RNAi-mediated silencing of the Bmi-1 gene causes growth inhibition and enhances doxorubicin-induced apoptosis in MCF-7 cells

The oncogene Bmi-1 is a member of the Polycomb group gene family. Its expression is found to be greatly increased in a number of malignant tumors including breast cancer. This could suggest Bmi-1 as a potent therapeutic target. In this study, RNAi was introduced to down-regulate the expression of Bmi-1 in a highly malignant breast adenocarcinoma cell line, MCF-7. A thorough study of the biological behavior and chemosensitivity changes of the MCF-7 cells was carried out in context to the therapeutic potential of Bmi-1. The results obtained indicated that siRNA targeting of Bmi-1 could lead to an efficient and specific inhibition of endogenous Bmi-1 activity. The mRNA and protein expression of Bmi-1 were determined by RT-PCR and Western blot, respectively. Furthermore, silencing of Bmi-1 resulted in a drastic inhibition of the growth of MCF-7 cells as well as G(1) /S phase transition. The number of target cells was found to increase in phase G (0) /G (1) and decrease in the S phase, but no increase in the basal level of apoptosis was noticed. On the other hand, a reduction in the expression of cyclin D1 and an increase in the expression of p21 were also noticed. Silencing of Bmi-1 made the MCF-7 cells more sensitive to the chemotherapeutic agent doxorubicin and induced a significantly higher percentage of apoptotic cells. Here, we report on a study regarding the RNAi-mediated silencing of the Bmi-1 gene in breast cancer.     

Crystal structure of a methyltransferase from a no-known-vector Flavivirus

Presently known flaviviruses belong to three major evolutionary branches: tick-borne viruses, mosquito-borne viruses and viruses with no known vector. Here we present the crystal structure of the Yokose virus methyltransferase at 1.7 Å resolution, the first structure of a methyltransferase of a Flavivirus with no known vector. Structural comparison of three methyltransferases representative of each of the Flavivirus branches shows that fold and structures are closely conserved, most differences being related to surface loops flexibility. Analysis of the conserved residues throughout all the sequenced flaviviral methyltransferases reveals that, besides the central cleft hosting the substrate and cofactor binding sites, a second, almost continuous, patch is conserved and points away from active site towards the back of the protein. The high level of structural conservation in this region could be functional for the methyltransferase/RNA interaction and stabilization of the ensuing complex.     

The interstrand amino acid pairs play a significant role in determining the parallel or antiparallel orientation of β-strands

It is widely considered that it is not appropriate to treat β-pairs in isolation, since other secondary structural models (such as helices, coils), protein topology and protein tertiary structures would limit β-strand pairing. However, to understand the underlying mechanisms of β-sheet formation, studies ought to be performed separately on more concrete aspects. In this study, we focus on the parallel or antiparallel orientation of β-strands. First, statistical analysis was performed on the relative frequencies of the interstrand amino acid pairs within parallel and antiparallel β-strands. Consequently, features were extracted by singular value decomposition from the statistical results. By using the support vector machine to distinguish the features extracted from the two types of β-strands, high accuracy was achieved (up to 99.4%). This suggests that the interstrand amino acid pairs play a significant role in determining the parallel or antiparallel orientation of β-strands. These results may provide useful information for developing other useful algorithms to examine to the β-strand folding pathways, and could eventually lead to protein structure predictions.     

Examining mummichog growth and movement: Are some individuals making intra-season migrations to optimize growth?

We used a combination of field experiments and stable isotopes to examine mummichog growth and movement within a New England estuary. We documented physical and biological patterns within the estuary by caging individually-marked fish in enclosures at four locations along a coastal river and measuring environmental parameters (e.g., salinity, tidal inundation) and fish characteristics (e.g., gut-contents, growth, and stable isotope values) at each location. The upstream location was fresh (1 ppt) at low tide, and the downstream location was saline at high tide (32 ppt). The upstream and downstream locations had more tidal inundation than the intermediate location. Fish gut contents were dominated by terrestrial insects at the upstream location, by algae and detritus at the intermediate locations, and by aquatic insects at the downstream location. Fish grew fastest at the upstream location and slowest at the downstream location. Stable isotope values (δ¹³C and δ¹⁵N) of fish held in cages were significantly different at upstream, intermediate, and downstream locations. We transferred fish from one location to another in order to document how stable isotope values change when fish switch diets by moving within this estuary. Because differences in rates at which different tissue types approach the isotopic value of new diet sources can be used as a way to estimate the time since diet shift, we used the δ¹³C and δ¹⁵N values of liver and muscle as indicators of short term previous diet (liver) and longer term previous diet (muscle). We collected wild (uncaged) mummichogs from each location, and we compared their liver and muscle isotope values to values of fish that were transferred among locations. When fish were transferred from one location to another, their stable isotope values were intermediate between expected values at the previous and current locations. The liver approached stable isotope values representative of current location faster than muscle. Wild fish showed greater variation in stable isotope values than fish held in cages. Wild fish from the upstream location showed patterns in liver and muscle stable isotope values that were consistent with patterns in fish that were transferred from the downstream location to the upstream location (∼ 10 km away). These patterns in stable isotope values could have multiple causes including intra-season movement between downstream and upstream locations.     

Structural Alphabets for Protein Structure Classification: A Comparison Study

Finding structural similarities between proteins often helps reveal shared functionality, which otherwise might not be detected by native sequence information alone. Such similarity is usually detected and quantified by protein structure alignment. Determining the optimal alignment between two protein structures, however, remains a hard problem. An alternative approach is to approximate each three-dimensional protein structure using a sequence of motifs derived from a structural alphabet. Using this approach, structure comparison is performed by comparing the corresponding motif sequences or structural sequences. In this article, we measure the performance of such alphabets in the context of the protein structure classification problem. We consider both local and global structural sequences. Each letter of a local structural sequence corresponds to the best matching fragment to the corresponding local segment of the protein structure. The global structural sequence is designed to generate the best possible complete chain that matches the full protein structure. We use an alphabet of 20 letters, corresponding to a library of 20 motifs or protein fragments having four residues. We show that the global structural sequences approximate well the native structures of proteins, with an average coordinate root mean square of 0.69 Å over 2225 test proteins. The approximation is best for all α-proteins, while relatively poorer for all β-proteins. We then test the performance of four different sequence representations of proteins (their native sequence, the sequence of their secondary-structure elements, and the local and global structural sequences based on our fragment library) with different classifiers in their ability to classify proteins that belong to five distinct folds of CATH. Without surprise, the primary sequence alone performs poorly as a structure classifier. We show that addition of either secondary-structure information or local information from the structural sequence considerably improves the classification accuracy. The two fragment-based sequences perform better than the secondary-structure sequence but not well enough at this stage to be a viable alternative to more computationally intensive methods based on protein structure alignment.     

Efficiency Evaluation of Nozawa-Style Black Light Trap for Control of Anopheline Mosquitoes

House-residual spraying and insecticide-treated bed nets have achieved some success in controlling anthropophilic and endophagic vectors. However, these methods have relatively low efficacy in Korea because Anopheles sinensis, the primary malaria vector, is highly zoophilic and exophilic. So, we focused our vector control efforts within livestock enclosures using ultraviolet black light traps as a mechanical control measure. We found that black light traps captured significantly more mosquitoes at 2 and 2.5 m above the ground (P < 0.05). We also evaluated the effectiveness of trap spacing within the livestock enclosure. In general, traps spaced between 4 and 7 m apart captured mosquitoes more efficiently than those spaced closer together (P > 0.05). Based on these findings, we concluded that each black light trap in the livestock enclosures killed 7,586 female mosquitoes per trap per night during the peak mosquito season (July-August). In May-August 2003, additional concurrent field trials were conducted in Ganghwa county. We got 74.9% reduction (P < 0.05) of An. sinensis in human dwellings and 61.5% reduction (P > 0.05) in the livestock enclosures. The black light trap operation in the livestock enclosures proved to be an effective control method and should be incorporated into existing control strategies in developed countries.     

Prediction of Interacting Protein Pairs from Sequence Using a Bayesian Method

With the development of bioinformatics, more and more protein sequence information has become available. Meanwhile, the number of known protein–protein interactions (PPIs) is still very limited. In this article, we propose a new method for predicting interacting protein pairs using a Bayesian method based on a new feature representation. We trained our model using data on 6,459 PPI pairs from the yeast Saccharomyces cerevisiae core subset. Using six species of DIP database, our model demonstrates an average prediction accuracy of 93.67%. The result showed that our method is superior to other methods in both computing time and prediction accuracy.     

Automated classification of bird and amphibian calls using machine learning: A comparison of methods

We compared the ability of three machine learning algorithms (linear discriminant analysis, decision tree, and support vector machines) to automate the classification of calls of nine frogs and three bird species. In addition, we tested two ways of characterizing each call to train/test the system. Calls were characterized with four standard call variables (minimum and maximum frequencies, call duration and maximum power) or eleven variables that included three standard call variables (minimum and maximum frequencies, call duration) and a coarse representation of call structure (frequency of maximum power in eight segments of the call). A total of 10,061 isolated calls were used to train/test the system. The average true positive rates for the three methods were: 94.95% for support vector machine (0.94% average false positive rate), 89.20% for decision tree (1.25% average false positive rate) and 71.45% for linear discriminant analysis (1.98% average false positive rate). There was no statistical difference in classification accuracy based on 4 or 11 call variables, but this efficient data reduction technique in conjunction with the high classification accuracy of the SVM is a promising combination for automated species identification by sound. By combining automated digital recording systems with our automated classification technique, we can greatly increase the temporal and spatial coverage of biodiversity data collection.     

乙酰肝素酶重组慢病毒转基因和siRNA干扰质粒的构建及鉴定

目的：构建乙酰肝素酶重组慢病毒转基因和siRNA干扰质粒,为探讨HPSE在在肿瘤浸润转移过程中的分子机理奠定基础。方法：乙酰肝素酶cDNA全长扩增和最佳siRNA干扰片段筛选分别采用PCR和Real-time PCR方法,慢病毒系统载体分别使用pWPI和siRNA pSico系统,采用限制性内切酶快速连接方法联接目的基因和最佳最佳siRNA干扰片段,表达载体鉴定均采用核苷酸序列测定,HPSE重组慢病毒表达质粒和siRNA片段细胞转染采用脂质体转染法。结果：成功扩增乙酰肝素酶全长并连接入pWPI载体构建成重组表达载体HPSE-pWPI,重组质粒测序结果显与HPSE基因的同源性达99%。转染293T后有HPSE基因的表达。筛选出最佳siRNA干扰片段为HPSE-1222并成功插入pSico载体,构建成重组表达载体HPSE-siRNA pSico,重组载体测序显示与构建的shRNA结构序列完全一致。结论：成功采用慢病毒载体系统构建了乙酰肝素酶重组慢病毒转基因和siRNA干扰质粒,为探讨HPSE在在肿瘤浸润转移过程中的分子机理奠定基础。     

PBOND： Web Server for the Prediction of Proline and Non-Proline cis / trans Isomerization

PBOND is a web server that predicts the conformation of the peptide bond between any two amino acids. PBOND classifies the peptide bonds into one out of four classes, namely cis imide (cis-Pro), cis amide (cis-nonPro), trans imide (trans-Pro) and trans amide (trans-nonPro). Moreover, for every prediction a reliability index is computed. The underlying structure of the server consists of three stages: (1) feature extraction, (2) feature selection and (3) peptide bond clas- sification. PBOND can handle both s...