Chemometric and Multivariate Statistical Analysis of Time-of-Flight Secondary Ion Mass Spectrometry Spectra from Complex Cu–Fe Sulfides

Secondary ion mass spectrometry imaging and multivariate data analysis reveal co-aggregation patterns of Populus trichocarpa leaf surface compounds on a micrometer scale

Spatially resolved analysis of a multitude of compound classes has become feasible with the rapid advancement in mass spectrometry imaging strategies. In this study, we present a protocol that combines high lateral resolution time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging with a multivariate data analysis (MVA) approach to probe the complex leaf surface chemistry of Populus trichocarpa. Here, epicuticular waxes (EWs) found on the adaxial leaf surface of P. trichocarpa were blotted on silicon wafers and imaged using TOF-SIMS at 10 μm and 1 μm lateral resolution. Intense M^+● and M^-● molecular ions were clearly visible, which made it possible to resolve the individual compound classes present in EWs. Series of long-chain aliphatic saturated alcohols (C₂₁ -C₃₀ ), hydrocarbons (C₂₅ -C₃₃ ) and wax esters (WEs; C₄₄ -C₄₈ ) were clearly observed. These data correlated with the ⁷ Li-chelation matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis, which yielded mostly molecular adduct ions of the analyzed compounds. Subsequently, MVA was used to interrogate the TOF-SIMS dataset for identifying hidden patterns on the leaf's surface based on its chemical profile. After the application of principal component analysis (PCA), a small number of principal components (PCs) were found to be sufficient to explain maximum variance in the data. To further confirm the contributions from pure components, a five-factor multivariate curve resolution (MCR) model was applied. Two distinct patterns of small islets, here termed 'crystals', were apparent from the resulting score plots. Based on PCA and MCR results, the crystals were found to be formed by C₂₃ or C₂₉ alcohols. Other less obvious patterns observed in the PCs revealed that the adaxial leaf surface is coated with a relatively homogenous layer of alcohols, hydrocarbons and WEs. The ultra-high-resolution TOF-SIMS imaging combined with the MVA approach helped to highlight the diverse patterns underlying the leaf's surface. Currently, the methods available to analyze the surface chemistry of waxes in conjunction with the spatial information related to the distribution of compounds are limited. This study uses tools that may provide important biological insights into the composition of the wax layer, how this layer is repaired after mechanical damage or insect feeding, and which transport mechanisms are involved in deploying wax constituents to specific regions on the leaf surface.

A direct observation of bacterial coverage and biofilm formation by Acidithiobacillus ferrooxidans on chalcopyrite and pyrite surfaces

To obtain a fundamental understanding of the population behaviour of Acidithiobacillus ferrooxidans at chalcopyrite and pyrite surfaces, the early stage attachment behaviour and biofilm formation by this bacterium on chalcopyrite (CuFeS2) and pyrite (FeS2) were studied by optical microscopy, Raman spectroscopy, time-of-flight secondary ion mass spectrometry (ToF-SIMS) and electron backscatter diffraction (EBSD). The results indicate there was no significant difference in selectivity of bacterial attachment between chalcopyrite and pyrite. However, the result of ToF-SIMS analysis suggests that the surface of the pyrite was covered more extensively by biofilm than that of the chalcopyrite, which may indicate more extracellular polymeric substances (EPS) formation by bacterial cells growing on pyrite. EBSD and optical image analysis indicated that selectivity of bacterial attachment to chalcopyrite was not significantly affected by crystal orientation. The results also suggest that the bacterial population in defective areas of chalcopyrite was significantly higher than on the polished surfaces.

Multivariate analysis of ToF-SIMS data from multicomponent systems: the why, when, and how

The use of multivariate analysis (MVA) methods in the processing of time-of-flight secondary ion mass spectrometry (ToF-SIMS) data has become increasingly more common. MVA presents a powerful set of tools to aid the user in processing data from complex, multicomponent surfaces such as biological materials and biosensors. When properly used, MVA can help the user identify the major sources of differences within a sample or between samples, determine where certain compounds exist on a sample, or verify the presence of compounds that have been engineered into the surface. Of all the MVA methods, principal component analysis (PCA) is the most commonly used and forms an excellent starting point for the application of many of the other methods employed to process ToF-SIMS data. Herein we discuss the application of PCA and other MVA methods to multicomponent ToF-SIMS data and provide guidelines on their application and use.