A variety of efforts to clarify various life aspects at the single cell level have been performed in recent years, in particular with the aim of characterizing rare cells or observing of heterogeneity among similar cells in a qualitative and quantitative manner. To achieve such purposes, it is necessary to analyze various molecules in a comprehensive and sensitive manner, in which mass spectrometry-based analyses could be one of the most effective methods for such purposes. Here we focus on single-cell metabolome analysis using mass spectrometry and introduce what kind of technology is being developed. Especially we focus on Live Single-Cell Mass Spectrometry (LSC-MS), which has been developed to be specialized in single cell observation in an intuitive way. We introduce two latest achievements using this method, characterization of circulating tumor cell as an example to rare cells and evaluation of pharmacokinetic heterogeneity between cells in a combination with Raman spectroscopy as an example of heterogeneity observation.

Recent research findings indicate that the posttranslational modification of human serum albumin (HSA) such as oxidation, glycation, truncation, dimerization and carbamylation is related to certain types of diseases. We report herein on a simple and rapid analytical method, using an ESI-TOFMS technique, that allows posttranslational modifications of HSA to be quantitatively and qualitatively evaluated with a high degree of sensitivity. In patients with chronic liver disease, chronic renal disease and diabetes mellitus, an increase in the level of oxidized Cys-34 of HSA accompanied by a decrease in the level of reduced Cys-34 was observed. The redox status of Cys-34 was correlated with ligand binding and the anti-oxidative functions of HSA. Available evidence indicates that monitoring the redox state of Cys-34 could, not only be a useful marker for evaluating the progression of disease and its complications, but also would permit therapeutic efficacy to be predicted. The redox state of Cys-34 was also used as an index of the quality of HSA preparations. These data suggest that monitoring the posttranslational modifications of HSA can be important, since the function of HSA is related, not only to its serum concentration, but also to the preservation of its structural integrity under disease conditions.

The soybean seed basic 7S globulin (Bg7S)-like proteins were found universally in many species of plants. Bg7S was originally thought to be one of the major seed storage proteins, but it was elucidated in later studies that Bg7S was not a storage protein but a protein with many functions such as stress response, antibacterial activity, hormone receptor-like activity, etc. Functional differences in Bg7S were found between legumes and other plants. Bg7S of plants other than legumes had a function to inhibit the invasion of pathogenic microorganisms into cells. In addition, in non-leguminous plants, there was no peptide such as leginsulin which has activity to bind to Bg7S. Although Bg7S-like proteins in leguminous plants and other plants are homologous, they may have evolved in functionally different directions. On the other hand, Bg7S and leginsulin were found to have functional effects on humans, rats, and mice, such as the control of blood glucose level, blood pressure and plasma cholesterol level, and cancer cell antiproliferative actions.

Omics analyses are accelerating the research of disease markers for requiring early detection, early clinical treatment and prevention of disease in the next generation of health care. In particular, metabolome analysis is a promising approach in the research field because the metabolite concentrations of body fluids are considered as quantitative traits that can describe and define phenotypic characteristics of each individual, which are generated through interactions between genes and environmental influences.

We established a protocol of metabolome analysis by gas chromatography triple quadrupole mass spectrometry (GC-MS/MS) in a large-scale cohort study, and analyzed human plasma samples (1,028) obtained from our cohort study; Tohoku Medical Megabank Project for creating a reference; Japanese Multi Omics Reference Panel, jMorp.

In our protocol, samples were prepared in a 96-well plate using an automated liquid-handling system, and the GC-MS/MS system equipped with an automated derivatized system. All data were imported for peak picking software and normalized by a Quantbolome software, which was created by our laboratory, to compensate for intra- and inter-batch differences. Finally, the information of 169 metabolites detected in 1,028 human plasma samples were listed in jMorp. The protocol and normalization method should be useful for the discovery and development of disease biomarkers in a large-scale cohort study.

Early diagnosis of cancer by liquid biopsy is desired to be realized in cancer treatment. Large-scale proteomic analysis for biomarker discovery has been actively conducted. However, biomarkers that can be used for early diagnosis have not been developed. In recent years, extracellular vesicles have attracted attention as biomarker resources for liquid biopsy. In our laboratory, extracellular vesicles were extracted from colon cancer patient serum and biomarker candidate proteins were identified by shotgun proteomics. These candidate proteins were further verified by targeted proteomics, SRM. In this article, we describe the pretreatment method of serum samples and optimization of analysis method in SRM.