In recent years, mass spectrometry (MS) has been applied to clinical microbial biotyping, exploiting the speed of matrix-assisted laser desorption/ionization (MALDI) in recording microbe-specific MS profiles. More recently, liquid atmospheric pressure (AP) MALDI has been shown to produce extremely stable ion flux from homogenous samples and ‘electrospray ionization (ESI)-like’ multiply charged ions for larger biomolecules, whilst maintaining the benefits of traditional MALDI including high tolerance to contaminants, low analyte consumption and rapid analysis. These and other advantages of liquid AP-MALDI MS have been explored in this study to investigate its potential in microbial biotyping.
Genetically diverse bacterial strains were analyzed using liquid AP-MALDI MS, including clinically relevant species such as Escherichia coli, Staphylococcus aureus and Klebsiella pneumoniae. Bacterial cultures were subjected to a simple and fast extraction protocol using ethanol and formic acid. Extracts were spotted with a liquid support matrix (LSM) and analyzed using a Synapt G2-Si mass spectrometer with an in-house built AP-MALDI source.
Each species produces a unique lipid profile in the m/z range of 400–1100, allowing species discrimination. Traditional (solid) MALDI MS produced spectra containing a high abundance of matrix-related clusters and an absence of lipid peaks. The MS profiles of the bacterial species tested form distinct clusters using principle component analysis (PCA) with a classification accuracy of 98.63% using a PCA-based prediction model.
Liquid AP-MALDI MS profiles can be sufficient to distinguish clinically relevant bacterial pathogens and other bacteria, based on their unique lipid profiles. The analysis of the lipid MS profiles is typically excluded from commercial instruments approved for clinical diagnostics.
Mass spectrometry (MS) is the workhorse of metabolomics, proteomics and lipidomics. Mass spectrometry imaging (MSI), its extension to spatially resolved analysis of tissues, is a powerful tool for visualizing molecular information within the histological context of tissue. This review summarizes recent developments in MSI and highlights current challenges that remain to achieve molecular imaging at the cellular level of clinical specimens. We focus on matrix-assisted laser desorption/ionization (MALDI)-MSI. We discuss the current status of each of the analysis steps and remaining challenges to reach the desired level of cellular imaging. Currently, analyte delocalization and degradation, matrix crystal size, laser focus restrictions and detector sensitivity are factors that are limiting spatial resolution. New sample preparation devices and laser optic systems are being developed to push the boundaries of these limitations. Furthermore, we review the processing of cellular MSI data and images, and the systematic integration of these data in the light of available algorithms and databases. We discuss roadblocks in the data analysis pipeline and show how technology from other fields can be used to overcome these. Finally, we conclude with curative and community efforts that are needed to enable contextualization of the information obtained.
Common traumas to the skeletal system are bone fractures and injury-related articular cartilage damage. The healing process can be impaired resulting in non-unions in 5–10% of the bone fractures and in post-traumatic osteoarthritis (PTOA) in up to 75% of the cases of cartilage damage. Despite the amount of research performed in the areas of fracture healing and cartilage repair as well as non-unions and PTOA, still, the outcome of a bone fracture or articular cartilage damage cannot be predicted. Here, we discuss known risk factors and key molecules involved in the repair process, together with the main challenges associated with the prediction of outcome of these injuries. Furthermore, we review and discuss the opportunities for mass spectrometry (MS) – an analytical tool capable of detecting a wide variety of molecules in tissues – to contribute to extending molecular understanding of impaired healing and the discovery of predictive biomarkers. Therefore, the current knowledge and challenges concerning MS imaging of bone and cartilage tissue as well as in vivo MS are discussed. Finally, we explore the possibilities of in situ, real-time MS for the prediction of outcome during surgery of bone fractures and injury-related articular cartilage damage.