scholarly journals In Silico Identification of Gene Amplification Targets for Improvement of Lycopene Production

2010 ◽  
Vol 76 (10) ◽  
pp. 3097-3105 ◽  
Author(s):  
Hyung Seok Choi ◽  
Sang Yup Lee ◽  
Tae Yong Kim ◽  
Han Min Woo
Keyword(s):  
Metabolic Engineering ◽  
Gene Amplification ◽  
In Silico ◽  
Gene Knockout ◽  
Flux Analysis ◽  
General Strategy ◽  
Enhanced Production ◽  
Synergistic Enhancement ◽  
Genome Wide ◽  
Lycopene Production

ABSTRACT The identification of genes to be deleted or amplified is an essential step in metabolic engineering for strain improvement toward the enhanced production of desired bioproducts. In the past, several methods based on flux analysis of genome-scale metabolic models have been developed for identifying gene targets for deletion. Genome-wide identification of gene targets for amplification, on the other hand, has been rather difficult. Here, we report a strategy called flux scanning based on enforced objective flux (FSEOF) to identify gene amplification targets. FSEOF scans all the metabolic fluxes in the metabolic model and selects fluxes that increase when the flux toward product formation is enforced as an additional constraint during flux analysis. This strategy was successfully employed for the identification of gene amplification targets for the enhanced production of the red-colored antioxidant lycopene. Additional metabolic engineering based on gene knockout simulation resulted in further synergistic enhancement of lycopene production. Thus, FSEOF can be used as a general strategy for selecting genome-wide gene amplification targets in silico.

scholarly journals Metabolic Engineering of Escherichia coli for Enhanced Production of Succinic Acid, Based on Genome Comparison and In Silico Gene Knockout Simulation

2005 ◽  
Vol 71 (12) ◽  
pp. 7880-7887 ◽  
Author(s):  
Sang Jun Lee ◽  
Dong-Yup Lee ◽  
Tae Yong Kim ◽  
Byung Hun Kim ◽  
Jinwon Lee ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Succinic Acid ◽  
In Silico ◽  
Acid Production ◽  
Gene Knockout ◽  
Fermentation Products ◽  
E Coli ◽  
Metabolic Analysis ◽  
Enhanced Production ◽  
Succinic Acid Production

ABSTRACT Comparative analysis of the genomes of mixed-acid-fermenting Escherichia coli and succinic acid-overproducing Mannheimia succiniciproducens was carried out to identify candidate genes to be manipulated for overproducing succinic acid in E. coli. This resulted in the identification of five genes or operons, including ptsG, pykF, sdhA, mqo, and aceBA, which may drive metabolic fluxes away from succinic acid formation in the central metabolic pathway of E. coli. However, combinatorial disruption of these rationally selected genes did not allow enhanced succinic acid production in E. coli. Therefore, in silico metabolic analysis based on linear programming was carried out to evaluate the correlation between the maximum biomass and succinic acid production for various combinatorial knockout strains. This in silico analysis predicted that disrupting the genes for three pyruvate forming enzymes, ptsG, pykF, and pykA, allows enhanced succinic acid production. Indeed, this triple mutation increased the succinic acid production by more than sevenfold and the ratio of succinic acid to fermentation products by ninefold. It could be concluded that reducing the metabolic flux to pyruvate is crucial to achieve efficient succinic acid production in E. coli. These results suggest that the comparative genome analysis combined with in silico metabolic analysis can be an efficient way of developing strategies for strain improvement.

scholarly journals Benchmarking and integrating genome-wide CRISPR off-target detection and prediction

2020 ◽  
Vol 48 (20) ◽  
pp. 11370-11379
Author(s):  
Jifang Yan ◽  
Dongyu Xue ◽  
Guohui Chuai ◽  
Yuli Gao ◽  
Gongchen Zhang ◽  
...  
Keyword(s):  
In Silico ◽  
Gene Knockout ◽  
Target Prediction ◽  
Systematic Evaluation ◽  
Detection Techniques ◽  
Prediction Tools ◽  
Benchmark Study ◽  
Genome Wide ◽  
Benchmark Datasets ◽  
One Stop

Abstract Systematic evaluation of genome-wide Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) off-target profiles is a fundamental step for the successful application of the CRISPR system to clinical therapies. Many experimental techniques and in silico tools have been proposed for detecting and predicting genome-wide CRISPR off-target profiles. These techniques and tools, however, have not been systematically benchmarked. A comprehensive benchmark study and an integrated strategy that takes advantage of the currently available tools to improve predictions of genome-wide CRISPR off-target profiles are needed. We focused on the specificity of the traditional CRISPR SpCas9 system for gene knockout. First, we benchmarked 10 available genome-wide off-target cleavage site (OTS) detection techniques with the published OTS detection datasets. Second, taking the datasets generated from OTS detection techniques as the benchmark datasets, we benchmarked 17 available in silico genome-wide OTS prediction tools to evaluate their genome-wide CRISPR off-target prediction performances. Finally, we present the first one-stop integrated Genome-Wide Off-target cleavage Search platform (iGWOS) that was specifically designed for the optimal genome-wide OTS prediction by integrating the available OTS prediction algorithms with an AdaBoost ensemble framework.

Genome-wide screening and in silico gene knockout to predict potential candidates for drug designing against Candida albicans

2020 ◽  
Vol 80 ◽  
pp. 104196
Author(s):  
Rashi Verma ◽  
Dibyabhaba Pradhan ◽  
Mohsin Maseet ◽  
Harpreet Singh ◽  
Arun Kumar Jain ◽  
...  
Keyword(s):  
Candida Albicans ◽  
In Silico ◽  
Gene Knockout ◽  
Genome Wide ◽  
Drug Designing

In-silico-driven metabolic engineering of Pseudomonas putida for enhanced production of poly-hydroxyalkanoates

2013 ◽  
Vol 15 ◽  
pp. 113-123 ◽  
Author(s):  
Ignacio Poblete-Castro ◽  
Danielle Binger ◽  
Andre Rodrigues ◽  
Judith Becker ◽  
Vitor A.P. Martins dos Santos ◽  
...  
Keyword(s):  
Metabolic Engineering ◽  
Pseudomonas Putida ◽  
In Silico ◽  
Enhanced Production

scholarly journals OptFlux: an open-source software platform for in silico metabolic engineering

2010 ◽  
Vol 4 (1) ◽  
Author(s):  
Isabel Rocha ◽  
Paulo Maia ◽  
Pedro Evangelista ◽  
Paulo Vilaça ◽  
Simão Soares ◽  
...  
Keyword(s):  
Metabolic Engineering ◽  
Open Source ◽  
Open Source Software ◽  
In Silico ◽  
Software Platform
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