Reconstruction and In Silico Analysis of Metabolic Network for an Oleaginous Yeast,Yarrowia lipolytica

With the emergence of energy scarcity, the use of renewable energy sources such as biodiesel is becoming increasingly necessary. Recently, many researchers have focused their minds on Yarrowia lipolytica, a model oleaginous yeast, which can be employed to accumulate large amounts of lipids that could be further converted to biodiesel. In order to understand the metabolic characteristics of Y. lipolytica at a systems level and to examine the potential for enhanced lipid production, a genome-scale compartmentalized metabolic network was reconstructed based on a combination of genome annotation and the detailed biochemical knowledge from multiple databases such as KEGG, ENZYME and BIGG. The information about protein and reaction associations of all the organisms in KEGG and Expasy-ENZYME database was arranged into an EXCEL file that can then be regarded as a new useful database to generate other reconstructions. The generated model iYL619_PCP accounts for 619 genes, 843 metabolites and 1,142 reactions including 236 transport reactions, 125 exchange reactions and 13 spontaneous reactions. The in silico model successfully predicted the minimal media and the growing abilities on different substrates. With flux balance analysis, single gene knockouts were also simulated to predict the essential genes and partially essential genes. In addition, flux variability analysis was applied to design new mutant strains that will redirect fluxes through the network and may enhance the production of lipid. This genome-scale metabolic model of Y. lipolytica can facilitate system-level metabolic analysis as well as strain development for improving the production of biodiesels and other valuable products by Y. lipolytica and other closely related oleaginous yeasts.     

Genetic Diversity and Population Structure Patterns in Chinese Cherry (<Emphasis Type="Italic">Prunus pseudocerasus</Emphasis> Lindl) Landraces

Chinese cherry (Prunus pseudocerasus Lindl.) is an ancient fruit crop with highly economic and ornamental values. It originated in China and the cultivation history can be traced back to 3,000 - 4,000 years ago. Over such a long-term domestication process, a large number of genetic variations have been accumulated in different landraces. However, their utilization for cultivar improvement is limited by the scarcity of information involving genetic diversity and population structure. Here, 17 populations comprised of 140 individuals were collected from four geographic areas: Sichuan Basin (SC), Qinglin Mountain (QL), Yungui Plateau (YG) and North of China (NC), and analyzed using a set of 20 microsatellite markers. In total, 126 polymorphic loci were generated, with 6.3 loci per primer. The global expected heterozygosity (He = 0.63) and Shannon information index (I = 1.23) implied a moderately high level of genetic variation. Two major clusters (cluster 1 and cluster 2) were demonstrated based on population structure analysis, which implied the presence of two potential domestication sites of Chinese cherry landraces. Individuals from SC were assigned to cluster 1 and those from QL, YG and NC were grouped into cluster 2. Samples from QL region contained the most plentiful admixture genetic components, implied the possibility of being one transition region of genetic variation. Moreover, botanical characteristics, such as long lifespan, inbreeding preference as well as vegetative propagation, might lead to a relatively low level but significant genetic divergence among populations. Finally, conservation strategies were proposed to protect these valuable natural germplasm based on these results.     

Regulation of Opioid Receptors by Their Endogenous Opioid Peptides

Cellular and Molecular Neurobiology - Activation of μ, δ, and κ opioid receptors by endogenous opioid peptides leads to the regulation of many emotional and physiological responses....     

Proteomic Analysis of Fetal Ovary Reveals That Ovarian Developmental Potential Is Greater in Meishan Pigs than in Yorkshire Pigs

Time-dependent expression of functional proteins in fetal ovaries is important to understand the developmental process of the ovary. This study was carried out to enhance our understanding of the developmental process of porcine fetal ovaries and to better address the differences in fetal ovary development of local and foreign pigs. The objective of the present study is to test the expression of key proteins that regulate the growth and development of fetal ovaries in Meishan and Yorkshire porcine breeds by using proteomics technology. Six Meishan and 6 Yorkshire pregnant gilts were used in this experiment. Fetal ovaries were obtained from Yorkshire and Meishan gilts on days 55 and 90 of the gestation period. Using 2D-DIGE (two dimensional-difference in gel electrophoresis) analysis, the results showed that there are about 1551 and 1400 proteins in gilt fetal ovaries on days 55 and 90, respectively of the gestation. Using MALDI TOF-TOF MS analysis, 27 differentially expressed proteins were identified in the fetal ovaries of the 2 breeds on day 55 of gestation, and a total of 18 proteins were identified on day 90 of gestation. These differentially expressed proteins were involved in the regulation of biological processes (cell death, stress response, cytoskeletal proteins) and molecular functions (enzyme regulator activity). We also found that alpha-1-antitrypsin, actin, vimentin, and PP2A proteins promote the formation of primordial follicles in the ovaries of Yorkshire pigs on day 55 of gestation while low expression heat shock proteins and high expression alpha-fetoproteins (AFP) may promote Meishan fetal ovarian follicular development on day 90 of gestation. These findings provide a deeper understanding of how reduced expression of heat shock proteins and increased expression of AFP can significantly reduce the risk of reproductive disease in obese Meishan sows. Our study also shows how these proteins can increase the ovulation rate and may be responsible for the low reproductive efficiency reported in other obese breeds. The ovarian developmental potential was found to be greater in Meishan pigs than in Yorkshire pigs.     

Rationally Targeted Mutations at the V1V2 Domain of the HIV-1 Envelope to Augment Virus Neutralization by Anti-V1V2 Monoclonal Antibodies

HIV-1 envelope glycoproteins (Env) are the only viral antigens present on the virus surface and serve as the key targets for virus-neutralizing antibodies. However, HIV-1 deploys multiple strategies to shield the vulnerable sites on its Env from neutralizing antibodies. The V1V2 domain located at the apex of the HIV-1 Env spike is known to encompass highly variable loops, but V1V2 also contains immunogenic conserved elements recognized by cross-reactive antibodies. This study evaluates human monoclonal antibodies (mAbs) against V2 epitopes which overlap with the conserved integrin α4β7-binding LDV/I motif, designated as the V2i (integrin) epitopes. We postulate that the V2i Abs have weak or no neutralizing activities because the V2i epitopes are often occluded from antibody recognition. To gain insights into the mechanisms of the V2i occlusion, we evaluated three elements at the distal end of the V1V2 domain shown in the structure of V2i epitope complexed with mAb 830A to be important for antibody recognition of the V2i epitope. Amino-acid substitutions at position 179 that restore the LDV/I motif had minimal effects on virus sensitivity to neutralization by most V2i mAbs. However, a charge change at position 153 in the V1 region significantly increased sensitivity of subtype C virus ZM109 to most V2i mAbs. Separately, a disulfide bond introduced to stabilize the hypervariable region of V2 loop also enhanced virus neutralization by some V2i mAbs, but the effects varied depending on the virus. These data demonstrate that multiple elements within the V1V2 domain act independently and in a virus-dependent fashion to govern the antibody recognition and accessibility of V2i epitopes, suggesting the need for multi-pronged strategies to counter the escape and the shielding mechanisms obstructing the V2i Abs from neutralizing HIV-1.     

Generation of “Virtual” Control Groups for Single Arm Prostate Cancer Adjuvant Trials

It is difficult to construct a control group for trials of adjuvant therapy (Rx) of prostate cancer after radical prostatectomy (RP) due to ethical issues and patient acceptance. We utilized 8 curve-fitting models to estimate the time to 60%, 65%, … 95% chance of progression free survival (PFS) based on the data derived from Kattan post-RP nomogram. The 8 models were systematically applied to a training set of 153 post-RP cases without adjuvant Rx to develop 8 subsets of cases (reference case sets) whose observed PFS times were most accurately predicted by each model. To prepare a virtual control group for a single-arm adjuvant Rx trial, we first select the optimal model for the trial cases based on the minimum weighted Euclidean distance between the trial case set and the reference case set in terms of clinical features, and then compare the virtual PFS times calculated by the optimum model with the observed PFSs of the trial cases by the logrank test. The method was validated using an independent dataset of 155 post-RP patients without adjuvant Rx. We then applied the method to patients on a Phase II trial of adjuvant chemo-hormonal Rx post RP, which indicated that the adjuvant Rx is highly effective in prolonging PFS after RP in patients at high risk for prostate cancer recurrence. The method can accurately generate control groups for single-arm, post-RP adjuvant Rx trials for prostate cancer, facilitating development of new therapeutic strategies.