Differential Kendrick's Plots as an Innovative Tool for Lipidomics in Complex Samples: Comparison of Liquid Chromatography and Infusion-Based Methods to Sample Differential Study

Exploiting Differential Signal Filtering (DSF) and Image Structure Filtering (ISF) Methods for Untargeted Mass Spectrometry Imaging of Bacterial Metabolites

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a label-free technique, producing images where pixels contain mass spectra. The technique allows the visualization of the spatial distribution of (bio)molecules from metabolites to proteins, on surfaces such as tissues sections or bacteria culture media. One particularly exciting example of MALDI-MSI use rests on its potential to localize ionized compounds produced during microbial interactions and chemical communication, offering a molecular snapshot of metabolomes at a given time. The huge size and the complexity of generated MSI data make the processing of the data challenging, which requires the use of computational methods. Despite recent advances, currently available commercial software relies mainly on statistical tools to identify patterns, similarities, and differences within data sets. However, grouping m/z values unique to a given data set according to microbiological contexts, such as coculture experiments, still requires tedious manual analysis. Here we propose a nontargeted method exploiting the differential signals between negative controls and tested experimental conditions, i.e., differential signal filtering (DSF), and a scoring of the ion images using image structure filtering (ISF) coupled with a fold change score between the controls and the conditions of interest. These methods were first applied to coculture experiments involving Escherichia coli and Streptomyces coelicolor, revealing specific MS signals during bacterial interaction. Two case studies were also investigated: (i) cellobiose-mediated induction for the pathogenicity of Streptomyces scabiei, the causative agent of common scab on root and tuber crops, and (ii) iron-repressed production of siderophores of S. scabiei. This report proposes guidelines for MALDI-MSI data treatment applied in the case of microbiology contexts, with enhanced ion peak annotation in specific culture conditions. The strengths and weaknesses of the methods are discussed.

Automated Structural Activity Screening of β-Diketonate Assemblies with High-Throughput Ion Mobility-Mass Spectrometry

Embracing complexity in design, metallo-supramolecular self-assembly presents an opportunity for fabricating materials of economic significance. The array of accessible supramolecules is alluring, along with favourable energy requirements. Implementation is hampered by an inability to efficiently characterise complex mixtures. The stoichiometry, size, shape, guest binding properties and reactivity of individual components and combinations thereof are inherently challenging to resolve. A large combinatorial library of four transition metals (Fe, Cu, Ni and Zn), and six β-diketonate ligands at different molar ratios and pH was robotically prepared and directly analysed over multiple timepoints with electrospray ionisation travelling wave ion mobility-mass spectrometry. The dataset was parsed for self-assembling activity without first attempting to structurally assign individual species. Self-assembling systems were readily categorised without manual data-handling, allowing efficient screening of self-assembly activity. This workflow clarifies solution phase supramolecular assembly processes without manual, bottom-up processing. The complex behaviour of the self-assembling systems was reduced to simpler qualities, which could be automatically processed.

What's the defect? Using mass defects to study oligomerization of membrane proteins and peptides in nanodiscs with native mass spectrometry

Many membrane proteins form functional complexes that are either homo- or hetero-oligomeric. However, it is challenging to characterize membrane protein oligomerization in intact lipid bilayers, especially for polydisperse mixtures. Native mass spectrometry of membrane proteins and peptides inserted in lipid nanodiscs provides a unique method to study the oligomeric state distribution and lipid preferences of oligomeric assemblies. To interpret these complex spectra, we developed novel data analysis methods using macromolecular mass defect analysis. Here, we provide an overview of how mass defect analysis can be used to study oligomerization in nanodiscs, discuss potential limitations in interpretation, and explore strategies to resolve these ambiguities. Finally, we review recent work applying this technique to studying formation of antimicrobial peptide, amyloid protein, and viroporin complexes with lipid membranes.