Label-free sub-micrometer 3D imaging of ciprofloxacin in native-state biofilms with cryo-time-of-flight secondary ion mass spectrometry

Spatially resolved metabolomics: From metabolite mapping to function visualising

Mass spectrometry imaging (MSI)-based spatially resolved metabolomics addresses the limitations inherent in traditional liquid chromatography-tandem mass spectrometry (LC-MS)-based metabolomics, particularly the loss of spatial context within heterogeneous tissues. MSI not only enhances our understanding of disease aetiology but also aids in the identification of biomarkers and the assessment of drug toxicity and therapeutic efficacy by converting invisible metabolites and biological networks into visually rendered image data. In this comprehensive review, we illuminate the key advancements in MSI-driven spatially resolved metabolomics over the past few years. We first outline recent innovations in preprocessing methodologies and MSI instrumentation that improve the sensitivity and comprehensiveness of metabolite detection. We then delve into the progress made in functional visualization techniques, which enhance the precision of metabolite identification and annotation. Ultimately, we discuss the significant potential applications of spatially resolved metabolomics technology in translational medicine and drug development, offering new perspectives for future research and clinical translation. HIGHLIGHTS: MSI-driven spatial metabolomics preserves metabolite spatial information, enhancing disease analysis and biomarker discovery. Advances in MSI technology improve detection sensitivity and accuracy, expanding bioanalytical applications. Enhanced visualization techniques refine metabolite identification and spatial distribution analysis. Integration of MSI with AI promises to advance precision medicine and accelerate drug development.

ToF-SIMS Investigation of Environmental Effects on Analyte Migration in Matrix Coatings for Mass Spectrometry Imaging Using a Newly Developed Vapor Deposition System

High resolution mass spectrometry images are of increasing importance in biological applications, such as the study of tissues and single cells. Two promising techniques for this are matrix-enhanced secondary ion mass spectrometry (ME-SIMS) and matrix-assisted laser desorption/ionization (MALDI). For both techniques, the sample of interest must be coated with a matrix prior to analysis, and analytes must migrate into the matrix. The mechanisms involved in this migration and the factors that influence the migration are poorly understood, which lead to difficulties with reproducibility. In this work, a sublimation matrix coater with an effusion cell and sample cooling was developed and built in-house for controlled physical vapor deposition. In this system, sample transfer between the coater and mass spectrometer is possible without breaking vacuum, which facilitates the study of environmental influences on analyte migration. The influence of exposure to ambient air on the migration of two analytes (a lipid and a peptide), which were coated with the matrix α-cyano-4-hydroxycinnamic acid (CHCA), was studied using 3D-SIMS imaging. Although the distribution of analyte in the matrix changed very little after 21 h of storage in vacuum, significant redistribution of the analyte was observed after exposure to ambient air. The magnitude of the effect was greater for the lipid than for the peptide. Further work is needed to determine the role of humidity in the redistribution process and the impact of analyte redistribution on MALDI measurements.

PCA, PC-CVA, and Random Forest of GCIB-SIMS Data for the Elucidation of Bacterial Envelope Differences in Antibiotic Resistance Research

Antibiotic resistance can rapidly spread through bacterial populations via bacterial conjugation. The bacterial membrane has an important role in facilitating conjugation, thus investigating the effects on the bacterial membrane caused by conjugative plasmids, antibiotic resistance, and genes involved in conjugation is of interest. Analysis of bacterial membranes was conducted using gas cluster ion beam-secondary ion mass spectrometry (GCIB-SIMS). The complexity of the data means that data analysis is important for the identification of changes in the membrane composition. Preprocessing of data and several analytical methods for identification of changes in bacterial membranes have been investigated. GCIB-SIMS data from Escherichia coli samples were subjected to principal components analysis (PCA), principal components-canonical variate analysis (PC-CVA), and Random Forests (RF) data analysis with the aim of extracting the maximum biological information. The influence of increasing replicate data was assessed, and the effect of diminishing biological variation was studied. Optimized m/z region-specific scaling provided improved clustering, with an increase in biologically significant peaks contributing to the loadings. PC-CVA improved clustering, provided clearer loadings, and benefited from larger data sets collected over several months. RF required larger sample numbers and while showing overlap with the PC-CVA, produced additional peaks of interest. The combination of PC-CVA and RF allowed very subtle differences between bacterial strains and growth conditions to be elucidated for the first time. Specifically, comparative analysis of an E. coli strain with and without the F-plasmid revealed changes in cyclopropanation of fatty acids, where the addition of the F-plasmid led to a reduction in cyclopropanation.

Matrix-assisted laser desorption/ionization mass spectrometry imaging for quorum sensing

Quorum sensing (QS) is a complex communication system in bacteria, directing their response to the environment. QS is also one of the main regulators of bacterial biofilms' formation, maturation and dispersion. Matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) is a molecular imaging technique that allows the mapping of QS molecules in bacterial biofilms. Here, we highlight the latest advances in MALDI-MSI in recent years and how this technology can improve QS understanding at the molecular level.

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.

Advancements in ToF-SIMS imaging for life sciences

In the last 2 decades, Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) has gained significant prominence as a powerful imaging technique in the field of life sciences. This comprehensive review provides an in-depth overview of recent advancements in ToF-SIMS instrument technology and its applications in metabolomics, lipidomics, and single-cell analysis. We highlight the use of ToF-SIMS imaging for studying lipid distribution, composition, and interactions in cells and tissues, and discuss its application in metabolomics, including the analysis of metabolic pathways. Furthermore, we review recent progress in single-cell analysis using ToF-SIMS, focusing on sample preparation techniques, in situ investigation for subcellular distribution of drugs, and interactions between drug molecules and biological targets. The high spatial resolution and potential for multimodal analysis of ToF-SIMS make it a promising tool for unraveling the complex molecular landscape of biological systems. We also discuss future prospects and potential advancements of ToF-SIMS in the research of life sciences, with the expectation of a significant impact in the field.

Secondary ion mass spectrometry for bone research

The purpose of this Tutorial is to highlight the suitability of time-of-flight secondary ion mass spectrometry (ToF-SIMS) and OrbiTrap™ SIMS (Orbi-SIMS) in bone research by introducing fundamentals and best practices of bone analysis with these mass spectrometric imaging (MSI) techniques. The Tutorial includes sample preparation, determination of best-suited measurement settings, data acquisition, and data evaluation, as well as a brief overview of SIMS applications in bone research in the current literature. SIMS is a powerful analytical technique that allows simultaneous analysis and visualization of mineralized and nonmineralized bone tissue, bone marrow as well as implanted biomaterials, and interfaces between bone and implants. Compared to histological staining, which is the standard analytical procedure in bone research, SIMS provides chemical imaging of nonstained bone sections that offers insights beyond what is conventionally obtained. The Tutorial highlights the versatility of ToF- and Orbi-SIMS in addressing important questions in bone research. By illustrating the value of these MSI techniques, it demonstrates how they can contribute to advance progress in bone research.