Systems metabolic engineering of Streptomyces albus for advanced production of the reverse antibiotic nybomycin
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1003853 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Time series data for several S. albus strains engineered to produce nybomycin.
2023-08-10 | GSE240471 | GEO
Project description:To elucidate the effect of the rational ribosomal engineering on the changes in the expression of the endogenious biosynthetic gene clusters the transcriptome analysis was performed. The Streptomyces albus strains carrying mutations in rpsL gene (encode for ribosomal protein S12) and the deletion of the rsmG gene (16S rRNA methyltransferase G), as well as their combination were used for the experiment. The list of the strains with mutations is next: S. albus K88E, S. albus GI92, S. albus K88E-GI92, S. albus P91S, S. albus K88E-P91S, S. albus del rsmG, S. albus K88E-GI92 del rsmG, S. albus K88E-P91S del rsmG. Abovementioned strains along with S. albus native strain were grown in NL-19 production medium. Samples were harvested by centrifugation after 48 and 72 hours of cultivation. For total RNA isolation, S. albus cells were grown in SG medium (for ara expression) or NL19 medium (for indigenous BGC expression). Then, 2 ml of 2-day and 3-day cultures was spun down for 20 s at 14,000 × rpm, and the pellets were immediately frozen in liquid nitrogen and stored at ?80 °C. Total RNA extraction was performed using an RNeasy Kit (Qiagen, Hilden, Germany) as previously described (Huser et al. 2003). An RNase-Free DNase set (Qiagen) was used two times for on-column DNA digestion, and an additional DNase treatment was then performed with a DNase I kit (Roche Diagnostics, Mannheim, Germany) to ensure that all DNA was completely removed. To check the RNA samples for DNA contamination, PCR was performed using oligonucleotides designed to create two different products approximately 150 bp and 500 bp in size. Initially, RNA quality was checked with Trinean Xpose (Gentbrugge, Belgium) and Agilent RNA Nano 6000 kits on an Agilent 2100 Bioanalyzer (Agilent Technologies, Böblingen, Germany). A Ribo-Zero rRNA Removal Kit for bacteria was obtained from Illumina (San Diego, CA, USA) and used to remove ribosomal RNA molecules from isolated total RNA. rRNA removal was checked using an Agilent RNA Pico 6000 kit on an Agilent 2100 Bioanalyzer (Agilent Technologies, Böblingen, Germany). A TruSeq Stranded mRNA Library Prep Kit (Illumina, San Diego, CA, USA) was used to prepare cDNA libraries (Koepff et al. 2017). The resulting cDNAs were pair-end sequenced on an Illumina HiSeq 1500 system (San Diego, CA, USA) using a 70 bp read length. Short read alignments and differential gene expression were illustrated using ReadXplorer 2.2.0 (Hilker et al. 2014) and DEseq (Anders and Huber 2010), respectively.
2019-05-01 | E-MTAB-7715 | biostudies-arrayexpress
Project description:Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET)
| PRJNA341430 | ENA
Project description:This SuperSeries is composed of the following subset Series: GSE38584: Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach (7TF and control) GSE38585: Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach (RAS-ROSE and ROSE with siRNA) Refer to individual Series
2012-07-31 | E-GEOD-38614 | biostudies-arrayexpress
Project description:Streptomyces albus S12, TK and Tet30Chl25 are the parental strain , low-yield and high-yield of salinomycin mutant obtained by ARTP and ribosome engineering ,respectively. There are total 1602 differentially expressed genes (DEGs) show differences in expression between the mutant strain TK, Tet30Chl25 and the initial strain S12. KEGG pathway analysis of differentially expressed genes (DEGs) between the mutant strain TK, Tet30Chl25 and the initial strain S12 show that the relevant differential pathways affecting salinomycin production were mainly related to butanoate metabolism, starch and sucrose metabolism, glyoxylate metabolism. Besides , the transcription of genes in the salinomycin biosynthesis gene cluster and the transcription level of related genes in the precursors biosynthesis pathway were more active in the high-yield salinomycin production strain Tet30Chl25. Furthermore, the transcription level ribosomal protein, string response, two component system and sigma factors are more active in high-yield of salinomycin mutants and that may involve in regulation of salinomycin biosynthesis and may account for the high-yield of salinomycin.
2019-10-01 | GSE133580 | GEO
Project description:To evaluate the DNA binding of FscRI in Streptomyces albus S4 in vivo ChIP-Seq experiments were carried out on dusing anti-FLAG antibodies against 3xFLAG-FscRI protein using two biological replicates. The wild type strain was used as a control in experiments using the anti-FLAG antibodies as well as a DNA only control.
2016-11-14 | E-MTAB-5122 | biostudies-arrayexpress
Project description:The TLX1 and TLX3 transcription factor oncogenes play an important role in the pathogenesis of T-cell acute lymphoblastic leukemia (T-ALL)1,2. Here we used reverse engineering of global transcriptional networks to decipher the oncogenic regulatory circuit controlled by TLX1 and TLX3. This Systems Biology analysis defined TLX1 and TLX3 as master regulators of an oncogenic transcriptional circuit governing T-ALL. Notably, network structure analysis of this hierarchical network identified RUNX1 as an important mediator of TLX1 and TLX3 induced T-ALL, and predicted a tumor suppressor role for RUNX1 in T-cell transformation. Consistent with these results, we identified recurrent somatic loss of function mutations in RUNX1 in human T-ALL. Overall, these results place TLX1 and TLX3 atop of an oncogenic transcriptional network controlling leukemia development, demonstrate power of network analysis to identify key elements in the regulatory circuits governing human cancer and identify RUNX1 as a tumor suppressor gene in T-ALL. This SuperSeries is composed of the following subset Series: GSE33539: Expression data obtained from ALLSIL cell line GSE33540: Expression data obtained from HPBALL cell line GSE33549: Expression data from mouse T-cell lymphomas
2011-11-08 | E-GEOD-33550 | biostudies-arrayexpress
Project description:To evaluate the DNA binding of AntA in Streptomyces albus S4, in vivo ChIP-Seq experiments were performed 3xFLAG-AntA and anti-FLAG antibodies using two biological replicates. The wild type strain was used as a control in experiments using the anti-FLAG antibodies as well as a DNA only control (which were published previously, E-MTAB-5122).
2019-02-28 | E-MTAB-7700 | biostudies-arrayexpress
Project description:Complex nonlinear dynamics arise in many fields of science and engineering, but uncovering the underlying differential equations directly from observations poses a challenging task. The ability to symbolically model complex networked systems is key to understanding them, an open problem in many disciplines. Here we introduce for the first time a method that can automatically generate symbolic equations for a nonlinear coupled dynamical system directly from time series data. This method is applicable to any system that can be described using sets of ordinary nonlinear differential equations, and assumes that the (possibly noisy) time series of all variables are observable. Previous automated symbolic modeling approaches of coupled physical systems produced linear models or required a nonlinear model to be provided manually. The advance presented here is made possible by allowing the method to model each (possibly coupled) variable separately, intelligently perturbing and destabilizing the system to extract its less observable characteristics, and automatically simplifying the equations during modeling. We demonstrate this method on four simulated and two real systems spanning mechanics, ecology, and systems biology. Unlike numerical models, symbolic models have explanatory value, suggesting that automated "reverse engineering" approaches for model-free symbolic nonlinear system identification may play an increasing role in our ability to understand progressively more complex systems in the future.
| S-EPMC1891254 | biostudies-other
Project description:RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype. RAS-ROSE cells were treated with siRNA against 7 transcription factors or controls,
2012-07-31 | E-GEOD-38584 | biostudies-arrayexpress