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Exosomes, small membrane vesicles secreted by a multitude of cell types, are involved in a wide range of physiological roles such as intercellular communication, membrane exchange between cells, and degradation as an alternative to lysosomes. Because of the small size of exosomes (30-100 nm) and the limitations of common separation procedures including ultracentrifugation and flow cytometry, size-based fractionation of exosomes has been challenging. In this study, we used flow field-flow fractionation (FlFFF) to fractionate exosomes according to differences in hydrodynamic diameter. The exosome fractions collected from FlFFF runs were examined by transmission electron microscopy (TEM) to morphologically confirm their identification as exosomes. Exosomal lysates of each fraction were digested and analyzed using nanoflow LC-ESI-MS-MS for protein identification. FIFFF, coupled with mass spectrometry, allows nanoscale size-based fractionation of exosomes and is more applicable to primary cells and stem cells since it requires much less starting material than conventional gel-based separation, in-gel digestion and the MS-MS method.

A linear octopole trap interface for an ion mobility time-of-flight mass spectrometer has been developed for focusing and accumulating continuous beams of ions produced by electrospray ionization. The interface improves experimental efficiencies by factors of approximately 50-200 compared with an analogous configuration that utilizes a three-dimensional Paul geometry trap (Hoaglund-Hyzer, C. S.; Lee, Y. J.; Counterman, A. E.; Clemmer, D. E. Anal. Chem. 2002, 74, 992-1006). With these improvements, it is possible to record nested drift (flight) time distributions for complex mixtures in fractions of a second. We demonstrate the approach for several well-defined peptide mixtures and an assessment of the detection limits is given. Additionally, we demonstrate the utility of the approach in the field of proteomics by an on-line, three-dimensional nano-LC-ion mobility-TOF separation of tryptic peptides from the Drosophila proteome.

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Exosomes are membrane-bound extracellular vesicles involved in intercellular communication and tumor cell metastasis. In this study, flow field-flow fractionation (FlFFF) was utilized to separate urinary exosomes by size, demonstrating a significant difference in exosome sizes between healthy controls and patients with prostate cancer (PCa). Exosome fractions of different sizes were collected for microscopic analysis during an FlFFF run and evaluated with exosome marker proteins using Western blot analysis. The results indicated that exosomes of different sizes originated from different types of cells. Collected exosome fractions were further examined using nanoflow ultrahigh performance liquid chromatography-electrospray ionization-tandem mass spectrometry (nUPLC-ESI-MS/MS) for lipidomic analysis. A total of 162 lipids (from 286 identified) were quantified using a selected reaction monitoring (SRM) method. The overall amount of lipids increased by 1.5- to 2-fold in patients with PCa and degree of increase was more significant in the smaller fractions (diameter <150 nm) than in the larger ones (diameter >150 nm) some classes of lipids. In addition, neutral lipids like diacylglycerol (DAG) and triacylglycerol (TAG) decreased in all exosomes without size dependency. Moreover, a dramatic increase in 22:6/22:6-phosphatidylglycerol (PG) was observed and significant decrease in (16:0,16:0)- and (16:1, 18:1)-DAG species (nearly 5-fold) and high abundant TAG species (>2.5-fold) was observed in patients with PCa. The results of this study indicate that FlFFF can be employed for the high-speed screening of urinary exosome sizes in patients with PCa and lipidomic analysis of the fractionated exosomes has potential for developing and distinguishing biomarkers of PCa.

In this study, an analytical method for the simultaneous separation and characterization of various molecular species of lysophospholipids (LPLs) and phospholipids (PLs) is introduced by employing nanoflow liquid chromatography-electrospray ionization tandem mass spectrometry (nLC-ESI-MS/MS). Since LPLs and PLs in human plasma are potential biomarkers for cancer, development of a sophisticated analytical method for the simultaneous profiling of these molecules is important. Standard species of LPLs and PLs were examined to establish a separation condition using a capillary LC column followed by MS scans and data-dependent collision-induced dissociation (CID) analysis for structural identification. With nLC-ESI-MS/MS, regioisomers of each category of LPLs were completely separated and identified with characteristic CID spectra. It was applied to the comprehensive profiling of LPLs and PLs from a human blood plasma sample and yielded identifications of 50 LPLs (each regioisomer pair of 6 lysophosphatidylcholines (LPCs), 7 lysophosphatidylethanolamines (LPEs), 9 lysophosphatidic acid (LPAs), 2 lysophosphatidylglycerols (LPGs), and 1 lysophosphatidylserine (LPS)) and 62 PLs (19 phosphatidylcholines (PCs), 11 phosphatidylethanolamines (PEs), 3 phosphatidylserines (PSs), 16 phosphatidylinositols (PIs), 8 phosphatidylglycerols (PGs), and 5 phosphatidic acids (PAs)).

Qualitative and quantitative profiling of six different categories of urinary phospholipids (PLs) from patients with prostate cancer was performed to develop an analytical method for the discovery of candidate biomarkers by shotgun lipidomics method. Using nanoflow liquid chromatography-electrospray ionization-tandem mass spectrometry, we identified the molecular structures of a total of 70 PL molecules (21 phosphatidylcholines (PCs), 11 phosphatidylethanolamines (PEs), 17 phosphatidylserines (PSs), 11 phosphatidylinositols (PIs), seven phosphatidic acids, and three phosphatidylglycerols) from urine samples of healthy controls and prostate cancer patients by data-dependent collision-induced dissociation. Identified molecules were quantitatively examined by comparing the MS peak areas. From statistical analyses, one PC, one PE, six PSs, and two PIs among the PL species showed significant differences between controls and cancer patients (p < 0.05, Student's t test), with concentration changes of more than threefold. Cluster analysis of both control and patient groups showed that 18:0/18:1-PS and 16:0/22:6-PS were 99% similar in upregulation and that the two PSs (18:1/18:0, 18:0/20:5) with two PIs (18:0/18:1 and 16:1/20:2) showed similar (>95%) downregulation. The total amount of each PL group was compared among prostate cancer patients according to the Gleason scale as larger or smaller than 6. It proposes that the current study can be utilized to sort out possible diagnostic biomarkers of prostate cancer.

Abnormalities in steroid hormones are responsible for the development and prevention of endocrine diseases. Due to their biochemical roles in endocrine system, the quantitative evaluation of steroid hormones is needed to elucidate altered expression of steroids. Gas chromatographic-mass spectrometric (GC-MS) profiling of 70 urinary steroids, containing 22 androgens, 18 estrogens, 15 corticoids, 13 progestins, and 2 sterols, were validated and its quantitative data were visualized using hierarchically clustered heat maps to allow "steroid signatures". The devised method provided a good linearity (r 2 Ͼ 0.994) with the exception of cholesterol (r 2 ϭ 0.983). Precisions (% CV) and accuracies (% bias) ranged from 0.9% to 11.2% and from 92% to 119%, respectively, for most steroids tested. To evaluate metabolic changes, this method was applied to urine samples obtained from 59 patients with benign prostatic hyperplasia (BPH) versus 41 healthy male subjects. Altered concentrations of urinary steroids found and heat maps produced during this 70-compound study showed also differences between the ratios of steroid precursors and their metabolites (representing enzyme activity). Heat maps showed that oxidoreductases clustered (5␣-reductase, 3␣-HSD, 3␤-HSD, and 17␤-HSD, except for 20␣-HSD). These results support that data transformation is valid, since 5␣-reductase is a marker of BPH and 17␤-HSD is positively expressed in prostate cells. Multitargeted profiling analysis of steroids generated quantitative results that help to explain correlations between enzyme activities. The data transformation and visualization described may to be found in the integration with the mining biomarkers of hormone-dependent diseases. Many naturally occurring steroids with similar chemical structures could yield biological information [7]. Endogenous steroids are divided into five groups, namely, androgens, estrogens, corticoids, progestins, and sterols, which are generally synthesized from cholesterol in the adrenal cortex, ovaries, and testes (Scheme 1). In biosynthetic pathways of steroid hormone, two major types of enzymes are involved, cytochrome P450 and steroid oxidoreductase. Abnormalities of these enzymes often lead to hormonal imbalances that have serious consequences, and which are responsible for the development of hormone-dependent diseases (see Supplementary Table 1, which can be found in the electronic version of this article). For example, concentrations of corticoids and their metabolic ratios provide diagnostic evidence of apparent mineralocorticoid excesses caused by 11␤-HSD deficiency [8] and congenital adrenal hyperplasia, which are caused by deficiencies of enzymes like hydroxylase (at C-11, 17, and 21) or 3␤-HSD [9]. In addition, enhanced androgen activity generated by the conversion of testosterone to dihydrotestosterone (DHT) by 5␣-reductase was utilized to allow early therapeutic intervention in young men [10].Enzyme activity profiles can be used to describe the functional diversities of biological systems, which are d...