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1.
Journal of Zhejiang University. Science. B ; (12): 891-900, 2019.
Article in English | WPRIM | ID: wpr-1010496

ABSTRACT

An efficient genetic transformation system and suitable promoters are essential prerequisites for gene expression studies and genetic engineering in streptomycetes. In this study, firstly, a genetic transformation system based on intergeneric conjugation was developed in Streptomyces rimosus M527, a bacterial strain which exhibits strong antagonistic activity against a broad range of plant-pathogenic fungi. Some experimental parameters involved in this procedure were optimized, including the conjugative media, ratio of donor to recipient, heat shock temperature, and incubation time of mixed culture. Under the optimal conditions, a maximal conjugation frequency of 3.05×10-5 per recipient was obtained. Subsequently, based on the above developed and optimized transformation system, the synthetic promoters SPL-21 and SPL-57, a native promoter potrB, and a constitutive promoter permE* commonly used for gene expression in streptomycetes were selected and their activity was analyzed using gusA as a reporter gene in S. rimosus M527. Among the four tested promoters, SPL-21 exhibited the strongest expression activity and gave rise to a 2.2-fold increase in β-glucuronidase (GUS) activity compared with the control promoter permE*. Promoter SPL-57 showed activity comparable to that of permE*. Promoter potrB, which showed the lowest activity, showed a 50% decrease in GUS activity compared with the control permE*. The transformation system developed in this study and the tested promotors provide a basis for the further modification of S. rimosus M527.


Subject(s)
Conjugation, Genetic , Glucuronidase/genetics , Promoter Regions, Genetic , Streptomyces rimosus/genetics
2.
Journal of Southern Medical University ; (12): 373-376, 2008.
Article in Chinese | WPRIM | ID: wpr-293373

ABSTRACT

<p><b>OBJECTIVE</b>To analyze alterations in the gene expression profiles of Velcade-treated K562 cells using bioinformatics methods.</p><p><b>METHODS</b>The total RNAs of Velcade-treated and control K562 cells were amplified and labeled with fluorescent dyes. The labeled RNAs were hybridized to Agilent Human 1A Microarray, and the raw expression data were processed with Agilent Feature Extraction Software. GeneSifter and GATHER were used for data analysis of the differentially expressed genes to perform gene ontology classification, KEGG pathway analysis, functional protein association network construction and literature mining.</p><p><b>RESULTS</b>Totally 228 differentially expressed genes were identified in the Velcade-treated K562 cells. including 84 up-regulated and 144 down-regulated genes. Chymase 1 gene had the greatest down-regulation by 10.80 folds (log ratio), and interferon alpha-21 gene was also down-regulated by 2.31 folds. Gene ontology classification suggested enhanced aging and leukocyte activity. KEGG pathway analysis showed significant impact of Velcade on JAK-STAT signaling pathway, cytotoxicity mediated by natural killer cells, and antigen processing and presentation pathways. Protein-protein interaction analysis revealed that ubiquitin-dependent protein catabolism, antigen presentation and immune response, as well as JAK-STAT signaling pathway were the major elements of the protein network. Literature mining showed that the differentially expressed genes were strongly associated with terms such as leukemia, apoptosis, cell cycle, proteasome, inhibitor, aging and IkappaB, etc.</p><p><b>CONCLUSIONS</b>Velcade may inhibit the cell survival pathways such as NF-kappaB and JAK-STAT signaling pathways to enhance the cytotoxicity and inducing tumor cell apoptosis. Velcade might also be involved in antigen processing and presentation, immune response and inflammation. Chymase 1 gene is probably the key target of Velcade.</p>


Subject(s)
Humans , Antineoplastic Agents , Pharmacology , Apoptosis , Boronic Acids , Pharmacology , Bortezomib , Chymases , Genetics , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , K562 Cells , Oligonucleotide Array Sequence Analysis , Methods , Pyrazines , Pharmacology
3.
Journal of Southern Medical University ; (12): 1582-1585, 2008.
Article in Chinese | WPRIM | ID: wpr-340774

ABSTRACT

<p><b>OBJECTIVE</b>To explore the mechanism of transcription regulation of the liver-selective genes responsible for cell communication.</p><p><b>METHODS</b>Tissue-selective Affymetrix probe sets (3919 probes in total) were clustered by functional categories. Liver-selective cell communication (LSCC) genes were selected for further analysis. The 500-bp upstream sequences of all the LSCC genes were extracted for predicting the transcription factor binding sites (TFBS) of known transcription factors (TFs) using 3 programs; literature mining was then performed for these LSCC genes and TFs, and the transcription regulatory network were constructed.</p><p><b>RESULTS</b>The binding sites of 50 and 72 transcription factors were predicted from the upstream sequences of 23 LSCC genes by two programs respectively. Among them, 18 transcription factors were found in common. The top 10 TFBS sequences were basically consistent to the predicted TFs. Literature mining indicated that LSCC genes and TFs were closely related to such terms as albumin, diabetes, glucose, lipid, metabolism, and JNK, in addition to those associated with hepatic tissue and TFs. These observations suggested that LSCC genes and TFs were involved in the regulation of glucose and lipid metabolism, binding and transport, coagulation signal cascades, inflammatory response, etc. PPP2R1B, which was out of the network, showed a partial functional similarity to DUSP10 in the network.</p><p><b>CONCLUSIONS</b>LSCC genes and the predicted TFs may be involved in the regulation of many important functions of the liver, which are integrated into a sophisticated transcription regulatory network. JUN may be the key target for regulation, and PPP2R1B is presumed to participate in the regulation of JUN.</p>


Subject(s)
Humans , Binding Sites , Genetics , Cell Communication , Genetics , Gene Expression Profiling , Gene Expression Regulation , Gene Regulatory Networks , Genetics , Liver , Cell Biology , Metabolism , Models, Biological , Transcription Factors , Genetics , Transcription, Genetic
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