Quality will determine the future of mass spectrometry imaging in clinical laboratories: the need for standardization

Hierarchical Biclustering of Mouse Pancreas Mass Spectrometry Imaging Data Using Recursive Rank-2 Non-negative Matrix Factorization

One of the main challenges in mass spectrometry imaging data analysis remains the analysis of m/z-spectra displaying a low signal-to-noise ratio caused by their low abundance, sample preparation, matrix effects, fragmentation, and other artifacts. Additionally, we observe that molecules with a high abundance suppress those with lower intensities and misdirect classical tools for MSI data analysis, such as principal component analysis. As a result, the observed significance of a molecule may not always be directly related to its abundance. In this work, we present a recursive rank-2 non-negative matrix factorization (rr2-NMF) algorithm that automatically returns spectral and spatial visualization of colocalized molecules, both highly and lowly abundant. Using this hierarchical decomposition, our method finds spatial and spectral correlations on different levels of abundances. The quality of the analysis is evaluated on MALDI-TOF data of healthy mouse pancreatic tissue for the annotation of molecules of interest in the lower abundances. The results show interesting findings regarding the functioning and colocalization of certain molecules.

Advancing personalized medicine: Integrating statistical algorithms with omics and nano-omics for enhanced diagnostic accuracy and treatment efficacy

Medical laboratory services enable precise measurement of thousands of biomolecules and have become an inseparable part of high-quality healthcare services, exerting a profound influence on global health outcomes. The integration of omics technologies into laboratory medicine has transformed healthcare, enabling personalized treatments and interventions based on individuals' distinct genetic and metabolic profiles. Interpreting laboratory data relies on reliable reference values. Presently, population-derived references are used for individuals, risking misinterpretation due to population heterogeneity, and leading to medical errors. Thus, personalized references are crucial for precise interpretation of individual laboratory results, and the interpretation of omics data should be based on individualized reference values. We reviewed recent advancements in personalized laboratory medicine, focusing on personalized omics, and discussed strategies for implementing personalized statistical approaches in omics technologies to improve global health and concluded that personalized statistical algorithms for interpretation of omics data have great potential to enhance global health. Finally, we demonstrated that the convergence of nanotechnology and omics sciences is transforming personalized laboratory medicine by providing unparalleled diagnostic precision and innovative therapeutic strategies.

Applications of spatially resolved omics in the field of endocrine tumors

Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors.

Device-Controlled Microcondensation for Spatially Confined On-Tissue Digests in MALDI Imaging of N-Glycans

On-tissue enzymatic digestion is a prerequisite for MALDI mass spectrometry imaging (MSI) and spatialomic analysis of tissue proteins and their N-glycan conjugates. Despite the more widely accepted importance of N-glycans as diagnostic and prognostic biomarkers of many diseases and their potential as pharmacodynamic markers, the crucial sample preparation step, namely on-tissue digestion with enzymes like PNGaseF, is currently mainly carried out by specialized laboratories using home-built incubation arrangements, e.g., petri dishes placed in an incubator. Standardized spatially confined enzyme digests, however, require precise control and possible regulation of humidity and temperature, as high humidity increases the risk of analyte dislocation and low humidity compromises enzyme function. Here, a digestion device that controls humidity by cyclic ventilation and heating of the slide holder and the chamber lid was designed to enable controlled micro-condensation on the slide and to stabilize and monitor the digestion process. The device presented here may help with standardization in MSI. Using sagittal mouse brain sections and xenografted human U87 glioblastoma cells in CD1 nu/nu mouse brain, a device-controlled workflow for MALDI MSI of N-glycans was developed.

Mass spectrometry as a tool to advance polymer science

In contrast to natural polymers, which have existed for billions of years, the first well-understood synthetic polymers date back to just over one century ago. Nevertheless, this relatively short period has seen vast progress in synthetic polymer chemistry, which can now afford diverse macromolecules with varying structural complexities. To keep pace with this synthetic progress, there have been commensurate developments in analytical chemistry, where mass spectrometry has emerged as the pre-eminent technique for polymer analysis. This Perspective describes present challenges associated with the mass-spectrometric analysis of synthetic polymers, in particular the desorption, ionization and structural interrogation of high-molar-mass macromolecules, as well as strategies to lower spectral complexity. We critically evaluate recent advances in technology in the context of these challenges and suggest how to push the field beyond its current limitations. In this context, the increasingly important role of high-resolution mass spectrometry is emphasized because of its unrivalled ability to describe unique species within polymer ensembles, rather than to report the average properties of the ensemble.

Egg White as a Quality Control in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI)

The strength of MALDI-MSI is to analyze and visualize spatial intensities of molecular features from an intact tissue. The distribution of the intensities can then be visualized within a single tissue section or compared in between sections, acquired consecutively. This method can be reliably used to reveal physiological structures and has the potential to identify molecular details, which correlate with biological outcomes. MALDI-MSI implementation in clinical laboratories requires the ability to ensure method quality and validation to meet diagnostic expectations. To be able to get consistent qualitative and quantitative results, standardized sample preparation and data acquisition are of highest priority. We have previously shown that the deposition of internal standards onto the tissue section during sample preparation can be used to improve the mass accuracy of monitored m/z features across the sample. Here, we present the use of external and internal controls for the quality check of sample preparation and data acquisition, which is particularly relevant when either many spectra are acquired during a single MALDI-MSI experiment or data from independent experiments are processed together. To monitor detector performance and sample preparation, we use egg white as an external control for peptide and N-glycan MALDI-MSI throughout the experiment. We have also identified endogenous peptides from cytoskeletal proteins, which can be reliably monitored in gynecological tissue samples. Lastly, we summarize our standard quality control workflow designed to produce reliable and comparable MALDI-MSI data from single sections and tissue microarrays (TMAs).