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This work presents molecular-level investigations of how wellcharacterized silica-supported phospholipid bilayers formed from either pure DOPC or a 9:1 mixture of DOPC:DOTAP interact with positively and negatively charged 4 nm gold metal nanoparticles at pH 7.4 and NaCl concentrations ranging from 0.001 to 0.1 M. Second harmonic generation (SHG) charge screening measurements indicate the supported bilayers carry a negative interfacial potential. Resonantly enhanced SHG measurements probing electronic transitions within the gold core of the nanoparticles show the particles interact irreversibly with the supported bilayers at a range of concentrations. At 0.1 M NaCl, surface coverages for the particles functionalized with the negatively charged ligand mercaptopropionic acid (MPA) or wrapped in the cationic polyelectrolyte poly(allylamine) hydrochloride (PAH) are estimated from a joint analysis of QCM-D, XPS, AFM, and ToF-SIMS to be roughly 1 × 10 7 and 1 × 10 11 particles cm −2 , respectively. Results from complementary SHG charge screening experiments point to the possibility that the surface coverage of the MPA-coated particles is more limited by interparticle Coulomb repulsion due to the charges within their hydrodynamic volumes than with the PAH-wrapped particles. Yet, SHG adsorption isotherms indicate that the interaction strength per particle is independent of ionic strength and particle coating, highlighting the importance of multivalent interactions. 1 H NMR spectra of the lipids within vesicles suspended in solution show little change upon interaction with either particle type but indicate loosening of the gold-bound PAH polymer wrapping upon attachment to the vesicles. The thermodynamic, spectroscopic, and electrostatic data presented here may serve to benchmark experimental and computational studies of nanoparticle attachment processes at the nano−bio interface.

Soil organic matter (SOM), a complex, heterogeneous mixture of above and belowground plant litter and animal and microbial residues at various degrees of decomposition, is a key reservoir for carbon (C) and nutrient biogeochemical cycling in soil based ecosystems. A limited understanding of the molecular composition of SOM limits the ability to routinely decipher chemical processes within soil and accurately predict how terrestrial carbon fluxes will respond to changing climatic conditions and land use. To elucidate the molecular-level structure of SOM, we selectively extracted a broad range of intact SOM compounds by a combination of different organic solvents from soils with a wide range of C content. Our use of electrospray ionization (ESI) coupled with Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) and a suite of solvents with varying polarity significantly expands the inventory of the types of organic molecules present in soils. Specifically, we found that hexane is selective for lipid-like compounds with very low O/C ratios (<0.1); water (H2O) was selective for carbohydrates with high O/C ratios; acetonitrile (ACN) preferentially extracts lignin, condensed structures, and tannin polyphenolic compounds with O/C > 0.5; methanol (MeOH) has higher selectivity toward compounds characterized with low O/C < 0.5; and hexane, MeOH, ACN, and H2O solvents increase the number and types of organic molecules extracted from soil for a broader range of chemically diverse soil types. Our study of SOM molecules by ESI FTICR MS revealed new insight into the molecular-level complexity of organics contained in soils. We present the first comparative study of the molecular composition of SOM from different ecosystems using ultra high-resolution mass spectrometry.

Secondary ion mass spectrometry (SIMS) has become an increasingly utilized tool in biologically relevant studies. Of these, high lateral resolution methodologies using the NanoSIMS 50/50L have been especially powerful within many biological fields over the past decade. Here, the authors provide a review of this technology, sample preparation and analysis considerations, examples of recent biological studies, data analyses, and current outlooks. Specifically, the authors offer an overview of SIMS and development of the NanoSIMS. The authors describe the major experimental factors that should be considered prior to NanoSIMS analysis and then provide information on best practices for data analysis and image generation, which includes an in-depth discussion of appropriate colormaps. Additionally, the authors provide an open-source method for data representation that allows simultaneous visualization of secondary electron and ion information within a single image. Finally, the authors present a perspective on the future of this technology and where they think it will have the greatest impact in near future.

Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.

Color vision deficiency (CVD) affects more than 4% of the population and leads to a different visual perception of colors. Though this has been known for decades, colormaps with many colors across the visual spectra are often used to represent data, leading to the potential for misinterpretation or difficulty with interpretation by someone with this deficiency. Until the creation of the module presented here, there were no colormaps mathematically optimized for CVD using modern color appearance models. While there have been some attempts to make aesthetically pleasing or subjectively tolerable colormaps for those with CVD, our goal was to make optimized colormaps for the most accurate perception of scientific data by as many viewers as possible. We developed a Python module, cmaputil, to create CVD-optimized colormaps, which imports colormaps and modifies them to be perceptually uniform in CVD-safe colorspace while linearizing and maximizing the brightness range. The module is made available to the science community to enable others to easily create their own CVD-optimized colormaps. Here, we present an example CVD-optimized colormap created with this module that is optimized for viewing by those without a CVD as well as those with red-green colorblindness. This colormap, cividis, enables nearly-identical visual-data interpretation to both groups, is perceptually uniform in hue and brightness, and increases in brightness linearly.

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.

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) enables chemically imaging the distributions of various lipid species in model membranes. However, discriminating the TOF-SIMS data of structurally similar lipids is very difficult because the high intensity, low mass fragment ions needed to achieve submicrometer lateral resolution are common to multiple lipid species. Here, we demonstrate that principal component analysis (PCA) can discriminate the TOF-SIMS spectra of four unlabeled saturated phosphatidylcholine species, 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC), 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), and 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC) according to variations in the intensities of their low mass fragment ions (m/z ≤ 200). PCA of TOF-SIMS images of phase-separated DSPC/DLPC and DPPC/DLPC membranes enabled visualizing the distributions of each phosphatidylcholine species with higher contrast and specificity than that of individual TOF-SIMS ion images. Comparison of the principal component (PC) scores images to atomic force microscopy (AFM) images acquired at the same membrane location before TOF-SIMS analysis confirmed that the PC scores images reveal the phase-separated membrane domains. The lipid composition within these domains was identified by projection of their TOF-SIMS spectra onto PC models developed using pure lipid standards. This approach may enable the identification and chemical imaging of structurally similar lipid species within more complex membranes.