Association of a common variant of SYNPO2 gene with increased risk of serous epithelial ovarian cancer.

In China, the majority of ovarian cancer patients (80%-90%) are women who are diagnosed with epithelial ovarian cancer. The SYNPO2 gene has recently been reported to be associated with epithelial ovarian cancer in Europeans. To investigate the association of common variants of SYNPO2 gene with epithelial ovarian cancer in Han Chinese individuals, we designed a case-control study with 719 epithelial ovarian cancer patients and 1568 unrelated healthy controls of Han Chinese descent. A total of 49 tagging single-nucleotide polymorphisms were genotyped; single-single-nucleotide polymorphism association, imputation, and haplotypic association analyses were performed. The single-nucleotide polymorphism rs17329882 was found to be strongly associated with serous epithelial ovarian cancer and with ages ≤49 years, consistent with the pre-menopausal status of analyzed epithelial ovarian cancer cases. Odds ratios and 95% confidence intervals provided evidence of the risk effects of the C allele of the single-nucleotide polymorphism on epithelial ovarian cancer. Imputation analyses also confirmed the results with a similar pattern. Additionally, haplotype analyses indicated that the haplotype block that contained rs17329882 was significantly associated with epithelial ovarian cancer risk, specifically with the serous epithelial ovarian cancer subtype. In conclusion, our results show that SYNPO2 gene plays an important role in the etiology of epithelial ovarian cancer, suggesting that this gene may be a potential genetic modifier for developing epithelial ovarian cancer.

Enhancing fatty acid production in Escherichia coli by Vitreoscilla hemoglobin overexpression.

Our recent 13 C-metabolic flux analysis (13 C-MFA) study indicates that energy metabolism becomes a rate-limiting factor for fatty acid overproduction in E. coli strains (after "Push-Pull-Block" based genetic modifications). To resolve this bottleneck, Vitreoscilla hemoglobin (VHb, a membrane protein facilitating O2 transport) was introduced into a fatty-acid-producing strain to promote oxygen supply and energy metabolism. The resulting strain, FAV50, achieved 70% percent higher fatty acid titer than the parent strain in micro-aerobic shake tube cultures. In high cell-density bioreactor fermentations, FAV50 achieved free fatty acids at a titer of 7.02 g/L (51% of the theoretical yield). In addition to "Push-Pull-Block-Power" strategies, our experiments and flux balance analysis also revealed the fatty acid over-producing strain is sensitive to metabolic burden and oxygen influx, and thus a careful evaluation of the cost-benefit tradeoff with the guidance of fluxome analysis will be fundamental for the rational design of synthetic biology strains. Biotechnol. Bioeng. 2017;114: 463-467. © 2016 Wiley Periodicals, Inc.

Additional Evidence Supports Association of Common Variants in COL11A1 with Increased Risk of Hip Osteoarthritis Susceptibility.

OBJECTIVE: In a recent study single nucleotide polymorphisms (SNPs) in the COL11A1 gene were found to be associated with hip osteoarthritis (OA) among European populations. In this study, our aim was to identify common genetic variants in COL11A1 predisposing to primary hip OA in Han Chinese individuals. METHODS: We designed a case-control study that included 313 hip OA patients and 911 unrelated healthy controls. Fourteen tagging single-nucleotide polymorphisms (SNPs) were genotyped, and single SNP and haplotypic association analyses were performed. RESULTS: Two SNPs (rs1241164 and rs4907986) were found to be significantly associated with hip OA risk (adjusted p = 0.000731 and 0.000477). An increased risk of OA was associated with possession of the C allele of rs1241164 (adjusted odds ratio [OR] = 1.73, 95% confidence interval [CI] = 1.27-2.36) and the T allele of rs4907986 (adjusted OR = 1.72, 95% CI = 1.24-2.35). Similar results were confirmed via genotypic association analyses. Moreover, two different haplotype blocks, including rs1241164 and rs4907986, respectively, were found to be strongly associated with hip OA risk as well. CONCLUSION: Variants in the COL11A1 gene modify individual susceptibility to hip OA in the Han Chinese population.

Association of common variants in MTAP with susceptibility and overall survival of osteosarcoma: a two-stage population-based study in Han Chinese.

Osteosarcoma (OS) is a common malignant tumor, which exists widely in the bone of children and adolescents, and genetic factors may influence its susceptibility. Recently, the gene MTAP has been reported to be associated with OS in a Caucasian population. To investigate the association of common variants in MTAP with OS risk in Han Chinese individuals, we designed a two-stage case-control study with 392 OS patients and 1,578 unrelated healthy controls of Han Chinese individuals. A total of 17 tagging single nucleotide polymorphisms (SNPs) were firstly genotyped in the discovery stage, and single-SNP association and haplotypic association analyses have been performed. The SNP rs7023329 was found to be strongly associated with the OS risk (adjusted P = 0.002908), and the results of odds ratios (ORs) and 95% confidence intervals (CI) revealed increased risks from A allele of the SNP on OS (OR=1.33, 95% CI=1.13-1.62). The results were confirmed with a similar pattern in the validation stage (adjusted P = 0.006737, OR=1.49, 95% CI=1.11-2.00). Moreover, haplotypic analyses indicated that one haplotype block containing rs7023329 was significantly associated with OS risk in both stages (both global P<0.0001). The statistically significant association between the rs7023329 genotype and poor survival in OS patients was also observed. To sum up, our results prove that MTAP plays an important role in the etiology of OS, suggesting this gene as a potential genetic modifier for OS development.

WUFlux: an open-source platform for 13C metabolic flux analysis of bacterial metabolism.

BACKGROUND: Flux analyses, including flux balance analysis (FBA) and 13C-metabolic flux analysis (13C-MFA), offer direct insights into cell metabolism, and have been widely used to characterize model and non-model microbial species. Nonetheless, constructing the 13C-MFA model and performing flux calculation are demanding for new learners, because they require knowledge of metabolic networks, carbon transitions, and computer programming. To facilitate and standardize the 13C-MFA modeling work, we set out to publish a user-friendly and programming-free platform (WUFlux) for flux calculations in MATLAB®. RESULTS: We constructed an open-source platform for steady-state 13C-MFA. Using GUIDE (graphical user interface design environment) in MATLAB, we built a user interface that allows users to modify models based on their own experimental conditions. WUFlux is capable of directly correcting mass spectrum data of TBDMS (N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide)-derivatized proteinogenic amino acids by removing background noise. To simplify 13C-MFA of different prokaryotic species, the software provides several metabolic network templates, including those for chemoheterotrophic bacteria and mixotrophic cyanobacteria. Users can modify the network and constraints, and then analyze the microbial carbon and energy metabolisms of various carbon substrates (e.g., glucose, pyruvate/lactate, acetate, xylose, and glycerol). WUFlux also offers several ways of visualizing the flux results with respect to the constructed network. To validate our model's applicability, we have compared and discussed the flux results obtained from WUFlux and other MFA software. We have also illustrated how model constraints of cofactor and ATP balances influence fluxome results. CONCLUSION: Open-source software for 13C-MFA, WUFlux, with a user-friendly interface and easy-to-modify templates, is now available at http://www.13cmfa.org /or ( http://tang.eece.wustl.edu/ToolDevelopment.htm ). We will continue documenting curated models of non-model microbial species and improving WUFlux performance.

Simulating cyanobacterial phenotypes by integrating flux balance analysis, kinetics, and a light distribution function.

BACKGROUND: Genome-scale models (GSMs) are widely used to predict cyanobacterial phenotypes in photobioreactors (PBRs). However, stoichiometric GSMs mainly focus on fluxome that result in maximal yields. Cyanobacterial metabolism is controlled by both intracellular enzymes and photobioreactor conditions. To connect both intracellular and extracellular information and achieve a better understanding of PBRs productivities, this study integrates a genome-scale metabolic model of Synechocystis 6803 with growth kinetics, cell movements, and a light distribution function. The hybrid platform not only maps flux dynamics in cells of sub-populations but also predicts overall production titer and rate in PBRs. RESULTS: Analysis of the integrated GSM demonstrates several results. First, cyanobacteria are capable of reaching high biomass concentration (>20 g/L in 21 days) in PBRs without light and CO2 mass transfer limitations. Second, fluxome in a single cyanobacterium may show stochastic changes due to random cell movements in PBRs. Third, insufficient light due to cell self-shading can activate the oxidative pentose phosphate pathway in subpopulation cells. Fourth, the model indicates that the removal of glycogen synthesis pathway may not improve cyanobacterial bio-production in large-size PBRs, because glycogen can support cell growth in the dark zones. Based on experimental data, the integrated GSM estimates that Synechocystis 6803 in shake flask conditions has a photosynthesis efficiency of ~2.7 %. CONCLUSIONS: The multiple-scale integrated GSM, which examines both intracellular and extracellular domains, can be used to predict production yield/rate/titer in large-size PBRs. More importantly, genetic engineering strategies predicted by a traditional GSM may work well only in optimal growth conditions. In contrast, the integrated GSM may reveal mutant physiologies in diverse bioreactor conditions, leading to the design of robust strains with high chances of success in industrial settings.

An ancient Chinese wisdom for metabolic engineering: Yin-Yang.

In ancient Chinese philosophy, Yin-Yang describes two contrary forces that are interconnected and interdependent. This concept also holds true in microbial cell factories, where Yin represents energy metabolism in the form of ATP, and Yang represents carbon metabolism. Current biotechnology can effectively edit the microbial genome or introduce novel enzymes to redirect carbon fluxes. On the other hand, microbial metabolism loses significant free energy as heat when converting sugar into ATP; while maintenance energy expenditures further aggravate ATP shortage. The limitation of cell "powerhouse" prevents hosts from achieving high carbon yields and rates. Via an Escherichia coli flux balance analysis model, we further demonstrate the penalty of ATP cost on biofuel synthesis. To ensure cell powerhouse being sufficient in microbial cell factories, we propose five principles: 1. Take advantage of native pathways for product synthesis. 2. Pursue biosynthesis relying only on pathways or genetic parts without significant ATP burden. 3. Combine microbial production with chemical conversions (semi-biosynthesis) to reduce biosynthesis steps. 4. Create "minimal cells" or use non-model microbial hosts with higher energy fitness. 5. Develop a photosynthesis chassis that can utilize light energy and cheap carbon feedstocks. Meanwhile, metabolic flux analysis can be used to quantify both carbon and energy metabolisms. The fluxomics results are essential to evaluate the industrial potential of laboratory strains, avoiding false starts and dead ends during metabolic engineering.