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The aim of this study was to use a two steps strategy metabolomics to screen/identify and validate novel metabolic biomarker(s) for epithelial ovarian cancer (EOC). In the screening step, serum samples from 27 healthy women, 28 benign ovarian tumors, and 29 EOCs were analyzed by using LC-MS based nontargeted metabolomics. The three groups were separated with OSC filtered PLS-DA model, and six metabolites (27-nor-5β-cholestane-3,7,12,24,25 pentol glucuronide (CPG), phenylalanine, glycocholic acid, propionylcarnitine, Phe-Phe and Lyso PC (18:2)) were considered as potential biomarker candidates. In the validation step, the six metabolites were analyzed in targeted metabolomics by LC-selective ion monitoring mass spectrometry in another 685 serum samples with various clinical backgrounds. As a result, CPG was evaluated to be a potential biomarker and its content was elevated in EOC tissues compared with benign ovarian tumor tissues (p = 0.0005). Besides, CPG levels were found to be up-regulated in early stage EOC and in the three types of EOC histological types. Other variables such as nonovarian diseases, medicine consumption, gynecological inflammations, and menopausal state did not interfere in using CPG as diagnosis marker. CPG was found to be complementary to CA125. Our findings suggest that CPG can be considered a statistical relevant biomarker of EOC, ready for early stage detection.

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Combinatorial approach of adsorbent resin HP20 addition and metabolic profiling analysis were carried out to enhance ascomycin production. Under the optimal condition of 5 % m/v HP20 added at 24 h, ascomycin production was increased to 380 from 300 mg/L. To further rationally guide the improvement of ascomycin production, metabolic profiling analysis was employed to investigate the intracellular metabolite changes of Streptomyces hygroscopicus var. ascomyceticus FS35 in response to HP20 addition. A correlation between the metabolic profiles and ascomycin accumulation was revealed by partial least-squares to latent structures discriminant analysis, and 11 key metabolites that most contributed to metabolism differences and ascomycin biosynthesis were identified. Based on the analysis of metabolite changes together with their pathways, the potential key factors associated with ascomycin overproduction were determined. Finally, rationally designed fermentation strategies based on HP20 addition were performed as follows: 2 % v/v n-hexadecane was added at 24 h; 1.0 g/L valine was supplemented at 48 h; 1.0 g/L lysine was added at 72 h. The ascomycin production was ultimately improved to 460 mg/L, a 53.3 % enhancement compared with that obtained in initial condition. These results demonstrated that the combination of HP20 addition and metabolic profiling analysis could be successfully applied to the rational guidance of production improvement of ascomycin, as well as other clinically important compounds.

To rationally guide the improvement of isobutanol production, metabolic network and metabolic profiling analysis were performed to provide global and profound insights into cell metabolism of isobutanol-producing Bacillus subtilis. The metabolic flux distribution of strains with different isobutanol production capacity (BSUL03, BSUL04 and BSUL05) drops a hint of the importance of NADPH on isobutanol biosynthesis. Therefore, the redox pathways were redesigned in this study. To increase NADPH concentration, glucose-6-phosphate isomerase was inactivated (BSUL06) and glucose-6-phosphate dehydrogenase was overexpressed (BSUL07) successively. As expected, NADPH pool size in BSUL07 was 4.4-fold higher than that in parental strain BSUL05. However, cell growth, isobutanol yield and production were decreased by 46%, 22%, and 80%, respectively. Metabolic profiling analysis suggested that the severely imbalanced redox status might be the primary reason. To solve this problem, gene udhA of Escherichia coli encoding transhydrogenase was further overexpressed (BSUL08), which not only well balanced the cellular ratio of NAD(P)H/NAD(P)+, but also increased NADH and ATP concentration. In addition, a straightforward engineering approach for improving NADPH concentrations was employed in BSUL05 by overexpressing exogenous gene pntAB and obtained BSUL09. The performance for isobutanol production by BSUL09 was poorer than BSUL08 but better than other engineered strains. Furthermore, in fed-batch fermentation the isobutanol production and yield of BSUL08 increased by 11% and 19%, up to the value of 6.12 g/L and 0.37 C-mol isobutanol/C-mol glucose (63% of the theoretical value), respectively, compared with parental strain BSUL05. These results demonstrated that model-driven complemented with metabolic profiling analysis could serve as a useful approach in the strain improvement for higher bio-productivity in further application.