Biomedical subjects

Xiao-Chen Bo

Publications and source records attributed to Xiao-Chen Bo.

3 recordsLinked to original sources

PubMed2005

Effective siRNA targets screening for human telomerase reverse transcriptase.

AIM: To study the inhibitory effects of siRNAs targeting different hTERT sequences and to screen the effective siRNA sequence. METHODS: Five double-stranded siRNAs targeting coding and non-coding regions of hTERT gene were designed and synthesized by T7 transcription system in vitro. siRNA4 sequence was screened by full length gene targeting technique and the rest of the siRNA sequences were selected randomly. After being purified by ethanol precipitation, the siRNAs were transfected to the human hepatocellular carcinoma cell (HepG2) by Lipofectamine 2000. At 48-72 h after siRNAs transfection, MTT assay, RT-PCR and Western-blot were applied to evaluate the effects of siRNAs on cell growth, mRNA and protein expression level of hTERT gene, respectively. RESULTS: Compared to the control cells, the cells treated with the five double-stranded siRNAs exhibited different degrees of inhibition of cell proliferation in a dose-dependent manner. siRNA2 and siRNA4, exhibited obvious effects of inhibiting hTERT mRNA and protein expression in HepG2 cells. CONCLUSION: siRNAs targeting different hTERT sequences have significantly various inhibitory effects on hTERT gene expression. The siRNA sequence screened by full length gene targeting technique has comparable inhibitory effect with the rest siRNA sequences screened by random selection, suggesting that siRNAs and antisense oligonucleic acids may have the same effective target sites. Compared with chemical synthesis method, synthesizing double-stranded siRNA by T7 transcription system in vitro is a rapid, simple, and inexpensive method suitable for screening high-effect siRNA targeting site for specific gene.

Carcinoma, Hepatocellular↗

PubMed2005

HBVPathDB: a database of HBV infection-related molecular interaction network.

AIM: To describe molecules or genes interaction between hepatitis B viruses (HBV) and host, for understanding how virus' and host's genes and molecules are networked to form a biological system and for perceiving mechanism of HBV infection. METHODS: The knowledge of HBV infection-related reactions was organized into various kinds of pathways with carefully drawn graphs in HBVPathDB. Pathway information is stored with relational database management system (DBMS), which is currently the most efficient way to manage large amounts of data and query is implemented with powerful Structured Query Language (SQL). The search engine is written using Personal Home Page (PHP) with SQL embedded and web retrieval interface is developed for searching with Hypertext Markup Language (HTML). RESULTS: We present the first version of HBVPathDB, which is a HBV infection-related molecular interaction network database composed of 306 pathways with 1 050 molecules involved. With carefully drawn graphs, pathway information stored in HBVPathDB can be browsed in an intuitive way. We develop an easy-to-use interface for flexible accesses to the details of database. Convenient software is implemented to query and browse the pathway information of HBVPathDB. Four search page layout options-category search, gene search, description search, unitized search-are supported by the search engine of the database. The database is freely available at http://www.bio-inf.net/HBVPathDB/HBV/. CONCLUSION: The conventional perspective HBVPathDB have already contained a considerable amount of pathway information with HBV infection related, which is suitable for in-depth analysis of molecular interaction network of virus and host. HBVPathDB integrates pathway data-sets with convenient software for query, browsing, visualization, that provides users more opportunity to identify regulatory key molecules as potential drug targets and to explore the possible mechanism of HBV infection based on gene expression datasets.

Databases, Genetic↗

PubMed2005

Screening of specific antigens for SARS clinical diagnosis using a protein microarray.

In this study several SARS-CoV structural proteins and fragments were expressed in E. coli as GST or TRX fusion proteins. They were fabricated on a microarray and tested with sera from SARS patients. Antigenic screening indicated that recombinant GST-N2 fusion protein, the carboxy-terminus 213aa-423aa of N protein, was strongest positive and weakest non-specific compared with others. An indirect antibody ELISA method was developed and clinical positive and negative sera for their antibodies against GST-N2 fusion protein were assayed. 311 out of the 442 sera from clinical SARS inpatients, as well as 229 out of 302 sera from convalescent patients gave positive reactivities; positive rates were 70.4% and 75.8% respectively. Sera from a total of 2726 non-SARS patients and healthy individuals were tested and the false positive rate was only 0.07%. When the sensitivity control sample was diluted 1 : 64, it yielded OD values above the cutoff value. Reported data showed that this was a relatively high degree of sensitivity and specificity for SARS-CoV antibody testing. The data indicate that GST-N2 fusion protein, which was screened by protein microarray, may be a valuable diagnostic antigen for the development of serological assays for SARS. In addition, protein microarray assay presents a higher positive rate and sensitivity (86.1% and 1 : 200) compared with the traditional ELISA screening method, and could provide a rapid, parallel and high-throughput antigen screening platform.

Antibodies, Viral↗