. As such, several phytohormones, which have various roles within stress responses and cellular communication, can now be spatially profiled, as demonstrated in poplar root and soybean root nodule

Expanded Coverage of Phytocompounds by Mass Spectrometry Imaging Using On-Tissue Chemical Derivatization by 4‑APEBA

Probing the entirety of any species metabolome is an analytical grand challenge, especially on a cellular scale. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a common spatial metabolomics assay, but this technique has limited molecular coverage for several reasons. To expand the application space of spatial metabolomics, we developed an on-tissue chemical derivatization (OTCD) workflow using 4-APEBA for the confident identification of several dozen elusive phytocompounds. Overall, this new OTCD method enabled the annotation of roughly 280 metabolites, with only a 10% overlap in metabolic coverage when compared to analog negative ion mode MALDI-MSI on serial sections. We demonstrate that 4-APEBA outperforms other derivatization agents by providing: (1) broad specificity toward carbonyls, (2) low background, and (3) introduction of bromine isotopes. Notably, the latter two attributes also facilitate more confidence in our bioinformatics for data processing. The workflow detailed here trailblazes a path toward spatial hormonomics within plant samples, enhancing the detection of carboxylates, aldehydes, and plausibly other carbonyls. As such, several phytohormones, which have various roles within stress responses and cellular communication, can now be spatially profiled, as demonstrated in poplar root and soybean root nodule

Multimodal MSI in Conjunction with Broad Coverage Spatially Resolved MS² Increases Confidence in Both Molecular Identification and Localization

One critical aspect of mass spectrometry imaging (MSI) is the need to confidently identify detected analytes. While orthogonal tandem MS (e.g., LC–MS²) experiments from sample extracts can assist in annotating ions, the spatial information about these molecules is lost. Accordingly, this could cause mislead conclusions, especially in cases where isobaric species exhibit different distributions within a sample. In this Technical Note, we employed a multimodal imaging approach, using matrix assisted laser desorption/ionization (MALDI)-MSI and liquid extraction surface analysis (LESA)-MS²I, to confidently annotate and localize a broad range of metabolites involved in a tripartite symbiosis system of moss, cyanobacteria, and fungus. We found that the combination of these two imaging modalities generated very congruent ion images, providing the link between highly accurate structural information onfered by LESA and high spatial resolution attainable by MALDI. These results demonstrate how this combined methodology could be very useful in differentiating metabolite routes in complex systems

Secondary ion images from within the m/z = 277 nominal mass.

<p>(A) Bi₃ ToF-SIMS and (D) C₆₀ FTICR-SIMS spectra excerpts showing multiple peaks within the 277 nominal mass. (B,C) Bi₃ ToF-SIMS ion images obtained from the first “peak” and second “peak” within the 277 nominal mass. (E–I) C₆₀ FTICR-SIMS ion images generated for the corresponding peaks in D with a m/z bin size of +/− 0.001.</p

Optical and secondary ion images of <i>D. discoideum</i> aggregation streams.

<p>(A) Optical and (B–F) ion images of aggregation streams generated by 25 keV Bi₃ TOF-SIMS analysis. (G) Optical and (H–L) ion images of aggregation streams generated by 40 keV C₆₀ FTICR-SIMS analysis.</p

Overlap between the detected lipid classes and the LIPID MAPS database.

<p>(A) The number of peaks identified from the C₆₀-FTICR-SIMS spectrum by lipid class. (B) Mass distributions for compounds from the LIPID MAPS database organized by lipid class. Each data point represents the number of lipids for a given class binned every 10 mass units.</p