Single cell lipidomics of SKBR-3 breast cancer cells by using time-of-flight secondary-ion mass spectrometry

Development and application of lipidomics for food research

Lipidomics is an emerging and promising omics derived from metabolomics to comprehensively analyze all of lipid molecules in biological matrices. The purpose of this chapter is to introduce the development and application of lipidomics for food research. First, three aspects of sample preparation are introduced: food sampling, lipid extraction, and transportation and storage. Second, five types of instruments for data acquisition are summarized: direct infusion-mass spectrometry (MS), chromatographic separation-MS, ion mobility-MS, MS imaging, and nuclear magnetic resonance spectroscopy. Third, data acquisition and analysis software are described for the lipidomics software development. Fourth, the application of lipidomics for food research is discussed such as food origin and adulteration analysis, food processing research, food preservation research, and food nutrition and health research. All the contents suggest that lipidomics is a powerful tool for food research based on its ability of lipid component profile analysis.

Mass spectrometry-based strategies for single-cell metabolomics

Single cell analysis has drawn increasing interest from the research community due to its capability to interrogate cellular heterogeneity, allowing refined tissue classification and facilitating novel biomarker discovery. With the advancement of relevant instruments and techniques, it is now possible to perform multiple omics including genomics, transcriptomics, metabolomics or even proteomics at single cell level. In comparison with other omics studies, single-cell metabolomics (SCM) represents a significant challenge since it involves many types of dynamically changing compounds with a wide range of concentrations. In addition, metabolites cannot be amplified. Although difficult, considerable progress has been made over the past decade in mass spectrometry (MS)-based SCM in terms of processing technologies and biochemical applications. In this review, we will summarize recent progress in the development of promising MS platforms, sample preparation methods and SCM analysis of various cell types (including plant cell, cancer cell, neuron, embryo cell, and yeast cell). Current limitations and future research directions in the field of SCM will also be discussed.

Chiral Analysis of Lactate during Direct Contact Coculture by Single-Cell On-Probe Enzymatic Dehydrogenation Derivatization: Unraveling Metabolic Changes Caused by d-Lactate

In vitro noncontact cell-based coculture models are frequently employed to study cell-to-cell communication. However, these models cannot accurately represent the complexity of in vivo signaling. d-Lactate is an unusual metabolite produced and released by cancer cells. The characterization of d-lactate is challenging as it shares the same mass but has much lower amounts compared with l-lactate. Herein, d-α-hydroxy acids were specifically recognized and dehydrogenated by d-α-hydroxy acid dehydrogenase. The dehydrogenation products were rapidly quaternized for enhancement of mass signals. An on-probe enzymatic dehydrogenation-derivatization method was proposed for chiral analysis of α-hydroxy acids at the single-cell level. It is a promising amplification methodology and affords over 3 orders of magnitude signal enhancement. Furthermore, direct contact coculture models were used to precisely mimic the tumor microenvironment and explore the communication between cancer and normal cells. Single-cell mass spectrometry (SCMS) was further applied to easily sample cell extracts and study the differences of the aspects of small molecule metabolism in cocultured cells. On the basis of direct contact coculture SCMS, several differential small molecule metabolites and differences of oxidative stress between cocultured and monocultured normal cells were successfully detected. Additionally, d-lactate was discovered as a valuable differential metabolite with application of the two developed methods. It may account for the cancer-associated metabolic behavior of normal cells. These changes could be relieved after d-lactate metabolism-related drug treatment. This discovery may promote the investigation of d-lactate metabolism, which may provide a novel direction for cancer therapy.

Single-Cell On-Probe Derivatization-Noncontact Nanocarbon Fiber Ionization: Unraveling Cellular Heterogeneity of Fatty Alcohol and Sterol Metabolites

Currently in single-cell mass spectrometry, the analysis of low-abundance cell metabolites such as fatty alcohols and sterols remains a challenge. In most research studies, single-cell samples are analyzed directly after sampling. However, this workflow may exclude many effective sample pretreatment methods such as derivatization for the improvement of detection sensitivity for specific cell metabolites in a single-cell sample. Metabolites in low abundance in a cell may not be detected. Herein on-probe derivatization coupled with noncontact nanocarbon fiber ionization is proposed for sensitive fatty alcohol and sterol metabolite analysis at the single-cell level. Fatty alcohol and sterol metabolites were rapidly quaternized by the single-cell on-probe derivatization method. The reaction products were directly ionized with no postreaction processing. Furthermore, a new ionization source for noncontact nanocarbon fiber ionization was developed to show good compatibility with dichloromethane, a low-polarity solvent used in on-probe derivatization. The quaternized fatty alcohols and sterols exhibited evidently enhanced ionization efficiency in mass spectra. In applications of the developed method, seven kinds of even-numbered-carbon fatty alcohols (C₁₂-C₂₂) and five kinds of sterols were detected in single L-02 and HepG2 cells. Then the L-02 and HepG2 cells were readily discriminated through principal component analysis. Additionally, a rough quantitative analysis of the detected fatty alcohols and sterols in single cells was performed. The mass intensities of fatty alcohols show a significant difference between L-02 and HepG2 cells while those of sterols remain stable.

Analysis of Lipids in Single Cells and Organelles Using Nanomanipulation-Coupled Mass Spectrometry

The ability to discriminately analyze the chemical constituents of single cells and organelles is highly sought after and necessary to establish true biomarkers. Some major challenges of individual cell analysis include requirement and expenditure of a large sample of cells as well as extensive extraction and separation techniques. Here, we describe methods to perform individual cell and organelle extractions of both tissues and cells in vitro using nanomanipulation coupled to mass spectrometry. Lipid profiles display heterogeneity from extracted adipocytes and lipid droplets, demonstrating the necessity for single cell analysis. The application of these techniques can be applied to other cell and organelle types for selective and thorough monitoring of disease progression and biomarker discovery.

TOF-SIMS analysis of an isocitrate dehydrogenase 1 mutation-associated oncometabolite in cancer cells

The development of analytical tools for accurate and sensitive detection of intracellular metabolites associated with mutated metabolic enzymes is important in cancer diagnosis and staging. The gene encoding the metabolic enzyme isocitrate dehydrogenase 1 (IDH1) is mutated in various cancers, and mutant IDH1 could represent a good biomarker and potent target for cancer therapy. Owing to a mutation in an important arginine residue in the catalytic pocket, mutant IDH1 catalyzes the production of 2-hydroxyglutarate (2-HG) instead of its wild type product α-ketoglutarate (α-KG), which is involved in multiple cellular pathways involving the hydroxylation of proteins, ribonucleic acid, and deoxyribose nucleic acid (DNA). Since 2-HG is an α-KG antagonist, inhibiting normal α-KG-dependent metabolism, high intracellular levels of 2-HG result in abnormal histone and DNA methylation. Therefore, accurate and sensitive analytical tools for the direct detection of 2-HG in cancer cells expressing mutant IDH1 would benefit this field, as it would minimize the need both for complicated experimental procedures and for large amounts of biological samples. Here, the authors describe a useful analytical method for the direct detection of 2-HG in lysates from a mutant IDH1-expressing cell line by time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis, a powerful surface analysis tool. In addition, the authors verified the efficacy of the specific mutant IDH1 inhibitor AGI-5198 by tracking the intracellular 2-HG concentration, which decreased in a dose-dependent manner. Our results demonstrate the large potential of TOF-SIMS as an analytical tool for the simple, direct detection of oncometabolites during cancer diagnosis, and for verifying the efficiency of the targeted cancer drugs.

Analysis of Chemotherapeutic Drug Delivery at the Single Cell Level Using 3D-MSI-TOF-SIMS

In this work, we show the advantages of label-free, tridimensional mass spectrometry imaging using dual beam analysis (25 keV Bi₃⁺) and depth profiling (20 keV with a distribution centered at Ar₁₅₀₀⁺) coupled to time of flight secondary ion mass spectrometry (3D-MSI-TOF-SIMS) for the study of A-172 human glioblastoma cell line treated with B-cell lymphoma 2 (Bcl-2) inhibitor ABT-737. The high spatial (~250 nm) and high mass resolution (m/Δm ~10,000) of TOF-SIMS permitted the localization and identification of the intact, unlabeled drug molecular ion (m/z 811.26 C₄₂H₄₄ClN₆O₅S₂^- [M - H]^-) as well as characteristic fragment ions. We propose a novel approach based on the inspection of the drug secondary ion yield, which showed a good correlation with the drug concentration during cell treatment at therapeutic dosages (0-200 μM with 4 h incubation). Chemical maps using endogenous molecular markers showed that the ABT-737 is mainly localized in subsurface regions and absent in the nucleus. A semiquantitative workflow is proposed to account for the biological cell diversity based on the spatial distribution of endogenous molecular markers (e.g., nuclei and cytoplasm) and secondary ion confirmation based on the ratio of drug-specific fragments to molecular ion as a function of the therapeutic dosage. Graphical Abstract ᅟ.

Matrix-assisted laser desorption/ionization mass spectrometry imaging of cell cultures for the lipidomic analysis of potential lipid markers in human breast cancer invasion

RATIONALE

Breast cancer is the leading cause of cancer death among women worldwide. Identification of lipid targets that play a role in breast cancer invasion may advance our understanding of the rapid progression of cancer and may lead to the development of new biomarkers for the disease.

METHODS

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) was applied for the lipidomic profiling of two poorly invasive and two highly invasive breast cancer cell lines to identify the differentially accumulated lipids related to the invasive phenotype. The four cell lines were individually grown on indium tin oxide (ITO)-coated glass slides, analyzed as cell cultures. The raster width and matrix for detection were optimized to improve detection sensitivity.

RESULTS

Optimized MSI measurements were performed directly on the cell culture with 9-aminoacridine as matrix, resulting in 215 endogenous compounds detected in positive ion mode and 267 endogenous compounds in negative ion mode in all the four cell lines, representing the largest group of analytes that have been analyzed from cells by a single MSI study. In highly invasive cell lines, 31 lipids including phosphatidylglycerol (PG) and phosphatidic acids were found upregulated and eight lipids including sphingomyelin (SM) downregulated in negative ion mode. The products of de novo fatty acid synthesis incorporated into membrane phospholipids, like oleic-acid-containing PG, may be involved in mitochondrial dysfunction and thus affect the invasion of breast cancer cells. The deficiency of SM may be related to the disruption of apoptosis in highly invasive cancer cells.

CONCLUSIONS

This work uncovered more analytes in cells by MSI than previous reports, providing a better visualization and novel insights to advance our understanding of the relationship between rapid progression of breast cancer and lipid metabolism. The most altered lipids may aid the discovery of diagnostic markers and therapeutic targets of breast cancer.

Single-cell profiling approaches to probing tumor heterogeneity

Tumor heterogeneity is a major hindrance in cancer classification, diagnosis and treatment. Recent technological advances have begun to reveal the true extent of its heterogeneity. Single-cell analysis (SCA) is emerging as an important approach to detect variations in morphology, genetic or proteomic expression. In this review, we revisit the issue of inter- and intra-tumor heterogeneity, and list various modes of SCA techniques (cell-based, nucleic acid-based, protein-based, metabolite-based and lipid-based) presently used for cancer characterization. We further discuss the advantages of SCA over pooled cell analysis, as well as the limitations of conventional techniques. Emerging trends, such as high-throughput sequencing, are also mentioned as improved means for cancer profiling. Collectively, these applications have the potential for breakthroughs in cancer treatment.

Lipid analysis of eight human breast cancer cell lines with ToF-SIMS

In this work, four triple negative (TN) cell lines, three ER+ and PR+ receptor positive (RP) cell lines, and one ER+, PR+, and HER2+ cell line were chemically distinguished from one another using time-of-flight secondary ion mass spectrometry (ToF-SIMS) and principal component analysis (PCA). PCA scores separation was observed between the individual cell lines within a given classification (TN and RP) and there were distinctly different trends found in the fatty acid and lipid compositions of the two different classifications. These trends indicated that the RP cell lines separated out based on the carbon chain length of the lipids while the TN cell lines showed separation based on cholesterol-related peaks (in the positive ion data). Both cell types separated out by trends in fatty acid chain length and saturation in the negative ions. These chemical differences may be manifestations of unique metabolic processes within each of the different cell lines. Additionally, the HER2+ cell line was distinguished from three other RP cell types as having a unique distribution of fatty acids including anticorrelation to 18-carbon chain fatty acids. As these cell lines could not be grown in the same growth media, a combination of chemical fixation, rinsing, C60 (+) presputtering, and selection of cellular regions-of-interest is also presented as a successful method to acquire ToF-SIMS data from cell lines grown in different media.