Streamlined Multimodal DESI and MALDI Mass Spectrometry Imaging on a Singular Dual-Source FT-ICR Mass Spectrometer

Fe-S cluster biosynthesis and maturation: Mass spectrometry-based methods advancing the field

Iron‑sulfur (FeS) clusters are inorganic protein cofactors that perform essential functions in many physiological processes. Spectroscopic techniques have historically been used to elucidate details of FeS cluster type, their assembly and transfer, and changes in redox and ligand binding properties. Structural probes of protein topology, complex formation, and conformational dynamics are also necessary to fully understand these FeS protein systems. Recent developments in mass spectrometry (MS) instrumentation and methods provide new tools to investigate FeS cluster and structural properties. With the unique advantage of sampling all species in a mixture, MS-based methods can be utilized as a powerful complementary approach to probe native dynamic heterogeneity, interrogate protein folding and unfolding equilibria, and provide extensive insight into protein binding partners within an entire proteome. Here, we highlight key advances in FeS protein studies made possible by MS methodology and contribute an outlook for its role in the field.

Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Applications for Metabolomics

Metabolomics is an interdisciplinary field that aims to study all metabolites < 1500 Da that are ubiquitously found within all organisms. Metabolomics is experiencing exponential growth and commonly relies on high-resolution mass spectrometry (HRMS). Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a form of HRMS that is particularly well suited for metabolomics research due to its exceptionally high resolution (105-106) and sensitivity with a mass accuracy in parts per billion (ppb). In this regard, FT-ICR-MS can provide valuable insights into the metabolomics analysis of complex biological systems due to unique capabilities such as the easy separation of isobaric and isomeric species, isotopic fine structure analysis, spatial resolution of metabolites in cells and tissues, and a high confidence (<1 ppm mass error) in metabolite identification. Alternatively, the large and complex data sets, long acquisition times, high cost, and limited access mainly through national mass spectrometry facilities may impede the routine adoption of FT-ICR-MS by metabolomics researchers. This review examines recent applications of FT-ICR-MS metabolomics in the search for clinical and non-human biomarkers; for the analysis of food, beverage, and environmental samples; and for the high-resolution imaging of tissues and other biological samples. We provide recent examples of metabolomics studies that highlight the advantages of FT-ICR-MS for the detailed and reliable characterization of the metabolome. Additionally, we offer some practical considerations for implementing FT-ICR-MS into a research program by providing a list of FT-ICR-MS facilities and by identifying different high-throughput interfaces, varieties of sample types, analysis methods (e.g., van Krevelen diagrams, Kendrick mass defect plot, etc.), and sample preparation and handling protocols used in FT-ICR-MS experiments. Overall, FT-ICR-MS holds great promise as a vital research tool for advancing metabolomics investigations.

Improved Detection of Tryptic Peptides from Tissue Sections Using Desorption Electrospray Ionization Mass Spectrometry Imaging

DESI-MSI is an ambient ionization technique used frequently for the detection of lipids, small molecules, and drug targets. Until recently, DESI had only limited use for the detection of proteins and peptides due to the setup and needs around deconvolution of data resulting in a small number of species being detected at lower spatial resolution. There are known differences in the ion species detected using DESI and MALDI for nonpeptide molecules, and here, we identify that this extends to proteomic species. DESI MS images were obtained for tissue sections of mouse and rat brain using a precommercial heated inlet (approximately 450 °C) to the mass spectrometer. Ion mobility separation resolved spectral overlap of peptide ions and significantly improved the detection of multiply charged species. The images acquired were of pixel size 100 μm (rat brain) and 50 μm (mouse brain), respectively. Observed tryptic peptides were filtered against proteomic target lists, generated by LC-MS, enabling tentative protein assignment for each peptide ion image. Precise localizations of peptide ions identified by DESI and MALDI were found to be comparable. Some spatially localized peptides ions were observed in DESI that were not found in the MALDI replicates, typically, multiply charged species with a low mass to charge ratio. This method demonstrates the potential of DESI-MSI to detect large numbers of tryptic peptides from tissue sections with enhanced spatial resolution when compared to previous DESI-MSI studies.

Advances in mass spectrometry imaging for spatial cancer metabolomics

Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.

Advances in Mass Spectrometry of Gangliosides Expressed in Brain Cancers

Gangliosides are highly abundant in the human brain where they are involved in major biological events. In brain cancers, alterations of ganglioside pattern occur, some of which being correlated with neoplastic transformation, while others with tumor proliferation. Of all techniques, mass spectrometry (MS) has proven to be one of the most effective in gangliosidomics, due to its ability to characterize heterogeneous mixtures and discover species with biomarker value. This review highlights the most significant achievements of MS in the analysis of gangliosides in human brain cancers. The first part presents the latest state of MS development in the discovery of ganglioside markers in primary brain tumors, with a particular emphasis on the ion mobility separation (IMS) MS and its contribution to the elucidation of the gangliosidome associated with aggressive tumors. The second part is focused on MS of gangliosides in brain metastases, highlighting the ability of matrix-assisted laser desorption/ionization (MALDI)-MS, microfluidics-MS and tandem MS to decipher and structurally characterize species involved in the metastatic process. In the end, several conclusions and perspectives are presented, among which the need for development of reliable software and a user-friendly structural database as a search platform in brain tumor diagnostics.

Spatial pharmacology using mass spectrometry imaging

The emerging and powerful field of spatial pharmacology can map the spatial distribution of drugs and their metabolites, as well as their effects on endogenous biomolecules including metabolites, lipids, proteins, peptides, and glycans, without the need for labeling. This is enabled by mass spectrometry imaging (MSI) that provides previously inaccessible information in diverse phases of drug discovery and development. We provide a perspective on how MSI technologies and computational tools can be implemented to reveal quantitative spatial drug pharmacokinetics and toxicology, tissue subtyping, and associated biomarkers. We also highlight the emerging potential of comprehensive spatial pharmacology through integration of multimodal MSI data with other spatial technologies. Finally, we describe how to overcome challenges including improving reproducibility and compound annotation to generate robust conclusions that will improve drug discovery and development processes.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Optimization of Mass Spectrometry Imaging for Drug Metabolism and Distribution Studies in the Zebrafish Larvae Model: A Case Study with the Opioid Antagonist Naloxone

Zebrafish (ZF; Danio rerio) larvae have emerged as a promising in vivo model in drug metabolism studies. Here, we set out to ready this model for integrated mass spectrometry imaging (MSI) to comprehensively study the spatial distribution of drugs and their metabolites inside ZF larvae. In our pilot study with the overall goal to improve MSI protocols for ZF larvae, we investigated the metabolism of the opioid antagonist naloxone. We confirmed that the metabolic modification of naloxone is in high accordance with metabolites detected in HepaRG cells, human biosamples, and other in vivo models. In particular, all three major human metabolites were detected at high abundance in the ZF larvae model. Next, the in vivo distribution of naloxone was investigated in three body sections of ZF larvae using LC-HRMS/MS showing that the opioid antagonist is mainly present in the head and body sections, as suspected from published human pharmacological data. Having optimized sample preparation procedures for MSI (i.e., embedding layer composition, cryosectioning, and matrix composition and spraying), we were able to record MS images of naloxone and its metabolites in ZF larvae, providing highly informative distributional images. In conclusion, we demonstrate that all major ADMET (absorption, distribution, metabolism, excretion, and toxicity) parameters, as part of in vivo pharmacokinetic studies, can be assessed in a simple and cost-effective ZF larvae model. Our established protocols for ZF larvae using naloxone are broadly applicable, particularly for MSI sample preparation, to various types of compounds, and they will help to predict and understand human metabolism and pharmacokinetics.

Spatially resolved metabolomics combined with bioactivity analyses to evaluate the pharmacological properties of two Radix Puerariae species

ETHNOPHARMACOLOGICAL RELEVANCE

P. lobata and P. thomsonii are medicinal plants with similar pharmacological functions but different therapeutic effects. A novel method is presented herein to investigate metabolites in terms of their distribution and qualification, quantification is necessary to elucidate the different therapeutic effects of the two Puerariae species.

AIM OF THE STUDY

The aim of the present study was to perform spatially resolved metabolomics combined with bioactivity analyses to systematically compare the metabolite differences in P. lobata and P. thomsonii by distribution, qualification, quantification, and biological activity to evaluate their pharmacological properties.

MATERIALS AND METHODS

Air flow-assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI) was performed to characterize the differences in the metabolite distributions of P. lobata and P. thomsonii. Further qualitative and quantitative analyses of the differential metabolites were performed using liquid chromatography-mass spectrometry (LC-MS). Biological activities correlated with the differences in the metabolites were validated by MTT assays.

RESULTS

Some metabolites showed complementary distributions of the phloem and xylem in the two species, saccharide, vitamin, and inosine levels were higher in the phloem of P. thomsonii but higher in the xylem of P. lobata. The 3'-hydroxyl puerarin level was higher in the xylem of P. thomsonii but higher in the phloem of P. lobata. Qualitative and quantitative analyses of the metabolites revealed a total of 52 key differential metabolites. MTT assays showed that daidzein, daidzin, puerarin, ononin, genistin, formononetin, 3'-hydroxy puerarin, 3'-methoxy puerarin, mirificin, and 3'-methoxy daidzin exerted protective effects on H9c2 cells against hypoxia/reoxygenation injury. P. lobata extracts exhibited a significantly better protective efficacy than P. thomsonii extracts.

CONCLUSIONS

In this study, AFADESI-MSI combined with LC-MS and biological activities comprehensively elucidated metabolite differences in the distribution, qualification, quantification, and pharmacological properties of P. lobata and P. thomsonii. The results of this study could provide a novel strategy for species identification and quality assessment of similar Chinese herbal medicines.

Advances in methods to analyse cardiolipin and their clinical applications

Cardiolipin (CL) is a mitochondria-exclusive phospholipid, primarily localised within the inner mitochondrial membrane, that plays an essential role in mitochondrial architecture and function. Aberrant CL content, structure, and localisation have all been linked to impaired mitochondrial activity and are observed in the pathophysiology of cancer and neurological, cardiovascular, and metabolic disorders. The detection, quantification, and localisation of CL species is a valuable tool to investigate mitochondrial dysfunction and the pathophysiological mechanisms underpinning several human disorders. CL is measured using liquid chromatography, usually combined with mass spectrometry, mass spectrometry imaging, shotgun lipidomics, ion mobility spectrometry, fluorometry, and radiolabelling. This review summarises available methods to analyse CL, with a particular focus on modern mass spectrometry, and evaluates their advantages and limitations. We provide guidance aimed at selecting the most appropriate technique, or combination of techniques, when analysing CL in different model systems, and highlight the clinical contexts in which measuring CL is relevant.

Image to insight: exploring natural products through mass spectrometry imaging

Covering: 2017 to 2022Mass spectrometry imaging (MSI) has become a mature molecular imaging technique that is well-matched for natural product (NP) discovery. Here we present a brief overview of MSI, followed by a thorough discussion of different MSI applications in NP research. This review will mainly focus on the recent progress of MSI in plants and microorganisms as they are the main producers of NPs. Specifically, the opportunity and potential of combining MSI with other imaging modalities and stable isotope labeling are discussed. Throughout, we focus on both the strengths and weaknesses of MSI, with an eye on future improvements that are necessary for the progression of MSI toward routine NP studies. Finally, we discuss new areas of research, future perspectives, and the overall direction that the field may take in the years to come.

Advances in ionisation techniques for mass spectrometry-based omics research

Omics analysis by mass spectrometry (MS) is a vast field, with proteomics, metabolomics and lipidomics dominating recent research by exploiting biological MS ionisation techniques. Traditional MS ionisation techniques such as electrospray ionisation have limitations in analyte-specific sensitivity, modes of sampling and throughput, leading to many researchers investigating new ionisation methods for omics research. In this review, we examine the current landscape of these new ionisation techniques, divided into the three groups of (electro)spray-based, laser-based and other miscellaneous ionisation techniques. Due to the wide range of new developments, this review can only provide a starting point for further reading on each ionisation technique, as each have unique benefits, often for specialised applications, which promise beneficial results for different areas in the omics world.

Build, Share and Remix: 3D Printing for Speeding Up the Innovation Cycles in Ambient Ionisation Mass Spectrometry (AIMS)

Ambient ionisation mass spectrometry (AIMS) enables studying biological systems in their native state and direct high-throughput analyses. The ionisation occurs in the physical conditions of the surrounding environment. Simple spray or plasma-based AIMS devices allow the desorption and ionisation of molecules from solid, liquid and gaseous samples. 3D printing helps to implement new ideas and concepts in AIMS quickly. Here, we present examples of 3D printed AIMS sources and devices for ion transfer and manipulation. Further, we show the use of 3D printer parts for building custom AIMS sampling robots and imaging systems. Using 3D printing technology allows upgrading existing mass spectrometers with relatively low cost and effort.

Method To Visualize the Intratumor Distribution and Impact of Gemcitabine in Pancreatic Ductal Adenocarcinoma by Multimodal Imaging

Gemcitabine (dFdC) is a common treatment for pancreatic cancer; however, it is thought that treatment may fail because tumor stroma prevents drug distribution to tumor cells. Gemcitabine is a pro-drug with active metabolites generated intracellularly; therefore, visualizing the distribution of parent drug as well as its metabolites is important. A multimodal imaging approach was developed using spatially coregistered mass spectrometry imaging (MSI), imaging mass cytometry (IMC), multiplex immunofluorescence microscopy (mIF), and hematoxylin and eosin (H&E) staining to assess the local distribution and metabolism of gemcitabine in tumors from a genetically engineered mouse model of pancreatic cancer (KPC) allowing for comparisons between effects in the tumor tissue and its microenvironment. Mass spectrometry imaging (MSI) enabled the visualization of the distribution of gemcitabine (100 mg/kg), its phosphorylated metabolites dFdCMP, dFdCDP and dFdCTP, and the inactive metabolite dFdU. Distribution was compared to small-molecule ATR inhibitor AZD6738 (25 mg/kg), which was codosed. Gemcitabine metabolites showed heterogeneous distribution within the tumor, which was different from the parent compound. The highest abundance of dFdCMP, dFdCDP, and dFdCTP correlated with distribution of endogenous AMP, ADP, and ATP in viable tumor cell regions, showing that gemcitabine active metabolites are reaching the tumor cell compartment, while AZD6738 was located to nonviable tumor regions. The method revealed that the generation of active, phosphorylated dFdC metabolites as well as treatment-induced DNA damage primarily correlated with sites of high proliferation in KPC PDAC tumor tissue, rather than sites of high parent drug abundance.

Spatially Mapping the Baseline and Bisphenol-A Exposed Daphnia magna Lipidome Using Desorption Electrospray Ionization-Mass Spectrometry

Untargeted lipidomics has previously been applied to the study of daphnids and the discovery of biomarkers that are indicative of toxicity. Typically, liquid chromatography—mass spectrometry is used to measure the changes in lipid abundance in whole-body homogenates of daphnids, each only ca. 3 mm in length which limits any biochemical interpretation of site-specific toxicity. Here, we applied mass spectrometry imaging of Daphnia magna to combine untargeted lipidomics with spatial resolution to map the molecular perturbations to defined anatomical regions. A desorption electrospray ionization—mass spectrometry (DESI-MS) method was optimized and applied to tissue sections of daphnids exposed to bisphenol-A (BPA) compared to unexposed controls, generating an untargeted mass spectrum at each pixel (35 µm²/pixel) within each section. First, unique lipid profiles from distinct tissue types were identified in whole-body daphnids using principal component analysis, specifically distinguishing appendages, eggs, eye, and gut. Second, changes in the lipidome were mapped over four stages of normal egg development and then the effect of BPA exposure on the egg lipidome was characterized. The primary perturbations to the lipidome were annotated as triacylglycerides and phosphatidylcholine, and the distributions of the individual lipid species within these classes were visualized in whole-body D. magna sections as ion images. Using an optimized DESI-MS workflow, the first ion images of D. magna tissue sections were generated, mapping both their baseline and BPA-perturbed lipidomes.

Developing mass spectrometry for the quantitative analysis of neuropeptides

INTRODUCTION

Neuropeptides are signaling molecules originating in the neuroendocrine system that can act as neurotransmitters and hormones in many biochemical processes. Their exact function is difficult to characterize, however, due to dependence on concentration, post-translational modifications, and the presence of other comodulating neuropeptides. Mass spectrometry enables sensitive, accurate, and global peptidomic analyses that can profile neuropeptide expression changes to understand their roles in many biological problems, such as neurodegenerative disorders and metabolic function.

AREAS COVERED

We provide a brief overview of the fundamentals of neuropeptidomic research, limitations of existing methods, and recent progress in the field. This review is focused on developments in mass spectrometry and encompasses labeling strategies, post-translational modification analysis, mass spectrometry imaging, and integrated multi-omic workflows, with discussion emphasizing quantitative advancements.

EXPERT OPINION

Neuropeptidomics is critical for future clinical research with impacts in biomarker discovery, receptor identification, and drug design. While advancements are being made to improve sensitivity and accuracy, there is still room for improvement. Better quantitative strategies are required for clinical analyses, and these methods also need to be amenable to mass spectrometry imaging, post-translational modification analysis, and multi-omics to facilitate understanding and future treatment of many diseases.