Prediction of protein structural classes for low-homology sequences based on predicted secondary structure

<p>Abstract</p> <p>Background</p> <p>Prediction of protein structural classes (<it>α</it>, <it>β</it>, <it>α </it>+ <it>β </it>and <it>α</it>/<it>β</it>) from amino acid sequences is of great importance, as it is beneficial to study protein function, regulation and interactions. Many methods have been developed for high-homology protein sequences, and the prediction accuracies can achieve up to 90%. However, for low-homology sequences whose average pairwise sequence identity lies between 20% and 40%, they perform relatively poorly, yielding the prediction accuracy often below 60%.</p> <p>Results</p> <p>We propose a new method to predict protein structural classes on the basis of features extracted from the predicted secondary structures of proteins rather than directly from their amino acid sequences. It first uses PSIPRED to predict the secondary structure for each protein sequence. Then, the <it>chaos game representation </it>is employed to represent the predicted secondary structure as two time series, from which we generate a comprehensive set of 24 features using <it>recurrence quantification analysis</it>, <it>K-string based information entropy </it>and <it>segment-based analysis</it>. The resulting feature vectors are finally fed into a simple yet powerful Fisher's discriminant algorithm for the prediction of protein structural classes. We tested the proposed method on three benchmark datasets in low homology and achieved the overall prediction accuracies of 82.9%, 83.1% and 81.3%, respectively. Comparisons with ten existing methods showed that our method consistently performs better for all the tested datasets and the overall accuracy improvements range from 2.3% to 27.5%. A web server that implements the proposed method is freely available at <url>http://www1.spms.ntu.edu.sg/~chenxin/RKS_PPSC/</url>.</p> <p>Conclusion</p> <p>The high prediction accuracy achieved by our proposed method is attributed to the design of a comprehensive feature set on the predicted secondary structure sequences, which is capable of characterizing the sequence order information, local interactions of the secondary structural elements, and spacial arrangements of <it>α </it>helices and <it>β </it>strands. Thus, it is a valuable method to predict protein structural classes particularly for low-homology amino acid sequences.</p

Targeted gene delivery in tumor xenografts by the combination of ultrasound-targeted microbubble destruction and polyethylenimine to inhibit survivin gene expression and induce apoptosis

<p>Abstract</p> <p>Background</p> <p>Noninvasive and tissue-specific technologies of gene transfection would be valuable in clinical gene therapy. This present study was designed to determine whether it could enhance gene transfection <it>in vivo </it>by the combination of ultrasound-targeted microbubble destruction (UTMD) with polyethylenimine (PEI) in tumor xenografts, and illuminate the effects of gene silencing and apoptosis induction with short hairpin RNA (shRNA) interference therapy targeting human survivin by this novel technique.</p> <p>Methods</p> <p>Two different expression vectors (pCMV-LUC and pSIREN) were incubated with PEI to prepare cationic complexes (PEI/DNA) and confirmed by the gel retardation assay. Human cervical carcinoma (Hela) tumors were planted subcutaneously in both flanks of nude mice. Tumor-bearing mice were administered by tail vein with PBS, plasmid, plasmid and SonoVue microbubble, PEI/DNA and SonoVue microbubble. One tumor was exposed to ultrasound irradiation, while the other served as control. The feasibility of targeted delivery and tissue specificity facilitated by UTMD and PEI were investigated. Moreover, immunohistochemistry analyses about gene silencing and apoptosis induction were detected.</p> <p>Results</p> <p>Electrophoresis experiment revealed that PEI could condense DNA efficiently. The application of UTMD significantly increases the tissue transfection. Both expression vectors showed that gene expressions were present in all sections of tumors that received ultrasound exposure but not in control tumors. More importantly, the increases in transgene expression were related to UTMD with the presence of PEI significantly. Silencing of the survivin gene could induce apoptosis effectively by downregulating survivin and bcl-2 expression, also cause up-regulation of bax and caspase-3 expression.</p> <p>Conclusions</p> <p>This noninvasive, novel combination of UTMD with PEI could enhance targeted gene delivery and gene expression in tumor xenografts at intravenous administration effectively without causing any apparently adverse effect, and might be a promising candidate for gene therapy. Silencing of survivin gene expression with shRNA could be facilitated by this non-viral technique, and lead to significant cell apoptosis.</p

Functional Promoter -31G>C Variant in Survivin Gene Is Associated with Risk and Progression of Renal Cell Cancer in a Chinese Population

BACKGROUND: Survivin is an inhibitor of apoptosis protein and is involved in the occurrence and progression of human malignancies. Recently, a functional polymorphism (-31G>C, rs9904341) in the promoter of survivin has been shown to influence its expression and confer susceptibility to different types of cancer. The present study was aimed to investigate whether the polymorphism also influences susceptibility and progression of renal cell cancer (RCC) in a Chinese population. METHODS: We genotyped this polymorphism using the TaqMan assay in a case-control study comprised of 710 RCC patients and 760 controls. The logistic regression was used to assess the genetic association with occurrence and progression of RCC. RESULTS: Compared with the genotypes containing G allele (GG and GC), we found a statistically significant increased occurrence of RCC associated with the CC genotype [P = 0.006, adjusted odds ratio (OR) = 1.38, 95% confidence interval (CI) = 1.08-1.76]. The polymorphism was associated with risk of developing advanced stage (OR = 2.02, 95%CI = 1.34-3.07) and moderately differentiated (OR = 1.75; 95%CI = 1.20-2.54) RCC. Furthermore, the patients carrying the CC genotype had a significantly greater prevalence of high clinical stage disease (P(trend) = 0.003). Similar results were also observed when we restricted the analysis to clear cell RCC, a major histological type of RCC. CONCLUSIONS: Our results suggest that the functional -31G>C polymorphism in the promoter of survivin may influence the susceptibility and progression of RCC in the Chinese population. Large population-based prospective studies are required to validate our findings

Interactions of the Apolipoprotein A5 Gene Polymorphisms and Alcohol Consumption on Serum Lipid Levels

Little is known about the interactions of apolipoprotein (Apo) A5 gene polymorphisms and alcohol consumption on serum lipid profiles. The present study was undertaken to detect the interactions of ApoA5-1131T>C, c.553G>T and c.457G>A polymorphisms and alcohol consumption on serum lipid levels.A total of 516 nondrinkers and 514 drinkers were randomly selected from our previous stratified randomized cluster samples. Genotyping was performed by polymerase chain reaction and restriction fragment length polymorphism. The levels of serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), ApoA1 and ApoB were higher in drinkers than in nondrinkers (P<0.05-0.001). The genotypic and allelic frequencies of three loci were not different between the two groups. The interactions between -1131T>C genotypes and alcohol consumption on ApoB levels (P<0.05) and the ApoA1/ApoB ratio (P<0.01), between c.553G>T genotypes and alcohol consumption on low-density lipoprotein cholesterol (LDL-C) levels (P<0.05) and the ApoA1/ApoB ratio (P<0.05), and between c.457G>A genotypes and alcohol consumption on TG levels (P<0.001) were detected by factorial regression analysis after controlling for potential confounders. Four haplotypes (T-G-G, C-G-G, T-A-G and C-G-T) had frequencies ranging from 0.06 to 0.87. Three haplotypes (C-G-G, T-A-G, and C-G-T) were significantly associated with serum lipid parameters. The -1131T>C genotypes were correlated with TG, and c.553G>T and c.457G>A genotypes were associated with HDL-C levels in nondrinkers (P<0.05 for all). For drinkers, the -1131T>C genotypes were correlated with TC, TG, LDL-C, ApoB levels and the ApoA1/ApoB ratio (P<0.01 for all); c.553G>T genotypes were correlated with TC, TG, HDL-C and LDL-C levels (P<0.05-0.01); and c.457G>A genotypes were associated with TG, LDL-C, ApoA1 and ApoB levels (P<0.05-0.01).The differences in some serum lipid parameters between the drinkers and nondrinkers might partly result from different interactions of the ApoA5 gene polymorphisms and alcohol consumption

Data-driven modeling of maritime transportation : key issues, challenges, and solutions

202306 bckwVersion of RecordOthersNational Natural Science Foundation of ChinaEarly releas

Implications of the EU’s inclusion of maritime transport in emissions trading system for shipping companies

202108 bchyVersion of RecordSelf-fundedPublishe

Periodontal treatment affects gene expression of EPCs in DM patients

Poster Session: Microbiology, Antimicrobials and Oral-systemic Interplay in Periodontal Therap