Development of a highly efficient solubilization method for mass spectrometric analysis of phospholipids in living single cells

Phospholipids are vital constituents of the cell membrane and aid in signal transduction. Phospholipid profiles vary distinctively with the cell type. Notably, specific phospholipid molecules are present in significantly higher or lower concentrations in cancer cells versus normal cells. In this study, live single-cell mass spectrometry (MS) was developed for analyzing phospholipids at the single-cell level. This method facilitates rapid molecular analysis of cells under microscopic observation. For nanoelectrospray ionization, phospholipids were extracted from single cells isolated in a glass capillary through a high-efficiency process. Cell-derived phosphatidylcholines were detected with high sensitivity when trehalose C14 was added as a solubilizing reagent. Trehalose C14 can solubilize cells at low concentrations owing to its low critical micelle concentration, and exerts minimal matrix effects (such as suppressing ionization and causing peak overlap) in the MS analysis of cellular molecules. Analyses of phospholipids in Raji and HEV0070 cells using the developed method revealed specific peaks of phosphatidylcholine and sphingomyelin in the respective cells. The developed technique not only affords phospholipid profiles at the single-cell level, but also holds promise for identifying biomarkers associated with various diseases, particularly cancer.

Single-Cell Metabolomics by Mass Spectrometry

Single-cell level metabolomics gives a snapshot of small molecules, intermediates, and products of cellular metabolism within a biological system. These small molecules, typically less than 1 kDa in molecular weight, often provide the basis of biochemical heterogeneity within cells. The molecular differences between cells with a cell type are often attributed to random stochastic biochemical processes, cell cycle stages, environmental stress, and diseased states. In this chapter, current limitations and challenges in single-cell analysis by mass spectrometry will be discussed alongside the prospects of single-cell metabolomics in systems biology. A few selected example of the recent development in mass spectrometry tools to unravel single-cell metabolomics will be described as well.

Ten Major Future Challenges in Single-Cell Metabolomics

Information on cellular metabolism at the single-cell level can unravel countless biochemical process providing invaluable biomedical insight. Single-cell analysis field is at the very early stage at this moment, and all the work done so far are proof-of-principle work by early-stage researchers. In this chapter, I have outlined ten fundamental issues that are required for the development of robust single-cell metabolomics platform using mass spectrometry (MS).

Different Bioactive Neuropeptides are Expressed in Two Sub-Classes of GABAergic RME Nerve Ring Motorneurons in Ascaris suum

Neuropeptides can have significant effects on neurons and synapses, but among the ∼250 predicted peptides in nematodes, few have been characterized functionally. Here, we report new neuropeptides in the 4 RME nerve ring motorneurons of the nematode Ascaris suum. These GABAergic neurons are involved in three-dimensional head movement. Mass spectrometry (MS) of single dissected RMEs detected a total of 12 neuropeptides (encoded by five genes), nine of which are novel. None of these are expressed in the DI/VI inhibitory GABAergic motorneurons that synapse onto body wall muscle. Using peptide sequences obtained by tandem MS, we cloned the peptide-encoding transcripts and synthesized riboprobes for in situ hybridization (ISH). This complementary technique corroborated the results from single-cell MS, showing that the dissections were not contaminated with adhering tissue from other cells. We also synthesized a multiple antigenic peptide to raise a highly specific antibody against one of the endogenous peptides, which labeled the same cells detected by MS and ISH. Our results show that the RMEs can be divided into two subsets: RMED/V (expressing afp-2, afp-15, Asu-nlp-58, and high levels of afp-16) and RMEL/R (expressing afp-15 and low levels of afp-4 and afp-16). Almost all of these peptides are bioactive in A. suum.