NGX6 gene inhibits cell proliferation and plays a negative role in EGFR pathway in nasopharyngeal carcinoma cells

Nasopharyngeal carcinoma (NPC) is a common cancer in South China but is rare in other parts of the world. A novel NPC-related gene was isolated by location candidate cloning strategy, whose expression was down-regulated in NPC. This gene was designated human NGX6 (Genbank accession AF188239) and encoded a predicted protein of 338 amino acids that harbors an EGF-like domain. The effects of NGX6 on cells from human NPC cell line HNE1 were investigated. The cells transfected with NGX6 had a markedly high expression of NGX6, leading to significant decrease in cell proliferation and the capability to form colonies in soft agar, delaying the G0-G1 cell cycle progression. Flow cytometry assay indicated that the expression of cyclin D1 significantly decreased in NGX6-transfected HNE1 cells as well as cyclin A and E. There was a delay in tumor formation and a dramatic reduction in tumor size when cells transfected with NGX6 were injected into nude mice. In another way, we found NGX6 played a negative role in EGFR Ras/Mek/MAPK pathway. We propose that NGX6, as an EGF-like domain gene, could delay cell cycle G0-G1 progression and thus inhibit cell proliferation by negatively regulating EGFR pathway in NPC cells and down-regulating the expression of cyclin D1 and E.     

Molecular evolution and multilocus sequence typing of 145 strains of SARS-CoV

In this study, we have identified 876 polymorphism sites in 145 complete or partial genomes of SARS-CoV available in the NCBI GenBank. One hundred and seventy-four of these sites existed in two or more SARS-CoV genome sequences. According to the sequence polymorphism, all SARS-CoVs can be divided into three groups: (I) group 1, animal-origin viruses (such as SARS-CoV SZ1, SZ3, SZ13 and SZ16); (II) group 2, all viruses with clinical origin during first epidemic; and (III) group 3, SARS-CoV GD03T0013. According to 10 special loci, group 2 again can be divided into genotypes C and T, which can be further divided into sub-genotypes C1-C4 and T1-T4. Positive Darwinian selections were identified between any pair of these three groups. Genotype C gives neutral selection. Genotype T, however, shows negative selection. By comparing the death rates of SARS patients in the different regions, it was found that the death rate caused by the viruses of the genotype C was lower than that of the genotype T. SARS-CoVs might originate from an unknown ancestor.     

Allosteric aptamers: targeted reversibly attenuated probes

Aptamers are unique nucleic acids with regulatory potentials that differ markedly from those of proteins. A significant feature of aptamers not possessed by proteins is their ability to participate in at least two different types of three-dimensional structure: a single-stranded folded structure that makes multiple contacts with the aptamer target and a double-helical structure with a complementary nucleic acid sequence. We have made use of this structural flexibility to develop an aptamer-based biosensor (a targeted reversibly attenuated probe, TRAP) in which hybridization of a cis-complementary regulatory nucleic acid (attenuator) controls the ability of the aptamer to bind to its target molecule. The central portion of the TRAP, between the aptamer and the attenuator, is complementary to a target nucleic acid, such as an mRNA, which is referred to as a regulatory nucleic acid (regNA) because it regulates the activity of the aptamer in the TRAP by hybridization with the central (intervening) sequence. The studies reported here of the ATP-DNA TRAP suggest that, as well as inhibiting the aptamer, the attenuator also acts as a structural guide, much like a chaperone, to promote proper folding of the TRAP such that it can be fully activated by the regDNA. We also show that activation of the aptamer in the TRAP by the complementary nucleic acid at physiological temperatures is sensitive to single-base mismatches. Aptamers that can be regulated by a specific nucleic sequence such as in an mRNA have potential for many in vivo applications including regulating a particular enzyme or signal transduction pathway or imaging gene expression in vivo.     

Growth and fatty acid composition of Nannochloropsis sp. grown mixotrophically in fed-batch culture

The cell growth and eicosapentaenoic acid (EPA) yields of Nannochloropsis sp. were enhanced in the fed-batch cultures. With feeding glucose solution, the biomass reached 1.1 g dry wt l(-1) after 10 days' culture, which was 40% higher than that obtained in the batch culture (0.8 g dry wt l(-1)). With supplement of nitrate solution, the biomass reached 1 g dry wt l(-1), and reached the stationary phase 2 days earlier than the others. The maximum of biomass (1.2 g dry wt l(-1)) was obtained with the supplement of the mixture of glucose and nitrate solution. The EPA yields of Nannochloropsis sp. after 10 days' growth in the fed-batch cultures were 52 mg l(-1), 43 mg l(-1) and 56 mg l(-1) with, respectively, addition of nitrate, glucose and both together. In batch culture only 35 mg EPA l(-1) was obtained.     

Improved use of organic phosphate by Skeletonema costatum through regulation of Zn2 + concentrations

The maximum growth rate (1.4-2 x 10(5) cells ml(-1) d(-1)), cell final yields (2.6-5.2 x 10(5) cells ml(-1)) and extracellular alkaline phosphatase activity (2.4-10.6 microg phosphate released ml(-1) h(-1)) of the red tide alga, Skeletonema costatum, increased when Zn2+ was increased from 0 to 24 pM, but decreased with 66 pM Zn2+ in growth medium with glycerophosphate as the sole phosphorus source. Extracellular carbonic anhydrase activity and the affinity for HCO3- and CO2 uptake increased when Zn2+ was increased from 0 to 12 pM, but then decreased at higher concentrations. The results suggested that utilization of organic phosphate required more Zn2+ than the uptake of inorganic carbon did, while utilization of dissolved inorganic carbon by Skeletonema costatum was very sensitive to Zn2+ concentration variations.     

Utilization of Nitrite as a Nitrogen Source by Botryococcus Braunii

Nitrite at 2 mM did not affect the growth of Botryococcus braunii and served as the sole nitrogen source giving a minimum biomass doubling time of 4.2 d, which was equal to that of the culture using 4 mM nitrate as nitrogen source. With nitrite at 4 mM, after a lag phase of about 10 d, the alga grew quickly, reaching 1.1 g l(-1) at the end. Respective nitrite removals were 100% and 99.7%. There were few differences in the hydrocarbons produced using different nitrogen sources.     

Casein kinase Iepsilon modulates the signaling specificities of dishevelled

Wnt signaling is critical to many aspects of development, and aberrant activation of the Wnt signaling pathway can cause cancer. Dishevelled (Dvl) protein plays a central role in this pathway by transducing the signal from the Wnt receptor complex to the beta-catenin destruction complex. Dvl also plays a pivotal role in the planar cell polarity pathway that involves the c-Jun N-terminal kinase (JNK). How functions of Dvl are regulated in these two distinct pathways is not clear. We show that deleting the C-terminal two-thirds of Dvl, which includes the PDZ and DEP domains and is essential for Dvl-induced JNK activation, rendered the molecule a much more potent activator of the beta-catenin pathway. We also found that casein kinase Iepsilon (CKIepsilon), a previously identified positive regulator of Wnt signaling, stimulated Dvl activity in the Wnt pathway, but dramatically inhibited Dvl activity in the JNK pathway. Consistent with this, overexpression of CKIepsilon in Drosophila melanogaster stimulated Wnt signaling and disrupted planar cell polarity. We also observed a correlation between the localization and the signaling activity of Dvl in the beta-catenin pathway and the JNK pathway. Furthermore, by using RNA interference, we demonstrate that the Drosophila CKIepsilon homologue Double time positively regulates the beta-catenin pathway through Dvl and negatively regulates the Dvl-induced JNK pathway. We suggest that CKIepsilon functions as a molecular switch to direct Dvl from the JNK pathway to the beta-catenin pathway, possibly by altering the conformation of the C terminus of Dvl.     

Effect of training datasets on support vector machine prediction of protein-protein interactions

Knowledge of protein-protein interaction is useful for elucidating protein function via the concept of 'guilt-by-association'. A statistical learning method, Support Vector Machine (SVM), has recently been explored for the prediction of protein-protein interactions using artificial shuffled sequences as hypothetical noninteracting proteins and it has shown promising results (Bock, J. R., Gough, D. A., Bioinformatics 2001, 17, 455-460). It remains unclear however, how the prediction accuracy is affected if real protein sequences are used to represent noninteracting proteins. In this work, this effect is assessed by comparison of the results derived from the use of real protein sequences with that derived from the use of shuffled sequences. The real protein sequences of hypothetical noninteracting proteins are generated from an exclusion analysis in combination with subcellular localization information of interacting proteins found in the Database of Interacting Proteins. Prediction accuracy using real protein sequences is 76.9% compared to 94.1% using artificial shuffled sequences. The discrepancy likely arises from the expected higher level of difficulty for separating two sets of real protein sequences than that for separating a set of real protein sequences from a set of artificial sequences. The use of real protein sequences for training a SVM classification system is expected to give better prediction results in practical cases. This is tested by using both SVM systems for predicting putative protein partners of a set of thioredoxin related proteins. The prediction results are consistent with observations, suggesting that real sequence is more practically useful in development of SVM classification system for facilitating protein-protein interaction prediction.