The Development of Single-Cell Metabolism and Its Role in Studying Cancer Emergent Properties

Metabolic reprogramming is one of the hallmarks of malignant tumors, which provides energy and material basis for tumor rapid proliferation, immune escape, as well as extensive invasion and metastasis. Blocking the energy and material supply of tumor cells is one of the strategies to treat tumor, however tumor cell metabolic heterogeneity prevents metabolic-based anti-cancer treatment. Therefore, searching for the key metabolic factors that regulate cell cancerous change and tumor recurrence has become a major challenge. Emerging technology––single-cell metabolomics is different from the traditional metabolomics that obtains average information of a group of cells. Single-cell metabolomics identifies the metabolites of single cells in different states by mass spectrometry, and captures the molecular biological information of the energy and substances synthesized in single cells, which provides more detailed information for tumor treatment metabolic target screening. This review will combine the current research status of tumor cell metabolism with the advantages of single-cell metabolomics technology, and explore the role of single-cell sequencing technology in searching key factors regulating tumor metabolism. The addition of single-cell technology will accelerate the development of metabolism-based anti-cancer strategies, which may greatly improve the prognostic survival rate of cancer patients.

Single-cell metabolomics reveals the metabolic heterogeneity among microbial cells

In microbial research, the heterogeneity phenomenon is closely associated with microbial physiology in multiple dimensions. For now, A few studies were proposed in transcriptome and proteome analysis to discover the heterogeneity among single cells. However, microbial single cell metabolomics has not been possible yet. Herein, we developed a method, RespectM, based on discontinuous mass spectrometry imaging, which can detect more than 700 metabolites at a rate of 500 cells per hour. While ensuring the high throughput of RespectM, it integrates matrix sublimation, QC-based peak filtering, and batch correction strategies to improve accuracy. The results show that RespectM can distinguish single microbial cells from the blank matrix with an accuracy of 98.4%, depending on classification algorithms. Furthermore, to verify the accuracy of RespectM for distinguishing different single cells, we performed a classification test on Chlamydomonas reinhardtii single cells among allelic strains. The results showed an accuracy of 93.1%, which provides RespectM with enough confidence to perform microbial single cell metabolomics analysis. As we expected, untreated microbial cells will spontaneously undergo metabolic grouping coherence with genetic and biochemical similarities. Interestingly, the pseudo-time analysis also provided intuitive evidence on the metabolic dimension, indicating the cell grouping is based on microbial population heterogeneity. We believe that the RespectM can offer a powerful tool in the microbial study. Researchers can now directly analyze the changes in microbial metabolism at a single-cell level with high efficiency.

Three-Dimensional Cell Metabolomics Deciphers the Anti-Angiogenic Properties of the Radioprotectant Amifostine

Aberrant angiogenesis is a hallmark for cancer and inflammation, a key notion in drug repurposing efforts. To delineate the anti-angiogenic properties of amifostine in a human adult angiogenesis model via 3D cell metabolomics and upon a stimulant-specific manner, a 3D cellular angiogenesis assay that recapitulates cell physiology and drug action was coupled to untargeted metabolomics by liquid chromatography–mass spectrometry and nuclear magnetic resonance spectroscopy. The early events of angiogenesis upon its most prominent stimulants (vascular endothelial growth factor-A or deferoxamine) were addressed by cell sprouting measurements. Data analyses consisted of a series of supervised and unsupervised methods as well as univariate and multivariate approaches to shed light on mechanism-specific inhibitory profiles. The 3D untargeted cell metabolomes were found to grasp the early events of angiogenesis. Evident of an initial and sharp response, the metabolites identified primarily span amino acids, sphingolipids, and nucleotides. Profiles were pathway or stimulant specific. The amifostine inhibition profile was rather similar to that of sunitinib, yet distinct, considering that the latter is a kinase inhibitor. Amifostine inhibited both. The 3D cell metabolomics shed light on the anti-angiogenic effects of amifostine against VEGF-A- and deferoxamine-induced angiogenesis. Amifostine may serve as a dual radioprotective and anti-angiogenic agent in radiotherapy patients.

Optical Microscopy-Guided Laser Ablation Electrospray Ionization Ion Mobility Mass Spectrometry: Ambient Single Cell Metabolomics with Increased Confidence in Molecular Identification

Single cell analysis is a field of increasing interest as new tools are continually being developed to understand intercellular differences within large cell populations. Laser-ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging technique for single cell metabolomics. Over the years, it has been validated that this ionization technique is advantageous for probing the molecular content of individual cells in situ. Here, we report the integration of a microscope into the optical train of the LAESI source to allow for visually informed ambient in situ single cell analysis. Additionally, we have coupled this ‘LAESI microscope’ to a drift-tube ion mobility mass spectrometer to enable separation of isobaric species and allow for the determination of ion collision cross sections in conjunction with accurate mass measurements. This combined information helps provide higher confidence for structural assignment of molecules ablated from single cells. Here, we show that this system enables the analysis of the metabolite content of Allium cepa epidermal cells with high confidence structural identification together with their spatial locations within a tissue.

Cell metabolomics analyses revealed a role of altered fatty acid oxidation in neurotoxicity pattern difference between nab-paclitaxel and solvent-based paclitaxel

Peripheral neuropathy (PN) is a dose-limiting, painful adverse reaction associated with the use of paclitaxel. This common side effect was often partially attributed to the solvent used for solubilization of the highly hydrophobic drug substance. Therefore, the development of alternative formulations thrived, which included that of Abraxane® containing nanoparticle albumin-bound paclitaxel (nab-paclitaxel). However, studies demonstrated inconsistent conclusions regarding the mitigation of PN in comparison with the traditional formulation. The mass spectrometry-based cell metabolomics approach was used in the present study to explore the potentially associated mechanisms. Although no significant difference in the effects on cell viability was observed, fold changes in carnitine, several acylcarnitines and long-chain fatty acid(s) were significantly different between treatment groups in differentiated and undifferentiated SH-SY5Y cells. The most prominent difference observed was the significant increase of octanoylcarnitine in cells treated with solvent-based paclitaxel, which was found to be associated with significant decrease of medium-chain acyl-CoA dehydrogenase (MCAD). The findings suggested the potential role of altered fatty acid oxidation in the different neurotoxicity patterns observed, which may be a possible target for therapeutic interventions worth further investigation.