Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Bioinformatic”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,657 records · Page 92Linked to original sources

[Molecular cloning and functional analysis of STGC3 - a novel gene on chromosome 3p21].

BACKGROUND & OBJECTIVE: A locus of loss of heterozygosity (LOH) with high frequency has been found on chromosome 3p21 in nasopharyngeal carcinoma (NPC). On the basis of our former research, this study was designed to clone and analyze a novel NPC-associated gene at this locus. METHODS: The full-length cDNA sequence of this gene was obtained by plasmid cDNA sequencing and RACE,and analyzed by bioinformatics. The pEGFP-C2/STGC3 fusion mammalian expression vector was constructed, and transfected into COS7 and CNE2 cell lines mediated by lipofectin to analyze the subcellular localization of gene expressing proteins. The expression of STGC3 was detected in normal tissues and tumor cell lines by Northern blot. RESULTS: An 1 271 bp full-length cDNA sequence of gene,which had no obvious homology with other known genes in bioinformatic databases,was obtained. This gene,named STGC3 (GenBank accession number:AY078383), localized on chromosome 3p21, and encodes a protein consisting of 146 amino acids. Protein localization analysis under fluorescent microscope indicated that STGC3 fusion protein was distributed in nucleus and cytoplasm 24-48 hours after transfection. MTE(TM)Array2 Northern blot analysis showed STGC3 expressed in both normal tissues and tumor cells,while its expression down-regulated in many tumor cell lines, such as Burkitt's lymphoma cell line Daudi. CONCLUSIONS: STGC3 is a novel gene, and down-regulated in NPC and many other tumor cell lines. STGC3 fusion protein distributes in cytoplasm and nucleus.

Amino Acid Sequence↗

[Analysis, identification and correction of some errors of model refseqs appeared in NCBI Human Gene Database by in silico cloning and experimental verification of novel human genes].

We found that human genome coding regions annotated by computers have different kinds of many errors in public domain through homologous BLAST of our cloned genes in non-redundant (nr) database, including insertions, deletions or mutations of one base pair or a segment in sequences at the cDNA level, or different permutation and combination of these errors. Basically, we use the three means for validating and identifying some errors of the model genes appeared in NCBI GENOME ANNOTATION PROJECT REFSEQS: (I) Evaluating the support degree of human EST clustering and draft human genome BLAST. (2) Preparation of chromosomal mapping of our verified genes and analysis of genomic organization of the genes. All of the exon/intron boundaries should be consistent with the GT/AG rule, and consensuses surrounding the splice boundaries should be found as well. (3) Experimental verification by RT-PCR of the in silico cloning genes and further by cDNA sequencing. And then we use the three means as reference: (1) Web searching or in silico cloning of the genes of different species, especially mouse and rat homologous genes, and thus judging the gene existence by ontology. (2) By using the released genes in public domain as standard, which should be highly homologous to our verified genes, especially the released human genes appeared in NCBI GENOME ANNOTATION PROJECT REFSEQS, we try to clone each a highly homologous complete gene similar to the released genes in public domain according to the strategy we developed in this paper. If we can not get it, our verified gene may be correct and the released gene in public domain may be wrong. (3) To find more evidence, we verified our cloned genes by RT-PCR or hybrid technique. Here we list some errors we found from NCBI GENOME ANNOTATION PROJECT REFSEQs: (1) Insert a base in the ORF by mistake which causes the frame shift of the coding amino acid. In detail, abase in the ORF of a gene is a redundant insertion, which causes a reading frame shift in the translation of an alternative protein, such as LOC124919 is wrong form of C17 orf32 (with mouse and rat orthologs determined by us). (2) Put together by mistake (with force). This is a wrong assembly of non-relating cDNA segment, such as LOC147007 is wrong form of C17orf32. (3) Mistakenly insert a base or one section of cDNA in the ORF which causes it ending beforehand, only coding cDNA sequence of N-terminal amino acids, incomplete. For example, LOC123722 is wrong form of SPRYD1, and even the human hypothetical gene LOC126250 or PDCD5 is wrong form of our PDCD5 (TFAR19). (4) Incomplete, only coding cDNA sequence of C-terminal amino acids. For example, human LOC149076 and mouse LOC230761 are wrong form of our verified human ZNF362 and mouse Zfp362, respectively. (5) Incomplete, only coding one section of coding protein cDNA sequence of correct gene ORF, lacking N-terminal and C-terminal amino acids sequence, and at the same time, mistakenly anticipates the first non-initiation codon amino acid of the incomplete protein amino acid as the initiation codon, e.g. anticipating L as M. For example, LOC200084 is wrong form of ZNF362. (6) Mistakenly insert a base or one section of cDNA in the ORF, wrongly causing unwanted termination codon before the insertion, so the coding protein lacks the first part of the amino acids. For example, the GenBank Acc. No. AL096883 ( LOCUS No. HS323M22B) is wrong form of an experimentally verified human NM_012263 with mouse ortholog of BC010510 determined. (7) It may regard the polluted genomic sequence as complete gene cDNA sequence and anticipate the so-called single exon gene, even the real one, only a small ORF in the very long single exon mRNA, while there really exists termination code in the same phase of the upper part of the ORF initiation code, no other characters accord with the gene's condition. For example, LOC91126 is wrong form of ZNF362. (8) The anticipated genes only have ORF which has no EST proofs on both terminal sides. Depending on this ORF, a complete gene cDNA with double support of EST and human genome (there are termination codes at the same phase of the upper part of ORF) which indicates the anticipated ORF reference sequence may be incorrect. For example, LOC164395 may be wrong form of novel human gene bankit4590055. (9) A similar but smaller protein-coding gene is anticipated in the range of the human genome sequence that has the support of EST experimental proof, so other new anticipated gene may be incorrect. For example, LOC167563 may be wrong form of CMYA5. However,these errors can be corrected or avoided by using our strategy. Here we give one example in detail: Comparision of the sequence SPRYD1 with human hypothetical gene LOC123722. The TAA bases in the position of 478-480 in LOC123722 cDNA is redundant, which causes a reading frame shift in the translation of an alternative protein. The redundancy of GTAAA of LOC123722 is not supported by our experimental clone,and is almost fully rejected by human EST alignment, and is shown as the next intron sequence by genomic GT/AG organization analysis. The verification of cDNA or genomic DNA sequence of SPRYD1 implies that LOC123722 has a wrong stop codon within its ORF because of the prediction program, thus being not complete cds. To sum up, by combining bioinformatics analyses with experimental verification, we have found that there are many errors of at least nine kinds appeared in NCBI GENOME ANNOTATION PROJECT REFSEQs through BLAST of our cloned genes in non-redundant database, and our strategy is helpful in correcting them, such as LOC14907, LOC200084 and LOC91126 (all of them should be ZNF362, but are three different kinds of wrong forms of ZNF362), three model reference sequences predicted from NCBI contig NT_004511 by automated computational analysis using gene prediction method, or such as LOC124919 and LOC147007 (both should be C17orf32, but are two different kinds of wrong forms of C17orf32), two model reference sequences predicted from NCBI contig NT_010808 by automated computational analysis using gene prediction method. Therefore, the correct identification and annotation of novel human genes may be still a heavy task, which can be finished within a long period of time. So human genome coding regions annotated by computer should be used with caution. The articles published in the past did not clearly point out the existence of mistakes in the NCBI human gene mode reference sequence. At the Seventh International Human Genome Conference held in April 2002, we first published the researching result on this aspect in the communication form of Posterly insert a base or one section of cDNA in the ORF, wrongly causing unwanted termination codon before the insertion, so the coding protein lacks the first part of the amino acids. For example, the GenBank Acc. No. AL096883 ( LOCUS No. HS323M22B) is wrong form of an experimentally verified human NM_012263 with mouse ortholog of BC010510 determined. (7) It may regard the polluted genomic sequence as complete gene cDNA sequence and anticipate the so-called single exon gene, even the real one, only a small ORF in the very long single exon mRNA, while there really exists termination code in the same phase of the upper part of the ORF initiation code, no other characters accord with the gene's condition. For example, LOC91126 is wrong form of ZNF362. (8) The anticipated genes only have ORF which has no EST proofs on both terminal sides. Depending on this ORF, a complete gene cDNA with double support of EST and human genome (there are termination codes at the same phase of the upper part of ORF) which indicates the anticipated ORF reference sequence may be incorrect. For example, LOC164395 may be wrong form of novel human gene bankit4590055. (9) A similar but smaller protein-coding gene is anticipated in the range of the human genome sequence that has the support of EST experimental proof, so other new anticipated gene may be incorrect. For example, LOC167563 may be wrong form of CMYA5. However, these errors can be corrected or avoided by using our strategy. Here we give one example in detail: Comparision of the sequence SPRYD1 with human hypothetical gene LOC123722. The TAA bases in the position of 478-480 in LOC123722 cDNA is redundant, which causes a reading frame shift in the translation of an alternative protein. The redundancy of GTAAA of LOC123722 is not supported by our experimental clone, and is almost fully rejected by human EST alignment, and is shown as the next intron sequence by genomic GT/AG organization analysis. The verification of cDNA or genomic DNA sequence of SPRYD1 implies that LOC123722 has a wrong stop codon within its ORF because of the prediction program, thus being not complete cds. To sum up, by combining bioinformatics analyses with experimental verification, we have found that there are many errors of at least nine kinds appeared in NCBI GENOME ANNOTATION PROJECT REFSEQs through BLAST of our cloned genes in non-redundant database, and our strategy is helpful in correcting them, such as LOC14907, LOC200084 and LOC91126 (all of them should be ZNF362, but are three different kinds of wrong forms of ZNF362), three model reference sequences predicted from NCBI contig NT_004511 by automated computational analysis using gene prediction method, or such as LOC124919 and LOC147007 (both should be C17orf32, but are two different kinds of wrong forms of C17orf32), two model reference sequences predicted from NCBI contig NT_010808 by automated computational analysis using gene prediction method. Therefore, the correct identification and annotation of novel human genes may be still a heavy task, which can be finished within a long period of time. So human genome coding regions annotated by computer should be used with caution. (ABSTRACT TRUNCATED)

Amino Acid Sequence↗

Novel retinal genes discovered by mining the mouse embryonic RetinalExpress database.

PURPOSE: Bioinformatics has emerged as a powerful tool for identifying novel genes and pathways associated with retinal biology and disease. The developing mouse retina expresses an exceedingly large and complex variety of genes. Many of these genes have not been characterized but nevertheless are likely to have important developmental or physiological functions. The purpose of this study was to use an in silico approach with a mouse embryonic retinal database of cDNAs/expressed sequence tags (ESTs) named RetinalExpress to identify previously uncharacterized genes that are represented in the developing retina. METHODS: cDNA clones unique to the RetinalExpress database were identified by comparing clones in the RetinalExpress database with those in other cDNA/EST databases. We used a hierarchical filtering procedure with high stringency criteria that included sequence quality, colinearity with hypothetical gene sequences, and absence of any substantial existing annotation to select clones that were likely to represent novel genes. Selected clones were located on mouse chromosomes using National Center for Biotechnology Informatics Map Viewer software and the database from the University of California at Santa Cruz Genome Bioinformatics Web browser. The expression of selected retinal transcripts was determined using reverse transcriptase (RT)-PCR. In situ hybridization of sectioned embryonic and postnatal retinas was performed to determine spatial expression patterns of selected transcripts. RESULTS: Of the 27,765 cDNA clones from RetinalExpress that we filtered through several public cDNA/EST databases, 26 cDNA/EST sequences were identified that, at the time of the analysis, were unique to RetinalExpress. Seventeen clones were selected for RT-PCR analysis, and retinal transcripts corresponding to previously uncharacterized genes were unambiguously detected for six clones. Three genes encoded open reading frames containing putative functional domains; one sequence contained an HMG DNA binding domain, another, an RFX DNA binding domain, and another, a phospholipase C catalytic domain X. Transcripts from the genes encoding DNA binding domains were expressed in embryonic and postnatal retinas with distinct spatial patterns. CONCLUSIONS: The characterization of 26 mouse genes whose partial nucleotide sequences were uniquely represented in the RetinalExpress cDNA/EST database demonstrated the feasibility of retinal gene discovery using in silico analysis. Two of these genes had distinctive spatial expression patterns in the retina and one was likely to function as a DNA binding protein in embryonic and postnatal retinas. The gene identification approach described here demonstrates the usefulness of establishing large cDNA/EST databases from highly specialized neuronal tissues such as the retina to find novel genes.

Animals↗

Computationally analyzing the possible biological function of YJL103C--an ORF potentially involved in the regulation of energy process in yeast.

Although the complete genomes of a number of organisms have been sequenced, the biological functions of many genes are still not known. Because experimentally studying the functions of those genes one by one requires tremendous time, it is vital to use published resources like microarray gene expression data for computational analysis of gene functions. One example is YJL103C, a yeast gene of unknown function in the Saccharomyces Genome Database (SGD). It is possible to quickly infer its biological function by computational analysis. In this study, we present an efficient model to explore the biological function of a novel gene using microarray data. We showed that the expression pattern of YJL103C is most similar to the genes in the energy group and respiratory chain subgroup. We further found that YJL103C contains a HAP2,3,4 box in its promoter region and a cytochrome C heme-binding signature in its protein sequence. Our findings define a potential role for YJL103C in the regulation of energy metabolism, specifically in the process of oxidative phosphorylation. Similar bioinformatics methods can be applied to infer the biological functions of other novel genes in organisms for which microarray data are available. In this work, we selected a single gene of unknown function as a case study. By focusing on the power of computer analysis and bioinformatics on the available microarray data, we have determined the likely biological function of YJL103C. Our study provides a method by which to explore the potential function of other genes currently annotated as having an unknown function in any organism for which global gene expression data are available.

Binding Sites↗

[Cloning and characterization of a novel human ceg1 gene cDNA].

ceg1 gene was a novel human gene, which was cloned by bioinformatics research and RT-PCR. It was a single exon gene and located on human chromosome 14. The length of the cDNA was 2050 bp. Bioinformatics analysis predicted a 1340 bp complete open reading frame (ORF) which encoded a 446 amino acid protein, containing an EGF-like and CLECT domain. We found that the homologous genes of ceg1 in mouse embryo and chicken embryo were specifically expressed in the brain by in-situ hybridization. The result of RT-PCR of the mature mouse organs showed it was widely expressed in many organs. The result indicates that ceg1 gene may have an essential role in the development of brain and the maintenance of the organs' normal function. The analysis of expression and function profile of ceg1 gene may provide valuable insights into the functions of ceg1 in the development and function of human body.

Amino Acid Sequence↗

In silico identification of breast cancer genes by combined multiple high throughput analyses.

Publicly available human genomic sequence data provide an unprecedented opportunity for researchers to decode the functionality of human genome. Such information is extremely valuable in cancer prevention diagnosis and treatment. Cancer Genome Anatomy Project (CGAP) and Gene Expression Omnibus (GEO) are two bioinformatic infrastructures for studying functional genomics. The goal of this study is to explore the feasibility of incorporating the Internet-available bioinformatic databases to discover human breast cancer-related genes. Several tools including the Gene Finder, Virtual Northern (vNorthern) and SAGE digital gene expression displayer (DGED) were used to analyze differential gene expression between benign and malignant breast tissues. A pilot study was performed using both EST and SAGE vNorthern to analyze the expression of a panel of known genes, including high abundance genes beta-actin and G3PDH, low abundance genes BRCA1 and p53, tissue-specific genes CEA and PSA and two breast cancer-related genes Her2/neu and MUC1. We found a high expression of beta-actin and G3PDH and a low expression of BRCA1 and p53 across different types of tissues as well as a tissue-specific expression of CEA in colon and PSA in prostate. A further analysis of 30 known breast cancer-related genes in breast cancer tissues by vNorthern demonstrated a high expression of oncogenes and low expression of tumor suppressor genes. An open-end analysis of two pools of breast cancer and benign breast tissue libraries by SAGE DGED produced 53 differentially expressed genes according to the screening criteria of a >five-fold difference and p<0.01. Further analysis by EST vNorthern and virtual microarray analysis reduced the candidate genes to six, with four down-regulated genes, ANXA1, CAV1, KRT5 and MMP7, and two up-regulated genes, ERBB2 and G1P3 in breast cancer. These findings were validated by a real-time RT-PCR analysis in eight paired human breast cancer tissue samples. We conclude that the combined multiple high throughput analyses is an effective data mining strategy in cancer gene identification. This approach may improve the usage of public available genomic data through strategic data mining of high throughput analysis.

Blotting, Northern↗

[Pro-apoptotic efficiencies of three reconstructed human caspase-8 on cervical cancer cell line HeLa].

BACKGROUND & OBJECTIVE: Apoptosis is a kind of evolutional high conservative cell death. Transferring high active pro-apoptotic molecules into cancer cells to induce apoptosis is a potential strategy for cancer gene therapy. Based on our previous generation of reconstructed human caspase-8, which can continuously induce apoptosis of cervical cancer cell line HeLa, by reversing its large and small subunits, this study was designed to investigate the pro-apoptotic efficiencies of 3 reconstructed human caspase-8 (Casp8CD, Rev8, and Rev8L) on HeLa cells, and to explore the feasibility of reconstructed human caspase-8 as potential apoptosis-inducing candidates. METHODS: The eukaryotic expression vectors pIRES2-EGFP carrying Casp8CD, Rev8, and Rev8L genes were transfected into HeLa cells, and breast cancer MCF-7 cells. Expressions and pro-apoptotic effects of Casp8CD, Rev8, and Rev8L genes were observed under fluorescent microscope, and their pro-apoptotic efficiencies were assessed by MTT assay and cells counting. The flexibilities of linking-peptides between subunits of Rev8 and Rev8L were analyzed by bioinformatics. RESULTS: Expressions of the 3 reconstructed caspase-8 genes were observed under fluorescent microscope, and the HeLa and MCF-7 cells expressing Rev8 or Rev8L genes displayed typical apoptotic volume decrease (AVD). MTT assay showed that compared with control cells, A(570) values of Rev8- and Rev8L-transfected cells began to decrease 20 h after transfection. Cell counting results indicated that cell death ratio of Casp8CD-, Rev8-, and Rev8L-transfected cells were 16.9%, 52.3%, and 47.7%, respectively, 24 h after transfection; and 12.9%, 51.6%,and 61.2%,respectively,48 h after transfection. Bioinformatics analysis showed that the linking-peptides between subunits of Rev8 and Rev8L were flexible. CONCLUSION: Rev8 and Rev8L molecules have similar pro-apoptotic effects and efficiencies, but over-expressed Casp8CD had no significant pro-apoptotic effects.

Apoptosis↗

Multi-class protein fold classification using a new ensemble machine learning approach.

Protein structure classification represents an important process in understanding the associations between sequence and structure as well as possible functional and evolutionary relationships. Recent structural genomics initiatives and other high-throughput experiments have populated the biological databases at a rapid pace. The amount of structural data has made traditional methods such as manual inspection of the protein structure become impossible. Machine learning has been widely applied to bioinformatics and has gained a lot of success in this research area. This work proposes a novel ensemble machine learning method that improves the coverage of the classifiers under the multi-class imbalanced sample sets by integrating knowledge induced from different base classifiers, and we illustrate this idea in classifying multi-class SCOP protein fold data. We have compared our approach with PART and show that our method improves the sensitivity of the classifier in protein fold classification. Furthermore, we have extended this method to learning over multiple data types, preserving the independence of their corresponding data sources, and show that our new approach performs at least as well as the traditional technique over a single joined data source. These experimental results are encouraging, and can be applied to other bioinformatics problems similarly characterised by multi-class imbalanced data sets held in multiple data sources.

Amino Acid Sequence↗

[Molecular unraveling of disease by means of DNA-microarrays].

Determination of the human genome sequence and the development of microarray technologies allowing the rapid measurement of all genes in the genome have generated new perspectives for our current biomedical research. Gene expression analysis will make a major contribution to our insight into the underlying biology of disease and will lead to improved methods for diagnostics, prognosis and treatment. Microarray studies create the possiblity to subclassify patients with diseases such as rheumatoid arthritis, diffuse large B-cell lymphoma and breast cancer, with both prognostic and therapeutic consequences. The simultaneous quantification of the activity of all genes in tissues or cells from patients by microarray technology, linked to the clinical parameters, creates a large number of data points, which cannot be analysed without the aid of the advanced application of bioinformatics. As a result, genomic research has become, in part, a bioinformatics discipline that will be integrated with clinical medicine. The microarray technology makes it possible to develop personalized medicine, with a more accurate diagnosis and prognosis for every patient and subsequently a tailored treatment strategy.

Arthritis, Rheumatoid↗

[Screening of HBeAgTP interacting proteins in hepatocytes with yeast-two hybrid technique].

OBJECTIVE: To screen proteins in hepatocytes interacting with HBeAg transactivated protein (HBeAgTP) with yeast-two hybrid technique for investigating the biological functions of HBeAgTP. METHODS: Suppression subtractive hybridization (SSH) and bioinformatics techniques were used for screening and cloning of the target genes transactivated by HBeAg. The HBeAgTP gene was amplified by polymerase chain reaction (PCR) and HBeAgTP bait plasmid was constructed with yeast-two hybrid system 3, and then transformed into yeast AH109. The transformed yeast mated with yeast Y187 containing liver cDNA library plasmid in 2 x YPDA medium. Diploid yeast was plated on synthetic dropout nutrient medium (SD/-Trp-Leu-His-Ade) and synthetic dropout nutrient medium (SD/-Trp-Leu-His-Ade) containing X-gal for selecting two times and screening. After extracting and sequencing of plasmid from blue colonies, the results were analyzed by bioinformatics. RESULTS: HBeAgTP gene was successfully cloned and expressed in yeast cells. Fifteen genes in twenty-four positive colonies were obtained using yeast-two hybrid technique. CONCLUSION: HBeAgTP conjugated protein genes were successfully cloned, along with the genes involved in transcription and translation of proteins, immunoloregulation, materials and energy metabolism in vivo.

Hepatitis B e Antigens↗

[Methods of statistical genetics and use of database for genome information].

Knowledge and technology of bioinformatics have become inevitable for gene and genome research. Education and research in this field of science are not sufficient in Japan. There are two different approaches to trait mapping, the way by which traits are mapped on the genome. Thus, the knowledge-based approach uses functions of molecules while the statistics-based approach uses polymorphisms. Statistics-based approach uses two different methods, linkage analysis and analysis based on linkage disequilibrium. Various phenotypes are efficiently mapped on the genome using such methods. Recently, bioinformatic data base search is mostly performed using internet. Anyone can perform sequence-search, homology-search and SNP-search. Since such data bases change quickly, readers should access the databases themselves and be used to the procedures for them.

Computational Biology↗

Using ontologies in PROTEUS for modeling proteomics data mining applications.

Bioinformatics applications are often characterized by a combination of (pre) processing of raw data representing biological elements, (e.g. sequence alignment, structure prediction), and an high level data mining analysis. Developing such applications needs knowledge of both data mining and bioinformatics domains, that can be effectively achieved by combining ontology about the application domain and ontology about the approaches and processes to solve the given problem. In this paper we talk about using ontologies to model proteomics in silico experiments. In particular data mining of mass spectrometry proteomics data is considered.

Computational Biology↗

[Basic principles of computational chemistry for medical biologists].

The lecture describes the basic principles of computational chemistry underlying the methods of molecular modelling used in bioinformatics area. The basic positions, methods of molecular and quantum mechanics and combined approaches are considered. This lecture is from theoretical cycle "Bioinformatics and Computer-Aided Drug Design" for fourth year students of Medico-Biological Department of Russian State Medical University (specialty--biochemistry, biophysics and medical cybernetics). It can also be advised for all students and post-graduate students of medico-biological specialties.

Computational Biology↗

[Screening tumor antigens of ovarian carcinoma by Western blot, immunoprecipitation, and mass spectrometry].

BACKGROUND & OBJECTIVE: Screening tumor antigens plays a key role in early diagnosis of ovarian carcinoma. Several technologies, such as phage antibody library, ribosome display, and serological analysis of recombinant cDNA expression libraries (SEREX), have been applied widely. This study was to screen and identify tumor antigens of ovarian carcinoma by Western blot, immunoprecipitation, and mass spectrometry, and to establish a new methodological entity. METHODS: Western blot was used to find out the obviously different serum in ovarian carcinoma patients; SKOV3 cells lysate was added in the serum; immunoprecipitation was used to enrich antigens; then, the different protein band was gained when compared with normal serum immunoprecipitates, identified by mass spectrometry, and analyzed with bioinformatics. RESULTS: The serum of patient No. 7 was the obviously different one screened with Western blot. Immunoprecipitation and SDS-PAGE showed a different protein band in the serum appeared in the position of about 66.2 ku when compared with normal serum immunoprecipitates. Through mass spectrometry and bioinformatics analysis, heat shock protein 70 (HSP70) and cytokeratin 9 were identified in the different protein band. CONCLUSION: Western blot, immunoprecipitation, and mass spectrometry is an effectively methodological entity for screening and identifying tumor antigens.

Antigens, Neoplasm↗

[Subcellular localization and tissues expression profile of hGPCRc: an orphan G protein-coupled receptor].

As a member of orphan G protein-coupled receptors (oGPCRs), hGPCRc was cloned from human colon tissue and analyzed by bioinformatic softwares. It was showed that the corresponding amino acids of hGPCRc formed seven-transmembrane domains as the key characteristic of GPCRs. Then, the recombinant GFP-hGPCRc was constructed by fussing hGPCRc into pEGFP-N1 carrying green fluorescent protein (GFP) gene, and CHO-K1 cells were subsequently transfected with the GFP-hGPCRc or pEGFP-N1. The green fluorescence protein expression in the two different transfected cells was observed under the laser scanning confocal microscopy (LSCM). It was showed that green fluorescence protein was distributed in the whole bodies of the cells transfected with pEGFP-N1, but mainly distributed on the plasma membrane and cytoplasm membrane transfected with GFP-hGPCRc. Thus, the localization on the membrane of hGPCRc was accorded with the predication by bioinformatic analysis. The expression analysis of hGPCRc by RT-PCR indicated that hGPCRc was abundantly expressed in heart, kidney, cerebel and colon etc., but absent in liver, cerebra, small intestine and muscle etc. The expressing profile of hGPCRc could provide some useful clues to understanding its effects on embryonic development and physiological functions.

Amino Acid Sequence↗

[Tumor relevance analysis of a highly conserved gene by using gene microarray hybridization].

Preliminary function research of a highly conserved human gene,which was cloned from human fetal cDNA library during large-scale cDNA sequencing,is illustrated in this article. Bioinformatics analysis indicates that this gene is highly conserved in human, mouse, fruit fly, thaliana and fission yeast. Other bioinformatics analysis implies its relevance with tumors. RT-PCR analysis shows its wide-ranging expression patterns. Its expression in 16 cancer cases (including 7 liver cancer cases, 5 pancreas cancer cases, 2 larynx cancer cases and 2 lung cancer cases) is studied by using gene microarray analysis. The result shows its relevance with tumors and implies it may have different status in different classification of tumors.

English Abstract↗

[Screening and cloning target genes transactivated by hepatitis C virus F protein using suppression subtractive hybridization technique].

OBJECTIVES: To identify and clone human genes transactivated by HCV F protein by constructing a cDNA subtractive library using the suppression subtractive hybridization technique. METHODS: Suppression subtractive hybridization (SSH) and bioinformatics techniques were used for screening and cloning of the target genes transactivated by HCV F protein. The mRNA was isolated from HepG2 cells transfected with pcDNA3.1 (-)-F or with pcDNA3.1(-) empty vector as a control, and SSH method was employed to analyze the differentially expressed DNA sequence between the two groups. After restriction enzyme Rsa I digestion, small sized cDNAs were obtained. Then tester cDNA was divided into two groups and ligated to the specific adaptor 1 or adaptor 2. After tester cDNA was hybridized with driver cDNA twice and underwent two times of nested PCR, it was then subcloned into T/A plasmid vectors to set up the subtractive library. Amplification of the library was carried out with E. coli strain DH5 alpha. The cDNA was sequenced and analyzed in GenBank with blast search after PCR. RESULTS: The subtractive library of genes transactivated by HCV F protein was constructed successfully. The amplified library contains 71 positive clones. Colony PCR shows that 56 clones contain 200-1000 bp inserts. Sequence analysis was performed on 28 clones randomly, and the full length sequences were obtained with using the bioinformatics method. Altogether 19 coding sequences were obtained, consisting of 17 known and 2 unknown. CONCLUSIONS: The obtained sequences may be target genes transactivated by HCV F protein, and some gene coding proteins are those involved in cell cycle regulation, metabolism, and cell apoptosis.

Cloning, Molecular↗

[Characteristics and expression of Mip5, a novel gene associated with myocardial ischemia/reperfusion in rats].

OBJECTIVE: To determine the characteristics of a novel gene Mip5 (GenBank accession number AY553870) and its expression under physiological and pathological conditions. METHODS: The characteristics of Mip5 were analyzed by bioinformatic programs including BLAST, spidey, psort, ClustalW and so on. RT-PCR was performed to detect Mip5 expression. RESULTS: Bioinformatic analysis showed that Mip5 gene lied in the 13th chromosome and contained 8 exons and 7 introns, its open reading frame contained 909 bp and its protein production was 302 amino acid residues including 6 kelth domains. Under normal conditions, MIP5 expressed abundantly in the heart, brain and kidney, but its expression could not be detected in the liver and muscle. Expression of Mip5 gene was increased significantly after ischemia-reperfusion compared with the sham groups, and reached its peak at 3 h and recovered at 12 h after the reperfusion. Conclusion Mip5 gene is a novel gene containing a putative open reading frame of 302 amino acids residues and may play an important role in rat cardiomyocytes suffering ischemia processing.

Amino Acid Sequence↗