P53参与抑制PC-1基因转录的结构域分析

目的:分析P53分子参与抑制PC-1基因转录的结构域。方法:构建P53分子突变体;将前列腺癌LNCaP细胞瞬时转染野生型或突变型p53及含PC-1启动子的荧光素酶表达载体p4939,分析PC-1启动子的转录活性。结果:P53分子N端转录激活域及富含脯氨酸功能域突变体没有减弱对PC-1启动子的转录抑制作用,而特异性DNA结合域上175、273位突变体和C端339～346位氨基酸的缺失突变体都减弱了对PC-1启动子转录的抑制作用;另外P53分子第175和273位突变体在前列腺癌细胞中对野生型P53的转录抑制功能表现出显性负效应。结论:P53分子特异性DNA结合域和C端结构域参与对PC-1基因启动子的转录抑制,而P53突变体的显性负效应可能是PC-1在前列腺癌进展中表达失调的因素之一。     

Redistribution of carbon flux in Torulopsis glabrata by altering vitamin and calcium level

Manipulation of cofactor (thiamine, biotin and Ca(2+)) levels as a potential tool to redistribute carbon flux was studied in Torulopsis glabrata. With sub-optimization of vitamin in fermentation medium, the carbon flux was blocked at the key node of pyruvate, and 69 g/L pyruvate was accumulated. Increasing the concentrations of thiamine and biotin could selectively open the valve of carbon flux from pyruvate to pyruvate dehydrogenase complex, the pyruvate carboxylase (PC) pathway and the channel into the TCA cycle, leading to the over-production of alpha-ketoglutarate. In addition, the activity of PC was enhanced with Ca(2+) present in fermentation medium. By combining high concentration's vitamins and CaCO(3) as the pH buffer, a batch culture was conducted in a 7-L fermentor, with the pyruvate concentration decreased to 21.8 g/L while alpha-ketoglutarate concentration increased to 43.7 g/L. Our study indicated that the metabolic flux could be redistributed to overproduce desired metabolites with manipulating the cofactor levels. Furthermore, the manipulation of vitamin level provided an alternative tool to realize metabolic engineering goals.     

Development of photoreceptor-specific promoters and their utility to investigate EIAV lentiviral vector mediated gene transfer to photoreceptors

BACKGROUND: We wanted to investigate the ability of recombinant equine infectious anemia virus (EIAV) vectors to transduce photoreceptor cells by developing a series of photoreceptor-specific promoters that drive strong gene expression in photoreceptor cells. METHODS: Promoter fragments derived from the rhodopsin (RHO), the beta phosphodiesterase (PDE) and the retinitis pigmentosa (RP1) genes were cloned in combination with an enhancer element, derived from the interphotoreceptor retinoid-binding protein gene (IRBP), into luciferase reporter plasmids. An in vitro transient reporter assay was carried out in the human Y-79 retinoblastoma cell line. The optimal promoters from this screen were then cloned into the recombinant EIAV vector for evaluation in vivo following subretinal delivery into mice. RESULTS: All promoters maintained a photoreceptor-specific expression profile in vitro and the gene expression was further enhanced in combination with the IRBP enhancer. The use of IRBP-combined RHO or PDE promoters showed modest but exclusive expression in photoreceptors following subretinal delivery to mice. By contrast an EIAV vector containing the cytomegalovirus (CMV) promoter drove reporter gene expression in both photoreceptors and retinal pigment epithelium. CONCLUSIONS: It may be possible to use recombinant EIAV vectors containing photoreceptor-specific promoters to drive therapeutic gene expression to treat a range of retinal degenerative diseases where the photoreceptor cell is the primary disease target.     

Ginsenosides promote proliferation of chicken primordial germ cells via PKC-involved activation of NF-kappaB

The effect of ginsenosides on proliferation of chicken primordial germ cells (PGCs) was evaluated and involvement of nuclear factor (NF)-kappaB in the signaling pathway was investigated. PGCs were isolated from the genital ridge of 3.5-4 day embryos and cultured in Medium 199 supplemented with 5% FCS and 10 ng/ml LIF. PGCs subcultured on chicken embryonic fibroblast feeder were challenged with ginsenosides alone or in combination with PKC inhibitor H(7) or activator phorbol 12-myristate 13-acetate (PMA) for 24h. Moreover, the translocation of NF-kappaB and degradation level of IkappaBalpha were investigated by Western blot analysis. Results show that PGCs were identified by periodic acid-Schiff, alkaline phosphatase histochemistry as well as c-kit, SSEA-1 and Oct-4 immunocytochemistry. Treatment with ginsenosides at 1-100 microg/ml significantly increased the number and area of PGC colonies in a dose-dependent manner. However, this proliferating effect was obviously attenuated by combined treatment of H(7) (10(-7)-10(-5)M). Similarly, PKC staining of PGC colonies was more intensive after ginsenosides treatment compared with the control group. In addition, treatment with ginsenosides at 1-10 microg/ml stimulated the translocation of NF-kappaB (p65). However, the NF-kappaB translocation and the degradation of IkappaBalpha were significantly blocked by combined treatment with 10(-6)M H(7). These results indicated that ginsenosides promote proliferation of chicken PGCs through activation of PKC-involved NF-kappaB signaling pathway.     

Probability-based pattern recognition and statistical framework for randomization: modeling tandem mass spectrum/peptide sequence false match frequencies

MOTIVATION: In proteomics, reverse database searching is used to control the false match frequency for tandem mass spectrum/peptide sequence matches, but reversal creates sequences devoid of patterns that usually challenge database-search software. RESULTS: We designed an unsupervised pattern recognition algorithm for detecting patterns with various lengths from large sequence datasets. The patterns found in a protein sequence database were used to create decoy databases using a Monte Carlo sampling algorithm. Searching these decoy databases led to the prediction of false positive rates for spectrum/peptide sequence matches. We show examples where this method, independent of instrumentation, database-search software and samples, provides better estimation of false positive identification rates than a prevailing reverse database searching method. The pattern detection algorithm can also be used to analyze sequences for other purposes in biology or cryptology. AVAILABILITY: On request from the authors. SUPPLEMENTARY INFORMATION: http://bioinformatics.psb.ugent.be/.     

A structural alignment kernel for protein structures

MOTIVATION: This work aims to develop computational methods to annotate protein structures in an automated fashion. We employ a support vector machine (SVM) classifier to map from a given class of structures to their corresponding structural (SCOP) or functional (Gene Ontology) annotation. In particular, we build upon recent work describing various kernels for protein structures, where a kernel is a similarity function that the classifier uses to compare pairs of structures. RESULTS: We describe a kernel that is derived in a straightforward fashion from an existing structural alignment program, MAMMOTH. We find in our benchmark experiments that this kernel significantly out-performs a variety of other kernels, including several previously described kernels. Furthermore, in both benchmarks, classifying structures using MAMMOTH alone does not work as well as using an SVM with the MAMMOTH kernel. AVAILABILITY: http://noble.gs.washington.edu/proj/3dkernel     

Robust smooth segmentation approach for array CGH data analysis

MOTIVATION: Array comparative genomic hybridization (aCGH) provides a genome-wide technique to screen for copy number alteration. The existing segmentation approaches for analyzing aCGH data are based on modeling data as a series of discrete segments with unknown boundaries and unknown heights. Although the biological process of copy number alteration is discrete, in reality a variety of biological and experimental factors can cause the signal to deviate from a stepwise function. To take this into account, we propose a smooth segmentation (smoothseg) approach. METHODS: To achieve a robust segmentation, we use a doubly heavy-tailed random-effect model. The first heavy-tailed structure on the errors deals with outliers in the observations, and the second deals with possible jumps in the underlying pattern associated with different segments. We develop a fast and reliable computational procedure based on the iterative weighted least-squares algorithm with band-limited matrix inversion. RESULTS: Using simulated and real data sets, we demonstrate how smoothseg can aid in identification of regions with genomic alteration and in classification of samples. For the real data sets, smoothseg leads to smaller false discovery rate and classification error rate than the circular binary segmentation (CBS) algorithm. In a realistic simulation setting, smoothseg is better than wavelet smoothing and CBS in identification of regions with genomic alterations and better than CBS in classification of samples. For comparative analyses, we demonstrate that segmenting the t-statistics performs better than segmenting the data. AVAILABILITY: The R package smoothseg to perform smooth segmentation is available from http://www.meb.ki.se/~yudpaw.     

Expression and homology modeling of sterol 14alpha-demethylase from Penicillium digitatum

Green mold of citrus, caused by Penicillium digitatum, is the most serious postharvest disease of citrus. Sterol 14alpha-demethylase (CYP51) is one of the key enzymes of sterol biosynthesis in biological kingdoms and is a prime target of antifungal drugs. To exploit novel 14alpha-demethylase inhibitor (DMI) fungicides, DNA and total RNA were isolated from P. digitatum. The CYP51 of P. digitatum was cloned and expressed in Escherichia coli, yielding recombinant protein with a molecular weight of c. 59 kDa. The P. digitatum CYP51 protein (PdCYP51) was purified and polyclonal antibodies were prepared. Compared with the sequence of P. digitatum PD5 in GenBank, there were four mutated nucleotides which resulted in four mutated amino acids. The three-dimensional (3D) model of P. digitatum CYP51 was established based on structure template of 1e9x.pdb and diniconazole was docked into the active site by FlexX. According to spectral data, it is suggested that the purified soluble protein had high affinity with diniconazole, a potent inhibitor of CYP51 reaction in fungi. At the same time, these spectral data suggested that the 3D model and the docking model were reasonable, which we hope can be used to provide a virtual screening of novel DMI drugs.