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A transposon was introduced close to a poorly selectable gene. This gene could be cloned by using selection for the antibiotic resistance marker of the transposon.
We previously found the preferential selection of VP7 gene from a parent rotavirus strain SA11 with G serotype 3 (G3) in the sequential passages after mixed infection of simian rotavirus SA11 and SA11-human rotavirus single-VP7 gene-substitution reassortants with G1, G2, or G4 specificity. However, it has not been known whether or not VP7 genes derived from other strains with G3 specificity (G3-VP7 gene) are preferentially selected in the genetic background of SA11. To address this question, mixed infections followed by multiple passages were performed with a reassortant SA11-L2/KU-R1 (SKR1) (which possesses VP7 gene derived from G1 human rotavirus KU and other 10 genes of SA11 origin) and one of the five G3-rotaviruses, RRV, K9, YO, AK35, and S3. After the 10th passage, selection rates of SA11-L2/KU-R1 gene 9 (G1-VP7 gene) and gene 5 (NSP1 gene) reduced considerably (0 to 20.4%) in the clones obtained from all the coinfection experiments, while all or some of other segments were preferentially selected from SKR1 depending on the pairs of coinfection. When viral growth kinetics was examined, SKR1 exhibited better growth and reached a higher titer than any G3 viruses. Although the generated reassortants with VP7 gene and NSP1 gene derived from G3 viruses showed almost similar growth kinetics to that of SKR1 during the first 20 h of replication, the titers of these reassortants were higher than that of SKR1 after 36 h postinfection. The results obtained in this study suggested that G3-VP7 gene is functionally more adapted to the genetic background of SA11.
Previously, we reported that adenoviral vectors carrying the carcinoembryonic antigen (CEA) promoter sequences to direct the Echerichia coli beta-galactosidase gene (AdCEA-lacZ) or cytosine deaminase (CD) gene (AdCEA-CD) confer selective gene expression on a CEA-positive gastric cancer cell line (MKN45) in vitro. Here, adenovirus-mediated tumor-specific gene therapy for CEA-positive gastric carcinoma in vivo was investigated. Using an animal model with i.p. disseminated MKN45 tumors, adenovirus-mediated tumor-specific transgene expression and therapeutic efficacy were analyzed. After an i.p. injection of AdCEA-lacZ, beta-galactosidase activity was confined to tumor xenografts. Moreover, CD mRNA was expressed exclusively in MKN45 tumor xenografts after infection with AdCEA-CD, despite the fact that an adenovirus-mediated transfer of CD DNA was detected in all tissues tested. In contrast, CD mRNA was detected not only in tumor xenografts but also in other organs of mice infected with AdCA-CD, in which CD gene expression is governed by an ubiquitous promoter. Suppression of tumor growth and prolongation of survival were noted in tumor-bearing mice treated with AdCEA-CD and 5-fluorocytosine (5FC) without observable adverse effects. In contrast, significant hepatic toxicity was noted in animals treated with AdCA-CD. These results reveal that the CEA promoter restricts CD gene expression to CEA-positive tumor cells in the adenoviral context in vivo, along with the beneficial therapeutic effects of 5FC treatment, suggesting the i.p. AdCEA-CD/5FC system may provide a novel approach to treatment of i.p. disseminated gastric cancer.
Two different techniques were used for labeling cells for subsequent generation of hybrid hybridomata. One of them was described earlier by De Lau and included isolation of an HATSNeoR double mutants of hybridomata cells. We proposed the second one consisting of introduction of dominant selectable genes conferring resistance to genecetin (G418) and hygromycin B into distinct hybridomata by retroviral vectors. Hybrid hybridomata secreting the bispecific antibodies have been obtained by both methods. However, comparison of the methods has revealed that highly efficient retroviral gene transfer of the selectable genes is a simpler and more convenient method for generation of cellular hybrids.
A series of vectors with two dominant selectable genes was constructed for repair and mutation studies following transfer into mammalian cells. The recombinant genes (SV-gpt and HSVtk-neo) were placed in different relative orientations and positions in the vectors. These variables were shown to affect transformation frequency of cells by the vectors especially where one of the genes had a relatively weak expression, modelled by truncating the promoter of the HSVtk-neo gene. The use of two-gene vectors to assess DNA repair was investigated by cutting the SV-gpt gene with a restriction endonuclease and monitoring correct rejoining by selecting for gene activity after transfer into various cell types. In such experiments, selection was first applied for the undamaged HSVtk-neo gene to eliminate transfer artefacts, followed by counterselection for the activity of the damaged SV-gpt gene. The measured frequency of correct rejoining of the damaged gene was found to vary both with the vector construct and with the recipient cell species (Chinese hamster V79 or human transformed fibroblasts). Despite this variation, correct rejoining was found to be consistently lower in radiosensitive (ataxia telangiectasia) human cells than in wild-type human cells, irrespective of the vector construct. In these experiments, some of the transformed cell colonies showed 'sectoring' on exposure to the counterselection, suggesting a slow determination of the fate of transferred DNA. For mutation studies a V79 cell clone carrying a single copy of one of these two-gene vectors was identified and shown to be stably integrated. Mutations of the SV-gpt gene in these cells were isolated while maintaining selection for the HSVtk-neo gene, to attempt to limit mutational loss of the total integrated sequence and provide at least one identifiable junction for analysis of deletion events. Spontaneous and X-ray-induced mutants were identified with a variety of genetic changes, as shown by Southern analysis, from presumed point mutations to deletions and rearrangements of the vector sequence. Rescue of integrated two-gene vector sequences from transformed cells, by recloning in E. coli, was shown to be feasible; thus alterations in transferred DNA can be analysed in detail.
MOTIVATION: One problem with discriminant analysis of DNA microarray data is that each sample is represented by quite a large number of genes, and many of them are irrelevant, insignificant or redundant to the discriminant problem at hand. Methods for selecting important genes are, therefore, of much significance in microarray data analysis. In the present study, a new criterion, called LS Bound measure, is proposed to address the gene selection problem. The LS Bound measure is derived from leave-one-out procedure of LS-SVMs (least squares support vector machines), and as the upper bound for leave-one-out classification results it reflects to some extent the generalization performance of gene subsets. RESULTS: We applied this LS Bound measure for gene selection on two benchmark microarray datasets: colon cancer and leukemia. We also compared the LS Bound measure with other evaluation criteria, including the well-known Fisher's ratio and Mahalanobis class separability measure, and other published gene selection algorithms, including Weighting factor and SVM Recursive Feature Elimination. The strength of the LS Bound measure is that it provides gene subsets leading to more accurate classification results than the filter method while its computational complexity is at the level of the filter method. AVAILABILITY: A companion website can be accessed at http://www.ntu.edu.sg/home5/pg02776030/lsbound/. The website contains: (1) the source code of the gene selection algorithm; (2) the complete set of tables and figures regarding the experimental study; (3) proof of the inequality (9). CONTACT: ekzmao@ntu.edu.sg.
BAR is a nuclear bile acid receptor (BAR) (FXR) receptor that regulates gene networks involved in cholesterol and bile acid homeostasis. We have identified two classes of synthetic compounds that differentially modulate BAR activity. The first class activates BAR target genes in the predicted fashion and is 25-fold more potent than endogenous bile acids. The second class, represented by AGN34, antagonizes BAR in transient reporter assays. Surprisingly, this compound acts in a gene-selective manner in vivo: it is an agonist on CYP7A1, an antagonist on IBABP, and is neutral on SHP. These findings indicate that synthetic BAR modulators can be developed to regulate transcription in a gene-specific fashion. Given the ability of BAR to regulate several lipid homeostatic pathways, the identification of gene-selective BAR modulators have important implications for the development of improved cholesterol lowering agents.
Constructing a classifier based on microarray gene expression data has recently emerged as an important problem for cancer classification. Recent results have suggested the feasibility of constructing such a classifier with reasonable predictive accuracy under the circumstance where only a small number of cancer tissue samples of known type are available. Difficulty arises from the fact that each sample contains the expression data of a vast number of genes and these genes may interact with one another. Selection of a small number of critical genes is fundamental to correctly analyze the otherwise overwhelming data. It is essential to use a multivariate approach for capturing the correlated structure in the data. However, the curse of dimensionality leads to the concern about the reliability of selected genes. Here, we present a new gene selection method in which error and repeatability of selected genes are assessed within the context of M-fold cross-validation. In particular, we show that the method is able to identify source variables underlying data generation.
Principal component analysis (PCA) has been widely used in multivariate data analysis to reduce the dimensionality of the data in order to simplify subsequent analysis and allow for summarization of the data in a parsimonious manner. It has become a useful tool in microarray data analysis. For a typical microarray data set, it is often difficult to compare the overall gene expression difference between observations from different groups or conduct the classification based on a very large number of genes. In this paper, we propose a gene selection method based on the strategy proposed by Krzanowski. We demonstrate the effectiveness of this procedure using a cancer gene expression data set and compare it with several other gene selection strategies. It turns out that the proposed method selects the best gene subset for preserving the original data structure.
The present study has undertaken the liver- and lobe-selective gene transfections following the instillation of plasmid DNA (pDNA) to the liver surface in mice. The luciferase levels produced in the applied (left) liver lobe at 6 h after liver surface instillation of pDNA were significantly higher than those produced in the other tissues assayed, and ranged from 8.5-fold higher in other liver lobes to 320-fold higher in other tissues. After small intestine surface instillation of pDNA, the gene expression was a little detected in the tissues assayed. Following liver surface instillation of pDNA at a time from 2 to 48 h or at a volume from 15 to 120 microl, the gene expressions of the applied liver lobe were always significantly higher than those of other liver lobes and other tissues. We demonstrated the novel liver- and lobe-selective gene transfection utilizing the instillation to the liver surface.
MOTIVATION: The number of expressed sequence tags (ESTs) in GenBank has now surpassed 200,000 for cattle and 100,000 for swine. The Institute of Genome Research (TIGR) has organized these sequences into approximately 60,000 non-redundant consensus sequences (identified by TIGR Gene Indices) for cattle and 40,000 for swine. Anonymous ESTs are of limited value unless they are connected to function. Functional information is difficult to manage electronically because of heterogeneity of meaning and form among databases. The Gene Ontology (GO) Consortium has produced ontologies for gene function with consistent meaning and form across species. Linking livestock EST to gene function through similarity with sequences from other annotation-rich mammals could accelerate: (1) the discovery of positional candidate genes underlying a livestock quantitative trait locus (QTL) and (2) comparative mapping between livestock and other mammals (e.g. humans, mouse and rat). We initiated this investigation to determine if incorporation of the GO into the annotation process could accelerate livestock positional candidate gene discovery. RESULTS: We have associated livestock ESTs with GO nodes through sequence similarity to the NCBI Reference Sequences (RefSeq). Positional candidate genes are identified within minutes that otherwise required days. The schema described here accommodates queries that return GO nodes from terms familiar to biologists, such as gene name, alternate/alias symbol, and OMIM phenotype. AVAILABILITY: Scripts and schema are available on request from the authors.
Upon transfection of (TK-)F9 teratocarcinoma stem-cells and (TK-)L fibroblasts with a plasmid carrying two selection genes, Eco.gpt and HSVI-tk, selection for gpt gene yielded ten times fewer colonies than selection for tk. Only the transformed clones selected for gpt had measurable xanthine guanine phosphoribosyltransferase (XGPRT) activity (Jami et al., 1983). Eco.gpt coding for XGPRT was under the control of simian virus 40 (SV40) early genes' regulating sequences (SV-gpt). In the present study, it was verified that the low efficiency of gpt selection in mouse cells was not due to the eucaryotic controlling sequences added to the bacterial gene. The transformed clones selected for tk that had no XGPRT activity possessed at least one uninterrupted copy of the composite SV-gpt gene and as many copies of the transforming plasmid as the cells selected for gpt expression. In a further test, the gpt gene was placed under the control of tk-regulating sequences and inserted with the tk gene in the same vector. Under these conditions, expression of XGPRT in the transformed clones selected for tk was improved, even though relative selection for gpt remained low.
DNA methylation can function as a toxic alkylation reaction exploited by chemotherapeutic agents to induce cancer cell death. However, finely tuned DNA methylation plays a fundamental role in cellular physiology, particularly in the epigenetic regulation of gene expression. Once thought to act solely as a repressor of gene transcription, its functional role has since been elucidated as genomic locus-specific and deeply connected with other epigenetic factors. Following the clinical approval of DNA methyltransferase inhibitors, such as Azacitidine and Decitabine, for the treatment of hematological malignancies, considerable efforts have been devoted to developing pharmacological tools that modulate epigenetic DNA methylation. However, the lack of gene selectivity in these agents limits their therapeutic efficacy and increases off-target toxicity. Moreover, the non-gene-selective nature of current DNA methylation-targeting molecules fails to meet the standards required to discern the nuanced roles of DNA methylation across diverse pathophysiological contexts and genomic loci, particularly in an era where next-generation sequencing and omics technologies enable high-resolution epigenetic analyses. In this review, we examine the mechanisms and roles of DNA methylation in epigenetic regulation, evaluate the current landscape of DNA methylation modulators, from traditional DNMT inhibitors to cutting-edge CRISPR-dCas9 fusion systems and protein-protein interaction disruptors, and discuss their clinical relevance. Finally, we emphasize the need for precise, locus-specific tools to advance both cancer research and therapeutic strategies.
We have used integrative pSV2 plasmids to learn how DNA lesions affect nonhomologous recombination with human chromosomes. Enhanced stable transformation of fibrosarcoma cells with a selectable gene was observed after chemical modification of the plasmid DNA; thus, cells transfected with plasmid pSV2-gpt carrying photoadducts of the cross-linking agent 4'-hydroxymethyl-4,5',8-trimethylpsoralen (HMT) yielded four- to sevenfold-higher levels of Gpt+ transformants than were obtained with untreated plasmid. The enhancement due to HMT interstrand cross-links was at least as great as that due to the monoadducts. DNA hybridization analysis indicated that the enhanced transformation frequency resulted from an increased number of cells carrying integrated plasmid sequences rather than from a higher copy number per transformant. The enhancement was not seen with a plasmid missing the sequences flanking the minimal simian virus 40 gpt transcription unit. Cotransfection with untreated and HMT-treated plasmids suggested that the HMT-containing DNA interacted preferentially with some cellular factor that promoted chromosomal integration of the plasmid DNA. It is concluded that (i) interstrand cross-linking as well as intrastrand DNA adducts promote nonhomologous recombination in human chromatin and (ii) DNA sequences flanking the selectable genes are the targets for such recombinational events.
A set of low-copy-number vectors (pPD) has been constructed that permit selective gene expression and high-level protein overproduction in Escherichia coli, based on the bacteriophage T7 RNA polymerase/T7 promoter system. These plasmids carry a chloramphenicol resistance gene (cat) as a selective marker and an extended multiple cloning site for convenient gene cloning. Their replication is mediated by ori sequences derived from the low-copy-number vector pSC101. The efficient T7 gene 10 promoter present on these vectors allows selective and high-level transcription of cloned genes carrying their own translational initiation signals. In addition, low-copy-number T7 vectors were constructed that permit expression of genes lacking their own transcription and translation initiation elements by providing a ribosome binding site, an ATG start codon and a multiple cloning site devised for the cloning in all three reading frames. The pPD expression vectors were used to achieve high-level overproduction of the E. coli integral outer membrane protein Tsx, and the cytoplasmic enzymes beta-galactosidase (beta Gal) and UTP:alpha-D-glucose-1-phosphate uridylyltransferase (GalU). The characteristics of these low-copy-number T7 expression vectors should prove very useful for the cloning and high-level overexpression of genes whose gene products are deleterious to the E. coli host.
The discrimination of cancer patients (including subtypes) based on gene expression data is a critical problem with clinical ramifications. Central to solving this problem is the issue of how to extract the most relevant genes from the several thousand genes on a typical microarray. Here, we propose a methodology that can effectively select an informative subset of genes and classify the subtypes (or patients) of disease using the selected genes. We employ a kernel machine, kernel Fisher discriminant analysis (KFDA), for discrimination and use the derivatives of the kernel function to perform gene selection. Using a modified form of KFDA in the minimum squared error (MSE) sense and the gradients of the kernel functions, we construct an effective gene selection criterion. We assess the performance of the proposed methodology by applying it to three gene expression datasets: leukemia dataset, breast cancer dataset and colon cancer dataset. Using a few informative genes, the proposed method accurately and reliably classified cancer subtypes (or patients). Also, through a comparison study, we verify the reliability of the gene selection and discrimination results.
SUMMARY: The fundamental problem of gene selection via cDNA data is to identify which genes are differentially expressed across different kinds of tissue samples (e.g. normal and cancer). cDNA data contain large number of variables (genes) and usually the sample size is relatively small so the selection process can be unstable. Therefore, models which incorporate sparsity in terms of variables (genes) are desirable for this kind of problem. This paper proposes a two-level hierarchical Bayesian model for variable selection which assumes a prior that favors sparseness. We adopt a Markov chain Monte Carlo (MCMC) based computation technique to simulate the parameters from the posteriors. The method is applied to leukemia data from a previous study and a published dataset on breast cancer. SUPPLEMENTARY INFORMATION: http://stat.tamu.edu/people/faculty/bmallick.html.
We have previously observed that the mRNA of selected genes involved in nucleotide excision repair appear to be coordinately expressed in human tissues from patients with ovarian cancer, testicular cancer, malignant brain tumors, and other malignancies. Such genes include ERCC1, XPA, XPB, XPD, XPF, and XPG. Coordinate mRNA expression appears to be most impressive in non-malignant tissues. We therefore began to explore possible reasons why such coordinate expression should occur. DNA sequences for the above noted genes were obtained from GeneBank. Two different software programs were applied to the DNA sequence, to the area 5' to the start of exon I of each gene. Analyses were performed by computer. The length of the 5' area assessed, was based on previous reports that determined what portion of the genomic sequence comprised the 5' UTR of the promoter of the respective gene. Based on this approach, potential DNA binding sites for no less than three dozen proteins, were identified in the 5'-flanking region of each of the NER genes studied. For each gene, potential binding sites for activator proteins and for repressor proteins were identified. The 5'-flanking regions for each gene noted above, had binding sites in common for 14 proteins with transcription modulatory activity. Eleven of these proteins are known for activator activity; two are reported to have repressor activity, and one has both repressor and activator function. These data suggest a possible molecular basis for the previously observed coordinate mRNA expression of selected NER genes in human tissue specimens.