Rapid visualization of lipopeptides and potential bioactive groups of compounds by combining ion mobility and MALDI imaging mass spectrometry

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.

Desorption Electrospray Ionization Cyclic Ion Mobility-Mass Spectrometry Imaging for Traumatic Brain Injury Spatial Metabolomics

Lipidomics focuses on investigating alterations in a wide variety of lipids that harness important information on metabolic processes and disease pathology. However, the vast structural diversity of lipids and the presence of isobaric and isomeric species creates serious challenges in feature identification, particularly in mass spectrometry imaging experiments that lack front-end separations. Ion mobility has emerged as a potential solution to address some of these challenges and is increasingly being utilized as part of mass spectrometry imaging platforms. Here, we present the results of a pilot mass spectrometry imaging study on rat brains subjected to traumatic brain injury (TBI) to evaluate the depth and quality of the information yielded by desorption electrospray ionization cyclic ion mobility mass spectrometry (DESI cIM MSI). Imaging data were collected with one and six passes through the cIM cell. Increasing the number of passes increased the ion mobility resolving power and the resolution of isobaric lipids, enabling the creation of more specific maps. Interestingly, drift time data enabled the recognition of multiply charged phosphoinositide species in the complex data set generated. These species have not been previously reported in TBI MSI studies and were found to decrease in the hippocampus region following injury. These changes were attributed to increased enzymatic activity after TBI, releasing arachidonic acid that is converted to eicosanoids to control inflammation. A substantial reduction in NAD and alterations in other adenine metabolites were also observed, supporting the hypothesis that energy metabolism in the brain is severely disrupted in TBI.

Metabolic insights from mass spectrometry imaging of biofilms: A perspective from model microorganisms

Biofilms are dense aggregates of bacterial colonies embedded inside a self-produced polymeric matrix. Biofilms have received increasing attention in medical, industrial, and environmental settings due to their enhanced survival. Their characterization using microscopy techniques has revealed the presence of structural and cellular heterogeneity in many bacterial systems. However, these techniques provide limited chemical detail and lack information about the molecules important for bacterial communication and virulence. Mass spectrometry imaging (MSI) bridges the gap by generating spatial chemical information with unmatched chemical detail, making it an irreplaceable analytical platform in the multi-modal imaging of biofilms. In the last two decades, over 30 species of biofilm-forming bacteria have been studied using MSI in different environments. The literature conveys both analytical advancements and an improved understanding of the effects of environmental variables such as host surface characteristics, antibiotics, and other species of microorganisms on biofilms. This review summarizes the insights from frequently studied model microorganisms. We share a detailed list of organism-wide metabolites, commonly observed mass spectral adducts, culture conditions, strains of bacteria, substrate, broad problem definition, and details of the MS instrumentation, such as ionization sources and matrix, to facilitate future studies. We also compared the spatial characteristics of the secretome under different study designs to highlight changes because of various environmental influences. In addition, we highlight the current limitations of MSI in relation to biofilm characterization to enable cross-comparison between experiments. Overall, MSI has emerged to become an important approach for the spatial/chemical characterization of bacterial biofilms and its use will continue to grow as MSI becomes more accessible.

Recent Advances in Mass Spectrometry-Based Spatially Resolved Molecular Imaging of Drug Disposition and Metabolomics

Mass spectrometric imaging is a nontargeted, tag-free, high-throughput, and highly responsive analytical approach. The highly accurate molecular visualization detection technology enables qualitative and quantitative analyses of biologic tissues or cells scanned by mass spectrometry in situ, extracting known and unknown multiple compounds, and simultaneously assessing relative contents of targeting molecules by monitoring their molecular ions and pinpointing the spatial locations of those molecules distributed. Five mass spectrometric imaging techniques and their characteristics are introduced in the review, including matrix-assisted laser desorption ionization mass spectrometry, secondary ion mass spectrometry, desorption electrospray ionization mass spectrometry, laser ablation electrospray ionization mass spectrometry, and laser ablation inductively coupled plasma mass spectrometry. The mass spectrometry-based techniques provide the possibility for spatial metabolomics with the capability of high throughput and precision detection. The approaches have been widely employed to spatially image not only metabolome of endogenous amino acids, peptides, proteins, neurotransmitters, and lipids but also the disposition of exogenous chemicals, such as pharmaceutical agents, environmental pollutants, toxicants, natural products, and heavy metals. The techniques also provide us with spatial distribution imaging of analytes in single cells, tissue microregions, organs, and whole animals. SIGNIFICANCE STATEMENT: The review article includes an overview of five commonly used mass spectrometers for spatial imaging and describes the advantages and disadvantages of each. Examples of the technology applications cover drug disposition, diseases, and omics. Technical aspects of relative and absolute quantification by mass spectrometric imaging and challenges for future new applications are discussed as well. The reviewed knowledge may benefit the development of new drugs and provide a better understanding of biochemical processes related to physiology and diseases.