Dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders.

BACKGROUND: Poor ovarian responders (POR) are women undergoing in-vitro fertilization who respond poorly to ovarian stimulation, resulting in the retrieval of lower number of oocytes, and subsequently lower pregnancy rates. The follicular fluid (FF) provides a crucial microenvironment for the proper development of follicles and oocytes through tightly controlled metabolism and cell signaling. Androgens such as dehydroepiandrosterone (DHEA) have been proposed to alter the POR follicular microenvironment, but the impact DHEA imposes on the FF metabolome and cytokine profiles is unknown. Therefore, the objective of this study is to profile and identify metabolomic changes in the FF with DHEA supplementation in POR patients. METHODS: FF samples collected from 52 POR patients who underwent IVF with DHEA supplementation (DHEA +) and without (DHEA-; controls) were analyzed using untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics and a large-scale multiplex suspension immunoassay covering 65 cytokines, chemokines and growth factors. Multivariate statistical modelling by partial least squares-discriminant regression (PLSR) analysis was performed for revealing metabolome-scale differences. Further, differential metabolite analysis between the two groups was performed by PLSR ß-coefficient regression analysis and Student's t-test. RESULTS: Untargeted metabolomics identified 118 FF metabolites of diverse chemistries and concentrations which spanned three orders of magnitude. They include metabolic products highly associated with ovarian function - amino acids for regulating pH and osmolarity, lipids such fatty acids and cholesterols for oocyte maturation, and glucocorticoids for ovarian steroidogenesis. Four metabolites, namely, glycerophosphocholine, linoleic acid, progesterone, and valine were significantly lower in DHEA + relative to DHEA- (p < 0.05-0.005). The area under the curves of progesterone glycerophosphocholine, linoleic acid and valine are 0.711, 0.730, 0.785 and 0.818 (p < 0.05-0.01). In DHEA + patients, progesterone positively correlated with IGF-1 (Pearson r: 0.6757, p < 0.01); glycerophosphocholine negatively correlated with AMH (Pearson r: -0.5815; p < 0.05); linoleic acid correlated with estradiol and IGF-1 (Pearson r: 0.7016 and 0.8203, respectively; p < 0.01 for both). In DHEA- patients, valine negatively correlated with serum-free testosterone (Pearson r: -0.8774; p < 0.0001). Using the large-scale immunoassay of 45 cytokines, we observed significantly lower MCP1, IFNγ, LIF and VEGF-D levels in DHEA + relative to DHEA. CONCLUSIONS: In POR patients, DHEA supplementation altered the FF metabolome and cytokine profile. The identified four FF metabolites that significantly changed with DHEA may provide information for titrating and monitoring individual DHEA supplementation.

Potential plasma biomarkers for progression of knee osteoarthritis using glycoproteomic analysis coupled with a 2D-LC-MALDI system.

BACKGROUND: Although osteoarthritis (OA) is a highly prevalent joint disease, to date, no reliable biomarkers have been found for the disease. In this study, we attempted to identify factors the amounts of which significantly change in association with the progression of knee OA. METHODS: A total of 68 subjects with primary knee OA were enrolled in the study. These subjects were followed up over an 18-month period, and plasma and serum samples were obtained together with knee radiographs every 6 months, i.e., 0, 6, 12 and 18 months after the enrollment. Progressors and non-progressors were determined from the changes on radiographs, and plasma samples from those subjects were subjected to N-glycoproteomic 2D-LC-MALDI analysis. MS peaks were identified, and intensities for respective peaks were compared between the progressors and non-progressors to find the peak intensities of which differed significantly between the two groups of subjects. Proteins represented by the chosen peaks were identified by MS/MS analysis. Expression of the identified proteins was evaluated in synovial tissues from 10 OA knee joints by in situ hybridization, western blotting analysis and ELISA. RESULTS: Among the subjects involved in the study, 3 subjects were determined to be progressors, and 6 plasma and serum samples from these subjects were subjected to the analysis together with another 6 samples from the non-progressors. More than 3000 MS peaks were identified by N-glycoproteomic 2D-LC-MALDI analysis. Among them, 4 peaks were found to have significantly different peak intensities between the progressors and non-progressors. MS/MS analysis revealed that these peaks represented clusterin, hemopexin, alpha-1 acid glycoprotein-2, and macrophage stimulating protein, respectively. The expression of these genes in OA synovium was confirmed by in situ hybridization, and for clusterin and hemopexin, by western blotting analysis and ELISA as well. CONCLUSIONS: In this study, 4 potential biomarkers were identified as potential prognostic markers for knee OA through N-glycoproteomic analysis. To the best of our knowledge, this is the first report for the use of glycoproteomic technology in exploring potential biomarkers for knee OA.

Utilizing Ion Mobility-Mass Spectrometry to Investigate the Unfolding Pathway of Cu/Zn Superoxide Dismutase.

Native mass spectrometry has emerged as a powerful tool for structural biology as it enables the evaluation of molecules as they occur in their physiological conditions. Ion mobility spectrometry-mass spectrometry (IMS-MS) has shown essential in these analyses as it allows the measurement of the shape of a molecule, denoted as its collision cross section (CCS), and mass. The structural information garnered from native IMS-MS provides insight into the tertiary and quaternary structure of proteins and can be used to validate NMR or crystallographic X-ray structures. Additionally, due to the rapid nature (millisecond measurements) and ability of IMS-MS to analyze heterogeneous solutions, it can be used to address structural questions not possible with traditional structural approaches. Herein, we applied multiple solution conditions to systematically denature bovine Cu/Zn-superoxide dismutase (SOD1) and assess its unfolding pathway from the holo-dimer to the holo-monomer, single-metal monomer, and apo-monomer. Additionally, we compared and noted 1-2% agreement between CCS values from both drift tube IMS and trapped IMS for the SOD1 holo-monomer and holo-dimer. The observed CCS values were in excellent agreement with computational CCS values predicted from the homo-dimer crystal structure, showcasing the ability to use both IMS-MS platforms to provide valuable structural information for molecular modeling of protein interactions and structural assessments.

Destruxin E decreases Beta-amyloid generation by reducing colocalization of beta-amyloid-cleaving enzyme 1 and beta-amyloid protein precursor.

Alzheimer-disease-associated beta-amyloid (Abeta) is produced by sequential endoproteolysis of beta-amyloid protein precursor (betaAPP): the extracellular portion is shed by cleavage in the juxtamembrane region by beta-amyloid-cleaving enzyme (BACE)/beta-secretase, after which it is cleaved by presenilin (PS)/gamma-secretase near the middle of the transmembrane domain. Thus, inhibition of either of the secretases reduces Abeta generation and is a fundamental strategy for the development of drugs to prevent Alzheimer disease. However, it is not clear how small compounds reduce Abeta production without inhibition of the secretases. Such compounds are expected to avoid some of the side effects of secretase inhibitors. Here, we report that destruxin E (Dx-E), a natural cyclic hexadepsipeptide, reduces Abeta generation without affecting BACE or PS/gamma-secretase activity. In agreement with this, Dx-E did not inhibit Notch signaling. We found that Dx-E decreases colocalization of BACE1 and betaAPP, which reduces beta-cleavage of betaAPP. Therefore, the data demonstrate that Dx-E represents a novel Abeta-reducing process which could have fewer side effects than secretase inhibitors.

Identification of potential prognostic markers for knee osteoarthritis by serum proteomic analysis.

BACKGROUND: As osteoarthritis (OA) is a highly heterogeneous disease in terms of progression, establishment of prognostic biomarkers would be highly beneficial for treatment. The present study was performed to identify novel biomarkers capable of predicting the progression of knee OA. METHODS: A total of 69 plasma samples (OA patients undergoing radiographic progression, n = 25; nonprogression, n = 33; healthy donors, n = 11) were analyzed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), and ion peaks of interest were identified by liquid chromatography and matrix-assisted laser desorption/ionization (MALDI)-TOF MS. The identities of these proteins were further validated by immunoprecipitation combined with SELDI-TOF MS analysis. RESULTS: SELDI-TOF MS analysis indicated that the intensities of 3 ion peaks differed significantly between progressors and nonprogressors. Subsequent analyses indicated that these peaks corresponded to apolipoprotein C-I, C-III, and an N-terminal truncated form of transthyretin, respectively. The identities of these proteins were confirmed by the loss of ion peaks in SELDI-TOF MS spectra by immunoprecipitation using specific antibodies for the respective proteins. CONCLUSIONS: Three potential biomarkers were identified whose serum levels differed significantly between OA progressors and nonprogressors. These biomarkers are expected to be prognostic biomarkers for knee OA and to facilitate the development of novel disease-modifying treatments for OA.

Development of quantitative plasma N-glycoproteomics using label-free 2-D LC-MALDI MS and its applicability for biomarker discovery in hepatocellular carcinoma.

There has been rapid progress in the development of clinical proteomic methodologies with improvements in mass spectrometric technologies and bioinformatics, leading to many new methodologies for biomarker discovery from human plasma. However, it is not easy to find new biomarkers because of the wide dynamic range of plasma proteins and the need for their quantification. Here, we report a new methodology for relative quantitative proteomic analysis combining large-scale glycoproteomics with label-free 2-D LC-MALDI MS. In this method, enrichment of glycopeptides using hydrazide resin enables focusing on plasma proteins with lower abundance corresponding to the tissue leakage region. On quantitative analysis, signal intensities by 2-D LC-MALDI MS were normalized using a peptide internal control, and the values linked to LC data were treated with DeView™ software. Our proteomic method revealed that the quantitative dynamic ranged from 10² to 106 pg/mL of plasma proteins with good reproducibility, and the limit of detection was of the order of a few ng/mL of proteins in biological samples. To evaluate the applicability of our method for biomarker discovery, we performed a feasibility study using plasma samples from patients with hepatocellular carcinoma, and identified biomarker candidates, including ceruloplasmin, alpha-1 antichymotrypsin, and multimerin-1.