Discriminant Principal Component Analysis of ToF-SIMS Spectra for Deciphering Compositional Differences of MSC-Secreted Extracellular Matrices

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.

Mass Spectrometry Imaging of Organoids to Improve Preclinical Research

Preclinical models are essential research tools before novel therapeutic or diagnostic methods can be applied to humans. These range from in vitro cell monocultures to vastly more complex animal models, but clinical translation to humans often fails to deliver significant results. Three-dimensional (3D) organoid systems are being increasingly studied to establish physiologically relevant in vitro platforms in a trade-off between the complexity of the research question and the complexity of practical experimental setups. The sensitivity and precision of analytical tools are yet another limiting factors in what can be investigated, and mass spectrometry (MS) is one of the most powerful analytical techniques available to the scientific community. Its innovative use to spatially resolve biological samples has opened many research avenues in the field of MS imaging (MSI). Here, this work aims to explore the current scientific landscape in the application of MSI on organoids, with an emphasis on their combined potential to facilitate and improve preclinical studies.

Macromolecular crowding in human tenocyte and skin fibroblast cultures: A comparative analysis

Although human tenocytes and dermal fibroblasts have shown promise in tendon engineering, no tissue engineered medicine has been developed due to the prolonged ex vivo time required to develop an implantable device. Considering that macromolecular crowding has the potential to substantially accelerate the development of functional tissue facsimiles, herein we compared human tenocyte and dermal fibroblast behaviour under standard and macromolecular crowding conditions to inform future studies in tendon engineering. Basic cell function analysis made apparent the innocuousness of macromolecular crowding for both cell types. Gene expression analysis of the without macromolecular crowding groups revealed expression of tendon related molecules in human dermal fibroblasts and tenocytes. Protein electrophoresis and immunocytochemistry analyses showed significantly increased and similar deposition of collagen fibres by macromolecular crowding in the two cell types. Proteomics analysis demonstrated great similarities between human tenocyte and dermal fibroblast cultures, as well as the induction of haemostatic, anti-microbial and tissue-protective proteins by macromolecular crowding in both cell populations. Collectively, these data rationalise the use of either human dermal fibroblasts or tenocytes in combination with macromolecular crowding in tendon engineering.

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.