In Vitro Liquid Extraction Surface Analysis Mass Spectrometry (ivLESA-MS) for Direct Metabolic Analysis of Adherent Cells in Culture

Modern machine-learning applications in ambient ionization mass spectrometry

This article provides a comprehensive overview of the applications of methods of machine learning (ML) and artificial intelligence (AI) in ambient ionization mass spectrometry (AIMS). AIMS has emerged as a powerful analytical tool in recent years, allowing for rapid and sensitive analysis of various samples without the need for extensive sample preparation. The integration of ML/AI algorithms with AIMS has further expanded its capabilities, enabling enhanced data analysis. This review discusses ML/AI algorithms applicable to the AIMS data and highlights the key advancements and potential benefits of utilizing ML/AI in the field of mass spectrometry, with a focus on the AIMS community.

Deeper Understanding of Solvent-Based Ambient Ionization Mass Spectrometry: Are Molecular Profiles Primarily Dictated by Extraction Mechanisms?

Solvent-based ambient ionization mass spectrometry (MS) techniques provide a powerful approach for direct chemical analysis and molecular profiling of biological tissues. While molecular profiling of tissues has been widely used for disease diagnosis, little is understood about how the interplay among solvent properties, matrix effects, and ion suppression can influence the detection of biological molecules. Here, we perform a systematic investigation of the extraction processes of lipids using an ambient ionization droplet microsampling platform to investigate how the physicochemical properties of the solvent systems and extraction time influence molecular extraction and detection. Direct molecular profiling and quantitative liquid chromatography-mass spectrometry (LC-MS) of discrete solvent droplets after surface sampling were investigated to provide insights into extraction and ionization mechanisms. The results of this study suggest that intermolecular interactions such as hydrogen bonding play a major role in extraction and detection of lipids using solvent-based ambient ionization techniques. In addition, extraction time was observed to impact the molecular profiles obtained, suggesting optimization of this parameter can be performed to favor detection of specific analytes.

Rapid identification of bear bile powder from other bile sources using chip-based nano-electrospray ionization tandem mass spectrometry

RATIONALE

Bear bile powder (BBP) is a widely used traditional Chinese medicine (TCM), and bile acids (BAs) are the main active components in BBP. Due to the scarcity of BBP resources, adulterations often occur in the market. Conventional methods to distinguish them are usually complicated and time-consuming. To enhance effectiveness and accuracy, a rapid and rough analytical method is desperately needed.

METHODS

In this study, a rapid strategy using chip-based nano-electrospray ionization tandem mass spectrometry (nano-ESI-MS/MS) was established to distinguish BBP from other sources of bile powder (BP). In addition, the results were further verified by ultra-high-performance liquid chromatography combined with high-resolution mass spectrometry (UPLC/MS).

RESULTS

The precision of the chip-based nano-ESI-MS/MS method was validated to be acceptable with relative standard deviation (RSD) <15%. The distinction between BBP and other sources of BP, including common adulterants of pig bile powder (PBP), cattle bile powder (CBP), sheep bile powder (SBP), and chicken bile powder (CkBP), can be observed in the spectra. By using orthogonal partial least-squares discriminant analysis (OPLS-DA), more potential m/z markers were investigated. A BAs-related m/z marker of 498.3 was discovered as a typical differential molecular ion peak and was identified as tauroursodeoxycholic acid (TUDCA) and taurochenodeoxycholic acid (TCDCA) in BBP.

CONCLUSIONS

The proposed strategy has simple sample pretreatment steps and significantly shortened analysis time. As an emerging technology, chip-based nano-ESI-MS not only provides a reference for the rapid distinction of adulterated Chinese medicines, but also provides some insights into the identification of other chemicals and foods.

Interim clinical trial analysis of intraoperative mass spectrometry for breast cancer surgery

Optimal resection of breast tumors requires removing cancer with a rim of normal tissue while preserving uninvolved regions of the breast. Surgical and pathological techniques that permit rapid molecular characterization of tissue could facilitate such resections. Mass spectrometry (MS) is increasingly used in the research setting to detect and classify tumors and has the potential to detect cancer at surgical margins. Here, we describe the ex vivo intraoperative clinical application of MS using a liquid micro-junction surface sample probe (LMJ-SSP) to assess breast cancer margins. In a midpoint analysis of a registered clinical trial, surgical specimens from 21 women with treatment naïve invasive breast cancer were prospectively collected and analyzed at the time of surgery with subsequent histopathological determination. Normal and tumor breast specimens from the lumpectomy resected by the surgeon were smeared onto glass slides for rapid analysis. Lipidomic profiles were acquired from these specimens using LMJ-SSP MS in negative ionization mode within the operating suite and post-surgery analysis of the data revealed five candidate ions separating tumor from healthy tissue in this limited dataset. More data is required before considering the ions as candidate markers. Here, we present an application of ambient MS within the operating room to analyze breast cancer tissue and surgical margins. Lessons learned from these initial promising studies are being used to further evaluate the five candidate biomarkers and to further refine and optimize intraoperative MS as a tool for surgical guidance in breast cancer.

Direct Liquid Extraction and Ionization Techniques for Understanding Multimolecular Environments in Biological Systems (Secondary Publication)

A combination of direct liquid extraction using a small volume of solvent and electrospray ionization allows the rapid measurement of complex chemical components in biological samples and visualization of their distribution in tissue sections. This review describes the development of such techniques and their application to biological research since the first reports in the early 2000s. An overview of electrospray ionization, ion suppression in samples, and the acceleration of specific chemical reactions in charged droplets is also presented. Potential future applications for visualizing multimolecular environments in biological systems are discussed.

Sequential Orbitrap Secondary Ion Mass Spectrometry and Liquid Extraction Surface Analysis-Tandem Mass Spectrometry-Based Metabolomics for Prediction of Brain Tumor Relapse from Sample-Limited Primary Tissue Archives

We present here a novel surface mass spectrometry strategy to perform untargeted metabolite profiling of formalin-fixed paraffin-embedded pediatric ependymoma archives. Sequential Orbitrap secondary ion mass spectrometry (3D OrbiSIMS) and liquid extraction surface analysis-tandem mass spectrometry (LESA-MS/MS) permitted the detection of 887 metabolites (163 chemical classes) from pediatric ependymoma tumor tissue microarrays (diameter: <1 mm; thickness: 4 μm). From these 163 classes, 60 classes were detected with both techniques, whilst LESA-MS/MS and 3D OrbiSIMS individually allowed the detection of another 83 and 20 unique metabolite classes, respectively. Through data fusion and multivariate analysis, we were able to identify key metabolites and corresponding pathways predictive of tumor relapse, which were retrospectively confirmed by gene expression analysis with publicly available data. Altogether, this sequential mass spectrometry strategy has shown to be a versatile tool to perform high-throughput metabolite profiling on sample-limited tissue archives.

Spatially Resolved Mass Spectrometry at the Single Cell: Recent Innovations in Proteomics and Metabolomics

Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.

Considerations for using isolated cell systems to understand cardiac metabolism and biology

Changes in myocardial metabolic activity are fundamentally linked to cardiac health and remodeling. Primary cardiomyocytes, induced pluripotent stem cell-derived cardiomyocytes, and transformed cardiomyocyte cell lines are common models used to understand how (patho)physiological conditions or stimuli contribute to changes in cardiac metabolism. These cell models are helpful also for defining metabolic mechanisms of cardiac dysfunction and remodeling. Although technical advances have improved our capacity to measure cardiomyocyte metabolism, there is often heterogeneity in metabolic assay protocols and cell models, which could hinder data interpretation and discernment of the mechanisms of cardiac (patho)physiology. In this review, we discuss considerations for integrating cardiomyocyte cell models with techniques that have become relatively common in the field, such as respirometry and extracellular flux analysis. Furthermore, we provide overviews of metabolic assays that complement XF analyses and that provide information on not only catabolic pathway activity, but biosynthetic pathway activity and redox status as well. Cultivating a more widespread understanding of the advantages and limitations of metabolic measurements in cardiomyocyte cell models will continue to be essential for the development of coherent metabolic mechanisms of cardiac health and pathophysiology.

Mapping chemotherapeutic drug distribution in cancer cell spheroids using 2D-TOF-SIMS and LESA-TIMS-MS

Three-dimensional (3D) cancer cell cultures grown in the form of spheroids are effective models for the study of in vivo-like processes simulating cancer tumor pharmacological dynamics and morphology. In this study, we show the advantages of Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS) combined with in situ Liquid Extraction Surface Analysis coupled to trapped Ion Mobility Spectrometry Mass Spectrometry (LESA-TIMS-TOF MS) for high spatial resolution mapping and quantitation of ABT-737, a chemotherapeutic drug, at the level of single human colon carcinoma cell spheroids (HCT 116 MCS). 2D-TOF-SIMS studies of consecutive sections (∼16 μm thick slices) showed that ABT-737 is homogenously distributed in the outer layers of the HCT 116 MCS. Complementary in situ LESA-TIMS-TOF MS/MS measurements confirmed the presence of the ABT-737 drug in the MCS slides by the observation of the molecular ion [M + H]+m/z and mobility, and the charateristic fragmentation pattern. LESA-TIMS-TOF MS allowed a quantitative assessment of the ABT-737 drug of the control MCS slice spiked with ABT-737 standard over the 0.4-4.1 ng range and MCS treated starting at 10 μM for 24 h. These experiments showcase an effective protocol for unambigous characterization and 3D mapping of chemotherapeutic drug distribution at the single MCS level.

Analytical challenges of shotgun lipidomics at different resolution of measurements

The essence of shotgun lipidomics is to maintain consistency of the chemical environment of lipid samples during mass spectrometry acquisition. This strategy is suitable for large-scale quantitative analysis. This strategy also allows sufficient time to collect data to improve the signal-to-noise ratio. The initial approach of shotgun lipidomics was the electrospray ionization (ESI)-based direct infusion mass spectrometry strategy. With development of mass spectrometry for small molecules, shotgun lipidomics methods have been extended to matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) and ambient mass spectrometry, including MS imaging methods. Furthermore, the object of analysis has extended from organ and body fluid levels to tissue and cell levels with technological developments. In this article, we summarize the status and technical challenges of shotgun lipidomics at different resolution of measurements from the mass spectrometry perspective.

Dynamic secretome of bone marrow-derived stromal cells reveals a cardioprotective biochemical cocktail

Transplanted stromal cells have demonstrated considerable promise as therapeutic agents in diverse disease settings. Paracrine signaling can be an important mediator of these therapeutic effects at the sites of acute or persistent injury and inflammation. As many stromal cell types, including bone marrow-derived stromal cells (BMSCs), display tissue-specific responses, there is a need to explore their secretory dynamics in the context of tissue and injury type. Paracrine signals are not static, and could encode contextual dynamics in the kinetic changes of the concentrations of the secreted ligands. However, precise measurement of dynamic and context-specific cellular secretory signatures, particularly in adherent cells, remains challenging. Here, by creating an experimental and computational analysis platform, we reconstructed dynamic secretory signatures of cells based on a very limited number of time points. By using this approach, we demonstrate that the secretory signatures of CD133-positive BMSCs are uniquely defined by distinct biological contexts, including signals from injured cardiac cells undergoing oxidative stress, characteristic of cardiac infarction. Furthermore, we show that the mixture of recombinant factors reproducing the dynamics of BMSC-generated secretion can mediate a highly effective rescue of cells injured by oxidative stress and an improved cardiac output. These results support the importance of the dynamic multifactorial paracrine signals in mediating remedial effects of stromal stem cells, and pave the way for stem cell-inspired cell-free treatments of cardiac and other injuries.

Molecular Characterization of Prostate Cancer with Associated Gleason Score Using Mass Spectrometry Imaging

Diagnosis of prostate cancer is based on histologic evaluation of tumor architecture using a system known as the "Gleason score." This diagnostic paradigm, while the standard of care, is time-consuming, shows intraobserver variability, and provides no information about the altered metabolic pathways, which result in altered tissue architecture. Characterization of the molecular composition of prostate cancer and how it changes with respect to the Gleason score (GS) could enable a more objective and faster diagnosis. It may also aid in our understanding of disease onset and progression. In this work, we present mass spectrometry imaging for identification and mapping of lipids and metabolites in prostate tissue from patients with known prostate cancer with GS from 6 to 9. A gradient of changes in the intensity of various lipids was observed, which correlated with increasing GS. Interestingly, these changes were identified in both regions of high tumor cell density, and in regions of tissue that appeared histologically benign, possibly suggestive of precancerous metabolomic changes. A total of 31 lipids, including several phosphatidylcholines, phosphatidic acids, phosphatidylserines, phosphatidylinositols, and cardiolipins were detected with higher intensity in GS (4+3) compared with GS (3+4), suggesting they may be markers of prostate cancer aggression. Results obtained through mass spectrometry imaging studies were subsequently correlated with a fast, ambient mass spectrometry method for potential use as a clinical tool to support image-guided prostate biopsy. IMPLICATIONS: In this study, we suggest that metabolomic differences between prostate cancers with different Gleason scores can be detected by mass spectrometry imaging.