Mcm10 plays an essential role in origin DNA unwinding after loading of the CMG components.

The CMG complex composed of Mcm2-7, Cdc45 and GINS is postulated to be the eukaryotic replicative DNA helicase, whose activation requires sequential recruitment of replication proteins onto Mcm2-7. Current models suggest that Mcm10 is involved in assembly of the CMG complex, and in tethering of DNA polymerase α at replication forks. Here, we report that Mcm10 is required for origin DNA unwinding after association of the CMG components with replication origins in fission yeast. A combination of promoter shut-off and the auxin-inducible protein degradation (off-aid) system efficiently depleted cellular Mcm10 to <0.5% of the wild-type level. Depletion of Mcm10 did not affect origin loading of Mcm2-7, Cdc45 or GINS, but impaired recruitment of RPA and DNA polymerases. Mutations in a conserved zinc finger of Mcm10 abolished RPA loading after recruitment of Mcm10. These results show that Mcm10, together with the CMG components, plays a novel essential role in origin DNA unwinding through its zinc-finger function.

[Prevention and management of appetite loss during cancer chemotherapy].

Appetite loss during cancer chemotherapy may lead to malnutrition and a decreased quality of life. To overcome this problem, evidence-based guidelines have been established for chemotherapy-induced emesis and mucositis. However, unsolved issues such as taste alimentation remain. Since the clinical picture of appetite loss is complex, individual management strategies depending on the type of the disease and treatment are required.

Analysis of the correlation between dipeptides and taste differences among soy sauces by using metabolomics-based component profiling.

Characterizing the relationships between the components and taste differences among soy sauces can help evaluate and improve the quality of soy sauces. Although previous studies have reported that certain taste-active dipeptides, the relationships between taste differences and dipeptides of soy sauces are unknown. Therefore, our objective in this study was to investigate the correlations between the dipeptides and the taste differences among soy sauces. To analyze the dipeptides, we constructed an analytical method using liquid chromatography/tandem mass spectrometry (LC/MS/MS) in multiple reaction monitoring mode. Based on this method, we detected 237 dipeptides, the largest number ever detected in soy sauce research. Next, orthogonal projections to latent structures regressions were performed. The data matrix of components, including dipeptides and other low-molecular-weight hydrophilic components obtained from gas chromatography/mass spectrometry (GC/MS), served as explanatory variables (366 in total), whereas a sensory data matrix obtained using quantitative descriptive analysis served as the response variable. The accuracy of models for the sweetness and saltiness differences constructed using the LC/MS/MS and GC/MS data matrix were higher than did models constructed using only the GC/MS data matrix. As a result of investigation of the correlation between the dipeptides and taste differences among soy sauces by using variable importance in the projection (VIP) score, many dipeptides showed the high correlation with taste differences. Specifically, Ile-Gln, Pro-Lys, Ile-Glu, Thr-Phe, and Leu-Gln showed the high VIP score on sweet differences. This study is the first report that reveals the correlations between the dipeptides and taste differences among soy sauces.

Metabolic profiling approach to explore compounds related to the umami intensity of soy sauce.

A metabolic profiling approach was employed to explore the compounds that affect the intensity of umami taste in soy sauce. Twenty-five kinds of soy sauces were analyzed using GC-MS and LC-MS, wherein measurement data for 427 compounds were obtained. The umami taste intensity of each soy sauce sample was also quantitated by sensory evaluation and a projection to latent structure (PLS) regression analysis was conducted using the compounds' measurements and umami taste intensity data. Variable importance for the projection (VIP) value obtained via PLS was used for the estimation of the relevance for umami taste intensity. N-(1-Deoxyfructos-1-yl)glutamic acid (Fru-Glu) had the highest VIP value, and addition of Fru-Glu to soy sauce increased umami taste intensity better than glutamic acid at the same concentration as confirmed by sensory evaluation. This study showed that the combination of metabolic profiling approach and sensory evaluation can be used effectively to determine compounds related to taste.

Metabolite profiling of soy sauce using gas chromatography with time-of-flight mass spectrometry and analysis of correlation with quantitative descriptive analysis.

Soy sauces, produced from different ingredients and brewing processes, have variations in components and quality. Therefore, it is extremely important to comprehend the relationship between components and the sensory attributes of soy sauces. The current study sought to perform metabolite profiling in order to devise a method of assessing the attributes of soy sauces. Quantitative descriptive analysis (QDA) data for 24 soy sauce samples were obtained from well selected sensory panelists. Metabolite profiles primarily concerning low-molecular-weight hydrophilic components were based on gas chromatography with time-of-flightmass spectrometry (GC/TOFMS). QDA data for soy sauces were accurately predicted by projection to latent structure (PLS), with metabolite profiles serving as explanatory variables and QDA data set serving as a response variable. Moreover, analysis of correlation between matrices of metabolite profiles and QDA data indicated contributing compounds that were highly correlated with QDA data. Especially, it was indicated that sugars are important components of the tastes of soy sauces. This new approach which combines metabolite profiling with QDA is applicable to analysis of sensory attributes of food as a result of the complex interaction between its components. This approach is effective to search important compounds that contribute to the attributes.