Annotation of 2,507 Saccharomyces cerevisiae genomes.

Saccharomyces cerevisiae (baker's yeast, budding yeast) is one of the most important model organisms for biological research and is a crucial microorganism in industry. Currently, a huge number of Saccharomyces cerevisiae genome sequences are available at the public domain. However, these genomes are distributed at different websites and a large number of them are released without annotation information. To provide one complete annotated genome data resource, we collected 2,507 Saccharomyces cerevisiae genome assemblies and re-annotated 2,506 assemblies using a custom annotation pipeline, producing a total of 15,407,164 protein-coding gene models. With a custom pipeline, all these gene sequences were clustered into families. A total of 1,506 single-copy genes were selected as marker genes, which were then used to evaluate the genome completeness and base qualities of all assemblies. Pangenomic analyses were performed based on a selected subset of 847 medium-high-quality genomes. Statistical comparisons revealed a number of gene families showing copy number variations among different organism sources. To the authors' knowledge, this study represents the largest genome annotation project of S. cerevisiae so far, providing rich genomic resources for the future studies of the model organism S. cerevisiae and its relatives.IMPORTANCESaccharomyces cerevisiae (baker's yeast, budding yeast) is one of the most important model organisms for biological research and is a crucial microorganism in industry. Though a huge number of Saccharomyces cerevisiae genome sequences are available at the public domain, these genomes are distributed at different websites and most are released without annotation, hindering the efficient reuse of these genome resources. Here, we collected 2,507 genomes for Saccharomyces cerevisiae, performed genome annotation, and evaluated the genome qualities. All the obtained data have been deposited at public repositories and are freely accessible to the community. This study represents the largest genome annotation project of S. cerevisiae so far, providing one complete annotated genome data set for S. cerevisiae, an important workhorse for fundamental biology, biotechnology, and industry.

Prediction of flavor and retention index for compounds in beer depending on molecular structure using a machine learning method.

In order to make a preliminary prediction of flavor and retention index (RI) for compounds in beer, this work applied the machine learning method to modeling depending on molecular structure. Towards this goal, the flavor compounds in beer from existing literature were collected. The database was classified into four groups as aromatic, bitter, sulfury, and others. The RI values on a non-polar SE-30 column and a polar Carbowax 20M column from the National Institute of Standards Technology (NIST) were investigated. The structures were converted to molecular descriptors calculated by molecular operating environment (MOE), ChemoPy and Mordred, respectively. By combining the pretreatment of the descriptors, machine learning models, including support vector machine (SVM), random forest (RF) and k-nearest neighbour (kNN) were utilized for beer flavor models. Principal component regression (PCR), random forest regression (RFR) and partial least squares (PLS) regression were employed to predict the RI. The accuracy of the test set was obtained by SVM, RF, and kNN. Among them, the combination of descriptors calculated by Mordred and RF model afforded the highest accuracy of 0.686. R 2 of the optimal regression model achieved 0.96. The results indicated that the models can be used to predict the flavor of a specific compound in beer and its RI value.

Effect of Hydraulic Retention Time on Anaerobic Digestion of Wheat Straw in the Semicontinuous Continuous Stirred-Tank Reactors.

Three semicontinuous continuous stirred-tank reactors (CSTR) operating at mesophilic conditions (35°C) were used to investigate the effect of hydraulic retention time (HRT) on anaerobic digestion of wheat straw. The results showed that the average biogas production with HRT of 20, 40, and 60 days was 46.8, 79.9, and 89.1 mL/g total solid as well as 55.2, 94.3, and 105.2 mL/g volatile solids, respectively. The methane content with HRT of 20 days, from 14.2% to 28.5%, was the lowest among the three reactors. The pH values with HRT of 40 and 60 days were in the acceptable range compared to that with HRT of 20 days. The propionate was dominant in the reactor with HRT of 20 days, inhibiting the activities of methanogens and causing the lower methane content in biogas. The degradation of cellulose, hemicellulose, and crystalline cellulose based on XRD was also strongly influenced by HRTs.

[Wastewater pollution characteristics from typical intensive pig farms in the Pearl River Delta and its ecological risk assessment].

Based on the wastewater quality investigation data from March 2009 to November 2011, wastewater qualities from typical intensive pig farms were assessed in the Pearl River Delta by single and comprehensive pollution index model. The results showed that key pollutants of piggery wastewater were fecal coliform (FC), total phosphorus (TP), chemical oxygen demand (COD) and biochemical oxygen demand (BOD), with their average mass concentrations of 1.98 x 10(9) CFU.L-1, 158.61 mg.L-1, 5 608.68 mg.L-1 and 1984.34 mg.L-1, respectively; key pollutants of biogas slurry were FC, TP, ammonia nitrogen (NH+4 -N) and suspended substance (SS), with their average mass concentrations of 8. 10 x 10(6) CFU.L-1, 81.76 mg.L-1, 476.24 mg.L-1 and 464.58 mg.L-1, respectively. Under the effect of wastewater pollutants, environment surrounding of typical intensive pig farms was seriously polluted, which decreased gradually from piggery wastewater to biogas slurry, and comprehensive pollution indices were 11.41, 6.91, 5.27, respectively. The risk analysis showed that the high-risk wastewater could never be discharged directly and irrigated crops. After the anaerobic treatment, FC, TP, NH+4 -N and SS were still strong factors with the potential ecological risk in the biogas slurry. In the long run, the ecological risk still exists for direct discharge or irrigation of them, and it is necessary to apply further treatment.

[Expression of cyclooxygenase-2 in bone marrow cells of chronic leukemia and its significance].

The study was aimed to investigate the expression of COX-2 in bone marrow cells of chronic leukemia patients and its potential pathogenetic implications. Western blot was applied for detecting COX-2 expression levels in bone marrow cells of 67 chronic leukemia patients and beta-actin expression levels. Bone marrow aspirations from 14 healthy donors were used as negative controls. The results showed that the positive rates of COX-2 in chronic-phase group of chronic myeloid leukemia (CML-CP) and in group of chronic lymphocytic leukemia (CLL) were 76.32% (29/38) and 75.86% (22/29) respectively. Both CML-CP and CLL group showed a higher expression than control group (p = 0.0000, p = 0.0000 respectively). The expression of LDH in Cox-2 positive group was higher than that in Cox-2 negative group, and the difference between the two groups was statistically significant (p < 0.001). It is concluded that the expression of COX-2 protein can be detected in bone marrow cells of CML-CP and CLL and the expression level of LDH were higher in cells of CML-CP and CLL. The expression of COX-2 may be correlated with prognosis of CML-CP and CLL.